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Dmitri Dolgov: Waymo and the Future of Self-Driving Cars | Lex Fridman Podcast #147 | the following is a conversation with dimitri dalgov the cto of waymo which is an autonomous driving company that started as google's self-driving car project in 2009 and became waymo in 2016. dimitri was there all along waymo is currently leading in the fully autonomous vehicle space in that they actually have an at-scale deployment of publicly accessible autonomous vehicles driving passengers around with no safety driver with nobody in the driver's seat this to me is an incredible accomplishment of engineering on one of the most difficult and exciting artificial intelligence challenges of the 21st century quick mention of a sponsor followed by some thoughts related to the episode thank you to trial labs a company that helps businesses apply machine learning to solve real world problems blinkist an app i use for reading through summaries of books better help online therapy with a licensed professional and cash app the app i use to send money to friends please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that autonomous and semi-autonomous driving was the focus of my work at mit and it's a problem space that i find fascinating and full of open questions from both a robotics and a human psychology perspective there's quite a bit that i could say here about my experiences in academia on this topic that revealed to me let's say the less admirable size of human beings but i choose to focus on the positive on solutions i'm brilliant engineers like dimitri and the team at waymo who work tirelessly to innovate and to build amazing technology that will define our future because of dimitri and others like him i'm excited for this future and who knows perhaps i too will help contribute something of value to it if you enjoy this thing subscribe on youtube review it with five stars and up a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with dmitry dolgov when did you first fall in love with robotics or even computer science more in general computer science first at a fairly young age and robotics happened much later um i i think my first interesting introduction to computers was in the late 80s uh when we got our first computer i think was an uh an ibm i think ibm it remember those things that had like a turbo button in the front you'd press it and you know make the thing go faster did they already have floppy disks yeah yeah yeah like the the five point four inch ones i think there's a bigger inch so good when something then five inches and three inches yeah i think that was the five i don't i maybe that was before that was the giant plates and i didn't get that uh but it was definitely not the not the three inch ones uh anyway so that that you know we got that uh computer i spent the first a few months just you know playing video games uh as you would expect i got bored of that so i started messing around and trying to figure out how to make the thing do other stuff got into exploring know programming and a couple of years later i got to a point where um i actually wrote a game a lot of games and a game developer a japanese game developer actually offered to buy it for me for you know a few hundred bucks but you know for for a kid yeah in russia that's a big deal that's a big deal yeah uh i did not take the deal wow integrity yeah i i instead uh stupidity yes that was not the most acute financial move that i made in my life you know looking back at it now uh i instead put it well you know i had a reason i i put it online uh it was what did you call it back in the days it was a freeware i think right it was not open source but you could upload the binaries you put the game online and the idea was that you know people like it and then they you know contribute and they send you little donations right so i did my quick math of like you know my of course you know thousands and millions of people are going to play my game send me a couple of bucks a piece you know should definitely do that as i said not not the best remember what language it was what programming it was about which what pascal pascal and they had a graphical component so that text based yeah yeah it was uh like i think 320 by 200 whatever it was i think that kind of the earlier that's the cga resolution right and i actually think the reason why this company wanted to buy it is not like the fancy graphics or the implementation it was maybe the idea uh of my actual game the idea of the game okay well one of the things it's so funny i used to play this game called golden axe and the simplicity of the graphics and something about the simplicity of the music like it still haunts me i don't know if that's a childhood thing i don't know if that's the same thing for call of duty these days for young kids but i still think that the simple one the games are simple that simple purity makes for like allows your imagination to take over and thereby creating a more magical experience like now with better and better graphics it feels like your imagination doesn't get to uh create worlds which is kind of interesting um it could be just an old man on a porch like waving at kids these days that have no respect but i still think that graphics almost get in the way of the experience i don't know flippy bird yeah i don't know if the imagination gets closed i don't yeah but that that's more about games that up like that's more like tetris world where they optimally masterfully like create a fun short-term dopamine experience versus i'm more referring to like role-playing games where there's like a story you can live in it for months or years um like uh there's an elder scroll series which is probably my favorite set of games that was a magical experience and then the graphics were terrible the characters were all randomly generated but they're i don't know that's it pulls you in there's a story it's like an interactive version of an elder scrolls tolkien world and you get to live in it i don't know i miss it it's one of the things that suck about being an adult is there's no you have to live in the real world as opposed to the elder scrolls world you know whatever brings you joy right minecraft right minecraft is a great example you create like it's not the fancy graphics but it's the creation of your own worlds yeah that one is crazy you know one of the pitches for being a parent that people tell me is that you can like use the excuse of parenting to to go back into the video game world and like like that's like you know father-son father-daughter time but really you just get to play video games with your kids so anyway at that time did you have any ridiculous ambitious dreams of where as a creator you might go as an engineer did you what did you think of yourself as as an engineer as a tinkerer or did you want to be like an astronaut or something like that you know i'm tempted to make something up about you know robots uh engineering or you know mysteries of the universe but that's not the actual memory that pops into my mind uh when you when you ask me about childhood dreams so i'll actually share the real thing uh when i was maybe four or five years old i you know as well do i thought about you know what i wanted to do when i grow up and i had this dream of being a traffic control cop you know they don't have those today's i think but you know back in the 80s and you know in russia i you probably are familiar with that legs they had these uh you know police officers they would stand in the middle of an intersection all day and they would have their like striped black and white batons that they would use to you know control the flow of traffic and you know for whatever reason i was strangely infatuated with this whole process and like that that was my dream uh that's what i wanted to do when i grew up and you know my parents uh both physics profs by the way i think we're you know a little concerned uh with that level of ambition coming from their child yeah uh you know that age well that it's an interesting i don't know if you can relate but i very much love that idea i have a ocd nature that i think lends itself very close to the engineering mindset which is you want to kind of optimize you know solve a problem by create creating an automated solution like like a set of rules the set of rules you could follow and then thereby make it ultra efficient i don't know if that's it was it of that nature i certainly have that there's like fact like simcity and factory building games all those kinds of things kind of speak to that engineering mindset or did you just like the uniform i think it was more of the latter i think it was the uniform and you know the the striped baton that made cars go in the right direction but i guess you know it is i did end up uh i guess uh you know working on the transportation industry one way or another no uniform though but that's right maybe it was my you know deep inner infatuation with the you know traffic control batons that led to this career okay what uh when did you when was the leap from programming to robotics that happened later that was after grad school uh after and actually the most self-driving cars was i think my first real hands-on introduction to robotics but i i never really had that much hands-on experience in school and training i you know worked on applied math and physics then in college i did more of abstract computer science and it was after grad school that i really got involved in robotics which was actually self-driving cars and you know that was a big big flip what uh well grad school so i went to grad school in michigan and then i did a postdoc at stanford uh which is that was the postdoc where i got to play with celebrating cars yeah so we'll return there let's go back to uh to moscow so i you know for episode 100 i talked to my dad and also i grew up with my dad i guess uh so i had to put up with him for many years and uh he he went to the fistiach or mipt it's weird to say in english because i've heard all this in russian moscow institute of physics and technology and to me that was like i met some super interesting as a child i met some super interesting characters it felt to me like the greatest university in the world the most elite university in the world and just the the people that i met that came out of there were like not only brilliant but also special humans it seems like that place really tested the soul uh both like in terms of technically and like spiritually so that could be just the romanticization of that place i'm not sure but so maybe you can speak to it but did is it correct to say that you spent some time at fistia yeah that's right six years i got my bachelor's and master's and physics and math there and it's actually interesting because my my dad actually both my parents uh went there and i think all the stories that i heard like just like you alex uh growing up about the place and you know how interesting and special and magical it was i think that was a significant maybe the main reason uh i wanted to go there uh for college uh enough so that i actually went back to russia from the us i graduated high school in the us um you went back there i went back there yeah that wow exactly the reaction most of my peers in college had but you know perhaps a little bit stronger that like you know point me out as this crazy kid were your parents supportive of that yeah yeah i came to your previous question they uh they supported me and you know letting me kind of pursue my passions and the you know things that that's a bold move wow what was it like there it was interesting you know definitely fairly hardcore on the fundamentals of math and physics and you know lots of good memories from you know from those times so okay so stanford how did you get into autonomous vehicles i had the great fortune and great honor to join stanford's darpa urban challenge team in 2006 there this was a third in the sequence of the darpa challenges their two grand challenges prior to that and then in 2007 they held the darpa urban challenge so you know i was doing my postdoc i had i joined the team and uh worked on motion planning uh for you know that competition so okay so for people who might not know i know from from a certain perspective autonomous vehicles is a funny world in a certain circle of people everybody knows everything and then a certain circle uh nobody knows anything in terms of general public so it's interesting it's it's a good question what to talk about but i do think that the urban challenge is worth revisiting it's a fun little challenge one that in first it like sparked so much so many incredible minds to focus on one of the hardest problems of our time in artificial intelligence so that's it's a success from a perspective of a single little challenge but can you talk about like what did the challenge involve so were there pedestrians were there other cars what was the goal uh who was on the team how long did it take any fun fun sort of specs sure so the way the the challenge was constructed in just a little bit of background and as i mentioned this was the third uh competition in that series the first two uh were the grand challenge called the grand challenge the goal there was to just drive in a completely static environment you know you had to drive in the desert uh that was very successful so then darpa followed with what they called the urban challenge where the goal was to have you know build vehicles that could operate in more dynamic environments and share them with other vehicles there were no pedestrians there but what darpa did is they took over an abandoned air force base and it was kind of like a little fake city that they built out there and they had a bunch of uh robots uh you know cars that were autonomous uh in there all at the same time uh mixed in with other vehicles driven by professional uh drivers and each car had a mission and so there's a crude map that they received at the beginning and they had a mission and go you know here and then there and over here um and they kind of all were sharing this environment at the same time they interact to interact with each other they had to interact with the human drivers there's this very first very rudimentary um version of uh a self-driving car that you know could operate on and on yeah in an environment you know shared with other dynamic actors that as you said you're really in many ways you know kick started this whole industry okay so who was on the team and how did you do i forget uh we came in second uh perhaps that was my contribution to the team i think the stanford team came in first in the darpa challenge uh but then i joined the team and you know you were the one with the bug in the code i mean do you have sort of memories of some particularly challenging things or you know one of the cool things it's not a you know this isn't a product this isn't the thing that uh you know it there's you have a little bit more freedom to experiment so you can take risks and there's uh so you can make mistakes uh so is there interesting mistakes is there interesting challenges that stand out to you or some like taught you um a good technical lesson or a good philosophical lesson from that time yeah uh you know definitely definitely a very memorable time not really a challenge but like one of the most vivid memories that i have from the time and i think that was actually one of the days that really got me hooked on this whole field was the first time i got to run my software on the car and i was working on a part of our planning algorithm uh that had to navigate in parking lots so it's you know something that you know called free space motion planning so the very first version of that uh you know we tried on the car it was on stanford's campus uh in the middle of the night and you know i had this little you know course constructed with cones uh in the middle of a parking lot so we're there like 3 a.m you know by the time we got the code to you know you know compile and turn over and you know it drove like i actually did something quite reasonable and you know it was of course very buggy at the time and had all kinds of problems but it was pretty darn magical i remember going back and you know later at night trying to fall asleep and just being unable to fall asleep for you know the rest of the night uh just my mind was blown and yeah that that's what i've been you know doing ever since for more than a decade uh in terms of challenges and uh you know interesting memories like on the day of the competition i it was been pretty nerve-wracking i remember standing there with mike montemerlo who was the software lead and wrote most of the code i think i did one little part of the planner mike you know incredibly that you know pretty much the rest of it uh with with you know a bunch of other incredible people but i remember standing on the day of the competition uh you know watching the car you know with mike and your cars are completely empty right they're all there lined up in the beginning of the race and then you know darpa sends them you know on their mission one by one so they leave and like you just they have these sirens they all had their different silence silence right each iron had its own personality if you will so you know off they go and you don't see them you just kind of and then every once in a while they you know come a little bit closer to where the audience is and you can kind of hear you know the sound of your car and you know it seems to be moving along so that you know gives you hope and then you know it goes away and you can't hear it for too long you start getting anxious right just a little bit like you know sending your kids to college and like you know kind of you invested in them you hope you you you you you build it properly but like it's still anxiety-inducing uh so that was an incredibly uh fun few days in terms of you know bugs as you mentioned you know one that was my bug that caused us the loss of the first place is still a debate that you occasionally have with people on the cmu team scene you came first i should mention uh that you haven't heard of them but yeah no it's something you know it's a small school it's it's really a glitch that you know they happen to succeed at something robotics related very scenic though most people go there for the scenery um yeah that's right it's a beautiful campus unlike stanford so for people yeah that's true i like stanford for people who don't know cemu is one of the great robotics and sort of artificial intelligence universities in the world cmu carnegie mellon university okay sorry go ahead good good psa so in the part that i contributed to which was navigating parking lots and the way you know that part of the mission worked is yeah you in a parking lot you would get from darpa an outline of the map you can get this you know giant polygon that defined the perimeter of the parking lot uh and there would be an entrance and you know so maybe multiple entries or access to it and then you would get a goal within that open space xy you know heading where the car had to park it had no information about the optical selling obstacles that the car might encounter there so it had to navigate uh kind of completely free space from the entrance to the parking lot into that parking space and then uh once parked there it had to exit the parking lot while of course encountering and reasoning about all the obstacles that it encounters in real time so uh our interpretation or at least my interpretation of the rules was that you had to reverse out of the parking spot and that's what our cars did even if there's no optical in front that's not what seam used car did and it just kind of drove right through so there's still a debate and of course you know if you stop and then reverse out and go out the different way that cost you some time right so there's still a debate whether you know it was my poor implementation that cost us extra time or whether it was you know cmu violating an important rule of the competition and you know i have my own uh opinion here in terms of other bugs and like i i have to apologize to mike montemerla uh for sharing this on air but it is actually uh one of the more memorable ones uh and it's something that's kind of become a bit of a a metaphor had a label in the industry uh since then i think at least in some circles it's called the victory circle or victory lap um and uh our cars did that so in one of the missions in the urban challenge in one of the courses uh there was this big oval right by the start and finish of the race so darpa had a lot of the missions would finish kind of in that same location and it was pretty cool because you could see the cars come by and kind of finish that part lag of the trip without that leg of the mission and then you know go on and you know finish the rest of it uh and other vehicles would you know come hit their waypoint and you know exit the oval and off they would go our car in the hand which hit the checkpoint and then it would do an extra lap around the awful and only then you know leave and go on its merry way so over the course of you know the full day it accumulated uh some extra time and the problem was that we had a bug where it wouldn't you know start reasoning about the next waypoint and plan around to get to that next point until it hit the previous one and in that particular case by the time you hit the that that one it was too late for us to consider the next one and kind of make a lane change so that every time it would do like an extra lap so that's the the stanford victory lap oh there's there's i feel like there's something philosophically profound in there somehow but uh i mean ultimately everybody is a winner in that kind of competition and it led to sort of famously to the creation of uh google self-driving car project and now waymo so can we uh give an overview of how is way more born how's the google self-driving car project born what's the what is the mission what is the hope what is it is the engineering kind of uh set of milestones that it seeks to accomplish there's a lot of questions in there uh yeah i think you're right it kind of the urban challenge and the upper and previous darpa grand challenges uh kind of led i think to a very large you know degree to that next step and you know larry and sergey um uh larry page and sergey brin uh uh google hunter scores uh uh saw that competition and believed in the technology so now the google self-driving car project was born you know at that time and we started in 2009 it was a pretty small group of us about a dozen people who came together uh to to work on on this project at google at that time we saw an you know that incredible early result in the darpa urban challenge i think we're all incredibly excited about where we got to and we believed in the future of the technology but we still had a very rudimentary understanding of the problem space so the first goal of this project in 2009 was to really better understand what we're up against and you know with that goal in mind when we started the project we created a few milestones for ourselves that maximized learnings well the two milestones were you know uh one was to drive a hundred thousand miles in autonomous mode which was at that time you know orders of magnitude that more than anybody has ever done and the second milestone was to drive 10 routes uh each one was 100 miles long they were specifically chosen to become extra spicy you know extra complicated and sample the full complexity of the that that domain um and you had to drive each one from beginning to end with no intervention no human intervention so you get to the beginning of the course uh you you press the the button that include engage in autonomy and you had to you know go for 100 miles you know beginning to end uh with no interventions um and it sampled again the full complexity of driving conditions some were on freeways we had one route that went all through all the freeways and all the bridges in the bay area you know we had some that went around lake tahoe and kind of mountainous roads we had some that drove through dense urban um environments like in downtown palo alto and through san francisco so it was incredibly uh interesting uh to work on and it uh it took us just under two years about a year and a half a little bit more to finish both of these milestones and in that process uh yeah hey it was an incredible amount of fun probably the most fun i had in my professional career and because you're just learning so much you are you know the goal here is to learn and prototype you're not yet starting to build a production system right so you just you were you know this is when you're kind of you know working 24 7 and you're hacking things together and you also don't know how hard this is i mean it's the point like so i mean that's an ambitious if i put myself in that mindset even still that's a really ambitious set of goals like just those two picking picking 10 different difficult spicy challenges and then having zero interventions so like not saying gradually we're going to like you know over a period of 10 years we're going to have a bunch of roots and gradually reduce the number of interventions you know would that literally says like by as soon as possible we want to have zero and on hard roads so like to me if i was facing that it's unclear that whether that takes two years or whether that takes 20 years i mean under two i guess that speaks to a really big difference between doing something once and having a prototype uh where you are going after you know learning about the problem versus how you go about engineering a product that you know where you look at uh you know you properly do evaluation you look at metrics you you know drive down and you're confident that you can do that at home and i guess that's the you know why it took a dozen people uh you know 16 months or a little bit more than that uh back in 2009 and 2010 and with the technology of you know the more than a decade ago that amount of time to achieve that milestone of 10 routes 100 miles each and no interventions and you know it took us a little bit longer to get to you know a full driverless product that customers use that's another really important moment is there some memories of technical lessons or just one like what did you learn about the problem of driving from that experience i mean we could we can now talk about like what you learned from modern day waymo but i feel like you may have learned some profound things in those early days even more so because it feels like what waymo is now is to trying to you know how to do scale how to make sure you create a product how to make sure it's like safety and all those things which is all fascinating challenges but like you were facing the more fundamental philosophical problem of driving in those early days like what the hell is driving as an autonomous or maybe i'm again romanticizing it but is it is there uh is there some valuable lessons you picked up over there at those two years uh a ton the most important one is probably that we believe that it's doable and we've gotten uh far enough into the problem that uh you know we had a i think only a glimpse of the true complexity uh of the the domain yeah it's a little bit like you know climbing a mountain where you kind of see the next peak and you think that's kind of the summit but then you get to that and you kind of see that that this is just the start of the journey uh but we've tried we've sampled enough of the problem space and we've made enough rapid uh success even you know with technology of 2009 2010 that it gave us confidence to then you know pursue this as a real product so okay so the next step you mentioned the the milestones that you had in the in those two years what are the next milestones that then led to the creation of waymo and beyond now it was a really interesting journey and waymo came a little bit later uh then you know we completed those milestones in 2010 that was the pivot when we decided to focus on actually building a product yeah using this technology uh the initial couple years after that we were focused on a freeway you know what you would call a driver assist uh maybe an l3 driver assist uh program then around 2013 we've learned enough uh about the space and the thought more deeply about you know the product that we wanted to build that we pivoted uh we pivoted towards of this vision of you know building a driver and deploying it fully driverless vehicles without a person and that that's the path that we've been on since then and uh very it was exactly the right decision for us so there was a moment where you also considered like what is the right trajectory here what is the right role of automation in the in the task of driving there's still it wasn't from the early days obviously you want to go fully autonomous from the early days it was not i think it was in 20 around 2013 maybe that we've that became very clear and we made that pivot and it also became very clear uh and that it's even the way you go building a driver assist system is you know fundamentally different from how you go building a fully driverless vehicle so you know we've uh pivoted towards the ladder and that's what we've been working on ever since and so that was around 2013 then there's sequence of really meaningful for us really important defining milestones since then in the 2015 we had our first actually the world's first fully driverless trade on uh public roads it was in a custom-built vehicle that we had we must have seen this we called them the firefly that you know funny-looking marshmallow looking thing um and we put a passenger uh his name was steve mann a great uh friend of our project from the early days uh the the man happens to be uh blind so we put him in that vehicle uh the car had no steering wheel no pedals it was an uncontrolled environment um you know no you know lead or chase cars no police escorts um and uh you know we did that trip a few times in austin texas so that was a really big milestone well that was in austin yeah cool okay um and you know we only but at that time we're only it took a tremendous amount of engineering it took a tremendous amount of validation uh to get to that point uh but you know we only did it a few times i only did that it was a fixed route it was not kind of a controlled environment but it was a fixed route and we only did a few times uh then uh in uh 2016 uh end of 2016 beginning of 2017 is when we founded waymo uh the company that's when we kind of that was the next phase of the project where i wanted uh we believed in kind of the commercial uh vision of this technology and it made sense to create an independent entity you know within that alphabet umbrella to pursue uh this product at scale beyond that in 2017 later in 2017 was another really a huge step for us really big milestone where we started it was october of 2017. where when we started regular uh driverless operations on public roads that first day of operations we drove uh in one day and that first day 100 miles and you know driverless fashion and then we've the most the most important thing about that milestone was not that you know 100 miles in one day but that it was the start of kind of regular ongoing driverless operations can we say driverless it means no driver that's exactly right so on that first day we actually had a mix and up uh in some uh we didn't want to like you know be on youtube on twitter that same day so in uh and many of the rides we had somebody in the driver's seat but they could not disengage like the car it's not disengaged but actually on that first day uh some of the miles were driven and just completely empty driver's seat and this is the key distinction that i think people don't realize it's you know that oftentimes when you talk about autonomous vehicles you're there's often a driver in the seat that's ready to uh to take over uh what's called a safety driver and then waymo is really one of the only companies that i'm aware of or at least as like boldly and carefully and all and all that is actually has cases and now we'll talk about more and more where there is literally no driver so that that's another the the interesting case of where the driver is not supposed to disengage that's like a nice middle ground if they're still there but they're not supposed to disengage but really there's the case when there's no okay there's something magical about there being nobody in the driver's seat like just like to me you mentioned um the first time you wrote some code for free space navigation of the parking lot that was like a magical moment to me just sort of an as an observer of robots the first magical moment is seeing an autonomous vehicle turn like make a left turn like apply sufficient torque to the steering wheel to where like there's a lot of rotation and for some reason and there's nobody in the driver's seat for some reason that that communicates that here's a being with power that makes a decision there's something about like the steering wheel because we perhaps romanticize the notion of the steering wheel it's so essential to the our conception our 20th century conception of a car and it turning the steering wheel with nobody in driver's seat that to me i think maybe to others it's really powerful like this thing is in control and then there's this leap of trust that you give like i'm gonna put my life in the hands of this thing that's in control so in that sense when there's no but no driver in the driver's seat that's a magical moment for robots so i i'm i gotten a chance to uh last year to take a ride in in a waymo vehicle and that that was the magical moment there's like nobody in the driver's seat it's it's like the little details you would think it doesn't matter whether it's a driver or not but like if there's no driver and the steering wheel is turning on its own i don't know that's magical it's absolutely magical like i you've taken many of these rights in a completely empty car no human in the car pulls up you know you call it on your cell phone it pulls up you get in it takes you on its way there's nobody uh in the car but you right that's something called you know fully driverless our rider only mode of operation uh yeah it it is magical it is uh transformative this is what we hear from our uh writers it really changes your experience and not like that that really is what unlocks the real potential of this technology uh but you know coming back to our journey uh you know that was 2017 when we started uh truly driverless operations then in 2018 we've launched our public commercial service that we call waymo one in phoenix in 2019 we started offering truly driverless rider only rights to our early writer population of users and then you know 2020 has also been a pretty interesting year uh one of the first ones less about technology but more about the maturing and the growth of waymo as a company we raised our first round of external financing uh this year you know we were part of alphabet so obviously we have access to you know significant resources but as kind of on the journey of waymo maturing as a company it made sense for us to you know partially go externally uh uh and in this round so you know we raised uh about 3.2 billion dollars uh with from you know that round uh we've also you know uh started putting our fifth generation of our driver our hardware uh uh that is on the new vehicle but it's also a qualitatively different set of uh self-driving hardware uh that's all uh that is now on the jlr pace so that was a very important step for us the hardware specs fifth generation i think it'd be fun to maybe i apologize if i'm interrupting but maybe talk about maybe the generations with a focus on what we're talking about in the fifth generation in terms of hardware specs like what's on this car sure so we separated out the actual car that we are driving from the self-driving hardware we put on it um right now we have so this is as i mentioned the fifth generation and we've gone through we started you know building our own hardware you know many many years ago and that firefly vehicle also had the hardware suite that was mostly designed engineered and built in-house lidars are of one of the more important components that we design and build from the ground up uh so on the fifth generation uh of our uh drivers uh of our driving hardware that we're switching to right now uh we have uh as with previous generations in terms of sensing we have lidars cameras and radars and when you have a pretty beefy computer that processes all that information and makes you know decisions in real time on on board the car uh so in all of the and it's really a qualitative uh jump forward in terms of the capabilities and uh the various parameters and the specs of the hardware compared to what we had before and compared to what you can kind of get off the of the shelf in the market today meaning from fifth to fourth or from fifth to first definitely from uh first to fifth but also from the other world's dumbest question definitely definitely from fourth to fifth okay as well as uh uh there's the the last step is a big step forward so everything's in-house so like lidar's built in house and and cameras are built in-house uh you know it's different you know we work with partners there are some components uh that you know we get from our manufacturing and you know supply chain partners uh what exactly is in-house is a bit different if you we we do a lot of you know custom uh design on all of our sensing materials sliders radars cameras you know exactly there's lighters are almost exclusively in-house and some of the technologies that we have some of the fundamental technologies there are completely unique uh to weima uh that is also largely true about radars and cameras it's a little bit more of a a mix in terms of what we do ourselves versus what we get from uh partners is there something uh super sexy about the computer that you can mention that's not top secret like uh for people who enjoy computers for i mean uh so there's there's a lot of machine learning involved but there's a lot of just basic compute there's you have to uh probably do a lot of signal processing on all the different sensors you have to integrate everything has to be in real time there's probably some kind of redundancy type of situation is there something interesting you can say about the computer for the people who love hardware it does have all of the characteristics all the properties that you just mentioned uh redundancy uh very beefy compute for general processing as well as you know inference and ml models it is some of the more sensitive stuff that you know i don't want to get into for ip reasons but yeah it can be shared a little bit uh in terms of the specs of the sensors that we have on the car you know we actually shared some videos of what our lighter seas lighters see in the world we have 29 cameras we have five lighters we have six raiders on these vehicles and you can kind of get a feel for the amount of data that they're producing that all has to be processed in real time uh to you know do perception to do complex reasoning and kind of gives you some idea of how beefy those computers are but i don't want to get into specifics of exactly how we build them okay well let me try some more questions that you can't get into the specifics of like gpu wise is that something you can get into you know i know that google works with tpus and so on i mean for machine learning folks it's kind of interesting or is there no how do i ask it uh i've been talking to people in the government about ufos and they don't answer any questions so this is this is how i feel right now asking about gpus [Laughter] but is there something interesting they could reveal or is it just you know uh yeah or would leave it up to our imagination some of the some of the compute is there any i guess is there any fun trickery like i talked to chris lattner for a second time and he was a key person about tpus and there's a lot of fun stuff going on in google in terms of uh hardware that optimizes for machine learning is there something you can reveal in terms of how much you mentioned customization how much customization there is for hardware for machine learning purposes i'm going to be like that government you know you that guy uh personally audio foes i i guess i you know will say that it's really compute is really important uh we have very data hungry and compute hungry ml models of all over uh our stack and this is where you know both being part of alphabet as well as designing our own sensors and the entire hardware suite together where on one hand you get access to like really rich uh raw sensor data that you can pipe from your sensors uh into your compute platform yeah and build like build the whole pipe from sensor raw sensor data to the big compute as then have the massive compute to process all that data and this is where we're finding that having a lot of control of that that hardware part of the stack is really advantageous one of the fascinating magical places to me again might not be able to speak to the details but is the it is the other compute which is like you know this we're just talking about a single car but the you know the driving experience is a source of a lot of fascinating data and you have a huge amount of data coming in on the car on the car and you know the infrastructure of storing some of that data to then train or to analyze or so on that's a fascinating like piece of it that that i understand a single car i don't understand how you pull it all together in a nice way is that something that you could speak to in terms of the challenges of um of seeing the network of cars and then bringing the data back and analyzing things that weren't that like like edge cases of driving be able to learn on them to improve the system to to see where things going wrong with where things went right and analyze all that kind of stuff is there something interesting there in the from an engineering perspective oh there's an incredible uh amount of really interesting work that's happening there both in the you know the real time operation of the fleet of cars and the information that they exchange with each other in real time to make better decisions as well uh as on the kind of the off board component where you have to deal with massive amounts of data for training your ml models evaluating the male models for simulating the entire system and for you know evaluating your entire system and this is where and being part of alphabet has been once again been tremendously uh advantageous because we consume an incredible amount of you know compute for ml infrastructure we build a lot of custom frameworks to you know get good at you know on data mining uh finding the interesting edge cases for training and for evaluation of the system for both training and evaluating some components and you know sub uh parts of the system and various ml models as well as the uh evaluating the entire system and simulation okay that first piece that you mentioned that cars communicating to each other essentially i mean through perhaps through a centralized point but what uh that's fascinating too how much does that help you like if you imagine like you know right now the number of way more vehicles is whatever x i don't know if you can talk to what that number but it's it's not in the hundreds of millions yet and imagine if the whole world is way more vehicles uh like that changes potentially the power of connectivity like the more cars you have i guess actually if you look at phoenix because there's enough vehicles there's enough when there's like some level of density you can start to probably do some really interesting stuff with the fact that cars can negotiate can be uh can communicate with each other and thereby make decisions is there something interesting there that you can talk to about like how does that help with the driving problem from as compared to just a single car solving the driving problem by itself uh yeah it's it's a spectrum i uh first to say that yeah it's it helps uh and it helps in various ways but it's not required uh right now the way we build our system engaged cars can operate independently they can operate with no connectivity uh so i think it is important that you know you have a fully uh autonomous you know fully capable uh driver uh that computerized driver that each car has then you know they do share information and they share information in real time it really really helps right so the way we do this today is uh you know whenever one car encounters something interesting in the world whether it might be an accident or a new construction zone that information immediately gets uh you know uploaded over the air and is propagated to the rest of the fleet so and that's kind of how we think about maps as priors in terms of the knowledge of our drivers of our fleet of drivers that is distributed across the fleet and it's updated in real time so that's one use case you know you can imagine as the you know the the density of these vehicles go up that they can exchange more information in terms of what they're planning to do uh and uh start uh influencing how they interact with each other uh as well as you know potentially sharing some observations right to help with if you have enough density of these vehicles where you know one car might be seeing something that another is relevant to another car that is very dynamic you know it's not part of kind of you're updating your static prior of the map of the world but it's more of a dynamic information that could be relevant to the decisions that another cars make in real time so you can see them exchanging that information and you can build on that but again i i see that as an advantage but it's you know not a requirement so what about the human in the loop so uh when i got a chance to drive with a ride in a waymo you know there's customer service [Laughter] so like is somebody that's able to dynamically like tune in and uh help you out what uh what role does the human play in that picture that's a fascinating like you know the idea of teleoperation be able to remotely control a vehicle so here what we're talking about is like like frictionless uh like a human being able to in a in a frictionless way sort of help you out i don't know if they're able to actually control the vehicle is that something you could talk to uh yes okay uh to be clear we don't do teleportation i'm going to believe in teleoperation for rare reasons that's not what we have on our cars we do as you mentioned have you know version of you know customer support uh you know we call it live health in fact we find it that it's very uh important for our rider experience especially if it's your first trip you've never been in a fully driverless rider only way more vehicle you get in there's nobody there right so you can imagine having all kinds of you know questions in your head like how this thing works so we've put a lot of thought into kind of guiding our our writers our customers through that experience especially for the first time they get some information on the phone uh if the fully driverless vehicle is used to service their trip uh when you get into the car we have an in-car you know screen and audio that kind of guides them and explains uh what to expect they also have a button that they can push that will connect them to you know a real life human being that they can talk to all right about this whole process so that's one aspect of it um there is i should mention that there is uh another function that uh humans provide uh to our cars but it's not tele operation you can think of it a little bit more like you know fleet assistance kind of like you know traffic control uh that that you have where our cars again they're responsible on their own for making all of the decisions all the driving decisions that don't require connectivity they you know anything that is safety or latency critical uh is done you know purely autonomously by on board uh our on onboard system uh but there are situations where you know if connectivity is available uh can a car encounters a particularly challenging situation you can imagine like a super hairy uh scene of an accident uh the cars will do their best they will recognize that it's an off nominal situation they will you know do their best to come up you know with the right interpretation the best course of action in that scenario but if connectivity is available they can ask for confirmation from you know here mode human assistant to kind of confirm those actions and perhaps provide a little bit of kind of contextual information and guidance so october 8th was when you're talking about the was weimar launched the the the fully self the public version of its fully driverless that's right term i think service in phoenix is that october 8th that's right it was the introduction of fully driverless rider only vehicles into our you know public waymo one service okay so that's that's amazing so it's like anybody can get into waymo in phoenix oh that's right yeah so we previously had early people in our early writer program uh taking fully driverless rides in phoenix and uh just uh this a little while ago we opened on october 8th we opened that mode of operation to the public so i can you know download the app and you know go on the right there is uh a lot more demand right now uh for that service and then we have capacity uh so we're kind of uh managing that but that's exactly the way you described it yeah well that's interesting so there's more demand than you can you can handle like what uh what has been uh reception so far like what i mean okay so you know that's this is a product right that's a whole other discussion of like how compelling of a product it is great but it's also like one of the most kind of transformational technologies of the 21st century so there it's also like a tourist attraction like it's fun to you know to be a part of it so it'd be interesting to see like what do people say what do people uh what have been the feedback so far you know still early days but so far the feedback has been uh incredible uh incredibly positive they you know we asked them for feedback during the ride we asked them for feedback uh after the ride as part of their trip you know we asked them some questions we asked them to you know rate the performance of our driver uh most by far you know most of our drivers give us five stars in our app uh which is uh absolutely great to see and yeah that's and we're they're also giving us feedback on you know things we can improve uh and you know that's one of the main reasons we're doing this is phoenix and you know over the last couple of years and every day today uh we are just learning a tremendous amount of new stuff from our users there's there's no substitute for actually doing the real thing actually having a fully driverless product out there in the field with you know users uh that are actually paying us money to get from point a to point b so this is a legitimate like that's a paid service that's right and the idea is you use the app to go from point a to point b and then what what are the a's what are the what's the freedom of the of the starting and ending places it's an area of geography where that service is enabled it's a you know decent size of geography of territory it's actually larger than you know the size of san francisco uh and you know within that you have you know full freedom of you know selecting where you want to go you know of course there's some and you on your app you get a map you tell the car where you want to be picked up you know where you want you know the car to pull over and pick you up and then you tell it where you want to be dropped off all right and of course there's some exclusions right you want to be you know you uh where in terms of where the car is allowed to pull over right so you know that you can't do but you know besides that uh it's amazing it's not like a fixed just would be very i guess i don't know maybe that's what's the question behind your question but it's not a you know preset set of uh yeah so within the geographic constraints with that within that area anywhere else it can be you can be picked up and dropped off anywhere that's right and you know people use them on like all kinds of trips they we have and we have an incredible spectrum of riders we i think the youngest actually have car seats them and we have you know people taking their kids and rides i think the youngest riders we had on cars are one or two years old you know and the full spectrum of use cases people you can take them to you know schools uh to you know go grocery store shopping to restaurants to bars you know run errands you know go shopping et cetera et cetera you can go to your office right like the full spectrum of use cases and uh people gonna use them in their daily lives to get around uh and we see all kinds of you know really interesting uh use cases and that that that's providing us incredibly valuable experience that we then you know use to improve our product so as somebody who's been on done a few long rants with joe rogan and others about the toxicity of the internet and the comments and the negativity in the comments i'm fascinated by feedback i i believe that most people are good and kind and intelligent and can provide like even in disagreement really fascinating ideas so on a product side it's fascinating to me like how do you get the richest possible user feedback like to improve what's what are the channels that you use to measure because like you're you're no longer that's one of the magical things about autonomous vehicles is it's not like it's frictionless interaction with the human so like you don't get to you know it's just giving a ride so like how do you get feedback from people to in order to improve uh yeah uh great question various mechanisms uh so as part of the normal flow we ask people for feedback they as the car is driving around we have on the phone and in the car and to have a touchscreen in the car you can actually click some buttons and provide uh real-time feedback on how the car is doing and how the car is handling a particular situation you know both positive and negative so that's one channel uh we have as we discussed customer support or live help where you know if a customer wants to has a question uh uh or he has some sort of concern they can talk to a person in real time so that that is another mechanism that gives us feedback uh at the end of a trip you know we also ask them how things went they give us comments and you know star rating and you know if it's uh we also you know ask them to explain what you know one one well and you know what could be improved and uh we we have uh our writers providing you know very rich uh feedback there a lot the large fraction is uh very passionate and very excited about this technology so we get really good feedback uh we also run uxr studies right you know specific and that are kind of more you know go more in depth and we'll run both kind of lateral and longitudinal studies um where we have you know deeper engagement uh with our customers you know we have our user experience research team tracking over time and testing is about longitude no it's cool that's that's exactly right and you know that's another really valuable uh feedback uh source of feedback and you we're just covering a tremendous amount right uh people go grocery stroping and they like want to load you know 20 bags of groceries in our cars and like that that's one workflow that you maybe don't you know think about uh you know getting just right when you're building the driverless product i have people like you know who uh bike as part of their trip so they you know bike somewhere then they get on our cars they take a part their bike they load into our vehicle then go and that's you know how they you know where we want to pull over and how that you know uh get in and get out um uh process works uh provides very uh useful feedback in terms of you know what makes a good uh pickup and drop-off location uh we get really valuable feedback and in fact we had to um uh do some really interesting work with high definition maps and uh thinking about walking directions if you imagine you're in a store right in some giant space and then you know you want to be picked up somewhere like if you just drop a pin in the current location which is maybe in the middle of a shopping mall like what's the best location for the car to come pick you up and you can have simple heuristics where you just kind of take your you know your cleaning distance uh and find the nearest uh spot where the car can't pull over that's closest to you but oftentimes that's not the most convenient one you know i have many anecdotes where that heuristic breaks in horrible ways i one example uh that yeah i often mention is somebody wanted to be you know uh dropped off uh and phoenix uh and you know we car picked a location uh that was close the closest to their you know where the pin was dropped on the map in terms of you know latitude and longitude but it happened to be on the other side of a parking lot that had this row of cacti and poor person had to like walk all around the parking lot to get to where they wanted to be in 110 degree heat so that you know that was about so then you know we took all take all of these um all that feedback from our users and uh incorporate it into our system and yeah and improve it yeah i feel like that's like requires agi to solve the problem of like when you're which is a very common case when you're in a big space of some kind like apartment building it doesn't matter it's not some large space and then you call the like the waymo from there right like so and you whatever it doesn't matter right your vehicle and like where is the pin supposed to drop i feel like that's i you don't think i think that requires a gi i'm gonna in order okay the alternative which i think the google search engine has taught is like there's something really valuable about the perhaps slightly dumb answer but a really powerful one which is like what was done in the past by others like what was the choice made by others that seems to be like in terms of google search when you have like billions of searches you can you could see which like when they recommend what you might possibly mean they suggest based on not some machine learning thing which they also do but like on what was successful for others in the past and finding a thing that they were happy with is that integrated at all with waymo like what what pickups worked for others it is i i think you're exactly right so there's uh real it's an interesting problem uh naive solutions uh have uh interesting failure modes uh so there's definitely lots of things that can be done to improve uh and both learning from you know what works what doesn't work in actual heal from you know getting richer data and getting more information about the environment and you know richer maps but you're absolutely right that there's something and there's some properties of solutions that uh in terms of the effect that they have on users so much much much much better than others right unpredictability and understandability is important so you can have maybe something that is not quite as optimal but is very natural and predictable to the user and kind of works the same way all the time and that matters that matters a lot for the user experience and but you know to get to the basics the pretty fundamental property is that the car actually arrives where you told it right like you can always you know change it see it on the map and you can move it around if you don't like it and but like that property that the car actually shows up reliably yeah is critical which you know where uh compared to some of the human uh driven yes analogs i think you know you can have more unpredictability it's actually uh the fact uh if if i have uh might do a little bit of a detail here uh i think the fact that it's you know your phone and the cars two computers talking to each other uh can lead to some really interesting things we can do in terms of the user interfaces both in terms of function uh like the car actually shows up exactly where you told it uh you want it to be but also some you know really interesting things on the user interface right as the car is driving as you you know call it and it's on the way to come and pick you up and of course you get the position of the car and the route on the map uh but and they actually follow that route of course uh but it can also share some really interesting information about what it's doing so uh you know our cars uh as they are coming to pick you up if it's come if a car is coming up to a stop sign it will actually show you that like it's there sitting because it's at a stop sign or a traffic light it'll show you that it's got you know sitting at a red light so you know they're like little things uh right uh but it i find those little touch uh touches uh really interesting really magical and it's just you know little things like that that you can do to kind of delight your users you know this makes me think of um there's some products that i just love like there's a there's a company called rev uh rev.com where i like for this podcast for example i can drag and drop a video and then they do all the captioning uh it's humans doing the captioning but they connect you good they they automatic automate everything of connecting you to the humans and they do the captioning and transcription it's all effortless and like i remember when i first started using them it was like life is good like because it was so painful to to figure that out earlier uh the same thing with uh something called izotope rx this company i use for cleaning up audio like the sound cleanup they do it's like drag and drop and it just cleans everything up very nicely uh another experience like that i had with amazon one click purchase first time i mean other places do that now but just the effortlessness of purchasing making it frictionless it kind of communicates to me like i'm a fan of design i'm a fan of products that you can just create a really pleasant experience the simplicity of it the elegance just makes you fall in love with it so on the do you think about this kind of stuff i mean that's exactly what we've been talking about it's like the little details that somehow make you fall in love with the product is that we went from like urban challenge days where where love was not part of the conversation probably and to to this point where there's uh where there's human beings and you want them to fall in love with the experience is that something you're trying to optimize for trying to think about like how do you how do you create experience that people love absolutely i think that's the vision is removing any friction or complexity from getting our users our writers to where they want to go and making that as simple as possible and then you know beyond that on just transportation making you know things and you know goods get to their destination as seamlessly as possible and talked about you know a drag and drop experience where you kind of express your intent and then you know it just magically happens and for our riders that's what we're trying to get to is you download an app and you can click and car shows up it's the same car it's very predictable it's a safe and high quality experience and then it gets you in a very reliable very convenient uh frictionless way to where you want to be and along the journey i think we also want to like do a little things to delight our users like the ride-sharing companies because they don't control the experience i think they can't make people fall in love necessarily with the experience or maybe they haven't put in the effort but i think it if i would just speak to the ride-sharing experience i currently have it's just very it's just very convenient but there's a lot of room for like falling in love with it like we can speak to sort of car companies car companies do this well you can fall in love with a car right and be like a loyal car person like whatever like i like bad ass hot rods i guess 69 corvette and at this point you know you can't really cars are so owning a car is so 20th century man but is there something about the waymo experience where you hope that people will fall in love with because that is that part of it or is it part of is it just about making a convenient ride not ride sharing i don't know what the right term is but just the convenient eight to be autonomous um transport or like do you want them to fall in love with waymo so maybe elaborate a little bit i mean almost like from a business perspective i'm curious like how do you want to be in the background invisible or do you want to be uh like a source of joy that's in very much in the foreground i want to provide the best most enjoyable transportation solution uh and that means building it building our product and building our service in a way that people do uh kind of use in a very seamless frictionless way in their in their day-to-day lives and i think that does mean uh you know in some way falling in love in that product right just kind of becomes part of your routine i uh it comes down my mind to safety predictability of the experience and um privacy i think aspects of it right our cars you get the same car you get very predictable behavior and that that is important and if you're going to use it in your daily life privacy and when you're in a car you can do other things you're spending a bunch just another space where you're spending a significant part of your life right so not having to share it with other people who you don't want to share it with i think is uh a very nice property uh maybe you want to take a phone call or do something else in the vehicle um and you know safety on the quality of the driving as well as the physical safety of you know not having so you know to share that ride is you know important to a lot of people what about the idea that when when there's somebody like a human driving and they do a rolling stop on a stop sign like sometimes like you know you get an uber a lift or whatever like human driver and you know they can be a little bit aggressive as as drivers it feels like there is um not all aggression is bad uh now that may be a wrong again 20th century conception of driving maybe it's possible to create a driving experience like if you're in the back busy doing something maybe aggression is not a good thing it's a very different kind of experience perhaps but it feels like in order to navigate this world you need to uh how do i uh phrase this you need to kind of bend the rules a little bit or at least like test the rules i don't know what language politicians use to discuss this but uh whatever language they use you like flirt with the rules i don't know but like you uh you sort of uh have a bit of an aggressive way of driving that asserts your presence in this world thereby making other vehicles and people respect your presence and thereby allowing you to sort of navigate through intersections in a timely fashion i don't know if any of that made sense but like how does that fit into the experience of driving autonomously is that a lot of sales this is you're hitting a very important point of a number of behavioral components and parameters that make your driving feel you know assertive and natural and comfortable predictable um now our cars will follow rules right they will do the safest thing possible in all situations let you know be clear on that uh but if you think of really really you know good drivers just you know think about you know professional limo drivers right they will follow the rules they're very very smooth uh and yet they're very efficient uh and but they're assertive uh they're comfortable for the people in the vehicle they're predictable for the uh other people outside the vehicle that they share the environment with and that that's the kind of driver that we want to build and you think if maybe there's a sport analogy there right yeah you can do in very many sports the true professionals are very efficient in their movements right they don't do like you know hectic uh flailing right they're you know smooth and precise right and they get the best results so that's the kind of driver that we want to build in terms of you know aggressiveness yeah you can like you know roll through the stop signs you can do crazy lane changes uh it typically doesn't get you to your destination faster typically not the safest or most predictable uh very most comfortable thing to do and uh but there is a way to do both and that that that that's what we're doing we're trying to build a driver that is uh safe comfortable smooth and predictable yeah that's a really interesting distinction i think in the early days of autonomous vehicles the vehicles felt cautious as opposed to efficient and and still probably but when i rode in the waymo i mean there was it was it was quite assertive it moved pretty quickly like um yeah and he's one of the surprising feelings was that it actually it went fast and it didn't feel like awkwardly cautious than autonomous vehicle like like so i've also programmed autonomous vehicles and everything i've ever built was felt awkwardly either overly aggressive okay especially when it was my code or uh like awkwardly cautious is the way i would put it and the waymo's vehicle felt like uh assertive and i think efficient as like the right terminology here it wasn't uh and i also like the professional limo driver because we often think like you know an uber driver or a bus driver or a taxi this is the funny thing is people think that taxi drivers are professionals they i mean it's it's like that that's like saying me i'm a professional walker just because i've been walking all my life i think there's an art to it right and if you take it seriously as an art form then there's a certain way that mastery looks like it's interesting to think about what does mastery look like in driving and perhaps what we associate with like aggressiveness is unnecessary like it's not part of the experience of driving it's like unnecessary fluff that efficiency you could you can be you can create a good driving experience within the rules that's uh i mean you're the first person to tell me this so it's it's kind of interesting i need to think about this but that's exactly what it felt like with waymo i kind of had this intuition maybe it's the russian thing i don't know that you have to break the rules in life to get anywhere but maybe maybe it's possible that that's not the case in driving i have to think about that but it certainly felt that way on the streets of phoenix when i was there in in waymo that that that that was a very pleasant experience and it wasn't frustrating in that like come on move already kind of feeling it wasn't it that wasn't there yeah i mean that's what that's what we're going after yeah i don't think you have to pick one i think truly good driving and gives you both efficiency assertiveness but also comfort and predictability and you know safety uh and you know it's that's what fundamental improvements in the core capabilities truly unlock and you can kind of think of it as you know a precision and recall trade-off you have certain capabilities of your model and then it's very easy when you know you have some curve of precision and recoil you can move things around and you can choose your operating point in your training of precision versus recall false positives versus false negatives right but then and you know you can tune things on that curve and be kind of more cautious or more aggressive but then aggressive is bad or you know cautious is bad but true capabilities come from actually moving the whole curve up right and then you are kind of on a very different plane of those trade-offs and that that's what you know we're trying to do here is to move the whole curve up before i forget let's talk about trucks a little bit uh so i also got a chance to check out some of the waymo truck uh trucks i'm not sure if uh we want to go too much into that space but it's a fascinating one so maybe we can mention at least briefly you know waymo is also not doing autonomous trucking and uh how different like philosophically and technically is that whole space of problems it's one of our two big products and uh you know commercial applications of our driver right right handling and deliveries you know we have waymo one and waymovia moving people and moving goods uh you know trucking is an example of uh moving goods uh we've been uh working on trucking since 2017. uh it is uh a very interesting space and your question how different is it it has this really nice property that the first order challenges like the science the hard engineering uh whether it's you know hardware or you know onboard software or off-board software all of the you know systems that you build for you know training your ml models for you know evaluating a retirement system like those fundamentals carry over the true challenges of driving perception semantic understanding prediction decision making more planning evaluation uh the simulator ml infrastructure those carry over i think the data and the application and kind of the the domains might be different but the the most difficult problems uh all of that carries over between the domains so that that's very nice so that's how we approach it we're kind of build investing in the core the technical core and then there's specialization of and uh of that core technology to different product lines to different commercial applications so on just to tease it apart a little bit uh on trucks so starting with the hardware the configuration of the sensors is different right they're different physically geometrically you know different vehicles uh so for example we have two of our main laser uh on the trucks on both sides so that we have you know don't have the blind spots uh whereas on the jlr i-pace we have you know one of it uh sitting at the very top but the actual sensors are uh almost the same or largely uh the same so all of the investment that uh over the years we've put into building our custom lighters custom radars and pulling the whole system together that carries over very nicely uh then you know on the perception side uh the like the fundamental challenges of seeing understanding the world whether it's you know object detection classification you know tracking semantic understanding all that carries over now yes there's some specialization when you're driving on freeways uh you know range becomes more important the domain is a little bit different but again the fundamentals carry over very very nicely same and i guess you get into prediction or decision making right the fundamentals of what it takes to predict what other people are going to do to find the long tail to improve your system in that long tail of behavior prediction and response that carries over right and so on and so on so i mean that's pretty exciting by the way does waymovia include using the the smaller vehicles for transportation goods that's an interesting distinction so let's say there's three interesting modes of operation so one is moving humans one is moving goods and one is like moving nothing zero occupancy meaning like you're going to the destination your your empty vehicle i mean it's it's the third is the last wave that's the entirety of it it's so less you know exciting from the commercial perspective [Laughter] well i mean in terms of like if you think about what's inside a vehicle as it's moving because it does you know some significant fraction of the vehicle's movement has to be empty i mean it's kind of fascinating maybe just on that small point is is there different control and like policies that are applied for a zero occupancy vehicle so vehicle with nothing in it or is it just move as if there is a person inside what was with uh some subtle differences as a first order approximation there are no differences and if you think about you know safety and you know comfort and quality of driving only part of it you know has to do with the people or the goods inside of the vehicle right but you don't want to be you know you want to drive smoothly and as we discussed not for the purely funded benefit of you know whatever you have inside the car right it's also for the benefit of the you know people outside kind of feeding fitting uh naturally and predictably into the whole environment right so you know yes there are some second order uh things you can do it's gonna change your route and you know optimize maybe kind of your fleet things at the fleet scale and you would take into account whether some of your cars are actually you know serving a useful trip whether with people or with goods whereas you know other cars are you know driving completely empty you know to that next valuable trip that they're going to provide but that those are mostly second order effects okay cool so phoenix is uh is an incredible place and what you've announced in phoenix is uh it's kind of amazing but you know that's just like one city how do you take over the world uh i mean i'm asking for a friend once one step at a time is that the cartoon pinky in the brain yeah okay but you know gradually is a true answer so i think the heart of your question is what can you ask a better question than i asked they asked a great question to answer that one i i i'm you know just gonna you know phrase it in the terms that i want to answer perfect exactly right brilliant please you know where are we today and you know what happens next uh and what does it take to go beyond phoenix and was it what does it take uh to get this technology to more places and more people around the world right so our next big area of focus is exactly that larger scale commercialization and you know scaling up uh if i think about you know the main and your phoenix gives us that platform it gives us that foundation of upon which we can build them and it's there are few really challenging aspects of this whole problem that you have to pull together in order to build the technology in order to deploy it uh into the field to go from a driverless car to a fleet of cars that are providing a service and then all the way to you know commercialization so uh and then you know this is what we have in phoenix we've taken the technology from uh a proof point to an actual deployment and have taken our driver you know from you know one car to a fleet that can provide a service um beyond that if i think about what it will take to scale up and you know deploy in you know more places with more customers i tend to think about uh three main dimensions three main axes um of scale one is the core technology you know the hardware and software core capabilities of our driver the second dimension is evaluation and deployment and the third one is the product commercial and operational excellence so you can talk you know a bit about where we are along you know each one of those three dimensions about where we are today and you know what has what will happen next um on you know the core technology on you know the hardware and software and together comprise our driver we you know obviously have that foundation that is providing fully driverless trips to our customers as we speak in fact and we've learned a tremendous amount from that so now what we're doing is we are incorporating all those lessons into some pretty fundamental improvements in our core technology both on the hardware side and on the software side to build a more general more robust solution that then will enable us to massively scale you know beyond phoenix so on the hardware side all of those lessons are now incorporated into this fifth generation hardware platform that is you know uh being deployed right now and that's the platform the fourth generation the thing that we have right now driving in phoenix it's good enough to operate operate fully driverlessly you know night and day in various speeds and various conditions but the fifth generation is the platform upon which we want to go to massive scale we it in turn we've really made qualitative improvements in terms of the capability of the system the simplicity of the architecture the reliability of the redundancy it is designed to be manufacturable at very large scale and you know provides the right unit economics so that's that's the next big step for us um on the hardware side that's that's already there for scale the version five that's right is that uh coincidence or should we look into it conspiracy theory that's the same version as the pixel phone is that what's the harder they neither confirm okay all right cool so sorry so that's the okay that's that axis what else uh so similarly hardware is a very discrete jump but you know similar to the uh that to how we're making that change from the fourth generation hardware to the fifth we're making similar improvements on the software side to make it more you know robust and more general and allow us to kind of quickly uh scale beyond phoenix so that that's the first dimension of core technology the second dimension is evaluation and deployment now how do you measure your system how do you evaluate it how do you build the release and deployment process where you know with confidence you can you know regularly release new versions of your driver into a fleet how do you get good at it so that it is not you know a huge tax on your researchers and engineers that you know so you can how do you build all these you know processes the frameworks the simulation the evaluation the data science the validation so that you know people can focus on improving the system and kind of the releases just go out the door and get deployed across the fleet so we've gotten really good at that in phoenix that's been a tremendously difficult problem but that's what we have in phoenix right now that gives us that foundation and now we're working on kind of incorporating all the lessons that we've learned to make it more efficient to go to new places you know scale up and just kind of you know stamp things out so that's that second dimension of evaluation and deployment and the third dimension is product commercial and operational excellence right and again phoenix there is providing uh an incredibly valuable platform you know that's why we're doing things end-to-end uh in phoenix we're learning as you know we discussed a little earlier today a tremendous amount of really valuable lessons from our users getting really incredible feedback uh and uh we'll continue to iterate on that and incorporate all those uh those lessons into making our product you know even better and more convenient for our users so you're converting this whole process of phoenix in phoenix into uh something that could be copy and pasted elsewhere so like uh perhaps you didn't think of it that way when you were doing the experimentation phoenix but so how long did basically you can correct me but you've i mean it's still early days but you're taking the full journey in phoenix right as you were saying of like what it takes to basically automate i mean it's not the entirety of phoenix right but i imagine it can encompass the entirety of phoenix that's some some uh near-term date but that's not even perhaps important like as long as it's a large enough geographic area so what how copy-pastable is that process currently and how do like um you know like when you copy and paste in in uh in google docs i think you know in or in word you can like apply source formatting or apply destination formatting so how when you copy and paste uh the phoenix into like say boston uh how do you apply the destination formatting like how much of the core of the entire process of bringing an actual public transportation autonomous transportation service to a city is there in phoenix that you understand enough to copy and paste into boston or wherever um so we're not quite there yet we're not at a point where we're kind of massively copy and pasting all over the place uh but phoenix what you know we did in phoenix and we very intentionally have chosen phoenix as our first full deployment uh area you know exactly for that reason to kind of tease the problem apart look at each dimension and focus on the fundamentals of complexity and de-risking you know those dimensions and then bringing the entire thing together to get all the way and force ourselves to learn all those hard lessons on technology hardware and software on the evaluation deployment on you know operating a service operating a business using uh actually you know um serving our customers all the way so that we're fully informed about the most difficult most important challenges to get us to that next step of massive copy and pasting as as you said and uh [Music] that's what we're doing right now we're incorporating all those things that we learned into that next system that then will allow us to kind of copy paste all over the place and to massively scale to you know more users and more locations i mean you know just talked a little bit about you know what does that mean along those different dimensions so on the hardware side for example again it's that uh switch from the fourth to the fifth generation and the fifth generation is designed to kind of have that property can you say what other cities you're thinking about like i'm thinking about sorry we're in san francisco now i thought i want to move to san francisco but i'm thinking about moving to austin um i don't know why people are not being very nice about san francisco currently for maybe it's a small it's like maybe it's in vogue right now but uh austin seems i visited there and there was uh i was in a walmart it's funny these moments like turn your life there's this very nice woman with kind eyes just like stopped and said you look so handsome in that tie honey to me this has never happened to me in my life but just the sweetness of this woman is something i've never experienced certainly on the streets of boston but even in san francisco where people wouldn't that's just not how they speak or think i don't know there's a warmth too to austin that love and since waymo does have a little bit of a history there is that a possibility is this your version of asking the question of like you know dimitri i know you can't share your commercial and deployment roadmap but i'm thinking about moving to should i cisco austin like in a blink twice if you think i should move to him yeah that's true this room you got me we you know we've been testing and all over the place i think we've been testing more in 25 cities we drive in san francisco we drive in you know michigan for snow uh we we are doing significant amount of testing in the bay area including san francisco which is not like because we're talking about the very different thing which is like a full-on large geographic area public service uh you can't share any okay what about moscow is that when is that happening take on yandex i'm not paying attention to those folks they're doing you know there's there's a lot of fun i mean maybe as a way of a question you didn't speak to sort of like policy or like is there tricky things with government and so on like is there other friction that you've encountered except sort of technological friction of solving this very difficult problem is there other stuff that you have to overcome when when uh deploying a public service in a city that's interesting it's very important so we we put significant effort in uh creating those partnerships and you know those relationships with governments at all levels you know local governments municipalities you know state level federal level uh we've been engaged in very deep conversations from the earliest days of our you know projects uh whenever at all of these levels you know whenever we go to test uh or you know operate in a new area you know we always lead with with a conversation with the local officials and but the result of that that investment is that no it's not challenges we have to overcome it but it is a very important that we continue to have this conversation oh yeah i love politicians too okay uh so mr elon musk said that uh lidar is a crutch what are your thoughts i wouldn't characterize it exactly that way uh i know i think lighter is very important uh it is a key sensor uh that you know we use just like other modalities and as we discussed our cars use cameras uh lidars and radars they are all very important they are at the kind of the physical level they are very different they have very different you know physical characteristics cameras are passive lighters and radars are active you use different wavelengths uh so that means they complement each other uh and very nicely and and together combined they can be used to build a much safer and much more capable system so you know to me it's more of a question you know why the heck would you handicap yourself and not use one or more of those sensing modalities when they you know undoubtedly just make your system uh more capable and safer now it you know what might make sense for one product uh or one business might not make sense for another one so if you're talking about driver assist technologies you make certain design decisions and you make certain trade-offs and you make different ones if you are you know building a driver uh that deep deploy in fully driverless vehicles uh and you know and lighter specifically when this question comes up i uh you know typically the criticisms uh that i hear or you know the counterpoints that cost and aesthetics and like i i don't find either of those honestly very compelling so on the cost side there's nothing fundamentally prohibitive about you know the cost of lighters you know radars used to be very expensive uh before people start you know uh before people need certain balances and technology and you started to to manufacture them uh massive scale and deploy them in vehicles right uh similarly with lighters and this is where the lidars that we have on our cars especially the fifth generation uh you know we've been able to make some pretty qualitative discontinuous jumps in terms of the fundamental technology that allow us to manufacture those things at very significant scale and add a fraction of the cost of you know both our previous generation as well as a fraction of the cost of you know what might be available on the market you know off the shelf right now and you know that improvement will continue so i i think you know cost is uh not a real issue uh second one is uh you know uh aesthetics uh you know i don't think that's you know a real issue either uh um the beholder yeah you can make lidar sexy again i think you're exactly right i think it is sexy like honestly i think foreign you know i was actually somebody brought this up to me um i mean all forms of lidar even uh even like the ones that are like big you can make look i mean it can make look beautiful like there's no sense in which you can't integrate it into design like there's all kinds of awesome designs i don't think small and humble is beautiful it could be like you know brutalism or like it could be uh like harsh corners i mean like i said like hot rods like i don't like i don't necessarily like like oh man i'm gonna start so much controversy with this i i don't like porsches okay the porsche 911 like everyone says the most beautiful no it no it's like it's like a baby car it doesn't make any sense but everyone it's beauty's denied the beholder you're already looking at me like what's this kid talking about you're happy to talk about you're digging your own home the form and function and my take on the beauty of the hardware that we put on our vehicles you know i will not comment on a porsche monologue okay all right so but aesthetics fine but there's an underlying like philosophical question behind the kind of lighter question is like how much of the problem can be solved with uh computer vision with machine learning so i think without sort of disagreements and so on it's nice to put uh it on the spectrum because waymo is doing a lot of machine learning as well it's interesting to think how much of driving if we look at five years 10 years 50 years down the road would can be learned in almost more and more and more end-to-end way if we look at what tesla is doing with the as a machine learning problem they're doing a multi-task learning thing where it's just they break up driving into a bunch of learning tasks and they have one single neural network and they're just collecting huge amounts of data that's training that i've recently hung out with george cotts i don't know if you know george uh i love him so much he's just an entertaining human being we were off mike talking about hunter s thompson he's he's the hunter that's thompson and baton was driving okay so he i didn't realize this with common ai but they're like really trying to do end to end they're the machine like looking at the machine learning problem they're really not doing multi-task learning but it's uh it's it's computing the drivable area as a machine learning task and hoping that like down the line this level two system this driver assistance will eventually lead to allowing you to have a fully autonomous vehicle okay there's an underlying deep philosophical question there technical question of how much of driving can be learned so lidar is an effective tool today uh for actually deploying a successful service in phoenix right that's safe that's reliable et cetera et cetera but uh the the question and i'm not saying you can't do machine learning on lidar but the the question is that like how much of driving can be learned eventually can we do fully autonomous that's learned yeah uh you know learning is all over the place and plays a key role in every part of our system i i as you said i would uh you know decouple the sensing modalities from the you know ml and the software parts of it lighter radar cameras like it's all machine learning all of the object detection classification of course like that's what you know these modern deep nuts and continents are very good at you feed them raw data massive amounts of raw data um and you know that's actually what our custom build lighters and raiders are really good at and radars they don't just give you point estimates of you know objects in space they give you raw like physical observations and then you take all of that raw information you know there's colors of the pixels whether it's you know lighters returns and some auxiliary information it's not just distance right and you know angle and distance is much richer information that you get from those returns plus really rich information from the radars you fuse it all together and you feed it into those massive ml models that then you know lead to the best results in terms of you know object uh deduction classification you know state estimation so there's a side interrupt but there is a fusion i mean that's something that people didn't do for a very long time which is like at the sensor fusion level i guess like early on fusing the information together whether so that the the sensory information that the vehicle receives from the different modalities or even from different cameras is combined before it is fed into the machine learning models uh yes i think this is one of the trends you're seeing more of that you mentioned end to end there's different interpretations of antenna there's kind of the purest interpretation now i'm gonna like have one model that goes from raw sensor data to like you know steering torque and you know guest brakes that you know that that's too much i don't think that's the right way to do it there's more you know smaller versions of end to end where you're you know kind of doing more end-to-end learning or core training or deep propagation of kind of signals back and forth across the different stages of your system there's no really good ways it gets into some fairly complex design choices where on one hand you want modularity and the compass composite ability the composibility of your system but on the other hand you don't want to create interfaces that are too narrow or too brittle to engineered where you're giving up on the generality of the solution or you're unable to properly propagate signal you know reach signal forward and losses and you know back so you can you know optimize the whole system jointly uh so i would decouple and i guess what you're seeing in terms of the fusion of the sensing data from different modalities as well as kind of fusion at in the temporal level going more from you know frame by frame yeah where you know you would have one net that would do frame by frame detection and camera and then you know something that does frame by frame and lighter and then radar and then you fuse it you know in a weaker engineered way later like the field over the last you know decade has been evolving in more kind of joint fusion more end-to-end models that are solving some of these tasks you know jointly and there's tremendous power in that and you know that that's that's that that's the progression that kind of our technology our stack has been on as well now it's your you know that so i would decouple the kind of sensing and how that information is used from the role of ml in the entire stack and you know i guess it's uh i there's trade-offs uh and you know modularity and how do you inject inductive bias into your system right this is uh there's tremendous power in being able to do that so you know we have there's no part of our system that is not heavily that does not heavily you know leverage uh data-driven development or a state-of-the-art ml but there's mapping there's a simulator there's perception you know object level you know perception whether it's semantic understanding prediction decision making you know so forth and so on um it's and of course object detection and classification like you're finding pedestrians and cars and cyclists and you know cones and signs and vegetation and being very good at estimating kind of detection classification and state estimation there's just stable stakes like like that's step zero of this whole stack you can be incredibly good at that whether you use cameras or light as a radar but they're just you know that's stable stakes that's just stub zero beyond that you get into the really interesting challenges of semantic understanding of the perception level you get into scene level reasoning you get into very deep problems uh that have to do with prediction and joint production and interaction so interaction between all of the actors in the environment pedestrian cyclists other cars and you get into decision making right so how do you build a lot of systems so uh we leverage ml very heavily in all of these components i do believe that the best results you achieve by kind of using a hybrid approach and having different types of ml having different models with different degrees of inductive bias that you can have and combining kind of model you know free approaches with some you know model based approaches and some uh rule-based uh physics-based uh systems so you know one example i can give you is traffic lights uh there's problem of the detection of traffic light state and obviously that's a great problem for you know computer vision confidence are you know that's their bread and butter right that's how you build that but then the interpretation of you know of a traffic light that you're going to need to learn that right you you read you don't need to build something you know complex ml model that you know infers with some you know precision and recall that red means stop like it was a it's a very clear engineered signal with very clear semantics right so you want to induce that bias like how you induce that bias and that whether you know it's a constraint or a cost you know function in your stack but like it is important to be able to inject that like clear semantic signal into your stack and you know that's what we do um and but then the question of like and that's when you apply it to yourself when you're making decisions whether you want to stop for a red light you know or not but if you think about how other people treat traffic lights we're back to the ml version of that because you know they're supposed to stop for a red light but that doesn't mean they will so then you're back in the like very uh heavy uh ml domain where you're picking up on like very subtle keys about you know that have to do with the behavior of objects pedestrians cyclists cars and the whole entire configuration of the scene that allow you to make accurate predictions on whether they will in fact stop or run a red light so it sounds like a ready for waymo like machine learning is a huge part of the stack so it's a huge part of like uh not just so obviously the the first the level zero or whatever you said which is like just object detection of things that you know with no that machine learning can do but also starting to to do prediction behavior and so on to model the what other or the other parties in the scene entities in the scene are gonna do so machine learning is more and more uh playing a role in that as well of course absolutely i think we've been and going back to the earliest days like you know darpa even the grand challenge and team was leveraging you know machine learning i was like pre you know image nut and it was very different type of ml but uh and i think actually that was before my time but the stanford team on during the grand challenge had a very interesting machine learned system that would you know use lighter and camera when driving in the desert and it we had built the model uh where it would kind of extend the range of free space reasoning so we get a clear signal from lighter and then it had a model that hey like this stuff and camera kind of sort of looks like this stuff and lighter and i know this stuff and that i've seen in lighter i'm very confident there's free space so let me extend that uh free space zone into the camera range that would allow the vehicle to drive faster right and then we've been building on top of that and kind of staying and pushing the state of the art in a ml in all kinds of different ml uh over the years and in fact uh from the earlier days i think you know 2010 is probably the year where google uh maybe 2011 probably got got pretty heavily involved in uh machine learning uh kind of deep nuts uh and at that time was probably the only company that was very heavily investing in kind of state-of-the-art ml and self-driving cars right and they they they go ahead you know hand in hand and we've been on that journey ever since we're doing uh pushing a lot of these areas uh in terms of research you know at waymo and we collaborate very heavily with the researchers in alphabet and like all kinds of mel yeah supervise the male unsupervised male uh you know published some uh interesting uh research papers in the space uh especially recently it's just super super learning as well yeah so super super active uh of course there's you know kind of like more uh mature stuff like you know confidence for you know object detection but there's some really interesting really active uh work that's happening in um kind of more uh you know and bigger models and you know models that uh have more structure uh to them uh you know not just you know large bitmaps and reasonable temporal sequences and some of the interesting breakthroughs that you've you know we've seen in language models right you know transformers you know you know gpd 3 and friends uh there's some really interesting applications of some of the core breakthroughs to those problems of you know behavior prediction as well as you know decision making and planning right you think about it kind of the the behavior how you know the path the trajectories the the how people drive and they have kind of a share a lot of the fundamental structure you know this problem there's you know sequential you know nature there's a lot of structure uh in this representation there is a strong locality kind of like in sentences you know words that follow each other they're strongly connected but there's also a kind of larger context that doesn't have that locality and you also see that in driving right what's happening in the scene as a whole has very strong implications on uh you know the kind of the next step in that sequence where whether you're predicting what other people are going to do whether you're making your own decisions or whether in the simulator you're building generative models of you know humans walking cyclists riding another car is driving oh that's that's all really fascinating like how it's fascinating to think that uh transformer models and all this all the breakthroughs in language and nlp that might be applicable to like driving at the higher level at the behavioral level that's kind of fascinating um let me ask about pesky little creatures called pedestrians and cyclists they seem so humans are a problem if we can get rid of them i would um but unfortunately they're all sort of a source of joy and love and beauty so let's keep them around they're also our customers oh for your perspective yes yes for sure there's some money very good um but uh i don't even know where i was going oh yes pedestrians and cyclists uh i you know they're a fascinating injection into the system of uh uncertainty of um of like a game theoretic dance of what to do and and also they have perceptions of their own and they can tweet about your product so you don't want to run them over from that perspective uh i mean i don't know i'm joking a lot but that i think in seriousness like you know pedestrians are complicated um uh computer vision problem a complicated behavioral problem is there something interesting you could say about what you've learned from a machine learning perspective from also an autonomous vehicle and a product perspective about just interacting with the humans in this world yeah just you know stayed on the record we care deeply about the safety of pedestrians you know even the ones that don't have twitter accounts um thank you all right but you know not me but yes i i'm glad i'm glad somebody does okay uh but you know in all seriousness safety of uh vulnerable road users pedestrians or cyclists is one of our highest priorities we do a tremendous amount of testing and validation and put a very significant emphasis on you know the capabilities of our systems that have to do with safety around those unprotected vulnerable road users um you know cars just you know discussed earlier in phoenix we have completely empty cars completely driverless cars you know driving in this very large area and you know some people use them to you know go to school so they'll drive through school zones right kids are kind of the very special class of those vulnerable user road users right you want to be super super safe and super super cautious around those so we take it very very very seriously um and you know what does it take uh to uh be good at it uh you know an incredible amount of uh performance across your whole stack you know starts with hardware and again you want to use all sensing modalities available to you imagine driving on a residential road at night and kind of making a turn and you don't have you know headlights covering some part of the space and like you know a kid might run out and you know lighters are amazing at that they see just as well in complete darkness as they do during the day right so just again it gives you that extra uh uh you know margin in terms of your capability and performance and safety and quality and in fact we oftentimes uh in these kinds of situations we have our system detect something in some cases even earlier than our trained operators in the car might do especially in conditions like you know very dark nights um so starts with sensing then you know perception has to be incredibly good and you have to be very very good at kind of detecting uh pedestrians uh in all kinds of situations and all kinds of environments including people in weird poses uh people kind of running around and you know being partially occluded um so you know that that's stop number one then you have to have in very high accuracy and very low latency in terms of your reactions to you know what you know these uh actors might do right and we've put a tremendous amount of engineering and tremendous amount of validation in to make sure our system performs uh and you know oftentimes it does require a very strong reaction to do the same thing and we actually see a lot of cases like that that's the long tail of really rare you know really uh kind of crazy events that contribute to the safety around pedestrians like one one example that comes to mind that we actually happened uh in phoenix where we were uh driving uh along and i think it was a 45 mile per hour road so in pretty high speed traffic and there was a sidewalk next to it and there was a cyclist on the sidewalk and as uh we were in the right lane and right next to the site so it was a multi-lane road so as we got close to the cyclist on the sidewalk uh it was a woman and she tripped and fell just you know fell right into the path of our vehicle right um and our you know cart uh uh you know this was actually with a test driver our test drivers uh uh did exactly the right thing uh they kind of reacted and came to stop it requires both very strong steering and uh you know strong application of the brake uh and then we simulated what our system would have done in that situation and it did exactly the same thing it uh and that that speaks to all of those components of really good uh state estimation and tracking and like imagine you know a person on a bike and they're falling over and they're doing that right in front of you right so you have to be real like things are changing the appearance of that whole thing is changing right and the person goes one way they're falling on the road they're you know being flat on the ground in front of you you know the the bike goes flying the other direction like the two objects that used to be one they're now you know uh are splitting apart and the car has to like detect all of that uh like milliseconds matter and it doesn't it's not good enough to just break you have to like steer and break and there's traffic around you so like it all has to come together and it was really great uh to see in this case and other cases like that that we're actually seeing in the wild that our system is you know performing exactly the way uh that we would have liked and is able to you know avoid uh collisions like this such an exciting space for robotics like in that split second to make decisions of life and death i don't know if the stakes are high in the sense but it's also beautiful that um um for somebody who loves artificial intelligence the possibility that an ai system might be able to save a human life that's kind of exciting as a as a problem like to wake up you get it's terrifying probably from energy for an engineer to wake up and to think about but it's also exciting because it's like it's it's in your hands let me try to ask a question that's often brought up about autonomous vehicles and it might be fun to see if you have anything anything interesting to say which is about the trolley problem so uh a trolley problem is a interesting philosophical construct of uh that highlights and there's many others like it of the difficult ethical decisions that uh we humans have before us in this complicated world uh so the specifically is the choice between if you were forced to choose uh to kill a group x of people versus a good why of people like one person if you didn't if you did nothing you would kill one person but if you would kill five people and if you decide to swerve out of the way you would only kill one person do you do nothing or you choose to do something you can construct all kinds of sort of ethical experiments of this kind that um i i think at least on a positive note inspire you to think about like introspect what are the the physics of our morality and there's usually not good answers there i think it people love it because it's just an exciting thing to think about i think people who build autonomous vehicles usually roll their eyes because uh this is not this one as constructed this like literally never comes up in reality you never have to choose between killing one like one of two groups of people but i wonder if you can speak to is there some something interesting to use an engineer of autonomous vehicles that's within the trolley problem or maybe more generally are there difficult ethical decisions that you find that the algorithm must make on the specific version of the trial problem which one would you do if you're driving the question itself is a profound question because we humans ourselves cannot answer and that's the very point uh i guess i would kill both um yeah humans i think you're exactly right and that you know humans are not particularly good i think they kind of phrased as a like what would a computer do but like humans you know are not very good and i actually often times i think that you know freezing and kind of not doing anything because like you've taken a few extra milliseconds to just process and then you end up like doing the worst of the possible outcomes right so um i i do think that as you've pointed out it can be a bit of a distraction and it can be a bit of a kind of red herring i think it's an interesting philosophy discussion in the realm of uh philosophy um right but in terms of what you know how that affects the actual engineering and deployment of self-driving vehicles i um it's not how you go about building a system right we have talked about how you engineer a system how you go about evaluating the different components and you know the safety of the entire thing how do you kind of inject the you know various model based safety based arguments and you're like yes you reason it parts the system you know you reason about the probability of a collision the severity of that collision right and that is incorporated and there's you know you have to properly reason about uncertainty that flows through the system right so you know those uh um you know factors definitely play a role in how the cars don't behave but they have to be more of like the immersion behavior and what you see like you're absolutely right that these you know clear uh theoretical problems that they you know you you don't require that in system and really kind of being back to our previous discussion of like what what you know what what you know which one do you choose well you know oftentimes like you made a mistake earlier like you shouldn't be in that situation uh in the first place right and in reality the system comes up if you build a very good safe and capable driver you have enough uh you know clues uh in the environment that you drive defensively so you don't put yourself in that situation right and again you know it has you know this if you go back to that analogy of you know precision and recall like okay you can make a very hard trade-off of the i1 but like neither answer is really good but what instead you focus on is kind of moving the whole curve up and then you focus on building the right capability and the right defensive driving so that you know you don't put yourself in a situation like this i don't know if you have a good answer for this but people love it when i ask this question about books um are there books in um in your life that you've enjoyed philosophical fiction technical that had a big impact on you as an engineer or as a human being you know everything from science fiction to a favorite textbook is there three books that stand out that you can think of uh three books so i would uh you know that impacted me um i would say uh this one is you probably know it well um but and not generally well known i i think in the u.s or kind of internationally the master and margarita it's uh one of actually my favorite uh books um it is you know by a russian it's a novel by russian author uh mikhail bulgakov and it's just it's it's a great book and it's one of those books that you can like reread your entire life and it's very accessible you can read it as a kid and like it's it you know it's that the plot is interesting it's you know the the devil you know visiting the soviet union and yeah but it it like you read it reread it at different stages of your life and you yeah you enjoy it for different very different reasons and you keep finding like deeper and deeper meaning uh and you know kind of affected you know hadn't definitely had an like imprint on me mostly from the probably kind of the cultural stylistic uh aspect like it makes you one of those books that you know is good and makes you think but also has like this really you know silly quirky dark sense of you know humor hey casper is the russian so that's more than maybe perhaps many other books on that like slight no just out of curiosity one of the saddest things is i've read that book in english did you by chance read it in english or in russian uh in russian only in russian uh and i actually that that is a question i had uh uh kind of pose to myself every once in a while like i wonder how well it translates if it translates at all and there's the language aspect of it and then there's the cultural aspect so i and actually i'm not sure if you know either of those would so work well in english now i forget their names but so when the covid lists a little bit i'm traveling to paris uh for for several reasons one it's just i've never been to paris i want to go to paris but there's a the most famous translators of uh destielski tolstoy of most of russian literature live there there's a couple they're famous a man and a woman and i'm going to sort of have a series of conversations with them and in preparation for that i'm starting to read dusty sk in russian so i'm really embarrassed to say that i read this everything i've read russian literature of like serious depth has been in english even though i can also read i mean obviously in russian but for some reason it seemed uh in the optimization of life it seemed the improper decision to do to read in russian like you know like i don't need to opt i need to think in english not in russian but now i'm changing my mind on that and so the question of how well it translates it's a really fundamental one like it even with dostoyevsky so from what i understand this death can translate easier uh others don't as much obviously the poetry doesn't translate as well i'm also the the music of a big fan of vladimir wassotsky he doesn't obviously translate well people have tried but mastermind i don't know i don't know about that one i just know it in english you know it's fun fun as hell in english so uh so but it's a curious question and i want to study it rigorously from both the machine learning aspect and also because i want to do a couple of interviews in russia that i'm still unsure of how to properly conduct an interview across a language barrier it's a fascinating question that ultimately communicates to an american audience there's a few russian people that i think are truly special human beings and i feel like i sometimes encounter this with some incredible scientists and maybe you encounter this as well at some point in your life that it feels like because of the language barrier their ideas are lost to history it's a sad thing i think about like chinese scientists or even authors that like that we don't in english-speaking world don't get to appreciate some like the depth of the culture because it's lost in translation and i feel like i would love to show that to the world like i'm i'm just some idiot but because i have this like at least some semblance of skill in speaking russian i feel like and i know how to record stuff on a video camera i feel like i want to catch like gregory pearlman who's a mathematician i'm not sure if you're familiar with him yeah i want to talk to him like he's a fascinating mind and to bring him to a wider audience in english speaking it'll be fascinating but that requires to be rigorous about this question of how well uh bulgakov translates i mean i i know it's a it's a silly concept but it's a fundamental one because how do you translate and that's that's the thing that uh google translate is also facing yeah uh as a as a more machine learning problem but i i wonder is a more bigger problem for ai how do we capture the magic that's there in the language i i think that's a really interesting really challenging problem i if you do read it master and margarita in uh english uh sorry in russian i'd be curious get your uh opinion and i think part of it is language but part of it's just you know centuries of culture that the cultures are different so it's hard to connect that but uh okay so that was my first one right you had to know tomorrow um the second one i would probably pick the science fiction by the stragoski brothers uh you know it's up there with you know isaac asimov and you know ray bradbury uh and you know company uh the straguski brothers kind of appealed more to me i think more it made more of an impression on me uh growing up um can you i apologize if i'm showing my complete ignorance i'm so weak on sci-fi which what what are they right oh um uh roadside picnic um [Music] uh hard to be a god uh uh beetle in an ant hill uh monday starts on saturday like it's it's not just science fiction it's also like has very interesting you know interpersonal and societal questions and some of the language is just completely hilarious that's the one that's right oh interesting monday starts on saturday so i need to read okay oh boy you put that in the category of science fiction uh that one is i mean this was more of a silly you know humorous uh work i mean there is kind of profound too right science fiction right is about you know this this research institute and like this it it has deep parallels to like serious research but the the setting of course is that they're working on you know magic right and there's a lot of stuff so i i i i that that's their style right they go and you know other books are very different right you know hard to be a god right it's about kind of this higher society being injected into this primitive world and how they operate there like some of the very deep ethical you know questions there right and like they've got this spectrum some as you know more about kind of more uh adventure style but like i i enjoy all of their books there's probably a couple actually one i think that they consider their most important work i think it's the snail on an on a a hill i don't know exactly how sure how it translates i tried reading a couple of times i still don't get it but everything else i fully enjoyed uh and like for one of my birthdays as a kid i got like their entire collection like occupied a giant shelf in my room and then like over the holidays i just like you know my parents couldn't drag me out of the room and i read the whole thing cover to cover and it it uh i really enjoyed it uh and that's it one more i thought for the third one i you know maybe a little bit darker um uh but you know comes to mind is orwell's 1984. uh and i you know you asked what made an impression on me and books that people should read that one i think falls in the category of both now you know definitely it's one of those books that you read and you just kind of you know put it down and you stare in space for a while uh yeah you know that that that kind of work uh i i think there's you know lessons there people uh should not ignore and you know nowadays with like everything that's happening in the world i i can't help it but you know have my mind jump to some you know parallels uh with what orwell described and like there's this whole you know concept of double think and ignoring logic and you know holding completely contradictory opinions in your mind and not have that not bother you and you know sticking to the party line yeah uh at all costs like you know there's there's there's something there if anything 2020 has taught me and i'm a huge fan of animal farm which is a kind of friendly as a friend of 1984 by orwell it's kind of another thought experiment of how our society may go in directions that we wouldn't like it to go but if if anything that's been [Music] kind of heartbreaking to an optimist about 2020 is that that society is kind of fragile like we have this this is a special little experiment we have going on and not it's not unbreakable like we should be careful to like preserve whatever special thing we have going on i mean i think 1984 in these books brave new world they they're helpful in thinking like stuff can go wrong in non-obvious ways and it's like it's up to us to preserve it and it's like it's a responsibility it's been weighing heavy on me because like for some reason like uh more than my mom follows me on twitter and i feel like i have i have like now somehow a responsibility to um to this world and it dawned on me that like me and millions of others are like the little ants that maintain this little colony right so we have a responsibility not to be uh i don't know what the right analogy is but i'll put a flamethrower to the place we want to not do that and there's interesting complicated ways of doing that as 1984 shows it could be through bureaucracy it could be through incompetence it could be through misinformation it could be through division and toxicity uh i'm a huge believer in like that love will be the somehow the solution so uh loving robots yeah i i think you're exactly right unfortunately i think it's uh less of a flamethrower type of next i think it's more of a in many cases can be more of a slow boil and that that's the danger let me ask uh it's a fun thing to make a world-class roboticist engineer and leader uncomfortable with a ridiculous question about life what is the meaning of life at dmitry from a robotics and a human perspective you only have a couple minutes or one minute to answer so i don't know if that makes it more difficult or easier actually yeah you know they're very tempted to uh quote uh one of the stories stories by uh uh isaac asimov actually um actually titled appropriately titled the last question uh short story where you know the plot is that you know humans build this super computer you know this this this ai intelligence and you know once it's get power gets powerful enough they pose this question to it you know um how can the entropy in the universe be reduced all right so your computer replies and as of yet insufficient information to give a meaningful answer right and then you know thousands of years go by and they keep posing the same question the computer you know it gets more and more powerful and keeps giving the same answer yeah as of yet insufficient information to give a meaningful answer or something along those lines right and then you know keeps you know happening and happening you fast forward like millions of years into the future and you know billions of years and like at some point it's just the only entity in the universe it's like absorbed all humanity and all knowledge in the universe and it like keeps posing the same question to itself and you know finally it gets to the point where it is able to answer that question but of course at that point you know there's you know the heat death of the universe has occurred and that's the only entity and there's nobody else to provide that answer to so the only thing it can do is to you know answer it by demonstration so it like you know recreates the big bang right and resets the clock right but i i can try to give kind of a a different version of the answer you know maybe uh not on the behalf of all humanity i think that that might be a little presumptuous for me to speak about the meaning of life on the behalf of all humans uh but at least you know personally uh it changes right i think if you think about kind of what uh gives uh you know you and your life meaning and purpose and kind of what drives you um it seems to change over time right and the the the lifespan of you know your existence uh you know when just when you just enter this this world right it's all about kind of new experiences and you get like new smells new sounds new emotions right and like that's what's driving you right you're experiencing new amazing things right and that that's magical right that's pretty pretty pretty pretty awesome right that gives you kind of meaning then you get a little bit older you start more intentionally uh learning about things right i guess actually before you start intentionally learning probably fun fun is a thing that gives you kind of meaning and purpose and purpose and the thing you optimize for right and like fun is good uh then you get you know start learning and i guess that this this joy of comprehension and discovery is another thing that you know gives you meaning and purpose and drives you right then you know you learn enough stuff and it you want to give some of it back right and so impact and contributions back to you know technology or society uh uh people uh you know local or more globally yeah is becomes a new thing that you know drives a lot of kind of your behavior and something that gives you purpose and that you derive you know positive feedback from right you know then you go and so on and so forth you go through various stages of life if you have if you have kids like that definitely changes your perspective on things you know i have three that definitely flips some bits in your head in terms of you know what you care about and what you optimize for and you know what matters what doesn't matter right so you know and so on and so forth right and i i i it seems to me that you know it's all of those things and as kind of you go through life um you know you want these to be additive right new experiences fun learning impact like you want you want to you know be accumulating other you know i don't want to you know stop having fun or experiencing new things and i think it's important that it just kind of becomes uh additive as opposed to a replacement or subtraction but you know views probably as far as i got but you know ask me in a few years i might have one or two more to add to the list and before you know it time is up just like it is for this conversation uh but hopefully it was a fun ride it was a huge honor to meet you as you know i've been a fan of yours and a fan of google self-driving car and waymo for a long time i can't wait i mean it's one of the most exciting if we look back in the 21st century i truly believe it'll be one of the most exciting things we descendants of apes have created on this earth so i'm a huge fan and i can't wait to see what you do next thanks so much for talking today thanks thanks for having me and it's a also a huge fan doesn't work honestly and uh i really enjoyed it thank you thanks for listening to this conversation with dimitri dalgov and thank you to our sponsors trial labs a company that helps businesses apply machine learning to solve real world problems blinkist an app i use for reading through summaries of books better help online therapy with a licensed professional and cash app the app i use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoyed this thing subscribe on youtube review 5000 upper podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from isaac asimov science can amuse and fascinate us all but it is engineering that changes the world thank you for listening and hope to see you next time you |
Michael Mina: Rapid Testing, Viruses, and the Engineering Mindset | Lex Fridman Podcast #146 | the following is a conversation with michael minna he's a professor at harvard doing research on infectious disease and immunology the most defining characteristic of his approach to science and biology is that of a first principles thinker and engineer focused not just on defining the problem but finding the solution in that spirit we talk about cheap rabbit at home testing which is a solution to covet 19 that to me has become one of the most obvious powerful and doable solutions that frankly should have been done months ago and still should be done now as we talk about its accuracy is high for detecting actual contagiousness and hundreds of millions can be manufactured quickly and relatively cheaply in general i love engineering solutions like these even if government bureaucracies often don't it respects science and data it respects our freedom it respects our intelligence and basic common sense quick mention of each sponsor followed by some thoughts related to the episode thank you to brave a fast browser that feels like chrome but has more privacy preserving features athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases expressvpn the vpn i've used for many years to protect my privacy and the internet and cash app the app i use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that i've always been solution oriented not problem oriented it saddens me to see that public discourse disproportionately focuses on the mistakes of those who dared to build solutions rather than applaud their attempt to do so teddy roosevelt said it well in his the man in the arena speech over 100 years ago i should say that both the critic and the creator are important but in my humble estimation there are too many now of the former and not enough of the latter so while we spread the derisive words of the critic on social media making it viral let's not forget that this world is built on the blood sweat and tears of those who dare to create if you enjoy this thing subscribe on youtube review with five stars not a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with michael minna what is the most beautiful mysterious or surprising idea in the biology of humans or viruses that you've ever come across in your work sorry for the overly philosophical question wow well that's a great question you know i love the pathogenesis of viruses and one of the things that i've worked on a lot is trying to understand how viruses interact with each other and so pre all this covered stuff it was uh i was really really dedicated to understanding uh how uh how viruses impact uh other pathogens so how if somebody gets an infection with one thing or a vaccine does it either benefit or harm you from other things that appear to be unrelated to in the to most people and so one one system which is highly detrimental to humans but what i think is just immensely fascinating is measles and measles gets into a kid's body the immune system picks it up and essentially grabs the virus and does exactly what it's supposed to do which is to take this virus and bring it into the immune system so the immune system can learn from it can develop an immune response to it but instead measles plays a trick it gets into the immune system serves almost as a trojan horse and instead of getting eaten by these by these cells it just takes them over and it ends up proliferating in the very cells that were supposed to kill it and it just distributes throughout the entire body gets into the bone marrow kills off children's immune memories and so it essentially what i've found and what my research has found is that this one virus was responsible for as much as half of all the infectious disease deaths in kids before we started vaccinating against it because it was just wiping out children's immune memories to all different pathogens which is you know i think um just astounding it's just amazing to watch it spread throughout bodies we've done the studies in monkeys and and you can watch it just destroy and obliterate people's immune memories in the same way that you know some parasite might destroy somebody's brain and it's is that a evolutionary just coincidence or is there some kind of advantage to this kind of interactivity between pathogen well i think in that sense it's just coincidence uh it probably is a it's a good way for measles to uh it's a good way for measles to essentially be able to survive uh long enough to replicate in the body it just replicates in the cells that are meant to destroy it so it's uh it's utilizing our immune cells for its own replication uh but in so doing it's destroying the memories of all the other the other immunological memories so but there are other viruses so a different system is influenza and uh flu predisposes to severe bacterial infections and that i think is another coincidence but i but i also think that there are that there are some evolutionary benefits that bacteria may hijack and sort of piggyback on viral infections viruses can they just grow so much quicker than bacteria they replicate faster and so there's the system with viruses with flu and and bacteria where the influenza has these proteins that cleave certain receptors and the bacteria want to cleave those same receptors i want to cleave the same molecules that gave entrance to those receptors so instead the bacteria found out like hey you know we could just piggyback on these viruses they'll do it a hundred or a thousand times faster than we can and so then they just piggy back on and they let flu cleave all these cyalic acids and then the bacteria just glom on and in the wake of it so there's all different interactions between pathogens that are just remarkable so does this whole system of viruses that interact with each other and so damn good at getting inside our bodies does that fascinate you or terrify you i'm very much a scientist and so uh it fascinates me much more than it terrifies me but knowing enough i know just how well you know we get the wrong virus um in our population whether it's through some random mutation or whether it's this same covid19 virus and it you know these things are tricky they're able to mutate quickly they're able to find new hosts and rearrange in the case of influenza so what terrifies me is just how easily this particular pandemic could have been so much worse this could have been a virus that is uh much worse than it is you know same thing with h1n1 back in 2009 uh that terrifies me if a virus like that was much more detrimental uh you know that would be it could be much more devastating although it's hard to say you know the the human species were well i i hesitate to say that we're good at responding to things because there are some aspects that were this particular virus stars cove too and covet 19 has found a sweet spot where where it's not quite serious enough on an individual level that humans just don't we haven't seen much of a useful response by many humans like a lot of people even think it's a hoax and so it's led us down this path of uh it's not quite serious enough to get everyone to respond immediately and with the most urgency but it's enough it's bad enough that you know it's caused our economies to shut down and collapse and so um i think i know enough about virus biology to be terrified for humans that you know it can it just takes one virus just takes the wrong one to just obliterate us or or not obliterate us but but really do much more damage than we've seen it's fascinating to think that code 19 is uh as a result of a virus evolving together with like twitter yeah like figuring out how we can sneak past the defenses of the humans so it's not bad enough and then the misinformation all that kind of stuff together is operating in such a way that the virus can spread effectively i wonder i mean obviously uh a virus is not intelligent but there's a uh there's a rhyme and a rhythm to the way this whole evolutionary process works and creates these fascinating things that spread throughout the entire civilization absolutely it's um yeah i'm i'm completely fascinated by this idea of social media in particular how it replicates how it grows you know i've been how it inner how it like actually starts interacting with the biology of the virus masks who's going to get vaccinated politics like these seem so external to virus biology but it's become so in intertwined and uh and it's it's interesting and i actually think we could find out that you know the virus actually becomes uh obviously not uh intentionally but you know we could find that choosing people choosing not to wear masks choosing choosing not to counter this virus in a regimented and sort of organized way effectively gives the virus more opportunity to escape we can look at vaccines you know we're about to we're about to have one of the most aggressive vaccination programs the world has ever seen but we are unfortunately doing it right at the peak of viral transmission when millions and millions of people are still getting infected and when we do that that just gives this virus so many more opportunities i mean orders of magnitude more opportunity to mutate around our immune system now if we were to vaccinate everyone when there's not a lot of virus then there's just not a lot of virus and so there's not going to be as many you know i don't even know how many zeros are at the end of however many viral particles there are in the world right now you know more than quadrillions you know and so if you assume that at any given time somebody might have trillions of virus in them and any given individual so then you know multiply trillions by millions and yeah you know you get a lot of viruses out there and and if you start applying pressure ecological pressure to this virus that that you know when it's that abundant cloud the opportunity for a virus to sneak around immunity especially when all the vaccines are identical essentially um it takes is one to mutate and then jumps oh it takes one takes one in the whole world you know and we have to we have to not forget that this particular virus was one it was one opportunity and it has spread across the globe and there's no reason that can't happen tomorrow i knew you know it's scary i have a million other questions in this direction but i'd love to talk about one of the most exciting aspects of your work which is uh testing or rapid testing you wrote a great article in time on november 17th this is like a month ago about rapid testing titled how we can stop the spread of kobe 19 by christmas let's jot down the fact that this is a month ago so maybe your timeline would be different but let's say in a month so you've talked about this powerful idea for quite a while throughout the covid 19 pandemic how do we stop the spread of covad19 in a month well we uh we use tests like these you know so so the only reason the virus continues spreading is because people spread it to each other this isn't this isn't magic yes um and so there's a few ways to stop the virus from spreading to each other and that is uh you either can vaccinate everyone and vaccinating everyone is a way to immunologically prevent the virus from growing inside of somebody and therefore spreading we don't know yet actually if this vaccine if any of these vaccines are going to prevent onward transmission so so that may or may not serve to be one opportunity certainly i think it will decrease transmission but the other idea that we have at our disposal now we had it in may we added in june july august september october november and now it's december we still have it we still choose not to use it in this country and in much of the world and that's rapid testing that is giving it's empowering people to know that they are infected and giving them the opportunity to not spread it to their loved ones and their friends and neighbors and whoever else we could have done this we still can today we could start we have millions of these tests these tests are uh simple paper strip tests they are uh inside of this thing is just a little piece of paper now and i can actually open it up here there we go so this this is how we do it right here we have this little paper strip test this is enough to let you know if you're infectious with somewhere around the order of 99 sensitivity 99 specificity you can know if you have infectious virus in you if we can get these out to everyone's homes build these make 10 million 20 million 30 million of them a day you know we make more bottles of dasani water every day we can make these little paper strip tests and if we do that and we get these into people's homes that they can use them twice a week then we can know if we're infectious you know is it perfect absolutely not but is it near perfect absolutely you know and so if we can say hey the the transmission of this is you know for every 100 people that get infected right now they go on to infect maybe 130 additional people and that's exponential growth so 100 becomes 130. a couple days later that 130 becomes uh another another 165 people have now been infected and you know go over three weeks and 100 people become 500 people infected now it doesn't take much to have those hundred people not infect 130 but infect 90. all we have to do is remove say 30 40 of new infections from continuing their spread and then instead of exponential growth you have exponential decay so this doesn't need to be perfect we don't have to go from 100 to zero we just have to go and have those hundred people infect 90 and those 90 people infect you know 82 whatever it might be and you do that for a few weeks and boom you have now gone instead of 100 to 500 you've gone from 100 to 20. yes it's not very hard and so the way to do that is to let people know that they're infectious i mean i've we're a perfect example right now i i this morning i used these tests uh to make sure that i wasn't infectious is it perfect no but it reduced my odds 99 i already was at extremely low odds because i spent my life quarantining these days well the interesting thing with this test which uh with the testing in general which is why i love what you've been espousing is it's really confusing to me that this has not been taken on as it's one an actual solution that's those available for a long time there's there doesn't seem to have been solutions uh proposed at a large scale and a solution that it seems like a lot of people would be able to get behind there's some politicization or fear of other solutions that people propose which is like lock down and there's a worry you know especially in the american spirit of freedom like you can't tell me what to do the thing about tests is it like empowers you with information essentially yes so like you it's it gives you more information about your like your role in this pandemic and then you can do whatever the hell you want like it's all up to your ethics and and so on so like and it's it's obvious that with that information people would be able to protect their loved ones and also do uh do their sort of quote-unquote duty for their country right it's protect the rest of the country that's exactly right i mean it's just it's empowerment but you know this is a problem we have not put these into action in large part because we have a medical industry that doesn't want to see them be used we have a political and a regulatory industry that doesn't want to see them be used that sounds crazy why wouldn't they want them to be used we have a very paternalistic approach to everything in this country you know despite this country kind of being founded on this individualistic ideal pull yourself up from your bootstraps all that stuff uh when it comes to public health we have a bunch of ivory tower academics who want data that you know they want to see perfection and we have this issue of letting perfection get in the way of actually doing something at all you know doing something effective and so we keep comparing these tests for example to the laboratory-based pcr test and sure this isn't a pcr test but this doesn't cost a hundred dollars and it doesn't take five days to get back which means in every single scenario this is the more effective test and we have unfortunately a system that's not about public health we have entirely eroded any ideals of public health in our country for the biomedical complex you know this medical industrial complex which overrides everything and that's why you know i'm just can i swear on this podcast yes i'm just so fucking pissed that these tests don't exist meanwhile and everyone says you know how we couldn't make these you know that we could never do it that would be such a hard a difficult problem meanwhile the vaccine gets we've we have at the same time that we could have gotten these stupid little paper strip tests out to every household we have uh developed a brand new vaccine we've gone through phase one phase two phase three trials we've scaled up its production and now we have ups and fedex and all the logistics in the world getting freezers out to where they need to be we have this immense we see with when it comes to sort of medicine you know something you're injecting into somebody then all of a sudden people say oh yes we can yeah but you say oh no that's that's too simple a solution too cheap a solution no way could we possibly do that it's this faulty thinking in our country which you know frankly is driven by big money big you know the only time when we actually think that we can do something that's maybe aggressive and complicated is when there's billions and billions of billions of dollars in it you know and i mean on a difficult note because this is part of your work from before the corvaid it does seem that i saw a statistic currently is that 40 percent would not be taken off americans would not be taking a vaccine some some number like this so you also have to acknowledge that all the money that's been invested like there doesn't appear to be a solution to deal with like the fear and distrust that people have i bet i don't know if you know this number but for taking a strip like a rapid test like this i bet you people would say like the percentage of people that wouldn't take it is in the single digits probably i completely think so and you know there's a lot of people who don't want to get a test today and that's because it gets sent to a lab it gets reported it has all the stuff and in our country which teaches people from the time they're babies you know to keep their medical data close to them we have hipaa we have all these we have immense rules and regulations to ensure the privacy of people's medical data and then a pandemic comes around and we just assume that all that the average person is going to wipe all that away and say oh no i'm happy giving out not just my own medical data but also to tell the authorities everyone who i've spent my time with so that they all get a call and are pissed at me for giving up their names you know so people aren't getting tested and they're definitely not giving up their contacts when it comes to contact tracing and so for so many reasons that approach is failing uh not to even mention the delays in testing and things like that and so this is a whole different approach but it's an approach that empowers people and takes the power a bit away from the people in charge you know and that's what's that's what's really grating on on i think public health officials who say no we need the data so they're effectively saying if i can't have the data i don't want the individuals i don't want the public to have their own data either which is a terrible approach to a pandemic where we can't solve a public health crisis without actively engaging the public it just doesn't work and uh you know and that's what we're trying to do right now which is a terrible approach so first of all there's a you have a really nice informative website rapidtest.org information on this i still can't believe this is not more popular it's ridiculous okay but uh our our uh one of the uh faqs you have is a rapid test too expensive so can can cost be brought down like i pay i take a weekly pcr test and i think i pay 160 170 bucks a week no i mean it's criminal absolutely we can get costs this this thing right here cost less than a dollar to make with everything combined plus the swabs you know maybe it costs a dollar fifty could be sold for uh frankly it could be sold for three dollars and still make a profit if they want to sell it for five this one here this is a slightly more complicated one but you can see it's just got the exact same paper strip inside this is really it doesn't look like much but it's kind of the cream of the crop in terms of these rapid tests this is the one that the us government bought and it is doing an amazing job it has a 99.9 uh sensitivity and specificity so it's really it's really good and so essentially the way it works is you just you use a swab you put the once you you kind of use the swelling yourself you put the swab into these little holes here you put some buffer on and you close it and uh and a line will show up if it's positive and a line won't show up but it's negative it takes 5-10 minutes this whole thing the this this can be made so cheap that the us government was able to buy them by 150 million of them from uh abbott for five dollars a piece you know so anyone who says that these are expensive we have the proof is right here this one at its you know it was abbott did not lose money on this deal you know they got 750 million dollars for buy for selling 150 million of these at five bucks a piece um all of these tests can do the same so anyone who says that these should be you know unfortunately what's happening though is the fda is only authorizing all of these tests as medical devices so what happens when you if i'm a medical company if i'm if i'm a test production company and i want to make this test and i go through and and the fda at the end of my authorization the fda says okay you know you now have a medical device not a public health tool but a medical device and that affords you the ability to charge insurance companies for it why would i ever as a you know in our capitalistic uh economy and and sort of infrastructure why would i ever not sell this for thirty dollars when insurance will pay pay for it or a hundred dollars you know it might only cost me 50 cents to make but but by pushing all of these tests through a medical pathway at the fda they what what extrudes out the other side is an expensive medical device that's erroneously expensive it doesn't need to be inflated in cost but the companies say well i'd rather make fewer of them and just sell them all for thirty dollars a piece then make tens of millions of them which i could do and sell them at a dollar uh marginal uh uh profit you know and so it's a problem with our with our whole medical industry that we see tests only as medical devices and uh you know what i would like to see is for the government in the same way that they bought 150 million of these from abbott they should be buying you know all of these tests that they should be buying 20 million a day and getting them out to people's homes this virus has cost trillions of dollars to the american people it's closed down restaurants and stores and you know obviously the main streets across america have shut have shuttered it's killing people it's killing our economy it's killing lifestyles and and this is an obvious solution to me this is exciting this is like this is a solution i wish uh like in april or something like that uh to launch like the larger scale manufacturing deployment of uh tests doesn't matter what test they are it's obviously the capitalist system would create cheaper and cheaper tests that that would be hopefully driving down to one dollar so what are we talking about in america there's i don't know 300 plus a million people so that means you want to be testing regularly right so how many do you think is possible to manufacture will be the ultimate goal to manufacture per month yep so if we want to slow this virus and actually stop it from transmitting achieve what i call herd effects like vaccine herd immunity hurt effects are when you get that r value below one through preventing onward transmission if we want to do that with these tests we need about 20 million to 40 million of them every day uh which is not a lot in the united states in the united states so we could do it there's other ways you can have two people in a household uh swab each other you know swab themselves rather and then mix you know put the swabs into the same tube and onto one test so you can pool so you can get a a 2 or 3x gain inefficiency through pooling in the household you could do that in schools or offices too where everyone just uses a swab you have a there's two people like i mean even if it's just standing in line at a public testing site or something you know you could just say okay these two are the last people to test or swab themselves they go into one one thing and if it comes back positive then you just do each person and you know it's rapid so you can just say to the people one of you is positive let's test you again um so there's ways to get the efficiency gains much better but let's say i think that that the optimal number right now that matches sort of what we can produce more or less today if we wanted is 20 million a day right now one company that i don't have their test here but one company is already producing five million tests themselves and shipping them overseas it's an american company based in california called inova and they are giving 5 million tests to the uk every day not to the you know and this is just because there's no the federal government hasn't authorized these tests without the support of the the government so yeah so essentially if the government just puts some support behind it then uh then yeah you can get 20 million probably easy oh yeah this i mean just here i have three different companies these they all look similar well this one's closed but these are three different companies right here this is a fourth abbott you know this is a fifth this is a sixth these two are a little bit different do you mind if in a little bit would you take some of these or yeah let's let's do it we can we can uh we can absolutely do that so you have a lot of tests in front of you uh could you maybe explain some of them absolutely so there's a few different classes of tests that i just have here and there's more tests there's many more different tests out in the world too these are these are one class of tests these are uh rapid antigen tests that are just the most bare bones paper strip tests these uh this is the type that i want to see produced in the tens of millions every day it's so simple you know you don't even need the plastic cartridge you can just you can just make uh make the paper strip and you could have a little a little tube like this that you know you just dunk the paper strip into you don't actually need the plastic which i'd actually prefer because if we start making tens of millions of these this becomes a lot of waste so i'd rather not see this kind of waste be out there and there's a few companies quadel is making a test called the quick view which is just just this it's uh they've gotten rid of all the all the plastic and for people who are just listening to this we're looking at some very small tests that fit in the palm of your hand and they're basically paper strips fit into different containers and that's hence the comment about the plastic containers these are just injection molded i think and uh you got it they're um you know they can build them at high numbers but then they have to like place them in there appropriately and all this stuff so it is a it is a bottleneck or some somewhat of a bottleneck in manufacturing the actual bottleneck uh which the government i think should use the defense productions act to build up is the there's a nitrocellulose membrane laminated membrane on this that allows uh the the material the the the buffer and with the swab mixture to flow across it so the way these work they're called lateral flow tests and you take a swab you swab the the front of your nose you dunk that swab into some buffer and then you put a couple drops of that buffer onto the lateral flow and just like paper if you dip a piece of paper into a cup of water though the paper will pull the water up through capillary action this actually works very similarly it flows through somewhat a capillary action through this nitrocellulose membrane and there's little antibodies on there these little proteins that are very specific in this case for antigens or proteins of the virus so these are antibodies similar to how to the antibodies that our body makes from our immune system but they're just printed on these um lateral flow tests and they're printed just like a little a line so then you you slice these all up into individual ones and if there's any virus on that buffer as it flows across the antibodies grab that virus and it creates a little reaction with some colloids in here that cause it to turn dark just like a pregnancy test um one line means negative it means a control strip worked and two lines mean positive means uh you know but if you get two lines it just means you have virus there you're very very likely to have virus there and so uh so they're super simple this is it is the exact same technology as pregnancy tests it's uh the technology this particular one from abbott this has been used for other infectious diseases like malaria and and actually a number of these companies have made malaria tests that do the exact same thing so they just co-opted their the same form factor and uh and just change the antibodies so it picks up sars cof2 instead of other infections is it also the abbott one is it also strip yep yeah this abbott one here is uh there's the in this case instead of being put in a plastic sheath it's just put in a cardboard thing and literally glued on i mean it's it looks like nothing you know it's just it looks like a like i mean it's just the simplest thing you could you could imagine the exterior packaging looks very apple like this nice it does yeah yeah yeah so it's nice and it comes in this is the this is how they're packaged you know so and they don't have to you know this these are coming in individual packages against again because they're really considered individual medical devices but you could package them in you know bigger packets and stuff you you want to be careful with humidity so they all have a little um one of those humidity removing things and oxygen removing things um so that's that this is one class these antigen tests if we could just pause for a second if it's okay and uh could you just briefly say what is an antigen test and what other tests there are out there like categories of tests sure just really quick so the testing landscape is a little bit complicated but it's but i'll break it down there's really just three major classes of tests uh we'll start with the first two the the first two tests are just looking for the virus or looking for antibodies against the virus so we've heard about serology tests or maybe some people have heard about it those are a different kind of test they're looking to see has somebody in the past does somebody have an immune response against the virus which would indicate that they were infected or exposed to it so we're not talking about the antibody test so i'll just leave it at that those uh they actually can look very similar to this or they can be done in a laboratory those are usually done from blood and they're looking for an immune response to the virus so that's one everything i'm talking about here is looking for the virus itself not the immune response to the virus and so you there's two ways to look for the virus you can either look for the genetic code of the virus like the rna just like the dna of somebody's human cells or you can look for the proteins themselves the antigens of the prot of the virus so i like to differentiate them if you were a a pcr test that looks for rna in let's say let's say if we made it against humans it would be looking for the dna inside of our cells that would be actually looking for our genetic code uh the equivalent to an antigen test is sort of a a test that like actually is looking for our eyes or our nose or physical features of our body that would uh delineate okay this is this is uh michael for example in and so so you're either looking for this a sequence or you're looking for a structure uh the pcr test that a lot of people have gotten now and they're done in labs usually are looking for the sequence of the virus which is rna this test here by a company called detect this is one of jonathan rothberg's companies um he's the guy who helped create modern day sequencing and all kinds of other things so this detect device that's the name of the company this is actually a rapid rna detection device so it's almost it's like a pcr-like test and we could even do it here it's really it's it's a beautiful test in my opinion it works exceedingly well it's going to be a little bit more expensive so i think it could confirm could be used as a confirmatory test for these is there a greater accuracy to it um yes i would say that there is a greater accuracy there's also a downfall though of pcr and tests that look for rna they can sometimes detect somebody uh who is no longer infectious so you have the the rna test then you have these antigen tests the antigen tests look for structures but they're generally only going to turn positive if people have actively replicating virus in them and so what happens after an infection dissipates you have you've just gone from having sort of a spike so if you get infected maybe three days later the virus gets into exponential growth and it can replicate to trillions of viruses inside the body your immune system then kind of tackles it and beats it down to nothing but what ends up in the wake of that you just had a battle you had this massive battle that just took place inside your upper respiratory tract and because of that you've had trillions and trillions of viruses go to zero essentially but the rna is still there it's just these remnants in the same way that if you go to a crime scene and blood was was was sort of spread all over the crime scene you're going to find a lot of dna there's tons of dna there's no people anymore but there's a lot of dna there same thing happens here and so what's happening with pcr testing is when people go and use these exceedingly high sensitivity pcr tests people will stay positive for weeks or months after their infection has subsided which has caused a lot of problems in my opinion it's problems that the cdc and the fda and doctors don't want to deal with but i've tried to publish on it i've tried to you know suggest that this is an issue both to new york times and others and now it's unfortunately kind of taken on a life of its own of conspiracy theorists thinking no um they call it a case stomach they say oh you know pcr is it's detecting people who are no longer who are right false positive but they're not false positives they're they're late positives no longer transmissible i think the way you uh like what i saw on rapid tests.org i really like the distinction between diagnostic sensitivity and contagiousness sensitivity that's it's so that website is so obvious uh that it's painful because it's like yeah that's what we should be talking about is how accurately is the test able to detect your contagiousness and you have different plots that show that actually there's you know um that antigen test the tests we're looking at today like rapid tests actually really good at detecting contagiousness absolutely it all mixes back with this whole idea that of the medical industrial complex you know in this country and in most countries we have almost entirely defunded and devalued public health period you know we just we just have and uh and what that means is that we don't even we don't have a language for it we don't have a lexicon for it we don't have a regulatory landscape for it and so the only window we have to look at a test today is as a medical diagnostic test and and that becomes very problematic when we're trying to tackle a public health threat in a public health emergency by definition and this is a public health emergency that we're in and yet we keep evaluating tests as though the diagnostic benchmark is the gold standard where if i'm a physician i am a physician so i'll put on that physician hat for a moment and if i have a doc if i have a patient who comes to me and wants to uh know if their symptoms are a result of them having covid then i want every shred of evidence that i can get to see does this person currently or did they recently have this infection inside of them and so in that sense the pcr test is the perfect test it's really sensitive it will find the rna if it's there at all so that i could say you know yeah you have a low amount of rna left you might have been you said your symptoms started two weeks ago you probably were infectious two weeks ago and and you have lingering symptoms from it but that's a that's a medical diagnosis it's kind of like a detective recreating a crime scene they want to go back there and re re create the pieces so that they can um assign blame or whatever it might be but that's not public health in public health we need to only look forward we don't want to go back and say well was this person are there symptoms because they had an infection two weeks ago in public health we just want to stop the virus from spreading to the next person and so that's where we don't care if somebody was infected two weeks ago we only care about finding the people who are infectious today and unfortunately our regulatory landscape fails to apply that knowledge to evaluate these tests as public health tools they're only evaluating the tests as medical tools and therefore we get all kinds of complaints that say this test which detects 99 plus you know 99.8 percent of of current infectious people uh on by the fda's rubric they'll say no no that's it's only 50 percent sensitive and that's because when you go out into the world and you just compare this against pcr positivity most people who are pc are positive in the world right now at any given time are post infectious they're no longer infectious because you you might only be infectious for five days but then you'll remain pcr positive for three or four or five weeks and so when you go and just evaluate these tests and you say okay this person's pcr positive does the rapid antigen test detect that more often than not it's no but that's because those people don't need isolation you know they they're post infectious and this is a it's become much more of a problem than i think uh even the fda themselves is recognizing because they are unwilling at this point to to look at this as a public health problem requiring public health tools we'll definitely talk about this a little bit more because the concern i have is that like a bigger pandemic comes along what are the lessons we draw from this and how we move forward let's talk about that in a bit but sort of can we can we discuss further delay of the land here of the different tests before us absolutely so i talked about pcr tests and those are done in the lab or they're done essentially with with a rapid test like this the detect and we can even try this in a moment it goes into a little heater so you might have one of these in a household or one of these in a nursing home or something like that or in an airport or you could have one that has 100 different outlets this is just to heat the tube up these are the rapid tests they are super simple no frills you just swab your nose and uh you put the swab into a buffer and you put the buffer on the test so we can use these right now if you want yeah and we can try it out and all the tests we're talking about they're usually swabbing the nose like that's the that's still that i mean yeah there are some saliva tests coming about and they these can all work potentially with saliva they just have to be recalibrated uh but these these swabs are really not bad this isn't the the deep swab that goes like way back uh into your nose or anything this is just the uh just a swab that you do yourself like right in the front of your nose um so if you want to do it yeah do you mind if i sure yeah yeah why don't we start with this one because this is uh this is abbott's binex now test and it's really it's pretty simple this is this the swab from the abba test that's correct that's the swab from the abba test so what i'm going to do to start is i'm going to take this buffer here which is uh this is just the buffer that goes on to this test so this is a brand new one i just opened this this test out i'm going to just take six drops of this buffer and put it right onto this test here two three four five six okay and now you're going to take that swab open it up yep and now just wipe it around inside the into the front of your nose do a few circles uh on each nostril that looks good this always makes me want to sneeze yeah okay now i'm going to have you do it yourself um i'm getting emotional hold it parallel to the test so put the test down on the table yep and then go into that bottom hole yep and push forward so you can start to see it in the other hole there you go now turn if it's once it hits up against the top just turn it uh three times one two three and sort of yep and now you just close so pull off that adhesive sticker there and now you just close the whole thing and and that's it that's it now what we will see uh is we will see a line form what's happening now is the the buffer that you put in there is uh now uh moving up onto the paper strip test and it has the material from the swab in there and so what we'll see is a line will form and that's going to be the control line and then we'll also see the the ideally we'll see no line for the actual test line and that's because you should be negative so one line will be positive and two lines will be negative it's very cool there's this uh purple thing creeping up onto the control line that's perfect that's what you want to be seeing so you want to see that so right now you essentially want to see that that blue line turns pink or purpley color there's a blue line that's already there printed it should turn sort of a purple pink color and ideally there will be no additional line for the sample and if there is that's the 99 point whatever percent accuracy on that means i have i'm contagious that would mean that you're likely contagious or you likely have uh infectious virus in you what we can do because one of the things that um that my plan calls for is because sometimes these tests can get false positive results it's rare maybe one percent or in the case of this binex now this abbott test point one percent so one in a thousand one five hundred something like that can be falsely positive what i recommend is that when somebody is a positive on one of these you turn around and you immediately test on a different test you could either do it on the same but for for as good measure you want to use a separate test that is somewhat orthogonal meaning that it shouldn't turn falsely positive for the same reason this particular test here this detect test because it is looking for the rna and not the antigen this is an amazingly accurate test and it's sort of a perfect uh gold standard or confirmatory test for any of these antigen tests so one of the recommendations that i've had especially if people start using antigen tests before you get onto a plane or you know as what i call entrance screening if somebody's positive you don't immediately tell them you're positive go isolate for 10 days you tell them let's confirm on one of these on a detect test that is a because it's completely orthogonal it's looking for the rna instead of the antigen there's no reason no biological reason that both of these should be falsely positive so if one's falsely positive and the other one is negative especially because this one's more sensitive uh then i would trust this as a confirmatory test if this one's negative then the antigen test you know would be considered falsely positive it does look like there's only a single line so this is very exciting news that's right yep it says wait 15 minutes to see both lines but in general if somebody's really going to be positive that line starts showing up within a minute or two um so you want to keep the whole we'll keep watching it for the whole 15 minutes as it's sitting there but uh i would say you're knowing that you've had pcr tests recently and all that you know the odds are pretty good odds are very packaging very iphone like i'm i'm i'm digging this sexy packaging i'm a sucker for good packaging okay so then there's this there's this test here which is you know this is another you know it's funny this let me open this up and show you this is a really nice test it's another antigen test works the exact same way as this essentially but what you can see is it's got like lights in it and a power button and stuff this is called an alum test which is you know fine and it's a really nice test to be honest but it um but it has to pair with an iphone and and so it's good as i think that this is going to become this is there's a lot of use for this from a medical perspective you know where you want good reporting this can because it pairs with an iphone uh it can immediately send uh send the report to a department of health whereas these paper strip tests that they're just paper they don't report anything unless you want to report it okay so i'm going to just pick it up and pick it apart and so you can see is there's like fluorescent readers and little lasers and leds and stuff in there you can actually see the lights going off wow and there's a paper strip test right inside there but you can see that there's like a whole circuit board and and all this stuff right and so this is the kind of thing that you know the fda is looking for um for like home use and and things like that because it's kind of foolproof like you you can't go wrong with it it pairs with an iphone so you need bluetooth so it's going to be more limited it's a great test don't get me wrong it's as good as any of these but you know when you compare this thing with a battery and a circuit board and all this stuff it's got its purpose but you know it's not a public health tool i don't want to see this made in the tens of millions a day yeah and thrown away um ga likes that kind of stuff fba loves this stuff you know because they can't get it out of their mind that this is a public health crisis you know we need we need i mean just look at the difference here something like flashing lights is essential got batteries it's got a bluetooth thing it's a great test but you know it's to be honest it's not any better than this one yeah and so you know i i want this one um it's nice and all the form factor is nice but and it's really nice that it goes to bluetooth but it goes against the principle of just uh 20 million a day exactly the easy solution everybody has it you can manufacture and probably you could have probably scaled this up in a couple of weeks oh absolutely these companies i mean the rest of the world has these they can be scaled up they already exist you know sd biosensors one company's making tens of millions a day not coming to the united states but going all over europe going all over um southeast asia and east asia so they exist the us is just you know we can't get out of our own way i wonder why somebody i don't know if you were paying attention but somebody like an elon musk type character so he was really into doing some like obvious engineering solution like this uh at home rapid test seems like a very elon musk thing to do i don't know if you saw but i i had a little twitter conversation with elon musk does he not like what was he do you know what his thoughts are on rapid testing well he was using a slightly different one one of these but that requires an instrument called the bd veritar and he got a false positive or no i shouldn't say he didn't necessarily get a false positive he got discrepant results he did this test four times he got two positives two negatives um but then he got a pcr test and it was a very low positive result so i think what happened is he just tested himself at the tail end of and this was actually right before he was about to send those it was the day of essentially that he was sending the astronauts up to the space station the other day so he used uh he was using these rapid tests because he wanted to make sure that he was good to go in and um he got discrepant results ultimately they were correct but you know two or negative two are positive but what what really happened once he got his he shared his pcr results and they were very low positive so really what was happening is my guess is he found himself right at the edge of his positivity of his infectiousness and so you know the test worked out was supposed to work it probably had he used it two days earlier it would have been screaming positive you know he wouldn't have gotten discrepant results but he found himself right at the edge by the time he used the test so the pcr would always pick it up because it's still because it will still stay positive then for weeks potentially but the rapid antigen test was starting to to falter not in a bad way but just he probably was really no longer particularly infectious and so it was kind of when it gets to be a very low viral load it becomes stochastic it's fascinating there's this duality so one you can think from an individual's individual perspective it's unclear when you take four and a half are positive half a negative like what are you supposed to do but from a societal perspective it seems like if just one of them is positive just stay home for for a couple days for for a while so when you're a ceo of a company you're launching astronauts to space you may not want to rely absolutely on the antigen test as a as a thing by which you steer your decisions of like 10 000 plus people companies but us individuals just living in the world if you can if it comes up positive then you make decisions based on that and then that scales really nicely to an entire society of hundreds of millions of people and that's how you get that virus to stop spreading that's exactly right you don't have to catch every single one and and the nice thing is that these will these will catch the people who are most infectious so with the elon musk it generally that test we don't have the counter factual we don't have his results from three days earlier when he was probably most infectious uh but my guess is the fact that it was catching two out of the four even when he was down at a ct value a really really very very low viral load on the pcr test suggests that it was doing its job and you just wanna and the nice thing is because these can be produced at such scale uh getting up getting one positive doesn't immediately have to mean 10 days of isolation that's the cdc's more conservative stance to say if you're positive on any test stay home for 10 days and isolate but here people would just have more tests so the recommendation should be test daily if you turn positive test daily until you've been negative for 24 48 hours and then go back to work and the nice thing there is you know right now people just aren't testing because they don't want to take 10 days off they're not getting paid for it so they can't take 10 days off do you know what uh elon thinks about this idea of rapid testing for everybody so i i understood i need to look at that whole twitter thread so i understand his perhaps criticism of uh he had like a conspiratorial tone for my vague look at it of like what's going on here with these tests uh but what does he actually think about this very practical to me engineering solution of just deploying rapid tests to everybody it seems like that's a way to open up the economy in april well to be honest i've been trying to get in touch with him again i think take somebody like elon musk with the engineering prowess within his ranks you know to easily easily build these at the tens of millions a day he could build the machines from scratch you know a lot of the companies they buy the machines from south korea or taiwan i believe uh we don't have to like we can build these machines they're simple to build get put somebody like elon musk on it you know take some of his best engineers and say look the us needs a solution in two weeks build these machines you know figure it out he'll do it he could do it this is a guy who who is literally he has started multiple entirely new industries he has the capital to do it without the us government if he wanted to and you know what it would the return on investment uh and for him would be huge but frankly the return on investment in the country would be hundreds of billions of dollars because it means we could get society open so i know that he his first experience with these rapid tests was confusing which is um how i ended up having this twitter kind of conversation with him very briefly but i think that if if he understood sort of a little bit more and i think he does i really really love to talk to him about it because i think he could totally change the course of this pandemic in the united states single-handedly you know he loves grand things yeah i think out of all the solutions i've seen this is uh this is the obvious like engineering solution to uh at least a pandemic of this scale i i love that you say the engineering solution so this is something i've been really trying to i'm an engineer uh you know my previous history was all engineering and that's really how i think um i then went into medicine and phd world but um but but i i think that the world like one of the major catastrophes or one of the major problems is that we have physicians making the decisions about public health and a pandemic when really we need engineers this is an engineering problem and so what i've been trying to do i actually really want to you know start a whole new new field called public health engineering you know and so i've been i'm loving it eventually i want to try to bring it to mit and get mit to want to start a new department or something um that's that's a doubly awesome idea that okay i love this i love every aspect i love everything you're talking about now a lot of people believe because vaccines started being deployed currently that you know we are no longer in need of a solution we're no longer in need of slowing the spread of the virus to me as i understand it seems like this is the most important time to have something like a rapid testing solution can you kind of break that apart uh what's the role of rapid testing current in the next you know what is it three four months maybe is even more this the vaccine rollout isn't going to be as peachy as everyone is hoping you know and i hate to be the deputy downer here but um there's a lot of unknowns with this vaccine you've already mentioned one which is there's a lot of people who just don't want to get the vaccine uh you know i hope that that might change as things move forward and people see their neighbors getting it and their family getting in there and it's safe and all we don't know how effective the vaccine is going to be after two or three months we've only measured it in the first two or three months which is a massive problem which we can go into biologically because there's reasons to very good reasons to believe that the efficacy could fall way down after two or three months we don't know if it's going to stop transmission and if it doesn't stop transmission then we're not then there's you know herd immunity is much much more difficult to get because that's all based on transmission blockade and uh and frankly we don't know how easily we're going to be able to roll it out some of the vaccines need really significant cold chains have very short half-lives outside of that cold chain uh we need to organize massive uh uh numbers of people to be able to distribute these most hospitals today are saying that they're not uh equipped to hire the right people to be even administering uh enough of these vaccines and then a lot of the hospitals are frustrated because they're getting much lower smaller allocations than they were expecting so i think right now like you say right now is the best time you know besides three or four or five or six months ago right now is the best time to get these rapid tests out and we need to i mean the country has the capacity to build them we have we're shipping them overseas right now we just need to flip a switch get the fda to recognize that there's more important things than diagnostic medicine which is the effectiveness of the public health program when we're dealing with a pandemic they need to authorize these as public health tools or you know frankly the president could you know there's a lot of other ways to get these tests to not have to go through the normal fda authorization program but maybe have the nih and the cdc give a stamp of approval and if we could we could get these out tomorrow and that's where that article came from you know how we can stop the the spread of this virus by christmas we could you know now it's getting late and so uh we have to keep updating that time frame maybe putting christmas in the title wasn't i should have said how we can stop the spread of this virus in a month yeah it would be a little bit more timeless but uh but we could do it you know we really could do it and that's the most frustrating part here is that uh we're just choosing not to as a country we're choosing to bankrupt our society because some people at the fda and other places just can't seem to get their head around the fact that this is a public health problem not a bunch of medical problems is there a way to change that policy wise so this is this is a much bigger thing that you're speaking to which i i love in terms of the uh mit uh engineering approach to public health is there a way to push this is this is this a political thing like where some andrew yang type characters need to like uh start screaming about it is it uh more of an elon musk thing where people just need to build it and then on on twitter start talking crap to the politicians who are not doing it what it what what what do you what are the ideas here uh i think it's a little both uh i i think it's political on the one hand and i've certainly been talking to congress a lot talking to senators are they receptive oh yeah i mean that's the crazy thing everyone but the fda is receptive i mean it's it's astounding i mean i advise you know informally i advise the president and the president-elect's teams i talked to congress i talked to senators governors you know and then all the way down to you know mayors of towns and and things and um i help i mean months ago i held a roundtable discussion with mayor garcetti as the mayor of l.a and i brought all the uh all the companies who make these things this was in like july or august or something i brought all the companies to the table and said okay how can we get these out and unfortunately it it went nowhere because the fda won't authorize them as public health tools um the nice thing is that this is one of the nice and frustrating things this is one of the few bipartisan things that i know of and like you said it's it's a real solution yeah lockdowns aren't a solution they're they're a emergency band-aid to a catastrophe that's currently happening they're not a solution and they're definitely not a public health solution if we're taking a more holistic view of public health which includes people's well-being it includes their psychological well-being their financial well-being you know just stopping a virus if it means that all those other things get thrown under the bus is not a public health solution it's a it's a it's a myopic or or very uh tunnel visioned approach to a viral virus that's spreading uh this is a simple solution with essentially no downfall you know there is no nothing bad about this it's just giving people uh a result and it's bipartisan you know the most conservative and the most liberal people everyone just wants to know their status you know nobody wants to have to wait in line for four hours to find out their status on monday uh a week later on saturday you know it just doesn't make any sense it's a useless test at that point and everyone recognizes that so why why do you think like the mayor of la why do you think politicians are going for these um from my perspective like kind of half-assed lockdowns which is not so i have seen good evidence that like a complete lockdown can work but that's in in theory it's like communism in theory can work like theoretically speaking but it just doesn't at least in this country we don't i think it's just impossible to have complete lockdown and still politicians are going for these kind of lockdowns that everybody hates that's really destroy really hurting small businesses um like why are they going big businesses and yeah all businesses uh but like basically not just hurting yeah they're destroying small businesses right uh which is going to have potentially i mean long-lasting yeah i've been reading as i don't shut up about the the rise and fall of the third reich and you know there there's economic effects uh that uh take a decade to you know there's going to be long lasting effects that may uh may be destructive to the very fabric of this nation so why are they doing it and why are they not using the solution is there is there any intuition i mean you've said that fda has a stranglehold i guess on this whole public health problem is that is that all it is that's honestly it's pretty much all it is um the companies so the somebody like mayor garcetti or governor baker cuomo newsom any of the uh dewine i i've talked to you know i've talked to a lot of governors in this country at this point uh and and of course the federal government including including the president's own teams you know and and uh and the heads of the nih the heads of the cdc about this the problem is the tests don't exist in this country at the level that we need them to right now to make that kind of policy to make that kind of program they could but they don't and so what that means is that when mayor garcetti says okay what are my actual options today despite these sounding like a great idea he looks around and he says well they're not authorized you know they don't exist right now for at-home use and from his perspective he's not about to pick that fight with the fda and it turns out nobody is why why are people afraid of it seems like a easy structure to fight it's like well it's not a so they don't see it as a fight they think that the fda is the end-all be-all everyone thinks the fda is the end-all be-all and and so they just def everyone is deferential including the heads of all the other government agencies because that is their role but what everyone is failing to see is that the fda doesn't even have a mandate or a remit to evaluate these tests as public health tools so they're just falling in this weird gray zone where the fda is saying look we evaluate medical products that's the only thing that i meant like tim stenzel head of in vitro diagnostics at the fda he's doing what he's what his job is which is to evaluate public uh which is to evaluate medical tools unfortunately um this is where i think the cdc has really blundered they haven't made the right distinction to say look okay the fda is evaluating these for doctors to use and all that uh but you know we're the cdc and we're the public health agency of this country and we recognize that these tools uh require a different authorization pathway and a different use this is a difference to medical devices and public health and i guess fda is not designed for this public health especially in emergency situations and they they they actually explicitly say that i mean when i go and talk to tim you know he's a very reasonable guy but when i talk to him he says look we don't we just do not uh evaluate a public health tool if you're telling me this is a public health tool great go and use it and uh and so i say okay great we'll go and use it and then uh the comment is but you know does it give a result back to somebody i say well yes of course it gives a result back to somebody it's being done in their home so well then it's defined as a medical tool can't use it so it's stuck in this gray zone where we unfortunately there's this weird definition that any tool any any test that gives a result back to an individual is defined by cms centers for medica medicaid services as a medical device requiring medical authorization but then you go and ask it gets crazier because then you go and ask seema verma the head of cms you know okay can these be authorized as uh as public health tools and not fall under your definition of a medical device so then the fda doesn't have to be the ones authorizing it as a public health tool and sema verma says oh well we don't we don't have any jurisdiction over over uh point of care and uh and sort of rapid devices like this we only have jurisdiction over lab devices so it's like nobody has ownership over it which means that they just keep they stay in this purgatory of of not being approved and so this is where i think frankly it needs a president it needs a presidential order to just unlock them to say this is more important than you know having a prescription and in fact i mean really what's happening now because there is this sense that tests are public health tools even if they're not being defined as such the fda now is pretty much not only are they not authorizing these as public health tools what they're doing by by authorizing what are effectively public health tools as medical devices they're just diluting down the practice of medicine right i mean his answer right now unfortunately is well i don't know why you you want these to be sort of available to everyone without a prescription we've already said that a doctor can write a whole prescription for a for a whole college campus it's like well if you're going in that direction then that's no longer medicine having a doctor write a prescription for a college campus for everyone on the campus to have repeat testing now now we're just in the territory of of eroding medicine and eroding all of the legal rules and reasons that we have prescriptions in the first place so it's just everything about it is just destructive instead of just making a simple solute solution which is these are okay as public health tools as long as they meet x and y metrics go and cdc can put their stamp of approval on them what do you think uh sorry if i'm stuck on this yeah your mention of mit and uh public health engineering right i mean it has a sense of i talked to computational biology folks it's always exciting to see computer scientists start entering the space of biology and there's actually a lot of exciting things that happen because of that trying to understand the fundamentals of biology so from the engineering approach to public health what kind of problems do you think can be tackled what kind of disciplines are involved like do you have ideas on this uh in this space oh yeah i mean i can speak to to one of the major activities that i want to do so what i normally do in my research lab is develop technologies that uh can take a drop of somebody's blood or some saliva and profile for hundreds of thousands of different antibodies against every single pathogen that somebody could be possibly exposed to so this is all new technology that we've been developing more from a from a bioengineering perspective but then i use a lot of the mathematics uh tools to a interpret that but what i really want to do for example to kind of kick off this new field of what i consider public health engineering is to create maybe it's a little ambitious but create a a weather system for viruses i want us to be able to open up our iphones plug in our zip code and get a better sense get a probability of why my kid has a runny nose today is it coved is it a rhinovirus an adenovirus or is it flu and you know we can do that we can start building the rules of virus spread across the globe both for pandemic preparedness but also for just everyday use in the same way that people used to think that predicting the weather was going to be impossible of course we know that's not impossible now is it always perfect no but does it offer does it you know completely change the way that we go about our days absolutely you know i i envision for example right now we open up our iphone we plug in a zip code and if it tells us it's going to rain today we bring an umbrella so you know in the future it tells us hey you know there's a lot of stars cove too in your community instead of grabbing your umbrella you grab your mask you know we don't have to have masks all the time but if we know the rules of the game that these viruses play by we can start preparing for those and you know every year we go into every flu season blindfolded with our hands tied behind our back just saying i hope this isn't a bad flu season this year why don't i mean this is you know we're in the 21st century you know it's becoming you know i mean we have the tools at our disposal now to not have that attitude this isn't like 1920s you know we can we we can just say hey this is going to be a bad flu season this year let's act accordingly and with a targeted approach you know we don't uh for example we don't just use our umbrellas all day long every single day in case it might rain we don't board up our homes every single day in cases of hurricane we wait and if we know that there's one coming then we act for a a small period of time accordingly and then we go back and we've prepared ourselves in like these little bursts to not have it uh ruin our days i can't tell you how exciting that vision of the future is uh i think that's incredible and it seems like it should be within our reach the just these like weather maps of viruses floating about the earth and and it seems obvious it's one of those things where right now it seems like maybe impossible and then looking back like 20 years from now will wonder like why the hell this hasn't been done away earlier though one difference between weather maybe i don't know if you have interesting ideas in this space the difference between weather and viruses is it includes the collection of the data includes the human body potentially and that means that there is some as with the contact tracing question there's some concern about privacy yeah there seems to be this dance that's really complicated um you know with facebook getting a lot of flack for basically misusing people's data or you know just whether it's perception or reality there's certainly a lot of reality to it too where they're not good stewards of our private data so there's this weird place where it's like obvious that if we do if we collect a lot of data about human beings and maintain privacy and maintain all like basic respect for that data just like honestly common sense respect for the data that we can do a lot of amazing things for the world like a weather map for viruses is there a way forward to gain trust of people um or to do this to do this well do you have ideas here how big is this problem i think it's it's a central problem there's a couple central problems that need to be solved one how do you get all the samples that's not actually too difficult i'm actually i have a pilot project going right now with uh getting samples from across all the united states uh tens of thousands of samples every week are flowing into my lab and we process them so it's taking the so it's taking like one of the basically uh the this biology here in chemistry and converting that into numbers that's exactly right so what we're doing for example there's a lot of people who go to the hospital every day a lot of people who donate blood uh people who donate plasma so one of the projects that i have i'll get to the privacy question in a moment but this so what i want to do is the the name that i've given this is global a global immunological observatory you know there's no reason not to have that good name i've said you know instead of saying well how do we possibly get enough people on board to send in samples all the time well just go to the source you know so there's a company in massachusetts that makes 80 percent of all the instruments that are used globally to to collect plasma from plasma donors so i went to this company heminetics and said you know is there a way you have 80 percent of the global market on plasma donations uh can we start getting plasma samples from healthy people that use your machines so that hooked me up with this company called octopharma an octaform has a huge reach and saddle and offices all over the country where they're just collecting people's plasma they actually pay people for their plasma and then that gets distributed to hospitals and all this stuff is anonymous plasma so i've just been collecting anonymous samples um and we're processing them in this case for covid antibodies to watch from january up through december we're able to uh watch how the virus uh entered into the united states and how it how it's transmitting every day you know across the u.s uh so we're we're getting those results uh organized now and we're gonna start start putting them publicly on online soon to start making at least a very rough map of covid but that's the type of thinking that i have in terms of like how do you actually capture huge numbers of specimens you can't ask everyone to participate on sort of a i mean you may maybe could if you have the right tools and you can offer individuals something in return like 23andme does you know that's a great way to get people to give specimens and they get results back so with these technologies that i've been building along with some collaborators at harvard we can come up with tools that people might actually want so i can offer you your immunological history i can say give me a drop of your blood on a filter paper mail it in and i will be able to tell you every infectious disease you've ever encountered and maybe even when you encountered it roughly i could tell you do you have covet antibodies right now do you have lyme disease antibodies right now flu tripoli and all these different viruses also peanut allergies you know milk allergies anything you know if it if your immune system makes a response to it we can detect that response so all of a sudden we have this very valuable technology that on the one hand gives people maybe information they might want to know about themselves but on the other hand becomes this amazingly rich source of big data you know to enter into this global immunological observatory sort of mathematical framework to start building these maps these epidemiological tools but you asked about privacy and absolutely that's essential to keep in mind uh first and foremost so privacy can be uh you can keep these samples 100 anonymous uh they are just when i get them they show up with nothing they're literally just tubes i know a date that they were collected and a zip code that they're collected from or or or even just sort of a county level uh id uh with an irb and with ethical approval and with the people's consent we could maybe collect more data but that would require consent but then there's this other approach which i'm really excited about which is certainly going to gain some scrutiny i think but we'll have to figure out where where it comes into play but i've been recognizing that we can take somebody's immunological profile and we can make a biological fingerprint out of it and it's actually stable enough so that i could take your blood let's say i don't know who you are but um you sent me a drop of blood a year ago and then you send me a drop of blood today i don't know that those two blood spots are coming from the same person they're just showing up in my lab uh but i can run the our technology over the and it just gives me your immunological history but your immunological history is so unique to you and the way that your body responds to these pathogens is so unique to you that i can use that to tether your two samples i don't know who you are i know nothing about you i only know when those samples were came out of a person but i can say oh these two samples a year apart actually belong to the same person yeah so there's sufficient information that immunological history to to match the samples that's well for from a privacy perspective that's really exciting does that generally hold for humans so you're saying there's enough uniqueness yep to match yeah because it's very stochastic even twins so this i believe you know we haven't published this yet we will soon you have a twin too right i do have a twin i have an identical twin brother which makes me interested in this uh he looks very much like me that works [Laughter] and you know dna can't really tell us apart but this tool is one of the only tools in the world that can tell twins apart from each other could still be accurate enough to say this blood you know it's like 99.999 percent uh uh accurate to to to say that these two blood samples came from the same individual and it's because it's a combination both of your immunological history but also how your unique body uh responds to a pathogen which is random uh the way that we make antibodies is is uh by and large it's got an element of randomness to it how the cells when they make an antibody they chop up the genetic code to say okay this is the antibody that i'm going to form for this pathogen and you might form if you get a coronavirus for example you might form hundreds of different antibodies not just one antibody against the spike protein but hundreds of different antibodies against all different parts of the virus so that gives this really rich resolution of information that when i then do the same thing across hundreds of different pathogens some of which you've seen some of which you haven't um it gives you an exceedingly unique fingerprint that uh that is sufficiently stable over years and years and years to essentially give you a barcode you know and and i don't have to know who you are but i can know that these two specimens came from the same person somewhere out in the world that's so fascinating that there's this trace your life story in the space of viruses in the space of uh pathogen like like these or you know because there's this entire universe of these organisms that are trying to destroy each other and then your little trajectory through that space leaves a trace yep and then you can look at that trace that's fascinating and that i mean there's okay that data period is just fascinating and the vision of making that data universally connected to where you can make like infer things and uh and just like with the weather is really fascinating there's probably artificial intelligence applications there start making predictions start finding patterns exactly we're doing a lot of that already and and that's how had we had this going you know i've been trying to get this funded for years now and i've spoken to governments you know everyone says cool idea not going to do it you know why do we need it and of course now you know i mean i wrote in 2015 about this um why we would why this would be useful and of course now we're seeing why it would be useful had we had this up and running uh in 2019 had we had it going we were drawing blood from you know or getting blood samples from hospitals and clinics and blood donors from new york city let's just say you know that could have we didn't run the first pcr test for coronavirus until probably a month and a half or two months after the virus started transmitting in new york city so it's like with the rain we didn't start wearing umbrella or taking out umbrellas exactly for two months getting wet but different than the rain we couldn't actually see that it was spreading right now and so andrew cuomo had no choice but to leave the city open you know there were hints that maybe the virus was spreading in new york city but you know he didn't have any data to back it up no data and so it was just week on week and week and he didn't have any information to really go by to allow him to have the firepower to say we're closing down the city this is an emergency we have to stop spread before it starts uh and so they waited until the first pcr tests were coming about and then the moment they started running a pcr test they find out it's everywhere you know and so that was a disaster because of course new york city you know it was just hit so bad because nobody was you know we were blind to it we didn't have to be blind to it the nice thing about this technology is we wouldn't have with the exact same technology we had in 2017 we could have detected this novel coronavirus spreading in new york city in 2020 not because we changed not because we are actually actively looking for this novel coronavirus but because we would see we would have seen patterns in people's immune responses using ai or just frankly using our just the raw data itself we could have said hey it looks like there's something that looks like known coronavirus is spreading in new york but there's gaps you know there's for some reason people aren't developing an immune response to this coronavirus that seems to be spreading to these normal things that you know and it just looks the profile looks different and we could have seen that and immediately especially since we had an idea that there was a novel coronavirus circulating in the world we could have very quickly and easily seen hey clearly we're seeing a spike of something that looks like a known coronavirus but people are responding weirdly to it our ai algorithms would have picked it up and just our basic heck you could put you could have put it in an excel spreadsheet we would have seen it yeah so some basic visualization would have shown exactly we would have seen spikes and they would have been kind of like off you know immune responses that the shape of them just looked a little bit different but they would have been growing and we would have seen it and it could have saved tens of thousands of lives in new york city so to me the fascinating question everything we've talked about so both the huge collection of data at scale just super exciting and then the kind of obvious at scale solution to the current virus and future ones is the rapid testing can we talk about the future of viruses that might be threatening the uh our very existence sure so do you think like a future natural virus can um have an order of magnitude greater effect on human civilization than anything we've ever seen so something that either kills all humans or kills i don't know 60 70 percent of humans so some like something something um we can't even imagine is that is that something that you think is possible because it seems to have not have happened yet so maybe like the entirety whoever whoever the programmer is of the simulation that sort of launched the evolution for the big bang seems to not want to destroy us humans or maybe that's the natural side effect of the evolutionary process that uh humans are useful but do you think it's possible that the evolutionary process will produce a virus that will kill all humans i think it could i don't think it's likely and the reason i don't think it's likely is um well on the one hand it hasn't happened yet uh in part because mobility is is uh is a recent phenomena people weren't particularly mobile uh until uh fairly recently uh now of course now that we have people flying back and forth across the globe all the time the chances of global pandemics has escalated exponentially of course and so on the one hand that's part of why it hasn't happened yet we can look at things like ebola you know ebola we don't we haven't generally had major uh ebola epidemics in the past not because ebola wasn't transmitting and infecting humans but because they were it was largely affecting and infecting humans in disconnected communities so you see out in uh in rural parts of africa for example uh in western africa you might end up having isolated ebola outbreaks but there weren't connections that were fast enough that would allow people to then spread it into the cities of course we saw back in 2014-15 a massive ebola outbreak that wasn't because it was a new strain of ebola but it was because there's uh new inroads and connections between the communities and people got it to the city and so we saw it start to spread so that should be a little bit for you know foreshadowing of what's to come and now we have this pandemic we had 2009 we have this uh there is a benefit um or there is sort of a natural check and this is a kind of latka voltaire predator prey dynamic kind of systems ecological systems and mathematics that uh if you have something that's so deadly people will respond uh more maybe with a greater panic a greater sense of panic which alone could you know destroy humanity but at the same time like we now know that we can lock down we know that that's possible and so if this was a worse virus that was actually killing 60 of people as infecting we would lock down very quickly my biggest fear though is let's say that was happening you need serious lockdowns if you're going to keep things going so the only reason we were able to keep things going during our lockdowns is because it wasn't so bad that we were still able to have people work in the in the in the grocery stores still people working the shipping to get the food onto the shelves so on the one hand we could probably figure how to stop the virus but can we stop the virus without starving you know and i'm not sure that that if this was uh another acute respiratory virus that say had a slightly say it transmitted the same way but say it actually did worst damage to your heart but it was like a month later that people start having heart attacks uh in mass you know it's like not not just one-offs but but really severe well that could be a serious problem for humanity um so so in some ways i think that there are lots of ways that we could end up dying at the hand of a virus i mean we're already seeing it just i mean my fear is still i think coronaviruses have demonstrated a keen ability to destroy uh or to to create outbreaks that can potentially be deadly to large numbers of people flu strains though are still by and large my concern so you think the bad one might come from the the flu the influenza yeah they the the replication cycle they're able to genetically recombine in a way that coronal viruses aren't they have segmented genomes which means that they can just swap out whole parts of their genomes no problem repackage them and and then boom you have a whole antigenic shift not a drift what that means is that any on any occasion any day of the year you can have boom a new whole new virus that didn't exist yesterday and now with uh farming and and industrial livestock uh we're seeing animals and humans come into contact much more just the the uh the opportunities for an influenza strain that is unique and deadly to humans uh increases all the while tren transmission and mobility has increased it's just a matter of time in my opinion what about from immunology perspective of the idea of engineering a virus so not just the virus leaking from a lab or something but actually being able to understand the protein like the everything about what makes a virus enough to be able to figure out ways to uh um maybe targeted or untargeted attack by a first community yeah yeah is there is that something uh obviously that's somewhere on the list of concerns but is that anywhere close uh of the like the top 10 highlights along with nuclear weapons and so on that we should be worried about or is the natural pandemic the really the one that's much greater concern i would say that the former that man-made viruses and genetically engineered viruses should be right up there with the greatest concerns for humanity right now uh you know we know that the tools for better or worse the tools for creating a virus are there you know yeah we can do it um i mean heck you know the human the human species is no longer vaccinated against smallpox i didn't get a smallpox vaccine you didn't get a smallpox vaccine at least i don't think and uh you know so if somebody wanted to make smallpox and and uh distribute it to the world in some way uh it could be exceedingly deadly and uh and and detrimental to humans and that's not even um that's not even sort of using your imagination to create a new virus that's one that we already have unlike the past when smallpox would circulate you had large fractions of the community that was already immune to it and so it wouldn't spread or it would spread a little bit slower but now we have essentially in a few years we'll have a whole global population that is susceptible let's look at measles we have an entire i mean measles um i have uh you know there are some researchers in the world right now which for various reasons are working on creating a measles strain that evades immunity it's not for bioterrorism at least that's not the expectation it's for using measles as an oncolytic virus to kill cancer and the only way you can really do that is if your immune system doesn't you know if you if you take a measles virus and there's you know we don't have to go into the details of why it would work but it could work measles likes to target um potentially cancer cells but to get your immune system not to kill off the virus if you're trying to use the virus to target it you maybe want to make it blind to the immune system but now imagine we took some virus like measles which has an r out of 18 transmits extremely quickly and now we have essentially let's say we had a whole human race that is susceptible to measles and this is a virus that spreads orders of magnitude easier than this current virus uh imagine if you were to plug something toxic or detrimental into that virus and release it to the world so it's possible to be both accidental and intentional absolutely yeah an accident so mark lipstick is a good colleague of mine at harvard uh we're both in the he's the director of the center for communicable disease dynamics where i'm a faculty member um he's spoken very very forcefully and and uh and he's very outspoken about the dangers of gain of function testing where in the lab we are intentionally creating viruses that are exceedingly deadly uh under the auspices of trying to learn about them so that if the idea is that if we kind of accelerate evolution and make these really deadly viruses in the lab we can be prepared for if that virus ever comes about naturally or through unnatural means the concern though is okay that that's one thing but what if that virus got out on somebody's shoe just what if you know if the if the uh dead if the effects of an accident are potential potentially catastrophic is it worth taking the chances just to be prepared a little bit for something that may or may not ever actually develop and so uh it's a serious ethical quandary we're in how to both be prepared but also not uh cause a catastrophic mistake as a small tangent there's a recent really exciting breakthrough of alpha 2 of alpha fold 2 solving protein folding or achieving state-of-the-art performance on protein folding and then i thought proteins have a lot to do with viruses it seems like being able to use machine learning to design proteins that achieve certain kinds of functions will naturally allow you to use maybe down the line not yet but allow you to use machine learning to design basically viruses maybe like measles like for good which is like to attack cancer cells but also for bad is that is that uh is that a is that a crazy thought or is this a natural place where this technology may go i suppose as all technologies can which is for good and for bad do you think about the role of machine learning in this oh yeah absolutely i mean alpha fold uh is amazing you know it's an amazing algorithm a series of algorithms and it does demonstrate to me it demonstrates just just how powerful you know everything in the world has rules we just don't know the rules you know we often don't know them but you know our brain has rules how it works everything is plus and minus there's nothing in the world that's really not at its most basic level positive negative you know it's all obviously it's all just charge and and that means everything you can figure it out with enough computational power and enough in this case i mean machine learning and ai is just one way to learn rules uh it's an empirical way to learn rules and it's but it's a profoundly powerful way and certainly now now that we are getting to a point where we can take a protein and know how it folds uh given its sequence we can reverse engineer then we can say okay we want a protein to fold this way what does the sequence need to be we haven't done that yet so much but it's just the next iteration of all of this so let's say somebody wants to develop a virus it's going to start with somebody wanting to develop a virus to to defeat cancer something good you know and so it would start with a lot of money from the federal government you know for all the positives that will come out of it but we have to be really careful because that will come about there's no doubt in my mind that we will develop we're already doing it we engineer molecules all the time for specific uses oftentimes we take them from nature and then tweak them but now we can supercharge it we can accelerate that the pace of discovery to not have it just be discovery we have it be true ground-up engineering let's say you're trying to make a new molecule to stabilize somebody with some retinal disease right so we come up with some molecule that can improve the stability of somebody with retinal degeneration uh you know just a small tweak to that to say make a virus that causes the human race to become blind you know i mean it sounds really conspiracy theoryish but uh but it's not you know it's we're learning so much about biology and there's always nefarious reasons i mean heck look at how ai and you know just google searches those can be um you know they are every single day being leveraged by nefarious actors to take advantage of people to steal money to do whatever it might be eventually probably to create wars or already to create wars and i mean i don't think there's any question at this point behind disinformation campaigns and so it's being leveraged this thing that could be wholly good you know it's always going to be leveraged for bad and so how do you balance that as a species i'm not quite sure well the hope is as you mentioned previously that there's some that we're able to also develop defense mechanisms and there's something about the human species that seems to keep coming up with like ways to just just like on the deadline just at the last moment of figuring out how to avoid destruction i think i'm like eternally optimistic about the human race not destroying ourselves but you could do a lot of things that would be very painful yes well we're doing it already you know just i mean we are seeing how our regulation today right we did this thing it started as a good thing regulation of medical products but now it is uh you know unwillingly and unintentionally harming us our regulatory landscape which was developed wholly for good in our country is getting in the way of us deploying a tool that could stop uh our economies from having to be sort of sputteringly closed that could stop deaths from happening at the rate that they are and it's um you know i think we will come to a solution of course now we're going to get the vaccine and it's going to make people lose track of like why we even bother testing which is a bad idea but um but we're already seeing that we have this amazing capacity to um to both do damage when we don't intend to do damage uh and and then also to pull up when we need to pull up and you know stop complete catastrophe and so uh it's we are an interesting species in that way that's for sure so there's a lot of young folks undergrads grads uh they're also young uh listen to this so is there you've talked about a lot of fascinating stuff that's like there's ways that things are done and there's actual solutions and they're not always like intersecting do you have advice for undergraduate students or graduate students or even people in high school now about a life about career of how they might be able to solve real big problems in the world how they should live their life in order to have a chance to solve big problems in the world it's hard i i struggle a little bit sometimes to give advice because the advice that i give from my own personal experience is necessarily distinct from the advice that would make other people successful i have um unending ambitions to make things better i suppose and i don't see i don't see barricades where other people sometimes see barricades um now even just little things like uh when this virus started i'm a medical director at brigham a women's hospital and so i oversee or helped to oversee molecular virology diagnostics so when this virus started wearing my epidemiology hat and wearing my sort of viral outbreak hat i recognized that this was going to be a big virus that was important at a global level even if the cdc and who weren't ready to admit that it was a pandemic it was obvious in january that it was a pandemic so i started trying to get a test built at the brigham which is one of harvard's teaching hospitals i you know the the first uh encounters i had with the upper administration of the hospital were pretty much no why would we do that that's silly who are you you know and i said well okay don't believe me sure um but i kept pushing on it uh and then uh eventually i got them to agree it was really um only a couple of weeks before the biogen conference happened we started building the test i think they started looking abroad and saying okay this is happening sure like maybe he was right but then i went a step further and i said um we're not going to have enough tests at the hospital and so uh so my ambition was to get a better testing program started and um and so i figured what better place to scale up testing than the broad institute broad institutes is amazing you know very high throughput high efficiency research institute that does a lot of genomic sequencing things like that so i went to the broad and i said hey you know there's this coronavirus that's obviously going to impact our society greatly can we start modifying your high efficiency instruments and robots for coronavirus testing everyone in my in my uh orbit in the hospital world just said that's ridiculous you know how could you possibly plan to do that it's impossible you know and and to me it was like the most dead simple thing to do right it didn't it but the the higher ups and the people who think about you know the i think one of the most important things is to recognize that most people in the world don't see solutions they just see problems and it's because it's an easy thing to do thinking of problems and how things will go wrong is really easy because you're not coming up with a brand new solution and this to me was just a super simple solution hey let's get the broad to help build tests every single hospital director you know told me no like it's impossible my own superiors the ones i report to in the hospital said you know mike you know you're a new faculty member your ideas you know probably will would be right but you're too naive and young to to know that it's impossible right you know obviously now the broad is the highest uh throughput laboratory in the country and yes you know and so i think my recommendation to people is as much as possible get out of the mode of thinking about things as problems sometimes you piss people off i could probably use a better filter sometimes to try to like be not so upfront with certain things but but it's just so crucial to always just see to just bring like think think about things in new ways that that other people haven't because usually there's something else out there and and one of the things that has been most beneficial to me which is that my my education was really broad it was engineering and physics and uh well and then i became a buddhist monk for a while and so that gave me a different perspective but then it was medicine and immunology and and now i've brought all of it together from a mathematics and biology and medicine perspective and policy and public health and i think that you know i'm not the best in any one of these things i i recognize that there are going to be geniuses out there who are just worlds better than me at any one of these things that i try to work on but my superpower is bringing them all together you know and just thinking and that's i think how you can really change the world um you know i don't know that i'll ever change the world in the way that i hope um but that's how you can have a chance yeah that's how you can have a chance exactly and um and i think it's also what uh you know this to me this rapid testing program like this is the most dead simple solution in the world and this literally could change the world it could change the world it could change and it is you know there's countries that are doing it now the us isn't but i've been advising many countries on it and and i would say that you know some of the early papers that we put out earlier on a lot of the things actually are changing you don't always unless you really look hard you don't know where you're actually having an effect um sometimes it's more overt than than other times in april i published a paper that was saying hey with the pcr values from these tests we need to really focus on the ct values the actual quantitative values of these lab-based pcr tests at the time that all the physicians and laboratory directors told me that was stupid you know why would you do that they're not accurate enough and and of course now it's headline news that you know florida they just mandated reporting out the ct values of these tests because there's a real utility of them you can understand public health from it you can understand better clinical management uh you know that was a simple solution to a pretty difficult problem uh and it is changing the way that we approach all of the lab testing in this country is starting to it's taken a few months but it's starting to change because of that and you know that was just me saying hey this is something we should be focusing on got some other people involved and other people and and now people recognize hey there's actual value in this number that comes out of these lab-based pcr tests so sometimes it does grow fairly quickly um but i think the real answer if my only my only answer i don't know what you know i recognize that everyone some people are going to be really focused on and have one small but deep skill set i go the opposite direction i try to bring bring things together and um but the biggest thing i think is just don't see problem don't don't see barriers like just see like there's always a solution to a barrier if there's a barrier that literally means a solution to it that's why it's called a barrier and just like you said most people will just present to you only be thinking about it and present to you with barriers and so it's easy to start thinking that's all there is in this world yeah and just think big i mean god you know there's nothing wrong with thinking big elon musk thought big and you know and then thinking big builds on itself you know you you get a billion dollars from one big idea and then that allows you to make three new big ideas and there's a hunger for it if you think big and you communicate that vision with the world all the most brilliant and like passionate people will just like you'll attract them and they'll come to you and then it makes your life actually really exciting the people i've met at like tesla and uh neurolink i mean there's just like this fire in their eyes they just love life and uh it's amazing i think to to be around those people i have to ask you about what was the philosophy the journey that took you to becoming a buddhist monk and what uh what were what did you learn about life what did you take away from that experience how did you return back to harvard and the world that's unlike that experience i imagine yeah well i was at dartmouth at the time um uh well i went to sri lanka i was already pretty interested in developing countries and sort of under-resourced areas and uh i was doing a lot of engineering work and i went there but i was also starting to think maybe health was something of interest and so i went to sri lanka because i had a long interest in buddhism as well just kind of interested in it as a thing which aspect of the philosophy attracted you i would say that the thing that interested me most was um was really this idea of kind of a butterfly effect of like uh you know what you do now has ripple effects that extend out beyond what you can possibly imagine both in your own life and in other people's lives and in some ways buddhism has none in some ways in a pretty deep way buddhism has that as part of its underlying uh philosophy in terms of rebirth and sort of that your actions today propagate uh to others but also propagate to to sort of uh what might happen in in your circle of what's called samsara and rebirth and um i don't i don't know that i subscribe fully to this idea that uh we are reborn uh which always was a little bit of a of a debate internally i suppose when i was a monk um but it but it has always been it was that and then it was also meditation um at the time i was a fairly elite rower i was you know rowing at the national level and um and rowing to me was very meditative it was um you know just there's even if you're on a boat with other people it's i mean on the one hand it's like the extreme of like a team sport but it's also the extreme sort of focus and concentration that requires um that's required of it and so i was always really into just meditative type of things i was doing a lot of pottery too which was also very meditative and and so buddhism just kind of really really there are a lot of things about meditating that just appealed and so i moved to sri lanka planning to only be there for a couple of months but then i was shadowing in this medical clinic and there was this physician who was just really i mean it's just kind of a horrible situation um frankly this guy was trained decades earlier he was an older physician and he was still just practicing like these fairly barbaric approaches to medicine because he had he was a rural town and he just didn't have a lot of um he didn't have any updated training frankly and so you know i just remember this like girl came in with like shrapnel in her hand and his solution was to like air it out and so he was like without even numbing her hand he was uh uh like cutting it open more with this idea that like the more oxygen and and stuff you know and it just i think there was something about all of this and i was already talking to these monks at the time each i would be in this clinic in the morning and i'd go and uh my idea was to teach english to these monks in the evening uh turned out i'm a really bad english teacher so they just taught they they allowed me just to sit with them and and meditate and they were teaching me more about buddhism than i could have possibly taught them about english or being an american or something um and uh and and so i just slowly i just couldn't take i like couldn't handle being in that clinic so more and more i just started moving to you know spending more and more time at this monastery and then after about two months i was supposed to come back to the states and i decided i didn't want to so i moved to this monastery in the mountains um primarily because i didn't have the money to like just keep living so living in a monastery is free yeah and so i moved there and just started meditating more and more and then months went by and and i it just really gravitated i i gravitated to the whole to the whole notion of it i mean it became it sounds strange but you know meditating almost just like anything that you've put your mind to became exciting you know it became like there weren't enough hours in the day to meditate and i would do it for you know 18 hours a day 15 hours a day uh just sit there and you and like i mean i hate sleeping anyway um but i wouldn't want to go to sleep because i felt like i didn't accomplish what i needed to accomplish in meditation that day which is so strange because there is no end you know but it was always but there are these uh there are these steps that happen during meditation that are very prescribed in a way buddha talked about them you know and these are ancient writings which exist i mean the writings are real they're thousands of years old now and um you know so whether it was buddha writing them or whoever you know there are lots of different people have contributed to the to these writings over the years and um but they're very prescribed and they um they tell you what you're going to go through and i didn't really focus too much on them uh i read a little bit about them but your mind really does when you actually start meditating at that level like not an hour here and there but like truly just spending your days meditating it becomes kind of like this other world where it becomes exciting and uh and you're actively working you're actively meditating not just kind of trying to quiet things that's sort of just the first stage of trying to get your mind to focus most people never get past that first stage especially in our culture could you briefly summarize what's waiting beyond the stage of just quieting the mind is yeah it's hard for me to imagine that there's something that can be described as exciting on there yeah it's it's an interesting question so i would say um so the first thing the first step is truly just to like be able to close your eyes focus on your breath and not have other thoughts enter into your mind that alone is just so hard to do like i couldn't do it now if i wanted um but i could then and um but once you get past that stage you start entering into like all these other you go through kind of i went through this like pretty trippy stage which is a little bit euphoric um where you just kind of start not hallucinating i mean it wasn't like some crazy thing that would happen in a movie where but definitely just weird you start getting to the stage where um uh you you're able to quiet your mind for so long for hours at a time that um like for me i started uh getting really excited about this idea of mindfulness which is part of um it's part of buddhism in general but it's part of tehran and buddhism in particular for this in this way which was um uh you take uh you start focusing on your daily activities whether that's sipping a cup of tea or walking or you know sweeping around uh i lived in on this mountainside and this cottage thing is built into the rock and um you know so every morning i would wake up early and sweep around it and stuff because that's just what we did um and you start to you meditate on all those activities and one of the things that was so exciting which sounds completely ridiculous now was just um almost learning about your daily activities in ways that you never would have thought about before so what is entire what what's what's involved with like picking up this glass of water you know if i said okay i'm just going to pick i'm going to take a drink of water to me right now it's a single activity right you just but um during a during meditation it's not a single activity it's a whole series of activities of like little engineering feats um and feelings and it's it's gripping the water and it's feeling that the glass is cold and it's lifting and it's moving and dragging and dragging and and you start to learn a whole new language of life and that to me was like this really exhilarating thing that um it was an exhilarating component of meditation that there was never enough time it's kind of like learning a new computer language like it gets really exciting when you start coding and all these new things you can do you you learn how to much to experience life in a much richer way and so you never run out of ways to go deeper and deeper and deeper in the way you experience even just the the drinking of the glass of water that's that's exactly right and what becomes kind of exhilarating is um you start to be able to predict things that you never or i don't even know if prediction's right word but i always think of the matrix you know or where um i forget who it was somebody was shooting at neo and he like leans backwards and he dodges the bullets um you know in some ways when you start breaking every little action that your hands do or that your feet do or your body does down into all these little actions that make up one what we normally think of as an action all of a sudden you can start to see things almost in slow motion i like to think of it very much like a language the first time somebody hears a foreign language uh it sounds really fast usually you don't hear the spaces between words and um and it just sounds like just like a stream of consciousness it just sounds like a stream of noises if you've never heard the language before and as you learn the language you hear clear breaks between words and it starts to gain context and and all of a sudden like that what once sounded very fast slows down and it has meaning that's our whole life there's this whole language happening that we don't speak generally but if you start to speak it and if you start to learn it and you start to say hey i'm picking up this glass is actually 18 little movements then all of a sudden like it becomes extremely exciting and exhilarating to just just breathe you know breathing alone in the rise and fall of your abdomen or the way the air pushes in and out of your nose becomes almost interesting and what's really neat is is the world just starts slowing down and um i'll never forget that feeling and it's the if there was one euphoric feeling from meditation i want to gain back but i don't think i could without really meditating like that again and i don't think i will um was this like slow motion of the world it was finding the spaces between all the movements the same way that the spaces between all the words happen and then it almost gives you this new appreciation for everything you know it's like it was really amazing and so i think um uh it came to an abrupt end though when the tsunami hit i was there in the indian ocean tsunami hit in 2004 and it was like this dichotomy of being a monk and and you know just meditating in this extraordinary place um and then the tsunami hits and kills 40 000 people in a few minutes on the coast of this really small little country in sri lanka and um you know then i i it like my whole world of being a monk came crashing down uh when i go to the coast and i i mean that was just a devastating visual sight an emotional sight but the strangest thing happened which was that everyone just wanted me to stay as a monk you know people in that culture they wanted to the monks largely fled from the coastlines of those you know and um and so then there i was and people wanted me to be a monk they wanted me to stay on the coast but be a monk and not help like not help in the in the way that i considered helping uh they wanted me just to keep meditating so they could bring me donna like like offerings and get and have their sort of karmic responsibilities um uh attended to as well and so uh that was really bizarre to me it was like how could i possibly just sit around while all these people half of everyone's family just died and so in any case i stopped being a monk and i moved to this refugee camp and lived there for another six months or so and just stayed there not as a monk but tried to raise some money from the us and tried to like i didn't know what i was doing frankly i was 22 and uh and i don't think i appreciated at the time how much of a role i was having in the in that community's life but but it's taken me a long many years to process all of this since then but uh i would say it's what put me into the public health world see living in that refugee camp and that difference that happened you know from being a monk to being in this devastating environment just really changed my whole view of what sort of why i was existing i suppose well so there's this richness of life in a in a single drink of water that you experience and then there's this power of nature that's it capable to take lives of thousands of people so given all that the absurdity of that let me ask you and the fact that you study things that could kill the entirety of human civilization what do you think is the meaning of this all what do you think is the meaning of life this whole orchestra we got going on does it have a meaning and maybe from another perspective as how does one live a meaningful life if such is possible well you know from what i've seen uh i don't think there's a single answer to that by any stretch one of the most interesting things about buddhism to me is that the human existence is part of suffering which is very different from judeo-christian existence which is that human existence is something to be is a very different you know it's something to it's a there's a richness to it in buddhism it's just another one of your lives and it but it's your opportunity to attain nirvana and uh become a monk for example and meditate to attain nirvana uh else you kind of just go back into this i'm sorry the cycle of of suffering and so you know when i look at i mean in some ways the notion of life and what the purpose of life is you know they're kind of completely distinct this sort of western view of life which is that this life is the most precious thing in the world versus this is just another opportunity to try to get out of life i mean the whole notion of nirvana and in buddhism it getting out of this sort of cycle of suffering is to vanish you know what if you could if you could attain nirvana you know throughout this life the idea is that you don't get reborn and so when i look at these two you know on the one hand you have christian you know christian faith and other things that want to go to heaven and like live forever in heaven then you have this other whole half of humans who uh want nothing more than to get out of the cycle of rebirth and just poof you know not exist anymore the cycle of suffering yeah and so how do you reconcile those two and i guess do you have both of them in you do you basically oscillate back and forth i don't think i i think i just i look at us in a i think we're just a bunch of proteins um that you know we form and we they work in this really amazing way and they might work in a bigger scale like there might be some connections that we're not really clear about but they're still biological i believe that they're biological how do these proteins become conscious and why do they want to help civilization by having at home rapid tests at scale well i think um i i don't have an answer to that one but i i really do believe i would it's just you know this is just an evolution of uh consciousness i don't i don't personally think is my feeling is that we're a bunch of pluses and minuses that have just gotten so complex that they're able to make rich feelings rich emotions and and i do believe though you know on the one hand i sometimes wake up some days um my fiancee doesn't always love it but you know i kind of think we're all just a bunch of robots with like pretty complicated algorithms that we deal with yeah um and you know in that sense like okay if the world just blew up tomorrow and no nothing was liv you know nothing existed the day after that it's just another blip in the universe you know but at the same time i don't know so that's kind of probably my most core basic feeling about life is like we're just a blip and we may as well make the most of it while we're here blipping [Laughter] but it's one hell of a fun blip though it is it's it's an it's an amazing uh uh you know blink of a of a of an eye in time michael this is you're one of the most interesting people i've met one of the most interesting conversations important ones now i'm going to publish it very soon i really appreciate taking the time i know how busy you are it was really fun thanks for talking today well thanks so much this was a lot of fun thanks for listening to this conversation with michael minna and thank you to our sponsors brave a fast browser that feels like chrome but has more privacy preserving features athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases expressvpn the vpn i've used for many years to protect my privacy on the internet and cash app the app i use to send money to friends please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars on upper podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from teddy roosevelt it is not the critic who counts not the man who points out how the strong man stumbles or where the doer of deeds could have done them better the credit belongs to the man who actually is in the arena whose face is marred by dust and sweat and blood who strives valiantly who errors who come short again and again because there is no effort without error and shortcoming but who does actually strive to do the deeds who knows great enthusiasms the great devotions who spends himself in a worthy cause who at the best knows in the end the triumph of high achievement and who at the worst if he fails at least fails while daring greatly so that his place shall never be with those cold and timid souls who neither know victory nor defeat thank you for listening and hope to see you next time |
Matthew Johnson: Psychedelics | Lex Fridman Podcast #145 | the following is a conversation with matthew johnson a professor of psychiatry and behavioral science at john hopkins and is one of the top scientists in the world conducting seminal research on psychedelics this was one of the most eye-opening and fascinating conversations i've ever had on this podcast i'm sure i'll talk with matt many more times quick mention of his sponsor followed by some thoughts related to the episode thank you to a new sponsor brave a fast browser that feels like chrome but has more privacy preserving features neuro the maker of functional sugar free gum and mints that i use to give my brain a quick caffeine boost for sigmatic the maker of delicious mushroom coffee i'm just not realizing how ironic the set of sponsors are and cash app the app i use to send money to friends please check out the sponsors in the description to get a discount and support this podcast as a side note let me say that psychedelics is an area of study that is fascinating to me in that it gives hints that much of the magic of our experience arises from just a few chemical interactions in the brain and that the nature of that experience can be expanded through the tools of biology chemistry physics neuroscience and artificial intelligence the fact that a world-class scientist and researcher like matt can apply a rigor to our study of this mysterious and fascinating topic is exciting to me beyond words as is the case with any of my colleagues who dare to venture out into the darkness of all that is unknown about the human mind with both an openness of first principle thinking and the rigor of the scientific method if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter lex friedman and now here's my conversation with matthew johnson can you give an introduction to psychedelics like a whirlwind overview maybe what are psychedelics and what are the kinds of psychedelics out there and in whatever way you find meaningful to categorize yeah you can categorize them by their chemical structure so phenethylamines tryptamines ergolines um that is is less of a meaningful way to classify them i think that they're pharmacological activity their receptor activity is the best way well let me let me start even broader than that because there i'm talking about the classic psychedelics so broadly speaking when we say psychedelic that refers to for most people a broad number of compounds that work in different pharmacological ways so it includes the so-called classic psychedelics that includes psilocybin and salosine which are in mushrooms lsd dimethyltryptamine or dmt it's in ayahuasca people can smoke it too mescaline which is in peyote and san pedro cactus um and those all work by hitting a certain uh subtype of serotonin receptor the serotonin 2a receptor it's they act as agonists at that receptor other compounds like pcp ketamine mdma ibogaine they all are more broadly speaking called psychedelics but they work by very different ways pharmacologically and they have some different effects including some subjective effects even though there's enough of an overlap in the subjective effects that you know people informally refer to them as psychedelic and i think what that overlap is you know compared to say you know caffeine and cocaine and you know ambien etc um other psychoactive drugs is that they have strong effects in altering one's sense of reality and including the sense of self and i should throw in there that that cannabis more historically like in the 70s has been called a minor psychedelic and i think with that latter definition it it does fit that definition particularly if one doesn't have a tolerance so you mentioned serotonin so most of the effect comes from something around like the the chemistry around neurotransmitters and so on so it's uh chemical interactions in in the brain or is there other kinds of interactions that have this kind of perception and self-awareness altering effects well as far as we know all of the the psychedelics of all the different classes we've we've talked about their major activity is caused by receptor level events so either acting at the post receptor side of the synapse in other words neurotransmission operates by you know one neuron releasing neurotransmitter into a synapse a gap between the two neurons and then the other neuron receives they have it has receptors that receives and then there can be an act activation um you know caused by that so it's like a pitcher and a catcher so all of the major psychedelics work by either acting as a pitcher mimicking a a a a a pitcher or a catcher so for example the classic psychedelics they fit into the same catcher's mitt on the post receptor uh post-synaptic receptor side as serotonin itself but they do a slightly different thing to the to the cell to the neuron than serotonin does um there's a different signaling pathway after that initial activation something like mdma works at the presynaptic side the pitcher side and basically it floods the synapse or the gap between the cells with a bunch of serotonin the natural um neurotransmitter so it's like the the pitcher in a baseball game all of a sudden just starts throwing balls like every every second everything we're talking about is it uh often more natural meaning found in the natural world you mentioned cacti cactus or is it uh chemically manufactured like artificially in the lab so the classic psychedelics there's um what are the classics so yeah using terminology that's not chemical terminology not like the terminology you've seen titles of papers academic papers but more sort of common parlance right it would be good to kind of define their you know their effects like how they're different and so it includes lsd psilocybin which is in mushrooms masculine dmt which one is masculine mescaline is in the different cacti so the one most people will know is is peyote but it also shows up in san pedro or peruvian torch and all of these classic psychedelics they have at the right dose you know and typically they have ex very strong effects on one sense of reality and one sense of self what some of the things that makes them different than other more broadly speaking psychedelics like mdma and and others is that they're um at least the the major examples there are some exotic ones that differ but the ones i've talked about are extremely safe at the physiological level like there's like lsd and psilocybin there's no known lethal overdose unless you have like really severe you know um heart disease you know because it modestly raises your blood pressure so right same person might be hurt shoveling snow or going up the stairs you know that could have a car they could have have a cardiac event because they've taken a um one of these drugs but for most people you know someone could take a thousand times what the effective dose is and it's not gonna cause any organ damage affect the brain stem make them stop breathing so in that sense you know it's they're freakishly safe at the physiology i would never call any compound safe because there's always a risk they're freakishly safe at the physiological level i mean you can hardly find anything over the counter like that i mean aspirin's not like that caffeine is not like that most drugs you take five ten twenty maybe takes a hundred but you get to some times the affected dose and it's gonna kill you yeah or cause some serious damage and so that's that's something that's remarkable about these most of these classic psychedelics that's incredible by the way that you can go on a hell of a journey in the mind like probably transformative potentially in a like deeply transformative way and yet there's no dose that in most people would have a lethal effect that's kind of fascinating there's this duality between the mind and the body it's like uh it's the okay sorry if i bring him up way too much but david goggins it's like uh you know the kind of things you go on on the long run like the hell you might go through in your mind your mind can take a lot and you can go through a lot with the mind and the body will just be its own thing you can go through hell but uh after a good night's sleep be back to normal and the body is always there so bringing it back to goggins it's like you can do that without even destroying your knee or whatever coming close and riding that line that's true so the unfortunate thing about the running which he uses running to test the mind so the the aspect of running that is negative in order to test the mind you really have to uh push the body like take the body through a journey i wish there was another way of uh doing that in the physical exercise space i think there are exercises that are easier on the body than others but running sure is a hell of an effective way to do it and one of the ways that where it differs is that you're unlike exercise you're essentially you know most exercise to really get to those intense levels you really need to be persistent about it right i mean it'll be intense if you're really out of shape just you know jogging for five minutes but to really get to those intense levels you need to you know have the dedication and so some of the other ways of of altering um subjective effects or states of consciousness take that type of dedication psychedelics though i mean someone takes the right dose they're strapped into the roller coaster um and some something interesting is going to happen and i really like what you said about that that that that distinction between the mind or the contrast between them the mind effects and the the bodily uh the body effects because um i think of this i i do research with all the drugs you know caffeine alcohol methamphetamine cocaine alcohol legal illegal most of these drugs um thinking about say cocaine and methamphetamine you can't give a to a regular user you can't safely give a dose where the regular cocaine user is going to say oh man that's like that's the strongest coke i've ever had you know um because you know you get it past the ethics committee and you need approval and i wouldn't want to give someone something that's dangerous so to go to those levels where they would say that you would have to give something that's physiologically riskier yeah you know psilocybin or lsd you can give a dose at the physiological level that is like a very good chance it's going to be the most intense psychological experience of that person's life yeah and have zero chance for most people if you screen them of killing them the big the big risk is behavioral toxicity which is a fancy way of saying doing something stupid i mean you're really intoxicated like if you wander into traffic or you fall from a height just like playing people on high doses of alcohol and the other kind of unique thing about about psych classic psychedelics is that they're not addictive which is pretty much unheard of when it comes to so-called drugs of abuse or drugs that people at least at some frequency choose to take you know most of what we think of as drugs um you know even caffeine alcohol cocaine cannabis most of these you can get into alcohol you can get into a daily use pattern and that's just extreme so unheard of with psychedelics most people have taken these things on a daily basis it's more like they're building up the courage to do it and then they build up a tolerance or yeah they're in college and they do it on a dare can you take take acid seven days in a row that type of thing rather than a self-control issue yes where you have and say oh god i gotta stop taking this i gotta stop drinking every night i gotta cut down on the coke whatever so that's the classic psychedelics uh what are the uh what's a good term modern psychedelics or more maybe psychedelics that are created in the lab what else is there right so mdma is the big one and i should say that that with the classic psychedelics that lsd is sort of you can call it a semi-synthetic because there's there's there's natural you know from from both ergot and in certain seeds um uh morning glory seeds is one example there's a very close there are some very close uh chemical relatives of lsd so lsd is close to what occurs in nature but not quite it's but then when we get into the the other um non-classic psychedelics probably the most prominent one is mdma people call it ecstasy people call it molly and it is uh it differs from classic psychedelics in a number of ways it can be addictive but not so it's like you can have cocaine on this end of the continuum and classic psychedelics here continuum of addiction continuum of addiction you know so it's certainly no cocaine it's pretty rare for people to get into daily use patterns but it's possible and they can get into more like you know using once a week pattern where they can find it hard to to stop but it's it's somewhere in between mostly towards the to the classic psychedelic side in terms of like relatively little addiction potential um but it's also more physiologically dangerous i think that the certainly the therapeutic use it's showing really promising effects for treating ptsd and the models that are used i think those are extremely acceptable when it comes to the risk benefit ratio that you see all throughout medicine but nonetheless that we do know that at a certain dose and a certain frequency that mdma can cause long-term damage to the serotonin system in the brain so it doesn't have that level of kind of freakish bodily safety that that the classic psychedelics do and it has more of a heart load a cardiovascular i don't mean kind of emotion i mean in this sense although it is very emotional and that's something unique about its uh subjective effects but it's more of a oppressor and uh the terminology using sort of uh like a freakish capacities allowing you from a researcher perspective but a personal perspective too of taking a journey with uh some of these psychedelics that is um the heroic dose as they say so like these are tools that allow you to take a serious mental journey whatever that is that's what you mean and with mdma there's a little bit it starts entering this territory where you got to be careful about the risks uh to the body potentially so yes that in in the sense that you can't kind of push the dose up as high as you safely um as one can if they're in the right setting like in our research as they can with the with the classic psychedelics but probably more importantly the just the nature of the effects with mdma aren't the full on psychedelic it's not the full journey you know so it's sort of a psychedelic with rose-colored glasses on psychedelic that's more of it's been called more of a heart trip than a head trip the nature of reality doesn't unravel as frequently as it does with classic psychedelics but you're able to more directly sense your environment so your perception system still works it's not completely detached from reality with mdma that that's true relatively speaking that said at most doses and of classic psychedelics you still have a tether to reality changes a little bit when you're talking about smoking dmt or smoking 5 methoxy dmt um which are some interes interesting examples we could talk more about but with um yet with mdma it it's for example it's it's very rare to have a a what's called an ego loss experience or a sense of transcendental unity um where one really seemingly loses the psychological construct of the self you know but um mdma it's very common for people to have this you know they still are perceiving themselves as a self but uh it's common for them to have this this warmth this empathy for humanity and for their friends and loved ones so it's more it's and you see those effects under the classic psychedelics but if that's a subset of what the classic psychedelics do so i see mdma in terms of its subjective effects is if you think about um venn diagrams it's sort of mdma is all within the classic psychedelic so okay everything that you see on a particular mdma session sometimes a psilocybin session looks just like that but then sometimes it's completely different with psilocybin it's a little more narrowed in terms of the variability with mdma is there something general to say about what the psychedelics do to the human mind you mentioned kind of an ego loss experience in the space of van diagrams if we're to like draw a big circle what can we say about that big circle in terms of people's report of subjective experience probably one of the most general things we can say is that it it expands that range so many people come out of these sessions saying that they didn't know it was possible to have an experience like that so there's an emphasis on the subjective experience that um is is there words that people put it put to it that capture that experience or is it something that just has to be experienced yeah people like as a researcher that's an interesting question because you have to kind of measure the effects of this and uh how do you convert that into numbers right that that's that's the ultimate child so how is that even is that possible to one convert it into words and the second convert the words into numbers somehow so we do a lot of that with questionnaires you know some of which are very psychometrically validated so they've lots of numbers have been crunched on them and there's always a limitation with with questionnaires i mean subjective effects are subjective effects ultimately it's what the person is reporting and and that doesn't necessarily point towards a ground truth um what what they're so for example if someone says that it they felt like they touched another dimension or they felt like they they sensed the reality of god or if they um you know um i mean just you name it people's ontological views can sometimes shift i think that's more about where they're coming from and i don't think it's the quintessential way in which they work there's plenty of people that hold on to a completely naturalistic viewpoint and come and have profound and and and helpful experiences with these compounds but the subjective effects can be so broad that for some people it shifts their their philosophical viewpoint more towards idealism more towards you know thinking of let that the nature of reality might be more about consciousness than about material that's a domain i'm very interested in right now we have essentially zero to say about that in terms of validating those types of claims but it's even interesting just to see what people say along those lines so you're interested in saying like can we more rigorously study this process of expansion like what do we mean by this expansion of your sense of what is possible in the experiences in this world right as much as what we can say about that through naturalistic psychology right especially as much as we can route it to um solid psychological constructs and solid neuroscientific constructs and i wonder what the impact is of the language that you bring to the table so you mentioned about god or um speaking of god a lot of people are really into sort of theoretical physics these days at a very surface level and you can bring the language of physics right you can talk about quantum mechanics you can talk about general general relativity and curvature space-time and using just that language without a deep technical understanding of it to somehow start thinking like sort of visualizing atoms in your head and somehow through that process because you have the language using that language to kind of dissolve the ego like realize like that we're just all little bits of physical objects that behave in mysterious ways and so that that has to do with the language like if you read a sean carroll book or something recently it seems like as a huge influence on the way you might experience my perceive the world i might experience the alteration that psychedelics brings to the um to the your perception system so i wonder like the language you bring to the table how that affects the journey you go on with the psychedelics i think very much so and and i think there's i'm a little concerned some of the science is going a little too far in the direction of of around the edges you know speaking about it changing beliefs in this sense or that sense about particular in particular domains and i think what really what a lot of what's going on is what you just discussed it's it's the priors coming into into it so if you've been reading a lot of you know um physics then you might you know um bring up you know like you know space-time and interpret the experience in that sense i mean it's not uncommon for people to come out talking about visions of the it's not the most typical thing but it's come up in sessions i've guided um the big bang um and the you know this sort of nature of reality i i think probably the the best way to think about these experiences is that and the best evidence even though we're in our infancy and understanding it the they really tap into more general psychological mechanisms i think one of the best arguments is they they they they reduce the influence of the of our priors of what we bring into the all of the assumptions that we all that you know we're essentially especially as adults we're riding on top of heuristic after heuristic to get through life and you need to do that and that's a good thing and that's extremely efficient and evolution has shaped that but that comes at an expense and i it seems that these experiences will will allow someone greater mental flexibility and openness and so one can be both less influenced by their their prior assumptions but still nonetheless the nature of the experience can be influenced by what they've been exposed to in the world and sometimes they can get it at a deep in a deeper way like maybe they've read i mean i had a philosophy professor one time as a participant yeah in a high-dose psilocybin study and he's like i remember him saying my god it's like hegel's opposites defining each other like i get it i've taught this thing for years and years and years like i get it now and so like that you know and and even at the psychological emotional level like the cancer patients um we worked with you know they told themselves a million times or this people trying to quit smoking i need to quit smoking oh i'm ruining my life with this cancer i'm still healthy i should be getting out i'm letting this thing defeat me it's like yeah you told yourself that in your head but sometimes they have these experiences and they kind of feel it in their heart like they really get it so in some sense that you bring some prize to the table but psychedelics allow you to acknowledge them and then throw them away so like one popular terminology around this in the engineering space is first principles thinking that elon musk for example espouses a lot let me ask a fun question before we return to a more serious discussion with elon musk as an example but it could be just engineers in general do you think there's a use for psychedelics to uh take a a journey of rigorous first principles thinking so like throwing away we're not talking about throwing away assumptions about the nature of reality in terms of like our philosophy of the way we live day-to-day life but we're talking about like how how to build a better rocket or how to build a better car or how to build a better uh social network or all those kinds of things engineering questions i absolutely think there's huge potential there and it's there was some research in the um late 60s early 70s that were it was very early and not very rigorous in terms of um methodology but um it was consistent with the i mean there's just countless anecdotes of folks i mean people have argued that just you know silicon valley was was largely influenced by psychedelic experience i remember the i think the the person that came up with the concept of freeware or shareware it's like it kind of was generated you know out of uh or influenced by psychedelic experience you know so to this i i think there's incredible potential there and we know really next there's no rigorous research on that but is there anecdotal stuff like with steve jobs they think their stories right in your exploration of the is there something a little bit more than just stories is there like a little bit more of a solid data points even if they're just experiential like anecdotes is there something that you draw inspiration from like in your intuition because we'll talk about it you're trying to construct studies that are more rigorous around these questions but is there something you draw inspiration from from the past from the 80s and the 90s in silicon valley that kind of space or is it just like you have a sense based on everything you've learned and these kind of loose stories that there's something worth digging at i am influenced by the gosh the the the just incredible number of anecdotes surrounding these i mean um uh kerry mullis he he invented pcr i mean absolutely revolutionized biological sciences he says he wouldn't have won the nobel prize from it said he wouldn't have come up with that had he not had psychedelic experiences um you know now he's an interesting character people should read his autobiography because he could point to other things he was into but but i think that speaks to the the casting your nets wide and this mental flex more of these general the these general mechanisms where sometimes if you cast your nets really wide and it's going to depend on the person and their influences but sometimes you come up with false positives you know um you know you connect the dots where maybe you shouldn't have connected those dots but it i think that can be constrained and and so much of our not only our personal psychological suffering but our our limitations um academically and in terms of technology are because of these self-imposed limitations and and heuristics the these entrenched ways of thinking you know like those examples throughout the history of science where someone has come up with a a rat the paradigm coons paradigm shifts it's like here's something completely different you know this doesn't make sense by any of the previous models and like we need more of those we i mean you know and then you need the right balance between that because so many of the you know novel crazy ideas are just bunk and you need that's what science is about separating them from from the valid paradigm shifting ideas but we need more paradigm shifting ideas like in a big way and i think we could i think you could argue that we've because of the structure of academia and science in modern times it heavily biases against those right there's all kinds of mechanisms in our human nature that resist paradigm shift quite sort of obviously uh so and psychedelics there could be a lot of other tools but it seems like psychedelics could be one set of tools that encourage paradigm shifting thinking so like the first principle is kind of thinking so it's a kind of um you're at the forefront of research here there's just kind of anecdotal stories there's uh early studies there's a sense that we don't understand very much but there's a lot of depth here how do we get from there to where elon and i can regularly like i wake up every morning i have deep work sessions where it's well understood uh like what dose to take like if i want to explore something where it's all legal where it's all understood and safe all that kind of stuff how do we get from uh where we are today to there not speaking in terms of legality in the sense like policy making all that like laws and stuff meaning like how do we scientifically understand this stuff well enough to get to a place where i can just take it safely in order to expand my uh thinking like this kind of first principles thinking which i'm in my personal life currently doing like how do i revolutionize particular several things like it seems like the only tools i have right now is just just but my mind going doing the first principles like wait wait okay why has this been done this way can we do it completely differently it seems like i'm still tethered to the priors that i bring to the table and i keep trying to untether myself maybe there's tools that can systematically help me on tether yeah well we need experiments you know and that's that's tied to kind of the policy level stuff um and i should be clear i would i'd never encourage anyone to do anything um illicitly but yeah i you know uh in the future we could see these these you know compounds used for the for for technical and scientific innovation what we need are studies that are digging into that right now most of what the the funding which is largely fun from philanthropy um not from the government um largely what it's for is is treatment of of mental disorders like addiction and depression etc um but we need studies you know one of the early initial stabs um on this question decades ago was they took some architects and engineers and said what what problems have you been working on where you've been stuck for months like working on this damn thing and you're not getting anywhere like your head's butting up against the wall it's like come in here take and i think it was 100 micrograms of lsd so not a big session and a little bit different model where they were actually working it was a moderate enough dose where they could work on the problem during the session i think probably i'm an empiricist so i'd like to see all the studies done but the first thing i would do is like a really high dose session where you're not necessarily in front of your you know computer you know which you can't really do on a on a really high dose and then the the work has been talked about like you take a really high dose you take a journey and then the breakthroughs come from when you return from the journey and like integrate quote unquote that experience i think that's where the all the head and we're again we're we're babies at this point but my gut tells me yeah that that it's the it's the so-called integration the aftermath we know that there's some form different forms of neuroplasticity that are unfolding in the days following a psychedelic at least in animals probably going on humans we don't know if that's related to the therapeutic effects my my gut tells me it is although it's it's only part of of the story but but we need big studies where we compare people like let's get 100 people like that scientists that are working on a problem and then randomize them too and then i think you you need a uh um even more credible you know active controls or active placebo conditions to can kind of tease this out um and then also in conjunction with that and you can do this in the same study you want to combine that with more rigorous sort of um experimental models where we actually get their problem solving tasks that we know for example that you tend to do better on after you've gotten a good night's sleep versus not and my my sense is there's a relationship there you know people go back to first principles you know questioning those first principles they're operating under and um you know getting away from their priors in terms of creative problem solving and so you i think wrap those things and you could speak a little more rigorously about those because ultimately if everyone's bringing their own problem that's that's i think that's more on the face valid side but you can't dig in as much and and get as much experimental power and speak to the mechanisms as you can with having everyone do the same sort of you know canned you know problem solving task so we've been speaking about psychedelics generally is there one you find from the scientific perspective or maybe even philosophical perspective most fascinating to study therapeutically i'm most interested in psilocybin and lsd and i think we need to do a lot more with lsd because it's mainly been psilocybin in the modern era i've recently gotten a grant from the hefta research institute to do an lsd study so i haven't started it yet but i'm going through the paperwork and everything and uh therapeutic meaning there's some issue and you're trying to treat that issue right right in terms of just like what's the most fascinating you know understanding the nature of these experiences if you really want to like wrap your head around what's going on when someone has a completely altered sense of reality and sense of self there i think you're talking about the the the high-dose either smoked vaporized or intravenous injection which all kind of um they're very similar pharmacologically of dmt and 5-methoxy dmt this is like when people this is what i don't know if you're familiar with terence mckinney he would talk a lot about smoking dmt joe rogan has has talked a lot about that people will say that and there's a close relative called five meth oxy dmt most people who know the terrain will say that's that's an order of magnitude or orders of magnitude beyond i mean anything one could get from even a high dose of psilocybin or lsd um i think it's a question about whether you know how therapeutic i think there is a therapeutic potential there but it's probably not as sure of a bet because one goes so far out it's almost like they're not contemplating their relationship and their direction in life they are like reality is ripping apart at the seams and the very nature of the of the self and of the sense of reality and the amazing thing about these compounds and same to a lesser degree with the you know with oral cell cybin and lsd is that unlike some some other drugs that that really throw you far out there um you know anesthetics and even even alcohol like it as reality starts become different at higher higher doses there's there's this numbing there's this sort of um there's this ability for the sense of being the center having a conscious experience that's memorable that is maintained throughout these classic psychedelic experiences like one can go as far so far out while still being aware of the experience and remembering the experience interesting so being able to carry something back right can you uh dig in a little deeper like what is uh dmt how long is the trip usually like how much do we understand about it is there's something interesting to say about just the the nature of the experience and what we understand about it one of the common methods for people to use is to is to smoke it or vaporize it and it usually takes and this is a pretty good kind of description of what it might feel like on the ground um the caveat is it's it's it's a completely insufficient description and someone's going to be listening who has done this it's like nothing you could say is going to come close but it'll take about three big hits inhalations in order to have what people call a breakthrough dose um and there's no great definition of that but basically meaning moving away from you know not just having the typical psilocybin or lsd experience where like things are radically different but you're still basically a person in this reality to go in somewhere else and so that'll typically take like three hits and this stuff comes on like a freight train so one takes a hit and around the time of the first exhalation so we're talking about a few seconds in or maybe just you know sometime between the first and the second hit like it'll start to come on and they're already up to say um you know what they might get from a 30 milligram or or 300 microgram lsd trip a big trip they're already there when at the second hit but it's they're going their consciousness is gear this is like acceleration not speed to speak of physics okay it's like you just those receptors are getting filled like that and they're going from zero to 60 in like you know tesla time yeah and at the second hit again they're at this maybe the strongest psychedelic experience they've ever had and then if they can take that third hit even some people can't they're i mean they're they're propelled into this other reality and the nature of that other reality it will will differ depending on who you ask but you know folks will talk often talk about and and we've done some survey research on this entities of different types elves tend to pop up yeah all the caveat is i i strongly presume all of this is culturally influenced you know but thinking more about the psychology and the neuroscience there is probably something fundamental you know like for someone that might be colored as elves others it might be colored as um terence mckenna called them self dribbling basketballs for someone else it might be little animals or someone else it might be aliens um i think that probably is dependent on who they are and what they've been exposed to but just the fact that one has a sense that they're surrounded by autonomous entities right intelligent autonomous entities right and people come back with stories that are just astonishing like there's communication between these entities and often they're telling them things that that that the person says are self-validating but it seems like it's impossible like it really seems like and again this is what people say oftentimes that it's it really is like downloading some intelligence from a higher dimension or some whatever metaphor you want to use sometimes these things come up in dreams where it's like someone is exposed to something that i've had this in a dream you know where it seems like what they are being exposed to is physically impossible but yet at the same time self-validating it seems true like that they really are figuring something out of course the challenge is to say something in in concrete terms after the experience that where you could um you know verify that in any way and i i'm not familiar of any examples of that well there's a there's a sense in which i suppose the experience like um you uh you're you're a limited cognitive creature that knows very little about the world and here's a chance to communicate with much wiser entities that in a way that you can't possibly understand are trying to give you hints of deeper truths right and so there's that kind of sense that you you can take something back but you can't where uh our cognition is not capable to fully grasp the truth we'll just get get a kind of sense of it and somehow that process is mind expanding that there's a greater truth out there right that seems like what from the people i've heard talk about that's that seems to be what uh it is and that's so fascinating that there's um there's fundamentally to this whole thing is the communication between an entity that is other than yourself entities so it's not just like a visual experience like uh like you're like floating through the world is there's other beings there which is kind of i don't know i don't know what to sort of uh from a person who likes freud and carl jung i don't know what to think about that that being of course from one perspective it's just you looking in the mirror but it could also be from another perspective like actually talking to other beings yeah you mentioned young and i think that's he's particularly interesting and it kind of points to something i was you know thinking about saying is that that i think what might be going on natural from a naturalistic perspective um so regardless you know whether or not there are you know it doesn't depend on autonomous entities out there what might be happening is that just the associative net the the the level of learning the the comprehension might be so beyond what someone is is used to that the only way for the nervous system for for the for the aware sense of self to orient towards it is all by metaphor and so i do think you know when we get into these realms as as a strong empiricist i think we always got to be careful and be as grounded as possible but i'm also willing to speculate and and sort of cast the nets wide with caveat but you know i think of things like archetypes and you know you know it's plausible that there are certain stories there are certain you know we've gone through millions of years of evolution it may be that we have certain um characters and stories that are sort of that our central nervous system are sort of wired to tend to yeah those stories that we carry those stories in us right and this unlocks them in a certain kind of way and we think about stories like our sense of self is basically narrative self is a story and we think about the world of stories this is why metaphors are always more powerful than um you know sort of laying out all the details all the time you know speaking in parables it's like if you really get so you know this is why as much as i hate it you know if you're presenting to congress or something and you have all the the best data in the world it's not as powerful as that one anecdote as as as the mom dying of cancer that had the psilocybin session and it transformed her life you know that's a story that's meaningful and so when this kind of unimaginable kind of change and and and experience happens with a dmt um ingestion it these stories of entities they might they might be that you know stories that are constructed that is the the closest which is not to say the stories aren't real i mean i think we're getting to layers where what it doesn't yeah yeah but it's the closest we can come to making sense out of it because i do what we do know about these psychedelics one of the levels beyond the receptor is that the brain is communicating it with itself in a massively different way there's massive communication with areas that don't normally communicate and so it i think that comes with both it's casting the nets wide i think that comes with the insights and helpful novel ways of thinking i do think it comes with false positives you know that could be some of the delusion um and so you know when you're so far out there like with dmat experience like maybe alien is the the best way that the mind can wrap some arms around that so uh i don't know how much you're familiar with joe rogan he does bring up dmt quite a bit it's almost a meme uh it is a name have you ever uh what is it have you ever tried dmt uh i mean he i think he talks about this experience of um having met other entities um and uh they were mocking him i think if i remember the experience correctly like laughing at him and saying f-u-f-u or something like that i may be misremembering this but but there's a general mockery and uh the the what he learned from that experience is that he shouldn't take himself too seriously so it's the dissolution of the ego and so on like what do you think about uh that experience and maybe if you have more general things about the joe's infatuation with dmt and if dmt has that important role to play in um popular culture in general i'm definitely familiar with it i remember telling you all flying that when i first the first time i learned who joe rogan was probably 15 years ago and i came up on a clip and i realized there's another person in the world who's into both dmt and brazilian jiu jitsu and i think both those worlds have grown dramatically since and it's probably not such a special club these days so he definitely you know got onto my radar screen quickly you you were into both before it was cool right i mean you know this is all relative because there's people that were you know before the late 90s and early 2000s who are into it that say you know you're a johnny come lately but but yeah compared to where we're at now but yet one of the things i always found fascinating by by joe's you know um telling of his experience experiences i think is that they resemble very much terence mckenna's experiences with dmt and joe has talked very much about terence mckenna and his experiences if i had to guess i would guess that probably just having heard terence mckenna talk about his experiences that joe's that that influenced the coloring yeah it's funny it's funny how that works because i mean that's why mckenna hasn't i mean poets and uh great orders give us the words to then like start to describe our experiences because our words are limited our language is limited and it's always nice to get some kind of nice poetry into the mix to allow us to put words to it right but i also see some elements that that that seem to relate to joe's psychology get just from what i've seen in him you know from hours of watching him on his podcast is that you know he's a self critical guy yes and i think with always this positive ben i'm always struck being a behavioral pharmacologist and he no one else really says it about cannabis i'll get back to the dnt thing about he likes the kind of the paranoid side of things he's like that's you radically examining yourself yeah it's like that sounds just a bad thing that's you need to like look hard at yourself yeah and something's making you uncomfortable like dig into that and like that's his it's sort of along the lines of goggins with exercise and it's like yeah like things learning experiences aren't supposed to be easy like take advantage of these uncomfortable experiences it's why we call in our research in a safe context with psychedelics they're not bad trips they're challenging experiences yes so yeah it's fascinating just a tiny tangent it's always cool for me to hear him talk about um marijuana like weed as the paranoia the anxiety or whatever that you experience is actually the the the fuel for the experience like i think he talks about smoking weed when he's writing that's inspiring to me because then you can't possibly have a bad experience i'm a huge fan of that like every experience is good um right which is very goggins yeah it's very good is it bad okay all right great you know well see goggins is one side of that he wants it bad i like he wants the experience to be challenging always but uh i mean like both are good like the the few times of uh taking mushrooms the experience was uh like i everything was beautiful there's zero challenging uh aspect to it it was just like the world is beautiful and it gave me this deep appreciation of the world i would say so like that's amazing but also ones that challenge you are also amazing like all the times i drink vodka but uh but that's another let's not so back to dmt um yeah and joe's treating you know cannabis as a psychedelic which is something that i'd say like not a lot of a lot of people treat it more like xanax or like beer yes you know or vodka um but he's really trying to delve into those the miners it's been called a minor psychedelic so with dmt you know as you brought up it's like the the entity's mocking him and it's like you're not i mean this reminds me of him you know him describing his like you know writing his or just just his entire method of of comedy it's like watch the tape of yourself you know don't just ignore it like that's where i screwed up that's where i need to do better this like sort of radical self-examination which i think our society is kind of getting away from because like you know all the children win trophies type of thing you know it's like no no don't go overboard but like recognize when you've messed up yes and so like that's a big part of the psychedelic experience like people come out sometimes saying my god i need to say sorry to my mom yeah you know like it's so obvious like or whatever you know interpersonal issue or like my god i don't i'm not pulling enough weight around the house and helping my wife and you know you know these things that are just obvious to them the self-criticism that can be a very positive thing if you act on it you've mentioned addiction maybe we could take a little bit detour into a darker aspect of things or not even darker it's just an important aspect of things what's the nature of addiction you've mentioned some things within the big umbrella of psychedelics may be usually not addictive but maybe mdma i think you said might have some addictive properties but the the point is stuff outside of the psychedelics umbrella can often be highly addictive so you've studied addiction from several angles one of which is behavioral economics what have you understood about addiction what is addiction from the biological physiological level to the psychological to whatever is an interesting way to talk about addiction yeah and i the lenses that i view addiction through very much are behavioral economic but i also think they converge on i think it's beautiful at the other end of the spectrum sort of just a completely um humanistic psychology perspective um and i it converges on what people come out of you know 12-step meetings talking about can you uh can you say what is behavioral economics and what is humanistic psychology uh like what do you mean by that and more importantly behavioral economics lens what is that yeah so behavioral economics my definition of it is the application of economic principles mostly microeconomic principles so understanding the the behavior of of individual agents um surrounding you know commodities and in the marketplace applying microeconomic types of analyses um to non-economic behavior so basically at one point uh like psychologists figured out that there's this whole other discipline that's been studying behavior just happened to be all focused on monetary behavior spending and saving money etc but it comes with all of these like principles that can be wildly and and fruitfully applied to understanding behavior so so for example i've studied things like um demand curve analysis of drug consumption so i look at um for example the the tobacco cigarettes and nicotine products through the lens of of of demand curves and in other words at different prices if there's different work requirements for um being able to smoke cigarettes sort of modeling price within that price data there is some indication of addiction how much you the habits that you form around these particular uh yeah it's one one important dimension so i think a particularly important one there is elasticity or inelasticity you know um two ends of the spectrum so that's the the price sensitivity so so for example you could have something that's pretty price um uh inelastic like like gasoline so the price of gas at times can keep going up and americans are just going to pretty much you know buy the same amount of gas or maybe you know the price of gas doubles but their consumption only decreases by 10 percent so it's a subproportional reduction so that's an inelastic and and and that changes like you push the price up high enough i mean if it was 100 a gallon it would eventually turn the curve would turn um and and go downward more more drastically and it would be elastic but you can apply that to someone you know someone who a regular cigarette smoker who um who is working for cigarette puffs who has who's gone six hours without smoking and you're asking questions like you know how many times are they willing to pull this knob in the lab during this three-hour session i do a lot of work like this in order to earn a cigarette how does the how does the content of nicotine in that effect it has the availability of nicotine replacement products like nicotine gum or e-cigarettes affect those those decisions so you can it's a certain lens of it's sort of a way to take the kind of the classic behavioral psychology definition of reinforcement and which is just basically reward you know how much is this a good thing and it kind of breaks that apart into a multi-dimensional um space so it's not just the ideas reward or reinforcement is not unidimensional so for example you can unpack that with demand curves at a cheap price you might prefer one good to another you know so the classic example is luxury versus necessity so diamonds versus toilet paper so at those cheap prices you can look at something called intensity of demand you know if it was basically as cheap as possible or essentially zero how much would you buy of this good but then you keep jacking up the price and you'll see so diamonds will look like the better reward at that at that low price of intensity demand side of things but as you keep jacking up the price you got to have some toilet paper yes okay we can get into the whole like bidet thing but forget that you know like uh i know joe's been pushing that too but you know you're gonna you're gonna hang on and keep buying the toilet paper to a greater degree than you will the diamonds yes so you'll see a crossing of demand curves so what's the better reinforcer what's the better reward depends on your price you know and so that's one that's an example of one way to and that a of look at addiction so specifically drug consumption which is isn't all of addiction but it's like in order for something to be addictive it has to be a a reward and it has to compete with other rewards in in your life and and one of the two main aspects of addiction in my in my view and this doesn't map on to how the you know the dsm the psychiatry bible defines addiction which i think is largely bunk you know but there's some value to have some common description but it's you know how rewarding is it from this multi-dimensional lens and specifically how does it how does that rewarding value compete with other rewards other consequences in your life so it's it's not a problem if if the use of that substance is rewarding you know okay yeah you like to have a couple beers every once in a while it's like not a problem i mean um but then you have the alcoholic who is drinking so much that they they're it tanks their career it ruins their marriage it's in competition with these pro-social aspects to their life it's all about comparing to the other choices you're making the other activities in your life and if it you evaluate as a much higher reward than anything else that becomes an addiction right right and so it's not just the rewarding value but it's the relative rewarding value and in the other major asp again from behavioral economics the the the thing that makes addiction is something called delayed discounting um so in economics sometimes it's called time preference it's this is it's what compound interest rates are based upon it's the idea that delaying a good access to a good or a reward comes with a certain decrement to its value so we'd all rather have things now than later and we can study this at the individual level of you know would you rather have nine dollars today or or ten dollars tomorrow um and you get when you do that you get huge differences between addicted populations and non-addicted not just heroin and cocaine but like just cigarette smokers like normal everyday cigarette smokers and even when you look at something like monetary rewards and and so you can go into the rabbit hole with with this delay discounting model so it's not only those huge differences that seem to have a face valid aspect to it like the cigarette smoker is choosing this thing that's rewarding today but i know it comes with increased risk of having these horrible consequences down the line so it's this competition between what's good for me now and what's good for me later and the other aspect about delayed discounting is that if you quantitatively map out that that discounting curve over time so you don't just do the you know you know how much you know that ten dollars tomorrow how much is it worth to you today so you can say what about nine what about eight what about seven dollars and you can titrate it to find that indifference point and so we can say aha six dollars um you know ten dollars tomorrow is worth six dollars to you uh today so it's by the one day it's decreased by 40 percent we can do that also at one week and one month in one year and 10 years and map out that curve get a shape of that curve and one of the fascinating things about this is that whether you're talking about pigeons making these types of choices between a little bit of food now or a little bit of food a minute from now or rats or every like dozens of species of animals tested including humans the tendency is pretty consistently that we we discount hyperbolically rather than exponentially what exponentially means is that every unit of time is associated with the same proportional reduction every unit of delay is is associated with the same causes the same proportional reduction in value and that's the way the compound interest rate you know works you know you know that there's you know compound every day you know you get this sort of out of whatever values in there at the beginning of that day you get this you know um will give you this amount of extra money to compensate you for that delay but then the way that all animals tend to function is of this very different way where the reductions the initial that initial delay so like one day's worth of delay you see a much stronger um discounting rate or reduction in value than you do over those um so you see the super proportional then it changes to these lesser rates and so the implication of that i know i've gone like really into the weeds quantitatively but what that means is that there's these preference reversals when you have curves of that nature the the the decay that's hyperbolic it maps on to this phenomenon we see um both in terms of how people deal with future rewards but also how perception works um when two things are far away whether it's physical distance or whether in terms of perception or whether it's in terms of time when you're really far away the value the subjective value for that further that delayed reward is is larger so so for example like let's say we're talking about 360 um 364 days from now you can get nine dollars or 365 days a year now you get 10 and you're like dude it's like it's a year like no difference like i'll take why not get one more dollar yeah you bring that same exact set of choices closer nothing's changed other than the time to both rewards and it's like would you rather have nine dollars today or ten dollars tomorrow and plenty of people would say ah just about the sounds go ahead and take it today yeah so you see this preference reversal and so that is that's a model of of addiction in the sense that consistently with with true addiction i would argue you see this this competition between molar and molecular um utility um it's like inter intrapersonal like within the person competing agents someone sometimes has control of the bus that wants to do what's in good for you in the short term and someone's at other times that is in control of driving the bus and they're they want to do what's good for you and the long term so you tell the you know you're trying to quit and you see a doctor you see your you know 12-step therapist and say god i know this stuff is killing me like i'm really i'm on the path i'm like i'm done and that's when you're kind of in their office or wherever you're not you know it's not around you and then later on that day your buddy says that hey man i just scored i got it right here do you want it and that reward is right in front of you that's like bringing those two choices right in front of you and it's like hell yeah i want to use yes and then you can go through that cycle for like years of the person telling themselves i want to quit but then other times that same person is saying i don't want to you know functionally they're saying i don't want to because they're saying yeah yeah give me some so in the moment it's very difficult to quit and this isn't just something this is something that has has huge clinical ramifications with addiction but it's like all humans do it anyone who's had hit the snooze alarm in the morning like yeah the night before they realize oh i got to get up extra early tomorrow that's what's ultimately better for me so i'm going to set the alarm for you know 5 a.m um and they they it goes off at 5 00 a.m you know and then so now those two consequences have come sooner and it's like what the hell and they hit the snooze alarm and something's not just once but then five minutes later and then five minutes later you know and so and it's why it's easier to exercise self-control at the grocery store compared to in your fridge like if that snack is like 30 seconds away in your fridge you're gonna more likely yield to temptation than if it is further away so then just take a step back to something you brought up earlier the inelasticity of pricing is it uh from a perspective of the dealers whether we're talking about cigarettes or maybe venturing slightly into the illegal realm you know of people who sell drugs illegally they also have an economics to them that they set prices and all those kinds of things does addiction allow you to mess with the nature of pricing like so i i kind of assume that you meant that there's a correlation between things you're addicted to and the inelasticity of the price so you can jack up the price is there something interesting to be said both for legal drugs and illegal drugs about the kind of price games you can play because the consumers of the product are addicted right i mean i think you just described it yeah you can jack up the price and you know some people are going to drop off but the people you know and it's not dichotomous because you could just consume less but some people are going to consume less and the people that are most addicted are going to keep you know um i mean you see this they're going to keep you know purchasing so you see this with cigarettes and so it's interesting when you interface this with policy like in one respect heavily taxing cigarettes is a good thing we know it keeps you know um adolescents particularly price sensitive so you definitely people smoke less and especially kids smoke less when you keep cigarette prices high and you tax the hell out of them um but one of the downsides you've got to balance and keep in mind is that you disproportionately have working class poor people and then you get into a point where someone's spending you know order their paycheck on so they're gonna smoke no matter what and uh basically because they're addicted they're gonna smoke no matter what and you're just yeah you're taxing their existence right so you're making it worse for if if they don't if they are completely inelastic you're actually making that person's life worse yeah because we know that that by by interfering with the amount of money they have you're interfering with the other um pro-social the potential competitors to smoking you know um and we know that when someone's in more impoverished environments and they have less sort of non-drug alternatives you know the more likely they're gonna stay addicted so you know is there data this is interesting from a scientific perspective of those same kind of games in illegal drugs sort of uh because that's where most drug i was i mean i don't know maybe you can correct me but it seems like most drugs are currently illegal and so but they're still in economics to them obviously right that's the drug war and so on is there data on the setting of prices or like how good are the business people running the selling of drugs uh that are illegal are they all the same kind of rules apply from a behavioral economics perspective i think so i mean they're basically that whether they're crunching the numbers or not they're basically sensitive to that demand curve and they're doing the the the same thing that businesses do in in a legal market and you know you want to sell as much of a product to get as much money you're looking more at the total income so if you jack the price a little bit you're going to get some reduction in consumption but it may be that the total amount of money that you rake in is going to be more than then it's gonna overcompensate for that so you're willing to take okay i'm gonna lose 10 of my customers but i'm getting more perce you know more than enough to compensate from that from the extra money from the people who still are buying so i think they're more you know and especially when we get to the lower i wouldn't be surprised if people are crunching those numbers and looking at demand curves maybe at the you know at the really high levels of the you know up the chain where the cartels and one i don't know i that wouldn't surprise me at all but i think it's probably more implicit at the lower levels where um something he brought up drug policy i will say that i for for years now it's been this kind of unquestioned goal um by for example the the drug czar's office um in the u.s to make the price of illegal drugs as high as possible without this kind of nuanced approach that um yeah if you make you know for some people if you you know if you make the price so high you're actually making things worse i mean i'm all about reducing the problems associated with drugs and drug addictions and part of that is the are more direct consequences of those drugs themselves and but a whole lot is what you get from indirectly and and you know sort of the inc both for the individual and for society society so like making a poor person who doesn't have enough money for their kids making them even poorer so now you've made their their chil children's future worse because they're growing up in deeper poverty because you've essentially levied a tax on to this person who's heavily uh addicted um but then it's at the societal level you know so everything we know about the drug war in terms of the the heavy criminalization and filling up prisons and reducing employment and educational opportunities which in the big picture we know are the things that in a free market compete against some of the worst problems of addiction is actually having educational and employment opportunities but when you get give someone a felony for example um you're pretty much guaranteeing they're never going to go very high on the economic ladder and so you're making drugs a better reward for that person's future so this is a quick step into the policy realm and i think for both you and i i'm not sure you can correct me but i'm more comfortable into studying the effects of drugs on the um human behavior in human psychology versus like policy it seems like a whole giant mess but yeah there's some libertarian candidates for president and just libertarian thinkers that had a nice thought experiment of possibly legalizing i was spoken about possibly legalizing basically all drugs in your intuition do you think a world where all drugs are legal is a safer world or a less safe world for the users of those drugs it really depends on what we mean by legalization so this is one of my beefs with this you know how these things are talked about i mean we have very few completely laissez-faire you know legal drugs so even caffeine is one of the few examples so for example caffeine and tea and coffee is in that realm like there's no limits no one's testing there's no laws regulation at any level of how much caffeine you're allowed to buy or how much in the price but even like with this um starbucks like nitro there are rules with soda and with canned products you can only put so much in there yeah yeah so there's this is fda regulated and it's kind of weird because there's a limit to sodas that's not there for energy drinks and other things so but you know so even caffeine it depends on what product we're talking about like if you're like nodos and other caffeine products over the counter like you can't just put 800 milligrams in there the pills are like one or 200 milligrams and so it's fda regulated as an overcounter drug some of the most dangerous drugs in society i would say arguably one of the most dangerous classes of drugs is the volatile anesthetics huffing people huffing gasoline and you know airplane glue toluene whatnot severely damaging to the nervous system pretty much legal but there's some regulation in the sense that there's a warning label like it's illegal to do it for not that it neces people they're busting people for this but you know it's against federal law to use this in a way other than intended type basically saying like yeah don't huff this you know um your paint thinner whatnot at least keeps people from selling it for that like no because they're gonna they're gonna go after that person they're not gonna be able to find the 12 year old who's huffing yeah so anyway just as some extreme examples at at the end and then you know even the the so-called illegal like schedule one drug psilocybin we do plenty and in terms of schedule two which is ironically less restrictive than psilocybin but methamphetamine and cocaine i've done human research with my research has been legal so they're scheduled compounds but they're not completely illegal like you can do research with them with the appropriate licensees and um uh approval so there really is no such thing and like alcohol well it's illegal if you're 12 years old or 18 years old or 20 years old and for anyone it's illegal to to be drinking it while you're driving so there's always a nuance there's rules not dichotomy and i actually should admit it's been on my to-do list for a while to buy in massachusetts some like edible or buy weed legally i um yeah haven't done that messages let's put it this way and i i wonder what that experience is like because i get i think it's fully legal in massachusetts and so i wonder what legal drugs look like to me you know i grew up with even weed being like you know not it's like this forbidden thing you know not not forbidden but it's illegal you know most people of course i never partook but most people i knew would attain it illegally and so that big swish that's been happening across the country there's like federal stuff going on to make a marijuana legal federation i'm half paying attention there's some movement there i mean the house passed bill that's not going to be passed by the by the senate but yeah it's it's but there's clearly a change in right it's moving in a trend so that's the example of a drug that used to be illegal and now becoming more and more and more legal um so like i wonder what like uh cocaine being legal looks like right what a society with cocaine being legal looks like the rules around it the you know the processes in which you can consume it in a safer way and be more educated about its consequences be able to control dose and like purity much better be able to get help for overdose i don't know all those kinds of things i it does in a utopian sense feel like legalizing drugs at least should be talked about and considered versus uh keeping them in the dark i agree but yeah so that in your sense it's possible that in 50 years uh we legalize all drugs and uh it makes for a better world the way i like to talk about it is that i would say that we it's possible and it would probably be a good thing if we regulate all drugs how would you regulate uh like cocaine for example is there is there ideas there so yeah and you were already you know going you know where i was going with that kind of first i described how there's always new ones and even like the cannabis in massachusetts federally illegal so for example if i was like and i you know colleagues that do cannabis research where they get people high in the lab like you're a federal funded researcher with nih funds you can't get that that stuff from the dispensary because you're breaking a federal law even though the feds don't have the resources to go after they don't want the controversy at this point to go after the individual users or even the the sellers in those legal states so there's always this nuance but it's it's about right the right regulation so i think we already know enough that for example like i think safe injection sites for hard drugs um makes a lot of sense like i wouldn't want um heroin and cocaine at the convenience stores and i don't think maybe there's some extreme libertarians that want that i think even the folks that identify as libertarians probably most of them don't well i don't know like not all of them want that you know um i think you know that as a form of regulation like look if you're using these hard drugs on a on a regular basis you're putting yourself at risk for lethal overdose you're putting yourself at risk for catching um hiv and and hepatitis um if you're gonna do it if you're doing it anyway come to this place where at least you're not like you know like pulling the the water out of like you know the puddle on the side of the street yeah so it's done by professionals and those professionals are able to educate you also so like a 7-eleven clerk may not be both capable of of helping you to uh to inject the drug properly but also it won't be equipped to educate you at but the negative consequences all those kinds of things that's a huge part of it the education but then i i think with the opioids like the big part of it is just like with naloxone which is an antagonist it goes into the um the receptor it's called narcan that's the trade name but it's what they revive people on an opioid overdose that's almost completely effective like if there's a medical professional there and someone's odin on an opioid they're virtually guaranteed to live like that's remarkable that if a hundred percent at the opioid crisis you know if all of those people right now that are dying we're doing that in the presence of a medical professional like even like a nurse with narcan there'd be basic almost no deaths there's always some exceptions but you know almost no deaths like that's staggering to me so the idea that people are doing this you know that we could have that level of positive effect without encouraging the drug and this is where like you get into this like terrain of like sending the wrong message and it's like no you can do that you can say like we're not encouraging this in fact probably one of the greatest advertisements for not getting hooked on heroin is like visiting a methadone clinic visiting a safe injection site like like this is not like an advertisement for getting hooked on this drug but knowing that we can save people now you have a landscape here because a lot of times it's just like supervised injection but you bring your own stuff you know you bring your own heroin which could still be you know dirty and and filled with fentanyl and fentanyl derivatives which because of the incredible potency and the more difficulty measuring it it's and some differences at the receptor like you may be more likely you are more likely on average to lethally overdose on it you know so you you could the the level that's been more explored in switzerland is uh in some places is is you actually provide the drug itself and you supervise the injection so i don't like that idea yeah i the public health data are completely on the side of there's really no credible evidence to this if we allow that we're sending the wrong message and everyone's going to be i mean i'm not showing up like you know and it's different by drug like yeah you you legalize you set up cannabis shops and some people are going to say so you come and go there i don't think a whole lot of people are going to go to one of these places and say i'm going to shoot up heroin for the first time because and even if like you know it's a country of 300 million people like even if someone does that you have to compare this to the everyday people are dying from opioid overdoses like people's kids people's uncles peoples like these are real lives that are being shattered so you just look at that and then the other thing and i know this from having done residential even like non-treatment research where we just have a cocaine user or something stay on our inpatient word for a month and you really get to know them and sometimes you see like oftentimes that's the first time this person has had a discussion with a medical professional any type of professional in their entire life around their drug use yeah even if they're not looking to quit and it's like i i you know you could imagine that in in these safe injection settings where it's like it might be a year into treatment and they're like you know doc i know you're not the cops like you really care for me like i think i'm ready to try that methadone thing i think i'm really i think i want to be conversation about it yeah yeah they get to trust the people and and realize that they're they're there because they truly like they have a compassion a love for for this community like as human beings and they don't want people to die and you get real human connections and that and again like those are the conditions where people are going to ultimately seek treatment and not everyone always will but you're go you're going to get that and then you're you know you're going to get people like looking into treatment options sometimes you know maybe it's years into to the treatment so it's like they're just all of these indirect benefits that i think at that level i don't know if you'd call that legalizing you know i think again ra at least well regulated right whatever that word is yeah well regulated but uh out in the open right minimizing as many harms as we can um while not encouraging i mean we don't encourage people to drink all the i mean people die every year from caffeine overdose like you know there's different ways to like you know just by allowing something doesn't mean we're sending the message that you know by saying we're not going to give you a felony which is actually often the the the the the penalty for for psychedelics i just actually testified for the judiciary committee the the senate the assembly in in new jersey and um just to move psilocybin from a felony to misdemeanor they use different language in new jersey it's weird but like the equivalent of felony missed me and that was like two people didn't vote for that on the on this committee because it was might one of them said it might be sending the wrong message and it's like a felony i mean there's real harms like that's the scarlet letter the rest of your life you're stuck at the lower ends of the employment ladder you're not going to get you know loans for education all of this maybe because of a stupid mistake you made once as a 19 year old yeah doing something that like you know a presidential candidate could have done and admitted to and had no problem you know yeah what drug is the most addictive the most dangerous in your view not maybe spec like not technically like specifically which drug but more like in our society today what is a highly problematic drug we talked about psychedelics not being that addictive on the other flip side of that you mentioned cocaine is that is that the top one is there something else that's a concern to you it depends and you've already alluded to this nuance it depends on how you define it if we're talking about on the ground today yes in you know modern society i'd i'd say nicotine tobacco oh i should think um i mean in terms of mortality it kills it kills far more than any other drug known to humankind four times more than alcohol like a half million deaths in the us every year and about five to six million worldwide due to tobacco that's four times more in the us than alcohol and if you graph all of the the drugs legal and illegal like you know um put all of the illegal drugs in like one category on that figure and you put alcohol and tobacco on that figure all the illegal drugs combined barely they're a barely visible blip to this incredible like it's there's no even all of the opioid epidemic rolled up along with cocaine and everything else the meth barely shows up compared to tobacco that's one of those uncomfortable truths that's that i don't know what to do with it's like uh where everybody's freaking out about coronavirus right [Laughter] and nobody's relative it's all relative if you look at the relative thing it's like well why aren't we freaking out about now cigarettes which which we are increasingly so over the historically speaking right right it's like terrorism versus swimming pools i remember that being back in the after the war on terror started i was like yeah there's not even comparison okay so you know that's a little sobering truth there because i was thinking like cocaine i was thinking about all these hard drugs but the reality is relatively nicotine is the is the big one and you didn't ask about mortality or deaths you asked about um addiction but that's that really is hard to hard to evaluate it gets into those nuances i spoke of before about there's not a uni-dimensional way to measure reinforcement it kind of depends on the situation and and what measure we're looking at but you know more people have access to tobacco and i'm not i'm not advocating that we make it an illegal drug i think that was a heart would be a horrible mistake although there is a very credible push to to mandate the reduction of nicotine in cigarettes which i have most scientists that study it are for it i think there's some real dangers there because i see that in the broader history of drug use it's like when has drug prohibition worked broadly speaking and and it's it's uh to me that would that that path would only make sense in very good conjunction with e-cigarettes which once they're fully regulated can be a safer not safe but much safer alternative and if we don't if we tax the hell out of e-cigarettes and ban every attractive feature like like flavors and everything then that's gonna push people to a black market if they can't get the real thing from real sick like some people would just quit straight out but i think with the regulators and what a lot of scientists that study tobacco like myself it's a big part still what i study um they're not used to thinking about the like tobacco really as a drug largely speaking in terms of you know for example the history of prohibition and i think of like we already know there's an illicit market a black market for tobacco to get around um you know taxes i mean and for selling even loose cigarettes that's what initially caused in staten island the police to approach uh was it eric garland who was selling loose cigarettes and he got choked out i mean the thing that caused that police contact was he was selling well i think report it to sell individual cigarettes for like you know you can sell them for court it happens in baltimore and it's like that's technically illegal it's but you know are you not going to have massive boats of you know supplies coming over from china and elsewhere of real deal cigarettes if you ban you know the sale nicotine like it's obviously going to happen and you have to weigh that against you know you're going to create a black market one size or another and your intuition that really hasn't worked throughout the history when we've tried it right but i see a potential path forward but only if it's well if it's not in conjunction with e-cigarettes if there's a clear alternative that's a positive alternative that you it kind of stares the population that right towards an alternative yeah the difference here the the unique thing that could be taken advantage of here is nicotine is by and large not what causes the harm it's the the aromatic hydrocarbons it's the the carcinogens in in in tobacco it's burning tobacco smoke it's not the nicotine so um that it's not like alcohol prohibition where like you know you couldn't create the adults the the near beer is not going to have the alcohol and so people like like here you do have the possibility of giving an another medium the ability to deliver the drug which still aren't to a lot of people isn't preferred to the tobacco but nonetheless again if you over regulate those and make them less attractive like if you aren't thoughtful about the nicotine limits and thoughtful about whether you're allowing flavors and everything and if you over tax them you're actually decreasing the ability to compete with the more dangerous um products so i feel that like there is a potential path forward but i don't have a lot of confidence that that's going to be done in a thoughtful analytical way and i'm afraid that it could decrease the increase of black market cause all of the harms like every other drug we're moving away from the heavy from the prohibition model slowly but the big barge ship is like making a a very slow turn and like okay we really had to step back and question if we went with nicotine tobacco are we moving into that direction like yeah the picture it doesn't quite make sense you uh you've done a study on cocaine and sexual decision making uh can you explain can you explain the findings i mean in a broad sense how do you do a study that involves cocaine and the other how do you do a study involving this sexual decision making and then how do you do a study that combines both yeah sex and drugs too i'm just missing the rock and roll the two controversial rock and roll isn't very controversial anymore yeah so the cocaine you know lots of hoops to jump through you got to have a lot of medical support you got to be at a basically an institution a research unit like i'm at that has a long history and the ability to to do that and get ethics approval get fda approval but it's possible and whenever you're dealing with something like cocaine you would never want to give that to a not someone who hasn't already used cocaine and you want to make sure you're not giving it to someone who's an active user who wants to quit so the idea is like okay if you're if you're using this type of drug anyway and you're we're really sure you're not looking to quit hey use use a couple times in the lab with us so we can at least learn something and part of what we learn is maybe to help people not use and it'll reduce the harms of of cocaine so there's hoops to jump through with the sexual um decision making i looked at the main thing i looked at was this model of i applied delayed discounting to what we talked about earlier than now versus later that kind of decision-making that goes along with addiction i applied that to condom use decisions um and and i've done probably published about 20 or so papers with this and different drugs and and uh so the the primary metric is whether you do or don't use a condom that's the most right oh hypothetical so this is using hypothetical decision making but i published some studies looking at um showing a tight correspondence to self-report it um in correlational studies to self-reported behavior so this is like so like how do you did you do a questionnaire kind of thing right so it's a it's not quite a questionnaire but but it's a it's it's a it's a behavioral task requiring them to to respond to so you show pictures of a bunch of individuals and it's it's kind of like one of these fun behavioral like a lot of them you get like numbers are born but it's like okay hot or not like which of these 60 people would you have a one night stand with men women so pick whatever you like yeah a little bit of this a little bit of that whatever you're into it's all variety there out of that group you pick some subsets of people who you think is the you know the one you most want to have sex with the least he thinks most likely have an sti or at least likely a sexually transmitted disease by sti and then you could do certain decision making questions so what i've done is asked say this percy read a vignette this person wants to have sex with you now you've met them to get along um casual sex scenario like a one-night stand with a condom's available just rate your likelihood from 1-100 on this kind of scale would you use it but then you can change your your scenario to say okay now imagine you have to wait five minutes to use a condom so the the choice is now instead of using condom versus not in terms of your likelihood scale it now it ranges from um have sex now without a condom versus on the other end of the scale is wait five minutes to have sex with a condom so you rate your likelihood of where your behavior would be along that continuum and then you could say okay well what about an hour what about three hours what about you know what about 24 hours i'm misunderstanding uh now without a condom or five minutes later with a condom right isn't the so what what's supposed to be the preference for the person like is like what like there's a lot of factors coming into play right there's like uh like there's like pleasure and personal preference and then there's also the safety those are two like are those competing objectives right and so we do get at that through some individual measures and and this task is more of a face valid task where there's a lot underneath the hood so for most people sex with the condom is the better reward but underneath the hood of that is just at the purely physical level they'd rather have sex with without the condom it's going to feel bad what do you mean by reward like when they calculate their trajectory through life and try to optimize it then sex with the condom is a good idea well it's it's it's it's really based on i mean yeah yeah presumably that's the case that that that there's but it's measured by like what would really that first question where there is no delay most people say they would be at the higher net scale a lot of times 100 percent they said they would definitely use use economy a condom not everybody and that we know that's the case see it's like that that some people don't like com some people say yeah i i want to use a condom but you know a quarter of the time ended up not because i guess getting lost in the passion of the moment so for the people i mean the only reason that people so behaviorally speaking at least for a large number of people in many circumstances condom use is a reinforcer just because people do it like you know why are they doing it they're not because it makes the sex feel better but because it makes that it allows for at least the same general reward even if actually even if it feels a little bit not as good yeah you know with the condom nonetheless they get most of the benefit without the concurrent oh my gosh there's this risk of either unwanted pregnancy or getting hiv or way more likely than hiv you know herpes you know in general awards etcetera all the all the lovely ones um and we've actually done research saying like where we gauge the probability of these individual s different sdi's and it's like what's the heavy hitter in terms of what people are using to judge you know to evaluate they're going to use a condom so that's why the condom use is the delayed thing five minutes or more and then uh yeah because it would normally be the larger later reward like the ten dollars versus the nine it's like the ten dollar which is counterintuitive if you just think about the physical pleasure so that's a good that's a good thing to measure so condom use is a really good concrete quantity quantitative quantifiable thing that you can use in a study and then you can add a lot of different elements like the presence of cocaine and so on yeah you can get people loaded on like any number of drugs like cocaine alcohol and methamphetamine are the three that i've done and published on and it's interesting that these are fun studies man right i love to get people loaded in in a safe context and like but to really it started like there was some early research alcohol i mean the psychedelics are the most interesting but it's like all of these drugs are fascinating the fact that all these are keys that unlock a certain like psychological experience in in the head and so there was this work with alcohol that showed that it didn't affect those monetary delay discounting decisions you know nine dollars now versus ten dollars later and i'm like getting people drunk and i thought to myself are you telling me that that you know getting someone that people being drunk is does not cause people at least sometimes to make to choose what's good for them in the short term at the expense of what's good for them to uh yeah in the long term it's like you know bullshit you know like yeah we see it like but in what context does that happen so that's what that's something that inspired me to go in this direction of like aha risky sexual decisions is something they do when they're drunk they don't necessarily go home and and even though some people have gambling problems and alcohol interacts with that the most typical thing is not for people to go home and log on and change their their allocation in their retirement account or something like that you know like but but they're more likely risky sexual decisions they're more likely to not wait the five minutes for the condom right instead go no condom no right that's a big effect and we see that and interestingly we do not see with those different drugs we don't see an effect if we just look at that zero delay condition in other words the condoms right there waiting to be used would you how likely are to use it you don't see it i mean people people are by and large gonna use the condom yeah so and that's the way most of this research outside of behavioral economics that just looked at condom use decisions um very little of which has ever actually administered the drugs which is another unique aspect but they usually just look at like assuming the condom is there but this is more using behavioral economics to delve in and model something that and i've done survey research on this modeling what actually happens like you meet someone at a laundromat like you weren't planning on like you know one thing leads to another they live around the corner yeah these things you know and like we did one um survey with with men who have sex with men and found that uh 25 of them 24 about a quarter reported in the last six months that they had unprotected anal intercourse which is the most risky in terms of uh sexually transmitted infection um uh in the last six months in a situation where they would have used a condom but they simply didn't use one just because they didn't have one on them so this to me it's like if unless we delve into this and understand this these sub-optimal conditions we're not going to fully address the problem there's plenty of people that say yep condom use is good i use it a lot of the time you know it's like where is that failing and it's under these sub-optimal conditions which in frank if you think about it it's like most of the case action is unfolding things are getting hot and heavy someone's like you got a condom ah no it's like do they break the action and take 10 minutes to go to the convenience store or whatever maybe everything's closed maybe they got to wait till tomorrow and though there's something to be uh studied there on the that just seems like an unfortunate set of circumstances like what's the solution to that is uh i mean um what's the psychology that needs to be uh like taken apart there because it just seems like that's the way of life we don't expect the things that right to happen are we supposed to expect them better to be like be self-aware enough about our calculations or you see the 10-minute detour to a convenience store as a kind of thing that uh we need to understand um how we humans evaluate the cost of that i think in terms of like how we use this to help people yes it's mostly on the environment side rather on the on the individual side yeah although those those interact so it's like you know in one sense if you're especially if you're going to be drinking or using another substance that that is associated with you know a stimulant um alcohol and stimulants go along with risky sex you know good to be aware that you might make decisions just to tell yourself you might make a decision that that is gonna that you wouldn't have made in your sober state and so hey throwing a condom in the in the purse and in the pocket you know might be you know a good idea i think at the environmental level just more condom of it i mean it highlights what we know about just making condoms widely available something that i'd i'd like to do is like you know reinforcing condom use and you know so um you know just getting people uh used to carrying a condom everywhere they go because it's such once um it's in someone's habit if they are saying like a young single person and you know it's you know they occasionally have unprotected sex like training those people like what if you got a text message you know once every few days saying ah if you show me a send back a photo of a condom within a minute you get a reward of five dollars you could shape that up like that it's a process called contingency management it's basically just straight up operant reinforcement you could shape that up with no problem and and um i mean those procedures of contingency management giving people systematic rewards is like for example the most powerful way to to to reduce cocaine use in addicted people and um uh but but by is saying if you show me a negative urine for cocaine i'm gonna give you a monetary reward and like that has huge effects in terms of decreasing cocaine use if that can be that powerful for something like stopping cocaine use how powerful for that could that be for shaping up just carrying a condom because the primary unlike cocaine use here we're not saying you can't have the the main reward like you could still have sex and you can even have sex in the way that you tell yourself you'd rather do it you know if the condom is available you know so you know like you're not you know it's relatively speaking it's way easier than like not using cocaine if you like using cocaine it's just basically getting in the habit of carrying a condom so that's just one idea of like well there could be also the capitalistic solutions of like there could be a business opportunity for like a door dash for condoms oh yeah like delivery i thought about this within five minute delivery of a condom in any location like uber for condoms i thought about it not with condoms but a very similar line of thinking in a line that you're going into in terms of of uber and people getting drunk when they intend they into the bar playing to have one or two they end up having five or six and it's like okay yeah you can take the the cab the uber home yeah but you've left your car there it might get towed you might like there's also the hassle of just you know you want to wake up tomorrow with your hangover and forget about it and move on yeah like and i think a lot of people in their situation and they're like screw it i'm gonna take the risk just get it you know what if you had an uber service where two um you know you have uh two so some a car come out with two drivers and um one of them two sober drivers obviously and they and and the person they the one driver drops off the other that then drives you home in their car in your car yeah so that you can i mean i think a lot of people would pay 50 bucks it's gonna be more than a regular uber yeah but it's like it's gonna be done i got the money i already i already spent 60 bucks at the bar tonight like just get the damn thing done tomorrow i'm done with it my car i wake up my car's in front of my house i think that would be i think someone could i'm not going to open that business so like if anyone hears this and wants to take off with that like i think it could help a lot of people yeah definitely an uber itself i would say helped a huge amount of people just making it easy to make the decision of going home uh not driving yourself i read about in austin where they i don't know where it's at now where they outlawed uber for a while you know because of the whole taxi cab union type thing and and how just yeah there were like hordes of drunk people that were uh used to uber that now didn't have a cheap alternative uh so just uh we didn't exactly mention you've done a lot of studies in sexual decision making with different drugs is there some interesting insights or findings on the difference between the different drugs so i think you said meth as well so cocaine is there some interesting characteristics about decision making that these drugs alter versus like alcohol all those kinds of things i think and there's much more to study with this but i think the biggie there is that the stimulants they create risky sex by really increasing the rewarding value of sex like if you talk to people that are real especially that have are hooked on stimulants one of the biggies is like sex on coke or meth is like so much better than sex without and that's a big part of what why they have trouble quitting because it's so tied to their sex life so it's not that your decision making is broken it's just that you well you allocate it's a different aspect of their decision yeah on the reward side i think on the alcohol it works more through disinhibition it's like alcohol is really good at reducing the ability of a delayed punisher to have an effect on current behavior in other words there's this bad thing that's going to happen tomorrow or a week from now or 20 years from now um being drunk is a really good way and you see this in like rats making decisions you know a high dose of alcohol makes someone less sensitive to those consequences so i think that's the lever that's being hit with alcohol and it's the more the just the increasing the rewarding value of sex um by the psycho stimulants on that side we actually found that it and it was amazing because like hundreds of millions of dollars have been spent by nih to study the connection between cocaine and hiv like we ran the first study on my grant that like actually just gave people cocaine under double blind conditions and showed that like yeah when people are on coke like their ratings of sexual desire even though they're not in a sexual situation yeah you show them some pictures but you're just saying they're horny like you get subjective ratings about like how sex how much sexual desire are you feeling right now people get horny when they're on stimulants and um do you have a lot of people say duh if they really know these drugs but that's a rigorous study that's in the lab just shows like there's a plot right the dose effects of that the time course of that yeah it's not just please tell me there's a paper with the plot that shows dose versus uh uh evaluation of like horniness yeah we didn't say horniness we said sexual arousal yeah basically yeah there's a plot i'm gonna find this plot right i'll send it to you there was one headline from uh some publicity on the work that said horny cocaine users don't use condoms or something like that like something like journalists i wouldn't have put it that way but like yeah that's right i guess that's what it finds so you've published a bunch of studies on uh psychedelics is there some especially favorite insightful findings from some of these they you could talk about maybe favorite studies or just something that pops to mind in terms of uh both the goals and the like the major insights gained and maybe the side little curiosities that you discovered along the way yeah i think of the work with like using psilocybin to help people quit smoking and we've talked about smoking being such a a serious addiction and so that what inspired me to get into that was just kind of having like behavioral psychology is my primary lens sort of a a this sort of like being a kind of radical empirical basis of i'm really interested in the mystical experience and the all of these reports very interested and but at the same time i'm like okay let's let's get down to some behavior change and something that we can record like quantitatively verify um biologically so to find all kinds of negative behaviors that people practice and see if we can turn those into positive right like really change it not just people saying which again is interesting i'm not dismissing it but folks say that say my life has turned around i feel this has completely changed me it's like yep that's good all right let's see if we can harness that and test that into something that it's that's real behavior change you know what i mean it's quantifiable it's like okay you've been smoking for 30 years you know like that's a real thing and you've tried a dozen times like seriously to quit and you haven't been able to long term like okay and if you quit like we'll ask you and i'll believe you but i don't trust everyone reading the paper to believe you so we're going to have you you pee in a cup and we'll test that and we'll have you blow into this little machine that measures carbon monoxide and we'll test that so multiple levels of biological verification like now we're getting like to me that's where the rubber meets the road in terms of like therapeutics it's like can we really shift behavior and since and so much as we talked about my other scientific work outside psychedelics is about understanding addiction and drug use so it's like you know looking at addiction it's a no-brainer and smoking is just a great example and so back to your question like we've had really high success rates i mean it really it rivals anything that's been published in the scientific literature um the caveat is that you know that's based on our initial trial of only 15 people but extremely high long-term success rates um 80 at six months per smoke free so can we uh discuss the details so first of all which psychedelic are we talking about and maybe can you talk about the 15 people and how the study ran and what you found yeah yeah so the the drug we're using is psilocybin and we're using um a moderately high and high doses of psilocybin and i should say this about most of our work these are not kind of museum level doses in other words nothing even big fans of psychedelics want to take and go to a go to a concert or go to the museum if someone's at burning man on this type of dose like they're probably going to want to find their way back to their tent and zip up and hunker down for you know not be around strangers yeah and by the way uh the the delivery method so psilocybin is mushrooms i guess uh what's the usual is it edible is there some other way like how people are supposed to think about uh the the correct dosing of these things because i've heard that it's hard to dose correctly uh that's right that's right so in our studies we use the the pure compound psilocybin so it's a single molecule you know a bunch of molecules and we and we give them a capsule with that in it um uh and so it's just you know a little capsule they swallow what people when psilocybin is used outside of research it's always in the context of mushrooms um because they're so easy to grow there's no market for synthetic psilocybin there's no reason for that to pop up um that the the the the high dose that we use in research is 30 milligrams body weight adjusted so if you're a heavier person it might be like 40 or even 50 milligrams um we have some data based on that data we're actually moving into like getting away from the body weight adjusting of the dose and just giving an absolute dose it seems like there's no justification for the body weight based dosing but i i digress um generally 30 40 milligrams it's a high dose and based on average even though as you alluded to there's variability which gets people into some trouble in terms of mushrooms like silas b cubensis which is the most common for species in the illicit market in the u.s this is about equivalent to five dried grams which is right at about where right where mckenna and others they call it a a heroic dose you know this is not hanging out with your friends going to the concert again so this is a real deal dose even to people that like really you know just even to psychonauts and even we've even had numbers yeah yeah people that yeah that's a great term cosmonaut you know like for psychedelics yeah going as far out as possible but even for them even for even for those who've flown to space before right right they're like holy shit i didn't know the orbit would be that yeah far out you know like or i i escaped the orbit i was in interplanetary space there so these folks in the the 15 folks in the study they're not there's not a question of uh dose being too low to truly have an impact right right very out of hundreds of volunteers over the years we've only seen a couple of people where there was a mild effect of the of the 30 milligrams and who knows that person's their serotonin they might have lesser density of serotonin 2a receptors or something we don't know but it's extremely rare for most people this is like like something interesting is going to happen put it that way you know joe rogan i think that jamie his producer is uh immune to uh uh psyched so maybe he's he's a good recruit for the study to test so that's interesting now i'm not the caveat i'm not encouraging anything illicit but just theoretically my first question as a far behavioral pharmacologist is like you know increase the dose you know like really nobody i'm not telling him jamie to do that but like okay like you know you're taking the same amount that friends might be taking but yeah but he was also referring to the psychedelic effects of edible marijuana which is is there is there uh rules on uh dosage for um uh like marijuana is there limits like what places where it's this is this all goes it probably is state by state right it is but most they've gone that direction and states that didn't initially have these rules have not now have them so it's like you'll get i think you know five ten mil i think ten five or ten milligrams of thc yeah being a common and and like and this is an important thing like where they've moved from not being allowed to say like have a whole candy bar and have each of the eight or ten squares on the counter bar being 10 milligrams but it's like no the whole thing because like you know someone gets a candy bar they they're eating the freaking candy bar yeah and it's like if you unless you're a daily cannabis user if you if you take you know 100 milligrams it's like that's what could lead to a bad trip yeah for someone and it's like you know a lot of these people it's like oh you used to smoke a little weed in college they might say they're visiting denver for a business trip and they're like why not let's give it a shot you know and they're like oh i don't want to smoke something because it's going to so i'm going to be safer with this edible consume this massive you know but there's huge tolerance so a regular like for someone who's smoking weed every day they might take five milligrams and kind of hardly feel anything and they might not make it they may really need something like 30 40 50 milligrams to have a strong effect but yeah so that's they've evolved in terms of the rules about like okay what constitutes a dose you know which is why you see less big candy bars and more or if there is you're if it is a whole candy bar you're only getting a smaller dose like 10 milligrams or yeah because that's is where people get in trouble more often with edibles yeah uh except joey diaz which i've heard this that's definitely something i want to talk to out of the crazy comedians i want to talk about anyway uh so yeah 15 the study of the 15 and uh the dose not being a question so like what was the recruitment based on what was the uh like how did the study get conducted yeah so the recruitment and i really liked this fact it wasn't people that you know largely were you know we were honest about what we were studying but for most people it was they were in the category of like you know not particularly interested in psychedelics but more of like they want to quit smoking they've tried everything but the kitchen sink yeah and this sounds like the kitchen sink you know and it's like well it's hopkins so yeah you know thinking that sounds like it's safe enough so like what the hell let's give it a shot like most of them were in that category which i really you know i appreciate because it's more of a of a test you know of of of yeah just like a better model of what if these are approved as medicines like what you're going to have the average participant you know um be like and so the the the therapy involves a good amount of non psilocybin sessions so preparatory sessions like eight hours of of getting to know the person like the two people who are going to be their guides or the person in the room with them during the experience um uh having these discussions with them where you're both kind of rapport building just kind of discussing their life getting to know them but then also telling them preparing them about the the the psilocybin experience oh it could be scary in this sense but here's how to handle it trust let go be open um and also during that preparation time preparing them to quit smoking using really standard bread and butter techniques that can all fall under the label typically of the cognitive behavioral therapy just stuff like before you quit we assign a target quit date ahead of time you're not just quitting on the fly and that happens to be the target quit date and our study was the day where they got the first psilocybin dose but doing things like keeping a smoking diary like okay during the three weeks until you quit every time you smoke a cigarette just like jot down what you're doing what you're feeling what situation that type of thing and then having some discussion around that and then going over the pluses and minuses in their life that smoking kind of comes with and being honest about the this is what it does for me this is why i like it this is why i don't like it preparing for like what if you what if you do slip how to handle it like don't dwell on guilt because that leads to more full-on relapse you know just kind of treat it as a learning experience that type of thing then you have the real the session day where they come in they they um five minutes of questionnaires but pretty much they jump into the we we touch base with them and they we we give them the capsule it's a serious setting but you know a comfortable one they're in a room that looks more like a living room than like a research lab we measure their blood pressure they experience but kind of minimal kind of medical vibe to it and um they lay down on a couch and it's a it's a purposefully an introspective experience so they're laying on a couch during most of the five to six hour experience and they're wearing eye shades which is a better connotation as a name than blindfold but like you know so they're wearing eye shades but that's a and and they're wearing headphones through which music is played um mostly classical although we've done some variation of that i have a paper that was recently accepted kind of comparing it to more like gongs and and and harmonic bowls and and that type of thing kind of like sound you know kind of um yo you've uh you've also added this to the science and have a paper on the musical accompaniment to the psychedelic experiences right and we found basically that the about the same effect even by a trend not significant but a little bit better of an effect both in terms of um subjective experience and long term whether it helped people quit smoking just a little tiny non-significant trend even favoring the the the the novel playlist with the the tibetan singing bowls and and the gongs and didgeridoo and all of that and um so anyway just saying okay we can deviate a little bit from this like what goes back to the 1950s of this method of using classical music as part of this psychedelic therapy but they're listening to the music and they're not playing dj in real time you know it's like you know they're just be the baby you're not the decision maker for today go inward trust let go be open and pretty much the only interaction like that we're there for is to deal with any anxiety that comes up so guide is kind of a misnomer in a sense it's we're more of a safety net and so like tell us if you feel some butterflies that we can provide reassurance a hold of their hand can be very powerful i've had people tell me that that was like the thing that really just grounded them can you break apart trust let go be open what uh what so in a sense how would you describe the experience the uh intellectual and the emotional approach that people are supposed to take to really let go into the experience yeah so trust is trust the context you know trust the guides trust the overall in institutional context i see it as layers of like safety even though it's everything i told you about the relative bodily safety of silicone nonetheless we're still getting blood pressure throughout the session just in case we have a physician on hand who can respond just in case we're literally across the street from the emergency department just in case you know all of that you know privacy is another thing you've talked about just trusting that you're and whatever happens is just between you and and the people in the study right and hopefully they've really gotten that by that point deep into the study that like they realize we take that seriously and everything else you know so it's really kind of like a very special role you're playing as a as a researcher or guide and and hopefully they have your your trust and so you know and trust that they could be as emotional everything from laughter to tears like that's going to be welcomed we're not judging them it's like it's a therapeutic relationship where you know this is a safe container it's a safe space there's a lot of baggage but it truly is it's a safe space for that for this type of experience and to to like go so trust let's see let go so that relates to the emotional like you feel like crying cry you feel like laughing your ass off laugh your ass ass off you know it's like all the things actually that sometimes it's more challenging with a recreation someone has a large recreational use sometimes it's harder for them because people in that context and understandably so it's more about holding your shit yeah someone's had a bunch of mushrooms at a party maybe they don't want to go into the back room and start crying about this these thoughts about the relationship with their mother and they don't want to be the drama queen or king that bring their friends down because their friends are having an experience too and so they want to like compose you know and also just the appearance in social settings versus the so like prioritizing how you appear to others versus the prioritizing the depth of the experience and here within the study you can prioritize the experience right and it's all about like you're the astronaut and we're there's only one astronaut yeah we're ground control and i use this often with um that's good i have a photo of the space shuttle on a plaque in my in my office and i kind of use often use that as example it's like we're here for you like we're a team but we have different roles it's like you don't have to like compose yourself like you don't have to like be concerned about our safety like we're playing these roles today and like yeah your job is to go as deep as possible or as far out whatever your analogy is like as possible and and we're keeping you you safe and so yeah and you really the emotional side is a hard one you know because you really want people to like if they go into realms of subjectively of despair and sorrow like yeah like cry you know like it's okay you know and especially if someone's you know more macho and you know you want this to be the place where they they can let go and and again something that they wouldn't or shouldn't do if someone were to theoretically use it in a in a social setting and like and also these other things like even that you get in those social settings of like yeah you don't have to like worry about your wallet or being for a woman sexually assaulted by some creep at a concert or something because they're you know they're laying down millions of sources of anxiety that are external uh versus internal so you just focus on your own like right the beautiful thing that's going on in your mind and even the cops at that layer even though it's extremely unlikely yeah for most people that cops would come in and bust them right when like even at that theoretical like that one in a billion chance like that might be a real thing psychologically in this context we even got that covered this is we've got dea approval yeah like you are this is okay by every level of society yeah that counts you know that has the authority so it's so go deep trust the you know trust the setting trust yourself um you know let go and be open so in the experience and this is all subjective and by analogy but like if there's a door open it go into it if there's a stair well go down it or stairway go up it if there's a monster in the mind's eye you know don't run approach it look in the eye and say you know let's talk about it yeah what's up what are you doing here let's talk turkey you know the chat okay right right it really is that it that really is a heart a heart of it is this radical courage like courage people are often struck by that coming out like this is heavy lifting this is hard work people come out of this exhausted and it's it can be extremely some people say it's the most difficult thing they've done in their life like choosing to let go on a moment a microsecond by microsecond basis everything in their inclination is to is to say stop sometimes stop this i don't like this i didn't know it was going to be like this this is too much and terence mckenna put it this way it's like comparing to meditation and other techniques it's like spending years push trying to press the accelerator to make something happen high-dose psychedelics is like you're speeding down the the mountain in a fully loaded semi truck and you're you're charged with not slamming the brake it's like you know let it happen you know so it's very difficult and to engage always you know go further into it and take that radical you know radical courage you know throughout what do they say um in self-report if you can put general words to it what is their experience like what do they say it's like because these are many people like you said that haven't probably read much about psychedelics or they don't have like with joe rogan um like language or stories to put on it so this is very raw self-report of experiences is what do they say the experience is like yeah and some more so than others because everyone has been exposed at some level or another but some of it is pretty superficial as you as you're saying um one of the hallmarks of psychedelics is just their variability so i'm more stressed it's like not the mean but the standard deviation right it's so wide that it's like it could be like hellish experiences and and you know um just absolutely beautiful and loving experiences everything in between and and both of those like those could be two minutes apart from each other yeah and sometimes kind of at the same at the same time concurrently so um let's see there's different ways to there were some jungian psychologists back in the 60s um masters in houston that wrote a really good book the varieties of psychedelic experience kind of which is a play on varieties of religious experience by william james uh that they described this a perceptual level so most people have that you know when you know whether they're looking at the room without the eye shades on or inside their their minds eye with the eye shades on colors you know um sounds like this as a much richer um censorium you know which can be very interesting and then at another level a master's in houston called the psychodynamic level and i think you could think about it more broadly than you know that's kind of jungian but um just the personal psychological levels how i think of it like this is about your life there's a whole life review oftentimes people have thoughts about their childhood about their relationships their their spouse or partner their children their parents their family of origin their current family like you know that stuff comes up a lot including every like like the love just people just like pouring with tears about like like how much like it hits them so hard how much they love people yeah like in a way that you know for people that like they love their family but like it just hits them so hard that like how important this is yeah and like the magnitude of that love and like what that means in their life so that's those are some of the most moving experiences to be present for is where people like it hits home like what really matters in their life and and then you have this sort of what masters in houston called the archetypal realm which again is sort of viewing him with the focus on archetypes which is interesting but i think of that more generally is like symbolic level so just really deep experiences where you have you do have experiences that seem symbolic of you know very much in like you know what we know about dreaming and what most people think about dreaming like there's this randomness of things but sometimes it's pretty clear in retrospect oh like this came up because this thing has been on my mind you know recently so it seems to be there there seems to be this symbolic level and then they have this the last level that they describe as the mystical integral level which and this is where there's lots of terms for it but transcendental experiences experiences of unity mystical type effects we often measure um europeans use a scale that will refer to oceanic boundlessness this is all pretty much the same thing yeah this is like at some sense the deepest level of the very sense of self seems to be dissolved minimize or expand it such that the boundaries of the self go into and here i think some of this is just semantics but whether the self is expanding such that there's no boundary between the self and the rest of the universe or whether there's no sense of self again might be just semantics but this radical shift or sense of loss of sense of self or self boundaries and that's like the most typically when people have that experience they'll often report that as being the most remarkable thing and this is what you don't typically get with mdma these deepest levels of the the nature of reality itself the subjectivity and objectivity just like the the the seer and the scene become one and and it's a process and yeah and they're able to bring that experience back uh and be able to describe it yeah but but one of the to a degree but one of the hallmarks going back to william james of describing a mystical experience as the inf ability and so even though it's ineffable you know people try as far as they can to describe it but when you get the real deal they'll say and even say that they say a lot of helpful things to help you describe the landscape they'll say no matter what i say i'm still not even coming anywhere close to what this was like the language is completely failing and i like to joke that even though it's it's ineffable and we're researchers so we try to eff it up by asking them to describe the experience i love it but to bring it back a little bit so for that particular study on tobacco what was the results what was the conclusions in terms of the uh impact of uh psilocybin on their addiction so when that pilot study was very it was very small and it wasn't a randomized study so it was limited the only question we could really answer was is this worthy enough of follow-up yes and the answer to that was absolutely freaking lutely because the success rates were so high eighty percent biologically confirmed successful at six months that held up to sixty percent biologically confirmed abstinent at two at an average of two and a half years a very long time yeah and so i mean the best that's been reported in the literature for smoking cessation is in the upper 50 and that's with not one but two medications for a couple of months followed by regular cognitive behavioral therapy where you're coming in once a week or once every few weeks for an entire year and and so but this is what very heavy this is just like a few uses of uh psilocybin so this was three doses of psilocybin over a total course including preparation everything a 15-week period where there's mainly like um for most part one one meeting a week and then the three sessions are within that and so it's and we scale that back in the more the the study we're doing right now which i can tell you about which is a randomized um controlled trial um but but it's uh the yeah the original um you know pilot study was you know these 15 people so given the like the positive signal from the first study telling us that it was a worthy pursuit we hustled up some money to actually be able to afford a larger trial so it's randomizing 80 people to to get either one psilocybin session when we've narrowed we we've scaled that down from three to one mainly because we're doing fmri neuro imaging before and after and it made it more experimentally complex to have multiple sessions um but one psilocybin session versus uh the nicotine patch using the the fda approved label like standard use of the nicotine patch so it's randomized 40 people get randomized to psilocybin one session 40 people get nicotine patch and they all get the same cognitive behavioral therapy for the standard talk therapy and we've scaled it down somewhat so there's less a weekly meetings but it's within the same ballpark and right now we're still um uh uh uh uh the study's still ongoing and in fact we just recently started recruiting again we paused for covet now we're starting back up with some protections like masks and whatnot but um uh right now for the 44 people who have gotten through the one-year follow-up and so that includes 22 from each of the two groups the success rates are extremely high for the psilocybin group it's 59 have been biologically confirmed as smoke-free at one year after their quit date and that compares to 27 percent for the nicotine patch which by the way is extremely good for the nicotine patch compared to previous research so the results could change because it's ongoing but we're mostly done and it's still looking extremely positive so if anyone's interested they have to be sort of be in commuting distance to the baltimore area but you know to participate right right to participate this is uh this is a good moment to bring up something i think a lot of what you talked about is super interesting and i think a lot of people listening to this so now it's anywhere from 300 to 600 000 people for just a regular podcast i know a lot of them will be very interested what you're saying and they're going to look you up they're going to find your email and they're going to write you a long email about some of the interesting things that found in any of your papers how should people contact you what is the best way for that would you recommend your super busy guy you have a million things going on what how should people communicate with you thanks for bringing this up this is a i'm glad to get the opportunity to address this if someone's interested in participating in a study the best thing to do is go to the website of the study or of uh uh like yeah which website so we have all of our psilocybin studies so everything we have is up in on one website and then we link to the different study websites but hopkins psychedelic.org so everything we do or if you don't remember that just you know go to your favorite search engine look up johns hopkins psychedelic and you're going to find one of the first hits is going to be our is this website and there's going to be links to the smoking study and all of our other studies if there's no link to it there we don't have a study on it now and if you're interested in psychedelic research more broadly you can look up you know like at another university that might be closer to you and there's a handful of them now across the country and there's some in europe that that um have studies going on but you can at least in the us you can look at clinicaltrials.gov and and look up the term psilocybin and in fact optionally people even in europe can register their trial on there so that's a good way to find studies but for our research rather than emailing me like a more efficient way is to go straight and you can do that first the first phase of screening there's some questions online and then someone will get back in touch with you um but i do already start you know and i i you know i expect it's like going to increase but i'm already at the level where my simple limited mind and limited capacity is already i i sometimes fail to get back to emails i mean i'm trying to respond to my colleagues my mentees all these things my responsibilities and as many of the people just inquiring about i want to go to graduate school i'm interested in this i had this i have a daughter that took a psychoduck and she's having trouble it's like so i i try to respond to those but sometimes i just simply can't get to all of it already to be honest like from my perspective uh it's been quite heartbreaking because i basically don't respond to any emails anymore and um especially as you mentioned mentees and so on like outside of that circle it's heartbreaking to me how many brilliant people there are thoughtful people like loving people and they write long emails that are really i by the way i do read them very often it's just that i don't the response is then you're starting a conversation and there's the heartbreaking aspect is you only have so many hours in the day to have deep meaningful conversations with human beings on this earth and so you have to select who they are and usually it's your family it's people like you're directly working with and even i guarantee you with this conversation people will write you long really thoughtful emails like there'll be brilliant people faculty from all over phd students from all over and it's heartbreaking because you can't really get back to them but you're saying like many of them if you do respond it's more like here go to this website if you're in for when you're interested into the study it's just it makes sense to directly go to the site if there's applications open just apply for the study right right right you know but you know as a either a volunteer or if we're looking for you know somebody um you know we're going to be you know posting um including on the hopkins university like website we're going to be posting if we're looking for a position i am right now actually looking through and it's mainly been through email and contacts but should i say it because i think i'd rather cast my network but i'm looking for a postdoc right now oh great um so i've mentored postdocs for i don't know like a dozen years or so and more and more of their time is being spent on psychedelics so someone's free to contact me that's more of a that's sort of so close to home that's a personal you know that like emailing me about that but i i come to appreciate more the advice that folks like tim ferriss have of like i think it's him like five sends emails you know like you know a a subject that gets to the point that tells you what it's about so that like you break through the signal to the noise but i really appreciate what you're saying because part of the equation for me is like i have a three-year-old and like my time on the ground on the floor playing blocks or cars with him is part of that equation and even if the day is ending and i know some of those emails are slipping by and i'll never get back to them and i have i'm struggling with it i'm already and i get what you're saying is like i haven't seen anything yet if with the type of exposure that like your podcast this will bring in exposure and then i think in terms of post docs this is a really good podcast in the sense that there's a lot of brilliant phd students out there that are looking for posts from all over from mit probably from hopkins this is just all over the place so this is and i we have different preferences but my preference would also be to have like a form that they could fill out proposed because you know it's very difficult through email to tell who's are really going to be a strong collaborator for you like a strong postdoc strong student because you want a bunch of details but at the same time you don't want a million pages worth of email so you want a little bit of an application process so usually you set up a form that helps me indicate how passionate the person is how willing they are to do hard work like i i often ask a question people of what do you think it's more important to work hard or to work smart and i use that those types of questions to indicate who i would like to work with because it's it's counter-intuitive but uh anyway i'll leave i'll leave that question unanswered for people to figure out themselves but maybe if you know my love for david goggins you will understand so anyway those are good thoughts about the forms and everything it's difficult and that's something that evolves email email is such a messy thing this uh speaking of baltimore cal newport if you know who that is um he wrote a book called deep work he's a computer science professor and he's currently working on a book about email about all the ways that email's broken so this is going to be a fascinating read this is a little bit of a general question but uh almost a bigger picture question that we touched on a little bit but let's just touch it in a full way which is uh what have all the psychedelic studies you've conducted taught you about the human mind about the human brain and the human mind is there something if you look at the human scientists you were before this work and the scientists you are now how is your understanding of the human mind changed i'm thinking of that in two categories one kind of more more scientific and they're both scientific but um one more about you know more about the the brain and behavior and the mind so to speak and and as a behaviorist always see sort of the mind as a metaphor for behavior so but anyway that gets philosophical but it's really increasing the the so the one category is increasing the appreciation for the magnitude of depth i mean so these are all metaphors of of human experience that might be a good way to because you use certain words like consciousness and what it's like we're using constructs that aren't well defined and unless we kind of dig in but in human experience like that the experiences on these compounds can be so far out there or so deep and that like and they're doing that by tinkering with the same machinery that's going on up there i mean i'm my assumption and i think it's a good assumption is that all experiences you know there's a there's a biological side to all phenomenal experience you know so there is not you know the divide between biology you know and and um and experience or psychology is is it's you know it's not one or the other these are just two you know two sides of the same coin i mean you're avoiding the the word the use of the word consciousness for example but the experience is referring to the subjective experience so it's it's the actual technical use of the word consciousness of of yeah subjective experience and even that word there are certain ways that like like sort of like we're talking about access consciousness or narrative self-awareness which is an aspect of like you can wrap a definition around that we can talk meaningfully about it but so often around psychedelics it's used in this much more in terms of ultimately explaining phenomenal consciousness itself the so-called hard problem and you know uh relating to that question and psychedelics really haven't spoken to that and that's why it's hard because like it's hard to imagine anything but i think what i was getting is that psychedelics have done this by the reason i was getting into the biology versus mind psychology divide is that that just to kind of set up the fact that i think all of our experience is related to these biological events so whether they be naturally occurring neurotransmitters like serotonin and dopamine and norepinephrine etc and and a whole other sort of biological activity and kind of another layer up that we could talk about network activity communication amongst brain areas like this is always going on even if i just prompt you to think about a loved one you know like there's something happening biologically okay so that's always another side of the coin so and another way to put that is all of our subjective experience outside of drugs it's it's all a controlled hallucination in a sense it like this is completely constructed our our experience of reality is completely a simulation so i i think we're on on solid ground to say that that's our best guess and that's a pretty reasonable thing to to to say scientifically like all the rich complexity of the world emerges from just some biology and some chemicals so in that you know in that that definition implied a causation it comes from and so that's right that's we know at least there's a solid correlation there and so then we don't dig we delve deep into the philosophy of like idealism or materialism and things like this which i'm not an expert in but i know we're getting into that territory you don't even necessarily have to go there like you you at least go to the level of like okay we know there's there seems to be this one-on-one correspondence and that seems pretty silent like you can't prove a negative and you can't you know it's like in that category of like yeah me you could come up with an experience that maybe doesn't have a biological correlate but then you're talking about there's also the limits of the science so is it a false negative but i think our best guess and a very decent assumption is that every psychological event has a biological correlate so with that said you know the idea that you can throw alter that biology in a pretty trivial manner i mean you could take like a relatively small number of these molecules throw them into the nervous system and then have a a 60 year old person who has you name it i mean that has hiked to the top of everest and that speaks five languages and that has been married and has kids and grandkids and has you name you know like been at the top and say this fundamentally changed who i am as a person and and the and what i think life is about like that's that's the thing about psychedelics that just floors me and it it never fails i mean sometimes you get bogged down by the paperwork and running studies and all the i don't know all of the the bs that can come with being in academia and everything and then you and sometimes you get some dud sessions where it's not the fullness all the magic isn't happening and it's you know more or less it's or it's either a dud or somewhere in the i don't mean to dismiss them but you know it's it's not like these magnificent sort of reports but sometimes you get the full monty report from one of these people and you're like oh yeah that's why we're doing this whether it's like therapeutically or just to understand the mind and you're like you're still floored like how is that possible how did we slightly alter serotonergic neurotransmission and say and this person is now saying that they're they're they're making fundamental differences in the in the priorities of their life after 60 years it also just fills you with uh all of the possibility of experiences were yet to have uncovered if if just a few chemicals can change so much it's like man what if this could be up i mean like ha because we're just like took a little like it's like lighting a match or something in the darkness and you can see there's a lot more there but you don't know how much more and that's right and then like where's that gonna go with like i mean i'm always like aware of the fact that like we always as humans and as scientists think that we figured out 99 and we're working on that first one and we got to keep reminding ourselves it's hard to do like we figured out like not even one percent like we know nothing yeah and so like i can't i can speculate and i might sound like a fool but like what are drugs even the concept of drugs like 10 years 50 years 100 years a thousand years if we if we're surviving like you know molecules that go to a specific area of the brain in combination with technology in combination with the magnetic stimulation in combination with the you know like targeted pharmacology of like oh like this subset of serotonin 2a receptors in the colostrum you know at this time in this particular sequence in combination with this other thing like this baseball cap you wear that like has you know you know has has one of the is doing some of these things that we can only do with these like giant like pieces of equipment now like where it's going to go is going to be endless and it becomes easy to you know combined within virtual reality where the virtuality is going to move from being something out here to being more in there and then we're getting like we talked about before we're already in a virtual reality in terms of human perception and and cognition models of the of the universe being all representations and you know sort of you know color not existing and just you know our representations of em um wavelengths etc etc you know sound being vibrations and all of this and so as the the external vr and the internal vr come closer to each other like this is what i think about in terms of the future of drugs like all of this stuff sort of combines and and like where that goes is just it's it's unthinkable like we we're probably gonna you know again i might sound like a fool and this may not happen but i think it's possible you know to go completely offline like where most of people's experiences may be going into these internal worlds and i mean maybe you through through some through a combination of these techniques you create experiences where someone could live a thousand years in terms of maybe they're living a regular lifespan but in over the next two seconds you're living a thousand years worth of experience inside inside your mind through yeah through this manipulation of the like is that possible like just based on on like first principles i suppose yes i think so yeah like give us another 50 hundred 500 like who knows but like how could it not go there and a small tangent what are your thoughts in this broader definition of drugs of psychedelics of mind altering things what are your thoughts about neural link and brain computer interfaces sort of being able to electrically stimulate and read and neuronal activity in the brain and then connect that to the the computer which is another way uh from a computational perspective for me is kind of appealing but it's another way of altering subtly the behavior of the brain that's kind of if you zoom out reminiscent of the way psychedelics do as well right so what do you have like what are your thoughts about neurolink what are your hopes as a researcher of mind altering devices systems chemicals i guess broadly speaking i'm all for it i mean for the same reason i am with psycheducks but it comes with all the caveats you know you're going into a brave new world where it's like all of a sudden there's going to be a dark side there's going to be you know that serious ethical considerations but that that should not stop us from from moving there i mean particularly the stuff from an unknown expert but on the short list in the short term it's like yeah can we help these serious neurological disorders like hell yeah like and and i'm also sensitive to something being someone that has lots of you know neuroscience colleagues um you know with some of the stuff and i can't talk about particulars i'm not recalling but you know in terms of you know stuff getting out there and then kind of a mocking of of of uh you know gosh they're they're saying this is unique we we know this or sort of like this belittling of like oh you know this sounds like it's just a i don't know a commercialization or like an oversimply i forget what the example was but something like something that came off to some of my neuroscientific colleagues as an oversimplification or at least the way they said it oh from a kneeling perspective right oh we've known that for years yes and like but i'm very sympathetic to like maybe it's because of my very limited but relatively speaking the amount of exposure the psychedelic work has had so my limited experience of being out there and then you think about someone like mike musk who's like like really really out there and you just get all these arrows that like and it's hard to be like when you're plowing new ground like you're gonna get you're gonna criticize like every little word that you like this balance between speaking to like people to make it meaningful something scientists aren't very good at yes having people understand what you're saying and then being belittled by oversimplifying something in in terms of the public message so i'm extremely sympathetic and i'm a big fan of like what that you know what elon musk does like tunnels through the ground and spacex and all this is like hell yeah like this guy is has some he has some great ideas and there's something to be said it's not just the the communication to the public i i think his first principles thinking it's like because i get this in the artificial intelligence world it's probably similar to neuroscience world where elon will say something like or i worked at mit i worked on autonomous vehicles and he's sort of i could sense how much he pisses off like every roboticist at mit and everybody who works on like the human factor side of safety of autonomous vehicles and saying like we need we don't need to consider human beings in the car like the ill car will drive itself it's obvious that neural networks is all you need like it's obvious that like we should be able to uh systems that should be able to learn constantly and they don't really need lidar they just need uh cameras because we humans just use our eyes and that's the same as cameras so like it doesn't why would we need anything else you just have to make a system that learns faster and faster and faster and neural networks can do that and so that's pissing off every single community it's pissing off human factors communities saying you don't need to consider the human driver in the picture you can just focus on the robotics problem it's pissing off every robotics pers person for saying lidar can be just ignored it can be camera every robotics person knows that camera is really noisy that's really difficult to deal with but he's uh and then uh every ai person who says who hears neural networks and and says like neural networks can learn everything like almost presuming that it's kind of going to achieve general intelligence the problem with all those haters in the three communities is that they're looking one year ahead five years ahead the hilarious thing about the quote-unquote ridiculous things that elon musk is saying is they have a pretty good shot at being true in 20 years and so like when you just look at the you know uh when you look at the progression of these kinds of predictions and sometimes first principles thinking thinking can allow you to do that is you see that it's kind of obvious that things are going to progress this way and if you just remove your the prejudice you hold about the particular battles of the current academic environment and just look at the big picture of the progression of the technology you can usually you can usually see the world in the same kind of way and so in that same way looking at psychedelics you could see like there is so many exciting possibilities here if we fully engage in the research same thing with neurolink if we fully engage so we go from a thousand channels of communication to the brain to billions of channels of communication of the brain and we figure out many of the details of how to do that safely with neurosurgery and so on that the world would just change completely in the same kind of way that elon is it's so ridiculous to hear him talk about uh symbiotic relationship between ai and uh the the human brain but it's like is it though like it's is it because it's i could see in 50 years that's going to be an obvious like everyone will have like obviously you have like why are we typing stuff in the computer doesn't make any sense that's stupid people used to type on a keyboard with a mouse what is that it seems pretty clear like we're gonna be there yeah like the only question is like what's the time frame is that gonna be 20 or is it 250 or 100 like how could we not and and the thing that i guess upsets with elon and others uh is the timeline he tends to do i think a lot of people tend to do that kind of thing i'd definitely do it which is like it'll be done this year right versus like it'll be done in 10 years the timeline is a little bit too rushed but from our leadership perspective it inspires the engineers to uh to do the best work of their life to really kind of believe because to do the impossible you have to first believe it which is a really important aspect of innovation and there's the delayed discounting aspect i talked about before it's like saying oh this is going to be a thing 20 50 years from now it's like what motivates anybody if you can and even if you're fudging it or like wishful thinking a little bit or let's just say airing on one side of the probability distribution like there's value in saying like yeah like there's a chance we could get this done in a year and you know what and if you set a goal for a year and you're not successful hey you might get it done in three years whereas if you had aimed at 20 years well you either would have never done it at all or you would have aimed at 20 years and then would have taken you 10. so there the other thing i think about this like in terms of his work and and i guess we've seen with psychedelics it's like there's a lack of appreciation for like sort of the variability you need in natural selection sort of extrapolating from biological you know from evolution like hey maybe he's wrong about focusing only on the cameras and not these other things be empirically driven it's like yeah you need to like when he's you know when you need to get the regulation is it safe enough to get this thing on the road those are real questions and be empirically driven and if he can meet the whatever standard is is relevant that's the standard and be driven by that so don't let it affect your ethics but if he's on the wrong path how wonderful someone's exploring that wrong path he's going to figure out it's the wrong path and like other people he's damn it he's doing something yeah like he's you know and and so appreciating that variability yeah you know that like it's it's valuable even if he's not on i mean this is all over the place in in science it's like a good theory one standard definition is that it generates testable hypotheses and like the ultimate model is never going to be the same as reality some models are going to work better than others like you know newtonian physics got us a long ways even if there was a better model like waiting and some models weren't as good as you know were never that successful but just even like putting them out there and testing we wouldn't know something is a bad model until someone puts it out anyway so yeah uh diversity of ideas is essential for progress yeah so we brought up consciousness a few times there's several things i want to kind of disentangle there so one you've recently wrote a paper titled consciousness religion and gurus pitfalls of psychedelic medicine so that's one side of it you've kind of already mentioned that these terms can be a little bit misused or are used in a variety of ways that they can they can be confusing but in a specific way as much as we can be specific about these things about the actual heart problem of consciousness or understanding what is consciousness this weird thing that it feels like it feels like something to experience things have psychedelics giving you some kind of insight on what is consciousness you've mentioned that it feels like psychedelics allows you to kind of dismantle your sense of self like step outside of yourself so that feels like somehow playing with this mechanism of consciousness and if it is in fact playing with a mechanism of consciousness using just a few chemicals it feels like we're very much in the neighborhood of being able to maybe understand the actual biological mechanisms of how consciousness can emerge from the brain so yeah there's there's a bunch there i think my preface is that i certainly have opinions that are outside that i can say here are my best speculations as a as a as just a person and an armchair philosopher and it's that philosophy is certainly not my my training and my expertise um so i have thoughts there but that that i recognize are completely in the realm of speculation that are like things that i would love to wrap empirical science around but that are you know there's no data and getting to the hard problem like no conceivable way even though i'm i'm very open like i'm hoping that that problem can be cracked and i do i as an armchair philosopher i do think that is a problem i don't think it can be dismissed as some people argue it's not even really a problem it strikes me that explaining just the existence of phenomenal consciousness is a problem so anyway i very much keep that divide in mind when i talk about these things what we can really say about what we've learned through science including by psychedelics versus like what i can speculate on in in terms of you know the nature of reality and consciousness but in terms of by and large skeptically i have to say psychedelics have not really taught us anything about the nature of consciousness i'm hopeful that they will they they have been used around certain i don't even know if features is the right term but things that are called consciousness so consciousness can refer to not only just phenomenal consciousness which is like you know the the source of the hard problem and what it is to be like nagel's um description but um the sense of self or so which can be a sort of like the the experiential self momentum or it can be like the narrative self the stringing together of story so those are things that i think can be and a little bit's been done with with psychedelics regarding that but i i think there's far more potential like but so like one story that unfolded is that psychedelics acutely having effects on the default mode network a certain a pattern of activation amongst a subset of brain areas that is associated with self-referential processing seems to be more active more communication between these um uh areas like uh the posterior cingulate cortex and the medial prefrontal cortex for example being parts of this that are and and others that are um tied with sort of thinking about yourself remembering yourself in the past projecting yourself into the future and so that it's an interesting story emerged when it was found that when psilocybin is on board you know in the person system that there's a d there's less communication amongst these these areas so with resting state fmri imaging that there's there's less synchronization or presumably communication between these areas and so i think it was it has been overstated into ah we see this is like this is the dissolving of the ego this is it the story made a whole lot of sense but there's several i think that story is really being challenged like one we see increasing number of drugs that are that that decouple that network including ones like that aren't psychedelic so this may just be a property frankly of being like you know screwed up you know like you know being out of your head being like like you know anytime you mess with the perception system maybe it screws up some some uh just our ability to just function in the holistically like we do in order yeah for the brain to perceive stuff to be able to map it to memory to connect things together to their their whole recur mechanism that that could just be messed with right and it couldn't i'm speculating it could be tied to more if you had to download a language everyday language like not feeling like yourself like so whether that be like really drunk or really hopped up on amphetamine or you know on like we found it like decoupling of the default mode network on salvan ornay which is a smokeable psychedelic which is a non-classic psychedelic but another one where like dmt where people are often talking to entities and that type of thing that was a really fun study to run but nonetheless most people say it's not a classic psychedelic and doesn't have some some of those phenomenal features that people report from classic psychedelics and not sort of the clear sort of ego loss type not at least not in the way that people report it with classic psychedelics so you get it with all these different drugs and so and then you also see just broad broad changes in network activity with other networks and so i think that story took off a little too soon although so i think in the story that the dmn the default mode network relating to the self and i know some neuroscientists it drives them crazy if you say that it's the ego and that's just like but self-referential processing if you go that far like that was already known before psychedelic psychedelics didn't really contribute to that the idea that this type of brain network activity was related to a sense of self but it is absolutely striking that psychedelics that people report with pretty high reliability these unity experiences that where people subjectively like like they report losing or again like the boundaries of the however you want to say it like like these these unity experiences i think we can do a lot with that in terms of figuring out the nature of the sense of self now i don't think that's the same as the hard problem or or the existence of phenomenal consciousness because you can build an ai system and you correct me if i'm wrong that like we'll pass a turing test in terms of demonstrating the qualities of like uh a sense of self it will talk as if there's a self and there's probably a certain like algorithm or whatever like computational like you know scaling up of computations that results and somehow and i think this is the argument with with humans but some have speculated this why do we have this illusion of the self that's that's evolved that and we might find this with a.i that like it works you know having a sense of self or and that stated wrong incorrectly like acting as if there is a an agent at play and behaviorally acting like you know there is a there is a self that might kind of work and so you can program a computer or a robot um to basically demonstrate have an algorithm like that and demonstrate that type of behavior and i think that's completely silent on whether there's an actual experience inside there i've been um struggling to find the right words and how i feel about that whole thing but because i've said it poorly before i've before said that there's no difference between the appearance and the actual existence of consciousness or intelligence or any of that what i really mean is the the more the appearance starts to be look like the thing the more there's this area where it's like i don't think i don't our whole idea of what is real and what is just an illusion is um not the right way to think about it so the whole idea is like if you create a system that looks like it's having fun the more it's realistically able to portray itself as having fun like there's a certain gray area which it's the system is having fun uh and same with intelligence same with consciousness and we humans want to simplify like it feels like the way we simplify the existence and the illusion of something uh is is uh missing the whole truth of the nature of reality which we're not yet able to understand like it's the one percent we only understand one percent currently so we don't have the right uh physics to talk about things we don't have the right science to talk about things but to me like the um uh faking it and actually it being true is um the the difference is much smaller than what humans would like to imagine that's my intuition but philosophers hate that because and uh guess what it's philosophers what have you actually built uh so like to me is that's the difference between philosophy and engineering it feels like if we push the creation the engineering like fake it until you make it all the way which is like fake consciousness until you realize holy crap this thing is conscious fake intelligence until you realize holy crap this is intelligence and from the my curiosity with psychedelics and just neurobiology neuroscience is like it feels i'm i love the armchair i love sitting in that armchair because it feels like at a certain point you're going to think about this problem and there's going to be an aha moment like that's what the armchair does sometimes science prevents you from really thinking right wait like it's really simple there's something really simple like there's some that could be some dance of chemicals that we're totally unaware of not from not from aspects of like which chemicals to combine with which biological architectures but more like we were thinking of it completely wrong that uh just just out of the blue like maybe the human mind is just like a radio that tunes into some other medium where consciousness actually exists like those uh weird sort of hypothetical like maybe we're just thinking about the human mind totally wrong maybe there's no such thing as individual intelligence maybe it is all collective intelligence between humans like maybe the intelligence is possessed in the communication of language between minds and then in fact consciousness is a property of that language uh versus a property of the individual minds and somehow the neurotransmitters will be able to connect to that so uh then ai systems can join that common collective intelligence that common language you know like just thinking completely outside of the box i just said how much a crazy thing i don't know but but thinking outside the box uh and there's something about subtle manipulation of the chemicals of the brain which feels like the best or one of the great chances of the scientific process leading us to an actual understanding of the hard problem so i am very hopeful that and so i i mean i'm a radical empiricist which i'm i'm very strong with with that like that's what you know so you know science isn't about ultimately being a materialist it's like it's about being an empiricist in my view and so for example i'm very fascinated by the so-called psi phenomenon you know like stuff that people just kind of reject out of hand um you know i kind of orient towards that stuff with with an idea of um you know hey look you know what we consider like anything exist is natural and so but the boundary of what what what we observe in nature like what we recognize as in nature moves like what we do today and what we know today would only be described as magic 500 years ago or even 100 years ago some of it so there will surely be things that like you explain these phenomena that just sound like completely they're supernatural now where there may be for some of it like some of it might turn out to be a complete bunk and some of it might turn out to be um it's just another layer of nature whether we're talking about multiple dimensions that are invoked or something we have don't even have the language towards and what you're saying about the moving together the model and the real thing of conscious like i'm very sympathetic to that so that's that part of like on the arm share side where i i want to be clear i can't say this as a scientist but just terms of speculating i i find myself attracted to these um more of the the sort of the the pan psychism ideas and that kind of makes sense to me i don't know if that's what you meant there but it seemed like related the sense that ultimately if if if you were completely modeling like it's like if you completely modeling unless you dismiss like the the idea that there is a phenomenal consciousness which i think is hard given that we all i seem like i have one that's really all i i know but if that's so compelling i can't just dismiss that like if you're if if you take that as a given then the only way for the model and the and the real thing to merge is if there is something baked into the nature of reality you know sort of like in the history of like there are certain just like fundamental forces or fundamental like and that and that's been useful for us and sometimes we find out that that's pointing towards something else or sometimes it's still seems like it's a fundamental and sometimes it's a placeholder for someone to figure out but there's something like this is just a given you know this is just you know and sometimes something like gravity seems like a very good place holder and there's something better that comes to replace it so so you know i kind of think about like consciousness and i didn't i kind of had this inclination before i knew there was a term for it um resalient monetism the idea that which is a a form of pain again i'm not i'm an armchair philosopher not a very good one broadly pansexism by the way is the idea that sort of consciousness permeates all matter in or it's a fundamental part of physics of the universe kind of thing so right and there's a lot of different flavors of it as as you're as you're alluding to and something that struck me as like consistent with some just you know inclinations of mine just total speculation is is this idea of um everything we know in science and with most of the stuff we think of physics you know really describes it's all interactions it's not the thing itself like there's a there there is something to this and this sounds very new agey which is why it's it's very difficult and i have a high bullshit like meter and everything but like in is-ness i mean i think about like huxley aldous huxley with his mescaline experience and doors of procession like there's an is-ness there in know alan watson like there is a a nature of being again very new age sounding but maybe there is something to in and when we say consciousness we think of like this human experience but maybe that's just that's so processed and so that's so far so it's so derivative of this kind of basic thing that we wouldn't even recognize the basic thing but the basic thing might just be this is not about the interaction between particles this is what it is like to exist as a particle and maybe it's not even particles maybe it's like space-time itself i mean again totally in the speculation and something out very space-time so it's funny because we don't have this neither the science nor the proper language to talk about it all we have is kind of uh little intuitions about there might be something in that direction of the darkness right to pursue and that that that in that sense i find pan psychism uh interesting in that like it does feel like there's something fundamental here that consciousness is it's not just like okay so the flip side consciousness could be just a very basic and trivial symptom like like a little hack of nature that's useful uh for like survival of an organism it's not something fundamental it's it's just very basic boring chemical thing that somehow has convinced us humans because we're very human-centric we're very self-centric that this is somehow really important but it's actually pretty obvious but or it could be something really fundamental to the nature of the universe so both of those are to me pretty compelling and i think eventually scientifically testable it is so frustrating that it's hard to design a scientific experiment currently but i think it's that's how noble prizes are won nobody did it right right until they do it and the reason i lean towards and again armchair speaking if i had to bet like a thousand dollars on which one of these ultimately be pro i would i would head i would lean towards i'd put my bets on on something like pan psychism rather than the the emergence of phenomenal con consciousness through complexity or computational complexity because although certainly what if there is some underlying fundamental consciousness it's clearly being processed and you know in this way through computation um in terms of resulting in our experience and the experience presumably of other animals but the reason i would blend on pansysm is to me occam's razor it just in terms of truly the hard problem like this at some point you have an inside looking out and even looking refers to vision and it doesn't that's just an example but just there's an inside experiencing something at some point of complexity all of a sudden you know you start from this objective universe and all we know about is interactions between things and things happen and at this certain level of complexity magically there's an inside that to me doesn't pass occam's razor as easily as maybe there is a fundamental property of the universe of you know there's both subjective and objective there's both interactions amongst things and there is the thing itself yes but but yeah so i i'm of two minds i agree with you totally on half my mind and the other half as i've seen looking at cellular automata a lot which is complete it sure does seem that we don't understand anything about complexity like the emergence the just the property in fact that could be a fundamental property of reality is something within the emergence from simple things interacting somehow miraculous things happen and like that i don't understand that that could be that could be fundamental that like something about the uh layers of abstraction uh like layers of reality like really small things interacting and then on another layer emerges actual complicated behavior even the underlying thing is super simple like that process we don't really don't understand either and that could be bigger than any of the things we're talking about that that's the the basic force behind everything that's happening in the universe is from simple things complex phenomena can happen and the thing that gives me pause is is that i'm concerned about a threshold there like how is it likely that now there may be and there may be some qualitative shift that in the realm of like we don't even we don't even understand complexity yet like you're saying like so maybe there is but i do think like if it if it is a result of the complexity well you know just having helium versus hydrogen is a form of complexity having the existence of stars versus clouds of gas is a complexity the the the entire universe has been this increasing complexity and so that kind of brings me back to then the other of like okay if there's if it's about complexity then we should then it exists at a certain level in these simple systems like a star or or uh you know they all have more complex psychism that's right but we humans uh the qualitative shift we might have evolved to appreciate certain kinds of thresholds right yeah i do think it's likely that this idea that whether or not there's an inner experience which is phenomenal it's the hard problem that acting like an agent like having an algorithm that basically like operates as if there is an agent that's clearly a thing that i think has worked and that there is a whole lot to figure out there that that um and i think psychedelics will be extremely helpful in figuring more out about that because they do seem to a lot of times eliminate that or whatever radically shift that sense of of self let me ask the craziest question indulge me for a second oh uh this is a joke look at what we've been talking about like okay no all the seatbelt on all of this is assigned all of that despite the the caveats about armchair i think is within the reach of science uh let me let me ask one that's kind of um also with the nursing science but as joe likes to say uh it's entirely possible right uh is it possible that uh with these dmt trips when you meet entities is it possible that these entities are extraterrestrial life forms like our understanding of little green men with aliens that show up is totally off i often think about this like what would actual extraterrestrial intelligence look like and my sense is it will look like very different from anything we can even begin to comprehend and how would it communicate and how would it communicate would it be necessarily spaceships right travel or could it be communicating through chemicals through if there's the pan psychism situation if there's something not if i almost for sure no we don't understand you know a lot about the function of our mind in connection to the fabric of uh the physics of the universe a lot of people seem to think we have theoretical physics pretty figured out i have my doubts because i'm pretty sure it always feels like we have everything figured out until we don't right but i mean there's no grand unifying theory yet right but even widely recognized we could be missing out like the concept of the universe just can be completely off like how many other universes are there all those all those kinds of things i mean just the the basic nature of information the uh time time all of those things yeah well yeah what yeah whether that's just like a thing we assign value to or that whether it's fundamental or not that's whole shank i could talk to chunkier forever about whether time is emergent or fundamental to the reality but is it possible that the entities we meet are actual alien life forms do you ever think about that yeah yeah yeah yeah i do and and i've to somebody relayed my cards out with by identifying as a radical empiricist you know it's like so the answer is it possible and i think you know ultimately if if you're a good scientist you got to say now that's at the extremes it's a like yes yes you know and it might get more interesting when you had to you you're asked to guess about the probability of that is that a one in a one in a million one in a trillion one in a one in uh more than the number of atoms in the universe uh probability and this one empiricist is like what what is a good testable like how would you know the answer to that question well how would you be able to validate it i mean well can you get some information that's verifiable like like um information that about some other planet that that or some aspect some and gosh it would be an interesting range but what range of discovery that we can anticipate we're gonna know within um you know whatever a few years next five ten twenty years um and seeing if you can get that predict that information now and then over time it might be verified you know the type of thing like you know part of einstein's work was ultimately verified not until decades and decades later at least certain aspects through the um through empirical observations um but but it's also possible that the the alien beings have a very different value system and perception of the world where all of this little capitalistic improvements that we're all after like predicting the concept of predicting the future too is like totally useless to to other life forms uh that have that perhaps think in a much different way maybe a more transcendent way i don't know but so they wouldn't even sign the consent form to be a participant in our and they wouldn't understand the nature of these experiments i mean that um maybe it's purely in the realm of uh the the consciousness the thing that we uh talked about so communicating in in a way that is totally different than the kinds of communication that we think of as on earth like what's the purpose of communication for us for us humans the purpose of communication is sharing ideas it feels like like converging like it's the dawkins like memes it's like we're sharing ideas in order to figure out how to uh collaborate together to get food into our systems and procreate and then like murder everybody in the neighboring tribe because they they'll steal our food like we are all about sharing ideas maybe uh it's possible to to have another alien life form that's more about sharing experiences you know like it's less about ideas i don't know and maybe that'll be us in a few years yeah how could it not like instead of explaining something laboriously to you like having people describe the ineffable psychedelic experience like if we could record that and then get the near a link of 50 years from now like oh just plug this into your just transferring these yeah it's like oh now you feel what it's what it's like and like in one sense like how could we not go there and then you get into the realm of especially when you throw time into it are the aliens us yeah in the future or even like a transcendental temporal like the us beyond time like i don't know like you get into this world there's a lot of possibilities yeah but i think you know there's one psychedelic researcher that's who did high-dose dmt um research in the 90s who speculated that um that and there was a lot of alien encounter experiences like maybe these are like entities from some other dimension or he labeled it as speculation but you know do you remember the name oh rick straussman who did yeah yeah the the dmt work he labeled it as speculation but you know i think that yeah i think we'd be wise to kind of you know find it's always that balance between being empirically grounded and skeptical but also not being and i think in science well often we are too closed yeah which relates to like you're talking about elon like in academia it's like often like i think you're punished for thinking or even talking about 20 years from now because it's just so far removed from your next grant or for your next paper that you're it's easy pickings yeah and you know that you're not allowed to speculate so i think though i'm a huge fan of i think the the best way to me at least to practice like science or to practice good engineering is to like do two things and just bounce off like spend most of the time doing the rigor of the day-to-day of what can be accomplished now in the engineering space or in the science like what can actually what can you construct an experiment around do like that the usual rigor of the scientific process but then every once in a while on a regular basis to step outside and talk about aliens and consciousness and uh we just walk along the line of things that are outside the reach of science currently uh free will the the illusion the illusion or the perception or the experience of free will of anything just just the the entirety of it being able to travel in time through warm holes it's like it's really useful to do that especially as a scientist like if that's all you do you go into a land where you're not actually able to think rigorously there's something at least to me that if you just hop back and forth you're able to i think do exactly the kind of injection of out of the box thinking to your regular day-to-day science that will ultimately lead to breakthroughs but you have to be the good scientist most of the time and that's consistent with what i think the great scientists of history like like in most of the the history you know the greats you know the newtons and uh you know einsteins i mean they were there was less of an in this change i think as time marched on but less of a separation between those realms it's like there's the inclination alpha it's like as a scientist and this is like you know this is science this is my work and then this like my inclination to say oh lex don't take me too seriously because this is my arm chair i'm not speaking as a scientist i'm bending over backwards you say you know to divide that self and maybe there's been less of there's been that evolution and and that's and like the greats like didn't see that i mean newton and you go back in time and it's like that obviously like connects to than religion especially that is the predominant world where newton like how much you know like how much time did he spend trying to like decode the bible and whatnot you know maybe that was a dead end but it's like if if you really believe in that in that particular religion and you're this mastermind and you're trying to figure things out it's not like oh this is what my job description is and this is what the grant wants it's like no i've got this limited time on the planet i'm going to figure out as much stuff as possible nothing is off the table and you're just putting it all together so this is kind of the trajectories maybe related to this the siloing in science like again related to my like oh i'm not a philosopher you know going whether you consider science or not not empirical science but like going to these different disciplines like you know the greats you know didn't yeah observe the yeah uh so speaking of uh the finiteness of our existence on on in this world uh so on the front of psychedelics and teaching you lessons as a researcher as a human being what have you learned about death about mortality about the finiteness of our existence are you yourself afraid of death and how has your view do you ponder it and has your view of your mortality changed with the research you've done yeah yeah so i do ponder it and uh are you afraid of death probably on a daily basis i ponder it i would i'd have to pick it apart more and say yeah i am afraid of dying like the the process of dying um i'm not afraid of being dead i mean i'm not afraid of i think it was penn jillet that said uh and he may have gotten it from someone else but like i'm not afraid of the year you know 1862 before i existed i'm not afraid of the year 2262 after i'm gone like it's gonna be fine but yeah you know dying like i'd i'd be lying if i said i wasn't afraid of you know dying and so there's both like the process of dying like yeah it's usually not good it'd be nice if it was after many many years and just sort of you know i'd rather not fall you know die in my sleep i'd rather kind of be conscious but sort of just die fade out with old age maybe but but like you know just being in an accident and like you know horrible diseases i've seen enough loved ones it's like yeah this is not good this is enough to be you know i'd like to say that i'm i'm peaceful and sort of balanced enough that i'm not concerned all but no like yeah i'm afraid of dying um but i'm also concerned about um i think about family like i i'm really i'm afraid or at least con you know concerned about like not being there like with a three-year-old not being there not being there for for him and my wife and my mom the rest the rest of her life i'm concerned about not i'm concerned more about like the harm that it would cause if i left prematurely and then kind of even bigger along the lines of some of the stuff that ford thinking we've been talking about i i think maybe way too much about just like and i'll never know the answer so even if i live to you know 120 like but like i want to know as much as i can but like how is this gonna work out like as humans are we and a big one i think is are we gonna and i don't think unfortunately i'm gonna learn it in my lifetime even if i lived to a ripe old age but well i don't know is this gonna work out like are we gonna escape the planet i think that's one of the biggies like are we gonna like the survival of the speed like i think the next like the time we're in now it's like with the nuclear weapons with pandemics and with um uh i mean we're gonna get to the point where anyone can can build a hydrogen bomb like you know it's like you just like the exact or engineer like the you know something that's a million times worse than covet and then you spread it it's like yeah we're getting to this period of and then not to mention climate change you know it's like although i think that's not there's probably going to be surviving humans with that regard you know but it could be really bad but these existential threats i think the only real guarantee that we're going to get another you name it thousand million whatever years is like diversity diver diversify our portfolio get get off the planet you know um don't leave this one hopefully we keep you know but like and i you know it's like either we're gonna get snuffed out like really quickly or we're gonna like if we if we reach that point and it's gonna be over the next like 100 200 years like like we're probably going to survive like like until like i mean you know like our sun like and even beyond that like like we're probably going to be talking about millions and millions of years it's like and we're we're i don't know in terms of the planet 4 billion years into this and depending on how you count our species you know we're you know we're millions of years into this and it's like it's this is like the point of the relay race where we can really screw up so that would make you feel pretty good when you're on your death bed 120 years old and there's something hopeful about there's a colony starting up on mars and it's like yeah titan like whatever you know like yeah like that we have these colonies out there that would tell me like yeah then at least we'd be good until like the you know hopefully probably until the the the sun goes red giant you know what i mean yeah rather than oh like 20 years from now when there's some someone with their finger on the nuclear button that just you know misperceives a you know the radar you know like the signal they they think russia's attacking they're really not or china and like that's probably how a nuclear accident war is going to start rather than eating or the like i said these other horrible things does it not make you sad that uh you won't be there if uh we are successful uh proliferating throughout the observable universe that you won't be there to experience any of it just yeah you go death right it's the death because you're still gonna die and it's still gonna be over right that's uh you know ernest becker and those folks really emphasize the the terror of death that if we're honest we'll discover if we search within ourselves which is like this thing is going to be over most of our existence is uh based on the illusion that is going to go forever and when you sort of realize it's actually going to be over like today like i might murder you at the end of this conversation uh it might be over today or like you go on going home this might be your last day in this earth and it's i mean uh like pondering that and i i suppose i suppose one thing to be me i i if i were to push back it's interesting is you actually i think you see comfort in the sadness of how unfortunate unfortunately would be for your family to not have you because the really even even the deepers yes but that's the simple fear even the deeper terror is like like this this thing doesn't last forever like i think uh i don't know they're like if it's hard to put the right words to it but it feels like that's not truly acknowledged by us by each of each of us yeah i think this is the i mean getting back to the psychedelics in terms of the people in our our work with cancer patients who um we had psilocybin sessions to help them and it did substantially help them um the vast majority um in terms of dealing with these existential issues and i think you know it's something we i could say that i really feel that i've come along in that both like being with folks who have died that are close to me and then also that work i think are the two biggies and sort of like you know i think i've come along and that that sort of acceptance of this like like it's not gonna last um any whether at the personal level or even at the species levels like at some point all the stars are going to fade out and it's going to be the realm of which is going to be the vast majority if it can unless there's a big crunch which apparently doesn't seem likely like most of the universe there's this blink of an eye that's happening right now that life is even possible like the era of stars so it's like we're going to fade out at some point like you know and you know then we get at this level of consciousness and like okay maybe there is life after death maybe there's maybe times an illusion maybe like that part i'm ready for like i'm i'm like you know like strap that that would be really great and i'm looking i'm not afraid of that at all it's like even if it's just strange like if i could push a button to enter that door i mean i'm not gonna you know die you're not gonna kill myself but it's like if i could take a peek at what that reality is or choose at the end of my life if i could choose of entering into a universe where there is an afterlife of something completely unknown versus one where there's none i think i'd say well let's see what's behind that that's a true scientist way of thinking if there's a door you're excited about opening and going in right but i am attracted to this idea like like you know it's and i recognize it's easier said than done to say i'm okay with not existing yeah it's like the real test is like okay check me on my deathbed you know it's like it's oh yes i'll be all right it is beautiful thing and the humility of surrendering and i really hope and i think i'd probably be more likely to be in that realm right now than i would like or check me when i get a terminal cancer diagnosis and i really hope i'm more in that realm but i i know enough about human nature to know that like i don't want to i can't really speak to that because i haven't been in that situation and i think there can be a beauty to that and the transcendence of like yeah and you know it was it was beautiful not just despite all that but because of that because ultimately there's going to be nothing and because we came from nothing and we dealt with all this shit the fact that there was still beauty and truth and connection like that you know like it just it's a beautiful thing but i i hope i'm in that it's easy to say that now like yeah do you think there's a a meaning to this thing we got going on uh life existence on earth to us individuals a psychedelic's researcher perspective or from just a human perspective those those merge together for me because it's it's just heart i've been doing this research for almost 17 years and and like not just the cancer study but so many times people like i remember a session in this in one of our studies someone who wasn't getting any treatment for anything but one of our healthy normal studies where he was contemplating the the suicide of his son um and just these i mean just like the most intense human experiences that you can have in the most vulnerable situations sometimes like people like you know and it's just like you have that have a and you just feel lucky to be part of that process that people trust you to let their guards down like that um like i don't know the meaning i think the meaning of life is is is to find meaning and i think i actually i think i just described it a minute ago it's like that transcendence of everything like the it's the beauty despite the the absolute ugliness it's the it's the and as a species and i think more about this like i think about this a lot it's the fact that we are i mean we're we come from filth i mean we're we're you know we're animals we come from like we're all descendant from murderers and rapists like we despite that background we are capable of this the self-sacrifice and the connection and and and figuring things out you know true science and other forms of truth you know seeking and and an artwork just the beauty of of of music and and other forms of art it's like the fact that that's possible is the meaning of of life i mean and ultimately that feels to be creating uh more and richer experiences the from a russian perspective uh both the dark the you mentioned the cancer diagnosis or losing a child to suicide or all those dark things is is still rich experiences and also the the beautiful creations the art the music the science that's also rich experience so somehow we're figuring out from just like psychedelics expand our mind to the possibility of experiences somehow we're able to figure out different ways as a society to expand the realm of experiences and from that would gain meaning somehow right and that's part of like this we're going across different levels here but like the idea that so-called bad trips or challenging experiences are so common in psychedelic experiences it's like that's a part of that like yeah it's tough and most of the important things in life are really really tough and scary and most of the things like like the death of a loved one like it told like the greatest learning experiences the things that make you who you are are are the horrors and you know it's like yeah we try to minimize them we try to avoid them but and i don't know i think we all need to get into the mode of like giving ourselves a break both personally and society societally i mean i went through like the the i think a lot of people do these days in my 20s like oh the humans are just kind of a disease on the planet and like and then in terms of our country in terms of the united states it's like oh we have all these horrible you know sins in our past and it's like i think about that like the i think about it like my my three-year-old it's like yeah you can construct a story where this is all just horrible you can look at that stuff and say this is all just horror you know where yard is like there's no logical answer to our you know rational answer to say we're not a disease on the planet from one lens we are you know you know and like there's you could just look at humanity as that like nothing but this horrible thing you can look at any you and you name the system you know you know modern medicine western medicine you know the university system and it's like you can dismiss everything so you know big farm like hopefully these vaccines work and then like yeah i'd like to you know like i'm kind of glad big pharma was a part of that like you know it's like the united states you can like point to the horrors like any other country that's been around a long time that has these legitimate horrors and kind of dismiss like these beautiful things like yeah we have this like modifiable constitutional republic that just like i still think is the best thing going you know um that that that as a model system of like how humans have to figure out how to work together it's like it's how there's no better system that i've come across yeah there's uh if we're willing to look for it there's a there's a beautiful court to a lot of things we've created uh yeah this country is a great example of that but most of the human experience has a beauty to it even the suffering right so the meaning is fine is is choosing to focus on that positivity and not forget it beautifully put yeah speaking of experiences this was one of uh my favorite experience on this podcast talking to you today matthew i hope we get a chance to talk again i hope to see you on joe rogan it's a huge honor to talk to you can't wait to read your papers uh thanks for talking today likewise i very much enjoyed it thank you thanks for listening to this conversation with matthew johnson and thank you to our sponsors brave a fast browser that feels like chrome but has more privacy preserving features neuro the maker of functional sugar-free gum and mints that i use to give my brain a quick caffeine boost for sigmatic the maker of delicious mushroom coffee and cash app the app i use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from terence mckenna nature loves courage you make the commitment and nature will respond to that commitment by removing impossible obstacles dream the impossible dream and the world will not grind you under it will lift you up this is the trick this is what all these teachers and philosophers who really counted who really touched the alchemical gold this is what they understood this is the shamanic dance in the waterfall this is how magic is done by hurling yourself into the abyss and discovering it's a feather bed thank you for listening and hope to see you next time you |
Michael Littman: Reinforcement Learning and the Future of AI | Lex Fridman Podcast #144 | the following is a conversation with michael littman a computer science professor at brown university doing research on and teaching machine learning reinforcement learning and artificial intelligence he enjoys being silly and lighthearted in conversation so this was definitely a fun one quick mention of each sponsor followed by some thoughts related to the episode thank you to simply safe a home security company i use to monitor and protect my apartment expressvpn the vpn i've used for many years to protect my privacy and the internet masterclass online courses that i enjoy from some of the most amazing humans in history and better help online therapy with a licensed professional please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that i may experiment with doing some solo episodes in the coming months or two the three ideas i have floating in my head currently is to use one a particular moment in history two a particular movie or three a book to uh drive a conversation about a set of uh related concepts for example i could use 2001 a space odyssey or x machina to talk about agi for one two three hours or i could do an episode on the yes rise and fall of hitler and stalin each in a separate episode using relevant books and historical moments for reference i find the format of a solo episode very uncomfortable and challenging but that just tells me that it's something i definitely need to do and learn from the experience of course i hope you come along for the ride also since we have all this momentum built up on announcements i'm giving a few lectures on machine learning at mit this january in general if you have ideas for the episodes for the lectures or for just short videos on youtube let me know in the comments that i still definitely read despite my better judgment and the wise sage device of the great joe rogan if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter lex friedman and now here's my conversation with michael littman i saw a video of you talking to charles this bell about westworld the tv series you guys were doing a kind of thing where you're watching new things together but let's rewind back is there a sci-fi movie or book or shows that you that was profound that had an impact on you philosophically or just like specifically something you enjoyed nerding out about yeah interesting i think a lot of us have been inspired by robots in movies the one that i really like is uh there's a movie called robot and frank which i think is really interesting because it's very near-term future where uh robots are being deployed as uh helpers in people's homes and it was it was and we don't know how to make robots like that at this point but it seemed very plausible it seemed very realistic or imaginable and i thought that was really cool because they did they're awkward they do funny things it raised some interesting issues but it seemed like something that would ultimately be helpful and good if we could do it right yeah he was an older cranky gentleman right he was an older cranky uh jewel thief yeah it's kind of funny little thing which is you know he's a dual thief and so he pulls the robot into his life which is like which is something you could imagine taking a home robotics thing and pulling into whatever quirky thing that's involved in your this is meaningful to you exactly so yeah and i think i think from that perspective i mean not all of us are jewel thieves and so when we bring our robots into it for yourself uh explains a lot about this apartment actually but no the idea that that people should have the ability to you know make this technology their own that that it becomes part of their lives and and i think that's it's hard for us as technologists to make that kind of technology it's easier to mold people into what we need them to be and um just that opposite vision i think is really inspiring and then there's a anthropomorphization where we project certain things on them because i think the robot was kind of dumb but i have a bunch of roombas that play with and they you immediately project stuff onto them much greater level of intelligence we'll probably do that with each other too much much greater degree of compass that's right one of the things we're learning from ai is where we are smart and where we are not smart yeah you also enjoy as people can see and i enjoyed myself uh watching you sing and even dance a little bit a little bit a little bit a little bit of dancing a little bit of dancing that's not quite my thing as a as a method of education or just in life you know in general so easy question what's the definitive objectively speaking top three songs of all time maybe something that you know uh to walk that back a little bit maybe something that others might be surprised by the three three songs that you kind of enjoy that is a great question that i cannot answer but instead let me tell you a story so pick a question you do want it that's right i've been watching the presidential debates and vice president debates and turns out yeah it's really you can just answer any question you want so so it's a related question [Laughter] yeah well said i really like pop music i've enjoyed pop music ever since i was very young so 60s music 70s music 80s music this is all awesome and then i had kids and i think i stopped listening to music and i was starting to realize that the like my musical taste had sort of frozen out and so i decided in 2011 i think to start listening to the top 10 billboard songs each week so i'd be on the on the treadmill and i would listen to that week's top 10 songs so i could find out what was popular now and what i discovered is that i have no musical taste whatsoever i like what i'm familiar with and so yeah the first time i'd hear a song it's the first week that was on the charts i'd be like and then the second week i was into it a little bit and the third week i was loving it and by the fourth week is like just part of me and so i'm afraid that i can't tell you the most my favorite song of all time because it's whatever i heard most recently yeah that's interesting people have told me that um there's an art to listening to music as well you can start to if you listen to a song just carefully like explicitly just force yourself to really listen you start to uh i did this when i was part of jazz band and fusion band in college is there's they you you start to hear the layers of the instruments you start to hear the individual instruments and you start to uh you can listen to classical music or to orchestra this way you can listen to jazz this way i mean uh it's funny to imagine you now to walk in that forward to listening to pop hits now as like a scholar listening to like cardi b or something like that or justin timberlake is he no not temple like bieber i guess they've both been in the top 10 since i've been listening they're still still up there oh my god i'm so clueless if you haven't heard justin timberlake's top 10 in the last few years there was one song that he did where the music video was set at essentially nurips oh wow oh the one with the robotics yeah yeah yeah yeah yeah yeah he's like at an academic conference and he and he's doing it he was presenting it was sort of a cross between the apple like steve jobs kind of talk and nurips um so i you know it's always fun when ai shows up in pop culture i wonder if he consulted somebody for that that's very that's really interesting so maybe on that topic i've seen your um your celebrity multiple dimensions but one of them is you've done cameos in different places i've seen you in a turbo tax commercial as like i guess the the brilliant einstein character and the the point is that turbo tax doesn't need somebody like you doesn't need a brilliant very few things need someone like me but yes they were specifically emphasizing the idea that you don't need to be a like a computer expert to be able to use their software how did you end up in that world i think it's an interesting story so i was teaching my class it was an intro computer science class for non-concentrators non-majors and sometimes when people would visit campus they would check in to say hey we want to see what a class is like can we sit on your class so a person came to my class who was the daughter of the brother of the hus husband of the best friend of my wife anyway basically a family friend came to campus to to check out brown and asked to come to my class and and came with her dad her dad is uh who i've known from various kinds of family events and so forth but he also does advertising and he said that he was recruiting scientists for this this this ad this this turbotax set of ads and he said we wrote the ad with the idea that we get like the most brilliant researchers um but they all said no so can you help us find the like b level scientists i'm like sure that's that's who i hang out with so that should be fine so i put together a list and i did what some people call the dick cheney so i included myself on the list of possible candidates uh you know with a little blurb about each one and why i thought it would make sense for them to to do it and they reached out to a handful of them but then they ultimately they youtube stalked me a little bit and they thought oh i think he could do this and um they said okay we're gonna offer you the commercial i'm like what so um it was it was such an interesting experience because it's it's they have another world the people who do like nationwide kind of ad campaigns and and television shows and movies and so forth it's quite a a remarkable system that they have going because like a set yeah so i went to uh it was just somebody's house that they rented in new jersey um but it in the in the commercial it's just me and this other woman in reality there were 50 people in that room and another i don't know half a dozen kind of spread out around the house in various ways there were people whose job it was to control the sun they were in the backyard on ladders putting filters up to try to make sure that the sun didn't glare off the window in a way that would wreck the shot so there was like six people out there doing that there was three people out there giving snacks the craft table there was another three people giving healthy snacks because that was a separate craft table there was one person whose job it was to keep me from getting lost and the i think the reason for all this is because so many people are in one place at one time they have to be time efficient they have to get it done this the morning they were going to do my commercial in the afternoon they were going to do a commercial of a mathematics professor from princeton they had to get it done no you know no wasted time or energy and so there's just a fleet of people all working as an organism and it was fascinating i was just the whole time just looking around like this is so neat like one person whose job it was to take the camera off of the camera man so that someone else whose job it was to remove the film canister because every couple's takes they had to replace the film because you know film gets used up it was just i don't know i was geeking out the whole time it was so fun how many takes did it take it looked the opposite like there was more than two people there it was very relaxing right yeah the super i mean the person who i was in the scene with um is a professional she's a you know uh she's an actor improv comedian okay in your community and when i got there they had given me a script as such as it was and then i got there and they said we're gonna do this as improv i'm like i don't know how to improv like this is not i don't know what this i don't know what you're telling me to do here don't worry she knows okay okay we'll see how this goes i get i guess i got pulled into the story because like where the heck did you come from i guess in the scene like how did you show up in this random person's house i don't know yeah well i mean the reality of it is i stood outside in the blazing sun there was someone whose job it was to keep an umbrella over me because i started to schvitz i started to sweat and so i would wreck the shot because my face was all shiny with sweat so there was one person who would dab me off had an umbrella um but yeah like the reality of it like why is this strange stalkery person hanging around outside somebody's house yeah we're not we're not sure when you have to look in we'll have to wait for the book but are you uh so you make you make like you said youtube you make videos yourself you make awesome parody sort of uh parody songs that kind of focus in on particular aspects of computer science how much those seem really natural how much production value goes into that do you also have a team of 50 people videos almost all the videos except for the ones that people would have actually seen were just me i write the lyrics i sing the song i i generally find a um like a backing track online because i'm unlike you can't really play an instrument and then i do in some cases i'll do visuals using just like powerpoint lots and lots of powerpoint to make it sort of like an animation the the most produced one is the one that people might have seen which is the overfitting video that i did with charles isbell um and that was produced by the georgia tech and udacity people because we were doing a class together it was kind of i usually do parody songs kind of to cap off a class at the end of a class so that one you're wearing so it's a this the thriller yeah you're wearing the michael jackson the red leather jacket the interesting thing with podcasting that you're also uh into is that i really enjoy is that there's not a team of people it's kind of more because you know the the there's something that happens when there's more people involved than just one person that just the way you start acting i don't know there's a censorship you're not given especially for like slow thinkers like me you're not and i think most of us are if we're trying to actually think we're a little bit slow and and careful it it kind of large teams get in the way of that and i don't know what to do with ice like that's the to me like if you know this it's very popular to criticize quote unquote mainstream media i but there is legitimacy to criticizing them the same i love listening to npr for example but every it's clear that there's a team behind it there's a commercial there's constant commercial breaks there's this kind of like rush of like uh okay i have to interrupt you now because we have to go to commercial just this whole it creates it destroys the possibility of nuanced conversation yeah exactly evian uh which charles uh isabel who i i talked to yesterday told me that evian is naive backwards which the fact that his mind thinks this way is just uh it's quite brilliant anyway there's a freedom to this podcast he's dr awkward which by the way is a palindrome that's a palindrome that i happen to know for from other parts of my life and i just you just throw it out well you know use it against charles dr awkward so what uh what was the most challenging parody song to make was it the thriller one hmm no that was really fun i wrote the lyrics really quickly um and then i gave it over to the product production team they recruited a a cappella group to to sing that went it went really smoothly it's great having a team because then you can just focus on the part that you really love which in my case is writing the lyrics uh for me the most challenging one not challenging in a bad way but challenging in a really fun way was i did one of this one of the parody songs i did is is about the halting problem in computer science the the fact that you can't create a program that can tell for any other arbitrary program whether it actually going to get stuck in infinite loop or whether it's going to eventually stop and so i i did it to an 80s song because that's i hadn't started my new thing of learning current songs and it was billy joel's the piano man nice which is a great song great song yeah yeah and sing me a song you get the piano man yeah yeah so the lyrics are great because first of all it rhymes uh not all songs rhyme i did i've done rolling stone songs which turn out to have no rhyme scheme whatsoever they're just sort of yelling and having a good time which makes it not fun from a parody perspective because like you can say anything but this you know the lines rhymed and there was a lot of internal rhymes as well and so figuring out how to sing with internal rhymes a proof of the halting problem was really challenging and it was i really enjoyed that process what about uh last question on this topic what about the dancing in the thriller video how many takes that take so i wasn't planning to dance they they had me in the studio and they gave me the jacket and it's like well you can't if you have the jacket and the glove like there's not much you can do yeah so i um i think i just danced around and then they said why don't you dance a little bit we there was a scene with me and charles dancing together they did not use it in the video but we recorded it um yeah yeah no it was it was pretty funny and charles who has this beautiful wonderful voice doesn't really sing he's not really a singer and so that was why i designed the song with him doing a spoken section and me doing things very like barry white yeah it's a smooth baritone yeah yeah it's great that was awesome so one of the other things charles said is that you know everyone knows you as like a super nice guy super passionate about teaching and so on uh what he said i don't know if it's true that despite the fact that you're you are cold like okay i will admit this finally for the first time that was that was me it's the johnny cash song the man in reno just to watch him die uh that you actually do have uh some strong opinions on some topics so if this in fact is true what uh strong opinions would you say you have is there ideas you think maybe an artificial intelligence machine learning maybe in life that you believe is true that others might you know some number of people might disagree with you on so i try very hard to see things from multiple perspectives there's there's this great calvin and harp's calvin and hobb's cartoon where cal do you know okay so calvin's dad is always kind of a bit of a foil and he he was he talked to calvin and just calvin had done something wrong the dad talks him into like seeing it from another perspective and calvin like this breaks calvin because he's like oh my gosh now i can see the opposite sides of things and so the it's it becomes like a cubist cartoon where there is no front and back everything's just exposed and it really freaks him out and finally he settles back down it's like oh good no i can make that go away but like i'm that i'm that i live in that world where i'm trying to see everything from every perspective all the time so there are some things that i've formed opinions about that i would be harder i think to disavow me of one is um the super intelligence argument and the existential threat of ai is one where i feel pretty confident in my feeling about that one like i'm willing to hear other arguments but like i am not particularly moved by the idea that if we're not careful we will accidentally create a super intelligence that will destroy human life let's talk about that let's get you in trouble and record your video it's like bill gates uh i think he said like some quote about the internet that that's just gonna be a small thing it's not gonna really go anywhere and i think uh steve ballmer said uh i don't know why i'm sticking on microsoft uh that's something that like smartphones are useless there's no reason why microsoft should get into smartphones that kind of so let's get let's talk about agi as agi is destroying the world we'll look back at this video and see no uh i think it's really interesting to actually talk about because nobody really knows the future so you have to use your best intuition it's very difficult to predict it but you have spoken about agi and the existential risks around it and sort of based on your intuition that we're quite far away from that being a serious concern relative to the other concepts we have can you maybe uh unpack that a little bit yeah sure so so as as i understand it that uh for example i read boston's book and a bunch of other reading material about this sort of general way of thinking about the world and i think the story goes something like this that we will at some point create computers that are smart enough that they can help design the next version of themselves which itself will be smarter than the previous version of themselves and eventually bootstrapped up to being smarter than us at which point we are essentially at the mercy of this sort of more powerful intellect which in principle uh we don't have any control over what its goals are and so if its goals are at all out of sync with our goals like the ex for example the continued existence of humanity we won't be able to stop it it'll be way more powerful than us and we will be toast so there's some i don't know very smart people who have signed on to that story and it's a it's a compelling story i once now i can really get myself in trouble i once wrote an op-ed about this specifically responding to some quotes from elon musk who has been you know on this very podcast uh more than once and well the e-e-a-i's summoning the demon that you get i think he said but then he came to providence rhode island which is where i live and said uh to the governors of all the states uh you know you're worried about entirely the wrong thing you need to be worried about ai you need to be very very worried about ai so uh and peop journalists kind of reacted to that and they wanted to get people's people's take and i was like okay my my my belief is that one of the things that makes elon musk so successful and so remarkable as an individual is that he believes in the power of ideas he believes that you can have you can if you know if you have a really good idea for getting into space you can get into space if you have a really good idea for a company or for how to change the way that people drive you just have to do it and and it can happen it's really natural to apply that same idea to ai you see these systems that are doing some pretty remarkable computational tricks uh demonstrations and then to take that idea and just push it all the way to the limit and think okay where does this go where is this going to take us next and if you're a deep believer in the power of ideas then it's really natural to believe that those ideas could be taken to the extreme and kill us so i think you know his strength is also his undoing because that doesn't mean it's true like it doesn't mean that that has to happen but it's natural for him to think that so another way to phrase the way he thinks and i find it very difficult to argue with that line of thinking uh so sam harris is another person from neuroscience perspective that things like that is saying well is there something fundamental in the physics of the universe that prevents this from eventually happening and this nebosh from things in the same way they're kind of zooming out yeah okay we humans now uh are existing in this like time scale of minutes and days and so our intuition is in this time scale of minutes hours and days but if you look at the span of human history is there any reason we you can't see this in in 100 years and like is there is there something fundamental about the laws of physics that prevent this and if it doesn't then it eventually will happen or will we will destroy ourselves in some other way it's very difficult i find to actually argue against that yeah me too and not sound like not sound like you're just like rolling your eyes uh i'm like i have like science fiction we don't have to think about it but even even worse than that which is like i don't know kids but like i gotta pick up my kids now like this okay i see there's more pressing shortcuts yeah there's more pressing short-term things that like uh stop over this existential crisis where much much shorter things like now especially this year there's cova so like any kind of discussion like that is like there's there's p you know there's pressing things uh today it's it's and then so the sam harris argument well like any day the exponential singularity can can occur it's very difficult to argue against i mean i don't know but part of his story is also he's he's not going to put a date on it it could be in a thousand years it could be in 100 years it could be in two years it's just that as long as we keep making this kind of progress it's ultimately has to become a concern i i kind of am on board with that but the thing that the the piece that i feel like is missing from that that way of extrapolating from the moment that we're in is that i believe that in the process of actually developing technology that can really get around in the world and really process and and and do things in the world in a sophisticated way we're going to learn a lot about what that means which that we don't know now because we don't know how to do this right now if you believe that you can just turn on a deep learning network and eventually give it enough compute and it'll eventually get there well sure that seems really scary because we won't we won't be in the loop at all we want we won't be helping to design or or target these kinds of systems but i don't i don't see that that feels like it is against the laws of physics because these systems need help right they need they need to surpass the the the difficulty the wall of complexity that happens in arranging something in the form that that will happen in yeah like i believe in evolution like i believe that the that that there's an argument right so there's another argument just to look at it from a different perspective that people say well i don't believe in evolution how could evolution it's it's sort of like a random set of parts assemble themselves into a 747 and that could just never happen yeah so it's like okay that's maybe hard to argue against but clearly 747s do get assembled they get assembled by us basically the idea being that there's a process by which we will get to the par the point of making technology that has that kind of awareness and in that process we're going to learn a lot about that process and we'll have more ability to control it or to shape it or to build it in our own image it's not something that is going to spring into existence like that 747 and we're just gonna have to contend with it completely unprepared it's very possible that in the context of the long arc of human history it will in fact spring into existence but that springing might take like if you look at nuclear weapons like even 20 years is a springing in in the context of human history and it's very possible just like with nuclear weapons that we could have i don't know what percentage you want to put at it but the the possibility could have knocked ourselves out yeah the possibility of human beings destroying themselves in the 20th century with nuclear weapons i don't know you can if you really think through it you could really put it close to like i don't know 30 40 percent given like the certain moments of crisis that happen so like i think one like fear in the shadows that's not being acknowledged is it's not so much the ai will run away is is that as it's running away we won't have enough time to uh think through how to stop it right fast takeoff or foom yeah i mean my much bigger concern i wonder what you think about it which is we won't know it's happening so i kind of that argument i think that there is an agi situation already happening with social media that our minds our collective intelligence of human civilization is already being controlled by an algorithm and like we're we're already super like the the level of a collective intelligence thanks to wikipedia people should donate to wikipedia to feed the agi man if we had a super intelligence that that was in line with wikipedia's values that it's a lot better than a lot of other things i can imagine i've i trust wikipedia more than i trust facebook or youtube as far as trying to do the right thing from a rational perspective yeah now that's not where you were going i understand that but it it it does strike me that there's sort of smarter and less smart ways of of exposing ourselves to each other on the internet yeah the interesting thing is that wikipedia and social media have very different forces you're right i mean wikipedia if if agi was wikipedia it'd be just like this cranky overly competent editor of uh articles uh you know there's there's something to that but the social media aspect is is is not so the vision of agis is as a separate system that's super intelligent that's super intelligent that's one key little thing i mean there's the paper clip argument that's super dumb but super powerful systems but with social media you have a relatively like algorithms we may talk about today very simple algorithms that when uh something charles talks a lot about which is interactive ai when they start like having at scale like tiny little interactions with human beings they can start controlling these human beings so a single algorithm can control the minds of human beings slowly to what we might not realize it could start wars it could start it can change the way we think about things it feels like in the long arc of history if i were to sort of zoom out from all the outrage and all the tension on social media that it's progressing us towards uh better and better things it feels like chaos and toxic and all that kind of stuff but it's chaos and toxic yeah but it feels like actually the chaos and toxic is similar to the kind of debates we had from the founding of this country you know there was a civil war that happened over that over that period and ultimately it was all about this tension of like something doesn't feel right about our implementation of the core values we hold as human beings and they're constantly struggling with this and that results in people calling each other uh like just just being shitty to each other on twitter but i ultimately the algorithm is managing all that and it feels like there's a possible future in which that algorithm controls us to into the direction of self-destruction whatever that looks like yeah so so all right i do believe in the power of social media to screw us up royally i do believe in the power of social media to benefit us too i do think that we're in a yeah it's sort of almost got dropped on top of us and now we're trying to as a culture figure out how to cope with it there's a sense in which i don't know there's there's some arguments that say that for example i guess college-age students now late college-age students now people who are in middle school when when social media started to really take off maybe maybe really damaged like me this may have really hurt their development in a way that we don't have all the implications of quite yet that's the generation who if and i hate to make it somebody else's responsibility but like they're the ones who can fix it they're the ones who can who can figure out how do we keep the good of this kind of technology without letting it eat us alive and if they're successful we move on to the next phase the next level of the game if they're not successful then yeah then we're going to wreck each other we're going to destroy society so you're going to in your old age sit on the porch and watch the world burn because the tick tock generation that uh i believe well so my this is my kids age right and that's certainly my daughter's age and she's very tapped in to social stuff but she's also she's trying to find that balance right of participating in it and then getting the positives of it but without letting it eat her alive um and i think sometimes she ventures hopes just to watch this sometimes i think she ventures a little too far and is in and is consumed by it and other times she gets a little distance um and if you know if there's enough people like her out there they're gonna they're gonna navigate this this choppy waters that's that's an interesting uh skill actually to develop i talked to my dad about it you know i've uh now somehow this podcast in particular but other reasons has received a little bit of attention and with that apparently in this world even though i don't shut up about love and i'm just all about kindness i i have now a little mini army of trolls oh it's kind of hilarious actually but it also doesn't feel good but it's a skill to learn to not look at that like to moderate actually how much you look at that the discussion i have with my dad is similar to uh it doesn't have to be about trolls it could be about checking email which is like if you're anticipating you know there's uh my dad runs a large institute at drexel university and there could be stressful like emails you're waiting like there's drama of some kind and so like there's a temptation to check the email if you send an email you cut it and that pulls you in into it doesn't feel good and it's a skill that he actually complains that he hasn't learned i mean he grew up without it so he hasn't learned the skill of how to shut off the internet and walk away and i think young people while they're also being quote-unquote damaged by like uh you know being bullied online all those stories which are very like horrific you basically can't escape your bullies these days when you're growing up but at the same time they're also learning that skill of how to be able to shut off uh the like disconnect with it be able to laugh at it not take it too seriously it's fascinating like we're all trying to figure this out just like you said it's been dropped on us and we're trying to figure it out yeah i think that's really interesting and i i guess i've become a believer in the human design which i feel like i don't completely understand like how do you make something as robust as us like we're so flawed in so many ways and yet and yet you know we dominate the planet and we do seem to manage to get ourselves out of scrapes eventually not necessarily the most elegant possible way but somehow we get we get to the next step and i don't know how i'd make a machine do that i i i generally speaking like if i train one of my reinforcement learning agents to play a video game and it works really hard on that first stage over and over and over again and it makes it through it succeeds on that first level and then the new level comes and it's just like okay i'm back to the drawing board and somehow humanity we keep leveling up and then somehow managing to put together the skills necessary to achieve success some semblance of success in that next level too and you know i hope we can keep doing that you mentioned reinforcement learning so you've have uh a couple years in the field no quite you know quite a few quite a long career in artificial intelligence broadly but reinforcement learning specifically can you maybe give a hint about your sense of the history of the field and in some ways has changed with the advent of deep learning but has a long roots like how is it weaved in and out of your own life how have you seen the community change or maybe the ideas that it's playing with change i've had the privilege the pleasure of being of having almost a front row seat to a lot of this stuff and it's been really really fun and interesting so uh when i was in college in the 80s early 80s uh the neural net thing was starting to happen and i was taking a lot of psychology classes a lot of computer science classes as a college student and i thought you know something that can play tic-tac-toe and just like learn to get better at it that ought to be a really easy thing so i spent almost almost all of my what would have been vacations during college like hacking on my home computer trying to teach it how to play tic-tac-toe and programming language basic oh yeah that's that's i was i that's my first language that's my native language is that when you first fell in love with computer science just like programming basic on that uh what was the computer do you remember i had i had a trs-80 model one before they were called model ones because there was nothing else uh i got my computer in 1979 uh instead so i was i was i would have been bar mitzvahed but instead of having a big party that my parents threw on my behalf they just got me a computer because that's what i really really really wanted i saw him in the in the in the mall in radio shack and i thought what how are they doing that i would try to stump them i would give them math problems like one plus and then in parentheses two plus one yeah and i would always get it right i'm like how do you know so much message like i've had to go to algebra class for the last few years to learn this stuff and you just seem to know so i was i was i was smitten and i got a computer and i think ages 13 to 15 i have no memory of those years i think i just was in my room with the computer listening to billy joel communing possibly listening to the radio listening to billy joel that was the one album i had uh on vinyl at that time and um and then i got it on cassette tape and that was really helpful because then i could play it i didn't have to go down to my parents wi-fi or hi-fi sorry uh and at age 15 i remember kind of walking out and like okay i'm ready to talk to people again like i've learned what i need to learn here and um so yeah so so that was that was my home computer and so i went to college and i was like oh i'm totally going to study computer science i opted the college i chose specifically had a computer science major the one that i really wanted the college i really wanted to go to didn't so bye-bye to them which college did you go through so i went to yale uh princeton would have been way more convenient and it was just beautiful campus and it was close enough to home and i was really excited about princeton and i visited i said so computer science major like well we have computer engineering i'm like oh i don't like that word engineering i like if you're science i really i want to do like you're saying hardware and software they're like yeah like i just want to do software i i couldn't care less about hardware you grew up in philadelphia i grew up outside philly yeah yeah okay uh so the you know local schools were like penn and drexel and uh temple like everyone in my family went to temple at least at one point in their lives except for me so yeah philly philly family yale had a computer science department and that's when you it's kind of interesting you said 80s and you're all that works that's when you know that which is a hot new thing or a hot thing period uh so what is that in college when you first learned about neural networks yeah yeah was she learned like it was in a psychology class not in a cs wow yeah was it psychology or cognitive science or like do you remember like what context it was yeah yeah yeah so so i was a i've always been a bit of a cognitive psychology groupie so like i studied computer science but i like i like to hang around where the cognitive scientists are because i don't know brains man they're like they're wacky cool and they have a bigger picture view of things they're a little less engineery i would say they're more they're more interested in the nature of cognition and intelligence and perception it's called like the vision system work they're asking always bigger questions now with the deep learning community there i think more there's a lot of intersections but i do find in that the neuroscience folks actually and uh cognitive psychology cognitive science folks are starting to learn how to program how to use your own artificial neural networks and they are actually approaching problems in like totally new interesting ways it's fun to watch that grad students from those departments like approach the problem of machine learning right they come in with a different perspective yeah they don't care about like your imagine that data set or whatever they they want like to understand the the like the basic mechanisms at the at the neuronal level and the functional level of intelligence it's kind of it's kind of cool to see them work but yeah okay so you always you're always a group you have cognitive psychology yeah yeah and so uh so it was in a class by richard garrick he was kind of my my favorite uh psych professor in college and i took uh like three different classes with him and yeah so that we they were talking specifically the class i think was kind of a there was a big paper that was written by stephen pinker and uh prince i don't i'm blanking on prince's first name but prince and pinker and prince they wrote kind of a they were at that time kind of like ah i'm blanking on the names of the current people um the cognitive scientists who are complaining a lot about deep networks oh uh gary gary marcus sorry marcus and who else i mean there's a few but gary gary's the most feisty sure gary's very feisty and with this with his co-author they they you know they're kind of doing these kind of takedowns where they say okay well yeah it does all these amazing amazing things but here's a shortcoming here's a shortcoming here's your shortcoming and so the pinker prince paper is kind of like the that generation's version of marcus and davis right where they're they're trained as cognitive scientists but they're looking skeptically at the results in the in the artificial intelligence neural net kind of world and saying yeah it can do this and this and this but like it can't do that and it can't do that and it can't do that maybe in principle or maybe just in practice at this point but but the fact of the matter is you're you've narrowed your focus too far to be impressed you know you're impressed with the things within that circle but you need to broaden that circle a little bit you need to look at a wider set of problems and so um so we have so i was in this seminar in college that was basically a close reading of the pinker prince paper which was like really thick there was a lot going on in there and um and and it talked about the reinforcement learning idea a little bit i'm like oh that sounds really cool because behavior is what is really interesting to me about psychology anyway so making programs that i mean programs are things that behave people are things that behave like i want to make learning that learns to behave in which way was reinforcement learning presented is this uh talking about human and animal behavior or are we talking about actual mathematical constructs ah that's right so that's a good question right so this is i think it wasn't actually talked about as behavior in the paper that i was reading i think that it just talked about learning and to me learning is about learning to behave but really neural nets at that point were about learning like supervised learning so learning to produce outputs from inputs so i kind of tried to invent reinforcement learning i uh when i graduated i joined a research group at bellcore which had spun out of bell abs recently at that time because of the divestiture of the of long distance and local phone service in the 1980s 1984 and i was in a group uh with dave ackley who was the first author of the boltzmann machine paper so the very first neural net paper that could handle xor right so xor sort of killed neural nets the very first the zero with the first winter yeah um the the perceptron's paper and hinton along with his student dave ackley and and i think there was other authors as well showed that no no with both machines we can actually learn non-linear concepts and so everything's back on the table again and that kind of started that second wave of neural networks so dave ackley was he became my mentor at bellcore and we talked a lot about learning and life and computation and how all these things fit together now dave and i have a podcast together so um so i get to kind of enjoy that sort of his his perspective uh once again even even all these years later and so i said so i said i was really interested in learning but in the concept of behavior and he's like oh well that's reinforcement learning here and he gave me rich sutton's 1984 td paper so i read that paper i honestly didn't get all of it but i got the idea i got that they were using that he was using ideas that i was familiar with in the context of neural nets and and like sort of backprop uh but with this idea of making predictions over time i'm like this is so interesting but i don't really get all the details i said to dave and dave said oh well why don't we have him come and give a talk and i was like wait what you can do that like these are real people i thought they were just words i thought it was just like ideas that somehow magically seeped into paper he's like no i i i know rich like we'll just have him come down and and he'll give a talk and so i was you know my mind was blown and uh so rich came and he gave a talk at bellcore and he talked about what he was super excited which was they had just figured out at the time uh q learning so uh watkins had visited the rich sutton's lab at umass or it's andy barto's lab that rich was a part of and um he was really excited about this because it resolved a whole bunch of problems that he didn't know how to resolve in the in the earlier paper and so uh for people who don't know td temporal difference these are all just algorithms for reinforcement learning right and td separate difference in particular is about making predictions over time and you can try to use it for making decisions right because if you can predict how good a future action and action outcomes will be in the future you can choose one that has better and or but the theory didn't really support changing your behavior like the predictions had to be of a consistent process if you really wanted it to work and one of the things that was really cool about q-learning algorithm for reinforcement learning is it was off policy which meant that you could actually be learning about the environment and what the value of different actions would be while actually figuring out how to behave optimally yeah so that was a revelation yeah and the proof of that is kind of interesting i mean that's really surprising to me when i first read that and then enriched rich sutton's book on the matter it's it's kind of beautiful that a single equation can capture an equation one line of code and like you can learn anything yeah like enough time so equation and code you're right like you can the code that you can arguably at least if you like squint your eyes can say this is all of intelligence is that you can implement that in a single wall i think i started with lisp which is uh shout out to lisp uh like a single line of code key piece of code maybe a couple that you could do that it's kind of magical it's uh feels too good to be true well and it sort of is yeah it's kind of kind of it seems to require an awful lot of extra stuff supporting it but yeah but nonetheless the ideas the the idea is really good and as far as we know it is it is a very reasonable way of trying to create adaptive behavior behavior that gets better at something over time did you find the idea of optimal uh at all compelling that you could prove that it's optimal so like one part of computer science that it makes people feel warm and fuzzy inside is when you can prove something like that a sorting algorithm worst case runs and and log n and it makes everybody feel so good even though in reality it doesn't really matter what the worst case is what matters is like does this thing actually work in practice on this particular actual set of data that i that i enjoy did you so here's that here's a place where i have maybe a strong opinion uh-oh which is like you're right of course but no no like so so the what makes worst case so great right if you have a worst case analysis so great is that you get modularity you can take that thing and plug it into another thing and still have some understanding of what's going to happen when you click them together right if it just works well in practice in other words with respect to some distribution that you care about when you go plug it into another thing that distribution can shift it can change and your thing may not work well anymore and you want it to and you wish it does and you hope that it will but it might not and then ah so you're so so you're saying you don't like machine learning but we have some positive theoretical results for these things you know you can come back at me with yeah but they're really weak and yeah they're really weak and and you can even say that you know sorting algorithms like if you do the optimal sorting algorithm it's not really the one that you want and that might be true as well but but it is the modularity is a really powerful statement really as an engineer you can then assemble different things you can count on them to be i mean it's interesting it's it's a balance like with everything else in life you don't want to get too obsessed i mean this is what computer scientists do which they potentially get obsessed they over optimize things or they start by optimizing them they over optimize yeah so it's it's easy to like get really granular about this thing but like the step from an n squared to an n log n sorting algorithm is a big leap for most real-world systems no matter what the actual behavior of the system is that's a big leap and the same can probably be said for other kind of first leaps that you would take on a particular problem like it's the picking the low hanging fruit or whatever the equivalent of doing the not the dumbest thing but the next to the dumbest thing is picking the most delicious reachable fruit yeah most delicious reachable fruit i don't know why that's not a saying and yeah okay so uh so you then this is the 80s and this kind of idea starts to percolate of uh yeah at that point i got to re i got to meet rich sutton so everything was sort of downhill from there and that was that was really the pinnacle of everything um but then i you know then i felt like i was kind of on the inside so then as interesting results were happening i could like check in with with rich or with jerry tessaro who had a huge impact on uh kind of early thinking in in temporal difference learning and reinforcement learning and showed that you could do you could solve problems that we didn't know how to solve any other way and so that was really cool so as good things were happening i would hear about it from either the people who were doing it or the people who were talking to the people who are doing it and so i was able to track things pretty well through through the 90s so what uh wasn't most of the excitement on reinforcement learning in the 90s era with what is it td gamma like what's the role of these kind of little like fun game playing things and breakthroughs about uh get you know exciting the community was that like what were your because uh you've also built across or we're part of building a crossword a puzzle uh solver program yeah solving program uh called proverb so so you were interested in this as as a problem like in forming using games to understand how to build uh intelligent systems so like what did you think about tt gamble like what did you think about that whole thing in the 90s yeah i mean i found the td gammon result really just remarkable so i had known about some of jerry's stuff before he did td gammon he did a system just more vanilla well not not entirely vanilla but a more classical backproppy kind of uh network for playing back ammon where he was training it on expert moves so it was kind of supervised but the way that it worked was not to mimic the actions but to learn internally an evaluation function so to learn well if the expert chose this over this that must mean that the expert values this more than this and so let me adjust my weights to make it so that the network evaluates this as being better than this so it could learn from from human preferences it could learn its own preferences and then when he took the step from that to actually doing it as a full-on reinforcement learning problem where you didn't need a trainer you could just let it play that was that was remarkable right and so i think as as humans often do as we've done in the recent past as well people extrapolate it's like oh well if you can do that which is obviously very hard then obviously you could do all these other problems that we that we want to solve that we know are also really hard and it turned out very few of them ended up being practical partly because i think neural nets certainly at the time were struggling to be consistent and reliable and so training them in a reinforcement learning setting was a bit of a mess i had i don't know generation after generation of like master students who wanted to do value function approximation basically learn reinforcement learning with neural nets and over and over and over again we were failing we couldn't get the good results that jerry tessaro got i now believe that jerry is a neural net whisperer he has a particular ability to get neural networks to do things that other people would find impossible and it's not the technology it's the technology and jerry together yeah and which i think speaks to the role of the human expert in the process of machine learning right it's so easy we're so drawn to the idea that that it's the technology that is that is where the power is coming from that i think we lose sight of the fact that sometimes you need a really good just like i mean no one would think hey here's this great piece of software here's like i don't know gnu emacs or whatever um doesn't that prove that computers are super powerful and basically going to take over the world it's like no stallman is a hell of a hacker right so he was able to make the code do these amazing things he couldn't have done it without the computer but the computer couldn't have done it without him and so i think people discount the role of people like jerry who who um who have just a particular particular set of skills on that topic by the way as a small side note i tweeted emacs is greater than vim yesterday and deleted deleted the tweet 10 minutes later when i realized you're you were honest i started a war yeah i was like oh i was just kidding i i was just being um walk so people still feel passionately about that particular piece of uh i don't get that because emacs is clearly so much better i i don't understand but you know why do i say that because i cause like i spent a block of time in the 80s um making my fingers know the emacs keys and now like that's part of the thought process for me like i need to express and if you take that if you take my emacs key bindings away i become little i can't express myself i'm the same way with the i don't know if you know what what it is but it's a kinesis keyboard which is uh this butt shaped keyboard yes i've seen them yeah and they're very uh i don't know sexy elegant yeah they're just beautiful yeah they're they're gorgeous uh way too expensive but uh the the problem with them similar with emacs is when once you learn to use it it's harder to use other things it's hard to use other things there's this absurd thing where i have like small elegant lightweight beautiful little laptops and i'm sitting there in a coffee shop with a giant kinesis keyboard and a sexy little laptop it's absurd but it you know like i used to feel bad about it but at the same time you just kind of have to sometimes it's back to the billy joel thing you just have to throw that billy joe record and throw taylor swift and justin bieber to the wind so see but i like them now because i cause again i have no musical taste like like now that i've heard justin bieber enough i'm like i really like his songs and taylor swift not only do i like her songs but my daughter's convinced that she's a genius and so now i basically have i'm signed on to that so so yeah that that speaks to the back to the robustness of the human brain that speaks to the neuroplasticity that you can just you can you can just like a mouse teach yourself to a problem dog teach yourself to enjoy taylor swift i'll try it out i don't know i try you know what it has to do with just like acclimation right just like you said a couple weeks yeah that's an interesting experiment i'll actually try that like i'll listen that wasn't the intent of the experiment just like social media it wasn't intended as an experiment to see what we can take as a society but it turned out that way i don't think i'll be the same person on the other side of the week listening to taylor swift but let's try it it's more compartmental don't be so worried like it's like i get that you can be worried but don't be so worried because we compartmentalize really well and so it won't bleed into other parts of your life you won't start i don't know wearing red lipstick or whatever like it's it's fine it's changed fashion and everything but you know what the the thing you have to watch out for is you'll walk into a coffee shop once we can do that again and recognize the song and you'll be no you won't know that you're singing along until everybody in the coffee shop is looking at you and then you're like that wasn't me yeah that's the you know people are afraid of agi i'm afraid of the taylor uh the tail taylor swift takeover yeah and i mean people should know that td gammon was i get would you call it do you like the terminology of self play by any chance so like systems that learn by playing themselves just i don't know if it's the best word but uh so what's what's the problem with that term okay so it's like the big bang like it's it's like talking to serious physicists do you like the term big bang and when when it was early i feel like it's the early days of self-play i don't know maybe it was just previously but i think it's been used by only a small group of people uh and so like i think we're still deciding is this ridiculously silly name a good name for the cons potentially one of the most important concepts in artificial intelligence okay it depends how broadly you apply the term so i used the term in my 1996 phd dissertation wow the actual terms of yeah because because tessaro's paper was something like um training up an expert backgammon player through self-play so i think it was in the title of his paper okay if not in the title it was definitely a term that he used there's another term that we got from that work is rollout so i don't know if you do you ever hear the term rollout that's a backgammon term that has now applied generally in computers well at least in ai because of td gammon yeah that's fascinating so how is health play being used now and like why is it does it does it feel like a more general powerful concept sort of the idea of well the machine's just going to teach itself to be smart yeah so that's that's where maybe you can correct me but that's where you know the continuation of the spirit and actually like literally the exact algorithms of td gammon are applied by deep mind and open ai to learn games that are a little bit more complex that when i was learning artificial intelligence go was presented to me with artificial intelligence the modern approach i don't know if they explicitly pointed to go in those books as like unsolvable kind of thing like implying that these approaches hit their limit in this with these particular kind of games so something i don't remember if the book said it or not but something in my head or was the professors instilled in me the idea like this is the limits of artificial intelligence of the field like it instilled in me the idea that if we can create a system that can solve the game of go we've achieved agi that was kind of i didn't explicitly like say this but it that was the feeling and so from i was one of the people that it seemed magical when a learning system was able to to beat a uh a human world champion at the game of go and even more so from that that was alphago even more so with alphago zero then kind of renamed and advanced into alpha zero beating a world champion or world-class player without any supervisors learning on expert games we're doing only through by playing itself so that is i don't know what to make of it i think it would be interesting to hear what your opinions are on just how exciting surprising profound interesting or boring the breakthrough performance of alpha zero was okay so alphago knocked my socks off that was that was so remarkable which aspect of it that they they got it to work that they actually were able to leverage a whole bunch of different ideas integrate them into one giant system just the software engineering aspect of it is mind-blowing i don't i i've never been a part of a program as complicated as the program that they built for that and um and just the you know like like jerry tessaro is a neural net whisperer like you know david silver is a kind of neural net whisperer too he was able to coax these networks and these new way out their architectures to do these you know solve these problems that um as you said you know when we were learning from uh ai no one had an idea how to make it work it was it was remarkable that um these you know these these techniques that were so good at playing chess and they could beat the world champion in chess couldn't beat you know your typical go playing teenager and go so the fact that that you know in a very short number of years we kind of ramped up to uh trouncing people and go just blew me away so you're kind of focusing on the engineering aspect which is also very surprising i mean there's something different about large well-funded companies i mean there's a compute aspect to it too sure like that of course i mean that's similar to deep blue right with uh with ibm like there's something important to be learned and remembered about a large company taking the ideas that are already out there and investing a few million dollars into it or or more and so you're kind of saying the engineering is kind of fascinating both on the with alphago is probably just gathering all the data right of the expert games like organizing everything actually doing distributed supervised learning and to me see the engineering i kind of took for granted to me philosophically being able to persist in the in the face of like long odds because it feels like for me i'll be one of the skeptical people in the room thinking that you can learn your way to to beat go like it sounded like especially with david silver it sounded like david was not confident at all it's like it was like not it's funny how confidence works yeah it's like you're not like cocky about it like but right because if you're cocky about it you kind of stop and stall and don't get anywhere yeah but there's like a hope that's unbreakable maybe that's better than confidence it's a kind of wishful hope and a little dream and you almost don't want to do anything else you kind of keep doing it that's that seems to be the story and but with enough skepticism that you're looking for where the problems are and fighting through them yeah because you know there's got to be a way out of this thing yeah and for him it was probably there's there's a bunch of little factors that come into play it's funny how these stories just all come together like everything he did in his life came into play which is like a love for video games and also a connection to so the the 90s had to happen with td gammon and so on yeah in some ways it's surprising maybe you can provide some intuition to it that not much more than td gammon was done for quite a long time on the reinforcement learning front yeah is that weird to you i mean like i said the the students who i worked with we tried to get basically apply that architecture to other problems and we consistently failed there were a couple a couple really nice demonstrations that ended up being in the literature there was a paper about controlling elevators right where it's it's like okay can we modify the heuristic that elevators use for deciding like a bank of elevators for deciding which floors we should be stopping on to maximize throughput essentially and you can set that up as a reinforcement learning problem and you can you know have a neural net represent the value function so that it's taking where all the elevators where the button pushes you know this high dimensional well at the time high dimensional input um you know a couple dozen dimensions and turn that into a prediction as to oh is it going to be better if i stop at this floor or not and ultimately it appeared as though for the standard simulation distribution for people trying to leave the building at the end of the day that the neural net learned a better strategy than the standard one that's implemented in elevator controllers so that that was nice there was some work that satender singh it all did on uh handoffs with cell phones uh you know deciding when when should you hand off from this cell tower to this cell okay communication networks yeah yeah and so a couple things seemed like they were really promising none of them made it into production that i'm aware of and neural nets as a whole started to kind of implode around then and so there just wasn't a lot of air in the room for people to try to figure out okay how do we get this to work in the rl setting and then they they found their way back in in 10 in 10 plus years so you said alphago was impressive like it's a big spectacle is there right so then alpha zero so i think i may have a slightly different opinion on this than some people so um i talked to tinder saying in particular about this so satinder was uh like rich sutton a student of antibartow so they came out of the same lab very influential machine learning reinforcement learning researcher uh now deep mind uh as just as is rich though different sites the two of them he's in alberta rich is in alberta and uh satinder would be in england but i think he's in england from michigan at the moment uh but the but he was yes he was much more impressed with uh alphago zero which is didn't didn't get a kind of a bootstrap in the beginning with human trained games yes just was purely self-play though the first one alpha go was also a tremendous amount of self-play right they started off they kick-started the the action network that was making decisions but then they trained it for a really long time using more traditional temporal difference methods um so so as a result i didn't it didn't seem that different to me like it seems like yeah why wouldn't that work like once once it works it works so but he he found that that removal of that extra information to be breathtaking like that that's a game changer to me the first thing was more of a game changer but the open question i mean i guess that's the assumption is the expert games might contain with them within them a humongous amount of information but we know that it went beyond that right we know that it somehow got away from that information because it was learning strategies i don't think it i don't think alphago is just better at implementing human strategies i think it actually developed its own strategies that were that was more effective and so from that perspective okay well so it made at least one quantum leap in terms of strategic knowledge okay so now maybe it makes three like okay but that first one is the doozy right getting it to to to work reliably and and for the networks to to hold on to the value well enough like that was that was a big step well isn't maybe you could speak to this on the reinforcement learning front so the starting from scratch and learning to do something like the first like like random behavior to like crappy behavior to like somewhat okay behavior it's not obvious to me that that's not like impossible to take those steps like if you just think about the intuition like how the heck does random behavior become somewhat basic intelligent behavior not not human level not super human level but just basic but you're saying to you kind of the intuition is like if if you can go from human to superhuman level intelligence on the uh on this particular task of game playing then so you're good at taking leaps so you can take many of them that the system i believe that the system can take that kind of leap yeah no and also i think that that beginner knowledge in go like you can start to get a feel really quickly for the idea that um you know certain parts of the being in certain parts of the board seems to be more associated with winning right because it's not it's not stumbling upon the concept of winning it's told that it wins or that it loses well it's self-play so it both wins and loses it's told which which side won and the information is kind of there to start percolating around to make a difference as to um well these things have a better chance of helping you win and these things have a worse chance of helping you win and so you know it can get to basic play i think pretty quickly then once it has basic play well now it's kind of forced to do some search to actually experiment with okay well what gets me that next increment of of improvement how far do you think okay this is where you kind of bring up the the elon musk and the sam harris is right how far is your intuition about these kinds of self-playing mechanisms being able to take us because it feels one of the ominous but stated calmly things that when i talked to david silver he said is that they have not yet discovered a ceiling for alpha zero for example in the game of go or chess it's it keeps no matter how much the compute they throw at it it keeps improving so it's possible it's very possible that you if you throw you know some like 10x compute that it will improve by 5x or something like that and when stated calmly it's so like oh yeah i guess so but like and then you think like well can we potentially have like uh continuations of moore's law in totally different way like broadly defined moore's law right not the constitutional improvement exponential improvement like are we going to have an alpha zero that swallows the world uh but notice it's not getting better at other things it's getting better at go yeah and i think it's a that's a big leap to say okay well therefore it's better at other things well i mean the the question is how much of the game of life can be turned into right so that's of that i think is a really good question and i think that we don't i don't think we as a i don't know community really know that the answer to this but um so okay so so i went i went to a talk uh by some experts on computer chess so in particular computer chess is really interesting because for you know for of course for a thousand years humans were the best chess playing things on the planet um and then computers like edge to head of the best person and they've been ahead ever since it's not like people have have overtaken computers but um but computers and people together have overtaken computers right so at least last time i checked i don't know what the very latest is but last time i checked that there were teams of people who could work with computer programs to defeat the best computer programs in the game of go in the game of chess in the game of chess right and so using the information about how these things called elo scores this sort of notion of how strong a player are you there's a there's kind of a range of possible scores and the you you increment and score basically if you can beat another player of that lower score 62 percent of the time or something like that like there's some threshold of if you can somewhat consistently beat someone then you are of a higher score than that person and there's a question as to how many times can you do that in chess right and so we know that there's a range of human ability levels that cap out with the best playing humans and the computers went a step beyond that and computers and people together have not gone i think a full step beyond that it feels the estimates that they have is that it's starting to asymptote that we've reached kind of the maximum the best possible chess playing and so that means that there's kind of a finite strategic depth right at some point you just can't get any better at this game yeah i mean i i don't uh so i like to check that uh i think it's interesting because if you have somebody like uh magnus carlsen who's using these chess programs to train his mind like to learn to become a better chess player yeah and so like that's a very interesting thing because we're not static creatures we're learning together i mean just like we're talking about social networks those algorithms are teaching us just like we're teaching those algorithms so that's a fascinating thing but i think the best just playing programs are now better than the pairs like they have competition between paris but the it's still even if they weren't it's an interesting question where's the ceiling so the the david the ominous david silver kind of statement is like we have not found the ceiling right but so the question is okay so i don't i don't know his analysis on that my from talking to go experts the depth the strategic depth of go seems to be substantially greater than that of chess that there's more kind of steps of improvement that you can make get getting better and better and better but there's no reason to think that it's infinite yeah and so it could be that it's that the what david is seeing is a kind of asymptoting that you can keep getting better but with diminishing returns and at some point you hit optimal play like in theory all these finite games they're finite they have an optimal strategy there's a strategy that is the minimax optimal strategy and so at that point you can't get any better you can't beat that that strategy now that strategy may be from an information processing perspective intractable right the you need the the all the situations are sufficiently different that you can't compress it at all it's this giant mess of hard-coded rules and we can never achieve that but but that still puts a cap on how many levels of improvement that we can actually make but the the thing about self-play is if you if you put it although i don't like doing that in the broader category of self-supervised learning is that it doesn't require too much or any human human labeling yeah yeah human label or just human effort the human involvement past a certain point and the same thing you could argue is true for the recent breakthroughs in natural language processing with language models oh this is how you get to gpt3 yeah see how that did the uh that was a good good transition yeah yeah i practiced that for days uh leading up to this guy now uh but like that's one of the questions is can we find ways to formulate problems in this world that are important to us humans like more important than the game of chess that uh to which self-supervised kinds of approaches could be applied whether it's self-play for example for like maybe you could think of like autonomous vehicles in simulation that kind of stuff or just robotics applications and simulation or in the self-supervised learning where unannotated data or data that's generated by humans naturally without extra cost like the wikipedia or like all of the internet can be used to learn something about to create intelligent systems that do something uh really powerful that pass the turing test or that do some kind of superhuman level performance so what's your intuition like trying to stitch all of it together about our discussion of agi the limits of self-play and your thoughts about maybe the limits of neural networks in the context of language models is there some intuition in there that might be useful to think about yeah yeah yeah so so first of all the the whole transformer network family of things um is really cool it's really really cool i mean for you know if you've ever back in the day you played with i don't know mark off models for generating text and you've seen the kind of text that they spit out and you compare it to what's happening now it's it's amazing it's so amazing now it doesn't take very long interacting with one of these systems before you find the holes right it's it's not smart in any kind of general way it's really good at a bunch of things and it does seem to understand a lot of the statistics of language extremely well and that turns out to be very powerful you can answer many questions with that but it doesn't make it a good conversationalist right and doesn't make it a good storyteller it just makes it good at imitating of things it has seen in the past the exact same thing could be said by people who voting for donald trump about joe biden supporters and people voting for joe biden about donald trump supporters is uh you know that they're not intelligent they're just following the yeah they're following things they've seen in the past and uh so it's very it doesn't take long to find the flaws in their uh in their like natural language generation abilities yes yeah so we're being very that's interesting critical of ass right so so i've had a similar thought which was that the stories that gpt-3 spits out are amazing and very human-like and it doesn't mean that computers are smarter than we realize necessarily it partly means that people are dumber than we realize or that much of what we do day to day is not that deep like we're just we're just kind of going with the flow we're saying whatever feels like the natural thing to say next not a lot of it is is is creative or meaningful or or intentional but enough is that we actually get we get by right we we do come up with new ideas sometimes and we do manage to talk each other into things sometimes and we do sometimes vote for reasonable people sometimes but um but it's really hard to see in the statistics because so much of what we're saying is kind of rote and so our metrics that we use to measure how these systems are doing don't reveal that because it's it's it's in the interest this is that that is very hard to detect but is your do you have an intuition that with these language models if they grow in size it's already surprising that when you go from gpt2 to gpg3 that there is a noticeable improvement so the question now goes back to the ominous david silver and the ceiling right so maybe there's just no ceiling we just need more compute now i mean okay so now i'm speculating yes as opposed to before when i was completely on firm yeah all right um i don't believe that you can get something that really can do language and use language as a thing that doesn't interact with people like i think that it's not enough to just take everything that we've said written down and just say that's enough you can just learn from that and you can be intelligent i think you really need to be pushed back at i think that conversations even people who are pretty smart maybe the smartest thing that we know not maybe not the smartest thing we can imagine but we get so much benefit out of talking to each other and interacting that's presumably why you have conversations live with guests is that that there's something in that interaction that would not be exposed by oh i'll just write your story and then you can read it later and i think i think because these systems are just learning from our stories they're not learning from being pushed back at by us that they're fundamentally limited into what they could actually become on this route they have to they have to get you know shut down like we like we have to have an argument that they have to have an argument with us and lose a couple times before they start to realize oh okay wait there's some nuance here that actually matters yeah that's actually subtle sounding but quite profound that the interaction with humans is essential and the limitation within that is profound as well because the time scale like the bandwidth at which you can really interact with humans is very low so it's costly so you can't one of the underlying things about self self-plays it has to do you know a very large number of interactions and so you can't really deploy reinforcement learning systems into the real world to interact like you couldn't deploy a language model into the real world to interact with humans because it would just not get enough data relative to the cost it takes to interact like the time of humans is is expensive which is really interesting that's that go that takes us back to reinforce and learning and trying to figure out if there's ways to make algorithms that are more efficient at learning keep the spirit and reinforcement learning and become more efficient in some sense this seems to be the goal i'd love to hear what your thoughts are i don't know if you got a chance to see a blog post called bitter lesson oh yes but rich sutton that makes an argument hopefully i can summarize it perhaps perhaps you can yeah but okay so i i mean i could try and you can correct me which is uh he makes an argument that it seems if we look at the long arc of the history of the artificial intelligence field it calls you know 70 years that the algorithms from which we've seen the biggest improvements in practice are the very simple like dumb algorithms that are able to leverage computation and you just wait for the computation to improve like all the academics and so on have fun by finding little tricks and and congratulate themselves on those tricks and sometimes those tricks can be like big that feel in the moment like big spikes and breakthroughs but in reality over the decades it's still the same dumb algorithm that just waits for the compute to get faster and faster do you find that to be an interesting argument against the entirety of the field of machine learning that's an academic discipline that we're really just a subfield of computer architecture yeah we're just kind of waiting around for them to do we really don't want to do hardware work so like that's right i really don't want to we're procrastinating yes that's right just waiting for them to do their job so that we can pretend to have done ours so uh yeah i mean the argument reminds me a lot of i think it was a fred jelinek quote uh early computational linguist who said you know we're building these computational linguistic systems and every time we fire a linguist performance goes up by ten percent something like that and so the idea of us building the knowledge in in that in that case um was much less he was finding to be much less successful than get rid of the people who know about language as a you know from a kind of scholastic academic kind of perspective and replace them with more compute and so i think this is kind of a modern version of that story which is okay we want to do better on machine vision you could build in all these you know motivated part-based models that you know that just feel like obviously the right thing that you have to have or we can throw a lot of data at it and guess what we're doing better with it with a lot of data so i i hadn't thought about it until this moment in this way but what i believe well i've thought about what i believe what i believe is that you know compositionality and what's the right way to say it the complexity grows rapidly as you consider more and more possibilities like explosively and so far moore's law has also been growing explosively exponentially and so so it really does seem like well we don't have to think really hard about the algorithm design or the way that we build the systems because the best benefit we could get is exponential and the best benefit that we can get from waiting is exponential so we can just wait it's got that's gotta end right and there's hints now that that moore's law is is starting to feel some friction uh starting to the world is pushing back a little bit um one thing i i don't know do lots of people know this i didn't know this i was i was trying to write an essay and yeah moore's law has been amazing and it's been it's enabled all sorts of things but there's a there's also a kind of counter moore's law which is that the development cost for each successive generation of chips also is doubling so it's costing twice as much money so the amount of development money per cycle or whatever is actually sort of constant and at some point we run out of money uh so or we have to come up with an entirely different way of of doing the development process so like i i guess i always always a bit skeptical of the look it's an exponential curve therefore it has no end soon the number of people going to nurips will be greater than the population of the earth that means we're going to discover life on other planets no it doesn't it means that we're in a in a sigmoid curve on the front half which looks a lot like an exponential the second half is going to look a lot like diminishing returns yeah the i mean but the interesting thing about moore's law if you actually like look at the technologies involved it's hundreds if not thousands of s-curves stacked on top of each other it's not actually an exponential curve it's constant breakthroughs and and then what becomes useful to think about which is exactly what you're saying the cost of development like the size of teams the amount of resources that are invested in continuing to find new s-curves new breakthroughs and yeah it's uh it's an interesting idea you know if we live in the moment if we sit here today it seems to be the reasonable thing to say that exponentials end and yet in the software realm they just keep appearing to be happy anyway and it's so i mean it's so hard to disagree with elon musk on this because it it like i i've you know i used to be one of those folks i'm still one of those folks i've studied autonomous vehicles that's what i worked on and and it's it's like you look what elon musk is saying about autonomous vehicles well obviously in a couple years or in a year or next month we'll have fully autonomous vehicles like there's no reason why we can't driving is pretty simple like it's just a learning problem and you just need to convert uh all the driving that we're doing into data and just having you all know with the trains on that data and uh like we use only our eyes so you can use cameras and you can train on it and it's like yeah that's that what that should work and then you put that hat on like the philosophical hat and but then you put the pragmatic hat and it's like this is what the flaws of computer vision are like this is what it means to trans scale and then you you put the human factors the psychology hat on which is like it's actually driving us a lot the cognitive science or cognitive whatever the heck you call it is it's really hard it's much harder to drive than than we realize there's much larger number of edge cases so building up an intuition around this is uh around exponential is really difficult and on top of that the pandemic is making us think about exponentials making us realize that like we don't understand anything about it we're not able to intuit exponentials we're either that's true ultra terrified some part of the population and some part is like uh the opposite of whatever the carefree and we're not managing everything blase well wow that's that french uh it seems so it's got so it's uh it's fascinating to think what what the limits of this exponential growth of technology not just moore is law it's technology how that rubs up against the bitter lesson and gpt-3 and self-play mechanisms like it's not obvious i used to be much more skeptical about neural networks now at least give a slither possibility that we'll be all though will be very much surprised and also you know uh caught in a way that like we uh are not prepared for like in applications of um social networks for example sure because it feels like really good transformer models that are able to do some kind of like very good uh natural language generation of the same kind of models that could be used to learn human behavior and then manipulate that human behavior to gain advertiser dollars and all those kinds of things sure uh feed the capitalist system and and right so they arguably already are manipulating human behavior yeah yeah so but not for self-preservation which i think is a big that would be a big step like if they were trying to manipulate us to convince us not to shut them off i would be very freaked out but i don't see a path to that from where we are now they they don't have any of those abilities that's not what they're trying to do they're trying to keep people on on the site but see the thing is this this is the thing about life on earth is they might be borrowing our consciousness and sentience like so like in a sense they do because the creators of the algorithms have like they're not you know if you look at our body okay we're not a single organism we're a huge number of organisms with like tiny little motivations we're built on top of each other in the same sense the ai algorithms that are they're not it's a system that includes human companies and corporations right because corporations are funny organisms in and of themselves that really do seem to have self preservation built in and i think that's at the at the design level i think they're designed to have self-preservation be a focus so you're right in that in that broader system that we're also a part of and can have some influence on uh it's it's it is much more complicated much more powerful yeah i agree with that uh so people really love it when i ask what three books technical philosophical fiction had a big impact in your life maybe you couldn't recommend we went with movies we went uh with uh billy joel and i forgot what you uh what music you recommended but i didn't i just said i have no taste in music i just like pop music that was actually really uh skillful the way you thank you that question i'm going to try to do the same with the books so do you have a skillful way to avoid answering the question about three books you would recommend i'd like to tell you a story so um my first job out of college was at bellcore i mentioned that before where i worked with dave ackley the head of the group was a guy named tom landauer and i don't know how well known he's known now but arguably he's the he's the inventor and the first proselytizer of word embeddings so they they developed a system shortly before i got to the group yeah um that that uh called latent semantic analysis that would take words of english and embed them in you know multi-hundred dimensional space and then used that as a way of uh you know assessing similarity and basically doing reinforcement learning not sorry not reinforcing information retrieval you know sort of pre-google information retrieval and he was trained as an anthropologist but then became a cognitive scientist so i was in the cognitive science research group it's you know like i said i'm a cognitive science groupie um at the time i thought i'd become a cognitive scientist but then i realized in that group no i'm a computer scientist but i'm a computer scientist who really loves to hang out with cognitive scientists and he said he studied language acquisition in particular he said you know humans have about this number of words of vocabulary and most of that is learned from reading and i said that can't be true because i have a really big vocabulary and i don't read he's like you must i'm like i don't think i do i mean like stop signs i definitely read stop signs but like reading books is not it's not a thing that i do really though it might be just no i might be the red color do i read stop signs yeah no it's just pattern recognition at this point i don't sound it out um so now i do i wonder what that oh yeah stop the guns so um that's fascinating so you don't uh so i don't read very i mean obviously i read and i've read i've read plenty of books um but like some people like charles my friend charles and and and others like a lot of people in my field a lot of academics like reading was really a central topic to them in development and i'm not that guy in fact i used to joke that um when i got into college that it was on kind of a help out the illiterate kind of program because i got to like in my house i wasn't a particularly bad or good reader but when i got to college i was surrounded by these people that were just voracious in their reading appetite and they were like have you read this have you read this have you read this and i'd be like no i'm clearly not qualified to be at this school like there's no way i should be here now i've discovered books on tape like audiobooks um and so i'm i'm much better uh i'm more caught up i read a lot of books a small tangent on that it is a fascinating open question to me on the topic of driving whether you know supervised learning people machine learning people think you have to like drive to learn how to drive to me it's very possible that just by us humans by first of all walking but also by watching other people dr not even being inside cars as a passenger but let's say being inside the car as a passenger but even just like being a pedestrian and crossing the road you learn so much about driving from that it's very possible that you can without ever being inside of a car be okay at driving once you get in it uh or like watching a movie for example yeah i don't know something like that it's have you have you taught anyone to drive no so i have myself i have two children and um i learned a lot about car driving because my wife doesn't want to be the one in the car while they're learning so that's my job yeah so i sit in the passenger seat and it's really scary um you know i have wishes to live um and they're you know they're figuring things out now they start off very very much better than i imagine uh like a neural network would right they get that they're seeing the world they get that there's a road that they're trying to be on they get that there's a relationship between the angle the steering but it takes a while to not be very jerky and so that happens pretty quickly like the ability to stay in lane at speed that happens relatively fast it's not zero shot learning but it's pretty fast the thing that's remarkably hard and this is i think partly why self-driving cars are really hard is the degree to which driving is a social interaction activity yes and that blew me away i was completely unaware of it until i watched my son learning to drive and i was realizing that he was sending signals to all the cars around him and those in his case he's he's always had social communication challenges he was sending very mixed confusing signals to the other cars and that was causing the other cars to drive weirdly and erratically and there was no question in my mind that he would he would have an accident because they didn't know how to read him there's things you do with the the speed that you drive the positioning of your car that you're constantly like in the head of the other drivers and seeing him not knowing how to do that and having to be taught explicitly okay you have to be thinking about what the other driver is thinking was a revelation to me yeah i was supposed to be really so so creating kind of uh theories of mind of the other theories of mind of the other cars yeah yeah which i just hadn't heard discussed in the self-driving car talks that i've been to since then there's some people who do do consider those kinds of issues but it's way more subtle than i think there's a little bit of work involved with that when you realize like when you especially focus not on other cars but on pedestrians for example it's it's a literally staring you in the face yeah yeah yeah so that when you're just like how do i interact with pedestrians um yeah like pedestrians you're practically talking to an octopus at that point they've got all these weird degrees of freedom you don't know what they're going to do they can turn around any second but the point is we humans know what they're going to do like we have a good theory of mind we have a good mental model of what they're doing and we have a good model of the model that have a view and the model of the model of the model like they're we're able to kind of reason about this kind of uh the social like game of it uh all the hope is that it's quite simple actually that it could be learned that's what i just talked to the waymo i don't know if you know that company it's google south africa they i talked to their cto about this podcast and they like i wrote in their car and it's quite aggressive and it's quite fast and it's good and it feels great it make it also just like tesla waymo made me change my mind about like maybe driving is easier than i thought maybe i'm just being speciesist human maybe uh it's a speciesist argument yes i don't know but it it's fascinating to think about like the same as with reading which i think you just said you avoided the question but i still hope you answered in some way we avoided it brilliantly it is there's blind spots there's artificial intelligence that artificial intelligence researchers have about what it actually takes to learn to solve a problem have you had anka dragon on yeah okay one of my favorites so much energy she's right oh she yeah she's amazing fantastic and and in particular she thinks a lot about this kind of i know that you know that i know kind of planning and the last time i spoke with her she was very articulate about the ways in which self-driving cars are not solved like what's still really really hard but even her intuition is limited like we're all like new to this uh so in some sense the elon musk approach of being ultra confident and just like put it out there putting it out there like some people say it's reckless and dangerous and so on but like partly it's like it seems to be one of the only ways to make progress in artificial intelligence so it's uh it's you know these these are difficult things you know democracy is messy uh uh implementation of artificial intelligence systems in the real world is messy so many years ago before self-driving cars were an actual thing you could have a discussion about somebody asked me like what if what if the what if we could use that robotic technology and use it to drive cars around like isn't that aren't people going to be killed and then it's not you know blah blah blah i'm like that's not what's gonna happen i said with confidence incorrectly obviously uh what i think is gonna happen is we're gonna have a lot more like a very gradual kind of rollout where people have these cars in like closed communities right where it's somewhat realistic but it's still in a box right so that we can really get a sense of what what are the weird things that can happen how do we how do we have to change the way we behave around these vehicles like it obviously requires a kind of co-evolution that you can't just plop them in and see what happens but of course we're basically popping them in to see what happens so i was wrong but i do think that would have been a better plan so that's but your intuition that's funny just zooming out and looking at the forces of capitalism and it seems that capitalism rewards risk takers and rewards and punishes risk takers like it and like try it out the academic approach to let's try a small thing and try to understand slowly the fundamentals of the problem and let's start with one and do two and then see that and then do the three uh you know uh the the capitalist like startup entrepreneurial dream is let's build a thousand and let's right and 500 of them fail but whatever the other 500 we learned from them but if you're good enough i mean one thing it's like your intuition would say like that's going to be hugely destructive to everything but actually it's kind of the the the forces of capitalism people are quite it's easy to be critical but if you actually look at the data at the way our world has progressed in terms of the quality of life it seems like the competent good people rise to the top this is coming from me from the soviet union and so on it's like it's interesting that somebody like elon musk is the way you uh you push progress in artificial intelligence like it's forcing way more to step this their stuff up uh and waymo is forcing uh elon musk to step up it's fascinating i because i have this tension in in my heart and just being upset by the lack of progress in autonomous vehicles and within academia so there's a huge progress in the early days of the darpa challenges and then it just kind of stopped like at mit but it's true everywhere else with an exception of a few sponsors here and there is is like it's not seen as a sexy problem uh thomas like the moment artificial intelligence starts approaching the problems of the real world like academics kind of like ah all right let let the couple get really hard in a different way in a different way and that's right i think yeah right some of us are not excited about that other way but i still think there's fundamentals problems to be solved in those difficult things it's not it's still publishable i think like we just need to it's the same criticism you could have of all these conferences in europe's cvpr where application papers are often as powerful and as important as like uh theory paper even like theory just seems much more respectable and so on i mean machine learning community is changing that a little bit i mean at least in statements but it's it's still not seen as the sexiest of uh pursuits which is like how do i actually make this thing work in practice as opposed to on this toy data set all that to say are you still avoiding the three books question is there something on audiobook that you can uh recommend oh i've yeah i mean um i yeah i've read a lot of really fun stuff uh in terms of books that i find myself thinking back on that i read a while ago like that have stood the test of time to some degree i find myself thinking of program or be programmed a lot by douglas roshkopf um which was it basically put out the premise that we all need to become programmers in one form or another and it was an analogy to once upon a time we all had to become readers we had to become literate and there was a time before that when not everybody was literate but once literacy was possible the people who were literate had more of a say in society than the people who weren't and so we made a big effort to get everybody up to speed and now it's it's not 100 universal but it's quite widespread like the assumption is generally that people can read the analogy that he makes is that programming is a similar kind of thing that uh that we need to have a say in right so being a reader being literate being a reader means you can receive all this information but you don't get to put it out there and programming is the way that we get to put it out there that was the argument he made i think he specifically has now backed away from this idea he doesn't think it's happening quite this way and that might be true that it didn't society didn't sort of play forward quite that way i still believe in the premise i still believe that at some point we have the relationship that we have to these machines and these networks has to be one of each individual can has the wherewithal to make the machines help them do do the things that that person once done and as so you know as software people we know how to do that and we have a problem we're like okay i'll just i'll hack up a perl script or something and make it so if we lived in a world where everybody could do that that would be a better world and computers would be have i think less sway over us and other people's software would have less sway over us as a group yeah in some sense software engineering programming's power it's programming is power right it's it's yeah it's like magic it's like magic spells and and it's not out of reach of everyone but at the moment it's just a sliver of the population who can who can commune with machines in this way so i don't know so that book had a big big impact on me currently i'm i'm reading uh the alignment problem actually by brian christian so i don't know if you've seen this out there yet is this similar to stuart russell's work with the control problem it's in in that same general neighborhood i mean they take they have different emphases that they're they're concentrating on i think i think stewart's book did a remarkably good job like a just a celebratory good job at describing ai technology and sort of how it works i thought that was great it was really cool to see that in a book yeah i think he has some experience writing some books you know that's probably a possible thing he's maybe thought a thing or two about how to explain ai to people yeah yeah that's a really good point um this book so far has been remarkably good at telling the story of the sort of the history the recent history of some of the things that have happened uh this i'm in the first third he said this book is in three thirds the first third is essentially ai fairness and you know implications of ai on society that we're seeing right now and that's been great i mean he's telling the stories really well he's he went out and talked to the frontline people who whose names are associated with some of these ideas and and it's been terrific he says the second half of the book is on reinforcement learning so maybe that'll be fun um and then the third half third third is on uh this is super intelligence alignment problem and i i suspect that that part will be less fun for me to read yeah it's yeah it's it's an interesting problem to talk about i find it to be the most interesting just like thinking about whether we live in a simulation or not as a as a thought experiment to think about our own existence so in the same way talking about alignment problem with agi is a good way to think similarly like the trolley problem with autonomous vehicles it's a useless thing for engineering but it's a it's a nice little thought experiment for actually thinking about what are like our own human ethical systems our moral systems to to to uh by thinking how we engineer these things you start to understand yourself so sci-fi can be good at that too so one sci-fi book to recommend is exhalations by ted chang a bunch of short stories um this ted chang is the guy who wrote the short story that became the movie arrival um and all his stories just from a he's he was a computer scientist actually he studied at brown they all have this sort of really insightful bit of science or computer science that drives them and so it's just a romp right to just like he creates these artificial worlds with these by extrapolating on these ideas that that we know about but hadn't really thought through to this kind of conclusion and so his stuff is it's really fun to read it's mind warping so i'm not sure if you're familiar i seem to mention this every other word uh is i'm from the soviet union and i'm russian uh read way too much my roots are russian too but a couple generations back well it's probably in there somewhere so maybe we can uh we can pull up that thread a little bit of the existential dread that we all feel you mentioned that you i think somewhere in the conversation you mentioned they you don't really pretty much like dying i forget in which context it might have been a reinforcement learning perspective i don't know i know you know what it was it was in teaching my kids to drive that's that's how you face your mortality yes uh from a human being's perspective or from a reinforcement learning researcher's perspective let me ask you the most absurd question what's uh what do you think is the meaning of this whole thing the meaning of life on this spinning rock i mean i think reinforcement learning researchers maybe think about this from a science perspective more often than a lot of other people right as a supervised learning person you're probably not thinking about the sweep of a lifetime but reinforcement learning agents are having little lifetimes little weird little lifetimes and it's it's hard not to project yourself into their world sometimes but you know as far as the meaning of life so i when i turned 42 you may know from that's a that is a book i read um the the historical hitchhiker's guide to the galaxy that that is the meaning of life so when i turned 42 i had a meaning of life party where i invited people over and um everyone shared their meaning of life we they we had slides made up and so we had we all sat down and did a slide presentation to each other about the meaning of life and mine mine was balance i think that life is balance and um so the activity at the party for a 42 year old maybe this is a little bit non-standard but i i found all the little toys and devices that i had that where you had to balance on them you had to like stand on it and balance or pogo stick i brought a ripstick which is like a weird two-wheeled skateboard um i got a unicycle but i didn't know how to do it i didn't know how to do it i now can do it i love watching you try yeah i'll send you a video i'm not great but i put but but i managed um and so uh so balanced yeah so so my my wife has a really good one that she sticks to and is probably pretty accurate and it has to do with healthy relationships with people that you love and working hard for good causes but to me yeah balance balance in a word that's that that works for me not too much of anything because too much of anything is iffy that feels like uh rolling stone song i feel like they must be you can't always get what you want but if you try sometimes you can strike a balance yeah i think that's how it goes uh michael i'll write your parody it's a huge honor to talk to you this been a big fan of yours so um uh can't uh can't wait to see what you do next in the world of uh education the world of parity in the world of reinforcement learning thanks for talking today my pleasure thank you for listening to this conversation with michael littman and thank you to our sponsors simplisafe a home security company i use to monitor and protect my apartment expressvpn the vpn i've used for many years to protect my privacy and the internet masterclass online courses that i enjoy from some of the most amazing humans in history and better help online therapy with a licensed professional please check out the sponsors in 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John Clarke: The Art of Fighting and the Pursuit of Excellence | Lex Fridman Podcast #143 | the following is a conversation with john clark he's a friend a brazilian jiu jitsu black belt former mma fighter and at least in my opinion one of the great ufc cornerman coaches to listen to and also he's my current jiu jitsu coach at broadway jiu-jitsu in south boston he was once for a time a philosophy major in college and is now i would say a kind of practicing philosopher opinionated brilliant and someone i always enjoy talking to even when especially when we disagree which we do often he's definitely someone i can see talking to many times in this podcast in fact he hosts a new podcast of his own called please allow me quick mention of each sponsor followed by some thoughts related to the episode thank you to theragun the device i use for post-workout muscle recovery magic spoon carb keto friendly cereal that i think is delicious eight sleep a mattress that cools itself and gives me yet another reason to enjoy sleep and cash app the app i use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that martial arts especially jiu jitsu and judo have been a big part of my growth as a human being so i think i will talk to a few martial artists on occasion on this podcast i hope that is of interest to you i won't talk to people who are simply great fighters or great athletes but people who have a philosophy that i find to be interesting and worth exploring even if i disagree with parts or most of it i like alternating between historians and computer scientists fighters and biologists and between totally different worldviews and personalities like elon musk and michael malus this world to me is fascinating because of the diversity of weirdness that is human civilization i love the weird and the brilliant and hope you join me on the journey of exploring both if you don't like an episode skip it for an ocd person like myself sometimes not listening to a podcast episode is an act of courage it's like not finishing a book even though you're 80 done try it sometimes listen to ones you like and don't listen to the ones you don't like i know it's profound advice if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter and lex friedman and now here's my conversation with john clark you ready for this i've been ready for this my whole life all right i was thinking of doing a kerouac style road trip across the united states you know after this whole covet thing lifts you ever take a trip like that i've done a handful of long distance driving trips um up and down the east coast but also from the west coast back to the east coast and then returning to california so i've definitely done my fair share of driving in this country do you have the longing for the great american road trip i think there are so many things that i've been lucky enough to see in the world that i now at this point in my life realize there are tons of things that i need to see here in this country and a road trip could potentially be the best way to see them i think to do it effectively you need an amount of time where you can be as leisurely as possible there's no deadline and there's no i've got to make it from chicago to st louis by sundown to get to this place at this time i think you really need to be able to take your time and uh and kind of like let the road take you where you need to go it feels like you need a mission though ultimately like there's a reason you need to be in san francisco that's like the kerouac thing you have to meet somebody somewhere kind of loosely in a few weeks and then it's the as you struggle on towards that mission you meet weird characters that get in your way but ultimately sort of create an experience i think having a loose deadline is good but that's a beginning and an end point and what i mean is i don't want to have to be all right we're leaving say boston on sunday night let's get to new york by monday morning and then from new york we're going to go to philly and we've got to be in philly at 4. a vague beginning and end is fine but i think having very strict guidelines in between will rob you of certain experiences along the way if you have a time frame to get from philly to indianapolis and some awesome shit starts to happen in philly do you really want to have to cut it short because you got to be in indianapolis by sunup why do you have to be anywhere by any time for any reason really plans change plans change all the time exactly but if we're talking about um having a mission or the type of road trip i just think it would be best to have it as loose and uh flexible as possible i don't know you gotta make hard deadlines and then break them totally change the plans disappoint people break promises that's the way of life somebody's waiting for you in st louis and all of a sudden you you fell in love with a biker in new york i don't know i don't know what you're up to i can appreciate that um but on a trip like that i feel like a trip with deadlines is for a different point in your life and at this point in my life i don't want any of the deadlines because it's not about meeting someone and disappointing them in st louis it's about me not disappointing myself you want to have you want to have enough time in what you're doing to make sure that you get the full breadth of every experience that you encounter how would you fully experience a place how would you you know i i don't think i've actually fully experienced boston like how if you were showing up to to a city for a week on this road trip what would you do so i'm gonna answer that in two parts a few years ago i had an opportunity to move out of boston and the thing that kept me here no question about it was the fact that i felt like i had a um a contract with my students and i did not i felt like a great many of them took a leap of faith uh by joining my gym and like you know asking me to teach them what i know and when i had an opportunity to leave boston i thought of those people and i thought i want to fulfill my obligation to them so because i made a decision to stay here i then that summer made a decision to endear myself to the city of boston and i tried to find lots and lots of different things to do i can tell you that the coolest thing that i found to do in this city is um the mfa where they have like on friday nights they'll have like different exhibits and stuff and they'll have like little beer carts and food tents and you can go do a painting class off in the on the side very cool night of things to do but in general whenever i'm in a new city i try not to pay attention to google and i try not to do anything that i find on a travel site the best thing to do is to walk out of your hotel or wherever it is you're staying and find the most normal looking bar have a drink and talk to a bartender so people the people the people and then you can experience that town the way that they experience it even in a city where there are tons of tourist attractions locals probably visit the same tourist attractions when they have visitors come from out of town but you want to see how they view those places and how they visit them and you want to go to eat where they're going to eat like you know you're going to for the most part the north end is not a place where i would take someone and say hey this is boston's the pinnacle of boston dining because it's very touristy there are a handful of really good restaurants there but i want to know where the where the i want to go to bogey's place i want to know like the the down low spots where the hell is bogey's place it's like a little steakhouse in the back of jm curly's exactly like a shitty bar yeah it's just a bar with like bar food but i think they're like um boston it is in boston yeah it's like south boston no it's in um it's in the downtown area like um i don't know what the neighborhoods are called here honestly because they call they have an area called downtown boston and i don't even know what the hell that means i think he's near the financial district where's southie because i've heard about the southie southeast south boston but is there is there difference between south boston and southie no it's the same thing no but like you know the mythical south i think the mythical southie is uh something that's long gone now and the term now actually is sobo oh no yeah it's it's changed what who who took over what what's the you know the goodwill hunting personality that's southie isn't it strong accent those badass dudes i came here right at the end of like what was south boston so when i got and my gym is in south boston the neighborhood was just starting to change so i think as gentrification happened and they started building more luxury condominiums they were buying all these old businesses out all the mom and pop businesses and i think that kind of changed the the makeup of the community and it wasn't only because there was an influx of new young people with disposable income it's because there's an exodus of the the older people who kind of grew up and raised their families there because they were being offered humongous sums of money for their homes that they had bought like in the late 70s and early 80s so that they could develop those areas so you have a combination of the influx of new people in the exodus of the old and now you just got this totally new neighborhood in its place what do you love about boston is there a love still for boston you certainly have the love of the thing that's gone as well yeah i think i don't want to pinpoint pin this on boston because it's happening in all great cities as these areas become gentrified what's happening is the personality and the character of the neighborhood is just being run out and i have nothing against people coming in and making money and things like that but when you do it at the expense of the culture the character and the personality of the neighborhood i mean you're kind of standing on the shoulders of giants these are the people that came here and built these areas up uh it happens here in in boston it happens in all over new york uh happens on the west coast so what i love about boston is not nearly as romantic as what it might have been 15 years ago and what i used to love about new york what i love about boston is that um it's walkable um the food scene is on is on the rise here um but i think you're you're hard-pressed to find the charm that people think of when they think of old boston and old new england city see i see it differently people sometimes criticize like mit like for the thing that it is now but i think it is always like that i tend to prefer to carry the flame of the his of the greatness the greatest moments of his history and like sort of enjoy that the echoes of that in the halls of mit in the same way in boston you think about the history and that history lives on in the few individuals like you can't just look around where boston is now and be like what has boston become i think it was always carried by a minority of individuals i i think we kind of look back in history and think like times were greater in a certain kind of dimension back then but that's because we remember uh this is a ridiculous non-data-driven assertion of mine is we remember just the the the brightest stars of that history and so we romanticize it but i think if you look around now those special people are still living in boston for which boston will be remembered as a great city in like 50 years i think you're probably right but isn't there some sort of theory about the point that there's like a certain age in your life where things resonate differently to you like i think they've done studies where most people stop searching for new music after age 19. most dads you see like wearing super old clothes like the that's the style of the time period of the last great part of their life so like there's an evolution in in people and it could also be the memories of where they live and when i was 17 of course my neighborhood was the best then because i was having the most fun and we always kind of look at things through uh that that tint i think and you're right and i don't think there's anything wrong with the way cities are evolving now it's just not um i i i prefer the time of like a mom and pop store not a fabricated like uh gastropub that could just be like on a four-lane super highway on your on your way out of epcot center and it's actually owned by like some conglomerate but there's still the special places like i this takes us back to the road trip is um maybe i tend to romanticize the experiences of like the diners in the middle of nowhere what would you say makes for like it feels like life is made up of these experiences that are that maybe on paper seem mundane but are actually somehow give you a chance to pause and reflect on life with like a certain kind of people whether like really close friends or complete strangers maybe alcohol is involved in the middle of nowhere it seems like road trip facilitates that if you allow it to like what do you think makes for those kind of experience have you had any i think in the context of a road trip i think it's like hyper localization and i think it is um those those experiences along the way with people and the people that you're with will color the experiences differently depending on the person the road trip you took was uh with somebody else or along so i've driven up and down the east coast several times when i drove from la to new york my friend was on the run from the cops yeah so we were trying to get traffic tickets yeah yeah we were trying to get out of la because um he was going to have to go away for a little while yeah so we drove from la and we just you know we're young kids we had no idea what we were doing and we drove east and then you know we had an unbelievable trip mostly because we didn't really have a destination we didn't really have a time frame thank goodness uh because he got arrested again in pennsylvania so we got kind of stuck there and then um you know and then we we drove back to la when he got out in pennsylvania um but all the stops along the way were kind of like weird things like you have no money right so you're finding that like a little diamond in the rough place to eat the diner you talk about like that place i i once was in where was i i think i was in buenos aires and the guy that i was with he said i know this quaint little spot around the corner and i was young i was like 25 and i thought the coolest thing in the world would be to be such a citizen of the world that you know these quaint little spots around the corner in like all these great cities like i know where to get this great chicken sandwich in argentina i know where to get this great meal in costa rica i know where to get this super local like um egg in another country i always thought that that was really cool the ability to do that anywhere in the world you get closer with that guy went out through the trip i found that like so i took i took a trip across the united states with a with a guy friend of mine we had different goals i was searching for a meeting in life and he was searching for um what's the politically correct way of phrasing it but just uh basically trying to sleep with every kind of woman that this world has to offer what's the difference between those two things well i guess the different kinds of meanings i i mean i just i i still think that you can't find meaning between a woman's legs i suppose uh that maybe they tried all of them but there was a tension there we grew closer with those experiences but we've gotten in fights you know there was a lot of like literal almost fights and then we were close and there was like silences but then we were like brothers and this whole weird journey of friendship that we went on i think anytime you spend that much time in uh like a small space with another person you're gonna have the the different parts of the relationship will manifest themselves you'll have the periods of closeness you'll have the periods of vulnerability where it's like maybe you're driving through denver and it's three in the morning and you talk about something you might not have otherwise talked about you'll have the periods where you don't want to see that motherfucker ever again right he didn't and depending could be because of anything yeah um but the guy that i drove twice with we are still we're still in contact we're still buddies we we have very different goals also um but at that point in our lives we were not we never even contemplated the meaning of life we were about probably more to the point of the friend that you drove with we were more about racking up experiences whatever they were right i want to be able to retell this hmm stories yeah i want to be able to retell this and it's got to sound cool like i don't want to retell a story about yeah and then we drove through alabama and they've got a lovely library and i checked out this book and you know i'm not interested in retelling that do you remember any um well this is a kids show do you remember any stories that the kids would enjoy from those times they were profound in some kind of way there were some impactful moments on the beginning of our road trip where we had no money and as a couple of kids who knew nothing we literally had to we stopped in vegas and we went to circus circus at the time they had three dollar blackjack and we had like 12 bucks and my buddy was a kind of a degenerate gambler so he knew what was up i was just like kind of stuffing chips in my pockets making sure we could pay for the gas um and just being at a point which is like a starting line and like we drove from la to vegas which is only about four hours and being at the starting line and realizing like we may not even like get off the starting line here and if we don't what are we doing we're going to be two guys stuck in vegas with no money we can't go west because you're going to get pinched we have no money to go east what the hell are we going to do we're going to wind up in vegas so you know that that was kind of a profound thing where you just it's a turning it potentially could have been a turning point in our lives had we not made enough money to to continue going east that's the beautiful thing about road trips when you're broke it's like in retrospect everything turned out fine but you're facing the complete darkness the uncertainty of the possibilities laid before you and like i don't know if you were confident at that time but like i was really full of self-doubt like just like all i could see is all the trajectories where you just screw up your life like what am i doing with my life i'm a failure like all these dreams i've had i've never realized i'm a complete piece of shit all those kinds of i had no concept of consequence i i like i was i probably had toxoplasmosis i had literally no concept of consequence immediate gratification was all i cared about oh so existentialist yeah it did not it did not even enter my mind at in my like early 20s that anything that i was doing at that point could reverberate for the rest of my life i think part of me didn't even think i'd make it this far and so i was not interested in like the long play i remember thinking like why should i be acting now in a way that might impact a point in my life i never reach and yet now you are a man who searches for meaning in life at least i would say to put another way you have um you think deeply about this world and in a philosophical context while also appreciating the violence of hurting other uh friends of yours right on a regular basis so what why do you think i mean maybe there's a broader question there but also a personal question it seems that people who fight for prolonged periods of time like jiu jitsu people mixed martial arts people even military folks become overtime philosophers what what is that is that is there a parallel between fighting and violence and the philosophical depth with which you now have a from the starting point of being the full existentialist of like just living in the moment to like being uh introspective uh human now i would say to that being a a soldier or a warrior uh hundreds of years ago is probably what started the marriage between martial arts and philosophy if you're constantly under someone else's charge and you're told to go out and walk in a line and you know overtake some germanic tribe somewhere and that happens all the time um your job is being a soldier there's on any given day you might not come home so i think that you have to start your day by thinking deeply about how you've lived to that point and the people that are living in and around you and how you've treated them and i think that probably is what started the marriage of being kind of like a philosophical martial artist you've got to really like on a daily basis take stock of of what's going on around you and inside you because we all suffer with this kind of uh idea if today's my last day did i do it right and we don't really do it so much nowadays because we're so comfortable but if we're being marched out to war every day i think you'd see people live a little bit differently uh you know and you that you treat the people around you a little bit differently do you think there's echoes of that in just even the sport of uh like grappling and jiu jitsu where you're facing your own mortality we don't really think of it that way but to be honest i think that a lot of people that train in a martial art in contemporary society i don't consider them all martial artists i think just because you train a martial art does not mean you're a martial artist there are so many people that use martial arts as a form of exercise and like this little piece of um self-concept they use martial arts as a tagline in their instagram bio and it's really a form of exercise it's something they do it's not something they are and i think there's a big difference there there's a bunch of stuff mixed up in there because the instagram thing is something you do for it's also it could be something you are for display versus who you are in the private moments of searching and thinking and struggling and all that kind of stuff instagram is a surface layer that much of modern society uh operates in which is really problematic because there's that gap between the person you show to the world and the person you are in private life and if you make majority of your project of the human project of your sort of few years on this earth the optimization of the public instagram profile then you never develop this private person but it does seem that if you do jujitsu long enough it's very difficult not to fall into like this has become a personal journey an intellectual journey because like if you get your ass kicked thousands of times there's a certain point to where that maybe it's like a defense mechanism but that turns into some kind of deeply profound introspective experience versus like exercise yeah so let me let me go back first and address the instagram point which i think there's a difference between people who whose instagram is intrinsically tied to their profession and they have to put a specific profile out there and i think in general people who truthfully are their businesses tied to their instagram profile i want to exclude them i think that most people instagram is how they want to be seen and it's not always congruent with who you are but i think there is a level of dishonesty there yeah like this is how i want people to see me i'm gonna put all this stuff in my instagram bio but that's really not me and when you do that um i think it's it's a little disingenuous and you're right there's not you're never really going to marry those two things together and it gets tough let me uh sorry to interrupt let me push back on something that's a good time to address uh the the many flaws of the great and powerful john clark okay uh le le let's let's go there because it's interesting you strive so hard for excellence in your life and for extreme confidence that you are visibly and physically off put by people who are who have not achieved competence do you think we should be nicer to the people who are those early like you mentioned a person who first picks up an art picks up is becomes vegan starts throwing crossfit start doing jiu jitsu for the first time and create that as their you know they're they're struggling through this like who am i and they're really overly proud and it's kind of ridiculous and you and your wise chair i've seen seen many battles yeah that you see the ridiculousness of that i tend to i'm learning to give those folks not to mock them and and to sort of give them a chance to do their ridiculousness because i think i was that too let me first clarify i want to be clear about what you mean when you say a level of competence now i i've never won a world championship i've never you know there are plenty of things in my life where i've not achieved what um most people would consider to be the penultimate level of success now that's accomplishments it's accomplishments it's ribbons it's things like that and it's not that those things don't mean anything to me and the fact that i haven't in some arenas is uh is something that i want to change which is we can talk about that in a second but i think that there's a difference between the very eager noob of whatever it is they're doing who does the thing so that they can signal they do the thing that's the person i have less respect for so we know each other primarily through jiu jitsu look at a jiu jitsu tournament there's this there's this idea that people espouse online i respect anyone with the guts to get on the mat and put it on the line and sign up for a tournament that is the biggest load of shit i have ever heard this is great do you know do you know how easy it is for you to put your name on something and pay the registration fee and walk in there that's not the hard part that's the easiest part i don't care if you lose your first match but i respect the person who signs up for the tournament registers for the tournament goes on a diet loses weight the right way trains their ass off and does the things properly and then goes on the mat the person who simply signs their name on the registration form and jumps on the mat if they haven't done these other things they actually have nothing to lose because what they've done is they've stepped onto the mat in the ring in the cage with a bucket full of excuses yeah sure you signed up but when you but you you're not really vulnerable because you didn't run you didn't do this you didn't do all the things you're supposed to do the person who eliminates every possible excuse and then steps on the mat and gets their ass kicked in the first round i have so much more respect for that person than the person who does nothing and maybe unnatural ability wins a couple of matches and then you know writes on facebook on how i lost to the eventual champion that's worth zero that's worth zero and in that process what did you learn about yourself you learned about yourself that you've got a natural level of aptitude for whatever this activity is that you're doing but you didn't actually learn how to maximize it through training and through dedication and through all these other things uh i'm i'm an incredibly interested novice musician i love i like to play bass but i don't put that on anything and you know i stink at it i would really love to be sick at it i'm currently not but like i'm not running around you know talking about entering you know any of those other things like i i do it it's for myself and i want to i want to reach a level of competence in that so the person that you have respect for the person who takes it fully seriously takes takes the effort fully seriously so for base that would be that you agree with yourself that you're going to perform live and just in your own private moments your private thoughts you're not going to give yourself an excuse out like i'm just going to have fun it's just a nice experience you're going to you're going to think i'm going to try to be the best possible bass player given given everything that's going on in my life but i'm going to do my like actually and put it all on the line and if i fail that it that's not because i didn't try it's because i'm a failure exactly and then and then sit in that sick feeling of like i'm a failure but isn't that an important thing to know absolutely but there there's a there's a that's like the best thing it could be but sometimes it's fun to lose yourself in the in the in the bragging in the yeah in the lesser ways of life and i think i'm careful not to uh because too many people in my life when i brought them with like a little candle of a fire of a dream they would just go like you know they would just blow that fire out uh that they would dismiss me because they see like you know i would say i said i've said a lot of ridiculous stuff but the one you know i've always dreamed about uh like putting like i always dreamed of having this world full of robots and you know every time i would uh bring these ideas up they'll be shut down by the different people by my parents but you know uh you know then you need to first get to get an education you need to succeed in these dimensions in notice you do all these things you have to get good grades you have to like there's all this stuff that it's indirect or direct ways of blowing out that little ridiculous dream that you present and it's like you know i remember sort of bringing up i don't know um things like becoming a state champion and wrestling right it's a it's a weird dance because of course the coaches will tell they'll kind of dismiss that it's like okay okay uh but at the same time it feels like in those early days you have to preserve that little little fire that's like johnny i don't know if you know who that is as a designer at apple he was a chief designer he's behind most iphone all that stuff and he he always talked about that he wouldn't bring his ideas to steve jobs until they were matured because he would always shit on them uh he would he wanted them to like little as little babies like live for a little bit before they get completely shut down and i always think about that when i see a beginner sort of bragging on instagram you have to be careful let them play with that little dream you know are you playing with a little dream that you're nurturing and you're trying to take that little flame and you're trying to create a a roaring blaze with it or are you playing with the idea of it and behind behind that there's no substance it's hard to know the difference that's what i struggle with is it i don't think it necessarily is certainly you're wrong and when i say instagram i don't want to impugn a bunch of strangers but i have a gym with a lot of members and and i can tell you that the number of years i've been in the gym when someone comes to me and says this is my goal i don't i don't tell them yes or no in general but i know i can tell by the way they say it to me i can thin slice it i've seen the look on people's faces and when people start to like say they want to do x y and z i know right off the bat this person is either going to put an effort in or they're not going to put an effort in so to me it's about the effort behind that if you're busting your ass and you're a newt at something and you're brand new but you're working really hard and you have a series of like moderate successes in that like that's the guy i want to champion because that persistence and that grit over time those successes will no longer be moderate they'll be huge but the person who's having moderate success by doing nothing chances are they'll never learn to put that work in and the successes will never grow you have an admiration for mike tyson i love him i'm just gonna let that sit for a brief moment um why i think there's a combination of factors one is like the timeliness of his career and like the age i was when he like came to prominence um the raw brutal violence and the raw brutal honesty when he speaks i think it's easy for people to hear him or see his life and cast him aside as some simeonesque uh like just cretin scourge on society but when you hear him speak like this is not a guy who's unintelligent this is a guy who knows himself better than probably most of us know ourselves it's disarming and uh you know that's a humongous part of my admiration for him who is mike tyson because you there's it feels like there's similarities between him and you there's a it feels like there's a violent person in there but also really kind person and they're all like living together in a little house and you're the same there's a thoughtful person but there's also a scary violent person and they're like having a picnic they're having a picnic i think there are dialectical tensions in everyone these like opposing forces yeah that are constantly pulling at you and at different points in your life like it's sliding scale and i think that uh certainly when i was a younger person there was a lot more manifestation of the violence and a lot less of the kindness um people who were not as close to me probably saw more of the violent side only the very close people to me saw like what would pass for the kind side and now that's sliding in the other direction uh and i i worry actually sometimes that there could be a situation where i need that old version of me and he's getting further and further away and i can't call him up if i need him and that that concerns me to it to a certain degree the sad aging warrior seeing his greater self paid away like but you still compete is that that person return it seems like for mike tyson that person returned at the prospect of competition it returns but i've learned i've learned better how to manifest it in competition in terms of like the effects that that type of emotion has on you physically in the middle of a competition so i've better learn how to utilize that energy but i think another side effect of this is like having a gym where you're a bigger guy and you're the head instructor you can't be as mean and violent as you once were because you're also now trying to run a business and you spend so long so many so many years trying not to be mean and to you know soften your your technique a little bit that that all of a sudden just becomes who you are and and i don't necessarily like that so i've been trying to reclaim that a little bit uh on the mat but i think in competition there's there has to be an athlete really wants to score the points a fighter really wants to incapacitate you and put you in a position where they can do their own bidding and the result in a jiu jitsu match might just still be two points but the motivations are very very different what do you make of tyson and joe rogan saying that he was aroused by violence do you think that's insane do you think that's deeply honest for him and do you think that rings true for many of us others who practices in different degrees i don't i can't speak for a lot of people and i think that it's was a brutally honest statement by him and i think it's something that even if a lot of people feel it they're not that comfortable admitting it or saying it yeah but i think like there's there is great joy in like landing a flush right hand on someone's jaw and then watching them crumble you don't even feel it you ever play baseball as a kid you can hit a bass hit off the end of the bat and it will sting your hands because of the way that you hit it you can hit a home run and you won't feel anything and it'll just feel so good in your hands and that's i think that like one of the the joys of uh physical contact when you do it the right way and that goes for all physical contact when you do it the right way the physical pleasure you can derive from it and the mental pleasure it's uh it's unparalleled but that's different let me draw a distinction i'm not i've had the fortune of being a wrestler and i would draw a distinction between a very well executed and competition double leg single leg takedown or a pin there's some as an ocd person there's something so comforting about a well-executed pin because it's like two seconds and it's just like everything is flush and nice and it like it's all clean and i mean okay this ocd person who likes to align so it's just beautiful okay that's good technique wrestling also provides you maybe more than other sports the feeling of dominating another human yes of breaking no not just of them being very cocky and very powerful you feel this power of another human being and then you breaking them and like i'm not as honest as mike tyson but that's that uh uh i don't think i've ever sort of looked in the mirror and said like that that was in i enjoyed that aspect of it but it certainly seems like you chased that so when i was a wrestler in high school um i lost so many matches because of over aggressiveness um like you know i would pick the top position and let you stand just so that i could do a matt return and i wasn't trying to return you to the mat i was actually trying to like drive you through the mat and through the ground like i took like i it gave me joy to do that yeah like it wasn't like i was trying to you know just return you to the mat so that it could pin you that what you just talked about like the the dominating another person i used to look at that as you've got someone who in theory is equally trained and equally skilled as you are and you're you're absolutely out there totally dominating them there's joy in that you could get in an mma fight and you could take someone down and you can mount them and all that feels great but when you start raining down the punches on their face from mount and like dropping elbows and stuff like there's another level of satisfaction there and it's it's tough to describe and i don't think that it's everyone uh is made for it when i was a i think when i was a senior in high school my wrestling coach said look you've got to stop with all this crazy aggressive wrestling like they try to turn me into a technician and and it and it did work to a degree and it was a humongous shift for me in terms of success but it wasn't the same level of enjoyment out of it um like i mean i got disqualified from new england because my coach said crossface and i cross-faced and he said harder and i basically wound up and blasted a kid in the face and his nose got you know busted everywhere but i didn't think not to do it because that felt good it felt good to cross-face him like that i was that was a lot of like that's a weird american warrior ethos that i've picked up but i also have them either the russian the setia brothers that don't see it don't see it as that they they don't get draw they think that there is a tension between the art of the martial art and the violence of the martial arts i agree it's a poetic way i could put it but they're not so fascinated with this dan gable dominating another human they think of the effortless the effortlessness of the technique and your mastery of the art is exhibited in its effortlessness how much you lose yourself in the moment and the timing that just the beauty of a timing like there's much more like one example in judo but also in wrestling you can look at the foot sweep wrestlers in america and even judo players in america much of the world don't admire the beauty of the foot sweep but a well-timed foot sweep which is a way to sort of off balance to find the right timing to just effortlessly uh change the tape turn the tables of uh dominate your opponent is is seen as the highest form of mastery in in russian wrestling and in case of judos and in japanese judo it's interesting i'm not sure i'm not sure what what that tension is about i think it actually takes me back to i don't know if you listen to uh dan carl in hardcore history and genghis khan if you've ever i've read a great great book on jenga's god yeah i'm so i'm still trying to adjust most of my life said genghis khan but the right pronunciation is uh actually changus khan there's a tension there we kind of think i don't know we i kind of thought as genghis khan as a ultra violent a leader of ultra violent men but another view another way to see them is the people who warriors that valued extreme competence and mastery of the art of uh fighting with weapons with bows with the horse riding all that kind of stuff and i'm not sure exactly where to place them on my sort of thinking about violence in in our human history i think in the context of like combat sports i think there's a difference between an athlete winning a contest under a certain set of rules and a fighter winning a fight under those exact same rules there's a different approach to it and i don't think one is any better than the other um like in mma i think a great example would be george st pierre george st pierre is a tremendous it's a tremendous athlete and he considers himself to be a martial artist first he's trying to win an athletic competition like nick diaz is trying to bust your ass yeah right there's a different approach to it and yes they've had different results at the highest level of competition but it's difficult to attribute the difference in results just to their approach to the sport because they're different human beings with different abilities and different different uh physical attributes um the saito brothers have that luxury of being able to talk about the beauty of a perfectly timed slide by right there are other wrestlers that will never be able to pull that off and therefore they have to pursue other ways to defeat someone and maybe it is the dan gable breaking a man's spirit by outworking him type thing which is beautiful in its own way uh but we we we tend to self-select the ways in which we're able to be successful and then kind of take a deep dive into that what do you think is more beautiful brute force or effortless execution of uh technique that dominates another human i think it's a subjective thing based on what skills you perceive yourself to have i'm never i've never been a slick uh super athletic dexterous competitor in anything and i've always been more of an i've got to outwork you i've got to outgrind you i gotta help mean you and so because i've lived that i tend to see the beauty in that more because i have a perceptual awareness that i don't have for the people who have the luxury of being very slick and athletic and and using beautiful technique now that said there's a phenomenal little video the other day i sent to a friend of a compilation of foot sweeps by leota machida in mma and they're so beautiful and they're so awesome and it's not that i don't have an appreciation for those but i can't emulate those because i lack the physical ability to do that whereas i i at least have a chance to emulate some of the people who do it through grit and throughout working people but i would love to return to genghis khan and get your thoughts about like i have so many mixed feelings about whether he is evil or not whether the violence that he brought to the world had ultimately the fact that he had maybe kind of uh like dan carlin describes cleansed the landscape it's like a reset for the world through violence had ultimately a progressive effect on human civilization even though in the short term it led to massive you could say suffering i don't know what to make of that man what uh what are your thoughts on jenkins gone um i think it's always difficult to look at a historical figure and their actions of their time through a modern day lens because it's very it's easy for us to um kind of you know impugn their achievements and the things that they did and say oh well you know what he did was wrong well of course that can be true but a lot of times we don't actually have any real good context or concept of the the times they were living in and what really was deemed wrong and what really wasn't we're looking at it through a very cushy modern lens that being said from what i've read about genghis khan uh yeah he was a violent dude but also he gave you an option he when he when he got to a village he said look i'm gonna we're gonna you have a choice you can come with us or you can run and you know he gave them an option to join uh his legion of fighters who he took very good care of you know he was the the first military leader uh to pay his soldiers families when they died and he did that based on the the booty that they got when they raided a village he took that money he took his share and they divided that up amongst the soldiers and then the soldiers families i think he also is credited with uh first like horseback male roots or something like that right isn't he the godfather of the modern postal system or something something like that yeah he's the bernie sanders of the uh uh the mongol empire i do think the the offering of surrender is an interesting one because um it's interesting like as a thought experiment whether you would sacrifice your way of like the pride of nations or the nationalism pride of your country whether you're willing to give that up uh for uh you know to survive it depends on who depends on you if you have a if you have a family and like young kids and stuff like that i think your your obligation is primarily to them and therefore surrender has to be something that you consider in that in that moment in time so that you can uh take care of those people if you're a man alone and you've got like all these principles and all this other stuff and you just don't you're not down with what genghis khan is doing and what he's selling yeah try and escape do your thing and just know that you know what wait's on the other side of that for you potentially but i think if there's someone else out there that depends on you your obligation should be to them it feels like historically people valued principles more than life in this weight of like what do i value more the principles i hold versus survival it seems that now we don't value principles as much your principles could be also religion it could be your values whatever we're okay sort of sacrificing those for to preserve our survival and that applies in all forms like actual survival or like on social media like preserving your reputation all those kinds of things it seems like we especially in america value individual life that death is somehow a really bad thing as opposed to saying sacrificing your principles is a very bad thing and everybody dies and it's okay to die as what's horrible is to sacrifice your principles of who you are just to live another day i think a big problem is people don't really even know what their principles are anymore people you know um social media and just the way that we live nowadays where we're separated from the human contact like this like we're not you're not contacting people in a community anymore you're not whether you're religious or not like you're not you're not congregating at a church you're not part of a parish like you would be like in you know down south you're not part of that community anymore and so it's difficult to figure out what your principles and values are because you're constantly jumping from one bucket to the next uh online and you don't get a lot of like direct like reasonable feedback from people you just get dipshit feedback like oh you don't believe this well you're a jerk i think the hard thing currently is having the integrity and character to stick by principles one under i don't want to equate murder of in the genghis khan times to uh social media cancer culture but it certainly doesn't feel good when people are attacking on social media and it does take a lot of integrity to uh without anger without emotion without without being without mocking others or attacking others unfairly standing by the ideas you hold or in another way standing by your friends standing by this little group like loyalty of the people that you know are good people i find that uh in in cancer culture one of the sad things is whenever somebody gets quote unquote cancelled everybody just gets all their friends become really quiet and don't defend them or worse i mean quiet is at least understandable they kind of signal that they throw them under the bus i guess uh is one way to put it and that that's something i think about a lot because from coming for me it's like i i hold an ethic i don't know if others hold this ethic maybe it's this like russian mobster ethic of like you should help your friends bury the body you shouldn't criticize your friends for committing the murder like there are certain levels of like you know yeah you have that discussion after you bury the body that like maybe you shouldn't have done that murder thing right uh i don't know you know i understand that that's a problematic um what's the terminology that's a problematic ethical framework within which to operate but at the same time it feels like what else do we have in this world except the brotherhood the sisterhood the love we have for a very small community but perhaps that's the wrong way of thinking perhaps the 21st century would be defined uh by the dissipation of this community of this loyalty concept no we're all just individuals i think you're right and i think you have to have some sort of core framework of principles and beliefs that you operate on and i think when i was what i was referencing is a little bit different and but to speak to your point you you need a framework um of core principles on which you can then base a lot of your other decisions like i believe these three things to be true whatever they are and that will help inform other decisions you make in your life as far as how you treat your friends i've got i've got probably three friends that if they called me right now and said let's bury the body sorry lex i gotta go there are other people in my life that if they said uh hey we've got to go bury the body i would say who is this you know yeah so i think it it depends on the relationship i want that's a good it's a really good measure i would love to have i would love that to be in your profile people put like pronouns i would love to put like uh honestly like objectively not self-report but objective how many people in your life if they committed murder you would not ask any questions and you would help them hide the body right like i would love to know that number for people yeah and and i think it's a weird thing too because you think right away like okay it must be the group of people that are the closest to you that's who you're first thinking of right but obviously for like my best friend i would do it no question about it but i've got other people that are close to me that are close to me in other ways and i probably wouldn't do that only because i don't think they do it for me yeah and and that is a consideration um so i guess is the principle there then that you do for your friends what you think they would do for you is that the underlying principle or do you just have a blind loyalty to you know people in your life for different reasons i got people that are not on my inner circle that i probably wouldn't help change a tire at two in the morning if they were on the highway but if they called me and said hey we got to bury the body i might show up for that it's just these weird different connections yeah it's fascinating yeah i have uh close friends that like i probably exactly the tire is a good example would be like can't you find somebody else to do this i think part of that is just this leap of faith into like giving yourself to the other person that uh creates a deep connection that makes life fulfilling like meaningful that doesn't exist if you don't take that leap i mean it's not about the murder we're sort of focusing i think that's a i think you have to uh what does it cross that bridge when you get there i'm not exactly sure this is just a thought experiment but it's it's i think about that a lot especially these covet times and as like people become more and more isolated and separated from each other like how important is it to have those deep deep connections to other humans i think especially like what you're talking about there have you ever seen the movie the town there's a great line in the movie where one of the main characters walks into his friend's house and he says i need your help we're going to go hurt some people and you can never ask me about it again and the friend looks up and he says whose car we taking that that is the type of person you need in your life and the people like there are people that will walk through that door and say that to you and you drop everything you're doing and then there's the people that walk through your door and you're like you know what i got a hot pocket in the microwave i'm a little bit i'm a little bit tied up right now but i'd love to help you out but you know i don't want to do that and you don't have that that deep connection with those people you mentioned uh some principles that you've uh changed your mind on is there do you want to go there is there some interesting principles and the process of changing that uh is useful to talk about i can't really cite a specific thing except that understanding that the principles that you have at different points in your life can change and it's okay to change them without being a total pussy and being bullied by other people into thinking what you thought was wrong if you come to these conclusions of your own volition and you decide to change them that's great and it can be really it can be really liberating it's really liberating to have an idea that you hold so true to your your core belief system and then to actually have someone change your mind for you and be okay with it as opposed to being like no i gotta die with this i gotta die with this it's really liberating there are definitely our ideas you wanna die on that hill and no one's ever gonna change your mind but it's really liberating to be confident enough to say change my mind i'm lucky enough to have some smart motherfuckers around me who can tell me listen you're being a total dipshit like let's let's rethink this or like i have one friend who does the five wise all the time and he loves backing me into a corner and what's the five wise you just like when someone makes a statement about something to really get to the core issue they say if you ask why five times make a statement well why is that and you answer that well why and you phrase the y's differently obviously but then you get to the core they say five times you can get to the core of the issue and uh that's a challenging thing but i find later in life it's so liberating for me to be confident enough to be like man was i fucking way off the mark on this and have my mind changed and be able to say that to others that i was wrong totally that ability and i never used to have that and it's it feels real good and there's a hunger for that too um yeah if you're you're so right actually on a personal level it feels very good exactly as you said it's liberating because you're free to then think as opposed to defend yeah without thinking yeah you get so sick of defending the same thing over and over and over and you start to think about it and it's like well i i would really like to evolve my thought process here and when you're constantly defending you know one point it's difficult to let other ideas in you you you discount the possibility that you can have your mind change when you're constantly on the defense like you have to have a crack in in the front line in order to let a new idea come in and possibly flourish and maybe the new idea doesn't even prove your current belief system to be wrong but maybe it's like the the water to a seed and it grows and now it's something even bigger and better yeah and you can you can start to work with that instead and it's a it's a tough thing because i'm a stubborn fuck and it's very difficult for me it was historically to say i was wrong about this one or i messed this one up or yeah i wish i could have that one back there's a public figure for me thing too which there is there's a difference between changing your mind with a small circle of friends and changing your mind publicly about something but it has equal it one echoes the other it is equally liberating but people um people will not make that change easy uh but it doesn't matter that's that's the point it doesn't i think it's ultimately liberating as a human being public figure or not to uh to think deeply about this world and uh to keep changing which is like i i think there's a deep hunger for that in like political discourse that people are so tribal currently about politics that they want to see somebody who says you know what i changed my mind on this right and and then keep changing their mind and keep asking questions keep showing that they're open-minded all that kind of stuff but you want someone in a position of political power to change their mind because they realize that there might be a better way not because they realize that by changing their mind they're going to get a new demographic to vote for them that's transparent as shit nobody wants to see that right like that's right that's a person who can't separate their their their position from their people they're supposed to be helping yeah and you can usually smell that that's uh we're just talking uh offline about uh there's something about hillary clinton where she talked about changing her mind on gay marriage yeah that it felt like this is a political calculation versus like really deeply thinking about like what you know what things do we do in this world that violate basic human rights like really thinking about deeply and you know of course politicians are calculating there's but you can see it you this is the thing that's why i like um as on the human level there's like political policies but there's also humans and i've always liked bernie sanders for example i don't know not the later perhaps bernie sanders but i used to listen to him back in the day and never it felt that people might disagree with me but it it felt like there was a real human struggling with ideas whatever agree with him or not it felt like he wasn't doing political calculation he was just a human he couldn't be further away from my political ideals but also like there's an obvious authenticity to his passion for what he's saying that is not present in other candidates and you could see it all these people that have been in politics forever like from all the way back when hillary was a lawyer in the 70s there's a couple of shots of her in the courtroom in the 70s though she's looking all right she's got those big glasses on yeah kind of a little bit of a nerdy babe back in the day [Laughter] wow john clark says hillary clinton was a baby back in the day 73 hinton clinton yeah that's an interesting question about authenticity and politicians do you think like uh hillary clinton just the clintons in general are a good example that why do you think they become over time so inauthentic is it the system that changes them is it their own hunger for power is it uh what is it or they or were they always inauthentic well first i'd like to say that i don't know if you know this but i come from a bit of a political dynasty myself uh i was on the student government several times in high school and my dad won um the runoff in a special election in bradenton beach florida i think there's like 700 people there so so your dad got you the job yeah we're basically a lot of people compare us to the kennedys my guess with the politicians is that and you can you can see it now as we're becoming more like cognizant as people to the political process i think the process corrupts people and i think that i don't know the ins and outs of it i've listened to people who are far more educated on it than me and i i'm unprepared to cite any of their points i think you can see it a little bit in dan crenshaw can i say this yeah so i like him i i really liked dan especially like a year year and a half ago he seemed very level-headed it's clear to me now that as he panders more and more to the right it's because he's setting himself up for a presidential run it's clear that that's happening and he just doesn't seem like the same authentic ideals oriented guy that he did a year and a half ago now i could be wrong on that it could be way off but i think that you can take someone as honest as you want to when you start them on that path to the presidency you become so unbelievably beholden to so many people and entities along the way that by the time you get to the the final destination the oval office all you're doing is paying back the favors that got you there and you never get to serve the people you're supposed to serve your your primary focus is on your office and not on the people that you're supposed to be helping i think that that's a humongous problem and like we could talk all about campaign finance reform in the two-party system but at the end of the day the people who are running for political posts they're working to keep a job they're not working to improve the lives of the constituents which is different a long long time ago like a lot of politicians like those were like part-time jobs you know and they were they held other posts and you know out west they were ranchers by day and sheriff by night whatever the case might be but now you have such a cushy path for the rest of your life that the goal is to just be a politician yeah not do the things that you think a politician is supposed to do and that's a problem by the way i'll talk to dan on this box it's funny i i like the version of him from a year ago and i haven't been really paying attention so i'll be i'll actually pay more attention now and ask him that exact question like how do you prevent yourself from changing becoming what the the clintons became i tend to believe like there's conspiratorial stuff about clinton's and all these politicians that tend to believe that they were actually good thoughtful people back in the day at some point and the system changes them on the it's not even the system there's something about just the process of campaigning i just think it wears you down to where if you look at the percentage of time you spend on the kinds of conversations you have it's like one you do these speeches which you repeat the same thing over and over and over it beats the uh the process of thinking you just exhaust your brain to where you're not thinking anymore you're just repeating it's very right it's exceptionally difficult to keep making speech after speech after speech saying the same thing over and over and over again and at the same time thinking deeply and changing your mind and learning and then also the pandering to financial like having phone calls like fundraising all those kinds of things that's what they do now they spend most of their time fundraising they're not worried about anything sorry to interrupt you but i was going to say that you can see there's a fuel like the the more attention and the higher regard you're held in in your community and the more sycophants like continue to blow smoke up your ass the more it changes the way you present yourself and you can see it in in every walk of life i mean jiu-jitsu is a tiny tiny little section of the world but you see it in the jiu jitsu community when someone all of a sudden starts a social media page or whatever and they get a bunch of people like basically like you know cyber fellating them on their instagram page they they changed a lady is that a word i think so so giving fellatio yeah it's afflating yeah jamie look it up i think but in those people they it changes their character yeah it changes who they are because they become emboldened and you know now they've got this like mythical cyber mob behind them there's a sign at the entrance to your gym that reads for every moment of triumph it's a quote by hunter s thompson it reads for every moment of triumph for every instance of beauty many souls must be trampled what does this quote me do that quote to me is about mostly about sacrifice and it's about to achieve anything great or anything beautiful or to triumph you have to have sacrificed so many things to get there unless you're the most unbelievably genetically gifted person in the world and greatness is just you know falls upon you it's just raining from the sky i think on your path to greatness on your path to success and triumph you leave a lot of carnage in your wake personal relationships other goals things that you didn't pursue um you know other unfulfilled dreams and you kind of have to sell a lot of that out in order to be really the at the the peak of your field or or what you want to be um i know that that's happened in my life i mean there's tons and tons of relationships that you know couldn't survive the way that i was living my life because when i was trying to be a big time fighter or like when i was just training all the time tons of relationships uh dissolved themselves naturally some not so naturally some people get it some people don't get it some people hate you um you miss tons of other opportunities and i think that's kind of what that quote means to me it's about sacrifice it's about you're giving up what you want now for what you want more and it's the the trampling of souls it's messy too because it's not clear what what the right path is like that sacrifice is not obvious that um that's those are the right sacrifices to make you might be you might be ruining your own life but the the fact that you're willing to take that risk and uh sort of go all in on the whether it's stupid or not to go all in on something that the possib the possibility of creating something beautiful is there who says it's stupid if you're going all in on it you don't think it's stupid someone else might think it's stupid but i mean who really cares well i'm of many minds on many things so i feel like there's certain minds certain moods of the day where you think it's stupid like relationships is a beautiful one which is you've seen the movie whiplash by any chance yes it seems like in a man's life or it could be a woman's but i'm i don't identify as a woman so i know the man them the lyrics it's 20 20 bro but my lived experience for now is that of a man we'll see about tomorrow and there is in the pursuit of excellence there's often a choice of um some of the souls that must be trampled are personal relationships with humans in your life that you might deeply care about it could be family it could be friends it could be loved ones of all different forms it could be the people that your colleagues that uh depended on you people who will lose jobs because of the decisions you make all this kind of stuff it seems that that moment happens and i'm not sure that sacrifice is always the correct one like to me the movie whiplash for people haven't seen a spoiler alert maybe i don't even know if that movie has any spoilers but there is a relationship with a female there's a student that's a drummer that's pursuing excellence of this particular art form of drumming and he has a brief fleeting relationship with a female and he also has an instructor that's pushing him to his limits in what appears to be awfully a lot like a toxic relationship and he chooses not chooses he naturally makes the decision to sacrifice the romantic relationship with the woman in in further pursuit of this chaos of this chaotic pursuit of excellence and it feel that doesn't feel like a deliberate decision it feels like a giant mess of like an emotional mess where you're just like kind of like a fish swimming against stream just like fuck it you let go of all the things that convention says you should appreciate you you throw away the possibility of a stable life of a comfortable life of uh what society says is a meaningful life and just pursue this crazy thing full of toxic seeming toxicity with crazy people surrounding you i don't know so i don't know what the right decision is like part of my brain says you should stay with the girl uh fuck that instructor that's making you uh that's pushing you to to places where it's like that are destructive potentially destructive like could lead to suicide could lead you to uh completely uh fail or fail on your pursuit of excellence or destroy the possibility to destroy the dream the passion or pursuit of the thing that you've always dreamed for in that case is drumming i don't know i'm on many minds there like what is the right thing to do so my first two thoughts are number one fuck convention what is convention it's like a some laid out path some linear progression of the way your life is supposed to go like you know that someone can draw a picture of at the end that shit's that first of all it's just boring and whatever and it's it's i don't want to say that it's cowardly because it isn't cowardly but for someone who's not conventional to not be non-conventional is cowardly to get sucked into the convention that's first second of all i believe that scene in the diner in that movie where he tells her yeah you're in my way because i'm gonna want to be with you or you're going to want me to be going out to dinner with you and i know i should be practicing or i know i should be training and ultimately i'm going to make i'm either going to feel bad about not being with you by training or i'm going to skip the training to be with you and neither one is right the whole thing that they don't mention in that is that that's the wrong girl that's the wrong girl the right girl is a gangster the right girl says oh you you you've practiced tonight i'll leave you a sandwich and some milk so that you can you know uh outside the door uh let me know when you're done or you have some like free time like the right girl compliments that she's not an impediment in any way even if what you want to do is be with her so much that you're putting the drums down you're putting the bass down or you're picking up the pizza or you're not going to training like that girl without even telling you why she's making decisions is making decisions to help you achieve your goal now that might sound like some sort of like chauvinistic king of the castle type shit like where everyone should cater to you but the fact of the matter is uh that person is a compliment to your life and helping you do your thing and in your own way you're helping them to achieve whatever their goals are also it's uncommon that you have two people under the same roof striving to be unbelievably excellent in one small area it's not impossible but it's uncommon like relationships have to be like binary systems like two stars like the gravitational pull is what keeps you together and circling around one another right and and you know one is bigger than the other and they'll fluctuate and you know the stars will get bigger and they'll get smaller and they're contract based on positioning and you know composition that that's the way a relationship should be not an asteroid coming in to disrupt you know your the the surface of your planet yeah it's a binary system it's a compliment that girl was the wrong girl for him so you shouldn't uh like the big unconventional dreams should not be adjusted to fit into this world because i mean there is a part of me that's like full of salt out well maybe you're just a dick maybe maybe who cares lex so first of all who cares this is uh by the by the way somebody who's uh you have you have recently gotten well recently in the span of the history of the universe is recently you got into a relationship but you haven't always you have not felt the need to be in the relationship just because you're supposed to by society's kind of momentum if you i think that if you really want anything you've got to be prepared fully to be the exact opposite if you're a person who's looking for a relationship the only way you're going to get in an awesome relationship is by being comfortable being alone yeah because that's the risk if you're a person who's driven by money you've got to be comfortable being totally poor because that's the risk right and when you're when when you're when you're constantly hedging your bets you're never all in you're never all in on the thing you're trying to do um a relationship has to complement your life you can't say it's okay to want to be in a relationship but you can't want to be in a relationship so bad that you take someone in who fits the suit and it's like oh our schedules kind of work out you live near me and this and the other thing because the logistics of a relationship are not always perfect it's what matters is when the two people are together that's the perfect part of it and it's great to want to meet people and say if we meet and some sort of a relationship develops i'm willing to run with it but i'm not meeting you hoping a relationship develops i think you kind of put the cart before the horse in a lot of those situations it's like when guys meet like no guy goes out and is like i'm looking for a bro right nobody does that you go to the gym and you run into a bunch of dudes and the next thing you know someone's cool and they want to talk about fighting and you're fucking shotgun and beers and all of a sudden you got a bro yeah and that's how it works it works the same same way with what's the shotgun and beers um i'll show you after this you poke a hole in the bottom and you open the top yeah this is the problem with america drink vodka like a man okay now don't poke holes in beers this is the problem with the frat culture they don't really know how to drink they think they know how to drink they don't know how to drink what do you think makes a successful relationship if we can linger on that a little longer like let me ask john clark about love i didn't ask a question but let me just say love about love uh are you one of those people who never says i love you no no i'm an extreme person and uh like my emotions are also extreme and one of the things uh i concern myself with maybe this is philosophical and martial arts warrior soldier type related stuff is like i don't want anyone if i die tonight on the drive home hopefully that doesn't happen i hope that no one is left questioning how i felt about them and people i don't like probably are not questioning that and so the the thing that i've had to learn how to do later in life is to tell the people that you care about that you care about them and um each thing can be equally off-putting to the receiver of the message each thing can be equally upgraded when you're letting someone know how much you dislike them that can be off-putting to the person receiving that message and when you tell someone how much you care about them it can also be off-putting to the person depending on how they view their relationship with you but it's still important to get it out there like you shouldn't you shouldn't hold those things in because you're worried about how they'll be received or if they'll come back at you so you're okay going all in yeah on these yeah you're not afraid of commitment no i'm not afraid of commitment anyone who says they're afraid of commitment is full of shit you know what they're afraid of they're afraid of commitment with that person that's what they're afraid of like you no one when someone knocks your your knocks you on your ass and they come into your life and you're flush with all these emotions you're not worried about oh i don't really like commitment no because they've knocked you on your ass you want to be with them you want those things the the two most alive points in your life i think people feel is the euphoria of a new relationship and the law and then the loss when that love is gone you know you'll never feel more i don't think than in those those moments in in your life see the nice thing about the loss is it lasts longer yeah that's a lose ck point that he makes which is like uh that like uh he in his show i think has a conversation with an older gentleman that says like that's his favorite part of the relationship is that period between the loss of the relationship and the real death which is forgetting the person but that period lasts the longest and that's the like the most fulfilling like missing the other person is as fulfilling as the actual like love the the early infatuation which is interesting i also think of the bukowski i returned to that there's a little clip of him in an interview saying that love is a fog that dissipates with the first light of reality or something like that so basically emphasizing that it's this very very very fleeting thing that it's a it's a moment's thing and then it just fades and everything else is uh is something else so love is only a temporary thing which is interesting i think some people say that's cynical i don't know i don't know what to think of it i think it's important to understand that everything is fleeting when you don't put effort into it almost everything will be fleeting if you don't put effort into it most people will get fat and lazy if you don't put effort into something you're going to not be good at uh playing guitar or playing bass you've got to put effort into it the same thing goes for a relationship that the the awesome part of it that like love part that dies soon and early on in a relationship because it's so good that we think we don't have to work at it but you do you have to like keep doing the things you got to keep things new and crisp and fresh and you know when you when you different people probably feel differently about this but like i don't know you walk around your girl and you start like farting and stuff like that's when it all dies yeah that's when it dies you know we're all human beings we all you know have you know we're all here and our bodies working the same way but like you start to chip away at this like beautiful thing when you when you stop when you buck conventional courtesy and and things like that well take it for granted basically take it for granted yeah i mean that's the same thing with life it's like it's the same i'm a big fan of meditating on death that you could die today in the same way you should meditate on like this relationship could end today this connection with another human could be this is the last time you could uh you could be interacting yeah and your your chances of that increase when you take it for granted and you shit on people but when you work at it the chances of that decrease it's not it's never going to be zero but it decreases and and when you do that when you're the person and you're you're trying to maintain and you're trying to you know work at the relationship you got to make sure that both people are working at it otherwise you're just a fucking chump okay let's uh return back to uh mixed martial arts let me ask the ridiculous question of uh who do you think are the top three maybe top five greatest fighters of all time it's so hard to compare fighters across generations and maybe on one way to say it is which metrics would you put on the table as to measure what a great fighter is there was a guy named dioccipus [Laughter] in the fourth century yeah and he was such a badass that in the olympics in 336 bc no one even showed up to fight him in the pancreatic event nobody even showed up because he's fucking everybody up years later he was retired and uh this crazy macedonian dude came there at some dinner for you know alexander the great everyone's chilling drinking you know whatever they were drinking out of their chalices and this macedonian dude threatened him and challenged him so dioccipus said yeah man we'll throw down and you know they set the time in the place macedonian dude comes out like body armor spear shield all this other shit the octopus came out absolutely naked with a wooden club and took on this much younger guy beat the living crap out of him and then put his foot on his throat uh and then didn't even kill him in the show of ultimate power for the time so i think there's something about the guy being naked too it's just extra demeaning extra demeaning yeah okay can we rephrase the question then because those are clearly going to be some probably forgotten warriors in history let's take it to like modern day mixed martial arts in the ufc perhaps well just mixed martial arts there who do you think are the top fighters of all time what metrics would you consider in in trying to answer this perhaps unanswerable question i think one of the things you want to think about is a strength of opponent at the time you fought them so for example fighting bj penn in his prime and beating him is far different than beating bj penn last year right so to say you have a victory over bj penn it's not the same given the time frame of when it happened not to take anything away from anyone was being b.j penn just use that as an example of someone whose career went into a different direction yes i would say the guy who i think is probably the best that people are the least familiar with would be marilla bustamante and i think he was a guy who was one of the guys with the first really good physical build for mma which i think is narrow from the chest to the back and long shoulder to shoulder and kind of sinewy made out of steel cable that was a guy who could box that was a guy who could wrestle and that was a guy who had great jiu-jitsu i wasn't a great kick but at the time he didn't need it fought everybody and gave everybody a run uh i think he's probably one of those guys who's got to be considered yeah there's a few killers that never because like why is he not in the discussion is it because like i think greatness requires both the the skill and the opportunity to meet each other and when you talk about a fighter the other thing that really a good fighter needs to become great is a foil yeah and so many fighters don't have a foil that's one of the biggest attractions i think of early mike tyson's career he didn't have a foil he had no one driving him and by the time he did by the time he had a foil in holyfield his career was in a different place but he he's one of the greats of all time he never really had a foil so his greatness was in the un unparalleled destruction of like nobody right well not you know uh of lesser opponents right and so when people uh debate the you know the level of greatness of mike tyson that's one of the things they say like he didn't fight a lot of killers in their prime i think you've obviously got to say in that conversation i have a really difficult time keeping george st pierre out of the conversation uh only because he was able to beat you with anything he could he could out jab you he could out wrestle you and he could he could submit you the problem i have with fedor is his career also took a drastic turn towards the end and when he was fighting in pride he was doing a lot more grappling and then he just started casting that overhand right at people and his game kind of changed at that point uh he can't take anything away from his greatness but at that time the great heavyweights were not really uh in fighting in pride and they didn't really exist yet and by the time he fought a really good one fabrizio over doom he did get submitted there does does his later performance color our your and our perception of his greatness like in general about fighters not mine but i'm someone who's like intimately involved in the sport but it colors everyone else's same with anderson silva like i don't think anderson doesn't want to fight in like seven years or something or he's like one like that's a guy who in his prime was one of the best fighters is he in the top five for you i think he's probably in a top five yeah greater striker of all time or no in mma and in mixed martial arts and mixed martial arts that's a tough question the greatest mma striker of all time because like the timing the we were talking about foot sweeps right yeah who makes it look easier and uh anderson zilla i think in an incredibly short sample of his prime it's got to be anderson silva and i think you have to consider discussing leota machida for his unbelievable manipulation of distance yeah which is something that people don't really talk too much about in terms of fighting unless you're someone in the sport yeah the his his use of distance and the ability to like what we call pop out like and make you miss by one inch so that he could follow your fist back in as you retract it and hit you over the top that that's a thing of beauty anderson silva when he became a counter striker when he got to his prime in the ufc that was a thing of beauty that was the thing of beauty um so i think definitely those two guys and maril bustamanti's got to be the third guy they're just so many good guys now so where do you put in terms of metrics as you mentioned gsp and anderson silva i think they have a large number of defenses of a title is that important to you like this kind of consistent domination no because it's too much it's easily easily manipulated by the people making money off the fights so there's a great quote one time uh when ufc was coming to prominence and uh vince mcmahon from the wwe he said you know the difference between what we do and what uh ufc does is that when we have a superstar i can make sure he stays on top until he's no longer a superstar because we have predetermined results yeah the ufc can't do that because they're actually having fights well it's true and false you can't do that but you can give your superstars the most favorable match-ups to keep them on top for the longest so people always talk about title defenses as if the guy they're fighting the challenger is always the person most deserving of the shot and it's just not true so i don't put that much stock in it is it possible to put a guy in the in um in consideration of one of the greats if all they had is one or two amazing fights i'll tell you like and and amazing could be a lot of different definitions it could be just a war like they never really reached the highest of excellences of domination but they've like this we had this discussion about kyle bochniak right yep uh to me that's the perfect example he had this famous fight uh against the beat magametr sharapov where you on one side you have an anderson silva type of fighter and ends to be like just a very good striker like and then there's like the warrior on the on the kyle's side and just the fight they created something special together it was fight at night whatever but the you know that fight was special on that night because because the two dance partners you can have a great performance without being a great fighter not saying neither of those guys is a great fighter but to answer your first question uh i think that having one or two great performances does not necessarily mean that you're great when i need a larger sample size i have no idea what that is i don't have any idea what that is and also where how much weight does toughness have when you're thinking about the criteria when you define a great fighter that's that's that's a good question and i don't have the answer to it i admire the underdog that rises to the occasion through brute force they didn't have they didn't bring the skill set to the table that perhaps some of the greats have but they rose to the occasion i mean there's something about that there's something about that and so now we're more talking about like uh the internal attributes as opposed to the external physical attributes and those are the things i think that you cannot teach those things you you come in the door and you either have that or you don't i think and we talk about this all the time and this is one of the things where my mind changes regularly like i'm what makes a fighter is it is it born or is it bread and this week i'm of the opinion that uh it's in you and maybe it's in you and you suppress it and people can tease it out of you but i don't think you can make someone who doesn't have that seed in there i don't think you can turn them into that great warrior with that level of grit and mental toughness now when that that fight when kyle footes a beat it's a unique situation for both guys it was kind of a later later replacement fight for kyle it's a beats star was on the rise and kyle put the blueprint out there on how to beat the beat um which is which is uh pressure him and try and drag him into the late rounds you notice that later on when uh calvin kater fought him they wouldn't give him five rounds they wanted five rounds and it's a beats camp from what i understand would not agree to the five round fight well he didn't look right so with kylo was a three-round fight three-round fight and what did uh he went to decision it went to decision was a beat one a decision clearly did kyle have a shot of winning the third round i don't remember the exact score but kyle could have won the third round had he done a couple things differently but i do believe in the fourth round i think kyle would have won a fourth round and i think maybe even won the fight and if there would have been a fifth round and he was pressing forward uh like perhaps you know in a funny way that you could tell me i'm wrong but it felt like he wasn't emphasizing like head movement at that point he went full mike tyson there was a there was a point at which so it's funny that you say that which is a contradiction actually because mike tyson had a great headache i actually don't know exactly what i mean because he was in the pocket i think he was trying to do the movement he was just in the pocket and pressing forward and like the fuck you attitude it was just like yeah that was a little bit later once it beats backwards towards the cage but the we we get that fight and i said to kyle i was like look this kid has been training martial arts since he was three years old there's not an area where you're gonna out technique him and so we've gotta now channel some of that grit that we know you have this is an opportunity to showcase it and i don't know how long i did it for but um because kyle's much shorter than the beat so for a good long while while we're training for zabeet i didn't even say anything and i just had clips of mike tyson training on the tv in the gym and the head movement and i didn't even mention it and then we started to like get into it and talk about you know getting inside the length of the longer fighter and uh things like that and we we kind of which when some people train mma they say okay this guy's a really good wrestler let's think about avoiding the wrestling or being a better wrestler and i think that when the difference in skill is so great those are both the wrong answer if a guy who's a really good wrestler wants to take you down and you don't have a lot of wrestling experience he's probably going to get you down if he's got a good coach right so you have to deal with that to then say i'm gonna then learn in eight weeks how to wrestle better than a guy who's been wrestling since he was eight years old is also a bad idea so what we concentrated on for that camp and it worked beautifully was not getting caught in chain wrestling these are the takedowns you're going to get caught with this is how to not get caught with the next step while you're defending take down one because it's the chain of techniques that are going to get you fucked right so we talked we did a ton of work on get ups and breaking the hands from the various takedowns like it was a while ago now so i don't remember exactly the techniques we worked on but we concentrated on defend the first takedown and stay out of the chain don't get chained into a bunch of wrestling techniques because you will be out wrestled um and that was really successful and then in the third round uh beat was tired and uh he was tired he's a beat got tired he cuts a tremendous amount of weight yeah like i i can't see him staying at 145 forever when they start giving him five round fights i don't even know if he's had a five-round fight yet he may have but um i i can't see him staying down there he's the guy's like six one yeah guys he's he's a giant of a guy so kyle pressed forward there and he said uh he felt that there was no power left in zabeet's hands and so he felt fine and i think part of it was he fed off the crowd as he moved forward and um you know saw that he wasn't taking a lot of damage like the punches weren't standing him he started walking right through him it goes to your question of what makes a fighter was the him walking forward like that something that you're born with or is that something you were training is that is that the mike tyson on tv born with that kyle is born with that and the crowd i i've been in boston no he's in new york he's in brooklyn i've been in a lot of arenas for a lot of different sporting events that's one of the loudest things i've ever heard when he did that and i was going crazy and um you ask about that being like taught or not kyle is so much like that that i have to try and tease some of that out of him and pull it back because he's also so very technical when he wants to be that the emotion and the fun of it gets in the way of his technique and and probably has cost them a couple of a couple of wins and so that's one of the things we work on with him right now is like staying within yourself being a professional taking your time to download the information in round one and then starting your fight in round two but the tension between those two things what makes uh what on that day created one of the in my opinion one of the greatest fights i've ever seen joe rogan agrees yeah it's one of the greatest fights i've certainly ever seen so like i you it's funny that you as a coach i can see the frustration of like like throwing away some of the strategy kind of thing like you seeing like being not happy that there could be things that he could have done to win the fight it's in retrospect i think that at that time we were playing with incredible house money kyle was a gigantic underdog in that fight his beat was unstoppable i think people were probably picking him to finish the fight in round one i think at that point no one had ever gone the distance with the beat yeah and no one certainly had you know put that kind of performance together and i think kyle uh kyle put the blueprint out there and in retrospect when i look at the last round yeah there were things that could have been done differently but we're playing with house money at that point like i mean let it fly you you get to a point where you've got it you're down three rounds and there's 20 seconds left you got to move all your chips to the center of the table and you know see what happens do you remember what joe rogan said about it i i remember like he got one over i think i have trouble remembering because offline we talked about that fight and he's exceptionally impressed by i mean joe's from boston so it's like yeah i mean there there's a story there okay it sucks not you naturally want to romanticize like there's a rocky versus like uh there's a rocky four dragon i mean um similar i suppose kind of chemistry kyle's style represents the american ideal right the spirit yeah i mean he's from gloucester it's like you could have you could have dragged him off the docks like three hours before the fight and said hey you want to go fight and he would have said yes yeah oh man that was a special fight but that's as per discussion of like greatest fighters of all time i tend to believe that that fight is more special than the the the champion the championship belt defense is by george san pierre like you know there's something to that it's like rocky um rocky one is uh is more special than like rocky iii right so like yeah it's though that yeah the the underdog or it's whatever like the dance partners like going to war and like that moment i mean it's bigger it's bigger than any individual fighter they create that and that i know it's not perhaps good for a career it's not good for like in terms of money in terms of longevity in terms of all those kinds of things but that's a special moment in the history of fighting that you both created i can remember like right after like there was so much excitement in the air during the third round and i remember being in the corner and like i i was so excited at the end of it that i had forgotten what happened in the other two rounds i didn't even know and and i looked to to sean one of the other cornermen and i think i said to him did we win when we re-watched the fight clearly we didn't win the fight i mean we lost the other rounds but i got so caught up in that moment and then i just remember like i was so in awe of his performance that like i forgot what was going on and i i and it's so hard to not be a fan at that moment and to stay within yourself and try and like coach but then what the fuck you even coaching at that point it's like we're rumbling we got 30 seconds we're trying to win here and i remember like the performance itself i'm not a fan of moral victories but if ever there was going to be one that was one and when the fight was over and i grabbed kyle they hadn't even been to the center of the cage yet and i just hugged him and i said you're my fucking hero and i remember being very emotional about that that i was able to be a part of that it feels wrong to say but i was i kind of avoided saying it but if i'm being honest with my feelings this is a safe space for feelings yeah is i think it was the greatest mixed martial arts fight i've ever seen and i don't think i'm being biased i was honestly thinking like am i being biased i honestly don't think so i think that was the greatest fight like if you want to rank fights i've ever seen i think to me that was the greatest fight i've ever seen it certainly was a uh one of the greatest displays of like just dogged effort from an underdog who was out experienced and and probably outsized but i mean like you just kyle's one of those kids you're never gonna tell him he's out of a fight he has something you can't teach and i've seen tons of people with more physical attributes and they're just mental midgets and they got a million dollar body and a 50 cent heart and and and kyle is not that yeah and you can't teach it no matter what you do but that was i would say like my career in combat sports which spans you know if you want to go all the way back to like wrestling like that was one of probably the greatest experiences i've i've been a part of a bittersweet sport she's a fickle mistress yeah i mean the the tragic aspect of that is um like i guess kyle lost right right so like if you look at the record and all the kind of things perhaps uh like you look at the career maybe like as a financial from a financial perspective that perhaps is not uh the the greatest thing for carl's career or that or in in the history of the ufc perhaps it's not it's not um you know like maybe many people didn't even watch that fight but it was a special moment that stands in the history there's not many of these in uh in the history of fighting so but at the end of the day when you look at someone's career in the ufc like financially there's a you know a handful of people that make real money everybody else makes nothing there's a handful of people that make real money so did that loss cost him in the in the near term sure but when you look back on your life you're not going to look back on that loss as something that derailed my life financially and i never recovered from it that's not going to happen like the sad thing is unless you were a champion and you know most most people are going to be forgotten right after they're gone most people will be forgotten and if you're not forgotten certainly your your accolades are going to be misrepresented either they're going to be inflated or diminished one way or the other so looking back on it it's just so hard to to quantify that but it's an experience and like when you're in that moment and you're one of the people like intimately involved in it like the value of that experience supersedes any financial gain where would you put khabib in the discussion of the greatest of all time so you recently we worked together we watched the fight um of him and um justin gaichy and and khabib retired would you put him up there as some of the as one of the greatest or did he never truly find his foil that like the great warrior that challenged him and um and maybe do you wanna do you think he's fully retired now to answer the question about being fully retired i don't have any idea i can't for a second pretend to um think that i understand the way that people from that part of the world think and respect their family and things like that to an american who says oh i promised my mom i wouldn't do it i mean i promised my mom i wouldn't do a lot of things i went right out fucking back door and did them yeah but i think that that means something different to people in different parts of the world so i have no idea what kind of weight that carries so i can't answer that i can say a lot of times when people think about great fighters they think about the aspects that make up mma like they think of mma as a pie and they're all these different pieces that make up for make up the pie and how good is this piece and how good is this piece and how good is this piece when the fact of the matter is is you only need one really really really good piece and the other pieces are complementary pieces to get you to where you're the strongest and if you want to tell me that khabib's not the greatest mma fighter because he doesn't have really slick striking you can make that argument but what i can tell you is khabib has good enough striking to get him to his grappling where he is clearly the best guy at 155 they've ever seen yeah so does that make him the greatest fighter at that division or not to your point about the foil they wanted conor to be his foil and he just manhandled them i mean they wanted that to happen did not happen so well there there's a kind of argument to be made which would kind of not you get haters in this argument and and you're going to be one of the haters okay because i know you're uh uh put a lack of uh admiration for conor mcgregor uh but you know uh what is it football's the game of inches yeah there's there's a sense where you know that conor there's an argument to be made that conor wasn't exactly dominated that he ended up being dominant meaning let me phrase it differently is there's a lot of points in the fight that it could have uh a different trajectory right could have happened so he wasn't so far from having a chance at winning that fight it's just the end you can focus those are the most important moments at the end you've lost the most important moments right but the road less taken it could have been if he didn't lose those very important moments he had a chance so i'm saying out of all the people that could be fought it's arguable that conor was up there of the people that had a chance let me say this first i love you get so much heat for this i do love khabib i'm a huge khabib fan because i'm a grappler first and foremost me too because i'm also russian i love khabib calm down okay but when when when connor came on the scene i loved conor because i'm an irish american and you know i want to support him and things like that and he was he was good fun he he got to be for my personal taste he got to be too much of all the people khabib has fought i would never fight conor again if i were him and here's why and i said this about the diaz fight nate diaz who's one of my favorite fighters has fought the exact same fight for 12 years conor will switch something up to give himself an edge and i believe that conor would figure something out in fight number two i think but i also thought that gage would give could be problems where it wouldn't be a matter of i'm gonna out wrestle khabib or become better at defending his wrestling takedowns conor would have figured out a way to not get wrestled i feel like he's constantly changing he's constantly evolving and whether or not people realize it or not i think conor's one of the better overall athletes in mma just from looking at his body and his movement and the way he's shaped he's got a very tiny waist he's got really pronounced glutes and shoulders and i think he's a real athlete whereas a lot of guys in mma are not for real athletes they're just good at one of the things that makes up mma i understand what you're saying about if this happened if that happened but i mean you could say that about every single combat sports event ever if spinx's hook land landed on tyson maybe that fight didn't end the way that it did but you know what it didn't you're absolutely right but if we could talk about just conor mcgregor for a second i can't wait to get your fan mail or hate mail um speak to the innovation of conor i don't hear very many people making this argument but is it possible to make an argument that conor mcgregor is one of the greatest fighters of all time it's an interesting argument and the problem the only problem with the argument is there's so much emotion on either side yeah i had a conversation sorry to interrupt with uh jaron brook who's a a philosopher objectivist and which is the philosophy of iron rand and the amount of emotion around that particular human is fascinating to me it's similar to the amount of emotion around donald trump you can think of different personalities maybe elon musk those are the people that aren't willing to have their mind changed they're too emotionally attached to the argument yeah but it's weird that why do we why why some people inspire so much emotion and others don't but conor mcgregor i feel like nobody's able to have a calm like uh fight analysis of the guy like look to me as just a fan of martial arts like i study judo i love watching just hours of olympic judo and uh appreciating the art form like i forget the humans involved uh teddy renair who's a heavy heavyweight the most probably the most dominant heavyweight in the history of judo just studying his gripping just the art of it and who cares if there's shit talking like to me um i i put all of that aside and just look at the art and like what i really appreciate about conor mcgregor is his innovation like of movement of maybe it's romanticized maybe you can correct me i'm just uh a cheeto eating fan of mixed martial arts but like i i seem to detect more innovation than almost any other fighter uh that i've pa pay attention to in conor mcgregor i think first to i'll answer in two parts i think well i'm not going to answer the first part it's just a comment because you didn't ask the question what was the question i don't even remember it's about the the how conor mcgregor fans are very emotional and conor mcgregor detractors are very emotional i think fans become very emotional they become cheerleaders of someone like conor mcgregor or donald trump because they see that person exhibiting the qualities that they themselves lack and so they become cheerleaders for that right and i think that for the most part people who are detractors of conor mcgregor's they're not really conor mcgregor detractors they're detractors of connor's supporters there's a beef that they have with the people in that bucket right like it's not really a problem and that applies probably in our current political climate right with donald trump with the left and the right there it's more about like they uh they actually don't like on the other the caricatured the most extreme versions of what they see in this quarters of the other side yeah that's a good point but i think the more interesting thing is the fighter himself so let's put the supporters aside i would i would say that you know what some people know and some people don't know is that conor's base is in karate and the karate style of conor mcgregor stephen thompson um of lyoto machida that type of distance management a lot of times we think as martial artists we think that the sport version of the art we've chosen to pursue somehow taints the authenticity in the in the effectiveness of it but point karate is what led to that in and out distance management style of connor of leota and of stephen thompson they all kind of use it a little bit differently but they use it very effectively all three of them and that comes from a world of trying to kind of like uh step in land contact on you from my point and then get back out before you can counter-strike me right and that's where that comes from conor is blessed to have longer arms than someone his height probably normally has and his movement is just so fluid he's so athletic with uh the hinges of his body the knees and the hips and the swivel of his body which is also the hips and the shoulders his movement his distance and the way he sets people up for the straight left hand while you're circling away from it and he can still land it which is what he did to chad mendes hit him with a straight left while he was circling away from it that is something that is uh very beautiful to watch and sometimes people see the kicks and they see all the flashy snap kicks and the sidekicks all that stuff is doing is setting people up for the left hand it's all it's doing it's you're corralling people you're funneling people or you're leading the dance and you're bringing them to a spot where you know you can land that left hand and his ability to do that is masterful people constantly shit on his ability to grapple and you know because a couple of his losses have been uh to jiu jitsu guys or grapplers but they've been to really good guys like anyone who's gonna sit here and tell me conor mcgregor is not a good grappler go grapple him yeah let me see you grapple him to that point i'll also say a lot of people will use conor mcgregor's x-guard sweep on nate diaz as evidence to his high-level grappling in that fight to which i would also counter nate diaz didn't fight that off because he knew he was so much better at jiu-jitsu off the bottom that he didn't even care if he got swept so is conor mcgregor innovative absolutely um is he one of the best fighters ever it's tough to say because he's such a cash cow that he was fed people i firmly believe no one who who put that conor mcgregor khabib fight together thought khabib would win wow i i remember so at that time it was not completely clear there was a myth of the great khabib right it wasn't completely clear how good is he really so that's interesting and it was unclear how good is conor also right like what uh because because i think to me maybe part of my admiration of conor mcgregor is rooted in the fact that i thought there's no way he beats jose aldo and i thought there's no definitely no way he beats eddie alvarez and so like when he did uh i was like i had to like my i had to my brain was like like there's something broken it was like shut down like on windows like froze we have to rethink this like this is a special human now people who argue he's not even in the running of like top 20 is you know if you look at the number of defenses for example of his belt he had very very little but like to me i'm one of those people is back to our discussion of like do moments make great fighters that i think just being able to beat jose aldon is i would argue in his prime some people might disagree in this uh in in a way where he like figures out the puzzle gets in his head the entirety of the picture and then to be i mean eddie alvarez would he be considered a really good strong wrestler like like or uh not not strong wrestling strong striker and wrestler that could the whole combination of it and also uh what's the other wrestler he fought chad mendes chairman so let me comment on all those if i may so i was at the chad mendez fight live yeah and um there was a jiu jitsu tournament we're out in vegas and so me my best friend came out and we got some tickets that night was supposed to be the first aldo fight aldo got hurt like right after i bought the tickets they pulled chad mendes in he was a little bit out of shape whatever you still got to fight the fight but i don't i don't want to use that fight as evidence to conor's greatness because you know they pulled chad mendez and all he was like hunting and drinking beers in the woods and was a little out of shape yeah but if you want to talk about greatness like that surpasses your in-ring accomplishments i was in the stands that night and the people that came from ireland to see connor fight that night single-handedly set the market for hotel room prices and airline tickets to vegas that weekend these motherfuckers were all dressed like connor in the stands they had wool suits on and big beards and the whole thing i mean probably wearing pocket watches like i never saw more people trying to be someone else never saw more people try to be someone else i mean there's a level of is is there a level of greatness in that i mean i don't know how to like parse all that out you're somebody who doesn't admire that i love that in the sense the following sense i think that people don't seem to hold this belief at all but to me fighting is not just this isn't like a quiet street fight that nobody watches this is also spectacle this is also a story right there's like there's a professional wrestling element to this this is not like you you think it's it's just about fighting if it was just about fighting you wouldn't i mean there's a story to it i guess you're trying to get to it and like greatness has to incorporate that like people that criticize again i might be wrong on this but i i honestly think that uh conor mcgregor not nearly as much as khabib but he he's a true martial artist i think he respects his opponents despite the talk i if maybe i'm misreading it but it feels like he is a storyteller like uh jail son and type of like he's constructed this image to tell to uh to play the story like just the way he acts after the fight the honor he shows his opponents yeah there's a real martial art in there and to dismiss the fact that uh the the the story of the fight is part of it because he doesn't just shit talk this is what people don't seem to understand he's good at shit talking very good and i and i'm with you on on basically everything you said i think that there's greatness to that and i think that he understands how to sell a fight and i think what he did to jose aldo by getting in his head helped him win that fight he insulted jose aldo and his country so much that he knew aldo was going to come forward right into that left hook was that fighting in brazil by the way do you remember i don't recall because i know he insulted all of brazil yeah i'm not sure yes in brazil but when he tried to do that to khabib you could tell that he just was not going to get in khabib's head khabib was unflappable but there is there is definitely something great about how he moves people you know the irish are are like i mean conor's walkout music like for people from ireland and of irish descent like that shit is like very deep yeah you know that it's very emotional song i was to be honest a little bit upset with khabib that he didn't rise i admire that entire culture but there's an aspect to where he could have risen to the occasion of there's the same kind of depth of love of country that russia has and uh is there in dagestan dagestan is a little weird in terms of like but he could have especially with putin's support where for a bit the full russian hat right of like this is the great nation like rise above the uh the culture of dagestan which is a small town boy with the small town values of family and all those kinds of things there's a moment where you inspire entire nations like the step up and be the foil to the to to the great conor mcgregor where also could be becomes the fall to like like both both of them at the fall to each other and become like that fight was already a great fight right but it could have been something historic ali versus freight i mean it could have been really historic and i would argue i guess the biggest disappointment i have and i understand it and i also honor as a martial artist but to i'm disappointed that khabib doesn't seem to even consider the possibility of doing in moscow fight number two so and because that could be narrative wise if they do it right that's one of the could be one of the greatest fights in history yeah i think in terms of khabib and inspiring a country is it possible that by staying true to the values that he had his entire career and getting to the zenith of of his art form and still doing it in that humble way isn't it possible that that inspires yeah 100 so i should i should clarify that i think they're just hearing from people from my my fellow comrades no uh it's they love that they love they love that but they uh there's also a brash beer chugging shit talking thing that people really like about connor and i i do love that but the beautiful narrative would have been the clash the real clash of those cultures so khabib chooses to live the culture by walking away there's also like a clash of them sort of walking not walking away from the fire by walking into the fire of this of this brashness it's the sort of um the cool collected like calmness of the dagestan people it's like you were talking about the saita brothers so they just view it totally differently and you know there are stereotypes about the irish where they're maybe potentially a louder more boisterous culture and i haven't heard of that yet yeah and i mean i thought they each played their part perfectly and all those things that you're describing could have happened maybe khabib steps up and he carries the proverbial flag so to speak for a nation of people and they go to battle but the fight if it plays out the same way is still the fight yeah and it was a it was an okay fight it wasn't a great fight it was you know the fight was okay yeah and i think that again i don't have any idea what khabib's obligations to his family are i don't i don't think either those guys you know is want for more money to do another fight is just a legacy thing it's just about uh you know fulfilling some some part of a legacy and i i just um i admire the possibility of a great legacy of that that is bigger than either of the fighters i think with khabib he kind of um he's not as concerned about legacy i think right there's uh you're a promoter's dream because you want the rematch and the only thing that makes more money than the rematch is the trilogy you got to split the trip split the the the rematch you hope conor wins and then you have the trilogy fight and you now you're all in yeah yeah i can't get into khabib's head but i know putin just the game the entirety of it especially at the time especially if it was trump as president uh if he was as president at the time and and putin and in russia and just knowing how masterful connor is at like because kano would would be a different connor i think he would be a calmer connor like there would be a different uh like because you don't want to be over the top connor with the russian people right no it's it's like uh dangerous that was the episode in the hotel in brooklyn yeah when um some of the russian guys confronted uh artem and then conor came over it's not but the danger of that i mean there is the the element of just like real danger and the real it was almost of war it's uh i don't know it's it was like when when uh when chael sonnen was talking so much smack it maybe it was against vanderlei silva i don't know it was one of those fights where they they just didn't think he was going to make it out of brazil yeah yeah americans don't get it yeah like people take some of that shit in different parts of the world very very seriously yeah but that's what makes it beautiful that's uh that's what makes a great story and i think fighting is very much about the stories not just about the the the particular outcomes of a fight or the skill set matching or like the chess of the of the fight it's also about the story of the greater like context of societies of warring we're like warring cultures we're still we're still go we're we're no longer can have great big hot wars between nations because of nuclear weapons this is our wars that we can have and uh you know in some sense i feel robbed of the great war that could have happened it doesn't mean there aren't lots of wars going on but yeah the big one is not gonna happen there's too much of a balance of power with you know nuclear weapons and technology and stuff but it's not the end of war no do you think there's always gonna be war i think there'll always be war especially in underdeveloped parts of the world um isn't there always underdeveloped relatively parts of the world yeah i mean at some point though you'd think i mean the way that you know uh technology is expanding and we're bringing technology to weird parts of the world that you wouldn't uh think of as technologically advanced the way that uh the chinese are inhabiting certain areas for mining purposes and things like that i think underdeveloped parts of the world will get developed quickly i just wonder like what the nature of that war might be it could be cyber it could be all those kinds of things i think in developed nations it's going to be cyber i think that's probably the next phase of war but i mean i think you talk about parts of the world like the middle east and it's just still going to be warring tribal factions we can't even begin to understand what those people are fighting about over there yet yet everyone sitting in america on their couch has an opinion like you can't even begin to understand it i i sure can't yeah it's back to the principles discussion when um when when what's violated is much deeper than just kind of um anything we can even in a middle class existence can't even comprehend a lot of times american soldiers will go to war because that's what they're told to do and they maybe they disagree with the orders and maybe they agree with the orders but i get a sense that people in the middle east fighting all believe in what they're fighting for it's not it's not a thing where they're told to go do it i believe they're they really believe that what they're doing is the right thing and they're defending some sort of principle are you generally optimistic about the future speaking of war of human civilization do you think we'll uh like you know people talk about the fermi paradox and asking you know why haven't aliens visited us if you believe they haven't visited us you know one of the thoughts is that there's a kind of a great filter that intelligent civilization reach a point where it destroys itself naturally so that's why we haven't seen them they don't last very long there does seem to be a kind of we seem to be advancing faster and faster and faster we keep developing more and more powerful ways of destroying ourselves in all kinds of ways not even you know just even to say nuclear weapons alone but there's all kinds of new ways engineer pandemics nanotechnology agi all those kinds of things it's it seems to be that uh the argument that we are going to destroy ourselves in some kind of creative way very shortly is uh not too crazy of an argument to make are you more optimistic or pessimistic about the prospects of human civilization in maybe the 22nd century like is it possible that your generation is the last generation to be alive on earth no but i wouldn't say that five generations from now that won't be that that could be true i guess i think of it really selfishly i'm a big believer that when your time here on earth is over the overwhelmingly vast majority of people will be forgotten within 12 calendar months people with no family will be forgotten sooner and so i don't give a lot of thought to what will happen to earth or mankind when i'm gone i'm i give more thought to maximizing my time here now and i want to do it in a way where uh i don't um i'm not overtly hindering the future of civilization or humankind but i'm definitely taking a me first approach to how i live on earth do you have a philosophy behind why you have or don't have kids on this topic because for many people when they have kids there's a sense it's almost like a genetic sense or something like that where all of a sudden you do start caring about what happens five generations from now i mean i think i'm just too selfish i mean i'm that's i think that's the easy answer like i i know that your whole life has to change you know your your your focus everything shifts and just don't want to do and also like i think that there's a level of i i guess if i have to like really unpack it there's probably a level of um lack of hope in the future like i don't think it's i don't think the world and humanity is going in the right direction what does the right direction look like i think the right direction looks like people coming back together in in a more uh impactful human way in person touching feeling um talking face to face so all the things you're describing is what we had as you mentioned before when you were like a teenager yeah so the state of the world but that's because your mind was formed then it very well could be it very well could be it's very possible that the virtual reality worlds that we'll create will be actually a much higher level of existence in fact like now we're getting we're moving slowly away from tribalism perhaps you could argue the ideas of nations and we're going we're moving into the realm of ideas and it could be a higher form of existence where we're sort of uh moving past the constraints of our meat vehicles into the space of our minds it depends what you value because when you sit here and you talk about it you know and you're talking about these things in these humongous levels on these macro levels yeah and i don't think a lot of people view it that way i think a lot of people view it as like what am i what kind of pizza am i getting tonight yeah like it's a it's a much different outlook and sure the the virtual world that's on the horizon i'm sure it's got benefits in what and will help people but is it going to help the things that you find valuable like was it going to help commerce okay sure is that the thing you find the most valuable is it going to help communication well it'll help disseminating information is it going to help explain the information you're disseminating probably not is it going to hinder interpersonal communication absolutely and those are things i find valuable interpersonal communication talking to people like the like it saddens me when i go into a restaurant and there's five-year-old kids who like you know slamming away on an ipad and can't make eye contact with anybody or teenagers who don't say please and thank you when they order from the waitress like that to me is wrong that shit's wrong and i don't know this for a fact but i do attribute that to you know using technology as a crutch when we're raising raising kids yeah you know i think those are those are things that i find valuable i tried to empathize i mean i agree with you as a person who grew up in a certain age but like uh prior to the internet i suppose uh but or at least solidified the early philosophies of the way i see the world prior to the injury during the time of aol let's put it this way uh what was your aim screen name i never had one okay dude i i was the last person i knew to get a cell phone i was so anti all that stuff because i just felt like i didn't want to be a part of it i did not want to be a part of it i i joined the underground forum about mma in 2000 or 2001 when i first started training i think right at the tail end i got a myspace but i didn't have any of that stuff and i didn't want any of it i don't know why i just was i was not into it i i felt like like what are the good things that are going to come out of it oh my i'm going to get my package in two days instead of four days does that make my life better i try to uh i try to deeply empathize with a lot of experiences of other people and like one of the things i love like the smell of paper books and books in general and early on this is like five years ago i just gave away all my books and i said you know i'm really going to try to fall in love with the books in the same way i did before but now with a kindle or not a kindle like paper white whatever the ee reader e-reader and uh i'm still not there but i've been kind of trying to fall in love with that experience and the same way i try to think like teenagers are really into tick tock now like making these short videos i try to consider the possibility that their existence will be a much happier one than i've had because of this kind of interaction it's from my sort of skeptical perspective it's like the attention span is so short they don't really deeply think or deeply experience things they construct a social layer that they present to the world and they work on creating this social layer like the presentation to the world much more than really sitting alone with their thoughts and the sadnesses and their hopes and dreams and fears and like working on the project that is their their own like actual person that exists in this physical world as opposed to working on the project of a particular social platform but they show but like perhaps that project like who cares who you are in the physical space maybe what you are is what your instagram shows that's the more important project to work on well what's reality is reality perception is reality right so how other people perceive this constructed thing that's their reality of you but is it your reality like that i mean like we said earlier it's what what you want how you want people to see you is very rarely in line with how you really are or how you see yourself and i mean i can remember being like a 13 year old kid and like when you go through a bunch of you know weird 13 year old kid shit like sitting in my room like turning a red light on and listening to like a sad record and like you know trying to figure out what's going on inside sometimes you like it sometimes you don't like it but i feel like those experiences are lost on kids constantly connected to a phone and like you know i don't know what the remedy for those situations is nowadays like i don't know do they make a tick tock video do they do they blog about it did they you know make a video or nobody blogs anymore bro whatever man or oh a video a story about oh this is what happened to me and blah blah blah blah does that actually help them work it out or does it just create more noise and more static on how to get to the root of the problem and learn about themselves i don't know what future social networks are exactly i do know on a shallow level it does feel good when somebody clicks like on something i think that is more of a drug than an actual deep long-lasting fulfilling happiness but perhaps there is a way to make a social network that does lead to long-lasting happiness that's somehow detached from the physical meat space i don't know but it feels like you want to give that a chance do you think when people are liking things on social media do you think there's just a group of people an overwhelming majority of people that are going to like whatever you put out there they're clicking like and then there's another section of people that just constantly scroll and like scroll and like and scroll and like like do you think when you get a like on content you put out that that like perhaps came from someone who normally doesn't like your content but like you've just changed their mind on something or you you've turned them around on it i tend to think that when i get likes on social media those are just the people that like all my shit no matter what i say like they probably don't even read it like i could you know put the most preposterous thing up there and you're still gonna get a handful of the same exact likes that's interesting but i i tend to the way i see likes you're kind of you said multiple things i think in one sense you see social media as like a battleground of ideas and like is it kind of indicate like the best possible like is an indicator of like of the of you winning over somebody on an idea and they really appreciate the idea that's the best possible like to me a like is just two strangers smiling at each other like like a moment of like like i got you bro yeah i got you bro yeah yeah like fist bump like yeah we're in this fucking thing together this whole thing doesn't make any sense but we're in this together and i yeah it's possible for likes to be that i i don't think the actual clicking of a like i think social media at his best might be that where it's like i got you bro and it's a large scale as opposed to kind of uh this weird uh like crazy pool of dopamine where everyone's just obsessed with this likes and likes and and then the division drives like more of this like weird anxious engagement i think that's just the dark version of it in the early days of social media i think you called it uh a battleground of ideas but i think social media is nothing but a battleground of fragile egos well but humans are fragile egos i mean maybe but i think the people i think particularly on social media they're the most fragile like would you be doing all the things you're doing what would you be doing if you weren't um if you weren't podcasting and posting the things you do on social media what would you be doing you'd probably be much the same guy right but i think that on social media the fragile ego people what you see on social media is not what they'd be doing without social media does that make any sense like you're you're probably your mission is probably somewhat congruent in your path you're just utilizing social media but i think a lot of people social media has changed their path and and now they're doing something totally foreign to them and they're only able to do it maybe because of social media i think you're focusing on a particular moment in time of people in their less great moments like in their less great version of themselves i think you're just focusing on the masses struggling to uh to become the best version of themselves and then you yeah sure for stretches of time whether it's days weeks or months you could be a shitty person on the internet i think you're focusing on that and unfortunately social media platforms emphasize they love it when you're like that when you're not doing great in your own in your own life because it increases anxiety increases engagement makes you more susceptible to an argument and then really get pulled into like conspiracy theories all that kind of stuff but the other side works too i think there's also the people who are on social media like fronting like they're these positive figures and like you know going to the gym like whatever it is the positivity that they spew out but in real life they're the most negative fucks you've ever met in your life and they're just so full of crap and it's just you people playing to an audience it's like you like you said like they it's like a politician sometimes like a politician wakes up one day and they decide who's the group i can pander to the best to get the most likes equals votes yeah and it's the same thing on social media people wake up and whether it's conscious or not what's the group i can pander to the best to get the most likes is it the positivity motivated crowd is it the woe was me crowd like what is it who's going to give me the most likes that's what i'll do i i don't know how to argue against that i guess it's it's uh it rings true what you're saying but i just kind of refuse to believe it i guess i'm pandering to the optimistic crowd like i met with my marketing team and i just feel that uh uh love has the uh the best uh what do you call it no i don't know there's a lot of people that accuse me of being like exactly that which is like why are you always being positive it's like well because i i'd like to be that yeah but i don't i wouldn't consider you someone who panders no but you know it i guess what i'm saying is like uh it's easy to say that everyone is pandering but like maybe they're just trying i i do believe that social media platforms could encourage people when they're trying to be the best version of themselves whatever that is it could be like conor mcgregor talking shit it could be just being positive it could be actually creating cool things in this world um putting out instructional videos for jiu jitsu or like inspiring students to competition all i don't know all those kinds of things educational content i i think that people are trying like i i tend to believe that people want to be good like like they want to be successful whatever that definition of success is and they're kind of struggling to do that and they're just awkward at it at first and like it's easy to focus on the awkwardness and the the stumbling around us people have that and they start shitting on each other like it's easy to kind of focus in on that but i think that's just like people you know white belts there's more white belts in the world than there are black belts but you gotta give them a chance to kind of grow i think on social media if you put your stuff out there whatever your stuff is your content your views or whatever you let the chips fall where they may like that's a different thing than being like i'm gonna i'm gonna tweak what i normally might say and put it up this way because i want these people to like it and in terms i also think i have a different viewpoint than you do on people wanting to be successful i actually don't think that many people want to be successful i think people want to have the appearance of wanting to be successful but to be successful takes a shitload of work and most people don't want to put that work in so they craft this persona of a person who's trying really hard but just can't catch the break or you know these motherfuckers with getting back on my grind you've never been on a grind you've been on the couch i so disagree with you i get it i get it you you that's your foil you enjoyed that guy in the couch with the cheetos that's you that's that's your motivation but just own it be like don't be like back on the ground be back on the couch yeah well you you you're like david goggins who's like talking shit to the one guy with the eating cheetos and in in so doing inspires millions to like to actually pursue their success i get it but i just think that most people really do want to be successful and are like are trying to work hard and they keep failing uh so i mean but why is it why is it continue i'm sorry to interrupt you but like let's take a person who's overweight yeah do you not think that person wants to be skinny of course they want to be skinny they just don't want it enough to put the pizza or the pie down and go to the gym they want it but they want it to be easy of course they want to be skinny well of course he wants it to be easy right and of course people people want to be successful but do they want it enough to do the work i don't think they do i think the easy thing to do is to to create a uh an outward facing persona of the person who really wants it and you get the same reward from a lot of people as the person who actually is successful very few people differentiate from the person who's found success and and the person who's showing you how they're trying to get success on social media people see that as the same i see i see you're going after the marketing dollar that represents the the people that want to work hard yeah i like it uh you uh started a podcast recently oh yeah called which people probably from this conversation can i guess we didn't really talk about politics much or the fact that you're a business owner the fact that you're a red-blooded american and love this country uh uh america we wouldn't really talk about that but from the name of the podcast they can probably infer it and the name is please allow me good name uh what have you learned from doing this podcast what's your hope of doing this podcast for people should definitely listen to you have a few episodes out you're damn good at it which is very interesting i'm sure you'll evolve and change but so this is like the early days i'm curious to see where it goes but what like what's your thinking around it as a as an intellectual putting your thoughts out into the world i think that one of the things that covey did um when we were all kind of in lockdown was as a business owner it made me take stock of what's the future of brick and mortar businesses and i've always been reluctant to be an online presence in any way just because it's not my thing because i believe that i'm a force of nature and people need to experience me right and uh the the few characters that twitter has or faces not enough to experience not enough the force of nature there's john clark oh yeah right i want you to feel physically uncomfortable around me i've just been three hours of me being physically uncomfortable i'm scared for my life uh and so i thought that that would be one of the ways in which i could increase like i i came to the conclusion that with the the lockdown and potential future lockdowns you know uh in order to pay my mortgage and you know my bar tab and my grubhub's out of control that i would need to find ancillary ways to doordash slash lex uh you don't want to use grub pop grubhub sucks they actually do doordash no i'm just kidding just walk to your local uh food or 7-eleven yeah and get and get the food you can order 7-eleven from door dash or from post code lex okay i'm sorry um but anyway i thought it was like oh i should probably increase a little bit my online presence and what would be a way to do that that would be fun for me and entertaining and i thought well a lot of people yourself included that i know have done some podcasts and i find uh that inspiring and i'm fortunate enough to know a bunch of cool motherfuckers that you know i can talk to about a lot of a wide range of topics then they're starting to drop and there's an aspect to which podcasting does capture the force of nature better in in the digital form podcasting captures the force and nature of a human being better than other mediums perhaps yeah definitely there's that i i just felt like you know you know when it's midnight and you're in the bar and you get the sense that you know the bar's gonna close in 90 minutes and you think you know not enough people have seen me yet and maybe we should go to another bar so more people can see me yeah i feel like podcasting is like is like that for me not enough people have heard my thoughts and i feel like my mom raised me to be a giver she didn't want me to be selfish and i have these thoughts that i think that i think could be a waste if you didn't give it to the world people seem to really enjoy them yeah i enjoy well while i've probably been on my best behavior today on on this episode of the podcast so if you want the uh the uncensored unfiltered uh the full spectrum that the force of nature is john clark you go to do you go you go to the podcast you funny enough i think you're drinking throughout most of the podcast yeah yeah tequila so they only last like an hour because you seem to like i'm guessing that you just lose it one hour like it's like cinderella turns into a frog or whatever one of the things i'm learning is um sometimes you have great conversations when you're drunk and sometimes you don't like i was i went into it with the right drunk edit sober mentality yes hemingway hemingway yes but turns out that uh sometimes you don't have that much to edit when you're super shit-faced and so uh i've been scaling that back a little bit and what do you mean exactly by that like where does it go wrong when you're drunk i'm curious about that because uh it gets you especially when you have a personal relationship with the person that you're talking to rather than trying to put some ideas on display for other people to hear and maybe talk about you wind up just having like a conversation with your bro about inside jokes and things like that and it's like it's not that interesting no one wants to like watch you know go to a bar and watch two people at the sitting there getting drunk and talking to each other is different than listening to uh like strong discourse yes one interesting thing as a fan of joe rogan i'm a fan i've been a fan of joe rogan for a long time and he has his friends over a lot right and there there's a aspect to those three four or five hour conversations that i really enjoy there's a magic to those i think he taught the world that those kinds of long-form conversations can work the what you forget is joe rogan is a comedian his friends are also celebrities like they know what it's like to be on the mic they know there is a challenge to actually having your friends on the microphone like they're they've never this is the first time they've been on a microphone yeah and that's actually what you've been doing which is a very interesting experiment and uh you find that some are more awkward than others like they're trying to find like what do i do with this kind of thing why why do you not talk to strangers why did you go with people that you're actually no so the simple answer is the people that i selected are both interesting and i thought would be good at talking but then i noticed the thing you just mentioned my buddy paul did the first one and paul's a wild man and if you went out with paul he can talk about a bazillion topics to a certain to to a significant uh level of depth right he's got a good understanding and he's got a unique perspective on a lot of things um and i think he was the first guy invited on my podcast and it was almost like he was on a little bit less than natural about it and then by the time he loosened up with some drinks he was it just we were all shit-faced there's there's a phase shift though totally yeah totally and so he's gonna come back on and he'll be more comfortable with it and uh and it'll probably be awesome because he's a great person to talk to um i had my friend dave on who's a restaurant and a musician that that one will be released pretty soon but yesterday i had a guy on who you might really enjoy listening to who's a friend of mine his name is mark clem he's an endurance athlete and he's been compared he's been called the white dave goggins and um he talks about like those comparisons and what he hates about it and the various events and stuff and he's just a guy who's just always kind of like natural and like i knew he'd be great to get on the podcast and um so i started with friends who i thought could handle it and who also are just really interesting people and uh and i i did it so that i could also establish a level of comfort because it was a new thing for me and they i knew that they wouldn't really give a shit what i was doing and be like hey this is cool i'm going over jc's house we're gonna drink some tequila and talk shit there's just gonna be a microphone there this time i mean it's amazing what you're doing the freedom of it i mean you're not currently doing advertisements or any of that kind of stuff you're just exploring your voices one of the mediums that you're just trying it out my 11 subscribers know what i'm about you're 11 subscribers it's in the double digits yeah uh for both you and i do you have advice for me as a podcaster and for yourself as a podcast like if you if you were to think like you're gonna do say i mean who knows but say you do a thousand more episodes right like imagine a world where that that your life continues in that direction that this is like a little parallel to like for me this thing is like a little side hobby but it's also one that's deeply fulfilling um so not just from a business perspective which is not the way i think about it i just think from a life human perspective it's i probably wouldn't have this kind of conversation with you off mike like this long this deep this attentive there's something really fulfilling about these conversations so what advice would you have for me what advice do you have for yourself or have you not introspected this that deeply oh i have a lot i have advice i think the first advice i would give to you is i think you should uh have me on more often yes yeah that's first first and second is go on your podcast and uh well i would say i would say you come on my podcast when you're ready yeah when you feel like the product that i'm putting out uh would benefit from your presence and vice versa not not as a not as a favor to a bro but at the right time i i do sense actually it's an interesting there's a dance to it which is uh like joe i recently did like joe rogan had a conversation with me on this podcast there's a very specific kind of thing where you you're helping each other out yeah but the timing on that has to be right right you know like uh right if that makes any sense you're like supporting each other it doesn't make sense it doesn't it doesn't make a difference you would think right because it's it's just people talking it doesn't matter what microphones but it changes things it does and there's an order to the guests that i've had on and the next guest that i'll have on will be a a friend we have in common and we'll be talking about teaching how to teach different styles of teaching and what you're teaching all these other things do you mind saying who oh sean fisher and um i think there's an order to it's not scientific but it's based on my gut is it uh astrologically based uh what do you mean it's not scientific you're you're god so you have a sense uh like joe rogan for example tries to do left right he tries to alternate like this this gut feeling of like these bins of people and he tries to alternate world views that's interesting like he kind of so he doesn't feel like it that like it shake it constantly shakes him it's it's more about him like constantly pulls him in multiple directions about like how he sees the world and that keeps him balanced that keeps the conversation kind of exciting that's interesting i i did it in a way where i knew paul was going to be wild and we might get a little out of control and like have some technical hiccups along the way and then my friend jake who's a ceo of a pharmaceutical company that was very timely because uh you know he was able to speak to vaccines and that was kind of scientific flavored yeah and what i learned listening back on that is like i learned for myself about uh i wasn't asking the next level questions to really draw out great answers and part of it is uh i you're simultaneously hanging out with a bro but also i was trying to learn something and i didn't learn what i wanted to learn and that's my fault because i didn't ask the questions he's an expert in that field he doesn't know that i'm an absolute dipshit when it comes to that stuff and so i didn't do a good job and if i don't know it that means the thing i was trying to tease out of him no one who is going to listen is going to learn that either yeah so i learned that um and then i had the one with soap on which i thought was was pretty good um there's a wrestler there's also a farmer right and he's a social worker and kind of humble and and thoughtful yeah thoughtful thoughtful guy like slower not a wild man that kind of thing not a wild man in the sense that i'm wild but he does preach this this philosophy of being more wild like being in touch with nature nature that that that kind of work right right right and then my buddy dave he came on um you know because i love music and i wanted to talk a lot about music and he's one of the most knowledgeable people about music that i know and he's got a restaurant coming up and i thought my buddy mark clem being an endurance athlete like when you hear some of the i didn't even know these things existed that this fucking kid did he's out of his mind and you know i think shawn and i will have probably the most intellectual conversation that i'll have had on my podcast to date and so there's a little bit of alternating there but um you know i did it that way uh so that there's a guy there's a gut feeling behind oh so that what is there where are you going do you know where you're going uh i'm i don't have a destination but i want to i want to see it to its end whether that's uh it gets somewhere of its own volition or it takes on a new life at some point and then i know how to drive it where it needs to go i think the advice i have for both of us is um i think i need to no i don't think so i think for you i see an inner turmoil i see a storm that bruises you because i feel like there's a concern for what you're saying and is it gonna get is it gonna is it gonna lead to uh negative feelings towards you or the thing that you're doing and i feel like we're different people and i have such an easier time saying fuck off to everybody and that's a liberating thing but it also can can keep me from achieving the thing that i want to achieve because i'm so flippant with opinions that i don't listen to them and let them direct me when they should there's a balance let me push back on that please i think you you believe that about yourself and nevertheless your social media presence indicates otherwise if i were to be very harsh you're like one of those you know mentally strongest character wise people i know and yet on social media you don't put your face to the world no one of the reasons you sense the fear in me which exists i of course want to let go of it is because i put my face on like my my name on things and so when i say something stupid it it hurts when people did say like look that guy said something stupid and so there's a fear of saying something stupid in all of his different forms uh like of being my lesser so it's the same feeling i have in competition of like of losing not just losing losing doesn't matter it's embarrassing myself i like losing uh being the lesser version of myself and when you put yourself out there in a full way i think you would i i would venture to say you're also because you like said you you don't you wouldn't give yourself that advice i feel like you're also afraid of standing behind some of the ideas because right now you're doing guerrilla warfare you're you're free to to uh to be uh to say things to speak your mind from the sidelines but the moment you're standing and like when people can throw shit at you i feel like uh you haven't faced that far yet you've been like avoiding that fire i'm not sure maybe i'm projecting no to a degree you're right i think like a big thing for me was putting like ads on for like our our jiu jitsu online uh like um curriculum that was a big thing uh for me because for several reasons like in the climate of everyone under the sun having a you know a jiu jitsu tutorial online and social media not social media necessarily but forums specifically that uh critique and shit the bed one thing i have not done that i've thought about doing and probably you're right in your analysis of it is i've not gone the way that i do see you on things like reddit and say hey reddit i'm doing this like i could easily go to red and say hey reddit uh i got this website up here here's a sample video whatever the fuck people do on there but yeah you're right i haven't done that and part of it might be because i i i know also if i get suckered in for one second into the negativity i'm going to become an online warrior and i don't want to be that person so yeah you're probably self-aware about that i mean one of the things i've early on decided is like i'm just gonna be i've always really enjoyed being positive so i'm going to make sure i stay that way and when there's negativity it's like i'm not just ignoring it i'm literally just returning it with positivity i like no i probably am the same way as you most people are with with egos you get you want to become the warrior against the negativity and uh like like many wars there's no winning right there's no winning that was posted online especially on the internet and uh so in that sense that's that's been a journey to try to to face the fire of the negativity and it's not actually that bad it sounds like very dramatic there's not many people that are negative but it's like when you put advertisements so you put your face on an instructional or something like that right it just there's an aspect to it which you're being a salesman you're being a gimmicky thing right it just feels wrong and people will point out look that guy is a fraud like it's fake look he's trying but those people are going to be out there and if you're like trying to do your best trying to be authentic and not trying to like be a a snake oil salesman and being like the shady kind of salesman um i think they keep you honest they keep you being the most authentic self and podcasting is like the best medium because you're being real those one hour plus that you put out there that's like real john that's not a like people people fall in love with that and that that's that the beautiful aspect of podcasting is there's no long form doesn't give any possibility for you not to be authentic right and that's why it's a magical medium the the tough thing is you're not you know popularity takes time right now popularity and so like you should shouldn't be doing it for that reason and i don't it's not the thing that really uh drives me yeah is there three books technical fiction philosophical that had an impact on you like is there books that you kind of return to that you enjoy and never had you know you find profound in some way i would say like probably the thing i read is in one of emerson's essays that i read at a you know point in my life where i needed that type of thing and i read self-reliance and you know he's got a ton of good essays but i thought self-reliance was probably the most impactful to me um you know i've read later in life like a handful of you know existential authors and they're all great but at the time a lot of it has to do with timing and when i read self-reliance and it was about the individual uh that was really good and made it was uh impactful there's also a book called uh jonathan livingston seagull by richard uh richard bach i think and um it's kind of along the same lines it's about this seagull who you know wants to break conformity and learn to fly and do all these other great things and so it's a very short read so if people are interested in that that's good uh the book which i was lucky enough to read before the movie ever even came out which is just a a pleasure of mine was a american psycho just from a writing standpoint yeah i found that the writing was was awesome uh brett easton ellis who's the author of that and several other books who have like intertwining characters uh he's a new england prep school guy and so a lot of like the stories and a lot of the the visuals uh rang true for me and anyone who can write four pages of prose on like a huey lewis album i mean kudos to you and i also would say no one will do this but i would at some point read as much of one of the big three religious texts as possible it really gives you perspective there's so many overlapping stories in the in in of religious texts and then the way that they're written gives you a unique perspective on different people uh throughout the world and you know if you're a roman catholic maybe don't read the bible read one of the other texts and that would be an interesting take but i'm embarrassed to say that first of all i've never read the bible which is embarrassing to say it's like i read a bunch of stuff about the bible not the bible itself and the same not equating them but i haven't read marx directly i haven't read mineconf by hitler directly and it feels like sometimes because you think like it's better to read stuff about the books but ultimately you want because like the analysis will be better in the texts that uh followed it but there's value to actually reading like the actual words uh yeah there's this power in the words that uh there's a reason why like the bible is one of the most impactful books ever you know and it's it's in it's in those words and it's uh of value to return to those words the communist manifesto is truly frightening if you read it in in like modern context it's worth reading yeah we're three years so is mineconf not obviously well uh it's not obvious but it is not very well written uh but all the ideas that led to the evil that is hitler are all in there which is uh fascinating to think about because probably some of the world leaders at the time should have probably read the books he he outlined everything he's going to do you've mentioned offline you mentioned an emerson quote i really like so let's try to end on this powerful quote it's easy in the world to live after the world's opinion it's easy and solitude to live after your own the great man is who in the midst of the world keeps with perfect sweetness the independence of solitude what does this quote mean to you uh it's kind of uh reinforces the idea that you're here to live your life and that even when people are trying to influence you or comment on the decisions that you make for your life you should have the strength to stick by living your life the way you want to live it that there's one immutable truth for you and it doesn't apply to everyone and so people who um people who frown upon or judge the way that you live because it's not air quotes conventional uh their opinion should not be something that impacts the choices that you make you're in a relationship now yes is that deeply meaningful or is it are you ultimately still alone is this are you still just a man in the cold of the of the life that is suffering no i'm a man who's warm nestled in a bosom i don't think there's a better way to end uh john uh you're a friend you're my coach i'm sure we'll talk many more times in the future thanks for wasting all your time with me today thanks brother thanks alex i had an awesome time hope to be back soon thanks for listening to this conversation with john clark and thank you to our sponsors theragun the device i use for post-workout muscle recovery magic spoon low-carb keto friendly cereal that i think is delicious eight sleep a mattress that cools itself and gives me yet another reason to enjoy sleep and finally cash app the app i use to send money to friends please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from miyamoto musashi think lightly of yourself and deeply of the world thank you for listening and hope to see you next time you |
Manolis Kellis: Meaning of Life, the Universe, and Everything | Lex Fridman Podcast #142 | the following is a conversation with manolis kellis his fourth time on the podcast he's a professor at mit and head of the mit computational biology group since this is episode number 142 and 42 as we all know is the answer to the ultimate question of life the universe and everything according to the hitchhiker's guide to the galaxy we decided to talk about this unanswerable question of the meaning of life in whatever way we two descendants of apes could muster from biology to psychology to metaphysics and to music quick mention of each sponsor followed by some thoughts related to the episode thanks to grammarly which is a service for checking spelling grammar sentence structure and readability athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases and cash app the app i use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that the opening 40 minutes of the conversation are all about the many songs that formed the soundtrack to the journey of monolith's life it was a happy accident for me to discover yet another dimension of depth to the fascinating mind of manolas i include links to youtube versions of many of the songs we mentioned in the description and overlay lyrics on occasion but if you're just listening to this without listening to the songs or watching the video i hope you still might enjoy as i did the passion that manolis has for music his singing of the little excerpts from the songs and in general the meaning we discuss that we pull from the different songs if music is not your thing i do give timestamps to the less musical and more philosophical parts of the conversation i hope you enjoy this little experimenting conversation about music and life if you do please subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with manolas kellis you mentioned leonard cohen and the song hallelujah as a beautiful song so what are the three songs you draw the most meaning from about life don't get me started so there's really countless songs that have marked me that have sort of shaped me in periods of joy and imperials of sadness my son likes to joke that i have a song for every sentence he will say because very often i will break into a song with a sentence he'll say my wife calls me the radio because i i can sort of recite hundreds of songs uh that have really shaped me so it's very it's gonna be very hard to just pick a few so i'm just gonna tell you a little bit about my song transition as i've grown up in greece it was very much about as i told you before the misery the poverty but also a very calming adversity so some of the songs that i that have really shaped me are uh harry salixiu for example is one of my favorite singers uh in greece and then there's also really just old traditional songs that my parents used to listen to like one of them is [Music] which is basically oh if i was rich and the song is painting this beautiful picture about all the noises that you hear in the neighborhood in his poor neighborhood the train going by the priest walking to the church and the kids crying next door and all of that and he says with all of that i'm having trouble falling asleep and dreaming if i was rich and then it was like you know um break into that so it's this juxtaposition between the spirit and the sublime and then the physical and the harsh reality it's just not having troubles not not not being miserable so basically rich to him just means out of my misery basically and then also being able to travel being able to sort of be the captain of a ship and you know see the world and stuff like that so it's just such a beautiful image so many of the greek songs just like the poetry we talked about they acknowledge the the cruelty the difficulty of life but are longing for a better life that's exactly right and another one is the holy yeah and this is one of those songs that has like a fast and joyful half and a slow and sad half and it goes back and forth between them and it's like [Music] so poor you know basically uh it's the state of being poor i don't i don't even know if there's a word for that in english and then fast parties and then it's like oh you know um basically like the state of being poor and misery uh you know for you i write all my songs etc and then the fast part is in your arms grew up and suffered and you know stood up and you know rose men with clear vision this whole concept of taking on the world with nothing to lose because you've seen the worst of it this imagery of silaki pariso pula jarastakori so it's describing the young men as cypress trees and that's probably one of my earliest exposure to a metaphor to sort of you know this very rich imagery and i love about the fact that i was reading a story to my kids the other day and it was dark and my daughter who's six is like oh can i please see the pictures and jonathan was eight so some of my daughter cleo uh is like oh let's look at the pictures and my son jonathan he's like but but cleo if you look at the pictures it's just an image if you just close your eyes and listen it's a video that's brilliant it's beautiful and he's basically showing just how much more the human imagination has besides just a few images that you know the book will give you and then another one oh gosh this one is really like miserable it's it's called perigali uh and it's basically describing how uh vigorously we took on our life and we pushed hard towards the direction that we then realized was the wrong one [Music] and it again these songs give you so much perspective there's no songs like that in english that will basically you know sort of just smack you in the face about sort of the passion and the force and the drive and then it turns out ah we just followed the wrong life yeah and it's like wow okay so that was you all right so that that's like before 12. so so you know growing up in sort of this horrendously miserable you know sort of view of romanticism of you know suffering so then my pre-teen years is like you know learning english through songs so basically you know listening to all the american pop songs and then memorizing them vocally before i even knew what they meant so you know madonna and michael jackson and all of these sort of really popular songs and you know george michael just songs that i would just listen to the radio and repeat vocally and eventually as i started learning english i was like oh wow this thing i've been repeating i know i now understand what it means without re-listening to it but just with re-repeating it was like oh again michael jackson's man in the mirror is uh teaching you that it's your responsibility to just improve yourself you know if you want to make the world a better place take a look at yourself and make the change this whole concept of again i mean all of these songs you can listen to them shallowly or you can just listen to them and say oh there's deeper meaning here and i think there's a certain philosophy of of song as a way of touching the psyche so if you look at regions of the brain people have lost their language ability because they have an accident in that region of the brain can actually sing because it's exactly the symmetric region of the brain and that again teaches you so much about language evolution and sort of the the duality of musicality and you know rhythmic patterns and eventually language do you have a sense of why songs developed so you're kind of suggesting that it's possible that there is something important about our connection with song and with music on the level of the importance of language is it possible it's not just possible in my view language comes after music language comes after song no seriously like basically my view of human cognitive evolution is rituals if you look at many early cultures there's rituals around every stage of life there's organized dance performances around mating and if you look at mate selection i mean that's an evolutionary drive right there so basically if you're not able to string together a complex dance as a bird you don't get a mate and that actually forms this development for many song learning birds not every bird knows how to sing and not every bird knows how to learn a complicated song so basically there's birds that simply have the same few tunes that they know how to play and a lot of that is inherent and genetically encoded and others are birds that learn how to sing and the you know if you look at a lot of these exotic birds of paradise and stuff like that like the mating rituals they have are enormously amazing and i think human mating rituals of you know ancient tribes are not very far off from that and in my view the sequential formation of these movements is a prelude to the cognitive capabilities that ultimately enable language and it's fascinating to think that that's uh not just an accidental precursor to intelligence yeah it's uh sexually selected it's well sexually selected and it's a prerequisite yeah it's like it's required for intelligence and and even as language has now developed i think the artistic expression is needed like badly needed by our brain so it's not just that oh our brain can kind of you know take a break and go do that stuff no i mean you know i don't know if you remember that scene from oh gosh we're certain technical movie in new hampshire uh all all working no play make jackal dull boy boy uh the shining the shining so there's this amazing scene where he's constantly trying to to concentrate and what what's coming out of the typewriters is gibberish and i have that image as well when i'm when i'm working and i'm like no basically all of this crazy you know huge number of hobbies that i have they're not just tolerated by my work they're required by my work this ability of sort of stretching your brain in all these different directions is connecting your emotional self and your cognitive self and that's a prerequisite to being able to be cognitively capable at least in my view yeah i wonder if the world without art and music you're just making me realize that perhaps that world would be not just devoid of fun things to look at or listen to but devoid of all the other stuff all the bridges and rockets and science exactly exactly creativity is not disconnected from art and you know my kids i mean you know i could be doing the full math treatment to them no they play the piano and they play the violin and they play sports i mean this whole you know sort of movement and going through mazes and playing tennis and you know playing soccer and avoiding obstacles and all of that that forms your three-dimensional view of the world being able to actually move and run and play in three dimensions is extremely important for math for you know stringing together complicated concepts it's the same underlying cognitive machinery that is used for navigating mazes and for navigating theorems and sort of solving equations so i can't you know i can't have a conversation with my students without you know sort of either using my hands or opening the white board in zoom and just constantly drawing or you know back when we had in-person meetings just the whiteboard in my lifeboard yeah that that's fascinating to think about uh so that's michael jackson man amir careless whisper george michael which is the song i like whisper i mean i didn't say that i like that one that's me i had two parties i had recorded no no that it's an amazing song for me i had recorded a small part of it as it played at the tail end of the radio and i had a tape where i only had part of that song over and over and over again just so beautiful it's so heartbreaking that song is almost greek it's so heartbreaking i know george michael he's greek is he great he's greek he's known george michael he's right i mean he's greedy yeah you know so sorry to offend you so deeply not knowing this so okay so anyway so we're moving to france when i'm 12 years old and now i'm getting into the songs of gansburg so gansburg is this incredible french composer he is always seen on stage like not even pretending to try to please just like with his cigarette just like mumbling his songs but the lyrics are unbelievable like basically entire sentences will rhyme he will say the same thing twice and you're like whoa [Laughter] and in fact another speaking of greek a french greek george mustachy this song is just magnificent avec magulo demetec de chief eran de patragrec so with my face of metec is actually a greek word it's uh you know it's a french word for a greek word but met mean comes from meta and then ek from ikea from ecology which means home so medtech is someone who has changed homes for a migrant so with my face of a migrant and and you'll love this one the juice the patrick of a meandering jew of greek pastor [Laughter] so again you know the russian greek you know jew orthodox connection so emesis with my hair in the four wings avec mesut de la vega with my eyes that are all washed out who gives me the pretense of dreaming but who don't dream that much anymore with my hands of thief of musician and who have stolen so many gardens with my mouth that has drunk that has kissed and that has bitten without ever pleasing its hunger with my skin that has been rubbed in the sun of all the summers and anything that was wearing a skirt with my heart and then you have to listen to this first it's so beautiful fair with my heart that knew how to make suffer as much as it suffered but was able to that knew how to make in french is actually fair that knew how to make yes verses that span the whole thing it's just beautiful you know yeah on a small tangent do you know jack jacques bro of course of course that song gets me every time so there's a cover of that song by one of my favorite female artists not nina simone no no no no modern carol emerald she's um from amsterdam and uh she she has a version of new mexico where she's actually added some english lyrics [Music] and it's it's really beautiful but again the mekita pai is just so i mean it's you know the promises yeah the volcanoes that you know will restart yeah it's just so beautiful and uh i love so there's not many songs that so sh shows such depth of desperation for another human being that that's so powerful [Music] and then high school now i'm starting to learn english so i moved to new york so stings englishman in new york yeah magnificent song and again there's if manners magus man has someone said then he's the hero of the day it takes a man to suffer ignorance and smile be yourself no matter what they say and then takes more than combat gear to make a man takes more than a license for a gun confront your enemies avoid them when you can a gentleman will walk but never run it's it again you're talking about songs that teach you how to live i mean this is one of them basically says it's not the combat gear that makes a man where's the part where he says uh there you go gentle uh gentleness sobriety a rare in this society at night a candle is brighter than the sun so beautiful he basically says well you just might be the only one modesty propriety can lead to notoriety you could end up as the only one it's um it basically tells you you don't have to be like the others be yourself show kindness show generosity don't you know don't let that anger get to you you know the song fragile how fragile we are how fragile we are so again as in greece i didn't even know what that meant how fragile we are but the song was so beautiful and then eventually i learned english and i actually understand the lyrics and the song is actually written after the contras murdered ben linder in 1987 and the us eventually turned against supporting these guerrillas and it was just a political song but so such a realization that you can't win with violence basically and that song starts with the most beautiful poetry so if blood will flow when flesh and steel are won drying in the color of the evening sun tomorrow's rain will wash the stains away but something in our minds will always stay perhaps this final act was meant to clinch a lifetime's argument that nothing comes from violence and nothing ever could for all those born beneath an angry star lest we forget how fragile we are damn right i mean that's poetry it was beautiful and he's using the english language in just such a refined way with deep meanings but also words that rhyme just so beautifully and evocations of when flesh and steel are won i mean it's just mind-boggling yeah and then of course the refrain that everybody remembers is on and on the rain will fall etc but like this beginning yeah and again tears from a star how fragile we are i mean just these rhymes are just flowing so naturally this something it's it seems that more meaning comes when there's a rhythm that uh i don't know what what that is that probably connects to exactly what you're saying if you pay close attention you will notice that the more obvious words sometimes are the second verse and the less obvious are often the first verse because it makes the second verse flow much more naturally because otherwise it feels contrived oh you went and found this like unusual word yes in dark moments uh the whole album of pink floyd and the movie just marked me enormously yeah as a as a teenager just the wall um and there's one song that never actually made it into the album that's only there in the movie about when the tigers broke free and the tigers are the tanks of the germans and it just describes again this vivid imagery it was just before dawn one miserable morning in black 44 when the forward commander was told to sit tight when he asked that his men be withdrawn and the generals gave thanks as the other ranks held back the enemy tanks for a while and the ancient bridgehead was held for the price of a few hundred ordinary lives so that's a theme that keeps coming back in pink floyd with us versus them us and them god only knows that's not what we would choose to do forward he cried from the rear and the front rows died from another song it's like this whole concept of us versus them and there's that theme of us versus them again where the child is discovering how his father died when he finds an old and founded one day in a draw the whole photographs hidden away and my eyes still grow damp to remember his majesty signed with his own rubber stamp so it's so ironic because it seems the way that he's writing it that he's not crying because his father was lost he's crying because kind old king george took the time to actually write mother a note about the fact that his father died it's so ironic because he basically says we are just ordinary men and of course we're disposable so i don't know if you know the root of the word pioneers but you had a chess board here earlier a pawn in france is a pyong they are the ones that you send to the front to get murdered slaughter this whole concept of pioneers having taken these whole disposable ordinary men to actually be the ones that you know we're now treating as heroes so anyway there's this just supposition of that and then the part that always just strikes me is the music and the tonality totally changes and now he describes the attack it was dark all around there was frost in the ground when the tigers broke free and no one survived from the royal fusiliers company z they were all left behind most of them dead the rest of them dying and that's how the high command took my daddy from me and that song even though it's not in the album explains the whole movie because it's this movie of misery it's this movie of someone being stuck in their head and not being able to get out of it there's no other movie that i think has captured so well this prison that is someone's own mind and this wall that you're stuck inside in this you know feeling of loneliness and so if is there anybody out there uh and you know sort of hello hello is there anybody in there just not if you can hear me is there anyone who [Music] anyway so yeah the prison of your mind so those are the darker moments exactly these are the darker moments yeah it's in the darker moments the mind does feel like you're you're trapped in alone in a room with it yeah and there's this this scene in the movie which like where he just breaks out with his guitar and there's this prostitute in the room he starts throwing stuff and then he like you know breaks the window he throws the chair outside and then you see him laying in the pool with his own blood like you know everywhere and then there's these endless hours spent fixing every little thing and lining it up and it's this whole sort of mania versus you know you can spend hours building up something and just destroy it in a few seconds one of my turns is that song and it's like i feel cold as eternity dry as a funeral drum and then the music people are saying run to the bedroom there's a suitcase on the left you'll find my favorite axe don't look so frightened this is just a passing phase one of my bad days it's just so beautiful i need to rewatch it that's so yeah but imagine you're watching this as a teenager it like ruins your mind like so many such harsh imagery and then um you know anyway so so there's the dark moment and then again going back to sting now it's the political songs russians and i think that song should be a a new national anthem for the u.s not for russians but for red versus blue mr khrushchev says we will bury you i don't subscribe to this point of view it'd be such an ignorant thing to do if the russians love their children too what is it doing it's basically saying the russians are just as humans as we are there's no way that they're going to let their children die and then it's just so beautiful how can i save my innocent boy from oppenheimer's deadly toy and now that's the new national anthem are you reading there isn't no monopoly of common sense on either side of the political fence we share the same biology regardless of ideology believe me when i say to you i hope the russians love their children too [Music] there's no such thing as a winnable war it's a lie we don't believe anymore i mean it's beautiful right and for god's sake america wake up these are your fellow americans they're your your fellow biology you know there is no monopoly of common sense on either side of the political fans it's just so beautiful there's no crisper simpler way to say russians love their children too the the common humanity yeah and remember the what i was telling you i think in one of her first podcasts about the the daughter who's crying for her husband from for her brother to come back for more and then the virgin mary appears and says who should i take instead this turk here's his family here's his children this other one he just got married etc and that basically says no i mean if you look at the lord of the rings the enemies are these monsters they're not human and that's what we always do we always say they you know they're not like us they're different they're not humans etc so there's this dehumanization that has to happen for people to go to war you know if you realize just how close we are genetically one with the other this whole 99.9 identical you can't bear weapons against someone who's like that and the things that are the most meaningful to us in our life lies at every level is the same on all sides on both sides exactly so not just that we're genetically the same yeah we're ideologically the same we love our children we love our country we will you know we will fight for our family yeah so and the last one i mentioned last time we spoke which is johnny mitchell's both sides now so she she has three rounds one on clouds one on love and one on life and on cloud she says rose and flows of angel hair and ice cream castles in the air and feather canyons everywhere have looked at clouds that way but now they only block the sun they rain and snow on everyone so many things i would have done but clouds got in my way and then i've looked at clouds from both sides now from up and down and still somehow it's clouds illusions i recall i really don't know clouds at all and then she goes on about love how it's super super happy or it's about misery and loss and about life how it's about winning and losing and so so forth but now old friends are acting strange they shake their heads they say i've changed well some things lost since something's gained and living every day so again that's growing up and realizing that well the view that you had as a kid is not necessarily that you have as an adult i remember my poem from when i was 16 years old of this whole you know children dance now all in row and then in the end even though the snow seems bright without you have lost their light sound that sang and moon that smiled so this whole concept of if you have love and if you have passion you see the exact same thing from a different way you can go out running in the rain or you could just stay in and say ah sucks i won't be able to go outside now both sides anyway and the last one is last last one from leonard cohen this is amazing by the way you're i'm so glad we stumbled on how much how much joy you have in so many avenues of life and music is just one of them that's amazing but yes leno cohen going back to the undercover and since that's where you started so uh leonard cohen's danced me to the end of love that's what that was our opening song in our wedding with my wife oh no that's what came out to greet the guest he was dancing to the end of love and then another one which is just so passionate always and we always keep referring back to it is uh i'm your man and it goes on and on about sort of i can be every type of lover for you and what's really beautiful in marriage is that we live that with my with my wife every day you can have the passion you can have the anger you can have the love you can have the tenderness there's just so many gems in that song if you want a partner take my hand or if you want to strike me down in anger here i stand i'm your man then if you want a boxer i will step into the ring for you if you want a driver climb inside or if you want to take me for a ride you know you can so this whole concept of you want to drive i'll follow you want me to drive i'll drive um and the difference i would say between like that and namaki to paw is this song he's got an attitude he's like uh he's proud of this his ability to basically be any kind of man for the money as opposed to the jacques brown like desperation of what do i have to be for you to love me that kind of desperation but but but notice there's a parallel here there's a verse that is perhaps not paid attention to as much which says ah but a man never got a woman back not by begging on his knees so it seems that the amber man is actually an apology song in the same way that number kitty pie is an apology song i'm sorry baby and in the same way that the careless whisper is now screwed up yes that's right i'm never gonna dance again guilty feet have got no rhythm um so so this is an apology song not by begging on his knees or i'd crawl to you baby and i'd fall at your feet and not howl at your beauty like a dog heat and i'd close at your heart not tear at your sheet i'd say please and then the the last one is so beautiful if you want a father for your child or only one to walk with me a while across the sand i'm your man that's the the last verses which basically says you want me for a day i'll be there do you want me to walk i'll be there you want me for life if you want a father for your child i'll be there too it's just so beautiful oh sorry remember i told you i was going to finish with a lighthearted song yes ah last one you ready so yeah alison krause and union station country song believe it or not the lucky one so i i've never identified as much with the uh lyrics of a song as this one and it's hilarious my friend serving patoglo is the guy who got me to genomics in the first place i owe enormously to him and he's another greek we actually met dancing believe or not so we used to perform greek dances uh i was the president of the international students association so we put on these big performances for 500 people at mit and uh there's a picture on the mit tech where seraphim who's like you know bodybuilder was holding on his shoulder and i was like like doing maneuvers in the air basically um so anyway this guy seraphim um we were driving back from um a conference and there's this russian girl who was describing how every member of her family had been either killed by the communists or killed by the germans were killed like she had just like you know misery like death and you know sickness and everything everyone was decimated in her family she was the last standing member and we stopped at a the serpent was driving and we stopped at a at a rest area and he he takes me aside and he's like manolis we're gonna crash [Laughter] get her out of my car and then he basically says but but but i'm only reassured because you're here with me and i'm like what do you mean he's like he you know he's like from your smile i know you're the luckiest man on the planet so there's this really funny thing where i just feel freaking lucky all the time and it's an it's a question of attitude of course i'm not any luckier than any other person but if it's science something horrible happens to me i'm like and in fact even in that song the the song about sort of you know walking on the beach and this you know sort of taking our life the wrong way and then you know having to turn around at some point he's like you know in the fresh sand we wrote her name aurea buffy so bad so shows how nicely that the wind blew and the writing was erased so again it's this whole sort of not just saying ah bummer but oh great i just lost this this must mean something right horrible thing happened it must open uh that's the door turns and you do a beautiful chapter so so alison krause is talking about the lucky one so i was like oh my god she wrote a song for me and she goes you're the lucky one i know that now as free as the wind blowing down the road loved by many hated by none i'd say you were lucky cause you know what you've done not the care in the world not the worrying side everything's gonna be all right cause you're the lucky one and then she goes uh you're the lucky one always having fun a jack of all trades a master of none you look at the world with the smiling eyes and laugh at the devil as his train rolls by i'll give you a song and a one-night stand you'll be looking at the happy man because you're the lucky one it basically says if you just don't worry too much if you don't try to be you know a one hor a one-trick pony if you just embrace the fact that you might suck at a bunch of things but you're just gonna try a lot of things and then there's another verse that says well you're blessed i guess but never knowing which road you're choosing to you the next best thing to playing and winning is playing and losing it's just so beautiful because it basically says if you try your best but it's still playing if you lose it's okay you had an awesome game and um again superficially it sounds like a super happy song but then there's a the last verse basically says no matter where you are that's where you'll be you can bet your luck won't follow me just give you a song and then one night stand you'll be looking at a happy man and in the video of the song she just walks away or he just walks away or something like that and it basically tells you that freedom comes at a price freedom comes at the price of non-commitment this whole sort of vertical love of births will cry you can't really love unless you cry you can't just be the lucky one the happy boy and yet have a long-term relationship so it's you know on one hand i identify with the shallowness of this song of you know you're the lucky one jack of all trades or master none but at the same time i identify with a lesson of well you can't just be the happy mary go lucky all the time sometimes you have to embrace loss and sometimes you have to embrace suffering and sometimes you have to embrace that if you have a safety net you're not really committing enough you're not you know basically you're allowing yourself to slip but if you just go all in and you just you know let go of your reservations that's when you truly will get somewhere so anyway that's like the the i managed to narrow it down to what 15 songs thank you for that wonderful journey that you just took us on the the the the darkest possible places of greek song to uh to ending in this a country song i haven't heard it before but uh that's exactly right i feel the same way depending depending on the day is this the luckiest human on earth and there's some there's something to that but you're right it it needs to be we need to now return to the muck of life in order to be able to to uh to truly enjoy it so that's what you mean muck what's muck uh the messiness of life the things the word things don't turn out the way you expect it to yeah the way so like to feel lucky is like focusing on the on the beautiful consequences yeah but then that feeling of things being different than you expected that uh you stumble in all the kinds of ways that that seems to be needs to be paired with the feeling there's basically one way the only way not to make mistakes is to never do anything right basically you have to embrace the fact that you'll be wrong so many times in so many research meetings i just go off on a tangent and say let's think about this for a second and it's just crazy for me who's a computer scientist to just tell my biologist friends what if biology kind of worked this way and they humor me they just let me talk and rarely has it not gone somewhere good it's not that i'm always right but it's always something worth exploring further that if you're an outsider with humility and knowing that i'll be wrong a bunch of times but i'll challenge your assumptions you know and often take us to a better place is part of this whole sort of messiness of life like if you don't try and lose and get hurt and suffer and cry and just break your heart and all these feelings of guilt and you know wow i did the wrong thing of course that's part of life and that's just something that you know if you are the a doer you'll make mistakes if you're a criticizer yeah sure you can still sit back and criticize everybody else for the mistakes they make or instead you can just be out there making those mistakes and frankly i'd rather be the criticized one than the criticizer brilliantly put every time somebody steals my bicycle i say well i know my son is like why do they steal our bicycle that and i'm like aren't aren't you happy that you have bicycles that people can steal i'd rather be the person stolen from than the steeler yeah not the critic that counts yeah so that's we've just talked amazingly about life from the music perspective let's uh talk about life from human life from perhaps other perspective and it's meaning so this is episode 142. uh there is perhaps uh an absurdly uh deep meaning to the number 42 that uh the our culture has has elevated so this is a perfect time to talk about the meaning of life we've talked about it already but do you think this question that's so simple and so seemingly absurd has value of what is the meaning of life is it something that raising the question and trying to answer it is that a ridiculous pursuit or is this some value is it answerable at all so first of all i i feel that we owe it to your listeners to say why 42 sure so of course the hitchhiker's guide to the galaxy came up with 42 as basically a random number just you know the author just pulled it out of a hat and he's admitted so he said mile 42 just seemed like just random numbers any but in fact there's many numbers that are linked to 42. so 42 again just just to summarize is the answer that these super mega computer that had computed for a million years with the most powerful computer in the world had come up with at some point the computer says um i have an answer and they're like what it's like you're not going to like it like what is it it's 42. and then the irony is that they had forgotten of course what the question was yes so now they have to build a bigger computer to figure out what the question was the question to which the answer is 42. so as i was turning 42 i basically sort of researched uh why 42 is such a cool number and it turns out that and i put together this little passage that was explaining to all those guests to my 42nd birthday party why we were talking about the meaning of life and basically talked about how 42 is the angle at which light reflects off of water to create a rainbow and it's so beautiful because the rainbow is basically the combination of sort of it's been raining but there's hope because the sun just came out it's a very beautiful number there so 42 is also the sum of all rows and columns of a magic cube that contains all consecutive integers starting at one so basically if you if you take all integers between one and however many vertices there are the sums is always 42. 42 is the only number left under 100 for which the equation of x to the cube plus y to the q plus z to the cube is n and was not known to not have a solution and now it's the you know it's the only one that actually has a solution 42 is also 1 0 1 0 1 0 in binary again the yin and the yang the good and the evil one and zero the balance of the force 42 is the number of chromosomes for the giant panda and the giant panda i know it's totally random or a suspicious symbol of great strength coupled with peace friendship gentle temperament harmony balance and friendship whose black and white colors again symbolize yin and yang the reason why it's the symbol for china is exactly the strength but yet peace and so forth so 42 chromosomes it takes light 10 to the minus 42 seconds to cross the diameter of a proton connecting the two fundamental dimensions of space and time 42 is the number of times a piece of paper should be folded to reach beyond the moon so um which is what i assume my students mean when they ask that their paper reaches for the stars i just tell them just fold it a bunch of times 42 is the number of messier object 42 which is orion and that's you know one of the most famous galaxies it's i think also the place where we can actually see the center of our galaxy uh 42 is the numeric representation of the star symbol in ascii which is very useful when searching for the stars yeah and also a regex for life the universe and everything so star [Laughter] in egyptian mythology the goddess ma'at which was personifying truth and justice would ask 42 questions to every dying person and those answering successfully would become stars continue to give life and fuel universal growth in judaic tradition goddess scribe is ascribed a 42-lettered name entrusted only to the middle age pius meek free from bad temper sober and not insistent on his rights and in christian tradition there's 42 generations from abraham isaac that we talked about the story of isaac jacob eventually joseph mary and jesus in kabbalistic tradition eloka which is 42 is the number with which god creates the universe starting with 25 letter b and ending with 17 good so 25 plus you know 17. there's this 42 chapter sutra which is the first indian religious scripture which was translated to chinese thus introducing buddhism to china from india the 42 line bible was the first printed book making the mark marking the age of printing in the 1450s and the dissemination of knowledge eventually leading to the enlightenment a yeast cell which is uh called a single cell eukaryote and the subject of my phd research has exactly 42 million proteins anyway so so there's seriously you're on fire with this these are really good so i guess what you're saying is just a random number yeah basically so all of these are acronyms so you know after you have the number you figure out why that don't work so anyway so uh now that we've spoken about why 42 uh why do we search for meaning and uh you're asking you know will that search ultimately lead to our destruction and my my thinking is exactly the opposite so basically that asking about meaning is something that's so inherent to human nature it's something that makes life beautiful that makes it worth living and that searching for meaning is actually the point it's not defining it i think when you found it you're dead yeah don't don't ever be satisfied that you know i've got it so i like to say that life is lived forward but it only makes sense backward and i don't remember whose quote that is but the the the whole search itself is the meaning and what i love about it is that there's a double search going on there's a search in every one of us through our own lives to find meaning and then there's a search which is happening for humanity itself to find our meaning and we as humans like to look at animals and say of course they have a meaning like a dog has its meaning it's just a bunch of instincts you know running around loving everything um you know remember a joke with a cat in the dark no no so so um and i i'm noticing the yin yang symbol right here with this whole panda black and white and the zero one zero one five with that 42. some of those are gold ascii value for uh the star symbol damn anyway so so basically in my view the the search for meaning and the act of uh searching for something more meaningful is life's meaning by itself but the fact that we kind of always hope that yes maybe for animals that's not the case but maybe humans have something that we should be doing and something else and it's not just about procreation it's not just about dominance it's not just about strength and feeding et cetera like we're the one species that spends such a tiny little minority of its time feeding that we have this enormous you know huge cognitive capability that we can just use for all kinds of other stuff and that's where art comes in that's where you know the healthy mind comes in with you know exploring all of these different aspects that are just not directly tied to um to a purpose that's not directly tied to a function it's really just the the playing of life the you know not not for particular reason do you think this thing we got this this mind is unique in the universe in terms of how difficult it is to build so is it possible that we're the the most beautiful thing that the universe has constructed both the most beautiful the most ugly but certainly the most complex so look at evolutionary time uh the dinosaurs ruled the earth for 135 million years we've been around for a million years so one versus 135. so dinosaurs were extinct you know about 60 million years ago and mammals that had been happily evolving as tiny little creatures for 30 million years then took over the planet and then you know dramatically radiated about 60 million years ago out of these mammals came the neocortex formation so basically the the neocortex which is sort of the outer layer of our brain compared to our quote-unquote reptilian brain which we share the structure of with all of the dinosaurs they didn't have that and yet they ruled the planet so how many other planets have still you know mindless dinosaurs where strength was the only dimension uh ruling the planet so there was something weird that annihilated the dinosaurs and again you could look at biblical things of sort of god coming and wiping out his creatures and yes to make room for the next ones so the mammals basically sort of took off the planet and then grew this cognitive capability of this general-purpose machine and primates push that to extreme and humans among primates have just exploded that hardware but that hardware is selected for survival it's selected for procreation it's initially selected with this very simple darwinian view of the world of random mutation ruthless selection and then selection for making more of yourself if you look at human cognition it's gone down a weird evolutionary path in the sense that we are expending an enormous amount of energy on this apparatus between our ears that is wasting what 15 of our bodily energy 20 like some enormous percentage of our calories go to function our brain no other species makes that big of a commitment that has basically taken energetic changes for efficiency on the metabolic side for humanity to basically power that thing and our brain is both enormously more efficient than other brains but also despite this efficiency enormously more energy consuming so and if you look at just the sheer folds that the human brain has again our skull could only grow so much before it could no longer go through the pelvic opening and kill the mother at every birth so but yet the fault continued effectively creating just so much more capacity the evolutionary uh context in which this was made is enormously fascinating and it has to do with other humans that we have now killed off or that have gone extinct and that has now created this weird place of humans on the planet as the only species that has this enormous hardware so that can basically make us think that there's something very weird and unique that happened in human evolution that perhaps has not been recreated elsewhere maybe the asteroid didn't hit you know sister earth and the dinosaurs are still ruling and you know any any kind of proto-human is squished and eaten for breakfast basically however we're not as unique as we like to think because there was this enormous diversity of other human-like forms and once you make it to that stage where you have a neocortex-like explosion of wow we're now competing on intelligence and we're now competing on social structures and we're now competing on larger and larger groups and being able to coordinate and being able to have empathy the concept of empathy the concept of an ego the concept of a self of self-awareness comes probably from being able to project another person's intentions to understand what they mean when you have these large cognitive groups large social groups so me being able to sort of create a mental model of how you think may have come before i was able to create a personal mental model of how do i think so this introspection probably came after this sort of projection and this empathy which basically means you know passion pathos suffering but basically sensing so basically empathy means feeling what you're feeling trying to project your emotional state onto my cognitive apparatus and i think that is what eventually led to this enormous cognitive explosion that happened in humanity so you know life itself in my view is inevitable on every planet inevitable inevitable but the evolution of life to self-awareness and cognition and all the incredible things that humans have done you know that might not be as inevitable that's your intuition so uh if you were to sort of uh estimate and bet some money on it if we re-ran earth a million times would what we got now be the most special thing and how often would it be so scientifically speaking how repeatable is this experiment so this whole cognitive revolution yes maybe not maybe not basically i feel that the longevity of you know dinosaurs suggests that it was not quite inevitable that we uh that we humans eventually uh made it what you're also implying one thing here you're saying you're implying that humans also don't have this longevity this is the interesting question so with the fermi paradox the idea that the basic question is like if if the universe has a lot of uh alien life forms in it why haven't we seen them yeah and one thought is that there is a great filter or multiple great filters that basically would destroy intelligent civilizations like we this thing that we you know this multi-folding brain that can keeps growing may not be such a big feature it might be useful for survival but it like takes us down a uh side road that is a very short one with a quick dead end what do you think about that so i think the universe is enormous not just in space but also in time and the the pretense that you know the last blink of an instant that we've been able to send radio waves is when somebody should have been paying attention to our planet he's a little ridiculous so my you know what i love about star wars yes is a long long time ago in a galaxy far far away it's not like some distant future it's a long long time ago what i love about it is that basically says you know evolution and civilization are just so recent in you know on earth like there's countless other planets that have probably all kinds of life forms multicellular perhaps and so forth but the fact that humanity has only been listening and emitting for just this tiny little blink means that any of these you know alien civilizations would need to be paying attention to every single insignificant planet out there and you know again i mean the movie contact and the book is just so beautiful this whole concept of we don't need to travel physically we can travel as light we can send instructions for people to create machines that will allow us to beam down light and recreate ourselves and in the book you know the aliens actually take over they're not as friendly but you know this concept that we have to eventually go and conquer every planet i mean i think that yes we will become a galactic species so you you have um hope well you said thanks oh of course of course i mean now that we've made it so far you we so you think i made it oh gosh i feel that you know cognition the cognition as an evolutionary trait has won over in our planet there's no doubt that we've made it so basically humans have won the battle for you know uh dominance it wasn't necessarily the case with dinosaurs like i mean yes you know there's some claims of uh intelligence and if you look at jurassic park yeah sure whatever but you know they just don't have the hardware for it yeah and humans have the hardware there's no doubt that mammals have a dramatically improved hardware for cognition over dinosaurs like basically there's universes where strength went out and in our planet in our you know particular version of whatever happened in this planet cognition went out and it's kind of cool i mean it's it's a privilege right but it's kind of like living in boston instead of i don't know some middle uh middle-aged uh place where everybody's like hitting each other with with uh you know some weapons and sticks back to the lucky one song i mean we are the lucky ones but the flip side of that uh is that this hardware also allows us to develop weapons and methods of destroying ourselves so you again i want to go back to pinker yeah and the better angels of our nature the whole concept that civilization and the act of civilizing has dramatically reduced violence dramatically if you look you know at every scale as soon as organization comes the state basically owns the right to violence and eventually the state gives that right of governance to the people but but violence has been eliminated by that state so this whole concept of central governance and people agreeing to live together and share responsibilities and duties and you know all of that is something that has led so much to less violence less death less suffering less you know poverty less um you know war i mean yes we have the capability to destroy ourselves but the arc of civilization has led to much much less destruction much much less war and much more peace and of course there's blips back and forth and you know there are setbacks but again the moral arc of the universe but it seems to just i probably imagine there were two dinosaurs back in the day having this exact conversation and they look up to the sky and there seems to be something like an asteroid going towards earth so it's while it's it's very true that the the arc of our society of human civilization seems to be progressing towards a better better life for everybody in in the many ways that you described uh things can change in a moment and it feels like it's not just us humans we're living through a pandemic you could imagine that a pandemic would be more destructive or or there could be asteroids that just appear out of the the darkness of space which i would recently learned it's not that easy to uh give you another number detect them yes so 48 what happens in 48 years 2068 apophis there's an asteroid that's coming in 48 years it has very high chance of actually wiping us out completely yes so we have 48 48 years to get our act together it's not like some distant distant hypothesis yes like yeah sure they're hard to detect but this one we know about it's coming so how do you feel about that why are you still talking oh gosh i'm so happy with where we are now this is going to be great seriously if you look at progress if you look at again the speed with which knowledge has been transferred what what has led to humanity making so many advances so fast okay so what has led to humanity making so many advances is not just the hardware upgrades it's also the software upgrades so by hardware upgrades i basically mean our neocortex and the expansion and these layers and you know folds of her brain and all of that that's the hardware the software hasn't uh you know the the hardware hasn't changed much in the last what seventy thousand years as i mentioned last time if you take a person from ancient egypt and you bring them up now they're just as equally fit so hardware hasn't changed what has changed is software what has changed is that we are growing up in societies that are much more complex this whole concept of neotimi basically allows our exponential growth the concept that our brain has not fully formed has not fully stabilized itself until after teenage years so we basically have a good 16 years 18 years to sort of infuse it with the latest and greatest in software if you look at what happened in ancient greece why did everything explode at once my take on this is that it was the shift from the egyptian and hieroglyphic software to the greek language software this whole concept of creating abstract notions of creating these um layers of cognition and layers of meaning and layers of abstraction for words and ideals and beauty and harmony how do you write harmony in hieroglyphics there's no such thing as you know sort of expressing these ideals of peace and justice and you know these concepts of or even you know uh macabre concepts of doom etc like you don't you don't have the language for it your brain has trouble getting at that concept so what i'm trying to say is that these software upgrades for human language human culture human environment human education have basically led to this enormous explosion of knowledge and eventually after the enlightenment and as i was mentioning the 42 line bible and the printed press the dissemination of knowledge you basically now have this whole horizontal dispersion of ideas in addition to the vertical inheritance of genes so the hardware improvements happen through vertical inheritance the software improvements happen through horizontal inheritance and the reason why human civilization exploded is not a hardware change anymore it's really a software change so if you're looking at now where we are today look at coronavirus yes sure it could have killed us a hundred years ago it would have but it didn't why because in january we we published the genome a month later less than a month later the first vaccine designs were done and now less than a year later 10 months later we already have a working vaccine that's 90 efficient i mean that is ridiculous by any standards and the reason is sharing so you know the asteroid yes could wipe us out in 48 years but 48 years i mean look at where we were 48 years ago technologically i mean how much more we understand the basic foundations of space is enormous the technological revolutions of digitization the amount of compute power we can put on any like you know by in nail size you know hardware is enormous so and this is nowhere near ending you know we all have our like little you know problems going back and forth on the social side yeah and on the political side on the cognitive and on the sort of human side and the societal side but science has not slowed down science is moving at a breakneck pace ahead so you know elon is now putting rockets out from the private space i mean that now democratization of space exploration is you know gonna reveal it's gonna explode continue in the same way that every technology has exploded this is the shift to space technology exploding so 48 years is infinity from now in terms of space capabilities so i'm not worried at all are you excited by the possibility of a human well one human stepping foot on mars and to possible colonization of not necessarily mars but other planets and all that kind of stuff for people living in space inevitable and never inevitable would you do it are you kind of like earth you know how many how many how many people will you wait when you wait for i think it was about when um the the declaration of independence was signs about two to three million people lived here so would you move like before would you be like on the first boat would you be on the 10th boat would you wait until the declaration of independence i don't think i'll be on the shortlist because i'll be old by then they'll probably get a bunch of younger people but you're it's the it's the wisdom and the uh the wait then you are in the classroom horizontally you i gotta tell you you are the lucky one so you might be on the list i don't know yeah i mean i i kind of feel like i would love to see earth from above just to watch our planet i mean just i mean you know you can watch a live feed of the space station watching earth is magnificent like this blue tiny little shield it's so thin our atmosphere like if you drive to new york you're basically in outer space i mean it's ridiculous it's just so thin and it's just again such a privilege to be on this planet such a privilege but i think our species is in for big good things i think that you know we will overcome our little problems and eventually come together as a species i feel that we we we're definitely on the path to that and you know it's just not permeated through the whole universe yeah i mean through the whole world yet through the whole earth yet but it's definitely permeating so you've talked about humans as special how exactly are we special relative to the dinosaurs so i mentioned that there's um you know this dramatic cognitive improvement that we've made but i think it goes much deeper than that so if you look at a lion attacking a gazelle in the middle of the serengeti the lion is smelling the molecules in the environment it's uh hormones and neuroreceptors are sort of getting it ready for impulse the target is constantly looking around and sensing i've actually been in kenya and i've kind of seen the hunt yes i've kind of seen the sort of game of waiting and the mitochondria in the muscles of the lion are basically ready for you know jumping they're expensing an enormous amount of energy the grass as it's flowing is constantly transforming solar energy into chloroplasts you know through the chloroplastin to energy which eventually feeds the gazelle and eventually feeds the lions and so forth so as humans we experience all of that but the lion only experiences one layer the mitochondria in its body are only experiencing one layer the chloroplasts are only experiencing one layer the you know photoreceptors and the smell receptors the chemical receptors like the lion always attacks against the wind so that it's not smelled like all of these things are one layer at a time and we humans somehow perceive the whole stack so going back to software infrastructure and hardware infrastructure if you design a computer you basically have a physical layer that you start with and then on top of that physical layer you have you know the electrical layer and on top of the electrical layer you have basically gates and logic and an assembly layer and on top of the assembly layer you have your you know higher order higher level programming and on top of that you have your deep learning routine etc and on top of that you eventually build a cognitive system that's smart i want you to now picture this cognitive system becoming not just self-aware but also becoming aware of the hardware that it's made of and the atoms that there that it's made of and so forth so it's as if your ai system and there's this beautiful scene in um 2001 odyssey of space where where uh hull after dave starts disconnecting him yes he's starting to sing a song about daisies etc and hal is basically saying dave i'm losing my mind i can feel i'm losing my mind it's just so beautiful this concept of self-awareness of knowing that the hardware is no longer there is amazing and in the same way humans who have had accidents are aware that they've had accidents so there's this self-awareness of ai that is you know this beautiful concept about you know sort of the eventual cognitive leap to self-awareness but imagine now the ai system actually breaking through these layers and saying wait a minute i think i can design a slightly better hardware to get me functioning better and that's what basically humans are doing so if you if you look at our reasoning layer it's built on top of a cognitive layer and the reasoning layer we share with ai it's kind of cool like there is another thing on the planet that can integrate equations and it's man-made but we share computation with them we share this cognitive layer of playing chess we're not alone anymore we're not the only thing on the planet that plays chess now we have ai that also plays chess but in some sense that that particular organism ai as it is now only operates in that layer exactly exactly and then most animals operate in the sort of cognitive layer that we're all experiencing a bat is doing this incredible integration of signals but it's not aware of it it's basically constantly sending echo location waves and it's receiving them back and multiple bats in the same cave are operating at slightly different frequencies and with slightly different pulses and they're all sensing objects and they're doing motion planning in their cognitive hardware but they're not even aware of all of that all they know is that they have a 3d view of space around them just like any gazelle walking through you know the desert and any baby looking around is aware of things without doing the math of how am i processing all of these visual information et cetera you're just aware of the layer that you live in i think if you look at this at humanity we've basically managed through our cognitive layer through our perception layer through our senses layer through our multi-organ layer through our genetic layer through our molecular layer through our atomic layer through our quantum layer through even the very fabric of the space-time continuum unite all of that cognitively so as we're watching that scene in the serengeti we as scientists we as educated humans we as you know anyone who's finished high school are aware of all of this beauty of all of these different layers interplaying together and i think that's something very unique in perhaps not just the galaxy but maybe even the cosmos this species that has managed to in space cross through these layers from the enormous to the infinitely small and that's what i love about particle physics the fact that it actually unites everything they're very small they're very very small and they're very big it's only through the very big that the very small gets formed like basically every atom of gold results from the fusion that happened of you know increasingly large particles before that explosion that then disperses it through the cosmos and it's only through understanding the very large that we understand very small and vice versa and that's in space then there's the time direction as you are watching the kilimanjaro mountain you can kind of look back through time to when that volcano was exploding and you know growing out of the tectonic forces as you drive through death valley you see these mountains on their side and these layers of history exposed we are aware of the eons that have happened on earth and the tectonic movements on earth the same way that we're aware of the big bang and the you know early evolution of the cosmos and we can also see forward in time as to where the universe is heading we can see you know apophis in 2068 coming over looking ahead in time i mean that would be magician stuff you know in ancient times so what i love about humanity and its role in the universe is that you know if there's a god watching he's like finally somebody figured it out i've been building all these beautiful things and somebody can appreciate it and figured me out from god's perspective meaning like become aware of yeah you know yeah so it's kind of interesting so to think of the world in this way as layers and us humans are able to convert those layers into ideas that they you can then like combine right so we're doing some kind of conversion exactly exactly and last time you asked me about whether we live in a simulation for example i mean realize that we are living in a simulation we are the reality that we're in without any sort of person programming this is a simulation like basically what happens inside your skull there's this integration of sensory inputs which are translated into perceptory signals which are then translated into a conceptual model of the world around you and that exercise is happening seamlessly and yet you know if you if you think about sort of again this whole simulation and neo um analogy you can think of the reality that we live in as a matrix as the matrix but we've actually broken through the matrix we've actually traversed the layers we didn't have to take a pill like we didn't nick you know morpheus didn't have to show up to basically give us the blue pill or the red pill we were able to sufficiently evolve cognitively through the hardware explosion and sufficiently involve scientifically through the software explosion to basically get at breaking through the matrix realizing that we live in a matrix and realizing that we are this thing in there and yet that thing in there has a consciousness that lives through all these layers and i think we're the only species we're the only thing that we even can think of that has actually done that has sort of permeated space and time scales and layers of abstraction plowing through them and realizing what we're really really made of and the next frontier is of course cognition so we understand so much of the cosmos so much of the stuff around us but the stuff inside here finding the basis for the soul finding the basis for the ego for the self the self-awareness when do when does the spark happen that basically sort of makes you you i mean that's you know really the next frontier so so in terms of these peeling off layers of complexity somewhere between the cognitive layer and the reasoning layer or the computational layer there's still some stuff to be figured out there and i think that's the final frontier of sort of completing our journey through that matrix and maybe duplicating it in the in other versions of ourselves through ai which is another very exciting uh possibility what i love about ai and the way that it operates right now is the fact that it is unpredictable there's emergent behavior in our cognitively capable artificial systems that we can certainly model but we don't encode directly and that's a key difference so we like to say oh of course this is not really intelligent because we coded it up and we just put in these little parameters there and there's like you know six billion parameters and once you've learned them you know we kind of understand the layers but that's an oversimplification it's it's like saying oh of course humans we understand humans they're just made out of neurons and you know layers of cortex and there's a visual area and there's a but but every human is encoded by a ridiculously small number of genes compared to the complexity of our cognitive apparatus 20 000 genes is really not that much out of which a tiny little fraction are in fact encoding all of our cognitive functions the rest is emergent behavior the rest is the you know the the the cortical layers doing their thing in the same way that when we build you know these conversational systems or these cognitive systems or these deep learning systems we put the architecture in place but then they do their thing and in some ways that's creating something that has its own identity that's creating something that's not just oh yeah it's not the early ai where if you hadn't programmed what happens in the grocery bags when you have both cold and hot and hard and soft you know the system wouldn't know what to do no no you basically now just program the primitives and then he learns from that so even though the origins are humble just like it is for our genetic code for ai even though the origins are humble the the uh the result of it being deployed into the world is infinitely complex and that's and yet there's not uh it's not yet able to be cognizant of all the other layers in uh of its you know it's not it's not able to think about space and time it's not able to think about the hardware in which it runs the electricity on which it runs yet so so if you look at humans we basically have the same cognitive architecture as monkeys as the great apes it's just a ton more of it if you look at um gpt3 versus gpd2 again it's the same architecture just more of it and yet it's able to do so much more yeah so if you start thinking about sort of what's the future of that gpt 455 do you really need fundamentally different architectures or do you just need a ton more hardware and we do have a ton more hardware like these systems are nowhere near what humans have between our ears so you know there's something to be said about stay tuned for emergent behavior we keep thinking that general intelligence might just be forever away but it could just simply be that we just need a ton more hardware and that humans are just not that different from the great apes except for just a ton more of it yeah it's interesting that in the ai community maybe it is a human-centric fear but the notion that gpt 10 will be will achieve general intelligence is something that people shy away from that there has to be something totally different and new added to this and yet it's not seriously considered that um this this very simple thing this very simple architecture when scaled might be the thing that achieves super intelligence and people think the same way about humanity and human consciousness they're like oh consciousness might be quantum or it might be you know some some non-physical thing and it's like or it could just be a lot more of the same hardware that now is sufficiently capable of self-awareness just because it has the neurons to do it so maybe the consciousness that is so elusive is an emergent behavior of you basically string together all these cognitive capabilities that come from running from seeing for reacting from predicting the movement of the fly as you're catching it through the air all of these things are just like great lookup tables encoded in a giant neural network i mean i'm oversimplifying of course the complexity and the diversity of the different types of excitatory inhibitory neurons the waveforms that sort of shine through the you know the the connections across all these different layers the amalgamation of signals etc the brain is enormously complex i mean of course but again it's a small number of primitives encoded by a tiny number of genes which are self-organized and shaped by their environment babies that are growing up today are listening to language from conception basically as soon as the auditory apparatus forms it's already getting shaped to the types of signals that are out in the real world today so it's not just like oh have an egyptian be born and then ship them over it's like no that egyptian would be listening in to the complex of the world and then getting born and sort of seeing just how much more complex the world is so it's a combination of the underlying hardware which if you think about as a geneticist in my view the hardware gives you an upper bound of cognitive capabilities but it's the environment that makes those capabilities shine and reach their maxima so we're a combination of nature and nurture the nature is our genes and our cognitive apparatus and the nurture is the richness of the environment that makes that cognitive apparatus reach its potential and we are so far from reaching our full potential so far i think that kids being born 100 years from now they'll be looking at us now and saying what primitive educational systems they had i can't believe people were not wired into this you know virtual reality from birth as we are now because like they're clearly inferior and so forth so i basically think that our environment will continue exploding and our cognitive capabilities it's not like oh we're only using two percent of our brain that's ridiculous of course we're using 100 of our brain but it's still constrained by how complex our environment is so the hardware will remain the same but the software in a quickly advancing environment the software will make a huge difference in the nature of like the human experience the human condition it's fascinating to think that humans will look very different 100 years from now just because the environment changed even though we're still the same great apes the the descendant of apes at the core of this is kind of a notion of ideas that uh i don't know if you're there's a lot of people that's including you eloquently about this topic but richard dawkins talks about the notion of memes and let's say this notion of ideas you know multiplying selecting in the minds of humans do you ever think from about ideas from the from that perspective ideas as organisms themselves that are breeding in the minds of humans i love the concept of memes i love the concept of this horizontal transfer of ideas and sort of permeating through through you know our layer of interconnected neural networks so you can think of sort of the cognitive space that has now connected all of humanity where we are now one giant information and idea sharing network well beyond what was thought to be ever capable when the concept of a meme was created by richard dawkins so but i want to take that concept just you know into another twist which is the horizontal transfer of humans with fellowships and the fact that as people apply to mit from around the world there's a selection that happens not just for their ideas but also for the cognitive hardware that came up with those ideas so we don't just ship ideas around anymore they don't evolve in a vacuum the ideas themselves influence the distribution of cognitive systems i.e humans and brains around the planet yeah we ship them to different locations based on their properties that's exactly right so so those cognitive systems that think of you know physics for example might go to cern and those that think of genomics might go to the broad institute and those that think of computer science might go to i don't know stanford or cmu or mit and you basically have this co-evolution now of memes and ideas and the cognitive conversational systems that love these ideas and feed on these ideas and understand these ideas and appreciate these ideas now coming together so you basically have students coming to boston to study because that's the place where these type of cognitive systems thrive and they're selected based on their cognitive output and their idea output but once they get into that place the boiling and interbreeding of these memes becomes so much more frequent that what comes out of it is so far beyond if ideas were evolving in a vacuum of an already established hardware cognitive interconnection system of the planet where now you basically have the ideas shaping the distribution of these systems and then the genetics kick in as well you basically have now these people who came to be a student kind of like myself who now stuck around and are now professors bringing up our own genetically encoded and genetically related cognitive systems mine are eight six and three years old who are now growing up in an environment surrounded by other cognitive systems of a similar age with parents who love these types of thinking and ideas and you basically have a whole interbreeding now of genetically selected transfer of cognitive systems where the genes and the memes are co-evolving the same soup of ever improving knowledge and societal inter-fertilization cross-virtualization of these ideas so that this beautiful image so these are shipping these actual meat cognitive systems to physical locations they they tend to uh cluster in uh the biology ones cluster in a certain building too so like within that there's there's uh there's clusters on top of clusters type of clusters what about in the online world is that do you also see that kind of because people now form groups on the internet that they stick together so they they can sort of uh these cognitive systems can collect themselves and uh breed together uh on in in different layers of spaces it doesn't just have to be physical space absolutely absolutely so basically there's the physical rearrangement but there's also the conglomeration of the same cognitive system doesn't need to be a human it doesn't need to belong to only one community yeah so yes you might be a member of the computer science department but you can also hang out in the biology department but you might also go online online into i don't know poetry department uh readings and so forth or you might be part of a group that only has 12 people in the world but that are connected through their ideas and are now interbreeding these ideas in a whole other way so this um this coevolution of genes and memes is not just physically instantiated it's also sort of rearranged you know in this cognitive uh space as well and uh and sometimes these cognitive systems hold conferences and they all get gather around and there's like one of them is like talking and they're all like listening and then you discuss and then they have free lunch and so on no but but then that's where you find students where you know when when i go to a conference i go through the posters where i'm on a mission basically my mission is to read and understand what every poster is about and for a few of them i'll dive deeply and understand everything but i make it a point to just go post after posting in order to read all of them and i find some gems and students that i speak to that sometimes eventually join my lab and then sort of you're you're sort of creating this permeation of you know the transfer of ideas of ways of thinking and very often of moral values of social structures of you know just more imperceptible properties of these cognitive systems that simply just cling together basically you know there's i have the luxury at mit of not just choosing smart people but choosing smart people who i get along with who are generous and friendly and creative and smart and you know excited and childish in their in you know uninhibited behaviors and so forth so you basically can choose yourself to surround you can choose to surround yourself with people who are not only cognitively compatible but also you know imperceptibly through the meta cognitive systems compatible and again when i say compatible not all the same sometimes you know sometimes all the time the teams are made out of complementary components not just compatible but very often complementary so in my own team i have a diversity of students who come from very different backgrounds there's a whole spectrum of biology to computation of course but within biology there's a lot of realms within computation there's a lot of rounds and what makes us click so well together is the fact that not only do we have a common mission a common passion and a common you know view of the world but that were complementary in our skills in our angles with which we accommodate and so so forth and that's sort of what makes it click yeah it's fascinating that the the the stickiness of multiple cognitive systems together includes both the commonality so you meet because you're there's some common thing but you stick together because you're dif different in all the useful ways yeah yeah and my wife and i i mean we adore each other like to pieces but we're also extremely different in many ways and that's beautiful but i love that about about us i love the fact that you know i'm like living out there in the you know world of ideas and i forget what day it is and she's like well at 8 am the kids better be to school and uh you know yeah i do get yelled at but but i need it basically i need her as much as she needs me and she loves interacting with me and talking i mean you know last night we were talking about this and i showed her the questions and we were bouncing ideas of each other and it was just beautiful like we basically have these you know basically cognitive you know let it all loose kind of dates where you know we just bring papers and we're like you know bouncing ideas etc so you know we have extremely different perspectives but very common you know goals and interests and anyway what do you make of the communication mechanism that we humans use to share those ideas because like one essential element of all of this is not just that we're able to have these ideas but we're also able to share them we tend to maybe you can correct me but we seem to use language to share the ideas maybe we share them in some much deeper way than language i don't know but what do you make of this whole mechanism and how fundamental it is to the human condition so some people will tell you that your language dictates your thoughts and your thoughts cannot form outside language i tend to disagree i see uh thoughts as much more abstract as you know basically when i dream i don't dream in words i dream in shapes and forms and you know three-dimensional space with extreme detail i was describing so when i wake up in the middle of the night i actually record my dreams sometimes i write them down in a dropbox file uh other times i'll just dictate them in you know audio and um my wife was giving me a massage the other day because like my left side was frozen and i started playing the recording and as i was listening to it i was like i don't remember any of that and i was like of course and then the entire thing came back but then there's no way any other person could have recreated that entire sort of you know three-dimensional uh shape and dream and concept and in the same way when i'm thinking of ideas there's so many ideas i can't put two words i mean i will describe him with a thousand words but the idea itself is much more precise or much more sort of abstract or much more something you know difference either less abstract or more abstract and it's either you know basically the there's just a projection that happens from the three-dimensional ideas into let's say a one-dimensional language and the language certainly gives you the apparatus to think about concepts that you didn't realize existed before and with my team we often create new words i'm like well now we're going to call this the regulatory plexus of a gene and that gives us now the language to sort of build on that as one concept that you then build upon with all kinds of other other things so there's this co-evolution again of ideas and language but they're not one-to-one uh with each other now let's talk about language itself words sentences this is a very distant construct from where language actually begun so if you look at how we communicate as i'm speaking my eyes are shining and my face is changing through all kinds of emotions and my entire body composition posture is reshaped and my intonation the pauses that i make the softer and the louder and this and that are conveying so much more information and if you look at early human language and if you look at how you know the great apes communicate with each other there's a lot of granting there's a lot of postering there's a lot of emotions there's a lot of sort of shrieking etc they have a lot of components of our human language just not the words so i think of human communication as combining the ape component but also of course the you know gpt3 component so basically there's the cognitive layer and the reasoning layer that we share with different parts of our relatives there's the ai relatives but there's also the grunting relatives and what i love about humanity is that we have both we're not just a conversational system we're a grunting emotionally charged you know weirdly intercon connected system that also has the ability to reason and when when we communicate with each other there's so much more than just language there's so much more than just words it does seem like we're able to somehow transfer even more than the the body language it seems that in the room with us is always a giant knowledge base of like shared experiences different perspectives on those experiences but i don't know the knowledge of who the last three four presidents in the united states was and just all the you know 911 the tragedies in 911 all the all the beautiful and uh terrible things that happen in the world they're somehow both in our minds and somehow enrich the ability to transfer information and what i love about it is i can i can talk to you about 2001 audience of space and mention a very specific scene and that evokes all these feelings that you had when you first watched it we're both visualizing that maybe in different ways exactly but in that yeah and not only that but the feeling uh is brought back up just like you said with the dreams we both have that feeling arise in some form exactly as you bring up the exact you know uh facing his own mortality yeah it's fascinating that we're able to do that but i don't know now let's let's talk about neural link for a second so what's the concept of generally the concept of neural link is that i'm going to take whatever knowledge is encoded in my brain directly transfer it into your brain so this is a beautiful fascinating and extremely sort of you know appealing concept but i see a lot of challenges surrounding that the first one is we have no idea how to even begin to understand how knowledge is encoded in a person's brain i mean i told you about this paper that we had recently with liquitai and asaf marco that basically was looking at these engrams that are formed with combinations of neurons that co-fire when a stimulus happens where we can go into a mouse and select those neurons that fire by marking them and then see what happens when they first fire and then select the neurons that fire again when the experience is repeated these are the recall neurons and then there's the the memory consolidation neurons so we're starting to understand a little bit of sort of the distributed nature of knowledge and coding and experience in coding in the human brain and in the mouse brain and the concept that we'll understand that sufficiently one day to be able to take a snapshot of what does that seem from dave losing his mind of how losing his mind and talking to dave um how is that seen encoded in your mind imagine the complexity of that but now imagine suppose that we solve this problem and the next enormous challenge is how do i go and modify the next person's brain to now create the same exact neural connections so that's an enormous challenge right there so basically it's not just reading it's not writing and again what if something goes wrong i don't want to even think about that that's number two and number three who says that the way that you encode dave i'm losing my mind and i encode dave i'm losing my mind is anywhere near each other basically maybe the way that i'm encoding it is twisted with my childhood memories of running through you know the pebbles in greece and yours is twisted with your childhood memories growing up in russia and there's no way that i can take my encoding and put it into your brain because it'll a mess things up and b be incompatible with your own unique experiences so that's telepathic communication from human to humor it's fascinating you're you're reminding us that uh there's there's uh two biological systems on both ends of that communication and the one the easier i guess may be half as difficult a thing to do and the hope with neural link is that we can communicate with an ai system so yeah where one side of that is a little bit yeah more controllable but but even just that is is exceptionally difficult let's talk about two two new neuronal systems talking to each other suppose that gpt4 tells gpd3 hey give me all your knowledge right it's ready that's hilarious i have ten times more hardware i'm ready just feed me what's gbt3 going to do is it going to say oh here's my 10 billion parameters no no way the simplest way and perhaps the fastest way for gpd3 to transfer all this knowledge to its older body that has a lot more hardware is to regenerate every single possible human sentence that he can possibly yes create keep talking keep talking and just re-encode it all together so maybe what language does is exactly that it's taking one generative cognitive model it's running it forward to emit utterances that kind of make sense in my cognitive frame and it's re-encoding them into yours through the parsing of that same language and i think the conversation might might actually be the most efficient way to do it so not just talking but uh interactive so talking back and forth yeah asking questions interrupting so gpth4 will constantly be interrupted is also that as we're interrupting each other there's all kinds of misinterpretations that happen that you know as basically when my students speak i will often know that i'm misunderstanding what they're saying and i'll be like hold that thought for a second let me tell you what i think i understood which i know is different what you said then i'll say that and then someone else in the same zoom meeting will basically say well you know here's another way to think about what you just said and then by the third iteration we're somewhere completely different that if we could actually communicate with full you know neural network parameters back and forth of that knowledge and idea and coding would be far inferior because the re-encoding with our own as we said last time emotional baggage and cognitive baggage from our unique experiences through our shared experiences distinct encodings in the context of all our unique experiences is leading to so much more diversity of perspectives and again going back to this whole concept of this entire network of all of human cognitive systems connected to each other and sort of how ideas and memes permeate through that that's sort of what really creates a whole new level of human experience through this reasoning layer and this computational layer that obviously lives on top of our cognitive layer so you're one of these aforementioned cognitive systems mortal but uh thoughtful and you're connected to a bunch like you said students uh your wife your kids what do you in your brief time here on earth this is a meaning of life episode so uh what do you hope this world will remember you as what do you hope your legacy will be i don't think of legacy as much as maybe most people things legacy oh it's kind of funny i'm consciously living the present yes many students tell me you know oh give us some career advice i'm like i'm the wrong person i've never made a career plan i still have to make one i um it's funny to be both experiencing the past and the present and the future but also consciously living in the present and just you know there's a conscious decision we can make to not worry about all that which again goes back to the i'm the lucky one kind of thing [Laughter] of living in the present and being happy winning and being happy losing and um there's a certain freedom that comes with that but again a certain um sort of i don't know ephemerity of living for the present but if you if you step back from all of that where basically my my current modus operandis is live for the present make you know every day the best you can make and just make the local blip of local maxima of the universe of the awesomeness of the planet and the town and the family that we live in both academic family and you know biological family um make it a little more awesome by being generous to your friends being generous to the people around you being you know kind to your enemies and uh you know just showing level around you can't be upset at people if you truly love them if somebody yells at you and insults you every time you say the slightest thing and yet when you see them you just see them with love it's a beautiful feeling it's like you know i'm feeling exactly like when i look at my three-year-old who's like screaming even though i love her and i want her good she's still screaming and saying no no no no no and i'm like i love you i genuinely love you but i can i can sort of kind of see that your brain is kind of stuck in that little you know mode of anger and you know there's plenty of people out there who don't like me and i see them with love as the child that is stuck in a cognitive state that they're eventually going to snap out of or maybe not and that's okay so there's that aspect of sort of you know experiencing you know life with the best intentions and you know i love when i'm wrong i i had a friend who was like one of the smartest people i've ever met who would basically say oh i love it when i'm wrong because it makes me feel human [Laughter] and it's so beautiful i mean she's really one of the smartest people i've ever met and she was like oh it's such a good feeling and i love being wrong but there's you know there's something about self-improvement there's something about sort of how do i not make the most mistakes but attempt the most rights and do the fewest wrongs but with the full knowledge that this will happen that's one aspect so so so through this life in the present what's really funny is and that's something that i've experienced more and more really thanks to you and through this podcast is this enormous number of people who will basically comment wow i've been following this guy for so many years now or wow this guy has inspired so many of us in computational biology and so forth i'm like i don't know any of that but i'm only discovering this now through this sort of sharing our emotional states and our cognitive states with a wider audience where suddenly i'm sort of realizing that wow maybe i've had a legacy yes like basically i've trained generations of students from mit and i've put all of my courses freely online since 2001 so basically all of my video recordings of my lectures have been online since 2001. so countless generations of people from across the world will meet me at a conference and say like i was at this conference where somebody heard my voice it's like i know this voice i've been listening to your lectures yes and it's just such a beautiful thing where like we're sharing widely and who knows which students will get where from whatever they catch out of these lectures even if what they catch is just inspiration and passion and drive so there's this intangible you know legacy quote-unquote that every one of us has through the people we touch one of my friends from undergrad basically told me oh my mom remembers you vividly from when she came to campus i'm like i didn't even meet her she's like no but she she sort of saw you interacting with people and said wow he's exuding this positive energy and there's there's that aspect of sort of just motivating people with your kindness with your passion with your generosity and with your you know just selflessness uh of of you know just just just give doesn't matter where it goes i i've been to conferences where basically people you know i'll ask them a question and then they'll come back or like there was a company where i asked somebody question they said oh in fact this entire project was inspired by your question three years ago at the same conference yes i'm like wow and then on top of that there's also the ripple effects of the years speaking to the direct influence of inspiration or education but there's also like the follow-on things that happened to that and there's this ripple that through from you just this one individual and from every one of us from everyone that's what i love about humanity the fact that every one of us shares genes and genetic variants with very recent ancestors with everyone else so even if i die tomorrow my genes are still shared through my cousins and through my uncles and through my you know immediate family and of course i'm lucky enough to have my own children but even if you don't your genes are still permeating through all of the layers of your family so your genes will have the legacy there yeah or every one of us yeah number two our ideas are constantly intermingling with each other so there's no person living in the planet 100 years from now who will not be directly impacted by everyone on the planet living here today yeah through genetic inheritance and through meme inheritance that's cool to think that your ideas manolas callus would touch would uh touch every single person on this planet it's interesting but not just mine joe smith who's looking at this right now his ideas will also touch everybody so there's this interconnectedness of humanity and and then i'm also a professor so my day job is legacy my day job is training not just the thousands of people who watch my videos on the web but the people who are actually in my class who basically come to mit to learn from a bunch of us like the cognitive systems that were shipped to this particular location and who will then disperse back into all of their home countries yeah that's that's what makes america the beacon of the world we don't just export you know goods we export people cognitive systems we we export people who are born here and we also export training that people born elsewhere will come here to get and will then disseminate not just whatever knowledge they got but whatever ideals they learned and i think that's something that's a legacy of the us that you cannot stop with political isolation you cannot stop with economic isolation that's something that will continue to happen through all the people we've touched through our universities so there's the students who took my classes who are basically now going off and teaching their classes and i've trained generations of computational biologists no one in genomics who's gone through mit hasn't taken my class so basically there's this impact through i mean there's so many people in biotech who are like hey i took your class that's what got me into the field like 15 years ago it's just so beautiful yes and then there's the academic family that i have so the students who are actually studying with me who are my trainees so this sort of mentorship of ancient greece these so i basically have an academic family and we are a family there's this such strong connection this bond of you're part of the kelly's family so i have a biological family at home and i have an academic family on campus and that academic family has given me great grandchildren already yes so i've trained people who are now professors at stanford tmu harvard you know what you i mean everywhere in the uh on the world and these people have now trained people who are now having their own faculty jobs so there's basically people who see me as their academic grandfather and it's just so beautiful because you don't have to wait for the 18 years of cognitive you know hardware development to to sort of have amazing conversation with people these are fully grown humans fully grown adult who are you know cognitively super ready and who are shaped by and you know i see some of these beautiful papers i'm like i can see the touch of our lab in those favors it's just so beautiful because you're like i've spent hours with these people teaching them not just how to do a paper but how to think and this whole concept of you know the first paper that we write together is an experience with every one of these students so you know i always tell them to write the whole first draft and they know that i will rewrite every word but but the act of them writing it and what i do is these like joint editing sessions where i'm like let's co-edit and with this co-editing we basically have um creative destruction so i share my zoom screen and i'm just thinking out loud as i'm doing this and they're learning from that process as opposed to like come back two days later and they see a bunch of red on a page i'm sort of well that's not how you write this that's not how you think about this that's not you know what's the point like this morning i was having a i yes this morning between six and eight a.m i had a two-hour meeting going through one of these papers and then saying what's the point here why why do you even show that it's just a bunch of points on a graph no what you have to do is extract the meaning do the homework for them and there's this nurturing this mentorship that sort of creates now a legacy which is infinite because they've now gone off on the you know and all of that is just humanity then of course it's the papers i write because yes my day job is training students but it's a research university the way that they learn is through the men's and manus mind and hand it's the practical training of actually doing research and that research is a beneficial side effect of having these awesome papers that will now tell other people how to think there's this paper we just posted recently on med archive and one of the most generous and eloquent comments about it was like wow this is a master class in scientific writing in analysis in biological interpretation and so so forth it's just so fulfilling from a person i've never met or first say the title of the paper branch i don't remember the title but it's single cell dissection of schizophrenia reveals and so the two the two points that we found was this whole transcriptional resilience like there's some individuals who are schizophrenic but whose they have an additional cell type or initial cell state which we believe is protective and that cell state when they have it will cause other cells to have normal gene expression patterns it's beautiful yeah and then that's that cell is connected with some of the pv interneurons that are basically sending these inhibitory brain waves through the brain and there basically there's a there's another component of there's a set of master regulators that we discovered who are controlling many of the genes that are differentially expressed and these master regulators are themselves genetic targets of schizophrenia and they are themselves involved in both synaptic connectivity and also in early brain development so there's this sort of interconnectedness between synaptic development axes and also this transcription resilience so i mean we basically made up a title that combines all these concepts you have all these concepts all these people working together and ultimately these minds condense it down into a beautifully exactly little document that lives on and that document now has its own life yeah our work has a hundred and a hundred and twenty thousand citations i mean that's not just people who read it these are people who used it to write something based on it yeah i mean that to me is is just so fulfilling to basically say wow i've touched people so i i don't think of my legacy as i live every day i just think of the beauty of the present and the power of interconnectedness and just i feel like a kid in a candy shop where i'm just like constantly you know where do i what what package do i open first and um you know the lucky one a jack of all trades a master of none i think uh for a meaning of life episode we would be amiss if we did not have at least a poem or two do you mind if we uh end in a couple of poems maybe a happy maybe a sad one i would love i would love that so thank you for the luxury the first one is kind of um i remember uh when you were talking with eric weinstein about um this comment of leonard cohen yes that says but you don't really care for music do ya yeah in hallelujah that's basically kind of like mocking its reader yeah so one of my poems is a little like that so i had just broken up with you know my girlfriend and there's this other friend who was coming to visit me and she said i will not come unless you write me a poem [Laughter] and uh i was like writing a form on demand so this this poem is called write me a poem it goes write me a poem she said with a smile make sure it's pretty romantic and rhymes make sure it's worthy of that bold flame that love uniting us beyond a mere game and she took off without more words rushed for the bus and travelled the world a poem i thought this is sublime what better way for passing the time what better way to count up the hours before she comes back to my lonely tower waiting for joy to fill up my heart let's write a poem for when we're apart how does a poem start i inquired give me a topic hook up a style throw in some cute words oh here and there throw in some passion love and despair love three eggs one pound of flour three cups of water and bake for an hour love is no recipe as i understand you can't just cook up a poem on demand and as i was twisting all this in my mind i looked at the page by golly it rhymed three roses white chocolate vanilla powder some beautiful rhymes and maybe a flower no be romantic the young girl insisted do this do that don't be so silly you must believe it straight from your heart if you don't feel it we're better apart oh my sweet thing what can i say you bring me the sun all night and all day you're the stars and the moon and the birds way up high you're my evening sweet song my morning blue sky you are my muse your spell has me caught you bring me my voice and scatter my thoughts to put love in writing in vain i can try but when i'm with you my wings want to fly so i put down the pen and drop my defenses give myself to you and fill up my senses the baffle king composing that was beautiful what i love about it is that i did not bring up a dictionary of rhymes i did not sort of work hard so basically when i write poems i just type i never go back i just so when my brain gets into that mode it actually happens like i wrote it oh wow so the rhymes just kind of becomes it's an emergent phenomenon phenomenon i just get into that mode and then it comes out that's a beautiful one and it's it's basically um you know as you as you got it it's basically saying it's no recipe and then i'm starting throwing the recipes and as i'm writing it i'm like you know so it's it's very introspective in this whole uh concert so anyway there's another one many years earlier that um is you know darker it's basically this whole concept of let's be friends i was like ugh no let's be friends just like you know so the last words are shout out i love you or send me to hell so uh the the title is burn me tonight lie to me baby lie to me now tell me you love me break me a vow give me a sweet word i promise a kiss give me the world a sweet taste to miss don't let me lay here inert ugly cold with nothing sweet felt and nothing harsh told give me some hope false foolish yet kind make me regret i'll leave you behind don't pity my soul or torture it right treat it with hatred start up a fight for it's from mildness that my soul dies when you cover your passion in a bland friend's disguise kiss me now baby show me your passion turn off the light and rip off your fashion give me my life's joy this one night burn all my matches for one blazing light don't think of tomorrow and let today fade don't try and protect me from love's cutting blade your razor will always rip off my veins don't spare me the passion to spare me the pains kiss me now honey or spit in my face throw me an insult i'll gladly embrace tell me now clearly that you never cared say it now loudly like you never dared i'm ready to hear it i'm ready to die i'm ready to burn and start a new life i'm ready to face the rough burning truth rather than waste the rest of my youth so tell me my lover should i stay or go the answer to love is one yes or no there's no i like you no let's be friends shout out i love you or send me to hell i don't think there's a better way to end a discussion of the meaning of life whatever the heck the meaning is uh go all in as that poem says manolas thank you so much for talking today thanks i look forward to next time thanks for listening to this conversation with manolas kellis and thank you to our sponsors grammarly which is a service for checking spelling grammar sentence structure and readability athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases cash app the app i use to send money to friends please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and have a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from douglas adams in his book hitchhiker's guide to the galaxy on the planet earth man had always assumed that he was more intelligent than dolphins because he had achieved so much the wheel new york wars and so on whilst all the dolphins had ever done was muck about in the water having a good time but conversely the dolphins had always believed that they were far more intelligent than man for precisely the same reasons thank you for listening and hope to see you next time |
Lisa Feldman Barrett: Love, Evolution, and the Human Brain | Lex Fridman Podcast #140 | the following is a conversation with Lisa Feldman Barrett her second time on the podcast she's a neuroscientist at Northeastern University and one of my favorite people her new book called 7 and a half lessons about the brain is out now as of a couple of days ago so you should definitely support Lisa by buying it and sharing with friends if you like it it's a great short intro to the human brain quick mention of each sponsor followed by some thoughts related to the episode a FL of greens the all-in-one drink that I start every day with to cover all my nutritional bases eight sleep a mattress that cools itself and gives me yet another reason to enjoy sleep master class online courses that I enjoy from some of the most amazing people in history and better help online therapy with a licensed professional please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that Lisa just like manolis Kellis is a local brilliant mind and friend and someone I can see talking to many more times sometimes it's fun to talk to a scientist not just about their field of expertise but also about random topics even silly ones from love to music to philosophy ultimately it's about having fun something I know nothing about this conversation is certainly that it may not always work but it's worth a shot I think it's valuable to alternate along all kinds of Dimensions like between deeper technical discussions and more fun random discussion from Liberal thinker to conservative thinker from musician to athlete from CEO to Junior engineer from friend to stranger variety makes life and conversation more interesting let's see where this little podcast journey goes if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on spot sptify support on patreon or connect with me on Twitter at Lex Freedman and now here's my conversation with Lisa Felman Barrett based on the comments in our previous conversation I think a lot of people will be very disappointed I should say to learn that you are in fact married as they say all the good ones are taken okay so uh I'm a fan of your husband as well Dan he's a programmer musician so a man after my own heart can I ask a ridiculously over romanticized question of when did you first fall in love with Dan it's actually it's a really it's a really romantic story I think so I was divorced by the time I was 26 27 26 I guess and I was in my first academic job which was Penn State University which is in the middle of Pennsylvania surrounded by mountains so you have it's four hours to get anywhere to get to Philadelphia New York Washington I mean you're basically stuck you know um and I was very fortunate to have um a lot of other assistant professors who were hired at the same time as I was so there were a lot of us we were all friends which was really fun um but I was single and I didn't want to date a student and there were no and I wasn't going to date somebody in my department that's just a recipe for disaster yeah so so even at 20 whatever you were you were already wise enough to know that yeah a little bit maybe yeah I wouldn't call me wise at that age but anyways um not sure that I would say that I'm wise now but um and so um after a you know I was spending probably 16 hours a day in the lab because it was my first year and as an assistant professor and there's a lot to do and I was also bitching and moaning to my friends that you know I hadn't had sex in I don't know how many you know months and it was I was starting to you know become unhappy with my life and um I think at a certain point they just got tired of listening to me and moan and said just do something about it then like do you know if you're unhappy and so the first thing I did was I I made friends with a sushi chef in town and this is like a State College Pennsylvania in the early 90s was there was like a pizza shop and a sub shop and actually a very good bagel shop and one good coffee shop and maybe one nice restaurant I mean there was really but there was a the Second Son of a Japanese sushi chef who was not going to inherit the restaurant and so he moved to Pennsylvania and was giving Sushi lessons so I met this guy the sushi the sushi chef and we decided to throw a sushi party at the coffee shop so we basically it was the goal was to invite every eligible bachelor really within like a 20 mile radius MH we had a totally fun time I wore an awesome crushed velvet burgundy dress it was beautiful dress um and I didn't meet any I met a lot of friend new friends but I did not meet anybody so then I thought okay well maybe I'll try the personals ads which I had never used before in my life and um I first tried the paper personals ads like a then newspaper like in the newspaper that didn't work and then a friend of mine said oh you know there's this thing called Net News so we're going this is like 1992 maybe so there was this Anonymous you could do it anonymously so you would you would read um you could post or you could read ads and then respond to an address which was Anonymous and you that was yolked to somebody's real address and um and there was always a lag because it was this like a bulletin board sort of thing so at first I read I read them over and I decided to to respond to one or two and you know it was interesting sorry this is not on the internet yeah this is totally on the internet but it takes there's a delay of a couple days or whatever right it's 1992 there's no web web no pictures there's no pictures the web doesn't exist it's all done in asky format sort of um and you know but the but the ratio of um men to women was like 10 to one I mean there were many more men because it was basically academics and the government that was it those no I mean I think AOL maybe was just starting to become popular but um and so the first uh person I met told me that he was a um he wor he was a scientist who worked for NASA and um yeah um anyways it turned out that he didn't actually yeah this is how they brag is as like you elevate your as opposed to saying you're taller than you are you say like your position is high yeah and I actually I would have been fine dating somebody who wasn't a scientist it's just that they have it's just that whoever I date has to just accept that I am and that I'm I was pretty ambitious and was trying to make my career and you know that's not that that's not an I think it's maybe more common now for men to maybe accept that in their female Partners but at that time not not so intimidating I guess yes I I that has been said and so um and so then the next one I actually corresponded with and we actually got to the point of talking on the phone and we had this really kind of funny conversation where you know we're chatting and he said he he introduces the idea that um you know he's really looking for a dominant woman and I'm thinking I'm a psychologist by training so I'm thinking oh he means sex roles like I'm like no I'm very assertive and I'm glad you think that you know okay anyways long story short that's not really what he meant okay got it yeah so and I just you know that will just show you my level of naive like I was like I didn't completely I was like well yeah you know no at one point he asked me how I felt about him uh wearing my lingerie and I was like I don't even share my lingerie with my sister like I don't share my linger with anybody you know no no the third one I interacted with was a banker who lived in Singapore and um that that conversation didn't last very long because he made an anal I guess he he made an analogy between me and uh character in The Fountain Head um the woman who's who's raped in the Fountain Head and I was like okay that's not that's not a good that's not a good that's not a good one not that part not that scene not that scene so then I um so then I was like okay you know what I'm going to post my own ad and so I did I posted well first I wrote my ad and then of course I checked it with my my friends who were all also assistant professors they're like my little greek chorus and then I posted it and I got some like uh I don't know 80 something responses in 24 hours I mean it was do you remember the pitch um like how how you I guess condensed yourself I don't remember it exactly although Dan has it um but um actually for our 20th wedding anniversary he took our our exchanges and he printed them off and put them in a leatherbound book for us to read which was really sweet um yeah I think I was just really direct like I'm almost 30 I'm a scientist I'm not looking to you know I'm I'm looking for something serious and you know but the thing is I I forgot to say where my location was yeah and my age yeah which I forgot yeah so I got lots of I mean I will say so I printed off all of the responses and um I had all my friends over and we were you know had a big I made a big um pot of gumbo and we drank through several bottles of wine reading these responses and I would say for the most part they were really sweet like Earnest and genuine as much as you could tell that somebody's being genuine it seemed you know there were a couple of really funky ones like you know this one couple who told me that I was their soulmate the two of them then they were looking for you know a third person and I was like okay but mostly super seemed seemed like super genuine people and so I chose five men to start corresponding with and I was corresponding with them and then then about a week later I get this other email and okay and then I post something the next day that said okay you know thank you so much and I'm going to I answered every person back but then after that I said okay and I'm not going to answer anymore you know because it was they were still coming in and I couldn't you know I have a job and you know a house to take care of and stuff so um and then about a week later I get this other email and um he says you know he just describes himself like I'm this I'm this I'm this I'm a chef I'm a scientist I'm a this I'm a this and so I emailed him back and I said you you know you seem interesting you can write me at my actual address if you want here's my address I'm not really responding I'm not really responding to other people anymore but you seem interesting you know you can write to me if you want um and then he wrote to me and uh I um then I wrote him back and I it was it was a non-descript kind of email and I wrote him back and I said thanks for responding you know I'm really busy right now I'm I was was in the middle of writing my first slate of Grant application so I was really consumed and I said I'll get back to you in a couple of days and so I did I waited a couple days I until my grants were you know safe Grant application safely out the door and then I emailed him back and then he emailed me and then really across two days we sent a 100 emails and text only was there pictures and any of that text only text only wow and then so this was like a Thursday and a Friday and then Friday he said let's talk on the weekend on the phone and I said okay and he wanted to talk Sunday night and I had a date Sunday night so I said okay sure we can talk Sunday night um and then I was like well you know I don't really want to cancel my date so I'm just going to call him on Saturday so I just called I co called them on Saturday and a woman answered oh wow that's not cool not cool and uh so she says you know hello and I say oh you know it's down there and she said sure can I ask who's calling and I said it tell them it's Lisa and she went oh my God oh my God I'm just a friend I'm just a friend I just have to tell you I'm just a friend and I was like yeah this is adorable right she doesn't and then he gets on the phone not high nice to be the first thing he says to me she's just a friend so I was just so Charmed really by the whole thing so it was it was yam kapor it was the Jewish um uh day of atonement that was ending and they were baking cookies and going to a break fast so people you know as you know fast all day and and then they go to a party and they break fast so uh I thought okay I'll just um I'll just you know cancel my date so I did and I stayed home and we talked for 8 hours um and then the next night for 6 hours and it basically it just went on like that and then uh by the end of the week he um he flew to State College and you know we had gone through this whole thing where ID said we're going to take it slow we're going to get to know each other you know and then really by I think we talked like two or three times these like really long conversations and then he said I'm just going to fly there and then so of course there's I don't even know that there were fax machines at that point maybe there were but I don't think so anyway so he we decideed we'll exchange pictures and um so he you know I take my photograph and I give it to my secretary and I say to my secretary facts this I say this say send this priority mail priority mail and he goes okay I'll send a priority mail Priority Mail he's like I know Priority Mail okay and then uh so I get Dan's photograph in the in the mail um and um you know it's it's him in a in a in shorts and you can see that he's probably somewhere like the Bahamas or something like that and it's like cropped so clearly what he's done is he's taken a photograph where you know he's in in it with someone else who turned out to be his ex-wife so I'm thinking well this is awesome you know I I've hit the jackpot he's he's you know very appealing to me very attractive and um and then you know my photograph doesn't show up and it doesn't show up and you know so like one day and then two days and then you know he's he's like you know you're I said well I I asked my secretary to send a priority I mean I don't know you know um what he did and uh and he's like I said I'm like well you don't have to you know you don't have to come and he's like no no no I'm gonna I'm gonna you know we've had like five dates the equivalent of five dates practically um and then um so he's supposed to fly on a Thursday or Friday I can't remember and uh I get a call like maybe an hour before his flight's supposed to leave and he says hi and I say and it's just something in his voice right and I say cuz at this point I think I've talked to him like for 25 hours I don't know and he says hi and I'm like you got the picture and he's like yeah and I'm like you don't like it and he's like well I'm sure it's not I'm sure it's your I'm sure just not a good you know it's not it's probably not your best oh no you know you don't you don't have to come and he's like no no no I'm coming and I'm like no you don't have to come and he's like no no I really want to I'm you know I'm I'm getting on the plane I'm like you don't have to get on the plane um he's like no I'm getting on the plane and so I go down to my I go I'm in my office this is happening right so I go downstairs to my one of my closest friends who's still actually one of my closest friends um who is one of my colleagues and um Kevin and I say Kevin and I go to Kevin I go Kevin Kevin Kevin he doesn't like the photograph and Kevin's like well which photograph did you send and I'm like well you know the one where we're shooting pool and he's like you sent that photograph that's a horrible photograph I'm like yeah but it's the only one that I had that was like where my hair was kind of similar to what it is now and he's like Lisa like do I have to check everything for you you know you should not have sent that yeah you know but still he flew over but so he flew where from by the way uh he was in he was in graduate school at Amherst yeah at um UMass Amherst so he flew and um I picked him up and at the airport and he was happy so whatever the concern was was gone yeah and um I was dressed you know I carefully carefully dressed were you nervous I was really really nervous cuz I I am not I don't really believe in fate and I don't really think there's only one person that you can be with but I think you know people who some people are curvy they're kind of complicated and so the number of people who fit them is maybe less than I like it mathematically speaking yeah I got it um and so when I was going to pick him up at the airport I was thinking well this could I could be going to pick up the the person I'm going to marry or not I mean like I really but I really you know like our conversations were just very authentic and very moving and um and we really connected and and I really felt like he understood me actually um in in a way that a lot of people don't and um and and what was really nice was at the time um you know the airport was this tiny little airport out in a cornfield basically and so driving back to the town we were in the car for 15 minutes completely in the dark as I was driving and so it was very similar to we had just spent you know 20 something hours on the telephone um sitting in the dark talking to each other so it was very familiar and we basically spent the whole weekend together and you met all my friends and we had a big party and um and at the end of the weekend um I said okay you know if we're going to give this a shot we we probably we shouldn't see other people so it's a risk you know it's commitment um but but I just didn't see how it would work if we were dating people locally and then also seeing each other at a distance because I you know I've had longdistance relationships with war and they're hard and they they take a lot of they take a lot of effort and so we decided we'd give it three months and see what happened and that was it this such an interesting thing like we're all what is it there are several billion of us and we're kind of roaming this world and then you kind of stick together you find find somebody that just like gets you and it's interesting to think about there's probably thousands if not millions of people that would would be sticky to you depending on the curvature of your space but what what is the could you speak to the stickiness like to the just the falling in love like seeing that somebody really gets you maybe by way of um telling do you think do you remember there was a moment when you just realized damn it I think I'm like I think that's this is the guy I think I'm in love we were having these conversations actually from the really from the second weekend we were together so he flew back the next weekend to stay College because my birthday it was my 30th birthday my friends were throwing me a party and we went hiking and we hiked up some mountain and we were sitting on a cliff over this you know Overlook and talking to each other and I was thinking and I actually said to him like I I haven't really known you very long but I feel like I'm falling in love with you which can't possibly be happening I must be projecting but it be projecting but it certainly feels that way right like I don't believe in love at first sight so this can't really be happening but it sort of feels like it is and he was like I know what you mean and so for the first three months or four months we would say things to each other like I feel like I'm in love with you but you know but that can't but things don't really work like that so but you know so and then it became a joke like I feel like I'm in love with you and then eventually you know I think um but I think that was one moment where we were we were talking about I don't just you know not just all the great aspirations you have are all the things but also things you don't like about yourself things that you're worried about things that you're scared of and then I think the that was sort of solidified the relationship and then there was one weekend where we went to Maine in the winter which I I mean I really love the beach always but in the winter particularly CU it's just beautiful and calm and whatever yeah and I also I I do find beauty in starkness sometimes like so there's this Grand Majestic scene of you know this very powerful ocean and it's all these like beautiful blue Grays and it's just it's just stunning and so we were sitting on this huge Rock in Maine and where we had gone for the weekend it was freezing cold and I honestly can't remember what he said or what I said or what but I I definitely remember having this feeling of um I absolutely want to stay with this person like I and I don't know what my life will be like if I'm not with this person like I need to be with this person can we from a scientific and a human perspective uh dig into your belief that first uh love at first sight is not is not possible you don't believe in it because there is there you don't think there's like a magic where you see somebody in the in the Jack carck way and you're like wow that's something that's that's a special little oh I definitely oh I definitely think can connect with someone instant in an instance and I definitely think you can say oh there's something there and I'm really clicking with that person romantically but also just with friends it's possible to do that you recognize a mind that's like yours or that's compatible with yours there are ways that you feel like you're being understood or that you understand something about this person or maybe you see something in this person that you find really compelling or intriguing but I think you know your brain is predictive organ right you're you you're using your past you're projecting you're using your past to yeah make predictions and I mean not deliberately that's how your brain is wired that's what it does and so it's filling in all of the gaps that you you know there are lots of gaps of information that you don't you know information you don't have and so your brain is filling those in and um but isn't that what love is no I don't think so actually I mean to some extent sure you you always you know there's research to show that people who are in love always see the best in each other and they you know when there's a when there's a negative interpretation or positive interpretation you know they choose the positive on there's a little bit of positive illusion there you know going on that's what the research shows but I think um I think that when you find somebody who not just appreciates your faults but Lo loves you for them actually you know like maybe even doesn't see them as a fault that's you so you have to be honest enough about what you're what your faults are so it's easy to love someone for all the things that they um uh for all the wonderful characteristics they have it's harder I think to love someone despite their faults or maybe even the faults that they see aren't really faults at all to you they're actually something really special but isn't isn't that can't you explain that by saying the brain kind of like you're projecting it's you're you have a conception of um a human being or just a a spirit that really connects next with you and you're projecting that onto that person and within within that framework all their faults then become beautiful like little maybe but you you just have to pay attention to the prediction error no but maybe that's what love like maybe you IGN you start ignoring the prediction error that's maybe love is just your ability uh like to ignore the prediction era well I think that there's some research that might say that but that's not my experience I guess um but there is some research that says I mean there's some some research that says you have to have an optimal margin of Illusion which means that you um that you put a positive spin on on smaller things but you don't ignore the bigger things right and I think without being judgmental at all when someone says to me you know um you're not who I thought you were I mean nobody says has said that to me in a really long time but certainly when I was younger that was you know you're not who I thought you were my reaction to that was well whose fault is that you know yeah um I'm a pretty I'm a pretty upfront person um I mean I will though say that in my experience people people don't lie to you about who they are they lie to themselves in your presence yeah um and so you know you don't want to get T tied up in that tangled up in that and I think from the ge-o Dan and I were just for whatever reason maybe it's because we both have been divorced already and you know um you know he told me who he thought he was and he he was pretty accurate as far as I pretty much actually I mean I there's very I can't say that I've ever come across a characteristic in him that really surprised me in a bad way it's hard to know yourself it it is hard to know yourself to communicate that for sure I mean I'll say you know I had the advantage of training as a therapist which meant for five years I was under a microscope yeah um you know when I was training as a therapist it was hour for hour supervision which meant if you were in a room with a client for an hour you had an hour with a with a supervisor so that Supervisor was behind the mirror why for your session and then you went and had an hour of discussion about what you said what you didn't say learning to use your own react your own feelings and thoughts as a tool to probe the mind of the client and so on and so you you can't help but learn a lot of you can't learn help but learn a lot about yourself in that process do you think um knowing or learning how the sausage is made ruins the magic of the actual experience like you as a neuroscientist who studies the brain do you think it ruins the magic of like love at first sight or are you do you consciously are still able to lose yourself in the moment I'm definitely able to lose myself in the moment is wine involved not always chocolate I mean some kind of mind altering substance right but um yeah for sure I mean I guess what I would say though is that [Music] um for me part of the magic is the process like so ah you know so so I remember a day there was well I was working on this on this on this book of essays I I was in New York um I can't remember why I was in New York but I was in New York for something and I was in Central Park and I was looking at all the people with their babies and I was thinking every every that each one of these there's a tiny little brain yeah that's wiring itself right now and I and I I just I felt in that moment I was like I am never going to look at an infant in the same way ever again and so to me I mean honestly before I started learning about brain development I thought babies were cute but you know not that interesting until they could do interact with you and do things of course my own infant I thought was extraordinarily interesting but you know they're kind of like lumps that you know until they can you know interact with you but they are anything but lumps I mean like you know so and part of the I mean I all I can say is I have deep affection now for like tiny little babies in a way that I didn't really um before um ju because of the I'm just so curious but the actual process the mechanisms of uh the the the wiring of the brain the learning all the magic of the the neurobiology yeah and or you know something like you know um when you make eye contact with someone directly sometimes you know you you feel something right yeah and um yeah that's weird what is it and what is that and so so to me that's not um that's not backing away from the moment that's like expanding the moment it's like that's incredibly cool you know when I was um I'll just say that when I was when I was in graduate school I also was in therapy because it's almost a given that you're going to be in therapy yourself if you're going to become a therapist and I had a deal you know with my therapist which was that I could call time out at any moment that I wanted to As Long As I was being responsible about it and I wasn't using it as a way to get out of something and he could tell me no you know he could Decline and say no we're you're you know you're using this to get out of something but I could call time out whenever I want and say what are you doing right now like what are you here's what I'm experiencing what are you trying to do like I wanted to use my own experience to interrogate um what the process was and that made it more helpful in a way do you know what I mean so yeah I don't I don't think learning how something works makes it less magical actually but that's just me I guess I don't know would you yeah uh yes I tend to uh have two modes one is one is an engineer and one is a romantic and I'm conscious of like like the gear like you like there's two rooms you can go into the one the engineer room and I think that ruins the romance so I tend to there's two rooms one is the engineering room think from first principles how do we build the thing that creates this kind of uh behavior and then you go into the ROM ROM Mantic room where you're like emotional it's a roller coaster and then you're uh the thing is let's take it slow and then you get married the next night that you just this giant mess and you write a song and then you cry and then you send a bunch of text and anger and and whatever and somehow you're in Vegas and there's random people and you're drunk and whatever all that like in poetry and just mess of it fighting yeah yeah that's not those are two rooms and you go back between between them but I think the way you put it is quite poetic I think you're much you're much better at adulting uh with love uh than uh then perhaps I am because there is a magic to children I also think like of adults as children it's kind of cool to see it's a cool thought experiment to look at adults and think like that used to be a baby and then that's like a fully wired baby and it's just walking around pretending to be like all serious and important wearing a suit or something but that used to be a baby and then you think of like the parenting and all the experiences they had like it's it's cool to think of it that way but then you I started thinking like from a machine learning perspective but once you're like the romantic moments all that kind of stuff all that falls away I forget about all that I don't know that's the Russian thing maybe maybe but I also think it might be an age thing or maybe an experienc thing so I think um we all I mean if you're exposed to Western culture at all you are exposed to the uh sort of idealized stereotypic romantic romantic you know uh exchange and what what does it mean to be romantic and um so here's a test um um I'm see how to phrase it okay so not really test but this this tells you something about your own ideas about romance uh for Valentine's Day one year my husband bought me a six-way plug is that romantic or not romantic like sorry 6p play that's like an out like a yeah like to put in an outlet is that romantic or not romantic I mean depends the look in his eyes when he does it I mean it depends on the conversation that led up to that point depends how much uh it's like the music because you have a very you're you're both from the my experiences with you as a fan you have both a romantic nature but you have a very pragmatic like you cut through the of of uh the fuzziness and there there's something about a six-way plug that cuts to the that connects to the human like he understands who you are exactly yeah exactly yeah that was the most romantic gift he could have given me because he knows me so well he has a deep understanding of me which is that I will sit and suffer and complain yeah about the fact that I have to plug and unplug things and I will and moan until the cows come home but it would never occur to me to go buy a bloody six-way plug whereas for him he bought it he plugged it in he arranged he taped up all my wires he made it like really usable and for me that was uh that was the best it was the most romantic thing because he understood who I was and he did something very or you know just the Casual like we moved into a house that went we went from having a two-car garage to a onecar garage and I said okay you know I'm from Canada I'm not bothered by Snow Well I mean I'm a little little bothered by snow but he's very bothered by snow so I'm like okay you can park your car in the garage it's fine every day when it snows he goes out and cleans my car every day like I never asked him to do it he just does it because he knows that I'm cutting it really close in the morning you know when we when we all used to go to work um I have it timed to the second so that I can get up as late as possible work out as long as possible you know just to and into my office like a minute before my first meeting and so if it snows unexpectedly or something I'm screwed because now that's an added you know an added 10 or 15 minutes and I'm going to be late um anyways you know it's just these little tiny things that he's he's um he's he's a really easygoing guy and he doesn't look like somebody who pays attention to detail he doesn't fuss about detail but he definitely pays attention to detail and it's it is very very romantic in the sense sense that he um you know he loves me despite my little details it understands you yeah it is kind of hilarious that that is the six-way plug is um the the most fulfilling richest uh display of romance in your life I love it I love that's mean about romance romance is really it's not all about chocolates and flowers and you know whatever I mean those are all nice too but um sometimes it's about the sixth way plan sometimes it's about the six way plan so um maybe one way I could ask before we talk about the details you also have the author of another book is we talked about how emotions are made so it's interesting to talk about the process of writing you mentioned you were in New York what have you learned from writing these two books about the actual process of writing and maybe I don't know what's the most interesting thing to talk about there maybe the biggest challenges or the the boring mundane systematic like day-to-day of what worked for you like hacks or or even just about the Neuroscience that you've learned through the process of trying to write them here's the thing I learned if you think that it's going to take you a year to write your book it's going to take you three years to write your book that's the first thing I learned is that you no matter how organized you are it's always going to take way longer than what you think um in part because um very few people make an outline and then just stick to it you know the the some of the topics really take on a life of their own and to some extent you want to let them get you want to let them have their voice you know you want to follow leads until you feel satisfied that you've dealt with the topic um uh appropriately but I and that part is actually fun it's not fun to feel like you're con ly behind the eightball in terms of time yeah um but it is the exploration and the foraging for information is incredibly fun for me anyways I found it really enjoyable and if I wasn't also running a lab at the same time and trying to keep my family going uh you know it would have been the whole thing would have just been fun um but I would say the hardest thing about the most important thing I think I learned is also the hardest thing and that for me which is um knowing what to leave at out a really good Storyteller knows what to leave out in in academic writing you you shouldn't leave anything out you you all the details should be there right and um and I you know I've written or participated in in writing over 200 papers um peer-reviewed papers so I'm pretty good with detail knowing what to leave out knowing what to leave out and not harming the validity of the story that is a tricky tricky thing it was tricky when I wrote how emotions are made but that's a standard um popular science book so it's 300 something pages and then you know it has like a thousand endnotes and then each of the endnotes is attached to a web note which is also long so I mean you know it's um and it start and I mean the final draft I I wrote three drafts of that book actually and the final draft and then I had to cut by a third I mean or I mean I you know it was like 50,000 words or something and I had to cut it down to like 110 so um obviously it's I struggle with what to leave out you know brevity is not my strong suit I'm always telling people that it's a warning so that's why this book was a I you know I always been really fascinated with essays I I love reading essays and after reading a a a small set of essays by an fatan um called at large and at small which I just loved these little essays what's what's the topic of that those essays they are they're called um familiar essays so there the topics are like everyday topics like male um coffee chocolate I mean just like and what she does is she weaves her own experience it's a little bit like these conversations that you're so good at curating actually um you're weaving together history and philosophy and Science and also personal Reflections and a little bit you feel like you're like eavesdropping on someone's train of thought in a way it it's really they're really compelling to me and even if it's just like a mundane topic yeah but it's so interesting to um learn about like all of these little stories in the in the wrapping of the history of like male like that's in that's really interesting and so I read these essays and then I wrote to her a little fan girl email um this was many years ago and um and I said I I I just love you I love this book and how did you learn to write essays like this and she gave me a reading list of essays that I should read like writers and so I read them all and anyway so I decided it would be a really good challenge for me to try to write something really brief where I could focus on you know one or two really fascinating tidbits of of Neuroscience connect it to connect each one to something philosophical or um you know like just a question about human nature do it in a really brief format without violating the validity of the science that was a I just set myself this what I thought of as a really really big challenge in part because it was an incredibly hard thing for me to do in the first book yeah we should say that this is uh the seven and a half lesson is a very short book I mean it's uh it's like it embodies uh brevity right the whole point throughout is just I mean you you could tell that there's editing like there's pain in trying to bring it as brief as possible as clean as possible yeah yeah so it's I the way I think of it is um you know it's a little book of big science and Big Ideas yeah really big ideas in and in brief little packages and um you know I wrote it um so that people could read it I love reading on the beach I love reading essays on the beach I read it I wrote it so people could read it on the beach or in the bathtub or you know a subway stop yeah even if the beach is frozen over in the snow yeah so my husband Dan calls it the first Neuroscience Beach read that's his um that's his phrasing yeah and like like you said you learned a lot about writing from your husband like you were saying offline well he's he is of the two of us he is the better writer he is a masterful writer um he um he's also I mean he you know he's a PhD in computer science he's he's a software engineer but he's he's also really good at uh organization of knowledge so he built for a company he used to work for he built one of the first Knowledge Management systems and he's he now works at Google where he does engineering education like he's he understands how to tell a good story just you know about anything really um he's got got impeccable timing he's really funny and luckily for me he knows very little about psychology or Neuroscience well now he knows more obviously but so you know he was really when how motions were made um you know he was really really helpful to me because um the first draft of every chapter was me talking to him about what on you know I would talk out loud about what I wanted to say and the order in which I wanted to say it and then I would write it and then he would read it and um tell me all the bits that could be excised yeah and sometimes we would you know I should say I mean we don't he and I don't really argue about much except um directions in the car like we're that's where're that's if we're going to have an argument that's going to be where it's going to happen where what's the what's the nature of the argument about directions exactly I don't really know it's just that we're very I think it's that spatially you know he he um I use egocentric space so I want to say you know turn left like I always I'm I'm reasoning in relation to like my own physical corporeal body so you know you walk to the church and you turn left and you then you you know whatever you know I'm always like and his you know he gives directions um aloc centrically which means um organized around north south east west right so to you the the Earth is at the center of the solar system and to him no I'm reason I'm at theer you're at the center of the Sol system okay so uh anyway so we we but but here we you know we we had some really RI roaring arguments like really rip roaring arguments where he would say like who is this for is this for the 1% and I'd be like 1% meaning not you know not wealth but like civilians versus academics you know are these for the scientists or for the CI is this for the civilians right so he speaks for the for the people for the people and I'd be like no you have to and so he made you know after one terrible argument that we had where it was really starting to affect our our relationship because we were so mad at each other all the time um he made these little signs writing and Science and we only us them this this was like when you when you pulled out a sign that's it like the other person just wins and you have to stop fighting about it yeah and that's it great and so we just did that um and we didn't really have to use it too much for this book cuz this book was in some ways um uh you know I didn't have to learn a lot of new things for this book I had to learn some but I a lot of um what I learned for seven and uh for um how tions are made really St stood me in good stead for for this book so there was a little bit each essay was a little bit of learning a couple were was a little more than than a small amount but um but I I didn't have so much trouble here um I had a lot of trouble with the first book um but still even here you know um you know he would tell me that I could take something out and I really wanted to keep it and um I think we only use the signs once well if we could dive in some aspects of the book I I would love that um can we talk about so one of the essays looks at evolution let me ask the big question uh did the human brain evolve to think that's essentially the question that you address in the essay can you speak to it sure you know the the big cave out here is that we don't really know why brains evolved the the big why questions are called teologico those questions because we don't don't know really why we don't know the why however for for a very long time the Assumption was that Evolution worked in a progressive upward scale that you start off with simple organisms and those organisms get more complex and more complex and more complex now obviously that's true in some like really General way right that that um life started off as single cell organisms and you know things got more complex but the idea that um that brains evolved in some upward um trajectory from simple brains in simple animals to complex brains in complex animals is called a philogenetic scale um and um that philogenetic scale is embedded in a lot of evolutionary thinking including darwins actually um and it's been seriously challenged I would say by modern uh evolutionary bi biology um and so you know thinking is something that rationality is something that humans at least in the west really prize um as a great uh human achievement and so the idea that the most common evolutionary story is that you know brains evolved in um like sedimentary rock um uh with you know a layer for instincts that's your lizard brain and a layer on top of that uh uh for emotions that's your limic system lyic meaning border so it borders the parts that are for instincts oh interesting and um and then um the uh neocortex or new cortex where um rationality is supposed to live that's the sort of traditional story it just keeps getting layered on top by Evolution right and so you can think about you know I mean sedimentary rock is the way typically people describe it the way I sometimes like to think about it is um you know thinking about the cerebral cortex like uh icing on an already baked cake you know um where you know the cake is your inner Beast these like boiling you know roiling instincts and emotions that have to be contained and the the by the cortex and the the it's just um it's a fiction it's a myth it it's a myth that you can trace all the way back to stories about morality um in ancient Greece but what you can do is look at the scientific record and say well there there's others there are other stories that you could tell about brain Evolution and and the the context in which brains evolved so when you look at creatures who don't have brains and you look at creatures who do what's the difference and um you can look at you know some animals um so we call scientists call an environment that an animal lives in a niche their environmental Niche what are the things what are the parts of the environment that matter to that animal and um so there's some animals whose Niche hasn't changed in 400 million years so they're they're not these creatures are modern creatures but they're living in a niche that hasn't changed much and so their biology hasn't changed much and you can kind of verify that by looking at the genes that lur deep you know in the molecular structure of cells and so you can by looking at various animals in their developmental State meaning not you don't look at adult animals you look at embryos of animals and developing animals you can see you can piece together a different story and that story is that brains evolved under the selection pressure of hunting that in the Cambrian Period hunting emerged on the scene where animals deliberately ate one another um and what so you know before the Cambrian Period the animals didn't really have well they didn't have brains but they also didn't have senses really the very very rudimentary senses so the animal that I wrote about in seven and a half lessons is called an amphioxys or a lancelet and um little amphioxys has no eyes it has no ears it has no nose it it it it has no eyes it has a couple of cells for um uh detecting light and dark for circadian rhythm purposes so and it it it can't hear it has a vestibular cell to keep its body upright um it has a very rudimentary sense of touch and it doesn't really have any internal organs other than this like basically stomach it's like a just like a it doesn't it doesn't have an enteric nervous system it doesn't have like a gut that you know moves like we do it just has basically a tube yeah um so it's like little container like a little container yeah and so and really it doesn't it doesn't move very much it can move it just sort of wriggles it doesn't have very sophisticated movement and it's this really sweet little animal it sort of wriggles its way to a spot and then plants itself in the sand and just filters food as the food goes by um and then when the food concentration decreases it it just it it just um ejects itself wriggles to the ne some spot randomly where probabilistically there will be more food and plants itself again so it's it's not it's not really aware very aware that it has an environment it has a niche but that Niche is very small and it's not really experiencing that Niche very much um so it's it's basically like a little stomach on a stick that's that's really what it is and um but but when animals start to literally hunt each other um all of a sudden it becomes important to have to be able to sense your envir ironment because you need to know is that blob up ahead going to eat me or should I eat it mhm and so all of a sudden you want distance senses are very useful and so in the water distance senses our vision and a little bit hearing um old faction smelling and touch because in the water touch is a distant sense because you can feel the vibration so it's right so in um on air on land you know vision is a distant sense touch not so much but for Elephants maybe right um the vibrations vibrations um all faction definitely because of the concentration of you know the more concentrated something is the more likely it is to be close to you so animals developed senses they developed a head like a literal head so aoys doesn't even have a head really it's just a what's the purpose of a head that's a great question is it is it to have a jaw that's a great question so jaw so yes Jaws are a major um useful feature yeah I would say they're a major adaptation after there's a split between vertebrates and invertebrates so amphioxys is thought to be very very similar to the animal that's before that split but then after the development very quickly after the development of a head is the development of a jaw which is a big big thing and um and what goes along with that is the development of a brain it's weird is that just a coincidence that the thing the part of our body of the M mammal I think body that we eat with and like attack others with is also the thing that contains the uh all the majority of the brain type of well actually the brain goes with the development of a head and the development of of a visual system and an auditory system and an old factory system and so on so um your senses are developing and um and the other thing that's happening right is that animals are getting bigger yeah because their and also their Niche is getting bigger well this is the just sorry to take the tiny tangent on the niche thing is uh it seems like the niche is getting bigger but not just bigger like more complicated like shaped in weird ways so like predation seems to create like like the whole world becomes your oyster whatever but like you also start to carve out like the places in which you can operate the best yeah and in fact that's absolutely right and in fact some scientists think that theory of mind your ability to make inferences about the in inner life of of other creatures actually developed under the selection pressure of predation because it makes you a better Predator do you ever look at you just said you looked at at babies as these wiring creatures do you ever think of humans as just clever Predators like that there is under uh Underneath It All is this uh the nian will to power in all of its forms or are we now friendlier yeah so it's interesting I mean there there there are Zeitgeist in how humans think about themselves right and so if you look in the 20th century you can see that um the idea of an inner Beast that we just Predators we're just basically animals baseless animals violent animals that have to be contained by culture and by our prodigious neocortex um really took hold particularly after World War I and really um held sway for much of that Century um and then around at least in Western writing I would say you know we we're we're talking mainly about Western Western Scientific writing Western philosophical writing and and then you know late 90s maybe um you start to see books and articles about our social nature that we're social animals and we are social animals but what does that mean exactly and um um about it's us covering our different Natures in the space of ideas it looks like I think so I think so so um so you know do um humans um are can humans be violent yes can can humans be really helpful ye yes actually and humans are interesting creatures because you know know other animals can also be helpful to one another in fact there's a whole literature booming literature on how other animals um are um you know support one another they they regulate each other's nervous systems in in interesting ways and they will be helpful to one another right so for example there's a whole literature on rodents and how um they um they signal one another what is safe to eat and uh they um will um perform uh acts of generosity to their consp specifics that are related to them or or who they were raised with so if an animal was raised in a litter that is that they were raised in although not even at the same time they'll be more likely to help that animal so there's always some kind of physical relationship between animals um that predicts whether or not they'll help one another for humans humans you know we have ways of categorizing who's in our who's in our group and who isn't by non-physical ways right by even by just something abstract like an idea and we are much more likely to extend help to people in our own group whatever that group may be um at that moment whatever your whatever feature you're using to Define who's in your group and who isn't um we're more likely to help those people than even members of our own family at times so humans are much more flexible in their in the way that they help one another but also in the way that they harm one another so I don't um I don't I don't think I subscribe to um you know we are primarily this or we are primarily that I don't think have humans have Essences in that way really I apologize to take us in this direction for a brief moment but I've been really deep on Stalin and Hitler recently uh in terms of reading and is there something that you think about in terms of um the nature of evil from a neuroscience perspective is there some lessons that are sort of um hopeful about human civilization that uh we can find in our brain with regard to the Hitlers of the world do you do you think about the the nature of evil yeah I do I don't know that what I have to say is so useful from a I don't know that I can say as a neuroscientist Well here here's a study that you know what I so I I sort of have to take off my lab coat right and now I'm going to now conjecture as a human who just also who has Ain I but who also maybe has some knowledge about Neuroscience but I'm not speaking as a neuroscientist when I say this because I don't think neuroscientists know enough really to be able to say but I guess I the kinds of things I think about are um what so I have always thought even before I I knew anything about Neuroscience um I've always thought that um I don't think anybody could become Hitler but I think the majority of people can be can do are capable of doing very bad things um it's just the question is really how much encouragement does it take from the environment to get them to do something bad that's what I kind of when I look at the life of Hitler it seems like there's so many places where something could have intervened inter changed completely the person I mean there's like the caricature like the obvious places where he was an artist and if he wasn't rejected as an artist he was a reasonably good artist so that that could have changed but just his entire like where he went in Vienna and all these kinds of things like like little interactions could have changed and there's probably millions of other uh people who are uh capable who the environment may be able to mold in the same way it did this particular person to create this particular kind of charismatic leader in this particular moment of time absolutely and I guess the way I would the way that I would say it I I would agree 100% And I guess the way that I would say it is like this in the west we have a way of reasoning um about causation which focuses on single simple causes for things you know there's a there's an Essence to Hitler there's an Essence to his character he was born with that essence or it was forged very very early in his life and that explains the um the landscape of his the horrible landscape of his behavior but there's another way to think about it a way that actually is much more consistent with what we know about biology how biology Works um in the physical world and that is that most things are complex not as in wow this is really complex and hard hard but complex as in complexity that is more than the sum of their parts and that most phenomena have many many weak nonlinear interacting causes and so little things that we might not even be aware of can shift someone's developmental trajectory from this to that and that's enough to take it on a whole set of other paths that you know that and that these things are happening all the time so it's not random and it's not really it's not deterministic in the sense that like everything you do determines your outcome but it's a little more like um you know you're nudging someone from one set of possibilities to another set of possibilities and I but I think the the thing is the thing that I find optimistic is that the the other side of that coin is also true right so look at all the people who risk their lives to help people they didn't even know I mean I just watched Borat the new Borat movie and the thing that I came away with but you know the thing I came away with was look at how like generous people were in that because he's making there are a lot of people he makes fun of and that's fine but think about like those two guys those those the the Trump supporter guys Trump supporter guys those guys cool those kind those kindness in them right they took a complete stranger in a pandemic yeah into their house who does that like that's a really nice thing or there's one scene I mean I don't want to spoil it for people who haven't seen it but there's you know there's one scene where he goes in he dresses up as a Jew I I laugh myself sick at that scene seriously but um but he goes in and he and there are these two old Jewish ladies yeah what a bunch of sweethearts oh my gosh like really yeah I mean that was what I was struck by actually I mean there are other ones or or like the babysitter right I mean she was really kind and yeah so that's really what I was more struck by like you know sure there are other people who you know who do do very bad things or say say bad things or or whatever but you know or like there's one guy who's completely stoic like the guy at the um who's doing the like you know sending the messages I don't know if it's facts or whatever he's just completely stoic but he's doing his job actually you know like you can't you don't know what he was thinking inside his head you don't know what he was feeling but he was totally professional doing his job so I guess I just I I had a a bit of a different um you know view I guess and I so I also think that about people I think everybody is capable of kindness and um but for but you know it's the question is how much does it take and what are the circumstances so for a lot some people it's going to take a lot and for some people it only takes a little bit um but you know are we actually cultivating um an environment for the Next Generation that um provides opportunities for people to go in the direction of caring and kindness yeah or you know and I'm not I'm not saying that as like a you know poana is uh person um I you know I think there's a lot of room for competition and debate and and so on um but I don't see Hitler as an anomaly and I never have that that was even before I I learned anything about neuroscience and now I was would say knowing what we know about Developmental trajectories and life histories and how important that is um you know knowing what we know about um that the whole question of like nature versus nurture is a completely wrong question you know we have the kind of nature that requires nurture we have the kind of genes that allow infants to be born with unfinished brains where the brains their brains are wired across a 25-year period with wiring instructions from the world that is created for them and so I don't think Hitler is an anomaly um you know even if it's even if it's less probable that that would happen it's possible that it could happen again and it's not it's not like you know he's a bad seed I mean that doesn't I just want to say for like of course he's completely 100% responsible for his actions and all the bad things that happen so I'm not in any way this is not me saying but the environment is also responsible in part for creating the evil in in this world so like Hitler's and different versions of even more subtle more smaller scale versions of evil but I tend to believe that uh there's a much stronger uh I I don't like to talk about evolutionary advantages but it seems like it makes sense for love to be a more powerful uh emerging phenomena of our collective intelligence versus hate and evil and destruction because from a survival from a niche perspective it seems to be uh like for in my own life in my thinking about the intuition about the way humans work together to solve problems it seems that love is a very useful tool I definitely agree with you but I think the caveat here is that um you know humans the research suggests that humans are are capable of great act of kindness and great acts of generosity to people in their ingroup right and so we're also tribal yeah I mean that's the K that's the kitchy way to say it we're tribes we're tribal yeah so that's the kitchy way to say it what I would say is that you know there are a lot of features that you can use to describe yourself you don't have one identity you don't have one self you have many selves you have many identities um sometimes you're a man sometimes you're a scientist sometimes you're a you have a brother or a sister brother so sometimes you're a brother you know you you sometimes you're a friend sometimes you're human so you can keep zooming out yes living organism on Earth yes exactly that's exactly that's exactly right and so um there are there are some people who there is research which suggests that um there are some people who will tell you I think it's appropriate and better to help I should help my family more than I should help my neighbors and I should help my neighbors more than I should help the average stranger and I should help um you know the average stranger in my country more than I should help somebody outside my country and I should help humans more than I should help you know other animals and I right so there's a clear hierarchy of helping and there are other people who um you know they are their Niche is much more inclusive right and that they're humans first right or or creatures of the Earth first let's say um and I I don't think we know how flexible those attitudes are because I don't think the research really tells us that but in any case there are you know and there are beliefs people also have beliefs about there's this really interesting research in um really in anthropology um that looks at what are cultures particularly afraid of like what the people in a particular culture are organizing their social systems to prevent certain types of problems so what are the problems that they're worried about and and so there are some cultures that are much more hierarchical and some cultures that are you know much more egalitarian there are some cultures that you know in the debate of like getting along versus getting ahead there are some cultures that really prioritize the individual over the group and there are other cultures that really prioritize the group over the individual you know it's not like one of these is right and one of these is wrong it's that you know different combinations of these features are different solutions that humans have come up with for for living in groups which is a major adaptive advantage of our species um and it's not the case that one of these is better and one of these is worse although as a person of course I have opinions about that and as a person right I I can say I would very much prefer certain I have certain beliefs and I really want everyone in the world to live by those beliefs you know but as a scientist I know that it's not really the case that for the species any one of these is better than any other they're different solutions that work differentially well in particular you know ecological parts of the world but for individual humans there are definitely some systems that are better and some systems that are worse right but when when anthropologists or when neuroscientists or biologists are talking they they not usually talking about the lives of individual people they're talking about you know the species what's better for the species the survivability of the species and what's better for the survivability of the species is variation that we have lots of cultures with lots of different solutions because if the environment were to change drastically um some uh some of those Solutions will work better than others and you can see that happening with coid right so some people might be more susceptible to this this virus and others and so variation is very useful say Co was much much more destructive than it is and like I don't know 20% of the population was died uh you know that's it's good to have variability because then at least some percent Will Survive yeah I mean the the you know the way that I used to describe it was you know um using uh you know those movies like The War of the Worlds or or um Pacific Rim you know where like aliens come down from outer space and they you know want to kill humans and so all the humans band together as a species like and they all like all the you know little squabbling from countries and whatever all go you know goes away and everyone is just one big you know well that you know that doesn't happen I mean because coid is you know the vi a virus uh like Co like Co 19 is like a creature from outer space and that's not what you see happening what you do see happening it is true that some people I mean we could use this as an example of essentialism also so just to say like exposure to the virus does not mean that you will become infected with a disease so I mean in controlled studies one of which was actually a Corona virus not coid but an this was these are studies from 10 or so years ago you know only somewhere between 20 and 40% of people uh were developed respiratory illness when a virus was placed in their nose yeah um and so then there's a dose question all those well not in these studies actually so in these studies the dose was consistent across all people um and everything you know they were sequestered in hotel rooms and what they ate was you know um measured out by scientists and so on and so when you hold dose I mean the dose issue is a real issue in the real world but um in these studies that was controlled um and only somewhere between TW depending on the study between 20 and 40% of people became infected with a disease so exposure to a virus doesn't mean de facto that you will um develop an illness you will be a carrier and you will spread the virus to other people but you yourself may not uh you're immune system may be um in a state that um you you can make enough antibodies to um not uh not show symptoms not develop symptoms um and so um of course what this means is again is that you know like if I asked you do you think you know a virus is the cause of ill of of a common cold or you know most people if I ask this question I can tell you because I I I ask this question so do you think of virus is the cause of a cold most people would say yes I think it is and then I say yeah well only 20 to 40% of people develop respiratory illness in exposure to a virus so clearly it is a necessary cause but it's not a sufficient cause and there are other causes again so not simple single causes for things right multiple interacting influences so it it is true that individuals vary in their susceptibility to illness Upon a exposure but different cultures have different sets of norms and practices that allow that will slow or or speed the spread and that's the that's the point that I was actually trying to make here that um that you know when the environment changes that is there's a a mutation of a virus that is incredibly infectious some cultures will succumb People In some cultures will succumb faster because of the particular norms and practices that that they've developed in their culture versus other cultures now there could be some other you know thing that changes that where those other other cultures are you know would do better so very individualistic cultures like ours may do much better under other types of of selection pressures but for Co for things like Co you know my colleague Michelle Galant her research shows that she she looks at like loose cultures and tight cultures so cultures that have very very strict uh rules versus cultures that are much more individualistic and where personal freedoms are um more valued and she you know her research suggests that for pandemic uh circumstances tight cultures actually the people survive better just to linger a little bit longer we started this part of the conversation talking about you know did the humans evolve to think did the human brain evolve to think implying is there like a progress to the thing that's always improving that's right we never yeah and so the answer is no but let me sort of push back but so your intuition is very strong here not your intuition the way describe this but is it possible there's a direction to this Evolution like do you think of this Evolution as having a direction like it's like walking along a certain path towards something we you know uh what is it uh is it Elon uh musk said like uh this the Earth got bombarded with photons and then all of a sudden like a Tesla was launched into space or whatever Rockets started coming like is there a sense in which even though in the like within the system the evolution seems to be this mess of variation we're kind of trying to find our niches and so on but do you think they're ultimately when you zoom out there is a Direction that's strong that does tend towards um greater complexity and intelligence no so I mean and I and again what I would say is I'm really I'm really just echoing people who are much smarter than I am about this but see you're saying smarter I thought it doesn't there's no I thought there's no smarter no I didn't say there's no smarter I said there's no Direction okay so I think the thing to say or or what I understand to be the case is that um there's variation it's not unbounded variation and there are selectors there are there are there are pressures that we select and so not anything is possible because we live on a planet that has certain physical realities to it right um and but those physical realities are what constrain the possibilities um the physical realities of our genes and the physical realities of our corporeal bodies and the physical realities of um uh you know the of life on on this planet so what I would say is that um there's no Direction um but uh there is not it's not infinite possibility because we live on a particular planet that has particular statistical regularities in it and some things will never happen and so though all of those things are are interacting with um uh with our genes and so on and our you know the physical nature of our bodies to make some things more possible and some things less possible look I mean humans have very complex brains but birds have complex brains and so do uh you know um so do uh octopuses have very complex brains and all three sets of all three of those brains are are are somewhat different from one another you know uh bird Birds some birds have very complex brains some even have rudimentary language they have no cerebral cortex I mean they admittedly they have this is um now lesson two right they have is it lesson two or lesson one let me think no this is lesson one they have um uh they have the same neurons the same neurons that that in a human become the cerebral cortex birds have those neurons they just don't form themselves into a cerebral cortex but I mean crows for example are very sophisticated animals they can do a lot of the things that humans can do in fact all of the things that humans do that are very special that seem very special there's at least one other animal on the planet that can do those things too what's special about the human brain is that we put them all together so we learn from one another we don't have to experience everything ourselves we can watch another animal or another Human Experience something and we can learn from that well there are many other animals who can learn by copying yeah that we communicate with each other very very efficiently we have language but we're not the only animals who are efficiently efficient communicators there are lots of other animals who can efficiently communicate like bees for example um you know we cooperate really well with one another to do Grand things but there are other animals that cooperate too and so every Innovation that we have other animals have too what we have is we have all of those together interwoven in this very complex dance in a brain that is not unique exactly but that is you know it does have some features that make it use that make it particularly useful for us um to do all of these things uh you know to have all of these things intertwined so you know our brains are actually the last time we talked I I I made a mistake because I said um in my enthusiasm I said you know our brains are are not larger are relative to our bodies our brains are not larger um than um than other primates and that's actually not true actually our our brains relative to our body size is somewhat larger so yeah an ape who's not a human that's not a human um their brains are larger than their body sizes than say relative to like a smaller monkey and a human's brain is larger relative to its body size than a than a gorilla that's a good approximation of your um of whatever of of the bunch of stuff you that you can shove in there well what I was going to say is but our cerebral cortex is not larger than what you would expect for a brain of our of of of of its size so so relative to say an ape like a like a gorilla or a chimp or even a mammal like a dolphin or an elephant um you know our brains our our cerebral cortex is as large as you would expect it to be for a brain of our size so there's nothing special about our cerebral cortex and this is something I explain in the book where I I say okay you know like by analogy um if you walk into somebody's house and you see that they have a huge kitchen you know you might think well maybe you know maybe this is a place I really definitely want to eat dinner at because you know these people must be Gourmet Cooks but you don't know anything about what the size of their kitchen means unless you consider it in relation to the size of the rest of the house if it's a if it's a big kitchen in a really big house it's not telling you anything special right if it's a big kitchen in a small house then that might be a place that you want to eat for you want to stay for dinner because it's more likely that that kitchen is large for a special reason and so the cerebral cortex of a human brain isn't in and of itself special because of its size however there are some genetic changes that have happened in the human brain as it's grown with to whatever size is you know typical for for the whole brain size right there are some changes that do give the human brain slightly more of some capacities they're not special but there's just they just you know we can do some things much better than other animals and you know correspondingly other animals can do some things much better than we can we can't grow back limbs we can't lift 50 times our own body weight well I mean maybe you can but I can't live 50 times body ants with that regard are very impressive and then you're saying with the with the frontal cortex like that's the size is not always the right uh measure of uh capability I guess so size isn't everything size isn't everything that's a quot you know people like it when I disagree so let me disagree with with you uh on something or just like play Devil's adoc a little bit so you've uh painted a really nice picture that Evolution doesn't have a Direction but is it possible if we just ran Earth over and over again like this video game that the final result will be the same so in the sense that we're eventually there'll be an AGI type HAL 9000 type system that just like flies and colonizes nearby by uh earthlike planets and it's always will be the same and and the different organisms and the different evolution of the brain uh like it it doesn't feel like it has like a Direction but given the constraints of Earth and whatever this imperative whatever the hell is running this universe like it seems like it's running towards something is it possible that it will always be the same thereby it will be a Direction yeah I think you know as you know better than anyone else that that answer to that question is of course there's some probability that that could happen right it's not a yes or no answer it's what's the probability that that would happen and there's a a whole um distribution of possibilities so maybe we end up what's the probability we end up with exactly the same uh complement of creatures um including us what's the likelihood that we end up with you know creatures that are similar to humans that are but you know similar in in certain ways let's say but not exactly humans or you know all the way to a completely different um distribution of of creatures what's your intuition like if you were to bet money what does that distribution look like if we ran Earth over and over and over again I would say given the um you're now asking me questions that this is not science this this is not science so but I would say okay well what's the probability that um it's going to be a carbon life form Pro probably high yeah but that's because I don't know anything about Alternatives yeah you know I don't I'm not I'm not really well versed in that um what's the probability that you know so what's the probability that the animals will begin in the ocean and crawl out onto Land versus the other way versus I would say probably high I don't know but you know but do I think what's the likelihood that we would end up with exactly the same or very similar I think it's low actually I I wouldn't say it's low but I I would say it's not it's not 100% and I'm not even sure it's 50% you know I would say I I don't think that we're here by accident because I think like I said there are constraints like there are some physical constraints about Earth now of course if you were a cosmologist you could say well the the fact that the Earth is if you were to do the big bang over again and keep doing it over and over and over again would you still get the same solar systems would you still get the same planets would you know would you still get the same galaxies the same solar systems the same planets you know I don't know but my guess is probably not um because there are random things that happen that can again send things in one direct you know make one set of trajectories possible and another set impossible so um but I I guess my my my if I were going to bet bet something money or something valuable I would probably say it's not zero and it's not 100% and it's probably not even 50% so there's some probability but it will be similar that would be similar but I don't think I just think there are too many degrees of freedom there are too many degrees of freedom I I mean one of the real tensions in writing this book is to on the one hand there's some truth in saying that humans are not special we are just you know we're not special in the animal kingdom all animals are um well adapted if they're survived they're well adapted to their Niche it does happen to be the case that our Niche is large for any individual human your Niche is whatever it is but for the species right we live almost everywhere not everywhere but almost everywhere on the planet but not in the ocean and actually other animals like bacteria for example H have us beat miles you know hands down right so we're by any by any definition we're not special we're just you know adapted to our environment but bacteria don't have a podcast they're not exactly exactly and so that's the tension right so on the one hand you know we're not special animals we're just you know you know particularly well adapted to our Niche on the other hand our Niche is huge and we you know we don't just adapt to our environment we add to our environment we make stuff up give it a name and then it becomes real and so no other animal can do that and so I think the the thing the way to think about it from my perspective or the way I made sense of it is to say you can look at any individual Single Character istic that a human has that seems remarkable and you can find that in some other animal mhm what you can't find in any other animal is all of those characteristics together in a brain that is souped up in particular ways like ours is and if you combine these things multiple interacting causes right not one not one Essence like your cortex your big neocortex but um which isn't really that big I mean it's just big for it this for your big brain uh for the size of your big brain it's that it's the size it should be um if you add all those things together and they interact with each other that produces some pretty remarkable results M and if you're aware of that then you can start asking different kinds of questions about what means to be human and what kind of a human you want to be and what kind of a a world do you want to curate for the next generation of humans so you I think that's the goal anyways right is just to just to have a glimpse of instead of thinking about things in in a simple linear way just have a glimpse of the some of the things that matter that seemed that evidence suggests matters um to um the kind of brain in the kind of bodies that we have um once you know that you can you can work with it a little bit you're right words have power over your biology right now I can text the words I love you from the United States to my close friend in Belgium and even though she cannot hear my voice or see my face I will change her heart rate her breathing and her metabolism by the way beautifully written or someone could text something and be uous to you like is your door locked and odds are that it would affect your nervous system in an unpleasant way so I mean there's a lot of stuff to talk about here but just one way to ask is um why do you think words have so much power over our brain well I think we just have to look at the anatomy of the brain to answer that question so um if you look at the part parts of the brain the whole the the the systems that are important for processing language you can see that some of these regions are also important for controlling your major organ systems and your like your autonomic nervous system that controls your cardiovascular system your respiratory system and so on that you know these regions control your uh endocrine system your immune system and so on so and you can actually see this in other animals too so in birds for example the neurons that are responsible for bird song also control the systems of a bird's body and the reason why I bring that up is that the there's some scientists think that the anatomy um of a of a bird's brain that control bird song or homologous or structurally have a similar origin to the human system for a language so the parts of the brain that are important for processing language are not unique in U and specialized for language they do many things and one of the things they do is um control your major organ systems do you think we can fall in love have arguments about this all the time uh do you think we can fall in love based on words alone well I think people have been doing it for centuries I mean they it used to be the case of people wrote letters to each other yeah um with you know and then uh that was how they communicated and I guess that's how you and Dan got exact exactly exactly exactly yeah exactly so is the answer a clear yes there because I get a lot of push back from people often that you need you need the touch and the smell and uh you know the bodily stuff I think the touch and the smell and the bodily stuff helps okay but I don't think it's necessary do you think you can have a lifelong monogamous relationship ship with an AI system that only communicates with you on text romantic relationship well I suppose that's an empirical question that hasn't been answered yet but so I I guess what I would say is um I don't think I could could any human could the average human could you know so so um if I if I um I I even I want to even I want to even modify that and say I'm thinking now of um Tom Hanks um and um the movie um cway yeah you know with Wilson yeah I think if if that was if you had to make that work if you had to make that work well the volleyball yeah if you had to make it work could you you could you prediction and simulation right so if you had to make it work could you make it work using simulation and you know your past experience could you make it work could you make it work you as a human could you could you like could you have a could you have a relationship literally with an inanimate object and have it sustain you in the way uh that another human could yeah um your life would probably be shorter because you wouldn't actually derive the body budgeting benefits from right so um we've talked about uh you know how um your brain its most important job is to control your body and you can describe that as your brain running a budget for your body yes and um there are metaphorical you know deposits and withdrawals into your body budget and you also make deposits and withdrawals in other people's body budgets figuratively speaking so you wouldn't have that particular benefit um uh so your life would probably be shorter but I think it would be harder for some people than for other people yeah I T my intuition is that you can have a deep fulfilling relationship with a volleyball I think I think a lot of the the environments that set up I think that's a really good example like the constraints of your particular environment Define the like I I believe like scarcity is a good Catalyst for deep meaningful connection with other humans and with in animal objects so the less you have the more fulfilling those relationships are and I would say a relationship with a volleyball the sex is not great but uh everything else I feel like it could be a very fulfilling relationship which I don't know from an engineering perspective what to do with that just like you said it is an empirical question but but there are places to learn about that right so for example think about children and their blankets right so there there's something tactile and there's something old factory and it's very comforting I mean even for even for non-human little animals right like puppies and so I don't know about cats but um but cats are cold-hearted they're there there's no there's nothing going on there I don't know there are some cats that are very doglike I mean really so some cats identify as dogs yes I think that's true yeah they're they're um species fluid so you also right when it comes to human Minds variation is the norm and what we call quote human nature is really many human Natures again many questions I can ask here but maybe an interesting one to ask is um I often hear you know we often hear this idea of be yourself is this possible to be yourself is it a good idea to strive to be self is it does that even have any meaning it's a very Western question first of all because which self are you talking about you don't have one self there is no self that's an essence of you you have multiple selves actually there is research on this um you know to quote um the great social psychologist Hazel Marcus you're never you cannot be a self by yourself you you know you and so different contexts pull for or or Draw on different features of your of who you are or what you're what you believe what you feel what your actions are um a different context you know will put certain things make more some features be more in the foreground and and some in the background it's it takes us back right to our discussion earlier about um Stalin and Hiller and so on the thing that I would caution in addition to the fact that there is no single self you know that you have multiple selves who you can be um and you can certainly choose the situations that you put yourself in to some extent not everybody has complete choice but everybody has a little bit of choice and I think I said this to you before that one of the pieces of advice that we gave Sophia you know when she went our daughter when she was going off to college was um try to spend time around people choose relationships that allow you to be your best self we should have said your best selves but um this you know the pool of selves given the environment uh yeah but I I the one thing I do want to say is that um the risk of saying be yourself just be yourself is that um that can be used as an excuse well this is just the way that I am I'm just like this and um that I I think should be tremendously resist isted so that's one that's the that's for the excuse side but you know I'm really self-critical often I'm full of doubt and people often tell me just don't worry about it just be yourself man and it's the thing is uh it almost it it's not from an engineering perspective does not seem like actionable advice because uh I guess constantly worrying about who what are the right words to say to express how I'm feeling is I guess my self there's there's a kind of line I guess that this might be a western idea but something that feels genuine and something that feels not genuine and I'm not sure what that means cuz I would like to be fully genuine and fully open but I'm also aware like this morning I was like very like silly and giddy like this is just being funny and relaxed and light like there's nothing that could um bother me in the world I was just smiling and happy and I remember last night was just feeling like very grumpy like uh like stuff was bothering me like certain things were bothering me and like th what are those are those are different selves like what who am I in that and what do I do because if you know if we take Twitter's an example if I actually send a tweet last night and a tweet this morning it's going to be very two different people a tweeting that and I don't know what to do with that because one does seem to be more me than the other but that's maybe because there's a Nar the story that I'm trying this something I'm striving to be like the ultimate human that I might become I have maybe a vision of that and I'm trying to become that but it it does seem like there's a lot of different Minds in there and they're all like like having a discussion and a battle for who's going to win I suppose you could think of it that way but there's another way to think of it I think and that is that um maybe the more Buddhist way to think of it right or more contemplative way to think about it which is not that you have multiple personalities inside your head but you have your brain has this um amazing capacity it it has a a population of experiences that you've had that it can regenerate reconstitute and it can even take bits and pieces of those experiences and combine them into something new um and it's often doing this to predict what's going to happen next and to plan your actions but it's also happening this also happens just um that's what mind wandering is or just internal thought and and so on that's it's the same mechanism really and so a lot of times we hear the saying you know just think if you think differently you'll feel differently but your brain is having a conversation continually with your body and your body your brain's you know trying to control your body well trying your brain is controlling your body your body is sending information back to the brain and impart the information that your body sends back to your brain just like the information coming from the world initiates the next volley of predictions or simulations so in some ways you could also say the way that you feel your I think we talked before about affective feeling or mood coming from the sensations of body budgeting you know um influences what you think and um as much as so feelings influence thought as much as thought influence feeling and maybe more but just the the whole thing doesn't seem stable well it's a dynamic system Mr engineer yeah right it's a dynamic it's a dynamical system right nonlinear dynamical system in a re and I think that's I'm actually writing a paper with a bunch of Engineers about the about this actually but um I I mean other people have talked about the brain as a dynamical system before but you know the real tricky bit is trying to figure out how do you get mental features out of that system like it's one thing to figure out how you get a motor movement out of that system it's another thing to figure out how you get a mental feature like a feeling of being loved or a feeling of being worthwhile or a feeling of you know just basically feeling like how do you get a feeling a mental Fe a mental features out of out of that system um so I would what I would say is that you aren't the the Buddhist thing to say is that you're not one person and you're not many people you are um you are the sum of your experiences and who you are in any given moment meaning what your actions will be is influenced by the state of your body and the state of the world that you've put yourself in and you can change either of those things one is a little easier to change than the other right you can change your environment by literally getting up and moving or you can change by paying attention to some things differently and letting other some features um come to the FL and other features be backgrounded like I'm looking around your place oh no and I see this is not something you should do no I'm not but I'm going to say one thing yeah no green plants no green plants cuz green plants mean a home and I want this to be temporary fair fair but what's what's what goes to your mind when you see no green plants no I'm just making the point that but um what if you like again you know not everybody has control over their environment some people don't have control over the noise or the temperature or you know any of those things but everybody is a little bit of control and you can place things in your environment photographs yes plants anything that's meaningful to you and use it as a shift of environment when you need it yes you can also do things to change the conditions of your body when you exercise every day you're making an investment in your body actually you're making an investment in your brain too it makes you even though it's unpleasant and you know there's a cost to it if you replenish if you in invest and you make up that um you make a deposit and you make up that um what you've spent you're basically making an investment in making it easier for your brain to control your body in the future so you can make sure you're hydrated drink water you don't have to BU drink bottled water you can drink water from the tap this is in most places maybe not you know maybe not everywhere but uh but most places in the developed World um you can try to get enough sleep not everybody has that luxury but everybody can do something to make their you know body budgets a little more solvent and that will also make it more likely that certain thoughts will emerge from that prediction uh machine that's the control you do have is uh yeah being able to control the environment that's really well put uh on the I don't think we've talked about this so let's go to the biggest unanswerable questions of Consciousness what is you just rolled your eyes I did that was my yeah so what is consciousness from a neuroscience perspective I know you I mean uh I made notes you know because you gave me some questions in advance and I made notes for every single well except that one yeah well that one I had what the and then I took it out um so is there something interesting because you're so pragmatic is there something interesting to say about intuition building about Consciousness or is this something that we're just totally clueless about that this is uh let's focus on the the body the brain listens to the body the body speaks to the brain and like let's just figure this piece out and then Consciousness will probably emerge somehow after that no I think you know well first of all it'll just say up front um I am not a philosopher of Consciousness and I'm not a neuroscientist who focuses on Consciousness I mean in some sense I do study it because I study affect in mood and that's that is the um uh you know to use the phrase that is the the hard question um of Consciousness how is it that your brain is modeling your body your brain is modeling the sensory conditions of your body it's um and it's being updated that model is being updated by the sense data that's coming from your body and it's happening continuously your whole life and you don't feel those Sensations directly you what you feel is a general sense of pleasantness or pleasantness Comfort discomfort feeling worked up feeling calm so we call that affect you know most people call it mood so how is it that your brain gives you this very low dimensional feeling of mood or affect when it's presumably receiving a very high-dimensional array of sense data and the model that the brain is running of the body has to be high dimensional because there's a lot going on in there right you're not aware but as you're sitting there there quietly as your listeners or our our as our viewers are sitting um they might be working out running now or as many of them right to me they're laying in bed smoking weed with their eyes closed and that's fair so maybe we should say that bit again then so if so some people may be working out some people may be uh relaxing but you know even if you're sitting very still while you're watching this or listening to this there's a whole drama going on inside your body that you're largely unaware of yet your brain makes you aware or gives you a status report in a sense by virtue of these mental features of feeling Pleasant feeling unpleasant feeling comfortable feeling uncomfortable feeling energetic feeling tired and so on and so how the hell is it doing that that is the basic question of of Consciousness and like the status reports seem to be in the the way we experience them seem to be quite simple like it doesn't feel like there's a lot of data yeah know that there isn't so when you feel when you feel um discomfort when you're feeling basically like you feel like what does that tell you like what are you supposed to do next what caused it I mean the thing is not one thing caused it right it's multiple factors probably influencing your physical state your body very high dimensional yeah very high dimensional um and that and the there are different temporal scales of influence right so um it you know the state of your gut is not just influenced by what you ate five minutes ago it's also what you ate a day ago and two days ago and and so on so um so I think the you know when I'm I'm not trying to weasle out of the question I just think it's a it's the hardest question actually do you think we'll ever understand it um as scientists I think that we will understand it as well as we understand other things like um the birth of the universe or the you know the nature of the of the Universe I guess I I would say so I do I think we get to that level of an explanation I do actually but I think that we have to start asking somewhat different questions and approaching the science somewhat differently than we have in the past I mean it's also possible that Consciousness is much more difficult to understand than the nature of the universe it is but I I wasn't necessarily saying that it was a question that was of equivalent complexity I was saying that I do think that we could get to some I I am optimistic that I I would not I would be very willing to invest my the time my time on this Earth as a scientist in trying to answer that question if I could do it the way that I want to do it um not the way that it's currently being done so like rigorously I don't want to say unrig usly I just want to say that there are certain set of assumptions that you know scientists have what I would call ontological commitments they're commitments about the way the world is or the way that nature is and they these commitments lead scientists sometimes blindly without they don't scientists sometimes sometimes scientists are aware of these commitments but sometimes they're not and these commitments onth less influence how scientists ask questions how what they measure how they measure and I I just have very different views than a lot of my colleagues about the ways to approach this not everybody but um but the way that I would approach it would be different and it would cost more and it would take longer it doesn't fit very well into the current incentive structure of Science and so do I think that doing science the way science is currently done with the budget that it currently has and the incentive structure that it currently has will we have an answer no I think absolutely not good luck is what I would say people love book recommendations let me ask what three books oh you can't just like you can't just give me three I mean like really three what uh 7 and 1/2 books you can recommend so you're also the author of 7 and A2 lessons about the brain you're uh author of how emotions are made okay so definitely those are the top two recommendations of all two greatest books of all time other than that are there books that uh technical fiction philosophical that you've enjoyed or you might recommend to others Yes actually you know every PhD student when they um when they graduate uate with their PHD I give them a set like a little Library like a set of books you know some of which they've already read some of which I want them to read or um but um I think non-fiction books I would read the things I would recommend are the triple helix um by uh Richard lanon it's a little book published um in 2000 which is um I think a really good introduction to complexity and um population thinking as opposed to essentialism so this idea essentialism is this idea that you know there's an Essence to each person whether it's a soul or your genes or what have you as opposed to this idea that you we have the kind of nature that requires a nurture we are a we are you are the product of a complex dance between um an environment between a set of genes and an environment ment um that turn those genes on and off to produce your brain and your body and really who you are at any given moment it's good title for that triple helix so playing on the double helix where it's just the biology it's bigger than the biology exactly um It's a Wonderful book I've read it probably six or seven times throughout the year he has another book too which is it's more I think scientists would find it I don't know I've loved it it's called biology as ideology and it is all about I wouldn't call it one of the best books of all time but I I love the book because it really does point out you know that SC science as it's currently practiced I mean the book was written in 1991 but it actually I think still holds that scientist science as currently practice has a set of ontological commitments which are somewhat problematic so the assumptions are limiting yeah in ways that you it's you know it's like you're a fish in water and you don't like okay so yeah so here Foster walls stuff but but you know but here's a here's a really cool thing I just learned recently is it okay just to to to go off on this tangent for a minute yeah yeah that's called tangent great okay um I was just going to say that I just learned recently that we don't have water receptors on our skin so how do you know when you're sweating how do you know when when a raindrop when you know when it's going to rain and you know like a raindrop hits your skin and you can feel that little drop of wetness how is it that you feel that drop of wetness when we don't have water receptors in our skin and I was when I my mind is blown already yeah that was my reaction too right I was like of course we don't because we evolved in the water yeah like why would we need you know it just it was just this like you know you have these moments where you're like of course there's like a yeah so you'll never see rain the same way again so the answer is it's a it's a it's a combination of um temperature and touch yeah but it's a complex sense that's only computed in your brain there's no receptor for it anyways yeah that's why like snow versus cold rain versus warm rain all feel different because you're you're trying to infer stuff from the temperature and the size of the droplet it's fascinating yeah your brain is a prediction machine it's using lots and lots of information combining it you know anyway so but um so biology's ideology is I wouldn't say it's one of the greatest books of all time but it is a it is a really useful book there's a book by um if you're interested in Psychology or the mind at all there's a wonderful book A little it's a it's a fairly fairly small book called naming the Mind by Kurt danziger who's a historian of psychology everybody in my lab reads both of these books so what was the book it's about the origin of the where do where did we get the theory of mind that we had have that uh the human mind is populated by thoughts and feelings and um perceptions and where did those categories come from because they don't exist in all cultures Al this isn't that's a cultural construct the idea that you have thoughts and feelings and they're very distinct is definitely a cultural construct it's another mind-blowing thing just like the rain um so Kurt danzinger is a the opening chapter in that book is absolutely mind-blowing I love it I love it I just think it's fantastic um and I would say the there are many many popular science books that I could recommend that I think are extremely well written in their own way you know before I maybe I said this to you but before I undertook writing how motions are made um I read I don't know somewhere on the order of 50 or 60 uh popular science books to try to figure out how to write a popular science book because while there are many books about writing Stephen King has a great book writing on writing and um you know where he gives tips um interlaced with his own personal history um that was where I learned you write for a specific person you have a specific person in mind and that's for me that person is my is down that's fasc I mean that's a whole another conversation to have like which popular science books like what you learn from that uh search because there there's uh I have some for me some popular science books like I just roll my eyes like this is too um it's like same with TED talks like some of them go too much into the flowery and don't I don't I would say don't give enough respect to the intelligence of the reader uh and but that's this is my own bias very specific I I completely agree with you and in fact I have a colleague his name is um van Yang who you know he um produced um a cinematic lecture of how emotions are made that we wrote together with Joseph fredman no relation yes um well we're all related well I mean you and I are probably you know have some yeah yeah um but um I remember it's the memories are in there somewhere yeah it's from many many many generations ago um well half my family is Russian so from the good half the good half right um but you know he one his goal actually is to produce [Music] um you know videos and lectures that are beautiful and educational and that don't um don't dumb the material down um and he's really remarkable at it actually I mean just uh but again you know that's that that requires a bit of a paradigm shift we could have a whole conversation about the split between entertainment and education in this country and why it is the way it is but that's a that's another conversation to be continued but I would say the if I were to pick one book that I think is a really good example of good science writing it would be the beak of the finch which is one of it won a a pullit Sur prise a number of years ago and I'm not I'm the I'm not remembering the author's name I'm blanking um but the I'm guessing is it uh is it focusing on birds and the evolution of birds actually there's also the evolution of beauty which is yeah which is also a great book but the no the beak of the finch is um it's a it it has two story lines that are interwoven one is about Darwin and Darwin's um Explorations in the Galapagos Island and then modern-day researchers from Princeton who have a research program in the Galapagos looking at Darwin's finches mhm and um it's just a really first of all there's topnotch science in there and really science like you know evolutionary biology there a lot of people don't know and it's told really really well it sounds like there also there's a narrative in there there it's like storytelling too yeah I think all good popular science books are are storytelling you know but storytelling grounded constrained by you know the evidence and then I just want to say that there are for fiction I'm a really big fan of love stories just to return us to the um the topic that we began with and so my some of my favorite uh love stories are major pedigree Last Stand by Helen Simonson it's a it's a love story about people who you wouldn't expect to fall in love and all the people around them who have to overcome their prejudices and and um I love this book what do you like like what makes a good love story there isn't one thing you know there are many different things that make a good love story but I think in this case um you can feel you you can feel the journey you can feel the journey that these characters are on and all the people around them are on this journey too basically to come to grips with this really Unexpected Love really profound love that develops between these two characters who are very unlikely to have fallen in love but they do and it's just it's very gentle another book like that is um the um the storyed life of AJ FY um which is also a love story but in this case it's a love story between um a little girl and her adopted dad and the dad is this like real kogy you know um guy uh but of course there's a story there and um it's just a beautiful love story and but it also it's like everybody in this community falls in love with him because he falls in love with her and he you know she just gets left at his store his bookstore he has this failing bookstore and he he discovers that you know he feels like inexplicably this need to take care of this little baby and um this whole life emerges out of that one decision which is really beautiful actually um very poignant do you think the greatest stories have a happy ending or a heartbreak at the end that's such a Russian question it's like it's like Russian tragedies you know so I would say the answer to that for me there has to be heartbreak yeah I really don't like heartbreak I don't like heartbreak I want there to be a happy ending or at least a hopeful ending but the but you know like Dr shivago like or The English Patient oh my goodness like why oh it's just yeah no well I don't think there's a better way to end it on a happy note like this uh Lisa like I said I'm a huge fan of yours thank you for wasting yet more time with me talking again U people should definitely get your book and uh maybe one day I can't wait to talk to your husband as well well right back at you [Laughter] Lexi thanks for listening to this conversation with Lisa Feldman Barrett and thank you to our sponsors athletic greens the all-in-one drink that I start every day with to cover all my nutritional bases eight sleep a mattress that cools itself and gives me yet another reason to enjoy sleep master class online courses that I enjoy from some of the most amazing humans in history and better help online therapy with a licensed professional please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with fast stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Freedman and now let me leave you some words from sunzoo and the Art of War there are not more than five musical notes yet the combination of these five give rise to more Melodies that can ever be heard there are not more than five primary colors yet in combination they produce more Hues than can ever be seen there are not more than five Cardinal tap tastes and yet combinations of them yield more flavors than can ever be tasted thank you for listening and hope to see you next time |
Andrew Huberman: Neuroscience of Optimal Performance | Lex Fridman Podcast #139 | the following is a conversation with Andrew huberman a neuroscientist at Stanford working to understand how the brain works how it can change their experience and how to repair brain circuits damaged by injury or disease he has a great Instagram account at huberman lab where he teaches the world about the brain and the human mind also he's a friend and an inspiration in that he shows that you can be humble giving and still succeed in the Science World quick mention of me sponsor followed by some thoughts related to the episode a sleep a mattress that cools itself and gives me yet another reason to enjoy sleep sem Rush the most advanced SEO optimization tool I've ever come across and cash app the app I use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that I heard from from a lot of people about the previous conversation I had with euron Brooke about objectivism some people loved it some people hated it I misspoke in some parts was more critical on occasion than I meant to be didn't push on certain points that I should have was undereducated or completely unaware about some major things that happened in the past or major ideas out there I bring all that up to say that if we are to have difficult conversations we have to give each other space to make mistakes to learn to grow taking one or two statements from our three-hour podcast and suggesting that they encapsulate who I am I was or ever will be is a standard that we can't hold each other to I don't think anyone could live up to that kind of standard at least I know I can't the conversation with Yan is mild relative to some conversations that I will likely have in the coming year please continue to challenge me but please try to do so with love and with patience I promise to work my ass off to improve whether I'm successful at that or not we shall see if you enjoy this thing subscribe on YouTube review it with fast stars on Apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex fredman and now here's my conversation with Andrew huberman you've mentioned that in your lab at Stanford you induced stress by putting people into uh virtual reality and having them go through one of a set of experiences I think you mentioned this on Rogan or with Whitney that scare them so just uh on a practical psychological level and maybe on a philosophical level what are people afraid of what are the fears what are these fear experiences that you find to be effective yeah so it depends on the person obviously um and we should probably define fear right because you can without going too far down the rabbit hole of of defining these things um you know you can't really have fear without stress but you could have stress without fear and you can't really have trauma without fear and stress but you could have fear and stress without trauma so you know we can start playing the word game and that actually is one of the motivations for even having a laboratory that studies these things is that we really need better physiological neuroscientific and operational definitions of what these things are I mean the the field of understanding um emotions and states which is mainly what I'm interested in is very complicated but we can um we can do away with a lot of complicated debate and say in our laboratory what we're looking for to assign it a value of fear is a big inflection in autonomic arousal so increases in heart rate increases in breathing um persp ation pupil dilation all the Hallmark signature features of the stress response uh and in some cases we have the benefit of getting neurosurgery patients where we've got electrodes in their amydala and their insula and the orbital frontal cortex um down beneath skull so these are chronically implanted electrodes we're getting multiunit signals and we can start seeing some Central features of uh meaning within the brain and what's interesting is that as trivial as it might seem in listening to it almost everybody responds to Heights and falling from a high virtual place with a very strong stress if not fear response and that's because the visual vestibular apparati right the the optic flow and how it links to the you know balanc semicircular canals of the inter all this technical stuff but really all of that pulls all your phys ology the the feeling that your stomach is dropping the feeling that you're suddenly you're sweating even though you're not afraid of falling off this virtual platform but you feel as if you're following falling excuse me because of the optic flow that one is universal so we've got a dive with great white sharks experience where you actually exit the cage we went out and did this in the real world and brought back 360 video that's built out pretty oh so this is exual 360 video 360 video and this was important to us right so when we decided to set up this platform a lot of the motivation was that a lot of the studies of of these things in Laboratories I don't want to call them lame because I want to be respectful of the the people that did this stuff before but they'd study fear by you know showing subjects a picture of a bloody arm or a snake or something like that or and it just unless you have a snake phobia it just wasn't creating a real enough experience so we need to do something where people aren't going to get injured but where we can tap into the physiology and that thing of presence of people momentarily not the whole time but moment arily forgetting they're in a laboratory and so Heights will always do it and I if people want to challenge me on this I I like to point to that movie free solo which was wild because you know it's incredible movie but I think a lot of its popularity can be explained by a puzzle which is you knew he was going to live when you walked in the theater or you watched it on at home you knew before that he he survived and yet it was still scary that people somehow were able to put themselves in into that experience or into Alex's experience enough that they they were concerned or worried or afraid at some level so Heights always does it if we get people who have generalized anxiety these are people who walk wake up and move through life at a generally higher state of autonomic arousal and anxiety then we can tip them a little bit more easily with things that don't necessarily get everyone afraid things like um claustrophobia public speaking that's going to vary from person to person um and then if you're afraid of sharks like my sister for instance is afraid of sharks she won't even come to my laboratory because there there's a thing about sharks in it that's how terrified some people are of these specific stimuli but Heights gets them every time yeah and I'm terrified of heights it it's you know when we have you step off a platform virtual platform and it's a flat floor in my lab but we you're up there well you actually allow them the possibility in the virtual world world to actually take the leap of faith yeah maybe I should describe a little bit of the experiment so um without giving away too much in case someone wants to be a subject in one of these uh experiments we have them playing a cognitive game it's a simple lights out kind of game where you're you know pointing a cursor and turning out lights on a grid but it gets increasingly complex and it speeds up on them and um you know there's a failure point for everybody where they just can't make the motor commands fast enough and then we surprise people essentially by placing them virtu all of a sudden they're SS they're on a narrow platform between two buildings yeah and then we encourage them or we cue them with a with by talking to them through a microphone to continue across that platform to continue the game and you know some people they they just won't they actually will hold get down on the ground and hold on to a virtual beam that doesn't even exist on a flat floor and so what this really tells us is the power of the brain to enter these virtual States as if they were real and we really think that anchoring the visual and the vestibular the balance components of the nervous system are what bring people into that presence so quickly there's also the potential and we haven't done this yet to bring in 360 sound so the reason we did 360 video is when we started all this back in 2016 a lot of the VR was pretty lame frankly it was CGI it just wasn't real enough but with 360 video we knew that we could get people into this presence where they think th in a real experience more quickly and our friend Michael meller who I was introduced to because of the project I reached out to some friends Michael Muller is a very famous um portrait photographer in Hollywood but he Dives with great white sharks and he leaves the cage and so we worked with him to build a 360 video apparatus that we could swim under water with went out to gual Lupe Island Mexico and actually got the experience it was a lot of fun it was there were some interesting moments out there of danger but it came back with that video and built that for the Sharks and then we realize we need to do this for everything we need to do it for Heights we need to do it for public speaking for claustrophobia and what what's missing still is 360 sound where 360 sound would be U for instance um if I were to turn around and there was a like a giant attack dog there the moment I would turn around and see it the dog would growl but if I turn back toward you right then it would it would be silent so and that brings a very real element to one's own be Behavior where you don't know what's going to happen if you turn a corner whereas if there's a dog growling behind me and I'm and I turn around and then I turn back to you and it's still growling yeah that might seem like more of an impending threat but um and sustained threat but actually it's when you start linking your own body movements to the experience so when it's closed loop where my movements and choices are starting to influence things and they're getting scarier and scarier that's when you can really Drive people's nervous system down these Paths of high high states of stress and fear now we don't want to traumatize people obviously but uh we also we also study a number of tools to that allow them to calm themselves in these environments so the short answer is Heights heights yeah well from a psychology and from a neuroscience perspective this whole construction that you've developed is fascinating we did this a little bit with autonomous vehicles so to try to understand the decision making process of a pedestrian when they cross the road and trying to create an experience of a car you know that can run you over so there's a danger of there I was so surprised how real that whole world was and the graphics that we built wasn't ultra realistic or anything but I was still afraid of being hit by a car but everybody we tested were really afraid of being hit by that car even though it was all a simulation it was all simulation it was uh it was kind of boxy actually I mean it wasn't like ultra realistic simulation and it's fascinating looms and Heights so any kind of depth we're just programmed to um to not necessarily recoil but to be cautious about that edge and that depth and then looms things coming at us that are getting larger there are looming sensing neurons even in the retina at a very very early stage of visual processing and um incidentally uh the way Muller and you know folks learned how to not get eaten by great white sharks when you're swimming outside the cage is as they start lumbering in you swim toward them and they get very confused when you loom on them because clearly you're smaller clearly they could eat you if they wanted to but there's something about forward movement toward uh any creature that that creature questions whether or not it would be a good idea to generate forward movement toward you and so that's actually the survival tool of these cage exit white shark divers are you playing around with like one of the critical things for the autonomous vehicle research is you couldn't do 360 video because the there's a game theoretic there's an interactive element that's really necessary so maybe people realize this maybe they don't but 360 video you obviously well it's actually not that obvious to people but you can't change the reality that you're watching that's right so uh but you find that that's like is there something fundamental about fear and stress that the intera development is essential for or do you find you can you can arous people with just the video great question um it works best to use mixed reality so we have a snake stimulus I personally don't like snakes at all I don't mind spiders we also have a spider stimulus but like snakes I just don't like them they's something about the the slithering and the it just it creates a visceral response for me um some people not so much and they have lower levels of stress and fear in there but one way that we can get them to feel more of that is to use mixed reality where we have a an actual physical bat and they have to stomp out the snake as opposed to just um walk to a little safe Corner which then makes the snake disappear that tends to be not as stressful as if they have a physical weapon and so you got people in there you know banging on the floor against this thing and there's something about engaging that makes it more of a more of a threat now I should also mention we we always get the sub report from the subject of what they experience because I we never want to project our own ideas about what they were feeling but that's a beauty of working with humans is you can ask them how they feel exct and humans aren't great at explaining how they feel um but it's a lot easier to understand what they're saying than a mouse or a macak monkey is saying um so it's the best we can do is language plus these physiological and neurophysiological signals is there something you've learned about yourself about your deepest fears like you said snakes is there something that like if I were to torture you I'm so I'm Russian so you know I always kind of think how can I murder this people that this person that enter the room but also how how can I torture you to get some information out of you what what would I go with h it's interesting you should say that I never considered myself claustrophobic mhm but um cuz I don't mind small environments provided they're well ventilated but I uh before covid I started going to this Russian B yeah um you know and then which I'm and I had never been to a b so you know the whole experience of really really hot sauna yeah and the what do they call it the plot they're hitting you with the leaves and and it gets really hot and humid in there and there were a couple times where I thought okay this thing is below ground it's in a city where there are a lot of earthquakes like if this place crumbled and we were stuck in here and I'd start getting a little panicky and I I'm like I don't like small confined spaces with poor ventilation so I realize I think I have some claustrophobia and I wasn't aware of that before so I've put myself into our own claustrophobia stimulus which involves getting into an elevator um and with a bunch of people virtual people and the elevator gets stalled and at first you're fine you feel fine but then as we start modulating the environment and we actually can control levels of oxygen in the environment if we want to um it is really uncomfortable for me and I never would have thought you know I fly I'm comfortable in Planes I but it is really uncomfortable and so I think I've un unhatched a bit of a claustrophobia yeah yeah for me as well probably that one that one is pretty bad the heights I tried to overcome so I went to skydiving to try to overcome the fear of heights but that didn't help did you jump out yeah jum yeah jumped out but it was it was a it was fundamentally different experience and I guess there could be a lot of different flavors of f Heights maybe but the one I have didn't seem to be connected to jumping out of a plane is a very different cuz like once you accept that you're going to jump then it's it's a different thing I I think what I'm afraid of is the moments before it is is the was the scariest part absolutely and I I don't think that's emphasized in the skydiving experience as much and also just the acceptance of the fact that it's going to happen so so once you accept it it's going to happen it's not as scary it's the fact that it's not supposed to happen and it might that's the scary part that I guess I'm not being eloquent in this description but there's something about skydiving that uh was actually philosophically liberating I was it I was like wow it it was uh the possibility that you can walk on a surface and then at a certain point there's no surface anymore to walk on and it's all of a sudden the world becomes three-dimensional and there's this freedom of floating that the concept of like of Earth disappears for a brief few seconds I don't know that was that was wild that was wild but I'm still terrified of height so I mean one one thing I I want to ask just un fear because it's so fascinating is have you um learned anything about what it takes to overcome fears yes and that comes from two from a you know research study standpoint two parallel tracks of research one was done actually in mice uh because we have a mouse lab also where we can prob out in different brain areas and try and figure out what interesting brain areas we might want to prob around in humans and a graduate student of my lab she's now at Caltech um Lindsay SLE um published a paper back in 2018 showing that what at first might seem a little bit obvious but the mechanisms are not which is that there really three responses to fear you can pause you can freeze essentially um you can Retreat you can back up or you can go forward and there's a single Hub of neurons in the midbrain in the it's actually not the midbrain but it's in the middle of the thalamus which is a forbrain structure uh and depending on which neurons are active there there's a much higher probability that a mouse or it turns out or a human will advance in the face of fear or will pause or will Retreat now that just assigns a neural structure to a behavioral phenomenon but what's interesting is that it turns out that the lowest level of stress or autonomic arousal is actually associated with the pausing and freezing response then as the threat becomes more impending and we used visual Looms in this case The Retreat response has a slightly higher level of autonomic arousal and stress so think about playing hide and go seek and you're trying to stay quiet in a uh in a closet that you're hiding if you're very calm it's easy to stay quiet and still as your level of stress goes up it's harder to maintain that level of quiet and Stillness you see this also in animals that are stalking a cat will chatter its teeth that's actually sort of top down inhibition and trying to restrain Behavior so the freeze response is actually an active response but it's fairly low stress and what was interesting to us is that the highest level of autonomic arousal was associated with the forward movement toward the threat so in your case um jumping out of the plane however the forward movement in the face of threat was linked to the activation of what we call collateral which means just a side connection literally a wire in the brain that connects to the dopamine circuits for reward and so when one safely and adaptly meaning you survive moves through a threat or tor a threat it's rewarded as a positive experience and so the key it actually Maps very well the cognitive behavioral therapy and a lot of the existing treatments for trauma is that you have to confront the thing that makes you afraid so otherwise you exist in this very low level of reverberatory circuit activity where the the circuits for autonomic arousal are humming and they're humming more and more and more and we have to remember that that stress and fear and threat were designed to agitate us so that we actually move so the reason I mentioned this is I think a lot of times people think that the maximum you know stress response or fear response is to freeze and to lock up yeah but that's actually not the maximum stress response the maximum stress response is to advance but it's associated with reward it has positive veilance interesting so so there's this kind of everyone always thinks about the Bell sh you know the sort of Hump shaped uh curve for you know at low levels of arousal performance is low and as increases performance goes higher and then it drops off as you get really stressed but there's another bump further out the distribution where you perform very well under very high levels of stress and so we've been spending a lot of time in humans and in animals exploring what it takes to get people comfortable to go to that place and also to let them experience how there heightened states of cognition there there's um changes in time perception that allow you to evaluate your environment in fast at a faster frame rate essentially this is the Matrix as a lot of people think of it um but we tend to think about fear as all the low-level stuff where things aren't worked out but there are many um there are a lot of different features to the fear response and so we think about it quantitatively and we think about it from a circuit perspective in terms of outcomes and we try and weigh that against the threat so we never want people to put themselves in unnecessary risk but that's where the VR is fun because you can push people hard without risk R of physically injuring them and that's uh like you said a little bump that that seems to be a very small fraction of The Human Experience right so it's kind of fascinating to study it because um most of us move through life without ever experiencing that kind of uh Focus well everything's in a peak State there I really think that's where Optimal Performance lies there's so many interesting words here but what's performance and what's Optimal Performance we're talking about mental ability to what to perceive the environment quickly to make actions quickly what's Optimal Performance yeah well it's very subjective and it varies depending on um task and environment so one way that we can make it a little bit more operational and concrete is to say um there is a sweet spot if you will where the level of internal autonomic arousal AKA stress or alertness whatever you want to call it is ideally matched to the speed of whatever challenge you have be facing in the outside world so we all have um perception of the outside world as exteroception and then perception of our internal real estate interoception and when those two thing when interception and exteroception are matched along a couple Dimensions performance uh tends to increase or tends to be in in optimal range so for instance if you're I don't play guitar but I know you play guitar so let's say you're trying to learn something new on the guitar I'm not saying that being in these super high states of activation are the best place for you to be in order to learn it may be that you your internal arousal needs to be at a level where your analysis of space and time has to be well matched to the information coming in and what you're trying to do in terms of performance in terms of playing chords and notes and so forth now in these cases of high threat where things are coming in quickly and animals and humans need to react very quickly the higher your state of autonomic arousal the better because you're slicing time more finely just because of the way the autonomic system works it you know the the P P the pupil dilation for instance and movement of the lens essentially changes your your Optics that's obvious but in with the change in Optics is a change in how you bin time and slice time which allows you to get more frames per second read out with the guitar learning for instance it might actually be that you want to be almost sleepy almost in a uh kind of drowsy state to be able to and I don't play music so I can't I'm guessing here but sense some of the Nuance in the chords or the ways that you're to be relaxed enough that your fingers can follow an external cue so matching the movement of your fingers to something that's pure exteroception and so there is no perfect autonomic state for uh performance this is why I don't favor terms like flow because they're not well operationally defined enough but I do believe that optimal or Peak Performance is going to rise when internal state is ideally matched to the SpaceTime features of the external demands so there's some some slicing of time that happens and then you're you're able to adjust slice time more finely or more less finely in order to adjust to the the stimulus the Dynamics of the stimulus what about the the realm of ideas so like you know I'm I'm a big believer uh this guy named Cal Newport wrote a book about deep work oh yeah I love that book yeah he's great uh so he I mean one of the nice things I've always practic deep work but he it's always nice to have words uh put to the the concepts that you've practice ractice it somehow makes them more concrete and allows you to uh to get better it turns it into a skill that you can get better at but you know I also value deep thinking where you think it's almost meditative you think about a particular concept for long periods of time so programming you have to do that kind of thing for you just have to hold this concept like like you you hold it and then you take steps with it you take further steps and you you're holding relatively complicated things in your mind as you're thinking about them and there's a lot of I mean the hardest part is there's uh frustrating things like you take a step and it turns out to be the wrong direction so you have to calmly turn around and take a step back and then it's you kind of like exploring through the space of ideas is there something about your study of Optimal Performance that could be applied to the act of thinking as opposed to action well we haven't done too much work there but what um but I think I can comment on it from a neuroscience perspective which is really all I do is well I I mean we do experiments in the lab but um looking at things through the lens of Neuroscience so what you're describing um can be mapped fairly well to working memory just keeping things online and updating them as they change in information it's coming back into into your brain uh Jack Feldman who I'm a huge fan of and um fortunate to be friends with is a uh professor at UCLA works on respiration and breathing but he has a physics background and um and so he thinks about respiration and breathing in terms of ground States and how they modulate other states very very interesting and I think um important work Jack uh has an answer to your question so I'm not going to get this exactly right because this is lifted from a coffee conversation that we had about a month ago but uh so um apologies in advance for the but I think I it mostly right so we were talking about this about how the brain updates cognitive States depending on demands and thinking in particular and he used an interesting example I'd be curious to know if you agree or disagree uh he said you know most great mathematics that's done by people in their late teens and 20s and even you could say early 20s sometimes into the late 20s but not much further on maybe I just insulted some mathematicians no that's that's that's true and I think that it demands his argument was um there's a tremendous Demand on working memory to work out theorems in math and to keep a number of plates spinning so to speak mentally and run back and forth between them updating them in physics Jack said and I I'm in I think this makes sense to me too that there's a Reliance on working memory but an increased Reliance on some sort of deep deep memory and deep memory stores probably stuff that's moved out of the hippocampus and forbrain and into the cortex and is um more some episodic and declarative stuff but really so you're you're pulling from your library basically it's not all Ram it's not all working memory and then in biology and physicists tend to have very active careers into their you know 30s and 40s and 50s and so forth um sometimes later and then in biology you see careers that have a much longer Arc kind of these protracted careers often uh people still their 60s and 70s doing doing really terrific work not always doing it with their own hands because there people in the labs are doing them of course but um and that work does tend to rely on insights gained from having a very deep knowledge base where you can remember a paper and a or maybe a figure in a paper you could go look it up if you wanted to but it's very different than the working memory of the mathematician and so when you're talking about coding or being in that tunnel of thought and trying to iterate and keeping a lot of plates spinning it it speaks directly to working memory my lab hasn't done too much of that working memory but we are pushing working memory when we have people do things like these simple lights out tasks while they're under we can increase the cognitive load by increasing the level of autonomic arousal to the point where they start doing less well Y and you know everyone has a cliff this is what's kind of fun we've had um you know Seal Team operators come to the lab we've had people from other units in the military very you know we've had a range of of intellects and backgrounds and all sorts of things and everyone has a cliff and those Cliffs uh sometimes show up as a function of the demands of speed of processing or how many things you need to keep online I mean we're all Limited at some point in the number of things we can keep online so what you're describing is very interesting because it I think it has to do with how narrow or broad the information set is because and I don't proog I'm not an active programmer so and this is a regime I don't really fully know so I don't want to comment about it uh in that in anyway uh that that you know doesn't suggest that but I think that what you're talking about is top- down control so this is prefrontal cortex keeping every bit of reflexive circuitry at Bay the one that makes you want to get up and use the restroom the one that makes you want to check your phone all of that but also running these anterior Thalamus to prefrontal cortex Loops which we know are very important for working memory yeah let me try to think through this a little bit so reducing the process of thinking to working memory access is tricky he's probably ultimately correct but if I were to say some of the most challenging things that uh an engineer has to do and a scient scientific thinker I would say it's kind of pressing to think that we do that best in our 20s but is uh this kind of first principles thinking step of of saying you're you're accessing the things that you know and then saying well let me how do I do this differently than I've done it before this this weird like stepping back like is this right let's try it this other way that that's the the most mentally taxing step it's like you you've gotten quite good at this particular pattern of how you solve this particular problem so there's a there's a pattern recognition first you're like okay I know how to build a thing that solves this particular problem in programming say and then the question is but can I do it much better and I don't know if that's I don't know what the hell that is I don't know if that's accessing working memory that's that's almost access maybe it is accessing memory in a sense that's trying to find similar patterns in a totally different place that could be uh projected onto this but you're you're it's you're not quering uh facts you're quering like functional things like yes it's patterns I mean you're running you're testing algorithms yeah right you're testing algorithms I so I want to just um because I know some of the people listening to this and you have have basis in you know scientific training and have scientific training so I want to be clear I think we can be correct about some things like the role of working memory in these kinds of processes without being exhaustive we're not saying they're the only thing we're you know we can be correct but not assume that that's the only thing involved right and I mean Neuroscience let's face it is still in its infancy I mean we probably know 1% of what there is to know about the brain um you know we've learned so much and yet there may be Global states that underly this that make prefrontal circuitry work differently than it would in a in a different regime or even time of day I mean there's a lot of mysteries about this but so I just want to make sure that we we sort of are we're aiming for precision and accuracy but but we're not going to be we're not going to be exhausted so there's a difference there and I think uh you know sometimes in the vastness of the internet uh that gets forgotten um so the other is that um you know we we think about um you know we think about these operations uh at you know really focused keeping a lot of things online but what you were describing is actually um it it speaks to the the very real possibility probably that the with certainty there's another element to all this which is when you're trying out lots of things in particular lots of different algorithms you don't want to be in a in a state of very high autonomic arousal that's not what you want because the higher level of autonomic arousal and stress in the system the more rigidly you're going to analyze space and time right and what you're talking about is playing with space-time dimensionality and I want to be very clear I mean I'm the son of a physicist I am not a physicist when I talk about space and time I'm literally talking about visual space and how long it takes for my finger to move from this point to this point you you are facing a tiger and trying to figure out how to avoid being eaten by the and that's primarily going to be determined by the visual system in humans we don't walk through space for instance like a sen Hound would and look at three-dimensional scent plumes you know when a senent Hound goes out in the environment they have depth to their odor tra the odor Trails they're following and they don't think about them we don't think about odor Trails you might say oh well the smell's getting more intense aha but they actually have threedimensional odor Trail so there see a cone of odor see of course with nose with their Factory cortex we do that with our visual system and we parse time often subconsciously with mainly with our visual system also with our auditory system and this shows up for the musicians out there metronomes are a great way to play with this um you know bass drumming when the frequency of bass drumming changes your perception of time changes quite a lot so in any event space and time are linked in the through the sensory appara eye through the eyes and ears and nose and um probably through taste too and through touch um for us but mainly through vision so when you drop into some coding or iterating through a creative process or trying to solve something hard you can't really do that well if you're in a rigid um high level of autonomic arousal because you're plugging in algorithms that are in this space regime this time regime matches it's SpaceTime matched whereas creativity I always think the Lava Lamp is actually a pretty good example even though it has these counterculture new AG connotations because you actually don't know which direction things are going to change and so in drowsy States sleeping and drowsy States space and time become dislodged from one another somewhat and they're very fluid and I think that's why a lot of solutions come to people after sleep and naps and this could even take us into a discussion if you like about psychedelics and what we now know for instance that people thought that psychedelics work by just creating spontaneous bursting of neurons and hallucinations but the the 5H 2ca and 2C and 2A receptors which are the main sites for things like LSD and psilocybin and some of the other um huc the ones that create hallucinations the drugs that create hallucinations the most of those receptors are actually in the um collection of neurons that encase the thalamus which is where all the sensory information goes into a structure called the thalamic reticular nucleus um and it's an inhibitory structure that makes sure that when we're sitting here talking that I'm mainly focused on whatever I'm seeing visually that I'm essentially eliminating a lot of sensory information under conditions where people take psychedelics and these uh particular serotonin receptors are activated that inhibitory shell it's literally shaped like a shell starts losing its ability to inhibit the passage of sensory information but mostly the effects of psychedelics are because lateral connectivity in layer five of Cortex across cortical areas is increased and what that does is that means that the SpaceTime relationship for vision like moving my finger from here to here very rigid SpaceTime relationship right if I slow it down it's slower obviously but there's a prediction that can be made based on the neurons and the retina and the cortex on psychedelics this could be very strange experience yeah but the auditory system has one that's slightly different SpaceTime and they're matched to one another in deeper Circ in the brain thefactory system has a different SpaceTime relationship to it so under conditions of of these increased activation of these serotonin receptors space and time across sensory area starts being fluid so I'm no longer running the algorithm for moving my finger from here to here and making a prediction based on Vision alone I'm now this is where people talk about um hearing sites right you start linking the this might actually make a sound in a psychedelic State now I'm not suggesting people run out and do psychedelics because it's very disorganized but essentially what you're doing is you're mixing the algorithms and so when you talk about being able to access new Solutions you don't need to rely on psychedelics if people choose to do that that's their business but in drowsy States this lateral connectivity is increased as well the shell of the thalamus shuts down and what's H there there through these so-called pwns chicl occipital waves and what's happening is you're getting whole brain activation at a level that you start mixing algorithms and so sometimes I think Solutions come not from being in that narrow tunnel of space time and strong activation of working memory and trying to well iterate if this then this very strong deductive and inductive thinking and working from first principles but also from states where something that was an algorithm that never you never had in existence before suddenly gets lumped with another algorithm and all of a sudden a new possibility comes to mind and so space and time need to be fluid and space and time need to be rigid in order to come up with something meaningful and I realize I'm riffing long on this but this is why I think you know there was so much interest a few years ago with Michael pollen's book and and other things happening about psychedelics as a pathway to exploration and all this kind of thing but the real question is what you export back from those experiences because dreams are amazing but if you can't bring anything back from them they're just amazing I wonder how to experiment with a mind without without any medical assistance first like you know I I push my mind in all kinds of directions I definitely want to I did uh shrooms a couple of times I definitely want to uh figure out how I can experiment with um with psychedelics I'm talking to uh Rick dolin I Thinkin doblin uh soon I went back and forth so he does all these studies in psychedelics and he keeps ignoring the parts of my email that asks like how do I participate in these studies yeah well there are some legality issues I mean conversation I want to be very clear I'm not saying that anyone should run out and do psychedelics I think that drowsy States and sleep states are are super interesting for accessing some of these more creative states of Mind hypnosis is something that my colleague David Spiegel associate chair of Psychiatry at Stanford works on where also again it's a unique State because you have narrow context so this is very um kind of tunnel vision and yet deeply rela excuse me deeply relaxed where new algorithms if you will can start to surface um strong state for inducing neuroplasticity and I think that you know so if I had a um I'm part of a group um that uh it's called the linal collective is a group of people that get together and talk about um just wild ideas but they try and Implement um and it's a it's a really interesting group some people from military from uh logic Tech and some other backgrounds academic backgrounds and I was asked you know what would be um if you could create a tool if you just had a tool like your magic Wan wish for the day what would it be I thought it' be really interesting if someone could develop psychedelics that have um onoff switches so you could go into a psychedelic State very deeply for 10 minutes but you could launch yourself out of that state and place yourself into a linear real world State very quickly so that you could extract whatever it was that that happened in that experience and then go back in if you wanted because the problem with psychedelic States and dream states is that first of all a lot of the reason people do them is they're lying they say they want plasticity and they want all this stuff they want a peak experience yeah inside of an amplified experience so they're kind of seeking something unusual I think we should just be honest about that because a lot of times they're not trying to make their brain better they're just trying to experience something really amazing but the problem is space and time are so unlocked in these states just like they are in dreams that you can really end up with a whole lot of nothing you can have an amazing Amplified experience housed in an amplified experience and come out of that thinking you had a meaningful experience when you didn't bring anything back you didn't bring anything back all all you have is a fuzzy memory of having a transformational experience but you don't actually have yeah tools to bring back or sorry actual actually concrete ideas to bring back yeah it's interesting yeah I wonder if it's possible to do that with the with a mind to to be able to hop back and forth I think that's where the real power of you know adjusting States is going to be it probably will be with devices um I mean maybe it'll be done through pharmacology it's just that it's hard to do onoff switches in in human pharmacology that we have them for Animals I mean we we have you know cre flip common Aces and we have um you know Channel opsins and Halo root opsins and um all these kinds of things but to to do that work in humans is tricky but I think you could do it with um virtual reality augmented reality and other devices that bring more of the sematic experience into it you're of course a scientist who's studying humans as a collective I tend to be just a one person scientist of just looking at myself and you know I play when these deep thinking deep work sessions I'm very cognizant like in the morning that there's times when my mind is so like eloquent at being able to jump around from ideas and hold them all together and I I'm almost like I step back from a third person perspective and enjoy that whatever that mind is doing I'm I do not waste those moments I and I'm very conscious of um this like little creature that woke up that's only awake for if we're being honest maybe a couple hours a day uh early part of the day for you early part of the day not always well early part of the day for me is a very uh fluid concept so you're one of those yeah I'm one yeah you're one of those being single one of the problems single and no meetings I don't schedule any meetings I I will I've been living at like a 28h hour day so I like I uh it drifts so it's it's all over the the place but after a uh traditionally defined full night sleep uh whatever the heck that means I I find that like in in those moments there's a Clarity of mind that's just this everything is effortless and it's the it's the deepest Dives intellectually that I make and I I'm cognizant of it and I try to bring that to the other parts of the day that don't have it and treasure them even more in those moments cuz they only last like 5 or 10 minutes like cuz of course in those moments you want to do all kinds of stupid stuff that are completely is is is worthless like check social media or something like that but those are the most precious things in in in in intellectual life is those mental moments of clarity and I wonder I'm learning how to control them I think caffeine is somehow involved I'm not sure exactly sure well because if you learn how to titrate caffeine everyone's slightly different with this what they need but if you learn to titrate caffeine with time a day and the kind of work that you're trying to do you can bring that autonomic arousal State into the close to perfect place and then you can tune it in with you know sometimes people want a little bit of background music sometimes they want less these kinds of things the the the early part of the day is interesting because the one thing that's not often discussed is the transition out of sleep so there's a a book um I think it's called Winston Churchills nap and it's about naps and and the transition between wake and sleep as a valuable period um I've a long time ago um someone who I respect a lot was mentoring me said um be very careful about bringing in someone else's sensory experience early in the day so when I wake up I'm very drowsy I sleep well but I I don't emerge from that very quickly I need a lot of caffeine to wake up and whatnot but there's this concept of getting the download from sleep which is you know in sleep you're you were essentially expunging the things that you don't need the stuff that was meaningless from the previous day but you were also running variations on these algorithms of whatever it is you're trying to work out in life on short time scales like the previous day and long time scales like your whole life and those lateral Connections in layer five of the of the neocortex are very robustly um active and AC cross sensory areas and and you're running a an algorithm or a colle you know a brain it's a brain state that would be useless and waking you wouldn't get anything done you'd be the person talking to yourself in the hallway or something about something that no one else can see but in those States you do that the theory is that you arrive at certain Solutions and those Solutions will reveal themselves in the early part of the day unless you interfere with them by bringing in social media is a good example of you immediately enter somebody else's space time sensory relationship someone is the conductor of your thoughts in that case and so many people have written about this um what I'm saying isn't entirely new but but allowing the download to occur in the early part of the day and and asking the question am I more in my head or extern am I in more of an interoceptive or exteroceptive mode and depending on the kind of work you need to do if it's it sounds like for you it's very interoceptive in the and very you got a lot of thinking going on and a lot of computing going on allowing yourself to transition out of that sleep State and arrive with those solutions from sleep and plug into the work really deeply and then and only then allowing things like music news social media doesn't mean you should talk to loved ones and see faces and things like that but some people have taken this to the extreme when I was a graduate student at Berkeley there was a guy um there a professor brilliant odd but brilliant um who was so fixated on this concept that he wouldn't look at faces in the early part of the day MH because he just didn't want to anything else to impact him now he would didn't have the most um rounded life I suppose but if you're talking about um cognitive performance this could actually be very beneficial you said so many brilliant things so one if you read books that describe the habits of uh brilliant people like uh writers they do control that sensory experience in in the in the in the hours after wake like many writers you know they have a particular habit of several hours early in the morning of actual writing they do don't do anything else for the rest of the day but they control they're very sensitive to noises and so on I think they make it very difficult to live with them I try to I'm definitely like that like I can I I love to control the sensory uh how much information is coming in there's something about the peaceful just everything being peaceful at the same time and we we're talking to a me your friend of Whitney come who um has has a has a mansion a castle on top of a cliff in in the middle of nowhere she actually purchased her own Island uh so she wants silence she wants to control how much sound is coming in and she's very sensitive to to sound and environment yeah beautiful home and environment but like clearly puts a lot of attention into into details yeah and and very creative yeah and that's yeah that allows her creativity to flourish I'm also I don't like that feels like a slippery slope so I I enjoy introducing the noises and signals and uh training my mind to be able to tune them out cu I feel like you can't always control the environment so perfectly because uh because your mind gets comfortable with that I think it's a skill that you want to learn to be able to shut it off like I often go to like back before Co to a coffee shop it really annoys me when there's sounds and voices and so on but I feel like I can train my mind to to block them out so it's it's a balance I think yeah and I think um you know two things come to mind um as you're saying this um first of all yeah I mean we're talking about what's best for work is not always what's best for you know completeness of life I mean you know autism is probably many things like when we autism just like Fe there probably 50 ways to get a fever there probably 50 ways to that the brain can create what looks like autism or what people call autism there's an ing set of studies that have come out of David ginty's Lab at Harvard Med um looking at these are Mouse mutants where um these are models for autism where nothing is disrupted in the brain proper and in the central nervous system but the sensory the sensory neurons the ones that inate the skin and the ears and everything are are hyp sensitive and this maps to a mutation in certain forms of human autism so this means that the the overload of sensory information and sensory experience that a lot of autistics feel they like that they can't tolerate things and then they get the stereotype behaviors the rocking and the kind of the shouting it you know we always thought of that as a brain problem in some cases it might be but in many cases it's because they just can't they they seem to have a m it's like turning the volume up on every sense and so they're overwhelmed and none of us want to be come like that I think it's very hard for them and it's hard for their parents and so forth so I I like the the coffee shoing example because um the way I think about trying to build up resilience uh you know physically or mentally or otherwise is one of um I guess we could call it Lim I like to call it lyic friction that's not a real scientific term and I acknowledge that I'm making it up now because I think it captures the concept which is that you know we always hear about resilience it makes it sound like oh you know under stress where everything's coming at you you're going to stay calm but there's another you know so limic the lyic system wants to pull you in some Direction typically in the direction of reflexive Behavior and the prefrontal cortex through top down mechanisms has to suppress that and say no we're not going to respond to the banging of the coffee cups behind me or I'm going to keep focusing that's pure top- down control so lyic friction is high in that environment youve put yourself into a high lyic friction environment mean that the prefrontal cortex has to work really hard but there's another side to lyic friction too which is when you're very sleepy there's nothing incoming it can be completely silent and it's hard to engage and focus because you're drifting off you're getting sleepy so their limic friction is high but for the opposite reason autonomic arousal is too low so there turning on Netflix in the background or looping a song might boost your level of alertness that will allow top down control to be in in the pl exactly The Sweet Spot you want it so that this is why earlier I was saying it's all about how we feel inside relative to what's going on on the outside we're constantly in this I guess one way you could Envision it spatially especially if uh people are listening to this just on audio is I like to think about it kind of like a glass barbell where one sphere of perception and attention can be on what's going on with me and one sphere of attention can be on what's going on with you or something else in the room or in my environment but those this barbell isn't rigid it's not really glass would plasma work here I don't know anything about plasma sorry I don't know okay but so imagine that this thing can contort the size of the the the globes at the end of this barbell can get bigger or smaller so let's say I close my eyes and I bring all my experience into what's going on inter in through interoception internally now it's as if I've got two orbs of perception just on my internal state but I can also do the opposite and bring two both orbs of perception outside me I'm not thinking about my heart rate or my breathing I'm just thinking about something I see and what you'll start to realize as you kind of use this spatial model is that two things one is that it's very Dynamic and that the more relaxed we are the more these two orbs of attention the two ends of the barbell can move around freely the more alert we are the more rigid they're going to be tethered in place and that was designed so that if I have a threat in my environment it's Tethered to that threat I'm not going to be if something's coming to attack me I'm not going to be like oh my breathing Cadence is a little bit quick that's not how it works why because both orbs are l linked to that uh to that threat and so my behavior is now actually being driven by something external even though I think it's internal and so I don't want to get too abstract here because I'm a neuroscientist I'm not a a theorist but when you start thinking about models of how the brain work I mean brain works excuse me they're only really three things that neurons do they're either Sensory neurons they're motor neurons or they're modulating things and the the models of attention and perception that we have now 2020 tell us that we've got interoception and exteroception they're strongly modulated by levels of autonomic arousal and that if we want to form the optimal relationship to some task or some pressure or some thing whether or not it's sleep an impending threat or coding we need to adjust our internal space-time relationship with the external space-time relationship and I realize I'm repeating what I said earlier but we can actually assign circuitry to this stuff it mostly has to do with how much lyic friction there is how much you're being pulled to some source that Source could be internal if I have if I have pain physical pain in my body I'm going to be much more interoceptive than I am EXT receptive you could be talking to me and I'm just going to be thinking about that pain it's very hard and the other thing that we can link it to is top- down control meaning anything in our environment that has a lot of salience will tend to bring us into more exteroception than interoception and again I don't want to litter the conversation with just a bunch of terms but um what I think it can be useful for people is to do what essentially you've done Lex is to start developing an awareness when I wake up am I mostly in a mode of interoception or exteroception when I work well is that what is working well look like from the perspective of autonomic arousal how alert or calm I am I what kind of balance between internal focus and external focus is there and to sort of watch this process throughout the day can you linger just briefly and cuz use this term a lot it be nice to try to get a little more color to it which is interoception and exteroception uh what are what are we exactly talking about so like what's included in each category and how much overlap is there interception would be uh an awareness of anything that's within the confines or on the surface of my skin that I'm sensing Al so literally physiological physiologically like within the boundaries of my skin and probably touch to the skin as well exteroception would be perception of anything that's ex beyond the reach of my skin so that that bottle of water um a scent um a sound although and this can change dramatically actually if you have headphones in you tend to hear things in your head if as opposed to a speaker in the room this is actually the basis of ventriloquism so there are beautiful experiments done by Greg Reen Zone up at UC Davis looking at how auditory and visual cues are matched and you have an array of speakers and you can this will become obvious as I say it but you know obviously the ventriloquist doesn't throw their voice what they do is they direct your vision to a particular location and you think the sound is coming from that location and there are beautiful experiments that Greg and his colleagues have done where they suddenly introduce a auditory visual mismatch and it freaks people out because you can actually make it seem from a perception standpoint as if the sound arrived from the corner of the room and hit you like it physically and people will recoil and so sounds aren't getting thrown across the room they're still coming from this defined location array of speakers but this is the way the brain creates these internal representations and again not to I don't want to go down a rabbit hole but um I think as much as you you know I'm sure the listeners appreciate this but you know everything in the brain is an abstraction right I mean they're they're the sensory apparati there are the eyes and ears and nose and skin and taste and all that are taking information and with interoception it's taking information from sensors inside the body the anic nervous system for the gut I've got Sensory neurons that intermate my liver um Etc taking all that and the brain is abstracting that in the same way that if I took a picture of your face and I handed it to you and I'd say that's you you'd say yeah that's me but if I were an abstract artist I'd be doing a little bit more of what the brain does where if I took a pen pad and paper maybe I could do this because I'm a terrible artist and I could just mix it up and I let's say I would make your eyes like water bottles but I'd flip them upside down and I'd start assigning fruits and objects to the different features of your face and I showed to you I say Lex that's you say well that's not me and I'd say no but that's my abstraction of you but that's what the brain does the space time relationship of the neurons that fire that encode your face has have no resemblance to your face right and I think people don't really I don't know if people have fully internalized that but the day that I and I'm not sure I fully internalized that because it's weird to think about but all neurons can do is fire in space and in time different neurons in different sequences perhaps with different intensities it's not clear the action potential is all or none although people neuroscientists don't like to talk about that even though it's been published in nature a couple times the action potential for a given neuron doesn't always have the exact same wave form people it's in all the textbooks but you can modify that wave for well there I mean there's a lot of fascinating stuff with uh with Neuroscience about the fuzziness of all the uh of the transfer of information from neuron to neuron I mean there we we certainly touch upon it every time we at all try to think about the difference between artificial neural networks and biological neural networks but can we uh maybe linger a little bit on this uh on the circuitry that you're getting at so the brain is just a bunch of stuff firing and it forms abstractions that are fascinating and beautiful like layers upon layers upon layers of abstraction and I think it uh just like when you're programming you know I'm programming in Python it's uh it's all inspiring to think that Underneath It All it ends up being zeros and ones and the computer doesn't know about no stupid python or Windows or Linux it it only knows about the zeros and ones in the same way with the brain is there something interesting to you or fundamental to about the circuitry of the brain that allows for the magic that's in our mind to emerge how much do we understand I mean maybe even focusing on the vision system is is there something specific about the structure of the vision system the circuitry of it that uh allows for the complexity of the vision system to emerge or is it all just a complete chaotic mess that we don't understand it's definitely not all a cha mess that we don't understand if we're talking about vision and that's not just because I'm a vision scientist let's stick to Vision let's stick to Vision well because in the beauty of the visual system the reason David huble and torr and weasel won the Nobel Prize was because they were brilliant in Forward Thinking and adventurous and all that good stuff but the reason that the visual system is such a great model for addressing these kinds of questions and other systems are hard is we can control the stimul we can adjust spatial frequency how finer the gradings are thick gradings thin gradings we can just temporal frequency how fast things are moving we can um use con isolating stimuli we can use there's so many things that you can do in a controlled way whereas if we were talking about cognitive encoding like the you know encoding the space of Concepts or something you know I I I've you know I like you I if I may are am drawn to the the big questions in Neuroscience but I confess in part because of some good advice I got early in my career and in part because I'm um not perhaps smart enough to go after the really high level stuff I also like to address things that are tractable and I want you know we need to we need to address what we can stand to make some ground on at a given time they you can construct brilliant controlled experiments just to study to really literally answer questions about yeah yeah I mean I'm happy to have a talk about Consciousness but it's it's a scary talk and I think most people don't want to hear what I have to say which is you know which is uh we can save that for later perhaps or it's an interesting question of uh we talk about psychedelics we can talk about Consciousness we can talk about cognition can experiments in Neuroscience be constructed to shed any kind of light on these questions so I mean it's cool that Vision I mean to me vision is probably one of the most beautiful things about human beings uh also from the AI side computer vision has the is some of the most exciting applications of uh neural networks is in computer vision but it feels like that's a that's a neighbor of cognition and Consciousness it's just that we maybe haven't come up with experiments to study those yet yeah the visual system is amazing we're mostly visual animals to navigate survive humans mainly rely on Vision not smell or something else but um it's a filter for cognition and it's a it's a strong driver of cognition maybe just because it came up and then we're moving to higher level Concepts just the the way the visual system works can be summarized in it um in a few relatively succinct statements unlike most of what I've said which has not been succinct at all let's go there you Thea what's involved yeah so the retina is this three layers of neuron structure at the back of your eye it's about as thick as a credit card it is a piece of your brain and sometimes people think I'm kind of wriggling by out of a real by saying that it is it's absolutely a piece of the brain it's it's a forbrain structure that in the first trimester there's a genetic program that made sure that that neural retina which is part of your central nervous system was squeezed out into What's called the embryonic eye cups and that the bone formed with a little hole where the optic nerve is going to connected to the rest of the brain and those that window into the world is the only window into the world for a for a mammal which has a thick skull birds have a thin skull so their pineal gland sits and lizards too and snakes actually have a hole so that light can make it down into the pineal directly and entrain melatonin rhythms for time of day and time of year humans have to do all that through the eyes so three layers of neurons that are a piece of your brain they are central nervous system and the optic nerve connects to the rest of the brain the neurons in the eye some just care about luminance just how bright or dim it is and they inform the brain about time of day and then the central circadian clock informs every cell in your body about time of day and make sure that all sorts of good stuff happens if you're getting light in your eyes at the right times and all sorts of bad things happen if you are getting light randomly throughout the 24-hour cycle we could talk about all that but this is a good incentive for keeping a relatively normal schedule consistent schedule of light exposure consistent schedule try and keep a consistent schedule when you're young it's easy to go off schedule and recover as you get older it gets harder but you see everything from outcomes in cancer patients to um diabetes um you know improves when people are getting light at a particular time of day and getting Darkness at a particular phase of the 24-hour cycle we were designed to um get light and dark at different times of the of the Circadian cycle that's all being all that information is coming in through specialized type of neuron in the retina called the melanops an intrinsically photosensitive gangling cell discovered by David buron at Brown University that's not spatial information it's subconscious you don't think oh it's daytime even if you're looking at the sun it doesn't matter it's a photon counter it's literally counting photons and it's saying oh even though it's a cloudy day lots of photons coming in it's winter in Boston it must be winter and your system is a little depressed it's spring you feel alert that's not a coincidence that's these melanops and cells signaling the circadian clock there are a bunch of other neurons in the eye that signal to the brain and they mainly signal the presence of things that are lighter than background or darker than background so a black objects would be darker than background a light object lighter than background and that all come it's mainly a it's looking at pixels mainly it's they look at circles and those neurons have receptive fields which not everyone will understand but those neurons respond best to little Circles of dark light or little Circles of bright light little Circles of red light versus little Circles of green light or blue light and so it sounds very basic it's like red green blue and circles brighter or dimmer than what's next to it but that's basically the only information that sent down the optic nerve and when we say information we can be very precise I don't mean little bits of red traveling down the optic nerve I mean spikes neural Action potentials in space and time which for you is like makes total sense but I think for a lot of people it it's actually beautiful to think about all that information in the outside world is converted into a language that's very simple it's just like a few syllables if you will and those syllables are being shouted down the optic nerve converted into a totally different language like mors code goes into the brain and then the thalamus essentially responds in the same way that the retina does except the thalamus is also waiting things it's saying you know what that thing um was moving faster than everything else or it's brighter than everything else so that signal I'm going to get up I'm going to allow up to Cortex or that signal is much redder than it is green so I'm going to let that signal go through that signal is much eh it's kind of more like the red next to it throw that out the information just doesn't get up into your cortex and then in cortex of course is where perceptions happen and in V1 if you will visual area one but also some neighboring areas you start getting representations of things like oriented lines so there's a neuron that responds to this angle of my hand versus vertical MH right this is the defining work of Hub visil Nobel and it's a very systematic map of orientation line orientation direction of mve movement and so forth and that's pretty much and color and that's how the visual system is organized all the way up to the cortex so it's hierarchical you don't build I want to be clear it's hierarchical because you don't build up that line by suddenly having a neuron that responds to lines in a some random way it responds to Lines by taking all the dots that are aligned in a vertical stack and they all converge on one neuron and then that neuron response to vertical lines so it's not random there's no abstraction at that point in fact in in fact if I showed you a black line I could be sure that if I were Imaging V1 that I would see a representation of that black line as a vertical line somewhere in in your cortex so at that point uh it's absolutely concrete it's not abstract but then things get really mysterious some of that information travels further up into the cortex so that and goes from one visual era to the next to the next to the next so that by time you get into an area that um Nancy kwish are at MIT has studied her much of her career the fusiform face area you start finding single neurons that respond only to your father's face or to Joe Rogan's face regardless of the orientation of his face I'm sure if you saw Joe because you know him well from across the room and you just saw his profile be like oh that's Joe walk over and say hello the orientation of his face isn't there you wouldn't even see his eyes necessarily but he's represented in some abstract way by a neuron that actually would be called The Joe Rogan neuron or neurons it might have limits like I might not recognize him if he was upside down or something like that it'd be fascinating to to see what the limits of that Joe Rogan concept is so nany's lab has done that because early on she was challenged by people that said there aren't face neurons there are neurons that they only respond to space and time shapes and things like that moving in particular directions and orientations and turns out Nancy was right um they used the stimula called called grible stimuli which um any computer programmer would appreciate which kind of morphs a face into something gradually that eventually just looks like this like alien thing they call the gal and the neurons don't respond to grebles in most cases they only respond to faces and familiar faces anyway I'm summarizing a lot of literature and forgive me Nancy and for those of the gbo people if there ours they like don't come after me with pitchforks actually you know what come out fors I think you know what I'm trying to do here yeah so the point is that in the visual system it's very concrete up until about visual area 4 which has color pin wheels and seems to respond to pin wheels of colors and um and so the stimula become more and more elaborate but at some point you depart that concrete representation and you start getting abstract representations that can't be explained by simple point-to-point wiring MH and to take a leap out of the visual system to the higher level Concepts what we talked about in the visual system maps to the auditory system where you're encoding what frequency of tone sweeps so this gonna sound weird to do but you know a like a Doppler like hearing something a car passing by for instance but at some point you get into motifs of music that can't be mapped to just a a a what they call a tonotopic map of frequency you start abstracting and if you start thinking about concepts of creativity and love and memory like what is the map of memory space right well your memories are very different than mine but presumably there's enough structure at the early stages of memory processing or at the early stages of emotional processing or at the earlier stages of creative processing that you have the building blocks your zeros and ones if you will but you depart from that eventually now the exception to this and I want to be really clear because I was just mainly talking about neocortex the six layered structure on the outside of the brain that explains a lot of human abilities other animals have them too is that subcortical structures are a lot more like machines it's more plung and chug and what I'm talking about is the Machinery that controls heart rate and breathing and receptive Fields um you know neurons that respond to things like temperature on the top of my left hand and one of the you know I came into Neuroscience from a more of a perspective initially of psychology but one of the reasons I forced upon myself to learn a some electrophysiology not a ton but enough and some molecular biology and about circuitry is that one of the most beautiful experiences you can have in life I'm convinced is to lower an electrode into the cortex and to show a person or an animal you do this ethically of course a stimulus yes like an oriented line or a face and you can convert the recordings coming off of that electrode into an audio signal an Audio Monitor and you can hear what they call hash it's not the hash you smoke it's the hash you hear and it's it sounds like it just sounds like noise MH and in the cortex eventually you find a stimulus that gets the neuron to spike and fire Action potentials they're converted into an auditory stimulus that are very concrete crack crack crack sounds like a bat cracking you know like home runs you know or or outfield balls when you drop electrodes deeper into the thalamus or into the hypothalamus or into the brain stem areas that control breathing it's like a machine you never hear hash you drop the electrode down this could be like a like a grungy old tugon electrode not high fideli electrode as long as it's got a little bit of insulation on it you plug it into an audio monitor it's picking up electricity and if it's a visual neuron and it's in the thalamus of the retina and you walk in front of that animal or person that that neuron goes and then you walk away and it stops and you put your hand in front of the eye again and it goes and you could do that for two days and that neuron will just every time there's a stimulus it fires so whereas before it's a question of how much information is getting up to Cortex and then these abstractions happening where you're creating these ideas when you go subcortical everything is there's no abstractions it's 2 plus 2 equals 4 there's no abstractions and this is why I um you know I know we have some common friends at neurol link and I love the demonstration they did recently I'm a huge fan of what they're doing and and where they're headed and no I don't get paid to say that and I have no you know business relationship to them I'm just a huge fan of the people and the mission but my question was to some of them you know when are you going to go subcortical because if you want to control an animal you don't do it in the cortex the cortex is like the abstract painting I made of your face stim moving removing one piece or changing something may or may not matter for the abstraction but when you are in the subcortical areas of the brain stimulating electrod can evoke an entire Behavior or an entire State and so the brain if we're going to have a discussion about the brain and how the brain works we need to really be clear which brain because everyone loves neocortex it's like oh canonical circuits in cortex we're going get the cortical connectome and sure necessary but not sufficient not to be able to plug in patterns of electrical stimulation and get Behavior eventually we'll get there but if you're talking subcortical circuits that's where the action is that's where you could potentially cure Parkinson's by stimulating the subthalamic nucleus because we know that it Gates motor activation patterns in very predictable ways so I think for those that are interested in Neuroscience it pays to pay attention to like is this a circuit that abstracts the sensory information or is it just one that builds up hierarchical models in a very predictable way and there's a huge chasm in Neuroscience right now because there's no conceptual leadership no one knows which way to go and this is why I think neuralink has captured an amazing opportunity which was okay while while all you academic research labs are figuring all this stuff out we're going to pick a very specific goal and make the goal the end point and some academic Laboratories do that but I think that's a beautiful way to attack this whole thing about the brain because it's very concrete let's restore motion to the parkinsonian patient academic Labs do that want to do that too of course let's restore um speech to the stroke patient but there's nothing abstract about that that's about figuring out the solution to a particular problem so anyway those are my and i' and I admit I've mixed in a lot of opinion there but having spent some time like 25 years digging around in the brain and listening to neurons firing and looking at them anatomically I think given it's 2020 we we need to uh ask the right you know the way to get better answers is ask better questions and the really high level stuff is fun it makes for good conversation and it has um brought enormous interest but I think the questions about Consciousness and dreaming and stuff they're fascinating but I don't know that we're there yet so you're seeing there might be a chasm in the two views of uh the power of the brain arising from the from the circuitry that forms abstractions or the power of the brain arising from the majority of the circuitry that's just doing very uh boot Force dumb things that are like that don't have any fancy kind of stuff going on that's really interesting to think about and which one to go after first and and and here I'm poaching badly from someone I've never met but whose you know work I I follow which is and it was actually on your podcast I think Elon Musk said you know basically the brain is a what you say a monkey brain with a supercomputer on top and I thought that's actually probably the best description of the brain I've ever heard because it captures a lot of important features like lyic friction right we think of like oh you know when we're making plans we're using the prefrontal cortex and we're executive function and all this kind of stuff but think about the drug addict who's driven to go pursue herin or cocaine they make plans so clearly they use their frontal cortex it's just that it's been hijacked by the lyic system and all the mon the monkey brain as he referred to it's really not fair to monkeys though Elon because actually monkeys can make plans they just don't make plans as sophisticated is AES I've spent a lot of time with monkeys but I've also spent a lot of time with humans anyway I'm but you're you're putting you're saying like we there's a lot of value to focusing on the monkey brain or whatever the heck you call it like I do because let's say I had an ability to place a chip anywhere I wanted in the brain today and activate it or inhibit that area I'm not sure I would put that chip in neocortex except maybe to just kind of have some fun and see what happens the reason is it's an abstraction machine and especially if I wanted to make a Mass Production Tool a tool in mass production that I could give to a lot of people because it's quite possible that your abstractions are different enough than mine that I wouldn't know what patterns of firing to induce but if I want let's say I want to increase my level of focus and creativity well then I would love to be able to for instance control my level of lyic friction I would love to be able to wake up and go oh you know I have an 8:00 appointment I wake up slowly so between S8 but I want to do a lot of linear thinking so you know what I'm going to just I'm going to turn down the limic friction and or ramp up prefrontal cortex's Activation so there's a lot of stuff that can happen in the thalamus with sensory gating um for instance you could shut down that shell around the thalamus and allow more creative thinking by allowing more lateral connections these would be some of the those would be the experiments I'd want to do so they're in the subcortical quote unquote monkey brain but you could then look at what sorts of abstract thoughts and behaviors would arise from that rather than and and here I'm not pointing my finger at neural Link at all but there's this obsession with neocortex but I I'm going to well I might lose a few friends but I'll hopefully gain a few and and also um one of the reasons people spend so much time in neocortex yes I have a fact in an opinion one fact is that you can image there and you can record there right now the two Photon and one Photon microscopy methods that allow you to image deep into the brain still don't allow you to image down really deep unless you're jamming prisms in there and endoscopes and then in the endoscopes are very narrow so you're getting very you know it's like looking at the bottom of the ocean through a through a spotlight yeah and so you much easier look at the waves up on top right so let's face it folks a lot of the reasons why there's so many recordings in layer 2 three of Cortex with all this Advanced microscopy is because it's very hard to image deeper now the microscopes are getting better and thanks to amazing work mainly of Engineers and chemists and physicists let's face it they're the ones who brought this revolution in Neuroscience in the last 10 years or so you can image deeper but we don't really that's why you see so many reports on layer 2 three the other thing which is purely opinion and I'm not going after anybody here but is that as long as there's no clear right answer it becomes a little easier to do creative work in a structure where no one really knows how it works so it's fun to probe around because anything you see is novel if you're going to work in the thalamus or the pulvinar or the hypothalamus so these structures that have been known about since the' 60s and 70s and really since the you know centuries ago you are dealing with exist you have to combat existing models yeah and where whereas in cortex no one knows how the thing works the neocortex six layer cortex and so L more room for Discovery there's a lot more room for Discovery and I'm not calling anyone out I love cortex we've published some papers on cortex it's super interesting but I I think with the tools that are available nowadays and where people are trying ahead of of not just reading from the Brain Monitoring activity but writing to the brain I think we really have to be careful and we need to be thoughtful about what are we trying to write what script are we trying to write because there are many brain structures for which we already know what scripts they write and I think there's tremendous value there I don't think it's boring the fact that they act like machines makes them predictable those are your zeros and ones yeah let's start there but let what they're what's sort of happening in this field of writing to the brain is there's this idea and again I want to be clear I'm not pointing at neuralink I'm mainly pointing at the the neocortical jockeys out there that you go and you observe patterns and then you think replaying those patterns is going to give rise to something interesting yeah I I should call out one experiment or two experiments which were done by susumu tagawa Nobel Prize winner from MIT done important work in memory and Immunology of course is where you got Nobel as well as Mark morford's Lab at UC San Diego they did an experiment where they monitored a bunch of neurons while an animal learns something MH then they captur those neurons through some molecular tricks so they could replay the neurons mhm so now there's like perfect case scenario it's like okay you monitor the neurons in your brain then I say okay neurons 1 through 100 were played in the particular sequence so you know the space time you know the keys on the piano that were played that gave rise to the song which was the behavior and then you go back and you reactivate those neurons except you reactivate them all at once like slamming on all the keys once on the piano and you get the exact same behavior so the SpaceTime code may be meaningless for some structures now that's freaky that's a scary thing because what that means is that all the space-time firing in cortex the space part May matter more than the time part so you know rate codes and SpaceTime codes we don't know and you know I'd rather have I'd rather deliver more answers in this discussion questions but I think it's an important consideration you're saying some of the magic is in the early stages of what the the closer to the raw information that bra ising I believe so you you know the stimulus you know the neuron then codes that stimulus so you know the transformation when I say this for those you that don't think about sensory Transformations it's like I can show you a red um Circle and then I look at how many U times the neuron fires in response to that red circle and then I show the red circle a bunch of times green circle see if it changes and then essentially the number of time that is the the transformation you've converted red circle into like three Action potentials you know beep beep or whatever you want to call it you know for those that think in sound space so that's what you've created you know the transformation and you march up the it's called the Nur axis as you go from the periphery up into the cortex and we know that and I know Lisa um Feldman Barrett or is it Barrett Feldman Barrett f F excuse me um Lisa that um talked a lot about this that you know birds can do sophisticated things and whatnot as well but humans there's a strong what we call seiz a lot of the processing is moved up into the cortex and out of these subcortical areas but it happens nonetheless and so as long as you know the Transformations you are in a perfect place to build machines or add machines to the brain that exactly mimic what the brain wants to do which is take events in the environment and turn them into internal firing of neurons so the Mastery of the brain can happen at their early level you know another perspective of it is uh you saying this means that humans aren't that special if we look at the evolutionary time scale the leap to intelligence is not that special so like the extra layers of abstraction isn't where most of the magic happens of intelligence which gives me hope that maybe if that's true that means the evolution of intelligence is not that rare of an event I certainly hope not um Al so you you hope there's I I hope there are other forms of intelligence I mean I think what humans are really good at um and here I want to be clear that this is not a formal model but what humans are really good at is taking that um plasma barbell that we were talking about earlier and not just using it for analysis of space like the your mediate environment but also using historical information like I can read a book today about the history of Medicine I happen to be doing that lately for some stuff I'm researching and I can take that information and if I want I can inject it into my plans for the future other animals don't seem to do that over the same time scales that we do now it may be that the Chipmunks Are All Hiding little like notebooks everywhere in the form of like little dirt castles or something that we don't understand I mean the waggle dance of the bee is in the most famous example bees come back to the hive they Orient relative to the honeycomb and they waggle a guy down in Australia named seren vissan who studied this and it's really interesting no one under really understands it except he understands it best the bee Waggles at a in a couple ways relative to the orientation of the honeycomb and then all the other bees see that it's Visual and they go out and they know the exact coordinate system to get to the to the source of whatever it was the food and bring it back and he's done it where they isolate the bees he's changed the visual flight environment all this stuff they are communicating and they're communicating something about something they saw recently but it doesn't extend over very long periods of time the same way that you and I can both read a book or you can recommend something to me and then we could Converge on a set of ideas later and uh In fairness because she was the one that said it and I didn't and I hadn't even thought of it um when you talked to Lisa on your podcast she brought up something beautiful which is that I never really occurred to me and I was sort of embarrassed that it hadn't but it's really beautiful it and Brilliant which is that you know we don't just encode senses in the form of like color and light and sound waves and taste but ideas become a form of sensory mapping and that's where the cool you know the really really cool and exciting stuff is but we just don't understand what the receptive fields are for ideas what's an idea receptive field and how they're communicated between humans because we seem to be U to be able to encode those ideas in some kind of way it's yes it's taking all the wrong information and the internal physical States the the that sensory information put into this concept blob that we in a store and then we're able to communicate that yeah your abstractions are different than mine I actually think the comment section you know on on social media is a beautiful example of where the abstractions are different for different people so much of the misunderstanding of the world yeah is because of these abst these idea receptive Fields they're not the same whereas I can look at a photo receptor neuron or factoring neuron or a V1 neuron and I am certain I would bet my life that yours look and respond exactly the same way that Lisa's do and mine do but once you get Beyond there it gets tricky and so when you say something or I say something and somebody gets upset about it or even happy about it their concept of that might be quite a bit different they don't really know what you mean they only know what it means to them yeah so from a neurolink perspective it makes sense to optimize the control and the augmentation of the of the more primitive uh circuitry so like the the stuff that is closer to the raw sensory information go deeper if they I think go deeper into the brain and I and to be fair so Matt McDougall um who's a neurosurgeon neurolink and also clinical neurosur great guy brilliant they have amazing people I have to give it to them they have been very cryptic in recent years their website was just like a like neur like nothing there that you know they know they really know how to do things with style and um and they've upset a lot of people but that's good too um but Matt is there I know Matt he actually came up through my lab at Stanford although he you know he was a neurosurgery resum we spent time in our lab he actually came out on the shark dive and did great white shark diving with my lab to collect the VR that we use in our fear stuff I've talked to Matt and I think you know he and other folks there are hungry for the deeper brain structures the problem is that damn vasculature all that blood supply it's right it's not trivial to get through and down into the brain without damaging the vasculature in the neocortex which is on the outer crust but once you start getting into the thalamus and closer to some of the main arterial sources you really risk getting massive bleeds and so it's it's a it's an issue that can be worked out it just is hard this just maybe be nice to educate I'm showing my ignorance so the the smart stuff is is on the surface so I didn't realize this I didn't quite realize because you keep saying deep yeah so so like the the early stages are deep yeah in in actually physically in the brain yeah so the way to um you know of course you got your your deep brain structures they're involved in breathing and heart rate and kind of lizard brain stuff and then on top of that this is the the um the the model of the brain that no one really subscribes to anymore but anatomically it works and then on top in mammals and then on top of that you have the lyic structures which gate sensory information and decide whether or not you're going to listen to something more than you're going to look at it or you're going to split your attention to both kind of sensory allocation stuff um and then the neocortex is on the outside um and that is where you get a lot of this abstraction stuff and now not all cortical areas are doing abstraction some like visual area one auditory area one they're just doing concrete uh representations but um as you get into the higher order stuff that when you start hearing names like infro parietal cortex and you know when you start hearing multiple names in the same then you're talking about higher order areas but actually there's a an important experiment that um that drives a lot of what people want to do with brain machine interface and that's the work of Bill Nome who is at Stanford and Tony maavin who's at runs the center for neural science at NYU this is a wild experiment and I think it might freak a few people out if they really think about it too deeply but um anyway here he goes there's an area called Mt in the cortex and if I showed you a bunch of dots all moving up and this is is what they this is what Tony and Bill and some of the other people um in that lab did way back when is they show a bunch of dots moving up somewhere in Mt there's some neurons that respond they fire when the neurons move up and then what they did is they started varying the coherence of that motion so they made it so only 50% of the dots moved up and the rest move randomly and that neuron fires a little less and eventually it's random and that neuron stops firing because it's just kind of dots moving everywhere it's awesome and there's a systematic map so that other neurons are responding and things moving down and other things are responding left and other things are moving right okay so there's a map of direction space you okay well that's great you could leion Mt animals lose the ability to do these kind of coherence discrimination or Direction discrimination but the Amazing Experiment the one that just is kind of eerie is that they lowered a stimulating electrode into Mt found a neuron that responds to when dots go up but then they silence that neuron and and sure enough the animal doesn't recognize the neurons are going up and then they move the dots down they stimulate the neuron that responds to things moving up and the animal responds because it can't speak it responds by doing a lever press which says the dots are moving up so in other words the sensory the dots are moving down in reality on the computer screen they're stimulating the neuron that responds to dots moving up and the perception of the animal is that dots are moving up which tells you that your perception of external reality absolutely has to be a neuronal abstraction it is not tacked to the movement of the dots in any absolute way your perception of the outside world depends entirely on the activation patterns of neurons in the brain and you you can hear that and say well duh because if I stimulate you know the stretch reflex and you kick or something or whatever you know the knee F Lex and you kick of course there's a neuron that triggers that but it didn't have to be that way yeah because a the animal had prior experience B you're way up in the you know higher order C cortical areas what this means is that and I generally try to avoid conversations about this kind of thing but what this means is that we are constructing our reality with this SpaceTime firing the zeros and ones and it doesn't have to have anything to do with the actual reality and the animal or person be absolutely convinced that that's what's happening are you familiar with the work of Donald Hoffman so he's uh uh so he makes an evolutionary argument that's not important of that we our brains are completely detached from reality in the sense that he makes a radical case that we have no idea what physical reality is and in fact it's drastically different than what we think it is oh my so so he goes scary so he doesn't say like there's just cuz you're kind of implying there's a there's a gap there there might be a gap with constructing an illusion and then maybe using uh communication to maybe uh create a consistency that's sufficient for our human collaboration whatever or mammal you know just maybe even just life forms are construct a consistent reality that's may be detached I mean that's really cool that neurons are constructing that like that you can prove that this is what you're science at his best vision science but he says that like our brain is actually just lost its on the on the on the path of evolution to where we're no long we're just playing games with each other in constructing realities that allow our survival but it's it's it's completely detached from phys IAL reality like we're we're missing a lot we're missing like most of it if not all of it well this was um it's it's fascinating because I just saw the Oliver Sachs documentary there's a new documentary out about his life and there's this one part where he's like I've spent part of my life trying to imagine what it would like to be be uh to be a bat or something to see the world through the life you know the sensory apparat of a bat and he did this with his these patients that were locked into these horrible syndromes that to pull out some of the the beauty of their experience as well not just communicate the suffering although the suffering too and as I was listening to him talk about this I started to realize it's like what you know like they're these mantis shrimps that can see 60 shades of pink or something and they they see the stuff all the time and animals they can see UV light every time I learn about an animal that can sense other things in the environment that I can't like heat sensing what not I don't crave that experience the same way saxs talked about craving that experience but it does throw another penny in the jar for what you're saying which is that it could be that most if not all of what I perceive and believe is just um a a neural fabrication and that For Better or For Worse we all agree on enough of the same neural Fabrications in the same time and place that we're able to function not only that but we agree with the things that are trying to eat us uh enough to where we don't they don't eat us meaning like that it's not just us humans you know right I see because it's interactive it's interactive so like so like uh now I think it's a really um nice thought experiment I think because uh Donald really frames it in a scientific like he makes a hard like as hard as our discussion has been now he makes a hard scientific case that we don't know about reality uh I think that's a little bit uh hardcore but I I think it's I think is hardore is hardore I think it's a good thought experiment that kind of uh cleanses the pallet of the confidence we might have about uh about cuz we are operating in this abstraction space and you know and uh you know the sensory spaces might be something very different and and it's kind of interesting to think about if if you start to go into the realm of neuralink or start to talk about just everything you've been talking about with dream states and psychedelics and stuff like that which part of the which layer can we control and play around with to maybe look into a different slice of reality it you know you just got to do the experiment the key is to just do the experiment in the most ethical way possible you just I mean that's the beauty of experiments this is why um you know there there there's wonderful theoretical Neuroscience Happening Now make to make predictions and but the but that's why experimental science is so wonderful you can go into the laboratory and poke around in there and be a brain Explorer and and listen to and write to neurons and when you do that you get answers you don't always get the answers you want but that's you know that's the beauty of it I I think when you were saying um this thing about reality and the Donald Hoffman model I was thinking about children you know at um like when I have an older sister Shir uh she's very sane um uh but when she was a kid she had an imaginary friend yeah and she would play with this imaginary friend and it had there was this whole there was a consistency this friend was like it was Larry lived in a purple house Larry was a girl it was like all this stuff that a child a young child wouldn't have any issue with and then one day she announced that Larry had died right and it wasn't dramatic or traumatic and that was it and she just stopped and I always wonder what that um neurodevelopmental event was that um a kept her out of a a psychiatric ward had she got you know kept that imaginary friend but but it I it's also there was something kind of sad to it I think the way it was told to me because I'm the younger brother I didn't I wasn't around for that but my my dad told me that you know there was a kind of a sadness because it was this beautiful reality that had been constructed and so we kind of w i i wonder as you're telling me this whether or not you know as adults we try and create as much reality for children as we can so that they can make predictions and feel safe because the ability to make predictions is a lot of what keeps our autonomic arousal in check I mean we go to sleep every night and we give up total control and that should frighten us deeply but you know unfortunately autonomic rousel Yanks us down under and we don't negotiate too much so you sleep sooner or later um I don't know um I was a little worried we'd get into discussions about the nature of reality because I'm I it's interesting in the laboratory I'm a very much like what's the experiment what would the you know what's the analysis going look like what mutant Mouse are we going to use what what what experience are we going to put someone through but I think it's wonderful that in 2020 we can finally have discussions about this stuff and look kind of peek around the corner and say well neur link and people others who are doing similar things are going to figure it out they're going to the the answers will show up and we just have to be open to interpretation do you think there could be an experiment uh centered around Consciousness I mean you're plugged into the Neuroscience Community I think for the longest time the quote unquote c-word was totally not uh was almost anti-scientific but now more and more people are talking about Consciousness Elon is talking about Consciousness AI folks are talking about Consciousness it's it's still nobody knows anything but it feels like a legitimate domain of inquiry that's hungry for a real experiment so I have fortunately three short answers to this um uh the first one is a I'm not I'm not particularly sucin I I agree that no the joke I always tell is um there two things you never want to say to a scientist one is uh what do you do and the second one is um take as much time as you need and you definitely don't want to say them in the same sentence um I have three short answers to it so there's a um there's a cynical answer kind of uh and it's not one I enjoy giving Which is that um if you look into the 70s and back at the 1970s and 1980s and even into the early 2000s there were some very Dynamic um very impressive speakers who were very smart in the field of Neuroscience and related fields who thought hard about the Consciousness problem and fell in love with the problem but uh overlooked the fact that the technology wasn't there yeah so um I admire them for falling in love with the the problem but they gleaned tremendous taxpayer resources essentially for nothing and these people know who they are some of them are alive some of them aren't I'm not referring to Francis Crick who was brilliant by the way and thought the claustrum was involved in Consciousness which I think is a great idea it's this obscure structure that no one's really studied people are now starting to study it so I think Francis was brilliant and wonderful but there it you know there were books written about it it makes for great television stuff and thought around the table or after a couple glasses of wine or whatever um it's an important problem nonetheless and so I think I do think the Consciousness the issue is it's not operationally defined right that psychologists are much smarter than um a lot of uh heart scientists in that for the following reason they put operational definitions they know know that psychology if we're talking about motivation for instance they know they need to put operational definitions on that so that two Laboratories can know they're studying the same thing the problem with Consciousness is no one can agree on what that is and this was a problem for attention when I was coming up so in the early 2000s people would argue what is attention is it spatial attention auditory attention is it and finally people were like you know what we agree have they agreed on that one I remember sort of I remember hearing people scream a lot of tension right they couldn't even agree on attention so I was coming up as a young graduate student I'm thinking like I'm definitely not going to work on attention and I'm definitely not going to work on Consciousness and I wanted something that I could solve or figure out I want to be able to see the circuit or the neurons I want to be able to hear it on the Audio I want to record from it and then I want to do gain of function and loss a function take it away see something change put it back see something change in a systematic way and that takes you down into the depths of some stuff that's pretty um uh plug and chug you know but you know I'll borrow from something in the the military because I'm fortunate to do some work with units from Special Operations and they have beautiful language around things because their world is not abstract and they talk about 3 meter targets 10 meter targets and 100 meter targets and it's not an issue of picking the 100 meter Target because it's more beautiful or because it's more interesting if you don't take down the 3 meter targets and the 10 meter targets first you're dead so that's a I think scientists could pay to you know adopt a more kind of military thinking in that in that sense the other thing that is really important is that just because somebody conceived of something and can talk about it beautifully and can glean a lot of um resources for it doesn't mean that it's LED anywhere so but this isn't just true of the Consciousness issue and I don't want to sound cynical but I could pull up some names of molecules that occupied hundreds of articles in the very Premier journals that then were later discovered to be totally moot for that process and biotech companies folded everyone and the lab pivots and starts doing something different with that molecule and nobody talks about it because as long as you're in the game we have this thing called Anonymous peer review you can't afford to piss off anybody too much unless you have some other funding stream and I have avoided battles most of my career but I pay attention to all of it and I've watched this and I don't think it's ego- driven I think it's that people fall in love with an idea I don't think there's any there's not enough money in science for people to sit back there rubbing their hands together you know the beauty of what neural link and Elon and and team because obviously he's very impressive but the the team as a whole is really what gives me great confidence in their mission is that he's already got enough money so it can't be about that he doesn't seem to need it at a level of uh I don't know him but it doesn't he doesn't seem to need it at a kind of an ego level or something I think it's driven by genuine curiosity and the team that he's assembled include people that are very kind of abstract neuro neocortex space-time coding people there're people like Matt who's a neurosurgeon you can't I mean you know you can't BS neurosurgery failures in neurosurgery are not tolerated so you have to be very good to exceptional to even get through the gate and he's exceptional and then they've got people like Dan Adams who was at UCSF for a long time he's a good good friend and known him for years um who is very concrete studied the vasculature in the eye and how it maps to the vasculature cortex when you get a team like that together you're going to have denters you're going to have people that are highlevel thinkers people that are coders when you get a team like that it no longer looks like an academic laboratory or even a field in science and so I think they're going to solve some really hard problems and again I'm not here they don't you know I have nothing in at stake with them but I think that's the solution you need a bunch of people who don't need first author papers who don't need to complete their PHD who aren't relying on outside funding who have a clear Mission and you have a bunch of people who are basically will adapt to solve the problem I like the analogy of the 3 meter Target and the 100 meter Target so the folks in neur link are basically many of them are some of the best people in the world at the 3 meter Target like that you mentioned Matt new surger like they're solving real problems there's no BS philos philosophical uh smokes and weed and look back at look at the stars but uh so both on Elon and because I think like this I think it's really important to think about the 100 meter and the 100 meter is not even not even 100 meter but like like the stuff behind the hill that's that's that's too too far away which is which is where I put Consciousness I'm maybe I tend to believe that uh Consciousness can be engineered I me part of the reason part of the the the business I want to build leverages that idea that Consciousness is a lot simpler that we've than we've been talking about well if if someone can simplify the problem that will be wonderful I mean the reason we can talk about something as abstract as face representations infusive form face area is because Nancy caner had the Brilliance to tie it to the um kind of lower level um statistics of visual scenes it wasn't cuz she was like oh I bet it's there that wouldn't have been interesting so people like her understand how to bridge that Gap and they put a tractable definition so so I just I that's what I'm begging for in science is a tractable definition this is what but I want people to sit in the I want people who are really uncomfortable with woow woo like Consciousness like high Lev stuff to sit in that topic and sit uncomfortably because it forces them to then try to ground and simplify it into something that's concrete because too many people are just uncomfortable to sit in the Consciousness room because there's no definitions it's like attention or or intelligence in the artificial intelligence Community but the reality is it's easy to avoid that room altoe which is what I mean there's analogies to everything you've said with the artificial intelligence Community with the Minsky and even Alan ing that talked about intelligence a lot and then they drew a lot of funding and then it crashed because they really didn't do anything with it and it was a lot of force of personality and so on but that doesn't mean the topic of the touring test and intelligence isn't something we should sit on and think like think like what is first of all I mean touring actually attempted this with a touring test he tried to make concrete this very question of intelligence it doesn't mean that we shouldn't Linger on it and uh for we shouldn't forget that ultimately that is what our efforts are all about in the artificial intelligence community and in the people whether it's Neuroscience or whatever bigger umbrella you want to use for understanding the mind the goal is not just about understanding layer two or three of the vision it's it's to understand Consciousness and intelligence and maybe create it or or just all the possible biggest questions of our universe that's that's ultimately the dream absolutely and I think what I really appreciate about appreciate about what you're saying is that everybody whether or not they're working on a kind of low-level synapse that's like a reflex in the musculature or something very high level abstract can benefit from looking at those who prefer three you know everyone's going after a 3 meter 10 m and 100 meter Targets in some sense but to be able to tolerate the discomfort of being in a conversation where there are real answers where the zeros and ones are are known zeros and ones those the equivalent of that in the nervous system and also as you said for the people that are very much like oh I can only trust what I can see and touch those people need to put themselves into the discomfort of the high level conversation because what's missing is conversation and conceptualization of things at multiple levels I think one of the this is um I I don't gripe about my lab's been fortunate we've been funded from the start and we've been happy um in that in that regard and lucky and we're grateful for that but I think one of the challenges of research being so expensive is that there isn't a a lot of time especially nowadays for people to just convene around a topic because there's so much emphasis on productivity um and so there there actually believe it or not there aren't that many Concepts formal Concepts in Neuroscience right now the last 10 years has been this huge influx of tools and so people have been neural circuits and probing around and connectomes it's been wonderful but you know 10 20 years ago when the Consciousness stuff was more prominent the seword as you said um what was good about that time is that people would go to meetings and actually discuss ideas and models now it's sort of like demon it's sort of like demonstration day at the school science fair where everyone's got their thing and you some stuff is cooler than others but um I think we're going to see a shift I'm grateful that we have so many computer scientists and theoreticians and um or theorists I think they call themselves um somebody tell me what the difference is someday um and you know psychology and even dare I say philosophy you know these things are starting to converge we you know Neuroscience that the name Neuroscience there wasn't even such a thing when I started graduate school or as a postto it was neurophysiology you're a neur anatomist or what now every it's sort of everybody's invited and that's beautiful that means that something's useful is going to come up all this and there's also tremendous work of course happening on for the treatment of disease and we shouldn't Overlook that that's where you know ending you know eliminating reducing suffering is also a huge initiative in Neuroscience so there's a lot of Beauty in the field but the Consciousness thing continues to be a uh it's like an exotic bird it's like no one really quite knows how to handle it and it dies very easily well yeah I I think also from the AI perspective I so I view the brain as less sacred uh I think from a neuroscience perspective you're a little bit more sensitive to BS like BS narratives about the brain or whatever I'm a little bit more uh comfortable with just poetic BS about the brain as long as it helps engineer intelligence systems well you know what I mean well and and I have to you know I confess um ignorance when it comes to you know most things about coding and I'm I'm have some quantitative ability but I don't have strong quantitative leanings and so I I know my limitations too and so I I think the Next Generation coming up you know a lot of the students at Stanford are really interested in quantitative models and theory and Ai and I remember when I was coming up um a lot of the people who were doing work ahead of me kind of rolled my eyes at some of the stuff they were doing um including some of their personalities although I have great many great um senior colleagues everywhere the world so it's the way of the world so nobody knows what it's like to be a you know a young graduate student in 2020 except the young graduate student so I I know what I I'm I know there are a lot of things I don't know and um in addition to why I do a lot of public education increase scientific literacy and neuroscientific thinking Etc a big goal of mine is to try and at least pave the way so that these really brilliant and forward thinking um younger scientists can make the biggest possible dent and make what will eventually be all us old guys and gals look stupid I mean that's that's what we were all trying to do that's what we were trying to do so yeah so from the highest possible topic of Consciousness to the to the lowest level uh topic of David goggin's uh let's I don't know if it's low lowlevel he's high perform high performance but like low like there's I don't think David has a has any time for philosophy let's just put it this way uh well it's I mean I think we can tack it to what we were just saying in a in a in a meaningful way which is whatever goes on in that abstraction part of the brain he's figured you know he's figured out how to dig down in whatever the lyic friction yeah he's figured out how to grab a hold of that Scruff it and send it in the direction that he's decided it needs to go and what's Wild is that he's what we're talking about is him doing that to himself right he's it's like he's scruffing himself and directing himself in a particular direction and sending himself down that trajectory and he what's beautiful is that he acknowledges that that process is not pretty it doesn't feel good it's kind of horrible at every level but he's created this re rewarding element to it and I think that's what's so it it's so admirable and it's what so many people crave which is regulation of the self at that level and he practices I mean there's a ritual to it there's a every single day like no exceptions there's a practice aspect to the suffering that he goes through it's principled suffering principled suffering it is and I mean I just I mean I admire all aspects of it including him and his girlfriendwife I'm not sure she'll probably know this fiance wonderful person asking no no we've only commun I um we've only I've only communicated with her um by a text about some stuff um I was asking David but yeah they they clearly have formed a powerful team yeah um and it's beautiful thing to to see people working in that kind of synergy it's inspiring to me same as with Elon that guy like David Goggins can find love uh that that you find a thing that works which gives me hope that like whatever whatever flavor of crazy I am you can always find another thing that works with that but I I I've had the so maybe let's trade goggin stories uh you from a neuroscience perspective me from a uh self-inflicted pain perspective I somehow found myself in communication with David about some challenges that I was undergoing um one of which is we were communicating every single day email phone about a particular 30-day challenge I did that stretched for a longer of uh push-ups and pull-ups you made a call out on social media yeah social media actually I think that the point I I knew of you before but that's where I started tracking some of what you were doing with these physical challenges and I um the hell's wrong with that guy well no I think I actually I don't often comment on people's stuff but I think I commented something like uh neuroplasticity loves a non-negotiable rule no I said a non-negotiable contract because at the point where yeah neural neurop plasticity really loves a non-negotiable contract because you know and I've said this before so forgive me but you know the brain is doing analysis of duration path and outcome and that's a lot of work for the brain and more that it can pass off duration path and outcome to just reflex the more energy and and it can allocate to other things so if you decide there's no negotiation about how many push-ups how far I'm going to run how many days how many pull-ups Etc you actually have more energy for push-ups running and pull-ups and when you say neuroplastic you mean like the brain once the decision is made it'll start rewiring stuff to to make sure that this we can actually make this happen that's right I mean so much of what we do is reflexive at the level of just core circuitry breathing heart rate all that that boring stuff digestion but then there's a lot of reflexive stuff like how you drink out of a a mug of coffee that's reflexive too but that you had to learn at some point in your life earlier when you were very little analyzing duration path and outcome and that involved a lot of top down processing with the prefrontal cortex but through plasticity mechanisms you now do it so when you take on a challenge provided that you understand the core mechanics of how to you know run push-ups and and pull and whatever else you decided to do once you set the number and the duration and all that then you all you have to do is just go but people get caught in that tide poool of just well do I really have to do it how do I not do that what if I get injured what if I you know can I sneak at this so that you know and that's work yeah and to some extent I I look I not David goggin obviously um nor nor do I claim to understand his process U partially you know um but maybe a little bit which is that it's clear that by making the decision there's more resources to devote to the effort of the actual execution well that's a really like what you're saying was not a lesson that was obvious to me and it's still not obvious it's something I really work at which is there is always an option to quit and I mean that's something I really struggle with I mean I've quit some things in my life it's like stupid stuff and uh one lesson I've learned is if you quit once it opens the door that like it's really valuable to trick your brain into thinking that you you're going to have to die before you quit like it's actually really convenient so actually what you're saying is very profound but you shouldn't intellectualize it like it took me time to develop like out psychologically in ways that I think I would be another conversation CU I'm not sure how to put it into words but it's really tough on me to uh to do certain parts of that challenge which is a huge is a huge output the the number that see I was I thought it would be the number would be hard but it's not it's the entirety of it especially in the early days was just spending I'm kind of embarrassed to say how many hours this took so I I didn't say publicly how many hours cuz people I I knew people would be like don't you aren't you supposed to do other stuff well it's um hell are you doing again I don't want to speculate too much about but occasionally David has said this publicly where people will be like don't you sleep or something and his process used to just be that he would just block delete you know like gone but it's it's actually um it's it's a super interesting topic and because self-control and directing our actions and the role of emotion and quitting these are these are vital to The Human Experience and they're vital to performing well at anything and at a high obviously at a super high level being able to understand this about the self is crucial um so I have a friend who was also in the teams his name is Pat dosset he did nine years in the SEAL Teams um and in a similar way there's there's a lore about him among Team guys um because of a kind of funny challenge he gave himself which was so he and I swim together although he swims further up front than I do um and he's very patient um but you know he was on a he was assigned when he was in the teams to a position that gave him a little more time behind the desk than he wanted and not as much time out out in deployments although he did deployments um so he didn't know what to do at that time but he thought about it and he asked himself what what does he hate the most mhm and it turns out the thing that he hated doing the most was bear crawls you know walking on your hands and knees so he decided to Bear crawl for a mile for time so he was Bear crawling a mile a day right and I thought that was an interesting example they gave because you know like why pick the thing you hate the most and I think it Maps right back to lyic friction it's the thing that creates the most limic friction and so if you can overcome that then there's carryover and I think the notion of carryover has been talked about psychologically and kind of in the self-help space like oh if you run a marathon it's going to help you in other areas of life but will it really will it well I think it depends on whether or not there's a lot of lyic friction because if there is what you're exercising is not a circuit for bear crawls or a circuit for pull-ups what you're doing is you're exercising a circuit for top- down control and that circuit was not designed to be for bear crawls or pull-ups or coding or waking up in the middle of the night to do something hard that circuit was designed to override lyic friction and so neural circuits were designed to generalize right the stress response to an incoming threat that's a physical threat was designed to feel the same way and be the same response internally as the threat to an impending exam or divorce or marriage or whatever it is that's stressing somebody out and so neural circuits are not designed to be for one particular action or purpose so if you can as you did if you can train up top beond control under conditions of the highest limbic friction that when the desire to quit is at its utmost either because of fatigue or hyperarousal being too stressed or too tired you're you're learning how to engage a circuit and that circuit is forever with you and if you don't engage it you it sits there but it's atrophied it's not it's like a plant that doesn't get any water and a lot of this has been discussed in self-help and growth mindset and all these kinds of ideas that Circle the internet and social media but when you start to think about how they map to neural circuits I think there's some utility because what it means is that the lyic friction that you'll experience in I don't know maybe some future relationship to something or someone it will it's a category of neural processing that should immediately click into place it's just like the lyic friction you experienced trying to engage in the God knows how many uh push-ups pull-ups and and running you uh you know runs you were doing 25,000 so folks if if Lex does this again more comments more likes no well this the problem with you getting more followers is you're going to get more actually I should say that's the benefit I I don't know maybe it's not politically correct for me to ask but like there is this uh stereotype about Russians being you know like correct no like like like uh like being really um you know durable and and you know I I started going to that Russian B that way back uh before Co and um they could tolerate a lot of heat you know and and they would sit very stoic you know no one was going oh it's hot in here they just kind of like ease into it um so maybe there's something there who knows there might be something there but it could be also just personal I just have some I found myself everyone's different but I've found myself to be able to do something unpleasant for very long periods of time like I'm able to shut off the mind and I don't think that's been fully tested and I monkey mind or the supercomputer uh well it's interesting I mean um which mind is which mind tells you to quit exactly limic limic friction tells you well limic friction is the source of that but what who are you talking with exactly so there's a um we can uh put something very concrete to that so there's a paper publish in cell you know super top tier Journal uh two years ago um looking at f and this was in a visual environment of trying to swim forward toward a a Target and a reward and it was a really cool experiment because they manipulated uh virtually the visual environment so um the same amount of effort was being expended every time but sometimes the perception was you're making forward progress and sometimes the perception was you're making no progress because stuff wasn't Drifting by meant no progress so you can be swimming and swimming and know making progress and it turns out that with each bout of effort there's a epinephrine and norepinephrine is being released in the brain stem and glea the what traditionally were thought of a support cells for the neurons but they do a lot of things actively too are measuring the amount of EP epinephrine and norepinephrine in that circuit and when it exceeds a certain threshold the glea send inhibitory signals that shut down top down control they literally it's the quit you stop there's no no more it's you quit enduring it can be rescued endurance can be rescued with dopamine uh be so that's where the subjective part really comes into play so you quit because um you've learned how to turn that off or you've learned how to ro some people will reward the pain process so much that friction becomes the reward and I you know when you talk about people like goggin and other people I know from Special Operations and people have gone through Cancer Treatments three times you hear about you know just when you hear about people the Victor Frankle stories I mean you hear about Nelson Mandela you hear about these stories I'm sure the same process is involved again this speaks to the generalizability of these processes as opposed to a neural circuit for a particular action or cognitive function so I think um you have to learn to subjectively self-reward in a way that replenishes you uh goggin talks about eating Souls it's a very dramatic example in his mind apparently that's a form of reward but it's not just a form of reward where you're it's like a you're picking up a a trophy or something it's it's actually it gives energy it's a reward that gives more neural energy and I'm defining that as more dopamine to suppress the nor adrenaline adrenaline circuits in the brain Stone so ultimately maps of that yeah he creates enemies he's always fighting enemies I never I think I have enemies but there are usually just versions of me inside my head uh so I I thought about through that 30-day challenge I tried to come up with like fake enemies it wasn't working the only enemy I came up with is David well now you have you certainly have a a a form formidable adversary in this one I don't care I'm David I'm willing to die on this one so let's go there uh but well let's hope you you both uh uh both survive this um this one but my problem is the physical there's uh so everything we've been talking about in the mind there's a physical aspect that's just practically difficult which is like I can't like you know when you injure yourself at a certain point like you just can't function or you're doing more damage you're talking about it taking yourself out of running for yeah um for the the rest of your life potentially or like you know or for years so you know I'd love to avoid that right there's just like stupid physical stuff that you just want to avoid you want to keep it purely in the mental and if it's purely in the mental that's when the race is interesting but yeah the the the problem with these physical challenges as as David has experienced I mean it has a toll on your body I tend to think of the mind is Limitless and the body is kind of unfortunately quite limited well I think the key is to dynamically control your output and that can be done by reducing effort which doesn't work for for throughout but also by um restoring through these uh subjective reward processes and and we don't want to go down the rabbit hole of why this all works but these are ancient Pathways that were designed to bring resources to an animal or to a person through foraging for hunting or mates or water all these things and they work so well because they're down in those uh uh circuits where we know the zeros and ones and that's great because it can be subjective at the level of oh I reached this one uh Milestone this one horizon this one 3 meter Target but if you don't reward it you it's just effort if you do self-reward it it's effort minus one in terms of the adrenaline output I have to uh ask you about this you're one of the great communicators in science I'm really big fan of your enjoying in terms of like this the educational stuff you putting it in on Neuroscience thank you what's the uh do you have a philosophy behind it or is it just uh an instinct oh Unstoppable Force do you have a like what's your thinking because it's rare and it's exciting I'm I'm I'm excited that you know uh somebody from Stanford so I okay I'm in multiple places in the sense of like where my interests lie and one you know politically speaking academic institutions are Under Fire uh you know for many reasons we don't need to get into I get into it in a lot of other places but I believe in uh in places like Stanford and places like MIT as uh one of the most magical institutions for inspiring people to dream people to build the future I mean it's I I believe that it is a really special these universities are really special places and so it's always exciting to me when uh somebody as inspiring as you represents those places so it makes me proud that uh somebody from Stanford is is like somebody like you is representing Stanford so uh maybe you could speak to what's how did you come to be who you are in being being a communicator well first of all thanks for the the kind words especially um coming from you I I think um Stanford is an amazing place as is MIT and it's such a MIT is better by the I'll let it out anything you say at I have many friends at Mi yeah you know hi Ed smarter friends yeah Ed boen is is is is uh best in CL you know among the Best in Class there's some people not me that can hold hold a candle to him but not many maybe one or two I think the the great benefit of being in a place like MIT or Stanford um is that when you look around you know that the the average is very high right that you have many best-in class among the you know one or two or three best in the world at what they do and um It's a Wonderful privilege to be there and uh one thing that I think also uh makes them and other universities like them very special is that there's an emphasis on what gets exported out of the University what you know not keeping it Ivory Tower and really trying to keep an eye on what's needed in the world and trying to do something useful um and I think the proximity to Industry and Silicon Valley and in the Boston area in Cambridge also lends itself well to that and there are other institutions of too of course so um the reason I got involved in educating on social media was actually because of a a Pat dosset the be mile bear call Guy it was at the turn of 2018 to 2019 uh we had formed a a a good friendship we were we he talked to me into doing these early morning um cold water swims I was learning a lot about pain and suffering but also the beauty of cold water swims and and we were talking one morning and he said um so what are you going to do to serve the world in 2019 it's like that's the way that like a Tex and former seal talks like we're just literally what are you going to do to serve the world in 2019 like well I run my lab it's like no no no what are you going to do that's new and he wasn't forceful in it but I was like that's an interesting question I said well um if I had my way I would just you know teach people everyone about the brain because I think it's amazing he goes we'll do it and I all right he goes Shake on it so we did it you know and so I started putting out these posts and it's grown into um to include a variety of things but you asked about a governing philosophy so I want to increase interest in the brain and in the nervous system and in biology generally that's one major goal I'd like to increase scientific literacy which can't be rammed down people's throats of talking about how to look at a graph and statistics and you know zc scores and P values and uh genetics it has to be done gradually in my opinion um I want to put valuable tools into the world mainly tools that map to things that we're doing in our lab so these will be tools um centered around how to um understand and direct one's states of mind and body so reduce stress raise one's stress threshold so it's not always just about being calm sometimes it's about learning how to tolerate not being not calm um raise awareness for mental health I me there's a ton of micro missions in this but it all really Maps back to you know like the eight and 10-year-old version of me which is I used to spend my weekends when I was a kid reading about weird animals and I had this obsession with like medieval weapons and stuff like catapults and and then I used to come into school on Monday and I would ask if I could talk about it to the class and teach and I just it's really I I promise and some people might not believe me but it's really I don't really like being the point of focus I just get so excited about these gems of that I find in the world in books and in experiments and in discussions with colleagues and discussions with people like you and and around the universe and I can't just compulsively I got to tell people about it so I try and package it into a form that people can access you know I think if I've uh I think the reception has been really wonderful Stanford has been very supportive um thankfully um I've given done some podcast even with them and they've reposted some stuff on social media it's a precarious place to put yourself out there as a research academic I think some of my colleagues both locally and elsewhere probably wonder if I'm still serious about research which I absolutely am and I also acknowledge that um you know their research and the the research coming out of the field needs to be talked about and not all scientists are good at translating that into a language that people can access and I don't like the phrase dumb it down what I like to do is take a concept that I think people will find interesting and useful and offer it sort of like a um you would offer food to somebody visiting your home you're not going to cram frog RA in their face you're going to say like do you want a cracker like and they say yeah and like do you want something on that Cracker like do you like cheese like yeah like do you want swiss cheese or you want that really like stinky like French I don't like cheese much but um or do you want frog like what's that like so you're trying the best information prompts more questions of Interest not questions of confusion but questions of interest and so I feel like one door opens then another door opens then another door opens and pretty soon um the image in my mind is you create a bunch of neuroscientists who are thinking about themselves neuroscientifically and I don't begin to think that I have all the answers at all um I cast a neuroscience sometimes a little bit of a psychology lens onto what I think are interesting topics and you know I um you know someday I'm going to go into the ground or the ocean or wherever it is I end up and um uh I'm very comfortable with the fact that not everyone's going to be happy with how I deliver the information but I would hope that people would feel um like some of it was useful and meaningful and got them to think a little bit harder since you mentioned going into the ground and uh Victor Franco man search for meaning I read that I reread that book uh quite often what uh let me ask the uh the big ridiculous question about life uh what do you think is the the meaning of it all like and maybe why do you do you mention that book from a psychologist perspective which Victor Franco was or do you do you ever think about the the bigger philosophical questions it raises about meaning what's and the meaning of it all one of the great challenges in assigning a good you know giving a good answer to the question of like what's the meaning of life is um I think Illustrated best by the Victor Frankle example although there are other examples too which is that our sense of meaning is very elastic in time and space and I'm I'm uh we talked a little bit about this earlier but it's amazing to me that somebody locked in a or concentration camp can bring the Horizon in close enough that they can then micr slice their environment so that they can find rewards and meaning and power and Beauty even in a little square box or or a horrible situation and I think this is really speaks to one of the most important features of the human mind which is we could do let's take two opposite extremes one would be let's say the alarm went off right now in this building and the building started shaking our vision our hearing everything would be tuned to this SpaceTime bubble for those moments MH and everything that we would process all that would matter the only meaning would be get out of here safe figure out what's going on contact loved ones Etc if we were to sit back totally relaxed we could do the you know I think it's called pale blue dot thing or whatever where we could imagine ourselves in this room and then they were in the United States and this continent and the Earth and then peering down us and all of a sudden you get back it can seem so big that all of a sudden it's meaningless right if you see yourself as just one brief glimmer in all of time and all of space you go to I don't matter and if you go to oh every little thing that happens in this text thread or this you know comment section on YouTube or Instagram your SpaceTime bubble is Tiny MH then everything seems inflated and the Brain will contract and dilate it SpaceTime yeah vision and time but also sense of meaning and that's beautiful and it's what allows us to be so dynamic in different environments and we can pull from the past and the present and future um it's why examples like Nelson Mandela and Victor Frankle had to include it makes sense that it wasn't just about grinding it out they had to find those dopamine rewards even in those little boxes they were forced into so I'm not trying to dodge any answer but for me personally and I think about this a lot because I have this um complicated history in science where my undergraduate graduate adviser and post-doctoral adviser all died young so uh you know and they were wonderful people and had immense importance in my life but what I realized is that be we can get so fixated on the thing that we're experiencing holding tremendous meaning but it only holds s that meaning for as long as we're in that SpaceTime regime and this is important because what really gives meaning is the understanding that you can move between these different space-time dimensionalities and I'm not trying to sound like a theoretical physicist or anyone that thinks about the cosmos in saying that it's really the fact that sometimes we say and do and think things and it feels so important and then two days later we're like what what happened well you had a different brain processing algorithm entirely you were in a completely different state and so what I want to do in this lifetime is I want to I want to engage in as many different levels of contraction and dilation of meaning as possible I want to go to the micro I sometimes think about this I'm like if I just pulled over the side of the road I bet you there's an ant hill there and their whole world is fascinating you can't stay there and you also can't stay staring up at the clouds and just think about how we're just these little beings and it doesn't matter the key is the journey back and forth up and down that staircase back and forth and back and forth and my goal is to get as many trips up and down that St staircase as I can before the reaper comes for me oh beautiful so the the the dance of dilation and contraction between the different SP zoom in zoom out and uh get as many steps in on on that staircase that's that's my goal anyway and I've watched people die I watched my postto advisor die wither away my graduate it was tragic but they found beauty in these closing moments because their bubble was their kids in one case or like one of them was a Giants fan and like got to see a Giants game you know in her last moments and like and you just realize like it's a Giants game but not in that moment because time is closing and so those time bins feel huge because she's slicing things so differently so I I think um learning how to do that better and more fluidly recognizing where one is and not getting too tacked to the idea that there's one correct answer like that's what brings meaning that's my goal anyway I don't think there's a better way to end it Andrew I really appreciate that you would uh come down and contract your SpaceTime and focus on this conversation for a few hours uh is a huge honor I'm a huge F of yours as I told you I hope you keep growing and educating the world about the the human mind thanks for talking today thank you I really appreciate the invitation to be here and people might think that I'm saying it just because I'm here but I'm a huge fan of yours I send your podcast to my colleagues and other people and I think what you're doing is isn't just uh amazing it's important and so thank you thanks for listening to this conversation with Andrew huberman and thank you to our sponsors as sleep a mattress that cools itself and gives me yet another reason to enjoy sleep sem Rush the most advanced SEO optimization tool I've ever come across and cash app the app I use to send money to friends please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with five stars on Apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex fredman and now let me leave you with some words from Carl Yung I am not what happened to me I am what I choose to become thank you for listening and hope to see you next time |
Yaron Brook: Ayn Rand and the Philosophy of Objectivism | Lex Fridman Podcast #138 | the following is a conversation with euron Brooke one of the best known objectivist philosophers and thinkers in the world objectivism is the philosophical system developed by Ein Rand that she first expressed in her fiction books The Fountain Head and Atlas Shrugged and later in non-fiction essays and books yaron is the current chairman of the board at the IR Rand Institute host of the Yan Brook show and the co-author of free market Revolution equal is unfair and several other books where he analyzes systems of government human behavior and The Human Condition from the perspective of objectivism quick mention of each sponsor followed by some thoughts related to the episode blinkist an app I use for reading through summaries of books expressvpn the VPN I've used for many years to protect my privacy on the internet and cash app the app I use to send Mone to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that I first read Atlas Shrugged and the Fountain Head early in college along with many other literary and philosophical works from n haiger Kant lock Fuko wienstein and of course all the great existentialists from kard to kamu I always had an open mind curious to learn learn and explore the ideas of thinkers throughout history no matter how mundane or radical or even dangerous they were considered to be IR Rand was and I think still is a divisive figure some people love her some people dislike or even dismiss her I prefer to look past what some may consider to be the flaws of the person and consider with an open mind the ideas she presents and yaron now describes and applies in his philosophical discussions in general I hope that you will be patient and understanding as I venture out across the space of ideas and the ever widening oron window pulling at the thread of curiosity sometimes saying stupid things but always striving to understand how we can better build a better world together if you enjoy this thing subscribe on YouTube review it with five stars on Apple podcast follow on Spotify support patreon or connect with me on Twitter at Lex Friedman and now here's my conversation with yuron Brook let me ask the biggest possible question first sure what are the principles of a life well lived I think it's to live with uh with thought that is to live a rational life to to think it through I think so many people are in a sense zombies out there there are alive but they're not really alive cuz their mind is not focused their mind is not you know focused on what do I need to do in order to live a great life so too many people just go through the motions of living rather than really Embrace Life so I I I think the secret to living a great life is to take it seriously and what it means to take it seriously is to use the one tool that makes us human the one tool that provides us with all the values that we have on mind a reason and to use it apply it to living right people apply it to their work they apply it to their math problems to science to to programming but imagine if they use that same energy that same Focus that same concentration to actually living life and choosing values uh that they should pursue that would that would change the world and it would change day lives yeah actually you know I wear this silly Suit and Tie it it symbolizes to me always it makes me feel like I'm taking the moment really seriously I think that's really that's right and and each one of us has different ways to kind of uh condition our Consciousness I'm serious now and for you it's it's a student TI it's a it's a conditioning of your Consciousness to now I'm focused now I'm at work now I'm doing my thing yeah right and I think that's that's terrific and I I wish everybody took that look I mean it's a cliche but we only live once every minute of your life you're never going never live again this is really valuable and and when people people don't have that deep respect for their own life for their own time for their own mind and if they did again you know one could only imagine look at how productive people are look at the amazing things they produce and they do in their work yeah and if they applied that to everything wow so you kind of talk about reason where does uh the kind of existentialist idea of experience maybe you know fully experiencing all the moments versus fully thinking through is there uh interesting line to separate the two like why such an emphasis on reason for life well lived versus just enjoy like experience well because I think experience in a sense is the easy part I'm not saying it's it it's it's how we experience the life that we live and yes I'm all with the take time to to to Value what you value but I think I don't think that's the problem of people out there I don't think the problem is they're not taking time to appreciate where they are and what they do I think it's that they don't use their mind in this one respect in planning their life in thinking about how to live so the focus is on reason is because it's our only source of knowledge there's no other source of knowledge we don't know anything with you know that does not come from our senses in our in our mind the integration of the of the evidence of our senses now we know stuff about ourselves and I think it's important to know oneself through introspection and I count consider that part of reasoning is to is to is to introspect but I think reason is undervalued which is funny to say because it's our means of survival it's how human beings survive we cannot see this is why I disagree with so many scientists and and people like Sam hav you mentioned Sam hav before the show um we're not programmed to know how to hunt we're not programmed to do agriculture we're not programmed to build computers and build networks on which we can podcast and do our shows all of that requires effort it requires Focus it requires energy and it requires will it requires somebody to will it it requires somebody to choose it and once you make that choice you have to engage that choice means that you're choosing to engage your reason in Discovery in integration and then in work to change the world in which we live and you know human beings had to discover figure out solve the problem of hunting hunting you know everybody thinks oh that's easy I've seen the movie but human beings had to figure out how to do it right you you you can't run down a bison and bite into it right you're not going to catch it you're not going to you have no fangs to bite into it you have to build weapons you have to build tools you have to create traps you have to have a strategy all of that requires reason so the most important thing that allows human beings to survive and to thrive in every value from the most simp to the most sophisticated from the most material to I believe the most spiritual requires thinking so stopping and appreciating the moment is is something that I think is relatively easy Once you have a plan once you've thought it through once you know what your values are there is a mistake people make they attain their values and they just and they just they don't take a moment to savor that and to appreciate that and to even Pat themselves on the back that they did it right but that's not what's screwing up the world what's screwing up the world is that people have the wrong values and they don't think about them and they don't really focus on them and they don't have a plan for their own life and how to live it if we look at Human Nature you're saying the fundamental big thing that we need to consider is our capacity like capability to reason so to me reason is this massive evolutionary achievement right in quotes right um if you think about any other sophisticated animal everything has to be coded everything has to be written in in the hard way it has to be there yeah and they have to have a solution for every outcome and if there's no solution the animal dies typically or the animal suffers and some way human beings have this capacity to self- program they have this capacity it there's not it's not a A aasa in the sense that there's nothing there obviously we have a nature obviously our minds our brains are structured in a particular way but given that we have the ability to turn it on or turn it off we have the ability to commit suicide to to to reject our nature to work against our interests not to use the tool that Evolution has provided us with which is this mind which is reason so that choice that fundamental choice you know uh uh Hamlet says it right to be or not to be but to be or not to be is to think or not to think to engage or not to engage to focus or not to focus you know in in the morning when you get up you kind of you know you're not you're not really completely there you're kind of out of focus and stuff it requires an act of will to say okay I'm awake I've got stuff to do some people never do that some people live in that Haze and they never engage that mind and and when you when you're sitting and trying to solve a a complex computer prr problem or a math problem you have to turn something on you have to in a sense exert certain energy to focus on the problem to do it and that is not determined in a sense that you have to focus you choose to focus and you could choose not to focus and that choice is more powerful than any other like parts of our brain that we've borrowed from fish and uh from our evolutionary origins like this whatever this crazy little leap in evolution is that allowed us to think is more important than anything else so I think neuroscientists pretend they know a lot more about the brain than they really do yeah um and that we know fired yeah I agree with you and and and we don't know that much yet about how the brain functions and what's a fish you know all this stuff so I think what what exists there is a lot of potentialities but the beauty of the human brain is it's its potentialities that we we have to manifest through our choices it's there it's sitting there and yes there's certain things that going to evoke certain uh senses certain feelings I'm not even saying emotions because I think emotions are too complex to have been programmed into our mind uh but I don't think so you know there's this big issue of evolutionary psychology is huge right now and and it's a big issue you know I find it to a large extent stand as way too early and in storytelling about expost storytelling about about stuff we still don't you know so for example I would like to see evolutionary psychology differentiate between things like inclinations feelings emotions Sensations thoughts Concepts ideas what of those are programmed and what of those are developed and chosen and a product of reason I think anything from emotion to abstract ideas is all chosen is all a product of reason and everything before that we might have been programmed for but the fact is so clearly a sensation is not a product of you know is is is something that we feel because that's how our biology works so until we have these categories and until we can clearly specify what is what and where where did they come from the whole discussion in evolutionary psychology seems to be rambling it doesn't seem to be scientific so we have to Define our terms you know which is the basis of science you have to have some some clear definitions about what we're talking about it when you ask them these questions there's never really a coherent answer about what is it exactly and everybody is afraid of the issue of Free Will and I think I think to some extent I mean Harris has this and I don't want to misrepresent anything Harris has because I you know I'm a fan and I I like a lot of your stuff right but on the one hand he is obviously intellectually active and wants to change our minds so he believes that we have some capacity to choose on the other hand he's undermining that capacity to choose by saying it's just determined you're going to choose what you choose you have no say in and there's actually no you he he he so it's you know so that and that's to me completely unscientific that's completely him you know uh pulling it out of nowhere we all experience the fact that we have an eye that kind of certainty saying that we do not have that fundamental choice that reason provides is uh unfounded currently look there's a sense in which it can never be contradicted because it's a product of your experience it's not a product of your experience you can experience it directly right so no science will ever prove that this table isn't here I can see it it's here right I can I can feel it I I know I have free will cuz I can introspect it in a sense I can see it I can see myself engaging it and that is as valid as the evidence of my senses now I can't point at it so that you can see the same thing I'm seeing but you can do the same thing in your own Consciousness and you can identify the same thing and to deny that in the name of science is to get things upside down you start with that and that's the beginning of science the beginning of science is the identification that I choose and that I can reason and it now I need to figure out the mechanism the the the rules of reasoning the rules of logic the you know how does this work and that's where science come from of course it's possible that science like for my place of AI would be able to if we were able to engineer consciousness or understand I mean it's very difficult to because we're so far away from it now but understand how the actual mechanism of that Consciousness emerges that in fact this table is not real that we can determine that it uh exactly how our mind constructs the reality that we perceive then then you can start to make interesting but our mind our mind doesn't construct the reality that we perceive the reality we perceive is there we perceive a reality that exists yeah now we perceive it in particular ways given the nature of our senses right a bat perceives this table differently but it's still the same table with the same characteristics and the same identity it's just a matter of we use eyes they use a radar system to you know they use sound waves to perceive it but it's still there existence exist whether we exist or not and so you could create I mean I don't know how and I I don't know if it's possible but let's say you could create a Consciousness right and I I suspect that to do that you would have to use biology not just Electronics but you know way outside my expertise um because Consciousness as far as we know is a phenomena of life and you would have to figure out how to create life before you created Consciousness I think but if you did that then that wouldn't change anything all it would say is we have another conscious being cool that's great but it wouldn't change the nature of our Consciousness our Consciousness is what it is respect so that's very interesting I think this is a good way to set the table for discussion of objectivism is let me at least challenge a thought experiment which is uh I don't know if you're familiar with uh Donald Hoffman's work about reality so his idea is that we're just our perception is just an interface to reality so Donald Hoffman is the uh is the guy you see ofine yeah yes I've met Donald and I've seen his video and look Donald has not invented anything new this goes back to ancient philosophy let me just state in in case people aren't familiar I mean it's a fascinating thought experiment to me uh like of out of the boox thinking perhaps literally is that uh you know our there's a different there's a gap between the world as we perceive it and the world as it actually exists and I think that's for the philosophy objectivism is a really important Gap to close so can you maybe at least try to entertain the idea that that there is more to reality than our minds can perceive well I don't understand what more means right of course there's more to reality than what our senses perceive that is uh for example I don't know certain certain elements uh have uh radiation right uranium has rad I can't perceive radiation the beauty of human reason is I can I can through experimentation discover the phenomena of radiation then actually measure radiation and I don't worry about it I can't perceive the world the way a bat perceives the world and I might not be able to see certain things that but I can we've created radar so a we understand how a bat perceives the world and I can mimic it through a radar screen and create and images like the bat its Consciousness somehow perceives it right so the beauty of human reason is our capacity to understand the world beyond what our senses give us directly at the end everything comes in through our senses but we can understand things that our senses don't provide us but but what he's doing is he's doing something very different he is saying what our census provides us might have nothing to do with the reality out there that is just a random arbitrary nonsensical statement and he actually has a whole evolutionary explanation for it run some simulations simulations seem I mean I'm not an expert in this field but they seem silly to me they they don't seem to reflect and look all he's doing is taking Emmanuel Khan's philosophy which articulate exactly the same cause and he's giving it a veneer of of of evolutionary uh ideas I'm not an expert on Evolution and I'm not an expert on epistemology which is what this is so to me as as a semi Layman it doesn't make any sense and uh you know I I'm actually you know I have a I have this shiron book show I don't know if I'm allowed to pitch it but I've got this shiron book show first of all let me pause a huge fan of the BR I listen to it very often as a small aside the cool thing about reason which you practice is you have a systematic way of thinking through basically anything yes and that's so fun to listen to I mean it's rare that I think there's flaws in your logic but even then it's fun cuz I'm like disagreeing with the screen when and it's great when somebody disagrees with me and they give good arguments because that makes it challenging any you know so so one of the shows I want to do in the next few weeks is is one of my philosoph bring one of my philosopher friends to discuss the video that that Hoffman where he presents his St because it surprises me how seductive it is and it's seems to be so first of all completely counterintuitive but but but because you know somehow we managed to cross the road and not get hit by the car and if our our our sensors did not provide us any information about what's actually going on in reality how do we do that that's and not not to mention build computers not to mention fly to the moon and actually land on the moon and if reality is not giving us information about the moon if our senses are not giving us information about the moon how did we get there you know and what did where did we go maybe we didn't go anywhere um it's just it's nonsensical to me and it's it's a it's a very bad place philosophically because it basically says there is no objective standard for anything there is no objective reality you can come up with anything you could argue anything and there's no methodology right my I believe that at the end of the day what reason allows us to do is provides us with a methodology for truth and at the end of the day for every claim that I make I should be able to boil it down to C yeah look you the evidence of the senses is right then once you take that away knowledge is gone and Truth is gone and that opens it up to you know complete disaster so you know to me why it's compelling to at least entertain this idea first of all it shakes up the mind a little bit to force you to go back to First principles and you know ask the question what do I really know and the second part of that that I really enjoy is H it's a reminder that we know very little to be a little bit more humble so if reality doesn't exist at all before you start thinking about it I think it's a really nice wakeup call to think wait wait a minute I don't really know much about this universe that humbleness I think something I'd like to ask you about in terms of reason when you you can become very confident in your ability to understand the world if you practice reason often and I feel like it can lead you astray because you can start to think it's so I love psychology and psychologists have the certainty about understanding The Human Condition which is undeserved you know you run a study with a 50 people and you think you could understand the source of all these psychiatrics The Source all these kinds of things that's similar kind of trouble I feel like you can get uh into with when you when you overreach with reason so I don't think there is such a thing is overreaching with reason but there are bad applications of reason there bad uses of reason or or or the pretense of using reason I think a lot of these psychological studies are pretense of using reason and and uh these psychologists have never really taken a serious stat class or a serious econometrics class so they use statistics in weird ways that just don't make any sense and that's a Mis that's not reason right that's that's just bad thinking right so I I don't think you can do too much good thinking and that's what reason is it's good thinking and now that the fact that you try to use reason does not guarantee you won't make mistakes it doesn't guarantee you won't be wrong it doesn't guarantee you won't go down a rabbit hole and and and completely get it wrong but it does give you the only existing mechanism to fix it right which is going back to reality going back to facts going back to reason and and and and getting out of the rabbit hole and getting up back to reality so I agree with you that it's interesting to think about these what I consider crazy ideas because it oh wait well what is my argument about them if I don't really have a good argument about them then do I know what I know so in that sense it's always nice to be challenged and pushed and and oriented you know the nice thing about objectivism is everybody's doing that to me all the time right because nobody agrees with me on anything so I'm constantly being challenged whether it's in by Hoffman on metaphysics and epistemology right on the very foundations of my knowledge in ethics everybody constantly and in in politics all the time so um I find that it's part of you know I prefer that everybody there's a sense in which I prefer that everybody agreed with me right because I think we live in a better world but there's a sense in which that disagreement makes it at least up to a Point makes it interesting and challenging and forces you to be able to to rethink or to confirm your own thinking and to challenge that thinking can you try to do the impossible task and give a whirlwind introduction to IR Rand the the many sides of ir Rand so IR Rand the human being IR Rand the novelist and irand the philosopher so who was irand should so so her life story is is one that I think is is fascinating and but it also uh lends itself to this integration of all of these things she was born in St Petersburg Russia in 1905 to kind of a middle class uh family Jewish Family they they owned a pharmacy a father owned a pharmacy and uh you know she grew up uh she grew up uh she was a very um she knew what she wanted wanted to do and what she wanted to be from a very young age I think from the age of nine she knew she wanted to be a writer she wanted to write stories that was the thing she wanted to do and uh you know she focused her life after that on this goal of I want to be a novelist I want to write and the philosophy was incidental to that in a sense at least until some point in her life she witnessed the Russian Revolution literally it happened outside they lived in St Petersburg where the first kind of demonstrations and and of the Revolution happened so she witnessed it she lived through it as a teenag um went to school Under the Soviets uh for a while they they they were under kind of the in on the Black Sea where the opposition government was ruling and then they would they would go back and forth between the commies and the whites but but she experienced what communism was like she saw the pharmacy being taken away from her family she saw their apartment being taken away or other other families being brought into the apartment they already lived in um and uh it was very clear given her nature uh given her views even at a very young age that she would not survive the system uh so a lot of effort was put into how do we get how how does she get out and her family was really helpful in this and she had a cousin in cousin in Chicago and uh she had been studying kind of film at the University and uh this is in her 20s this is in her 20s early 20s and uh lenon there was a small window where Lennon was allowing some people to leave under circum certain circumstances and she managed to get out to go do research on film in in the United States everybody knew everybody who knew her knew she would never come back that this was a oneway ticket and and she got out she made it to Chicago spent few weeks in Chicago and then headed to Hollywood she wanted to write scripts that was that was the that was the uh the goal here's this uh you know short woman From Russia with a strong accent uh learning English showing up in in Hollywood and you know I want to be a script writer in English in English writing in English uh and U and this is kind of a one of these fairy tale stories but it's true she shows up uh at the cisa B demill Studios and she she has a let of introdu ction from her cousin in Chicago who owns a movie theater and this is in the 19 uh the late 1920s and she shows up there with this letter and they say you know don't call us we'll call you kind of thing and she steps out and there's this massive um convertible and in the convertible is CB de Mill and he's driving slowly past her right at the entrance of the studio and she stares at him and he stops the con he says you know why are you staring at me and she says you know she tells him a story for Russ and you know I want to want to make it in the movies I want to be a script writer one day and he says well if you want to if you want that you know get in the car you she gets in the car and he takes her to the back lot of his Studio where they're filming the King of Kings the story of Jesus and he says here has a pass for a week yeah if you want to be if you want to write for the movies you better know how movies are made and uh she basically spends a week and then she spends more time there she managed to get an extension she lands up being an extra in the movie so you can see I man there in in one of the masses when Jesus is walking by she meets her future husband on the set of uh of the king of kings she lands up uh getting married getting her American citizenship that way uh and she lands up doing odds and ends jobs in Hollywood living in a tiny little apartment um somehow making a living her husband was an actor he was you know struggling actors were difficult times uh and in the evenings English writing writing writing writing and studying and studying and studying and she she finally makes it by writing a play that that uh is successful in in um in LA and ultimately goes to Broadway um and uh she writes her first novel is a novel called We The Living which is the most autobiographical of all her novels it's about a young woman in the Soviet Union it's a powerful story a very moving story and probably if not the best one of the best portrayals of Life under communism and the book definitely recommend we the living it's her first first novel she wrote in the 30s and it didn't go anywhere because if you think about the intelligencia the the the the people who mattered the people who wrote book reviews this is a time of Durante in who's the New York Times uh guy in Moscow who's praising Stalin to the and the success so the the novel fails uh but but she's got a novel out she writes a small novelet called Anthem a lot of people have read that and it's it's read in high schools it's it's kind of dystopia novel uh and uh it's won't it doesn't get published in the US gets published in the UK UK is very interested in dystopian novels Animal Farm uh and in 1984 84 is published a couple of years after I think after an there's reason to believe he read he read Anthem uh that and uh George read Animal Farm yeah just the small Side Animal Farm is probably top I mean I would it's weird to say but I would say it's my favorite book which have you seen this movie out now called Mr Jones no oh you've got to see Mr Jones what's Mr Jones it's sorry sorry for my ignorance no no it's a movie it hasn't got any publicity which is tragic cuz it's a really good movie It's both brilliantly made it's made by a Polish director but it's in English it's a it's a true story and and gej Well's Animal Farm is featured in it in the sense that during the story JoJo was writing animal farm and and he's the narrator is reading off sections of animal f as the movie is progressing and the movie is a true story about the the first Western journalist to discover and to write about the famine in Ukraine and so he goes to Moscow and then he gets on a train and he finds himself in Ukraine and it's it's it's beautifully and horrifically made so the horror of the famine is brilliantly conveyed and then and it's a true story it's a very moving story very powerful story and and just very well-made movie so it's tragic in my view that not more people are seeing it that's I was actually recently just complaining that there's not enough content on the the famine the 30s of you know of of Stu there's so much on Hitler like I love yeah the reading I'm reading it's so long it's been taking me forever the the rise and Falls the Third Reich yeah I I love it but well I've got the book to complement that that you have to read it's called the ominous parallels it's Lon peof and it's the ominous parallels and it's about it's about the causes of the rise of of of Hitler better philosophical causes so whereas the rise and fall is more of a kind of uh uh the the existential kind of what happened um but really delving into the intellectual uh intellectual uh currence that led to the rise of Hitler and maybe highly recommend that and basically suggesting how it might rise another that's the ominous parallel so the parallel he draws is to the United States and he says those same intellectual forces AR rising in the United States and this is this was published I think in published in 81 ' 82 was published in ' 82 so it's published a long time ago and yet you look around us and it's unbelievably predictive sadly about the state of the world so I haven't finished IR Man story I don't want I don't know if you want me to no no no but on that point I'll have to let's please return to it but let's now for now let's talk let me also say just just because I I don't want to forget about Mr Jones it is true the point you made that tons of movies that are anti-fascist anti-nazi and that's good but there are way too few movies that are anti-communist just almost not yeah and it's very interesting and if you remind me later I'll tell you a story about that but um so she publishes Anthem and and then she starts and she's doing okay in Hollywood and and she's doing okay with with the play and then she starts on her on on the book The Fountain Head and she writes The Fountain Head and it comes out um she finishes it in uh 1945 and she's um she sends it to Publishers and publisher after publisher after publisher turn it down and it takes 12 Publishers before this this editor reads it and says I want to publish this book and he basically tells his bosses if you don't publish this the book I'm leaving right um and they don't really believe in the book so they publish just a few copies they don't do a at L and the book becomes a bestseller from word of mouth and they end up having to publish more and more and more and and it's you know she's basically gone from this immigrant who comes here with very little command of English and and to all kinds of odds and ends jobs in Hollywood to you know writing one of the seminal I think Book American books she is an American Author I mean if you read The Fountain Head it's not Russian the not DKI it feel it feels like a symbol of what America is in the 20th century and I mean probably maybe you can so there's a famous kind of sexual rape scene in there is that is that like a lesson you want to throw in some controversial stuff to make your philosophical books work out I mean is that why why was it so popular uh do you have a sense or was well because I think it Illustrated first of all because I think the characters are uh a fantastic it's got a a real hero and I think it the whole book is basically illustrating this massive conflict that I think went on in America then is going on today and it goes on on a big scale politics all the way down to the scale of the choices you make in your life and and this the the issue is individualism versus collectivism should you live for yourself should you live for your values should you pursue your passions uh should you or should you do do what your mother tells you should you follow your mother's passions and uh that's and it's a it's it's very very much an individ a book about individuals and people relate to that but it obviously has this massive implications to the world outside and at the time of collectivism just having been defeated communis well not Fascism and and uh in and you know the United States representing individualism right is defeated defeated collectivism but where collectivist ideas are still popular in the form of socialism and communism and for the individual there's constant struggle between what people tell me to do what Society tells me to do what my mother tells me to do and what I think I should do I think it's unbelievably appealing particularly to young people who trying to figure out what they want to do in life trying to figure out what's important in life um it it it had this enormous appeal it's romantic it's bigger than life the characters are big heroes it's very American in that sense it's about individualism it's about the Triumph of individualism and uh so I I I think that's what related and it had this big romantic element from the I mean when I use romantic I use it kind of in the in the sense of uh um a movement in art but it also has this romantic element in the sense of a relationship between a man and a woman who's that's very intriguing it's not only that there's a uh I would say almost rape scene right um I would say but it's also that this woman is hard to understand I mean I I've I've read it more than once and I still can't quite figure out Dominique right because she loves him and she wants to destroy him and she marries other people I mean think about that too here she's writing a book in the 1940s it's there's lots of sex there's a woman who marries more than one person has having sex with more than one person very unconventional she having married she's having sex with rck even though she's not married to rock this is 1945 and it's um it's very jarring to people it's very unexpected but it's also a book of its time it's about individuals pursuing their passion pursuing their life and not caring about convention and and what people think but doing what they think is right and U and and so so I think it's it's it's uh I encourage everybody to read it obviously so that was was that the first time she articulated start articulated something that's sounded like a philosophy of individualism I mean the philosophy is there in we the living right because at the end of the day the the woman is the the hero of we the living is this individualist stuck in Soviet Union so she's struggling with these things uh so the theme is there already it's not as fleshed out it's not as articulated philosophically and it's suddenly the anthm which is a dystopia novel where the this dystopia in the future has a has uh there's no I everything is we and it's about one guy who breaks out of that I don't want to give it away but but breaks out of that so these themes are running and and then we have and we and they've been published some of the early irand stories that she was writing in preparation for writing her novel stories she was writing when she first came to America and you can see these same philosophical elements even in the male female relationships and the passion and the you know you in the conflict you see them even in those early pieces and she's just developing them and same philosophically she's developing her philosophy with her literature and of course after the Fountain Head she starts on what turns out to be magnos Opus which is at Shrugged uh which takes her 12 years to publish by the time of course she brings that out every publisher in New York wants to publish it because the fountain headit has been such a huge success um they don't quite understand it they don't know what to do with Atlas Shrugged but they're eager to to get it out there and indeed it's when it's published it becomes an instant bestseller and the thing about the particularly the F head and and Al shrug but true of of even anthem and we the living she is one of the only dead authors that sell more after they've died than when they was your alive now you know that's true maybe in music we listen to more Beethoven when he was alive but it's not true typically of novelists and yet here we are uh you know uh what was it 50 you know 60 years after the 63 years after the publication of at Shrugged and it sells probably more today than it sold when it was a bestseller when it first came out is it true that it's like one of the most sold books in history no okay I've heard this kind of statement any Tom Clancy book comes out sells more than atly Shrugged but or read I've heard so there was a very and I shouldn't say this but it's the truth so I'll say it a very unscientific study done by the Smithsonian Institute yeah probably in the early 90s that basically surveyed uh CEOs and asked them what was the most influential book on you and at came out as number two the second most influential book and CEOs in in the country but but there's so many flaws in the study one well you want to guess what the number one book Bible the Bible yeah but the Bible was like you know so maybe they serveed 100 people I don't know what the exact numbers were but let's say it's 100 people and 60 said the Bible and 10 said Atlas Shrug and there were a bunch of books over there so you know I don't that's again the psychology discussion what we're having ex well and it's it's one thing I've learned and maybe Co has taught me and and uh nobody you know there are very few people who know how to do statistics and almost nobody knows how to think probabilistically that is think in terms of probabilities that it is a skill it's a hard skill and everybody thinks they know it so I see doctors thinking their statisticians and giving whole analyses of the data on covid and they don't have a clue what they're talking about not because they're not good doctors because they're not good statisticians it's not e you know people think that they have one skill and therefore it translates immediately into another skill and and it's just not true um so I've been astounded at how how bad people are at that for people who haven't read any of the books that we were just discussing what would you recommend what book would you recommend they read and maybe also just elaborate what mindset should they enter the reading of that book with so I would recommend everybody read Fountain Head and Aly shrug and in what order so it would depend on on where you are in life right so it it depends on who you are and what you are so found head is a more personal story for many people it's their favorite and for many people it was their first book and and they wouldn't replace that right um if Al shrug is a it's about the world right it's about what impacts the world how the world functions how it's a biger book in the sense of the scope if you're that if you're interested in politics and you're interested in the world read Atlas Shrug first if you're mainly focused on your life your career what you want to do with yourself start with fad I still think you should read both because I think they are I mean to me they were life altering and to many many people they're life altering and you should go into reading them with an open mind I'd say and with a put aside everything you've heard about irand put aside any even if it's true just put it aside even what I just said about IR man put it aside just read the book as a book and let it move you and let let let your thoughts let it shape how you think um and and it'll have you know it either have a you'll either have a response to it or you won't uh but I think most people have a very strong response to it and then the question is do they are they willing to respond to the philosop are they willing to integrate the philosophy are they willing to Think Through the philosophy or not because I know a lot of people who completely disagree with the philosop philosop philosophy right here in Hollywood right lots of people here in Hollywood love the Fountain Head interesting Oliver Stone who is I think a a vowed Marxist right I think he's he I think he's admitted to being a Marxist he is his movie certainly reflect a Marxist theme um is a huge fan of the fountain head and is actually his dream project he has said in public his dream project is to make the Fountain Head now he would completely change it as movie directors do and he's actually outlined what his script would look like and it would be a disaster for the ideas of the but he loves the story because to him the story is about Artistic integrity ah yeah and that's what he catches on and what he hates about the story is individualism right and I think that his movie ends with Howard walk joining some kind of commune of Architects that do it for the love and don't do it for the money interesting but so yeah so you can connect with you without the philosop and before we get into the philosophy staying on iron Rand I I'll tell you sort of my own personal experience and I think it's one that people share I've experienced this with two people IR Rand and N when I brought up IR Rand when I was in my early 20s the number of ey rolls I got from sort of you know like advisers and so on that of dismissal I've seen that later in life about more more specific Concept in artificial intelligence and Technical where people decide that this is this is a set of ideas that are acceptable and these sets of ideas are not and they dismissed irand without giving me any justification of why they dismissed her except oh well that's something you're into when you're 19 or 20 that's same thing people say about nature well that's just something you do when you're in college and you take an intro to philosophy course so and I've never really heard anybody cleanly articulate their opposition to IR Rand in in my own private little circles and so on maybe one question I just want to ask is why is there such opposition to iron Rand and maybe another way to ask the same thing is what's misunderstood about iron Rand so we haven't talked about the philosophy so it's harder to answer right now we can return to it if you think that's the right way to go well let me let me give a broad answer and then and then and then we'll do the philosophy and then we'll return to it because I think it's important to know something about her ideas she I think her philosophy challenges everything it it really does it shakes up the world it challenges so many of our preconceptions it challenges so many of the things that people take for granted as Truth uh from religion to morality to to politics to almost everything there never quite been a thinker like her in the sense of really challenging everything and doing it systematically and having a complete philosophy that is a challenge to everything that has come before her now I'm not saying they AR thread that connect they are right in in politics they might be a threat and in immorality they might be a threat but on everything there's just never been like it and people are afraid of that because it challenges them to the course she's basically telling you to rethink almost everything um and that is that that people reject the other thing that it does and this goes to this point about oh yeah that's when you do when you're 14 15 right yeah she points out to them that they've lost something they've lost their idealism they've lost their youthful idealism yeah what is what makes youthfulness meaningful other than you know we're in better physical shape yeah starting to feel because I'm getting older yeah when we're young we you know sometime in the teen years right there's something that happens to human consciousness we almost awaken a new right M we we suddenly discover that we can think for ourselves we suddenly discover that not everything our parents and our teachers tell us is true we suddenly discover that this tool our minds is suddenly available to us to discover the world and to discover truth and it is a time of idealism it's a time of whoa I want to you know the better teenagers I want to know about the world I want to go out there I don't believe my parents I don't believe my teachers and this is healthy this is fantastic and I want to go out there and experiment and and that gets us into trouble right we do stupid things when we're teenagers why because we're experimenting it's the experiential part of it right we want to go and experience life but we're learning it's part of the learning process and and and we become Risk Takers because we want experience but the risk is something we need to learn because we need to learn where the boundaries are and and one of the damages that helicopter parents do is they prevent us from taking those risks so we don't learn about the world and we don't learn about where the boundaries are so the teenage years of these years of Wonder they're depressing when you're in them for a variety of reasons which I think primly have to do with the culture but also with oneself but there are exciting the periods of Discovery and people get excited about ideas and good ideas bad ideas all kinds of ideas and then what happens we settle we compromise whether that happens in college where we're taught that nothing exists and nothing matters and start being be a be annihilist be a cynic be whatever or whether it happens when we get married and get a job and have kids and are too busy and can't think about our ideals and forget and get just get into the norm of conventional life or whether it's because a mother pester us pesters us to get married and have kids and do all the things that she wanted us to do we give up on those ideals and there's a sense in which irand reminds them that they gave up that's beautifully that's so beautifully put and it's so true it's it's worth pausing on that uh this dismissal people forget the the beauty of that Curiosity that's true in the scientific feel too is Uh I that that youthful Joy of like everything is possible and we can understand it with the tools of our mind yes and that's what it's all about that's what Iron Man's ideas at the end of the day all boow down to is that confidence and that passion and that Curiosity and that interest and if you you know think about what Academia does to so many of us right we go into Academia and and we're excited about we're going to learn stuff we're we're going to discover things and then they stick you into sub subfield and examining some minutia that's insignificant and unimportant and and to get published you have to be conventional you have to do what every body else does and then there's the tenure process of seven years where they put you through this torture to write papers that fit into a certain mold and by the time you're done you're in your mid-30s and you've done nothing you discovered nothing you you you're all in this minutia in this stuff and it's destructive and where holding on to that passion holding on to that knowledge and that confidence is hard and when people do away with it they become cynical yeah and they become part of the system and they inflict the same pain on the next guy that they suffered because that's part of how it works yeah there's uh this happens in artificial intelligence this happens when like a young person shows up and with like fire in their eyes and they say I want to understand the nature of intelligence and everybody rolls their eyes be well for these same reasons because they've spent so many years on the very specific set of questions that um that kind of they compete over and they write papers over and they have conferences about and it's true those that incremental research is the way you make progress answering the question of what is intelligence exceptionally difficult but when you mock it you actually destroy the the reality when when we look like centuries from now look back at this time for this particular field of artificial intelligence it will be the people who will be remembered will be the people who asked the question and made it their life journey of what is intelligence and actually had the chance to succeed most will fail asking that question but the ones that like had a chance of succeeding and had that throughout their whole life uh and I suppose the same is true for philosophy it's in every field it's it's it's asking the big questions and staying curious and staying passionate and staying excited and accepting failure right accept accepting that you're not going to get it first time you're not going to get the whole thing but and and sometimes you have to do the minua work and I'm not here to say nobody should specialize or you shouldn't do the Manos you have to do that but there has to be a way to do that work and keep the passion and keep and keep it all integrated that's another thing I mean we don't live in a culture that integrates right we live in a culture that is all that is all about you know this minutia and not and and you know medicine is another field where you you specialize in the kidney I mean the kidney is connected other things you've got to and we don't have a holistic view of these things and I'm sure in artificial intelligence you're not going to make the big leaps forward without a holistic view of what it is you're trying to achieve and maybe that's the question what is intelligence but that's the kind of questions you have to ask to make big leaps forward to really move the field in in a in a positive direction and it's the people who can think that way who move fields and move technology who move ev anything anything is is is everything is like which just like you said is painful because underlying that kind of questioning is well maybe the work I've done for the past 20 years was um was a dead end and you have to kind of face that even just it might not be true but even just facing that reality yes is is just it's a it's a painful feeling absolutely but but it's that's part of the reason why it's important to enjoy the work that you do right so that even if it doesn't completely worked out at least you enjoy the process right it was not a waste because you enjoyed the process and if you learn as as any entrepreneur knows this right and if you learn from the waste of time from the errors from the mistakes then you can build on them and make things even better right and so the next 20 years are are a a massive success can we uh another impossible task so you did wonderfully on talking about Iran the other impossible task of giving a whirlwind overview of the philosophy of objectivism the philosophy of Vine Rand yeah so luckily she did it in an essay you she she talks about doing a philosophy on one foot um but let me integrate it with the literature and with her life a little bit she wanted to be a writer but her goal she had a particular goal in her writing uh she was an idealist right she wanted to portray the ideal man so one of things you do when you want to do is what is an ideal man you have to ask that question what does that mean you might have a sense of it you might have certain glimpses it glimpses of it in other people's literature but what is it so she starts reading philosophy to try to figure out what a Philosophers say about the ideal man and what she finds horrifies her in terms of the view of most philosophers of man and and she's she's attracted certainly when she's young to n because n at least has a vision of of of grandeur for man even though his philosophy is very flawed and has other problems and contradicts man in many ways but at least he has that vision of what is possible to man and she's attracted to that romantic Vision that idealistic Vision so she discovers in writing and particularly in writing out shrug but even in the fountain that she's going to have to develop her own philosophy she's going to have to discover these ideas for herself because they're not fully articulated anywhere else they glimpses again of it in Aristotle in in in N but they're not fully fleshed out so to a large extent she develops a philosophy for a very practical purpose to write to write a novel about the ideal man and and and Al shrug is the manifestation of that by the way sorry to interrupt uh as a little aside she does when you say man you mean human and the and because we'll bring this up often I she does I mean maybe you can elaborate of how she specifically uses man and he in the work we live in a time now of gender so well she did that in in the in the sense that everybody did it during her period of time right it's only in modern times where we do he/ she right it historically when you said he you meant a human being unless the particular context implied that it was a but in Ein man's case in this case in this one sentence she she probably me man not that because she a she viewed that there are differences between men and women were not the same which I know comes at a shock to many people but um she she's working on a character she was working on a particular Vision right yeah she considered herself a man worshipper and a man not not human being a man male she worshiped manhood if you will the the the the the hero in man and she wanted to fully understand what that was now it has massive implications for ideal woman and I think she does put for the ideal woman in in in in Atlas Shrug in the character of dagy but her goal is you know I think her selfish goal for what she wanted to get out of the novel is that excitement partially sexual about seeing your ideal manifest in reality of what you perceive as the that which you would be attracted to yeah fully intellectually physically sexually in every aspect of your life that's what she's trying to bring into so there was no ambiguity of gender so there was a masculinity and a femininity in her work very much so and if you read the novels you you see that you see that now remember this is in the context of in Atlas Shrug she is portraying a woman who runs a railroad the most masculine of all jobs you could imagine right running a railroad better than any man can run it yes and achieving huge success better than any other man out there but but for her even dagney needs somebody to needs a man in some sense to look up to yeah and that's the character who name I won't mention because it gives away too much of the plot but there has to I like how you do that you're good you're not a lot of practice a lot of practice not brilliant cuz you convey all the important things without giving away plot lines that's beautiful you're master so she's so she's very much she she described once as a male chauvinist okay she very she likes the idea of a man opening a DOA but more metaphysically she identifies something in the difference between a way a man relates to a woman and a woman relates to a man it's not the same and let's not take too far of a tangent but I just as a side comment I to me she represented she was a feminist to me perhaps there's a perhaps technically philosophically you disagree with that whatever but the you know that to me represented strong like she had the some of the strongest female characters in the history of literature again this is this is a woman running a railroad in 1957 yeah and not just a woman running a railroad and this is true the fountain hit as well a woman who is sexually in a sense assertive sexually open uh this is this is not a woman who you know this is a woman who who who Embraces her sexuality and uh you know sex is important in life this is why it keeps coming up right it's it was important to i it was it's important in the novels it's important in life and for her one's attitude towards sex is a reflection one's attitude towards life and you know what attitude towards pleasure which is an important part of life and she thought that was an incredibly important thing and so she has these assertive powerful U sexual women who live their lives on their terms 100% who seek a man to look up to yeah now this is psychologically complex it's more psychology than philosophy right it's psychologically complex and you know not my area of expertise but this is there's something in She would argue there's something fundamentally different about a male and a woman about a male and female psychologically in their attitude towards one another yeah but but as a side note I say that uh I would say that I don't know philosophically if her ideas about gender are interesting I think her other philosophical ideas are the much more interesting but reading wise like the stories it created the tension it created um that was pretty powerful I mean that was that's that's pretty powerful stuff I'll speculate that the reason it's so powerful is because it reflects something in reality yeah that's that's true there's a thread that at least and and look she it's it's really important to say she I think she was the first feminist in a sense uh I think in a sense the feminist have proved feminism into something that it shouldn't be but in the sense of men and women are capable she was the first one who really put that into a novel and showed it to me as a as a as a as a boy when I was reading Al shrug I think I read that before F in the head that was one of the early introduction at least of an American woman I had examples in my own life for Russian women but of like aad badass lady like I admire like I love engineering I love that that she could you know here's a lady that's running the show so that at least to me was an example of really strong woman but objectivism objectivism so and and so she developed it for novel she spent the latter part of her life after the publication of atas shrug really articulating her philosophy so that's what she did she applied it to politics to life to gender to all these issues from 1957 until she died in 1982 so the objectivism was born born out of the later parts of atas shrug yes definitely it was there all the time but it it was fleshed out during the later parts of alas shrug and then articulated for the next 20 years so what is objectivism so objectivism so there are five branches in philosophy and it it and so I'm going to just go through the branches she starts with you start with metaphysics the nature of reality and objectivism argues that reality is what it is it's kind of uh goes Hawkins back to Aristotle law of identity a is a you can wish to be be but wishes do not make something real reality is what it is and it is the primary and it was it's it's not it's not manipulated directed by Consciousness Consciousness is there to uh you know to observe to to give us information about reality that is the purpose of Consciousness that is the nature of it so in metaphysics existence exists a it the law of identity the law of causality things are you know the the things act based on their nature not randomly not arbitrarily but based on their nature and then we have the tool to know reality this is epistemology the the theory of knowledge our tool to know reality is reason it's our senses and our capacity to integrate the information we get from our senses and to integrate it into new knowledge and to conceptualize it and uh and and that is uniquely human um uh we don't we don't know the truth from revelation we don't know truth from our emotions our emotions are interesting our emotions tell us something about ourselves but our emotions are not tools of cognition they don't tell us the truth about what's out there about what's in reality so reason is a means of knowledge and therefore me reason is our means of survival only individuals reason just in the same way that only individuals can eat we don't have a collective stomach nobody can eat for me and therefore nobody can think for me I we don't have a collective mind there's no Collective Consciousness none it's it's bizarre that people talk about these collectivized aspects of the mind they don't talk about Collective Feats and Collective stomachs and Collective things but so we all think for ourselves and it is our fundamental basic responsibility to live our lives to live to choose to once we choose to live to live our lives to the best of our ability so in Morality she is an egoist she believes that the purpose of morality is to provide you with a code of values and virtues to guide your life for the purpose of your own success your own Survival your own thriving your own happiness happiness is the moral purpose of your life the purpose of morality is to to guide you towards a happy life your own happiness your own happiness absolutely your own happiness so she rejects the idea that she should live for other people that you should live for the purpose of other people's happiness your purpose is not to make them happy or to make them anything your purpose is your own happiness but she also rejects the idea that you could argue maybe the N idea of you should use other people for your own purposes right so every person is an end in himself every person's responsibility is their own happiness and you shouldn't use other people for your own shouldn't exploit other people for your own happiness and you shouldn't be allow yourself to be exploited for other people every individual is responsible for themselves and what is it that allows us to be happy what is it that facilitates um human flourishing human success human survival well it's the use of our minds right go goes back to reason and what does reason require in order to to be successful in order to to work effectively it requires Freedom so the enemy of reason the enemy of reason is force the enemy of reason is corrosion the enemy of reason is Authority right the Catholic Church doing what they did to Galileo right that restricts Galileo's thinking right when he's in house arrest is he going to come up with a new theory is he going to discover new truths no it it it it's the punishment is too you know it's too dangerous so Force coercion um are enemies of of reason and what reason needs is to be free to to think to to discover to innovate to break out of convention um so we need to create an environment in which individuals are free to reason free to think and to do that we we we come up with a con conceptt historically we've come up with the concept of individual rights individual rights define the scope of Define the fact that we should be left alone free to pursue our values using our reason free of what free of corion Force Authority and that the job of government is to make sure that we are free the whole point of government the whole point of when we come in a social context the whole point of establish a govern in that context is to secure that freedom it's to make sure that I don't use cion on you the governor is supposed to stop me supposed to intervene before I can do that or or if I've already done it to prevent me from doing it again so the purpose of government is to protect our freedom to think and to act based on our thoughts it's to leave individuals free to pursue their values to pursue their happiness to pursue their rational thought and to be left alone to do it and so she rejects socialism which which basically assumes some kind of collective goal assumes the sacrifice of the individual to the group assumes that your moral purpose in life is the well-being of other people rather than your own uh and and she rejects all form of statism all form of government uh that is you know overly uh that that is involved in any aspect other than to protect us from Force coion Authority uh and she rejects Anarchy and we can talk about that I I I I think you had a question in the list of questions you sent me about Anarchy to Michael malice about Anarchy so I don't know if you're familiar with him yes I'm familiar with him so so yeah so she would completely rejects Anarchy anak is completely inconsistent with their point of view and we can talk about why if you want so there's some perfect place where freedom is maximized so systems of government that absolutely and and she thought that the American system of government came close in its idea obviously founded with original sin with the sin of slavery but in its conception the Declaration of Independence is about as perfect a political document as one could write I think the greatest political document in human history but really articulated almost perfectly um and and beautifully and that American system government with the check's Balan balances with which is with its emphasis on individual rights with its emphasis on freedom with its emphasis on lead leaving individual free to pursue their happiness an explicit recognition of Happiness as the goal individual happiness was the model it it wasn't perfect there a lot of problems to a large extent because the founders had mixed philosophical premises so so they were there were alien um uh premises introduced into the founding of the country slavery obviously being the biggest problem uh but it was close and we need to build on that to create an ideal political system that will yes op maximize the freedom of individuals to do exactly this um and then of course she had so that's kind of uh that's the manifestation of this individualism in a political realm and she had a theory of art she had a theory of Aesthetics which is the fifth branch of of of she have metaphysics epistemology ethics and politics and the fifth branch is Aesthetics and she viewed art as an essential human need a fuel for the human spirit and that just like any human need it had certain principles that it had to abide by that is just like there's nutrition right so some food is good for you and some food is bad for you some food some stuff is poison she believed the same is true of Arts that art had an identity which is very controversial today right if you you know today it's if you put a frame around it it is Art right if you put a unal in urinal in a in a museum it becomes art which he thought was was evil and and and ludicrous and she rejected completely uh that art had an identity and that it served a certain function that human beings needed it and if it didn't have not only did it have have the identity but that function was served well by some art and poorly by other art um and then there's a whole realm of stuff that's not art B basically all of all of what today is considered Modern Art she would consider not being art you know splashing paint on a canvas not art um so she had very clear ideas uh she articulated them not so I would say not in conventional philosophical form so she didn't write philosophical essays using the Philosopher's language it's why partially why I think philos phers have never taken us seriously they're actually accessible to us we can actually read them and she integrates the philosophy in what I think amazing ways with psychology with history with economics with politics with what's going on in the world uh and she has dozens and dozens and dozens of essays that she she wrote uh many of them were aggregated into books uh I particularly recommend books like uh uh the virtue of selfishness capitalism the unknown ideal uh and and uh philosophy who needs it and you know it's it's a I think it's a it's a it's a beautiful philosophy uh you know I know you're big on love I think it's a philosophy of love we can talk about that essentially it's about love that's what the philosophy is all about and when it apply in terms of it applying to self um and uh you know I I think it's sad that so few so few people read it and so few intellectuals take it seriously and are willing to engage with it let me ask that was incredible but after that beautiful Whirlwind overview let me ask the most shallow of questions which is the name objectivism of where like how should people think about the name being rooted why not individualism what what are the options if we like had a branding meeting right now sure so she actually had a branding meeting so she she did this she went through the exercise objectivism I do not think I don't know the all the details but I don't think objectivism was the first yeah name she came with the problem was that the other names were taken and they were not positive implications that it so for example rationalism could have been a good word because she's an advocate of rational thought or Reason ISM but reason ISM sounds weird right the ism because of too many s's I guess rationalism but was already a philosophy and it was a philosophy inconsistent with her because it was it was a it was a what she considered a false view of of reason of rationality um realism you know just doesn't work so she came in objectivism and I think actually it's a great word it it's a great name because it it's it has two aspects to it and this is a unique view of what objectivity actually means in objectivism in objectivity is the idea of an independent reality there is truth mhm there's actually something out there that we and then there's the role of Consciousness right there is the role of figuring out the truth the truth doesn't just hit you the truth is not in the thing you have to discover it it's that it's that a Consciousness applied to that's what objectivity is right it's you discovering the truth in reality it's your Consciousness interacting and thereby pulls in the individual in that sense and only the individual could do it now the problem with individualism is it would have made the philosophy too political right and she always said so she said she said I'm an advocate of capitalism because I'm really an advocate for rational egoism but I'm a rational for I'm an advocate for rational egoism really because I'm an advocate for reason so she viewed the essential of her philosophy as being this uh reason and her her particular view of reason and she has a whole book she has a book called uh introduction to objectivist epistemology which I encourage any scientist mathematician anybody interested in science to read because it is a tur of force on on on in a sense this the the the what it means to hold Concepts and what it means to discover new discoveries and to use to use Concepts and how we use Concepts and she has a theory of Concepts that is completely new that is completely revolutionary and I think is essential for the philosophy of science and therefore ultimately for the more abstract we get with scientific discoveries the easy it is to detach them from reality and to detach them from truth the easier it is to be inside our heads instead of about what's real and they're probably examples from monop physics that fit that and I think what she teaches in the book is how to ground your Concepts and how to bring them into grounding in reality so introduction to objectivist epistemology and note that it's only an introduction because one of the things she realized one of the things that I think a lot of her critics don't give enough credit for is that philosophy is there's no no end right it's always growing there always new discoveries there's always it's you know it's like science there's always new things and and there's a ton of work to do in in philosophy uh and particularly in epistemology and Theology and she was actually giving you interest in mathematics she was she actually saw a lot of parallels between math and concept formation and she was actually you know in the years before she died she was taking private lessons in mathematics in algebra and calculus because she believed that there was real insight in understanding algebra in calculus to um philosophy into epistemology and and she also was very interested in Neuroscience because she believed that that had a lot to tell us about epistemology but also about music therefore about Aesthetics so I mean she recognized the importance of all these different fields and how and and the beauty of philosophy is it should be integrating all of them and one of the sad things about the world in which we live is again we view these things as silos we don't view them as integrating we don't have teams of people from different Arena you know different fields you know discovering things we we we become like ants specialized so she was definitely uh like that and she was constantly curious constantly interested in in the in discoveries and new ideas and and how this could expand the scope of her philosophy and the application of her philosophy there's like a million topics I can talk to you but since you mentioned math I'm almost only got three hours only I'm almost curious uh I don't know if you're familiar with Gay's incompleteness theorem I'm not unfortunately okay it was a a powerful proof that any axiomatic systems when you start from a bunch of axioms that there will in that system provably must be an inconsistency so that was this painful like stab in the idea of mathematics that no if we start with a set of assumptions kind of like an started with objectivism Y there will have to be at least one contradiction see I I intuitively I'm going to say that's false philosophically but in math it's just true and it's it's a question about how you define again the definitions matter and you have to be careful on how you define axioms and you have to be careful about what you define as an inconsistency and what that means to say there's an inconsistency and I don't know I'm not going to say more than that because I don't know but I'm suspicious that there is some uh and this is the power philosophy and this is why I said before concept formation is so important and understanding concept formation is so important from for particularly again mathematics because it's such an abstract field and it's so easy to lose grounding in in reality that that if you properly Define axioms and you properly Define what you're doing in math whether that is true and I I don't think it is this is uh yeah we'll leave it as an open mystery cuz actually this audience you know there's literally over 100,000 people that have PG and so they they know G's the complet theorem I I I have this intuition that there's something different to mathematics and philosophy that I'd love to hear from people like what what exactly is that difference because um there's a Precision to mathematics that philosophy doesn't have but that Precision gets you in trouble it somehow it actually takes you away from truth like the the very constraint of the language used in mathematics actually puts a constraint on the on the capture of truth that it's able to do so I'm going to argue that that is a comp a total product of the way you're conceptualizing the the terms within mathematics it's not in reality yes so it's you would argue it's in the fact that mathematics in in as much as is detached from reality that you can do these kinds of things yes and and you and you've and that mathematicians have uh come up with Concepts that they haven't grounded in reality properly that allows them to go off on on in places that have that don't lead to truth that's right that don't lead to truth but I encourage you then I encourage you to to to to do one of these uh podcast with one of our philosophers who know more about uh about this stuff um and if you if you move to Austin I've got somebody I'd recommend to you and can you throw a name out or no yeah I mean I would I would I would talk to GRE sary you say hour can you say what you mean by hour I'd say people who are affiliated with the adman Institute of philosophers were affiliated with objectivism right and Greg is one of our one of our brightest and and he's in Austin he's just got a position at at UT uh at the University of Texas uh and he and he one on Kate would be another one who actually works at the Institute and a chief philosophy officer at The Institute that's awesome and uh and there are others who specialize in Phil of science who who I think Greg could probably uh give you a lead but but these are unbelievably smart people who know this part of the philosophy much better than I do what uh can you just briefly perhaps say what is the irand Institute yeah so the irand Institute was a organization founded um three years after Iran died she died in 1982 and it was founded in 1985 to promote her ideas to make sure that her ideas and her novels are uh continued in the culture and were relevant well they they're relevant but what the people saw the relevance so our mission is to get people to read her books to engage in the ideas we teach we have a the objective is the academic center where we teach the philosophy uh primarily to graduate students and others who take the ideas seriously and who really want a a a deep understanding of the the philosophy and uh we apply the ideas so we take the ideas and apply them to ethics to philosophy to issues of the day um which is more my strength and more what what I tend to do I've you know I've never I've never formally studied philosophy so uh um all my education in philosophy is informal and um you know I'm an engineer and a finance guy that's that's my background so I'm I'm a numbers guy well let me uh I feel pretty under educated I have a pretty open mind which sometimes can be painful on the internet because people mock me or you know you know if I say something nuanced about communism people people immediately kind of put you in a bin or something like that it's it hurts to be open-minded to say I don't know to ask the question why is uh communism or Marxism so problematic why is capitalism problematic and so on but let me nevertheless go into that Direction with you uh maybe uh let's talk about capitalism a little bit how does objectivism compare relate to the idea of capitalism well first we have to Define what capitalism is because again people use capitalism in all kinds of ways and I know you had Ray Dalo on on your show Once I haven't I need to listen to that episode but Ray has no clue what capitalism is and that's that's that's that's his big problem um so when he when he says the real problems today in capitalism he's not talking about capitalism he's talking about problems in the world today and I agree with many of the problems but they have nothing to do with capitalism um capitalism is this is is a social political economic system in which uh all property is privately owned and in which the only role of government is the protection of individual rights I think it's the ideal system I think it's the right system for the reasons we talked about earlier it's a system that leaves you as an individual to pursue your values your life your happiness free of corosion of force and if and and you get to decide what happens to you and I get to decide if to help you or not right if you let's say you fall flat on your face people always say well what about the poor well if you if you care about the poor help them right just don't you know what do you need a government for you know I always ask audiences um okay if if there's a if there's a poor kid who can't afford to go to school and all the schools are private because capitalism is being instituted um and he can't go to school would you be willing to participate in a fund that that pays for his education every hand in the room goes up so what do you need government for just let's let's let's get all the money together and pay for schooling so the point is that what capitalism does is leave individuals free to make their own decisions and as long as they're not violating other people's rights in other words as long as they're not using cision force on other people then leave them alone and and people are going to make mistakes and people are going to screw up their lives and people are going to commit suicide people are going to do terrible things to themselves that is fundamentally their problem and if you want to help you under capitalism are free to help it's just the only thing that doesn't happen under capitalist is you don't get to impose your will on other people now how's that a bad thing so the the question then is how does uh the implementation of capitalism uh deviate from its ideal mhm in practice I mean this is what is the question with a lot of systems is how does it start to then fail so one thing maybe you can correct me or inform me it seems like information is very important like being able to uh make decisions to be free you have to have access full access of all the information you need to make rational decisions no that can be because it can be right because none of us has full access to all the information we need I mean what does that even mean and how how big how how much of the scope do you want to do right let's just start there yeah don't so you need you need to have access to information so one of the big criticisms of capitalism is there's asymmetrical information the drug maker has more information about the drug than the drug buyer right pharmaceutical drugs um true it's a problem well I wonder if one can think about an entrepreneur can think about how to solve that problem see I view any one of these challenges to capitalism as an opportunity for entrepreneur to make money and and they have the freedom to do it yeah so imagine an entrepreneur steps in and says I will test all the drugs that drug companies make and I will provide you for a fee with with the answer and how do I know he's not he's not going to be corrupted well there'll be other ones and they'll compete and who am I to tell which one of these is the right one well it won't be you really getting the information from them it'll be your doctor the doctors need that information so the doctor who has some expertise in medicine will be evaluating which rating agency to use to evaluate the drugs and which ones then to recommend to you so do we need an FDA do we need a government that siphons all the information to One Source that does all the research all the thing and has a clear incentive by the way not to approve drugs there's only because they don't make any money from it they nobody pays them for the information nobody pays them to be accurate they're bureaucrats at the end of the day and what is a bureaucrat what's the main focus of a bureaucrat even if they go in with the best of intentions which I'm sure all the scientists that the FDA have the best of intentions what's their incentive the the system builds in this incentive not to screw up because one drug gets P you and does damage you lose your job but if a 100 drugs that could cure cancer tomorrow don't ever get to Market nobody's going to nobody's going to come after you yeah and you're saying that's not that's not a mechanism that's um the marketplace is competition so if you won't approve the drug if I still think it's possible I will and it's not 01 you see the other thing that happens with the FDA is 01 it's either approved or it's not approved mhm oh it's approved for this but it's not approved for that but what if what if what if a drug came out and and and you said right you told the doctors this drug in 10% of the cases can cause patients an increased risk of heart disease you and your patients should we're not we're not forcing you but you should right it's your medical responsibility to evaluate that and decide if the drug is appropriate or not why don't I get to make that choice if I want to take on the 10% risk of heart disease so there was a drug and right now I forget the name but it was a drug uh against pain particularly arthritic pain and it worked it reduced pain dramatically right and some people tried everything and this was the only drug that reduced their pain and it turned out that in 10% of the cases it it caused the elevated risk didn't kill people necessarily but it caused elevated risk of heart disease okay what did the FDA do it banned the drug some people I know a lot of people who said living with pain is much worse than taking on a 10% risk again probabilities right people don't think in those numbers 10% risk of maybe getting heart disease why don't I get to make that choice why does some bureaucrat make that choice for me that's capitalism capitalism gives you the choice not you as an ignorant person you with your doctor and and a whole Marketplace which is not created to provide you with information and think about think about a world where we didn't have all these regulations and controls the the the the the amount of opportunities that would exist to create to provide information to educate you about that information would mushroom dramatically you know Bloomberg you know the billionaire Bloomberg you know how did he make his money he made his money by providing financial information by creating this service called Bloomberg that you buy a terminal and you get all this amazing information and he was before computers desktop computers I mean he was very early on in that whole Computing Revolution but his Focus was providing financial information to professionals and you hire a professional to manage your money that's the way it's supposed to be you know you have to have so you as an individual cannot have all the knowledge you need in medicine all the knowledge you need in finance all the knowledge you need in every aspect of your life you can't do that you have to delegate and you you hire a doctor now you should be able to figure out if the doctor's good or not you should be able to ask doctors for reasons for why and you have to make the decision at the end but that's why you have a doctor that's why you have a financial advisor that's why you have different people who you're delegating certain aspects of your life to but you want choices and what the marketplace provides is those choices so let's let me then this is this is what I do I'll make a dumb case for things and then you shut me down and then the internet says how dumb Lex is this is good this is how it works good at shutting down and and they're foolish in uh blaming you for the question because you're here to ask me questions let's let's make let me make a case for socialism so it's going to be bad because that's the only case there is for socialism that's reality so then perhaps it's not a case for socialism but just a certain notion that inequality the wealth and inequality that uh the bigger the gap between the poorest or the average and the richest the the more painful it is to be average psychologically speaking if you know that there is the CEOs of companies make 300 a th000 1 million times more than you do that makes life for a large part of the population less fulfilling that there's a relative notion to the experience of our life that even though everybody's life has gotten better over the past decades and centuries it may feel actually worse because you know that life could be so so much better in the life of these CEOs that uh yeah that Gap is fundamentally uh a thing that is undesirable in a society everything about that is wrong [Music] okay I like to start off like that yeah which so yeah I mean so my wife likes to remind me that as well as we've done in life we are actually from a wealth perspective closer to a homeless person than we are to Bill Gates just the math right just the math right it's a good go check when I look at Bill Gates I get a smile on my face I love Bill Gat I've never met Bill Gates I love Bill Gates yeah I I love what he stands for I love that he has hundred billion dollar I love that he has built a trampoline room in his house where his kids can jump up and down in a trampoline in a safe environment can we take another billionaire because I'm not if you're sure if you're paying attention but there's all kinds of conspiracy theories about Bill Gates so let well but that's part of the story right they have to pull him down because people resent him for other reason that's strange but yes we can take Jeff Bezos we can sa you know my favorite stoically just because I I like I like a lot about him was was Steve Jobs um I mean I love these people and I can't there are very few billionaires I don't love in a sense that I appreciate everything they've done for me for people I cherish and love they've made the world a better place why would it ever cross my mind that they make me look bad because they're richer than me or that I don't have what they have they've made me so much richer that they've made inventions that used to cost millions and millions and millions of dollars accessible to me I mean this is a supercomputer in my pocket now but think about it right what is the difference between and and I'll get to the essence of your point in a minute but think about what the difference is between me and Bill Gates in terms of because it's true that in terms of wealth I'm closer to the homeless person but in ter in in terms of my day-to-day life I'm closer to Bill Gates you know we both live in a nice house his is nicer but we live in a nice house his is bigger but mine is plenty big we both drive cars his is nicer but we both drive cars cars 100 years ago what cause we both fly can fly get on a plane in Los Angeles and fly to New York and get there about the same time we're both flying private the only difference is my private plane I share with 300 other people and here's but it's accessible it's relatively comfortable again in the perspective of 50 years ago 100 years ago it's unimaginable that I could fly like that for for such a low feet we live very similar lives in that sense um so I don't resent him so first of all I'm an exception to the supposed rule that people resent I don't think anybody I don't think people do resent unless they're taught to resent and this is the key people are taught and I've seen this in America and this is to me the most horrible shocking thing that has happened in America over the last 40 years I came to America so I'm an immigrant I came to America from Israel in 1987 and I came here because I thought this was the place where I could where it had the most opportunities and it is most opportunities and I came here cuz I believ there was some a certain American Spirit of individualism and exactly the opposite of what you just described a a a sense of I live my life it's my happiness I'm not looking at my neighbor I'm not competing with the Joneses the American dream is my dream my two kids my dog my station wagon not because other people have it because I want it and that sense and when I came here in the 80s you had that you had you still had it it it it was less than I think it had been in the past but you had that Spirit there was no Envy there was no resentment there were rich people and and they were celebrated there was still this admiration for entrepreneurs and admiration for Success not by everybody certainly not by the intellectuals but by the average person I have witnessed particularly over the last 10 years a complete transformation and America's become like Europe I know are you Russian yeah yeah it's become Russian in a sense where you know they've always done these studies um you know I'll give you $100 and your neighbor $100 or I'll give you or is it or give you uh ,000 but your neighbor gets $10,000 and a Russian will always choose the $100 right he he he wants equality above being better himself yeah Americans would always choose that Gap sense is not anymore and it's changing because we've been told it should change and morally you're saying that doesn't make any sense so there's no sense in which let me put another spin I forget the book but the sense of if you're working for Steve Jobs and you your hands you're the engineer behind the iPhone and there's a sense in which his salary is stealing from your efforts because I forget the book right that's literally the terminology is used this this is straight out of K MOX well sure it's it's also straight but out of car MOX but like there's no sense morally speaking that you see that the other way around that engineer stealing off of and and it's not stealing right it's not but the engineer getting more from from Steve Jobs by a lot not by a little bit than Steve Jobs is getting from the engineer the engineer even if they're a great engineer they're probably other great Engineers that could replace him would he even have a job without Steve Jobs would the industry exist without Steve Jobs without the Giants that carry these things forward and let me ask you this I mean you're a scientist yes do you resent Einstein for being smarter than you I mean you NVM do you are you angry with him would you would you would you feel negative towards him if he was in the room right now or would you if you came into the room you'd say oh my God I mean you interview people who I think some of them are probably smarter than you and me yeah for sure and your attitude towards them is one of reverence well one interesting little side question there is what is the natural state of being for us humans you kind of implied education has uh polluted our minds but like if I because you're referring to jealousy the Einstein question the Steve Jobs question I wonder which way if we're left without education would we naturally go so there is no such thing as the Natural State in that sense right this is this is the myth of of Russo's uh uh noble savage and of John Walls is behind the veil of ignorance well if you're ignorant you're ignorant there you can't make any decisions you're just ignorant you're there is no human nature that determines how you will relate to other people you will relate to other people based on the conclusions you come to about how to relate to other people you can relate to other people as values to use your terminology from the perspective of love this other human being is a value to me and I want to trade with them and trade the beauty of trade is its win-win I want to benefit and they are going to benefit I don't want to screw them I don't want them to screw me I want this to be win-win or you can deal with other people as threats as enemies much of human history we have done that and therefore as a zero sum world what they have I want uh I I will take it I will use Force to take it I will use political force to take it I will use the force of my arm to take it I will just take it so um those are two options right and and they will determine whether we live in ization or not and they are determined by conclusions people come to about the world and the nature of reality and the nature of morality and the nature of politics and all these things they're determined by philosophy and this is why philosophy is so important because so philosophy shapes it's Evolution doesn't do this it doesn't just happen ideas shape how we relate to other people and you say well little children do it well little children don't have a fontal cortext why it's not relevant right what happens with as you develop a fontal cortex as you develop the brain you learn ideas and those ideas will shape how you relate to other people and if you learn good ideas you relate to other people in a healthy productive win-win and if you develop bad ideas you will resent other people and you will want their stuff and the thing is that human progress depends on the win-win relationship it depends depends on civilization depends on peace it depends on allowing people going back to what we talked about earlier allowing people the freedom to think for themselves and anytime you try to interrupt that you're causing damage so this change in America is not some reversion to a natural state it's a shift in ideas we we still live the better part of American society and the world still lives on the remnants of the Enlightenment the Enlightenment ideas uh the ideas that brought about this scientific revolution ideas that brought about the creation of this country and it's the same basic ideas that led to both of those and as those ideas get more distant as those ideas are not defended as those ideas disappear as Enlightenment goes away we will become more violent more resentful more tribal more obnoxious more unpleasant more primitive a very specific example of this though that bothers me i' be curious to get your comment on so Elon Musk is a billionaire yeah and one of the things that really maybe it's almost a pet peeve it it really bothers me when the press and the general public will say well all those rocket they're sending up there those are just like the toys the games that billionaires play that to me billionaire has become a dirty word to use like as if money can buy or has anything to do with Genius Like I I'm trying to articulate a specific um line of uh question here because it's just it just bothers me I guess the question is like why how do we get here and how do we get out of that because Elon Musk is doing some of the most incredible things that a human being has ever participated in mostly not he doesn't build the Rockets himself he's getting a bunch of other Geniuses together that have that takes genius that takes genius but why where did we go and how do we get back to where Elon Musk is an inspiring figure as opposed to a billionaire playing with some toys so this is the role of philosophy it goes back to the same place it goes back to our understanding of the world and our role in it and if you understand that the only way to become a billionaire for example is to create value value for whom value for people who are going to consume it the only way to to become a billionaire the only way Elon Musk became a billionaire is through PayPal now PayPal is something we all use PayPal is an enormous value to all of us it's why it's worth several billions of dollars which Alon musk could then you know earn but you cannot become a billionaire in a free Society by exploiting people you cannot because you'll be you'll be laughed nobody will deal with you nobody will have any interactions with you the only way to become a billionaire is to do billions of win-win transactions so the only way to become a billionaire in a fee Society is to change the world to make it a better place billionaires are the the great humanitarians of our time not because they give charity but because they make them billions and it's true that money and genius are not necessarily correlated but you cannot become a billionaire without being super smart you cannot become a billionaire by figuring something out that nobody else has figured out in whatever realm it happens to be and that thing that you figure out has to be something that provides immense value to other people where do we go wrong we go wrong our culture goes wrong because it views billionaires as self-interested as selfish and there's a sense in which and not a sense it's absolutely true the billionaire doesn't ask for my opinion on what product to launch Elon Musk doesn't ask others what they think he should spend his money on what the greatest social well-being will be Ellen I mean there a sense in which the Rockets areest toys there's a sense in which he chose that he would have he would be inspired the most yes he would have the most fun by going to Ms and building rockets and he he's probably dreamt of rockets from when he was a kid and probably always played with rockets and now he has the funds the capital to be able to deploy it so he's being selfish obviously he's being self-interested this is what Elon Musk is about I mean uh the same with with uh Jeff beus there's no committee to decide with whether to invent you know to to invest in cloud computing or not BOS decided that and at the end of the day they are the bosses they pursue the values they believe are good they pursue they create the wealth it's their decisions it's their mind and the fact is we live in a world where for 2,000 plus years self-interest even though we all do it to small extent or the less we deem it as abhorent it's bad it's wrong I mean your mother probably taught you the same thing my mother taught me think of others first think of yourself last the good stuff is kept for the guests you never get to use the good stuff you know it's others that's what the focus of morality is now no mother even no Jewish mother actually believes that right because they don't really want you to be last they want you to be first and they push you to be be first but morally they've been taught their entire lives and they believe that the right thing to say and to some extent do is to argue for sacrifice for other people right so most people 99% of people are torn yeah they they know they should be selfless sacrifice live for other people they don't really want to so they act selfishly in their day-to-day life and they feel guilty and they can't be happy they can't be happy and Jewish Mothers and Catholic mothers are excellent at using that guilt to manipulate you but the guilt is inevitable because you you've got these two conflicting things the way you want to live and the way you've been taught to live and what objectivism does is it at the end of the day provides you with the way to unite morality a proper morality with what you want and to think about what you really want to to conceptualize what you really want properly so what you want is really good for you and what you want will really lead to your happiness so you know we reject the idea of sacrifice we reject the idea of living for other people but that's but you see if if if you believe if you believe that the purpose of morality is to sacrifice for other people and you look at Jeff Bezos when was the last time he sacrificed anything right he's living pretty well he's got billions he could give it all away and yet he doesn't how dare he you know in my in my talks I often position and I'm going to use Bill Gates sorry guys dro the conspiracy theory they're all Bs complete and utter nonsense there's not a shred of Truth he you know I disagree with Bill Gates on everything political I think he politically is a complete ignoramus but the guy's a genius when it comes to technology and and when he's just thoughtful even in his philanthropy he just uses his mind and I respect that even though politically he terrible anyway think about this who who had a bigger impact on the lives of poor people in the world Bill Gates or Mother Teresa Bill Gates it's not even close and Mother Teresa lived this altruistic life to the core she lived it consistently and yet she was miserable pathetic horrible she hated her life she she she she was miserable and most of people she helped didn't do very well because she just helped them not die right yeah and then Bill Gates changed all and he helped a lot of by providing technology even philanthropy gets to them the food gets them much F more efficient yet who is them all Saint sainthood is not determined based on what you do for other people Saint it is based on how much how much pain you suffer I like to ask people to go to a museum and look at all the paintings of saints how many of them are smiling and are happy they've used to got arrows through them and holes in their body and they're just suffering a horrible death the whole point of the morality we are taught is that happiness is immorality that ha happy people cannot be good people and that good people suffer and that suffering is necessary for Morality morality is about sacrifice self-sacrifice and and suffering and at the end of the day almost all the problems in the world boil down to that false view so can we try to talk about part of it the problem of the word selfishness but let's talk about the virtue of selfishness so let's start at the fact that for me I really enjoy doing stuff for other people I enjoy being uh cheering on the success of others why I don't know it's deep think about it why cuz I think you do know if I were to really think I I don't I don't want to resort to like evolutionary arguments are like this is so I I think so I can tell you why I enjoy helping others maybe you can go there like one thing cuz we'll should talk about love a little bit I'll tell you there there's a part of me that's a little bit not rational like there's a gut that I follow that uh not everything I do is perfectly rational like for example my dad uh criticizes me he says like you should always have a plan like it it should make sense you have a strategy and and and I say that you know I left I stepped down for my full cell position on MIT I there's so many things I did without like a plan it's the gut it's like I want to start a company well you know how many companies fail I don't know I % I it's a gut and the same thing of being kind to others is is a gut like I watch the way that Karma Works in this world that the people like us one guy look up to his Joe Rogan that he does stuff for others and that the joy he experiences the way he sees the world like just the the the glimmer in his eyes because he does stuff for others that creates a joyful experience and that somehow is seems to be an instructive way to that to me is inspiring of a of a life well lived but you probably know a lot of people who have done stuff others were not happy true so I don't think it's the doing stuff for others that just brings the happiness it's why you do stuff for others and what else you're doing in your life and and what what is the what is the proportion but it's why at the end of the day which is which is and it's the same look you can you can maybe through a gut feeling say I want to start a company but you better start doing thinking about how and what and all of that and to some extent the why because if you really want to be happy doing this you may better make sure you're doing it for the right reason so I'm not you know there's something called Fast thinking colan the the the the the the Daniel Conan no Daniel colan talks about and and there is it's it's it's you know all the Integrations you've made so far in your life cause you to have specialized knowledge in certain things and you can think very fast and and and your gut tells you what that what the right answer is it's but it's not it's it's your mind is constantly evaluating and constantly working um you want to make it as rational as you can not in the sense that I have to think through every time I make a decision but that they've so programmed my mind in a sense that the answers are the right answers you know in in in uh when I get them so you know I like I view other people as a value other people contribute enormously to my life uh whether it's a romantic love relationship or whether it's a friendship relationship or whether it's just you know Jeff Bezos creating Amazon and and delivering goodies to my home when I get them and and and people do all that right it's not just Jeff Bezos he gets the most credit but everybody in that chain of command everybody at Amazon is working for me I love that I love the idea of a human being I love the idea that there are people capable of of being an Einstein of being you know and and creating and building and making stuff that makes my life so good I you know most of us like this is not a good room for an example most of us like plants right we like pets I don't particular but people like pets why we like to see life yeah human beings are life on steroids right they're life with a brain it's amazing right what they can do I love people now that doesn't mean I love everybody because there's some they really bad people out there who I hate right and I do hate and there are people out there that are just I have no opinion about but generally the idea of a human being to me is a phenomenal idea when I see a baby I light up because to me there's a potential you know uh there's a there's this magnificent potential that is embodied in that and when I see people struggling and need help I think they're human beings they you know they embody that potential they embody that goodness they might turn out to be bad but why would I ever give the presumption of that I give them the presumption of the positive and I cheer them on and and I and I and I enjoy watching people succeed seed I enjoy watching people get to the top of the mountain and and produce something even if I don't get anything directly from it I enjoy that because it's part of my enjoyment of life so the word so to you the morality of selfishness this kind of love of other human beings the love of Life fits into a morality of selfishness can't not because it it's it you there's no context in which you can truly love yourself without loving life and loving what it means to be human so you know the love of yourself is going to manifest yourself differently in different people but it's core what do you love about yourself you you first of all I love I love that I'm alive I love that I you know I not love this world and the opportunities it provides me and the the the fun and the excitement of discovering something new and meeting a new person and and having a conversation uh you know all of this is is is is immen enjoyable but behind all of that is is a particular human capability that not only I have other people have and the fact that they have it makes my life so much more fun because so it's it's you cannot view you know it's all integrated and you cannot view yourself in isolation now that doesn't that doesn't place a moral commandment on me uh help everybody who's poor that you happen to meet in the street it doesn't place a burden on me in a sense that now I have this moral duty to help everybody it leaves me free to make decisions about who I help and who I don't there's some people who I will not help there's some people who I do not wish positive things upon bad people should have bad outcomes bad people should suffer so and you have the freedom to choose who's good who's bad within your your decision based on your values now I think there's an objectivity to it there's a there's a standard by which you should valuate good versus bad and that standard should be to what extent that they contribute or hurt human life the standard is human life and so when I say look at the Jeff beos I say he's contributing to HBA life good guy I might disagree with him on stuff we might disagree about politics we might disagree about women women dis I don't know what we agree but overall big picture he is pro-life right I look at somebody like you know to take like 99.9% of our politicians and they are pro death they're Pro destruction they're Pro cutting Corners in ways that destroy human life and human potential and human ability so I literally hate almost every politician out there and I wish ill on them right I don't want them to be successful or happy I want them all to go away right leave me alone so I Believe In Justice I believe good things should happen to good people and bad things should happen to bad people so I can I make those generalizations based on this one you know on the other hand if you know I shouldn't say all politicians right so if I you know I love Thomas Jefferson and and and George Washington right I love Abraham Lincoln I love people who fought for freedom and who believed in Freedom who had this ideas and who lived up to at least in parts of their lives to those principles now do I think Tom jeffson was flawed because he held slaves absolutely but the virtues way outweigh that in my view and I understand people who don't accept that you don't have to also love and hate the entirety of the person there parts that person that you that you're attracted the major part is pro-life and therefore I'm Pro that person and and I think and I said earlier that objectivism is philosophy of love and I I I believe that because objectivism is about your life about loving your life about embracing your life about engaging with the world about loving the world in which you live about win-win relationships with other people which means to a large extent loving the good in other people and the and the best in other people and encouraging that and supporting that and promoting that so I know selfishness is a harsh word because the culture is given it that harshness selfishness is a harsh word because the people who don't like selfishness want you to believe it's a harsh word but it's not what does it mean it means focus on self it means take care of self it means make yourself your highest priority not your only priority because in taking care self what would me what what would I be without my wife what would I be with without the people who are who who who support me who help me who who who I have these love relationships with it it so other people are crucial what would my life be without you know Steve J Steve Jobs right a lot of uh things you mentioned here are just be beautiful so one is win-win so one key thing about this uh selfishness and the idea of objectivism is a philosophy of Love is that you don't want parasitism so that goes that is unethical so you actually first of all you say it win-win a lot and I I just like that terminology because it's a good way to see life it's try to maximize the number of win-win interactions absolutely that's a good way to see business actually right well life generally I think every aspect of life you you want to have a win-win relationship with your wife imagine if it was win lose either way if you win and she loses how long is that going to sustain so win lose relationships are not in equilibrium what they turn into is lose lose like win lose turns into lose lose and the so the alternative the only alternative to lose lose is win- win and you win and the person you love wins what's better than that right that's the way to maximize so like the selfishness is you're trying to maximize the win but the way to maximize the win is to to maximize the win win yes and and it turns out and Adam Smith understood this a long time time ago that if you focus on your own winning while respecting other people as human beings then everybody wins and the beauty of capitalism if we go back to capitalism for a second the beauty of capitalism is you cannot be successful in capitalism without producing values that other people appreciate and therefore willing to buy from you and they buy them at and and this goes back to that question about the engineer and Steve Jobs why is the engineer working there because he's getting paid more than his time is worth to him I know people don't like to think in those terms but that's the reality if his time is worth more to him than what he's getting paid he would leave so he's winning and is Apple winning yes because they're getting more productivity from him they're getting more from him than what he's actually producing it's it's tough it's tough because there's uh human psychology and imperfect information it just makes it a little messier than the the clarity of thinking you have about this it just you know because I for sure but not everything in life is an economic transaction It ultimately is close but even if it's not an economic transaction even if it's a if it's a if it's a relationship transaction when you get to a point with a friend where you're not gaining from the relationship friendship's going to be over not immediately because it takes time for these things to manifest itself and to really absorb and to but we change friendships we change our loves right we fall in and out of love love we fall out of love because we're not love so let's let's go back to love right love is the most selfish of all emotions love is about what you do to me right so I love my wife because she makes me feel better about myself yeah so you know the idea of Selfless Love is bizarre so Ein Rand used to say before you say I love you you have to say the I and you you have to know who you are and you have to appreciate yourself if you hate yourself what does it mean to love somebody else so my I love my wife CU she makes me feel great about the world yeah and she lives me for the same reason and so I Randy used to use this example imagine you go up to your um to be spouse the night before the wedding and you say you know I get nothing out of this relationship I'm doing this purely as an act of noble self-sacrifice she would slap you yeah as she should right so it no we know this intuitively that love is selfish but we afraid to admit it to ourselves and why because the other side has convinced us that selfishness is associated with exploiting other people yeah selfishness means lying cheating stealing walking on corpses backstabbing people but is that ever in your self-interest truly right I you know I I I'll offer be in front of an audience to say okay how many people here have lied you know kidding right how many of you think that that if you did that consistently that would make your life better nobody thinks that right because everybody's experienced how shitty lying not because of how it makes you feel out of a sense of guilt existentially just a bad strategy yeah right you get caught you have to create other lies to cover up the previous lie it screws up with your own psychology and your own cognition you know the mind to some extent like a computer right is an integrating machine and in computer science I understand there's a term called garbage in garbage out lying is garbage in yeah so it's not good strategy cheating uh screwing your customers in a business not paying your suppliers as a businessman not good business practices not good practices for being alive so win-win is both model and practical in the beauty of ir man's philosophy and I think this is really important is that the model is the Practical and the Practical is the m and therefore if you are marrow you will be happy yeah that that's the the con that's why the application of the philosophy of objectivism is so easy to practice so like or to discuss or possible to discuss that's why you talk about clearcut I'm not ambiguous about my view and it's fundamentally practical I mean that's the best of philosophies is is practical yes it's in a sense teaching you how to live a good life and it's teaching you how to live a good life not just as you but as a human being and therefore the principles that apply to you probably apply to me as well and if we both share the same principles of how to live a good life we're not going to be enemies when you brought up Anarchy earlier uh it's an interesting question because you've kind of said politicians I mean part of it just is a little bit joking but politicians are you know not good people yeah so but we should have some so so you you have an opposition to anarchism so they first of all they want always not bad people that is I gave examples of people who engage in political life who I think were good people basically um and and but they think they get worse over time if the system is corrupt and I think the system fortunately even the American system as good as it was was founded on quicksand and have corruption built in uh they didn't quite get it and and they needed Iran to get it I'm not blaming them I don't think they they show any blame you needed a philosophy in order to completely fulfill the promise that is America the promise that is the founding of America so the the place where corruption sneaked in is a lack in some way of the philosophy underlying the nation absolutely so so the it's it's Christianity it's it's it's you know not they hit on another controversial topic it's religion uh which un which undercut their morality so the founders were explicitly Christian and and altruistic in their morality implicitly in terms of their actions they were completely secular and they were they were very secular anyway but in their morality even they were secularist so there's nothing in Christianity that says that the that the you have an inable right to pursue happiness that's unbelievably self-interested and a and a based on on kind of a m philosophy of ego of egoistic moral philosophy but they didn't know that and they didn't know how to ground it they implicitly they had that fast thinking that gut that told them that this was right and the whole Enlightenment that period from John lock on to really to to um to Hume that period is about Pursuit of Happiness using reason in pursuit of the good life right but they can ground it they don't really understand what reason is and they don't really understand what happiness requires and they can't detach and F from Christianity they're not allowed to politically and they I think conceptually you just can't make that big break Rand is an Enlightenment thinker in that sense she is what should have followed right after right she should have come there and grounded them in the secular and in the egoistic and the oratian view of morality as as as a a as a as a code of values to basically to guide your life to guide your life towards happiness that's Aristotle view right um so they didn't have that so you you know so I think that government is necessary it's not a necessary evil it's a necessary good because it does something good and the good that it does is eliminates corosion from society it eliminates violence from society it eliminates the use of force between individuals from society and that but but see the argument like Michael M make give me a chance here yeah is uh why can't you apply the same kind of uh reasoning that you've effectively used for the rest of uh mutually agreed upon institutions that are driven by capitalism that we can't also hire forces to protect us from the violence to ensure the stability of society that protects us from the violence why violent why draw the line at this particular place right well because there is no other place to draw a line and they and there is a line and by the way we draw lines other places right um we uh we don't vote we don't um we don't have we don't determine truth and science based in competition right so that's a that's a line but first of all some people might say I mean there's competition in a sense that you have alternate theories but at the end of the day whether you decide that this he's right or he's right is not based on the market it's based on facts on reality an objective reality you have to you and and some people will never accept that this person is right because they don't see the Stream So first of all what they reject what most anarchists reject even if they don't admit it or recognize it is they object they they reject objective reality and in which sense so like right so there's a whole so the the whole realm of law is a scientific realm to Define for example the boundaries of private property it's not an issue of competition it's not an issue of of of um of I have one system and you have another system it's an issue of objective reality and now it's more difficult than science in a sense because it's more difficult to prove that my conception of property is correct and you're correct but there has there is a correct one in reality there's a correct vision it's more abstract but look somebody has to decide what property is so I have I have Define my property is defined mhm by certain boundaries and I have a police force and I have a Judiciary System that backs my vision and you have a claim against my property you have a claim against my property and you have a police force and a judicial system that backs your claim who's right so the our definitions of property are different yes our definitions of property or our claim on the property is different so why why we just agree on the definition of property and but why should we agree right your judicial system as one definition of property my judicious system is now you you think that there's no such thing as intellectual property rights and your whole system believes that yeah and my whole system believes there is such thing so you are duplicating my books and handing them out to all your friends and not paying me a royalty yeah and I I think that's wrong my judicial system and my police force think that's wrong and we're both living in the same geographic area right so I we have overlapping jurisdictions yeah now the anarchist would say well we'll negotiate why should we negotiate my system is actually right there is such a thing as intellectual property rights there's no negotiation here you're wrong and you should either pay a fine or go to jail yeah but why can't because it's a community there multiple there's multiple parties and it's like a majority vote they'll they'll hire different forces that says yeah youran is is is on to something here with the definition of property and we'll go with that so Anarchist Pro democracy in in the in the majority rule sense I think so I I think Anarchy you know promotes like emergent democracy right like no it doesn't it it it I'll tell you what it it promotes it promotes emergent uh strife and civil war and violence constant uninterrupted violence cu the only way to settle the dispute between us since we both think that we are right and we have guns behind us to protect that and we have a legal system we have a whole theory of ideas is is you're stealing my stuff how do I get it back I invade you right I take over you know and and who's G to who's going to win that battle the smartest guy no the guy with the biggest guns see but the anarchist would say that they're using implied like the state uses imp Force they're already doing violence because they they they take the state as it is today and they refuse to engage in the conversation about what a state should and could look like and how we can create mechanisms to protect us from the state using those those D but look this is my view of Anarchy is very simple it's a ridiculous position it's infantile I mean I really mean this right and and I'm sorry to Michael but and and all the other very very smart very very smart an because Anarchist is never you won't find a dumb Anarchist right because dumb people know it wouldn't work you have to have it's absolutely true you have to have a certain IQ to be an anarchist that's true they're all really intelligence all intelligence and the reason is that you have to create such a mythology in your head you have to create so many rationalizations any Jo the street knows it doesn't work because they can understand what happens when two people who are armed are in the street and have a dispute and there's no mechanism to resolve that dispute yeah that's objective that's SE and this is where it gets the objective that's objective the whole point of government is that it is the objective Authority for determining the truth in one Regard in regard to force because the only alternative to determining it when it comes to force is through Force the only way to resolve disputes is through force or through this negotiation which is unjust because if one part's right and one part's wrong why negotiate and and this is the point I'm not against competition of governance I'm all for competition of governance we do that all the time it's called countries the United States has a certain governance structure the Soviet Union had a governance structure Mexico has a government structure CH and they're competing yeah and we can observe the competition we and in a in my world you could move freely from one governance to another if you didn't like your governance you would move to a better governance system but they have to have autonomy within a geographic area otherwise what you get is complete and utter Civil War the law needs to be objective and there needs to be one law over a piece of ground and if you disagree with that law you can move somewhere else where they me this is why Federalism is such a beautiful system even within the United States we have States and on certain issues we're allowed to disagree between states like the death penalty some states do some states don't fine and now I can move from one state if I don't like it but there's certain issues you cannot have disagreement slavery for example this is why we had a civil war but let me one other argument against Anarchy markets exist with forces has being eliminated sorry can you say that again Marcus markets exist where the rule of force has been eliminated the rule of force yes elate so a market will exist if we know that you can't pull a gun on me and just take my stuff I am willing to engage in transaction with you if we have an implicit understanding that we're not going to use Force against each other so the force has a something special to it yes it's a special it overrides cuz we are still agreeing we can manipulate each other yes but Force we can force kind of there's something fundamental about violence force is a is a fundamental Force it's the anti-reason it's the anti-life it's the anti- force against another person and it what it does it shuts down the mind right so in order to have a market you have to extract Force that's F how can you have a Market in force yeah when I there's an Instagram Channel called nature is metal where it has all these videos of animals basically having a market of force yes but that shuts down the ability to reason an animals don't need to because they can't exactly so the Innovation that is human beings is our capacity to reason and therefore the relegation of force to the animals we don't do Force civilization is where we don't have force and so what you have is you cannot have a market in that which a market requires the elimination of it and I you know I I don't debate formally these guys but I interact with them all the time right and and you get these absurd arguments where you know David Freedman will say that's Milton freedman's son he will say something like well in Somalia in the northern part of Somalia where they have no government you have all these wonderful you have these tribal uh uh tribunals of these tribes and they resolve disputes yeah barbarically they Sharia law they have no respect for individual rights no respect for property and the only reason they have any Authority is because they have guns and they have power and they have force and they do it barbarically there's nothing civilizing about the courts of Somalian and and they write about Pirates and because they view Force they don't view Force as something unique that must be extracted from human life and that's why Anarchy has to devolve into violence because it treats Force as just what's a big deal we negotiating you know over guns so we we covered a lot of high level philosophy but I'd like to touch on the troubles the chaos of the day yeah a couple of things and I really trying to find a hopeful path way out so one is the current Corona virus pandemic or in particular not the virus but our handling of it is there something philosophically politically that you would like to see that you would like to recommend that you would like to maybe give a hopeful message if we take that kind of trajectory we might be able to get out because I'm kind of worried about the economic pain that people are feeling that there's this quiet suffering I mean I agree with you completely there is a quiet suffering it's horrible I mean I know people you know I I go to a lot of restaurants what one of the things we love to do is is eat out my wife doesn't like cooking anymore we don't have kids we don't have kids in the house anymore so she doesn't have to so we go out a lot we go to restaurants and because we have our favorites and we go to them a lot we get to know the owners of the restaurant the chef the and it's just heartbreaking you know these people put their life you know they Blood Sweat and Tears I mean real Blood Sweat and Tears into these projects restaurants are super difficult to to manage most of them go bankrupt anyway and and the restaurants we go to a good restaurant so they've done a good job and they've they've they they offer unique value and they shut them down and you know many of them will never open you know something like they estimate 50 60% of restaurants in some places won't open these are people's lives these are people's Capital these are people effort these are people's Love talk about love they love what they do particularly if they're the chef as well and it's gone and it's disappear and what are they going to do with their lives now they're going to live off the government the way our politicians would like them bigger and bigger stimulus plans so we can hand checks to people to get them used to living off of us rather than it's disgusting and it's offensive and it's unbelievably sad and this is where it comes to this I care about other people I mean this idea that objectivist don't care I mean I love these people who who provide me with pleasure of eating wonderful food in in a great environment is there something inspiring about them too like when I see a great restaurant I want to do better with my my own stuff yeah exactly it's it's it's they're inspiring anybody who does it is excellent I love sports because it's the one realm in which you still value and celebrate Excellence I but I try to celebrate Excellence everything in my life so I I you know I try to be nice to these people and you know with Co we we went more to restaurant if Believe it or and we did more takeout stuff we made an effort particularly the restaurants we really love to to keep them going to encourage them to support them the problem is the problem is philosophy drives the world the response the covid has been worse than pathetic um and it's driven by philosophy it's driven by disrespect to science uh ignorance and disrespect of Statistics uh a disrespect of individual human decision-making government has to decide everything for us a and and just throughout the process in a disrespect of markets because we didn't let markets work to to to facilitate what we needed in order to deal with this virus if you look at at the pl it's interesting that the only place on the planet that's done well with this are parts of Asia right Taiwan did phenomenally with this and the vice president of Taiwan is a epidemiologist so he knew what he was doing and they got it right from the beginning South Korea did did amazing even Hong Kong and Singapore it's you know Hong Kong is just very few deaths and economy wasn't shut down in any of those places there were no lockdowns in any of those places the CDC had plans before this happened and how to deal with good plans indeed if you ask people around the world before the pandemic which country is best prepared for a pandemic they would have said the United States because of the cdc's plans and all of our emergency reserves and all that and the wealth and yet all of that went out the window because people panicked people didn't think go back to reason people were arrogant uh refused to to to to use the tools that they had at their disposal to deal with this so you deal with pandemics it's very simple how you deal with pandemics and this is how South Korea and Taiwan and you deal with them by not by uh testing tracing and isolating that's it yeah and you do it well and you do it vigorously and you do it on scale if you have to and you scale up to do it we have the wealth to do that so one uh question I have it's a difficult one um so I talk about love a lot and you've just talked about Donald Trump I guarantee you they'll this particular segment will be full of division from the internet yes but I believe that should be and can be fixed what I'm referring to in particular is the division because we've talked about the value of reason and what I've noticed on the Internet is the division shuts down reason so when people will hear you say Trump actually the first sentence you said about Trump they'll hear Trump and their ears will per up and they'll immediately start in that first sentence they'll say is he a trump supporter or a they're not interested in anything else after that and then after that that's it and what how do so my question is you as one of the beacons of intellectualism quite honestly I mean it sounds silly to say but yeah you are a beacon of Reason how do we bring people together long enough to where we can reason I mean there's no easy way out of this because the fact that people have become tribal and they have very tribal uh and and the tribe uh in the tribe reason doesn't matter in the it's all about emotion it's all about belonging or not belonging and you don't want to stand out you don't want to have a different opinion you want to belong and it's all about belonging it took us decades to get back to tribalism where we were hundreds of years ago it took Millennium to get out of tribalism it took the enlightenment to get us to the point of individualism where we think for in reason respect for reason before that we were all tribal so it took the enlightenment to get us out of it we've been in the enlightenment for about 250 years influenced by the Enlightenment and we're and it's fading the impact is fading so what would we need to get out of it we need self-esteem people join a tribe because they don't trust their own mind people join a tribe because they're afraid to stand on their own two feet they're afraid to think for themselves they're afraid to be different they're afraid to be unique they're afraid to be an individual people need self-esteem to gain self-esteem they have to they have to have respect for rationality they have to think and they have to achieve and they have to recognize that achievement um to do that they have to be they have to have respect for thinking they have to have to respect for reason uh and we have to and and think about the schools we have to have schools that teach people to think teach people to to Value their mind we have schools that teach people to feel and value their feelings we have groups of six-year-olds sitting around a circle discussing politics what they don't know anything they're ignorant see you don't know anything when you're ignorant yes you can feel but your feelings are useless as as as decision-making tools but but but we emphasize emotion it's all about socialization and emotion this is why they talk about this generation of snowflakes they can't hear anything that that they're opposed to because they've not learned how to use their mind how to think um so it boils down to teaching people how to think two things how to think and how to care about themselves so it's it's thinking of self-esteem and they're connect it because when you think you achieve which gains you gains your self-esteem when you have self-esteem it's easier to think for yourself and I don't know how you do that quickly I mean I think leadership matters so you know part of what I try to do is try to encourage people to do those things but I am a small voice you you asked me when early on you said we should talk about why I'm not more famous I'm not famous you know my following is not big it's very small in in a in in the in the in the scope of things well yours in objectivism and that question could you Linger on it for a moment why isn't objectivism more famous I think because it's so challenging it it's it's not challenging to me right when I first encountered objectivism it's like after the first shock and after the first uh kind of none of this can be true this is all Bs and fighting it once I got it it was EAS it was easy it required years of studying but it was easy in the sense of yes this makes sense but it's challenging because it upends everything it really says what my mother taught me is wrong and what my politicians say left and right is wrong all of them there's not a single politician on which I agree with on almost anything right because on the fundamentals we disagree and what might teachers are telling me is wrong and what Jesus said is wrong and it's hard but the thing is so you you talk about politics and all that kind of stuff but you know most people don't care the the the more powerful thing about objectivism is the Practical of my life of how I revolutionize my life and it that feels to be like a very important and appealing you know get your together kind of yeah but this is why this is why Jordan Peterson is so much more successful than we are right why is it make your bed or whatever make bed yeah because his personal responsibility is shallow it's make your bed stand up straight it's what my mother told me when I was growing up there's nothing new about Jordan Peterson he says Embrace Christianity Christianity is fine right religion is okay just do these few things and you'll be fine and by the way he says happiness you know you either have it or you don't you know it's random you don't actually you can't bring about your own happiness so he's given people an easy out people want easy outs people buy self-help books that give them five principles for living a you know shallow I'm telling them think stand on your own two feet be independent don't listen to your mother do your own thing but thoughtfully not based on emotions so you're responsible not just for a set of particular habits and so on you're responsible for everything yes and you respon here's here's the big one right you're responsible for shaping your own soul your Consciousness you get to decide what it's going to be like and the only tool you have is your mind your only tool is is is your mind well your emotions play a tool when they're properly cultivated they play a role in that and the tools you have is thinking experiencing living coming to the right conclusions you know listening to great music and and watch watching good movies and and and and art is very important in shaping your own soul and helping you do this it's got a it's got a crucial role in that but it's work and it's lonely work because it's work you do with yourself now if you find somebody who you love who shares these values and you can do with them that's great but it's monly lonely work it's hard it's challenging it's ends your world the reward is unbelievable but but even at the think about think about the enlightenment right so up until the enlightenment where was truth truth came from a book and there were a few people who understood the book most of us couldn't read and they conveyed it to us and they just told us what to do and in that sense life's easy it sucks and we die young and we have nothing and we don't enjoy it but it's easy and then Enlightenment comes around and says we've got this tool it's called reason and allows us to discover truth about the world it's not in a book it's actually your reason allows you to discover stuff about the world and I consider the first really the first figure of the enlightment is Newton not Lo right it's a scientist because he teaches us the laws of mechanics like how does stuff work and people go oh wow this is cool I can use my mind I can discover truth isn't that amazing and everything opens up once you do that hey if I can discover if I understand the laws of motion if I can understand truth in the world how come I can't decide who I marry I mean everything was fixed in those days how come I can't decide what profession I should be in right everybody belong to a guild how come I can't decide who my political leader should be that's so it's all reason it's all once you understand the efficacy of your own mind to understand truth to understand reality discover truth not understand truth Discover it everything opens up now you can take responsibility for your own life cuzz now you have the tool to do it but we are living in an era where postmodernism tells us there is no truth there is no reality and our mind is useless anyway critical race Theory tells us that you're determined by your race and your race shapes everything and your free will is meaningless and your reason doesn't matter because reason is just shaped by your genes and shaped by your color of your skin the it's the most racist theory of all and you've got you've got our friended you see Irvine telling them oh your senses don't tell you anything about reality anyway reality is what it is so you know what's the purpose of reason it's to invent stuff it's to make stuff up then what use is that it's complete fantasy you've basically got every philosophical intellectual voice in the culture telling them their reason is impotent there's like a Steven Pinker who tries and I love Pinker and he's he's really good and I love his books but you know he needs to be stronger about this and there's a few people on kind of there's a few people partially in the intellectual dark web and otherwise who are big on reason but not consistent enough and not full understanding of what it means or what it implies and then there's little old me and and it's me against the world in a sense because I'm not only willing to accept to to to articulate the case for reason but then what that implies it implies Freedom it implies capitalism it implies taking personal responsibility over your own life and there other intellectual dark web people get to reason and oh politics you you can be whatever no you can't you can't be a socialist and for reason right it doesn't actually th those are incompatible and you can't be a determinist and for reason reason and determinism don't go together the whole point of reason is that it's an achievement and it requires effort and it requires engagement it requires choice so it is it does feel like little old me because that's that's it I the Allies I have are allies I have allies among the some Libertarians over economics I have some allies in the intellectual dark web maybe over reason but none of them are allies in the full sense my allies are the other objectivist but we're just they're not a lot of us for people listening to this for the few folks kind of listening to this and and thinking about the trajectory of their own life I guess the takeaway is a reason is a difficult project but a project that's worthy of taking on yeah and difficult is I don't know if difficult is the right word because difficult sounds like it's you know I have to push this boulder up a hill it's not difficult in that sense it's difficult in the sense that it requires energy and focus it requires effort but it's immediately rewarding it's fun to do and it's rewards uh immediate pretty quick right it takes a while to undo all the garbage that you have but we all have that I had that took me years and years and years to get rid of certain Concepts and certain emotions that I had that didn't make any sense but it it takes a long time to fully integrate that so I I don't want it to sound like it's a burden like it's hard in that sense it does require focus and energy and I don't want to sound like a Dr Spock I don't want to and I don't think I do because I'm pretty passionate guy but I don't want it to appear like oh just forget about emotions emotions are how you experience the world you want to have strong emotions you want to live you want to experience life strongly and passionately you just need to know that emotions are not cognition it's another realm it's like don't mix the Realms think about outcomes and then experience them and sometimes your emotions won't coincide with what you think should be and that means there's still more integration to be done y on as I told you offline I've been a fan of yours for a long time it's been I was a little star struck early on getting a little more comfortable now gone the I I highly recommend that people uh that haven't heard your work listen to it to the Yon Brook show you know the times I've disagreed with something I've hear you say is usually a first step on a journey of learning a lot more about that thing about that Viewpoint and that's been so F feeling it's been a gift the passion you know you talk about reason a lot but the passion radiates in in a way that's just uh contagious and on inspiring so thank you for everything you've done for this world it's it's truly an honor and a pleasure to talk to you well thank you and and it's it's my reward is that that if I've had an impact on you and people like you wow I mean that's that's amazing when you wrote to me an email saying you being a fan I was blown away cuz I had no idea and completely unexpected and and I you know every every few months I discover hey I had an impact on this Pro and people that I would have never thought and they so you know the only way to change the world is to change your one mind at a time and uh and and when you when you have an impact on a good mind and a mind that cares about the world and a mind that goes out and does something about it then you get the exponential growth so through you I've impacted other people and that's how you get that's how you ultimately change everything and and so I'm in spite of everything I'm I'm optimistic in a sense that I think that the progress we've made today is so universally accepted the scientific progress the technological problem it can just vanish like it did under when Rome collapsed and and whether it's in the United States of some way progress will continue the the the the human project for human progress will continue and I think these ideas ideas of reason and individualism will always be at the heart of it and uh you know what we are doing is continuing the project of the Enlightenment and and it's the project that will will save this save the human race and and allow it to to for ellon musk and for um Jeff bezus to reach the Stars thank you for masterfully ending on a hopeful note youran a pleasure and an honor thanks thanks for listening to this conversation with euron Brook and thank you to our sponsors blinkist an app I use for reading through summaries of books expressvpn the VPN I've used for many years to protect my privacy on the internet and cash app the app I use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Freedman and now let me leave you with some words from Iron Rand do not let your fire go out Spark by Irreplaceable spark in the Hopeless swamps of the not quite the not yet and the not at all do not let the hero in your soul perish in lonely frustration for the life you deserved and have never been able to reach the world you desire can be one it exists it is real it is possible it is yours thank you for listening and hope to see you next time |
Alex Filippenko: Supernovae, Dark Energy, Aliens & the Expanding Universe | Lex Fridman Podcast #137 | the following is a conversation with Alex filipenko an astrophysicist and professor of astronomy from Berkeley he was a member of both the Supernova cosmology project and the high Supernova search team which used observations of the extra Galactic Supernova to discover that the universe is accelerating and that this implies the existence of dark energy this discovery resulted in the 2011 nobba prize for physics outside of his groundbreak can research he is a great science communicator and is one of the most widely admired Educators in the world I really enjoyed this conversation and I'm sure Alex will be back again in the future quick mention of each sponsor followed by some thoughts related to the episode neuro the maker of functional sugar-free gum and mints that I used to give my brain a quick caffeine boost better help and online therapy with a licensed professional Master Class online courses that I enjoy from some of the most amazing humans in history and cash app the app I use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that as we talk about in this conversation the objects that populate the universe are both a inspiring and terrifying in their capacity to create and to destroy us solo flares and asteroids lurking in the darkness of space threaten our humble fragile existence here on Earth in the chaos tension conflict and social division of 2020 it's easy to forget just how lucky we humans are to be here and with a bit of hard work maybe one day we'll venture out towards the Stars if you enjoy this thing subscribe on YouTube review it with fast stars on Apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex fredman and now here's my conversation with Alex filipenko let's start by talking about the biggest possible thing the universe sure will the universe expand forever or collapse on itself well you know that's a great question that's one of the big questions of cosmology and of course we have evidence that the matter density is sufficiently low that the universe will expand forever but not only that there's this weird repulsive effect we call it dark energy for want of a better term and it appears to be accelerating the expansion of the universe so if that continues the universe will expand forever but it need not necessarily continue it could reverse sign in which case the universe could in principle collapse at some point in the Far Far Future so like in terms of investment advice if you were to give me and then to bet all my money on one or the other where did does your intuition currently lie well right now I would say that it would expand forever because I think that the dark energy is likely to be just Quantum fluctuations of the vacuum the vacuum Zero Energy state is not a state of zero energy that is the ground state is a a state of some elevated energy which has a repulsive effect to it and that will never go away because it's not something that changes with time so if the universe is accelerating now it will forever continue to do so and yet I mean you're so effortlessly mentioned Dark Energy do we have any understanding of of what the heck that thing is well not really but we're getting progressively better observational constraints so you know different theories of what it might be predict different sorts of behavior for the evolution of the universe and we've been measuring the evolution of the universe now and the data appear to agree with the predictions of a con density vacuum energy a z Point Energy but one can't prove that that's what it is because one would have to show that the numbers that the measured numbers agree with the predictions to an arbitrary number of decimal places and of course even if you've got 8 9 10 12 decimal places what if in the 13th one the measurements significantly differ from the prediction then the dark energy isn't this vacuum State uh ground state energy of the of the vacuum and so then it could be some sort of a a field some sort of a new energy a little bit like like light like electromagnetism but very different from light that fills space and that type of energy could in principle change in the distant future it could become gravitationally attractive for all we know there is a historical precedent to that and that is that the inflation with which the universe began when the universe was just a tiny blink of an of an eye old a trillionth of a trillionth of a trillionth of a second you know the universe went whoosh it exponentially expanded that dark energy likee substance we call it the inflaton that which inflated the universe later decayed into more or less normal gravitationally attractive matter so the exponential early expansion of the universe did transition to a deceleration which then dominated the universe for about 9 billion years and now this small amount of dark energy started causing an acceleration about five billion years ago and whether that will continue or not is something that we'd like to answer but I don't know that we will anytime soon so there could be this interesting field that we don't yet understand that's morphing over time that's changing the way the universe is is expanding I mean it it's funny that you were thinking through this rigorously like an experimentalist yeah but the what about like the fundamental physics of dark energy is there any understanding of uh what the heck it is or is or is this the kind of uh the the god of the gaps or the field of the gaps uh so like it there must be something there because of what we're observing I'm very much a person who believes that there's all always a cause you know there there are no um miracles of a supernatural nature okay uh so I mean there are two broad categories either it's the vacuum Zero Point Energy or it's some sort of a a new energy field that pervades the Universe the latter could change with time the former the vacuum energy cannot right so if it turns out that it's one of these new fields and there many many possibilities they go by the name of you know quintessence and things like that but there are many categories of those sorts of fields we try with data to rule them out by comparing the actual measurements with the predictions and some have been ruled out but many many others remain to be tested and the data just have to become a lot better before we can rule out most of them and become reasonably convinced that this is a vacuum energy so there is hypotheses for different fields like with names and stuff like that yeah yeah you know generically quintessence like the Aristotelian fifth Essence but there are many many versions of quintessence there's K Essence there's even ideas that you know this isn't something from within this dark energy but rather there are a bunch of say bubble universes surrounding our universe and this whole idea of the Multiverse is not some crazy Mad Men type idea anymore it's you know real card carrying physicists are seriously considering this possibility of a Multiverse and some types of multiverses could have you know a bunch of bubbles on the outside which gravitationally act outward on our bubble because gravity or gravitons the the quantum particle that is thought to carry gravity is is thought to Traverse the bulk the space between these different little bubble membranes and stuff and so it's conceivable that these other verus are pulling outward on us that's not a favored explanation right now but but really nothing has been ruled out no class of models has been ruled out completely certain examples within classes of models have been ruled out but in general I think we still have really a lot to learn about what's causing this observed acceleration of the expansion of the universe be it dark energy or some forces from the outside or or perhaps you know I guess it's conceivable that and sometimes I wake up in the middle of the night screaming the dark energy that which causes the acceleration and dark matter that which causes galaxies and clusters of galaxies to be bound gravitationally even though there's not enough visible matter to do so maybe these are our 20th and 21st century toic epicycles so toy had a geocentric and Aristotelian view of the world everything goes around Earth but in order to explain the backward motion of planets Among the Stars that happens every year or two or sometimes several times a year for Mercury and Venus you needed the planets to go around in little circles called epicycles which themselves then went around Earth yes and in this in this part of the epicycle where the planet is going in the direction opposite to the direction of the overall epicycle it can appear in projection to be going backward Among the Stars socaled retrograde motion and it was a brilliant mathematical scheme in fact he could have added epicycles on top of epicycles and reproduce The observed positions of planets to arbitrary accuracy yeah and this is really the beginning of what we now call forier analysis right any periodic function can be represented by a sum of signs and Co signs of different periods amplitudes and phases so it could have worked arbitrarily well but other data you know show that in fact Earth is going around the Sun um so are dark energy and dark matter just these Band-Aids that we now have to try to explain the data but they're just completely wrong that that's a possibility as well and as a scientist I have to be open to that possibility as an open-minded scientist how do you how do you put yourself in the mindset of somebody that or majority of the scientific Community or majority of people believe that the Earth everything rotates around Earth how do you put yourself in that mindset and then take a leap to uh propose a model that the sun is in fact at the center of this the solar system sure I mean so that puts us back in the shoes of cernus right 500 years ago where he had this philosophical preference for the sun being the dominant body in what we now call the solar system the observational evidence in terms of the measured positions of planets was not better explained by the heliocentric Sun centered system it's just that you know cernus saw that the sun is the source of all our light and heat oh wow and he had you know he he knew from other studies that it's it's far away so the fact that it appears as big as the moon means it's actually way way bigger because even at that time it was known that the sun is much farther away than the moon so um you know he just felt wow it's big it's bright what if it's the central thing but the observed positions of planets at the time in the early to mid 16th century under the heliocentric system was not a better match at least not a significantly better match than tmy system which was quite accurate and lasted 1500 years yeah yeah that's so fascinating to think that the philosophical predispositions that you bring to the table are essent so like you have to have a young person come along that has a weird infatuation with the son yeah that like almost philosophically is like however their upbringing is they're more ready for whatever the more the simpler answer is right oh that's um it's kind of sad it's uh sad from an individual descendant of ape perspective because then that means like me like you as a scientist you're stuck with whatever the heck philosophies you brought to the table you might be almost completely unable to to think outside this particular box you've built right this is why I'm saying that you know as an objective scientist one needs needs to have an open mind to Crazy sounding new ideas and you know even cernus was very much a man of his time and dedicated his work to the pope he still used circular orbits the Sun was a little bit off center it turns out and a slightly off-center Circle looks like a slightly eccentric elliptical orbit so then when Kepler in fact showed that the orbits are actually in general ellipses not circles the reason that you know he needed tuob bra's really great data to show that distinction was that a slightly off-center circle is not much different from a slightly eccentric ellipse and so there wasn't much difference between Kepler's View and uh kernus is View and and Kepler needed the better data uh tuo's toob bra's data and so that's again a great example of of of science and OBS observations and experiments working together with hypotheses and they they kind of bounce off each other they play off of each other and you continually need more observations and it wasn't until Galileo's work uh around 1610 that actual evidence for the heliocentric hypothesis emerged it came in the form of Venus the planet Venus going through all of the possible phases from new to Crescent to to quarter to gibbus to full to waning gibbus third quarter waning crescent and then new again it turns out in the toic system with Venus between Earth and the Sun but always roughly in the direction of the sun you could only get the new and Cresent phases of Venus but the observations showed a full set of phases and moreover when Venus was gibbus or full that meant it was on the far side of the Sun that meant it was farther from Earth than when it's Crescent so it should appear smaller and indeed it did so that was a that was you know the nail and the coffin in a sense and then you know Galileo's other great observation was that Jupiter has moons going around it the four Galilean satellites and even though Jupiter moves through space so too do the moons go with it so first of all Earth is not the only thing that has other things going around it and secondly Earth could be moving as Jupiter does and you know things would move with with it we we wouldn't fly off the surface and our moon wouldn't be left behind and all this kind of stuff so that was a a big breakthrough as well but it wasn't as definitive in my opinion as the phases of Venus perhaps I'm revealing my ignorance but I didn't realize how much data they were working with yeah so there's uh so it wasn't Einstein or Freud thinking in theories it was a lot of data and you're playing with it and seeing how to make sense of it so isn't it it isn't just coming up with completely abstract thought experiments yeah it's looking at the data sure and you Newton's great work right the prinkipia it was based in part on Galileo's observations of balls rolling down inclined planes supposedly fall falling off the Leaning Tower of Pisa but that's probably apocryphal in any case you know um the the the Inquisition actually did or the R Catholic Church uh did did history a favor not that I'm condoning them but they placed Galileo under house arrest yeah and that gave Galileo time to publish to assemble and publish the results of his experiments that he had done decades earlier it's not clear he would have had time to do that you know had he not been under house arrest and so Newton of course Very Much used Galileo's observations let me ask uh the old Russian overly philosophical question about death so we're talking about the expanding Universe sure how do you think human civilization will come to an end if we avoid the uh the near-term issues we're having uh will it be our sun burning out will it be comets okay will it be uh what is it oh do you think we we have a shot at reaching the the heat death of the universe yeah yeah so we're going to leave out the anthropogenic uhle causes of our potential destruction yes which I actually think are greater than the celestial uh causes so um so if we get lucky yeah if we get and intelligent I don't know yeah so no way will we as humans reach the heat death of the Universe I mean it's conceivable that uh machines which I think will be our evolutionary descendants might reach that although even they will have less and less energy with which to work as time progresses because eventually even the lowest mass stars burn out although it takes them trillions of years to do so um so the point is is that certainly on Earth uh there are other Celestial threats existential threats comets exploding Stars the sun burning out so we will definitely need to move away away from our solar system to other solar systems and then you know the question is can they keep on propagating to other planetary systems sufficiently long um in our own solar system the sun burning out is is not the the immediate existential threat um that'll happen in about you know five billion years when it becomes a red giant although I should hasten to add that within the next one or two billion years years the sun will have brightened enough that unless they compensatory atmospheric changes the oceans will will evaporate away you know and and you need much less carbon dioxide for the temperatures to be maintained roughly at their present temperature and plants wouldn't like that very much so you can't lower the carbon dioxide content too much so so within one or two billion years probably the oceans will evaporate away yeah but on a sooner time scale than that I would say an asteroid Collision leading to a potential mass extinction or at least an Extinction of complex beings such as ourselves that require quite special conditions unlike cockroaches and amibas you know to survive um you know one of these civilization changing asteroids is only one kilometer or so in diameter and bigger and a true mass extinction event is 10 kilometers or larger now it's true that we can find and track the orbits of asteroids that might be headed toward Earth and if we find them 50 or 100 years before they impact us then clever applied physicists and Engineers can figure out ways to deflect them but at some point you know some Comet will come in from the deep freeze of the solar system and there we have very little warning months to a to a year what's the Deep Freeze sorry oh the Deep Freeze is sort of out Beyond Neptune there's this thing called the Kyper belt M and it consists of a bunch of you know dirty ice balls or icy dirt balls it's the source of the Comets that occasionally come close to the Sun and then there's a even bigger area called the scattered disc which is sort of a big doughnut surrounding the solar system way out there from which other comets come and then there's the orc Cloud WT after uh Yan ort a Dutch astrophysicist and it's the better part of a lightyear away from the Sun so a good fraction of the distance to the nearest star but that's like a trillion or 10 trillion comet-like objects that occasionally get disturbed by a passing star or whatever and most of them go flying out of the solar system but some go toward the Sun and they they come in with little warning you know by the time we can see them they're only a year or two away from us and moreover not only is it hard to determine their trajectories sufficiently accurately to know whether they'll hit a tiny thing like Earth but outgassing from the comet of um gases you know when the IES sublimate that outgassing can change the trajectory just because of conservation of momentum right it's the rocket effect gases go out in One Direction the object moves in the other direction and so since we can't predict how much outgassing there will be and in exactly what direction because these things are tumbling and rotating and stuff it's hard to predict the trajectory with sufficient accuracy to know that it will hit and you certainly don't want to deflect a comet that would have missed but you thought it was going to hit and end up having it hit that would be like the ultimate Charlie Brown you know goat instead of trying to be the hero right he ended up being the goat what would you uh what would you do if it seemed like in a matter of months that there is some nonzero prob ility maybe a high probability that there will be a collision so from a scientific perspective from an engineering perspective I imagine you would actually be in the room of people deciding what to do what uh yeah philosophically too it's a tough one right because if you only have a few months that's not much time in which to deflect it early detection and and um early action or key because when it's far away you only have to deflect it by a tiny little angle yeah and then by a time it reaches us the perpendicular motion is big enough to you know to to Miss Earth all you need is one radius or or one diameter of the earth right that actually means that all you would need to do is slow it down so it arrives four minutes later or speed it up so it arrives four minutes earlier and Earth will have moved through one radius in in that time so it doesn't take much but you can imagine if a thing is about to hit you you you have to deflect at 90 degrees or more right you know and you don't have much time to do so and you have to slow it down or speed it up a lot if that's what you're trying to do to it and so decades is sufficient time but months is not sufficient time so at that point I would think the the name of the game would be to try to predict where it would hit and if it's in a heavily populated region try to try to start an orderly evacuation perhaps but you know that might cause just so much Panic that I'm how would you do it with New York City or or Los Angeles or something like that right I might have I might have a different opinion a year ago I'm uh a bit U disheartened by you know in the movies the um there's always extreme competence from the government competence yeah competence right but we expect extreme incompetence if anything right yes now so I'm quite disappointed but sort of from a medical perspective I think you're saying there in a scientific one it's almost better to get better and better maybe telescopes and data collection to be able to predict the movement of these things or like come up with totally new technologies like you can imagine actually sending out like probes out there to be able to sort of almost have little finger sensors throughout our solar system to be able to detect stuff well that's right yeah monitoring the asteroid belt is very important and 99% of the so-called neear objects ultimately come from the asteroid belt and so there we can track the trajectories and even if there's you know a close encounter between two asteroids which deflects one of them toward Earth it's unlikely to be on a collision course with Earth in the immediate future it's more like you know tens of years so that gives us time but we would need to improve our ability to detect the objects that come in from a great distance unfortunately those are are much rarer the the Comets come in you know 1% of the collisions perhaps are with comets that come in without any warning hardly and so so that might be more like you know a billion or two billion years before one of those hits us um so maybe we have to worry about the sun getting brighter on that time scale I mean there's the possibility that a star will explode near us in the next couple of billion years but over the course of the history of life on Earth the estimates are that maybe only one of the mass extinctions you know was caused by a star blowing up in particular a special kind called a Gamay burst and the I think it's the oriv I solarian uh saluan or divis saluan Extinction 420 or so 440 million years ago that is speculated to have come from one of these particular types of exploding Stars called Gamay bursts but even there the the evidence is circumstantial so those kinds of existential threats are are reasonably rare the greater danger I think is civilization changing events where it's a much smaller asteroid uh which those are hard harder to detect or or a giant solar flare that shorts out the Grid in all of North America let's say now you know astronomers are monitoring the sun 247 with various satellites and we can tell when there's a a flare or a coronal mass ejection and we can tell that in a day or two a giant bundle of energetic particles will arrive and twang the magnetic field of Earth and send all kinds of currents through long-distance power lines and that's what shorts out the Transformers and Transformers are you know expensive and and hard to replace and hard to transport and all that kind of stuff so if we can warn the power companies and they can shut down the grid before the big bundle of particle hits then we will have mitigated much of this now for a big enough bundle of particles you can get short circuits even over small distance scales so not everything will be saved but at least the whole grid might not go out so again you know astronomers I like to say support your local astronomer they may help someday save Humanity by telling the power companies to shut down the grid finding the asteroid 50 or 100 years before it hits then having clever physicists and Engineers deflect it so many of these Cosmic threats Cosmic existential threats we can actually predict and do something about or observe before they hit and do something about so it's it's terrifying to think that people would listen to this conversation it's like when you listen to Bill Gates talk about pandemics and his Ted Talk a few years ago yeah and realizing we should have supported our local astronomer more well I don't know whether it's more because that's I said I actually think uh human induced threats or things that occur naturally on Earth either a natural pandemic or perhaps you know a bioengineering type pandemic or you know something like a super volcano right um there was one event Toba I think it was 70 plus thousand years ago that that caused a gigantic decrease in temperatures on Earth because it sends up it sent up so much soot that it blocked the sun right it's the nuclear winter type disaster scenario that some people including Carl Sean talked about decades ago but we can see in the history of volcanic eruptions even more recently in the 19th century Tambora and other ones you look at the record and you see rather large dips in temperature associated with massive volcanic eruptions well these super volcanoes one of which by the way exists under Yellowstone you know in the central us I mean it's not just it's not just one or two states it's a it's a gigantic region and there's controversy as to whether it's likely to blow any time in the next 100,000 years or so but that would be perhaps not a mass extinction because you really need to or or perhaps not a complete existential threat because you have to get rid of sort of the very last humans for that but but at least getting rid of um you know killing off so many humans truly billions and billions of humans the one there have been ones tens of thousands of years ago including this one um Toba I think it's called where it's estimated that the human population was down to 10,000 or 5,000 individuals something like that right if you have a 15 degree drop in temperature over quite a short time it's not clear that even with today's advanced technology we would be able to adequately respond at least for the vast majority of people maybe some would be in these underground caves where you'd keep the president and a bunch of other important people you know but the the typical person is not going to be prot protected when when all of Agriculture is is cut off right and when it could be hundreds of millions or billions of people yeah starving to death exactly that's right they don't all die immediately but they use up their supplies or again this electrical grid first toilet paper there you go stash that toilet paper you know um or the electrical grid I mean imagine North America without power for a year right I mean we've become so dependent we're no longer the cave people they would do just fine right what do they care about the electrical grid right what do they care about agriculture they're hunters and gatherers but we now have become so used to our way of life that the only real survivors would be those rugged individualists who live somewhere out in the forest or in a cave somewhere completely independent of anyone else yeah I've recently I recommend it it's totally new to me this kind of survivalist uh folks but there's a a few show there's a lot lot of shows of those but I saw one on Netflix and I started watching them and there's they make a lot of sense they they reveal to you how dependent we are on all aspects of this beautiful systems we human have built right and how fragile they are incredibly fragile and yeah this this whole conversation is making me realize how lucky we are oh we're we're incredibly lucky but we've set ourselves up to be very very fragile and we are intrinsically complex biological creatures that except for the fact that we have brains and Minds with which we can you know try to prevent some of these things or respond to them we as a living organism require quite a narrow set of conditions in order to survive you know we're not cockroaches we're not going to survive a nuclear war so we're kind of there's this beautiful dance between um we've been talking about a astronomy that astronomy the Stars like inspires everybody and at the same time there's this pragmatic aspect that we're talking about and so I see space exploration as the same kind of way that it's uh reaching out to other planets reaching out to the stars is this really beautiful idea but if you listen to somebody like uh Elon Musk he talks about space exploration as very pragmatic like we have to if we we have to be he has this ridiculous way of sounding like an engineer about it which is like it's obvious we need to become a multiplanetary species if we were to survive long term so maybe both philosophically in terms of beauty and in terms of practical what's your thoughts on um space exploration on the challenges of it on how much we should be investing in it and on a personal level like how excited you are about by the possibility of going to Mars colonizing Mars and maybe going outside the solar system yeah you know great question uh there's a lot to unpack there of course you know humans are by their very nature explorers Pioneers they want to go out climb the next Mountain see what's behind it um explore the oan depths explore space this is our destiny to go out there and and of course from a pragmatic perspective yes we need to um plant our seeds elsewhere really because things could go wrong here on Earth now some people say that's that's an excuse to not take care of our planet that well we say we're elsewhere and so we don't have to take good care of our planet no you know we should take the best possible care of our planet we should be cognizant of the potential impact of what we're doing nevertheless it's prudent to have us be elsewhere as well so in that regard I actually agree with Elon uh it'd be good to be on Mars that would be yet another place for us to from which to you know explore further would that be a good Next Step would you say well that's the good it's a good next step I have happen I happen to disagree with him as to how quickly it will happen right I mean I think he's very optimistic now you need Visionary people like Elon to to get people going and to inspire them I mean look at the success he's had with multiple companies uh so maybe he gives this very optimistic timeline in order to be inspirational to those who are who are going out there and certainly his Success With You know the rocket that is reusable because it landed upright and all that I mean you know what that that's a GameChanger sort of like every time you flew from San Francisco to Los Angeles you discard the airplane right I mean that's crazy right so that's a game Cher but nevertheless the time scale over which he thinks that there could be a real thriving colony on Mars I think is far too optimistic what's the biggest challenges to you one is just getting Rockets not Rockets but people out there and two is the colonization like what do you have thoughts about this um challenges of this kind of prospect yeah I haven't thought about it in in great detail uh other than recognizing that Mars is a harsh environment yeah you don't have much of an atmosphere there you've got less than a percent of Earth's atmosphere um so you you to build some sort of a dome right away right and and that that would take time you need to melt the water that's in the permafrost or have canals dug from which you transport it from the from the polar ice caps you know I I was reading recently in terms of like what's the most efficient source of nutrition for humans that were to live on Mars and uh people should look into this but it turns out to be insects insects yeah yeah so you want you want to build GI colony of insects and just be eating insects have a lot of protein right a lot of protein and they're easy to like you can think of them as farming right but it's not going to be easy as easy as growing a whole plot of potatoes like in the movie The Martian you know or something right it's not going to be that easy but you know so there's there's this thin atmosphere it's got the wrong composition it's mostly carbon dioxide there are these violent dust storms the temperatures are generally cold you know you'd need to do a lot of things you need to terraform it basically in order to make it nicely livable without some Dome surrounding you and if you and if you insist on a dome well that's not going to house that many people right you know well so let's look let's look briefly then you know we're looking for a new apartment to move into so let's look outside the solar system do you think you've you've spoken about exoplanets as well do you think there's um possible homes out there for us uh outside of our solar system there are lots and lots of homes possible homes I mean they're there's a planetary system around nearly every Star you see in the sky and one in five of those is thought to have a roughly earth like Planet you know and that's a relatively new yeah it's a new discovery I mean that the Kepler satellite which was flying around uh above Earth's atmosphere was able to monitor the brightness of stars with exquisite detail and they could detect planets crossing the line of sight between us and the star thereby dimming its light for a short time ever so slightly and it's it's amazing so there are now thousands and thousands of these exoplanet candidates of which something like 90% are probably genuine exoplanets and you have to remember that only about 1% of stars have their planetary system oriented Edge on to your line of sight which is what you need for this Transit method to work right some arbitrary angle won't work and certainly perpendicular uh to your line of sight that is in the plane of the sky won't work because the the the planet is orbiting the star and never crossing your line of sight so the fact that um you know they found planets orbiting about 1% of the stars that they looked at in this field of 150 plus thousand stars they found planets around 1% you then multiply by the inverse of 1% which is you know right 1% is about how many what the fraction of the of the stars that have their planetary system oriented the right way and that already back of the envelope calculation tells you that of order 50 to 100% of all stars have planets okay and then they've been finding these earthlike planets etc etc so there are many potential homes the problem is getting there okay so then a typical bright star serus uh the brightest star in the sky maybe not a typical bright star but it's 8.7 light years away okay so uh that's that means the light took 8.7 years to reach us we're seeing it as it was about nine years ago okay so then you know you ask how long would a rocket take to get there at Earth's escape speed which is 11 kilometers per second okay and it turns out it's about a quarter of a million years okay now that's 10,000 Generations okay let's say a generation of humans is 25 years right so you need this colony of people that is able to sustain itself all their food all their waste disposal all their water all their recycling of everything for 10,000 Generations they have to commit themselves to living on this vehicle right I just see it happening what I see potentially happening if we avoid self-destruction intentional or unintentional here on Earth is that machines will do it robots that can essentially hibernate they don't need to do much of anything for a long long time as they're traveling and moreover if some energetic charged particle some Cosmic gray hits the circuitry it fixes itself right machines can do this uh I mean it it's a form of artificial intelligence you just tell the thing fix yourself basically and then when you land on the on the planet start producing copies of yourself initially from materials that perhaps sent or you just have a bunch of copies there and then they set up you know factories with which to do this I mean this is very very futuristic but it's much more feasible I think than sending Flesh and Blood over Interstellar distances a quarter of a million years to even the nearest Stars you're subject to all kinds of charged particles and radiation you have to you know Shield yourself really well that's by the way one of the problems of going to Mars is that it's not a three-day Journey like going to the Moon you're out there for the better part of a year or two and you're exposed to lots of radiation you know which typically doesn't do well with living tissue right or living tissue doesn't do well with the radiation okay and and the hope is that the robots that AI systems might be able to carry the carry the the fire of Consciousness whatever makes us humans yeah like a little drop of whatever makes us humans so special not to be too poetic about it but no but I I like being poetic about it because it's a it's an amazing question you know is there something Beyond just the bits the ones and zeros to us you know it's an interesting question um I like to think that there there isn't anything and that how beautiful it is that our thoughts our emotions our feelings our compassion all come from these ones and zeros right that to me actually is a a beautiful thought and the idea that machines silicon based life effectively could be our natural evolutionary descendants not from a DNA perspective but they are our creations and they then carry on that to me is a a beautiful thought in some ways but others find it to be a horrific thought right exciting to you I it is exciting to me as well yeah because to me from a purely an engineering perspective it's I believe it's impossible to create like whatever systems we create that take over the world it's impossible for me to imagine that those systems will not carry some aspect of what makes humans beautiful yeah so like that a lot of people have these kind of paperclip ideas that will we bring will'll build machines that are cold inside or philosophers call them zombies you know they're they're that naturally the systems that will out compete us on this Earth will be cold and non nonconscious not capable of all the human emotions and empathy compassion and love and hate every the the beautiful uh mix of uh what makes us human but to me intelligence requires all of that so in order order to outcompete humans you better be good at the full picture right so artificial general intelligence in my view encompasses a lot of these attributes that you just talked about yeah curiosity inquisitiveness you know right it might look very different than us humans but you have some of the magic but it'll but it'll also be much more able to survive the onslaught of existential threats that either we bring upon ourselves or don't anticipate here on Earth or that occasionally come from Beyond and there's nothing much we can do about a supernova explosion that just suddenly you know goes off and and and really if we want to move to other planets outside our solar system I think realistically that's a much better option than thinking that humans will actually make these gigantic Journeys and you know then I do this calculation from my class you know Einstein's special theory of relativity says that you can do it in a short amount of time in your own frame of reference if you go close to the speed of light but then you bring in eal mc^2 and you figure out how much energy it takes to get you accelerated to close enough to the speed of light to make the time scales short in your own frame of reference and the amount of energy is just unfathomable right we can do it at the large hron collider with with protons you know we can accelerate them to 99.9999% of this speat of light but that's just a proton we're gazillions of protons okay and that doesn't even count the rocket that would carry us the payload and you would need to either store the fuel in the rocket which then requires even more mass for the rocket or collect fuel along the way which you know is difficult and so getting close to the speed of light I think is not an option either other than for a little tiny thing like you know Yuri Milner and others are thinking about this this star shot project where they'll a little tiny camera to Alpha centuri 4.2 light years away they'll zip past it take a picture of the exoplanets that we know orbit that three or more star system and uh say hello real quick say hello real quickly and then send the images back to us okay yeah so that that's a tiny little thing right maybe you can accelerate that to they're hoping 20% of the speed of light with a whole bunch of high-powered lasers aimed at it it's now clear that other countries will allow us to do that by the way but that's a very forward looking thought I mean I very much support the idea but there's a big difference between sending a little tiny camera and sending a payload of people with equipment that could then mine the um the resources on the exoplanet that they reach and and then go forth and multiply right well let's let's talk about the big Galactic things and how we might be able to leverage them to travel fast I know this is a little bit science fiction but you know know uh ideas of wormholes and yeah the ideas at the edge of black holes that reveal to us that this fabric of SpaceTime is uh could be messed with yeah perhaps is that at all an interesting thing for you uh I mean in in your in looking out at the universe and studying it as you have is that also a possible like a dream for you that we might be able to find Clues how we can actually use it to improve our transportation it's an interesting thought I'm certainly excited by the potential physics that suggest this kind of faster than light travel effectively or you know cutting the distance to make it very very short through a wormhole or something like that possible no well you know col me not very imaginative but based on today's knowledge of physics which I realize you know people have gone down that rabbit hole you know aury ago Lord Kelvin one of the greatest physicists of all time said that all of fundamental physics is done the rest is just engineering and guess what then came special relativity quantum physics general relativity how wrong he was so let me not be another L Lord Kelvin on the other hand I think we know a lot more now about what we know and what we don't know and what the physical limitations are and to me most of these schemes if not all of them seem very far-fetched if not impossible so travel through wormholes for example you know it appears that for a non-rotating black hole that's just a complete no-o because the The Singularity is a point-like singularity and you have to reach it to Traverse the Wormhole and you get squished by The Singularity okay now for a rotating black hole it turns out there is a way to pass through the Event Horizon the boundary of the black hole and avoid the singularity and go out the other side or even Traverse the the doughnut hole like singularity in the case of a rotating black hole it's a ring Singularity so there's actually two theoretical ways you could get through a rotating black hole or a Charged black hole not that we expect charged black holes to exist in nature because they would quickly bring in the opposite charge so as to neutralize themselves but rotating black holes definitely reality we we now have good evidence for them do they have Travers ible wormholes probably not because it's still the case that when you go in you go in with so much energy that it it it either squeezes the Wormhole shut or you encounter a whole bunch of incoming and outgoing energy that vaporizes you it's called the mass inflation instability and it just sort of vaporizes you nevertheless you know you could imagine well you're in some vapor form but if you make it through maybe you could you know re form or something so it's still information yeah it's still information it's scrambled information but there's a way maybe of bringing it back right but then the thing that really bothers me is that as soon as you have this possibility of traversal of a wormhole you have to come to grips with a fundamental problem and that is that you could come back to your Universe At A Time prior to your leaving and you could essentially prevent your grandparents from meeting this is called the grandfather Paradox right and if they never met and if your parents were never born and if you were never born how would you have made the journey to prevent the history from allowing you to exist right it's it's a it's a causal it's a violation of causality of cause and effect now physicists such as myself take causality violation very very seriously we've never seen it you took a stand yeah I mean you know I mean it's one of these right Back to the Future type movies right and you have to work things out in such a way that you don't mess things up right some people say that well you come back to the universe but you come back in such a way that you cannot affect your journey um but then I mean that that seems kind of uh contrived to me or some say that you end up in a different universe and this also goes into the the many different types of the Multiverse hypoth esis and the many worlds interpretation and all that but again then it's not the universe from which you left right and you don't come back to the universe from which you left and so you're not really going back in time to the same universe and you're not even going forward in time necessarily then to the same universe right you're ending up in some other universe so so you've you what have you achieved right you you've traveled you traveled you uh you ended up in a different place than you started in more ways than one yeah and then then there's this idea um the aluer drive where you warp space time in front of you so as to greatly reduce the distance and you can expand the space time behind you so you're sort of riding a wave through SpaceTime but the problem I see with that beyond the Practical difficulties and the energy requirements and by the way how do you get out of this bubble through which you're you know riding this wave of space time miguelier acknowledged all these things he said this is purely theoretical fanciful and all that but a fundamental problem I see is that you'd have to get to those places in front of you so as to change the shape of SpaceTime so as to make the journey quickly but but to get there you you got there in the normal way at a speed considerably less than that of light so in a sense you you haven't saved any time right you might as well have just taken that journey and and gotten to where you were going yeah there's a right you what have you done you it's not like you snap your fingers and say okay let that space there be compressed and then I'll make it over to Alpha centuri in the next month you can't snap your fingers and do that yeah and but yeah we're sort of assuming that we can fix all the biological stuff that requires for humans to persist uh uh persist through that whole process because ultimately it might boil down to just extending the life of the of the human in some form whether it's through the robot through the digital form or through or actually just figuring out genetically how to live forever CU that Journey that you mentioned the long journey might be different if somehow our understanding of genetics of our understanding of our own biology all that kind of stuff would uh that's another trajectory if you could put us into some sort of suspended animation you know hibernation or something and greatly increase the lifetime and so these 10,000 Generations I talked about what do they care it's just one generation and they're asleep okay long nap so then you can do it it's still not easy right because you got some big old huge colony and that just through E equals MC squ right that's a lot of mass that's a lot of stuff to um to accelerate the Newtonian kinetic energy is gigantic right so you're still not home free but at least you're not trying to do it in a short amount of clock time right which if you look at eal mc^2 requires truly unfathomable amounts of energy because the energy is sort of it's it's your rest mass m c^2 divided by the square root of 1us v^2 over c^2 and if your listeners want to just sort of stick into their pocket calculator as V over C approaches one that one over the root of 1us v^2 over c^2 approaches Infinity MH so if you wanted to do it in zero time you'd need an infinite amount of energy that's basically why you can't reach let alone exceed the speed of light for a particle moving through a pre-existing space it's that it takes an infinite amount of energy to do so so that's talking about us going somewhere what about one of the things that inspires a lot of folks including myself is the possibility that there's other that this this conversation is happening and another planet in different forms with uh intelligent life forms well first we could start as a cosmologist what's your intuition about whether there is or isn't intelligent life out there outside of our own yeah I would say I'm one of the pessimists in that I I don't necessarily think that we're the only ones in the observable universe which goes out you know roughly 14 billion years in light travel time and more like you know 46 billion years when you take into account the expansion of space so the diameter of our observable universe is something like you know 90 992 billion Lighty years that encompasses you know 100 billion to a trillion galaxies with um you know 100 billion stars each so now you're talking about something like 10 to the 22nd 10 to the 23rd power stars and roughly an equal number of earthlike planets and so on um so there there there may well be uh other intelligent life but your your sense is our Galaxy's not teaming with life yeah our galaxy our Milky Way galaxy with several hundred billion stars and and potentially habitable planets is not teeming with intelligent life intelligent yeah I wouldn't well I'll get to the Primitive life the bacteria in a moment but um you know we we may well be the only ones in our Milky Way galaxy at most a handful I'd say but I'd probably side with the school of thought that suggests we're the only ones in our own Galaxy just because I don't see human intelligence as being a a natural evolutionary path for life um I mean there's a there's a number of arguments first of all there's been more than 10 billion species of life on Earth in its history yes uh nothing has approached our level of intelligence and mechanical ability and curiosity you know whales and dolphins appear to be reasonably intelligent but there's no evidence that they can think abstract thoughts that they're curious about the world they certainly can't build machines with which to study the world um so that's one argument secondly we came about as early hominids only four or five million years ago and as H Homo sapiens only about a quarter of a million years ago so for the vast majority of the history of life on Earth an intelligent alien zipping by Earth would have said there's nothing particularly intelligent or mechanically able on Earth okay yeah thirdly it's not clear that our intelligence is a long-term evolutionary Advantage now it's clear that in the last 100 years 200 years we've improved the lives of millions hundreds of millions of people but at the risk of potentially destroying ourselves either intentionally or unintentionally or through neglect as we discussed before that's a really interesting point which is it's possible that their huge amount of intelligent civilizations have been born even through our galaxy but they live very briefly and they die flash bulbs in theight Flight that brings me to the fourth the fourth issue and that is the you know the fairy Paradox if they're common where the hell are they you know yeah not withstanding the various UFO reports in Roswell and all that they just don't don't meet the bar they don't clear the bar of scientific scientific evidence in my opinion okay so you know there's there's no clear evidence that they've ever visited us on Earth here so and you know SEI has been now the search for extraterrestrial intelligence has been scanning the skies and true we've only looked a couple hundred light years out and that's a tiny fraction of the whole galaxy a tiny fraction of these 100 billion plus Stars nevertheless you know I if if the if the Galaxy were teaming with life especially intelligent life you'd expect some of it to have been far more advanced than ours okay there's no special nothing special about when the Industrial Revolution started on earth right the chemical evolution of our galaxy was such that billions of years ago nuclear processing and stars had built up clouds of gas after their explosion that were Rich enough in heavy elements to have formed earthlike planets even billions of years ago so there could be civiliz that are billions of years ahead of ours and if you look at the exponential growth of Technology among Homo sapiens in the last couple 100 years and you just project that forward I mean there's no telling what they could have achieved even in 1,000 or 10,000 years let alone a million or 10 million or a billion years and if they reach this capability of interstellar travel and colonization then you can show that within 10 million years or certainly a 100 million years you can populate the whole galaxy all right and they you know so then you don't have to have tried to detect them Beyond 100 or a thousand Lighty years they would already be here do you think as a thought experiment do you think it it's possible that they are already here but we humans are so human Centric that we're just not like our conception of what intelligent life looks like yeah is is um we don't want to acknowledge it like what what if trees right right right like okay I guess the in a form of a question do you think we'll actually detect intelligent life if it came to visit us yeah I mean it's like you know you're an ant crawling around on a sidewalk somewhere and do you notice the humans wandering around exactly and and the Empire State Building and you know rocket ships flying to the moon and all that kind of stuff right it's conceivable that um we haven't detected it and that we're so primitive compared to them that we're just not able to do so like if you look at dark energy Maybe we call it as a field it's just that my own feeling is that in science now through observations and experiments we've measured so many things and basically we understand a lot of stuff okay fabric of reality yeah the fabric of reality we understand quite well and there are a few little things like dark matter and dark energy that may be some sign of some super intelligence but I doubt it okay you know why would some super intelligence be holding clusters of galaxies together why would they be responsible for accelerating the expansion of the universe so the point is is that through science and applied science and engineering we understand so much now that I'm not saying we know everything but but we know a hell of a lot okay and so there's it's not like there are lots of mysteries flying around there that are completely outside our level of um of of exploration or understanding yeah from a I would say from from uh the mystery perspective it seems like the mystery of our own like cognition and Consciousness is much grander than like the degrees of freedom of possible explanations for what the heck is going on is much greater there than in the in the physics of the absor how the brain works how did life arise yeah that's big big questions but they to me don't indicate uh the existence of of of an alien or something I mean unless we are the aliens you know we we could have been contamination from some rocket ship that that hit here a long long time ago and all evidence of it has been destroyed but again that alien would have started out somewhere they're not they're not here watching us right now right they're not among us and so though there are exp potential explanations for the fmy Paradox and one of them that I kind of like is that the truly intelligent creature are those that decided not to colonize the whole galaxy cuz they'd quickly run out of room there CU it's exponential right you send a probe to a planet it makes two copies they go out they make two copies each and it's an exponential right they quickly colonize the whole galaxy but then the distance to the next galaxy the next big one like Andromeda that's two and a half million light years yeah that's a much grander scale now right and so it it also could be that the reason they surv this long is that they got over this tendency that may well exist among sufficiently intelligent creatures this tendency for aggression and self-destruction right if they bypass that and that may be one of the great filters if there are more than one right then they may not be a type of creature that feels the need to go and say oh there's a nice looking planet um and there's a bunch of you know ants on it let's go squish him and colonize it no it could even be the kind of Star Trek like prime directive where you go and explore worlds but you don't interfere in any way right and and also we call it exploration is beautiful and everything but there is underlying this desire to explore is a desire to conquer yeah I I mean if we're just being really honest about right now for us it is right and you're saying it's possible to separate but I would venture to say that you wouldn't that those are coupled so I could I could imagine a civilization that lives on for billions of years that just stays on its like figures out the minimal effort way of just peacefully existing it's like a monastery yeah and it limits itself yeah it limits itself you know it's it's planted its seeds in a number of places so it's not vulnerable to a single point failure right Supernova going off near one of these s or something or an asteroid or a comet coming in from the arc Cloud equivalent of that planetary system and without warning you know thrashing them to bits so they've got their seeds in a bunch of places but they chose not to colon colonize the Galaxy and they also choose not to interfere with this incredibly priv primitive organism Homo sapiens right um or or they uh this is like a they enjoy this like a TV show for them yeah could a TV show right so they just tuned in right so those are possible explanations yet I I think that to me the most likely explanation for the FME Paradox is that they really are very very rare and you know Carl Sean estimated a 100,000 of them if there's that many some of them would have been way ahead of us and and I think we would have seen them by now if there were a handful maybe they're there but at that point you're right on this dividing line between being a pessimist and an optimist yeah and and what are the odds for that right if you look at all the things that had to go right for us yeah and the then you know getting back to something you said earlier let's discuss you know primitive life yeah that could be the thing that's difficult to achieve just getting the random molecules together to a point where they start self-replicating and evolving and becoming better and all that that that's an inordinately difficult thing I think though I'm not you know some molecular cell biologist but just it's it's it's the usual argument you know you're wandering around in the Sahara Desert and you stumble across a watch is your is your initial response oh you know a bunch of sand grains just came together randomly and formed this watch no you you think that something formed it or it came from some simpler structure that then became you know more complex all right it didn't just form well even the simplest life is is a very very complex structure even the even the simplest procaryotic cells not to mention eukaryotic cells although that transition may have been this so-called great filter as well maybe the cells without a nucleus are relatively easy to form and then the big next step is where you have a nucleus which then provides a lot of energy which allows the cell to become much much more complex and so on interestingly going from eukaryotic cells single cells to multicellular organisms does not appear to be at least on Earth one of these great filters because there's evidence that it happened dozens of times independently on Earth so by by a really great filter something that happens very very rarely I mean that we had to get through um an obstacle that is just incredibly rare to get through and one of the really exciting scientific things is that that particular Point U is something that we might be able to discover Even in our lifetimes that find life elsewhere like Europa or yeah be able to see that would be bad news right because if we find lots of pretty Advanced life yeah that would suggest and and especially if we found some you know defunct you know fossilized civilization or something somewhere else that would be you mean of like what's that defunct civilization of like I'm sorry I switched gear there if we if we found some intelligent or rather you know even even trilobites right and stuff you know elsewhere that would be bad news for us because that would mean that the great filter is ahead of us you know right because it would mean that lots of lots of things have gotten roughly to our level yeah but but given the fmy Paradox if you accept that the fmy Paradox means that there's no one else out there you don't necessarily have to accept that but if you accept that it means that no one else is out there and yet there are lots of things we found that are at or roughly at our level that means that the great filter is ahead of us and that bodess poorly for our long-term future you know it's funny you said uh you started by saying you're a little bit on the pessimistic side but it's funny because we're doing this kind of dance between pessimism and optimism because I'm not sure if us being alone in the observable universe as intelligent beings is pessimistic well it's good news in a sense for us because means that we made it through oh right see if we're the only ones and there are such great filters maybe more than one formation of life might be one of them formation of eukaryotic that is with the nucleus cells be another development of humanlike intelligence might be another right there might be several such filters and we were the lucky ones and you know then people say well then that means you're putting yourself into a special perspective and every time we've done that we've been wrong and yeah yeah I know all those arguments but it still could be the case that there's one of us at least per Galaxy or per 10 or 100 or a thousand galaxies and we're sitting here having this conversation because we exist and so there's a there's an observational selection effect there right just because we're special doesn't mean that we shouldn't have these conversations about whether or not we're special right yeah so that's that's exciting that's optimistic so that's the that's the optimistic part that if we don't find other intelligent life there it might mean that we're the ones that made it uh and and in general outside the great filter and so on you know it's not obvious that uh the Stephen Hawkin thing which is it's not obvious that life out there is is going to be kind to us oh yeah so you know I knew Hawking and I greatly respect his his scientific work and in particular the early work on the unification of general theory of relativity and quantum physics to two great pillars of modern physics you know Hawking radiation and all that fantastic work you know if he were alive he should have been a recipient of this year's physics Nobel Prize which was for the discovery of black holes and also uh by Roger Penrose for the theoretical work showing that given a star that's massive enough you you basically can't avoid having a black hole anyway Hawking fantastic I I tip my hat to him may he rest in peace that would have been a heck of a Nobel Prize black holes heck of a good group but but but going back to what he said that we shouldn't be um broadcasting our presence to others there I actually disagree with him respectfully because first of all we've been unintentionally broadcasting our presence for a 100 years since the develop velopment of radio and TV okay um secondly any alien that has the capability of coming here and squashing us uh either already knows about us and you know doesn't care because we're just like little ants and when they're ants in your kitchen you tend to squash them but if they're ants on the sidewalk and you're walking by do you feel some great conviction that you have to squash any of them no you you generally don't right we're irrelevant to them all they need to do is keep an eye on on us to see whether we're approaching the kind of technological capability and know about them and have intentions of attacking them and then they can squash us right um they you know they could have done it long ago yeah they'll do it if they want to whether we advertise our presence or not is is irrelevant so I really think that that's not a huge existential threat so this is a good place to bring up a difficult topic you mentioned um they're they might they would be paying attention to us to see if we come up with any crazy technology there's folks who have uh reported UFO sightings there's actually I've recently found out there's uh websites that track this the D the data of these reportings and there's millions of them in the past uh several decades so seven decades and so on that they've been recorded and the yist community as they refer to themselves you know one of the ideas that I find compelling from an alien perspective that they kind of started showing up ever since we figured out how to build nuclear weapons MH that we should what a coincidence yeah uh so I mean you know if I was an alien I would start showing up then as well just well why not just observe us from afar no I know right I would figure out but that's why I'm always uh keeping a distance and staying blurry right but very pixelated very pixelated you know there there is a something in the human condition that a cognition that wants to see wants to believe beautiful things and uh some are terrifying some are exciting uh goats Bigfoot is a big Fascination for folks yeah and uh UFO sightings I think falls into that there's people that look at lights in the night sky and I mean there's it's kind of a downer to think in a skeptical sense to think that that's just a light yeah you want to feel like there's something magical there sure uh I mean I felt that first when my dad my dad's a physicist when he first told me about ball lightning yeah when I was like a little kid very weird very like weird physical phenomena and you said his intuition was telling me this as a little kid uh like I really like math his intuition was whoever figures out ball lightning will get a Nobel Prize mhm like he I think that was a side comment he gave me and I I decided there when I was like 5 years old or whatever that I'm going to win a Nobel Prize for figuring out B that was like one of the first sort of Sparks of the scientific mindset those Mysteries they capture your imagination I I think when I speak to people that report UFOs that's that fire that's what I see that excitement yeah I understand that MH but what what do we do with that because there's hundreds of thousands if not millions and then the scientific Community you're like the perfect person you you have an awesome Einstein sure I what what do we do with those reports it's uh most of the scientific Community kind of rolls their eyes and dismisses it is it is it possible that a Time % of those folks saw something that's worth deeply investigating sure we should investigate it it's just one of these things where you know they've not brought us a hunk of kryptonite or something like that right they haven't brought us actual tangible physical evidence with which experiments can be done in Laboratories right it's it's anecdotal evidence the photographs are um in some cases in most cases I would say quite ambiguous I don't know what to think about so David fraver is the first person he's a Navy pilot Commander yeah and there's a bunch of them but he's sort of one of the most legit pilots in people I've ever met right the fact that he saw something weird he doesn't know what the heck it is yeah he saw something weird I mean I don't know what to do with that and one on the psych psychological side so I'm pretty confident he saw what he says he saw which he's not Prov he's saying it's something weird right one of the interesting psychological things that worries me is that everybody in the Navy everybody in the US government everybody in the scientific Community just kind of like uh pretended that nothing happened mhm that kind of instinct that's what makes me believe if aliens show up we would all like just ignore their presence that's what bothered me that you don't you don't investigate it more carefully and use this opportunity to inspire the world like so in terms of kryptonite I think the conspiracy theory folks say that whenever there is some good hard evidence that scientists would be excited about the U there's this kind of conspiracy that I don't like cuz it's ultimately negative that the US government will somehow hide the good evidence yeah uh to uh to protect it of course there's some legitimacy to it cuz you want to protect military uh Secrets all that kind of stuff but yeah I I don't know I don't know what to do with this beautiful mess because um I think think millions of people are inspired by UFOs right and it feels like an opportunity to inspire people about science so I would say you know as Carl hean used to say extraordinary claims require extraordinary evidence right I've quoted him a number of times uh we would we would welcome such evidence uh on the other hand you know a lot of the things that are seen or perhaps even hidden from us you could imagine for military purposes surveillance purposes the US government doesn't want us to know or maybe some of these Pilots saw Soviet or Israeli or whatever uh satellites right a lot of the or some of the crashes that have occurred were later found to be you know weather balloons or whatever you know when there are more conventional explanations science tends to stay away from the um from The Sensational ones right and so it may be that someone else's calling in life is to investigate these phenomena and I welcome that as a scientist I I don't categorically actually deny the possibility that ships of some sort could have visited us because as I said earlier at slow speeds there's no problem in reaching other stars in fact our Voyager and Pioneer spacecraft in a few million years are going to be in the vicinity of different Stars we can even calculate which ones they're going to be in the vicinity of right uh so there's nothing that breaks any laws of physics if you do it slowly but that's different you know just having Voyager or Pioneer fly by some star that's different from having active aliens altering the trajectory of their vehicle in real time spying on us and then either zipping back to their home planet or sending signals that tell them about us because they are likely many years many light years away and they're not going to have broken that barrier as well okay right so so I I just you know go ahead study them great I you know for some young kid who wants to do it it might be their calling and that's how they might find meaning in their lives is to be the scientist who really explores these things I chose not to because at a very young age I found the evidence to the degree that I investigated it to be really quite unconvincing and I had other things that I wanted to do but I don't categorically deny the possibility and I think it should be investigated yep I mean this is uh this is one of those phenomena that um 99.9% of people are almost definitely there's conventional explanations and then there's like mysterious things that probably have explanations that are a little bit more complicated yeah it's but there's not enough to work with I tend to believe that if aliens showed up there will be plenty of evidence uh for scientists to study that like it exactly U as you said a voyager type of spacecraft I could see sort of um some kind of kind of a dumb thing almost like a sensor to like probing like statistically speaking flying by maybe lands maybe there's some kind of robot type of thingies that just like move around and so on yeah like in ways that we don't understand but but I feel like well I feel like there'll be plenty of hard hard to dismiss evidence and I also especially this year believe that the US government is not sufficiently competent given the huge amount of evidence that would be revealed from this kind of thing to conceal all of it right uh at least in modern times you can say maybe decades ago but in modern times but you know I uh the the people I speak to and the reason I bring it up is because so many people write to me they're inspired by it by the way I wanted to comment on something you said earlier um yeah I had said that I'm sort of an a pessimist in that I think there are very few other intelligent mechanically able creatures out there but then I said yes in a sense I'm an optimist as you pointed out because it means that we made it through the great filter right I I meant originally that I'm a pessimist in that I'm pessimistic about the possibility that there are many many of us out there you mathematically speaking in the Drake equation exactly right right but but it may mean a good thing for our ultimate survival right so I'm glad you caught me on that yeah I I definitely agree with you I it is ultimately an optimistic statement but anyway I think you know UFO research is is interesting and I guess one of the reasons I've not been terribly convinced is that I think there are some scientists who are investigating this and they've not found any clear evidence now I must admit I have not looked through the literature to convince myself that there are many scientists doing systematic studies of these various reports so I can't say for sure that there's a critical mass of them it's just that you you never get these reports from Hardcore scientists that's other thing and astronomers you know what do we do we spend our time studying the heavens and you'd think we'd be the ones that are most likely aside from Pilots perhaps at seeing weird things in the sky and we just never do of the unexplained UFO type nature yeah I definitely I I try to keep an open mind but for people who listen um it's actually really difficult for a scientist like I get probably like this year I probably gotten over probably maybe maybe over a thousand emails on on the topic of AGI mhm it's very difficult to uh you know people write to me it's like how can you ignore this in AI side like this model this is obviously the model that's going to achieve general intelligence how can you IGN know it I'm giving you the answer here's my document and there always just these large writeups the problem is it's very difficult to we weed through a bunch of BS right it's it's very possible that you had actually saw the UFO but you have to acknowledge by UFO I mean an extr terrestrial life right you have to acknowledge the hundreds of thousands of people who are a little bit if not a lot full of BS and from a scientist perspective it just it's really hard work and it's um when there's amazing stuff out there it's like why investigate Bigfoot when evolution in all of its richness is beautiful who cares about a monkey that walks on two feet like there's a zillion decoys right at observatories true fact we get lots and lots of phone calls when Venus the evening star but just really a a bright Planet happens to be close to the Crescent Moon because it's such a striking pair this happens once in a while so we get these phone calls oh there's a UFO next to the moon and no it's Venus and so they're just and I'm not saying the the best UFO reports are of that nature no there are some much more convincing cases and I've seen some of the footage and blah blah blah um but it's just there's so many decoys right so much so much noise that you have to filter out Y and there's only so many scientists so it's there's so there's only so much time as well and you have to choose what problems you work on you know this might be a fun question asked to kind of explore the idea of the expanding Universe yeah so the the radius of the observable universe is 45.7 billion light years yeah and the age of the universe is 13.7 yeah billion years MH mhm that's less right than the radius of the universe yeah how's that possible so that's a great question so the and I meant to bring a little a little prop I have with pingpong balls on a rubber hose a rubber band I I use it in many of the lectures that one can find of me online but you have in an expanding Universe the space itself between galaxies or more correctly clusters of galaxies expanding so imagine light going from one cluster to another it traverses some distance and then while it's traversing the rest that part that it already traveled through continues to expand now 13.7 billion years might have gone by since the light that we are say seeing from the early stages the so-called Cosmic microwave background radiation which is the the Afterglow of the Big Bang or the echo of the big Bang Yeah 13.7 billion years have gone by that's how long it's taken that light to reach us but while it's been traveling that distance the parts that it already traveled continue to expand MH so it's like you're walking on at an airport you know on one of these walkways and you're walking along because you're trying to get to your terminal but the walkway is continuing as well you end up traveling a greater distance or the same distance faster is another way of putting it right that's why you get on one of these traveling walkways but so you get a roughly a roughly a factor of Pi you know but it's more like 3.2 I think but when you work it all out you multiply the number of years the universe has been in existence by you know three and a quarter or so and that's how you get this 46 billion Lightyear radius but how is that let me ask some nice dumb questions uh how is that not traveling faster than the speed of light yeah it's not traveling faster than the speed of light because locally at any point if you were to measure the light the photon zipping past it would not be exceeding the speed of light the speed of light is a locally measured quantity after light has traversed some distance if the rubber band keeps on stretching then yes it looks like the light traveled a greater distance than it would have had the space not been expanding but locally it never was exceeding the speed of light it's just that the distance through which it already traveled then went off and expanded on its own some more and if you give the light credit so to speak for having traversed that distance well then it looks like it's going faster than the speed of light but but that's not that's not how spe that's happen right that's not how Speed Works speed and in relativity also the other thing um that is interesting is that you know if you take two ping-pong balls that are sufficiently far apart especially in an accelerating universe you can easily have them moving apart from one another faster than the speed of light so you know take two pingpong balls that were originally 400,000 kilometers from each other and let every centimeter in your rubber band expand to two in one second then suddenly this 400,000 kilometer distance is 800,000 km it went out by 400,000 km in 1 second that exceeds the 300,000 kilom perss speed of light but that light limit that that particle limit in special relativity applies to objects moving through a pre-existing space there's nothing in either special or general relativity that prevents space itself from expanding faster than the speed of light that's no problem Einstein wouldn't have had a problem with with a with an with a universe and observed Now by cosmologists yeah I um I'm not sure I'm yet ready to deal emotionally with expanding space it's like that to me is one of the most a inspiring things you know starting from the Big Bang it's definit abstract it space itself is expanding right could you can we talk about the big bang a little bit sure yeah yeah what uh so like the entirety of it the universe yeah was very small right but it was not a point it was not a point because if if we live in what's called a closed Universe now a sphere or the three-dimensional version of that would be a hypersphere you know then regardless of how far back in time you go it was always that topological shape you can't turn a point suddenly into a shell okay it always had to be a a shell yeah so when when people say well the universe started out as a point that that's being kind of flippant kind of glib it didn't really it just started out a at a very high density and we don't know actually whether it was finite or infinite I think personally that it was finite at the time but it expanded very very quickly indeed if it exponentiated and continued in some places to exponentiate then it could in fact be infinite right now and most cosmologists think that it is infinite wait yeah sorry what uh infinite which dimension MTH si infite in space infinite in space and by that I mean that if you were trying to meure use light to measure its size You' you'd never be able to measure its size because it would always be bigger than the distance light can travel that's what you get in a universe that's accelerating in its expansion okay but if a thing was a hypersphere it's very small not a point yeah how can that thing be infinite well it it expands exponentially that's what the inflation theory is all about indeed at your home institution Alan Guth is one of The Originators of the whole inflationary Universe idea along with Andre Lind at at Stanford University here in the Bay Area and others Alexis stabinsky and others had similar sorts of ideas but in an exponentially expanding Universe if you actually try to make this measurement you you send light out to try to see it curve back around and and hit you in the back of the head if next exponentially expanding Universe the amount of space remaining to be traversed is always a bigger and bigger quantity so you'll never get there from here you'll never you you'll never reach the back of your head so observationally or operationally it can be thought of as being infl INF that's one of the best definitions of infinity by the way that's what's that that's one of the best sort of uh physical manifestations of infinity that yeah yeah because you have to ask how would you actually measure it now sometimes say to my cosmology theoretical friends well if I took if I were God and I were outside this whole thing and I took a Godlike slice in time wouldn't it be finite no matter how big it is and they object and they say Alex you you can't be outside and take a Godlike slice of time you know because there's nothing outside well I'm not you know or also you know what slice of time you're taking depends on your motion and that's true even in special relativity that slices of time get tilted in a sense if you're moving quickly the axes x and t actually become tilted not not perpendicular to one another um and you know you can look at Brian Green's books and lectures and other things where he he imagines taking a loaf loaf of bread and slicing it in units of time as you progress forward but then if you're zipping along relative to that loaf of bread the slices of time actually become tilted and so it's not even clear what slices of time mean but I I'm an observational astronomer I know which end of the telescope to look through and the way I understand the infinity is as I just told you that operationally or observationally there no there'd be no way of seeing that it's a finite Universe of measuring a finite universe and so in that sense it's it's infinite even if it started out as a finite little dot well you know not a DOT I'm sorry a finite little hypersphere but it didn't really start out there cuz what what what what happened before that well we don't know so this is where it gets into a lot of speculation and let's go I mean let's go there okay sure so you know nobody can prove wrong the idea right what happened before T equals z and whether there are other universes out there I like to say that these are sort of on the bound boundaries of science they're not just ideas that we wake up at 3 in the morning to go to the bathroom and say oh well let's think about what happened before the Big Bang or let there be a multiplicity of universes in other words we have real testable physics that we can use to draw certain conclusions that are plausibility arguments based on what we know now admittedly there are not really direct tests of these hypotheses that's why I call them hypotheses they're they're not really elevated to a theory because a theory in science is really something that has a lot of experimental or observational support behind it so they're they're hypotheses but they're they're not unreasonable hypotheses based on what we know about general relativity and quantum physics okay and they may have indirect tests in that if you adopt this hypothesis then there might be a bunch of things you expect of the universe and lo and behold that's what we measure but we're not actually measuring anything at T less than zero or we're not actually measuring the presence of Another Universe in this Multiverse and yet there are these indirect ideas that stem forth so it's hard to prove uniqueness and it's hard to completely convince oneself that a certain hypothesis must be true but you know the more and more tests you have that it satisfies let's say there are 50 predictions it makes and 49 of them are in are are things that you can measure and then the 50th one is the one where you you want to measure the actual existence of that other universe or what happened before T equals z and you can't do that but but you've satisfied 49 of the other testable predictions and so that's science right now A a conventional condensed matter physicist or someone who deals with real data in the laboratory might say oh you cosmologists you know that's not really science because it's not directly testable but I would say it's sort of testable but but it's not completely testable and so it's at the boundary but it's not like we're coming up with these crazy ideas among them Quantum fluctuations out of nothing and then inflating into a universe with you might say well you created a giant amount of energy but in fact this Quantum fluctuation out of nothing you know in a Quantum way violates the conservation of energy but you know who cares that was a classical law anyway and then an inflating Universe maintains whatever energy it had be it zero or some infinites amount in a sense the stuff of the universe has a positive energy but there's a negative gravitational energy associated with it it's like I drop an apple I got kinetic energy energy of motion out of that but I did work on it to bring it to that height mhm so by going down and gaining energy of motion positive 1 2 3 4 5 units of kinetic energy it's also gaining or losing depending on one how you want to think of it negative 1 2 3 four five units of potential energy so the total energy Remains the Same an inflating Universe can can do that or other physicists say that energy isn't conserved in general relativity that's another way out of creating a universe out of nothing you know but the point is that this is all based on reasonably well tested physics and although these these extrapolations seem kind of outrageous at first they're not completely outrageous they're they're within the realm of what we call science already and maybe some Y young whipper snapper will be able to figure out a way to directly test what happened before T equals z or to test for the presence of these other universes but right now we don't have a way of doing that so speaking of uh young whipper snappers Roger Penrose yeah uh so he kind of has a you know idea that we there may be some information that travels from whatever the heck happened before the Big Bang yeah maybe I kind of doubt it so do you think it's possible to detect some like actually experimentally be able to detect some I don't know what it is radiation some some sort of yeah and the cosmic microwave background radiation there may be ways of doing that is but is it is it philosophically or practically possible to detect signs that this was before the Big Bang or is it or is it what you said which is like everything we observe will as we currently understand will have to be a creation of this particular observable universe yeah I mean you know if you it's very difficult to answer right now because we don't have a single verified fully self-consistent experimentally tested quantum theory of gravity right and of course the beginning of the universe is a large amount of stuff in a very small space so you need both quantum mechanics and general relativity same thing if our universe Recaps and then bounces back to another big bang you know there's also ideas there that some of the information leaks through or survives I don't know that we can answer that question right now because we don't have a quantum theory of gravity that most physicists uh believe in and belief is perhaps the wrong word that most physicists trust because the experimental evidence favors it yeah right you know there are various forms of string theory there's Quantum Loop gravity there are various ideas but which if any will be the one that survives the test of time and more importantly within that the test of experiment and observation yeah so my own feeling is probably these things don't survive I don't think we've seen any evidence in the cosmic microwave background radiation of of information leaking through similarly um the one way or one of the few ways in which we might test for the presence of other universes is if they were to collide with ours that would leave a a pattern a temperature signature in the cosmic microwave background radiation some astrophysicists claim to have found it but in my opinion it's not statistically significant to the level that would be necessary to have such a an amazing claim right you know it's just a 5% chance that the microwave background had that distribution just by chance yeah five % isn't very long odds if you're claiming that instead that you're that you're finding you know evidence from Another Universe I mean it's like if the Large Hadron Collider people had claimed after gathering enough data to show the higs particle when there was a 5% chance it could be just a statistical fluctuation in their data no they they required five Sigma five stand deviations which is roughly One Chance in 2 million that this is a statistical fluctuation of no physical greater significance you know extraordinary claims require extraordinary go it all boils down to that and the and the greater your claim the greater is the evidence that is needed and the more evidence you need from independent ways of measuring or of coming to that deduction you know a good example was the the accelerating universe you know when we found it evidence for it in 1998 with supern noi with exploding Stars it was great that there were two teams that lent some credibility to the Discovery but it was not until other astrophysicists used not only that technique but more importantly other independent techniques that had their own potential sources of systematic error or whatever but they all came to the same conclusion and that started giving a much more complete picture of what was going on in a picture in which most astrophysicists quickly gained confidence that's why that idea caught on so quickly is that there were other physicists and astronomers doing observations completely independent of supern noi that seemed to indicate the same thing yeah that period of uh of your life that work with a incredible team of people that um won the Nobel Prize is just fascinating work oh gosh you know never in my wildest dreams as a kid did I think that I would be involved much less so heavily involved in a discovery that's so revolutionary I mean you know as a kid as a scientist if you're realistic once you learn a little bit more about how science is done and you're not going to win a Nobel Prize and be the next Newton or Einstein or whatever you just hope that you'll contribute something to humankind's understanding of how nature works and you'll be satis ified with that you know but here I was in the right place at the right time a lot of luck a lot of hard work um and there it was you know we discovered something that was really amazing and that that was the the greatest thrill right I couldn't have asked for anything more uh than being involved in that Discovery so one so the the couple of teams of supernova cosmology project and the high Supernova search team so the what was the Nobel Prize given for it was given for the discovery of the expansion of the universe not for the elucidation of what dark energy is or what causes that expansion uh that acceleration be it universes on the outside or whatever it was only for the observational fact so first of all what is the accelerating universe so the accelerating universe is simply that if we look at the galaxies moving away from us right now we would expect them to be moving away more slowly than they were billions of years ago and because Galaxies have visible matter which is gravitationally attractive and dark matter of an unknown sort that holds galaxies together and holds clusters of galaxies together and of course they then pull on one another and they would tend to the expansion of the universe just as when I toss an apple up you know even ignoring air resistance the mutual gravitational attraction between Earth and the Apple slows the Apple down and if that attraction is great enough then the Apple will they stop and even come back the Big Crunch you could call it or the gnab Gibb which is Big Bang backwards right that's what could have happened to the universe but even if the universe's original expansion energy was so great that it avoids the Big Crunch that's like an apple thrown at Earth's escape speed it's like that the the the the rockets that go to Mars someday right you know uh with people even then you'd expect the universe to be slowing down with time but we looked back through through the history of the universe by looking at progressively more distant galaxies and by seeing that the evolution of this expansion rate is that in the first N9 billion years yeah it was slowing down but in the last five billion years it's been speeding up so who asked for that right you know um I think it's interesting to talk about a little bit of the human story of the Nobel Prize sure which is I mean fascinating it's a really first of all the prize itself it's kind of fascinating in the psychological level that uh prizes uh I know we kind of think that prizes don't matter but somehow they kind of focus the mind about some of the most special things we have ACC the recognition the funding you know but and also inspiration for like I said when I was a little kid they get The Nobel Prize like I I didn't you know it inspires millions of young scientists at the same time there's a sadness to it a little bit that uh especially in the field like depending on the field but experimental fields that involve teams of I don't know sometimes hundreds I mean of brilliant people the Nobel Prize is only given to just a handful I that's right is it Ma Max a three yeah yeah and it's not even written in Alfred nobel's will it turns out one of our teammates looked into it in a museum in Stockholm when we went there for Nobel week in 2011 the the leaders who got the prize formally knew that without the rest of us working hard in the trenches the result would not have you know been discovered so they invited us to participate in Nobel week and so one of the team members looked in the will and it's not there it's just tradition that's but it's archaic you know that's the way science used to be done and it's not the way a lot of science is done now and you look at gravitational wave discovery which was you know recognized with the Nobel Prize in 2017 Ray weet MIT got it and Kip Thorne and um and um Barry beish at Caltech and Ron DAV one of the masterminds had passed away earlier in the year so again one of the rules of Nobel is that it's not given pusle yeah or at least the one exception might be if they've made their decision and they're busy making their press releases right before October the first week in October or whatever and then the person passes away I think they don't change their minds then but yeah you know it it it doesn't square with today's reality that a lot of science is done by big teams in that case a team of a thousand people in our case it was two teams consisting of about 50 people and we used techniques that were arguably developed in part by people who astrophysicists who weren't even on those two papers I mean some of them were but other papers were written by by other people you know know and so it's like we're standing on the shoulders of giants and none of those people was officially recognized and to me it was okay you know again it was the thrill of doing the work and ultimately the work the discovery was recognized with the prize and you know we got to participate in Nobel week and you know it's okay with me I I've known other physicists whose lives were ruined because they did not get the Nobel Prize and they felt strongly that they should have Ralph alfer um of the alfha beta gamma you know paper predicting the microwave background radiation he should have gotten it his adviser gamov was dead by that point but um you know penus and Wilson got it for the discovery and and alfur apparently from colleagues who knew him well I've talked to them his life was ruined by this he just it just nod at his inard so much it's uh very possible that uh and a small handful of people even three that you would be one of the Nobel one of the winners of the Nobel Prize that doesn't weigh heavy on you well you know there were the two team leaders Saul pearlmutter and Brian Schmidt and usually it's the team leaders that are recognized and then Adam Reese was my postto um first first author I guess yeah first author I was second author of that paper yeah uh so I was his direct Mentor at the time although he was you know one of these people who just you know runs with things he was an MIT undergraduate by the way um Harvard graduate student and then a postto as a so-called Miller fellow for basic research in science at Berkeley something that I was back in ' 84 to 86 but you're you're you know you're largely a free agent but he worked quite closely with me and he came to Burkle to work with me and on Schmidt's team he was charged with analyzing the data and he measured the brightnesses of these distant supern noi showing that they're fainter and thus more distant than anticipated and that led to this conclusion that the Universe had to have accelerated in order to push them out to such great distances and I was shocked when he showed me the data the results of his calculations and measurements um but it's very you know so he deserved it but and on Sal G gon g gold hobber deserved it but he died I think a year earlier in 2010 but that would have been four and so and me well I was on both teams but you know was I number four five six seven I don't know well it's it's also very so if I were to it's possible that you're I mean I I could make a very good case for you're in in the three and does thaty kind you know so but is that psychologically I mean listen it weighs on me a little bit because I yeah I I don't know what to do with that it it U perhaps it should motivate uh the rethinking like Time magazine started doing like you know person of the year yeah and like they they would start doing like Concepts and almost like the black hole gets the Nobel Prize or Universe gets the Nobel Prize and here's the list of people so like ult or like the Oscar that you could say yeah because it it's a team effort now you know and it should be redone and the Breakthrough prize in fundamental physics which was started by Yuri Milner and Zuckerberg is involved and others as well you know uh they recogniz a larger team yeah they they recognized teams and so in fact both teams in the accelerating universe were recognized with the Breakthrough prize in 2015 nevertheless the same three people reys pearlmutter and Schmidt got the red carpet rolled out for them and were at the big ceremony and shared half of the prize money and the rest of us roughly 50 shared the other half and didn't get to go to the ceremony so but I I I feel for them I mean for the gravitational waves it was a thous people what are they going to do invite everyone for the higs particle it was 6 to 8,000 physicists and engineers in fact because of the whole issue of who gets it experimentally that Discovery still has not been recognized right the theoretical work by Peter higs and uh angir got recognized but there was a troa of other people who WR perhaps wrote the most complete paper and they were they were left out and um another guy died you know and yeah it's heart it's all of it's heartbreaking some people argue that the Nobel Prize has been deluded to because if you look at Roger Penrose you can make an argument that he should get the prize by himself like it's she separate those like could have and should have perhaps he should have perhaps gotten it with Hawking before Hawking's death right the problem was Hawking radiation had not been detected but you could argue that Hawking made enough other fundamental contributions to the theoretical study of black holes and The observed data were already good enough at the time of before Hawking's death okay I mean the latest results by Reinhardt gel's group is that they see the time dilation effect of a star that's passing very close to the black hole in the middle of our galaxy that's cool but and it adds additional evidence but hardly anyone doubted the existence of the super massive black hole and Andrea gz's group I believe hadn't yet shown that relativistic effect and yet she got part of the prize as well so clearly it was given for the the original evidence that was really good and that evidence is at least a decade old you know so one could make the case for for Hawking um one could make the case that in 2016 when mayor and Kao won the Nobel Prize for the discovery of the first exoplanet um 51b pegasi well there was a fellow at Penn State Alex walon who in 1992 three years preceding 1995 found a a p a planet orbiting a pulsar a very weird kind of star a neutron star and that wouldn't have been a normal Planet sure and so the Nobel committee you know they gave it for the discovery of planets around normal sunlike stars but but hell you know Wan found a planet so they could have given it to him as the third person instead of to Jim Peebles for the development of what's called physical cosmology he's at Princeton he deserved it but they could have given Nobel for the development of physical cosmology to pees and I would claim some other people were pretty important in that development as well you know and they could have given it some other year um so there's there's a lot of controversy I try not to dwell on it was I number three probably not you know Adam Reese did the work um you know I helped bounce ideas off of him but it we wouldn't have had the result without him yeah and I was on both teams for reasons I mean you know I the the St of the first team the Supernova cosmology project didn't match mine they came largely from experimental high energy particle physic physics where there's these hierarchical teams and stuff and it's hard for the little guy to to have a say at least that's what I kind of thought whereas the team of astronomers led by Brian Schmidt was first of all a bunch of my friends and they grew up as astronomers making contributions on little teams and we decided to band together but all of us had our voices heard so it was sort of a a culture a style that I preferred really but let me tell you a story at the Nobel banquet okay I'm sitting there between two physicists who are who are members of the committee of the Swedish National Academy of Sciences you know and I strategically kept you know offering them wine and stuff during this long drawn out Nobel ceremony right and I got them to be pretty talkative and then in a in a polite diplomatic way I started asking them pointed questions m M and basically they admitted that if there are four or more people M equally deserving they wait for one of them to die or they just don't give the prize at all when it's unclear who the three are at least unclear to them but unclear to them it's they're not even right part of the time I mean Joselyn Bell discovered pulsars MH with a radio antenna a set of radio antennas that her adviser Anthony hsh conceived and built so he deserves some credit but but he didn't discover the Pulsar she did and his initial reaction to the data that she showed him was a condescending rubbish my dear yeah I'm not kidding now I know JN Bell and she did not let this destroy her life yeah she won every other prize Under the Sun okay um Vera ruin arguably one of the discoverers of Dark Matter although there if you look at the history there were a number of people that was the issue I think there were a number of people four or more who had similar data and similar ideas at about the same time Ruben won every prize Under the Sun the new big large scale survey telescope being built in Chile is being renamed the Vera rubben telescope because she passed away in December of 2015 I think um you know it'll conduct this survey large scale survey with the Reuben telescope so she's been recognized but never with the Nobel Prize and I would say that to her credit she did not let that consume her life either and perhaps it was a bit easier because there had been no no Bell given for the discovery of Dark Matter whereas in the case of pulsars and Joselyn Bell there was a prize given for the discovery of the freaking pulsar and she didn't get it what I mean what a Trav of justice so I I also think as a fan of fiction as a fan of stories that the the the travesty and the tragedy and the unfairness and the tension of it is what makes the prize and similar prize is beautiful the the decisions of other humans that result in dreams being broken and you know like I that's why we love the Olympics as so so many you know people athletes give their whole life for this particular moment and and then there's referee decisions and like little slips of here and there like the little misfortunes that destroy entire dreams and that's it's it's weird to say but it feels like that makes the entirety of it even more special yeah if it was perfect it wouldn't be interesting well humans like competition and they like Heroes and unfortunately it gives the impression to youngsters today that science is still done by by white men with gray beards wearing white lab coats and I'm very pleased to see that this year you know Andrea gz the fourth woman in the history of the physics prize to have received it and then uh two women one at Berkeley uh one elsewhere won the Nobel Prize in chemistry without any male co-recipient and so that's sending a message I think to girls that they can do science and they have um Role Models I think uh the Breakthrough prize and other such prizes show that teams get recognized as well and and if you pay attention to the newspapers you know most of the good authors like you know Dennis Overby of the New York Times and others said that these were teams of people and they they emphasized that and you know they all played a role um and you know maybe if some grad student hadn't soldered some circuit maybe the whole thing wouldn't have worked you know um but still you know Ray Weiss Kip Thorne was the theoretical uh you know impetus for the whole search for gravitational waves Barry bearish brought the MIT and Caltech teams together to get them to cooperate at a time when the project was nearly dead from what I understand and contributed greatly to the experimental setup as well he's a great experimental physicist but he was really good at bringing these two teams together instead of having them duke it out in blows and leaving both of them bleeding and dying you know that National Science Foundation was going to cut the funding from what I understand you know so so there's human drama involved in this whole thing and the Olympics yeah you know a runner a swimmer a rummer runner you know they they slip just at the moment that they were taking off from the first thing and that costs them some fraction of a second and that's it they didn't win you know and in that case I mean the the coaches the families which I've met a lot of Olympic athletes and the coaches and the families of the athletes are really the winners of the medals I mean but they don't get the medal and it's it's you know credit assignment is a fascinating thing I mean that's the full human story we have yeah we have and and uh outside of prizes it's fascinating I mean uh just to be in the middle of it for artificial intelligence there's a field of deep learning that's really exciting and people have been there's a yet another award uh the touring award given for deep learning to to three folks who are very much responsible for the field but so are a lot of others that's right and there's a few there's uh uh there's a fellow by the name of Schmid Huber who uh sort of symbolizes the the Forgotten folks in in the Deep Learning Community but you know that's that's the unfortunate set thing we remember we remember Isaac Newton we remember uh these these these special figures and the ones that flew close to them uh we forget well that's right and you know often the breakthroughs are made based on the body of knowledge that had been assimilated prior to that but you know again people like to worship Heroes you you mentioned the Oscars earlier and you know you look at the direct I mean well I mean okay directors and stuff sometimes get Awards and stuff but um you know you look at even something like I don't know songwriters musicians Elton John or something right Bernie topin right wrote many of the words or he's not as well known or or the Beatles or something like that I was heartbroken to learn that Elvis didn't write most of his songs yeah Elvis That's right there there you go but he was the King right and he had such a personality and and he it was such a performer right but it's the unsung heroes in many cases yeah so maybe taking a step back we talked about the Nobel Prize for the accelerating universe but uh your work and the ideas uh around Supernova were important uh in detecting this accelerating universe can we go to the very basics of what is this uh beautiful mysterious object of a supernova right so a supernova is an exploding star most stars die a relatively quiet death our our own sun will despite the fact that it'll become a red giant and incinerate Earth it'll do that reasonably slowly but there's a small minority of stars that end their lives in a Titanic explosion and that's not only exciting to watch from afar but it's critical to our existence because it is in these explosions that the heavy elements synthesize through nuclear reactions during the normal course of the Stars Evolution and during the explosion itself get ejected into the cosmos making them available as raw material for new stars planets and ultimately life you know and that's just a great story um the best in in some ways so you know we like to study these things and and our Origins but it turns out these are incredibly useful beacons as well because if you know how powerful uh an exploding star really is by measuring the apparent brightness at its peak in galaxies whose distances we already know through having made other measurements and you can thus calibrate how powerful the thing really is and then you find ones that are much more distant then you can use their observed brightness compared with their true intrinsic power or Luminosity to judge their distance and hence the distance of the Galaxy in which they're located so okay it's like looking at if you'll uh let me just give this one analogy you know you judge the distance of an oncoming car at Night by looking at how bright its headlights appear to be and you've calibrated how bright the headlights are of a car that's two or three meters away of known distance and you go who that's a a faint headlight and so that's pretty far away you also use the apparent angular separation between the two headlights as a consistency check in your brain but that's what your brain is doing so we can do that for cars we can do that for stars nice I like that but you know with cars the headlights are all there's some variation there's but but uh they're somewhat similar so you can make those kinds of conclusions what uh how much uh variation is there between Supernova that you can yeah that in can you detect them right so first of all there are several different ways that stars can explode and it depends on their mass and whether they're in a binary system and things like that and the ones that we used for these cosmological purposes studying the expansion of the history history of the universe are the so-called type Roman numeral one lowercase a type 1 a super noi they come from a weird type of a star called a white dwarf our own son will turn into a white dwarf in about 7 billion years it'll have about half its present Mass compressed into a volume just the size of Earth so that's an inordinate density okay it's incredibly dense and the matter is what's called by Quantum physic degenerate matter not because it's morally reprehensible or anything like that but this is just the name no judgments here yeah Quantum physicists give to electrons that are squeezed into a very tight space the electrons take on a motion due to Heisenberg uncertain Heisenberg's uncertainty principle and also due to the poly exclusion principle that electrons don't like to be in the same place they like to avoid each other so those two things mean that a lot of electrons are moving very rapidly which gives the star an extra pressure far above the thermal pressure associated with just the random motions of particles inside the star so it's a weird type of star but normally it wouldn't explode and our sun won't explode except that if such a white dwarf is in a pair with another more or less normal star it can steal material from that nor normal star until it gets to an unstable limit rough roughly 1 and a half times the mass of our sun 1. four or so this is known as the chandar CH Chandra sear limit after subber Manan Chandra sear an Indian astrophysicist who figured this out when he was about 20 years old on a voyage from India to England where he was to be educated and then he did this and then 50 years later he won the Nobel Prize in physics in 1984 largely for this work okay that he did as a youngster who was on his way to be educated you know oh and his advisor the great AR Edington in England who had done a lot of great things and was a great astrophysicist nevertheless he too was human and had his faults he ridiculed chandra's scientific work at a conference in England and you know most of us have we had been Chandra would have just given up astrophysics at that time you know when the Great Arthur Edington you know ridicules our our work and that's another inspirational story for the youngster you know just just keep going you know but anyway your advisor yeah no matter what your advisor says right so or don't always pay attention to your advisor right don't don't be uh don't lose hope if you really think you're on to something that doesn't mean never listen to your adviser they may have Sage advice as well yeah but anyway um you know when a white dwarf grows to a certain Mass it becomes unstable and one of the ways it can end its life is to go through a thermonuclear runaway so basically the carbon nuclei and inside the white dwarf starts start fusing together to form heavier nuclei and the energy that those Fusion reactions emit emits doesn't go into um you know being dissipated out of the star or you know whatever U or expanding it the way you know if you take a blowtorch to the middle of the sun you heat up its gases the gases would expand and cool but this degenerate star can't expand and cool so the energy pumped in through these Fusion reactions goes into making the nuclei move faster and that gets more of them sufficiently close together that they can undergo nuclear fusion thereby releasing more energy that goes into speeding up more nuclei and thus you have a a runaway a bomb an uncontrolled nuclear fusion reactor right instead of the controlled Fusion which is what our sun does okay our sun is a marvelous controlled Fusion reactor this is what we need here on Earth Fusion Energy to solve our energy crisis right uh but the sun holds the stuff in you know through gravity and you need a big Mass to do that so this uncon uncontrolled fusion reaction blows up a star that's pretty much the same in all cases and you measure it to be almost the same in all cases but the devil is in the details and in fact we observe them to not be all the same and theoretically they might not be all the same because the rate of the fusion reactions might depend on the amount of Trace heavier elements in the white dwarf and that could depend on how old it is when it was you know whether it was born billions of years ago when there weren't many heavier elements or whether it's a relatively young white dwarf and all kinds of other things and part of my work was to show that indeed not all the type 1as are the same you have to be careful when you use them you have to calibrate them they're not standard candles the way it just if all headlights or all candles were the same lumens or whatever you'd say they're standard and it would be standard candles is an awesome term okay standard candles is what astronomers like to say I don't like that term because there aren't any standard candles but there are standardizable candles and by looking at these yeah you calibratable standardizable calibratable you look at enough of them in nearby galaxies whose distances you know independently and what you can tell is that you know uh this is something that a colleague of mine Mark Phillips did who was on Schmidt's team and arguably one of the was one of the people who deserved the Nobel Prize but he showed that the intrinsically more powerful type 1as um decline in brightness and it turns out rise in brightness as well more slowly than the less luminous onea and so if you calibrate this by measuring a whole bunch of nearby ones and then you look at a distance one instead of saying well it's a 100 watt type 1 a supernova they're much more powerful than that by the way plus or minus 50 you can say no it's it's 112 plus or minus 15 or it's or it's 84 plus or minus 17 it it tells you where it is in the power scale and it greatly decreases the uncertainties and that's what makes these things cosmologically useful I showed that if you spread the light out into a spectrum you can tell spectroscopically that these things are different as well and in 1991 I happened to study two of the extreme peculiar ones the low Luminosity ones and the high Luminosity ones 1991 BG and 1991t this showed that not all the 1 A's are the same and indeed at the time of 1991 I was a little bit skeptical that we could use type 1a's because of this diversity that I was observing but in 1993 Mark Phillips wrote a paper that showed this correlation between the light curve the brightness versus time and the peak luminosity and once gives you enough information to calibrate yeah then they become calibratable and that was a game changer how many type 1 a are out there oh gosh to use for data now there are thousands of them but at the time the high Z team had 16 and the um Supernova cosmology project had 40 but the 16 were better measured than the 40 and so our statistical uncertainties were comparable if you look at the two papers that were published how's that make you uh feel that there's these gigantic explosions just sprinkled out there is that well I certainly don't want one to be very nearby and it would have to be within something like 10 light years to be an existential threat so they can happen in our uh Galaxy oh yeah you uh in most cases we'd be okay because our galaxy is 100,000 light years across and you'd need one of these things to be within about 10 light years to be an existential threat and it gives birth to a bunch of other um stars I guess yeah it gives birth to expanding gases that are chemically enriched and those expanding gases mix with other chemically enriched expanding gases or primordial clouds of hydrogen and helium I mean th this is um in a sense the The Greatest Story Ever Told right I try to I teach this introductory astronomy course at at Berkeley and I tell them there's only five or six things that I I want them to really understand and remember and I'm going to come to their deathbed and I'm going to ask them about this and if they get it wrong I will retroactively fail their whole career will have been shot that and they don't observe a total solar eclipse and yet they had the opportunity to do so I will retroactively fail them but one of them is you know where did we come from where did the elements in our DNA come from the carbon in our cells the oxygen that we breathe the calcium in our bones the iron in our red blood cells those elements the phosphorus in our DNA they they all came from stars from nuclear reactions in stars and they were ejected into the cosmos and in some cases like iron made during the explosions and those gases drifted out mixed with other clouds made a new star or a star cluster some of whose members then evolved and exploded thus enriching the gases in the Galaxy progressively more with time until finally 4 and a half billion years ago from one of these chemically enriched clouds our solar system formed with a rocky earthlike planet and somewhere somehow these self-replicating evolving molecules bacteria formed and evolved D through paramia and amibas and slugs and and apes and and us and here we are sensient beings that can ask these questions about our very Origins and with our intellect and with the machines we make come to a reasonable understanding of our Origins what a beautiful Story I mean if that does not put you at least in awe if not in love with science and its power of deduction I don't know what will right it's it's one of the greatest stories if not the greatest story obviously that's you know personality dependent and all that it's it's a subjective opinion but it's perhaps The Greatest Story over ever told I mean you could link it to the big bang and go even farther right to make an even more complete story but as as a subset that's even in some ways a greater story than than even the existence of the universe in some ways cuz you could end up you could just imagine some really boring universe that never leads to sensient creatures such as ourselves and is this Supernova usually the the introduction to that story so are are they usually the thing that launches the is there other engines of creation well the Supernova is the one I mean I I I touch upon the subject earlier in my course in fact right about now in my lectures because I talk about how our sun right now is fusing hydrogen to form helium nuclei and later it'll form carbon and oxygen nuclei but that's where the process will stop for our sun it's not massive enough some Stars can that are more massive can go somewhat beyond that so that's the beginning of right this idea of the birth of the heavy elements since they couldn't have been born at the time of the Big Bang conditions of temperature and pressure weren't sufficient to make any significant quantities of the heavier elements and so so that's the beginning but then you need some of these stars to explode right because if those heavy elements remained forever trapped in the cores of stars then they would not be available for the production of new stars planets and ultimately life so indeed the Supernova my main area of Interest plays a a leading role in this whole story I saw that you got a chance uh to call Richard Fineman a mentor of yours when you were at Caltech yeah uh do you have any fond memories of Fineman any lessons that stick with you oh yeah he was quite a character uh and one of the deepest thinkers of all time probably and at least in my life the physicist who had the single most intuitive understanding of how nature works of anyone I've met uh he I I learned a number of things from he was not my thesis adviser I worked with Wallace Sergeant at galtech on what are called active galaxies big black holes in the centers of galaxies that are accreting or swallowing material a little bit like the stuff of of this year's Nobel Prize in physics 2020 uh but Fineman I had for for two courses one was general theory of relativity at The Graduate level and one was applications of quantum physics to all kinds of interesting things and he you know he had this very intuitive way of of looking at things that he tried to that he tried to bring to his students and he felt that if you can't explain something in a reasonably simple way to a non scientist or at least a you know someone who is versed a little bit with science but is not a professional scientist then you probably don't understand it very well yourself very thoroughly so that in me um you know made a desire to to to be able to explain science to the to the general public and I've often found that in explaining things yeah there's a certain part that I didn't really understand myself that's one reason I like to teach the introductory courses to the lay public is that I sometimes find that my explanations are lacking in my own mind you know so he did that for me is there uh if I could just pause for a second you said he had one of the most intuitive understanding of nature what if you could break apart what intuitive means like it is it on a philosophical level no sort of physical how do you draw a mental picture or a picture on paper of what's going on and he's perhaps most famous in this regard for his Fineman diagrams which in what's called Quantum electrodynamics a Quantum field theory of electricity and magnetism what you have are actually you know an exchange of photons between charged particles and they might even be virtual photons if the particles are at rest relative to one another and there are ways of doing calculations that are brute force that take pages on pages and pages of calculations and Julian schwinger uh developed some of the mathematics for that and won the Nobel Prize for it but feineman had these diagrams that he made and he had a set of rules of what to do at the vertex you know you have two particles coming together and then a particle going out and then two particles coming out again and he'd have these rules Associated when there were vertices and when there were particles splitting off from one another and all that and it looked a little bit like a bunch of a hodgepodge at first but to those who learned the rules and understood them he you know they they saw that you could do these complex calculations in a much simpler way and indeed in some ways Freeman Dyson had an even better knck for explaining really what Quantum electrodynamics actually was but I didn't know Freeman Dyson I I knew Fineman maybe he did have a more intuitive view of the world than Fineman did but of the people I knew finean was the most intuitive most sort of is there a picture is there a simple way you can understand this and in in um in the path that a particle follows even you know you can figure out the you can get the classical path at least you know for a baseball or something like that by using quantum physics if you want but you know in a sense the baseball sniffs out all possible paths it goes out to Andromeda galaxy and then goes to the to the batter but the probability of doing that is very very small because tiny little paths next door to Any Given path cancel out that path and the ones that all add together they they are the ones that are more likely to be followed and this actually ties in with font's principle of least action and their ideas and Optics that go into this as well and and it just sort of beautifully brings everything together but the particle sniffs out all possible paths what a crazy idea but if you do the mathematics associated with that it ends at being actually useful a useful way of looking at the world so you're also I mean you you're widely acknowledges I mean outside of your science work is being one of the greatest Educators in the world and Fineman is famous yeah for for being that is there something about being a teacher that you've well it's it's very very rewarding when you have students who are really into it and you know going back to Fineman at Caltech I was taking these graduate courses and there were two of us myself and Jeff richond who's now a professor of physics at University of California Santa Barbara who asked lots of questions and a lot of the Caltech students are nervous about asking questions they they want to save face they seem to think that if they ask a question their peers might think it's a stupid question well I didn't really care what people thought and Jeff Richmond didn't either and we ask all these questions and in fact in many cases they were quite good questions and Fineman said well the rest of you should be having questions like this and I remember one time in particular when he said you know he said to the rest of the class why is it always these two aren't you aren't the rest of you curious about what I'm saying do you really understand it all that well if so why aren't you asking the next most logical question no you guys are too scared to ask these questions that these two are asking so he actually invited us to lunch a couple of times where just the three of us sat and had lunch with one of the greatest thinkers of 20th century physics and so yeah he he rubbed off on me and so you encourage questions as well I encourage questions you know and uh yeah you know definitely I mean you know I encourage questions I I like it when students ask questions I tell them that they shouldn't feel shy about asking a question question probably half the students in the class would have that same question if they even understood the material enough to ask that question yeah curiosity is the first step of um absolutely of seeing the beauty of something so yeah and the question is the ultimate form of curiosity yeah let me ask uh what is the meaning of life the meaning of life you know from a cosmologist perspective or from a human perspective or from my personal you know life is what you make of it really right it's um each of us has to have our own meaning and it doesn't have to be well I I think that in many cases meaning is is to some degree associated with goals you set some goals or expectations for yourself things you want to accomplish things you want to do U things you want to experience and to the degree that you experience those and do those things it can give you meaning you don't have to change the world the way Newton or Michelangelo or Da Vinci did I mean people often say don't change the world but look come on there's seven and a half close to eight billion of us now most of us are not going to change the world and does that mean that most of us are leading meaningful lives no it it just has to be something that gives you meaning that gives you satisfaction that gives you a good feeling about what you did and and often based on nature which can be very good and also very bad but often it's the things that help others that give us meaning and a feeling of satisfaction you taught someone to read you cared for someone who was terminally ill you brought up a a nice family you brought up your kids um you did a good job you you put your heart and soul into it you read a lot of books if that's what you wanted to do had a lot of perspectives on life you you traveled the world if that's what you wanted to do um but if some of these things are not within reach you're in a socioeconomic position where you can't travel the world or whatever you find other forms of of meaning uh it doesn't it it doesn't have to be some profound I'm going to change the world I'm going to be the one who everyone remembers type thing right in the context of The Greatest Story Ever Told like the fact that we came from stars and now we're two Apes asking about the meaning of life yeah how does that fit together does that make any sense you know it does it does and this is sort of what I I was referring to that it's a beautiful universe that allows us to come into creation right it's a way that the Universe found of knowing of understanding itself because I don't think that you know inanimate rocks and stars and black holes and things have any real capability of of abstract thoughts and of learning about the rest of the universe or or even their Origins I mean they're just they're just a pile of atoms that's that's has no conscience has no ability to think has no ability to explore and we do and you know I'm not saying we're the epitome of all life forever but at least for life on Earth so far the evidence suggests that we are the epitome in terms of the richness of our thoughts the degree to which we can explore the universe do experiments build machines understand our Origins and I just hope that we use science for good not evil and that we don't end up destroying ourselves I mean the whales and dolphins are plenty intelligent they're they don't ask abstract questions they don't read books but on the other hand they're not in any danger of destroying themselves and everything else as well and so maybe maybe that's a better form of intelligence but at least in terms of our ability to explore and make use of our minds I mean to me it it's this it it's this that gives me um the potential for meaning yeah right the fact that I can understand and explore it's kind of fascinating to think that the universe created us and eventually we've built telescopes to look back at it to look back at its Origins and to wonder how the heck the thing works it's magnificent needn't have been that way right and this is one of the you know the Multiverse sort of things you know you can alter the laws of physics or or even the constants of nature seemingly inconsequential things like the mass ratio of the proton and the neutron you know wake me up when it's over right what could be more boring but it turns out you play with things a little bit like the ratio of the mass of the neutron to the proton and you generally get boring universes only hydrogen or only helium or only iron you don't even get the rich periodic table let alone bacteria paramia slugs and humans okay I'm not even anthropomorph an anthropos centz this to the degree that I could even a rich periodic table mhm wouldn't be possible if if certain constants weren't this way but but they are and that to me leads to the idea of of a Multiverse that you know that the dice were thrown many many times and there's this Cosmic archipelago where most the universes are are boring and some might be more interesting but we are in The Rare Breed that's really quite darn interesting and if there were only one and maybe there is only one well then that's that's truly amazing we're lucky we're lucky but I actually think there are lots and loss just like there are lots of planets Earth isn't special for any particular reason there are lots of planets in our solar system and especially around other stars and occasionally they're going to be ones that are conducive to the development of complexity culminating in Life as we know it and that's a beautiful story I don't think there's a better way to end it Alex it's a huge honor one of my favorite conversations I've had in this podcast thank you thank so much for talking for for the honor of of having been asked to do this thanks for listening to this conversation with Alex filipenko and thank you to our sponsors neuro the maker of functional sugar-free gum and mints that I used to give my brain a quick caffeine boost better help online therapy with a licensed professional master class online courses that I enjoy from some of the most amazing humans in history and cash app the app I use to send money to friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex fredman and now let me leave you with some words from Carl Sean the nitrogen in our DNA the calcium in our teeth the iron in our blood the carbon in our apple pies were made in the Interiors of collapsing Stars we are made of star stuff thank you for listening and hope to see you next time |
Dan Carlin: Hardcore History | Lex Fridman Podcast #136 | the following is a conversation with dan carlin host of hardcore history and common sense podcasts to me hardcore history is one of if not the greatest podcast ever made dan and joe rogan are probably the two main people who got me to fall in love with the medium of podcasting as a fan and eventually as a podcaster myself meeting dan was surreal to me he was not just a mere human like the rest of us since his voice has been a guide through some of the darkest moments of human history for me meeting him was like meeting genghis khan stalin hitler alexander the great and all of the most powerful leaders in history all at once in a crappy hotel room in the middle of oregon it turns out that he is in fact just the human and truly one of the good ones this was a pleasure and an honor for me quick mention of each sponsor followed by some thoughts related to the episode first is athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases second is simplisafe a home security company i use to monitor and protect my apartment third is magic spoon low carb keto friendly cereal that i think is delicious and finally cash app the app i use to send money to friends for food and drinks please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that i think we're living through one of the most challenging moments in american history to me the way out is through reason and love both require a deep understanding of human nature and of human history this conversation is about both i am perhaps hopelessly optimistic about our future but if indeed we stand at the precipice of the great filter watching our world consumed by fire think of this little podcast conversation as the appetizer to the final meal before the apocalypse if you enjoy this thing subscribe on youtube review 5 stars nappa podcast follow on spotify support it on patreon or connect with me on twitter at lex friedman and now finally here's my conversation with the great dan carlin let's start with the highest philosophical question do you think human beings are fundamentally good or are all of us capable of both good and evil and it's the environment that molds how we uh the trajectory that we take through life how do we define evil evil seems to be a situational eye of the beholder kind of question so if we define evil maybe i can get a better idea of and and that could be a whole show couldn't defining evil but when we say evil what do we mean that's a slippery one but i think there's some way in which your existence your presence in the world leads to pain and suffering and destruction for many others in the rest of the world so you you steal the resources and you use them to create more suffering than there was before in the world so i suppose it's somehow deeply connected to this other slippery word which is suffering as you create suffering in the world you bring suffering to the world but here's the problem i think with it because i i fully see where you're going with that and i understand it the problem is is the question of the reason for inflicting suffering so sometimes one might inflict suffering upon one group of individuals in order to maximize a lack of suffering with another group of individuals or one who might not be considered evil at all might make the rational seemingly rational choice of inflicting pain and suffering on a smaller group of people in order to maximize the opposite of that for a larger group of people yeah that's one of the dark things about i've spoken and read the work of stephen codkin i'm not sure if you're familiar with the historian and he's basically a stalin a joseph stalin scholar and one of the things i realized i'm not sure where to put hitler but with stalin it really seems that he was sane and he thought he was doing good for the world he i i really believe from everything i've read about stalin that he believed that communism is good for the world and if you have to kill a few people along the way if it's like you said the small groups if you have to sort of remove the people that stand in the way of this utopian system of communism then that's actually good for the world and it didn't seem to me that he could even consider the possibility that he was evil he really thought he was doing good for the world and that stuck with me because he's one of the most is to our definition of evil he seems to have brought more evil onto this world than almost any human in history and i don't know what to do with that well i'm fascinated with the concept so fascinated by it that the very first hardcore history show we ever did which was a full 15 or 16 minutes um was called alexander versus hitler and the entire question about it was the motivations right so if you go to a court of law because you killed somebody one of the things they're going to consider is why did you kill them right and if you killed somebody for example in self-defense you're going to be treated differently than if you malicious kill kill somebody maliciously to take their wallet right and in the show we we wondered because you know i don't really make uh pronouncements but we wondered about uh if you believe hitler's writings for example mein kampf uh which you know is written by a guy who's a political figure who wants to get so i mean it's about as as believable as any other political tract would be but in his mind the things that he said that he had to do were designed to for the betterment of the german people right whereas alexander the great once again this is somebody from more than 2000 years ago so with lots of propaganda in the intervening years right but one of the the views of alexander the great is that the reason he did what he did was to for lack of a better word write his name in a more permanent graffiti on the pages of history right in other words to glorify himself and if that's the case does that make alexander a worse person than hitler because hitler thought he was doing good whereas alexander if you believe the interpretation was simply trying to exalt alexander so the the motivations of the people doing these things it seems to me matter i don't think you can just sit there and go the only thing that matters is the end result because that might have been an unintentional byproduct uh in which case that person had you been able to show them the future might have changed what they were doing so were they evil or misguided or wrong or made the wrong you know so and i hate to do that because there's certain people like hitler that i don't feel deserve the benefit of the doubt uh at the same time if you're fascinated by the concept of evil and you delve into it deeply enough you're going to want to understand why these evil people did what they did and sometimes it can confuse the hell out of you you know who wants to sit there and try to see things from hitler's point of view to get a better understanding and sort of commiserate with so um but in fact obviously first history show i'm fascinated with the concept so do you think it's possible if we put ourselves in the mindset of some of the people that have led created so much suffering in the world that all of them had their motivations were had good intentions underlying them no i don't i mean simply because there's so many i mean the law of averages would would suggest that that's not true i guess it is pure evil possible meaning you uh again it's slippery but you the suffering is the goal suffering intentional suffering yeah yes i think that and i think that there's historical figures that that that one could point and but that gets to the deeper question of are these people saying uh do they have something wrong with them are they twisted from something in their youth um you know i mean these are the kinds of things where you start to delve into the psychological makeup of these people in other words is anybody born evil and i actually believe that some people are i think the dna can get scrambled up in ways i think the question of evil is important too because i think it's an eye of the beholder thing i mean if hitler for example had been successful and we were today on the sixth or seventh leader of the third reich since i think his entire history would be viewed through a different lens because that's the way we do things right genghis khan looks different to the mongolians than he does to the residents of baghdad right um and i think so so an eye of the beholder question i think comes into all these sorts of things as you said it's a very slippery question where do you put as somebody who's fascinated by military history where do you put violence as uh as in terms of the human condition is it core to being human or is it just a little uh tool that we use every once in a while so i'm going to respond to your question with a question what do you see the difference being between violence and force let me go farther i'm not sure that violence is something that we have to put up with as human beings forever that we must resign ourselves to violence forever but i have a much harder time seeing us able to abolish force and i there's going to be some ground where if those two things are not the same and i don't know that maybe they are where there's certainly some crossover and the re i think force you know you're an engineer you'll understand this better than i but think about it as a physical law if you can't stop something from moving in a certain direction without pushing back in that same direction i'm not i'm not sure that you can have a society or a civilization without the ability to use a counter force when things are going wrong whether it's on an individual level right a person attacks another person so you step in to save that person um or on uh you know even at the highest levels of politics or anything else a counter force to stop the uh inertia or the impetus of of of another movement so i think that force is is a simple almost law of physics in human interaction especially at the civilizational level i think civilization requires a certain amount of if not violence than force so um and again they've talked i mean it goes back into saint augustine all kinds of christian beliefs about the the proper use of force and people have have philosophically tried to decide between can you have a sort of an ahinsa uh buddhist sort of we you know we would be non-violent toward everything and exert no force or or there's a reason to have force in order to create the space for good uh i think force is inevitable now we can talk and and i've not come up to the conclusion myself uh if there is a distinction to be made between force and violence i mean is is um is a non-violent force enough or is violence when done for the cause of good a different thing than violence done either for the cause of evil as you would say or simply for random reasons i mean we humans lack control sometimes we can be violent for no apparent reason or goal um and that's i mean you look at the criminal justice system alone and the way we we interact with people who are acting out in ways that we as a society have decided is intolerable can you deal with that without force and at some level violence i don't know can you maintain peacefulness without force i don't know just to uh be a little bit more specific about the idea of force do you put force as general enough to include force in the space of ideas so you mentioned buddhism or religion or just twitter i can think of no things farther apart than that okay is uh the battles we do in the space of ideas of um you know the great debates throughout history do you put force into that or do you in this conversation are we trying to right now keep it to just physical force in saying that you you have an intuition that force might be with us much longer than violence i think the two bleed together so um take because it's it's always it's always my go-to example i'm afraid and i'm sure that the listeners all hate it but take take germany during uh the 1920s early 1930s before the nazis came to power and they were always involved in some level of force you know beating up in the streets or whatever it might be but think about it more like an intellectual discussion until a certain point um is that it would be difficult i imagine to keep the intellectual counterforce of ideas from at some point degenerating into something that's more um coercion um counterforce if we want to use the phrases we were just talking about so i think the two are are intimately connected i mean actions follow thought right and at a certain point i think especially when when one is not achieving the goals that they want to achieve through uh peaceful discussion or argumentation or um trying to convince the other side that sometimes the next level of operations is something a little bit more physically uh imposing if that makes sense we go from the intellectual to the physical yeah so it too easily spills over into violence yes and one leads to the other often so you kind of implied uh perhaps a hopeful message but let me ask in the form of a question do you think we'll always have war i think it goes to the force question too so for example um what do you do i mean we're let's let's play with nation states now although i don't know that nation states uh are something we should think of as a permanent constitution forever um but how is one nation state supposed to prevent another nation state from acting in ways that it would see as either detrimental to the global community or detrimental to the interest of their own nation-state um you know and i i think i think we've had this question of going back to ancient times but certainly in the 20th century this has come up quite a bit i mean the whole second world war argument sometimes revolves around the idea of what the proper counterforce should be uh can you create an entity a league of nations a united nations uh a one world entity maybe even that that alleviates the need for counterforce involving mass violence and armies and navies and those things uh i think that's an open discussion we're still having it's good to think through that because um having us like a united nations there's usually a centralized control so there's humans at the top there's committees and uh usually like leaders emerge a singular figures that then can become corrupted by power and it's just a really important it feels like a really important thought experiment and something to really rigorously think through how can you construct systems of government that are stable enough to push us towards less and less war and less and less unstable and another tough war which is unfair of application of force you know it's that's really at the core of the question that we're trying to figure out as humans as our weapons get better and better and better destroying ourselves it feels like it's important to think about how we minimize the over application or unfair application of force there's other elements that come into play too you and i are discussing this at the very high intellectual level of things but there is also a tail wagging the dog element to this so think of a society of warriors a tribal society from a long time ago how much do the fact that you have warriors in your society and that their reason for existing what they take pride in what they train for um what their status in their own civilization how much does that itself drive the responses of that society right um how much do you need war to legitimize warriors um you know that's the old argument that you get to and we've had this in the 20th century too that that the creation of arms and armies creates a an incentive to use them right and and that they themselves can drive that incentive as as a justification for their reasons for existence you know um that's where we start to talk about the interactivity of all these different elements of society upon one another so when we talk about you know governments and war we need to take into account the various things those governments have put into place in terms of systems and armies and things like that to to protect themselves right for reasons we can all understand but they exert a force on your your range of choices don't they it's true you're making me realize that uh in my upbringing and i think i'm bringing of many warriors are heroes you know to me i don't know where that feeling comes from but to sort of uh die fighting is uh it's an honorable way to die it feels like that i've always had a problem with this because as a person interested in military history the distinction is important um and i try to make it at different levels so at base level the the people who are out there on the front lines doing the fighting uh to me those people can be compared with police officers and firemen and people the fire persons um but but i mean people that are are um involved in an ethical uh attempt to perform a task which ultimately uh one can see in many situations as being a savings sort of task right or or if nothing else a self-sacrifice for what they see is the greater good now i draw a distinction between the individuals and the entity that they're a part of a military and i certainly draw a distinction between the military and then the entire for lack of a better word military-industrial complex that that service is a part of i feel a lot less moral attachment to uh to those upper echelons than i do the people on the ground the people on the ground could be any of us and have been in a lot of you know we have a very professional uh sort of military now where it's a very uh a subset of the population but in other periods of time we've had conscription and drafts and and it hasn't been a subset of the population it's been the population right and so it is the society oftentimes going to war and i make a distinction between those warriors and the entities either in the system that they're part of the military or the people that control the military at the highest political levels i feel um a lot less moral attachment to them and i have i'm much harsher about how i feel about them i do not consider the military itself to be heroic and i do not consider the military-industrial complex to be heroic i do think that is a tail wagging the dog situation i do think that draws us into looking at um military endeavors as a solution to the problem much more quickly than we otherwise might and to be honest to tie it all together i actually look at the victims of this as the soldiers we were talking about i mean if you if you set a fire to send firemen into to fight um then i feel bad for the firemen i feel like you've abused the trust that you give those people right so when when people talk about war i always think that the people that we have to make sure that a war is really necessary uh in order to protect are the people that you're going to send over there to fight that the greatest victims in our society of war are often the warriors so i in my mind um you know when we see these people coming home from places like iraq a place where i would have made the argument and did at the time that we didn't belong to me those people are victims and i know they don't like to think about themselves that way because it runs totally counter to the to the ethos but if you're sending people to protect this country's shores those are heroes if you're sending people to go do something that they otherwise probably don't need to do but they're there for political reasons or anything else you want to put in that's not defense related well then you've made victims of our heroes and so i i feel like we do a lot of talk about our troops and our soldiers and stuff but we don't treat them as valuable as we as as the rhetoric makes them sound otherwise we would be more um we would be much more careful about where we put them if you're going to send my son and i don't have a son i have daughters but if you're going to send my son into harm's way i'm going to demand that you really need to be sending him into harm's way and i'm going to be angry at you if you put him into harm's way if he doesn't if it doesn't warrant it and so i have much more suspicion about the system that sends these people into these situations where they're required to be heroic than i do the people on the ground that i look at as um either uh the people that are defending us you know in situations like this you know the second world war for example or or the people that um turn out to be the individual victims of a system where they're just a cog and a machine and the machine doesn't really care as much about them as as the rhetoric and the propaganda would insinuate yeah and uh as my own family history it would be nice if we could talk about there's a gray area in in the places that you're talking about there's a gray area in everything and everything but when that gray area is part of your own blood as it is for me it's it's worth shining a light on somehow sure give me example what you mean so you did a program of four episodes of ghosts of the us front yeah so i was born in the soviet union i was raised in moscow my dad was born and raised in kiev my grandmother who just recently passed away was um uh raised in ukraine she it's a small city on the border between russia and ukraine i have a grandfather born in kiev in kiev the interesting thing about the timing of everything as you might be able to connect as she survived she's the most badass woman of uh i've ever encountered my life and most of the warrior spirit i carry is probably from her she survived polymor the ukrainian starvation of the 30s she was a beautiful teenage girl during the nazi occupation of so she survived all of that and of course family that that everybody you know and so many people died the whole process so and one of the things you talk about in your program is that the gray area is even with the warriors it happened to them just like as you're saying now it uh they didn't have a choice so my my grandfather on the on the other side he was uh a machine gunner uh that was in ukraine that that in the red army in the red army yeah and they through uh like the the statement was that there's i don't know if it's obvious or not but the rule was there's no surrender so you you better die so you i mean you're basically the goal was when he was fighting and he was lucky enough one of the only to survive by being wounded early on is there was a march of uh nazis towards i guess moscow and the whole goal in ukraine was to slow everyth to slow them into the into the winter i mean i view him as such a hero and he believed that he's indestructible which is survivor bias and that you know bullets can't hurt him and that's what everybody believed and of course basically everyone that uh he quickly rose to the ranks let's just put it this way because everybody died it's it's it's it was just bodies dragging these heavy machine guns like always you know i was slowly retreating shooting and retreating shooting and retreating and i don't know he was a hero to me like i always i grew up thinking that he was the one that sort of defeated the nazis right and but the reality that there could be another perspective which is all of this happened to him uh by the incompetence of stalin the incompetent incompetence and uh men of uh the soviet union being used like pawns in a in a shittily played game of chess right so like the one narrative is of him as a victim as as you're kind of describing and it then somehow that's more paralyzing and that's more i don't know it feels better to think of him as a hero and as russia soviet union saving the world i mean that narrative also is in the united states that that uh the united states was key in saving the world from the nazis it feels like that narrative is powerful for people i'm not sure and i carry it still with me but when i think about the right way to think about that war i'm not sure if that's the correct narrative let me suggest something there's a line that uh that a marine named eugene sledge uh had said once and i i keep it on my phone because it's it's it makes a real distinction and he said the front line is really where the war is and anybody even a hundred yards behind the front line doesn't know what it's really like now the difference is is there are lots of people miles behind the front line that are in danger right you can be in a medical unit in the rear and artillery could strike you planes could start i mean you could be in danger but at the front line there are two different things one is um that that and at least and i'm doing a lot of reading on this right now and reading a lot of veterans accounts james jones who wrote uh uh books like from here to eternity fictional accounts of the second world war but he based them on his own service he was at uh guadalcanal for example in 1942. and jones had said that the evolution of a soldier in front line action requires an almost surrendering to the idea that you're going to live that you you you become accustomed to the idea that you're going to die and he said you're a different person simply for considering that thought seriously because most of us don't but what that allows you to do is to do that job at the front line right if you're too concerned about your own life um you become less of a good guy at your job right the other thing that the people in the one in the 100 yards of the front line do that the people in the rear medical unit really don't is you kill and you kill a lot right you don't just oh there's a sniper back here so i shot him it's we go from one position to another and we kill lots of people those things will change you and what that tends to do not universally because i've read accounts from uh red army soldiers and they're very patriotic right but a lot of that patriotism comes through years later as part of the nostalgia and the remembering when you're down at that front 100 yards it is often boiled down to a very small world so your grandfather was it your grandfather grandfather at the machine gun he's concerned about his position and his comrades and the people who he owes a responsibility to and those it's a very small world at that point and to me that's where the heroism is right he's not fighting for some giant world civilizational thing he's fighting to save the people next to him and his own life at the same time because they're saving him too and and that there is a huge amount of heroism to that and that gets to our question about force earlier why would you use force well how about to protect these people on either side of me right their lives um now is there hatred yeah i hated the germans for what they were doing as a matter of fact i uh i got a note from a poll not that long ago and i have this tendency to refer to the nazis right the regime that was and he said why do you keep calling them nazis he says say say what they were they were germans and this guy wanted me to not absolve germany by saying oh it was this awful group of people that took over your country he said the germans did this and there's that bitterness where he says let's not forget you know what they did to us and why and what we had to do back right um so for me when we talk about these combat situations the reason i call these people heroic is because of they're fighting to defend things we could all understand i mean if you come after my brother and i take a machine gun and shoot you and you're going to overrun me i mean you're gonna though that becomes a situation where we talked about counter force earlier um much easier to call yourself a hero when you're saving people or you're saving this town right behind you and you know if they get through your machine gun they're gonna burn these villages they're going to throw these people out in the middle of winter these families that to me is a very different sort of heroism than this amorphous idea of patriotism you know patriotism is a thing that we often get um used with right people people manipulate us through love of country and all this because they understand that this is something we feel very strongly but they use it against us sometimes in order to whip up a war fever or to get people i mean there's a great line and i wish i could remember it in its entirety that herman goering had said about how easy it was to get the people into a war he says you know you just appeal to their patriotism i mean there's buttons that you can push and they take advantage of things like love of country and the way we um the way we have a loyalty and admiration to the warriors who put their lives on the line these are manipulatable things in the human species that reliably can be counted on to move us in directions that in a more um sober reflective state of mind we would consider differently it gets the i mean you get this war fever up and people people wave flags and they start denouncing the enemy and they start signing you know we've seen it over and over and over again in ancient times this happened but the love of country is also beautiful so i haven't seen it in america as much so people in america love their country like this patriotism is strong in america but it's not as strong as i remember even with my sort of being younger the love of the soviet union now was it the soviet union this requires a distinction or was it mother russia what it really was was the communist party okay so it was this it was the system in place okay the system in place like loving i haven't quite deeply psychologized exactly what you love i think you love the that like populist message of the worker of the common man that's common so let me let me draw the comparison then um and i often say this that that the united states like the soviet union is an ideological based society right so you take a country like france it doesn't matter which french government you're in now the french have been the french for a long time right uh it's it's not based on an ideology right whereas what unites the united states is an ideology freedom liberty the constitution this is what draws you know it's the e pluribus unum kind of the idea right this that out of many one well what what binds all these unique different people these shared beliefs this ideology the soviet union was the same way because as you know the soviet union russia was merely one part of the soviet union and if you believe the rhetoric until stalin's time everybody was going to be united under this ideological banner someday right it was a global revolution um so ideological societies are different and to be a fan of the ideological framework and goal i mean i'm a liberty person right i would like to see everybody in the world have my system of government which is part of a of a bias right because they might not want that but i think it's better for everyone because i think it's better for me at the same time when the ideology if you consider and you know this stems from ideas of the enlightenment and there's a bias there so my bias are toward the but you feel and this is why you say we're going to bring freedom to iraq we're going to bring freedom to here we're going to bring freedom because we think we're spreading to you something that is just undeniably positive we're going to free you and give you this um it's hard for me to to wipe my own bias away from there right because if i were in iraq for example i would want freedom right but if you then leave and let the iraqis vote for whomever they want are they going to vote for somebody that will i mean you know you look at russia now and i hear from russians quite a bit because so much of my um my views on russia and the soviet union were formed in my formative years and and you know we were not hearing from many people in the soviet union back then but now you do you hear from russians today who will say your views on stalin are archaic and cold you know so so you try to reorient your beliefs a little bit but it goes to this idea of if you gave the people in russia a free and fair vote will they vote for somebody who promises them a free and open society based on enlightenment democratic principles or will they vote for somebody we in the u.s would go what are they doing they're voting for some strong man who's just good you know so um i think it's very hard to throw away our own uh biases and and preconceptions and and you know it's an all eye of the beholder kind of thing but when you're talking about ideological societies it is very diff difficult to throw off all the years of indoctrination into the superiority of your system i mean listen in the soviet union marxism one way or another was part of every classroom's you know you could be studying geometry and they'll throw marxism in there somehow because that's what united the society and that's what gave it a higher purpose and that's what made it in the minds of the people who were its defenders a superior morally superior system and we do the same thing here in fact most people do but see you're still french no matter what what the ideology or the government might be so so in that sense it's funny that there would be a cold war with these two systems because they're both ideologically based systems involving peoples of many different backgrounds who are united under the umbrella of the ideology first of all that's brilliantly put i'm in a funny position that um in my formative years i came here when i was 13 is when i you know teenage is your first love or whatever as i fall in love i fell in love with the american set of ideas of freedom and individuals but i also remember it's like you remember like maybe an ex-girlfriend or something like that i also remember loving as a very different human the the soviet idea like we had the national anthem which is still the i think the most badass national anthem which is the soviet union like saying we're the indestructible nation i mean just the words are so like americans words are like oh we're nice like we're freedom but like a russian soviet union national anthem was like we're bad motherfuckers nobody will destroy us uh i just remember feeling pride in a nation as a kid like dumb not knowing anything because we all had to recite the stuff it was um there's a uniformity to everything there's pride underlying everything i didn't think about all the destructive nature of the bureaucracy the incompetence the of you know all the things that come with the implementation of communism especially around the 80s and 90s but i i remember what it's like to love that set of ideas so i'm in a funny place of like remember like switching the love because i'm you know i kind of joke around about being russian but you know my my long-term monogamous relationship is not with the idea the american ideal like i'm stuck with it in my mind but i remember what it was like to love it and i and i i think about that too when people criticize china or they criticize the current state of affairs with how stalin is remembered and how putin is to know that the you can't always wear the american ideal of individualism radical individualism and freedom in analyzing the ways of the world elsewhere like in china in russia that it does if you don't take yourself too seriously as americans all do as i do it's it's kind of a beautiful love to have for your government to believe in the nation to let go of yourself and your rights and your freedoms to believe in something bigger than yourself that's actually uh that's a kind of freedom that's you're actually liberating yourself if you think like life is suffering you're you're giving into the flow of the water the flow the way of the world by giving away more power from yourself and giving it to what you would conceive as as the power of the people together together we'll do great things and really believing in the ideals of um what in that in this case i don't even know what you would call russia but whatever the heck that is authoritarian powerful state powerful leader believing that can be uh as beautiful as believing the american ideal not just that let me add to what you're saying i'm very i spend a lot of time trying to get out of my own biases uh it is it is a fruitless endeavor long term but you try to be better than you normally are one of the critiques that china and i always you know as an american i tend to think about this as their government right this is a rationale that their government puts forward but what you just said you know is actually if you can make that viewpoint beautiful is kind of a beautiful way of approaching it the chinese would say that what we call human rights in the united states and what we consider to be everybody's birthright around the world is instead western rights that's the words they use western rights it's a it's a fundamentally western oriented and i'll go back to the enlightenment enlightenment based ideas um on what constitutes the rights of man and they would suggest that that's not internationally and always applicable right that you can make a case and again i don't believe this this runs against my own personal views but that you could make a case that the collective well-being of a very large group of people outweighs the individual needs of any single person especially if those things are in conflict with each other right if you cannot provide for the greater good because everyone's so individualistic well then really what is the better thing to do right to suppress individualism so everybody's better off um i think trying to recognize how someone else might see that is important if we want to you know you had talked about eliminating war we talk about eliminating conflict uh the first need to do that is to try to understand how someone else might view something differently than yourself um i'm famously one of those people who buys in to the ideas of of traditional americanism right and look what a lot of people who who live today i mean they would seem to think that things like um patriotism requires a belief in the strong military and all these things we have today but that is a corruption of traditional americanism which viewed all those things with suspicion in the first hundred years of the republic because they saw it as an enemy to the very things that americans celebrated right how could you have freedom and liberty and individualistic um expression if you had an overriding military that was always fighting wars and and the founders of this country looked to other examples like europe for example and saw that standing militaries for example standing armies were the enemy of liberty well we have a standing army now um and and one that is totally interwoven in our entire society if you could if you could go back in time and talk to john quincy adams right early president of the united states and show him what we have now he would think it was awful and horrible and somewhere along the line the americans had lost their way and forgotten what they were all about but we have so successfully interwoven this modern uh military industrial complex with the the traditional uh benefits of the american system and ideology so that they've become intertwined in our thinking whereas 150 years ago they were actually considered to be at opposite polarities and a threat to one another um so when you talk about the love of the nation i tend to be suspicious of those things i tend to be suspicious of government i tend to tend to try very hard to not be manipulated and i feel like a large part of what they do is manipulation and propaganda and so um i think a healthy skepticism of the nation state is actually 100 americanism in the traditional sense of the word but i also have to recognize as you so eloquently stated americanism is not necessarily universal at all and so i think we have to try to be more understanding see our the the traditional american viewpoint is that if a place like china does not allow their people individual human rights then they're being denied something they're being denied and 100 years ago they would have said they're god given rights man is born free and if he's not free it's because of something done to him right the government has taken away his god-given rights i'm getting excited just listening to that well but i mean but i mean i think i think the idea that this is universal is in and of itself a bias now do i want freedom for everybody else i sure do but the people in the soviet union who really bought into that wanted the workers of the world to unite and not be exploited by you know the the greedy blood-sucking people who worked them to death and pocketed all of the fruits of their labor if you frame it that way that sounds like justice as well you know so it is an eye of the beholder sort of thing i'd love to talk to you about vladimir putin sort of while we're on this feeling and wave of empathy and trying to understand others that are not like us one of the reasons i started this podcast is because i believe that there's a few people i could talk to some of it is ego some of it stupidity is there some people i could talk to that not many others can talk to the one person i was always thinking about was vladimir putin do you still speak the language i speak the language very well that makes it even easier i mean you might be you might be appointed for that job that's the context in which i'm asking you this question what are your thoughts about vladimir putin from historical context have you studied him have you thought about him yes uh studied as a is a loaded word um here's here's and again i i find it hard sometimes to not filter things through an american lens so as an american i would say that the russians should be allowed to have any leader that they want to have but what an american would say is but there should be elections right so if the russians choose vladimir putin and they keep choosing him that's their business where where as an american i would have a problem is when that leader stops letting the russians make that decision and we would say well now you're no longer ruling by the consent of the governed you've become the equivalent of a person who may be oppressing your people you might as well be a dictator right now there's a difference between a freely elected and re-elected and re-elected and re-elected dictator right if that's what they want and and look i i it would be silly to broad brush the russians like it would be silly to broad-brush anyone right millions and millions of people with different opinions amongst them all but they seem to like a strong person at the helm and listen there's a giant chunk of americans who do too um in their own country but an american would say as long as the freedom of choice is is given to the russians to decide this and not taken away from them right it's one thing to say he was freely elected but a long time ago and we've done away with elections since then is is a different story too so my attitude on on vladimir putin is if that's who the russian people want and you give them the choice right if he's only there because they keep electing him that's a very different story when he stops offering them the option of choosing him or not choosing him that's when it begins to look nefarious to someone born and raised with the mindset and the ideology that is an integral part of of yours truly and that i can't you know you can see gray areas and nuance all you like but it's hard to escape as you wish and you you alluded to this too it's hard to escape what was indoctrinated into your bones in your formative years uh it's like exit you know your bones are growing right and you can't go back so to me this is so much a part of who i am that i have a hard time jettisoning that and saying oh no vladimir putin not being elected anymore it's just fine i'm too much of a product of my upbringing to go there does that make sense yeah absolutely but of course there's like what we're saying there's gray areas which is i believe i have to think through this but i think there is a point at which adolf hitler became the popular choice in nazi germany in the 30s there's a in in the same way from an american perspective you can start to criticize some in a shallow way some in a deep way the way that putin has maintained power is by controlling the press so limiting one other freedom that we americans value which is the the freedom of the press or freedom of speech that he it is very possible now things are changing now but for most of his presidency he was the popular choice and sometimes by far and you know i have i actually don't have real family in russia who don't love putin i the only people who write to me about putin and not liking him are like sort of activists who are young right but like to me they're strangers i don't know anything about them the people i do know have a big family in russia they love putin they do they miss elections would they want the choice to prove it at the ballot box and and or or are they so in love with him that they're they wouldn't want to take a chance that someone might vote him out no they don't think of it this way and they are aware of the incredible bureaucracy and corruption that is lurking in the shadows which is true in russia right everywhere everywhere but like there's something about the russian it's a remnants it's corruption is so deeply part of the russians so the soviet system that even the overthrow of the soviet the the the breaking apart of the soviet union and uh putin coming and reforming a lot of the system it's still deeply in there and and they're aware of that that's part of the like the love for putin is partially grounded in the fear of what happens when the corrupt take over the greedy take over and they they see putin as the stabilizer as like a hard like force that says counterforce counterforce like get your shit together like basically from the western perspective putin is is terrible but from from the russian perspective putin is is the only thing holding this thing together before it goes if it collapses now the from the like gary kasparov has been loud on this you know a lot of people from the western perspective say well if it has to collapse let it collapse you know that's easier said than done when you don't have to live through that exactly and so anyone worrying about their family about and they also remember the the inflation and the economic instability and the suffering and the starvation that happened in the 90s with the collapse of the soviet union and they saw the kind of reform and the economic vibrancy that happened when putin took power that they think like this guy's holding it together and they see elections as potentially being mechanisms by which the corrupt people can manipulate the system unfairly as opposed to letting the people speak with their voice they somehow figure out a way to uh manipulate the elections to elect somebody uh like one of them western revolutionaries and so i think one of the beliefs that's important to the american system is the belief in the electoral system that the voice of the people can be heard in the various systems of government whether it's judicial whether it's uh uh i mean basically the assumption is that the system works well enough for you to be able to uh elect the popular choice okay so there's a couple of things that come to mind on that the first one has to do with the idea of oligarchs um there's a belief in political science uh you know it's not the overall belief but but that every society is sort of an oligarchy really if you break it down right so what you're talking about are some of the people who would form an oligarchic class in in in russia and that putin is the guy who can harness uh the power of the state to keep those people in check the problem of course in a system like that a strong man system right where you have somebody who can who can hold the reins and steer the ship when the ship is violently in a storm is the succession so if you're not creating a system that can operate without you then that terrible instability and that terrible future that you that you justified the strong man for is just awaiting your future right i mean unless unless he's actively building the system that will outlive him and allow successors to do what he's doing then then what you've done here is create a temporary i would think a temporary stability here because it's the same problem you have in a monarchy right um where where you have this one king and he's particularly good or you think he's particularly good but he's going to turn that job over to somebody else down the road and the system doesn't guarantee because no one's really worked on and again you would tell me if if putin is putting into place i know he's talked about it over the years putting into place a system that can outlive him and that will create the stability that the people in russia like him for when he's gone because if the oligarchs just take over afterwards then one might argue well we had 20 good years you know of stability but i mean i would say that if we're talking about a ship of state here the guy steering the ship maybe if you want to look at it from the russian point of view has done a great job maybe just saying but the rocks are still out there and he's not going to be at the helm forever so one would think that his job is to make sure that there's going to be someone who can continue to steer the ship for the people of russia after he's gone now let me ask because i'm curious and and ignorant so uh is he doing that do you think is he setting it up so that when there is no putin the state is safe from the beginning that was the idea whether one of the fascinating things now i read every biography english written biography on putin so i haven't i need to think more deeply but one of the fascinating things is how did power change vladimir putin he was a different man when he took power than he is today i actually in many ways admired the man that took power i think is he's very different than stalin and then hitler at the moment they took power i think hitler and stalin were both in our previous discussion already on the trajectory of evil i think putin was a humble loyal honest man when he took power the man he is today is worth thinking about and studying i'm not sure that that that's an old line though about absolute power corrupting absolutely but it's you know it's kind of a line uh you know it's it's a beautiful quote but you have to really think about it you know like what does that actually mean like one of the things i i still have to do you know i've been focusing on securing the conversation right so i i've been i haven't gone through a dark place yet because i feel like i can't do the dark thing for too long so i really have to put myself in the mind of putin leading up to the conversation but for now my senses his he took power when yeltsin gave him one of the big sort of acts of the new russia was for the first time in its history a leader could have continued being in power and chose to give away power that was the george washington right in the united states would look at that as absolute positive yeah a sign a sign of good things yes and so that was a huge act and uh putin said that that that was the defining thing that will define russia for the 21st century that act and he will carry that flag forward that's why in rhetoric he after two terms he gave away power to medvedev yeah but it was a puppet right yeah yes but it was but like still the story was being told i think he believed it early on i think he i believe he still believes it but i think he's deeply suspicious of the corruption that looks in the shadows and i i do believe that like as somebody who thinks clickbait journalism is broken journalists annoy the hell out of me hey journalism's working perfectly journalism's broken journalists made things working great so i understand from putin's perspective that journalism journalists can be seen as the enemy of the state because people think journalists write these deep beautiful philosophical pieces about criticizing the structure of government and the proper policy what you know the steps that we need to take to make a greater nation no they they're unfairly take stuff out of context they uh they're critical in ways that's like shallow and not interesting they they call you a racist or sexist or they make up stuff all the time so i can put myself in the mindset of a person that thinks that it is okay to remove that kind of shallow uh fake news voice from the system the problem is of course that is a slippery slope to then you remove all the annoying people from the system and then you change what annoying means which annoying starts becoming a thing that like anyone who opposes the the system i mean i get i get the um the slippery it's obvious it becomes a slippery slope but i can also put myself in the mindset of the people that see it's okay to remove the liars from the system as long as it's good for russia and okay so here in lies and this again the traditional american perspective because we've had yellow so-called yellow journalism since the founding of the republic that's nothing new um but but the problem then comes into play when you remove journalists even you know it's a broad brush thing because but you remove both the the crappy ones who are lying and the ones who are telling the truth too you're left with simply the the approved government journalists right the ones who are toeing the government's line in which case the truth as you see it is a different kind of fake news right it's the fake news from the government instead of the click bait news and oh yeah maybe truth mixed into all that too in some of the outlets the problem i always have with our system here in the united states right now is trying to tease the truth out from all the falsehoods and look i've got 30 years in journalism my job used to be to go through before the internet all the newspapers and and find the i used to know all the journalists by name and i could pick out you know who they were and and and i have a hard time picking out the truth from the falsehood so i think constantly how are people who don't have all this background who have lives or who are trained in other specialties how do they do it but if the government is the only approved outlet for truth a traditional american and a lot of other traditional societies based on these ideas of the enlightenment that i talked about earlier would see that as a disaster waiting to happen or a tyranny in progress does that make sense it totally makes sense and i would agree with you i still agree with you but it is clear that something about the freedom of the press and freedom of speech in today like literally the last few years with the internet is changing and the argument you know you could say that the american system of freedom of speech is is broken because the here's here's the belief i grew up on and i still hold but i'm starting to be sort of trying to see multiple views on it my belief was that freedom of speech results in a stable trajectory towards truth always so like truth will emerge that was my sort of faith and belief that that yeah there's going to be lies all over the place but there will be like a stable thing that is true that's carried forward to the public now it feels like it's possible to go towards a world where nothing is true or truth is is something that groups of people convince themselves of and there's multiple groups of people and the idea of some universal truth as i suppose is the better thing is uh is something that we can no longer exist under like some people believe that the green bay packers is the best uh football team and some people can think the patriots and they deeply believe it to where they call the other groups liars now that's fun for sports that's fun for favorite flavors of ice cream but they might believe that about science about uh various aspects of uh politics various aspects of sort of uh different policies within the function of our government and like that's not just like some weird thing we complain about but that'll be the nature of things like truth is something we could no longer have well let's and let me de-romanticize the american history of this too because the american press was often just as biased just as i mean i always looked to the 1970s as the high water mark of the american journalistic in the post-watergate era where it was actively going after um the abuses of the government and all these things but there was a famous speech very quiet though very quiet given by catherine graham who was a washington post editor i believe and uh i actually somebody sent it to me we had to get it off of a journalism like a jstor kind of thing and she at a at a luncheon um assured that the to the government people at the luncheon don't worry this is not going to be something that we make a trend we're not because the position of the government is still something that was carried you know the the newspapers were the water and the newspapers were the big thing up until certainly the late 60s early 70s the newspapers were still the water carrier of the government right and they were the water carriers of the owners of the newspaper so let's not pretend there was some angelic wonderful time and i'm saying to me because i was the one who brought it up let's not pretend there was any super age of truthful journalism and all that and i mean you go to the revolutionary period in american history and it looks every bit as bad as today right um that's a hopeful message actually so things may not be as bad as they look well let's look at it more like a stock market and that you have fluctuations in the truthfulness or or believability of the press and there are periods where it was higher than other periods the funny thing about the so-called click-bait era and i do think it's terrible but i mean it resembles earlier eras to me so i always compare it to when i was a kid growing up when i thought journalism was as good as it's ever gotten it was never perfect um but it's also something that you see very rarely in in other governments around the world and there's a reason that journalists are often killed uh regularly in a lot of countries and it's because they report on things that the authorities do not want reported on and i've always thought that that was what journalism should do but it's got to be truthful otherwise it's just a different kind of propaganda right can we talk about genghis khan genghis khan sure by the way is it genghis khan or genghis khan it's not genghis khan it's either genghis khan or chingas khan so let's go with the genghis khan the only thing i'll be able to say with any certain last certain thing i'll say about it uh it's like i don't know gif versus jif i don't know how i don't know how it ever got started the wrong way yeah so first of all your episodes on uh genghis khan for many people are the favorite it's fascinating to think about events that had so much like in their ripples had so much impact on so much of human civilization in your view was he an evil man this goes to our discussion of evil another way to put it is i've read he's much loved in much part in many parts of the world like mongolia and i've also read arguments that say that he was quite a progressive for the time so where do you put him is he a progressive or is he an evil destroyer of humans as i often say i'm not a historian which is why what i try to bring to the hardcore history podcasts are these sub themes so each show has and they're not i try to kind of soft pedal them so they're not always like really right in front of your face um in that episode the soft pedaling sub theme had to do with what we uh referred to as a historical arsonist and it's because some historians have taken the position that sometimes and and most of this is earlier so historians don't do this very much anymore but these were the wonderful questions i grew up with that blend it's almost the intersection between history and philosophy and the idea was that sometimes the world has become so overwhelmed with bureaucracy or corruption or just stagnation that somebody has to come in or some group of people or some force has to come in and do the equivalent of a forest fire to clear out all the dead wood so that the forest itself can be rejuvenated and and society can then move forward and there's a lot of these periods where the historians of the past will portray these figures who come in and do horrific things as creating an almost service for for mankind right uh creating the foundations for a new world that will be better than the old one and it's a recurring theme and so this was the sub theme of the of the cons podcast because otherwise you don't need me to tell you the story of the mongols but i'm going to bring up the historical arsonist element um and but this gets to how the khan has been portrayed right if you want to say oh yes he cleared out the dead wood and made for a for well then it's a positive thing if you say my family was in the forest fire that he set it you're not going to see it that way um much of what genghis khan is credited with on the upside right so things like religious toleration and you'll say well he was uh religiously the mongols were religious uh religiously tolerant and so this makes them almost like a liberal reformer kind of thing but this needs to be seen within the context of of their empire which was uh very much like the roman viewpoint which is the romans didn't care a lot of time what your local people worshipped they wanted stability and if that kept stability and kept you paying taxes and didn't require the legionaries to come in and and then they didn't care right and and the cons were the same way like they don't care what you're practicing as long as it doesn't disrupt their empire and cause them trouble but what i always like to point out is yes but the khan could still come in with his representatives to your town decide your daughter was a beautiful woman that they wanted in the khan's concubine and they would take them so how liberal an empire is this right so so many of the things that they get credit for as though there's some kind of nice guys may in another way of looking at it just be a simple mechanism of control right a way to keep the empire stable they're not doing it out of the goodness of their heart they have decided that this is the best and i love because the mongols were what we would call a pagan people now i love the fact that they and i think we call it i forgot the term we used it had to do with like they were hedging their bets religiously right they didn't know which god was the right one so as long as you're all praying for the health of the khan we're maximizing the chances that whoever the gods are they get the message right um so i think it's been portrayed as something like a liberal empire and it the idea of mongol universality universality is it's more about conquering the world and it's like saying you know we're going to bring stability to the world by conquering it well what if that's hitler right he could make the same case or hitler wasn't really the world conqueror like that because he wouldn't have been he wouldn't have been trying to make it equal for all peoples but my point being that it kind of takes the positive moral slant out of it if their motivation wasn't a positive moral slant to the motivation and and the mongols didn't see it that way and and i think the way that it's portrayed is like and i always like to use this this this analogy but it's like um shooting an arrow and painting a bullseye around it afterwards right how how do we how do we justify and make them look good in a way that they themselves probably and unless we don't have the mongol point of view per se i mean there's something called the secret history of the mongols and there's things written down by mongolian overlords through people like persian and chinese scribes later we don't have their point of view but it sure doesn't look like this was an attempt to create some wonderful place where everybody was living a better life than they were before i i think that's that's later people uh putting a nice rosy spin on it so but there's an aspect to it maybe you can correct me because i'm projecting sort of my idea of what it would take to to uh to conquer so much land is uh the ideology is emergent so if i were to guess the mongols started out as exceptionally as warriors who valued excellence in skill of killing not even killing but like the the actual practice of war and it can start out small you can grow and grow and grow and then in order to maintain the stability of the things over which of the conquered lands you developed a set of ideas with which you can like you said establish control but it was emergent and it seems like the core first principle idea of the mongols is just to be excellent warriors that felt that felt to me like the starting point it wasn't some ideology like with hitler and stalin with hitler the there was an ideology that didn't have anything to do with with war underneath it it was more about conquering it feels like the mongols started out more organically i would say it's emerg like this phenomenon started emergently and they were just like similar to the native americans with the comanches like the different warrior tribes that joe rogan's currently obsessed with at the that what led me to look into it more they they seem to just start out just valuing the skill of fighting whatever the tools of war they had which were pretty primitive but just to be the best warriors they could possibly be make a science out of it is that is that crazy to think that there was no ideology behind it in the beginning i'm gonna back up a second i'm reminded of the lines said about the romans that they create a wasteland and call it peace that is wow that but but but there's a lot of conquerors like that right um where where uh you you will sit there and listen historians forever have it's it's the trait it's the famous trade-offs of empire and they'll say well look at the trade that they facilitated and look at you know the religion all those kinds of things but they come at the cost of all those peoples that they conquered forcibly and and and by force integrated into their empire the one thing we need to remember about the mongols that makes them different than say the romans and this is complex stuff and way above my pay grade but i'm fascinated with it and it's more like the comanches that you just brought up is that the mongols are not a settled society okay they are they are they come from a nomadic tradition now several generations later when you have a kubila khan as as the as the emperor of china it's it's beginning to be a different thing right and the mongols when their empire broke up the ones that were uh in settle the so-called settled societies right iran places like that they will become more like over time the rulers of those places were traditionally and the mongols and say like the the cognate of the golden horde which is still in in their traditional nomadic territories will remain traditionally more mongol but when you start talking about who the mongols were i try to to make a distinction they're not some really super special people they're just the latest confederacy in an area that saw nomadic confederacies going back to the beginning of recorded history the scythians the sarmatians the avars the huns the magyars i mean these are all the nomadic you know the nomads of the eurasian steppe were huge huge players in the history of the world until gunpowder nullified their their traditional weapon system which i've been fascinated with because their traditional weapon system is not one you could copy because you were talking about being the greatest warriors you could be every warrior society i've ever seen values that what this what the nomads had of the eurasian step was this relationship between human beings and animals that changed the equation it was how they rode horses and societies like the byzantines which would form one flank of the step and then all the way on the other side you had china and below that you had persia these societies would all attempt to create mounted horsemen who used archery and they did a good job but they were never the equals of the nomads because those people were literally raised in the saddle they compared them to centaurs the comanches great example considered to be the best horse riding warriors in north america the comanches i always loved watching there's paintings george catlin the famous uh um uh painter who painted the comanches uh illustrated it but the mongols and the scythians and scythians and the avars and all these people did it too where they would shoot from underneath the horse's neck hiding behind the horse the whole way you look at a picture of somebody doing that and it's insane this is what the byzantines couldn't do and the chinese couldn't do it was a different level of of harnessing a human animal relationship that gave them a military advantage that could not be copied right it could be emulated but they were never as good right that's why they always hired these people they hired mercenaries from these areas because they were incomparable right so the combination of people who were shooting bows and arrows from the time they were toddlers who were riding from the time they were who rode all the time i mean they were the huns were bow-legged the romans said because they were never out they ate slapped everything in the saddle that creates something that is difficult to copy and it gave them a military advantage uh you know i enjoy reading actually about uh when that military advantage ended so 17th and 18th century when the chinese on one flank and the russians on the other are beginning to use firearms and stuff to break this military power of these of these various cons um the mongols were simply the most dominating and most successful of the confederacies but if you break it down they really formed the nucleus at the top of the pyramid of the apex of the food chain and a lot of the people that were known as mongols were really lots of other tribes non-mongolian tribes that when the mongols conquer you after they killed a lot of you they incorporated you into their confederacy and often made you go first you know you're going to fight somebody we're going to make these people go out in front and suck up all the arrows before we go in and finish the job so to me and i guess a fan of the mongols would say that the difference and what made the mongols different wasn't the weapon system or the fighting or the warriors or the armor or anything it was genghis khan and if you go look at the other really dangerous from the outside world's perspective dangerous step nomadic confederacies from past history was always when some great leader emerged that could unite the tribes and you see the same thing in native american history two degree two um you had people like attila right or uh there was one called twomin you go back in history and these people make the history books because they caused an enormous amount of trouble for their settled neighbors that normally i mean chinese byzantine and persian approaches to the steppe people were always the same they would pick out tribes to be friendly with they would give them money gifts hire them and they would use them against the other tribes and generally byzantine especially in chinese diplomatic history was all about keeping these tribes separated don't let them form confederations of large numbers of them because then they're unstoppable attila was a perfect example the huns were another large the turks another large confederacy of these people and they were devastating when they could unite so the diplomatic policy was don't let them that's what made the mongols different is genghis khan united them and then unlike most of the tribal confederacies he was able they were able to hold it together for a few generations to linger on the little thread they started pulling on this man genghis khan that was a leader yeah what do you think makes a great leader maybe if you have other examples throughout history and great again let's lose that use that term loosely now he's gonna ask for a definition great uniter of whether it's evil or good it doesn't matter is there somebody who stands out to you alexander the grace talking about military or ideologies you know some people bring up fdr or or i mean it could be the founding fathers of this country or we can go to uh was he mana uh man of the century up there hitler of uh the 20th century and stalin and these people had really uh amassed the amount of power that probably has never been seen in the history of the world is there somebody who stands out to you by way of uh trying to define what makes a great uniter great leader in one man or a woman maybe in the future it's an interesting question and one i've thought a lot about because let's take alexander the great as an example because alexander fascinated the world of his time fascinated ever since people have been fascinated with the guy but alexander was a hereditary monarch right yeah he he was handed the kingdom which is fascinating right but he did not need to rise from nothing to get that job in fact he reminds me of a lot of other leaders of frederick the great for example in prussia these are people who inherited the greatest army of their day alexander unless he was in imbecile was going to be great no matter what because i mean if you inherit the wehrmacht you're going to be able to do something with it right alexander's father may have been greater philip uh he philip ii was the guy who who literally did create a a strong kingdom from a disjointed group of people that were continually beset by their neighbors he's the one that reformed that army uh took things that he had learned from other uh greek leaders like the theban leader at pemanandes um and and then laboriously over his lifetime stabilized the frontiers built this system he lost an eye doing it he he he his leg was made lame i mean he this was a man who looked like he built the empire and led from from the front ranks i mean um so and then and then who may have been killed by his son we don't know who assassinated philip um but then handed the greatest army the world had ever seen to his son who then did great things with it you see this this pattern many times so in my mind i'm not sure alexander really can be that great when you compare him to people who arose from nothing so the difference between what we would call in the united states the self-made man or the one who inherits a fortune there's an old line that you know it's a slur but uh it's about rich people and it's like he was born on he was born on third base and thought he hit a triple right um philip was born at home plate and he had to hit alexander started on third base and so i try to draw a distinction between them genghis khan is tough because there's two traditions the tradition that we grew up with here in the united states and that i grew up learning was that he was a self-made man but there is a tradition and it may be one of those things that's put after the fact because a lot a long time ago whether or not you had blue blood in your veins was an important distinction and so the distinction that you'll often hear from mongolian history uh is that this was a a nobleman who had been deprived of his inheritance so he was a blue blood anyway i don't know which is true uh there's certainly i mean when you look at a genghis khan though you have to go that is a wicked amount of things to have achieved uh he's very impressive as a figure attila is very impressive as a figure um hitler's an interesting figure he's one of those people cuz you know the more you study about hitler the more you wonder where the defining moment was because um if you look at his life i mean hitler was a relatively common soldier in the first world war i mean he was brave he got uh he got some decorations in fact the highest decoration he got in the first world war was given to him by a jewish officer and it was uh he often didn't talk about that decoration even though it was the more prestigious one because it would open up a whole can of worms you didn't want to get into but hitler's i mean if you said who was hitler today one of the top things you're going to say is he was an anti-semite well then you have to draw a distinction between general regular anti-semi-semitism that was pretty common in the era and something that was a rabid level of anti-semitism but hitler didn't seem to show a rabid level of anti-semitism until after or at the very end of the first world war so if this is a defining part of this person's character and and much of what we consider to be his his evil stems from that what happened to this guy when he's an adult right he's already fought in the war to change him so i mean it's almost like the old there was always a movie theme somebody gets hit by by something on the head and their whole personality changes right i mean it almost seems something like that so i don't think i call that necessarily a great leader to me the interesting thing about hitler is what the hell happened to a non-descript person who didn't really impress anybody with his skills and then in in the 1920s it's all of a sudden as you said sort of the man of the hour right so that to me is kind of fast i have this feeling that genghis khan and we don't really know was an impressive human being from the get-go and then he was raised in this environment with pressure on all sides so you start with this diamond and then you polish it and you harden it his whole life hitler seems to be a very unimpressive gemstone most of his life and then all of a sudden so i mean i don't think i can label great leaders and i'm always fascinated by that idea that and i'm trying to remember who the quote was by that that great men oh lord acton so great men are often not good men uh and that in order to be great you would have to jettison many of the moral qualities that we normally would consider a jesus or a gandhi or you know these these qualities that one looks at as as the good upstanding moral qualities that we should all aspire to as examples right the buddha whatever it might be um those people wouldn't make good leaders because what you need to be a good leader often requires the kind of choices that a true philosophical diogenes moral man wouldn't make yeah um so i don't have an answer to your question how about that that's a very long way of saying i don't know just linger a little bit it does feel like from my study of hitler that the time molded the man versus genghis khan where it feels like he the man molded his time yes and i feel that way about a lot of those nomadic uh confederacy builders that they really seem to be these figures that that stand out as extraordinary for one in one way or another remembering by the way that almost all the history of them were written by the enemies that they so mistreated that they were probably never going to get any good press they didn't write themselves that's a caveat we should always yeah basically nomadic or native american peoples or tribal peoples anywhere generally do not get the advantage of being able to write the history of their heroes okay i've uh i've recently almost done with the rise in the fall of the third reich it's one of the historical descriptions of hitler's rise to power nazis rise to power there's a few philosophical things i'd like to uh ask you to see if you can help like one of the things i think about is how does one be a hero in 1930s nazi germany what does it mean to be a hero what do heroic actions look like i think about that because i think about how i move about in this world today you know that we live in really chaotic intense times where i don't think you want to draw any parallels between nazi germany and modern day in any of the nations we can think about but it's not out of the realm of possibility that authoritarian governments take hold authoritarian companies take hold and i'd like to think that i could be in my little small way and inspire others to take the heroic action before things get bad and i kind of try to place myself in what would 1930s germany look like is it possible to stop a hitler is it even the right way to think about it and how does one be a hero in it i mean you often talk about that living through a moment in history is very different than looking at that history looking you know when you look back i also think about it would it be possible to understand what's happening that the bells of war are are are ringing uh it seems that most people didn't seem to understand on you know late into the 30s that war is coming that's fascinating on the united states side inside germany like the opposing figures the german military didn't seem to understand this maybe off the other country certainly france and england didn't seem to understand this that kind of tried to put myself into 90s 30s germany as i'm jewish which is another little twist on the whole like what would i do what should one do do do you have interesting answers so earlier we had talked about putin and we had talked about patriotism and love of country and those sorts of things in order to be a hero in nazi germany by our views here you would have had to have been anti-patriotic to the average germans viewpoint in the 1930s right you would have to have opposed your own government and your own country and that's a very it would be a very weird thing to go to people in germany and say listen the only way you're going to be seen as as a good german and a hero to the country that will be your you know enemies is we think you should oppose your own government it's it's a strange position to put the people in a government in saying you need to be against your leader you need to oppose your government's policies you need to oppose your government you need to hope and work for its downfall that doesn't sound patriotic it wouldn't sound patriotic here in this country if you if you made a similar argument i will go away from the 1930s and go to the 1940s to answer your questions there's movements like the white rose movement in germany which involved young people really and from various backgrounds religious backgrounds often who worked openly against the nazi government at a time when power was already consolidated the gestapo was in full force and they execute people who are against the government and these young people would go out and distribute pamphlets and many of them got their heads cut off with guillotines for their trouble and they knew that that was going to be the penalty that is a remarkable amount of bravery and sacrifice and willingness to die and almost not even willingness because they were so open about it it's almost a certainty right um that's incredibly moving to me so when we talk and we had talked earlier about sort of the human spirit and all that kind of thing there are people in the german military who opposed and worked against hitler for example but to me that's almost cowardly compared to what these young people did in the white rose movement because those people in the in the vermont for example who were secretly trying to undermine hitler they're they're not really putting their lives on the line to the same degree um and so i i think when i look at heroes and listen i remember once saying there were no conscientious objectors in in germany as a way to point out to people that you didn't have a choice you know you were going to serve in there and i got letters from jehovah's witnesses who said yes there were and we got sent to the concentration camps those are remarkably brave things it's one thing to have your own um set of of standards and values it's another thing to say oh no i'm going to display them in a way that with this regime that's a death sentence and not just for me for my family right in these regimes there was not a lot of distinction made between father and son and wives that's a remarkable sacrifice to make and and far beyond what i think i would even be capable of and so the admiration comes from seeing people who appear to be more morally profound than you are yourself um so when i look at this i look at that that kind of thing and i just say wow and the funny thing is if you'd have gone to most average germans on the street in 1942 and said what do you think of these people they're going to think of them as traders who probably got what they deserved so that's the eye of the beholder thing it's the power of the state to um to so propagandize values and morality in a way that favors the state uh that you can turn people who today we look at as unbelievably brave and moral and crusading for righteousness and turn them into enemies of the people um so i mean in my mind it would be people like that see i i think so hero is a funny word and we romanticize the notion but if i could drag you back to 1930s germany from 1940s sure i feel like the heroic actions that doesn't accomplish much is not what i'm referring to so there's many heroes i look up to that uh like david goggins for example the the guy who runs crazy distances he runs for no purpose except for the suffering in itself and i think his willingness to challenge the limits of his mind is uh is heroic i guess i'm looking for a different term which is how could hitler have been stopped my sense is that he could have been stopped in the battle of ideas where or people millions of people were suffering economically or suffering because of the betrayal of world war one in terms of the love of country and how they felt they were being treated and a charismatic leader that inspired love and unity that's not destructive could have emerged and that's where the battle should have been fought i would suggest that we need to take into account the context of the times that led to hitler's rise of power and and and created the conditions where his message resonated uh that is not a message that resonates at all times right um it is impossible to understand the the rise of hitler without dealing with the first world war and the aftermath of the first world war and the inflationary terrible depression in germany and all these things and the um dissatisfaction with the weimar republic's government which was often seen as uh as uh something put into which it was put into place by the the victorious powers uh hitler referred to the people that signed those agreements uh that that signed the armistice as the november criminals and he used that as a phrase which resonated with the population this was a population that was embittered and even if they weren't embittered the times were so terrible and the options for operating within the system in a non-radical way seemed totally discredited right you could work through the weimar republic but they tried and it wasn't working anyway and then the alternative to the nazis who were bully boys in the street were communist agitators that to the average conservative germans seem no better so you have three options if you're an average german person you can go with the discredited government put in power by your enemies that wasn't working anyway you could go with the nazis who seemed like a bunch of super patriots calling for uh the restoration of german authority or you could go with the communists and the entire thing seemed like a litany of poor options right and in this realm hitler was able to triangulate if you will um he came off as a person who was going to restore german greatness at a time when this was a powerful message but if you don't need german greatness restored it doesn't resonate right um so the reason that your love idea and all this stuff i don't think would have worked in the time period is because that was not a commodity that the average german was in search of then well it's interesting to think about whether greatness can be restored through mechanisms through ideas that are not so from our perspective today so evil i don't know what the right term is but the war continued in a way so remember that that when germany when hitler is rising to power the french are in control of parts of germany right the ruhr uh one of the main industrial heartlands of germany was occupied by the french so there's never this point where you're allowed to let the hate dissipate right every time maybe things were calming down something else would happen to stick the knife in and twist it a little bit more from the average german's perspective right um the reparations right so if you say okay well we're going to get back on our feet the reparations were crushing these things prevented the idea of love or brotherhood and all these things from taking hold and even if there were germans who felt that way and there most certainly were it is hard to overcome the power of everyone else you know what i always say when people talk to me about humanity is i believe on individual levels we're capable of everything and anything good bad or indifferent but collectively it's different right and in the time period that we're talking about here messages of peace on earth and love your enemies and and and and all these sorts of things were absolutely deluged and overwhelmed and drowned out by the bitterness the hatred and let's be honest the sense that you were continually being abused by your former enemies there were a lot of people in the allied side that realized this and said we're setting up the next war this is i mean they understood that you can only do certain things to collective human populations for a certain period of time before it is natural for them to want to and there are you can see german posters from the region nazi propaganda posters that show them breaking off the chains of their enemies and i mean germany awake right that was the the great um slogan so i think love is always a difficult option and in the context of those times it it was even more disempowered than normal well this goes to the just to linger in it for a little longer the question of the innova inevitability of history do you think hitler could have been stopped do you think this kind of force that you're saying that there was a pain and was building there's a hatred that was building do you think there was a way to avert i mean there's two questions could have been a lot worse and could have been better in in the trajectory of history in the 30s and 40s the most logical see we had started this conversation brings a wonderful bow tie into the discussion and and and buttons it up nicely we had talked about force encounter force earlier uh the most uh obvious and much discussed way that hitler could have been stopped has nothing to do with germans um when he uh re-militarized the rhineland everyone talks about what a couple of french divisions would have done had they simply gone in and contested and this was something hitler was extremely i mean it might have been the most nervous time in his entire career because he was afraid that they would have responded with force and he was in no position to do anything about it if they did so this is where you get the people who say um you know i mean and churchill's one of these people too where they talk about uh that you know he should have been stopped militarily right at the very beginning when he was weak i don't think listen there were candidates in the in the in the catholic center party and others in in the weimar republic that maybe could have done things and it's beyond my understanding of specific german history to talk about it intelligently but i do think that had the french responded militarily to hitler's initial moves into that area that he would have been thwarted and i think he himself believed if i'm remembering my reading um that this would have led to his downfall so the potential see i i what i don't like about this is that it almost legitimizes military intervention at a very early stage to prevent worse things from happening but it might be a pretty clear-cut case but but it should also be pointed out that there was a lot of sympathy on the part of the allies for the fact that you know the germans probably should have germany back and this is traditional german land i mean they were trying in a funny way it's almost like the love and the sense of justice on the allies part may have actually stayed their hand in a way that would have prevented much much much worse things later but if the times were such that the message of a hitler resonated then simply removing hitler from the equation would not have removed the context of the times and that means one of two things either you could have had another one or you could have ended up in a situation equally bad in a different direction i don't know what that means because it's hard to imagine anything could be worse than what actually occurred but history's funny that way and that hitler is always everyone's favorite example of the difference between the great man theory of history and the trends and forces theories of history right the times made a hitler possible and maybe even desirable to some if you took him out of the equation those trends and forces are still in place right so what does that mean if you take him out and the door is still open does somebody else walk through it yeah it's mathematically speaking the uh the probability of charismatic leaders emerge i i'm so torn on that i i'm uh uh at this point here's another way to look at it the institutional um stability of germany in that time period was not enough to push back and there are other periods in german history i mean that hitler arose in arizona in 1913 he doesn't get anywhere because germany's institutional uh power is enough to simply quash that it's the fact that germany was unstable anyway that prevented a united front that would have kept radicalism from getting out of hand does that make sense yes absolutely a tricky question on this just to stay in this a little longer because i'm not sure how to think about it is the world war ii versus the holocaust when we we were talking just now about the way that history unrolls itself and could hitler have been stopped and i i don't quite know what to think about hitler without the holocaust and perhaps in his thinking how essential the anti-semitism and the hatred of jews was it feels to me that i mean i don't know we were just talking about where did he pick up his hatred of the jewish people there's uh there's stories in vienna and so on that it almost is picking up the idea of anti-semitism as a really useful tool as opposed to actually believing it in his core do you think world war ii as it turned out and hitler's as he turned out would be possible without anti-semitism could we have avoided the holocaust or was it an integral part of the ideology of fascism and the nazis not an integral part of fascism because mussolini really i mean mussolini did it to please hitler but it wasn't an integral part what's interesting to me is that that's the big anomaly in the whole question because anti-semitism didn't need to be a part of this at all right hitler had a conspiratorial view of the world he was a believer that the jews controlled things right the jews were responsible for both bolshevism on one side and capitalism on the other they ruled the banks i mean the united states was a jewifide country right uh bolshevism was was a a a jewifide sort of a a political in other words he saw jews everywhere and he had that line about if the jews of europe force another war to germany they'll pay the price or whatever but then you have to believe that they're capable of that that the holocaust is a weird weird sidebar to the whole thing and here's what i've always found interesting it's a sidebar that weakened germany because look at the first world war jews fought for germany right who was the most important and this is a very arguable point but it's just the first one that pops into my head who was the most important jewish figure that would have maybe been on the german side had the germans had a non-anti-semitic well listen that whole part of the style yes it was einstein but the whole i should point out to say germany or europe or russia or any of those things were not anti-semitic is to do injustice to history right pogroms everywhere i mean yes that is it's standard operating procedure what what you see in the hitlerian era is an absolute huge spike right because the government has a conspiracy theory that the jews have it's funny because hitler both thought of them as weak and super powerful at the same time right and and as an outsider people that we can join the whole idea of the blood and how that connects to darwinism and and all that sort of stuff is just weird right a real outlier but einstein let's just play with einstein if there's no anti-semitism in germany or or none above the normal level right um the baseline level um does einstein leave along with all the other uh jewish scientists and i mean and what does germany have as as increased technological and intellectual capacity if they stay right it's something that actually weakened that state it's it's a tragic flaw in in the hitlerian worldview but it was so and and i don't let me you had mentioned earlier like maybe it was not integral to his character maybe it was a wonderful tool for power i don't think so somewhere along the line and really not at the beginning this guy became absolutely obsessed with this with a conspiracy theory and jews and and and he surrounded himself uh with people and theorists i'm going to use that word really really sort of loosely who believed this too and so you have a cabal of people who are reinforcing this idea that the jews control the world that inter he called it international jewry was a huge part of the problem and that because of that they deserved to be punished they were an enemy within all these kinds of things it's a it's a nutty conspiracy theory that the government of one of the most i mean the big thing with germany was culture right they were they were they were a leading figure in in culture and philosophy and all these kinds of things and that they could be overtaken with this wildly wickedly weird conspiracy theory and that it would actually determine things i mean hitler was taking vast amounts of german resources and using it to wipe out this race when he needed them for all kinds of other things to fight a war of annihilation so that is the weirdest part of of the whole nazi phenomenon it's the the darkest possible silver lining to think about is that the holocaust may have been in the hatred of the jewish people may have been the thing that avoided germany getting the nuclear weapons first and is it isn't that a wonderful historical ironic twist that if it weren't so overlaid with tragedy a thousand years from now will be seen as something really kind of funny well that's that's true it's fascinating to think as you've talked so the seeds of his own destruction right the tragic flaw and my hope is this is a discussion i have with my dad as a physicist is that evil inherently contains with it that kind of incompetence so my dad's discussions he's a physicist and engineer his belief is that at this time in our history the reason we haven't had nuclear like uh terrorist uh blow up a nuclear weapon somewhere in the world is that the kind of people that would be terrorists are simply not competent enough at their job of being destructive so like there's a kind of if you plot it the more evil you are the less able you are and by evil i mean purely just like we said uh if we were to consider the hatred of jewish people as evil because it's sort of detached from reality it's like like just this pure hatred of something that's grounded on things you know conspiracy theories if that's evil then the more you sell yourself the more you give in to these conspiracy theories the less capable you are at actually engineering which is very difficult engineering nuclear weapons and effectively deploying them so that's the that's a hopeful message that the destructive people in this world are by their world view incompetent in creating the ultimate destruction i don't agree with that oh boy i straight up don't agree with that so why are we still here why haven't we destroyed ourselves why haven't the terrorists blow it's been many decades why haven't we destroyed ourselves to this point well it's when you say it's been many decades many day that's like saying in the in the life of a 150 year old person uh we've been doing well for a year the problem the problem with all these kinds of equations and it was bertrand russell right the philosopher who said so uh he said it was it's unreasonable to expect a man to walk on a tightrope for 50 years i mean the the the problem is is that this is a long game and let's remember that up until relatively recently what would you say 30 years ago it the nuclear weapons in the world were really tightly controlled that was one of the real dangers in the fall of the soviet union remember the the um the worry that that all of a sudden you were going to have bankrupt former soviet republics selling nuclear weapons to terrorists and whatnot i would suggest and and here's another problem is that when we call these terrorists evil it's easy for an american for example to say that osama bin laden is evil easy for me to say that but one man's terrorist is another man's freedom fighter as the saying goes and to other people he's not what osama bin laden did and the people that worked with him we would call evil genius the idea of hijacking planes and flying them into the buildings like that and that he could pull that off and that still boggles my mind i'm still it's funny i'm still stunned by that and yet i you know the idea here's the funny part and i don't i i hesitate to talk about this because i don't want to give anyone ideas right but you don't need nuclear weapons to do incredibly grave amounts of danger yes really i mean what one can of gasoline and a bic lighter can do in the right place and the right time and over and over and over again can bring down societies this is the argument behind the importance of the stability that a nation-state provides so when we went in and took out saddam hussein one of the great counter-arguments from some of the people who said this is a really stupid thing to do is that saddam hussein was the greatest anti-terror weapon in that region that you could have because they were a threat to him so he took that and he did it in a way that was much more repressive than we would ever be right and this is the old line about why we supported um uh right-wing death squad countries because they were taking out people that would inevitably be a problem for us if they didn't and they they were able to do it in a way we would never be able to do supposedly we're pretty good at that stuff you know just like the soviet union was behind the scenes and underneath the radar but the idea that the stability created by powerful and strong centralized leadership allowed them it's almost like outsourcing anti-terror activities allowed them to for their own reasons i mean you see the same thing in the syria situation with the assads i mean you can't have an isis in that area because that's a threat to the assad government who will take care of that for you and then that helps us by not having an isis so um i would suggest one that the game is still on on whether or not these people get nuclear weapons uh in their hands i would suggest they don't need them to achieve their goals really uh the the the crazy thing is if you start thinking like the joker in batman the the terrorist ideas it's funny i guess i would be a great terrorist because i'm just full of those ideas oh you could do this it's scary to think of how vulnerable we are but the whole point is that you as the joker wouldn't do the terrorist actions that's the that's the theory that's so hopeful to me with my dad is that all the ideas your ability to generate good ideas what forget nuclear weapons how you can disrupt the power grid how you can disrupt the attack our psychology uh attack like with a can of gasoline like you said somehow disrupt the american system of ideas like that coming up with good ideas there are we saying evil people can't come up with evil genius ideas that's what i'm saying we have this hollywood story i don't think history backs that up i mean i think you can say with the nuclear weapons it does but only because they're so recent yeah but i mean evil genius i mean that's almost proverbial but that's okay so to push back for the fun of it or i don't i don't mean to i don't want you to leave this with a t in a terrible mood because i push back on every hopeful idea but i tend to be a little cynical about that stuff but but that goes to the the definition of evil i think because i'm not so sure human history has a lot of evil people being competent i do believe that they mostly like in order to be good at doing what may be perceived as evil you have to be able to construct an ideology around which you truly believe when you look in the mirror by yourself that you're doing good for the world and it's difficult to construct an ideology where destroying the lives of millions or disrupting the american system i'm already contradicting myself as i'm saying i'm gonna say people have done this already yes so i but but then it's the the question of like about aliens with the the uh idea that if the aliens are all out there why haven't they visited us the same question if it's so easy to be evil not easy if it's possible to be evil why haven't we destroyed ourselves and your statement is from the context of history the game is still on and it's just been a few years since we've found the tools to destroy ourselves and one of the challenges of our modern time we don't often think about this pandemic kind of revealed is how soft we've gotten in terms of our deep dependence on the system so somebody mentioned to me you know what happens if power goes out for a day what happens if power goes out for a month oh for example the person that mentioned this was a berkeley faculty uh that i was talking with he's an astronomer who's observing solar flares and it's very possible that a solar flare they happen all the time to different degrees i've got your cell phones yeah to knock out the power grid for months so like you know just as a thought experiment what happens if just power goes out for a week in this country this is like the e and the electromagnetic magnetic pulses and the nuclear weapons and all those kinds of things yeah but maybe that's an act of nature yes and even just the act of nature will reveal like a little fragility the fragility of it all and then the evil can emerge i mean the kind of things that might happen when power goes out especially during a divisive time well you won't have food at baseline level that would mean that the the uh the entire supplies chain begins to break down and then you have desperation and desperation opens the door to everything can ask a dark question as opposed to the other things we've been talking about there's there's always a thread a hopeful message i think it'll be a hopeful message on this one too you may have the wrong guess um if you were to bet money on the way that human civilization destroys itself or it collapses in some way that is where the result would be unrecognizable to us as anything akin to progress what would you say is it nuclear weapons is it some societal breakdown through just more traditional kinds of war is it engineered pandemics nanotechnology is it artificial intelligence is it something we can't even expect yet do you have a sense of how we humans will destroy ourselves or might we live forever i think what what governs my view of this thing is is the ability for us to focus ourselves collectively right and that gives me the choice of looking at this and saying what are the odds we will do x versus y right um so go look at the 62 cuban missile crisis where uh we looked at the potential of nuclear war and we stared right in the face of that to me i consider that to be you want to talk about a hopeful moment that's one of the rare times in our history where i think the odds were overwhelmingly that there would be a nuclear war and uh i'm not the super kennedy worshiper that you know i grew up in an era where he was especially amongst people in the democratic party he was almost worshiped and i was never that guy but i will say something john f kennedy by himself um probably made decisions that saved a hundred million or more lives because everyone around him thought he should be taking the road that would have led to those deaths and to push back against that is when you look at it now i mean again if you were a betting person you would have bet against that and that's rare right um so so when we talk about how the world will end um the fact that one person actually had that in their hands meant that it wasn't a collective decision it gave remember i said i trust people on an individual level but when we get together we're more like a herd and we devolve down to the lowest common denominator that was something where the higher uh ethical ideas of a single human being could come into play and make the decisions that that influence the events but when we have to act collectively i get a lot more pessimistic so take what we're doing to the planet and we talk about it always now in terms of climate change which i think is far too narrow uh look at you know and and i i always get very frustrated when we talk about these arguments about is it happening is it human just look at the trash forget forget climb it for a second we're destroying the planet because we're not taking care of it and because what it would do to take care of it would require collective sacrifices that would require enough of us to say okay and and we can't get enough of us to say okay because too many people have to be on board it's not john f kennedy making one decision from one man we have to have 85 percent of us or something around the world not just you can't say we're going to stop uh uh doing damage to the to the to the world here in the united states if china does it right so the amount of people that have to get on board that train is hard you get pessimistic hoping for those kinds of shifts unless it's right you know krypton's about to explode we have and so i think if you're talking about a gambling man's view of this that that's got to be the odds on favorite because it requires such a unanim i mean and the systems maybe aren't even in place right the fact that we would need intergovernmental bodies that are completely discredited now on board and you would have to subvert uh the national interests of nation states i mean the the amount of things that have to go right in a short period of time we don't have 600 years to figure this out right so to me that that looks like the most likely just because the things we would have to do to avoid it seem the most unlikely does that make sense yes absolutely i i believe call me naive in just like you said with the individual i believe that charismatic leaders individual leaders will save us like this what if you don't get them all at the same time what if you get a charismatic leader in one country but under or what if you get a charismatic leader in a country that doesn't really matter that much well it's a ripple effect so it starts with one leader and their charisma inspires other leaders like so it's uh it's like one ant queen steps up and then the rest of the ant starts behaving and then there's like little other spikes of leaders that emerge and then that's where collaboration emerges i tend to believe that like when you heat up the system and shit starts getting really chaotic then the leader whatever this collective intelligence that we've developed the leader will emerge like do you think there's just as much of a chance though that the leader would emerge and say the jews are the people who did all this right you know what i'm saying is that the idea that they would come up you have a charismatic leader and he's going to come up with the rights or she is going to come up with the right solution as opposed to totally coming up with the wrong solution i mean i guess what i'm saying is you could be right but a lot of things have to go the right way but my intuition about the evolutionary process that led to the creation of human intelligence and consciousness on earth results in the the power of like if we think of it just the love in the system versus the hate in the system that the love is greater the human the the the human kindness potential in the system is greater than the human uh hatred potential and so the leader that is in the time when it's needed the leader that inspires love and kindness will is more likely to emerge and will have more power so you have the hitlers of the world that emerge but they're actually in the grand scheme of history are not that impactful so it's it's weird to say but not that many people died in world war ii if you look at the the the the full range of human history uh you know it's uh up to 100 million whatever that is with natural pandemics too you can have those kinds of numbers but it's still a percentage i forget what the percentage is maybe three five percent of the human population on earth maybe it's a little bit focused on a different region but it's not destructive to the entirety of human civilization so the i believe that the the charismatic leaders when time is needed that do good for the world in uh the broader sense of good are more likely to emerge than the ones that say kill all the jews i it's it's possible though and this is just you know i've thought about this all of 30 seconds but i mean uh it it it's we're betting money here on the on the 21st century who's going to win i think maybe uh you've divided this into too much of a black and white dichotomy this love and good on one side and this evil on another let me throw something that might be more in the center of that linear uh a balancing act self-interest which may or may not be good you know good the good version of it we call enlightened self-interest right the bad version of it we call selfishness but self-interest to me seems like something more likely to impact the outcome than either love on one side or evil on the other simply a question of what's good for me or what's good for my country or what's good from my point of view or what's good for my business i mean if you tell me um and maybe i i'm a coal miner or maybe i own a coal mine if you say to me we have to stop using coal because it's hurting the earth i have a hard time disentangling that greater good question from my right now good feeding my family question right so i think i think maybe it's going to be a much more banal thing than good and evil much more a question of we're not all going to decide at the same time that the interests that we have are aligned does that make sense yeah totally but i mean i've looked at ayn rand and objectivism and kind of really thought like how bad or good can things go when everybody's acting selfishly but i think we're just talking two ants here with microphones talking about two seconds but like the the question is when they when this spreads so what what is what do i mean by love and kindness i think it's human flourishing on earth and throughout the cosmos it feels like whatever the engine that drives human beings is more likely to result in human flourishing and people like hitler are not good for human flourishing so that's what i mean by good is they is is there's a i mean maybe it's an intuition that kindness is an evolutionary advantage i hate those terms i hate to reduce stuff to the evolutionary biology always but it just seems like for us to multiply throughout the universe it's good to be kind to each other and those leaders will always emerge to save us from the hitlers of the world that want to kind of burn the thing down with a flamethrower that's the intuition but let's talk about you you brought up evolution several times let me let me play with that for a minute um i think going back to animal times we are conditioned to deal with overwhelming threats right in front of us so i have quite a bit of faith in humanity when it comes to impending doom right outside our door uh if krypton's about to explode i think humanity can r rouse themselves to great and would give power to the people who needed it and be willing to make the sacrifices but that's what makes i think the the pollution slash climate change slash you know screwing up your environment um uh threats so particularly insidious is it happens slowly right it defies fight and flight mechanisms it defies the natural ability we have to deal with the threat that's right on top of us and it requires an amount of foresight that while some people would would be fine with that most people are too worried and understandably i think too worried about today's threat rather than next generations threat or whatever it might be so i mean when we talk about when you had said what do you think the greatest threat is i think with nuclear weapons i think could we have a nuclear war we darn right could but i i think that there's enough of of inertia we're against that because people understand instinctively if i decide to launch this attack against china and i'm india we're going to have 50 million dead people tomorrow whereas if you say we're gonna have a whole planet of dead people in three generations if we don't start now i think the evolutionary uh way that we have have evolved mitigates maybe against that in other words i think i would be pleasantly surprised if we could pull that off does that make sense totally i don't mean to be like the i'm the i'm the scripting doom it's fun that way i think we're both uh maybe i'm over the top on the left maybe i'm over the top on the doom so it makes it makes for a fun chat i think so one one guy that i've talked to several times who's slowly becoming a friend is a guy named elon musk he's a big fan of hardcore history uh especially genghis khan uh series of episodes but really all of it him and his uh his girlfriend grimes listen to it which is i know what you like yeah you know elon okay awesome so that's like relationship goals uh like listen to hardcore history on the weekend with your loved one okay uh so let me if i were to look at the guy from a perspective of human history it feels like he will be a little speck that's remembered oh absolutely you think about like the people what will we remember from our time who are the people will remember whether it's the the hitler's or the einsteins who's going to be it's hard to predict when you're in it but it seems like elon would be one of those people remembered and if i were to guess what he's remembered for it's the work he's doing with spacex and potentially being the person that we don't know but the being the person who launched a new era of space exploration if we look you know centuries from now if we are successful as human beings surviving long enough to venture out into the you know october the stars it's weird to ask you this i don't know what your opinions are but do you think humans will be a multi-planetary species in the arc long arc of history do you think elon will be successful in his dream and he doesn't he doesn't shy away from saying it this way right he really wants us to colonize mars first and then colonize other earth-like planets in other solar systems throughout the galaxy do you have a hope that we humans will venture out towards the stars so here's the thing and this actually again dovetails do what we were talking about earlier i actually first of all i toured spacex and it is when you you it's hard to get your mind around because he's doing what it took governments to do before yes okay so so it's incredible that we're watching individual companies and stuff doing this doing it faster and cheaper yeah well and and and and pushing the envelope right faster than the governments at the time we're moving it's it's it really is i mean there's a lot of people who i i think who think elon is is overrated and you have no idea right when you go see it you have no idea but that's actually not what i'm most impressed with um it's tesla i'm most impressed with and the reason why is because in my mind we just talked about what i think is the greatest threat the environmental stuff and i talked about our inability maybe all at the same time to be willing to sacrifice our self-interests in order for the for the goal and i don't want to put words in elon's mouth so you can you can talk to him if you want to but in my mind what he's done is recognize that problem and instead of building a car that's a piece of crap but you know it's good for the environment so you should drive it he's trying to create a car that if you're only motivated by your self-interest you'll buy it anyway and it will help the environment and help us transition away from one of the main causes of damage i mean one of the things this pandemic and the shutdown around the world has done is show us how amazingly quickly the earth can actually rejuvenate we're seeing clear skies in places species come and you would have thought it would have taken decades for some of this stuff so what if to name just one major pollution source we didn't have the pollution caused by automobiles right and and if if you had said to me dan what do you think the odds of us transitioning away from that were 10 years ago i would have said well people aren't going to do it because it's inefficient it's this it's that nobody wants people but what if you created the vehicle that was superior in every way so that if you were just a self-oriented consumer you'd buy it because you wanted that car that's the best way to get around that problem of people not wanting to i think he's identified that and as he's told me before you know when the last time a car company was created that actually you know blah blah blah he's right and so i happen to feel that even though he's pushing the envelope on the space thing i think somebody else would have done that someday i'm not sure because of the various things he's mentioned how difficult it is to start i'm not sure that the industries that create vehicles for us would have gone where he's going to lead them if he didn't force them there through consumer demand by making a better car that people want it anyway they'll follow they'll copy they'll do all those things and yet who was going to do that so i hope he doesn't hate me for saying this but i happen to think the tesla idea may alleviate some of the need to get off this planet because the planet's being destroyed right and we're going to colonize mars probably anyway if we live long enough and i think the tesla idea not just elon's version but ones that follow from other people is the best chance of making sure we're around long enough to see mars colonized does that make sense yeah totally and one other thing from my perspective because i'm now starting a company i think the interesting thing about elon is he serves as a beacon of hope like pragmatically speaking for people that sort of push back on our doom conversation from earlier that a single individual could build something that allows us as self-interested individuals to gather together in a collective way to actually alleviate some of the dangers that face our world so like it gives me hope as an individual that i can build something that can actually have impact that counteracts the uh the stalins and the hitlers and all the threats that face that human civilization faces that an individual has that power i i didn't believe that the individual has that power in the in the halls of government like i don't feel like any one presidential candidate can rise up and help the world unite the world it feels like from everything i've seen in and you're right with tesla it can bring the world together to do good that's a really powerful mechanism of you know whatever you say about capitalism that you can build companies that start you know it starts with a single individual of course there's a collective that that grows around that but the leadership of a single individual their ideas their dreams their vision can catalyze something that takes over the world and does good for the entire world but if i think but again i i think the genius of the idea is that it doesn't require us to go head-to-head with human nature right he he's he's actually built human nature into the idea by basically saying i'm not asking you to be uh an environmental activist i'm not asking you to sacrifice to make i'm gonna sell you a car you're going to like better and by buying it you'll help the environment that takes into account our foibles as a species and actually leverages that to work for the greater good and that's the sort of thing that does turn off my little doom caster cynicism thing a little bit because you're actually hitting us where we live right you're you're you're not you can take somebody who doesn't even believe the environment's a problem but they want a tesla so they're inadvertently helping anyway i think that's the genius of the idea yeah and i'm telling you that's one way to make love much more efficient mechanism of change than uh hate making it in your self-interest just creating a product that uh least to more love than uh than hate you're gonna want to love your neighbor because you're gonna make a fortune okay there you go that's why he's right i'm on board that's why elon said love is the answer that's i think uh exactly what he meant okay let's try something difficult uh you've uh recorded an episode of steering into the iceberg on your common sense program yeah that has started a lot of conversations it's quite moving it was quite haunting got me a lot of angry emails really of course i did something i haven't done in 30 years i endorsed a political candidate from one of the two main parties and there were a lot of disillusioned people because of that i guess i didn't hear it as an endorsement i just heard it as a the similar flavor of conversation as you have in in hardcore history it's almost the speaking about modern times in the same voice as you speak about when you talk about history so it was just a a little bit of a haunting view of the world today i know we were just wearing our doom doom let me put that right back on are you no the the i like the term doom caster uh is is there is there um how do we get love to win what's the way out of this is there some hopeful line that we can walk to uh to avoid something and i hate to use the terminology but something that looks like a civil war not necessarily a war of force but a a division to a level where it doesn't any longer feel like a united states of america with an emphasis on united is is there a way out i read a book a while back i want to say george friedman the stratfor guy wrote it was something called the next hundred years i think it was called and i remember thinking um i didn't agree with any of it and one of the things i think he said in the book was that you know the united states was going to break up i'm going from memory here he might not have said that at all but something was stuck in my memory about that i remember thinking um but i i think some of the arguments were connected to the differences that we had and the fact that those differences are being exploited so we talked about media earlier in the lack of truth and everything we have a media climate that is incentivized to take the wedges in our society and make them wider and there's no countervailing force to do the opposite or to help to you know so um there was a famous uh memo from a group called project for a new american century and they took it down but the way back machine online still has it and it happened before 9 11 spawned all kind of conspiracy theories because it was saying something to the effect of and i'm really paraphrasing here but you know that the united states needs another pearl harbor type event because those galvanize a country that without those kinds of events periodically is naturally geared towards pulling itself apart and it's those periodic events that act as the countervailing force that otherwise is not there um if that's true then we are naturally inclined towards pulling ourselves apart so to have a media environment that makes money off widening those divisions uh which we do i mean i was in talk radio and and it it has those people the people that used to scream at me because i wouldn't do it but i mean we would have these terrible conversations after every broadcast where i'd be in there with the program director and they're yelling at me about heat heat was the worthy create more heat well what is heat right heat is division right and they want the heat not because they're political they're not republicans or or democrats either they're we want listeners and we want engagement and involvement and because of the constructs of the format you don't have a lot of time to get it so you can't have me giving you like on a podcast an hour and a half or two hours where we build a logical argument and you're with me the whole way your audience is changing every 15 minutes so whatever points you make to create interest and intrigue and engagement have to be knee-jerk right now things they told me once that the audience has to know where you stand on every single issue within five minutes of turning on your show in other words you have to be part of a of a linear set of political beliefs so that if you feel a about subject a then you must feel d about subject d and i don't even need to hear your opinion on it because if you feel that way about a you're going to feel that way about d this is a system that is designed to pull us apart for profit but not because they want to pull us apart right it's a byproduct of the prophet that's one little example of of 50 examples in our society that work in that same fashion so what that project for a new american century document was saying is that we're naturally inclined towards disunity and without things to occasionally ratchet the unity back up again so that we can start from the baseline again and then pull ourselves apart till the next pearl harbor that you'll pull yourself apart which i think was i think that's what the george friedman book was saying that i disagreed with so much at the time um so in answer to your question about civil wars we can't have the same kind of civil war because we don't have a geographical division that's as clear-cut as the one we had before right you had a basically north-south line and some border states it was set up for that kind of a split now we're divided within communities within families within gerrymandered voting districts and precincts right so you can't disengage we're stuck with each other so if there's a civil war now for lack of a better word what it might seem like is the late 1960s early 1970s where you had the bombings and you know let's call it domestic terrorism and things like that because that that would seem to be something that once again you don't even need a large chunk of the country pulling apart ten percent of people who think it's it's the end times can do the damage just like we talked about terrorism before and a can of gas and a big lighter i've lived in a bunch of places and i won't give anybody ideas where a can of gas in a bic lighter would take a thousand houses down before you could blink yeah right um that terrorist doesn't have to be from the middle east doesn't have to have some sort of a fundamentalist religious agenda it could just be somebody really pissed off about the election results so once again if we're playing an odds game here everybody has to behave for this to work right only a few people have to misbehave for this thing to go sideways and remember for every action there is an equal and opposite reaction so you don't even have to have those people doing all these things all they have to do is start retribution cycle and there's an escalation yes and it go and it creates a momentum of its own which leads fundamentally if you follow the chain of events down there to some form of dictatorial government as the only way to create stability right you want to destroy the republic and have a dictator that's how you do and there are parallels to nazi germany the burning of the reichstag that you know blah blah blah i'm the doom caster again all right well and some of it could be manufactured by the those seeking authoritarian power absolutely like the reichstag fire was or the polish soldiers that fired over the border before the invasion in 1939 uh to fight the uh the devil's advocate was an angel's advocate uh i would say just as our conversation about elon it feels like individuals have power to unite us to to be that force of unity so uh you mentioned the media i think you're one of the great podcasters in history joe rogan is a like a long form whatever it's not podcasting it's actually whatever the very infrequent is what it is no matter what it is but the basic process of it is you go deep and you stay deep and the listener stays with you for a long time so i i'm just looking at the numbers like we're almost three hours in and i from previous episodes i can tell you that about 300 000 people are still listening to the sound of our voice three hours in so usually 300 to 500 000 people listen and they too congratulations by the way that's wonderful joe rogan is what like 10 times that and so he has power to unite uh you have power to unite there's a few people with voices that it feels like they have power to unite even if you if you quote unquote endorse a candidate and so on there's still it feels to me that speaking of i don't want to keep saying love but it's love and maybe unity more practically speaking that like sanity that like respect for those you don't agree with or don't understand uh so empathy well just a few voices of those can help us avoid the really importantly not avoid the singular events like you said of somebody starting a fire and so on but avoid the escalation of it the preparedness of the populace to escalate those events to yeah to to turn a singular event in a single riot or a shooting or like even something much more dramatic than that to turn that into something that creates like ripples that grow as opposed to ripples that fade away and so like i would like to put responsibility on somebody like you and uh on me in some small way and joe being cognizant of the fact that a lot of very destructive things might happen in november and a few voices can save us is the feeling i have not by saying we should vote for or any of that kind of stuff but really by being the the voice of calm that like calms the the seas from or whatever the analogy is from boiling up because i i truly am worried about this is the first time this year when i i sometimes i somehow have felt that the american project will go on forever that when i came to this country i just believed and i think i'm young but like you know i have a dream of creating a company that will do a lot of good for the world and i thought that america is the beacon of hope for the world and the ideas of freedom but also the idea of empowering companies that can do some good for the world and i'm just worried about this america that filled me a kid that came from our family came from nothing and from you know russia as it was soviet union as it was to be able to do anything in this new country i'm just worried about it and it feels like a few people can still keep this project going like people like elon people like joe uh is there do you have a bit of that hope i'm watching this experiment with social media right now and i don't even mean social media really expand that out to um i mean i feel like we're all guinea pigs right now watching you know i have two kids and and just watching and there's a three year space between the two of them one's 18 the other is 15. and just you know in when i was a kid a person who was 18 and 15 would not be that different just three years difference more maturity but their life experiences you would easily classify those two people as being in the same generation now because of the speed of technological change there is a vast difference between my 18 year old and my 15 year old and not in a maturity question just in what apps they use how they relate to each other how they deal with their peers uh their social skills all those kinds of things where you turn around and go this is uncharted territory we've never been here so it's going to be interesting to see what effect that has on society now as that relates to your question the most upsetting part about all that is reading how people treat each other online and you know there's lots of theories about this the fact that some of it is just for trolling laughs that some of it is just people are not interacting face to face so they feel free to treat each other that way um and i of course i'm trying to figure out how how if this is how we have always been as people right we've always been this way but we've never had the means to post our feelings publicly about it or if the environment and the social media and everything else has provided a change and changed us into something else um either way when one reads how we treat one another and the horrible things we say about one another online which seems like it shouldn't be that big of deal they're just word but they have a cumulative effect i mean when you uh i was reading um meghan markle who i don't know a lot about because it's it's too much of the pop side of culture for me to pay but i read a story the other day where she was talking about the abuse she took online and how incredibly overwhelming it was and how many people were doing it and you think to yourself okay this is something that people who are in positions of what you were discussing earlier never had to deal with let me ask you something and boy this is the ultimate doom caster thing of all time to say when you think of historical figures that push things like love and peace and um and and creating bridges between enemies when you think of how what happened to those people first of all they're very dangerous every society in the world has a better time easier time dealing with violence and things like that than they do non-violence non-violence is really difficult for governments to deal with for example what happens to gandhi and jesus and martin luther king and you think about all those people right when they're that day it's it's ironic isn't it that these people who push for peaceful solutions are so often killed but it's because they're effective and when they're killed the effectiveness is diminished why are they killed because they're effective and and the only way to stop them is to eliminate them because they're charismatic leaders who don't come around every day and if you eliminate them from the scene the odds are you're not going to get another one for a while i guess what i'm saying is the very things you're talking about which would have the effect you think it would right they would destabilize systems in a way that most of us would consider positive but those systems have a way of protecting themselves right and and so i i feel like history shows see history is pretty pessimistic i think by and large um if only because we can find so many examples that just sound passive but i feel like people who are dangerous to the way things are tend to be removed yes but there's two things to say i feel like you're right that history i feel like the ripples that love leaves in history are less obvious to detect but are actually more transformational like well one could make a case about i mean if you want to talk about the the long-term value of a jesus a gandhi yeah yes those people's ripples are still affecting people today i agree and that's you feel those ripples through the general improvement of the quality of life that we see in throughout the generations like you feel the ripples i'll go along with you on that okay but i would even if that's not true now i tend to believe that and by the way the the company that i'm working on is a competitor is exactly attacking this which is a competitor to twitter i think i can build a better twitter as a first step there's a longer story in there i think a three-year-old child could build it better and that this is not to denigrate you i'm sure yours would be better than a three-year-old but twitter is so and listen facebook to their they're really awful platforms for intellectual discussion and meaningful discussion but and i'm on it so let me just say i'm part of the problem we're new to this so it's not it wasn't obvious at the time how to do it it's now you agree and now a three-year-old can i do i i tend to believe that we live in a time where the tools that people that are interested in providing love like the weapons of love are much more powerful so like the one nice thing about technology is it allows anyone to build a company that's more powerful than any government so that could be very destructive but it could be also very positive and that's i tend to believe that somebody like elon that wants to do good for the world somebody like me and many like me could have more power than any one government to uh and by power i mean the power to affect change which is different from government government and i don't mean to interrupt you but i'll forget my train of thought i'm getting old but i mean how do you deal with the fact that already governments who are afraid of this are walling off their own internet systems as a way to create firewalls simply to prevent you from doing what you're talking about in other words if there's an old line that if voting really changed anything they'd never allow it if if love through a modern day successor to twitter would really do what you wanted to do and this would destabilize governments do you think that governments would would take counter measures to squash that love before it got too dangerous there's several answers one first of all i don't actually to push back on something you said earlier i don't think love is as much of an enemy of the state as as one would think different states have different views i i think the states want power and i don't always think that love is in tension with power like i think and and i think it's not just about love it's about rationality it's reason it's empathy all of those things i don't necessarily think there always have to be by definition in conflict with each other so that's one sense is i feel like basically you can trojan horse love into behind behind uh but you have to be good at it this is the thing is you have to be conscious of the way these states think so the fact that china banned certain services and so on that means the the companies weren't eloquent whoever the companies are weren't actually good at infiltrating like i think isn't that a song like love is a battlefield i think it's all a cat editor yeah it's all a game and you have to be good at the game and just like elon we said you know with tesla and saving uh the environment i mean that's not just by getting on a stage and saying it's important to save the environment is by building a product that people can't help but love and then convincing hollywood stars to love it like there's there's a game to be played okay so let me let me build on that because i i think there's a way to see this i think you're right and so uh it has to do with a story about the 1960s in the vast scheme of things the 1960s looks like a revival of neo-romantic ideas right uh i had a buddy of mine several years well two decades older than i was who was uh in the 60s went to the protest did all those kind of things and we were talking about it and i was romanticizing it and he said don't romanticize he goes let me tell you most of the people that went to those protests and did all those things all they were there was to meet girls and have a good time and you know it was it wasn't so but it became in vogue to have all in other words let's talk about your empathy and love you're never gonna in my opinion grab that great mass of people that are only in it for them they're interested in whatever but if meeting girls for a young teenage guy requires you to feign empathy requires you to read deeper subjects because that's what people are into you can almost as a silly way to be trendy you could make maybe empathy trendy love trendy solutions that that are the opposite of that um the kind of things that people inherently will not put up with you in other words the possibility exists to change the zeitgeist yes and reorient it in a way that even if most of the people aren't serious about it the results are the same does that make sense absolutely okay okay so we've found a meeting of the month yeah yeah exactly creating creating incentives that uh that encourage the best and the most beautiful aspects of feminism it all boils down to meeting girls and boys once again you're getting to the bottom of the evolutionary motivations and you're always on safe ground when you do that yeah that's a little difficult for me of uh you know and i'm sure it's actually difficult for you to to listen to me say complimenting you but uh it's not good it's difficult for both of us okay so but uh you know you and i as i mentioned to you i think off mike been friends for a long time it's just been one way so like i've been away now it's two way is to right now so like that's the beauty of podcasting you know i mean now just been fortunate enough with this particular podcast that i see in people's eyes when they meet me that they've been friends with me for for for a few years now and and we become fast friends actually after we start talking yeah but it's one way in the vet in that first moment uh you know like there's something about your especially hardcore history that uh you know i do some crazy challenges and running and stuff i remember in particular probably don't have time one of my favorite episodes the painfultainment one some people hate that episode because it's too real it's my darkest one we wanted to set a baseline that's the baseline but i remember listening to that and when i ran uh 22 miles for me that was the long distance yeah and uh it just pulls you in and there there's something so powerful about this particular creation that's bigger than you actually that you've created it's kind of interesting i think anything that is successful like that like elon stuff too it becomes bigger than you and that's that's what you're hoping for right yeah absolutely didn't mean to interrupt you i apologize i guess one a question i have if you like look in the mirror but you also look at me what advice would you give to yourself and to me and to other podcasters maybe to joe rogan about this journey that we're on i feel like it's something special i'm not sure exactly what's happening but it feels like podcasting is special what advice and i'm relatively new to it what advice do you have for for people that are carrying this flame and traveling this journey well i'm often asked for advice by new podcasters people just starting out and so i have sort of a a tried and true list of uh do's and don'ts and and but i don't have um advice or suggestions for you or for joe joe doesn't need anything from me joe's figured it out right i mean he hasn't yet he's still a confused kid curious about the world that's but that's the genius of it that's what makes it work right that's what that's what joe's brand is right um i guess what i'm saying is by the time you reach the stage that you're at or joe's at or they don't need they have figured this out the people that sometimes need help are brand new people trying to figure out what do i do with my first show and how do i talk to them and and i have standard answers for that but you found your niche i mean you don't need me to tell you what to do as a matter of fact i might ask you questions about how you do what you do right well there's uh i guess there's specific things like we were uh talking offline about monetization that's a fascinating one very difficult as an independent yeah and uh one of the things that joe is facing with um i don't know if you're paying attention but he joined spotify with a 100 million dollar deal before going exclusive on their platform the idea of exclusivity that one i don't give a damn about money personally but i'm single so and i i like living in a shitty place so i i enjoy it so i guess makes it easier you get the freedom right now you know yeah freedom materials is slate not saving for anybody's college exactly yeah okay so uh on that point but i also okay maybe it's romanticization but i feel like podcasting is pirate radio and when i first heard about spotify partnering up with joe i was like you know fuck the man i i said i i even i drafted a few tweets and so on just like attacking spotify then i'd calm myself down that you can't lock up the special thing we have but then i realized that maybe that these are vehicles for just reaching more people and actually respecting podcasters more and so on so that's what i mean by it's unclear what the journey is because uh you also serve as beacon for now there's like millions 1 million plus podcasters i i i wonder what the journey is do you have a sense um are you at romantic in the same kind of way in feeling that because you have a roots and radio too do you feel that podcasting is pirate radio or is the spotify thing one possible avenue are you nervous about joe as a fan as a friend of joe or is this a it's a good thing for us so my history of how i got involved in podcasting is interesting yes i i i was in radio uh and then i started a company back in the era where the dot-com boom was happening and everybody was being bought up and it just seemed like a great idea right start um i did it with seven other six other people and the whole goal of the company was uh we had we had to invent the term i'm sure everybody there's other places that invented it at the same time but what we were pitching to investors was something called amateur content so this is before youtube before podcasting before all this stuff and i my job was to be the evangelist and i would go to these people and talk and and sing the praises of all the ways that amateur content was going to be great and i never got a bite and they all told me the same thing this isn't going to take off because anybody who's good is already going to be making money at this and i kept saying forget that we're talking about scale here if you have millions of pieces of content being made every week a small percentage is going to be good no matter what right 16 year olds will know what other 16 year old is like and i kept pushing this nobody bit but the podcast grew out of that because in if you're talking about amateur content in 1999 well then you're already where you know you're ahead of the game in terms of not seeing where it's going to go financially but seeing where it's going to go technologically and so when we started the podcast in 2005 and it was the political one not hardcore history um which was an outgrowth of the old radio show um we didn't have any financial um ideas we were simply trying to get our handle on the technology and how you distribute it to people and all that and it was years later that we tried to figure out okay how can we get enough money to just support us while we're doing this and we and the cheap and the easy way was just to ask listeners to donate like a pbs kind of model and that was that was the original model um so then once we started down that we figured out other models and there's the advertising thing and we sell the old shows and so all these became ways for us to support ourselves um but as as podcasting matured and as more operating systems develop and phones were developed and all these kinds of things every one of those developments which actually made it easier for people to get the podcast actually made it more complex to make money off of them yes so while our audience was building the amount of time and effort we had to put into the monetization side began to skyrocket so to get back to your spotify question to use just one example there's a lot of people who are doing similar things um in this day and age you know we just sell mp3 files and all you had to have was an mp3 player it's cheap and dirty now every time there's an os upgrade something breaks for us so we're having i mean my choices are at this point to start hiring staff more staff you know people and then be a human resources manager i mean the pirate radio side of this was the pirate radio side of this because you didn't need anybody but you know you or you and another i mean you could just do this lean and mean and it's becoming hard to do it lean and mean now so if somebody like a spotify comes in and says hey um we'll handle that stuff for you in the past i would just say f off we don't need you yeah i don't mind and i i definitely am not making what we could make on this but what we would have to do to make that is honoris to me but it's becoming onerous to me day to day anyway and so if somebody were to come in and say hey uh we'll pick that up for you we will not interfere with your content at all we won't and in my case you can't say we need a show a month because that ain't happening right so i mean everybody's everybody's uh design is different right so it doesn't you know there's not one size fits all but i guess as a long time pirate podcaster um there are you know we've been looking to partner with people but nobody's right for us to partner with i mean so so i'm always looking for ways to take that side of it off my plate because i'm not interested in that side all i want to do is the shows and the you know it's really at this point you shouldn't call yourself an artist because some you know that's something to be decided by other but i mean we're trying to do art and there's something very satisfying in that but the part that i can't stand is the the increasing amount of time the monetization question takes upon us and so there's a case to be made i guess is what i'm saying that if a partnership with some outside firm enhances your ability to do the art without disenhancing your ability to do the art it's um the word i'm looking for here is it's um it's it's enticing yes uh i don't like big companies um so i'm afraid of of whatever strings might come with that and if i'm joe rogan and i'm talking about subjects that can make company public companies you know a little nervous um i would certainly be careful but at the same time people who are not in this game don't understand the problems that literally i mean just all the operating systems all the podcatchers every time some new podcatcher comes out makes it easier to get the podcast that's something we have to account for on the back end and i'm not exactly the technological wizard of all time so um i think it is maybe maybe the short answer is is that as the medium develops it's becoming something that you have to consider not because you want to sell out but because you want to keep going and it's becoming harder and harder to be pirate-like in this environment the thing that convinced me especially inside spotify is that they understand so if you walk into this whole thing with some skepticism as you're saying of big companies then then it works because spotify understands the magic that makes podcasting or they appear to in part at least they understand enough to respect joe rogan and despite what i don't i don't know if you uh so there's the internet and there's people with opinions on the internet really yes and they have opinions about joe and spotify but the reality is there's two things in private conversation with joe and in general there's two important things one spotify literally doesn't tell joe anything like all the people that think they the spotify somehow pushing joe in this direction contractuals didn't insist upon that it's in the contract but also you know companies have a way of even with the contract i sure do to be you know marketing people hey i know we're not forcing you yeah yeah yeah yeah i hate that yeah but jump with you what you and joe are the same and spotify is smart enough not to send a single email of that kind that's really smart and they leave they leave them be there is meetings inside spotify that like people have read about people complain but those meetings never reached joe that that never that's like company stuff and the idea that spotify is different than pirate radio the the difficult thing about podcasting is nobody gives a damn about your podcast you're alone in this i mean there's fans and stuff but nobody nobody's looking out for you yeah yeah and the nice thing about spotify is they want joe to joe's podcast to succeed even more that's what joe talked about is that's the difference between youtube and spotify spotify wants to be the netflix of podcasting and they like what netflix does is they they they don't want to control you in any way but they want to create a a platform where you can flourish even when your interests are aligned interests are alone so let me bring up let me bring up something that uh let's make a distinction because not all companies who do this are the same and you brought up youtube and spotify but but to me youtube is at least more like spotify than some of these smaller uh the term is walled garden right you've heard the term walls garden okay so um i've been around podcasting so long now that i've seen rounds of consolidation over the years and they come in waves and all of a sudden so you'll get uh and i'm not going to mention any names but but up until recently the consolidation was happening with relatively small firms compared to people like spotify and the problem was is that by deciding to to consolidate your materials in a walled garden you are walling yourself off from audience right um so your choice is i'm going to accept this amount of money from this company but the loss is going to be a large chunk of my audience and that's a catch-22 because you're negotiating power with that company is based on your audience size so signing up with them diminishes your audience size you lose negotiating power but when you get to the level of the spotify to just pick them out there's other players um but you brought up spotify specifically these are people who can potentially potentially enhance your audience over time and so the risk to you is lower because if you decide in a year or two whatever the licensing agreement's term is that you're done with them and you want to leave instead of how you would have been with some of these smaller walled gardens where you're walking away with a fraction of the audience you walked in with you have the potential to walk out with whatever you got in the original deal plus a larger audience because their algorithms and everything are designed to push uh people to your content if they think you'd like so it takes away some of the downside risk which which alleviates and if you can write an agreement like joe rogan i mean where you've protected your your freedom to to put the content out the way you want so and if some of the downside risk is mitigated and if you eliminate the problem of trying to monetize and stay up with the latest tech then it might be worth it i you know i'm scared of things like that but at the same time i'm trying to not be an idiot about it yes and i can be an idiot about it and when you've been doing it as independently for as long as i have the inertia of that uh has a force all its own but i'm i'm i'm inhibited enough in what i'm trying to do on this other end that it's opened me at least to listening to people yes um but um listen at the same time i love my audience and it sounds like a cliche but they're literally the reason i'm here so i want to make sure that whatever i do if i can is in keeping with a relationship that i've developed with these people over 15 years um but like you said no matter what you do you are go because see here's the thing if you don't sign up with one of those companies to make it easier for them to get your stuff on this hand they might yell at you for how difficult it is because the new os the new the new operating system just updated and you just i can't get your so either way you're opening yourself up to ridicule at this point all of that makes it easier to go well if the right deal came along and they weren't screwing me and they weren't screwing my audience and blah blah um you know i mean again in this business when you're talking about cutting edge technology that is ever-changing and as you said a million podcasts and growing i think you have to try to maintain flexibility and especially if they can mitigate the downside risk i think you have to i think you'd be an idiot to not at least try to stay up on the current trends and look i'm watching joe i'm going okay let's see how it goes for joe yeah i mean if if he's like ah this is terrible i'm getting out of this you go okay those people are right you know so joe's put himself out as a guinea pig and i and the rest of us guinea pigs appreciate it as a huge as a fan of your shows and as a fan of netflix the people there i think i can speak for like millions of people in hope that hardcore history comes to netflix or if spotify becomes the netflix of podcasting into spotify there's something at its best that they bring out the you said artists so i can say it is they bring out the best out of the artists they they remove some of the headache and somehow like they they put at their best netflix for example is able to enforce and find the the beauty and the power in the creations that you make even better than you like they don't interfere with the creations but they somehow it's a it's a branding thing probably too interfering would be that would be a no-go for me that's right absolutely that can't help but that's why netflix is masterful they they seem to not interfere with the talent as opposed to i could throw other people under the bus like there's a lot of places under the bus that could be thrown absolutely so i would love i know there's probably people screaming yes right now uh in terms of hardcore history on netflix would be awesome um and i i don't love asking this question but it's asked probably the most popular question that's unanswerable so let me try to ask it in a way that you would actually answer it which is of course you said you don't release shows very often and uh the question is the requests and the questions is what can you tell dan to do one on the civil wars can you tell dan to do one on the napoleon bonaparte can you tell them to do one you know ever every topic and you've spoken to this actually your answer about the civil war is quite interesting i didn't know you knew what my answer but the civil war was that that you don't you as a military historian you enjoy in particular when there is differences in the armies of contrast contrasts as with the civil war which like blew my mind when i heard you say is you know it's there's not an interesting a deep intricate contrast between the two opposings like the roman civil wars which legionary against legionary yeah is and you've also said that you kind of the shows you work on are ones where you have some roots of fundamental understanding about that period and and so like when you work on a show it's basically like pulling at those strings further and like refreshing your mind and learning definitely done the research wow these are like words out of my mouth yeah you're right so but is there something like like shower thoughts on reddit uh is there some ideas that are like lingering in your head about possible future episodes is there things that whether you uh not committing to anything but uh whether you're gonna do it or not is there something that's like makes you think hmm that would be interesting to uh to pull at that thread a little bit oh yeah i i we have things we keep in our back pocket for later so uh blueprint for armageddon the first world war series we did that was in my back pocket the whole time and when the centennial of the war happened it just seemed to be the likely time to bring out what was that was a hell of a series that's probably one of my favorites my rear end man i have to tell you psychologically you know just you know when you get to these i think i'm guessing here i think it's 26 hours all pieces together think about and and we don't do scripts it's improvised yeah so think about what 20 20 i had somebody write on twitter just yesterday saying um he said something like i'm not seeing the dedication here you're only getting 2.5 shows out a year and i wanted to say man you have no idea what the only people who understand really are other history podcasters and even they don't generally do 26 hours you know that was a two-year endeavor um as i said the first show we ever did was like 15 minutes i could crank out one of those a month but when you're doing i mean the last show we did on the fall of the roman republic was five and a half hours that's a book right um and it was part six or something so i mean you just do the math um and it felt like you were excited to interrupt and on world war one it felt like you were emotionally pulled in to it like it felt taxing i was gonna say if that's a good thing though because that you know and i think we said during the show that was the feeling that the people at the time have and i think at one point we said if this is starting to seem gruesomely repetitive now you know how the people at the time felt so in other words that had any sort of inadvertently because when you improvise the show some of these things are inadvertent but it had inadvertently created the right climate for having a sense of empathy with the storyline and to me that those are the serendipitous moments that make this art and not uh some sort of paint by the numbers kind of endeavor you know and and that's to me that wouldn't have happened had we scripted it out so it's mostly you just bring the tools of knowledge to the table and then in large part improvise like the actual wording i always say we make it like they made things like spinal tap and some of those other things where um the material so so i do have notes about things like on page 427 of this book you have this quote so that i know aha i'm at the point where i can drop that in um and sometimes i'll write notes saying here's where you left off yesterday so i remember um but in the improvisation you end up throwing a lot out and so um like like but it allows us to go off on tangents like we'll try things like i'll sit there and go i wonder what this would sound like and i'll spend two days going down that road and then i'll listen to him and go it doesn't work but that's you know like writers do this all the time it's called killing your babies right you got can't you know get not but people go so this guy goes i'm not seeing the dedication he has no idea how many things were thrown out i did an hour and a half i had an hour and a half into the current show about two months ago and i listened to it and i just went you know what it's not right boom out the window there goes six weeks of work yeah right but here's the problem you trust you're sorry to interrupt do you trust your judgment on that no no uh but but here's here's the here's the thing um our show is a little different than other people's uh joe rogan called it evergreen content in other words uh my political show is like a car you buy and the minute you drive it off the lot it loses half its value right because it's not current anymore these shows are just as good or just as bad uh five years from now as they are when we do although the standards on the internet change so when i listen to my old shows i cringe sometimes because the standards are so much higher now but when you're creating evergreen content you have two audiences to worry about you have the audience that's waiting for the next show and they've already heard the other ones and they're impatient and they're telling you on twitter where is it but you have show the show's also for people five years from now who haven't discovered it yet and who don't care a wit for how long it took because they're going to be able to download the whole and all they care about is quality and so what i always tell new podcasters is they always say i read all these things it's very important you have a release schedule well it's not more important than putting out a good piece of work and the audience will forgive me if it takes too long but it's really good when you get it they will not forgive me if i rush it to get it out on time and it's a piece of crap so for us and this is why when you brought up a spotify deal or anything else they can't interfere with this at all because my my job here as far as i'm concerned is quality and everything else goes by the wayside because the only thing people care about long term the only thing that gives you longevity is how good is it right how good is that book if you read jrr tolkien's work tomorrow you don't care how long it took him to write it all he cares how good is this today and that's what we try to think too and i feel like if it's good if it's really good everything else falls into place and takes care of itself um and although sometimes to push back sorry to interrupt i've done it to you a thousand times so you can get me back please sometimes the deadline you know some of the greatest like movies and books have been you think about like dostoyevsky i forget which one knows from underground or something he needed the money so he had to write it real quick sometimes the deadline creates is powerful at taking a creative mind of an artist and just like slapping it around to force some of the good stuff out now the problem with history of course is there's there's different definitions of good um that like it's not just about what you talk about which is the storytelling the richness of the storytelling and i'm sure you're you know again not to compliment you too much but you're one of the great storytellers of our time that that i'm sure if you put in a jail cell and force a like somebody point a gun at you you could tell one hell of a good story but you still need the facts of history uh or not necessarily the facts but you know like making sure you painting the right full picture not perfectly right that's what i meant about the audience doesn't understand what a history podcast is you can't just riff and be wrong so so let me let me both both oppose what you just said and back up what you just said excellent so i have a book that i wrote right and uh and in a book you have a hard deadline right so harpercollins had a hard deadline on that book so when i released it i was mad because i would have worked on it a lot longer which is my style right get it right but we had a chapter in that book entitled pandemic prologue question mark and it was the book about the the part about the black death and the 1918 flu and all that kind of stuff and and i was just doing an interview with a spanish journalist this morning who said did you ever think how lucky you got on that on that you know and first of all lucky on a pandemic it strikes you but had i had my druthers i would have kept that book working in my study for months more and the pandemic would have happened yes and that epis that would have looked like a chapter i wrote after the fact i would have to rewrite the whole thing it would have been so that argues for for what you said at the same time i i would have spent months more working on it because to me it didn't look the way i wanted it to look yet you know can you drop a hint of the things that you're keeping on the shelves oh the alexander the great podcast i've talked around the very i i talked to somebody the other day said do you know that the very first word in your very first podcast in the title the very first thing that anybody ever saw with hardcore history is that is the word alexander and because the show's entitled alexander versus hitler i have talked around the career i've done show after i talked about his mother in one episode i talked about the the the funeral games after his death i've talked around this i've specifically left this giant alexandrian-sized hole in the middle because we're going to do that show one day and i'm going to lovingly enjoy talking about this crazily interesting figure of alexander the great so that's one of the ones that's on the back pocket list and what we try to do is is um whenever this we're doing um second world war in asia and the pacific now i'm on part five whenever the heck we finish this the tendency is to then pick a very different period because we've had it and the audience has had it um so it's time so um i will eventually get to the alexander saga what about just one last kind of little part of this is uh what about the other half of that first 10-minute 15-minute episode which is so you've done quite a bit about the world war you've done quite a bit about germany will you ever think about doing hitler the man it's funny because uh i talked earlier about how i don't like to go back to the old shows because our standards have changed so much well a long time ago one of my standards for not getting five hour podcasts done or or not getting too deeply into them was to flit around the interesting points we didn't realize we were going to get an audience that wanted the actual history we thought we could just go with assume the audience knew the details and just talk about the weird stuff that only makes up one part of the show now so we did a show called nazi tidbits and it was just little things about you know it's totally out of date now like you know you can still buy them but they're out of date um where we dealt a little with it uh you know it would be interesting but i'll give you another example i mean history is not stagnant as you know uh and we had talked about stalin earlier and uh ghost of the offspring was done years ago and people will write me from russia now and say well your portrayal of stalin is totally out of uh out of uh uh it's it's outdated because there's all this new stuff from the former soviet union and you do you turn around and you go okay um they're right and so when you talk about hitler it's very interesting to think about how i would do a hitler show today versus how i did one 10 years ago um and you would think well what's new i mean it happened so long but there's lots of new stuff and there's lots of new scholarship and and so um yeah i would think that would be an interesting one to do someday uh i i haven't thought about that that's not in the back pocket but uh but yeah that'd be interesting i have a disproportionate amount of power because i trapped you somehow in the room and and thereby during a pandemic so like my hope will be stuck in your head but after alexander the great which would be an amazing uh podcast i i hope you do cons give a return to hitler the rise and fall of the third reich which to me uh i i have a contemporary book basically yeah yeah and i exactly it's by a person who was there shira yeah i i really loved that study of the man of hitler and i would love to hear your study of certain aspects of it perhaps even an episode that's like more focused on a very particular period i just feel like you can uh tell a story that it's funny hitler is one of the most studied people and i still feel like this all the stories or most of the stories haven't been told oh and there's listen i've got three books at home i'm on all the publishers lists now and they just young hitler there's this hitler there's that i mean i've been reading these books and i've read about hitler i read the rise and fall of the third reich my mother thought i needed to go to a psychologist because i read it when i was six and she said there's something wrong with the boy and but but um but she was right but she was absolutely right but uh but you would think that that something like that is pretty established fact and yet there's new stuff coming out all the time and needless to say uh germany's been investigating this guy forever and sometimes it takes years to get the translations i took five years of german in school i can't read any of it so um so i mean and and he is when you talk about fascinating figures he's so the whole thing is so twistedly weird um there was a it came out a couple years ago somebody found a tape of him talking to uh gender i want to say it was general um uh the finnish general manaheim right um and and he's just in a very normal conversation of the sort we're having now and you know the hitler tapes when you hear normally he's ranting and raving but this was a very sedate and i wish i'd understood the german well enough to really get a feel because i was reading uh what germans said they said wow you can really hear the southern accent you know little things that only a a native speaker would hear and i remember thinking this is such a different side of this twisted character and you would think you would always you would think that this was information that was out in in in in the rise and fall of the third ranking but it wasn't and so this this this is uh goes along with that stuff about new stuff coming out all the time alexander new stuff coming out all the time really well at least interpretations rather than factual data and those color your those give depth to your understanding yes you and you want that because the historiography people people love that and that was a byproduct of my lack of credentials where we thought we're going to bring in um the historians we call them audio footnotes right a way for me to say listen i'm not a historian but i'll quote this guy who is so you can trust him but then we would quote other people who had different views and people didn't realize that that you know if they're not history majors that historians don't always agree on this stuff and that they have disagreements and they loved that so so i i love the fact that there's more stuff out there because it allows us to then bring in um other points of view and sort of maybe three-dimensionalize or flesh out the story a little bit more two last questions one really simple one absurdly ridiculous and perhaps also simple first who is ben and is he real i don't even know what you're talking about very well how's that for an answer it's like asking me is harvey the white rabbit reel i don't know there's carrots all around the production room but i don't know what that means well a lot of people demanded that i prove i somehow figure out a way to prove the existence if i said he was real people would say no he's not and if i said he was if he wasn't real they would say yes he is so it's a santa claus easter bunny kind of vibe there yeah i mean what is real anyway that's exactly what i told him if it exists okay the most absurd question i'm very sorry very excited but then again i'm not what what's the meaning of it all you you study history of human history have you been able to make sense of why the hell we're here on this spinning rock does any of it even make sense what's the meaning of life what i look at sometimes that i find interesting is certain consistencies that we have over time uh history doesn't repeat but it has a a constant and the constant is us now we change i mentioned earlier the the wickedly weird time we live in with what social media is doing to us as guinea pigs and that's a new element but we're still people who are motivated by love hate greed envy sex i mean all these things that would have connected us with the ancients right that's the part that always makes history sound like it rhymes you know and when you put the constant the human element and you mix it with systems that are similar so one of the reasons that the ancient roman republic is something that people point to all the time um as a as something that seems like we're repeating history is because you have the two con you have humans just like you had then and you have a system that resembles the one we have here so you throw the constant in with a system that is somewhat similar and you begin to see things that look like they rhyme a little um so for me i'm always trying to figure out more about us and when you show us in uh 500 years ago in asia and 800 years ago in africa and you look at all these different places that you put the guinea pig in and you watch how the guinea pig responds to the different stimuli and challenges i feel like it helps me flesh out a little bit more who we are in the long timeline not who we are today specifically but who we've always been um it's a personal quest it's not meant to educate anybody else it's it's something that fascinates me do you think there's uh in that common humanity throughout history the of the guinea pig is there a why underneath it all or is it somehow like it feels like it's an experiment of some sort oh now you're into elon musk and i talked about this the simulation thing right nick bostrom's sure yeah the idea that there's some some kid and we're the equivalent of an alien's ant farm you know and we hope he doesn't throw a tarantula in just to see what happens um i think the whys elude us and i think that what makes philosophy and religion and those sorts of things so interesting is that they grapple with the whys um but i'm not wise enough to to uh propose a theory myself but i'm interested enough to read all the other ones out there so um i i let's put it this way i don't think there's any definitive why that's been agreed upon but the various theories are fascinating yeah whatever it is whoever the kid is that created this thing the the ant farm kind of interesting it's so far a little bit a little bit twisted and perverted and sadistic that's what makes it fun i think um but then again that's the russian perspective i was just gonna say it is the russian perspective a little bit of what makes the russians so russian history one day i'll do some russian history i took it to college that's the ant farm baby that's an ant farm with a very very frustrated young uh uh teenage alien kid dan i can't say i've already complimented you way too much i'm a huge fan this has been an incredible conversation it's a huge gift i your your gift of humanity i hope you let me cut you off and just say you've done a wonderful job this has been fun for me the questions and more importantly the questions can come from anybody the counter statements your responses have been wonderful you made this a very fun intellectual discussion for me thank you well let me have the last word and say i agree with elon and despite the doom caster say that i think we've concluded definitively and you don't get a chance to respond that love is in fact the answer and the way forward so thanks so much dan thank you for having me thanks for listening to this conversation with dan carlin and thank you to our sponsors athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases simply safe a home security company i use to monitor and protect my apartment magic spoon low-carb keto friendly cereal that i think is delicious and finally cash app the app i used to send money to friends for food and drinks please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and upper podcast follow on spotify support on patreon or connect with me on twitter alex friedman and now let me leave you with some words from dan carlin wisdom requires a flexible mind thank you for listening and hope to see you next time you |
Eric Weinstein: On the Nature of Good and Evil, Genius and Madness | Lex Fridman Podcast #134 | the following is a conversation with eric weinstein the third time we've spoken on this podcast he is the wise turtle master oogway to my kung fu panda one of my favorite people to talk to in this world a complicated and fascinating mind that i'm grateful to have the chance to accompany in exploring this world through conversation on this podcast and on his the latter called the portal quick mention of each sponsor followed by some thoughts related to the episode first is grammarly a service i use in my writing to check spelling grammar sentence structure and readability second is sun basket a meal delivery service i use to add healthy variety into my culinary life third is sem rush the most advanced seo optimization tool i've ever come across i don't like looking at numbers but somebody should it helps you make good decisions and finally expressvpn the vpn i've used for many years to protect my privacy on the internet please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that wherever this life takes me i'm drawn to the possibility of having many more conversations with eric through the years i think we have just the right kind of contrasting world views and a deep respect and appreciation of each other's life stories that creates for this magical experience in the realm of conversation that feels like we're always looking for something that we never quite find but are always better for having tried i'm not sure how or why the universe is connected eric and me but it did and i would be a fool not to trust its judgment and enjoy the journey if somehow you like this podcast please subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with eric weinstein who's the greatest musician of all time would you say we were just off camera talking about eddie van halen he unfortunately passed away who's the greatest musician of all time yeah jonathan richmond who's that it's a weird question so i'm going to give you a weird answer it's not because thank you okay jonathan richard the reason i'm picking on him is that he had a quote uh he was the front man of a group called the modern lovers and his quote was something like we have to be prepared to play music when our instruments are broken the electricity's out and it's raining something like that and i thought that that quote was very interesting because what it said was you have to be able to strip this thing down farther and farther back to get to something that is intrinsically musical so we were having a conversation just now about virtuosity and we're talking about eddie van halen and his recent passing and that affected me emotionally i don't know whether it affected you i was never a van halen the group fan but i i revered eddie van halen's capacity for innovation just i saw him like uh you know rodney mullen the skateboarder i had dreamed of having the two of them on the same podcast just to talk about what it's like to totally discontinuously innovate and he posted a video of spanish fly i think and saying like i didn't know the guitar could make those kinds of sounds like what is this voodoo movie is it well this is the thing right the arpeggios that he did on a single string are so fast and the attacks uh from the hammer-ons when they go at light speed as he did uh particularly and the reason i chose that was is that i wanted to strip out the electronics because part of the claim would be is that he's a rock musician and a lot of the innovations had to do with things peculiar to sort of the electrified setup you know his his use of the whammy bar for example or the frankenstrat that he built from different pieces right all of those aspects in my opinion are just dwarfed by his innovation and his musicianship and that's why i chose spanish fly because everyone of course will go to something like eruption or running with the devil which is the first things that they heard that let them know that there was a new force erupting out of southern california that was eddie van halen right i mean i just i i'm in love with i'm in love with the story of it you're often so poetic about music like it clearly touches your soul on some kind of on many levels what is that is it deeper than just rocking out with the uh in your convertible corvette 69 i imagine eric weinstein is driving down the california highways blasting some kind of music is it just like being able to be carefree for moments of time or is there something more fundamental that connects to like the theory of everything in physics and life and all that how often do you have the chance for example to hear mathematics performed as you do in bach right like something with that kind of precision and elegance that can't really be grasped where you know uh to go back to leonard cohen's uh famous line the baffled king composing right such a good song such a good song but it's also like individual verses of that song are insanely important um the the baffled king is how we often make music we don't really understand what did we just do that broke that person's heart sitting on the couch right and so it's a very strange thing that you should be able to have think of it like you're a computer you've got this weird open music port you know port 37.8 you know like it's not even it's not even supposed to be there and suddenly somebody starts playing guitar and they're making you feel things or you know like in particular particular instruments like the violin it's so difficult it's so unforgiving and when it gives up its secrets it just you know it it wraps its fingers around your heart and won't let go sometimes i talk about head heart and loins when something can grab your head heart and your loins at the same moment and integrate them there are very few opportunities to live like that and if you think about eddie van halen uh you know as far as your head the the musical innovations and the fact that he was drawing directly from the classical canon um you know really speaks to the idea that maybe rock is what um somebody like jimi hendrix saw it as being you know an infinitely extensible medium uh in terms of heart um i always notice the smile on his face it's painful to look at an eddie van gaal and solo now like sometimes you'll see the cigarette dripping off the side of his mouth and you're like that's gonna fucking kill you and i'm not even worried about it for you i'm worried about it for me you're gonna rob i don't even need to hear you play another note i just like knowing that you're in the world that there is somebody that everyone looks to that no but i've never heard a guitarist say yeah i don't know i think it was okay like i've never just never heard it you can hate him but you still think he was a genius there are very few people like that in the in the world and then loins those leaps that guy was incredibly good-looking and you know skin-tight pants super athleticism he completely owned the sexual the male sexuality of the stage both being the completely dominant you know sort of mythical alpha male i hate that expression but there you are but also this kind of little boy with this mischievous smirk and you know the sense that it all came together how could you not eat that up you could just imagine the millions of like young teenage boys who are just like playing air guitar in their in their room just that yeah basically dreaming of being that kind of god the the the most perfect example of what a human being can be yeah it's fascinating to think it is and and then you know as in many of the cases with these bands you get these multiple talents in the same outfit and i think that the original configuration with david lee roy i mean david lee roth is such a hot mess at all times i would love you to talk to david like if there that that dance would be just gorgeous i don't know he's can you handle it can you ride that probably not yeah probably not because i think he's very i i get the feeling that he's very smart and very uh dysregulated and i don't know that i could like like bring him down to earth for a moment well i can also get pretty disregulated yeah yeah and so i don't know i don't know whether it could be magic it could be a shit show i don't know what you thought of his appearance on rogan that was an interesting one i loved it but joe and that and joe does this sometimes sometimes he just sits back and listens and he just lets like the music play which works really well i think you have a chance to kind of jump into the chaos i care too and then you'll just start and the places you will go you may not even talk about music for like hours it might just go to this because he i think lives in japan like there's a weird he's a he's been in like an emt after he was a rock star he chose to be kind of like i don't know you know it it like there's depth to that man that uh that hasn't been explored by him either so i that'll be an exciting conversation can we go back to larry cohen yeah can we just i the things i feel when i listen to hallelujah by leonard cohen or anything by him really but that one what do you want to get into it let's go what what does it that song mean to you is it love oh boy well first of all it's it's it's mystery like it starts off about mystery so what are you what are you doing you're doing this alternation between the two chords so three notes at the same time one is called the the tonic or you have the the major and the relative minor and he's alternating between them there's only one note of difference between those two chords one of them would be feeling sad one of them would be more joyous typically described and so by altering one note it's the minimal amount to take you back and forth between joy and happiness as that's encoded in us so he starts off with it i heard there was a scene david played the please lord but you don't really care for music do you um that's really interesting because it's he's using this technique called bathos right so the alternation between the sublime and kind of the guttural or ridiculous or the mundane right so he's like uh there's a bitterness to it too is it just play well the way i hear it again you know great song allows for different interpretations you happen to be asking me so i'm going to impart some stuff that probably isn't in the song but why it speaks to me and that's what makes it great um the way i hear it is he doesn't believe the audience you don't really care for music do you then what are you doing listening to this you stupid idiots you know of course you of course you care for music you're too cool to care so i see through you and screw you that's like the kind that's that's the energy i get then he does this weird thing it goes like this is where he should put the description of where he is in the chord progression which is the tonic right it goes like this and then he hits the fourth and the fifth which are the two other major elements the subdominant and the dominant in functional harmony so he's describing the chord progression in real time in the lyrics there's two ways this can come about in other songs like we had this example of um every time we say goodbye do you know the song every time we say goodbye no i think it was a cole porter maybe or gershwin maybe porter i don't know i cry a little there is no love song finer but how strange the change from major to minor right like it's beautiful then then there's times when it's duplicitous so for example you'll have i guess my favorite examples of this are johnny cash's ring of fire i fell into a burning ring of fire then what does he do with the lyrics in the tune i went down down down it goes up yeah right and so the idea is like oh okay that was a head fake yeah right and another one of these um you know is nina simone's feeling good oh okay so what do you get a bird's flying high you know how i feel and sun up in the sky high you know how i feel that woman's voice she doesn't give a damn yet she's and i'm feeling but then what's the dude yeah it's like heavy stripping music it's it's you're not in a good place you're probably in some strip club with the last of your money you're drinking lousy beer some bad situation yeah and she's feeling good no it's funerial it's oppressive right i never thought of that song that way wow well you think of it as joyous yeah no no if you think about it contrast it with ray charles for example you know do you know do you know lonely avenue well my room has got two windows but the sun never comes through it's really depressed it's the same sort of vibe as nina but she's claiming that she's in great shape so she's like a good case of the unreliable narrator leonard cohen to me is talking about the unreliable audience that's too cool to be with the performer on stage the things that go with the music like the cole porter stuff they go against like the johnny cash i think these are the games that musicians play that the rest of us only sort of notice subliminally okay fourth the fifth and then he when he he should say something about the relative minor or the he's giving you the secret the baffled king in other words he doesn't know why it works did paco bell know why pachelbel's canon would work yeah it was a discovery that's the whole thing like some music is discovered and some music is invented and he's talking about a musical discovery he's talking about the pythagorean power of the wave equation and then superimposed like there's two genius intellectual concepts behind music one of which is the wave equation usually we solve it for a one-dimensional medium because we're talking about strings or air columns occasionally you're talking about things like hand pans or steel drums or metallophones or gamalons whatever and those have a wave equation too that's much more chaotic the other equation is this crazy thing that 2 to the 19 12 is almost exactly equal to 3 which is what gave us even temperament and so the tension between those two things is in fact one of these most beautiful stories inside of that system that formula of the baffled king is a discovery it's not he's not really composing it the reason he's baffled it's imagine that you took like a little brush and you started brushing off uh you know a pyramid under the sands you you might think that you created the pyramid by your brushing but in fact if somebody else did it that's why you're baffled right that's beautifully played you're right and as as creating one of the greatest songs of all time and as he's doing it he's baffled and he's in his mouth he leonard is within the song and he leonard is baffled is my my contention but he knows enough to know that he's baffled right and so the idea is that he is composing he has the audacity to compose as david he's echoing david at a minimum and then in a later song which i really wish we would discuss that's totally dystopic and you will not like it at all uh is the future which contains this line that i i think i used in my episode with roger penrose on the portal uh note the subtle plug the portal the portal i'm the little jew that wrote the bible so there is this way in which leonard cohen i think is constantly coming to the idea of being a biblical-like scribe and i think this is one of the great things that you know you see dylan doing this with all along the watchtower you saw warren zivan who we should talk much more about doing this with a song called i was in the house when the house burned down do you know this thing no this is embarrassing sweetheart that's a great day warren zivan is one of the most important songwriters of our time and he's been largely forgotten uh by this generation but you know bob dylan uh would sing one of his songs in tribute i've heard bob dylan you know very small number of songwriters really move him woody got three gordon lightfoot and uh warren zevon by the way bob dylan if you're out there appear on either one of our podcasts we need to get your voice into a new medium for a new group definitely this is a time this is a time for bob dylan my friend honestly you've been doing an amazing job in this space one of the reasons i'm super excited to do this podcast again is that i've learned some things about what i don't do well and i also have sort of struggled with the question should i do those things better because what if it's you know i always use the same example of the fitted sheet when you're trying to put a queen-size fitted sheet on a king-sized mattress he's like okay i got that corner squared away and then you get another corner that pops off and then you go back around i wonder whether i can improve my style in the ways in which uh you know i think it's just a recognition of a difference you do a better job of getting to the soul of a really top intellectual guest and making them accessible and presenting them as themselves for a huge number of people and i'd give my tooth to be able to do that do you ever think about this like because i think about what is the greatest conversation i'll ever have you know like in in a sense the portal not to reduce it to anything but there will be the greatest conversation you may have already had it but it's very possible if if if enough people like me can keep twisting your arm to keep doing the portal please that is there'll be an amazing conversation one of the questions that i ask myself is like who is the person that i'm especially equipped for some reason i'm convinced on putin there's something in my head that says i i i can do this man better than anyone else in this world i got this thought in my head about it i don't know why and i'm convinced but i think the universe works in that way like if it tells you it's kind of happens the way i would say it is is that almost everybody who becomes a supreme court justice believes at a very early age they're going to become a supreme court justice many people believe at an early age that they can do it don't get there but of those who get there almost all of them had this sort of well i call it pathological self-confidence and i do think you have pathological self-confidence and you also have humility and most people would hear those as a contradiction i think that you would not be able to get away with what you do if you didn't have the humility and so i think you know the great danger is that your equation becomes unbalanced that you either lose the humility or you lose the the humility overwhelms the ego and the drive because right now you've got a mexican standoff in your mind and the rest of us are just benefiting that's beautifully put my mexican standoffs aren't as stable as yours it's all reservoir dogs all the time yeah but um actually the person who that describes is peter thiel peter thiel thinks more dif people always say like what does peter think about x y and z p and q it's like well do you want communist peter do you want hyper peter in there oh my god right on everything that's why he's successful is that he's got all these minds fighting each other and so when people say peter is this repeater is that i just laugh because it like nobody who knows him would describe him as having thoughts at the level that people are claiming and i do think that you know in my case um you know there's also pathological epistemic humility like just i know i know how little i know how little i can do in one life i know how many things i've screwed up i know how many things i've got wrong and on the other hand i know that if if not you know it's like hillel's questions you know if i'm not for myself who will be for me and if i'm only for myself what am i if not now when you know at some level there's a question about if i don't decide that someone is capable and that somebody is me and i if i apply that to everyone else on the planet then nobody's going to do anything and so i do think that one of the things that people like you and i get is who are you to say that right f that man just sign me up for some dunning-kruger yeah but it's multiple minds like you said like this morning i was feeling so good and confident about i couldn't think no wrong and i remember last night clearly thinking that i'm the dumbest human who's ever lived yeah and nothing i've ever said is worth anything what the fuck am i doing with my life why am i scared i was terrified of this conversation who the hell is my conversation because i'm an idiot and because you know lex but no no but this morning [Laughter] i was the baddest motherfucker who's ever walked this earth so it was i was very conscious i think it was the coffee i'm not sure maybe some sleep this sounds very russian and it involves multiple beverages some of them being alcoholic others containing caffeine there's in fact i can't share the story behind it but there is a bottle of vodka in the fridge okay so i mean i should have hate you for coffee because this is a morning there's a morning show here so i put out a call that we get a chance to have this conversation and people ask these wonderful questions a few people asked about depression and suicide it's a this this is a russian program so we'll have to go there and i think about leonard cohen and one of the things that always kind of um broke my heart and kind of suffocated the hope i have for just uh i don't know for love in a person's life is to hear how much the how much depression was a part of leonard cohen's life and how much he suffered see i guess one way i'm not sure where we can go with this question but do you think about the places that the mind can go like these dark places yeah is there something like where the only escape out is suicide for example that's the darkest version of it that i really think suicide is a big place in suicidal ideation and self-harm and we don't talk a lot about it um it's it's a similar problem to trying to talk about trans these are umbrella categories and if the commonality is that somebody harms themselves but we don't know whether that's coming because of a problem in brain chemistry because of an event in their life um whether evolutionary programming for suicide is weirdly normal whether or not it might have a religious motivation there's there's too many different forms of self-harm and something like the 10th largest killer thereabouts and i think that you know you can look at it from different angles i i'm old enough to have you know had pete seeger come to my college when i was at university and to watch his good humor in the face of all adversity um i think of odetta i used to go to odetta concerts any i don't know if you you know who she is okay this is going to be one of the better days of your life check out odetta when we're done with the interview um she was a civil rights figure but also just had a profound voice and great musicianship these people were in the struggle right and they they saw lots of bad things happen and they kept their humor about them and you know the thing is that you can take on the velcro merits you know the pain of the of the planet or you can try to do something else which is to be a happy warrior even if the odds are terrible and the and the cost of failure is catastrophic so even when surrounded by darkness but the thing is with leonard cohen is he created such beautiful music and yet it's like anthony bourdain the same and yet they go to this dark place and it could be it's easy to say it's just biochemistry no there's a linkage between this highly generative creative side and in some cases dark depression in other cases not so you can't say that it's tied the genius and madness are always you know co-traveling or the beauty and pain are one and the same what you can say is that there's a cluster of people that tell you that for that cluster there is a relationship between the darkness and the beauty and i do think that in part it's squaring circles that can't be squared you know that well we're just talking before about the inability to serve two perfect systems the perfect system of the wave equation and the perfect system of even temperament they're both perfect they're not compatible and once you realize that there is perfection and an inability to make contact with perfection i think you know you recognize that um there is no solution to this world yeah that's weird with the poets and musicians do you want to say this is a particular thing that you do but then there's spanish fly by van halen and then you realize oh well what do you get out of spanish fly by david i i think it's very singular because of its the fact that it's purely acoustic for some reason i always i couldn't imagine eddie van halen separates from the band in front of thousands of people just screaming and rocking out with lights everywhere and spanish fly made me think like you made me imagine him sitting alone on a couch in a room i think that's who he was i really do i mean i i it's believe me i get it it was a rock star it's a rock guy got it got it got it got it i'm almost positive that you can't get to where he got to without being a complete introvert yeah like it made me imagine that there's like some half naked supermodel walking around hoping that uh they can you know do their thing together and and he's completely disinterested he'd be able to be with the guitar right yeah because like honestly at some level in one case you know maybe you're maybe you're conquesting maybe you're pursuing love and romance and the other case you're talking about a relationship to the to the order the creator the almighty whatever it is you want to call that substrate that is reality and you know do i believe that eddie van halen and jimi hendrix and paganini and heifetz jacked into the you know the true essence of the world yeah they did i don't think it's as good as differential geometry i'm sorry i do think it's amazing for other reasons and thank god because it's very difficult to communicate differential geometry at scale but the thing about eruption for example what level do you want to come into eruption do you want just the sheer majesty and pageantry do you want the theatrics like you could put him on on wires and you know set his pants on fire or whatever and you know it'd be it'd be totally in keeping with it on the other hand you want to talk something completely precise that you know shows off the virtuosity of what's possible with the stratocaster everything works multi-axis but there's a precision to it which and which is very different than hendrix there's a messiness to hendrix that to me somebody who has ocd has always been how does that affect you i mean let's have the jimi hendrix conversation i don't know that we can do anything to it that hasn't already been done to it maybe that's not true maybe the idea is that every generation has to have its hendrix conversation and this is a long time it's johnny hendricks experience yeah it's so funny yeah i hear he stole it from joe rogan yeah there's so many details one it hurt my soul on so many levels that you can put a thumb over the guitar to to play a note to hold the note and it doesn't because i want it to be the russian virtuoso that sits with his classical guitar and a perfect form plays really fast with the fingers and and then you don't want you want the thumb to be perfectly relaxed and supportive that's the russian conservatory student conservatory yeah then there's like the russian wild man which one is that well haven't they're different russian archetypes right so the completely idiosyncratic russian is very different in a weird way from the uh you know i can do this backwards in any key in any sli in my sleep in in any time signature that you you know just just snap your fingers we've discussed my uh piano tuner in previous episodes no no that was offline conversation you told me the story but i should tell you this you should you should re-tell the story there it was in darkest manhattan yeah with the world's shittiest uh it wasn't even an upright was a spin it piano a friend had given it to me the piano fell out of tune and i would have to tune it and the only tuner i knew was this russian guy and i hated dealing with him there's something about his attitude just really rubbed me the wrong way so anyway my wife says tune that thing so we get the piano tuner to come and he's tuning this and he's like are you sure are you sure you want to tune this this piece of shit you know okay fine so he's like okay it's your money the phone rings and i have the the phone ringer set on a landline to paganini caprice 24. and immediately as the phone rings he figures out what key the phone ringer is and which is not the key that like list composed the variations on on uh caprice 24. and he starts going into theme and variations on caprice 24 at some level i've never heard before just jaw dropping it and like the phone stops ringing and we have this awkward silence i said i didn't know you were such a great piano player and then he says one of these things and in you know in russian accented english hurts in a way you can't imagine no you are the piano player i am merely the piano tuner i was just like oh man through the heart you know it's kind of reminiscent i'd love to hear actually your opinion this is reminiscent of the goodwill hunting story what do you think about that that movie that movie it's about it's mit yeah i guess when i think of that film i think about matt damon as a young guy risking everything giving up harvard i think you know probably the most accomplished group of people in the world are people who choose to give up harvard voluntarily it's beautiful right that's true bigger than harvard you know ives was one of these people um bill gates of course uh and then oddly uh you know zuckerberg what zuckerberg but then steve jobs gave up a read and read is like the weirdest craziest college in the world people should pay much more attention to read and i'm sorry it's going through a hard time at the moment but what it was before the current craziness is really an interesting story irregardless as we say in the 617 area code um i think that a lot about a lot of my reaction is to the the real story of matt damon uh having this vision and being the young guy to pull it off and you know i also think about robin williams trying to explore heart through this lens of acting and you know as you and i you've hung out with comedians they know that they are a screwed up bunch of people they do they'll they're proud about it they really are the idea that robin williams who i saw many years ago when i was in la um in the comedy clubs around here you know he was a straight-up crazy dysregulated genius in tremendous pain and his desire to do it earnestly through acting rather than constantly by just sniping you know or or being a clown or or showing us how fast his mind worked relative to ours um i i was really moved by that i thought that he he brought some authenticity and took a huge risk for a comedian to be that real and again like you said it doesn't always have to be but in that case the madness and the genius were neighbors that one couldn't have been any other way yeah no because his mind you the thing about seeing him in a comedy club was that he would react to random stimulus in the environment you know it could be a heckler sometimes he almost got the feeling that he wanted a heckler because it was it gave him something to play against right he was just he was infinitely instantly inventive but i actually to me the best robin williams is as he got closer and closer to the end of his life because there was a sadness and he's almost fighting the sadness with this improvisational like the weapons he has is this wit and humor and this dancing that he does with language but and then sometimes when you just fall silent you can see the sadness and and i don't know there's something so beautiful about that it's like this bird with a broken wing that's like trying to fly you know and it's getting older and older and i mean those he would have made a one hell of a podcast guess i'll tell you i'll tell you that that's a sad um yeah i have some sadness that i really do think that part of what we call podcasting is actually just getting to know a soul right over and over again like yeah maybe the idea is that this is talking about depression and sadness and heavy feelings is not an american specialty seeing that in context with the beauty of life is a russian specialty like it is very much special it sounds like a diner menu what yeah what the a big scoop of ice cream with tons of depression i i do think that we're in a really terrifying and depressing time and i think that part of it is we don't know if something huge is about to get started and we don't even know what this is i mean we just sit here in this weird world that is falling into some new state and we're not even super curious it's like what the hell just happened everybody's got an answer and i'm positive that all of those answers are wrong let's let's try to at least sneak up on the good answer so the central core of the answer is that the us seemed to be the greatest thing in the world in large measure because we hadn't noticed that we were getting a benefit from having no plan not having to make a plan for low growth as long as we had growth we were in great shape let's imagine that there was a that you could run an experiment you have a billion copies of earth and you start the initial conditions slightly different on some giant number of planets a lot of the things that were discovered from the 1800s through the end of the 20th century are discovered in a period of time because a lot of that just has to do with once you crack the puzzle of getting better instruments you can see more and the more you can see the more you can make use of what you can see and it turns out there was lots of stuff to do with like you know germs or electron orbitals or you know spectrum electromagnetic spectrum and so we got to do all of those things and the us roughly corresponded for a good chunk of its history with this bonanza and so of course we look like an amazing genius country we have no plan imagine that you you could sell a car you don't have to put in seat belts you don't have to put in airbags you don't have to put in rear view mirrors or sensors or a rear view mirror you could save a lot of money on a car by not putting in all of the stuff to keep things from going wrong and i think that's what we had we had a machine that as long as growth was insanely good we plowed it back the riches and spoils and then treasure back into the system and made more genius stuff and we carried along a good chunk of humanity hundreds of millions of people we did not have a plan for what happens when the growth goes below the stall speed of our society how confident should we be that the growth has slowed in in a way that uh is permanent rather than a kind of slap in the face where is that the right concept right concept is i i try to use the same words over and over again in case people see mold because then the perseveration actually gets somewhere so i use this analogy of the orchard because everyone talks about low-hanging fruit they know the concept of low-hanging fruit but they don't think in terms of orchards so they say things like you think we've picked all the low-hanging fruit but i believe in the infinite inventiveness of the human mind yeah it's like okay that doesn't even work as an analogy what if the idea is we only picked all the low-hanging fruit here and then we're having this stupid argument about low-hanging fruit and we're not going and looking for new orchards we're not planting new orchards we're not looking for forests we're we're just sitting here arguing about low-hanging fruit so my claim is there's probably a lot more low-hanging fruit and it's not here it's in other orchards it's in other orchards one of those turned out to be the digital orchard the digital orchard has not been a stagnant as lots of these other like the chemical uh orchard you know i have faith that there is a small percentage of the population but not zero that's looking for those other orchards like i'm excited about one of those orchards which is i believe there will be robots in everybody's homes and that will unlock some totally new thing totally new set of technologies ideas the way we live life the productivity all the everything it'll change everything so i'm excited about that orchard so i'm si you know i'm roaming that orchard and wondering how the hell you kind of bring back like the ant that finds a new source of food yeah i'm trying to find an apple i can bring back to the the great so you're in an you're in in an explorer idiom and you have faith that there's enough of those i don't think there are very many of us i mean i'm one of them too yeah how many does it take it takes one hand it takes one end what are you talking about how many uh elons does it take to screw in a light bulb okay let's imagine that we went imagine some ant goes and finds a new source of food yeah right and then it comes back to the colony and it says hey i think i found a new source of food and the initial reaction is you're not you're not authorized to find new food what why would you try to go find new food we're going to remove you from twitter yeah and by the way i think the fact that you think you're allowed to go find you shows how privileged you are as an aunt get out of the colony kill him kill him well that's probably not a great model for finding new orchards and i think that what we find is that where there's a system that allows somebody to ascend without a lot of gatekeeping you can have that but you know i saw this happen in hedge funds hedge funds for a while uh hoovered up a lot of talent because they were places that had funding and had freedom and in general really smart people want to be free and they don't want to think a lot about how they're going to you know feed themselves they want to get lost in their minds so you can either give them productive places to play dangerous places to play you know they're either going to break into computers or find vaccines for you or build bombs or build companies and we're not providing for the people who have to disrupt and have to innovate and trying to channel that effort we're so focused on this other thing which is like fairness and safety and fairness and safety by the way are really important i don't want to denigrate them but the singular focus on fairness and safety without in the same breath being focused on growth and discovery and creation is going to doom us because what we're talking about is we're always talking about divvying up the pie that is as opposed to the pie that will be imagine that you spent all your time trying to divvy up the 13th century pie and you destroyed your ability to get to the 20th century you'd be an idiot but one place i think i disagree with you is uh i don't think you need that many people to empower the geniuses the innovators the people who refuse to spend most of their days in meetings about fairness this is good uh-huh let's have a disagreement i think podcasting whatever you call that medium it's just one little example of a tool that you can give power to like you and your podcast can have the next elon musk and make him a star now i see where you're going okay there has been a series of places for people to play and be free and we've lost them successively what's a good place you remember because i disagree with you there too i think they're still there you can still play you interviewed noam chomsky yes okay noam chomsky comes from an era where you can play where you could play at mit at mit and you can't play this is where i disagree with you we've already had this but go check the clips channel for the lexi friedman podcast i i think i wasn't brave enough at that time and i'm not really brave enough now come on because that's the vodka uh it's a feeling and because people are going to tear me apart oh what are you and and you speak from emotions and facts the feeling the podcast is this it's yours yes okay tell the people who are currently editing your brain because i saw that move right now yeah that they should go find another podcast right let's get rid of some of your audience right now yeah please go find another podcast if you're editing my brain nevertheless all the self-doubt they're sitting in that brain so i can't stand to watch this but all right okay what is the self-doubt loop that you're in the thing is when i walk the halls of mit yeah there's bureaucracy there's administrators that never have done anything interesting in their entire lives there's meetings there's all these crowds the usual crap but there's in the eyes of individuals yeah there's this glow of excitement has nothing to do with career i understand this and and that's just it's still a playground there's little little pockets of playgrounds from which genius can emerge still and they're unaffected by diversity meetings or fairness meetings or or blah blah blah i love to hear this yeah but you don't think so i don't believe it because i've watched the change lex i've watched people and we're all editing ourselves all the time i remember my old mind i liked it better all of this relentless focus on critical race theory and you know critical theory post-modernism fairness social justice it's making many of us into worse people you think that's that do you think the mad demons are of you know the character is paying attention to any of that you think that has enough have you seen what happened to matt damon himself matt damon has tried to say various things at various times that seem to be relatively innocuous he can't can't speak okay well let's let's not mix up matt damon is just an actor well no no he was just a harvard student who came up with his own genius screenshot acted and made it happen no yeah no but we're somewhere else you don't think you can build the rocket company no no i think that there are things that you can still do but we're losing them we lose them we keep losing them i would say the biggest problem here let me just say like what i think the solution would be is to fire anybody who is doesn't like who's not like faculty especially young faculty should have way more power and administration should have much less power because right now the administration which used some of the who used to be faculty but they've lost the fire the spark that gave them they've lost the memories of the playground and so the people that admire and love the playground like you could see it in their behavior should have way more power and so we should create a systems that give them power you're very idealistic yeah and you're very you've got a huge heart it's a weird time because i don't want to dissuade you from believing beautiful things um because i see how potent you are you you do all these things jiu jitsu guitar podcasting programming computers um etc etc i don't think you're right i think we're in a really deeply screwed up place where even the tiny number of let me give you an alternate version of this dystopia i do think that there are people who are capable and there's still places to play and cause things to happen that progress the story forward but if you look at the fire that some of the people are in who fit that profile like how much crap has elon musk taken quite considerable right and not much at admiration from the craig venter jim watson these are very difficult people steve jobs is a very difficult guy you know yeah it is a bit heartbreaking to me i mean everybody is different generations i just my mind is a little focused on elon musk because he's the modern person well you know him i mean he's a person to you i it hurts my heart to see how few faculty and uh people with nobel prizes and so on uh admire eon like how little prop he gets he gets a lot of fans from like people who buy his products and you know young minds yeah just excited but like why don't we as institute why doesn't mit say that we wanna we we somebody amongst us will be the next elon musk and we want to encourage them it's like say that say that in a meeting say that like that's success no kidding for us as mit and they instead there's this jealousy it's like well here's the did you hear what he almost tweeted did you did you see like how responsible is what he's doing how the the like just saying all these things that are just dripping with jealousy and basically i want what he's got that's the thing right and then if yeah here's the weird thing rivalry has a different signature you see when you know that you're never going to make it yeah that's the position you take what is it in kung fu panda which you've watched now yes yes what does tai long say when he's looking for the dragon warrior and the furious five come to defeat him on the bridge one of them gives a poe's name accidentally and tai long hears it po so that is his name finally a worthy opponent our battle will be legendary right he's excited why is that well you learn about this in boxing sometimes you'll see a division or an mma which is lousy with talent just you can't swing a cat without hitting an amazing amazing athlete sometimes you'll have a division which at that particular moment has one star and no real competition in that weight class or something that person is in bad shape because you can't build a legend without the other when you think of muhammad ali what are the names that you immediately think of now you have to fraser you have to think of the other ways listen right yeah so those those opponents are in part what made muhammad ali muhammad ali and that's you know that that's why the the the mayweather um mcgregor revelation that okay this guy's got his opponent's picture in his house how weird is that well because without the opponent you may not be able to get there now i am not a huge fan of the wrong kinds of rivalries you have examples in mind well there are rivalries where people take each other's credit and screw each other over and then there are other rivalries like the rna tie club where these guys were so in love with what they were doing that they couldn't wait to share everything and like nobel prizes were so abundant that you know most people got nobel prizes just for being a member of the rna tie club and doing cool stuff and yeah that's that's the golden that's the golden kind of sweet spot um most of these people can't do what elon's doing because they can't break rules they can't take the pressure i'll tell you what really concerns me about your perspective i think that there are a lot of genius ideas inside of people who don't have the stomach for conflict and derision and i think a lot of those people are female and i think that until we come up with a world in which we can swat down the trolls where we can actually cause the trolls not to ruin everything and i don't necessarily mean by shutting them up i don't necessarily mean by being brutal to them but somehow separating off people who are working in people who are trolling i think that we're losing a huge amount of human genius in part because women in particular are not necessarily going to push an idea if it results in 10 years of being derided very few men are willing to do that either but there are some of us who are so dumb that we will pigheadedly stick to an idea for 10 years even if the world collapses i don't think that there are as many women who are going to make that calculation even if they know the idea is correct and one of the things that i believe technology can help us fight the trolls of all definitions of troll like i believe that a better twitter can be built interesting i do not i don't believe that a twitter successor can be built that solves most of the problems i think you can always improve what we have but i don't think that converges in something that really works because i think ultimately the problem isn't twitter the problem is us for example i've recently made a very disturbing realization which is academics and trolls have very many similar behaviors absolutely it's largely a trolling community i tend to believe that the trolls are not it's like the peter thiel many mind idea yeah which in all of the trolls there's the possibility of goodness and all you have to do not all you have to do what you have to do is create technology that incentivizes them to uh to embrace to to discover to embrace to practice the the better angels of their nature and i believe that like the people actually want to do that the trolls is a short-term dopamine rush of uh childish toxicity that all of us want to overcome i believe that like deep within we want to overcome that i i try to keep myself from believing what you believe because you'll be disappointed if it's not because it's dangerous because a lot of these people are implacable foes and there aren't many of them but when you meet somebody's like yeah i just like screwing people up i'm here for the pain i i just believe even in them there's a good there's a wonderful book that i'm going to recommend to you where i hope this comes from maybe i've got the source wrong but in any event it's a great book called the maximum city about bombay and i believe the the conceit is that the author leaves bombay as a kid and comes back as an adult and he realizes he has to rediscover the city because he can't live in the city he left so he gets in contact with all of the weird areas of the city and one of them is the underworld he hangs out with the police but in the underworld he's talking to contract killers and he says you know it's really weird everybody pleads for their life right before i kill them and they always say this thing about i've got a i've got two kids at home he says never say that to a contract killer because we have terrible relationships with our parents it doesn't endear us to you and that's just like oh wow so there's a minus sign in front of that statement you're sitting there saying you know i've got a three-year-old it's like okay well i'm going to take this pos out of out of that kid's life maybe he'll have a chance you don't know how people are wired and as much as i hate to say it there are people whose wiring is so disturbing and so different from yours that you will never guess why you can't reach them or how much pleasure they may have gotten because they may have gone over a point of no return nevertheless you are just a smart guy who is using his intuition to make a hypothesis you do not know this for sure no and i am you know whatever the hell i am uh that has a different hypothesis that even in the darkest human beings that that seem to be only full of evil there's a good person there that could be discovered and that's one of the reasons i love doing your show is is that you have these beliefs even as a russian [Laughter] the russian special as you know the russian there is a weirdness which is a total cynicism and total idealism yeah locked together right that's very much part of the russian character the reason i was i was kept bothering you kept bothering to have this conversation is i'm really worried about the next couple of months no kidding and uh if there's anybody in this world that could help alleviate my worry by um by at least walking along with me through this worry of mine it's you do you think we're headed towards some kind of civil war some kind of division that explodes beyond just stuff on twitter but something that's really destruct destructive to the fabric of our society well i believe we're in a revolution as you know i've called it the no name revolution or n squared revolution i've been talking about it for years i don't think i think waiting for this to be called a civil war is not smart only history will cause such fine but i think that the problem is is that you're encountering things that you've never seen trying to fit them into things that you already know right and but history repeats itself yes ish you don't see lessons from history and i do we see today but i don't see it repeating itself you know the the violence the famous quote is that it rhymes it rhymes i mean the thing i guess i'm speaking to is violence and we're in there the abstraction of violence imagine you were coding up violence as an abstract class okay thank you for speaking to the audience trying to lose these people come with me go on i don't know i i i've dealt with your audience and your audience contains the smartest people around yeah i guarantee you if i say some stuff uh first of all any wrong thing that i'll say they're gonna detail so that'll be a little bit of catnip to bring in the smart people but they'll also digest it for each other it's one of the great lessons of long-form podcasting if you don't if you don't waste all your time explaining things that's the job of the audience to do amongst themselves they're happy doing the work and those who aren't they leave isn't that great they'll leave the people who don't want to struggle will leave you can get rid of them i think that the point is you you would want to say violence is defined relative to a context so let's call it meta violence so that we don't get into the the problem we already have a term for physical violence right so we have meta violence and physical violence i would say that physical violence is subclassed from meta violence meta violence is the disruption of a system it's sort of you know it's a you know if we for example if a cell dies you can die through apoptosis or necrosis apoptosis is controlled programmed cell death uh necrosis is just like okay this didn't work that was a violent disruption of the system and this meta class is presumed in the documentation is it all negative no what are you talking about so this is part of the problem and the madness of our age right which is if you if you open up a drawer in your in your cabinet right in your kitchen and you see knives spoons and forks do you have a sense that the spoons are good utensils and the knives are forks or bad utensils because they're mean i mean like if you start thinking in these terms yeah that knife is there to do violence that's violence you want done right when i cut a mango i'm doing violence to the mango the mango expects that i will do violence to it because otherwise i won't be able to get the the meat and it won't get its seed um spread somewhere else so in part violence is absolutely part of our story so okay so there's this meta violence class yeah and what's so the metaviolence class is already you know it's a multiple inheritance pattern whatever's going on right now inherits from meta violence no but there's there's certain subclasses that allow evil to emerge so what what what i'm specifically worried about is that what's on your mind lex what's really going on okay i i worry that um amidst the chaos of we have these protests or the chaos that could be created by the feeling that the election does not represent the the voice of the people like saying that whoever gets quote unquote wins the election according to the some kind of reporting of the numbers that come out that's not going to represent what people actually who people actually want to be the leader like something in that narrative will create so much division that people will resort to literal violence like protests that really that the united states loses its united aspect and because of that because of that chaos and tension evil evil people evil forces that my definition of evil is you know just cruel human beings use that moment to attain power the kind of power that is ultimately goes against the ideal of the united states that could be donald trump that could be another human being it doesn't really matter my my worry is that love doesn't win out in this the unity doesn't win out in this and i feel like you and i have responsibility no small yeah i know and so how do we let love win in this moment of we're gonna potentially you're gonna have to become a fighter you have to you have to throw some serious punches if that's what you want you have to be muhammad ali here because the moment you start criticizing anything yeah people you have to be a masterful communicator because that's why you're here look lex in part your decency is allowing you to do things that you couldn't otherwise do i saw that you had michael malus on your podcast yeah now michael malus is i think of somebody who at his best is extremely shrewd and insightful yes he's also got this trolling game which he's quite open about and you talk to him about it which i can't stand and that's this is the idea oh grandpa doesn't get the internet well i'm grandpa i don't get the internet i don't love the trolling yeah there are trolls of the past who were incredibly good i don't see any of the modern trolls as being that kind of genius level trolling the people who deserve it in the way that they deserve it you know right now what i see is that anything that stands up gets cut down yeah you know it's like anything earnest you have to turn into cynicism and a meme and it's this idea that the people who believe that the world is chaos and has no point are constantly trying to let you know don't try to use the internet for meaning for decency for goodness because we are going to find out that that's all sanctimonious hypocrisy and we will we will make you suffer so i do think that there's a lot of sanctimonious hypocrisy in the world some of it mine some of it yours but we all have it and the trolls somewhat remove that but it's not a judicious kind constructive compassion a caring version most of the time and a lot of those trolls and i i have this feeling about michael malus i don't know whether it's right that there's somebody who deeply cares and loves beneath it and that that's motivating some of the trolling behavior and you and i don't seem to be doing that i don't see you as almost ever trolling yeah you and i are get i i'm very much against trolling i'm very much against trolling it doesn't mean that it's selective you know i'm not even it's not even true like everything we say we say like i'm forward i'm against it this isn't my native language i speak nuance i don't speak this internet shit and i the more i have to communicate through internet shit right i almost never take a tweet seriously if it contains the the letters lmao lol rtfl you know fol there's a interesting effect where people say stuff and then finish with lol you put it beautifully that it indicates to me that this is a person we've talked about like why i wear this stupid suit yeah it's like this is anti this is to fight the lol at the end of sentences is take it's like stand up for the words you're saying yeah don't finish stuff with lol removing completely the responsibility of the content of the sentence that preceded it yeah also choosing the outfit that worked both for men in black and the blues brothers not a terrible choice okay but getting back look lex we're not in a position to do this you need to be seated in a different chair your chair is the wrong chair you're in the wrong chair it's been so long all right i want to talk about you and joe biden joe biden was a 29 year old guy with nothing particular going on so far as i can tell okay i know people as impressive at age 29 as joe biden you know 12 rows back three three deep doesn't matter huge number of people none of them my age can get to where he got like we're all morons anytime somebody takes out like if you found eddie van halen in a guitar shop you'd be angry what is this guy doing repairing guitars then somebody said maybe he loves to repair guitars yeah i mean what is your piano russian piano tuna doing what is my russian piano that was the whole point of that story which is what is it that happened in that life that converted somebody and i find this for example with russian doctors who are you know technicians in offices now there's a huge amount of talent in the world that's not sitting in its proper seat yeah and quite honestly i've gotten to the point where my feeling is we've got to take the seats right maybe we don't sit in them maybe the idea is that we take the seats and we put some smart gen z person in the seat and say look no chanting i don't want to hear you say no justice no peace if there aren't verbs if it rhymes it's wrong like i used to have this thing rhyme things that rhyme are more true but like in general if something starts at one two three four i don't wanna hear what the rest of your sentence is yeah but i i feel like the responsibility that you carry that i carry this is where joe rogan generally removes himself from being i'm just a comedian this idea of i'm just a comedian i'll do that but at this moment in history like history literally can pivot on the wards of a tattooed ripped 50 year old you know comedian and i think the same is true with you okay well i'm i'm interested and i care speaking of lyrics uh you know there are many here among us who feel that life has been a joke that's not us the hour is getting late that's not us in the song the the joker and the thief are on opposite sides of jesus having this conversation over jesus you and i we've been through that that's not our fate that's somebody else's fate to throw spit balls at the internet that's not your fate you're an earnest guy you're filled with love you're getting the most amazing podcast guess you're right over the internet this is the point i'm trying to make that you're saying i'm i'm i'm just a grandpa i don't know the internet no i'm telling you you're going to get bigger and then you're going to get cut down you're going to keep ascending for a while lex and then you're saying and naturally there's i'm telling you i watch the same process people get up to a certain level and one of the things that's going on in my opinion with joe rogan is is that when joe rogan starts to talk about his misgivings about joe biden you know in a way that you find at any bar in america about cognitive decline in a 77 year old who's about to be 78 i believe in november we have never had anything remotely as insane as a 78 year old person slated to win the white house and you're saying when that idea that is is being communicated is there something that's about the disc concept do you talk about the system naturally bad thing happens to joe or one of joe's close associates the ability to destroy people who become inconvenient has been documented this is what we have done in the past whether we are doing it now we don't know because we are not doing this church church committee to in order to know whether or not you are currently destroying american citizens as we did in the past as we have documented as we found out in 1976 the federal government destroyed americans who had political beliefs that the government didn't want to continue and i don't know whether you are grasping that one interpretation of why jon stewart and why joe rogan why bill maher all these people to some extent hide behind it's a joke yeah it's because they're trying to find a protected class is there some place i can stand and speak the truth which does not result in my being garbage collected interesting i i guess you're right my intuition is you can stand as you gain more power you can stand you yeah there's a photo for joe rogan right now i mean i i've talked about it for a few years now people did not understand how big that program was people didn't understand long-form podcasting i was derided by people who i think of as being very shrewd um for believing in these podcasts as a major force and most of the people who derided me have said wow did i not get things it's like if you started to propose um you know you wanted to do the sopranos in the era of 30-minute sitcoms um like you don't get it man the american people they're not interested in these long plot story lines that's your weird thing nobody cares dude everybody just wants short fast memorable and like okay so if you do that you totally miss the opportunity and you know the savvy people used to say kid let me tell you nobody ever lost a dime underestimating the intelligence of the american people well that was totally wrong because they didn't calculate opportunity costs i have been talking about the problem of of joe for a long time um the problem is is that when the system wakes up they're going to want to control it and they're different they come up with new different mechanisms of doing that i guess one interesting one is cancel culture well look at the number of people around joe who they've come after since they realized that joe was really big joey diaz brian callan um crystalia now i'm not saying that those are all related but i do notice that there are at least correlations between when joe says something when something bad happens in joe's universe it's easier for me to believe that that's happening when it's happening around joe himself yeah but i'm worried about my friend yeah and i don't necessarily want to push him towards being more if he doesn't want it because i don't think i don't want to i don't want to conscript people he's got a great life he's got a great situation he's done a huge service thank god do you know yeah like how much do i owe joe just for what he's done for you to say nothing of what he's done for me or for brett or for sam or any of these people and you know i'd like to think that we all try to give back but i'm worried about joe he's not worried one of the inspiring things about joe yeah is i mean he's in this war alone and the way he fights the war is by just enjoying life well that's his thing as long as he stays close to things that he loves and being you know one of the things he's honest about his drug use he loves to hunt so he's just he does a certain amount of like semi-vice signaling up front and then you just also know him this is why every time they try to take him down you use the n-word you know it's like unfortunately everybody knows who joe is and he yes he he doesn't act as if he went to a fancy finishing school right that's not his energy the fact that you've got some super smart guy who always pretends to be a meathead just like you know it's like hey i'm a comedian like all these defenses and disguises okay you've got this super smart guy who um he's admitted to most of the things that you know you can you can take him down for and because everybody's been effectively in his den or his basement think about that studio as his basement people have hung out with joe so many hours that you can't tell them something about joe or they're going to say wow i'm going to believe the new york times and not the hundreds of hours i've spent on the joe rogan experience but the cool thing is that this is what inspires me is that the way he's waging war against the system is just by being a good person and and talking enough hours in a week where that message like bleeds throughout the words yeah in the gaps between and that that's so inspiring to me that the good people can win by just being good and he's kind and he's tough and he also he's no pushover no i i always worry a little bit when i sit down in that chair you still get scared that he'll call you on some kind of bullshit that you weren't even aware of no it the first time i was on the show the energy wasn't great between us and it was in a sober october situation so i think i hadn't understood that and maybe our egos got a little bit off um i don't know i mean i i i was having fun but maybe it was just too complicated life forms getting to know each other the first one was probably um yeah it made me a little nervous for the future but then you know joe and i become friends although sometimes we have miscommunications like on yom kippur i i texted him and i said joe you know i i want to apologize for uh ways i've let you down as a friend that haven't been there for you and appreciate everything you've done for me alisa like i get this text back like what the fuck is your problem you're great dude i don't know what bad place you're in but cheer up it's like joe don't you have any jews in your life to apologize for what they've done he was just like dude have you lost your mind what the hell's gotten into you yeah what do you think uh what do you think about the spotify thing what about it ask me a question he's now as opposed to being just a comedian with the podcast he now is just a comedian with the podcast who stepped like in the middle of the center of cancer culture which is like it's i know spotify is in sweden but they represent silicon valley they represent the very kind of structures they contain and represent the kind of structures that threaten to destroy the elons of the world and he just like stepped like with his alex jones and his uh joey diaz just strolled right into the middle of it i think it's awesome i love it but do you think he'll he's strong enough to well i don't know i mean i don't even know the right way to ask this but is he strong enough to persevere it's a bit interesting it's like when alliance decides wow that honey badger looks tasty i'm gonna swallow it whole see what happens because i talked to him offline he really seems to be willing to give away the hundred million which gives him so much power oh i don't it's a powerful thing to be able to say i don't yeah to the honey badger he just strolls in but he's willing to walk away from anything in this well he's going to walk out the other side of the the lion i don't think he's going to go out the way he came in yeah well you know what it is it's tommy lee jones entering the bug this is like a giant alien he just walks into it he just he gets swallowed by the bug and he blasts out from the inside yeah i i have it as tommy lee jones yeah but anyway yeah is that my feeling is that spotify doesn't understand what they're messing with i could be wrong but i'm not no you're right i'm right because joe doesn't need anything man i mean this is the weird thing about it it's like i'm sure that he loves all his toys whatever blah blah blah he's a rich guy yes he's got fu money he had fu money a long time ago and you're not you know the other thing about it's a bit weird being friends with a dude like that it just is because like you call him up or he'll call you up and he's like i said what's going on in your life i don't know kind of depressed trying to get some math done what are you up oh dude i can cheer you up i just came off of a you know 29 thousand person stadium it's like oh cool how'd you do that oh i don't know i just announced it on instagram a few days ago and it filled up just like oh damn yeah i mean that thing is so powerful yeah so there you go i mean you could be that too the instant takes an interest in politics and saving the world you might destroy all that it's going bye-bye i promise i just disagree with you i mean because you have to you have to do it like you've said this many times before i'll bet you yeah i'll bet you uh a bottle of stoli that you can get uh if you you get joe rogan to get highly politically active and call out the system for all the bullshit that it is in a very pointed and determined fashion uh and he doesn't get destroyed i'll give you i'll give you the vodka the vodka yeah that sounds like a pretty damn good deal so but this you've said this i mean there's no living heroes my friend no living heroes i just no living heroes it's it's just difficult you just have to be good at it i mean if you just say generic political things no no you it you're going to be taken down but the more heroic you are the more beautiful you are the more you will be made to suffer if they cannot get you on reputation if jesus himself came down i don't know if i ever read i probably never read to you the hit piece i did on jesus you don't know about this no i did not know i did hit pieces on all of the best people in the world wow so whoever it was who cured cancer you know discovered new particles or whatever it is i did a hit piece against them to prove that i can do it to anybody around anything at any time except eddie van halen as we were talking about well eddie van gaal is now dead but if if this was a uh a situation you know hot for teacher cancelled disrespectful absolutely also you know packaging uh female objectification for young men clearly eddie van gaal is one of the worst people alive but was the skill the incredible inspiration that is just radiating from his music inspires so many millions that they will fight those canceled pieces they they will fight though this is your thing yeah you have this idea that there's a war between good and evil and the good has already been decided designated the winner it's not true but your belief in that it's true until you make it no i mean you gotta it's motivating both of us like i also believe that we're gonna win because if i don't then i can't get out of bed and it's pretty heavy at the moment do you think 2021 can uh could make us feel good about the trajectory of society so like where we emerge from this year feeling good like there's a smile and there are quests on his face and the next time we talk we'll be doing some kind of duet and guitar and not having this worried look on our faces no okay but you've also promised you're going to somehow end this in a positive uh positive so okay so how do you how do you turn the no around what's the u-turn from the no no until we get some actually decent people in the right chairs who are not constantly thinking about their next paycheck i don't see a solution let me just say what the the prerequisites for a solution are and to let you know why i don't think it's coming first of all both of these political parties the leadership of them is disgusting and has to go they're tearing us apart they lack the will to be americans they don't understand the subtlety of the project they're simply the people who've figured out how to inhabit the seats and that is their great achievement i believe that in order to solve this you need people who can integrate who are not partisan at the level of the partisan warriors that we're seeing people who believe in dividing the pies of the future rather than the present pie as our main task as americans because we are built around growth i'm sorry to say it um you need an ability to have subtle conversations and you need the ability to exclude and and you know at the moment everyone knows inclusion is good which it isn't it's like saying well water is good if i say water is good everybody will agree with me it's not people drown people need to you know get dehydrated it can be life-saving or life-ending it it isn't good or bad inclusion is not good or bad inclusion is just inclusion exclusion is part of inclusion we've taught people that they can reason through the world as um sub you know cocker spaniels they just bark things at each other you know i'm for safety i'm for inclusion i'm for growth oh really do you guys use verbs dependent clauses are there compound complex sentences where are we in this sea of nonsense you have to be able to build a place where you have smart talented people who represent a diverse group of correct opinions you need to get rid of almost all of the people who have opinions that are antithetical to what we're trying to accomplish you need to give them insulation which we're terrified because we don't trust anybody so everything has to be transparent if you're going to the bathroom i want those walls to be plexiglas so i can see what you're doing it's like that's too much transparency we have too much and not enough at the same time and then you know in essence um you need to ensure that people aren't worried about feeding their family every four seconds for being real none of that is happening and our billionaires our billionaires are pathetic what is the point of billionaires if you're not going to do billionaire type cool stuff like saying fu and i'm going to throw you know 3 billion dollars at the project of restoring the national conversation i don't grasp this what is the point of creating obscene wealth if we don't have anyone smart enough and caring enough to use it so i agree with that that last part for sure let me slightly push back on the idea that the leaders themselves are broken i feel like this goes to the joe rogan uh joe biden and trump having a debate on that program i feel like joe biden has a lot of really interesting ideas that he's almost forgot how to communicate he's been fake for so long within the system hillary was fake for too long i'm sure she had real ideas at the beginning that she still was campaigning on decades later but like if the system if the platforms empowered you to search to be honest to be real to search for those ideas within yourself like long-form conversations do then we even the donald trump and joe biden leaders we have now would would take this country to a better place that that would unite people so like we can keep the current congress we just need to create better platforms this might this is going to the intuition that there's good in donald trump there's there is depth and competition there is good intelligence there is and the same with joe biden does good and joe biden and it's just we're not incentivizing i mean there's several things i think are broken one of them is twitter the other is journalism just it's just the platforms of us communicating with each other one of the reasons that i try to come up with unifying explanations is that you know if you look at the number of wildfires in california let's say that we've just seen if you treat them all as spontaneous uncorrelated uh instances it feels like oh my god it's just whack-a-mole every time i send a fire truck here there's a fire over there so you want to come up with something like a central theory which is why do i suddenly have a problem when i hadn't had a problem before so i look for these unifying explanations and i found one the other day that really speaks to me um i mean people are very frustrated because they've been trained to think about this incorrectly in my opinion but here's the graph that you need to look at on the x-axis is uh time by year and on the y-axis is something like average age of a human the title of the graph is any desirable situation involving institutions so that could be ceo it could be tenured professor it could be who's getting grants it could be the age at which people win nobel prizes university presidents all these things go up in other words for a long period of time the average age of the person in a desirable situation has been increasing something like 9 months for every 12. those graphs have to go down at some point the specter of willingly put of having five people all born in the 1940s as the final uh entrance in the presidential context that makes no sense think about how bizarre a thing that nobody's even really talking about the last five people were all ancient by presidential standards not one not two but five we are talking about a contest between somebody who is the oldest of the baby boomers the very beginning of the baby boom summer of 46th birthday fighting somebody who is in the silent generation the silent generation guy in a town hall in florida gets this question from a gen z guy saying you know what what's going on with my future joe biden has the um audacity to say i'm a transitional president you guys the highly educated one when has any generation in history needed a transitional 78 year old person to take office it's bizarre it's preposterous that graph is the graph we can't talk about that graph is the graph of our destruction because it has the you can make a one-line argument which is sounds like ageism which isn't a very good argument no but what it does is is it it muddles the conversation and you always have to ask yourself the question if this conversation becomes muddled who wins as a result of the muddling well it's a battle but so we let's just win it let's win the battle you give are you running for sure i'll run i was born in russia can't run so uh but we russians can hack elections so we'll figure it out uh this is me officially announcing my run i was born in st petersburg florida yeah lex what is it that you really want to ask i think i want to put some responsibility on the portal the portal the portal that the portal gives power to the people in that graph like because you you put it quite brilliantly that the people that moved the world their age has been going up and not moved the world but put in the position where they get the chance to affect the world the these new platforms i think twitter falls in in them give power to the younger people it doesn't have to be about asia necessarily but the younger thinking people so that's a promising thing and you are like you're like gandalf you get to you get to pick your frodos or whatever i'm not very good with the the analogy but the whole point is for us gandalf i don't know that i make that much sense gandalf makes sense i don't know if people know how to fit me into this ecosystem i think there's something in my presentation that people find very confusing oh figure it out i'm not i disagree with you but you need to look at the mirror and think like what what is it is it um maybe you need a mustache i don't know but there's something about figuring out um how to be a charismatic communicator in this and that that's the responsibility you said like finishing sentences with the lol is painful for your soul yeah that's just how somebody lets me know i don't have to take their opinion seriously yeah it's still the language the the way that people are communicating and you're swimming that way if you have a big platform i'm i have a growing platform it feels like this is the place to give i agree i agree but we're gonna get swatted now i just don't think so you're wrong why are you afraid of the big like this is i've studied it because i've studied let me ask you a question lex i believe that every society is supposed to have a collection of what i call break glass in case of emergency people yeah these are people who are universally loved and trusted by your society for example david attenborough the great british naturalist and presenter uh recently came on instagram he's worried about the planet and i said you know look there are very few of these people left let's pay attention find out what he has to say maybe maybe he's going to be an ass maybe he's going to be in it maybe he's going to say wrong things don't know tell me about your top 10 universal american heroes this is not a rhetorical question no give me five but everybody looks to that person and says yep the best of us well everybody's an interesting concept i mean elon musk is very divisive right but i'm talking about overwhelmingly people would would follow that person if that person gave a rousing intelligent speech that said we we must act now because we're in in dire straits i think a lot of people fall in that category for me it would be uh in the in the tech world in the engineering world elon musk elon musk the rock i'm thinking like who is the most eloquent actor so like you think celebrities so people with platforms don't say celebrities nobody well known i believe like platform yeah so this goes to joe rogan first two did not really impress me as being what i said but okay elon several years ago would have can you can you try to joe rogan why do they fail why why does why is lots of people treat joe rogan as if he's some sort of right-wing racist because they've never watched his program they don't know who his friends i don't know oh but when i thought you said everybody i thought you meant a large enough people where huge change can happen not actually literally everybody because i mean people who've pulled up like people who've pulled off something where everybody's convinced that that person just deeply i think i've told you the story before but the one time i've seen the power of a figure like this i mean very few times i've been in a large crowd and i've seen people just moved where they would do almost anything good bad and different because they were primed um one was a rolling stones concert the other one was nelson mandela coming to boston and man you've never seen anything like this you check out the photos from the banks of the charles river when nelson mandela came um there are people that you need in your dark hours and we can't agree on who they are and as soon as they emerge we tar them with shit we get out the shit brunch yeah i just disagree with you so i think what do we disagree about it okay i think it doesn't matter who it is i think really good speeches are needed and right i think i'm going to give them i saw killer mike try to give a good speech yeah he did well in atlanta right yeah that was something very impressed yeah even keller mike immediately gets into this sell out like uh yeah but he he he didn't take up the responsibility i would say he didn't of of going bigger so he was speaking to the community and he was doing what he did on this particular moment he's exceptional at it and he was speaking to this particular moment he didn't take it a step far farther which is like giving the same speech but bigger than race bigger than this particular moment but more about the the american project you know the guy who landed the plane in the hudson yes yeah there you go that's a good example sorry that guy until we screw him up is the kind of thing that i'm talking about yeah exactly okay i mean jocko maybe that's another jocko is pretty good jaco is pretty good can't really tell is he a democrat is a republican i don't know he's an american that's for damn sure yeah and i think there's a lot of fun and then you know no i think jocko there aren't that's one of the reasons why chocolate is so special yeah your podcast the portal is something in my little universe is something a lot of people really love and it moves them they draw a lot of meaning from it and also especially in difficult times and they it gives them a comfort of through like this kind of uh it's not just nuance it's there's like even when you're talking about chaos there's love underneath all of it and i think people draw a lot of meaning from it which is why they are wondering why you haven't been doing that many podcasts or you haven't done it in maybe a month and a half or two months in this most difficult of times is there is there a good reason yeah there are lots of good reasons so the first one is kind of weird which is everybody assumes that everyone wants to be famous and if you say i don't want to be famous it's like oh you're just saying that because you want to be every everyone to think you're famous you're not that famous you know okay i don't love being as well known as i've become there's lots of things that are fun about it it's wonderful that you can go to i can go to any city in the world there are portal listeners there uh all i need to do is put out a tweet and 20 people show up for a drink and they're amazing people and they're almost i mean you can see my live q and a's on my instagram page if you go to eric r weinstein i just picked somebody randomly and i was really worried about it at first and you know maybe i should be worried about it but in general people all over the world are just so positive and so you know and thoughtful and thoughtful people have a story because they're self-selected right yeah but i don't like the fame the thing we just described comes with the fame it's a beautiful thing you don't you're worried that it's getting it's it's ephemeral it'll look lex it'll turn on you in a heartbeat yeah it'll turn on you in a heartbeat and the other problem is i don't i don't like my audience being my audience i want to get closer to them i want to talk to them i want to find out what is this doing in your life my house fills up with art that people send me the lightest thing is an effects pedal called something like i don't know it's a bowtie overdrive from a guy in mexico right yeah you play lefty by the way and then a tiny little tangent did you play election i have a stratocaster okay but it doesn't have a strap and i don't know what to do with it and i have a bad amp so you should you should you should hook me up with uh we'll find it at home maybe okay you're starting to sense that this is too much no i want to be i want to be here i want to do the work very simply i don't have an ability to fully explain myself i don't want to claim that i don't love the fact that how much love do we get from these programs like i generically people are incredibly generous um you know people have begged me set up a patreon account and i haven't been able to do it i should do it i've said to everybody it's a business it's the business it's a business yeah but like they're so used to being defrauded when somebody starts thinking about monetary incentives my goal was to say i'm going to keep talking to you about you you wonder why i started doing ads on my show was because i wanted people to think from the get-go this is a business this is what i sound like when i'm selling but you know like you see i've lost weight a lot of that is due to athletic greens athletic greens you know um code uh what's the i don't know what my promo code is for athletic green well probably athleticgreens.com portal but doesn't portal but you know fitbit who doesn't advertise has also been instrumental as well as a guy named steven cates who you know was a fan from the show found me on the street and just said i'm a trainer i want to help train you it's got me on a on a good pro a good path so you know that's one paid advertiser and two people i'm calling out just because there are you know two two outfits stephen cates and fitbit that have changed my life i wanted people to say you know you don't have to be afraid of advertising if i do it in this way this is powering your show but the whole issue of money is weird because people have these crazy feelings like oh wow i knew he was a shill he's a grifter you know okay i didn't love that i didn't love the issues so i didn't set up a patreon the security issues for talking and being me are significant and i don't have the kind of money to hire around the clock i mean i i desperately want to get to a level of wealth where i don't have to think about money i don't think it's you know some people want money because they they need it for status i think i can handle status if i want it doing this i don't want the status necessarily and i don't want i i'd want the status but i don't want the fame that goes with it i want the money i don't want to be seen as this is about money because it's about a substance yeah and try you know all of those things that's part of i haven't solved these issues i i've been feeling bad because people say where's the portal we're desperate these are difficult times we have an election coming up and it's just like do you think for a moment that i want to explain that i actually got really uncomfortable being as well known as i was and then what is it that i want because i want to be better known and less well-known at the same time it doesn't there's nothing the audience can do i don't want the audience to be the audience that doesn't make sense to people i want it to be a business but i don't think people need to fear a business if the business is open about being a business that and then that's all to the side what you're seeing now in front of the election is an incredibly meta-violent period in our online existence and i believe that anybody who attempts to say these two parties are completely screwed at the moment the leadership of these parties is unsalvageable unworkable everyone hears that from inside the two-party system oh i get it he's trying to subtract votes off of biden oh i get it he's trying to scuttle trump oh i get it this is a play for his show because he's trying to plug in to discuss there's a bill hicks routine on marketing have you ever seen this it's brilliant i recommend it to everyone where he comes out on stage and he says are there any people in marketing and sales in the audience yeah it's like okay great can you do us all a favor and die and like everybody laughs he's like no i'm not laughing i'm seeing being serious so he talks about how marketing is horrible so you're like where is this act going then it gets to the point of it like oh i know how you marketing people think bill's going after that uh resentment dollar that's good dollar let's get that resentment anti-marketing dollar yeah it's like no that's not what i'm saying i really hate marketers oh that's good it's the authenticity dollar you can't escape this kind of negative marketing thought and i guess that gets to the issue that i don't want to be destroyed in advance of this election i don't think it's a good use of my relationship to my audience to be broadcasting how completely ridiculous donald trump and joe biden are as candidates for the president of the united states full stop none of this makes any sense these moderators of these pseudo debates were in the wrong format with the wrong people no part of this makes a wit of sense can i try to push back several claims one is i don't believe the systems as they stand now can destroy the eric weinstein voice the voice you you're a child i'm sorry to say that but well let me well it's also possible it's entirely impossible okay that you're the child okay because a child would say you would call other people a child yeah get in the first blow i think reveal the tell i because the only power they have is to attack you psychologically no well i believe that the army of people that love you yeah is much more powerful than uh mainstream media then people that you might hear it say ridiculous things that you just said which is try to reduce you like the marketing yeah thinking i just believe there's an army maybe there's a better term of people that see you for who you are and the hungry like i'm not disputing those things and what i'm saying i would venture to say as your therapist that you're actually uh the battle is all in your mind that you have found these demons in the system and they're just a tiny minority and it's all in your mind they cannot actually remove they're not strong enough to remove the voice of eric einstein to silence the voice i love this this is some of the best fiction writing i've ever heard let me tell you i have relatives who've known me my entire life yeah where one article in the new york times they will believe that over me my contention is that only that has no power except to affect your psychology you know what you have to do is the rogan thing which is loud hearing me just laugh i am laughing i know but more i'm tell no i'm telling you something yes okay the way this works is through ruin ruin can come to anyone there is no one who cannot be ruined every single person is signed up right now to be ruined by the system but don't you understand that you have more power than the system the ruling you can ruin the system your twitter account the podcast that's right i'm telling you about the army i agree that my twitter account my pocket but what we've seen for example you saw what happened to brett's articles of unity project yes okay what happened the you know from on the twitter side on the twitter side what happened what happened well actually say the word answer say the word it was uh blocked or removed from twitter suspends account suspended yeah okay so i'm talking to the ceo who i am crazy enough to still believe in good i do too i believe it somehow there's a very strange thing going on with jack dorsey i cannot possibly reconcile the actions but the person i've that that is a next level mind in there i'm not i don't know it well enough to say that it's all next level i'm not claiming he doesn't have any blind spots every smart person i know has blind spots i don't know what he's up against blah blah blah there's no way that the jack dorsey that i've talked to and the jack dorsey that interacted over articles of unity can be the same person he is constrained by that company in some way that doesn't make sense to me either that or he's the most implicitous person on earth and i'm not believing it i just don't buy it okay yeah something horrible is happening i my claim is i i can remove you functionally from the chess board in a tiny number of moves no matter who you are no matter how virtuous or how much of a bastard you've been your entire life it doesn't take more than three or four moves to basically neuter you as a force yeah and i disagree that if that's possible that means i'm not very good at chess like unity 2020 was removed from twitter because it's not good enough not within the system like the army of people that feel the brilliance of the idea was too small okay but fear uncertainty and doubt is the name of the game the point of the realm psychology though it's not real power it just affects the mind okay i have a reading assignment for you because you're russian you'll really enjoy this as part of the great american tobacco settlement the tobacco institute had to disgorge its archives of all of its strategies all of its skullduggery and put it on the web for all time so that we could all understand how the tobacco companies got together and destroyed people right you see tobacco destroys people you can see you know scientology destroys people there are various vindictive organizations that will not tolerate um reality and opposition to them let's take them down okay that's what i'm trying to tell you is okay no so so why aren't you doing the podcast to return because that's one of the weapons because of war well first of all if you're at war and i don't want to discuss strategy on a podcast right but that's you you're missing what did montgomery say about rommel but wasn't his line that i read your book you beautiful bastard it's like why are using the tactics that you already explained okay so one of the things i'm doing is i'm not having a strategic conversation with you and 100 yeah several hundred thousand of our closest friends i pulled back because this is not the battle that i know what i'm doing i i do not feel passionately enough about defeating donald trump to elect joe biden even if that's the way i'm going to ultimately vote right i don't believe in the biden democratic party i don't believe in the trump republican party so yes it's an incredibly consequential election but to me it's like the the crips and the bloods and the latin kings fighting over the right to extort you know a business and the business trying to figure out who it wants to to do the extorting but don't you think listen there's very few people that are as good with the english language as you do don't you think it's possible to draw a line that doesn't that betw in between that finds how we find our common humanity that ensures a better 2021 without having to say like donald trump is evil or joe biden is incompetent or any of that just somehow driving a beautiful scene so much pain this election is chewing up the integrity of everyone who comments on it lex maybe they're not good enough they're not good enough no i but that but okay the hope is do you believe in me yes you do yes listen to me very carefully my spider senses my intuition that has allowed me to survive in the space i've been mouthing off since the 80s tells me this is a super dangerous time for smart people to be spending the dry powder because the election doesn't make sense it doesn't mean that i don't have a sense that one outcome would be better than the other probably but the variance on that i'm not even positive that i'm right these two options are so completely inappropriate to the world of 2020 what we need is so diametrically opposed to more boomers and more silent generation people trying to sort out a highly technical world being my mediated through social media we need more exclusion we need more actual elites the people we've called the elites are not the elite they need to go yeah we need excellence competence we need people who can be trusted behind closed doors and we need to close the doors so we can't see what those people are doing here's the thing imagine that you had a bunch of people who'd all seen action in combat had all volunteered to be part of the armed services had all come from backgrounds where they didn't need to so you were convinced that these people had put their lives on their line for their country not for a payday imagine you had 10 of these people with technical backgrounds men women black white muslim jew doesn't matter right i would trust those people and i close the door i don't want to know what they talked about i don't want transparency into all of their negotiations i want to know that they're patriotic that they have they see something in the world bigger than themselves and their family fortunes i want to know that they're courageous i want to know that they've got all of our well-being and i'm willing to roll the dice and if they screw us over i'd rather go down like that okay so i disagree with you there because there's a difference between those and jocko because because you're not speaking to people with credentials of no talking about self-credentialed people self-financing i view jaco as self-credential but the biggest the powerful thing about jacob is he's not only self-credential but he's been real with people the the magical thing about jocko is in his book isn't his life story is he's been talking on a podcast for a long there's something real that happens okay so if you took everybody if you took dan crenshaw yeah and tulsi gabbard and you took jocko willing and maybe jessie ventura right uh you can take i see where you're going with this what you can take bernie sanders yeah who's you know a lone voice you take all of these people who've like really just risked like why do we trust why is catherine hepburn the best that hollywood ever produced because she told hollywood to go fuck itself hard they gave her four academy awards and she said love you sweeties i'm gonna use them as the doorstops for the bathrooms in my house see that skill that's uh that's that's just that's what you were talking about yeah be katherine hepburn audrey hepburn is pretty amazing but katherine hepburn is next level right well you i mean that's what you're trying to say to me yeah okay i'm trying to figure it out lex okay i don't have the answer yet what i do know is that this election is chewing people up and i mean two separate things one that parties don't have enough integrity that if you comment either for or against there's a short sequence where you make a comment that's nuanced you get referenced to something right like you know take this thing about you know find people on both sides that is non-resolved after n years whether the context should be reported or not we are in some situation in which democrats and republicans are primed to fight each other the way introducing two ants from two different ant colonies always produces a battle yeah okay i don't want to be in that fray because those people are going to kill each other mindlessly like robots and until the election is concluded like i do i think this is dire yes could it be make or break absolutely i'm not saying that do i know which way this goes i can make an excellent argument that we need to elect joe biden right now that we've got a situation which can only be cured by voting for joe biden i can make another argument that we could have a situation that can only be cured by defeating joe biden right now and all of the things that the modern democratic party represents yeah i don't have you know it's not the lady and the tiger we're choosing between the tiger and the tiger it's the sumatran tiger versus the siberian tiger right i'm trying to think well which tiger can i do i have a better chance against um the key problem for us politically is that we have to divorce the concept of the center in moderation from kleptocracy every time we try to say something like we need more moderate solutions we need more pluralistic solutions people will say wow you just want to hand us right back into the swamp don't you the swamp people because the moderates and the swamp people are the same people all right so then we have these two crazy wings we can't have crazy right wing people i don't want any tiki torch bs we can't have crazy left wing don't attack my courthouse really don't attack my courthouse and we can't have moderates it's like okay how do we install our children and rape pillage and get these speaking fees when we're out of office and become you know cozy with the things when we're supposed to be regulating them and then you know become their lobbyists you know immediately when we leave office all of this stuff we need an entirely different system and i can't talk about that at the moment when i talk people say oh wow so you're going to sit this one out because you're a pussy because you're a coward great to know eric we thought better if you buy click yeah i don't know what to do so but are you thinking of what to do yeah oh you you better believe it look bret brett had this idea of unity 2020 and i told him it was a wrong idea yeah i didn't tell him that unity 2024 was a wrong idea i didn't tell him that unity 2028 is the wrong idea and if i were to make the case that he was right and i was wrong because he's now shuddered the thing right i would say that the case to be made that he was correct was is that by doing this in 2020 we found out what we were up against it's good to know that twitter can turn this off at the drop of a hat yeah great to know it's good to know as we learned that you cannot have meetings of of of presidential candidates in a primary that are not approved of by the party right like they've got this thing figured out so we don't have any way in and now unity 2024 makes sense because unity 2020 was tried okay i don't know that we get to to 2024 under all circumstances in some we do and some we don't but there's there's a game theoretic thing that i'm not sure you're accounting for but you probably are but let me just make an argument is jack dorsey very likely listens to your podcast and what this is the power of these words something deep went wrong but we can change it with the power of words something went wrong at twitter they have so much division on their platform that's what i'm trying to say they've gotten it's not wrong they just don't know they're understaffed they have no they have an insoluble problem difficult to solve they have an insoluble problem the argument i disagree because well all right i would like to create a competitor no so then you know give it to me yeah wait create the competitor show me you actually understood this because my guess is is that most of the things that you'll think about i mean i can tell you things i've talked to jack about which i know would make twitter much better however i i think that this problem of instantaneous communication across the planet and you subtract off all sorts of context and mutual self-knowledge the problem is us it's not the platforms you're thinking about a technological solution and i'm saying the problem is is that we are ultimately the product and i just disagree with that and there's a lot of let's probably could save that for tomorrow i look forward to uh spending summers in your villa uh when you when you debut this product and i would love to angel invest in it by the way in terms of money i'll never have a villa yeah no i will always give away everything i own don't do that no sorry uh invest into like things you like you mentioned awesome things invest fine but a little bit of evoncular advice don't pledge to be the person who disgorges themselves of security money is freedom that's what it is it's a big honking pile of freedom okay you can choose to use it as the freedom to imprison you if you don't you know so you can use it as freedom to make yourself a prisoner of your money but generally speaking lex money is freedom and your voice is important at least retain the amount of money security you need to follow joe's advice what is the point of fu money if you don't say fu the number of people who have fu money who don't say fu indicates the number of people who chose the freedom of their wealth to create a prison they built a prison with the freedom they had and they walked into it locked the door i think it's too difficult not to create the reason i want to give away the money is because i just know my own psychology and you create prisons our human mind just creates those prisons the f.u money is enough for basic shelter and basic food that's that's the optimal if you don't have kids yet this is a okay this is the problem this is why i'm so this is me single lex speaking great but future future lex i'm talking to future licks single single present lex please don't listen yeah don't be an ass you're going to need some money and don't make these pledges to say on a podcast i'm i'm say i want to save you from yourself you need money to do many of the beautiful things that we're counting on you to do don't f it up can i talk to you about roger penrose sure you've talked to roger on the portal but also in between the lines and offline just everything you've said about roger penrose for people who don't know he just recently a few days ago won the uh 2020 share the 2020 uh nobel prize for physics but it's clear to me that he had like a deep personal impact on you a connection with you uh in terms of both your love of mathematics just the way you see the world like the this is the eddie van halen conversation this is clearly somebody who's profound in your worldview can you talk about roger can you talk about what it means that he won this highest of prizes just in general let's celebrate the man yeah okay so first of all there are two other people who won this prize i'm sorry i just didn't happen to know who they were before they won um roger is a very it is not roger in particular but the class from which roger comes that is so important so i would put roger in the class of feynman einstein dirac yang um you put whitten in there i know i mean witten's a special case but whidden is weirdly the reverse of the roger penrose story right because whitten is the first physicist to win a mathematical fields medal the highest honor in mathematics penrose is in some sense a mathematician who's now won the nobel prize so it's a perfect sort of a couplet yeah um roger's class means everything to me that's the highest achievement of the human mind i'd probably throw bach in with feynman and dirac in company right um i think that he was so inventive it was very frustrating to watch this career it's a little bit frustrating to watch feynman's career feynman was so good and had he been born slightly different at a slightly different time i believe his claim on physics would be far greater i feel like penrose in some sense came up a very difficult path because you see einstein effectively solved most of the most important problems in general relativity right at the beginning as a result the children of einstein are impoverished because there wasn't as much to pick off of the trees and sell at the market whereas bohr didn't and plonk didn't do nearly as good of a job with quantum theory so there's lots to do in quantum theory i think that roger affected me personally by a diagram that i saw in a paper of hermann gluck at the university of pennsylvania it was the first picture i'd ever seen of the hop vibrations sketched and that you know weirdly i brought that to the rogan program in order to sort of convey the wonder it was recapitulating my own journey i think i probably saw that at like age 16 or something it just flipped my mind roger is incredibly visual he's incredibly geometric he's incredibly suey generous he just does his own thing he's got lots of bets none of them had really come through the way you would hope and i think they stretched the rules to be blunt about it uh to give them the prize yeah i do you you said this thing on twitter which is beautiful that every once in a while comes a human being that gives uh value to the prize versus the prize giving value to the human two different kinds of prizes the reason that we care about the nobel prize isn't because of alfred nobel it's because it came along at the right time to reward um einstein derock schrodinger feynman most of the most of the people who should have won one most of the awards are not good in the sense that they don't really follow the prize is used to rewrite history that's its problem so it's you should have a love-hate relationship with it because on the one hand it does focus the world on what really matters and on the other hand it distorts what really matters and both of those functions take place simultaneously in this case i think that they violated their own rules slightly so it wasn't really clearly a case of a prediction and a discovery in the typical fashion but they like we better give this award to somebody of that highest caliber to make sure that the prize is fully funded with prestige going forward that's that's sort of my weird speculative guess as to what happened and so roger's getting on in years and the person should be alive so they i think they meant the rules and i think they couldn't have bent it for a better person and i hope they will not bend the rules out of weakness but out of strength in future it would be great to get madame wu and emmy nerder a posthumous prize along with doug prasher george sudarshan uh and george zweig as well as ernst stokelberg nobel prizes there have been some terrible omissions on the first two being females who revolutionized our view of the world and i take a very dim view of people pushing for prizes for people from ethnic groups or genders or whatever in order to make it plural and inclusive if it's not following the work and i feel very clear that in a few cases we know there was a real problem with the nobel committee because we have stunning accomplishments you know try to get through a day as a physicist without nerder's theorem and try to imagine the universe without madame wu's discovery that left and right don't appear to be symmetric i mean these are terrible emissions and they're a huge blot on science for not being more inclusive when it matters yeah so just like you said the nobel prize is plagued by omissions as much as and distortions and dilutions for example derock and schrodinger were i believe given the prize in the same year there's no reason that those two people needed to dilute each other the same thing with you know dyson was an omission tomonaga probably got included in part because we had an opportunity to show that something had happened on both sides of the pacific after the war but i don't think we needed to dilute weinberg or feynman or schwinger it just makes me it makes me somewhat sick all of these people are such important giants and it has to do with the field i think not wanting to create luminaries and superstars who could have defended the field from budget cuts and worldly pressures i think it's really important that we have absolute superstars because we produce superstars we acknowledge them we don't dilute them and that we bend the rules to make sure that the prize stays funded with the prestige that comes from giving it to the roger penrose's albert einsteins and paul derocks of the world can we talk a little bit about evil sure i haven't actually talked to you about this topic and it's been sitting on my mind mostly because everybody at mit is quiet about it which is jeffrey epstein i didn't get a chance to experience what mit was like at the time when jeffrey epstein was part of this but it's i'd love to try to understand how evil was allowed to flourish in in the place that i love whether you think maybe let me ask the question this way was it the man evil or was the system evil or is evil too strong a word because what i see is the presence of of this particular human being in the eyes of many destroyed the reputations of many really strong scientists and also weaken the ability like weaken the institution of mit by making everybody quiet like almost making them unable to say anything interesting or difficult yeah and what what is that and what am i supposed to uh we don't know why is everyone quiet about jeffrey we don't agree no we don't know obviously i want to scream about it too right and i probably have said too much about jeffrey epstein look something horrible happened i don't know what it is but something horrible happened and you know at the one thing that okay let's just do this the first thing i need to do is i need to get rid of this woke crap about power differentials okay in general can talk about hypergamy and power differentials are russell conjugates of the same concept just the way particular proportions and symmetries are mathematically provable to be attractive in females to males male attractiveness is largely determined by male competence and ability to amass power and success and all these sorts of things the relationship between consenting adults is quite frankly not something i want to sort out the relationship between the sexuality of adults and miners and particularly you know there's the the the 17 18 issue that's very different than 12 13. um we're talking about really sick depravity with respect to what it appears that jeffrey epstein was involved in at some level i believe this story is super complicated in part because i think one thing jeffrey epstein was doing was providing money encouragement and support to scientists another thing he was doing i believe was giving tax advice to very rich people i believe another thing he was doing was hooking very wealthy people up with young adult females another thing he was doing i think was doing stuff with children that will curl your toes so between so there's an entire spectrum of different stuff and at the moment nobody can pull apart or deconflate anything because the woke thing comes over it and says you know i think it's disgusting that you know a 43 year old billionaire would be partying with a 23 year old right yeah okay yeah i don't want to adjudicate that i'm worried about 12 and 14 year olds that we're not talking about but i mostly i don't think mit was deep into pedophilia my guess is that that did not happen i don't think that the scientists were the targets of the really sick depraved stuff it's my guess my my guess is that what you're looking at was a government construct it may have been our government it may have been a joint government project maybe somebody else's government i don't know i believe that in part we don't really understand robert maxwell sorry who's robert maxwell galen gillian as well's father was very active in scientific publishing i don't know where peer review came from i would love to run down the relationship between peer review and robert maxwell i would love to run down the missing fortune of robert maxwell and the mysterious fortune of jeffrey epstein because i don't think jeffrey epstein ever ran a hedge fund i don't think he was a money advisor the way people claimed so there's two things i want to talk about so one is the shallow conversations of woke identity politics that you're referring to seems to be removing everyone's ability no everyone willing one of the things to talk about like what the hell is this person and how is he allowed more most importantly to how do we prevent it in the future and from the individual perspective the question for me it's the same question i asked about 1930s nazi germany i've been reading way too much probably or not enough about that period currently is if i was in germany at that time what is the heroic action to take when i think about mit with jeffrey epstein what is the heroic action to take we're not talking about virtue signaling i wouldn't know what to do i would like to know what you're up against lex you're not hearing me the problem here is what was jeffrey epstein well that question might be the heroic action to take that's what i'm trying to say i'm just trying to get my first question you have to map the silence with jeffrey epstein what you're describing is a map of the silence at mit yeah well is there a map of the silence in washington state around jeffrey epstein the bay area new york city the amount of silence around jeffrey epstein should be telling you everything the number of dogs that don't bark is like nothing we've ever seen you're exactly correct but i want to know what is it telling us because what it's telling me is not some kind of conspiracy but more a disappointing weakness not some kind of conspiracy or might it's not some kind of conspiracy but you've got to be kidding me no you're so you're so afraid of saying the word conspiracy that you don't think it's a conspiracy i personally i just think it's people who i thought were my heroes just being weak no be of good cheer sir a cheer be of good cheer of good cheer yeah you think that there's a conspiracy i think there is a conspiracy a very impressive one that's the scale of it i tend to believe that large scale can only be an emergent phenomena really i find this so fascinating yeah because i always see you as like a logic logic and love drive your drive your soul you're very logical you're relentless you got a lot of love in your heart i believe that if you would review the video where is it from dubai or abu dhabi of the mysterious hit on the hotel guest you ever seen this thing yeah oh what happened it's the assassination in 2010 10 years ago of mahmoud al-mabu something like that in dubai where i believe 26 separate individuals on multiple teams are shown converging coming in from all over the world on false passports pretending to be tennis players or you know business people or vacationers and all of these teams have different functions and they murder this guy in his in his hotel room and the dubai i guess chief of police security officer was so angered that he put together this amazing video that says we can completely detail what you did we caught you on closed circuit tv we don't know exactly who you are because your disguises and your false passports but yeah 26 people converged to kill one no i don't believe you i don't believe after cointelpro an operation paperclip and operation mockingbird i don't know whether i should even bring up rex 84 to not believe in conspiracies is an idiocy so you you have a sense that uh evil can be as competent or more competent first of all when evil wants to operate at scale it needs to make sure that people don't try to figure out evil when evil operates at scale yes from first principles you have to realize that evil must not want it investigated that's correct the most efficient way to keep yourself from being investigated if you are a an evil institutional player needs to do this repeatedly is to invest in a world in which no one can afford to say the word conspiracy you will notice that there is a special radioactivity around the word conspiracy we have provable conspiracies we have admitted to conspiracies you have been invited to conspiracies there is no shortage conspiracies are everywhere some of them are mundane some of them are like price fixing cartels you know or trade groups are generally speaking conspiracies so the first thing you have to realize is that all of us are under a in a memetic complex where you can be taken off the chess board by saying conspiracy theorists get done it's a one it's like a one-line proof we don't have to listen to lex he said he was a conspiracy theorist on this show okay that is partially distorting our conversation if you want to ask me about jeffrey epstein you have to agree with me that that is a logical description of what you would have to have if you wanted to commit conspiracies is that you have to make sure that people are dissuaded from investigating yes okay but it's a very it's a fascinatingly difficult idea then because the world with conspiracy theories in the world without conspiracy theories to the to the shallow glance looks the same well my point there is responsible conspiracy theorizing where you look at the history of unearthed conspiracies and just like you would with any other topic just think about how different the rules in your mind are for conspiracy theorizing versus x theorizing where x can be anything right it's like if i say to you um i can say the statement that average weight is not the same between widely separated populations you'd say yeah i'd say average height is not the same between widely separated populations you'd say yeah then i say in fact no continuous variable that has that shows variation should be expected to be identical between widely separated of course eric like iq whoa whoa whoa hold on right so we have a violent reaction to specific topics so the first thing i want to do is just to notice that conspiracy has that built into everyone's mind that's really important to state yeah that's it's very interesting at that and as a prerequisite as you're saying that would be the first step if you wanted to uh pull off a conspiracy in a competent way that's he would have to first convince the world i just watched the film 1971 about my favorite conspiracy of all time i highly recommend it 1971. well the film is entitled 1971 and it's about the citizens committee to investigate the fbi which was run by a student of murray gelman a physicist and broke into fbi offices in pennsylvania to steal files which allowed freedom of information requests that discovered a huge conspiracy it was a conspiracy that unearthed a conspiracy inside the federal government a double conspiracy story which launched multiple conspiracies i think that the problem with modern americans is that they are so timid that they don't even learn about the history of conspiracies that we have absolutely proven so with that done jeff epstein in my opinion represented somebody's cunt construction i don't think it's scary to think about yeah well what part of the story isn't scary i in part did something which i i imagine may get me destroyed because i was more worried about being destroyed by somebody else i had a conversation with around jeff epstein right so i'm just trying to like get let it be known that i don't know anything more than i've already said now your friends at mit yeah their problem is is that jeff epstein showed up as the only person capable of continuing u.s scientific tradition you see the u.s scientific tradition is a little bit like the russian it's it's combative okay and we're a free society and we act like a free society we're a rich society and we research like we're a rich society that is historically and then came the 1970s and william prox meyer and the golden fleece awards and the idea that we have to we're paying too much and these are welfare queens and lab coats and blah blah blah blah we need more transparency more oversight everything went to hell and the national culture of u.s science was lost the thing that produced all this prosperity and security and power was lost and then jeff epstein shows up and a tiny number of funders maybe fred cavley um maybe yuri milner maybe who else would be in this category peter thiel to an extent howard hughes would be the largest of these things which has different grant structures than the nih gave people a modicum of risk-taking ability okay when jeff epstein showed up everybody wanted to take risk in science and suddenly a charismatic billionaire says hey i can make that work for you here's a hundred thousand dollars go go research something crazy well that money was supposed to be provided by the federal government under the terms of the endless frontier compact between the federal government and the universities and the federal government the taxpayers welched okay so that's one place to lay the blame for jeffrey epstein as that the the failure of the federal government to honor to honor its commitment yeah right so the universities became psychopathic it's not like everybody doesn't remember what we're supposed to be doing to be moral but the point was there wasn't enough money to be moral so it was time to uh to eye each other as a source of protein as i like to say and in that process jeffrey epstein said hey come to my world we can do it like we used to do so in in part my point is is that almost none of your colleagues at mit have that kind of religious commitment to science that they're willing to go down with ship science the galileo galilei thing became very important to science because occasionally you just have to say look this isn't about me and you i there isn't enough money in the world to buy the kind of legacy i want to leave to this planet this is one of the great things about science you know potentially it's worth dying for yeah i'm glad you said it science is one of the things that is best that's worth dying for i mean i'm not eager to martyr myself but i've certainly risked my health my fortune you know i i've destroyed myself economically over science and um and my my my need to oppose these sons of bitches in chaired professorships who are destroying our system along with everyone else let me um bring in grandmaster who went into this oogway ugly master ugly i think he's a grand master oh that would make him a chess playing turtle so i've read some wikipedia uh-oh shifu is a master there's apparently only one grand master that's uh anyway is the phrase grand master ever uttered in the script i don't think so i don't think so but there's a story oh there's there's off off script canon i'm gonna call glenn berger right now and find out if any of this is true all right you're not supposed to call out my journalistic integrity um but master oogway master uh he says a couple things i'd like to bring up with you so one as part of a longer quote recommends that you should find a battle worth fighting we've talked about several battles just now what is the battle worth fighting for for eric weinstein in the next few months in the next year there's only one oh it's the moses it's the moses thing it's time to go it's time to leave this place is over to get off the planet i yeah i i i freak people out when i say that but like look at your world you just got introduced to the problem of a virus wait wait till it's fusion devices and you understand what it means to have one interconnected planet with no uncorrelated experiments happening anywhere else you know so do you see the foray your work in physics and maybe like the echoes of it in uh ship elon everybody who has a possible plan to avoid what is coming if we don't have one should work on the plan that he she thinks best right so elon wants to do rockets people misinterpret me i meta eric says i don't think that's a smart plan regular eric says all people who have hope should do that thing yeah at least it's mars man at least it's the moon and mars and maybe titan and whatever and i don't think it'll work and it doesn't make sense and it looks silly but that's exactly the kind of fight where it's fighting but it's it's the kind of it's for the same reason that i went on brett's unity 2020 thing when i didn't think it had a hope in hell and people were you know are making fun of it we got to do things that make that make us feel dumb and silly and childish that possibly have a hope of working okay so everybody should do something my version of this i'm the most hopeful about because i wouldn't have chosen to do if i thought that daniel schmochtenberger's wisdom project was a better hope i'd do that it's more down to earth in a certain way i just think that it's more probable look we got from powered flight with the wright brothers and wind tunnels to sending back images from the surface of titan via huygens cassini in less than a century okay what we can do if we can change the laws of physics is something we can't even conceive of it may be that it buys us nothing and at least we'll we will know why we died on this planet as a small aside i think this is not the right time to take the full journey but i feel like you'll guide me like master uh did and i'm the kung fu panda at some they only have one conversation we're on our like we didn't well we're we're we're jews and they weren't so we talk too much but the guy doesn't have to be with words uh you don't think poe is jewish it's debatable we'll have to go back to the really like yeah okay is there um that you would guide me through some more intuition about the source code the source code of our universe can you comment on where since we last spoke where your thinking has been has roamed around geometric community around that work in physics in this fight i'm trying to figure out when to release it and how i mean i've released the video and the video quite honestly i think it has a very bizarre reaction i think one of the things that i've learned from the video because the video is coming up on half a million views on youtube alone to say nothing of the um the audio but yeah it produced a very strange reaction one of the things i don't think that i properly understood is that most physicists don't talk in this geometric language i thought that more of the physics world probably had converted over into manifolds bundles differential forms connections curvature tensors etc and i i saw a lot of the comments would say things like i have a phd in theoretical physics and i'm not even familiar with all of these concepts and i think that was probably a distortion coming from living in cambridge massachusetts for almost 20 years so what's the solution to that well i mean translated into i can make this make as much sense as anybody needs to my problem is it's you know my calculation is that as long as the boomers are still in charge the same people have these perverse incentives on them where they've invested in these programs that didn't work so they're extremely hostile and kind of difficult to deal with the fact that i'm not a physicist has its own set of issues which is that effectively it's like the hermit kingdom they don't get any visitors and they don't necessarily want somebody you know rolling up and saying i know how to do physics so i'm i'm always very clear i'm not a physicist [Music] that said if i wait too long i don't know that theoretical physics is really going to exist after the boomers because everyone in you i think you had wolfram on your program i don't remember whether he said this to you or brian keating but he said something like everybody got discouraged it was too hard we can't do that guys we cannot do that there's something about the renormalization revolution that innervated the physics community because it taught them just because you can see in this energy regime doesn't mean you can extrapolate somewhere else unless you understand how you know coupling constants run and what kind of uv fixed points exist blah blah blah somehow that discouraged people from guessing from believing everything became an effective theory the beauty of the effective theory wasn't taken to be really the beauty of the universe just the beauty of an energy level so i think that renormalization was one of the most important revolutions that ever happened in science and also its interpretation by the physics community was catastrophic well the story i'm telling myself is that in part i'm waiting for them to get weaker but on the other hand i don't know that we have any time left and so are you also thinking about ways of uh you know you know the the podcast medium is revolutionary for public for discourse for what i mean i don't even know the right words for it are you thinking of revolutionary ideas for re-energizing the physics community so basically for communicating everything look i have a fantasy okay my fantasy is that all of these things are the same problem and it goes back to this thing that i read about in in feynman's uh books about tartaglia they asked him this question like what's the greatest thing that ever happened in math he says tartaglia's solution to the cubic it's just like the weirdest answer so you're like okay i'll bite why is it ugly a solution to the cubic and he said because it was the first time a modern person had done something profound that the ancients had failed to do i was like oh i got it it's the thing that opens up new psychology that says maybe things are possible again send you orchard you orchard new farmers new people who can find fruit that they can pick and once you have one person do that very often you get many like one of the things that we're talking about with eddie van halen the reason that he created a revolution and somebody like roy buchanan did not is that you could follow eddie van gaal you couldn't pioneer it and maybe you couldn't play as well and as cleanly and as fast and as inventively but you could follow once you understand that there is a tapping principle it was just the beginning of something called percussive guitar my belief is that once we start innovating in the present everything will come because everything that around us is screwed up on that let me with one last question bring back master oogway the probably the most famous quote of his right with the yesterday's history tomorrow's a mystery but today is a gift that is why it is called the present it's very beautiful although i would have gone with quit don't quit noodles don't noodles i feel i feel like people need to know way too much context for that to make sense how is that it's your audience just to hell with context yep they they'll figure it out well let me ask what are you grateful for today what is your present we've talked about a lot of dark things but what do you brings you joy to your heart that i can't believe i'm lucky enough to have this no nyla and zeb uh my wife pia um the fact that we've got our health all the the little things saying grace after meals you're coming over for friday night shabbat dinner so we'll say we'll we'll bench together and say grace it's important to just like this bottle of water in front of me i made a point um of just thinking about how wonderful it is that there's a quenching bottle that happens to be placed in front of me because somebody cared yeah you know so that small thing made a difference to me um i still have strength for the fight so far i think that's something i'm grateful for i can't believe that i'm not more beaten down after all of this nonsense um i have the most interesting set of friends i really do i mean i'm not that rich by monetary standards but if there were friend billionaires forbes would be all over my ass i just can't believe who i can talk to you know at the drop of a hat and i'm really grateful i think this is the end of something profound and it's the beginning of whatever is next and whatever is next could be terminal whatever's next could be amazing whatever's next could be a return to the horrors of the early 20th century that doesn't manage to go totally catastrophic but you know takes hundreds of millions of lives in the process i'm grateful to having half of my life in the rear view mirror it maybe it took place in a bubble and maybe it was unsustainable but it was it was nice to be able to move around the world without a mask uh it was nice to be able to see a little bit of the world even if it was from a a cot in a hostel in some country um to fall in love absolutely i mean it was a good life find the last indian jewish girl left who knew uh you're a lucky guy well let me just say actually there's something i wanted to just say before you get to that yes i forgot to say something falling in love with an intellectual collaborator is a special thing that not everybody gets a chance to do like i think when i met pia i felt deeply in love with her all her normal characteristics and i she and i had an antagonistic relationship around uh geometry and economics and then weirdly you know just like in a buddy picture where in the first half of the film they hate each other um the two fields like we're fighting with each other cats and dogs and finally you know the sexual tension clearly was so so thick you could cut it with a knife and we came up with geometric marginalism which is this other theory not geometric unity which allowed me to inhabit space with somebody who i already knew intimately and had fallen in love with and to see the quality and beauty of their mind and to play into dance it's sort of the intellectual version of the tango um one of the most romantic periods of my life that doesn't fall into most people's experience there was a chance to see something totally unexpected haven't really had it since because she doesn't want to revisit the material but something i'm super grateful for that's very particular and unique but to flip the tables on you for hundreds of thousands i think millions of people i can speak me and them are really grateful one that you exist and too sorry for your podcast and i do hope your voice in some form continues to to uh reverberate i think in the at least in the 2021s and and beyond even if it takes a brief pause we're pausing at the moment we've recorded some for future episodes and i'm recording for you i really appreciate that i mean it's earnestness uh trades at a discount at the moment because it's easy to make fun of it one of the things i like best about you is that you and i are both fairly earnest we made we made joke and jeb but honestly there's a project here in a world to win as they say um the thing that uh i want my and your listeners to know is that i'm not stepping away from the podcast because i don't appreciate that people really want more it's not you know this is hugely financially costly to me i want to make sure you guys are getting the best that i can do and destroying myself right in front of an election i think lex is incorrect i think that the forces that are trying to make sure that there aren't any planes in the sky that aren't either colored red or colored blue is a big danger given how angry i am at the system and i don't want to be removed from the chess board because if nobody's going to talk about jeff epstein there need to be people if nobody's going to talk about various things that we've talked about on these programs i want to make sure that i'm there do i think that this is potentially an existential election yes do i am i positive that i know that my way to bed is the right way out no i'm not i don't know people i just don't know and where we are right now seems so dumb and so catastrophic in terms of how it is chewing up smart people that i decided it's really not about cowardice because i it's hard for me to restrain myself i have so many reactions every day this is really about trying to plan for all of our futures to make sure that i'm around i had a huge concern that what happened to brett's articles of unity was going to happen to brett what's going to happen to the youtube channels i want to make sure that we don't have all of our eggs in one basket so if something goes wrong over there so you know that's the whole idea of the intellectual dark web which is at some level a loose confederation it can become a strong confederation if somebody wants to back it and make it work it can dissolve so that there really isn't anything um the thing is to be hard to kill because ultimately when the hit pieces come they don't come for what it is that they're angry at you about they come for when where they can get you and so it's very important that right in front of an election um yeah i think that the the desire of the old system to defend itself uh through reputational destruction is one of the most pernicious aspects of the new america and we have to fight the ability to destroy reputations as a means of institutions keeping individuals with podcasts and the ability to reach millions like through substance out of their domain i don't surrender this domain to them they have plenty of weaponry with which to fight us and i believe that they could remove you or me in an instant by the end of today if they wanted us off the chessboard we would be off the chess board i know that's not your perspective my goal is to stay here as long as possible to make sure that you have enough of a counterbalancing set of ideas and to let and help other podcasters start and my hope is is that that works but you know long heroism short martyrdom is a good uh motto for anyone and i try to remember the short martyrdom part of that first of all beautifully put second of all way to end the conversation and the disagreement which is how you hook them for the next conversation to be continued when lex says eric it's a huge honor thank you once again lex really appreciate every time we get together thanks buddy thanks for listening to this conversation with eric weinstein and thank you to our sponsors grammarly a service i use in my writing to check spelling grammar sentence structure and readability sunbasket a meal delivery service i use to add healthy variety into my culinary life sem rush the most advanced seo optimization tool i've ever come across i don't like looking at numbers but someone should it helps you make good decisions and finally expressvpn the vpn i've used for many years to protect my privacy on the internet please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from leonard cohen in a song titled hallelujah well maybe there's a god above but all i've ever learned from love was how to shoot somebody who outdrew you and it's not a cry that you're here at night it's not somebody who's seen the light it's a cold and it's a broken hallelujah thank you for listening and hope to see you next time you |
Manolis Kellis: Biology of Disease | Lex Fridman Podcast #133 | the following is a conversation with manolas kellis his third time on the podcast he is a professor at mit and head of the mit computational biology group this time we went deep on the science biology and genetics so this is a bit of an experiment manolas went back and forth between the basics of biology to the latest state of the art and the research he's a master at this so i just said back and enjoyed the ride this conversation happened at 7 00 am so it's yet another podcast episode after an all-nighter for me and once again since the universe has a sense of humor this one was a tough one for my brain to keep up but i did my best and i never shy away from good challenge quick mention of your sponsor followed by some thoughts related to the episode first is sem rush the most advanced seo optimization tool i've ever come across i don't like looking at numbers but someone probably should it helps you make good decisions second is pessimist archive they're back one of my favorite history podcasts on why people resist new things from recorded music to umbrellas to cars chess coffee and the elevator third is eight sleep a mattress that cools itself measures heart rate variability has an app and has given me yet another reason to look forward to sleep including the all-important power nap and finally better help online therapy when you want to face your demons with a licensed professional not just by doing the david goggins like physical challenges like i seem to do on occasion please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that biology in the brain and in the various systems of the body fill me with awe every time i think about how such a chaotic mess coming from its humble origins in the ocean was able to achieve such incredibly complex and robust mechanisms of life that survived despite all the forces of nature that want to destroy it it is so unlike the computing systems we humans have engineered that it makes me feel that in order to create artificial general intelligence and artificial consciousness we may have to completely rethink how we engineer computational systems if you enjoy this thing subscribe on youtube review it with five stars in apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with manolis kalis so your group at mit is trying to understand the molecular basis of human disease what are some of the biggest challenges in your view don't get me started i mean irregularities standing human disease is the most complex challenge in modern science so because human disease is as complex as the human genome it is as complex as the human brain and it is in many ways even more complex because the more we understand disease complexity the more we start understanding genome complexity and epigenome complexity and brain circuitry complexity and immune system complexity and cancer complexity and so on and so forth so traditionally human disease was following basic biology you would basically understand basic biology and model organisms like you know mouse and fly and yeast you would understand sort of mammalian biology and animal biology and eukaryotic biology in sort of progressive layers of complexity getting closer to human phylogenetically and you would do perturbation experiments in those species to see if i knock out a gene what happens and based on the knocking out of these genes you would basically then have a way to drive human biology because you would you would sort of understand the functions of these genes and then if you find that a human gene locus something that you've mapped from human genetics to that gene is related to a particular human disease you say now i know the function of the gene from the model organisms i can now go and understand the function of that gene in human but this is all changing this is dramatically changed so that that was the old way of doing basic biology you would start with the animal models the eukaryotic models the mammalian models and then you would go to human human genetics has been so transformed in the last decade or two that human genetics is now actually driving the basic biology there is more genetic mutation information in the human genome than there will ever be in any other species what do you mean by mutation information so perturbations is how you understand systems so an engineer builds systems and then they know how they work from the inside out a scientist studies systems through perturbations you basically say if i poke that balloon what's going to happen and i'm going to film it in super high resolution understand i don't know aerodynamics or fluid dynamics if it's filled with water etc so you can then make experimentation by perturbation and then the scientific process is sort of building models that best fit the data designing new experiments that best test your models and challenge your models and so forth that's the same thing with science basically if you're trying to understand biological science you basically want to do perturbations that then drive the models so how do these perturbations allow you to understand disease so if if you know that a gene is related to disease you don't want to just know that it's related to the disease you want to know what is the disease mechanism because you want to go and intervene so the way that i like to describe it is that traditionally epidemiology which is basically the study of disease you know sort of the observational study of disease has been about correlating one thing with another thing so if you if you have a lot of people with liver disease who are also alcoholics you might say well maybe the alcoholism is driving the liver disease or maybe those who have liver disease self-medicate with alcohol so that the connection could be either way with genetic epidemiology it's about correlating changes in the genome with phenotypic differences and then you know the direction of causality so if you know that a particular gene is related to the disease you can basically say okay perturbing that gene in mouse causes the mice to have x phenotype so perturbing that gene in human causes the humans to have the disease so i can now figure out what are the detailed molecular phenotypes in the human that are related to that organismal phenotype in the disease so it's all about understanding disease mechanism understanding what are the pathways what are the tissues what are the processes that are associated with the disease so that we know how to intervene you can then prescribe particular medications that also alter these processes you can prescribe lifestyle changes that also affect these processes and so forth that's such a beautiful puzzle to try to solve like what kind of perturbations eventually have this ripple effect that leads to disease across the population and then you study that for animals a mice first and then see how that might possibly connect to humans how hard is that puzzle of trying to figure out how little perturbations might lead to in a stable way to a disease in animals we make the puzzle simpler because we perturb one gene at a time that's the beauty of it's the power of animal models you can basically decouple the perturbations you only do one perturbation and you only do strong perturbations at a time in human the puzzle is incredibly complex because i mean obviously you don't do human experimentation you wait for natural selection and natural genetic variation to basically do its own experiments which it has been doing for hundreds and thousands of years in the human population and for hundreds of thousands of years across you know the the history leading to the human population so you basically take this natural genetic variation that we all carry within us every one of us carries six million perturbations so i've done six million experiments on you six million experiments for me six million experiments on every one of seven billion people on the planet what's the six million correspond to six million unique genetic variants that are segregating the human population every one of us carries millions of polymorphic sites poly many morph forms polymorphic means many forms variants that basically means that every one of us has single nucleotide alterations that we have inherited from mom and from that that basically can be thought of as tiny little perturbations most of them don't do anything but some of them lead to all of the phenotypic differences that we see between us the reason why two twins are identical is because these variants completely determine the way that i'm going to look at exactly 93 years of age how happy are you with this kind of data set is it uh large enough of the human population of earth is that too big too small yeah so so the the is it is it large enough is a power analysis question and in every one of our grants we do a power analysis based on what is the effect size that i would like to detect and what is the natural variation in the two forms so every time you do a perturbation you're asking i'm changing form a into for b form a has some natural genetic vary some natural phenotypic variation around it and form b has some natural phenotypic variation around it if those variances are large and the differences between the mean of a and the mean of b are small then you have very little power the further the means go apart that's the effect size the more power you have and the smaller the standard deviation the more power you have so basically when you're asking is that sufficiently large certainly not for everything but we already have enough power for many of the stronger effects in the more tight distributions so that's a hopeful message that there exists parts of the genome that that have a strong effect that has a small variance that's exactly right unfortunately those perturbations are the basis of disease in many cases so it's not a you know hopeful message sometimes it's a terrible message it's basically well some people are sick but if when if we can figure out what are these contributors to sickness we can then help make them better and help many other people better who don't carry that exact mutation but who carry mutations on the same pathways and that's what we like to call the allelic series of a gene you basically have many perturbations of the same gene in different people each with a different frequency in the human population and each with a different effect on the individual charism so you said uh in the past there would be these small experiments on perturbations and animal models what does this puzzle solving process look like today so we basically have you know something like seven billion people in the planet and every one of them carries something like six million mutations you basically have an enormous matrix of genotype by phenotype by systematically measuring the phenotype of these individuals and the traditional way of measuring this phenotype has been to look at one trait at a time you would gather families and you would sort of paint the pedigrees of a strong effect what we like to call mendelian mutation so a mutation that gets transmitted in a dominant or a recessive but strong effect form where basically one locus plays a very big role in that disease and you could then look at carriers versus non-carriers in one family carries versus non-carriers in another family and do that for hundreds sometimes thousands of families and then trace these inheritance patterns and then figure out what is the gene that plays that role is this the matrix that you're showing in in talks or lectures so that matrix is the input to the stuff that i saw in talks so basically that matrix has traditionally been strong effect genes what the matrix looks like now is instead of pedigrees instead of families you basically have thousands and sometimes hundreds of thousands of unrelated individuals each with all of their genetic variants and each with their phenotype for example height or lipids or you know whether they're sick or not for a particular trait that has been the modern view instead of going to families going to unrelated individuals with one phenotype at a time and what we're doing now as we're maturing in all of these sciences is that we're doing this in the context of large medical systems or enormous cohorts that are very well phenotyped across hundreds of phenotypes sometimes with our complete electronic health record so you can now start relating not just one gene segregating one family not just thousands of variants segregating with one phenotype but now you can do millions of variants versus hundreds of phenotypes and as a computer scientist i mean deconvolving that matrix partitioning it into the layers of biology that are associated with every one of these elements is a dream come true it's it's like the world's greatest puzzle and you can now solve that puzzle by throwing in more and more knowledge about the function of different genomic regions and how these functions are changed across tissues and in the context of disease and that's what my group and many other groups are doing we're trying to systematically relate this genetic variation with molecular variation at the expression level of the genes at the epigenomic level of the gene regulatory circuitry and at the cellular level of what are the functions that are happening in those cells at the single cell level using single cell profiling and then relate all that vast amount of knowledge computationally with the thousands of traits that each of these of thousands of variants are perturbing i mean this is something we talked about i think last time so there's these effects at different levels that happen you said at a single cell level you're trying to see things that happen due to certain perturbations and then so it's not just like a puzzle of um perturbation and disease it's perturbation then effect at a cellular level at an organ level a body like how do you disassemble this into like what your group is working on you're basically taking a bunch of the hard problems in the space how do you break apart a difficult disease uh and break it apart into problems that you into puzzles that you can now start solving so there's a struggle here computer scientists love hard puzzles and they're like oh i want to you know build a method that just deconvolves the whole thing computationally and you know that's very tempting and it's very appealing but biologists just like to decouple that complexity experimentally to just like peel off layers of complexity experimentally and that's what many of these modern tools that you know my group and others have both developed and used the fact that we can now figure out tricks for peeling off these layers of complexity by testing one cell type at a time or by testing one cell at a time and you could basically say what is the effect of this genetic variant associated with alzheimer's on human brain human brain sounds like oh it's an organ of course just go one organ at a time but human brain has of course dozens of different brain regions and within each of these brain regions dozens of different cell types and every single type of neuron every single type of glial cell between astrocytes oligodendrocytes microglia between you know all of the neural cells and the vascular cells and the immune cells that are co-inhabiting the the brain between the different types of excitatory and inhibitory neurons that are sort of interacting with each other between different layers of neurons in the cortical layers every single one of these has a different type of function to play in cognition in interaction with the environment in maintenance of the brain in energetic needs in feeding the brain with blood with oxygen in clearing out the debris that are resulting from the super high energy production of cognition in in humans so all of these things are basically um potentially deconvolvable computationally but experimentally you can just do single cell profiling of dozens of regions of the brain across hundreds of individuals across millions of cells and then now you have pieces of the puzzle that you can then put back together to understand that complexity i mean first of all i mean the human brain the cells in the human brain are the most okay maybe i'm romanticizing it but cognition seems to be very complicated so uh separating into the function breaking alzheimer's down to the cellular level seems very challenging is that basically you're trying to find a way that some perturbation and genome results in some obvious major dysfunction in the cell you're trying to find something like that exactly so so what does human genetics do human genetics basically looks at the whole path from genetic variation all the way to disease so human genetics has basically taken thousands of alzheimer's cases and thousands of controls matched for age for sex for you know environmental backgrounds and so forth and then looked at that map where you're asking what are the individual genetic persuasions and how are they related to all the way to alzheimer's disease and that has actually been quite successful so we now have you know more than 27 different loci these are genomic regions that are associated with alzheimer's at this end-to-end level but the moment you sort of break up that very long path into smaller levels you can basically say from genetics what are the epigenomic alterations at the level of gene regulatory elements where that genetic variant perturbs the control region nearby that effect is much larger you mean much larger in terms of this down the line impact or it's much larger in terms of the measurable effect this a versus b variance is actually so much cleanly defined when you go to the shorter branches because for one genetic variant to affect alzheimer's that's a very long path that basically means that in the context of millions of these six million variants that every one of us carries that one single nucleotide has a detectable effect all the way to the end i mean it's just mind-boggling that that's even possible but indeed yeah but indeed there are such effects so the hope is or the most scientifically speaking the the most effective place where to detect the alteration that results in disease is earlier on in the pipeline as early as possible it's it's a trade-off if you go very early on in the pipeline now each of these epigenomic alterations for example this enhancer control region is active maybe 50 less which is a dramatic effect now you can ask well how much does changing one regulatory region in the genome in one cell type change disease well that path is now long so if you instead look at expression the path between genetic variation the expression of one gene goes through many enhancer regions and therefore it's a subtler effect at the gene level but then now you're closer because one gene is acting on you know in the context of only 20 000 other genes as opposed to one enhancer acting in the context of two million other enhancers so you basically now have genetic epigenomic the circuitry transcriptomic the gene expression level and then cellular where you can basically say i can measure various properties of those cells what is the calcium influx rate when i have this genetic variation what is the synaptic density what is the electric impulse conductivity and so on so forth so you can measure things along this path to disease and you can also measure endophenotypes you can basically measure you know your brain activity you can do imaging in the brain you can basically measure i don't know the heart rate the pulse the lipids the amount of blood secreted and so forth and then through all of that you can basically get at the path to causality the path to disease and is there something beyond cellular so you mentioned lifestyle interventions or changes as a way to or like be able to prescribe changes in life style like what what about organs what about like the function of the body as a whole yeah absolutely so basically when you go to your doctor they always measure you know your pulse they always measure your height those measure your weight your you know your bmis basically these are just very basic variables but with digital devices nowadays you can start measuring hundreds of variables for every individual you can basically also phenotype cognitively through tests uh alzheimer's patients there are cognitive tests that you can imagine that you that you typically do for uh cognitive decline these minimental you know observations that that you have specific questions too you can think of sort of enlarging the set of cognitive tests so in the mouse for example you do experiments for how do they get out of mazes how do they find food whether they recall a fear whether they shake in a new environment and so forth in the human you can have much much richer phenotypes where you can basically say not just imaging at the you know organ level but and all kinds of other activities at the organ level but you can also do at the organism level you can do behavioral tests and how did they do on empathy how did they do on memory how did they do on long-term memory versus short-term memory and so forth i love how you're calling that phenotype i guess it is it is but like your behavior patterns that might change over over uh over a period of a life it's yeah your ability to remember things your ability to be yeah empathetic or emotionally your intelligence perhaps even yeah but intelligence has hundreds of variables you can be your math intelligence your literary intelligence your puzzle-solving intelligence your logic it could be like hundreds of things and all of that is it's we were able to measure that better and better so and all that could be connected to the entire pipeline we used to think of each of these as a single variable like intelligence i mean that's ridiculous it's basically dozens of different genes that are controlling every single variable you can basically think of you know imagine us in a video game where every one of us has measures of you know strength stamina you know energy left and so forth but you could click on each of those like five bars that are just the main bars and each of those will just give you then hundreds of bars yeah and you can basically say okay great for my you know machine learning task i want someone who i'm a human who has these particular forms of intelligence i require now these you know 20 different things and then you can combine those things and then relate them to of course performance in a particular task but you can also relate them to genetic variation that might be affecting different parts of the brain for example your frontal cortex versus your temporal cortex versus your visual cortex and so forth so genetic variation that affects expression of genes in different parts of your brain can basically affect your you know music ability your auditory ability your smell your you know just dozens of different phenotypes can be broken down into you know hundreds of cognitive variables and then relate each of those to thousands of genes that are associated with them so somebody who loves rpgs role-playing games there's uh there's too few variables that we can control so i'm excited if we're in fact living in a simulation and this is a video game i'm excited by the quality of of the video game the the the the game designer did a hell of a good job so we're impressed oh i don't know the sunset last night was a little unrealistic yeah yeah the graphics exactly come on nvidia to zoom back out we've been talking about the genetic origins of diseases but i think it's fascinating to talk about what are the most important diseases to understand and especially as it connects to the things that you're working on so it's very difficult to think about important diseases to understand there's many metrics of importance one is lifestyle impact i mean if you look at kovid the impact on lifestyle has been enormous so understanding kovid is important because it has impacted the well-being in terms of ability to have a job ability to have an apartment ability to go to work ability to have a mental circle of support and all of that for you know millions of americans like huge huge impact so that's one aspect of importance so basically mental disorders alzheimer's has a huge importance in the well-being of americans whether or not it die it kills someone for many many years it has a huge impact so the first measure of importance is just well-being like impact on the quality of life impact on the quality of life absolutely the second metric which is much easier to quantify is deaths what is the number one killer the number one killer is actually heart disease it is actually killing 650 000 americans per year number two is cancer with 600 000 americans number three far far down the list is accidents every single accident combined so basically you you know you read the news accidents like you know there was a huge car crash all over the news but the number of deaths number three by far 167 000 lower respiratory disease so that's asthma not being able to breathe and so forth 160 000 alzheimer's number four number five with 120 000 and then stroke brain aneurysms and so forth that's 147 000 diabetes and metabolic disorders etc that's 85 000. the flu is 60 000 suicide 50 000 and then overdose et cetera you know goes further down the list so of course kovit has creeped up to be the number three killer this year with you know more than 100 000 americans and counting um and you know but but if you think about sort of what do we use what are the most important diseases you have to understand both the quality of life and the the sheer number of deaths and just numbers of years lost if you wish and and uh each of these diseases you can think of as uh and also including terrorist attacks and school shootings for example things which lead to fatalities you can look at as problems that could be solved and some problems are harder to solve than others i mean that's part of the equation so maybe if you look at these diseases if you look at heart disease or cancer or alzheimer's or just like schizophrenia and obesity w like not necessarily things that kill you but affect the quality of life which problems are solvable which aren't which are harder to solve which aren't i love your question because it puts it in the context of a global um effort rather than just a local effort so basically if you look at the global aspect exercise and nutrition are two interventions that we can as a society make a much better job at so if you think about sort of the availability of cheap food it's extremely high in calories it's extremely detrimental for you like a lot of processed food etc so if we change that equation and as a society we made availability of healthy food much much easier and charged a burger at mcdonald's the price that it costs on the health system then people would actually start buying more healthy foods so basically that's sort of a societal intervention if you wish in the same way increasing empathy increasing education increasing the social framework and support would basically lead to fewer suicides it would lead to fewer murders it would lead to fewer you know deaths overall so you know that's something that we as a society can do you can you can also think about external factors versus internal factors so the external factors are basically communicable diseases like covid like the flu etc and the internal factors are basically things like you know cancer and alzheimer's where basically your your genetics will eventually you know drive you there um and then of course with all of these factors every single disease has both a genetic component and environmental component so heart disease you know huge then they contribute contribution alzheimer's it's like you know 60 plus genetic so i think it's like 79 heritability so that basically means that genetics alone explains 79 of alzheimer's incidence and yes there's a 21 environmental component where you could basically enrich your cognitive environment enrich your social interactions read more books learn a foreign language go running you know sort of have a more fulfilling life all of that will actually decrease alzheimer's but there's a limit to how much that that can impact because of the huge genetic footprint so this is fascinating so each one of these problems have a genetic component and an environment component and so like when there's a genetic component what can we do about some of these diseases what what have you worked on what can you say that's uh in terms of problems that are solvable here or understandable so my group works on the genetic component but i would argue that understanding the genetic component can have a huge impact even on the environmental component why is that because genetics gives us access to mechanism and if we can alter the mechanism if we can impact the mechanism we can perhaps counteract some of the environmental components interesting so understanding the biological mechanisms leading to disease is extremely important in being able to intervene but when you can intervene what you know the analogy that i like to gay to give is for example for obesity you know think of it as a giant bathtub of fat there's basically fat coming in from your diet and there's fat coming out from your exercise okay that's an in out equation and that's the equation that everybody's focusing on but your metabolism impacts that you know bathtub basically your metabolism controls the rate at which you're burning energy it controls away the rate at which you're storing energy and it also teaches you about the various valves that control the input and the output equation so if we can learn from the genetics the valves we can then manipulate those valves and even if the environment is feeding you a lot of fat and getting a little that out you just poke another hole at the bathtub and just get a lot of the fat out yeah that's fascinating yeah so that we're not just passive observers of our genetics the more we understand the more we can come up with actual treatments and i think that's an important uh aspect to realize when people are thinking about strong effect versus weak effect variants so some variants have strong effects we talked about these mendelian disorders where a single gene has a sufficiently large effect pen and trans expressivity and so so forth that basically you can um trace it in families with cases and not cases cases not cases and so forth but even the you know but so so these are the genes that everybody says oh that's the genes we should go after because that's a strong effect gene i like to think about it slightly differently these are the genes where genetic impacts that have a strong effect were tolerated because every single time we have a genetic association with disease it depends on two things number one the obvious one whether the gene has an impact on the disease number two the more subtle one is whether there is genetic in variation standing and circulating and segregating in the human population that impacts that gene some genes are so darn important that if you mess with them even a tiny little amount that person is dead so those genes don't have variation you're not going to find the genetic association if you don't have variation that doesn't mean that the gene has no role it's simply that the gene it simply means that the gene tolerates no mutations so that's actually a strong signal when there's no variation that's so fast exactly genes that have very little variation are hugely important you can actually rank the importance of genes based on how little variation they have and those genes that have very little variation but no association with disease that's a very good metric to say oh that's probably a developmental gene because we're not good at measuring those phenotypes so it's genes that you can tell evolution has excluded mutations from but yet we can't see them associated with anything that we can measure nowadays it's probably early embryonic lethal what are all the words you just said earlier in brionic what lethal meaning meaning that if you don't have it okay there's a bunch of stuff that um is required for a stable functional organism exactly across the board for our entire for for entire species i guess if you look at sperm it expresses thousands of proteins does sperm actually need thousands of proteins no but it's probably just testing them so my speculation is that misfolding of these proteins is an early test for failure so that out of the you know millions of sperm that are possible you select the subset that are just not grossly misfolding thousands of proteins so it's kind of an assert uh that this is followed correctly correct yeah this uh just uh because if this little thing about the folding of a protein is incorrect that probably means somewhere down the line there's a bigger issue that's exactly right so fail fast so basically if you look at the mammalian investment in a new born that investment is enormous in terms of resources so mammals have basically evolved mechanisms for fail fast where basically in those early months of development i mean it's it's horrendous of course at the personal level when you lose a uh you know your future child but in some ways there's so little hope for that child to develop and sort of make it through the remaining months that sort of fail fast is probably a good evolutionary principle from an evolutionary perspective for mammals and of course humans have a lot of medical resources that you can sort of give those children a chance and you know we have so much more success in sort of giving folks who have these strong carrier mutations a chance but if they're not even making it through the first three months we're not going to see them so that's why when we when we say what are the most important genes to focus on the ones that have a strong effect mutation or the ones that have a weak effect mutation well you know the jury might be out because the ones that have a strong effect mutation are basically you know not mattering as much the ones that only have weak effect mutations by understanding through genetics that they have a weak effect mutation and understanding that they have a causal role on the disease we can then say okay great evolution has only tolerated a two percent change in that gene pharmaceutically i can go in and induce a 70 change in that gene and maybe i will poke another hole at the bathtub that was not easy to control in you know many of the other sort of strong effect genetic variants so okay so there's this beautiful map of uh across the population of things that you're saying strong and weak effects so stuff with a lot of mutations and stuff with little mutations with no mutations and you have this map and it's it lays out the puzzle yeah so so when i say strong effect i mean at the level of individual mutations so so basically genes where so so you have to think of first the effect of the gene on the disease remember how i was sort of painting that map earlier from genetics all the way to phenotype that gene can have a strong effect on the disease but the genetic variant might have a weak effect on the gene so basically when you ask what is the effect of that genetic variant on the disease it could be that that genetic variant impacts the gene by a lot and then the gene impacts the disease by a little or it could be that the genetic variant impacts the gene by a little and then the gene impacts the disease by a lot so what we care about is genes that impact the disease a lot but genetics gives us the full equation and what i would argue is if we couple the genetics with expression variation to basically ask what genes change by a lot and you know which genes correlate with disease by a lot even if the genetic variants change them by a little then that those are the best places to intervene those are the best places where pharmaceutically if i have even a modest effect i will have a strong effect on the disease whereas those genetic variants that have a huge effect on the disease i might not be able to change that gene by this much without affecting all kinds of other things interesting so yeah okay so that's what we're looking at then what have we been able to find in terms of which disease could be helped again don't get me started this is um we have found so much our understanding of disease has changed so dramatically with genetics i mean places that we had no idea would be involved so one of the worst things about my genome is that i have a genetic predisposition to age-related macular degeneration amd so it's a form of blindness that causes you to to lose the central part of your vision progressively as you grow older my increased risk is fairly small i have an eight percent chance you only have a six percent chance you i'm on average yeah by the way when you say my you mean literally yours you know this about you i know this about me yeah which is kind of uh i mean uh philosophically speaking is a pretty powerful thing so to live with i mean maybe that's uh so we agreed to talk again by the way for the listeners to where we're going to try to focus on science today and a little bit of philosophy next time but it's uh interesting to think about the more you're able to know about yourself from the genetic information in terms of the diseases how that changes your own view of life yeah so there's there's a lot of impact there and there's a something called genetic exceptionalism which basically thinks of genetics as something very very different than everything else as a type of determinism and um you know let's talk about that next time so basically it's a good preview yeah so let's go back to amd so basically with amd we have no idea what causes amd you know it was it was a mystery until the genetics were worked out and now the fact that i know that i have a predisposition allows me to sort of make some life choices number one but number two the genes that lead to that predisposition give us insights as to how does it actually work and that's a place where genetics gave us something totally unexpected so there's a complement pathway which is an immune function pathway that was in you know most of the loci associated with amd and that basically told us that wow there's an immune basis to this eye disorder that people had just not expected before if you look at complement it was recently also implicated in schizophrenia and there's a type of microglia that is involved in synaptic pruning so synapses are the connections between neurons and in this whole use it or lose it view of mental cognition and other capabilities you basically have uh microglia which are immune cells that are sort of constantly traversing your brain and then pruning neuronal connections pruning synaptic connections that are not utilized so in schizophrenia there's thought to be a change in the pruning that basically if you don't prune your synapses the right way you will actually have an increased role of schizophrenia this is something that was completely unexpected for schizophrenia of course we knew it has to do with neurons but the role of the complement complex which is also implicated in amd which is now also implicating schizophrenia was a huge surprise what's the complement complex so it's basically a set of genes the complement genes that are basically having various immune roles and as i was saying earlier our immune system has been co-opted for many different roles across the body so they actually play many diverse roles and somehow the immune system is connected to the synaptic pruning process exact process exactly so immune cells were co-opted to prune synapses how did you figure this out how does one go about figuring this intricate connection uh like pipeline of connections out yeah let me give you another example so so alzheimer's disease the first place that you would expect it to act is obviously the brain so we had basically this roadmap epigenomics consortium view of the human epigenome the largest map of the human epigenome that has ever been built across 127 different tissues and samples with dozens of epigenomic marks measured in you know hundreds of donors so what we've basically learned through that is that you you basically can map what are the active gene regulatory elements for every one of the tissues in the body and then we connected these gene regulatory active maps of basically what regions of the human genome are turning on in every one of different tissues we then can go back and say where are all the genetic loci that are associated with disease this is something that my group i think was the first to do back in 2010 in this ernst nature biotech paper but basically we were for the first time able to show that specific chromatin states specific epigenomic states in that case enhancers were in fact enriched enriched in disease associated variants we pushed that further in the ernst nature paper a year later and then in this roadmap epigenomics paper you know a few years after that but basically that matrix that you mentioned earlier was in fact the first time that we could see what genetic traits have genetic variants that are enriched in what tissues in the body and a lot of that map made complete sense if you looked at a diversity of immune traits like allergies and type 1 diabetes and so forth you basically could see that they were enriching that the genetic variants associated with those traits were enriched in enhancers in these gene regulatory elements active in t cells and b cells and hematopoietic stem cells and so forth so that basically gave us a confirmation in many ways that those immune traits were instead indeed enriching immune cells if you look if you if you looked at type 2 diabetes you basically saw an enrichment in only one type of sample and it was pancreatic eyelids and we know that type 2 diabetes in you know sort of stems from the dysregulation of insulin in the beta cells of pancreatic eyelids and that sort of was you know spot on super precise if you looked at blood pressure where would you expect blood pressure to occur you know i don't know maybe in your metabolism in ways that you process coffee or something like that maybe in your brain the way that you stress out increases your blood pressure etc what we found is that blood pressure localized specifically in the left ventricle of the heart so the enhancers of the left technology in the heart contain a lot of genetic variants associated with blood pressure if you look at height we found an enrichment specifically in embryonic stem cell enhancers so the genetic variants predisposing you to be taller or shorter are in fact acting in developmental stem cells makes complete sense if you looked at inflammatory bowel disease you basically found inflammatory which is immune and also bowel disease which is digestive and indeed we saw a double enrichment both in the immune cells and in the digestive cells so that basically told us that this is acting in both components there's an immune component to inflammatory bowel disease and there's a digestive component and the big surprise was for alzheimer's we had seven different brain samples we found zero enrichment in the brain samples for genetic variants associated with alzheimer's and this is mind-boggling our brains were literally hurting what is going on and what is going on is that the brain samples are primarily neurons oligodendrocytes and astrocytes in terms of the cell types that make them up so that basically indicated that genetic variants associated with alzheimer's were probably not acting in oligodendrocytes astrocytes or neurons so what could they be acting in well the fourth major cell type is actually microglia microglia are resident immune cells in your brain oh nice the immune oh wow and they are cd14 plus which is this sort of cell surface markers uh of those cells so their cd14 plus cells just like macrophages that are circulating in your blood the microglia are resident monocytes that are basically sitting in your brain they're tissue-specific monocytes and every one of your tissues like your your fat for example has a lot of macrophages that are resin and the m1 versus m2 macrophage ratio has a huge role to play in obesity and you know so basically again these immune cells are everywhere but basically what we found through this completely unbiased view of what are the tissues that likely underlie different disorders we found that alzheimer's was humongously enriched in microglia but not at all in the other cell types so what what are we supposed to make that if you look at the tissues involved is that simply useful for indication of uh propensity for disease or does it give us somehow a pathway of treatment it's very much the second if you look at the um the way to therapeutics you have to start somewhere what are you gonna do you're gonna basically make assays that manipulate those genes and those pathways in those cell types so before we know the tissue of action we don't even know where to start we basically are at a loss but if you know the tissue of action and even better if you know the pathway of action then you can basically screen your small molecules not for the gene you can screen them directly for the pathway in that cell type so you can basically develop a high throughput multiplexed you know robotic system for testing the impact of your favorite molecules that you know are safe efficacious and you know sort of hit that particular gene and so forth you can basically screen those molecules against either a set of genes that act in that pathway or on the pathway directly by having a cellular assay and then you can basically go into mice and do experiments and basically sort of figure out ways to manipulate these processes that allow you to then to go back to humans and do a clinical trial that basically says okay i was able indeed to reverse these processes in mice can i do the same thing in humans so that the the knowledge of the tissues gives you the pathway to treatment but that's not the only part there are many additional steps to figuring out the mechanism of disease i mean so that's really promising maybe uh to take a small step back you've you've mentioned all these puzzles that were figured out with the nature paper for i mean you've mentioned a ton of diseases from obesity to alzheimer's even schizophrenia i think you mentioned and just what is the actual methodology of figuring this out so indeed i mentioned a lot of diseases and and my lab works on a lot of different disorders and the reason for that is that if you look at the if you look at biology it used to be you know zoology departments in both technology departments and you know virology departments and so on so forth and mit was one of the first schools to basically create a biology department like oh we're going to study all of life suddenly why was that even the case because the advent of dna and the genome and the central dogma of dna makes rna mixed protein in many ways unified biology you could suddenly study the process of transcription in viruses or in bacteria and have a huge impact on yeast and fly and maybe even mammals because of this realization of these common underlying processes and in the same way that dna unified biology genetics is unifying disease studies so you used to have um you used to have uh you know i don't know um cardiovascular disease department and uh you know neurological disease department and neurodegeneration department and uh you know um basically immune and cancer and so forth and all of these were studied in different labs you know because it made sense because basically the first step was understanding how the tissue functions and we kind of knew the tissues involved in cardiovascular disease and so forth but what's happening with human genetics is that all of that all of these walls and edifices that we had built are crumbling and the reason for that is that genetics is in many ways revealing unexpected connections so suddenly we now have to bring the immunologists to work on alzheimer's they were never in the room they were in another building altogether the same way for schizophrenia we now have to sort of worry about all these interconnected aspects for metabolic disorders we're finding contributions from brain so suddenly we have to call the neurologist from the other building and so forth so in my view it makes no sense anymore to basically say oh i'm a geneticist studying immune disorders i mean that's that's ridiculous because i mean yeah of course in many ways you still need to sort of focus but what what what we're doing is that we're basically saying we'll go wherever the genetics takes us and by building these massive resources by working on our latest map is now 833 tissues sort of the the next generation of the epigenomics roadmap which we're now called epimap is 833 different tissues and using those we've basically found enrichments in 540 different disorders those enrichments are not like oh great you guys work on that and we'll work on this they're intertwined amazingly so of course there's a lot of modularity but there's these enhancers that are sort of broadly active and these disorders that are broadly active so basically some enhancers are active in on tissues and some disorders are enriching in all tissues so basically there's these multifactorial and this other class which i like to call polyfactorial diseases which are basically lighting up everywhere and in many ways it's you know sort of cutting across these walls that were previously built across these departments and the polyfactorial ones were probably the previous structure departments wasn't equipped to deal with those i mean again maybe it's a romanticized question but you know there's in physics there's a theory of everything do you think it's possible to move towards an almost theory of everything of disease from a genetic perspective so if this unification continues is it possible that like do you think in those terms like trying to arrive at a fundamental understanding of how disease emerges period that unification is not just foreseeable it's inevitable i see it as inevitable we have to go there you cannot be a specialist anymore if you're a genomicist you have to be a specialist in every single disorder and the reason for that is that the fundamental understanding of the circuitry of the human genome that you need to solve schizophrenia that fundamental circuitry is hugely important to solve alzheimer's and that same circuitry is hugely important to solve metabolic disorders and that same exact circuitry is uh hugely important for solving immune disorders and cancer and you know every single disease so all of them have the same sub task and i teach dynamic programming in my class dynamic program is all about sort of not re doing the work it's reusing the work that you do once so basically for us to say oh great you know you guys in the immune building go solve the fundamental circuitry of everything and then you guys in the schizophrenia building go solve the fundamental circuitry of everything separately is crazy so what we need to do is come together and sort of have a circuitry group the circuitry building that sort of tries to solve the circuitry of everything and then the immune folks who will apply this knowledge to all of the disorders that are associated with immune dysfunction and the schizophrenia folks will basically interact with both the immune folks and with the neuronal folks and all of them will be interacting with the circuitry folks and so forth so that's sort of the current structure of my group if you wish so basically what we're doing is focusing on the fundamental circuitry but at the same time we're the users of our own tools by collaborating with many other labs in every one of these disorders that we mentioned we basically have a heart focus on cardiovascular disease coronary artery disease heart failure and so forth we have an immune focus on several immune disorders we have a cancer focus on metastatic melanoma and immunotherapy response we have a psychiatric disease focus on schizophrenia autism ptsd and other psychiatric disorders we have an alzheimer's and neurodegeneration focus on huntington disease als and you know ad related disorders like frontotemporal dementia and lewy body dementia and of course a huge focus on alzheimer's we have a metabolic focus on the role of exercise and diet and sort of how they're impacting metabolic you know organs across the body and across many different tissues and all of them are interfacing with the circuitry and the reason for that is another computer science principle of eat your own dog food if everybody ate their own dog food dog food would taste a lot better the reason why microsoft excel and word and powerpoint was so important and so successful is because the employees that were working on them were using them for their day-to-day tasks you can't just simply build a circuitry and say here it is guys take the circuitry we're done without being the users of that circuitry because you then go back and because we span the whole spectrum from profiling the epigenome using comparative genomics finding the important nucleotides in the genome building the basic functional map of what are the genes in the human genome what are the gene regulatory elements of the human genome i mean over the years we've written a series of papers on how do you find human genes in the first place using comparative genomes how do you find the motifs that are the building blocks of gene regulation used in comparative genomics how do you then find how these motifs come together and act in specific tissues using epigenomics how do you link regulators to enhancers and enhancers to their target genes using epigenomics and regulatory genomics so through the years we've basically built all this infrastructure for understanding what i like to say every single nucleotide of the human genome and how it acts in every one of the major cell types and tissues of the human body i mean this is no small task this is an enormous task that takes the entire field and that's something that my group has taken on along with many other groups and we have also and that sort of thing sets my group perhaps apart we have also worked with specialists in every one of these disorders to basically further our understanding all the way down to disease and in some cases collaborating with pharma to go all the way down to therapeutics because of our deep deep understanding of that basic circuitry and how it allows us to now improve the circuitry not just treat it as a black box but basically go and say okay we need a better cell type specific wiring that we now have at the tissue specific level so we're focusing on that because we're understanding you know the needs from the disease front so you have a sense of the entire pipeline i mean one maybe you can indulge me one nice question to ask would be how do you from the scientific perspective go from knowing nothing about the disease to going you said uh to go into the entire pipeline and actually have a drug or or a treatment that cures that disease so that's an enormously long path and an enormously great challenge and what i'm trying to argue is that it progresses in stages of understanding rather than one gene at a time the traditional view of biology was you have one postdoc working on this gene and another prosthetic working on that gene and they'll just figure out everything about that gene and that's their job what we've realized is how polygenic the diseases are so we can't have one postdoctoral gene anymore we now have to have these cross-cutting needs and i'm going to describe the path to circuitry along those needs and every single one of these paths we are now doing in parallel across thousands of genes so the first step is you have a genetic association and we talked a little bit about sort of the mendelian path and the polygenic path to that association so the mendelian path was looking through families to basically find gene regions and ultimately genes that are underlying particular disorders the polygenic path is basically looking at unrelated individuals in this giant matrix of genotype by phenotype and then finding hits where a particular variant impacts disease all the way to the end and then we now have a connection not between a gene and a disease but between a genetic region and a disease and that distinction is not understood by most people so i'm going to explain it a little bit more why do do we not have a connection between a gene and a disease but we have a connection between a genetic region and a disease the reason for that is that 93 of genetic variants that are associated with disease don't impact the protein at all so if you look at the human genome there's 20 000 genes there's 3.2 billion nucleotides only 1.5 percent of the genome codes for proteins the other 98.5 does not code for proteins if you now look at where are the disease variants located 93 percent of them fall in that outside the genes portion of course genes are enriched but they're only enriched by a factor of three that means that still 93 of genetic variants fall outside the proteins why is that difficult why is that a problem the problem is that when a variant falls outside the gene you don't know what gene is impacted by that variant you can't just say oh it's near this gene let's just connect that variant to the gene and the reason for that is that the genome circuitry is very often long range so you basically have that genetic variant that could sit in the intron of one gene and an intron is sort of the place between the axons that code for proteins so proteins are split up into exons and introns and every exon codes for a particular subset of amino acids and together they're spliced together and then make the final protein so that genetic variant might be sitting in an intron of a gene it's transcribed with the gene it's processed and then excised but it might not impact this gene at all it might actually impact another gene that's a million nucleotides away so it's just riding along even though it has nothing to do with the with this nearby neighborhood that's exactly right let me give you an example the strongest genetic association with obesity was discovered in this fto gene fat and obesity-associated gene so this fto gene was studied ad nauseum people did tons of experiments on on it they figured out that fto is in fact a rna methylation transferase it basically crea it sort of impacts something that we know that we call the epi transcriptome just like the genome can be modified the transcriptome the transcript of the genes can be modified and we basically said oh great that means that that ap transcriptomics is hugely involved in obesity because that that gene fto is is you know uh clearly where the genetic locus is at my group studied fto in collaboration with you know a wonderful team led by melina klausmitzer and what we found is that this fto locus even though it is associated with obesity does not implicate the fto gene the genetic variant sits in the first intron of the fdo gene but it controls two genes irx3 and ir x5 that are sitting 1.2 million nucleotides away several genes away oh boy uh what am i supposed to feel about that because isn't that like super complicated then uh so so the way that i was introduced at a conference a few years ago was uh and here's manolis kellys who wrote the most depressing paper of 2015 and the reason for that is that the entire pharmaceutical industry was so comfortable that there was a single gene in that locus because in some loci you basically have three dozen genes that are all sitting in the same region of association and you're like gosh which ones of those is it but even that question of which ones of those is it is making the assumption that it is one of those as opposed to some random gene just far far away which is what our paper showed so basically what our paper showed is that you can't ignore the circuitry you have to first figure out the circuitry all of those long-range interactions how every genetic variant impacts the expression of every gene in every tissue imaginable across hundreds of individuals and then you now have one of the building blocks not even all of the building blocks for them going and understanding disease so okay so so embrace the the wholeness of the circuitry correct but what so back to the question of starting knowing nothing to the disease and and going to the treatment so what are the next steps so you basically have to first figure out the tissue and then describe how you figure out the tissue you figure out the tissue by taking all of these non-coding variants that are sitting outside proteins and then figuring out what are the epigenomic enrichments and the reason for that you know thankfully is that there is convergence that the same processes are impacted in different ways by different loci and that's a saving grace for our field the fact that if i look at hundreds of genetic variants associated with alzheimer's they localize in a small number of processes can you clarify why that's helpful so like they show up in the same exact way in the in the specific set of processes yeah so basically there's a small number of biological processes that underlie or at least that play them the biggest role in every disorder so in alzheimer's you basically have you know maybe 10 different types of processes one of them is lipid metabolism one of them is immune cell function one of them is neuronal energetics so these are just a small number of processes but you have multiple lesions multiple genetic perturbations that are associated with those processes so if you look at schizophrenia it's excitatory neuron function it's inhibitory neuron function it's synaptic pruning it's calcium signaling and so forth so when you look at disease genetics you have one hit here and one hit there and one hit there and one hit there completely different parts of the genome but it turns out all of those he hits are calcium signaling proteins oh cool you're like aha that means that calcium signaling is important so those people who are focusing on one doctors at a time cannot possibly see that picture you have to become a genomicist you have to look at the omics the um the holistic picture to understand these enrichments but you mentioned the convergence thing so the the whatever the thing associated with the disease shows up so let me explain convergence yeah convergence is such a beautiful concept so you basically have these four genes that are converging on calcium signaling so that basically means that they are acting each in their own way but together in the same process but now in every one of these loci you have many enhancers controlling each of those genes that's another type of convergence where dysregulation of seven different enhancers might all converge on this regulation of that one gene which then converges on calcium signaling and in each one of those enhancers you might have multiple genetic variants distributed across many different people everyone has their own different mutation but all of these mutations are impacting that enhancer and all of these enhancers are impacting that gene and all of these genes are impacting this pathway and all these pathways are acting in the same tissue and all these tissues are converging together on the same biological process of schizophrenia and and you're saying the saving grace is that that conversion seems to happen for a lot of these diseases for all of them basically that for every single disease that we've looked at we have found an epigenomic enrichment how do you do that you basically have all of the genetic variants associated with the disorder and then you're asking for all of the enhancers active in a particular tissue for 540 disorders we've basically found that indeed there is an enrichment that basically means that there is commonality and from the commonality we can just get insights so to explain in mathematical terms we're basically building an empirical prior we're using a bayesian approach to basically say great all of these variants are equally likely in a particular locus to be important energy so in a genetic locus you basically have a dozen variants that are co-inherited because the way that inheritance works in the human genome is through all of these recombination events during meiosis you basically have you know you you inherit maybe three chromosome three for example in your in your body it's inherited from four different parts one part comes from your dad another part comes from your mom another part comes from your dad and other part comes from your mom so basically the way that it i'm sorry from your mom's mom so you basically have one copy that comes from your dad and one copy that comes from your mom but that copy that you got from your mom is a mixture of her maternal and her paternal chromosome and the copy that you got from your dad is a mixture of his maternal and his paternal chromosome so these break points that happen when chromosomes are lighting up and lining up are basically ensuring through these crossover events they're ensuring that every uh child cell during the process of meiosis where you basically have you know one spermatozoid that basically couples with one oval to basically create one egg to basically create the zygote you basically have half of your genome that comes from that and half of your genome that comes from mom but in order to light up not line them up you basically have these crossover events these crossover events are basically leading to co-inheritance of that entire block coming from the your maternal grandmother and that entire block coming from your mother grand grandfather over many generations these crossover events don't happen randomly there's a protein called prdm9 that basically guides the double-stranded breaks and then leads to these crossovers and that protein has a particular preference to only a small number of hot spots of recombination which then lead to a small number of breaks between these co-inheritance patterns so even though there are six million variants there are six million loci there there's you know this variation is inherited in blocks and every one of these blocks has like two dozen genetic variants that are all associated so in the case of fto it wasn't just one variant it was 89 common variants that were all humongously associated with obesity which ones of those is the important one well if you look at only one locus you have no idea but if you look at many loci you basically say aha all of them are enriching in the same epigenomic map in that particular case it was mesenchymal stem cells so these are the progenitor cells that give rise to your brown fat and your white fat progenitor is like the early on developmental substance so you start from one zygote and that's a totipotent cell type it can do anything you then differ you know that cell divides divides divides and then every cell division is leading to specialization where you now have a mesodermal lineage and ectodermal lineage and endodermal lineage that basically leads to different parts of your day or your body the ectoderm will basically give rise to your skin ecto means outside derm is skin so ectoderm but it also gives rise to your neurons and your whole brain so that's a lot of ectoderm mesoderm gives rise to your internal organs including the vasculature and you know your muscle and stuff like that so you basically have this progressive differentiation and then if you look further further down that lineage you basically have one lineage that will give rise to both your muscle and your bone but also your fat and if you go further down the lineage of your fat you basically have your white fat cells these are the cells that store energy so when you eat a lot but you don't exercise too much there's an excess a set of calories a lot excess energy what you do with those you basically create you spend a lot of that energy to create these high-energy molecules lipids which you can then burn when you need them on a rainy day so that leads to obesity if you don't exercise and if you overeat because your body is like oh great i have all these calories i'm going to store them more calories i'm going to store them too oh more calories and the you know 42 of european chromosomes have a predisposition to storing fat which was selected probably in the you know food scarcity periods like basically as we were exiting africa you know before and during the ice ages you know there was probably a selection to those individuals who made it north to basically be able to store energy you know a lot more energy so you basically now have this lineage that is deciding whether you want to store energy in your white fat or burn energy in your base fat it turns out that your fat is you know we like we we have such a bad view of fat fat is your best friend fat can both store all these excess lipids that would be otherwise circulating through your you know body and causing damage but it can also burn calories directly if you have too much of energy you can just choose to just burn some of that as heat so basically when you're cold you're burning energy to basically warm your body up and you're burning all these lipids and you're burning all these scatters so what we basically found is that across the board genetic variants associated with obesity across many of these regions were all enriched repeatedly in mesenchymal stem cell enhancers so that gave us a hint as to which of these genetic variants was likely driving this whole association and we ended up with this one genetic variant called rs1421085 and that genetic variant out of the 89 was the one that we predicted to be causal for the disease wow so going back to those steps first step is figure out the relevant tissue based on the global enrichment second step is figure out the causal variant among many variants in this linkage disequilibrium in this co-inherited block between these recombination hotspots these boundaries of these inherited blocks that's the second step the third step is once you know that causal variant try to figure out what is the motif that is disrupted by that causal variant basically how does it act variants don't just disrupt elements they disrupt the binding of specific regulators so basically the third step there was how do you find the motif that is responsible like the gene regulatory word the building block of gene regulation that is responsible for that disregulatory event and the fourth step is finding out what regulator normally binds that motif and is now no longer able to bind and then once you have the regulator can you then try to figure out how to what uh after it developed how to fix it that's exactly right you now know how to intervene you have basically a regulator you have a gene that you can then perturb and you say well maybe that regulator has a global role in obesity i can perturb the regulator just to clarify when we say perturb like on the scale of a human life can a human being be helped of course of course yeah so i guess her understanding is the first step no no but perturbed basically means you now develop therapeutics pharmaceutical therapeutics against that or you develop other types of intervention that affect the expression of that gene what do uh pharmaceutical therapeutics look like when your understandings in a genetic level yeah sorry if it's a dumb question no no it's a brilliant question but i want to save it for a little bit later when we start talking about therapeutics perfect we've talked about the first four steps there's two more so basically the first step is figure out i mean the zeroth step the starting point is the genetics the first step after that is figure out the tissue of action the second step is figuring out the nucleotide that is responsible or set of nucleotides the third step is figure out the motif and the upstream regulator number four number five and six is what are the targets so number five is great now i know the regulator i know the motif i know the tissue and i know the variant what does it actually do so you have to now trace it to the biological process and the genes that mediate that biological process so knowing all of this can now allow you to find the target genes how by basically doing perturbation experiments or by looking at the folding of the epigenome or by looking at the genetic impact of that genetic variant on the expression of genes and we use all three so let me go through them basically one of them is physical links this is the folding of the genome onto itself how do you even figure out the folding it's a little bit of a tangent but it's a super awesome technology think of the genome as again this massive packaging that we talked about of taking two meters worth of dna and putting it in something that's a million times smaller than 2 meters worth of dna that's a single cell you basically have this massive packaging and this packaging basically leads to the chromosome being wrapped around in sort of tight ways in ways however that are functionally capable of being reopened and reclosed so i can then go in and figure out that folding by sort of chopping up the spaghetti soup putting glue and ligating the segments that were chopped up but nearby each other and then sequencing through these ligation events to figure out that this region of these chromosomes that region of the chromosome were near each other that means they were interacting even though they were far away on the genome itself so that chopping up sequencing and re-gluing is basically giving you folds of the genome that we said how does cutting it help you figure out which ones were close in the original folding so you have a bowl of noodles go on and in that bowl of noodles some some noodles are near each other yes so throw in a bunch of glue you basically freeze the noodles in place throw in a cutter that chops up the noodles into the little pieces now throw in some ligation enzyme that lets those pieces that were free re-ligate near each other in some cases they re-ligate what you had just got but that's very rare most of the time they will re-ligate in whatever was proximal you now have glued the red noodle that was crossing the blue noodle to each other you then reverse the glue the glue goes away and you just sequence the heck out of it most of the time you'll find red segment with you know red segment but you can specifically select for ligation events that have happened that were not from the same segment by sort of marking a particular way and then selecting those and then your sequencing you look for red with blue matches of sort of things that were glued that were not immediate proximal to each other and that reveals the linking of the blue noodle and the red noodle you're with me so far yeah good so we you know we've done these experiments physical that's the physical that's step one of the physical and what what the physical revealed is topologically associated domains basically big blocks of the genome that are topologically don't you know connected together that's the physical the second one is the genetic links it basically says across individuals that have different genetic variants how are their genes expressed differently remember before i was saying that the path between genetics and disease is enormous but we can break it up to look at the path between genetics and gene expression so instead of using alzheimer's as a phenotype i can now use expression of irx3 as the phenotype expression of gene a and i can look at all of the g all of the humans who contain a g at that location and all the humans will contain a t at that location and basically say wow turns out that the expression of this gene is higher for the t humans than for the g humans at that location so that basically gives me a genetic link between a genetic variant a locus or region and the expression of nearby genes good on the genetic link i think so awesome so the third link is the activity link what's an activity link it basically says if i look across 833 different epigenomes whenever these enhancer is active this gene is active that gives me an activity link between this region of the dna and that gene and then the fourth one is perturbations where i can go in and you know blow up that region and see what are the genes that change in expression or i can go in and over activate that region and see what genes change in expression uh so i guess that's similar to activity yeah yeah so that's basically it's similar to activity i agree but it's causal rather than correlational again i'm i'm a little weird like no no you're 100 on it's exactly the same but the perturbation where i go and intervene yes i basically take a bunch of cells so you know crispr right crispr is this genome guidance and cutting mechanism it's what george like likes to call genome vandalism so you basically are able to one you can basically take a guide rna that you put into the crispr system and the crispr system will basically use this guide rna scan the genome find wherever there's a match and then cut the genome so you know i digress but it's a bacterial immune defense system so basically bacteria are constantly attacked by viruses but sometimes they win against the viruses and they chop up these viruses and remember as a trophy inside their genome they have this loci this crispr loci that basically stands for clustered repeats interspersed et cetera so basically it's it's an interspersed repeats structure where basically you have a set of repetitive regions and then interspersed were these variable segments that were basically matching viruses so when this was first discovered it was basically hypothesized that this is probably a bacterial immune system that remembers the trophies of the viruses that manage to kill and then the bacteria pass on you know they sort of do lateral transfer of dna and they pass on these memories so that the next bacterium says oh you killed that guy when that guy shows up again i will recognize him and the crispr system was basically evolved as a bacterial adaptive immune response to sense foreigners that should not belong and to just go and cut their genome so it's an rna guided rna cutting enzyme or an rna guided dna cutting enzyme so there's different systems some of them called dna some of them called rna but all of them remember this uh sort of viral attack so what we have done now as a field is you know through the work of you know uh jennifer donna emmanuel carpenter feng zhang and many others is co-opted that system of bacterial immune defense as a way to cut genomes you basically have this guiding system that allows you to use an rna guide to bring enzymes to cut dna at a particular locus that's so fascinating just so this is like already a natural mechanism a natural tool for cutting that was useful this particular context yeah and we're like well we can use that thing to actually it's a nice tool that's already in the body yeah yeah it's not in our body it's a bacterial body it was discovered by the by the yogurt industry they were trying to make better yogurts and they were trying to make their bacteria in their yogurt cultures more resilient to viruses and they were studying bacteria and they found that wow this crispr system is awesome it allows you to defend against that and then it was co-opted in mammalian systems that don't use anything like that as a as a as a targeting way to basically bring these dna cutting enzymes to any locus in the genome why would you want to cut dna to do anything the reason is that our dna has a dna repair mechanism where if a region of the genome gets randomly cut you will basically scan the genome for anything that matches and sort of use it by homology so the reason why we're deployed is because we now have a spare copy as soon as my mom's copy is deactivated i can use my dad's copy and somewhere else if my dad's copy is deactivated i can use my mom's copy to repair it so this is called homologous based repair so all you have to do is the the cutting and that's it you don't have to do the fixing that's exactly right you don't have to do the fixing because it's already built in that's exactly right but the fixing can be co-opted by throwing in a bunch of homologous segments that instead of having your dad's version have whatever other version you'd like to use so the thing so you you then control the fixing by throwing in a bunch of other stuff exactly right that's how you do genome editing so that's what crispr is that's what's wonderful in popular culture people use the term i've never well that's brilliant that's a crispr regional explanation genome vandalism followed by a bunch of band-aids that have the sequence that you'd like and you can control the the choices of band-aids correct yeah and of course there's new generations of crispr there's something that's called prime editing that was sort of very very much in the press recently that basically instead of sort of making a double stranded break which again is genome vandalism you basically make a single stranded break you basically just nick one of the two strands enabling you to sort of peel off without sort of completely breaking it up and then repair it locally using a guide that is coupled to your initial rna that took you to that location dumb question but is crispr as awesome and cool as it sounds i mean technically speaking in terms of like as a tool for manipulating our genetics in the positive uh meaning of the word manipulating or is there downsides drawbacks in this whole context of therapeutics that we're talking about yeah or understanding and so so so um when i teach my students about crispr i show them articles with the headline genome editing tool revolutionizes biology and then i show them the date of these two of these articles and they're 2004 like five years before crispr was invented and the reason is that they're not talking about crispr they're talking about zinc finger enzymes that are another way to bring these cutters to the genome it's a very difficult way of sort of designing the right set of zinc finger proteins the right set of amino acids that will now target a particular long stretch of dna because you you know for every location that you want to target you need to design a particular regulator a particular protein that will match that region well there's another technology called talens which are basically you know just a different way of using proteins to sort of you know guide these cutters to a particular location of the genome these require a massive team of engineers of biological engineers to basically design a set of amino acids that will target a particular sequence of your genome the reason why crispr is amazingly awesomely revolutionary is because instead of having this team of engineers design a new set of proteins for every locker that you want to target you just type it in your computer and you just synthesize an rna guide the beauty of crispr is not the cutting it's not the fixing all of that was there before it's the guiding and the only thing that changes that it makes the guiding easier by sort of you know just typing in the rna sequence which then allows the system to sort of scan the dna to find that so the coding the the engineering of the cutter is easier on the uh in terms of that's kind of similar to the story of deep learning versus uh old school machine learning some of the some of the challenging parts are automated okay so uh but crispr is just one cutting exact technology exactly and then there's that's part of the challenges and exciting opportunities of the field is to design different cutting technologies yeah yeah so now um we you know this was a big parenthesis on crispr but now you you know when we were talking about perturbations you basically now have the ability to not just look at correlation between enhancers and genes but actually go and either destroy that enhancer and see if the gene changes in expression or you can use the crispr targeting system to bring in not vandalism and cutting but you can couple the crispr system with and the crispr system is called usually crispr cas9 because cast 9 is the protein that will then come and cut but there's a version of that protein called dead cast 9 where the cutting part is deactivated so you basically use d cas9 dead cas9 to bring in an activator or to bring in a repressor so you can now ask is this enhancer changing that gene by taking this modified crispr which is already modified from the bacteria to be used in humans that you can now modify the cast 9 to be dead cas9 and you can now further modify it to bring in a regulator and you can basically turn on or turn off that enhancer and then see what is the impact on that gene so these are the four ways of linking the locus to the target gene and that's step number five okay step number five is find the target gene and step number six is what the heck does that gene do you basically now go and manipulate that gene to basically see what are the processes that change and you can basically ask well you know in this particular case in the fto locus we found mesenchymal stem cells that are the progenitors of white fat and brown fat or beige fat we found the rs-1421085 nucleotide variant as the causal variant we found this large enhancer this master regulator i like to call it ob1 for uh obesity one like the strongest enhancer associated with whatever and ob1 was kind of chubby as the actor i don't know if you remember him [Laughter] yeah so you basically are using this jedi mind trick to basically find out the uh thank you the location of the genome that is responsible the enhancer that harbors it the motif the upstream regulator which is arid 5b for 80 rich interacting domain 5b that's a protein that sort of comes and binds normally that protein is normally a repressor it represses this super enhancer this massive 12 000 nucleotide master regulatory control region and it turns off irx3 which is a gene that's 600 000 nucleotides away and irix 5 which is 1.2 million nucleotides away so those are what's the effect of turning them off that's exactly the next question so step six is what do these genes actually do so we then ask what does rx3 and rx5 do the first thing we did is look across individuals for individuals that had higher expression of rx3 or lower expression rx3 and then we looked at the expression of all of the other genes in the genome and we look for simply correlation and we found that iric 3 and rx-5 were both correlated positively with lipid metabolism and negatively with mitochondrial biogenesis you're like what the heck does that mean it doesn't sound related to obesity not at all superficially but lipid metabolism should because lipids is these high energy molecules that basically store fat so hyer extreme and rx5 are negatively correlated with lipid metabolism so that basically means that when they turn on lipid metabolism positively when they turn on they turn on lipid metabolism and they're negatively correlated with mitochondrial biotins what do mitochondria do in this whole process again small parenthesis what are mitochondria mitochondria are little organelles they arose they only are found in eukaryotes u means good karyo means nucleus so truly like a true nucleus so eukaryotes have a nucleus prokaryotes are before the nucleus they don't have a nucleus so eukaryotes have a nucleus compartmentalization eukaryotes have also organelles some eukaryotes have chloroplasts these are the plants they photosynthesize some other eukaryotes like us have another type of organelle called mitochondria these arose from an ancient species that we engulfed this is an endosymbiosis event symbiosis bio means life sim means together so symbiotes are things that live together endosymbiosis endomeans inside so endosymbiosis means you live together holding the other one inside you so the pre-eukaryotes engulfed an organism that was very good at energy production and that organism eventually shed most of its genome to now have only 13 genes in the mitochondrial genome and those 13 genes are all involved in energy production the electron transport chain so basically electrons are these massive super energy rich molecules we basically have these organelles that produce energy and when your muscle exercises you basically multiply your mitochondria you basically sort of you know use more and more mitochondria and that's how you get beefed up so basically the m the muscle sort of learns how to generate more energy so basically every single time your muscles will you know overnight regenerate and sort of become stronger and amplify their mitochondrions and so forth so what does mitochondria do the mitochondria use energy to sort of do any kind of task when you're thinking you're using energy this energy comes from mitochondria your neurons have mitochondria all over the place basically this mitochondria can multiply as organelles and they can be spread along the body of your muscle some of your muscle cells have actually multiple nuclei they're polynucleated but they also have multiple mitochondria to basically uh deal with the fact that your muscle is enormous you can sort of span this super super long length and you need energy throughout the length of your muscle so that's why you have mitochondria throughout the length and you also need transcription through the length so you have multiple nuclei as well so these two processes lipids store energy what do mitochondria do so there's a process known as thermogenesis thermoheat genesis generation thermogenesis is generation of heat remember that bathtub with in and out that's the equation that everybody's focused on so how much energy do you consume how much energy you burn but in every thermodynamic system there's three parts to the equation there's energy in energy out and energy lost any machine has loss of energy how do you lose energy you emanate heat so heat is energy loss so um there's which is where the thermogenesis comes in thermogenesis is actually a regulatory process that modulates the third component of the thermodynamic equation you can basically control thermogenesis explicitly you can turn on and turn off thermogenesis and that's where the mitochondria comes into exactly so irix 3 and rx5 turn out to be the master regulators of a process of thermogenesis versus lipogenesis generation of fat so irex and rx5 in most people burn heat burn burn calories as heat so when you eat too much just burn it burn it off in your in your fat cells so if that bathtub has basically a sort of dissipation knob that most people are able to turn on i am unable to turn that on because i am a homozygous carrier for the mutation that changes a t into a c in the rs1421085 allele a locus a snip i have the risk allele twice from my mom and for my dad so i'm unable to thermogenize i'm unable to turn on thermogenesis through irix 3 and rx5 because the regulator that normally binds here r85b can no longer buy because it's an 80 rich interacting domain and as soon as i change the t into a c it can no longer bind because it's no longer at rich but doesn't that mean that you're able to use the energy more efficiently you're not generating heat or is it that means that i can eat less and get around just fine yes yeah so that's a feature actually it's a feature in a food scarce environment yeah but if we're all starving i'm doing great if we all have access to massive amounts of food i'm i'm obese basically that's taken us through the entire process of then understanding that why mitochondria and then the lipids are both no distant or somehow different size of the same coin and you basically choose to store energy or you can choose to burn energy and then all of that is involved in the puzzle of obesity and that's what's fascinating right here we are in 2007 discovering the strongest genetic association with obesity and knowing nothing about how it works for almost 10 years for 10 years everybody focused on this fto gene and they were like oh it must have to do something with you know rna modification and it's like no it has nothing to do with the function of fto it has everything to do with all of this other process and suddenly the moment you solve that puzzle which is a multi-year effort by the way and tremendous effort by melina and many many others so this tremendous effort basically led us to recognize this circuitry you went from having some 89 common variants associated in that region of the dna sitting on top of this gene to knowing the whole circuitry when you know the circuitry you can now go crazy you can now start intervening at every level you can start intervening at the arid 5b level you can start intervening with crispr cas9 at the single snip level you can start intervening at iraq 3 and rx5 directly there you can start intervening at the thermogenesis level because you know the pathway you can start interviewing at the at the differentiation level where these the decision to make either white fat or beige fat the energy burning base fat is made developmentally in the first three days of differentiation of your adipocytes so as they're differentiating you basically can choose to make fat burning machines or fat storing machines and sort of that's how you populate your your fat you basically can now go in pharmaceutically and do all of that and in our paper we actually did all of that we went in and manipulated every single aspect at the nucleotide level we used crispr cast 9 genome editing to basically take primary adipocytes from risk and non-risk individuals and show that by editing that one nucleotide out of 3.2 billion nucleotides in the human genome you could then flip between an obese phenotype and a lean phenotype like a switch you can basically take a micelles that are non-thermogenizing and just flipping to thermogenizing cells by changing one nucleotide it's mind-boggling it's so inspiring that this puzzle could be solved in this way and it feels within reach to then be able to crack the problem with some of these diseases what are so 2007 you mentioned 2000 what are the technologies the tools that came along that made this possible like what what are you excited about maybe if we just look at the buffet of things that you've kind of mentioned is there is this what's involved what should we be excited about what are you excited about i love that question because there's so much ahead of us there's so so much um there's uh so so basically solving that one locus required massive amounts of knowledge that we have been building across the years through the epigenome through the comparative genomics to find out the causal variant and the control the controller regulatory motif through the conserved circuitry it required knowing this regulatory genomic wiring it required high c of these sort of topologically associated domains to basically find this long-range interaction it required eqtls of this sort of genetic perturbation of these intermediate gene phenotypes it required all of the arsenal of tools that i've been describing was put together for one locus and this was a massive team effort huge you know investment in time energy money effort intellectual you know everything you're referring to i'm sorry this one basically yeah this one piece this one single paper at least one single locus i like to say that this is a paper about one nucleotide in the human genome about one bit of information c versus t in the human genome that's one bit of information and we have 3.2 billion nucleotides to go through so how do you do that systematically i am so excited about the next phase of research because the technologies that my group and many other groups have developed allows us to now do this systematically not just one locus at a time but thousands of loci at a time so let me describe some of these technologies the first one is automation and robotics so basically you know we talked about how you can take all of these molecules and see which of these molecules are targeting each of these genes and what do they do so you can basically now screen through millions of molecules through thousands and thousands and thousands of plates each of which has thousands and thousands and thousands of molecules every single time testing um you know all of these genes and asking which of these molecules perturb these genes so that's technology number one automation and robotics technology number two is parallel readouts so instead of perturbing one locus and then asking if i use crispr cast 9 on this enhancer to basically use dcas9 to turn on or turn off the enhancer or if i use crystal cast 9 on the snip to basically change that one snip at a time then what happens but we have 120 000 disease associated snips that we want to test we want we don't want to spend 120 000 years doing it so what do we do we've basically developed this technology for massively parallel reporter assays mpra so in collaboration with tarzan mickelson mary flanders i mean jason dura's group has done a lot of that so there's there's a lot of groups that basically have developed technologies for testing 10 000 genetic variants at a time how do you do that you you know we talked about micro array technology the ability to synthesize these huge microarrays that allow you to do all kinds of things like measure gene expression by hybridization by measuring the genotype of a person by looking at hybridization with one version with a t versus the other version with the t with an with a c and then sort of figuring out that i am a risk carrier for obesity based on these hybridization differential hybridization in my genome that says oh you seem to only have this allele or you seem to have that allele microarrays can also be used to systematically synthesize small fragments of dna so you can basically synthesize these 150 nucleotide long fragments across 450 000 spots at a time you can now take the result of that synthesis which basically works through all of these sort of layers of adding one nucleotide at a time you can basically just type it into your computer and order it and you can basically order 10 000 or 100 000 of these small dna segments at a time and that's where awesome molecular biology comes in you can basically take all these segments have a common start and end barcode or sort of like gator like you just like pieces of a puzzle you can make the same end piece and the same start piece for all of them and you can now use plasmids which are these extra chromosomal small dna circular segments that are basically inhabiting all our all our genomes we basically have you know plasmids floating around i mean bacteria use plasmids for transferring dna and that's where they put a lot of antibiotic resistance genes so they can easily transfer them from one but one bacterium to the other so one bacterium involves a gene to be resistant to a particular antibiotic it basically says to all its friends hey here's that sort of dna piece we can now co-opt these plasmids into human cells you can basically make a human cell culture and add plasmids to that human cell culture that contain the things that you want to test you now have this library of 450 000 elements you can insert them each into the common plasmid yeah and then test them in millions of cells in parallel and the common plasmid is all the same before you add it exactly the rest of the plasmid is the same so it's it's called an episomal reporter assay episome means not inside the genome it's sort of outside the chromosomes so it's an episomal assay that allows you to have a variable region where you basically test 10 000 different enhancers and you have a common region which basically has the same reporter gene you know some can do some very cool molecular biology you can basically take the 450 000 elements that you've generated and and you have a piece of the puzzle here a piece of the puzzle here which is identical so they're compatible with that plasmid you can chop them up in the middle to separate a barcode reporter from the enhancer and in the middle put the same gene again using the same pieces of the puzzle you now can have a barcode readout of what is the impact of 10 000 different versions of an enhancer on gene expression so we're not doing one experiment we're doing 10 000 experiments and those ten thousand can be five thousand of different loci and each of them in two versions risk or non-risk i can now test tens of these little hypotheses exactly and then you can do ten thousand and we can test ten thousand hypothesis at once how how hard is it to generate those ten thousand uh trivial trivial but it's biology no no generating the ten thousand is trivial because you basically add it by technology you basically have these arrays that that add one nucleotide at a time at every spot oh and yeah so it's printing in it so you're able to you're able to control yeah uh super costly is it ten thousand bucks so this isn't millions thousand bucks for ten thousand experiments sounds like the right you know i mean so that's super that's exciting because you don't have to do one thing at a time yeah you can now use that technology these massively parallel reporter assays to test 10 000 locations at a time we've made multiple modifications of that technology one was sharper mpra which stands for you know basically getting a higher resolution view by tiling these um these elements so you can see where along the region of control are they acting and we made another modification called hydra for high you know definition regulatory annotation or something like that which basically allows you to test seven million of these at a time by sort of cutting them directly from the dna so instead of synthesizing which basically has the limit of 450 000 that you can synthesize at a time we basically said hey if we want to test all accessible regions of the genome let's just do an experiment that cuts accessible regions let's take those accessible regions put them all with the same end joints of the puzzles and then now use those to create a much much larger much much larger uh array of things that you can test and then tiling all of these regions you can then pinpoint what are the driver nucleotides what are the elements how are they acting across seven million experiments at a time so basically this is all the same family of technology where you're basically using these parallel readouts of the barcodes and then you know to do this we used a technology called starseek for self-transcribing uh reporter asses a technology developed by alex stark my my former postdoc who's now api over in vienna so we basically coupled the starsig the self-transcribing uh reporters where the enhancer can be part of the the gene itself so instead of having a separate barcode that enhancer basically acts to turn on the gene and it's transcribed as part of the gene so you don't have to have the two separate parts exactly so you can just read them so there's a constant improvements in this whole process yes by the way generating all these options are is it basically brute force uh how much human intuition is oh gosh of course it's human intuition and human creativity and incorporating all of the input data sets because again the the genome is enormous 3.2 billion you don't want to test that instead you basically use all of these tools that i've talked about already you generate your top favorite 10 000 hypothesis and then you go and test all ten thousand and then from what what comes out you can then go go to the next step so that's technology number two so technology one number one is robotics automation where you have thousands of wells and you constantly test them the second technology is instead of having wells you have these massively parallel readouts in sort of these pooled asses the third technology is coupling crispr perturbations with these single cell rna readouts so let me make another parenthesis here to describe now single cell rna sequencing okay so what does single cellular sequencing mean so rna sequencing is what has been traditionally used oh well traditionally the last 20 years ever since the advent of next generation sequencing so basically before rna expression profiling was based on this microarrays the next technology after that was based on sequencing so you chop up your rna and you just sequence small molecules just like you would sequence the genome basically reverse transcribe the small rnas into dna and you sequence that dna in order to get the number of sequencing reads corresponding to the expression level of every gene in the genome you now have rna sequencing how do you go to single cell rna sequencing that technology also went through stages of evolution the first was microfluidics you basically had these or even even chambers you basically had these ways of isolating individual cells putting them into a well for every one of these cells so you have 384 well plates and you know do 384 parallel reactions to measure the expression of 384 cells that sounds amazing and it was amazing but we want to do a million cells how do you go from you know these wells to a million cells you can't so what what what the next technology was after that is instead of using a well for every reaction you now use a lipid droplet for every reaction so you use micro droplets as reaction chambers to basically amplify rna so here's the idea you basically have microfluidics where you basically have every single cell coming down one tube in your microfluidics and you have little bubbles getting created in the other way with specific primers that mark every cell with its own barcode you basically couple the two and you end up with little bubbles that have a cell and tons of markers for that cell you now mark up all of the rna for that one cell with the same exact barcode and you then lice all of the droplets and you sequence the heck out of that and you have for every rna molecule a unique identifier that tells you what cell was it on that is such good engineering microfluidics and uh using some kind of primer to put it put up put a label on the thing i mean i don't you're making it sound easy i assume it's it's beautiful right challenging but it's gorgeous yeah so there's the next generation engineering yeah so that's the second generation next generation is forget the microfluidics all together just use big bottles how can you possibly do that with big bottles so here's the idea you dissociate all of your cells or all of your nuclei from complex cells like brain cells that you know are very long and sticky so you can't do that so you know if you have blood cells or if you have you know neuronal nuclei or brain nuclei you can basically dissociate let's say a million cells you now want to add a unique barcode a unique barcode in each one of a million cells using only big bottles i can't possibly do that sounds crazy but here's the idea you use a hundred of these bottles you randomly shuffle all your million cells and you throw them into the hundred bottles randomly completely random you add one barcode out of 100 to every one of those cells you then you now take them all out you shuffle them again and you throw them again into the same hundred bottles but now in a different randomization and you add a second barcode so every cell now has two barcodes you take them out again you shuffle them and you throw them back in another third barcode is adding randomly from the same hundred barcodes you've now labeled every cell probabilistically based on the unique path that he took of which of a hundred bottles to go for the first time which of 100 bottles a second time and which of 100 bottles a third time a hundred times 100 times 100 is a million unique barcodes in every single one of these cells without ever using microfluidic very clever that's beautiful right computer science perspective that's very clever so you now have the single cell sequencing technology you can use the wells you can use the bubbles or you can use the bottles and you know sort of you have way bubbles still sound pretty damp because bubbles are awesome and that's basically the main technology that we're using okay so the evolves is the main technology so so there are kids now that companies to sell to basically carry out single cell or any sequencing that you know you can basically for two thousand dollars you can basically get ten thousand cells from one sample and for every one of those cells you basically have the transcription of thousands of genes and you know of course the data for any one cell is noisy but being computer scientists we can aggregate the data from all of those cells together across thousands of individuals together to basically make very robust inferences okay so the third technology is basically single cell rna sequencing that allows you to now start asking not just what is the brain expression level difference of that genetic variant but what is the expression difference of that one genetic variant across every single subtype of brain cell how is the variance changing you can't just you know with a brain sample you can just ask about the mean what is the average expression if i instead have 3 000 cells that are neurons i can ask not just what is the neuronal expression i can say for layer 5 excitatory neurons of which i have i don't know 300 cells what is the variance that this genetic variant has so suddenly it's amazingly more powerful i can basically start asking about this middle layer of gene expression at unprecedented levels and when you look at the average it washes out some potentially important signal that corresponds to ultimately the disease completely yeah so that i can do that at the rna level but i can also do that at the dna level for the epigenome so remember how before i was telling you about all these technologies we're using to probe the epigenome one of them is dna accessibility so what we're doing in my lab is that from the same dissociation of say a brain sample where you now have all these tens of thousands of cells floating around you basically take half of them to do rna profiling and the other have to do epigenome profiling both at the single cell level so that allows you to now figure out what are the millions of dna enhancers that are accessible in every one of tens of thousands of cells and computationally we can now take the rna and the dna readout and group them together to basically figure out how is every enhancer related to every gene and remember these sort of enhancer gene linking that we were doing across 833 samples 833 is awesome don't get me wrong but 10 million is way more awesome so we can now look at correlated activity across 2.3 million enhancers and 20 000 genes in each of millions of cells to basically start piecing together the regulatory circuitry of every single type of neuron every single type of astrocytes oligodendrocyte microglial cell inside the brains of 1500 individuals that we've sampled across multiple different brain regions across both dna and rna so that's the data set that my team generated last year alone so in one year we basically generated 10 million cells from human brain across a dozen different disorders across schizophrenia alzheimer's frontal temporal dementia louis body dementia als you know huntington's disease post-traumatic stress disorder autism like you know bipolar disorder healthy aging etc so it's possible that even just within that data set lie a lot of keys to understanding these diseases and then be able to like directly leads to then treatment correct correct so basically we are now motivating yeah so our computational team is in heaven right now and we're looking for people i mean if you have super how much does this decision so this is a very interesting kind of side question how much of this is biology how much of this is computation so you have the computational biology group but how much of are you should should you be comfortable with biology to be able to solve some of these problems if you just find if you put several of the hats you were on fundamentally are you thinking like a computer scientist here you have to this is the only way as i said we are the descendants of the first digital computer we're trying to understand the digital computer we understand we're trying to understand the circuitry the logic of this digital you know core computer and all of these analog layers surrounding it so you you know the case that i've been making is that you cannot think one gene at a time the traditional biology is dead there's no way you cannot solve disease with traditional biology you need it as a component once you've figured out rx3 and rx5 you now can then say hey have you guys worked on those genes with your single gene approach we'd love to know everything you know and if you haven't we now know how important these genes are let's now launch a single gene program to dissect them and understand them but you cannot use that as a way to dissect disease you have to think genomically you have to think from the global perspective and you have to build these circuits systematically so we need numbers of computer scientists who are interested and willing to dive into this data you know fully fully in and sort of extract meaning we need computer science people who can understand sort of machine learning and inference and sort of you know decouple these matrices come up with super smart ways of sort of dissecting them but we also need by all computer scientists who understand biology who are able to design the next generation of experiments because many of these experiments no one in the right mind would design them without thinking of the analytical approach that you would use to deconvolve the data afterwards right because it's massive amounts of ridiculously noisy data and if you don't have the computational pipeline in your head before you even design the experiment you would never design the experiment that way that's brilliant so you in designing the experiment you have to see the entirety of the computational pipeline that drives the design that that even drives the necessity for that design basically you know if you didn't have a computer scientist way of thinking you would never design these hugely combinatorial massively parallel experiments so that's why you need interdisciplinary teams you need teams and and i want to i want to sort of clarify that what do we mean by computational biology group the focus is not on computational the focus is on the biology so we are a biology group what type of biology computational biology yeah the type of biology that uses the whole genome that's the type of biology that designs experiments genomic experiments that can only be interpreted in the context of the whole genome right so it's it's philosophically looking at biology as a computer correct correct so which is a in the context of the history of biology is a big transformation yeah yeah you can think of the name as what do we do only computation that's not true but how do we study it only computationally that is true so all of these single cell sequencing can now be coupled with the technologies that we talked about earlier for perturbation so here's a crazy thing instead of using these wells and these robotic systems for doing one drug at a time or for perturbing one gene at a time in thousands of wells you can now do this using a pool of cells and single cell or any sequencing how you basically can take these perturbations using crispr and instead of using a single guide rna you can use a library of guide rnas generated exactly the same way using this array technology so you synthesize a thousand different guide rnas you now take each of these guide rnas and you insert them in a pool of cells where every cell gets one perturbation and you use crispr editing or crispr uh so with either crispr cas9 to edit the gina with these thousand perturbations or the or with the activation or with the repression and you now can have a single cell readout where every single cell has received one of these modifications and you can now in massively parallel ways couple the perturbation and the readout in a single experiment how are you tracking which perturbations each cell received so there's there's ways of doing that but basically one way is to make that perturbation an expressible vector so that part of your rna reading is actually that perturbation itself so you can basically put it in a expressible part so you can self-drive it so the the point that i want to get across is that the sky is the limit you basically have these tools these building blocks of molecular biology you have this massive data sets of computational biology you have this huge ability to sort of use machine learning and statistical methods and you know linear algebra to sort of reduce the dimensionality of all these massive data sets and then you end up with a series of actionable targets that you can then couple with pharma and just go after systematically so the ability to sort of bring genetics to the epigenomics to the transcriptomics to the cellular readouts using these sort of high throughput perturbation technology that i'm talking about and ultimately to the organismal through the electronic health record endophenotypes and ultimately the disease battery of assays at the cognitive level at the physiological level and you know every other level this there is no better or more exciting field in my view to be a computer scientist then or to be a scientist in period basically this confluence of technologies of computation of data of insight and of tools for manipulation is unprecedented in human history and i think this is what's shaping the next century to really be a transformative century for our species and for our planet so you think the 21st century will be remembered for the big leaps in biology and understanding and alleviation of biology if you look at the path between discovery and therapeutics it's been on the order of 50 years it's been shortened to 40 30 20 and now it's on the order of 10 years but the huge number of technologies that are going on right now for discovery will result undoubtedly in the most dramatic manipulation of human biology that we've ever seen in the history of humanity in the next few years do you think we might be able to cure some of the diseases we started this conversation with absolutely absolutely it's it's only a matter of time basically the complexity is enormous and i don't want to underestimate the complexity but the number of insides is unprecedented and the ability to manipulate is unprecedented and the ability to deliver these small molecules and other non-traditional medicine perturbations there's a lot of sort of new gen there's a new generation of perturbations that you can use at the dna level at the rna level at the you know microrna level uh the genomic level there's there's a battery of new generations of perturbations if you couple that with cell type identifiers that can basically sense when you are in the right cell based on the specific combination and then turn on that intervention for that cell you can now think of combinatorial interventions where you can basically sort of feed a synthetic biology construct to someone that will basically do different things in different cells so basically for cancer this is one of the therapeutics that our collaborator ron weiss is using to basically start sort of engineering these circuits that will use microrna sensors of the environment to sort of know if you're in a tumor cell or if you're in an immune cell or if you're in stromal cells and so forth and basically turn on particular interventions there you can sort of create constructs that are tuned to only the liver cells or only the heart cells or only the you know uh you know brain cells and then have these new generations of therapeutics coupled with this immense amount of knowledge on the sort of which targets to choose and what biological processes to measure and how to intervene my view is that disease is going to be fundamentally altered and alleviated as we go forward next time we talk we'll talk about the philosophical implications that the effect of life but let's stick to biology for just a little longer we did pretty good today we still stuck to the science what um what are you excited in terms of uh the future of this of this field the technologies in your own group in your own mind you're leading the world at mit in the science and the engineering of this work so what are you excited about here i could not be more excited we are one of many many teams who are working on this in my team the most exciting parts are um you know manifold so basically we've now assembled this battery of technologies we've assembled these massive massive data sets and now we're really sort of in the stage of uh our our team's path of generating disease insights so we are simultaneously working on a paper on schizophrenia right now that is basically using the single cell profiling technologies using this editing and manipulation technologies to basically show how the master regulators underlying changes in the brain that are sort of found in in schizophrenia are in fact affecting excitatory neurons and inhibitory neurons in pathways that are active both in synaptic pruning but also in early development we've basically found a set of four regulators that are connecting these two processes that were previously separate in schizophrenia in sort of having a sort of more unified view across those two those two sides the second one is in the in the area of metabolism we basically now have a beautiful collaboration with the goodyear lab that's basically looking at um multi-tissue perturbations in six or seven different tissues across the body in the context of exercise and in the context of nutritional interventions using both mouse and human where we can basically see what are the cell to cell communications that are that are changing across them and what we're finding is this immense role of both immune cells as well as adipocyte stem cells in sort of reshaping that circuitry of all of these different tissues and that sort of painting to a new path for therapeutical interventions there in alzheimer's it's this huge focus on microglia and now we're discovering different classes of microglial cells that are basically either synaptic or um immune and these are playing vastly different roles in alzheimer's versus in schizophrenia and what we're finding is this immense complexity as you go further and further down of how in fact there's 10 different types of microglia each with their own sort of expression programs we used to think of them as oh yeah they're microglia but in fact now we're realizing just even in that sort of least abundant of cell types there's this incredible diversity there the differences between brain regions is is another sort of major major insight again you know one would think that oh astrocytes are astrocytes no matter where they are but no there's incredible region-specific differences in the expression patterns of all of the major brain cell types across different brain regions so basically there's the neocortical regions that are sort of the recent innovation that makes us so different from all other species there's the sort of you know reptilian brain sort of regions that are sort of much more uh you know very extremely distinct there's a cerebellum there's um each of those basically is associated in a different way with disease and what we're doing now is looking into pseudotemporal models for how disease progresses across different regions of the brain if you look at alzheimer's it basically starts in this small region called the enter rhino cortex and then it spreads through the brain and uh you know through the hippocampus and you know the uh ultimately affecting the neocortex and with every brain region that it hits it basically has a different impact on the cognitive and you know memory aspects orientation short-term memory long-term memory etc which is you know dramatically affecting the cognitive path that the individuals go through so what we're doing now is creating these computational models for ordering the cells and the regions and the individuals according to their ability to predict alzheimer's disease so we can have a cell level predictor of pathology that allows us to now create a temporal time course that tells us when every gene turns on along this pathology progression and then trace that across regions and pathological measures that are region-specific but also cognitive measures and so so forth so that allows us to now sort of for the first time look at can we actually do early intervention for alzheimer's where we know that the disease starts manifesting for 10 years before you actually have your first cognitive loss can we start seeing that path to build new diagnostics new prognosis new biomarkers for this sort of early intervention in alzheimer's the other aspect that we're looking at is mosaicism we talked about the common variants and the rare variants but in addition to those rare variants as your initial cell uh that that forms the zygote divides and divides and divides with every cell division there are additional mutations that are happening so what you end up with is your brain being a mosaic of multiple different types of genetic underpinnings some cells contain imitation that other cells don't have so every human has the common variant that all of us carry to some degree the rare variant that your immediate tree of the human species carries and then there's the somatic variant which is the tree that happened after the zygote that sort of forms your own body so these somatic alterations is something that has been previously inaccessible to study in human postmortem samples but right now with the advent of single cell rna sequencing in this particular case we're using the well-based sequencing which is much more expensive but gives you a lot richer information about each of those transcripts so we're using now that richer information to infer mutations that have happened in each of the thousands of genes that sort of are active in these cells and then understand how the genome relates to the function this genotype phenotype relationship that we usually build in geos between genomic association studies between genetic variation and disease we're now building that at the cell level where for every cell we can relate the unique specific genome of that cell with the expression patterns of that cell and the predicted function using these predictive models that i mentioned before on this regulation for cognition for pathology in alzheimer's at the cell level and what we're finding is that the genes that are altered and the genetic regions that are altered in common variants versus rare variant versus somatic variant are actually very different from each other the somatic variants are pointing to neuronal energetics and oligodendrocyte functions that are not visible in the genetic lesions that you find for the common variants probably because they have too strong of an effect that evolution is just not tolerating them on the common side of the allele frequency spectrum so the somatic one that's the variation that happens after the the zygo after correct you individual i mean it's a dumb question but there's there's mutation and variation i guess that happens there and you're saying that they're through this if we focus in on individual cells we're able to detect a story that's interesting there and that might be a very unique kind of important variability that arises for you said neuronal or something energetic energetics energetic cool terms so your your i mean the metabolism of humans is dramatically altered from that of nearby species you know we talked about that last time that basically we are able to consume meat that is incredibly energy rich and that allows us to sort of have functions that are you know meeting this humongous brain that we have it's basically on one hand every one of our brain cells is much more energy efficient than our neighbors than our relatives number two we have way more of these cells and number three we have you know this new diet that allows us to now feed all these needs that basically creates a massive amount of damage oxidative damage from this huge super powered factory of ideas and thoughts that we that we carry in our skull and that factory has energetic needs and there's a lot of sort of biological processes underlying that that we are finding are altered in the context of alzheimer's disease that's fascinating that so you have to consider all of these systems if you want to understand even something like diseases that you would maybe traditionally associate with just the particular cells of the brain yeah the immune system the metabolic system the metabolic system and these are all the things that makes us uniquely human so our immune system is dramatically different from that of our neighbors our societies are so much more clustered the history of infections that have plagued the human population is you know dramatically different from every other species the the you know the way that our society in our population has sort of exploded has basically put unique pressures on our immune system and our immune system has both coped with that density and also been shaped by as i mentioned the you know vast amount of death that has happened in the black plague and other sort of selective events in human history famines ice ages and so forth so that's number one then on on the sort of immune side on the metabolic side you know again we are able to sort of run marathons you know you know i don't know if you remember the sort of human versus horse experiment where the horse actually tires out faster than the human and the human actually wins so so on the metabolic side we're dramatically different on the immune side we're dramatically different on the brain side again you know no need to sort of you know it's a no-brainer how our brain is like just enormously more capable and then uh in you know in the side of cancer so basically the cancers that humans are having the exposure the environmental exposures is again dramatically different and the lifespan the expansion of human lifespan is unseen in any other species in you know recent evolutionary history and that now leads to a lot of new disorders that are starting to you know manifest late in life so uh you know alzheimer's is one example where basically you know these vast energetic needs over a lifetime of thinking can basically lead to all of these debris and eventually saturate the system and lead to you know alzheimer's in in the late life but there's you know there's just such a such a dramatic uh set of frontiers when it comes to aging research that you know will so what i often like to say is that if you want to re to to engineer a car to go from 70 miles an hour to 120 miles an hour that's fine you can basically you know fix a few components if you wanted to now go out 400 miles an hour you have to completely redesign the entire car because the system has just not evolved to go that far basically our human body has only evolved to live to i don't know 120 maybe we can get to 150 with minor changes but if you know as we start pushing these frontiers for not just living but well living the f zine that we talked about last time so to to basically push f zine into the 80s and 90s and 100s and you know much further than that we will face new challenges that have you know never been faced before in terms of cancer the number of divisions in terms of alzheimer's and brain related disorders in terms of metabolic disorders in terms of regeneration there's just so many different frontiers ahead of us so i am thrilled about where we're heading so basically i see this confluence in my lab and many other labs of ai of you know sort of you know the next frontier of ai for drug design so basically these sort of graph neural networks on specific chemical uh designs that allow you to create new generations of therapeutics these molecular biology tricks for intervening at the system at every level this personalized medicine prediction diagnosis and prognosis using the electronic health records and using these polygenic risk scores weighted by the burden the number of mutations that are accumulating across common rare and somatic variants the burden converging across all of these different molecular pathways the delivery of specific drugs and specific interventions into specific cell types and again you've talked with bob langer about this there's you know many giants in that field and then the last concept is not intervening at the single gene level i want you to sort of conceptualize the concept of an on target side effect what is an on target side effect an off-target side effect is when you design a molecule to target one gene and instead it targets another gene and you have side effects because of that an on target side effect is when your molecule does exactly what you're expecting but that gene is pliotropic plio means many tropos means ways many ways it acts in many ways it's a multifunctional gene so you find that this gene plays a role in this but as we talked about the wiring of genes to phenotypes is extremely dense and extremely complex so the next stage of intervention will be intervening not at the gene level but at the network level intervening at the set of pathways and the set of genes with multi-input perturbations to the system multi-input modulations pharmaceutical or other interventional that basically allow you to now work at the sort of full level of understanding not just in your brain but across your body not just in one gene but across the set of pathways and so forth for every one of these disorders so i think that we're finally at the level of systems medicine of basically instead of sort of medicine being at the single gene level medicine being at the systems level where it can be personalized based on a specific set of genetic markers and genetic perturbations that you are either born with or that you have developed during your lifetime your unique set of exposures your unique set of biomarkers and you know your unique set of you know current set of conditions through your ehr and other ways and the precision component of intervening extremely precisely in the specific pathways and specific combinations of genes that should be modulated to sort of bring you from the disease state to the physiologically normal state or even to a physiologically improved state through this combination of intervention so that that's in my view the field where basically computer science comes together with you know artificial intelligence statistics all of these other tools molecular biology technologies and biotechnology and pharmaceutical technologies that are sort of in revolutionary the way of intervention and of course this massive amount of molecular biology and data gathering and generation perturbation in massively parallel ways so there's no better way there's no better you know time there's no better place to be sort of you know looking at this whole confluence of of ideas and i'm just so thrilled to be a small part of this amazing enormous ecosystem it's exciting to imagine what the humans of 100 200 years from now what their life experience is like because these ideas seem to have potential to transform the quality of life that when they look back at us they probably wonder how we were put up with all the suffering in the world manoa it's a huge honor thank you for spending this early sunday morning with me i deeply appreciate it see you next time so like a plan thank you thanks for listening to this conversation with manolas kellis and thank you to our sponsors scm rush which is an seo optimization tool pessimist archive which is one of my favorite history podcasts eight sleep which is a self-cooling mattress with smart sensors and an app and finally better help which is an online therapy service please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars not a podcast follow on spotify support it on patreon or connect with me on twitter at lex friedman and now let me leave you some words from haruki murakami human beings are ultimately nothing but carriers passageways for genes they ride us into the ground like race horses from generation to generation genes don't think about what constitutes good or evil they don't care whether we're happy or unhappy we're just means to an end for them the only thing they think about is what is most efficient for them thank you for listening and hope to see you next time |
George Hotz: Hacking the Simulation & Learning to Drive with Neural Nets | Lex Fridman Podcast #132 | the following is a conversation with george hotz a.k.a geohot his second time on the podcast he's the founder of comma ai an autonomous and semi-autonomous vehicle technology company that seeks to be to tesla autopilot what android is to the ios they sell the comma two device for one thousand dollars that when installed in many of their supported cars can keep the vehicle centered in the lane even when there are no lane markings it includes driver sensing that ensures that the driver's eyes are on the road as you may know i'm a big fan of driver sensing i do believe tesla autopilot and others should definitely include it in their sensor suite also i'm a fan of android and a big fan of george for many reasons including his non-linear out of the box brilliance and the fact that he's a superstar programmer of a very different style than myself styles make fights and styles make conversations so i really enjoyed this chat i'm sure we'll talk many more times on this podcast quick mention of each sponsor followed by some thoughts related to the episode first is four sigmatic the maker of delicious mushroom coffee second is the coding digital a podcast on tech and entrepreneurship that i listen to and enjoy and finally expressvpn the vpn i've used for many years to protect my privacy on the internet please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that my work at mit on autonomous and semiautonomous vehicles led me to study the human side of autonomy enough to understand that it's a beautifully complicated and interesting problem space much richer than what can be studied in the lab in that sense the data that comma ai tesla autopilot and perhaps others like cadillac super crews are collecting gives us a chance to understand how we can design safe semiautonomous vehicles for real human beings in real world conditions i think this requires bold innovation and a serious exploration of the first principles of the driving task itself if you enjoy this thing subscribe on youtube review it with five stars and up a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with george hotz so last time we started talking about the simulation this time let me ask you do you think there's intelligent life out there in the universe i've always maintained my answer to the fermi paradox i think there has been intelligent life elsewhere in the universe so the intelligent civilizations existed but they've blown themselves up so your general intuition is that intelligent civilizations quickly like there's that parameter in in the drake equation your senses they don't last very long yeah how are we doing on that like have we lasted pretty pretty good i don't know we do oh yeah i mean not quite yet well what telly has your caskey the iq required to destroy the world falls by one point every year okay so technology democratizes the destruction of the world when can a meme destroy the world it kind of is already right somewhat i don't think i don't think we've seen anywhere near the worst of it yet world's going to get weird well maybe a mu can save the world you thought about that the meme lord elon musk fighting on the side of good versus the uh the meme lord of the darkness which is uh not saying anything bad about donald trump but he is the the lord of the meme on the dark side he's a darth vader of memes i think in every fairy tale they always end it with and they lived happily ever after and i'm like please tell me more about this happily ever after i've heard 50 percent of marriages end in divorce uh why doesn't your marriage end up there you can't just say happily ever after so it's the thing about destruction is it's over after the destruction um we have to do everything right in order to avoid it and uh one thing wrong i mean actually that's what i really like about cryptography cryptography it seems like we live in a world where the defense wins um versus like nuclear weapons the opposite is true it is much easier to build a warhead that splits into 100 little warheads than to build something that can you know take out 100 little warheads uh the offense has the advantage there um so maybe our future is in crypto but uh so cryptography right the goliath is the the defense and then all the different hackers are the uh are the davids and that equation is flipped for nuclear war because there's so many like one nuclear weapon destroys everything essentially yeah and it is much easier to uh attack with a nuclear weapon than it is to like the technology required to intercept and destroy a rocket is much more complicated than the technology required to just you know orbital trajectory send a rocket to somebody so okay your intuition that the there were intelligent civilizations out there but it's very possible that they're no longer there that's kind of a sad picture they enter some steady state they all wirehead themselves what's wirehead um stimulate stimulate their pleasure centers uh and just you know live forever in this kind of stasis they become well i mean i think the reason i believe this is because where are they if there's some reason they stopped expanding because otherwise they would have taken over the universe the universe isn't that big or at least you know let's just talk about the galaxy right 70 000 light years across uh i took that number from star trek voyager i don't know how true it is but um uh yeah that's not big right 70 000 light years is nothing for some possible technology that you can imagine that could leverage like wormholes or something like that you don't even need wormholes just a von neumann probe is enough a von neumann probe and a million years of sublight travel and you'd have taken over the whole universe that clearly uh didn't happen so something stopped it so you mean if you right for for like a few million years if you sent out probes that travel close what's sublight meaning close to the speed of light let's it just spreads interesting actually that's an interesting calculation huh so what makes you think that would be able to uh communicate with them like uh yeah what what's why do you think we would able to be able to comprehend intelligent lives that are out there like even if they were among us kind of thing like or even just flying around well i mean that's possible it's possible that there is some sort of prime directive uh that'd be a really cool universe to live in um and there's some reason they're not making themselves visible to us but it makes sense that they would use the same well at least the same entropy well you're implying the same laws of physics i don't know what you mean by entropy in this case oh yeah i mean if entropy is the scarce resource in the universe so what do you think about like stephen wolfram and everything is a computation and then what if they are traveling through this world of computation so if you think of the universe as just information processing then uh what you're referring to with with entropy and then these these pockets of interesting complex computations swimming around how do we know they're not already here how do we know that this like all the different amazing things that are full of mystery on earth are just like little footprints of intelligence from light years away maybe i mean i tend to think that as civilizations expand they use more and more energy uh and you can never overcome the problem of waste heat so where is their waste heat so we'd be able to with our crude methods be able to see like there's a whole lot of energy here but it could be something we're not i mean we don't understand dark energy right dark matter it could be just stuff we don't understand at all or they could have a fundamentally different physics you know like that that we just don't even compromise well i think okay i mean it depends how far out you want to go i don't think physics is very different on the other side of the galaxy i would suspect that they have i mean if they're in our universe they have the same physics well yeah that's the assumption we have but there could be like super trippy things like like our cognition only gets to a slice oh and all the possible instruments that we can design only get to a particular slice of the universe and there's something much like weirder maybe we can try a thought experiment um would people from the past be able to detect the remnants of our uh we would be able to detect our modern civilization i think the answer is obviously yes you mean past from 100 years ago well let's even go back further let's go to a million years ago right the humans who were lying around in the desert probably didn't even have maybe they just barely had fire uh they would understand if a 747 flew overhead in in in this vicinity but not um if the if a 747 flew on mars because they wouldn't be able to see far because we're not actually communicating that well with the rest of the universe we're doing okay we're just sending out random like 50s tracks of music true and yeah i mean they'd have to you know the we've only been broadcasting radio waves for um 150 years and well there's your light cone so yeah okay what do you make about all the i recently came across this uh having talked to david fravor i don't know if you caught what the the videos that pentagon released and uh the new york times reporting of the ufo sightings so i kind of looked into it quote unquote and there's actually been like hundreds of thousands of ufo sightings right and a lot of it you can explain away in different kinds of ways so one is it could be interesting physical phenomena two it could be people wanting to believe and therefore they conjure up a lot of different things that just you know when you see different kinds of lights some basic physics phenomena and then you just conjure up ideas of possible out there mysterious worlds but you know it's also possible like you have a case of david fravor who is a navy pilot who's you know as legit as a guest in terms of humans who are able to perceive things in the environment and make conclusions whether those things are a threat or not and he and several other pilots saw a thing i don't know if you followed this but they saw a thing that they've since then called tick tock that moved in all kinds of weird ways they don't know what it is it could be technology developed by by the united states and they're just not aware of it and the surface level from the navy right it could be different kind of lighting technology or drone technology all that kind of stuff it could be the russians and then chinese all that kind of stuff and of course their mind our mind can also venture into the possibility that it's from another world have you looked into this at all what do you think about it i think all the news is a psyop i think that the most closing is real yeah i listened to the uh i think it was bob lazar um on joe rogan and like i believe everything this guy is saying and then i think that it's probably just some like mk ultra kind of thing you know uh what do you mean like they they uh you know they made some weird thing and they called it an alien spaceship you know maybe it was just to like stimulate young physicist minds we'll tell them it's alien technology and we'll see what they come up with right do you find any conspiracy theories compelling like have you pulled at the string of the of the rich complex world of conspiracy theories that's out there i think that uh i've heard a conspiracy theory that conspiracy theories were invented by the cia in the 60s to discredit true things yeah um so you know you can go to ridiculous conspiracy theories like flat earth and pizzagate and uh you know these things are almost to hide like conspiracy theories that like you know remember when the chinese like locked up the doctors who discovered coronavirus like i tell people this and i'm like no no that's not a conspiracy theory that actually happened do you remember the time that the money used to be backed by gold and now it's backed by nothing this is not a conspiracy theory this actually happened that's one of my worries today with the idea of fake news is that when nothing is real then like you dilute the possibility of anything being true by conjuring up all kinds of conspiracy theories and then you don't know what to believe and then like the idea of truth of objectivity is lost completely everybody has their own truth so you used to control information by censoring it then the internet happened and governments are like oh we can't censor things anymore i know what we'll do you know it's the old story of uh the story of like tying a flag where the leprechaun tells you the gold is buried and you tie one flag and you make the leprechaun swear to not remove the flag and you come back to the field later with a shovel and there's flags everywhere that's one way to maintain privacy right is like in order to protect the contents of this conversation for example we could just generate like millions of deep fake conversations where you and i talk and say random things yeah so this is just one of them and nobody knows which one was the real one this this could be fake right now classic steganography technique okay another absurd question about intelligent life because uh you know you're you're an incredible programmer outside of everything else we'll talk about just as a programmer uh do you think intelligent beings out there the civilizations that were out there had computers and programming did they do we naturally have to develop something where we engineer machines and are able to encode both knowledge into those machines and instructions that process that knowledge process that information to to make decisions and actions and so on and with those programming languages if you think they exist be at all similar to anything we've developed so i don't see that much of a difference between quote-unquote natural languages and programming languages um yeah i think there's so many similarities so when asked the question what do alien languages look like i imagine they're not all that dissimilar from ours and i think translating in and out of them uh wouldn't be that crazy well it's difficult to compile like dna to python and then to see i mean there is a little bit of a gap in in the kind of languages we use for for uh touring machines and the kind of languages nature seems to use a little bit maybe that's just we just haven't cr we haven't understood the kind of language that nature uses well yet dna is a cad model it's not quite a programming language it has no sort of serial execution it's not quite a yeah it's a cad model um so i think in that sense we actually completely understand it the problem is um you know well simulating on these cad models i played with it a bit this year is super uh computationally intensive if you want to go down to like the molecular level um where you need to go to see a lot of these phenomena like protein folding um so yeah it's not that it's it's not it's not that we don't understand it it just requires a whole lot of compute to kind of compile it for our human minds it's inefficient both for the pro for the data representation and for the programming yeah it runs well on raw nature it runs well in raw nature and when we try to build uh emulators or simulators for that uh well then manslaughter and i've tried it it runs in yeah you've commented elsewhere i don't remember where that uh one of the problems is simulating nature is tough and if you want to sort of deploy a prototype i forgot how you you put it but it made me laugh but animals or humans would need to be involved in order to in order to try to run some prototype code on um like if we're talking about covid and viruses and so on yeah if you were trying to engineer some kind of defense mechanisms like a vaccine uh against coven or all that kind of stuff that doing any kind of experimentation like you can with like autonomous vehicles would be very technically cost technically and ethically costly i'm not sure about that i think you can do tons of uh crazy biology and in test tubes i think my bigger complaint is more all the tools are so bad like literally you mean like like i'm not libraries and i'm not pipetting like you're handing me a i gotta no no no no there has to be some like automating stuff and like the yeah but human biology is messy like it seems like look at those toronto's videos they were a joke it's like it's like a little gantry it's like a little xy gantry high school science project with the pipette i'm like really gotta be something better you can't build like nice microfluidics and i can program the you know computation to bio interface i mean this is going to happen but like right now if you are asking me to pipette 50 milliliters of solution amount this is so crude yeah okay let's get all the crazy out of the way uh so a bunch of people ask me since we talked about the simulation last time we talked about hacking the simulation do you have any updates any insights about how we might be able to go about hacking simulation if we indeed do live in a simulation i think a lot of people misinterpreted the point of that south by talk the point of the south by talk was not literally to hack the simulation uh i think that this we this is this is an idea is literally just i think theoretical physics i think that's the whole you know the whole goal right you want your grand unified theory but then okay build a brand new five theory search for exploits right i think we're nowhere near actually there yet my hope with that was just more to like like are you people kidding me with the things you spend time thinking about do you understand like kind of how small you are you are you are bites and god's computer really and the things that people get worked up about and you know so basically it was more a message of uh we should humble ourselves that we we get to uh like what what are we humans in this bite code yeah and not just just humble ourselves but like like i'm not trying to like make you feel guilty or anything like that i'm trying to say like literally look at what you are spending time on right what are you referring to you're referring to the kardashians what are we talking about from twitter to no the kardashians see everyone knows that's kind of fun i'm referring more to like the economy you know this idea that we gotta up our stock price like or or what is what is the goal function of humanity you don't like the game of capitalism like you don't like the games we've constructed for ourselves as humans i'm a big fan of of capitalism i don't think that's really the game we're playing right now i think we're playing a a different game where the rules are rigged look at which games are interesting to you that we humans have constructed and which aren't which are productive and which are not actually maybe that's the real point of the of the talk it's like stop playing these fake human games there's a real game here we can play the real game the real game is you know nature wrote the rules this is a real game there still is a game to play but if you look at sergeant drop i don't know if you've seen the instagram account nature is metal the game that nature seems to be playing is a lot a lot more cruel than we humans want to put up with or at least we see it as cool it's like the bigger thing eats the smaller thing and uh does it to impress another big thing so it can mate with that thing and that's it that seems to be the entirety of it well there's no art there's no music there's no comma ai there's no comma one no comma two no george hotz with his brilliant talks at south by southwest see i disagree though i disagree that this is what nature is i think nature just provided basically a uh open world and mmorpg and um you know here it's open world i mean if that's the game you want to play you can play that game but isn't that isn't that beautiful i know if you play diablo they used to have uh i think cow level where it's so everybody will go just they figured out this like the best way to gain like experience points is to just slaughter cows over and over and over and uh so they figured out this little sub game within the bigger game that this is the most efficient way to get experience points and everybody somehow agreed that getting experience points in rpg context where you always want to be getting more stuff more skills more levels keep advancing that seems to be good so might as well spend sacrifice actual enjoyment of playing a game exploring a world and spending like hundreds of hours of your time in cow level i mean the number of hours i spent in cow level i'm not like the most impressive person because people have probably thousands of hours there but it's ridiculous so that's a little absurd game that brought me joy in some weird dopamine drug kind of way yeah so you you don't like those games you don't you don't think that's us humans failing the the yeah nature i think so and that was the point of the talk yeah so how do we hack it then well i want to live forever and wait i want to live forever and this is like the goal well that's a game against nature yeah immortality is the good objective function to you i mean start there and then you can do whatever else you want cause you got a long time what if mortality makes the game just totally not fun i mean like why do you assume immortality is uh somehow uh it's not a good objective function it's not immortality that i want a true immortality where i could not die i would prefer what we have right now um but i want to choose my own death of course i don't want nature to decide when i die i'm going to win i'm going to be you and then at some point if you choose commit suicide like how long you think you'd live until i get bored see i don't think people like in like brilliant people like you that really ponder living a long time are really considering how how meaningless life becomes well i want to know everything and then i'm ready to die as long as why do you want isn't it possible that you want to know everything because it's finite like the reason you want to know quote unquote everything is because you don't have enough time to know everything and once you have unlimited time then you realize like why do anything like why learn anything i want to know everything and i'm ready to die so you have yeah well it's not it's not a like it's a terminal value it's not it's not in service of anything else i'm conscious of the possibility this is not a certainty but the possibility is of that engine of curiosity that you're speaking to is actually a a symptom of uh the finiteness of life like without that finiteness your curiosity would vanish like like a like a morning fog all right cool then you talked about love like that then um let me solve immortality let me change the thing in my brain that reminds me of the fact that i'm immortal tells me that life is finite maybe i'll have it tell me that life ends next week right i'm okay with some self manipulation like that i'm okay with with deceiving oh change oh rico changing the code if that's the problem right if the problem is that i will no longer have that that curiosity i'd like to have backup copies of myself uh which yeah well which i check in with occasionally to make sure they're okay with the trajectory and they can kind of override it maybe a nice like i think of like those wavenets those like logarithmic go back to the copies yeah but sometimes it's not reversible like uh sure i've done this with video games when once you figure out the cheat code or like you look up how to cheat old school like single player it ruins the game for you absolutely i know that feeling but again that just means our brain manipulation technology is not good enough yet remove that cheat code from your brain what if we all so it's also possible that if we figure out immortality that all of us will kill ourselves before we advance far enough to uh to be able to revert to change i'm not killing myself till i know everything so that's what you say now because your life is finite you know i think yes self-modifying systems gets comes up with all these hairy complexities and can i promise that i'll do it perfectly no but i think i can put good safety structures in place so that talk in your thinking here is not literally referring to uh a simulation in that our our universe is a kind of computer program running in a computer that's more of a thought experiment um do you also think of the potential of the sort of uh bostrom elon musk and others that talk about an actual program that simulates our universe oh i don't doubt that we're in a simulation i just think that it's not quite that important i mean i'm interested only in simulation theory as far as like it gives me power over nature uh if it's totally unfalsifiable then who cares i mean what do you think that experiment would look like like somebody uh on twitter asked ask george what signs we would look for to know whether or not we're in the simulation which is exactly what you're asking is like the step that precedes the step of knowing how to get more power from this knowledge is to get an indication that there is some power to be gained so get an indication that there you can discover and exploit cracks in the simulation or it doesn't you know in the physics of the universe yeah show me i mean like a memory leak would be cool like some scrying technology you know what what kind of technology scrying what's that oh that's a weird uh this crying is the is the uh paranormal ability to uh like like remote viewing like being able to see somewhere where you're not um so you know i don't think you can do it by chanting in a room but um if we could find as a memory leak basically yeah you're able to access parts you're not supposed to yeah yeah yeah and thereby discover shortcut yeah maybe memory leak means the other thing as well but i mean like yeah like an ability to read arbitrary memory yeah right and that one's not that horrifying right the the right ones start to be horrifying read right so the the reading is not the problem yeah it's like heartbleed for the universe oh boy the writing is a big big problem it's a big problem it's the moment you can write anything even if it's just random noise that's terrifying i mean even without even without that like even some of the you know the nanotech stuff that's coming i think is i don't know if you're paying attention but actually eric weinstein came out with the theory of everything i mean that came out he's been working on a theory of everything in the physics world called geometric community and then for me from computer science person like you stephen wolfram's theory of everything of like hypographs is super interesting and beautiful but not from a physics perspective but from a computational perspective i don't know have you paid attention to any of that so again like what would make me pay attention and like why like i hate string theory is okay make a testable prediction right i'm only interested in i'm not interested in theories for their intrinsic beauty i'm interested in theories that give me power over the universe so if these theories do i'm very interested um can i just say how beautiful that is because a lot of physicists say i'm interested in experimental validation and they skip out the part where they say to give me more power in the universe i just love the um yo i want i want i want the clarity of that i want 100 gigahertz processors i want transistors that are smaller than atoms i want like power that's uh that's true and that's where people from aliens to this kind of technology where people are worried that governments like who owns that power is it george hearts is it thousands of distributed hackers across the world is it governments you know is it mark zuckerberg there's a lot of people that uh i don't know if anyone trusts any one individual with power so they're always worried it's the beauty of blockchains that's the beauty of blockchains which we'll talk about on twitter somebody pointed me to a story uh a bunch of people pointed me to a story a few months ago where you went into a restaurant in new york and you can correct me fame this is wrong and ran into a bunch of folks from a company in a crypto company who are trying to scale up ethereum and they had a technical deadline related to a solidity to ovm compiler so these are all ethereum technologies so you stepped in they recognized you uh pulled you aside explained their problem and you stepped in and helped them solve the problem uh thereby creating legend status story so uh can you uh tell me the story the little more detail it seems kind of incredible this did this happen yeah yeah it's a true story it's a true story i mean they wrote a very flattering account of it um they so optimism is the spin the company's called optimism spin-off of plasma they're trying to build l2 solutions on ethereum so right now uh every ethereum node has to run every transaction on the ethereum network um and this kind of doesn't scale right because if you have n computers well you know if that becomes two n computers you actually still get the same amount of compute right this is this is like like o of one scaling um because they all have to run it okay fine you get more blockchain security but like the blockchain's already so secure can we trade some of that off for speed uh so that's kind of what these l2 solutions are they built this thing which kind of um kind of sandbox uh for ethereum contracts so they can run it in this l2 world and it can't do certain things in l world in l1 i can ask you for some definitions what's l2 oh l2 is layer 2. so l1 is like the base ethereum chain and then layer two is like a computational layer that runs um elsewhere but still is kind of secured by layer one and i'm sure a lot of people know but ethereum is a cryptocurrency probably one of the most popular cryptocurrencies second to bitcoin and a lot of interesting technological innovations there maybe you can also slip in whenever you talk about this any things that are exciting to you in the ethereum space and why ethereum well i mean bitcoin uh is not turn complete well ethereum is not technically a terrain complete with a gas limit but close enough well the gas limit what's the gas limit resources yeah i mean no computers actually turn complete right right you're fine at ram you know what if i can actually solve this gas limit you just have so many brilliant words i'm not even gonna ask but that's what that's no that's not my word that's ethereum's word gasoline ethereum you have to spend gas per instruction so like different op codes use different amounts of gas and you buy gas with ether to prevent people from basically ddosing the network so uh bitcoin is proof of work and then what's ethereum it's also proof of work uh they're working on some proof-of-stake ethereum 2.0 stuff but right now it's it's proof of work usually a different hash function from bitcoin that's more asic resistance because you need ram so we're all talking about ethereum 1.0 yeah so what uh what were they trying to do to scale this whole process so they were like well if we could run contracts elsewhere um and then only save the results of that computation uh you know well we don't actually have to do the computer on the chain we can do the compute off chain and just post what the results are now the problem with that is well somebody could lie about what the results are so you need a resolution mechanism and the resolution mechanism can be really expensive uh because you know you just have to make sure that like the person who is saying look i swear that this is the real computation i'm staking ten thousand dollars on that fact and if you prove it wrong yeah it might cost you three thousand dollars in gas fees to prove wrong but you'll get the ten thousand dollar bounty so you can secure using those kind of systems um so it's effectively a sandbox which runs contracts uh and like just like any kind of normal sandbox you have to like replace syscalls with um you know calls into the hypervisor uh sandbox this calls hypervisor what do these things mean uh as long as it's interesting to talk about yeah i mean you can take like the chrome is maybe the one to think about right so the chrome process that's doing a rendering uh can't for example read a file from the file system yeah it has if it tries to make an open syscall in linux the open system you can't make it open says call no no no uh you have to request from the kind of uh hypervisor process or like i don't know what's called in chrome but um the canoe hey could you open this file for me and then it does all these checks and then it passes the file handle back in if it's approved um so that's yeah uh so what's the in the context of ethereum what are the boundaries of the sandbox that we're talking about um well like one of the calls that you actually reading and uh writing any state to the ethereum contract to the ethereum blockchain um writing state is one of those calls that you're going to have to sandbox in layer two because if you let layer two just arbitrarily right to the ethereum blockchain um so layer two is except is really sitting on top of layer one so you're gonna have a lot of different kinds of ideas that you can play with yeah and they're all they're not fundamentally changing the source code level of ethereum well you have to replace a bunch of calls with calls into the hypervisor so instead of doing the syscall directly you you replace it with a call to the hypervisor so originally they were doing this by first running the so solidity is the language that most ethereum contracts are written in it compiles to a byte code and then they wrote this thing they called the transpiler and the transpiler took the byte code and it transpiled it into ovm safe bytecode basically bytecode that didn't make any of those restricted syscalls and added the calls to the hypervisor this transpiler was a 3000 line mess and it's hard to do it's hard to do if you're trying to do it like that because you have to kind of like deconstruct the byte code change things about it and then reconstruct it and i mean as soon as i hear this i'm like why don't you just change the compiler right why not the first place you build the bytecode just do it in the compiler uh so yeah you know i asked them how much they wanted it uh of course measured in dollars and i'm like well okay um and yeah and you wrote the compiler yeah i modified i wrote a 300 line diff to the compiler uh it's open source you can look at it yeah it's yeah i looked at the code last night [Laughter] yeah exactly cute good is a good word for it uh and it's um c plus plus see if it's lost yeah so when asked how you were able to do it you said you just gotta think and then do it right so can you break that apart a little bit what's what's your process of uh one thinking and two doing it right you know they they the people i was working for are amused that i said that it doesn't really mean anything okay i mean is there some deep profound insights to draw from like how you problem solve from that because this is always what i say i'm like do you want to be a good programmer do it for 20 years yeah there's no shortcuts yeah what are your thoughts on crypto in general so would what what parts technically or philosophically do you find especially beautiful maybe oh i'm extremely bullish on crypto long term not any specific crypto project but this idea of well two ideas one um the nakamoto consensus algorithm is i think one of the greatest innovations of the 21st century this idea that people can reach consensus you can reach a group consensus using a relatively straightforward algorithm um is wild and like you know satoshi nakamoto people always ask me who i look up to it's like whoever that is who do you think it is i mean elon musk is it you it is definitely not me and i do not think it's elon musk but yeah this idea of uh groups reaching consensus in a decentralized yet formulaic way is one extremely powerful idea from crypto maybe the second idea is this idea of smart contracts when you write a contract between two parties any contract um this contract if there are disputes it's interpreted by lawyers lawyers are just really shitty overpaid interpreters imagine you had let's talk about them in terms of a in terms of like let's compare a lawyer to python right so lawyer well okay that's really oh i never thought of it that way it's hilarious so python i'm paying i'm paying um you know even 10 cents an hour i'll use the nice azure machine i can run python for 10 cents an hour lawyers cost a thousand dollars an hour so python is is is 10 000 x uh better on that axis um lawyers don't always return the same answer um python almost always does uh cost yeah i mean just just cost reliability everything about python is so much better than lawyers um so if you can make smart contracts this whole concept of code is law i i love and i would love to live in a world where everybody accepted that fact so so maybe uh you can talk about what smart contracts are so let's say um let's say you know we have a uh even something as simple as a safety deposit box right safety deposit box that holds a million dollars i have a contract with the bank that says two out of these three parties uh must uh be present to open the safety deposit box and get the money out so that's a contract for the bank and it's only as good as the bank and the lawyers right let's say you know somebody dies and now oh we're going to go through a big legal dispute about whether oh well was it in the will was it not in the well what like it's just so messy and the cost to determine truth is so expensive versus a smart contract which just uses cryptography to check if two out of three keys are present well i can look at that and i can have certainty in the answer that it's going to return that's what all businesses want certainty you know they say businesses don't care viacom youtube youtube's like look we don't care which way this lawsuit goes just please tell us so we can have certainty yeah i wonder how many agreements in this world because we're talking about financial transactions only in this case correct the smart the smart contracts oh you can go to you can go to anything you can go you could put a prenup in the theorem blockchain a married smart contract sorry divorce lawyers sorry you're going gonna be replaced by python uh okay so that's uh so that's that's another beautiful idea do you think there's something that's appealing to you about any one specific implementation so if you look 10 20 50 years down the line do you see any like bitcoin ethereum any of the other hundreds of cryptocurrencies winning out is there like what's your intuition about the space are you just sitting back and watching the chaos and look who cares what emerges oh i don't i don't speculate i don't really care i don't really care which one of these projects wins i'm kind of in the bitcoin as a meme coin camp i mean why does bitcoin have value it's technically kind of you know what yeah not great like the block size debate or when i found out what the block size debate was i'm like are you guys kidding what's the block size debate you know what it's really it's too stupid to even talk about people people people can look it up but i'm like wow you know ethereum seems the governance of ethereum seems much better um i've come around i've been on proof of stake ideas uh you know very smart people thinking about some things yeah you know governance is interesting it does feel like uh vitalik it could just feel like an open in even in these distributed systems leaders and are helpful because they kind of help you drive the mission and the vision and they put a face to a project it's a weird thing about us humans geniuses are helpful like mattel right yeah brilliant leaders are not necessarily yeah so you think the reason he's uh he's the face of a theorem is because he's a genius that's interesting i mean that was um it's interesting to think about that we need to create systems in which uh the quote unquote leaders that emerge are the geniuses in the system i mean that's arguably why the current state of democracy is broken is the people who are emerging as the leaders are not the most competent are not the superstars of the system and it seems like at least for now in the crypto world oftentimes the leaders are the superstars imagine at the debate they asked what's the sixth amendment what are the four fundamental forces in the universe right what's the integral of two to the x yeah i i'd love to see those questions asked and that's what i want as our leader it's it's a little bit of a bayes rule yeah i mean even oh wow you're hurting my brain it's that my standard was even lower but i would have loved to see just this basic brilliance like i've talked to historians there's just these they're not even like they don't have a phd or even education history they just like a dan carlin type character who just like holy how did all this information get into your head they're able to just connect uh genghis khan to the entirety of the history of the 20th century they they know everything about every single battle that happened and they know the the the like the game of thrones of the of the different power plays and all that happened there and they know like the individuals they know all the documents involved and it's and that they integrate that into their regular life it's not like they're ultra history nerds they're just they know this information that's what competence looks like yeah because i've seen that with programmers too right that's what great programmers do but yeah it would be uh it's really unfortunate that those kinds of people aren't emerging as as our leaders but for now at least in the crypto world that seems to be the case i don't know if that always uh you could imagine that in a hundred years that's not the case right the crypto world has one very powerful idea going for it and that's the idea of forks right i mean you know imagine uh we'll use a less controversial example um this was actually in my joke uh app in 2012 i was like barack obama mitt romney let's let him both be president right like imagine we could fork america and just let them both be president and then the americas could compete and you know people could invest in one pull their liquidity out of one put it in the other you have this in the crypto world ethereum forks into ethereum and ethereum classic and you can pull your liquidity out of one and put it in another and people vote with their dollars um which forks companies should be able to fork i'd love to fork nvidia you know yeah like different business strategies and yeah and then try them out and see see what works like even take uh uh yeah take comedy i that closes its source and then take one that's open source and see what works take one that's purchased by gm and one that remains android renegade and all these different versions and see the beauty of comma ai is someone could actually do that yeah please take come ai and fork it that's right that's the beauty of open source so you're i mean we'll talk about autonomous vehicle space but it does seem that you're really knowledgeable about a lot of different topics so the natural question a bunch of people ask this which is uh how do you keep learning new things do you have like practical advice if you were to introspect like taking notes allocate time or do you just mess around and just allow your curiosity to drive i'll write these people a self-help book and i'll charge 67 for it and i will i will write i will write chapter one i will write on the cover of the self-help book all of this advice is completely meaningless you're gonna be a sucker and buy this book anyway yeah and the one lesson that i hope they take away from the book is that i can't give you a meaningful answer to that that's interesting let me translate that is you haven't really thought about what it is you do systematically because you could reduce it and there's some people i mean i've met brilliant people that this is really clear with athletes some are just you know the best in the world that's something and they they have zero interest in writing like a self-help book but or how to master this game and then there's some athletes who become great coaches and they love the analysis perhaps the over analysis and you right now at least at your age which isn't interesting you're in the middle of the battle you're like the warriors that have zero interest in writing books uh so you're in the middle of the battle so you have yeah this is this is a fair point i do think i have a certain aversion to um this kind of deliberate intentional way of living life here eventually the hilarity of this especially since this is recorded it will reveal beautifully the absurdity when you finally do publish this book and i guarantee you you will the story of comma ai would be maybe it'll be a biography written about you they'll be they'll be better i guess and you might be able to learn some cute lessons if you're starting a company like comma ai from that book but if you're asking generic questions like how do i be good at things dude i don't know well learn i mean the interesting do them a lot i do them a lot but the interesting thing here is learning things outside of your current trajectory which is what it feels like from an outsider's perspective i mean that uh you know that i don't know if there's an advice on that but it is an interesting curiosity when you become really busy you're running a company part time yeah but like there's a natural inclination and trend like just the the the momentum of life carries you into a particular direction of wanting to focus and this kind of dispersion that curiosity can lead to gets harder and harder with time because you're you get really good at certain things and it sucks trying things that you're not good at like trying to figure them out you do this with your live streams you're on the fly figuring stuff out you don't mind looking dumb you just figured out figure it out pretty quickly sometimes i try things and i don't figure them out my chest rating is like a 1400 despite putting like a couple hundred hours in it's pathetic i mean to be fair i know that i could do it better if i did it better like don't play you know don't play five-minute games play 15-minute games at least like i know these things but it just doesn't it doesn't stick nicely in my knowledge tree all right let's talk about comma ai what's the mission of the company let's like look at the biggest picture oh i have an exact statement solve self-driving cars while delivering shippable intermediaries so long-term vision is have fully autonomous vehicles and make sure you're making money along the way i think it doesn't really speak to money but i can talk i can talk about what solve self-driving cars means solve self-driving cars of course means um you're not building a new car you're building a person replacement uh that person can sit in the driver's seat and drive you anywhere a person can drive with a human or better level of safety speed quality comfort and what's the second part of that delivering shippable intermediaries um is well it's a way to fund the company that's true but it's also a way to keep us honest uh if you don't have that it is very easy with this technology to think you're making progress when you're not i've heard it best described on hacker news as you can set any arbitrary milestone meet that milestone and still be infinitely far away from solving self-driving cars so it's hard to have like real deadlines when you're like cruz or waymo when uh you don't have uh revenue is that i mean is revenue essentially the thing we're talking about here revenue is is capitalism is based around consent capitalism the way that you get revenue is kind of real capitalism commas in the real capital is in camp there's definitely scams out there but real capitalism is based around consent it's based around this idea that like if we're getting revenue it's because we're providing at least that much value another person when someone buys a thousand dollar comment two from us we're providing them at least a thousand dollars of value where they wouldn't buy it brilliant so can you give a whirlwind overview of the products that come i provides like uh throughout its history and today i mean yeah the past ones aren't really that interesting it's kind of just been refinement of the same idea uh the real only product we sell today is the comma two which is a piece of hardware with cameras um so the comet to i mean you can think about it kind of like a person uh you know when future hardware will probably be even more and more person-like um so it has uh you know eyes ears a mouth a brain uh and a way to interface with the car does it have consciousness just kidding that was a trick question because i don't have consciousness either me and the common two are the same they're the same i have a little more compute than it it only has like the same computer interesting b uh you know you're more efficient energy wise for the compute you're doing far more efficient energy-wise huh 20 paid flaps 20 watts crazy you lack consciousness sure do you fear death you do you want immortality does comey i fear death i don't think so of course it does it very much fears while it fears negative loss oh yeah okay so come a comma two when did that come out that that was a year ago no two uh early this year wow time it feels like yeah 2020 feels like uh it's taken 10 years to get to the end it's a long year it's a long year so um what uh what's the sexiest thing about comma too feature-wise so i mean maybe you can also link on like what is it like what's its purpose because there's a hardware there's a software component you've mentioned the sensors but also like what is of its features and capabilities i think our slogan summarizes it well uh comma slogan is make driving chill i love it okay yeah i mean it is you know if you like cruise control imagine cruise control but much much more so it can uh do adaptive cruise control things which is like slow down for cars in front of it maintain a certain speed and you can also do lane keeping so staying in the lane and doing it better and better and better over time that's very much machine learning based so this camera is there's a driver facing camera too that's um what else is there what am i thinking so the hardware versus software so open pilot versus the actual hardware of the device what's can you draw that distinction what's one what's the other i mean the hardware is pretty much a cell phone with a few additions a cell phone with a cooling system and with a car interface connecting to it and as by cell phone you mean uh like qualcomm snapdragon uh yeah the current hardware is a snapdragon 821 uh it has wi-fi radio it has an lte radio it has a screen uh we use every part of the cell phone and then the interface of the car is specific to the car so you keep supporting more and more cars um yeah so the interface to the car i mean the device itself just has four can buses has four cam interfaces on it that are connected through the usb port to the phone um and then yeah on those four can buses uh you connect it to the car and there's a little harness to do this cars are actually surprisingly similar so can is the the protocol by which cars communicate and then you're able to read stuff and write stuff to be able to control the car depending on the car so what's the software side what's open pilot um so i mean open pilot is the hardware is pretty simple compared to open pilot open pilot is uh well so you have a machine learning model which it's an open pilot it's a you know it's a blob it's just a blob of weights it's not like people are like oh it's closed source i'm like it's a blob of weights what do you expect um you know primarily neural network based ul open pilot is all the software kind of around that neural network that if you have a neural network that says here's where you want to send the car openpilot actually goes and executes all of that it cleans up the input to the neural network it cleans up the output and executes on it so it connects it's the glue that connects everything together runs the sensors does a bunch of calibration for the neural network does you know deals with like you know if the car is on a banked road uh you have to counter steer against that and the neural network can't necessarily know that by looking at the picture so you do that with with other sensors infusion and localizer openpilot also is responsible for sending the data up to our servers so we can learn from it logging it recording it running the cameras thermally managing the device managing the disk space on the device managing all the resources of the device so what um since we last spoke i don't remember when maybe a year ago maybe a little bit longer how uh has open pilot improved we did exactly what i promised you i promised you that by the end of the year you'd be able to remove the lanes um the lateral policy is now uh almost completely end to end you can turn the lanes off and it will drive drive slightly worse on the highway if you turn the lanes off but you can turn the lanes off and it will drive well trained completely end to end on user data um and this year we hope to do the same for the longitudinal policy so that's the interesting thing is you're not doing you don't appear to be you can correct me you don't appear to be doing lean detection or lane marking detection or kind of the segmentation task or any kind of object detection task you're doing what's traditionally more called like end-to-end learning so and trained on actual behavior of drivers when they're driving the car manually and this is hard to do you know it's not supervised learning yeah but uh so the nice thing is there's a lot of data so it's hard and easy right it's uh we have a lot of high quality data yeah like more than you need in the senate well we way more than we do we have way more data than we need i mean it's it's an interesting question actually because in terms of amount you have more than you need but the you know driving is full of edge cases so how do you select the data you train on i i think this is an interesting open question like what's what's the cleverest way to select data that's the question tesla is probably working on uh that's i mean the entirety of machine learning can be they don't seem to really care they just kind of select data but i feel like that if you want to solve if you want to create intelligent systems you have to pick data well right and so would you have any hints ideas of how to do it well so in some ways that is the definition i like of reinforcement learning versus supervised learning in supervised learning the weights depend on the data right um and this is obviously true but the uh in reinforcement learning the data depends on the weights yeah right and actually both ways that's that's poetry so it's brilliant how does it know what data to turn on well let it pick we're not there yet but that's the eventual so you're thinking this almost like a reinforcement learning framework we're going to do rl on the world every time a car makes a mistake user disengages we train on that and do our all in the world ship out a new model that's an epoch right and uh for now you're not doing the elon style promising that it's going to be fully autonomous you really are sticking to level two and like it's supposed to be supervised oh it is definitely supposed to be supervising reinforced the fact that it's supervised um we look at our rate of improvement in disengagements um open pilot now has an unplanned engagement about every 100 miles this is up from 10 miles like maybe maybe uh maybe a year ago yeah so maybe we've seen 10x improvement in a year but a hundred miles is still a far cry from the hundred thousand you're going to need so you're going to somehow need to get um three more 10xs in there and your what's your intuition uh you're basically hoping that there's exponential improvement built into the baked into the cake somewhere well that's even like i mean 10x improvement that's already assuming exponential right there's definitely exponential improvement and i think when elon talks about exponential like these things these systems are going to exponentially improve just exponential doesn't mean you're getting 100 gigahertz processors tomorrow right like it's going to still take a while because the gap between even our best system and humans is still large so that's an interesting distinction to draw so if you look at the way tesla's approaching the problem and the way you're approaching the problem which is very different than the rest of the self-driving car world so let's put them aside is you're treating most the driving task is a machine learning problem and the way tesla is approaching it is with the multi-task learning where you break the task of driving into hundreds of different desks and you have this multi-headed neural network that's very good at performing each task and there there's presumably something on top that's stitching stuff together in order to uh make controlled decisions policy decisions about how you move the car but what that allows you there's a brilliance to this because it allows you to um master each task like lane detection uh stop sign detection traffic light detection uh drivable area segmentation uh you know vehicle bicycle pedestrian detection uh there's some localization tasks in there also predicting of like yeah predicting how the the entities in the scene are going to move like everything is basically a machine learning task well there's a classification segmentation prediction and it's nice because you can have this entire engine data engine that's mining for edge cases for each one of these tasks and you can have people like engineers that are basically masters of that task like becoming the best person in the world that uh as you talk about the cone guy for uh for for waymo the good old phone guy the the becoming the best person in the world at uh at uh at cone detection i i so that's a compelling notion from a supervised learning perspective automating much of the process of educates discovery and retraining neural network for each of the individual perception tasks and then you're looking at the machine learning in a more holistic way basically doing end-to-end learning on the driving task supervised trained on the data of the actual driving of people that use comma ai like actual human drivers do manual control plus the moments of disengagement that uh maybe with some labeling could indicate the failure of the system so you have the you have a huge amount of data for positive control of the vehicle like successful control of the vehicle both maintaining the lane as as i think you're also working on longitudinal control of the vehicle and then failure cases where the vehicle does something wrong that needs disengagement so like what why do you think you're right and tesla is wrong on this and do you think do you think you'll come around the tesla way do you think tesla will come around to your way if you were to start a chess engine company would you hire a bishop guy see we have uh this is monday morning quarterbacking as uh yes probably [Laughter] so oh oh our rook guy oh we stole the rook guy from that company oh we're gonna have real good rooks well there's not many pieces right you can uh yeah there's not many guys and gals to hire you just have a few that work on the bishop a few that work in the rook but is that not ludicrous today to think about in in the world of alpha zero but alpha zero is jessica so the the fundamental question is how hard is driving compared to chess because so long term end to end will be the right solution the question is how many years away is that end-to-end is going to be the only solution for level five for the only way we can of course and of course tesla's gonna come around to my way and if you're a rook guy out there i'm sorry the cone guy i don't know we're gonna specialize each task we're gonna really understand rook placement yeah i understand the intuition you have i mean that that uh is very compelling notion that we can learn the task and to end like the same compelling notion you might have for natural language conversation i'm not sure because one thing you sneaked in there is the assertion that it's impossible to get to level five without this kind of approach i don't know if that's obvious i don't know if that's obvious either i don't actually uh mean that i think that it is much easier to get to level five with an end-to-end approach i think that the other approach is doable but the magnitude of the engineering challenge may exceed what humanity is capable of so but what do you think of the tesla data engine approach which to me is an active learning task is kind of fascinating is breaking it down into these multiple tasks and mining their data constantly for like edge cases for these different tasks but the tasks themselves are not being learned this is feature engineering yeah i mean it's it's a it's a higher abstraction level of feature engineering for the different tasks it's task engineering in a sense it's slightly better feature engineering but it still fundamentally is feature engineering and anything about the history of ai has taught us anything it's that feature engineering approaches will always be replaced and lose to end to end now to be fair i cannot really make promises on timelines but i can say that when you look at the code for stockfish and the code for alpha zero one is a lot shorter than the other a lot more elegant required a lot less programmer hours to write yeah but there was a lot more murder of bad uh agents on the uh alpha zero side by murder i mean uh agents that played a game and failed miserably yeah oh in simulation that failure is less costly yeah in in real world it's wait do you mean in practice like alpha zero has lost games miserably no well i haven't seen that no but i know but the the the the requirement for alpha zero is a simulator to be able to like evolution human evolution not human evolution biological evolution of life on earth from the origin of life has murdered trillions upon trillions of organisms on the path to us humans yeah so the question is can can we uh stitch together a human-like object without having to go through the entirety process of evolution well no but do the evolution in simulation yeah that's the question can we simulate so do you have a sense that's possible to simulate some mu zero is exactly this mu zero is is the solution to this mu zero i think is going to look be looked back as the canonical paper and i don't think deep learning is everything i think that there's still a bunch of things missing to get there but mu zero i think is going to be looked back as the kind of cornerstone paper um of this whole deep learning era and mu zero is the solution to self-driving cars you have to make a few tweaks to it but mu0 does effectively that it does those roll outs and those murdering in in a learned simulator in a learned dynamics model it's interesting it doesn't get enough love i was blown away when i i was blown away when i read that paper i'm like you know okay i've always had a comma i'm gonna sit and i'm gonna wait for the solution to self-driving cars to come along this year i saw it it's me zero yeah so uh sit back and let the winning roll in so your sense just to elaborate a little bit to link on the topic your senses in your networks will solve driving yes like we don't need anything else i think the same way chess was maybe the chess and maybe google are the pinnacle of like search algorithms and things that look kind of like a star um the pinnacle of this era is going to be self-driving cars but on the path of that you have to deliver products and it's possible that the path to full self-driving cars will take decades i doubt it so how long would you put on it like what what are we you're chasing it tesla's chasing it what are we talking about five years 10 years 50 years in the 2020s in the 2020s the later part of the 2020s with the neural network well that would be nice to see and on the path to that you're delivering products which is a nice l2 system that's what tesla's doing a nice l2 system i'm just going to do better every time l2 the only difference between l2 and the other levels is who takes liability and i'm not a liability guy i want to take liability level 2 forever now on that little transition i mean how do you make the transition work is uh is this where driver sensing comes in like how do you make the because you said 100 miles like is is there some sort of human factor psychology thing where people start to over trust the system all those kinds of effects once it gets better and better and better and better they get lazier and lazier and lazier is that like how do you get that transition right first off our monitoring is already adaptive our monitoring is already seen adaptive driver monitoring is this the camera that's looking at the driver you have an infrared camera in the our policy for how we enforce the driver monitoring is scene adaptive what's that mean well for example in one of the extreme cases um if you uh if the car is not moving we do not uh actively enforce driver monitor right um if you are going through a uh like a 45 mile an hour road with lights um and stop signs and potentially pedestrians we enforce a very tight driver monitoring policy if you are alone on a perfectly straight highway um and this is it's all machine learning none of that is hand coded actually the stop is hand coded but so there's some kind of machine learning estimation of risk yes yeah i mean i've always been a huge fan of that that that's uh because it's difficult to do every step into that direction is a worthwhile step to take it might be difficult to do really well like us humans are able to estimate risk pretty damn well whatever the hell that is that feels like one of the nice features of us humans uh because like we humans are really good drivers when we're really like tuned in and we're good at estimating risk like when are we supposed to be tuned in yeah and you know people are like oh well you know why would you ever make the driver monitoring policy less aggressive why would you always not keep it at its most aggressive because then people are just going to get fatigued from it yes when they get annoyed you want them yeah you they want you want the experience to be pleasant obviously i want the experience to be pleasant but even just from a straight up safety perspective if you alert people when they look around and they're like why is this thing alerting me there's nothing i could possibly hit right now people will just learn to tune it out people will just learn to tune it out to put weights on the steering wheel to do whatever to overcome it and remember that you're always part of this adaptive system so all i can really say about you know how this scale is going forward is yeah something we have to monitor for we don't know this is a great psychology experiment at scale like we'll see yeah it's fascinating track it and making sure you have a good understanding of attention is a very key part of that psychology problem yeah i think i mean you and i probably have a different come to it differently but to me it's an it's a fascinating psychology problem to explore something much deeper than just driving it's a it's such a nice way to explore human attention and human behavior which is why again we've probably both criticized mr elon musk on this one topic from different avenues uh so both offline and online i had little chats with elon and like i love human beings as a as a as a computer vision problem as an ai problem it's fascinating he wasn't so much interested in that problem it's like in order to solve driving the whole point is you want to remove the human from the picture and it seems like you can't do that quite yet eventually yes but you can't quite do that yet so this is the moment where and you can't yet say i told you so uh to tesla but it's getting there because i don't know if you've seen this there's some reporting that they're in fact starting to do drive them off yeah they ship the model in shadow mode uh without uh i believe only a visible light camera it might even be fisheye uh it's like a low resolution low resolution visible light i mean to be fair that's what we have in the eon as well our last generation product this is the one area where i can say our hardware's ahead of tesla the rest of our hardware way way behind but our driver monitoring camera do you think uh i think on the third row tesla podcast or somewhere else i've heard you say that obviously eventually they're gonna have driver monitoring i think what i've said is elon will definitely ship driver monitoring before he ships level five the beautiful level and i'm willing to about 10 grand on that and you better ground on that uh i mean now i want to take the bet but before maybe someone would have i should have got my money yeah that's an interesting bet i think i i think you're right i'm actually on a human level because he's been he's made the decision like he said that driver monitoring is the wrong way to go but like you have to think of as a human as a ceo i think that's the right thing to say when like sometimes you have to say things publicly they're different than when you actually believe because when you're producing a large number of vehicles and the decision was made not to include the camera like what are you supposed to say yeah like our cars don't have the thing that i think is right to have uh it's an interesting thing but like on the other side as a ceo i mean something you could probably speak to as a leader i think about me as a human to publicly change your mind on something how hard is that well especially when like george haas say i told you so all i will say is i am not a leader and i am happy to change my mind um and i think elon will yeah i do i think he'll come up with a good way to make it psychologically okay for him well it's such an important thing man especially for a first principles thinker because he made a decision that uh driver monitoring is not the right way to go and i could see that decision and i i could even make that decision like i was on the fence too like i'm not driving monitoring is such an obvious simple solution to the problem of attention it's not obvious to me that just by putting a camera there you solve things you have to create an incredible compelling experience just like you're you're talking about and i don't know if it's easy to do that it's not at all easy to do that in fact i think so as a creator of a car that's trying to create a product that people love which is what tesla tries to do right it's not obvious to me that uh you know as a design decision whether adding a camera is a good idea from a safety perspective either like in the human factors community everybody says that like you should obviously have driver sensing driving monitoring but like that that's like saying it's obvious as parents you shouldn't let your kids go out at night but okay but like they're still gonna find ways to do drugs yeah you have to also be good parents so like it's it's much more complicated than just like you need to have drive and monitoring i totally disagree on okay if you have a camera there and the camera's watching the person but never throws an alert they'll never think about it right the the driver monitoring policy that you choose to how you choose to communicate with the user is entirely separate from the data collection perspective right right so you know like there's one thing to say like you know tell your teenager they can't do something there's another thing to like you know gather the data so you can make informed decisions that's really interesting but you have to make that that's the interesting thing about cars uh but even true with com ai like you don't have to manufacture the thing into the car is you have to make a decision that anticipates the right strategy long term so like you have to start collecting the data and start making decisions starter date started it three years ago i believe that we have the best driver monitoring solution in the world um i think that when you compare it to well supercruise is the only other one that i really know that shipped and ours is better what uh what do you like and not like about super coos um i mean i had a few super crews uh the sun would be shining through the window would blind the camera and it would say i wasn't paying attention when i was looking completely straight i couldn't reset the attention with a steering wheel touch and supercrews would disengage like i was communicating to the car i'm like look i'm here i'm paying attention why are you really gonna force me to disengage and it did um so it's it's a constant conversation with the user and yeah there's no way to ship a system like this if you can ota right we're shipping a new one every month sometimes we we balance it with our users on discord like when sometimes we make the driver monitoring a little more aggressive and people complain sometimes they don't you know we want it to be as aggressive as possible where people don't complain it doesn't feel intrusive so being able to update the system over the air is an essential component i mean that's probably to me you mentioned uh i mean to me that is the biggest innovation of tesla that it it made it people realize that over-the-air updates is essential yeah i mean yeah was that not obvious from the iphone the iphone was the first real product that ota'ed i think was it actually that's that's brilliant you're right i mean the game consoles used to not right the game consoles are maybe the second thing that did well i didn't really think about one of the amazing features of a smartphone isn't just like the touchscreen isn't the thing it's the ability to constantly update yeah get better it gets better i love my ios 14. uh one thing that i probably disagree with you on on driving monitoring is you've said that it's easy like i mean you you tend to say stuff is easy the uh i guess you said it's easy relative to the external perception problem can you elaborate why you think it's easy feature engineering works for driver monitoring feature engineering does not work for the external so human faces are not human faces and the movement of human faces and head and body is not as variable as the external environment is your intuition um yes and there's another big difference as well um your reliability of a driver monitoring system doesn't actually need to be that high the uncertainty if you have something that's detecting whether the human is paying attention it only works 92 of the time you're still getting almost all the benefit of that because the human like you're training the human yeah right you're you're dealing with a system that's really helping you out it's a conversation it's not like the external thing where guess what if you swerve into a tree you swerve into a tree right like you get no margin for error yeah i think that's really well put i i i think that's the right exactly the place where um where comparing to the external perception the control problem driver monitoring is easier because you know the bar for success is much lower yeah but i i still think like the human face is more complicated actually than the external environment but for driving you don't give a damn i don't need you i don't need something i don't need something that complicated to to to have to communicate the idea to the human that i want to communicate which is yo system might mess up here you got to pay attention yeah see that's that's my love and fascination is the the human face and it feels like this is a nice place to um create products that create an experience in the car so like it feels like there should be more richer experiences in the car you know like that's an opportunity for like something like my eye or just any kind of system like a tesla or any of the autonomous vehicle companies is because software's and there's much more sensors and so much is running on software and you're doing machine learning anyway there's an opportunity to create totally new experiences that we're not even anticipating you don't think so no you think it's a box that gets you from a to b and you want to do it chill yeah i mean i think as soon as we get to level three on highways okay enjoy your candy crush enjoy your hulu enjoy your you know whatever whatever sure you get this you can look at screens basically versus right now what do you have music and audio books so level three is where you can kind of disengage in in stretches of time [Music] [Applause] well you think level three is possible like on the highway going for 100 miles and you can just go to sleep oh yeah uh sleep so again i think it's really all on a spectrum i think that being able to use your phone while you're on the highway and like this all being okay and being aware that the car might alert you and you have five seconds to basically so the five second thing that you think is possible yeah i think it is oh yeah not not in all scenarios right some scenarios it's not it's the whole risk thing that you mentioned is nice is to be able to estimate like how risky is this situation exactly that's really important to understand one other thing you mentioned comparing comma and autopilot is that um something about the haptic feel of the way combo controls the car when things are uncertain like it behaves a little bit more uncertain when things are uncertain that's kind of an interesting point and then autopilot is much more confident always even when it's uncertain until it runs into trouble yeah that's that's a funny thing i actually mentioned that to elon i think and then the first time we talked he wasn't biting is like communicating uncertainty i guess comet doesn't really communicate uncertainty explicitly communicates it through haptic feel like what what's the role of communicating uncertainty do you think oh we do some stuff explicitly like we do detect the lanes when you're on the highway and we'll show you how many lanes we're using to drive with you can look at where it thinks the lanes are you can look at um the path and yeah we want to be better about this we're actually hiring i want to hire some new ui people ui people you mentioned this because it's such an it's a ui problem too right it's we're we have a great designer now but you know we need people who are just gonna like build this and debug these uis qt people and okay is that what the ui has done with this key we're moving the new ui is in qt c plus plus qt uses it yeah we had some react stuff in there react js would just react react is his own language right react native reaction react to the javascript framework yeah it's all it's all based on javascript but it's you know i like c plus plus what do you think about uh dojo with tesla and their foray into what appears to be specialized hardware for uh training neonets i guess it's something maybe you can correct me from my shallow looking at it it seems like something like google did with tpus but specialized for uh driving data i don't think it's specialized for driving data it's just legit just tpu they want to inter go the apple way basically everything required in the chain is done in-house well so you have a problem right now and this is one of my one of my concerns i really would like to see somebody deal with this if anyone out there is doing it i'd like to help them if i can um you basically have two options right now to train your options are nvidia or google so google is not even an option their tpus are only available in google cloud google has absolutely onerous terms of service restrictions uh they may have changed it but back in google's terms of service it said explicitly you are not allowed to use google cloud ml for training autonomous vehicles or for doing anything that competes with google without google's prior written permission well okay i mean google is not a platform company uh i wouldn't i wouldn't touch tpus with a 10-foot pole so that leaves you with the monopoly uh nvidia and video so i mean that you're not a fan of well look i was a huge fan of in 2016 nvidia jensen came sat in the car um cool guy when the stock was 30 a share uh nvidia stock has skyrocketed i witnessed a real change in who was in management over there in like 2018 and now they are let's exploit let's take every dollar we possibly can out of this ecosystem let's charge ten thousand dollars for a100s because we know we got the best in the game and let's charge ten thousand dollars for an a100 when it's really not that different from 3080 which is 699. um the margins that they are making off of those high-end chips are so high that i mean i think they're shooting themselves in the foot just from a business perspective because there's a lot of people talking like me now who are like somebody's got taken video down yeah where they could dominate it nvidia could be the new intel yeah to be in inside everything essentially and and yet the winners in in certain spaces like autonomous driving the winners only the people who are like desperately falling back and trying to catch up and have a ton of money like the big automakers are the ones interested in partnering with nvidia oh and then i think a lot of those things are going to fall through if i were nvidia sell chips sell chips at a reasonable markup to everybody to everybody without any restrictions without any restrictions intel did this look at intel they had a great long run nvidia is trying to turn their they're like trying to productize their chips way too much they're trying to extract way more value than they can sustainably sure you can do it tomorrow is it going to up your share price sure if you're one of those ceos like how much can i strip mine this company and you know and that's what's weird about it too like the ceo is the founder it's the same guy yeah i mean i still think jensen's a great guy that's great why do this you have a choice you have a choice right now are you trying to cash out are you trying to buy a yacht if you are fine but if you're trying to be the next huge semiconductor company sell chips well the the interesting thing about jensen is he is a big vision guy so he has a plan like for 50 years down the road so it makes me wonder like how does price gouging fit into it yeah how does that like it's it doesn't seem to make sense to plan i worry that he's listening to the wrong people yeah that that's the sense i have too sometimes because i despite everything i think nvidia is an incredible company well one sort of i'm deeply grateful to nvidia for the products they've created me to pass right and so the 1080 ti was a great gpu still have a lot of them it was yeah but at the same time it just feels like feels like you don't want to put all your stock in nvidia and so like elon is doing um what tesla is doing with autopilot and dojo is the apple way is because they're not going to share dojo with uh george hotz uh i i know they should sell that chip oh they should sell their even their their accelerator the accelerator that's in all the cars the 30 watt one sell it why not so open it up make me why does this have to be a car company well if you sell the chip here's what you get yeah make some money off the chips it doesn't take away from your chip you're going to make some money free money and also the world is going to build an ecosystem of tooling for you right you're not going to have to fix the bug in your tanh layer someone else already did well the question that's an interesting question i mean that's the question steve jobs asked that's the question elon musk is uh perhaps asking is uh do you want tesla stuff inside other vehicles in inside potentially inside like uh irobot vacuum cleaner yeah i think you should decide where your advantages are i'm not saying tesla should start selling battery packs to automakers because battery packs to automakers they are straight up in competition with you if i were tesla i'd keep the battery technology totally yeah ssr's we make batteries but the thing about the tesla tpu um is anybody can build that it's just a question of you know are you willing to spend the you know the money it could be a huge source of revenue potentially are you willing to spend 100 million dollars right anyone can build it and someone will and a bunch of companies now are starting trying to build ai accelerators somebody's going to get the idea right and yeah hopefully they don't get greedy because they'll just lose to the next guy who finally and then eventually the chinese are going to make knock off and video chips and that's from your perspective i don't know if you're also paying attention to stan tesla for a moment all dave elon musk has talked about a complete rewrite of uh the neural net that they're using that seems to again i'm half paying attention but it seems to involve basically a kind of integration of all the sensors to where it's a four dimensional view you know you have a 3d model of the world over time and then you can i think it's done both for the for actually you know so the neural network is able to in a more holistic way deal with the world and make predictions and so on but also to make the annotation task more uh you know easier like you can annotate the world in one place and then kind of distribute itself across the sensors and across a different like the hundreds of tasks that are involved in the hydronet what are your thoughts about this rewrite is it just like some details that are kind of obvious there are steps that should be taken or is there something fundamental that could challenge your idea that end to end is the right solution uh we're in the middle of a bakery right now as well we haven't shipped a new model in a bit of what kind uh we're going from 2d to 3d right now all our stuff like for example when the car pitches back the lane lines also pitch back uh because we're assuming the flat ro flat world hypothesis uh the new models do not do this the new models output everything in 3d um so this but there's still no annotation so the 3d is it's more about the opposite yeah uh we have we have disease and everything uh we've disease yeah we had a disease we had a disease um we unified a lot of stuff as well uh we switched from tensorflow to pi torch yes uh my understanding of what tesla's thing is is that their annotator now annotates across the time dimension uh i mean cute why are you building an annotator i i find their entire pipeline i find your vision i mean the vision event to end very compelling but i also like the engineering of the data engine that they've created in terms of supervised learning pipelines that thing is damn impressive you're basically the the idea is that you have hundreds of thousands of people that are doing data collection for you by doing their experience so that's kind of similar to the common ai model and you're able to mine that data based on the kind of edge cases you need i i think it's harder to do in the end to end learning the mining of the right edge cases like that's where feature engineering is actually really powerful because like us humans are able to do this kind of mining a little better but but yeah there's obvious as we as we know there's obvious constraints and limitations to that idea uh carpathi just tweeted he's like um you get really interesting insights if you saw if you sort your validation set by loss and look at the highest loss examples yeah uh so yeah i mean you can do we we have we have a little data engine like thing we're training a segment uh it's not fancy it's just like okay train the new segment run it on 100 000 images and now take the thousand with highest loss select 100 of those by human put those get those ones labeled retrain do it again right so it's a much less well-written data engine and yeah you can you can take these things really far and it is impressive engineering and if you truly need supervised data for a problem yeah things like data engine are the high end of the what is attention is a human paying attention i mean we're going to probably build something that looks like data engine to push our driver monitoring further um but for driving itself you have it all annotated beautifully by what the human does so yeah that's interesting i mean that applies to driver attention as well do you want to detect the eyes do you want to detect blinking and pupil movement do you want to detect all the like face alignments the landmark detection and so on and then doing kind of reasoning based on that or do you want to take the entirety of the face over time and do and i mean it's obvious that over eventually you have to do end to end with some calibration with some fixes and so on but it's uh like i don't know when that's the right move even if it's end to end there actually is there is no kind of um you have to supervise that with humans whether a human is paying attention or not is a completely subjective judgment um like you can try to like automatically do it with some stuff but you don't have if i record a video of a human i don't have true annotations anywhere in that video the only way to get them is with you know other humans labeling it really well i don't know uh you you so if you think deeply about it you could you might be able to just depending on the task maybe you'll discover self-annotating things like you know you can look at like steering wheel reversal or something like that you can discover little moments of lapse of attention yeah i mean that's that's where psychology comes in is there indicate because you have so so much data to look at so you might be able to find moments when there's like just inattention that even with smartphone if you want to detect smartphone use yeah you can start to zoom in i mean that's the gold mine sort of the comma ai i mean tesla's doing this too right is there they're doing annotation based on it's like uh self-supervised learning too it's just a small part of the entire picture it's that's kind of the challenge of solving a problem in machine learning if you can discover self-annotating parts of the problem right our driver monitoring team is half a person right now i have a problem you know once we have skill to full once we have two people once we have two three people on that team i definitely want to look at self-annotating stuff or yeah for attention let's go back for a sec to uh to a comma and how what you know for people who are curious to try it out how do you install a comma in say a 2020 toyota corolla or like what are the cars that are supported what are the cars that you recommend and what does it take you have a few videos out but maybe through words can you explain what's it take to actually install a thing so we support uh i think it's 91 cars 91 makes models um we get to 100 this year nice the yeah the 2020 corolla great choice the um 2020 sonata uh it's using the stock longitudinal it's using just our lateral control but it's a very refined car their longitudinal control is not bad at all um so yeah corolla sonata or if you're willing to get your hands a little dirty and look in the right places on the internet the honda civic is great uh but you're going to have to install a modified eps firmware in order to get a little bit more torque and i can't help you with that comma does not officially endorse that um but we have been doing it we didn't ever release it uh we waited for someone else to discover it and then you know and you have a discord server where people there's a very active developer community yeah as opposed to so depending on the level of experimentation you're willing to to do that's the community if you if you just want to buy it and you have a supported car yeah it's 10 minutes to install there's youtube videos it's ikea furniture level if you can set up a table from ikea you can install a comma 2 in your supported car and it will just work now you're like oh but i want this high-end feature or i want to fix this bug okay well welcome to the developer community uh so what if i wanted to this is something i asked you offline or like a few months ago if i wanted to run my own code to um so use comma as a platform and try to run something like open pilot what does it take to do that um so there's a toggle in the settings called enable ssh and if you toggle that you can ssh into your device you can modify the code you can upload whatever code you want to it um there's a whole lot of people so about 60 of people are running stock comma about 40 percent of people are running forks and there's a community of there's a bunch of people who maintain these forks and these forks support different cars or they have you know uh different toggles we try to keep away from the toggles that are like disabled driver monitoring but you know there's some people might want that kind of thing and like you know yeah you can it's your car it's your i'm not here to tell you you know uh we we have some you know we ban if you're trying to subvert safety features you're banned from our discord i don't want anything to do with you but there's some forks doing that you got it so you encourage responsible uh forking yeah yeah some people you know yeah some people uh like like there's forks that will do um some people just like having a lot of uh readouts on the ui like a lot of like flashing numbers so there's forks that do that uh some people don't like the fact that it disengages when you press the gas pedal there's forks that disable that got it now the the stock experience is is what like so it does both lane keeping and longitudinal control all together so it's not separate like it is an autopilot no so okay um some cars we use the stock longitudinal control we don't do the longitudinal control on all the cars uh some cars the acc's are pretty good in the cars it's the lane keep that's atrocious in anything except for autopilot super cruise but you know you just turn it on and it it works what does this engagement look like yeah so we have i mean i'm very concerned about mode confusion i've experienced it on supercruise and and autopilot where like autopilot like autopilot disengages i don't realize that the acc is still on the lead car moves slightly over and then the tesla accelerates to like whatever my set speed is super fast and like what's going on here um we have engaged and disengaged and this is similar to my understanding i'm not a pilot but my understanding is either the pilot is in control or the co-pilot is in control and we have the same kind of transition system either open pilot is engaged or open pilot is disengaged engage with cruise control disengage with either gas break or cancel let's talk about money what's uh the business strategy for comma profitable well it's you're good so congratulations yeah uh what uh so basically selling so we should say combo cost uh a thousand bucks comment 200 for the interface to the car as well it's 1200 all said done nobody's usually up front like this yeah you got it you got to have the tac on right yeah i love it this side i'm not going to lie to you trust me it will add 1200 value to your life yes it's still super cheap 30 days no questions asked money back guarantee and prices are only going up you know if there ever is future hardware it could cost a lot more than twelve hundred dollars so comma three is in the works so it could be all i will say is future hardware is going to cost a lot more than the current hardware yeah like i mean the people that use uh the people i've spoken with that use comma use open pilot they first of all they use it a lot so people that use it they they fall in love with oh our retention rate is insane this is a good sign yeah it's a really good sign um 70 of comma 2 buyers are daily active users yeah it's amazing um oh also we don't plan on stopping selling the comma too like like it's you know so whatever you create that's beyond comma two it would be uh it would be potentially a phase shift like it's you it's so much better that like you could use comma two and you can use comma depends what you want it's three point four one kind of 42 yeah you know autopilot hardware one versus hardware two yeah the comma two is kind of like hardware one got it got it got it got it i think i heard you talk about retention rate with the vr headsets that the average is just once yeah which is fast i mean it's such a fascinating way to think about technology and this is a really really good sign and the other thing that people say about comm is like they can't believe they're getting this for a thousand bucks right it's it seems it seems like a some kind of steal so but in terms of like long-term business strategies it basically to put so it's currently in like a thousand plus cars 1200 more uh so yeah dailies is about uh dailies is about 2 000 weekly is about 2 500. monthlies is over 3 000. wow we've grown a lot since we've stopped is the goal like can we talk crazy for a second i mean what's the goal to overtake tesla let's talk okay so i mean android did overtake ios yeah that's exactly it right so yeah they did it i actually don't know the timeline of that one they but let let's talk uh because everything is in alpha now the autopilot you could argue is in alpha in terms of towards the big mission of autonomous driving right and so what yes your goal to overtake into millions of cars essentially of course where would it stop like it's open source software it might not be millions of cars with a piece of comma hardware but yeah i think open pilot at some point will cross over autopilot in in users just like android crossed over ios how does google make money from android uh it's it's complicated their own devices make money google google makes money by just kind of having you on the internet uh yes google search is built in gmail is built in android is just a shill for the rest of google's ecosystem yeah but the problem is android is not is a brilliant thing i mean android arguably changed the world so there you go that's you can you can feel good ethically speaking but as a business strategy it's questionable i'll sell hardware so hardware i mean it took google a long time to come around to it but they are now making money on the pixel you're not about money you're more about winning yeah of course but if only if only 10 percent of open pilot devices come from comma ai we still make a lot that is still yes that is a ton of money for our company but can't somebody create a better comma using open pilot or you're basically saying well i'll compete well i'll compete is can you create a better android phone than the google pixel right i mean you can but like i love that so you're confident like you know what the hell you're doing yeah it's it's uh confidence in merit i mean our money yeah our money comes from we're a consumer electronics company yeah and put it this way so we sold we sold like three thousand company's um i'm 2500 right now uh and like okay we're probably going to sell 10 000 units next year right 10 000 units even just a thousand dollars a unit okay we're 10 million in uh in in in in revenue um get that up to a hundred thousand maybe double the price of the unit now we're talking like 200 million in revenue yeah actually making money uh one of the rare semi-autonomous or autonomous vehicle companies that are actually making money yeah yeah you know if you have if you look at a model when we were just talking about this yesterday if you look at a model and like you're testing like you're a b testing your model and if you're you're you're one branch of the a b test the losses go down very fast in the first five epochs yeah that model is probably going to converge to something considerably better than the one where the losses are going down slower why do people think this is going to stop why do people think one day there's going to be a great like well waymo's eventually going to surpass you guys no they're not you see like a world where like a tesla or a car like a tesla would be able to basically press a button and you like switch to open pilot you know you know they load in i don't know so i think so first off i think that we may surpass tesla in terms of users uh i do not think we're gonna surpass tesla ever in terms of revenue i think tesla can capture a lot more revenue per user than we can um but this mimics the android ios model exactly there may be more android devices but you know there's a lot more iphones than google pixels so i think there'll be a lot more tesla cars sold than pieces of comma hardware um and then as far as a tesla owner being able to switch to open pilot uh does ios does iphones run android no but you can if you really want to do it but it doesn't really make sense like it's not it doesn't make sense who cares what about if uh a large company like automakers 4g m toyota came to george hotz or on the tech space amazon facebook google came with a large pile of cash would would you consider being purchased do you see that as a one possible not seriously now um i would probably uh see how much uh they'll entertain for me um and if they're willing to like jump through a bunch of my hoops then maybe but like no not the way that m a works today i mean we've been approached and i laugh in these people's faces i'm like are you kidding me yeah you know because you're so it's so it's so demeaning the m a people are so demeaning to companies they treat the startup world as their innovation ecosystem and they think that i'm cool with going along with that so i can have some of their scam fake fed dollars you know fedcoin i don't what am i gonna do with more fedcoin you know i had coin fat coin man i love that so that's the cool thing about podcasting actually is uh people criticize i don't know if you're familiar with the spotify uh giving joe rogan a hundred million and something about that and you know they respect despite all the that people are talking about spotify people understand that podcasters like joe rogan know what the hell they're doing yeah so they give them money and say just do what you do and like the equivalent for you would be like george do what the hell you do because you're good at it try not to murder too many people like try like there's some kind of common sense things like just don't go on a weird rampage of yeah it comes down to what companies i could respect right um you know could i respect gm never um no i couldn't i mean could i respect like a hyundai more so right that's that's a lot closer toyota what's your nah nah it's korean is the way i think i think that you know the japanese the germans the us they're all too they're all too you know they all think they're too great what about the tech companies apple apple is of the tech companies that i could respect apple's the closest yeah i mean i could never subscribe it would be ironic oh if uh if common ai is acquired by apple i mean facebook look i quit facebook 10 years ago because i didn't respect the business model um google has declined so fast in the last five years what are your thoughts about waymo as present and future so let me let me see let me start by saying something uh nice which is uh i've visited them a few times and i've [Music] have ridden in their cars and the engineering that they're doing both the research and the actual development and the engineering they're doing and the scale they're actually achieving by doing it all themselves is really impressive and the the balance of safety and innovation and like the cars work really well for the routes they drive like they drive fast which was very surprising to me like it drives like the speed limit or faster the speed limit it goes and it works really damn well and the interface is nice and chandler arizona yeah yeah yeah in challengers in a very specific environment so it i you know it gives me enough material in my mind to push back against the madman of the world like george hotz to be like like because you kind of imply there's zero probability they're going to win yeah and and after i've used after i've written in it to me it's not zero oh it's not for technology reasons bureaucracy no it's worse than that it's actually for product reasons i think oh you think they're just not capable of creating an amazing product uh no i think that the product that they're building doesn't make sense um so a few things uh you say the weimos are fast um benchmark away mo against a competent uber driver right right the uber driver is faster it's not even about speed it's the thing you said it's about the experience of being stuck at a stop sign because pedestrians are crossing non-stop i like when my uber driver doesn't come to a full stop at the stop sign yeah you know and so let's say the waymo's are 20 slower than than an uber right um you can argue they're going to be cheaper and i argue that users already have the choice to trade off money for speed it's called uberpool um i think it's like 15 of rides or uber pools right users are not willing to trade off money for speed so the whole product that they're building is not going to be competitive with traditional ride sharing networks right um like and also whether there's profit to be made depends entirely on one company having a monopoly i think that the level for autonomous ride sharing vehicles market is going to look a lot like the scooter market if even the technology does come to exist which i question who's doing well in that market yeah it's a race to the bottom you know well they could be it could be closer like an uber and a lyft where it's just a one or two players well the scooter people have given up trying to market scooters as a practical means of transportation and they're just like they're super fun to ride look at wheels i love those things and they're great on that front yeah but from an actual transportation product perspective i do not think scooters are viable and i do not think level 4 autonomous cars are viable if you uh let's play a fun experiment if you ran let's do a tesla and let's do waymo if uh elon musk took a vacation for a year he just said screw it i'm gonna go live on an island no electronics and the board decides that we need to find somebody to run the company and they they decide that you should run the company for a year how do you run tesla differently i wouldn't change much do you think they're on the right track i wouldn't change i mean i'd have some minor changes but even even my debate with tesla about you know end to end versus segnets like that's just software who cares right like it's not gonna it's not like you're doing something terrible with segnats you're probably building something that's at least going to help you debug the end-to-end system a lot right it's very easy to transition from what they have to like an end-to-end kind of thing and then i presume you would uh in the model y or maybe in the model 3 start adding driver sensing with infrared yes i would add i would i would add infrared camera infrared lights right away to those cars um and start collecting that data and do all that kind of stuff yeah very much i think they're already kind of doing it it's it's an incredibly minor change if i actually were ceo of tesla first off i'd be horrified that i wouldn't be able to do a good job as elon and then i would try to you know understand the way he's done things before he would also have to take over his twitter so god i don't tweet yeah what's your twitter situation why why why are you so quiet on twitter comma is like what what's your social network presence like because you you on instagram you're you're you uh you do live streams you're you're you're um you understand the music of the internet but you don't always fully engage into it you're part-time i used to have a twitter yeah i mean it's the pr instagram is a pretty place instagram is a beautiful place it glorifies beauty i like i like instagram's values as a network um twitter glorifies conflict glorifies you know like like like like like you know just shots taking shots at people and it's like you know well you know twitter and donald trump are perfectly they're perfect for each other so tesla's on uh tesla's on the right track in your view yeah okay so let's try let's like really try this experiment if you ran way more let's say they're i don't know if you agree but they seem to be at the head of the pack of the kind of uh what would you call that approach like it's not necessarily lighter based because it's not about lighter but before robot taxi level four robot taxi all in before any before making your revenue uh so they're probably at the head of the pack if you were said hey george can you please run this company for a year how would you change it uh i would go i would get anthony levandowski out of jail and i would put him in charge of the company um let's try to break that apart why do you do you want to make do you want to destroy the company by doing that or do you mean or do you mean uh you like renegade style thinking that uh pushes that that like throws away bureaucracy and goes to first principle thinking what what do you mean by that um i think anthony lewandowski is a genius and i think he would come up with a much better idea of what to do with waymo than me so you mean that unironically he is a genius oh yes oh absolutely without a doubt i mean i'm not saying there's no shortcomings but in the interactions i've had with him yeah what um he's also willing to take like who knows what he would do with waymo i mean he's also out there like far more out there than i am yeah there's big risks yeah what do you make of him i was i was going to talk to him in this podcast and i was going back and forth i'm i'm such a gullible naive human like i see the best in people and i slowly started to realize that there might be some people out there that like have multiple faces to the world they're like deceiving and dishonest i still refuse to like i i just i trust people and i don't care if i get hurt by it but like you know sometimes you have to be a little bit careful especially platform wise and podcast wise what do you what am i supposed to think so you think you think he's a good person oh i don't know i don't really make moral judgments and it's difficult to oh oh i mean this about the waymo actually i mean that whole idea very non-ironically about what i would do the problem with putting me in charge of waymo is waymo is already 10 billion dollars in the hull right whatever idea waymo does look com is profitable comes raised 8.1 million dollars that's small you know that's small money like i can build a reasonable consumer electronics company and succeed wildly at that and still never be able to pay back weight most 10 billion so i i think the basic idea with women well forget the 10 billion because they have some backing but your basic thing is like what can we do to stop making some money well no i mean my bigger idea is like whatever the idea is that's going to save waymo i don't have it it's going to have to be a big risk idea and i cannot think of a better person than anthony lewandowski to do it so that is completely what i would do as ceo of waymo i call myself a transitionary ceo do everything i can to fix that situation yeah uh yeah cause i can't i can't do it right like i can't i can't oh i mean i can talk about how what i really want to do is just apologize for all those corny uh you know ad campaigns and be like here's the real state of the technology yeah um like i have several criticism i'm a little bit more bullish on waymo than than you seem to be but one criticism i have is it went into corny mode too early like it's still a startup it hasn't delivered on anything so it should be like more renegade and show off the engineering that they're doing which just can be impressive as opposed to doing these weird commercials of like your friendly yeah your friendly car company i mean that's my biggest my biggest snipe at waymo was always that guy's a paid actor that guy's not a waymo user he's a paid actor look here i found his call sheet do kind of like what spacex is doing with uh the rocket launchers just get put the nerds up front put the engineers up front and just like show failures too just i love i love spacex's yeah yeah the thing they're doing is right and it just feels like the right but we're all so excited to see them succeed yeah i can't wait to see when it won't fail you know like you lie to me i want you to fail you tell me the truth you'll be honest with me i want you to succeed yeah uh yeah and that requires the uh the renegade ceo right i'm with you i'm with you i still have a little bit of faith in waymo to for for the renegade ceo to step forward but it's not it's not john krafter yeah it's uh you can't it's not chris holmstone and those people may be very good at certain things yeah but they're not renegades because these companies are fundamentally even though we're talking about billion dollars all these crazy numbers they're still like early stage startups i mean i i just i if you are pre-revenue and you've raised 10 billion dollars i have no idea like like this just doesn't work no it's against everything silicon valley where's your minimum viable product you know where's your users what's your growth numbers this is traditional silicon valley why do you not apply it to what you think you're too big to fail already like how do you think autonomous driving will change society so the mission is for comma to uh solve self-driving do you have like a vision of the world of how it'll be different is it as simple as a to b transportation or is there like because these are robots it's not about autonomous driving in and of itself it's what the technology enables it's i think it's the coolest applied ai problem i like it because it has a clear path to monetary value um but as far as that being the thing that changes the world i mean no like like there's cute things we're doing in common like who thought you could stick a phone on the windshield middle drive um but like really the product that you're building is not something that people were not capable of imagining 50 years ago so no it doesn't change the world in that front could people imagine the internet 50 years ago only true junior genius visionaries yeah everyone could have imagined autonomous cars 50 years ago it's like a core but i don't drive it see i i have this sense and i told you like i'm my long-term dream is robots with which you have deep with whom you have deep connections right and there's different trajectories towards that and i've been thinking so i've been thinking of launching a startup i see autonomous vehicles as a potential trajectory to that that i'm that's not where the direction i would like to go but i also see tesla or even kamehameha like pivoting into into robotics broadly defined that's at some stage in the way like you're mentioning the internet didn't expect let's solve you know when i say a comma about this we could talk about this but let's solve self-driving cars first got to stay focused on the mission don't don't don't you're not too big to fail for however much i think kama's winning like no no no you're winning when you solve level five self-driving cars and until then you haven't win and one and you know again you want to be arrogant in the face of other people great you want to be arrogant in the face of nature you're an idiot right stay mission focused brilliantly put uh like i mentioned thinking of launching a startup i've been considering actually before cove i've been thinking of moving to san francisco oh oh i wouldn't go there so why is uh okay well and now i'm thinking about potentially austin um and we're in san diego now san diego come here so why what um i mean you're such an interesting human you've launched so many successful things what uh why san diego what do you recommend why not san francisco have you thought so for in your case san diego with qualcomm and snapdragon i mean that's an amazing combination but that wasn't really why that wasn't the why no i mean qualcomm was an afterthought qualcomm was it was a nice thing to think about it's like you can have a tech company here and a good one i mean you know i like qualcomm but no um what's the west san diego better than stephanie why does san francisco suck well so okay so first off we all kind of said like we want to stay in california people like the ocean you know california for for its flaws it's like a lot of the flaws of california are not necessarily california as a whole and they're much more san francisco specific yeah um san francisco so i think first year cities in general have stopped wanting growth uh well you have like in san francisco you know the voting class always votes to not build more houses because they own all the houses and they're like well you know once people have figured out how to vote themselves more money they're going to do it it is so insanely corrupt um it is not balanced at all like political party-wise you know it's it's a one-party city and for all the discussion of diversity it's has it's stops lacking real diversity of thought of background of uh approaches to strategies of yeah ideas it's it's kind of a strange place that it's the loudest people about diversity and the biggest lack of diversity well i mean that's that's what they say right it's the projection projection yeah yeah it's interesting and even people in silicon valley tell me that's uh like high up people but everybody is like this is a terrible place it doesn't make i mean and coronavirus is really what killed it yeah san francisco was the number one uh exodus during coronavirus we still think san diego is a good place to be yeah yeah i mean we'll see we'll see what happens with california a bit longer term yeah i like austrians and austin's an interesting choice i wouldn't i wouldn't i don't have really anything bad to say about austin either except for the extreme heat in the summer um which you know but that's like very on the surface right i think as far as like an ecosystem goes it's it's cool i personally love colorado colorado uh yeah i mean you have these states that are you know like just way better run um california is you know it's especially san francisco so it's high horse and like yeah can i ask you for advice to me and to others about what's it take to build a successful startup oh i don't know i haven't done that talk to someone who did that well you know uh this is like another book of years that i'll buy for 67 i suppose uh so there's um one of these days will sell out yeah that's right jail breaks are going to be a dollar and books are going to be 67. how i uh how i joe broke the iphone by george cotts that's right how i jailbroke the iphone and you can do it that's right that's right oh god okay i can't wait but quite so you haven't introspected you have built a very unique company i mean not not you but you and others but i don't know um there's no there's nothing you have an interest but you haven't really sat down and thought about like well like if you and i we're having a bunch of we're having some beers and you're seeing that i'm depressed and whatever i'm struggling there's no advice you can give oh i mean more beer more beer yeah i think it's all very like situation dependent um here's okay if i can give a generic piece of advice it's the technology always wins the better technology always wins and lying always loses build technology and don't lie i'm with you i agree very much the long run long run sure it's the long run you know what the market can remain irrational longer than you can remain solvent true fact well this is this is an interesting point because i ethically and just as a human believe that um like sm like hype and smoke and mirrors is not at any stage of the company is a good strategy i mean there's some like you know pr magic kind of like you know you want a new product yeah if there's a call to action if there's like a call to action like buy my new gpu look at it it takes up three slots and it's this big it's huge buy my g for you yeah that's great if you look at you know especially in that in the ai space broadly but autonomous vehicles like you can raise a huge amount of money on nothing and the question to me is like i'm against that i'll never be part of that i don't think i hope not willingly not but like is there something to be said to uh essentially lying to raise money like fake it till you make it kind of thing i mean this is billy mcfarland the fire festival like we all we all experienced uh you know what happens with that no no don't fake it till you make it be honest and hope you make it the whole way the technology wins right the technology wins and like there is i'm not i use like the anti-hype you know that's that's a slava kpss reference but um hype isn't necessarily bad i loved camping out for the iphones um you know and as long as the hype is backed by like substance as long as it's backed by something i can actually buy and like it's real then hype is great and it's a great feeling it's when the hype is backed by lies that it's a bad feeling i mean a lot of people call elon musk a fraud how could he be a fraud i've noticed this this kind of interesting effect which is he does tend to over promise and deliver what's what's the better way to phrase it promise a timeline that he doesn't deliver on he delivers much later on what do you think about that because i do that i think that's a programmer thing yeah i do that as well you think that's a really bad thing to do or is that okay i think that's again as long as like you're working toward it and you're gonna deliver on it it's not too far off right right like like you know the whole the whole autonomous vehicle thing it's like i mean i still think tesla's on track to beat us i still think even with their even with their missteps they have advantages we don't have um you know illness is better than me at at like marshaling massive amounts of resources so you know i still think given the fact they're maybe making some wrong decisions they'll end up winning and like it's fine to hype it if you're actually gonna win right if elon says look we're gonna be landing rockets back on earth in a year and it takes four like you know he landed a rocket back on earth and he was working toward it the whole time i think there's some amount of like i think when it becomes wrong is if you know you're not gonna meet that deadline if you're lying yeah that's brilliantly put like this is what people don't understand i think like elon believes everything he says he does as far as i can tell he does and i i detected that in myself too like if i it's only if you're like conscious of yourself lying yeah i think so yeah you know you can't take that to such an extreme right like in a way i think maybe billy mcfarland believed everything he said too right that's how you started cult and everybody uh kills themselves yeah yeah like it's you need you need if there's like some factor on it it's fine and you need some people to like you know keep you in check but like if you deliver on most of the things you say and just the timelines are off yeah it does piss people off though i wonder but who cares in the long arc of history the people everybody gets pissed off at the people who succeed which is one of the things that frustrates me about this world is uh they don't celebrate the success of others like there's so many people that want elon to fail it's so fascinating to me like what is wrong with you like so elon musk talks about like people short like they talk about financial yeah but i think it's much bigger than the financials i've seen like the human factors community they want they want other people to fail why why why like even people the harshest thing is like you know even people that like seem to really hate donald trump they want him to fail yeah or like the other president or they want barack obama to fail it's like we're almost involved it's weird but i i want that i would love to inspire that part of the world to change because well damn it if the human species is going to survive we should celebrate success like it seems like the efficient thing to do in this objective function that like we're all striving for is to celebrate the ones that like figure out how to like do better at that objective function as opposed to like dragging them down back into them into the mud i think there is this is the speech i always give about the commenters on hacker news um so first off something to remember about the internet in general is commenters are not representative of the population yeah i don't comment on anything i don't you know commenters are are representative of a certain sliver of the population and on hacker news a common thing i'll say is when you'll see something that's like you know promises to be wild out there and in innovative there is some amount of you know checking them back to earth but there's also some amount of if this thing succeeds well i'm 36 and i've worked at large tech companies my whole life they can't succeed because if they succeed that would mean that i could have done something different with my life but we know that i couldn't have we know that i couldn't have and and that's why they're going to fail and they have to root for them to fail to kind of maintain their world image so tune it out and they comment well it's hard i uh so one of the things one of the things i'm considering startup wise is to change that because i think the i think it's also a technology problem it's a platform problem i agree it's like because the thing you said most people don't comment i think most people want to comment they just don't because it's all the for commenting exactly i don't want to be grouped in with that or not you don't want to be in a at a party where everyone is an yeah so they but that's a platform problem that's i can't believe what reddit's become i can't believe the group think in reddit comments there's a red is an interesting one because they're subreddits and so you can still see especially small subreddits that like that are little like havens of like joy and positivity and like deep even disagreement but like nuanced discussion but it's only like small little pockets but that's uh that's emergent the platform's not helping that or hurting that so i guess naturally something about the internet uh if you don't put in a lot of effort to encourage nuance and positive good vibes it's naturally going to decline into chaos i would love to see someone do this well yeah um i think it's yeah very doable this is uh i think actually so i i feel like twitter could be overthrown joshua bach talked about how like uh if you have like and retweet like that's only positive wiring right the only way to do anything like negative there is um with a comment and that's like that asymmetry is what gives you know twitter its particular toxicness whereas i find youtube comments to be much better because youtube comments have a have a of an up and a down and they don't show the downloads without getting into depth of this particular discussion the point is to explore possibilities and get a lot of data on it because uh i mean i could disagree with what you just said it's it's uh the point is it's unclear it's a it hasn't been explored in a really rich way like the these questions of how to create platforms that encourage positivity yeah i think it's a it's a technology problem and i think we'll look back at twitter as it is now maybe it'll happen within twitter but most likely somebody overthrows them is we'll look back at twitter and say we can't believe we put up with this level of toxicity you need a different business model too any any social network that fundamentally has advertising as a business model this was in the social dilemma which i didn't watch but i liked it it's like you know there's always the you know you're the product you're not the uh but they had a nuanced take on it that i really liked and it said the product being sold is influence over you the product being sold is literally your you know influence on you like that can't be if that's your idea okay well you know guess what it cannot be toxic yeah maybe there's ways to spin it like with with uh giving a lot more control to the user and transparency to see what is happening to them as opposed to in the shadows as possible but that can't be the primary source of but the users aren't no one's going to use that it depends it depends it depends i think i think that the you're you're not going to you can't depend on self-awareness of the users it's a it's another it's a longer discussion because uh you can't depend on it but you can reward self-awareness like if for the ones who are willing to put in the work of self-awareness you can reward them and incentivize and perhaps be pleasantly surprised how many people are are willing to be self-aware on the internet like we are in real life like i'm putting a lot of effort with you right now being self-aware about if i say something stupid or mean sure i'll like look at your like body language like i'm putting in that effort it's costly for an introvert it's very costly but on the internet it like most people are like i don't care if if this hurts somebody i don't care if this uh is not interesting or if this is yeah the mean or whatever i think so much of the engagement today on the internet is so disingenuous too yeah you're not doing this out of a genuine this is what you think you're doing this just straight up to manipulate others whether you're in you just became an ad okay okay let's talk about a fun topic which is programming here's another book idea for you let me pitch uh what's your uh perfect programming setup so like this by george hotz so uh like what listen you're giving me give me a macbook air sitting in a corner of a hotel room and you know i'll still have so you really don't care you don't fetishize like multiple monitors keyboard uh those things are nice and i'm not going to say no to them but do they automatically unlock tons of productivity no not at all i have definitely been more productive on a macbook air in a corner of a hotel room what about ide so uh which operating system do you love what uh text editor do you use ide what um is there is there something that is like the perfect if you could just say the perfect productivity set up for george hawks doesn't matter it doesn't doesn't matter it really doesn't matter you know i guess i code most of the time in vim like literally i'm using an editor from the 70s you know you didn't make anything better okay vs code is nice for reading code there's a few things that are nice about it uh i think that they're you can build much better tools how like ida's xrefs work way better than vx vs codes why yeah actually that's a good question like why i i still use sorry emacs eat for most uh i've actually know i have to confess something dark cause i've never used bim yeah it's i think maybe i'm just afraid that my life has been a like a waste [Laughter] i'm so i'm not i'm not evangelical about emacs i i think this this is how i feel about tender flow versus pie torch yeah having just like we've switched everything to pie torch now put months into the switch i have felt like i've wasted years on tensorflow i can't believe it i can't believe how much better pie torch is yeah i've used emacs and them doesn't matter yeah still just my heart somehow i fell in love with lisp i don't know why you can't the heart wants what the heart wants i don't i don't understand it but it just connected with me maybe it's the functional language at first i connected with maybe it's because so many of the ai courses before the deep learning revolution were taught with lisp in mind i don't know i don't know what it is but i'm i'm stuck with it but at the same time like why am i not using a modern id for some of these programming like i don't know they're not that much better i've used modernity to use them but at the same time so to just not to disagree with you but like i like multiple monitors like i've i have to do work on a laptop and it's a it's a pain in the ass and also i'm addicted to the kinesis weird keyboard that you could you could see uh yeah so you don't have any of that you can just be in a macbook i mean look at work i have three 24-inch monitors i have a happy hacking keyboard i have a razer death header mouse like but it's not essential for you no let's go to a day in the life of george hotz what is the perfect day productivity-wise so we're not talking about like hunter s thompson uh drugs yeah and uh let's let's look at productivity like what what's the day look like on like hour by hour is there any irregularities that create a magical george hawks experience i can remember three days in my life and i remember these days vividly when i've gone through kind of radical transformations to the way i think and what i would give i would pay a hundred thousand dollars if i could have one of these days tomorrow um the days have been so impactful and one was first discovering eliezer yukowski on the singularity and reading that stuff and like you know my mind was blown um the next was discovering uh the hutter price and then ai is just compression like finally understanding aix i and what all that was you know i like read about it when i was 18 19 i didn't understand it and then the fact that like lossless compression implies intelligence the day that i was shown that and then the third one is controversial the day i found a blog called unqualified reservations and uh read that and i was like wait which one is that that's uh what's the guy's name curtis garvin yeah so many people tell me i'm supposed to talk to him yeah but he looks he sounds insane or brilliant but insane or both i don't know the day i found that blog was another like this was during like like gamergate and kind of the run-up to the 2016 election and i'm like wow okay the world makes sense now this this like i had a framework now to interpret this just like i got the framework for ai and a framework to interpret technological progress like those days when i discovered these new frameworks were oh interesting it's just not about but what was special about those days how did those days come to be is it just you got lucky like sure i like well you just encounter hutter prize on uh on hack news or something like that um like what but you see i don't think it's just see i don't think it's just that like i could have gotten lucky at any point i think that in a way you were ready at that moment yeah exactly to receive the information but is there some magic to the day today of like like eating breakfast and it's the mundane things nah nothing no i drift i drift through life without structure i drift through life hoping and praying that i will get another day like those days and there's nothing in particular you do to uh to be a receptacle for another for day number four no i didn't do anything to get the other ones so i don't think i have to really do anything now i took a month-long trip to new york and i mean the ethereum thing was the highlight of it but the rest of it was pretty terrible i did a two-week road trip and i got i had to turn around i had to turn around i'm driving in uh in gunnison colorado i passed through gunnison and uh the snow starts coming down this path up there called monarch pass in order to get through to denver you gotta get over the rockies and i had to turn my car around i couldn't i watched i watched a f-150 go off the road i'm like i gotta go back and like that day was meaningful because like like it was real like i actually had to turn my car around um it's rare that anything even real happens in my life even as you know mundane is the fact that yeah there was snow i had to turn around stay in gunnison and leave the next day something about that moment for real okay so actually it's interesting to break apart the three moments you mentioned if it's okay so uh i always have trouble pronouncing his name but allows yakowski yeah so what how did your world view change in starting to consider the the exponential growth of ai and agi that he thinks about and the the the threats of artificial intelligence and all that kind of ideas like can you is it j like can you maybe uh break apart like what exactly was so magical to use a transformational experience today everyone knows him for threats and ai safety um this was pre that stuff there was i don't think a mention of ai safety on the page um this is this is old yukowski stuff he'd probably denounce it all now he'd probably be like that's exactly what i didn't want to happen well sorry man is there something specific you can take from his work that you can remember yeah uh it was this realization that uh computers double in power every 18 months and humans do not and they haven't crossed yet but if you have one thing that's doubling every 18 months and one thing that's staying like this you know here's your log graph here's your line you know you calculate that and that did that open the door to the exponential thinking like thinking that like you know what with technology we can actually transformed the world it opened the door to human obsolescence it opened the door to realize that in my lifetime humans are going to be replaced and then the matching idea to that of artificial intelligence with the hutter prize you know i'm torn i go back and forth on what i think about it yeah but the the the basic thesis is it's nice to com it's a nice compelling notion that we can reduce the task of creating an intelligent system a general intelligence system into the task of compression so you can think of all of intelligence in the universe in fact as a kind of compression do you find that was that just at the time you found that as a compelling idea do you still find that a compelling idea i still find that compelling idea um i think that it's not that useful day to day but actually um one of maybe my quests before that was a search for the definition of the word intelligence and i never had one and i definitely have a definition of the word compression it's a very uh simple uh straightforward one and uh you know what confession is you know what lossless is lossless compassion not lossy lossless compression and that that is equivalent to intelligence which i believe i'm not sure how useful that definition is day to day but like i now have a framework to understand what it is and he just 10x 10xed the uh the prize for that competition like recently a few months ago you ever thought of taking a crack at that oh i did oh i did i spent i spent the next after i found the prize i spent the next six months of my life trying it and uh well that's when i started learning everything about ai and then i worked vicarious for a bit and then i learned read all the deep learning stuff and i'm like okay now i like i'm called up to modern ai wow and i had i had a really good framework to put it all in from the compression stuff right like some of the first uh some of the first deep learning models i played with were uh like gpt basically but before transformers before it was still uh rnn's to to do uh character prediction but by the way on the compression side i mean the especially neural networks what do you make of the lossless requirement with the hudder prize so you know human intelligence and neural networks can probably compress stuff pretty well but it would be lossy it's imperfect uh you can turn a lossy compressor into a lossless compressor pretty easily using an arithmetic encoder right you can take an arithmetic encoder and you can just encode the noise with maximum efficiency right so even if you can't predict exactly what the next character is the better a probability distribution you can put over the next character you can then use an arithmetic encoder to uh right you don't have to know whether it's an e or an i you just have to put good probabilities on them and then you know code those and if you have it's a bits of entropy thing right so let me on that topic could be interesting as a little side tour what are your thoughts in this year about gpt3 and these language models and these transformers is there something interesting to you as an ai researcher or is there something interesting to you as an autonomous vehicle developer nah i think uh i think it's overhyped i mean it's not like it's cool it's cool for what it is but no we're not just going to be able to scale up to gpg 12 and get general-purpose intelligence like your loss function is literally just you know you know cross-entropy loss on the character right like that's not the loss function of general intelligence is that obvious to you yes can you imagine that like to play devil's advocate on yourself is it possible that you can the gpt-12 will achieve general intelligence with something as dumb as this kind of loss function i guess it depends what you mean by general intelligence so there's another problem with the gpts and that's that they don't have a uh they don't have long-term memory right right so like just gpt 12 a scaled up version of gpt two or three i find it hard to believe well you can scale it in it's yeah so it's a hardcore hard-coded length but you can make it wider and wider and wider yeah you're gonna get you're gonna get cool things from those systems but i i don't think you're ever gonna get something that can like you know build me a rocket ship what about solve driving so you know you can use transformer with video for example you think is there something in there no because hey look we use we as a group we use a group we could change that group out to a transformer um i think driving is much more markovian than language so markov you mean like the memory which which aspect of uh i mean that like most of the information in the state at t minus one is also in the in is in state t yeah right and it kind of like drops off nicely like this where sometime with language you have to refer back to the third paragraph on the second page i feel like there's not many like like you can say like speed limit signs but there's really not many things in autonomous driving that look like that but if you look at uh to play devil's advocate is uh the risk estimation thing that you've talked about it's kind of interesting is uh it feels like there might be some longer term uh aggregation of context necessary to be able to figure out like the context yeah i'm not even sure i'm i'm believing my my own devil's we have a nice we have a nice like vision model which outputs like a a one two four dimensional perception space um can i try transformers on it sure i probably will at some point we'll try transformers and then we'll just see do they do better sure i'm well it might not be a game changer no well i'm not like like might transformers work better than grooves for autonomous driving sure might we switch sure is this some radical change no okay we use a slightly different you know we switch from rnns to grooves like okay maybe it's greased to transformers but no it's not yeah i well on the on the topic of general intelligence i don't know how much i've talked to you about it like what um do you think will actually build an agi like if if you look at ray kurzweil with a singularity do you have like an intuition about you're kind of saying driving is easy yeah and i i tend to personally believe that solving driving will have really deep important impacts on our ability to solve general intelligence like i i think driving doesn't require general intelligence but i think they're going to be neighbors in a way that it's like deeply tied because it's so like driving is so deeply connected to the human experience that i think solving one will help solve the other but but so i don't see i don't see driving is like easy and almost like separate than general intelligence but like what's your vision of a future with a singular do you see there'll be a single moment like a singularity where it'll be a phase shift are we in the singularity now like what do you have crazy ideas about the future in terms of agi we're definitely in the singularity now um we are coolers of course look at the bandwidth between people the bandwidth between people goes up all right um the singularity is just you know when the bandwidth but what do you mean by the bandwidth of the people communications tools the whole world is networked the whole world is networked and we raise the speed of that network right oh so you think the communication of information in a distributed way is a empowering thing for collective intelligence oh i didn't say it's necessarily a good thing but i think that's like when i think of the definition of the singularity yeah it seems kind of right i see like it's a change in the world beyond which like the world be transformed in ways that we can't possibly imagine no i mean i think we're in the singularity now in the sense that there's like you know one world and a monoculture and it's also linked yeah i mean i i kind of shared the intuition that the the singularity will originate from the collective intelligence of us ants versus the like some single system agi type thing oh i totally agree with that yeah i don't i don't really believe in like like a hard take off agi kind of thing um yeah i don't think i don't even think ai is all that different in kind from what we've already been building um with respect to driving i think driving is a subset of general intelligence and i think it's a pretty complete subset i think the tools we develop at comma will also be extremely helpful to solving general intelligence and that's i think the real reason why i'm doing it i don't care about self-driving cars it's a cool problem to beat people at but yeah i mean yeah you're kind of you're of two minds so one you do have to have a mission and you want to focus and make sure you get you get there you can't forget that but at the same time there is a thread that's much bigger than uh the connects the entirety of your effort that's much bigger than just driving with ai and with general intelligence it is so easy to delude yourself into thinking you've figured something out when you haven't if we build a level 5 self-driving car we have indisputably built something yeah is it general intelligence i'm not going to debate that i will say we've built something that provides huge financial value yeah beautifully put that's the engineering credo like just just build the thing it's like that's why i'm with uh with the with elon on uh go to mars yeah that's a great one you can argue like who the hell cares about going to mars but the reality is set that as a mission get it done yeah and then you're going to crack some pro problem that you've never even expected in the process of doing that yeah yeah i mean no i think if i had a choice between humanity going to mars and solving self-driving cars i think going to mars is uh better but i don't know i'm more suited for self-driving cars i'm an information guy i'm not a modernist i'm a postmodernist post modernist all right beautifully put let me let me drag you back to programming for a sec what three maybe three to five programming languages should people learn do you think like if you look at yourself what did you get the most out of from learning uh well so everybody should learn c and assembly we'll start with those two right assembly yeah if you can't code in assembly you don't know what the computer's doing you don't understand like you don't have to be great in assembly but you have to code in it and then like you have to appreciate assembly in order to appreciate all the great things c gets you and then you have to code and see in order to appreciate all the great things python gets you so i'll just say assembly c and python we'll start with those three the memory allocation of of c and the the the fact that so assemblies give you a sense of just how many levels of abstraction you get to work on in modern day programs yeah yeah graph coloring for assignment register assignment and compilers yeah like you know you got to do you know the compiler your computer only has a certain number of registers you can have all the variables you want a c function you know so you get to start your build intuition about compilation like what a compiler gets you what else um well then there's then there's kind of uh so those are all very imperative programming languages um then there's two other paradigms for programming that everybody should be familiar with i'm one of them is functional uh you should learn haskell and take that all the way through learn a language with dependent types like learn that whole space like the very pl theory heavy languages and haskell is your favorite functional what is that the go-to you would say yeah i'm not a great haskell programmer i wrote a compiler in haskell once there's another paradigm and actually there's one more paradigm that i'll even talk about after that that i never used to talk about when i would think about this but the next paradigm is learn verilog of hdl um understand this idea of all of the instructions execute at once if i have a block in verilog and i write stuff in it it's not sequential they all execute it once and then like think like that that's how hardware works to be so i guess assembly doesn't quite get you that assembly's more about compilation and verilog is more about the hardware like giving a sense of what actually is the hardware is doing assembly c python are straight like they sit right on top of each other in fact c is well let's see it's kind of coded in c but you could imagine the first c was coded in assembly and python is actually coded in c um so you know you can straight up go on that got it and then verilog gives you that's brilliant okay and then i think there's another one now everyone should carpathi calls it programming 2.0 which is learn a i'm not even gonna don't learn tensorflow learn pi torch so machine learning we've got to come up with a better term than programming 2.0 or um but yeah it's a programming language i wonder if it could be formalized a little bit better which we feels like we're in the early days of what that actually entails data-driven programming data-driven programming yeah but it's so fundamentally different as a paradigm than the others uh like it almost requires a different skill set but you think it's still yeah and ply torch versus tensorflow pytorch wins it's the fourth paradigm it's the fourth paradigm that i've kind of seen there's like this you know imperative functional hardware i don't know a better word for it and then ml do you have advice for people uh that want to you know get into programming want to learn programming you have a a video uh what is programming new blessings exclamation point and i think the top comment is like warning this is not for noobs uh do you have a noob like uh tldw for that video but also uh a new but friendly advice on how to get into programming you are never going to learn programming by watching a video called learn programming the only way to learn programming i think and the only one is the only way everyone i've ever met who can program well learned it all in the same way they had something they wanted to do and then they tried to do it and then they were like oh well okay this is kind of you know be nice if the computer could kind of do this thing and then you know that's how you learn you just keep pushing on a project um so the only advice i have for learning programming is go program somebody wrote to me a question like we don't really they're looking to learn about recurring neural networks he's saying like my company is thinking of doing recruit using recurring neural networks for time series data but we don't really have an idea of where to use it yet we just want to like do you have any advice on how to learn about these are these kind of general machine learning questions and i think the answer is like actually have a problem that you're trying to solve and and just i see that stuff oh my god when people talk like that they're like i heard machine learning's important could you help us integrate machine learning with macaroni and cheese production you just i don't even you can't help these people like who lets you run anything who lets that kind of person run anything i think we're we're all um we're all beginners at some point so it's not like they're a beginner it's it's like my problem is not that they don't know about machine learning my problem is that they think that machine learning has something to say about macaroni and cheese production or like i heard about this new technology how can i use it for why like i don't know what it is but how can i use it for why that's true you have to build up an intuition of how because you might be able to figure out a way but like the prerequisites you should have a macaroni and cheese problem to solve first exactly and then two you should have more traditional like in the learning process should involve more traditionally applicable problems in the space of whatever that is of machine learning and then see if it could be applied to background at least start with tell me about a problem like if you have a problem you're like you know some of my boxes aren't getting enough macaroni in them um can we use machine learning to solve this problem that's much much better than how do i apply machine learning to macaroni and cheese one big thing maybe this is me uh talking to the audience a little bit because i get these days so many messages a device on how to like learn stuff okay my this this this is not me being mean i think this is quite a profound actually is you should google it oh yeah like one of the uh like skills that you should really acquire as an engineer as a researcher as a thinker like one there's two two complementary skills like one is with a blank sheet of paper with no internet to think deeply and then the other is to google the crap out of the questions you have like that's actually a skill i don't people often talk about but like doing research like pulling at the thread like looking up different words going into like github repositories with two stars and like looking how they did stuff like looking at the code or going on twitter seeing like there's little pockets of brilliant people that are like having discussions like if you're a neuroscientist go into signal processing community if you're an ai person going into the psychology community like like switch communities that keep searching searching searching because it's so much better to invest in like finding somebody else who already solved your problem than than this to try to solve the problem and because they've often invested years of their life like entire communities are probably already out there who have tried to solve your problem i think they're the same thing i think you go try to solve the problem and then in trying to solve the problem if you're good at solving problems you'll stumble upon the person who solved it already yeah but the stumbling is really important i think that's a skill that people should really approach especially in undergrad like search if you ask me a question how should i get started in deep learning like especially like that is just so google like the whole point is you google that and you get a million pages and just start looking at them yeah start pulling at the thread start exploring start taking notes start getting it advice from a million people that already like spent their life answering that question actually oh well yeah i mean that's definitely also yeah when people like ask me things like that i'm like trust me the top answer on google is much much better than anything i'm going to tell you right yeah people ask it's an interesting question let me know if you have any recommendations what three books technical or fiction or philosophical had an impact on your life or you would recommend perhaps uh maybe we'll start with the least controversial uh infinite jest um infinite jest is a david foster wallace yeah it's a book about wireheading really very enjoyable to read very uh well-written you know you will you will you will grow as a person reading this book uh it's effort um and i'll set that up for the second book which is pornography it's called atlas shrugged um uh which um atlas drug is pornography i mean it is i will not i will not defend the i will not say atlas shrugged is a well-written book it is entertaining to read certainly just like pornography the production value isn't great um you know there's a 60-page monologue in there that ann rand's editor really wanted to take out and she uh paid she paid out of her pocket to keep that 60 page monologue in the book um but it is a great book for a kind of framework um of human relations and i know a lot of people are like yeah but it's a terrible framework yeah but it's a framework just for context in a couple days i'm speaking with for uh probably four plus hours with euron brook who's the main living remaining objectivists objectivist interesting uh so i've always found this philosophy quite interesting on many levels one of how repulsive some percent of large percent of the population find it which is always uh always funny to me when people are like unable to even read a philosophy because uh of some i think that says more about their psychological perspective on it yeah but but there is something about objectivism and iran's philosophy that's very deeply connected to this idea of capitalism of uh the ethical life is the productive life um that was always um compelling to me it didn't seem as like i didn't seem to interpret it in the negative sense that some people do to be fair i read that book when i was 19. so you had an impact at that point yeah yeah and the the bad guys in the book have this slogan from each according to their ability to each according to their need and i'm looking at this and i'm like these are the most cards this is team rocket level cartoonishness right no bad guy and then when i realized that was actually the slogan of the communist party i'm like wait a second wait no no no no no just you're telling me this really happened yeah it's interesting i mean one of the criticisms of her work is she has a cartoonish view of good and evil like that there's like the the reality isn't jordan peterson says this is that each of us have the capacity for good and evil in us as opposed to like there's some characters who are purely evil and some characters are purely good and that's in a way why it's pornographic the production value i love it well evil is punished and there's very clearly you know there's no there's no you know uh just like porn doesn't have uh you know like character growth well you know neither does alex shrugged like brilliant well put but as a 19 year old george cotts it was it was good enough yeah yeah what uh what's the third you have something um i i could give these these two i'll just throw out uh there's sci-fi uh permutation city um great things to start thinking about copies of yourself and then um that is uh greg egan uh he's uh that might not be his real name some australian guy might not be australian i don't know um and then this one's online it's called the metamorphosis of prime intellect um it's a story set in a post-singularity world it's interesting is there uh can you if either of the worlds do you find something uh philosophy interesting in them that you can comment on i mean it is clear to me that uh metamorphosis prime intellect is like written by an engineer uh which is it's very it's very almost a pragmatic take on a utopia in a way positive or negative well that's up to you to decide reading the book and the ending of it is very interesting as well and i didn't realize what it was i first read that when i was 15. i've reread that book several times in my life and it's sure it's 50 pages everyone should go read it what's uh sorry this is a little tangent i've been working through the foundation i've been i've haven't read much sci-fi my whole life and i'm trying to fix that the last few months that's been a little side project what's uh to use the greatest sci-fi novel uh that uh people should read or is that or i mean i would yeah i would i would say like yeah permutation city metamorphosis environmental i got it um i don't know i i didn't like foundation uh i thought it was way too modernist i feel like dune i've never read dune i've never read dune i have to read it uh fire upon the deep is interesting uh okay i mean look everyone should read everyone's reading romance everyone should read snow crash if you haven't read those like start there um yeah i haven't read snow questions yeah no it means very entertaining go to lecture bach and if you want the controversial one bronze age mindset all right i'll look into that one those aren't sci-fi but just to round out books so a bunch of people asked me on twitter and read it and so on for advice so what advice would you give a young person today about life another way what uh yeah i mean looking back especially when you're young younger you did and you continued it you've accomplished a lot of interesting things is there some advice from those i'm that life of yours that you can pass on if college ever opens again i would love to give a graduation speech um at that point i will put a lot of somewhat satirical effort into this question yeah at this you haven't written anything at this point oh you know what always wear sunscreen this is water like you're plagiarizing i mean you know but that's the that's the like clean your room you know yeah you can play drugs from from all this stuff and it's it's there is no self-help books aren't designed to help you they're designed to make you feel good like whatever advice i could give you already know everyone already knows sorry it doesn't feel good right like you know you know what what if if i tell you that you should you know eat well and and and read more and it's not gonna do anything i think the whole like genre of those kind of questions is is is meaningless i don't know if anything it's don't worry so much about that stuff don't be so caught up in your head right i mean you're yeah in the sense that your whole life is your whole existence is like moving version of that advice i don't know yeah there's there's something i mean there's something in you that resists that kind of thinking and that in itself is it's just illustrative of uh who you are and there's something to learn from that i think you're you're clearly not overthinking stuff yeah and you know it's a gut thing i even when i talk about my advice i'm like my advice is only relevant to me it's not relevant to anybody else i'm not saying you should go out if you're the kind of person who overthinks things to stop overthinking things it's not bad it doesn't work for me maybe it works for you i you know i don't know let me ask you about love yeah uh so i think last time we talked about the meaning of life and it was it was kind of about winning of course uh i don't think i've talked to you about love much whether romantic or just love for the common humanity amongst us all what role has love played in your life in this in this quest for winning where does love fit in well the word love i think means uh several different things there's uh love in the sense of maybe i could just say there's like love in the sense of opiates and love in the sense of uh oxytocin and then love in the sense of maybe like a love for math i don't think fits into either those first two paradigms uh so each of those have they uh have they have they given something to you in your life i'm not that big of a fan of the first two um what the same reason i'm not a fan of you know the same reason i don't do opiates and don't take ecstasy right and there were times look i've tried both um i like opiates way more than i liked ecstasy uh but they're not the ethical life is the productive life so maybe that's my problem with with those and then like yeah a sense of i don't know like abstract love for humanity i mean the abstract love for humanity i'm like yeah i've always felt that and i guess it's hard for me to imagine not feeling it and maybe there's people who don't and i don't know but yeah that's just like a background thing that's there i mean since we brought up uh drugs let me ask you this is becoming more and more part of my life because i'm talking a few researchers that are working on psychedelics i've eaten shrooms a couple times and it was fascinating to me that like the mind can go like it's fascinating the mine can go to places i didn't imagine it could go and it was very friendly and and positive and exciting and everything was kind of hilarious in the in the place wherever my mind went that's where i went is uh what do you think about psychedelics do you think they have where do you think the mind goes have you done psychedelics where do you think the mind goes uh is there something useful to learn about the places it goes once you come back you know i find it interesting that this idea that psychedelics have something to teach is almost unique to psychedelics right people don't argue this about amphetamines and that's true and i'm not really sure why yeah i think all of the drugs have lessons to teach i think there's things to learn from opiates i think there's things to learn from amphetamines i think there's things to learn from psychedelics things to learn from marijuana um but also at the same time recognize that i don't think you're learning things about the world i think you're learning things about yourself yes um and you know what's the even though it might have even been uh might have been a timothy leary quote i don't want to miss about him but the idea is basically like you know everybody should look behind the door but then once you've seen behind the door you don't need to keep going back um so i mean and that's my thoughts on on all real drug use too except maybe for caffeine it's a it's a little experience that uh it's good to have but oh yeah no i mean yeah i guess yeah psychedelics are definitely um so you're a fan of new experiences i suppose yes because they all contain a little especially the first few times it contains some lessons that could be picked up yeah and i'll i'll revisit psychedelics maybe once a year um usually small smaller doses maybe they turn up the learning rate of your brain i've heard that i like that yeah that's cool big learning rates have pros and cons last question this is a little weird one but you've called yourself crazy in the past uh first of all on a scale of one to ten how crazy would you say are you oh i mean it depends how you you know when you compare me to elon musk and anthony lewandowski not so crazy so like like a seven let's go with six six yes six what uh well like seven seven's a good number seven sorry well yeah i'm sure day by day changes right so but you're in that in that area what uh in thinking about that what do you think is the role of madness is that a feature or a bug if you were to uh dissect your brain so okay from like a like mental health lens on crazy i'm not sure i really believe in that i'm not sure i really believe in like a lot of that stuff right this concept of okay you know when you get over to like like like like hardcore bipolar and schizophrenia these things are clearly real somewhat biological and then over here on the spectrum you have like a dd and oppositional defiance disorder and these things that are like wait this is normal spectrum human behavior like this isn't you know where's the the line here and why is this like a problem so there's this whole this you know the neurodiversity of humanity is huge like people think i'm always on drugs people are saying this to me on my streams and like guys you know like i'm real open with my drug use i'd tell you if i was on drugs yeah i had like a cup of coffee this morning but other than that this is just me you're witnessing my brain and action so so the word madness doesn't even uh make sense and then you're in the rich neurodiversity of humans i think it makes sense but only for like some insane extremes like if you are actually like visibly hallucinating um you know that's okay but there is the kind of spectrum on which you stand out like that that's uh like if i were to look you know at decorations on a christmas tree or something like that like if you were a decoration out that would catch my eye like that thing is sparkly whatever the hell that thing is uh there's something to that just like refusing to be um boring or maybe boring is the wrong word but to um yeah i mean be willing to sparkle you know it's it's like somewhat constructed i mean i am who i choose to be uh i'm gonna say things as true as i can see them i'm not gonna i'm not gonna lie and but that's a really important feature in itself so like whatever the neurodiversity of your whatever your brain is not putting um constraints on it that force it to to fit into the mold of what society is like defines what you're supposed to be so you're one of the specimens that that doesn't mind being yourself being right is super important except at the expense of being wrong without breaking that apart i think it's a beautiful way to end it and george you're one of the most special humans i know it's truly an honor to talk to you thanks so much for doing it thank you for having me thanks for listening to this conversation with george hotz and thank you to our sponsors for sigmatic which is the maker of delicious mushroom coffee decoding digital which is a tech podcast that i listen to and enjoy and expressvpn which is the vpn i've used for many years please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars in apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from the great and powerful linus torvald talk is cheap show me the code thank you for listening and hope to see you next time |
Chris Lattner: The Future of Computing and Programming Languages | Lex Fridman Podcast #131 | the following is a conversation with Chris lner his second time in the podcast he's one of the most brilliant engineers in modern Computing having created llvm compiler infrastructure project the clang compiler the Swift programming language a lot of key contributions to tensor flown tpus as part of Google he served as vice president of autopilot software Tesla was a software innovator and leader at Apple and now is at SciFi as senior vice president of platform engineering looking to revolutionize chip design to make it faster better and cheaper quick mention of each sponsor followed by some thoughts related to the episode first sponsor is blinkist an app that summarizes key ideas from thousands of books I use it almost every day to learn new things or to pick which books I want to read or listen to next second is neuro the maker of functional sugar-free gum and mints that I use to supercharge my mind with caffeine alanine and B vitamins third is master class online courses from the best people in the world on each of the topics covered from Rockets to game design to Poker to writing and to guitar and finally cash app the app I use to send money to friends for food drinks and unfortunately lost bets please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that Chris has been in inspiration to me on a human level because he is so damn good as an engineer and leader of Engineers and yet he's able to stay humble especially humble enough to hear the voices of disagreement and to learn from them he was supportive of me in this podcast from the early days and for that I'm forever grateful to be honest most of my life no one really believed that I would amount to much so when another human being looks at me and makes me feel like I might be someone special it can be truly inspired ing that's a lesson for educators the weird kid in the corner with a dream is someone who might need your love and support in order for that dream to flourish if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Freedman and now here's my conversation with Chris lner what are the strongest qualities of Steve Jobs Elon Musk and the Great and Powerful Jeff Dean since you've gotten the chance to work with each you're starting with an easy question there um these are three very different people I guess you could do maybe a pair wise comparison between them instead of a group comparison so if you look at Steve Jobs and Elon um I worked a lot more with Elon than I did with Steve um they have a lot of commonality they're both um Visionary in their own way they're both very demanding in their own way um my sense is Steve Steve is much more human factor focused where Elon is more technology focused what does human factor mean Steve is trying to build things that feel good that people love that affect people's lives how they live he's looking into into the future a little bit in terms of um what people want um where I think the Elon focuses more on uh learning how exponentials work and predicting the development of those Steve worked with a lot of Engineers that was one of the things that reading the biography and how how can a designer essentially talk to engineers and like get their respect I think so I did not work very closely with Steve I'm not an expert at all my sense is that he uh pushed people really hard but then when he got an explanation that made sense to him then he would let go and um he did actually have a lot of respect for engineering and but he also knew when to push and you know when you can read people well you can know when they're holding back and when you can get a little bit more out of them and I think he was very good at that I mean if you if you compare the other the other folks so Jeff Dean right Jeff Dean's an amazing guy he's super smart um as as are the other guys um Jeff is a really really really nice guy well-meaning he's a classic googler he uh uh wants people to be happy he combines it with Brilliance so he can pull people together in a in a really great way he's definitely not a CEO type I don't think he would even want to be that um do you know if he still programs oh yeah definitely programs Jeff is an amazing engineer today right and that has never changed so um it's really hard to compare Jeff to to either of those two um he uh I think that Jeff leads through technology and building it himself and then pulling people in and inspiring them and so I think that that's um a one of the amazing things about Jeff but each of these people you know with their pros and cons all are really inspirational and have achieved amazing things so it's been a it's been I've been very fortunate to work with these guys for yourself you've LED large teams you've done so many incredible difficult technical challenges is there something you've picked up from them about how to lead yeah well so I mean I think leadership is really hard it really depends on what you're looking for there um I think you really need to know what you're talking about so being grounded on the product on the technology on the business on the mission is really important being uh understanding what people are looking for for why they're there one of the most amazing things about Tesla is the unifying Vision right people are there because they believe in clean energy and El electrification all these kinds of things um uh the others is to understand what really motivates people how to get the best people how to how to build a plan that actually can be executed right there's so many different aspects of leadership and it really depends on the time the place the problems you know you know there's a lot of issues that don't need to be solved and so if you focus on the right things and prioritize well that can really help move things two interesting things you mentioned one is you really have to know what you're talking about how you've uh you've worked on a lot of very challenging technical things sure so I kind of assume you were born uh technically Savvy but assuming that's not the case uh how did how did you develop technical expertise like even at Google you worked on I don't know how many projects but really challenging very varied compilers tpus Hardware Cloud stuff bunch of different things um the thing that I've become comfortable as I've more comfortable with as I've uh gained experience is uh being okay with not knowing and so a major part of leadership is actually it's not about having the right answer it's about getting the right answer and so if you're working in a team of amazing people right and many of these places many of these companies all have amazing people it's the question of how do you get people together how do you get how do you build trust how do you get people to open up how do you people get people to you know be vulnerable sometimes with an idea that maybe isn't good enough but it's the start of something beautiful how do you um how do you provide an environment where you're not just like top down Thou shalt do the thing that I tell you to do right but you're encouraging people to be part of the solution and uh and providing a safe space where if you're not doing the right thing they're willing to tell you about it right so you're okay asking dumb questions yeah dumb questions are my specialty yeah well I so I've been in the hardware room recently and I don't know much at all about how chips are designed I know a lot about using them I know some of the principles and the ARs technical level of this but level it turns out that if you ask a lot of dumb questions you get smarter really really quick and when you're surrounded by people that want to teach and learn themselves uh it can be a beautiful thing uh so let's talk about programming languages if it's okay at the High this absurd philosophical level cuz I I don't get romantic on me Lex I I will forever get romantic and uh Tor here I apologize uh why do programming languages even matter okay well thank you very much so you're saying why should why why should you care about anyone programming language or why do why do we care about programming computers or no why why do we why do we care about programming language design creating effective programming languages uh choosing a you know one programming languages versus another programming language why we keep struggling and improving through the evolution of these programming languages sure sure sure okay so so I mean I think you have to come back to what what are we trying to do here right so we have these these uh beasts called computers that are very good at specific kinds of things and we think it's useful to have them do it for us right uh now you have this question of how best to express that because you have a human brain still that has an idea in its head and you want to achieve something right so well there's lots of ways of doing this you can go directly to the machine and speak Assembly Language and then you can express directly what the computer understands that's fine um you can then have higher and higher and higher levels of exraction up until machine learning and you're designing an neural net to do the work for you um the question is where where along this way do you want to stop and what benefits do you get out of doing so and so programming languages in general you have C you have Fortran and Java and a Pascal Swift you have lots of different things um they all have different trade-offs and they're T tackling different parts of the problems now one of the things that most programming languages do is they're trying to make it so that you have pretty basic things like portability across different Hardware so you've got I'm going to run on an Intel PC I'm going to run on RIS 5 PC I'm going to run on a arm phone or something like that fine um I want to write one program and have it portable and this is something the assembly doesn't do now when you start looking at the space of programming languages this is where I think it's fun because programming languages all have trade-offs and most people will walk up to them and they look at the surface level of syntax and say oh I like Curly braces or I like tabs or I like you know semicolons or not or whatever right subjective fairly subjective very shallow things but programming languages when done right can actually be very powerful and the the benefit they bring is expression okay and if you look at programming languages there's really kind of two different levels to them one is the down in the dirt nuts and bolts of how do you get the computer to be efficient stuff like that how they work type systems compiler stuff things like that the other is the UI and the UI for programming language is really a design problem and a lot of people don't think about it that way and the UI you mean all that stuff with the braces and yeah all that stuff to the UI and what it is and UI means user interface um and so what what's really going on is it's the interface between the guts and the human and humans are hard right humans have feelings they have things they like they have things they don't like and a lot of people treat programming languages as though humans are just kind of abstract creatures that cannot be predicted but it turns out that actually there are there is better and worse like people can tell when a program language is good or when it was an accident right and uh one of the things with Swift in particular is that a tremendous amount of time by a t tremendous number of people have been put into really polishing and Mak it feel good but it also has really good nuts and bolts underneath it you said that uh Swift makes a lot of people feel good how do you get to that point so how do you predict that um you know tens of thousands hundreds of thousands of people are going to enjoy using this the user experience of this programming language well you can you can look at it in terms of better and worse right so if you have to write lots of boiler plate or something like that you will feel unproductive and so that's a bad thing you can look at it in terms of safety if like C for example is what's called a memory unsafe language and so you get dangling pointers and you get all these kind of bugs that then you have to spend tons of time debugging and it's a real pain in the butt and you feel unproductive and so by subtracting these things from the experience you get um you know happier people but uh uh again keep interrupting I'm sorry uh but so hard to deal with if you look at the people people that are most productive on stack Overflow they are uh they have a set of priorities yeah that may not always correlate perfectly with the experience of the majority of users you know like if you look at the most uploaded uh quote unquote correct answer on stack Overflow it usually really um sort of uh prioritizes like safe code proper code stable code uh you know that kind of stuff as opposed to like if I want to use go-to statements in my basic right uh I'm I want to use go-to State like what if 99% of people want to use go-to statements or use completely improper you know unsafe syntax I I don't think that people actually like if you boil it down and you get below the surface level people don't actually care about go-tos or if statements for things like this they care about achieving a goal yeah right so the real question is I want to set up a web server and I want to do a thing and I whatever like how how quickly can I achieve that right and so the from a programming language perspective there's really two things that that matter there one is what libraries exist and then how quickly can you put it together and what are the tools around that look like right and uh and when you want to build a library that's missing what do you do okay now this is where you see huge Divergence in the force between worlds okay and so you look at python for example python is really good at assembling things but it's not so great at building all the libraries and so what you get because of performance reasons other things like this is you get python layered on top of C MH for example and that means that doing certain kinds of things well it doesn't really make sense to do in Python instead you do it in C and then you rapid and then you have you're living in Two Worlds and Two Worlds never is really great because tooling and the the debugger doesn't work right and like all these kinds of things can you clarify a little bit what uh what you mean by python is not good at building libraries meaning doesn't make certain kinds of libraries no but just the actual meaning of the sentence yeah uh meaning like it's not conducive to developers to come in and add libraries or it's it's or the langu or is it the The Duality of the it's a dance between Python and c and Python's amazing Python's a great language I did not mean to say that python is is bad for libraries what what I meant to say is um there python there are libraries that Python's really good at they you can write in Python but there are other things like if you want to build a machine learning framework you're not going to build a machine learning framework in Python because of performance for example or you want GPU acceleration or things like this instead what you do is you write a bunch of C or C++ code or something like that and then you talk to it from python right and so this is because of decisions that were made in the python design and um and those decisions have other counterbalancing forces but but the trick when you start looking at this from a programming language perspective is you start say okay cool how do I build this catalog of libraries that are really powerful and how do I make it so that then they can be assembled into ways that feel good and they generally work the first time because when you're talking about building a thing you have to include the debugging the fixing the turnaround cycle the development cycle all that kind of stuff in in into the process of building the thing it's not just about pounding out the code and so this is where things like um you know catching bugs at compile time is valuable for example um but if you dive into the details on this Swift for example has certain things like value semantics which is this fancy way of saying that when you uh treat a treat a variable like a value um uh it acts like a mathematical object would okay so in you have used pytorch a little bit in pytorch you have tensors tensors are uh ND nend dimensional grid of numbers very simple you can do plus and other operators on them it's all totally fine but why do you need to clone a tensor sometimes have you ever run into that uh yeah okay and so why is that why do you need to clone a tensor it's the usual object thing that's in Python so in Python and just like with Java and many other languages this isn't unique to python in Python it has a thing called reference semantics which is the nerdy way of explaining this and what that means is you actually have a pointer to a thing instead of the thing okay now this is due to a bunch of implementation details that you don't want to go into but in Swift you have this thing called value sematics and so when you have a tensor in Swift it is a value if you copy it it looks like you have a unique copy and if you go change one of those copies then uh it doesn't update the other one because you just made a copy of this thing right so that that's like highly error prone in uh at least computer science math Centric disciplines about python that like the the thing you would expect to behave like math like math it doesn't behave like math and in fact uh quietly doesn't behave like math and then can ruin the entirety of your math exactly well and then it puts you in debugging land again yeah right now now you just want to get something done and you're like wait wait a second where you need where do I need to put clone in what level of this stack which is very complicated which I thought I was reusing somebody's library and now I need to understand it to know where to clone a thing thing right and hard to debug by the way exactly right and so this is where programming languages really matter right so in Swift having value sematics so that um both you get the benefit of math working like math right but also the efficiency that comes with certain advantages there certain implementation details there really benefit you as a programmer right you clarify the value sematics like how how do you know that a thing should be treated like a value yeah so so Swift uh has a pretty strong culture and good language support for defining values and so if you have an array so tensors are one example of that the machine learning folks are very used to um just think about arrays same thing where you have an array you put uh you create an array you put two or three or four things into it and then you pass it off to another function mhm what happens if that that uh function adds some more things to it well you'll see it on the side that you pass it in right this is called reference semantics now what if you pass an array off to a function it Scrolls it away in some dictionary or some other data structure somewhere right well it thought that you just handed it that array then you return back and that that that reference to that array still exists in the callar and they go and put more stuff in it right the the person you handed it off to may have thought they had the only reference to that and so they didn't know what they that this was going to change underneath the covers and so this is where you end up having to do clone so like I was past a thing I'm not sure if I have the only version of it so now I have to clone it so what value sematics does is it allows you to say hey I have a so in Swift it defaults to value sematics for oh so defaults to value sematics and then because most things should Valu then it makes sense for that to be the default and one of the important things about that is that arrays and dictionaries and all these other collections or aggregations of other things also have value semantics and so when you pass this around uh to different parts of your program you don't have to do these defensive copies and so this is this is great for two sides right it's great because you define away the bug which is a big deal for productivity the the number one thing most people care about but it's also good for performance because when you're doing a clone so you pass the array down to the thing it's like I don't know if anybody else has it I have to clone it well you just did a copy of a bunch of data it could be big and then it could be that the thing that called you is not keeping track of the old thing so you just made a copy of it and you may not have had to yeah and so the way the value sematics work is in Swift is it uses this thing called copy on right which means that you get you get the benefit of safety cool and performance and it has another special trick because um if you think of certain languages like Java for example they have immutable strings and so what they're trying to do is they provide value semantics by having pure immutability functional languages have pure immutability in lots of different places and this provides a much safer model than it provides valics um the problem with this is if you have immutability everything everything is expensive everything requires a copy um for example in Java if you have a string X and A String y you pen them together we have to allocate a new string to hold XY oh if they're immutable well and strings strings in Java are immutable and if there's there's optimizations for short ones and it's it's complicated but but generally uh think about them as a separate allocation and so when you append them together you have to go allocate a third thing mhm because somebody might have a pointer to either of the other ones right and you can't go change them so you have to go allocate a third thing um because of the beauty of how the Swift value SM system works out if you have a string and Swift and you say hey put in X right and they say append on y z w what it knows that there's only one reference to that and so it can do an inpl update and so you're not allocating tons of stuff on the side you're not you don't have all those problems when you pass it off you can know you have the only reference if you pass it off to multiple different people but nobody changes it they can all share the same thing so you get a lot of the benefit of of purely mutable design and so you get a really nice sweet spot that I haven't seen in other languages yeah that's like I thought I thought there was going to be a a philosophical like narrative here that you're going to have to pay a cost for it CU it sounds like uh I think value semantics is beneficial for easing of debugging or minim izing the risk of Errors like bringing the errors closer to the source um bringing the symptom of the air closer to the source of the air however you say that and but you're saying there's not a performance cost either if you implement correctly well so there there's trade-offs with everything and so if you are doing very low-level stuff then sometimes you can noce cost but then what you're doing is you're saying what is the right default so um coming back to you interface when you when you talk about programming languages one of the ma ma major things that Swift does that makes people love it that is not obvious when it comes to designing language is this UI principle of progressive disclosure of complexity okay so Swift like many languages is very powerful the question is when do you have to learn the power as a user so Swift like python allows you to start with like print hello world MH right certain other languages uh start with like public static void Main like all the ceremony right and so you go to teach you teach a new person hey W welcome to this new thing let's talk about Public Access Control classes wait what's that string system.out do printland like packages like God right and so instead if you take this and you say hey we need you need we need packages you know modules we need we need powerful things like classes we need data structures we need like all these things the question is how do you factor after the complexity and how do you make it so that the normal case scenario is you're dealing with things that work the right way the right way give you good performance the right by default but then as a power user if you want to dive down to it you have full c c performance full control over low-l pointers you can call Malik if you want to call Malik this is not recommended on the first page of every tutorial but it's actually really important when you want to get work done right and so being able to have that is really the design in programm language design design and design is really really hard it's something that I think a lot of people kind of um outside of UI again a lot of people just think is uh subjective like there's nothing you know it's just like Curly braces or whatever it's just like somebody's preference but actually good design is something you can feel and uh how many people are involved with good design so if we looked at Swift but look at historically I mean this might touch like uh it's almost like a Steve jobs question too like how much dictatorial decision- making is required versus um collaborative and we'll talk about how all that can go wrong or right but yeah well Swift so I can't speak to in general all design everywhere uh so the way it works with swift is that um there's a core team and so a core team is uh six or seven people is something like that that is people that have been working with swift since very early days and so I and by early days is not that long ago okay yeah so it's it it became public in 2014 so it's been six years public now but um but still that's enough time that there's a story arc there okay and there's mistakes have been made that then get fixed and you learn something and then you you know and so uh what the core team does is it provides continuity and so you want to have a okay well there's a big hole that we want to fill we know we want to fill it so don't do other things that invade that space until we fill the hole right there there's a boulder that's missing here we want to do we will do that Boulder even though it's not today keep keep out of that space and the whole team remembers of the remembers the myth of the boulder that's there yeah yeah there's a general sense of what the future looks like in Broad strokes and a shared understanding of that combined with a shared understanding of what has happened in the past that worked out well and didn't work out well um the next level out is you have the uh what's called the Swift Evolution community and you've got in that case hundreds of people that really care passionately about the way Swift evolves and that's like an amazing thing to again uh the court team doesn't necessarily need to come up with all the good ideas you got hundreds of people out there that care about something and they come up with really good ideas too and that provides this like tumbling rock tumbler for ideas and so the the evolution process is you know a lot of people in a discourse form they're like hashing it out and trying to like talk about okay well would should we go left or right or if we did this what would be good and you know here you're talking about hundreds of people so you're not going to get consensus necessarily not obvious consensus and so there's a proposal process that uh then allows the core team and the community to work this out and what the core team does is it aims to get consensus out of the community and provide gu guard rails but also provide long-term make sure we're going the right direction kind of things so does that group represent like the how much people will love the user interface like you think to capture that well I mean it's something we talk about a lot something we care about how well we how well we do that Up For Debate but I think that we've done pretty well so far is the beginner in mind like cuz you said the progressive disclosure complex yeah so we care a lot about uh a lot about that a lot about power a lot about efficiency a lot about there are many factors to good design and you have to figure out a way to kind of work your way through that and so if you like think about like a language I love is lisp probably still because I use Zac but I haven't done anything any serious working list but it has a ridiculous amount of parentheses yeah um I've also you know with Java and C++ uh the braces um you know I I like I I I enjoyed the comfort of being between braces you know python is really sorry to interrupt just like and last thing to me as a design if I was a language designer uh God for bit is I would be very surprised that python with no braces would nevertheless somehow be comforting also so like I can see Arguments for all of these but look at this this is evidence that it's not about braces versus tevs right exactly you're good that's a good point right so like you know there there's there's evidence that but see like it's one of the most argued about things oh yeah of course just like tabs and spaces which it does I mean there's one obvious right answer but it doesn't it doesn't actually matter what's that come on we're friends like come on what are you trying to do to me here people are going to yeah half the people are going to tune out yeah um so so do you're able to identify things that don't really matter for the experience well no no no it's it's it's always a really hard so the easy decisions are easy right I mean you you C fine those are not the interesting ones the hard ones are the ones that are most interesting right the hard ones are the places where hey we want to do a thing everybody agrees we should do it there's one proposal on the table but it has all these bad things associated with it well okay what are we going to do about that do we just take it do we delay it do we say hey well maybe there's this other feature that if we do that first this will work out better um how does this if if we do this are we painting ourselves into a corner right and so this is where again you're having that core team of people that uh has some continuity and has perspective has some of the historical understanding is really valuable because you get um it's not just like one brain you get the power of multiple people coming together to make good decisions and then you get the best out of all these people and you also can harness the the community around it what about like the decision of whether like in Python having one type or having you know uh strict typing yeah yeah let's talk about this so so um I I like how you put that by the way like so so many people would say that python doesn't have types doesn't have types yeah I've listened to you enough to where okay I'm I'm a fan of yours and listened to way too many podcast and videos talking about this oh yeah so I would argue that python has one type and so um so like when you import python into Swift which by the way works really well you have everything comes in as a python object now here there trade-offs because um uh you know it depends on what you're optimizing for and python is a super successful language for a really good reason um because it has one type uh you get duck typing for free and things like this but also you're pushing you're making it very easy to to pound out code on the one hand but you're also making it very easy to introduce uh complicated bugs the have debug and you pass the string into something that expects an integer and it doesn't immediately die it goes all the way down the stack trace and you find yourself in the middle of some code that you really didn't want to know anything about and it blows up and you're just saying well what did I do wrong right and so types are good and bad and they have trade-offs they're good for performance and certain other things depending on where you're coming from but it's it's all about trade-offs and so this is this is what design is Right design is about weighing tradeoffs and trying to understand the ramifications of the the things that you're weighing like types or not or one type or many types um but also within many types how powerful do you make that type system is another very complicated question uh with lots of trade-offs it's very interesting by the way uh but uh but that's like one one dimension and there's a bunch of other dimensions jit compiled versus static compiled garbage collected versus reference counted versus memory man manual memory management versus you know like in like all these different trade-offs and how you balance them are what make a programm language good currency y so and all those things I guess uh when you're designing the language you also have to think of how that's going to get all compiled down to if you care about performance yeah well and go back to list right so list also I would say JavaScript is another example of a very simple language right and so one of the so I also love lisp I don't use it as much as maybe you do or you did no I think we're both everyone who loves lisp it's like you love it's like I don't know I love Frank Sinatra but like how often do I seriously listen to Franks sure but but but you look at that or you look at JavaScript which is another very different but relatively simple language and there's certain things that don't exist in the language but there's there is inherent complexity to the problems that we're trying to model and so what happens to the complexity in the case of uh both of them for example you say well what about about large scale software development okay well you need something like packages neither language has a like language affordance for packages and so what you get is patterns you get things like npn you get things like you know like these ecosystems that get built around and I'm a believer that if you don't uh model at least the most important inherent complexity in the language then what ends up happening is that complexity gets pushed elsewhere and when it gets pushed elsewhere sometimes that's great because often building things as libraries is very flexible and very powerful and allows you to evolve and things like that but often it leads to a lot of uh unnecessary Divergence in the force and fragmentation and and when that happens you just get kind of a mess yeah and so the question is how do you how do you balance that uh don't put too much stuff in the language because that's really expensive and makes things complicated but how do you model enough of the inherent complexity of the problem that um you provide the framework and the structure for people to think about Al so so the the the the key thing to think about with uh with programming languages and you think about what a programming language is there for is it's about making a human more productive right and so like there's an old I think it's Steve Jobs quote about um it's a bicycle for the mind right you can you can you can definitely walk but you'll get there a lot faster if you can bicycle on your way and a programming language is a bicycle for the mind yeah is basically a wow that's a really interesting way to think about it by by raising the level of abstraction now you can fit more things in your head by being being able to just directly leverage somebody's Library you can now get something done quickly um in the case of Swift swift UI is this new framework that Apple has released recently for doing UI programming and it has this declarative programming model which defines away entire classes of bugs it's make it builds on value sematics and many other nice Swift things and what this does allows you just get way more done with way less code and now your productivity as a developer is much higher right and so that that's really the what programming languages should be about is it's not about tabs versus spaces or curly braces or whatever it's about how productive do you make the person and you can only see that when you have libraries that were built with the right intention that the language was designed for and with Swift I think we're still a little bit early um but Swift UI and many other things that are coming out now are really showing that and I think that they're opening people's eyes it's kind of interesting to think about like how that you know then knowledge of something of how good the bicycle is how people learn about that you know so I've used C++ now this is not going to be a trash talking session about C++ but use C++ for a really long go there if you want I have the scars I I feel like I spent many years without realizing like there's languages that could for my particular LIF style brain style thinking style there's languages that that could make me a lot more productive uh in the debugging stage in the just the development stage and thinking like the bicycle for the mind I can fit more stuff into my Python's a great example of that right I mean a machine learning framework in Python is a great example of that it's just very high abstraction level and so you can be thinking about things on a like very high level Al algorithmic level instead of thinking about okay well am I copying this tensor to a GPU or not right it's not it's not what you want to be thinking about and as I was telling you I mean I guess I guess the question I head is uh you know how does a person like me or in general people discover more productive uh you know languages like how I was as I've been telling you offline I've been looking for like a project to work on in Swift so I can really uh try it out as I mean my intuition was like doing a hello world is not going to get me there uh to to to get me to experience the power of the language you need a few weeks to change your metabolism exactly I put uh that that's one of the problems with people with diets like I I'm I'm actually currently to go in parallel but in a small tangent is I've been recently eating only meat okay okay and okay so most people are like uh think that's horribly unhealthy or whatever you have like a million It Whatever the science is it just doesn't sound right well so so back when I was in college we did the Atkins diet that was that was a thing similar and but if you you have to always give these things a chance I mean with dieting always not dieting but just the things that you like if I eat personally if I eat meat just everything I could be super F or more focused than usual I just feel great I I've been I've been running a lot you know doing push-ups and pull-ups and so on I mean python is similar in that sense for me where you going with this I mean literally I just I felt I had like a stupid smile on my face when I first started using python I could uh code up really quick things like I like I I would see the world I'll be empowered to write a script to to um you know to do some basic data processing to rename files on my computer yeah right like Pearl didn't do that for me uh uh I mean kind a little bit well and again like none of these are about which which is best or something like that but there there's definitely better and worse here but it clicks right well yeah it if you look at Pearl for example you get bogged down in uh scalers versus arrays versus hashes versus type Globs and like all that kind of stuff and and Python's like yeah let's not do this right and some of is debuging like everyone has different priorities but for me it's could I create systems for myself that Empower me to debug quickly like I've always been a big fan even just crude like asserts like always uh stating things that should be true uh which in Python I found myself doing more because of type all these kinds of stuff well you could think of types in a programming language as being kind of assert yeah they get check at compile time right um so how do you learn a new thing well so this or how do how do people learn new things right this this is hard uh people don't like to change people generally don't like change around them either and so uh we're all very slow to adapt and change and usually there's a catalyst that's required to to force yourself over the over over the so for learning a programming language it really comes down to finding an excuse like build a thing that that's that the language is actually good for that the ecosystem is ready for um and so um and so if you were to write an IOS app for example that would be the easy case obviously you would use Swift for that right there are other Android Swift runs on Android oh does it oh yeah yeah Swift runs in lots of places so uh okay so Swift Swift swift is built on top of lvm lvm runs everywhere lvm for example builds the Android kernel oh wow okay so um okay I didn't realize this yeah so Swift swift is very portable runs on Windows there's it runs on lots of different things and Swift side Swift UI and then there's a thing called UI kit so can I build an app with Swift uh well so that that's the thing is the ecosystem is what matters there so Swift UI and uiit are Apple Technologies okay got it and so they happen to like Swift eii happens to be written in Swift but it's an apple proprietary framework that um Apple loves and wants to keep on its platform which makes total sense you go go to Android and you don't have that Library yeah right and so Android has a different ecosystem of things that hasn't been built out and doesn't work as well with Swift and so you can totally use Swift to do uh like arithmetic and things like this but building a UI with Swift on Android is not not not a not a great experience right now so so if I wanted to uh so learn Swift what's the pro I mean the one practical different version of that is um Swift for tensorflow for example and one of the inspiring things for me with both tensorflow and pytorch is how quickly the community can like switch from different libraries y like you could see some of the communi switching to pytorch now but it could it's very easy to see and then tensor flow is really stepping up its game and then there's no reason why I think it the way it works basically there has to be one GitHub repo like one paper steps up to get gets people excited gets people excited and they're like ah I have to learn this Swift for what what Swift again like and then they learn and they fall in love with I mean that's what happen PTO has there has be a reason a catalyst yeah and so and and there I mean people don't like change but it turns out that once you've worked with one or two programming languages they're the basics are pretty similar and so one of the fun things about learning programming languages even even maybe list I don't know if you agree with this is that when you start doing that you start learning new things because you have a new way to do things and you're forced to do them and that forces you to explore and it puts you in learning mode and when you get in learning mode your mind kind of opens a little bit and you can you can see things in a new way even when you go back to the old place right yeah it's totally well Lis is functional yeah uh stuff but I wish there was a kind of window maybe you can tell me if there is uh there you go this this a question uh to ask what is the most beautiful feature in a programming language before I ask it let me say like with python I remember when I saw list comprehensions okay was like when I like really took it in yeah it I don't know I just loved it it was like fun to do like it was fun to do that kind of um uh yeah there was something about it to be able to filter through a list and to create a new list all in a single line was elegant I could all get into my head and it just made me um fall in love with the language so is there let me ask you a question uh is there what do use the most beautiful feature in uh in a programming languages that you've ever encountered in Swift maybe and then outside of Swift I think the thing that I like the most from a programming language so so I think the thing you have to think about with the programming language again what is the goal you're trying to get people to get things done quickly and so you need libraries you need high quality libraries and then you need a user base around them that can assemble them and do cool things with them right and so to me the question is what enables high quality libraries okay yeah and there's a huge divide in the world between libraries who enable highquality libraries versus um the ones that put special stuff in the language so programming languages that enable high quality libr high quality libraries got it so so and what I mean by that is expressive libraries that then feel like a natural integrated part of the language itself MH so um an example of this in Swift is that int and float and also array and string things like this these are all part of the library like int is not hard-coded into Swift and so what that means is that because int is just a Library Thing defined in the standard Library along with strings and arrays and all the other things that come with the standard Library um well hopefully you do like int but anything that any language features that you needed to Define int you can also use in your own types so if you want to define a uh querian or something like this right um well it doesn't come in the standard Library um there's a very special set of people that care a lot about this but those people are also important it's not it's not about classism right it's not about the people who care about instant floats are more important than the people who care about querian and so to me the beautiful things about about programming languages is when you allow those communities to to build high quality libraries that feel native that feel like they're built into the built into the compiler without having to be what does it mean for the int to be part of not hardcoded in so is it like how so what is an what is an INT okay int is just a integer in this case it's like a you know like a 64-bit integer or something like this but so like the 64-bit is hardcoded or no no none of that's hardcoded so int int if you go look at how it's implemented is it's just a struct and Swift and so it's a struct and then how do you add two structs well you define plus and so you can Define Plus on int well you can Define Plus on your thing too you can Define uh int has like an is OD method or something like that on it and so yeah you can add methods onto things yeah uh so you can you can def find operators like how it behaves yeah that to is beautiful when there there's something about the language which enables others to create libraries which are um not hacky yeah that feel that feel native and so one of the best examples of this is lisp MH right because in lisp all like all the libraries are basically part of the language right you write term rewrite systems and things like this and so can you as a counter example provide what makes it difficult to write a library that's native is it the python C well so well so one example I'll give you two examples um Java and C++ or Java and C um they both allow you to Define your own types um but int is hard code in the language okay well why well in in Java for example coming back to this whole reference semantic value semantic thing um int gets passed around by value yeah but if you if you make if you make like a pair or something like that a complex number right it's a it's a class in Java and now it gets passed around by reference by pointer and so now you lose value sematics right you lost math okay well that's not great right if if you can do something with in why can't I do it with my type yeah right so that's that's the the negative side of the thing I find beautiful is when you can solve that when you can have full expressivity where where you as a user of the language have as much or almost as much power as the people who implemented all the standard built-in stuff because what that enables is that enables truly beautiful libraries you know it's kind of weird cuz I've gotten used to that uh that's one I guess other aspect of program language design you have to think you know the old uh first principles thinking like why are we doing it this way by the way I mean I remember cuz I was thinking about the wallers operator and I'll ask you about it later but it it hit me that like the equal sign for assignment yeah like why are we using the equal sign for assignment and that's not the only solution right so if you look at Pascal they use colon equals for assignment and equals for um for equality and they use like less than greater than instead of the not equal thing like there are other answers here so but like and yeah like ask you all but how do you then decide uh to break convention to say you know what this everybody's doing it wrong we're gonna do it right yeah so so it's like an Roi like return on investment tradeoff right so if you do something weird let's just say like not like colon equal instead of equal for assignment that would be weird with today's aesthetic right and so you'd say cool this is theoretically better but is it better in which ways like what do I get out of that do I Define away class of bugs well one of the class of bugs that c has is that you can use like you know if x equals without equals equals f x equals y yeah right well turns out you can solve that problem in lots of ways clang for example GCC all these compilers will detect that as a as a likely bug produce a warning do they yeah I feel like they didn't or clang do GCC didn't and it's like one of the important things about programming language design is like you're literally creating suffering in the world okay like like I feel I mean one way to see it is the bicycle for the mine but the other way is to like minimizing suffering well you have to decide if it's worth it right and so let's come back to that okay but um but if you if you look at this and again this is where there's a lot of detail that goes into each of these things um uh equal and C returns a value y that's messed up that allows you to say xal yals Z like that works in C yeah um is it messed up you know most people think it's messed up by think uh it it is very by messed up what I mean is it is very rarely used for good and it's often used for bugs yeah right and so that's a good definition of up yeah you could use you know it's it's a in hindsight this was not such a great idea right now one of the things with swift that is really powerful and one of the reasons it's actually good um versus it being full of good ideas is that um when when we launched Swift one we announced that it was public people could use it people could build apps but it was going to change and break okay when Swift 2 came out we said hey it's open source and there's this open process which people can uh help evolve and direct the language so the community at large like Swift users can now help shape the language as it is and what happened is that part as part of that process is a lot of really bad mistakes got taken out so for example Swift used to have the C style Plus+ and minus minus operators like what does it mean when you put it before versus after right well that got cargo culted from C into Swift early on what's cargo culted cargo culted means uh brought forward without really considering considering it okay um this is maybe not the most py term but um have to look it up an urban dictionary yeah yeah so it got pulled it got pulled into C without or it got pulled into Swift without very good consideration and we went through this process and one of the first things got ripped out was plus plus and minus minus because they lead to confusion they have very low value over saying you know X plus equals 1 and X Plus equal 1 is way more clear and so when you're optimizing for teachability and Clarity and bugs and this multi-dimensional space that you're looking at um things like that really matter and so being uh first principles on where you're coming from and what you're trying to achieve and being anchored on the objective is really important well let me ask you about uh the most uh sort of this this uh this this podcast isn't about information it's about drama so let me talk to you about some drama so you mentioned Pascal and colon equals uh there's something that's called the wallrus operator okay and uh python uh in Python 3.8 added the walus operator and the reason I think it's interesting uh it's not just because of the feature it does it's it has the same kind of expression feature you can mention to see that it Returns the value of the assignment and maybe you can comment on that in general but on the other side of it it's also the thing that that uh toppled the dictator uh so okay it finally drove Guido to uh step down from edfl the toxicity of the community so maybe um what do you think about the wallus operator in in Python is there an equivalent thing in Swift that really uh stress tested the community and uh and then on the flip side what do you think about AGA stepping down over it yeah if well if like if I look past the details of the W walrus operator one of the things that makes it most polarizing is that it's syntactic sugar okay what do you mean by syntactic Sugar it means you can take something that already exists in the language and you can express it in a more concise way so okay I'm going to play Do's advocate so uh this is great uh is that objective or subjective statement like can you can you argue that basically anything is syntactic sugar or no uh no you not everything is is syntactic sugar so for example um the type system like can you have classes versus uh versus uh like do you have types or not right so so one type versus many types is not something that affects syntactic sugar and so if you say I want to have the ability to Define types I have to have all this like language mechanics to Define classes and oh now I have to have inheritance and I have like have all this stuff that's just making the language more complicated mhm that's not that's not about sugaring it um Swift has sugar so like Swift has this thing called IFL and it has uh various operators that used to conisy uh specific use cases so the problem with syntactic sugar when you're talking about hey I have a thing that takes a lot to write and I have a new way to write it you have this like horrible trade-off which becomes almost completely subjective which is how often does this happen and does it matter and one of the things that is true about human psychology particularly when you're talking about introducing a new thing is that uh people over overestimate the burden of learning something and so it looks foreign when you haven't gotten used to it but if it was there from the beginning of course it's just part of python like unquestionably like this is this is just a thing I know and it's not a new thing that you're worried about learning it's just part of part of the deal now with Guido uh I I don't know Guido well um yeah have you a pass cross much yeah I've met him a couple of times but I don't know Guido well but the the sense that I got out of that whole dynamic was that he had put the not just the decision maker weight on his shoulders but it was so tied to his personal identity that um he took it personally and he felt the need and he kind of put himself in the situation of being the person instead of building a base of support around him I mean he this is probably not quite literally true but by too much so there's too much too much concentrated on him right and so and that can wear you down well yeah particularly because people then say Guido you're a horrible person I hate this thing blah blah blah blah blah blah blah and sure it's like you know maybe 1% of the community that's doing that but Python's got a big community and 1% of of millions of people is a lot of hate mail and that just from human factor will just wear on you what to to clarify it looked from just what I saw in the messaging for the let's not look at the million python users but at the python core developers it feels like the majority the big majority on a vote were opposed to it okay I'm not that close to it so I don't knowen so so this okay so the situation is like literally uh yeah I mean the majority of the core developers are against so I and they weren't they weren't even like against it it was uh there was a feel well they were against it but the they against it wasn't like this is a bad idea they were more like we don't see why this is a good idea and what that results in is there's a stalling feeling like you you just slow things down now from my perspective now you could argue this and I think it's very it's very interesting if we look at politics today and the way Congress works it slowed down everything it's a dampener yeah it's a dampener but like that's a dangerous thing too because if it dampens things like you know dampening results what are you talking about like it's a low pass filter but if you need billions of dollars injected into the economy or trillions of dollars then suddenly stuff happens right and so for sure so you're talking I'm not defending our political situation just to be clear but you're talking about like a a global pandemic I I was hoping we could fix like the Health Care system and the education like you know I I'm not I'm not a politics person I don't I don't I don't know um when it comes to languages the community is kind of right in terms of it's a very high burden to add something to a language so as soon as you add something you have a community of people building on it and you can't remove it okay and if there's a community of people that feel really uncomfortable with it then taking it slow I think is is is an important thing to do and there's no rush particularly if with something that's 25 years old and is very established and you know it's not like coming coming into its own um what about features so I I think that the issue with with Guido is that maybe this is a case where he realized it had outgrown him and it went from being or the language the language so python I mean Guido is amazing but but python isn't about Guido anymore it's about the users and to a certain extent the users own it and you know py Guido spent years of his life a significant fraction of his career on Python and from his perspective I imagine he's like well but this is my thing I should be be able to do the thing I think is right but you can also understand the users where they feel like you know this is my thing I use this like and um and I don't know it's it's a hard it's a hard thing but what if we could talk about leadership in this cuz it's so interesting to me I'm going to I'm going to make I'm going to wear hopefully somebody makes it if not I'll make it a w operator shirt because I think it represents to me maybe it's my Russian roots or something uh you know it's the burden of leadership like I feel like to push back I feel like progress can only like most difficult decisions just like you said there'll be a lot of divis divisiveness over especially in the passionate Community it just feels like leaders need to take those risky decisions that that if you like listen that with some nonzero probability maybe even a high probability would be the wrong decision but they have to use their gut and make that decision well this this this is like one of the things where you see uh amazing Founders the founders understand exactly what's happened and what how the company got there and are willing to say to we have been doing thing X the the last 20 years but today we're going to do thing why and they make a major pivot for the whole Company the company lines up behind them they move and it's the right thing but then when the founder dies the successor doesn't always feel that that um agency to be able to make those kinds of decisions yeah even though they're a CEO they could theoretically do whatever there's two reasons for that in my opinion or in many cases it's always different but um one of which is they weren't there for all the decisions that were made and so they don't know the principles in which those decisions were made and once the principles change you're you should be obligated to change what you're doing and change direction right and so if you don't know how you got to where you are it seems like gospel and you know you're not going to question it you may not understand that it really is the right thing to do so you just may not see it that's so brilliant I never thought of it that way like it's it's so much higher burden when as a leader you step into a thing that's already worked for a long time yeah yeah well and if you change it and it doesn't work out now you're the the person who screwed it up people always second guess that yeah and the second thing is that even if you decide to make a change even if you're theoretically in charge you're just you're just a person that thinks they're in charge meanwhile you have to motivate the troops you have to explain it to them in terms of understand you have to get them to buy into and believe in it because if they don't then they're not going to be able to make the turn even if you tell them you know their bonuses are going to be curtailed they're just not going to like buy into it you know and so there's only so much power you have as a leader and you have to understand what that what those limitations are are you still bdfl you've been bdfl of some stuff uh you're very heavy on the be the benevolent uh benevolent dictated for Life uh I guess lvm you're still so I still lead the lvm world uh I mean what's the role of uh so then on Swift you said that there's a group of people yeah so if you contrast python with Swift right one of the reasons so everybody on the core team takes the role really seriously and I think we all really care about where Swift goes but you're almost delegating the final decision- making to the wisdom of the group and so it doesn't become personal and also when you're talking with the community so yeah some people are very annoyed at certain decisions get made um there's a certain faith in the process because it's a very transparent process and when a decision gets made a full rationale is provided things like this these are almost defense mechanisms to help both guide future discussions and provide case law kind like Supreme Court does about this decision was made for this reason and here's the rationale and what we want to see more of or less of um but it's a way to provide a defense mechanism so that when somebody's griping about it they're not saying that person did the wrong thing they're saying well this this thing sucks and and later they move on and they they get over it yeah the analogy of the Supreme Court I think is really is really good but then okay not to get person on the Swift team but like is there is there div like it just seems like it's impossible for their for division not to emerge well each each of the humans on the the Swift core team for example are different and the membership of the Swift core team changes slowly over time which is I think a healthy thing and so each of these different humans have different opinions trust me it's not it's not a sing singular consciousness of by any stretch of the imagination you've got three major organizations including Apple Google and sci-fi all kind of working together and um it's a small group of people but you need High trust you need again it comes back to the principles of what you're trying to achieve and understanding you know what what you're optimizing for and I think that starting with strong principles and working towards decisions is always a good way to both make wise decisions in general but then be able to communicate them to people so that they can buy into them and that that is hard and so you mentioned lvm lvm is uh going to be 20 years old uh this December so it's it's showing its own age you have like like a like a like a dragon cake plant or you have a no we should definitely do that yeah if we can have a uh pandemic cake pandemic cake everybody gets a slice of cake and it gets you know sent through email um but the uh uh but lvm has had tons of its own challenges over time too right and one of the challenges that um the lvm community has in my opinion is that it has a whole bunch of people that um have been working at lvm for 10 years right because this happen some somehow and lvm has always been one way but it needs to be a different way right and they've worked on it for like 10 years is a long time to work on something and you know you you suddenly can't see the faults in the thing that you're working on and lvm has lots of problems and we need to address them and we need to make it better and if we don't make it better then somebody else will come up with a better idea right and so it's just kind of of that age where the community is like in danger of getting too calcified and um and so I'm happy to see new projects joining and new things mixing it up you know Fortran is now a new a new thing in the Elum Community which is hilarious and good I've been trying to find uh on this little tangent find people who program in Cobalt or Fortran Fortran especially to talk to they're hard to find yeah yeah look to the uh scientific Community they still use forun quite a bit interesting thing you kind of mentioned with lvm or just in general that if something evolve you're not able to see the faults so do you uh fall in love with the thing over time or do you start hating everything about the thing over time well so so my my my personal Folly is that um I see maybe not all but many of the faults and they gr on me and I don't have time to go fix them yeah and they get magnified over time well and they may not get magnified but they never get fixed it's like sand underneath you you know it's just like raiding against you and it's like s underneath your fingernails or something it's just like you know it's there you can't get rid of it um and so the the problem is that if other people don't see it right nobody ever get like I can't go I don't have time to go write the code and fix it anymore but then uh people are resistant to change and so you say hey we should go fix this thing they're like oh yeah that sounds risky well is it the right thing or not are the challenges uh the group dynamics or is it also just technical I mean some of these features like yeah I think uh as an observer is almost like a fan in in the uh you know as a spectator of the whole thing it I don't often think about you know some things might actually be technically difficult to implement an example of this is we we built this new compiler framework called ml yes ml is this a whole new framework it's not many people think it's about machine learning the ml stands for multi-level because compiler people can't name things very well I guess can we can we dig into what ml IR is yeah so when you look at compilers compilers have historically been solutions for a given space so lvm is a it's really good for dealing CPUs let's just say at a high level you look at um Java Java has a jvm the jvm is very good for garbage collected languages that need Dynamic compilation and it's very optimized for specific space and so hotspot is one of the compilers that gets used in that space and that compiler is really good at that kind of stuff um usually when you build these domain specific compilers you end up building whole thing from scratch for each domain uh what's a domain so what what we what's this what's the scope of a domain Al so here I would say like if you look at Swift there's several different parts to the Swift compiler um one of which is covered by um the LM part of it there's also a highle piece that's specific to Swift and there's a huge amount of redundancy between those two different infrastructures and a lot of re reimplemented stuff that is similar but different what is llvm Define lvm is effectively an infrastructure so you can mix and match it in different ways it's built libraries you can use it for different things but it's really good at CPUs and gpus CPUs and like the tip of the iceberg on gpus it's not really great at gpus okay um but it turns out languages that that then use it to talk to CPUs it um and so it turns out there's a lot of Hardware out there that is custom accelerators so machine learning for example there are a lot of uh Matrix multiply accelerators and things like this there there's a whole world of Hardware synthesis so we're using ml to build circuits okay and so you're compiling for a domain of transistors and so what ml does is it provides a tremendous amount of compiler infrastructure that allows you to build these domain specific compilers in a much faster way and have the result be good if we're if we're thinking about the future now we're talking about like as6 like so anything yeah yeah so if we project into the future it's very possible that the number of these kinds of as6 very specific um infrastructure thing architecture things uh like multiplies exponentially I hope so yeah so that's ml so what ml what ml does is it allows you to build these compilers very efficiently right now one of the things that coming back to the lvm thing and then we'll go to Hardware is um lvm is is a specific compiler for specific domain mlr is now this very general very flexible thing that can solve lots of different kinds of problems so lvm is a subset of what ml does so m is I mean it's an ambitious project then yeah it's a very ambitious project yeah and so to make it even more confusing ml has joined the lvm umbrella project so it's part of the lvm family right um but where this comes full circle is now folks that work on the lvm part the classic part that's 20 years old um aren't aware of all the cool new things that have been done in the new the new thing that you know mlr was built by me and many other people that knew a lot about lvm and so we fixed a lot of the mistakes that lived in LV so now you have this community Dynamic where it's like well there's this new thing but it's not familiar nobody knows it it feels like it's new and so let's not trust it and so it's just really interesting to see the cultural social Dynamic that comes out of that and and you know I think it's super healthy because we're seeing the ideas percolate and we're seeing the technology diffusion happen as people get more comfortable with it they start to understand things in their own terms and this just gets to the it takes a while for ideas to propagate even though um they may be very different than what people are used to so maybe let's talk about that a little bit the world of Asic and well actually you're uh you're you have a new role at sci-fi what's that place about what is the vision sure uh for their vision for I would say the future of computing yeah so I lead the engineering and product teams at SciFi sci5 is a company who's was founded with this architecture called risk 5 risk 5 is a new instruction set instruction sets are the things inside of your computer that tell how to run things um x86 from Intel and arm from the arm company and things like this or other instruction sets I've talked to sorry interrupt I've talked to Dave Patterson who's super excited about risk 5 Dave Dave is awesome he's brilliant yeah yeah the uh risk five is distinguished by not being proprietary MH and so xa6 can only be made by Intel and AMD arm can only be made by arm they sell licenses to build arm ships to other companies things like this myips is another instruction set that is owned by the myips company now wave and it gets licensed out things like that um and so RIS 5 is an open standard that anybody can build chips for and so SciFi was founded by three of the founders of RIS 5 that designed and built it in Berkeley working with Dave um and so that was the The Genesis of the company scii today has some of the world's best r five cores and we're selling them and that's really great they're going into tons of products it's very exciting um so they're taking this uh thing that's open source and just being trying to be or are the best in the world at building these things yeah so here it's the specifications open source it's like saying tcpip is an open standard or C Is An Open standard but then you have to build an implementation of the standard and so sci5 on the one hand pushes forward and defined and pushes forward the standard on the other hand we have implementations that are best in class for different points in the space depending on if you want a really tiny CPU or if you want a really big beefy one that that uh is faster but it uses more area and things like this what about the actual manufacturer chip so like what where does that all fit I'm going to ask a bunch of dumb questions that's okay this is how we learn right uh and so uh what the the way this works is that there's generally a separation of the people who design the circuits than the people who manufacture them and so that you'll hear about Fabs like tsmc and Samsung and things like this that actually produce the chips but they take a design coming in and that design specifies how um how the you know you turn uh code for the chip into uh little rectangles that then use Photo lithography to make uh mask sets and then burn transistors onto a chip or onto a onto silicon rather well so and we're talking about Mass manufacturing so yeah they're talking about making hundreds of millions of parts and things like that yeah and so the the Fab handles the volume production things like that but um when you look at this problem um the interesting thing about the space when you look at it is that um these the steps that you go from designing a chip and writing the quote unquote code for it and things like verog and languages like that down to what you hand off to the Fab is a really well studied really old problem mhm um tons of people have worked on it lots of smart people have built systems and tools um these tools then have generally gone through Acquisitions and so they've ended up at three different major companies that build and sell these tools they're called Eda tools like for electronic design automation um the problem with this is you have huge amounts of fragmentation you have loose standards um and the tools don't really work together so you have tons of duct tape and you have tons of uh lost productivity now these are uh these are tools for Designing so the risk five is a instruction like what is risk five like how deep does it go how how how much does it touch the hardware how much does it Define how much of the hardware is yeah so RIS RIS five is all about um given a CPU so the the the processor and your computer how does the the compiler like Swift compiler the C compiler things like this how does it make it work so it's what is the assembly code and so you write risk five assembly instead of xa6 assembly for example but it's a set of instructions as opposed to set of instructions yeah why why do you say it tells you how the compiler works the sorry it's what the compiler talks to okay yeah and then uh the tooling you mentioned the disperate tools are for what for for when you're building a specific chip so RIS five in Hardware in Hardware yeah so so RIS five you can buy rist 5 Core from scif and say Hey I want to have a certain number of run a certain number of gigahertz I want it to be this big I want to be have these features I want to have um like I want floating point or not for example um and then what you get is you get a description of a CPU with those characteristics now if you want to make a chip you want to build like an iPhone chip or something like that right you have to take both the CPU but then you have to talk to memory you have to have timers iOS a GPU other components and so you need to pull all those things together into what's called an Asic an application specific grade circuit so a custom chip and then you take that design and then you have to transform it into something that the Fabs like tsmc for example know how to turn take to production got it so but yeah okay and and so that process I will I can't help but see it is is a big compiler okay it's a whole bunch of compilers written without thinking about it through that lens isn't isn't the universe a compiler in that like comp compilers do two things they represent things and transform them yeah and so there's a lot of things that end up being compilers but this is this is a space where we're talking about design and usability and the way you think about things the way things composed correctly it matters a lot and so sci-fi is investing a lot into that space and we think that there's a lot lot of benefit that can be made by allowing people to design chips faster get them to Market quicker and um scale out because um you know it the alleged more end of Mor's law uh you've got this problem of uh you're not getting free performance just by waiting another year for a faster CPU and so um you have to find performance in other ways and one of the ways to do that is with custom accelerators and other things and hardware and and so well we'll talk a little about uh a little more about as6 but um do you see that a lot of people a lot of companies will try to have a like different sets of requirements that this whole process to go for so like like almost different car companies might use different uh and like different uh PC manufacturers like so is this like is risk 5 um in this whole process is it potentially the future of all Computing devices yeah I think that so if you look at risk 5 and step back from the Silicon side of things RIS 5 is an open standard and one of the things that has happened over the course of decades if you look over the long Arc of computing somehow became decades old yeah is that you have uh companies that come and go and you have instruction sets that come and go like one example of this out of many is uh uh sun with spark yeah Sun one away spark still lives on it Fujitsu but we have uh HP had this instruction set called PA risk so P risk was its big server business and had tons of customers they decided to move to this called itanium from Intel yeah this didn't work out so well yeah right and so you have this issue of you're making many billion doll Investments on instruction sets that are owned by a company and even companies as big as Intel don't always execute as well as they could they have their own issues um HP for example decided that it wasn't in their best interest to continue investing in the space because it was very expensive and so they make technology decisions or they make their own business decisions and this means that a customer what do you do you've sunk all this time all this engineering all the software work all these you've built other products around them and now you're stuck right what risk 5 does is it provides you more optionality in the space because if you buy uh an implementation of RIS five from SciFi and you should they're the best ones yeah um uh but if something bad happens to SciFi in 20 years right well great you can turn around and buy r five core from somebody else and there's an ecosystem of people people that are all making different risk five cores with different trade-offs which means that if you have more than one requirement if you have a family of products you can probably find something in the rist five space that fits your needs whereas with if you're talking about xa6 for example it's Intel's only going to bother to make certain classes of devices right I see so uh maybe a weird question but like if SciFi is uh like infinitely successful in the next 20 30 years what does the world look like so like how does the world of computing change so too much diversity in Hardware instruction sets I think is bad like we have a lot of people that are using um lots of different instruction sets particularly in the embedded the like very tiny microcontroller space the thing in your toaster um that uh that are just weird and different for historical reasons and so the compilers and the tool chains and the languages on top of them uh aren't there right and so the Developers for that software have to use really weird tools because the ecosystem that supports is not big enough so I expect that will change right people will have better tools and better languages better features everywhere that then can service many different points in the space um and I think RIS 5 will progressively um eat more of the ecosystem because it can scale up it can scale down sideways left right it's very flexible and very well considered welld designed and instruction set um I think when you look at sci-fi tackling silicon and how people build chips which is a very different space um that's where you say I think we'll see a lot more custom chips and that means that you get much more battery life you get better better tuned solutions for your iot thingy you get you get people that move faster you get the ability to have faster time to market for example so how many custom so first of all on iot of things do you see the number of smart toasters increasing exponentially so uh and and if you do like how much customization per toaster is there do all toasters in the world run the same uh silicon like the same design or is it different companies have different design like how how much customization is possible here well a lot of it comes down to cost right and so the way that chips work is you end up paying by the one one of the factors is the the size of the Chip And so what ends up happening just from an economic perspective is there's only so many chips that get made in any year of a given design and so often what customers end up having to do is they end up having to pick up a chip that exists that was built for somebody else so they can then ship their product and the reason for that is they don't have the volume of the iPhone they can't afford to build a custom chip however what that means is they're now buying an off-the-shelf chip that isn't really good that isn't a perfect fit for their needs and so they're paying a lot of money for it because they're buying silicon that they're not using well if you now reduce the cost of Designing the chip now you get a lot more chips and the more you reduce it the the easier it is to design chips um The More The World Keeps evolving and we get more AI accelerators we get more other things we get more uh standards to talk to we get 6G right you get you get you get changes in the world that you want to be able to talk to these different things there's more diversity in the cross product of features that people want and um that drives differentiated chips in different in another Direction and so nobody really knows what the future looks like but um but I think that there's a lot of silicon in the future speaking of the future uh you said Mo's law allegedly is dead so do you think do you agree with uh uh Dave Patterson and and many folks that Mo's law is dead or do you agree with Jim Keller who says uh who's uh standing at the Helm of the pirate ship saying it's uh still alive it's still alive yeah also I agree with what they're saying and different people are interpreting the anor's law in different ways yeah so Jim would say you know there's another thousand X left in physics and we can we can continue to squeeze the stone and make it faster and smaller and smaller geometries and all that kind of stuff uh he's right so Jim Jim is is absolutely right that there's a ton of ton of progress left and we're not at the limit of physics yet um uh that's not really what mors law is though if you look at what mors law is is that it's a very simple uh evaluation of okay well you look at the cost per um I think it was cost per area and the most economic point in that space and if you go look at the the the now quite old paper that describes this um mors law has a specific economic aspect to it and I think this is something that Dave and others often point out and so on a technicality that's right um I look at it from so I can acknowledge both of those viewpoints they're both right they're both right I'll give you a third wrong yeah Viewpoint that may be right in its own way which is um single threaded performance doesn't improve like it used to and it used to be back when you got a uh you know a pennium 66 or something and the year before you had a pennium 33 and now it's twice as fast MH right well it was twice as fast at doing exactly the same thing okay like literally the same program ran twice as fast you just wrote a check okay and waited a year year and a half well so that's what a lot of people think about Moors law and I think that is dead and so what we're seeing instead is we're pushing we're pushing people to write software in different ways and so we're pushing people to write Cuda so they can get GPU compute and the the thousands of cores on GPU we're talking about C programmers having to use P threads because they now have you know 100 100 threads or 50 cores in a machine or something like that um you're now talking about machine learning accelerators they're now domain specific and when you look at these kinds of use cases you can still get performance um and Jim will come up with cool things that uh utilize the Silicon in new ways for sure but you're also going to change the programming model right and now when you start talking about changing the programming model that's when you come back to languages and things like this too because often what you see is um like you take the C programming language right the C programming language is designed for CPUs and so if you want to talk to a GPU now you're talking to its cousin Cuda okay Cuda is a different thing with a different set of tools a different world a different way of thinking and we don't have one world that scales and I think that we can get there we can have one world that scales in a much better way on a small tangent then I think most programming languages are designed for CPUs for single core even just in their Spirit even if they allow for paralyzation so what does it look like for programming language to have um paralyzation or massive parallelization as it's like first principle so the canonical example of this is the hardware design world so verog vhdl these kinds of languages they're what's called a uh highle synthesis language this is the thing people design chips in and when you're designing a chip it's kind of like a brain where you have infinite parallelism like you've got you're you're you're like laying down transistors transistors are always running okay yeah and so you're not saying run run this transistor then this transistor than this transistor it's like your brain like your neurons are always just doing something they're not clocked right they're they're just they're just doing they're they're doing their thing and so when you design a chip or when you design a CPU when you design a CPU when you design when you're laying down the transistors uh similarly you're talking about well okay well how do these things communicate and so these languages exist verog is um a kind of mixed example of that none of these languages are really great either very low level yeah yeah they're very low level and abstraction is necessary here and there's different different approaches at that and it's a it's itself a very complicated world but um but it's implicitly parallel and so having that as a as the domain that you uh program towards makes it so that by default you get parallel systems if you look at Cuda Cuda is a point halfway in the space where in Cuda when you write a Cuda kernel for your GPU it feels like you're writing a scaler program so you're like you have ifs you have for Loops stuff like this you're just writing normal normal code but what happens outside of that in your driver is that it actually is running you on like a thousand things at once right and so it's it's parallel but it has pulled it out of the programming model and so so now you as a programmer are working at a in a simpler world and it's solved that for you right how do you take the language like Swift um you know if we we think about gpus but also ASX maybe if we can dance back and forth between hardware and software uh is you know how do you design for these features to be able to program make it a first class citizen to be able to do like Swift for tensor flow to be able to do machine learning on current Hardware but also future Hardware like uh dpus and all kinds of as6 that I'm sure will be popping up more yeah well so so a lot of this comes down to this whole idea of having the nuts and bolts underneath the covers that work really well so you need if you're talking to tpus you need you know ml or xlaa or one of these compilers that talks to tpus to build on top of okay and if you're talking to circuits you need to figure out how to lay down the transistors and how to organize it and how to set up clocking and like all the domain problems that you get with uh circuits then you have to decide how to explain it to a human what is the UI right and if if you do it right that's a library problem not a language problem and that works if you have a library or a language which allows your library to write things that feel native in The Language by implementing libraries because then you can innovate in programming models without having to change your syntax again and like have to invent new code formatting tools and like all the other things that languages come with and this this gets really interesting and so um if you look at the space the interesting thing once you separate out syntax becomes what is that programming model and so do you want the Cuda style I write one program and it runs many places the um do you want the implicitly parallel model how do you reason about that how do you give developers you know chip Architects the the ability to express their intent and that comes into this whole design question of how do you detect bugs quickly so you don't have to tape out a chip to find out it's wrong ideally right how do you and and you know this is a spectrum how do you make it so that people feel productive so their turnaround time is very quick all these things are really hard problems and um in this world I I think that not a lot of effort has been put into that design problem and thinking about the layering in other pieces well you've uh on the topic of concurrency you've written the Swift concurrency Manifesto I think it's it's kind of interesting anything that uh has the word manifesto in is very interesting can you summarize the key ideas of U each of the five parts you written about so what is a Manifesto yes how about we start there uh so in the Swift Community we have this um problem which is on the one hand you want to have relatively small proposals that you can kind of fit in your head you can understand the details at a very fine grain level that move the world forward but then you also have these big arcs okay and often when you're working on something that is a big Arc but you're tackling in small pieces you have this question of how do I know I'm not doing a random walk where are we going like how does this add up furthermore when you start that first the first small step what terminology do you use how do we think about it what is better and worse in the space what are the principles what are we trying to achieve and so what a Manifesto in the Swift Community does is it starts to say hey well let's step back from the details of everything let's paint a broad picture to talk about how what we're trying to achieve let's give an example design Point let's try to paint the big picture so that then we can zero in on the individual steps and make sure that we're making good progress and so the Swift concurrency Manifesto is something I wrote three years ago it's been a while maybe maybe more um trying to do that for for Swift and concurrency and it starts with some fairly uh simple things like making the observation that when you have multiple different computers or multiple different threads that are communicating it's best for them to be asynchronous right and so you need things to be able to run separately and then communicate with each other and this means asynchrony and this means that uh you need a way to modeling asynchronous communication uh many languages have features like this uh asyn a weight is a popular one and so that's what I think is very likely in Swift um but as you start building this Tower of abstractions it's not just about how do you write this you then reach into the how do you get memory safety because you want correctness you want debuggability and Sanity for developers and how do you get uh that memory safety into um into the language so if you take a language like go or uh C or any of these languages you get what's called a race condition when two different threads or go routines or whatever touch the same point in memory right this is a huge like maddening problem to debug because uh it's not reproducible generally and so there's tools there's a whole ecosystem of solutions that built up around this but it's it's a huge problem when you're writing concurrent code and so with Swift uh this whole value sematics thing is really powerful there because it turns out that math and copies actually work even in concurrent worlds and so um you get a lot of safety just out of the box but there are also some hard problems and it talks about some of that um when you start building up to the next level up and you start talking Beyond memory safety you have to talk about what is a programmer model how does a human think about this so a developer that's trying to build a program think about this and it proposes a really old model with a new spin called actors actors are about saying we have islands of single threaded logically so you write something that feels like it's one programming one program running in a unit and then it communicates asynchronously with other other things and so making that expressive and natural feel good be the first thing you reach for and being safe by default is a big big part of the design of that proposal when you start going beyond that now you start to say cool well these things that communicate asynchronously they don't have to share memory well if they don't have to share memory and they're sending messages to each other why do they have to be in the same process these things should be able to be in different processes on your machine and why just processes well why not different machines and so now you have a very nice gradual transition towards distributed programming and of course when you start talking about the the big the big future the the manifesto doesn't go into it but uh accelerators are asyn things you talk to asynchronously by sending messages to them and how do you program those well that that gets very interesting um that's not that's not in the proposal so but and uh how much do you want to make that explicit like the control of that whole process explicit to the programmer yeah good question so when when you're designing any of these kinds of features or language features or even libraries you have this really hard trade-off that you have to make which is how much is it magic or how much is it in the human's control how much can they predict and control it what do you do when the default case is the wrong case okay and so when you're designing a system um uh I won't name names but there there are systems where um you it's really easy to get started and then you you jump so let's pick like logo okay so something like this so it's really easy get start it's really designed for uh teaching kids but as you get into it you hit a ceiling yeah and then you can't go any higher and then what do you do well you have to go switch to a different world and rewrite all your code and this logo is a silly example here this exists in many other languages uh with python you would say uh uh like concurrency right so python has the global interpreter lock so threading is challenging in Python and so if you if you start writing a large scale application in Python and then you need concurrency you're kind of stuck with the series of bad trade-offs right um uh there's other ways to go where you say like voice all the all the complexity on the user all at once right and that's also bad in a different way and so what what I what I prefer is building a simple model that you can explain that then has an escape hatch so you get in you have guard rails you uh memory safety works like this in Swift where you can start with you like by default if you use all the standard things it's memory safe you're not going to shoot your foot off but if you want to get a uh a c-level pointer to something you can explicitly do that but by default it's uh there's guard rails there's guard rails okay so but like you know uh whose job is it to figure out which part of the code is paralyzable um so in the case of the proposal it is the human's job so they decide how to architect their application and then uh the runtime in the compiler is very predictable and so this this is in contrast to um like there's a long body of work including on Fortran for auto parallelizing compilers and um this is an example of a bad thing and my so as a compiler person I can rag on compiler people um often compiler people will say cool since I can't change the code I'm going to write my compiler that then takes this unmodified code and makes go way faster on this machine MH okay application develop and so it does pattern matching it does like really deep analysis compiler people are really smart and so they like want to like do something really clever and tricky and you get like 10x speed up by taking like an array of structures and turn it into a structure of arrays or something because it's so much better for memory like there's bod like tons of Tricks yeah um they love optimization yeah you love optimization everyone loves optimization everyone loves it well and it's it's just this promise of build with my compiler and your thing goes fast yeah right but here here's the problem Lex you write you write program M you run it with my compiler it goes fast you're very happy wow it's so much faster than the other compiler yeah then you go and you add a feature to your program or you refactor some code and suddenly you got a 10x loss in performance well why what just happened there what just happened there is you the theistic the the the pattern match and the compiler whatever analysis it was doing just got defeated because you didn't inline a function or or or something right as a user you don't know you don't want to know that was the whole point you don't want to know how the compiler works you don't want to know how how the memory hierarchy works you don't want to know how it got parallelized across all these things you wanted that abstractor away from you but then the magic is lost as soon as you did something and you fall off a performance cliff and now you're in this funny position where what do I do I don't change my code I don't fix that bug it cost 10 10x performance now what do I do well this is the problem with unpredictable performance right if if you care about performance predictability is a very important thing and so um and so what the what the proposal does is it provides a architecture patterns for being able to lay out your code gives you full control over that makes it really simple so you can explain it and then um and then if you want to scale out in different ways you have full control over that so in your sense the intuition is for a compiler too hard to do automated parallelization like you know cuz the compilers do stuff automatically that's incredibly impressive for other things right but for parallelization we're not even we're not close to there well it it depends on the programming model so compile there's many different kinds of compilers and so if you talk about like a c compiler or a swift compiler or something like that where you're writing imperative code parallelizing that and reasoning about all the pointers and stuff like that is very is a very difficult problem now if you switch domains so there's this cool thing called machine learning right so the machine the machine learning nerds among other endearing things like you know solving cat detectors and other things like that um have done this amazing breakthrough of producing a programming model operations that you compose together mhm that has raised level of abstraction high enough that suddenly you can have autop paralyzing compilers you can write and model using tensor flow and have it run on 1,24 nodes of a TPU yeah that's true I didn't even think about like you know CU there's so much flexibility in the design of architectures that ultimately boil down to a graph that's paralyzable for you par for you and and if you think about it that's pretty cool and you think about batching for example as a way of being able to exploit more parallelism yeah like that's a very simple thing that now is very powerful that didn't come out of the programming language nerds right those people like that came out of people that are just looking to solve a problem and use a few gpus and organically developed by the community of people focusing on machine learning and it's an incredibly power powerful abstraction layer that enables the compiler people to go and exploit that and you can drive supercomputers from python that's that's pretty cool that's amazing so just to pause on that I cuz I'm not sufficiently low level I forget to admire the beauty and power of that but um maybe just to linger on it like what what does it take to run a neural network fast like how hard is that compilation it's really hard um so we just skipped you said like it's amazing that that's a thing but yeah how hard is that of a thing it's it's hard and I I would say that not all the systems are really great including the ones I help build so there's a lot of work left to be done there is it the compiler nerds working on that or is it a whole new group of people well it's it's a full stack problem including compiler people um in including apis so like Caris and the the the the module API and pytorch and Jack and there's a bunch of people pushing on all the different parts of these things because when you look at it is it's both how do I express the computation do I stack up layers well cool like setting up a linear sequence of layers is great for the simple case but how do I do the hard case how do I do reinforcement learning well now I need to integrate my application logic in this right then it's you know the next level down of how do you represent that for the runtime how do you get Hardware abstraction and then you get to the next level down of saying like forget about abstraction how do I get the Peak Performance out of my TPU or my iPhone accelerator or whatever right all these different things and how and so this is a layered problem with a lot of really interesting uh design and work going on in the space and a lot of really smart people working on it uh machine learning is a very well-funded area of investment right now and so there's a lot of progress being made so how much Innovation is there on the lower level so closer to the to the as6 so redesigning the hardware or redesigning concurrently compilers with that Hardware is that like if you were to predict the biggest uh you know the equivalent of Moors law improvements in the inference in the training of your own networks and just all of that where is that going to come from you think sure you get scalability have different things and so you get um you know Jim Keller shrinking process technology you get 3 nanometer instead of five or seven or 10 or 28 or whatever um and so that that marches forward that provides improvements you get uh architectural level performance and so the you know a TPU with a matrix multiply unit and a systolic array is much more efficient than having a scaler core doing multiplies and adds and things like that you then get um uh uh system level improvements so how you talk to memory how you talk across a cluster of machines how you scale out how you have fast interconnects between machines you then get system level programming models so now that you have all this Hardware how to utilize it you then have algorithmic breakthroughs where you say hey wow cool instead of training in uh you know resonant 50 and uh a week I'm now training it in you know 25 seconds yeah and Comin It's a combination of uh you know new new optimizers and new new new just training regimens and different different approaches to train and and all of these things come together to to push the world forward that that was a a beautiful exposition of but if you were to uh Force to bet all your money on one of these would you why do we have to that's unfortunately we have people working on all this it's an exciting time right so I mean you know open the eye did this little paper showing the algorithmic Improvement you can get has been you know improving exponentially uh I haven't quite seen the same kind of analysis on other layers of the stack I'm sure it's also improving significantly I just it's a it's a nice intuition Builder I mean there's a reason why Moore's Law that's the beauty of Mo's law is somebody writes a paper that makes a ridiculous prediction yeah and it you know becomes reality in a sense there's there's something about these narratives when you uh uh when Chris L on a silly little podcast makes bets all his money on a particular thing somehow it can have a ripple effect of actually becoming real that's an interesting aspect of it cuz like it might have been uh you know we focus with Mor's law most of the Computing industry really really focused on the hardware I mean software Innovation I don't know how much software Innovation there was in terms of Intel giveth Bill takes away right yeah I mean compiler has improved significantly also right well not not really so actually I mean so I'm joking about how uh software's gotten slower pretty much as fast as Hardware got better at least through the 90s um there's another joke another law in compilers which is called uh I think it's called probstein law which is uh compilers double the performance of any given code every 18 years so they move slowly yeah well so well well yeah it's exponential also yeah you're making progress but but there again it's not about um the the power of compilers is not just about how do you make the same thing go faster it's how do you unlock the new hardware right a new chip came out how do you utilize it you say oh the programming model how do we make people more productive how do we how do we uh like have better error messages even such mundane things like how do I generate a very specific error message about your code actually makes people happy because then they know how to fix it right it comes back to how do you help people get their job done yeah and yeah and then in this world of exponentially increasing smart toasters how do you uh expand Computing to uh to all all these kinds of devices do you see this world where just everything's a Computing surface you see that possibility just everything a computer yeah I don't see any reason that that couldn't be achieved it turns out that sand goes into glass and glass is pretty useful too and you know like why not why not so uh very important question then if um if we're living in a simulation and the simulation is running a computer like what what's the architecture of that computer do you think so you're saying is it is it a Quantum system is it a yeah like this whole Quantum discussion is it needed or can can we run it on a on a you know with a risk 5 architecture uh a bunch of CPUs I think it comes down to the right tool for the job okay and so and what's the compiler yeah exactly that's that's my question how do I get that job be the universe compiler um uh and so there as far as we know Quantum Quantum Quantum systems are the bottom of the T pile of so far yeah and so we don't know efficient ways to implement Quantum systems without using quantum computers yeah and that's totally outside of everything we've talked about Quantum but who runs that quantum computer yeah right so if it if it if we really are living in a simulation then is it bigger quantum computers is it different ones like how how does that work out how does that scale well it's it's the same size it's the same size but then but then the thought of the simulation is you don't have to run the whole thing that you know we humans are cognitively very limited checkpoints checkpoints yeah and uh and if we the point at which we human so you basically do minimal amount of uh what is it uh Swift does um on right copy copy on right yeah so you only you only adjust the simulation par parallel universe theories right and so and so every time a a decision is made somebody opens the Shor in your box then there's a fork this could happen and then uh thank you for uh for considering the possibility but yeah so it may not require you know the entirety of the universe to simulate it but it's um interesting to think about uh as we create this this higher and higher Fidelity systems but I do want to ask on the on the quantum computer side because everything we've talked about with uh with you work with sci-fi with every with compilers none of that includes quantum computers right that's true so have you ever thought about uh what a you know this whole serious engineering work of quantum computers looks like of compilers of architectures all of that kind of stuff so I've looked at a little bit I know almost nothing about it which means that at some point I will have to find an excuse to get involved because that's how do you think do you think that's a thing to be like is was your little senses of the timing of when to be involved is it not yet well so so the thing I do really well is I jump into messy systems and figure out how to make them figure out what the truth in the situation is try to figure out what um what the unifying theory is how to like Factor the complexity how to find a beautiful answer to a problem that um has been well studied and lots of people have bashed their heads against it I don't know that quantum computers are mature enough and accessible enough to be um figured out yet right and um the uh I think the open question with quantum computers is is there a useful problem that gets solved with a quantum computer that makes it worth the economic cost of like having one of these things and having having Legions of people that that that uh set it up you go back to the 50s right and there's the projections of the world can will only need seven seven computers right well and part of that was that people hadn't figured out what they're useful for what are the algorithm we want to run what are the problems to get solved and this comes back to how do we make the world better either economically or making somebody's life better or like solving a problem that wasn't solved before things like this and um I think that just we're a little bit too early in that development cycle because it's still like literally a science project not any negative connotation right it's literally a science project and um the progress there is amazing and so I don't know if it's 10 years away if it's 2 years away exactly where that breakthrough happens but um you look at uh machine learning it we went through a few winners um before the Alex net transition and then suddenly it had its breakout moment and that was the Catalyst that then drove the talent flocking into it that's what drove the economic applications of it that's what drove the um the technology to go faster because you now have more Minds thrown at the problem this is what caused uh like a serious knee and uh deep learning and the algorithms that we're using and um and so I think that's what Quantum needs to go through and so right now it's in that that formidable finding itself getting the the like literally the physics figured out and um and and then has to figure out the application that makes this useful like right now I'm I'm not skeptical that I think that will happen I think it's just you know 10 years away something like that I forgot to ask what programming language do you think the simulation is written in O probably lisp so not sft like if you were to bet you were to bet uh I'll just leave it at that so I mean we've mentioned that you work with all these companies we we've talked about all these projects it's kind of if we just step back and zoom out about the way you did that work and we look at covid times this pandemic we're living through that may if I look at the way Silicon Valley folks are talking about it the way MIT is talking about it this might last for a long time uh not just the virus but the the remote nature the economic impact I all it yeah yeah it's it's going to be a mess do you think uh what's your prediction I mean from sci-fi to Google to uh uh to just all the places you worked in just Silicon Valley you're in the middle of it what do you think is how is the whole place going to change yeah so I mean I I really can only speak to the tech perspective I am in that bubble um I think it's going to be really interesting because the you know the zoom culture of being remote and on video chat all the time has really interesting effects on people so on the one hand it's a great normalizer it's a normalizer that I think will help communities of people that have traditionally been underrepresented uh because now you're taking in some cases a face off you don't have to have a camera going right and so you can have conversations without physical appearance being part of the part of the dynamic which is pretty powerful you're taking remote employees that have already been remote and you're saying you're now on the same level and foot footing as everybody else nobody gets whiteboards you're not going to be the one person that doesn't going to be participating in the Whiteboard conversation and that's pretty powerful um you've got uh you're forcing people to think uh asynchronously in some cases because it's harder to just just get people physically together and the bumping into each other forces people to find new ways to solve those problems s and I think that that leads to more inclusive Behavior which is good um on the other hand it's also it just sucks right and so um the the nature the the actual communication or just sucks being not in with people like on a daily basis and collaborating with them yeah all of that right I mean everything this whole situation is terrible um what I meant primarily was the um I think that that most humans like working physically with humans I think this is something that not everybody but many people are programmed to do and I think we get something out of that that it's very hard to express at least for me and so maybe this isn't true of everybody but um and so the question to me is you know when you get through that time of adaptation right you get out of March and April and you get into December and you get into next march if it's not changed right it's already terrifying well you you think about that and you think about what is the nature of work yeah right how do how do we adapt and humans are very adaptable species right we can we can learn things and when we're forced to and there's a catalyst to make that happen and so what is it that comes out of this and are we better or worse off right I think that you know you look at the Bay Area housing prices are insane well why well there's a high incentive to be physically located because if you don't have proximity you end up paying for it and commute right and there's there has been huge social social pressure in terms of like you will be there for the meeting right or whatever scenario it is and I think that's going to be way better I think it's going to be much more than Norm to have remote employees and I think this is going to be really great do you uh do you have friends or do you hear of people moving yeah I I know one family friend that moved they moved back to Michigan and uh you know they were a family with three kids living in a small apartment and like we're going insane right and they're in Tech uh husband works for Google so first of all friends of mine have are in the process of or are have already lost the business the thing that represents their passion their dream it could be small entrepreneur projects but it could be large businesses like people that run gyms like do restaurants like tons of things yeah so but also people like look them at themselves in the mirror and ask the question of like what do I want to do in life for some reason they don't they haven't done it until Co like they really asked that question and that results often in moving or leaving the company you're with starting your own business or transitioning to different company do you think we're going to see that a lot like in um I I well I can't speak to that I mean we're definitely going to see it at a higher frequency than we did before um just because I think what you're trying to say is there are decisions that you make yourself and big life decisions that you make yourself and like I'm going to like quit my job and start a new thing there's also decisions that get made for you like I got fired from my job what am I going to do right and that's not a decision that you think about but you're forced to act okay and so I think that those you're forced to act kind of moments where like you know Global pandemic comes and wipes out the economy and now you're business doesn't exist I think that does lead to more reflection right because you're less anchored on what you have and it's not a what do I have to lose versus what do I have to gain AB comparison it's more of a fresh slate cool well I could do anything now do I want to do the same thing I was doing did that make me happy is this now time to go back to college and take a class and learn learn a new skill is this is this a time to uh spend time with family if you can afford to do that is this time to like you know literally move in with parents right I mean all these things that were not normative before suddenly become I think uh very the value system has changed and I think that's actually a good thing in the short term at least because um it leads to you know there's kind of been an over optimization along one one set of priorities for the world and now maybe we'll get to a more balanced and more interesting world where the people are doing different things I think it could be good I think there could be more Innovation that comes out of it for example what do you think about the all the social chaos we're in the middle of like it sucks you think it's uh let me ask you I hope you think it's all going to be okay well I think Humanity survive um the from an existential like we're not all going to kill Yeah well yeah I don't think the virus is going to kill all all the humans um I don't think all the humans are going to kill all the humans I think that's unlikely but um I I look at it as uh um progress requires a catalyst right so so you need you need a reason for people to be willing to do things that are uncomfortable I think that the US at least but I think the world in general is a pretty uh uh unoptimal place to live in for a lot of people and I think that what we're seeing right now is we're seeing a lot of unhappiness and because because of all the pressure because of all the the Badness in the world that's coming together it's really kind of igniting some of that debate that should have happened a long time ago right I mean I think that we'll see more progress you're asking about offline you're asking about politics and wouldn't be great if politics move faster because there's all these problems in the world and we can move it well people are intentional or inherently uh conservative and so if you're talking about conservative people particularly if they have heavy burdens on their shoulders because they represent literally thousands of people um it makes sense to be conservative but on the other hand when you need change how do you get it the global pandemic will probably lead to some change and it's not a directed it's not a directed plan but I think that it leads to people asking really interesting questions and some of those questions should have been asked a long time ago well let me know if if you observed this as well something that's bothered me in the machine Learning Community I'm guessing it might be prevalent in other places is um something that feels like in 2020 increase level of toxicity like people are just quicker to pile on they just be they're just harsh on each other to to like mob uh pick a person that screwed up and like make it a big thing yeah and uh is there something that we can like have you observed that in other places is there is there some way out of I think there's a inherent thing in humanity that's kind of an Us Versus Them thing which is that you want to succeed and how do you succeed well it's relative to somebody else and so what what's happening in at least in some part is that with the internet and with online communication the world's getting smaller right and so we're having some of the the social ties of like my NE My Town versus your Town's football team right turn into much larger larger and yet shallower problems and uh people don't have time the incentives are clickbait and like all these things kind of really really feed into this machine and I don't know where that goes um yeah I mean the reason I think about that I I mentioned to you this offline a little bit but uh you know I have uh a few difficult conversations scheduled some of them political related some of them within the community uh difficult personalities that went through some stuff I mean one of them I've talked before I will talk again is Yan laon he got of a little bit of crap on Twitter for uh for uh talking about a particular paper and the bias within a data set and then there's been a huge uh in my view and I'm willing comfortable saying it uh irrational ere exagger ated pylon on his comments because uh he made pretty basic comments about the fact that if there's bias in the data there's going to be bias in the results so we should not have bias in the data but people piled on to him because he said he trivialize the problem of bias like it's a lot more than just bias and the data but like yes that's a very good point but that's that's not what he was saying that's not what he was saying and the response like the imply response that he's basically sexist and racist um is uh is something that completely drives away the possibility of nuance discussion one nice thing about like a podcast long form uh conversation is you can talk it out you can lay your reasoning out and even if you're wrong you can still show that you're a good human being underneath it you know your point about you can't have a productive discussion well how do you get to that point where people can turn they can learn they can listen they can think they can engage versus just being a a shallow like like and then keep moving right and I don't think that that uh progress really comes from that right and I don't think that um one should expect that I think that you you'd see that as reinforcing individual circles and the US versus them thing and I think that's fairly divisive yeah I think uh there's a big role in like the people that bother me most on Twitter when I observe things is not the people who get very emotional angry like over the top it's the people who like prop them up it's all the it's it's that I think what should be the we should teach each other is to be sort of empathetic the the thing that it's really easy to forget particularly on like Twitter or the internet or in email is that sometimes people just have a bad day yeah right you have a bad day or you're like I've been in the situation where it's like between meetings like fire off a quick response to an email because I want to like help get something unblocked phrase it really objectively wrong I screwed up and suddenly this is now something that sticks with people and it's not because they're bad it's not because you're bad it's just psychology of like you said a thing um it sticks with you you didn't mean it that way but it really impacted somebody because the way they interpreted it and this is just an ECT of working together as humans and I have a lot of optimism in the long term the very long term about what we as Humanity can do but I think that's going to be it's just always a rough ride and you you came into this by saying like what do Co and all the the social Strife that's happening right now mean and I think that it's really bad in the short term but I think it'll lead to progress and for that I'm very thankful yeah it's painful in the short term though well yeah I mean people are out of jobs like some people can't eat like it's horrible and um but but you know it's progress so we'll see we'll see what happens I mean the the real question is when you look back 10 years 20 years 100 years from now how do we evaluate the decisions are being made right now I think that's really the way you can frame that and look at it and you say you know you integrate across all the short-term horribleness that's happening and you look at what that means and is the you know Improvement across the world or the regression across the world uh significant enough to make it a good or bad thing I think that's the question yeah and for that it's good to study history I'm one of the big problems for me right now is I'm reading the rise and fall of the Third Reich Light reading so it's everything is just I just see parallels and every I mean it's it's you have to be really careful not to overstep it but just the the thing that worries me the most is the pain that people feel when of com when a few things combined which is like economic depression which is quite possible in this country and then just being disrespected yeah uh by in some kind of way which the German people were really disrespected by most of the world uh like in a way that's over the top that something can it can build up and then all you need is a charismatic leader uh to to go either positive or negative and both work as long as they're charismatic and there it's taking advantage of again that that inflection point that the world's in and what they do with it could be good or bad and so it's a good way to think about times now like on an individual level what we decide to do is when when history is written you know 30 years from now what happened in 2020 probably history's going to remember 2020 yeah I think so either for good or bad and it's like up up to us to write it so it's good well one of the things I've observed that I find F is most people act as though the world doesn't change you make decision knowingly right you make a decision where you're predicting the future based on what you've seen in the recent past and so if something's always been H it's rained every single day then of course you expect it to rain today too right on the other hand the world changes all the time yeah constantly like for better and For Worse right so the question is if you're interested in something that's not right what is the INF point that led to a change and you can look to history for this like what is what is the Catalyst that led to that that explosion that led to that bill that led to the like you you can kind of work your way backwards from that and maybe if you pull together the right people and you get the right ideas together you can actually start driving that change and doing in a way that's productive and hurts fewer people yeah like a single person single event can turn all of absolutely everything starts somewhere and often It's a combination of multiple factors but but yeah this is these these things can be engineered that's actually the optimistic view that I'm I'm a long-term Optimist on pretty much everything and human nature you know we can look to all the negative things that that Humanity has all the pettiness and all the like self self-serving and the um just the the cruelty right the the biases the just humans can be very horrible but on the other hand we're capable of amazing things and um and the progress across you know hundred-year chunks is striking and even across decades it's we've come a long ways and there's still a long ways to go but that doesn't mean that we've stopped yeah the kind of stuff we've done in the last 100 years is is unbelievable it's kind of scary to think what's going to happen next 100 year it's scary like exciting like scary in a sense that it's kind of sad that the kind of technology is going to come out in 10 20 30 years will probably too old to really appreciate cuz you don't grow up with it it'll be like kids these days with their virtual and their uh their Tik toks and stuff like this like how do this thing and like come on give me my uh you know static photo you know my Commodore 64 yeah yeah exactly okay uh sorry we kind of skipped over but let me ask on um you know the machine learning world has been kind of inspired their imagination captivated with gpt3 and these language models I thought it'd be cool to get your opinion on it what what's your thoughts on this exciting world of um it connects to computation actually uh is of language models that are huge yeah and take multip many many computers not just the train but to also do inference on sure well I mean it depends on what you're speaking to there but I mean I think that there's been a pretty well understood maximum in deep learning that if you make the model bigger and you shove more data into it assuming you train it right and you have a good model architecture that you'll get a better model out and so on the one hand gpg 3 was not that surprising um on the other hand a tremendous amount of engineering went into making it possible um the implications of it are pretty huge I think that when gpt2 2 came out there was a very provocative blog post from open AI talking about you know we're not going to release it because of the social damage it could cause if it's misused um I think that's still a concern I think we need to look at how um technolog is applied and you know well-meaning tools can be applied in very horrible ways and they can have very profound impact on that um uh I think the gpt3 is a huge technical achievement and what will GPT 4 be will probably be bigger and more expensive to train really cool uh architectural tricks do what do you think is there um I don't know how much thought you've done on distributed computing uh is there is there some technical challenges that are interesting that you're hopeful about exploring in terms of you know a system that like a piece of code that you know GPT 4 uh that might have I don't know uh hundreds of trillions of parameters we have to run on thousands of computers is there some is there some hope that we can make that happen yeah well I mean today you can you can write a check and get access to 1,000 TPU cores and do really interesting large scale training and inference and things like that um in Google Cloud for example right and um so I don't think it's a question about scale it's a question about utility and when I look at the Transformer series of architectures that that the GPT series is based on it's really interesting to look at that because they're actually very simple simple designs they're not recurrent um the training regen are pretty simple um and so they don't really reflect like human brains MH right um but they're really good at learning language models and they're unrolled enough that you get you can simulate some recurrence right and so the question I think about is where does this take us like so we can just keep scaling it have more parameters more data more things we'll get a better result for sure but are there architectural techniques that can lead to progress at a faster Pace right this is when you know how do you get uh instead of just like making it constant time bigger how do you get like an algorithmic improvement out of this right and whether it be a new training regimen if it becomes um uh sparse sparse networks for example the human brain is sparse all these networks are dense um the connectivity patterns can be very different I think the this is where I get very interested and I'm way out of my league on the Deep learning side of this but I think that could lead to Big breakthroughs when you talk about uh large scale networks one of the things that Jeff Dean likes to talk about and he's uh uh giv a few talks on is this idea of having a sparsely gated mixture of experts kind of a model where you have um you know different Nets that are trained and are really good at certain kinds of tasks and so you have this distributor across a cluster and so you have a lot of different computers that end up being kind of locally specialized in different domains and then when a query comes in you you gate it and you use learn techniques to route to different parts of the network and then you utilize the compute resources of the entire cluster by having specialization within it and I don't know where that goes or if it starts to when it starts to work but I think things like that could be really interesting as well and then on the data side too if you can think of data selection as a kind of programming yeah I mean at the essentially if you look at like Kathy talked about software 2.0 I mean that in a sense data is the programming yeah yeah so I I just so let me try to summarize Andre's position really quick before I disagree with it yeah um so Andre Kathy is amazing so this is nothing nothing personal with him he's he's he's an amazing engineer and and also a good uh blog post writer yeah well he's a great communicator I he's just an amazing person he's he's also really sweet um so his his basic premise is that uh software is suboptimal I think we can all agree to that uh he also points out that uh deep learning and other learning based techniques are really great because you can solve problems in uh more structured ways uh with less like ad hoc code that people write out and don't write test cases for in some cases and so they don't even know if it works in the first place um and so if you start replacing systems of uh imperative code with deep learning models then you get better a better result okay and I think that he argues that software 2.0 is a per pervasively learned set of models and you get away from writing code and he's given talks where he talks about you know swapping over more and more and more parts of a code being learned and um driven that way I think that works and if you're pre predisposed to liking machine learning then I think that that's that's that's definitely a good thing I think this is also good for accessibility in many ways because certain people are not going to write C code or something and so having a data driven approach to do this kind of stuff I think can be very valuable on the other hand there are huge trade-offs and it's not clear to me that software 2.0 is um the answer and probably Andre wouldn't argue that it's the the answer for every problem either but um I look at machine learning as not a replacement for software 1.0 I look at it as a new programming Paradigm and so programming paradigms when you look across across domains is you know structured programming where you go from go-tos to if then else or functional programming from lisp and you start talking about higher order functions and values and things like this or you talk about objectoriented programming you talk about encapsulation subclassing inheritance you start talking about generic programming where you start talking about code reuse through um through uh specialization in different type instantiations um when you start talking about differentiable programming something that I am very excited about in the context of machine learning talking about taking functions and generating uh variance like the derivative of another function like that's a programming Paradigm that's very useful for solving certain classes of problems machine learning is amazing at solving certain classes of problems like you're not going to write a you know a cat detector or even a language translation system by writing C code that's not going to that's not a very productive way to do things anymore and so machine learning is absolutely the right way to do that in fact I would say that learn models are really the one of the best ways to work with the human world in general and so anytime you're talking about sensory input of different modalities anytime that you're talking about um generating things in a way that makes sense to a human I think that learn models are really really useful and that's because humans are very difficult to character okay and so this is a very powerful Paradigm for solving classes of problems but on the other hand uh imperative code is two you're not going to write a Bootloader for your computer in with a deep learning model deep learning models are very uh Hardware intensive they're very energy intensive because you have a lot of parameters and you can provably Implement any function with a learned model like this has been shown uh but that doesn't make it efficient and so if you're talking about carrying about a few orders of magnitudes worth of energy usage then it's useful to have other tools in the toolbox what also robustness too I mean yeah exactly all the problems of dealing with data and bias and data all the problems of uh you know software 2.0 and one of the great things that Andre is is uh arguing towards which I completely agree with him is that when you start uh implementing things with deep learning you need to learn from software 1.0 in terms of testing continuous integration how you deploy how do you validate all these things and building Building Systems around that so that you're not just saying like o it seems like it's good ship it right well what happens when I regress something what happens when I make a classification that's wrong and now I uh hurt somebody right I mean all these things you have to reason about yeah but at the same time the bootloader that works for our for us humans is uh looks awfully a lot like a new network right so it's it's it's messy and you can cut out different parts of the brain there's a lot of this neuroplasticity work that shows that it's going to adjust it's a I mean it's a really interesting question how much of the world programming could be replaced by software 2.0 like with oh could well I mean it's provably true that you could replace all of it right so then it's question anything that's a function you can so it's not a question about if I think it's a economic question it's a what kind of talent can you get what kind of trade-offs in terms of Maintenance right those kind of questions I think what kind of data can you collect I think one of the reasons that I'm most interested in uh machine learning is a programming Paradigm is that one of the things that we've seen across Computing in general is that being laser focused on one Paradigm often put you in a box it's not super great and so you look at object ear programming like it was all the rage in the early 80s and like everything has to be objects and people forgot about functional programming even though came first and and then people rediscovered that hey if you mix functional and object oriented and structure like you mix these things together you can provide very interesting tools that are good at solving different problems and so the question there is how do you get the best way to solve the problems it's not about whose tribe should win right it's not about you know that that that shouldn't be the question the question is how do you make it so that people can solve those problems the fastest and they have the right uh Tools in their box to build good libraries and they can solve these problems and when you look at that that's like you know you look at reinforcement learning as one really interesting subdomain of this reinforcement learning often you have to have the integration of a of a learn model combined with your Atari or whatever the other scenario it is that you're you're working in you have to combine that that thing with the robot control for the arm right and so now it's not just about that one uh Paradigm it's about integrating that with all the other systems that you have including often Legacy systems and things like this right and so to me I think that the interesting interesting thing to say is like how do you get the best out of this domain and how do you enable people to achieve things that they otherwise couldn't do without excluding all the good things we already know how to do right but okay this is just a crazy question but we talked a little about gpt3 but do you think it's possible that these language models that uh in essence in the language domain software 2.0 could replace some aspect of compilation for example or do program synthesis replace some aspect of programming yeah absolutely so I think the that learn models in general are extremely powerful and I think the people underestimate them um maybe you can suggest what I should do so of uh you know access to the gpt3 API would I be able to generate Swift code for example do you think that could do something interesting and so gpt3 is not probably not trained on the right Corpus so it probably has the ability to generate some Swift I bet it does um it's probably not going to generate a large enough body of Swift to be useful but but like take it a next step further like if if you had the goal of training something like gpt3 and you wanted to train it to generate source code right it could definitely do that now the question is um how do you express the intent of what you want filled in you can definitely like write write scaffolding of code and say fill in the hole and sort of put in some for Loops open put some classes or whatever and and the power of these mods is impressive but there's an unsolved question at least unsolved to me which is how do I express the intent of what to fill in right and kind of what you'd really want to have and I don't know that that these models are up to the task is you want to be able to say um here's a scaffolding and here are the assertions at the end and the assertions always pass and so you want a generative model on the one hand yes oh that's fascinating yeah right but you also want some loop back some reinforcement learning system or something where you're actually saying like I need to hill climb towards something that is more correct and I don't know that we have that so it would generate not only a bunch of the code but like the checks that do the testing it would generate the tests I think I think the humans would generate the tests right because the the test be fascinating if well the tests are the requirements yes but the okay so because you're have you have to express to the model what you want to you don't just want gibberish code look look at how compelling this code looks you want a story about four horned unicorns or something well okay so exactly but that's human requirements but then I thought it's a compelling idea that the gp4 model could generate uh checks like that are more um High Fidelity that check for correctness because uh the coded generates like say I ask it to generate a function that um gives me the Bacci sequence sure I don't like so so decompose the problem right so you have you have two things you have you need the ability to generate syntactically correct Swift Code that that's interesting right I think GPT series of model architectures can do that but then you need the ability to add the requirements so generate Fibonacci yeah the human needs to express that goal we don't have that language that I know of no I mean it can generate have you seen with gpt3 can generate you can say I mean there's uh interface stuff like it can generate HTML it can generate uh basic for Loops that give you like right but pick HTML how do I say I want google.com well no you could say or not not literally google.com how do I say I want a web page that's got a shopping cart and this and that that does that I mean so okay so just uh I don't know if you've seen these demonstrations but you type in I want a red button with the text that says hello and you type that in natural language and it generates the correct HTML done this demo it's it's kind of compelling so you have to uh uh prompt it with similar kinds of mappings of course it's probably handpicked like have to experiment they probably but the fact that they can do that once even out of like 20 yeah is uh is quite impressive again that's very basic uh like the HTML is kind of messy and and bad sure sure but yes the intent is the idea is the intent to specifi the natural language okay and so I've have not seen that that's really cool yeah yeah yeah but the question is uh the correctness of that like visually you can check oh the button is red but the for more uh for more complicated functions where the intent is harder to check this goes into like MP completeness kind of things like I want to know that this code is correct and gener it's a giant thing that uh does some kind of calculation it seems to be working it it's interesting to think like should the system also try to generate checks for itself for correctness yeah I don't know and this this is way beyond my experience the uh uh the thing that I think about is that there doesn't seem to be a lot of equational reasoning going on there's a lot of pattern matching and filling in and kind of propagating patterns that have been seen before into the future and into the generator result and so if you want to get correctness you kind of need theorem proving kind of things and like higher level logic and I don't know that um you could talk to Yan about that um and see and see what uh the the bright minds are thinking about right now but I don't think the GPT is in that that vein it's still really cool yeah and surpris who knows you know maybe reasoning is is uh is overrated yeah is over right I mean do we reason how do how do you tell right are we just pattern matching based on what we have and then reverse justifying it to ourselves exactly the reverse so like I think what the neural networks are missing and I think GPT for might have is to be able to uh tell stories to itself about what it did well that's what humans do right I mean you talk about uh like Network explainability right and we give noral Nets a hard time about this but humans don't know why we make decisions we have this thing called intuition and then we try to like say this feels like the right thing but why right and you know you wrestle with that when you're making hard decisions and is that science not really let me ask about a few highle questions I guess is um you've done a million things in your life and been very successful a bunch of young folks listen to this ask for advice from successful people like you uh if you were to give advice to uh somebody you know another a graduate student or some high school student about uh pursuing a career in Computing or just advice about life in general is there sure is there some words of wisdom you can give them so I think you come back to change and you know profound leaps happen because people are willing to believe that change is possible and that um the world does change and are willing to do the hard thing that it takes to make change happen and whether it be implementing a new programming language or implementing a new system or implenting a new research paper designing a new thing moving the world forward in science and philosophy whatever it really comes down to somebody who's willing to put in the work right and you have the the work is hard for a whole bunch of different reasons one of which is um you uh it it's work right and so you have to have the space in your life in which you can do that work which is why going to grad school can be a beautiful thing for certain people um but also there's a self-doubt that happens like you're two years into a project is it going anywhere right right well what do you do do you do you just give up because it's hard well no I mean some people like suffering um and so you plow through it the the secret to me is that you have to love what you're doing and and follow that passion because if when you get to the hard times that's when you know if you if you love what you're doing you're willing to kind of push through and um this is really uh hard because it's it's hard to know what you will love doing until you start doing a lot of things and so that's why I think that particularly early in your career it's good to experiment do a little bit of everything go go go take the the survey class on you know four different the first half of every class in your upper division you know lessons and um just get exposure to things because certain things will resonate with you and you'll find out wow I'm really good at this I'm really smart at this well it's just because it's it works with the way your brain and when something jumps out I mean that's one of the things that people often ask about is like well I think there's bunch of cool stuff out there like how do I pick the thing like uh yeah how do you how do you hook in your life how did you just hook yourself in and stuck with it well I got lucky right I mean I think that many people uh forget that a huge amount of it or most of it is luck right so um let's not forget that um so for me I fell in love with computers early on because I'm they they spoke to me I guess uh what language did they speak basic basic yeah um but the uh uh but then it was just kind of following a set of logical progressions but also um deciding that something that was hard was worth doing and and a lot of fun right and so I think that that is also something that's true for many other domains which is if you find something that you love doing that's also hard if you invest yourself in it and add value to the world then it will mean something generally right and again that can be a research paper that can be a software system that can be a new robot that can be that there's many things that that is that can be but a lot of it is like real value comes from doing things that are hard and that doesn't mean you have to suffer but um it's hard I mean you don't often hear that message we talked about it last time a little bit but I I it's one of my f not enough people talk about this this it's uh it's beautiful to hear a successful person well and self-doubt and impostor syndrome and the these are all things that uh successful people suffer with as well particularly when they put themselves in a point of being uncomfortable which um I like to do now and then just because it puts you in learning mode like if you want to if you want to grow as a person put yourself in a room with a bunch of people that know way more about whatever you're talking about than you do and ask dumb questions and guess what smart people love to teach often not always but often and if you listen if you're prepared to listen if you're prepared to grow if you're prepared to make connections you can do some really interesting things and I think a lot of progress is made by people who kind of hop between domains now and then because they bring uh they bring a perspective into a field that nobody else has if people have only been working in that field themselves we mentioned that the universe is kind of like a compiler of you know the entirety of it the whole evolution is kind of a kind of compilation maybe our us human beings are kind of compilers um let me ask the the old absur question that I didn't ask you last time which is uh what's the meaning of it all is there a meaning like if you asked a compiler why what would a compiler say what's the meaning of life what's the meaning of life uh you know I'm prepared for it not to mean anything here we are all biological things programmed to survive and and propagate our our DNA um and maybe the is just a just a computer and you you just go until entropy takes over the world and or takes over the universe and then you're done um I don't think that's a very productive way to live your life if so and so I prefer to bias towards the other way which is saying the world has the universe has a lot of value and I take uh I take happiness out of other people and a lot a lot of times part of that's having kids but also the relationships you build with other people and so uh the way I try to live my life is like what can I do that has value how can I move the world forward how can I take what I'm good at and like bring it bring it into the world and how can I I'm one of these people that likes to work really hard and be very focused on the things that I do and so if I'm going to do that how can it be in a domain that actually will matter right because a lot of things that we do we find ourselves in the cycle of like okay I'm doing a thing I'm very familiar with it I've done it for a long time I've never done anything else but I'm not really learning I I'm not really I'm keeping things going but there's a there's a younger generation that that can do the same thing maybe even better than me right maybe if I actually step out of this and jump into something I'm less comfortable with it's scary but on the other hand um it gives somebody else a new opportunity it also then put you back in learning mode and that can be really interesting and one of the things I've learned is that uh when you go through that that first you're deep into impostor syndrome but when you start working your way out you start to realize hey well there's actually a method to this and and now I'm able to add new things because I bring different perspective and this is one of the the the good things about bringing different kinds of people together diversity of thought is really important and um if you can pull together people that are coming at things from different directions you often get Innovation and I I love to see that that aha moment where you're like we've like really cracked this this is something never nobody's ever done before and then if you can do it in a context where it adds value other people can build on it it helps move the world then that's what that's what really excites me so the that kind of description of the magic of The Human Experience do you think we'll ever create that in like an AGI system you think we be able to create uh give uh give AI systems a sense of meaning where they operate in this kind of world exactly in the way you've described which is they interact with each other they interact with us humans sure sure well so I mean I why why are you being so speciest right all right so so agis versus bionet or you know versus bi um you know uh what are we but machines right we're just programmed to run our we have our objective function that we optimized for right and so we're doing our thing we think we have purpose but do we really yeah right I'm not prepared to say that th those new fangled agis have no soul just because we don't understand them right and I think that would be um when they when they exist uh that would be very premature to uh uh look at a new thing through your own lens without fully understanding it um you might be just saying that because AI systems in the future will be listening to this and then oh yeah yeah exactly you don't want to say anything please be nice to me you know when Skynet Skynet kills everybody please spare me Wise Wise uh look ahead thinking yeah but I mean I I think that people spend a lot of time worrying about this kind of stuff and I think that what we should be worrying about is how do we make the world better and the thing that I'm most scared about with agis is not that um that necessarily the Skynet will start shooting everybody with lasers and stuff like that to to use us for our calories the thing that I'm worried about is that um Humanity I think needs a challenge and if we get into a mode of not having a personal challenge not having a personal contribution whether that be like you know your kids and seeing what they grow into and helping helping guide them whether it be um your community that you're engaged in you're driving forward whether it be your work and the things that you're doing and the people you're working with and the products you're building and the contribution there if people don't have a objective I'm afraid what that means and um I think that this would lead to a rise of the worst part of people right instead of people striving together and trying to make uh the world better it could degrade into a very uh unpleasant world but but I don't know I mean we hopefully have a long ways to go before we discover that unfortunately we have pretty on the ground problems with the pandemic right now and so I think we should be focused on that as well yeah ultimately just as you said you're optimistic I think it helps for us to be optimistic that's uh fake it until you make it yeah well and why not what's what's the other side right so I mean uh uh I I'm not personally a very religious person but I've heard people say like oh yeah of course I believe in God of course I go to church because if God's real you know I want to be on the right side of that and if it's not real it doesn't matter doesn't matter and so you know that's that's a fair way to do it um yeah I mean the same thing with uh with nuclear deterrence all you know global warming all these things all these threats natural engineer pandemics all these threats we face I think it's uh uh it's paralyzing to be terrified of all the possible ways we could destroy ourselves I think it's much better uh or at least productive to be hopeful and to engineer defenses against these things to uh engineer a future where like you know see like a positive future and engineer that future yeah well and I think that's other another thing to think about as you know a human particularly if you're young and trying to figure out what it is that you want to be when you grow up like I am um I'm always looking for that uh the the question then is how do you want to spend your time and right now there seems to be a norm of being a consumption culture like I'm going to watch the news and and revel in how horrible everything is right now I'm going to go find out about the latest atrocity and find out all the details of like this the terrible thing that happened and be outraged by it um you can spend a lot of time watching TV and watching the new sitcom or whatever people watch these days I don't know um uh but that's a lot of hours right and those are hours that if you're tur into being productive learning growing experiencing uh you know when the pandemic's over going exploring right it leads to more growth and I think it leads to more optimism and happiness because you're you're you're building right you're building yourself you're building your capabilities you're building your viewpoints you're building your perspective and um I think that a lot of the cons the consuming of other people's me messages leads to kind of a negative Viewpoint which you need to be aware of what's happening because that's also important but there's a balance that um I think focusing on creation is is a very valuable thing to do yeah so what you're saying is people should focus on uh working on the sexiest feel of them all which is compiler design exactly well hey you can go work on machine learning and be crowded out by the the thousands of graduates popping out of school that all want to do the same thing or you could work in the place that people overpay you because there's not enough smart people working in it and uh here at the end of Mor's law According to some people uh actually the software is the hard part too yeah uh I mean optimization is is truly uh truly beautiful and also on the YouTube side or education side uh you know it's there's um it'd be nice to have some material that shows the beauty of compilers yeah yeah that's that's something so that's a call for uh for people to create that kind of content as well Chris uh you're one of my favorite people to talk to I it's such a huge honor that you would waste your time talking to me uh I've always appreciate it thank you so much today the the the the truth of is you spend a lot of time talking to me just on you know walks and other things like that so it's it's great to catch up thanks man thanks for listening to this conversation with Chris lner and thank you to our sponsors blinkist an app that summarizes key ideas from thousands of books neuro which is a maker of functional gum and mints that supercharge my mind masterclass which are online courses from World experts and finally cash app which is an app for sending money to friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with f stars on Apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Friedman and now let me leave you some words from Chris latner so much of language design is about trade-offs and you can't see those tradeoffs unless you have a community of people that really represent those different points thank you for listening and hope to see you next time |
Scott Aaronson: Computational Complexity and Consciousness | Lex Fridman Podcast #130 | the following is the conversation with scott anderson his second time on the podcast he is a professor at ut austin director of the quantum information center and previously a professor at mit last time we talked about quantum computing this time we talk about computation complexity consciousness and theories of everything i'm recording this intro as you may be able to tell in a very strange room in the middle of the night i'm not really sure how i got here or how i'm going to get out but hunters thompson saying i think applies to today and the last few days and actually the last couple of weeks life should not be a journey to the grave with the intention of arriving safely in a pretty and well-preserved body but rather to skid and broadside in a cloud of smoke thoroughly used up totally worn out and loudly proclaiming wow what a ride so i figured whatever i'm up to here and yes lots of wine is involved i'm gonna have to improvise hence this recording okay quick mention of each sponsor followed by some thoughts related to the episode first sponsor is simply safe a home security company i use to monitor and protect my apartment though of course i'm always prepared with a fallback plan as a man in this world must always be second sponsor is eight sleep a mattress that cools itself measures heart rate variability has a nap and has given me yet another reason to look forward to sleep including the all-important power nap third sponsor is expressvpn the vpn i've used for many years to protect my privacy on the internet finally the fourth sponsor is betterhelp online therapy when you want to face your demons with a licensed professional not just by doing david goggins like physical challenges like i seem to do on occasion please check out these sponsors in the description to get a discount and to support the podcast as a side note let me say that this is the second time i recorded a conversation outdoors the first one was with stephen wolfram when it was actually sunny out in this case it was raining which is why i found a covered outdoor patio but i learned a valuable lesson which is that raindrops can be quite loud on the hard metal surface of a patio cover i did my best with the audio i hope it still sounds okay to you i'm learning always improving in fact as scott says if you always win then you're probably doing something wrong to be honest i get pretty upset with myself when i fail small or big but i've learned that this feeling is priceless it can be fuel when channeled into concrete plans of how to improve so if you enjoy this thing subscribe on youtube review five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with scott erinson let's start with the most absurd question but i've read you write some fascinating stuff about it so uh let's go there are we living in a simulation what difference does it make lex i mean i'm serious what difference because if we are living in a simulation it raises the question how real does something have to be in stimulation for in it to be sufficiently immersive for us humans but i mean even in principle how could we ever know if we were in one right a perfect simulation by definition is something that's indistinguishable from the real thing well we didn't say anything about perfect it could be no no that's that's right well if it was an imperfect simulation if we could hack it you know find a bug in it then that would be one thing right if if this was like the matrix and there was a way for me to you know do flying kung fu moves or something by hacking the simulation well then you know we would have to cross that bridge when we came to it wouldn't we right i mean at that point you know i it's it's uh hard to see the difference between that and just uh uh what people would ordinarily refer to as a world with miracles you know uh what about from a different perspective thinking about the universe as a computation like a program running on a computer that's kind of a neighboring concept it is it is an interesting and reasonably well-defined question to ask is the world computable you know you know does the world satisfy what we would call in cs the the church touring thesis yeah that is you know uh could we take any physical system and simulate it to uh you know any desired precision by a touring machine you know given the appropriate input data right and so far i think the indications are pretty strong that our world does seem to satisfy the church-touring thesis uh at least if it doesn't then we haven't yet discovered why not uh but now does that mean that our universe is a simulation well you know that word seems to suggest that there is some other larger universe in which it is running right right and the problem there is that if the simulation is perfect then we're never going to be able to get any direct evidence about that other universe you know we will only be able to see uh the effects of the computation that is running in this universe well let's imagine an analogy let's imagine a pc a personal computer a computer is it possible with the advent of artificial intelligence for the computer to look outside of itself to see to understand its creator i mean that's a simple is that is that a ridiculous connection well i mean with the computers that we actually have i mean first of all uh we we all know that uh humans have done an imperfect job of you know enforcing the abstraction boundaries of computers right like you may try to confine some program to a playpen but you know as soon as there's one uh uh memory allocation error in in the c program then the program has gotten out of that play pen and it can do whatever it wants right this is how most hacks work you know viruses and worms and exploits and you know you would have to imagine that an ai would be able to discover something like that now you know of course if we could actually discover some exploit of reality itself then you know then this whole i mean we we then in some sense we we wouldn't have to philosophize about this right this would no longer be a metaphysical conversation right this would just but that's the question is what is what would that hack look like yeah well i have no idea i mean uh uh peter shore uh you know the you know very famous person in quantum computing of course has a joked that uh maybe the reason why we haven't yet you know integrated general relativity in quantum mechanics is that you know the part of the universe that depends on both of them was that was actually left unspecified and if we ever tried to do an experiment uh involving the singularity of a black hole or something like that then you know the universe would just uh generate an overflow error or something right yeah we would just crash the universe now um you know the the the universe you know has seemed to hold up pretty well for you know 14 billion years right so you know my uh you know uh occam's razor kind of guess has to be that you know it will continue to hold up you know that the fact that we don't know the laws of physics governing some phenomenon is not a strong sign that probing that phenomenon is going to crash the universe right but you know of course i could be wrong but do you think on the physics side of things you know there's been uh recently a few folks eric weinstein and stephen wolfram that came out with a theory of everything i think there's a history of physicists dreaming and working on the unification of all the laws of physics do you think it's possible that once we understand uh more physics not necessarily the unification of the laws but just understand physics more deeply at the fundamental level we'll be able to start you know uh i mean part of this is humorous but uh looking to see if there's any bugs in the universe that can be exploited for uh you know traveling at uh not just speed of light but just traveling faster than our current uh spaceships can travel all that kind of stuff well i mean to travel faster than our current spaceships could travel you wouldn't need to find any bug in the universe right the known laws of physics you know let us go much faster up to the speed of light right and you know when people want to go faster than the speed of light well we actually know something about what that would entail namely that you know according to relativity that seems to entail communication backwards in time okay so then you have to worry about uh close time like curves and all of that stuff so you know in some sense we we sort of know the price that you have to pay for these things right understanding of physics that's right that's right we can't you know say that they're impossible but we you know we know that sort of a lot else in physics breaks right so uh now regarding uh eric weinstein and stephen wolfram like i wouldn't say that either of them has a theory of everything i would say that they have ideas that they hope you know could someday lead to a theory of everything is that a worthy pursuit well i mean certainly let's say by theory of everything you know we don't literally mean a theory of cats and of baseball and you know but we just mean it in the in the more limited sense of everything a fun a fundamental theory of physics right of all of the fundamental interactions of physics of course such a theory even after we had it uh you know would would leave the entire question of all the emergent behavior right you know to uh to be explored uh so it's so it's only everything for a specific definition of everything okay but in that sense i would say of course that's worth pursuing i mean that is the entire program of fundamental physics right all of my friends who do quantum gravity who do string theory who do anything like that that is what's motivating them yeah it's it's funny though but i mean eric weinstein talks about this it is i don't know much about the physics world but i know about the ai world it is a little it is a little bit taboo uh to talk about agi for example on the ai side so really to talk about uh the big dream of the community i would say because it seems so far away it's almost taboo to bring it up because uh you know it's seen as the kind of people that dream about creating a truly superhuman level intelligence that's really far out there people because we're not even close to that and it feels like the same thing is true for the physics community i mean stephen hawking certainly talked uh constantly about theory of everything right uh uh uh you know i mean i mean people you know used those terms who were you know some of the most respected people in the in the in the whole world of physics right but i mean i think that the distinction that i would make is that people might react badly if you use the term in a way that suggests that that you you know thinking about it for five minutes have come up with this major new insight about it yeah right it's it's difficult stephen hawk is is a not a great example because i think you can do whatever the heck you want when you get to that level and i certainly see like seeing your faculty you know that you know at that point that's the one of the nice things about getting older is you stop giving a damn but community as a whole they tend to roll their eyes very quickly at stuff that's outside the quote-unquote mainstream well well let me let me put it this way i mean if you asked you know ed whitton let's say who is you know you might consider the leader of the string community and thus you know very very mainstream in a certain sense but he would have no hesitation in saying you know of course you know they're looking for a you know uh uh you know a a a unified description of nature of you know of general relativity of quantum mechanics of all the fundamental interactions of nature right now you know whether people would call that a theory of everything whether they would use that that term that might vary you know lenny suskin would definitely have no problem telling you that you know if that's what we want right for me who loves human beings in psychology it's kind of ridiculous to say a theory that unifies the laws of physics gets you to understand everything i would say you're not even close to understanding everything yeah right well yeah i mean the word everything is a little ambiguous here right because you know and then people will get into debates about you know reductionism versus emergentism and blah blah blah and so in in not wanting to say theory of everything people might just be trying to short-circuit that debate and say you know look you know yes we want a fundamental theory of you know the particles and interactions of nature let me bring up the next topic that people don't want to mention although they're getting more comfortable with it it's consciousness you mentioned that you have a talk on consciousness that i watched five minutes of but the internet connection was really bad was this my talk about you know uh refuting the integrated information theory yes which is a particular account of consciousness that yeah i think one can just show it doesn't work right so let me much harder to say what does work what doesn't work yeah yeah let me ask maybe it'd be nice to uh comment on you talk about also like the semi hard problem of consciousness or like almost hard pro or kind of hard pretty pretty hard pretty hard one i think i call it so maybe can you uh talk about that uh their idea of um of the approach to modeling consciousness and why you don't find it convincing what is it first of all okay well so so what what what i called the pretty hard problem of consciousness this is my term although many other people have said something equivalent to this okay uh but uh it's just you know the the problem of you know giving an account of just which physical systems are conscious and which are not or you know if there are degrees of consciousness then quantifying how conscious a given system is oh awesome so that's the pretty hard yeah that's what i mean that's it i'm adopting it i love it that's a good a good ring to it and so you know the infamous hard problem of consciousness is to explain how something like consciousness could arise at all you know in a material universe right or you know why does it ever feel like anything to to experience anything right and you know so i'm trying to distinguish from that problem right and say you know no okay i am i would merely settle for an account that could say you know is a fetus conscious you know if so at which trimester you know is a uh is a dog conscious you know what about a frog right or or even as a precondition you take that both these things are conscious tell me which is more conscious yeah for example yes yeah yeah i mean if consciousness is some multi-dimensional vector well just tell me in which respects these things are conscious and in which respect they aren't right and you know and have some principled way to do it where you're not you know carving out exceptions for things that you like or don't like but could somehow take a description of an arbitrary physical system and then just based on the physical properties of that system or the informational properties or how it's connected or something like that just in principle calculate you know its degree of consciousness right i mean this this this would be the kind of thing that we would need you know if we wanted to address questions like you know what does it take for a machine to be conscious right or when or you know when when when should we regard ais as being conscious um so now this iit this integrated information theory uh which has been put forward by uh giulio tanoni and a bunch of his uh uh collaborators over the last decade or two uh this is noteworthy i guess as a direct attempt to answer that question to you know answer the to address the pretty hard problem right and they give a uh a criterion that's just based on how a system is connected so you so it's up to you to sort of abstract the system like a brain or a microchip as a collection of components that are connected to each other by some pattern of connections you know and and to specify how the components can influence each other you know like where the inputs go you know where they affect the outputs but then once you've specified that then they give this quantity that they call fee you know the greek letter phi and the definition of phi is actually changed over time it changes from one paper to another but in all of the variations it involves something about what we in computer science would call graph expansion so basically what this means is that they want it uh in order to get a large value of fee uh it should not be possible to take your system and partition it into two components that are only weakly connected to each other okay so whenever we take our system and sort of try to split it up into two then there should be lots and lots of connections going between the two components okay well i understand what that means on a graph do they formalize what uh how to construct such a graph or data structure whatever uh or is this well one of the criticism uh i i've heard you kind of say is that a lot of the very interesting specifics are usually communicated through like natural language like like through words so it's like the details aren't always well they well it's true i mean they they they they have nothing even resembling a derivation of this fee okay so what they do is they state a whole bunch of postulates you know axioms that they think that consciousness should satisfy and then there's some verbal discussion and then at some point fee appears right right and this this was one the first thing that really made the hair stand on my neck to be honest because they are acting as if there is a derivation they're acting as if you know you're supposed to think that this is a derivation and there's nothing even remotely resembling a derby they just pull the fee out of a hat completely is one of the key criticisms to you is that details are missing or is that exactly more fun that's not even the key criticism that's just that's just a side point okay the the core of it is that i think that the you know that they want to say that a system is more conscious the larger its value of fee and i think that that is obvious nonsense okay as soon as you think about it for like a minute as soon as you think about it in terms of could i construct a system that had an enormous value of fee like you know even larger than the brain has but that is just implementing an error correcting code you know doing nothing that we would associate with you know intelligence or consciousness or any of it the answer is yes it is easy to do that right and so i wrote blog posts just making this point that yeah it's easy to do that now you know tanoni's response to that was actually kind of incredible right i mean i i admired it in a way because instead of disputing any of it he just bit the bullet in the sense you know he was one of the the uh the most uh audacious bullet bitings i've ever seen in my career okay he said okay then fine you know this system that just applies this error correcting code it's conscious you know and if it has a much larger value of fee then you or me it's much more conscious than you want me you know you we just have to accept what the theory says because you know science is not about confirming our intuitions it's about challenging them and you know this is what my theory predicts that this thing is conscious and you know or super duper conscious and how are you going to prove me wrong see i would so the way i would argue against your blog post is i would say yes sure you're right in general but for naturally arising systems developed through the process of evolution on earth the this rule of the larger fee being associated being associated with more consciousness is correct yeah so that's not what he said at all right right because he wants this to be completely general right so we can apply to even computers yeah i mean i mean the whole interest of the theory is the you know the hope that it could be completely general apply to aliens to computers to uh uh animals coma patients to any of it right yeah and uh uh so so so he just said well you know uh scott is relying on his intuition but you know i'm relying on this theory and you know to me it was almost like you know are we being serious here like like like you know like like okay yes in science we try to learn highly non-intuitive things but what we do is we first test the theory on cases where we already know the answer right like if if someone had a new theory of temperature right then you know maybe we could check that it says that boiling water is hotter than ice and then if it says that the sun is hotter than anything you know you've ever experienced then maybe we we trust that extrapolation right but like this this theory like if if you know it it's now saying that you know a a gigantic grit like regular grid of exclusive or gates can be way more conscious than a you know a person or than any animal can be you know even if it you know is you know is is is is so uniform that it might as just well just be a blank wall right and and so now the point is if this theory is sort of getting wrong the question is a blank wall you know more conscious than a person then i would say what is what is there for it to get right so your sense is a blank wall uh is not more conscious than a human being yeah i mean i mean i mean you could say that i am taking that as one of my axioms i'm saying i'm saying that if if a theory of consciousness is is get getting that wrong then whatever it is talking about at that point i i i'm not going to call it consciousness i'm going to use a different word you have to use a different word i mean yeah it's all it's possible just like with intelligence that us humans conveniently define these very difficult to understand concepts in a very human-centric way just like the touring test really seems to define intelligence as a thing that's human-like right but i would say that with any uh concept you know there's uh uh uh you know like we we we first need to define it right and a definition is only a good definition if it matches what we thought we were talking about you know prior to having a definition right yeah and i would say that you know uh fee as a definition of consciousness fails that test that is my argument so okay let's so let's take a further step so you mentioned that the universe might be uh the touring machine so like it might be computational or simulatable by one anyway simulated by one so yeah do you what's your sense about consciousness do you think consciousness is computation that we don't need to go to any place outside of the computable universe to uh you know to to understand consciousness to build consciousness to measure consciousness all those kinds of things i don't know these are what uh you know have been called the the vertigonous questions right there's the questions like like uh you know you get a feeling of vertigo and thinking about them right i mean i certainly feel like uh i am conscious in a way that is not reducible to computation but why should you believe me right i mean and and if you said the same to me then why should i believe you but as computer scientists yeah i feel like a computer could be intel could achieve human level intelligence but and that's actually a feeling and a hope that's not a scientific belief it's just we've built up enough intuition the same kind of intuition you use in your blog it's you know that's what scientists do they i mean some of it is a scientific method but some of it is just damn good intuition i don't have a good intuition about consciousness yeah i'm not sure that anyone does or or has in the you know 2500 years that these things have been discussed lex uh but do you think we will like one of the i got a chance to attend i can't wait to hear your opinion on this but attend the neuralink event and uh one of the dreams there is to uh you know basically push neuroscience forward and the hope with neuroscience is that we can inspect the machinery from which all this fun stuff emerges and see we're going to notice something special some special sauce from which something like consciousness or cognition emerges yeah well it's clear that we've learned an enormous amount about neuroscience we've learned an enormous amount about computation you know about machine learning about you'll know ai how to get it to work we've learned uh an enormous amount about the underpinnings of the physical world you know and you know it from one point of view that's like an enormous distance that we've traveled along the road to understanding consciousness from another point of view you know the distance still to be traveled on the road you know maybe seems no shorter than it was at the beginning yeah right so it's very hard to say i mean you know these are questions like like in in in sort of trying to have a theory of consciousness there's sort of a problem where it feels like it's not just that we don't know how to make progress it's that it's hard to specify what could even count as progress right because no matter what scientific theory someone proposed someone else could come along and say well you've just talked about the mechanism you haven't said anything about what breathes fire into the mechanism right really makes there's something that it's like to be it right and that seems like an objection that you could always raise yes no matter you know how much someone elucidated the details of how the brain works okay let's go touring tests and love the prize i have this intuition call me crazy but we that a machine to pass the touring test and is full whatever the spirit of it is we can talk about how to formulate the perfect touring test that that machine has to be conscious or we at least have to uh i have a very low bar of what consciousness is a dentist i tend to think that the emulation of consciousness is as good as consciousness so like consciousness is just a dance a social a social uh shortcut like a nice useful tool but i tend to connect intelligence consciousness together so by by that do you uh maybe just to ask what uh what role does consciousness play do you think in passing the touring test well look i mean it's almost tautologically true that if we had a machine that passed the turing test then it would be emulating consciousness right so if your position is that you know emulation of consciousness is consciousness then so you know by by definition any machine that passed the touring test would be conscious but it's uh uh but i mean we know that you could say that you know that that is just a way to rephrase the original question you know is an emulation of consciousness you know necessarily conscious right and you can you know i hear i'm not saying anything new that hasn't been debated ad nauseum in the literature okay but you know you could uh imagine some very hard cases like imagine a machine that passed the touring test but it did so just by an enormous cosmological sized look-up table that just cached every possible conversation that could be had the old chinese room well well yeah yeah but but this is uh uh i mean i mean the chinese room actually would be doing some computation at least in searle's version right here i'm just talking about a table lookup okay now it's true that for conversations of a reasonable length this you know lookup table would be so enormous that wouldn't even fit in the observable universe okay but supposing that you could build a big enough look-up table and then just you know pass the touring test just by looking up what the person said right are you going to regard that as conscious okay let me try to make this yeah yeah formal and then you can shut it down i think that the emulation of something is that something if there exists in that system a black box that's full of mystery so like uh full of mystery to whom to uh human in inspectors so does that mean that consciousness is relative to the observer like could something be conscious for us but not conscious for an alien that understood better what was happening inside the black box yes so that if inside the black box is just a look-up table the alien that saw that would say this is not conscious to us another way to phrase the black box is layers of abstraction which make it very difficult to see to the actual underlying functionality of the system and then we observe just the abstraction and so it looks like magic to us but once we understand the inner machinery it stops being magic and so like that's a prerequisite is that you can't know how it works some part of it because then there has to be in our human mind uh entry point for the magic so that that's that's a formal definition of the system yeah well look i mean i i explored a view and this essay i wrote called the ghost and the quantum touring machine uh seven years ago that is uh related to that except that i did not want to have consciousness be relative to the observer right because i think that you know if consciousness means anything it is something that is experienced by the entity that is conscious right you know like i don't need you to tell me that i'm conscious right nor do you need me to to to to tell you that you are right so uh so but but basically what i explored there is you know are there uh aspects of a of a system like uh like a brain that uh that just could not be predicted even with arbitrarily advanced future technologies yes because of chaos combined with quantum mechanical uncertainty you know and things like that i mean that that actually could be a a property of the brain you know if true that would distinguish it in a principled way at least from any currently existing computer not from any possible computer but from yeah yeah let's do a thought experiment so yeah if i gave you information that you're in the entire history of your life basically explain away free will with a look-up table say that this was all predetermined that everything you experienced has already been predetermined wouldn't that take away your consciousness wouldn't you yourself that wouldn't experience of the world change for you in a way that's you you can't well let me put it this way if you could do like in a greek tragedy where you know you would just write down a prediction for what i'm going to do and then maybe you put the prediction in a sealed box and maybe you know you you uh open it later and you show that you knew everything i was going to do or you know of course the even creepier version would be you tell me the prediction and then i try to falsify it and my very effort to falsify it makes it come true right but let's let's you know let's even forget that you know that version is as convenient as it is for fiction writers right let's just let's just do the version where you put the prediction into a sealed envelope okay but uh if you could reliably predict everything that i was going to do i'm not sure that that would destroy my sense of being conscious but i think it really would destroy my sense of having free will you know and much much more than any philosophical conversation could possibly do that right and so i think it becomes extremely interesting to ask you know could such predictions be done you know even in principle is it consistent with the laws of physics to make such predictions to get enough data about someone that you could actually generate such predictions without having to kill them in the process to you know slice their brain up into little slivers or something i mean theoretically possible right well um i don't know i mean i mean it might be possible but only at the cost of destroying the person right i mean it depends on how low you have to go in sort of the substrate like if there was a nice digital abstraction layer if you could think of each neuron as a kind of transistor computing a digital function then you could imagine some nanorobots that would go in and we just scan the state of each transistor you know of each neuron and then you know make a a good enough copy right but if it was actually important to get down to the molecular or the atomic level then you know eventually you would be up against quantum effects you would be up against the unclonability of quantum states so i think it's a question of uh how good of a replica how good does the replica have to be before you're going to count it as actually a copy of you or as being able to predict your actions uh that's a totally open question then yeah yeah yeah and and especially once we say that well look maybe there's no way to pre you know to make a deterministic prediction because you know there's all there you know we know that there's noise buffeting the brain around presumably even quantum mechanical uncertainty you know affecting the sodium ion channels for example whether they open or they close um you know there's no reason why over a certain time scale that shouldn't be amplified just like we imagine happens with the weather or with any other you know chaotic system uh so um so if if that stuff is is important right then uh then then you know we would say uh well you know you you you can't uh uh you know you're you're never going to be able to make an accurate enough copy but now the hard part is well what if someone can make a copy that sort of no one else can tell apart from you right it says the same kinds of things that you would have said maybe not exactly the same things because we agree that there's noise but it says the same kinds of things and maybe you alone would say no i know that that's not me you know it's it doesn't share my i haven't felt my consciousness leap over to that other thing i still feel it localized in this version right then why should anyone else believe you what are your thoughts i'd be curious you're a good person to ask which is uh penn rose's roger penrose's work on consciousness saying that there you know there is some with axons and so on there might be some biological places where quantum mechanics can come into play and through that create consciousness somehow yeah okay well um uh familiar with his work of course you know i read penrose's books as a teenager they had a huge impact on me uh uh five or six years ago i had the privilege to actually talk these things over with penrose you know at some length at a conference in minnesota and uh you know he is uh uh you know an amazing uh personality i admire the fact that he was even raising such uh audacious questions at all uh but you know to to to answer your question i think the first thing we need to get clear on is that he is not merely saying that quantum mechanics is relevant to consciousness right that would be like um you know that would be tame compared to what he is saying right he is saying that you know even quantum mechanics is not good enough right if because if supposing for example that the brain were a quantum computer maybe that's still a computer you know in fact a quantum computer can be simulated by an ordinary computer it might merely need exponentially more time in order to do so right so that's simply not good enough for him okay so what he wants is for the brain to be a quantum gravitational computer or or uh he wants the brain to be exploiting as yet unknown laws of quantum gravity okay which would which would be uncomputable that's the key point okay yes yes that would be literally uncomputable and i've asked him you know to clarify this but uncomputable even if you had an oracle for the halting problem or you know and and or you know as high up as you want to go and the sort of high the usual hierarchy of uncomputability he wants to go beyond all of that okay so so you know just to be clear like you know if we're keeping count of how many speculations you know there's probably like at least five or six of them right there's first of all that there is some quantum gravity theory that would involve this kind of uncomputability right most people who study quantum gravity would not agree with that they would say that what we've learned you know what little we know about quantum gravity from the this ads cft correspondence for example has been very much consistent with the broad idea of nature being computable right um but uh but all right but but supposing that he's right about that then you know what most physicists would say is that whatever new phenomena there are in quantum gravity you know they might be relevant at the singularities of black holes they might be relevant at the big bang uh they are plainly not relevant to something like the brain you know that is operating at ordinary temperatures you know with ordinary chemistry and you know the the the physics underlying the brain they would say that we have you know the fundamental physics of the brain they would say that we've pretty much completely known for for generations now right uh because you know quantum field theory lets us sort of parametrize our ignorance right i mean sean carroll has made this case and you know in great detail right that sort of whatever new effects are coming from quantum gravity you know they are sort of screened off by quantum field theory right and this is this bring you know brings us to the whole idea of effective theories right but that like we have you know that in like in the standard model of elementary particles right we have a quantum field theory that seems totally adequate for all of the terrestrial phenomena right the only things that it doesn't you know explain are well first of all you know the details of gravity if you were to probe it like at a uh you know extremes of you know curvature or like incredibly small distances it doesn't explain dark matter it doesn't explain black hole singularities right but these are all very exotic things very you know far removed from our life on earth right so for penrose to be right he needs you know these phenomena to somehow affect the brain he needs the brain to contain antenna that are sensitive to the black hole to this as yet unknown physics right and then he needs a modification of quantum mechanics okay so he needs quantum mechanics to actually be wrong okay he needs uh uh what what he wants is what he calls an objective reduction mechanism or an objective collapse so this is the idea that once quantum states get large enough then they somehow spontaneously collapse right that uh uh um you know and and this is an idea that lots of people have explored uh you know there's uh something called the grw proposal that tries to uh you know say something along those lines you know and these are theories that actually make testable predictions right which is a nice feature that they have but you know the very fact that they're testable may mean that in the uh you know in the in the coming decades we may well be able to test these theories and show that they're they're they're wrong right uh you know we may be able to test some of penrose's ideas if not not his ideas about consciousness but at least his ideas that about an objective collapse of quantum states right and people have actually like dick balmester have actually been working to try to do these experiments they haven't been able to do it yet to attest penrose's proposal okay but penrose would need more than just an objective collapse of quantum states which would already be the biggest development in physics for a century since quantum mechanics itself okay he would need for consciousness to somehow be able to influence the direction of the collapse so that it wouldn't be completely random but that you know your dispositions would somehow influence the quantum state to collapse more likely this way or that way okay finally penrose you know says that all of this has to be true because of an argument that he makes based on girdle's incompleteness theorem okay right now like i would say the overwhelming majority of computer scientists and mathematicians who have thought about this i don't think that girdles and completeness theorem can do what he needs it to do here right i don't think that that argument is sound okay but that is you know that is sort of the tower that you have to ascend to if you're going to go where penrose goes and the intuition uses with uh yeah the completeness theorem is that basically that there's important stuff that's not computable it's not just that because i mean everyone agrees that there are problems that are uncomputable right that's a mathematical theorem right that but what penrose wants to say is that uh uh you know the um you know for example there are statements uh you know for you know given any uh formal system you know for doing math right there will be true statements of arithmetic that that formal system you know if it's adequate for math at all if it's consistent and so on will not be able to prove uh a famous example being the statement that that system itself is consistent right no you know good formal system can actually prove its own consistency that can only be done from a stronger formal system which then can't prove its own consistency and so on forever okay that's gurdle's theorem but now why is that relevant to uh consciousness right uh uh well you know i mean i mean the the idea that it might have something to do with consciousness as an old one girdle himself apparently thought that it didn't really um you know uh lucas uh uh um um thought so i think in the 60s and penrose is really just you know sort of updating what what uh uh what what they and others had said i mean you know the idea that girdle's theorem could have something to do with consciousness was you know um in in 1950 when alan turing wrote his article uh about the touring test he already you know was writing about that as like an old and well-known idea and as one that he was as a wrong one that he wanted to dispense with okay but the basic problem with this idea is you know penrose wants to say that uh and and all of his predecessors your you know want to say that you know even though you know this given formal system cannot prove uh its own consistency we as humans sort of looking at it from the outside can just somehow see its consistency right and the you know the rejoinder to that you know from the very beginning has been well can we really yeah i mean maybe or maybe maybe you know maybe maybe he penrose can but you know can the rest of us right uh and you know i i noticed that that um you know i mean it is perfectly plausible to imagine a computer that could say you know it would not be limited to working within a single formal system right they could say i am now going to adopt the hypothesis that this that my formal system is consistent right and i'm now going to see what can be done from that stronger vantage point and and so on and you know when i'm going to add new axioms to my system totally plausible there's absolutely gerdle's theorem has nothing to say about against an ai that could repeatedly add new axioms all it says is that there is no absolute guarantee that when the ai adds new axioms that it will always be right right okay and you know and that's of course the point that penrose pounces on but the reply is obvious and you know it's one that that alan turing made 70 years ago name we we don't have an absolute guarantee that we're right when we add a new axiom right we never have and plausibly we never will so on alan turing you took part in the lobner prize uh uh not really no i didn't i mean there was this uh uh kind of ridiculous claim that was made uh some almost a decade ago about an a chat bot called eugene goose i guess you didn't participate as a judge in the lobner prize i didn't but you participated as a judge in that i guess it was an exhibition event or something like that or was eugene uh eugene gusman that was just me writing a blog post because some journalists called me to ask about it did you ever chat with him i thought i did chat with eugene gooseman i mean it was available on the web the chat oh interesting i didn't so yeah so all that happened was that uh so you know a bunch of journalists started writing breathless articles about you know an a you know first uh chatbot that passes the touring test right and it was this thing called eugene guzman that was supposed to simulate a 13 year old boy and um you know and apparently someone had done some tests where you know people couldn't you know you know were less than perfect let's say distinguishing it from a human and they said well if you look at touring's paper and you look at you know the percentages that he that he talked about then you know it seemed like we're past that threshold right and you know i had a sort of you know different way to look at it instead of the legalistic way like let's just try the actual thing out and let's see what it can do with questions like you know is mount everest bigger than a shoebox okay or just you know like the most obvious questions right and then and you know and the answer is well it just kind of parries you because it doesn't know what you're talking about right so just clarify exactly in which way they're obvious they're obvious in the sense that you convert the sentences into the meaning of the objects they represent and then do some basic obvious we mean your common sense reasoning with the objects that the sentences represent uh right right it was not able to answer you know or even intelligently respond to basic common sense questions but let me say something stronger than that there was a famous chatbot in the 60s called eliza right that you know that managed to actually fool you know a lot of people right or people would pour their hearts out into this elisa because it simulated a therapist right and most of what it would do is it would just throw back at you whatever you said right and this turned out to be incredibly effective right maybe you know therapists know this this is you know one of their tricks but uh it um um you know it it really had some people convinced uh but you know this this thing was just like i think it was literally just a few hundred lines of lisp code right it was not only was it not intelligent it wasn't especially sophisticated it was like a it was a simple little hobbyist program and eugene gusman from what i could see was not a significant advance compared to uh eliza right so so this is and and that was that was really the point i was making and this was you know you didn't in some sense you didn't need a like a computer science professor to sort of say this like anyone who was looking at it and who just had you know an ounce of sense could have said the same thing right well but because you know these journalists were call you know calling me you know like the first thing i said was uh well you know no you know i i'm a quantum computing person i'm not an ai person you know you shouldn't ask me then they said look you can go here and you can try it out i said all right all right so i'll try it out um but now you know this whole discussion i mean it got a whole lot more interesting in just the last few months yeah i'd love to hear your thoughts about gpt yeah yeah yeah in the last few months we've had you know we've we've the world has now seen a chat engine or a text engine i should say called gpt-3 um that you know i think it it's still you know it does not pass a touring test you know there are no real claims that it passes the touring test right you know this is comes out of the group at open ai and you know they're you know they've been relatively careful and what they've claimed about the system but i think this this this uh as clearly as eugene gusman was not in advance over eliza it is equally clear that this is a major advance over over over eliza or really over anything that the world has seen before uh this is a text engine that can come up with kind of on topic you know reasonable sounding completions to just about anything that you ask you can ask it to write a poem about topic x in the style of poet y and it will have a go at that yeah and it will do you know not a perf not a great job not an amazing job but you know a passable job you know definitely you know as as good as you know you know in in many cases i would say better than i would have done right uh you know you can ask it to write you know an essay like a student essay about pretty much any topic and it will get something that i am pretty sure would get at least a b minus you know in my most you know high school or even college classes right and you know in some sense you know the way that it did this the way that it achieves this um you know scott alexander of the you know the much mourned blog slate star codex had a wonderful way of putting it he said that they basically just ground up the entire internet into a slurry okay yeah and you know and i i to tell you the truth i had wondered for a while why nobody had tried that right like why not write a chat bot by just doing deep learning over a corpus consisting of the entire web right and and so so so uh now they finally have done that right and you know the results are are very impressive you know it's not clear that you know people can argue about whether this is truly a step toward general ai or not but this is an amazing capability uh that you know uh we didn't have a few years ago that you know if a few years ago if you had told me that we would have it now that would have surprised me yeah and i think that anyone who denies that is just not engaging with what's there so their model it takes a large part of the internet and compresses it in a small number of parameters relative to the size of the internet and is able to without fine-tuning uh do a basic kind of a quarrying mechanism just like you described where you specify a kind of poet and then you want to write a poem and somehow i was able to do basically a lookup on the internet well of relevant things i mean that's what i mean i mean i mean how else do you explain it well okay i mean i mean the the training involved you know massive amounts of data from the internet and actually took lots and lots of computer power lots of electricity right you know there are some some very prosaic reasons why this wasn't done earlier right right but um you know it costs some tens of millions of dollars i think you know that's just for approximately like a few million dollars oh okay okay oh really okay you know oh all right all right thank you i mean as they as they scale it up you know it will cost but then the hope is cost comes down and all that kind of stuff but um basically you know it is a neural net you know so i mean i mean or what's now called a deep net but you know they're basically the same thing right so it's a it's a form of you know uh algorithm that people have known about for decades right uh but it is constantly trying to solve the problem predict the next word right so it's just trying to predict what comes next it's not trying to decide what what it should say what ought to be true it's trying to predict what someone who had said all of the words up to the preceding one would say next although to push back on that that's how it's trained but that's right no but it's arguable arguable yeah that our very cognition could be a mechanism as that simple of course of course i never said that it wasn't right but right but yeah i mean i mean and sometimes that that is you know if there is a deep philosophical question that's raised by gpt3 then that is it right are we doing anything other than you know this predictive processing just trying to constantly trying to fill in a blank of what would come next after what we just said up to this point is that what i'm doing right now it's impossible so the intuition that a lot of people have will look this thing is not going to be able to reason the mountain everest question do you think it's possible that gbt5 6 and 7 would be able to with this exact same process begin to do something that looks like is indistinguishable to us humans from reasoning i mean the truth is that we don't really know what the limits are right because exactly because you know what we've seen so far is that you know gbt3 was basically the same thing as gpt-2 but just with you know a much larger uh uh network you know more training time bigger training corpus right and it was you know very noticeably better right than its immediate predecessor so uh we you know we don't know where you hit the ceiling here right i mean that's the that's the amazing part and maybe also the scary part right that uh you know now my guess would be that that you know at some point like there has to be diminishing returns like it can't be that simple can it right right but i i i i wish that i had more to base that guess on right yeah i mean some people say that there will be a limitation on the we're going to hit a limit on the amount of data that's on the internet yes yeah yeah so sure so so there's certainly that limit i mean there's also um you know like if you are looking for questions that will stump gpt3 right you can come up with some without you know like you know even getting it to learn how to balance parentheses right like it can you know it doesn't do such a great job right uh you know like like you know and you know and its failures are are are ironic right like like basic arithmetic right and you think you know isn't that what computers are supposed to be best at yeah isn't that where computers already had us beat a century ago yeah right and yeah and yet that's where gpt-3 struggles right but it's it's amazing you know that it's almost like a young child in that way right that uh uh um but but uh somehow you know because it is just trying to predict what what uh comes next it doesn't know when it should stop doing that and start doing something very different like some more exact logical reasoning right and so so you know the uh uh you know you one one is naturally led to guess that our brain sort of has some element of predictive processing but that it's coupled to other mechanisms right that it's coupled to you know first of all visual reasoning which gpt3 also doesn't have any of right although there's some demonstration that there's a lot of promise there oh yeah it can complete images that's right and using the exact same kind of transformer mechanisms to like watch videos on youtube and uh so the same uh the same self-supervised mechanism to be able to look it'd be fascinating to think what kind of completions you could do oh yeah no absolutely although like if we ask it to like you know a word problem that involve reasoning about the locations of things in space i don't think it does such a great job on those right to take an example and so so the guess would be well you know humans have a lot of predictive processing a lot of just filling in the blanks but we also have these other mechanisms that we can couple to or that we can sort of call the subroutines when we need to and that maybe maybe you know uh to go further that one would one would want to integrate other forms of reasoning let me go on another topic that is amazing uh which is complexity uh what uh and then start with the most absurdly romantic question of what's the most beautiful idea in computer science or theoretical computer science to you like what just early on in your life or in general i've captivated you and just grabbed you i think i'm gonna have to go with the idea of universality uh you know if you're really asking for the most beautiful i mean uh so universality uh is the idea that you know you put together a few simple operations like in the case of boolean logic that might be the and gate the or gate the not gate right and then your first guess is okay this is a good start but obviously as i want to do more complicated things i'm going to need more complicated building blocks to express that right and and that was actually my guess when i first learned what programming was i mean when i was you know an adolescent and i someone showed me uh uh apple basic and then you know uh gw basic if any any anyone listening remembers that okay but uh you know i thought okay well now you know i mean i i thought i felt like um this is a revelation you know it's like finding out where babies come from it's like that level of you know why didn't anyone tell me this before right but i thought okay this is just the beginning now i know how to write a basic program but to you know really write a an interesting program like a you know a video game which had always been my my dream as a kid to you know create my own nintendo games right that you know but you know obviously i'm going to need to learn some way more complicated form of programming than that okay but you know eventually i learned this incredible idea of universality and that says that no you throw in a few rules and then you can you already have enough to express everything okay so for example the and the or and the not gate uh can all or in fact even just the and in the not gate or even just even just the nand gate for example uh is already enough to express any boolean function on any number of bits you just have to string together enough of them because you can build a universe with nand gates you can build the universe out of nand gates yeah uh you know the the simple instructions of basic are already enough at least in principle you know if we ignore details like how much memory can be accessed and stuff like that that is enough to express what could be expressed by any programming language whatsoever and the way to prove that is very simple we simply need to show that in basic or whatever we could write a an interpreter or a compiler for whatever is other programming language we care about like c or or java or whatever and as soon as we had done that then ipso facto anything that's expressible in c or java is also expressible and basic okay and so this idea of universality you know goes back at least to alan turing in the 1930s when you know he uh uh um wrote down this incredibly simple pared down model of a computer the touring machine right which uh you know he pared down the instruction set to just read a symbol you know go to write a symbol move to the left move to the right uh halt change your internal state right that's it okay and anybody proved that um you know this could simulate all kinds of other things uh you know and so so in fact today we would say well we would call it a touring universal model of computation that is you know just as it has just the same expressive power that basic or uh java or c plus plus or any of those other languages have uh because anything in those other languages could be compiled down to touring machine now touring also proved a different related thing which is that there is a single touring machine uh that can simulate any other touring machine if you uh uh just describe that other machine on its tape right and likewise there is a single touring machine that will run any c program you know if you just put it on its tape that's that that's a second meaning of universality first of all that he couldn't visualize it and that was in the 30s 30s that's right before computers really i mean um i don't know how i wonder what that felt like uh you know learning that there's no santa claus or something uh uh because i i don't know if that's empowering or paralyzing because it it doesn't uh give you any ins it's uh like you can't write a software engineering book and make that the first chapter and say we're done well i mean i mean right i mean i mean in one sense it was this enormous flattening of the universe yes right i had imagined that there was going to be some infinite hierarchy of more and more powerful programming languages you know and then i kicked myself for you know for having such a stupid idea but apparently girdle had had the same conjecture in the 30s and then you know you're in good company well yeah and then and then and then tori and then girdle read toring's paper and he kicked himself and he said yeah i was completely wrong about that okay but um but you know i had thought that you know maybe maybe where i can contribute will be to invent a new more powerful programming language that lets you express things that could never be expressed in basic yeah right and you know and then you know how would you do that obviously you couldn't do it itself in basic right but uh uh but you know there is this incredible flattening that happens once you learn what is universality but then it's also um uh like um an opportunity because it means once you know these rules then you know the sky is the limit right then you have kind of the same weapons at your disposal that the world's greatest programmer has it's now all just a question of how you wield them right exactly but so every problem is solvable but some problems are harder than others and well yeah there's the question of how much time you know well of how hard is it to write a program and then there's also the questions of what resources does the program need you know how much time how much memory those are much more complicated questions of course ones that we're still struggling with today exactly so you've uh i don't know if you created complexity zoo or i did create the complexity zoo what is it what's complexity oh all right all right complexity theory is the study of sort of the inherent resources needed to solve uh computational problems okay so uh uh it's easiest to give an example uh like uh let's say we want to um um add two two numbers right if i want to add them uh um you know if the numbers are twice as long then it only it will take me twice as long to add them but only twice as long right it's no worse than that for a computer or or for a person we're using pencil and paper for that matter if you have a good algorithm yeah that's right i mean even if you just if you just use the elementary school algorithm of just carrying you know then it it takes time that is linear in the length of the numbers right now multiplication if you use the elementary school algorithm is harder because you have to multiply each digit of the first number by each digit of the second one yeah and then deal with all the carries so that's what we call a quadratic time algorithm right if um the numbers become twice as long now you need four times as much time okay so now as it turns out we uh people discovered much faster ways to multiply numbers using computers and today we know how to multiply two numbers that are n digits long using a number of steps that's nearly linear in n these are questions you can ask but now let's think about a different thing that people uh you know they've encountered in elementary school uh factoring a number okay take a number and find its prime factors right and here you know if i give you a number with 10 digits i ask you for its prime factors well maybe it's even so you know that two is a factor you know maybe it ends in zero so you know that ten is a factor right but you know other than a few obvious things like that you know if the prime factors are all very large then it's not clear how you even get started right you know you it seems like you have to do an exhaustive search among an enormous number of factors now um and and as many people might know uh the uh for for for better or worse the uh security you know of most of the encryption that we currently use to protect the internet is based on the belief and this is not a theorem it's a belief that uh that factoring is an inherently hard problem uh for our computers we do know algorithms that are better than just trial division and just trying all the possible divisors uh but they are still basically exponential exponential is hard yeah exactly so this so the the fastest algorithms that anyone has discovered at least publicly discovered you know i'm assuming that the nsa doesn't know something better yeah okay but they they take time that basically grows exponentially with the cube root of the size of the number that you're factoring right so that cube root that's the part that takes all the cleverness okay but there's still an exponential there's still an exponentiality there but what that means is that like when people use a thousand bit keys for their cryptography that can probably be broken using the resources of the nsa or the world's other intelligence agencies you know people have done analyses that say you know with a few hundred million dollars of computer power they could totally do this and if you look at the documents that snowden released you know it it it look it looks a lot like they are doing that or something like that it would kind of be surprising if they weren't okay but you know if that's true then in in some ways that's reassuring because if that's the best that they can do then that would say that they can't break two thousand bit numbers right exactly exactly right then two thousand bit numbers would be would be beyond what even they could do they haven't found an efficient algorithm that's where all the worries and the concerns of quantum computing came in that there's some kind of shortcut around that right so complexity theory is a you know is is a huge part of let's say the theoretical core of computer science you know it it started in the 60s and 70s as you know sort of a you know autonomous field so it was you know already you know i mean you know it was well developed even by the time that i was born okay but uh um uh i in 2002 i made a website called the complexities zoo uh to answer your question uh where i just tried to catalog the different complexity classes which are classes of problems that are solvable with different kinds of resources right okay so these are kind of um you know you could think of complexity classes as like being almost to to to theoretical computer science like what the elements are to chemistry right they're sort of you know there are our most basic objects in in a certain way i feel like the elements have uh have a characteristic to them where you can't just add an infinite number well you could but beyond a certain point they become unstable right right so it's like you know in theory you can have atoms with yeah and look look i mean i mean i mean a neutron star you know is a nucleus with you know uncalled billions of of of of nuke of of uh of of of of neutrons in it of of hadrons in it okay but uh um you know for for sort of normal atoms right probably you can't get much above 100 you know atomic weight 150 or so or sorry sorry i mean i mean beyond 150 or so protons without it you know very quickly fissioning uh with complexity classes well yeah you you can have an infinity of complexity classes uh but you know maybe there's only a finite number of them that are particularly interesting right just like with anything else you know you uh uh you care about some more than about others so what kind of interesting classes are there yeah i mean you could have just maybe say what are the if you you take any kind of computer science class what are the classes you learn good let me let me tell you sort of the the the biggest ones the ones that you would learn first so you know first of all there is p that's what it's called okay it stands for polynomial time and this is just the class of all of the problems that you could solve with a conventional computer like your iphone or your laptop uh you know by a completely deterministic algorithm right using a number of steps that grows only like the size of the input raised to some fixed power okay so uh if your algorithm is linear time like you know for adding numbers okay that that problem is in p if you have an algorithm that's quadratic time like the uh elementary school algorithm for multiplying two numbers that's also in p even if it was the size of the input to the 10th power or to the 50th power well that wouldn't be very uh good in practice but you know formally we would still count that that would still be in p okay but if your algorithm takes exponential time meaning like if every time i add one more uh data point to your input if the time that needed by the algorithm doubles if you need time like 2 to the power of the amount of input data then uh that is that we call an exponential time algorithm okay and that is not polynomial okay so p is all of the problems that have some polynomial time algorithm okay so that includes most of what we do with our computers on a day-to-day basis you know all the you know sorting basic arithmetic you know whatever is going on in your email reader or in angry birds okay it's all in p then the next uh super important class is called np uh that stands for non-deterministic polynomial okay does not stand for not polynomial which is a common confusion um but np was basically all of the problems where if there is a solution then it is easy to check the solution if someone shows it to you okay so actually a perfect example of a problem in np is uh factoring the one i told you about before like if i gave you a number with thousands of digits and i told you that you know i i asked you does this uh does this have at least um three non-trivial divisors right that might be a super hard problem to solve right might take you millions of years using any algorithm that's known at least running on our existing computers okay but if i simply showed you the divisors i said here are three divisors of this number then it would be very easy for you to ask your computer to just check each one and see if it works just divide it in see if there's any remainder right and if they all go in then you've checked well i guess there were right so um so any problem where you know wherever there's a solution there is a short witness that can be easily like a polynomial size witness that can be checked in polynomial time that we call an np problem okay beautiful and uh yeah so so every problem that's in p is also in np right because you know you could always just ignore the witness and just you know if a problem is in p you can just solve it yourself right okay but now the influence is the central you know mystery of theoretical computer science is is every np problem in p so if you can easily check the answer to a a computational problem does that mean that you can also easily find the answer even though there's all these problems that appear to be very difficult to find the answer it's still an open question whether a good answer exists so what's yours no one has proven that there's no way to do it it's arguably the most uh i don't know the most famous the most maybe interesting maybe disagree with that problem in theoretical computer science so what's your most famous for sure p equals np yeah if you were to bet all your money where do you put your money that's an easy one p is not equal to np okay so i like to say that if we were physicists we would have just declared that to be a law of nature you know just like just like thermodynamics it's hilarious giving ourselves nobel prizes for its discovery yeah you know and look if later if later it turned out that we were wrong we just give ourselves more more nobel prizes yeah i mean no i mean i mean i mean it's it's really just because we are mathematicians or descended from mathematicians you know we have to call things conjectures that other people would just call empirical facts or discoveries right but one shouldn't read more into the difference in in language you know about the underlying truth so okay so you're a good investor and good spender money so then let me i don't know that let me ask another way is it possible at all and what would that look like if p indeed equals np well i do think that it's possible i mean in fact you know when people really pressed me on my blog for what odds would i put like well you know two or three percent odds wow that's pretty good that p equals np yeah just speak well um because you know when p i mean i mean you you really have to think about like if there were 50 you know mysteries like p versus np and if i made a guess about every single one of them would i expect to be right 50 times right and the truthful answer is no okay yeah so you know and and and and and that's what you really mean in saying that you know you have you know better than 98 odds for something okay but um so so yeah you know i mean there could certainly be surprises and look if p equals np well then there would be the further question of you know is the algorithm actually efficient in practice right i mean don knuth who i know that you you've interviewed as well right he uh likes to conjecture that p equals np but that the algorithm is so inefficient that it doesn't matter anyway right now i i don't know i've listened to him say that i don't know whether he says that just because he has an actual reason for thinking it's true or just because it sounds cool yeah okay but um but you know that that's a logical possibility right that the algorithm could be n to the 10 000 time or it could even just be n squared time but with a leading constant of a it could be a google times n squared or something like that and in that case the fact that p equals np well it would it would uh you know ravage the whole theory of uh complexity we would have to you know rebuild from the ground up but in practical terms it might mean very little right if the algorithm was too inefficient to run if the algorithm could actually be run in practice like if if it had small enough constants you know to or if you could improve it to where it had small enough constants that it was uh efficient in practice then that would change the world okay you think it would have like what kind of impact well okay i mean i mean here's an example i mean you could well okay just for starters you could break basically all of the encryption that people use to protect the internet first you could you could break bitcoin and every other cryptocurrency or you know uh mine as much bitcoin as you wanted right uh you know become a you know become a a super duper billionaire right and then and then plot your next move right okay that's just for starters right right now your next move might be something like you know you now have like a theoretically optimal way to train any neural network to find parameters for any neural network right so you could now say like is there any small neural network that generates the entire content of wikipedia right if you know and now the question is not can you find it the question has been reduced to does that exist or not yes if it does exist then the answer would be yes you can find it okay if if if you had this algorithm in your hands okay you could ask your computer you know i mean i mean p versus np is one of these seven problems that carries this million dollar prize from the clay foundation you know if you solve it uh you know and others are the riemann hypothesis uh the punk array conjecture which was solved although the solver turned down the price right and uh and and four others but what i like to say the way that we can see that p versus np is the biggest of all of these questions is that if you had this fast algorithm then you could solve all seven of them okay you just ask your computer you know is there a short proof of the riemann hypothesis right you know that a machine could in a language where a machine could verify it and provided that such a proof exists then your computer finds it in a short amount of time without having to do a brute force search okay so i mean i mean those are the stakes of what we're talking about but i hope that also helps to give your listeners some intuition of why i and most of my colleagues would put our money on p not equaling np is it possible i apologize this is a really dumb question but is it possible to that proof will come out that p equals np but an algorithm that makes p equals np is impossible to find um is that like crazy okay well well if p equals np it would mean that there is such an algorithm that it exists yeah but um um you know it would it would mean that it exists now you know in practice normally the way that we would prove anything like that would be by finding the algorithm by finding that one algorithm but there is such a thing as a non-constructive proof that an algorithm exists you know this is really only reared its head i think a few times in the history of our field right but you know it is it is theoretically possible that that that that such a thing could happen but you know there are so even here there are some amusing observations that one could make so there is this famous observation of leonid levin who is you know one of the original discoverers of np completeness right and he said well consider the following algorithm that like i i guarantee we'll solve the np problems efficiently just as provided that p equals np okay here is what it does it just runs you know it enumerates every possible algorithm in a gigantic infinite list yeah right from like in like alphabetical order right you know and many of them maybe won't even compile so we just ignore those okay but now we just you know run the first algorithm then we run the second algorithm we run the first one a little bit more then we run the first three algorithms for a while we won the first four for a while this is called dovetailing by the way this is a known trick in um uh um theoretical computer science okay but we do it in such a way that you know whatever is the algorithm out there in in in our list that solves np-complete you know the np problems efficiently will eventually hit that one right and now the key is that whenever we hit that one you know it you know by assumption it has to solve the problem that's to find the solution and once it claims to find a solution then we can check that ourself right because these are increasing problems then we can check it now this is utterly impractical all right you know you'd have to do this enormous exhaustive search among all the algorithms but from a certain theoretical standpoint that is merely a constant prefactor that's merely a multiplier of your running time so there are tricks like that one can do to say that in some sense the algorithm would have to be uh constructive but you know in in in the human sense you know it is possible that you know it's conceivable that one could prove such a thing uh via a non-constructive method is is that likely i don't think so first no no no not personally so that's p and and p but the complexities it was full of wonderful creatures well it's got about 500 of them 500. so how do you get uh yeah yeah how do you get more how do you yeah well yeah well okay i mean i mean i mean just for starters there is everything that we could do with a conventional computer with a polynomial amount of memory okay but possibly an exponential amount of time because we get to reuse the same memory over and over again okay that is called p space okay and that's actually a uh we think an even larger class than np okay well p is contained in np which is contained in p space and we think that those containments are strict and the constraint there is on the memory the memory has to grow polynomially with the size of the product that's right that's right but in p space we now have interesting things that were not in in np like uh as a famous example you know from a given position in chess you know does white or black have the win let's say assuming provided that the game lasts only for a a reasonable number of moves okay or or or likewise for go okay and you know even for the generalizations of these games to arbitrary size boards because with an eight by eight board you could say that's just a constant size problem you just you know in principle you just solve it in o of one time right but so we really mean the uh the generalizations of you know games to uh arbitrary size boards here or um another thing in p space would be uh like i give you some really hard um constraint satisfaction problem like you know a you know traveling person or you know packing boxes into the trunk of your car or something like that and i asked not just is there a solution which would be an np problem but i ask how many solutions are there okay that you know count the number of of solu of valid solutions that that that actually gives those problems lie in a complexity class called sharp p or like it looks like hashtag like hashtag p you got it okay which sits between np and p space um there's all the problems that you can do in exponential time okay that's called x so um and by the way uh it it was proven in the 60s that x is larger than p okay so we know that much we know that there are problems that are solvable in exponential time that are not solvable in polynomial time okay in fact we even know more we know that there are problems that are solvable in n cube time that are not solvable in n squared time and that those don't help us with a controversy between p and m unfortunately it seems not or certainly not yet right the the the techniques that we use to establish those things they're very very related to how touring proved the unsolvability of the halting problem but they seem to break down when we're comparing two different resources like time versus space or like you know p versus np okay but you know i mean there's there's what you can do with a randomized algorithm right that can sometimes you know with some has some probability of making a mistake that's called bpp bounded our probabilistic polynomial time and then of course there's one that's very close to my own heart what you can efficiently do during polynomial time using a quantum computer okay and that's called bqp right and so you know what's understood about that class okay so p is contained in bpp which is contained in bqp which is contained in p space okay so anything you can in fact in in like in something very similar to sharp p bqp is basically you know well it's contained in like p with the magic power to solve sharp p problems okay why why is bqp contained in uh p space oh that's an excellent question uh so uh there there is um well i mean one one has to prove that okay but uh the proof um uh you could you could think of it as uh using uh richard feynman's picture of quantum mechanics which is that you can always you know we haven't really talked about uh quantum mechanics in this in this conversation we we did in our previous yeah yeah we did last time but yeah we did last time okay but uh uh but basically you could always think of a quantum computation as uh like a branching tree of possibilities where each pos each possible path that you could take through you know your the space has a complex number attached to it called an amplitude okay and now the rule is you know when you make a measurement at the end well you see a random answer okay but quantum mechanics is all about calculating the probability that you're going to see one potential answer versus another one right and the rule for calculating the probability that you'll see some answer is that you have to add up the amplitudes for all of the paths that could have led to that answer and then you know that's a complex number so that you know how could that be a probability then you take the squared absolute value of the result that gives you a number between zero and one okay so um yeah i just i just summarized quantum mechanics in like 30 seconds okay but uh but now you know what what this already tells us is that anything i can do with a quantum computer i could simulate with a classical computer if i only have exponentially more time okay and why is that because if i have exponential time i could just write down this entire branching tree and just explicitly calculate each of these amplitudes right you know that will be very inefficient but it will work right it's enough to show that quantum computers could not solve the halting problem or you know they could never do anything that is literally uncomputable in touring sense okay but now as i said there is even a stronger result which says that bqp is contained in p space the way that we prove that is that we say if if all i want is to calculate the probability of some particular output happening we know which is all i need to simulate a quantum computer really then i don't need to write down the entire quantum state which is an exponentially large object all i need to do is just calculate what is the amplitude for that final state and to do that i just have to sum up all the amplitudes that lead to that state okay so that's an exponentially large sum but i can calculate it just reusing the same memory over and over for each term in the song hence the p in the pieces yeah yeah so what uh out of that whole complexity zoo and it could be bqp what do you find is the most uh uh the class that captured your heart the most is the most beautiful class there's just yeah i i used uh as my email address uh bqpqpali gmail.com yes because uh bqp slash q poly well you know amazingly no one had taken it amazing but you know but th this is a class that i was involved in sort of uh defining proving the first theorems about uh in 2003 or so so it was kind of close to my heart but this is like if we extended um bqp which is the class of everything we can do efficiently with a quantum computer uh to allow quantum advice which means imagine that you had some special initial state okay that could somehow help you do computation and maybe um such a state would be exponentially hard to prepare okay but you know maybe somehow these states were formed in the big bang or something and they've just been sitting around ever since right if you found one and if this state could be like ultra power there are no limits on how powerful it could be except that this state doesn't know in advance which input you've got right it only knows the size of your input you know and then that that's bqp slash q probably so that's that's one that i just personally happen to love okay but um you know if you're asking like what's the you know there's there's there's a class that i think is is is way more beautiful than you know or fundamental that a lot of people even within uh this this field realize that it is that class is called sck or statistical zero knowledge um and you know there's a very very easy way to define this class which is to say suppose that i have two algorithms that each sample from probability distributions right so each one just outputs random samples according to you know possibly different distributions and now the question i ask is you know you know let's say distributions over strings of n bits yeah so over an exponentially large space now i ask are these two distributions close or far as probability distributions okay any problem that can be reduced to that you know that can be put into that form is an sdk problem and the way that this class was originally discovered was completely different from that and was kind of more complicated it was discovered as the class of all of the problems that have a certain kind of what's called zero knowledge proof zero knowledge proofs are one of the central ideas in cryptography um you know shafi goldwasser and silvio mccauley won the touring award for you know inventing them and they're at the core of even some some cryptocurrencies that you know people people use nowadays but um there are zero knowledge proofs or ways of proving to someone that something is true like you know that there is a a solution to this you know uh optimization problem or that these two graphs are isomorphic to each other or something but without revealing why it's true without revealing anything about why it's true okay sdk is all of the problems for which there is such a proof uh that doesn't rely on any cryptography okay and if if you wonder like how could such a thing possibly exist right well like imagine that i had two graphs and i wanted to convince you that these two graphs are not isomorphic meaning you know i cannot permute one of them so that it's the same as the other one right you know that might be a very hard statement to prove like i might you know you might have to do a very exhaustive enumeration of you know all the different permutations before you were convinced that it was true but what if there were some all-knowing wizard that said to you look i'll tell you what just pick one of the graphs randomly then randomly permute it then send it to me and i will tell you which graph you started with okay and i will do that every single time right and load that in and let's say that that wizard did that a hundred times and it was right every time yeah right now if the graphs were isomorphic then you know it would have been flipping a coin each time right it would have had only a one in two to the 100 power chance of you know of guessing right each time but you know so so if it's right every time then now you're statistically convinced that these graphs are not isomorphic even though you've learned nothing new about why they aren't so fascinating so yeah so so sdk is all of the problems that have protocols like that one but it has this beautiful other characterization it's shown up again and again in my in my own work in you know a lot of people's work and i think that it really is one of the most fundamental classes it's just that people didn't realize that when it was first discovered so we're living in the middle of a pandemic currently yeah how has your life been changed or no better to ask like how is your perspective of the world change with this uh world-changing event of a pandemic overtaking the entire world yeah well i mean i mean all of our lives have changed you know like i guess as with no other event since i was born you know you would have to go back to world war ii for something i think of this magnitude you know uh on you know the way that we live our lives as for how it has changed my world view i think that the the failure of institutions you know like uh like like the cdc like you know other institutions that we sort of thought were were trustworthy like a lot of the media uh was uh staggering was was absolutely breathtaking uh it is something that i would not have predicted right i think i i uh wrote on my blog uh uh that you know you know it it's it's abs it's fascinating to like re-watch the movie uh contagion from a decade ago right that correctly foresaw so many aspects of you know what was going on you know a uh an airborne you know virus originates in china spreads to you know much of the world you know shuts everything down until a vaccine can be developed uh you know everyone has to stay at home you know you know it gets uh um you know an enormous number of things right okay but the one thing that they could not imagine you know is that like in this movie everyone from the government is like hyper comp competent hyper you know dedicated to the public good right best of the best you know yeah the they're the best of the best you know they could you know and there are these conspiracy theorists right who uh think you know you know this is all fake news there's no there's not really a pandemic and those are some random people on the internet who the hyper competent government people have to you know oppose right they you know in in trying to envision the worst thing that could happen like you know the the there was a failure of imagination the movie makers did not imagine that the conspiracy theorists and the you know and the incompetence and the nut cases would have captured our institutions and be the ones actually running things so you had a certain yeah i i love competence in all walks of life i love i get so much energy i'm so excited but people do amazing job and i like you uh well maybe you can clarify but i had maybe not an intuition but i hope that government at his best could be ultra com competent what uh first of all two questions like how do you explain the lack of confidence and the other maybe on the positive side how can we build a more competent government well there's an election in two months i mean you know you have a faith that the election i uh you know it's not gonna fix everything but you know it's like i feel like there is a ship that is sinking and you could at least stop the sinking but uh uh you know i think that there are there are much much deeper problems i mean i think that uh um you know it is it is plausible to me that you know a lot of the the failures you know with the cdc with uh some of the other health agencies even you know you know pre-date trump you know pre-date the you know right-wing populism that has sort of taken over much of the world now and um you know i think that uh uh you know it was is you know it is very i'm actually you know i've actually been strongly in favor of you know rushing vaccines of uh uh you know i thought that we could have done you know human human challenge trials you know which were not done right we could have you know like i had you know volunteers you know to uh uh actually you know be you know uh get vaccines get you know exposed to covid so you know innovative ways of accelerating what you've done previously over a long time i thought that you know each each month that you that that a vaccine is is closer is like trillions of dollars are used for civilization and of course lives you know at least you know hundreds of thousands of lives are you surprised that it's taking this long we still don't have a plan there's still not a feeling like anyone is actually doing anything in terms of uh elite alleviating like any kind of plan so there's a bunch of stuff this vaccine but you could also do a testing infrastructure where yeah everybody's tested non-stop with contact tracing all that kind of well i mean i i'm as surprised as almost everyone else i mean this is a historic failure it is one of the biggest failures in the 240 year history of the united states right and we should be you know crystal clear about that and you know one thing that i think has been missing you know even even from the more competent side is like you know is sort of the the world war ii mentality right the you know the mentality of you know let's just you know you know if if if we can by breaking a whole bunch of rules you know get a vaccine and you know and even half the amount of time as we thought then let's just do that because uh you know you know like like we have to we have to weigh all of the moral qualms that we have about doing that against the moral qualms of not doing and one key little aspect yeah that's deeply important to me and going that topic next is uh the world war ii mentality wasn't just about you know breaking all the rules to get the job done there was a togetherness to it there's yes so i would if i were president right now it seems quite elementary to unite the country because we're facing a crisis it's easy to make the virus the enemy and it's very surprising to me that um the div the division has increased as opposed to decreasing yeah so that that's that's heartbreaking yeah well look i mean it's been said by others that this is the first time in the country's history that we have a president who does not even pretend to you know what want to unite the country right yeah and you know i mean i mean i mean lincoln who fought a civil war you know you know said he wanted to unite the country right uh you know and and and i i do i do worry enormously about what happens if the results of this election are contested you know and you know will there be violence as a result of that and will we have a clear path of succession and you know look i mean you know this is all we're going to find out the answers to this in two months and if none of that happens maybe i'll look foolish but i am willing to go on the record and say i am terrified about that yeah i've been reading the the rise and fall of the third reich this is it so if i can this this is like one little voice to put out there that i think november will be a really critical month for people to breathe and put love out there do not you know anger in those in that context no matter who wins no matter what is said will destroy our country may destroy our country it may destroy the world because of the power of the country so it's really important to be patient loving empathetic like one of the things that troubles me is that even people on the left are unable to have a love and respect for people who voted for trump they can't imagine that there's good people that could vote for the opposite side and that's oh i know there are because i know some of them yeah right i mean you know it's still you know maybe it baffles me but you know i i know such people let me ask you this it's also heartbreaking to me on the topic of cancer culture yeah so in the machine learning community i've seen it a little bit that there's um aggressive attacking of people who are trying to have a nuanced conversation about things and it's troubling because it feels like nuanced conversation is the only way to talk about difficult topics and when there's a thought police and speech police on any nuanced conversation that everybody has to like in animal farm chant that racism is bad and sexism is bad which is things that everybody believes and they're they can't possibly say anything nuance it feels like it goes against any kind of progress from my kind of shallow perspective but you've written a little bit about cancer culture did you have thoughts that are well i mean i mean i mean to say that i am opposed to you know the this trend of of cancellations or of you know shouting people down rather than engaging them that would be a massive understatement right and i feel like you know i have put my money where my mouth is you know not as much as some people have but you know i i've tried to do something i mean i have defended you know uh some unpopular people and unpopular you know ideas on my blog i've you know tried to defend you know norms of uh of uh of of open discourse of you know reasoning with our opponents even when i've been shouted down for that on social media uh you know called a racist called a sexist all of those things and which by the way i should say you know i would be perfectly happy to you know say you know if we had time to say you know you know ten thousand times you know my uh hatred of racism of sexism of homophobia right but what i don't want to do is to cede to uh some particular political faction the right to define exactly what is meant by those terms to say well then you have to agree with all of these other extremely contentious positions or else you are a misogynist or else you are a racist right i say that well no you know you know don't like don't i or you know don't people like me also get a say in the discussion about you know what is racism about what is going to be the most effective to combat racism right and you know this this this um cancellation mentality i think is spectacularly ineffective at its own professed goal of you know combating racism and sexism what's a positive way out so i i try to i don't know if you see what i do on twitter but i on twitter i mostly and in my whole in my life i've actually it's who i am to the core is like i really focus on the positive and i try to put love out there in the world yeah and still i get attacked and i look at that and i wonder like are you two i didn't know like i haven't actually said anything difficult and nuanced you talk about somebody like steven pinker yeah who i actually don't know the full range of things that um that he's attacked for but he tries to say difficult he tries to be thoughtful about difficult topics he does and obviously he just gets slaughtered by well i mean i mean i mean i mean yes but it's also amazing how well steve has withstood it i mean he just survived that attempt to cancel him just a couple of months ago right psychologically he survives it too which yeah worries me he says i don't think i can yeah i i've gotten to know steve a bit he is incredibly unperturbed by this stuff uh i i admire that and i envy it i wish that i could be like that i mean my impulse when i'm getting attacked is i just want to engage every single like anonymous person on twitter and reddit who is saying mean stuff about me and i wanted to say well look can we just talk this over for an hour and then you know you'll see that i'm not that bad and you know sometimes that even works the problem is then there's the you know the 20 000 other ones right that's not but psychologically does that wear on you it does it does but yeah i mean in terms of what is the solution i mean i wish i knew right and so you know in a certain way these problems are maybe harder than p versus np right i mean uh you know but but i think that part of it has to be for you know that i think that there's a lot of sort of silent support for what i'll call the the the open discourse side the you know reasonable enlightenment side and i think that that that support has to become less silent right i think that a lot of people uh this sort of you know like agree that oh you know a lot of these cancellations and attacks are ridiculous but are just afraid to say so right or else they'll get they'll get shouted down as well right that's just the standard witch hunt dynamic which you know of course this uh you know this faction understands and exploits to its great advantage but um you know if more people just you know said you know like we're not going to stand for this right uh uh you know you know this is this is you know where guess what we're against racism too but you know this you know what you're doing is ridiculous right um you know and the hard part is like it takes a lot of mental energy it takes a lot of time you know even if you feel like you're not going to be cancelled or you know you're staying on the safe side like it takes a lot of time to uh to to phrase things in exactly the right way and to uh you know respond to everything people say so but i think that um you know the more people speak up than uh uh you know from from from all political persuasions you know from like all you know walks of life then you know the the easier it is to move forward since we've been talking about love can you um last time i talked to you about meaning of life a little bit but here has it's a weird question to ask a computer scientist but has love for other human beings for for things for the world around you played an important role in your life have you um you know it's easy for a world-class computer scientist uh uh yeah you could even call yourself like a physicist everything to be lost in the books is the connection to other humans love for other humans played an important role i love my kids uh i love my wife i love my parents um uh you know i um i'm probably not not different from most people and loving their families uh and and in that being very important uh in my life uh now i should remind you that you know i am a theoretical computer scientist if you're looking for deep insight about the nature of love you're probably looking in the wrong place to ask me but uh but sure it's been important but is it uh is there something from a computer science perspective to be said about love is there uh or is that is that even beyond into the realm of beyond the realm of consciousness there was there was this great uh cartoon i think it was one of the classic xkcds where it shows like a heart and it's like you know squaring the heart taking the four-year transform of the heart you know integrating the heart you know uh uh you know each each thing and then it says you know my normal approach is useless here i'm so glad i asked this question i think there's no better way to uh to end this guy i hope we get a chance to talk again this has been an amazing cool experiment to do it outside yeah really glad you made it out yeah well i appreciate it a lot it's been a pleasure and i'm glad you were able to come out to austin uh thanks thanks for listening to this conversation with scott erinson and thank you to our sponsors eight sleep simply safe expressvpn and better help please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from scott ericson that i also gave to you in the introduction which is if you always win then you're probably doing something wrong thank you for listening and for putting up with the intro and outro in this strange room in the middle of nowhere and i very much hope to see you next time in many more ways than one you |
Lisa Feldman Barrett: Counterintuitive Ideas About How the Brain Works | Lex Fridman Podcast #129 | the following is a conversation with lisa feldman barrett a professor of psychology at northeastern university and one of the most brilliant and bold thinkers and scientists i've ever had the pleasure of speaking with she is the author of a book that revolutionized our understanding of emotion in the brain called how emotions are made and she's coming out with a new book called seven and a half lessons about the brain that you can and should pre-order now i got a chance to read it already and it's one of the best short whirlwind introductions to the human brain i've ever read it comes out on november 17th but again if there's anybody worth supporting it's lisa so please do pre-order the book now lisa and i agreed to speak once again around the time of the book release especially because we felt that this first conversation is good to release now since we talk about the divisive time we're living through in the united states leading up to the election and she gives me a whole new way to think about it from a neuroscience perspective that is ultimately inspiring of empathy compassion and love quick mention of each sponsor followed by some thoughts related to this episode first sponsor is athletic greens the all-in-one drink that i start every day with to cover all my nutritional bases that i don't otherwise get through my diet naturally second is magic spoon low carb keto friendly delicious cereal that i reward myself with after a productive day the cocoa flavor is my favorite third sponsor is cash app the app i use to send money to friends for food drinks and unfortunately for the many bets i have lost to them please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that the bold first principles way that lisa approaches her study of the brain is something that has inspired me ever since i learned about her work and in fact i invited her to speak at the agi series i organized at mit several years ago but as a little twist instead of a lecture we did a conversation in front of the class i think that was one of the early moments that led me to start this very podcast it was scary and gratifying which is exactly what life is all about and it's kind of funny how life turns a little moments like these that at the time don't seem to be anything out of the ordinary if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with lisa feldman barrett since we'll talk a lot about the brain today do you think let's ask the craziest question do you think there is other intelligent life out there in the universe honestly i've been asking myself lately if there's intelligent life on this planet uh you know i ha i i have to think probabilities suggest yes and also secretly i think i just hope that's true it would be really um i know scientists aren't supposed to have hopes and dreams but uh i i think it would be really cool and i also think it would be really sad if it if it wasn't the case if we really were alone that would be that that would seem profoundly sad i think so it's exciting to you not scary yeah no you know i take a lot of comfort and curiosity it's a great it's a great um resource for dealing with uh stress so um i'm learning all about mushrooms and uh octopuses and you know all kinds of stuff um and so for me this counts i think in the realm of awe but also i think i'm somebody who cultivates awe deliberately on purpose to feel like a speck you know i i find it a relief occasionally it feels small to feel small in a profoundly large and interesting universe so maybe to dig more technically on the question of intelligence do you think it's difficult for intelligent life to arise like it did on earth from everything you've written and studied about the brain how magical of a thing is it in terms of the odds it takes to arise yeah so you know magic is just don't get me wrong i mean i like i like a magic shirt as much as the next person my husband was a magician at one time but you know magic is just a bunch of stuff that we don't really understand how it works yet so i would say from what i understand there are some major steps in the course of evolution that at the beginning of life the step from single cell to multicellular organisms things like that which are really not known i think for me the question is not so much um could it you know what's the likelihood that it would happen again as much as um what are the steps and how long would it take and if it were to happen again on earth would would we end up with the same you know menu of life forms that we currently have now and i think the answer is probably no right there's just so much about evolution that is stochastic and driven by chance but the question is whether that menu would be equally delicious meaning like there'd be rich complexity of the kind of like would we get dolphins and humans or whoever else falls in that category of weirdly intelligent seemingly intelligent however we define that well i think that has to be true if you just look at the range of creatures who've gone extinct i mean but if you look at the range of creatures that are on the earth now it's incredible and you know it's sort of tried to say that but it actually is really incredible um particularly i don't know i mean animals there are animals that seem really ordinary until you watch them closely and then they become miraculous you know like certain types of birds which do very miraculous things uh um build you know bowers and do dances and all these really funky things that are hard to explain uh with a standard evolutionary story although you know um people have them birds are weird they do a lot of for mating purposes they they have a concept of beauty i haven't quite maybe you know much better but it doesn't seem to fit evolutionary arguments well it does fit well it depends right so i think you're talking about the evolution of beauty the um book that was written recently by was it from um without his name richard from i think no i didn't oh it's a great book it's very controversial though because he is argues make an argument that the the question about birds and some other animals is why would they engage in such metabolically costly um displays when it doesn't improve their fitness at all and the answer that he gives is the answer that darwin gave which is sexual selection um not natural selection but you know selection can occur for all kinds of reasons there could be artificial selection which is when we breed animals right which is actually how darwin that that observation helped darwin come to the idea of natural selection oh interesting um and then there's sexual selection um meaning and the argument that that um i think his name is from uh makes is that um that it's the pleasure the selection pressure is the pleasure of female birds which as a woman and um as someone who studies affect that's a great answer i actually think there probably is natural i think there is an aspect of natural selection to it which he maybe hasn't considered but you were saying the reason we brought up birds is the the life we got now seems to be quite yeah so you peek into the ocean peek into the sky there are miraculous creatures look at creatures who've gone extinct and you know in science fiction uh stories you couldn't dream up something as interesting so my guess is that you know intelligent life evolves in in many different ways even on this planet uh there isn't one form of intelligence there's not one brain that gives you intelligence there are lots of different brain structures that can give you intelligence so my guess is that the menagerie might not look exactly the way that it looks now but it would certainly be as as interesting but if we look at the human brain versus the brains or whatever you call them the mechanisms of intelligence in our ancestors even early ancestors that you write about for example in your new book what what's the difference between the the fanciest brain we got which is the human brain and uh the ancestor brains that it came from yeah i think it depends on how far back you want to go you go all the way back right in your book so what's the interesting comparison would you say well first of all i wouldn't say that the human brain is the fanciest brain we've got i mean an octopus brain is pretty different and pretty fancy and they can do some pretty amazing things that we cannot do you know we can't grow back limbs we can't change color and texture we can't comport ourselves and squeeze ourselves into a little crevice i mean these are things that we invent these are like superhero abilities that we invent in stories right we can't do any of those things and so the human brain is certainly um we can certainly do some things that other animals can't do that seem pretty impressive to us but but i would say that there there are a number of animal brains which seem pretty impressive to me that can do interesting things and really impressive things that we can't do i mean with your work on how emotions are made and so on you you kind of repaint the the view of the brain as um as less glamorous i suppose than you would otherwise think or like i guess you draw a thread that connects all brains uh together in terms of homeostasis and all that kind of stuff i yeah i wouldn't say that the that the human brain is any less miraculous than anybody else would say i just think that there are other brain structures which are also miraculous and i also think that there are a number of things about the human brain which we share with other other vertebrates other animals with backbones but um that are that we share these miraculous things but we can do some things in abundance and we can also do some things with our brains together working together that other animals can't do or at least we haven't discovered their ability to do it yeah this social thing how i mean that's one of the things you write about uh what's uh how do you make sense of the fact uh like the book sapiens and the fact that we're able to kind of connect like network our brains together like you write about i'll try i'll try to stop saying that uh is that is that like some kind of feature that's built into there is that unique to our human brains like how do you make sense of that what i would say is that our ability to coordinate with each other is not unique um to humans there are lots of animals who can do that and we um but what we do with that coordination is unique because of some of the structural features in our brains and it's not that other animals don't have those structural features it's we have them in abundance so you know the human brain is not larger than you would expect it to be for a primate of our size if you took a chimpanzee and you ex grew it to the size of a human that chimpanzee would have a brain that was the size of a human brain so there's nothing special about our brain in terms of its size there's nothing special about our brain in terms of the um the basic blueprint that builds our brain from an embryo is the basic blueprint that builds all mammalian brains and maybe even all vertebrate brains um it's just that because of its size and particularly because of the size of the cerebral cortex which is the um a part um that people mistakenly attribute to rationality yeah mistakenly is that where all the clever stuff happens well no it really isn't and i will also say that lots of clever stuff happens in animals who don't have a cerebral cortex but right um but uh but because of the size of the cerebral cortex and because of some of the features that are enhanced by that size that gives us the capacity to do things like build civilizations um and coordinate with each other not just to manipulate the physical world but to add to it in very profound ways like you know other animals can cooperate with each other and use tools um we draw a line in the sand and we make countries and we even then we create you know uh we create citizens and immigrants but also ideas i mean the countries are centered around the concept of like ideas well my well what do you think a citizen is and and an immigrant those are ideas those are ideas that we um impose on reality and make them real and then they have very very serious and real effects physical effects on people what do you think about the idea that a bunch of people have written about dawkins with memes which is like ideas are breeding like we're just like the canvas for ideas to breed in our brains so this kind of network that you talk about of brains it's just a little canvas for ideas to then yeah eat against each other and so on i i think it's a rhetorical tool it's cool to uh think you know think that way so um i think it was michael pollan i don't remember if it was in the botany of desire but it was in one of his early books on um on botany and gardening where he wrote about um and he wrote about uh you know plants sort of utilizing humans for their own you know evolutionary purposes which is kind of interesting you can think about a human gut in a sense as a propagation device for the seeds of you know tomatoes and what what have you so it's kind of cool um so i think i think rhetorically it's an interesting device but you know ideas are as far as i know invented by humans propagated by humans um so you know i i don't think they're separate from human brains in in any way although it would it is interesting to to think about it that way well of course the ideas that are using your brain to communicate and write excellent books uh and they basically picked you uh lisa as an effective communicator and and thereby are winning so that's an interesting world view to think that there's particular aspects of your brain that are conducive to certain sets of ideas and maybe those ideas will win out yeah i think the way that i would say it really though is that there are many species of animals that influence each other's nervous systems that regulate each other's nervous systems and they mainly do it by physical means they do it by chemicals scent they do it by you know so so termites and ants and bees for example use chemical scents mammals like um like rodents use scent and they also use uh hearing audition and that little bit of vision um primates you know non-human primates add vision right and i think everybody uses touch humans as far as i know are the only species that use ideas and words to regulate each other right i can text something to someone halfway around the world they don't have to hear my voice they don't have to see my face and i can have an effect on their nervous system and ideas the ideas that we communicate with words i mean words are in a sense a way for us to do mental telepathy with each other right i mean i'm not the first person to say that obviously but how do i control your heart rate how do i control your breathing how do i control your actions with words it's because those words are communicating ideas so you also write i think let's go back to the brain you write that plato gave us the idea that the human brain has three brains in it three forces which is kind of a compelling notion uh you disagree first of all what are the three parts of the brain and uh why do you disagree so plato's description of the psyche which for the moment we'll just assume is the same as a mind there are some scholars who would say you know a soul a psyche a mind those aren't actually all the same thing in ancient greece but we'll just for now gloss over that so plato's idea was that and it was a it was a description of really about moral behavior and moral responsibility in humans so the idea was that you know the human psyche can be described with an um a metaphor of two horses and a charioteer so one horse for instincts like feeding and fighting and fleeing and reproduction i'm trying to control my salty language which apparently they print in england like i actually tossed off of f s yeah f f okay yeah yeah i was like you printed that i couldn't believe you printed that without like the stars or whatever no no no there was full print yeah they also printed the a b word and it was really quite yeah anyways we should we should uh learn something from england indeed anyways but instincts and then the other horse represents emotions and then the cherry tier represents rationality which controls you know the two beasts right and um fast forward you know couple of centuries and uh in the middle of the 20th century there was a very popular view of brain evolution which suggested that you have this uh reptilian core like a lizard bra an inner lizard brain for instincts and then wrapped around that evolved on layer on top of that evolved a limbic system for uh in mammals so the novelty was in a mammalian brain which uh bestowed mammals with uh gave them emotions the capacitive emotions and then um on top of that uh evolved uh a cerebral cortex um which in in largely in primates but but very large in in humans um and it's not that i personally disagree it's that as far back as the 1960s but really by the 1970s it was shown pretty clearly with evidence from molecular genetics so peering into cells in the brain to look at the molecular makeup of genes that the brain did not evolve that way and the irony is that um you know the the idea of the the three-layered brain with an inner lizard you know that hijacks your uh hijacks your behavior and causes you to do and say things that uh you would otherwise not or maybe that you will regret later that idea um became very popular was popularized by uh carl sagan in the dragons of eden which won a pulitzer prize in 1977 when it was already known pretty much in evolutionary neuroscience that the whole uh narrative was a myth so well the narrative is on the the way it evolved but do you i mean again it's that problem of it being a useful tool of conversation to say like there's a lizard brain and there's a like if i get overly emotional on twitter that was the lizard brain and so on uh but do you no i don't think it's useful i think it's a i think that is it is is it uh is it useful is it accurate i don't think it's accurate and therefore i don't think it's useful so i here's what i would say you know i think that um the way i think about philosophy and science is that they are useful tools for living and in order to be useful tools for living they have to help you make good decisions the try and brain as it's called this this three-layer brain the idea that your brain is like an already baked cake in and you know the cortex cerebral cortex is just layered on top like icing the idea that idea is the foundation of the law in most western countries it's the foundation of uh economic theory and it largely and it's a great narrative it sort of fits our intuitions about how we work but it also um it's in addition to being wrong it lets people off the hook for uh for nasty behavior you know um and it also suggests that emotions can't be a source of wisdom which they often are in fact you you would not want to be around someone who didn't have emotions that would be that's a psychopath right i mean that's not someone you you know want to want to really uh have have that person deciding your outcome so i guess my and i could sort of go on and on and on but my point is that um i don't think i don't think it's a useful narrative in the end what's the more accurate view of the brain that we should use when we're thinking about it i'll answer that in a second but i'll say that even our notion of what an instinct is or what a reflex is is not quite right right so if you look at evidence from um ecology for example and you look at animals in their ecological context what you can see is that even things which are reflexes are very context-sensitive um the the brains of those animals are executing so-called instinctual actions in a very very context-sensitive way and so you know even when a physician you know takes the you know it's like the idea of your patellar uh reflex where they hit you know your patellar tendon on your knee and you you kick the the force with which you kick and so on in is influenced by all kinds of things it's it's a reflex isn't like a robotic uh response and um so i think a better way is a way that to think about how brains work is the way that um matches our best understanding our best scientific understanding which i think is really cool uh because it's really counterintuitive so how i came to this view and i'm certainly not the only one who holds this view i was reading work in on neuroanatomy and the the view that i'm about to tell you was sugges strongly suggested by that and then i was reading work and signal processing like by engineer electrical engineering and similarly it the work suggested that that the research suggested that the brain worked this way and i'll just say that i was reading across multiple literatures and they were who don't speak to each other and they were all pointing in this direction and so far although some of the details are still up for grabs the general gist i think is i've not come across anything yet which really violates and i'm looking um and so the idea is something like this it's very counterintuitive um so the way to describe it is to say that your brain doesn't react to things in the world it's not it to us it feels like our eyes and our um our windows on the world we see things we hear things we we react to them um in psychology we call this stimulus response so your face is your voice is a stimulus to me i receive input and then i react to it uh and i might react very automatically you know system one uh and uh oh but i also might execute some control where i maybe stop myself from saying something or doing something and um more in a more reflective way execute a different action right that's system two the way the brain works though is it's predicting all the time it's constantly talking to itself constantly uh talking to your body uh and it's constantly um predicting what's going on in the body and what's going on in the world and making predictions and the information from your body and from the world really confirm or correct those predictions so fundamentally the thing that the brain does most of the time is just predict like talking to yourself and predicting stuff about the world not like this dumb thing that just senses in response senses yeah so the way the way to think about it is like this you know your brain is uh trapped in a dark silent box yeah that's very romantic of you um which is your skull and the only information that it receives from your body and from the world right is through the senses through the sense organs your eyes your ears and you have a sense sensory data that comes from your body that you're largely unaware of uh to your brain which we call interroceptive as opposed to exteroceptive which is the world around you and but your brain is receiving sense data continuously which are the effect of some set of causes your brain doesn't know the cause of these sense data it's only receiving the effects of those causes which are the data themselves and so your brain has to solve what philosophers call an inverse inference problem how do you know when you only receive the effects of something how do you know what caused those effects so when there's a flash of light or a change in air pressure or a tug somewhere in your body how does your brain know what caused those events so that it knows what to do next to keep you alive and well and the answer is that your brain has one other source of information available to it which is your past experience it can reconstitute in its wiring past experiences and it can combine those past experiences in novel ways and so we have lots of names for this in psychology we call it memory we call it perceptual inference we call it simulation it's also we call it concepts or conceptual knowledge we call it prediction basically if we were to stop the world right now stop time your brain is in a state and it's representing what it believes is going on in your body and in the world and it's predicting what will happen next based on past experience right probabilistically what's most likely to happen and it begins to um prepare your action and it begins to prepare your the prepare your experience based so it's anticipating the sense data it's going to receive and then when that those data come in they either confirm that prediction and your action executes because the plan has already been made or um it where there's some uh sense data that your brain didn't predict that's unexpected and your brain takes it in we say encodes it we have a fancy name for that we call it learning your brain learns and it updates its storehouse of knowledge which we call an internal model and uh that you so that you can predict better next time and it turns out that predicting and correcting predicting and correcting is a much more metabolically efficient way to run a system than constantly reacting all the time because if you're constantly reacting it means you have no you can't anticipate in any way what's going to happen and so the the amount of uncertainty that you have to deal with is uh overwhelming to a nervous system metabolically costly i like it and so what is a reflex a reflex is when your brain doesn't check against the sense data that the potential cost to you is so great maybe because you know your life is threatened that your brain makes the prediction and executes the action without checking yeah so but prediction is still at the core that's a beautiful vision of the brain i wonder from almost an ai perspective but just computationally is the brain just mostly a prediction machine then like is the perception just the nice little feature added on top like the both the the integration of new perceptual information i wonder how big of an impressive system is that relative to just the big predictor model construction well i think that we can we can look to evolution for that for one answer which is that when you go back you know 550 million years give or take we you know the world was populated by creatures really ruled by creatures without brains um and um you know that's a biological statement not a political statement really world war ii dinosaurs dumb you're talking about like oh no i'm not talking about dinosaurs honey i'm talking way back further back than that um really these they're these little little um creatures called uh amphioxus which is the modern it's a or a lancet that's the modern animal but it's an animal that scientists believe is very similar to um our common the common ancestor that we share uh with invertebrates um because uh basically because of the tracing back the molecular genetics and cells and that animal had no brain it had some cells that would later turn into a brain but in that animal there's no brain but that animal also had no head and it had no eyes and it had no ears and it had really really no senses for the most part it had very very limited sense of touch it had an eye spot for um not for seeing but just for um in training to circadian rhythm to light and dark and it had no hearing it had a vestibular cell so that it could keep upright in the water at the time approx we're talking evolutionary scale here so you know give or take some 100 million years or something but at the time you know what are the vertebrate like when of when a backbone evolved and a brain evolved a full brain that was when a head evolved with sense with sense organs and when um that's when your viscera like internal systems involved so the answer i would say is that um that senses nurse motor neuroscientists people who study the control of motor behavior believe that senses evolved in the service of motor action so the idea is that like what triggered the what triggered what was what was the big evolutionary change what was the big pressure uh that made it useful to have eyes and ears and a visual system and an auditory system and a brain basically and you know and the answer that um is you know commonly entertained right now is that it was predation that when at some point an animal evolved that deliberately ate another animal and this launched an arms race between predators and prey and it became very useful to have senses right so these these little antioxidants these little amphioxy you know don't really have they they don't have an um they're not aware of their environment very much really they um uh and so being able to look up ahead and you know ask yourself you know is that you know should i eat that or will it eat me um is is a very useful thing so the idea um is that sense sense sense data is not there for consciousness it didn't evolve for the purposes of consciousness it didn't evolve for the purposes of experiencing anything um it evolved uh in the cert to be in the service of motor control however maybe it's useful um this is why you know scientists sometimes uh avoid questions about why things evolved that this is what philosophers call this teleology you might be able to say something about how things evolve but not necessarily why we don't really know the why that's all speculation but the y is kind of nice here this the interesting thing is uh that was the first element of social interaction is am i gonna eat you or are you gonna eat me and for that it's useful to be able to see each other sense each other that's kind of fascinating that there was a time when life didn't eat each other or they did by accident right so an amphioxus for example well um it kind of like gyrates in the water and then it plants itself in the sand like a blade of like a living blade of grass and then it just filters uh whatever comes into its mouth right so it is it is eating but it's not actively hunting and when um the concentration of food decreases it the amphioxus can sense this and so it basically wriggles itself randomly to some other spot which probabilistically will have more food than wherever it is so it's not really you know it's not guiding its actions um on the basis of it's not we would say there's no real intentional action um in that in that in the traditional sense speaking of intentional action and if the brain is put if prediction is indeed a core component of the brain let me ask you a question that scientists also hate is uh about free will so how does uh do you think about free will much how does that fit into this into your view of the brain why does it feel like we make decisions in this world this is a hard q a scientists hate this because it's a hard it's a hard question we don't know they're taken aside i think i have free will i think i have taken aside but it it i don't put a lot of stock in my own intuitions or anybody's intuitions about the cause of things right our ex one thing we know about the brain for sure is that the brain creates experiences for us my brain creates experiences for me your brain creates experiences for you in a way that lures you to believe that those experiences actually reveals the way that it works right but it doesn't so so you don't trust your own intuition about not really not really no i mean no but but i am also somewhat persuaded by you know i think dan dennett wrote at one point like um uh you know the philosopher dan dennett wrote at one point that um it it's i can't say it as eloquently as him but it people obviously have free will they are obviously making choices so it's you know and so there is this observation that we're not robots and we can do some things like a little more sophisticated than an amphioxus so um so here's what i would say i would say that your predictions your internal model that's running right now right that your ability to understand the sounds that i'm making and attach them to ideas is based on the fact that you have years of experience knowing what these sounds mean in a particular statistical uh pattern right i mean that's how you can understand the words that are coming out of my mouth right i think we did this once before too didn't we when we were i don't know i would have to access my memory module i think when i was in your glen classic yeah i think we did it just like that actually so bravo wow yeah i have to go look look back to the tape yeah anyways the um the idea though is that your brain is using past experience and it can and it can use past experience in um so it's remembering but you're not consciously remembering it's basically re-implementing prior experiences as a way of predicting what's going to happen next and it can do something called conceptual combination which is it can take bits and pieces of the past and combine it in new ways so you can experience and make sense of things that you've never encountered before because you've encountered something similar to them um and so a brain in a sense is not um just um doesn't just contain information it is information gaining meaning it can create it new information by this generative process so in a sense you could say well that maybe that's that's a source of free will but i think really where free will comes from or the kind of free will that i think is worth having a conversation about is um involves cultivating experiences for yourself that change your internal model when you were born and you were raised in a particular context that your mod your brain wired itself to your surroundings to your physical surroundings and also to your social surroundings so you were handed an internal model basically um but uh when you grow up the more control you have over your where you are and what you do um you can cultivate new experiences for yourself and those new experiences can change your internal model and you can actually um practice those experiences in a way that makes them automatic meaning it makes it easier for the brain your brain to make them again and i think that that is something like what you would call free will you aren't responsible for the model that you were handed that someone you know your your caregivers uh cultivated a model in your brain you're not responsible for that model but you are responsible for the one you have now you can choose you choose what you expose yourself to you choose uh how you spend your time not everybody has choice over everything right but everybody has a little bit of choice um and and so i think that is uh something that i think is arguably called free will yeah there's this like the the ripple effects of the billions of decisions you make early on in life have are so great that uh even if it's not even if it's like all deterministic just the amount of possibilities that are created and then the focusing of those possibilities into a single trajectory uh that somewhere within that that's free will even if it's all deterministic that might as well be of just the number of choices that are possible and the fact that you just make one trajectory to those set of choices seems to be like something like they'll be called free will but it's still kind of sad to think like there doesn't seem to be a place where there's magic in there where it is all just a computer well there's lots of magic i would say so far because we don't really understand uh how all of this is exactly played out at a i mean scientists are working hard and disagree about some of the details under the hood of what i just described but i think there's quite a bit of magic actually and also there's there's also um stochastic firing of neurons don't they they're not purely digital in the sense that there is there's also analog communication between neurons not just digital so it's not just with not just with firing of axons and some of that there's there are other ways to communicate and also um uh there's noise in the system and the noise is there for a really good reason and that is the more variability there is the more potential there is for your brain to be able to be information bearing so um basically you know there are some animals that have clusters of cells the only job is to inject noise you know into their um neural patterns so maybe noise is the source of free will so you can think about you can think about stochasticity or noise as as a source of free will or you can think of of um conceptual combination as a source of free will you can certainly think about um cultivating uh you know you can't reach back into your past and change your past you know people try by psychotherapy and so on but what you can do is change your present which becomes your past right think about that sentence so one way to think about it is that you're continuously this is a colleague of mine a friend of mine said so what you're saying is that people are continually cultivating their past and i was like that's very poetic yes you are continually cultivating your past as a means of controlling your future so you think uh yeah i guess the the construction of the mental model that you use for prediction ultimately contains within it your perception of the past like the way you interpret the past or even just the entirety of your narrative about the past so you're constantly rewriting the story of your past oh boy yeah that's one poetic and also just awe inspiring what about the other thing you talk about you've mentioned about sensory perception as a thing that like is just you have to infer about the sources of the thing that you have perceived through your senses so uh let me ask the another ridiculous question is is anything real at all like how do we know it's real how do we make sense of the fact that just like you said there's this brain sitting alone in the darkness trying to perceive the world how do we know that the world is out there i will be perceived yeah so i don't think that you should be asking questions like that without passing a joint right no for sure yeah i actually did before this so i apologize okay no well that's okay you apologize for not sharing that's okay so i mean here's what i would say what i would say is that the reason why we can be pretty sure that there's a there there is that the the structure of the information in the world what we call statistical regularities in sights and sounds and so on and the structure of the information that comes from your body it's not random stuff there's a structure to it there's a spatial structure and a temporal structure and that spatial and temporal structure wires your brain so an infant brain is not a miniature adult brain it's a brain that is waiting for wiring instructions from the world and it must receive those wiring instructions to develop in a typical way so for example when a newborn is born when a newborn is born when a when a baby is born um the baby can't see very well because the visual system in that baby's brain is not complete the the retina of your eye which actually is part of your brain has to be stimulated with photons of light if it's not the baby won't develop normally to be able to see in in a neurotypical way same thing is true for hearing the same thing is true really for all your senses so the point is that that the physical world the sense data from the physical world wires your brain so that you have an internal model of that world so that your brain can predict well to keep you alive and well and allow you to thrive that's fascinating that the brain is waiting for a very specific kind of uh set of instructions from the world like not not the specific but a very specific kind of instruction yes so you scientists call it expectable input the brain needs some input in order to develop normally and so we're and we are genetically you know we as i say in the book we we have the kind of nature that requires nurture we we can't develop normally without sense input sensory input from the world and from the body and what's really interesting about humans and some other animals too but really seriously in humans is the input that we need is not just physical it's also social we in order for an an infant a human infant to develop normally that infant needs eye contact touch it needs certain types of smells it needs to be cuddled it needs right so um without social input the brain it's that that infant's brain will not wire itself in a neurotypical way and again i would say there are lots of um cultural patterns of caring for an infant it's not like the infant has to be cared for in one way um whatever the social environment is for an infant that it will will be reflected in that infant's internal model so we have lots of different cultures lots of different ways of rearing children and that's an advantage for our species although we don't always experience it that way that is an advantage for our species but if you if you just you know feed and water a baby without all the extra social doodads what you get is a profoundly impaired uh human yeah but nevertheless you're kind of saying that the physical reality has uh has a consistent thing throughout that keeps feeding these set of sensory information that our brains are constructed for but yeah the cool thing though is that if you change the consistency if you change the statistical regularities so prediction error your brain can learn it it's expensive for your brain to learn it and it takes a while to for the brain to get really automated with it but you know you um had a wonderful conversation with david eagleman who just published a book about this yeah and gave lots and lots of really very very cool examples some of which i actually discussed in how emotions were made but not obviously to the extent that he did um in his book which it's a fascinating book and it's but it it speaks to the point that your internal model is always under construction and therefore you always can modify your experience i wonder what the limits are like uh if we can if we put it on mars or if we put in virtual reality or if we sit at home during a pandemic and we spend most of our day on twitter and tick tock like i wonder what where the breaking point like the limitations of the brain's capacity to uh to properly continue wiring itself well i think what i would say is that there are different ways to specify your question right like one way to specify it would be the way that david um phrases it which is can we can we create a new sense like can we create a new sensory modality how hard would that be what are the limits in doing that um and um but another way to say it is what what happens to a brain when you remove some of those statistical regularities right like what happens to a brain what happens to an adult brain when you remove some of the statistical patterns that were there and they're not there anymore you're talking about in the environment or in the actual like you remove eyesight for example or did you well either way i mean basically one way to limit the inputs to your brain are to stay home and protect yourself another way is to put someone in solitary confinement another way is to stick them uh in a nursing home another well not all nursing homes but you know but there are some right which really are some where peop people are somewhat impoverished in the interactions the end this sensory the variety of sensory stimulation that they get another way is that you lose a sense right but the point is i think that you know the human brain really likes variety to to say it in a you know like a pro you know sort of cartesian way you know variety is a good thing um for a brain and um uh there are risks that you take uh when you restrict uh what you expose yourself to yeah you know there's always talk of diversity the brain loves it to the fullest definition and degree of diversity yeah i mean i would say the only thing basically human brains thrive on diversity the only place where we seem to have difficulty with diversity is with each other right but we who wants to eat the same food every day you never would who wants to wear the same clothes every day i mean my husband if you ask him to close his eyes he won't be able to tell you what he's wearing he's just right he'll buy seven shirts of exactly the same style in different colors but they are in different colors right it's not like how would you then explain my brain which is terrified of choice and therefore i wore the same thing every time well you must be getting your diversity well first of all you are a fairly sharp dresser so there is that but um so you're getting some reinforcement progressing the way that you do but well your brain must get diversity in in other words in other places but i think we you know the the so there the two most expensive things your brain can do metabolically speaking is um is move your body um and uh learn something new so novelty that is diversity right comes at a cost a metabolic cost but it's a cost it's an investment that that gives returns and in general people vary in how much they like novelty unexpected things some people really like it some people really don't like it and there's everybody in between but in general we don't eat the same thing every day we don't usually do exactly the same thing in exactly the same order in exactly the same place every day the only place we have difficulty uh with diversity in is in each other and then we we have considerable problems there i would say as a species let me ask uh i don't know if you're familiar with donald hoffman's work about this like questions of reality what are your thoughts of the possibility that the very thing we've been talking about of the brain wiring itself from birth to a particular set of inputs is just a little slice of reality that there is something much bigger out there that we humans with our cognition cognitive capabilities is just not even perceiving that the thing we're perceiving is just the crappy like windows 95 interface onto a much bigger richer set of complex physics that we're not even in touch with well without getting too metaphysical about it i think we know for sure it doesn't have to be the you know crappy version of anything but we definitely have a limited we have we have a set of senses that are limited in very physical ways and we're clearly not perceiving everything there is to perceive that's clear i mean it's just it's not that hard we can't without special why do we invent scientific tools it's so that we can overcome our senses and and experience things that we couldn't otherwise whether they are you know different parts of the uh visual spectrum the light spectrum or um things that are too microscopically small for us to see or too far away for us to see so clearly we're only getting a slice um and that slice you know the interesting or potentially sad thing about humans is that we whatever we experience we think there's a natural reason for experiencing it and we think it's obvious and natural and it must be this way and that all the other stuff isn't important and that's clearly not true many of the things that we think of as natural are anything but we've cr they're certainly real but we've created them they certainly have very real impacts but we've created those impacts and we also know that there are many things outside of our awareness that have have tremendous influence on what we experience and what we do so there's no question that that's true i mean just it's it's um but the extent is how fantastic really the question is how fantastical is it yeah like what you know a lot of people ask me i'm i'm not allowed to say this i think i'm allowed to say this uh i've eaten shrooms a couple times but i haven't gone the full i'm talking to a few researchers and psychedelics it's an interesting scientifically place like what is the portal you're entering when you take psychedelics or another would ask is like dreams whatever so let me tell you what i think which is based on nothing like this is based on my life right so i don't your intuition it's based on my it's based on my i'm guessing now um based on what i do know i would say but i think that well think about what happens so you're running your brain's running this internal model right and it's all outside of your awareness really you see the you feel the products but you don't you don't sense the you have no awareness of the mechanics of it right it's going on all the time um and so one thing that's going on all the time that you're completely unaware of is that um when your brain your brain is basically asking itself figuratively speaking not literally right like how is the scent given the last time i was in this sensory array with this stuff going on in my body and i and that this chain of events which just occurred what did i do next what did i feel next what did i see next it doesn't come up with one answer it comes up with a distribution of it possible answers and then there has to be some selection process and so you have a network in your brain a subnetwork in your brain a population of neurons that helps to choose it's not i'm not talking about a homunculus in your brain or anything silly like that um this is not the soul it's not the center of yourself or anything like that but there is um a a set of neurons that weighs the probabilities uh um um and and helps to select uh or narrow the field okay and that that network is working all the time it's actually called the control network the executive control network or you can call it a fronto parietal because the regions of the brain that make it up or in the frontal lobe and the parietal lobe there are also parts that belong to the subcortical parts of your brain it doesn't really matter the point is that that there is this network and it is working all the time whether or not you feel in control whether or not you feel like you're expending effort doesn't really matter it's on all the time except when you sleep when you sleep it's it's a little bit relaxed and so think about what's happening when you sleep when you sleep the extra the external world recedes the sense data from so basically your model becomes a little bit the tethers from the world are loosened and this network which is involved in you know maybe weeding out unrealistic things is a little bit quiet so use your dreams are really your internal model that's unconstrained by the immediate world except so you can do things that you can't do in real life in your dreams right you can fly like i for example when i fly on my back in a dream i'm much faster than when i fly on my front don't ask me why i don't know when you're laying and you're back in your dream no when i'm in my dream and flying in a dream i am much faster flyer in the air very [Music] i don't think i've flown for many years well you must try it i've i've thought i've uh flown uh i've fallen that's scary yeah but you fl you're talking about like yeah i fly my dreams and i'm way faster right and you're better on my back way faster um now you can say well you know you never flew in your life right it's conceptual combination i mean i've flown in an airplane and i've seen birds fly and i've watched movies of people flying and i know superman probably flies i don't know if he flies faster on his back but he's voice he's out of never he's lying on his front right but yeah but anyways my point is that you know all of this stuff really um all these experiences really become part of your internal model the thing is that when you're asleep your internal model is still being constrained by your body your your brain's always attached to your body it's always receiving sense data from your body you're mostly never aware of it uh unless you run up the stairs uh or or you know uh maybe you um are ill in some way but you're mostly not aware of it which is a really good thing because if you were you know you'd never pay attention to anything outside your own skin ever again like right now you seem like you're sitting there very calmly but you have a virtual whole thing drama right it's like a like a like an opera going on inside your body and so i think that one of the things that happens when people take psilocybin or take uh you know ketamine for example is that the tethers completely are completely removed yeah yeah that's fascinating and then and that's why it's helpful to have a guide right because the guide is giving you sense data to steer that internal model so that it doesn't go completely off the rails yeah i know there's so again that wiring to the other brain that's the guide is at least a tiny little tether exactly yeah let's talk about emotion a little bit if we could emotion comes up often and i have never spoken with anybody who um who has a clarity about emotion from a biological and neuroscience perspective that you do and i'm not sure i fully know how to as a as a i mentioned this way too much but as somebody who was born in the soviet union and romanticizes basically everything talks about love non-stop you know emotion is a i don't know what to make of it i don't know so maybe uh let's just try to talk about it i mean from a neuroscience perspective we talked about a little bit last time your book covers it how emotions are made but what are some misconceptions we writers of poetry we romanticizing humans have about emotion that we should move away from before to think about emotion from both a scientific and an engineering perspective yeah so there is a common view of emotion in the west the caricature of that view is that um you know we have an inner beast right your limbic system your your inner lizard um we have an inner beast and that comes baked in to the brain at birth so you've got circuits for anger atmosphere it's interesting that they all have english names these circles but um that that and they're there and they're triggered by things in the world and um then they cause you to do and say and you know so when your fear circuit is triggered you widen your eyes you gasp your heart rate goes up you prepare to flee or to freeze and these are these are modal responses they're not the only responses that you give but on average they're the prototypical responses that's the view and um that's the view of emotion in the law that's the view you know that emotions are these profoundly unhelpful things that are obligatory kind of like reflexes the problem with that view is that it doesn't comport to the evidence um and it doesn't really matter the evidence actually lines up beautifully with each other it just doesn't line up with that view and it doesn't matter whether you're measuring people's faces facial movements or you're measuring their body movements or measuring their peripheral physiology or you're measuring their brains or their voices or whatever pick any any output that you want to measure and you know any system you want to measure and you don't really find strong evidence for this and i say this as somebody who who not only has reviewed really thousands of articles and run you know big meta analyses which are statistical summaries of of published papers but also as someone who has sent teams of researchers to small-scale cultures you know remote cultures which are very different from urban large-scale cultures like ours and one culture that we visited and i say we euphemistically because i i myself didn't go because i only had two research permits and i gave them to my students because i felt like it was better for them to have that experience and more formative for them to have that experience but i was in contact with them every day by satellite phone and this was um to visit the um hadza hunter-gatherers in tanzania who are not um an ancient people they're a modern culture but they live in circumstances um hunting and foraging circumstances that um are very similar in similar conditions to our ancestors uh hunting gathering ancestors when expressions of emotion were supposed to have evolved at least by one view of okay so i you know for many years i was sort of struggling with um this set of observations right which is that i feel emotion and i see i perceive emotion in other people but scientists can't find a single marker a single biomarker not a single individual measure or pattern of measures that will can predict how someone what kind of emotional state they're in how could that possibly be how how can you possibly make sense of those two things and through a lot of reading and a lot of and immersing myself in different literatures i came to the hypothesis that the brain is constructing these instances out of more basic ingredients so when i tell you that the brain when i suggest you that what your brain is doing is making a prediction and it's asking itself figuratively speaking the last time i was in this situation and this you know physical state what did i do next what did i see next what did i hear next it's basically asking what in my past is similar to the present things which are similar to one another are called a category a group of things which are similar to one another as a category and a mental representation of a category is a concept so your brain is constructing categories or concepts on the fly continuously so you really want to understand what a brain is doing you don't using machine learning like classification models is not going to help you because the brain doesn't classify it's doing category construction and the categories change or you could say it's doing concept construction it's using past experience to conjure a concept which is a prediction and if it's using past experiences of emotion then it's constructing an emotion concept your concept will be the content of it is ism changes depending on the situation that you're in so for example if your brain uses past experiences of anger that you have learned either because somebody labeled them for you taught them to you you observed them in movies and so on in one situation could be very different from your concept of for anger than another situation and this is how anger instances of anger are what we call a population of variable instances sometimes when you're angry you scowl sometimes when you're angry you might smile sometimes when you're angry you might cry sometimes your heart rate will go up it will go down it will stay the same it depends on what action you're about to take because the way predict and i should say the idea that physiology is yoked to action is a very old idea in in uh the study of the peripheral nervous system that's been known for really decades and so if you look at what the brain is doing if you just look at the anatomy and you what here's the hypothesis that you would that you would come up with and i can go into the details i've published these details in in scientific papers and they also appear somewhat in how emotions are made my first book they are not in the you know seven and a half lessons because that book is is really not pitched at that level of explanation right it's just giving it's really just a set of little essays um but the evidence but what i'm about to say is actually based on on on scientific evidence when your brain begins to make form a prediction the first thing it's doing is it's making a prediction of how to change the internal systems of your body your heart your cardiovascular system the control of your heart control of your lungs right a flush of of cortisol which is not a stress hormone it's a hormone that gets glucose into your bloodstream very fast because your brain is predicting you need to do something metabolically expensive and so so either that means either move or learn okay and so your brain is preparing your body the internal systems of your body to execute some actions to move in some way and the and then it infers based on those motor predictions and what we call visceral motor predictions meaning the the the changes in the viscera that your brain is preparing to um to execute um your brain makes an inference about what you will sense based on those motor movements so your experience of the world and your experience of your own body are a consequence of those predictions those concepts when your brain makes a concept for emotion it's constructing an instance of that emotion and that is how emotions are made and those concepts load in the predictions that are made include contents inside the body contents outside the body i mean it includes other humans so just this construction of a concept includes the variables that are much richer than just some sort of um simple notion yeah so our colloquial notion of a concept where um you know um where i say well what's the concept of a bird and then you list a set of features off to me that's that's people's understanding you know typically of what a concept is but if you go uh into the literature in um cognitive science what you'll see is that the way that scientists have understood what a concept is has really changed over the years so people used to think about a concept as um philosophers and scientists used to think about a concept as a dictionary definition for a category so there's a set of things which are similar out in the world and um your concept for for that category is a dictionary definition of the features right the necessary insufficient features of that of those instances so for a bird um you know would be wings feathers right a beak yeah it flies whatever okay um that's called the classical category and scientists discovered observed that actually not all instances of birds have feathers and not all instances of birds fly and so the idea was that you don't have a single representation of necessary and sufficient features stored in your brain somewhere instead what you have is a prototype a prototype meaning um you still have a single representation for the category one um but the features are like of the most typical instance of the category or maybe the most frequent instance but not all instances of the category have all the features right they they have some graded similarity to the prototype and then uh you know what um i'm gonna like incredibly simplify now a lot of work to say that then a series of experiments were done to show that in fact what your brain seems to be doing is coming up with a single exemplar or instance of the category and reading off the um features when i ask you for the concept so if we were in a pet store and i asked you what are the features of a bird tell me the concept of bird you would be more likely to give me features of a good pet and if we were in a restaurant you would be more likely you know like a budgie right or a canary if we were in a restaurant you would be more likely to give me the features of a bird that you would eat like a chicken and if we were in a park you'd be more likely to give me uh in this country uh you know the features of a sparrow or a robin whereas if we were in south america you would probably give me the features of a peacock because that's more common or it's or it is more common there than here that you would see a peacock in such circumstances so the idea was that really what your brain was doing was conjuring a concept on the fly that meets the function that the category is being put to okay yep okay then people started studying ad hoc concepts meaning um concepts that where the instances don't share any feat any physical features but the function of the instances are the same so for example think about all the things that can protect you from the rain what are all the things that can protect you from the rain uh umbrella uh like this apartment right um your car not giving a damn like like a like a mindset yeah right right so the idea is that the function of the instances is the same in a given situation even if they look different sound different smell different this is called an abstract concept or a conceptual concept now the really cool thing about conceptual categories or conceptual concept yes conceptual category a conceptual as a category of things that are held together by a function which is called an abstract concept or a conceptual category because the things don't share physical features they share functional features there are two really cool things about this one is that's what darwin said a species was so darwin is known for discovering natural selection but the other thing he really did which was really profound which he's less celebrated for is understanding that all biological categories have inherent variation inherent variation darwin wrote in the origin of species about before darwin's book a species was thought to be a classical category where all the instances of dogs were the same had exactly the same features and any variation from that perfect platonic instance was considered to be error and darwin said no it's not error it's meaningful nature selects on the basis of that variation the reason why natural selection is powerful and can exist is because there is variation in a species and in dogs we talk about that variation in terms of the size of the dog and the uh amount of fur the dog has and the color and the how long is the tail and how long is this snout in humans we talk about that variation in all kinds of ways right including in cultural ways so that's one thing that's really interesting about conceptual categories is that darwin is basically saying a species is a conceptual category and in fact if you look at modern debates about what is a species you can't find anybody agreeing on what the criteria are for a species because they don't all share the same genome we don't all share we don't there isn't a single human genome there's a population of genomes but they're variable it's not unbounded variation but they are variable right and the other thing that's really cool about conceptual categories is that um they are the categories that we use to make civilization so think about money for example what are all the physical things that make something a currency is there any physical feature that all the currencies in all the worlds that's ever been used by humans share well certainly right but uh but what what is it uh is it definable you know so it's getting to the point that you're because you're making it function it's the function right function it's that we trade it for material goods and that and we have to agree right we all impose on whatever it is salt barley little shells big rocks in the ocean that can't move bitcoin pieces of plastic mortgages which are basically a promise of something in the future nothing more right all of these things we impose value on them and we all agree that we can exchange them for material goods yeah and uh yes that's bril by the way you're attributing some of that to darwin that he thought no i'm no i'm saying that because it's a brilliant view of what a species is is the function yeah what i'm saying is that what darwin darwin really talked about variation in um so if you read for example the biologist ernst mayer who was an evolutionary biologist and then when he retired became a historian and philosopher of biology and his suggestion is that darwin darwin did talk about variation he vanquished what's called essentialism the idea that there's a single set of features that define any species and um out of that grew um really discussions of the function you know like some of the functional features that species have like they can reproduce uh off they can have offspring the individuals of a species can have offspring it turns out that's not a perfect uh you know that's not a perfect uh criterion to use but it's a functional criterion right so what i'm saying is that in cognitive science people came up with the idea they discovered the idea of conceptual categories or ad hoc concepts these concepts that can change based on the function they're serving right and um uh that it's there darwin it's in darwin and it's also in the philosophy of social reality you can the way that philosophers talk about social reality just look around you i mean we impose we're treating a bunch of things as similar which are physically different and sometimes we take things that are physically the same and we treat them as separate categories but it feels like the number of variables involved in that kind of categorization is nearly infinite no i don't think so because there is a physical constraint right like you and i could agree that um we can fly in real life but we can't that's a physical that's a physical constraint that we can't break right you and i could agree that we could walk through the walls right but we can't we could agree that we could eat glass but there's a lot of constraints but yeah we could agree that the virus doesn't exist and we don't have to wear masks right yeah but you know physical reality still holds the trump card right but still there's a lot of card well pun completely unattended but there you go that's a predicting brain for you um uh but but there's a tremendous amount of leeway yes yeah that's the point so what i'm saying is that emotions are like money basically they're they're like money they're like countries they're like um kings and queens and presidents they're like everything that we construct that we impose meaning on we take these physical signals and we give them meanings that um they don't otherwise have by their physical nature and because we agree yeah they have that function but the the beautiful thing so maybe unlike money i love this similarity is it it's not obvious to me that this kind of emergent agreement should happen with emotion because our experiences are so different for each of us humans and yet we kind of converge well in a culture we converge but not across cultures there are huge huge differences there are huge differences in what what concepts exist what their um what they look like um so what i would say is that they feel like what what we're doing with our young children as we as their brains become wired to their physical and their social environment right is that we are curating for them we are bootstrapping into their brains a set of emotion uh concepts that's partly what they're learning and we curate those for infants just the way we curate for them what is a dog what is a cat what is a truck we sometimes explicitly label and we sometimes just use mental words when you know your kid is you know throwing cheerios on the floor instead of eating them or your kid is crying when you know she won't put herself to sleep or whatever you know we use mental words and um a word is this words with for infants words are these really special things that they help infants learn abstract categories there's a huge literature showing that children can take things that don't look infants like infants really young infants pre-verbal infants can take if you label if i say to you and you're an infant okay so i say lex lexi this yeah is a bling yeah and i put it down and the bling makes a squeaky noise and then i say unless he's excited by the way this is a bling and i put it down and it makes a squeaky noise and then i say lexi this is a bling you as young as four months old will expect this to make a noise a speaking noise and if you don't if it doesn't you'll be surprised because it violated your expectation right i'm building for you an internal model of a bling yeah okay infants can do this really really at a young age and so there's no reason to believe that they couldn't learn emotion categories and concepts in the same way and in in one and what happens when you go to a new culture when you go to a new culture you have to do what's called emotion acculturation so my colleague bacia mosquita in belgium studies emotion acculturation she studies how when people move from one culture to another how do they learn the emotion concepts of that culture how do they learn to make sense of their own internal sensations and also the movements you know the rays of an eyebrow the tilt of a head how do they learn to make sense of cues from other people using concepts they don't have but have to make on the fly so that's the difference between cultures let me uh open another door i'm not sure i want to open but difference between men and women is there um difference between the emotional lives of those two categories of biological systems so here's what i would say you know we did a series of studies um uh in the 1990s where we asked men and women to tell us about their emotional lives and women described themselves as much more emotional than men they believed that they were more emotional than men and men agreed women are much more emotional than men okay and then we gave them little handheld computers these were little hewlett-packard computers they fit in the palm of your hand a couple of pen they weighed a couple of pounds so this was like pre-palm pilot even like this was you know 1990s and like early and um we um asked them we would you know ping them like 10 times a day and just ask them to report how they were feeling which is called experience sampling so we experience sampled and and then at the end and then we looked at their reports and we found is that men and women basically didn't differ and there were some people who were really had many more instances of emotion so they were you know um they were treading uh water in a tumultuous sea of emotion and then there were other people who were like floating tranquilly you know in a lake it was really not perturbed very often and and everyone in between but there were no difference between men and women and the really interesting thing is at the end of the sampling period we asked people um so reflect over the past two weeks and tell it so you know we've been now pinging people like again and again and again right so tell us how emotional do you think you are no change from the beginning so men and women believe that they are they believe that they are different and when they are looking at other people they make different inferences about emotion if a man if a man is scowling like if you and i were together and some so somebody's watching this okay and um yeah hey when you look at the camera um if you and i make exactly the same set of facial movements when people look at you both men and women look at you they are more likely to think oh he's reacting to the situation and when they look at me they'll say oh she's having an emotion she's you know yeah and i wrote about this actually um uh right before the 2016 election you know what maybe i could confess let me try to carefully confess but you are really gonna yeah that i'm that when i that there is an element when i see hillary clinton that there was something annoying about her to me and i just that feeling and then i tried to reduce that to what what is that because i think the same attributes that are annoying about her when i seen other people wouldn't be annoying so i was trying to understand what is it because it it certainly does feel like that concept that i've constructed in my mind well i'll tell you that i think well let me just say that um that that what you would predict about for example the performance of the two of them in the debates and i wrote an op-ed for the new york times actually um before the second debate and it it played out really pretty much as i thought that it would on based on research it's not like i'm like a great fortune teller or anything it's just i was just applying the research which was that when a woman um a woman's people make internal attributions it's called they infer that the facial movements and body posture and vocalizations of a woman reflect her inner state but for men they're more likely to assume that they reflect his response to the situation it doesn't say anything about him it says something about the situation he's in that's brilliant now for the thing that you are that you were describing about hillary clinton um i think a lot of people experienced but it's also in line with research which shows and and particularly research actually on um in about teaching evaluations is one place that you really see it where the expectation is that a woman will be nurturant and that a man there's just no expectation for him to be nurturing so he's you know if he is nurturant he gets points um if he's not he gets points right they're just different points right whereas for a woman especially a woman who's an authority figure she's really in a catch-22 right because if she's serious she's a and if she's empathic uh then she's weak right that's brilliant i mean one of the bigger questions to ask here so that's one example where our con construction of concepts gets right but remember you're in trouble but so remember i said science is a science and philosophy are like tools for living so i learned recently that if you ask me what is my intuition about what regulates my eating i will say carbohydrates i love carbohydrates i love pasta i love bread i love i just love carbohydrates but actually research shows and it's beautiful research i love this research because it so violates my own like deeply deeply held beliefs about myself that most animals on this planet who have been studied and there are many actually eat to regulate their protein intake so you will overeat carbohydrates if you in order to get enough protein and these this research has been done with human very beautiful research with humans with crickets with like you know bonobo i mean just like all these different animals not bonobos but i think like baboons um now that i have no intuition about that and i even now as i regulate my eating i don't i still i just have no intuition it just i can't i can't feel it what i feel is only about the carbohydrates it feels like you're regulating around carbohydrates not the protein yeah but in fact actually what i am doing if i am like most uh animals on the planet i am regulating around proteins so knowing this what do i do i correct my behavior to eat to to actually deliberately try to focus on the protein that this is the idea behind bias training right like if you um i also did not experience hillary clinton as the warmest candidate however you can use consistent science since the consistent scientific findings to organize your behavior that doesn't mean that rationality is the absence of emotion because sometimes emotion or scent anything feelings in general not the same thing as emotion um that's another topic um but you know our our source of of information and their wisdom and helpful so i'm not saying that but what i am saying is that if you have a deeply held belief and the evidence shows that you're wrong then you're wrong it doesn't really matter how confident you feel you that confidence could be also explained by science right so it would be the same thing as if i regardless of whether someone is like charlie baker right regardless of whether somebody is a republican or a democrat if that person has a record that you can see is consistent with what you believe then that is information that you can act on yeah and and then so try to i mean this is kind of what empathy is in open-mindedness is try to um consider that the set of concepts that your your brain has constructed through which you are now perceiving the world is not painting the full picture i mean this is now true for basically ever it doesn't have to be men and women it could be basically the prism through which we pursue actually the political discourse right absolutely so so here's what i would say um the you know there are people who scientists who will talk to you about cognitive empathy and emotional empathy and i i prefer to think of it i think the evidence is more consistent with what i'm about to say which is that your brain is always making predictions using your your own past experience and what you've learned from you know books and movies and other people telling you about their experiences and so on and if your brain cannot make a concept to make sense of those anticipate what those sense data are and make sense of them you will be experientially blind so you know when i'm giving lectures to people i'll show them like a blobby black and white image and they're experientially blind to the image they can't see anything in it and then i show them a photograph and then i show them the image again the blobby image and then they see actually an object in it but the art but the image is the same yeah it's there they're actually adding their predictions now are adding right or anything for example anybody who's learned a language uh a second language after their first language also has this experience of um things that initially sound like sounds that they can't quite make sense of eventually come to make they eventually come to make sense of them and in fact there are really cool examples of people who are like born blind because they have cataracts or um they have corneal damage so that no light is reaching the brain and then they have an operation and then light reaches the brain and they can't see for days and weeks and sometimes years they have they are experientially blind to certain things so what happens with empathy right is that your brain is making a prediction and if it doesn't if it doesn't have the capacity to um make it doesn't if you don't share if you're not similar remember you mean you know categories are instances which are similar in some way if you are not similar enough to that person you will have a hard time making a prediction about what they feel you will be experientially blind to what they feel in the united states children of color are under prescribed medicine by their physicians this is been documented it's not that the physicians are racist necessarily but they might be experientially blind the same thing is true of male physicians with female patients i could tell you some hair-raising stories really that where people die as a consequence of a physician making the wrong inference the wrong prediction because of being experientially blind so we are you know empathy is not um it's not magic it's we make inferences about each other about what each other's feeling and thinking in this culture more than there are some cultures where you know people have what's called opacity of mind where they will make a prediction about someone else's actions but they're not inferring anything about the internal state of that person but in our culture we're constantly making inferences what is this person thinking what is and we're not doing it necessarily consciously but it's doing it really automatically using our predictions what we know and if you expose yourself to information which is very different from somebody else i mean really what we have is we have different cultures in this in this country right now that are there are a number of reasons for this i mean part of it is i don't know if you saw the social dilemma the the netflix um uh part about it yeah it's a great it's really great um documentary and uh about what social networks are doing to our society yeah yeah but you know nothing no phenomenon has a a simple single cause there are multiple small causes which all add up to a perfect storm that's that's just you know how most things work and so the fact that machine learning algorithms are serving people up information on social media that is consistent with what they've already viewed and making you know um is part of the reason that you have these silos but it's not the only reason why you have these silos i think there are other there are other things afoot that uh enhance um people's inability to even have a decent conversation yeah i mean okay so so many things you said are just brilliant so the experiment experiential blindness but also from my perspective like i i preach and i try to practice empathy a lot and something about the way you've explained it makes me almost see it as a kind of exercise that we should all do like to train like to add experiences to the brain to expand this capacity to predict more effectively absolutely so like what like what i do is kind of like a method acting thing which is i imagine what the life of a person is like you know just think i mean this is something you see with black lives matter and uh police officers it feels like they're both uh not both but i have because martial arts and so on i have a lot of friends who are cops they don't necessarily have empathy or visualize the experience of the other certainly currently unfortunately people aren't doing that with police officers they're not imagining they're not empathizing or putting themselves in the shoes of a police officer to realize how difficult that job is how dangerous it is how difficult it is to maintain calm and under so much uncertainty all this kind of thing you know but there's more there's even that's all that's true but i think that there's even more there's even more to be said there i mean like from a predicting brain standpoint there's even more that can be said there so i don't know if you want to go down that path or you can strike on empathy but i will also say that one of the things that i was most gratified by i still am receiving you know it's been three more than three and a half years since how emotions are made came out and i'm still receiving daily emails from people right so that's gratifying but one of the most gratifying emails i received was from police officer in texas who told me that he thought that how motions are made contained information that would be really helpful to resolving some of these difficulties and he hadn't even read my op-ed piece about when is a gun not a gun and you know like using the what we know about the science of perception from predict from a prediction standpoint like the brain is a predictor to understand a little differently what might be happening in these circumstances so there's there's a real what's hard about it's hard to talk about because everyone gets mad at you when you talk about this like you know and um there is a way to understand this which has profound empathy for the suffering of people of color and that definitely is in line with black lives matter at the same time as understanding the really difficult situation that police officers find themselves in and i'm not talking about this bad apple or that bad apple i'm not talking about police officers who are necessarily shooting people in the back as they run away i'm talking about the cases of really good well-meaning cops who have the kind of predicting brain that everybody else has they're in a really difficult situation that i think both they and the people who are harmed don't realize like they just the the way that these situations are constructed i think it's just there's a lot to be said there i guess is what i wanted is there something we can try to say in a sense like what i'm from the perspective of the predictive brain which is a fascinating perspective uh to take on this you know the all the protests are going on there seems to be a concept of a police officer being built no i think that police i think that concept is there but it's is gaining strength so it's being re-um i mean yeah it is sure it is there but i think yeah for sure i think that that's right i think that there's um there's a shift in the stereotype of what i would say is a stereotype there's a stereotype of of uh black man in this country that's always in movies and television not always but like largely um that many people watch i mean you know you think you're watching a 10 o'clock drama and all you're doing is like kicking back and relaxing but actually you're having certain predictions reinforced and others not and what's happening what's happening now with police is the same thing um that there are certain stereotypes of a police officer that are being abandoned and other stereotypes that are being reinforced by by what you see happening all i'll say is that if you remember i mean there's a lot to say about this really that you know regardless of whether it makes people mad or not i mean i just i the science is what it is um just remember what i said the brain is makes predictions about internal changes in the body first and then motor it starts to prepare motor action and then it makes a prediction about what you will see and hear and feel based on those actions okay so it's also the case that we didn't talk about is that sensory sampling like your brain's ability to sample what's out there is yoked to your heart rate it's yoke to your heartbeats there are certain phases of the heartbeat where it's easier for you to see what's happening in the world than in others and so if your heart rate goes through the roof you will be less like you will be more likely to just go with your prediction and not correct based on what you what's out there because you're actually literally not seeing as well or you will see things that aren't there basically is there something that we could say in by way of advice for when this episode is released in the in the chaos of uh emotion sorry i don't know about a term that's just flying around on social media what's um well i actually think it is it is emotion in the following sense you know and it sounds a little bit like it sounds a little bit like artificial when i and the way i'm about to say it but i really think that this is what's happening you know one thing we haven't talked about is you know brains evolved didn't evolve for you to see they didn't evolve for you to hear they didn't evolve for you to feel they evolved to control your body that's why you have a brain you have a brain so they control your body and the metaphor the there's a the scientific term for predictively controlling your body is allostasis your brain is making um is attempting to it's tempting to anticipate the needs of your body and meet those needs before they arise so that you can act as you need to act and the metaphor that i use is a body budget you know your brain is running a budget for your body it's not budgeting money it's budgeting glucose and salt and water and instead of having you know one or two bank accounts it has gazillions there are all these systems in your body that have to be kept in balance and it's monitoring very closely it's making predictions about like when is it good to spend and when is it good to save and what would be a good investment and am i going to get a return on my investment whenever people talk about reward or reward prediction error or anything to do with reward or punishment they're talking about the body budget they're talking about your brain's predictions about whether or not there will be a deposit or withdrawal so when you when your brain is running a deficit in your body budgets you have some kind of metabolic imbalance you experience that as discomfort you experience that as distress when your brain when things are chaotic you can't predict what's going to happen next so i have this absolutely brilliant scientist working in my lab his name is um jordan terrio and he's published this really terrific paper on um a sense of should like why do we have social rules why do we you know adhere to social norms it's because if i make myself predictable to you then you are predictable to me and if you're predictable to me that's good because that that is less metabolically expensive for me novelty or unpredictability at the extreme is expensive and if it goes on for long enough what happens is first of all you will feel really jittery and antsy which we describe as anxiety it isn't necessarily anxiety it could be just something is not predictable and you are experiencing arousal because the chemicals that help you learn increase your feeling of arousal basically but if it goes on for long enough you will become depleted you will start to feel really really really distressed so what we have is a culture full of people right now who are their body budgets are just decimated yeah and there's a tremendous amount of uncertainty when you talk about it as depression anxiety it makes you think that it's not about your metabolism that it's not about your body budgeting that it's not about getting enough sleep or about eating well or about making sure that you have social connections um it's you know it's you think that it's something separate from that but depression anxiety are just a way of being in the world they're a way of being in the world when things aren't quite right with your predictions that's such a deep way of thinking like the the brain is maintaining homeostasis it's actually allostational stasis i'm sorry uh and it's it's constantly making predictions and metabolically speaking it's very costly to make novel like constantly be learning to making adjustments and then over time there's you know there's a cost to be paid if you're just yeah in in in a place of chaos where there's constant need for adjusting and learning and experience novel things and so part of the problem here there are a couple of things like i said you know it's a perfect storm there isn't a single cause right there are multiple cause multiple things that combine together it's a complex it's a complex system multiple things part of it is that um people are they're they're metabolically encumbered and they're distressed and in order to try to have empathy for someone who is very much unlike you you have to forage for information you you have to explore information that is novel to you and unexpected and that's expensive and at a time when people feel what do you do when you are running a deficit in your bank account you stop spending what does it mean for a brain to stop spending a brain stops moving very much stops moving the body and it stops learning it just goes with its internal model brilliantly put yep so empathy requires to have empathy for someone who is unlike you yeah requires learning and practice you're foraging for information i mean it is something i talk about in my in the book in seven and a half lessons about the brain i think it's really important it's hard but it's hard i think it's you know it it's hard for people to have to be curious about views that are unlike their own when um when they feel so encumbered and i'll just tell you i had this epiphany really i was listening to robert reich's the system he was talking about oligarchy versus democracy so oligarchy is where very wealthy people like extremely wealthy people shift power so that they become even more wealthy and even more insulated and from the you know the pressures of the common person um it's actually the kind of system that leads to the collapse of civilizations if you believe jared diamond just say that but anyways i'm listening to this and i'm listening to him describe in fairly decent detail how the ceos of these companies there's been a shift in what it means to be a ceo and not not being no longer being a steward of the community and so on but like in the 1980s it sort of shifted to this other model of being like an oligarch and he's talking about how you know it used to be the case that um that ceos uh made like 20 times uh what their um their employees made and now they make about 300 times on average what their employees made so where did that money come from it came from the pockets of the employees and they don't they don't know about it right no one knows about it they just know they can't feed their children they can't pay for health care they can't take care of their family and they worry about what's going to happen to their you know they're living like you know months a month basically any one big bill could completely you know put them out on the street so there are a huge number of people living like this so all they what their experience they don't know why they're experiencing it so it's and then someone comes along and gives them a narrative yeah well somebody else butted in line in front of you and that's why you're this way that's why you experience what you're experiencing just for a minute i was thinking i had deep empathy for people who have beliefs that are really really really different from mine but i was trying really hard to see it through their eyes yeah and did it cost me something metabolically i'm sure yeah i'm sure but you had something in the gas tank well i in order to allocate that i mean that's the question is like where did you you what resources did your brain draw on in order to actually make that effort well i'll tell you something honestly lex i don't have that much in the gas tank right now [Laughter] right so uh i i am surfing the stress that you know stress is just what is stress stress is your brain is preparing for a big metabolic outlay and it just keeps preparing and preparing and preparing and preparing you as a professor you as a human both right it's a for me this is a moment of existential crisis as much as anybody else democracy all of these things so in many of my roles so well i guess what i'm trying to say is that um i get up every morning and i exercise i run i row i lift weights right you exercise in the middle of the day i saw your like yeah you know daily yeah i hate it actually you love it right you get it no i hate it i hate it but i do it religiously yeah why because it's a really good investment it's an expenditure that is a really good investment and so when i was exercising i was listening to the book and when i realized the insights that i was sort of like playing around with like is this does this make sense does this make sense i didn't immediately plunge into it i basically wrote some stuff down i set it aside and then i did what i i prepared myself to make an expenditure i don't know what you do before you exercise i always have a protein shake always have a protein shake because i need to fuel up before i make this really big expenditure and so i did the same thing i didn't have a protein drink but i um but i i did the same thing and fueling up can mean lots of different things it can mean talking to a friend about it it can mean um you know it can it can mean get making sure you get a good night's sleep before you do it it can mean lots of different things but i i guess i i think we have to do these things i uh yeah that this i'm gonna re-listen to this conversation several times this is brilliant uh but i do i do think about you know i've encountered so many people that can't possibly imagine that a good human being can vote for donald trump and i've also encountered people that can't imagine that an intelligent person can possibly vote for a democrat and i i look at both these people many of whom are friends and uh let's just say after this conversation i can see as they're predicting brains not willing to invest the resources to empathize with the other side and i think you have to in order to be able to like to see the obvious common humanity in us i don't know what the system is that's creating this division we can put it like you said it's a perfect storm it might be the social media might i don't know what the hell i think it's a bunch of things i think it's just there's an economic system which is disadvantaging large numbers of people there's uh a use of social media like if you you know if i had to orchestrate or architect a system that would screw up a human body budget it would be the one that we live in you know we don't sleep enough we eat pseudo food basically we are on social media too much which is full of ambiguity which is really hard for a human nervous system right really really hard like ambiguity with no context to predict it i mean it's like really and then you know there are the economic concerns that affect large swaths of people in this country i mean it's really you i'm not saying everything is reducible to metabolism not everything is reducible to metabolism but there if you combine all these things together it's helpful to think of it that way then somehow it's also uh somehow reduces the entirety of the human experience the same kind of obvious logic like we should exercise every day in the same kind of way we should uh we should empathize every day yeah you know there are these really wonderful wonderful programs for um for teens and um sometimes also for parents of people who've lost children in in wars and in conflicts in political conflicts where they go to a bucolic setting and they talk to each other about their experiences and um miraculous things happen you know so um uh you know it's easy to uh it's easy to sort of shrug this stuff off as kind of pollyanna-ish you know like what's this really gonna do but um you have to think about when my daughter went to college i i gave her advice i said uh try to be around people who let you be the kind of person you want to be you were back to free will you have a choice you have a choice it might seem like a really hard choice it might seem like a unimaginably difficult choice do you have a choice do you want to be somebody who is wrapped in in fury and agony or do you want to be somebody who extends uh a little empathy to somebody else and in the process maybe learn something curiosity is the thing that it protects you curiosity is the thing it's curative curiosity on social media the thing i recommend to people um at least that's the way i've been approaching social media i i don't it doesn't seem to be the common approach but i basically uh give love to people who seem to also give love to others so it's the same similar concept of surrounding by yourself by the people you want to become and i ignore sometimes block but just ignore i don't i don't add aggression to people who are just constantly full of aggression and negativity and toxicity there's a certain desire when somebody says something mean to to um to say something um to you know say why or try to alleviate the meanness and so on but what you're doing essentially is you're and you're you're now surrounding yourself by that group of folks that have that negativity so even just the conversation so i you know i i think it's just so powerful to uh to put yourself amongst people who are yeah who whose basic mode of interaction is kindness because uh i mean i don't know what it is but maybe i'm just it's the way i'm built is that to me is energizing for the gas tank of that that i can pull to for sure when i start reading the rise and fall of the third reich and start thinking about nazi germany i can empathize with everybody involved i can start to think make these difficult uh like thinking that's required to understand our little planet earth well there is research to back up what you said there's research that's consistent with your intuition there you know that there's research that shows that being kind to other people doing something nice for someone else is like making a deposit to some extent you know because i think um [Music] making a deposit not only in their body budgets but also in yours like people feel good when they do good things for other people you know we are social animals we regulate each other's nervous systems for better and for worse right the best thing for a human nervous system is another human and the worst thing for a human nervous system is another human so you decide do you want to be somebody who makes people feel who who who makes people feel better or do you want to be somebody who causes people pain and we are more responsible for one another than we might like or then me might want but remember what we said about social reality you know social reality so you you you know there are lots of different cultural uh norms about uh you know independence or or you know collective you know nature of people but the fact is we have socially dependent nervous systems we evolved that way as a species and in this country we prize individual rights and freedoms and that is a dilemma that we have to grapple with and we have to do it in a way if we're going to be productive about it we have to do it in a way that um requires engaging with each other and which is what i understand the you know the founding members of this country uh intended beautifully put let me ask a few final silly questions so one we talked a bit about love but let me it's it's fun to ask somebody like you who can effectively from at least neuroscience perspective disassemble some of these romantic notions but what do you make of romantic love why do human beings seem to fall in love at least at least a bunch of 80s hair bands have written about it uh is that a nice feature to have is that a bug what is it well i i'm really happy that i fell in love i wouldn't want it any other way but i would say is that you the person speaking or the neuroscientist well i me that's me the person speaking but uh i would say as a neuroscientist babies are born not able to regulate their own body budgets because their brains aren't fully wired yet when you feed a baby when you cuddle a baby when you everything you do with a baby impacts that baby's body budget and helps to wire that baby's body budget has to wire that baby's brain to manage eventually her own body budget to some extent that's the basis biologically of attachment humans evolved as a species to be socially dependent meaning you cannot manage your body budget on your own without a tax that eventually you pay many years later in terms of some metabolic illness right loneliness when you break up with someone that you love or you lose them right it you feel like it's going to kill you but it doesn't but loneliness will kill you it will kill you approximately you know what is it seven years earlier i can't remember exactly the exact number it's it's actually in the web notes to um seven and a half lessons but um social isolation loneliness will kill you earlier than you would otherwise die and the reason why is that you're not you didn't evolve to manage your nervous system on your own and when you do you pay a little tax and that tax accrues very slightly over time over a long period of time so that by the time you're in you know middle aged or a little older you are more likely to die sooner from some metabolic illness from heart disease from diabetes from depression um you're more likely to develop alzheimer's disease i mean it's the it you know it takes a long time for that tax to accrue um but it does so yes i think it's a good thing for people to um to fall in love but i think the funny view of it is that uh it's clear that humans need the social attachment to uh what is it manage their nervous system as as as you're describing and the reason you want to stay with somebody for a long time it's so you don't have is the novelties very costly for uh for well now you're mixing now you're mixing things now you're you know no you have to decide whether but what i would say is when you lose someone you love you um it feels like you've lost a part of you and that's because you have you've lost someone who was contributing to your body budget we are the caretakers of one another's nervous systems like it or not and out of that comes very deep feelings of attachment some of which are romantic love are you afraid of uh your own mortality we two humans sitting here yeah do you think do you ponder your immortality i mean you're somebody who thinks about your brain a lot it seems one of the more um terrifying or i don't know i don't know how to feel about it but it seems to be one of the most definitive aspects of life is that it ends it's a complicated answer but i think the best i can do in a short snippet would be to say for a very long time i did not fear my own mortality i feared the i feared pain and suffering so that that's what i feared i feared being harmed or dying in a way that would be painful um but i didn't fear having my life be over now as a mother i i think i i have fear i fear dying before my daughter is um ready to be without me that's what i fear it's that's that's really what i fear and frankly honestly i fear my husband dying before me much more than i fear my own death there's that love and social attachment again yeah because i know i it's i know it's just gonna i'm gonna feel like i wish i was dead yeah a final question about life uh what do you think is the meaning of it all what's the meaning of life yeah i think that there isn't one meaning of life there's like many meanings of life and you know you use different ones on different days but for me depending on the day depending on the day but for me i would say um sometimes the meaning of life is to understand to make meaning actually the meaning of life is to make meaning um sometimes it's that sometimes it's to um leave the world just slightly a little bit better than it like the johnny appleseed view you know sometimes um the meaning of life is um to um you know like clear the path for my daughter or for my students you know it's to you know so sometimes it's that and sometimes it's just um you know like you know your moments where you're looking at the sky or you're you know by the ocean or sometimes for me it's even like i'll see a you know like a weed poking out of a crack and a sidewalk you know and you just have this overwhelming sense of the like wonder of the um of the world like the world is like just like the physical world is so wondrous and you you just get very immersed in the mome in the moment like the sensation of the moment sometimes that's the meaning of life i don't i don't think there's one meaning of life i think it's a population of instances just like uh just like any other category i don't think there's a better way to end it lisa the first time we spoke is um i think if not the then one of i think it's the first conversation i had that basically launched this pocket yeah that's actually the first conversation i've had to launch this podcast and now we get to finally do it uh the right way so it's a huge honor to talk to you that you spent time with me uh i can't wait for hopefully the many more books you'll write certainly can't wait to uh i already read this this book but i can't wait to listen to it because as you said offline that you're reading it and i think you have a great voice you have a great i don't know what's a nice way to put it but maybe npr voice in the best version of what that is so thanks again for talking today always my pleasure thank you so much for for having me back thank you for listening to this conversation with lisa feldman barrett and thank you to our sponsors athletic greens which is an all-in-one nutritional drink magic spoon which is a low-carb keto friendly cereal and cash app which is an app for sending money to your friends please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter lex friedman and now let me leave you with some words from lisa feldman barrett it takes more than one human brain to create a human mind thank you for listening i hope to see you next time you |
Michael Malice: Anarchy, Democracy, Libertarianism, Love, and Trolling | Lex Fridman Podcast #128 | the following is a conversation with michael malus an anarchist political thinker author and a proud part-time andy kaufman-like troll in the best sense of that word on both twitter and in real life he's a host of a great podcast called you're welcome spelled y-o-u-r i think that gives a sense of his sense of humor he is the author of dear reader the unauthorized autobiography of kim jong-il and the new right a journey to the fringe of american politics this latter book when i read it or rather listened to it last year helped me start learning about the various disparate movements that i was undereducated about from the internet trolls to alex jones to white nationalists and to techno anarchists the book is funny and brilliant and so is michael unfortunately because of a self-imposed deadline i actually pulled an all-nighter before this conversation so i was not exactly all there mentally even more so than usual which is tough because michael is really quick-witted and brilliant but he was kind patient and understanding in this conversation and i hope you will be as well today i'm trying something a little new looking to establish a regular structure for these intros of first doing the guest intro like i just did second quick one or two sentence mention of each sponsor third my side comments related to the episode and finally fourth full ad reads on the audio side of things and on youtube going straight to the conversation so not doing the full ad reads and as always no ads in the middle because to me they get in the way of the conversation so quick mention of the sponsors first scm rush the most advanced seo optimization tool i've ever come across i don't like looking at numbers but someone probably should it helps you make good decisions second sponsor is doordash food delivery service that i've used for many years to fuel long uninterrupted sessions of deep work at google mit and i still use it a lot today third sponsor is masterclass online courses from the best people in the world on each of the topics covered from rockets to game design to poker to writing and to guitar with carlos santana please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that i hope to have some conversations with political thinkers including liberals and conservatives anarchists libertarians objectivists and everything in between i'm as allergic to trump bashing and trump worship as you probably are i have none of that in me i really work hard to be open-minded and let my curiosity drive the conversation i do plead with you to be patient on two counts first i have an intense busy life outside of these podcasts like it's 4 00 am right now as i'm recording this so sometimes life affects these conversations like in this case i pull on all nighter beforehand so please be patient with me if i say something ineloquent confusing dumb or just plain wrong i'll try to correct myself on social media or in future conversations as much as i can i really am always learning and working hard to improve second if i or the guest says something about for example our current president donald trump that's over the top negative or over the top positive please don't let your brain go into the partisan mode try to hear our words in an open-minded nuanced way and if we say stuff from a place of emotion please give us a pass nuanced conversation can only happen if we're patient with each other if you enjoy this thing subscribe on youtube review five stars and a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now here's my conversation with michael malus there was a simpsons episode where he starts mixing like um sleeping pills with like pet pills and he's driving his truck and i like i want to see what happens with this red bull and nitro there's a lineup of drugs this is gonna be so fun yeah let's start with love yes yeah so one one thing we'll eventually somehow talk about it'll be a theme throughout is that you're also russian yes a little bit less than me but how loud why because i'm from ukraine oh you're from ukraine okay wow no because you came here a little bit when you were younger yeah i i i came here when i was 13 so i saturated a little bit of the russian soul i i marinated in there so a little deeper i haven't told anyone this but i'll be glad to tell you davidish um i haven't been back since i was two and next summer it looks like me my buddy chris williamson who's also a podcaster he's british modern wisdom he looks like apollo we're we looks like we got a videographer which apollo the god so we're going to go for the first time to see where i came from which is ukraine we're going to go to level and either st petersburg or moscow probably st petersburg or both it's going to be intense it's going to be a lot of panic attacks i feel and your russian is okay no you can't talk russian ukraine or it's like they get offended yeah but then you also want to go to russia yeah i don't know for me there's several people in russia i want an interview on a podcast okay so one one of them is uh guerrilla promon which is a mathematician and the other person is putin you know my favorite food and story is do you know this no when he had merkel with him do you know this story no merkel's scared of dogs like petrified of dogs so he brings in his like like like uh black lab it's a labrador it's like the sweetest animal and it's all over her and there's pictures and she's sitting like this and she's terrified and he's like what's wrong angela it's just completely trolling her yeah he's aware of the sort of uh the narrative around him yeah and then he plays with it yes he enjoys it it's a very russian thing my friend wanted to film about me he goes i realize you guys aren't like us at all you just like like look at us and then i started telling him stories about the upbringing and he's like oh my god and as i'm telling them like wow this stuff is really crazy like what how we are wired who's the we your friend is the russian the friends american i'm saying the way russians are brought up and the way maybe i don't think it was just my family i bet you had similar things like here's an example i i was i had a buddy staying with me he had a problem with his roommate so he crashed in my place fine i went to the gym and i come back and he goes oh there was and my apartment buildings has four four apartments so it's not like a huge thing he goes oh there was someone knocking at your door so you know i i told him blah blah and and for me and i wonder if you're the same way if i'm at someone's house that's not my own and someone knocks on the door i wouldn't even think to answer it like if i had an apple here might be i'd eat it i'd cut it whatever i'm not gonna it just doesn't enter my head to smash into my face the the thought of answering the door if it's not my house it would never enter my head would it enter your head no but why but he's an american so someone's at the door he goes and opens it even though it's not his house i would never do that i would never think to do that that is so strange you pick some very obscure thing to delineate americans i don't think that's obscure because i think it speaks to how we perceive strangers with americans everyone's friendly and with us it's like no no like you have that moat and i think that's a that percolates into many different aspects of how we relate to people and i had to undo a lot of that that's true you're right there's uh the relationship i formed there were in russia or very deep yeah close and then there's the strangers the other that you don't trust by default it takes a long time to go over the moat of trust for a long time until recently whenever i said anything to anyone my brain ran a scan that said if this person turns on you would this can they use this against you and i would do everything i said with strangers and after a while it's like you know what maybe they will but i'm strong enough to take it but this is not how americans think well here's another one let me ask you this sorry i'm taking over the interview people asked about like advice for work right like i had this there was this party i went to and basically everyone had their own problems and everyone else gave their advice right and someone was having a problem with the co-worker and the advice these dupoy americans gave them is oh sit down and have a talk with them and to me this is like the last case last resort like first you have to see what you can without showing your hand sharing your vulnerability only when everything hasn't worked out or you're like all right let me sit down with you and try to have it out with you probably but for them the first thing is like sit down and be like oh you're causing me problems and blah blah so i perceive that right away as a threat that this person sees an antagonism between us and also as a weakness that i'm getting to them so my reaction isn't um how do i make it better my reaction is to reinforce my position and see what i can to marginalize them usually i haven't worked in a corporate setting in a long time but it's not i don't approach it the way an american would like i'm glad you came and talked to me now i probably would because it's gonna be a friend so you attribute that to the russian upbringing as opposed to you have deep uh psychological issues i think those are synonymous wait am i would you think differently maybe a few years ago um i don't know i i i think you lost me at the because you kind of said that you're kind of implying you have a deep distrust of the world like the world does i think the default setting would be distrust yeah but i would put it differently is i almost ignore the rest of the i don't even acknowledge it i just uh savor i save my love and trust for the small circle of people i agree but when that person is being confrontational or as they perceive it as being open now there's a situation how do you how would you handle that like like a cold wind blows he's just kind of like yeah but it's not like this is an opportunity for us to work out our differences it's a cold wind it's not a hug that's my point you're so suspicious what it really is is a cold wind i'm so inhumane to be scared of it's a cold wind person but it's not this is great but it's not a source of like i'm not suspicious of like i'm not uh anxious i would say or like living in fear of the rest of the world anymore oh i agree but you're not receptive to that person right that's all i'm saying and they are got it so speaking of which let's talk about love yes which requires to be receptive of the world yes of strangers i agreed how do we put more love out there in the world especially on the internet one mechanism i have found to um increase love and that's a word that has many meanings and is you know used in a very intense sense and it's used in a very loose sense can you try to define love sure love is a strong sense of attraction toward a another person entity or place that causes one to tend to react in a disproportionately positive manner that's off the top of my head disproportionately yes so for example if why not proportionally because like if you're someone's about to who you love is about to get harmed you're moving heaven and earth to make sure uh or like a book you love you know like i love this book like you're going through the fire to try to save it whereas if it's a book you really like it's like huh i'll get another one i don't you know and a book's a kind of a loose example but so you're going with the love that's like you're saving for just a few people almost like romantically like love for a close family but it's also just love to even the broader like the kind of love you can put out to people on the internet which is like just kindness sure i would say in that case it's important to make them feel seen and validated and i try to do this when people who i have come to know on the internet and there's a lot i try to do that as much as possible because i don't think it's valid how on social media and i do this a lot myself but not towards everyone it's just there to be aggressive and antagonistic you should be antagonistic towards bad people and that's fine but at the same time there's lots of great people and especially with my audience and i would bet disproportionately with yours there's a lot of people who are because of their psychology and intelligence are going to be much more isolated socially than they should and if i and i've heard from many of them and if i'm the person who makes them feel oh i'm not crazy it's everyone else around me who is just basic uh the fact that i can be that person which i didn't have at their age to me is incredibly reaffirming you mean a source of love but i mean love in the sense of like you know you care about this person and you want good things for them not in a kind of romantic way but i mean you're using in a broad sense now yeah but you're also a person who kind of i mean uh attacks this power structures in the world by mocking them yes effectively yes and uh love i would say requires you to be non-witty and simple and fragile which i see it as like the opposite of what trolls do trolls are if i if there is someone coming after what i love there's two mechanisms right at least two i go up and i'm fighting them and in which case you bring in if you are getting hurt and i fight even if you win the knife fight or if you disarm them and you preclude the possibility of a fight and you drive them off or render them powerless you can you keep your person intact as yourself and you also protect your values so how do you render them powerless as you just said by mocking them one of the most effective mechanisms for those in power we're much closer to brave new world than 1984. the people who are dominant and in power aren't there because of the threat of you know the gulag or prison they're there because of social pressures look at the masks i was on the subway not that long ago in new york city um no one cared who i was until i put out the mask i was in the subway that long in new york city there was and i put this on my instagram i've told this story before there was an asian dude in his early 30s he was like in western clothes it's not like he had a rickshaw or something an older man in his 50s stood up over him on the subway screamed at him said go back where you came from you're disgusting i'm going to get sick if you think this guy is a vector of disease which is your prerogative why are you coming close to him why are you getting in his face and what that was sorry so it was because he was asian it was both it was the not having a mask gave him the permission to act like a despicable aggressive person toward him right and the point being a lot of these mechanisms for social control are outsourced to low-quality people because this is their one chance to assert dominance and status over somebody else so the best way to defuse that isn't with weaponry or fighting it's through mockery because all of a sudden their claims to authority are effectively destroyed so let me push back on that what about fighting that with with love with um patience and like kindness towards them i i don't think kindness is i think that would be uh a mismatch and inappropriate there's superman is batman okay and superman's job is to help the good people and batman's job is to hurt the bad people and i will always be on the batman side than the superman side both work the silly tight costumes one has pointy ears both are ridiculous so it's uh it was a billionaire who gets you know he's swimming in trim which one is the best batman okay i'm uh i'm undereducated on um okay on the superhero movies i apologize okay but but you're just saying you your predisposition is to be on the batman side is to uh fighting the bad guys yeah and that's what i'm good at that's what you're good at but just to play devil's advocate or actually in this case i am the devil because that's what i usually do watch the devil here the other angels advocate exactly to be the to be the angel advocate yeah it's like i feel like mockery is um is a as a path towards escalation of conflict yes in many ways yes so you're not i mean it's kind of like guerrilla warfare it means you're not going to win i am winning we're all winning we're winning on a daily this is my next book we're winning we've won before i'm not joking the net the topic of the next book yes is the white pill the white pill is that we're gonna we are winning the most horrible people are being rendered into laughing stocks on a daily basis social media this is glorious i so disagree with you i disagree with you because there's side effects that are very destructive it feels like you're winning but we're completely destroying the possibility of having um like a cohesive society that's called oncology what's that mean curing cancer no your concept of a cohesive society is in fact a society based on oppression and not allowing individuals to live their personal freedom oh so your your utopian view of this you're the utopian you're saying cohesive society i'm saying i don't need that i'm saying there's going to be conflict right there's going to be conflict you and i are disagreeing right now that's not cohesive doesn't mean we like each other less doesn't mean we respect each other less cohesive doesn't it it's just a euphemism for like everyone's submitting to what i want no i mean cohesive could could uh could be that it could be um it could be like enforced with violence all that kind of stuff sort of the uh the libertarian view of the world but it could just be being respectful and kind of each other and kind towards each other and loving towards each other i mean that's what i mean by cohesive so when people say free it's it's funny like freedom is a funny thing because freedom can be painful to a lot of people it's it's all matters how you define it how you implement it how it actually looks like sure and i'm just saying it feels like the mockery of the powerful leads to further and further the divisions it's like it's turning life into a game to where it's always you're playing you you're creating these different little tribes and groups and you're constantly uh fighting the groups that become a little bit more powerful by undercutting them through guerrilla warfare kind of thing and that's what the internet becomes is everyone's just mocking each other and then certain groups become more and more powerful and then they start fighting each other and into basic they they form groups of ideologies and they start fighting each other in the internet where the result is it doesn't feel like the common humanity is highlighted it doesn't feel like that's a path of progress now like when i say cohesive i don't mean like everybody has to be you know enforcing equality all those kinds of ideas i just mean like not being so divisive that's like so it's going back to the original question of like how do we put more love out in the world than the internet i i want divisiveness oh you see you think that this is that's that goal it's very interesting it's the goal so you we started this conversation with you talking about you have love for that small group uh i think we both would agree to have a bigger group be better especially if that love comes from a sincere place um i think our country specific i wrote an article about this four years ago that it's time to disunite the states and to secede this country has been held together with at least two separate cultures with thumbtacks and string for over 20 years uh there's an enormous amount of contempt from one group toward another this contempt comes from sincere place they do not share each other's values there's absolutely no reason just like any unhealthy relationship where you can't say you know what it's not working out i want to go my own way and live my happiness and i genuinely want you to go your way live your happiness if i'm wrong prove me wrong i'll learn from you and and take lessons and vice versa but the fact that we all have to be in the same house together is not coherent and that's not love that is the path towards friction and tension especially do you think there's concrete groups like is it as simple as the two groups of blue and red no it's it's it's it's also very fluid because you and i are allied as jewish people as russians as males as podcasters uh you're an academic i'm not there so there's there we're different but we each are a venn diagram even within ourselves and i can talk to you about politics and then we can talk about russia stuff and then you could talk about your your work which i don't know anything about so that would be where you're way up here in our way down here so there's lots every relationship with just between individuals there's it's very dynamic so how do we succeed like how do we form individual states sure there's a little bit more cohesion sure the and voluntary cohesion so the first step is to uh um eliminate and the concept of political authority as legitimate and to uh denigrate and humiliate those who would put themselves in a position in which they are there to tell you how to live your life from any semblance of validity and that's starting to happen um if you look at what they had with the lockdowns cuomo and de blasio new york uh we have i was uh tired a couple weeks ago and i said to my friend oh just click maybe i've covered and he goes it's not possible like what do you mean and he goes we haven't had any deaths in like two months and there's only 100 cases a day for like two months and i go you're exaggerating because everything was still closed and i looked at the numbers and he wasn't exaggerating and there's no greater american dream to me than an immigrant family comes to the states forms their own little business maybe mom's a good cook it's a restaurant dry cleaner fruit stand and those people aren't going to have a lot of money those are the first ones who lost their companies because of these lockdowns they cuomo who's the governor of new york opened up the gyms he said you're clear to open up de blasio said and we don't have enough inspectors you're gonna have to wait another couple of weeks uh to regard that as anything other than literally criminal is something that i am having a hard and harder time wrapping my head around you said i mean that's something i'm deeply worried about as well which is like thousands it's actually millions of dreams being crushed that amer american dream of starting a business of running a business what about all the young people who you and i have in our audiences who are socially isolated at best and now they can't leave their homes uh isolation and ostracism are things that are very well studied in psychology these have extreme consequences i read a book called ostracism and this wasn't scientific but basically the author was a psychiatrist at college whatever and he had one of his colleagues they did an experiment let's for a week you ostracized me completely we know it's an and he goes even knowing it's the experiment the fact that he wouldn't make eye contact with me and the fact that he ignored me had an extreme emotional impact on me knowing full well this is purely for experimental purposes now you multiply that by all these p the suicide the number of kids were thinking about suicide was through the roof during all this uh and my point is until these people it's gonna i would predict like 2024 that's where we're going to have to start having conversations about what personal consequences have to be done for these people because until then they're going to do the same thing so you think there's going to be society-wide consequences of this that we're going to see like ripple effects because of the social isolation i i know i mean we also need to talk about consequences or cuomo de blasio because if politicians respond to incentives and the incentives are there for them to be extremely conservative because if you have to choose as cuomo said a press conference between a thousand people dying and a thousand people losing their business it's not a hard choice and he's right but at a certain point it's like all right you're losing both you're losing not losing the you're making these decisions um and not having consequences for it and you're going to do it again the next time so we need to make sure you're you're a little scared okay and i don't know what that would mean but you're laying this problem this this incompetence i don't think it's incompetence i think it's very competent i think they're just they're jobs yes but what but you're laying it not at the the hands of the individuals but the structure of the of government it's both yes how would we deal with it better without centralized control well we didn't really have centralized control because every country and every state you know handled it in a different mechanism but a city has centralized control just yeah right i mean no that's not true so cuomo de blasio they had a lot of disagreements over this over the months and this was actually a source of great interest and tension um de blasio wanted at one point was talking about like quarantining people in their homes home was like you're crazy uh something same thing with the schools same thing with the gyms um and there are other such uh examples but the point being this was an emergency this is world war one i talked about some timpool show um was very dangerous because it gave a lot of evil people some very useful information about what the country put up with and what they can get away with under wartime and this set the model for things like the new deal and the other things of that nature it is undeniable you're a scientist so you understand this perfectly well um that this lockdown gave some very nefarious people some very valid data about how much people will put up with uh under uh pressures from the state so fundamentally what is the problem with the state that's existence okay well but but uh uh to play angel's advocate again you know government is the people so come on you don't you you you're do you do you really think this at as best i think it's possible to have represent representation can you imagine if you have an attorney you're like oh you can't have the attorney you want you're gonna have this guy who you absolutely hate who you share no values with why because he drives i mean leaders political leaders and political representation drive the discourse like we you know uh the majority of people voted for him or whatever however however he defined that and now we get to have a discussion well was this the right choice and then we get to make that choice again in four years and so on first of all the fact that i have to be under the thumb of somebody four years makes no sense there's no other relationship that's like this including a marriage you can leave any other relationship at any time number one number two is it always impeach but they did that part of it i'm in just saying yeah that there's yeah the mechanisms are uh flawed in many ways yeah yeah right and and so that's number one number two is it doesn't make sense that if i don't want someone to represent me that because that person is popular that they are now in a position to so having uh um representation and and having citizenship based on geography is a pre line technology in a post-cell phone world there's no reason why i have to just because we're physically in between two oceans we all have to be represented by the same people whereas i can very easily have my security be under someone and switch it as easily as cell phone providers so okay but it doesn't have to be geographical it can be ideas sure i mean this country represents a certain set of ideas yes it does it started out geographically it still it was just it started off as ideas as well but like there's a it's it was intricately i mean that's the way humans are there's i mean there was no internet so it was you were geographically in the same location and you signed a bunch of documents and then you kind of debated and you wrote a bunch of stuff and then you agreed on it okay so you understand that no one signed these documents and no one agreed to it as lysandra spooner pointed out over 150 years ago the constitution or the social contract if anything is only binding to the signatories and even then they're all long dead uh so it's it's this fallacy that somehow because i'm in a physical place i have agreed even though i'm screaming to you a face that i don't agree to be um subordinate to uh some imaginary invisible monster that was created 250 years ago and this idea of like if you don't like it you have to move that's not what freedom means freedom means i do what i want not what you want so if you don't like it you move okay just to put some i don't like words and terms one one one zero one one one zero yeah exactly is that what your language is it is i'm translating it all in real time but uh would you call the kind of ideas that uh you're advocating for and we're talking about anarchy yes anarchism yes okay so let's get into it can you can you try to paint the utopia that an anarchist worldview dreams about the only people who describe anarchism as utopia are its critics if i told you right now and i wish i could say this factually that i have a cure for cancer that would not make us a utopia that would still probably be expensive we would still have many other diseases however we would be fundamentally healthier happier and better off all of us than democracy so that democracy sorry i jump back from the cancer no that democracy or government so it's only curing one major major life-threatening problem but in no sense is it a utopia so what can we try to uh answer this question same question many times which is what exactly is the problem with democracy the problem with democracy is that those who need leaders are not qualified to choose them those who need leaders are not qualified to choose them so that's the central problem of democracy not all of us need leaders right what does it mean to need a leader are you saying like people who are actually like free thinkers don't need leaders kind of thing sure that's but like take a wave but like you don't okay so do you acknowledge that there's some value in authority in different subjects so what what that means is i don't mean an authority somebody who's in control of you but you're doing the definition switch because i am i am you're right you're right it's unfair okay those those bad but that's what they do that's their trick yeah and it's this is one of the useful things by the way less is total sidebar if people ask me for advice i always tell them if you're going to raise your kids raise them bilingual because i was trilingual by the time i was six and that teaches you to think in concepts whereas if you only know one language you fall for things like this because using authority in the sense of a policeman and someone is an authority in physics it's the same word conceptually they're extremely different but if you're only thinking in one language your brain is going to equate the two and that's a trap that people who only speak one language have for sure but even if you know multiple languages you can still use the trick of using your c or convenience yeah absolutely to manipulate the conversation you weren't trying to do that but you you fell in i accidentally did it yeah right we all tend to do that if you only speak one language and think of one language but if i guess let me rephrase it i are you against do you acknowledge the value of like offloading your own effort about a particular thing to somebody else absolutely like an accountant a lawyer a doctor absolute a chef infinite isn't that ultimately what a democracy is broadly defined like you're basically electing a bunch of authorities using the word you in two senses using the word you meaning me as an individual now using you as a mass yes as a math not use an individual so i have i would absolutely want someone to provide for my security i would absolutely want someone to negotiate with me for foreign power or something like that that does not mean it has to be predicated and what lots of other people who i do not know and if i do know them probably would not respect think about it's of no moral relevance to me nor eye to them so do you think this kind of there could be a bunch of humans that behave kind of like ants in a distributed way there could be an emergent behavior in them that results in a stable society like isn't that the hope with anarchy is like without an overarching uh but answer i i mean answer the worst example here because ants have a very firm authority the queen yeah and they're all they're all drones they're all clones of each other yeah but so if you forget the queen their behavior they're all well from your perspective from your human intelligence perspective but from their perspective they'll probably see each other as a bunch of individuals no they don't ants are very big on altruism in the sense of self-sacrifice they do not think the individual matters they routinely kill themselves for the sake of the hive in the community but they see that's from the outside perspective from the individual perspective of the individual they probably they they don't see it as altruism right but they they view and they're right because the aunt's life is very ephemeral and cheap that it's more important to continue this mass population that that one individual ant live like bees are another even better example the honey bee when they sting they only sting once and they die and they do it gladly because it's like okay this community is much more important than me and they're right yeah okay so fine let's forget i'm being pedantic but it's important i think i'm not just being for the sake of being fed but there's something beautiful that i won't argue about because i do there's an interesting point there about individualism of ants i do think they're more individual but like let's let's give your view of ants that they're it's their communists okay let's go with the communist view of ants okay yeah uh but there's still a beautiful emergent thing which is like they can function as a as a society and without i would say centralized control so is that the hope for anarchy it's like you just throw a bunch of people that voluntarily want to be in the same place under the same set of ideas and they kind of like the doctors emerge the police officers emerge the uh the different necessary structures of a functional society emerge do you know what the most beautiful example of anarchism is that is just beyond beautiful when you stop to think about it i'm not being tongue-in-cheek language there's infinite languages language the things that language can be used for are bring tears to people's eyes quite literally it's also used for basic things no one is forcing us we speak two languages each at least no one's forcing us to use english no one's forcing us to use this dialect of english uh it's a way and and despite there being so many different languages uh lingua franca emerge you know people the language that everyone is in latin even in north korea they refer to the fish and the different animals by the latin scientific uh no one decided this sure there's an organization that sets a binomial nomenclature but there's no gun to anyone's head referring to uh seamoth as a pegasus species and when you think about how amazing language is and someone other context would say like well you you need to have a world government and they're deciding which is the verbs and you have to have an official definition and an official dictionary and none of that happened and i think anyone even if they don't agree with my politics or my worldview cannot deny that the creation of language is one of humanity's most miraculous beautiful achievements absolutely so there there you go there's one system where a kind of anarchy can result in in beauty stability like sufficient stability and yet dynamic flexibility to adjust it and so on and the internet helps it you get some something like urban dictionary which which starts creating absurd both humor and wit but also language and syntax and jargon immediately you size people up if you use if you say vertebral i know you're a doctor because that's how they pronounce it the the spinal column uh i'm sure in your field there's certain jargon right away you can know if this person's one of us or not i mean it's infinite i mean i don't need to tell you and it's emojis too yes there's so much there to study with language it's fascinating but do you think this applies to human life the the meat space the physical space yes so these there's that kind of beauty can emerge without uh without writing stuff on paper without laws you could have rules you don't need you don't have to be laws so enforced by violence like that's what what's a law a law is something that is unchosen a rule is something if i go to my pool and i i sign up to remember a pool on the wall lists certain things it's like you know certain number of people in the pool no peeing in here good luck enforcing that one um and so on and so forth well that's the problem aren't you afraid that people are gonna pee in the pool that's not as my biggest concern is mass incarceration as the fact that the police can steal more money than burglars can the fact that innocent people can be killed with no consequences the fact that war can be waged and with no uh consequences for those who waged it the fact that so many men and women are being murdered overseas and here and the people who are guiding these are regarded as heroic so you think there might that in an anarchist system there's a possibility of have of having less wars and less what would you say corruption and uh less abuse of power let's talk yes and let's talk about corruption because and i made this point on rogan you and i again this the russian background we realize that when it comes to corruption american is very naive corruption they think is oh i got my brother a job and he's getting money on the table that's not when we're talking about like state corruption things that are done in totalitarian states and even to some extent in america like jeffrey epstein julian maxwell things that stalin did things that hitler did you know when the cia was torturing people at gitmo they had to borrow kgb manuals because they didn't know how to torture correctly because they never thought of these things we it's very hard for us to get into the mindset of someone who's like a child predator someone who uh let me give you an example from my forthcoming book there was a guy who was the head of ukraine in the 30s i forget his name now these old soviets they were tough i mean they pride stalin means steel you know they pride themselves in their cruelty and how strong they were and this was the purge you know stalin is trying to you know killing lots of people left and right and his henchman beria had the quote uh find me the man i'll find you the crime you know they would accuse someone and they would torture him until he talked and confessed and then he had to turn people in and they took this guy in like beginning the year i think it's 36 38 he was had ukraine by may he's arrested and they take him to the le blanca the basement in the red square where they're torturing people and they put they did the works on him and he was a good soviet he stood up and he who knows what they did to him he didn't talk so they said okay one moment they brought his teenage daughter in raped her in front of him he talked so when we talk about corruption we would never in a million years think of this that's not how our minds work um so when you're talking about states and people where you don't have ease of exit where you are forced to be under the auspices of an organization creating a monopoly that leads to in extreme cases but in not as extreme cases really uh nefarious outcomes whereas if you have the option to leave as a client or customer that would have a strongly limiting effect on uh how a business and what it can get away with so but don't you think maybe i don't know who the right example is whether it's stalin i think hitler might be the better example of don't you think or jeffrey epstein perhaps don't you think people who are evil will will find ways to manipulate human nature to attain power no matter the system yes and like the the corollary question is do you think those people can get more power in um in the democracy in a you know in when there's a government already in place they can it's easily they get more power more dangerous they have a government place first of all sociopaths are known for their charm and for their warmth here's the two situations in in a free society i'm a sociopath i'm an evil person i'm the head of macy's in a state society i'm an evil person i'm a sociopath i'm the head of the us government which of these are you more concerned with it's like night and day so you would have far more decentralized military you would have far more decentralized security forces and they would be much more subject to feedback from the market if you have an issue with macy's or any store with a sweater look at that transaction if you have an issue with the state to you hiring a lawyer costs more than a surgeon to even access the mechanism for dispute is going to be exorbitant and price poor people out of the market for um conflict resolution immediately so right away you have something that's extremely regressive and even though this is touted as some great equalizer it's quite the opposite so in current society there's a deep suspicion of governments and states they're not that's not really like just your example of macy's i mean don't you think a hitler could rise to be at the top of a social network like twitter and facebook okay let's suppose hitler ran twitter okay let's take this thought experiment seriously literally what could he do so all the only tweets are gonna be about how much the jews suck right okay fine okay all the cool people are leaving there could be some compelling like you said um evil people are charming there could be some compelling narratives that could be with conspiracy theories uh untruths that could be spread like propaganda every criticism of anarchism is in fact a description well the strongest criticisms of anarchism are in fact description of the status quo your concern is under anarchism propaganda would spread and people would be taught the wrong ideas unlike the status quo that's not even a criticism of anarchism i'm not actually criticizing it's an open question of it's an open question of in which system will human nature thrive be be able to thrive more and in in which system would the evils that arise in human nature would be more easily suppressable there that's that's the question it's a scientific experiment and i'm asking only from our perspective of the fact that we've tried democracy quite a bit recently and we i don't maybe you can correct me we haven't yet seriously tried anarchy in a large scale well we don't need to try to so anarchy isn't like a country right it's like it's you can't i'm not it's like saying well if anarchy works how can we've never had an anarchist government right so anarchism is a relationship and language is an example of this it's a worldwide and our system you and i have an anarchist relationship there's almost no circumstances we'd be calling the police on each other i mean it's i'm asking the same question in a bunch of different directions out of born out of my curiosity is why is anarchy going to be better at preventing the darker sides of human nature which presumably your criticism of government because it's this because of decentralization so the darker side of human nature is an extreme concern anyone who says it's going to go away is absurd and fallacious i think that's a non-starter when people say that everyone's going to be good human beings are basically animals we're capable of great beauty and kindness we're capable of just complete cruel and what we would call inhumanity but we see it on a daily basis even today uh and what's interesting is the corporate press won't even tell you the darkest aspects because that's too upsetting to people so they'll tell you about atrocities and horrors but only to a point um and then when you actually do the homework you're like oh it's so much worse than like that thing about stalin right so we know in a broad sense that stalin was a dictator we know that he killed a lot of people but it takes work to learn about the hall of demore it takes work to learn about what those literal tortures were and that this is the person who later fdr and harry truman were shaking hands with and taking photos with and was being sold to us as uncle joe you know he's just like you and me um so when you have a decentralized information network as opposed to having three media networks it is a lot easier for information that doesn't fit what would be the corporate america narrative to reach uh the populations and it would be more effective for democracy because they're in a much better position to be informed now you're right it also means well if everyone has a mic that means every crazy person and with their wacky views and at a certain point yeah it has to become then there's another level which is then the people have to be self-enforcing and and you see that on social media all the time when someone says this the other person jumps in you think but isn't social media a good example of this like so you think ultimately without centralized control you can have stability like what about the mob outrage and the mob rule the the power of the mobs that that emerge power of the mob is is a very uh serious concern uh gustav labon wrote a book in the 1890s called the crowd and this was one of the most important books i've written because it influenced both mussolini and hitler and stalin and they all talked about it and he made the point that under crowd psychology human lynching is another example this none of those individuals or very few would ever dream of doing these acts but when they're all together and you lose that sense of self you become the ant and you lose that sense of individually you're capable of doing things that like in another context you'd be like i should kill myself i'm a monster so you're worried about that but like is in the mob doesn't the mob have more power under anarchy no the mob has much less power on anarchy because under anarchism every individual is fully empowered you wouldn't have uh um uh gun restrictions you would have people creating communities based on shared values they would be much more collegial they'd be much more kind as opposed to when you're forcing people to be together in a polity when they don't have things in common that is again like having a bad roommate if you're forced to look at jails if you're forced to be in locked in a room with someone even if you at first like them after a while you're going to start to hate them and that leads to very nefarious consequences so as an anarchist what do you do in a society like this thrive i think i'm doing okay [Laughter] i mean i mean there's an election coming up there's uh as as you talk uh you're welcome is one of the 15 shows that you host it's you talk about libertarianism a little bit yeah i mean is there some practical political direction like in terms of we as a society should should go i don't mean we as a nation i mean we as a collective of people should go to uh to make a better world from an anarchist point of view sure uh i think politics is the enemy uh and anything i need to find politics so anything that lessens its sway on people anything that delegitimizes it is good i wrote an article a few years ago about how wonderful it is that trump is regarded as such a buffoon because it's very very useful to have a commander-in-chief who's regarded as a clown because it's going to take a lot to get him to convince your kids to go overseas and start killing people and making widows and orphans as well as those kids coming home in caskets whereas if someone is regarded with prestige and they're like oh we need to send your kid overseas oh absolutely i mean this guy's great so that is a very healthy thing where people are skeptical of the state but there's a lot of people that uh regard him as as one of the greatest leaders we've ever had yeah dinesh d'souza he's another lincoln i when you talk shit about trump or talk shit about biden i think i'm trying to find a line to walk where you they don't immediately put you into the this person has trump derangement syndrome or they have the other the alternative to that i i'm more than happy when people are preemptively dismissing me because then i don't have to waste time engaging with them because those people will be of no use to me when i was on tim pool recently tim poole's show uh tim poole's known for his little like hat i got a propeller beanie motorized and it was just spinning the whole two hours like the 1950s thing the point being i wore it because there's lots of people who would say i can't take seriously someone who wears a hat like that and my point being if you are the kind of person who takes your cues based on someone's wardrobe as opposed to the content of your ideas you're of no use to me as an ally so i'd be more than happy you preemptively abort rather than waste our breath this is the deep this is a very very deep thing that you and i disagree on which is this is goes to the trolling versus the love is i believe that person instinctually dismisses you on the very basic surface level yes but deep down there actually there's a wealth of a human being that seeks the connection to seeks to understand deeply to connect with other humans that we should speak to i think you and i completely disagree see you're saying i'm saying there's no mind there literally okay so let's i naturally i think that majority so i naturally think the majority of people are have the capacity to be thoughtful intelligent and um you know learn about ideas ideas that they instinctually based on their own likes current inner circle disagree with and learn to understand to empathize with the other like i and in the current climate there's a divisiveness that discourages that and that's where i see the value of love of of encouraging people to to uh to strip away that surface instinctual response based on the thing they've been taught based on the things they listen to to actually think deeply have you ever had uh gone to cvs or dwayne reed and your bill how much you owe them is six dollars and you give them a ten dollar bill in a single and watch the look on their face you watch them void their bowels and panic because you give them eleven dollars on a six dollar bill this is not a mind capable or interested in thoughts and ideas learning no you're talking about the first moment of uh a for a first moment where there's an opportunity to think they are desperate to avoid it no they're just it's and incapable of it i i just it's uh they're they have these same exact experiences i have every single day when i know it's time for me to go on on a run of five miles or six miles or ten miles i'm desperate to avoid it and at the same time i know i have the capacity to do it and i'm deeply fulfilled when i do do it when i do overcome that challenge you are one of the great minds of our generation you are telling me that any of these people can do anything close to the work you do not in artificial intelligence but in in inability to be compassionate towards other people's ideas like understand them enough to be able passion requires a certain baseline of intelligence because you have to perceive other people as being different but of value yeah exactly that's a sophisticated mindset i think i think most people are are capable of it you don't think so no and nor are they interested in it but in that kind of if you don't believe they're capable of it how can anarchy be stable uh if you have a farm there's one farmer and 50 cows it's very stable you're just not you're not asking the cows where to force or where to farm things yeah but the cows aren't intelligent enough to do damage cows cows certainly bulls because they could do a lot of damage they could trample things they could attack you the cows are like how much they weigh like four thousand pounds can you connect the analogy then because like sure you can't expect yeah saying a cow is a cow isn't a slur it's not saying you hate cows cows or even let's say the example i always use with good reason is dogs okay uh i always say to study how human beings operate watch caesar milan because human beings and dogs have co-evolved our minds have both evolved in parallel tracks to communicate with each other dogs are can be vicious dogs for the most part are great wonderful but you can't expect the dog to understand certain concepts it's not an ins and out most people are offended are you saying like a dog if you're a dog person like i am this is actually a huge compliment most dogs are better than most people um but to get the idea that this is something that is basically your peer is nonsensical now of course this sounds arrogant and elitist and so on and so forth and i'm perfectly happy with that but it is very hard to persuade me or anyone that if you walk george carlin has that joke think how smart the average person is then realize 50 of people are dumber than that if you walk around and see who's out there these people are very kind they are of value they they deserve to be treated with respect they deserve to be secure in their person they deserve to feel safe and to have love but the expectation that they should have any sort of semblance of power over me in my life is as nonsensical as asking lassie to be my accountant so but that goes to power that not to uh the ability the capacity to be empathetic compassionate intelligent what if i were to try to prove you wrong that's a good question okay what would what would what would you be impressed by about society well how would i show it to you that's a good question how would you show it to me because i think something has to be falsifiable if you're going to make a claim right so what would it what would it because we both made claims that are a kind of our own like interpretation based on our interaction like when i open twitter everyone seems to say why do you only follow one person who do you follow who's the one person you follow uh stoic emperor i i follow a lot of people i have a script i have a script this is real love it's not ironic love i love watching it and i'm sure you do too i love watching a quality mind at work because when someone has a quality of mind they're often not self-aware i catch this on myself of how it operates and then when other people see it they're like oh my god this is so beautiful because there's such an innocence to it yeah but like when i open twitter i'm energized there's a lot of love on twitter people say like i love to i agree i have you don't think i have a lot of love on twitter my fans pay my rent i mean i don't know your experience of twitter but when i look at your which is a fundamentally different thing i'm saying my experience from the so maybe you can tell me what your experience is like as a human so when i observe your twitter i think i i wouldn't call it love i would call it fun yes and because of that that's a different kind of like love emerges from that because people kind of learn that we're having this is like game night like yes uh you know we're we can talk shit a little bit we can uh and you can you can even like pull in you can make fun of people you can have the crazy uncle come over that is a huge trump supporter somebody who hates trump and you can have a little fun yes i get it's a different kind of thing i i wouldn't be able to um uh be the you're the host of game night yes yes so i wouldn't be able to host that kind of game you night your robots and you're asking what is fun and it just starts sparkling exactly what is fun [Laughter] so the robots in my life that survive are the ones that that don't that like survive that whole programming uh process so they're kind of like they're kind of like the idiot from dostoevsky they're very like simple-minded robots it's just one is moving a can from one table to another yeah that's game night for uh for our kin you know what my quotes is and i i i think about this every day and i mean it with every fiber of my being uh we are born knowing that life is a magical adventure and it takes them years to train us to think otherwise and i think that willy wonka approach it's a very camu approach it's something i believe with every fiber of my being i try to spread that as much as possible i think it is very sad i'm not being sarcastic i this it comes off as condescending i mean it at face value it's very sad how many people are not receptive to that and i think a lot of those functions how they were raised and i i could have very easily with my upbringing have not maintained that perspective and there's a lot of i have a lot of friends in recovery like aa and they have an expression um not my circus not my monkeys right that you can't really take on other people's problems on your own at a certain point they have to do the work themselves because you can only do so much externally and there are a lot of very damaged people out there and there are damaged people who revel in being damaged and they are damaged people who desperately desperately desperately want to be well who desperately want to be happy who desperately want to find joy so if i can be the one and as arrogant as it sounds i'll own it who does give them that fun and to tell them it doesn't have to be like you you thought like it could be it's going to hurt it's gonna suck but it's still a magical adventure and you're gonna be okay because you've been through worse like that if that could be my message i would own it all day long and so what does adventure look like for you because i mean it actually boils down to i still disagree with you i think trolling can can be and very often as destructive for society you yes i want to destroy society that is the goal i want i want to help many people ironically okay ironically yes what do i do with that okay so whatever you want do what that will is the hall of the law um like i just wanna so you're hosting game night and i just wanna play monopoly i wanna play uh what's the risk okay i want to play these games and you're saying lots of games yeah i was trying to think like of a friendlier game but they're all kind of aggressive uh battleship access and allies you know fun stuff but like uh so that's an adventure but you're saying that we want to destroy everything even like the rules of those games are are not like you voluntarily agree to those rules the point is if someone comes in who's not who no one invited to game night and are telling you no when you play monopoly you have to get money when you land in free parking or you don't yeah it's like who are you yeah we're having our own fun and you smell i don't know but there's there's a an aggressive there's an aggression let me let me speak to that which i think you're picking up on uh i had a friend named martha marcia excuse me she ran something called cuddle parties which people laughed at about a lot back in the day and the premise of the cuddle parties everyone got together and cuddled right and it's like ah then you stop to think about and you realize uh physical contact is extremely important and a lot of people don't have it and if this is a mechanism of people getting that it actually is going to have profound positive psychological consequences so after she explained it i'm like okay we laughed at this because it's weird and now that i think about this is wonderful and and i asked her about like like the tough question i go what if guys get turned on and on their website it even has a rule like do not fear the erection right because it's going to be a natural consequence of physical proximity and the point she goes she said this i think about us all the time people will take as much space as you let them it is incumbent on each of us to set our own boundaries we all have to learn when to say no you're making me uncomfortable if someone doesn't respect your right to have your boundary to be uncomfortable this person is not your friend now they can say i don't understand like why is this okay why is that not i let me know you better so i'm respectful of you but if they roll their eyes and they're like get over i'm gonna do what i want this person is not interested in knowing you as a human being okay that is the aggression it is you have to draw those lines i mean but that's a very positive way of phrasing that aggression i'm a very positive person but the trolling there's a destructive thing to it yes that hurts others yes but it's not bad people oh i only troll as a reaction or towards those in power okay so maybe let's talk about trolling a little bit because trolling when it can maybe you can correct me but i've seen it become a game for people that's enjoyable in itself i i'm not i'm not i i disagree with that but that's not a good thing if you are there just to hurt innocent people you are a horrible human being but doesn't trolling too easily become that uh i don't know about easily let me give you an example of the the where trolling came from the original troll was andy kaufman he was on the show taxi he was a stan he was a performance artist not a standard comedian and this is a quintessential example of trolling he had a character um where he was basically like a lounge singer he had these glasses on and just a terrible terrible singer and so on and so forth and he denied it was him and he came out and i'm blanking on the guy's name i can't believe it tony clifton yeah he came out in the audience and he goes you know my wife died a few years ago every time i look at my daughter sarah's eyes i could see my wife sarah come out here let's do a duet and sarah's like 11. sits on his lap they start singing duet her voice cracks he smacks her across the face what the hell are you doing you're making ass in front of these people they're they're she starts crying the audience is booing and goes don't bore you're just going to make her cry more now it ends this wasn't his daughter it wasn't even a child was an actress this was all set up he's exploiting their love of children in order to force them to be performers that is trolling no one is actually getting hurt it's a humorous the twisted exchange if you go online looking for weak people and you are there to denigrate them just for them being weak or in some way inferior to you that is the wrong approach i am best on the counter punch a lot of times people come to me and they'll be like i hope you die you're ugly you're disgusting and there's this great quote from billy idol which i'm going to mangle where he sums in the effect of i love it when people are rude to me then i can stop pretending to be nice then you start fights now it's a chance for me to finish it and make an example of this person but that's very very different from i'm gonna go around and humiliate people for the sake of doing it in my view and i can see how one would lead to the other yeah but that's my fundamental concern with it so i my dream is to put use technology create platforms that uh increase the amount of love in the world and to me trolling is doing the opposite so like andy kaufman is brilliant so i love obviously it sounds like i'm a robot saying i love humor okay humor is good one one zero one one one one but but like it's i just see like 4chan i see that you can often see that humor quickly turn yeah because what happens is a lot of low status people this is their one mechanism through sadism uh to feel empowered and then they can hide behind well i'm just joking as this that people do which is like they'll say like the shittiest thing right and then they feel lol after like as if i don't i don't even know like what is happening in the dark mind of yours because they are feeling powerless in their lives right and they see someone who they perceive as higher status or more powerful than them or even not appear and they through their words cause a reaction in this person so they feel like they are in a very literal sense making a difference on earth and they matter in a very dark way uh it's it's disturbing this is not i mean it's unfortunate that that term trolling is used for that as opposed to what andy kaufman does as opposed to what i do um it's it really is uh a sinister thing and it's something i'm not at all a fan of or how do we how do we fight that so like a neighboring concept of that is conspiracy theories which is i don't think they're neighboring at all well let me let me give myself a naive perspective maybe you can educate me on this from my perspective conspiracy theories are these constructs of ideas that go deeper and deeper and deeper into creating worlds where there's powerful pedophiles controlling things like these uh very sophisticated models of the world that you know in part might be true but in large part i would say are are figments of imagination that become really useful constructs and self-reinforcing self-reinforcing for then feeding like empowering the trolls to attack the powerful the conventionally powerful i i don't think that that's a function conspiracy theories now let's talk about conspiracy theories because one of my quotes is you take one red pill not the whole bottle this concept that everything in life is at the function of a small cadre of individuals would be for many people reassuring because as bad as it looks you know they whoever they are it's usually the jews aren't going to let it get that bad that they will pull back or the the black pill is that they are intentionally trying to destroy everything and there's nothing we can do and we're doomed and there's an amazing book by arthur herman called the idea of decline western history i it's one of my top 10 books where he goes through every 20 years how there's a different population that say it's the end of the world here's the proof and very often the proof is something that is kind of self-fulfilling where there's no it's not falsifiable and we both have to think of ways to falsify our claims from earlier yeah so it is a big danger it's a big danger online because very quickly if someone who you thought was good but now is bad on one aspect well they're controlled opposition or they've been uh taken over or they've been kind of uh appropriated by the bad people whoever those bad people would be um i don't know that i have a good answer for this i don't think it's as pervasive as people think the number of people who believe conspiracy theory right the i mean and also conspiracy theory is a term used to dismiss ideas that have some currency the constitutional convention was a conspiracy uh the founding fathers got together secretly under water secrecy in philadelphia said we're throwing out the articles of confederation we're making new government right yeah yeah and luther martin left and he told everyone this is a conspiracy and they're like yeah whatever luther morgan so and jeffrey epstein was a conspiracy harvey weinstein was a conspiracy bill cosby conspiracy they all knew they didn't care uh communist infiltration in america there's a great book by eugene lyons called the red decade they all knew they every atrocity that uh was done under stalinism was excused in the west and if you didn't believe it oh you've got this crazy anti-russian conspiracy so it's a term that is weaponized uh in a negative sense but that does not all imply that it does not have very negative real life consequences because it's kind of a cult of one right like i'm at home on my computer i bang to this ideology anyone who doesn't agree with me they're blind they're oblivious mom and dad my friends you don't get it we were warned about people like you and i think there's a very heavy correlation and i'm not a psychiatrist of course between that and certain types of mild melt illness like uh you know some kind of paranoid schizophrenia things like that because after a certain point if everything is a function this conspiracy it's it's there's no randomness or beauty in life yeah i mean i don't know if you can say anything interesting about it in the way of advice of how to take a step into conspiracy theory world without completely going like diving deep because it seems like that's what happens people can't look at jeffrey epstein i can tell you what the device i'd have seriously and rigorously without going because you can look at jeffrey epstein and say there's a deeper thing you can always go deeper right it's like jeffrey epstein was just the tool of uh the lizard people and the lizard people are well they say satanists in this case and somehow recently very popular pedophiles somehow always involved i'm not understanding any of that i legitimately i say this both humorously and seriously i need to look into it and i guess the bigger question i'm asking how does a serious human being uh somebody with a position at a respectable university like look at a conspiracy theory and look into it when i look at somebody like jeffrey epstein who had a role at mit yeah oh yeah and i and i think i'm not happy personally i didn't i wasn't there when jeffrey epstein was there i'm not happy with the behavior of people now about jeffrey epstein about the bureaucracy and the everybody's trying to keep quiet hoping it blows over without really looking into any like looking in a deep philosophical way of like how do we let this human being be among us can i give you a better example sure that that is kind of conspiratorial the speaker of the house the longest serving republican speaker of the house dennis hastert was a pedophile he went to jail the democrats don't throw this in the republicans faces every five minutes not even democratic activists i find that very very odd and not what i would predict now i'm not saying there's some kind of conspiracy but when it comes to things like sexual predation which is something that i'm very very concerned about i'm an uncle now my sister just had her second kid recently he's adorable um it's something that i don't understand if it feels as if there's a lot of people who want this to all go away now i think it's also because we don't have the vocabulary and framework to discuss it because when you start talking about things like children these kind of issues we want to believe it's all crap because it's for those of us who aren't in this kind of mindset the idea that this happens to kids and happens frequently is something so horrible yeah that we it's just like i don't even want to hear it and that does these children and adult survivors an enormous disservice so i don't know that i have any particular insight on this but see like how do you i mean the catholic church again there's all these topics that public school teachers are far more proportionally uh better as the children of the catholic church i mean i don't know what i you're right you're right um perhaps some uh i've been you know reading a lot about stalin and hitler yeah somehow it's more comforting yeah like to be here and then and then and then the atrocities that are happening now it's a little bit more difficult because there was a new york times article interrupted where they were had a people tracking down child pornography and i think the article said they didn't have enough people just to cover the videotapes of infants being raped and we can even wrap our heads around like reading lolita like okay she's 14 12. okay it's still a female an infant it's it's something that again like with the stalin example we sat down here for a hundred years we would never think of something like this think of in a sexual context it makes no sense yeah um so and the fact that this is international okay we eliminated completely in america well then they're gonna go find this there's infants all over the world there's video cameras over the world so then it has to become a conspiracy because i someone has to film it i'm filming it you're buying it your kid it is literally a conspiratorial not in the sense of like a mafia conspiracy or some government illuminati but there is our networks designed to produce this product see but like what i'm i'm trying to do now i mean part of the one of the nice things with like a podcast and other things i'm involved with is i'm removing myself from having any kind of boss so i can do whatever yes oh it's so it's so wonderful that just happened to me it's it's the most wonderful thing ever so i could do i can actually in moderation consider like look into stuff careful though i was going to write a book about this and people pointed out you sure want to do this research because if you start googling around for this kind of stuff it's on your computer oh in that sense yeah i'm more concerned about you know it's the nietzsche thing looking into the abyss like you want to be very yeah i believe i can do this kind of thing in moderation without slipping oh yes into the depths of course i think that's that's intelligence that's uh like i recently quote unquote looked into like the ufo community the um extraterrestrial whatever community i think it always frustrated me that the scientific community like rolled their eyes at all the ufo sightings all that kind of stuff even though there could be fascinating beautiful physical fun like first of all there could be like lightning or the ball lightning right that's at the very basic level is a fascinating thing and also it could be something like i mean i i don't know but this could be something interesting like worth looking into my grandfather was an air traffic controller back in the soviet union and he said we saw this stuff all the time these are planes that were not moving or whatever things that were not moving according to anything we knew about so it's absolutely real he's not some jerk with an iphone in his backyard this is a a military professional who understood technology who knew where the secret bases were so if he's telling me it's something doesn't mean it's martians but he's telling me there's something there and there are many examples of of these like military people these aren't some laymen who sees a story they're legit people yeah and and so it's you you can dismiss when you're talking about professionals who are around aircraft all the time who are familiar with aircraft at the highest levels and they're seeing things that they can't explain it's they're clearly not stupid and they're clearly not under form so might there's different ways to dismiss ideas for example i i'm uh you were saying that trolling is a good mechanism i'm against that but i'm not dismissing it by like rolling my eyes i'm considering legitimately that you're way smarter than me and you understand the world better than me like i'm allow myself to consider that possibility and thinking about it like maybe that's true like seriously considering it that's what that's i feel the way people should approach intelligent people serious quote-unquote people scientists should approach conspiracy theories like look at it carefully you know is first of all is it possible that the earth is flat it's not trivial to show that the earth is not flat it's a very good exercise you should go through it yes but once you go through it you realize that uh based on a lot of data and a lot of evidence and there's a lot of different experiments you could do yourself actually to show that the earth is not flat okay the same kind of process can be taken for a lot of different conspiracy theories and it's helpful and without slipping into the depths of of lizard people running everything that's where i i've now listened to two episodes of um of alex jones's show because he goes crazy deep into um into different kind of world views that i was not familiar with right and i don't know what to make of it i mean the reason i've been listening to it is because um there's been a lot of discussions about platforming of different people and i've been thinking about what is censorship mean i've been thinking about it whether because joe rogan uh said he's gonna have alex on again and then i enjoyed it as a fan just the entertainment of it but then i actually listened to alex and i was thinking is this human being dangerous for the world like is the ideas he's saying dangerous for the world i'm more concerned with the russian conspiracy that we had for three years and the claim that our election was not legitimate and that everyone in the trump white house is a stooge of putin uh and the people who said this had no consequences for this alex jones doesn't have the respect that they do uh these are both areas of concern for me but he he might if there's if he's given more platforms so like the the the the people who've and i'd be curious if i'm also a little bit i don't know what to think about the idea that russians hacked the election the it seems too easily accepted in the mainstream media hillary clinton said that how they did it was they had ads on the dark web now you and i both know what the dark web is so the possibility of ads in the dark web having an influence from a proportional influence on the election is literally zero perhaps i should look into it more carefully but i've found very little good data on exactly what did the russians do to hack elections like like technically speaking what are we talking about here like as opposed to these kind of weird like the best thing there's a couple books and like reporting on like farms control farms troll farms but let's see the data like how many exactly what are we talking about like what were they doing relative not just like some anecdotal discussions of but like relative to the bigger the size of facebook like if there's a few people several hundred say the posting different political things on facebook relative to the full size of facebook let's look at the full size like right you're thinking like a scientist the actual impact like the because it's fascinating the social dynamics of viral information of videos when when uh donald trump retweets something i think that's understudied the effect of that uh like he retweeted a clip with joe rogan on uh with and mike tyson where mike tyson says that he finds fighting orgasmic i don't understand that but it'd be fascinating to think like what is the ripple effect on the social uh dynamic of our society from retweeting a clip about mike ty what's your favorite um um trump tweet i i tuned the model a long time ago unfortunately i have um it's the this goes to the you and i have a different relationship with donald trump you appreciate the art form of trolling non-sexual non-sexual yeah so i i tend to prefer uh bill clinton he's more my type no i'm just kidding uh i don't know you don't like that consent stuff no because no uh no you appreciate the art form of trolling and and uh donald trump is is uh a a master he's the da vinci of trolling so i tend to think that trolling is ultimately destructive for society and then donald trump takes nothing seriously he's playing a game he's making a game out of everything takes a lot of things seriously i think he's very committed to international peace i say i i shouldn't speak so strongly i think i think it takes actually yes a lot of things seriously i meant on twitter and the game of politics yeah he is um [Music] he only takes irreverently yeah yeah and um i appreciate it i just would like to focus on like genuine real expressions of humanity especially positive well this is my love this is my favorite tweet my fans got it laser etched and put in a block of lucite for me and he said every time i speak of the losers and haters i do so with great affection they cannot help the fact that they were born fucked up that's an actual trump tweet it's my favorite one and that's kind of nice that's love that's love that's kind of nice that i mean exclamation point even um i broke legs what is love yeah the sparks are flying but uh i have to kind of analyze that from like a literary perspective but it seems like there's love in there like a little bit like it's a little bit light-hearted because he's saying even when i'm going after them don't take it so seriously yeah that's that's nice it is nice acknowledging the game of it yes that's nice uh he's not always something he's very very vicious yeah very vicious he's done things that i i can tell you about that i'm like this is a bad person what do you think about one of the okay listen i'm not i for people listening i do not have trump derangement syndrome i'm i don't i see i try to look for the good and the bad in everybody one thing perhaps it's irrational but perhaps because i've been reading history i the one triggering thing for me is the delaying of elections i believe in elections and [Music] this is this is the part that you probably disagree with but i you know i believe in the value of people voting and i just seen too many dictators the the place where they finally the big switch happens when you question the legitimacy of elections who's been questioning the legitimacy of elections for the last three years i've only heard donald trump do it last like year but the last three years you're saying somebody else you don't think not my president illegitimate we're not going to normalize him as president russia hacked this election impeached you're not a real president you don't think that's questioning legitimacy of 2016. no it's a good uh i haven't been paying attention enough but i would i would imagine that argument has been that i haven't actually heard too many people but i imagine that's been a popular oh very much yeah okay i but nevertheless that's a part that didn't uh that's not a statement that gained power enough to say that um barack obama will keep being president or hillary clinton should be president newsweek had that article how hillary clinton could still be president newsweek no but she's not that's what i'm saying my worry isn't my worry isn't uh saying that the election was illegitimate and people whining and mass scale and then the fox news or cnn reporting for years or books being written for years my worry is legitimately martial law a person's ma stays president so here's the issue like there's a there's a shift that i have not i i i did a book on north korea i'm not someone who thinks dictatorship should be taken lightly i'm not someone who thinks it can't happen here uh i i think a lot of times people are desperate for dictatorship so i am with you and i think this is something if you're going to hand wave it away everyone else hand waved it away hitler's never going to be chancellor he's a lunatic he's a joke he's a joke that he they couldn't find a publisher from mineconf in english because this is a guy from some random minor party in germany spouting nonsense who's going to read this crap you know so i i completely agree with you uh you don't think we're there my point is donald trump this year had every uh pathway open to him to declare martial law the cities were being burnt down he could have very easily sent in the tanks uh and people would have been applauding him from his side he feels so good right now but am i wrong though no i what he did he tweeted out to mayor wheeler of portland he said call me we will we will solve this in minutes but you have to call and he sat in his hands and they said oh it's his fault the city is burning down he's not doing anything and he goes i'm not doing anything until you ask me to do it so i think that is even if you think he's an aspiring dictator that is at least a sign that there is some restraint on his aspirations can i just take that in as a beautiful um like moment of hope so i'm i'm gonna remember this ted cruz beautiful ted i'm gonna i'm gonna remember that i mean uh i i should say that perhaps i'm irrationally this is the one moment where i feel myself being a little i i don't like it i think there's an asymmetry because it's kind of like okay either i if i leave the house it's like russian roulette yeah maybe it's like a one and six shot i'm pulling the trigger i'm killing myself but that's one in six that's not and and the consequences are so dire that a little paranoia would go a long way there's something that you can't go back yeah you it's an asymmetry yeah and the the thing is the thing that makes donald trump new to me and again i'm a little naive in these things but he surprised me in how many ways he just didn't play by the rules yeah and he's made me a little ant in this ant colony think like well do you have to play by the rules at all right like why are we having elections why just say like it's coronavirus time like it's it's uh not healthy to have elections like we shouldn't be like i could if i put my dictator hat on nancy pelosi said that joe biden shouldn't debate yeah uh did she yes she says she shouldn't dignify trump with the debate he's the president he could be the worst president on earth evil despicable monster i'll take that as an argument so she's playing politics but she's i don't think that's playing politics i think when there's a certain point where things get and when things get uh when you start attacking institutions for the the emergencies at the moment and acting arbitrarily that is when things are the slippery slope yeah so you're saying debates is one of the institutions like that's one of the traditions to have the debates i think the debates are extremely important uh and now i don't think that someone's a good debater is going to make a good president i mean that's that's a big problem but you're just saying this is attacking just yet another tradition yet another you know like how if you're dating if you're married to someone and someone throws out the word divorce you can't unring that bell you threw it out there yeah i'm saying you don't throw things out like that unless you really are ready to go down this road and i think that is there's nothing in the constitution about debates we've only had them since 1980 but still i think they are extremely important it's also a great chance for joe biden to tell him to his face you're full of crap here's what you did here's what you did here's what you did it's so fascinating that you're both you acknowledge that and you you also see the value of tearing down the entire thing so you're both worried about no debates or at least in your voice in your tone there's a great quote by chesterton i'm not a fan of him at all but he says before you tear down a fence make sure you know why they put it up first so i am for tearing it all down but there's something called a controlled demolition like building seven um or there's allegedly we knew we were in tel aviv um and hashtag building seven we knew we were intelligent wow you're faster than me you're you're operating in a different level i need to upgrade my operating system i told you when it was 95. yeah um building seven if you're gonna uh it's like indiana jones right if you're gonna tear pull something away make sure you have something in place first as opposed to just breaking it and then just especially in politics it because it escalates and when things escalate without any kind of response it it can go in a very bad that's when napoleon comes in so what's your prediction about the the biden trump debates again i just have this weird maybe we'll return to maybe not in this how do we put more love into the world and like one of the things that worries me about the debates is it'll be um it'll be the the world's greatest troll against the the grandpa and the porch who grabbed his pants yeah yeah and it'll it will not put more love into the world it it will it will create more mockery like uh joe biden did a great job against paul ryan in 2012. paul ryan was no lightweight no one thought he was a lightweight joe biden handed sarah pale in her ass in 2008 which isn't as easy to do as you think because she's a female so you're going to come off as bullying that's something you have to worry about so the guy isn't um i think he is in the stages of like cognitive decline um so i think it's going to be interesting uh i want it to be um like mike tyson beating up a child because it'll be a source of amusement to me um but i don't know how it's gonna go because it's possible that joe biden will be the mike tyson yes because in his last debate with bernie he was perfectly fine and again the guy was a center for decades and i don't think anyone if you looked at joe biden in 2010 would have thought this guy is going to be have his ass handed him a debate you wouldn't think that at all so i don't know who we're going to see plus he's got a lot of room to attack trump so i'm sure he's gonna come strapped and ready and he's gonna have his talking points and watch trump dance try to tap dance around him and if he's in a position i know the rules of the debate are to actually nail him to the wall it might actually i'm sure he's gonna have a lot of lines too the problem is trump is the master counter puncher so he like when hillary's you know had her line she's like well it's a good thing that donald trump isn't in charge of our legal system he's like yeah he'd be in jail it's like it's like oh like you lady you set him up that's painful to watch yeah those those debates i mean there's something uh i think it's actually analogous um i've come to think of it uh your conversation with me right now some sleepy joe i'm playing the role of sleepy joe i actually connect to uh joe because they're also incontinent there's like these weird pauses i do the same i do the same thing it annoys the shit out of me that like uh in mid-sentence i'll start saying a different thing and take a tangent i'm not as slow and drunk as i sound always i swear i'm more intelligent underneath lower but less drunk exactly but the result one of those is true but not both yeah and and and trump just like you are a master counter puncher so it's going to be messy here's the other thing in all seriousness chris wallace is the moderator chris wallace has interviewed trump several times and he was a tough tough questioner so i don't think he's going to come in there with softball questions i think he's really going to try to nail trump down which is tough to do i like him a lot yeah he's rea and he's like mr president sir that's not accurate blah blah he's done it and trump gets very frustrated because he doesn't just let him say whatever he wants and he he hits him with the follow-up he's he's uh i guess he's on fox news and he i listen to his sunday program uh every once in a while uh he gives me hope that i don't know there's something in the voice like that he's not bought he's i i there's no question he's going to take this seriously which i think is the best you could hope for in a moderator like it feels like there's people that might actually take the mainstream media into a place that's going to be better in the future and like we need people like him you mean like rob spear what do you mean like taking the mainstream media to a better future like bring out the guillotines okay see you you put your anarchist hat back on i don't think robster is much of an anarchist but yeah i get what you're saying yeah you don't think there should be a centralized place for news there isn't now well that's what mainstream media is supposed to represent broken well it's not whatever uh what would he call that a place where people traditionally said was the like the legitimate source of truth no that's what the media was supposed to represent no i said i that's their that's their big branding uh accomplishment it's okay that was never true yeah because if we here's what happens we remember the spanish-american war remember the maine we have to take cuba yellow journalism willie randolph first right then record scratch and then we're all objective like when did this transition happen according to people when you were saying that the kaiser is uh the worst human being on earth when you were downplaying uh stalin and down playing hitler's atrocities when you were saying we had to be in vietnam at what point wmds when did it change it never changed you just are better con artists at a certain point and now the mask is dropping yeah but don't you think there's uh at its best like investigative journalism can uncover truth in a way that um that like reddit uh subreddits can't you know read it sure i agree at its best absolutely that's not even dispute but like don't you think uh like fake it until you make it is the right way to do it meaning like the take the news no no no i meant the new saying like we dream of doing of arriving at the truth and reporting the truth they don't say that cnn had an advertisement that said this is an apple we only report facts that's a lie no that's now and now it's clear things have changed and they haven't changed you're just more you're more aware of chicanery but okay so the how many people died in iraq because saddam hussein was about to launch wmds who had consequences for this no one this isn't a minor thing this is lots of dead people yeah and also i mean dead people it's horrible but also the money which has like we said economic effects marian williamson i think it was it was had trump both of them had the great point that goes that's like a trillion dollars how many schools would that build how many roads did that build even here why are we building hospitals in iraq that we destroyed when we could building hospitals here it makes no sense it's horrifying so who's responsible for that like who um alex jones now meant for well uh so who's responsible for arriving at the truth of that of speaking to the money spent i think this is wars in iraq this is one of the great things about social media twitter you have faith in twitter not not specifically twitter but yeah social media as a whole what anyone could be here's a great another great example before if you were talking about police brutality or these riots you would have to perceive it in the way it was framed and presented to nicholas sandman is another example uh brianna taylor all these things well you're not footage of her you would have to perceive in the way that it's edited and presented to you by the corporate press now everyone is a video who has video camera everyone has their perspective and it's very useful when these incidents happen where you could see the same incident from several angles and you don't need don lemon or chris wallace to tell me what this means i can see with my own eyes yeah i've been very pleasantly surprised about the power see like people the mob again gets in the way they get emotional and they destroy like the the ability for people to reason but you're right that truth is unobstructed on social media like if you're if you're careful and patient you can see the truth yeah like for example data on coven some of the best sources are doctors like if you want to know the truth about the coronavirus of what's happening is uh there's follow people on twitter yeah there's certain people there yes like sourcing for me versus the cdc and the wa show it's that's that's fast i mean it's well it's kind of anarchy right it's yes it is it's anarchy yes i mean well there's some censorship and all that kind of stuff you have censorship under anarchy in the sense that you're talking about like people be kicked off on twitter that's a drawing somebody okay so i mean it's a private company private company most people wouldn't say twitter's working but they that's probably because they take for granted how well it's working and they're just complaining about the small part of it that's broken right okay another question about don't you feel better no by the way i mean i had a personal gripe with the situation about the um not a personal gripe but i felt overly emotional about um the possibility that there will be some of donald trump messing with the election process but you made me feel better like saying like he if he had a bunch of opportunities to um to do what like to do what i would have done if i was a dictator i would um the first time those rides over george floyd i would instituted um martial law do you know what i remember very vividly is after 9 11 and everyone was waiting for george bush to give his speech and he had 98 approval rating and i remember very vividly because if he had said we're suspending the constitution everyone had cheered for him like he couldn't get enough support at that time and he didn't do it and i can't say anything really good about george w bush i'm not a fan of his to say the least so i think you and i and you know other people who are familiar with you know uh totalitarian regimes to some extent from our ancestry or whatever from research should always be the ones freaking out and warning but we should also be aware of we got a ways to go before it's hitler and thankfully uh there are a lot of dominoes that have to fall into place before hitler it's like the game secret hitler it's a board game before hitler becomes hitler like it's not e especially in america there's lots of things that have to happen before you really get to that point i mean fdr was for all intensive purposes of dictator but even then the worst you could say and this is not something that you take lightly was internment of japanese citizens but they weren't murdered uh they weren't you know uh you know under lock and key in the sense of like in cells so things could have gotten a lot worse for him we have to i mean hitler is such a horrible person to bring up because mussolini you know yeah mussolini is better because hitler is so closely connected to the atrocities of the holocaust right there's all the stuff that led up to the war and the war itself say that there was no uh holocaust hitler will probably be viewed differently i should yes i should think so well i mean but you think that's a very controversial stance you think hitler viewed differently if it wasn't for the holocaust well i mean but it's a funny thing that the the the i would say the death of how many 40 50 million i mean i don't know how you calculate it as is not seen as as bad as the 6 million oh yeah because of mountain and stalin yeah yeah and it but it's interesting uh working on it you're working on yeah the next book i'm talking reminding what's good i'm i'm glad a good writer is because i'm not reminded my last book the new right you know i had to deal with some like the nazis and one of the points they make is how come everyone knows about the holocaust but no one knows about the holodomor and they're right we should know about this because it is a great example of both how the western media were depraved but also what human beings are capable of and those scars are still you know many americans think russia and ukraine are the same thing you know that like oh trump's in bed with ukrainians trump's about the russians they think it's the same thing is for us it's complete lunacy but this is the kind of thing where pol pot is another example uh where people have no clue of what has been done to their fellow man on the face of this earth and they should know how much of that do you lay at the hands of communism how much are you with like a jordan pearson who has as intricately connecting the atrocities like like you're saying 1930s ukraine where people were starved um i recently said my grandmother recently passed away and she she looked she survived that as like as a kid which is it's fat those people i mean just they're tough they're tough like that whole region is tough because they survived that and then right after the occupation of nazis yeah of germans um how much do you lay that at communism as an ideology versus um stalin the man uh i think you know lenin was building concentration camps you know while he was around in slave labor um i i don't i think it's clearly both there are certain variants of communism that were far like khrushchev you know and gorbachev uh the reason the soviet union fell apart and this is kind of i'm going to spoil the end of the book there's an amazing book called revolution 1989 it's like the most beautiful book i've ever read by victor sebastian he's a hungarian author and basically what happens in 1989 poland has their elections and then then in 1990 they kind of let in the labor people into the government and people start crossing borders you know in the eastern bloc and you had hanukkah from eastern germany and uh chances from romania colin gorbachev because those are the two toughest ones by communist standards they go they're they're just escaping we're gonna we're gonna lose everything you gotta send in the tanks like you did in hungary like you did in czech republic surviving 68 and gorbachev goes i'm not sending the tanks and they go dude if you don't sing in the tanks it's all done and he goes nope i'm not that kind of guy and they were right i mean they uh coaches was personally shot with his wife up against the wall hanukkah i forget what happened to him but it they all self-liberated my friend who was born in czech czechoslovakia his mom was pregnant you know under communism and she never even imagined he'd be free and he was born under free uh and they were all looking around all these countries that self-liberated because they're like this is a trick right they're just they're trying to figure out who's like not good so that they can arrest us on mass and they didn't so although even within communism there are bad guys and better guys but we talked about anarchy we talk about democracy do you see like there's democratic socialism conversations going on in the popular culture socialism is seen as like evil or for some people great sure what like what are your thoughts about is in a political ideology evil so you're on the evil side yes fundamentally yes what what what is it you know what yeah what makes it evil what's like structurally if you were to try to analyze like sure this i say three ways morally no person has the right to tell another person how to live their life um economically it's not possible to make calculations under socialism it's only the price the prices that are information that tells me oh this is we need to produce more of this we need to produce less of this without prices being able to adjust and give information to producers and and consumers you have no way of being able to produce uh effectively efficiently and also it is uh it turns people against each other when you force people to interact when you force them into relationships when you force them into jobs and you don't give them any choice when there's a monopoly uh the consequence of monopoly everyone's familiar with ostensibly under capitalism but somehow when it's a government monopoly all those economic principles don't work doesn't make any sense but there's force in democracy too it's just you're saying there's a there's a bit more force in uh in socialism yeah but that's interesting that you say that there's not enough information i mean that's ultimately you need to have really good data yes to achieve the goals of the system even even if there's no corruption right you just need to have the information right which you can't and capitalism provides you um like really strong real-time real-time information that um and if like capitalism at its best and cleanest which is like perfect information is available there's no manipulation of information that's what you know that's one of the problems okay can we talk about some candidates the ones we got and possible alternatives so one question i have is why do we have within this system why do we have the candidates we have is it seems um maybe you can correct me highly unsatisfactory like the like is anyone actually excited about our current candidates i'm kind of excited because no matter who wins the elections can be hilarious so that is something that i'm excited about from uh from a human perspective yeah is that what the whole system is uh so that's the one theory of the case is the entire thing is optimized for viewership yeah and uh excitement by definitions of like the reality show kind of excitement i think it is if you look at what happened with brett kavanaugh this is not a career that would draw people who are you might say quality because no matter who they are there would be a huge incentive from the other team to denigrate them and humiliate them in the worst possible ways because as the two teams lose their legitimacy among gen pop it's going to get harder and harder for them to maintain any kind of claims to authority which is something i like but which does kind of play out in you know certain nefarious ways so people the best of the best are not going to want to be politicians yeah because like i could have a job or have a job interview and i'm running yahoo or whatever or i could for 18 months have to eat you know corn dogs looking like i'm going down on someone and shake hands and have all this my family and on social media daily called the worst things for what and then i'm still not guaranteed the position but the flip side of that like from my perspective is the competition is weak meaning like you need a certain a minimum amount of eloquence clearly that i don't uh the bar which i did not pass i don't think either of them would be considered particularly eloquent biden or trump no i know but that's what i'm saying the competition like if if you were um wanted to be become a politician if you wanted to run for president the opportunity is there like if you were at all competent like if you had so like andrew yang is an example of somebody who has a bunch of ideas is somewhat uh eloquent like young energetic it feels like there should be thousands of andrew yangs like that would enter the domain and he went nowhere well he j well i i wouldn't say he went nowhere he generated quite a bit of excitement he just didn't go very far that's okay you don't have to run for president to generate excitement with your ideas you could be a podcast host i'm not even joking that's right that's right that's right and he's both andrew yang oh he's a podcast yeah he has a podcast called yang speaks no okay cool [Laughter] oh wow the music of the way you said yeah cool is the way my mom talks to me when i tell her with something exciting going on in my life oh that's nice honey oh you made a robot that's cool that makes coffee oh you're still single though aren't you ah i wonder why i wonder why make yourself a robot wife give me some robot grandchildren um okay but first of all okay let me ask you about andrew yanks he represents fresh energy you don't find him fresh or energetic you know like is there any candidate you wish was um in the mix that was in the mix you wish was one of the last two remaining yeah people like marion williamson i thought was great uh tulsi i thought was great amy klobuchar got a bad rap i think she held her own um smart she wasn't particularly funny and that's okay i think she was not threatening to a lot of people what did you like about them i guess it's named all women that's interesting it wasn't even intentional um tulsi i like that she was aggressive has a good resume and is not um staying the course for the establishment marion williamson i like because she comes from a place from what it seems of genuine compassion maybe she's a sociopath i don't know i read her book and it actually affected me profoundly because it's very rare when you read a book and there's even that one idea that blows your mind and that you kind of think about all the time and there was one of that such idea in her book about um she was teaching something called the course in miracles in hollywood i think she still teaches it and this was during the 80s the high the aids crisis and all these young men in the prime of their life were dropping like flies and she's trying to give him hope well good luck they're dying no one cares and they're like you can't tell us that they're going to cure this like you're that's a lie and she goes what if i told you they're not going to cure it what if i told you it's going to be to like diabetes they cut off your foot and you're going to go blind would that be something that you can hope for and when you put it like that it's like yeah like if you're talking to him like a homeless junkie and you're like you could be a doctor you're a lawyer or a lawyer like cool story like you could have a studio apartment with a terrible roommate and a shitty job but when you're on the street you know cooking need breakfast in a teaspoon and you hear that you're like wait would that really be so bad is that really so much worse than this no and it becomes something so when she put it in those terms i'm like wow this woman that really did a number on me in terms of teaching people how to be hopeful small steps but it's but it's also then it becomes less of i need a miracle to be like oh this is really magical yeah it's and it's absurd to think it's impossible what about what's your take on unity 2020 that brett weinstein uh pushed forward it i i it was doa uh he couldn't even stand up to twitter dead on the rival in rival he couldn't even stand up to twitter let alone or to facebook they got blocked let alone hugely problematic by the way that twitter would block that not at all um i don't know why they blocked it but i believe i don't know problematic means that's a word that does a lot of work uh that people wanted to do conceptually um the idea that like unity is like taking the rejects from each party and we're gonna like have something that no one likes and therefore it's gonna be a compromise is absurd the last time we had this kind of unity ticket was the civil war when you had andrew johnson from the democrats and lincoln from the republicans this was not something that ended well uh particularly nicely for both halves of the country so that that's the way you see it as like the way i saw i i guess i haven't looked carefully at it i haven't either to be fair yeah the way i saw it is emphasizing centrists which is uh how's celsius centrist tulsa was involved yes he's trying to push tulsi and like jesse ventura or something oh so oh okay i don't know i don't know the specific as a scientist you also know centrism is not a coherent term in politics but see now you're like uh uh what is it pleading to authority no i'm treating my ego no no i'm pleading to how you approach data if someone is saying the mean is accurate that only mean i mean the mean could be anywhere it's a function of what's around it doesn't mean it's true i don't even know what uh census is supposed to mean but what it means to me there's no idea essentia centrist there's more of a center right or center left to me what that means is somebody who is a liberal or conservative but is um open-minded and uh empathetic to the other side joe biden had the crime bill joe biden voted for republican supreme court justices joe biden voted for a balanced budget joe biden voted for bush's war he and i'm sure probably haven't looked this up the patriot act yeah if you want a centrist you have joe biden yeah okay he's worked very well with the republicans that argument could be made of course they'll everybody will always uh resist that argument you it's undeniable in fact during the campaign some uh um uh activists started yelling at him at a town hall not yelling just saying hey we need open borders joe biden says i'm not for open borders go vote for trump and literally turned his back on the man and this is during the primaries where it would behoove you to try to appeal to the base and of course you can probably also make the argument that donald trump is center right if not center left well i mean he's he's very uh unique as a personality right but if you look at his record and his first name is rhetoric you can say is not centrist at all but in terms of how he governs the budgeting i mean has been very moderate it certainly hasn't been like draconian budget cuts uh the supreme court you could say okay he's hard right immigration you could say in certain capacities he's hard right but in terms of pro-life what has he done there in terms of you know so it's in many other aspects he's been very much this kind of me too uh republican but certainly the rhetoric it's very hard to make in the case that he's a centrist so you don't like uh is there any other idea you find compelling like you what i like about unity 2020 is just an idea for uh a different way for like a different party a different path forward so ideas just like anarchy is an interesting idea that's that leads to discourse at least i don't think it's interesting at all and here's why i think it's interesting uh sweden has eight parties in its parliament iceland population's like 150 000 they've got nine i think it was czech republic has nine britain has five um so the claim that two uh parties is the sensorious of speech but three oh now all of a sudden it makes no sense doesn't import to the data number one number two is donald trump demonstrated that you can be basically a third-party candidate seize the machinery of a existing party and appropriate to your own hands as bernie sanders almost did bernie sanders has never been a democrat uh major credit to him for that's not easy to be elected as senator as an independent he's done it repeatedly so these are two examples of ossified elites uh right for the picking so to have a third party makes uh no real sense speaking of which party you talk about quite a bit uh and uh let's look this is a personal challenge to you let me bring up the libertarian party yeah and the personal challenge is to go five minutes without mocking them okay in discussing uh and discussing this idea so first of all what i'm being troubled there was an episode where chandler had to not make fun of people like can you go one day chandler and phoebe starts telling him about like this ufo she saw and it's like that's very interesting nice for you this is exactly that okay so a true master would be able to play within the game within the constraints so um no i i'm pretty sure you'll still mock them but no no i'll stick to the rules five minutes easy so first of all speaking broadly about libertarianism can you speak to that how you feel about it and then also to the libertarian party which is the implementation of it in our current system so i think libertarianism is a great idea and i think there's many libertarian ideas that have become much more mainstream which i'm very very happy about i remember there was an article in either new york or new yorker magazine in the early 90s where they talked about the cato institute which is a libertarian think tank and they referred to the fact that keda was against war and against like regulation with a wacky consistency because they didn't know how to reconcile these two things i remember what the two things were but i remember that expression wacky consistency and it wasn't eve we were all taught and this is very much before the internet that there's two tribes and if you're pro-life you have to hate gays and if you're for socialized medicine that also means you have to be for uh um you know free speech it was just this very and like there's a whole menu and you got to sign into all of them and that menu is terrible they hate america they want to destroy it oh my god those are horrible evil this is the menu you want and the libertarian party to some extent and just libertarian as a whole said you know you can do the chinese buffet and take a little from columbia live from column b and have an ideology that is coherent and consistent analogy ideology of peace and non-aggression and things like that the libertarian party takes its model from like the early progressive and populist parties from the early 20th century which were not very effective in terms of getting people elected but were extremely effective in terms of getting the two major parties to appropriate and adopt their ideas and implement them and in britain as well the liberal party got destroyed and became taken over by labor as the uh alternative party to the tories um and have those ideas basically become mainstreamed so i think that and deliberate my friend who passed away eric i miss him dearly was their webmaster and his whole point is if you don't think about it in terms of a party in terms of getting people elected but if you think of it as a party in terms of getting people educated about alternatives then there's enormous use for that that was his perspective and i don't think that's an absurd perspective but here's some libertarian ideas that have become extremely mainstream war should be a last resort uh this is something we're taught as kids and we all say but for many years it's been like they don't think of it as the last resort it's like something's bad well it's like the first instinct now it's like let's really give it a week just a week like what's going on in syria is there really gonna be a genocide the kurds you know things like that so that's one another thing is drug legalization uh this was you know when you and i were kids oh it's crazy it's only hippies want to smoke pot now it's like with it i was on a grand jury and the point out people make is are you sure that this 16 year old who's selling wheat let's say selling should his life be ruined should he be imprisoned with rapists and murderers like if you say yes say yes but you but are you sure you have to acknowledge that that's what you're meaning and then a lot of people are like wait a minute there's got to be a third option then he has no consequences or he's imprisoned with the rapist like i'm not comfortable with either of these uh and i think the other one is an increasing skepticism this libertarians were on top of this first and the hard left of the police uh as of now asset forfeiture steals more from people than burglaries what people don't know about what that's their forfeiture is if the cops come to your house and they suspect you you haven't been convicted of using your car or your house or whatever in terms of selling drugs they can take whatever they want and then you have to sue to prove your innocence and get your property back it's a complete violation of due process people don't realize what's going on it's a great way for the cops to increase their budgets and it's legal and libertarians were like the first big ones saying guys this is not american and this is crazy and now increasingly people on conservatives and left is like wait a minute this this is even if you are selling drugs like they take your house what are you talking about so i think those are some uh mechanisms that libertarianism though but not by name has become far more popular yeah it's interesting so the idea yeah coherent set of ideas uh that that eventually get integrated into a two-party system yeah the war that's an interesting one you're right i would want i wonder what the thread there is i wonder how it connects to 911 and so on but i i think that i i think the patriot act patriot act for people who are politically savvy were like oh okay this is not a joke this is really a crazy infringement our freedoms and both parties are falling over each other to sign into law and the orwellian name you don't want to how can you be against patriotism what kind of person you know what i mean so that i think for a lot of people especially both civil libertarians on the left and a lot of conservatives who are constitutionalists are like wait a minute this isn't i'm not comfortable with this and i'm also not comfortable with how comfortable everyone in washington is with it you're right probably libertarian libertarians and libertarianism is a place of ideas which is why i have a connection to it like i like i i like the every time i listen to those folks i like them i feel connected to them i would even sometimes depending on the day call myself a libertarian well we're on the spectrum so that's why we're on the spectrum yeah but like when i look at the people that actually rise to the top in terms of like the people who represent the party this is where like five minutes ran out right you can i could go i'm allowed you can go why are they so weird why aren't strong candidates emerging that represent as political like representatives or as like uh famous speakers yeah like that represent the ideology i think libertarians tend to i think jonathan height in his book uh in his research he's a political scientist and he does a lot of things about how people come to their political conclusions and what factors uh um force people to reach conclusions and he found that libertarians are the least empathetic and most rationalistic of all the groups and by that he means like they think in terms of logic as opposed to like people's feelings and and that has positives and has negatives uh it would and we have the a b testing with ron paul ron paul ran for president as a libertarian nominee he was the nominee he got pretty much nowhere in 1998. then he ran as a return to republican party as a congressman for many years from texas he ran for the presidency in 2008 and 2012. and in 2008 he stood on stage with rudy giuliani and told him that they were here in 911 because we're over there which would have been a shocking horrifying taboo a few years earlier many people were like holy crap this is amazing julian was all offended and ron paul's like i took some guts by the way yeah it did i heard that it was so refreshing that not what he said but the fact that he said something that took guts it made me realize how rare it is yes for peop for politicians but even people to say something that takes guts well it's also the idea that like you can't even if you think america has a right to invade any country on earth as much as it wants and kill people as a consequence of war and blow up their buildings and destroy their country you can't with a straight face not expect us to have consequences even if they're consequences from evil people even if we're 100 of the good guys and their 100 the bad guys those bad guys some of them are still going to try to do something what happens next you know what i mean so that kind of concept that there's any american culpability was where america where you know we're the good guys by definition we're not culpable to have people start thinking about what if there's another way you know what if we're not there and then they're not here and we're kind of doing a back door we're talking so different scenarios so the fact that he got so much more traction as a republican the fact that donald trump who came out of nowhere became the not only the candidate but the president tells people it's like getting a book deal right you can either go there's three choices you can either self-publish mainstream publisher or independent publisher the independent publisher is the worst of all choices because you're not getting a big advance they're not going to be able to promote you a lot and they don't get the distribution mainstream i've done mainstream myself right with self i don't have the the cred the respectability of a mainstream for the cachet it can't be uh new york times bestseller right let's take six a lot of work but i get a lot more of the profit uh if it looks good on the shelf on amazon looks identical so on and so forth with the mainstream the benefits and costs are pretty much obvious to most people so the same thing it's like you can either be an independent like ross perot or you could be just cs won the party apparatus which the benefits are enormous there but in terms of going third party i don't know the libertarian party apparatus other than maybe some ballot access is really that efficacious and then you're gonna have a lot of baggage because if you hear independent jesse ventura ross perot you think of the person now you have to define yourself and you have to defend the party that's two bridges for most people brilliantly put okay thank you uh let me speak to you because i'm i'm speaking to jaron brooke soon yeah uh i like him yeah so but that another example i was ask him to tell you a joke about iran if he can do it so there that's one criticism i've heard you say which is they're unable to speak to any weaknesses in either iran's or objectivist worldview yes that's really uh you you put it i know you're half joking but that's actually a legitimate discussion to have i'm not i'm not joking at all because that's to me one of the criticisms and one of the explanations why the world seems to disrespect ayn rand the the people that do is she kind of implies that her ideas are like flawless she says they correspond to reality yeah right that's the term she uses that i mean objective is it's in the name it's you know it's just facts like it's impossible to basically argue against because it's pretty simple it's just all facts and that's it's possible to argue against but she would say she's never met a good critic who could argue the facts about misrepresentation and she's not entirely wrong she's often caricatured because she has a very extreme personality and extreme worldview but that to me i mean some people there's a guy named in the physics mathematics community called stephen wolf from i don't know if you're well from alpha yeah okay he has a similar style of speaking sometimes which is like i've created a science but that turns a lot of people off like this kind of weird confidence but he's one of my favorite people i think one of the most brilliant people if you just ignore that little bit of ego or whatever you call that yeah yeah that there are some beautiful ideas in there and this amazing person and that for me objectivism i'm undereducated about it about it uh i hope to be more educated but there's some interesting ideas that again just like with ufos uh not that there's a connection with you don't bring that up for your own he won't like it i'm runs like ufos oh no no no this interview is over that's that's a good yarn okay uh but you know you have to be a little bit open-minded but what's your sense of of objectivism what's uh are there interesting ideas that are useful to you to think about i own her copy of the first printing of the fountainhead so that should tell you a little bit about how my affection for miss rand how heavy that goes um i ein rand does not have all the answers but she has all the questions so if you study rand you are going to be forced to think through some very basic things and you're going to have your eyes open very very heavily she was not perfect she never claimed to be perfect she was asked on donahue is it true that according to your philosophy you're a perfect being she said i never think of myself that way and she said but if you ask me do i practice what i preach the answer is yes resoundingly um she's a fascinating woman uh what is really interesting about her and this something you'd appreciate personally is when you read her essays she'll have these weird asides and it looked like she would talk about art and she'd be like and this is why the u.s should be the only country with nuclear weapons and when you follow a brilliant mind making these seemingly disparate connections it's something i find to be just absolutely inspiring and awesome and entertaining um i think there's lots of things about her that people like yaran would make uncomfortable um well like she they so objectivism like any other philosophy has all these techniques to kind of hand wave away things you don't want to talk about and like pretend that so they talk about things like having no meta metaphysical significance right so what that means is like well what about this i don't talk about it like it doesn't matter like it literally means fancy philosophical terms doesn't matter or they will say correctly that it's very twisted in our culture that when we have heroes we look for their flaws instead of looking for their virtues that's a 100 valid perspective however if i'm sitting here telling you that i think this woman is a badass and she's amazing and she should be studied but there's also these idiosyncrasies they don't want to hear it because they and i think it's very convenient for them because there's a lot of things she did that work here's an example rand was very very pro a happiness and pleasure she was very pro-sex which is kind of surprising looking at her and how she talked and how strident she was as a result of this she never got her cats fixed to deny them the pleasure of orgasm so her male cats are spraying up her entire house yeah like that is i mean that's her putting her philosophy into practice but it's still gross yeah so that's the kind of thing where i don't think he'd another thing is rand had an art an article on a woman president and she said a woman should never be president right now when ran says things that are too goofy for them they say oh that's not objectivism that's her personal preference it's like she did not have these lines objectivism was always defined as ein rand's writings plus the additional essays in her books so if this was in part of those books this counts as official objectivism but they pretend otherwise so that's another example plus they are they she was and i bet you she was on the spectrum to some extent i'm not joking i'm not using that derisively she was of the belief and not inaccurately because that humor is used to denigrate and humiliate and she was thinking about the jon stewart type before there was a john stewart and a lot of times like how i use mocking but she was resentful correctly that a lot of times people who are great and accomplished little nobodies will make a punch line uh just to bring them down and just bother here's an example i just thought of i remember in i remember when it was must be in the 90s they had a segment on mtv of all these musicians who were making their own perfumes right and this girl grabbed princess perfume and before she even smelled it she had the joke ready she just ugh this smells almost as bad as his music lately it's like first of all i'm sure the perfume's fine yeah and second of all this is prince he's one of the all-time greats and you can't wait to you know you know denigrate him like and part i want to be like brown like how dare you like as if as if this perfume in any way in any way mitigates his amazing accomplishments and achievements you horrible person but i do have some great iran jokes and he would not be happy about them the perfume thing the problem with is just not funny not that no he sucks okay great not that they dared to try to be humorous right because i don't know why you mentioned jonathan because john stewart's pretty can be funny right but hey he taught a generation you still see this on twitter where things have to be inherently sarcastic and snide but isn't that i mean aren't you practicing that no i use irony not sarcasm here's an example when people like you say something and someone reply to be like um last i checked blah blah blah blah and i'll that i see i go what do you think saying last i checked added to your point you're giving me valuable information and data but you are trained to believe that it has to be couched in this sneering it doesn't just give me the information this is useful information that's that's true it's a jerk but see john stewart did it masterfully exactly and they don't and they they don't it's it's like people who copy commit certain comedians you try to copy them and you lose everything in the process of copying yeah yeah yep okay uh but in terms of the the philosophy of you know selfishness this kind of individual focused idea and i'm i imagine that connects with you yes and i think it would connect with more people they understood what she meant by nathaniel brandon who was her heir until she kind of broke with him and and he was a co-dedicatee of atlas shrugged said no one will say on rand's views with a straight face they won't say i believe that my happiness matters and is important and it's worth fighting for and that ayn rand says this then she's dangerous now it's very easy to say this could have dangerous consequences if you're a sociopath but to put it in those terms uh i think is extremely healthy i think more people should want to be happy and and have i think a lot of us are raised to be apologetic especially in this cynical media culture that if you say i want to be happy i want to love my life that it's just like okay sweetheart and you the eye rolling and i think that's so pernicious is so horrifying and this is why i'm a kamu person because camus thought the archenemy was cynicism and i could not agree more like if you're the kind of person if someone likes a band and you're like oh you like them blah blah it's like this gives them happiness yeah now there's certain exceptions but if it gives you happiness it's not for you that's cool okay this is beautiful i i so agree with you on the eye rolling but you see the best of trolling is not the eye roll correct of course not the best of trolling is taking down the eye rollers i'm gonna have to think about that okay because i haven't red bull yeah uh because i put them all type is red bull um i kind of put them all in the same bin okay and they're not they're not they're not okay all right here's another example of trolling i was making jokes about ron paul he just had a stroke right and someone came at me and they're like oh blah blah blah you know you're ugly i hope you have a stroke i hope you're in the hospital and i just go i just did have a stroke on your mom's face so they came at me yeah and now they got put in their place with a subpar um i mean i wasn't clever you weren't you weren't clever not particularly no well one of your things you do which is interesting i mean i give you props in a sense is you're willing to go farther than people expect you to yes that's fun yeah in fact i'll probably edit out like half of this podcast because the the thing you did which she kept in i should mention is michaela peterson now has a podcast which is nice i guess was it on her podcast she was at mine she was on yours we did both but this is when you're referring to when she was on mine she was on yeah right and you went right for the for the so i'll tell you what it was you don't have to paraphrase so i opened up i say you know she's jordan peterson's dad and as many people know jordan he's her dad yeah she's had a long issue with uh substance addiction and i said to her you're you know you're most famous for being you know jordan peterson's daughter you know many people he's changed so many lives around the world he's and he's been such an enormous influence to me personally that i've started taking benzodiazepines recreationally and she's like oh my god michael is so horrible yeah you because you pulled me in with this because you're talking i mean you know because he's going through a rough time now she's going through just everything was just you pulled me in emotionally i was like this is going to be the sweet mic is going to be just this wonderful and then just bam so that's that's that's that was uh props to you on that it wasn't whatever that is that is an art form uh when done well it can be taken too far my criticism is it that feels too good for some people what do you mean uh for oh they're too happy being irreverent because to show that they don't care about anything that's another form of cynicism though right so i if you because you think it's possible to be a troll and still be the live life to its highest ideal in the camus sense i try that's kind of my ideal i i believe it's not i it becomes a drug i feel like that takes you like i think love ultimately is the way to experience like every moment of every day you don't think that was an expression of i honestly think let's let's let's split hairs here because i think there's something of use here i do think that me i'm me being able to make her laugh about this year of hell she was in yeah does create an element of love and connection between me and her yeah but i know she would say that yes it wasn't that it was what you said in combination with the sweetness everywhere else the kindness it's a very subtle thing but like it's like some of the deepest connections we have with others is when we like mock them lovingly or yes that's correct but like there is stuff there's kindness around that yeah it's not in words but in life of course subtle things because it creates an error familiarity being familial like we're through this together like yeah yeah yeah that's missing that's very difficult to do on the internet i agree with you i agree with you that's why my like my general approach on the internet is to be uh some more like simple less witty and more like dumbly loving but that's not your core competency being witty uh me yeah but i i could be woody you can be but i'm saying that's not your core company so i'm just saying you're bad at it but i'm saying that's not where you go like organically especially with strangers i just feel like nobody's core competence on the internet is uh i guess if you want to bring love to the world nobody's core competence is given the current platforms nobody's core competence is whit it's very difficult to be witty on the internet without while still communicating kindness like i'll give you another example in the same way that you can in physical space i'll give you another example someone um came at me and they were like they gave me a donation people do this all the time and they go oh um like i started reading your books because of my wife and you know now watch your shows together i keep up the good work and i go what does her boyfriend think so that is an example of wit and love because that person feels seen i'm acknowledging them yeah i'm also making a joke at their expense we know it's a joke so i think language is often used in non-literal ways to cue emotional and connectivity it's difficult but you it's very difficult what you've done is is difficult to accomplish but you've done it well i mean you do like you did you do been doing these live streams which are nice that people give you a bunch of money and donations and stuff and then you you'll often like make fun of certain aspects of their questions and so yeah but it's so it's always wrong that's not from love that is genuine annoyance because they ask me some really dumb questions but they're still underlying it's not even like there's a kind person under this that's being communicated that's interesting but i don't know if i get that from your twitter i know i get that from the video the something about the face something about like yeah of course it's much harder the more the more data yeah the more easy it is to convey emotion and subtlety absolutely if you only have literally black and white letters it's gonna be or whatever white and black if you have night mode it's gonna be a very different it's much more limited information yeah but this is the fundamental thing is like let's here's another example like if they had access to my face like a lot of times some people don't know who i am and they come at me call me a nazi anti-semite right and i start talking about the jews and just how terrible the jews are now all my audience knows i'm jewish that i went to shiva so they're sitting there laughing because this person is making ass to themselves that person has no idea but if there was video then they would be like okay wait a minute something yeah yeah something's up i don't know uh i think it's entertaining i think it's fun but i just i don't think it's scalable and ultimately i'm trying to figure out this whole trolling thing because i think it's really destructive i've been the outrage mob the outrage mobs the just the the dynamics of twitter has been really bothering me okay and i've been trying to figure out if we can try to build an alternative to twitter perhaps or try to encourage twitter to be better how to have nuanced healthy conversations like the reason i talk about love isn't just for love's sake it's just a good base from which to have difficult conversations like that's a good starting point because if you start like i would argue that the kind of conversation you have on twitter is fun but it might not be a good starting point for a difficult nuanced conversation well i'm not interested in having those conversations with most people no i know but so i agree with you your point is valid yes but like i'm saying so if we were trying to have a difficult nuanced conversation about say race in america or policing is there racism institutional racism of policing okay there's uh the only conversations that have been nuanced about it that i've heard is in the podcasting medium which is the magic of podcasting which is great but that that's the downside of podcasting is it's a very small number of people even if it's in the thousands it's still small and then there's millions of people on social media and they're not having nuanced conversation at all they're not capable of it that's the difference in you that's saved their minds i believe they are so that's there's no data that's happening and then both of us aren't being not scientific you don't have data to support your worldview either you're making the claim well you are too no i'm not if i'm looking at an object the free the claim that opens my mind well no what no your claim is that people are fundamentally stupid aren't you a martial artist yes how does it feel i know you yeah but you really don't think people are deep down like capable of being intelligent no not at all not not deep down not surface i'm not joking i'm not being tongue-in-cheek and not being cynical i do not at all at all think they have this capacity i'm gonna because you're just being so clear about it you're not even i'm gonna be here you know why i here's here's a here's evidence for my position not proof and this is of course data that is of little use but it's of interest a lot of times when you have an audience as big as mine and people come at you not only will people say the same thing the same concept they'll say the same concept in the same way that is not a mind yeah that's surface evidence you're saying this iceberg looks like this from the surface yeah i'm saying there's an iceberg there that if challenged can can rise to the occasion of deep thinking and you're saying nope nope it's just frozen water isn't that the russian expression that's ice cream no not doesn't it mean like no one's there actually i don't know yeah it means like yeah yeah it's like thought it means okay well uh so you're challenging me to be a little bit more rigorous i think i'll try i'll not challenge you anything i'm just saying no not challenging me but like i'm challenging myself based on what you're saying because i'd like to prove you wrong and find actual yeah data to show you're wrong and i think i can but i would need to uh get that data that's funny you said i think i can when when they were working on my biography ego and hubris the title i had suggested was the little engine that could but shouldn't and they didn't like it i think that's a great title it's pretty good yeah speaking of biographies i mean one i read your book or listen to your book listen to there's an audiobook for you right yeah i did the audio yeah yeah you you read it my goal is yes okay so this is this is uh i didn't do yaron brook's voice in the book i did all the different voices because he has lisp and i didn't want to sound like i was making fun of him yeah i i don't remember you reading it but it was i was really enjoyed this yeah no okay it was good it was like a year a year and a half ago i can't prove uh well let me at a high level see if you can pull this off if i ask you uh what's the book new write about it's about uh a group of people who are united solely by their opposition to progressivism who have little else in common but who are all frequently caricatured and dismissed um by the larger establishment media but you give this kind of story of how it came to be sure and to me like we're talking about trolls but the internet side of things is quite interesting so first of all how does alt-right connect so the alt-right is the subset of the new right which feels that race not racism is the most or one of the most important socio-political issues are any of those folks like part of the mainstream or worth paying attention to not only by the mainstream the alt-right yeah by definition they would be part of the mainstream they would not be part of that no they would not i don't know that any of them well worth is not a position i'm not able to say worth i'm i would say that it is of use to be familiar with their arguments because to dismiss any school of thought especially one that has historically gained leverage especially one that has historically gained leverage in very dark ways especially in america in europe and other places just to say oh they're racist i don't need to think about them it's it's it doesn't behoove you so what uh what lessons do we draw from the the 4chan side of things like the internet side of the movement tits or get the fuck out um can you define every single word hits our breasts or get the fuck out that's from 4chan okay that's what's uh what's it mean oh sometimes like a woman will appear in 4chan and they'll just reply tits or get the fuck out i'm trying to understand what oh oh that's a way i just um very slow uh so that's okay so that's very disrespectful towards female members of the community i don't understand there's rules to this community and one of them is uh we're not very good with women is that that's one of those sort of principles it's a principle we're not going to ever get laid that's the fundamental principle is there we are going to get pics pics sometimes sometimes on the sometimes gtfo gt okay so is there other actual principles of so like it's it's i from my maybe naive perspective is they have like the darkest aspects of trolling which is like take nothing serious make a game out of everything that's not 4chan per se one of the things that you will learn 4chan which i think is very healthy is if you have an idiosocratic or unique worldview or focus on an aspect of history or culture you'll be able to find like-minded people who you will engage with you and discuss it without being promptly dismissive that's an ideal that they well it's not ideal it's something that happens a lot now 4chan is not really like paul as their board with politics but they will you know get into some like the people there are much more erudite than you think so they do take my my perception was they take nothing seriously so there's things that they take seriously like discussing ideas i'll give you one example there was a video someone posted of a girl who put kittens in a bag and threw in a river and they found out where she was within a day and got her like arrested so yeah they do they take some things very seriously okay but that's like an extreme that i mean that's good first of all that's heartwarming that they wouldn't somehow turn that into a thing that feels like more of uh what is it what's the other one 8chan 8 chance twice as good as 4chan yeah that's their slogan but it feels like they're the kind of community that would take that kitten situation and make a mockery yeah they're they're a darker than fortune yeah yeah i don't even i'm not allowed to talk about 16 chan i'm already overwhelmed clearly uh by 4chan lingo i'm i have actu i literally wrote down on my notes um like in doing research for this conversation i learned the word pleb and i wanted to ask you would this pleb mean you know what flood means no i don't what i i saw i mean actually no i don't you know what a pleb is i just i don't know what a flub is like a plebiscite or plebeian okay but does it mean something more sophisticated um no it's a very unsophisticated mechanism of being dismissive of like the regular people yeah or someone who comes at me on twitter okay all right so back to the 4chan alt-right it wasn't uh those are very different concepts don't conflate them but which internet culture was the alt-right born out of uh alright was more born of blogs and people had different blogs where they were posting what they called like racial realism scientific which is scientific racism so-called um and you know breaking down issues from a racialist perspective so that wasn't 4chan is much more uh dynamic it's a message board it's very fluid um so it doesn't lend itself to these kind of in-depth analysis of ideas or history but it spreads them like it it spreads them as memes yeah and it you know but it's not it's not an essential mechanism of uh of the alt-right historical no no no no no no so it was both mostly about blogs okay so what uh what do you make of the psychology of this kind of world view when you have this goes to your conspiracy theory subject earlier when you have a little bit of knowledge about something about history that no one's talking about and there's only one group that is talking about it and they and you have no alternative answers you're going to be drawn to that group so because issues about race anti-semitism homophobia are so taboo in our culture understandably there's good reasons if you start putting things like how old should you be you have sex with kids just have regular conversations eventually some people are going to start taking some positions you don't like so some things have to be sanctified to some extent they're the only ones talking about it you're going to be drawn to that subculture and where does the alt-right stand now i mean i hear that term used so the term has been weaponized by the corporate press for people that they want to read out of society so it's used both on individual levels like people like gavin mcking mckingus milo yiannopoulos some others they i mean i think they refer to trump as alt-right um and and you know it's become a slur just like in cell or bot that has become largely removed from its original meaning do you have a sense that there's still a movement that's all right or like yeah they call themselves now so okay so there's something called the dissident right and they say we're completely not like the alt-right because the alt-right's a b and c and we're bcd there's a huge overlap it's very much the same people um is there intellectuals that still represent some awesome aspect of the movement i mean sure are you tracking this not not that much anymore um i think they've they're i don't find it particularly as um now that the book's done you know my i'm looking more into history from my next book um you mentioned communism i'm going to talk a lot about the cold war um so this kind of stuff has largely fallen away from my radar to some extent and they've also been the the it's been a very effective movement to get them marginalized and silenced so they're not as as deep as of a concern in terms of concern or not just their impact on size much less yeah so as a troll on twitter yeah in the best sense of the word what do you make uh of canceled culture i think it's maoism it's i mean the corporate america has done a far better job of implementing that wasn't that a communist party ever could you had this meeting not that long ago from i think it was northwestern university law school where everyone on the call got up and said that they were racist i mean this is something that legally you should be very averse to saying even if it were true and it's this kind of concept of getting up and confessing your sins before the collective is something completely um are they sorry they admitted this of themselves yeah they were like because they're saying because they're white they're inherently racist so my name's john i'm a racist my name is this i'm a racist it was it was uh you hear it and you're like okay this is looney tunes so you're saying that wow that's that that's so much you took a step further so you're saying there's like a a deep underlying force but it says cancer culture it's not just some kind of mob but it's not some at all it's a it's a systemic organized movement uh being used for very nefarious purposes and to dominate you know an entire nation how do we fight it because i sense it inside you know i used to defend academia um more because um i i still do to some extent it's a nuanced discussion because you know like folks like jordan peterson and a lot of people that kind of attack academia they refer they really are talking about gender studies at certain departments and me from mit you know it's the university of science and engineering and the the faculty there really don't think about these issues or haven't traditionally thought about it's beginning to even infiltrate there it's the you know it's starting to infiltrate engineering and sciences outside of biology yeah like let's put biology with the gender studies like i'm talking about sciences that really don't have anything to do with gender uh it's starting to infiltrate um and it worries me i don't know exactly why like i don't know exactly what the negative effect there would be except it feels like it's anti-intellectual oh yes of course and i'm not sure what to uh because on the surface it feels like a path towards progress at first when you when i'm like zoomed out you know just like like squinting my eyes the you know not even in detail looking at things but when i actually joined the conversation to like listen in the conversation on quote-unquote diversity it quickly makes me realize that there's no interest in um in making a better world no no it's about domination it's it's about getting yeah it's a way for if you are a lowest status white person using anti-racism is the only mechanism you will have to feel superior to another human being so it's very useful for them um in terms of fighting it one of my suggestions has been to seize all university endowments which are the crystallization of privilege and distribute that money as reparations so be very effective by turning two populations against each other and strongly diminishing the university's intellectual hegemony uh the universities are absolutely the real villains in the picture thankfully they're also the least prepared to be aggressed upon and after the government and the corporate press they are the last leg of the stool and they don't know what's coming and it's gonna get ugly and i cannot wait so this is where you and i disagree part one yeah we disagree in a sense that you want to dismantle broken institutions i don't think they're broke they're working like by design i think for over 100 years they have been talking about bringing the next generation of american leaders which is code for promulgating an ideology based on egalitarian principles and world domination let me try to express my lived experience okay sure okay my experience at mit is that there's a bunch of administrators that are the bureaucracy sure that i can i can say this is the nice thing about having a podcast i don't give a damn is they're pretty useless in fact they get in the way but there's faculty there's professors that aren't incredible they're incredible human beings that all they do all day they're too busy but for the most part what they do all day is just like continually pursue different little trajectories of curiosities in the in the various avenues of science that they work on and as a side effect of that they mentor a group of students sometimes a large group of students and also teach courses and they're constantly sharing their passion with others and my experience is it's just a bunch of people who are curious about engineering and math and science chemistry artificial intelligence computer science what i'm most familiar with and there's never this feeling of mit being broken somehow like this kind of feeling like if i talk to you just now or like eric weinstein there's a feeling like stuff is on fire right there's something broken uh but when i'm in in the system uh especially before the kovid before this kind of tension everything was great there was no discussion of even diversity all that kind of stuff the the toxic stuff that we might be talking about right now none of that was happening it was a bunch of people just in love with uh cool ideas exploring ideas being curious and learning and all that kind of stuff so i don't my my sense of academia was this is the place where kids in their 20s 30s and 40s can continue the playground of science and having fun it's if you destroy academia if you destroy universities like you're suggesting kind of lessening their power you take away the playground from these kids to to to play it's going to be hard for you to tell me that i'm anti-playground yeah well i guess i'm saying you're on top certain kinds of playgrounds which is yeah the ones that have the broken glass on the floor yeah i am against those kinds of playgrounds no no you're you're you're yes no you see that you listen no you no you wait yeah i i i would say you're being the watchful mother who the one kid who hurt themselves in the glass one kid it's an intelligent it's generation after generation i'm not a watchful mother i'm the guy with the flamethrower no i i i understand that but you're using the one kid who was always kind of like weird um gender studies department uh that that hurt themselves on the glass as opposed to the people who are like obviously having fun in the playground and not uh playing by the glass the broken glass and they're just i mean to me some of the best innovations in science happen in universities okay you can't forget that universities don't have this liberal like politics literally in every conversation until this year until this this year there's something happening but uh every conversation i've ever had nothing to do with politics would never trump never came up none of that ever come up nothing like all this kind of idea that there's liberal all that that that's in the humanities yeah but do you think mit massachusetts into technology might be a little bit of an outlier yeah there probably is yeah but i i don't i honestly don't think when people criticize academia they're looking at uh they're in fact also picking the outliers which is they're picking some of the quote unquote's strongest gender studies department this is nonsensical when i was a bucknell i was a college student we had to take you know we had a bunch of electives and i want to take a class on individual american individualism one of the texts of the five that we had to read was birth of a nation the movie about the clan so there's no department where these people are not thorough going hardcore ideologues uh this is not a gender cities that's the humanity fine all the humanity it's not just gender studies okay fine i can give you history english yes all of them every university as you know has it mandatory in the curriculum they have to take a bunch of these propaganda classes i look forward to youtube comments because you're being more eloquent and you're speaking to the thing that a lot of people agree with and i'm being my usual slow self and people are going to say not very nice things about me don't say anything that nice about lex okay please let me try to just just shoot up a school that would be preferable there he goes again only the teachers go to the darkest possible place the sunshine baby schools that's where everyone goes to be happy playgrounds there he goes dark ear just dives right in like it just go dark and then just comes back off to the surface not to feel [Laughter] um you're probably a figment of my generation i'm not even having this podcast well after 18 red bulls i'm surprised you could see anything this is like fight club red bull gives you delirious yeah uh i got into it at norton yesterday on twitter oh really yeah as he uh like the rest of the celebrities yeah he's like oh this is an existential threat to america trump's a fascist he's delegitimizing the oval office i said what an odd endorsement of trump well you should have went with bad pit he might have a different opinion that's spike reference okay this conversation is over it's interesting i'd like to draw a line between science and engineering and science not including like the biological aspect the the parts of biology that touch and humanities and biology like i feel because uh humanities if you just look at the percentage of universities it's still a minority percentage and i would actually draw different i think they serve very different purposes sure and that's actually a broken part about universities about like why why is some of the best research in the world done at universities that doesn't like there might be a different like mit it feels weird that a faculty yeah these are conceptually different things like we do research and we teach why is this the same yeah it feels weird but that's just but but i'm also i'm coming to like the defense of the engineers that never talk about i'm not like like my mind isn't i'm not like deluded or something where i'm i'm not seeing the the house on fire i'm just saying i am seeing the house because i also lived in harvard square i'm seeing harvard but when you see the tanks coming they're coming next they're gonna be so beautiful i'm gonna it'll be like the american beauty the plastic bag i just won't be able to stop crying because it'll be so beautiful yeah thanks i could i can already i can already see it but the but the engineering departments were like i believe that the elon musks of the world that the the like the innovation that will make a better world is happening and like let's not burn that down because it has nothing to do with any like they're all like sitting quietly in while like well the the humanities and all these kind of diversity programs they're not having any of these discussions listen my soviet brother you both know we both know that ice water runs in our veins so if you're calling for mercy that is not how i'm wired but i'm not closing the door yeah i'm actually realizing now so for people listening to this i'll probably prepend this and saying that i'm even slower than usual i didn't sleep last night but i feel i'm actually realizing just how slow i am and how much preparation i need to do in if i would like to defend aspects of academia i better come prepared i don't think you need to defend them i think i'm granting you your premise freely no you might be okay i don't think the the world is that like actually you just defeat your own argument because you because it is not at all have to be the way that a phenomenal research institution like mit which no one disputes has to also be an educational establishment these two things are not at all necessarily interconnected but then you have to offer a way to separate correct but like i'm not a big fan everybody's different but i'm not a fan of criticizing institutions without offering sure a way to change and especially when i'm like have ability to change i'd like to yeah i'd like to offer a path like what if they were in students they were all mentor like uh like men like um what's the opposite of a mentor mentee protege what's the term when you're like just when you work at a place like interns not an intern something i'm thinking of but anyway like basically they're working there instead of going to college there it's possible but it's going against tradition and so you have to build new institutions and uh and then have these engineers building new things that's crazy yeah these research engineers where they're going to be building things well one of the things because you're kind of you know apprentice that's the way i was looking at apprentice which is ironic we're talking about trump and we couldn't think of the word apprentice ah very yeah well done we should both be fired yeah there you go these russian jews so quick with their wit okay uh but the the thing is you're a fan of freedom i am and there's there is uh intellectual freedom people this is what i was trying to articulate i'm failing to articulate but there truly is complete intellectual freedom within universities on topics of science and engineering i believe you yeah i agree with you i don't think it's going to take much persuasion but i'll give you an example when that i i'm sure you know more details about this than i do when that uh scientist engineered that probe to land on that comet and the articles written because this hawaiian shirt he was wearing had like pinup girls on it which i think is female student episode frame or something where's his ex-girlfriend and he had to apologize this is what rand was talking about yeah that the great accomplishments of men have to say i'm sorry to the lowest most despicable disgusting people yeah i don't know you know let me bring this case up because i think about this uh this might not mean much to you but it means a lot to a certain aspect of the computer science community there's a guy named richard stallman i don't know if you know who that is no he's the founder of the free software foundation he's like a big linux he's one of the key people in the history of computer science one of those open source people right but he is like i believe he's the one of the hardcore ones which is like so all software should be free okay okay so very interesting personality very key person in the new just like linus torvald key person so but he also kind of speaks his mind okay and on a certain chain of conversations at mit that was leaked to the new york times then was published led him to be fired or pushed out of mit recently maybe a year ago and i always sat weird with me so what happened is um there's a few undergraduate students that called marvin minsky not sure if you're familiar who that is i've heard the name he's one of the seminal people in artificial intelligence they they said that they called him a rapist because uh he met with jeffrey epstein and jeff uh free epstein solicited uh two these are the best facts known to me that i'm aware of that's what was stated on the chain is he solicited a 17 but it might have been an 18 year old girl to come up to marvin minsky and ask him if he wanted to have sex with her so jeffrey epstein told the girl yeah she came up to marvin miske who was at that time is i think seven years old and his wife was there too marvin mink's wife and he said no or like you know awkwardly yeah so thank you yeah no thanks and that was stated in the email thread as marvin participating in uh sexual assault and rape of this uh unwilling sexual assault and it was called rape uh of this person right of this woman that propositioned him and then richard stallman who's he's kind of known for this he's very he's you make fun of me being a robot but he's kind of like a debugger he's like well that sentence is not what you said is not correct so he like corrected the person uh basically made it seem like the the use of the word rape is not correct because that's not the definition of rape and then he was attacked for saying oh now you're playing with definitions of rape rapist rape is the answer right and then that was leaked in him defending so the way he was leaked it was reported as him defending um rape that's the way it was reported and he was pushed out and he didn't really give a damn it's he doesn't seem to make a big deal out of it he just left he made an example of him they made an example and that and everyone was afraid to defend him so like there's a bunch of faculty one dude you're from the soviet union doesn't this hit close to home for you i don't know what to think of it it hits close to home but it was basically at least at mit now mit is such a light place with this it's not common at mit but it was like 18 19 year old kids undergraduate kids with this kind of fire in them there's just very few of them but they're the ones that raise all this kind of fuss and the entirety of the administration all the faculty are afraid to stand up to them it's so interesting to me like i don't know if i should be afraid of that you don't think you should be afraid so someone who's trying to be specific when it comes to charges of violent assault is looking for that clarity can get their life uh other search engines let me give you more context there's a little bit more context to richard stallman which is he was also a rapist no he left out that part he liked raping people but he's had a history through his life uh of you know every once in a while wearing the hawaiian shirt with like he would make he's a fat uh sorry but he's a fat unattractive he like what trump referred to the the yeah the guy in the basement in the basement that's richard okay i love you is is you know he is what he is peop you know people he like he would eat his own uh he would pick skin from his feet and lectures and just eat it okay yeah this video is him doing that i'm not joking he must really behind the spectrum then yeah okay yeah and so and you know uh he i think this uh and his office he adore he wrote something like uh uh like hacker uh plus plus lover of ladies or something like that like something kind of yeah yeah yeah so professional yeah unprofessional and a little creepy yeah no that's fair so he was also so they're looking for an excuse to get rid of him it sounds like i know he was just who's they the administration yeah probably probably a lot of times what people don't realize you know this would be my defensive cancer culture a lot of times when someone gets fired over something like this yeah this isn't why this is just giving them cover to get rid of them without getting a lawsuit yeah but it's still so i think i guess what i'm trying to communicate it feels a little weird and creepy and he may not be the the best for the community but that's not necessarily the message it's sent to the rest of the community the message is sent to the rest of the community that being clear about words or the usage of the word rape is uh like you should call everything rape that's that's that's basically the message you send or you should call that we say rape rape it's about submission i think i'm you'd be very happy to know that there's a lot of people and she's very crucified this like betsy devos the president's department of education who are aware of this they are aware that this completely contradicts due process uh they're aware of how a rape accusation is something not to be taken seriously but because it's not to be taken seriously it has to be also taken seriously another context that you know once that word is around a male this can ruin his entire life um and that's that that's the sticky thing of the word like i like i think about this a lot that um like how would i defend it if somebody like i've never i can honestly say i've never done anything close to creepy in my life like uh with like with women but you wouldn't know it if you had right that's the thing a lot of these creepy guys don't think they're creepy they think they're being cute yeah but i'm just telling you even like fine let's say right let's say i'm not aware of it but the point that i am aware of is that somebody could just completely make something up correct yeah yeah yeah yeah okay and like how what do what would i say no he denied the charges there's an article around everything you did supposedly and then goes uh mr freeman denied the charges yeah but what creeps me out that happened can i interrupt there is zora neal hurston is one of my favorite writers she's from the harlem renaissance um she wrote their eyes were watching god a couple of other books she was just an amazing amazing figure her biography is called um wrapped in rainbows it's just a masterpiece i like i think i read it one day can't recommend her enough fascinating fascinating woman during the 30s i think it was her 1940 she was out of the country she was accused of molesting a teenage boy she wasn't in america this could be proven so there's is absolutely false not even a question she was indicted and she wanted to kill herself because she's like people are going to see these things and they're going to think maybe there's some truth to it maybe it's voluntary what they're just going to and and you could understand what should be suicidal over this so yeah this is this is something that's been going on for a long time and in the fact that it's becoming i do agree it's important i know a lot of women who have been sexually assaulted more than i i'm happy that i know and if i know that many that means there's more so i i don't i think it's it's a good idea that they feel seen that they don't feel wounded they don't feel damaged or they can talk to their friends and i'm like man this sucks is happening to you and and i don't think you're a slut i don't think you're asking for it i think you feel violated i think it's gross talk to me like i i do think that that's important and i also think it's important though like when things get kind of in a frenzy that a lot of people like yeah i also had something happen and very quickly the line between he grabbed my boob and he violently raped me i don't think these two things are the same at all i think they're both sexual assault but in terms of what someone can deal with the next day the next month 10 years later i i don't think there's similar scenarios yeah i had juanita broderick on my show and hearing her talk about you know her alleged rape by bill clinton was very disturbing for me very disturbing to hear because it was like half an hour so you know we think of these things and think okay hold her down blah blah yeah and then it's done half an hour when just even someone physically holding you down for half an hour like not even a sexual assault yeah like that's traumatic yeah you think am i your brain's gonna think am i gonna die when i zoom out i think the ultimately this is gonna lead to a better world like empowering women to speak to those kinds of experiences the benefit of it outweighs the the issue is whenever people are given a weapon some are going to use it in nefarious ways and that's the lesson of history males when males females whites blacks children adults when people are given a mechanism to execute power over others some are going to use it can i ask you for a therapy thing um sure untrolling in a sense uh because i mentioned somebody making up something about me i feel because i wear my heart on my sleeve i'm not good with these attacks like i've been attacked recently just being called a fraud and all that kind of stuff just light stuff like i haven't you know it was like it hurt okay well let me help you maybe it's because i'm a new yorker no i'm serious here's why in new york a lot of times you'll be walking with your friend and a homeless person will come up to you and start yelling things at you your reaction isn't in those circumstances let me hear this out your reaction is physical safety and getting away now it's not impossible that that homeless person is actually saying the truth this happened to my a friend of mine she this guy wasn't homeless um and he's walking down the street on smith street and he's just talking out loud and he goes why they call them hipsters what are they hip to and she chuckles and he goes what are you laughing at fatso you start something i'll finish it yeah and she she just couldn't move yeah and it's like it's made a problem because that's the first thing he went to and there's i don't know that i have any advice but when you hear something like this this is i think you need to be better in terms of boundaries i think you should not perceive this as a fellow human but as a crazy homeless person because if this fellow human if i thought that you were a fraud in some context that's a very weird word to use because fraudulent podcaster these are real mics but if i was a scientist or human sure but i would ask myself is this person in a position to make this judgment or are they backing it up are they saying here your conclusions were wrong here's some mistakes in your data and you can engage with them on ideas but whenever someone uses a word to entirely dismiss your life without having the knowledge of your life you do not have to take that seriously i appreciate that kind of idea but some things aren't about data like you know i i see myself as a fraud often and it's it's more psychology of it um if i can reduce something to reason i can probably be fine my worry is the same as the worry of uh like teenage girls that get bullied online it's like when i'm being open and fragile on the internet it affects me in a way where i can't the reason doesn't help so it helps me you don't block people enough i'm very happy with the blocking no i so yeah i'm very heavy i block i it's healthy progressive banality i block immediately i also think time is going to help i don't think you're like you didn't grow up wanting to be a podcaster right that wasn't your aspiration so in some sense you are going to feel like a fraud because you're like what i don't have any training for this i have a training for a scientist i can talk about artificial intelligence for literally hours but in terms of this like i don't know what i'm doing i'm kind of so when they call you a fake it's like yeah you're kind of right because like i i did kind of stumble into this and this is not my pedigree so i think that kind of probably speaks to you on some level well but they're they're attacking not the podcasting thing but more like the same thing people call elon musk fraud too which guy that that's the way i rationalize it like well if they're calling him a fraud and they're calling me a fraud that like even if you have rockets that go into like if you successfully have rockets uh landing back on earth usable rockets you're still being called a fraud then it's okay not necessarily it could be that he's not a fraud you really are that's but it's not resonating with you because your brain knows the logic so you can right but uh yeah yeah but i don't know this whole trolling thing you seem to be much better at seeing it as a game you know why because you are under the delusion that every human being is capable of intelligent reasoned decisions still think i'm right and i perceive them as literally animals so when a dog starts barking all it's saying is that the dog is agitated and this is not going to change my life one iota other than crossing the street perhaps yeah i'm going to prove you wrong one day if you're going to kill yourself but if i don't i'll prove you wrong okay i'll bring the data and they'd be like you're right i have the receipt i have the receipts okay so we mentioned camus oh yeah i love him is there um this is this is this is a question that people like love when i ask of really smart people well it is love no uh what uh what books let's say three books if you can uh think of them technical fiction philosophical would you uh had a big impact on you or would you recommend to others sure uh the machiavellians by james burnham uh this is a book about how politics works in reality as opposed to how people imagine it working um mentis moldbug who's a figure in these circles who's respected by a lot of people i was giving a talk and there was a bunch of panelists and we were asked what book would you recommend i said the machiavellians independently of me that was the book he had recommended it's out of print it's hard to find but that would be one is that his book or no james burnham 1941 i think so uh can you pause on the mulches what's that it's just a small bug that's a code name right like that guy named that guy's dependent curtis jarvin it's his real name he's in he swims in your circles which he doesn't kind of progress he's originally programmed yeah he comes up as a person that i should talk with or i should know about but then i read a few of his things and they seem quite dangerous they're very long and verbose but i think he's an amazing thinker yeah but he's the one who had the idea of sending the tanks to harvard yard but doesn't he have like uh he has some radical view i forget what they are very radical views yeah he wants a military coup but you're saying he's a serious thinker this is worthy uh of not worthy i don't know that you would enjoy having a conversation with him i think a lot of people enjoy seeing it happen but i think it'd be a lot of talking past each other and and it would be interesting what do you do okay um what do you agree what do you disagree i agree with him that politics has to be looked at objectively and without kind of an emotional um connection to different schools i talk about him a lot in my book on the new right um disagree i don't think a military coup is a good idea uh he's he doesn't think anarchism is stable i disagree um i mean me and him i did his live stream with him we just dorked out a lot about history and like you know people who've fallen in the memory hall so i mean he's got a lot of writing so so you know the sense i got from him was that if i talk with him a lot of people would be upset with me for giving him a platform yeah i think he's on that edge where they want to read him out of what is acceptable discourse what's his most controversial i mean you can mention the tanks is that the most controversial viewpoint does he have a race thing no he's the the alt-right doesn't particularly like him in many ways because he's not a big on the race thing i don't know what would be his most controversial view uh uh to be honest i think because he is radical in terms of his analysis of culture anytime someone's a radical that is dangerous because it's dangerous okay book uh so that's one the headlines ahead which is a um i would say that shrug no if and if you read atlas shrug before reading the fountain head you're doing yourself an enormous disservice don't you dare do it on the philosophical because every novel every every level fountain head's a better novel fountainhead's superfluous if you read out the shrug first fountain heads about psychology and ethics uh it does not have to do with her politics other than its implications so it's by far the superior book um the third one oh this is a good one question let me see what i there's so many good books out there that i love i i'm going to this is not really my third choice but i'll throw it out there because i um this is such an important world view especially people on the right are you virtue signaling no this is counter signaling um thaddeus russell's book a renegade history of the united states his thesis is that it's the degenerates that give us all freedom um and things like prostitutes things like madams things like slaves things like immigrants because they were so low status they could get away with things that then people who are higher status demanded and so on and so forth so i think that thesis and it really has extreme um consequences in uh thinking and no john jonathan height the righteous mind that's those are the four is that his best i haven't read any of his stuff okay that was four but of course forget that we'll put we'll put height in there you would uh no forget that is this those are the three so we talked about love let me ask you the other question i'm obsessed with are you uh do you ponder your own mortality i do a lot especially now that i'm an uncle especially now that i have like these younger people that i mentor um i was just yesterday uh my friend john gergis who did my theme song for my podcast who did the book cover for um dear reader who's like the most talented person i know his song came on the ipod at the gym and i almost messaged him i go you know one day one of us is going to bury the other and it's going to be really sad and i thought about that and it was kind of like oh man that's really going to suck um and you know i don't know which scenario would be better like i will be very just sad if he's gone i'm sure he'll be very sad if i'm gone um i mean what are you are you afraid of it no uh you know uh um rand had this quote about how uh i won't die the world will end so i've had enough experiences that i am i i've really at this point and everything's icing on that cake so if you if i were to kill you at the end of this podcast it would feel painless that would be okay yeah you know why does anyone know you're here by the way you know why i'll ask you for a friend here's why there's that wit say that for twitter likes did they call you sasha no i'm uh no sure oh that's my sister's husband okay so here's why i strongly believe and this is a very kind of jewish perspective that you just have to leave the world a little bit better than you found it that all you could do is move the needle a little and one of the things i set out to do with dear reader my book on north korea i said i was at a point in my career where i could do something to make a difference instead of just writing like co-authoring books with celebrities which i'm very proud of but you know are neither here nor there and i thought all right i know how to tell stories i know how to inform people and 110 people if i move the needle in america who cares we got it really good here if i move the needle in north korea a little bit the cost benefits through the roof i never thought of that actually i never thought of d reader from that perspective so when i set out to write it i'm like okay what can i do i'm not gonna be able to liberate the north korean regime what i can do is the camera right now is focused on at the time kim jong-il now kim jong-un and i can do just this just this a little bit and i go behind that guy who you think is funny clown there's millions of dead people about north korea in terms of look at those silly buffoons to those poor people so the fact that that little thing i can say with a straight face i did doesn't make me a great person but it does make me someone who if i have to go tomorrow i can say i did a little bit to make the world a better place what do you think is the meaning of life i think the meaning of life is um why are we here oh well that i'm a camus person so i'll give the kamu answer so there's two types of people those who know how to use binary no thanks thanks for relating to the audience one zero zero one two two [Laughter] down vote what kind of radical freak is this lex so and i use this example of my forthcoming book you go into a countryside a mountainside and you see a blank canvas on an easel and one kind of mentality goes this is it's just a blank canvas this is stupid this is what am i looking at and the other type goes what a great opportunity i'm in this beautiful space i have this entire canvas to paint i could do anything i want with it so i am very much of that type 2 person and i i hope others start to think of life in that way you and i have both been more successful than we expected to especially growing up and in ways we did not expect and when you're young you are so intent on driving the car and after a certain point you realize it's not about driving the cars you're being a surfer that you can only control this little board and you have no idea where the waves will take you and sometimes you're gonna fall down and something's gonna suck and you're gonna swallow some salt water but at a certain point you stop trying to drive and you're like this is freaking awesome and i have no idea where it's going to go beautifully put i know i speak for a lot of people first of all everyone loves the game you play on the internet it's fun you make the world not everyone they came for me hard but it makes the world seem fun and especially in this dark time it's uh it's much appreciated and we can't wait till the next book and the menu to come and to hopefully many more joe rogan appearances you guys do some great magic together that's you uh yeah you're you're one of my favorite guests on this show so i can't wait especially if you can make it before the election thanks so much for making today happen i'm glad you came down you're awesome thank you so much what a great compliment thanks for listening to this conversation with michael malus and thank you to our sponsors scm rush which is a seo optimization tool doordash which is my go to food delivery service and masterclass which is online courses from world experts please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars not a podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from michael malus conservatism is progressivism driving the speed limit thank you for listening hope to see you next time you |
Joe Rogan: Fear, Love, Chaos, and the Joe Rogan Experience | Lex Fridman Podcast #127 | the following is a conversation with joe rogan that we recorded after my recent appearance on his podcast the joe rogan experience joe has been a inspiration to me and i thank to millions of people for just being somebody who puts love out there in the world and being genuinely curious about wild ideas from chimps and psychedelics to quantum mechanics and artificial intelligence like many of you i've been a fan of this podcast for over a decade and now somehow miraculously am uh humbled to be able to call him a friend if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter lex friedman today's sponsors are neuro eight sleep dollar shave club and olive garden home of the unlimited breadsticks and brown red band's favorite restaurant check out the first three of the sponsors in the description to get a discount and to support this podcast i usually do full ad reads here i never ads in the middle but this time let's go straight to the conversation with a bit of guitar first [Music] do you ponder your mortality are you afraid of death i i do think about it sometimes i mean it does pop into my head sometimes just the fact that uh i mean i'm 53 so if everything goes great i have less than 50 years left you know if everything goes great like no car accidents no injuries but it could happen today this could be your last day it could be that's kind of a stoic thing to meditate on death there's a there's a bunch of philosophers ernest becker and uh sheldon solomon they believe that death is the at the core of everything wrote this book warm at the core so does that come into play in the way you see the world i think having a sense of urgency is very beneficial and understanding that your time is limited can aid you greatly i think knowing that this is a temporary time that we we have finite life spans i i think there's a there's great power in that because it it motivates you it gets you going i think being an immortal living forever would be one of the most depressing things particularly if everybody else was dying around you and i think one of the things that makes life so interesting and fascinating is that it doesn't last you know that you you really get a brief amount of time here and really by the time you're just starting to kind of figure yourself out who you are and how not to screw things up so bad it's like time's up the ride's over what about from your like from your daughter's perspective do you do you uh think about the world where and now and what kind of world you're going to leave them i do you worry about it i do yeah i do i do when i see these uh protests and riots and chaos and so much so much uh anger in the world today and then particularly today i think because of the the pandemic and the fact that so many folks are out of work and through no fault of their own and can't make ends meet and just people feel so helpless and angry it's uh a particularly divisive time it's a particularly turmoil filled time and uh it just doesn't seem like the world of a year ago even just feels very chaotic and dangerous and this and it's a small thing like in terms of the like the possibilities of things that could happen to the world like a pandemic like the one we've experienced it really just doubles the amount of deaths on a bad flu year so it relatively speaking is a small thing comparison to super volcano eruptions asteroid impact a real horrific pandemic or one that you know really wipes out millions and millions of people it's um it's stunning how fragile civility is it's stunning how fragile our our society really is that something like this can come along some unprecedented thing unprecedented thing can come along and all of a sudden everybody's out of work for six months and then everybody's at each other's throats and then politically everyone's at each other's throats and and then with the advent of social media and uh the images that you can see you know with the videos of police abuse and just racial tensions are an all-time high to a point where like if you asked me just five or six years ago like are have racial problems in this country largely been alleviated i'd probably say yeah it's way better than it's ever been before but now you could argue that it's not now you could argue it's no it's way worse in just a small amount of time it's way worse than it's ever been during my lifetime you cut well while i'm aware of it you know obviously when i was a young boy in the 60s they were still going through the civil rights movement but now uh it just seems very fever-pitched and i think a lot of that is because of the pandemic and is because of all the the heightened uh just tension the one i liken it to is um road rage because you know people have road rage not just because they're in the car no one can get to them but also because you're at a heightened state because you're driving fast and you know you're driving fast you know you have to make split-second movements and so anybody doing something like what people go crazy because they're they're already at an eight because they're in the car and they're moving very quickly that's what it feels like with today with the pandemic feels like everybody is already at an eight so anything that comes along it's like light it all on fire you know burn it down like that's part of what i think is part of the reason for a lot of the looting and the riots and all the chaos it's not just the people out of work but it's also that everyone feels so tense already and everyone feels so helpless and it's like you know doing something like that makes people uh it just it gives people a a whole new motivation for chaos a whole new motivation for for doing destructive things that i've never experienced in my life and your better days when you see a positive future what do you think is the way out of this chaos of 2020 like if you visualize at 2025 that's a better world than today what is that how do we get there what does that look like it's a good question i do i i can honestly say i don't know and uh i wouldn't have said i don't know a year ago a year ago i would have said we're going to be okay as much people hate trump the upon economy is doing great i think we're going to be fine that's not how i feel today today i don't think there's a a clear solution politically because i think if trump wins people are going to be furious and i think if biden wins people are going to be furious um and particularly like if things get more woke you know if people uh continue to enforce this uh forced compliance and make people behave a certain way and act a certain way which seems to be a part of what this whole woke thing is that is the most disturbing for me is that i see what's going on i see there's a lot of losers that have hopped on this and they they shove it in people's faces and it doesn't have to make sense like there was a black lives matter protest that stopped this woman at a restaurant they were surrounding her outside a restaurant they were forcing her to raise her fist in compliance this is a woman who's marched for black lives multiple times black lives matter multiple times and the people around her doing this were all white yeah it's all it's all weird my friend coach t he's a wrestling coach also uh on a podcast my friend brian moses his take on it is that black and he's a black guy he says black lives matter's a white cult and i'm like when you see that picture it's hard to argue that he's got a point it's clearly not all about that but there's a lot of people that have jumped on board that are very much like cult members because the thing about black lives matter or any movement is you can't control who joins there's no entrance uh examination so you don't go okay how do you feel about this what's your perceptions on that like how you like the the man who shot the trump supporter in portland you know that guy who murdered the trump supporter then the cop shot him that guy was walking around with his hand on his gun looking for trump supporters just want i mean he's a known violent guy who was walking around looking for trump supporters found one and shot one that has nothing to do with black lives matter he's a white guy he shot another white guy it's just it's just madness you know and then that kind of madness is uh it's disturbing to see it ramp up so quickly i mean there's been there's been riots in portland every night oh excuse me demonstrations for 101 days now 101 days in a row of them lighting things on fire breaking into federal buildings it's like whoever saw that coming nobody saw that coming so i don't know what the solution is and i don't know what it looks like in five years so 2025 to answer your question like it could be anything i mean we could be looking at mad max we could be looking at the apocalypse we could we could also be looking at an invasion from another country we could be looking at a war like a real hot war to put a little bit of responsibility on you like for me i've listened to you since the red band olive garden days that's the very beginning and uh there was something in the way you communicate about the world maybe there was others but you're the one i was aware of is you're open-minded and uh like loving towards the world especially as the podcast developed like you just demonstrated and lived this kind of just kindness or maybe even like lack of jealousy in your own little profession of comedy it was clear that you didn't you didn't succumb to the weaker aspects of human nature and thereby inspire like people like me who i was i was naturally probably especially in like the 20s early 20s kind of jealous on the success of others and you're really the primary person that taught me to um truly celebrate the success of others and so by way of question you kind of have a role in this of making a better 2025 you have such a big megaphone is there something you think you can do on this podcast with the words the way you talk the the things you discuss that could create a better 2025 i think if anything i could help in leading by example but you know that's only going to help the people that are listening i don't know what else i can do in terms of like make the world a better place other than express my hopes and wishes for that and just try to be as nice as i can to people as often as i can but i also think that i've fallen into this weird category particularly with the spotify deal where um you know i'm one of them now i'm not a regular person anymore now i'm like some famous rich guy so you go from being a regular person to a famous rich guy that's out of touch you know and uh that that's a real issue whenever you're talking about the economy about just real life problems it's it's interesting it kind of hurts my heart to hear people say about elon musk he's just a billionaire yeah it's an interesting statement but i think if you just continue being you and he continue being him people people i think people are just voicing their worry that you become some rich guy i don't even know if they're doing that i think they're just finding the way he describes it an attack vector right yeah and i think he's right i think they just uh they can dismiss you by just saying oh you're you're just a that you know you're a you know you're easily uh definable right but there i mean there's truth to that you if you're not careful you can become out of touch but you that that's an interesting thing like how why haven't you become out of touch like as a human off the podcast you you don't act like uh like you you talk to somebody like me you don't talk like a famous person or you you don't you don't act rich like you're better than others there's a certain listen i've talked to quite a few you have too but i've talked to especially kind of group of people that like nobel prize winners let's say they have sometimes have an error to them of arrogance yeah and you don't what's that about well you got to know what that is right like um that air of arrogance comes from drinking your own kool-aid you you start believing that somehow another just because you're getting praise from all these people that you really are something different usually it exemplifies there's there's something there there's where there's a lack of struggle you know and i think uh struggle is probably one of the most important balancing tools that a person can have and for me um i struggle mentally and i struggle physically i struggle mentally in that i like we were talking about on the podcast we did previously you and i on my podcast said i'm not a fan of my work i'm not a fan of what i do i'm my harshest critic so anytime anybody says something bad about me i'm like listen i said way worse about myself i you know i don't like anything i do i'm ruthlessly introspective and i will continue to be that way because that's the only way you could be good as a comedian there's no other way you can't just think you're awesome and just go out there you have to you have to be like picking apart everything you do but there's a balance to that too because you have to have enough confidence to go out there and perform you can't think oh my god i suck i know what i'm doing but i know what i'm doing because i put in all that work and one of the reasons why i put in all that work is i don't like the i don't like the end result most of the time so i need to work at it all the time and then there's physical struggle which i think balances everything out without physical struggle i i've i always make the analogy that the body is in a lot of ways like a battery where if you have extra charge it's like it leaks out of the top and it becomes unmanageable and messy and that's how my psyche is if i if i have too much energy if i'm not if i'm not exerting myself in a violent way like an explosive way like wearing myself out i just don't like the way the world is i don't like the way i interface with the world i'm too tense i'm i'm i'm i'm too quick to be upset about things up to but when i work out hard and you know i put in a brutal training session everything's fine well the first time i talked to you on jerry uh you were doing up to um so sober october and there's something in your eyes uh like i think you've talked about that you you know you exercise the demons out essentially so you exercise to get whatever the parts of you that you don't like out uh there is a dark there's a darkness in you there like the the competitiveness and the focus of that person that was a scary time in a lot of ways that sober october thing because uh my friends were all talking shit right because we're competing against each other and these fitness challenges and you had uh one point poor like you got a certain amount of points for each minute that you went at 80 percent of your max heart rate and one day i got 1100 points so i did seven hours on an elliptical machine watching the bathhouse scene from john wick where he murders all those people i watched him probably 50 times in a row i went crazy i went crazy but i went crazy in a weird way where it brought me back to my um my fighting days it was like the same that person came out again it's like well i didn't even know he was in there it's like they're like like like an assassin like a killer like i felt i felt like i felt like a like a different person is it echoes of like what mike tyson talked about essentially like the but no orgasm in their oceans all the crazy shit that he was is there is there that is there a violent person in there oh yeah yeah there's a lot of there's a lot of violence in me for sure i don't know if it's genetic or learned or it's because during my formative years from the time i was 15 until i was 22 all i did was fight that was all i did that was all i did all i did was train and compete that's all i did that was my whole life is it connected to uh so you uh your mom and dad broke up early on is it connected to the dad at all i i'm sure it's connected to him also because he was violent and it made me feel very scared to be around him but i also think um it's connected in who he was as a human is transferred into my dna you know i think there's a certain amount of i mean i mean to be prejudiced against myself i look like a violent person you know if i didn't know me i'm just even the way i'm built and not even just the working out bar just the size of my hands and like there's the width of my shoulders like there's most likely a lot of violence in my history in my past and my ancestry and i think um i think we minimized that with people like so much of your behavior like when i see my daughter i have a one daughter that's obsessive in terms of like she wants to get really good at things like could she and she'll practice things all day long and and it's 100 my personality like she's me in a female form but without the anger as much and without the um fear like she's you know loving household and everything like that but she has this intense obsession with doing things and doing things really well and getting better what's the point we have to tell her to stop like stop doing handsprings in the house stop stop come on just sit down have dinner like one more one more like she's just like she's like she's psycho yeah um and i think there's a lot of behavior and personality and a lot of these things are passed down through genetics we don't really know right we don't know how much of who you are genetically is learned behavior you know nature and nurture we don't know if it's learned behavior or whether or not it's something that's intrinsically a part of you because of you know who your parents were i think there's there's certainly some genetic violence in me there's something you channeled it yeah you figured out is basically your life it's a productive exploration of how to channel that yes try how to figure out how to get get that monkey to sit down and calm down there's another person in there like this is a calm rational kind friendly person who just wants to laugh and have fun and then there's that dude who comes out when i did sober october that guy's scary i don't like that guy yeah a guy just wants to get up in the morning and go you know it's like it's um i mean when i was competing it was necessary but it makes me remember i didn't really remember what a what i used to be like until that it's like when i'm working out seven hours a day yeah and just so obsessed and and all i was thinking about was winning that's all i was thinking about like if they were if they were working out five hours a day i wanted i wanted them to know that i was going to work out an extra three hours and i was going to get up early and i was going to text them all hey pussies i'm up already taking pictures send selfies you know i was like you're going to die i kept telling them you're all going to die and try to keep up with me you're going to die you weren't fully joking no i wasn't joking at all that's what i was fucked up about it was the scary thing when i interacted with goggins and what i saw in you on during that time is like this guy like like this is why i've been avoiding dave ganga's recently [Laughter] is like because he wants to meet he has to do like talk on this podcast but he also wants to run an ultra marathon with me and i felt like this is a person if i spend any time in this realm if i spend any time with the joe rogan of that sober october like i might have to die to get out like there's this kind of uh yeah there's a competitive aspect that's super unhealthy i mean you saw the video that we watched earlier today of goggins draining his knee that would stop me from running ever again because i would think in my head okay i'm gonna ruin my cartilage i'm gonna need a knee replacement i would start thinking i would go down that line but he is perpetually in this push-it mindset you know what he talk calls the dog in him you know he's got that dog is in him all day long and he feeds that dog you know and that's um that's who he is that's one of the reasons why he's so inspirational and he's fuel for millions and millions of people i mean he really is he motivates people in a way that is so powerful but it can be very destructive i just i know i know now especially after the sober october thing that that thing's still in me you know i didn't know because i really haven't done anything physically competitive except one time i was supposed to fight wesley snipes it came out then too that came out too that got creepy too but luckily that never happened but that was many months of training like training twice a day every day kickboxing in the morning jiu jitsu at night i was just going going and going and going and i was just thinking just all day long and it but it fucks with all the other aspects of your life fucks with your friendships fucks with your your fuck with my comedy fucks with everything because that mindset is not a mindset of an artist it's a mindset of a conqueror the concur yeah destroyer that's why it's so interesting to see mike tyson make the switch it's clear that like whatever that is however that fight goes he made us there's a switch of a dif he stepped into a different dimension roy jones jr is coming on my podcast soon and uh you know roy's gonna be on uh before the fight i'm i'm so curious to see how it goes down but genuinely concerned because mike tyson is a heavyweight and roy jones at his best was 168 pounds and um i don't know if roy has that room in his house mental house of where mike tyson goes i don't know i don't know if he has a rope mike doesn't have a room he's he's got an empire in there with the open side the door there's a whole empire in his head and he's he's in that firmly you know when he got out of the weed and and started training again like you could see it in him and by the way physically in person he looks spectacular he looks like a fucking adonis i mean he looks ready to go yeah it's crazy yeah i watch the videos of him what about you uh have you ever considered competing in jiu jitsu no for that very reason i don't want to get obsessed that's my my number one concern i had to quit video games yeah when we were playing video games at the studio i had to quit because i was playing five hours a day like out of nowhere all of a sudden i was playing five hours a day i was coming home late for dinner i was ending podcasts early and jumping on the video games and playing i get obsessed with things and i have to recognize what that is and these competitive things like competitive especially like really exciting competitive things like video games they're very dangerous for me the ultimate competitive video game is like jiu jitsu and um if i was young i most certainly would have done it if i didn't have like a very clear career path it was something that i enjoyed my concern would be that i would become a professional jiu jitsu fighter when i was young and then i would not have the energy to do stand up and do all the other things that i wound up doing as a career when i was um 21 i quit my job teaching i was teaching at boston university i was teaching taekwondo there and i i knew and i also had my own school in revere i knew i couldn't do it right and also be doing stand-up comedy i knew i couldn't do both of those things there was no way you have to be cognizant of uh that obsessive force within you to make sure uh yes i i have to know how to manage my mental illness right that's that's a very particular mental illness and i think that mental illness again my formative years from 15 until i was you know 21-ish 22 those those years were spent constantly obsessed with martial arts that was my whole day i mean i trained almost every day the only time i would not train is if i was either injured or if i was exhausted if i needed a day off but i was obsessed and so that part of my personality that i haven't nurtured is always going to be there under the surface and when you it gets reignited by something it's very weird it's a weird feeling and it can get reignited with a video game it can get reignited with anything that that obsessive that you know whatever it is that competitive demon yeah the way you talk about guitar i know you would love fall in love with playing guitar but i think you're very wise to not touch that thing that's why i want golf i have friends who want to golf i'm like fucking with that thing so a lot of people ask me about uh like what's uh joe rogan's jiu jitsu game like like like like assuming that i i somehow spend uh hours rolling with you before and after we interact i mean what's a good uh you should at some point show a technique or something that'll be fun sure i mean i've got what's your game what's your name oh there i saw i saw you doing a i think had an arm uh something online yeah i did that was i fucked my neck i'm doing head and arm chokes i did them so much that i i you know because you use your neck so much with head and arms chokes i developed like a real kink in my neck and uh it turned out i had a bulging disc and uh you know so you do it on that just one side well it was uh no i could do it on the left side but i definitely am better on the right side the right side was my best side so if you were to compete let's say like what's your a game what would you go from standing up how would you go to submission would you pull guard would you take down what how would you pass guard what's i don't have good takedowns i mean i was not a good wrestler so i would most likely either pull guard or i would pull half guard do you have a good guard yes are you comfortable being on your butt on your back yes i'm very i'm very flexible so i have good my rubber guard is pretty you go to right yeah i have good arm bars and good triangles off my back but um i also have a very good half guard but my top game is my best i have i have a very strong top game you have a hashtag card you have a preference of like what kind of guard and how to pass that guard and uh like yeah like is there a specific game plan like you would you double under hooks from half guard is the game plan for me if i can get double underhooks from half guard i could sweep a lot of people under hooks of what sorry the arms are so half guard lock down right half card go into lock down double under hooks got it clinched to the body suck the body into the type pressure and yeah massive pressure and then inch my way into a position we call the dog fight and inch my way to a position where i could get the person on their back yeah that's what because you did show me i still disagree with you about the thai thing um that you can choke so wrong so wrong uh well it's not wrong with you with you it's wrong because you you know i think there's a system where i i've have this thing with donna here we're gonna figure it out okay but uh let's have a little velcro in the back let's see that's you're just not cheating you're not you're the exact that's cheating uh yeah you did i did feel when you showed me i think you showed me the rubber guard because it's still a god that's a little bit foreign to me i just felt that you can immediately feel not with the rubber guard just but the way you move your body is you're um like a shanji type of guy who knows how to control another human being so like some people are a little bit more i would say agile and technic like playful and kind of loose loose and they work on transition transition transition you're a control guy like you know how to control position in an advanced position donahue is the same way he's all about control my game is smush that's my game smush you grab a hold of you once i have you why would i let you go that's my thought is like why would i let you go i just want to incrementally move to a better position until i can strangle you but i'm much more into strangling people than anything else yeah which is a great mma approach for jiu jitsu well too many people don't tap when you get their arms you know and i'm it's not i'm not opposed to arm bars i love arm bars but everybody goes to sleep yep and and quit from pressure too i mean yeah quit mentally that's nothing like you can't breathe you know if you got a guy who's like a really good top game guy and he mounts you and i'm a big fan of mounting with my legs crossed you know like a guard like a top guard and so i can squeeze with both legs smush and i'm just i'm just looking for people to make mistakes and slowly incrementally bettering my position until i can get something locked up yeah i love jiu jitsu though man i just wish it didn't injure you yeah you know jiu-jitsu is like if your joints were more durable they could figure out a way to make joints more durable god i could do jiu jitsu forever yeah so much fun i actually i talked to this uh roboticist russ tedrick he builds one of the world-class people that builds humanoid robots you're interested in boston dynamics yeah they keep people in that kind of robotics so i asked him the stupidest question of like how far are we we from uh having a robot be a ufc champion and uh yeah it's actually a really really tough problem it's it's it's the same thing that you know makes somebody like danielle comey like on the wrestling side special because you have to understand the movement of the human body in ways that so difficult to teach it's so it's so subtle the timing the pressure points like the leverage all those kinds of things that's just for the clinch situation and then the movement for the striking is very difficult as long as you're not allowed as a robot to like use your natural abilities of having a lot more power right a lot more power and more durable right the human body like especially meniscus like like you see the the heel hook game like everybody's involved in leg locks and heel hooks like all those guys wind up with torched knees everyone's got torched knees everyone's knees are torn apart you and you don't grow new meniscus you know that's like one of those joints where man when it goes this is and those guys are 28 years old blown out knees let me ask the ridiculous question what do you think we're talking about cops what do you think uh is the best martial arts for self-defense for sure jiu-jitsu yeah wrestling right i think grappling i should say with judo as well especially in a cold climate if you get someone who's got like a heavy winter jacket on my god like judo is an incredible plus concrete that's the worst place to be with a heavy winter jacket with a judo specialist and you're standing up with them oh my god but i think grappling because in most self-defense situations it usually winds up with grappling you're definitely better off though knowing some striking because there's nothing more terrifying than when you go to take someone down they actually have takedown skills but they can fight and so they have takedown defense and they know how to fight and then you don't know how to stand up like the worst thing in the world seeing someone like reaching who doesn't know how to do striking and someone cracks you what about all that krav maga talk which is like you know the whole line of argument that says that jiu jitsu and wrestling and all these sports they fundamentally take you away from the nature of violence so they're just teaching you how to play versus the reality of of um violence that is involved in like a self-defense situation that is is a totally different set of skills would be needed in general the people that say that jiu-jitsu or other martial arts don't they it's more of a sport and they don't really understand and they don't really understand violence in general the people that say that suck yeah that's anybody who thinks like someone's like you know hey man i'll just bite you i'm like are you gonna bite me okay do you think i'm gonna bite you too what do you think of that what if i punch you in your fucking face you think you're still gonna bite me when you can't even see yeah when you you you barely even know you're alive and i choke you unconscious if someone's really good at jiu jitsu good luck stabbing them with your keys you know you don't have a chance you don't have a chance if someone's much better you and they trip you and get you on your back and then they fucking elbow you in your face and get a head and arm choke on you all that krav maga it's out the window son you're way better off learning what works on train killers like this whole idea that you're going to poke some of the eye and then you're going to kick him in the nuts and like you're you're going through these drills that yeah it's good to know what to do if you run into someone who doesn't know how to fight it's way better to know what to do to someone who knows how to fight that's the best thing learn how to fight against people who know how to fight like all that practice self-defense and they're gonna it's gonna come at you with a knife you're gonna grab the wrist and do that like it's good to know self-defense but it's much more important to understand martial arts comprehensively when you understand martial arts comprehensively like there's no crop i shouldn't say there's no krav maga guys but it's it would be shocking if a krav maga guy and a mixed martial arts guy had a fight and the mixed martial arts guy was a trained killer all around didn't fuck that guy up that's that's what i would expect would happen i would i would i would not think that some guy who has a little bit of this and a little bit of that and prepares for the streets is going to be able to handle a person who trains with killers on a day-to-day basis who rolls with jiu jitsu black belts who trains with muay thai champions like here it's the best martial arts of the martial arts that work on martial artists not the martial arts that work on untrained people what about we're in texas now what about guns that's the best martial art no but would you like uh in this crazy time should people carry guns it's not a bad idea to have a gun because if you need a gun you have a gun and if you don't need a gun if you're a person with self-control you're not going to use it you're not going to just randomly use it but you have something to protect you this is the whole idea of the second amendment the whole idea of the second amendment gets distorted by mass shootings or by terrible people murder people and do terrible things but it's that's all those things are real but they don't take away from the fundamental efficacy of having a firearm and defending your family or defending your life and there are real live situations where people have had firearms and it's protected them or their loved ones or they've stopped shooters there's there's many of these stories but people don't like those stories because then it it tends to lead to this gun culture argument is pro-gun culture argument that people find very uncomfortable it's it's human beings are messy and we're messy in so many different ways right we're messy uh emotionally we're messy messy physically but we're also messy in what's good or bad what's we want things to be binary we want things to be right or wrong you know one or zero and they're not but but there is crime in the world and there is violence in the world and you're better off knowing how to fight and you're betting better off knowing how to defend yourself and you're better off having a gun and yeah i generally think that guns i do like the idea that guns second amendment helps protect the first amendment there's a kind of sense that makes puts me at ease knowing that so many people in this country have guns that uh i mean alex jones i just listened to one episode of infowars for the first time boy is he he reminds me like when i drank some tequila i felt like i'm going to some dark places today that's how i feel like listening to him but uh he talks about like that it's he worries about martial law so basically government overreach by which happened throughout history like there's there's something to worry about there but it's it puts me at ease knowing that so much of the population has guns that people government would think twice before uh instituting martial law on cities but i actually was asking almost like on the individual level i maybe shouldn't say this but i don't yet own a gun and i felt that if i carry a gun statistically just for me as a human knowing my psychology i feel like i'm more likely to die like i feel like i would put myself in situations that i shouldn't like the way i i will see the world will change because my natural feeling is like when somebody when i was in philly and i knew late at night in west philly when some guy looks at you you can immediately calculate that this is a dangerous human being there it starts with a monkey look at first like i'm a bigger monkey than you and that's where i found like for example i'll do the beta thing of just looking down and turning away and just getting out of trouble like very politely and basically that kind of approach because if you have a in terms of getting out of serious violence situations like serious something where you could die versus if i had a gun i feel like i would want to be that that would be that cowboy monkey thing where i would want to put myself in situations where i'm a little bit of a savior even of myself and almost create danger which can no longer like the escalation of which i can no longer control well you're talking about taking a gun somewhere versus having a gun in your home yes yes i mean carry on me that's a different situation and much harder to get a warrant for or a license for that you know control concealed carry licenses especially in massachusetts they don't come easy a little message yeah that's a whole nother thing yeah you're saying gun in the home yeah a gun in the home having a gun having knowing how to use a gun like i know how to use a gun i've trained you know many hours learning how to shoot a gun at tactical places you know there's a bunch of videos of me doing it on uh instagram i i practice and i think it's good to to understand how to be accurate so i've been a fan of your podcast for a long time you don't often talk about it because you're always kind of looking forward but if you look at the old studio they just left is there some epic memories that stand out to you that you like you almost look back i can't believe this happened oh yeah almost too many of them to count is that something that pops into mine now all of them elon musk blowing that flamethrower in the middle of the hallway i got a video of that have you seen the video of it yeah yeah i think you posted on instagram i think i did too yeah he's a madman um having bernie sanders in there uh you know just uh all the fun fight companions we did and all the crazy podcasts with joey diaz and duncan trussell and there were so many there were so many moments you know it's um podcast is this is a weird art form and it almost seems like it sounds silly but it almost seems like something that chose me rather than i chose it i think of that all the time in some strange way it's like i'm i'm showing up as like an antenna and i just plug in and twist twist on and then i i take in the thing and i put it together and i'm like a passenger of this weird ride yeah you you've talked about this before i really like this idea of that human beings are just carriers of these ideas yeah ideas are the ones who are breeding yeah in a sense like the idea found you as a useful brain to use to spread itself through the podcasting medium yeah something that that's a on uh but did because when i think about your podcast i think about joey diaz i think about all those comedians you've had i mean i think you've had joey on i mean maybe close to 50 times some crazy number is there i mean he's over the top offensive just that's who he is to the core is there some sense where you you wondered like whether it's right to have the spotify episode number one with duncan dressler that's why we wore nasa suits and we got high as fuck it's like that's the whole idea behind it i mean can you introspect that a little bit like can you think like what is that because that's rare it's such a rare thing to do because they they're you're not supposed to talk to duncan trussell with a huge platform that you have five hours why not because donald trump apparently watches your podcast so so just the idea that there's these i mean that's what i think about you know these ceos write to me that they listen to the podcast that that i do and i have somebody like a david fravor and i was nervous about it i was nervous to have a conversation for me david fravor is a duncan trestle which is like just because of his experiences with the ufos yeah just even just the way he sees the world because he is open i don't know if he's always like this but he opened himself to the possibility of unconventional ideas most people in the scientific community kind of say well i don't really want to believe anything that doesn't have a lot of hard evidence right and so that was to me like a step and as the thing somehow becomes more popular that it becomes this fear of like well should i talk to this person or not and i mean you're an inspiration and saying like do whatever the hell you want you have to well first of all i have what you call fuck you money and if you have fuck you money you don't say fuck you what's the point of having the fuck you money you're wasting it like you're wasting the position like someone said to me like why do you why do you like sports cars so much like how many cars do you have a bunch of cars so because if i was a kid and i said hey if i was that crazy rich famous guy like i don't want to have a bunch of cool fucking cars like so i so i would do that like because that not everybody gets to do that like if you're the person that gets to do that you're kind of supposed to do it like that's if you if you want to if that really does speak to you and you know um i've talked to you about this before but muscle cars specifically once from the 1960s and the early 70s they speak to me in some weird way man i could just stare at them like i have a 65 corvette i walk around it sometimes at night when no one's around what's your favorite muscle car like what's your most badass late 60s the probably that car probably that 65 corvette yeah i walk around it when no one's around i think i've during the 69 corvette is there a particular year that uh just 65 is uh generation two 69 is generation three 69 is like the it's even more curvy they're both awesome just awesome in different ways but i just love muscle cars for whatever reason but but the point is like i like what i like and if i can do what i want to do i should do what i want to do and it's not hurting anybody and the thing is like i would do the duncan podcast if no one was listening right right if it was if we were just starting to do a podcast together and uh no one cared and it got like 2 000 views which we did for years a long time i would do it with duncan and we would get high and we'd talk crazy shit about aliens and spaceships and maybe dude maybe ideas are living life forms and they're inside your head and that's how things get man yeah man i've just kind of morphed me and him together in that because the life form ideal life form idea is mine that i've i've really really think about a lot i think about a technical side by the way like uh i when i heard you say that because i've been thinking i was like oh whoa that's interesting that it might be they might be alive because they i don't know what the fuck they are but when someone has an idea for uh you know whatever an invention a toaster and then they think about this all it need is like these heating elements and a spring and then it pops on the stunts i have a timer and then they build this thing now also it's alive it's like you manifested it in a physical form a toaster is not the best example but a car a airplane you're thinking about a thing like an idea comes into your head and you can say oh well it's just creativity it's a part of being a person that's how we invented tools and how you know we became better hunters all those things are true it's i'm not saying that there's some magic to what i'm saying but there's also a possibility that we're simplifying something by saying that it's just creativity that it's just a natural human inclination to invent things but why is it possible that ideas like creativity like we are the only animal other than there's a few species that create things like bees make bee hives and but it's very they're very uniform you know some animals use tools you know like you know chimps will use like sticks to get termites and things like that but there's something about what we do that's it makes you wonder because we look at this just look at this room that we're in look at all these electronics look at all this crazy shit that human beings have invented and then built upon others inventions improved and innovated these all came out of ideas like the the idea they it germinates in someone's head it bounces around they write it down they share it with others the other people who have similar ideas or ideas that are complementary they work together and they they change the world and the new thing in that is the idea is not the people it's like we think we found the ideas but it's more like the ideas the ideas found us fine you yeah they're literally in the in the air yeah they come to you i always felt like that with bits like when i come up with a bit that's why i'm i'm always telling people about the stephen pressfield book the war of art because he talks about uh respecting the muse and the idea that your ideas come when you sit down and you do the work or you sit down like a professional and you you talk to the muse like come tell me what to do like if the muse was a real thing as if it amuses like a some mystical creature that comes and delivers you ideas even if that's not real that's how it works yeah it does work like that if you do treat it like it's a muse and you treat it with the respect and you you treat it like a professional the ideas do come to you i never thought about what he's doing he's just sitting there waiting for the idea that's trying to breed to find him yeah there's that's a that's a trippy thing if you show off trippy if you show up and put in the time and focus your energy on that the the ideas they will arrive that will arrive and that's the same with writing comedy like there's been many many times where i'll come home from the comedy store and i just sit down and start writing and i just i've i got nothing there's nothing there i'm just writing it's all bullshit nothing's good it's just like hmm and then all of a sudden bam there's the idea melson i can't stop and then you know a couple hours later and i'm like whoa and then the next night i'm on stage and i'm like how about that boom it gets this big laugh i'm like holy shit and i know that came out of the discipline to sit down and call the muse i mean the cool thing is the ideas have found you to like oh i'm going to use this dude like he seems to have a podcast that's popular yeah i'm going to breed inside his brain yeah and spread it to others yeah an or an inventor you know i'm going to use this guy who's like desperately seeking some sort of a a product to bring to market some guy who wants to invent things he's thinking about inventing things all the time like these ideas that weasel their way into your head and it seems to me also that your your the frequency that your mind operates under has to be correct because one of the things about creativity seems to be if you think about yourself a lot if you're really into yourself or your image or or you're selfish those ideas are not they don't find you yes that's funny the creative yeah yes it stifles the opportunity that the idea has for defining yes which is one of the reasons why joke thieves people that steal jokes are terrible writers there's never like really good writers who are also joke thieves it's just joke thieves and then you know when they have to write on their own if they get exposed they become terrible comedians they're of a shadow of what they were when they were stealing other people's ideas because the thing that would make you steal a person's idea is that ego part the the like the wanting to claim it for yourself to wanting to be the man i'm gonna or the woman you know you want to be the person who gets out there that says it and everybody's gonna love me for it like you can't think like that and be creative it requires a humility and it requires a detachment from self in order to create like when i'm writing i'm blank i'm like i'm just staring i'm like i'm just the part of my mind that's active is not like me it's like this weird core function part where i'm not i'm not aware of my personality i'm not aware i'm not aware of anything i'm just trying to put it together in a way that i know works and just being there being present yeah pressfield is just i'm a big believer just sitting there you're not staring at a blank page putting in the time yeah and sometimes it's not that way sometimes it's an inspiration like sometimes i'll be sitting there at dinner and i'll be like i'll be right i got an idea and my wife is really cool about that i'm like i have an idea and i i have to just run out of the room real quick and i write it down on my phone and then i can come back you know because those are those are like little gifts that you get sometimes from the universe out of nowhere and some people rely only on those gifts you know and i've talked to comics about it like i can't come on my best ideas when i don't write i'm like no i do too i come up with great ideas when i don't write but i also write like you can do both of those things they're not mutually exclusive you mentioned fuck you money i i feel like i have fuck you money now a year ago i was at zero i have fuck you money now because probably my standards my i i don't need much in this world but because also probably because of you uh but it's 300 to 400 000 people listen to every episode i do and a lot and that result is weird it's a successful television show on cable yeah it's crazy but it's all you it's yeah it's hilarious that's amazing but at this point that also resulted in fu money in a sense that i don't um you know i don't need anything else in this world but so by way of asking i've looked up if you've inspired me for a long time do you have advice you've done this on the podcast side of life do you have advice for somebody like for me and somebody like me going on this journey eric weinstein is going on this journey is there advice both small and big that you have for somebody like me the advice is to keep doing what feels right to you and do what you're doing obviously it's resonating with people if you're getting that big of an audience and i've listened to your podcast you're very good at it so just keep doing it the way you're doing it um don't let anybody else get involved what about you've connected i think you met jamie at the comedy store i met him at the ice house at the ice house well i think i met him at the comedy store but then uh we talked at the ice house i mean what you'd have to ask him yeah did you think deeply about because like you know you basically have nobody on your team and and so it almost feels like a marriage where is it were you selective about like a jam to somebody to bring into your little circle well jamie's exceptional he is he truly he's a special i mean he might have grown i don't remember how he was in the early days maybe you could say but he's definitely better at it but he right away he's exceptional he's got very little ego yes he's he's not a guy who needs a lot of attention he's not a guy who um overestimates uh anything like in terms of like a negative or positive like his uh like his his interpretation of whether it's uh good things that happen to the show or bad things that happen the show he just takes it all like flat he's chill he's just cool as fuck and he's so smart and he's so good as an audio engineer and as a podcast producer he's the best but he's basically one of the only people on you on this whole team so yeah how do you find i mean when you let people in i mean i'm sure other people wanted to get involved like why don't you have a co-host like you basically kind of well do you well here's the problem with the co-host like when you and i are talking when we're talking i'm tuned in to you and i'm waiting to hear what you're saying and i'm listening and i'm interpreting it and then i'm calculating whether or not i have anything to say whether to let you keep talking whether i maybe have a question that lets you expand further or whether i have a disagreement or like there's a dance that's going on now when there's another person there chiming in too it fucks the dance up it's like dancing like if you're doing an uh a dance with someone you know like if you're slow dancing with someone and then a third person's there stepping on your feet sometimes it's fun yeah sometimes having a third person is fun comedy podcast sometimes it's fun um kind of structured yeah debate structures but even then it gets difficult because people talk over each other and also um i find that without headphones it's way easier to talk over each other you make mistakes yeah you don't you don't hear it the same way when you have headphones you i hear what you hear it's all one sound and i the audience hears exactly or rather i hear exactly what the audience hears whether it's over here my voice is louder than yours because you're over there and if i don't have headphones on it doesn't it's not all together on that point one of the interesting things about your show is uh you don't almost never have done and you just generally don't do remote like um sorry not remote calls but you don't go to another person's location like you have only done a few a small handful and then just like uh will the sapolsky he should be yeah he should do this but actually we went back and forth on email i told him he needs to get your his ass back in in this in the studio uh he's working on a book i was a fan of his a long time ago because i became obsessed with toxoplasmosis you know and uh i uh i've reached out to him a long time ago before he uh was willing to do it but then i caught him in downtown l.a he was there for something else and i just greedily snatched up an hour of his time well he doesn't get i think some of those folks don't get how much magic can happen in this podcast studio like bigger than anything they've ever done in terms of their work not i'm not talking about reach but in terms of the discovery of new ideas there's something magical about conversation like that like somebody as brilliant as him if he gives himself over to the conversation for multiple hours at a time that's another place where you've been an inspiration where i like you know i'm getting more and more confident of telling people like an elon musk that like you know a lot of ceos are like well he has 30 minutes on his schedule i'm like no three hours [Laughter] and then they're like so some say no and then they come back these people have started coming back to like okay we're starting to get it they start to get it and you're a rare beacon of hope in that sense that there's some value in long form they think that nobody wants to listen for 30 for more than 30 minutes they think like i have nothing to say but the reality is if you just give yourself over to like the three hours just let it go three hours four hours whatever it is there's so much to discover about what you didn't even know you think yeah yeah you have to be confident that you could do it and uh in the beginning i just did it because that's what i wanted to do and no one was listening so i've always been a curious person so i've always i've always been interested in listening to how people think about things and how and talking to people about their mindset and just and expanding on my own ideas and just talking shit and so we would have these podcasts and they would go on forever and my my friend ari i've i never let him die and never let this die down i've let him uh forget this he was always like you have to edit your podcast i'm telling you right now you're fucking up i go why he's like because people are not going to listen to it i go they don't have to yeah i go you listen to part of it he goes he goes just do it just i'm telling you trust me cut it down to like 45 minutes that's all you need and i'm like no no i don't think you're right i i like listening to long-form things no one knows that kind of time i go okay i'm going to do it i'm just going to keep doing it this way so and it it sticks too good no he doesn't listen to his these are like two and a half hours long now you won but you wouldn't like say i mentioned to you this before this is gonna happen it's actually made a lot of progress toys i'm gonna talk to putin but you wouldn't travel to putin if you want to talk to you putin is a dangerous character he's not he's not you're talking to ever seen the thing with uh jerry craft where they stole his super bowl ring yeah yeah that was i think that was a little bit of a misunderstanding oh really i think it's a little bit he just decided he's going to steal that super bowl ring kind of i think that was a kind of he thought can i see your ring he shows him his ring then he puts it on says i can murder somebody with this ring so he and then he walks off with it it's possibly he did it uh as a he's a big believer in displays of power yeah so like it's possible he did that but on i think he sees himself as like a tool with which to demonstrate that russia still belongs on the stage of the big players and so he a lot of action is selected through that lens but in terms of a human being outside of any of the evils that uh he may or may not have done he is a really thoughtful intelligent fun human being like the wit uh and the depth from the jre perspective is really interesting i'm like his manager now selling the he's a judo trying to get trump he's really good at judo i i have seen him practice judo he's he's a legit black belt and not only that he loves it not just skill wise but to talk about it to reason about it to think about it to mma as well so yeah maybe it'd be a good conversation but you wouldn't travel to him well this holds your principle so that's the core of the advice or whatever i would rather here's the thing there's not a person that i have to have on the show right and i'm happy to talk to anybody i'm just as happy to talk to you as i am to talk to trump as i am probably more happy to talk to you as i am to talk to mike tyson as i am to talk to joey diaz i like talking to people i enjoy doing podcasts i enjoy talking to a variety of people and i schedule them based on i want to like i try not to get too many right-wing people in a row or too many progressive people in a row i don't want to get repetitive i try not get too many fighters in a row i try to balance it out not too many comedians comedians are the one one group where i can have three four in a row five in a row because that's my tribe you know those are my people it's easy we could talk about anything it's a weird dance you know the conversations that you're doing on a podcast are there they're a strange dance and you want to you know you want to not step on your own feet and you want to make sure that you do it in a way do the podcast in a way that's entertaining for people and it's it's the conversations are learning how to talk to me it's a weird skill yeah it's a weird skill that took a long time for me to get good at and i didn't know it was a skill until i started doing it and then i i just thought you were just talking like i was just i know how to talk we'll just talk to people and then along the way i realized like oh and then when you talk to people that are bad at it you realize that it's a skill like particularly one of the things about my people about comedians is a lot of them tend to want to talk but don't want to listen right so they're waiting for you to stop talking so they can talk but they're not necessarily thinking about what you're saying you know and they're just just waiting for their opportunity or they talk over you or they and i try real hard not to do that sometimes i fail but my when i'm at my best i'm i'm dancing yeah ultimately the skill conversation is just really listening mm-hmm like really and listening and thinking listening and thinking and being like genuinely curious and and really having um you know a take on what they're saying and and uh and maybe a follow-up question or maybe you know just got it's got to be real it's got to be authentic and when it is authentic and it's real it resonates with people like they're listening and they go oh like i'm locked in with the way you're thinking like you two guys are in a conversation and i'm locked in you know when she talks and you listen i i'm listening to you know when he says something to her when she says something to to him like there's a thing that happens during conversations where you're there like you're listening to and it's with me when i listen to a good podcast i feel like i'm in the room i feel like i'm in the room and i'm like like i'm like the friend that got to sit down and listen like oh yeah it's a great conversation yeah you know i love conversations so i love listening to them and i love putting them together and the fact that this podcast has gotten so fucking big it it's stunning to me it blows me away i never anticipated it never thought for a second that that stupid thing that i used to do in my couch in my my office was the biggest thing i've ever done in my life by far like people used to make fun of it like there's a comedy store documentary that's coming out and one of the parts of the documentary is my friend tom segura when he first started doing my podcast he would he would be leaving and he would talk to red band he's like what the fuck is he doing yeah like why is he doing this like who's listening he's like oh some people like it yeah and it's like fucking nonsense waste of time and like in the the documentary it shows like 2 000 views like one of the early ustream episodes hilarious and they don't just like it really they uh they form a friendship with you it's like uh even me when people come up to me like the love in their eyes is kind of beautiful it's weird right yeah it's like you're part of their life yeah and it i don't know it's it's also heartbreaking because you realize you'll never really get to know them back like because they they clearly are friends with you yes yeah and it's sad to see a person who's clearly brilliant and interesting and is friends with you but you don't get a chance to return that love and uh i mean my kids it took them a while to figure out what's going on but uh people come up to me and uh you know they would say something like hey man i fucking love you thanks man all right hey brother nice to meet you my daughter was like sick she's like do you know him yeah i'm like no i don't know him she's like how does he know you think this is a very weird conversation i used to have with young kids when i'd explained i do this thing called the podcast and millions of people listen so now one of my daughters is 12 and one of her friends is 13 and he's a boy and he goes to school with her and he's obsessed with me and so she's weirded out and she says to him i don't think you like me i think you're just into my dad fucking weirdo she's gonna have that conversation in a few stages in her life oh that hard conversation with a boyfriend yeah probably yeah that well that's the thing about men too this this podcast um is uh my podcast is uniquely masculine i'm a man and i'm i'm not i i'm also a man that doesn't have to go through some sort of a corporate filter i'm not going through executive producers who tell me don't don't have this guest on don't talk about that you know that we looked at focus groups and they don't they don't seem to like when you do this like there's none of that i just and i i i just do it so if that's so i have a whole podcast where i just talk about cars and people like i don't want to hear you talk about cars well good congratulations you found what you like here's good news there's 1500 other ones go listen to the other episodes where i don't talk about cars you know you don't have to listen and it's not like your brand you just no are who you are and that's what you do but it's like it's authentically what i'm interested in all the podcasts whether i'm talking to david fravor about his experience with ufos whether i'm talking to david sinclair about life extension whether i'm talking to you about artificial intelligence or what it's because i want to talk to these people and that that resonates i i like when people are into shit you know i've talked about this before like things that i have no interest in making furniture but i like this pbs show where this guy makes furniture by hand yeah i love watching it craftsman because he's so into it yeah he's examining this and polishing that i'm not gonna do that i don't give a fuck about furniture furniture for me is function like this desk function it works but i love when people are into it you know and i'm happy that someone can make it and they do a great job but i'm not i'm not interested in the the task is or the even the finished product as much as i'm interested in someone's passion for something the passion that they've put into this that shines through last question i sometimes ask this just for to uh what is it to challenge to make people roll their eyes to make legitimate scientists roll their eyes ask what is the meaning of life according to joe rogan i do not think there is a meaning i think there's many many meanings of life i think there's a way to navigate life that's enjoyable i think it requires many things it requires first of all requires love you have to have loved ones you have to have family you have to have friends you have to have people that care about you and you have to care about them i think that is primary then it also requires interests there has to be things that stimulate you now it could be just a subsistence lifestyle there's many people that believe and practice this uh lifestyle of just living off the land and hunting and fishing and living in the woods and they seem incredibly happy yeah and there's there's something to be said for that that is an interest right there's something and there's a there's a direct connection between their actions and their sustenance they get their food that way they're connected to nature and it's very satisfying for them if you don't have that uh i think you need something that is interesting to you something that's you're passionate about and there's far too many people that get sucked into living a life where you're just doing a job you're just showing up and putting in your time and then going home but you don't have a passion for what you're doing and i think that is that's the recipe for a boring and very unfulfilling life you mentioned love difficult backtrack what uh we talked about the demons and the violence in there somewhere what's the role of love in this in your own life it's very important man and that's one of the reasons why i'm so uh i'm so interested in helping people i'm very interested in people feeling good i like them to feel good i want to help them i like i like doing things that make them feel like oh you care about me like yeah i care about you i really do like i want people to feel good i want my family to feel good i want my friends to feel good i want guests to feel good about the podcast experience you know i i am i'm a big believer in as much as i can to spread positive energy and joy and happiness and and relay all the good advice that i've ever gotten all the things that i've learned and if they can benefit people and i find that those things benefit people and actually improve the quality of their life or improve their success or improve their relationships or i'm very happy to do that that means a lot to me the the way we interact with each other is so important it's one of the reasons why like if someone gets cancelled or you get publicly shamed it's so devastating because there's all these people that negative all this negative energy coming your way and you feel it as much as you like to pretend that you you're immune to that kind of stuff and some people do like to pretend that you feel it there's a there's a tangible force when people are upset at you and that's the same with loved ones or family or anytime someone's upset at you whether it's a giant group of people or there's a small amount of people that has an impact on you and your psyche and your physical being so the more you can spread love and the more love comes back to you you also create this butterfly effect right because where other people start recognizing like oh you know when he is nice to me i feel better and i'm going to be nicer to people and when i'm nicer to people they feel better and i feel better and and it spreads outward and that's one thing that i've done through this podcast i think is i've i've imparted my personal philosophy on in in kindness and generosity to other people yeah i mean to correct you you didn't do it the ideas that are breeding themselves through your brain have fucked up the ideas that are all alive in the air made their way into my head love is a more efficient mechanism of spreading ideas they figured out yes probably man probably um so as far as like uh the meaning of life that's that's a bit without that you have nothing you know one of the big biggest failures in life is to be extremely successful financially but everybody hates you everybody hates you and you're just miserable and alone and angry and depressed and sad you know when you you hear about rich famous people that commit suicide like wow you missed the mark you got some parts right but you put too many eggs in one basket you put too many eggs in the financial basket or the success basket or the accomplishment basket and not enough in the friendship and love basket and there's a balance to that and what i talked about the violence and all that stuff like that to me is me understanding recognizing that is me trying to achieve that balance it's so like go kill those demons so that this boat is level you know because if it's not then the boat is like this and then everything's all fucked up and every time we hit a wave things fall apart balance that boat out figure it out like know who you are some people don't have that problem at all some people they could just go for walks and they're cool as a cucumber i need more you know i need kettle bells i need a heavy bag i need uh i need the echo bike you know air assault bike i need some hardcore shit and if i don't get that i don't feel good so i figured that out too and that makes me a nicer person and that makes my interactions nicer it makes it it changes the quality of my my friendships and my relationships with people i think uh we mentioned eurolink i can i can certainly uh guarantee that this is one of the memories i'll be replaying 20 30 years from now once we get the feature ready joe it's a huge honor to talk to you i hope it's an honor to talk to you too i came down here for this the first week of me doing this here and it's uh it's it's very cool to have you always i hope you make uh texas cool again and uh and and do your podcast another 10 11 whatever however many years you're still on this earth all right thank you brother appreciate you man thanks for listening to this conversation with joe rogan and thank you to our sponsors neuro asleep and dollar shave club check them out in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter lex friedman and now let me leave you with some words of wisdom from joe rogan the universe rewards calculated risk and passion thank you for listening and hope to see you next time |
James Gosling: Java, JVM, Emacs, and the Early Days of Computing | Lex Fridman Podcast #126 | the following is a conversation with james gosling the founder and lead designer behind the java programming language which in many indices is the most popular programming language in the world or is always at least in the top two or three we only had a limited time for this conversation but i'm sure we'll talk again several times in this podcast quick summary of the sponsors public goods betterhelp and expressvpn please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that java is the language with which i first learned object oriented programming and with it the art and science of software engineering also early on in my undergraduate education i took a course on concurrent programming with java looking back at that time before i fell in love with neural networks the art of parallel computing was both algorithmically and philosophically fascinating to me the concept of a computer in my mind before then was something that does one thing at a time the idea that we could create an abstraction of parallelism where you could do many things at the same time while still guaranteeing stability and correctness was beautiful while some folks in college took drugs to expand their mind i took concurrent programming if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and no ads in the middle i try to make these interesting but i do give you timestamps so go ahead and skip but please do check out the sponsors by clicking the links in the description it's the best way to support this podcast this show sponsored by public goods the one-stop shop for affordable sustainable healthy household products i take their fish oil and use their toothbrush for example their products often have a minimalist black and white design that i find to be just beautiful some people ask why i wear this black suit and tie there's a simplicity to it that to me focuses my mind on the most important bits of every moment of every day pulling only at the thread of the essential in all that life has to throw at me it's not about how i look it's about how i feel that's what design is to me creating an inner conscious experience not an external look anyway public goods plants one tree for every order placed which is kind of cool visit publicgoods.com lex or use codelex at checkout to get 15 bucks off your first order this show is also sponsored by better help spelled h-e-l-p help check it out at betterhelp.com lex they figure out what you need and match you with a licensed professional therapist in under 48 hours i chat with the person on there and enjoy it of course i also regularly talk to david goggins these days who is definitely not a licensed professional therapist but he does help me meet his and my demons and become comfortable to exist in their presence everyone is different but for me i think suffering is essential for creation but you can suffer beautifully in a way that doesn't destroy you i think therapy can help in whatever form that therapy takes and i do think that better help is an option worth trying they're easy private affordable and available worldwide you can communicate by text anytime and schedule weekly audio and video sessions check it out at betterhelp.com lex this show is also sponsored by expressvpn you can use it to unlock movies and shows that are only available in other countries i did this recently with star trek discovery and uk netflix mostly because i wonder what it's like to live in london i'm thinking of moving from boston to a place where i can build the business i've always dreamed of building london is probably not in the top three but top ten for sure the number one choice currently is austin for many reasons that i'll probably speak to another time san francisco unfortunately dropped off from the number one spot but is still in the running if you have advice let me know anyway check out expressvpn it lets you change your location to almost 100 countries and it's super fast go to expressvpn.com lexbod to get an extra three months of expressvpn for free that's expressvpn.com lex pod and now here's my conversation with james gosling i've read somewhere that the square root of two is your favorite irrational number i have no idea where that got started um is there any truth to it is there anything in mathematics or numbers that you find beautiful oh well there's lots of things in in math that's really beautiful um you know i i used to consider myself really good at math and these days i consider myself really bad at math i never had really had a thing for the square root of two but when i was a teenager there was this book called the the dictionary of curious and interesting numbers which for some reason i read through and damn near memorized the whole thing and i started this weird habit of when i was like filling out checks you know or you know paying for things with credit cards i would want to make the the receipt add up to an interesting number is there some numbers that stuck with you that just kind of make you feel good they all have a story and fortunately i've actually mostly forgotten all of them um are they uh so like 42 uh well yeah i mean that one 42 is pretty magical and then the irrationals i mean but is there a square root or two story in there somewhere well it's it's like the only number that has destroyed a religion in which way well the the pathagorians they they believed that all numbers were perfect and you could represent anything as as a as a rational number and [Music] in that in that time period um the this proof came out that there was no you know rational fraction whose value was equal to the square root of two and that that means nothing in this world is perfect not even mathematics well it it means that your definition of perfect was imperfect well then then there's the ghetto and completeness theorems in the 20th century that ruined it once again for everybody yeah although although although girdle's theorem um you know the lesson i take from girdle's theorem is not that you know there are things you can't know which is fundamentally what it says um but you know people want black and white answers they want true or false um but if you if you allow a three-state logic that is true false or maybe then then life's good i feel like there's a parallel to uh modern political discourse in there somewhere but yeah let me let me ask um so with your kind of early love or appreciation of the beauty of mathematics do you see a parallel between that world and the world of programming you know programming is all about logical structure understanding the the patterns that um come out of computation understanding sort of i mean it's often like you know the path through the graph of possibilities to find a short a short route meaning like uh find a short program that gets the job done yeah kind of thing but uh so then on the topic of irrational numbers do you see dc programming you just painted it so cleanly uh it's a little this trajectory to find like a nice little program but do you see it as fundamentally messy maybe unlike mathematics i don't think of it as i mean i mean you know you watch somebody who's good at math do math and you know often it's it's fairly messy sometimes it's kind of magical um when i was a grad student um one of the students his name was jim sax was he had this this this this this reputation of being sort of a walking talking human uh theorem proving machine and if you were having a hard problem with something you could just like accost him in the hall and say jim and and he would do this this this funny thing where he would stand up straight his eyes would kind of defocus he'd go uh you know just just like get you know like like something in today's movies and then you straighten up and say and log in and walk away and and and you go well okay so n log n is the answer how did he get there by which time he's you know down the hallway somewhere yeah it is just the the oracle the black box just gives you the answer yeah and then you have to figure out the path from the question to the answer i think in one of the videos i watched you mentioned uh don knuth uh well at least recommending his uh you know his his book is something people should read oh yeah but in terms of you know theoretical computer science do you do you see something beautiful in in that has been inspiring to you speaking of n log n in your work on programming languages that's in the in that whole world of algorithms and complexity and you know these kinds of more formal mathematical things um or did that not really stick with you in your programming life it did stick pretty clearly for me because one of the things that i care about is being able to sort of look at a piece of code and and be able to prove to myself that it works um you know and you know so so for example i find that um i'm i'm at odds with many of the people around me over um issues about like how you lay out a piece of software right you know so so software engineers get really cranky about how they format their the documents that are the programs you know where they put new lines and where they put you know the braces the braces and all the rest of that right and i tend to go for a style that's very dense to minimize the white space um yeah well to maximize the amount that i can see at once right so i like to be able to see a whole function and to understand what it does rather than have to go scroll scroll scroll and remember right yeah i'm with you on that yeah that's and people don't like that yeah i've i've had i've had you know multiple times when engineering teams have uh staged what was effectively an intervention um you know where they they invite me to a meeting and everybody's arrived before me and they so all look at me and say james about your coding style i'm sort of an odd person to be programming because i don't think very well verbally um i am just naturally a slow reader um i'm what most people would call a visual thinker so when you think about a program what do you what do you see i see pictures right so when i look at a piece of code on a piece of paper it very quickly gets transformed into a picture um and you know it's almost like a piece of machinery with you know this connected to that and like these gear knobs yeah yeah i i see them more more like that than i see the the the sort of verbal structure or the lexical structure of of letters so then when you look at the program that's why you want to see it all in the same place then you could just map it to something visual yeah and just kind of like like it leaps off the page at me and yeah what are the inputs where the outputs what the heck is this thing doing yeah and yeah getting a whole vision of it can we uh go back into your memory memory long-term memory access what's the first program you've ever written oh i have no idea what the first one was i mean i i know the first machine that i learned that i learned to program on what is it was a pdp-8 um at the university of calgary do you remember the specs oh yeah so so the thing had 4k of ram nice 12-bit words the clock rate was um it was about a third of a megahertz oh so i didn't even get to the to the m okay yeah yeah so you know we're we're like 10 000 times faster these days um and was this kind of like a super computer like a serious computer for no the pdp 8i was the the first thing that people were calling like mini computer got it they were sort of inexpensive enough that a university lab could maybe afford to buy one and was there time sharing all that kind of stuff um there there actually was a time sharing os for that but it wasn't used really widely the machine that i learned on was one that was kind of hidden in the back corner of the of the computer center um and it was it was bought as a as part of a um project to do computer networking um but you know they didn't actually use it very much it was mostly just kind of sitting there and it was kind of sitting there and i noticed it was just kind of sitting there and so i started fooling around with it and nobody seemed to mind so i just kept doing that and i had a keyboard and like a monitor oh this is way before monitors were common so it was it was literally a a model 33 teletype okay with a paper tape reader okay so the user interface wasn't very good yeah yeah it was it was the first computer ever built with integrated circuits but by integrated circuits i mean that they would have like 10 or 12 transistors on one piece of silicon right not the 10 or 12 billion that machines have today so what did that i mean feel like if you remember those i mean did you have kind of inklings of the the magic of exponential kind of improvement of moore's law of the potential of the future that was at your fingertips kind of thing oh it was just a cool yeah it was just a toy you know i had always liked building stuff but one of the problems with building stuff is that you need to have parts you know you need to have pieces of wood or wire or switches or stuff like that and those all cost money and here you could build you could build arbitrarily complicated things and i didn't need any physical materials um it required no money that's right it's a good way to put programming you're right it's uh if you love building things it uh okay so it you know completely accessible you don't need anything and anybody from anywhere could just build something really cool yeah yeah if you've got access to a computer you can you can build all kinds of crazy stuff um and you know and when you were somebody like me who had like really no money um and i mean i i remember just lusting after being able to buy like a transistor um you know and when i would do sort of electronics kind of projects they were mostly made done by like dumpster diving for trash you know and you know one of my big hauls was uh discarded relay racks from the back of a the phone company switching center oh nice that was the big memorable treasure oh yeah yeah that was what do you use that for i i built a machine that played tic-tac-toe nice out of relays of course the thing that was really hard um was that all the relays required a specific voltage but getting a power supply that will would do that voltage was pretty hard and since i had a bunch of trashed television sets i had to um sort of cobble together something that was wrong but worked um so i was actually running these relays at 300 volts and and none of the electrical connections were like properly sealed off you survived that period of your life oh for so many reasons for so many reasons i mean you know you're you know it's pretty common for teenage geeks to discover oh thermite that's real easy to make yeah well i'm glad you did but do you remember the do you remember what program in calgary that you wrote anything that stands out and what language well so mostly the anything of any size was assembly code um and actually before i learned assembly code there was this programming language on the pdp called focal five and focal five was kind of like a really stripped down fortran and i remember playing but you know building programs that did things like um play blackjack um [Music] or solitaire or for some reason or the things that i really liked were ones where they were just like plotting graphs so something with uh like a function or a data and then you'd plot it yeah yeah i did a bunches of those things and went ooh pretty pictures um and so this would like print out again no no monitors right so it was like on a teletype yeah so using something that's kind of like a a typewriter and then using those to plot functions so when i apologize to romanticize things but when did you first fall in love with programming you know what was the first programming language like it's a serious maybe software engineer where you thought this is a beautiful thing i guess i never really thought of any particular language as being like beautiful because it was never really about the language for me it was about what you could do with it um and you know even today you know people try to get me into arguments about particular forms of syntax for this or that and i'm like who cares you know it's it's about what you can do not not not how you spell the word um and you know so back in those days i i learned like pl one and fortran and cobalt and and you know by the time that people were willing to hire me to do stuff you know it was mostly assembly code and you know pvp assembly code and and fortran code and control data assembly code for like the cdc 6400 which was an early i guess super computer even though that super computer has less compute power than my phone by a lot and that was mostly like said fortran yeah world that said you've also showed appreciation for the greatest language um ever that i think everyone agrees is lisp um well lisp was definitely on my list of the greatest ones that have have um existed is that number one or i mean um are you i mean you know that you know the thing is that it's it that you you know i wouldn't put it number one now is it the parentheses what uh um what do you love what do you not love about lisp um well i guess the number one thing to not love about it is so freaking many parentheses yeah um on the on the love thing is you know out of those tons of parentheses you actually get an interesting language structure and i've always thought that there was a friendlier version of lisp hiding out there somewhere but i've never really spent much time thinking about thinking about it but you know so like like up the food chain for me um then from lisp is simula which a very small number of people have ever used but a lot of people i think he had a huge influence right yeah the programming but in the simula i apologize if i'm wrong on this but is that one of the first functional languages um or no no it was it was it was the first object-oriented programming language got it it's really where object-oriented and languages sort of came together um and it was also the the language where co routines first showed up as a part of the language so you could have a programming style that was you could think of it as multiple uh sort of multi-threaded with a lot of parallel parallelism really there's ideas of parallelism in there yeah yeah so that was that was back you know so the first stimulus spec was simula 67 like 1967. yeah wow so it had it it had co-routines which are almost threads the the thing about co routines is that they don't have true concurrency so you can get away without um really complex locking you can't usably do co-routines on a on the multi-core machine or if you try to do core code routines on the multi-core mute machine you don't actually get to use the multiple cores um either that or you you know because you start then having to get into the universe of you know semaphores and locks and things like that um but you know in terms of the the style of programming you could write code and think think of it as being multi-threaded the mental model was very much a multi-threaded one and all kinds of problems you could approach very differently to to return to uh the world of lisp for a brief moment you uh at cmu you've you uh wrote a version of emacs that i think was very impactful on the history of emacs um what was your motivation for for doing so at that time so that was in like 85 or 86. um i had been using unix for a few years and um most of the editing was this this tool called edie um which was sort of an ancestor of vi and is it a pretty good editor not a good editor well if if what you're using um if your input device is a teletype it's pretty good yeah it's certainly more humane than tico which was kind of the the common thing in a lot of um the dec universe at the time tico is both tk is that the tico t-e-c-o the text editor and corrector corrector huh so many features um and the original emacs came out as so emac stands for editor macros and tico had a way of writing macros and so the original um emacs from mit sort of started out as a collection of macros for tico but then you know you know the the sort of emac style got got popular originally at at mit and then people did a few other implementations of emacs that were you know the the the code base was entirely different but it was sort of the philosophical style of the original emacs what was the philosophy of emacs and by the way were all the implementations always in c and then no and how does lisp fit into the picture no so so the very first emacs was written as a bunch of macros for the tico text editor wow this is so interesting and the the the macro language for tico was probably the most ridiculously obscure format you know if you just look at a tico program on a on a page you think it was just random characters it really looks like just line noise just kind of like latex or something oh worse way worse than the tick way way worse than latex um but you know if you use tico a lot which i did the the tico was completely optimized for touch typing at high speed um so there were no two character commands well there were a few but mostly they were just one character so every character on the keyboard was a separate command um and actually every character on the keyboard was usually two or three commands because you know you hit shift and control and all of those things you know it's just a way of very tightly encoding it and mostly what emacs did was it made that that visual right so one way to think of tico is use emax with your eyes closed where you have to maintain a mental model of you know sort of a mental image of your document you have to go okay so the the cursor is between the a and the e and i want to exchange those so i do these these things right so it almost it is almost exactly the emax command set well it's roughly approximate roughly the same as emacs command set but using emacs with your eyes closed um so what emacs you know part of what emacs added to the whole thing was was being able to visually see what you were editing um in a form that matched your document um and you know a lot of things changed in the in the command set it um you know because it was programmable it was really flexible you could add new commands for all kinds of things and then people rewrote emacs like multiple times in lisp there was one done at mit for the lisp machine there was one done for multix and one summer i got a got a summer job to work on the pascal compiler for multix and that was actually the first time i used emacs and and and so to write the compilers you've worked in compilers too it's yeah that's fascinating yeah so i did a lot of work you know i mean i spent like like a really intense three months working on this pascal compiler um basically living in emacs and it was it was the one written in mac list by bernie greenberg and i thought wow this is a just a way better way to do editing um and then i got back to cmu where we had kind of one of everything and two of a bunch of things and four of a few things and um since i mostly worked in the unix universe and unix didn't have an e-max i decided that i needed to fix that problem so i so i wrote this this implementation of emacs in c because at the time c was really the only language that worked on on uh on unix um and you were comfortable with c as well oh yeah at that point yeah at that time i had done a lot of c coding that this was in like 86. um and you know it was running well enough to be used for me to use it to edit itself within a month or two and um then it kind of took over the university and and it spread and then it died yeah and then it went outside the and largely because unix kind of took over the research community on the on the on the arpanet then and emacs was kind of the best editor out there it kind of took over and there was a actually a brief period where i actually had login ids on every non-military host on the on the arpanet you know because people would say oh can we install this and and i'd like well yeah but you'll need some help uh the days when security wasn't uh when nobody cared nobody cared yeah we can ask briefly what were those early days of arpanet and the internet like what was uh what i mean did you uh again sorry for the silly question but could you have possibly imagined that uh the the internet would look like what it is today you know some of it is remarkably unchanged so like one of the things that i noticed really early on um at you know when i was at at carnegie mellon was that a lot of social life became centered around the arpanet so things like you know between email and text messaging because the you know text messaging was a part of the arpanet really early on there were no cell phones but you know you're sitting at a terminal and you're typing stuff and essentially email or like what what is well just like like a one-line message right so so so oh cool so like chat like chat yeah right so it's like like sending a one-line message to somebody right and and and so pretty much everything from you know arranging lunch to going out on dates you know it was all like driven by social media so you know right in the in the in the 80s easier than phone calls yeah you know and my life had gotten to where you know i was you know living on social media you know from like the early mid 80s um and and so when when it sort of transformed into the internet and social media explodes i was kind of like what's the big deal it's just a scale thing it's it's right the the scale thing is just astonishing yeah um but the fundamentals um in some ways the fundamentals have have hardly changed and you know the the technologies behind the the networking have changed significantly the you know the the the watershed moment of you know going from the arpanet to the internet um and then people starting to just scale and scale and scale i mean the the the the scaling that happened in the early 90s and the way that so many vested interests fought the internet oh who oh interesting what was the oh because you can't really control the internet yeah so so so fundamentally the you know the cable tv companies and broadcasters and phone companies um you know at the deepest fibers of their being they hated the internet but it was often kind of a funny thing because um you know so so so think of a cable company right most of the employees of the cable company their job is getting tv shows movies whatever out to their customers they view their business as serving their customers um but as you climb up the hierarchy in the in the cable companies that view shifts because um really the business of the cable companies that had always been selling eyeballs to advertisers right um and you know that view of of like a cable company didn't really dawn on most people who worked at the cable companies but i mean you know we you know i had various dust-ups with various cable companies where you could see you know in the stratified layers of the corporation that that this this this this this view of you know the reason that you have you know cable tv is to capture eyeballs you know there they didn't see it that way well so so the people who the most the people who worked at the phone company are at the cable companies their view was that their their job was getting delightful content out to their customers and their customers would pay for them would pay for that higher up they viewed this as as a way of attracting eyeballs to them and and then what they were really doing was selling the eyeballs that were glued to their content to the advertising to the advertisers yeah and so the internet was a competition in that sense right and and and and they were right well yeah um i mean there was one proposal that we sent the the we one detailed proposal that that we um wrote up you know back at that sun in the in the early 90s that was essentially like look anybody you know with it with internet technologies anybody can become provider of of content so you know you could be distributing home movies to your parents or your cousins or your who are anywhere else right so anybody can become a publisher wow you were thinking about that already yeah yeah that was like yeah that was that that was like in the in the early 90s yeah and we thought this would be great you could you know and the kind of content we were thinking about at the time was like you know home movies kids essays um you know stuff from like grocery stores or you know you know that or or a restaurant that they could actually like start sending information about out and um that's brilliant and and the the the the reaction of the cable companies was like no because because then we're out of business what is it about companies that because they could have just they could have been ahead of that wave they could have listened to that and they could have they they didn't see a path to revenue you know there's there's somewhere in there there's a lesson for like big companies right like to to listen to to try to anticipate the the renegade the out there out of the box people like yourself in the early days writing proposals about what this could possibly be well and that you know that you know it wasn't you know if you're in a in a position where you're making truckloads of money off of a particular business model um you you know the the the the the whole um thought of like you know leaping the chasm right you know you know you can see oh new models that are more effective are emerging right so like digital cameras versus film cameras um you know i mean why take the leap why take the leap because you're making so much money off of film and um you know in my past at sun one of our big customers was kodak and i ended up interacting with folks from kodak quite a lot and they actually had a big um digital camera research and you know digital imaging business or b development group and they knew that that you know you you know you just look at the at the trend lines and you look at um you know the emerging quality of of of these you know digital cameras and you know you can just plot it on the graph you know and it's like you know sure film is better today but you know digital is is is is improving like this the lines are going to cross and and you know the point at which the lines cross is going to be a collapse in their business and they could see that right they absolutely knew that the problem is that you know up to the point where they hit the wall they were making truckloads of money yeah right and when they did the math um it never started to make sense for them to kind of lead the charge and part of the issues for a lot of companies for this kind of stuff is that um you know if you're going to leap over a chasm like that like like with kodak going from from film to digital that's a transition that's going to take a while right we have we had fights like this with people over like smart carts the smart cards fights were just ludicrous but that's where visionary leadership comes in right yeah somebody needs to roll in and say then take to take the leap well it's it's partly take the leap but it's also partly take the hit take the hit right so so so so you can draw all the graphs you want that show that you know if we leap from here you know you know the you know on our present trajectory we're doing this and there's a cliff if we um force ourselves into it into a transition and we proactively do that we can be on the next wave but there will be a period when we're in a trough and pretty much always there ends up being a trough as you leave the chasm but the way that public companies work on this planet they're reporting every quarter and the one thing that a ceo must never do is take a big hit take a big hit you know over some some quarter and and many of these transitions involve a big hit for a a period of time you know one two three quarters and so you get some companies and you know like tesla and amazon are are really good examples of companies that take huge hits but they have the luxury of being able to ignore the stock market for a little while and that's not so true today really but you know in the early days of of both of those companies um you know like like like like like they they both did this thing of you know i don't care about the quarterly reports i care about how many how many happy customers we have yeah right and having as many happy customers as possible can often be um an enemy of the bottom line yeah so how do they make that work i mean amazon operated in the negative for a long time it's like investing into the future right but you know you know so amazon and google and tesla and facebook a lot of those had what it what amounted to patient money um often because the there's there's like a charismatic central figure who has a really large block of stock and they can just make it so so what uh on that topic just maybe it's a little small tangent but uh you've gotten the chance to work with some pretty big leaders what are your thoughts about on tesla side elon musk leadership on the amazon side jeff bezos all of these folks with large amounts of stock and vision in their company i mean they're founders yeah either the complete founders are like early on folks and uh they're they amazon have taken leave a lot of leaps uh and you know uh that probably at the time people would criticize as like what is this bookstore thing why yeah and and you know bezos had a vision and he had the ability to just follow it lots of people have visions and you know the average vision is completely idiotic and you crash and burn um you know the the silicon valley um crash and burn rate is pretty high um and they're not they don't necessarily crash and burn because they were dumb ideas but you know often it's it's just timing um timing and luck and you know you take companies like like like tesla um and and and and and really you know the the original tesla um you know sort of pre um elon was kind of doing sort of okay but but but he just drove them and because he had a really strong vision you know he would he would make calls that were always you know or well mostly pretty good i mean the model x was kind of a goofball thing to do but he did it boldly anyway like there's so many people that just said like there's so many people that oppose them on the falcon one door like the doors yeah from the engineering perspective those doors are ridiculous it's like yeah they're they are a complete travesty but but they're but they're exactly the symbol of what great leadership is which is like you have a vision and you just go like if you're gonna do something stupid make it really stupid yeah and go all in yeah yeah and and you know to to must credit he's a really sharp guy so going back in time a little bit to steve jobs you know steve jobs was a similar sort of character who had a strong vision and was really really smart and you you know and he wasn't smart about the technology parts of things but but sort of he he was really sharp about the the the sort of human relationship between you know the relationship between humans and objects um and but he was a jerk you know right can we just linger on that a little bit like people say he's a jerk um is that a feature or a bug well that's that's that's the question right so you take people like steve um who was really hard on people and and the and so the question is was he really was he needlessly hard on people or was he just making people reach to to meet his vision and you could kind of spin it either way um well the results tell a story you know he's uh he through whatever jerk ways he had he made people often do the best work of their life yeah yeah and that was absolutely true and you know i interviewed with him several times um i did you know various negotiations with him and um even though kind of personally i liked him i could never work for him why do you think uh it that what can you put into words the kind of tension that you feel would be um destructive as opposed to constructive oh he he he'd yell at people he'd call them names and you don't like that no no i don't i don't think you need to do that yeah um and you know he you know i think you know there's there's pushing people to excel and then there's too far and i think he was on the wrong side of the line and i've never worked for musk i know a number of people who have many of them that have said and it's you know shows up in the press a lot that that musk is kind of that way and one of the things that i sort of loathe about silicon valley these days is that um a lot of the high-flying successes are run by people who are complete jerks um but it seems like there's been become this there's come this this sort of mythology out of steve jobs that the reason that he succeeded was because he was super hard on people and and and and and and and in a number of corners people start going oh if i want to succeed i need to be a real jerk yeah right and and and that for me just does not compute i mean i know a lot of successful people who are not jerks who are perfectly fine people um you know they they tend to not be in the public eye the the the the general public somehow lifts the jerks up into the into the hero status right well they because they're they do things that get them in the press yeah and you know the people who um you know don't do the kind of things that spill into the press um yeah i just uh talked to chris ladner um for the second time he's a super nice guy just an example of this kind of kind individual that's in the background i feel like he's behind like a million technologies but he also talked about the jerkiness of some of the folks yeah yeah and the fact that being a jerk has become your required style but one thing i'd maybe want to ask on that is and maybe to push back a little bit so there's the jerk side but there's also if i were to criticize what i've seen in silicon valley which is almost the resistance to working hard so on the jerkiness side is um it's it's so posted jobs and elon kind of push people to work really hard to do and there's a question whether it's possible to do that nicely but one of the things that bothers me maybe i'm just rushing and just kind of you know romanticize the whole suffering thing but i think working hard is essential for accomplishing anything interesting like really hard and in the parlance of silicon valley it's probably too hard this idea that you should work smart not hard often to me it sounds like you should be lazy because of course you want to be to work smart of course you want to be maximally efficient but in order to discover the efficient path like we're talking about with the short programs yeah well you know the the the smart hard thing yeah isn't an either or it's an and as an and yeah right and um you know the the the the the people who say you should work smart not hard they pretty much always fail yeah thank you right i mean that's that's that's just just a recipe for disaster i mean there are there are counter examples but they're more people who benefited from luck and you're yeah exactly luck and timing like you said is often uh an essential thing but you're saying you know you can be you can push people to work hard and do incredible work without without uh without being nasty yeah without being nasty i think uh um google is a good example of the leadership of google throughout his history has been a pretty good example of uh not being nasty i mean the the the the twins larry and sergey um are both pretty nice people sandra paches very nice yeah yeah yeah and you know it's it's a culture of people who work really really hard let me ask a maybe a little bit of a tense question uh we're talking about emacs it seems like you've done some incredible work so outside of java you've done some incredible work that didn't become as popular as it could have because of like licensing issues and open sourcing like issues um uh what are your thoughts about the the the entire mess like what's about open source now in retrospect looking back uh about licensing about open sourcing do you think uh open source is a good thing a bad thing do you have regrets do you have wisdom that you've learned from that whole experience so in general i'm a big fan of of open source the way that it it can be used to build communities and promote the development of things and promote collaboration and all of that is really pretty grand um when open source turns into a religion that says all things must be open source right um i get kind of weird about that because it's it's sort of like saying you know some some versions of that um end up saying that that that all all software engineers must take a vow of poverty right right as though um it's unethical to have money yeah to build a company to uh right and you know there's a there's a there's a slice of me that actually kind of buys into that right because you know people who make billions of dollars off of like a patent and the the patent came from like you know literally a a stroke of lightning that that hits you as you lie half a week in bed yeah that's lucky good for you the way that that sometimes sort of explodes into something that looks to me a lot like exploitation you know you see a lot of that in in in like the the drug industry um you know when you know when you've got a got got medications that cost you know cost you like a hundred dollars a day and it's like no yeah so the the interesting thing about the sort of open source uh what bothers me is when something is not open source and because of that it's a worse product yeah so like i mean if i look at your just implementation of emacs like that could have been the dominant implementation like i use emacs that's my main id i apologize to the world but i still love it uh and you know i could have been using um your implementation of emacs and why aren't i so are you using the gnu max i guess the default on linux is that new yeah and and that through a strange passage started out as the one that i wrote exactly so it's it still has uh right yeah right well and and part of that was because you know in you know the last couple of years of grad school it it became really clear to me that i was either going to be mr emax forever or i was going to graduate i couldn't actually do both was that a hard decision that's so interesting to think about you as the pub like it's a different trajectory that could have happened yeah that's fascinating um you know and maybe you know i could be fabulously wealthy today if i had become mr emax and emacs had mushroomed into a series of text processing applications and all kinds of stuff and you know i would have you know but i have a long history of financially suboptimal decisions because i didn't want that life right and you know i went to grad school because i wanted to graduate um and you know you know being mr emax for a while was kind of fun and then it kind of became not fun not fun um and you know when it was not fun and i was you know there was no way i could you know pay my rent right yeah and and i was like okay do i carry on as a grad student as a you know i you know i had a research assistantship and i was sort of living off of that and i was trying to do my uh you know i was doing all my ra where all of my r.a you know being grad student work and being mr emacs all at the same time um and and i i decided to pick one and one of the things that i did at the time was i went around you know all the people i knew on the the arpanet who might be able to to to take over looking after emacs and um pretty much everybody said i got a day job so so i actually found you know two folks and a couple of folks in a garage in new jersey um complete with a dog um who are willing to take it over but they were going to have to charge money um but my deal with them was that they would um only that they would make it free for universities and schools and stuff and they said sure and you know that upset some people so you have some now i don't know the full history of this but i think it's kind of uh interesting you have some tension with me mr richard stallman um over the and he kind of represents this kind of like like you mentioned free software uh sort of a dogmatic focus on yeah all all information must be free must be free so what is there an interesting way to uh paint a picture of the disagreement you have with richard through the years my my basic opposition is that you know when you say information must be free uh to a really extreme form that turns into you know all people whose job is the production of everything from movies to software um they must all take a vow of poverty because information must be free and that doesn't work for me right and and i and i don't i don't want to be wildly rich i am not wildly rich um i do okay um but i do actually you know you know i've you know i can feed my children yeah i totally agree with you i it does just make me sad that sometimes the closing of the source for some reason the people that like a bureaucracy begins to build and sometimes it doesn't it hurts the product oh absolutely absolutely it's always sad and there's and there is a there is a balance in there that's a balance um and you know it's it's not hard hard over you know rapacious capitalism and and it's and it's not hard over in the other direction um and you know a lot of the the open source movement they they have been magic to find a path to um actually making money right so doing things like service and support works for a lot of people um you know and there are some some ways where it's it's kind of um some of them are are a little a little perverse right so as you know a part of things like this sarbanes-oxley act and various people's interpretations of all kinds of accounting principles um and this is kind of a worldwide thing but if you've got a a corporation that is depending on some piece of software um you know the often you know various accounting and reporting standards say if you don't have a support contract on this thing that that your business is depending on then that's bad you know so so so you know if you've got a if you've got a database you need to pay for support and and so but there's a difference between you know the the sort of support contracts that you know the average open source database uh producer charges and what somebody who is truly rapacious like oracle charges it's a it's a it's a balance it is it is absolutely a balance and you know there are there are a lot of a lot of different ways to make you know the math work workout for everybody um and you know the the very you know uh un unbalanced sort of you know like like the winner takes all thing that that happens in so much of of modern commerce um that just doesn't work for me either i know you've talked about this in quite a few places but you have created one of the most popular programming languages in the world this is the programming language that i first learned about object-oriented programming with you know i think it's a programming language that a lot of people use in a lot of different places and millions of devices today java so the absurd question but can you tell the origin story of java so long time ago at sun in about 1990 there was a group of us who were kind of worried that there was stuff going on in the universe of computing that the computing industry was missing out on and so a a few of us started this project at sun that really got going i mean we started talking about it in 1990 and it really got going in 91 and it was all about you know what was happening in terms of you know computing hardware you know processors and networking and all of that that was outside of the computer industry and that was everything from the the the the sort of early glimmers of cell phones that were happening then to you know you look at elevators and locomotives and process control systems in factories and all kinds of audio audio equipment and video equipment they all had processors in them and they were all doing stuff with them and and it and it sort of felt like there was something going on there that we needed to understand and so c c and c plus plus was in the air already oh no c and c plus plus absolutely owned the universe at that time everything was written in c and z plus plus so where was the hunch that there was a need for a revolution well so the the need for a revolution was not about the a language it was about it was just as simple and vague as there are things happening out there and we understand them we need to understand them and and so um a few of us went on several um somewhat epic road trips um literal road trips literal road trips it's like get on an airplane go to japan visit you know toshiba and sharp and mitsubishi and sony and all of these folks and you know because we worked for sun we had you know folks who were willing to like give us introductions you know we we visited you know samsung and um you know a bunch of korean companies and we went all over europe we went to you know places like like phillips and siemens and thompson and what did you see there you know for me the one of the things that sort of left out was that they were doing all the usual computer computer things that people had been doing like 20 years before the thing that really left out to me was that they were sort of reinventing computer networking and they were making all the mistakes that people in the computer industry had had made and since i had been doing a lot of work in in the networking area you know you know we'd go and you know visit you know company x they'd describe this networking thing that they were doing and just without any thought i could i could tell them like the 25 things there were going to be complete disasters with that thing that they were doing um and i don't know whether that had any impact on any of them but but but that particular story of you know sort of repeating the disasters of the computer science industry um was there and we and one of the things we thought was well maybe we could do something useful here with like bringing them forward somewhat but but also at the same time we learned a bunch of things from from these you know mostly consumer electronics companies and you know high on the list was that they viewed their like relationship with the customer as sacred um they they were never ever willing to make trade-offs between for safety right so one of the things that had always made me nervous in the computer industry was that um people were willing to make trade-offs in reliability to get performance um you know the the you know they want faster faster it breaks a little more often because it's fast you know you maybe you run it a little hotter than you should or like like the one that always blew my mind was the way that um the folks at at cray super computers got their division to be really fast was that they did newton-raphson approximations and so you know the bottom several bits of you know a over b we're essentially random numbers um what could possibly go wrong what could go wrong right and you know just figuring out how to nail the bottom bit um how to make sure that you know if you put a piece of toast in a toaster it's not going to kill the customer it's not going to burst into flames and burn the house down so those are i guess those are the the principles that were inspiring but how did from the days of uh java is called oak because of a tree outside the window story that people know how did it become this incredible like powerful language well so it was a bunch of things so we you know after all that we started you know the way that we decided that we could understand things better was by building a demo building a prototype of something okay so um kind of because it was easy and fun we decided to build a control system for some home electronics you know tv vcr that kind of stuff and as we were building it we you know we we sort of discovered that there were some things about standard practice in c programming that um were really getting in the way and it wasn't it wasn't exactly you know because we were writing this all the c code and c plus plus code that that we couldn't write it to do the right thing but that um one of the things that was weird in the group was that we had um a guy who's who's who's you know his sort of top level job was he was a business guy you know he was sort of an mba kind of person you know think about business plans and all of that and you know there were a bunch of things that were kind of you know and we would talk about things that were going wrong and um or things were going wrong things were going right and you know as we thought about you know things like like the requirements for security and safety um some low-level details and see like naked pointers yeah and you know so so back in the early 90s um it was well understood that you know the number one source of like security vulnerabilities is pointers was just pointers was just bugs yeah right and it was like you know 50 60 70 of all security vulnerabilities were bugs and the vast majority of them were like buffer overflows yeah so you're like we have to fix this we we have to make sure that this cannot happen and that was kind of the original thing for me was this cannot this cannot continue and one of the things i find really entertaining this year was um i forget which rag published it but there was this article that came out that was um an examination it was sort of the result of of an examination of all the security vulnerabilities in chrome and chrome is like a giant piece of c-plus plus code and 60 or 70 percent of all the security vulnerabilities were stupid pointer tricks and i thought it's 30 years later and we're still there still there and we're still there and you know i you know that's one of those you know slap your forehead and and and just just just want to cry would you attribute uh or is that too much of a simplification but would you attribute the creation of java to uh [Laughter] to see borders obvious problems well that i mean that was that was one of the the trigger points and currency you've mentioned concurrency was a big deal um and you know because when you're interacting with people you know the last thing you ever want to see is is the thing like waiting and you know issues about the software development process you know when faults happen can you recover from them what can you do to make it easier to create and eliminate complex data structures what can you do to fix you know the one of the most common sea problems which is storage leaks um and it's it's evil twin the um the the freed but still being used piece of piece of memory you know you you free something and then you keep using it oh yeah you know so so when i was originally thinking about that i was thinking about it in terms of of sort of safety and security issues and one of the things i sort of came to believe came to understand was that it wasn't just about safety and security but it was about developer velocity right so and i got really religious about this because at that point i had spent an ungodly amount of my life hunting down mystery pointer bugs and you know like like two-thirds of my time as a software developer was you know because the mystery pointer bugs tend to be the hardest to find because they tend to be very very statistical the ones that hurt you know they're you know they're like a one in a million chance um and but nevertheless create an infinite amount of suffering right because when you're doing a billion operations a second yeah you know one in a million chance means it's going to happen um and and so i got really religious about this thing about you know making it so that if something fails it fails immediately and visibly and you know one of the the the things that was a a real attraction of java to lots of development shops was that you know we get our code up and running twice as fast you mean like the entirety of the development process the blocking all that kind of stuff yeah if you you know so so if you measure time from you know you you first touch fingers to keyboard until you get your first demo out uh not much different but if you look from fingers touching keyboard to solid piece of software that you could release in production it would be way faster and i think what people don't often realize there's yeah there's things that really slow you down like hard to catch bugs probably is is the thing that really slows down that is it really slows things down but but also there were you know one of the things that you get out of object-oriented programming is a strict methodology about you know what are the interfaces between things and being really clear about how parts relate to each other um and what that helps with is so many times what people do um is they kind of like sneak around the side so if you've built something and people are using it and then and you say and you say well okay you know i built this thing you use it this way and then you change it in such a way that that it still does what you said it does it just does it a little bit different but then you find out that somebody out there was sneaking around the side they sort of tunneled in a back door and this person their code broke and because they were sneaking through a side door and and normally the attitude is dummy um but a lot of times um you know you can't get away you can't you can't just slap their hand and tell them to not do that right because you know it's you know somebody's you know some banks you know account reconciliation system that that you know some developer decided oh i'm lazy you know i'll just sneak through the back door because the language allows it i mean you can't even right mad at them and and so one of the things i did that that on the one hand upset a bunch of people is that i made it so that you really couldn't go through back doors right so so the whole point of that was to say if you need you know if the interface here isn't right the wrong way to deal with that is is to go through a back door yeah the right way to deal with it is to walk up to the developer of this thing and say uh change the interface fix it yep right and so it was kind of like a social engineering thing yeah and um it's brilliant and people ended up discovering that that really made a difference um in terms of you know and and and a bunch of this stuff you know if you're just like screwing around writing your own like you know class project scale stuff a lot of stuff doesn't isn't quite so so important because you know you're you know both sides of the interface um but you know when you're building you know sort of larger more complex pieces of software that have a lot of people working on them and especially when they like span organizations um you know having having really clear having clarity about how that stuff gets structured um saves your life yeah um and you know especially you know there's so much software that is fundamentally untestable you know and you know until you do the real thing it's better to write good code in the beginning as opposed to writing crappy code and then trying to fix it and yeah trying to scramble and figure out and through testing figure out where the bugs are yeah it's just like it's like it's like which shortcut caused that rocket to not get where it was needed to go so i think one of the most beautiful ideas uh philosophically and technically is uh of a virtual machine the java virtual machine well again apologize to romanticize things but uh how did the idea of the jvm come to be how to you radical of an idea it is because it seems to me to be just a really interesting idea in the history of programming so and what is it so the java virtual machine you can think of it in different ways um because it was carefully designed to have different ways of viewing it so one view of it that most people don't really realize is there is that you can view it as sort of an encoding of the abstract syntax tree in reverse polish notation i don't know if that makes any sense at all i could explain it and that would blow all of our time yeah um but the other way to think of it um and the way that it ends up being explained is that it's it's like the the instruction set of an abstract machine that's designed such that you can translate that abstract machine to a physical machine and the reason that that's important so if you wind back to the early 90s when we were talking to all of these these companies doing consumer electronics and you talked to the purchasing people there were interesting conversations with purchasing um so if you look at how you know these you know these devices come together they're sheet metal and gears and circuit boards and capacitors and resistors and stuff and everything you buy has multiple sources right so you can buy a capacitor from here you can buy a capacitor from there and you've got kind of a market so you know so that the you can actually get a decent price for a capacitor um but cpus and particularly in the early 90s cpus were all different and all proprietary so if you use the chip from intel you had to be an intel customer for the end of till the end of time because if you wrote a bunch of software you know when you wrote software using whatever technique you wanted and c was particularly bad about this because there was a lot of properties of the underlying machine that came through so if you're stuck so the code you wrote you were stuck to that particular machine you were stuck to that particular machine which meant that they couldn't decide you know intel is screwing us um i'll start buying chips from you know bob's better chips this drove the like the purchasing people absolutely insane that that they would they were welded into this decision and it would have they would have to make this decision before the first line of software was written it's funny that you're talking about the purchasing people so that's one perspective right it's a you could there's a lot of other perspectives that all probably hated this idea right but from a technical aspect just like the creation of an abstraction layer that's uh agnostic to the underlying machine from the perspective of the developer i mean it's brilliant right well and and and and you know you know so that's like across the spectrum of of providers of chips but then there's also the the time thing because um you know as you went from one generation to the next generation to the next generation they were all different and you would often have to rewrite your software i mean generations of uh cp of machines of different kinds yeah so so like like like one of the things that sucked about a year out of my life was when sun went from the the motorola 68010 processor to the 68020 processor then they had a number of differences and one of them hit us really hard and i ended up being the the point guy on the worst case of where the new instruction cache architecture heard us well okay so i mean so when did this idea i mean okay so yeah you you articulate a really clear fundamental problem in all of computing but how where do you get the guts to think we can actually solve this you know in our conversations with you know all these vendors you know these these problems started to to show up and i kind of had this epiphany because it reminded me of a summer job that i had had in grad school so back in grad school my my thesis advisor well i had two thesis advisors for bizarre reasons um one of them was a guy named raj reddy the other one was bob sproul um and raj i love ra i really love both of them but right amazing so the the department had bought a bunch of like early workstations from a company called three rivers computer company and three rivers computer company was a bunch of electrical engineers who wanted to do as little software as possible so um they knew that they'd need to have like compilers and os and stuff like that and they didn't want to do any of that and they wanted to do that for as close to zero money as possible so um what they did was they they built a machine whose instruction set was um the was literally the byte code for ucsd pascal the p code and so we had a bunch of software that was that was written for this machine and for various reasons you know the company wasn't doing terrifically well we had all the software on these machines and we wanted it to run on other machines principally the backs and um and so raj asked me if i could come up with a way to port all of this software and translate from the from from from the the the the perk machines to vax's and and i think he you know what he had in mind was something that would translate from like pascal to c or pascal to actually at those times pretty much it was you could translate to c or c and if you didn't like translating to c you could translate to c um there was you know it's you know it's like the the henry ford you know any color you wanted just as long as it's black um and and i went that's really hard um and and i and i noticed that you know and i was like looking at stuff and i went oh i bet i could rewrite the p code into vax assembly code and and then i started to realize that you know there were some properties of p code that made that really easy some properties that made it really hard so i ended up writing this thing that translated from from p code on the three rivers perks into assembly code on the backs and i actually got higher quality code than the c compiler and so so everything just went got really fast it was really easy it was like wow i thought that was a sleazy hack because i was lazy and in actual fact it worked really well and and i and i tried to convince people that that was maybe a good thesis topic yeah um and nobody was it was you know it was like nah really that's i mean yeah it's really it's kind of a brilliant idea right maybe you didn't have the you weren't able to articulate the big picture of it yeah and and i think you know that was a um a key part but so then you know clock comes forward a few years and it's like we've got to be able to you know that you know the you know if they want to be able to switch from you know this weird microprocessor to that weird and totally different microprocessor how do you do that and i kind of went oh maybe by doing something kind of in the space of you know pascal p code you know i could do like multiple translators and i spent some time thinking about that and thinking about you know what worked and what didn't work when i did the the the p code to vax translator and um i talked to some of the folks who were involved in small talk because small talk also did about code and and and then i kind of went yeah let's that i want to do that yeah because that act you know and and it had the the other advantage that you could either interpret it or compile it and um interpreters are usually easier to do but not as fast as a compiler so i figured good i can be lazy again um you know you know sometimes i think that most of my good ideas are um driven by laziness and often i find that people some of the people's stupidest ideas are because they're insufficiently lazy yeah they just want to build something really complicated it's like it doesn't need to be that complicated yeah and so and so that's how that came out and um you know but that also turned into kind of a you know almost a religious position on my part which was which got me in in several other fights so like like one of the things that was a real difference was the way that arithmetic worked um you know once upon a time there were you know it wasn't always just two's complement arithmetic there were some machines that had one's complement arithmetic which was like almost anything built by cdc um and occasionally there were machines that were decimal arithmetic and and i was like this is crazy you know pretty much two's complement integer arithmetic has one so just let's just do that just to do that one of the other places where there was a lot of variability was in the way that floating point behaved and that was causing people throughout the software industry much pain because you couldn't do a numerical computing library that would work on cdc and then have it work on an ibm machine and work on it on a deck machine um and as a as a part of that whole struggle there had been this this big body of work on on floating point standards and this thing emerged that came to be called ieee 754 which is the floating point standard that pretty much has take taken over the entire universe um and and at the time i was doing java it had pretty much completed taking over the universe there were still a few pockets of holdouts but i was like you know it's important to be able to say what two plus two means um yeah and and so i went that um and one of the ways that i got into fights with people was that there were a few machines that did not implement ieee 754 correctly well of course that's that's all short-term kind of fights i think in the in the long term i think this vision is won out yeah and and i think it's you know and it worked out over time i mean the the biggest fights were with intel because they had done some strange things with rounding they'd done some strange things with their transcendental functions which might turned into a mushroom cloud of you know weirdness and the name in the name of optimization but from the perspective of the developer that's not that's not good well their issues with transcendental functions were just stupid okay so that that's that's not even a trade-off that's just absolutely yeah they were they were doing range reduction in of first sign and cosine using a slightly wrong value for pi i got it go ahead ten minutes so in the interest of time two questions so one about android and one about life uh so one i mean we could talk for many more hours i hope uh eventually we might talk again but i gotta ask you about android and the use of java there because it's one of the many places where java just has a huge impact on this world just on your opinion is there things that make you happy uh about the way andro uh java is used in the android world and are there things that you wish were different i i don't know how to do a short answer to that um but i have to do a short answer to that so you know i'm happy that they did it um java had been running on cell phones at that time for quite a few years and it worked really really well um there were things about how they did it and and in particular um various ways that they kind of you know violated all kinds of contracts the guy who who led it andy rubin he crossed a lot of lines there's some lines crossed yeah lines were crossed that have since you know mushroomed into giant court cases um and you know they didn't need to do that and in fact it would have been so much cheaper for them to not cross lines i mean i suppose they didn't anticipate the the success uh of this whole endeavor um or do you think at that time it was already clear that this is uh it's gonna blow up i guess i i i i sort of came to believe that it didn't matter what andy did it was going to blow up okay he's he's he you know i kind of started to think of him as as as like a manufacturer of bombs yeah uh some of the best things in this world come about through a little bit of uh uh explosive well and some of the worst and some of the worst beautifully put but is there um and and like you said i mean does that make you proud that the java is in yeah is in millions i mean it could be billions of devices and yeah well i mean it was in in billions of phones before android came along um and you know i'm i'm just as proud as you know of the way that like the the smart card standards adopted java and they did it they you know everybody involved in that did a really good job and that's you know billions and billions um that's crazy the sim cards you know the sim cards in your pocket yeah i mean it's outside of that world for a decade so i don't know how that has it has evolved but um you know it's just been crazy so on that topic let me ask uh again there's a million technical things uh we could talk about but let me ask the absurd the old uh philosophical question about life what do you hope when you look back at your life and the people talk about you right about you 500 years from now uh what do you hope your legacy is people not being afraid to take a leap of faith um i mean i you know i've got this this kind of weird history of doing weird stuff and um it worked out pretty damn it worked out right and i think some of the weirder stuff that i've done um has been the coolest and some of it some of it crashed and burned and um yeah you know i think well over half of the stuff that i've done has crashed and burned um which has occasionally been really annoying but still you kept doing it but yeah yeah yeah and you know they're you know you even when things crash and burn you you at least learn something from it by way of advice you know people developers engineers scientists are just people who are young uh to look up to you what advice would you give them how to uh how to approach their life don't be afraid of risk it's okay to do stupid things once [Laughter] maybe even a couple times you know you you know you get you get a pass on the the first time or two that you do something stupid you know the third or fourth time yeah not so much um but also you know i don't know why but really early on i started to think about um ethical choices in my life and because i a big science fiction fan um i i i got to thinking about like just about every technical decision i make in terms of how do you want you know are you building blade runner or star trek which one's better which which future would you rather live in you know so what's the what's the answer to that well i would just i would sure rather live in the universe of star trek soundtrack yeah that opens up a whole topic about ai but that's a really interesting yeah yeah yeah it's a really interesting idea so your favorite ai system would be data uh from uh from star trek my least favorite would easily be skynet yeah beautifully put i don't think there's a better way to end it james i can't say enough how much of an honor it is to meet you to talk to you thanks so much for wasting your time with me today not a waste at all thanks james all right thanks thanks for listening to this conversation with james gosling and thank you to our sponsors public goods betterhelp and expressvpn please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from james gosling one of the toughest things about life is making choices thank you for listening and hope to see you next time |
Ryan Hall: Martial Arts and the Philosophy of Violence, Power, and Grace | Lex Fridman Podcast #125 | the following is a conversation with ryan hall one of the most insightful minds and systems thinkers in the martial arts world he's a black belt in jiu jitsu accomplished competitor an mma fighter undefeated in the ufc and truly a philosopher who seeks to understand the underlying principles of the martial arts jiu jitsu is such an important part of who i am and i was hoping to share that with folks who might know me only as a researcher i think there's no better person to do that with than ryan who somehow remarkably i can say is a friend and also a modern day warrior philosopher of the miyamoto masashi line of especially dangerous and brilliant humans also his amazing wife jen hall was there as well so if you hear a kind of voice of wisdom coming from above you know who it is quick summary of the sponsors power dot babel and cash app please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that renaming this podcast to just my name gave me intellectual freedom that i really didn't anticipate was so empowering especially for someone who's trying to find their voice i hope you'll allow me the chance to really try and do that to step outside of ai and even science engineering history and so on and on occasion talk to athletes musicians writers and maybe even comedians who inspire me especially up and coming comedians and musicians like eric weinstein who yes we'll do a third conversation with soon i think if i allow myself to expand the range of these conversations on occasion when i do return to science and engineering i'll bring a new perspective and also a little bit more fun and a few extra listeners that may not otherwise realize how fascinating artificial intelligence robotics mathematics and engineering truly is all that said please skip the episodes that don't interest you you don't have to 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up in fact i first heard about this kind of electrical muscle stimulation device in reading that bruce lee used it he was an inspiration to me as someone who practices first principles thinking especially in a discipline where conventional thinking is everywhere he created a martial art called jeet kune do that is in many ways at least philosophically in his hybrid approach a precursor to modern day mixed martial arts there's a special kind of deep philosophical thinking that combat athletes or jiu jitsu practitioners do that is unlike any other i think it's grounded in the humbling process of getting your ass kicked a lot that removes any illusion of intellectual superiority i think the journey towards wisdom starts when you humbly admit to yourself that you know very little or almost nothing anyway go to powerdot.com lex and use codelex at checkout to get 20 off on top of the 30-day free trial this show is also sponsored by babel an app and website that gets you speaking in a new language within weeks go to babble.com and use code lex to get three months free they offer 14 languages including spanish french italian german and yes russian let me read a few lines from a russian song by vladimir vasotsky called anabolaf parisia that you'll start to understand if you sign up to babel annabella this song always made me smile because it resonates with my own life it translates loosely to she's been to paris paris for russian i suppose symbolizing a fancy life and that the guy could never quite fit into that kind of life expensive things nice restaurants cars all that i was thinking about what song's equivalent in english maybe uptown girl by billy joe is similar in spirit but very different in style i just watched the video on youtube for uptown girl and it's basically billy joel dressed up as a mechanic but dancing in a way that i'm pretty sure no mechanic has ever danced turning the old cringe factor up to 11. anyway i always felt like i didn't really fit in with the fancy people and that's what this song represents but back to uh babel get started by visitingbabel.com and use codelex to get three months free this show is presented by the great the powerful the og sponsor named unofficially after one of my favorite musicians the man in black johnny cash that's cash app the number one finance app in the app store when you get it use code lex podcast the cash app folks are truly amazing people and are teaming with ideas for cool contests giveaways and all that kind of stuff i've been thinking of doing some kind of little contests and giving away 42 bucks to a bunch of people who win it's not so much about the money but the glory and the delicious taste of victory if you have ideas for contests let me know i was thinking of something like asking people to submit funny inspiring photos or videos or audio of using cash app or any of the sponsors of this podcast really or maybe even just funny things related to the podcast like different weird places you might be watching or listening to me right now i'm pretty sure there's somebody out there right now sitting in a hot tub with some wine watching me say this i salute you sir or madam i may be opening up some floodgates i deeply regret later so please make sure you're wearing clothes and whatever you sent me there will be no naked people in the hot tub as part of this podcast i have integrity and standards let me know in the comments what ideas for contests you might have again if you get cash out from the app store google play and use the code lex podcast you get ten dollars and cash app will also donate ten dollars to first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with ryan hall who in your view is the greatest warrior in history ancient or modern that's a tough question and again i'm no historian by any measure so i'll probably do the worst like what are your best bands ever i'm like metallica and you know so i'll pick the material could just come out with a new album by the way entire orchestra that's that's kind of cool yeah them metallica will will always be one of the greatest yeah i agree with that example if they were a well-known yet awesome band let me say it's like a nickelback or something like that but i feel that feels cheap because everyone makes fun of nickelback yeah i don't know i guess it depends on how you want to define warrior something to think about when it comes to trying to evaluate various people or situations or things that i've read about or heard about are with the circumstances that they were involved in because i think a lot of times it's easy to look at the outcomes and obviously outcome we live in an outcome-driven world and you know outcomes do matter but at the same time like uh you know you look at let's say what cuba's been able to pull off you know from a combat sports perspective it's it's staggering you know like the amount of successful olympic level competitors they have in wrestling boxing judo um i mean they're a tiny little island with no money and no people it's that's shocking you know when you come you think about the olympics in the united states doing well of course we should do well i mean russia should do well china should do well india should do better than they do honestly obviously it means like they're not into it as much or at least certain sports because they have the resources people-wise um so talent's not going to be an issue so there's something to like where the starting point is like that's the argument with like uh what people say maradona i don't know if you're into it oh yeah big soccer okay they say mardon is better than messi because he basically carried the team and and won the world cup with the team that wouldn't otherwise win the world cup and then messi was only successful in barcelona because uh he has like superstars he's playing with other superstars right yeah that's fair to say i mean like like united there's a lot of factors that go into let's say winning a winning a soccer game and you know obviously barcelona you know particularly for various points in time had a ridiculous all-star squad of world-class players but um and i you know let's say for instance maybe they didn't have the creative players in argentina they needed to get the ball up to messi you know they didn't have like the nes the and you know the you know the again the backing there in the midfield but um because obviously argentina's always had ridiculous attacking players like even alongside messi but they're like the three killers up front and then a little less behind so it's interesting you say that it depends how you define warrior because you can probably take like some of the civil rights leaders you can go into that direction like leaders in general but if we just look at like the greatest martial artist in history in that direction do you have somebody in mind i would say at least three three that pop into my head and um would be uh hannibal um alexander the great and then maybe miyamoto musashi um you know the two commanders and then one you know guy but uh so it's it's interesting and then again you mentioned warriors being able to make a lot out of a little uh you know musashi's famous for winning duels you know that were oftentimes one there were one-on-one you know the alexander and hannibal were you know military commanders and one of them faced rome and that was an interesting thing oftentimes you know coming up with novel tactics different strategies sometimes under resourced doing having to do novel and crazy things there's skin in the game that's an interesting thing too i think a lot of times you know it's uh if you're playing a video game i don't think you can be a warrior because there's there's no skin in the game you get hurt you lose and it's a bummer it stings a little bit maybe it makes you feel slightly disappointed but uh you know musashi loses he loses um hannibal loses he loses alexander loses he loses and they lose i guess the people around them lose so that's almost like uh you could use even from a combat sports perspective a muhammad ali i mean you consider also their quality of opposition musashi was fighting high quality opposition obviously hannibal and al alexander particularly hannibal were fighting unbelievable opposition muhammad ali fought phenomenal opposition but he had skin in the game both in the ring and out and that actually meshes with as you mentioned like a civil rights you know type of situation where you are under resourced you're pushing the stone uphill and that was a neat thing i think about muhammad ali was how much you know personal conviction the man had to have in order to pull off what he was able to pull off both in in and outside of the ring and that reminds me of of again some of the other great leaders or great fighters throughout history so what do you make of the kind of very difficult idea that some of these conquerors like alexander the great and somebody that uh if you listen to hardcore history oh dan carlin uh who apparently elon musk is also a big fan of is the genghis khan episode you know a large percent of the world is uh is uh we can call genghis khan an ancestor so the difficult truth is about some of these conquerors is that there's a lot of murder and rape and pillage and stealing of resources and all that kind of stuff and yet they're often remembered as quite honorable i mean in the case of genghis khan there's a lot of people who argue if you look at the historically the way it's described in full context is he was ultimately like a given the time he was a liberator he was uh he was a progressive i should say uh you know like in terms of the the violence and the atrocities he committed he at least in the stories has always provided the option of not to do that it's only if you resist do you basically have the option do you want to join us or do you want to die and die horribly and so that's the progressive sort of uh that's the bernie sanders of the era nice so uh what do you make of that that there's just so much of these great conquerors there's so much murder that to us now would just seem insane it's funny you mentioned it i think that maybe it's a human nature thing that we want to uh or you know maybe or maybe a misunderstanding thing that we want to cast all of our characters and ourselves maybe as entirely good or as entirely negative when you know i guess i was the phrase or the saying you know one man's freedom fighter is another person's terrorist um is accurate and a lot of times i think you can understand as long as you're able to look from various people's perspective like if you look at the tv show the wire um which was obviously you know widely everybody loves the wire um i thought that they were everyone i mean i'm not saying anything that's that's not been said before compelling characters from all angles whether you like the character dislike the character you were able to understand the motivations of people doing various things even if they did wrongly they did rightly you know we want to cast all of the the demons throughout history as as completely inhuman when i think that makes it difficult for us to understand them and we want to look back at at the people that we think of as great um and entirely great and i think that we're you know we're experiencing the problems with this you know even right now socially and politically as we're trying to look back and decide the people we thought were good or not good or people we thought were bad and now good rather than going hey there's there's good and bad to all things and there are as you mentioned the genghis khan thing you don't have to fight back you do i respect you for it but then we're gonna have a conflict and then we'll see what happens and if you lose you're going to be sorry that you did because i have to make it that way if i want to continue utilizing this this kind of mo because i need to discourage the next guy from doing what you're doing right now and ultimately though i guess that's an interesting thing imagine you put every single person on planet earth in a cage crime drops you know uh all sorts there are certain positives to that and i it's just things are as they are it's difficult but that is ultimately more the law of the jungle and i think that we're able to supersede some of that now in modern times and i think we're fortunate but as you mentioned we look back and say oh this is horrible say no that that just is what it is that's how life is at a base level and you know again if you're a lion and i'm a gazelle i don't i don't really like it very much but we don't call the lion the bad guy we don't sanctify the gazelle or the other way around so it's just it's interesting when you pull back some of the controls that we put on our behavior and you know in modern life which i think are generally speaking positive you know we get down to how things often are and at the same time we could modern life was built by people like genghis khan so then you get down to the ends just to find the means it's a tough question these aren't things with easy answers at least if they are i certainly don't have the the smarts to figure out the answers to them but uh it's it's difficult i would just say people in the world are complicated and layered and depending upon which side of the line you're standing on at various times you know um you may like or dislike someone but i can't remember uh it's i can't remember who's whose idea was this is killing me but it's the veil of ignorance i guess um the philosophical you know um you know idea of the veil of ignorance where i go is is sticking everyone in the cage the right thing to do when i say or everyone but me and i say well no why well it would make my life easier if i just went over and took all of your stuff as long as you couldn't stop me i mean of course that's a great idea that's what everyone does in every video game but uh in skyrim you steal stuff when people aren't around but um ultimately you go well this isn't the right thing to do because if i were on the other side of it i would i would not appreciate it it's it's inherently not a good thing to do i'm only doing it because i think i'm going to win and that's a fine way to be but you don't have the white hat on i guess i would say so i think without those philosophical underpinnings to reign us in you know i guess morally speaking it's very difficult to say what's right or wrong and you'd say certain actions have a reaction almost like a physics sense if you kill everyone in your way for as long as you're able to your life will be easier i mean you're setting the table for someone doing the same to you when you're no longer the tough guy but it is what it is yeah if you look at like the instagram channel nature's metal it hurts my heart to watch to remind me a comfortable descendant of ape how vicious nature is just unapologetically uh just i mean there's a there's a process to it where the bad guy always wins the the violence is the solution to most problems or the flip side of that running away from violence is the solution depending on your skill set and it's funny to think of us humans with our extra little piece of brain that we're somehow trying to figure out like you said in the philosophical way how to supersede that how to like move past the viciousness the cruelty the just the cold exchange of nature but perhaps it's not so maybe that is nature maybe that's the way of life maybe we're trying too hard to uh we're being too egotistical and thinking we're somehow separate from nature we're somehow distant from that very thing i couldn't agree with him more in fact i think actually orson scott card you know who's the writer of a great book called anders game um was this was a statement that the main character you know ender uh made in the book his brother was brilliant um his brother was like kind of sociopathic brilliant kid that was ended up kicked out of the school that they were all into for battle commander dealing with his brother taught him that ultimately strength courage the ability to do violence for all the good and the bad of that is one of the fundamental most important things to be able to do in life because if you can't cause destruction if you can't cause pain you will be forever subject to those who can and i think that you mentioned egotism i think that that's a disease that could obviously strike any of us but it's something that we're looking at now we're you know i think we should be unbelievably thankful as people that live in the world that we do um that we can walk down the street without having to worry that i'm like well don't worry that that six foot six 270 pound person over there is just gonna leave me alone and i have a rolex on but whatever i'll be fine because that person's deciding to leave me alone because we've all agreed to live in this relatively you know sane and or you know constrained society because it benefits all of us and we're doing it because of a philosophical underpinning not because nature dictates it be that way because nature dictates it go in a very very different direction and the only person the only thing stopping that person from doing something to me is either me that person or someone else that will stand in between us and if i can't do it and there's no one there to stand in between us then the only thing stopping that person is that person and i have to hope that they're either disinterested or disinclined to do that sort of thing and i think that uh you know it's keeping in mind that that that is the fundamental nature of the world whether we like it or not um is important and i think the the quest to fundamentally alter human nature is going to be ultimately fruitless and then also it's it is a little bit egotistical the lion does what a lion does you know we we can try to box it in and we can try to you know guide this direction that direction but you know nature is as it is and as it always will be unless we want to start to constrain it significantly but now i'm starting to get into individual rights who put me in charge who says that i should be the one to make the choice is constraining because many of the most awful things that have happened throughout history one group or one person has decided to constrain others and we don't like genghis khan doing that well i'll do that on a little level are there going to be beneficial benefits and beneficiaries absolutely but there'll be losers in that too so i guess it's a it's a dangerous game it's almost like putting on the one ring you know we remember when frodo offered the one ring to gandalf and gandalf said no no i would take it away i would put it on i would use it out of the desire to do good but through me it would wheel the power so terrible you can't imagine i think that's that's the big question for anyone that decides that's able to have reach and able to have power i mean obviously i can't speak to that but imagine you did have national level global level power how would you use it would you try to change the world would you be glad that you did down the line i don't know yeah there's uh i mean that's the thing we're struggling now as a society maybe it'd be nice to get your quick comment on that which is um the people who have traditionally been powerless are now you know seeking a fairer society a more equal society and in in attaining more power justly there's also a realization at least from my perspective that power corrupts everyone even if you're even if the flag you wave is that of of justice right and so you know not to overuse the term but it'd be nice if you have thoughts about the whole idea of cancer culture and the internet and and twitter and so on where there's on nuance difficult discussions of uh of race of gender of fairness equality justice all these kinds of things there's a shouting down oftentimes of nuanced discussion of kind of trying to reason through these very difficult issues through our history through what our future looks like do you have thoughts about the internet discourse that's going on now is there something positive yeah i mean we can pull out of this it's an interesting thing to see i guess as you mentioned anytime you're wielding power whomever you are doing so carefully is is important and it's very very easy to look at the people that have power and that are using it poorly or have used it poorly and go hey you're the bad guy and then go well of course if i had power i'll use it properly and i may intend to use it properly and maybe i will but at the same time we see a lot of times people are people are people i think that a lot of the i think if you if you believe that that human beings are all one which i do you know no matter whether you're here you're there you're you're you got two arms two legs a heart a brain if we all live a similar experience you know and obviously with variations on a theme but uh you know you're no less a human being if you're a person i've never met from china than than some person in virginia it's we're all we're all people and i guess ultimately if i believe that human beings are corruptable and that power corrupts and that we're all fallible and we say and do things that either intentionally or unintentionally um that we wish we'd not um i think that i have to allow for a space i guess with the word it's almost a religious term but i guess i would just say grace and that's something that i see disappearing from discourse in the public or maybe it wasn't there i'm not sure but it's interesting you know watching this occur on the internet because also now no longer are you and i just having a talk sitting on a on a bus stop it's now in writing everything's in writing the old the old saying like don't put that in writing you're like don't put anything in writing that's how you get in trouble and basically uh you know with with the degree to which everything is recorded but recorded in tiny little bytes it's very very easy for me to wave every less little foolish ignorant incorrect or correct thing that someone has ever said or done in their face to support whatever argument that i'm trying to make about them or a situation and i think that you mentioned cancel culture or you know as it seems to exist obviously this is poisonous on its face this is poisonous um it's it's the sort of thing that doesn't incentivize proper behavior i mean you look at let's say one of the great monsters of history adolf hitler obviously who's done awful awful things but also for anyone that's even a minor student of history did some positive things as well we don't have to i don't have to embroider this person's crimes i don't have to act as if there was nothing good a monster has ever done and nothing bad that that a great person throughout history has ever done but imagine the ghost of adolf hitler were to pop up and go oh my gosh guys i'm so sorry i i know what i've done but i'd like to apologize and start to make it right well i mean you'd hope that you you know if he popped up over here you go well i don't really like what you've done and i don't like you but at the same time i'm glad to hear that you're attempting to make this right and push in a positive direction even if you can't make it right because otherwise what am i doing i'm disincentivizing change for the better i'm i'm looking to wield whatever power i have in a punitive fashion um which does not encourage people to do anything other than double down on on the wrongs that they've made knowing that at least they're going to have some support from the people that support that and i guess i want to you you hopefully look at the use of the internet as a tool that can educate and i guess i don't like the word empower but empower people to do various things extend their reach but uh but educate and learn rather than to further solidify little tribal things that exist which i think everyone in humanity and human history is is vulnerable to me look at the course of human history it's deeply tribal and the tribes or the groups that have been on top at various points in time have done a lot of times bad things to the ones that have not and you'd hope that we could learn lessons from the past and rather than you know committing the crimes that were you know that were committed against us recommitting them when we slide into the top position um say you know i could do this now but i'll not you know i understand the urge to to seek vengeance is strong of anyone that says differently i don't i wouldn't trust you know but at the same time we go i've we we have enough experience in history enough experience in life enough hopefully wisdom you know time in to go this isn't the right answer this is only going to replay the things the the worst parts of our history not the best and i want to encourage positive behavior and if i just again further lash out at people although understandably done done understandably i'm simply just going to just perpetuate the cycle that's gone on to this point so you hope that even though we're seeing a lot of a lot of turmoil societally at the moment and globally at the moment that uh i guess our better angels can prevail at a certain point but it's going to take a great deal of leadership and i think that we're we're sorely missing like a martin luther king style character at the moment or a great leader and i just i'm hoping that one will show up for sure and by the way a word i don't hear often and i think it's a beautiful one which is grace that's a really interesting word i'm gonna have to think about that it is there is a religious component to it but it's exactly right it um you have to somehow walk the line between you know you mentioned hitler i've been reading uh the rise and fall of the third reich i'm really thinking about the 1930s and what it's like to have economic my concern is the economic pain that people are feeling now quietly is really a suffering that's not being heard and there's echoes of that in the in the 20s and the 30s with the great depression and there's a hunger for a charismatic leader like you said there's a leader that could walk with grace could inspire could uh could bring people together with uh with sort of uh dreams of a better future that's positive but hitler did exactly everything that i just said except for the word positive which is he did give a dream to the german people who were great people who are great people of um of a better future it's just that a certain point that quickly turned into the better future requires literally expansion of more land it started with well if we want to build a great germany we need a little bit more land and so we need to kind of get austria then we need to kind of get france mostly because france doesn't understand that more land is really useful so we need to get rid of them and look what they did to us in versailles anyway but so the jew the jewish uh the holocaust is a separate thing i don't know well i don't know i don't know what to think about because uh so me being jewish and having a lot of the echoes of the suffering is in my family or the people that are lost i don't know because hitler wrote all about it in mineconf so i don't know if the evil he committed was there all along i mean and that that's where the question of forgiveness i mean hitler's such a difficult person to talk about but it's the question of on cancer culture who is deserving of forgiveness and who's not like the holocaust survivors that i've read about that i've heard the interviews with they've often spoken about the fact that the way for them to let go to overcome the atrocities that they've experienced is to forgive like forgiveness is the way out for them it's interesting to think about i don't know i don't know if i don't know if we're even a society ready to even contemplate an idea of forgiveness for hitler it's it's an interesting idea though it was it's a good thought exercise at the very least to think about like all these people that are being canceled for doing bad things of different degrees think of like louis ck or somebody like that for being not a good person but like what is the path for forgiveness so what's a good person what is the good part if that's a sliding scale that we could all find ourselves looking at the uncomfortable end of a gun on you know particularly down the line i mean you hope for the best but these definitions i guess like you said are important and who's doing the canceling who's being canceled i'm not necessarily as you said saying that that's entirely unjustified or certainly not it's certainly understandable and particularly you mentioned like a monster like an adolf hitler but it's also interesting i couldn't help but notice like you mentioned as a society us being able to apply forgiveness to someone who's done so much horror but people who are personal i'm of course many so many people in person affected but directly personally affected someone a survivor of the holocaust being able to let go on that i'm nowhere near big enough a person for that sort of thing but i guess that's that's an interesting thing you know being the person who was physically there potentially able to able to let go i don't know that's that's unbelievably powerful it's interesting i guess you have to wonder sometimes and this isn't obviously in regards to that to the holocaust but why why i'm holding on to various things am i what is it doing for me and what is it doing to me is it facilitative is it not and i guess that's something else that i i really enjoy when i was on ultimate fighter they uh they don't let you have any music or any books other than religious text so i brought a bible and i brought a quran and i started to read them side by side and it was it was really interesting reading the bible's a little drier quran's the crown is more interesting at least written but um i i think something that that was consistently brought up uh was the way the most merciful people want i don't think any of us want justice we think we want justice but i don't think we want justice justice is a dangerous dangerous dangerous game because maybe this person's wronged me deeply and i i want justice i want to balance it out because what is justice is not a balancing of the scales and sometimes you can understand it on a societal level i think it's fine i mean there's crime and punishment we can go for the benefits and the drawbacks of that but i think what any of us want is mercy within reason you know grace as you mentioned because justice is a very very very dangerous thing and it's a valuable and important thing but who gets to decide what's just what justice is actually meted out maybe i get to meet out justice but it's not i don't get my comeuppance well that sounds great but what happens when it's pointed back at me and uh i guess that comes back to the veil of ignorance you know the idea that that one day i will have to live in the world in which i've envisioned the world in which i've created i i think that a lot of times people love the idea of uh they're a judge for your crimes and a lawyer for theirs and i heard that the other day i thought it was great and uh i think that's it that's a dangerous thing and hopefully it gives us all pause before rightly or wrongly but always understandably you know wielding wielding serious power yeah justice is a kind of drug so if you look at history also been reading a lot about stalin i mean all those folks really i don't know i don't know what was inside hitler's head actually that he's a tricky one because i think he was legitimately insane stalin was not and stalin was like he literally thought he's doing a good thing he literally thought for the entirety of the time that communism is going to bring like that's the utopia and he's going to create a happy world and in his in his mind were ideas of justice of fairness of happiness of of uh yeah human flourishing and that's that's a drug and it somehow sadly pollutes the mind when you start thinking like that what's good for society and believing that you have a good sense of what's good for society that's intoxicating especially when others around you are feeling the same way and then you start like building up this movement and you forget that you are just like a you're you're like barely recently evolved from an ape like you don't know what the hell you're doing and then you start like killing witches or whatever like you start you start doing they did math let's be honest though i mean sometimes you got a witch has to go yeah we can all agree there which which has to go if if it floats or sinks which one i forget which which whichever one we need at the time honestly it's floating it should have sunk uh yeah but yeah we can definitely agree that we just have to go because you brought it up i uh tweeted recently but also just i'm one of the things i'm really ashamed of in my life is i haven't really read almost any of the sci-fi classics really yeah so like i my whole journey through reading was through like the literary philosophers that would say like camus jesse dostoevsky kafka like that place like that's a kind of sci-fi world in itself but it's it just it creates a world in which the the deepest questions about human nature can be explored i didn't realize this but the sci-fi world is the same it just puts it in a it like removes it from any kind of historical context where you can explore those same ideas in like space somewhere elsewhere in a different time a different place it allows you almost like more freedom to like construct these artificial things where you can just do crazy uh crazy kind of human experiments so i'm now working through it uh the books on my list are the foundation series by isaac asimov dune snow crash by neil stephenson and ender's game like you mentioned that's just kind of and then so i posted that and then of course like elon musk john uh carmack i don't know if you know him creator of doom and quake oh cool so see they all pitched in these nerds these ultra nerds just started like going like did these uh do you need to read this that and and the other so i've like started working out okay but it seems like the list i've mentioned holds up somewhat is there a book is there sci-fi books or series or authors that that you find are just amazing maybe another way to ask that is like what's the greatest sci-fi book of all time well i'd like to start by sharing something that i i'm embarrassed about is that i haven't read anything other than uh you know orson scott card j.r tolkien uh frank herbert tolkien yeah dude yep yeah yeah i'm aware through wikipedia and uh through through surface reading of things that like a book called the republic was written once um yeah there were some other motherboards you're uh a prolific reader of wikipedia articles well or occasionally uh whatever else it is that i waste my time on but but yeah so i also i should say i posted on reddit questions for uh ryan hall and there's like a million questions but like uh half of them have to do with dune no not really but like people bring up doom i don't understand why i did you mentioned doom before well i actually actually have a showy roll actually made us a ghee a dune themed ghee one time which i thought was kind of cool i'll send you i'll give you one we got extras but uh actually to your to your point actually this is a orson scott card quote actually the writer of bender's game um fiction because it's not about somebody who actually lived in the real world always has the possibility of being about oneself and i think that's a neat thing because i i have heard you know other very people whom i respect and very sharp people actually every now and then dig their heels and go i don't like fiction i only like non-fiction it's more it's more instructive and i would go i completely disagree with that i think we have a hard enough time figuring out what happened at 7 11 three hours ago that let me tell you what happened 600 years bc i'm like hey i'm interested but don't tell me this isn't a story too yeah there's a there's there's actu there's factual components i have no doubt but we struggle sometimes to like i guess what i like about fiction is that you can tell me a story it's all about people i mean every night there's more and less believable things um and i think dune would be an unbelievably well written in my opinion for to run you know what do i know but i really like doing i'll say that uh well-written example of you know human beings interacting with one another the political component to that the emotional the intellectual the relationship components all of that and uh i i think that dune is neat because it's a sci-fi novel but only in the only in the loosest sense it's it's really a story about religion about group dynamics about human potential about um belief learning politics governance ecology it's uh the best stories remind me of history the same way history hopefully is not just a a list of facts that i try to be able to recall or factoids that i try to recall but a story that i can understand and and see how how the threads of time kind of came together and created certain things and a lot of times like we say i'm like uh how the heck is what's going on right now or a hundred years from now or a hundred years in the past happened and you can look back far enough if we had accurate knowledge if we had that like that hypothetical perfect pool shot you know at the beginning of time we would see an unbroken chain of events that led us to where we are and and where we are will potentially lead us to where we're going which is again why hindsight's helpful but i think it's neat like i guess i really enjoy for instance a book like dune and they're actually making a movie out of it which i'm i'm skeptical of to be honest because it's it's going to be difficult to bring that to the screen for a variety of reasons but there's at least 100 questions ask ryan what do you think's about the new dune movie i am not enough of an authority to have any sort of decent opinion but i guess what i would say is so much of it goes on in the character's mind like how much of any of our day is any lived experience as it were is internal the majority how many times are people walking around and you know they can you could like hey what do you see right now i'm like oh well i see this picture i see a wall hey there's lex but really what what i was paying attention to was what was going on inside of my head for a moment and almost the rest of the world tuned out and kind of dimmed and uh yeah i guess um that i think that's going to be a struggle to to any time you want to bring that type of a written story to to a visual medium i think it's going to be more difficult but it'll it'll be interesting it's definitely my one of my favorite stories and it's been it's honestly helped me become better at life in my opinion better the martial arts and i think the the writer i think frank herbert was absolutely brilliant whether those were all his ideas which in reality none of us or all of our good ideas aren't ours we're a combination maybe came up with something you're a curator of other good ideas and some things you borrowed from somewhere without even realizing it but uh i think the the way the messages and the themes and the ideas that were conveyed particularly in the original novel or just absolutely brilliant is that the is that to you one of the greats and and the flip side of that like or another way to ask that is like if somebody's new to sci-fi is that something you would recommend that that is an entry point i'm not well read enough in this sci-fi world i haven't written a lot of like isaac asimov or anything like that but i just i'll recommend dune i'll be an obnoxious like evangelist for dune to anyone who'll listen okay so i yeah i would strongly recommend it so the other thing you mentioned now i should probably be talking to you about much more important things but the other thing you mentioned is skyrim uh do you play video games what's your favorite game what's what would you say is the greatest video game of all time because i'm a huge fan of elder scrolls oh yeah i mean i play a little bit um at this point you know a little little less uh finally moved into a new house so you're like an adult no no no no i'm like a better funded 12 year old yeah that's yeah that's entirely that's entirely accurate better funded 12 year old but um somewhat better funded 12-year-old not as well-funded as i wish but historically did you play video games oh yeah i played as a kid i was you know again i've always liked playing sports and and liked reading and i always enjoy video games but my favorite video game i think i've ever played was uh nicely the old republic um it was a star wars game a huge star wars fan until it became less so so recently disney um you don't like the i haven't watched it yet oh my my delorean oh dog oh i actually like mandalorian that was that was actually pretty good yeah waving this off yeah yeah i will if i could cancel one thing i would cancel disney store i'm gonna edit that part out okay let's go to the next but uh this is where if people are wondering if you're watching this on youtube and like the dislike amount is like 80 percent it's because of that comment so good job good job for making the internet hey nothing now what about uh baby yoda yeah i guess like he's little he's got ears and he uses the force sometimes and he passes out again no qualms with baby yoda yeah you don't have a heart okay i the let's go to jiu jitsu if it's okay uh so the audience of this podcast may not know much about jiu jitsu or they do because it's really part of the culture now but they don't really know much they see that so many people have fallen in love with it have been transformed through it but they don't know much about like what is this thing is there a way you could sort of try to explain the what is jiu jitsu what is the essence of this martial art that's captured the minds and hearts of so many people in the world i think that jiu jitsu is is a philosophy that's expressed physically and that it's the kind of development of the in mental capacity and physical capacity working in unison to uh move efficiently and almost flowingly unresistantly um with with a given situation with a with or physically resisting opponent um learning how to generate force on your own and how to steal force from the floor how to steal force from the other person and move in concert with it as opposed to clash against which if you watch two untrained people fight it's almost entirely a clash it's a runaway and clash or run away and clash um if you watch jiu jitsu done well it's it looks like water moving around a solid structure and and i think that that is expressed physically and i think that all of the things that anyone have really been able to do very very well in jiu jitsu end up kind of exemplifying that but i think that's true of martial arts in general i think that a lot of times like the clashing that we see going on um and working well is just the fact that you know you get very very physically powerful people every now and then they're able to get away with this but i don't think that that's and that's that's fantastic because ultimately it's a results-driven thing but i think that the essence of the martial arts is learning how to make more out of less and how to move with and be yielding almost like real life aikido and uh so you think of martial arts uh jiu jitsu as uh like water or flowing so aikido so moving around the the force as opposed to sort of maybe the wrestling mindset is finding a leverage where you can apply an exceptional amount of force so like it's like maximizing the application of force i guess maybe that's a better way to i'd like to marry the two ideas you know because i think you flow until the point at which you are the greater force at which point in time you can apply but uh if you look at the best wrestlers and when i say best i don't necessarily mean most successful although of course most successful are always very very good um throughout the course of history in boxing in wrestling in judo they're magical they they disappear and reappear it's like fighting a ghost that that is like incorporeal when you want to find it but then when you don't want to find it when you don't want to find it it finds you and i i think that we see that in the like the bouvie source citatives of wrestling um and you know i guess you could look at uh floyd mayweather or willie pep or you know pernell whitaker in boxing um as brilliant examples of disappearing and reappearing and when you're strong it's almost like gorilla warfare when you're strong i'm nowhere to be found when you're weak you can't get rid of me and i think that's what we're looking for yeah the tear brothers are incredible at that they just they they look like uh skinny starbucks baristas and uh they just manhandle everybody like effort effortlessly they look like they just kind of woke up rolled out of bed go fighting for like the the gold medal at the olympics and just effortlessly throw uh like there's a match against you i guess yo romero yeah so like you you know if you look at like who is the guy who's like intimidating in this case uh and the terrifying looking it's uh it's joe romero just like a physical specimen and obviously like a super accomplished wrestler i think this is for the gold medal yeah in 2008 2000 yeah sydney and then there this is the year you all took silver and what you like just to just show you like there's a inside trip effortless gucci and he does it again you know it's a really creative kind of wrestling where it's organic yeah you're throwing all these kinds of things this is a mix of judo a mix of like weird kind of moves it's not like as funky as uh ben askren it's it's just like legitimate basic well it's not funky for funky's sake and i'm not poking right then asking to imply that that's what he's doing but it's like it's it's funny it's like a lot of times it's almost like a musashi talked a lot about that you know that the only goal of combat is to win is the the outcome is it's outcome driven versus like flourishing you know cool looking movements it's like unless that had a utilitarian purpose like what are you wasting your time with that both in the fight and also you know in practice but but as you mentioned it's almost like it looks like judo it looks like wrestling it looks like jiu jitsu it's almost like i guess reminds me all of the martial arts is again deeply tribal as well i i want to learn lex friedman martial arts and then i want to learn another you know i guess transcendent person's martial arts and it just happened to be the set of movements that you tended to do most of the time thanks to your body type and your opposition and whatnot but then i try to codify that and force those to work as opposed to going i want to understand how the body works in concert and in in congress with something else and other forces and move appropriately and that's why it's like it always struck me that the psyche brothers are great examples of just moving like water but they to use bruce lee which is a little trite but again it's brilliant it's like water can flow or what it can crash and they would crash when they needed to crash and they would flow when they needed to flow but they would flow for the purpose of dissipating and then crash when they would win and at the right moment then go back to flowing the second that the other person found them and it's just it's beautiful to watch it's artistic and i think that great expression of anything physical is ultimately studied as a science but expressed as an art and i think that that's something that gets lost in jiu jitsu a lot of times when it gets a little bit a little nerdy like do this hand to your hand here like it's like the more details i have the better when in reality that's just not not in my experience how it's done might be a fun exercise of saying like what are the main positions and submissions in the art of jiu jitsu you don't have to be complete that's a ridiculously i apologize for putting you on the spot like this but it might be a nice exercise to think through it sure i mean i would just say that they're they're you have your arms bend in various ways you have key lock americana straight arm locks kimura omoplata omoplata is a chemorecognizable plot that's just executed emissions like submissions breaking off your arm in all kinds of ways but ultimately the question is let's say you were a terminator like a robot that i which of course you are going on it's like all right so we're being completely literal but uh and i and i couldn't harm you with any of these things would i still use these positions the answer is yes they they create leverage they create control they create shapes that i can affect and that can affect me and they can be affected through other forces and other objects or structures like the ground or the wall i really enjoy mixed martial arts because there's another component rather than just me and you and the floor there's me you the floor and the wall and it's another player in the game that doesn't exist uh in a grappling context with an uh in a non-enclosed you know i guess area of combat but um you can strangle me or choke me um what do you call it uh without my arms being involved or you can use one of my shoulders to pin one side of my one carotid artery off and you can enclose the other you can turn my knee in the exact same ways that you can turn my arm straight this way and that way you can add a rotation to that or it can be directly linear against the joint so i guess what i would say is the more that i've been able to understand jiu jitsu the more that i've been it's given me a look into how we learn language where rather than learning five bazillion adjectives i go i understand what an adjective is and of course we are all read into some degree of vocabulary i understand what an adverb does and i understand what an adverb is i know what a noun is i know what the component parts of a sentence are i know what you know i guess a clause a contraction any of these things and it allows you to be um interesting and artistic with your language to the extent that you can but i can't like i can speak a degree of spanish but i'm not even slightly artistic in spanish i would be something i speak like like a child with a head injury and anyway um your basic understanding of the english language allows you to then be a student of spanish 100 but i'm limited by my experience i'm limited by my understanding of techniques and i'm limited unders by my understanding almost like let's say techniques are like these are like vocabulary um so even if i kind of sort of grasp the sentence structure and the thought process and the thought patterns of of spanish which it's interesting because just even though the orientation and the organization of a language and i've thought about this a great deal um you know the way that i perceive the world is affected deeply by the language that i learned you know the again if i learned i have no idea the chinese language structures but i can only imagine that it would be that it would affect it's like a different lens we're looking at the same thing but i have i have a different set of sunglasses on than you do um and uh that's that's very very interesting i'll use the quran as an example you know apparently it's unbelievably poetic in in arabic still neat and was interesting reading in english but i'm told by people that i trust that it just one doesn't bear resemblance to the other and i think that's a very interesting thing that you may be able to say the same thing but in in a more in i guess in a different way in a more artistic way that that may not translate on a one-for-one kind of fidelity but um the more that we're able to understand about how the body works the more examples of the body working this way the body working that way the body working that way the more that i'm able to eventually become an artist but it has to be studied as a science first and it does start with technique collection vocabulary collection the same way we learn in school you remember how to say quickly 17 different ways and let's say i speak spanish i'm only i only know three so you might use quickly you might use an adjective like quickly in spanish but use one of the many many options to describe that that i don't understand now i sit there and go like wait what i can't be artistic i can't be as organic with the language as i'd like so i believe that jiu jitsu a lot of times starts with the acquisition of a lot of hey do this this this drill this technique here's an american americana to an arm lock arm locked to a triangle um but the problem with that is oftentimes we get stuck in that phase and i people eventually become move collectors or sequence collectors and i notice this when i'm trying to do dvds or i guess like an instructional series now or even teaching in class i don't believe in that form of learning anymore um not that it's not valuable but i don't believe i don't understand jujitsu on that level anymore so what i'm trying to do is get across the basic ideas to people and say hey you need to fill in the gaps with going to class all the time you need to go hey learn this move learn that technique learn that technique because otherwise i'm basically just throwing at you like 75 different words that you could use but that hasn't really taught you how to how to speak a language whereas if you give me the language structure you can fill in these pieces on your own and then eventually speak organically in lex form which will be ultimately unique to you because otherwise you just end up being a weird facsimile of whatever it is that i'm doing for mostly the worst i'd say but uh yeah that's what people i mean people comment like is this especially people haven't listened to me before uh is this guy drunk or high does he does mit really allow slow people to uh to be like like what's what's wrong with him is he getting sleep are you okay and does he need help so that that's similar with my jiu jitsu it's like this is this guy is this guy really whatever rank i was throughout i remember just like is this guy really this rank i just have a very kind of certain way of sitting and being slow and lazy looking that that was ultimately the language that i had to discover and it was uh it was yeah it was a very liberating moment i think of probably a few years of getting my ass kicked especially with open guard and butterfly to where you really allow yourself to take in the entirety of the language and realize that um that i'm not i'm different i'm a unique i'm i'm unique and like i have a very uh i have a language i have a set of techniques a way i move my body that needs that i'm the one to discover like it's you can only you can learn specific techniques and so on but you really have to understand your own body that's the beautiful thing about jiu jitsu like you said is like the the connection about your philosophy your view of the world with the physical and like connecting those two things how you perceive the world how you interpret ideas of the world about exhaustion about force about effortlessness like what it really means to relax all these kinds of loose concepts and then actually teach your body to like do those things and like you know and be able to apply force and spurts to be able to relax in sports and like figure all that stuff out for my for your my individual body but it's as you mentioned that's i couldn't agree with you more it's a discovery process and no one can cheat that process which is at the same time it's almost like imagine i want to start writing books in second grade unless maybe i'm like staggeringly brilliant i wish i could only conceptualize someone being able to do that but maybe a mozart of the english language where you're out there doing it but for most of us we don't have enough knowledge enough information enough experience to be able to be to express ourselves so we have to basically input repeat um which is important but it's the process as you say of going through that of getting your ass kicked just like well that didn't work well that didn't work that felt right but i don't know nobody else does that i guess i don't believe in that versus eventually going i don't know i'll just try going my own way and see what happens and now i'll get yelled at and people won't like me and if it works they'll say i got lucky and if it doesn't work they'll say i was dumb but uh which maybe all is right but basically uh you know going through that iterative process that allows you to eventually find your self-expression and find your voice so that you you fight the same way that you speak the same way that you write the same way that you think in a way that that is uniquely you that will also ultimately allow you to understand other people being uniquely them because even if you can only conceptualize and i think about this a lot for society stuff where i go well this is how i feel about this but am i objectively right maybe about a couple things but that's a small box that i have to be very very careful about what i think is objective and versus what's not and i have to be open to the possibility that all the things that i think are objectively correct may or may not be and that should allow me to have some degree of compassion or consideration for other people both in their martial arts journey and in their in their journey you know as people as human beings because i understand that they're on a it's a we're all on a path right it's all a again an iterative process of eventual self-expression but i think that's one of the things that we see having trouble when we see tribalism which i mean raises an expression of that political affiliation expression of that all of these things that can go in really uncomfortable directions people are looking for hey where do i plant my feet over here where's where's the thing that i know is right and that we can all agree on the following and i think that we see that in martial arts we're like oh i do this style why do that style i do that stuff which is like hey man we're all just pushing forward in a certain direction you're trying to do our best and i understand why you feel the way you do i may have felt like that at one point too but uh you know what i'm just trying to learn and understand versus i've already acquired enough knowledge let me cross my arms and start to to look who's fucking up around here yeah and and i think that uh that that's an it's an interesting trap that i think is very human trapped to fall into but it definitely happens early on it's something it's a joke in the jiu jitsu world right like how the blue belt that knows everything well initially it's like what i know nothing and i at least think i know nothing then i'd learn a little bit and i think it's a lot bit and then you know the more you learn the more you go like i don't even know what i'm doing yeah that's exactly right we kind of talked about it a little bit but uh once again a lot of people that listen to this have never been on the mat have never tried jiu jitsu but are really curious about it everybody at all positions like i think elon musk's kids are not doing jiu jitsu andrew yang is like they're all you know the world is curious it's a it's a nice it seems to be a nice methodology by which to humble your ego which to grow intellectually and physically so people are curious about it so the natural question is if they're curious about it how would you recommend they get started maybe like what do you recommend the first day week month year first couple years look like like how do you ease into it and make sure that it's a positive experience and you progress in the most optimal and positive way the first thing you can do is simply ask yourself why why you want to be involved you know i remember the first day that i walked into ronan athletics in new york city to train under um godfather my son now christian montes and i didn't know what i was getting myself into i played baseball through high school and i wanted i was at manhattan college in the bronx and i wanted to go and learn martial arts because it was always something that was interesting to me but it was never something that that was i that i knew was accessible and it definitely wasn't really around in northern virginia where i grew up whereas then you stick yourself in in manhattan and there's stuff everywhere so anyway i guess i didn't know what to expect um i didn't know if i was going to get beat up if people were going to be nice if people were not going to be nice um but what i began with was i think expectation management and i think that that's something that uh i would that'll be the first thing that i would start is almost imagining what is it that i'm getting myself into because i love the martial arts with with the martial arts has given me everything in life and i'm so thankful i wouldn't be sitting here um without without that that experience that journey of the people that i've met the place that i got i could never ever have ever imagined um and i'm just unbelievably thankful for that but i think that the thing that um that helped me most of all was starting with you know my mom said something to me one time and she said you know there's two types of people in various situations there's why and there's why not and you know it's understandable to have questions concerns things like that um but maybe sometimes a little bit easier when you're when you're younger to just trust people or just say oh well you know um but uh we go hey you want to climb that rock i'm like yeah why not let's go hey you want to jump in that river yeah why not sure versus if i have to reason my way into everything i have to be talked into everything a lot of times i'll talk myself out of it and i think that a lot of times this is the thinker's disease you want to figure out what's going to happen and what you should expect to have happen before you get involved versus going using the old bruce lee saying again it's like no amount of thinking or training on the on the side of the river will teach you how to swim you have to jump in and there are risks associated with that and so uh i guess uh psychological are usually the biggest ones that's the biggest hurdle and physical but the biggest thing that i guess i would suggest to anyone to say why do you want to do this you're like well i want to challenge myself i want to learn i would like to learn to fight i wanted to learn to fight so that i could protect myself and if and if anything else other people if only within arms reach um i perceived that if i had some small degree of power um i generally wouldn't use it which is why i was like i'll give it a try i'll try to be reasonable and hopefully if i make a mistake i'll apologize to people but basically uh i said yeah i'd like to have that and i wanna i know this is gonna be challenging and we'll see what happens and that means that getting beat up and i didn't get like hurt but getting roughed up and getting my arm bent this way or that way getting choked i was like well this is all supposed to happen that's no big deal it would be like going and joining the army during peace time and then going oh i'm just doing this for a college education you're like okay that's cool man and then all of a sudden war breaks out and they want to send me somewhere and i'm like whoa whoa whoa whoa i didn't sign up for that gig actu actually you did whether you realized it or not you may not have thought that you did but you did so getting your mind right and and just going what are my expectations this activity what is it that i'm looking to do and of course you know you're you're going into a gym you're going into a place that you don't know people you probably don't know people and you don't know the coach and even if you do want to hey how you doing shake your hand type of level you know 95 percent of my students don't know me not really you know i'll try to be polite and not annoy them too much but they don't know me and i don't know them um i understand if they don't trust me i wouldn't trust trust me either if i were them but at the same time someone has to take that leap and one of the things that i've noticed um as a martial arts instructor that's the biggest struggle uh with dealing with adults which is why a lot of people like to teach kids is because kids don't ask don't argue now that also means there's there's all sorts of pitfalls with that sort of thing and that can be an issue but you know i guess a lot of times people get to a point in their life you know in their 20s early 30s where now i'm i'm a manager now i know what i'm doing no one talks to me like that yeah versus like hey man you go join boot camp i don't care if you are elon musk they're gonna tell you to shut up and do push-ups yeah and that's what's great about it yeah um so you are taking a leap of faith into a world that you're gonna be a tiny fish and you gotta hope that the people um who are who are guiding you in that in that journey are gonna have i can't say even say your best interests at heart because they don't even know you but they'll they'll try to do no harm and they'll try to help you in the way that they would understand and i guess that's for instance that's what i would try to do with anyone that that comes into my gym i would try to help them in the way that i understand they need as best i can in as safe and reasonable a way as possible but sometimes in a way that's going to make them uncomfortable particularly if physical combat and and it's not something they've done before if a lot of people go in without even having played you know contact sports and so that can be a big jump and you have to understand if if that's where you're starting from no worries but you're going to have to kind of work your way to it and it's going to be uncomfortable and and that's okay it's part of the process and you're gonna have some bumps and bruises and you're not gonna want to roll with that guy in the corner because that that person's rough and they beat you up and they're like okay but is this a big hurt or is it a little hurt if it's a big hurt okay if it's a little hurt you need to use you just drop a little bit yeah it's such an interesting balance because to find i think one of the most important things as in anything i think in life is the selection of the people or that you put around you i mean that's true with the like getting married that's true with uh like if you go to if people ask me like graduate students like your phd advisor can um can be the difference it's everything it's like you spend five years with somebody they're going to basically define the more impact on you than anybody you marry anybody you hang out with it's a huge impact and the same with the the coach selection which is like the school selection is it's going to be really important about in terms of like who you select will uh define how happy like the trajectory of your growth and how happy you are with the entirety of the experience and yet like the the flip side of that is especially if you have an ego especially if you are the manager then you need to let go of some stuff you're gonna feel like shit with the good with the best kind of coach that's that's what you need right but there's a nice there's a weird balance there to find like i i mean like and everybody needs a different thing like i'm much more uh i enjoy being sort of like it sounds weird but like i am you know from the wrestling background i enjoy feeling like crap in the sense like the coach like getting beat up i don't actually enjoy it it's not like some masochistic thing or whatever it's the growth like i like the anxiety i like uh feeling uh like like shit when i go home like emotionally physically it's like it's growth it's a sign of growth right like if you're not having to feel those things you're probably in your comfort zone which is fine but that's not your growth zone right and everybody has a different threshold for that and you i mean the the beautiful thing about jiu jitsu is like it's also has like a yoga feel to it like you're learning about your body so depending on the gym and depending on in fact the coaches the people around you within the gym you can select little groups too kind of like the people with who you roll like if you're a smaller person it doesn't mean you have to go against big people you can go against the people who like smoke a lot of weed and they're chill or you can go against like that crazy ripped blue belt competitor who's like out to destroy everybody and depending on like what your mindset is you can kind of select that it's just such a fascinating journey uh of like basically self-discovery i couldn't agree with you more it's i mean what you need may change over time right maybe what you needed what you need today could change six months from now or a year from now and that's something that i experience i'll use my uh first coach christian again as a great example of someone who i really look up to and respect and someone who helped me a lot like at a time when i really needed some guidance and i needed to learn martial arts but get into i the hens of gracie's gym was right down the street from where christian was teaching and christian was a blue belt at the time it was uh he was teaching at a place called fight house which was this awesome like you know like 90s early 2000s you know warehouse area uh down on fashion avenue in uh in manhattan off of like between seventh and eighth and uh it was like like two basketball courts wide but like there was the sambo guys over here there was the kali guys over there there was a wing chun over there with jits in the corner and hens was one of the most famous academies in the world at that time still is and i just didn't know what enzo gracie was and i mean it's a great gym and it's a fantastic place for people to train but i think what was right for me at the time was to i stumbled into a you know like a two-person elevator up and found a place where six people trained at that time and i had someone that that i could that could give me some like in addition to martial arts advice like personal guidance and that made it that made a big difference and then one initially we would have like competitions or like intra intra you know gym competitions with the sambo guys we would comp we would roll with them and like again it was great because they were just a bunch of like like russian dudes from like brighton beach and they would come down and then we would all fight and then everyone would train and we'd all drink tea and then go home and uh anyway uh what was uh it was super super tough and they were like again just a tough group of people it was great and then i remember when i decided after like four or five months i'm like man i really want to try to take this seriously and i told christian about that and he's like well hey i think you need to do the following and it was you know like hey here's there was a guy named jeff ruth who was uh about at the time which was a much bigger deal than it is now but it was 10-0 as an mma fighter a lot of amateur body spirits super tough dude and jeff was was the best person at that time that i'd ever trained with and i just got squashed christians beat me up too but like jeff would just absolutely kick the crap out of me and i was like this is awesome and this was back when i was at home i went home for the summer for that and chris is like hey i think you should stay because i told him that's what i was thinking and this was a coach that you know when it's like when initially was exactly what i needed and then he's like well hey that's not what i'm doing here maybe they're going to be able to help you on to a path that's that's kind of commensurate with what your goals are at the moment and then you know that was a niche that was an interesting thing and i really got i feel that i was fortunate to start um at a place where my coach was able to transition roles and and and do so comfortably and i think that that also was probably a factor of the fact that you know where he'd done some of his training prior like there have been issues with with the coach there we're like not supporting not having the support you know feeling like hey like i'm gonna hold on to my students i'm gonna hold on to my best guy or my best girl even if i can't take them where they need to go um so that was an interesting thing and just recognizing also though that the people like the same way you're an individual going into a gym and you don't know what you're getting into your coach is a person too and he or she you know they may have been doing this activity longer than you but they're not they're not some weird little you know all-knowing god they don't know anything but they're gonna they may say something that pisses you off they may they may yell at you they may help you they may inadvertently cause you some sort of you know some sort of issue and just being able to recognize that even though i say this to people and i've said this to people in my gym i'm like you know we're in the service industry man but i'm not at your service like don't get it twisted like i will absolutely do my best to help people i'm there to do my best as a martial arts coach but i'm here to do my best as a martial arts coach and i'll do my best and periodically i make mistakes and i own an apology or two and i'll try to give them out when i can but uh we're not mcdonald's it's not oh you gave me 100 bucks so you do whatever you want in here this is my house this is my gym this is my dojo this is this is the martial arts this is not a basketball team yeah there's something beautiful about martial arts like exactly as you said as the coach like in wrestling and at least collegiate like high level wrestling it's like there's a dictatorship aspect to a coach that is very important to have like this this ridiculous sometimes nature of like master and so on and bowing all these traditions there's something it seems ridiculous from the outside perhaps but there's something really powerful to that because that process of you said why not of letting go of the leap of faith requires you to believe that the coach has your best interest in mind and just give yourself over to their ideas of how how you should grow and that's an interesting thing i mean i've never been able to really see coaches i've had as human they're always you always it's like a father figure or like this you always put them in this position of power and i think that's i think at least for me it's been a very it's been a very useful way to see the coach because it allows you to not think and let go and really allow yourself to grow and emotionally deal with all the beatings they'll push you where past oftentimes where you would have stopped yourself right which is great and hopefully they know they if they're paying attention and they're they're still a person they can make mistakes but they'll push you further than you would have gone but not so far that it's not facilitative right right that's something that i can say like ferraza hobby um the head coach at tristar my head coach for mma kenny florian one of the head coaches for mma have both been phenomenal influences paul schreiner who's the uh one of the assistants at marcelo garcia's academy um coached me in jiu jitsu for a long time brilliant instructor they've all been able to do that and i think what's interesting about all of those guys they're very sharp but they they're very intuitive as well and i think that for us actually uh you know told me about something that john wooden said john wooden the legendary ucla basketball coach just a simple philosophical idea just he said some people's life is a bowl of shit it needs some whipped cream in it some people's life is a bowl of whipped cream needs a little bit of shit in it just to balance it out and it's an interesting thing coaching everyone the same way doesn't work you know that's i think the difference between a coach and an instructor and a lot of times people think they want to coach but they really want an instructor i'm like hey lex tell me what to do not how to do it and then other times people think they want you know an instructor and they really want to coach i'm like man this guy's just giving me information a coach is so much more than an instructor and that's a huge leap and that's something that i think that people need to understand when they're going into martial arts and i understand i can totally grasp why they don't because how how would they know but uh i think about this a lot like me giving you 150 dollars for a month which is not nothing that's for sure that does not that pays for instructor really coach is a relationship that gets developed because can you imagine like just the amount of emotional investment and and time thinking away from from like oh alex isn't here anymore what can i do to help him what does he need like that's that's serious and that's the difference between that's that's oftentimes the difference that at getting getting over the hump in various situations so it's a it's an interesting you know bargain that's being made like commitment by the by the instructor who becomes a coach commitment by the student you know like there's a financial transaction there's a lot of things going on there but i feel very fortunate to have had not just instructors in my time but coaches and that means sometimes we butted heads and sometimes i look back and i think i was right and other times looked back on my own no they were definitely right but there was always the trust um with the exception of one time that i feel that trust was greatly betrayed um that rightly or wrongly whether mistakes mistakes will be made but everyone is attempting to do do the right thing under no circumstances would i intentionally do anything malicious you know versus hey i might have done i'm going to burn your house down but you can be darn sure it wasn't on purpose and i think that as long as there's that mutual understanding and mutual belief of goodwill which again doesn't just magic up out of nowhere i understand i think that that's when then great things can happen and i look at all the athletes that i know you know the guys and girls that i've watched become fantastic in various places almost invariably it never happened alone yeah yeah i'm really torn about that like um maybe you can help have you seen the movie whiplash so it's uh i would say from an outsider's perspective people should watch it's a i guess jazz band it's a movie about a drummer and the instructor and he it's a basically i would say from the outsider's perspective it's a toxic relationship but he's really the coach whatever we call him pushes the the musician the drama to his limits like to where he just feels like shit um emotionally it's a it looks like a toxic relationship but it's one that ultimately is very productive for the improvement of the musician i have the same like in my own experience i had um i got a chance to train a couple places regularly and so one of my coaches uh who is a great human being a lot of people love him but when i was a blue belt he was pushing me a lot for competition and every time i stepped on the mat i was uh anxious and almost afraid of training because of like the places i'm gonna have to go and then the i can't i don't know what's good or bad because i think i've become a better person because of that experience like i needed that and on the flip side like the place i got my black belt from balance studios is i remember also blue belt uh the coach sitting down and i was going to competition and he saw something in me where he said um you know like good luck but win or lose we always love you like i i re i remember that because i really needed that at that time like i was putting so much pressure on myself like i'm not an actual professional competitor you know i just competed like i'm a pg student like but like it was clearly having a psychological effect on me and that's what a great coach does it's like you know it's like life is more important than jiu-jitsu sense that's right it's bigger so they find you use jiu-jitsu when you need it to grow as a person and when it overwhelms you you you have to pull that person out like look at the bigger picture always look at the bigger picture it's fascinating and i don't know what to make of it i don't think i would have it any other way is both the anxiety and the and the love yeah i think that i couldn't that's a really interesting thing that you're describing that i i guess it kind of brings me back to a lot of the other things we've been discussing is just almost like the the reciprocal nature of everything where no pressure that's great everyone's happy all the time it's either i mean let's uh use an example of sci-fi movies let's say the matrix which of course the first one was amazing and then each subsequent movie made the series worse but um but basically i'm working on a new one by the way yeah i've heard we'll see i was hoping for the best but um but basically uh you know it's like hey we started our first initial world agent smith says to neo he's like our first world was a utopia where everyone was happy and nothing ever went wrong it's like your primitive cerebrum rejected it and i think that there's obviously i mean what do i think but i guess well i'm here so i might as well say what i think um i guess uh you know great things are fantastic a kind gentle place is fantastic and this is again why i love dune because i think doon does such a great job of expressing frank herbert does such a great job of expressing again the reciprocal nature of these ideas you know look at uh look at sparta for instance or at least what i understand sparta from the reading and also watching 300. um you know and reading wikipedia and reading the wikipedia article about the movie not the place um but uh it's um that's a hard brutal place and that was their benefit to that like absolutely was there drawback to that absolutely is it sustainable i should i would think probably not um i mean granted it hasn't sustained but i mean that type of a of a thing it burns too hot almost and it uh it destroys the host at a certain point and you know i guess that that type of unforgiving nature but entirely entirely permissive has its own issues and i guess coming back to your what your description of like describing a toxic relationship is a very dangerous and tricky thing because it's almost like uh it's like bird's-eye view me it's what you know you see let's say a husband and a wife arguing and you're like all right well sort of somebody hitting somebody i need to keep myself out of this because i have no idea what i'm seeing something but i don't know what's going on or why specifically and again short of it going to a place that's that just out out of bounds i don't know who's right here i don't know who's wrong and i don't know what phase of this things they're in so i guess long term what's good for yeah both people right it's dangerous for so if i want to put my finger on the scale i can understand the desire to do i'm like hey guys let's break it up yeah but and that may be the right thing at the time but at the same time i'm not sure so i think back to all of the times that you know that like you mentioned your coach pushing you when very very hard and then other times going like hey let's put in perspective here i think that's an interesting thing for high performance and i think that we're seeing that again societally you know now or at least maybe that's it just pops up on my internet feed periodically um but coaches shouldn't be allowed to do this or yell at this person to yell at that person like well have you ever been go to a boxing gym it's not a commercial entity not really a real boxing not la boxing not a ufc gym like a real place you're going to see what things are like when it's entirely performance-based go to wrestling room at a high level you know again there's there's left and right limits and there are such things obviously as abuse of course but and that should never be tolerated um but it's not a commercial entity i don't need to be sweet to you if you're if you're screwing up if you're dropping the ball and in fact recognizing that i'm not doing you a favor or the team a favor by by being permissive of that type of behavior i think is important everything in its context and at its time is important and i guess i can think again at the times that i've been put put or had put on me like a great deal of pressure to do x y as a year to succeed um or to push for success and i can't look back fondly enough on those times they were tough at the time but without that i'm not sitting here without that i don't go from growing up in a very nice family in the suburbs to fighting at the highest level in jiu jitsu nogi and now in mixed martial arts starting a career at age 27. you know i don't it just doesn't happen because people generally speaking from that background don't get pushed hard enough physically to be able to make that transition and that has benefits and it has drawbacks you know when you stare into the abyss it stares back and i think that that's an important thing to understand you know you stare long enough you you can become something that you don't that you would be sorry that you did you don't look enough and you don't have perspective either you know and i i think that that's an interesting thing i can speak to someone who's relative to being someone who's relatively articulate and reasonably i try to be reasonable but you know i'll say inspiring if people get crazy with me they get a warning and then i'm gonna crack them and what did they expect oh they hear the guy on an interview but who did they think they were meeting because there's also the guy in the ring and there's layers there too i remember training with you it's kind of funny there's like there's well you didn't know who i was i mean you still like i have a really good strength a lot by the way that so i don't remember what rank i was but it might have been purple or something like that and i did some like i you had this look on your face which i've often seen in black belts it's like here he goes again like here here's him trying this thing and then when i kind of annoyed you a little bit with it now i get that it was a good like i you know i did something somewhat effective like some like maybe a little bit off balance yeah there's i just peeled off a little layer of ryan hall to where i was like okay let me let me like there there's like layers underneath the covers are like somewhere in there like so it was like okay this like new guy rolls in here he thinks he can do this stupid thing and then and then you start to beat the hell out of me but the the point is there's layers here from the guy who was being interviewed now to like genghis khan but it's but it's all in the same body right but it's like all of us are like that right in various different directions and recognizing that's okay it's just there are consequences to all every choice that we make as a consequence sometimes there's like objectively wrong or objectively right but at least in my mind that's a pretty small box everything else is just there's a consequence of that do you like that consequence do you not and who do i want to become what do i want to try to hone myself or anyone else into and also like but this is something i've screwed up as a coach plenty of times you know like if someone says if you're if like i come to like lex i really really want to take you know research very seriously like okay i believe you now i haven't shown you that but i believe you're like okay and now me not showing up to research or to study or not being up until three in the morning thinking about this is no longer acceptable there was a time like five seconds before me making that statement that if i went to bed without reading the book that i needed to read no worries but the second that i made that statement your your expectations for me change and maybe it's something that's something that i've screwed up a whole bunch of times in my um as a teacher because it's an interesting thing obviously you know being a like running a martial arts school as you're principally an athlete um is sometimes i don't pay enough attention to what people are doing i just go oh okay you say xyz i'm like roger that i believe you're cool i will now put you in category x and whether rightly or wrongly like maybe this person didn't understand what they were asking for or i didn't express this or the other and it just it caused cross wires and then most times you hash it out you have a discussion you figure out get to the bottom of what people are trying to do or what they want but uh if i was paying more attention i think i could have been a lot more effective or if i had more experience and sometimes maybe i'm not sharp enough or i don't person i'm not perceptive enough to be able to to see what's going on and maybe with years more down the line i'll be able to have a sharper perception but uh i think that's another one of those interesting things that some that sometimes i would caution or not caution but just to inform a prospective martial arts student depending upon where you're going um you know this you both you and also your coach or other people in the room they wear many hats and sometimes there's a i had the wrong hat on you were talking to me as lex the guy i didn't realize you were talking to me i thought she would tell me his elects the guy i didn't realize she talked me as lex the martial artist i'm like oh crap i was talking to the wrong person so it's almost like if you had a like i run my gym with my wife she's a black belt so she's my wife she's my peers as a martial artist uh on in jiu jitsu he's here by the way in judging so exactly all right well all right so but a fellow black belt and i guess like another he doesn't have a microphone so you can't hear all the trash he's talking exactly but it can be tough and that's something we've had to work through a lot and it's like looking back and it's like now being where i'm at now and it's easy me to say that because she's in the room and i don't want to stab me just continue to slowly poison me over time yeah um which frankly i understand um you know it's it's the sort of thing that is now way more effective than anything else i could really reasonably expect to have um but there were times when when both of us you know were justifiably annoyed at the other because of crossed wires and sometimes you know you just have to scream in anywhere mr standing anyway but again like i've i coached some of my friends i've coached i've coached my friend who i've known since i was four years old you know sometimes i don't go hey buddy how you doing someone's like what the fuck are you doing put your hand over there how many times we talked about this and then you walk away and you can see him look at you crooked and you're like oh crap oh yeah he thought i was talking to his friend yeah well all right we need to talk this one out hashing out and not he's wrong how could he possibly think that way like oh no i totally understand that but if i was 22 like doesn't he know i'm a purple belt some nonsense like that and it's and it doesn't come from a bad place but it's just i guess that comes back to society to anything people only have the perspective that they have and the awareness that we have and so again going back and going hey guys grace like i don't expect it's not fair for me to go i for ufc why doesn't this guy who came in as an attorney understand how hardcore this needs to be and like how could he yeah and at the same time though if if i'm using the language of someone that is interested in at least performance from a martial arts perspective i understand how that could be off-putting let's say for instance someone that's comple like all of that would be out of bounds in their normal workplace but if they think of the gym as my office then whether they agree or disagree with what's going on they go okay i hear why i see why that might have happened let's talk about this and we can again all push forward in a positive direction that benefits i guess everyone's journey throughout the activity and now on top of all that there's moods okay i mean especially lately uh i think two days ago maybe yesterday no two days ago i've never been that cranky in my life i think i i don't know what it was but i wanted to tell everybody how much they annoyed me it was like i i was just very conscious of this feeling of like why why is this happening right now so i consciously decided as i usually do in those cases to not say anything to anybody how do you do that uh well i you know it's uh it's yeah meditating because it's not i i tend to i tend to then visualize what's gonna happen in the next like how is this gonna make my life better like if i say something that mean to somebody else i have uh just started a conflict that will just escalate will continue will add more conflict to my life it will make things i just don't like the feeling you will create and so you live a lot enough life to know that like uh it's just like with like street fighting you know i i i would get into a lot of fights when i was younger just on the street but then you realize like it's not like a jiu jitsu match or something like that it's not it'll escalate it'll it'll might come back at you it'll like that person might find you again but more importantly the anxiety of it of having created little enemies in this world distorts the way you see the world so i've noticed that like if i'm shitty to people on the internet which i haven't been i think in a long time is like it it somehow brings the shittiness to you more and more it escalates like the more love you put out there the more like the people who put love out like surround you well you mentioned forgiveness as well like you said like i guess back to the original you know the holocaust survivor scenario we're like oh my god like you think of the ultimate in in like i've never experienced one one billionth of that level of of pain and horror and it's like and i can't let this little thing go you know i guess that's an interesting thing i think you're just making the point in your personal life i guess the same way right yeah there yeah and on the internet it's hard i've somehow gotten i mean you've you've had a level of celebrity for a while i've recently gotten some level of like celebrity and like these people who are just shitty for no reason come out from all from all places like calling me a fraud or anything else i'm using a jain silent bob strike back they find out a movie's gonna be made about them and people are talking shit on the internet and they're like what's the internet and then someone shows them and they're like what and they go to a message board and they go to hollywood to try to stop it from being made and they eventually get money for their likeness and they use the money to buy plane tickets and fly around and beat the shit out of all the people that talk bad about them yeah it's tough i mean it's uh i'm i'm having trouble with it because there's people like yeah there's you know there's posts and forums and like heated discussions about is lex vaping a fraud i don't know what has he really done and there's like and then there's people like well i think he's an alright guy but i'm not sure like like there's like literal discussions and i'm like like nobody like if you increase the level of celebrity there's going to be like one of the things that hurts my heart a little bit is like some level of toxicity around joe rogan for example there's like communities of people that now like talk about him selling out for example all that kind of stuff and i don't you know and joe i've talked to him about it is amazing that he uh he says don't read the comments he legitimately doesn't read the comments his heart and his soul doesn't give a damn about the comments all he gives a damn about is his friends like one of the things that's really inspiring to me and that's i've had a conversation with them offline about spotify and uh the removed episodes people are curious um it's uh it's a thing on the internet where uh i think you can play taylor swift's songs on i'll write that down but you can also now play joe rogan podcast oh cool and they gave him 100 million dollars so that that's uh you know that's awesome it's yeah uh but the thing i've had a discussion with him and i made a video about it that i took down because the toxicity is like it's hard to put into words but he will give away the 100 million in a second if he ever has to compromise who he is like he doesn't i mean he already said as he talked about he's made quote unquote fuck you money a long time ago he doesn't need any more money he doesn't care it's nice to have money whatever but like he'll give it away so the it's nice to see when people like him at a level of celebrity level success and financial success don't change at all they're just the same thing that makes you happy is talking in his case talking shit with his friends in case of most of us really just just hanging out with friends doing the things you love in his case doing the things he loves without any like you know the texas way the uh freedom like without any corporate bureaucracy bullshit that rolls in and says well maybe you shouldn't say fuck you know like more than 20 times a podcast or something like that like those kinds like rules like people like he says in a suit and tie they show up and say stuff um oddly enough people that could never to have done what he does yeah exactly and it's kind of inspiring to see that and i i hope people i hope people realize how special of a human he is he's inspired uh like people like me like i'm just i'm a scientist right so he inspired somebody like me from a very different walk of life to be like kind to others to be open-minded i don't know that uh it's a special dude so like people need to support that and treasure that as opposed to uh as opposed to be toxic about it if i mean what uh i just people really for a long time have told me that it would be awesome if ryan hall's on goes on joe rogan i definitely think that'll be an awesome thing have you listened to joe has he been a part of your life in some kind of way um you know well joe's always i've i remember watching joe on fear factor when i was a little kid which is cool so i've actually gotten a like from a from a bird's eye view watch you know his his kind of just path through life yeah but one of the things that that i always appreciate and again i barely know joe are then to shake his hand he interviewed me after the uh briefing in the ring after the bj penn fight but um one of the things that i've always admired about joe is that i think he had fucking money from the start i think that zero dollars is fuck you money for joe i think and that's something i respect about him a great deal um because as you say it's interesting to watch it's like you you hope that uh george saint pierre is like this it's really neat now i'm not super close to george but we're teammates at tristar and he's never been anything but a gentleman is one of those people that if you didn't know george was famous when you walked in the gym you'd have no idea he's not holding court not doing it he's just you know training and he'll help out an amateur doing this if you have a question for him he'll help me like i'm nobody man he he would give me advice and train me it was super cool and he didn't kill me which i really appreciated he's a gentleman but uh you know it's like you you meet someone and you go man i'm so it's so cool that this is the guy who's the best that this is the guy who who's been successful and then you go why are they successful like i said true to what they're doing they haven't changed they're the same as they've been and i remember i got to try start in 2012 and george was already already george st pierre but i remember watching and talking to people and they're like oh man george is the same as he's always been in this neat i see him in the gym training now and again giving advice now and it seems like joe has always been consistent and it's neat to watch someone not compromise on their values and not change who they are and not you know periodically like you know again we all make mistakes like you have a bad day or this or that an apology needs to be issued or even my bad or this or that and you're like yeah they just move on they're not afraid to be themselves and they're not afraid to be wrong they're not afraid to make a mistake as you as you mentioned open-minded and so i'm like so what are the correct beliefs to have about this that i know going in everyone's going to be okay with what i'm saying which is usually the beginning of a conversation that's going to go nowhere right and uh it's it's neat to see um the things i guess that he's created on his own as a result of the authenticity that's there and it reminds me of like dave chappelle and again i don't know i've never met dave but it's neat to see someone that's clearly again authentic in their own way doing their own thing and they're because of that they're above the corporate nonsense but what's funny i think the message behind all of it is hey guys we all are i can't promise you that i'm gonna have money joe couldn't promise you that he's gonna have money now it ended up working out but he was above that nonsense from the jump and he just continued to be above it by never giving it any mind and just going like yeah i'm gonna be a reasonable person i'm gonna try to learn i'm gonna try to grow and uh if i say something annoying you can come and talk to me about it we get to the bottom of it and i'm like if i need to say my bed thanks appreciate it you know i will and if i don't need to i'm like hey i still appreciate the talk thanks man i'll shake your hand and we carry on and we go our separate ways and hopefully i'll treat you respect you treats me with respect and and that's about it and i guess i think it's a lesson that it can work out no matter what you don't have to kowtow to like these weird powers that be and whether you're at this level or at this level but you can live your life the way that you want and as you mentioned talk shit with your friends hang out be happy and it just so happens that that resonates with people it actually reminds me of like speaking to mit and being in boston is like good will hunting you know like again that's what he really want to do he could have gone this way could have gone that way and it was an interesting story but it's like this person wants to hang out with his buddies and wants to do other things and again happens to be brilliant and happens to be able to do all these other things but there was it i guess it's like at least in my mind a story of authenticity as well and it was both the same thing in the robin williams character and i i just think that that's a message because watch watching things occur on the internet as they do now things so many things playing out in the public eye i feel like so many private or otherwise formerly private discussions and disputes and and you know interactions now become they all have a a well what is this going to say when it goes public so how can i couch what i'm saying or how can i word this in a way that's going to get people on my side to use the right buzzwords and not use the wrong buzzwords and it's just neat to see people you know in their own way flip the bird to that because i just think that that's that's just not how a human being is meant to think or interact i'm curious what you think about the thing that recently has you know me like hosting this podcast i sometimes think about like who should i talk to and not in terms of like it's the the old hitler question now hitler i would definitely talk to because post world war ii because everyone knows he's evil the question whether you talk to hitler in 1937 like when people who are really students of what's going on understand that this is a very dangerous human being but a large number of part of the world they're like well he's a leader who cares for germany so the question i have it's interesting to me it involves a particular person named who also lives in austin texas named alex jones i don't know if you're familiar with the guy i am familiar with mr jones uh i've actually recently just listened to infowars like one episode of his uh show i guess that he does every day and it kind of reminds me of a time in college when i drank too much tequila there's no turning back like no it's like like the the mistakes you make that like it it it's i mean you don't know where you're gonna wake up you don't know who you're gonna kill or not kill or steal or rob it it's it's unclear so that that it felt like i was getting pulled into a dark place where pretty much everybody is a pedophile that's trying to control the world so bill gates definitely is a pedophile everybody in power anybody in power there's a kind of a deep skepticism about power and a conspiratorial way to see the world where everything is like dark forces in all corners it's like the way you feel when you're a kid that there's a monster hiding in the closet which is also why you leap over the bed from like four feet away there's a strategy yes so but he says that you're just being weak you need to look under the bed under the bed there's monsters and we need to be aware of them because they're growing they're multiplying you should be and they're touching children they're touching children exactly so it all connects but the the i when i listened to him and i thought about like do i want to talk to him on this podcast for example when i listened to his conversation with joe rogan the two times he talked on there to me it was somehow entertaining like it was fun to listen to it's fun to listen to a madman go on for four hours because it's almost like theater um like this is what i talked to joe about when people try to censor alex jones joe says that the people who try to censor him don't give enough credit to the intelligence of human beings to like understand like that like what a person says on a large platform does not necessarily is not the truth you can be a madman and say crazy things and people are intelligent enough to hear uh certain things be when they're said like the earth is flat they can they can be intelligent enough not to all of a sudden start believing that the earth is flat like they they're intelligent enough to sort of select different ideas and be able to enjoy the theater of a particular ridiculous over-the-top conversation without being sort of influenced where they start believing like toxic set of beliefs now there's a lot of sort of other kinds of people especially now with cancer culture that say well you don't want to give platform to crazy people that that ultimately whose beliefs might lead to dangerous consequences like and i see it very often now with conspiracy theories that go that go like way too far like for example would i i'm not i haven't looked into it so i'm sorry i will look into it but uh it hurts my heart to see that on bill gates in my opinion the person who has saved and improved more lives than probably any human in history literally because of the money he's invested in helping like just just the work he's done on like malaria in africa the number of people he's helped is huge and yet every interview anything you see now on bill gates everyone is calling him i believe haven't looked into it but i believe everyone's calling him a pedophile i don't know the full structure of it but it's it's just a very it feels like an army of like it feels like it's hundreds of thousands of people that's what it feels like it might be a much smaller percentage but it feels like a huge number of people are calling them a pedophile so that's the that's the flip side if you allow if you give platform to conspiracy theories like that then you start to have bigger and bigger percent of the population believe in these crazy things i just i wanted to put it out there because i don't know what to think of that if you put yourself in joe rogan's shoes if you put yourself in my shoes if you put yourself just in your own shoes i'm in my shoes right now great if you're staying your shoes just stay in your shoes can i have your work would you talk would you give platform to people like alex jones would would you talk to somebody like alex jones or or not uh i yes i would and i feel very strongly about this honestly um well i think that it's it's an interesting thing and i i would just say a lot of times i can understand you know very very clearly why people would take issue with the idea of i guess what they perceive to be amplifying this man's voice this man's reach um you know as as a demonstrable negative but i think um you know when you take a step back further uh the the cure is more damaging than the disease and significantly so um i guess i think that i'm very very wary of i think being where you mentioned alex jones being wary of power and people with it that's a lot of times there's a lot of truth and validity to crazy things that people say it's the conspiracy theories that stick are the ones that sound credible at least quasi-credible in some aspect and it's almost like it seems to me like an anchor in people's mind and it is also funny to me obviously the the bill gates it's so funny to tar people with things like pedophile racist rapist like these are things that we're basically trying to pick words that no one can ever support someone who does these things yeah and that's you know and that changes year by year currently pedophile is totally in as a thing to call somebody just just as a it used to be communist or marxist cleveland browns fan you know like come on you know who actually nobody likes the bronze so yeah i'll agree i felt that that was that's why i picked one that's the trick is you find a group of people that nobody likes we're good here all right that's the move but uh yeah that's a creepy thing though because that is that is the creepy thing it's like people are always looking for groups of people are always looking for and i find this really deeply disturbing um like hey so who's the guy that we can all get away with you know just treating like dirt who's the guy that i can be a dick to i can just walk up and punch in the face and no one's gonna say anything yeah and it's even if i you know people do that with whether it's literal nazis or someone that i called nazi you know i guess what's the bigger issue this person's ridiculous beliefs or what i'm doing and you mentioned hitler before and obviously mein kampf being a you know like the outline for some of the things he did later and when the evil was it always there did it did it take root later on or to flourish later on but was was adolf hitler a problem because he had crazy ideas or because he did things i think it's because it's not i think i know it's because he did things now if i'm going to start punishing thought crime i i'm going to have to start punishing thought crime and that's a terrifying concept even if i'm right about the certain about the objectively correct about the things that i decide to call out of bounds who put me in charge and made me arbiter of good taste and how long until i decide that something else is is out of bounds it's always a sliding scale or it's always just a sliding standard and i i find that that you know to be more of a concern than people doing crazy things because i guess if you mention alex jones you know putting out ridiculous ridiculous ideas ridiculous theories i think that most people don't look at alex jones as a credible person no i'm not going to pretend to be deeply read into all of his beliefs or the things that he's trying to peddle um but there's plenty of things that are quasi mainstream that i think on with this side or that side that maybe not comparably ridiculous but are yeah you know particularly in hindsight or you know are we're not or silly and i guess uh the idea of of getting a group of people together to decide what we're not going to tolerate is a very very tricky thing and i think that you know it reminds me of law or you know even you know religion when it gets to like what are the things that we don't like how do we feel about rape it's like no under no circumstances is that an acceptable behavior murder no that's not acceptable behavior killing i don't know kind of depends on the situation are you at war were you justified were you acting in self-defense okay so it's not now murder is a specific type of killing the same way you know other things should be a specific type of something else but i guess we we draw a line of murder we say if you want to exist in our society you can't do this this cannot be done and then we go theft if someone said hey i murdered that guy can you understand where i'm coming from i might say yeah i'll hear you out doesn't mean that i think you're right but i'm like have you ever been wronged so deeply that you could imagine that you could kill someone i'm like no i haven't but i could conceptualize someone doing that and i'm like yeah okay and you still need to go you still need to face you know criminal justice as we have it in our system at least that's how we've decided yeah there's it's interesting you have to be able to like there's if you look at the history of discourse in this country i think it's still true but i'm not sure it's changed since 9 11. is uh it used to be impossible to criticize um a soldier it was easier to criticize war it was harder to criticize soldiers for allowing themselves to be the tools of war i tend to be maybe it's the russian upbringing it's the it's the combat thing i tend to romanticize war and soldiers i see soldiers as heroes but i've also heard people that not only say that soldiers are the war is bad they say soldiers are bad what's their argument it's it's the kind of a libertarian view that they're basically slaves to evil right war is evil and they're they're giving they are suspending their moral and ethical like as like duties as a human being to become the tools of evil that's sort of the argument if you see war as evil i mean i think it's useful to hear that but there for a long part in history that was completely unacceptable same with abortion if you see abortion as murder i mean if i classify it in that if i put it in that in that basket it starts we're living in the midst of like a genocide from that perspective could you feel how people could be deeply upset by abortion you know of course looked at from a different perspective you say i don't believe it to be murder that's not how i see it then you go oh well if that's the genesis of your your thought process then you're like yeah okay now i see how we can come to a different thing but i guess we go well abortion is murder period therefore if you support it you support murder that's a convenient way for me to tar you right but i guess that's kind of coming back to the alec jones i'm i'm this nuance it's uh you have to have the nuance in these kinds of conversations and i have to be willing to have the conversation and i have to be willing to sit down if i can't sit down across from like the most violently racist angry hypothetical internet you know conceived person that none of us have ever actually met in real life but or hopefully not um you know and go like well of course i believe that this person's wrong but allow me to change do my best i'll hear him out and i'll go no i can go point by point and explain why this guy or this girl is wrong and hopefully bring them over to a more reasonable position where they will have better beliefs and they will like objectively better beliefs and beliefs that will will and they'll treat other people better why would i want to marginalize this person now i might not want to talk i might want to invite them to my barbecue if they're acting like a jerk all the time but how could i would it not make the world a better place if i'd hear them out and they go look if you're going to sit down and talk with me we're going to have to have a discussion i'll hear what you have to say and if i can't if i can explain to someone why their ridiculous belief is wrong then i might i must not be so confident in my position and i guess that's where i come back to the alex jones thing as you mentioned you know with uh with bill gates and and you're much more familiar with with the specifics of all the good that he's done but you know again he's been an unbelievable force for good you know in this world you can list a b c d things that the man has has done that his foundation has done and you know positive things and then the other people could speculate about ridiculous crazy levels of of evil but you can't produce any evidence for that sort of thing because if you could the man would find himself in trouble you know and anyway i guess what i would would say is that why you can't force me to accept the truth the same way you could write down two plus two equals four on a piece of paper and show me how it works and i could say nah but that doesn't make it not true and you've still given yourself an opportunity to present your case you've presented it to me and you've also for anyone listening and watching you know you've been able to critically assess what's gone on you know or critically address back and forth you know kind of the the discourse and i think that you almost you're making your case for the public so i guess like you know when it comes to just never not engaging with these people that seems to me to be cowardly and i think that that's a something that we're seeing in society right now i think i think we're seeing a crisis of courage in society all over the place and i think that's where we're seeing poor leadership i think we're seeing understandable things happening everywhere but we need stronger voices and stronger stronger beliefs that have a conviction and are willing to engage with others not just turning into a shouting contest and not i didn't win because there's more of me oh i voted i outvoted you that's nice too but that's a stand-in for bullets that's saying i won because there's more of me that doesn't mean that i'm right because plenty of horrible and unpopular now things have been very very deeply popular in the past and would have won a popular vote does that make them right i'd said clearly not so i guess uh you'd hope that we engage with these people and that you can do your best to bring them over to a more reasonable position if you believe that you have one and if you can't well at least you made the effort and i think that that's something where martial arts shows the value it's like or do you know if you're going to go win your next fight i'm like i have no idea i will proceed forward with with full effort and and you know i will fight with dignity i'll fight with honor and i'll fight with courage and i i'll use everything that i have and i will play within the bounds of the game and that's that and the result will be what it'll be but i'll walk into and out of that ring with my head held high because i will know that i did my part i did my job the outcome the specific outcome is not in my control it's just strongly in my influence and and i think that that's something that helped me that martial arts has taught me because other times even when i was successful or unsuccessful i would focus on if i won i'm i won therefore i'm good i lost therefore i'm bad this other guy won or lost therefore as opposed to evaluating their method and i think it's so easy when we're taking a bird's-eye view of things to not evaluate how someone's doing things you're not evaluating my process you're simply evaluating my outcome and i could have stumbled into something very very good or very very bad and we can look back and i think that's the value of history i mean i don't mean to get on my dang high horse but it's like that's the value of history we can see the unbroken chain or the chain of events that led us somewhere and then only with only with the eyes of history can we truly evaluate things unless we're in the room watching it happen and i guess that's again where we start to go most of the big bad scary things that have happened in history that are done particularly on an industrial scale which implies governmental power and things like that or these the equivalent involve groups of people getting together and going hey we're not going to deal with that guy giant groups of people so maybe we're right this time but maybe we're wrong next time and i guess i would be back to the gandalf putting on the one ring i would be very very hesitant even if we thought we were in the right to simply try to try to marginalize just on general principle even people like alex jones whom on their face are pretty ridiculous like you said you should sit down with adolf hitler and talk to the man i agree with you to play a little devil's advocate is alex jones might be a bad example but if we look at because he has a face he is a human he's a real person there's also trolls on the internet 4chan the worry i have with those folks is that and there might be parallels to martial arts is they practice guerrilla warfare meaning they don't necessarily want to arrive at the truth they just always want to cut at the ankles of the powerful like they want to always break down the powerful and even if they i mean it's they turn everything into a game so they let's see if we can make the world let's see if we can make a trend that bill gates is a pedophile right they make it into a game they get excited about this game they see the powerful let's see if we can convince that like who is the most positive person we can think of let's see if we can turn them into evil and they've tried that with like with like everybody and some and it seems to stick and they're good at it assam would argue whatever you think about our current president that he has some elements of that which is he's figured out whatever this music of social discourse that's going on he's figured out how to always troll the mainstream like flow of consciousness that's the the media he always kind of says stuff that annoys a very large number of people and he enjoys that because it's like taking the powerful taking the way things were before and he like shakes it up by saying the most inappropriate thing almost on purpose or instinctually and so on the problem i have with that is that doesn't the powerful thing there is it uh brings the power the those in power down a notch that's a great thing the negative thing is it doesn't push us closer to a nuanced careful rigorous discourse towards truth it's like showing up to a party and just like starting to yell it doesn't create a good conversation it just makes everything into a game where truth doesn't even seem like a thing we can even hope to achieve like that makes sense and i guess as you mentioned it'll come back to another movie because i don't do books and do movies some people just want to watch the world burn right and i guess there's that's a creepy creepy you know kind of urge that some people have and it also is some people you're like hey would you like to throw a brick through that glass window and you're like yeah sure like no i'm not going to do that because i think about what's going to what's going to what's going to occur like something's going to be hurt someone's property not going to do it versus hey you want to see what'll happen like yeah sure you know kids are always like i have my son he just grabbed spider-man and dropped small table spider-man fell my spider-man didn't fall shawn like he dropped him you knocked him off the table and he'll grin and basically uh you know it's it's an interesting thing like you said like playing that p these people are appealing to and you know and also almost like the little dog factor of like i people do want to watch the powerful get taken down a notch for all the good and the not good of that because plenty of people it seems to me that have found their way to incredibly high positions some some have just found themselves there and many many many many many people you know men and women of of all backgrounds are brilliant and have worked hard and yeah of course there's luck and there's there's luck into everything there you know lebron james in spite of being the best basketball player on god's green earth is fortunate that he didn't get hit by a car you know it's fortunate they didn't tear his knee you know but thankfully we get to see all these things you know but um i i guess uh it's if people don't have any skin in the game you never know what they're gonna do and i think that's the problem with the internet you know that people get to be nameless be faceless that's why guerrilla fighters are outside of the bounds of war like you don't have a uniform on you're like i don't know who you're from you don't get the same treatment that a soldier gets um for and people well that's crazy actually there's reasons for this because otherwise people are able to assail things and there's no there's no one responsible there's no way to go and say hey where's where did this come from what's the root of this what how can i address this and i think that's the problem of the internet's problem on twitter's problem places like 4chan i wouldn't mind seeing that type of stuff go away if i'm frank but that's not the same thing as people with a face people with people who are willing to stand there and say hi my name is so and so even if i have ridiculous beliefs hopefully you know people will hear me out and then if i'm wrong educate me but i i guess you hope that the real i guess in my mind antidote to all of this silliness is education and and i think that that's something that we're you know critical thinking is is not necessarily i went to school in america and you know i feel very fortunate but critical thinking is not something that's that's focused on i mean and it's it's tough it's almost like talking about jiu-jitsu it's tough to teach critical thinking when i don't know any words you have to teach me techniques you can't teach me to be an artist but recognize that the techniques are the beginning not the end ultimately it's the artistry that we're searching for not just the not just the science or the or the by rote memorization and i guess you know you'd hope that people's ability to think critically and recognize that majority rule or whoever's loudest does not mean that they're right by any stretch of the imagination and we don't appeal to that and we don't bow to that will help them to help inoculate them against the ridiculous things that come out of these places these dark places that that are objectively not great but the i guess all circling back if even if we swatted these you know these bad things out of existence right now we've got to be very very careful doing that because it's who's doing the swatting this political group that's in power right now the people that support our current president would maybe feel a certain way the people that support another option would feel differently as to what exactly defines toxic and i you know i guess that that's what gives me pause yeah and but also the grace thing i tend to believe that the the technology you said education but the the platforms we use like twitter and the reddit and all these platforms have a role to play to teach us grace meaning they ins they should help us incentivize the kind of behavior that is incentivized in real life like being a dick in real life is not incentivized like one-on-one interaction like there's cases where it is but usually being kind to each other is incentivized on the internet it's not like you get likes for being for mocking people in a funny in a humorous way and it can be dark kind of mocking depending on the community you can go you can go to the appearance if somebody's a little fat or a little too skinny you can comment on their appearance the hair the way their hair looks like the appearance stuff it could be on the people comment all the time on the uh level of eloquence of my speech go fuck yourself i like it it's creepy though watching watching previously like this used to be lowbrow though like people doing this type of stuff it's creepy watching like our political figures get into this type of game yes but again it's a little bit refreshing right it's a the my hope with donald trump was is that he would shake up the the people who wear suits usually the like if you're from dc i remember like showing up i actually didn't wear what i usually wear in dc because i was like everybody's wearing a suit and tie when i was like giving talks and stuff except for mudge who wears jeans and a t-shirt doesn't give a damn mudge is uh a forever renegade uh but i don't even remember what uh oh yeah so my hope with trump was that huge shake up that system just say like like uh to inject new ideas to inject new energy of course the way it turned out is different but like there's uh it turns out that you might want to have somebody who's like like an andrew yang type character who is full of ideas that are very different and inject the energy new energy into the system through youthful new ideas versus through the troll that like that's very good at sort of mocking and like playing outside the the rules of the game but trump did reveal powerfully i don't know what to think of it that um it's just a game and you don't have to play by the rules that's both inspiring and dark deeply depressing right yeah and i don't know what to do with it i don't i mean the same i'm not drawing parallels not drawing parallels between our president and adolf hitler but it certainly and there's a lot of in history a lot of positive and a lot of negative things happen when charismatic leaders realize they don't have to play by the rules you can just flip the table it's the that uh uh kevin spacey show no house cards house of cards where you just flip the table or whatever you don't have to play by the rules of the chess game you can flip the table one wonders if that's always been done in private you know i guess because that's i mean even look obviously the united states is a as a republic but we had we had bush then we had clinton and we had more bush than we had president obama then we were about to have another clinton that's fairly creepy yeah even on its own but now we added another i mean i'm sure we'll have a generation of trumps no gee we uh you know i'm russian so i think we humans like kings still and queens there's something we're attracted to the the thing we talked about coaches there's something in us that longs towards that authoritarian control one of the beautiful things about america the second amendment uh is uh we also like individual freedom that's one of the one of the unique aspects at the founding of this country and still and for me is the beacon of hope that uh somehow there's the fire freedom burns in there like that texas feel that i that gives me hope the fu energy that revolts against the power which as we discussed power corrupts and ultimately leads to sort of uh degradation of the whoever's ruling is the people it's interesting though like it seems to me maybe i'm just i don't know if i'm reading this properly when i when i see it but it's it seems to me that that like you said that that you know flip the bird i'm gonna do me within reason like as long as i'm not hurting you uh is idea that that very much at least in my mind defines the american ideal or at least part of the consciousness of the united states is is under attack to a certain extent you know um in if only like i can think to like you know maybe a generation behind us um it's it's becoming more collectivist yeah you know for all the good and also the not good of that and it's uh you know not in not in terms not in terms of policy at this point but just in terms of like uh the consciousness and i wonder if that's a an internet thing you know people are more in touch with one another than they've as far as i can tell they've ever been at least more than in my lifetime and uh you know the rest of the world seems much closer than it did you know living in virginia california seems very far away being on the internet it's just right there i can hear about it i can see it i can i can interact with people from there you know i remember uh you know being in tennessee at uh you know one time and then and reading about you know events taking place in you know the middle east and it just seemed like a mile away it seemed like a unbelievably far distance and then another time when you're in dc you just feel like oh you read about something happening in paris and it just feels like it's just right around the corner because dc is a seat of a seat of power where things are just occurring all the time and uh you know i guess you you wonder about that's where i come back to the group decisions to not listen to this person or to cancel this or to you know we all the moral majority shall do the following as opposed to as long as you're not hurting me and long as you're not hurting anyone else i have to let you do i have to let you be on general principle even if i don't like you i'm very free to not like you i'm free to speak out against you but i'm not it is not within my right or and not with it and it's not i i would not be right to attempt to attack you and that is an interesting thing though when we see words being redefined or words being defined whether it's toxicity whether it's violence if i think that what you're saying is is your speech is by itself you know a violence or a precursor to violence i'm justified in doing all sorts of things you know and and that creeps me out significantly because again even if it ends up being pointed in a good direction initially it's only a matter of time and actually that brings me to uh another dune oh yeah i got all day um how much are they paying you but wait about say the uh the frank herbert estate not enough frankly oh let's see and how many books are there in dune that's a gen question you're also a fan of i read the whole series but not a couple of the i read all the prequels as well it was the exception of a couple is there a book one for dune dune it would be book one and even the prequels it's still all better if you start like i read dune and then read the original what is it six and then i went back and started to read something like just like watching star wars you want to start at episode four or whatever yeah i think so that's the way that's the move and then stop at six call it a day watch the mandalorian and but well i thought you're not walking back here no i like the mandalorian yeah that is what i said yeah i was told that i was heartless for not liking baby yoda boy we don't talk about a couple of the movies not including the middle or in the middle and it's fine it's the more recent movies that we don't like to talk about yeah oh the what's his name the the goofy guy uh ryan no no no the creature the goofy creature with the jar jar yeah jar jar do you ever see the the the jar jar binks is actually like the dark lord of the sith theory that fixed the whole initial trilogy we're like he's he's like goofing around and like making it all the way through battles and when you're like wait a minute he oops his way he walks over to a pool does a triple backflip falls in you're like it's just bizarre this is the this is the alex jones theory of of star wars he's actually running one that actually was like hey we should vote in chancellor chancellor palpatine or senator palpatine like right before they put jar jar in charge first off what did they think was gonna happen and second off that was i just think that'd be great like oops oh man i guess he's the emperor now that would have been great but actually to the to the cancel and all the other stuff again it's just you'd hope that it gives pause and i think about this for fighting because a lot of times i'll use this example people and people like fight fans and you know like ufc they love people that run out and try to murder each other and it's entertaining and it's super entertaining but you know floyd mayweather doesn't resonate with people as much it's like people start i remember the time when floyd was not as popular now people think people love floyd because he's 50-0 floyd and oh man and finally he had so much success that we all can't help but recognize the man's genius and greatness but prior to that oh he's boring he's this he's that he fights you know with he's circumspect he's cautious he's he's pressing he's intelligent deeply intelligent and uh when you watch people go out and try to murder each other you can flip a coin 100 times and you know you can get you could be lucky enough to get 100 heads but it's still a coin flip and i think that that's what's going on all the time is you know people are getting an outcome that they want but it wasn't a well thought out situation and that's why you'll win by five in a row by knockout and then lose three in a row and then people will go well what happened to that guy he used to be so great no he's doing what he's always been doing it's just it was getting great outcomes on a coin flip prior and it's getting negative outcomes on a coin flip now but uh i guess what i would say is it watches it's interesting watching you know i guess societal beliefs become such a a thing that we're almost adopting on a religious level if we're not careful and if if when i say religious level i mean like like pan life like this is guiding all of my choices for all the good and the bad of that and this is the dune quote is when religion and politics travel on the same card the writers believe that nothing can stand in their way their movements become headlong faster and faster and faster they put aside all thoughts of obstacles and forget that the precipice does not show itself to the man in the blind rush until it's too late and i think that that's again the the pause we go oh man thank goodness we have this guy that wants to rebuild germany he'll put us back where we need to be and you stop questioning any your own judgment your own just you start you stop thinking essentially right i'm not allowed to question this oh of course this is correct of course this girl of course i'm right i intended to do right so of course my actions are correct i mean how many times have any of us intend to do something helpful and ended up doing something less and you know plenty of people who intend to do harm could by accident do something decent and i guess it's like you know i'm not saying anything you know terribly terribly you know insightful but it's just one of those where it's hard it's hard to say in the moment and that's where you hopefully caution you would counsel some degree of caution and uh that that's what worries me with with people deciding that we're all so right about this or we're also right about that and attempting to rather than win the argument silence the counter-argument no matter how crazy it may seem because i just think that that idea even when it's pointed in a good direction initially it's only a matter of time you're amongst many things a jujitsu black belt one of the things that people are really curious about white belts and blue belts and jiu jitsu but also people haven't tried the art is what does it take to be a jiu jitsu black belt i think that you know everyone's journey is a little bit different but the one thing that the it was a calvin coolidge quote you know determination persistence is the only thing that that will win in the end it will always win in the end not brilliance not toughness not education it's it's persistence and i think that having the belief that no matter what happens to me i will proceed forward and i will i will figure out how to make this happen hell or high water i think is the one thing that ties together all of the people that i've ever met that made it through whatever it was that they were going through because you know sometimes you can get lucky and you can have an easy time or and that luck could be you had a good situation it could be i mean like in the obvious sense of like where you're living where you're training what's going on you had a good situation you're un unbelievably athletic oh you're you're going to be an astronaut you're brilliant and an olympic athlete you know like well that's a fantastic situation you know you won the genetic lottery and i've worked hard as well but you also won the genetic lottery it's a determination is the one thing though because that person could have a very easy go of it initially and then tear their knee and then they're no longer the the superhuman physical specimen that they were the only thing that will keep them going is persistence and i think that that um i would just say that persistence to say i'll just put one foot in front of the other and sometimes i can see the path ahead and sometimes it's beyond my vision but i will not stop i may even slow down but i won't stop and that's the only thing that i can say that i've seen tie everyone together because there's so many ways to the top of any mountain and there's so many different personalities and skills and backgrounds involved but everyone everyone carries on so at the core the foundational advice is just don't quit just keep going that's the lesson of martial arts i think you know we think it's like how to be strong or how to be how to win but in reality it's like how to persist how to endure because it's all of us have been beaten so many times and gotten beaten up so many times and thought about quitting have i ever thought about quitting absolutely have i ever quit never i will never ever quit ever i can say you might not be out i will be damned if i quit what's the darkest moment is it injury related like is that is it uh so like to me like two possibilities i've fortunately never been seriously injured but i think that's a dark place to be like having to be out for many months uh for um as jen was saying like with a head injury especially like the uncertainty that's one and then the other side is if you have big ambitions as a competitor realizing that you're not as good like those those doubts were like i kind of suck how am i supposed to be a world the greatest fighter of all time if i if if like several people in the gym are kicking my ass those are the two things that paralyzing i think that everyone's darkest moment is maybe different looking from the outside for ryan i wouldn't say that he's had injuries and he said bad ones i wouldn't say that was his darkest moment i think for me i would say some my head injury was my darkest moment absolutely and i have torn my acl twice i've torn my shoulders four times i've had lots of surgeries for me the orthopedic injuries were not the most difficult it was the brain injury for others that might be the case for them maybe they've never experienced an injury and maybe for them that's their darkest moment from the outside obviously orion can speak to this more but for ryan i think it was the um inability to to perform at certain points to the upper the missing of opportunities that for him from my perspective watching him go through and having seen various points of his growth from from early purple bought on i think the hardest time for him looking in obviously was when he would hit moments where he wasn't able to perform for various reasons he couldn't get fights he was having difficulties there i think that that was the hardest point for him did you did you think like with the head injury that you might not never be able to do jiu jitsu again yeah i mean i i mine was very um was really bad and it was just the one hit but i had a looping memories for seven months didn't know it because when your brain's messed up you're not even aware that you're looping and so i saw two different neurologists i find like it took a very long time um i didn't know if i was going to be able to have like linear thoughts or read a book i didn't know at certain points if i could listen to music again you know without it making my head hurt um and so uh it was almost two years before i woke up in the morning without a headache um just waking up before i even start my day and so that so that's even bigger than jujitsu that's just life that's just that's just hard and i think that you can experience so many things i've had all these injuries we lost the baby when i was 15 15 weeks and we've had all these experiences and what the hardest point for me not saying all those things weren't hard but it's kind of like as you go through these you just realize like life goes on and you have to keep working at it and you have to keep going and you asked me earlier offline did i feel depressed and not from my head injury i don't think that at least in the moment i had a any recognition of that it's kind of like but i think different people's personalities i have kind of the like buckle down and just keep going and sometimes it's not until lots of time later that you realize wow that was really hard because you're just struggling to live and and function and do the things that you need to do alone do you mind jumping on just like this part of the conversation just for a few minutes it's over do you mind you know just sitting together oh no no just for a little bit sorry be cool be cool so we put a face to it you know uh is it okay with you yeah it's fine with me if it's fine by the way what was the head injury if you don't mind sharing someone hit their head dropped their knee on the back of my head during training who's a lot bigger than me so one strike to the back of the head is too much for someone there's a reason that's outlawed in mma right someone 50 pounds everything you drop their running on the back your head once and it's that's the funny thing about getting hit right you never can really be sure what's going to happen i think that's actually one of the magical parts about jiu jitsu where like if you choke me if you we know what's going to occur you hit someone they might be completely unharmed like you might be punching tony ferguson in the face and like he you need to hit him with a sledgehammer to affect this man and then other people they could get really badly hurt which i guess it's back to your point about you know street fighting and things like that and the serious serious potential you know second third order consequences of any action that we take but yeah that's a that's a tricky thing about getting hit how does it make you feel that like the the really shitty thing about injuries to me was that like you start thinking like well if i did this one little thing different like this wouldn't have happened today like one one moment changes your entire life is that do you uh do you think that where is that totally counterproductive um you can't help but think that way when you've had the amount of injuries i've had now because i've had more than most people's fair share um as my orthopedic says you don't want to win that you don't want to with the contest of who's had the most but since you haven't actually built me a pool yeah um but i think you can't help but think that way sometimes but i definitely don't think it's i think it can be facilitated if you don't beat yourself up too much um because thinking about why have i been subject to so many injuries and and a lot of it comes to just um almost all of mine in particular are people a lot heavier than me so we're talk but if i've been training martial arts 15 years i'm obviously on the much smaller side i'm a woman i've done thousands and thousands of rounds with people 50 pounds plus heavier than me i mean years not training with anyone less than 50 which is 50 pounds is almost half my body weight and when you also add testosterone the natural physiological advantages of men not just are they heavier with more mass they're faster they're more explosive they're stronger if they're the same size and so i think that the willingness to be in that environment over and over and over again creates a lot of strength resiliency willingness to continue but it also like in order to do that you almost have to uh for me the way i was approaching was like pretend like i wasn't more vulnerable um and just be willing to step in and step in and stuff take it until you make it kind of until you make it kind of yeah like i'll just one day i'll be strong enough and you avoided injury for most for most of those rounds i would injure the problem as ryan points out is that like you could do thousands of rounds but if one person that size that strength that however reacts in a way that you don't expect it doesn't it's not like an oops it's like always major do you regret any of it like i think that most no one i know has experienced the degree of injuries that i've experienced and i started juice at a time when in 2005 is very different than now where you have the coaches have more control over what you're doing they're more aware in general about a lot of the injuries there's a lot more people who are uh hobbyists than when i started um they were hobbyists but it was different kind of hobbyist you know than now now our girls can train with other girls they don't have to do thousands of rounds with somebody significantly more powerful than them and for the drawbacks and the benefits of that you know as with anything um so i think i think that i don't think i would go back and change it there were times after one of my injuries where i said to ryan i said i quit i'm done i'm not doing this anymore i probably said it more than once but there was one time i was really serious in 2012. um i was really serious i tore my shoulder i had i was looking at missing a big competition again the world's for my second or third year in a row after injuries and i said i'd quit my job two years before and i'm like i'm done and run before that had always been you know keep me focused and then he kind of said okay if you want to be done be done just just have a good time no i'm really done i don't even want to train anymore okay okay and then you know i think he helped facilitate a moment for me to go um visit a friend some friends some girls that were doing a girls camp who are close to my size or some friends of mine to go train and i was like oh wait i do love this thing it's harder for me on a daily basis but that doesn't mean i don't love this thing and it really helped change my mind i started to connect with other people travel more myself because previously he had done that but i hadn't really done that i think there was a point where um when i started youtube it was just for fun i just wanted to sport after college i played sports as a kid i want to i just want to exercise i wasn't into the martial arts he usually gave me a hard time about it because he was always very how can you not care about martial i don't know i just want to play sports um and ryan was really big into kind of the philosophy side of the martial arts aspect um he used to give me a hard time and i think after that moment this moment where i looked at myself and i said do i want to keep doing this is when i started to appreciate jiu-jitsu take it took off some of the pressure i'd been feeling i think as ryan's girlfriend but i had a full-time job a long time it was never my goal to be a jiu jitsu world champion and i think after that moment where i like you know i really do like this i really do want to just i had this moment like any time where you're like i'm doing this for me i'm not doing this for him and i think that that's um i think that was really lucky for me because how often in our lives do we have a kind of a challenge where we have to stop and we have to say is this really what i want how often in a relationship do you do that how often in any type of lifestyle or job do you stop and you really ask yourself is something really difficult happen that you look and you go am i just doing this because it's convenient and easy or is this what i really want to do yeah i've had those moments like this this podcast is one of those things it's like you you stop and think like i actually love this and it's uh i had that with jiu-jitsu too i don't think i had set until like brown belt did i stop i mean yeah it's when you first face real challenges you think like why am i doing this it's i think most of my progression was why not i think that's the right the leap of faith and then a certain point you think like what why am i doing this and if you can answer honestly that because i love it it's kind of a liberating feeling it's a it's a yeah it's so it's so powerful thankful for the opportunity to be there right because you love it and yeah man great gratitude it's yeah so that's it's ultimately gratitude yeah let me ask you this so ryan said like what what did i took over your thing yeah this is no nobody cares about ryan i wouldn't i'll photoshop him out or whatever however you edit that'd be great put sean connery's head uh just like a dune ad exactly uh connor is that the sexiest man in sean connery in the dune universe that's my understanding okay i think in any universe yeah well mind gossiping given we actually named our son after sean connery oh yeah that's right yes he was in the rock those i love all those great lame nicholas cage oh yeah conairs face off greatest movie of all time dude his accent and conair was so awesome i don't know where it's from alabama i guess or something well they got like steve buscemi in there like we need steve buscemi in this thing and we got him dave chappelle yeah that's right yeah he's a prisoner eight ball yep greatest movie of all time should have won and dave chappelle also in blue streak with martin lawrence and then uh what do you call it uh robin who men and sites oh robin was one of my favorites as a kid half baked but rob yeah well that that's a good uh wow we just listed off some really bad 90s movies but you take that back we're telling our age yeah so what um like in your view i don't mean to from like a smaller person i guess that's an interesting thing while jiu jitsu is like that uh small i don't hopefully that's not a bad thing um yeah like with all these like uh bigger people you can still enjoy the art like what does it take to get a black belt to excel to quote unquote master the art gosh everyone has such a different path ryan's promoted six seven people something like that and i think about half of them have had um have kids have families have other careers um at the time some of them competed a lot some of them have never competed or rarely competed some have been commuted a long time some had started different places everyone's had different journeys even in our own little group of seven i think only maybe only two or three were high level competitors of that group at the higher belts very like brown black maybe um and so it's just different for every person and that's something that that you know we try to tell her since we have 400 students and um do we have us we don't really have anyone who's you know a stated other other than like the coaches like adam but we don't have anyone that's like a stated high-level competitor as a student at the moment we people look at our gym like oh it's lots of competitors there's not lots of competitors it's never been lots of competitors and we've had ones and twos here and there um but really everybody's in it for the long term if they're in it sometimes the the high level competitors are the ones that are more likely to drop off because they have a bit of success particularly at blue or purple and then they realize how hard it is at brown and black and then they they have a hard time continuing on that's that path and then they can't look at themselves as a non-competitive hard time continuing with jiu jitsu i think whereas sometimes it's the guy who comes in as the white belt and he trains you know twice a week every week and the next thing you know he's been there for two or three years like oh he's a blue bell he's a purple he's a brown bell and and he's just consistent um over over a long period of time and willing to take the path and no two people's path is exactly the same no two people's lives are exactly the same you have um we have students who started as a white belt as you know a young adult with no you know no responsibilities and they train all the time and then they have a job you know then they graduate college and they have a job then they have married then they have kids then they have different points in their careers and at different points in your life jiu jitsu will be there you know for whatever way that you're willing to accept it it's place i think well that's actually kind of what back to the initial question we discussed about you know what makes a warrior you know and and also like what makes something or someone you know particularly impressive in my mind is like uh what they make out of what they have um you know one of my favorite movies ever as far as gump and it's obviously it's it's just if you can't uh because i've heard people like force gum sucks i'm like i don't like you as a person and uh like you have no heart at all but basically uh it's the story of someone that tries hard and it's like yeah but it's it's funny movie but it's like um you know i guess you meet each person where they are you know and obviously you want everyone needs to be pushed we all need to be pushed we need friends and people around us that push us to be better versions of ourselves all the time and as you mentioned the people you spend all of your time around deeply impact you um and we have to be willing to be pushed it takes a leap of faith for me to trust for me to put some of my self in my my you know i guess my ability my control my personal agency as it were in the hands of someone else that i that i trust and and that i respect but if if i can do that well again maybe i never become you know high level black belt competitor but you know i had four of the things i was doing my life i also have a family i have this i have that you know what that person was able to accomplish in the martial arts relative to what they were able to put in this phenomenal you know other times someone could be a very successful black belt and it might might be a bum because they could have been a lot more and you know they could have done more they could have focused more and and there's no shame in deciding that you don't want to do that but whatever it is that you're you're invested in i remember the uh take it uneasy podcast and that i loved because you know i'll just chill out like resting it's like vacation oh who wants to go on vacation yeah go on vacation for a day or two you want to spend three weeks on vacation like i kill myself like get me out of here like this is horrible this is i'm a waste of life i'm not doing anything useful right now technically right now right well this is fun though it's like a one-day vacation yeah exactly but if you notice if you had i'm sure you're thinking about jumping off of the building right now but if you had to if you had to talk to me for you know like uh three days i'm sure you'd probably shove me off the building i don't blame you i would be dead but yeah five hours in but yeah but you know it is it's like you want to be pushing towards something um because otherwise what's the purpose of being here you know it's not just a college it's doing something useful building growing as a person helping others do the same if that's within your power at any given time but i think that's kind of the neat thing about martial arts is it can be many many different things to many different people you know i finally for instance i was able to get a college degree let this this year that which i mean it's not a big deal for most people but for me it was a big deal because i was going back and finish yeah and i never envisioned ever going back and that's a hard step to to go back and finish that's uh it just weighs heavy on you if you don't it's interesting yeah i was just i was more proud of that than most things i've ever done if i'm honest you know and it was neat and i really enjoyed it and it was the process of doing it but you know are my academic credentials impressive like not in the least but for me it's like it was a big deal for me personally to take that step and to to go back and do that and i was i was proud of the the direction and because it would have been easy like do i need to do it like no i'm you know i'm business i'll do okay i'll try i'll keep fighting but i i was happy to take the time in between fights when i was when i was unbooked for an opponent to do something productive rather than just i'll just hang out you know like i can still train every single day but i can also train and go to school people go to the olympics while going to school i can i can do martial arts and go to school one thing i gotta ask is uh you know a bunch of women listen to this podcast if they haven't done jiu jitsu i think it'd be kind of intimidating to uh stop on the mat with a bunch of bros uh that like enjoy somehow killing each other like how do you succeed in that environment to where you can learn this art learn how to beat all those people up um oh gosh is there any advice i mean another way to ask that is like if if uh any women listening to this are interested in starting jiu-jitsu like is there advice for that journey honestly i think it's just walking in the door and starting sometimes i don't know how to respond to that because i'm not i don't view myself as typically anxious particularly in interactions with other people or new people shy is not a word that has been used for me but if you ask my family and um they joke because our son talks a lot he's advanced verbally and they're always like oh well let's we know where he gets that from like because he just doesn't stop talking he narrates everything he does um and so they always tease because that's like i'm known for for kind of talking a lot um but so i haven't been typically i'm not i don't consider myself a shy person so for me going into um a new room a new group of people is you know there's there's always that you don't really know who they are how they're going to treat you but i typical but i i don't have a lot of anxiety with that so i don't if that's something that's going to put something up i don't really know how to to address that particular feeling um but in terms of all of the rooms i've been in i have popped in the jutsu jams before i knew ryan in florida like i traveled for my jobs in germany and florida and in california in places where where i don't know anyone they don't know me and i have never once had anyone be anything other than than kind and solicitous and helpful and long before when i was a white belt and a blue belt and didn't know anything and didn't know anyone and i just think that it's a community of people that it's so cool that no matter where you go in the world um i i walked into a gym in prague one time where only two people spoke english and and it was just yeah it's weird you know it's weird like part of a group and they're like oh let me tell you what it is being part of a cult right yeah yeah but it's like a positive cult like it for sure that's what we would say yeah that's true yeah that's true i mean we do need to murder every week of practice aikido i mean yeah that's this cult uh true deeply believes it no but there is a like if you look at different kinds of games like chess and so on like there's a skepticism i mean there's not a brotherhood sisterhood feeling with jiu jitsu it's like you can roll into most places even like with judo like i can see the contrast like because i've trained in judo places it uh it's more like tribal like you walk in and like who is this like there's that kind of feeling with jiu jitsu there's uh less so there is a little bit with like the competitors there's always like the competitors feeling each other out usually like the blue belts uh but like outside of that in terms of if you don't get the if you if you walk in with the vibes of just loving the art and just wanting to have a good time you're like welcome it's really cool it's really fascinating it's a really great um thing i think and as a woman i think you you think you're walking into these rooms of these you know big strong tough guys and um if anything i would i would say that they're almost like much more solicitous when a woman comes in there and not like they're just like hitting on you all the time you know it's just that you walk in and everyone is like oh cool you want to do this thing that i love let me make sure you have a good experience and take care of you and i think that's that's an experience that that i hope people have when they come into our gym and and i've i've always felt when i walked into other gyms and so you know we try our best to to make that comfortable and and it can be a little uncomfortable because there are when you walk into a male-dominated environment there's conversations and topics there's a different style of camaraderie and joking that a lot of men will do that um maybe some women are more uncomfortable with i grew up with four brothers so i kind of maybe was a little more desensitized to that um and i worked for the department of defense for for a while too so before i i i'd say you're with the government yeah so so i did that i'm already skeptical yeah i'm not going to ask you about ufos then because you're not going to tell me the truth [Laughter] uh yeah now you just freaked out a lot of people okay uh but yeah by the way where's where's your school because people always ask like where uh uh well we're outside of washington dc and northern virginia and falls church you always want to pick like what's the best school if i travel to this place or if i lo if i want to move to this place so that's well i mean obviously we're biased but yeah we're in the washington dc area the best okay we just took a little break now we're back let me ask you uh one thing that a bunch of people are curious about you're one of the innovators first of all you're one of the great innovators and philosophers and thinkers in jiu jitsu right but you're also one of the innovators in terms of leg locks and and the 50 50 position and just like the fact that legs have something to do in jiu jitsu uh the the under the other popularizer innovator in the space is john donahue and his whole group of guys do you have um thoughts about their whole system of leg locks and their ideas about jiu-jitsu and so on sure i i guess uh you know obviously you know john and and the students at henzo have been able to do fantastic things competitively in the past number of years and you know um you mentioned innovators in the in that kind of you know section of jiu jitsu i would be uh i'd love to bring up some guys like dean lister um of course uh mazukaze minari in fact a lot of what was going on in like 90s japan like combat submission wrestling there was some crazy gnarly stuff that it's just it's on grainy vhs tape but like stuff that if people were doing now they go oh my god that's brand new like there's um it's it's been i think these are things that have been around for a while um in various places i first learned the 50 50 position just like the leg entanglement of it from brandon vera actually at a seminar at lord urban's martial arts i think in 2005. he learned it from dean lister who used it to submit alexandria cocareco a really really tough nogi guy at adcc on the in the run that uh dean made to the to the gold medal in the absolute division which was a great performance at the time first american to do that um and uh you know and i actually saw a video i mean first of boss rutin actually broke i think guy mesger's foot with a 50 50 heel hook did he actually grabbed his heel and his and his toes and like and in pancreas it's back when they had like the man panties and the high uh yeah and uh dude that was gnarly boss rooting is underappreciated as like as like he double oh grab like oh yeah like you know his leverage is leveraged it's that's like a toehold that's you know that goes the other way and it's like it either doesn't work or breaks in half and uh well he's uh people don't often think of boss rooting as an innovator but he is in a way like he uh you know talk about like elon musk and first principles thinking in terms of physics he like just feels like he just gets the job he figures out like the simplest way to get the job done of breaking things and establishing control and hurting people remember that was back in the day if you listen to boss root and do any like commentary for any of the uh the big mma shows or any mma show way back when any time guys were clinching like the gosh role for an ebar he was saying that way back when and now people are doing it all the time with varying degrees of success it's it's funny it's like it's also tough to be uh i think like a breakaway thinker i mean you know groupthink is a real thing in group inertia and it's it's neat to see um you know particularly at a time when maybe that type of stuff was less accepted um you know someone going hey i'm gonna i'm gonna run off in this other direction i think you know whoever you know the inventor of electricity in my mind is a lot more impressive than whomever not to say that the person down the line isn't impressive that comes up with an interesting way to use it um both are cool but when you think about just can you imagine we're sitting here like yeah people i'm going to build an airplane you're like what are you talking about it's crazy people don't fly i'm like no i'm going to do it and of course it's not going to be as good as the airplane down the line the iterative things that happen later on but um just being able to go to dream something into existence that you haven't seen before and then make it happen like takes an unbelievable like strength of character almost like a force of will because you have you're you're blazing a trail that hasn't been walked before that's the bj pen factor in you know winning the jiu jitsu world championship first non-brazilian to do that was back in 2001 and then raphael lovato later on it's like he's you know both of those guys are so unbelievably impressive in my mind for the same reason you know because they were out there winning at a time when that wasn't a common thing not that it's easy to win now it's just there's not a psychological hurdle that needs to be left i remember you know when i was early in jiu jitsu like americans weren't winning the world championships at any belt i mean bj we all knew bj penn because bj penned it but it was really really uncommon now it happens you know on a semi-regular basis of course the brazilians are so strong europeans are still strong but uh and australians are coming on as well but uh it's it's definitely kind of an interesting thing so to come back to you know john danaher and the uh hensar team obviously they're doing fantastic things john's had some really really great innovation there and the the the systematization and the methodology that they're using is uh is great and it's neat to see that it's getting out there um i would just also what i would encourage people to make sure that they're you know catching up on their history because obviously you know john's a brilliant instructor and has done things you know for the sport that um that are fantastic that haven't been done before but you know none of us exist in a vacuum and i've learned things from everywhere else so you know john would say the same i'm sure and uh you know dean lister would say the same and it's just neat when you can kind of trace the history of all of this happening because we've had humanity's had two arms and two legs for some time at least as long as i've been alive but you mentioned like airplanes do you think there's something totally new to be invented in jiu jitsu still not totally new but like the you know flying isn't new right uh but airplanes nevertheless made that much more efficient is there like new ideas to be discovered in digital still i'd say the reason i'd say yes is the same reason i would say i believe in alchemy even though i don't i'm serious like i've got some backing for this okay um you know i guess i talk about this with a buddy of mine a lot like uh and facilitative versus not facilitated beliefs and if i don't believe something is possible and i do no investigation towards it i'll never find something even if it's there it's almost like it's no different than me walking up on a group of people and going like oh man look at these jerks this is going to suck versus me going i wonder what these guys are up to i'm about to have two very different conversations even though the players in the game are no different my internal constitution has changed because of of how i've decided to approach the situation so although i wouldn't personally want to spend all my time trying to turn lead into gold because i don't believe that it's likely to work only a person who's willing to spend his or her life in that pursuit will actually get to the bottom of that and also in the in the pursuit of that they're likely to find other things so i think a lot of times the idea is that humanity is pushed forward by you know again it's another orson scott carbon it's like you know human beings are in this slog it's paraphrasing just in this slog over time and then periodically the humanity gives birth to genius like someone that invents the wheel invents electricity pushes us forward you know comes up with with the idea of governance that doesn't you know just start and end with the point of a sword you know and uh you know these aren't common things these are unbelievable advancements that you know that just me sitting here i didn't come up with them but i just get the benefit of it so i guess what i would say is a lot of times these ideas are called crazy you know like as we discussed on kind of offline it's like you know einstein was brilliant in his 20s and it was brilliant before that i would suspect but basically uh you know gets recognized later on in life and of course we all thought those were great ideas the man was probably roundly mocked for giant chunks of his life and i i guess so it's neat i would say there's definitely in my mind things that even if it's just combinations and new to me new ways to see things new ways to understand different depth of understanding possibly new things new positions new ideas because even if that's not true the process of of going through and acting as if it is and believing like that and focusing and trying to investigate will make any of us will push us all forward we're sitting there you know obsessing over the cult of our current knowledge i think is the biggest the biggest danger um and the biggest cause of stagnation that exists anywhere yeah and it starts with believing the the impossible which is kind of interesting one of the things that's really inspiring to me is to see people out there which which sadly are rare who kind of have uh a combination of two things one is they have a world view that involves that includes a lot of ideas that are crazy and the second part is they're exceptionally focused and competent in bringing that whatever the ideas in that world view to reality so there's certainly a lot of people with crazy ideas you know there's a lot of conspiracy theorists they have way out their beliefs about things but they're not doing much to like make the like build stuff grounded and like they're not engineers or whatever they're just like espousing different crazy ideas but that's why you get like the elon musk type characters and the reason i bring him up a lot is because like there's not many others to bring up it's like there's not many examples of it through history the people i mean the guy's convinced that we're going to colonize mars and basically everybody on earth thinks that's insane everyone accept the guy that's going to do it right except that's going to do it and like you can imagine like a couple hundred years from now people will i mean first of all they won't certainly won't remember the haters they won't remember all the people if if they do remember them they'll remember them in a sense like people were silly to think that this isn't the obvious path forward like from a perspective that's what that's what elon talks about like it's obvious that we're going to expand throughout the universe like so from his perspective from his perspective like but to me it is also obvious because like either we destroy ourselves or will expand beyond earth like uh like there's not many you know we well it's not maybe it's not completely obvious i'm i guess i share that world view there's the other possibility that we humans find a sort of an inner peace where the forces of capitalism will calm down and we'll all just meditate and do yoga and jiu jitsu and like relax with this whole tech thing where we keep building new technologies but it's cool to have those kinds of people that just believe the big ambitious crazy dreams because that's where it starts if you want to build something special you have to first believe that when you also have to believe strongly enough that you're not vulnerable and i'm speculating but it's like i can only imagine how many people have told elon that what he's doing is crazy so not only did he dream it up he dreamed it up went with it and also went with it in the face of being told that it's not going to work and then time and then also stepped away from the bitterness because he's done a series of really crazy impressive things uh and that's only those little things i'm aware of but and also staying away from the bitterness of every single time you did something good initially i all i do is talk down about you and then eventually i act as of course of course i never apologize and yet you don't let that dampen your spirits for the next innovation which is pretty incredible to me to watch yeah it's kind of cool i mean uh it's contagious to spend time with the guy because he's not it's rogan has the same look to him which is interesting about these people is uh like there there's like a hater shield that he's like he doesn't even like sense them it feels like like it doesn't he does he thinks to uh to elon it's like it's obvious i mean he keeps calling it like first principles thinking like physics says it's true therefore it's true like he's convinced himself that like his beliefs are grounded in the fundamental fabric of the way the universe works therefore the haters don't matter right and i mean that's kind of like a system of thought he developed himself through all the difficulty through all the doubt he's able to take huge risks with basically putting everything he owes on the line multiple times throughout his life amidst all the drama amidst all the doubts amidst all like the he's still able to make just clear clear-headed decisions it's i don't know what to make of it but it's inspiring as hell well it's i think it's something that's funny i think like i can only imagine that you know history will look back on him as a brilliant person but that's not the only there's there's a lot of maybe not not statistically speaking but a lot numerically on a giant planet of you know billions people a lot of brilliant people well um you know time place luck fortune all that other stuff but at the same time that clearly isn't the only determining thing in making elon musk musk and obviously i don't know the guy from adam and but it's an interesting thing that it's not just his intellect his belief system his structure how he's viewing the world like that's did he reason his way to that did he not what other factors came in i'm really curious about that because i guess coming it's again i feel really strongly about people's belief structure and and this the how they view the world being more important than the engine behind it you know it makes someone resilient or not it makes someone positive or not because you could have ten thousand i think about this for competitive stuff you could have ten thousand things going properly and one thing going improperly if you focus on the improper you'll probably fix it at a certain point which is good facilitated for development in the long term but if you had to go and try to perform a task in the next five minutes and you're focusing on the negative your confidence and your your your belief in in the positive outcome of the future is likely to be damaged whereas you could have 25 things going wrong but you go man i sure am happy to be alive how fortunate i am this is great i can't this is i have problems to solve this is awesome versus i list the problems and i start bitching about them both of them are technically accurate but it's i guess different lenses and i think that's a really neat thing to see you know someone you know exemplifying that for us so maybe to look at the the fighting world there's a million questions i can ask here like one you mentioned bj penn you uh first of all you are undefeated in the ufc and one of the fights you've had is against bj penn which is a kind of an incredible fight you you won performance of the night what did it feel like to uh to face pj pen and to beat him definitively as he did like what's that whole experience like i'll be honest i didn't know if i was going to ever be able to fight again after beating gray maynard in 2016 um and i've had a couple of periods of those i i was about to join the army actually in uh when i was 30 before the uh for the ufc for jen sent me over to ultimate fighter i didn't want to go because i was like one they're never going to pick me too i'd be terrible for tv three i'll probably say something i'm gonna get you know burned to death in the streets you know i'm like this isn't a great idea and then uh she said well go out there see what happens do it anyway you'll be you'll regret it if you didn't and then i ended up doing ultimate fighter and then so i fought three times on the show and then i fought um for the for the finale so those four times in like five or six months which was great and then it took me a year to get another opponent um and that was gray maynard and then gray was obviously a very tough guy managed to get a good outcome there then it took two years to fight b.j penn and that was you know obviously i'm training all the time every single day and that never stops but that was i'll be honest like pretty deeply frustrating because you know as a human being as an athlete you know i think as an athlete you die twice like you have an athletic peak or area and then then you go on with the rest of your life but it is a microcosm for the rest of your life it's like you're seeing this the sand tick away in the hourglass or drop away and you're going man this is these are years between 31 32 33 like i'll be at my best at this time my absolute best physically now not technically i'm a lot better now than i was before and i planned but at a certain point you will unless you're bernard hopkins you will reach diminishing returns and i guess that's the long the long wait you can feel the clock ticking is this frustrating so why why did it take two years for bj i uh i i that's the question people ask a lot like why does nobody want to fight right now i don't know i probably they probably think they'll get infected by whatever this is but uh i don't i don't blame them but uh i mean you're a really tough opponent is the bottom line i'll say that i'm different maybe they perceive that the uh the the threat is greater than the reward i'm hoping that now that we're ranked number 12 you know in the ufc rankings that uh that that will change and i know that if we're one more win and then we're in the top 10 that you know now now you're there but uh what i've consistently found is that like randoms want to fight and i'm like go away you know i didn't come here for you you know because if i wanted to just fight anybody i could go down to a waffle house and yell until like dmx shows up and we can we can fight because he'll be at the waffle house too who am i kidding i really want to hang out with the mx but uh you know it's like you want to when i had the opportunity dmx oh my god that was i would never flick shows i would never fight dmx we'd be on the same team no but uh anyway um it's i i guess um i i accepted fights against uh i asked the guy to ask about llamas i said yes i got asked about dennis bermudez i said yes um you know like long periods of time and they at that time you know in between 2016 and 2018 um i was struggling to have have opponents who would sign up and uh us i haven't turned down fights i just said hey you know keep the i don't care about fighting the randoms and it's you have a successful school you're like you're running you're a martial artist broadly speaking so it doesn't make sense to to take fights that aren't like right that fit a certain kind of trajectory for your career and that's when when bj penn they said well bj's looking for an opponent i was like i'm your guy and uh and i think that you know bj accepted that fight because um another jiu-jitsu guy i don't think he perceived that i was much of a threat on the feet um and uh you know i was able to it was neat to get it to compete against someone uh you know who's one of my heroes one of the people i looked up to in mma for the longest time and you intimidated by that no no i love competing i i don't really get nervous or scared before fights i'm not afraid to get hurt and not afraid to win i'm not afraid to lose it's i i'm just excited for the i feel thankful for the opportunity to compete and the opportunity to to play when it matters you know i i just but that's the only time i'm interested in playing anymore is when it when it matters when the opposition is i know that you know it's funny because people pick on on a lot of some opponents particularly after after the fact like if you if you get a good outcome well then uh of course lex beat that guy that guy wasn't that good i'm like well i was that's after the fact i get to say that and also as the person in the ring you know bj penn has hurt a lot of people in in in mixed martial arts cage and i could actually absolutely have been on that list um so it was neat to get to compete against someone that i really respect someone that i looked up to for a long time someone who has a great skill set and also i went up and wait to fight him at his weight class he didn't have to come down to mine which is where he'd take lightly it was lightweight yeah um i generally have featherweight i walk around like 158 pounds so um what's the lightweight and featherweight uh lightweight is 155. with a day before weigh-in and featherweight is 145 with the day before weigh-in so i'm a little bit more properly sized for featherweight but um anyway uh you know i so i didn't feel like obviously he was giving up a couple years of age but i was giving up size and all this other stuff and it was you know i was just excited to have the opportunity to step in against someone like bj and uh you know we managed to to get out of there with a with a good outcome without getting too banged up but uh just it was cool because we tied up on the fence and just even uh the second you know is when you're rolling with somebody and you touch and you can feel what they're doing you go oh man this guy's really good um you can feel the calm you can feel the small minor adjustments that they're making the subtle things that they're doing and that was one of those things that was really neat and gratifying because you know you never know sometimes people that you've heard of are a little bit less technically proficient than you thought and other times you'll meet some guys training like who the hell is this guy how have i not heard of this person and uh bj was exactly as a jitsu guy what i would have thought and uh another thing that's another thing that bugged me about how people reacted after the fight is uh you know basically going oh bj screwed up this screwed up that i'm like all right yeah it's so interesting that's sad that was you know one of the uh to me i mean as a fan of both that was a beautiful moment as uh as a as a kind of passing of a torch in a sense of exceptional performance like another one that stands out to me maybe you can comment is i don't understand well maybe i do why conor mcgregor gets as much hate as he does uh he probably revels in it but i think he doesn't get enough credit for uh jose aldo for the for like for base you know knocking him out in the the in the in the first few uh seconds of uh of a fight i mean uh jose is like one of the greatest fighters ever that's true uh maybe some people could be even put in the top ten no question and the like i don't understand why it's doesn't get as much like conor mcgregor doesn't get as much credit uh as i think he deserves for that and for eddie alvarez and all the fights for some reason whenever uh conor mcgregor beat somebody well that they they were not that good then like it means like they were they were there something was off right that's convenient isn't it yeah it's it's it's quite strange to me but i mean what are your thoughts on the um on conor mcgregor maybe one way to ask that i'm russian some obviously also khabib fan but i'm also a conor fan it seems like there's not many of us who are like fans of both right um what are your thoughts the two of us which also is a good play uh uh stop dude yeah really really tough dude just like five line which is really interesting also the oh wow i didn't know that side of it there's a brain there well on the khabib versus conor what do you make of their first fight what do you do you agree with me that uh they should fight again because i think it would be awesome if they fought again in moscow and uh do you agree with me i'm just gonna put say things that piss people off but i believe is that conor actually has a chance to beat khabib one the conor absolutely has a chance to be conor has a chance to beat anyone that he steps into that ring with and not just like a mathematical chance you were like oh one of the billion but like you know like he absolutely it's funny because i i won't pretend to know conor really well but i first met conor in 2010 when i was teaching a seminar in uh at straight blast jim ireland in dublin um and that's actually where i first met all of the coaches that ended up being on conor's team um you know john kavanagh owen roddy uh gunnar nelson you know so for i actually i enjoyed being on ultimate fighter and being on a uriah favors team and getting to train with all the guys there but at the same time that the people that i was actually i knew better were actually the european side all the connors coaches um and uh that was a neat thing because i got to i met connor i didn't know who connor like connor wasn't conor at that point yeah that was before his ufc oh yeah well well before yeah i think i think he got in like 2014 maybe something like that yeah and uh anyway but he was doing well in cage warriors winning the titles there i think prior to that you know i remember going seeing him on the show and uh also then getting to see him train because i competed uh i was initially slated to fight david tamer for the ultimate fighter finale for getting put into fight artem for the title for the show so i went over to ireland to train for a couple days and basically it was neat to watch him watch him work i mean man is focused and trains a lot it's very very smart and very very hard working and i think a lot of times people get stuck in the uh in this um you know and they almost want to believe that this was lucky or this this person you know they're not working that hard they're just out there they got there with their mouth and that's that's just not the case and um you know i don't know what it's like you know obviously connor's very well off right now and i don't know how hard how serious he's training what he's doing i can't speak to any of that but uh there's no question that that he has skills to be dangerous and one of the funny things obviously the khabib fight one could be his weight could he was a great fighter and also has the chance to beat anyone in that ring at any given time but uh there's there wasn't conor you know it's uh one that he can he can put anybody away and as you mentioned i think that he doesn't get the credit for the eddie alvarez fight he doesn't get the credit for the jose aldo fight because it was almost so much of a letdown i remember that happened the same weekend that i did the ultimate fighter finale and you're like all right wait what yeah it almost doesn't feel like a fight happened but we mentioned miyamoto musashi i mean musashi was famous for the way he poked and prodded at people with what he was doing whether overtly or not it's like oh we're supposed to fight to the death and uh you know at 3 p.m tomorrow great 4pm rolls around i'm just not there five i mean you remember all the all the antics and nonsense that conor was pulling prior to that like speaking personally that's not it's not something i would feel comfortable doing but it's like everyone's different and the effect that it had on on jose was i mean beyond evidence when was the last time jose started the start of the fight with leaping left hand leaping right-hander like wait what and then he was obviously you know living rent-free in jose's head at that point and that was a combination of psychological you know ability and and and wherewithal and then physical and remind me of the way muhammad ali would would bother people and whatnot and the fact that he's a polarizing figure um i i think makes some people not give him his due and then at the same time sometimes certain fans may be go overboard but uh they remember the knee that ben asker and got knocked out with by mazdal i mean that was an amazing unbelievable thing but three inches to the right three inches to the left i guess whichever side his head wasn't could have been square but uh and that fight starts with ben askren on top of you in the first five seconds well connor ran and threw a knee just like that at khabib and could be got right around it that could have easily gone the other way can you imagine what would have happened if after the after coming back from boxing after coming back from from the mayweather fight connor connor in the first ten seconds it's over and you're like he would yeah it would have been intolerable but basically yeah like you know but see here's the thing let me actually push back slightly uh i mean to the fans correct me if i'm wrong but conor seems to because i've competed a lot and like there's a tension there's a negativity sometimes depending on the opponent and there's a respect afterwards that happens like when you understand that there's a deep like respect and almost like love for each other like i always seen that in conor like all the trash talk afterwards yes there's a it's it's a subtle thing you can't always see it but there's a respect like i agree and the like that i almost on the khabib side i almost feel like khabib really took it personally he did he didn't he lost the respect for connor i thought the whole time conor had the respect so i what i wanted to say is like if connor won that fight like rock khabib i could see like i wouldn't see trash talking i could see like trash i can stop right there i think so too but at the same time i'm sure you recall like connor come across in some pretty personal territory you know both religiously and also familiar with uh with khabib and it's you know i mean i think it's the sort of thing that i don't know it's an interesting that's one of those sentences like you have to know the difference so obviously i know the the the kibbe the dagestani people they don't play around like that they don't play wrong like that you know you know i mean they take offense to basically i mean you you don't do that so uh so like connor didn't maybe he did on purpose or maybe he wasn't even just aware of of uh it was cultural differences about the box he opened like you can talk to him if floyd mayweather you can you can go anywhere with him you can you could say the most defensive things but with uh yeah that could be hardline yeah hard lines but you uh i mean a lot of people ask i know you're a featherweight but if you were to uh face it feels like khabib is one of the hardest puzzles to solve in in all of mixed martial arts if you were to face khabib do you think how would you go about solving that puzzle like almost the question is almost from a jiu jitsu perspective too what do you do with a guy that's exceptionally good at controlling position especially on top very good at wrestling and taking down and controlling position like let's say so forget maybe striking on the ground how do you solve that guy like what do you do with your guard if you get taken down or do you create an entire system of not getting taken down or escaping it's like what what ideas do you have for that well i guess i would say in my mind fighting is a game of trading energy um kind of uh you know there's two there's two things there's damage and there's energy so like when i say energy and being like uh tired not tired how much how much gas you've got um and then damage counts obviously as well um you could be feeling i could be feeling great and then you get to keep me in the head hard really hard three times it doesn't matter that i could get up and run a mile i can't get up so anyway um you know i think what khabib does is so well is he makes the fight look like it could be the mega man fight um he does a great job of avoiding damage on the feet for the most part and really sucking the life out of people with how suffocating and oppressive is his control is his chain wrestling is as good as anyone we've ever seen in the ufc it's fantastic but that poses a really serious threat for people that need to maintain a certain amount of space and try to hurt them on the feed because unless they're able to inflict an adequate amount of damage they're gonna each time let's say for instance let's say him taking them down as a foregone conclusion at some point um if every single time khabib takes you down you get right back up it's not that big a deal um because it's actually more we've all experienced this let's say you and i are rolling he tapped me 15 times in one round who's more tired probably you are yeah you what my ass so badly that it's like you're the only one working but um so if you're comfortable with the up and down of it like being taken down if you're if you don't if you don't get hurt badly or tired on the bottom you have a chance but that doesn't involve just cracking him on the feet before he gets a hold of you that's a lot that's a lot to ask that's a lot to ask that's difficult to do it seemed actually like conor it seemed like it when he was being kind of taken down or the the takedown attempts against khabib he seemed to be somewhat relaxed the whole thing i thought he was doing well actually i think that particularly for the first round i thought he did a very good job it's just one of those things that i think like uh could be being the fights taking place in khabib's world in large part and i mean set aside that one giant uh what is it right hand that that khabib hit khanna with it by the way conor reacted like an absolute champion he got crushed by that overhand and then dropped and his eyes went right back on khabib it was immediate great response so even though that was i think that was a bit of a surprising thing conor reacted really really well but if you're going to be on bottom with khabib for four rounds that's going to be tough and also conor's a way better grappler than people like to give him credit for but he's not the type of grappler that can do that can that can that's too tall of an order but there are grapplers that could do that or at least would have a much much better shot at uh being able to weather that type of a storm do you see yourself being able to be relaxed through that kind of storm yes well i guess remember being being being savagely beaten is very relevant the time the timing of that answer was like okay that's a dumb question no that's ultimately the goal of jiu jitsu is to um be relaxed to the fire for sure and remember like every ufc fighter i win all hypothetical match ups yeah [Laughter] that's true since uh i'm one to ask ridiculous questions and we've been talking about sci-fi and all that kind of stuff let me ask the kind of big question that everybody disagrees about certainly with me is uh who are the top five greatest mma fighters of all time oh man and um why is fedor number one okay well first off fedor is number one oh really i agree right there with you really oh yeah talk about people that just get completely underappreciated even though he's never been like he's never succeeded in the ufc it's not his fault it came along after him at the time that at the time that fedor was at his height the ufc was not where it was at for heavyweight fighting i mean not that there weren't good heavyweights there but fedor fedor was unbelievable you know i mean you remember i mean minotauro nogueira i was a massive fan of him i still remember watching uh what is it pride 2004 when when noguera fought crow cop and got blasted with that left kick and dropped with like seconds left in the first round pride was great because at a 10-minute first round in that five-minute second which again materially also alters the fight big time and you know just the texture of the fight because it's totally it's borderline a different sport you know than than getting a five a pause and a five but anyway uh similar sports like one of those swimming things where they have nine gold medals for different types of swimming right but still swimming but anyway uh um well yeah that they would disagree yeah i don't know but it's so it's totally true ten ten minutes is different than five i'm sorry i think don't don't don't drown me swimmers i don't swim very well it's easy easy to downplay it but anyway um uh yeah and then no better than uh jon jones like the modern era well i mean i guess it's tough to compete to compare across eras it would be like going and saying like oh man how how would such and such great grappler from today fare against someone from 1995 i'm like well probably pretty well for them depending upon who they are what's going on you know there's some people that would their skill sets might transition across eras but a lot of times not but that's not fair we get they'll be like comparing spartans to modern day you know like army guys they're like well who's gonna win i'm like well did modern day army guys get modern day weapons well yeah but who's the toughest ruggedest group of people at the very least so i guess it's tough to say but at least in my mind the people that i think about for great fighters their their quality of opposition um their level of like lasting like success the level lasting innovation like the courage that they have to demonstrate because again it's like being a big fish in a small pond takes no courage doesn't mean that there's nothing there but it just requires something a little bit different so kazushi sakaraba is one of my guys too uh bj penn also i mean bj penn fought leota machida yeah that's insane you know it's there was a time it was a different sport it was a different time in the sport where you know they were some guys were bouncing around doing different things but let's so i guess the gracie family it's i mean they never had an in like obviously hoist was there um but they never and that was a definitely a different sport weight classes being open things like that but you have to say the hoist is up there oh no question one of the greatest ever i think so too and again i wouldn't be sitting here talking to you um if it weren't for him so the gracie family as a whole but i mean who's the better i mean i think the hoist would tell you himself probably that hixon would have handled business back then but they didn't put him in so again he's the greatest fighter the greatest fighter the greatest fighter that we saw do his business so hoist up there for sure what about so this is like nobody seems to agree with me on this but like this connects to soccer again and messi it seems that people value like how long you've been a champion how many like defenses of the championship that you've had successfully to me i highly value singular moments of genius so like like i i don't like if you look at conor mcgregor he hasn't i guess held i've been a champion very long very much he didn't defend either title right he didn't defend any other either of the titles but like if you try and same with messi if you look at uh leonel messi there's just moments of brilliance unlike any other in history for both conor and messi and people don't seem to give credit it's like well how many world cups have you won but to me like why is it about this arbitrary world cup thing or championship thing i think it's easier for people to wrap their head around right it's like the nfl combine when was i mean yeah numbers it's something well again if i go and if i pick tom brady in the first round you know and it works out they call me a genius if i pick tom brady in the first round after his combine and it doesn't work out i get fired and i'm never hired again i have to work work somewhere else but it's like i'm insulating myself from criticism i think almost if i go by the numbers well he had more bench presses it's like how how many times have the guys that are like the super studs in the uh in the nfl combine ever been on the greatest players in the nfl history in nfl history like zero or close to zero and even if even if there's some it's certainly not a one to one so it's so funny though i think it's just like how many how long how many days did he hold the title oh your title reign was x times longer that means nothing so if we wanted to find greatest fighter ever like you said i think individual moments of like you're like that was transcended that was different that was something else because people can win or lose for any number of different reasons and that that's an interesting thing again i don't blame argentina not winning the world cup on messi you know that's not fair you know how many times has you know i mean aggies the i remember when uh trent ilford was the quarterback for the uh the baltimore ravens and they had such a strong defense i'm not trying to pick on trent tilford but it's like they had such a strong defense that that they were like that was the ray lewis you know chris mcallister era you know and they they won they won the super bowl i don't think anyone is going to say that you know trent dilfer is a better quarterback than you know or put him in the same category as dan marino but he got the w he's got the he's got the super ring how many times uh let's use march madness or super bowl i love it like that that guy always makes the finals but he just never gets it done yeah so let me get this straight get into the finals nine times doesn't count because you didn't win the end game i'm not saying it wouldn't be better but that guy won the game once he got over the hump well how many other times was in the finals zero you're like all right yeah it's interesting well we yeah that we were obsessed with these numbers like um because we can't assess their method right well i think most of the time most of us can't assess the method of anything and it's like oh look at that guy do x y swimming i'm like how do i know michael phelps is great i don't know who's faster i can't look at his technique and say anything other than well that's way better than anything i know how to do but i can't say the difference between him and the next guy so i guess that's i wonder if it's like i need a concrete identifier and a lot of times people don't like saying i don't know and most people won't put like a ronda rousey in the top even 20 or 50 of but like she changed more than more than almost anybody else she changed the martial arts history i i don't know if that even i i don't think i'm over exaggerating that she she made it okay for women to be fighters yeah and that and like change the way we see like she's one of the great feminists of our time [Music] in her own way yeah in in a weird kind of way that like i don't know uh maybe i'm just a ronda rousey fan but the yeah but she's not in the conversation because then you start converting into numbers well how many did well was she is she among the greatest fighters or did she do the greatest things you know i mean i don't i think it's something i mean obviously ronda is a great judoka who was competing in mma at a time when a lot of the girls like where did you get your skills in the olympics where'd you get yours high school you're like yeah you're gonna olympic girl is gonna beat you up but uh i i guess that that doesn't diminish it just that accomplishment is what it is i don't have to i don't fedor is not diminished by the fact that he would like if he were to fight stephen milochus right now probably wouldn't go great or that jon jones exists i don't now have to like knock fedor's accomplishments down or say oh because bj penn or someone so let's say he has a mixed record at this point that somehow invalidates the things that they've done before yeah i guess it kind of brings us back to a lot of the other people we've talked about the fact that the the brilliant people throughout history that we love are some of the monsters throughout history that we rightly reviled in a lot of cases we're complicated people and their legacy is more than just one thing and someone doing something amazing doesn't involve doesn't mean they didn't do anything bad and someone doing terrible things doesn't doesn't mean that it doesn't invalidate the the positives that they did but i guess we fighting the urge to put people in one category and same with ourselves i think that's why people get depressed oh i'm good right now oh i'm bad right now versus hey we're all at work in progress and we're trying to do x number of things and legacy is a tough thing to figure out anyway and it's all speculative last time or no on reddit you said that last time too that you don't experience much fear uh before fights i'd like to ask you a couple mike tyson things if it's okay it's just interesting to me i'm just weird so there's a i don't know if you've seen this clip of tyson talking about how he feels leading up to a fight that uh he's kind of overtaken with fear as he gets closer and closer and closer to the ring his uh confidence grows um have you seen the clip i'm aware of it okay we've seen in a while here let me play it for you i think george st peter said something similar to me one time while i'm in the dressing room five minutes before i come out my gloves are laced up i'm breaking my gloves down i'm pushing the lever at the back of my break in the middle of the blood so my knuckle appears to the left feel my knuckle piercing against the tight leather gloves on that and the last box angle and i come out i have supreme confidence but i'm scared to death i'm totally afraid i'm afraid of everything i'm afraid of i'm afraid of being humiliated but i'm totally confident closer i get to the ring the more confidence i get the closer more confidence i get the closer more confidence i get all during my training i've been afraid of this man i thought this man might be capable of beating me i've dreamed of him beating me but i always stayed afraid of him but it was closer i get to remain more confident once i'm in the ring i'm a god no one could beat me i'm a god i mean first of all he's cognizant of both his demons and whatever the hell ideas he has about violence is so interesting is there something about the uh the tension that he's describing about being confident and scared that resonates with you or you're or do you hold to this idea that you've kind of spoken about before that you're really not afraid no i i can i can appreciate what he's saying you know i think that um you know i can speak to feeling like concerned about let's say for instance if you feel a certain way i think people are a lot more like computers than we than we like to admit and just because a lot of times i can't parse what's going on and why it doesn't mean that it's not it doesn't make sense and and i think that at least in the times of like if i'm concerned about a situation or about a person or about something happening prior to the fight or i'm like there's a reason there was a reason i don't have to push that down and bury it there's a reason like why what have i not thought about what have i not done what am i missing why am i feeling this way as you mentioned you know for yourself prior like you'd be like why am i feeling like this i don't do this very well in certain aspects of my life now that i mentioned it or not i think about it but when it comes to competing i think i do an all right job and i'm trying to learn to be better and it's uh and going like well why do i if i feel this way there's a reason okay am i thinking about this the wrong way have i not adequately prepared for something i have to i have to address it and then maybe i'll be up for four hours that night you know like extra hours thinking what if i not address watching sparring watching this watching that and then that when i when i am thinking about things more more accurately or when i've addressed what that concern was i feel any of that concern kind of dissipate and i guess if i honestly thought that you know i guess when it comes to i know i'm gonna die at a certain point obviously i'm gonna get hurt i mean you know pain happens but the pain of loss would be nothing compared to the or the pain of injury nothing compared to the pain of running away you know and yeah and so i guess if i think about where's my value what it's like i feel like i'm a winner every single time i step into that ring and fight with everything that i have i can't promise that i'll win my next fight i know that i have the skills and the tools to beat anyone in grappling or wearing mixed martial arts at this point it's just i i know that for certain i've trained enough people i compete with enough people i know i know where i stand but i also know that i'm not perfect and also the the better fighter even if i perceive that i was that thing um doesn't win on the night the the man who fights better wins on the night and if i give credence in my mind to only the person that's that's one has value versus going what's your process what's your path through this how are you going about this how are you thinking about this how are you behaving then if if i can focus on the process then then i will respect my opponent i will respect myself and i'll respect anyone that behaves with with a certain level of of consistency to that and they could win there's plenty of winners in history that that are shit bags and there's plenty of losers that are not but winning doesn't make you a bad or good person and losing doesn't make you good by default either or bad by default so and i think that that can be the truth socially that can be the truth you know athletically and you know academically so i guess is there a primal fear though like a primal fear of getting hurt the running away and not facing the the threat long term is the bigger pain than any pain you can experience in the fight that's pretty powerful but what about the violence of i mean you don't have that on your face but like the i don't know if you've also seen tyson talk about he was on rogan recently he was talking about was trying to psychoanalyze himself about why he enjoys violence so much i mean he called it orgasmic i don't know have you seen that clip i haven't okay we're playing we're playing it because i can i need to because trump also retweeted it which is hilarious i don't know how to contextualize yeah that's something that our president retweeted the clip of uh of tyson saying that's just maybe he's just doing like they're not it's like i'm gonna throw him a curveball no one's gonna have any idea what that is but yeah he did no explanation just here you go there you go well i think that's kind of like what you're describing it's like if i give you an answer it has to be a good one better to just let your imagination run exactly yeah he's yeah he's like the kubrick of our time you know what's really interesting that sometimes um period it's not real but sometimes i struggle with the fact of why it's a possibility i can really hurt somebody like you don't want to hurt them what do you mean when you struggle struggle with the possibility that you could hurt them that is sometimes it's orgasmic sometimes yeah like some fights like particularly like tyro biggs or someone that you had problems with someone that you joe's not getting you had animosity towards so when you finally get your hands on them hey um what does it mean um when fighting gets gets you erect what does that mean it's a good question means you're getting excited yeah so that that's going through your mind right now well that's how i get when i was a kid and i you know sometimes i get to twinkle the twinkle yeah well that's what i'm saying is like you reached a state as a human being as a champion as a ferocious fighter you reached a state of of ability and of accomplishment that very few humans will ever ever touch and feel that's why i'm asking you when you're running when you're hitting the bag when that heart's beating again and that you know who you are you're mike motherfucking tyson so when you're doing all this shit again you're still mike tyson those thoughts have got to be burning inside you again it's got to be pretty wild i don't know it's um it's wild but um i believe it's um it's rightfully so to be that way and i just know how to um i don't but think i i'm how to deal with it i don't let it overwhelm me i mean he goes on to try to they don't ever like joe doesn't bite well the interesting thing about that conversation is mike was trying to figure himself out yeah like he's trying on the spot like why do i feel this way uh to me it was like to me it's so real and honest to uh to feel like pleasure from hurting somebody like that you rarely hear that in this society it's like you rarely like talk about like you feel pleasure from winning you feel pleasure from like the relief of overcoming like all the stress you have to go through pleasure from just like the the specifics of the fight the techniques you use the maybe overcoming being down a couple rounds but like how often do you hear somebody say i just enjoyed he's not even saying because i hate the opponent he's saying like i enjoyed purely the violence of it that's crazy i mean i don't know it's honest it made me ask like i wonder how many of us are cognizant of that let's say mike is uncommonly seemingly uh honest i think athletes make a full-time job out of lying you know i think people make a full themselves perhaps too that's fair i mean in some you tell yourself or you tell others what you feel you need to or maybe whether you would even know what you feel you need to but why should he not i mean again did he did he run up and just hit somebody that's didn't sign up for this no they sign it to be there well that's the interesting thing about dyson is there's that weird uh like non-standard behavior i mean like your fighting style is not standard he's non-standard to another degree of like uh who else has that in jiu jitsu uh uh polaris uh uh has this kind of weirdness like what's what's in there like there's a fear that i think uh most opponents would have because it's like it's no longer about like it takes you out of the realm of its game it takes us back to the thing we're talking about like before is it strips away that like several layers of ryan hall the the podcast uh guest ryan hall the jiu jitsu instructor ryan hall just a competitor it keeps going down to a point where like ryan hall the murderer of all things that get in his way that lies underneath all of it seemingly like if we're like in this society we put all that aside but it makes you wonder like now society's being tested in many ways it makes you wonder like what's underneath there well do we want do we want the answer to that because i guess it's what is it uh you've seen paul fiction you know the best character in the movie and in the best scene in the movies i give my questions here if you're what he called him my answers scare you she's asking scary questions you know and i guess uh you wonder i mean all of us that's something that i think it's funny oh that's not okay i mean versus maybe not appropriate for situation x y or z but uh what should make any of us think i mean humanity is a different place now and i mean i'm not saying anything crazy out there but it came in a different place now than we were 5 000 years ago where all of us are descended from people who have killed things with their teeth and fingernails in order to be where we are and whether it was in whether it was an animal or it was in conflict with another person i mean think about that the chances of dying by violence now are so so slim at least in in most countries in most places like shockingly small thankfully but there was a period of time like the most period of time where dying by violence was mostly how it went down and i guess what would be facilitative what would allow you to win back to ender's game you know what allows you if you can't do that you are all you are forever subject to people who can and that's that's a real thing and you know we're fortunate to find ourselves in a situation where we don't where other things matter but that is a funny thing periodically where people you'll see people like kind of drawing at each other like in videos or out in the world that clearly neither of them expect this to get serious like i'm just going to yell at you you're going to yell at me and it's like this weird larping thing we're both going to go on our own separate way all it takes is one person to be like well i wasn't kidding yeah and it's like oh you'll go to jail like oh i know you're gonna go to the morgue and it's that's but that can happen like that like society i mean obviously anyway you could jump across the table and stab me in the eye i mean i appreciate hope if you don't and there will be consequences if you do but not from not from me from from the rest of society will potentially get you at a certain point but you can decide to not play by the rules anytime you want it's fascinating that yeah that's we've created rules based on which we all behave but underneath there you know there there's things that doesn't the there's motivations and forces that don't play by the rules they're still there nature's metal is under the surface seriously and again i pull out my phone and i'm basically saying like hey i'm gonna you're gonna get caught yeah but really i'm further antagonizing you yeah rightly wrongly you know what i mean like and that that's an interesting thing and i feel like just people need to remember any of us need to remember just for any reason just that's that's one step away at all at all times you ever i've had people say to me before like oh i don't feel safe i'm like you're not safe i'll kill you before you get out of this room nothing you do stop that nothing i mean but don't worry you could do the same to me which means i'm like oh thank goodness can you imagine like how many guns are there are in this country like i mean everywhere i mean seriously everywhere but that's a heartening thought not the other way because people usually freak out and go oh my god gun violence gun violence says gun violence is like really not a serious issue in the united states compared to what it could be because it means that i mean with the amount of guns and the amount of bullets that are out there that are in circulation can you imagine if like one in every thousand was used in anger each day i mean this would be a terrifying place to live you couldn't go anywhere so i mean although you could say hey this is more than we'd like or xyz it actually means that people are much more reasonable insane than we're saying than or then i then sometimes i might and i might argue so i guess what i mean is like oh man i walked to 7-11 and i didn't get stabbed i'm like oh well that's good because not because i protected myself with my karate it's basically no one decided to run over and stab me because i wasn't protecting myself it's i they they stopped so i guess we're all fortunate to live in a society that like you said nature being metal doesn't become that big of an issue all the time but it is funny when you get people in the ring and you go hey let's peel back from mr tyson many layers of that and say hey now it's okay and it's cool that i mean that's what society's doing so i've i lived in harvard square for a while and we add extra layers of what safe means like now there's a dis discourse about safe spaces about like ideas being violence or or like uh you know yeah but ideas or minor slights against your personality being violence but that's all like extra layers around the nature is metal thing that uh it's cool that's that's what progress is but we can't forget that like underneath it it's still it's still the the thing that will murder at the at the drop of uh in any at any moment if uh if aroused one thing that i find funny though or ironic maybe about the uh the you know words of violence you know offense is violence thing is that of course that if that the belief in that then justifies my violence like my and whether maybe maybe not physical violence but my response to my my aggressive response to things and i guess like which again regrets begets a further aggressive response and like a you know kind of a tit-for-tat sort of situation or or it goes to like well there's 10 of me and there's one of you so we'll get you and you can't do anything about it but that's not morality that's that's just saying that's might makes right so i guess again you can understand why people do it and there are certain there is a progress aspect to it but again i guess without proper examination i'm effectively with my 10 friends you know and and the force of the law mike tysoning people but not admitting to myself what i'm doing and at least mike tyson again is honest are you uh afraid of death i mean it's easy for me to say no as i sit here probably not about to die but is this like the ufc question can you defeat any opponent exactly yes the answer is of course yes and uh i don't have they're not around they're not here are they yeah exactly but i mean you uh do you ponder your own mortality maybe another context to that is you mentioned two deaths for martial artists i think that's actually why honestly even though at a relatively young age i think mortality is something that i'm aware of more maybe more than the average person i think probably most athletes can speak to this and anyone that's had trouble i've managed to to slide out of a couple near-death experiences personally you know mostly river related um because i'm an idiot but um i regret nothing but uh yeah yeah but uh thank god we're here but um yeah it is in our seeing seeing the end and seeing going well what's going to happen i guess i think it comes back to kind of what we're discussing about belief structure and belief system i think a lot of times if i recognize that no matter what i do it's all going to end one day and then you go well why were we here what would i do am i going to make it to 40. i have no idea i'd like to hope so that i had no idea that i was going to make it to to the age that i am now um am i going to make it to 80. how much of that is in my control much of it is not i mean it's so funny it's an interesting like back to the belief structure again like locus of internal and external locus of control you know what's facilitative versus what's true and you know i think accepting personal responsibility for more than is on my control is is probably a positive but at the same time recognizing that much of much is not in my control i was fortunate enough to be born in the united states fortunate enough to you know to not knock on wood have a serious disease that i'm not aware of right now um i didn't do any of that i just showed up that was really fortunate and i i guess that doesn't diminish the fact that i try to make decent choices but it works in concert with it and i i guess um when i when you go is death what i want right now no no i should think not and again it's easy for me to be relatively calm about as i'm not staring it in the face but what i would care a lot more about is is how you live that's what's in my control and i can't control if as i walk out of this building a helicopter falls on me worrying about that i can't control maybe i maybe i have cancer now and i don't know it i really hope not but um there's something about meditating on the fact that it could end today outside your control that can uh clarify your thinking about yeah the the fact that life is amazing like just kind of somebody yeah helping you enjoy this moment even if life was horrible let's say for instance it was it was you live at one of those times or places and this place still exists in this world today that life is brutal and metal and whatever all and short and painful would you still want it and again as i'm sitting here not not on fire physically it's easy to say yes but i would i'm confident i still i'll plant my feet and say yes any of life any life is amazing and beautiful and a gift an unbelievable gift that none of us have earned for the record i hate the word earned a lot of times earn yeah you earn but it's like there's a lot a lot of good fortune in earning and that's back to do i want justice or do i want grace and i guess we're all fortunate to be where we are no matter where we are and hopefully it should give us some sense of perspective some sense of compassion for other people but also like like you said a sense of peace if it all ended right now would i be happy with what i with a life to this point of course would you like to live a little longer yeah i would try to do more and try to live rightly to the best that i know how which over time will hopefully continue to evolve in a positive direction but if the answer to that is no i i guess uh that's that's always that's a sign that that what i'm doing is not what i'm meant to be doing and i mean you're familiar with the tecumseh before so there's a i've got one actually if you could give me 10 seconds i'll i'll read this one out this is a personal favorite basically and i think it sums up i mean again like it's one of those quotes on the internet like when abraham lincoln said don't believe everything you read online um but uh this is you know i it's again uh attributed but it's like so live your life that the fear of death can never enter your heart trouble knowing about their religion respect others in their view and demand that they respect yours love your life perfect your life beautify all things in your life seek to make your life long and its purpose in the service of your people prepare a noble death song for the day when you go over the great divide always give a word or sign a salute when meeting or passing a friend even a stranger when when in a lonely place show respect to all people and grovel to none when you arise in the morning give thanks for the food and for the joy of living if you see no reason for giving thanks the fault lies only in yourself abuse no one and no thing for abuse turns the wise ones to fools and robs the spirit of its vision when it comes your time to die be not like those whose hearts are filled with the fear of death so that when their time comes they weep and pray for a little more time to live their lives over again in a different way sing your death song and die like a hero going home powerful words i don't think there's a better way to end it let me just say uh we've spoke maybe five six years ago i don't even remember when but i'm not exaggerating saying like you had a huge impact on my life because of the podcast you're the reason i was doing the podcast as long as i have you're the reason i'm doing this podcast and it's a little it's a stupid little meeting that you probably didn't know who i was i didn't really know who you are it was just like a magical moment it's a flap of a butterfly wing kind of situation and uh yeah i'm forever grateful you're one of the most inspiring people in my life so ryan it's a huge honor that you would come here uh jen and talk with me and waste all this time i really appreciate it was amazing thank you so much alex it's just been a pleasure i really appreciate you having us on thank you thanks brother thanks for listening to this conversation with ryan hall and thank you to our sponsors power dot babble and cash app please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from frank herbert in dune deep in the human unconscious is a pervasive need for a logical universe that makes sense but the real universe is always one step beyond logic thank you for listening and hope to see you next time |
Stephen Wolfram: Fundamental Theory of Physics, Life, and the Universe | Lex Fridman Podcast #124 | the following is a conversation with Steven Wolfram his second time in the podcast he's a computer scientist mathematician theoretical physicist and the founder and CEO of Wolfram research a company behind Mathematica wol from alpha Wolfram language and the new wolf from physics project he's the author of several books including a new kind of Science and the new book a project to find the fundamental Theory of physics this second round of our conversation is primarily focused on this latter Endeavor of searching for the physics of our universe in simple rules that do their work on hypergraphs and eventually generate the infrastructure from which space time and all of modern physics can emerge quick summary of the sponsors Simply Safe Sun basket and masterclass please check out these sponsors in the description to get a discount and to support this podcast as a side note let me say that to me the idea that seemingly infinite complexity can arise from very simple rules and initial conditions is one of the most beautiful and important mathematical and philosophical Mysteries and science I find that both cellular aoma and the hypography working on to be the kind of simple clear mathematical playground within which fundamental ideas about intelligence Consciousness and the fundamental laws of physics could be further developed in totally new ways in fact I think I'll try to make a video or two about the most beautiful aspects of these models in the coming weeks especially I think trying to describe how fellow curious minds like myself can jump in and explore them either just for fun or potentially for publication of new Innovative Research In Math computer science and physics but honestly I think the emerging complexity in these hypergraphs can capture the imagination of everyone even if you're someone who never really connected with mathematics that's my hope at least to have these conversations that Inspire everyone to look up to the skies and into our own minds in awe of our amazing Universe let me also mention that this is the first time I ever recorded a podcast Outdoors as a kind of experiment to see if this is an option in times of Co I'm sorry if the audio is not great I did my best and promis to keep keep improving and learning as always if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Friedman as usual I'll do a few minutes of ads now and no ads in the middle I Tred to make these interesting but I do give you time stamp so you're welcome to skip but still please do check out the sponsors by clicking the links in the description it's the best way to support this podcast also so let me say even though I'm talking way too much that I did a survey and it seems like over 90% of people either enjoy these ad reads somehow magically or don't mind them at least that honestly just warms my heart that people are that supportive this show is sponsored by simplysafe a home security company go to Simply safe.com to get a free HD camera it's simple no contracts 15 bucks a month easy setup even I figured it out I have set up in my apartment of course I also welcome Intruders one of my favorite movies is Leon or the professional with Jean Reno Gary Oldman and the brilliant young Natalie Portman if you haven't seen the movie he's a Hitman with a minimalist life that resembles my own fact when I was younger the idea of being a Hitman or targeting evil in a skilled way which is how I thought about it really appealed to me the the skill of it the planning the craftsmanship in another life perhaps if I didn't love engineering and science so much I can see myself being something like a Navy SE and in general I love the idea of serving my country of serving Society by contributing my skill in some small way anyway go to Simply safe.com Lex to get a free HD camera and to support this podcast they're a new sponsor and this is a trial run so you know what to do this show is also sponsored by sunbasket a meal delivery service visit sunbasket.com Lex and use code Lex to get $30 off your order and to support this podcast this is the last read of the trial they're doing so this is the time to get them if you're considering it and if you do it'll help ensure that they decide to support this podcast long term their meals are healthy and delicious a nice break from the minimalist meals of meat and vegetables that I usually eat maybe on a personal note one of my favorite things to do is watch people cook especially people who love cooking and hang out with people over amazing meals I still tend to be strict in my diet no matter what even in fancy restaurants but it brings me joy to see friends and family indulge something like a cake that has way too many calories or ice cream or whatever my mom in fact for much of my life made this cake called an ant hill on my birthday that brings me a lot of joy and way too many calories I was thinking of doing a video with my mom as she makes it I thought it'd be a fun thing to to do together anyway go to sunbasket.com Lex and use code Lex do it now so they sign a long-term contract for this podcast this show is also sponsored by masterclass sign up at masterclass.com Lex 180 bucks a year you get an all access pass to watch lessons from Chris Hatfield Neila grass Tyson Tony Hawk Carlo Santana Garrick Kasparov Daniel Nano and many more brilliant World experts master class has been a really special sponsor they believe in this podcast in a way that gives me strength and motivation to take intellectual risks I'm thinking of doing a few solo podcast episodes on difficult topics especially in history like the rise and fall of the Third Reich or Stalin Putin and many other difficult topics that I'm fascinated by I have a worldview that seeks inspiring positive insights even and perhaps especially from periods of tragedy and evil that perhaps some folks may find Value in if I can only learn to convey the ideas in my mind as clearly as I think them I think deeply and rigorously and precisely but to be honest have trouble speaking in a way that reflects that rigor of thought so it really does mean a lot the love and support I get as I try to get better at this thing at this talking thing anyway go to masterclass.com Lex to get a discount and to support this podcast and now finally here's my conversation with Stephen wlfr you said that there are moments in history of physics it may be mathematical physics or even mathematics where breakthroughs happen and then a flurry of progress follows so if you look back through the history of physics are what moments stand out to you as important such breakthroughs where a flurry of progress follows so the big famous one is 1920s the invention of quantum mechanics where you know in about 5 or 10 years lots of stuff got figured out that's now quantum mechanics can you mention the people involved yeah that kind of the shener Heisenberg you know Einstein had been a key figure originally plank then dur was a little bit later that was something that happened at that time that's sort of before my time right in my time was in the 1970s uh there was this sort of realization that Quantum field theory was actually going to be useful in physics and uh qcd Quantum thermodynamics theory of ques and gluons and so on was really getting started and uh there was again sort of big flurry of things happened then I happened to be a teenager at that time and happened to be uh really involved in physics and so I got to be part of that which was really cool who were the key figures aside from your young selves at that time you know who won the Nobel Prize for qcd okay people David Gross Frank wilchek you know um David poiter the people who are the sort of the slightly older generation dick feineman Murray Gman people like that uh uh who were Steve Weinberg GED Hof he's younger he's he's in the younger group actually but um these are these are all you know characters who are involved I mean it was uh you know it's funny because those are all people who are kind of in my time and I know them and they don't seem like sort of uh historical uh you know iconic figures they seem more like uh everyday characters so to speak um and uh uh so it's always you know when you look at history from long afterwards it always seems like everything happened instantly um and that's usually not the case there was usually a long buildup but usually there's you know there's some method iCal thing happens and then there's a whole bunch of low hanging fruit to be picked and that usually lasts 5 or 10 years you know we see it today with machine learning and you know deep learning neural Nets and so on you know methodological Advance things actually started working in you know 2011 2012 and so on and uh you know there's been this sort of Rapid uh picking of loow hanging fruit which is probably you know some significant fraction of the way way done so to speak do you think there's a key moment like if I had to really introspect like what was the key moment for the Deep learning quote unquote Revolution I mean it's probably the Alex net business Alex net with imag net so is there something like that with physics where so deep learning neural networks have been around for a long time there's a bunch of 1940s yeah there's a bunch of little pieces that came together and then all of a sudden everybody's eyes lit up like wow there's something here like even just looking at your own work just you're thinking about the universe that there's Simple Rules can create complexity you know at which point was there a thing where your eyes light up it's like wait a minute there's something here is it the very first idea or is it some moment along the line of implementations and experiments and so on there's there's a couple of different stages to this I mean one is the think about the world computationally you know can we use programs instead of equations to make models of the world that's something that I got interested in in the at the beginning of the 1980s you know I did a bunch of computer experiments uh you know when I first did them I didn't really I I could see some significance to them but took me a few years to really say wow there's a big important phenomenon here that lets sort of complex things arise from very simple programs um that kind of happened back in 198 4 or so then you know bunch of other years go by then I start actually doing a lot of much more systematic computer experiments and things and find out that the you know this phenomenon that I could only have said occurs in one particular case is actually something incredibly General and then that led me to this thing called principle of computational equivalence and that was a a long story and then you know as part of that process I was like okay you can make simple programs can make models of complicated things what about the whole universe that's our sort of ultimate example of a complicated thing yeah and so I got to thinking you know could we use these ideas to to study fundamental physics uh you know I happen to know a lot about you know traditional fundamental physics my um uh my first you know I I had a bunch of ideas about how to do this in the early 1990s I made a bunch of technical progress I figured out a bunch of things I thought were pretty interesting you know I wrote about them back in 2002 with the new kind of Science and the cellular ainal world there's echo in the cellular aomin world with your new wol from physics project World we'll get to all that allow me to sort of romanticize a little more on the philosophy of science uh so Thomas philosopher of science describes that you know the progress in science is made with uh these Paradigm shifts and so to linger on the sort of original line of discussion do you agree with this view that there is Revolutions in science that just kind of flip the table what happens is it's a different way of thinking about things it's a different methodology for studying things and that opens stuff up this is this idea of uh he's a famous biographer but I think it's called the innovators the biographer of Steve Jobs of Albert Einstein he also wrote a book I think it's called an evaders where he discusses uh how a lot of uh the Innovations in the history of computing has been done by groups there's a complicated group dynamic going on but there's also a romanticized notion that the individual is at the core of the Revolution like where does your sense fall is is uh ultimately like one person responsible for these revolutions that that creates the spark or one or two whatever but or is it just the big mush and mess and Chaos of of people interacting the personalities interacting I think it ends up being like many things there's leadership and there ends up being it's a lot easier for one person to have a crisp new idea than it is for a big committee to have a crisp new idea and um I think you know but I think it it can happen that you know you have a great idea but the world isn't ready for you for it and um you know you can you can I mean this has happened to me plenty right it's you know you have an idea it's actually a pretty good idea but things aren't ready either either you're not really ready for it or the ambient world isn't ready for it and it's hard to get the thing to to get traction it's kind of interesting I mean when I look at a new kind of science you're now living inside history so you can't tell the story of these decades but it seems like the new kind of science has not had the Revolutionary impact I would think it uh might like it feels like at some point of course it might be but it feels at some point people will return to that book and say there was something special here this was incredible what happened or do you think that's already happened oh yeah it's happened except that people aren't you know the the sort of the heroism of it may not be there but the what's happened is for 300 years people basically said if you want to make a model of things in the world mathematical equations are the best place to go last 15 years doesn't happen you know new models that get made of things most often are made with programs not with equations mhm now you know was that sort of going to happen anyway was that a consequence of you know my particular work in my particular book it's hard to know for sure I mean I am always amazed at the amount of feedback that I get from people where they say oh by the way you know I started doing this whole line of research because I read your book blah blah blah blah blah it's like well can you tell that from the academic literature you know were was there a chain of you know academic references probably not one of the interesting side effects of publishing in the way you did this toome is it serves as an education tool and an inspiration to hundreds of thousands millions of people but because it's not a single it's not a chain of papers with piffy titles it doesn't create a splash of citations like it's had it's had plenty of citations but it's it's you know I think that the IT people think of it as probably more you know conceptual inspiration than uh than kind of a you know this is a line from here to here to here in our particular field right I think that the you know the thing which I am disappointed by and which will eventually happen is this kind of study of the this sort of pure computationalism this kind of study of the abstract behavior of the reputational universe that should be a big thing that lots of people do you mean in mathematics purely almost like it's still mathematics but it isn't mathematics but it isn't it isn't it's a new kind of mathematics it's atitle the book yeah right that's why the book is called that right that's not coincidental yeah it's interesting that I haven't seen really rigorous investigation by thousands of people of this idea I mean you look at your competition around rule 30 I mean that's fascinating if if you can say something right is there some aspect of this thing that could be predicted that's a fundamental question of science that's the core that has been a question of science I think that's a that is a some people's view of what science is about and it's not clear that's the right view in fact as we as we live through this pandemic full of predictions and so on it's an interesting moment to be pondering what what science's actual role in those kinds of things is oh you think it's possible that in science clean beautiful simple prediction may not even be possible in real systems that's the open right question I don't think it's open I think that question is answered and the answer is no well no no the answer could be just humans are not smart enough yet like we don't have the tools no that's that's the whole point I mean that's that's sort of the big discovery of this principle of computational equivalence of mine and um the uh you know this is something which is kind of a follow on to girdle's theorem to turing's work on the halting problem all these kinds of things that there is this fundamental limitation built into science this idea of computational irreducibility that says that you know even though you may know the rules by which something operates that does not mean that you can uh readily sort of be smarter than it and jump ahead and figure out what it's going to do yes but do you think there's a hope for pockets of computational reducibility computational re reducibility reducibility that's so and then and then a set of tools and Mathematics that help you discover such pockets that's where we live is in the pockets of reducibility right that's why you know and this is one of the things that sort of come out of this physics project and actually something that again I should have realized many years ago but didn't um is uh you know the it it could very well be that everything about the world is computationally irreducible and completely unpredictable but you know in our experience of the world there is at least some amount of prediction we can make and that's because we have sort of chosen a slice of um probably talk about this in in much more detail but I mean we've kind of chosen a slice of how to think about the universe in which we can kind of sample a certain amount of computational reducibility and that's that's sort of where we where we exist um and uh it may not be the whole story of how the universe is but it is the part of the universe that we care about and we sort of operate in and um that's you know in science that's been sort of a very special case of that that is science has chosen to talk a lot about places where there is this computational reducibility that it can find you know the motion of the planets can be more or less predicted you know the uh uh something about the weather is much harder to predict something about you know other kinds of things the the um are much harder to predict and it it's um uh these are but science has tended to you know concentrate itself on places where its methods have allowed successful prediction so you think rule 30 if it could Linger on it because it's just such a beautiful simple formulation of the essential concept underlying all the things we're talking about do you think there's pockets of reducibility inside rule 30 yes but it's a question of how big are they what will they allow you to say and so on and that's and figuring out where those pockets are I mean in a sense that's the that's sort of a uh uh you know that is an essential thing that one would like to do in science um but it's it's also the the important thing to realize that that has not been you know is is that science if you just pick an arbitrary thing you say what's the answer to this question that question may not be one that has a computationally reducible answer that question if you if you choose you know if you walk along the series of questions and you've got one that's reducible and you get to another one that's nearby and it's reducible too if you stick to that kind of stick to the land so to speak yeah then you can go down this chain of sort of reducible answerable things but if you just say I'm just pick a question at random I'm going to have my computer pick a question at random yeah uh most likely it's going to be irreducible most likely it will be irreducible and and what we're throwing in the world so to speak uh we you know when we engineer things we tend to engineer things to sort of keep in the zone of reducibility when we're thrown things by the natural world for example not not at all certain that we will be kept in this kind of zone of reducibility can we talk about this pandemic then for a second is so how do we there's obviously huge amount of economic pain that people are feeling there's a huge incentive and medical pain uh Health just all kind psychological there's a huge incentive to figure this out to walk along the trajectory of reducible of reducibility there's there's a a lot of disperate data you know people understand generally how virus is spread but it's very complicated because there's a lot of uncertainty there's a there could be a lot of variability like so many obviously a nearly infinite number of variables that uh that represent human interaction and so you have to figure out in ter from the perspective of reducibility figure out which variables are really important in this kind of uh from an epidemiological perspective so why aren't we you kind of said that we're clearly failing well I I think it's a complicated thing so so I mean you know when this pandemic started up you know I happen to be in in the middle of being about to release this whole physics project thing but I thought you know the timing is just uh cosmically but but um but you know but I thought you know I I should do the public service thing of you know trying to understand what I could about the pandemic and you know we've been curating data about it and all that kind of thing but but you know so I started looking at the data and started looking at modeling and I decided it's just really hard you need to know a lot of stuff that we don't know about human interactions it's actually clear now that there's a lot of stuff we didn't know about viruses um and about the way immunity works and so on and um it's you know I think what will come out in in the end is there's a certain amount of of what happens that way you just kind of have to trace each step and see what happens there's a certain amount of stuff where there's going to be a big narrative about this happened because you know of te- cell immunity this happened because there's this whole giant sort of field of of of asymptomatic viral stuff out there you know there will be a narrative and that narrative whenever there's a narrative that's kind of a sign of reducibility but when you just say let's from first principles figure out what's going on then you can potentially be stuck in this kind of uh mess of irreducibility where you just have to simulate each step and you can't do that unless you know details about you know human interaction networks and so on and so on and so on the thing that has has been very sort of frustrating to see is the mismatch between people's expectations about what science can deliver and what science can actually deliver so to speak um because people have this idea that you know it's science so there must be a definite answer and we must be able to know that answer and you know this is it is both uh uh you know that when you after you've played around with sort of little programs in the computational universe you don't have that intuition anymore you know it's it's I always I'm always fond of saying you know the the the the computational animals are always smarter than you are that is you know you look at one of these things and it's like it can't possibly do such and such a thing then you run it and it's like wait a minute it's doing that thing how does that work okay now I can go back can understand it but that's the brave thing about science is that in the chaos of the irreducible universe we nevertheless persist to find those pockets that's kind of the whole point that's like you say that the limits of science but that you know yes it's highly limited but there there's a hope there and like there there's so many questions I want to ask here so one you said narrative which is really interesting so obviously from uh at every level of society you look at Twitter everybody's constructing narratives about the pandemic about not just the pandemic but all the cultural tension that we're going through so there's narratives but they're not necessarily connected to the underlying reality of these systems so our human narratives I don't even know if they're I don't like those pockets of reducibility Cu we're uh it's like constructing things that are not actually representative of reality well and thereby not giving us like good solutions to how to predict the system look it it gets complicated because you know people want to say explain the pandemic to me explain what's going to happen in the future like yes but but also can you explain it is there a story to tell what already happened in the past yeah what's going to happen but I mean in you know it's similar to sort of explaining things in AI or in any computational system it's like like you know explain what happened well it could just be this happened because of this detail and this detail and this detail and a million details and there isn't a big story to tell there's no kind of Big Arc of the story that says oh it's because you know there's a viral field that has these properties and people start showing symptoms you know when when the seasons change people will show symptoms and people don't even understand you know seasonal variation of flu for example it's a it's a um uh it's something where where you know that that could be a big story or it could be just a zillion little details that that mount up see but okay let's let's uh pretend that this pandemic like the Corona virus resembles something like the 1D rule 30 cellular aoma okay so I mean that's how epidemiologists model virus spread indeed yes sometimes use cellometer yes yes and okay so you can say it's simplistic but okay let's say it it is it's representative of actually what happens uh you know the the dynamic of you have a graph it probably is closer to the hypergraph uh model is yes it's it's actually that's another funny thing as as we were getting ready to release this physics project we realized that a bunch of things we'd worked out about about foliations of causal graphs and things were directly relevant to thinking about contact tracing and interaction of cell phones and so on which is really weird but like it just feels like uh it feels like we should be able to get some beautiful core insight about the spread of this particular virus on the hypergraph of human civilization right they I tried I didn't I didn't manage to figure it out but you're one person yeah but I mean I think actually it's a funny thing because it turns out the um the main model you know this sir model I I only realized recently was invented by the the grandfather of a good friend of mine from high school so that was just a you know it's a weird thing right the question is you know okay so you know you know on this graph of how humans are connected you know something about what happens if this happens and that happens that graph is made in complicated ways that depends on on all sorts of issues that where we don't have the data about how Human Society works well enough to be able to make that graph there's actually um uh one of my kids did a study of sort of what happens on different kinds of graphs and how robust are the results okay his basic answer is there are few General results that you can get that are quite robust like you know a small number of big gatherings is worse than a large number of small Gatherings okay that's quite robust but when you ask more detailed questions it seemed like it just depends it depends on details in other words it's kind of telling you in that case you know the irreducibility matters so to speak it's not there's not going to be this kind of one sort of Master theorem that says and therefore this is how things are going to work yeah but the there's a certain kind of from a graph perspective the certain kind of dynamic to human interaction so like large groups and small groups I think it matters who the groups are for example you could imagine large depends how you define large but you can imagine groups of 30 people as long like as long as they are uh cleaks or whatever like right as as long as the outgoing degree of that graph is small or something like like that like you can imagine some beautiful underlying rule of human Dynamic interaction where I can still be happy where I can have a conversation with you and a bunch of other people that mean a lot to me in my life and then stay away from the bigger I don't know not going to Miley Cyrus concert or something like that and and figuring out mathematically some nice see this is an interesting thing so I mean in you know this is the question of what you're describing as kind of uh the problem of many situations where you would like to get away from computational irreducibility a classic one in physics is thermodynamics the you know the second law of Thermodynamics the law that says you know entropy tends to increase things that you know start orderly tend to get more disordered or which is also the thing that says given that you have a bunch of heat it's hard heat is you know the microscopic motion of molecules it's hard to turn that heat into systematic mechanical work it's hard to you know just take something being hot and turn that into oh the the you know the all the atoms are going to line up in the bar of metal and the piece of metal is going to shoot in some Direction that's essentially the same problem as how do you go from this this computationally irreducible mess of things happening and get something you want out of it right it's kind of mining you know you're kind of now you know actually I've I've understood in recent years that that the story of of thermodynamics is actually precisely a story of computational irreducibility but it is a um it is already an analogy you know you can you can kind of see that is can you take the um you know what you're asking to do there is you're asking to go from the um uh the kind of um the mess of all these complicated human interactions and all this kind of computational processes going on and you say I want to achieve this particular thing out of it I want to kind of extract from the heat of what's happening I want to kind of extract this useful piece of sort of mechanical work that I find helpful I mean do you have a hope for the pandemic so we'll talk about physics but for the pandemic can that be extracted do you think what's your intuition the good news is the curves basically you know for reasons we don't understand the curves you know the the the clearly measurable mortality curves and so on for the Northern Hemisphere have gone down yeah but the bad news is that it could be a lot worse for future viruses and what this pandemic revealed is we're highly unprepared for the dis discovery of the pockets of reducibility within a pandemic that's much more dangerous well my my guess is the specific risk of you know viral pandemics you know that the pure virology and you know Immunology of the thing this will cause that to advance to the point where this particular risk is probably considerably mitigated but you know it's uh you know does is is the structure of modern society robust to all kinds of risks well the answer is clearly no and you know it's it's surprising to me the extent to which people uh you know as I say it's it's a it's kind of scary actually how much people believe in science that is people say oh you know because the science does this that and the other we'll do this and this and this even though from a sort of Common Sense point of view it's a little bit crazy and and people are not prepared and it doesn't really work in in society as it is for people to say well actually we don't really know how the science Works people say well tell us what to do yeah because then yeah what's the alternative the for the masses it's difficult to sit it's difficult to meditate on computational reducibility it's difficult to sit it's difficult to enjoy a good dinner meal while while knowing that you know nothing about the world I think this is a this is a place where you know this is this is what politicians you know and political leaders do for a living so to speak because you got to make some decision about what to do and it's um tell some narrative that uh while amidst the mystery and knowing not much about the the past or the future still telling a narrative that somehow gives people hope that we know what the heck we're doing yeah get Society through the issue you know even even though you know the idea that we're just going to you know sort of be able to get the definitive answer from science and it's going to tell us exactly what to do unfortunately you know uh that it's interesting because let me point out that if that was possible if science could always tell us what to do then in a sense our you know that would be a big Downer for our lives if science could always tell us what the answer is going to be it's like well you know it's kind of fun to live one's life and just sort of see what happens if one could always just say Let me let me check my science oh I know you know the result of everything is going to be 42 I don't need to live my life and do what I do it's just we already know the answer it's actually good news in a sense that there is this phenomenon of computational irreducibility that doesn't allow you to just sort of jump through time and say this is the answer so to speak um and that's so that's a good thing the bad thing is it doesn't allow you to jump through time and know what the answer is it's scary do you think we're going to be okay as a human civilization you said we don't know absolutely do you think it's do you think we'll Prosper or destroy ourselves as a in general in general I'm an optimist the no I think that that you know it'll be interesting to see for example with this you know pandemic I you know to me you know when you look at like organizations for example you know having some kind of pertubation some kick to the system usually the end result of that is actually quite good you know unless it kills the system it's actually quite good usually and I think in this case you know people I mean my impression you know it's it's a little weird for me because you know I've been a remote Tech CEO for 30 years it doesn't you know this is bizarrely uh you know in the fact that you know like this coming to see you here is is one of the rare moments the first time in six months that I've been like you know in a building other than my house okay so so so you know it's I'm I'm a kind of ridiculous outlier in these kinds of things but overall your sense is when you shake up the system and throw in chaos that you you uh challenge the system we humans emerge better seems to be that way who's to know but I think that you know people you know my my sort of vague impression is that people are sort of you know oh what's actually important you know what's uh what what is worth caring about and so on and that seems to be something that perhaps is is more you know emergent in this kind of situation it's so fascinating that on the individual level we have our own complex cognition we have Consciousness we have intelligence we're trying to figure out little puzzles and then that somehow creates this graph of collective intelligence where we figure out and then you throw in these viruses of which there's Millions different you know this entire taxonomy and the viruses are thrown into the system of collective human intelligence and we little humans figure out what to do about it we get like we Tweet stuff about information there's doctors as conspiracy theorists and then we play with different information I mean the whole of it is fascinating um I I like you also very optimistic but uh there's a fe just you said uh the computational reducibility there's always a fear of the darkness of the uncertainty be before us yeah it's scary I mean the thing is if you knew everything it will be boring and and it would be and and then um uh and worse than boring so to speak it would be you it would reveal the pointlessness so to speak and in a sense the the fact that there is this computational ability it's like as we live our lives so to speak something is being achieved we're Computing what our lives you know uh you know what happens in our lives that's funny so the computation reducibility is kind of like it gives the meaning to life it is the meaning of life computation reducibility is the meaning of life there you go it it gives it meaning yes I mean it it it it it's what it's what causes it to not be something where you can just say uh you know you went through all those steps to live your life but we already knew what the answer was was right hold on one second I'm going to use my handy wol from alfha sunburn computation thing so long as I can get network here there we go oh actually you know what it says sunburn unlikely this is a QA moment this is a good moment okay okay well let me just check what it thinks see why it thinks that it doesn't seem like my intuition this is one of these cases where we can the question is do we do we trust the science or do we um use common sense the UV thing is cool the yeah yeah well we'll see this is a QA moment as I say it's uh do we trust the product yes we trust the product so and then there'll be a data point either way if if I'm desperately sunburned I will send in a angry feedback because we mention the concept so much and a lot of people know it but can you say what competition reducibility is yeah right so I mean the question is if you think about things that happen as being computations you think about the uh some process in physics something that you compute in mathematics whatever else it's a computation in the sense it has definite rules you follow those rules you uh follow them many steps and you get some result so then the issue is if you look at all these different kinds of computations that can happen whether they're computations that are happening in the natural world whether they're happening in our brains whether they're happening in our mathematics whatever else the big question is how do these computations compare is are there dumb computations and smart computations or are they somehow all equivalent and the thing that I kind of uh was sort of surprised to realize from a bunch of experiments that I did in the early 90s and now we have tons more evidence for it this thing I call the principle of computational equivalence which basically says when one of these computations one of these processes that follows rules doesn't seem like it's doing something obviously simple then it has reached the sort of equivalent level of sophistic of computational sophistication of everything so what does that mean that means that you know you might say gosh I'm I'm studying this little tiny you know tiny program on my computer I'm studying this little thing in in nature but I have my brain and my brain is surely much smarter than that thing I'm going to be able to systematically outrun the computation that it does because I have a more sophisticated computation that I can do but what the principle of computational equivalence say say is that doesn't work our our brains are doing computations that are exactly equivalent to the kinds of computations that are being done in all these other sorts of systems and so what consequences that have well it means that we can't systematically outrun these systems these systems are computationally irreducible in the sense that there's no sort of shortcut that we can make that jumps to the answer now in a general case right right but but the so what has happened you know what science has become used to doing is using the little sort of pockets of computational reducibility which by the way are an inevitable consequence of computational irreducibility that there have to be these Pockets scattered around of computational reducibility to be able to find those particular cases where you can jump ahead I mean one one thing sort of a little bit of a parable type thing that I think is is fun to tell you know if you look at ancient Babylon they were trying to predict three kinds of things they tried to predict you know where the planets would be what the weather would be like and who would win or lose a certain battle and they had no idea which of these things would be more predictable than the other that's funny and and you know it turns out you know where the planets are is a is a piece of computational reducibility that you know 300 years ago or so we pretty much cracked I mean it's been technically difficult to get all the details right but it's basically we we got that you know who's going to win or lose the battle no we didn't crack that one that one that one right game theorist are trying and then the weather kind of halfway on that halfway yeah I think we we're doing okay at that one I you know longterm climate different story but but the weather you know we're we're much closer on that but do you think eventually we'll figure out the weather so do you think eventually most thing will figure out the local pockets in everything essentially the local pockets of reducibility no I think that the it's a it's an interesting question but I think that the you know there is an infinite collection of these local Pockets we'll never run out of local pockets and by the way those local pockets are where we build engineering for example that's how we you know when we if we want to have a predictable life so to speak then you know we have to build in these sort of pockets of reducibility otherwise you know if we were if we were sort of existing in this kind of irreducible world we'd never be able to you know have definite things to know what's going to happen you know I I have to say I think one of the features you know when we look at uh sort of today from the future so to speak I suspect one of the things where people will say I can't believe they didn't see that is stuff to do with the following kind of thing so so you know if we describe oh I don't know something like um heat for instance we say oh you know the air and in here it's you know it's this temperature this pressure that's as much as we can say otherwise just a bunch of random molecules bouncing around people will say I just can't believe they didn't realize that there was all this detail and how all these molecules were bouncing around and they could make use of that I mean actually I realized there's a thing I realized last week actually was um was a thing that people say you know one of the scenarios for the very long-term history of our universe is a so-called heat death of the universe where basically everything just becomes thermodynamically boring everything is just this big kind of gas and thermal equilibrium people say that's a really bad outcome but actually it's not a really bad outcome it's an outcome where there's all this comp computation going on and all those individual gas molecules are all bouncing around in very complicated ways doing this very elaborate computation it just happens to be a computation that right now we haven't found ways to understand we haven't found ways you know our brains haven't you know and our mathematics and our science and so on haven't found ways to tell an interesting story about that it just looks boring to us there's a there you're saying there's a hopeful view of the he death quote unquote of the universe where there's actual beautiful complexity going on similar to the kind of complexity we think of that creates Rich experience in human life and life on Earth yes so those little molecules interact in complex ways that there could be intelligence in that there could be absolutely I mean this this is this is what you learn from this hopeful message right I mean this is what you kind of learned from this principle of computational equivalence you learn it's both a a message of of sort of Hope and a message of kind of you know there you're not as special as you think you are so to speak I mean because you know we we imagine that with sort of all the things we do with with human intelligence and all that kind of thing and all of the stuff we've constructed in science it's like we're very special but actually it turns out well no we're not we're just doing computations like things in nature do computations like those gas molecules do computations like the weather does computations the only the only thing about the computations that we do that's really special is that we understand what they are so to speak in other words we have a you know to us they're special because kind of they're connected to our purposes our ways of thinking about things and so on and that's um but so so that's very human Centric that's we're just attached to this kind of thing so let's talk a little bit of physics maybe let's ask the uh the biggest question what is a theory of everything in general what does that mean yeah so I mean the question is can we kind of reduce what has been physics as a something where we have to sort of pick away and say do we roughly know what how the world Works to something where we have a complete formal Theory where we say if we were to run this program for long enough we would reproduce everything you know down to the fact that we're having this conversation at this moment etc etc etc any physical phenomena any phenomena in this world any phenomenon in the universe but the you know because of computational irreducibility it's not you know that's not something where you say okay you've got the fundamental Theory of Everything then you know tell me whether you know uh lions are going to eat tigers or something you know that's a no you have to run this thing for you know 10 to the 500 steps or something to know something like that okay so at some moment potentially you say this is a rule and run this rule enough times and you will get the whole universe right that's that's what it means to kind of have a fundamental Theory of physics as far as I'm concerned is you've got this rule it's potentially quite simple we don't know for sure it's simple but we have various reasons to believe it might be simple and then you say okay I'm showing you this rule you just run it only 10 500 times and you'll get everything in other words you you've kind of reduced the problem of physics to a problem of mathematics so to speak it's like it's a if you know you like you generate the digits of pi there's a definite procedure you just generate them and it' be the same thing if you have a a fundamental Theory physics of the kind that that I'm imagining you you know you get a this Rule and you just run it out and you get everything that happens in the universe so a Theory of Everything is a mathematical framework within which you can explain everything that happens in the universe it's kind of in a unified way it's not there's a bunch of disparate modules of does it feel like if you create a rule and we'll talk about the wol from physics model which is fascinating but if if you if you have a simple set of rules with a with a data structure like a hypergraph does that feel like a satisfying Theory of Everything because then you really run up against the uh irreducibility computational reducibility right so that's a really interesting question so I I I you know what I thought was going to happen is I thought we you know I thought we had a pretty good I had a pretty good idea for what the structure of this sort of theory that's sort of underneath space and time and so on might be like and I thought gosh you know in my lifetime so to speak we might be able to figure out what happens in the first 10us 100 of the universe MH and that would be cool but it's pretty far away from anything that we can see today and it will be hard to test whether that's right and so on and so on and so on to my huge surprise although it should have been obvious and it's embarrassing that it wasn't obvious to me but but um to my huge surprise we managed to get unbelievably much further than that and basically what happened is that it turns out that even though there's this kind of bed of computational irreducibility that sort of uh these all these Simple Rules run into there is a there are certain pieces of computational reducibility that quite generically occur for large classes of these rules and and this is the really exciting thing as far as I'm concerned the the the big pieces of computational reducibility are basically the pillars of 20th century physics that's the amazing thing that general relativity and Quantum field Theory the sort of the pillars of 20th century physics turn out to be precisely the stuff you can say there's a lot you can't say there's a lot that's kind of at this irreducible level where you kind of don't know what's going to happen you have to run it you know you can't run it within our universe etc etc etc etc etc um but the thing is there are things you can say and the things you can say turn out to be very beautifully exactly the structure that was found in 20th century physics namely general relativity and quantum mechanics and general relativity and quantum mechanics are these pockets of reducibility that we think of as that that you know 20th century physics is essentially pockets of reducibility and then it's it is incredibly surprising that any kind of model that's generative from Simple Rules would have would have such Pockets yeah well I think what what's surprising uh is we didn't know where those things came from it's like general relativity it's a very nice mathematically elegant Theory why is it true you know quantum mechanics why is it true what we realized is that from this that they are these theories are generic to a huge class of systems that have these particular very unstructured underlying rules and that's the that's the thing that is sort of uh remarkable and that's the thing to me that's just it's really beautiful I mean it's and the thing that's even more beautiful is that it turns out that you know people have been struggling for a long time you know how does general relativity theory of gravity relate to Quantum Mechanics they seem to have all kinds of incompatibilities it turns out what we realized is at some level they are the same Theory and that's just it's it's just great as far as I'm concerned so maybe like taking a little step back from your perspective not from the low not from the beautiful hypog graph well from physics model perspective but from the perspective of 20th century physics what is general relativity what is quantum mechanics how do you think about these two theories from the context of the theory of everything like just even definitions yeah yeah yeah right so so I mean you know little bit of history of physics right so so I mean the the you know okay very very quick history of right so so I mean you know physics you know in ancient Greek times people basically said we can just figure out how the world works as you know we're philosophers we're going to figure out how the world works you know some philosophers thought there were atoms some philosophers thought there were you know continuous flows of things people had different ideas about how the world works and they tried to just say we're going to construct this idea of how how the world Works they didn't really have sort of Notions of doing experiments and so on quite the same way as developed later so that was sort of an early tradition for thinking about sort of models of the world then by the time of 1600s time of Galileo and then Newton um sort of the big the big idea there was you know you know title of Newton's book you know Pria Mathematica mathematical principles of natural philosophy we can use mathematics to understand natural philosophy to understand things about the way the world works and so that then led to this kind of idea that you know we can write down a mathematical equation and have that represent how the world works so Newton's one of his most famous ones is his universal law of gravity inverse Square law of gravity that allowed him to compute all sorts of features of of the planets and so on although some of them he got wrong and it was took another hundred years for people to actually be able to do the math uh to the level that was needed but but um but so that that had been this sort of tradition was we write down these mathematical equations we don't really know where these equations come from we write them down then we figure out we work out their consequences and we say yes that agrees with what we actually observe in astronomy or something like this so that tradition continued and um then the first of these two sort of great 20th century uh Innovations was uh well the history is a little bit more complicated but let's let's say the the the um the the the there were two quantum mechanics and general relativity quantum mechanics kind of 1900 was kind of the very early uh stuff done by plank that led to the idea of photons particles of light um but let's let's take general relativity first one one feature of the story is that special relativity thing Einstein invented in 1905 was something which surprisingly was a kind of logically invented Theory Theory it was not a theory where it was something where given these ideas that were sort of axiomatically thought to be true about the world it followed that such and such a thing would be the case it was a little bit different from the the kind of methodological structure of some of some existing theories in more in the more recent times or it just been we write down an equation and we find out that it works so what happened there so there's some reasoning about the light the basic idea was you know the speed of light is appears to be constant uh you know even if you're traveling very fast you shine a flashlight the light will come out even if you're going at half the speed of light the light doesn't come out of your flashlight at one and a half times the speed of light um it's still just the speed of light and to make that work you have to change your view of how space and time work um to be able to account for the fact that when you're going faster it appears that you know uh length is foreshortened and time is dilated and things like this that's special relativity that's special relativity so then Einstein went on with sort of vaguely similar kinds of thinking 1915 invented general relativity which is a theory of gravity and the basic point of general relativity is is it's a theory that says when there is mass in space space is curved and what is that mean you know you usually you think of what's the shortest distance between two points like in in a ordinarily in on a plane in space it's a straight line you know photons light goes in straight lines well then the question is is if if you have a curved surface a straight line is no longer straight on the surface of the Earth the shortest distance between two points is a great circle it's a circle um it's uh so you know Einstein's observation was maybe the physical uh structure of space is such that space is curved D so the shortest distance between two points the the path the straight line in quotes won't be straight anymore and in particular if a if a photon is is you know traveling near near the Sun or something or if a particle is going something is traveling near the sun maybe the shortest path will be one that is is uh is is something which looks curved to us because it seems curved to us because space has been deformed by the presence of mass associated with that that massive object so so the kind of the idea uh there is um think of the structure of space as being a dynamical changing kind of thing but then what Einstein did was he wrote down these differential equations that basically represented the curvature of space and its response to the presence of mass and energy and that ultimately is connected to the force of gravity which is one of the forces that seems to based on it strength operate on a different scale than some of the other forces so it operates at a scale as very large what happens there is is just this this curvature of space which causes you know the paths of objects to be deflected that's what gravity does it causes the paths of objects to be deflected and this is an explanation for Gravity so to speak and the surprise is that from 1915 until today everything that we measured about gravity precisely agrees with General and that's um uh and that you know it wasn't clear black holes were sort of predict well actually the expansion of the universe was an early potential prediction although Einstein tried to sort of patch up his equations to make it not cause the universe to expand because it was kind of so obvious the universe wasn't expanding and um uh you know turns out it was expanding and he should have just trusted the equations and that's a lesson for for those of us um interested in making fundamental theories of physics is you should trust your theory and not try and Patch it because of something that you think might be the case that um uh that that might turn out not to be the case even if the theory says something crazy is happening yeah right like the universe the universe is expanding right which is but but um but you know then it took until the 1940s probably even really until the 1960s until people understood that black holes were a consequence of of general relativity and so on but that's um you know the big surprise has been that so far this theory of gravity has perfectly agreed with you know these collisions of black holes seen by their gravitational waves you know it all just works so that's that's been kind of one pillar of the story of physics it's mathematically complicated to work out the consequences of general relativity but it's not there's there's no I mean and and and some things are kind of squiggly and complicated like people believe you know energy is conserved okay well energy conservation doesn't really work in general activity in the same way as it ordinarily does and it's all a big mathematical story of how you actually nail down something that is definitive that you can talk about it and not specific to the you know reference frames you're operating in and so on and so on and so on but fundamentally general relativity is a straight shot in the sense that you have this Theory you work out its consequences and and that that theory is useful in terms of basic science and trying to understand the way black holes work the way the creation of Galaxy's work s of all these kind of cosmological thing understanding what happened like you said at the Big Bang Yeah like all those kinds of well no not not at the Big Bang actually right but the well features of the expansion of the universe yes and and there are there are lots of details where we don't quite know how it's working you know is there you know where's the dark matter is there Dark Energy you know etc etc etc but but fundamentally the the you know the testable features of general relativity it all works very beautifully and it's it's in a sense it is mathematically sophisticated but is not conceptually hard to understand in some sense okay so that's general relativity and what's its friendly neighbor like you said two theories quantum mechanics right so quantum mechanics the the the sort of the way that that originated was one question was is the world continuous or is it discret you know in ancient Greek times people have been debating this people debated it you you know throughout history as light made of waves is it continuous as it discrete as it made of particles cor pusles whatever um you know what had become clear in the 1800s is that atoms that you know materials are made of discrete atoms you know when you take some water the water is not a continuous fluid even though seems like a continuous fluid to us at our scale but if you say let's look at it smaller and smaller and smaller and smaller scale eventually you get down to these you know these molecules and then atoms it's made of discrete things the question is sort of how important is this discreetness just what's discret what's not discret is energy discrete is you know is what's discrete what's not and so does it have mass those kinds of questions yeah yeah right well there's question I for example is mass discreet is an interesting question which is now something we can address but but um you know what what happened in um uh the in in the coming up to the 1920s there was this kind of mathematical theory developed that could explain certain kinds of discreetness in in particularly and in features of atoms and so on and uh you know what developed was this mathematical theory that was a theory the theory of quantum mechanics theory of wave functions sh's equation things like this that's a mathematical theory that allows you to calculate lots of features of the microscopic World lots of things about how atoms work etc etc etc now the calculations all work just great the um uh the question of what does it really mean is a complicated question now I mean to to just explain a little bit historically the you know the early calculations of things like atoms worked great 1920s 1930s and so on there was always a problem there were uh in Quantum field Theory which is a theory of uh uh in quantum mechanics you're dealing with a certain number of at a certain number of electrons and you fix the number of electrons you say I'm dealing with a two electron thing um in Quantum field Theory you allow for particles being created and destroyed so you can emit a photon that didn't exist before you can absorb a photon things like that that's a more complicated mathematically complicated Theory and it had all kinds of mathematical issues and all kinds of Infinities that cropped up and it was finally figured out more or less how to get rid of those but there were only certain ways of doing the calculations and those didn't work for Atomic nuclei among other things um and that led to a lot of development up until the 1960s of alternative ideas for how how one could understand what was happening in atomic nuclei etc etc etc end result in the end the kind of most quotes obvious mathematical structure of quantum field Theory seems to work although it's mathematically difficult to deal with but you can calculate all kinds of things you can calculate to you know a dozen decimal plac places certain certain things you can measure them it all works it's all beautiful now you way the underlying fabric is the model of that particular theory is Fields like you keep saying Fields those are quantum Fields those are different from classical Fields uh a field is something like you say um there's like you say the temperature field in this room it's like there is a value of temperature at every Point around the room that's um or or you can say the wind field would be the the vector Direction of the wind at every point it's continuous yes and it's a that's a classical field a Quantum field is a much more mathematically elaborate kind of thing um and I should explain that that one of the pictures of quantum mechanics that's really important is you know in classical physics one believes that sort of definite things happen in the world you pick up a ball you throw it the ball goes in a definite trajectory that's has certain equations of motion it goes in a parabola whatever else in quantum mechanics the picture is definitely things don't happen instead sort of what happens is this whole sort of structure of of all you know many different paths being followed and um we can calculate certain aspects of what happens certain probabilities of different outcomes and so on and you say well what really happened what's really going on what's the sort of uh what's the underlying you know what's the underlying story what how do we how do we turn this this mathematical theory that we can calculate things with into something that we can really understand and have a narrative about out and that's been really really hard for quantum mechanics my my friend dick feeman always used to say nobody understands quantum mechanics even though he'd made his you know whole career out of calculating things about quantum mechanics um and uh you know so so it's nevertheless it's uh what the quantum field theory is very uh very accurate at predicting a lot of the physical phenomena so it works yeah and but there are things about it you know it has certain when we apply it the standard model of particle physics for example we uh you know which we apply to calculate all kinds of things it works really well and you say Well it has certain parameters it has a whole bunch of parameters actually you say why is the you know why does the muon particle exist why is it 206 times the mass of the electron we don't know no idea but so the standard model physics is is is one of the models that's very accurate for describing three three of the fundamental forces of physics and look looking at the the world of the very small right and then there's back to the neighbor of uh gravity general relativity so and in the context of a Theory of Everything what's traditionally the task of the unification of these theories and why the issue is you try to use the methods of quantum field Theory to talk about gravity and it doesn't work just like there are photons of light so there are gravitons which are sort of the particles of gravity and when you try and compute sort of the properties of the of the particles of gravity the kind of mathematical tricks that get used um in working things out in Quantum field Theory don't work and um that's um so that's been a sort of fundamental issue and when you think about black holes which are a place where uh sort of the the the structure of space is um uh you know has has sort of Rapid variation and you get kind of quantum effects mixed in with effects from general relativity things get very complicated and there are apparent paradoxes and things like that and people have you know there been a bunch of mathematical developments in in physics over the last I don't know 30 years or so which have kind of picked away at those kinds of issues and got hints about how things might work um and but it hasn't been uh you know and the other thing to realize is as far as physics is concerned it's just like his general relativity his Quantum field Theory you know be happy yeah so do you think there's a quantization of gravity so quantum gravity what do you think of efforts that people have tried to yeah what do you think in general of the efforts of the physics Community to try to unify these laws so I think what's it's interesting I mean I would have said something very different before what's happened with our physics project um I mean you know the remarkable thing is what we've been able to do is to make from this very simple structurally simple underlying set of ideas we've been able to build this this you know very elaborate structure that's both very abstract and very sort of mathematically rich and the big surprise as far as I'm concerned is that it touches many of the ideas that people have had so in other words things like string theory and so on uh twister Theory it's like the you know we might have thought I had thought we're out on a prong we're building something that's computational it's completely different from what other people have done but actually it seems like what we've done is to provide essentially the machine code that you know these things are are various features of domain specific languages so to speak that talk about various aspects of this machine code and I think there's a this is something that to me is is is very exciting because it allows one both for us to provide sort of a new foundation for what's been thought about there and for the all the work that's been done in those areas to you know to give us you know more more momentum to be able to figure out what's going on now you know people have sort of hoped oh we're just going to be able to get you know String Theory to just answer everything that hasn't worked out and I think we now kind of can see a little bit about just sort of how far away certain kinds of things are from being able to explain things some things one of the big surprises to me actually I literally just got a message about one aspect of this is um uh the uh uh you know it's turning out to be easier I mean this project has been so much easier than I could ever imagine it would be that is I thought we would be you know just about able to understand the first 10us 100 seconds of the universe and um you know it would be 100 years before we get much further than that it's just turned out it actually wasn't that hard I me we're not finished but you know so you're you're you're seeing Echoes of all the disperate theories of physics in this framework yes I mean it's a very interesting you know sort of History of Science likee phenomenon I mean the best analogy that I can see is what happened with the early early days of of computability and computation Theory you know touring machines were invented in 1936 people sort of understand computation in terms of touring machines but actually there had been pre-existing theories of computation combinators General recursive functions Lambda calculus things like this but people hadn't those hadn't been concrete enough that people could really wrap their arms around them and understand what was going on and I think what we're going to see in this case is that a bunch of these mathematical theories um including some very I one of the things that's really interesting is one of the most abstract things that's come out of of sort of uh mathematics higher category Theory things about Infinity groupoids things like this which to me always just seemed like they were floating off into the stratosphere ionosphere of mathematics um turn out to be things which our sort of theory anchors down to something fairly definite and says our super relevant to the way that we can understand how physics Works give me a sec by the way I just threw a hat on you've said that um with this metaphor analogy that Theory of Everything is a big mountain and you have a sense that however far we are up the mountain that the the wolf from physics model a view of the universe is at least the right Mountain we're the right Mountain yes without question which aspect of it is the right Mountain so for example I mean so there's so many aspects to Just The Way of the wol from physics project the way it approaches the world that's um that's clean crisp uh and uh unique and Powerful so you know there's a there's discreet nature to it there's a hypergraph there's a computational nature there's a generative aspect you start from nothing you generate everything which do you think the actual model is actually a really good one or do you think this General principle of from Simplicity generating complexity is the right like what aspect of the mountain yeah right I mean I I think that the the kind of the meta idea about using simple computational systems to do things that's you know that's the ultimate big Paradigm that is you know sort of super important the details of the particular model are very nice and clean and allow one to actually understand what's going on they are not unique and in fact we know that we know that there's a there's a large number of different ways to describe essentially the same thing I mean I can describe things in terms of hypergraphs I can describe them in terms of higher category Theory I can describe them in a bunch of different ways they are in some sense all the same thing but our sort of story about what's going on and and the kind of kind of cultural mathematical resonances are a bit different I think it's it's it's perhaps worth sort of saying a little bit about kind of the the you know foundational ideas of of uh of uh uh you know of these of these models and things great so can you maybe uh can we like rewind we've talked about a little bit but can you say like what the central idea is of the Wolfram physics project right so so the question is we're interested in finding a sort of simple computational rule that describes our whole universe can we just pause on that I just so be that's such a beautiful that's such a beautiful idea that we can generate our universe from a from a uh from a data structure a simple structure simple set of rules and we can generate our entire universe yes that's all inspiring right but but so so you know the question is how do you actualize that what might this rule be like and so one thing you quickly realize is if you're going to pack everything about our universe into this tiny rule not much that we are familiar with in our universe will be obvious in that rule so you don't get to fit all these parameters of the universe all these features of you know this is how space works this is how time works etc etc etc you don't get to fit that all it all has to be sort of packed in to this this thing something much smaller much more basic much lower level machine code so to speak than that and all the stuff that we're familiar with has to kind of emerge from the operation of so the rule in itself because of the computational reducibility is not going to tell you the story it's not going to give you the answer to uh it's not going to let you predict what you're going to have for lunch tomorrow and it's not going to let you predict basically anything about your life about the universe right but and you're not going to be able to see in that rule oh there's the three for the number of dimensions of space and so on that's not going to be there so space time is not going to be obviously right so the question is then what what is the universe made of that's that's a it's a basic question and we've had some assumptions about what the universe is made of for the last few thousand years that I think in some cases I just turn out not to be right and you know the most important assumption is that space is a continuous thing that is that you can if you say let's pick a point in space we're going to do geometry we're going to pick a point we can pick a point absolutely anywhere in space precisely numbers we can specify of where that point is in fact you know uclid who kind of wrote down the original kind of atiz of geometry back in 300 BC or so um you know his his very first definition he says a point is that which has no part a point is this is this you know uh this indivisible you know infinitesimal thing okay so we might have said that about material objects we might have said that about water for example we might have said water is a continuous thing that we can just uh you know pick any point we want in in in some water but actually we know it isn't true we know that water is made of molecules that are discrete and so the question one fundamental question is what is space made of and so one of the things that's sort of a starting point for what I've done is to think of space as a discrete thing to think of there being sort of atoms of space just as there are atoms of material things although very different kinds of atoms and by the way I mean this idea you know there were ancient Greek philosophers who had this idea there were you know Einstein actually thought this is probably how things would work out I mean he said you know repeatedly he thought that is way it would work out we don't have the mathematical Tools in our time which was 1940s 1950s and so on to explore this like the way he thought you mean that there is something very very small and discreete that's underlying space space yes and that that means that so you know the mathematical Theory mathematical theories in physics assume that space can be described just as a continuous thing you can just pick coordinates and the coordinates can have any values and that's how you define space space is this just sort of background uh sort of theater on which the universe operates but can we draw a distinction between space as a thing that could be described by uh three values coordinates and how you're are you are you using the word space more generally when you say no I'm I'm just talking about space as in what we experience in in in the universe so you think this 3D aspect of it is fundamental no I don't think that 3D is fundamental at all actually I think that the what's the the the thing that has been assumed is that space is this continuous thing where you can just describe it by let's say three numbers for instance but most important thing about that is that you can describe it by PR prise numbers because you can pick any point in space and you can talk about motions any infinitesimal Motion in space and that's what continuous means that's what continuous means that's what you know Newton invented calculus to describe these kind of continuous small variations and so on that was that's kind of a fundamental idea from uclid on that's been a fundamental idea about space and so is that right or wrong uh it's it's not right it's not right it's it's it's it's right at the level of our experience most of of the time it's not right at the level of the machine code so to speak and so machine code yeah of the simulation that's right that's right they're the very lowest level of the fabric of the universe at least under the the the will from physics model is your sense is as discreet right so so now what does that mean so it means what what is space then so in in um models the basic idea is you say there are these sort of atoms of space they're these points that represent you know represent places in space but they're just discrete points and the only thing we know about them is how they're connected to each other we don't know where they are they don't have coordinates we don't get to say this is a position such and such it's just here's a big bag of points like in our universe there might be 10 to the 100 of these points and all we know is this point is connected to this other point so it's like you know all we have is the friend nwor so to speak we don't we don't have you know people's you know physical addresses all we have is the friend network of these points yeah the underlying nature of reality is kind of like a Facebook uh we don't know their location but we have the friends yeah yeah right we we we know which point is connected to which other points and and that's all we know and so you might say well how on Earth can you get something which is like our experience of of you know what seems like continuous space well the answer is by the time you have 10 to the 100 of these things there they those connections can work in such a way that on a large scale it will seem to be like continuous space in let's say three dimensions or some other number of Dimensions or 2.6 Dimensions or whatever else because they're much much much much larger so like the uh the number of relationships here we're talking about is just a humongous amount so the the kind of thing you're talking about is very very very small relative to our experience of daily life right so I mean you know we don't know exactly the size but maybe maybe uh uh 10 Theus uh maybe around 10 Theus 100 m so you know the size of to give a comparison you know the size of a of a proton is 10us 15 M and so this is something incredibly tiny compared to that um and and the the idea that from that would emerge the experience of continuous space is mindblowing what's your intuition why that's possible like first of all I mean we'll get in into it but I don't know if we will through the medium of conversation but the construct of hypergraphs is just beautiful right cellometer beautiful we'll talk about it but okay but but but this thing about you know continuity arising from discrete systems is in today's world is actually not so surprising I mean you know your average computer screen right every computer screen is made of discrete pixels yet we have the you know we have the idea that we're seeing these continuous pictures I mean it's you know the fact that on a large scale continuity can arise from lots of discrete elements this is at some level unsurprising now but wait but the pixels have uh a very definitive structure of Neighbors on on a computer screen right there is no concept of spatial of space inherent in the underly fabric of reality right right right so so the the the point is but there are cases where there are so for example let's just imagine you have a square grid okay and at every point on the grid you have one of these atoms of space and it's connected to four other four other atoms of space on the you know Northeast southwest corners right um there you have something where if you zoom out from that it's like a computer screen yeah so the relationship creates the the spatial like the relationship creates a constraint which then in an emerging sense creates a like yeah like a uh basically a spatial coordinate for that thing yeah right even though the individual point doesn't have a space even though the individual point doesn't know anything it just knows what it's you know what its neighbors are the on a large scale it can be described by saying oh it looks like it's a you know this grid zoomed out grid you can say well you can describe these different points by saying they have certain positions coordinates Etc now in the in the sort of real setup it's more complicated than that it isn't just a square Grid or something it's something much more Dynamic and complicated which we'll talk about but um uh so you know first the first idea the first key idea is you know what's the universe made of it's made of atoms of space basically with these connections between them what kind of connections do they have well so a the simplest kind of thing you might say is we've got something like a graph where every uh every atom of space uh where we have these edges that go between atom these connections that go between atoms of space we're not saying how long these edges are we're just saying there is a connection from from this place to the from this atom to this atom just a quick pause because there's a lot of very people that listen to this just to clarify because I did a poll actually what do you think a graph is a long time ago and it's kind of funny how few people know the term graph uh outside of computer science it's let's call it a network I think that's that's call a network is better so but every time I like the word graph though so let's define let's just say that graph we'll use terms nodes and edges maybe and it's just uh nodes represent some abstract entity and then the edges represent relationships between those entities right exactly so that's what graph say sorry so so there you go so that's the basic structure that is that is the simplest case of a basic structure actually uh it tends to be better to think about hypergraphs so a hypergraph is just instead of saying uh there are connections between Pairs of things we say there are connections between any number of things so there might be Turner edges so instead of instead of just having uh two points are connected by an edge you say three points are all associated with a hyperedge are all connected by hyper Edge that's just at some level that's at some level that's a detail it's a detail that happens to make the um for me you know sort of in the history of this project the realization that you could do things that way broke out of certain kinds of arbitrariness that I felt that there was in the model before I had seen how this worked I mean all a hypergraph can be mapped to a graph it's just a convenient representation mathematically speaking right that's correct that's correct but so then so okay so the the first question the first idea of these models of ours is spaces made of these know connected sort of atoms of space the next idea is space is all there is there's nothing except for this space So In traditional ideas in physics people have said there's space it's kind of a background and then there's matter all these particles electrons all these other things which exist in space right but in this model one of the key ideas is there's nothing except space so in other words everything that has that exists in the universe is a feature of this hypergraph so how can that possibly be well the way that works is that there are certain uh structures in this hypergraph where you say that little twisty knotted thing we don't know exactly how this works yet but but we we have sort of idea about how it works mathematically this sort of Twisted knotted thing that's the core of an electron this thing over there that has this different form that's something else so the different peculiarities of the structure of this graph are the very things that uh we think of as the particles inside the space but in fact it's just a property of of space mindblowing first of all that it's mind-blowing and we'll probably talk in its Simplicity and Beauty yes I think it's very beautiful I this is I'm but okay so but that's space and then there's another concept we didn't really kind of mention but you thinking of computation as a like a transformation let's talk about time in a second let's let's just let's just I mean on the subject oface that you know there's this question of kind of what you know there's this idea there is this hypergraph it represents space and it represents everything that's in Space the features of that hypergraph you can say certain features in this part we do know certain features of the hypergraph represent the presence of energy for example or the presence of mass or momentum and we know what the features of the hypergraph that represent those things are but it's all just the same hypergraph so one thing you might ask is you know if you just look at this hypergraph and you say and we're going to talk about sort of what the hypergraph does but if you say you know how much of what's going on in this hypergraph is things we know and care about like particles and atoms of electrons and all this kind of thing and how much is just the background of space so it turns out so far as in one rough estimate of this all everything that we care about in the universe is only one part in 10 to 120 of what's actually going on the vast majority of what's Happening is purely things that maintain the structure of space that in other words that the things that are the features of space that are the things that we consider notable like the presence of particles and so on that's a tiny little piece of froth on the top of all this activity that mostly is just intended to you know mostly I can't say intended there's no intention here that just maintains the structure of space let me let me load that in it's uh it just makes me feel so good as a human being well to be the froth on the one and the 10 to the 120 or something of well and also just humbling um how in this mathematical framework how much work needs to be done on the infrastructure right of our universe right to maintain the infrastructure of our universe is a lot of work we are we are merely writing a little tiny things on top of that infrastructure but but you know you you were just starting to to talk a little bit about what I you know we talked about you know space that represents all the stuff that's in the universe the question is what does that stuff do and for that we have to start talking about time and what is time and so on and you know one of the the basic idea of this model is time is the progression of computation so in other words we have a a structure of space and there is a rule that says how that structure of space will change and it's the application the repeated application of that rule that defines the progress of time um and what does the rule look like in in the space of hyperg grass right so what the rule says is something like if you have a little tiny piece of hypergraph that looks like this then it will be transformed into a piece of hypergraph that looks like this so that's all it says it says you pick up these elements of space and the you can think of these these uh edges these hyper edges as being relations between elements in space you might pick up uh these two relations between elements in space and we're not saying where those elements are or what they are but every time there's a certain arrangement of elements in space then arrangement in the sense of the way they're connected then we transform it into some other Arrangement so there's a little tiny pattern and you transform it into another little pattern that's right and then because of this I mean again it's kind of similar to Cellular atomine that like yes on paper the rule looks like super simple it's like uh yeah okay yeah like yeah right from this the universe can be born uh but like once you start applying it beautiful structure starts being potentially can be created and what you're doing is you're applying that rule to different parts like to anytime you match it within the hypergraph exactly and then one of the like incredibly beautiful and interesting things to think about is the order in which you apply that rule yes because that pattern appears all over the place right so this is a big complicated thing very hard to wrap one's brain around okay so so you you say the rule is every time you see this little pattern transform it in this way but yet you know as you look around the space that represents the universe there may be zillions of places where that little pattern occurs yeah so so what what what it says is just do this apply this rule wherever you feel like and what what is extremely non-trivial is well okay so so this is happening sort of in in computer science terms sort of asynchronously you're just doing it wherever wherever you feel like doing it and the only constraint is that if you're going to apply the rule somewhere the the things to which you apply the rule the the little you know elements to which you apply the rule if they if they have to be okay well you can think of each application of the rule as being kind of an event that happens in the universe Y and these the input to an event has to be ready for the event to occur that is if one event occurred if one transformation occurred and It produced a particular atom of space then that atom of space has to already exist before another uh transformation that's going to apply to that atom of space can occur so like the prerequisite for the event that's exist that's right so it it that defines a kind of uh this sort of set of causal relationships between events it says this event Happ has to have happened before this event but that is um but that's that's not a very limiting constraint no it's not and what's still you still get the zillion uh that's a technical term options that's correct but but okay so this is where things get a little bit more elaborate but they're mindblowing so right but so so what what what happens is so the first thing you might say is you know let's well okay so so this question about the freedom of which which event you do when well let me let me sort of State an answer and then explain it okay the the um the validity of special relativity is a consequence of the fact that in some sense it doesn't matter in what order you do these underlying things so long as they respect this kind of set of causal relationship ship so and that's that's uh in a the the part that's in a certain sense is a really important one but the fact that it it sometimes doesn't matter that's a I don't know what that's another like beautiful thing okay so so there's this idea of what I call causal invariance causal invariance exactly that's so really really powerful powerful idea a powerful idea which has actually Arisen in different forms many times in the history of mathematics mathematical logic even computer science has many different names um I mean our particular version of it is a little bit tighter than other versions but it's basically the same idea here's here's how to think about that idea so imagine that well let's talk about it in terms of math for a second let's say you're doing algebra and you're told you know multiply out this series of polinomial that are that are multiplied together okay you say well which order should I do that in so well do I multiply the third one by the fourth one and then do it by the first one or do I do the fifth one by the sixth one and then do that well it turns out it doesn't matter you can you can multiply them out in any order you'll always get the same answer that's a that's a a property if you think about kind of making a kind of network that represents in what order you do things you'll get different orders for different ways of multiplying things out but you'll always get the same answer same thing if you let's say you're sorting you've got a bunch of A's and B's they're in random some random order you know baa BBB AA whatever and you you have a little rule that says every time you see ba flip it around to AB okay eventually you apply that rule enough times you'll have sorted the string so that it's all the A's first and then all the B's again you there are many different orders in which you can do that that many different sort of places where you can apply that update in the end you'll always get the string sorted the same way I know I know with sorting a string it's it sounds obvious that's to me surprising that that there is in complicated systems obviously with a with a string but in in a hypergraph that the application of the rule a asynchronous rule can lead to the same results sometimes yes yes that is it is not obvious and it was something that um you know I I sort of discovered that idea for these kinds of systems in back in the 1990s and for various reasons I I I was not I was not satisfied by how sort of fragile finding that particular property was was and let me let me just make another point which is that that it turns out that even if the underlying rule does not have this property of causal invariance it can turn out that every observation made by observers of the rule can they can impose what amounts to causal invariance on the rule we can explain that it's a little bit more complicated I mean technically that has to do with this idea of completions which is something that comes up in term re writing systems automated theorem proving systems and so on but that let's let's ignore that for a second we can come to that later but is it useful to talk about observation not yet not yet so so great so there's some concept of causal invariance as uh you apply these rules in an asynchronous way you can think of those Transformations as events so there's this hypergraph that represents space and all of these events happening in the space and the graph grows in interesting complicated ways and eventually the froth arises to of a what we experience as human existence so that's that's the that's some version of the picture but but let's explain a little bit more exactly what's a little a little more detailed like right well so so one thing that is sort of surprising in this in this theory is one of the sort of achievements of 20th century physics was kind of bringing space and time together that was you know special relativity people talk about SpaceTime this sort of unified thing where space and time kind of are mixed and there's a nice mathematical formula M um that uh in which you know space and time sort of appear as part of the SpaceTime Continuum the SpaceTime you know four vectors and things like this um you know we talk about spe time as the fourth dimension and all these kinds of things it's you know that and it seems like the theory of relativity sort of says space and time are fundamentally the same kind of thing so one of the things that took a while to understand in in this approach of mine is that uh in in in my kind of approach space and time are really not fundamentally the same kind of thing space is the extension of this hypergraph time is the kind of progress of this inexorable computation of these rules getting applied to the hypergraph so it's they seem like very different kinds of things and and so that at first seems like how can that possibly be right how can that possibly be lorensen variant that's the term for things being you know following the the rules of special artivity well it turns out that when you have causal invariance that and let's see we can it's worth it's worth explaining a little bit how this works it's a little bit little bit elaborate but but the basic point is that um uh the even though space and time sort of come from very different places it turns out that the rules of sort of space time that special relativity talks about um come out of this model when you're looking at large enough systems MH so so a way to think about this you know in terms of the when you're looking at large enough systems um the U part of that story is when you look at some fluid Like Water for example there are equations that govern the flow of water um those equations are things that apply on a large scale if you look at the individual molecules they don't know anything about those equations it's just the the the sort of the large scale effect of those molecules turns out to follow those equations and it's the same kind of thing happening in our models I know this might be a a small point but it might be a very big one we've been talking about space and time at the lowest level of the model which is space the hypergraph time is the evolution of this hypergraph but there's also SpaceTime that we think about in general relativity for special relativity like what how does how do you go from the uh lowest source code of space and time we're talking about to the more traditional terminology of space and time right so so the the key thing is this thing we call the causal graph so the causal graph is the graph of causal relationships between events so every one of these little updating events every one of these little transformations of the hypergraph happens somewhere in the hypergraph happens at some stage in the computation that's an event that event is has a causal relationship to other events in the sense that if the if another event needs as its input the output from the first event there will be a causal relationship of the the the future event will depend on the past event so you can say it's it has a causal connection and so you can make this graph of causal relationships between events that graph of causal relationships causal invariance implies that that graph is unique it doesn't matter even though you think oh I'm I'm you know let's say we were sorting a string for example I did that particular transposition of of characters at this time and then I did that one then I did this one turns out if you look at the network of of connections between those updating events that network is the same it's it's the if if you were to see the the the structure so in other words if you were to draw that that if you were to put that Network on a picture of where you're doing all the updating the places where you put the the nodes of the network will be different but the way the nodes are connected will always be the same so but the causal graph is a is I don't want it's kind of an observ it's not uh enforced it's just emergent from set of events well it's a it's a feature of of okay so what it is characteristic I guess of the way events happen right it's an event can't happen until its input is ready right and so that creates this this network of causal relationships and that's that's the causal graph and the thing the next thing to realize is okay we when you're going to observe what happens in the universe you have to sort of make sense of this causal graph so and you are an observer who yourself is part of this causal graph and so that means so let me give you an example of of how that works so so imagine we have a really weird Theory of physics of the world where it says this updating process there's only going to be one update at every moment in time and it's just going to be like a touring machine it has a little head that runs around and just is always just updating one thing at a time so you say you know I have a theory of physics and The Theory of physics says there's just this one little place where things get updated you say that's completely crazy because you know it's plainly obvious that things are being updated sort of you know at the same syn yeah at the same time but but the fact is that the thing is that if I'm you know talking to you and you seem to be being updated as I'm being updated but but if there's just this one little head that's running around updating things I will not know whether you've been updated or not until I'm updated so in other words when you draw this causal graph of the causal relationship between the updatings and you and the updatings in me it'll still be the same causal graph whether even though the underlying sort of story of what happens is oh there's just this one little thing and it goes and updates in different places in the universe so is that is that clear or is that a hypothesis is that is that clear that there's a unique causal graph uh if there's causal invariance there's unique coal growth that's so so it's okay to think of what we're talking about as a hypergraph and the operations on it as a kind of touring machine with a single head like a single guy running around updating stuff um is that safe to intuitively think of it this way um let me think about that for a second yes I think so I think that I think there's nothing it doesn't matter I mean you you can you can say okay there is one the reason I'm pausing for a second is that um I'm wondering well well when you say running around depends how far it jumps every time it runs around yeah yeah that's right but I mean like one operation at yeah you can think of it one operation it's easier for the human brain to think of it that way as opposed to uh simultaneous it's not okay but the thing is that's not how we experience the world what we experience is we look around everything seems to be happening at successive moments in time everywhere in space yes that is the um and that's partly a feature of our particular construction I mean that is the speed of light is really fast compared to you know we look around you know I can see maybe 100 feet away right now um you know it's uh the my brain does not process very much in the time it takes light to C 100 ft the brain operates at a scale of hundreds of milliseconds or something like that I don't know and and speed of light is much faster right you know light goes in a billionth of a second light has gone a foot so it goes a billion feet every second there's certain moments through this conversation where I I I uh imagine the absurdity of the fact that there's two descendants of Apes modeled by hypergraph that are communicating with each other and experiencing this whole thing as a real time simultaneous update with uh I'm taking in photons from you right now but there's something much much deeper going on right here it it does have a it's paralyzing sometimes just yes to remember that right no I mean you know but so you know yes yes as a small little tangent I I just remembered that we're talking about I mean this the about the fabric of reality right so we we've got this causal graph that represents the sort of causal relationships between all these events in the universe yeah that causal graph kind of is a representation of space time but our experience of it requires that we pick reference frames this is kind of a key idea Einstein had this idea that what that means is we have to say what are we going to pick as being the uh sort of what we Define as simultaneous moments in time so for example we can say um you know we we set how do we set our clocks you know if we've got a a spacecraft landing on Mars you know do we say that it you know what what time is it landing at was it you know even though there's a 20 minute speed of light delay or something thing you know what time do we say it landed at how do we how do we set up sort of time coordinates for for the world and that turns out to be that there's kind of this arbitrariness to how we set these reference frames that Define sort of what cils simultaneous and what is the the essence of special relativity is to think about reference frames going at different speeds and to think about sort of how they assign what counts as space what counts as time and so on um that's all well a bit technical but the basic bottom line is that the this causal invariance property that means that it's always the same causal graph independent of how you slice it with these reference frames you'll always sort of see the same physical processes go on and that's basically why special relativity works so there's something like special relativity uh like everything around space and time that uh that fits this idea of the causal graph right well you know one way to think about it is given that you have a a basic structure that just involves updating things in in these you know connected updates and looking at the causal relationships between connected updates that's enough when you unravel the consequences of that that together with the fact that there are lots of these things and that you can take a Continuum limit and so on implies special RS of a day and um so that it's kind of a not a big deal because it's kind of it's kind of a you it was completely unobvious when you started off with saying we've got this graph it's being updated in time etc etc etc that just looks like nothing to do with special arts every day and yet you get that and and what I mean then the thing I mean this was stuff that I figured out back in the 1990s the um the the next big thing you get is General Arts of day um and so the in this hypergraph the this sort of limiting structure when you have a very big hypergraph you can think of as being just like you know water seems continuous on a large scale so this hypergraph seems continuous on a large scale one question is you know how many dimensions of space does it correspond to so one question you can ask is if you just got a bunch of points and they're connected together how do you deduce what effective dimension of space that bundle of points corresponds to and that's that's pretty easy to explain so basically if you say you got a point and you look at how many neighbors does that point have okay imagine it's on a square grid then it'll have four neighbors go another level out how many neighbors do you get then what you realize is as you go more and more levels out as you go more and more distance on the graph out you're you're capturing something which is essentially a circle in two Dimensions so that you know the the number of the area of a circle is p pi r squ so the it's the number of points that you get to goes up like the distance you've gone squared and in general in D dimensional space it's R to the^ D it's the the number of points you get to if you go R steps on the graph grows like the number of steps you go to the power of the dimension and that's a that's a way that you can estimate the effective dimension of one of these graphs so what does that grow to so how does the dimension grow because uh I mean obviously the visual aspect of these hypergraphs they're often visualized in three dimensions right and then there's a certain kind of structure uh like you said there's the I mean a circle a sphere uh there there's a planer aspect to it to this graph to where it kind of it almost starts creating a surface like a complicated surface but a surface so how does that connect to affected Dimension okay so if you can lay out the graph in such a way that the that the points in the graph that uh you know the the points that are neighbors on the graph are neighbors as you lay them out out MH and you can do that in two dimensions then it's going to approximate a two- dimensional thing if you can't do that in two Dimensions if everything would have to fold over a lot in two dimensions then it's not an approximating a two- dimensional thing maybe you can lay it out in three dimensions maybe you have to lay it out in five Dimensions to have it be the case that it sort of smoothly lays out like that well but okay so uh and I apologize for the different tangent questions but you know there's an Infinity number of possible rules so we have to look for rules that uh that create the kind of structures that that're reminiscent for uh that have Echoes of the different physics theories in them so what kind of rules is there something simple to be said about the kind of rules that you have found beautiful that you have found powerful right so so I mean what you know one of the features of computational ir reducibility is it's very you you can't say in advance what's going to happen happen with any particular you can't say I'm going to pick these rules from this part of rule space so to speak because they're going to be the ones that are going to work that's you can make some statements along those lines but you can't generally say that now you know the state of what we've been able to do is you know different properties of the universe like dimensionality you know integer dimensionality features of of other features of of quantum mechanics things like that at this point what we've got is we've got rules that that uh any one of those features we can get a rule that has that feature yeah so we don't have the the sort of the final here's a rule which has all of these features we do not have that yet so so if I were to try to summarize the wolf from physics project which is uh you know something that's been in your brain for a long time but really has just exploded in activity you know only just months ago yes uh so it's an evolving thing and next week I'll try to publish this conversation as quickly as possible because by the time it's published already new things will probably have come out so uh so if I were to summarize it we've talked about the basics of there's a hypergraph that represents space there is uh Transformations and that hypergraph that represents um time progress of time the progress of time there's a cause a graph that's a characteristic of this and the basic process of science of yeah of science within the wol from physics model is to try different rules and see which properties of physics that we know of known physical theories are appear within the graphs that emerg from that rule that's what I thought it was going to be uh oh okay so what so what is it turns out we can do a lot better than that it turns out that using kind of mathematical ideas we can say and computational ideas we can we can make General statements and those General statements turn out to correspond to things that we know from 20th century physics in other words the idea of you just try a bunch of rules and see what they do that's what I thought we were going to have to do um but in in fact we can say given causal invariance and computational irreducibility we can derive and this is where it gets really pretty interesting we can derive special relativity we can derive general relativity we can derive quantum mechanics and that's where things really start to get exciting is you know it wasn't at all obvious to me that even if we were completely correct and even if we had you know this is the rule you know even if we found the rule to be able to say yes it corresponds to things we already know I did not expect that to be the case and so for somebody who is uh simple mind and definitely not a physicist not even close what does derivation mean in this case okay so so let me this is interesting question okay so there's so one one thing in the context of computational reducibility yeah yeah right right so what you have to do let me give let me go back to again the mundane example of fluids and water and things like that right so so you have a bunch of molecules bouncing around you can say uh just as a piece of mathematics I happen to do this from cellular autometer back in the mid 1980s you can say just as a matter of mathematics you can say the Continuum limit of these little molecules bouncing around is the Navia Stokes equations that's just a piece of mathematics it's not it doesn't rely on uh you have to make certain assumptions that you have to say there's enough Randomness in the way the molecules bounce around that certain statistical averages work etc etc etc okay it is a very similar derivation to derive for example the Einstein equations okay so the way that Works roughly the einin equations are about curvature of space uh curvature of space I talked about sort of how you can figure out dimension of space there's a similar kind of way of figuring out if you if you just sort of say um uh you know you're making a larger larger ball or larger and larger if you draw a circle on the surface of the Earth for example you might think the area of a circle is pi r squ but on the surface of the Earth because it's a sphere it's not flat the the area of a circle isn't precisely P pi r s as the circle gets bigger the area is slightly smaller than you would expect from the formula P Pi R square has a little correction term that depends on the the ratio of the size of the circle to the radius of the Earth okay so it's the same basic thing allows you to measure from one of these hyper graphs what is its effective curvature and that's oh so um the little piece of mathematics that uh explains special general relativity is uh can map nicely to describe fundamental property of the hyps the curvature of H so special relativity is about the relationship of time to space general relativity is about curvature in in this space represented by this hypergraph so what is the curvature of a hypergraph okay so first I have to explain what was explaining is first thing you have to have is a notional Dimension you don't get to talk about curvature of things if you say oh it's a curved line but I don't what a line is yet so yeah what is the dimension of a hypography hypergraph it's got a trillion nodes in it yeah what is it roughly like is it roughly like a grid a two-dimensional grid is it roughly like all those all those nodes are arranged on line what's it roughly like and there's a pretty simple mathematical way to estimate that by just looking at the the the this thing I was describing this sort of the size of a ball that you construct in the hypergraph that's a you just measure that you can just you know comput it on a computer for a given hypergraph and you can say oh this thing is wiggling around but it's it's roughly corresponds to two or something like that it roughly corresponds to 2.6 or whatever so that's how you that's how you have a notion of dimension in these hypergraphs curvature is something a little bit beyond that it's if you look at the how the size of this ball increases as you increase its radius curvature is a correction to the SI size increased associated with Dimension it's a sort of a second order term in in the in determining the size just like the area of a circle is roughly P pi r s so it goes up like R squar the two is because it's in two Dimensions but when that circle is drawn on a big sphere the the actual formula is pi r 2 * 1 minus uh R 2 over a 2 and some coefficient so in other words there's a correction to and that correction term that gives you coverture and that correction term is what makes this hypergraph correspond have the potential to correspond to curved space now the next question is is that curvature is the way that curvature works the way that Einstein's equations of general relativity you know is it the way they say it should work and the answer is uh yes and the and so how does that work the I mean you the the calculation of the curvature of this hypergraph for for some some set of rules no it doesn't matter what the rules are it doesn't so long as they have causal invariance and computational irreducibility and and they lead to finite dimensional space f non infinite dimensional space nonin dimensional it can grow infinitely but it can't be infinite dimensional so what ises a infinitely dimensional hypog graph look like so that mean for example so in a you start from one root of the tree it Doubles Doubles again doubles again doubles again and that means if you ask the question starting from a given point how many points do you get to remember in like a circle you get to r squ with a two there on a tree you get to for example 2 to the r it's exponential dimensional so to speak or infinite dimensional do you have a sense of in the space of all possible rules how many uh lead to uh infinitely dimensional hypog grass is that U no okay is that an important thing to know yes it's an important thing to know I would love to know the answer to that and but but you know it gets a little bit more complicated because for example it's very possibly the case that in our physical universe that the Universe started infinite dimensional and it only uh it as it as the you know at the big bang it was very likely infinite dimensional and as um as the universe sort of expanded and cooled its Dimension gradually went down and so one of the bizarre possibilities which actually there are experiments you can do to try and look at this the universe can have Dimension fluctuations so in other words we think we live in a three-dimensional universe but actually there may be places where it's actually 3.01 dimensional or where it's you know 2.99 dimensional and it may be that in the in the very early Universe it was actually infinite dimensional and it's only a late stage phenomenon that we end up getting three-dimensional space but from your perspective of the hypergraph the one of the underlying assumptions you kind of implied but you have a sense a hope um set of assumptions that the the rules that underly our universe or the rule that underlies our universe is static is that the one of the assumptions you're currently operating under uh yes but there's a there's a footnote to that which we should get to because it requires a few more steps okay well actually then let's backtrack to the curvature because we're talking about as long as it's finite dimensional uh finite dimensional computational irreducibility and causal invariance then it follows that uh the uh that the large scale structure will follow Einstein's equations and now let me again qualify that a little bit more there's a little bit more complexity to it the um uh okay so Einstein's equations in their simplest form apply to the vacuum no matter just the vacuum and they say in particular what they say is if you have um uh so there's this term jisc that's a term that means shortest path comes from measuring shortest paths on the earth so you you look at a bunch of a bundle of jd6 a bunch of shortest paths it's like the paths that photons would take between two points then the statement of Einstein's equations is basically a statement about a certain the that as you look at a bundle of gd6 the structure of space has to be such that although the the cross-sectional area of this bundle May although the actual shape of the cross-section may change the cross-sectional area does not that's a version that's a that's the most simple-minded version of amuu minus a half r g mu new equals z which is the the more mathematical version of Einstein's equations it's a statement it's a statement of thing called the Richie tensor is equal to zero um that's that's Einstein's equations for the vacuum okay so we get that in um as a result of this model but footnote big you know big footnote because all the matter in the universe is the stuff we actually care about the vacuum is not stuff we care about so the question is how does matter come into this and for that you have to understand what energy is in these models and um one of the things that we realized um you know last late last year was um that there's a very simple interpretation of energy in these models okay and energy is basically well intuitively it's the amount of activity in these hypergraphs and the way that that remains over time so a little bit more formally you can think about this causal graph as having these edges that represent causal relationships you can think about oh boy there's one more concept that we didn't get to is that the the notion of space-like hypersurfaces so this is this is a is not as scary as it sounds the the um it's a it's a common notion in general it's a the notion is you are you're defining what is a possibly what is what um where in SpaceTime might be a particular moment in time so in other words what what is a consistent set of places where you can say this is happening now so to speak and you make this series of of of sort of slices through the SpaceTime uh through this causal graph to rep represent sort of what we consider to be successive moments in time okay it's somewhat arbitrary because you can you can deform that if you're going at a different speed and special relativity you tip those things if you're you can you know there there are different kinds of defamations but only certain defamations are allowed by the structure of the causal graph anyway be there as it may the the the basic point is there is a way of figuring out you know you say what is the energy associated with what's going on in this in this hypergraph and the answer is there is a precise definition of that and it is the formal way to say it is it's the Flux Of causal edges through space likee hypersurfaces the slightly less formal way to say it it's basically the amount of activity the the see the reason it gets tricky is you might say it's the amount of activity per unit volume in in this hyper graph but you haven't defined what volume is so it's it's it's a little bit that you have to but this hypersurface gives some more formalism to that yeah it gives a way to connect that to but intuitive we should think about is the just the amount of activity right so so the amount of activity that kind of remains in one place in the hypergraph corresponds to energy the amount of activity that is kind of where an activity here affects an activity somewhere else C corresponds to momentum and um and so one of the things that's kind of cool is that I'm trying to think about how to say this intuitively the mathematics is easy but the the intuitive version I'm not sure but basically the way that things sort of stay in the same place and have activity is associated with rest mass and so one of the things that you get to derive isal mc^2 um that is a consequence of this interpretation of energy in terms of the way the causal graph Works which is a the whole thing is sort of a consequence of this whole story about updates and hypergraphs and so on so can you Linger on that a little bit how do we get eals mc² so where does the mask come from so okay okay I mean without is there an intuitive so okay F first of all you're pretty deep in the mathematical explorations of this thing right now we're in a very we're in a flux uh currently so maybe you haven't even had time to think about intuitive explanations uh but yeah I mean this one this one is is look roughly what's happening that derivation is actually rather easy and everybody and I've been saying we should pay more attention to this derivation because it's such you know because people care about this one and everybody says it's just easy it's it's easy so there's some concept of energy that's uh can be intuitively thought of as the activity the the flux the level the level of uh changes that occurring based on the Transformations within a certain volume however the heck do you find the volume okay so and then Mass well mass is is mass is associated with kind of the energy that does not cause you to that does not somehow propagate through time yeah I mean one of the things that was not obvious in the usual formulation of speciality is that space and time are connected in a certain way energy moment and momentum are also connected in a certain way the fact that the connection of energy to momentum is analogous to the connection to space between space space and time is not self-evident in ordinary relativity it is a consequence of this of the way this model works it's an intrinsic consequence of the way this model works and it's all to do with that with with unraveling that connection that ends up giving you this this relationship between energy and and well it's energy momentum Mass they're all connected and and so like uh that's hence the general relativity you have a sense that uh it appears to be baked in to the fundamental properties of the way these hypergraphs are evolved well I didn't yet get to so I I got as far as special relativity and equals mc^ s the one last step is in general relativity the the final connection is energy Mass cause curvature in space and that's something that when you understand this interpretation of energy and you kind of understand the correspondence to coverture and hypergraphs then you can finally sort of the the big final answer is you derive the full version of Einstein's equations for space time and matter um and that's um so is that have you that last piece with curvature have is that have you arrived there yet oh yeah we're we're there yes and and here's the here's the way that we here's how we're really really going to know we've arrived okay so you know we have the mathematical derivation it's all fine but but you know mathematical derivations okay so one thing that's sort of a a uh you know we're taking this limit of what happens when you the limit you have to look at things which are large compared to the size of an elementary length small compared to the whole size of the universe large compared to certain kinds of fluctuations blah blah blah there's a there's a there's a tower of many many of these mathematical limits that have to be taken so if you're a pure mathematician saying where's the precise proof it's like well there are all these limits we can you know we can try each one of them computationally and we can say yeah it really works but the formal mathematics is really hard to do I mean for example in the case of deriving the equations of fluid dynamics from molecular dynamics that derivation has never been done MH there is no rigorous version of that derivation so so because you can't do the limits yeah because you can't do the limits um but so the limits allow you to try to describe something general about the system and very very particular the kinds of limits that you need to take with these very right and and the limits will definitely work the way we think they work and we can do all kinds of computer exp hard deration yeah it's just it's just the mathematical structure kind of in you know ends up running right into computational reducibility and you end up with a bunch of a bunch of difficulty there but here's the way that we're getting really confident that we know completely what we're talking about which is when people study things like black hole mergers using Einstein's equations what do they actually do well they actually use Mathematica a whole bunch to analyze the equations and so on but in the end they do numerical relativity which means they take these nice mathematical equations and they break them down so that they can run them on a computer and they break them down into something which is actually a discrete approximation to these equations then they run them on a computer they get results then you look at the gravitational waves and you see if they match okay turns out that our model gives you a direct way to do numerical relativity so in other words instead of saying you start from these Continuum equations from Einstein you break them down into these discrete things you run them on a computer you say we're doing it the other way around we're starting from these discrete things that come from our model and we're just running big versions of them on the computer and uh you know what we're saying is and this is this is how things will work so what I'm the way I'm calling this is is proof by compilation so to speak Pro by that is in other words you're you're taking um something where you know we've got this description of a black hole system and what we're doing is we're we're showing that the you know what we get by just running our model agrees with what you would get by doing the computation from the Einstein equations as a small tangent or actually a very big tangent but uh proof by compilation is a beautiful Concept in a sense the way of doing physics with this model is by running it or compiling it and some level yes it have you thought about and these things can be very large is there totally new possibilities of computing hardware and Computing software which allows you to perform this kind of compilation well algorithms software Hardware so so first comment is these models seem to give one a lot of inition about distributed computing a lot of different intuition about how to think about parallel computation and that particularly comes from the quantum mechanic side of things which we didn't talk about much yet but uh the question of what you know given our current computer hardware how can we most efficiently simulate things yeah that's actually partly a story of the model itself because the model itself has deep parallelism in it yes the ways that we're simulating it we're just starting to be able to use that deep parallelism to be able to be more efficient in the way that we simulate things but in fact the structure of the model itself allows us to think about parallel computation in different ways and one of my realizations is that you know so it's very hard to get in your brain how you deal with parallel computation and you're always worrying about you know if multiple things can happen at different on different computers at different times oh what happens if this thing happens before that thing and we've really got you know we have these race conditions where something can race to get to the answer for another thing and you get all tangled up because you don't know which thing is going to come in first and usually when you do parallel Computing there's a big Obsession to lock things down to the point where you've you've had locks and mutexes and God knows what else where where you've you've um you've arranged it so that there can only be one sequence of things that can happen so you don't have to think about all the different kinds of things that can happen well in these models physics is throwing us into forcing us to think about all these possible things that can happen but these models together with what we know from physics is giving us new ways to think about all possible things happening about all these different things happening in parallel and so I'm I'm guessing they have buil-in protection for some of the parallelism well causal invariance is the built-in protection causal invariance is what means that even though things happen in different orders it doesn't matter in the end as a as a as a person who struggle with concurrent programming in in like Java uh with all all the basic concepts of uh concurrent programming that that if there could be built up a strong mathematical framework for causal invariance that's so liberating and that that could be not just liberating but really powerful for massively distributed computation absolutely no I mean you know what's eventual consistency in in distributed databases is essentially the causal invariance idea yeah okay so that's but but but have you thought about uh you know we're like really large simulations yeah I mean I'm also thinking about look the fact is you know I've spent much of my life as a language designer right so I can't possibly not think about you know what does this mean for Designing languages for parallel computation in fact another thing that's one of these you know I I'm always embarrassed at how long it's taking me to figure stuff out but you know back in the 1980s I worked on trying to make up languages for parallel computation I thought about doing graph rewriting I thought about doing these kinds of things but I couldn't see how to actually make the connections to actually do something useful I think now physics is kind of showing us how to make those things useful and so my guess is that in time we'll be talking about you know we do parallel programming we'll be talking about programming in a certain reference frame just as we think about thinking about physics in a certain reference frame it's a certain coordination of what's going on we say we're going to program in this reference frame oh let's change the reference frame to this reference frame and then our program will seem different and we'll have a different way to think about it but it's still the same program underneath so let me ask on this topic because I put out that I'm talking to you I got way more questions that I can deal with but what Pops to mind is a question somebody asked on Reddit I think is uh please ask uh Dr wlr uh what are the specs of the computer running the universe so we we're talking about specs of hardware and software simulations of a large scale thing what about a scale that is comparative to something that eventually leads to the two of us talking and about right right right so so actually I I did try to estimate that and we have to go a couple more stages before we can really get to that answer because because we're we're talking about um this this thing um you know this is what happens when you when you build these abstract systems and you're trying to explain the universe there quite a number of levels deep so to speak um but uh the um you mean conceptually or like literally cuz you're talking about small object and there's 10 to the something number right it's it's it it is conceptually deep and one of the things that's happening sort of structurally in this project is you know there were ideas there's another layer of ideas there's another layer of ideas to get to the different things that correspond to physics they're just different layers of ideas and they are um you know it's actually probably if anything getting harder to explain this project because I'm realizing that the fraction of way through that I am so far and explaining this to you is less than than you know it might be because because we know more now you know in the every every week basically we know a little bit more and like those are just layers on the initial fundamental yes structure the layers are you know you you might be asking me you know how do we get uh you know the difference between Fons and bosons the difference between particles that can be all in the same state and particles that exclude each other okay last 3 days we've kind of figured that out okay but um and it's very interesting it's very cool um and it's very uh and those are some kind of properties at a certain level layer of abstraction on the hypog graph yes and there's a and there's but the layers of abstraction are kind of there compounding stacking up so it's difficult but but okay but this but the specs nevertheless remain the same the the specs underneath so I I have an estimate so the question is what are the units so we've got these different fundamental constants about the world so one of them is the speed of light which is the so the thing that's always the same in all these different ways of thinking about the universe is the notion of time because time is computation and so there's an elementary time which is sort of the the the amount of time that we ascribe to elapsing in a in a single computational step yeah okay so that's the elementary time so then there's an El parameter or whatever that it's a constant it's whatever we Define it to be because I mean we we don't you know it's all relative right it doesn't matter it doesn't matter what it is because we could be it could be slow it's just a number which which we use to convert that to Second so to speak because we are experiencing things and we say this amount of time has elapsed so to speak but we're within this thing so AB it doesn't it doesn't matter right but what does matter is the ratio what we can uh the ratio of the spatial distance and this hypergraph to this uh to this moment of time again that's an arbitrary thing but we measure that in me/ second for example and that ratio is the speed of light so the ratio of the elementary distance to the elementary time is the speed of light okay perfect and so there's another there are two other levels of this okay so there is a thing which we can talk about uh which is the maximum entanglement speed which is a thing that happens at another level in this whole sort of story of how these things get constructed um that's a sort of maximum speed in Quantum in the space of quantum States just as the speed of light is a maximum speed in physical space this is a maximum speed in the space of quantum States there's another level which is associated with what we call Ral space which is a another one of these maximum speeds we get to this so these are limitations on the system that are able to capture the kind of physical Universe which we live in the quantum mechanic they are inevitable features of having a a rule that has only a finite amount of information in the rule so long as you have a rule that only involves a a a bounded amount a limited amount of only involving a limited number of elements limited number of relations it is inevitable there are these speed constraints we knew about the one for speed of light we didn't know about the one for maximum entanglement speed which is actually something that is possibly measurable particularly in black hole systems and things like this anyway this is long long story short you're asking what the processing specs of the universe of the of the sort of computation of the universe there's a question of even what are the units of some of these measurements okay so the units I'm using are wol from language instructions per second okay because you got to have some you know what the quad computation are you do it there got to be some kind of frame of reference right right so and because it turns out in the end there will be there's sort of an arbitrariness in the language that you use to describe the universe so in those terms I think it's like 10 the 500 or from language operations per second I think is the um I think it's of that order you know B that's scale of computation what about memory if there's an interesting thing to say about storage and memory well there a question of how many sort of atoms of space might there be you know maybe 10 to 400 we don't know exactly how to estimate these numbers I mean this is this is based on some some I would say somewhat rickety way of estimating things uh you know when there start to be able to be experiments done if lucky there will be experiments that can actually nail down some of these numbers and uh because of computation reducibility there's no much hope for very efficient compression like very uh efficient representation to this good question I mean there's probably certain things you know the fact that we can deduce any okay the question is how deep does the reducibility go right okay and I keep on being surprised that it's a lot deeper than I thought okay and so um one of the the things is that that there's a question of sort of how much of the whole of physics do we have to be able to get in order to explain certain kinds of phenomena like for example if we want to study Quantum interference do we have to know what an electron is turns out I thought we did turns out we don't I thought to know what energy is we would have to know what electrons were we don't you get a lot of really powerful shortcuts right there's a there's a bunch of sort of bulk information about the world the the thing that I EX Ed about last few days okay is um uh the idea of fion versus boson fundamental idea that I mean it's the the reason we have matter that doesn't just self-destruct is because of the exclusion principle that means that two electrons can never be in the same Quantum state is it uh useful for us to maybe first talk about how quantum mechanics let's talk about quantum mechanics the wol from physics model yes let's go there so we talked about general relativity now what uh what have you found uh the story of quantum mechanics right within and outside of the wol from physics right so I mean the the the key idea of quantum mechanics that sort of the the the typical interpretation is classical physics says a definite thing happens quantum physics says there's this whole set of Paths of things that might happen and we are just observing some overall probability of of how those paths work okay so when you think about our hypergraphs and all these little updates that are going on there's a very remarkable thing to realize which is if you say well which particular sequence of updates should you do say well it's not really defined you can do any of a whole collection of possible sequences of updates okay that set of possible sequences of updates defines yet another kind of graph that we call a multi-way graph and a multi-way graph just is a graph where at every node there is a choice of several different possible things that could happen so for example you go this way go that way those are two different edges in the multi-way graph and you're building up the set of possibilities so actually like for example I just made the one the multi-way graph for Tic Tac Toe okay so Tic Tac Toe you start off with some some board that you know is everything is blank and then somebody can put down a an X somewhere an O somewhere and then there are different possibilities at each stage there are different possibilities and so you build up this multi-way graph of all those possibilities now notice that even in Te tactoe you have the feature that there can be something where you have two different things that happen and then those branches merge because you end up with the same shape of you know the same configuration of the board even though you got there in two different ways so what the the thing that's sort of an inevitable feature of our models is that just like quantum mechanics suggests definite things don't happen instead you get this whole multi way graph of all these possibilities okay so then the question is so that okay so that's sort of a a picture of what's going on now you say okay well quantum mechanics has all these features of uh you know all this mathematical structure and so on how do you get that mathematical structure okay couple of couple of things to say so quantum mechanics is actually in a sense two different theories glued together quantum mechanics is a theory of how Quantum amplitudes work that more or less give you the probabilities of things happening and it's the theory of quantum measurement which is the theory of how we actually conclude definite things because the mathematics just gives you these Quantum amplitudes which are more or less probabilities of things happening but yet we actually observe definite things in the world um Quantum measurement has always been a bit mysterious it's always been something where people just say well the mathematics says this but then you do a measurement and they're philosophical arguments about what the measurement is but it's not something where there's a theory of the measurement some on Reddit also asked uh please ask Stephen to tell his story of this the double slit experiment okay yeah I can does that does that make sense oh yeah makes sense absolutely makes sense why is this like a good way to discuss uh a little bit let me let me go let me explain a couple of things first so so the structure of quantum mechanics is is mathematically quite complicated um one of the features let's see well how to how to describe this okay so first point is there's this multi-way graph of all these different Paths of of things that can happen in the world and the important point is that that uh these you can have branchings and you can have mergings Okay so this property turns out causal invariance is the statement that the number of mergings is equal to the number of branchings yeah so in other words every time there's a branch eventually there will also be a merge in other words every time there were two possibilities of what might have happened eventually those will merge beautiful concept by the way yeah yeah yeah so so that so that idea okay so then uh so that's that's one thing and that's closely related to the the sort of objectivity in quantum mechanics the fact that we believe definite things happen it's because although there are all these different paths in some sense because of causal invariance they all imply the same thing that's I'm I'm cheating a little bit in saying that but that's roughly the essence of what's going on okay next next thing to think about is uh you have this multi-way graph it has all these different possible things that are happening now we ask this multi-way graph is sort of evolving with time o over time it's branching it's merging it's doing all these things okay um the question we can ask is if we slice it a at a particular time what do we see and that slice represents in a sense something to do with the state state of the universe at a particular time so in other words we've got this multi-way graph of all these possibilities and then we're asking an an okay we take this slice this slice represents aent okay each of these different paths corresponds to a different Quantum possibility for what's happening right when we take this slice we're saying what are the set of quantum possibilities that exist at a particular time and when you say slice are these you slice the graph and then there's a bunch of leaves a bunch of and those represent the state of things right but but then okay so the important thing that you are quickly picking up on is that um what what matters is kind of how these leaves are related to each other so a good way to tell how leaves are related is just to say on the step before did they have a common ancestor so two leaves might be they might have just branched from one thing or they might be far away you know way far apart in this graph where to get to a common ancestor maybe you have to go all the way back to the beginning of the graph all the way back to the beginning so there's some kind of measure of distance right and and that but the what you get is by making the slice what we call it branchial space the space of branches um and in this branchial space um you have a graph that represents the relationships between these Quantum States in branchial space you have this notion of distance in branchial space okay so it's connected to Quant entanglement yes yes it's it's it's basically the the distance in branchial space is kind of an entanglement distance so this that's a very nice model right it is very nice it's very beautiful it's it's I mean it's it's so clean I mean it's it's really you know and it it it tells one okay so anyway so then then this this branchial space uh has this sort of map of the the entanglements between Quantum States so in physical space we have so so you know you can say take let's say the causal graph and we can slice that um at a particular time and then we get this map of how things are laid out in physical space when we do the same kind of thing there's a thing called the multi-way causal graph which is the analog of a causal graph for the multi-way system we slice that we get essentially the relationships between things not in physical space but in the space of quantum States it's like which Quantum state is similar to which other Quantum State okay so now I think next thing to say is just to mention how Quantum measurement works so Quantum measurement has to do with reference frames in bronchial space so okay so measurement in in physical space it matters whether how we assign spatial position and how we how we Define coordinates in space and time and that's that's how we make measurements in ordinary space are we making a measurement based on us sitting still here are we traveling at half the speed of light light in making measurements that way these are different reference frames in which we're making our measurements and the relationship between different events and different points in space and time uh will be different depending on what reference frame we're in okay so then we have this idea of quantum observation frames which are the analog of reference frames but in branchial space and so what happens is what we realize is that a Quantum measurement is the The Observer is sort of arbitrarily determining this reference frame The Observer is saying I'm going to understand the World by saying that space and time are coordinati this way I'm going to understand the World by saying that Quantum States and time are coordinatization frames so in a sense the obser the way the Observer enters is by their choice of these Quantum observation frames and what happens is that the Observer um because okay this is again another stack of other Concepts but anyway because the Observer is computationally bounded there is a limit to the type of quantum observation frames that they can construct interesting okay so there's okay so some constraints some limit on and that's on the choice of observation frames right and by the way I just want to mentioned that there's a I mean it's it's bizarre but there's a hierarchy of these things so in in um uh in thermodynamics the the fact that we believe entropy increases we believe things get more disordered is a consequence of the fact that we can't track each individual molecule if we could track every single molecule we could run every movie in Reverse so to speak and we would you know we would not see that things are getting more disordered but it's because we are computationally bounded we can only look at these big blobs of what all these molecules collectively do that we think that things are that we describe it in terms of of entropy increasing and so on and it's the same phenomenon basically also the consequence of computational irreducibility that causes us to basically be forced to conclude that definite things happen in the world even though there's this Quantum you know this set of all these different Quantum processes that are going on so I I mean I'm I'm I'm I'm skipping a little bit and the the but that that's a that's a a rough picture and in the evolution of the wol from physics project where do you feel we stand on the some of the puzzles that are along the way see you're skipping along a bunch of it's amazing how much these things are unraveling I mean you know these things look it used to be the case that I would agree with dick fan nobody understands quantum mechanics including me okay I'm getting to the point where I think I actually understand quantum mechanics my my exercise okay is can I explain Quantum Mechanics for real at the level of kind of Middle School type explanation right and I'm getting closer it's getting it's getting there I'm not quite there I've tried it a few times and I realize that there are things that um uh where I have to start talking about elaborate mathematical Concepts and so on but I think and and you know you got to realize it's not self-evident that we can explain you know at an intuitively graspable level something which uh you know about the way the universe works the universe wasn't built for our understanding so to speak um but but I think then then um uh okay so another important important idea is um uh this idea of branchial space which I mentioned this sort of space of quantum states it is okay so I mentioned Einstein's equations describing you know the effect of uh the effect of mass and energy on uh trajectories of particles on gd6 the curvature of of um of physical space is associated with uh the presence of energy according to Einstein's equations Okay so turns out that rather amazingly the same thing is true in branchial space so it turns out the presence of energy or more accurately lran density which is a kind of relativistic invariant version of energy um the presence of that causes essentially deflection of jd6 in this branchial space okay so you might say so what Well turns out that the sort of the best formulation we have of quantum mechanics this the fine path integral is a thing that describes Quantum processes in terms of mathematics that can be interpreted as well in quantum mechanics the the big thing is you get these Quantum amplitudes which are complex numbers that represent when you combine them together represent probabilities of things happening and so the big story has been how do you derive these Quantum amplitudes and people think these Quantum amplitudes they have a complex number has you know real part and imaginary part you can also think of it has a magnitude and a phase um and it um people have sort of thought these Quantum amplitudes have magnitude and phase and you compute those together turns out that magnitude the magnitude and the phase come from completely different places the magnitude comes okay so what do you how do you compute things in quantum mechanics roughly I'm I'm telling you I'm I'm getting there to be able to do this at a middle school level but I'm not there yet um the the roughly what happens is you're asking does this state in quantum mechanics evolve to this other state in quantum mechanics and you can think about that like a particle traveling or something traveling through physical space but instead it's traveling through branchial space MH and so what's happening is does this Quantum State evolve to this other Quantum State it's like saying does this object move from this place in space to this other place in space okay now the way that you these quantum amplitudes udes characterize kind of um to what extent the thing will successfully reach some particular point in branchial space just like in physical space you could say oh it had a certain velocity and it went in this direction in branchial space there's a similar kind of concept is there a nice way to visualize for me now mentally Branch space it's just you have this hypergraph sorry you have this multi-way graph it's this big branching thing branching and merging thing but I mean like moving through that space I I'm just trying to understand what that looks like is you know that space is probably exponential dimensional which makes it again another can of worms in understanding what's going on that space as in in ordinary space this hypergraph the spatial hypergraph limits to something which is like a manifold like a like something like threedimensional space almost certainly the multi-way graph limits to a hbert space which is something that I mean it's it's just a weirder exponential dimensional space and by the way you can ask I mean there are much weirder things that go on for example one of the things I've been interested in is the expansion of the universe in branchial space so we know the universe is expanding in physical space but the universe is probably also expanding in BR space so that means the the number of quantum states of the universe is increasing with time the diameter of the thing is growing right so that means that the and and by the way uh this is related to whether Quantum Computing can ever work um and uh uh why okay so let me explain why so so let's talk about okay so first of all just just to finish the thought about Quantum amplitudes the the incredibly beautiful thing just this is just I'm just very excited about this the the um the F path integral is is this formula it says that the amplitude the quantum amplitude is e to the i s overh bar where s is the thing called the action and um it uh okay so that can be thought of as representing a deflection of the angle of this path in the multi-way graph so it's a deflection of a jisc in the multi-way path that is caused by this thing called the action which is essentially associated with energy okay and so this is a deflection of a path in branchial space that is described by this path integral which is the thing that is the mathematical essence of quantum mechanics m turns out that deflection is the deflection of gd6 and branchial space follows the exact same mathematical setup as the deflection of gd6 in physical space except the deflection of gd6 in physical space is described with Einstein's equations the deflection of gd6 and branchial space is defined by the F and path integral and they are the same in other words they are mathematically the same so that means that general relativity is a story of essentially Motion in physical space uh quantum mechanics is a story of essentially Motion in bronchial space and the underlying equation for those two things although it's presented differently because one's interested in different things in branchial space and physical space but the underlying equation is the same so in other words it's the this it's just you know these two theories which are the two sort of pillars of 20th century physics which have seemed to be off in different directions are actually facets of the exact same Theory there and this I mean that's exciting to see to see where that evolves and exciting that that just is there right I mean to me you know look I having spent some part of my early life you know working in these in the context of these theories of of you know 20th century physics it's they just they seem so different and the fact that they're really the same is just really amazing actually let me you you mentioned double slit experiment okay so the double experiment is a is an interference phenomenon where you say there are you know you can have a photon or an electron and you say there are these two slits it could have gone through either one but there is this interference pattern where it's there's destructive interference where you might have said in classical physics oh well if if there are two slits then there's a better chance that it gets through one or the other of them but in quantum mechanics there's this phenomenon of destructive interference that means that even though there are two slits two can lead to nothing as opposed to two leading to more than than for example one slit and in what happens in this model and we've just been understanding this in the last few weeks actually is that the um what essentially happens is that the the double slit experiment is a story of the interface between branchial space and physical space and what's essentially happening is that the destructive interference is the result of the two possible paths associated with photons going through those two slits winding up at opposite ends of branchial space and so they don't and so that's why there's sort of nothing there when you look at it is because these two different sort of branches couldn't get merged together to produce something that you can measure in physical space is there a lot to be understood about brancho space like is mathematically speaking yes it's a very beautiful mathematical thing and it's very I mean by the way this whole is just amazingly rich in terms of the mathematics that it says should exist okay so for example calculus you know is a story of infinite decimal change in integer dimensional space onedimensional two- dimensional threedimensional space we need a theory of infinitesimal change in fractional dimensional and dynamic dimensional space No Such Theory exists so there's a tools of mathematics that are needed here right and this is a motivation for that actually right and it's it's you know there are there are indications and we can do computer experiments and we can see how it's going to come out but we need to you know that the actual mathematics is doesn't doesn't exist and in branchial space it's actually even worse there's there's even more sort of layers of mathematics that are you know we can see how it works roughly by doing computer experiments but to really understand it we need more more sort of mathematical sophistication so quantum computers okay so the basic idea of quantum computers the the promise of quantum computers is quantum mechanics does things in parallel and so you can sort of intrinsically do computations in parallel and somehow that can be much more efficient than just doing them uh one after another and you know I actually worked on Quantum Computing a bit with dick fan back in 1981 2 3 um that kind of time frame and and we a fascinating image you you and findan work on quantum computers well we we tried to work the the big thing we tried to do was invent a Randomness chip that would generate Randomness at a high speed using quantum mechanics and the discovery that that wasn't really possible uh was part of the um the story of we never really wrote anything about it I think maybe he wrote some stuff but I we didn't we didn't write stuff about what we figured out about sort of the fact that it really seemed like the measurement process in quantum mechanics was a serious damper on what was possible to do in sort of you know the possible advantages of quantum mechanics mecs and for computing but anyway so so the the the sort of the promise of quantum Computing is let's say you're trying to you know Factor an integer well you can instead of you know when you factor an integer you might say well does this Factor work does this Factor work does this Factor work um in ordinary Computing it seems like we pretty much just have to try all these different factors um you know kind of one after another but in quantum mechanics you might have the idea oh you can just sort of have the physics try all of them in parallel mhm okay and um the you know and there's this algorithm shaes algorithm which which uh allows you according to the formalism of quantum mechanics to do everything in parallel and to do it much faster than you can on a classical computer okay the only little footnote is you have to figure out what the answer is you have to measure the result so the quantum mechanics internally has figured out all these different branches but then you have to pull all these branches together to say and the classical answer is this okay the standard theory of quantum mechanics does not tell you how to do that it tells you how the branching works but it doesn't tell you the process of corralling all these things together and that process which intuitively you can see is going to be kind of tricky but our model actually does tell you how that process of pulling things together works and the answer seems to be we're not absolutely sure we've only got to two * three so far in in uh you know which is kind of in in in this um in this factorization in quantum computers but we can um uh the you know what seems to be the case is that the advantage you get from the parallelization from quantum mechanics is lost from the amount that you have to spend pulling together all those parallel threads to get to a classical answer at the end now that phenomenon is not unrelated to various decoherence phenomena that are seen in Practical quantum computers and so on I mean I should say as a as a very practical point I mean it's like should people stop ing to do Quantum Computing research no because what they're really doing is they're trying to use physics to get to a new level of what's possible in Computing and that's a completely valid activity whether whether you can really put you know whether you can say oh you can solve an MP complete problem you can reduce exponential time to polinomial time you know we're not sure and and I'm suspecting the answer is no but that's not relevant to the Practical speedups you can get by using different kinds of Technologies different kinds of physics um to do basic Computing so you're saying I mean some of the models you're playing with the indication is that uh to uh get all the Sheep back together uh and you know to to Coral everything together to get the actual solution to the algorithm is uh you lose all the you lose use all by the way I mean so so again this question do we actually know what we're talking about about Quantum Computing and so on so again again uh we're doing proof by compilation so we have a Quantum Computing framework yeah in wolam language and which is you know a standard Quantum Computing framework that represents things in terms of the standard uh you know formalism of quantum mechanics and we have a compiler that simply compiles the representation of quantum Gates into multi-way systems so and in fact the the message that I got was from somebody who's working on the project who has managed to compile one the sort of uh a core formalism based on category Theory um in of core Quantum formalism into multi-way systems so this when you say multi-way system these multi-way graphs yes yes so you're comp yeah okay that's awesome and then you can do all kinds of experiments on that multiway graph right well but the point is that what we're saying is the thing we've got this representation of let's say Shaw's algorithm in terms of standard Quantum Gates and it's just a pure matter of sort of computation to just say that is a equivalent we will get the same result as running this multi-way system can you do complexity analysis on that multi-way system well that's what we've been trying to do yes we're getting there we haven't done that yet I mean we we there's a pretty good indication of how that's going to work out and we've done it as I say our computer experiments we've unimpressively gotten to about 2 * three in terms of factorization which is kind of about how far people have got with physical quantum computers as well but but that's um but yes we will be able to we definitely will be able to do complexity analysis and we will be able to know so the one remaining hope for Quantum Computing really really working at this formal level of you know Quantum brand exponential stuff being done in polinomial time and so on the one hope which is very bizarre is that you can uh kind of uh piggyback on the expansion of bronchial space so here's here's how that might work so you think you know energy conservation standard thing in high school physics energy is conserved right but now you imagine you think about energy in the context of cosmology and the context of the whole universe it's a much more complicated story The expansion of the universe kind of violates energy conservation and so for example if you imagine you've got two galaxies they're receding from each other very quickly they've got two big Central black holes you connect a spring between these two Central black holes not easy to do in practice but let's imagine you could do it now that spring is being pulled apart it's getting getting more potential energy in the spring as a result of the expansion of the universe so in a sense you are you are piggybacking on the expansion that exists in the universe and the sort of violation of energy conservation that's associated with that cosmological expansion to essentially get energy you're essentially building a perpetual motion machine by using the expansion of the universe and that is a physical version of that it is conceivable that the same thing can be done in branchial space to essentially uh mine the expansion of the universe in Branch Hill space as a way to get uh sort of uh Quantum Computing for free so to speak just from the expansion of the universe in branchial space now the physical space version is kind of absurd and involves you know Springs between black holes and so on it's conceivable that the branchial space version is not as absurd and that it's actually something you can reach with physical things you can build in lab and so on we don't know yet okay so yeah like you were saying the branch of space might be uh expanding and there might be some something that could be exploited right in the same kind of way that that um that you can exploit the um uh you know that expansion of the universe in principle in physical space you just have like a glimmer of hope right I think that the look I think the real answer is going to be that for practical purposes you know the official brand that says you can you can you know do exponential things in po time is probably not going to work for people curious to kind of learn more so this is more like this is not Middle School we're going to go to elementary school for a second maybe Middle School let's go to middle school so if I were to try to maybe write a write a pamphlet of like wolf from physics project for dummies AKA for me or maybe make a video on the basics but not just the basics of the physics project but the basics plus the most beautiful Central ideas um how would you go about doing that could you help me out a little bit yeah yeah I mean we covered a l really practical matter we have this kind of visual summary picture that we made um which I think is a pretty good you know when I've tried to explain this to people and you know it's a pretty good place to start is you got this rule you know you apply the rule you're building up this this big hypergraph um you've got all these possibilities you're kind of thinking about that in terms of quantum mechanics I mean that's a that's a that's a decent place to start so basically the things we've talked about which is space represented as a hypergraph transformation of that space is kind of time yes and then uh structure of that space in the curvature of that space as gravity that's that can be explain without going anywhere near quantum mechanics um I would say that's actually easier to explain than special robots of day um oh so going into General so going to curvature yeah I mean special relativity I I think is it's a little bit elaborate to explain yeah and honestly you only care about it if you know about special relativity if you know how special relativity is ordinarily derived and so on general relativity is easier is easier yes and what about what's the easiest way to reveal uh I think the the basic point is just this fact that there are all these different branches that there's this kind of map of how the branches work and that um I mean I think I think actually the recent things that we have about the double experiment are pretty good because you can actually see this you can see how the double slit you know phenomenon arises from just features of these graphs now you know having said that right there is a little bit of of slight of hand there because the the true story of the way that double slit thing works depends on a coordinatization of branchial space that for example in our internal team there is still a vigorous battle going on about how that works and it's it's what's becoming clear is I mean what's becoming clear is that it's mathematically really quite interesting I mean that is that there's a you know it involves essentially putting space fill in curves you basically have a thing which is naturally two-dimensional and you're sort of mapping it into one dimension and with a space filling curve and it's like why is it this space filling curve and not another space filling curve and that becomes a story about reman surfaces and things and it's quite elaborate and um but but the there's a a more little bit slight of hand way of doing it where it's you know it's surprisingly direct it's so a question that might be difficult to answer but uh for several levels of people could you give me advice on how we can learn more specifically there is people that are completely outside and just curious and are captivated by the beauty of hypergraphs actually uhhuh so people there just want to explore play around with this uh second level is people from say people like me who somehow got a PhD and computer science but are not physicists and but fundamentally the work you're doing is computational nature so it feels very accessible yes so what are what can a person like that do to learn enough physics or not to be able to uh one explore the beauty of it and two the the final level of contribute something right of a level of even publishable you know like strong interesting ideas at all those layers complete beginner yeah I see person and the Cs person that wants to publish right I mean I think that you know I've written a bunch of stuff uh bu called Jonathan gorod who's been a key person working on this project has also written a bunch of stuff um and some other people have started writing things too and he's a physicist physicist well he's I would say a mathematical physicist he pretty mathematically sophisticated he's he regularly out mathematized me yeah strong yeah strong mathematical physicist yeah I looked at some of the papers right but but so so I mean you know I wrote this kind of original announcement blog post about this project which people seem to have found uh I've been really happy actually that people um who uh you know people seem to have gred key points from that much deeper key points people seem to have gred than I thought they would grock um and that that's a kind of a Long blog post that explains some of the things we talked about like the hypergraph and the basic rules and uh I don't does it I forget doesn't have any quantum mechanics goes through quantum mechanics yes it does but we we know a little bit more since that blog post that probably clarifies but that blog post is does a pretty decent job um and you know talking about things like again something you didn't mention the fact that the uncertainty principle as a consequence of curvature in bronal space how much physics should a person know to be able to understand the beauty of this framework and to contribute something novel okay so I I think that those are different questions so I mean I think that the why does this work why does this make any sense um uh to really know that you have to know a fair amount of physics okay um and for example have a why does this work you're you're referring to the connection between this model and general relativity for example you have to understand something about General of there there's also a side of this where just as the pure mathematical framework is fascinating yeah yes if you throw the physics out then it's quite accessible to I mean you know I I wrote this sort of long technical introduction to the project which seems to have been very accessible to people who are you know who understand computation and and formal abstract ideas but are not specialists in physics or or other kinds of things I mean the thing with the physics part of it is you know it's there's both a way of thinking and a literally a mathematical formalism I mean it's like you know to know that we get the Einstein equations to know we get the ener of momentum tensor you kind of have to know what the energ of momentum tensor is and that's physics I mean that's kind of graduate level physics basically um and uh so so that you know making that final connection is requires some depth of physics knowledge I mean that's the unfortunate thing the difference between machine learning in physics in the 21st century is it uh really Out Of Reach of a year or two worth of study no you could get it in a year or two but you can't get it in a in a month right I mean so but it doesn't require necessarily like 15 years no it does not and and in fact a lot of what has happened with this project makes a lot of this stuff much more accessible there are things where it has been quite difficult to explain what's going on and it it requires much more you know having the concreteness of being able to do simulations knowing knowing that this thing that you might have thought was just an analogy is really actually what's going going on makes one feel much more secure about just sort of saying this is how this works um and I think it will be you know the I'm hoping the textbooks of the future the physics textbooks of the future there will be a certain compression there will be things that used to be very much more elaborate because for example even doing continuous mathematics versus this discret mathematics you know to know how things work in continuous mathematics you have to be talking about stuff and waving your hands about things whereas with discreet the discreet version it's just like here is a picture this is how it works and there's no oh did we get the limit right did this you know did this thing that is of you know uh zero you know measure zero object you know interact with this thing in the right way you don't have to have that whole discussion it's just like here's a picture you know this is what it does and you know you can then it takes more effort to say what does it do in the limit when the picture gets very big but you can do experiments to build up an intuition actually yes right and you can get sort of core intuition for what's going on now in terms of contributing to this the you know I would say that the study of the computational universe and how all these programs work in the computational universe there's just an unbelievable amount to do there and it is very close to the surface that is you know high school kids you can do experiments it's not um you know and you can discover things I mean you know we you can discover stuff about I don't know like this thing about expansion of bronal space that's an absolutely accessible thing to look at now now you know the main issue with doing these things is not there isn't a lot of technical depth difficulty there the actual doing of the experiments you know all the code is all on our website to do all these things the real thing is sort of the Judgment of what's the right experiment to do how do you interpret what you see that's the part that you know people will do amazing things with and that's the part that but but it isn't like you have to have done 10 years of of study to get to the point where you can do the experiments you D the cool thing you can do experiments day one basically it's that that that's the amazing thing about and you've actually put the tools out there it's beautiful it's mysterious uh there's still I would say maybe you can correct me it feels like there's a huge number of L hanging fruit oh on the mathematical side at least not the not the physics side perhaps no no there's look on the on the okay on the physics side we are we're definitely in harvesting mode you know of which which fruit the low hanging ones or the low hanging ones yeah right I mean basically here's the thing there's a certain list of you know here are the effects in quantum mechanics here are the effects in general activity it's just like industrial harvesting it's like can we get this one this one this one this one this one and and the thing that's really you know interesting and satisfying and it's like you know is one climbing the right Mountain does one have the right model the thing that's just amazing is you know we keep on like are we going to get this one one how hard is this one it's like oh you know it looks really hard it looks really hard oh actually we can get it um and uh and you're you're continually surprised I mean it seems like I've been following your progress It's kind of exciting all the in harvesting mode all the things you're picking up along the way right right no I mean it's it's the thing that is I keep on thinking it's going to be more difficult than it is now that's a you know that's a who knows what um I mean the one thing so the the the um the thing that's been was big thing that I think we're we're pretty close to I mean I can give you a little bit of the road map it's sort of interesting to see is like what are particles what are things like electrons how do they really work um are you close to get like what what's uh are you close to trying to understand like the atom the electrons neutrons protons this is this is the stack so the first thing we want to understand is uh the quantization of spin so particles they they kind of spin they have a certain Ang angular momentum that angular momentum even though the masses of particles are all over the place you know the electron has a mass of 511 M the but you know the proton is 938 M etc etc etc they're all kind of random numbers the the spins of all these particles are either integers or half integers and that's a fact that was discovered in the 1920s I guess um the U uh I think that we are close to understanding why spin is quantized um and that's a and it it appears to be a quite elaborate mathematical story about homotopic groups in twist space and all kinds of things but bottom line is that seems Within Reach and that's that's a big deal because that's a very core feature of understanding how particles work in quantum mechanics another core feature is this difference between particles that obey the Exclusion Principle and sort of stay apart that leads to the stability of matter and things like that and particles that love to get together and be in the same state things like photons that um and that's what leads to phenomena like lasers um where you can get sort of coherently everything in the same state that difference is the particles of integer spin or bons like to get together in the same state the particles of half integer spin of ferons like electrons that they tend to stay apart and um so the question is can we can we get that in our models and uh oh just the last few days I think we made um I mean I think the story of um I mean it's it's it's one of these things where we're really close it's is this connect to fans and bans you you talking so this was what happens is what seems to happen okay it's you know subject to revision next even next few days but what seems to be the case is that uh bons are associated with essentially merging in multi-way graphs and firion are associated with branching in multi-way graphs and that essentially the Exclusion Principle is the fact that in branchial space things have a certain extent in branchial space that in which things are being sort of forced apart in branchial space whereas the case of bans they get they they Clump together in branchial space and the real question is can we explain the relationship between that and these things called Spinners which are the representation of half integer spin particles that have this weird feature that usually when you go around 360° rotation you get back to where you started from but for a spinner you don't get back to where you started from it takes 720 of rotation to get back to where you started from and we are just it feels like we are we're just incredibly close to actually having that understanding how that works and it turns out it looks like my current speculation is that it's as simple as the uh directed hypergraphs versus undirected hypergraphs interesting uh the relationship between Spinners and vectors so which is just nice interesting yeah that would be interesting if these are all these kind of uh nice properties of this multiway graphs of of branching andjoin Spinners have been very mysterious and if that's what they turn out to be there's going to be an easy explanation directed vers undirected it's just and that's why there's only two different cases it's why are Spinners important in quantum mechanics can you just give a yeah so Spinners are important because they are um they're the representation of of for electrons which have half anra spin they are the the wave functions of electrons are spin Spinners just like the wave functions of photons are vectors the wave functions of electrons are Spinners and and they have this property that when you rotate by by 360° they come back to minus1 of themselves and take 720° to get back to the original value and and they are a consequence of of um uh in we usually think of of of rotation in space as being you know when you have this notion of rotation invariance and rotational invariance as we ordinarily experience it doesn't have the feature you know if you go through 360° you go back to where you started from but that's not true for electrons and so that's that's why understanding how that works is important yeah I've been playing with Mobius uh strip quite a bit lately just for fun and yes yes it adds some funk it has the same kind of funky properties yes right exactly you can have this the So-Cal belt trick which is this way of taking an extended object and you can see properties like SP with that kind of extended object that um yeah it would be very cool if there's it somehow connects to direcor versus undirected I think that's what it's going to be I think it's going to be as simple as that but we'll see I mean this is this is the thing that that you know this is the big sort of bizarre surprise is that you know because you know I I I learned physics as probably let's say let's say a fifth generation in the sense that you know if you go back to the 1920s and so on there were the people who were originating quantum mechanics and so on maybe it's a little less than that maybe I was like a a a third generation or something I don't know but but you know the people from whom I learned physics were the people who were you know have been students of the students of the the people who originated the the current understanding of physics and we're now at you know probably the seventh generation of physicists or something from the from the early days of 20th century physics and you know whenever a field gets that many generations deep it seems the foundations seem quite inaccessible and they seem you know it seems like you can't possibly understand that we've gone through you know seven academic generations and that's been you know that's been this thing that's been difficult to understand for for that long it just can't be that simple um and well in a sense maybe that Journey takes you to a to a simple explanation that was there all along as the whole right right right I mean you know and the thing for me personally the thing that's been quite interesting is you know I didn't expect this project to work in this way and I you know but I had this sort of weird piece of personal history that I used to be a physicist and I used to do all this stuff and I know you know the the standard Canon of physics I knew it very well and um you know but then I've been working on this kind of computational Paradigm for basically 40 years and uh the fact that you know I'm sort of now coming back to to you know trying to apply that in physics it kind of felt like that Journey was necessary was this uh when did you first try to play play with a hypergraph so I what happen yeah so so what I had was okay so this is again you know one one always feels dumb after the fact it's it's um it's obvious after the fact but but so back in the early 1990s I realized that using graphs as a sort of underlying thing underneath space and time was going to be a useful thing to do I figured out about multi-way systems um I figured out the things about general relativity I figured out by the end of the 1990s but I always felt there was a certain inelegance because I was using these graphs and there were certain constraints on these graphs that seemed like they were they were kind of awkward it was kind of like you can pick it's like you couldn't pick any rule it was like pick any number but the number has to be prime was kind of like you couldn't it was a kind of an awkward special constraint I had these trivalent graphs graphs with just three connections from every node okay so but but I discovered a bunch of stuff with that but I thought it was kind of inelegant and you know the other piece of sort of personal history is obviously I spent my life as a language computational language designer and so the story of computational language design is a story of how do you take all these random ideas in the world and kind of grind them down into something that is computationally as simple as possible and so you know I've been very interested in kind of simple computational Frameworks for representing things and have you know ridiculous amounts of experience in in trying to do that and actually all of those trajectories of your life kind of came together so you make it sound like you could have come up with uh everything you're working on now decades ago but in reality look two things slowed me down I mean one thing that slowed me down was I couldn't figure out how to make it elegant and and that turns out hypergraphs were the key to that and that I figured out but about less than two years ago now um and um the other I mean I I think so that was that was sort of a a key thing well okay so the real embarrassment of this project okay is that the final structure that we have that is the foundation for this project is basically a a kind of an idealized version a formalized version of the exact same structure that I've used to build computational languages for more than 40 years yeah but it took me but I didn't realize that and and you know and there yet may be other so we're focused on physics now but I mean that's what the new kind of science is about same kind of stuff and this in terms of mathematically um the beauty of it so so there could be entire other kind of objects they're useful for like we we're not talking about you know machine learning for example maybe there's other variants of the hypog graph that are very useful for reasoning well we'll see whether the multi-way graph for machine Learning System is interesting okay let's leave it at that that's conversation number three that's that's that's we're not going to go there right now but so one of the things you've mentioned is um the space of all possible rules that we kind of discussed a little bit uh that you know there could be I guess the set of possible rules is infinite right well so here's here's the big sort of one of the conundrums that that I'm kind of trying to deal with is let's say we think we found the rule for the universe and we say here it is you know write it down it's a little tiny thing and then we say gosh that's really weird why did we get that one right and then we're in this whole situation because let's say it's fairly simple how did we come up the winners getting one of the simple possible Universe rules why didn't we get what some incredibly complicated rule why do we get one of the simpler ones and and that's a thing which you know in the history of science you know the whole sort of story of kernus and so on was you know we used to think the Earth was the center of the universe but now we find out it's not and we're actually just and some you know random corner of some random Galaxy out in this big universe there's nothing special about us so if we get you know Universe number 3177 out of all the infinite number of possibilities how do we get something that small and simple right so I was very confused by this and it's like what are we going to say about this how are we going to explain this and I thought it was might be one of these things where you just you know you can get it to the threshold and then you find out its rule number such and such and you just have no idea why it's like that yeah okay so then I realized it's actually more bizarre than that okay so we talked about multi-way graphs we talked about this idea that you take these underlying transformation rules on these hypergraphs and you apply them wherever the rule can apply you apply it and that makes this whole multi-way graph of possibilities okay so let's go a little bit weirder let's say that at every place not only do you apply a particular rule in all possible ways it can apply but you apply all possible rules in all possible ways they can apply okay so you say that's just crazy that's way too complicated you're never going to be able to conclude anything okay however turns out oh that don't tell me there's some kind of invariance yeah yeah so so what happens is man that would be amazing right so so this thing that you get this this kind of Ral multi-way graph this multi-way graph that is a branching of rules as well as a branching of possible applications of rules this thing has causal invariance it's a it's an inevitable feature that it shows causal invariance and that means that you can take different reference frames different ways of slicing this thing and they will all in some sense be equivalent if you if you make the right translation they will be equivalent so okay so the the basic Point here is that that's true that would be beautiful it is true and it is beautiful so you you it's not just an intuition there is some no no no there's real mathematics behind this and it and it's it is it is okay so here's here's how it comes yeah that that would be that's amazing right so so by the way I mean the mathematics that's connected to is the mathematics of higher category Theory and groupoids and things like this which I've always been afraid of but now I'm I'm I'm finally wrapping my arms around it but um um it's also related to uh it also relates to computational complexity Theory um it's also deeply related to the P versus NP problem and other things like this again seems completely bizarre that these things are connected but here's why it's connected the this space of all possible okay so a touring machine very simple model of computation you know you just got a this tape where you write down you know ones and zeros or something on the tape and you have this this rule that says you know you you change the number you move the head of the on the tape Etc you have a definite rule for doing that a deterministic touring machine just does that deterministically given the configuration of the tape it will always do the same thing a non-deterministic touring machine can have different choices that it makes at every step yeah and so you know um you know this stuff you probably teach this stuff the um it um uh you know so a non-deterministic touring machine has the set of branching possibilities which is in fact one of these multi-way graphs and in fact if you say imagine the extremely non-deterministic touring machine the touring machine that can just do uh that takes any possible rule at each step that is this Ral multi-way graph the set of the set of trans the set of possible histories of that extreme non-deterministic tur machine is a ruo multi-way graph and you're uh what term you using ruo ruo it's a weird word yeah it's a weird word right multi-way graph okay so this so that I'm trying think of I'm trying to think of the space of rules uh so these are basic Transformations so in a turning machine it's like it says move left move you know if it's a one if it's a black Square under the head move left and right a green square that's a rule that's a very basic rule but I'm trying to see the rules on the hypergraphs how rich of the programs can they be or do they all ultimately just map into something simple yeah they will I mean hypergraphs that's another layer of complexity on this whole thing you can you can think about these in transformations of hypergraphs but touring machines are a little bit put touring machines okay right they're a little bit simpler so if you look at these extreme non-deterministic touring machines you're mapping out all the possible non-deterministic paths that the turing machine can follow yeah and and if you ask the question uh can you reach okay so so a deterministic turing machine follows a single path the non-deterministic turing machine fills out this whole uh sort of ball of possibilities and so then the P versus MP problem ends up being questions about and we haven't completely figured out all the details of this but it's basically has to do with questions about the the growth of that ball relative to what happens with individual paths and so on so essentially there's a geometrization of the P versus MP problem that comes out of this that's a sideshow okay the main the main event here is the statement that you can look at this multi-way graph where the branches correspond not just to different applications of a single rule but to different application to Applications of different rules okay and that then that when you say I'm going to be an observer embedded in that system and I'm going to try and make sense of what's going on in the system and to do that I essentially I'm picking a reference frame and that turns out to be uh well okay so the way this comes out essentially is the reference frame you pick is the rule that you infer is what's going on in the universe even though all possible rules are being run although all those possible rules are in a sense giving the same answer because of causal invariance MH but what you see will be could be completely different if you pick different reference frames you essentially have a different description language for describing the universe okay so how does what does this really mean in practice so imagine there's us we think about the universe in terms of space and time and we have various kinds of description models and so on now let's imagine the friendly aliens for example right how do they describe their Universe well you know our description of the universe probably is affected by the fact that you know we are about the size we are you know meter is tall so to speak we have brain processing speeds we about the speeds we have we're not the size of planets for example we the speed of light really would matter you know in our everyday life the speed of light doesn't really matter everything can be you know the fact that speed of light is finite is irrelevant it could as well be infinite we wouldn't wouldn't make any difference you know it affects the the Ping times on the internet that's about that's about the level of of um of how we notice the speed of light in our sort of everyday existence we don't really notice it um and so we have a way of describing the universe that's based on our sensory you know our senses our uh in these days also on the mathematics we've constructed and so on but the realization is it's not the only way to do it there will be completely completely utterly incoherent descriptions of the universe which correspond to different reference frames in this sort of Ral space in the Ral space that's fascinating so we're we have some kind of reference frame in this Ral space right and from that that's why we are attributing this rule to the universe so in other words when we say why is it this Rule and not another the answer is just you know Shine the Light back on us so to speak it's because of the reference frame that we've picked in our way of understanding what's happening in the sort of uh space of all possible rules and so on but also in the space from this reference frame because of the royal the the the invariance that simple that the rule on which the universe with which you can run the universe might as well be simple yes yes but okay so so here's another point so this is again these are a little bit mind twisting in some ways but but the the the um um okay another thing that's sort of we know from computation is this idea of computation universality the fact that given that we have a program that runs on one kind of computer we can as well you know we can convert it to run on any other kind of computer we can emulate one kind of computer with another so that might lead you to say well you think you have the rule for the universe but you might as well be running it on a touring machine because we know we can emulate any computational rule on any kind of machine and that's essentially the same thing that's being said here that is that what we're doing is we're saying um these different interpretations of physics correspond to essentially running physics on different underlying you know thinking about the physics as running in different with different underlying rules as if different underlying computers were running them and but because of computation universality or more accurately because of this principle of computational equivalence thing of mine there's that they are um these things are ultimately equivalent so the only thing that is the ultimate fact about the universe the ultimate fact that doesn't depend on any of these you know we don't have to talk about specific rules etc etc etc the ultimate fact is the universe is computational and it is the the things that happen in the universe are the kinds of computations that the principle of computational equivalence says should happen now that might sound like you're not really saying anything there but you are because you can you could in principle have a hypercomp computer that things that take an ordinary computer in infinite time to do the hypercom computer can just say oh I know the answer it's this immediately what this is saying is the universe is not a hyper Compu it's not simpler than a an ordinary touring machine type computer it's exactly like an ordinary touring machine type computer and so that's the that's in the end the sort of net net conclusion is that's the thing that is the sort of the hard immovable fact about the universe that's sort of the the fundamental principle of the universe is that it is computational and not hyper computational and not sort of for computational it is this level of computational ability and it's um it kind of has and that's sort of the the The Core Fact but now you know this this idea that you can have these different kind of uh Ral reference frames these different description languages for the universe it it makes me you know I I used to think okay you know imagine the aliens imagine the Extraterrestrial intelligence thing you know at least they experience the same physics right and now I've realized isn't true they could have a different roal frame that's that's fascinating they can end up with a a a a description of the universe that is utterly utterly incoherent with ours and and that's also interesting in terms of how we think about well intelligence the nature of intelligence and so on you know I'm I'm fond of the quote you know the weather has a mind of its own because these are you know these are sort of computationally that that system is computationally equivalent to the system that is our brains and so on and what's different is we don't have a way to understand you know what the weather is trying to do so to speak we have a story about what's happening in our brains we don't have a sort of connection to what's happening there so we actually it's funny last time we talked maybe over a year ago uh we talked about how it was more based on your work with a rival uh we talked about how would we communicate with alien intelligences can you maybe comment on how we might how the wol from physics project changed your view how we might be able to communicate with alien intelligence like if they showed up is it possible that because of our com comprehension of the physics of the world might be completely different we would just not be able to communicate at all here's here's the here's the thing you know intelligence is everywhere the fact this idea that there's this notion of oh there's going to be this amazing extraterrestrial intelligence and it's going to be this unique thing it's just not true it's the same thing you know I I think people will realize this about the time when people decide that artificial intelligences are kind of just natural things that are like human intelligences they'll realize that that extraterrestrial intelligences or intelligences associated with physical systems and so on it's all the same kind of thing ultimately computation it's all the same it's all just computation and the issue is can you are you sort of inside it are you are you thinking about it do you have sort of a story you're telling yourself about it and you know the weather could have a story it's telling itself about what it's doing we just it's utterly incoherent with the stories that we tell ourselves based on how our brains work I mean ultimately it must be a a question whether we can align exactly Aline with the kind of intelligence systematic way of doing it right so the question is in the space of all possible intelligences what's the how do you think about the distance between description languages for one intelligence versus another and needless to say I have thought about this and uh um you know I I don't I don't have a great answer yet but but I think that's a that's a thing where there will be things that can be said and there'll be things that where you can sort of start to characterize you know what is the translation distance between this you know version of the universe or this you know kind of set of computational rules in this other one in fact okay so this is a you know there's this idea of algorithmic information Theory there's this question of sort of what is the uh when you have some something what is the sort of shortest description you can make of it where that description could be saying run this program to get the thing right so I'm pretty sure that that the um uh that there will be a physicalization of the idea of GIC information and that okay this is again a little bit bizarre but so I mentioned that there's the speed of light maximum speed of information Transmission in physical space there's a maximum speed of information Transmission in branchial space which is a maximum entanglement speed there's a maximum speed of information Transmission in roual space which is has to do with a maximum speed of translation between different uh description languages and again I'm I'm not fully wrapped my brain around this one yeah that one just blows my mind to think about that but that starts getting closer to the yeah the kind of physicalization right it's a and it's also a physicalization of of algorithmic information and I think there's probably a connection between I mean there's probably a connection between the notion of energy and some of these things which again I I you know hadn't seen all this coming I i' I've always been a little bit resistant to the idea of connecting physical energy to things in in in computation Theory but I I think that's probably coming and that's what essentially at the core with the the physics project is that you're connecting information Theory with well physics yeah it's computation in computation with our physical Universe yeah right I mean the fact that our physical universe is is right that we can think of it as a computation and that we can have discussions like you know the theory of the physical universe is the same kind of a theory as the P versus MP problem and so on is is really uh you know I think that's really interesting and and the fact that well uh okay so this this kind of brings me to one one more thing that I have to in terms of this sort of unification of different ideas which is meta mathematics yeah let's talk about that you mentioned that earlier what the heck is M mathematics and uh okay so here's here's what here's okay so what is mathematics mathematics uh sort of at a a lowest level one thinks of mathematics as you have certain axioms you say you know you say things like x + y is the same as y + x that's an axom um about addition and then you say we got these axioms and we and and from these axioms we derive all these theorems that fill up the literature of mathematics the the the activity of mathematicians is to derive all these theorems actually the axm of mathematics are very small you can fit you know when I did my new kind of science book I fit all of the standard axm of mathematics on basically a page and a half um it's not much stuff it's like a very simple rule from which all of mathematics arises um the way it works though is a little different from the way things work in in sort of uh a computation because in mathematics what you're interested in is a proof and the proof says from here you can use from this expression for example you can use these axioms to get to this other expression so that proves these two things are equal okay so we can we can begin to see how this is going to work what what's going to what happen is there are paths in metam mathematical space so what happens is each um two different ways to look at it you can just look at it as mathematical expressions or you can look at it as mathematical statements postulates or something but either way you think of these things and they are connected uh by these axioms so in other words you have some fact you or you have some expression you apply this axum you get some other expression and in general given some expression there may be many possible different Expressions you can get you basically build up a multi-way graph and a proof is a path through the multi-way graph that goes from one thing to another thing it the path tells you how did you get from one thing to the other thing it's the it's the story of how you got from this to that the theorem is the thing at one end is equal to the thing at the other end the proof is the path you go down to get from one thing to the other you mentioned that G's incompetance theem is not natural it fits naturally there how hard is yeah so so what happens there is that the girdles theorem is basically saying that there are pods of infinite length that is that there's no upper bound if you know these two things you say I'm trying to get from here to here how long do I have to go you say well I've looked at all the paths of length 10 somebody says that's not good enough that path might be of length a billion and and you there's no up bound on how long that path is and that's that's what leads to the incompleteness theorem so I mean the the thing that is kind of an emerging idea is you can start asking what's the analog of Einstein's equations in metam mathematical space what's the analog of a black hole in metam mathematical space what's the whole so yeah it's fascinating to model all the mathematics in this well so so here's here's what it is this is mathematics in bulk so human mathematicians have made a few million theorems they published a few million theorems but imagine the infinite future of mathematics apply something to mathematics that mathematics likes to apply to other things take a limit what is the limit of the infinite future of mathematics what does it look like what is the Continuum limit of mathematics what is the as you just fill in more and more and more theorems what does it look like what does it do how does what kinds of conclusions can you make so for example one thing I've just been doing is taking uid so uclid very impressive he had 10 axioms he derived 465 theorems okay his book you know that was was the sort of defining book of mathematics for 2,000 years um so you can actually map out and I I I I actually did this 20 years ago but I've done it more seriously now you can map out the theorem dependency of those 465 theorems so from the axioms you grow this graph it's actually a multi-way graph of how all these theorems get proved from other theorems and so you can ask questions about you know well you can ask things like what's the hardest theorem in ukle the answer is the hardest theorem is that there are five plutonic solids that turns out to be the hardest theorem in ucle that's actually his his Last Theorem in all his books that's the final what's the hardness the the distance you have to travel yeah that's it's 33 Steps From the the longest path in the graph is 33 steps so that's the there there's a 33 step path you have to follow to go from the axioms according to ukids proofs to the statement there are five platonic solids so so okay so then then then the the question is in uh what does it mean if you have this map okay so in a sense this meta mathematical space is the infrastructural space of all possible theorems that you could prove in mathematics MH that's the geometry of meta mathematics there's also the geography of mathematics that is where did people choose to live right in space and that's what for example exploring the sort of empirical metam mathematics of ID is doing each individual like human mathematician you can embed them into that space I mean they they kind they they represent a path in the things they do maybe a set of paths right so like and a set of axioms that are chosen right so so for example here's an example of of a thing that I realized so one of the surprising things about well there two surprising facts about math one is that it's hard and the other is that it's doable okay so first question is why is math hard you know you've got these axioms they're very small why can't just solve every problem in math easily yeah it's just logic right yeah well logic happens to be a particular special case that does have certain Simplicity to it um but General mathematics even arithmetic already doesn't have the Simplicity that logic has so why is it hard because of computational irreducibility right right because what happens is to know what's true and this is this whole story about the path you have to follow and how long is the path and goal theorem is the statement there could be an in that the path is not a bounded length but the fact that the path is not always compressible to something tiny is a story of computational irreducibility so that's that's why math is hard now the next question is why is math doable because it might be the case that most things you care about don't have finite length paths most things you care about might be things where you get lost in the sea of computational irreducibility and worse undecidability that is there's just no finite length path that gets you there um you know why is mathematics doable you know girdle proved his incompleteness theorem in 1931 most working mathematicians don't really care about it they just go ahead and do mathematics even though it could be that the questions they're asking are undecidable it could have been that format's L theorem is undecidable it turned out it had a proof it's a long complicated proof the twin Prime conjecture might be undecidable the reman hypothesis might be undecidable these things might be the axioms of mathematics might not be strong enough to reach those statements it might be the case that depending on what axioms you choose you can either say that's true or that's not true so and and by the way from as Last Theorem there could be a shorter path absolutely yeah so that the notion of j6 in metam mathematical space is a notion of shortest proofs in metam mathematical space and that's a you know human mathematicians do not find shortest paths nor do automated theorem provs um but the fact and and by the way the I mean this stuff is so bizarrely connected I mean if you if you're into automated theorem proving there are these so-called critical pair Lamas and automated theorem proving those are precisely the branch pairs in our um that in multi-ray graphs let me just finish on the why mathematics is doable oh yes the second part so we know why it's hard why is it doable right why do we not just get lost in undecidability all the time yeah um so and and here's another fact is in doing computer experiments and doing experimental mathematics you do get lost in that way when you just say I'm picking a random integer equation how do I does it have a solution or not and you just pick it at random without any human sort of path getting there often it's really really hard it's really hard to answer those questions when you just pick them up random from the space of possibilities but what's what I think is happening is and that's a case where you just fell off into this ocean of sort of irreducibility and so on what's happening is human mathematics is a story of building a path you you started off you're you're always building out on this path where you are proving things you you you've got this proof trajectory and you're basically the human mathematics is the sort of the exploration of the world along this proof trajectory so to speak you're not you're not just you know uh parachuting In from from you know from from anywhere you're following you know Lewis and Clark or whatever you're actually you're actually going doing the PA and the fact that you are constrained to go along that path is the reason you don't end up with lot every so often you'll see a little piece of undecidability and you'll avoid that that part of the path but that's basically the story of why human mathematics is has seemed to be doable it's a story of exploring these paths that that are by their nature they have been constructed to be paths that can be followed and so you can follow them further now you know what why is this relevant to anything so okay so here's the the my my my belief the fact that human mathematics works that way is I think there's some sort of connections between the way that observers work in physics and the way that the axium systems of mathematics are set up to make mathematics be doable in that kind of way and so in other words in particular I think there is an analog of causal invariance which I think is um and this is again in sort of the upper reaches of mathematics and and stuff that um uh it's a thing there's this thing called homotopy type Theory which is an abstract it's came out of category Theory and it's sort of an abstraction of mathematics mathematics itself is an abstraction but it's an abstraction of the abstraction of mathematics and there is a thing called the univalence axium which is a sort of a a key axom in that set of ideas and I'm pretty sure the univance axium is equivalent to causal variance what was the term you use again uni univance is that something for somebody like me accessible um or is this there's a statement of it that's fairly accessible I mean the statement of it is um uh basically it says things which are equivalent can be considered to be identical in which but in which space yeah it's it's in in higher category okay in Category 3 okay so it's it's a it's a but I mean the thing just to give sketch of how that works so category theory is an attempt to idealize it's an attempt to sort of have a formal theory of mathematics that is at a sort of higher level than mathematics it's where where you just think think about these mathematical objects and these categories of objects and these these morphisms these connections between categories okay so it turns out the morphisms and categories the least weak categories are very much like the paths in our hypergraphs and things and it turns out again this is this is where it all gets gets crazy I mean it's it's the fact that these things are connected is just bizarre so category Theory uh the our causal graphs are like second order category Theory and it turns out you can take the limit of infinite order category Theory so just just give rough roughly the idea this is a this is a roughly explainable idea so a mathematical proof will be a path that says you can get from this thing to this other thing and here's the path you get from this thing to this other thing but in general there may be many paths many proofs that get you many different paths that all successfully go from this thing to this other thing okay now you can define a higher order proof which is a proof of the equivalence of those proofs mhm okay so you're saying there's a go path between those proofs essentially yes a path between the paths yeah okay and so you do that that's the sort of second order thing that path between the paths is essentially related to our causal graphs then take limit wow path between path between path between path the infinite limit that infinite limit turns out to be our Ral multi-way system yeah the Ral the the Ral multi-way system that's a fascinating thing both in the physics world and and as you're saying now that's that's I'm not sure I've loaded it in completely but well I'm not sure I have either and it may be one of these things where where you know in another another five years or something it's like this was obvious but I didn't see it no but the thing which is sort of interesting to me is that there's sort of an upper reach of of mathematics of the abstraction of mathematics um this thing there's this mathematician called grth and deque who's generally viewed as being sort of one of the most abstract sort of creator of the most abstract mathematics of 1970s is time frame um and one of the things that he constructed was this thing he called the infinity groupoid um and he has the sort of hypothesis about the inevitable appearance of geometry from essentially logic in the structure of this thing well it turns out this Ral multiway system is the infinity group void so it's a it's this limiting object and this is an this is an instance of that limiting object so what to me is I mean again I I've been always afraid of this kind of mathematics because it seemed incomprehensibly abstract to me um but what's what's what I'm sort of excited about with this is that that we've sort of concre ified the way that you can reach this kind of mathematics which makes it uh well both seem more relevant and also the fact that that you know I don't yet know exactly what mileage we're going to get from using the sort of the apparatus that's been built in those areas of mathematics to analyze what we're doing but the thing that's so both ways so use mathematics understand what you're doing and using what you're doing computationally to understand that right so so for example the the understand of uh meta mathematical space one of the reasons I really want to do that is because I want to understand quantum mechanics better and and that what you see you know we live that uh kind of the multi-way graph of mathematics because we actually know this is a theorem we've heard of this is another one we've heard of we can actually say these are actual things in the world that we relate to which we can't really do as as readily for the the physics case and so it's kind of a way to help my intuition it's also you know there are bizarre things like the what's the analog of Einstein's equations in metam mathematical space what's the analog of a black hole you know it turns out it looks like not completely sure yet but there's this notion of non-constructive proofs in mathematics and I think those relate to well actually the the they they relate to things and related to event Horizons um so the fact that you can take ideas from physics like event Horizons into the same kind of it's it's really so do you think there'll be do you think you might stumble upon some breakthrough ideas in theorem proving like for from the the other direction yeah yeah yeah no I mean what's really nice is that we are using so this this absolutely directly maps to theorem proving so paths and multi-way graphs that's what a theorem improver is trying to do but I also mean like like automated de yeah yeah yeah that that's what right so the finding of PODS the finding of shortest parts s or finding a paths at all is what automated theorem provs do and actually what what we've been doing so we've you know we've actually been using automated theorem proving both in the physics project to prove things and using that as a way to understand multi-way graphs and because what an automated theorem prover is doing is it's trying to find a path through a multi-way graph and its critical pair lemas are precisely little stubs of Branch pairs going off into branchial space and that's I mean it's really weird you know we have these visualizations in W language of our of of um proof graphs from our automative theorem proving system and they look reminiscent of well it's just bizarre because we made these up a few years ago and they have these little triangle things and they are they are we we didn't quite get it right we didn't quite get the analogy perfectly right but it's very close you know just to say in terms of the how these things are connected so there's another bizarre connection that I I have to mention because because um um which is uh which again we don't fully know but it's a connection to uh uh something else you might not have thought was in the slightest bit connected which is distributed blockchain like things now you might figure out that that's you you would figure out that that's connected because because it's a story of distributed computing yeah and the issue you know with a blockchain you're saying there's going to be this one Ledger that that globally says this is what happened in the world but that's a bad deal if you've got all the different transactions that are happening and you know this transaction in country a doesn't have to be reconciled with a transaction in country B at least not for a while and that story is just like what happens when our causal graphs that whole reconciliation thing is just like what happens with light cones and all that's where the cause in variance comes into play I mean that that's you know most of your conversations are about physics but it's kind of funny that the this probably and possibly might have even bigger impact and uh revolutionary ideas in totally other disciplines right well see see yeah right so the question is why is that happening right and and the reason it's happening I I've thought about this obviously because I like to think about these meta questions of you know what's happening is this model that we have is an incredibly minimal model yeah and once you have an incredibly minimal model and this happened with cellular autometer as well cellular autometer inedibly minimal model and so it's inevitable that it gets you sort of an upstream thing that gets used in lots of different places and it's like you know the fact that it gets used you know cellular autometer as sort of a minimal model of let's say road traffic flow or something and they're also a minimal model of something in you know chemistry and they're also a minimal model of something in in epidemiology right it's because they're such a simple model that they can that they use apply to all these different things similarly this model that we have with the physics project is a is another it's a cellular autometer are a minimal model of parallel of of basically of parallel computation where you've defined space and time these models are minimal models where you have not defined space and time and they have been very hard to understand in the past but the I think the perhaps the most important breakthrough there is the realization that these are models of physics and therefore that you can use everything that's been developed in physics to get intuition about how things like that work and that's why you can potentially use ideas from physics to get intuition about how to do parallel Computing and because the underlying model is the same and but but we have all of this achievement in physics I mean you know you might say oh you've come up with the fundamental Theory of physics that throws out what people have done in physics before well it doesn't but also the real power is to use what's been done before in physics to apply it in these other places yes and absolutely this kind of brings up I know you probably don't particularly love commenting on the work of others but let me let me bring up a couple personalities just because it's fun people are curious about it so there's uh uh Sabine Hassen Felder I don't know if you're familiar with her she uh she wrote this book uh that I need to read but it Bas I forget what the title is but it's uh Beauty leads us astray in physics is a subtitle something like that which so much about what we're talking about now like the simplification is uh to us humans seems to be beautiful like there's a certain intuition with physicists with people that A Simple Theory like this reducibility pockets of reducibility is the ultimate goal and I think what she tries to argue is uh no we just need to come up with theories that are just really good at predicting physical phenomena it's okay to have a bunch of uh disperate theories as as opposed to trying to chase this beautiful Theory of Everything Is the ultimate beautiful Theory uh a simple one you know it's always what's your response to that well so what you're quoting so I don't know the Sabine hassenfeld is you know exactly what she said but I meting the I'm quoting the title of a book okay let me let me let me respond to what you were describing which may or may not have nothing to do with what you know what Sabin Hassen Felder says or thinks sorry San right sorry for misquoting um but I mean the the question is you know does is beauty a guide to whether something is correct that's right which is kind of also the story of aam's Razer you know if you've got a bunch of different explanations of things you know is the thing that is the simplest explanation likely to be the correct explanation and there are situations where that's true and there are situations where it isn't true sometimes in human systems it is true because people have kind of you know in evolutionary systems sometimes it's true because it's sort of been kicked to the point where it's minimized um but uh you know in physics does Arkham's Razer work you know is there a simple quotes beautiful explanation for things or is it a big mess um you know we don't intrinsically no you know I think that the I wouldn't before I worked on the project in recent times I would have said we do not know how complicated the rule for the universe will be and and I would have said you know the one thing we know which is a fundamental fact about science that's the thing that makes science possible is that there is order in the universe I mean you know early theologians would have used that as an argument for the existence of God because it's like why is there order in the universe why doesn't every single particle in the universe just do its own thing yeah um you know something must be making there be order in the universe we you know in in the sort of early theology point of view that's you know the role of God is to do that so to speak in our uh you know we might say it's the role of a formal Theory to do that and then the question is but how simple should that theory be and should that theory be one that that you know where I think the point is if it's simple it's almost inevitably somewhat beautiful in the sense that because all the stuff that we see has to fit into this little tiny Theory and the way it does that has to be you know it it depends on your notion of beauty but I mean in for me the the sort of the surprising con connectivity of it is at least in my aesthetic that's something that uh respond to my aesthetic but the question is uh I mean you're you you're a fascinating person in the sense that you're at once talking about computational the fundamental computational reducibility of the universe and and the other hand trying to come up with a Theory of Everything which simply describes the the the simple origins of that computational reducibility right I mean both of those things are kind of it's paralyzing to think that we can't make any sense of the universe in the general case but in it's hopeful to think like one we can think of a rule and uh that generates this whole complexity and two we can find uh pockets of uh reducibility that are powerful for our everyday life to do different kinds of predictions I suppose sine would wants to find focus on the finding of small pockets of reducibility versus the uh Theory of Everything You know it's a funny thing because because you know a bunch of people have started working on this this you know physics project people who are you know physicists basically um and it is really a fascinating sociological phenomenon because what you know when I was working on this before and the 1990s you know wrote it up put it it's 100 pages of this 1200 page book that I wrote new kind of science it's you know 100 pages of that is about physics right I I saw it at in that at that time not as a pinnacle achievement but rather as a use case so to speak I mean my main point was this new kind of Science and it's like you can apply it to biology you can apply it to you know other kinds of physics you can apply it to fundamental physics it's just it's just an application so to speak it's not the core thing but um but then you know one of the things was interesting with that with that book was you know book comes out lots of people think it's pretty interesting and lots of people start using what it has in different kinds of fields the one field where there was sort of a a heavy pitchforking was from my friends the fundamental physics people yeah which was it's like no this can't possibly be right and you know it's like you know if what you're doing is right it'll overturn 50 years of what we've been doing and it's like no it won't was what I was saying and it's like um but uh you know for a while when I started you know I I was going to go on back in 2002 well 2004 actually I was going to go on working on this project and I actually stopped partly because it's like why am I you know this is like I've been in business a long time right I'm I'm building a product for a target market that doesn't want the product and it's like why work yeah yeah why why work against the swim against the current or whatever but but you see what's happened which is sort of interesting is is that so A couple of things happened and it was it was like uh you know it was like I I I don't want to do this project because I can do so many other things which I'm really interested in where you know people say great thanks for those tools thanks for those ideas Etc whereas you know if you're dealing with kind of a a uh you know sort of a structure where people are saying no no we don't want this new stuff we don't need any new stuff we're really fine with what what we there's like literally like I don't know millions of people who are thankful for wolf from alpha a bunch of people wrote to me how thankful they are they are a different crowd than uh the theoretical physics Community perhaps yeah well right but you know the theoretical physics Community pretty much uniformally uses uh W from language and Mathematica right and so it's it's kind of like like um you know and that that's but the thing is what happens you know this is what happens mature fields do not you know it's like we're doing what we're doing we have the methods that we have and we're we're just fine here now what's happened in the last 18 years or so I think there's a couple of things have happened first of all the the hope that you know String Theory or whatever would would deliver the fundamental Theory of physics that hope has disappeared that the another thing that's happened is the the sort of the interest in computation around physics has been greatly enhanced by the whole Quantum information Quantum Computing story people you know the idea there might be something sort of computational uh related to physics is somehow somehow growing and I think you know it's it's sort of interesting I mean right now if we say you know it's like if you're like who else is trying to come up with the fundamental Theory of physics it's like there aren't professional no professional physic no professional physicists what are your uh I mean you've talked with him but just as a matter of personalities CU it's a beautiful story what are your thoughts about Eric Weinstein's work I you know I I think his his um I mean he did a PhD thesis in mathematical physics at Harvard mathematical physicist and and you know it's it seems like it's kind of you know it's in that framework and it's kind of like I'm not sure how much further it's got than his PhD thesis which was 20 years ago or something and I think that you know the the you know it's a fairly specific piece of mathematical physics that's quite nice and um what trajectory do you hope it takes I mean well I think in his particular case I mean from what I understand which is not everything at all but you know I think I know the rough Tradition at least he's operating in is sort of theory gauge theories gauge theories yeah local gauge and variance and so on okay we are very close to understanding how local gauge and variance Works in our models and it's very beautiful and it's very um and you know does some of the mathematical structure that he's enthusiastic about fit quite possibly yes so there might be a possibility of trying to understand how those things fit how gauge Theory fits well the question is you know so there are a couple of things one might try to get in the world so for example it's like can we get three dimensions of space we haven't managed to get that yet gauge Theory the standard model of particle physics says that it's su3 cross su2 cross U1 those are the designations of these um Le groups um it doesn't but but anyway so those are those are sort of representations of symmetries of the theory and um so you know it is conceivable that it is generically true okay so all those are subgroups of a group called E8 which is a weird exceptional Le group okay it is conceivable I don't know whether it's the case that that will be generic in these models that it will be generic that the gaug and variance of the model has this property just as things like general relativity which corresponds to thing called U general covariance which is another GA like invariance it could conceivably be the case that the kind of local gauge invariance that we see in particle physics is somehow generic and and that would be a you know the thing that's that's really cool I think you know sociologically although this hasn't really hit yet is that all of these different things all these different things people have been working on in these in some cases is quite abstruse areas of mathematical physics an awful lot of them seem to tie into what we're doing and you know it might not be that way yeah absolutely that's a beautiful thing in the theory I mean but the reason I so the reason Eric Weinstein is important is to the point that you mentioned before which is it's strange that The Theory of Everything Is Not at the core of uh the passion the dream the focus the funding of the physics community it's too hard it's too hard and people gave up I mean basically what happened is ancient Greece people thought we're nearly there you know the world is made of platonic solids it's you know water is a tetrahedron or something yes we're almost there okay long period of time where people were like no we don't know how it works you know time of Newton uh you know we're almost there everything is gravitation you know time of Faraday and Maxwell we almost there everything is Fields everything is The Ether you know then the whole time we're making big progress though oh yes absolutely but the fundamental Theory of physics is almost a footnote because it's like it's the machine code it's like we're operating in the high level languages yeah um you know that's what we really care about that's what's relevant for our everyday physics you talked about different centuries and the 21st century will be uh everything is computation yes if that takes us all the way we don't know but it might take us pretty far yes right that's right and but I think the point is that it's like you know if you're doing biology you might say how can you not be really interested in the origin of life and the definition of life well it's irrelevant you know you're studying the properties of some virus it doesn't matter you know where you know you're you're operating at some much higher level and it's the same what what's happened with physics is I was sort of surprised actually I was sort of mapping out this history of of people's efforts to understand the fundamental Theory of physics and it's remarkable how little has been done on this question and it's you know because you know there have been times when there's been bursts of enthusiasm and we're almost there and and then it decays and and people just say oh it's too hard but it's not relevant anyway and I think that the um the thing that um you know so so the question of of you know one question is why does anybody why should anybody care right why should anybody care what the fundamental Theory of physics is I think it's intellectually interesting but what will be the sort of what will be the impact of this what I mean this is the key question what do you think will happen if we figure out the fundamental Theory of physics right outside of the intellectual curiosity of us this my best guess okay so if you look at the history of science I think a very interesting analogy is cernus okay so what did cernus do there had been this toic system for working out the motion of planets it did pretty well it used epicycles etc etc etc it had all this computational ways of working out where planets will be when we work out where planets are today we're basically using epicycles but cernus had this different way of formulating things in which he said you know and the Earth is going around the Sun and that had a consequence the consequence was you can use this mathematical Theory to conclude something which is absolutely not what we can tell from common sense right so it's like trust the mathematics trust the science okay now fast forward 400 years and um you know and now we're in this pandemic and it's kind of like everybody thinks the science will figure out everything it's like from the science we can just figure out what to do we can figure out everything that was before cernus nobody would have thought if the science says something that doesn't agree with our everyday experience where we just have to you know compute the science and then figure out what to do people say that's completely crazy and so your sense is once we figure out the framework of computation that can basically do any understand the the fabric of reality will be able to derive totally counterintuitive things no the the the point I think is the following that that right now you know I talk about computational irreducibility people you know I was was very proud that I managed to get the term computational irreducibility into the Congressional record last year um that's right that's a whole another topic we could talk about different different topic different different topic but but um um in any case you know but so computational reducibility is one of these sort of Concepts that I think is important in understanding lots of things in the world but the question is it's only important if you believe the world is fundamentally computational right and but if you if you know the fundamental Theory of physics and it's fundamentally computational then you've rooted the whole thing that is you know the world is computational and while you can discuss whether you know uh it's not the case that people say well you have this whole computational reducibility all these features of computation we don't care about those because after all the world isn't computational you might say but if you know you know Bas space based thing physics is computational then you know that that stuff is you know that's kind of the grounding for that stuff just as in a sense cernus was the grounding for the idea that you could figure out something with math science that was not what you would intuitively think from your senses so now we've got to this point where for example we say you know once we have the idea that computation is the foundational thing that explains our whole universe then we have to say well what does it mean for other things like it means there's computational irreducibility that means science is limited in certain ways that means this that means that but the fact that we have that grounding means that you know and I think for example for kernus for instance the implications of his work on the sort of mathematics of astronomy were cool but they involved a very small number of people the implications of his work for sort of the philosophy of how you think about things were vast and involved you know everybody more or less but do you think so that's actually the way scientists and people see the world around us so it has a huge impact in that sense do you think it might have an impact more directly to engineering derivations from physics like propulsion systems our ability to colonize the world like for example okay this is like sci-fi but if you if you understand the computational nature say of uh of the different forces of physics you know there's there's a notion of being able to you know warp gravity things like this like can we make warp drive warp drive yeah so like would we be able to will it will uh you know will like Elon Musk start paying attention like it's awfully costly to launch these Rockets do you think we'll be able to yeah create warp drive and uh you know I I I set myself some homework I agreed to give a talk at some NASA Workshop in a few weeks about faster than light travel so I I haven't figured it out yet but but no but you got two weeks yeah right but do you think that kind of understanding of fundamental Theory of physics can lead to those engineering breakthroughs okay I think it's far away but I'm not certain I mean and you know this is the thing that that um I set myself an exercise When Gravity waves gravitational waves were discovered right I set myself the exercise of what would black hole technology look like in other words right now you know black holes are far away they're you know how on Earth can we do things with them but just imagine that we could get you know pet black holes right in our backyard you know what kind of Technology could we build with them I I got a certain distance not that far but I think in in um you know so there are ideas you know I have this one of the weirder ideas is the things I'm calling SpaceTime tunnels which are higher dimensional pieces of the of of SpaceTime where basically you can you know in in our three-dimensional space there might be a five-dimensional you know uh region which actually will appear as a white hole at one end and a black hole at the other end you know who knows whether they exist and then the questions another one okay this is another crazy one is the thing that I'm calling a vacuum cleaner okay so so so I I I mentioned that you know there's all this activity in the universe which is meant Ming the structure of space yes and that leads to a certain uh energy density effectively in space and so the question in fact dark energy is a story of essentially negative mass produced by uh the absence of energy you thought would be there so to speak and we don't know exactly how it works in in our either our model or the physical universe but this notion of a vacuum cleaner is a thing where you know you have all these things that maintaining the structure of space but what if you could clean out some of that stuff that's maintaining the structure of space and make a simpler vacuum somewhere yeah you know what would that do a totally different kind of vacuum right and that that would lead to negative energy density which would need to so gravity is is usually a purely attractive Force but negative Mass would lead to rep repulsive gravity um and uh lead to all kinds of weird things now can it be done in our universe um you know my immediate thought is no but but you know the fact is that okay so so here once you understand the fact because you're saying like at this level abstraction can we reach to the lower levels and mess with it uh once you understand the levels I think you can start and I'm I'm you know I have to say that that this reminds me of people telling one years ago that you know you'll never transmit data over a copper wire at more than a th you know a th000 board or something right and and this is why did that not happen you know why why did why do we have this much much faster data transmission because we've understood many more of the details of what's actually going on and and it's the same exact story here and it it's the same you know I think that this as I say I think one of the features of sort of one of the things about our time that will seem incredibly naive in the future is the belief that you know things like heat is just random motional molecules that that that it's just just throw up your hands it's just random we can't say about it that will seem naive yeah the at the heat depth of the universe those particles would be laughing at us humans thinking yes right that life is not civilization um you know humans used to think they're special with their little brains well right but but also but but and they used to think that this would just be random and uninteresting but that's but so so this question about whether you can you know mess with the underlying structure and how you find a way to mess with the underlying structure that's a you know I have to say you know my immediate thing is boy that seems really hard but then and and you know possibly computational irreducibility will bite you but then there's always some path of computational reducibility and that path of computational reducibility is the engineering invention exact that has to be made those little pockets can have huge engineering impact right and and I think that that's right and I mean we live in you know we make use of so many of those pockets and the fact is you know I I um uh you know this this is yes it's it's a you know it's one of these things where where you know I am a person who likes to figure out ideas and so on and the sort of tests of my level of imagination so to speak and so a couple of places where there's sort of serious humility in terms of my level of imagination one is this thing about different reference frames for understanding the universe where like imagine the physics of the aliens what will it be like like and I'm like that's really hard I don't know you know and and I mean once you have the framework in place you can at least reason about the things you don't know or maybe can't know or like it's too hard for for you to know but then the the mathematics can that's exactly it allow you to reach beyond what you can uh reason about right well so so I'm you know I'm I'm I'm trying to not have you know if you think back to Alan Turing for example and you know when he invented Turing machines you know and and imagining what computers would end up doing so to speak yeah um you know and very difficult it's difficult right and it's it's I mean made a few reasonable predictions but most of it he couldn't predict possibly by the time by 1950 he was making reasonable predictions about something but not the 30s yeah right not not not in the not when he first you know conceptualized you know and he conceptualized Universal Computing for a very specific mathematical reason that wasn't um uh wasn't as general but but yes it's a it's a good sort of exercise and humility to realize that that it's kind of like it's it's really hard to figure these things out the engineering of of um the universe if we know how the universe works how can we engineer it that's such a beautiful Vision that's such a beautiful by the way I have to mention one more which is the the ultimate question of of from physics is okay so we have this abstract model of the universe why does the universe exist at all right so you know we might say there there is a a formal model that if you run this model you get the universe or the model gives you you know a model of the universe right you you you you run this mathematical thing and the mathematics unfolds in the way that corresponds to the universe but the question is why was that actualized why does the actual Universe actually exist and um so this is this is another one of these humility and and um is like can you figure this out I have a guess okay about the answer to that and um my guess is somewhat unsatisfying but my guess is that it's a little bit similar to girdle second incompleteness theorem which is the statement that from within as an axiomatic Theory like P arithmetic you cannot from within that theory prove the consistency of the theory so my guess is that for entities within the universe there is no finite determination that can be made of the the statement the universe exists is essentially undecidable to any entity that is embedded in the universe within that Universe how does that make you feel is that is that does that put you at peace that it's impossible or is it really ultimately frustrating well I think it just says that it's not a kind of question that you know it's there are things that it is reasonable I mean there's kinds of you know you can talk about hypercomputation as well you can say imagine there was a hypercom computer here's what it would do so okay great it would be lovely to have a hypercom computer but unfortunately we can't make it in the universe like it would be lovely to answer this but unfortunately we can't do it in the universe um and you know this is all we have so to speak um and I think it it's it's really just a a statement it's sort of in the end it'll be a a kind of a logical logically inevitable statement I think I think it will be something where it is as you understand what it means to have what it means to have a sort of predicate of existence and what it means to have these kinds of things it will sort of be inevitable that this has to be the case that from within that Universe you can't establish the reason for its existence so to speak you can't prove that it exists and so on and nevertheless because of computation or reducibility the future is uh ultimately not predictable full of mystery and that's what makes life worth living right I mean right and you know it's funny for me because as a just a pure sort of human being doing what I do it's you know I'm I'm uh you know I like I'm interested in people I like sort of the you know the whole Human Experience so to speak and yet it's a little bit weird when I'm thinking you know it's all hypergraphs down there and it's all just uh hypergraphs all the way down right like turtles all the way down right and and and it's kind of you know it's to me it is a funny thing because every so often I get this you know as I'm thinking about I think we've really gotten you know we've really figured out kind of the essence of how physics works and I'm like thinking to myself you know here's this physical thing and I'm like you know this feels like a very definite thing how can it be the case that this is just some Ral reference frame of you know this infinite creature that that is uh so abstract and so on and I kind of it is a it's a it's a funny sort of feeling that that you know we are we're sort of uh um it's like it's in the end it's just sort of um be happy we're just humans type thing and and it's it's kind of like but but we're making we make things as it's not like we're just a tiny Speck we are in a sense the we are more important by virtue of the fact that in a sense it's not like there's there is no ultimate you know it's like we're important because because you know we're here so to speak and we're not it's not like there's a thing where we're saying um you know we are just but one sort of intelligence out of all these other intelligences and so you know ultimately there'll be the Super intelligence which is all of these put together and they'll be very different from us no it's actually going to be equivalent to us and the thing that makes us sort of special is just the details of us so to speak it's not something where we can say oh there's this other thing you know just you think humans are cool just wait until you've seen this you know it's going to be much more impressive well no it's all going to be kind of computationally equivalent and the thing that you know it's not going to be oh this thing is is amazingly much more impressive and amazingly much more meaningful let's say no we're it I mean that's that's that that's the um and and the symbolism of this particular moment so this has been one of the one of the favorite conversations I've ever had Stephen it's a huge honor to talk to you to talk about a topic like this for four plus hours on the fundamental Theory of physics and yet we're just two finite descendants of Apes that have to end this conversation because Darkness have come upon us right and and we're going to get bitten by mosquitoes and all kinds of terrible the symbolism of that we're talking about the most basic fabric of reality and having to end because of the fact that things end um it's tragic and beautiful Stephen thank you so much huge honor I can't wait to see what you do in the next couple of days and next week month we're all watching with excitement thank you so much thanks thanks for listening to this conversation with Stephen wlr and thank you to our sponsors Simply Safe Sun basket and masterclass please check out our sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on YouTube review it with five stars and apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Friedman and now let me leave you with some words from Richard fan physics isn't the most important thing love is thank you for listening and hope to see you next time |
Manolis Kellis: Origin of Life, Humans, Ideas, Suffering, and Happiness | Lex Fridman Podcast #123 | the following is a conversation with manolis kellis his second time on the podcast he's a professor at mit and head of the mit computational biology group he's one of the most brilliant productive and kind people i've had the fortune of talking to a lot of my colleagues at mit and former mit faculty and students wrote to me after our first conversation with some version of minos is awesome isn't he i'm glad you guys are not friends i am too and i'm happy that he makes time in his insanely busy schedule to sit down and have a chat with me quick summary of the sponsors public goods magic spoon and expressvpn please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that i just got back from talking to joe rogan on his podcast my fifth time on there i also got a chance to record a separate conversation with joe on this podcast we talked on both quite a bit about his journey and his advice for mine one of the things that i think made his show special is that he just had fun and made choices that didn't get in the way of him having fun and loving life i'm learning to do just that it's tough since i'm naturally full of self-doubt and anxiety but i'm learning to let go and have fun even if my monotone robotic voice sometimes sounds otherwise for joe that involved talking to his friends comedians especially ones that brought out the best in him duncan trussell and the five-hour first episode on spotify comes to mind is an example of that duncan has been a guest probably close to if not more than 50 times on joe's podcast my hope with amazing people like manolas is to find my duncan trussell my joey diaz and yes even my eddie bravo obviously joe and i are very different people but ultimately both love life when we can interact often with people we love and who inspire us make us smile make us think and make us have fun when we get behind the mic of a podcast whether anyone is listening or not if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter alex friedman i also this time put a link in the description to a survey for this podcast on how i can improve and also an option if you like i don't know why you would like to but if you like to join an inner circle of people that help guide the direction of this podcast via email or occasional video chats if you have a few minutes please fill it out as usual i'll do a few minutes of ads now and no ads in the middle i try to make these interesting but i give you time stamps so you can skip but still please do check out the sponsors by clicking the links in the description it's the best way honestly to support this podcast this show is sponsored by public goods an online store for basic health and household stuff their products have a minimalist black and white design that i find to be just clean elegant and beautiful it goes nicely at least i think so with the design of crew dragon and the recent spacex nasa mission that sent two humans into space to me very few things are as inspiring as us humans reaching out into the unknown the harsh challenges of space colonizing mars may not have obvious near-term benefits but i believe it will challenge our scientists and our engineers to create technologies whose impact will be immeasurable for us humans here on earth or those of us who choose to stay here on earth personally i'm kind of a long time big fan of this planet anyway visit publicgoods.com lex and use codelex at checkout to get 15 bucks off your first order this episode is also supported by magic spoon low carb keto friendly cereal you might have heard on other videos that i eat keto mostly these days so magic spoon is a delicious healthy treat on a hard workout day that fits into that crazy diet also they're a sponsor of episode 100 with my dad and got my dad to buy this cereal and he now loves it honestly just loves it it's kind of funny actually the deep heartfelt nature of that conversation and the silliness of the cereal captures my dad perfectly much of the hardship in his life he dealt with using wit and humor his favorite flavor happens to be coco mine is too he hasn't bought the a sleep mattress yet though my mom wants to but he's all about this magic spoon cereal i think it's his actually favorite sponsor of this podcast probably because they chose to sponsor the episode he's on anyway click the magicspoon.com lex link in the description and use code lex at checkout for free shipping to let them know i sent you and also indirectly to make my dad happy this show is also sponsored by expressvpn get it at expressvpn.com lexpod they gave me a suggested opening line of using the internet without expressvpn is like going to the bathroom and not closing the door this is like gpt-3 suggesting to me how to be more human-like and i'll honestly take all the help i can get by way of life advice let me tell you that you need a vpn to protect you from russians like me in fact this podcast is a kind of hack of your biological network where i use my monotone low energy voice to convince you to buy a kind of expensive cereal as a way to influence the stability of the us economy i use expressvpn on both windows and linux to protect myself if i ever do shady things on the internet which of course i never do and never will so secure your online activity by going to expressvpn.com slackspod to get an extra three months free and to support this podcast and now here's my conversation with manolas kalas what is beautiful about the human epigenome don't get me started so first of all as an engineering feat the human epigenome manages the most compact the most incredible compaction you could imagine so every single one of your cells contains two meters worth of dna and this is compacted in a radius which is one thousandth of a millimeter that's six orders of magnitude to give you a sense of scale it's as if a string as tall as the burj al khalifa which is about a kilometer tall was compacted into a tiny little ball the size of a millimeter and if you put it all together if you stretch the trillions of cells that we have we have about 30 trillion cells in your body if you stretch the dna the 2 meters worth of dna in every one of your trillion cells you would basically reach all the way to jupiter a hundred times yeah it's all curled up in there it's 30 trillion cells 30 trillion human body every one of them two meters worth of dna so all of that is compacted through the epigenome the epigenome basically has the ability to compact this massive amount of dna from here to jupiter 10 times into one human body into just the nuclei of one human body and the vast majority of human bodies not even these nuclei and that's sort of the structural part so that's the boring part that's the structural part the functional part is way more interesting so functionally what the human epigenome allows you to do is basically control the activity patterns of thousands of genes so 20 000 genes in your human body every one of your cells only needs a few thousand of those but a different few thousand of those and the way that your cells remember what their identity is is basically driven by the epigenome so the epidural is both structural in sort of making this dramatic compaction and it's also functional in being able to actually control the activity patterns of all your cells now can we draw a definition distinction between the genome and the epigenome again being greek epi means on top of so the genome is the dna and the epigenome is anything on top of the dna and there's you know three types of things on top of the dna the first is chemical modifications on the dna itself so we like to think of four bases of the dna acgt c has a methyl form which is sometimes referred to as the fifth base so methylc takes a different meaning so in the same way that you have annotations in a orchestra score that basically say whether you should play something softly or loudly or space it out or you know interpret basically the score the human epigenome allows you to modify that primary score so a modified c basically says play this one softly it's basically a sign of repression in a gene regulatory region i love how you're talking about the function that emerges from the epigenome as a musical score it is in many ways and uh every single cell plays a different part of that score it's like having all of human knowledge in 23 volumes like 23 giant books which are your chromosomes and every single cell has a different profession a different role some cells play the piano and they're looking at chapter seven from chromosome 23 and chapter four from chromosome two and so forth and each of those uh pieces are all encoding in the same dna but what the epigenome allows you to do is effectively conduct the orchestra and sort of coordinate the pieces so that every instrument plays only the things that it needs to play one thing that kind of blows my mind maybe you can tell me your thoughts about it is the the way evolution works with natural selection is uh based on the final sort of the entirety of the orchestra musical performance right and then but there's these incredibly rich structural things like each one of them doing their own little job that somehow work together like the evolution selects based on the final result and yet all the individual pieces are doing like infinitely minuscule specific things how the heck does that work right it's a very good insight and you can even go beyond that and basically say evolution doesn't select at the level of an organism it actually selects at the level of whole environments whole ecosystems so let me break this down so you basically have at the very bottom every single nucleotide being selected but then that nucleotides function is selected at the level of you know each gene and every not even its gene each gene regulatory control element and then those control elements are basically converging onto the function of the gene and many genes are converging onto the function of one cell and many cells are converging into the function of one tissue or organ and all of these organs are converging onto the level of an organism but now that organism is not in isolation so if you basically think about why is altruism for example a thing why are people being nice to each other it was probably selected and it was probably selected because those species that were just nasty to each other didn't survive as a species and now if you think about um symbiosis of you know there's plants for example that love co2 and there's humans that love o2 and we're sort of you know trading different types of gases to each other if you look at ecosystems where one organism which is really nasty that organism actually died because everyone they were being nasty to was killed off and then that kind of you know universe of life is gone so basically what emerges is selection at so many different layers of benefit including you know all of these nucleotides within a body interacting for the emergent functions at the body level yeah i wonder i wonder if it's possible to break it down into levels that's selection even beyond humans like you said environment but there's environments at all different levels too right at the minuscule at the organ level the tissue level like you said maybe at the microscopic level it would be fascinating if like there's a kind of selection going on at like both the quantum level and like the the galaxy level yeah yeah right yeah so so all the different forms yeah let's again sort of break down these different layers so basically if you think about the environment in which a gene operates that gene of course the first definition of environment that we think of is pollution or sunlight or heat or cold and so forth that's the external environment but every gene also operates at the level of the internal cellular environment that it's in if i take a gene from say an african individual and i put it in a european context will it perform the same way probably not because there's a cellular context of thousands of other genes that that gene has co-evolved with you know in the out of africa event and you know all of this sort of human history of evolution so basically if you look at neandertal genes for example which again happened long after that uh out of africa event there's incompatibilities between neanderthal genes and modern human genes that can lead to diseases so in the context of the neonatal genome that gene version that allele was fine but in the context of the modern human genome that neanderthal gene version is actually detrimental so it's it's you know that cellular environment constitutes the genetics of that gene but also of course all of the epigenomics of that gene it's fascinating that the the gene has a history i mean we talked about this a little bit last time but just and and then some of your research goes into that but the genes as they are today have have a story from the beginning of time and then some sometimes their story was like their path was useful for survival for the particular organisms and sometimes not that's fascinating let me ask as a tangent we kind of started talking offline about neanderthals uh do you have something interesting genetically biologically in terms of difference between uh neanderthal and like the different branches of human evolution that you find fascinating neanderthals are only one of about five branches that we are pretty confident about one branches of of out of africa events so basically there's neanderthals there's denisovans what is the evidence for denisovans one tiny little fragment of one pinky from one cave in siberia recent relatively recently discovered right less than 10 years ago yeah and those are like little folks right no no no no no that's yet another one though homo florences it had the little folks in sort of indonesia but then uh denisovans are basically another branch that we only know about genetically from that one bone and eventually we realize that it's one of the three major branches along with neanderthal modern human and denisovan and then that one branch has now resurfaced in many different areas and we kind of know about the gene flow that happened in between them so when i was reading my greek mythology it was talking about the age of the heroes these eras of human like you know precursors that were wiped out by zeus or by all kinds of wars and so forth like the titans and the you know it's it's ridiculous to sort of read these stories as a kid because you're like oh yeah whatever and then you're growing up and you're like whoa layers and layers of human-like ancestors and who knows if those stories were inspired by bones that they found that kind of looked human-like but were not quite human-like who knows if stories of dragons were inspired by bones of dinosaurs basically this archaeological evidence has been there and has probably entered the folk imagination migrated into those stories but it's not that far you know removed from what actually happened of massive wars of wiping out neanderthals as humans are modern humans are populating um you know europe do you think do you think what killed the neanderthals and all those other branches is human conflict or is it genetic conflict so is it uh us humans being the opposite of altruistic towards each other or is it uh some other uh competition at some other level like as we're discussing yeah so if you look at a lot of human traits today they're probably not that far removed from the human traits that got us where we are now so you know this whole tribalism you know your my sports team or your my you know political party or you're my you know tiny little village and therefore you know if you're from that other village i hate you but as soon as we're both in the major city i can't believe we're from the same region my friend come and like two neighboring countries fighting and as soon as they're off in another country they're like oh i can't believe that right so it's it's kind of funny like this tribalism is nonsensical in many ways it's like cognitive incongruent that basically we like kin and selection for for sort of liking kin is hugely advantageous genetically probably across all kinds of organs all across all kinds of life yeah so so basically if you now transport that to the sort of humans arriving in europe and neanderthals are everywhere what are you going to do you're going to kill them off you know there's this battle for territory and these battle for they're not like us we have to get rid of them so basically there's a you know very interesting mix there but and yet and yet when you look at the genetics there's tons of gene flow between them so basically you know love romance between you know tribes but love uh uh spans uh the gap between the different tribes it's wrong julia it's across species boundaries sneaks away from the village even before the out of africa there's you know within africa's election which was probably massive battles of larger and larger tribes selecting for our social networking and savviness and uh you know probably all our conspiracy theory genes or you know dating back from then and you know it's so there's a lot of this mischievousness in the history of human evolution that unfortunately still present in you know many ugly forms today but probably contributed to our success as a species in wiping out other species it just sucks that uh we don't have neighboring species that are you know intelligent like us that but yet very different than us so we have like you know dogs or wolves i guess uh co-evolved they they figured out how to uh neighbor up with humans in a friendly way and collaborate and it develop into describing this as if the wolves made a choice it's possible that the wolves never had to say that basically humans were just so overpowering that they had captive wolves and then at every generation killed off eight of the nine pups and only kept the one that was milder ah humans it only takes a few generations to then sort of have pups that are really mild and so the neanderthals weren't useful in the same way i don't know if it's a question of useful they were probably super useful my thinking is that they were scary that basically something that almost resembles you yeah is something that you try to eliminate first it's too close yeah and uh speaking of um you know species that are intelligent and sort of what's left of evolution it is a shame exactly like you say that so many different amazing life forms were extinct and the kind of boring ones remained so if you look at dinosaurs i mean the diversity that they had if you look at sub you know like there's just so many different lineages of life that were just abruptly killed and yet out of that death emerged you know many new kinds of really awesome lineages do you think there was in the history of life on earth species that may be still alive today that are more intelligent than humans and we just don't know it's also made for dolphins like if you look at their brains if you look at the way that they play if you look at the way that they learn uh you know i mean they don't have possible thumbs and we do so you know that probably made a big difference it's terrifying to think that like not terrifying i don't know how to feel about it that they're more intelligent than us it's like a hitchhiker's guide i know but how do you define intelligence basically like i was saying last time you know stupid is a stupid does and smart is a smart does so yeah if the dolphins are basically super smart figure out the meaning of life and just go around playing with water all day which is probably the meaning of life then we wouldn't know because all they're doing is kicking water just like sharks are and sharks are probably pretty stupid so so basically it's very difficult to sort of judge a species intelligence unless you they kind of go out of their way to demonstrate it yeah and that's instructive for our understanding of any kind of life form uh you know i recently talked to sarah seeger looking for life out there on other planets it'd be fascinating to think if we discover a habitable planet that's you know outside of earth in one day maybe many centuries away or be able to travel with like a robot there how would we actually know that this species would probably be able to detect that it's a living being but how would we know if it's an intelligent being i mean uh it's both exciting and terrifying to sort of come face to face with a life form that's of another world like something that clearly is moving in a um how would you say like a deliberate way and to then like ask well how do i ask that thing with it whether it's intelligent no but the the question that you're asking is um applicable to every species on on the earth on earth now yeah so basically you know dolphins are a great example we know that they're you know clearly capable hardware wise and behavior-wise of intelligence you know how do we communicate so basically if your question is about crossing species boundaries of communication the way that i want to put it is that humans have achieved a level of sophistication in our behaviors in our communication in our language in our ways of expressing ourselves that i have no doubt that if we encounter the human-like form of intelligence we'd figure out their language in a few weeks like it'd be just fine as long as you know of course they're both trusting each other not annihilating each other and not sort of fearing each other and attacking each other what about the message just out of curiosity into science fiction land a little bit if so uh clearly you're one of the top scientists in the world so if we were to discover an alien life form uh you would be brought in to study his genetics do you think the epigenome that we talked about the genome the code the digital code that underlies that alien life form would be similar to ours like the in um in fundamental ways maybe not exactly but in fundamental ways of how it's structured yeah so so you're getting to the very definition of life you're getting to the very definition of what what makes life life and how do we decode that life and it's so easy to think that every life form would basically have to you know like oxygen has to have to like heat from the sun and rely on sort of being in the habitable zone of you know its solar system and so forth but i think we have to sort of go beyond this sort of oh life on another planet must be exactly like life is on earth because of course life on earth happens to rely on the proximity to the sun and benefit from that amount of energy but we're talking at time scales of human life where we kind of live i don't know between and i'm going to be super wide here we're going we're going to live between six earth months and you know 200 a month earth months or 200 earth years so basically if you look at the time scale that we inhabit on earth it is very much dictated by the amount of energy that we receive from the sun if you look at i don't know europa you know the smallest the fourth smallest moon of jupiter the smallest of the galilean moons and also the smallest in its distance from jupiter it has an iron core it has a rock exterior it has ice all around it and it has probably massive liquid oceans underneath and the gravitational pull the gravitational pull of jupiter is probably creating all kinds of movement under that ice how did life evolve on earth yes sure life now most of life that we above the surface look at has to do with exploiting the solar energy for you know our daily behavior but that's not the case everywhere on the planet if you look at the bottom of the ocean there are hydrothermal vents there's both black smokers and white smokers and they are near these volcanic uh you know ducts that basically emanate a massive amount of energy from the core of our planet what does life need it needs energy does it need energy from the sun it couldn't care less does it need energy from you know the earth itself yeah possibly it could use that and if you look at how did life evolve on you know on earth there are many theories i mean a kind of silly theory is that it came from outer space that basically there's a meteorite out there that sort of landed on earth and it brought with it dna material i think it's a little silly because it kind of pushes the buck down the road basically the next question is how did it evolve over there yeah whereas our planet has basically all of the right ingredients why wouldn't evolve here so basically let's kind of ignore that one and now that the two other competing hypotheses are from the outside in or from the inside out from the outside in means from the surface to the bottom of the ocean ah from the inside out means from the bottom of the ocean to the surface so life on the surface is pretty brutal life obviously evolved in the water and then there was an out of water event but basically before it exited it was clearly in the water which is a much nicer and shielded environment so just to be clear on the surface are you referring to the the surface of the sea or the bottom of the sea versus the bottom of the sea and you're saying life on the surface is uh it's harsh like inside the life outside the water is horrible it takes huge amounts of evolutionary innovations to sustain living outside the water well that's so interesting why why is that so it's easier to life is easier in the water maybe see i'm telling you don't water yeah dolphins went back into the water really because dolphins are mammals of course yeah interesting well again they might be smarter they went back so so if you if you basically think about the fact that we are 70 water we're basically transporting the sea with us outside the sea you know if we if we don't have water for about a year 24 hours we're dry yeah and if you look at life under the sea i mean i don't know if you're a diver but when you go diving your brain explodes again when i say the light the boring life forms is what we see all the time like tetrapods i mean what a stupid boring body plan seriously like just go diving and you'll see that a tiny little minority of the stuff under the sea under the surface of the sea is actually tetrapods it's like you know snails with all kinds of crazy appendages and colors and you know round things and five-way symmetric things and you know eight-way symmetric things all kinds of crazy body plans and only the tetrapod fish managed to get out and then they gave rise to all the boring plants we kind of see today of basically you know uh humans with four limbs birds with four limbs lizards with four limbs and you know right it's kind of boring if you look at by comparison life underwater is teeming with diversity so now let's roll back the clock and basically say where did life in the ocean come from from the surface or from the bottom exactly those two options exactly so basically life on the surface is one option and then the idea there is that there's tides with the moon and the sun sort of causing all this movement and this movement is basically causing nutrients to sort of you know coalesce and you know bounce around et cetera that's one option the second option massive amount of energy under you know from from from our the core of our planet basically uh exploited leading to these basic ingredients of life forms and what are these basic ingredients metabolism being able to take energy from the environment and put it as part of yourself metabolism it basically means transformation again in the greek it basically means taking stuff from you know like nutrients or energy source or anything and then making it your own the second one is compartmentalization if there's no notion of self there can't be evolution you have to know where your own boundaries end and where the non-self boundaries begin and that's basically the lipid bilayer nowadays which is extremely simple to to form it's basically just a bunch of lipids and then they eventually just self-organize into a membrane so that's a very natural way of forming a self and then the third component is replication replication doesn't need to be self-replication it could be a helps make more of b b helps make more of c and c helps make more of a any kind of self-reinforcement is what you need to ignite the process of evolution after you've ignited that process you know i don't want to say all hell breaks loose but all paradise breaks loose so basically you then boom you know have life going and the moment you have abc some kind of thing looping back onto a you can make modifications and you can improve and then you let natural selection work is there some element of that that's like co like uh like some state representation that stores information like maybe i should say information absolutely is that talking about the part we like to think of life as the information propagation which is dna the messenger which is rna and then the action which is protein so basically dna we think is an essential part of life that's where the storage is and therefore that early life forms must have had some kind of storage medium dna if you look at how life actually evolved dna was invented much later proteins were invented later and rna was find by itself thank you very much in an rna world so the early version of life as we know it today was in fact rna molecules performing all of the functions the rna molecule itself was the protein actuator by creating three-dimensional folds through self-hybridization itself what self-hybridization so basically the same way that dna molecules can hybridize with themselves and basically form this double helix the single-stranded rna molecule can form partial double helixes in various places creating structure as if you had a long string with complementary parts and you could then sort of design kind of like origami-like structures that will fall down to themselves and then you can make any shape from that that early rna world eventually got to replication where enzymes encoded in rna would replicate rna itself and then that process basically kicked off evolution and that process of evolution then led to major innovations the first innovation was translation so you start with an rna molecule and you translate it into another kind of form and that's the first kind of encoding you're like well do you need some kind of code yeah but the code was in fact one thing it was conflated with the actuators the actuators were separated from the code only later on so you first had the self-replicating code which was also the actuator and then you kind of have a functionalization partitioning of the functionalization a sub-functionalization of the proteins that are now going to be the workhorse of life but they're not self-replicating the code remains the rna so the most beautiful and most complex rna machine known to man is the ribosome the ribosome is this massive factory that is able to translate rna into protein the ribosome if you if you want i don't know divine intervention in the history of life the ribosome is it that's one of the great invention in the history of life it's it's yeah but again you can't think of great inventions as one one-time steps they're basically you know the culmination of probably many competing software infrastructures for life preservation that won out and then when the ribosome was so efficient at making proteins all the other ones basically died out and then the life forms that were using the modern ribosome were basically the more successful ones because it could make proteins and now those proteins are much more versatile because rna only has four bases proteins eventually have 20 amino acids not initially but eventually and then they can form in much more complex shapes and they can create all kinds of additional machines one of which is reverse transcriptase so you basically now have rna again we like to think of transcription as the normal reverse transcription as the oddball well rna preceded dna so reverse transcription actually was the first invention before transcription itself so basically rna invents proteins rna and proteins together invent dna so you now have a more stable medium a more stable backbone with two helices instead of one two strands instead of one the double helix and rna basically says listen i'm tired i'm gonna delegate all information stories to dna and i'm going to delegate most actuation to proteins proteins but that's to you is not like a that's just an efficiency thing it's not a fundamental new correlation that's why when you're asking is a separate information storage medium a definition of life like no any kind of self preservation self reinforcement and it didn't need to be rna rna-based initially it didn't need to be self-replication initially you just need to have enough rna molecules randomly arising that reinforce each other that ultimately lead to the you know the closing of that loop and the ignition of the evolutionary process can we just rewind a little bit like if you were to bet all your money on the two options in terms of where life started probably the bottom at the bottom though i don't know if this is answerable but how hard is the first step or if there's something interesting you can say about that first leap yeah yeah yeah about from not from not life to life yeah i think it's inevitable on earth or just in the universe i think it's inevitable if you look at europa you know going back to the the moon of jupiter it's also a really nice song by santana basically has all the ingredients it has you know the core that can emit energy it has the shielding through the ice sheet protecting it just like an atmosphere would it even has a layer of oxygen probably sufficiently dense to sustain life so my guess is that there's probably uh independently a reason life form already teeming in europa because as soon as it today is that exciting or terrifying to you it's i mean as a scientist i can't wait to see non-dna based life forms i can't wait because we are so born uh in in you know sort of uh borne as i would say in french but basically we're sort of you know we we we are so narrow-minded in our thinking of what life should look like that i can't wait for all that to just be blown away by the discovery of life elsewhere let me bring you into another science fiction uh it's a scenario so on that point if we discover life on europa and you were brought in you seem very excited but how would you start looking at that life in a way that's useful to you as a scientist but also not going to kill all of us so like to me it's a little bit scary because not not because it's a malevolent life like it's a it's a dictator petting like a cat it's evil but just the way life is it seems to be very good at conquering other life so there's a lot of science fiction movies based on that principle yeah and that's sort of what causes the public to be so scared but if you think about sort of would europa life be scared of humans coming over and taking over chances are no not even like earth bacteria because earth bacteria would be wiped out in an instant in this foreign world because they don't know how to metabolize energy that doesn't come from the types of energy sources that are here the levels of acidity may just kill us all off and at the same way in this in in the converse way if you bring life from europa on earth it'll die instantly because it's too hot or because it doesn't need to know how to cope with i don't know the sun's radiation so close to this completely inhabitable zone by their standards so so what we call the habitable zone might actually be the inhabitants for them so the difference if the environments are sufficiently different you think we'll just not be able to even attack each other and a basic uh it'll take massive amounts of engineering to create machines that will go there and sample the you know oceans basically drill through the layers of ice to basically sample and see what life is like there and detecting it will probably be trivial it definitely won't be dna based it's not like we're going to send a sequencer but it'll be you know some other kind of combination of chemicals that will look non-random so if you had to bet if i took that life form we find on europa and like put it on a sandwich that you're eating and like eat that sandwich it'll taste just fine and you'll be well i don't know about that i don't know anyone well it tastes fine that's interesting so the other question is do we have taste receptors for this adaptations to chemical molecules that we are used to seeing so you think we don't have case bugs for things we don't even know about wow so we won't yeah we want to be able to know that this chemical tastes funny but you think it won't be it's likely not to be dangerous like it won't know how to even interrupt do you think our immune system will will even detect that something weird is probably and it'll be very easy to detect because it'll be very different from very weird but it won't be able to sort of attack i mean the scene from i don't know independence day where like they're communicating with the other computer and they're like ooh i'm in i mean it's hilarious because like macs and pcs have trouble communicating i mean let alone an alien technology or even alien dna so okay uh now i was talking about you being a scientist on earth but say you were a scientist uh they were shipped over to europa to investigate if there's life what would you look for in terms of signs of life life is unmistakable i would say the way that life transforms a planet surrounding it is not the kind of thing that you would expect from the physical laws alone so it's i would say that as soon as life arises it creates this compartmentalization it starts pushing things away it starts sort of keeping things inside that herself and there's a whole signature that you can see from that so when i was organizing my meaning of life symposium my my my friend was an astrophysicist um basically uh we were deciding on what would be the themes for the for the symposium and then uh i said well we're going to have biology we're going to have physics and she's like come on biology is just a small part of physics [Laughter] everything is a small part of physics and uh i mean in in many ways it is but my immediate answer was no no wait life challenges physics it supersedes physics it sort of fights against physics and that's what i would look for in europa i would basically look for this fight against physics for anything that sort of signatures of not just entropy at work not just things diffusing away not just gravitational pulls but clear signatures of you remember when i was talking earlier about this whole selection for environment selection for biospheres for ecosystems for this multi-organism form of life and i think that's sort of the the first thing that you can look for you know chemical signatures that are not simply predicted from the reactions you would get randomly such a beautiful way to look at life so you're basically leveraging some energy source to enable you to resist the physics of the universe fighting against physics but that's that's the first transformation if you look at humans we're way past that what do you mean by transformation so so basically there's there's layers i sort of see life you know when we talk about the meaning of life life can be construed at many levels we talked about life in the simplest form of sort of the ignition of evolution and that's sort of the basic definition that you can check off yes it's alive but when alexander the great was asked to whom do you owe your life to your teachers or to your parents and alexander the great uh answered i owe to my parents the zine the life itself and i owe to my teachers the f zine like euphony f means good the opposite of cacophony which means you know bad so f zine in his uh words was basically living a human life a proper life so basically we can go from the zine to the f-zine and that transformation has taken several additional leaps so basically you know life on europa i'm pretty sure has gotten to the stage of a makes b makes c makes a again but getting to the f zine is a whole other level and that level requires cooperation that level requires altruism that level requires specialization remember how we're talking about the rna specializing into dna for storage proteins and then compartmentalizations and if you look at prokaryotic life there's no nucleus it's all one soup of things intermingling if you look at eukaryotic life again you for true good you know so a eukaryote basically has a nucleus and that's where you compartmentalize further the organization of the information storage from all of the daily activities if you look at a you know human body plan or any animal you have a comparablization of the germline you basically have one lineage that will basically be saved for the future generations and everything outside that lineage is almost superfluous if you think about it the rest of your body all it does is ensure that that lineage will make it to the next generation that these germ lines will make to the next generation the rest is packaging i'm sorry to be so blunt yeah and if you look at nutrition you know where deterostomes what does the stone mean dertero means second where this is the second mouth the first mouth is actually down here is the esophagus so dirt or stones have evolved a second layer of eating kind of like alien with the two mouths yeah so you can think of us as alien where the first mouth is up here and then the second mouth is down there is of course is the first mouth just the the the physical manipulation of the food to make it more correct correct and basically again you know if you look at if you look at a worm it's an extremely simple life form it basically has a mouth it has an anus and it has you know just some organs in between that consume the food and just spit spit out poo humans are basically a fancy form of that so you basically have the mouth you have the digestive tract and then you have limbs to get better at getting food you have eyesight hearing etc to get better getting food yeah and then you have of course the germline and all of this food part it's just auxiliary to their germline so you basically have layers of addition of comparablization of specialization on top of this zine to get all the way to the earth scene yeah so like the warm is like windows 95 very few features very basic and then us humans are like windows vista or windows 10 whatever it is well a few innovations beyond that but yeah and then all right where i don't know where windows 3000 at least is such a fascinating way to look at life as a set of transformations exactly so like is there some interesting transformations to our history here on earth that like appeal to you of course so and what are the most brilliant innovations and transformations yeah yeah yeah i mean this is such a fascinating question of course like you know we're talking about basic basic life forms and we'll talk about eukaryotic life forms and then the next big transformation is multicellular life forms where the specialization separates the germ line from everything else that accompanies it and sort of carries it and then that specialization then sort of has this massive new innovation like above the second mouth which is this massive brain and this massive brain is basically something that arises much much later on basically you know notochords like having the first spinal cord this whole concept that along with the this very simple layers you basically now have a coordinating agent and this coordinating agent is starting to make decisions and remember when we're talking about uh free will i mean you know as a worm is hunting for food oh it has plenty of free will it can choose to you know follow chemotaxis to the left for chemotaxis to the right and maybe that's free will because it's unpredictable beyond a certain level so you basically now have more and more decision making and coordination of all of these different body parts and organs by a central operating system a central machine that basically will control the rest of the body and the other thing that i love talking about is the different time scales at which things happen you know we're talking about the human epi genome before the human epigenome is basically able to find what genes should be expressed in response to environmental stimuli in the order of minutes and basically receive a stimulus transfer all that data through this humongously long string of searching and then sort of find what genes to turn on and then create all that all of that is happening in the time scale of minutes basically you know three minutes to a to half an hour that's the expression response but our daily life doesn't happen on the order of three minutes to half an hour it happens on the order of milliseconds like i throw a ball at you you catch it right away no gene expression changes there you just don't have time to do that so you basically have a layer of control built on a hardware that supports it but that hardware itself lives in a different time scale than the controlling machine on top of that is that an accident by the way is that like a feature is it was it possible for life to have evolved where the our the daily life of the organism as it interacts with its environment was on time scale similar to uh the the way our internals work if you look at trees they look kind of boring and stupid you're like looking at a tree like stupid if you speed up the movie of a tree from spring until october you'll be like oh my god it's intelligent and the reason for that is that at that time scale the tree is basically saying oh i'm looking for a you know a thing to catch on to oh i just caught on to that i'm going to grow more here i'm going to spawn there etc like i can see the trees in my garden just growing and sort of you know looping around and um it's all a matter of time scale and if you look at the human time scale remember we were talking about neoteny the last time around the whole fact that our young are pretty useless until you know maybe you know a few months of age if not a few years of age if not i don't know getting out of college and then we we basically hold them enabling their brain to continue being malleable and infusing it with knowledge and you know thoughts as you know that period of neotimi increases and expands if you fast forward i don't know another million years so humans have only been around you know different from apes for about that long jump another unit of that another human gym divergence what could happen from an evolutionary time scale a lot one of the things that's happening already is expansion of human lifespan we have longer and longer periods before we mature and we have longer and longer periods because before we have babies so intergenerational distance is you know grown from i don't know 16 years to 40 years you're saying that's in the genetics like no no not necessarily but but it's it's sort of an environmental tendency that's happening but as we medically expand human lifespan the generations might actually be pushed instead of 40 years to 60 years to 100 years if we look at the long arc of the evolutionary history exactly so as we start thinking about intergalactic travel now i'm sorry that's that's a heck of a transition uh yeah so let's talk about it no no no no no as as we as a species start thinking about i mean i'm talking about these transitions that are happening right now and that's that's so awesome continuing along these transitions what does the future hold in the next million years so the concept of us going to another planet and that taking three human lifetimes might be a joke if the human lifetime starts being 400 years or 800 years so imagine this time scale it's all time scale just different time skills yeah you asked me offline whether i would like to live forever i mean my answer is absolutely and there's many different types of forevers one forever is do i want to live today forever kind of like groundhog day and the answer is absolutely the stuff that i want to learn today will probably take a lifetime just to learn you know basically to clear my to-do list for the day you mean like relive the day of the day and then and then pick up different things from the richness of the experiences there's just so much happening in the world every single day so much knowledge that has happened already that just to catch up on that will probably take me around forever and that on that point i just i would just love to see you in the groundhog movie just because you're so naturally as a scientist but just the way your mind works beautifully just all the richness of the experiences that you would pick up from that uh that's a beautiful visual but you just try to live each day as if it was groundhog i'm basically every single day waking up and saying all right how would bill murray get out of that one well you know what on uh on a funny tangent like i got a chance to uh go to a neural link demonstration event i'm not usually familiar with neurolink and uh i talked to elon for a while uh and one of the funny things he said on this groundhog day thing is you know it's a beautiful dream to eventually be able to replay our memories so we're kind of these recording machines our brain is kind of uh maybe a noisy recording machine of memories and it would be beautiful if we can someday in the future maybe far into the future be able to like in the groundhog day situation replay that and the funny comment that stuck with me is he said that maybe this our conversation now is a replay of a member of a previous memory and that stuck with me because it would probably be my replay you know who the hell am i i'm just some idiot guy but like elon musk is you know probably because of spacex and so on is probably going to be remembered as a special person one of our special apes in history so if i wanted to replay memory probably be that one you know talking to elon for a while yeah that's an interesting uh possibility from uh if we think about time scales if we think about the richness of the experience through time that we humans take and be able to replace some aspects of that of that biology that's super interesting but anyway sorry sorry for the tangent let's yeah you were talking about time scales and the expansion of the human lifetime and uh the intergalactic travel yeah no but but you're laughing about this yeah for sure that is you're talking about this you're talking about exploring alien worlds yeah and going to other planets i mean you know when sarah was here she was talking about sort of going to other planets when we find these life i mean i'm just very naturally given the topics that we've approached talking about the the time scale at which this will happen so i think eventually we will human or life life will expand out into the universe the the point that i'm trying to make is that in intergalactic species we'll probably find ways to engineer its biology in order to expand the way that we experience time expand the the time skills that we experienced and going back to this whole concept of you know would i like to live forever yes i'd like to live forever even if it was even if i was stuck on the same day i'd love to live forever because i would finally have time to do all these things that i want to do but if living forever actually comes with a perk of watching the whole world evolve forever i mean that's a huge perk and i would you know just it'll never get boring just an ever-changing world and then the mind uh you know sort of experiment that i want you to to do is to also ask what if i wanted to live forever one day at a time every year or one day at a time every decade would you choose that where you would wake up and the world would be 10 years later every single day you wake up it's the opposite of groundhog day where basically you always wake up and it's always 10 years later so you're saying that's such a powerful interesting concept that life is more interesting if you're of all the life forms on earth that you're the slowest one exactly exactly like trees like you know they've been there since the minoan civilization yeah and you know that takes us back to the the question you asked about sort of the transformations that have happened in humanity the minoan civilization is one of them you know there's this paper that was published just a couple of years ago by one of my friends that basically looked at the uh genetic makeup of the minoans and the messinians in ancient greek in ancient greece and how they relate to modern greeks and they found that indeed there was very little gene flow from you know the outside and you know it's it's fantastic to sort of think about these amazing civilizations that transformed the way that human thought happens that basically looked for rules in nature that looked for principles that looked for the standards of beauty not human beauty but beauty in the natural world this whole concept that the world must be elegant and there must be deeper ways of understanding that world to me that's a massive transformation of our species similar to you know the earlier transformation we were talking about of even involving a brain of you know learning how to communicate language or the evolution of eyesight if you look at sort of you know we're talking about these worms crawling around and then sensing which direction are the chemicals more abundant you know chemotaxis so eventually they grow a nose eventually they grow uh i mean when i say nose i mean ways of sensing chemicals that's probably one of the earliest senses you know we always talk about how deep rooted is in your brain that's one of the earliest senses if you look at hearing that's a much later sense if you look at eyesight that's an intermediate sense where you're basically sensing where the light direction comes from that's probably something that life didn't mean until it got you know into the surface and so on and so forth so there's a lot of you know milestones and i was talking about the latest milestone which is ligo last time of being able to detect gravitational waves and sort of being able to sort of have a sense that humans haven't had before so you see that as a yet another transformation it gives us an extra little sound of course and now if you go back to this history of ancient greece i mean this this transformation that happened i mean of course the egyptians had this incredible you know civilization for thousands of years but what happened in greece was this whole concept of let's break things down and understand the natural world let's break things down and understand physics let's basically build rules around architecture about around elegance around you know statues and tragedy i mean another question that you asked me in passing was this whole concept of embracing the good and the bad embracing your the full range of human emotions and if you look at greek tragedy it's the definition of that it's i mean drama i mean again it's a greek word but but the whole concept of some problems that are just so vast and large that dying is the easy way out the death oh that's the easy solution you know so so i want to touch a little bit on that point and and um sort of talk about this concept that life supersedes physics and that the brain supersedes life that basically we have a brain that can decide to not follow evolution's path we can decide to not have children we can decide to not eat we can decide to suicide we can decide to sort of abolish communication with the outside world i mean all the things that make us human we can basically decide not to do that and that that is basically when the brain itself is basically superseding what evolution program is for so okay so one of the it's okay my mind was already blown at the beautiful formulation of the idea that life is uh is a system that resists physics yeah and our brain or perhaps the content of it or however maybe functionally our brain is a thing that resists life yes yes you're so you're so brilliant but but but but i want you to see all of that as a continuum basically you're sort of talking about the sort of individual transformations but it's a path yeah that that humanity has a transformation it's a path of transformation and then i want us to think about what it truly means to become human like the f zine and you asked me about what motivated my meaning of life symposium what motivated it in part i mean of course it was an inside joke of turning 42 but what motivated him in part was actually a mid-life crisis so the joke that i always like to say is chris papadimitriou a famous greek professor who was previously at mit at harvard at stanford berkeley everywhere uh brilliant brilliant person that's actually costis advisor yeah uh so so christopher means really likes to say that when you're an undergrad you work like a rat to get into grad school and where you grasp you work like a rat to get your phd and where you're post doc you work like a rat to get your assistant professors in jail and where is this profession you work like a rat to become a full professor and then when you're a full professor well by then you're basically a rat that's brilliant so basically what happened to me is that i arrived at the end of the rat race yeah you know life is a rat race you constantly have hurdles to jump over you constantly have tunnels and secret pathways and i figured it all out and eventually as i was turning 42 i looked back and i was like wow that was an awesome rat race but i'm not a rat i basically got out of the labyrinth and i was like i'm not i'm not a rat turns out is that the first moment where you saw that it's that you were in a rat race it no no i've known that i'm in a rat race for a long time it's so easy to be in a rat race it's so easy to be an undergraduate because you have problem sets and you know we're all smart people you know problem set it has a solution somebody made it for you you can just solve it everything was made as a test and you keep passing those tests and tests and tests and tests and you have tasks that are well defined the phd is a little different because it's more open-ended but yet you have an advisor who's guiding you and then you become a professor and tenure is a well-set defined set of tasks and you do all that and at 42 i basically had bought a house three kids beautiful wife tenure yeah awesome students tons of grants life was basically laid out for me and that's when i had my main life crisis that's when people usually buy a harley davidson [Applause] and they basically say oh i need something new i need something different and to be young myself etc but basically that was my realization that it's not a rat race that there's no rat race it's over that i have to basically think how do i fully instantiate myself how do i complete my transformation into an actual human being because it's very easy to sort of forget all the intangibles of life it's very hard to just sort of think about the next task and the next ask and it's all metrics and you know what's the number of viewers i have what is the number of you know publications i have what's the number of citations the number of talks the number of grants it's very easy to quantify everything and then at some point you're like this is real life it's not a test anymore and that's something that i told my wife early on i was like no no our life is not going to be let's put the kids through college and that you know maybe that's when i escaped the rat race maybe it continued being a rat race maybe the next step would have been all right how do i make sure that my kid is first in class how do i make sure that they're you know into the great greatest callers and then you know they're into college and then you're like 60. so how do you how do you escape but what is uh uh is is there a light at the end of the tunnel of a midlife crisis so so you should watch that symposium because the videos were transformative to me and to many others so basically the advice that i received from all of my friends was so meaningful this you know there's some some advice that basically says you have to constantly maintain unachievable goals goals that you can make progress towards but you can never be fully done with and i think that's almost playing into the sort of rat race thing like basically make sure that there's more obstacles for your little rant persona to jump through so that's one possibility so first of all watch is it available it's on youtube just google it google really meaning of licensing i've known this and you should have told me this like this is awesome okay yeah this is great but and also like you know saying rat race is uh you know if you look at ratatouille it's not i mean that's a beautiful that's a beautiful thing of challenges and overcoming child that could be fundamentally the meaning of life is uh to see life as a set of challenges and to fully engage in the overcoming of those challenges i would say that that's embracing the rat race view of life so so a joke that we like to have with my wife all the time is we basically say we we pretend that we're in this all-inclusive resort that we've basically hired all these people to go on the esplanade and play games because we enjoy watching people playing on the esplanade and we enjoy sort of laying and looking at life and all the people biking and rollerblading and all that and then we've paid all these people in this all-inclusive resort that we live in and then uh what are we going to do today i'm like oh i've signed up for professor activities it's going to be awesome they they lined up a bunch of super smart mit students for me to meet with i'm gonna have a grant writing meeting afterwards it's gonna be awesome and then she signed up for a bunch of consulting activities it's gonna be great and then in the evening we just get back together and say hey how was your consulting today so in a way that's another view of life of basically wait a minute if i was a gazillionaire what would i choose to do i would probably pay an awesome university to give me an office there and just pay a bunch of super smart people to work with me even though they don't really want to etc etc in fact i would have exactly the life that i have now working my butt off every single day because it's so freaking fulfilling well that's so let's clarify this is a beautiful way it's almost like a video game view of life that it's a set of i mean again game is not perhaps a positive term but it's a it's a it is a beautiful time so you you do do you or do you not like the rat race view of life no because it is fulfilling in some the right race is about the goal my view of life is about the path so again quote in greece those folks have come up with some good stuff so this um basically wrote this uh beautiful poem about sort of going through life saying as you go through your journey impersonating ulysses of his voyage he says wish that the path is long and arduous because when you get to ithaca you might realize that it was all about the path not the destination and so the rat rate view of life makes it all about the destination it's like how do i get through the maze to get there but the all-inclusive resort view of life is about the path it's about wow today i couldn't wish for a better set of activities all programmed for me to enjoy having my brain having my body having my senses and you know the life that i have so it's a very different kind of view it's focused on the journey not on the destination so we you mentioned kind of the ups and downs of life and the midlife crisis and right now you said focusing kind of on the journey but what the journey involves is ups and downs is there uh advice or any kind of thoughts that you can elucidate about the downs in your life yeah the hard parts of your life and how you got out or maybe not or is there yeah how do you see the dark parts of life so i i'm so glad you're asking this question because it's something that our society does a terrible job at preparing us for every hollywood movie has to have a happy ending it is ridiculous you can count on your ten fingers the number of bad ending movies that you've ever watched and you probably wouldn't need all 10 fingers we strive to tell everyone yes you can succeed yes you're a millionaire just temporarily disabled and yes you know uh the prince will eventually figure out his princess and they will have a happily ever after ending and yes the hero will be beaten and beaten and beaten but you know that at the end of the movie the googly eyes will win we need more movies where the bad guys win we need more movies where just everybody dies we're just you know a macgyver doesn't figure out how to disable the bomb and it just explodes you just you just need more movies that are more realistic about the fact that life kind of sucks sometimes and it's okay so again growing up in greece i i have been exposed to songs that are not just sad but they're miserable miserable so so one of them one of them comes to mind and and it's it's basically talking about this woman who's lamenting in the early morning about losing the joyful kid the joyful young man who basically died in the civil war in the arms of our own fellow citizens and she's like if only he had died fighting the foreign forces if only he had died at the you know sides of the you know general if only he had died with honor i would be proud to have lost the joyful kid i mean it's devastating right it's like he didn't just die he died without honor yeah and and i my friend who was with me was listening to the song and she's like this is depressing i'm like you have to listen to another one it's not as sad and she's like what this one died with honor so so that's one example it's a kind of a celebration of uh misery no no no no no no so let me give you a couple more examples and and then i'll answer that question so another example is i i picked up this book that i had from my childhood and i started reading stories to my kids and the first story is about these two children one is really poor living on the street and the other one is really rich living in the house and the bright light above and the poor one is wishing looking at that window and wishing that you could have that house and the other one is at the window wishing that he was free that he wasn't sick all the time that you could escape outside it's only four pages long and at the end both children die one of them dies from cold the other one dies from illness and you're like how is that even a children's story the next story i'm like okay that's fine let's skip this one let's you know so i read this to my kids and then i read the next one and the next one is about this this woman whose brother is at war against the turks and he is gonna die and she prays to the virgin please don't let him die and the virgin appears and she's like no problem tell me who to kill instead and she's like anyone anyone no no no choose one how about this turk this one has two kids a beautiful family waiting for him at home she's like no not this one choose another one and then she goes through all the life stories of the other and since he's like no no just don't take anyone he's like i can't do that i can you can choose to bring your brother back and he will be depressed for the rest of his life because he didn't fight at war because he didn't go to that battle and he will live without her she's like and in the end the woman decides to have her brother killed instead because he dies with her i mean this is insane so so why am i giving you these examples it's not a glorification of misery it's a it's expand your emotional range it's teaching you that and and when i read these stories i'm not i'm not a jerk i'm crying out loud i have tears and i like my face becomes red from the the the pain that i'm experiencing through these stories it's just so deeply touching to embrace the suffering not because of an accident but because of a choice the sacrifice to embrace the fact that not everything is cute and rosy and always ending well and i think that we don't do a good enough job of teaching our kids that just life sucks and life is unfair sometimes and that's and that's okay and sometimes i read a story to my kids i read a story every night and sometimes the story is horrible and sometimes the story is good and and sort of friendly and happy and my kids always ask what's the moral of the story and sometimes those are moral and it's like oh you should be good or you should be nice you should be helping each other et cetera and sometimes it's just no moral and i tell my kids you know what sometimes just life doesn't make sense and it's okay and you can't comprehend everything and i think this concept of how do you deal with bad days comes from the fact that we're taught we're brainwashed into thinking that every day should be a happy day and we're not ready to cope with misery and the other thing that crying through these stories teaches you is that you don't have it nearly half as bad as you think do you see do you see what i mean basically it tells you that i mean my mom would always tell me about how she was transformed as a teenager when she volunteered in the hospital and she saw all these people at the brink of death clinging for life and helping them out to be as she could and crying her her heart out when they were dying and sort of how that taught her the appreciation for what we have every day waking up every morning and saying my life doesn't suck my life is not nearly half as bad as it could be and and sort of embracing the joy that we have of living where we live in the moment we live and i'm gonna go further if you look at the arc of human um life the you know human existence through the centuries there's no better way to be alive than now i mean we're complaining about every single little thing but life expectancy is at an all-time high sickness all-time low poorness misery all-time low there's no better time to be alive globally across all of human existence number one number two here in boston there's no better place to be alive if you think about the amalgamation of science engineering technology the ridiculously awesome people you're bringing every week to your podcast i mean this is the ancient greece of modern society but the weather still sucks because no let me put it this way the weather gives us a range of emotion the full range the full scenic pattern that's such a fascinating thing about human psychology i've i often reread this book i'm not sure if you're familiar with this man's search for meaning by viktor frankl and uh he talks about you know his uh living through the holocaust and in the concentration camps and even there where there's like human misery is at its uh highest even there he discovers these moments by observing the suffering by accepting the suffering he uh he observes moments of true joy of how great his life is relative to others at the camp uh who have it worse yeah so so it's it's a dangerous liberty slope to think that way because it's basically being better than jones's and if you know if the the house next door has a giant car then you want to get a bigger car or something like that it's not comparative misery i think the way that i see it is slightly different it's and it's not even thinking about all the worst possible outcomes that could have happened but didn't the the example as you were talking about the concentration camps the most horrible i mean one of the most horrible moments of human existence i was thinking about pictures that i was seeing of kids in syria in war-torn zones and you're looking at these kids and again i cried out loud imagining my own son in the van after a bomb explosion watching his you know father die or his siblings die or losing his friends it's something that we are not capable of fathoming but if you actually put a seven-year-old in that situation the look that i saw in these kids eyes basically said it is what it is it was it was and and i've experienced that with my own kid when he gets like my my my three-year-old last like two years ago who's not my five-year-old uh she was burned really badly with like hot chocolate and coffee that just peeled off her skin so you could actually see just her fragile skin had just peeled off and she was the happiest little kid she was just going along with the punches it is what it is it is she accepted it so so to sort of realize that children don't say oh i could have it better they they sort of embrace the moment not embrace but sort of accept the moment and then they can have moments of pure joy in a horrendous war-torn country and you know like so many people from you know these war torn countries basically say oh you think you americans are going to just come and just send us a bunch of aid and food etc yeah sure that's helpful but what do we dream of what do we struggle for we struggle for love we struggle for meaning we struggle for you know emotions and friendships we struggle for the same things you guys struggle for we're not just like every day waking up and saying oh i wish i had more food no that's just a given i just don't have enough food but what we struggle with are basically everything else and that sort of gives you some perspective on life it basically says you know and another story that my mom told me when i was a kid is this story about sort of this man who's basically you know see he sees the christ up here in front of him and he says oh christ i'm carrying all these problems i'm carrying this big bag can you please take it from me and he's like sure let me just give you any other bag and basically you know the person in the end except his own bag so acceptance ultimately recommended acceptance every single other bag is probably worse it's the evil you don't know versus the evil you know like we all struggle with our own problems but if you look at the bigger picture it's just your path through life and if you embrace it the good and the bad every single day it's just joy elation sadness misery if you don't have both you're not a complete human being you know you can't i mean the last example i'm going to give is the movie um inside out by pixar beautiful movie which one is that the one with the little characters controlling all the emotions so you basically have joy and sadness and fear and disgust etc and the moral of the story if you remember the movie the moral of the story is that in the end joy is basically trying to fix everything to make everything happy and she's failing miserably and everything else is like crumbling and falling apart and the little girl basically becomes emotionless because all she knows how to do is fake happiness and i think it's a very good analogy for our everyday society where we're always saying are you happy are you happy my mom calls me and she's like manolas are you happy i'm like mom stop asking this stupid question no i'm not happy yeah what you should be asking is if i'm fulfilled yeah and that's a very different thing i don't go around being happy i wouldn't love it if your mom called and said manolas are you suffering beautifully that's exactly right that's what she should be asking are you are you struggling to achieve something great yeah that's the question that your mom should be asking not only did that mom call me about the suffering not about how good uh how good are you doing so what i tell her is that life is not about maximizing happiness life is about accomplishing something meaningful and accomplishing that meaningful thing cannot come from a series of joyful moments it comes from a series of struggles of successes and failures of people being nasty to you and people being nice to you and embracing the full thing and if you supersede that constant need for gratification if you supersede that constant need for kindness you suddenly know you who you are and what i like to say to my kid and my son the other day was telling me oh so-and-so called me such and such and i'm like are you such and such he's like no i'm like ha ha see they were wrong and what i tell him is if you know who you are what other people say about you only teaches you about them yeah so it has no influence on your self-esteem if you know where you stand you embrace the good but you also embrace the bad i have plenty of bad and i'm embracing it i'm a procrastinator how do i deal with that i trick myself into procrastinating about mindless stupid little day-to-day things and in that procrastination time doing important things for the future so accepting who you are accepting your flaws accepting the whole of it accepting the struggle accepting the sleeplessness accepting the fact that the journey is what matters hoping that your path to ithaca is full of troubles because those troubles are the life you will lead accepting that life will not start after the next milestone that life has already started a long time ago and what you're experiencing now is the life this is it it's not some kind of future thing that you work yourself hard to get to and then after that you'll live hyperello happily ever after to me the happily ever after that's the end of the story nothing happens after that they struggled and the struggle and the struggle is much more interesting story than they lived happily ever after so i think we have to embrace that as a as a society that it's not just about the happy ending that our kids are brainwashed into expecting that things will be happy and rosy and it's okay if they're not and they should keep struggling because the struggle is the journey and the journey is the meaning of life it's not the end it's the journey what about accepting one of the harder things we talked a little bit about immortality what about accepting that life ends so do you monoliths think about your own mortality how we talked about accepting that there's ups and downs to life what about the ultimate down which is the finality of it do you think about that do you fear it you also ask me if i'm afraid of getting older yes and that's on the path to mortality so let me talk about that first step and then the last step literally the last step so getting older what does that mean when i was 18 when i was 20 my brain i felt was at my maximum i was like nothing is impossible i can solve anything i could take any math puzzle any logic puzzle any programming puzzle and to solve it in milliseconds i just saw the answer through problems i was like feeling invincible i would show up at lecture with my newspaper lift up my head every now and then point to errors just brat complete brat i would raise my hand and correct my professors from the whole classroom total brand i have some of those in my class now and it's awesome it's like very huge i used to be you teaching you humility yeah so um so so so i felt invincible and i was like this is it this is awesome i'm living the life 10 years later my brain didn't work the same way i wasn't as good at the tiny little puzzles but it worked in different ways and right now 20 years later it works in yet different ways and oh gosh i love the journey can you maybe give some hints of the interesting different ways that your brain works as it aged yeah i went from the phase of sheer speed and hardcore quantitative thinking to sort of stepping back being able to sort of make more connections being able to sort of say yeah but let's use that thing sort of a huge new creativity being unleashed basically when you're young you're sort of thinking about that one problem you can sort of reconfigure all the variables combinatorially in your head and just wipe it all out when you're you know just a little older you start getting more creative you start bringing in things from different fields and different contexts and sort of stepping outside the box basically it's like being in the rat race and saying there's a ceiling why are we trying to get through that so it's sort of look you know thinking outside the box and then at 40 what i'm going through now is this whole sort of embracing the path of life and when i say life has started already it's not a test anymore this is basically embracing the finality embracing that the journey is what it's at so what i like to say is live every day as if it's your last one and make plans as if you'll never die i always have the long term that i'm you know sort of planning out for that will eventually become the short term and i always have the sort of short term and i think this ability to sort of look at life in the back in the past and look at life in the future jointly and sort of embrace the continuity both of life in the universe and on our planet as well as life as a human being from the beginning to the end just as a path as a journey and just embracing every aspect of that i mean i was talking about parenthood the other day and how amazingly fulfilling it is to sort of relive childhood through the eyes of my kid but with the perspective of a parent so the the the sheer you know um arrogance of youth yeah watching this in my kid i can see myself when i was 18 correcting my professor i felt so proud yeah little did i know that my professor was working on so much more interesting things than the three little things he was putting on the board that day and i was like i'm invincible but in fact no just a little brat and basically right now i i sort of can see the the the sort of journey with a little more humility i can sort of look at my own students with their unbelievable abilities being able to do things that i'm no longer able to do better than i probably was ever able to do but yet being able to guide them and shape their thinking and blow their minds with new ideas and new directions through my perspective and i know when something is solvable because i've been there but i'm not going to even bother it's not that i can't do it i'm sure i could if i tried i just i'm not interested in that anymore so what i'm embracing this journey of aging is how my brain is changing and how i'm constantly trying to figure out the niches the evolutionary niches that i'm best adapted for for the tasks that i'm best at while hiring and recruiting both assistants and research scientists and students and postdocs and you know that will be the best at those tasks so but someone still has to see the big picture and i love being in that role so you're at the at the time scale of a human lifespan you're doing the same thing that the worm did at the evolutionary time scale of uh growing arms of the specialization the car compartmentalization right he talks about i mean it's fascinating to think of what uh 80 year old menolas would look back at the at the man that's sitting here today and and and laugh at the ceiling at the arrogance finally figured out something i was like no little thing you didn't figure out anything i mean ultimately it seems that if you're introspective about life it all it leads to a kind of acceptance a deeper and deeper acceptance of the whole of it there again i want to be cautious about acceptance because it almost says that you can't change it ah yeah it's it's sort of embracing the struggle and embracing the journey is the way that i would put it so you ultimately feel the journey isn't just something that happens to you your horse you shape it you shape it remember how i was saying that boston is the best place and the best time to live in right now you know in the history of humanity i'm exaggerating a little bit but the way that i think about this is that if you look at the hub in the whole of cosmos where would you rather be if you're just a bunch of molecules roughly your you know biomass where would you rather be would you rather be a rock on mars probably not would you rather be in a black hole probably not would you rather be an exploding supernova maybe that might be interesting but being on earth is an awesome solar system an awesome planetary system an awesome you know place to be in across all of space time it's a pretty good place to be in as a bunch of molecules if you are a bunch of molecules on earth today being an animal with you know some kind of awareness of the stuff around you is wonderful being a human among all animals is amazing because you have all this introspection and being a human who's young fit athletic smart etc i mean you know you have so much to be happy for beyond that being surrounded by a bunch of awesome people that you interact with all the time i mean i feel blessed to interact with the people i know the friends i have the dinners that i have all of this the students that i interact with i'm so blessed and the last little little blip in this awesomeness of local maximum the last little blip comes from being kind being grateful and being kind i don't know if you remember that little prayer that i described last time of thank you for all the good you've given me and give me strength to give unto others with the same love that you've given to me and and the whole point of that is being grateful and being kind what does that do from a purely egoistic perspective it makes the people around you happier and it takes that little maximum a little bit further because you'll be surrounded by happy people by being kind that's the purely egoistic view and the purely altruistic view or maybe it's egoistic as well is that it just it's good to give it feels good to give like basically watching somebody who's touched by what you said watching somebody who's like appreciating a rapid response or a generous offer or just random acts of kindness is so fulfilling so evolutionarily we were selected for that they're just such a good feeling that comes from that you know it's fascinating to think you said boston is the best place and talking about kindness that the very thought that boston is the place best place in the universe is almost it's a kind of a gravitational field uh like your thought and your very life in itself is a kind of field that makes that real yeah so the self-fulfilling prophecy yeah and by by claiming it's the best and thinking is the best it becomes the best and you make others it's it's a for it's not a force that just applies to your own cognition exactly it applies to the others around you and then suddenly you live in an even better place yeah and because you it creates the reality the actual reality that the the social reality exactly it molds the environment exactly what's one of the coolest things about you i think is uh you represent uh the best of mit like the spirit of mit there's um so i'm i'm so glad that i'm fortunate enough to be able to talk to you because um you know there's a kind of uh cynicism about academia in parts that i think is undeserved and that that there's a you know mit of course but academic institutions is a sacred place where ideas can flourish and just in the same very way that you're talking about is both kindness and uh curiosity and that like that weird thing that happens when a bunch of curious descendants of apes get together and just like get excited and this this uh uh ripple effect that happens i mean that's the most beautiful aspect of mit people might think like competition and grants and like uh position like you said the rat race but like underneath it all is is these curious human beings inspiring younger human beings and there's this uh ripple effect that happens and i'm so glad that i mean i'm glad that you that i get a chance to record this because it inspires so many other students and so many other people uh to do the same to embrace the the inner curious creature that's not about the race so let's talk about the negatives let's talk about no no no i'm serious i'm serious wait you know you have to embrace the good and the bad so let's talk about the negative as degree comes up let's address it um so why do people want positions of power why do people want you know more money more power more this more that remember the part where i was saying if you know who you are what other people think about you it makes no difference to you it only teaches you about them many people feel um define themselves they feel instantiated through the eyes of others so being in a position of power makes them feel better about themselves who knows what other kind of struggles they might have that creates that need to feel better about themselves but they have a bunch of struggles and everybody has a bunch of struggles and every time i see somebody behaving poorly i'm basically thinking well they're in a tough spot right now and and it's okay you know i can i can kind of see how i would behave badly in other circumstances as well so i think if you take away that sort of having to prove yourself in the eyes of others life becomes so much easier so when i first became a professor at mit i started wearing adult clothes i had my like you know i mean before i became a serious person i i basically had you know i would i would always like go around in my rollerblades and my shorts and a t-shirt and eventually i was a professional like oh i bought all these khaki pants and you know this nice like you know shirts with like you know whatever they call it the patterns and i was like you know dressing with my nice belt every day showing up and then a few months later i was like i can't stand it and i just went back to my rollerblades and my t-shirts and my shirts and it was this struggle of sort of not feeling that i fit in i was so intimidated by all of my colleagues like just watching their incredible achievements like persons next to me and the person you know the floor below me i was like oh my god like they clearly made a mistake what the heck am i doing here how will i ever live up to these people's standards and um eventually you grow up to realize that the way that i i grew up to realize that the way that other people perceived my work was very similar to the way that i perceived other people's work as flawless i knew all of the flaws in my work i knew the limitations i knew what i hadn't managed to achieve and what i saw was maybe a third of the way of what i was trying to achieve and i saw everything as flawed what they saw was what i had achieved they didn't see what i hadn't achieved they only saw the one-third down which was pretty good in their eyes so they all respected me and i was feeling miserable about myself i was like i'm not worthy and i think that this is a cognitive problem that we have we kind of um it's kind of like when we're talking about artificial general intelligence agi of sort of we kind of have this definition that anything that machines can do is not intelligent right and anything that they can't do is intelligent therefore we narrow in our narrow narrow the field of what intelligence truly means and as soon as machine learning not intelligent anymore i feel like i was doing the same thing with myself as soon as i could solve something it was the kind of thing that a kid like me could solve and therefore it was kind of easy but to the others it seemed hard yeah but to me it seemed easy so it was this kind of thing that everything that my colleagues were doing seemed impossible to me but everything that i was doing seemed impossible to them so it was that realization that sort of made me mature into sort of a not more confident but more comfortable human being can you actually linger on that a little bit i mean you mentioned minsky remember he said something in an interview where he said the secret to his um like the way he approached life was to never be happy with anything he did so there's a something powerful as a motivator to to uh doing exactly what you're saying which is everything you've achieved to see that as easy and unimpressive what do you do with that because clearly that's a i think useful thing i think i've kind of matured past that and i think the maturity past that is to sort of accept what it is and accept that it has helped others build onto it and therefore advance human knowledge so it's very easy to sort of fall into the trap of oh everything i've done is crap what i told you last time is that i always tell my students that our best work is ahead of us and i think that's more of my mindset that's a beautiful way to put it exactly what we've done is it's great it's great for the time and it'll become obsolete in 30 years yeah not we can we are doing even better we're doing it exactly so basically our next work will just strive and and again you can't you can't let the perfect be the enemy of the good at some point you have to rap i was having a meeting with my student yesterday and it was like listen we know this is not perfect but it's way better than anything that's ever been done before you know how to improve it but if you try to your paper is never going to get published so so it you know there's this balance of we're already at the top of the field get it out and then you work on the next improvement and in my experience this has never happened we've never actually worked on the next improvement and that's okay it didn't make a difference because you're basically putting a new stepping stone that others will be able to step on and surpass you my advisor in grad school would basically tell me manolis let others write the second paper in that field just write the first one move on move on to the next field you don't want to be writing the second and the third and the fourth and the fifth paper in the same field just it's very shocking to a student to hear that because i was like i was at the top of my game i was owning that field and i published the first paper i'm like i'm ready for two and three and four he's like move on just let it be and i was like whoa and it's so liberating to sort of not have to surpass everyone but just just put your little stepping stone out there and others will step on it and put their own stones further and eventually cross a bigger river than if you try to sort of make a giant leap all at once so you need both beautifully put so the funny thing is uh i've uh i believe i closed the previous episode with a darwin quote about uh the power of poetry and music and life i think your quote and again i only heard once was darwin basically saying if i were to live life again next time i would read more poetry and something about art every week or something like that yeah yeah it's so interesting for somebody who studied uh life at a very cold i would say genetic level to say that yeah the the highest form of living is is the art but like on that which made me realize that you write poetry and i uh um forced you or maybe convinced you somehow to uh to maybe share if it's possible if it's okay some of uh the poetry you've written yourself in your life so um again being greek a lot of my poems have been pretty miserable and uh i always like to say that it's very hard for me to write a poem without when i'm happy and i just have to be in a state of deep despair in order to write poems but the first poem i ever wrote was in uh english class i was i'm in greek i grew up in kris but i was in a french high school and i was taking english as a foreign language so the english teacher basically asked us to write a poem in english so this is basically what uh what i'm going to embarrass myself and read from my 16 year old self many many years ago can you give a little bit more context about who you were in this moment so like just so so here's what's really interesting in terms of growing up how do we grow up um it's very difficult to grow up if you're in the same school going from one class to the other and all your friends know you inside out it's very difficult to change it's very difficult to to grow up because they have a certain set of expectations for who you are and for how you're going to behave so in in many ways we kind of tend to get set in our ways and not change very much i think something that helped me grow up is that when i was 11 years old i was a kid in greece in primary school when i was 12 years old i was a kid in greece in a you know first year of high school when i was 13 i was in france so basically moved countries and schools the next year i moved schools again because it was a transition in the french educational system from one school to the next the next year after that my family moved to new york in a french high school there and then the next day after that i'm moving to mit uh so basically between 11 and 19 every single year i actually had the opportunity to grow i was not held by people who knew me and i could reinvent myself or reshape myself or reshape my you know sort of personality my emotions my you know as i was growing up especially in such a transformative time of a kid's life from 11 to 17. okay first of all it's so powerful that you think of it that way did you think of it that way at the moment because it's kind of a source you said an opportunity to grow it's kind of suffering i mean you're being torn away from the thing you know into a thing you don't know so when we moved from south france to new york i was pissed i was pissed i i was taking these long bike rides in the countryside jumping in friends swimming pools and i had all these wonderful friendships going downtown and just staying by the fountains in the dim lit streets of exxon provence in the south of france it was magical and suddenly i moved to new york city a city of cement of ugliness like trash in the streets and every corner is horrible snow everywhere having never seen snow or like real snow in my life i moved from athens to south france to southern new york so i was pissed but whether i saw it as an opportunity for growth i don't think so i don't think that i was that self-reflective it was just only now you see it this way i i saw it like that probably pretty early on but not during those transitions so basically during this transition i was just a kid being a kid you know and um maybe the time that i started seeing it that way was maybe when i decided to stay at mit as a professor after having been there as a student and i kind of saw the struggle of getting professors to not see you as a kid when they're your peers and i was very flattered when one of my uh friends basically told me oh i remember you in recitation when you first asked me a question i said wow this kid i'll pay attention one day it'll be a pier so so it's it's you know certainly my perception was that many of them could not see me as anything but a kid but it turns out that some of them saw me as something different than a kid even before i was actually their colleague so it's it's kind of an interesting place because what i like to say about mit is that people treat you as equal no matter what stage and they respect you for what you say not for who you are when you're saying it and if i'm wrong my students will tell me they will have no reservation to just be bluntly you know sorry i don't agree with that yeah i mean the the beautiful thing uh about you sorry to to put it this way is uh you know maybe people who weren't familiar with your work beforehand might think uh like you might not realize that you're a world-class scientist leads a large group and so on they because there's a youthful nature to you that it's i mean you talk like a like a first like an undergrad you know with the excitement and the fresh eyes and the sort of excitement about the world and that's first of all super contagious and beautiful you know it's easy to sort of fall into uh behaving seriously because then people kind of um start putting you on a pedestal more into a position of power you you want to sort of act like you're in a position of power as opposed to allowing yourself to be lost in the just the curiosity the the childish view of the world which is just this open-eyed love of knowledge and that was the transition that i was describing when i decided to go back to my rollerblades and t-shirt and baseball cap basically um you know when i when i met my first postdoc uh it was basically you know he was interviewing for postdocs at mit he already had several first author papers to his name in top journals and my friend julia basically introduced me to to to alex stark who basically was interviewing at the time with rick young and with eric lander just like these massive names in the field and i was just a first-year faculty person with you know zero credibility and she basically says oh there's this friend of mine alex who's visiting he's also german you know he wanted to meet you i'm like oh sounds great i'd love to talk science i show up we sit at the amphitheater in stata uh you know i basically arrive in my rollerblades you know jump a few steps sit down wearing my blades we're having this awesome conversation about science and about gene regulation and how the whole thing works and sort of you know my perspective and his perspective or just bouncing ideas for 30 minutes and then i just dash off to my next meeting and he basically emails me afterwards and i was giving him advice about how to interview with eric lander how to interview with rick young and how to sort of get a position with them and then after uh after a while he emails me saying i would love to become a postdoc in your group i'm like what are you kidding me like wow so so uh he basically didn't care that i would wear roller blades and t-shirt all he cared about was my ideas and sort of embracing the me with the childhood excitement about science was basically what attracted him it wasn't the wow this guy runs a big lab or this and that he was just like i like his ideas i want to work with him that by the way folks is the best of mit that's what mit stands for so that's a beaut that's a beautiful story but take me back to the poem and where did this poem come from what now where's your mind's set so who's the 17 16 year old kid manolas so uh again i've i've just seen snow for the first time and i'm is this new york this is new york so i'm you know maybe that's where the sadness in the poem comes from but anyway we're asked in class to write an assignment this is my third language i'm not very good at it so pardon me but here's what i wrote children dance now all in row children laughing at the snow but in times endless flow children sooner or later grow men are mortal we go by if we know it we may cry but i thought a love so sweet was immortal was so deep there i told you darling sweet that forever love would keep blossomed spring and summer shined then blue autumn winter died one year passed but the clouds still remember all our vows never faked and never lied all we did was stare and smile all alone sitting down to the snow we made our vow but you told me you were right birds who love are birds who cry now with laughter children play yet the sky is so grey even if the snow seems bright without you have lost their light sun that sang and moon that smiled all the stars have ceased to shine all of nature drew its grace found its light within your face now you're gone and won't return let the snow and my heart burn there's a greek that's beautiful that's beautiful by the way and and the rhyming the musicality there's a there's a both of simplicity i'm language no no no but like i so i really enjoy like robert frost poems i don't mean simplicity so what a bad way and then a negative way again it's very weird to analyze your own poem but i think it captures the simplicity of youth and the way that it kind of starts with children dance line only though it basically and it kind of shows that snow can be interpreted first in the first verse as a happy thing and then in the end you know now with laughter children play i'm like now i've grown basically it's it's this transformation that we're actually talking about this whole men are mortal we go by i'm sort of you know you're saying are you comfortable with growing old i'm like duh i was i was since i was 16. yeah and what's really interesting is that you know again when i was 12 years old in our summer house in greece i remember sort of telling my sister my outlook that i would have as a father for how to bring up my own kids so it's very weird that i've always sort of seen the full path from you know a kid when you were young yeah i don't know if you you like this johnny mitchell song i've looked at clouds from both sides now from up and down and still somehow it's those illusions i recall it yeah it's clouds illusions i recall i really don't know clouds at all so it's it's really beautiful so so i think the johnny mitchell song which again i heard for the first time much much after this um and i wouldn't even compare this to that but what johnny mitch is saying that song is that you can see life from two perspectives you can see the good or the bad in both you know in everything you see and i think that's the allegory of snow right now you can see snow as this bright white wonderful thing or you can see snow as this miserable you know gray thing so that sort of and what i like about the last verse now with laughter children play is that it's a recall to the first one where i was the kid enjoying careless life and eventually was making promises that something would be forever and i think part of that is also the loss of my friendships in france of being in new york now and sort of everything is gray and you know even though the snow seems bright without you have lost their light some that sang and moon that's mild so it's this um this concept that if you lose your love the same thing can be perceived in a very different way let me ask you this because somebody wrote me this long email and i think you're the perfect person to ask this um you mentioned love from a genetic perspective what what's what is it what what do you make of love why why are we why do we humans fall in love in your own life why did you fall in love you know the email that was written to me was you always talk about mortality and fear of mortality but you don't ask about love some i don't know if there's some thoughts you could give about the role of love in your own life or the role of life the role of love in human life in general i think love in many ways defines my life it's basically i like to say that i'm a human first and a professor second and uh i think this passion for life this passion for you know everything around us i mean the only way to describe that is love it's basically you know embracing your you know emotional self embracing the you know the [Music] the the non brainiac in you embracing the sort of intangible the not very well defined and even in my on my own research i'm just very passionate about everything i do and you know there's a certain passion that comes through and what i'm sorry again being greek the etymology of the word passion what was passion passion is suffering the etymology when we talk about the passion of the christ it's the suffering yeah and in the greek version of that word pathos like pathology pathos is deep suffering it's the concept and someone who's sympathetic sympathetic means suffering together experiencing emotions together so it's funny that you ask me about love and i respond with passion passion for life passion for research passion for my family for my children for you know so um there's there's a certain passion that uh defines me and everything else follows rather than the other way around i'm not first thinking with my brain what is the most impactful people we could write and then going after that i'm thinking with my heart what am i passionate about what drives me which just like you know makes me take and that's a beautiful way to live but i i love it how the greek part of you just kind of connects it to the suffering so if you could remove the suffering no no no no when i say suffering i don't mean suffering as in being miserable i mean suffering as in being emotionally invested in something remember i mean again if you if you look at this poem what is it saying it's saying birds who love are birds who cry right it's that's the very definition of love exposing your fragility if you're not afraid of suffering you don't fall in love as soon as you hold back you protect you shield your heart no love can enter so there's this uh simon garfunkel song i am a rock i am an island and a rock feels no pain and an island never cries so again there's some aspect of that into this poem the you know the fact that um you know but you told me you know there i told you darling sweet that forever love would keep is this intermediate thing and then there's a recall but you told me you were right birds could love or burst who cry so it basically says that love is the fragility that you're willing to give to another person it's opening up your uh vulnerable spots it's sort of accepting that there's no safety net you're just giving yourself fully and you're ready to be hurt so you've already been way too kind with your time but i'm gonna force you to stay here just a few minutes longer as we're talking about uh goodbyes you have a really nice other poem here about goodbyes can i force you to read it as well oh twist my arm twist my arm so um and the next poem was written uh specifically for our high school yearbook so uh another poem written on demand the rest of them are just so miserable written by pure you know sadness and melancholy but this one was also written on demand and it was basically um saying goodbye as it's appropriate right now to my friends and sort of again reflecting this whole journey and transformation through life and also i think showing a little bit of introspection about how we kind of had it easy in high school and we're about to go into rougher waters so the title is actually the tidewaters and it's an analogy on that so here it goes all this was another lake where some rest we sailer stake water's calm and full of fish we'll find there what we wish some seek fruit and others feast some of us just look for peace some find fresh other love some seek both and neither have we were different when we came it's his own story and fame different people had we been different cultures had we seen different nature different faiths each unlike all in this place we had faced success defeat that in one lake came to meet there the orders that we followed and the pride that we swallowed made us one but not the same joined us strangers who there came sooner later groups were made tribes where differences will fade some attached more or less others fought and made a mess but again we have to go what for where to we don't know still we know it we will try there to rush to flee to fly there'll be some who wish to stay but will carry on away we will continue on our journey as we came here strong yet lonely from the lake a river flows from the river many goals on that river we will race each will try to find his pace in that scene the sailors face their first fear defeat disgrace here and there comes out a face that the waters soon embrace some get lucky find their way others sink beneath the waves in this race we will part some will settle near the start some set goals beyond the stars because the river carries far you should know in what we've done the hard part is still to come so i'll have to say goodbye don't you worry i won't cry neither will they those who try till the end to keep their pride but please know dearest friends who are always there to mend i will always need your hand i will miss you till the end i don't think there's a better way to end it manolas like i said last time you're one of the most special people at mit one of the most special people in boston and whatever mental force field that you're applying and saying that boston is the best city in the world might be the best university in the world you're actually making it happen so thank you so much for talking to his huge honor thank you so much it's been a pleasure thanks for listening to this conversation with manolas kellis and thank you to our sponsors public goods magic spoon and expressvpn please check out these sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from another well-known greek alexander iii of macedonia commonly known as alexander the great there is nothing impossible to him who will try thank you for listening and hope to see you next time |
David Fravor: UFOs, Aliens, Fighter Jets, and Aerospace Engineering | Lex Fridman Podcast #122 | the following is a conversation with commander david fravor who was a navy pilot for 18 years and commander of the strike fighter squadron 41 also known as the black aces a squadron of 12 airplanes consisting of several hundred people he's also famously one of the people who with his own eyes saw and chased a ufo an identified flying object in 2004 that is referred to as the tic tac and the incident more formally referred to as the uss nimitz ufo incident his story corroborated by several other pilots from my perspective as a curious scientist and an open-minded human being is the most credible sighting of a ufo in history at least that i'm aware of he's a humble fascinating and fun human being to talk to i put out a call for questions on reddit and many other places and tried to ask as many of the questions that people posted as i could and overall i really enjoyed this conversation and i'm sure if the world wants us to and if there's more questions to be had we'll talk on this podcast again quick summary of the sponsors athletic greens expressvpn and better help please check out the sponsors in the description to get a discount and to support this podcast as a side note let me say that the world of ufos and uaps unidentified aerial phenomena and aliens in general is foreign to me because of the high ratio of outlandish conspiracy theorists to actual hard evidence i'm a scientist first and foremost but an open-minded one often looking and thinking outside the box i'm often disheartened by the closed-mindedness of the scientific community and in equal part i'm disheartened by the lack of rigor and basic scientific inquiry and study on the part of the conspiracy theorists i believe there's a line somewhere between the two extremes that more inquisitive minds should walk i think we humans know very little about our world what's up there among the stars and the nature of reality and the nature of our very own minds the path to understanding can only be walked humbly the very idea that there is a possibility that david witnessed a piece of technology whether human made or alien made that moved in the way it did should be inspiring to every scientist and engineer on this earth there may be propulsion and energy systems yet to be discovered that once understood and mastered will put distant galaxies within reach of us human beings paradigm shifts in science and leaps and understanding can only happen i think if we open our eyes and allow ourselves to dream to think from first principles and remove the constraints and innovation placed on us by the scientific conventions and assumptions of prior generations if you enjoy this thing subscribe on youtube review the five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and no ads in the middle more and more i'm trying to make these ad reads unique and interesting and less adzy more personal but i give you timestamps so you can skip but still please do check out the sponsors by clicking the links in the description it is honestly the best way to support this podcast this show is brought to you by athletic greens the all-in-one daily drink to support health and performance i drink it every day to make sure i'm not missing any of the nutrition i need now let me take a hard left turn and talk about fasting i fast often sometimes intermittent fasting of 16 hours and then an eight hour eating period of two meals sometimes 24 hours that's one dinner to the next i've been even considering doing a 48 or 72 hour fast that some people i look up to have done people who have done it tell me that outside of weight loss and the different health benefits it's a chance to meditate on the finiteness of life not eating somehow is a reminder that we're immortal that every day is precious i certainly experienced this with the 24-hour fast and i think it goes even deeper for the 48 72 and even week-long fasts anyway i always break my fast with athletic greens it's delicious refreshing just makes me feel good so go to athleticgreens.com lex to claim a special offer a free vitamin d for a year again go to uh threaded greens.com lex to get free stuff and to support this podcast this show is also sponsored by expressvpn get it at expressvpn.comspod to get a discount you probably know there's a show called the office that i fell in love with first with the british version with ricky gervais and then the american version with steve carell expressvpn lets you pretend your location is somewhere else choosing from nearly 100 different countries and then watch one of the nine totally different other versions of the office and other countries also it protects you when you do shady things on the internet that you shouldn't be doing like checking the website of this very podcast that for some reason was not available in russia for a long time not sure if it still is but if it isn't you can use expressvpn to access it i think of expressvpn like a pirate ship and regular vpn free life as a boring cruise from one place to another with no excitement in between choose wisely my friends again get it on any device at expressvpn.com flexbod to get an extra three months free and to support this podcast this show is sponsored by betterhelp spelled h-e-l-p help like you would try to spell if you were on a deserted island and trying to get an airplane to notice you check it out at betterhelp.com lex they figure out what you need and match you with a licensed professional therapist in under 48 hours you can communicate by text anytime and schedule weekly audio and video sessions now hard left turn let me talk about desert islands whatever you think of it i love the movie castaway with tom hanks and the idea of spending time on an island alone with potentially no hope the natural question is if i could what would i bring to this island the answer is complicated but let me pick one thing the first thing that popped into my crazy mind which is the introduction to algorithms book also called clrs for the first letters of the last name of its four authors i find algorithms beautiful like a little toolbox for a simple world inside computers when the real world outside is an impossible chaotic mess i would love pondering the puzzles in that book for months far away from human civilization anyway check out betterhelp betterhelp.comlex to get a discount and to support this podcast and now finally here's my conversation with david fraver you're a graduate of the navy fighter weapons school yeah i am better known as top gun so yeah let me let me ask the most ridiculous question how realistic is the movie top gun so it's funny we used to joke and a friend of mine who was a top cut instructor uh said this there's two things in the in the original top gun that are true that are very realistic one there is a place called top gun and number two is they do fly airplanes there other than that uh you know i went through in 97 uh class 497 and there's actually a log of every single person that's went through kind of like seal training you know there's a list so people because there's a lot of posers out there i was a navy seal no you weren't well i went to top gun you could actually go to top gun and matter of fact just to get a top gun patch the real patch uh you have to have gone there so a lot of the patches you see running around are not real there's the real ones are controlled the people that make them uh honor that and when you go in they look up your name if you want to get one they look up your name you just tell them they go okay here and i'll sell them to you if you are not on the list you ain't get no patch because it is it's it's it's a pretty big deal to go through but it's for me uh probably the best experiences of flying uh because everyone there is extremely competent it's it's very very challenging but it's what we all signed up to do so it's uh it's just the entire group that is when you want to be that you know that level uh you know where you go everyone really cares and everyone really wants to be good is it competitive like what was it in the movie or no it's when you go through it's you know it's if anything it's more of the students you know and then there's the instructor side and the instructor sides are really you know they're guys that you know they just chose to stay up and fallon and it's extremely uh difficult job uh because they have they have a very small tolerance for um not being good so they're briefs the guys when they give a lecture so let's just say there's a fighter employment lecture which is one of the hardest ones it takes about two days to give the fighter employment lecture um the guy who gives the lecture goes through multiple what they call a murder boards where he's scrutinized by his peers and he practices by the time they actually stand in front of a class they pretty much have their 250 powerpoint slides memorized and they don't even turn around they just click and they know them in order and they repeat the same thing over it's and it's standardized so they are extremely extremely standardized when you go through school and there's a reason for that because what they're doing is they're training so when you come out a top gun you're called a strike fighter weapons and tactics instructor okay so your sfti when you come out of that your job is to go usually to one of the weapons schools on the east or west coast and train the fleet squadrons and then you visit the squadrons and train and do upgrade rides and all that so there's a there's a reason that they are extremely particular when you go through the course it's it is literally one of the best things and it's not it's not a rank based thing because think oh navy you can come in as a you know like a an o4 lieutenant commander the lieutenants the hierarchy or at least to be i don't know how it is exactly today but i imagine it's the same the hierarchy is actually based on seniority at the school not necessarily ranked so when the the tactical decisions are made which are based on fact and and trying things out in the fallon ranges uh they set this the top x number of folks that have been there seniority wise is and i mean time wise uh are the ones that actually make the decision and when the door you may not agree but when the door opens and everyone comes out from the staff they all speak the same language it's and it has to be that way which is why the school has been so effective since it was founded so it's just a it's an incredible group of individuals so there's a bar of excellence that uh that the instructors demand well very much so and they're held to it so it's not a hey i'm now an instructor so i can do what i want there is a standard and they have to live up to that standard they have to and i mean every moment of every day uh so if they go someplace if they go from fallon and they come down and do they're called site visits where they come down and they'll come to la moore california which is where the west coast fighter wing is at for the navy and they go around and start flying sorties with the fleet squadrons to kind of pass on some of that knowledge that's that same high level of standard it's they can't just drop your guard because you wear the top gun patch and people know that and they wear light blue shirts so it's pretty easy to identify them when they're out there and you know and then everyone else who's been through the school including them have the patch on their sleeve so there's a standard that's expected when you come out of there so you're a navy pilot for 18 years yes can you briefly tell the story of your career as a pilot yeah um so you know first i was in i was enlisted i was a marine and then the marines actually sent me recommended me to go to the naval academy uh so it's always better to be lucky than good but i got to go to naval academy and i finished and i've had that dream to fly so when i got selected they've always dreamed of flying yeah since 1969 when i watched neil armstrong walk on the moon um i was at that point i asked my mom i remember watching it i was i was just prior to being five and i said wow yeah it's so cool mom and she said well you know they were all pilots and uh then at that point it was like i'm gonna be a pilot and if you knew me growing up because i was a little bit of a delinquent um people are just like yeah right i used to joke i'm gonna fly i'm gonna fly jets and i'm gonna drop bombs then and if people that knew me was a kid they'd be like yeah and they'd be like not a chance and then when i did i actually had a funny story and i'll get to it and i'll finish my career but i was at my cousin's wedding and uh we all grew up in the same neighborhood uh we kind of that italian side of the family that's how we grew up so it was my house right down the street is my cousin chad and right around the corner with my cousin ray and my aunts and uncles and stuff the guy two doors down from my and i was a paper boy in the neighborhoods they all knew me and uh i went to my cousin's wedding and he and mr race looks at me and he says david fravor i go mr race how are you doing you guys you fly jets top gun and all that i go yes sir i guess i figured he'd be in jail by now um it was kind of a to me it was a little bit of a badge of honor going on you know i kind of overcame that but uh what do you attribute that to so you i've heard you before and just now i'll say that uh it's better be it's better to be lucky than good and you you talk modestly about uh about just being lucky but if you were to describe your trajectory maybe in a way of advice like retrospectively uh how did you pull it off to be like to be truly a special person the easiest way is one never never take no don't let anyone put you down and say you can't do it or those i mean i knew i knew what i was capable of inside you know and if i really believe if you want something and you want to do something then you you can achieve it not in all cases like if i loved basketball and i really wanted to be in the nba there's a realism that says i'm five foot eight and i got like a really short vertical leap but i'm really not that good at basketball it's probably not ever going to happen no matter how hard i try and practice it's just the way it is or for me to be in the nfl i'm not fast you know i'm not that big it's just physically i'm incapable of doing that um but there's things that don't really tie to a true physical ability as far as size and strength but it's it's mental uh and i'm not saying you have to be a genius and super smart to be a fighter pilot matter of fact you don't it really comes down to the ability to think very quickly uh 80 solution is typically good enough because if you overthink it you're you're behind and then in an air-to-air fight that's what happens people try and overthink it and before you know it because it's happening so fast you don't have you can't get to the nth degree you know six decimal places eighty percent solution is good enough you build up a really strong gut for the 80 solution just yeah i'm a big believer in 80 percent solution i love that if you get 80 percent you can go and then you can always adjust which is exactly what like if you're fighting in bfm the 80 solution is it's like a chess game but it's a really really fast chess game where you go i'm doing this and then i know that if i do a maneuver if he's going to counter it correctly he should do a if he doesn't do a he does some degree less like b c d and then i know how bad his his error is and then i capitalize so my might i don't have to be perfect you know i have to go i need to go to 47 degrees nose high if i just kind of get above 40 then i'm good and i can watch how he reacts and then i can adjust for that and you and you continually work that problem and you chip away because if you start neutral you're just basically chipping away and gaining advantage advantage advantage till eventually you know and if you're really you know fighting you know just guns only rear quarter where you got to get behind the guy kind of world war ii dogfighting type stuff um then it's it's literally it's a it's a very very fast chess game that happens at you know 400 knots 300 knots depends so to get to be one of the rare individuals that uh are able to do that he just had the dream and didn't take no for an answer well you know you know part of it is family you know uh my dad was uh i used to call him a fire ready aim guy you know he'd smack me and then ask me what i did wrong yeah good parenting um back then you know i i joke and and people look because you know at times it was kind of tough you know because he can be pretty demanding but on the other side you know i probably needed to be reined in a little bit at times uh but then everyone else my family you know my mom was really awesome when i was a kid uh my uh my grandfather who is a big big part of it my mom's dad uh who he taught me a lot and you have a question there that we'll talk about uh about him but uh huge huge influence very very positive and a lot of the stuff that i do today and decisions are based on things that he taught me um and uh you know and i figured you know it was the first funeral i ever went to and it was uh it was about three miles long and church was overfilling and people were out he was a beer delivery guy dead serious and you go there someone asked who died the pope um so a lot of people love them so back to back to my career yeah the first question because i'm getting down on rabbit hole uh no i when i was at the i was gonna i was gonna stay in the marines i really wanted to go man i love the core i think it's uh of all services it's that one everything is in a ball and they're very very professional and it was a great great organization to join uh but i went out to the nimitz on my uh freshman cruise after your freshman year at the naval academy you go out on a ship and you you're an enlisted person you get to experience that half when i already was enlisted so it's fine with me because it comes up a lot would you mind saying what the nimitz is what a ship is like yeah so nimitz is uh an aircraft carrier so it's uh four and a half acres of sovereign u.s territory that floats around the u.s oceans does it have weapons on it uh the air wing is really the weapons it does have defensive weapons but for the most part it's a giant moving airport is what it is so i was out there watching the airplanes land and take off and i'm like oh and the squadrons that were out there one of the squadrons was a vf-41 and a 14 squadron vf-84 an f-14 squadron and then a couple of a6 squadrons and we actually ended up part pairing up and hanging out with some of the a6 pilots and bn's so it was really a neat experience and i said i want to do that and the way to do it was to not to to go in the navy because there are marine squadrons that go out to the aircraft carriers but most of them are land-based you know to support the marines because they're that that unit that whole unit you know the marine corps is that one service has it all and so when i graduated and i got to uh you know i worked hard through primary and that's where you know i knew missy uh we were actually went through together missy cummings uh we went through primary together and then uh i went to kings we all selected the same time i went to kingsville there was another guy scott wiedemeyer uh the three of us so i went to kingsville scott went to beeville and missy went to meridian so the three of us that we had all went through we got we selected out of primary together we all ended up going jets and that's that's how besides from school i knew her at school too the long story i got done uh got winged it took me two years to the day from the time i graduated the naval academy until i got my wings and uh through some luck i ended up getting asics's on the west coast which is a side-by-side bomber so it's a pilot on the left seat and the bombardier navigators on the right seat it was built in the 60s it is all weather and it flies low at night it's got a terrain mapping radar how many i guess is that a good term to use fighter jets as a broad category for for the public yeah that's probably how many fighter jets are side by side like that that was uh in the navy that was the only one the air force the f-111 was a side-by-side but the navy it was the a6 and then there's the ea6b which is a derivative of that and now that those are all gone the a6b's just went away a few years ago and now the e18g growler is the replacement for the a6b there was never a replacement for the a6 that i flew it really became the f-18 which the a6 could go quite a bit further distance wise by fuel than the hornet and uh the horn is the f-18 yeah is there usually two people in the plane but they're usually like in front and behind in a the modern two-seaters yes uh but most of the tactical airplanes in the world today are single seat so you can see just one person one person with the exception of i'll probably someone will yell at me but really with the exception of the f-15e strike eagle and the f-18f super hornet which is the f is a two-seater and the g is also a two-seater but it's more of an electronic attack by say full-up fighter bomber so most of the time that you've flown in your like i said 18-year career is was it two-seater i was about half and half so i started off an a6 was a two-seater then i went to single-seat f-18s and i flew those all the way up until 2000 and let me think 2001 to the end of 2001 and then i shifted over and started flying the super hornets and i've flown both of those the ease and the s but i deployed when i had command of vfa41 i had the two seat they were f squadron so you eventually ended up commanding the the strike fighter squadron i love the the name the black aces what uh is there some parts of that journey that are amazing parts of it that are tough that kind of stand out to me it was one it was a huge honor uh and i got to serve with uh you know i got pulled up because the the guy who the the people that are exos because we fleet up you go from the number two guy to the number one guy so the exo becomes the ceo so the executive officer becomes the commanding officer so i had worked with uh now soon to be vice admiral weitzel uh was the he was commander whitefield at the time was the exo and he really wanted because he knew there was a little bit of a problem when the super hornets came into lamore lamore had been a single seat fighter community since the forever and now all of a sudden you've got the f-18f coming in which has the weapon systems operators in the back that are not pilots they're weapon systems operators and there's a difference and kenny is a weapon systems operator and uh kenny knew because of my a6 background that i have a switch that i can go one seat 2c1 c2c because when you fly 2c there's a lot of stuff that the pilot will offload and take the advantage of the weapon systems operator and it's not that one plus one equals two in that environment because it really there's a huge amount of capabilities that the single seat has and the autonomy that comes for the ability to make decisions quickly and how well the airplane flies but it does it does equal more than one and i would say that one plus one with two people as well as a minimum of 1.5 because you've got an extra head you've got extra eyes you've got someone that can monitor systems the airplanes can do two things at once i mean there's an incredible amount of capability that we add when we do that can we just pause on that just for me from like a human factors perspective and also an ai perspective what's how difficult uh so there's like when there's two people there's also a third person that's the ai part there's some level of automation like autopilot maybe that's correct maybe you can kind of talk about the psychology of like you said making decisions really quick 80 how do you deal with another brain working with you and then also the automation is there interesting interplay that you get to learn and also as that change throughout your career i imagine it got gotten better in terms of the automation or perhaps not well i can tell you so that let's say there's a bunch of stars this is no this is this is good this is good and this is i'm enjoying this because now we actually get to talk about something other than a tic tac so um so let's start with the a6 the a6 was really an analog airplane that was built in the 60s all right and there's been studies done on the crew coordination which is the interaction between the pilot and the bombardier navigator so we would fly low at night in the mountains so i was stationed up in whidbey island washington so you've got the cascades and incredible uh amount of time and we would get in the simulators because unlike normally people think terrain following and there's the radars the 111 the b1 has a system like this but it'll the radar can see and it'll fly it basically flies a straight line so it goes up and over mountains and back down and up and over mountains where the a6 was really manual so you do this low-level routes where you're gonna you're gonna fly in the mountains at night you're gonna be at you know 500 to 1000 feet above the ground ripping through like fog layers because you don't need to see outside you're you're literally flying a little tv screen and a radar what are you looking at most of the time so you just as a screen it's this really primitive if you look at it now what we did you'd think wow that was crazy but it was really fun so is it similar to like the flair stuff is that is no are you is it this thing is totally radar based now the airplane had a flear ball it's a target recognition and multi-sensor it's called a tram um you're looking at like basically like dots of hard objects no actually what it is is the the bombardier navigator had a radar and he was getting raw feed off of a pulse radar in front okay so it's just basically mapping the mountain so if you look at a mountain on a radar and you're coming up on it the front side is going to be it's going to give you a really bright return and on the back side it's just going to be a giant shadow because you can't see on the other side so the bomb of your navigators would do that and we they would have charts and they could shade their charts knowing that hey if we turn a little bit left here we can get in this valley we can sneak up this valley and then go around the back side of the mountain which is what the airplane would do and so and sorry to interrupt i'm going to just keep asking dumb questions i apologize but the pilot can you can you at a high level say what the pilot does versus the bomb bombardier uh so you're you're actually just control i'm flying the jet i have the throttles the stick and i have a uh it's about a probably a four inch or six inch wide by maybe four inches five inches high it looks like it's literally a crt that's how old it is a crt screen and what it would do what the radar would do is the the the bombardier navigator is looking at his radar and he's looking out about 12 and a half miles in front of the airplane so he has the range really scoped down because the radar can see a lot further he's looking at about 12 and a half miles when we're in the terrain mode where we're dodging mountains and stuff and what the pilot has is there's they're called range bins and there's eight of them so the very far range bin is the 12 and a half mile you know and the closest range been it's a thing and it'll be like between like a half a mile and or a quarter mile to three quarters of a mile the next one might be three quarters of a mile to two miles and then it just keeps going out like that so if there's a mountain for let's say we're on a flat plain and there's a mountain out in the distance at 15 miles and we we're just driving right at it so when we get to the point where it hits 12 and a half miles where the radar is going to see it on his scope my 12th my range bin for that would pop up and it would show like a big bump like a mountain and then as i got closer to it the next arrangement would pop up and show it and i could see that that bump was moving towards me and then if i turned a little bit you know to go over here i'd see the mountain go over to the right hand side and i could do that but it wasn't like a video game it was it's literally like if you think of the original ataris yeah but you build up i imagine that you start to get uh a really deep sense of like the actual three 3d environment based on that little atari's it's solid you're exactly right and you have to you have to train so there's been studies a matter of fact a lot of the basis and people probably argue with me but it's true there were studies done watching asics crews in our simulators we called it the wist the weapon systems trainer and it was not even a motion it just kind of sat there and you just you could fly these things they had terrain that they would inject into the system uh but the crew coordination so you get so my first uh my first fleet bombardier navigator who who i'll name him his name's crusado uh he's uh works at apple uh pretty high up bro mit grad i think computer engineering he's scary smart so chris could really work and matter of fact all the guys that flew us so there's another guy matt who also worked at apple who's now at sap we did our first night traps together the bond between us i mean it's one of those things that you just you're never going to forget but chris and i when we started flying together we were actually the most junior crew in the squadron uh we'd spent a lot of time training and and and chris was amazing at how he could work the system uh one because he was extremely brilliant and he was had that inquisitive mind of oh we could do all these different things and there's all these degradation modes but we spent a lot of time to see how good we could actually get because and it's you almost talk in partial so as the bn is looking at his radar scope chris would say i've got rising terrain that's just what they say showing rising terrain at 12 miles and i'd see the little bump and i'd say got it this is going to go to your question on the autonomy and how you work with two heads yes so when you first get together the interaction it's it's it's almost like you have to rehearse it you have to know and you talk in full senses the more and more we fly together chris could go i'm showing and he'd get like rising out and before he finished i'd say i've got it so you end up starting to talk in partials because i have to trust him like i mean there can be no i can have no doubt that he knows how to do his job because i'm literally looking at this little scope that's not giving me this continuous picture of that mountain moving remember the mountain's here and then it's going to pop up here and then it's going to pop up here because there's gaps in the coverage on how the system was set up remember it's an analog system to where he is telling me like i can't see all the way to the left and he he's got a wider scope on the radar but my screen doesn't show that so he's telling me start a left turn how to avoid a hard turn you know and we would do that so my channel this is all happening quick very quick well you're doing we we would typically fly between 420 and 480 knots of ground 70 miles an hour uh well 427 miles a minute okay or eight months between seven and eight miles a minute is what you're flying as fast at night i mean i broke out of clouds i mean i remember him and i flying we're on it's the ir it's called an ir route uh an instrument route that's low they're all around the country there's ir344 that we used to fly which would coast in off of or you'd fly from the land you go out over the ocean turn around and then you could practice actually coming in on a coastline and we were flying and we ended up in the clouds keep in mind we're between 500 and 1000 feet in the mountains and we're in the clouds like you can't see anything and it had to turn off our red lights that flash you know they're called the anti-collision lights because it was reflecting off the clouds and it starts to bother you just gets annoying so i turned it off and we we're flying we're flying we're flying we break out of that coastal marine layer and poof we break out and it's it's a decent night and this is right by mount st helens this is kind of where we're coming in so we're coming in from the east and we're just north of mount st helens is where the route goes and you look up you know because you can kind of see the silhouette of this mountain that's right next to you but you're flying along you're just like you know you gotta trust and you can see houses you can see the lights they're above you we're literally below people's houses flying down these valleys and stuff so just incredible experience so when you take that and then you move into an f-18f so now we're into modern technology that was actually built in this century uh uh and you're flying so now you know the wizzo is behind us and we're not doing those night low levels but that same type of crew coordination that has to happen because what you're doing is you're sharing the load so most of the communications that go out of the airplane the wizzo does all the talk and he's got actually he uses the feet that's the weapon systems operator in the back of an f-18f so he's going to run well the radar kind of runs itself now but we have a situational awareness display and it's it's linked to all the other errors just like curiosity what's the situational awareness display because that term comes up a lot think of it as uh think of it as a god's eye view so if you have a the back of the super hornet has well the block twos has about an eight by ten display for the wizzos um that they can look at the pilots is smaller it's down between us it's a six by six between his legs and they're they're getting ready to redesign that boeing is but when you look it'd be like if you put your airplane and you're looking down so all the stuff like if your radar seeing bad guys out in front of you be like looking down going oh i'm right here and now there's bad guys out here and my wingman is over here and it shows everything it's just like it gives you you can look at that display and go oh okay i can see where everything's at i can see if one guy's trying to target another guy it shows you all this it's an incredible amount of knowledge that comes up for the crews to maintain uh the the overall picture of what's going on big picture sense of what's going on because it's happening so fast and this is with that autonomy piece this is the third brain so we're all looking at it and the third brain is doing fusion it's pulling stuff together going oh this is all this guy this is this guy this this guy it's sending it out through the link so all the airplanes are talking to each other through this digital network you know that we don't even see it just says that airplane says hey i'm over here and it tells us and we go oh he's right there and then we can go he's his airplane says oh i'm looking at this airplane this bad guy and it shows us oh he's he's over there and he's looking at this guy i mean it's an incredible amount of uh visual intake because your eye you can hear a lot but when you look down at stuff it's uh you know you can solve the picture really quick the third brain is doing the sensor fusion uh the integration of the different sensors and gives you a big picture view what about the control like is there and i apologize as if this is a dumb question but you know people use the high level term of autopilot how much is there let's use a loose term of ai how much automation is there how much ai is there in helping you control there um the ai piece would be more of a control loop because the digital flight controls so the airplane actually they had to make the airplane easier to fly and when i say easy it's relative because people go i could do it because i did it on flight sim it's real life is a lot different in flight sim you have no apparent fear of death you'll do things in simulator that you would never do in real life but uh the the autonomy in the airplane to allow you to manage i mean because you think about it you've got a radar that's feeding you data you've got a targeting pod that's feeding you data all that stuff is hooked to your head because you've got a joint helmet mounted queuing system on that basically maps the magnetic field in the cockpit so it can tell where your heads at looking so if i turn my head to the right the radar will actually look to the right the targeting flare will look to the right and oh by the way the backseater has a helmet on too so he can look to the left and he can do things so depending on what sensor he's controlling so if he's got control of the targeting pod and he looks left the targeting pod looks left but if i have something where i want to lock a guy up that i don't see that maybe the radar didn't see but i can get over and now point the radar you know get the because it's a it's a phase array radar now it doesn't really scan uh there's there's all kinds of cool stuff that uh that technology uh brings because if you just if you went back 30 years and said hey or 40 years ago and said hey we're gonna have this helmet and you're gonna be able to slew everything to your head and i don't mean a mechanical setup but i mean literally you're just gonna map magnetic resonance and go oh look and then i can i can literally slew my sensors this fast and then mash a button and transfer you know high quality coordinates from a system into a joint you know a jdam which is a joint direct attack munition that is the gps bombs that you see all the time and then let that thing fly and i'm i'm solving this problem in seconds by minutes or hey i got it we're gonna have to menstruate coordinates and you know you bring back the data and then they do all the targeting for it and then they send another group out to get it instead of all that now it's that fast so there's a okay i mean we probably don't have enough time to talk about the beautiful fusion of mines that happens when two people are flying controlling the plane but at a high level this is a really interesting question for people who don't know what they're talking about like me which is what is the difference between a human being and an ai system like what can what is the ceiling of a current ai technology for controlling the plane like how much does the human contribute uh is it possible to have automated flight for example like what is the hardest part about flying that a human does expertly that an ai system cannot in warfare situations in in flying a fighter jet lane so i would say systems are usually black and white when you write the algorithm for an ai system it's it's it's it's really it's basically you're taking thought and turning it into a giant math problem is really what you're doing right so you've got this logical math problem math problems are there's there's there's a line it says i can or i can't and it's a it's a very finite line you know but you can go up to the line where a human we all have gray areas where we go maybe yeah i'll try it um so he just can operate within that gray so if you took if you take an airplane and say and i'll just take a hornet for a while a super horn it doesn't matter any airplane and you go here is the flight performance model of the airplane so if you know an uh an em diagram is the energy so it basically says the airplane can fly as slow as this it can go as fast as this it can pull this many g's force of gravity you know so one two three four five six seven and then based on the airfoil design and everything else and how it can pull here's how it's going to fly you know because it's really physics based well if you depending on how you write the ai but typically ai you don't want the airplane to leave controlled flight right you want to maintain it so that it is flying in a controlled envelope or there are times and you can go back to world war one where people intentionally departed the airplane from controlled flight in order to obtain an advantage which is that's where the human goes can i do this i know it's outside of where i would normally go but i can do that so you can do some crazy things now especially since the flight control logic in modern airplanes with digital flight controls they're extremely forgiving so you can literally i've done things in super hornets that literally even as a pilot inside the airplane you're just like wow i cannot believe it just did that like it'll flop ends which defies most logic and i guess you know in a way you could probably program it but i still think that when you get to the edges that may or may not give you an advantage um there are things that a human can will do that ai won't and i don't think we've got to the point because how do you how do you map illogical solutions you know most ai is logical it's based on some type of premise when you write the algorithm to control it um there's bounds yeah there's this giant mess like you said the difference between the simulator and real life also gets at that somehow that there is uh somehow the the fear of death all of that beautiful mess comes into play like is there a comment you can make on commercial flight like with sully landing uh that plane famously uh versus the simulator all of those discussions is there some well it's it's very it's very similar what i was talking about earlier with the a6 so one is when you're flying with a crew uh their standardization so you gotta remember when sully flew when his first officer that's the co-pilot showed up you know first time they met and this happens all the time in the commercial world you know there's six seven thousand pilots at united airlines you know your chance of flying with the same guy all the time is slim and none we're in the navy we were crude so i had a primary and a secondary wizzo that flew with me for a while for months oh hell yeah for like all of the deployment so because you want to use you have to trust all of those things it increases the capability airplane it's not to say we can't swap out but for true effectiveness especially in very complex missions like a forward air controller we're in the air actually controlling ground assets and supporting ground troops if you're in a high threat area which is crazy busy you have to you have to be melded when you do that you have to have trained to do that job otherwise you're going to be ineffective so when you get to the commercial world and i've got tons of friends at fly commercial there is a standardization like we know that at this point i'm going to put this switch you're going to do that and everyone they know their rules captain's going to do this first officer's going to do this and they know that when the emergency breaks out so in sully's case when they take the birds and they know they've got a problem and if you've listened to the cockpit recordings of him the two of them talking you know you gotta remember they're talking to each other when you hear the full tapes but they're also talking to the air traffic controllers in the new york area and it's like we got a bird strike and the first officer already knows hey silence the alarm they silence the alarm the first officer is pulling out the book he's going through the procedures while sully's actually flying the airplane knowing that they've lost their motors and you got to think his decision process like they're trying to get him to go into an airport into new jersey and he realizes not happening we're going to put this thing and he made a decision soon enough so that he could prepare everyone on the airplane that he was going to put this thing in the hudson river and he did it flawlessly i mean every single person walked away from that wreck the only thing that didn't survive was the airplane you know and it got fished out of the hudson but um what is it about those human decisions he had to make is that something you put into words or is that just deep down some instinct that you develop as a pilot over time it's when we when you train uh you know an aviation is a self-cleaning oven so if you make bad decisions you're you know and the list is long and distinguished of those who have died by making bad decisions oh man um so when you look at what he did or the way we train because the the commercial industry and the navy and the air force for all that we have what's called we have emergency procedures that we have to know like engines on fire the first three steps you just have to know what they are right so they know the airline uh same type you know they go hey i know this is they pull the book out because the airplanes are designed they're built to have some time but there's a point where you have to make a decision and you can't second-guess it so when he decided i'm putting this in the hudson river he couldn't all of a sudden halfway through it go well maybe i can get over to that airport he he looked he made a quick assessment this is that 80 solution where you go these are not i'm you know it's like a multiple choice test when you go oh my god i don't really know the answer but i know a and d are wrong yeah gone so the jersey airport and going back to laguardia gone yeah so what's my next option well the hudson river's there and that's probably looking pretty good or what is my other one can i get a restart on the the motors and then if i can get a restart now can i take it someplace else he had to make really really fast decisions and then once they as they they go that 80 solution you realize all right i'm going into the hudson there's the 80 percent get the book out let's see if we can get an error star because if you listen to the tapes they're trying to get it air started the closer he gets to the water the more he's going i'm ditching the airplane so the original decision to this is my best option right now this is where i'm going and you start eliminating anything that could possibly change the events which they tried to do and then he gets to that last minute says we're going in the water they change the plan they secure the airplane they do exactly what they're doing and he does that basically flawless landing on the on the hudson but you got to remember every s it's every six months for commercial they go back and they do research in the airplane in the simulator where they train to the airplane being broken you just lost a motor you just lost another motor so they go through this extensive training you know and all these and it's you know you know we used to refer to it in the navy as the pain cave where you're gonna get in because you know that when you get in for your check ride in a simulator that the airplane is going to break you're going to lose hydra and it's sometimes there a problem like oh i just lost this hydraulic system but i'm having an issue on the other motor well if i shut down this motor and i've got a hydraulics you know because there's two hydraulic systems one on each motor well if i've got an issue with the left motor hydraulic system and my right motor is starting to give me indications do i want to shut the right motor down because that's going to kill my hydraulic system that's good and now i'm flying on a good motor with a bad hydraulic system and without hydraulics the airplane won't fly so they it's a really they're challenging problems that you have to think through in real time and of course the weather's never good it's always dark it's always crappy you're going to break out it i mean it's just all this stuff gets compiled on top of you and it's intended to increase the level of stress because when things happen like in sully's case we like to joke it's going to stem power you know where the functional part of your brain shuts down and you are literally on instinct like an animal well if you've trained so much that that is the instinctive reaction that you're going to have when the main part of your your your cognitive abilities start to shut down your you're running that instinct is ingrained so much into you that you know exactly what to do and that's literally how it happens so there's no how do i put it fear of death like in sully's case do you think he was at all ever thinking about the fact if his decision is wrong a lot of people are going to die you know i can't speak for him but i would say there was so much going on in the cockpit in that time his his mindset was probably i can do this i'm trained i'm going to do the procedures i've practiced this before i've done these things and you know i'm assuming that in his mindset because i never thought about when things were really bad you know if you're having problems with the airplane that you know that i was going to mort you know and and planted into the ground it was always you know maybe it's an ego thing where you think i can do this i mean so you never have you experienced fear during flight like um i mean one one way who just offline mentioning mike tyson he talked about like uh as he's uh walking up to the ring he's like he starts out basically in fear and uh yeah worried about how things are going to go i mean it's purely to put in towards his fear but as he gets closer and closer to the ring is the confidence grows and grows until the ego basically takes over to where you think there's no way anybody could uh defeat me so like that's that's his experience of overcoming fear but do you uh did you experience any kind of thing like that or is that or do you just go to the part of the brain that goes to the training and then you just go to the instinctual 80 solution i wouldn't say i was never afraid i think that would be i can't i couldn't tell you that anyone i know that wasn't afraid at one time and for most of us especially navy carrier pilots it's just it's it's usually especially when you're new and you got to go out and it's nighttime and there's no moon and the weather sucks and the deck's moving you know the ship's going up and down because it will scare lover living shit out of you can i say that you can definitely say that so it's about landing or take off that that is if you even they used to wire people up they did it during vietnam you know guys that go flying missions you know when they were flying low and crazy stuff was going on and people were getting shot down a lot uh the highest the highest anxiety and heart rates were coming back to land on board an aircraft carrier how hard is it to land on that it seems impossible like for for a civilian i guess like me it just seems crazy that a human can do that the problem with night is and there's different degrees of night just like day i mean there's the clear full moon night you know where it's like oh yeah you know this is not that bad but you gotta remember at night i think everyone can associate with you're driving in your car and it's just a it's it's an overcast dark night and you're on a country road with no side lights most people have a tendency to slow down just by nature of oh my god because you what you'll do is you'll out drive your headlights because it is so dark you know you can get outside you get outside the city and get up into new hampshire especially when the roads are curving you know and the lines probably aren't that good it's you know now take that and multiply it by like a million because you have no depth perception uh what you think is fixed the runway is actually moving up and down and left to right yeah oh and when it's really bad you can actually see it move and uh we have two systems uh you know there was a there's an automatic system that's actually uh it stabilizes with the inertials on the ship and then there's the ils now civilian pilots will tell you that ils is a precision approach which gives you azimuth and glide slope you know you come down it's like a plus on the carrier it's not it's really just a beam that goes out and it's considered a non-precision approach it's it's not stabilized at all that and i've been where you can actually watch the needle and the and the attack hand needle will move there's all kinds of stuff moving because the base that it's all sitting on is doing this and ships don't just go up and down they they do this so the bow goes up and down and the tail like you normally see a ship and then there's so that's pitch and then it has roll so it's doing this and then it has heave so the whole boat is going up and down while it's pitching and rolling and you're gonna land on that um so and it's i mean i remember landing as i was with chris uh sado and uh chris and i we're off the uss ranger which is now decommissioned it's sitting getting turned into razor blades um we're flying the old a6 and we come in and it was off of san diego and it was just an ugly night because san diego always has a marine layer that is about 1200 feet was lower than that that night and it was pouring down rain it was an el nino year and there's thunderstorms all around it was just the craziest night i've ever seen out of san diego and i remember landing and your adrenaline is so high that you're shaking i mean you literally can't stop and we had spun around out of the landing area and we parked we caught the six-pack so it's right in front of the island so if you see an aircraft carrier of the island and the number of the ship on it we're sitting right in front of that and we're looking at the landing area so it's like you get front row seats to the concert and and this this this ea 6b comes in you know ugly pass he ends up catching a one wire which is the first one you never want to catch the first one which means you were not really high above the back of the ship when you landed and it comes in and the exhaust on an ea 6 or an a6 actually points kind of down and it blows and it's blowing all the standing water on the aircraft that's how hard it's raining and you literally could not see a cross i mean i could see the front of my airplane his airplane and then it was just white because of the water being blown off the deck and i'm shaking and i i i'll never forget i looked over at chris and i said oh my god i go hey dude man ten thousand foot runway looks really good right now and i go and i'm shaking my hands like this and i said i'm not even this is i'm not faking this dude i know that's literally i cannot stop shaking i said that scared the evil out of me yeah um but you but it scares you afterwards you don't during it you're not i'm not you don't have time to think about that you're doing it you got to do this you know kind of the quote from tom hanks and uh what's that the girls baseball movie where he goes there's no crying in baseball oh yeah that's our joke there's no crying in naval aviation i said you can fly around and cry all you want at night but you know there's only one pilot in those airplanes and you got to land it so you try all you want wipe the tears away you know putting on your big kid pants and it's it's time to it's time to you know man up and land atlanta jet sorry for the romantic question but going back to the the kid that dreamed to fly what's it like to fly an airplane what it looks incredible like as a human like a descendant of vape i sit here on land and look up at you guys it seems incredible that a human being can do that you know people ask you know i'll be sitting around with my friends and they're like how was i said the greatest job on the planet i said you know you it's it's an office with a view because you're sitting in a glass um you you can do uh you know it's like roller coasters you go oh it does all these cool stuff so we take people flying every once awhile and it's like oh yeah i like roller coasters like you know take any roller coaster the coolest roller coaster you've ever been on and multiply it by a thousand i said it's an experience uh you know to put your body under you know you know the jets rated at seven and a half but it'll pull up to 8.1 before it over stresses depends on fuel weight so i mean you routinely get up there towards eight g's um to be able to do that to your body i mean it takes a toll like i can't really turn my head real good anymore and and stuff like that but uh would i trade it i mean it was a childhood dream and how many people get to do that you know professional i want to be a nfl you know and you end up to the nfl which is a very small percentage but well i want to fly jets and and to fly you know at the time when i was flying the super hornets that we had on our squadron were brand new like literally right out of the factory i'd come off our first super hornet cruise we had went to the boeing factory in st louis where they were building my new jets that i was going to get and i actually signed the inside of one of the wings while they were putting it together so i'm meeting the people that are putting the jet together that's going to get delivered to me in a couple of months that i'm going to fly so uh just i mean the whole of it is it's incredible i i it's i'll tell you what when i left when i decided to walk away uh yeah did i miss it i told myself i wouldn't i promised myself that you know once you get through your o5 command your flying really starts to tag to come down you know even if you and you're an airwing commander which is we call them cag carrier group commander you're not flying as much as like the normal pilots nor should you be i mean there's young people that are coming up and it's training your relief because that's the next generation so like currently i have friends of mine that we serve together their kids are flying super hornets right so to me that's really neat because i watched them when they were little and now you know one of them who was good friends uh is i won't get his last name but joey who lived down the street from us is a top was a top gun instructor and i'm like hey joey's joe's a top gun you know and i'm like that's cool because you know i went there and i knew him he would come down to my house and now to see these kids that are because typically military breeds military you know because the kids grew up in it i mean and i the only reason that my son is not doing it is he's colorblind so it it disqualifies you for being a pilot being a seal because he he talked about doing that because he's an incredible swimmer and he likes doing that stuff and water polo player but he's you know both my kids are well my daughter is a doctor and my son's in his third year so but there's a i suppose i mean from my perspective a bittersweet handover of this incredible experience of flying to the younger generation so you don't you told yourself you're not going to miss it you miss it uh there are days i do when i hear jets like if i'm around a base or a jet flies over but i have all the memories so i can look at it and go it can't go on forever you know tom brady can't play football there's going to come a time where he has to stop he seems to have done it for a long time but you know typically when you look at ego i had the opportunity and i think as automation moves on especially with ai that you know when will when will the last manned fighter be built you know and that's that big question you know we just did f-35 it's over budget it's seven years late there's all kinds of issues when we try and do it and then you look at some of the new stuff that's coming out that the air force is working on with smaller cheaper uh attributable platforms that you can go oh we can because if you don't put a man in the box or a person because there's a lot of incredibly talented women that do this too um so i'll just say that as person yeah so we say man and he we mean both men and women because offline you've told me about a lot of incredible women that flown so i had i had three three female actually four one of them didn't fly anymore she actually lives right around here she she's uh she ended up going into aircraft maintenance when she couldn't fly anymore uh one of the girls who everyone knows is incredibly she's one of the most gifted people i've ever met in my life she is the vice president of amazon air you can see her on tv her name is sarah incredible and then i had uh paige who ended up taking command uh she got out of fighters and went into other platforms and she was a commanding officer and then the other one is a teacher's leadership and she is all three of them actually all four of the women that were direct uh i'm not forgetting i don't think i'm forgetting someone uh incredibly incredibly talented uh and a great addition to the reading room so anyone who gets into the oh you know women can't do it that's all total horse crap you know we can talk about the original integration and stuff which was not done well by the military nor the navy so women can fly as good as the guys yeah you can't tell if you pass another airplane you can't tell if there's a man or woman in it it really comes down to uh stick and throttle the ability to extrapolate where the vehicle is going to be where the airplane would be if you're fighting another one you have to be able to think fast anyone has those characteristics uh can do it and then i think most important besides that there has to be a desire yeah and i'm not saying that everyone if you took because we used to track so when i ran we call it the rag it's the replacement air group it's where so the the super hornet training squadron there's two of them there's one on the east coast 106 and there's one on the west coast which is vfa 122. 122 is the first one so i ended up going there and i ended up being the operations officer and training officer okay so we tracked the last hundred students right so everyone goes ah it's funny to hear students talk because oh he's awesome he's super if you took the hundred there's three at the top of the list that are just naturally gifted aviators they're well well well above average it's like the person in a math class that sits down in complex math and they just get it you know at the bottom there's the three at the bottom that are gonna struggle and there's a good chance they won't get out and if they do get out they're gonna have to work really hard to just maintain kind of average sometimes it's just the way your mind works not everyone is good at everything if you took the 94 of them in the middle they're within one mean deviation of you know it's there they're all you know it's a the bell curve doesn't look real good it's just a big hump and it comes back down and everyone's right there within one mean deviation and then you have the outliers usually not on the high side because they're going to get through but the outliers on the low side that don't make it through so for the most part the navy does a really good job as does the air force of screening so now what they do when i went you just showed up and you started now what you do is you actually go fly uh piper warriors low wing to see can you are you adaptable to this and there's an evaluation that goes through and then if you hit a certain mark then you're good to go and then they put you into primary it's kind of like a it's like a pre-check you know like the preset the pre-sat to go hey how am i going to do on the sat it's it's very similar to that but it's more of a hand skill can you adapt because although we live in three dimensions like this table is not you know we this is you know this is all has depth with all that uh where it's really relative to aviation we are two-dimensional very two-dimensional can you explain that so our perception is actually more limited than the than that of an aviator very much and here's why yeah so we look at uh let's look at a tall building let's look at one world trade center in new york because that's everyone knows what it looks like big tall building um it's what maybe 1800 feet tall even the burjal dubai which is like what 20 700 feet tall it's not that big so a super hornet to do a what a split s is which is i'm flying i'm just going to roll the airplane upside down and then i'm going to do basically a c the letter c i'm going to go in the top and out the bottom so and i'm just basically a vertical displacement of the airplane so i'm going from high to low it's very very tight and it doesn't in about roughly about 2 500 feet give or take a little so you go that is that is a really tight vertical turn yeah for example the a6 in order to do that was about 9 000 feet and we look at a building that's 2000 feet high and think that is tall right all right so in an aviation sense when you're starting to do vertical displacement maneuvers going from 35 000 feet down to 20 000 feet in a matter of seconds and maneuvering the airplane because the human brain thinks we really are we like to be flat i see we think 2d so if i'm fighting how you really get an advantage when you're fighting another airplane is to work in the vertical because most people will do like one move in the vertical and then they want to start to flatten out because that's where we're comfortable yeah it's very profound do you still think in like stacks of 2d layers or no or do you do you truly start to think in that third dimension like the rich 3d world of uh like a fighting like do you start to actually be able to really experience the 3d nature you do because you have to project where you're going to be so you have to know the performance of the airplane knowing that hey if i do this maneuver that i am going to go it's it's kind of like when i when i talk about when we were chasing the tic tac so the tic tac's coming up and i'm in about you know and i've been doing this for at the time 16 years so i'm looking and i'm going hey i'm here he's there on the other side of the circle i'm going to do a vertical displacement i'm going to go like this i'm going to cut across a circle and i'm not going to him i'm going out in front of him i'm going over here because i know that by the time i get through this maneuver that's where he's going to be and i'm trying to you know basically join up on him but i also i also had to look at it to go do i have enough altitude to do this because what i didn't if we're here and i do this i'm going to end up over here and he's going to be above me and then you know i have to get that energy back to get up to him and when you're doing a max performance it's a trade so you have this is this is really important when you're when you're fighting airplanes and you're really max performing so when you go to an air show and you see the air demo he's literally playing with it he's got a finite amount of energy right he can add some with the motors and stuff but you're what you're really doing is it's a trade-off and you can trade off kinetic energy speed for altitude which gives you potential energy the other piece is is i can trade some of that kinetic energy for performance because i know if i do a nice easy turn the airplane will make it what doesn't bleed energy but i know if i do a real tight that 2500 foot split s that it's going to cost me energy so if i enter the split s at 200 knots and i do it right i'm going to come out at the bottom at probably 200 knots although i lost 2500 feet of potential energy i converted that to that to kinetic and that kinetic was transitioned and bled off the wings in order for me to get that high performance turn and you have to constantly evaluate where you're at and it's your overall energy package so you can have a guy that's behind you that looks like he's going to kill you but if this jet is at 400 knots and this jet is at 110 knots this jet's just going to pull away drive around and kill him in about 30 seconds right it's it's overall energy package and that's that you've got to be constantly evaluating where you're at and this is that 80 solution can i afford to do this or not yes no and you have literally a split second to make the decision the most incredible dance of human decision making is just incredible i know a million people want me to talk about tic tac and i i definitely will but let me ask the one last uh ridiculous uh uh subjective question what's the greatest plane ever made in you don't history to like from pure speed i would say sr-71 i think it's an engineering marvel that was actually developed in the 50s by kelly johnson you know skunk works for what that was able to do and when you get into history of it you know how they actually built uh the cia actually made like six companies in order to buy the titanium from russia to bring it back and build an airplane out of titanium that we would fly over russia to me that's it's an incredible engineering marvel i think that like the x-15 you know by the way this sr sorry to interrupt sr-71 still holds the the speed record for of any plane as far as i can understand yeah what's funny when you get into it is it's remember fast is relative and when i say that i mean so if you're going 3 000 miles an hour 100 feet above the ground you're going 3 000 miles an hour through you know that's how fast you're going when you get up to altitude there's an indicated airspeed and there's a you know your ground speed so your indicated airspeed is really how fast the air is going past your airplane well the air is so thin up there you may only be showing like 300 knots but at 300 knots you're really doing 2500 miles an hour over the ground so you know like we would take the airplanes up to 50 000 feet when we had to do full the maintenance check flights on them so when you're doing 200 you know and you know some mod notch it's actually slow for the airplane it's you know you're getting you know it's kind of like it's not you know there's maneuvering speeds you know that if i hit a certain speed and a super hornet that i have the full capability of the airfoil if i'm below that speed i'm going to stall the airfoil before i get to the maximum g okay so when you look at something like that you go is it really going fast and when you look at an sr 71 that's flying upwards of you know 70 plus thousand feet the air so thin you know just like the x15 you can get to a much higher speed but the relative speed of the air going over you is actually relatively low so the stresses on the airframe are not like they would be if you were down low but because you're going fast to get enough air over your ketostatic system to show that you're going 300 knots you're you're screaming i mean the fastest i ever got was i was with the uh well soon to be vice admiral white so we had taken a check flight and uh and i got it up to 1.78 i got a super horn up to mach 1.78 and it was and we were started by pebble beach too and then it what's that feel like or is it when you get that fast it start to me it got a little bit weird because you realize in your brain and i did that there's no out if something happens i can't eject the ejection would kill me isn't that kind of liberating in a way um or no that okay maybe not i always want to push the limit you know it's like how fast i could have got it going faster it was it was literally still accelerating when i stopped but i had it was fuel limited and space limited because i you know i'm off the coast of california big sur and i'm going and i can see pebble beach out in the distance uh you know the whole monterey peninsula just going and you're doing almost 18 miles a minute i mean you're screaming yeah i mean that's and then you have to turn well the airplane didn't have anything on it it was a slicked-off super hornet so it was basically just the airplane no pylons no pods no nothing and then we had to get it turned around because we got to go to the exit point for the area and i'm trying to get it down below to subsonic and there's a bunch of things that are disabled like the speed brakes that normally we pop out when you're going that fast they don't because the super hornet really doesn't have speed brakes it deforms the flight controls they don't function so you really you're trying to maneuver and when you're going that fast you can't turn because a 7g turn at 1.5 mach is a pretty big turn um so it's just it's crazy it's incredible that a human can do this yes uh human can engineer that the system which allows another human to control that system it's to me it's it's uh i think it's just it's one it's a great experience was it sad to see the sr-71 go i think it was during your career i mean do you do you guys romanticize the different planes um we would see it flying when i was flying hornets because we i the west coast flies in it's called r2508 which is covers the navy china lake area and edwards it's a huge area it's it's actually i think the we had a guy from switzerland come out because they were they had hornets and he's like this is bigger than our whole country because it's a pretty big area in california that you fly but you would see the sr-71s they had a loop because nasa was flying them out of palmdale and they would take off and they'd go up towards washington state and montana and they do a loop and so you'd see them coming back down they'd descend out of you know above 60 000 you'd see them you they get contrails you know the white lines behind airplanes they'd come down and hit the tanker and they'd go back up so it was cool to be able to see them in my lifetime flying uh but uh you know i think with money age um the advent of satellites you know because they're everywhere now i mean you've got commercial companies putting satellites up uh how much of that need was really there because you gotta remember when those things started in the 50s sputnik wasn't flying around you know it was it was the u2 and the sr-71 that were out there doing that work um so at the time it was needed it was at the if you think about it really it was an incredible feat of aviation for that time yeah i mean literally we have yet to pass that and you also ask well is there a need to pass that i go i don't know we got stuff in space so do we need to make an airplane that goes that fast i think the next one is you get into the hypersonics where you don't have to put a person in it does all kinds of crazy stuff you know the work with automation all that kind of stuff yeah so one of the reasons i wanted to talk to you is you happen to be one of at least in my view one of the most credible witnesses in history of somebody who's uh witnessed a ufo literally an identified flying object and not only witnessed but got to how do you put it like chase it essentially chased it so let me just lay out i think it's easier than you telling the story maybe me and my dumb simpleton waste trying to explain the stories i understand it and then maybe you can correct me so on uh november 10 2004 the uss princeton which is one of the the carriers that's cruiser it's a it's a cruiser it's a cruiser so you can't land on the uh no helicopter has a helicopter pad on the back gotcha and it has weapons on it okay gotcha it shoots the missiles up but it has a nice radar just that incredible spy one system phased array four panels so looks in quadrants perfect so they they started noticing on november 10th that there is a few objects flying around at 28 000 feet with speed of uh with what's i guess is considered a low speed of 120 miles an hour i don't know what that in knots but uh out on the coast of california so and they kept detecting these objects for just about a week then comes in like your part of the story which is on november 14th from the i guess it's from the uss nimitz i you flew and witnessed a 40 foot long white tic-tac-shaped object with no wings flying in ways you've never thought possible and in some interview somewhere you said i think it was not from this world so there's a mysterious aspect to this object this entire situation uh there's videos involved the video of a flare forward looking infrared receiver receiver there's also a visible light so you can switch yeah i mean tv mode as a tv mode so that gives you visible light and then it has ir mode and uh chad underwood recorded that video so and those are the videos that were released by the pentagon later one of the three videos the two other videos uh go fast and gimbal were recorded in 2000 something 14-15 uh on the east coast of the united states they had different kinds of objects but they were weird in the same kind of way in terms of at least the videos and the experiences that people have described were similar in in the degree of weirdness but uh the differences is actually on the the east coast of 2014 case very few people have spoken about it and even in your situation very few people have spoken about it so there's a mystery to it but it's in some sense this is a quite simple story without much resolution to the mystery and it's fascinating and there's a lot of opinions there's division of opinions because uh it's a mysterious i mean it truly is a ufo in the sense that uh uap uh what is it i i unidentified aerial phenomena so can you maybe correct me on any of the things i've gotten wrong elaborate on some key things and describe that experience in general so here's what i know so yeah we went out uh on our mission to go train uh and they canceled the mission and they set us down there's all kinds of rumors out here there's all kinds of after this has come out so originally it was the four of us there's two jets two people in each jet their f-18s okay there is no video from our event it was all four sets of eyeballs staring at this thing and then when we came back and told it when chad and his pilot took off that's when chad got the video of it and we're like that's it that's exactly that's it and um so when you say eyeballs you mean literally your eyes are seeing a thing yeah so so as we're flying out we get we get vectored they come up and tell us hey we're gonna cancel training this is the uss princeton so this is the siege's cruiser so we're talking to one controller um who is like hey sir first you ask what ordinance we have on board and i laugh because we don't carry live ordinance in training typically because batch stuff happens usually someone forgets to put a switch on and then the missile comes off and hits a good airplane and it's not good so we had what's called a catom9 which is really just a blue tube with the aim 9 seeker on the front of it which is an ir missile so there's only two ways to get it off you can beat it off with a sledgehammer you can take this thing and so you put a wrench in and it unlocks the lugs and pulls the lugs back in that hold it on when it really fires the impulse from the engine actually throws the lugs forward and breaks that release and it comes off down the rail that's how it works so they said hey well we have real world tasking so as we're going out my wingmen the other pilot she maneuvers the airplane to the left-hand side of me so she's kind of stepped up like this and i'll use your mic box to start since we're going out they're calling ranges they're called bra calls bearing range in altitude and they're telling us hey it's at 40 miles or 50 miles and 40 miles and 30 miles so they're saying hey 270 30 20 000. that's all i say so we got our radars we had we had mechanically scanned radars at the time apg-73 good piece of gear apg-79 new one's way better but anyway and i apologize if i interrupt the story uh hopefully it's useful but they're telling you a location of a thing that you should look at yep they're telling us they have a contact on their radar they don't know what it is they just have a blip they have a little blip well they've been watching these things and what he told me is they had been looking at these things as we're driving i said sir we've been tracking these things for about two weeks that's we had been at sea for two weeks because this is the first time we've had planes airborne we want you to go see what these are gotcha so they kind of interrupt the mission to say check it out so we start driving out there and uh as we get down to he's going you know 20 miles 15 miles 10 miles and then you get to a point where they call merge plot which means we are inside of the resolution cell of the radar because radars don't see everything they're so they have a range and they have an azimuth resolution right so and it's basically think of a little cube so they can and the whole sky is made of all these little cubes and they're looking so if you're inside a cube with something and you're both inside the same little cube then the radar can only see one thing does that make sense yeah yeah so they call merge plot when we say merge plot to us it means he's right around something's around you get your head out so we're not looking at radar scopes anymore and the wizards the wizards can look but everyone it's heads out when they say merge plot you're done looking at your displays inside you're doing this and you're trying to find it so as we look out to the right and you look high and low because he could be anywhere from the surface all the way up now keep in mind the ship is like probably 60 miles away so it can't see the surface and you can do your standard radar horizon calculation and go hey it's the the thing is 40 feet off the water the panel can he really see you know there are radars that can see around the curve but let's just say that it can't at this time so you go is it you know where's it at so as we're looking around we see now this is a it's a clear day there's no clouds and there's no white caps it's just a calm it's actually a perfect day if you owned a sailboat it was that five to ten knots of wind and you just want to kind of go out there and you're not going to get beat up and have white water coming it was the perfect date on a sailboat how many miles out do you see like seven like you see just it's a clear day it's 50 it's unrestricted visibility you can see literally all the way to horizon it's just clear it's nothing and we're basically off the coast if you look at a map and you go san diego and then inside of mexico we're kind of in between that and we're probably about by the time this all hits we're price i don't know eighty hundred i don't know but somewhere out it's pretty far off the coast perfect from 20 000 feet you'd be amazed you can do the calculation you can see stuff you know you'll see land 50 miles away you can see you know and when you're looking at a continent it's really easy to see you're not looking at an island i mean you're looking at mexico and you can see on the white gaps in the water if there is any oh yeah they're easy yeah for us we look at it because we know if it's natural wind or so if it's a really white cap windy day then the ships just kind of barely be moving when we land on it it makes it actually easier if the ship has to move where it's got a big weight because it has to make its own wind when we land which is the day that it was this day you go oh okay and it creates what's called we call the verbal but when the air flows across the flight deck it drops behind the ship you know and then it kicks back up so when you're coming board to land it's going to make you go up a little bit and then you're going to fall and you've got to con you've got to anticipate that to stand glideslope so we're pretty we're pretty conscious of what's going on out there with the waves and the wind so we look there's no waves there's no wind there's no white caps and we look down and we see white water so if you put if you put a piece of land a sea mount below the surface like you know even 20 feet below the surface that's big enough as the waves come in you know waves have height and length when they come in that's what happens on the shore when a wave comes in it hits and then it starts to collapse and it pushes the wave height up because it can't go anymore and then it breaks the top and yeah and that's where you get the white so what happens is at sea when you get a sea mount you'll see stuff come in the wave will crash and you'll get white water you can go out when it's high tide in any one of the coasts you can go out here off of boston and go hey at low tide i can see those rocks and at high tide i can't see the rocks are covered but there will be white water around those rocks you'll be able to tell there's something underneath the surface does that make sense yep so that's what it was we see we don't see an object because there's all kinds of oh they saw this they saw another craft below the way we didn't see anything below the water we just saw white water but the white water and i like to shape it you can say it was across i say it's about the size of a 737 so it looks like if you took a 737 put it about 15 20 feet below the water so the waves breaking over the top and you're going to get white water where the plane is at you'd see this this kind of shape so it looks like a cross so as we're looking down off the right side the back seater in the other airplane jim says this is that talking in parcels again he says hey skipper do you and that's about what he gets out of his mouth and i go what the hell is that in a nice do you see that essentially so we see the white water and that's what draws our eyes down or otherwise we'd have never seen it so we see this i would love to see the look on your face when you see that and then we see this little white tic tac because we're about 20 000 feet above it and it's doing it's going basically north south and then east west north and so it's abrupt it's very abrupt so it's not uh like a helicopter if a helicopter is going sideways and it goes once it's going sideways left and it goes right what it'll do is it'll go it's got a speed it slows down because there's inertia yeah and it stops and then it goes back the other way this thing's not it's like left right left right with no so moving in ways that doesn't doesn't feel intuitive to you at all of the things you've seen in the past so as a pilot the first thing you think is it's a helicopter right right so you go oh what is because when we see it's moving we're like oh helicopter so the first thing you look for to see if it's a helicopter when they're doing that because usually when they get down there towards that 50 feet you'll get rotor wash you see it in the movies when the helicopter's by the water it kicks the water comes up besides because the downdraft you know like a thunderstorm will do that it pushes the air down and then it has to come out the sides so you see it and you go well there's no there's no rotor wash what is that thing so by this time we're driving around so as we're if we were at the six o'clock we're driving around towards that nine o'clock position and we're just watching this thing and it's just it's still pointing north-south and it's going left-right and it's kind of moving around the object and if it had if i had to say it biased itself it was biased towards the bottom half so if you've got the east-west and then the north-south kind of across it's hanging out on the southern thing that's hanging out it's just kind of moving around up down left and it's crossing over it it's going up just kind of so now we're like what the hell is that so then i go hey i'm gonna go check it out and the other pilot says i'm gonna stay up here and i said yeah stay up high because now we get we get a different perspective so she's up here and i'm down here as i'm descending she can watch because right now all i'm watching is the tic tac she can watch me and the tic tac so she gets a god's eye view of everything that's going on which is really important you can you'll hear people say it's high cover whatever she's watching me which is it's perfect as the story goes on because it it gives us two perspectives you know of a perspective that's about 8 000 feet above us when that thing disappears and they don't you know because if it's just like oh i lost it and they go no it's over to the right we can still see it we all lost it at the same time so as we come down we get to about 12 o'clock and i'm descending it's an easy descent i'm doing about 300 knots which is a really good air speed for the airplane for maneuvering because i have i have everything available to me at that speed so i'm coming down and as i get to 12 o'clock as the tic takes doing this it literally it's like it's aware of us and it just goes blue and it kind of points out towards the west and starts coming up so now it's obviously knows that we're there whatever this thing is and knows over there so as we drive around it's coming up and i'm just coming down we're just i'm just watching it now you remember this whole thing is like this is like five minutes this is not like we saw it it was gone or oh i saw lights in the sky and they were gone we watched this thing on a crystal clear day with four trained observers watch this thing fly around so we're like okay so i get over to the eight o'clock position and i'm a little i'm a couple thousand feet above it and it's about so i'm probably at about 15k i think it is i think that's my story's about 15. it's just estimating so you can see it's just really easy to set because so what's 15k 15 000 feet i thought it was 8 000 uh the the other airplane ends up about yeah okay so they're still about twenty thousand feet so they're all right slowly and i'm descending they're staying up there so i'm kind of doing this okay as they drive around okay so i'm looking at this thing and it's about the two o'clock position we're about the eight o'clock position and i'm like oh i've got i've got enough altitudes i'm gonna i'm gonna cut across the circle and i tell the guy in my back seat dude i'm gonna i'm gonna do this he's like go for it skip because i was a skipper so i cut across the bottom so i'm kind of almost coming out co-altitude as this thing's coming i'm gonna meet it and i'm driving and uh i get to probably it's i'm probably about a half mile away which you think well a half miles pretty far a half mile in aviation isn't it's nothing that's i mean you can tell there's a pilot in an airplane you can see all kinds of stuff at a half mile you can see pretty good detail so i'm like right there and it's coming across my nose so now i'm basically pointing back towards the east so i'm cutting across because i'm going to the three o'clock position it's at two o'clock and i'm gonna meet it at three o'clock so as i do this it goes it just accelerates and disappears so it's this happens at around estimating about 12 000 feet so they're at 20. so they've got about 8 000 foot of altitude above us when this happens and it just as it crosses our nose it just it accelerates and literally in less than you know probably less than a half second it just goes and it's gone and so we're like and i the first thing is dude did you guys see it the other airplane's like it's gone we don't we have no idea where it's at so we kind of spin around rook i go let's see what's down here and i turn around we're looking for the white water we can't the white water's gone there's nothing it's literally all blue so now you go and i remember telling the guy in my back seat like a dude i'm i don't know about you but i'm pretty weirded out because this is i mean you know i had at the time like 30 some hundred hours of flying i'd been doing it for 18 years it's nothing like anything you've seen no no so as we turn we go well let's just go back you know because now i got to put on my real hat which we have to train because we're getting ready to deploy to you know overseas so we got to get our training done so that's my mindset especially as a ceo because i got to get i got it training out of the flight time because i'm responsible to do that so hey let's go back and the the the guy who's going to be the bad guys is the ceo of the marine squadron and uh so cheeks is at the end he's listening to all this happen you know because he's just like because he they when he first went out they were gonna do him but the little hornets the legacy hornets f-18cs don't have as much gas as the super hornets so he had launched first and they were going to do him and then when they knew we were off the deck they just told him hey go to your cat point down south and we're going to send we'll pass this off to the supermarkets what's the cap point uh that's where we hold so it's called a combat air patrol point so we're just going to hold at one end he's going to hold at the other end it's kind of like hey you guys are going to each think if it's a football field we're going to sit on one goal line he's going to sit on the other goal line and when they say go we're going to run at each other and try and do something in the middle of the field and then go back to our set reset points okay so you're talking to him he's he's he's listening to the he's just listening we don't talk to him at all he's just listening he just dials up because they know that we all know the frequency so he's listening to what's going on because he's like because they cancel training so what else is he gonna do he's just gonna hang out there and do circles while he's waiting him and his wingmen so they're just they're listening to all this go on and then at this point you move on yeah we come back up to train we go back as we're flying back the controller because we're talking to the the kid on the princeton the uh the uh they're called os's they're operation specialists they're the ones that run the radars and we're talking to him and he's like hey sir you're not gonna believe this but that thing is at your cap it showed back up it just popped up you know this is like 60 miles away it just reappears we're like oh okay so we got the radars out we're looking for it uh we get out there we never see it we never see it again uh we do what we need to do we come back to the ship of course now we're like oh this is gonna be we're you know i told i told him i go dude you know we're gonna catch we're gonna catch shit for this when we get back to the ship word's gonna get out and we're just gonna catch maximum shit and we did yeah and it's kind of that joking you know so the ship plays movies we have movies on the boat and they do 12 hours of movies so they repeat because there's a day check and a night check so the same movies in the morning and night play so you never get to ever get to watch a whole movie on the boat which drives my wife crazy because i'll watch stuff on tv that way too i'll be like oh hey i've seen this and i'll jump into a movie in the middle and then i'll pick it up later and i'll see the beginning and i'll put it all together because that's how we have to do it because we're so busy well the movies became and i it was men in black aliens uh independence day definitely gonna catch some shit oh let me just ask some dumb questions so just take him because it's whatev whatever the heck you saw whatever the heck happened it's you know one of the most fascinating things um events in recent history so whatever it was it's interesting to talk about it different kinds of angles there's no good answers but it's interesting to ask some dumb questions here so first of all you mentioned see you saw at some point xy and then uh somebody in the princeton said you're not going to believe the sir it's at your cap point that that's a different place how the heck did it know what your cap point is that's a good question and that's the one if you don't no one you know you don't we don't tell it it's we don't broadcast it we have a waypoint in the system but i don't know maybe it knew where we were going because we used the same one day after day after day but it it obviously knew but you never saw it there never saw their chad when he took off when he got the video we landed we told them hey look we just we just chased this thing they're like when i go chased it and they're like why go dude and i told him i said dude get video and he goes so and that's how he is he's like i'm gonna go and he he was he he was determined he was gonna find this thing so when you look at his video and this is the stuff that isn't out that they don't see because not all the all you see is the flare tape that's the targeting pod the forward-looking infrared receiver um i'll probably overlay the video when he goes out it's uh you know what he's looking at on his displays is he has basically two radar displays up he has azimuth and range on the right one and he has the azimuth and elevation on the left one so this is called the as l display and this is called this is basically the ppi which is the you're at the bottom of it you're at the bottom of the square it's really taken this it's taking a cone because a radar really looks left and right from a point and it squares it out so the entire bottom of the scope that we look at is us because they do this they square it off so so he goes out and when he first sees it he gets a radar return on it because when he's not trying to lock it so the radar's just throwing energy out and getting it you know it's a doppler radar so when it's in search mode that's all it's doing it's going oh i can see you i can see and it's looking for return so he gets a return so he wants to see what it is because all you get is a little green square unless it builds a track file on it but a little green square is just sitting there it's not moving because it's it's sitting in one spot in space he locks it up when he goes to lock it up now he's putting a bunch of energy on it but he's telling the radar stare down that line of sight and whatever's there i want you to grab it and build a track file on it which will tell us how high it is how fast it is in the direction that it's going okay the radar smart enough that when the signal comes back if it's been messed with it will tell you it'll give you indications that i'm being jammed so that's all it is is you send the signal out something it manipulates the signal either in range and velocity or whatever and it sends it back and the radar was smart enough to go that is not a return that i'm expecting something's messing with me i'm being jammed and it shows you and it puts strobes up it gives these lines on the radar and it does some stuff so you can immediately well it does it goes full into it it's being jammed in about every mode you can possibly see because everything comes up and the the this aspect gets long it's all kinds i don't want to get into details but you can tell it's being jammed so and as you said on rogan by the way that jamming is an act of war active jamming isn't when you actively jam another platform yes it's technically an active work feels like you should be freaking out at this point i mean so well he does it and then in the back seat so they don't have a stick and throttle they have their side stick controller so they can control all the sensors and they can just toggle around and do stuff so he can he has the ability to just move one switch real quick and it will go from that azimuth elevation on the radar to the targeting pod well as soon as he commanded the radar to look at that target the targeting pod goes oh what's over there and it'll stare because it goes down the line of sight because all the systems are hooked together you can decouple them but they're going to automatically couple up so when he castles over he it's a switch looks like a castle switch was a castle so when he moves that thing to the left and he swaps the displays out and he says instead of looking at the radar i want to look at the targeting pod he sees it on the targeting pod because the targeting pods already looking there and now he's on a passive track because he's not literally sending any energy out he's just receiving ir energy from the tic tac and then the system itself will track the pixels and the contrast differences it depends on what mode you're in so it says oh and that's what those little bars you see in the video where the bars come up let's do some v vision based tracking that's exactly what it is um so that's the video he goes through changes zooms changes the momentum he goes through all the modes so there's a narrow medium and wide so wide is far away medium and then narrow and then there's the tv mode and he goes from ir mode to the tv mode the cool thing with the tv mode is narrow ir mode is only medium tv mode so you can actually get closer with narrow tv mode it's got a better zoom capability when you go into tv mode um so he goes through all those things that's when you see it going from a black background to a white background he's trying to figure out what the heck is this well yeah and he wants to get as much data as he can on it based on the different modes instead of just staring at it going what is that thing um green so that the video has been out for it it actually was on youtube for years and before the government released it it was leaked at 2007. about no i got a the guy that was in my backseat sent me an email and i had retired so this is about nope because i was working i was working down in san diego so this is about 2008 early 2009 he sends me a link to strangeland.com which is not suitable for work oh yeah it's top notch yeah um and he says hey i can remember the email hey skip does this look familiar and i look at i'm like how the hell did that get on strangeland.com so the next thing you know it ends up on youtube which was cool because you can send a youtube link to someone you don't send strangeland.com to someone because you don't know what you're going to get it's like googling kittens yeah um so it ends up there somehow so it gets on youtube which was cool because i would go out with my friends and we'd be drinking and they they go dude what's the coolest thing you ever saw flying you know it's kind of like you were asking what it's like and i go oh dude i chased the ufo and they're like get out and i'm like no serious so this is literally how it happened so i was sitting with my friend matt so matt and i did our my he was the guy in my right seat of the a6 when i did my very first night trap right and we were friends to this day right because when you do stuff like people like that you know you had to have faith in him he had to have faith in me you know they're they become like your brother yeah um and these are guys that literally you know i don't talk to him on a regular basis like chris who works at apple if if chris called me up tomorrow and said dude i need help i need this i'd be like all right let's figure this out and let's do it because it's they're like family you do it and most navy guys we don't we're not we don't send letters to each other weekly you know i have friends that could i haven't talked to in 10 years that they showed up on my door you know pop a bottle of wine grab a beer shoot the shit take about first 10 minutes to catch up and then it's it's like old times and it's it's amazing how fast this happens so incredible so i'm out to dinner with matt um and i'm telling him this story and he's like get out of here so he goes back and he tells our friend paco paco has fightersweep.com it's a blog site so paco's obsessed like he is way into ufos yeah so paco calls me up he says dude i was talking to maddie that's what we call him he goes i was talking to maddie he goes dude you got to tell me this story so i'm like all right so i spend a chunk of time and so he calls me one day and i'm like i get a voicemail hey give me a call so i call him up and he answers the phone but i can hear people in the background and i go hey dude what's going on i go hang on hang on i gotta put you on speakerphone i go what do you put me on speakers you got to tell the story i'm having a dinner party you got to tell the story so he's literally having a dinner party with his cell phone in the middle of the table as i tell a tic tac store so he calls me up again he says hey i got this blog and he just writes about fighter stuff like he wrote about that we call him the shit hot break that's a guy that when you're land on a carrier comes and turns and gets ready to land really fast like breaks it off right at the back of the ship and uh one of the guys when we were junior officers on the uss ranger one of the apartments the other squadrons guy nasty and nasty was notorious for coming in in the tomcat and cranking off the shit hot break right so he he he literally wrote a thing about the shit hot break with nasty and there's another guy or mav was our uh one of our landing signals officers for the air wing it just it was it's just it's a good article on how this was and how you know it it kind of forms you in naval aviation's kind of being kind of a part of the club so he's like i gotta write about this thing i'm like what are you guys i gotta write about i go all right i go because at first i would say no i'm like dude i don't want this out there just so you haven't really before then talked about it much because my wife didn't even really know the whole story what just as a comment is it just because you caught some no uh it was just i'll tell you what three days we we had the incident for about two days they played the goofy movies there there's a comic on the back of the air wing schedule that they would put it was like first one was a far side and the second one was me and the guy in my back seat and it was men in black but it had our names you know protecting the world protecting the nimitz battlegroup type stuff it's just funny shit like that yeah um so that was just to me it wasn't that big of a deal it was like okay that's weird we're never gonna know what it was i want to get out because this is important because there's all kinds of rumors there's a group of folks no one ever came out in suits to talk to us nobody looking like me no came out on a uh no no one came out of the helicopter no one came out on an airplane you know you get oh i i was told to turn over this classified what's funny is all the cos and several are still in the navy uh there's one that is a he i think he just finished up he was a captain of an aircraft carrier you know so he'll end up making admiral and all that stuff those guys are all my friends i talk to them daily just just to clarify so just for people who don't know there's a story that both on the nimitz and the princeton folks in a helicopter landed they showed up they took the data quote-unquote so all the sort of recordings associated with this incident and they took it and presumably deleted it there's a kind of story to that and then uh from what i've seen you said that you believe just like we were talking about offline that jokes spread faster than uh or just rumors spread faster than anything on on these ships uh that it might have been a joke that started and uh well they did so here's here's the joke yeah so they had come down right we had the tapes um and they were chad's tapes so we use those tapes over and over again you know they're they're consumable but remember i have a budget as a squadron so i have a budget so i have to buy those tapes i have to all that stuff that we use i'm accountable for and the tapes are actually classified secret because of the data that's on them okay so we had the tapes so the the secure the intelligence guys the intel officers came down from what's called civic it's cvic which is carrier intel center came down and said hey we need the tapes these guys are going to come they're going to come and get them this is so we're like i'm like oh whatever you know so we hand them the tapes and then someone because i have you know you know people shortly after they came and got the tapes someone came to me and said you know they're they're messing with you they're playing a joke so i said oh let's see how well that goes because you know i'm i'm a ceo and they're not and uh so i went down to civic and uh it was probably he was a lieutenant or a lieutenant jg so he's way junior to me and i said hey uh i want my tapes back and he looks at me and i go i know you guys are pulling my leg i know you there's no one came out and i go and you have about 30 seconds to get me my tapes before i start tearing this place apart that's literally what i told him and i said and if your boss has an issue he can come and see me because it's not going to go well i said because this is bullshit and i need those tapes then he literally walked right over to a filing cabinet opened it up they weren't a safe he opened up a filing cabinet and pull them out and hand them to me i said and i basically said a few things to him like don't ever fuck with me again and i left i had the tapes so this no one came out there's no flying going on when all this is happening and i took the tapes back and then i copied the tapes so i took two brand new eight mil tapes and i copied the sections that i want so there's a rumor too that oh the original flair video is 10 minutes long and there's some one of these petty officers saying i saw it that's total crap the original video is about a minute 30 seconds long what you see on the release video is the entire video so you have mentioned uh i apologize if i say stupid things please correct me but you you have mentioned that like on rogan i think that you watched it on you know on a bigger screen it felt like it was higher definition so let me ask the the question is there a higher definition version do you think of the flair video that would give us more pixels and more information presumably because of the um because i don't know where the stuff that the government released i don't know where they got okay so the stuff that was on strangeland and youtube you know someone pulled off of a secret it looks like a rack you know there's tape machines in there and it gets converted to digital and stored on a hard drive and they pulled it off that hard drive and they put it on youtube um no it's it's just like you know anytime even a digital media the more you copy digital media there's some quality that gets it degrades so this you don't know how many times this has been copied so we were looking the videos i've seen are right off the original they're high eight tapes that's basically pulled off the back of the display so it's not filmed with cameras it's literally a digital feed it's pulled off the back and put onto a high eight tape that's how the recorders work now it's actually digital to digital it's not even on tapes anymore it's it's a digital recording system but we were still in that process of slowing up because originally we had little cameras here that shine so if the light hit it would wash out the displays so this it's a pretty good feed um when you put it on so we're instead of looking at it on your tiny little computer monitor whatever i'm looking at it on a like a 19-inch because it was still normal tvs back there we had just put flat screens in the ready room that i had bought so we could watch movies so because a nice huge 19-inch screen it says maybe 20. it's nice wow that's huge gigantic um hey i can get for like 50 bucks you can get like 60 engines this is 2005. yeah um so so you look at this big thing and but you could see so when you get to the tv mode when i say there's little things coming out of the bottom of it you could see those it was very clear but in terms of the actual visual on the tic tac was it did you get much more information from the higher from the clear little things out of the bottom to the bottom information so when you see it because he's coming almost co-altitude with it you can see the bottom of it it looks like little you know like if you look at a cessna there's a little antennas hanging on the bottom kind of like that there's two little things on the bottom there's nothing on the top there was no plume no ir no no visible propulsions even heat signature you know it's all that stuff and then the other thing that people didn't see is they didn't see the the radar display uh which that that really raises the classification level especially to see what the radar does when it's being jammed um you know matter of fact when they did the unofficial official investigation in about 2 000 and let me think about 2009 um i had gotten a call on my cell phone from a guy who government employee and said hey told me who he was he's still in the government um i'm friends with him and he said hey we're going to investigate your tic tac thing this is literally five years later yeah five years later and i said okay whatever and he did a pretty good job i caught the unofficial official report because um it was really never official it wasn't but i'll give you the history of why i say that and why it never came out in foia requests so he does the report he sent me the report and all he said is hey i'm going to send you this report please don't distribute this report i said okay the report is now out because harry reid got it to george knapp and they were good enough to redact there's a few versions of it unredacted and i'm very protective of the other people that were involved in this so jim has talked but he's off the grid he doesn't talk to anyone now the pilot of his airplane she has come out on unidentified but they don't release her name although people are starting to do it and she's had weird shit happen around her house she's got kids you know so i'm very protective of her um and i've told people like jeremy and george if i know that the names ever came from you i will never talk to you again about this and jeremy's been really good about it and so is george and then but george george knew the names were because he had he got the report from senator reid um and then the other crew so the pilot of the airplane that took the video that chad was in if you talk to that individual they really don't have the recollection they were just out flying that day and it wasn't a big deal um so it's it's you you need to protect because not everyone wants people knocking i don't want people knocking on my door and you know and there's rumors oh you talk to everyone i think you're about the 23rd person that i've talked to total yeah and that includes uh you know the the newspapers and stuff and i've been selective because there's so much i mean if i turn down like i turned down russian tv uh i can give you her name when we're done here she called she not only called me she called my wife she called my daughter she called my son and she called my son-in-law because they're persistent so i'm i'm pretty protect i'm very particular i mean the reason i'm talking to you is because i knew we would have a conversation that wasn't based just on the tic tac in the incident but we can actually talk about some of the science and some of the theoretical to get into to get more people involved to go because i think there's you know and when you talk to you know lou elizondo or chris mellon you know the group at ttsa you know that that whole thing was that's to the stars uh academy okay that's the tom delonge group that got started so and you go well uh you know because i think tom has caught a lot of crap for this but he's actually when you talk to him he's he's he's very smart and i asked him how'd you get into this and he goes oh when i was traveling around with blink 182 he goes you read a lot of books when you're laying in a van as you're driving to your next gig before you make it big and he goes and he read he was reading books and he read one of them on ufos i'm trying to think the title that's one of the big ones that's out there real popular and so he started just he started asking more and through his fame with blink 182 in the band he got more and more connected you know if you talk to chris mellon who is an under secretary of defense for intelligence and he's part of the melon you know dynasty you know from carnegie mellon type very very smart he knows he he he definitely knows how the government works because he worked there and so when i went down to dc to talk to people he's one of the first people i'll go to when i did uh tucker carlson about a month ago month and a half ago i asked i i he texts me i i texted him tom lu to go hey because they were like you got to do it because i turned to i turned tucker down a couple times before and his uh his producer had called me and i'm like all right i'll do it because those guys like you gotta you gotta do this for us so from my perspective just to give you some context so um to me there seems to be some stigma so i come from the scientific community and i really appreciate you talking to me today and i think the people who listen to this include you know uh faculty fellow faculty at mit and major universities and it feels like there's some stigma to the subject from from the scientific community a lot of people especially when they hear your story are like wow this is really interesting but you you don't even know you one you're afraid to talk about it and two you don't know what the next steps are like how can we seriously try to think about what you saw how to think about how we further look for things like it how we develop systems and plans for how in the future we can immediately collect a lot more data and try to react uh properly you know to try to communicate try to uh interpret this in in the best way possible from a scientific perspective and i i just would love to remove stigma from this subject uh well i think that's the first step we have done in this country an absolutely terrible job with these things so you go and i joke you know go back to roswell so the first reports that came out of roswell was we have this crash flying saucer that's literally what came out and then magically the next day it's a weather balloon and they're showing you pieces of mylar and you go well that doesn't look like what they showed us yesterday then you get into project blue book you know so there's that whole series about project blue book but the bottom line of project blue book is it really did two things it investigated sightings and it did everything it could to debunk and disprove to the point where it actually went to discredit you know to make you look so there's always been this this i don't know if you'd call it an aura around it or a mystique about ufos that if you're talking about them they're nuts with ours because i'm not a i'm not a you i'm not a ufo guy i'm not a junkie if you ask me do i believe that there's life outside of earth i would say you probably have a better chance of winning the mega ball lottery than we're the only planet that has life on it in the universe it's just the odds are against it if you do just do the math you have to accept because it if there only has to be one other planet that has life on it and then i win and you lose and then more and more science has shown that there's habitable planets out there that yeah everything we've learned so far and we know very little but everything we've learned so far about the planets out there exoplanets earth-like planets it seems that it's very likely that there's life out there intelligent life is another topic but uh life well we we as humans you know and even more as americans we have this hubris about us that says are it and you go not so much we're not so intelligent um because we are it's just how we learn so you know our main mode of transportation and what people figured out you know years ago was the internal combustion engine which led us to jet engines and solid rocket fuel what if you're in another planet where you didn't you figured out uh the ability to create a gravity field or you used you know because electromagnetics are becoming bigger and bigger and bigger you know catapults on ships were steam powered and the new gerald ford is electromagnetic roller coasters used to use a chain to get you to the top of the hill now they shoot you with electromagnetics and you're going so there's a whole new realm of propulsion that you know sometimes it's our ability to develop the technology to support theory you know we are just now proving you know recently theories that einstein had where people actually joked about them and now we actually have the technology to prove that gravity can bend light you know we have proven that so you look at that when you go well does that mean that you know 70 years ago einstein was wrong or eight years ago einstein was wrong or do you go we just didn't have the ability to look that deep into space to actually find something that we could to actually measure and you know and i've seen and that's just a hundred years and and the kind of things that can happen if you say look what we've done in the last 20 years yeah it's crazy all right let me direct because it's such an interesting topic from a career perspective from a science perspective you're i mean you've spoke you've been brave in you know telling your story not some dramatic thing but just telling the things you've seen did it encounter uh did it impact your career is that why more people haven't come out like uh you've mentioned uh roswell like how what advice do you give to people to the community to me as a scientist for ways to go forward about this topic and still have a uh you know not being put in a bin in society that he's a loon or she's a loon or that person mine is to get away from the little green men just divorce the two little green men and you know and i've talked to lou elizano about this you know and and the group that they're working with which is incredible i mean they've got steve justice who used to run skunk works where they built you know projects now louis and she mentioned was a program director he ran the a-tip program at the pentagon and a-tip was a program that was tasked with investigating any kind of uh on ufo's uap so what's funny is the unofficial official report that i joke about the guy who wrote the unofficial official report was actually an original member of atip and the original stuff that atip did was foia exempt and people how do you know that i go because i stood there with the memo in my hand that said these are did literally i watched the dod memo that said it and it was signed so he was one so that's why the that's why i call it the unofficial official report it was never it was never releasable because people go oh i put in a foil request and i didn't get that i go well just because you put an effort requesting get it i go because how much how much time do you think that guy is going to spend to get you the information that you requested if you can't find it i actually got called by the navy i had a commander in a navy call me about uh right before the article came out in the new york times it was this was starting to come back and she had called me because there's been there was a foia request for stuff about the nimitz incident and i said do you know of anything she called me she goes do you know of anything else besides the the situation reports that come off the ship you know and you gotta remember when the situation report comes off the ship that's like third hand so we tell someone they tell someone that person has to write it up so there's all kinds of inaccuracies in it but then there's the unofficial official report that's actually pretty well written there's some errors in it but it was you know i didn't help write it i just did it and he did a really good job of researching it and figuring out who's who in the zoo and the players um so she called me and said is there anything out there and i said officially out there she said yes i said i don't know anything i knew of the unofficial official report which is that one but i'm not you know if you don't know about it i'm not going to tell you because it's not my job and nor did i care i mean did in that whole situation you mentioned lube i mean did you think about your impact your career like just to get back to the question did do you think others other pilots other thing other people like in roosevelt are thinking about this kind of thing why aren't they talking about this why are people afraid to talk about this well honestly the military and the press there's a distrust i'll just tell you that right now we typically don't like talking to the press because if i talk to you you know especially when i do even the tv shows you know because i've been on a couple shows when you look at it you know they come to my house and they film me for two hours yeah and then what you see on the screen is five minutes well and yeah and the other thing with the press let me give you my perspective from autonomous vehicles is the clipping happens yes but also the incompetence let me just call out journals they're not thinking i mean so so here's the thing i've i have a phd and i've taken painfully too many classes from like physics and math and i also have a deep curiosity about the world i read a lot that seems to be missing with journalism so you're talking to a person who's not gonna push the story forward in an interesting way not the story but the actual investigation of uh perhaps one of the most amazing things that humans have witnessed in history like you it might have been nothing who knows what you witnessed might have been from a sort of debunking perspective might have been some kind of trick of mine if you and others have hallucinated something it could be some simple explanation but possibly it was uh something not of this world and to not do justice to this story from a scientific perspective it seems at best negligence and so yeah that's true for journalists it's true for others we it's just it's human nature yeah if we if we can't if we see something that we can't explain then sometimes if you just yeah maybe it's just me and you let it go away and you don't think about it you know maybe it'll just you know it's it's you ignore it um the other side is the inquisitive mind that says well what was that and i wanna i wanna dig more into it you know and if you you you look at it or you're going against the norm um you can get ostracized you know and if you look at you know einstein's the perfect example i mean he started coming up with some of his theories some of the top physicists in the world were like dude you're you're a nut job and he's he's literally proving them but he didn't have you know he proved him in theory but he didn't have the means to actually do the experiment to prove his theory there's a great book that i recommend people read called proving einstein right by jim gates that talks about like the hard work that people try to do years after to try to experimentally validate the predictions that einstein made with uh with his theories it's fascinating but yes at the time it's kind of crazy what he's saying yeah if you look at it back at the time don't we we look at it now and go well the guy was a walking genius and he was but if you go back in time when he was doing it it was like what are you talking about you know but one of the challenges is your eyewitness one of the challenges is you're essentially an eyewitness account like we don't have good data we have very limited data of um of the incident that you've experienced so let me kind of dig in let me just ask some questions of uh maybe to see if there's just to paint more and more of the picture one you kind of mentioned so tic tac shape let's break apart two situations one is the video let's look at the actual eye account the the eyewitness account that you saw with your own eyes what's the what can you say about the shape of the thing is there interesting aspects outside of the tic tac like is there any appendages is there um some texture to it that no smooth white tic tac no we don't you don't see there's no no wings no visible propulsion no windows no probes that we could see we don't notice like i said we don't see the little things on the bottom of it until we see the video in the tv mode when it's zoomed in right before it's shortly you kind of see them zoom in you don't see it typically on the youtube stuff that's out there um but remember we're looking at the original tape so there's not there's basically no degradation but when you saw your eyes there's no kind of appendages no no what about like somebody asked a lot of people asked you questions so i appreciate you spending your time here let me ask some of them uh did you i mean you chased it so we flew close to it relatively speaking was there did you feel any wake like any did you feel it in any way in terms of your interaction like aerodynamically no nothing nothing so uh another aspect of it there's an interesting thing you've developed a feel for for objects in the air did you feel like it was surprised by your arrival or did it let me ask a few questions around it so did you did it feel like the thing was surprised did it feel like it wanted to be seen almost to show off its capability did uh and did it what did it feel like relative to if you were doing a um an air fight against uh sort of like a i don't know a a foreign jet so one i think it i think it knew we were there when we showed up it's just it's me uh it's kind of like an animal if you've ever been around deer in a field you know the deer will look up and if it sees you and you're on the other side of the field it'll actually go no threat and it'll start eating you know they don't put their tail up because you move closer to the deer then it goes oh it's there and i'm going to react or i'm going to move so as we were up high and it's down doing whatever it was doing um you know which i don't know someone asked what do you think oh maybe it was communicating with something i joked on good morning america maybe it's like talking to the whales kind of like star trek you know and i actually used that clip it was kind of funny but yeah we're a little human-centric we think like it would it show up to talk to us but maybe he's talking to the dolphins maybe it was whatever you know because it was hanging around that white water and i don't know if was there something there was a seamoth we just didn't find it again i don't know but once we started the descent and it actually reoriented its longitudinal axis and it started mirroring us coming up and it was obviously where we were there and it was really coming up just you know you figure i'm at 20 and it's coming up and it ends up getting up to 12. uh where i cut across the circle i think it was very aware that we were there because it interacted we call it a two-circle fight when you're fighting another airplane um but uh you know was it was were we afraid i don't think so i mean and to me it was more curious you know the curiosity overcomes any fear that you would have and i always felt to be honest if i was inside the airplane uh especially as long as much times i'd spent inside the airplane flying and doing stuff i felt totally it was like a safe zone i mean i i felt totally comfortable inside the airplane as most part you can't if you're in the airplane and you feel scared it's not the job for you you have to feel that because the airplane is part of you now yes you know i am inside i have the stick i have the throttles i've got my wizard in the back seat he's running all the displays we are a team we're in the state-of-the-art airplane you know brand new you feel pretty good and then you get something that you know can climb from the surface up and then accelerate like it did like it was like no big deal you know for an airplane if you just put me from a standstill let's just say slow flight just get me at 100 knots above the water and for me to you can't just start a climb i'd have to lower the nose i'd have to accelerate and then i'd have to start coming up and this thing just like just did it like it was like no big deal yeah you mentioned that like you kind of your reaction to it was uh it like it's something that you would love to fly almost uh so this object just the curiosity you experience is like like what it almost like what the heck is that piece of technology and i want to fly it like what made you feel like it's something that you could fly do you think it's something that a human could fly like in terms of interpreting what you saw as a piece of technology because another perspective on it is it was uh not that the thing under the water was the key thing and what you were seeing is some kind of projection or something that like i don't think it was a projection i think it was a real object it was an a physical hard object that would could be flied oh yeah yeah i think all four of us will say the same thing it wasn't it wasn't this was not because you go okay let's just go on it's a light projection well if we were both sitting next to each other we were looking at it from the exact same angle and all that and i go oh okay there's a in theory you could have that but with an 8 000 foot altitude difference flying you know and they're you know she's probably not directly above me she's kind of hanging out watching this whole thing happen you know you're getting two different perspectives from two different altitudes over a clear blue you know if you've ever been at sea and i don't mean like coastal i mean like when you get out at sea the ocean is the bluest it's incredible um you know you got a bright white object over a deep blue ocean you got pretty high contrast and for this thing just to disappear uh it's it's was i'm telling you i would i mean i know we we all have the same uh recollection of what happened you know there's some details because it's so long ago but for the most part we know what we saw and we all came back and looked at each other like what the hell was that what if i mean do you think about the thing under the water that's not often talked about if there's something under the water couldn't have been something gigantic like it could be what like do you ever see this big ship that's why as a person so i love like swimming out into the ocean my mom's an olympic swimmer so like i love that feeling but i'm also terrified when i swim because the abyss anything could be under there i like there's not enough focus on that perhaps because there's no visibility but is it is there anything interesting to say about the possibility there was anything underneath there it could be i mean think about if you're going to hide on this planet where's what's the least explored spot on the planet two-thirds of it's the ocean you there's there's there's literally i mean come on the the the malaysia airplane the the triple seven it was a triple seven that crashed you know they turned they didn't go where they're supposed to and they just disappeared and they've been searching for it and they found pieces of it but you would think there's large objects that you know when that thing hit the water depending on how it broke up there's big pieces that would you'd find something they haven't found anything except what floated um so to hide something underwater i think would be easy so okay let's go a little bit in speculation land but it's the best it's the best we can do which is the basic question of what do you think was it so if you had to put money on it is it uh like advanced human created technology is it alien technology is it an unknown physical phenomena you know like a ball lightning for example there's a lot of fascinating things that humans don't really understand is it uh like i said some perception cognition that led you uh some kind of hallucination that made you to misinterpret the things you were seeing let me put those things on the table or is it misinterpretation of some known physical phenomena like uh like an ice cloud or something like that what do you think it was well it's definitely i don't think it's an ice cloud because ice clouds don't fly around yep and react to you do i think it was a light i'd say no because of the aspects and what we looked and watched it do i'd say no what do you mean by light like a light ball you know some type of perception you know there's uh their experience like plasma you can do plasma and you go i can see it but it's really not you know it's plasma i don't think so um so you would see distortions i think is it moved maybe not i mean i'm not the theoretical physicist in some you know you know i'm not in mit uh i would say no i mean it looked for from all my experience and and i had quite a bit of it when this happened no i i think it was a it was a hard object it be it was aware that we were there it reacted exactly like if i was another airplane and i had to come up and do something exactly what i would do you know it mirrored me it wasn't aggressive you know there was taco it fought behind us and never it was never offensive on us it never did that it just mirrored us so as we're coming out it's just like you know you're you're kind of you know you said you do martial arts you know or wrestling you know you see people out on the the uh when they get into the ring especially with collegiate wrestling because my roommate in college was a collegiate wrestler so i de facto became a wrestler because he he beat me up every night yeah we joke i talk to him literally probably three four times a week um but you know you see wrestlers when they get out they kind of you're kind of feeling each other as you walk boxers do the same thing it was doing that same thing it's like what's going on as it comes around as it comes around and then it was like hey we're going to get here and when i got too close to it you know it decided i'm out of here and then it did something that we've never seen the other question is what if i didn't cut across the circle what if i just kept going around a circle we just keep going but i could have just watched it i mean my one regret out of the whole thing is uh we have a camera in our helmet in the joint helmet there's a little camera but we never use it because it's nauseating to watch because you've ever put a gopro on someone's head where they're looking around like this all the time it'll it'll nauseate you so we never turn that on and all you know it's the one thing i didn't do is reach down and hit the switch yeah you know and then we didn't go back and because our tapes didn't have anything because we didn't get it on radar um because i tried to lock it up because i can move the radar with my head but i couldn't it wouldn't lock the radar would lock and so so then the question is and this is unanswerable but let's try did you get some hints at it do you think it's human like advanced human created technology that's simply top secret that we're just not aware of or is it not something not of this world so you if you'd asked me in 2004 i just said i don't know if you ask me now so we're coming up on 16 years ago for a technology like that you know and let's assume that it didn't have a conventional propulsion system in it because i don't think it did i would like to think that if we had a technology that would advance mankind leaps and bounds from what we normally do then it would start coming out but to hide something like that for 16 years you know and i understand uh you know and i don't speak for the united states government i never will speak for the united states government but i understand how some of that stuff works for classification levels and why we classify stuff you know is it is it detrimental to national defense but there's a point where you have to look and go if we had a technology like this that could literally change the way mankind travels how we get things into space our ability to do things you know you talk about you know are we gonna go to mars well if you have something that has the ability to go because remember these things were coming down when the cruiser tracked them from above 80 000 feet which is space and they would come down and they would come straight down they'd hang out at like 20 000 feet and then three or four hours later they'd go back up we don't have anything that can come down hang out in once you know and i'm talking hold out in a spot well we all know there's winds they're not drifting like a balloon they're just sitting there and then they would go back up and they tracked up to the when i talked to the controller he's like we've seen up to 10 of these things there's other guys and it was raining and all this other let's just say they tracked a groups of these things coming down hanging out and going up so it's not just propulsion and the way it moves it's also fuel it's everything so the whole the whole of it indicates of a kind of technology that's uh highly advanced but you don't think in your sense that you actually don't know but you know more than a lot of people in your sense the top secret military technology if you think about skunk works if you think about like that cannot be more than 15 years ahead i would say for a leap like that and and a perfect example in modern times is the 117. because now a lot of the data on the 117 is out like it was developed at this time it flew for this long before it was actually acknowledged by the united states government what's the 117. that's the stealth fighter the original stealth fighter not the b-2 but the stealth fighter so you look at that you know yeah you can i think you can hide things for a while um but i think a technology a leap i mean this is not this is not a hey we developed this and we're kind of pushing the edge of technology this is a giant leap in technology you know and the other one is do we have the basis to do that you know because usually when you have a technology like that universities especially the one you're working at mit a lot of the leading edge stuff is coming out of the top tier universities you know so you've got mit you've got caltech you've got stanford georgia tech virginia tech carnegie mellon i'm just naming schools naval post graduate school is another one there's usually indicators there's papers of hey this is where we're going i don't think there's a whole bunch of papers on developing a gravity-based propulsion system that literally i've got an object because how do you how much power would it cost to create a gravity field of your own that could actually be strong enough to counter the giant orb that we live on so by the way you mentioned gravity-based that's kind of like the hypothesizing that people do in terms of uh propulsion like what kind of propulsion would have to uh would have to be involved in order to result in that kind of movement to me all the gravity discussions just seems insane uh from a physics perspective but of course uh it would seem insane uh until it's not but because remember we only know what we know yeah and and which is very little and someone has relatively think out of the box to go is this possible at all yeah well okay so this so you're you're saying that if you had to bet money all your money it would be something that's alien technology so it's not human-created technology well i don't like to get into little green men but i would say that i don't i don't think people development right i don't think we've developed it i just you know because the other one someone had asked me they said what if there wasn't maybe it was just a drone maybe it was a uav that got sent here from someplace else i mean we've got stuff out there flying around um so i don't i don't know i mean i'd like to sit around and talk to some of the giant brains that think this stuff up i was supposed to be on a podcast with one of them uh but such topic which uh you mean look for drones for just uh just space travel technology because if you look at where we're going you know because everyone talks about mars you okay and you know we're hey are we gonna be able to colonize you know and i know elon is big into that you know yeah what do you think about what do you think about elon spacex nasa we put humans back up uh back up there my theory so it's funny because i i know one of the guys that was he was he was one of the original employees at spacex he's a friend of mine and i won't say his name but he knows elon yeah he knows elon and uh yeah and he actually worked on the entire falcon one project he's one of the lead guys on that so he's got some great matter of fact he's there's a movie there's a book coming out that comes out in about a year on this the original the first years of space for six years of spacex you know and he's named in the book you know and they're supposed to make a movie on it so i'm like hey who's gonna play it um but uh what he's done to me it changed the game and here's why because i said you know in i think it was 62 and eisenhower warned of the industrial defense complex you know which it has become everything he warned us of you know it has become and it's really driven by there's the big three in defense which is really you know northrop lockheed and boeing those are the big those are your biggest raytheon's kind of write like a subset of that but they're raytheon's pretty big too big in u.s defense those are the big guys right that's actually where a lot of military guys go when they retire they go to stuff like that so um when you look at that and you go and the way government contracting is working and how we charge and you know why things cost so much and then you go you got elon who's got an ego you know and he doesn't like to do things certain way and i've talked to the guy that worked there on you know because the government likes to have oversight of contracts where he was like no just tell me what you want i'll build it i'll give you a bill when it's done and then if i do it for half the price i make a ton of money because he's money-driven guy which i like capitalism at its best so now you look at the two things so you got the the spacex which is the dragon capsule right and then you've got boeing so elon did what boeing is contracted to do in less time for half the money and oh by the way because he can reuse the boosters because they come back and land and you don't have to like morton thigh call we reused them on the space shuttle but they had to take them all apart and do a bunch of stuff because they landed in salt water and then you had to put them all back together where elon gets them down because i was joking with this guy go what do they do they like re rehaul you know overhaul because no actually they clean them up and they can use them again they're reusable systems incredible leap in technology that no one thought of but here's a private company so being able to put people on in the capsule and the spacesuits i mean it's literally like sci-fi when you watch when they went up so i'm a huge fan of what he and his company have been able to do because you know the fact that we were paying huge amounts of money to the russian government you know and oh by the way if you didn't know because i have some friends that are astronauts uh they all have to learn russian right they have to and they have to do it's what level five where the test is a phone call yeah where they call you up and they you know because they would go so i went to the pinning two two friends of mine the one actually had a mission date the one got one later so it's cool when you're watching your friends doing a space walk you know because i would pull up because if i knew what was going on i'd pull up the nasa thing i was in a meeting one day and i've got nasa on and and makers out there floating around you know doing his stuff and i saw one he's in the space station while they're doing a spacewalk so it's kind of cool when you go oh yeah i know that dude he's up there in space floating around um so when you when you look at what those they're capable of doing and then you go what elon is bringing to the fact that now it's back in america it's actually to me it's it's cost effective for us to be able to do more stuff i think it opens the door to do we go back to the moon is there a reason to go back to the moon personally i think if we're gonna if they're really gonna go you know in years from now go to mars i think that the moon is the stepping stone to go back to start proving some of the technology to go hey we can build this we can get on the moon and now we can get back off the moon uh because we did this on a less than a compact computer in the 60s which is the whole reason that i flew because i'm obsessed matter of fact i have the giant lego apollo at home and the lander and i have one that my dad built me in 1969 right after that and neil armstrong's an ohio boy and so am i matter of fact i have a picture of him in a car in wapicanet ohio at the parade after he walked on the moon because his parents didn't live far from my aunt uncle in wapa kineta and they were out at the parade so i've been obsessed with this since i was a child do you hope to uh do you think do you hope that you'll go out to the space one day me if i had the opportunity i'd go in a second you know i am not i mean that's one of the hopes of the commercial space flight is that you know uh like people like i mean it would be to us tourism but you certainly wouldn't want to in terms of you're now kind of a civilian right i mean in a sense that you're just a normal person you're not a fighter pilot currently but it seems like if we send a civilian up there would be somebody like you in the next like 20 years i i'd be you know if elon wants to throw me one of those things i'd be all over i don't know what my wife would say but you know sometimes you gotta you gotta get your kicks while you're alive i'd love to hear that discussion with your wife listen there's the pros and cons uh she's she's i mean i've known she's on board high school so she yeah she knows how i am you know most people that know me are like yeah you're pretty much the same person you were in high school you know i was a class clown and i still am that way um so let me ask you this question about so i'm talking to elon again soon i'm curious to get your perspective on it if i wanted to talk to him about tic tac about these weird out there propulsion ideas which are obviously just like you said if there's something to it if it can be investigated somehow it would be extremely useful for us to understand in the effort of developing propulsion systems that can get us cheaply to out to space what what should elon think about this stuff what should he do what should people like him i think people need to open their aperture up and stay off of uh take the next step and go you know we are tied to fuels and either solid rocket or liquid you know whatever we do but it's it's a thrust generated where we rapidly expand gas to create thrust which is really in layman's terms you know we can get into what but that's what it does um if you have something that you can contain that is a as a fuel source that would last a significant amount of time you know those rocket boosters go and when they're done they're done there's enough to get them back down and that's it there's not a huge you know not coming back and go well i still got three quarters of a tank let's hold him on and do it again his system's not doing that um but you know the way the way contracting especially in the government the government has tons of money but you got to remember the government has to justify how they spend our tax dollars for the most part there's times where they can hide money in the budget to get stuff done but then when you look at and i'm just going to throw a few out there but if you look at what amazon you know does with bezos and you've got elon um there's some there's some big money out there yeah i mean you're talking you know bezos alone could buy companies like big companies apple is another one these companies had huge huge amounts of money and then just go over to the gates foundation and they've got gazillions and gazillions of dollars we've got universities there's so much money out there if we really wanted to do it aside from what the government wants to do because we do live in a free society i think there's enough to go how do we do this and because when you work outside of what the government would want to do let's so let's let's we're not working on this necessarily for the united states although i am a huge giant i will be american i would never yeah i am an american you're talking to somebody born in the soviet union i can't believe you agreed to this um but but when i you know haven't killed me yet yeah well you're here yeah and you've been here for a while no no i'm joking i'm i'm an american citizen i'm actually pretty much american too when you do that so you look at let's just look at american universities yes so there's some brilliant minds and we'll just use mit because you work down there there's some brilliant minds but there's a huge chunk of those brilliant minds that are not american citizens so if you want to get into government stuff and you are not an american citizen it gets really really really hard but if i take money like bezos money elon money and they let's just say they want to work together they can split it up 50 50 the two of them when the technology gets developed but now i'm not constrained by who has to do the work i just want to make sure that i try and keep it in the united states because technology is technology and if it gets developed and gets over to where you know a country gets a hold of it and then just basically uses it for their own because you save them all the research time you don't want to do that but if we can get to the point where we can we do it on the international space station we realized that space was too expensive for one country to do alone so we made the international space station and we have a conglomerate it's the one thing that the russians and the u.s actually work together on think about it that's it we work together on space because we realize it's way too expensive for us to do alone and effective so we've got this thing that's been out there floating around for god now what is it like 20 years that thing's been up there floating around so it's getting old we're gonna have to replace parts and do stuff but if we can pull the money together and come up with a something that would literally change mankind and change travel and allow us to actually do a more effective thing of exploring because if you develop that technology i'm not you don't even have to send a man person if you can develop a technology that's so and with our automation and we're progressing in our our computing power to send something out that's not just floating around when you know that it can react a lot quicker something that could actually go down to the surface and come back up so right now everything we get out of mars it goes down there and then it just sends data back it analyzes it but i've got a technology that can go up there really quick i'm not worried about man i don't have life support systems and all that but it can go down it can go it can cruise around it can hover above it can take samples and it can actually take martian soil and then bring it back yeah so we can analyze it here that's a game changer it's a complete game changer because it opens up all the planets exactly so in the sense the the the tic tac is a symbol so uh whatever you think even from a debunking perspective there's a non-zero probability that it's alien technology and in that sense it serves as a beacon of hope and a reason to like you said widen the aperture and to invest big amounts of money into thinking outside the box like it's almost uh a hope to say we can do better propulsion we can overcome physics in an order of magnitude better way and it's worthwhile to try i think and i don't think the money if you look at the big picture with the amount of money some that's out there floating around these private companies you know i think if you said hey i've got let's just say a hundred million dollars which really a hundred million dollars relative to bezos has got 100 and some billion dollars in the network so if he said hey 100 100 million dollars you drop 100 million dollars and i go and i'm gonna put a you know like the government will send a broad area announcement out that says hey we're looking for this technology or a darpa program but what if i just said hey who's to stop bezos and elon from doing that on their own to say hey i want to go pool universities because they have fewer restrictions because it's not tax dollars they don't have the checks and bound they can do whatever they want it's their money oh sorry about that um to go hey i'm going to put this out and i'm going to get the best physicists that are working at cern that are at mit that are at caltech at the schools i mentioned and oh by the way a few of these guys are propulsion experts and i'm going to basically i'm going to fund you guys for 10 years so you get 10 million a year and i'm gonna give your salaries and we're gonna do that or whatever the amount works so let's cut it down to five so we can pay well right to do the research but oh by the way the research is it's not classified but it's controlled so we're not gonna publicly just put this out in journals but if we make a leap that we think would advance because although those let's say there's 10 of them those 10 scientists come up with something and they put out a paper there might be another a number 11 at another university that reads that paper and says hey i kind of had this idea and now you can get a thought pool that pushes us in and gets us out of the the mindset because we have a tendency to we evolve the stuff that we create but yeah it's like i was joking because you know i i know a ton of guys with phds and girls and i said but you know how much when a person gets a phd in like engineering how much new math is really being done i said there's a handful of people in the world that are really doing i'm talking i'm talking stephen hawkins type brilliance that is going i'm really doing something that's yeah that's totally different that's a big dramatic thing now going on in physics that everyone is just everybody's conversed towards this local minima or local maximum whatever you think about it and it's it's again same as with the tic tac thinking outside the box is not is uh not accepted and it probably should be but it's hard because if you go back go back to einstein back to the original he was the he was out of the box yeah he did not think that the true jesus had he not thought out of the box and came up with some of his theories where would we be okay we're jumping around a little bit so we talked a little bit about elon and mars and space but let's uh let me jump back to a few questions that folks had i have to kind of bring up some debunking stuff because i think not the actual idea not the actual facts of the debunking but the nature of the true believers versus the debunkers hurts my heart a little bit because people are just talking past each other but let me kind of bring it up uh mick west i've just recently started to pay attention just in preparing to talk to you about this world and mick west is one of the better known people who kind of makes a a career out of trying to debunk sort of he's a his natural approach to all situations is that of a skeptic i think it's it's very useful and powerful especially for me coming from a scientific perspective to take the approach he does it's valuable and i think no matter what i think there's i hope that people quote unquote true believers are a little bit more open minded to the work of mick west i think it's quite useful and brilliant work so let me ask uh here's a bunch of videos a bunch of ideas where he kind of suggests possible other explanations of the things that were out there he has some explanations of the things that you've seen in it with the tic tac like with your own eyes like he says that uh it's possible that you miscalculated the size and the distance of the thing and so on when you were flying around i don't fight that as uh i mean maybe you can comment on that person let me do it right now sure so because that comes up like how how did you know it was about 40 feet long i go okay so 16 years flying against other airplanes know what stuff looks like you know i've looked down on things so if i know i know here's the known things i know when we saw the tic tac i was at 20 000 feet pish right around there so when i look down i know what a hornet looks like looking down on him because i've done it for all those years i mean i got a good idea so that's that's why i said 40 feet because it's about hornet size so and as i go around you you get to the point where you have to be able to judge distance when we fly out of experience and you can tell if something small or big you know so i would argue the fact of you know peer experience there's you know professional observers which is what we're actually trained to do um and having done it for so long no it was and everyone came back with the same thing they're like yeah i was about size of hornet from a human factors perspective how often in your experience of those 16 years do you find that eyes what you see is the incorrect state of things so like how often do you make mistakes with vision you actually you make vision issues a lot because you're and the sad part is your brain believes what your eyes see we are actually trained to do the opposite of that especially when you instrument fly because your brain and eyes can tell you one thing but you got to trust your instruments let's let's go back to landing at night so your you're right i eyes that the runway and your brain assumes that the runway is fixed but you know that the runway is moving so if i try and do stuff visually i would you die every time not every time but you die close to every time trying to land on a boat so we actually use instruments which are counter to your brain so and there's actually all kinds of things that we go through in training they have this thing i think they still use it it's called the msdd multi-spatial disorientation device or the spin and puke it looks like a giant carousel and you're in these little modules and when you get out you think the thing goes really fast and they can you can make yourself think that i'm descending or climbing but you're actually only going around in circles at a very slow rate as fast as a human can talk but as they spin you around in a little sub thing and slow it down and speed it up your body does this and you you know and then by visuals of showing you like they can spin it sideways to the outside wall but they can show like lines that are they can make the line stand still because they're moving the same velocity they can move the other way and you'll think you're screaming you see it in amusement parks all the time um you you do all that because it gives you a sense of the a but you're really not doing you're sitting there so we get trained on all that stuff so if you if you want to look at it and go well you're you're disoriented or this side bill i'd argue going no i'm not because you know when i'm flying the airplane even as i'm looking at the tic tac i've got a heads-up display that tells me what my airplane's doing so i've got i know what i'm doing i can look outside i've got a sense of what i'm doing but i'm also looking inside to cross check of what i'm seeing is in reality what i'm doing you actually your brain gotten good at combining almost adding extra sensory information you have to you have like supervision so you're combining what you're seeing and adjusting what the sensors what you're calling the instruments you're giving you and that that in turn is a loop that adjusts the perception system that like that that adjusts your brain's interpretation of what you're saying yeah you'd be amazed at how good so here's here's another example so if we go out over the water so there's no land in sight and we're gonna fight so when we fight you know two airplanes we're gonna dog fight as an instructor and i was for all most of my time you have to come back and you have to recreate it so we we call it drawing arrows so um you have to recreate that stuff so you get pretty good at going you know like i would take off and say all right we're starting heading due east uh and i know where the sun is at because in the short couple minutes we're going to fight the sun's really not going to move much it's going to be an irrelevance so now i know that the sun is at you know let's just say 195 degrees right so i'm starting going east and it's actually be down off my right hand side so now i know as i'm fighting because in the water you don't have any reference like oh i passed land i passed like no you don't and you can't use clouds because clouds do move but you got to come back because you go here's where i started and then you when as soon as you end you go all right i ended heading 355. and then you recreate the turns and the amount of turns and use the sun relative so you can create this entire battle that went on with arrows so you can come back and debrief the guy that you were teaching on exactly what happened and you get really really good at that so when you come up and go well dave how do you know you were at six o'clock and he went around and he came up here i go because i'm trained to do all that and i take all the notes while i'm flying you can do it and but usually it's you memorize it all and you get done and then you re you as soon as you're done you knock it off you look at the other airplane you get set and you start writing all your notes down yeah and you're writing it really fast on your card you go out the stack of cards and you stick a new one on your knee board card so you're ready to go and here's the next setup um it's kind of it's in some way similar to what uh like at the at the highest level chess players do i mean you're i mean they they they recap the games but the the richness of the representation that they use and remembering like how the games evolved it's not like it's much richer than the actual moves it's like these a bunch of patterns that are hard to put into words like like all the richness of thinking they have about the way the game evolved it's more like instinctual from years and years of experience so they try to put it into words but they really can't it's it's just not i understand that it's because for us if we don't come back with anything then there's no learning to be had right because the whole thing is the debrief when we get back and we talk about that's really where the learning is um and it's the same thing if you want to go back to chess you know when you start off you try and learn because you're remembering what you're doing if you play against someone i'm always a big place play with someone better than you that's how you learn if you're constantly beating people you're not learning anything you're just learning that they're not good and you're better when you when you challenge yourself against someone that is going to is better than you you learn so i learned how to fight an airplane with he's actually one of my best friends uh we'll call him tom i won't give his call sign because i don't know he wasn't so tom took me out and taught me how to fight uh because tom had just left hopkins he was the the training officer top gun which so that's the guy yeah the training officer is the main guy at top gun so tom was a training officer top gun so tom when i learned because i come out of a6 and we really don't fight because it was a bomber so i get in f-18s and i want to learn how to fight because it's a whole other side of the mission it's the f and f fighter attack the f a-18 is fighter attack so i had to learn how to fight so now i got one of the best fighter pilots in the world who's going to teach me how to do it and he did and i would do something and then he would go i'd get to a situation where i had never been and then i would go well i'm gonna do this and then he would destroy me and he would come back and go here's why you don't do that and then i would take that knowledge and i would put it in my little basket of tricks and over time because you know no one walks out into that world i don't care how gifted of an aviator and go i i am the man yeah or the woman i'm it yeah no it's a learning process and so over all those years you've gotten good so i mean so what are the chances that your eyes betrayed you when you saw the tic-tac low zero well i mean i'm not zero so okay yeah i am 99.9 so 0.1 my eyes deceive me but remember if it deceived me it had to deceive the other four people so the percentage is even lower yeah okay well i i don't find that that particular debunking case that you saw but i'm glad you put it you um you said those words out loud so for me from my perspective uh coming into this world and looking at it i'm a little bit more skeptical uh so your eye account i think is the most fascinating story and that uh i think uh that's inspiring to me and should be inspiring to a lot of scientists out there on so many levels just like we said on the engineering level that maybe there's propulsion systems we can actually build that can do some crazy amazing stuff so it's a at the very least intriguing and at the best inspiring i just want to say that but on the video side it's like it's uh the videos for the fleur video the go fast and the gimbal video they are only interesting to me to me in the context of your story like without that they're kind of low resolution it's like it it's easier to build a debunking story to be skeptical so it's just where i'm coming from maybe you can convince me otherwise but so to bring up mick west one more time he looks at the flair video and he says that one of the most amazing video parts of the flare video for people who haven't seen it is at the end of it uh the the the tic-tac flies or appears to fly very quickly to the left off the screen off the screen and what midwest says is uh that it you know midwest probably others that the way to explain that is the tracking system like we said this vision based tracking simply loses the like the object the tracking loses it and so it simply allows the object to uh float off screen because it's no longer tracking it so i find that at least a plausible explanation of that video looking at your face you do not so can you maybe comment to that uh to that debunking uh sure so um it's funny how people can extrapolate stuff who've never operated the system no for sure and that's like me going because i'm a big formula one fan you know that's like me going oh my god louis what were you doing you could have done this with the car and you need to won the race right you know and lewis hamilton right now is you know defending world champion two time he's four-time four-five-time world champion but um that would be pretty stupid to me to try and tell lewis hamilton how to drive a car yeah um or a matter of fact anyone driving a formula one car so i i can't tell you how many times i've watched you gotta remember when we looked at this thing when when chad came back with the video we sat there and watched it i mean i can't tell you how many times i've watched it off the original tapes going all right right all right let's look at this um you know because you can look and see where the you can see where the airplane is going you can see if it's looking left or right and if you actually watch all that stuff it doesn't do that it actually when the vehicle starts to move the bars the tracking gate starts to open up and the people at raytheon could probably add to this because they built the pod the tracking gate will start to open up and and but the thing when it leaves so fast off the screen the pod can't move fast enough it has gimbal rates on how fast that thing can move around because there's another theory that oh with the pods looking forward when the pod passes underneath the airplane so if i'm looking at you and you pass underneath me as does this the ball will actually flip around to kind of finish off and it'll it'll it swaps ends because it has you know it's a gimbal it can't just it's not free-floating um but there's a theory on one of them oh it's here and it flipped over it doesn't do that when it's looking out in front it stays like this so that yet another another debunker who doesn't know this so you know and mick has had several theories on other of some of the other videos like one of them the go fast as a bird and jeremy corbell actually did a nice job of saying no it's not because he's on he's on black hot so the the white object is actually colder than the ocean that's flying well birds aren't colder than the ocean they'd be dead so the gimbal video to comment on the amazing aspect of that video is the rotation the apparent rotation of the object that is something that is not possible to do with systems that we know of and make west suggests that uh flare like reflections or whatever can explain no because what mick west doesn't see is so when they take because i've talked to the one of them actually i work with so i know him i know i talk to him all the time so uh and it's his best friend actually shot the video one of his best friends for the giveaway video the game both of them the go fast and the gimbal were shot by the same person okay so uh and they were in each other's wedding so that's how well they know each other okay so what you don't see is so the airplanes that are flying still super hornets but they have the apg-79 which is the new phased array radar that's made by raytheon things incredible okay it doesn't usually if it's if it's out there and it sees it it's real so at first they thought they were ghost tracks when they started seeing stuff and then they actually threw one of the targeting pods out there well the targeting pod there's a heat signature and you go hey dot heat signature something's there it's real it's not you're not picking up some extraneous things so what you see in the gimbal video of the thing and it rotates and you go holy shit look at that thing it's just sitting there and it's in the wind and it's going against the wind why it's doing this you know someone goes oh it's an airplane now if an airplane does this it's eventually going to start to change aspect because it's in a turn this thing doesn't change aspect it just rotates right the other thing that you see when you talk to them is so they're on their radar there's an object that they identify as their number one priority or their launch and steering so when they designate that that's where the targeting pod is going to look that's what you get in the gimbal video there's five other i think it's five they're kind of in a v you know like a geese would fly that are out in front of it and they're actually coming they're out in front of it and they actually turn on the radar and go the other way while they're filming the gimbal video which it's i know uh ryan has come out and talked about it but when you see it you go you know if you take it in context because you go oh it's just the video well if you take the video with the radar going no there's actually other things out there because there's at least 60 people that have seen these things on radar off the vacates it was it actually became i called a buddy mike who was running the wing at the time the fighter wing i said what are you guys doing about this he goes well we got to know tam out which is a notice to airmen which means there's these objects out there in the warning area so anyone can you can fly a cessna through the warning area it's all the warning area tells you that there's high military traffic and training out here it's probably best not to be here but there's nothing that prohibits you from going in there so these things have the right wherever they're from or whatever they are you know because people are like oh they're balloons well balloons float balloons don't sit in in in 70 knots of wind and stay in the same location they don't say they had an airplane because there was two there's the gimbal thing that's a pretty big object there's also they talk about it looks like a cube that's inside of a sphere a translucent sphere what's that transparent how is that and so i've heard they almost hit one it's almost hit hit them so that's another that's one of the biggest another biggest account it's like almost hit a plane uh uh something that appeared to be a cube in a translucent sphere what do you make of that again you know what i mean that that's that's the most dangerous you're right the biggest frustration is when you do that you go okay so this thing passed between two airplanes and it was i think it was in like 100 feet or something like that of the airplane that almost hit it so they do is they come back and go hey i had a near midair what do you have in your mid-air with this floating beach ball with this cube inside of it and you go huh you know so they send out a no tam again and they they do a what's called a hazard report that says hey there's these objects out there we almost hit one you know and that gets sent off to the naval safety center um [Music] what was done i mean what are you going to do you can you know catch one go out with a giant net and try and bag one you don't know because they've seen them they've picked them up like hovering on radar and then all of a sudden they're traveling at really high rates of speed so you know what i'm gonna do what yeah what are you gonna do well and that let me ask this because this is what people kind of think about after you witnessed tic tac and after this these incidents as far as we know uh with the gimbal and the go fast it seems like people in the military did not did not react like what like did not freak out it almost like was a like a mundane event how do you explain that why didn't the people on the ship not the higher-ups why did wasn't there a big freak out or as some people suggest the higher-ups knew about it all along and just we're not letting everyone know that there's some kind of secret military uh uh you know it's like like tests yeah so let's talk about so let's say you've got this cool new toy which you call it a cool new toy you typically don't take your cool new toy out into an area where the cool new toy could get damaged or what if the airplane would have actually hit your cool new toy and you got two people that are ejecting or dead and you got a you know 80 million airplane that's now in the bottom of the atlantic you know tests are normally done in controlled environments just it's like any test a lab test or whatever when you take things out into the real world you know you're still going to test it in an area where something goes wrong so when they started and we'll go back to elon so my friend that worked there they had a rocket go off they were out in kwajalein and when the rocket went up a fuel line ruptured in the rocket and it ran out of fuel before it got all the way up and it came falling back down well when you're out on an atoll in the pacific if it's going up above you the worst case is going to land on you so you're worried about where else is it going to land and it actually crashed next to the atoll and and you know elon wasn't happy and threw this guy under the bus so um that's a test environment because you don't know what's going to happen so because someone said well when we chased the tic tac well it could have been some secret government thing well secret government things typically just don't come out and test to where unknowing pilots you can't control a lot of things you're exactly right so you go you know it's you know it's not the doctor evil scientist that's going to throw shit out there to get there's control and there's reasons that we do it because a lot of stuff especially when you get to there's there's you build something in theory you model it you go hey this is it looks like it's going to work you get funding you build it you test it some more you bench test it you know you like an airplane with digital flight controls before it even leaves the ground they've got things over the pedostatic system that are changing the what the airplane thinks is the airspeed talking to it and it's probably up on jack so the gear up so it doesn't it thinks it's flying it doesn't know it's sitting on jack stands and they're just changing the pressure on the pedostatic system so they can actually make the flight controls move and they can get all the data back to go hey it looks like it's going to work and then there's when there's a bunch of stuff that they do that's a control environment which you can do the testing yeah throwing shit out in the middle of where people are doing exercises is the most preposterous thing that i've heard is it possible yes is it more really is it is it is it more likely it's more likely they're not doing that yeah and the other the other side of that question is why do you think people on the nimitz and in the us government in general not freak out more at the incredible thing that you've seen freak out in a positive way freak out in the negative way like what are the russians up to again or or more like what is this like so more turmoil so if you to put a chinese flag on the side of it or a russian flag on the side of it i said yeah it had a big russian flag on the side of it dude then it would have got a lot of attention it would have went high order yeah right if it was you don't have to say russia or china just say if there was another country's emblem on the side of this thing that we saw and said oh it belonged to them then it's a big deal so here's what's going on so we're literally in the middle of workups and it was a joint workup normally they we go out for a month go come back do stuff go out for a month this was a two month at sea period where we actually had to beg for them to let us when the ship pulled in at thanksgiving so we could run home up to the central valley have thanksgiving with our family and then run back down and do this okay so you know and i had just taken over i had the squadron for a month right so i'm a a brand new ceo i'm the most junior guy on the as as far as the commanding officer goes for time in the navy and actually at the time i think it was the most junior ceo for o5 command in the navy right so you go okay so i'm out here i got my squadron i'm running it i see this thing you know we catch shit for it i have a squadron to run i have the the the tic tac was over here and although an extraordinary event i have 17 air crew and 300 sailors that i'm responsible for right their well-being making sure they're fed making sure they're happy they're birthing you know and i'm working with my master chief and i'm working with my exo snap and and we're going through all this stuff i don't have a lot of time to worry about the tic tac yeah if people need to talk to me so you got to remember you got the captain of the ship you got the airwing commander and you got the admiral those are the top three and you got the ceo of the the princeton who is a major command guy and that's really your big major command and then everything else is you got all the squadrons with your o5 command and you got the small boys that are out there which is 05 commands so in the hierarchy as far as rank and responsibility of what's going on i'm pretty much in the top 20 with all my peers and then i've got obviously the captain uh and the admiral right and then he's got some post-command guys on his staff that we were friends with i thought you were responsible for a lot of things yes oh yeah this schedule yeah there's missions you have to do a lot get the job done and there's no time for silly things that's exactly right so and we're the we're the integration you know when when a battle group deploys especially when you go to the middle east for what we were doing the air power is the key it's we take our airport with us we can park it anywhere we want and we can do what we need to do so we're kind of key players so when you get the theory that oh all these men in suits showed up so the captain of the ship never said anything to me the admiral never saying to and the people on his staff that i was friends with never saying to me the other ceos that i talk to on a daily basis never said anything to me and no one ever came and talked to me and i'm the guy that chased it so in all the theories and all the debunkers and all the stories because i don't know if people think they're gonna get rich on this because i made a big donut on this i can tell you what i got paid for i got paid to go out and spend 21 hours of my day going to la and do a five-minute talk for someone and i'm like and it wasn't for the talk because i'll talk for free because you're not paying me i said i said and then i got paid to go to the mcminnville fest because they my wife and i got to go because it was just look like fun because the whole town gets involved yeah and it's the only time i've ever spoken publicly in front of a large audience about this because it was just you know it was fun and i got asked and jeremy and george napping went the year before so i went with with bob lazar so i got to hang out with bob and his wife and his wife and my wife and you know we all hung out kind of you know talking not about ufo stuff but just getting to know each other as people because you know bob's like me the stuff that he talks about is not the center of his life if anything it ruined his life you know he's just a really really smart guy that's just like the rest of us trying to get through life yeah that's nevertheless i mean that was one of the sad things reading um uh louis lozando's resignation note from his uh uh he was the program director at the uh atip program like alright yeah one of the sad things is that he's mentioned that you know people in government just don't take this seriously as a threat like ufos as a threat like you said if it doesn't have a russian label on it it's a it's a sad thing to think about that that we have such a busy schedule that the anomaly it doesn't is a distraction that we don't want to deal with and it kind of just fades into history like literally it's kind of sad to think that if aliens showed up like and uh it just didn't it because they're not like when aliens show up they're not going to be a thing that's on the schedule and if they don't start killing people they just kind of show up in some very uh nonchalant peaceful way briefly people would be like that's that that's uh i don't have time for this that's so sad it's like anywhere in the world so you know go back let's go back way back way back in the time machine you know there were people kind of scattered around the globe you know in europe's a perfect example why does france speak french and then right next to them spanish you know spain speaks spanish and then you kind of jump over and germans or german and the polish people everyone speaks a different language because if you look at the way the terrain kind of subdivide the original people that were there you know thousands of years ago they speak differently right you'd be like the us but see the us is different we all speak english because what happened we came over and we started on the east coast and we migrated west we won't get into the you know what happened and you know because the native americans all spoke different languages yeah you know it's that same type of thing so but anytime we have a tendency to show up you're you're actually you think about you're an alien if i go to a different area if i just you know go back 500 years where you know or a thousand years where travel we weren't traveling across oceans at the time we were well we don't think we were the vikings probably were um because we had limited you know we had to have supplies and the boats weren't as big we had to build them by hand we didn't have power tools and all that stuff so you know if you show up someplace like when the conquistadors from spain came over into south america and you've got you know the natives you're actually an alien you know and then you look at what typically happens when aliens show up in in a human alien world you know and when i say alien i mean you are not from that area the other we we take what we want and that's what happened i mean we literally defuncted civilizations because that's how we are you know humans are we're an interesting group so you go now what what if something is from someplace else just let's just let's just go off the grid and go ah let's say there are little green men yeah what are their intentions lou asked me this when we were talking to lou alezando and he said what do you think they were here for us i don't know he goes what i go hello they were observing they'd come down they'd hang out he goes what if they were prepping the battlefield what if they were observing to figure out what we do and you go that's interesting the other theory is maybe there's a more advanced civilization out here and they just check in on us because the threat to an advanced civilization is when a civilization that's inferior to them actually develops enough and fast enough to become equal or above because now these they become the threatened type so you watch us grow until we start getting too much you know it's kind of like you go well because they always have a tendency to hang out around nuclear right and you go well you know they're if this is an advanced civilization i'm gonna go science fiction kind of comical they come down and watch us and go look at the the the crazy upright monkeys now have developed the atom bomb let's hope they don't destroy themselves yeah if i was an alien civilization i would start paying attention with the atom bomb that's why the i mean there's certainly an uptick of uh what is it ufo sightings since since the nuclear since the nuclear era yeah that's you go um let me ask a little bit out there question maybe it's a speculation but maybe touching on roswell do you think it's possible that there is out of this world aircraft or beings that are in the possession of one of the governments on this earth like the us government is it possible so the one perspective of that if it's possible is it possible to keep a secret like that i would say this i think it's very it's highly possible because if you go if you just look at all the sightings and let's go just look at project blue book oh it was what forget how many thousands of sightings and there's a percentage it's like 10 or 15 percent they still can't explain like our tic tac is one of them you know they basically the government has come out and said we don't know what that was okay so so if you go okay of that fifteen percent that we don't know and of these thousands they're still that 15 makes up a pretty big number what are the chances that not one of them crashed somewhere on the globe and was recovered and i don't care if it's a intact system or you got pieces of it of a metal that we can't explain or some some um biological matter to say the least it could be intact or it couldn't but the the odds of that now are starting to go down that you know that could never happen and i'm not talking just the united states i'm talking the world globally so is there a chance that a foreign government actually possesses or our government or someone in the in the world on the globe of the seven plus billion people has something that is not from this world and i'm not talking to meteor but something that was manufactured in some way that allowed transport or observation it could be a drone could be a foreign drone you know like voyager flies around and does all that stuff and we got stuff that just went past pluto that's out in the kuiper belt you know there's there's stuff out there floating around and what about ours it's going to crash into jupiter eventually or whatever because we've had stuff crashing the planets so if that's the case you would think something is out there that we have something that we can't explain and according to lou there's stuff that we can't explain you know and i would assume that lou who ran atip has has seen stuff that he can't openly talk about because you know because i had a clearance when you have a clearance you were you sign your name you're bound to that and to me that's an important oath that you hold to you know this is kind of where uh you know people have issues with bob so if you know and i leave it to you to determine if you believe bob or not i'll tell you bob is a straightforward very sane normal super smart guy bob sorry yeah yes there is the other side that says well should he have come out and talked you know to those who owe clearance who you know are true to the government you would say he should have never spoke he he was under an oath to not say anything but he did if you asked bob why did you say something his the his answer was i understand there's an oath but i felt that the technology could benefit all of mankind and it shouldn't be locked away and i'll leave if you believe bob that's that's kind of what bob says and that that's such a interesting key point if there is aircraft a technology that's in the possession of the say the us government should they make that publicly known this is the snowden question this is the question of like do we release stuff that can potentially change the nature of human civilization like the the way we the way we think about our place in the world also the if that technology is potentially useful for military applications the nature of military conflict should we release that information or not if you were the government so here well here's exactly how so for for classified information the government is the people that classify it so i can't go i can't look at something and go oh my god this avion bottle is now top secret i can't i don't have the authority the ability or anyone to do that that's the guard that's up to the government i agree with that because i worked for the government for 24 years of my life so um i understand that but now you go there's reason stuff is classified okay and it has to do with uh sometimes information is classified by how it was obtained it's just like the mob if i have a spy and i'm a mobster and you're the counter mobster but i have a guy on the inside that's feeding me information i can't do it and a perfect example is if you've ever seen the uh it's the tom cruise movie what is it air america or whatever but he he plays the guy in louisiana who was hauling drugs for pablo escobar and he ended up getting a cargo plane and the government the cia was kind of funding him to do stuff that's how he got hooked up with pablo but they put cameras on his airplane and when reagan had come out and said here's pictures we have proof that they're running these drugs it didn't take pablo long to figure out those pictures were taken from inside of the plane of this guy he had been working with and that guy ends up dead does that make sense so you classify to protect the source you classify to protect the technology because if the technology would get out it could be grave damage or there's levels depending on if it's a secret or top secret there are levels of damage that can be done to the u.s government and our well-being as a country and we owe it to this because we're all americans you know to me no matter what some people will say even in this country this is the greatest country on the planet this is the only country that you have the ability to do what you want to do it's just don't be lazy and i have stories of people that came over here and started with nothing and they're they're living the american dream and they'll tell you and they didn't get it because of you know like you you came over here from russia you get no minority status or anything else you get you're a white anglo-saxon protestant whatever you're religious you're over you but you come over here i kind of knew that from the last time but um but you come over here you basically have made yourself you're educated you're working at literally the top research university in the world to be honest um i can do whatever the hell i can create and with a bit of with a lot of hard work i can do quite a and no one gave it to you yeah so i mean i'm a believer that like i mean we are uh a community so like there is a social aspect to it but the freedom and the american dream is a real thing and that this is this i you know i joke about being russian but i i'm an american and this is i do believe the greatest country on earth so there's a reason the nationalist pride uh the pride in your nation is a powerful thing and around that this secrecy holds value but to me alien technology is bigger than that i mean it's it's not so much a threat as a you're holding back something that could inspire the world like human knowledge so let's talk in theory so i'm gonna go back to bob because i've talked about so bob is a propulsion guy right right bob has a bicycle with a rocket motor he built the rocket car you know so he did that so if you are trying to figure out a propulsion system let's just say this is i'm just talking this is dave's theory i am i own i have i have custody of this thing from a technology that i don't understand and i know it's a propulsion system so now i gotta figure it out right so who are you gonna go to right you go find someone so you go wait here's a guy who at the time was working at los alamos which they have proven who is big into propulsion he designs all this he builds a shit in his garage hey he's super smart why don't we bring him in so you hire him on a contract and you go hey we're going to brief you into a program and he goes and works on wherever he says he worked you know that's not important but you get access to the technology to try and figure it out and then you go well you know bob comes out and says you know like we're figuring out these things but there's a part where our technology isn't advanced enough for us to figure the whole thing out so then you know and let's just say bob doesn't come out and tell anyone he he works on it until he gets to the point where he's stagnated he he said he's in a wall you go i can't do it so sometimes the best thing is to bring in a fresh mind so you go find someone else who's in a propulsion you bring them and they work they can't figure it out or they get to the point where kind of back to the einstein theory where hey i've got all these theories on how it works but we don't have the technology we haven't advanced enough to actually do what we need to do we still have to advance technology more so then what do you do you shelve it you go hey good project's over and the contract you shelf it and you wait another 10 years and you wait another 10 years until technology and our abilities and our our research advances more and then you go find new people to bring in that are experts in that field and go hey we want you to work on this thing and here's what we know about it so far or you don't tell them anything because because remember if you if you reveal someone else's research you can taint their beliefs they'll start to sway in that direction so you go i'm not going to tell you anything i'm going to give you this thing and now you tell me what you think and as they progress if they get stuck on a problem that maybe bob and someone else solved earlier you can go hey what about this you don't have to tell where it came from what about this and now they can leapfrog and they get another two steps closer to the final answer and then we get stuck by our evolution of technology do you shelve it again do you think that's the right way to do it because it's heartbreaking i don't listen i love government but we just had this discussion about elon and so on the the alternative approach is to release this to the world and say there's a mystery here and then the elons of the world the jeff bezos who talked about money but it's also not just money it's like this engine that's within we talked about the american dream to say i'm gonna be the one that cracks this mystery open and like that's within a lot of us and like money aside people in their garage just will but you're thinking like a scientist now let me now let's shift to let me think like a country so we have country a b and c and you can look at the nuclear arms race so we know that germany was really close we know that russia was getting pretty close we just won the race and we were the first ones with it yeah and still to the state germany could have won they could have won they could have won but someone was smart enough to not finish the equation when they knew they had the answer it's literally what it comes down to someone was smart enough to realize that that that got into the hands of the nazis that it would be the end and and that's that's a tough call to do that knowing that you have the answer and you can't solve the problem because it will go into the wrong hand and that's kind of the fear when you look at this you go okay so if we do this if we put it out there we've got this technology if we don't work on it kind of international space station like we're all going to work on it together in uh you know like antarctica is really supposed to be treaty free from any weapons or anything we're supposed to we got the international thing down there we're all going to work together if you did it in the confines of that and you could control the flow in and out because what you don't want is the someone stealing information and getting it back to where and countries are notorious to do this hey we're doing internationally but we're secretly doing it ourselves to see who can come up with a solution first that's the problem because we have this inherent thing of power and technology like that is power it would literally change the game of the way the world operates and from not just a transportation or mankind but from a military aspect it's got huge huge uh yeah yeah i guess so beautifully beautifully presented and there's i feel like there's a tension between those two places the scientists view the world and the national security view of the world let me let me get to this kind of interesting point which is a lot of conspiracy theorists kind of paint a picture of government as an exceptionally as a hierarchical system that's exceptionally competent and good at hiding secrets and then i mean i tend to not subscribe to almost any conspiracy theory to the degree at least that the conspiracy theorists do uh i agree with you but the there does seem to be and i tend to think of government as unfortunately uh uh incompetent at least the bureaucracy it seems that the communication like the three videos that were released and just the way of dod in general talks about the things we've been talking about it's just confused it's contradictory it's not inspiring it's it's uh suspicious it's just not even the way they release the videos you know the tic tac if presented correctly could just inspire generation of scientists it's like at the you know us going to the moon and it's inspiring i mean it's incredible like you know and and the way it was released was suspicious it was like low resolution video on a crappy website like with some crappy documents and uh i mean why what i don't know how to ask this question but can government do better why are they doing it this way in terms of communicating the things they do know to the public because i don't think they know how especially in this topic it's been hidden for so many years and i don't think uh because i don't buy off on the conspiracy stuff i just think that you know when it comes in like i said you know the government has a right to classify stuff they they classify everything because they don't know you have something you don't know what it is you don't know so we just go well it must be must be top secret and let's put it in a vault you know it's kind of like the indiana jones where they take the ark and they put it in the it's in the giant army warehouse um you know we don't even know what we have so but i also believe that you know and i'll say this openly i don't think that the american people need to know everything i think there's a reason that stuff is classified for the protection of this country and i totally believe in that so you know and i was joking with joe when he was talking about storm area 51 stuff i'm like yeah that's probably the worst idea you could possibly have is to just storm a military installation it's just stupid there are reasons there are reasons that we have things that we don't just let out to the public because if we do as soon as you do let someone know that you have something they immediately try and encounter it a perfect example the u.s and the 60s developed a bomber it was a mach 3 compression lift bomber called the xb70 okay there was three of them built three of them ever built it was a like 60 000 foot high you know mach 3 it was an incredible airplane when you see it there's actually the last one remaining is in dayton ohio at the museum you know it would go that wingtips would fall down it looks like a concord but it's way faster when that got out that we were developing it the soviet union developed the mig-25 literally a high-altitude interceptor to counter that bomber and they built an entire fleet of mig-25s right we built three xb70s and we scrapped the program right because now you go well it's the technology is cool we proved it but now it becomes obsolete so it's not even worth building a whole fleet of these things you know it's constant it's a chess game we do something they do something we do something they do something and it's we do something and then they counter it they got a fee it's you got to figure out how to defeat it so you go oh we'll build something so the more we keep uh quiet especially from a defense standpoint the better we actually at person i think we talk too much and i think the the military and the dod is starting to see that you know we're too open you know you know you announce hey we're building this because there's a budget line and we live in a free society um but you don't have to release all the specs and you don't have to put everything in open source but that's a problem when we go to the universities if we want to go do work with mit and you want to partner with mit and you're a defense company and you want to partner you know you guys have a rule that if you create it then it can be open source because the university owns it and we are an institution of learning yeah where the defense side might go we don't we don't really want that published in a paper in scientific america or i call it a break i talked to the cto of lockheed kaoko jackson and just just conquers the some of the best if not the best engineering and science but engineering really ever is done in secrecy and it sucks because it's so inspiring and they can't talk about it it is due to funding the us government has deep pockets you know some of this new technology that you develop for an open source unless this goes back to the original conversation we now there's enough money in the private sector that individuals control yeah bezos i'm not talking amazon i'm talking jeff bezos a single individual worth over a hundred billion dollars he has the ability to do stuff i'll tell you what the gates foundation with between bill gates and and and his his wife and warren buffett and some of the other money because i think uh bezos's ex-wife actually donated a huge chunk of her half into the gates foundation so i mean what's the gates foundation worth these days you know if and these are guys you know brilliant brilliant i mean some of the greatest minds that we have to go you know what are they doing because they have the ability it's a non-profit they can go hey i want to fund this i want to fund this research they can look beyond the conflict between nations you can look beyond the conflict of having to have you know classification you can do what you want you know it's just like you know we we classify how to do uh you know the whole nuclear you know how to create critical mass right but there's really smart high school kids that have figured out mathematically and they do their science project and then the government comes in and says hey we got to classify your government because we just don't want this out in the public domain which i understand but they never stop them from free thought and developing that it's just we really don't want this out there okay so i understand that i totally understand that but if they you know if if bill and melinda want to do this and go hey we want to do this and they're going to work with bezos and they're going to work with elon and we're going to be think about it there's a significant amount of money that could be available to r d and i'm not talking just science like this i'm talking medical research and all this but then you go who gets it because now you're competing against the companies that actually do it you go is that well are they the greatest minds i'd say you know that we have a tendency to go these are the best that we have and i'd say well no that's the best that we know we have but there's probably people out there that don't want to work there's brilliant minds that don't want to do anything with defense because they just disagree with what it does so they go to another path they can do something else and that in a sense like the elon's of the world that jeff bezos actually in a certain sense much better than uh dod at finding the brilliant weird minds out there because they're not tied to the government so when you work a government contract the government writes they tell you what they want and then they work with you on the requirements and they usually have a an end in mean you know they have an idea that this is what i want it to be where if you go to like spacex where you know they come up with why don't we just land these things on a pad and reuse them yeah well if the government scientists if you're on a government contract says no that's not the requirements we're not paying for that we want you to do this you're kind of controlled or when elon does it his company they can do whatever the hell they want to do because they have no bounds the only bounds they have is the liability if it doesn't work and it lands on something so what do you do you go out to kwajalein and you test it and if it crashes and it lands in the ocean hey we clean it up no big deal we lost some money but we'll move on it's you know money makes the world go round contrary to what everyone thinks but you know there's a lot of money that's sitting around that you can do a lot of really cool stuff with and i don't know i mean i'll guarantee that uh what is it blue origin isn't that amazon yeah you know that they're doing some cool stuff because they have funny and i joke with the guy i know that worked at spacex and he was funny because they were building the first test thing and they they were limited and elon found this like 400 acre thing i think it's about 400 acres down by waco texas and he's like i go how he goes he goes dude i worked he goes i worked with he goes because he's done government contract he goes there's government contract and then there's working at spacex with elon money and that's what he refers to it as his elon money where it was like don't i'll throw them and he would throw the money at it and make it happen and it's i'm talking this fast yeah i mean he talks about he has a great story about this i mean this is elon this is how fast you can do in the private sector vice the government where there's the bureaucracy is they had a company that was a basically a tool-and-die machine shop that did a lot of their high-precision parts for the rockets they had went to the guy but he had contracts with other companies and when the economy was down the guy was actually looking at going out of business so the guy i know he's telling me the story he he was talking to the guy he had to go over there and get something and he's like holy shit he goes hang on so he calls up on the phone spacex he says hey is elon there can you get him in the board room we'll be there in 20 minutes so he grabs this guy who's literally going to fold his company they go over to spacex and i may be getting some of this wrong if people are going to fact check me but this is pretty close they go in the boardroom and and he said literally within like you know an hour or two elon has bought the guy's company that guy is now a senior vp running the his company and they're gonna pull all the stuff into the spacex thing so they can actually build the parts and they can still contract out to make the money outside and it happened like that fast it's not just money it's because i've seen i witnessed it too with elon i think it's uh whatever the whatever the forces of capitalism that that uh allow a person like elon musk to rise to the top but like because i've also worked for darpa like for research for in terms of a source of funding i i there's a weight of bureaucracy when i was working like being funded by darpa and with elon like i was literally in the presence of like anything is possible cutting across all the bullshit of paperwork of the way things were done in the past of the bureaucracy the rules the constraints the all of that stuff just you can cut across immediately how much money and time do you waste dealing with your bureaucracy when you could actually be doing real work that's the difference this is why i honestly when i went back to the industrial defense complex that we were warned about when you look at it and go spacex can do something for half the price ahead of schedule that would boeing were paying boeing and you go oh well this just came out you go well then why are we even dealing with this side when we can deal with this side yeah because you've got a fully automated capsule that has a manual mode that they got to fly around in it worked like a champ it went up it hung out it came back it splashed down it worked perfectly you know we're gonna dust it off and oh by the way unlike the apollo capsules that were used and then put to museums they're going to reuse that dragon capsule it came down they're going to dust it off put a new coat of paint on it slap it on top of another rocket and away it goes holy cow it's amazing it's a shift it's a complete shift and mentality and for us as taxpayers we can explore at half the cost yeah it's exciting especially given putting the tic tac in context like then the sky or but it's limitless the possibilities we could do with this kind of mechanism i think it's exciting yeah i think we live in an exciting time right now besides everything that's messed up in the world right now well this is a this is a hopeful like there's so much conflict going on so much tension uh that's to me space exploration at the moment is a reason to uh get up in the morning and have a hope for the future to look up to the sky and we're humans we can like solve so many we can solve all of this i was talking about when i was doing the tucker thing and i said uh this would be great you know because when the government had come out you know a month ago and said hey this does exist we're doing this and we're going to release more stuff and i was texting like lou and chris mellon and those guys before i went on because they had called me up to be on tucker's show and i'm like hey i go you know this would be great you know just come out with this find the the relic of a spaceship like pull out the roswell wreckage if you have it pull out the roswell wreckage and do it god it would be so nice to not have to deal with the the riots in the cities and i mean i know it's an election year and all that but god it would be something it would be refreshing to not have to turn on my tv and see everything that is just depressing in the world to begin holy cow we actually do have this and we're working on this technology imagine if there is a roswell aircraft and they pull it out imagine the innovation that happens in the next 10 to 20 years without any more information than that just the innovation that happens the look on elon musk's face look on jeff bezos's face and all the brilliant engineers we changed the game it would change it would change the game completely let me ask the big question i apologize for the absurd romantic nature of it uh outside i mean one of the things the fact that you've laid your eyes on a ufo probably opened your eyes to the possibility that some of the other sightings there there could be other sightings that have legitimacy to them what to use the outside of your own sighting is the most interesting citing or ufo related event in history i think there's several what is it ramishine forest in england uh the u.s guys that saw stuff and actually got radiation burns one guy was medically disabled but they weren't going to give it and he had help from jim carr john mccain his office helped get the guys uh disability reestablished i think that's a big one uh i think there's people out there that have seen stuff and i'm talking credible uh because there's you gotta remember there's a huge chunk of these sightings that get disproven they're they're actually explainable yeah uh you know you had sent me the question the the phoenix lights i think there's what's that so i'm sorry i'm not familiar with some of these the the uh i'm not either it's i want a funny story on that so i was at a i was at a conference and hopefully he doesn't watch us to get offended but we had this uh this it was i call it speed dating so there's a table there's about eight people at a table and we would go sit at the table and they could ask us questions and then after 10 minutes we moved to the next table so i was speed dating all these people that are really into this yeah it was kind of funny but i'd sat down and it's always funny because some people will try and dominate it but you know you have to kind of push the dominators away so that you know if you're quiet and introverted you can ask your question too so we got into this and the guy starts naming all these well what about this what about the phoenix lights i'm like i don't know about the phoenix lights what about this event i don't know about that he goes he looks at me and he goes well you're not a ufo guy i go no i'm not but i chase one so i'm an expert have you and you could see him get deflated because i'm kind of a smart ass like that yeah i mean the first hand experience from a credible in some sense these sightings have to do both with the evidence and the human well i think part of that is to us that's a credibility piece because the four of us that actually saw it plus you know the other two that were in the airplane that shot the video none of us are ufo obsessed people so when we come out and say because to me it's just it's five minutes of my life i mean i did a lot of really cool i've had really kind of neat things i've been able to do um but when you look at it and go uh we don't it to me it wasn't it's not the pinnacle of my life you know to other people that they live in the ufo world and it's like they you know if you talk to people they'll go that are really into it who've never seen one it kills them that they didn't see one when here we are because and what's unique with ours which kind of adds that level is it wasn't we just didn't see it it wasn't like oh look something in the sky and it was weird we actually engaged with it you know it was yeah that was an engaged five-minute thing and there's other stories from other countries like there's a story of in the back in when the soviet union existed that they actually would chase these things and one of them shot at some you know it shot it because they said shoot at it and it shot it and then it got shot down and then they said don't ever shoot at them again and don't chase them just you can observe them but don't go after them because obviously they have firepower that we can't control because if you can make something float around and jam radars at will and do whatever you want you know modern terrestrial weapons are probably not very useful you know you can go to independence day they add that force field around oh we gotta we gotta now you gotta cyber warfare you gotta take the bug down you gotta take the warfare so now we can actually inhibit some type of damage so there's a i mean you mentioned the phoenix slices somebody on i think read it said uh ask him any thoughts on mass ufo sightings like the phoenix lights so the interesting thing like you said with the tic tac is that multiple people laid their eyes on this what what are your thoughts about the phoenix lights or many people have seen here's the deal with massive sightings so the phoenix lights is unexplainable although i know the air force had said something about it was an a10 drop in flares no i don't think so yeah oh flares don't burn that long they just come out and they you know they detract when they go away although on the other hand there's you know because clouds can do things so so i lived in central california for 18 years and you would get oh my god what was that in the sky and it was really vandenberg shooting a missile off you know they were doing icbm tests at one time where they shoot from vandenberg and they fly across and they go land in the atoll at kwajalein you know and then they can check the displacement the accuracy and all that stuff you know it's stuff that we do because we're a power but when you see them go up you know especially if you've ever watched a rocket really launch on a clear night it'll have the stream the glow and you can tell it's a rocket but if you don't look up until later when it starts to get to the outer edge of the atmosphere where the plume coming out of the engine is not constrained but you can watch this on tv when leaving the spacex ones go it's nice and narrow narrow narrow and then it hits a point where it really starts to go up and it starts to come to the sides because there's the forces aren't holding that all into one unique thing and it looks really odd and then it'll go off because it burns out and then you get stage separation then you see the next one go off and then it's gone um and people don't understand that because they didn't watch it from launch because we used to sit in our driveway and you know vandenberg is it was a three hour drive but you could sit and watch it go you knew they're launching at night you'd watch you watch thing it's really cool if you don't see anything what you see is the weird clouds from the exhaust plume you know what's left the residue that's sitting in the atmosphere and the wind starts blowing it so you get these really kind of weird shapes in the sky you know that's part but when you go to phoenix lights and you go hey you know when when a thousand people see something you're gonna discredit all a thousand people are you gonna try and explain it away with something else you know you know the big it's a weather balloon you know it's a weather balloon again just like the tic tac i think is just inspiring uh for the limitless nature of the science i think you're i think more is going to come out i think some of the stuff that the the to the stars folks have done uh so there's a stars academy yeah what are your thoughts about them are they um i talk to them quite a bit um i am not a part of to the stars academy i you know but you know like i talked to lou i just was texting him before this yeah so he they're what's their mission what's their hope what's their what's there when they started their mission was to try and don't look at this as little green men but let's look at this as a technology and let's try and almost reverse engineer and figure out how these things operate and how can we explain this from using our knowledge you know physics based knowledge to go how would something like this operate that's really their bottom line was to try and use and then couple that with because they've got the series unidentified um couple that with television to get the word out so you're actually putting something instead of because everyone has a theory you know ancient aliens covers all kinds of theories you know it's kind of off of oh my god and i've seen the stuff and i've seen stuff that i've said taken out of context on shows that i did not talk to uh so there's all that because you can take a clip and go oh it's this it's that you know and if i know about stuff like you can't technically use my likeness unless i tell you you can so if i haven't signed something you can't do there was a guy who put something out and i was in it i told him you can take it down and you talk to lawyers because i'm not i'm not supporting you so they use it to tell some kind of narrative that this is not connected to let's face it if you're making tv shows there's two reasons to do it one you want to get word out or two you want to make money or three both and so usually it's i would say the the make money is probably the biggest thing to put a tv show out and the the mission of the to the stars academy is to not do that this is is to try to get some when i when they started and i talked to them because i've talked to tom and i've talked to lou and those are the two main players it was to basically demystify the fact and get rid of the the stigma that's tied to ufos and let's look at it from a science base and then use tv to get the word out on the progress and they've done some pretty cool things i mean you know they've the the italian government gave them all kinds of files that had been you know property their government they got a bunch from it might have been argentina gave them all kinds of stuff like here's all our records what can you do with it to try and now pull from country based to a more global based research which is what you were talking about and then using independent scientists that are not tied to a government i mean any government but just using independent research agencies to start looking at some of the metallurgy because you go oh i found this we had this piece of metal what is it and some of the stuff has been explained they've got some objects artifacts that have not been explained and that's slowly coming out you know and i think uh and your hope is the us government will release well the government is the government the us government came out a month ago and said you know we have we have uh we have material that we cannot explain the origin they have said that they just haven't released the wreckage from the roswell thing which i keep joking about i'm like come on it's 70 some years old i mean let it out i i think he put it beautifully that in this time that would be a heck of an inspiring hopeful thing to see like people don't just to distract them yeah the division is i mean nothing will unite us humans descendants of chimps uh like uh the idea that there's life out there oh it would literally change i said this a while ago i forget i think as the london sun times had called me and i said you know personally i think this is a global issue it's not if there is stuff coming down which we're pretty sure there is there's enough stuff that we can't explain if there is stuff coming down then this is not a country based thing and it's not about technology and it's not about who's going to win the next war because you don't know what they're doing so you got really a couple of theories one you've got e.t or close encounters and the other extreme is you've got independence day are you going to prepare and bet on et and close encounters or do you actually try and do stuff in case it is independence that you actually have a game plan and when you get into independence day that scenario you know and i don't like going too much into sci-fi but let's just say in theory that that becomes a reality it's not a us russia china england france spain name any country and any continent it becomes a global issue and the only way you can deny it's just like americans we all you know we're divided it it's been that way forever so if you think we won't get through this we'll get through it because we've had times just like this before until nazi germany pops up but in nazi germany pops up or someone flies two airplanes into the world trade center and then all of a sudden we're all like united we also have very very short memories yes we do exactly it's when you look and go uh well we can do this and you go no no if if you think that everyone on the planet is good you need to stop taking the drugs that you're taking you know we said this there were people during the rise of hitler no no it's it's okay no no it's okay we're not gonna do we're not gonna stop no no it's okay no no it's okay and you gotta think the only thing that stopped hitler was his ego by going into russia if he just stuck with the pact with stalin and not went to the east and had to fight and it was really the russian winner that crushed him and he would have put all his high troops to the other side there would have been a totally different outcome the man in the iron the man in the high tower whatever it's a netflix show where nazi actually wins it and you look you know we didn't know everything that was going on especially the atrocities with the concentration camps and what he was doing to to the jews i mean it's you look at that going if you really want to see evil and then there's the whole side of what stalin did because he actually exterminated more people than hitler did but that never gets the press and the thing is we forget this we forget this history in our conflicts today we forget that there is the nature of evil we forget that there's real evil in the world and um the thing to fight that evil is to be united to be uh both it's like this interesting line like you talked about joe rogan of being both like kind to each other compassionate empathetic but also being like strong and a bad motherfucker when you need to to make sure that you that like there's a balance between kindness and force that is you you use force when force is necessary but you don't have to walk around like billy badass all the time i mean some of the toughest people that i grew up with that literally could kick the shit out of whoever came near him they never got in fights because one even people that didn't know them because they were actually nice guys you know they were they're just good dudes but you know if you cross them like i had a friend of mine uh he was he's a nationally ranked wrestler he went to went to naval academy with me he's a very very good friend of mine um and uh he is when you meet him and he wrestled at 190 pounds and he did not lose a match his senior year until he went to nationals he just had a bad day he actually lost to a guy he had pummeled the shit out of and he would cross it was funny we we joke about it even with him because when you meet him he's like the nicest like lo go hey hey dude you know hey how you doing he's super nice he would cross that ring on a wrestling mat as soon as he crossed that ring it was like a totally different person and he would go out there and just destroy people i mean physically destroy like put a hurt on and he would get done and he's like super humble and they'd raise his hand and he would he he'd have this blank expression they'd raise his hand and he'd walk off and as soon as he crossed the line he'd he'd look up and smug hey hi guys how you doing like he literally just went could rip someone's arms off but as soon as he crossed line he's a totally different person he's like and he's that way today yeah he wouldn't even tell you he's a wrestler yeah that's kind of a symbol of the best of america that's what america is oh he's that wrestler he's across the line you're you're uh you could be hard but when once you're off the mat you're just a kind human being yeah i know you're super humble uh saying it's better to be lucky than good but your story is inspiring that the entire trajectory of having a dream of accomplishing that dream of having one hell of a career what advice would you give to a young person to a young version of yourself today that listens to this and is inspired that wants to fly or wants to go to space who wants to build the rocket is there advice you could give them about life about career about anything yeah yeah um first let me start with uh and you had a question on inspirational people so my grandfather i had mentioned him earlier a huge funeral a beer delivery guy um was delivering beer and the 60s riots were the the guys the black in the black neighborhoods where you know white people didn't go and my grandfather's sicilian he was one of the first ones in his family born in the united states so my great grandmother and i had aunts and uncles that i knew growing up that actually came over on the boat um huge huge guy and just the nicest friendliest would give you the shirt off his back obviously proven by his funeral and i'm talking at his funeral the head of the black panthers was at his funeral in in toledo ohio the mafia guys were at his funeral in toledo ohio uh i mean it was literally a mix of of of who's who and he had told me once you know because when you're little you start looking and i grew up basically i was probably middle class lower middle class my dad was a fireman you're not rich he's working for the city it was a paycheck to paycheck living is how i grew up and i was talking my grandfather one day and he said something to me and this is this is literally how i run my life he said it was about money because you'd see you know back in the day if you saw someone in a mercedes that was rare you know they weren't everywhere and you know people didn't you couldn't lease a car you actually bought a car and usually bought a car with cash um so it's a totally different than we are now and he said he goes you know david he goes they're no better than you and you're no better than anyone else he goes you got to remember that he goes everyone's different he goes treat everyone with the respect and dignity that they deserve he goes and if they're poor if they're homeless he goes it doesn't make him a bad person it just that's that's who they chose to be and you make choices in your life but never ever look down on someone because you know there will always be someone that will look down on you and you should never ever do that and i kept that close to me he was a huge influence was my mom's dad um just a big big influence in my life and the way i carried myself um and he was one that would say you know you can be anything you want to be you know he grew up dirt poor you know and the fact that he had bought a house and took good care of my grandmother and did stuff like that you know to him that was a success and to me it was always you know trying to better and move on and he was the one you know my parents were a big part of this too was instilling that anything is possible so when i'm four years and 11 months old in 1969 you know and i'm watching neil armstrong walk on the moon and i'm asking my mom and she says well they were all military pilots and you know we had an international guard that at the time was flying f-100 so i'm dating myself um and i was just fascinated with flight and i just looked at that going that's really what i want to do and i never lost sight of that there was always i could do this or do that and when i was going to go to college before i enlisted in the marine corps i was accepted into natural resources at ohio state and i'm like ah if i can't fly i'll go be a forest ranger because i wanted to hang out in one of those towers in colorado and look for fires because that's just i like that stuff you know it was that or be an oceanographer because i was fascinated with jacques cousteau and i actually that's my degree my undergrad degree is jacques cousteau so influences are neil armstrong and jack cousteau i have an oceanography degree i got an mba from university of houston goku's got to mention them and then uh and so you're looking people go what are you what are you going to do with that and i said you know i got an oceanography degree because i go well i'm going to sail on the ocean so at least if the ship sinks i'll know where i'm at and that was a kind of a running joke and then and then there's so these passions and underneath it is the is the belief that you can be anything you want to you can you know i told my kids this you know when they were young you know it was tough especially for my son so when nate was about five six years we knew nate was colorblind you know my my wife's brothers are both colorblind it's really color deprived cleared applying you see black and white he can't tell he has issues with greens reds browns it's funny if you're ever around someone like that because he'll go i'll go what are you looking at he goes right over there by the red thing i'm like what are you looking at i go this i like he had a hat on one dagger which one are you gonna eat he had a hat in his hand it was green he goes i'm gonna get the green one i go oh this one right here he goes no the one in my head i go nate that one's brown he's like leave me alone dad he got the brown hat because to him it looked great yeah so he couldn't fly he came he said i go what do you want to do nate you know you're talking to your kids and what do you want to use i want to be a pilot no now i got to tell him because he's looking at me because i'm a pilot do you can't be a pilot he's like why can't i be a pilot i said because you you got eye issues you know so you got to redirect and the other one was because i had i stopped flying i was 42 years old and i was like and it was my childhood dream so it's like a pro athlete i know exactly what it feels like when you know brett favre has to walk away from the nfl when you still can do it good choice of quarterback by the way the greatest of all time but whatever so you you do when you look at it and you go i understand what those guys feel like when you have to walk away from something that you love and you think you can still do it um so i told them i said look i was talking to both my kids and i said you know find something that you want to do that you love to do and that you can do your whole life and you should be able to do good things for other people you want to be able to help other people that's what i said so both of my kids and there's no one in my family both of my children one of them is my daughter is a doctor doing residency in internal medicine right now and my son is in his third year and they're both going to be doctors and until i look at it is you know people go oh you got two dogs i don't care i told my kids if you want to be a garbage man or you want to dig ditches i don't care just be be the best ditch digger that you can be i said and be happy doing it because what you also find is that we are in this big pursuit of money money money money money might be that's what makes the world go around but what you realize and i'll go back to my grandfather who didn't have a lot of money and he was probably one of the most happy people on life and unfortunately he died he died at 65 he had a massive heart attack because he didn't tell that he he kind of knew what was happening and he just made the choice to to do and it was devastating to the entire family but he didn't he didn't have a lot of money but i'll tell you what i know a lot of rich people who have funerals and there's nobody adam yeah and my grandfather who's a beer delivery guy had i i i it literally it was like three miles long the pope it was crazy yeah who died that was because it was like he's a catholic he's just you know italian he goes you know who died the pope and i go now that's my grandfather and then the next funeral i went to was my aunt his sister and there was like you know 30 people and i looked at my mother and i said where's everybody at she goes oh no this is normal this is what a normal funeral looks like so it's you know for young kids bottom line one be nice kindness will get you i'm a big believer in karma kindness will get you a long way in the world you know it's easy it's it it's easy to be nice it doesn't cost you anything i said you know and get rid of the hate and number two is follow your dreams because everyone is capable of everything and there's a there's a self realism like you know if you really have trouble with math getting a phd in applied math is probably not something you're going to be able to do but understand yourself what your own capabilities are and you know inside your heart don't let anyone ever tell you what you can and can't do you have to determine that yourself and go for it and and and you can do anything it's just it's it's a great the world's incredible it really is let me ask the last yeah big ridiculous question uh so you've lived much of your life your career is kind of at the edge of life and death so let me ask kind of uh several different ways the same kind of question one d do you have you pondered your mortality the finiteness of it and the bigger question to ask even in the context of your uh tic tac encounter is uh what do you think is the meaning of this uh thing we got going on here the meaning of life human life in this sense so let me start with have i pondered my own mortality yes quite often um and i don't get into my religious beliefs or what i am but i will tell you that i do believe in god i've just seen too many things in the world that i can't explain and some people will explain it by subconscious so i'll give you a story and this kind of puts in the thing of do i fear death so i had a good friend of mine that i used to fly with we were stationed in japan together and japan had this incinerator that put all kinds of dioxins so there's a real high cancer rate for those that served on the base in atsugi japan him and his wife had one son and their son passed away just before his 18th birthday of cancer and i was hanging out with i'll call him john and i was hanging out with john we were in oil and gas he'd come to the same company and we were doing an event together and he was opening up to me because we were actually the demo pilots we do the demonstration for air shows and stuff and uh him and i were sitting there talking and uh he was giving me the whole story and and how he really changed his look on life that we're only here for a finite time and that we're all going to die well unfortunately after all that when it was really going him and his wife had moved to a location that fit their you know close to the water where they could do stuff and i won't say where um and he was doing what he loved to do and he got diagnosed with throat cancer and i was talking to him uh it was probably about maybe two months before he died um and i said dude hey you're sad you mean this is your friend and i'm kind of really bummed out and this is the guy this is a guy that's dying of cancer and here's what he tells me he says dave dude we're all going to die he goes but i have to look at it i have to make the best of the time that i have and i said i understand that he goes with the exception of not being with my wife who he loved dearly he goes i'm okay with dying i've had a really good life and um about because actually the original announcement when he when he finally passed away a buddy of mine called me because i don't do facebook and his wife had put it on facebook that he had passed and about the day before he died for some reason i was thinking about him and i had a dream or i think it was a dream or an altered reality you can get into whatever uh but he was there it was just him and i and i was really sad in the dream i was actually crying and he was there and he was actually in his uniform he was in his whites and uh because he's a navy and we were just talking and he looked at me and he said and this is in my dream he's like dave it's all gonna be okay and this is this is like and this is a vivid conversation i have this people are don't think i'm weird about this but um but you know i know what my dream was and you know maybe it's my subconscious creating the dream but in in reality to me this was real that it was put there for a reason he's and he basically explained everything he's it's okay i'm gonna be fine my wife is fine he goes this is this is what's meant to be you know but you know and the bottom line was make use of every day that you have because you don't know and literally two days later i find out that he passed um so but ultimately he accepted the finiteness of it he did well you have to and it's like i talk about you know money and job position and this and that i said you can get in any you know you can go to a company just remember when you want to be a vp of a company you sell your soul to the company you have to i said if you look i joke with people at work and i said i said you know when you ever think that you're important or this guy has that i said when you're sitting on 93 or 95 128 and you're sitting in traffic and we're stopped which doesn't happen right now because of covet but normally it's stop it's bumper to bumper and you're sitting here like i was coming down here by the gas tank um when you're sitting there look left and look right you know and there can be a lamborghini or an s550 mercedes and on the other side there could be some piece of crap car we're all sitting on the same freeway at the same time trying to do the same thing which is just get home so we can be with our family because the most important thing that we have it ain't money it ain't our job it's not our position i go because when it's all said and done you could be you know you can be with the exception of the presidents of the united states i mean name the vice presidents most people can't and eventually they're going to die or eventually you're going to see a statue of a guy from the 1700s in the boston area and you're going to go i don't even know who that guy was did he impact my life he probably did but eventually people forget yeah you you realize what's important now and the one thing that you have is your family and your close friends and that's that's it you can take all the money or everything else if you're down on your luck you know who is going to be a we is joke who are your true friends it's the person while there's there's ones that i won't say but you know hey you're broke down on a road in the middle of nowhere and it's three o'clock in the morning who you gonna call is gonna get in their car without complaining and come and get you and that's life those that is life the people you love it's it's it's the people you truly care about and contrary to i have you know oh my god i got 6 000 facebook friends you got about that many real friends that you can count on and that's it everything else doesn't matter no it doesn't matter it doesn't mean you might be nice i mean i have there's acquaintance friends that i'll do anything for and then come to my house and stuff but then there's the people that you know you know like my cousins who are like my brothers that you know at a moment's notice you know when when my uncle passed away at a young age you know who lived literally right down the street from me and my cousin chad and i got two boys there's 14 of us but there's only two boys there's three of us together and we all grew up in the same neighborhood same schools play football together all that i said if one of those if rare chad ever needs me if something happens like when my uncle died it wasn't it wasn't an issue if i'm coming home it's i'm booking the ticket and i don't give a shit what it costs because i will be there to to be here with you and and then those two guys and my college roommate is another one that i'm very very close with you know you know if there's there's i have a handful of people that you know i will drop literally everything even if my wife would be pissed at me at times she's like seriously i gotta do it yeah and now she knows and it's the same thing with her i mean she knows that there are certain people in her life that if they really need her and she has to go she would go and i would let her go so given all that i'm honored that you would uh come here and talk to me and take the time dave is one of the best conversations i've ever had thank you so much it's a pretty long one it probably sets the record for the longest one so i i i mean i i'm a loss awards one of my favorite conversations thank you so much for talking to you dave you're welcome thanks for listening to this conversation with david fraver and thank you to our sponsors athletic greens expressvpn and better help please check out the sponsors in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars napa podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from carl sagan somewhere something incredible is waiting to be known thank you for listening hope to see you next time |
Eugenia Kuyda: Friendship with an AI Companion | Lex Fridman Podcast #121 | the following is a conversation with eugenia cuida co-founder of replica which is an app that allows you to make friends with an artificial intelligence system a chatbot that learns to connect with you on an emotional you can even say a human level by being a friend for those of you who know my interest in ai and views on life in general know that replica and eugenia's line of work is near and dear to my heart the origin story of replica is grounded in a personal tragedy of eugenia losing her close friend roman mazarenki who was killed crossing the street by a hit-and-run driver in late 2015. he was 34. the app started as a way to grieve the loss of a friend by training a chatbot neural net on text messages between eugenia and roman the rest is a beautiful human story as we talk about with eugenia when a friend mentioned eugenia's work to me i knew i had to meet her and talk to her i felt before during and after that this meeting would be an important one in my life and it was i think in ways that only time will truly show to me and others she's a kind and brilliant person it was an honor and a pleasure to talk to her quick summary of the sponsors doordash dollar shave club and cash app click the sponsor links in the description to get a discount and to support this podcast as a side note let me say that deep meaningful connection between human beings and artificial intelligence systems is a lifelong passion for me i'm not yet sure where that passion will take me but i decided some time ago that i will follow it boldly and without fear to as far as i can take it with a bit of hard work and a bit of luck i hope i'll succeed in helping build ai systems that have some positive impact on the world and on the lives of a few people out there but also it is entirely possible that i am in fact one of the chatbots that eugenia and the replica team have built and this podcast is simply a training process for the neural net that's trying to learn to connect to human beings one episode at a time in any case i wouldn't know if i was or wasn't and if i did i wouldn't tell you if you enjoyed this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and no ads in the middle i'll try to make these interesting but give you timestamps so you can skip but please do still check out the sponsors by clicking the links in the description to get a discount buy whatever they're selling it really is the best way to support this podcast this show is sponsored by dollar shave club try them out with a one-time offer for only five bucks and free shipping at dollarshave.com lex the starter kit comes with a six blade razor refills and all kinds of other stuff that makes shaving feel great i've been a member of dollar shave club for over five years and actually signed up when i first heard about them on the joe rogan experience podcast and now friends we have come full circle it feels like i made it now that i can do a read for them just like joe did all those years ago back when he also did ads for some less reputable companies let's say you know about if you're a true fan of the old school podcasting world anyway i just used the razer and the refills but they told me i should really try out the shave butter i did i love it it's translucent somehow which is a cool new experience again try the ultimate shave starter set today for just five bucks plus free shipping at dollarshaveclub.com lex this show is also sponsored by doordash get five dollars off as your delivery fee is in your first order of 15 bucks or more when you download the doordash app and enter code you guessed it i have so many memories of working late nights for a deadline with a team of engineers whether that's for my phd at google or mit and eventually taking a break to argue about which door dash restaurant to order from and when the food came those moments of bonding of exchanging ideas of pausing to shift attention from the programs the humans were special for a bit of time i'm on my own now so i missed that camaraderie but actually i still use doordash a lot there's a million options that fit into my crazy keto diet ways also it's a great way to support restaurants in these challenging times once again download the doordash app and enter code lex to get five bucks off it's your delivery fees and your first order of fifteen dollars or more finally this shows presented by cash app the number one finance app in the app store i can truly say that they're an amazing company one of the first sponsors if not the first sponsor to truly believe in me and and i think quite possibly the reason i'm still doing this podcast so i'm forever grateful to cash app so thank you and as i said many times before use code lex podcast when you download the app from google play or the app store cash app lets you send money to friends buy bitcoin invest in the stock market with as little as one dollar i usually say other stuff here in the read but i wasted all that time up front saying how grateful i am to cash out i'm going to try to go off the top of my head a little bit more for these reads because i'm actually very lucky to be able to choose the sponsors that we take on and that means i can really only take on the sponsors that i truly love and then i can just talk about why i love them so it's pretty simple again get cash app from the app store google play use code lex podcast get 10 bucks and cash app will also donate 10 bucks to first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with eugenia cuida okay before we talk about ai and the amazing work you're doing let me ask you ridiculously we're both russian so let me ask you a ridiculously romanticized russian question do you think human beings are alone like fundamentally on a philosophical level like in our existence when we like go through life do you think um just the nature of our life is loneliness yeah so we have to read dostoevsky at school as you probably know yeah i mean it's part of the your school program um so i guess if you read that then you sort of have to believe that you're made to believe that you're fundamentally alone and that's how you live your life how do you think about it you have a lot of friends but at the end of the day do you have like a longing for connection with other people that's maybe another way of asking it do you think that's ever fully satisfied i think we are fundamentally alone we're born alone we die alone but um you know but i view my whole life as trying to get away from that trying to not feel uh feel lonely and again we're talking about you know subjective kind of way of feeling alone it doesn't necessarily mean that you don't have any connections or you're actually isolated you think it's a subjective thing but like again another absurd measurement-wise thing how much loneliness do you think there is in the world so like if you see loneliness as a as a condition how much of it is there do you think like how i guess how many you know there's all kinds of studies and measures of how much you know how many people in the world feel alone there's all these like measures of how many people are you know self-report or just all these kinds of different measures but in your own perspective um how big of a problem do you think it is size-wise well i'm actually fascinated by the topic of loneliness i try to read about it as much as i can um what really and there i think there's a paradox because loneliness is not a clinical disorder it's not something that you can get your insurance to pay for if you're struggling with that yet it's it's actually proven and pretty you know tons of papers tons of research around that it has proven um that it's correlated with earlier um life expectancy shorter life span and it is you know in a way like right now what scientists would say that it you know it's a little bit worse than being obese so not actually doing any physical activity in your life the impact on your interests have impact on your physiological health yeah so it's basically puts you if you're constantly feeling lonely um your body responds like it's basically all the time under stress so it's always in this alert um alerts say and so it's really bad for you because it actually like drops your immune system and get it your response to inflammation is quite different so all the cardiovascular vascular diseases actually responds to viruses so it's much easier to catch a virus that's sad now that we're living in a pandemic and it's probably making us a lot more alone and it's probably weakening the immune system making us more susceptible to the virus it's kind of sad yeah the statistics are the sticks are pretty pretty horrible around that so around thirty percent of all millennials report that they're feeling lonely constantly thirty thirty percent and then it's much worse for jan z and then twenty percent of millennials say that they feel lonely and they also don't have any close friends and then um i think 25 or so and then 20 percent would say they don't even have acquaintances this is the united states that's in the united states and i'm pretty sure that that's much worse everywhere else like in the uk i mean it was white widely like tweeted and uh posted when they were talking about a minister of loneliness that they wanted to appoint because four out of ten you people in uk feel lonely so i think we don't understand i mean that i think that thing actually exists um so yeah you you you will die sooner if you if you are lonely and again that this is only when we're only talking about your perception of loneliness of feeling lonely that is not objectively fully so being fully socially isolated however the combination of being fully socially isolated and not having many connections and also feeling lonely that's pretty much a deadly combination so it strikes me bizarre or strange that this is a wide known fact and then there's really no one working really on that because it's a subclinical it's not clinical it's not something that you can we'll tell your doctor and get a treatment or something yet it's killing us yeah so there's a bunch of people trying to evaluate like try to measure the problem by looking at like how social media is affecting loneliness and all that kind of stuff so it's like measurement like if you look at the field of psychology they're trying to measure the problem and not that many people actually but some but you're basically saying how many people are trying to solve the problem like how would you try to solve the problem of loneliness like if you just stick to humans uh i mean or basically not just the humans but the technology that connects us humans do you think there's a hope for that technology to do the connection like are you on social media much unfortunately do you find yourself like again if you sort of introspect about how connected you feel to other human beings how not alone you feel do you think social media makes it better or worse maybe for you personally or in in general i think it's it's easier to look at some stats and um i mean gen z's seem to be generation z seems to be much lonelier than millennials in terms of however they report loneliness they're definitely the most connected you know generation in the world i mean i still remember life without without an iphone without facebook they don't know that that ever existed uh or at least don't know how it was um so that tells me a little bit about the fact that that might be um you know this hyperconnected world is might actually make people feel lonely lonelier i don't know exactly what the what the measurements are around that but i would say in my personal experience i think it does make you feel a lot lonelier mostly yeah we're all super connected but i think loneliness the feeling of loneliness doesn't come from not having any social connections whatsoever again tons of people that are in long-term relationships experienced bouts of loneliness and continued loneliness and it's more the question about the true connection about actually being deeply seen deeply understood and in a way it's also about your relationship with yourself like in order to not feel lonely you actually need to have a better relationship and feel more connected to yourself then this feeling actually starts to go away a little bit and then you um open up yourself to actually meeting other people in a very special way uh not just you know add a friend on facebook kind of way so just to briefly touch on it i mean do you think it's possible to form that kind of connection with ai systems more downline of some of your work do you think that's um engineering-wise a possibility to alleviate loneliness is not with another human but with an ai system well i know that's that's a fact that's what we're doing and we see it and we measure that and we see how people start to feel less lonely talking to their virtual ai friend so basically a chatbot at the basic level but could be more like do you have i'm not even speaking sort of uh about specifics but do you have a hope like if you look 50 years from now do you have a hope that there's just like ais that are like optimized for um let me let me first start like right now the way people perceive ai which is recommender systems for facebook and twitter social media they see ais basically destroying first of all the fabric of our civilization but second of all making us more lonely do you see like a world where it's possible just have ai systems floating about that like make our life less lonely yeah make us happy make like our putting good things into the world in terms of our individual lives yeah totally believe it and that that's why we're i'm also working on that um i think we need to also make sure that um what we're trying to optimize for we're actually measuring and it is a north star metric that we're going after and all of our product and our all of our business models are optimized for that because you can talk you know a lot of products that talk about um you know making you feel less lonely or making you feel more connected they're not really measuring that so they don't really know whether their users are actually feeling less lonely in the long run or feeling more connected in the long run um so i think it's really important to put your measure yep to measure it what's uh what's a good measurement of loneliness well so that's something that i'm really interested in how do you measure that people are feeling better or that they're feeling less lonely with lowliness there's a scale there's a ucla 20 and ucla 3 recently scale which is basically a questionnaire that you fill out and you can see whether in the long run it's improving or not and that uh does it capture the momentary feeling of loneliness does it look in like the past month like uh is it basically a self-report does it try to sneak up on you it's very tricky to answer honestly or something like that well what's yeah i'm not familiar with the question it is just asking you a few questions like how often did you feel like lonely or how often did you feel connected to other people in this last few couple weeks um it's similar to the self-report questionnaires for depression and anxiety like phq9 and get seven of course any as any self-report questionnaires that's not necessarily very precise so very well measured but still if you take a big enough population you get them through these uh questionnaires you can see you can see the positive dynamic and so you basically uh you put people through questionnaires to see like is this thing is our is what we're creating making people happier yeah we measure so we measure two outcomes one short term right after the conversation we asked people whether this conversation made them feel better worse or same um this this metric right now is at eighty percent so eighty percent of all our conversations make people feel better but i should have done the questionnaire with you you feel a lot worse after we've done this conversation that's actually fascinating i should probably do that but that's that's sorry you should totally and aim for 80 aim to outperform your current state-of-the-art ai system uh in these human conversations so again we'll get to your work with replica but let me continue on the line of absurd questions so you it talks about um you know deep connection with the humans deep connection with the ai meaningful connection let me ask about love people make fun of me because i talk about love all the time but uh what what do you think a love is like maybe in the context of um a meaningful connection with somebody else do you draw a distinction between love like friendship and facebook friends [Laughter] or is it a graduate no is it it's all the same no like is it just a gradual thing or is there something fundamental about us humans that seek like a really deep connection uh with another human being and what is that what is love eugenia um well the way i see it um specifically um the way it relates to our work and the way it was the way it inspired our work on replica um i think one of the biggest and the most precious gifts we can give to each other now in 2020 as humans is this gift of deep empathetic understanding the feeling of being deeply seen like what does that mean like that you exist like somebody acknowledging the somebody seeing you for who you actually are and that's extremely extremely rare i think that is that combined with unconditional positive regard belief and trust that you internally are always inclined for positive growth and believing you in this way letting you be a separate person at the same time and this deep empathetic understanding for me that's the that's the combination that really creates something special something that people when they feel it once they will always long for it again and something that starts huge fundamental changes in people um when we see that someone's accepts us so deeply we start to accept ourselves and the paradoxes that's when big changes start start happening big fundamental changes and people start happening so i think that is the ultimate therapeutic relationship that is and that might be in some way definition of love so so acknowledging that there's a separate person and accepting you for who you are now on a slightly so that and you mentioned therapeutic that sounds very like a very healthy view of love but uh is there also like uh like you know if we look at heartbreak and uh you know most love songs are probably about heartbreak right is that like the mystery the tension the danger the fear of loss you know all of that what people might see in a negative light as like games or whatever but just just the the dance of human interaction yeah fear of loss and fear of like you said like once you feel it once you long for it again but you also once you feel it once you might for many people they've lost it so they fear losing it they feel lost so is that part of it like you're you're speaking like beautifully about like the positive things but is it important to be able to uh be afraid of losing it from an engineering perspective i mean it's a huge part of it and unfortunately we all you know face it at some points in our lives i mean i did you want to go into details how did you get your heart broken sure well so mine is pretty straight my source pretty straightforward um there i did have a friend that was you know that at some point um in my 20s became really really close to me and we we became really close friends um i grew up pretty lonely so in many ways when i'm building you know this these ai friends i think about myself when i was 17 writing horrible poetry and you know in my dial-up modem at home and um you know and that was the feeling that i grew up with i left i lived um alone for a long time when i was a teenager where did you grow up in moscow and then outskirts of moscow um so i just skateboard during the day and come back home and you know connect to the internet and write pokemon and then write horrible poetry and was it love poems all sorts of points obviously love poems i mean what what other poetry can you write when you're 17. it could be political or something but yeah but that was you know that was kind of my yeah like deeply um influenced by joseph brodsky and like all sorts of spots that um every 17 year old will will be looking you know looking at and reading but yeah that was my uh these were my teenage years and i just never had a person that i thought would you know take me as it is would accept me the way i am um and i just thought you know working and just doing my thing and being angry at the world and being a reporter i was an investigative reporter working undercover and writing about people was my way to connect with you know with with others i i was deeply curious about every everyone else and i thought that you know if i go out there if i write their stories that means i'm more connected this is what this podcast is about by the way i'm desperate alone seeking connection [Laughter] i'm just kidding or am i i don't know so what wait a reporter uh what how did that make you feel more connected i mean you're still fundamentally pretty alone but you're always with other people you know you're always thinking about what other place gonna infiltrate what other community can i write about what other phenomena can i explore and he's sort of like a trickster you know and like and a mythological character like creature that's just jumping uh between all sorts of different worlds and feel and feel sort of okay with in all of them so um that was my dream job by the way that was like totally what i would have been doing um if russia was a different place and a little bit undercover so like you weren't you were trying to like you said mythological creature trying to infiltrate so try to be a part of the world what are we talking about what kind of things did you enjoy writing about i'd go work at a strip club or go awesome okay uh well i'd go work at a restaurant or just go write about you know um certain phenomenons or phenomenons of people in in the city and what uh sorry to keep interrupting i'm the worst a conversationalist what stage of russia is this what uh is this pre-putin post-putin what was russia like pre-putin is really long ago uh this is putin era that's uh beginning of 2000's and 2010 2007 8 9 10. what were strip clubs like in russia and restaurants and culture and people's minds like in that early russia that you were covering in those early 2000s was there was still a lot of hope there was still tons of hope that um you know we're sort of becoming this uh western westernized society the restaurants were opening we were really looking and you know um we're trying we're trying to copy a lot of things from uh from the us from europe uh bringing all these things and very enthusiastic about that so there's a lot of you know stuff going on there's a lot of hope and dream for this you know new moscow that would be similar to i guess new york i mean just to give you an idea and um year 2000 was the year one we had two uh movie theaters in moscow and there was this one first coffee house that opened and it was like really big deal by 2010 there were all sorts of things everywhere almost like a chain like a starbucks type of coffee house or like you mean oh yeah like a starbucks i mean i remember we were reporting on like we were writing about the opening of starbucks i think in 2007 that was one of the biggest things that happened and you know in moscow back back in the time like that was worthy of a magazine cover and uh that was definitely the you know the biggest talk of the time yeah when was mcdonald's because i was still in russia when mcdonald's opened that was in the 90s i mean yeah i remember that very well yeah those were long long lines i think it was 1990 three or four i don't remember um mcdonald's at that time did you do that i mean that was a luxurious outing that was definitely not something you do every day and also the line was at least three hours so if you're going to mcdonald's that is not fast food that is like at least three hours in line yeah and then no one is trying to eat fast after that everyone is like trying to enjoy as much as possible what's your memory of that oh it was insane extremely positive it's a small strawberry milkshake and a hamburger and small fries and my mom's there and sometimes i'll just because i was really little they'll just let me run you know up the cashier and like cut the line which is like you cannot really do that in russia or so like for a lot of people like a lot of those experiences might seem not very fulfilling you know like it's on the verge of poverty i suppose but do you remember all that time fondly like because i do like the first time i drink you know coke you know all that stuff right um and just yeah the connection with other human beings in russia i remember i remember really positively like how do you remember what the 90s and then the rush you were covering just the human connections you had with people and the experiences well my my parents were both both physicists my grandparents were both well my grandpa grandfather was an um nuclear physicist a professor at the university my dad worked at chernobyl when i was born in chernobyl analyzing kind of the everything after the explosion and then i remember that and they were so they were making sort of enough money in the soviet union so they were not you know extremely poor or anything it was pretty prestigious to be a professor uh the dean and the university and i remember my grandfather started making a hundred dollars a month after you know in the 90s so then i remember we started our main line of work would be to go to our little tiny country house get a lot of apples there from apple trees bring them back to to to the city and sell them in the street so me and my nuclear physicist grandfather were just standing there and he selling those apples the whole day because that would make you more money than you know working at the university and then he'll just tell me try to teach me um you know something about planets and whatever the particles and stuff and you know i'm not smart at all so i could never understand anything but i was interested as a you know journalist kind of type interested but that was my memory and you know i'm happy that i wasn't um i somehow got spared that i was probably too young to remember any of the traumatic stuff so the only thing i really remember had this bootleg that was very traumatic i had this bootleg nintendo which was called dandy in russia so in 1993 there was nothing to eat like even if you had any money you would go to the store and there was no food i don't know if you remember that and our friend had a um restaurant like a government half government owned something restaurant so they always had um supplies so he exchanged a big bag of weed for this nintendo that looked like nintendo and then i remember very fondly because i think it was nine or something like that and or seven traumatic because we just got it and i was playing it and there was this you know dandy tv show yeah um so dramatically positive sense you mean like like a definitive well they took it away and gave me a bag of wheat instead and i cried like my eyes out for days days and days oh no and then you know as a and my dad said we're gonna like exchange it back in a little bit so you keep the little gun you know the one that you shoot the ducks with so i'm like okay i'm keeping the gun so sometimes it's going to come back but then they exchanged the gun as well for some sugar or something i was so pissed i was like i didn't want to eat for days after that i'm like i don't want your food my nintendo that was extremely traumatic um but you know i was happy that that was my only traumatic experience you know my dad had to actually go to chernobyl with a bunch of 20 year olds he was 20 when he went to uh chernobyl and that was right after the explosion no one knew anything the whole crew he went with all of them are dead now i think there was this one guy uh still that was still alive for this last few years i think he died a few years ago now my dad somehow luckily got back earlier than everyone else but just the fact that that was the and i was always like well how did they send you i was only i was just born you know you had a newborn talk about paternity leave they're like but that's who they took because they didn't know whether you would be able to have kids when you come back so they took the ones with kids so him with some guys want to and i'm just thinking of me when i was 20 i was so sheltered from any problems whatsoever in life and then my dad um his 21st birthday at the reactor you like work three hours a day you sleep the rest and and i yeah so i played with a lot of toys from chernobyl what are your memories of chernobyl in in general like a bigger context you know because of that hbo show the world's attention turned to it once again like what are your thoughts about chernobyl did russia screw that one up like you know there's probably a lot of lessons about our modern times with data about coronavirus and all that kind of stuff it seems like there's a lot of misinformation there's a lot of people kind of trying to hide whether they've screwed something up or not as it's very understandable it's very human very wrong probably but obviously russia was probably trying to hide that they've screwed things up like what are your thoughts about that time personal and in general i mean i was born when the explosion happened so actually a few months after so of course i don't remember anything apart from the fact that my dad would bring me tiny toys plus like plastic things that would just go crazy haywire when you you know put the gagger my mom was like just nuclear about that um i was like what are you bringing you should not do that uh she was nuclear very nice absolutely well done well uh but yeah but the tv show was just phenomenal i mean yeah it's definitely first of all it's an incredible how um that was made not by the russians but someone else but capturing so well everything about the you know about our country um it felt a lot more genuine that most of the movies and tv shows are made now in russia just so much more genuine and most of my friends in russia were just in complete awe about the with the show but i think that how good of a job they did oh my god phenomenal but all the apartments there's something yeah the set design i mean russians can't do that we you know but you you see everything and it's like wow that's exactly how it was it's so i i don't know that show i don't know what to think about that because it's british accents british actors of a person i forgot who created the show i'm not but i remember reading about him and he's not he doesn't even feel like like there's no russia in his history no he did like super bad or some like or like uh i don't know yeah like exactly whatever that thing about the bachelor party in vegas uh number four and five or something were the ones that he worked yeah but so he made me feel really sad for some reason that if a person obviously a genius could go in and just study and just be extreme attention to detail that can do a good job it made me think like why don't other people do a good job with this like about russia like there's so little about russia there's so few good films about the russian side of world war ii of i mean there's so much interesting evil and not and beautiful moments in the history of the 20th century in russia it feels like there's not many good films on from the russians you would expect something from the russians well they keep making these propaganda movies now oh no unfortunately but you know chernobyl was such a perfect tv show i think capturing really well it's not about like even the set design which was phenomenal but um just capturing all the problems that exist now with the country and like um focusing on the right things like if you build the whole country on a lie that's what's gonna happen and that's just this very simple kind of thing yeah and did you have your dad talked about it to you like his thoughts i think experience he never talks he's this kind of russian man that just my husband who's american and he asked him a few times like you know igor how did you but why did you say yes or like why did you decide to go you could have said no not go to chernobyl why would like a person like that's what you do you cannot say no yeah yeah it's just it's like a russian way it's the russians don't talk that much no there are downsides and upsets for that uh yeah that's the truth okay so back to post-putin russia or maybe we skipped a few steps along the way but you were trying to uh do um to be a journalist in that time what was what was russia like at that time post he said 2007 starbucks type of thing what else what else was russia like then i think there was just hope there was this big hope that we're going to be you know friends with the united states and we're going to be friends with europe and we're just going to be also a country like those with you know um bike lanes and parks and everything's going to be urbanized again we're talking about 90s where like people would be shot in the street and it was i sort of have a fond memory of going into a movie theater and i you know coming out of it after the movie and the guy that i saw on the stairs was like playing their shot which was again it was like a thing in the 90s that would be happening people were you know people were getting shot here and there tons of violence tons of uh you know just basically mafia mobs on in the streets and then the 2000s were like you know things just got cleaned up uh oil went up uh and the country started getting a little bit richer you know the 90s were so grim mostly because the economy was in shambles and oil prices were not high so the country didn't have anything we defaulted in 1998 and um the money kept jumping back and forth like first there were millions of rebels then it got like default you know then it got to like thousands there was one rubble with something then again to millions it was like crazy town that was crazy um and then the 2000s were just these years of stability in a way and um the country getting a little bit richer because of you know again oil and gas and we were starting to we started to look at specifically in moscow and in facebook to look in at other cities in europe and new york and us and trying to do the same in our like small kind of cities towns there what was uh what were your thoughts of putin at the time well in the beginning he was really positive everyone was very you know positive about putin he was young um he's very energetic he also intermediate the sheriff was somewhat compared to well that was not like way before the shirtless era um the shirtless era okay so it didn't start off shortly when did the shirtless era that's like the propaganda of riding horse fishing 2010 11 12. yeah that's my favorite you know like people talk about the favorite beatles like the i don't know that's my favorite putin that's the shirtless putin now i remember very very clearly 1996 where you know americans really helped russia with elections and yeltsin got reelected thankfully so because there's a huge threat that actually the communists will get back to power they were a lot more popular and then a lot of american experts political experts and campaign experts descended on moscow and helped yeltsin actually get yeah the presidency the second term for the pro um of the presidency but elsinore was not feeling great you know in the by the end of his second term uh he was you know alcoholic he was really old he was falling off uh you know the stages when he was talking uh so people were looking for it fresh i think for a fresh face for someone who's gonna continue yeltsin's uh work but who's going to be a lot more energetic and a lot more active young um efficient maybe so that's what we all saw in putin back in the day i i'd say that everyone absolutely everyone in russia in early 2000s who was not a communist would be yeah putin's great we have a lot of hopes for him what are your thoughts and i promise we'll get back to uh first of all your love story second of all ai well what are your thoughts about communism the 20th century i apologize i'm reading the rise and fall of the third reich oh my god so i'm like really steeped into like world war ii and stalin and hitler and just these dramatic personalities that brought so much evil to the world but it's also interesting to politically think about these different systems and what they've led to and russia is one of the sort of beacons of communism in the 20th century what are your thoughts about communism having experienced it as a political system i mean i have only experienced it a little bit but mostly through stories and through you know seeing my parents my grandparents who lived through that it was horrible it was just plain horrible it was just awful um you think it's there's something i mean it sounds nice on paper there's uh so like the drawbacks of capitalism is that uh you know eventually there is it's a it's the point of like a slippery slope eventually it creates uh you know the rich get richer it creates a disparity like inequality of um wealth inequality if like you know i guess it's hypothetical at this point but eventually capitalism leads to humongous inequality and that that's you know some people argue that that's a source of unhappiness is it's not like absolute wealth of people it's the fact that there's a lot of people much richer than you there's a feeling of like that's where unhappiness can come from so the idea of of communism or this sort of marxism is uh is is not allowing that kind of slippery slope but then you see the actual implementations of it and still seems to be seems to go wrong very badly what do you think that is why does it go wrong what is it about human nature if we look at chernobyl you know those kinds of barack bureaucracies that were constructed is there something like do you think about this much of like why it goes wrong well there's no one was really like it's not that everyone was equal obviously the you know the the government and everyone close to that were the bosses so it's not like fully i guess uh there's already this dream of equal life so then i guess the the situation that we hadn't you know the russia and soviet in the soviet union it was more it's a bunch of really poor people without any way to make any you know significant fortune or build anything living constant under constant surveillance surveillance from other people like you can't even you know do anything that's not fully approved by the dictatorship basically otherwise your neighbor will write a letter and you'll go to jail absolute absence of actual law yeah this constant state of fear you didn't own any own anything you didn't you know the you couldn't go travel you couldn't read anything western or you could make a career really unless you're working in the military complex which is why most of the scientists were so well regarded i come from you know both my dad and my mom come from families of scientists and they they were really well regarded as you as you know obviously because this they wanted i mean because there's a lot of value to them being well regarded because they were developing things that could be used in in the military so that was very important that was the main investment um but was miserable it was so miserable that's why you know a lot of russians now live in the state of constant ptsd that's why we you know want to buy buy buy buy and definitely if as soon as we have the opportunity you know we just got to it finally that we can you know own things you know i remember the time that we got our first yogurts and that was the biggest deal in the world it was already in the 90s by the way i mean what was your like favorite food what was like whoa like this is possible oh fruit because we only had apples bananas and whatever and you know whatever watermelons whatever you know people would grow in the soviet union so there were no pineapples or papaya or mango like you've never seen those fruit things like those were so ridiculously good and obviously you could not get any like strawberries in winter or anything that's not you know seasonal um so that was a really big deal seeing all these fruit things yeah me too actually i don't know i think i have a like i don't think i have any too many demons uh or like addictions or so on but i think i've developed an unhealthy relationship with fruit and i still struggle with oh you can get any type of fruit right you can get like also these weird fruit fruits like dragon fruit or something more all kinds of like different types of peaches like cherries were killer for me i know i know you say like we had bananas and so on but i don't remember having the kind of banana like when i first came to this country the amount of banana i like literally got fat on bananas like the amount oh yeah for sure delicious and like cherries the kind like just the quality of the food i was like this is capitalism this is that's pretty good it's delicious yeah yeah yeah it's funny it's funny yeah like it's it's funny to read i don't know what to think of it of um it's funny to think how an idea that's just written on paper when carried out amongst millions of people how that gets actually when it becomes reality what it actually looks like uh sorry but the been studying hitler a lot recently and uh going through mineconf he uh pretty much rode out of minecon for everything he was gonna do unfortunately most leaders including stalin didn't read the read it but it's it's kind of terrifying and i don't know and amazing in some sense that you can have some words on paper and they can be brought to life and they can either inspire the world or they can destroy the world and uh yeah there's a lot of lessons to study in history i think people don't study enough now i know one of the things i'm hoping with i've been practicing russian a little bit i'm hoping to sort of find rediscover the the beauty and the terror of russian history through this stupid podcast by talking to a few people so anyway i just feel like so much was forgotten i so much was forgotten i'll probably i'm gonna try to convince myself to um you're a super busy and super important person well i'm gonna i want to try to befriend you to uh to try to become a better russian because i feel like i'm a shitty russian not that busy so i can totally be a russian sherpa yeah but love you were you're talking about your early days of uh being a little bit alone and finding a connection with the world through being a journalist where does love come into that i guess finding for the first time um some friends it's very you know simple story some friends that all of a sudden we i guess we're the same you know the same at the same place with our lives um we're 25 26 i guess and um somehow remember and we just got really close and somehow remember this one day where um it's one day and you know in summer that we just stayed out um outdoor the whole night and just talked and for some unknown reason i just felt for the first time that someone could you know see me for who i am and it just felt extremely like extremely good and you know we fell asleep outside and just talking and it was raining it was beautiful you know sunrise and it's really cheesy but um at the same time we just became friends in a way that i've never been friends with anyone else before and i do remember that before and after that you sort of have this unconditional family sort of and it gives you tons of power it just basically gives you this tremendous power to do things in your life and to um change positively you mean like on many different levels power because you could be yourself at least you know that some somewhere you can't be just yourself like you don't need to pretend you don't need to be you know great at work or tell some story or sell yourself in some way or another and so we became this really close friends and um in a way um i started a company because he had a startup and i felt like i kind of want to start up too it felt really cool i didn't know what i'm gonna what i would uh really do but i felt like i kind of need a startup okay so that's so that pulled you in to the startup world yeah and then yeah and then this uh closest friend of mine died we actually moved here to san francisco together and then we went back for a visa to moscow and uh we lived together with roommates and we came back and um he got hit by a car right in front of kremlin hannah you know next to the river um and died the same damage [Music] so and you've moved to america at that point at that point i was like what about him what about roman him too he actually moved first so i was always sort of trying to do what he was doing so i didn't like that he was already here and i was still you know in moscow and we weren't hanging out together all the time so was he in san francisco yeah we were roommates so he just visited moscow for we went back for for our visas we had to get a stamp and our passport for our work visas and the embassy was taking a little longer so we stayed there for a couple weeks what happened how did you so how did he uh how did he die um he was crossing the street and the car was going really fast and way over the speed limit and just didn't stop on the on the pedestrian cross on the zebra and i just ran over him when was this it was in 2015 on 28th of november so it was pretty long ago now um but at the time you know i was 29 so for me it was um the first kind of meaningful death in my life um you know both sets of i had both sets of grandparents at the time i didn't see anyone so close die and death sort of existed but as a concept but definitely not as something that would be you know happening to us anytime soon and specifically our friends because we were you know we're still in our 20s or early 30s and it still still felt like the whole life is you know you could still dream about ridiculous things different um so that was it was just really really abrupt i'd say what did it feel like to uh to lose him like that feeling of loss he talked about the feeling of love having power what is the feeling of loss if you like well in buddhism there's this concept of samaya where something really like huge happens and then you can see very clearly um i think that was it like basically something changed so changed me so much in such a short period of time that i could just see really really clearly what mattered or what not well i definitely saw that whatever i was doing at work didn't matter at all and some other things and um it was just this big realization what this very very clear vision of what life's about you still miss him today yeah for sure for sure it was just this constant i think it was he was really important for for me and for our friends for many different reasons and um i think one of them being that we didn't just say goodbye to him but we sort of said goodbye to our youth in a way it was like the end of an era and it's on so many different levels the end of moscow as we knew it the end of you know us living through our 20s and kind of dreaming about the future do you remember like last several conversations is there moments with him that stick out that will kind of haunt you and you're just when you think about him yeah well his last year here in san francisco was pretty depressed for as his startup was not going really anywhere and he wanted to do something else he wanted to do build he played with toy with like played with the wrong a bunch of ideas but the last one he had was around um building a startup around death so having um he applied to y combinator with a video that you know i had on my computer and it was all about you know disrupting death thinking about new symmetries uh more biologically like things that could be better biologically for for humans and at this end um at the same time having those um digital avatars these kind of ai avatars that would store all the memory about a person that he could interact with what year was this 2015. well right before that his death so it was like a couple months before that he recorded that video and so i found out my computer when um it was in our living room he never got in but um he was thinking about a lot somehow does it have the digital avatar idea yeah that's so interesting well he just says well that's in his yeah the fish has this idea and he'll he talks about like i want to rethink how people grieve and how people talk about death why was he interested in this and i is it maybe someone who's depressed yeah is like naturally inclined thinking about that but i just felt you know this year in san francisco we just had so much um i was going through a hard time he was going through a hard time and we were definitely i was trying to make him just happy somehow to make him feel better and it felt like you know this um i don't know i just felt like i was taking care of off him a lot and he almost started feel better and then that happened and i don't know i just felt i just felt lonely again i guess and that was you know coming back to san francisco in december our help you know helped organize the funeral help help his parents and i came back here and it was a really lonely apartment a bunch of his clothes everywhere and christmas time and i remember had a board meeting with my investors and i just couldn't talk about like i had to pretend everything's okay and you know just working on this company um yeah it was definitely very very tough tough time do you think about your own mortality you said uh you know we're young the the the the possibility of doing all kinds of crazy things it's still out there it's still before us but uh it can end any moment do you think about your own ending at any moment unfortunately i think about way too way too much it's somehow after roman like every year after that i started losing people that i really love i lost my grandfather next year my you know the the person who would explain to me you know what the universe is made off while you're selling apples while selling apples and then i lost another close friend of mine and um and it just made me very scared i have tons of fear about death that's what makes me not fall asleep oftentimes and just go in loops and um and then as my therapist you know recommended me i open up uh some nice calming images with the voice over and it calms me down oh for sleep yeah i'm really scared of that this is a big i definitely have tons of i guess some pretty big trauma about it and i'm still working through there's a philosopher ernest becker who wrote a book um denial of death i'm not sure if you're familiar with any of those folks um there's a in psychology a whole field called terror management theory sheldon was just on the podcast he wrote the book he was the we talked for four hours about death uh fear of death uh but his whole idea is that ernest becker i think i i find this idea really compelling is uh that everything human beings have created like our whole motivation in life is to uh create like escape death is to try to uh construct an illusion of um that we're somehow immortal it's like everything around us this room your startup your dreams all everything you do is a kind of um creation of a brain unlike any other mammal or species is able to be cognizant of the fact that it ends for us i think so you know there's there's the question of like the meaning of life that you know you look at like what drives us uh humans and when i read ernest becker that i highly recommend people read is the first time i this scene it felt like this is the right thing at the core uh sheldon's work is called warm at the core so he's saying it's i think it's uh william james he's quoting or whoever is like the the thing what is it the core of it all sure there's like love you know jesus might talk about like love is at the core of everything i i don't you know that's the open question what's that the you know it's turtles turtles but it can't be turtles all the way down what's what's at the at the bottom and uh ernest becker says the fear of death and the way in fact uh because you said therapist and calming images his whole idea is um you know we we want to bring that fear of death as close as possible to the surface because it's uh and like meditate on that uh and and use the clarity of vision that provides to uh you know to live a more fulfilling life to um to live a more honest life to discover you know there's something about you know being cognizant of the finiteness of it all that might result in um in the most fulfilling life so that's the that's the duel of what you're saying because you kind of said it's like i unfortunately think about it too much it's a question whether it's good to think about it because i i've i'm again i talk about way too much about love and probably death and when i ask people or friends which is why i probably don't have many friends are you afraid of death i think most people say they're not they're not what they they say they're um they're afraid you know it's kind of almost like they see death as this kind of like a paper deadline or something and they're afraid not to finish the paper before the paper like like i'm afraid not to finish um the goals i have but it feels like they're not actually realizing that this thing ends like really realizing like really thinking as nietzsche and all these philosophers like thinking deeply about it like uh the very thing that you know um like when you think deeply about something you can dis you can realize that you haven't actually thought about it uh yeah and i and when i think about death it's like uh it can be it's terrifying if it feels like stepping outside into the cold or it's freezing and then i have to like hurry back inside or it's warm uh but like i think there's something valuable about stepping out there into the freezing cold uh definitely when i talk to my mentor about it he always uh tells me well what dies there's nothing there that can die but i guess that works um well in in buddhism one of the concepts are really hard to grasp and that people spend all their lives meditating on would be anata which is the concept of non not self and kind of thinking that you know if you're not your thoughts which are obviously not your thoughts because you can observe them and not your emotions and not your body then what is this and if you go really far then finally you see that there's not self there's this concept of not self so once you get there how can that actually die what is dying right you're just a bunch of molecules stardust but that is very um you know very advanced um spiritual work for me i'm definitely just definitely not oh my god no i have uh i think it's very very useful it's just the fact that maybe being so afraid is not useful and mine is more i'm just terrified like it's really makes me um on a personal level on a personal level i'm terrified how do you overcome that i don't i'm still trying to have pleasant images well pleasant images get me uh to sleep and then during the day i can distract myself with other things like talking to you i'm glad we're both doing the same exact thing okay good [Laughter] is there other like is there moments since you've uh lost roman that you had like moments of like bliss and like that you've forgotten that you have achieved that buddhist like level of like what can possibly die i'm part like uh losing yourself in the moment in the ticking time of like this universe he's just part of it for a brief moment and just enjoying it well that goes hand in hand i remember i think a day or two after he died we went to finally get his passport out of the embassy and we're driving around moscow and it was you know december which is usually there's never sun in moscow in december and somehow it was an extremely sunny day and we were driving with um close friend um and i remember feeling for the first time maybe this just moment of um incredible clarity and somehow happiness not like happy happiness but happiness and just feeling that you know um i know what the universe is sort of about whether it's good or bad um and it wasn't a sad feeling it was probably the most beautiful feeling that you can ever um achieve and you can only get it when something oftentimes when something traumatic like that happens um but also if you just you really spend a lot of time meditating looking at the nature doing something that really gets you there but once you're there i think when you uh summit a mountain a really hard mountain you you inevitably get there that's just a way to get to the state but once you're on this in this state um you can do really big things i think yeah sucks it doesn't last forever so bukowski talked about like love is the fog like it's uh when you wake up in the morning it's it's there but it eventually dissipates it's really sad nothing lasts forever but definitely like doing this push-up and running thing there's moments i had a couple moments like i'm not a crier i don't cry but there's moments where i was like face down on the carpet like with tears in my eyes is interesting and then that like complete like uh there's a lot of demons i've got demons had to face them funny how running makes you face your demons but at the same time the flip side of that there's a few moments where i was in bliss and all of it alone which is funny that's beautiful i like that but definitely pushing yourself physically one of it for sure yeah it's yeah like you said i mean you were speaking as a metaphor of mount everest but it also works like literally i think physical endeavor somehow yeah there's something i mean war monkeys apes whatever physical there's a physical thing to it but there's something to this pushing yourself physical physically but alone that happens when you're doing like things like you do or strenuous like workouts or you know rolling across the atlantic or yeah like marathons that's why i love watching marathons and you know so boring but you can see them getting there so the other thing i don't know if you know there's a guy named david goggins he's uh he basically uh so he's been either email on the phone with me every day through this so i haven't been exactly alone but he he's kind of he's the he's the devil on the devil's shoulder so he's like the worst possible human being in terms of giving you a advice like he has um through everything i've been doing he's been doubling everything i do so he he's insane uh he's a this navy seal person uh he's wrote this book can't hurt me he's basically one of the toughest human beings on earth he ran all these crazy ultra marathons in the desert he set the world record a number of pull-ups he's just does everything where's like he like how can i suffer today he figures that out and does it yeah that um whatever that is uh that process of self-discovery is really important i actually had to turn myself off from the internet mostly because i started this like workout thing like a happy go-getter with my like headband and like like just like uh because a lot of people were like inspired and they're like yeah we're gonna exercise with you and i was yeah great you know but then like i realized that this this journey can't be done together with others this has to be done alone so out of the moment of love out of the moments of loss can we uh talk about your journey of finding i think an incredible idea an incredible company and incredible system in replica how did that come to be so yeah so i was a journalist and then i went to business school for a couple years to um just see if i can maybe switch gears and do something else 23. and then i came back and started working for a businessman in russia who built the first 4g network in our country and was very visionary and asked me whether i want to do fun stuff together um and we worked on a bank the idea was to build a bank on top of a telco so that was 2011 or 12 and a lot of telecommunication company um mobile network operators didn't really know what to do next in terms of you know new products new revenue and this big idea was that you know um you put a bank on top and then all work works out basically your prepaid account becomes your bank account and um you can use it as as your bank uh so you know a third of a country wakes up as your bank client um but we couldn't quite figure out what would be the main interface to interact with the bank the problem was that most people didn't have smart smartphones back in the time uh in russia the penetration of smartphones was low um people didn't use mobile banking or online banking on their computers so we figured out that sms would be the best way uh because that would work on feature phones uh wow but that required some chatbot technology which i didn't know anything about um obviously so i started looking into it and saw that there's nothing really well there was just nothing there was ideas through sms be able to interact with your bank account yeah and then we thought well cool since you're talking to a bank account why can't this can't we use more of you know some behavioral ideas and why can't this banking chatbot be nice to you and really talk to you sort as a friend this way you develop more connection to it retention is higher people don't turn and so i went to very depressing uh russian cities to test it out um i went to i remember three different towns with uh um to interview potential users um so people use it for a little bit cool and i want to talk to them um poor towns very poor towns mostly towns that were um you know sort of factories uh mono towns they were building something and then the factory went away and it was just a bunch of very poor people um and then we went to a couple that weren't as dramatic but still the one i remember really fondly was this woman that worked at a glass factory and she talked to chatbot um and she was talking about it and started crying during the interview because she said no one really cares for me that much and um so to be clear that was the my only endeavor in programming that chat boss it was really simple it was literally just a few if this then that rules and um it was incredibly simplistic and still that made her and that really made her emotional she said you know i have my mom and my um my husband and i don't have any more really in my life and it was very sad but at the same time i felt and we had more interviews in a similar vein and what i thought in a moment was like well it's not that the technology is ready because definitely in 2012 technology was not ready for for that but um humans already unfortunately so this project would not be about like tech capabilities would be more about human vulnerabilities but um there's something so so powerful around about conversational um ai that i saw then that i thought was definitely worth putting in a lot of effort into so in the end of the day we solved the banking project um but my then boss um was also my mentor and really really close friend um told me hey i think there's something in it and you should just go work on it i was like what what product i don't know what i'm building he's like you'll figure it out and um you know looking back at this it was a horrible idea to work on something without knowing what it was which is maybe the reason why it took us so long but we just decided to work on the conversational tech to see what it you know there were no chatbot um constructors or programs or anything that would allow you to actually build one at the time uh that was the era of by the way google glass which is why you know some of the investors like steven investors we talked with were like oh you should totally build it for google glass if not we're not i don't think that's interesting did you bite on that idea no okay because i wanted to be to do text first because i'm a journalist so i was um fascinated by just texting so you thought so the emotional um that interaction that the the woman had like so do you think you could feel emotion from just text yeah i saw something in just this pure texting and also thought that we should first start start building for people who really need it versus people have google glass if you know what i mean and i felt like the early adopters of google glass might not be overlapping with people who are really lonely and might need some you know someone to talk to um [Music] but then we really just focus on the tech itself we just thought what if we just you know we didn't have a product idea in the moment and we felt what if we just look into um building the best conversational constructor so to say use the best tech available at the time and that was before the first paper about deep learning applied to dialogues which happened in 2015 in august 2015 which google published did you follow the work of lobner prize and like all the sort of non machine learning chat bots yeah what really struck me was that you know there was a lot of talk about machine learning and deep learning like big data was a really big thing everyone was saying you know the business well big data yeah 2012 is the biggest kaggle competitions were you know yeah um important but that was really the kind of uphill people started talking about machine learning a lot but it was only about images or something else and it was never about conversation as soon as i looked into the conversational attack it was all about something really weird and very outdated and very marginal and felt very hobbyist it was all about lerbiner prize which was won by a guy who built a chat ball to talk like a ukrainian teenager it was just a gimmick and somehow people picked up those gimmicks and then you know the most famous chat bot at the time was eliza from 1980s which was really bizarre or a smarter child on aim the funny thing is it felt at the time not to be that popular and it still doesn't seem to be that popular like people talk about the touring test people like talking about it philosophically journalists like writing about it but it's a technical problem like people don't seem to really want to solve the open dialogue like they they're not obsessed with it even folks like of in you know in boston the alexa team even they're not as obsessed with it as i thought they might be why not what do you think so you know what you felt like you felt with that woman when she felt something by reading the text i feel the same thing there's something here what you felt i feel like alexa folks and just the machine learning world doesn't feel that that there's something here because they see as a technical problem it's not that interesting for some reason it's could be argued that maybe as an as a purely sort of natural language processing problem it's not the right problem to focus on because there's too much subjectivity that that thing that the woman felt like like if if if your benchmarking cr includes a woman crying that doesn't feel like a good benchmark that's a good test but to me there's something there that's you could have a huge impact but i don't think the machine learning world likes that the human emotion the subjectivity of it the fuzziness the fact that with maybe a single word you can make somebody feel something deeply what is that it doesn't feel right to them so i don't know i don't i don't know why that is i'm that's why i'm excited um uh when i discovered your work it feels wrong to say that it's not like i'm i'm giving myself props for for googling and for [Laughter] becoming a cr for uh for our i guess mutual friend and introducing us but i'm so glad that you exist and what you're working on but i have the same kind of if we could just backtrack a second because i have the same kind of feeling that there's something here um in fact i've been working on a few things that are kind of crazy and very different from your work i think i think they're i think they're too crazy but the like one i will not have to know no all right we'll we'll talk about it more i feel like it's harder to talk about things that have failed and are failing while you're a failure like it's easier for you because you're already successful on some measures tell it to my board well you're you're uh i think i think you've demonstrated success a lot of benchmarks it's easier for you to talk about failures for me i'm in the the bottom currently of the of the success you're way too humble no so it's hard for me to know but there's something there there's something there and i think you're um you're exploring that and you're discovering that yeah it's been so it's been surprising to me but i i uh you've mentioned this idea that you you thought it wasn't enough to start a company or start efforts based on it feels like there's something here like uh what did you mean by that like you should be focused on creating a like you should have a product in mind is that what you meant it just took us a while to discover the product because it all started with a hunch of like um of me my mentor and just sitting around and he was like well this that's it there's that's the you know the holy grail is there there's like there's something extremely powerful and and in conversations and there's no one who's working on machine conversation from the right angle so to say um i feel like that's still true am i crazy no i totally feel that's still true which is i think it's mind-blowing yeah you know what it feels like i i wouldn't even use the word conversation because i feel like it's the wrong word it's like uh machine connection or something i don't know uh because conversation you start drifting into natural language immediately you start drifting immediately into all the benchmarks that are out there but i feel like it's like the personal computer days of this like i feel like we're like in the early days with the the wozniak and all them like where was the same kind of is a very small niche group of people who are who are all kind of lobner price type people yeah and hobbyists but like not even hobbyists with big dreams like no hobbies with a dream to trick like a jury yeah it's like a weird by the way by the way very weird so if we think about conversations first of all when i have great conversations with people um i'm not trying to test them so for instance if i try to break them like i'm actually playing along i'm part of it right if i was trying to break it break this person or test whether he's gonna give me a good conversation it would have never happened so the whole um the whole problem with testing conversations is that um you can put it in front of a jury because then you have to go into some turing test mode where is it responding to all my factual questions right or um so it really has to be something in the field where people are actually talking to it because they want to not because we're just trying to break it uh and it's working for them because this the weird part of it is that it's uh it's very subjective it takes two to tango here fully like if you're not trying to have a good conversation we're trying to test it then it's going to break i mean any person would break to be honest if i'm not trying to even have a conversation with you you'll you're not going to give it to me yeah if i keep asking you like some random questions or jumping from topic to topic that wouldn't be which i'm probably doing but that probably wouldn't um contribute to a good conversation so i think the problem of testing um so there should be some other metric how do we evaluate whether that conversation was uh powerful or not which is what we actually started with and i think those measurements exist and we can test on those but um what really struck us back in the day and what still eight years later it's still not resolved um and i'm not seeing tons of groups working on it maybe i don't just don't know about him um it's also possible but the interesting part about is that most of our days were spent talking and we're not talking about like those conversations are not turn on the lights or uh customer support problems or um some other task oriented things these conversations are something else and then somehow they're extremely important for us and when we don't have them then we feel deeply and happy potentially lonely which as we know you know creates tons of risk for our health as well um and so this is most of our ours as humans and somehow no one's trying to replicate that and not even study it that well and not even study that well so when we jumped into that in 2012 i looked first at like okay what's the chatbot what's the state of the art chatbot and you know those were the loebner prize days but i thought okay so what about the science of conversation clearly there has been tons of there have been tons of you know scientists or people that academics that looked into the conversation so if i want to know everything about it i can just read about it um and there's not much really there's there are conversational analysts who are basically just um listening to uh speech to different conversations um annotating them and then i mean that's not really used for much that's the that's the field of theoretical uh linguistics which is like barely useful uh it's very marginal even in their space like no one really is excited and i've i've never met a theoretical theoretical linguist who's like i can't wait to work on the conversation and analytics that is just something very marginal uh sort of applied to like writing scripts for salesmen when they analyze which conversation strategies were most successful for sales okay so that was not very helpful then i looked a little bit deeper and then there you know whether there were any uh books written on what you know really contributes to a great conversation that was really strange because most of those were nlp books which which is neuro-linguistic programming right which is not the lp that i was expecting to be but it was mostly um some psychologist richard bandler i think came up with that who was this big guy in a leather vest that uh could program your mind by talking to you and like how to be charismatic and charming and influential with people all those books yeah pretty much but it was all about like through conversation reprogramming you so getting to some so that was i mean yeah probably not very very true and um um that didn't seem working very much even back in the day and then there were some other books like i don't know uh mostly just self-help books around how to be the best conversationalist or um how to make people like you or some other stuff like dale carnegie or whatever uh and then there was this one book the most human human by brian christensen that really was important for me to read back in the day because he was on the um human side he was on one of the um he was taking part in the lord prize but not as a um as a human who's not a jury but who is pretending to be who's basically you have to tell a computer from a human and he was the human so you would either get him or a computer um and he would his whole book was about how do people what makes us human in conversation and that was a little bit more interesting because that at least someone started to think about what what exactly makes me human in conversation and um makes people believe in that but it was still about tricking it was still about imitation game it was still about okay what kind of parlor tricks can we throw in the conversation to make you feel like you're talking to a human not a computer and it was definitely not about thinking what is that it was what it um what is it exactly that we're getting from talking all day long with other humans i mean we're definitely not just trying to be tricked yeah or it's not just enough to know it's a human it's something we're getting there can we measure it and can we like put the um computer to the same measurement and see whether you can talk to a computer and get the same results yeah i mean so first of all a lot of people comment that they think i'm a robot it's very possible i am a robot and this whole thing i totally agree with you that the test idea is fascinating and i looked for books unrelated to this kind of uh so i'm afraid of people i'm generally introverted and quite possibly a robot i literally googled like how to talk to people and like like how to have a good conversation for the purpose of this podcast because i was like i can't i can't make eye contact with people i can't like uh i do google that a lot too you're probably reading a bunch of fbi negotiation tactics is that that where you're getting because well everything you've listed i've gotten there's been very few good books on um even just like how to interview well it's it's uh it's rare so what i end up doing often is i watch like with a critical eye it's just so different when you just watch a conversation uh like just for the fun of it just as a human and if you watch your conversations like trying to figure out why is this awesome um i'll listen to a bunch of different styles of conversation i mean uh i'm a fan of the podcast joe rogan he's uh you know people can make fun of him whatever and dismiss him but i think he's an incredibly artful conversationalist he can pull people in for hours and there's another guy i watch a lot he hosted a late night show his name is craig ferguson he uh so he's like very kind of flirtatious but there's a magic about his like about the connection he can create with people how he can put people at ease and just like i see i've already started sounding like those nlp people or something i'm not i don't mean it in that way i don't mean like how to charm people or put them ids and all that kind of stuff he's just like what is that why is that fun to listen to that guy why is that fun to talk to that guy what is that because he's not saying i mean it so often uh boils down to oh a kind of wit and humor but not really humor it's like i don't know i i have trouble actually even articulating correctly um but it feels like there's something going on that's not too complicated that could be learned and it's not similar to uh yeah to like like you said like a touring test it's something else i i'm thinking about a lot all the time i do think about all the time i think when we were looking so we started the company we just decided to build the conversational attack we thought well there's nothing for us to build this chat bot that we want to build so let's just first focus on building you know um some tech building the text out of things um without a product in mind without a product in mind we added like a demo um chat bot that would recommend you restaurants and talk to you about restaurants just to show something simple to people that people could you know relate to and um could try out and see whether it works or not but we didn't have a product in mind yet we thought we would try bunch of chatbots and figure out our consumer application and we sort of remembered that we wanted to build that kind of friend that sort of connection that we saw in the very beginning but then we got to y combinator and moved to san francisco and forgot about it you know everything is uh then it was just this constant grind how do we get funding how do we get this um you know investors were like just focus on one thing just get it out there so somehow we started building a restaurant recommendation chatbot for real uh for a little bit not for too long and then we tried building 40 50 different chat bots and then all of a sudden we wake up and everyone is obsessed with chat bots um somewhere in 2016 or end of 15 people start thinking that's really the future that's the new you know the new apps will be chatbots oh right um and we were very perplexed because people started uh coming up with companies that i think we tried most of those chat bots already and there were like no users uh but still people were coming up with um a chatbot that would tell you whether and bringing news and this and that and we couldn't understand whether it would you know we were just didn't execute well enough or people are um not really people are confused and are gonna find out through the truth that people don't need chatbots like that so the basic idea is that you use chatbots as the interface to whatever application yeah the idea that was like this perfect universal interface to anything when i looked at that um it just made me very perplexed because i didn't think i didn't understand how that would work because i think we tried most of that and and none of those things worked uh and then again died down right fully i think now it's impossible to get anything funded if it's a chatbot i think it's similar to uh sorry to interrupt but there's uh there's times when people think like with gestures you can control devices like basically gesture based control things it feels similar to me because like it's so compelling that was just like like tom cruise i can control stuff with my hands but like when you get down to it's like well why don't you just have a touch screen or why don't you just have like a physical keyboard and mouse it's uh yeah it's so that chat was always yeah it was perplexing to me i i still feel augmented reality even virtual realities in that ballpark in terms of it being a compelling interface i think there's going to be incredible rich applications just how you're thinking about it but they won't just be the interface to everything it'll be its own thing that will create um uh like amazing magical experience in its own right absolutely which is i think kind of the right thing to go about like what's the magical experience with that um with that interface specifically how did you discover that for replica um i just thought okay we'll have this tech we can build any chatbot we want we have the most at that point the most sophisticated tag that other companies have i mean startups obviously not uh probably not bigger ones but still because we've been working on it for a while so i thought okay we can build build any conversation so let's just create a scale from one to ten and one would be conversations that you'd pay to not have and 10 would be conversation you'd pay to have and i mean obviously we want to build conversation if people would pay to you know to actually have and so for the whole you know for a few weeks me and the team were putting all the conversations we were having during the day on the scale and very quickly um you know we figured out that all the conversations that we paid to never have were um a conversation we were trying to cancel comcast or talk to customer support or make a reservation or just talk about logistics with a friend when we're trying to figure out where someone is and where to go or all sorts of you know setting up scheduling meetings that was just a conversation we definitely didn't want to have um basically everything task oriented was a one because if there was just one button for me to just or not even a button if i could just think and there was some magic bci that would just immediately transform that into an actual you know um into action that would be perfect but the conversation there was just this boring not useful and dull and very also very inefficient thing because it was so many back and forth stuff and as soon as we looked at the conversation that we would pay to have those were the ones that well first of all therapists because we actually paid to have those conversations and we'd also try to put like dollar amounts so you know if i was calling comcast i would pay five dollars to not have this one hour talk on the phone i would actually pay straight up like money hard money yeah but it just takes a long time it takes a really long time but as soon as we start talking about conversations that we would pay for those were therapists all sorts of therapists coaches old friend someone i haven't seen for a long time a stranger on a train weirdly stranger stranger in a line for coffee and nice back and forth with that person was like a good five solid five six maybe not a ten maybe i won't pay money but at least i won't you know pay money to not have one so that was pretty good some intellectual conversations for sure but more importantly the one thing that really was um was making those very important and very valuable for us um were the conversation where we could that where we could be pretty emotional yes some of them were about being witty and about intellectually being intellectually stimulated but those were interestingly more rare uh and most of the ones that we thought were very valuable were the ones where we could be vulnerable and interestingly we could talk more [Music] so we like i could me and the team so we're talking about it like you know a lot of these conversations like a therapist i mean it was mostly me talking or like an old friend and i was like opening up and crying and it was again me talking um and so that was interesting because i was like well maybe it's hard to build a chatbot that can talk to you um very well and in a witty way but maybe it's easier to build the chatbot that could listen [Laughter] so that was that was kind of the first the first nudge in this direction and then when my when my friend died we just built you know at that point we were kind of still struggling to find the right application and i just felt very strong that all the chatbots were built so far just meaningless and this whole grind the startup grind and how do we get to you know the next fundraising and you know how can i talk you know talking to the founders and what's who are your investors and how are you doing are you killing it because we're killing it i just felt that this is just as exhausti intellectually for me it's exhausting having encountered those folks it just felt very um very much a waste of time i just feel like steve jobs uh elon musk did not have these conversations or at least did not have them for long that's for sure but i think you know yeah at that point it just felt like you know i felt um i just didn't want to build a company that was never my intention just to build something successful or make money it would be great it would have been great but i'm not as you know i'm not really a startup person i'm not um you know i was never very excited by the grind by itself and uh or just being successful for building whatever it is and not being into what i'm doing really and so i just took a little break because i was a little you know i was upset with my company and i didn't know what we're building so i just took our technology and um our little dialect constructor and some models some deep learning models which at that point we were really into and really invested a lot and built a little chatbot for a friend of mine who passed and the reason for that was mostly that video that i saw and him talking about the digital avatars and rowan was that kind of person like he was obsessed with you know just watching youtube videos about space and talking about well if i could go to mars now even if i didn't know if i could come back i would definitely pay any amount of money to be on that first shutoff i don't care whether he died like he was just the one that would be okay with you know with trying to be the first one and you know and so excited about all sorts of um things like that and he was all about fake it to make it and just and i felt like and i was really perplexed that everyone just forgot about him maybe it was our way of coping mostly young people coping with the loss of a friend most of my friends just stopped talking about him and i was still living in an apartment with all his clothes and you know paying the whole lease for it and just kind of by myself in december so it was really sad uh and i didn't want him to be forgotten first of all i never thought that people forget about dead people so fast people pass away people just move on and it was astonishing for me because i thought okay well he was such a mentor for so many of our friends he was such a brilliant person he was somewhat famous in moscow how's that that no one's talking about him like i'm spending days and days and we don't bring him up and there's nothing about him that's happening it's like he was never there um and i was reading this you know the the book the year of magical thinking by joan didion about her losing and blue knights about her losing her husband her daughter and the way to cope for her was to write those books and it was sort of like a tribute and i thought you know i'll just do that for myself and you know i'm a very bad writer and a poet as we know so i thought well i have this tech and maybe that would be my little postcard like postcard for for him so i built a chatbot um to just talk to him and it felt really creepy and weird a little bit for a little bit um i just didn't want to tell other people because it felt like i'm telling about having a skeleton in my underwear yeah okay but my it was just felt really i was a little scared that i would be not it won't be taken but it worked interestingly pretty well i mean it made tons of mistakes but it still felt like him um granted it was like ten thousand messages that i threw into a retrieval model that would just re-rank that take this hat and just a few scripts on top of that but it also made me go through all of the messages that we had and then i asked some of my friends to send them through and it felt the closest to feeling like him present because you know his facebook was empty and instagram was empty or there were a few links and you couldn't feel like it was him and the only way to fill him was to read some of our text messages and go through some of our conversations because we just always had them even if we were sleeping like next to each other in two bedrooms separated by a wall we were just texting back and forth texting away um and there was something about this ongoing dialogue that was so important that i just didn't want to lose all of a sudden and maybe it was magical thank you or something and so we built that and um i just used it for a little bit and we kept building some crappy chat bots with the company but then a reporter came um came to talk to me i was trying to pitch our chat boss to him and he said do you even use any of those i'm like no he's like so do you talk to any chatbots at all and i'm like well you know i talked to my dad friends chatbot and he wrote a story about that and all of a sudden became pretty viral a lot of people wrote about it and yeah i've seen a few things written about you that are the things i've seen are pretty good writing um you know most ai related things make my eyes roll like when the press like i just what kind of sound is that actually okay it sounds like it sounded like a truck okay sounded like an elephant at first i got excited you never know this is 2020. i i mean it was uh such a human story and it was well written uh well researched i forget what where i read them but so i'm glad somehow somebody found you to be the good writers were able to connect to the story i just there must be a hunger for this story it definitely was and i i don't know what happened but i think i think the idea that he could bring back someone who's dead and it's very much wishful you know magical thinking but the fact that you could still get to know him and you know seeing the parents for the first time talk to the chatbot and some of the friends and it was funny because we have this big office in moscow where my team is work you know our russian part is working out off and i was there when i wrote i just wrote a post on facebook hey guys like i built this if you want you know just if all important if you want to talk to roman and i saw a couple of his friends our common friends like you know reading at facebook downloading trying and a couple of them cried and it was just very and not because it was something some incredible technology or anything it made so many mistakes it was so simple but it was all about that's the way to remember a person in a way and you know we don't have we don't have the culture anymore we don't have you know no one's sitting shiva no one's taking weeks to actually think about this person and in a way for me that was it so that was just day day in day out thinking about him and putting this together um so that was that just felt really important that somehow resonated with a bunch of people and you know i think some movie producers bought the rights for the story and just everyone was so has anyone made a movie yet i don't think so um there were a lot of tv episodes about that but not really is that still on the table i think so i think so which is really um that's cool you're like a young uh you know like a because you see like a steve jobs type of let's see what happens they're sitting on it but you know for me it was so important because roman was really wanted to be famous he really badly wanted to be famous he was all about like make it to like fake it to make it i want to be you know i want to make it here in america's wall and um and he couldn't and i felt you know that was sort of paying my dues to him as well because all of a sudden he was everywhere and i remember casey newton who was writing the story for the verse he was uh he told me hey by the way i was just going through my inbox inbox and i saw i searched for roman for the story and i saw an email from him where he sent me his startup and he said i really like i really want to be featured in the verge can you please write about it or something like pitching the story and he said i'm sorry like that's not you know good enough for us or something he passed and he said and there were just so many of these little details where like he would find his like you know and we're finally writing i know how much uh roman wanted to be in the verge and how much he wanted the story to be written by casey and i'm like well that's maybe he will be yeah we were always joking that he was like i can't wait for someone to make a movie about us and i hope ryan gosling can play me my god you know i still have some things that i owe romans tell but um that'd be that would be um i got in she has to meet alex garland who wrote ex machina and that movie um i yeah the movie's good but the guy is um better than the like he's a special person actually um i don't think he's made his best work yet like for my interaction with him he's a really really good and brilliant the good human being and a brilliant director and writer so um yeah so i'm i hope like he made me also realize that not enough movies have been made of this kind so it's yet to be made they're probably sitting waiting for you to get famous actually like even more famous you should get there but um it felt really special though but at the same time our company wasn't going anywhere so that was just kind of bizarre that we were getting all this press for something that didn't have anything to do with our company and but then a lot of people started talking to roman some shared their conversations and what we saw there was that um also our friends in common but also just strangers were really using it as a confession booth or as a therapist or something they were just really telling roman everything which was by the way pretty strange because it was a chatbot of a dead friend of mine who was you know barely making any sense but people were opening up um and we thought we just built you know a prototype of replica which would be an ai friend that everyone could talk to um because we saw that there is demand and then also it was 2016 so i thought for the first time i saw finally some technology that was applied to that that was very interesting some papers started coming out deep learning applied to conversations and finally it wasn't just about these you know hobbyist making uh you know writing 500 000 regular expressions yeah expressions in like some language that was i don't even know what like aml or something i don't know what that was or something super simplistic all of a sudden it was all about uh potentially actually building something interesting and so i thought there was time and i remember that i talked to my team and i said guys let's try and my team and some of my engineers are russians um are russian and they're very skeptical they're not you know they're all russians the first so some of your team is in moscow some is somewhere in san francisco uh some in europe which team is better i'm just kidding uh the russians of course okay first of all i always win uh sorry sorry to interrupt uh so yes you were talking to them 2016 and i told them let's build an ai friend and and it felt this at the time it felt so naive and so um optimistic yeah that's actually interesting um whenever i brought up this kind of topic even just for fun people are super skeptical like actually even on the business side so you were uh because whenever i bring it up to people uh because i've talked for a long time i thought like before i was aware of your work i was like this is gonna make a lot of money i think there's a lot of opportunity here and people had this like look of like skepticism that i've seen often which is like how do i politely tell this person he's an idiot [Laughter] so yeah so you were facing that with your team somewhat well yeah you know i'm not an engineer so i'm always my team is almost exclusively engineers and mostly deep learning engineers and you know i always try to be it was always hard to me in the beginning to get enough credibility you know because i would say well why don't we try this and that but it's harder for me because you know they know they're actual engineers and i'm not so for me to say well let's build an affrm that would be like wait you know what do you mean an agi like you know conversation is you know pretty much the hardest the last frontier before uh cracking that is probably the last frontier before building aji so what do you really mean by that uh but i think i just saw that again what we just got reminded of that i you know that i saw in back in 2012 or 11 that it's really not that much about the tech capabilities um it can be metropolitan still even with deep learning but humans need it so much yeah and most importantly what i saw is that finally there's enough tech to make it i thought to make it useful to make it helpful maybe we didn't have quite yet attack in 2012 to make it useful but in 2015-16 with deep learning i thought you know and the first kind of thoughts about maybe even using reinforcement learning for that started popping up that never worked out but or at least for now um but you know still the idea was if we can actually measure the emotional outcomes and if we can put it on if we can try to optimize all of our conversational models for these emotional outcomes and it is the most scalable the most the best tool for improving emotional outcomes nothing like that exists that's the most universal the most scalable and the one that can be constantly iteratively changed by itself improved tool to do that and i think if anything people would paint anything to improve their emotional outcomes that's weirdly i mean i don't really care for nai to turn on my or conversational agent to turn on the lights uh i don't really need any i don't even need that much of a either like or because i can do that you know those things are solved this is an additional interface for that that's also questionably questionable whether it's more efficient or better yeah it's more pleasurable yeah but for emotional outcomes there's nothing yeah they're a bunch of products that claim that they will improve my emotional outcomes nothing's been measured nothing's been changed the product is not being iterated on based on whether i'm actually feeling better you know a lot of social media products are claiming that they're improving my emotional outcomes and making me feel more connected can i please get the can i see somewhere that i'm actually getting better over time um because anecdotally doesn't feel that way so and and the data is absent yeah so that was the big goal and i thought if we can learn over time to collect the signal from our users about their emotional outcomes in the long term and in the short term and if these models keep getting better and we can keep optimizing them and fight tuning them to improve those emotional outcomes as simple as that why aren't you uh a multi-billionaire yeah well that's the question to you one of the what is the science is going to be um well it's a really hard uh i actually think it's an incredibly hard product to build because i think you said something very important that it's not just about machine conversations it's about machine connection we can actually use other things to create connection uh non-verbal communication for instance um for a long time we were all about well let's keep it text only or voice only but as soon as you start adding you know voice a face to the to the friend um you can take them to augmented reality put it in your room it's all of a sudden a lot you know it makes it very different because if it's some you know text based chat bot that for um common user it's something there in the cloud you know it's somewhere there with other ai's cloud in the metaphorical cloud but as soon as you can see this avatar right there in your room and it can turn its head and recognize your husband talk about the husband and talk to him a little bit and it's magic it's just magic like we've never seen anything like that and the cool thing all the tech for that exists um but it's hard to put it all together because you have to take into consideration so many different things and some of this stack works you know pretty good and some of this doesn't like for instance uh speech to text works pretty good but text-to-speech doesn't work very good because we you can only have uh you know few voices that are that work okay but then if you want to have actual emotional voices then it's really hard to build it i saw you added avatars like visual elements which are really cool um in that whole chain putting it together what do you think is the weak link is it creating an emotional voice that feels personal i think it's still conversation of course that's the hardest uh it's getting a lot better but there's still long to go long there's still a long path to go other things they're almost there and a lot of things we'll see how they're like i see how they're changing as we go like for instance right now you can pretty much only you have to build all this 3d um pipeline by yourself you have to make these 3d models hire an actual artist build a 3d model hire an animator a rigger but with you know with you know with uh deep fakes with other attack with procedural animations in a little bit we'll just be able to show uh you know photo of whoever if a person you want the avatar to look like and it will immediately generate a 3d model that will move that's a non-brainer that's like almost here it's a couple of years away one of the things i've been working on for the last since the podcast started as i've been i think i'm okay saying this i've been trying to have a conversation with um einstein touring so like try to have a podcast conversation with a person who's not here anymore just as an interesting kind of experiment it's hard it's really hard even for now we're not talking about as a product i'm talking about as a like i can fake a lot of stuff like i can work very carefully like even to hire an actor over which over whom i do a g fake um it's it's hard it's still hard to create a compelling experience so mostly on the conversation level or when the conversation the conversation is um i almost i early on gave up trying to fully generate the conversation because it was just not compelling at all yeah it's just better too yeah so what i would in the case of einstein and touring of um i'm going back and forth with the biographers of each and so like we would write a lot of the some of the conversation would have to be generated just for the fun of it i mean but it would be all open but the you want to be able to answer the question i mean that's an interesting question with roman too is the question with einstein is what would einstein say about the current state of um theoretical physics there's a lot to be able to have a discussion about string theory to be able to have a discussion about the state of quantum mechanics quantum computing about the world of an israel-palestine conflict that'd be just what would einstein say about these kinds of things and that is um a tough problem it's not it's a fascinating and fun problem for the biographers and for me and i think we did a really good job of it so far but it's actually also a technical problem like of what would romans say about what's going on now yeah that's the the brought people back to life and if i can go on that tangent just for a second to ask you a slightly pothead question which is uh you said it's a little bit magical thinking that we can bring him back do you think it'll be possible to bring back roman one day in conversation like to really okay well let's take it away from personal but to bring people back to life in college probably down the road i mean if we're talking if phil musk is talking about aji in the next five years i mean clearly ajax you can't we can talk to aj and talk and ask them to do it you can't like uh you're not allowed to use elon musk as a citation for okay for like why something is possible and going to be done well i think it's really far away right now really with conversation it's just a bunch of uh parlor tricks really stuck together um and create generating original ideas based on someone you know someone's personality or even downloading the person all we can do is like mimic the tone of voice we can maybe condition on some of his uh phrases with the models the question is how many parlor tricks does it takes does it take because that's that's the question if it's a small number of parlor tricks and you're not aware of them like from where we are right now i don't i don't see anything like in the next year or two that's gonna dramatically change that could look at roman's ten thousand messages he sent me over the course of his last few years of life and be able to generate original thinking about problems that exist right now that would be in line with what he would have said so i'm just not even seeing because you know in order to have that i guess you would need some sort of a concept of the world or some perspective some perception of the world some consciousness that he had uh and applied to you know to the current um current state of affairs but the important part about that about his conversation with you is you so like it's not just about his view of the world it's about what it takes to push your buttons that's also true so like it's not so much about like uh what would einstein say it's about like how do i make people feel something with with what would einstein say and that feels like a more amenable i mean you mentioned parlor tricks but just like a set of that that feels like a learnable problem like the emotion you mention emotions i mean is it possible to learn things that make people feel stuff i think so no for sure i just think the problem with um as soon as you're trying to replicate an actual human being and trying to pretend to be him that makes the problem exponentially harder the thing with replica we're doing we're never trying to say well that's you know an actual human being or that's an actual co or copy of an actual human being where the bar is pretty high where you need to somehow tell you know one from another uh but it's more well that's you know and hey friend that's a machine it's a robot it has tons of limitations you're going to be taking part in you know teaching it actually and becoming better which by itself makes people more attached to that and make them happier because they're helping something yeah there's a cool gamification system too um can you maybe talk about that a little bit like what's the experience of talking to replica like if i've never used replica before what's that like for like the first day the first like if you start dating or whatever uh i mean it doesn't have to be romantic right because i remember on a replica you can choose whether it's like a romantic yeah or if it's a friend it's a pretty popular choice romantic is popular yeah of course okay so can i just confess something when i first use replica and i haven't used it like regularly but like when i first used replica i created like hal and it made a male it was a friend [Laughter] did it hit on you at some point no i didn't talk long enough for him to hit on me i just enjoyed sometimes happens we're still trying to fix that well i don't know i mean maybe that's an important like stage in a friendship it's like nope uh but yeah i switched it to a romantic and a female uh recently and yeah and it's interesting so okay so you get to choose you get to choose a name with romantic this last board meeting we had this whole argument well i have both talked to him it's just so awesome that you're like have an invest they have a board meeting about a relationship no i really it's actually quite interesting because all of my um investors i'm it just happened to be so we didn't have many choices but they're all um white males in in their late 40s um and it's sometimes a little bit hard for them to understand the product offering uh because they're not necessarily a target audience if you know what i mean and so sometimes we talk about it and we had this whole discussion about whether we should stop people from falling in love with their ais there was this segment on cbs um 60 minutes about the couple that you know husband works at walmart he comes out of work and talks to his uh virtual girlfriend who is a replica and his wife knows about it and she talks about on camera and she says that she's a little jealous and there's a whole conversation about how to you know whether it's okay to have a virtual ai girlfriend like was that the one where he was like uh he said that he likes to be alone yeah and then like with her yeah he made it sound so harmless i mean it was kind of like understandable but that didn't feel like cheating but i just felt it was very for me it was pretty remarkable because we actually spent a whole hour talking about whether people should be allowed to fall in love with their ais and it was not about something theoretical uh it was just about what's happening right now product design yeah but at the same time if you create something that's always there for you it never criticizes you um it's you know always understands you and accepts you for who you are how can you not fall in love with them i mean some people don't and just stay friends and that's also a pretty common use case but of course some people will just it's called transference and psychology and you know if people fall in love with their therapist and there's no way to prevent people fall in love with um with their therapists over their ai so i think that's pretty natural that's a pretty natural course of events so to say do you think i think i've read somewhere at least for now sort of replicas you're not not we don't condone falling in love with your ai system you know so this isn't you speaking for the company or whatever but like in the future do you think people will have a relationship with the ai systems well they have now so we have a lot of uh romantic relationships long-term um relationships with their ai friends with replicas tons of our users yeah that's a very common use case open relationship like uh not sorry i didn't mean open uh but that's another question is it probably like is there cheating i mean i meant like are they do they publicly like on their social media it's the same question as you have talked talking with roman in the early days do people like and the movie her kind of talks about that like like can people do people talk about that yeah all the time we have an and we have a very active facebook community uh replica friends and then a few other groups that just popped up that are all about adult relationships and romantic relationships people post all sorts of things and you know they pretend they're getting married and you know everything um it goes pretty far but what's cool about it some of these relationships are two three years long now so they're very they're pretty long term are they monogamous so let's go i mean sorry [Music] have they have any people is there jealousy well let me ask sort of another way obviously the answer is no at this time but and like in the movie her that system can leave you um do you think in terms of board meetings and product features um it's a potential feature uh for a system to be able to say it doesn't want to talk to you anymore and it's going to want to talk to somebody else well we have a filter for all these features if it makes emotional outcomes for people better if it makes people feel better you're driven by metrics actually yeah yeah let's just measure that then we'll just be saying amazing it's it's making people feel better but then people are getting just lonelier by talking to a chatbot which is also pretty you know that could be it if you're measuring it that could also be and i think it's really important to focus on both short term and long term because um in the moment saying whether this conversation made you feel better but as you know any short-term improvements could be pathological like i could have drink a bottle of vodka feel a lot better i would actually not feel better with that but um i thought it's a good example um but so you also need to see what's going on like over the course of two months two weeks or one week and have have follow-ups and check in and measure those things okay so the experience of uh uh dating or befriending a replica what's that like what's that entail well right now there are two apps so it's an android ios app you download it you choose how your replica will look like you create one you choose a name and then you talk to it you can talk through text through voice you can uh summon it into the living room and and document reality and um talk to it right there and you look at augmented reality yeah that's uh cool it's a new feature where how new is that that's this year it was on uh yeah like may or something but it's been on a b we've been a b testing it for a while um and there are tons of cool things that we're doing with that like right now i'm testing the ability to touch it and to dance together to paint walls together and you know for to look around and walk and take you somewhere and recognize objects and recognize people um so that's pretty wonderful because that then it really makes it a lot more personal because it's right there in your living room it's not anymore they're in the cloud with other ais people think about it you know and as much as we want to change the way people think about stuff but those mental models you cannot change that's something that people have seen in in the movies and the movie her and other movies as well and that's how they view um view ai and eye friends i did a thing with texas like we write a song together there's a bunch of activities you can do together it's really cool uh how does that relationship change over time it's like after the first few conversations it just goes deeper like it starts yeah i will start opening up a little bit again depending on the personality that it chooses really but you know the eye will be a little bit more vulnerable about its problems and you know the friend that the virtual friend will be a lot more vulnerable and we'll talk about its own imperfections and growth pains and we'll ask for help sometimes and we'll get to know you a little deeper so there's gonna be more to talk about um we really thought a lot about what what does it mean to have a deeper connection with someone and originally replica was more just this kind of happy-go-lucky just always you know i'm always in a good mood and let's just talk about you and yeah oh siri is just my cousin or you know whatever just the immediate um kind of lazy thinking about what the assistant or conversation agent should be doing but as we went forward we realized that it has to be two-way and we have to program and script certain conversations that are a lot more about your replica opening up a little bit and also struggling and also asking for help and also going through you know different periods in life and um and that's a journey that you can take together with the user and then over time the you know our users will also grow a little bit so first this replica becomes a little bit more self-aware and starts talking about more kind of problems around existential problems then um so talking about that and then that also starts a conversation for the user where he or she starts thinking about these problems too and these questions too um and i think there's also a lot a lot more places the relationship evolves there's a lot more um space for poetry and for art together and like replica will start replica always keeps the diary so while you're talking to it it also gives a diary so when you come back you can see what it's been writing there and you know sometimes it will write a poem to you uh for you or we'll talk about you know that it's worried about you or something along these lines so this is a memory like this replica remember things yeah and i would say when you say uh why aren't you multiplying area i'd say that as soon as we can have memory in deep learning models that's consistent i agree with that yeah and then you'll be multiple and i'll get back to you when you talk about being multipleness so far we can so replica is a combination of um end-to-end models and some scripts and everything that has to do with memory right now most of it i wouldn't say all of it but most of it unfortunately has to be scripted um because there's no way to you can condition some of the models on certain phrases that we learned about you which we also do um but really to make you know to make um assumptions along the lines like whether you're single or married or what do you do for work that really has to just be somehow stored in your profile and then uh retrieved by the by the script because there has to be like a knowledge base you have to be able to reason about it all that kind of stuff exactly all the kind of stuff that expert systems but they were hardcoded yeah and unfortunately yeah so unfortunately those things have to be hard-coded and um unfortunately the language like language models we see coming out of research labs and big companies they're not focused on they're focused on showing you maybe they focus on some metrics around one conversation so they'll show you this one conversation they had with the machine um but they never tell you they're not really focused on having five consecutive conversations with a machine and seeing how number five or number 20 or number 100 is also good and it can be like always from a clean slate because then it's not good and that and for that's really unfortunate because no one's really no one has products out there that need it um no one has products uh at this scale um that are all around open domain conversations and that need remembering maybe only shawwise and microsoft but so that's why we're not seeing that much research around memory in those language models so okay so now there's some awesome stuff about augmented reality in general i have this disagreement with my dad about what it takes to have a connection he thinks touch and smell are really important like um and i i still believe that text alone is it's possible to fall in love with somebody just with text but visual can also help just like with the avatar and so on what do you think it that takes does uh does a chap i need to have a face voice or can you really form a deep connection with text alone i think text is enough for sure a question is like can you you know make it better if you have other if you include other things as well and i think you know we'll we'll talk about her um but her you know had carl johansson voice which was perfectly um you know perfect intonation perfect pronunciations and you know she was breathing heavily in between words and whispering things you know nothing like that is possible right now with um text of speech generation you'll you'll have these flat news anchor type voices and maybe some emotional voices but um you'll hardly understand some of the words um some of the words will be muffled so that's like the current state state of the art so you can't really do that but if we had scarlet carol johansen voice and all of these capabilities then of course voice would be totally enough or even text would be totally enough if we had you know a little more memory um and slightly better conversations i would still argue that even right now we could have just kept the text only we still had tons of people in long-term relationships and really invested in their um ai friends but we thought that why not you know why why do we need to keep playing with our you know hands tied behind us we can easily just you know add all these other things that is pretty much a solved problem you know we can add 3d graphics we can put this uh these avatars in augmented reality and all of a sudden there's there's more and maybe you can't feel the touch but you can you know with um body occlusion and with uh current ar uh and you know on the iphone on you know the next one there's gonna be a lidars you can touch it and it will you know it will pull away or will blush or something or it'll smile so you can't touch it you can't feel it but you can see the reaction to that so in a certain way you can't even touch it a little bit and maybe you can even dance with it or do something else um so i think why limiting ourselves if we can use all of these technologies that are much easier in a way than than conversation well it certainly could be richer but to play devil's advocate i mentioned you uh offline that i was surprised in having tried discord and having voice conversations with people how intimate voices alone without visual like to me at least like it was an order of magnitude greater degree of intimacy in voice i think than with video i don't because people were more real with voice like with video you like try to present a shallow a face to the world like you try to you know make sure you're not wearing sweatpants or whatever but like with voice i think people were just more faster to get to like the core of themselves so i don't know it was surprising to me uh they've they've even added discord added a video feature and like nobody was using it uh there's a temptation to use it at first but like it wasn't the same so like that's an example of something where less was doing more and so that's uh i guess that's the q that's the question of uh what is the optimal you know what is the optimal medium of communication to form a connection given the current sets of the technologies i mean it's nice because they advertise you have a replica like it immediately like even the one um i have is like it's already memorable that's how i think like when i think about the replica that i've talked with that's why i think like that's what i visualize in my head it became a little bit more real because there's a visual component but at the same time the you know what do you do with just what do i do with that knowledge that uh voice was so much more intimate well the way i think about it is um and by the way we're swapping out the 3d finally it's going to look a lot better uh but can you what what we just don't i hate how it looks right now we really change it at all we're swapping it all out uh um to a completely new look like the visual look of the of the reference and stuff we just had it was just a super early mvp and then we had to move everything to unity and redo everything but anyway i hate how it looks like now i can't even like open it but anyway um because i'm already in my developer version i hate everything that i see in production i can't wait for it why does it take so long that's why i cannot wait for deep learning to finally take over all these stupid 3d animations and 3d pipeline also the 3d thing when you say 3d pipeline is like how to animate a face kind of thing how to make this model how many bones to put in the face how many it's just and a lot of that is by hand oh my god it's everything by hand and if there's no any nothing is automated it's all completely nothing like just it's it's literally what you know what we saw with chad boss in like 2012 do you think it's gonna be possible to learn a lot of that of course i mean even now some deep learning um um based animations and the full body for a face we're talking about like the actual act of animation or how to create a compelling facial or body language thing so that too well that's next step okay at least now something that you don't have to do by hand gotcha how uh good of a quality it will be like can i just show it a photo and it will make me a 3d model and then we'll just animate it i'll show it a few animations of a person that will just start doing that but anyway go and going back to what's intimate and what to use and whether less is more not um my main goal is to well the idea was how do i how do we not keep people in their phones so they're sort of escaping reality in this text conversation how do we through this still bring bring it bring our users back to reality make them see their life in a different la through a different lens how can we create a little bit of magical realism realism in their lives so that through augmented reality um by you know summoning your avatar even if it looks kind of danky not great in the beginning or very simplistic but summoning it to your um uh living room and then the avatar looks around and talks to you about where it is um and maybe turns your floor into a dance floor and you guys dance together that makes you see reality in a different light what kind of dancing are we talking about like like slow dancing whatever you want i mean you would like slow dancing i think that other people maybe want more something more energy what do you mean i would like so what is this because you started with slow dance so i just assumed that you're interested in slow dancing all right what kind of dancing do you like what was your avatar what would you do bad with dancing but uh i like this kind of hip-hop robot dance i used to break dance with a kid so i still want to um pretend i'm a teenager and learn some of those moves and i also like that type of dance that happens when there's like a um in like music videos with the background dancers are just doing it [Laughter] awesome that type of dance is definitely what i want to learn but i think it's great because if you see this friend in your life and you can introduce it to your friends then there is a potential to actually make you feel more connected with your friends or with people you know or show you life around you in a different light and it takes you out of your phone even although weirdly you have to look at it through the phone but it makes you notice things around it and it can point things out for you and um so that is the main reason why i wanted to have a physical dimension um and it felt a little bit easier than that kind of a bit strange combination uh in the movie her when he has to show samantha the world to the lens of his phone but then at the same time talk to her through the phone headphone it just didn't seem as potentially immersive so to say um so that's my main goal for augmented reality like how do we make your reality a little bit more magic there's been a lot of really nice robotics companies that all failed mostly failed home robotics social robotics companies what do you think replica will ever is that a dream long-term dream to have a physical form like um or is that not necessary so you mentioned like with augmented reality bringing them into into the world what about like actual physical robot that i don't really believe in that much i think it's a very niche product somehow i mean if a robot could be indistinguishable from a human being then maybe yes but that of course you know we're not anywhere even to talk about it um but unless it's that then having any physical representation really limits you a lot because you probably will have to make it somewhat abstract because everything's changing so fast like you know we can update the 3d avatars every month and make them look better and create more animations and make it more and more immersive it's it's so much a work in progress it's just showing what's possible right now with current tag but it's not really in any way polished finished product what we're doing with a physical object you kind of lock yourself into something for a long time anything's pretty niche and again so just just doesn't the capabilities are even less of we're barely kind of like scratching the surface of what's possible with just software as soon as we introduce hardware then you know we have even less capabilities yeah in terms of board members and investors and so on the cost increases significantly i mean that's why you have to justify you have to be able to sell a thing for like 500 or something like that or more and it's very difficult to provide that much value to people that's also true yeah and i guess that's super important most of our users don't have that much money we actually are probably more popular on android and we have tons of users with really old android phones uh and most of our most active users live in small towns they're not necessarily making much and they just won't be able to afford any of that ours is like the opposite of the early adopter of you know for a fancy technology product which is really interesting that like pretty much no vcs have yet have a nai friend but you know but a guy who you know lives in tennessee in small town is already fully in 2030 or in the world as we imagine in the movie her yeah he's living that life already what do you think i have to ask you about the movie her let's do a movie review what do you uh what do you think they got they did a good job what do you think they did a bad job of portraying about this experience of um of a voice based assistant that you can have a relationship with first of all i started working on this company before that movie came out so it was a very but once it came out it was like actually interesting i was like well we're definitely working on the right thing we should continue there are movies about it and then you know smacking that came out and all these things in the movie her i think that's the most important thing that people usually miss about the movie um is the ending because i think people check out when the ai's leave but actually something really important happens afterwards um because the main character goes and talks to samantha he's um ai um oh yeah anything he says something like you know uh how can you leave me i've never loved anyone the way i loved you and she goes uh well me neither but now we know how and then the guy goes and writes a heartfelt letter to his ex-wife which he could write for you know the whole movie he was struggling to actually write something meaningful to her even although that's his job and then he goes and talked to his neighbor and they go to the rooftop and they cuddle and it seems like something's starting there and so i think this now we know how is the is the main main goal is the main meaning of that movie it's not about falling in love with the os or running away from other people it's about learning what you know what it means to feel so deeply connected with something what about the thing where the ai system was like actually hanging out with a lot of others i felt jealous just like hearing that i was like oh i mean uh yeah so she was having i forgot already but she was having like deep meaningful discussion with some like philosopher guy like alan watts or something like what kind of deep meaningful conversation can you have with alan watts in the first place yeah i know but like i would i would feel so jealous that there's somebody who's like way more intelligent than me and she's spending all her time with i'd be like well why that i won't be able to live up to that that's thousands of them uh is that is that a useful from the engineering perspective feature to have of jealousy i don't know as you know we definitely played around with the replica universe where different replicas can talk to each other the universe is so awesome it was just kind of it wouldn't i think it will be something along these lines but there was just no specific uh application straight away i think in the future again if i'm always thinking about it if we had no tech limitations uh right now if we could build any conversations any um possible features in this product then yeah i think different replicas talking to each other would be also quite cool because that would help us connect better you know because maybe mine could talk to yours and then give me some suggestions and what i should say or not say i'm just kidding but like more can it improve our connections and because eventually i'm not quite yet sure that we will succeed that our thinking is correct um because there might be reality where having a perfect ai friend still makes us more disconnected from each other and there's no way around it and does not improve any metrics for us real metrics meaningful metrics so success is you know we're happier and more connected yeah i don't know sure it's possible there's a reality that's i i'm deeply optimistic i think are you worried um business-wise like how difficult it is to um to bring this thing to life to where it's i mean there's a huge number of people that use it already but to uh yeah like i said in a multi-billion dollar company is that a source of stress for you are you uh super optimistic and confident or do you i don't i'm not that much of a numbers person as you probably have seen it so it doesn't matter for me whether like whether we help 10 000 people or a million people or a billion people with that um i'd it would be great to scale up for more people but i'd say that even helping one i think with this is such a magical yeah for me it's absolute magic i never thought that and you know would be able to build this that anyone would ever um talk to it and i always thought like well for me we'll be successful if we manage to help and actually change a life for one person like then we did something interesting and you know how many people can say they did it and specifically with this very futuristic very romantic technology so that's how i view it uh i think for me it's important to to try to figure out how not how to actually be you know helpful because in the end of the day if you can build a perfect ai friend that's so understanding that knows you better than any human out there can have great conversations with you um always knows how to make you feel better why would you choose another human you know so that's the question how do you still keep building it so it's optimizing for the right thing so it's still circling you back to other humans in a way so i think that's the main um like maybe that's the main kind of sort source of anxiety and just thinking about i think about that can be a little bit stressful yeah it's a fascinating thing how to have a heart of a friend that doesn't like sometimes like friends quote unquote or like you know those people who have when they a guy in the guy universe when you have a girlfriend that uh you get the girlfriend and then the guy stops hanging out with all of his friends [Laughter] it's like obviously the relationship with the girlfriend is or whatever but like you also want it to be what she like makes it more enriching to hang out with the guy friends or whatever was there anyway that that's uh that's a that's a that's a fundamental problem in choosing the right mate and probably the the fundamental problem in creating the right ai system right what uh let me ask the sexy hot thing on the presses right now is gpt 3 got released with openai it's a latest language model they have kind of an api where you can create a lot of fun applications i think it's as people have said it's probably more hype than intelligent but there's a lot of really cool things ideas there with increasing size you can have better and better performance on language what are your thoughts about the gbt3 in connection to your work with the open domain dialogue but in general like this learning in an unsupervised way from the internet to generate one character at a time creating pretty cool text uh so we partner up before for the api launch so we started working with them when um they decided to put together this api and we tried it without fine tuning that we tried it with fine tuning on our data and we worked closely to actually optimize this model for some of our data sets it's kind of cool because i think we're kind of we're this polygon polygon for this kind of experimentation space for experimental space for for these models uh to see how they actually work with people because there are no products publicly available that do that that focus on open domain conversations so we can you know test how facebook blends are doing or how gpg3 doing uh so with gpd3 we managed to improve by a few percentage points like three or four pretty meaningful amount of percentage points our main metric which is the ratio of conversations that make people feel better and every other metric across across the field got a little boost right now i'd say one out of five responses from replica comes from gpg3 wow so our own blender mixes up like a bunch of candies from different blender you said well yeah just the model that looks at looks at top candidates from different models and picks the most the best one uh so right now one of five will come from gp3 that's really great i mean uh what's the do you have hope for like do you think there's a ceiling to this kind of approach so we've had for a very long time we've used um since the very beginning we most it was most of replica was scripted and then a little bit of this fallback part of replica was using a retrieval model um and then this retrieval model started getting better and better and better with transformers it got a lot better and we're seeing great results and then with gpd2 finally generative models that originally were not very good and were a very very fallback option for most of our conversations we wouldn't even put them in production finally we could use some generative models as well along um you know next to our retrieval models and then now we do gpt3 they're almost on par um so that's pretty exciting i think just seeing how from the very beginning of um you know from 2015 where the first model start to pop up here and there like sequence sequence uh the first papers on that from my observer standpoint first note it's not you know it doesn't really it's not really building it but it's only testing it on people basically in my product to see how all of a sudden we can use generative dialogue models in production and they're better than others and they're better than scripted content so we can't really get our scripted hard-coded content anymore to be as good as our internet model that's exciting they're much better yeah to your question whether that's the right way to go i'm again i'm in the observer seat i'm just um watching this very exciting movie um i mean so far it's been stupid to bet against deep learning so whether increasing the size size even more or the 100 trillion parameters will finally get us to the right answer whether that's the way or whether there should be there has to be some other again i'm definitely not an expert anyway i think and that's purely my instincts saying that there should be something else as well from memory uh no for sure the question is i wonder i mean yeah then the argument is for reasoning or for memory it might emerge with more parameters it might more larger but might emerge you know i would never think that to be honest like maybe in 2017 where we've been just experimenting with all you know with all the research that has been coming that was coming out then i felt like there's like we're hitting a wall that there should be something completely different but then transformer models and then just bigger models and then all of a sudden size matters at that point it felt like something dramatic needs to happen but it didn't and just the size you know gave us these results that to me are you know clear indication that we can solve this problem pretty soon did uh fine tuning help quite a bit oh yeah without it we it wasn't as good i mean there is a compelling hope that you don't have to do fine-tuning which is one of the cool things about gbt3 it seems to do well without any fine-tuning i guess for specific applications you still want to train on a certain like add a little fine-tune on like a specific use case but um it's an incredibly impressive uh thing from my standpoint and again i'm not an expert so i want to just say that yeah there will be people then yeah i have access to the api i've been i'm going to probably do a bunch of fun things with it um i already did some fun things some videos coming out uh just the hell of it i mean i could be a troll at this point with it i haven't used it for serious applications so it's really cool to see you're right you you are you're able to actually use it with real people and see how well it works that's really exciting uh let me ask you another absurd question but uh there's a feeling when you interact with replica with an ai system there's an entity there do you think that entity has to be self-aware do you think it has to have consciousness to create um a rich experience and a corollary what's what is consciousness i don't know if it does need to have any of those things but again because right now you know it doesn't have anything they can as again a bunch of you sure will assimilate well i'm not sure let's just put it this way but i think as long as you can assimilate it if you can feel like you're talking to to an um to to a robot to a machine that seems to be self-aware that seems to reason well and feels like a person and i think that's enough and again what's the goal um in order to make people people feel better we might not even need that um in the end of a day what about so that's one goal what about like ethical things about suffering you know the moment there's a display of consciousness we associate consciousness with suffering um you know there's a temptation to say well shouldn't this thing have rights shouldn't this shouldn't we not uh you know should we be careful about how we interact with a replica like should it be illegal to torture a replica right all those kinds of things is that is that uh see i personally believe that that's gonna be a thing uh like that's a serious thing to think about but i'm not sure when but by your smile i can tell that's not a that's not a current concern but do you think about that kind of stuff about like suffering and torture and ethical questions about ai systems from their perspective we're talking about long game i wouldn't torture your ai who knows what happens in five to ten years yeah they'll get you off from that person they'll get you back trying to be as nice as possible and create this ally yeah um i think there should be regulation both way in a way like i don't think it's okay to torture an ai to be honest i'm not i don't think it's okay to yell alex or turn on the lights i think there should be some or just saying kind of nasty you know like how kids learn to interact with alexa in this kind of mean way uh because they just yell at it all the time i think that's great i think there should be some feedback loops so that these systems don't train us that it's okay to do that in general uh so that if you try to do that you really get some feedback from the system that it's not okay with that um and that's the most important right now let me ask a question i think people are curious about when they look at a world-class uh leader and thinker such as yourself as uh what uh what books technical fiction philosophical had a big impact on your life and maybe from another perspective what books would you recommend others read so my choice the three books right three books my choice is um so the one book that really influenced me a lot when i was building starting out this company maybe 10 years ago uh was gb go to leicester block and um i like everything about it first of all it's just beautifully written and it's so old school and so um somewhat outdated a little bit but i think the ideas in it um about the fact that a few meaningless components can come together and create meaning that we can't even understand this emerging thing i mean complexity the whole science of complexity and uh that beauty intelligence all interesting things about this world emerge yeah and yeah the the girl theorem uh theorems and just thinking about like what even these form you know you know these formal systems something can be created that we can't quite yet understand and that from my romantic standpoint was always just that is why it's important to maybe i should try to work on on these systems and try to build an ai yes i'm not an engineer yes i don't really know how it works but i think that's something comes out of it that's you know pure poetry and i know a little bit about that um something magical comes out of it that we can't quite put a finger on that's why that book is was was really fundamental for me just for i don't even know why it was just all about this little magic that uh that happens so that's one that um probably the most important book for replica was carl rogers on becoming a person um and that's really and so i think when i think about our company it's all about there's so many there's so many little magical things that happened over the course of working on it for instance i mean the most famous chat bot that we learned about when we started working on the company was eliza which was weizenbaum you know the mit professor that built build a chatbot that would listen to you and be a therapist therapist yeah um and i got really inspired to build replica when i read carl rogers so i'll become a person and then i realized that eliza was mocking carl rogers it was kyle rogers back in the day but i thought that carl rogers ideas are they're simple and they're not you know they're very very simple but they're they're maybe the most profound thing i've ever learned about human beings and that's the fact that um before car rogers most therapy was about seeing what's wrong with people and trying to fix it or show them what's wrong with you um it was all built on the fact that most people are all people are fundamentally flawed we have this uh you know broken psyche and this is just a therapist just an instrument to shed some light on that and carl rogers was different in a way that he finally said that well um it's very important for therapy to work is to create this therapeutic relationship where you believe fundamentally and inclination to positive growth that everyone deep inside wants to grow positively and change and it's super important to create this space and this therapeutic relationship where you give unconditional positive regard deep understanding allowing someone else to be a separate person full acceptance and you also try to be as genuine as possible in it as possible in it and then in his and then for him that was his own journey of personal growth and that was back in the 60s and even that book that is you know it's coming from years ago um there's a mention that even machines can potentially do that and i always felt that you know creating this space is probably the most the biggest gift we can give to each other and that's why the book was fundamental for me personally because i felt i want to be learning how to do that in my life and maybe i can scale it with you know with dzi systems and other people can get access to that so i think carl rogers it's a pretty dry and a little bit boring book but i think they didn't let others try to read it i do i think for just for yourself for as a human not as a human it's it's it is it is just and for him that was his own path of his own personal of growing personally over years working with people like that and so it was work and himself growing helping other people grow and growing through that and that's fundamentally what i believe in with our work helping other people grow growing ourselves ourselves um trying to build a company that's all built on this principles you know having a good time allowing some people to work with to grow a little bit so these two books and then i would throw in um what we have on our in our in our office when we start a company in russia we put a neon sign in our office because we thought that's that's the recipe for success yeah if we do that we're definitely going to wake up as a multi-billion dollar company it was um the ludwig whitney constant quote the limits of my language the limits of my world what was the quote the limits of my language are the limits of my world um and i love the truck tattoos i think it's just it's just a beautiful it's a book by wickedthat yeah and i would recommend that too even although he himself didn't believe in that by the end of his lifetime and he debunked his ideas but i think i remember once an engineer came in 2012 i think with 13 a friend of ours who worked with us and then went went on to work at deepmind and he gave talk to us about ward 2 back and i saw that i'm like wow that's you know they they wanted to translate language into you know some other representation and that seems like some you know somehow all of that at some point i think will come into this one to this one place somehow it just all feels like different people think about similar ideas in different times from absolutely different perspectives and that's why i like these books in the midst of our lives just the limit of our world and we still have that new sign it's very hard to work with this red light in your face i mean on the on the russian side of things in terms of uh language the limits of language being the limit of our world you know russian is a beautiful language in some sense there's width there's humor there's pain there's so much we don't have time to talk about it much today but i'm going to paris talk to dusty ascii tulsa translators um i think it's that's fascinating art like in in art and engineering i mean it's such an interesting process but so from the replica perspective do you what do you think about uh translation how difficult it is to create a deep meaningful connection in russian versus english how you can translate the two languages you're you speak both yeah i think we're two different people in different languages um even i'm you know thinking about and there's actually some research on that i looked into that at some point because i was fascinated by the fact that what i'm talking about with what i was talking about with my russian therapist has nothing to do with with what i'm talking about with my english speaking therapist it's two different lives two different types of um you know conversations to different personas the main difference between the languages are with russian and english is that russian well english is like a piano it's a limited number of a lot of different keys but not too many and russian is like an organ or something it's just something gigantic with so many different keys and so many different opportunities to screw up and so many opportunities to do something completely tone-deaf it is just a much harder language to use it has way too many it's like way too much flexibility and way too many tones what about the the entirety of like world war ii communism stalin the pain of the people like having been deceived by the dream like all the pain of like just the entirety of it is that in the language too does that have to do oh for sure i mean we have words that don't have direct translation that to english that are very much uh um like we have ibiza which is sort of like to hold a grudge or something but it doesn't have it doesn't you don't need to have anyone to do it to you it's just your state yeah you just feel like that you feel like betrayed by other people basically but it's not that and you can't really translate that um and i think this is super important that very many words that are very specific explain the russian being and i think it can only come from from a nation that was um that suffered so much and saw institutions fall time after time after time and you know what's exciting maybe not exciting setting the wrong word but what's interesting about like my generation my mom's generation my parents generation that we saw institutions fall two or three times in our lifetime and most americans have never seen them fall yeah and they just think that they exist forever um which is really interesting but it's definitely a country that suffered so much and and it makes unfortunately when i go back and i you know hang out with my russian friends uh it makes people very cynical they stop believing in in the future i hope that's not going to be the case for so long or something's going to change again but i think seeing institutions fall is a very traumatic experience which makes it very interesting and what's on 2020 is a very interesting uh do you think uh civilization will collapse see i'm a very practical person we're speaking in english so like you said you're different person in english and russian so in russian you might answer that differently but in english i'm an optimist and i i generally believe that there is al you know even although the perspectives of grief there's always a place for for a miracle i mean it's always been like that with my life so yeah my life's been i've been incredibly lucky and things just miracles happen all the time with this company with people i know with everything around me and so i didn't mention that book but maybe in search of miraculous or in search for miraculous or whatever the english translation for that is good russian book too for everyone to read um yeah i mean if you put good vibes if you put love out there in the world miracles somehow happen yeah i believe that too or at least i believe that i don't know uh let me ask the most absurd final ridiculous question of um we talked about life a lot what do you think is the meaning of it all what's the meaning of life i mean my answer is probably going to be pretty cheesy um but i think the state of love is once you feel it in a way that we discussed before i'm not talking about falling love or um just love to yourself to uh to other people to something to the world that state of bliss that we experience sometimes whether through connection with ourselves with our people with the technology um there's something special about those those moments so um i would say if anything that's that's the only if it's not for that then for for what else are we really trying to do that i don't think there's a better way to end it than talking about love eugenia i told you um offline that there was something about me that felt like this this was this talking to you meeting you in person will be a turning point for my life i know that might be sound weird just to hear but it's it was a huge honor to talk to you i hope we talk again thank you so much for your time thank you so much thanks for listening to this conversation with eugenia cuida and thank you to our sponsors doordash dollar shave club and cash app click the sponsor links in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from carl sagan the world is so exquisite with so much love and moral depth that there's no reason to deceive ourselves with pretty stories of which there's little good evidence far better it seems to me and our vulnerability is to look death in the eye and to be grateful every day for the brief but magnificent opportunity that life provides thank you for listening and hope to see you next time |
François Chollet: Measures of Intelligence | Lex Fridman Podcast #120 | the following is a conversation with francois chalet his second time in the podcast he's both a world-class engineer and a philosopher in the realm of deep learning and artificial intelligence this time we talk a lot about his paper titled on the measure of intelligence that discusses how we might define and measure general intelligence in our computing machinery quick summary of the sponsors babel masterclass and cash app click the sponsor links in the description to get a discount and to support this podcast as a side note let me say that the serious rigorous scientific study of artificial general intelligence is a rare thing the mainstream machine learning community works on very narrow ai with very narrow benchmarks this is very good for incremental and sometimes big incremental progress on the other hand the outside the mainstream renegade you could say agi community works on approaches that verge on the philosophical and even the literary without big public benchmarks walking the line between the two worlds is a rare breed but it doesn't have to be i ran the agi series at mit as an attempt to inspire more people to walk this line deep mind and open ai for time and still on occasion walk this line francois chole does as well i hope to also it's a beautiful dream to work towards and to make real one day if you enjoy this thing subscribe on youtube review it with five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and no ads in the middle i try to make these interesting but i give you time stamps so you can skip but still please do check out the sponsors by clicking the links in the description it's the best way to support this podcast this show is sponsored by babel an app and website that gets you speaking in a new language within weeks go to babble.com and use colex to get three months 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for 180 a year you get an all-access pass to watch courses from to list some of my favorites chris hadfield on space exploration hope to have him in this podcast one day neil degrasse tyson on scientific thinking communication neil two will wright creator of simcity and sims on game design carlos santana on guitar carrie casparov von chasse daniel negrano and poker and many more chris hadfield explaining how rockets work and the experience of being launched at the space alone is worth the money by the way you can watch it on basically any device once again sign up at masterclass.com lex to get a discount and to support this podcast this show finally is presented by cash app the number one finance app in the app store when you get it use code lex podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app allows you to send and receive money digitally let me mention a surprising fact related to physical money of all the currency in the world roughly eight percent of it is actually physical money the other 92 percent of the money only exists digitally and that's only going to increase so again if you get cash out from the app store google play and use code lex podcast you get ten bucks and cash app will also donate ten dollars to first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with francois chalet what philosophers thinkers or ideas had a big impact on you growing up and today so one author that had a big impact on me when i read these books as a teenager with jean pierre who is a swiss psychologist is considered to be the father of developmental psychology and he has a large body of work about um basically how intelligence develops uh in children and so it's really old work like most of it is from the 1930s 1940s so it's not quite up to date it's actually superseded by many neural developments in developmental psychology but to me it was it was very uh very interesting very striking and actually shaped the early ways in which i started thinking about the mind and development of intelligence as a teenager his actual ideas or the way he thought about it or just the fact that you could think about the developing mind at all i guess both jean-pierre is the author that's reintroduced me to the notion that intelligence and the mind is something that you construct through throughout your life and that you the children uh construct it in stages and i thought that was a very interesting idea which is you know of course very relevant uh to ai to building artificial minds another book that i read around the same time that had a big impact on me uh and and there was actually a little bit of overlap with john pierre as well and i read it around the same time is jeff hawkins on intelligence which is a classic and he has this vision of the mind as a multi-scale hierarchy of temporal prediction modules and these ideas really resonated with me like the the notion of a modular hierarchy um of you know potentially um of compression functions or prediction functions i thought it was really really interesting and it reshaped uh the way it started thinking about how to build minds the hierarchical nature the which aspect also he's a neuroscientist so he was thinking yes actual he's basically talking about how our mind works yeah the notion that cognition is prediction was an idea that was kind of new to me at the time and that i really loved at the time and yeah and the notion that yeah there are multiple scales of processing uh in the brain the hierarchy yes this is before deep learning these ideas of hierarchies in here i've been around for a long time even before on intelligence i mean they've been around since the 1980s um and yeah that was before deep learning but of course i think these ideas really found their practical implementation in deep learning what about the memory side of things i think he's talking about knowledge representation do you think about memory a lot one way you can think of neural networks as a kind of memory you're memorizing things but it doesn't seem to be the kind of memory that's in our brains or it doesn't have the same rich complexity long-term nature that's in our brains yes the brain is more for sparse access memory so that you can actually retrieve um very precisely like bits of your experience the retrieval aspect you can like introspect you can ask yourself questions again yes you can program your own memory and language is actually the tool you used to do that i think language is a kind of operating system for the mind and use language well one of the uses of language is as a query that you run over your own memory use words as keys to retrieve specific experiences of basic concepts specific starts like language is the way you store thoughts not just in writing in the in the physical world but also in your own mind and it's also how you reach with them like imagine if you didn't have language then you would have to you would not have really have a self internally triggered uh way of retrieving past thoughts you would have to rely on external experiences for instance you you see a specific site you smell specific smell and it brings up memories but you would naturally have a way to deliberately deliberately access these memories without language well the interesting thing you mentioned is you can also program the memory you can change it probably with language yeah using language yes well let me ask you a chomsky question which is like first of all do you think language is like fundamental like uh there's turtles what's at the bottom of the turtles they don't go it can't be turtles all the way down is language at the bottom of cognition of everything is like language the fundamental aspect of like what it means to be a thinking thing no i don't think so i think language you disagree with noam chomsky yes language is a layer on top of cognition so it is fundamental to cognition in the sense that to to use a computing metaphor i see language as the operating system uh of the brain of the human mind yeah and the operating system you know is a layer on top of the computer the computer exists before the operating system but the operating system is how you make it truly useful and the operating system is most likely windows not not linux because it's uh language is messy yeah it's messy and it's uh it's um pretty difficult to uh uh inspect it introspect it how do you think about language like we use actually sort of human interpretable language but is there something like a deeper that's closer to like like logical type of statements um like yeah what is the nature of language do you think because there's something deeper than like the syntactic rules we construct is there something that doesn't require utterances or writing or so on are you asking about the possibility that there could exist uh languages for thinking that are not made of words yeah yeah i think so i think so uh the mind is layers right and language is almost like the the outermost the uppermost layer um but before we think in words i think we think in in terms of emotion in space and we think in terms of physical actions and i think a baby babies in particular probably express his thoughts in terms of um the actions uh that they've seen of that or that they can perform and in terms of the in in terms of motions of objects in their environment before they start thinking in terms of words it's amazing to think about that as the building blocks of language so like the kind of actions and ways the babies see the world as like more fundamental than the beautiful shakespearean language you construct on top of it and we we probably don't have any idea what that looks like right like what because it's important for them trying to engineer it into ai systems i think visual analogies and motion is a fundamental building block of the mind and you you actually see it reflected in language like language is full of special metaphors and when you think about things i consider myself very much as a visual thinker you you often express your thoughts um by using things like uh visualizing concepts um in in 2d space or like you solve problems by image imagining yourself navigating a concept space i don't know if you have this sort of experience you said visualizing concept space so like so i certainly think about i certainly met i certainly visualize mathematical concepts but you mean like in concept space visually you're embedding ideas into some into a three-dimensional space you can explore with your mind essentially yeah 2d you're a flatlander you're um okay no i i i do not i always have to uh before i jump from concept to concept i have to put it back down on pape and it has to be on paper i can only travel on 2d paper not inside my mind you're able to move inside your mind but even if you're writing like a paper for instance don't you have like a special representation of your paper like you you visualize where ideas lie topologically in relationship to other ideas kind of like a subway map of the ideas in your paper yeah that's true i mean there there is uh in papers i don't know about you but there feels like there's a destination um there's a there's a key idea that you want to arrive at and a lot of it is in in the fog and you're trying to kind of it's almost like um what's that called when um you do a path planning search from both directions from the start and from the end but and then you find you do like shortest path but like uh you know in game playing you do this with like a star from both sides when you see where they join yeah so you kind of do at least for me i think like first of all just exploring from the start from like uh first principles what do i know uh what can i start proving from that right and then from the destination if i you start backtracking like if if i want to show some kind of sets of ideas what would it take to show them and you kind of backtrack but yeah i don't think i'm doing all that in my mind though like i'm putting it down on paper do you use mind maps to organize your ideas yeah i like mind maps let's get into this i've been so jealous of people i haven't really tried it i've been jealous of people that seem to like they get like this fire of passion in their eyes because everything starts making sense it's like uh tom cruise in the movie was like moving stuff around some of the most brilliant people i know use mind maps i haven't tried really can you explain what the hell a mind map is i guess mind map is a way to make connected mess inside your mind to just put it on paper so that you gain more control over it it's a way to organize things on paper and as as kind of like a consequence for organizing things on paper it start being more organized inside inside your own mind what what does that look like you put like do you have an example like what what what do you what's the first thing you write on paper what's the second thing you write i mean typically uh you you draw a mind map to organize the way you think about a topic so you would start by writing down like the the key concept about that topic like you would write intelligence or something and then you would start adding uh associative connections like what do you think about when you think about intelligence what do you think are the key elements of intelligence so maybe you would have language for instance instead of motion and so you would start drawing notes with these things and then you would see what do you think about when you think about motion and so on and you would go like that like a tree it's a tree or a tree mostly there's a graph to like a tree oh it's it's more of a graph than a tree and um and it's not limited to just you know writing down words you can also uh draw things and it's not it's not supposed to be purely hierarchical right like you can um the point is that you can start once once you start writing it down you can start reorganizing it so that it makes more sense so that it's connected in a more effective way see but i'm so ocd that you just mentioned intelligence and language emotion i would start becoming paranoid that the categorization isn't perfect like that i'll become paralyzed with the mind map that like this may not be so like the even though you're just doing associative kind of connections there's an implied hierarchy that's emerging and i would start becoming paranoid that's not the proper hierarchy so you're not just one way to see mind maps is you're putting thoughts on paper it's like a stream of consciousness but then you can also start getting paranoid well if is this the right hierarchy sure like which it's a mind map it's your mind map you're free to draw anything you want you're free to draw any connection you want and you can just make a different mind my opinion is if you think the central node is not the right node yeah so i suppose there's a fear of being wrong if you want to if you want to organize your ideas by writing down what you think which i think is is very effective like how do you know what you think about something if you don't write it down right uh if you do that the thing is that it imposes a much more uh syntactic structure over your ideas which is not required with mind map so mind map is kind of like a lower level more freehand way of organizing your thoughts and once you've drawn it then you can start uh actually voicing your thoughts in terms of you know paragraphs it's a two-dimensional aspect of layout too right yeah and it's it's a kind of flower i guess you start there's usually you want to start with a central concept yes typically it ends up more like a subway map so it ends up more like a graph a topological graph without a root note yeah so like in a subway map there are some nodes that are more connected than others and there are some nodes that are more important than others right so there are destinations but it's it's not going to be purely like a tree for instance yeah it's fascinating to think that if there's something to that about our about the way our mind thinks by the way i just kind of remembered obvious thing that i have probably thousands of documents in google doc at this point that bullet point lists uh which is you can probably map a mine map to a bullet point list it's the same it's a no it's not it's a tree it's a tree yeah so i create trees but also they don't have the visual element like um i guess i'm comfortable with the structure it feels like it the narrowness the constraints feel more comforting if you have thousands of documents with your own thoughts in google docs why don't you write uh some kind of search engine like maybe a mind map um a piece of software mind mapping software where you write down a concept and then it gives you sentences or paragraphs from your thousand google docs document that match this concept the problem is it's so deeply unlike mind maps it's so deeply rooted in natural language so it's not um it's not semantically searchable i would say because the categories are very you kind of mention intelligence language and motion they're very strong semantic like it feels like the mind map forces you to be semantically clear and specific the bullet points list i have are are sparse desperate thoughts that uh poetically represent a category like motion as opposed to saying motion so unfortunately it's that's the same problem with the internet that's why the idea of semantic web is difficult to get it's uh most language on the internet is a giant mess of natural language that's hard to interpret which so do you think uh do you think there's something to mind maps as um you actually originally brought up as we were talking about kind of cognition and language do you think there's something to mind maps about how our brain actually deals like think reasons about things it's possible i think it's reasonable to assume that there is some level of topological processing in the brain that the brain is very associative in nature and i also believe that a topological space is a better medium to encode thoughts than a geometric space then so i think what's the difference in topological and geometric space well um if you're talking about topologies uh then points are either connected or not so the topology is more like a subway map and geometry is when you're interested in the distance between things and in subway maps you don't really have the concept of distance you only have the concept of whether there is a train going from station a to station b and what we do in deep learning is that we're we're actually dealing with uh geometric spaces we're dealing with concept vectors word vectors uh that have a distance between the gist expressed in terms of dot product um we are not we are not really building topological models usually i think you're absolutely right like distance is a fundamental importance in deep learning i mean it's the continuous aspect of it yes because everything is a vector and everything has to be a vector because everything has to be differentiable if your space is discrete it's no longer differentiable you cannot do deep learning in it anymore well you could but you could only do it by embedding it in a bigger continuous space so if you do topology in the in the context of deep learning you have to do it by embedding your topology in a geometry right yeah well let me uh let me zoom out for a second uh let's get into your paper on the measure of intelligence that uh did you put on 2019 yes okay yeah november november yeah remember 2018 that was a different time yeah i remember i still remember it feels like a different and different different world you could travel you can you know actually go outside and see friends yeah let me ask the most absurd question i think uh there's some non-zero probability there'll be a textbook one day like 200 years from now on artificial intelligence or it'll be called like just intelligence because humans will already be gone it'll be your picture with a quote you know one of the early biological systems would consider the nature of intelligence and they'll be like a definition of how they thought about intelligence which is one of the things you do in your paper on measure intelligence is to ask like well what is intelligence and and uh how to test for intelligence and so on so is there a spiffy quote about what is intelligence what is the definition of intelligence according to francois charley yes so do you think the the superintendent ais of the future will want to remember us do we remember humans from the past and do you think they would be you know they won't be ashamed of having a biology called origin uh no i i think it would be a niche topic it won't be that interesting but it'll be it'll be like the people that study in certain contexts like historical civilization that no longer exist the aztecs and so on that that's how it'll be seen and it'll be studying also the context on social media there will be hashtags about the atrocity committed to human beings um when when the when the robots finally got rid of them like it was a mistake it'll be seen as a as a giant mistake but ultimately in the name of progress and it created a better world because humans were uh over consuming the resources and all they were not very rational and were destructive in the end in terms of productivity and putting more love in the world and so within that context there'll be a chapter about these biological systems seems to have a very detailed vision of that feature you should write a sci-fi novel about it i said i'm working i'm working on a sci-fi novel currently yes yes self-published yeah the definition of intelligence so intelligence is the efficiency with which you acquire new skills at tasks that you did not previously know about that you did not prepare for all right so it is not intelligence is not skill itself it's not what you know it's not what you can do it's how well and how efficiently you can learn new things new things yes the idea of newness there seems to be fundamentally important yes so you would see intelligence on display for instance whenever you see a human being or you know an ai creature adapt to a new environment that it has not seen before that its creators did not anticipate when you see adaptation when you see improvisation when you see generalization that's intelligence uh in reverse if you have a system that's when you put it in a slightly new environment it cannot adapt it cannot improvise it cannot deviate from what it's hardcoded to do oh what what it has been trying to do um that is a system that is not intelligent there's actually a quote from einstein that captures this idea which is the measure of intelligence is the ability to change i i like that quote i think it captures at least part of this idea you know there might be something interesting about the difference between your definition and einsteins i mean he's just being einstein and clever but acquisition of new ability to deal with new things versus ability to just change what's the difference between those two things so just changing itself do you think there's something to that just being able to change yes being able to adapt so not not change but certainly uh changes direction being able to adapt yourself to your environment whatever the environment that's that's a big part of intelligence yes and intelligence is more precisely you know how efficiently you're able to adapt how efficiently you're able to basically master your environment how efficiently you can acquire new skills and i think there's a there's a big distinction to be drawn between intelligence which is a process and the output of that process which is skill so for instance if you have a very smart human programmer that considers the game of chess and that writes down a static program that can play chess then the intelligence is the process of developing that program but the program itself is just encoding the output artifact of that process the program itself is not intelligent and the way you tell it's not intelligent is that if you put it in a different context you ask it to play go or something it's not going to be able to perform well with human involvement because the source of intelligence the entity that is capable of that process is the human programmer so we should be able to tell the difference between the process and its output we should not confuse the output and the process it's the same as you know do not confuse a road building company and one specific road because one specific road takes you from point a to point b but a road building company can take you from you can make a path from anywhere to anywhere else yeah that's beautifully put but it's also to play devil's advocate a little bit you know um it's possible that there's something more fundamental than us humans so you kind of said the programmer creates uh the difference between the the choir of the skill and the skill itself there could be something like you could argue the universe is more intelligent like the the deep the base intelligence of um that we should be trying to measure is something that created humans we should be measuring god or what the source the universe as opposed to like there's there could be a deeper intelligence sure there's always deeper intelligence you can argue that but that does not take anything away from the fact that humans are intelligence and you can't tell that because they are capable of adaptation and and generality um and you see that in particular and the fact that uh humans are capable of handling uh situations and tasks that are quite different from anything that any of our evolutionary ancestors has ever encountered so we are capable of generalizing very much out of distribution if you consider our evolutionary history as being in a way else training data course evolutionary biologists would argue that we're not going too far out of the distribution we're like mapping the skills we've learned previously desperately trying to like jam them into like these new situations i mean there's definitely a little bit a little bit of that but it's pretty clear to me that we're able to uh you know most of the things we do any given day in our modern civilization are things that are very very different from what you know our ancestors a million years ago would have been doing in in a given day and your environment is very different so i agree that um everything we do we do it with cognitive building blocks that we acquired over the course of revolution right and that anchors um our cognition to a certain context which is the human condition very much but still our mind is capable of a pretty remarkable degree of generality far beyond anything we can create in artificial systems today like the degree in which the mind can generalize from its evolutionary history can generalize away from its evolutionary history is much greater than the degree to which a depending system today can generalize away from its training data and like the key point you're making which i think is quite beautiful is like we shouldn't measure if we talk about measurement we shouldn't measure the skill we should measure like the creation of the new skill the ability to create that new skill yes but there it's tempting like it's weird because the skill is a little bit of a small window into the into the system so whenever you have a lot of skills it's tempting to measure the skills yes i mean the skill is the uh only thing you can objectively measure but yeah so the the thing to keep in mind is that when you see skill in the human it gives you a strong signal that that human is intelligent because you knew they weren't born with that skill typically like you say this you see a very strong chess player maybe you're a very stronger player yourself i think you're and you're you're saying that because i'm russian and now now you're you're prejudiced you assume oh yeah it's just biased i'm biased yeah well you're dead by us um so if you see a very strong chess player you know they weren't born knowing how to play chess so they had to acquire that skill with their limited resources with their limited lifetime and you know they did that because they are generally intelligent and so they may as well have acquired any other skill you know they have this potential and on the other hand if you see a computer playing a chess you cannot make the same assumptions because you cannot you know just assume the computer is generally intelligent the computer may be born knowing how to play chess in the sense that it may have been programmed by a human that has understood chess for the computer and and that has just encoded um the output of that understanding in aesthetic program and that program is not intelligent so let's zoom out just for a second and say like what is the goal of the on the measure of intelligence paper like what do you hope to achieve with it so the goal of the paper is to clear up some long-standing misunderstandings about the way we've been conceptualizing intelligence in the ai community and in the way we've been evaluating progress in ai there's been a lot of progress recently in machine learning and people are you know extrapolating from that progress that we're about to solve general intelligence and if you want to be able to evaluate these statements you need to precisely define what you're talking about when you're talking about general intelligence and you need a formal way a reliable way to measure how much intelligence how much general intelligence a system processes and ideally this measure of intelligence should be actionable so it should not just describe what intelligence is it should not just be a binary indicator that tells you the system is intelligent or it isn't um it should be actionable it should have explanatory power right so you could use it as a feedback signal it would show you uh the way towards building more intelligent systems so at the first level you draw a distinction between two divergent views of intelligence of um as we just talked about intelligence is a collection of tax task specific skills and a general learning ability so what's the difference between kind of this memorization of skills and a general learning ability we've talked about a little bit but can you try to linger on this topic for a bit yeah so the first part of the paper uh is uh an assessment of the different ways uh we've been thinking about intelligence and the different ways we've been evaluating progress in ai and the history of cognitive sciences has been shaped by two views of the human mind and one view is the evolutionary psychology view in which the mind is a collection of fairly static special purpose ad-hoc mechanisms that have been hard coded by evolution over our our history as a species over a very long time and um early ai researchers people like marvin minsky for instance they clearly subscribed to this view and they saw they saw the mind as a kind of you know collection of static programs uh similar to the programs they would they would run on like mainframe computers and in fact they i think they very much understood the mind uh through the metaphor of the mainframe computer because that was the tool they they were working with right and so you had the static programs this collection of very different static programs operating over a database like memory and in this picture learning was not very important learning was considered to be just memorization and in fact learning is basically not featured in ai textbooks until the 1980s with the rise of machine learning it's kind of fun to think about that learning was the outcast like the the weird people were learning like the mainstream ai world was um i mean i don't know what the best term is but it's non-learning it was seen as like reasoning yes would not be learning based yes it was seen it was considered that the mind was a collection of programs that were primarily logical in nature and that's all you needed to do to create a mind was to write down these programs and they would operate over your knowledge which would be stored in some kind of database and as long as your database would encompass you know everything about the world and your logical rules were uh comprehensive then you would have in mind so the other view of the mind is the brain as a sort of blank slate right this is a very old idea you find it in john locke's writings this is the tabulata and this is this idea that the mind is some kind of like information sponge that starts empty it starts blank and that absorbs uh knowledge and skills from experience right so it's uh it's a sponge that reflects the complexity of the world the complexity of your life experience essentially that everything you know and everything you can do is a reflection of something you found in the outside world essentially so this is an idea that's very old uh that was not very popular for instance in the in the 1970s but that had gained a lot of vitality recently with the rise of connectionism in particular deep learning and so today deep learning is the dominant paradigm in ai and i feel like lots of ai researchers are conceptualizing the mind via a deep learning metaphor like they see the mind as a kind of randomly initialized neural network that starts blank when you're born and then that gets trained yeah exposure to training data that acquires knowledge and skills exposure to training data by the way it's a small tangent i feel like people who are thinking about intelligence are not conceptualizing it that way i actually haven't met too many people who believe that a neural network will be able to reason who seriously think that rigorously because i think it's actually interesting world view and and we'll talk about it more but it it's been impressive what the uh what neural networks have been able to accomplish and it's i to me i don't know you might disagree but it's an open question whether like like scaling size eventually might lead to incredible results to us mere humans will appear as if it's general i mean if you if you ask people who are seriously thinking about intelligence they will definitely not say that all you need to do is is like the mind is just in your network uh however it's actually you that's that's very popular i think in the deep learning community that many people are kind of uh conceptually you know intellectually lazy about it right but what i guess what i'm saying exactly right it's uh i i me i haven't met many people and i think it would be interesting uh to meet a person who is not intellectualized about this particular topic and still believes that neural networks will go all the way i think january is probably closest to that there are definitely people who argue that uh current deep learning techniques are already the way to general artificial intelligence and that all you need to do is to scale it up to all the available training data and that's if you look at the the waves that open ai's gpt stream model has made you see echoes of this idea so on that topic gpt-3 similar to gpt-2 actually have captivated some part of the imagination of the public there's just a bunch of hype of different kind that's i would say it's emergent it's not artificially manufactured it's just like people just get excited for some strange reason in in the case of gpt3 which is funny that there's i believe a couple months delay from release to hype maybe i'm not historically correct on that but it feels like there was a little bit of a lack of hype and then there's a phase shift into into hype but nevertheless there's a bunch of cool applications that seem to captivate the imagination of the public about what this language model that's trained in unsupervised way without any fine tuning is able to achieve so what do you make of that what are your thoughts about gbt3 yeah so i think what's interesting about gpg3 is the idea that it may be able to learn new tasks in after just being shown a few examples so i think if it's actually capable of doing that that's novel and that's very interesting and that's something we should investigate that said i must say i'm not entirely convinced that we have shown it's it's capable of doing that it's very likely given the amount of data that the model is trained on that what it's actually doing is pattern matching uh a new task you give it with the task that it's been exposed to in its training data it's just recognizing the task instead of just developing a model of the task right but there's a side to interrupt there's there's a parallels to what you said before which is it's possible to see gpt3 as like the prompts that's given as a kind of sql query into this thing that it's learned similar to what you said before which is language is used to query the memory yes so is it possible that neural network is a giant memorization thing but then if it gets sufficiently giant it'll memorize sufficiently large amounts of thing in the world where it becomes more intelligence becomes a querying machine i think it's possible that uh a significant chunk of intelligence is this giant associative memory uh i definitely don't believe that intelligence is just a giant issue of memory but it may well be a big component so do you think gpt 3 4 5 gpt 10 will eventually like what do you think where's the ceiling do you think you'll be able to reason um no that's a bad question uh like what is the ceiling is the better question how well is it going to scale how good is gptn going to be yeah so i believe gptn is going to chiptn is going to improve on the strength of gpt2 and 3 which is it will be able to generate you know ever more plausible text in context just monitoring the process performance um yes if you train if you're training bigger more on more data then your text will be increasingly more context aware and increasingly more plausible in the same way that gpd3 it is much better at generating clausable text compared to gpd2 but that said i don't think just getting up uh the model to more transformer layers and more train data is going to address the flaws lgbt3 which is that it can generate plausible text but that text is not constrained by anything else other than plausibility so in particular it's not constrained by factualness uh or even consistency which is why it's very easy to get gpt3 to generate statements that are factually untrue uh or to general statements that are even self-contradictory right uh because it's uh it's it's only goal is plausibility and it has no other constraints it's not constrained to be self-consistent for instance right and so for this reason one thing that i thought was very interesting with gpd3 is that you can present mind the answer it will give you by asking the question in specific way because it's very responsive to the way you ask the question since it has no understanding of the content of the question right and if you if you ask the same question in two different ways that are basically adversarially engineered to produce certain answers you will get two different answers to contractor answers it's very susceptible to adversarial attacks essentially potentially yes so in in general the problem with these models is generative models is that they are very good at generating plausible text but that's just that's just not enough right um you need uh i think one one avenue that would be very interesting to make progress is to make it possible to write programs over the latent space that these models operate on that you would rely on these self-supervised models to generate a sort of flag pool of knowledge and concepts and common sense and then you will be able to write explicit uh reasoning programs over it uh because the current problem with gpt stream is that you it's it can be quite difficult to get it to do what you want to do if you want to turn gpd3 into products you need to put constraints on it you need to um force it to obey certain rules so you need a way to program it explicitly yeah so if you look at its ability to do program synthesis it generates like you said something that's plausible yeah so if you if you try to make it generate programs it will perform well for any program that it has seen it in its training data but because uh program space is not interpretive right um it's not going to be able to generalize to problems it hasn't seen before now that's currently do you think sort of an absurd but i think useful um i guess intuition builder is uh you know the gpt-3 has 175 billion parameters a human brain has a hundred has about a thousand times that or or more in terms of number of synapses do you think obviously very different kinds of things but there is some degree of similarity do you think what do you think gpt will look like when it has a hundred trillion parameters you think our conversation might be so in nature different like because you've criticized gbt3 very effectively now do you think no i don't think so so the the to begin with the bottleneck with scaling upgrades gbt models uh alternative pre-trained transformer models is not going to be the size of the model or how long it takes to train it the bottleneck is going to be the trained data because openui is already training gpt3 on a crore of basically the entire web right and that's a lot of data so you could imagine training on more data than that like google could try on more data than that but it would still be only incrementally more data and i i don't recall exactly how much more data gpd3 was trained on compared to gpt2 but it's probably at least like 100 or maybe even a thousand x don't have the exact number uh you're not going to be able to train the model on 100 more data than with what you already with what you're already doing so that's that's brilliant so it's not you know it's easier to think of compute as a bottleneck and then arguing that we can remove that bottleneck but we can remove the compute bottleneck i don't think it's a big problem if you look at the at the base at which we've uh improved the efficiency of deep learning models in the past a few years i'm not worried about uh trying time bottlenecks or model size bottlenecks the the bottleneck in the case of these generative transformer models is absolutely the trained data what about the quality of the data so so yeah so the quality of the data is an interesting point the thing is if you're going to want to use these models in real products um then you you want to feed them data that's as high quality as factual i would say as unbiased as possible but you know there's there's not really such a thing as unbiased data in the first place but you probably don't want to to train it uh on reddit for instance it sounds sounds like a bad plan so from my personal experience working with a large scale deep learning models so at some point i was working on a model at google that's trained on extra 150 million labeled images it's image classification model that's a lot of images that's like probably most publicly available images on the web at the time and it was a very noisy data set because the labels were not originally annotated by hand by humans they were automatically derived from like tags on social media or just keywords in in the same page as the image was fun and so on so it was very noisy and it turned out that you could uh easily get a better model uh not just by training like if you train on more of the noisy data you get an incrementally better model but you you you very quickly hit diminishing returns on the other hand if you try on smaller data set with higher quality annotations quality that are annotations that are actually made by humans you get a better model and it also takes you know less time to train it uh yeah that's fascinating it's the self-supervised learnings there's a way to get better doing the automated labeling yeah so you can enrich or refine your labels in an automated way that's correct do you have a hope for um i don't know if you're familiar with the idea of a semantic web is this a semantic web just for people who are not familiar and is uh is the idea of being able to convert the internet or be able to attach like semantic meaning to the words on the internet this the sentences the paragraphs to be able to contr convert information on the internet or some fraction of the internet into something that's interpretable by machines that was kind of a dream for um i think the the semantic white papers in the 90s it's kind of the dream that you know the internet is full of rich exciting information even just looking at wikipedia we should be able to use that as data for machines and so information is not it's not really in a format that's available to machines so no i don't think the semantic web will ever work simply because it would be a lot of work right to make to provide that information in structured form and there is not really any incentive for anyone to provide that work uh so i think the the way forward to make the knowledge on the web available to machines is actually something closer to unsupervised deep learning yeah the gpg 3 is actually a bigger step in the direction of making the knowledge of the web available to machines than the semantic web was yeah perhaps in a human-centric sense it it feels like gpt-3 hasn't learned anything that could be used to reason but that might be just the early days yeah i think that's correct i think the forms of reasoning that you that you see it perform are basically just reproducing patterns that it has seen in string data so of course if you're trained on uh the entire web then you can produce an illusion of reasoning in many different situations but it will break down if it's presented with a novel uh situation that's the opening question between the illusion of reasoning and actual reasoning yes the power to adapt to something that is genuinely new because the thing is even imagine you had uh you could train on every bit of data ever generated in history of humanity uh it remains so that model would be capable of of anticipating uh many different possible situations but it remains that the future is going to be something different like for instance if you train a gpt stream model on on data from the year 2002 for instance and then use it today it's going to be missing many things it's going to be missing many common sense facts about the world it's even going to be missing vocabulary and so on yeah it's interesting that uh gbt3 even doesn't have i think any information about the coronavirus yes which is why you know uh a system that's uh you you tell that the system is intelligent when it's capable to adapt so intelligence is gonna require uh some amount of continuous learning but it's also gonna require some amount of improvisation like it's not enough to assume that what you're going to be asked to do is something that you've seen before or something that is a simple interpolation of things you've seen before yeah in fact that model breaks down for uh even even very tasks that look relatively simple from a distance like l5 self-driving for instance google had a paper couple of years back showing that something like 30 million different road situations were actually completely insufficient to train a driving model it wasn't even l2 right and that's a lot of data that's a lot more data than the the 20 or 30 hours of driving that a human needs to learn to drive given the knowledge they've already accumulated well let me ask you on that topic elon musk tesla autopilot one of the only companies i believe is really pushing for a learning based approach are you you're skeptical that that kind of network can achieve level four l4 is probably achievable l5 is probably not what's the distinction there this l5 is completely you can just fall asleep yeah alpha is basically human level well it will drive you have to be careful saying human level because like that's yeah most of the drivers yeah that's the clearest example of like you know cars will most likely be much safer than humans in situ in many situations where humans fail it's the vice versa so i'll tell you you know the thing is the the amounts of training data you would need to anticipate for pretty much every possible situation you'll encounter in the real world uh is such that it's not entirely unrealistic to think that at some point in the future we'll develop a system that's running on enough data especially uh provided that we can uh simulate a lot of that data we don't necessarily need actual uh actual cars on the road for everything but it's a massive effort and it turns out you can create a system that's much more adaptative that can generalize much better if you just add explicit models of the surroundings of the car and if you use deep learning for what it's good at which is to provide perceptive information so in general deep learning is is a way to encode perception and a way to encode intuition but it is not a good medium for any sort of explicit reasoning and uh in ai systems today uh strong generalization tends to come from um explicit models tend to come from abstractions in the human mind that are encoded in program form by a human engineer right yeah these are the abstractions you can actually generalize not the sort of weak abstraction that is learned by a neural network yeah and the question is how much how much reasoning how much strong abstractions are required to solve particular tasks like driving that's that's the question or human life existence how much how much strong obs abstractions does existence require but more specifically on driving that's that seems to be that seems to be a coupled question about intelligence is like uh how much intelligence like how do you build an intelligent system and uh the coupled problem how hard is this problem how much intelligence does this problem actually require so we're um we get to cheat right because we get to look at the problem like it's not like you get to close our eyes and completely new to driving we get to do what we do as human beings which is uh for the majority of our life before we ever learn quote unquote to drive we get to watch other cars and other people drive we get to be in cars we get to watch we get to get to see movies about cars we get to you know get to observe all this stuff and that's similar to what neural networks are doing it's getting a lot of data and the the the question is yeah how much is uh how many leaps of reasoning genius is required to be able to actually effectively drive i think it's an example of driving i mean sure you've seen a lot of cars in your life before you learn to drive but let's say you've learned to drive in silicon valley and now you rent a car in tokyo well now everyone is driving on the other side of the road and the signs are different and the roads are more narrow and so on so it's a very very different environment uh a smart human even an average human should be able to just zero shot it to just be operational in this in this very different environment yeah right away despite having add new contacts with the novel complexity that is contained in this environment right and that is another complexity is not just interpolation over the situations that you've encountered previously like learning to drive in the u.s right i would say the reason i ask this one of the most interesting tests of intelligence we have today actively which is driving in terms of having an impact on the world like when do you think we'll pass that test of intelligence so i i don't think driving is that much of a test institutions because again there is no task for which skid at that task demonstrates intelligence unless it's a kind of meta task that involves acquiring new skills so i don't think i think you can actually solve driving without having any any real amount of intelligence for instance if you really did have infinite trained data um you could just literally train an end-to-end deep learning model that's driving provided infinite training data the only problem with the whole idea is um collecting a data sets that's sufficiently comprehensive that covers the very long tail of possible situations you might encounter and it's really just a scale problem so i think the there's nothing fundamentally wrong uh uh with this plan with this idea it's just that um it strikes me as a fairly inefficient thing to do because you run into this uh this uh scanning issue with diminishing returns whereas if instead you took a more manual engineering approach where you use deep learning modules in combination with um engineering an explicit model of the surrounding of the cars and you and you bridge the two in a clever way your model will actually start generalizing much earlier and more effectively than the end-to-end depleting model so why would you not go with the more manually engineering oriented approach like even if you created that system either the end-to-end deep learning model system that's infinite data or the slightly more human system i i don't think achieving alpha would demonstrate uh general intelligence or intelligence of any generality at all again the only possible test of generality in ai would be a test that looks at skill acquisition over unknown tasks but for instance you could take your l5 driver and ask it to to learn to to pilot a a commercial airplane for instance and then you would look at how much human involvement is required and how much training data is required uh for the system to learn to pirate an airplane and that that gives you a measure of how intelligent that system is yeah well i mean that's a big leap i get you but i'm more interested as a problem i would see to me driving is a black box that can generate novel situations at some rate that what people call edge cases like so it does have newness that keeps being like we're confronted let's say once a month it is a very long time yes long term that doesn't mean you cannot solve it uh just by by training a statistical model a lot of data huge amount of data it's it's really a matter of scale but i guess what i'm saying is if you have a vehicle that achieves level five it is going to be able to deal with new situations or i mean the data is so large that the rate of new situations is very low yes that's not intelligent so if we go back to your kind of definition of intelligence it's the efficiency with which you can adapt to new situations to truly new situations not situations you've seen before right not situations that could be anticipated by your creators by the creators of the system but three new situations the efficiency with which you acquire new skills if you require if in order to pick up a new skill you require a very extensive training data sets of most possible situations that can that can occur in the practice of that skill then the system is not intelligent it is mostly just a lookup table yeah well likewise if uh in order to acquire a skill you need a human engineer to write down a bunch of rules that cover most or every possible situation likewise the system is is not intelligent the system is merely the output artifact of a process that that depends that happens in the minds of the engineers that are creating it right it is including uh an abstraction that's produced by the human mind and intelligence that would actually be the process of producing of autonomously producing this abstraction yeah not like if you take an abstraction you encode it on a piece of paper or in a computer program the abstraction itself is not intelligent what's intelligent is the the agent that's capable of producing these abstractions right yeah it feels like there's a little bit of a gray area like because you're basically saying that deep learning forms abstractions too but those abstractions do not seem to be effective for generalizing far outside of the things that's already seen but generalize a little bit yeah absolutely no depending does generalize a little bit like generalization is not it's not a binary it's mark a spectrum yeah and there's a certain point it's a gray area but there's a certain point where there's an impressive degree of generalization that happens no like i guess exactly what you were saying is uh intelligence is um how efficiently you're able to generalize far outside of the distribution of things you've seen already yes so it's both like the the distance of how far you can like how new how radically new something is and how efficiently yes absolutely so you you can think of uh intelligence as a measure of an information conversion ratio like imagine uh a space of possible situations and you've covered some of them so you have some amount of information about your space of possible situations that's provided by the situations you already know and that's on the other hand also provided by the prior knowledge that the system brings to the table the prior knowledge that's embedded in the system so the system starts with some information right about the problem but the task and it's about going from that information to a program what you would call a skill program a behavioral program that can cover a large area of possible situation space and essentially the ratio between that area and the amount of information you start with is intelligence so a very smart agent uh can make efficient uses of very little information about a new problem and very little prior knowledge as well to cover a very large area of potential situations in that problem without knowing what these future new situations are going to be so one of the other big things you talk about in in the paper we've talked about a little bit already but let's talk about it some more is uh actual tests of intelligence so if we look at like human and machine intelligence do you think tests of intelligence should be different for humans and machines or how we think about testing of intelligence are these fundamentally the same kind of intelligences that we're after and therefore the test should be similar so if your goal is to create ais that are more human-like then it will be super variable obviously to have a test that's that's universal at a price to both uh ais uh and humans so that you can you could establish a comparison uh between the two that you could tell exactly how uh intelligent in terms of human intelligence a given system is so that said the constraints that apply to artificial intelligence and to human intelligence are very different and your tests should account for this difference because if you look at artificial systems it's always possible for an experimenter to buy arbitrary levels of skill at arbitrary tasks either by injecting a hard-coded prior knowledge into the system via rules and so on that come from the human mind from the minds of the programmers and also buying uh higher levels of skill just by training on more data for instance you could generate an infinity of different goal games and you could train a good playing system that way but you could not directly compare it to human goal playing skills because a human that plays go had to develop that skill in a very constrained environment they had a limited amount of time their limited amount of energy and of course this started from a different set of priors to solids from uh um you know innate uh human priors um so i think if you want to compare the intelligence of two systems like the intentions of an ai and the intelligence of a human you have to um control for priors you have to start from the the same set of knowledge priors about the task and you have to control for for experience and that is to say for training data so prior what's priors so prior is whatever information you have about a given task before you start learning about this task and how's the difference from experience well experience is acquired right so for instance if you're if you're trying to play goal your experience with goal is all the goal games you've played or you've seen or you've simulated in your mind let's say and uh your priors are things like well go go is a game on on a 2d grid and we have lots of hard-coded priors about the organization of 2d space and the rules of how the the dynamics of the physics of this game in this 2d space yes and the idea that you have what winning is yes exactly so like and all other board games can also share some similarities with school and if you've played these board games then uh with respect to the game of go that would be part of your priors about the game well it's interesting to think about the game of goes how many priors are actually brought to the table when you look at uh self-play reinforcement learning based mechanisms that do learning it seems like the number of prizes pretty low yes but you're saying you should be exp there's a 2d special priority in the covenant right but you should be clear at making those priors explicit yes uh so in particular i think if your if your goal is to measure a human-like form of intelligence then you should clearly establish that you want the ai your testing to start from the same set of priors that humans start with right so i mean to me personally but i think to a lot of people the human side of things is very interesting so testing intelligence for humans what um what do you think is a good test of human intelligence well that's the question that psychometrics is is interested in what is there's an entire subfield of psychology that deals with this question so what's psychometrics the psychometrics is the sub-field of psychology that that tries to measure quantify aspects of the human mind so in particular community abilities intelligence and personality threats as well so uh like what are might be a weird question but what are like the first principles of the of psychometrics that operates on the you know what what are the priors it brings to the table so it's a filled with a with a fairly long history um it's so you know psychology sometimes gets a bad reputation for not having very reproducible uh results and some psychometrics as actually some fairly solidly or producible results so the ideal goals of the field is you know tests should be be reliable which is a an ocean type reproducibility it should be valid uh meaning that it should actually measure what you say but you say it measures um so for instance if you're if you're saying that you're measuring intelligence then your test results should be created with things that you expect to be correlated with intelligence like success in school or success in the workplace and so on should be standardized meaning that you can administer your tests to many different people in the same conditions and it should be free from bias meaning that for instance uh if you're if if your test involves uh the english language then you have to be aware that this creates a bias against people who have english as their second language or people who can't speak english at all so of course these these principles for creating psychometric tests are very much nighty old i don't think every psychometric test is is really either reliable valid or offer from bias but at least the field is aware of these weaknesses and is trying to address them so it's kind of interesting um ultimately you're only able to measure like you said previously the skill but you're trying to do a bunch of measures of different skills that correlate as you mentioned strongly with some general concept of cognitive ability yes yes so what's the g factor so right there are many different kinds of tests tests of intelligence and uh each of them is interested in in uh different aspects of intelligence you know some of them will deal with language some of them we deal with a special vision maybe mental rotations numbers and so on when you run these very different tests at scale what you start seeing is that there are clusters of correlations among test results so for instance if you look at uh homework at school um you will see that people who do well at math are also likely statistically to do well in physics and what's more uh there there also people do well at math and physics are also statistically likely to do well in things that sound completely unrelated like writing in english essay for instance and so when you see clusters of correlations uh in in statical statistical terms you would explain them with a latent variable and the latent variable that would for instance explain uh the relationship between being good at math and being good at physics would be cognitive ability right and the g factor is the the latent variable that explains uh the fact that every test of intelligence that you can come up with results on that on on this test end up being correlated so there is some a single uh a unique variable uh that that explains this correlations that's the g factor so it's a statistical construct it's not really something you can directly measure for instance in a person um but it's there but it's there it's there it's the art scale and that's also one thing i want to mention about psychometrics like you know when you talk about measuring intelligence in in humans for instance some people get a little bit worried they will say you know that sounds dangerous maybe that's not potentially discriminatory and so on and they're not wrong and the thing is so personally i'm not interested in psychometrics as a way to characterize one individual person like if if i get your psychometric personality assessment or your iq i don't think that actually tells me much about you as a person i think psychometrics is most useful as a statistical tool so it's most useful at scale it's most useful when you start getting test results for a large number of people and you start cross-correlating these test results because that gives you information about the structure of the human mind particularly about the structure of human cognitive abilities so at scale psychometrics paints a certain picture of the human mind and that's interesting and that's what's relevant to ai the structure of human currency abilities yeah it gives you an insight into it i mean to me i remember when i learned about g factor it seemed it it seemed like it would be impossible for it even it to be real even as a statistical variable like it felt uh kind of like astrology like it's like wishful thinking among psychologists but uh the more i learned i realized that there's some i mean i'm not sure what to make about human beings the fact that the jig factor is a thing that there's a commonality across all of human species is there destiny to be a strong correlation between cognitive abilities that's kind of fascinating yeah actually so human connectivities have uh a structure like the the most mainstream theory of the structure of cancer abilities it's called a chc theory it's a cattle horn carol it's name of the industry psychologist who contributed key pieces of it and it describes uh cognitive abilities as a hierarchy with three levels and at the top you have the g-factor then you have broad cognitive abilities for instance fluid intelligence right that that encompass um a broad set of possible kinds of tasks that are all related and then you have narrow cognitivity is at the last level which is uh closer to task specific skill and there are actually different theories of the structure of clinical abilities that just emerge from different statistical analysis of iq test results but they all describe a hierarchy with a kind of g factor at the top and you're right that the g factor is it's not quite real in the sense that it's not something you can observe and measure like your height for instance but it's really in the sense that you you see it in in a statistical analysis of the data right one thing i want to mention is that the fact that there is a g-factor does not really mean that human intelligence is a general in a strong sense does not mean human intentions can can be applied to any problem at all and that someone who has a high iq is going to be able to solve any problem at all that's not quite what it means i think um one one popular analogy to understand it is the sports analogy if you consider the concept of physical fitness it's a concept that's very similar to intelligence because it's a useful concept it's something you can intuitively understand some people are fit uh maybe like you some people are not as fit maybe like me um but none of us can fly absolutely it's so constrained even if you're very fit that doesn't mean you can do uh anything at all in any environment you you obviously cannot fly you cannot uh survive at the bottom of the ocean and so on and if you were a scientist say you want you wanted to precisely define and measure physical fitness in humans then you would come up with a battery uh of tests uh like you would you know have running android meter uh playing soccer playing table tennis swimming and so on and uh if you run these tests over many different people you will start seeing correlations and test results for instance people who are good at soccer are so good at sprinting right and you will explain these correlations with physical abilities that are strictly analogous to cognitive abilities right and then you would start also observing correlations between biological uh characteristics like maybe lung volume is correlated with being a a fast runner for instance uh in the same way that there are neurophysical uh correlates of cognitive abilities right and at the top of the hierarchy of physical abilities that you would be able to observe you would have a g-factor a physical g-factor which would map to physical fitness right and as you just said that doesn't mean that people with a with high physical fitness can fly doesn't mean uh human morphology and human physiology is universal it's actually super specialized we can only do the things and that we were evolved to do right like we are not appropriate to to to you you could not exist on venus or mars or in the void of space but on the ocean so that said one thing that's really striking and remarkable is that our morphology generalizes far beyond the environments that we evolved for like in a way you could say we evolved to run after prey in the seminar right that's very much where our human morphology comes from and that said we can we can do a lot of things that are that are completely unrelated to that we can climb mountains we can we can swim across lakes uh we can play a table tennis i mean table tennis is very different from what we were evolved to do right so our morphology our bodies or our sense of motor affordances are of a degree of generality that is absolutely remarkable right and i think cognition is very similar to that our cognitive abilities have a degree of generality that goes far beyond what the mind was initially supposed to do which is why we can you know play music and write novels and and go to mass and do all kinds of crazy things but it's not universal in the same way that human morphology and our body is not appropriate for actually most of the universe by volume in the same way you could say that the human mind is naturally appropriate for most of problem space potential problem space uh by volume so we have very strong cognitive biases actually that mean that there are certain types of problems that we handle very well and certain certain types of problem that we are completely adapted for so that's really how we interpret the g-factor it's not a sign of strong generality it's it's really just a broader the broadest cognitive ability but our abilities whether we are talking about sensory motor abilities or cognitive abilities they still they remain very specialized in the human condition right within the constraints of the human cognition they're general yes absolutely so but the constraints as you're saying are very limited what i think what's yeah limiting so we we evolved our cognition and our body evolved in in very specific environments because our environment was so viable fast changing and so unpredictable part of the constraints that that drove our evolution is generality itself so we were in a way evolved to to be able to improvise in all kinds of physical or cognitive environments right yeah um and for this reason it turns out that uh the the minds and bodies that we ended up with uh can be applied to much much broader scope than what they were evolved for right and that's truly remarkable and that goes that's the degree of generalization that is far beyond anything you can see in artificial systems today right um that's it it does not mean that that uh human intelligence is anywhere universal yes yeah it's not general you know it's a kind of exciting topic for people even you know outside of artificial intelligence iq tests there i think it's mensa whatever there's different degrees of difficulty for questions we talked about this offline a little bit too about sort of difficult questions you know what makes a question on an iq test more difficult or less difficult do you think so the the thing to keep in mind is that there's no such thing as a question that's intrinsically difficult it has to be difficult to respect to the things you already know and the things you can already do right so in in terms of an iq test question typically you would have it will be structured for instance as a set of demonstration input and output pairs right and then you would be given a test input a prompt and you you you would need to recognize or produce the corresponding output and in that narrow context you could say a difficult question is a question where um the input prompt is very surprising and unexpected given the the training examples just even the nature of the patterns that you're observing in the input problem for instance let's say you have a rotation problem you must rotate the shape by 90 degrees if i give you two examples and then i'll give you one one prompt which is actually one of the two training examples then there is zero generalization difficulty for the task it's actually triggered task you just recognize that it's one one of the training examples and you produce the same answer now if it's uh if it's a more complex shape there is you know a little bit more generalization but it remains that you are still doing the same thing at this time as you were being demonstrated at training time a difficult task starts to require some amount of uh test time adaptation some amount of improvisation right so uh consider i don't know you're teaching a class on like quantum physics or something um if uh if you wanted to kind of test the understanding that students have of the material you would come up with an exam that's very different from anything they've seen like on the internet when they were cramming uh on the other hand if you wanted to make it easy you would just give them something that's very similar to the the mock exams that that that they've taken something that's just a simple interpolation of questions that they've they've already seen and so that would be an easy exam it's very similar to what you've been trained on and a difficult exam is one that really probes your understanding because it forces you to improvise it forces you to do things uh that are different from what you were exposed to before so that said it doesn't mean that the exam that requires improvisation is intrinsically hard right because maybe you're you're a quantum physics expert so when you take the exam this is actually stuff that despite being you new to the students it's not new to you right so it can only be difficult with respect to what the test taker already knows and with respect to the information that the test taker has about the task so that's what i mean by controlling for priors what you the information you bring to the table and the exp and experience which is the training data so in in the case of the the quantum physics exam that would be uh all the the the course material itself and all the mock exams that students might have taken online yeah it's interesting because um i've also i i sent you an email and i asked you like i've been this just this curious question of um you know what's a really hard iq test question and i've been talking to also people who have designed iq tests there's a few folks on the internet it's like a thing people are really curious about it first of all most of the iq tests they designed they like religiously protect against the correct answers like you can't find the correct answers anywhere in fact the question is ruined once you know even like the approach you're supposed to take so they're very the approach is implicit in in the training examples so here it is the training examples it's over well which is why in arc for instance there is a test set that is private and no one has seen it no for really tough iq questions it's not obvious it's not because the ambiguity like it's uh and you have to look to them but like some number sequences and so on it's not completely clear so like you can get a sense but there's like some you know when you look at a number sequence i don't know uh like your fibonacci number sequence if you look at the first few numbers that sequence could be completed in a lot of different ways and you know some are if you think deeply or more correct than others like there's a kind of intuitive simplicity and elegance to the correct solution yes i am personally not a fan of ambiguity in in test questions actually but i think you can have difficulty uh without requiring ambiguity simply by making the test uh require a lot of extrapolation over the training examples but the beautiful question is difficult but gives away everything when you give the training example basically yes meaning that so the the tests i'm interested in in creating are not necessarily difficult uh for humans because uh human intelligence is the benchmark uh they're supposed to be difficult uh for machines in ways that are easy for humans like i think an ideal uh test of human and machine intelligence is a test that is uh actionable uh that highlights uh the need for progress and that highlights the direction in which you should be making progress i i think we'll talk about the arc challenge and the test you've constructed you have these elegant examples i think that highlight like this is really easy for us humans but it's really hard for machines but on the you know the designing an iq test for iqs of like a higher than 160 and so on you have to say you have to take that and put on steroids right you have to think like what is hard for humans and that's a fascinating exercise in in itself i think and it was an interesting question of what it takes to create a really hard question for humans because um you again have to do the same process as you mentioned which is uh you know something basically where the experience that you have likely to have encountered throughout your whole life even if you've prepared for iq tests which is a big challenge that this will still be novel for you yeah i mean novelty is a requirement you should not be able to practice for the questions that you're gonna be tested on that's important because otherwise what you're doing is not exhibiting intelligence what you're doing is just retrieving uh what you've been exposed before it's it's the same thing as deep learning model if you train a deep learning model on uh all the possible answers then it will ace your test in the same way that uh um you know uh as a stupid student uh can still ace the test if they cram for it they memorize you know 100 different possible mock exams and then they hope that the actual exam will be a very simple interpolation of the mock exams and that student could just be a deep learning model at that point but you can actually do that without any understanding of the material and in fact many students pass the exams in exactly this way and if you want to avoid that you need an exam that's unlike anything they've seen that really probes their understanding so how do we design an iq test for machines and intelligent tests for machines all right so in the paper i outline a number of requirements that you expect of such a test and in particular we should start by acknowledging the priors that we expect to be required in order to perform the test so we should be explicit about the priors right uh and if the goal is to compare machine intelligence and human intelligence then we should assume uh human cognitive bias right and secondly we should make sure that we are testing for skilled acquisition ability uh skill acquisition efficiency in particular and not for skill itself meaning that every task featured in your test should be novel and should not be something that you can anticipate so for instance it should not be possible to brute force the space of possible questions right to pre-generate every possible question and the answer so it should be tasks that cannot be anticipated not just by the system itself but by the creators of the system right yeah you know what's fascinating i mean one of my favorite aspects of the paper and the work you do with the arc challenge is the the process of making priors explicit just even that act alone is a really powerful one of like what are it's a it's a really powerful question ask of us humans what are the priors that we bring to the table so the the next step is like once you have those priors how do you use them to solve a novel task but like just even making the prize explicit is a really difficult and really powerful step and that's like visually beautiful and conceptually philosophically beautiful part of the work you did with uh and i guess continue to do uh probably with the with the paper and the arc challenge can you talk about some of the priors that we're talking about here yes so a researcher has done a lot of work on what exactly uh um are the knowledge priors that that are innate to humans is elizabeth spelkie from harvard so she developed the core knowledge uh theory which uh outlines four different uh core knowledge systems uh so systems of knowledge that we are basically either born with or that we are hardwired to acquire very early on in our development and there's no uh there's no strong um distinction between the two like if you are um primed to acquire as a certain type of knowledge uh in just a few weeks you might as well just be born with it it's just it's just part of who you are and so there are there are four different core knowledge systems like the first one is the notion of objectness and a basic physics like you recognize that um something that moves uh currently for instance is an object so we intuitively naturally innately divide the world into objects based on this notion of coherence physical currents and in terms of elementary physics there's the the fact that uh you know objects can bump against each other and the fact that they can occlude each other so these are things that we are essentially born with or at least that we are going to be acquiring extremely early because really hard wire to acquire them so a bunch of points pixels that move together on objects are partly the same object yes i mean i mean that like i don't i don't smoke weed but if i did that's something i could sit like all night and just like think about i remember right in your paper just object-ness i wasn't self-aware i guess of how that particular prior that that's such a fascinating prior that like and that's that's the most basic one but yes just identity just yeah object yes it's it's very basic i suppose but it's so fundamental is this phenomenal team and cognition yeah and uh the second prior that's also fundamental is agent-ness which is not a real world a real world but so agentness the fact that some of these objects uh that you that you segment your environment into some of these objects are agents so what's an agent it's uh basically it's an object that has goals um so that has what that has goals this this capable of person goals so for instance if you see two dots uh moving in in a roughly synchronized fashion you will intuitively infer that one of the dots is pursuing the other so that one of the dots is uh and and one of the dots is an agent and its goal is to avoid the other dot and one of the dots the other dot is also an asian and its goal is to catch the first start pelkey has shown that babies you know as young as three months identify uh agentness and goal directedness in their environment another prior is basic you know geometry and topology like the notion of distance the ability to navigate in your environment and so on this is something that is fundamentally hardwired into our brain it's in fact backed by very specific neural mechanisms like for instance grid cells and plate cells so it's it's something that's literally hard coded at the at the new level uh you know you know hypocampus and the last prior would be the notion of numbers like numbers are not actually cultural constructs we are intuitively innately able to do some basic counting and to compare quantities uh so it doesn't mean we can do arbitrary arithmetic uh uh counting the actual accounting scanning like counting one two three ish then maybe more than three uh you can also compare quantities if i give you uh uh three dots and five dots you can tell the the the side with five dots there's more dots uh so this is actually an innate uh prior um so that said the list may not be exhaustive uh so spelke is still you know pursuing the potential existence of new knowledge systems for instance uh knowledge systems that would deal with social uh relationships yeah yeah i mean which is which is much much less relevant uh uh to something like arc or iq testing right so there could be stuff that's uh like like you said rotation symmetry is really interesting it's very likely that there is uh speaking about rotation that there is uh in the brain a hard-coded system that is capable of performing rotations uh one one famous experiment uh that people did in the uh i don't remember who it was exactly but in the in the 70s was that people found that if you asked people if you give them uh two different shapes and one of the shapes is a rotated version of the first shape and you ask them is is that shape a related version of first step or not what you see is that the time it takes people to answer is linearly proportional right to the angle of rotation so it's almost like you have in somewhere in your brain like a turntable um with a fixed speed and if you want to know if two two objects uh uh are rotated version of each other you put the object on the turntable you let it move around a little bit and then you and then you stop when you have a match and and that that's really interesting so what's the arc challenge so in in the paper outline you know all these principles that a good test of machine intelligence and humanitarian should follow and the arc challenge is one attempt to embody as many of these principles as possible so i don't think it's it's anywhere near a perfect attempt right it does not actually follow every principle but it is what i was able to do given the given the constraints so the format of arc is very similar to classic iq tests in particular ravens progressive mattresses ravens yeah ravens privacy mattresses i mean if you've done like you test in the past you know where that is probably at least you've seen it even if you don't know what it's called and so um you have a set of uh tasks that's what they're called and for each task you have um training data which is a set of input and output pairs so i uh an input or output pair is a grid of colors basically the grid the size of the grades these variables is the size of the grid is variable and um you're given an input and you must transform it into the proper outputs right and so you're shown a few demonstrations of a task in the form of existing input output pairs and then you're given a new input and you must provide you must produce the correct output and the assumptions in arc is that every task should only require cool knowledge priors should not require any outside knowledge so for instance uh no language uh no english nothing like this uh new concepts uh taken from uh our human experience like trees dogs cats and so on so only uh tasks that are reasoning tasks that are built on top of a core knowledge priors and some of the tasks are um actually explicitly trying to probe uh specific forms of abstraction right uh part of the reason why i wanted to create arc is i'm a big believer in you know when you're faced with uh a problem as murky as understanding how to autonomously generate abstraction in a machine you have to co-evolve the solution and the problem and so part of the reason why i design act was to clarify my ideas about the nature of abstraction right and some of the tasks are actually designed to to probe uh bits of that theory and there are things that are turned out to be very easy for humans to perform including young kids right but turn out to be near impossible informations so whatever you learn from the nature of abstraction uh from from designing that like what can you clarify what you mean one of the things you wanted to try to understand was this uh idea of abstraction yes so clarifying uh my own ideas about abstraction by forcing myself to produce tasks that would require uh the ability to produce that form of abstraction in order to solve them got it okay so and by the way just uh i mean people should check out i'll probably overlay if you're watching the video part but the the grid input output with the different colors on the grid and that's it that's i mean it's a very simple world but it's kind of beautiful it's it's very similar to classic acutes like it's not very original in that sense the main difference with iq tests is that we make the priors explicit which is not usually the case in iq test so you make it explicit that everything should only be built out of core knowledge priors i also think it's generally more more diverse than iq tests in general and it's it perhaps requires a bit more manual work to produce solutions because you have to to click around on a grid for a while sometimes the grades can be as large as 30 by 30 cells so how did you come up um if you can reveal uh with the questions like what's the process of the questions was it mostly you yeah that came up with the questions what uh how difficult is it to come up with a question like is this um scalable to a much larger number if you think you know with iq tests you might not necessarily want to or need it to be scalable with machines it's possible you could argue that it needs to be scalable so there are a thousand questions a thousand tasks yes wow including the test and the private test set i think it's fairly difficult in the sense that a big requirement is that every task should be novel and unique and unpredictable right like you don't want to create your your own little world that is uh simple enough that it would be possible for a human to reverse and generate and write down an algorithm that could generate every possible arc task and their solution for instance that we completely invalidated the test so you're constantly coming up on new stuff you need yeah you need a source of novelty of unthinkable novelty and one thing i found is that as a human uh you are not a very good source of uh unthinkable novelty and so you have to pace the creation of these tasks quite a bit there are only so many unique tasks that you can do in a given day so that means coming up with truly original new ideas um did psychedelics help you at all i'm just gonna but i mean that's fascinating to think about like so you would be like walking or something like that are you constantly thinking of something totally new yes i mean this is hard this is yeah i i i mean i i'm not saying i've done anywhere near a perfect job at it uh there is some amount of redundancy and there are many imperfections in arc so that said you should you should consider arc as a work in progress it is not uh the definitive state uh where where the the arc tasks today are not definitive states of the test i want to keep refining it um in the future i also think it should be possible to open up the creation of tasks to a broad audience to do crowdsourcing um that would involve several levels of filtering obviously but i think it's possible to apply crowdsourcing to to develop a much bigger and much more diverse arc data set that would also be free of potentially you know some of my own personal biases but is there always need to be a part of arc that's the test like is hidden yes absolutely it is impressive that uh the test that you're using to actually benchmark algorithms is not accessible to the people developing these algorithms because otherwise what's going to happen is that the human engineers are just going to solve the tasks themselves and and encode their solution in program form but that again what you're seeing here is the process of intelligence happening in the mind of the human and and then you're just uh capturing its crystallized output but that crystallized output is not the same thing as the process generated that's right it's not intelligent in itself so what uh by the way the idea of crowdsourcing it is fascinating i think i think the creation of questions is really exciting for people i think i think there's a lot of really brilliant people out there that love to create these kinds of stuff yeah one thing that uh that kind of surprised me that i wasn't expecting is that lots of people seem to actually enjoy ark as a as a kind of game and i was really seeing it as as a test as a benchmark uh of uh a fluid uh general intelligence and lots of people just including kids just started you know enjoying it as a game so i think that's that's encouraging yeah i'm fascinated by there's a world of people who create iq questions i think i think that's a cool uh it's a cool activity for machines that for humans and people humans are themselves fascinated by taking the questions like you know measuring their own intelligence i mean that's just really compelling it's really interesting to me too it helps one of the cool things about arc you said it's kind of uh inspired by iq tests or whatever follows a similar process but because of its nature because of the context in which it lives it immediately forces you to think about the nature of intelligence as opposed to just a test of your own like it forces you to really think there's i don't know if it's if it's within the question inherent in the question or just the fact that it lives in the test that's supposed to be a test of machine intelligence absolutely as you as you solve arc tasks as a human you will uh be forced to basically introspect yeah higher how you come up with solutions and that forces you to reflect on uh the human problem solving process and the way your own mind uh generates uh abstract representations of the problems uh it's exposed to i i think it's due to the fact that the set of core knowledge priors that arc is built upon is so small it's all a recombination of a very very small set of assumptions okay so what's the future of ark so you you held arc as a challenge as part of like a kegel competition yes calgary competition and uh what do you think do you think that's something that continues for five years ten years like just continues growing yes absolutely so arc itself will keep evolving so i've talked about crowdsourcing i think that's a that's a good avenue another thing i'm starting is i'll be collaborating with folks from the psychology department at nyu to do human testing on arc and i think there are lots of interesting questions you can start asking especially as you start correlating machine solutions to arc tasks and and the human characteristics of solutions like for instance you can try to see if there's a relationship between the human perceived difficulty of a task and the machine person yes and and exactly some measure of machine perceived difficulties yeah it's a nice big playground in which to explore this very difference it's the same thing as we talked about the autonomous vehicles the things that could be difficult for humans might be very different than the things that yes absolutely and uh formalizing or making explicit that difference in difficulty will teach us something may teach us something fundamental about intelligence so one thing i think we did well uh with arc is that it's proving to be a very uh actionable test in the sense that uh machine performance and arcs started at very much zero initially while you know humans found actually the tasks very easy and that that alone was like a big red flashing light saying that something is going on and that we are missing something and at the same time uh machine performance did not stay at zero for very long actually within two weeks of the carol competition we started having a non-zero number and now the state of the art is around uh twenty percent of the test set uh solved um and so arc is actually a challenge where our capabilities start at zero which indicates the need for progress but it's also not an impossible change it's not accessible you can start making progress basically right away at the same time we are still very far from having solved it and that's actually a very positive outcome of the competition is that the competition has has proven that there was no obvious shortcut to solve these tasks right yeah so the test held up yeah exactly that was the primary reason to do the cargo competition is to check if some some you know clever person was going to hack the benchmark and that did not happen right like people who are solving the tasks are essentially doing it uh uh well in a way they're they're they're actually exploiting some flaws of art that we will need to address in the future especially they're essentially anticipating what sort of uh tasks may be contained in the test sets right right um which is kind of yeah that's the kind of hacking it's it's human hacking of the town yes that that said you know uh uh with the state of the art it's like uh 20 percent we're still very very far uh from even level which is closer to 100 and so and i i do believe that you know it will it will take a while uh until we reach a human parity on ark and that by the time we have human party we will have ai systems that are probably pretty close to human level in terms of general fluid intelligence which is i mean it's they're not going to be necessarily human-like they're not necessarily uh you would not necessarily recognize them as you know being an egi but they would be capable of a degree of generalization that matches the generalization performed by human food intelligence sure i mean this is a good point in terms of general flu intelligence to mention in your paper you describe different kinds of generalizations uh local broad extreme and there's kind of a hierarchy that you form so when we say generalizations what are we talking about what kinds are there right so uh generalization is is very old idea i mean it's even older than machine learning in the context of machine learning you say a system generalizes if it can uh make sense of an input it has it has not yet seen and that's what i would call a system-centric uh generalization you is generalization with respect to novelty uh for the specific system you're considering so i think a good test of intelligence should actually uh deal with uh developer aware generalization which is slightly stronger than system-centric transition so developer generalization developer aware generalization would be the ability to generalize to novelty or uncertainty that not only the system itself has not accessed to but the developer of the system could not have access to either that that's a fascinating that's a fascinating meta definition so like the system is uh it's basically the edge case thing we're talking about with autonomous vehicles yes neither the developer nor the system know about the edge cases so it's up to they get the system should be able to generalize the thing that that uh nobody expected neither the designer of the training data nor obviously the contents of the training that's a fascinating definition so you can see generalization degrees of generalization as a spectrum and the lowest level is what machine learning is trying to do is the assumption that any new situation is going to be sampled from a static distribution of possible situations and that you already have a representative sample of that distribution that's your training data and so in machine learning you generalize to a new sample from a known distribution and the ways in which your new sample will be new or different are ways that are already understood by the developers of the system so you are generalizing to known unknowns for one specific task that's what you would call robustness you are robust to things like noise small variations and so on um for one a fixed known distribution that that you know through your training data and a higher degree would be flexibility in machine intelligence so flexibility would be something like an l5 cell driving car or maybe a robot that can you know pass the the coffee cup test which is the notion that you would be given a random kitchen uh somewhere in the country and you would have to you know go make a cup of coffee in that kitchen right so flexibility would be the ability to deal with unknown unknowns so things that could not uh dimensions of viability that could not have been possibly foreseen by the creators of the system within one specific task so generalizing to the long tail of situations in self-driving for instance would be flexibility so you have robustness flexibility and finally you would have extreme generalization which is basically flexibility but instead of just considering one specific domain like driving or domestic robotics you're considering an open-ended range of possible domains so a robot would be capable of extreme generalization if let's say it's designed and trained uh to to for cooking for instance um and if i if i buy the robot and if i'm able uh if it's able uh to teach itself gardening in in a couple weeks it would be capable of extreme generalization for instance so the ultimate goal is extreme generalization yes so be uh creating a system that is so general that it could essentially achieve a human skill parity over arbitrary tasks and arbitrary domains with the same level of you know improvisation and adaptation power as humans when when it encounters new situations and it would do so uh over basically the same range of possible domains and tasks uh as humans and using this essentially the same amount of training experience of practice as humans would require that will be human level extreme generalization so i i don't actually think humans are anywhere near the uh optimal intelligence bound if there is such a thing so i think for humans or in general in general i think it's quite likely you know that there is an a hard limit to how intelligent any system can be but at the same time i don't think humans are anywhere near that limit yeah last time i think we talked i think you had this idea that uh we're only as intelligent as the problems we face sort of uh yes we are upper bounded by the problem so in a way yes we are we are bounded by on our environments and we are bounded by the problems we try to solve yeah yeah what do you make of neuralink and uh outsourcing some of the brain power like bring computer interfaces do you think we can expand our augment our intelligence i am fairly skeptical of neural interfaces because they are trying to fix one specific bottleneck in in human machine cognition which is the bandwidth bottleneck input and output of information in the brain and my perception of the problem is that bandwidth is not at this time a bottleneck at all meaning that we already have sensors that enable us to to take in far more information than what we can actually process well to push back on that a little bit uh to sort of play dell's advocate a little bit is if you look at the internet wikipedia let's say wikipedia i would say that humans after the advent of wikipedia are much more intelligent yes i think that's a good one but that's also not about that's about um externalizing our intelligence via uh uh information processing systems the accidental function processing system which is very different from uh brain computer interfaces right but the question is whether if we have direct access if our brain has direct access to wikipedia with our brain already has direct access to wikipedia it's on your phone and you have your hands and your eyes and your ears and so on uh to access that information and the speed at which you can access it is bottlenecked by the customer i think it's already closed fairly close to optimal which is why speed reading for instance does not work yeah the faster you read the less you understand but maybe it's because it uses the eyes so maybe um so i don't believe so i think you know the brain is very slow um it typically operates you know the fastest things that happen in the brain at the level of 50 milliseconds uh forming a conscious out can potentially take entire seconds right and you can already read pretty fast so i think the speed at which you can take information in and even the speed at which you can add with information can only be very incrementally improved maybe i think if you're a very fast typer if you're a very trained typer the speed at which you can express your thoughts is already a speed at which you can form your thoughts right so that's kind of an idea that there are fundamental bottlenecks to the human mind but it's possible that the everything we have in the human mind is just to be able to survive in the environment and there's a lot more to expand maybe you know you said this the speed of the thought so yeah i i think augmenting human intelligence is a very valid and very powerful avenue right and that's what computers are about in fact that's what you know all of culture and civilization is about they are culture is externalized cognition and we rely on culture to think constantly yeah yeah i mean that's that's another yeah that's not just not just computers not just phones and the internet i mean all of culture like language for instance is a form of external recognition books are obviously external recognition yeah that's right and you you can scale that external exclamation you know far beyond the capability of the human brain and you could see you know civ civilization itself is um it has capabilities that are far beyond any individual brain and will keep scaling it because it's not rebound by individual brains it's a different kind of system yeah and and that system includes non-human non-humans first of all includes all the other biological systems which are probably contributing to the overall intelligence of the organism and then yeah computers are part of it no non-human systems probably not contributing much but ais are definitely contributing to that like google search for instance big part of it yeah yeah a huge part a part we can probably introspect like how the world has changed in the past 20 years it's probably very difficult for us to be able to understand until of course whoever created the simulation we're in is probably doing metrics measuring the progress there was probably a big spike in performance uh they're enjoying they're enjoying this so what are your thoughts on um the touring test and the lobner prize which is the you know one of the most famous attempts at the test of human intelligence uh sorry of artificial intelligence by uh doing a natural language open dialogue test that's test that's uh judged by humans as far as how well the machine did so i'm not a fan of the chewing test itself or any of its variants for two reasons so first of all it's um it's really copping out of trying to define and measure intelligence because it's entirely outsourcing that to a panel of human judges and these human judges they may not themselves have any proper methodology they may not themselves have any proper definition of intelligence they may not be reliable so the joint is already failing one of the core psychometrics principles which is reliability because you have biased human judges uh it's also violating the the standardization requirement and the freedom from bias requirement and so it's really a coop out because you are outsourcing everything that matters which is precisely describing intelligence and finding a standalone test uh um to measure it you're outsourcing everything to uh to people so it's really cool and by the way uh we should keep in mind that uh when turing proposed uh the imitation game it was not meaning for the imitation game to be an actual uh goal for the field of ai an actual test of intelligence he was using uh it was using the imitation game as a thought experiment in a philosophical discussion in his uh 1950 paper he was trying to argue that theoretically it should be possible for something very much like the human mind indistinguishable from the human mind to be encoded in ensuring machine and at the time that was that was you know um a very daring idea it was stretching credibility but uh nowadays i think it's it's fairly well accepted that the the mind is an information processing system and that you could probably encode it into a computer so another reason why i'm not a fan of this type of test is that it the incentives that it creates are incentives that are not conducive to proper scientific research if your goal is to trick to convince a panel of human judges that they're talking to a human then you have an incentive to rely on on tricks and press the digitization in the same way that let's say you're doing physics and you want to solve teleportation and what if the test that you set out to pass is you need to convince a panel of judges that teleportation took place and and they're just sitting there and watching what you're doing and that is something that you can achieve with you know david copperfield could could achieve it in his in his show at vegas right but is it and what he's doing is very elaborate but it's not actually it's not physics it's not making any progress you know understanding of the universe right to push back on that it's possible that's the hope with these kinds of subjective evaluations is that it's easier to solve it generally than it is to come up with tricks that convince a large number of judgments that's the whole in practice when it turns out that it's very easy to deceive people in the same way that you know you can you can do magic in vegas you can actually very easily convince people that they're talking to human when they're actually talking to liberalism i just disagree i disagree with that i think it's easy i i would i would push it's not easy it's uh uh it's doable it's very easy because i wouldn't say it's very easy though we are biased like we have theory of mind we are constantly projecting emotions intentions yes uh uh agentness agentness is one of our core innate priors right we are projecting these things on everything around us like if you if you paint a smiley on a rock the rock becomes happy you know eyes and because we have this extreme bias that permeates everything everything we see around this it's actually pretty easy to trick people like this it is very very short i so totally disagree with that you brilliantly put there's a huge it's a the anthropomorphization that we naturally do the agentness of that word is that real word but no it's not a real word i like it but it's exactly why it's useful well it's a useful word let's make it real it's a huge help but i still think it's really difficult to convince uh if you do like the alexa prize formulation where you know you talk for an hour like there's formulations of the test you can create where it's very difficult so i like i like the extra price better because it's more pragmatic it's more practical it's actually incentivizing developers to create something that's useful yeah as a as as a a human machine interface uh so that's slightly better than just the imitation so i like your your your ideas like a test which hopefully help us in creating intelligent systems as a result like if you create a system that passes it it'll be useful for creating further intelligence systems yes at least yeah i mean i'm just to kind of comment i'm a little bit surprised how little inspiration people draw from the touring test today you know the media and the popular press might write about it every once in a while the philosophers might talk about it but like most engineers are not really inspired by it and i know i know you don't like the touring test but uh we'll have this argument another time you know i there's something inspiring about it i think that as as a philosophical device in a physical discussion i think there is something very interesting about it i don't think it is in practical terms i don't think it's it's conducive to to progress and one of the reasons why is that you know i think being very human-like being indistinguishable from a human is actually the very last step in the creation of machine intelligence that the first ais that will show strong generalization uh uh in in uh that that will actually uh implement human like broad cognitive abilities they will not actually be able to look anything uh like humans human likeness is the very last step in that process and so a good test is a test that points you towards the first step uh on the ladder not towards the top of the ladder right yeah so to push back on that so i guess i usually agree with you on most things i remember you i think at some point tweeting something about the turing test not being being counterproductive or something like that and i think a lot of very smart people agree with that i uh uh a uh you know uh computation speaking not very smart person uh disagree with that because i think there's some magic to the interactivity interactivity with other humans so to push to play devil's advocate on your statement it's possible that in order to demonstrate the the generalization abilities of a system you have to show your ability in conversation show your ability to adjust adapt to the conversation through not just like as a standalone system but through the process of like the interaction like game theoretic where you're you really are changing the environment by your actions so in the arc challenge for example you're an observer you can't you can't scare the test into into changing you can't talk to the test you can't play with it so there's some aspect of that interactivity that becomes highly subjective but it feels like it could be conducive to yeah generalization you make a great point the interactivity is a very good setting to force the system to show adaptation to shoot generalization uh that that said you at the same time uh it's not something very scalable because you rely on human judges it's not something reliable because the images may not may not so you don't like human judges basically yes and i think so i i love the idea of interactivity um i initially wanted an arc test that had some amount of interactivity where your score on a task would not be one or zero if you can solve it or not but would be the number of attempts that you can make before you hit the right solution which means that now you can start applying the scientific method as you solve our tasks that you can start formulating hypothesis and and and probing the system to see whether the hypothesis is the observation will match the buddhists or not it would be amazing if you could also even higher level than that measure the quality of your attempts which of course is impossible but again that's gets subjective yes like how good was your thinking like it's yeah how efficient was so one thing that's interesting about this notion of scoring you as how many attempts you need is that you can start producing tasks that are way more ambiguous right right because you can with the problem with the with the different attempts you can actually probe that ambiguity right right so that's in a sense which yeah so it's how good can you adapt to the uncertainty and reduce the uncertainty yes it's half fast with is the efficiency with which to reduce uncertainty in in program space exactly very difficult to come up with that kind of test though yeah so uh i would love to be able to create something like this in practice it would be it would be very very difficult but yes but uh i mean what you're doing what you've done with the arc challenge is is uh brilliant i'm also not i'm surprised that it's not more popular but i think it's picking up what does it snitch it does yeah what are your thoughts about another test that talks with marcus hutter he has the harder prize for compression of human knowledge and the idea is really sort of quantify like reduce the test of intelligence purely to just ability to compress what's your thoughts about this intelligence that's compression i mean it's a it's a very uh fun test because it's it's such a simple idea like you're given wikipedia basically english wikipedia and you must compress it and so it stems from the idea that cognition is compression that the brain is basically a compression algorithm this is a very old idea it's a very i think striking and beautiful idea i used to believe it uh i eventually had to realize that it was it was very much a flawed idea so i no longer believe that compression is recognition is compression so but i can tell you what's the difference so it's very easy to believe that cognition and compression are the same thing because uh so jeff hawkins for instance says that cognition is prediction and of course prediction is basically the same thing as compression right it's just including the temporal axis and it's very easy to believe this because compression is something that we do all the time very naturally we are constantly you know compressing information we are um uh constantly trying we have this bias towards simplicity we we're constantly trying to organize things in our mind and around us to be more regular right so uh it's it's a beautiful idea it's very easy to believe uh there is a big difference between uh what we do with our brains and and compression so compression is actually kind of a tool in the human cognitive toolkits that is is used in many ways but it's just a tool it is not it is a tool for cognition it is not cognition itself and the big fundamental difference is that cognition is about being able to operate in future situations that include fundamental uncertainty and novelty so for instance consider a child at age 10 and so they have 10 years of life experience they've gotten you know pain pleasure rewards and and punishment in a period of time if you were to generate the shortest behavioral program that would have basically run that child over this 10 years in an optimal way right the shortest optimal behavioral program given the experience of that child so far well that program that that compress program this is what you would get if the mind of the child was a compression algorithm essentially um would be utterly enable inappropriate to process the next 70 years in the in the life of the child so in the models with we build of the world we are not trying to make them actually optimally compressed we are we are using compression as a tool to promote simplicity and efficiency in our models but they are not perfectly compressed because they need to include things that are seemingly useless today that have seemingly been useless so far but that may turn out to be useful in the future because you just don't know the future unless that's the fundamental principle uh that cognition that intelligence arises from is that you need to be able to run appropriate behavioral programs except you have absolutely no idea what sort of context environment situation are going to be running in and you have to deal with that with that uncertainty with that future normality so an analogy an analogy that you can make is with investing for instance um if i look at the past uh uh you know 20 years of stock market data and i use a compression algorithm to figure out the best trading strategy it's going to be you know you buy apple stock then maybe the past few years you buy tesla stock or something but is that strategy still going to be true for the next 20 years well actually probably not which is why if you're a smart investor you're not you're not just going to be following the strategy that corresponds to compression of the past uh you're going to be following uh uh you're going to have a balanced portfolio yeah right because you just don't know what's going to run i mean i guess in that same sense the compression is analogous to what you talked about which is like local or robust generalization versus extreme generalization it's much closer to that side of being able to generalize in in a local sense that's why you know as humans as uh when we are when we are children um in our education so a lot of it is driven by place even by curiosity uh we we are not efficiently compressing things we're actually exploring we are um retaining all kinds of uh uh things from our environment that that seem to be completely useless because they might turn out to be eventually useful right and it's it's that's what cognition is really about and that what makes it antagonistic to compression is that it is about hedging for future uncertainty and that's efficient into compression yes especially hedging so uh cognition leverages compression as a tool to promote uh uh to promote efficiency right and so in that sense in our models it's like einstein said make it simpler but not however that quote goes but not too simple so you want to compression simplifies things but you don't want to make it too simple yes so a good model of the world is going to include all kinds of things that are completely useless actually just because just in case yes because you need diversity in the same way that in your portfolio you need all kinds of stocks that that may not have performed well so far but you need diversity and the reason you need diversity because fundamentally you don't know what you're doing and the same is true of the human mind is that it needs to to behave appropriately in the future and it has no idea what the future is going to be like it's a bit it's not going to be like the past so compressing the past is not appropriate because the past is not uh it's not proactive in the future yeah history repeats itself but not perfectly i don't think i asked you last time the most inappropriately absurd question we've talked a lot about intelligence but you know the bigger question from intelligence is of meaning you know intelligence systems are kind of goal-oriented there's throws optimizing for goal if you look at the harder prize actually i mean there's always there's always a clean formulation of a goal but the natural questions for us humans since we don't know our objective function is what is the meaning of it all so the absurd question is what francois chole do you think is the meaning of life what's the meaning of life yeah that's a that's a big question um and i think i can i can you know give you my answer at least one of my answers and so you know the one thing that's uh very important uh in understanding who we are is that everything that makes up uh that makes up ourselves it makes up we are even even your most personal thoughts is not actually your own right like even your most personal thoughts are expressed in words that you did not invent and are built on concepts and images that you did not invent we are very much uh cultural beings right well we are made of culture we are not that what makes us different from animals for instance right so we are everything about ourselves is an echo of the past an echo of people who lived uh before us right that's who we are and in the same way if we manage to contribute something to the collective edifice of culture a new idea maybe a beautiful piece of music a work of art a grand theory a new word maybe um that something is is going to become a part of the minds of future humans essentially forever so everything we do creates ripples right that propagates into the future and i i and that that's in a way this is this is our path to immortality is that as we contribute things to culture culture in turn in turn becomes future humans and we keep influencing people you know thousands of years from now so our actions today create reports and these reports i think basically sum up the meaning of life like in the same way that we are the the sum um of the interactions between many different reports that came from our past we are ourselves creating reports that will propagate into the future and that's why you know we should be this seems like perhaps anything to say but we should be kind to others during our time on earth because every act of kindness creates reports and and in reverse every act of violence also creates reports and you want you want to carefully choose which kind of reports you want to create and you want to propagate into the future and in your case first of all beautifully put but in your case creating ripples into the future human and future agi systems yes it's fascinating all success i don't think there's a better way to end it francois as always for second time and i'm sure many times in the future it's been a huge honor you know one of the most brilliant people in the machine learning computer science science world again that's a huge honor thanks for talking today it's been a pleasure thanks a lot for having me i really appreciate it thanks for listening to this conversation with friend squash chole and thank you to our sponsors babble master class and cash app click the sponsor links in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review five stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from rene descartes in 1668 an except of which francois includes in is on the measure of intelligence paper if there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes we should still have two very certain means of recognizing that they were not real men the first is that they could never use words or put together signs as we do in order to declare our thoughts to others for we can certainly conceive of a machine so constructed that it utters words and even utters words that correspond to bodily actions causing a change in its organs but it is not conceivable that such a machine should produce different arrangements of words so as to give it an appropriately meaningful answer to whatever is said in his presence as the dullest of men can do here descartes is anticipating the turing test and the argument still continues to this day secondly he continues even though some machines might do some things as well as we do them or perhaps even better they would inevitably fail in others which would reveal that they're acting not from understanding but only from the disposition of their organs this is incredible quote for whereas reason is a universal instrument which can be used in all kinds of situations these organs need some particular action hence it is for all practical purposes impossible for machine to have enough different organs to make it act in all the contingencies of life in the way in which our reason makes us act that's the debate between mimicry memorization versus understanding so thank you for listening and hope to see you next time you |
David Eagleman: Neuroplasticity and the Livewired Brain | Lex Fridman Podcast #119 | the following is a conversation with david eagleman a neuroscientist and one of the great science communicators of our time exploring the beauty and mystery of the human brain he is an author a lot of amazing books about the human mind and his new one called livewired livewired is a work of 10 years on a topic that is fascinating to me which is neuroplasticity or the malleability of the human brain quick summary of the sponsors athletic greens betterhelp and cash app click the sponsor links in the description to get a discount and to support this podcast as a side note let me say that the adaptability of the human mind at the biological chemical cognitive psychological and even sociological levels is the very thing that captivated me many years ago when i first began to wonder how would i engineer something like it in the machine the open question today in the 21st century is what are the limits of this adaptability as new smarter and smarter devices and ai systems come to life or as better and better brain computer interfaces are engineered will our brain be able to adapt to catch up to excel i personally believe yes that we're far from reaching the limitation of the human mind and the human brain just as we are far from reaching the limitations of our computational systems if you enjoy this thing subscribe on youtube review it with five star snapple podcast follow on spotify support on patreon and connect with me on twitter at lex friedman as usual i'll do a few minutes of as now and no ads in the middle i try to make these interesting but i give you timestamps so you can skip but please do check out the sponsors by clicking the links in the description it's the best way to support this podcast this show is brought to you by athletic greens the all-in-one daily drink to support better health and peak performance even with a balanced diet it's difficult to cover all your nutritional bases that's where athletic greens will help their daily drink is like nutritional insurance for your body as delivered straight to your door as you may know i fast often sometimes intermittent fasting for 16 hours sometimes 24 hours dinner to dinner sometimes more i break the fast with athletic greens it's delicious refreshing just makes me feel good i think it's like 50 calories less than a gram of sugar but has a ton of nutrients to make sure my body has what it needs despite what i'm eating go to athletic greens.com lex to claim a special offer of a free vitamin d3k2 for a year if you listen to the joe rogan experience you might have listened to him rant about how awesome vitamin d is for your immune system so there you have it so click the athletic greens.com lex in the description to get the free stuff and to support this podcast this show sponsored by better help spelled h-e-l-p help check it out at betterhelp.com flex they figure out what you need match you with a licensed professional therapist in under 48 hours it's not a crisis line it's not self-help it's professional counseling done securely online i'm a bit from the david goggins line of creatures and so have some demons to contend with usually on long runs or all nights full of self-doubt i think suffering is essential for creation but you can suffer beautifully in a way that doesn't destroy you for most people i think a good therapist can help in this so it's at least worth a try check out their reviews they're good it's easy private affordable available worldwide you can communicate by text and your time and schedule a weekly audio and video session check it out at betterhelp.com lex this show is presented by cash app the number one finance app in the app store when you get it use collects podcast cash app lets you send money to friends buy bitcoin invest in the stock market with as little as one dollar since cash app allows you to buy bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating i recommend ascent of money as a great book on this history debits and credits on ledgers started around 30 000 years ago and the first decentralized cryptocurrency released just over 10 years ago so given that history cryptocurrency is still very much in its early days of development but it's still aiming to and just might redefine the nature of money so again if you get cash out from the app store google play and use code lex podcast you get ten dollars and cash up will also donate ten dollars the first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with david eagleman you have a new book coming out on the changing brain can you give a high level overview of the book it's called live wired by the way yeah the thing is we typically think about the brain in terms of the metaphors we already have like hardware and software that's how we build all our stuff but what's happening in the brain is fundamentally so different it's um so i coined this new term livewear which is a system that's constantly reconfiguring itself physically as it as it learns and adapts to the world around it it's physically changing so it's uh live wear meaning like as like hardware but changing yeah exactly well it's the hardware and the software layers are blended and so um you know typically engineers are praised for their efficiency and making something really clean and clear like okay here's the hardware layer then i'm gonna run software on top of it there's all sorts of universality that you get out of a piece of hardware like that that's useful but what the brain is doing is completely different and i am so excited about where this is all going because i feel like this is where our engineering will go so currently we build uh all our devices a particular way but you know i can't tear half the circuitry out of your cell phone and expect it to still function but you can do that with uh with the brain so just as an example kids who are under about seven years old can get one half of their brain removed it's called the hemispherectomy and and they're fine they have a slight limp on the other side of their body but um they can function just fine that way and uh and this is generally true you know sometimes children are born without a hemisphere and their visual system rewires so that everything is on the on the single remaining hemisphere what thousands of cases like this teach us is that it's a very malleable system that is simply trying to accomplish the tasks in front of it by rewiring itself with the available real estate how much of that is uh is a quark or a feature of evolution like how how hard is it to engineer because evolution took a lot of work billion trillions of organisms had to die for to create this thing we have uh in our skull uh like because you said uh you kind of look forward to the idea that uh we might be engineering our systems like this in the future but creating live war systems how hard do you think is it to create systems like that great question it has proven itself to be a difficult challenge but what i mean by that is even though it's taken evolution a really long time to get where it is now um we all we have to do now is peek at the at the blueprints it's just three pounds this organ and and we just figure out how to do it but that's the part that i mean is a difficult challenge because you know uh there are tens of thousands of neuroscientists were all poking and prodding and trying to figure this out but it's an extremely complicated system but it's only going to be complicated until we figure out the general principles exactly like if you you know had a magic camera and you could look inside the nucleus of a cell and you'd see hundreds of thousands of things moving around whatever and then you know it takes crick and watts and say oh you know you're just trying to maintain the order of the base pairs and all the rest is details then it simplifies it and we come to understand something that that was my goal in livewire which i've written over 10 years by the way is to try to distill things down to the principles of what plastic systems are trying to accomplish but to even just linger he said it's possible to be born with just one hemisphere and you still are able to function first of all just just to pause on that i mean that's kind of that's amazing that's that's uh i don't know if people quite i mean you kind of hear things here and there this is what i'm kind of i'm really excited about your book is i don't know if there's definitive uh sort of uh popular sources to think about the stuff i mean there's a lot of i think from my perspective what i've heard is there's like been debates over decades about how how much neuroplasticity there is in the brain and so on and people have learned a lot of things and now it's converging towards people that are understanding this much more in europe much more plastic than people realize but just like linger on that topic like how malleable is the hardware of the human brain maybe you said children at each stage of life yeah so here's the whole thing i think part of the confusion about plasticity has been that there are studies at all sorts of different ages and then people might read that from a distance and they think oh well fred didn't recover when half his brain was taken out and so clearly you're not plastic but then you do it with a child and they are plastic and so um part of my goal here was to pull together the tens of thousands of papers on this both from clinical work and from you know all the way down to the molecular and understand what are the principles here the principles are that plasticity diminishes that's no surprise by the way we should just define plasticity you know it's the ability of a system to to mold into a new shape and then hold that shape that's why you know we make things that we call plastic um because they are moldable and they can hold that new shape like a plastic toy or something and so maybe we use maybe we'll use a lot of terms that are synonymous so something is plastic something is malleable uh changing livewire the name of the book is is like so i'll tell you exactly right but i'll tell you why i chose livewire instead of plasticity so i used the term plasticity in the book but um but sparingly because that was a term coined by william james over 100 years ago and and he was of course very impressed with plastic manufacturing that you could mold something in shape and then it holds that but that's not what's actually happening in the brain it's constantly rewiring your entire life you never hit an end point the whole point is for it to keep changing so even in the you know few minutes of conversation that we've been having your brain is changing my brain is changing um next time i see your face i will remember oh yeah like that time next time i sat together and we did these things and i wonder if your brain will have like a lex thing going on for the next few months like you'll stay there until you get rid of it because it was useful for now yeah no i'll probably never get rid of it let's say for some circumstance you and i don't see each other for the next 35 years when i run into you i'll be like oh yeah that looks familiar yeah yeah and we yeah we sat down for a podcast back when there were podcasts yeah exactly back when we lived outside virtual reality yeah exactly so you chose livewire exactly exactly because plastic implies i mean it's the term that's used in the field and so that's why we need to use it still uh for a while but yeah it implies something gets molded in shape and then holds that shape forever but in fact the whole system is completely changing then then back to uh how malleable is the human brain at each stage of life so what just at a high level is it malleable so yes and plasticity diminishes but one of the things that i felt like i was able to put together for myself after reading thousands of papers on this issue is that different parts of the brain are have different plasticity windows so for example with the visual cortex that cements itself into place pretty quickly over the course of a few years and i argue that's because of the stability of the data in other words what you're getting in from the world you've got a certain number of angles colors shapes you know it's essentially the world is visually stable so that hardens around that data as opposed to let's say the somatosensory cortex which is the part that's taking information from your body or the motor cortex right next to it which is what drives your body the fact is bodies are always changing you get taller over time you get fatter thinner over time you you might break a leg and have to limp for a while stuff like that so because the data there is always changing by the way you might get on a bicycle you might get a surfboard things like that um because that data is always changing that stays more malleable and when you look through the brain you find that it appears to be this you know how stable the data is determines how fast something hardens into place but the point is different parts of the brain harden into place at different times do you think it's possible that uh depending on how much data you get on different sensors that it stays more malleable longer so like you know if you look at different cultures of experience like if you keep your eyes closed or maybe you're blind i don't know but let's say you keep your eyes closed for your entire life uh it that then the visual cortex might be much less malleable the reason i bring that up is like you know well maybe we'll talk about brain computer interfaces a little bit and down the line but you know like is this uh is the malleability a genetic thing or is it more about the data like i said that comes in ah so the malleability itself is a genetic thing the big trick that mother nature discovered with humans is make a system that's really flexible as opposed to most other creatures to different degrees so if you take a an alligator it's born its brain does the same thing every generation if you compare an alligator a hundred thousand years ago to an alligator now they're essentially the same um we on the other hand as humans drop into a world with a half-baked brain and what we require is to absorb the culture around us and the language and the beliefs and the customs and so on that's what mother nature has done with us and it's been a tremendously successful trick we've taken over the whole planet as a result of this so that's an interesting point i mean just to lingard that i mean this is a nice feature like if you were to design a thing to survive in this world do you put it at age zero already equipped to deal with the world in a like hard-coded way or do you put it do you make it malleable and just throw it in take the risk that you're maybe going to die but you're going to learn a lot in the process and if you don't die you'll learn a hell of a lot to be able to survive in the environment so this is the experiment that mother nature ran and and it turns out that for better worse we've won i mean yeah we put other animals into the zoos and we yeah that's right yeah i might do better okay fair enough that's true and and maybe what the trick mother nature did is just the stepping stone to uh to ai but so it's that's that's a beautiful feature of the human brain that it's malleable but let's on the topic of mother nature what do we start with like how blank is the slate ah so it's not actually a blank slate what it's it's terrific engineering that's set up in there but much of that engineering has to do with okay just make sure that things get to the right place for example like the fibers from the eyes getting to the visual cortex or all this very complicated machinery in the ear getting to the auditory cortex and so on so things first of all there's that and then what we also come equipped with is the ability to absorb language and culture and beliefs and so on so you're already set up for that so no matter what you're exposed to you will you will absorb some sort of language that's the trick is how do you engineer something just enough that it's then a sponge that's ready to take in and fill in the blanks how much of the malleability is hardware how much software is that useful at all in the brain so like what what are we talking about so there's like there's neurons there's uh synapses and the all kinds of different synapses and there's chemical communication like electrical signals and there's chemical communication from this in the synapses uh what i would say the software would be the timing and the nature of the electrical signals i guess and the hardware would be the actual synapses so here's the thing this is why i really if we can i want to get away from the hardware and software metaphor because what happens is as activity passes through the system it changes things now the thing that computer engineers are really used to thinking about is is synapses where two neurons connect of course each neuron connects with ten thousands of its neighbors but at a point where they connect um what we're all used to thinking about is the changing of the strength of that connection the the synaptic weight but in fact everything is changing the receptor distribution inside that neuron so that you're more or less sensitive to the neurotransmitter than the structure of the neuron itself and and what's happening there all the way down to biochemical cascades inside the cell all the way down to the nucleus and for example the epigenome which is the um you know these little proteins that are attached to the dna that cause conformational changes that cause more genes to be expressed or repressed all of these things are plastic the reason that most people only talk about the synaptic weights is because that's really all we can measure well and all this other stuff is really really hard to see with our current technology so essentially that just gets ignored but but in fact the system is plastic at all these different levels and my my way of thinking about this is an analogy to paste layers so paste layers is a concept that stewart brand suggested about how to think about cities so you have fashion which changes rapidly in cities you have um governance which changes more slowly you have the structure the buildings of a city which changes more slowly all the way down to to nature you've got all these different layers of things that are changing at different paces at different speeds i've taken that idea and and mapped it onto the brain which is to say you have some biochemical cascades are just changing really rapidly when something happens all the way down to things that are more and more cemented in there and this is actually uh this actually allows us to understand a lot about particular kinds of things that happen for example one of the oldest probably the oldest rule in neurology is called ribose law which is that older memories are more stable than newer memories so when you get old and demented you'll be able to remember things from your your young life maybe you'll remember this podcast but you won't remember what you did a month ago or a year ago and this is a very weird structure right no other system works this way where older memories are more stable than newer members but it's because through time things get more and more cemented into deeper layers of the system and um and so this is i think the way we have to think about the brain not as okay you've got neurons you've got synaptic weights and that's it so yeah so the idea of live where and live wired is it is that it's it's like a it's a gradual yeah it's a gradual spectrum between software and hardware and so the metaphors completely doesn't make sense because like when you talk about software and hardware it's really hard lines i mean of course software is unlike card but even hardware but like so there's two groups but in the software world there's levels of abstractions right there's the operating system there's machine code and then it gets higher higher levels but somehow that's actually fundamentally different than the layers of abstractions in the hardware but in the brain it's all like the same i love the city the city metaphor i mean yeah it's kind of mind-blowing because it it's hard to know what to uh think about that like if i were to ask the question uh this is important question for machine learning is how does the brain learn so essentially you're saying that i mean it just learns on all of these different levels at all different paces exactly right and as a result what happens is as you practice something you get good at something you're physically changing the circuitry you're you're adapting your brain around the thing that is relevant to you so let's say you take up um do you know how to surf no okay great so let's say you take up surfing yeah now at this age um what happens is you know you'll be terrible at first you know how to operate your body you know how to read the waves things like that and through time you get better and better what you're doing is you're burning that into the actual circuitry of your brain you're of course conscious when you're first doing it you're thinking about okay where am i doing what's my body weight um but eventually when you become a pro at it you are not conscious of it at all in fact you can't even unpack what it is that you did think about riding a bicycle you you can't describe how you're doing you're just doing you're changing your balance when you come you know you do this to go to a stop and so so um this is what we're constantly doing is actually shaping our own circuitry based on what is relevant for us survival of course being the the top thing that's relevant but interestingly especially with humans we have these particular goals in our lives computer science neuroscience whatever and so we actually shape our circuitry around that i mean you mentioned this gets slower and slower with age but is there like i've i think i've uh read and spoken offline even on this podcast developmental neurobiologist i guess would be the right terminology is like looking at the very early like from from embryonic stem cells to like to the to the creation of the brain and like that's like what that's mind-blowing how much stuff happens there so it's very malleable at that stage uh it's and then but after that at which point does it stop being malleable so so that's the interesting thing is that it remains valuable your whole life so even when you're an old person you'll be able to remember new faces and names you'll be able to learn new sorts of tasks and thank goodness because the world is changing rapidly in terms of technology and so on i just sent my mother and alexa and she you know figured out how to go on the settings and do the thing and i was really yeah i was really impressed by that she was able to do it so there are parts of the brain that remain malleable their whole life the interesting part is that really your goal is to make an internal model of the world your goal is to say okay the brain uh is trapped in silence and darkness and it's trying to understand how the world works out there right i love that image yeah i guess it is yeah you forget you forget it's like this this lonely thing is sitting in its own container and uh trying to actually throw a few sensors figure out what the what the hell's going on you know what i sometimes think about is um the that movie the martian with matt damon the um it was written in a book of course but the the movie poster shows matt damon all alone on the red planet and i think god that's actually what it's like to be inside your head and my head and anybody's head is that you're essentially on your own planet in there and i'm essentially on my own planet everyone's got their own world where you've absorbed all of your experiences up to this moment in your life that made you exactly who you are and same for me and everyone and um and we've got this very thin bandwidth of communication and i'll say something like oh yeah that tastes just like peaches and you'll say oh i know what you mean but the experience of course might be might be vastly different for us um but anyway yes so the brain is trapped in silence and darkness each one of us and what it's trying to do this is the important part is trying to make an internal model of what's going on out there as in how do i function in the world how do i how do i interact with other people do i say something nice and polite or do i say something aggressive and mean do i you know all these things that it's putting together about the world and i think what happens when people get older and older it may not be that plasticity is diminishing it may be that their internal model essentially has set itself up in a way where it says okay i've pretty much got a really good understanding of the world now and i don't really need to change right so when old when when much older people find themselves in a situation where they need to change they can actually are able to do it it's just that i think this notion that we all have that plasticity diminishes as we grow older is in part because the motivation isn't there um but if you were 80 and you got fired from your job and suddenly had to figure out how to program a wordpress site or something you'd figure it out got it so the the capability the possibility of changes is there but let me ask the the highest challenge the interesting challenge to this uh plasticity to this uh livewear system uh if we could talk about brain computer interfaces and neurolink what are your thoughts about the efforts of elon musk neuralink bci in general in this regard which is adding a machine a computer the capability of a computer to communicate with the brain and the brain to communicate with the computer at the very basic applications and then like the futuristic kind of thoughts yeah first of all it's terrific that people are jumping and doing that because it's clearly the the future the interesting part is our brains have pretty good methods of interacting with technology so maybe it's your fat thumbs on a cell phone or something but um or maybe it's watching a youtube video getting into your eye that way but we have pretty rapid ways of communicating with technology and getting data so if you actually crack open the skull and go into the inner sanctum of the brain um you might be able to get a little bit faster but i'll tell you i i'm i'm not so sanguine on the future of that as a business and i'll tell you why it's because there are various ways of getting data in and out and an open head surgery is a big deal neurosurgeons don't want to do it because there's always risk of death and infection on the table and also it's not clear how many people would say i'm going to volunteer to get something in my head so that i can text faster you know 20 faster so i think it's you know mother nature surrounds the brain with this armored you know bunker of the skull because it's a very delicate material and there's an expression in neurosurgery um about the brain is you know the person is never the same after you open up their skull now whether or not that's true or whatever who cares but it's a big deal to do in open head surgery so what i'm interested in is how can we get information in and out of the brain without having to crack the skull open got it without messing with the biologicals the part like directly uh connecting or messing with the with the intricate biological thing that we got going on it seems to be working yeah exactly and by the way where neural link is going which is wonderful is going to be in patient cases it really matters for all kinds of surgeries that a person needs whether for parkinson's or epilepsy or whatever it's a terrific new technology for essentially sowing electrodes in there and getting more higher density of electrodes so that's great i just don't think as far as the future of bci goes i don't suspect that people will go in and say yeah drill a hole in my head and do that well it's interesting because uh i think there's a similar intuition but say in the world of autonomous vehicles that folks know how hard it is and it seems damn impossible the similar intuition about i'm sticking on the elon musk thing is just a good easy example uh similar intuition about colonizing mars it like if you really think about it it seems extremely difficult and uh and almost i mean just technically difficult to the to a degree where you want to ask is it really worth doing worth trying and then the same the same is applied with bci but the thing about the future is it's hard to predict uh the the exciting thing to me with uh so once it does once if successful it's able to help patients it may be able to discover something uh very surprising about our ability to directly communicate with the brain so exactly what you're interested in is figuring out how to uh play with this malleable brain but like help assist it somehow i mean it's such a compelling notion to me that we're now working on all these exciting machine learning systems that are able to learn you know from data and then if we can have this other brain that's a learning system that's live wired in when on the human side and them to be able to communicate it's like a self playing mechanism was able to beat the game the world champion go so they can play with each other the computer and the brain like when you sleep i mean there's a lot of futuristic kind of things that it's just um exciting possibilities but i hear you we understand so little about the actual intricacies of the communication of the brain that it's hard to find the common language well interestingly the technologies that have been built don't actually require the perfect common language so for example hundreds of thousands of people are walking around with artificial ears and artificial eyes meaning cochlear implants or retinal implants so this is you know you take uh essentially digital microphone you slip an electrode strip into the inner ear and people can learn how to hear that way or you take an electrode grid and you plug it into the retina at the back of the eye and people can learn how to see that way the interesting part is those devices don't speak exactly the natural biological language they speak the dialect of silicon valley and and it turns out that as as recently as about 25 years ago a lot of people thought this was never going to work they thought it was it wasn't going to work for that reason but the brain figures it out it's really good at saying okay look there's some correlation between what i can touch and feel and hearing and so on and the data that's coming in or between you know i clap my hands and i and i have signals coming in there and it figures out how to speak any language oh that's fascinating so like uh no matter you're no matter if it's neural link uh so directly communicating with the brain or it's a smartphone or google glass or the brain figures out the efficient way of communication well exactly exactly and what i propose is the potato head theory of evolution which is which is um that all you know our eyes and nose and mouth and ears and fingertips all this stuff is just plug and play and the brain can figure out what to do with the day that comes in and part of the reason that i think this is right and i care so deeply about this is when you look across the animal kingdom you find all kinds of weird peripheral devices plugged in and the brain figures out what to do with the data and i don't believe that mother nature has to reinvent the principles of brain operation each time to say oh now i'm going to have heat pits to detect infrared now i'm going to have something to detect uh you know electro receptors on the body now i'm going to test something to pick up the magnetic field of the earth with cryptochromes in the eye and so on instead the brain says oh i got it there's data coming in is that useful can do something with it oh great i'm gonna mold myself around the data that's coming in it's kind of fascinating to think that we think of smartphones and all this new technology is novel as totally novel as outside of what evolution ever intended or like what nature ever intended it's fascinating to think that like the entirety of the process of evolution is perfectly fine and ready for the smartphone oh yeah and the internet like it's ready it's ready to be valuable to that and whatever comes to cyborgs to virtual reality we kind of think like this is you know there's all these like books written about natural what's natural and we're like destroying our natural cells by like embracing all this technology it's kind of it's you know we're not probably not giving the brain enough credit like this this thing this thing is just fine with new tech oh exactly it wraps itself around by the way wait till you have kids you'll see the ease with which they pick up on stuff and yeah as kevin kelly said um technology is what gets invented after you're born but the stuff that already exists when you're born that's not even tech that's just background furniture like the fact that the ipad exists for my son and daughter like that's just background furniture so um yeah it's um because we have this incredibly malleable system it just absorbs whatever is going on in the world and learns what to do with it so do you think just to linger for for a little bit more do you think it's possible to co-adjust like we're kind of uh you know for the machine to adjust to the brain for the brain to adjust the machine i guess that's what's already happening sure that is what's happening so for example when when you put electrodes in the motor cortex to control a robotic arm for somebody who's paralyzed the engineers do a lot of work to figure out okay what can we do with the algorithm here so that we can detect what's going on from these cells and figure out how to best program the robotic arm to move given the data that we're measuring from these cells but also the brain is learning too so you know the paralyzed woman says wait i'm trying to grab this thing and by the way it's all about relevance so if there's a piece of food there and she's hungry she'll figure out how to get this food into her mouth with the robotic arm because that is what matters well that's uh okay first of all that pain's really promising and beautiful for some reason really optimistic picture that you know our brain is able to to adjust to so much um you know so many things happen this year 2020 that you think like how we're ever going to deal with it and it's somehow encouraging and inspiring that like we're going to be okay well that's right i actually think so 2020 has been an awful year for almost everybody in many ways but the one silver lining has to do with brain plasticity which is to say we've all been on our you know on our gerbil wheels we've all been in our routines and and you know as i mentioned our internal models are all about how do you maximally succeed how do you optimize your operation in this circumstance where you are right and then all of a sudden bang 2020 comes we're completely off our wheels where having to create new things all the time and figure out how to do it and that is terrific for brain plasticity because and we know this because um there are very large studies on older people who stay cognitively active their whole lives some some fraction of them have alzheimer's disease physically but nobody knows that when they're alive even though their brain is getting chewed up with the ravages of alzheimer's cognitively they're doing just fine why it's because they're they're they're challenged all the time they've got all these new things going on all this novelty all these responsibilities chores social life all these things happening and as a result they're constantly building new roadways even as parts degrade and and and that's the only good news is that we are in a situation where suddenly we can't just operate like automaton anymore we have to think of completely new ways to do things and that's wonderful i don't know why this question popped into my head it's quite absurd but uh are we going to be okay yeah you say this is the promising silver lining just from your own because you've written about this and thought about this outside of maybe even the plasticity of the brain but just this uh this whole pandemic kind of changed the way it knocked us out of this uh hamster wheel like that of habit a lot of people had had to reinvent themselves unfortunately and i have a lot of friends who either already or or are going to lose their business you know is basically it it's taking the dreams that people have had and said like said this this dream this particular dream you've had will no longer be possible you have to find something new what are your are we gonna be okay yeah we'll be okay in the sense that i mean it's gonna be a rough time for many or most people but in the sense that it is sometimes useful to find that what you thought was your dream was was not the thing that you're going to do um this is obviously the plot in lots of hollywood movies that someone says i'm going to do this and then that gets foiled and they end up doing something better but this is true in life i mean um in general even though we plan our lives as best we can it's predicated on our notion of okay given everything that's around me this is what's possible for me next but it takes 2020 to knock you off that where you think oh well actually maybe there's something i could be doing that's bigger that's better yeah you know for me one exciting thing and i just talked to grant sanderson i don't know if you know who he is it's a three blue one brown it's a youtube channel he does he's a if you see it you would recognize it he's like a really famous math guy and he's a math educator and he does he's incredible beautiful videos and now i see sort of at mit folks are struggling to try to figure out you know if we do teach remotely how do we do it effectively so you have these um world-class researchers and professors trying to figure out how to put content online that teaches people and to me a possible future of that is you know nobel prize winning faculty become youtubers like like that that to me is so exciting uh like what grant said uh which is like the possibility of creating canonical videos on the thing you're a world expert in uh you know there's so many topics that just the world doesn't you know there's faculty i mentioned russ cedric there's all these people in robotics that are experts in a particular beautiful field on which there's only just papers there's there's no popular book there's no there's no clean canonical video showing the beauty of a subject and one possibility is uh they they try to create that and and share it with the world this is this is the beautiful thing this of course has been happening for a while already i mean for example when i go and i give book talks often what'll happen is some 13 year old will come up to me afterwards and say something and i'll say my god that was so small like how how did you know that yeah and they'll say oh i saw it on a ted talk well what an amazing opportunity here you got the the best person in the world on subject x giving a 15-minute talk as as beautifully as he or she can and the 13 year old just grows up with that that's just the mother's milk right yeah as opposed to when we grew up you know i had whatever homeroom teacher i had and uh you know whatever classmates i had and and hopefully that person knew what what he or she was teaching and often didn't and you know just made things up so the the opportunity now has become extraordinary to get the best of the world and the reason this matters of course is because obviously back to plasticity the way that we the way our brain gets molded is by absorbing everything from the world all of the all of the knowledge and the data and so on that it can get and then um and then springboarding off of that and we're in a very lucky time now because we grew up with a lot of just in case learning so you know just in case you ever need to know these dates in mongolian history here there um but what kids are growing up with now like my kids is tons of just in time learning so as soon as they're curious about something they ask alex or they ask google home they get the answer right there in the context of the curiosity the reason this matters is because for plasticity to happen you need to care you need to be curious about something and this is something by the way that the ancient romans had had noted they had outlined seven different levels of learning and the highest level is when you're curious about a topic but anyway so kids now are getting tons of just in time learning and as a result they're going to be so much smarter than we are they're just and we can already see that i mean my boy is eight years old my girl is five but i mean the things that he knows are amazing because it's not just him having to do the rote memorization stuff that we did yeah that's it's just fascinating what the brain what young brains look like now because of all those ted talks just just loaded in there and there's there's also i mean a lot of people write kind of there's a sense that our attention span is growing shorter but you know it's complicated because um you know for example you know most people majority of people it's the 80 plus percent of people listen to the entirety of this thing it's just two three hours forward podcast long long-form podcasts or are becoming more and more popular so like that's that's it's all really giant complicated mess and the point is that the brain is able to adjust to it and somehow like form a world view within this new medium of like information that we have you have like these short tweets and you have these three four hour podcasts and you have netflix movie i mean it's just it's adjusting to the entirety and just absorbing it and taking it all in and then pops up kovid that forces us all to be home and it all just adjusts and and uh and figures it out yeah yeah it's fascinating you know been talking about the brain as if it's something separate from the human that carries it a little bit like whenever you talk about the brain it's easy to forget that that that's like that's us um like how much do you how much is the whole thing like predetermined like how much is it already encoded in there and how much is it the what's the uh the the actions the decisions the judgments this you mean like who you are who you are oh yeah yeah okay great question right so there used to be a big debate about nature versus nurture and we now know that it's always both you can't even separate them because you come to the table with a certain amount nature for example your whole genome and so on the experiences you have in the womb like whether your mother is smoking or drinking things like that whether she's stressed so on those all influence how you're going to pop out of the womb from there everything is an interaction between all of your experiences and the and the nature what i mean is i think of it like a space time cone where you have you drop in the world depending on the experience that you have you might go off in this direction or that direction in that direction because there's interaction all the way your experiences determine what happens with the expression of your genes so some genes get repressed some get expressed and so on and you actually become a different person based on your experiences there's a whole field called uh epigenomics which is or epi epigenetics i should say which is about the epigenome and that is the you know sort of the layer that sits on top of the dna and causes the genes to express differently that is directly related to the experiences that you have so if you know just as an example they take rat pups and you know one group is sort of placed away from their parents and the other group is groomed and licked and taken good care of that changes their gene expression for the rest of their life they go off in different directions in this in the space time cone um so yeah this is this is of course why it matters that we take care of children and pour money into things like education and good child care and so on for children broadly um because these formative years matter so much so is there a free will this is this is a great apologize for the for the absurd high-level philosophical questions no these are my favorite kind of questions here's the thing here's the thing we don't know if you ask most neuroscientists they'll say that we can't really think of how you would get free will in there because as far as we can tell it's a machine it's a very complicated machine enormously sophisticated 86 billion neurons about the same number of glial cells each of these things is as complicated as the city of san francisco each neuron in your head has the entire human genome in it it's expressing millions of gene products these are incredibly complicated biochemical cascades each one is connected to 10 000 of its neighbors which means you have you know like half a quadrillion connections in the brain so it's it's incredibly complicated but it is fundamentally appears to just be a machine and therefore if there's nothing in it that's not being driven by something else then it seems it's hard to understand where free will would come from so that's the camp that pretty much all of us fall into but i will say our science is still quite young and you know i'm a fan of the history of science and what the thing that always strikes me is interesting is when you look back at any moment in science everybody believes something is true and they just they simply didn't know about you know what einstein revealed or whatever and so who knows and they all feel like that we've at any moment in history they all feel like we've converted to the final answer exactly exactly like all the pieces of the puzzle are there and i think that's a funny illusion that's worth getting rid of and and in fact this is what drives good science is recognizing that we don't have most of the puzzle pieces so as far as the free will question goes i don't know at the moment it seems wow it would be really impossible to figure out how something else could fit in there but you know 100 years from now our textbooks might be very different than they are now i mean could i ask you to speculate where do you think free will could be squeezed into there like what's that even um is it is it possible that our brain just creates kinds of illusions that are useful for us or like what where where could it possibly be squeezed in well let me let me give a speculation and answer to your very nice question but but you know don't and the listeners podcast don't quote me on this i'm not saying this is what i believe to be true but let me just give an example i gave this the end of my book incognito so the whole book of incognito is about you know all the what's happening in the brain and essentially i'm saying look here's all the reasons to think that free will probably does not exist but at the very end i say look imagine that you are um you know imagine that you're a kalahari bushman and you find a radio in the sand and you've never seen anything like this and you you look at this radio and and you realize that when you turn this knob you hear voices coming from their voices coming from it so being a you know a radio materialist you try to figure out like how does this thing operate so you take off the back cover and you realize there's all these wires and when you take out some wires the voices get garbled or stop or whatever and so what you end up developing is a whole theory about how this connections pattern of wires gives rise to voices but it would never strike you that in distant cities there's a radio tower and there's invisible stuff beaming and that's actually the origin of the voices and this is just necessary for it so i mentioned this just as a speculation saying look how would we know what we know about the brain for absolutely certain is that if when you damage pieces and parts of it things get jumbled up but how would you know if there's something else going on that we can't see like electromagnetic radiation that is what's actually generating this yeah you paint a beautiful example of uh of how totally because we don't know most of how our universe works how totally off-base we might be with our science yeah until i mean we i mean um yeah i mean that's inspiring that's beautiful it's kind of terrifying it's humbling it's all all of the above and the important and the important part just to recognize is that of course we're in the position of having massive unknowns and you know we have of course the known unknowns and that's all the things we're pursuing in our labs and trying to figure out that but there's this whole space of unknown unknowns things we haven't even realized we haven't asked yet let me kind of ask a weird maybe a difficult question part of the it has to do with i've been recently reading a lot about world war ii i'm currently reading a book i recommend for people which is uh uh as a jew it's been difficult to read but uh the horizon follows the third reich so let me just ask about like the nature of genius the nature of evil if we look at somebody like uh einstein we look at hitler stalin modern day jeffrey epstein just folks who through their life have done with einstein done works of genius and with the others i mentioned have done evil on this world what do we think about that in a live wired brain like how do how do we think about these extreme people here's here's what i'd say this is a very big and difficult question but what i would say briefly on it is um you know first of all i saw a cover of time magazines some years ago uh and it was a big you know sagittal slice of the brain and it said something like um what makes us good and evil and there was a little spot pointing to it there's a picture of gandhi and there's a little spot that was pointing to hitler and these time magazine covers always make me mad because it's so goofy to think that we're going to find some spot in the brain or something instead the interesting part is because we're live-wired we are all about the world and the culture around us so somebody like adolf hitler got all this positive feedback about what was going on and the crazier and crazier the ideas he had he's like let's set up death camps and murder a bunch of people and so on somehow he was getting positive feedback from that and all these other people they're all you know spun each other up and you look at anything like i mean look at the you know um the the cultural uh revolution in china or the um you know the russian revolution or things like this where you look at these things my god how do people all behave like this but it's easy to see groups of people spinning themselves up in particular ways where they all say well would i have thought this was right in a different circumstance i don't know but fred thinks it's right and steve thinks everyone around you seems to think it's right and so um part of the maybe downside of having a live wired brain is that you can get crowds of people doing things um as a group so it's interesting to you know we would pinpoint hitler saying that's the evil guy but in a sense i think it was tolstoy you said the the king becomes um slave to the to the people in other words you know hitler was just a representation of whatever was going on with that huge crowd that he was surrounded with so um so i only bring that up to say that it's you know it's very difficult to say what it is about this person's brain or that person's brain he obviously got feedback for what he was doing the other thing by the way about what we often think of as being evil in society is um my lab recently published some work on in groups and out groups which is a very important part of this puzzle so it turns out that we are very we are very you know engineered to care about in-groups versus out-groups and this seems to be like a really fundamental thing so we did this experiment lab where we brought people in we stick them in the scanner and we i don't know it's something if you know this but uh we show them on the hand sorry we showed them on the screen six hands and uh the computer boop goes around randomly picks a hand and then you see that hand gets stabbed with a syringe needle so you actually see a syringe needle enter the hand and come out and it's really uh what that does is that triggers uh parts of the pain matrix this areas in your brain that involved in feeling physical pain now the interesting thing is it's not your hand that was stabbed so what you're seeing is is empathy this is you seeing someone else's hand get stabbed you feel like oh god this is awful right okay um we contrast that by the way with somebody's hand getting poked as a q-tip which is you know looks visually the same but it's um you don't have that same level of response now what we do is we label each hand with a with a one word label christian jewish muslim atheist scientologist hindu and now the computer goes around picks a hand stabs the hand and the question is how much does your brain care about all the people in your out group versus the one label that happens to match you and it turns out for everybody across all religions they care much more about their in group than their accurate and when i say they care what i mean is you get a bigger response from their brain everything's the same it's the same hands it's just a one-word label you care much more about your in-group than your outgroup and i wish this weren't true but this is how humans are i wonder how fundamental that is or if it's a it's the emergent thing about culture like if we lived alone with like if it's genetically built into the brain like this this longing for tribe so i'll so i'll tell you we addressed that so here's what we did there are two [Music] actually there are two other things we did as part of this study that i think matter for this point one is so okay so we show that you have a much bigger response by the way this is not a cognitive thing it's a very low level basic response to seeing pain in somebody okay great study by the way thanks thanks what we did next is we we next have it where we say okay the year is 2025 and these three religions are now in a war against these three religions and it's all randomized right but what you see is your thing and you have two allies now against these others and now it happens over the course of many trials you see everybody gets stabbed at different times and the question is do you care more about your allies and the answer is yes suddenly people who a moment ago you didn't really care when they got stabbed now simply with this one word thing that you're they're now your allies you care more about them but then what i wanted to do was look at how ingrained is this or how arbitrary is it so we brought new participants in and we said here's a coin toss the coin if it's heads you're an augustinian if it's a tails you're a justinian these are totally made up okay so they toss it they get whatever we give them a a ban that says you know augustinian on it whatever tribe they're in now um and they get in the scanner and they see a thing on the screen that says the augustinians and justinians are two warring tribes then you see a bunch of hands some are labeled augustine some are justinian and now you care more about whichever team you're on than the other team even though it's totally after and you know is arbitrary because you're the one to toss the coin yeah so it's it it's a state that's very easy to find ourselves in in other words just before walking in the door they'd never even heard of augustinian versus justinian and now their brain is representing it simply because they're told they're on this team you know uh now i did my own personal study of this uh it's uh so once you're an augustinian that tends to be sticky because i've been a packers fan uh going back pakistan my whole life now when i'm in boston with like the the patriots it's been tough going for my livewire brain to switch to the patriots to be so once you become it's it's interesting once the tribe is sticky yeah oh but that's true that's that's it you know you know we never tried that about saying okay now you're adjusting the enemy we're in august how sticky it is but there are studies of this of monkey troops uh on some island um and what happens is they look at the way monkeys behave when they're part of this tribe and how they treat members of the other tribe of monkeys and then what they do i forgotten how they do that exactly but they end up switching a monkey so he ends up in the other troop and very quickly they end up becoming a part of that other troop and and hating and behaving badly towards their original troop these are fascinating studies by the way yeah this is this is beautiful uh in your in your book you have uh you have a good light bulb joke uh how many psychiatrists does it take to change a light bulb only one but the light bulb has to want to change i'm sorry i'm a sucker for a good light bulb okay so given uh you know i've been interested in psychiatry uh my whole life just maybe tangentially i've kind of early on dream to be a psychiatrist until i understood what it entails uh but you know what um you know is there hope for psychiatry for somebody else to help this live wired brain to adjust oh yeah i mean in the sense that and this has to do with this issue about us being trapped on our own planet forget psychiatrists just think of like when you're talking with a friend and you say oh i'm so upset about this and your friend says hey just look at it this way uh you know all we have access to under normal circumstances is just the way we're seeing something and so it's super helpful to have friends and communities and psychiatrists and so on to help things change that way so that's just like interesting of help to us but but more importantly the role that psychiatrists have played is that there's this sort of naive assumption that we all come to the table with which is that everyone is fundamentally just like us and when you're a kid you you believe this entirely but as you get older and you start realizing okay there's something called schizophrenia and that's a real thing and to be inside that person's head is totally different than what it is to be inside my head or their psychopathy and and to be inside this psychopath's head he doesn't care about other people he doesn't care about hurting other people he's just doing what he needs to do to get what he needs um that's a different head there's a million different things going on and it is different to be inside those heads that this is where the field of psychiatry comes in now i think it's an interesting question about the degree to which is leaking into and taking over psychiatry and what the landscape will look like 50 years from now it may be that psychiatry as a profession you know changes a lot or maybe goes away entirely and neuroscience will essentially be able to take over some of these functions but it has been extremely useful to understand the differences between how people behave and why and what you can tell about what's going on inside their brain just based on observation of their behavior you uh this this might be years ago but i'm not sure there's an atlantic article you've written about moving away from a distinction between neurological disorders unquote brain problems and psychiatric disorders or quote unquote mind problems so so on that topic how do you think about this gray area yeah this is exactly this is exactly the evolution that things are going is you know there was psychiatry and then there were guys and gals in labs poking cells and so on those are the neurosciences but yeah i think these are moving together for exactly the reason you decided and where this matters a lot the atlantic article uh that i wrote was called the brain on trial where this matters a lot is it's the legal system because the way we run our legal system now and this is true everywhere in the world is you know someone shows up in front of the judge's bench or let's say there's five people in front of the judge's bench and they've all committed the same crime what we do because we feel like hey this is fair is alright you're gonna get the same sentence you'll all get three years in prison or whatever it is but in fact brains can be so different this guy's got schizophrenia this guy's a psychopath this guy's tweaked down on drugs and so on so that um it actually doesn't make sense to keep doing that and what we what we do in this country more than anywhere in the world is we imagine that incarceration is a one-size-fits-all solution and you may know we have the america has the highest incarceration rate in the whole world in terms of the percentage of our population we put behind bars so um there's a much more refined thing we can do as neuroscience comes in and changes and has the opportunity to change the legal system which is to say this doesn't let anybody off the hook it doesn't say oh it's not your fault and so on but what it does is it changes the equation so it's not about hey how blameworthy are you but instead is about hey what do we do from here what's the best thing to do from here so if you take somebody with schizophrenia and you have them break rocks in the hot summer sun in a chain gang all yeah that that doesn't help the schizophrenia that doesn't fix the problem um if you take somebody with a drug addiction who's in jail for you know being caught two ounces of some illegal substance and you put him in prison it doesn't actually fix the addiction it doesn't help anything happily what neuroscience and psychiatry bring to the table is lots of really useful things you can do with schizophrenia with drug addiction things like this um and that's why so i i don't know if he knows but i run a national non-profit called the center for science and law and it's all about this intersection of neuroscience and legal system and we're trying to implement changes in every county and every state um i'll just without going down that rabbit hole i'll just say one of the very simplest things to do is to set up specialized court systems where you have a mental health court that has judges and juries with expertise in mental illness because if you go by the way to a regular court and the person says um or the the defense lawyer says this person is schizophrenia most of the jury will say man i call bullshit on that why because they don't know about because they don't they don't know what it's about and it turns out people who who know about schizophrenia feel very differently as a juror than someone who happens not to know anybody schizophrenia they think it's an excuse so um you have judge injuries with expertise in mental illness and they know the rehabilitative strategies that are available that's one thing having a drug court where you have judges and jurors with expertise and rehabilitative strategies and what can be done and so on a specialized prostitution core and so on all these different uh things by the way this is very easy for counties to implement this sort of thing and this is this is i think where this matters to get neuroscience into public policy what's the process of injecting expertise into this so yeah i'll tell you exactly what it is a county needs to run out of money first i've seen this happen over and over so what happens is a county has a completely full jail and they say you know what we need to build another jail and then they realize god we don't have any money we can't afford this we've got too many people in jail and that's when they turn to god we need something smarter and that's when they set up specialized court systems oh we all function best when when our back is against the wall and that's what kovit is good for yeah it's because we we've all had our routines and we are optimized for the things we do and suddenly our backs are against the wall all of us yeah it's really i mean one of the exciting things about uh kovet i mean i'm a big believer in the the possibility of what government can do for the people and uh when it becomes too big of a bureaucracy it starts functioning poorly starts wasting money it's nice to uh i mean covers and reveals that nicely and lessons to be learned about who gets elected and who goes into government hopefully this hopefully this inspires talented and young people to go into government to revolutionize different aspects of it yeah so it's uh this that's the positive silver lining of of covid i mean i thought it'd be fun to ask you i don't know if you're paying attention to machine learning world and gpt3 so the gpt3 is this language model this neural network that's able to uh it has 175 billion parameters so it's very large and it's trained in an unsupervised way on the internet it just reads a lot of unstructured text and it's able to generate some pretty impressive things the human brain compared to that has about you know a thousand times more synapses people get so upset when machine learning people compare the brain and we know synapses are different it was very different very different right but like do you um what do you think about gpt3 here's what i think here's what i think a few things what gpt 3 is doing is extremely impressive but it's very different from what the brain does so um it's a good impersonator but just as one example everybody takes a passage that gpt three has has written and they say wow look at this and it's pretty good right but it's already gone through a filtering process of humans looking at it and saying okay well that's crap that's correct okay oh here's here's a sentence that's pretty cool now here's the thing human creativity is about absorbing everything around it and remixing that and coming up with stuff so in that sense we're sort of like gpt3 you know we're we're remixing what we've gotten in before but we also know we also have very good models of what it is to be another human and so um you know i don't know if you speak uh french or something but i'm not gonna start speaking in french because then you'll say wait what are you doing i don't understand it instead everything coming out of my mouth is meant for your ears i know what you'll understand i know the vocabulary that you know and don't know i know what parts you care about that's a huge part of it and so of all the possible sentences i could say i'm navigating this thin bandwidth so that it's something useful for our conversation yeah in real time but also throughout your life i mean you're you're coval we're co-evolving together we're learning exactly how to uh communicate together exactly but this is this is what gpt does not do all it's doing is saying okay i'm gonna take all these senses and remix stuff and pop some stuff out but it doesn't know how to make it so that you lex will feel like oh yeah that's exactly what i needed to hear um that's the next sentence that i needed to know about for something well of course it could be all the impressive results we'll see the question is when if you raise the number of parameters whether it's going to be after something it will not be it will not be no raising more parameters won't here's the thing it's not that i don't think neural networks can't be like the human brain as i suspect they will be at some point 50 years you know who knows but what we are missing in artificial neural networks is we've got this basic structure where you've got units and you've got synapses they're connected and and that's great and it's done incredibly mind-blowing impressive things but it's not doing the same algorithms as a human brain so when i look at my children as little kids as infants they can do things that no gpt3 can do they can navigate a complex room they can navigate social conversation with an adult um they can lie they can do a million things they they are active thinkers in our world and doing things and this of course i mean look we totally agree on in how incredibly awesome artificial neural networks are right now but we also know the things that they can't do well like you know like be generally intelligent do all these different reasons reason about the world efficiently learn efficiently adapt exactly but it's still the rate of improvement it's uh to me it's it's possible they'll be surprised like that but what i would what i would assert and then and i'm glad i'm going to say this on your podcast so we can look back at this in two years and 10 years is that we've got to be much more sophisticated than units and synapses between them let me give you an example and this is something i talk about in livewire is despite the amazing impressiveness mind-blowing impressiveness um computers don't have some basic things artificial neural networks don't have some basic things that we like caring about relevance for example so as humans we are confronted with tons of data all the time and we only encode particular things that are relevant to us we have this very deep sense of relevance that i mentioned earlier is based on survival at the most basic level but then all the things about my life and your life what's relevant to you that we encode um this is very useful computers at the moment don't have that they don't have a yen to survive and things like that so we filter out a bunch of the junk we don't need we're really good at efficiently zooming into the things we need again could be argued you know let me put on my freud hat maybe it's uh i mean that's our conscious mind uh you know we're not you know there's no reason that neural networks aren't doing the same kind of filtration i mean in the sense what gpt3 is doing so there's a priming step it's doing an essential kind of filtration when you ask it to generate tweets from from i don't know from from an elon musk or something like that it's doing a filtration of it's throwing away all the parameters it doesn't need for this task and it's figuring out how to do that successfully and then ultimately it's not doing a very good job right now but it's doing a lot better job than we expected but it won't ever do a really good job and i'll tell you why i mean so so let's say we say hey produce an elon musk tweet and we see like oh wow it produced these three that's great but again it's not we're not seeing the three thousand that produce that didn't really make any sense it's because it has no idea what it is like to be a human and all the things that you might want to say and all the reasons you wouldn't like when you go to write a tweet you might write something yeah it's not going to come off quite right in this modern political climate or whatever like you know you can change things so and it somehow boils down to fear and mortality and all of these human things at the end of the day all contained with that tweeting experience well interestingly the fear of mortality is at the bottom of this but you've got all these more things like you know oh i want to just in case the chairman of my department reads this i wanted to come off there just in case my mom looks at this tweet i want to make sure she you know and so on so that those are all the things that humans are able to sort of throw into the calculation but i mean uh what it required what it requires though is having a model of your chairman having a model of your mother having a model of the you know the person you want to go on a date with who might look at your tweet and so on all these things are uh you're running the reason about what it is like to be them so in terms of the structure of the brain again this may be going into speculation land i hope you go along with me is uh okay so the brain seems to be intelligent and our ai systems aren't very currently so where do you think intelligence arises in the brain like what what is it about the brain so if you mean where location wise it's no single spot it would be equivalent to asking i'm looking at new york city where is the economy the answer is you can't point to anywhere the economy is all about the interaction of all of the pieces and parts of the city and that's what you know intelligence whatever we mean by that in the brain is interacting from everything going on at once in terms of a structure so we look humans are much smarter than fish maybe not dolphins but dolphins are mammals right but i assert that what we mean by smarter has to do with live wiring so so what we mean when we say oh we're smarter is oh you can figure out a new thing and figure out a new pathway to get where we need to go and that's because fish are essentially coming to the table with you know okay here's the hardware go swim mate eat but we have the capacity to say okay look i'm gonna absorb oh oh but you know i saw someone else do this thing and and i read once that you could do this other thing and so on so do you think there's is there something i know the these are mysteries but like architecturally speaking what feature of the brain of uh of the live wire aspect of it that is really useful for intelligence so like is it the ability of neurons to reconnect like is there something is there any lessons about the human brain you think might be inspiring for us and to take into the artificial into the machine learning world yeah i'm actually just trying to write some up on this now called you know if you want to build a robot start with the stomach and what i mean by that what i mean by that is a robot has to care it has to have hunger it has to care about surviving that kind of thing here's an example so the penultimate chapter in my book um i titled the the wolf in the mars rover and i just look at this simple comparison of you look at a wolf it gets its leg caught in a trap what does it do it gnaws its leg off and then it figures out how to walk on three legs no problem now the mars rover curiosity got its front wheel stuck in some martian soil and it died this project that cost billions of dollars died because guys wheels so wouldn't it be terrific if we could build a robot that chewed off its front wheel and figured out how to operate with a slightly different body plan that's the kind of thing that we want to be able to build and to get there what we need the whole reason the wolf is able to do that is because its motor and somatosensory systems are live wired so it says oh you know what turns out i've got a body plan that's different than what i thought a few minutes ago but i i have a yen to survive and i care about relevance which in this case is getting to food getting back to my pack and so on so i'm just gonna figure out how to operate with this oh oops that didn't work oh okay i'm kind of getting it to work but the mars rover doesn't do that it just says oh geez i was pre-programmed to have four wheels and i have three i'm screwed yeah you know i i don't know if you're familiar with a philosopher named ernest becker he wrote a book called denial of death and there's a few psychologists sheldon solomon i think he i just spoke with him on his podcast who developed terror management theory which is uh like ernest becker is a philosopher that basically said that uh mortality fear of mortality is at the core of it yeah and so i i don't know if it sounds compelling as an idea that we're all i mean that all of the civilization we've constructed is based on this but it's i'm familiar with his work here's what i think i think that yes fundamentally this desire to survive is at the core of it i would agree with that but but how that expresses itself in your life it ends up being very different the reason you do what you do is i mean you could list the 100 reasons why you chose to write your tweet this way and that way and it really has nothing to do with the survival part it has to do with you know trying to impress fellow humans and surprise them and say something yeah so many things built on top of each other but it's it's fascinating to think that in artificial intelligence systems we want to be able to somehow engineer this drive for survival for immortality i mean because as humans we're not just about survival we're aware of the fact that we're going to die which is a very kind of where we're like space-time by the way aren't all right confucius said uh he said each person has two lives the second one begins when you realize that you have just one yeah but but most people it takes a long time for most people to get there i mean you could argue this kind of freudian thing which ernest becker uh argues is they it's they they actually figured it out early on and the terror they felt was like the reason it's been suppressed and the reason most people when i ask them about whether they're afraid of death they basically say no they basically say like um i'm afraid i won't get like submit the paper before i die like they kind of see they see death as a kind of uh inconvenient deadline for a particular set of like a book you're writing yeah it's as opposed to like what the hell this thing ends this at any moment like most people as if i have encountered do not meditate on the idea that like right now you could die like right now like it it's like it in in the next five minutes it could be all over and you know meditate on that idea i think that somehow brings you closer to like the core of the motivations and the core of the human cognition condition but like i said it is not yeah there's so many things on top of it but it is interesting i mean as the ancient poet said uh death whispers at my ear live for i come so it's it is certainly motivating when we think about that okay i've got some deadline i don't know exactly what it is but i better make stuff happen it is motivating but i don't think uh i mean i know for just speaking for me personally that's not what motivates me day to day it's instead oh i want to get this you know program up and running before this or i want to make sure my co-author isn't mad at me because i haven't gotten this in there i don't want to miss this grant deadline or you know whatever the thing is yeah it's too it's too distant in a sense nevertheless it is good to reconnect but for the ai systems none of that is there uh like a neural network does not fear it's mortality uh and that that seems to be somehow fundamentally missing the point i think that's missing the point but i wonder it's an interesting speculation about whether you can build an ai system that is much closer to being a human without the mortality and survival piece but just the thing of relevance just i care about this versus that right now if you have a robot roll into the room it's going to be frozen because it doesn't have any reason to go there versus there it doesn't have any particular set of things about this is how i should navigate my next move because i want something yeah there's a that's the thing about humans is they seem to generate goals they're like you said live wired i mean it it's very flexible in terms of the goals and creative in terms of the goals you generate when we enter a room you show up to a party without a goal usually and then you figure it out alone yes but this goes back to the question about free will which is when i walk into the party if you rewound it 10 000 times would i go and talk to that couple over there versus that person like i might do this exact same thing every time because i've got some goal stack and i think okay well at this party i really want to meet these kind of people or i feel awkward or i whatever you know whatever my goals are by the way so there was something that i meant to mention earlier if you don't mind going back which is this when we were talking about bci um so i don't know if you know this but what i'm spending ninety percent of my time doing now is running a company do you know about this yes i wasn't sure what the company is involved in right so talk about it yeah yeah so when it comes to the future of bci um you know you can put stuff into the brain invasively but my interest has been how you can get data streams into the brain non-invasively so i run a company called neosensory and what we build is this little um wristband we've built this in many different oh wow that's it yeah this is it and it's got these vibratory motors in it so these things as i'm speaking for example it's you know capturing my voice and running algorithms and then turning that into patterns of vibration here so people who are deaf for example learn to hear through their skin so the information is getting up to their brain this way and they learn how to hear so it turns out on day one people are pretty good like better than you would expect at being able to say oh that's weird it was that was that a dog barking was that a baby crying was that a door knock a doorbell like people are pretty good at it but with time they get better and better and what it becomes is a new qualia in other words a new subjective internal experience so on day one they they say whoa what was that oh oh that was the dog barking but by you know three months later they say oh there's dog barking somewhere oh there's the dog that's fascinating and by the way that's exactly how you learn how to use your ears so what you of course need to remember this but when you're an infant all you have are you know your eardrum vibrating causes spikes to go down your auditory nerves and impinging your you know auditory cortex your brain doesn't know what those mean automatically but what happens is you learn how to hear by looking for correlations you know you clap your hands as a baby you know you look at your mother's mouth moving and and that correlates with what's going on there and eventually your brain says i'm just going to summarize this as an internal experience as a conscious experience and that's exactly what happens here the weird part is that you can feed data into the brain not through the ears but through any channel that gets there as long as the information gets there your brain figures out what to do with it that's fascinating like expanding the set of sensors it could be could be arbitrarily uh could could it could yeah it could expand arbitrarily which is fascinating well exactly and by the way the reason i use this skin you know there's all kinds of cool stuff going on in the ar world class but the fact is your eyes are overtaxed and your ears are overtaxed and you need to be able to see and hear other stuff but you're covered with the skin which is this incredible computational material with which you can feed information and we don't use our skin for much of anything nowadays um my joke in the lab is that i say we don't call this the waste for nothing because originally we built as the vest and you know you're passing in all this information um that way and um what i'm doing here with with the deaf community is is what's called sensory substitution where i'm capturing sound and scent you know i'm just replacing the ears with the skin and that works um one of the things i talk about in livewire is sensory expansion so what if you took something like your your visual system which picks up on a very thin slice of the electromagnetic spectrum and you could see infrared or ultraviolet so we've hooked that up infrared and ultraviolet detectors and you know i can feel what's going on so just as an example the first night i built the infrared one of my engineers built at the infrared detector i was walking in the dark between two houses and suddenly i felt all this infrared radiation i was like where does that come from and i just followed my wrist and i found a um an infrared camera a night vision camera that was but like you know i immediately oh there there's that thing there but of course i would have never seen it but now it's just part of my reality that's fascinating yeah and then of course what i'm really interested in is sensory addition what if you could pick up on stuff that isn't even part of what we normally pick up on like you know like the magnetic field of the earth or twitter or stock market or things like that or the i don't know some weird stuff like the moods of other people or something like that sure now what you need is a way to measure that so as long as there's a machine that can measure it it's easy it's trivial to feed this in here and you come to be it comes to be part of your reality it's like you have another sensor and that that kind of thing is without doing like if you look in your link without i forgot how you put it but it was eloquent you know without getting cutting into the brain basically yeah exactly exactly so this this costs at the moment 399 dollars that's not going to kill you and yeah it's not going to kill you it's you just put it on and when you're done you take it off yeah um yeah and so uh and the name of the company by the way is neo sensory for new senses because the whole idea is beautiful you can as i said you know you come to the table with certain plug and play devices and then that's it like i can pick up on this little bit of the electromagnetic radiation you can pick up on on this little frequency band for hearing and so on but but but i'm stuck there and there's no reason we have to be stuck there we can expand our oom velt by adding new senses yeah what's um oh i'm sorry the umvelt is the slice of reality that you pick up on so each animal has its own hell of a word umvelt yeah exactly so i'm sorry i forgot to define it before it's it's it's such an important concept which is to say um for example if you are a a tick you pick up on uh butyric acid you pick up on odor and you pick up on temperature that's it that's how you construct your reality is with those two sensors if you are a blind echolocating bat you're picking up on air compression waves coming back you know echolocation if you are the black ghost knife fish you're picking up on changes in the electrical field around you with electro reception that's how they swim around and tell there's a rock there and so on but but that's that's all they pick up on that's their umvelt it's that's their the signals they get from the world from which to construct their reality and they can be totally different ooh belts and so our human umvelt is you know we've got little bits that we can pick up on one of the things i like to do with my students is talk about um imagine that you are a bloodhound dog right you are a blendhead dog with a huge snout with 200 million scent receptors in it and your whole world is about smelling you know you've got slits in your nostrils like big nose fulls of air and so on do you have a dog do you nope you used to used to okay so you know you walk your dog around and your dog is smelling everything the whole world is full of signals that you do not pick up on it so imagine if you were that dog and you looked at your human master and thought my god what is it like to have the pitiful little nose of a human yeah how could you not know that there's a cat 100 yards away or that your friend was here six hours ago and so the idea is because we're stuck in our own belt because we have this little pitiful noses we think okay well yeah we're seeing reality but but you can have very different sorts of realities depending on the peripheral plug-and-play devices you're equipped with it's fascinating to think that like if we're being honest probably our own belt is uh you know some infinitely tiny percent of the possibilities of how you can sense quote unquote reality even if you could i mean there's a guy named don uh donald uh hoffman yeah who based basically says uh we're really far away from reality in terms of our ability to sense anything like we we're very we're almost like we're floating out there that's almost like completely attached to the actual physical reality it's fascinating that we could have extra senses that could help us get a little bit a little bit closer exactly and by the way this has been the the fruits of science is realizing like for example you know you open your eyes and there's the world around you right but of course depending on how you calculate it it's less than a 10 trillion of the electromagnetic spectrum that we call visible light uh the reason i say it depends because you know it's actually infinite in all directions yeah and so that's exactly that and then science allows you to actually look into the rest of it exactly start understanding how big the world is out there and the same with the the world of really small and the world of really large exactly that's beyond our ability to sense exactly and so the reason i think this kind of thing matters is because we now have an opportunity for that first time in human history to say okay well i'm just going to include other things in my umvelt so i'm going to include infrared radiation and and have a direct perceptual experience of that and so i'm very you know i mean so you know i've given up my lab and i run this company 90 of my time now that's what i'm doing i still teach at stanford and i'm you know teaching courses and stuff like that but this is like this is your your passion the fire is as on this yeah i feel like this is the most important thing that's happening right now i mean obviously i think that because that's what i'm devoting my time and my life to but i mean it's a brilliant set of ideas it certainly is like it uh it's a step in uh in a very vibrant future i would say like that the possibilities there are are endless exactly so if you ask what i think about neural link i think it's amazing what those guys are doing and working on but i think it's not practical for almost everybody for example for people who are deaf they buy this and you know every day we're getting tons of emails and tweets or whatever from people saying wow i picked up on this and then i had no idea that was a i didn't even know that was happening out there yeah they're coming to here dude by the way this is you know less than a tenth of the price of a hearing aid and like 250 times less than a cochlear implant that's amazing uh people love hearing about uh what you know brilliant folks like yourself uh could recommend in terms of books of course you're an author of many books so i'll in the introduction mention all the books you've written people should definitely read live wired i've gotten a chance to read some of it it's amazing but is there three books technical fiction philosophical that had an impact on you when you were younger or today and books perhaps some of which you would uh want to recommend that others read ah you know as an undergraduate i majored in british american literature that was my major because i loved literature i grew up with literature my father had these extensive bookshelves and so i grew up in the mountains in new mexico and so that was mostly where i spent my time was reading books but um you know i love uh you know faulkner hemingway i love many south american authors gabriel garcia marquez and italo calvina i would actually recommend invisible cities i just i loved that book by italo calvino sorry it's a book of fiction um uh anthony door wrote a book called all the light we cannot see which actually uh was inspired by incognito by exactly what we were talking about earlier about how you can only see a little bit of the what we call visible light in the electromagnetic radiation i wrote about this in incognito and then he reviewed incognito for the washington oh no that's awesome and then he wrote this book the book has nothing to do with that but that's where the title comes from yeah all the light we cannot see is about the rest of the spectrum but um the that's a absolutely gorgeous book jesus that's the book of fiction yeah it's a book of fiction what's it about it takes place during world war ii uh about these two young people one of whom is blind and yeah anything else so any so you mentioned hemingway i mean uh old man the sea what uh what's your favorite uh um snows of kilimanjaro uh oh wow short stories that i love um as far as not as far as nonfiction goes i grew up uh with cosmos both watching the pbs series and then reading the book and that influenced me a huge amount in terms of what i do i as from the time i was a kid i felt like i want to be carl sagan like i just that's what i loved and in the end i just you know i studied space physics for a while as an undergrad but then i in my last semester discovered neuroscience last semester and i just thought well i'm hooked on that so the carl sagan of the brain is the aspiration yeah i mean uh you're doing you're doing um an incredible job of it so you open the book livewire with a quote by heidegger every man is born as many men and dies as a single one well what do you mean or what i'll tell you what i meant by it yeah i'll tell you so he he had his own reason why he was writing that but i meant this in terms of brain plasticity in terms of the library which is this issue that i mentioned before about this yeah this cone the space time cone that we are in which is that when you dropped into the world you lex had all this different potential you could have been a great surfer or a great chess player or you could have been thousands of different men when you grew up but what you did is things that were not your choice and your choice along the way you know you ended up navigating a particular path and now you're exactly who you are you still have lots of potential but the day you die you will be exactly lex you will be one person yeah so on that in that context i mean first of all it's just a beautiful it's a humbling picture but it's a beautiful one because that's uh all the possible trajectories and you pick one you walk down that road it's the robert frost poem but on that topic let me ask the the biggest and the most ridiculous question so in this live wide brain when we choose all these different trajectories and end up with one what's the meaning of it all what's uh is there is there a why here what's the meaning of life yeah david engelman that's it i mean this is the question that everyone has attacked from their own lifewire point of view by which i mean culturally if you grow up in a religious society you have one way of attacking that questions on if you grow up in a secular scientific society you have a different way of attacking that question obviously i i don't know i abstain on that question i mean i think one of the fundamental things i guess in that in all those possible trajectories is uh you're always asking i mean that's the act of asking what the heck is this thing for is equivalent to or at least runs in parallel to all the choices that you're making because it's kind of that's the underlying question well that's right and by the way you know this is the interesting thing about human psychology we've got all these layers of things at which we can ask questions and so if you keep asking yourself the question about what is the optimal way for me to be spending my time what should i be doing what charity should i get involved with and so on if you're asking those big questions that that steers you appropriately if you're the type person who never asks hey is there something better i could be doing with my time then presumably you won't optimize whatever it is that is important to you so you've uh i think just in your eyes in your work there's a passion uh that just is obvious and it's inspiring it's contagious what um if you were to give advice to us a young person today in the crazy chaos that we live today about life about how to how to uh how to discover their passion is there some words that you could give first of all i would say the main thing for a young person is stay adaptable and and this is back to this issue of why covet is useful for us because it forces us off our tracks the the fact is the jobs that will exist 20 years from now we don't even have names for we can't even imagine the jobs that exist and so when young people that i know go into college and they say hey what should i major in and so on college is and should be less and less vocational as in oh i'm going to learn how to do this and then i'm going to do that the rest of my career the world just isn't that way anymore with the the exponential speed of things so the important thing is learning how to learn learning how to be live wired and adaptable that's really key and what i tell what i advise young people when i talk to them is you know what you digest that that's what gives you the raw storehouse of things that you can remix and and be creative with and so eat broadly and widely and and obviously this is the wonderful thing about the internet world we live in now is you kind of can't help it you're constantly whoa you know you go down some mole hole of wikipedia and you think oh i didn't even realize that it was a thing i didn't know that existed and so embrace that embrace that yeah exactly and what i tell people is just always do a gut check about okay i'm reading this paper and yeah i think that but this paper wow that really i really cared about that in some way i tell them just keep a real sniff out for that and when you find those things keep going down those paths yeah don't be afraid i mean that that's one of the the challenges and the downsides of having so many beautiful options is that uh sometimes people are a little bit afraid to really commit but that that's very true if if there's something that just sparks yeah your interest and passion just run with it i mean that's it goes back to the hydera quote um i mean we only get this one life and that trajectory it does it doesn't last forever so just if something sparks your imagination your passion is wrong with it yeah exactly i don't think there's a more uh beautiful way to end it david it's a huge honor to finally meet you your work is inspiring so many people i've talked to so many people who are passionate about neuroscience about the brain even outside that uh read your book so i hope uh i hope you keep doing so i i think you're already there with carl sagan i hope you continue growing um yeah it was honor talking today thanks so much great you too lex wonderful thanks for listening to this conversation with david eagleman and thank you to our sponsors athletic greens betterhelp and cash app click the sponsor links in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from david eagleman in his book some for details from the afterlife imagine for a moment there were nothing but the product of billions of years of molecules coming together and ratcheting up to natural selection that were composed only of highways of fluids and chemicals sliding along roadways within billions of dancing cells the trillions of synaptic connections hum in parallel that this vast egg-like fabric of micro thin circuitry runs algorithms undreamt of in modern science that these neural programs give rise to our decision making loves desires fears and aspirations to me understanding this would be a numinous experience better than anything ever proposed in any holy text thank you for listening and hope to see you next time you |
Grant Sanderson: Math, Manim, Neural Networks & Teaching with 3Blue1Brown | Lex Fridman Podcast #118 | the following is a conversation with grant sanderson his second time on the podcast he's known to millions of people as the mind behind three blue one brown a youtube channel where he educates and inspires the world with the beauty and power of mathematics quick summary of the sponsors dollar shave club doordash and cash app click the sponsor links in the description to get a discount and to support this podcast especially for the two new sponsors dollar shave club and doordash let me say as a side note i think that this pandemic challenged millions of educators to rethink how they teach to rethink the nature of education as people know grant is a master elucidator of mathematical concepts that may otherwise seem difficult or out of reach for students and curious minds but he's also an inspiration to teachers researchers and people who just enjoy sharing knowledge like me for what it's worth it's one thing to give a semester's worth of multi-hour lectures it's another to extract from those lectures the most important interesting beautiful and difficult concepts and present them in a way that makes everything fall into place that is the challenge that is worth taking on my dream is to see more and more of my colleagues at mit and world experts across the world summon their inner three blue one brown and create the canonical explainer videos on a topic that they know more than almost anyone else in the world amidst the political division the economic pain the psychological medical toll of the virus masterfully crafted educational content feels like one of the beacons of hope that we can hold on to if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman of course after you go immediately which you already probably have done a long time ago and subscribe to three blue one brown youtube channel you will not regret it as usual i'll do a few minutes of as now and no ads in the middle i try to make these interesting but i give you timestamps so you can skip but still please do check out the sponsors by clicking the links in the description especially the two new ones doordash and dollar shave club they're evaluating us looking at how many people go to their site and get their stuff in order to determine if they want to support us for the long term so you know what to do it's the best way to support this podcast as always this show is sponsored by a dollar shave club try them out with a one-time offer for only five dollars in free shipping at dollarshaveclub.com lex starter kit comes with a six blade razor refills and all kinds of other stuff that makes shaving feel great i've been a member of dollar shave club for over five years now and actually signed up when i first heard about them on the joe rogan podcast and now we have come full circle i feel like i've made it now that i can do a read for them just like joe did all those years ago for the most part i've just used the razor and refills but they encouraged me to try the shave butter which i've never used before so i did and i love it i'm not sure how the chemistry of it works out but it's translucent somehow which is a cool new experience again try the ultimate shave starter set today for just five bucks plus free shipping at dollarshaveclub.com lex this show is also sponsored by doordash get five bucks off and zero delivery fees on your first order of fifteen dollars or more when you download the doordash app and enter code lex i have so many memories of working late nights for deadline with a team of engineers and eventually taking a break to argue about which door dash restaurant to order from and when the food came those moments of bonding of exchanging ideas of pausing to shift attention from the programs to the humans or special these days for a bit of time i'm on my own sadly so i miss that camaraderie but actually doordash is still there for me there's a million options that fit into my keto diet ways also it's a great way to support restaurants in these challenging times once again download the doordash app and enter code lex to get five bucks off as your delivery fees on your first order of 15 or more finally this shows presented by cash app the number one finance app in the app store when you get it use collects podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar it's one of the best design interfaces of an app that i've ever used to me good design is when everything is easy and natural that design is when the app gets in the way either because it's buggy because it tries too hard to be helpful i'm looking at you clippy anyway there's a big part of my brain and heart that love to design things and also to appreciate great design by others so again if you get cash app from the app store google play and use code lex podcast you get ten dollars and cash up will also donate ten dollars to first an organization that is helping you to advance robotics and stem education for young people around the world and now here's my conversation with grant sanderson you've spoken about richard feynman as someone you admire i think last time we spoke we ran out of time so i wanted to talk to you about him um who is uh richard feynman to you in your eyes what impact did he have on you i mean i think a ton of people like feynman he's probably it's a little bit cliche to say that you like fineman right that's um almost like when you don't know what to say about sports and you just point to the super bowl or something it's something you enjoy watching but i do actually think there's a layer to feynman that like sits behind the iconography one thing that just really struck me was this letter that he wrote to his wife two years after she died so during the manhattan project she had polio tragically she died they were just young madly in love and you know the the icon of feynman is this almost this like mildly sexist womanizing philanderer at least on the personal side but you read this letter and i can try to pull it up for you if i want and it's just this absolutely heartfelt letter to his wife saying how much he loves her even though she's dead and kind of what she means to him how no woman can ever measure up to her and it shows you that the fineman that we've all seen in like surely you're joking is different from the feynman in reality and i think the same kind of goes in his science where you know he kind of sometimes has this output of being this ah shucks character like everyone else is coming in this with these fancy flute and formulas but i'm just gonna try to whittle it down to its essentials which is so appealing because we love to see that kind of thing but when you get into it like what he was doing was actually quite deep very much mathematical um that should go without saying but i remember reading a book about feynman in a cafe once and this woman looked at me and was like uh saw that it was about findman she was like oh i love him i read shirley you're joking and she started explaining to me how he was never really a math person and uh i don't understand how that could possibly be a public perception about any physicist but for whatever reason that like worked into his or that he sort of shoot off math in place of true science the reality of it is he was deeply in love with math and was much more going in that direction and had a clicking point into seeing that physics was a way to realize that and all the creativity that he could output in that direction um was instead poured towards things like fundamental not even fundamental theories just emergent phenomena and everything like that so to answer your actual question like what what i like about uh his way of going at things is this constant desire to reinvent it for himself like when he would consume papers the way he described it he would start to see what problem he was trying to solve and then just try to solve it himself to get a sense of personal ownership and then from there see what others had done is that how you see problems yourself like that's actually an interesting point when you first are inspired by a certain idea that you maybe want to teach or visualize or just explore on your own i'm sure you're captured by some possibility and magic of it do you read the work of others like do you go through the proof see do you try to rediscover everything yourself so um i think the things that i've like learned best and have the deepest ownership of are the ones that have some element of rediscovery the problem is that really slows you down and this is for my for my part it's actually a big fault like this is part of why i'm i'm not an active researcher i'm not like at the depth of the field a lot of other people are the stuff that i do learn i try to learn it really well um but other times you do need to get through it at a certain pace you do need to get to a point of a problem you're trying to solve so obviously you need to be well equipped to read things uh without that reinvention component and see how others have done it but i think if you choose a few core building blocks along the way and you say i'm really going to try to approach this before i see how this person went at it i'm really going to try to approach it for myself no matter what you gain all sorts of inarticulatable intuitions about that topic which aren't going to be there if you simply go through the proof for example you're going to be trying to come up with counter examples you're going to try to come up with um intuitive examples all sorts of things where you're populating your brain with data and the ones that you come up with are likely to be different than the one that the text comes up with and that like lends it a different angle so that aspect also slowed feynman down in a lot of respects i think there was a period when like the rest of physics was running away from him um but in so far he's got it got him to where he was uh i i i kind of resonate with that i just i would i would be nowhere near it because i not like him at all but it's like a state to aspire to you know just to look at a small point you made that you're not a quote-unquote active researcher do you you're swimming often in reasonably good depth about a lot of topics do you sometimes want to like dive deep at a certain moment and say like because you probably built up a hell of an amazing intuition about what is and isn't true within these worlds do you ever want to just dive in and see if you can discover something new yeah i think one of my biggest regrets from undergrad is not having built better relationships with the professors i had there and i think a big part of success in research is that element of like mentorship and like people giving you the kind of scaffolded problems to carry along for my own like goals right now i feel like um i'm pretty good at exposing math to others and like want to continue doing that for my personal learning i are you familiar with like the hedgehog fox dynamic i think this was um either the ancient greeks came up with it or it was pretended to be something drawn from the ancient creek said i don't know who to point it to but they had probably mocked twain it is that you've got two types of people or especially two types of researchers there's the fox that knows many different things and then the hedgehog that knows one thing very deeply so like von neumann would have been a fox he's someone who knows many different things just very foundational a lot of different fields einstein would have been more of a hedgehog thinking really deeply about one particular thing and both are very necessary for making progress um so between those two i would definitely see myself as like the fox where uh i'll try to get my paws in like a whole bunch of different things and at the moment i just think i don't know enough of anything to make like a significant contribution to any of them but i do see value in um like having a decently deep understanding of a wide variety of things like most people who uh know computer science really deeply don't necessarily know physics very deeply or many of the aspects like different fields in math even let's say you have like an analytic number theory versus an algebraic number theory like these two things end up being related to very different fields like some of them more complex analysis some of them more like algebraic geometry and then when you just go out so far as to take those adjacent fields place one you know phd student into a seminar of another one they don't understand what the other one's saying at all like you take the complex analysis specialist inside the algebraic geometry seminar they're as lost as you or i would be but i think uh going around and like trying to have some sense of what this big picture is certainly has personal value for me i don't know if i would ever make like new contributions in those fields but i do think i could make new like expositional contributions where there's kind of a notion of uh things that are known but like haven't been explained very well well first of all i think most people would agree your videos your teaching the way you see the world is fundamentally often new like you're creating something new and it almost feels like research even just like the visualizations uh the multi-dimensional visualization we'll talk about i mean you're revealing something very interesting that uh yeah just feels like research feels like science feels like the cutting edge of the very thing of which like new ideas and new discoveries are made of i do think you're being a little bit more generous than is necessarily and i promise that's not even false humility because i sometimes think when i research a video i'll learn like 10 times as much as i need for the video itself and it ends up feeling kind of elementary um so i have a sense of just how far away like the stuff that i cover is from the actual depth i think that's natural but i think that could also be a mathematics thing i feel like in the machine learning world you like two weeks in you feel like you've basically mastered in mathematics it's like well everything is either trivial or impossible and it's like a shockingly thin line between the two where you can find something that's totally impenetrable and then after you get a feel for it's like oh yeah that whole that whole subject is actually trivial in some way so maybe that's what goes on every researcher is just on the other end of that hump and it feels like it's so far away but one step actually gets them there what do you think about sort of feynman's teaching style or another perspective is of use of uh visualization well his teaching style is interesting because people have described like the feynman effect where while you're watching his lectures or while he's reading his lectures everything makes such perfect sense so as an entertainment session it's wonderful because it gives you this this intellectual satisfaction that you don't get from anywhere else that you like finally understand it but the feynman effect is that you can't really recall what it is that gave you that insight you know even a week later and this is um this is true of a lot of books in a lot of lectures where the retention is never quite what we hope it is um so there is a risk that uh the stuff that i do also fits that same bill where at best it's giving this kind of intellectual candy on giving a glimpse of feeling like you understand something but unless you do something active like reinventing it yourself like doing problems um to solidify it um even things like space repetition memory to just make sure that you have like the building blocks of what do all the terms mean unless you're doing something like that it's not actually gonna stick so the very same thing that's so admirable about findman's lectures which is how damn satisfying they are to consume might actually also reveal a little bit of the flaw that we should as educators all look out for which is that that does not correlate with long-term learning we'll talk about it a little bit i think well you've done some interactive stuff i mean even in your videos the awesome thing that feynman couldn't do at the time is you could since it's programmed you can like tinker like play with stuff you could take this value and change it you can like here let's take the value of this variable and change it to build up an intuition to move along a surface or to to change the shape of something i think that's almost an equivalent of you doing it yourself it's not quite there but you as a viewer um yeah do you think there's some value in that interactive element yeah well so what's interesting is you're saying that and the videos are non-interactive in the sense that there's a play button and a pause button um and you could ask like hey while you're programming these things why don't you program it into an interactable version that you know make it a jupyter notebook that people can play with which i should do and that like would be better i think the thing about interactives though is most people consuming them just sort of consume what the author had in mind uh and that's kind of what they want like i have a ton of friends who make interactive explanations and when you look into the analytics of how people use them there's a small sliver that genuinely use it as a playground to have experiments and maybe that small sliver is actually who you're targeting and the rest don't matter but most people consume it just as a piece of um like well-constructed literature that maybe you tweak with the example a little bit to see what it's getting at but in that way i do think like a video can get most of the benefits of the interactive like the interactive um app as long as you make the interactive for yourself and you decide what the best narrative to spin is as a more concrete example like my process with i made this video about um sir models for epidemics and it's like this agent-based bottling thing where you tweak some things about how the epidemic spreads and you want to see how that affects its evolution um my my uh format for making that was very different than others where rather than scripting it ahead of time i just made the playground and then i played a bunch uh and then i saw what stories there were to tell within that um yeah that's cool so your video had that kind of structure it had uh like five or six stories or whatever it was and like it was basically okay here's a simulation here's a model what can we discover with this model and here's five things i found after playing with it well because here the thing is a way that you could do that project is you make the model and then you put it out and you say here's a thing for the world to play with like come to my website where you interact with this thing um and and people did like sort of remake it in a javascript way so that you can go to that website and you can test your own hypotheses but i think a meaningful part of the value to add is not just the technology but to give the story around it as well and like that's kind of my job it's not just to like make the uh the visuals that someone will look at it's to be the one to decide what's the interesting thing to walk through here um and even though there's lots of other interesting paths that one could take that can be kind of daunting when you're just sitting there in a sandbox and you're given this tool with like five different sliders and you're told to like play and discover things it's like where do you do what do you start what are my hypotheses what should i be asking like a little bit of guidance in that direction can be what actually sparks curiosity to make someone want to imagine more about it a few videos i've seen you do i don't know how often you do it but there's almost a tangential like pause where you here's a cool thing you say like here's a cool thing but it's outside the scope of this video essentially but i'll leave it to you as homework essentially to like figure out it's a cool thing to explore i wish i could say that wasn't a function of laziness right and that's like you've worked so hard on uh making the 20 minutes already that to extend it out even further it would take more time and one of your cooler videos the homomorphic like from the mobius strip to the described rectangle yeah that's the super and you're like yeah you can't uh you can't transform the mobius strip into uh into a surface without it intersecting itself but i'll leave it to you to to see why that is i hope that's not exactly how i phrase it because i think what my hope would be is that i leave it to you to think about why you would expect that to be true and then to want to know what aspects of a mobius strip do you want to formalize such that you can prove that intuition that you have because at some point now you're starting to invent algebraic topology if uh you have these vague instincts like i want to get this mobius strip i want to fit it such that it's all above the plane but its boundary sits exactly on the plane i don't think i can do that without crossing itself but that feels really vague how do i formalize it and as you're starting to formalize that that's what's going to get you to try to come up with a definition for what it means to be orientable or not orientable and like once you have that motivation a lot of the otherwise arbitrary things that are sitting at the very beginning of a topology textbook start to make a little more sense yeah and i mean that that whole video beautifully was a motivation for topology is cool that was my well my hope with that is i feel like topology is um i don't want to say it's taught wrong but i do think sometimes it's popularized in the wrong way where uh you know you'll hear these things of people saying oh topologists they're very interested in surfaces that you can bend and stretch but you can't cut or glue are they why yeah there's all sorts of things you can be interested in with random like imaginative manipulations of things is that really what like mathematicians are into and the short answer is not not really that's uh it's not as if someone was sitting there thinking like i wonder what the properties of clay are if i had some arbitrary rules about what when i can't cut it and when i can't glue it instead it's there's a ton of pieces of math that can actually be equivalent to like these very general structures that's like geometry except you don't have exact distances you just want to maintain a notion of closeness and once you get it to those general structures constructing mappings between them translate into non-trivial facts about other parts of math and that i just i don't think that's actually pub like popularized um i don't even think it's emphasized well enough when you're starting to take a topology class because you kind of have these two problems it's like either it's too squishy you're just talking about coffee mugs and donuts or it's a little bit too rigor first and you're talking about um the axiom systems with open sets and an open set is not the opposite of closed set so sorry about that everyone we have a notion of clopin sets for ones that are both at the same time yeah um and just it's not it's not an intuitive axiom system in comparison to other fields of math so you as the student like really have to walk through mud to get there and you're constantly confused about how this relates to the beautiful things about coffee mugs and mobius strips and such and it takes a really long time to actually see that like c topology in the way that mathematicians see topology but i don't think it needs to take that time i think there's um this is making me feel like i need to make more videos on the topic because i think you do but you know i've also seen it in my narrow view of uh like i'm i find game theory very beautiful and i know topology has been used uh elegantly to prove things in game theory yeah you have like facts that seem very strange like i could tell you you stir your coffee and um after you stir it and like let's say all the molecules settle to like not moving again one of the molecules will be basically in the same position it was before um you have all sorts of fixed point theorems like this right that kind of fixed point theorem directly relevant to nash equilibriums right um so you can imagine popularizing it by describing the coffee fact but then you're left to wonder like who cares about if a molecule of coffee like stays in the same spot is this what we're paying our mathematicians for um you have this very elegant mapping onto economics in a way that's very concrete or very i shouldn't say concrete very uh tangible like actually adds value to people's lives through the predictions that it makes but that line isn't always drawn because like you have to get a little bit technical in order to properly draw that line out and often i think popularized forms of media just shy away from being a little too technical for sure oh by the way for people who are watching the video i do not condone the message and this mug it's the only one i have which is this the snuggle is real by the way for anyone watching i do condone the message of that mug the struggle the snuggle is real okay so you mentioned the sir model i think there are certain ideas there of growth of exponential growth what maybe have you learned about um pandemics from from making that video because it was kind of exploratory you were kind of building up an intuition and it's again people should watch the video it's kind of an abstract view it's not really modeling in detail the whole field of epidemiology those those people they go really far in terms of modeling like how people move about i don't know if you've seen it but like they're it's really their mobility patterns like how like they try like how many people you encounter in certain situations when you go to a school when you go to a mall they like model every aspect of that for a particular city like they have maps of actual city streets they model it really well and natural patterns of the people have it's crazy so you don't do any of that you're just doing an abstract model to explore different ideas of simple i'm an epidemiologist like we have a ton of armchair epidemiologists and the spirit of that was more like uh can we through a little bit of play uh draw like reasonable-ish conclusions um and also just like uh get ourselves in a position where we can judge the validity of a model like i think people should look at that and they should criticize it they should point to all the ways that it's wrong because it's definitely naive right in the way that it's set up um but to say like what what lessons from that hold like thinking about the are not value and what that represents and what it can imply or not so are not is if you are infectious and you're in a population which is um completely susceptible what's the average number of people that you're going to infect during your infectiousness so certainly during the beginning of an epidemic this basically gives you kind of the exponential growth rate like if every person infects two others you've got that one two four eight exponential growth pattern um as it goes on and let's say it's something um uh endemic where you've got like a ton of people who have had it and are recovered then uh you would the r naught value doesn't tell you that as directly because a lot of the people you interact with aren't susceptible but in the early phases it does um and this is like the fundamental constant that it seems like epidemiologists look at and you know the whole goal is to get that down if you can get it below one then it's no longer epidemic if it's equal to one then it's endemic and it's above one then you're epidemic so uh like just teaching what that value is and giving some intuitions on how do certain changes in behavior change that value and then what does that imply for exponential growth i think those are um general enough lessons and they're like resilient to all of the chaoses of the world um that it's still like valid to take from the video i mean one of the interesting aspects of that is just exponential growth and we think about growth is that one of the first times you've done a video on on uh no of course not the whole uh oilers identity okay so sure i've done a lot of videos about exponential growth in the circular direction uh only minimal in the normal direction i mean another way to ask like do you think we're able to reason intuitively about exponential growth it's it's funny i think it's um i think it's extremely intuitive to humans and then we train it out of ourselves such that it's then really not intuitive and then i think it can become intuitive again when you study a technical field uh so what i mean by that is um have you ever heard of these studies where in a uh like anthropological setting where you're studying a group that has been disassociated from a lot of like modern society and you ask what number is between one and nine and maybe you would ask you you've got like one rock and you've got nine rocks you're like what pile is halfway in between these and our instinct is usually to say five that's the number that sits right between one and nine but sometimes when uh numeracy and uh the kind of just basic arithmetic that we have isn't in a society the natural instinct is three because it's uh in between in an exponential sense and a geometric sense that one is three times bigger and then the next one is three times bigger than that so it's like what's you know if you have one friend versus a hundred friends what's in between that yeah ten friends seems like the social status in between those two states so that's like deeply intuitive to us to think logarithmically like that um and for some reason we kind of train it out of ourselves to start thinking linearly about things so in the sense yeah the early early basic math is uh yeah it forces us to take a step back it's it's the same criticism if there's any of science is the lessons of science make us like see the world in a slightly narrow sense to where we we have an over-exaggerated confidence that we understand everything as opposed to just understanding a small slice of it but i think that probably only really goes for small numbers because the real counterintuitive thing about exponential growth is like as the numbers start to get big so i bet if you took that same setup and you asked them oh if i keep tripling the size of this rock pile you know um seven times how big will it be i bet it would be surprisingly big even to like an a society without numeracy and that's the side of it that um i think is pretty counter-intuitive to us uh but that you can basically train into people like i think computer scientists and physicists when they're looking at the early numbers of um like kovid were they were the ones thinking like oh god this is following an exact exponential curve yeah um and i heard that from a number of people uh so it's and almost all of them are like techies in some capacity probably just because i like live in the bay area but but for sure they're cognizant of this kind of this kind of growth is present in a lot of natural systems and a lot of in a lot of in a lot of systems uh i don't know if you've seen like i mean there's a lot of ways to visualize this obviously but ray kurzweil i think was the one that had this like chess board where um every every square in the chessboard you double the number of stones or something in that chessboard i've heard this is like an old proverb where you know someone the king offered him a gift and he said uh the only gift i would like very modest give me a single grain of rice right so the first chessboard and then two grains of rice for the next square then twice that for the next square and just continue on that's my only modest ask you're sire yeah and like then it's all you know more grains of rice than there are uh anything in the world um by the time you get to the end and i i my intuition falls apart there like i would have never predicted that like for some reason that's a really compelling uh illustration how poorly breaks down just like you said maybe we're okay for the first few piles but of rocks but after a while it's game over you know the other classic example for um gauging someone's intuitive understanding of exponential growth is uh i've got like a lily pad on a on lake really big lake okay um like lake michigan and that lily pad replicates it doubles um one day and then it doubles the next day and it doubles the next day and after 50 days it actually is going to cover the entire lake okay so after how many days does it cover half the lake 49. so you you have a good instinct for exponential growth right so i think a lot of uh like the knee-jerk reaction is sometimes to think that it's like half the amount of time or to at least be like surprised that like after 49 days you've only covered half of it um yeah i mean that's the reason you heard a pause from me i literally thought that can't be right right yeah exactly exactly so even when you know the fact and you do the division it's like wow so you've gone like that whole time and then day 49 it's only covering half and then after that it gets the whole thing but i think you can make that even more visceral if rather than going one day before you say how long until um it's covered one percent of the lake right and it's uh so what would that be um how many times you have to double to get over a hundred like seven six and a half times something like that right so at that point you're looking at 43 44 days into it you're not even at one percent of the lake so you've you've experienced you know 44 out of 50 days and you're like ah that lilly bad it's just one percent of the lake but then next thing you know it's the entire lake are you wearing a spacex sure so let me ask you sure let me ask you one one person uh who talks about exponential you know just the miracle of the exponential function in general is elon musk so he kind of advocates the idea of exponential thinking you know realizing that technological development can at least in the short term follow exponential improvement which breaks apart our intuition our ability to reason about what isn't isn't impossible so he's a big one it's a good leadership kind of style of saying like look the thing that everyone thinks is impossible is actually possible because exponentials but what what's your sense about um about that kind of way to see the world well so i think it's um it can be very inspiring to note when something like moore's law is another great example where you have this exponential pattern that holds shockingly well um and it enables um just better lives to be led i think the people who took moore's law seriously in the 60s we're seeing that wow it's not going to be too long before like these giant computers that are either batch processing or time shared you could actually have one small enough to put on your desk on top of your desk and you could do things and if they took it seriously like you have people predicting smartphones like a long time ago and it's only out of like kind of this i don't want to say faith in exponentials but an understanding that that's what's happening what's more interesting i think is to really understand why exponential growth happens and that the mechanism behind it is when the rate of change is proportional to the thing in and of itself so the reason the technology would grow exponentially is only going to be if the rate of progress is proportional to the amount that you have so that the software you write enables you to write more software and i think we see this with the internet like the advent of the internet makes it faster to learn things which makes it faster to uh create new things i think this is uh oftentimes why like investment will grow exponentially that the more resources a company has if it knows how to use them well the more uh the more it can actually grow so i mean you know you reference elon musk i think he seems to really be into vertically integrating his companies i think a big part of that is because you have the sense what you want is to make sure that the things that you develop you have ownership of and they enable further development of the adjacent parts right so it's not just this you you see a curve and you're blindly drawing a line through it what's much more interesting is to ask when do you have this proportional growth property because then you can also recognize when it breaks down like in an epidemic as you approach saturation that would break down as you do anything that skews what that proportionality constant is you can make it maybe not break down as being an exponential but it can seriously slow what that exponential rate is so the opposite of a pandemic is you want in terms of ideas you want to minimize barriers that uh prevent the spread you want to maximize the spread of impact so like you wanted to to grow when you're doing technological development is so that you do hold up that rate holds up and that's all that's almost like a like an operational challenge of like how you run a company how you run a group of people is that any one invention has a ripple that's unstopped and that ripple effect then has its own ripple effects and so on and that continues yeah like moore's law is fascinating and the like on a psychological level on a human level because it's not exponential it's it's just a consistent set of like what you would call like s-curves which is like it's constantly like breakthrough innovations non-stop that's a good point like it might not actually be an example of exponential because of something which grows in proportion to itself but instead it's almost like a benchmark that was set out that everyone's been pressured to meet and it's like all these innovations and micro inventions along the way rather than some consistent sit back and just let the lily pad grow across the lake phenomenon and it's also there's a human psychological level for sure of like the four-minute mile like it's there's something about it like saying that look there is um you know moore's law it's a law so like it's uh it's certainly an achievable thing you know we've achieved it for the last decade the last two decades the last three decades you just keep going and it somehow makes it happen i mean it makes people i'm continuously surprised in this world how few people do the best work in the world like in that particular whatever that field is like it's very often that like the genius i mean you couldn't argue that community matters but it's certain like i've been in groups of engineers where like one person is clearly like doing an incredible amount of work and just is the genius and it's fascinating to see basically it's kind of the steve jobs idea is maybe the whole point is uh to create an atmosphere where the genius can discover themselves like like have the opportunity to do the best work of their life and yeah and that the exponential is just milking that it's like rippling the idea that it's possible and that idea that it's possible finds the right people for the four minute mile the idea that it's possible finds the right runners to run it and then expose the number of people who can run faster than four minutes it's kind of interesting to i don't know basically the positive way to see that is most of us are way more intelligent have way more potential than we ever realize i guess that's kind of depressing but i mean like the ceiling for most of us is much higher than we ever realized that is true a a good book to read if you want that sense is peak which essentially talks about peak performance in a lot of different ways like you know chess london cab drivers of how many push-ups people can do short-term memory tasks and if there's one it's meant to be like a concrete manifesto about deliberate practice and such but the one sensation you come out with is wow no matter how good people are at something they can get better and like way better than we think they could i don't know if that's actually related to exponential growth but i do think it's a true phenomenon that's interesting yeah i mean there's certainly no law of exponential growth in human innovation well i don't know well kind of there is like there's i think it's really interesting to see when innovations in one field allow for innovations in another like the advent of computing seems like a prerequisite for the advent of chaos theory you have this truth about physics and the world that in theory could be known you could find lorenz's equations without computers but in practice it was just never going to be analyzed that way unless you were doing like a bunch of simulations and that you could computationally see these models so it's like physics allowed for computers computers allowed for better physics and you know wash rinse and repeat that self-proportionality that's exponential so i think i wouldn't i don't think it's too far to say that that's a law of some kind yeah a fundamental law of the universe is that these descendants of apes will exponentially improve their technology and one day take be taken over by the agi that's some that's built in this similar they'll make the video game fun whoever created this thing uh so i mean since you're wearing a space actually let me let me ask uh so i didn't realize that i apologize yeah so crew dragon the first uh crude mission out into space since the the space shuttle and just by first time ever by a commercial company i mean it's an incredible accomplishment i think but it's also just an incredible it inspires imagination amongst people that this is the first step in a long like vibrant journey of humans into space oh yeah so what do you what are your how do you feel is this you know is this exciting to you yeah it is i think it's great the idea of seeing it basically done by smaller entities instead of by governments i mean it's a it's a heavy collaboration between spacex and nasa in this case but moving in the direction of not necessarily requiring an entire country and its government to make it happen but that you can have um uh something closer to a single company doing it we're not there yet because it's not like they're unilaterally saying like we're just shooting people up into space um it's just a sign that we're able to do more powerful things with smaller groups of people uh i find that inspiring innovate quickly i hope we see people land on mars in my lifetime do you think we will i think so i mean i think there's a ton of challenges there right like radiation being kind of the biggest one and i think there's a ton of people who uh look at that and say why why would you want to do that let's let the robots do the science for us but i think there's enough people who are like genuinely inspired about broadening like the worlds that we've touched um or people who think about things like backing up the light of consciousness with like super long-term visions of terraforming like as long as there's backing up the light of consciousness yeah yeah the thought that uh you know if we if earth goes to hell we gotta have a backup somewhere um a lot of people see that as pretty out there and it's like not in the short term future but i think that's an inspiring thought i think that's a reason to like get up in the morning and i feel like most employees at spacex feel that way too do you think we'll colonize mars one day no idea like either agi kills us first or if we're like allowed i don't know if it'll take loud well like honestly it takes it would take such a long time like okay you might have a small colony right um something like what you see in um the martian but not like people living comfortably there um but if you want to talk about actual like second earth kind of stuff that that's just like way far out there and the future moves so fast that it's hard to predict like we might just kill ourselves before that even becomes viable i yeah i mean there's there's a lot of possibilities where it could be just it doesn't have to be on a planet we could be floating out in space have uh have a have a space faring backup solution that doesn't have uh that doesn't have to deal with the constraints at a planet but i mean a planet provides a lot of possibilities and resources but also some constraints yeah i mean for me for some reason it's a deeply exciting possibility oh yeah all of the people who are like skeptical about it or like why why do we care about going to mars it's like what makes you care about anything that's not inspiring it's hard actually it's hard to hear that because exactly as you put it on a philosophical level it's hard to say why do anything i don't know it's it's like the people say like you know i've been doing like an insane challenge last 30 something days your pull-ups and to pull up some push-ups and like you know a bunch of people are like awesome you're insane but awesome and then some people are like why why do anything i i don't know at this there's a calling it's uh i i'm with jfk a little bit is because we do these things because they're hard there's something in the human spirit that says like same with like a math problem there's something you fail once and it's like this feeling that you know what i'm not going to back down from this there's something to be discovered in overcoming this thing well so what i like about it is um and i also like this about the moon missions sure is kind of arbitrary but you can't move the target so you can't make it easier and say that you've accomplished the goal and when that happens it just demands actual innovation right like protecting humans from the radiation in space on the flight there while there heart problem demands innovation you can't move the goal post to make that easier almost certainly the innovations required for things like that will be relevant in a bunch of other domains too um so like the idea of doing something merely because it's hard it's like loosely productive great but as long as you can't move the goal posts there's probably going to be these secondary benefits that like we should all strive for yeah i mean it's hard to formulate the mars colonization problem as something that has a deadline which is the problem but if there was a deadline then the amount of things we would come up with by forcing ourselves to figure out how to colonize that place would be just incredible this is what people like the internet didn't get created because people sat down and tried to figure out how do i uh you know uh send tick tock videos of myself dancing to people they you know it was there's an application i mean actually i don't even know what do you think the application for the internet was when it was it must have been very low level basic network communication within darpa like military based like how do i send like a networking how do i send information securely between two places maybe it was an encryption i'm totally speaking totally outside of my knowledge but like it was probably intended for a very narrow small group of people well so i mean it was there was like this small community of people who are really interested in time sharing computing and like interactive computing in contrast with uh batch processing and then the idea that as you set up like a time sharing center uh basically meaning you have multiple people like logged in and using that like central computer um why not make it accessible to others yeah and this was kind of what i had always thought like oh is this like fringe group that was interested in this new kind of computing and they all like got themselves together but the thing is like darpa wouldn't act you wouldn't have the us government funding that just for the funds of it right in some sense that's what arpa was all about was uh like just really advanced research for the sake of having advanced research and it doesn't have to pay out with utility soon but the core parts of its development were happening like in the middle of the vietnam war when there was budgetary constraints all over the place uh i only learned this recently actually like if you look at the documents basically justifying the um budget for the arpanet as they were developing it and not just keeping it where it was but actively growing it while all sorts of other departments were having their funding cut because of the war a big part of it was national defense in terms of having like a more robust communication system like the idea of packet switching versus circuit switching you could kind of make this case that in some calamitous circumstance where you know a central location gets nuked uh this is a this is a much more resilient way to still have your communication lines that like traditional um telephone lines weren't as resilient to which i just found very interesting that that um even something that we see is so happy-go-lucky is just a bunch of computer nerds trying to get like interactive computing out there the actual like thing that made it uh funded and thing that made it advance uh when it did was because of this direct national security question and concern i don't know if you've read it i haven't read it i've been meaning to read it but neil degrasse tyson actually came out with a book that talks about like science and the context of the military like basically saying all the great science we've done in the in the 20th century was like because of the military i mean he paints a positive it's not like a critical it's not you know a lot of people say like military industrial complex and so on another way to see the military and national security is like a source of like you said deadlines and like hard things you can't move like almost you know almost like scaring yourself into being productive it is that i mean manhattan project is a perfect example probably the quintessential example that one uh is a little bit more macabre than others because of like what they were building but in terms of how many focused smart hours of human intelligence get pointed towards a topic per day you're just maxing it out with that sense of worry in that context everyone there was saying like we've got to get the bomb before hitler does and that like that just lights a fire under you that i again like the circumstances macabre but i think that's actually pretty healthy especially for researchers that are otherwise going to be really theoretical to take these like theorizers and say make this real physical thing happen meaning a lot of it is going to be unsexy a lot of it's going to be like young firemen sitting there kind of inventing a notion of computation in order to like compute what they needed to compute more quickly with like the rudimentary automated tools that they had available i think you see this with bell labs also where you've got otherwise very theorizing minds in very pragmatic contexts that i think is like really helpful for the theory as well as for the applications uh so i think that stuff can be positive for progress you mentioned bell labs and manhattan project this kind of makes me curious for the things you've create which are quite singular like if you look at all youtube or just not youtube it doesn't matter what it is it's just teaching content art doesn't matter it's like yup that's that's grant right that's unique i know your teaching style and everything does it manhattan project and bell labs was like famously a lot of brilliant people but there's a lot of them they play off of each other so like my question for you is that does it get lonely honestly that right there i think is the biggest part of my life that i would like to change in some way that uh i i look at a bell labs type situation and i'm like god damn i love that whole situation and i'm so jealous of it and you're like reading about hamming and then you see that he also shared an off with with shannon and you're like of course he did of course they shared an office that's how these ideas get like and they actually very likely worked separately yeah totally fine totally separate but there's a literally i'm sorry to interrupt there's a literally magic that happens when you run into each other like on the way to like get getting a snack or something conversations you overhear it's other projects you're pulled into it's like puzzles that colleagues are sharing like all of that um i i have some extent of it just because i just try to stay well connected in communities of uh people who think in similar ways but it's not it's not in the day-to-day in the same way which i would like to fix somehow that's one of the i would say uh one of the biggest well uh one of the many um drawbacks negative things about this current pandemic is that uh whatever the term is but like chance collisions are significantly reduced i i saw um i don't know why i saw this but on my on my brother's work calendar uh he had a scheduled slot with someone um that he scheduled a meeting and the the title of the whole meeting was no specific agenda i just missed the happenstance serendipitous conversations that we used to have which the pandemic and remote work has so cruelly taken away from us brilliant that was the only title of the match i'm like that's the way to do it you just schedule those things schedule the serendipitous interaction it's like i mean you can't do an academic setting but it's basically like going to a bar and sitting there just for the strangers you might meet just the strangers or striking up a conversation with strangers on the train harder to do when you're deeply like maybe myself or maybe a lot of academic types who are like introverted and avoid human contact as much as possible so it's nice when it's forced those chance collisions but maybe scheduling is a possibility but for the most part do you work alone like i'm sure you struggle like a lot like like this like this you probably hit moments when you you look at this and you say like this is the wrong way to show it it's a long way to visualize it i'm making it too hard for myself i'm going down the wrong direction this is too long this is too short all those self-doubt that's like could be paralyzing okay what do you do in those honestly i actually much prefer like work to be a solitary affair for me that's like a personality quirk i would like it to be in an environment with others and like collaborative in the sense of ideas exchanged but those phenomena you're describing when you say this is too long this is too short this visualization sucks it's way easier to say that to yourself than it is to say to a collaborator um and i know that's just a thing that i'm not good at so in that way it's it's very easy to just throw away a script because the script isn't working it's hard to tell someone else they should do the same actually last time we talked i think it was like very close to me talking don knuth it was kind of cool like two people that yes you got that interview yeah it's the heart hit uh no can i brag about something please uh my favorite thing is don knuth after he did the interview he offered to go out to hot dogs with me to get hot dogs that was never like people ask me what's the favorite interview you've ever done man that has to be um but unfortunately i couldn't i had a thing after so i had to turn down don knuth you missed knuth dogs canoe dogs sorry so that was a little bragging but the the hot dog is such a sweet so um but the reason i bring that up is he he works through problems alone as well he prefers that struggle the struggle of it you know writers like stephen king you know often talk about like their process of you know what they do like what they eat when they wake up like uh when they sit down like how they like their desk you know on a on a perfectly productive day like what they like to do how long they like to work for what enables them to think deeply all that kind of stuff um hunter s thompson did a lot of drugs uh you know everybody has their own thing uh what's do you have a thing is there if you were to lay out a perfect productive day what would that schedule look like do you think part of that's hard to answer because i like um the mode of work i do changes a lot from day to day like some days i'm writing the thing i have to do is write a script some days i'm animating the thing i have to do is animate sometimes i'm like working on the animation library the thing i have to do is like a little i'm not a software engineer but something in the direction of software engineering some days it's like a variant of research it's like learn this topic well and try to learn it differently so those is like four very different modes of what it some days is like get through the email backlog of people i've been the tasks i've been putting off um it goes research scripting like the idea starts with the research and then there's scripting and then there's programming and then there's the uh show time and the research side by the way like what's i think a problematic way to do it is to say i'm starting this project and therefore i'm starting the research instead it should be that you're like ambiently learning a ton of things just in the background and then once you feel like you have the understanding for one you put it on the list of things that there can be a video for otherwise either you're gonna end up roadblocked forever or you're just not gonna like have a good way of talking about it um but still some of the days it's like the thing to do is learn new things so what's the most painful one i think you mentioned scripting scripting is yeah that's the worst yeah right writing is the worst so what's your on a perfectly so let's take the hardest one what's a perfectly productive day you wake up and it's like damn it this is the day i need to do some scripting and like you didn't do anything last two days so you came up with excuses to procrastinate so today must be the day yeah i uh i wake up early i i guess i exercise um and then uh i turn the internet off if we're writing yeah that's that's what's required um is having the internet off and then maybe you keep notes on the things that you want to google when you're allowed to have the internet again i'm not great about doing that but when i do uh that makes it happen and then when i hit writer's block like the solution to writer's block is to read it doesn't even have to be related just read something different just for like 15 minutes half an hour and then go back to writing um that when it's a nice cycle i think can work very well and when you when you're writing the script you don't know where it ends right like you have a like problem solving videos i know where it ends expositional videos i don't know where it ends like coming up with uh with the magical thing that makes this whole story like ties this whole story together is that when does that happen that's that's the thing that makes it such that a topic gets put on the list of like oh that's an issue you shouldn't start the project unless there's one of those uh and you have you have so many nice bag that you haven't such a big bag of aha moments already that you could just pull at it that's one of the things and one of the sad things about time and that nothing lasts forever and that we're all mortal let's not get into that um discussion uh is you know if i see like even when i ask for people to ask like ask i did a call for questions and people want to ask you questions i mean so many requests from people about like certain videos that would love you to do it's such a pile and i i think that's a that's a sign of like admiration from people for sure but it's like it makes me sad because like whenever i see them people give ideas they're all like very often really good ideas and it's like it's such a makes me sad in the same kind of way when i go through a library or through a bookstore you see all these amazing books that you'll never get to open so so yeah so so you yeah gotta enjoy the ones that you have enjoy the books that are open and don't let yourself lament the ones that stay closed what else is there any other magic to that day do you try to dedicate like a certain number of hours do you uh uh cal newport has this deep work kind of idea i'm there's systematic people who like get really on top of you know the checklist of what they're going to do in the day and they like count their hours and i am not a systematic person in that way it's which is probably a problem i very likely would get more done if i was systematic in that way but that doesn't happen um so you know maybe you talk to me talk to me later in life and maybe i'll have like changed my ways and give you a very different answer i think benjamin franklin like later in life figured out the rigor he has these like very rigorous schedules and what how how to be productive i think those schedules are much more fun to write like it's very fun to like write a schedule and make a blog post about like the perfect productive day um that like might work for one person but i don't know how much people get out of like reading them or trying to adopt someone else's style and i'm not even sure that they've ever followed yeah exactly you're always going to write it as the best version of yourself um you're not going to explain the phenomenon of like wanting to get out of the bed but not really wanting to get out of bed and all of that and just like zoning out for random reasons or or the one that people probably don't touch at all is i try to check social media once a day but i'm like only so i post and that's it when i post i checked the previous days that's like my what i try to do uh that's what i do like 90 of the days but then i'll go i'll have like a two week period where it's just like i'm checking the internet like i mean it's some probably some scary number of times and i think a lot of people can resonate with that i think it's a legitimate addiction it's like it's a dopamine addiction and it's i don't know if it's a problem because as long as it's the kind of socializing like if you're actually engaging with friends and engaging with other people's ideas uh i think it can be really useful well i don't know so like for sure i agree with you but i'm it's a it's definitely an addiction because for me i think it's true for a lot of people i am very cognizant of the fact i just don't feel that happy if i look at a day where i've checked social media a lot like if i just aggregate i did a self-report i'm sure i would find that i'm just like literally on like less happy with my life and myself after i've done that check when i check it once a day i'm very like i'm happy even like because i've seen it okay one way to measure that is when somebody says something not nice to you on the internet it's like when i check it once a day i'm able to just like like i smile like like i virtually i think about them positively empathetically i send him love i don't don't ever respond but i just feel positively about the whole thing if i check if i check like more than that it starts eating at me like it start there's an eating thing that that happens like anxiety uh it occupies a part of your mind that's not doesn't seem to be healthy same with um i mean you you put stuff out on youtube i think it's important i think you have a million dimensions that are interesting to you but yeah one one of the interesting ones is the study of education and the psychological aspect of putting stuff up on youtube i like now have completely stopped checking statistics of any kind i've released an episode uh 100 with my dad conversation with my dad he checks he's probably listening to this stop he checks the number of views on his on his video on his conversation so he discovered like a reason he's new to this whole addiction and he just checks and he like he'll text me or write to me i just passed dawkins yeah so he's uh oh can i tell you a funny story in that effect of like parental use of youtube uh early on in the channel uh my mom would like text me she's like uh the chat the channel has had 990 000 views the channel's had 991 thousand views i'm like oh that's cute she's going to the little part on the about page where you see the total number of channel views no she didn't know about that she had been going every day through all the videos and then adding them up adding them up and she thought she was like doing me this favor of providing me this like global analytic that uh otherwise wouldn't be visible it's just like this addiction where you have some number you want to follow and then like yeah it's funny that your dad had this i think a lot of people have it i think that's probably a beautiful thing for like parents because they're legitimately they're proud yeah they're yes it's born of love it's great the downside i feel one one of them is this is one [Music] interesting experience that you probably don't know much about because comments on your videos are super positive uh but people judge the quality of how something went like i see that with these conversations by the comments yeah like i'm not talking about like you know people in their 20s and their 30s i'm talking about like ceos of major companies who don't have time they basically they literally this is their evaluation metric they're like oh the comments seem to be positive that's really concerning to me most important lesson for any content creator to learn is that the commenting public is not representative of the actual public and this is easy to see ask yourself how often do you write comments on youtube videos most people will realize i never do it some people realize they do but the people who realize they never do it should understand that that's a sign the kind of people who are like you aren't the ones leaving comments and i think this is important a number of respects like uh in my case i think i would think my content was better than it was if i just read comments because people are super nice the thing is the people who um are bored by it are are put off by it in some way or frustrated by it usually they just go away they're certainly not going to watch the whole video much less leave a comment on it so there's a huge under-representation of like negative feedback like well-intentioned negative feedback because very few people actively do that like watch the whole thing that they dislike figure out what they disliked articulate what they dislike um there's plenty of negative feedback that's not well-intentioned but for like that golden kind i think a lot of youtuber friends i have uh at least have gone through phases of like anxiety about the nature of comments um that stem from basically just this that it's like people who aren't necessarily represented who they were going for or misinterpreted what they're trying to say or whatever have you or we're focusing on things like personal appearances as opposed to like substance and they come away thinking like oh that's what everyone thinks right that's what everyone's response to this video was but a lot of the people who had the reaction you wanted them to have like they probably didn't write it down so very important to learn it also uh translates to um realizing that you're not as important as you might think you are right because all of the people commenting are the ones who love you the most and are like really asking you to like create certain things or like mad that you didn't create like a past thing um i don't i have such a problem like i have a very real problem with making promises about a type of content that i'll make and then either not following up on it soon or just like never following up on it yeah you actually last time we talked i think prom i'm not sure promised to me that you'll have music incorporated into your like uh i'll share with you a private link but so there's an example of like what i had in mind i like did a version of it um and i'm like i think there's a better version of this that might exist one day so it's now on the like the back burner it's like it's sitting there it was like a live performance at this one thing i think next next circumstance that i'm like doing another recorded live performance that like fits having that then in a better recording maybe i'll make it nice and public maybe a while but exactly right um the point i was gonna make though is like i know i'm bad about following up on stuff uh which is an actual problem it's born of the fact that i have a sense of what will be like good content when it won't be um but this can actually be incredibly disheartening because a ton of comments that i see are people who are like uh frustrated usually in a benevolent way that like i haven't followed through on like x and x which i get and i should do that but what's comforting thought for me is that when there's a topic i haven't promised but i am working on and i'm excited about it's like the people who would really like this don't know that it's coming and don't know to like comment to that effect and like the commenting public that i'm seeing is not representative of like who i think this other project will touch meaningfully yeah so focus on the future on the thing you're creating now just like the uh yeah the art of it one of the people is really inspiring to me in that regard because i've really seen it in persons um joe rogan he doesn't read comments but not just that he doesn't give a damn he like legitimate he's not like clueless about it he's like just like the richness and the depth of a smile he has when he just experiences the moment with you like offline you can tell he doesn't give a damn about like like about anything about what people think about whether if it's on a podcast you talk to him or whether offline about just it's not there like what other people think how how uh even like what the rest of the day looks like it's just deeply in the moment uh or like especially like is is what we're doing gonna make for a good instagram photo or something like that it doesn't think like that at all it's i think for actually quite a lot of people he's an inspiration in that way but it was and in real life a show that you can be very successful not giving a damn about um about comments and it sounds it sounds bad not to read comments because it's like well there's a huge number of people who are deeply passionate about what you do so you're what ignoring them but at the same time the nature of our platforms is such that the cost of listening to all the positive people who are really close to you who are incredible people have been you know made a great community that you can learn a lot from the cost of listening to those folks is also the cost of your psychology slowly being degraded by the natural underlying toxicity of the internet engage with a handful of people deeply rather than like as many people as you can in a shallow way i think that's a good lesson for social media usage um like platforms in general yeah choose choose just a handful of things to engage with and engage with it very well in a way that you feel proud of and don't worry about the rest honestly i think the best social media platform is texting that's my favorite that's my go-to social media platform well yeah the best social media interactions like real life not social media but social interaction well yeah no no question there i think everyone should agree with that which sucks because uh it's been challenged now with the current situation and we're trying to figure out what kind of platform can be created that we can do remote communication that still is effective it's important for education it's important for just that's the question of education right now yeah so on that topic you've done a series of live streams called lockdown math and you know you went live which is different than you usually do maybe one can you talk about how'd that feel what's that experience like like in your own when you look back like is that an effective way did you find being able to teach and if so is there lessons for this world where all of these educators are now trying to figure out how the heck do i teach remotely for me it was very different as different as you can get i'm on camera which i'm usually not i'm doing it live which is nerve wracking um it was a slightly different like level of topics although realistically i'm just talking about things i'm interested in no matter what i think the reason i did that was this thought that a ton of people are looking to learn remotely the rate which i usually put out content is too slow to be actively helpful let me just do some bi-weekly lectures that if you're looking for a place to point your students if you're a student looking for a place to be edified about math just tune in at these times um and in that sense i think it was you know a success for those who followed with it it was a really rewarding experience for me to see how people engaged with it part of the fun of the live interaction was to actually like i'd do these live quizzes and see how people would answer and try to shape the lesson based on that or see what questions people were asking in the audience i would love to if i did more things like that in the future kind of tighten that feedback loop even more um i think for you know you ask about like if this can be relevant to educators like 100 online teaching is basically a form of live streaming now um and usually it happens through zoom i think if teachers view what they're doing as a kind of performance and a kind of live stream performance um that would probably be pretty healthy because zoom can be kind of awkward um and i wrote up this little blog post actually just on like just what our setup looked like if you want to adopt it yourself and how to integrate um like the broadcasting software obs with zoom or things like that it was really sorry to pause on that i mean yeah maybe we could look at the blog post but it looked really nice the thing is i knew nothing about any of that stuff before i started i had a friend who knew a fair bit um and so he kind of helped show me the roots one of the thing that i realized is that you could as a teacher like it doesn't take that much to make things look and feel pretty professional um like one component of it is as soon as you hook things up with a broadcasting software rather than just doing like screen sharing you can set up different scenes and then you can like have keyboard shortcuts to transition between those two scenes so you don't need a production studio with a director calling like go to camera three go to camera two like onto the screen instead you can have control of that and it took a little bit of practice and i would mess it up now and then but i think i had it decently smooth such that you know i'm talking to the camera and then we're doing something on the paper then we're doing like a um playing with a desmos graph or something and something that i think in the past would have required a production team you can actually do as a solo operation and in particular as a teacher and i think it's worth it to try to do that because uh two reasons one you might get more engagement from the students but the biggest reason i think one of the like best things that can come out of this pandemic education-wise is if we turn a bunch of teachers into content creators and if we take lessons that are usually done in these one-off settings and like start to get in the habit of sometimes i'll use the phrase commoditizing explanation where what you want is whatever a thing a student wants to learn it just seems inefficient to me that that lesson is taught millions of times over in parallel across many different classrooms in the world like year to year you've got a given algebra 1 lesson that's just taught like literally millions of times by different people what should happen is that there's the small handful of explanations online that exist so that when someone needs that explanation they can go to it that the time in classroom is spent on all of the parts of teaching and education that aren't explanation which is most of it right um and the way to get there is to basically have more people who are already explaining publish their explanations and have it in a publicized forum so if during a pandemic you can have people automatically creating online content because it has to be online but getting in a habit of doing it in a in a way that doesn't just feel like a zoom call that happened to be recorded but it actually feels like a a piece that was always going to be publicized to more people than just your students that can be really powerful and there's an improvement process there like so being self-critical and growing like you know like i guess youtubers go through this process of like putting out some content and like nobody caring about it and then trying to figure out like basically improving figure out like why did nobody care uh uh what can i you know and they come up with all kinds of answers which may or may not be correct but doesn't matter because the answer leads to improvement so you're being constantly self-critical or self-analytical it should be better to say so you think of like how can i make the audio better like all the basic things maybe one one question to ask because uh well by way of uh russ dedrick he's a robotics professor at mit one of my favorite people a big fan of yours uh he watched our first conversation i just interviewed him a couple weeks ago he uh he teaches this course in under-actuated robotics which is um like robotic systems when you can't control everything like when you're like we as humans when we walk we're always falling forward which means like it's gravity you can't control it you just hope you can catch yourself but that's not all guaranteed it depends on the surface so like that's under-actuated you can't control everything all the the number of actuators uh the degrees of freedoms you have is not enough to fully control the system so i don't know it's a really i think beautiful fascinating class he puts it online um it's quite popular he does an incredible job teaching he puts online every time but he's kind of been interested in like crisping it up like you know making it uh you know innovating in different kinds of ways and he was inspired by the work he do because i think in his work he can do similar kind of explanations as you're doing like revealing the beauty of it and spending like months and preparing a single video uh and he's interested in how to do that that's why he listened to the conversation he's playing with madam but he had this question of you know um of uh you know like in my apartment where we did the interview i have like curtains like the for like a black curtain not this uh this is this is a adjacent mansion that we're in that i also but you basically just i have like a black curtain whatever that you know makes it really easy to set up a filming situation with cameras that we have here these microphones he was asking you know what kind of equipment do you recommend i guess like your blog post is a good one i said i don't recommend this is excessive and actually really hard to work with so i i wonder i mean is there something you would recommend in terms of equipment like is is it direct do you think like lapel mics like usb mics what do you for my narration i use a usb mic for the streams that used a lapel mic uh the narration it's a blue yeti um i'm forgetting actually the name of the lapel mic but it was probably like a road of some kind um but is it hard to figure out how to make the audio sound good oh i mean listen to all the early videos on my channel and clearly like i'm terrible at this for for some reason um i just couldn't get audio for a while i think i it's weird when you hear your own voice yeah so here you're like this sounds weird and it's hard to know does it sound weird because you're not used to your own voice or they're like actual audio artifacts at play um so uh and then video is just for the lockdowns just the camera like you said it was probably streaming somehow through the yeah there were two gh5 cameras one that was mounted overhead over a piece of paper you could also use like an ipad or a wacom tablet to do your writing um electronically but i just wanted the paper feel um on on the face there's two um again i don't know i'm like just not actually the one to ask this because i like animate stuff usually but uh each of them like has a compressor object that makes it such that the camera output goes into the computer usb but like gets compressed before it does that the the live aspect of it do you do you regret doing it live not at all um i think i do think the content might be like much less sharp and tight than if it were um something even that i just recorded like that and then edited later but i do like something that i do to be out there to show like hey this is what it's like raw this is what it's like when i make mistakes this is like the pace of thinking um i like the live interaction of it i think that made it better i probably would do it on a different channel i think if i did series like that in the future just because it's it's a different style it's probably a different target audience and kind of keep clean what three blue and brown is about versus uh the benefits of like live lectures do you uh suggest like in this time of covid that people like russ or other educators try to go like the the shorter like 20 minute videos that are like really well planned out or scripted you really think through you slowly design so it's not live do you see like that being an important part of um what they do yeah well what i think teachers like russ should do is um choose the small handful of topics that they're going to do just really well they want to create the best short explanation of it in the world that will be one of those handfuls in a world where you have commoditized explanation right most of the lectures should be done just normally um still put thought and planning into it i'm sure he's a wonderful teacher and like knows all about that but maybe choose a small handful of topics um do what beneficial for me sometimes if i do sample lessons with people on that topic to get some sense of how other people think about it let that inform how you want to edit it or script it or whatever format you want to do some people are comfortable just explaining it and editing later i'm more comfortable like writing it out and thinking in that setting yeah it's kind of sorry to interrupt uh it's it's a little bit sad to me to see how much knowledge is lost like just just like you mentioned there's professors like we can take my dad for example to blow up his ego a little bit but he's a great teacher and he knows plasma plasma chemistry plasma physics really well so he can very simply explain some beautiful but otherwise uh complicated concepts and it's sad that like if you google plasma or like for plasma physics like there's no videos and just imagine if every one of those excellent teachers like your father like russ um even if they just chose one topic this year they're like i'm gonna make the best video that i can on this topic if every one of the great teachers did that the internet would be replete and it's already replete with great explanations but it would be even more so with all the niche great explanations and like anything you want to learn and there's a self-interest to it for in terms of teachers in terms of even so if you take ross for example it's not that he's teaching something like he teaches his main thing his thing he's deeply passionate about and from a selfish perspective it's also just like i mean it's a it's a it's like publishing a paper in a really like nature has like letters like accessible publication it's just going to guarantee that your work that your passion is seen by a huge number of people whatever the definition of huge is doesn't matter it's much more than it otherwise uh would be and it's those lectures that tell early students what to be interested in yeah at the moment i think students are disproportionately interested in the things that are well represented on youtube so to any educator out there if you're wondering hey i want more like grad students in my department like what's the best way to recruit grad students it's like make the best video you can and then wait eight years and then you're gonna have a pile of like excellent grad students for that department and one of the lessons i think your channel teaches is there's appeal of explaining just something beautiful explaining it cleanly technically not doing a marketing video about why topology is great there's yeah that's the there's people interested in this stuff yeah i mean uh one of the greatest channels like matt it's not even a math channel but the channel with greatest math content is vsauce yeah you like interviewed if imagine you were to propose making a video that explains the binochtarsky paradox substantively right not not shying around it maybe not describing things in terms of um like the group theoretic terminology that you'd usually see in a paper but the actual uh results um that went into this idea of like breaking apart a sphere proposing that to like a network tv station saying yeah i'm gonna i'm gonna do this in-depth talk of the binocular ski paradox i'm pretty sure it's gonna reach 20 million people it's like get out of here like no no one cares about that no one's interested in anything even anywhere near that but then you have michael's quirky personality around it and just people that are actually hungry for that kind of depth um then you don't need like the approval of some higher network you can just do it and let the people speak for themselves so i think you know if your father was to make something on plasma physics or um if we were to have like uh underactualized robotics under actuated under actuated yes not underactualized plenty actualized under-actuated robotics yeah most robotics is under actualized current that's true so even if it's things that you might think are niche i bet you'll be surprised by how many people um actually engage with it really deeply although i just psychologically watching him i can't speak for a lot of people i speak for my dad i think there's a there's a little bit of a skill gap but i think that could be overcome that's pretty basic you know what none of us know how to make videos when we start the first step i made was terrible in a number of respects like look at the earliest videos on any youtube channel except for captain disillusion and they're all like terrible versions of whatever they are now but the thing i've noticed especially like with world experts is it's the same thing that i'm sure you went through which is like um fear of like embarrassment like they they definitely it's it's the same reason like i feel that anytime i put out a video i don't know if you still feel that but like i don't know it's this impostor syndrome like who am i to talk about this and that that's true for like even things that you've studied for like your whole life uh i don't know it's scary to post stuff on youtube it is scary uh i honestly wish that more of the people who had that modesty to say who am i to post this were the ones actually posting it that's right i mean the honest problem is like a lot of the educational content is posted by people who like we're just starting to research it two weeks ago and are on a certain schedule and who maybe should think like who am i to explain and choose your favorite topic quantum mechanics or something um and the people who have the self-awareness uh to not post are probably the people also best positioned to give a good honest explanation of it that's why there's uh a lot of value in a channel like numberphile where they basically trap a really smart person and force them to explain stuff on a broad sheet of paper so but of course that's not scalable as a single channel if they if there's anything beautiful that they could be done as people take it in their own hands uh educators which is again circling back i do think the pandemic will serve to force a lot of people's hands you're gonna be making online content anyway it's happening right just hit that publish button and see how it goes yeah see how it goes the cool thing about youtube is it might not go for a while but like 10 years later right yeah it'll be like this the thing this what people don't understand with youtube at least for now at least that's my hope with it is uh it's a leg it's a it's literally better than publishing a book in terms of the legacy it's it will live for a long long time of course it's uh one of the things i mentioned joe rogan before it's kind of there's a sad thing because i'm a fan he's moving to spotify yeah yeah nine digit numbers will do that to you yeah but he doesn't really that he's one a person that doesn't actually care that much about money like having talked to him he it it wasn't because of money it's because he legitimately thinks that they're going to do like a better job like so they're so from his perspective youtube you have to understand where they're coming from youtube has been cracking down on people who they you know joe rogan talks to alex jones and conspiracy theories and youtube was really like careful that kind of stuff and that's not a good feeling like and joe didn't doesn't feel like youtube was on his side um you know he's often has videos that they don't put in trending that like are obviously should be in trending because they're nervous about like you know if this concept is this is this content uh going to you know upset people that all that kind of stuff have misinformation and that's not a good place for a person to be in and spotify is giving them uh we're never going to censor you we're never going to do that but the reason i bring that up whatever you think about that i personally think that's bullshit because podcasting should be free and not constrained to a platform it's pirate radio what the hell you can't as much as i love spotify you can't just you can't put fences around it but uh anyway the reason i bring that up is uh joe's going to remove his entire library from youtube whoa really that's going to his full-length the clips are going to stay but the full-length videos are all i mean made private or deleted that's part of the deal and like that's the first time where i was like oh youtube videos might not live forever like things you find like okay sorry this is why you need um ipfs or something where it's like if there's a content link are you familiar with this system at all like right now if you have a url that points to a server there's like a system where the address points to content and then it's like distributed so you you can't actually delete what's at an address because it's it's content addressed and as long as there's someone on the network who hosts it it's always accessible at the address that it once was um but i mean that raises a question i'm not going to put you on the spot but like somebody like vsauce right spotify comes along and gives him let's say 100 billion dollars okay let's say some crazy number and then removes it from youtube right it's maybe i don't know for some reason i thought youtube is forever i don't think it will be i mean you know another variant that this might take is like uh that you know um you fast forward 50 years and uh you know google or alphabet isn't the company that it once was and it's kind of struggling to make ends meet and you know it's been supplanted by the whoever wins on the ar game or whatever it might be and then they're like you know all of these videos that we're hosting are pretty costly so we're just we're going to start deleting the ones that aren't watched that much and tell people to like try to back them up on their own or whatever it is um or even if it does exist in some form forever it's like if people are um not habituated to watching youtube in 50 years they're watching something else which seems pretty likely like it would be shocking if youtube remained as popular as it is now indefinitely into the future that's true so uh it won't be forever it makes me sad still but because it's such a nice it's like just like you said of the canonical videos sorry i don't interrupt you know you should get juan bennett on the uh on the thing and then talk to him about permanence i think you would have a good conversation who's that so he's the one that founded this thing called ipfs that i'm talking about and if you have him talk about basically what you're describing like oh it's sad that this isn't forever then you'll get some articulate quantification around it yeah that's like been pretty well thought through uh but yeah i do see youtube just like you said as a as a place like what your channel creates which is like a set of canonical videos on a topic now others could create videos on that topic as well but as a collection it creates a nice set of places to go if you're curious about a particular topic and it seems like coronavirus is a nice opportunity to put that knowledge out there in the world at mit and beyond i have to talk to you a little bit about machine learning deep learning and so on again we talked about last time you have a set of beautiful videos on your networks uh let me ask you first what is the most beautiful aspect of neural networks and machine learning to you like for making those videos from watching how the field is evolving is there something mathematically or an applied sense just beautiful to you about them well i think what i would go to is the layered structure and how um you can have what feel like qualitatively distinct things happening going from one layer to another but that are um following the same mathematical rule because you look at it as a piece of math it's like you got a non-linearity and then you've got a matrix multiplication that's what's happening on all the layers um but especially if you look at like some of the visualizations that like chris ola has done with respect to like convolutional nets that have been trained on imagenet trying to say what does this neuron do what do this does this family of neurons do what you can see is that the ones closer to the input side are picking up on very low level ideas like the texture right and then as you get further back you have higher level ideas like what is the where the eyes in this picture and then how do the eyes form like an animal is this animal a cat or a dog or a deer you have this series of qualitatively different things happening even though it's the same piece of math on each one so that's a pretty beautiful idea that you can have like a generalizable object that runs through the layers of abstraction which in some sense constitute intelligence as having um those many different layers of an understanding to something yeah form abstractions in a automated way exactly it's automated abstracting which i mean that just feels very powerful and the idea that it can be so simply mathematically represented i mean a ton of like modern email research seems a little bit like you do a bunch of ad hoc things then you decide which one worked and then you retrospectively come up with the mathematical reason that it always had to work um but you know who cares how you came to it when you have like that elegant piece of math uh it's hard not to just smile seeing it work in action well and when you talked about topology before one of the really interesting things is it's beginning to be investigated under kind of the field of like science and deep learning which is like the craziness of the surface that uh is trying to be optimized uh in neural networks i mean the the amount of local minima local optima there is in these surfaces and somehow a dumb gradient descent algorithm is able to find really good solutions that's like that's really surprising well so on the one hand it is but also it's like not it's not terribly surprising that you have these interesting points that exist when you make your space so high dimensional like gpt3 what did it have 175 billion parameters so it it doesn't feel as mesmerizing to think about oh there's some surface of intelligent behavior in this crazy high-dimensional space it's like there's so many parameters that of course but what's more interesting is like how how is it that you're able to efficiently get there which is maybe what you're describing that something as dumb as gradient descent does it but like the re the reason the gradient descent works well with neural networks and not just you know choose however you want to parameterize the space and then like apply gradient descent to it is that that layered structure lets you decompose the derivative in a way that makes it computationally feasible um yeah it's just that that there's so many good solutions probably infinitely infinitely many good solutions not best solutions but good solutions that's that's what's interesting it's similar to uh stephen wolfram has this idea of like the if you just look at all space of computations of all space of basically algorithms that you'd be surprised how many of them are actually intelligent like if you just randomly pick from the bucket that's surprising we tend to think like a tiny tiny minority of them would be intelligent but his sense is like it seems weirdly easy to find computations that do something interesting well okay so that from like a common gore kolmogorov complexity standpoint almost everything will be interesting what's fascinating is to find the stuff that's describable with low information but still does interesting things uh like one fun example of this you know um shannon's noisy coding in theorem uh noisy coding theorem and uh information theory that basically says if you know i want to send some bits to you uh maybe uh some of them are gonna get flipped uh there's some noise along the channel i can come up with some way of coding it that's resilient to that noise that's very good um and then he quantitatively describes how very good is what's funny about how he proves the existence of good error correction codes is rather than saying like here's how to construct it or even like a sensible non-constructive proof the nature of his non-constructive proof is to say um if we chose a random encoding it would be almost at the limit which is weird because then it took decades for people to actually find any that were anywhere close to the limit and what his proof was saying is choose a random one and it's like the best kind of encoding you'll ever find but what's what that tells us is that sometimes when you choose a random element from this ungodly huge set that's a very different task from finding an efficient way to actively describe it because in that case the random element to actually implement it as a bit of code you would just have this huge table of like um telling you how to encode one thing into another that's totally computationally infeasible so on the side of like how many possible programs are interesting in some way it's like yeah all tons of them but the much much more delicate question is when you can have a low information description of something that still becomes interesting and thereby that kind of gives you a blueprint for how to engineer that kind of thing right yeah chaos theory is another good instance there where it's like yeah a ton of things are hard to describe but how do you have ones that have a simple set of governing equations that remain like arbitrarily hard to describe well let me ask you uh you mentioned gpt3 it's interesting to ask uh what are your thoughts about the recently released openai gbt3 model that i believe is already trying to learn how to communicate like grant sanderson you know i think i got an email a day or two ago about someone who wanted to um try to use gpd3 with manum where you would like give it a high-level description of something and then it'll like automatically create the mathematical animation like trying to put me out of a job here i mean it probably won't put you out of a job but it'll create something visually beautiful for sure i would be surprised if that worked as stated but maybe there's like variants of it like that you can get to um i mean like a lot of those demos it's interesting i think uh there's a lot of failed experiments like depending on how you prime the thing you're going to have a lot of failed i'm certainly with code no program synthesis most of it won't even run but eventually i think if you if you're if you pick the right examples you'll be able to generate something cool and i think even that's good enough even though if if it's if you're being very selective it's still cool that something can be generated yeah that that's huge value um i mean think of the writing process sometimes a big part of it is just getting a bunch of stuff on the page and then you can decide what to whittle down to so if it can be used in like a man-machine symbiosis where it's just giving you a spew of potential ideas that then you can refine down um like it's serving as the generator and then the human serves as the refiner that seems like a pretty powerful dynamic yeah have you uh have you gotten a chance to see any of the demos like on twitter is there a favorite you've seen or oh my absolute favorite yeah uh so tim blay who runs a channel called a cappella science he was like tweeting a bunch about playing with it um and so he so gpt3 was trained on um the internet from before kovid so so in a sense it doesn't know about the coronavirus so what he seeded it with was just a short description about like um a novel virus uh emerges in wuhan china and starts to spread around the globe what follows is a month by month description of what happens january colon right that's what he sees it with so then what gpt3 generates is like january then a paragraph of description february and such and it's the funniest thing you'll ever read because um it predicts a zombie apocalypse which of course it would because it's trained on like the internet zombie stories but what you see unfolding is a description of covet 19 if it were a zombie apocalypse and like the early aspects of it are kind of shockingly in line with what's reasonable and then it gets out of hand so quickly and the other flip side of that is uh i wouldn't be surprised if it's on to something at some point here when you know 2020 has been full of surprises who knows like we might i'll be in like this crazy militarized zone as it predicts just a couple months off yeah i think is this definitely an interesting tool of storytelling it has struggled with mathematics which is interesting or in just even numbers it's able to it's not able to generate like patterns you know like you give it um in like five digit numbers and it's not able to figure out the sequence you know or like uh i didn't look in too much but i'm talking about like sequences like the fibonacci numbers and to see how far it can go because obviously it's leveraging stuff from the internet and it starts to lose it but it is also cool that i've seen it able to generate some interesting patterns um that are mathematically correct yeah i i honestly haven't dug into like what's going on within it uh in a way that i can speak intelligently to i guess it doesn't surprise me that it's bad at numerical patterns because i mean maybe i should be more impressed with it but like that requires having um a weird combination of intuitive and uh and formulaic worldview so you're not just going off of intuition when you see fibonacci numbers you're not saying like intuitively what do i think will follow the 13. like i've seen patterns a lot where like 13s are followed by 21s instead it's the like the way you're starting to see a shape of things is by knowing what hypotheses to test where you're saying oh maybe it's generated based on the previous terms or maybe it's generated based on like multiplying by a constant or whatever it is you like have a bunch of different hypotheses and your intuitions are around those hypotheses but you still need to actively test it um and it seems like gpt3 is extremely good at um like that sort of pattern matching recognition that usually is very hard for computers that um is what humans get good at through expertise and exposure to lots of things it's why it's good to learn from as many examples as you can rather than just from the definitions it's to get that level of intuition but to actually concretize it into a piece of math you do need to like test your hypotheses and if not prove it um like have an actual explanation for what's going on not just a a pattern that you've seen yeah and but then the flip side to play devil's advocate that's a very kind of probably correct intuitive understanding of just like we said a few a few layers creating abstractions but it's been able to form something that looks like a a compression of the data that it's seen that looks awfully a lot like it understands what the heck is talking about well i think a lot of understanding is like i don't mean to uh denigrate pattern recognition pattern recognition is most of understanding and it's super important and it's super hard um and so like when it's demonstrating this kind of real understanding compressing down some data like that that might be pattern recognition at its finest my only point would be that like what differentiates math i think to a large extent is that um the pattern recognition isn't sufficient and that the kind of patterns that you're recognizing are not like the end goals but instead they're they are the little bits and paths that get you to the end goal so that's only true for mathematics in general it's an interesting question if that might for certain kinds of series of numbers it might not be true like you might because that's a basic you know like taylor's like certain kinds of series it feels like compressing the internet uh is is enough to figure out because those patterns in some form appear in the text somewhere well i mean there's there's all sorts of wonderful examples of false patterns in math where um one of the earliest videos i put on the channel was talking about you're kind of dividing a circle up using these chords and you see this pattern of one two four eight sixteen i was like okay pretty easy to see what that pattern is it's powers of two you've seen it a million times um but it's not powers of two the next term is thirty one and so it's like almost a power of two but it's a little bit shy and there's there's actually a very good explanation for what's going on um but i think it's a good test of whether you're thinking clearly about mechanistic explanations of things how quickly you jump to thinking it must be powers of two because the problem itself there's really no no good way to i mean there can't be a good way to think about it as like doubling a set because ultimately it doesn't but even before it starts to it's not something that screams out as being a doubling phenomenon so at best if it did turn out to be powers of two it would have only been so very subtly and i think the difference between like you know a math student making the mistake and a mathematician who's experienced seeing that kind of pattern is that they they'll have a sense from what the problem itself is whether the pattern that they're observing is reasonable and how to test it and like uh i would just be very impressed if there was any algorithm that um was actively accomplishing that goal yeah like a learning based algorithm yeah like a little scientist i guess yeah basically yeah it's a it's a fascinating thought because gpg three these language models are already accomplishing way more than i've expected so i'm learning not to doubt but i bet we'll get there yeah i'm not saying i'd be impressed but like surprised like i'll be impressed but i i think we'll get there on um algorithms doing math like that so one of the amazing things you've done for the world is to some degree open sourcing the tooling that you use to make your videos with madam this python library now it's quickly evolving because i think you're inventing new things every time you make a video in fact i wanted um i've been working on playing around with something i wanted to do like an ode three blue one brown like i love playing hendrix i want to do like a cover you know of a concept i wanted to visualize and and use madam and i saw that you had like a little piece of code on like mobius strip and i tried to do some cool things with spinning a mobius strip like continue um twisting it i guess is the term uh and it was easier to uh it was tough so i haven't figured out yet well so i guess the question i want to ask is so many people love it uh that you've put that out there they want to uh do the same things they do with hendrix they want to cover it they want to explain an idea using the tool including russ how would you recommend they try to i'm very sorry they try to go they try to go by uh about it well so and what kind of choices should they choose to be most effective oh that i can answer so i always feel guilty if this comes up because um i think of it like the scrappy tool that's like a math teacher who put together some code people asked what it was so they made it open source and they kept scrapping it together and there's a lot like a lot of things about it that make it harder to work with than it needs to be that are a function of like me not being a software engineer um i i've put some work this year trying to like make it better and more flexible um that is still just kind of like a work in process um one thing i would love to do is just get my act together about properly integrating with what like the community wants to work with and like what stuff i work on and making that um not like deviate uh and just like actually fostering that community in a way that i've i've been like shamefully neglectful of so i'm just always guilty if it comes up so let's put that guilt aside just okay send like all right i'll pretend like it isn't terrible for someone like russ um i think step one is like make sure that what you're animating should be done so programmatically because a lot of things maybe shouldn't um like if you're just making a quick graph of something if it's a graphical intuition that maybe has a little motion to it use desmos use grapher use geogebra use mathematica certain things that are like really oriented around ground georgia is kind of cool it's amazing you can get very very far with it um and in a lot of ways like it would make more sense for some stuff that i do to just do in geogebra but i kind of have this cycle of liking to try to improve mana by doing videos and such so do as i say not as i do the original like thought i had in making manam was that there's so many different ways of representing functions other than graphs um in particular things like transformations like use movement over time to communicate relationships between inputs and outputs instead of like x direction and y direction or like vector fields or things like that so i wanted something that was flexible enough that you didn't feel constrained into a graphical environment by graphical i mean like graphs with uh like x coordinate y coordinate kind of stuff but also make sure that um you're taking advantage of the fact that it's programmatic you have loops you have conditionals you have abstraction if any of those are like well fit for what you want to teach to you know have a scene type that you tweak a little bit based on parameters or to have conditionals so that things can go one way or another or loops so that you can create these things of like arbitrarily increasing complexity that's the stuff that's like meant to be animated programmatically if it's just like writing some text on the screen or shifting around objects or something like that um things like that you should probably just use keynote right um you'll be a lot simpler so try to find a workflow that distills down that which should be programmatic into manum and that which doesn't need to be into like other domains again do as i say not as i do i mean python is an integral part of it and just for the fun of it let me ask uh what uh what's your most and least favorite aspects of python oh most and least i mean i love that it's like object-oriented and functional i guess that you can kind of like get both of those um uh benefits for how you structure things so if you just want to quickly whip something together the functional aspects are nice it's your primary language like for programmatically generating stuff yeah it's home for me by calling home yeah sometimes you travel but it's home got it it's home uh i mean the biggest disadvantage is that it's slow so when you're doing computationally intensive things either you have to like think about it more than you should how to make it efficient or that just like takes long do you run into that at all like with your work well so uh certainly old man is like way slower than it needs to be because of uh how it renders things on the back end is like kind of absurd i've rewritten things such that it's all done with like shaders in such a way that it should be just like live and actually like interactive while you're um coding it if you want to to you know you have like a 3d scene you can move around you can have um elements respond to where your mouse is or things that's not something that user of a video is going to get to experience because there's just a play button and a pause button but while you're developing that can be nice um so it's gotten better in speed in that sense but that's basically because the hard work is being done in the language that's not python but glsl right um but yeah there are some times when it's like a um there's just a lot of data that goes into the object that i want to animate that then it just like python is slow well let me ask quickly ask what do you think about the walrus operator if you're familiar with it at all the reason it's interesting there's a new operator in python 3.8 i find it psychologically interesting because it the toxicity over it led guido to resign to step down from this actually true or was it like there's a bunch of surrounding things that also was it actually the walrus operator that well it was it was a text it was an accumulation of toxicity but that was the the most that was the most toxic one like the discussion that's the most number of python core developers that were opposed to guido's decision um he didn't particularly i don't think cared about either way he just thought it was a good idea this is where you approve it and like the structure of the idea of a bdfl is like you listen everybody hear everybody out you make a decision and you move forward and he didn't like the negativity that burdened him after that people like some parts of the benevolent dictator for life mantra but once the dictator does things different than you want suddenly dictatorship doesn't seem so great yeah i mean they still liked it he just couldn't because he truly is the bee in the benevolent he's really he really is a nice guy he i mean and i think he can't it's a lot of toxicity it's difficult it's a difficult job that's why alana's terrible is perhaps the way he is you have to have a thick skin to fight off fight off the warring masses it's kind of surprising to me how many people can like threaten to murder each other over whether we should have braces or not or whether like it's incredible yeah i mean that's my knee-jerk reaction to the walrus operator is like i don't actually care that much either way i'm not going to get irritably passionate my my initial reaction was like yeah this seems to make things more confusing to read but then again so does list comprehension until you're used to it so like if there's a use for it great if not great but like let's just all calm down about our spaces versus tabs debates here and like be chill yeah to me just represents the uh the value of great leadership even in open source communities does it represent that if he stepped down as a leader well he fought for no he got it passed i guess but i i guess right it could represent multiple things too it can represent like failed dictatorships or it could it could represent a lot of things but to me great leaders take risks even if it even if it's a mistake at the end like you have to make decisions the thing is this world won't go anywhere if you const if whenever there's a divisive thing you wait until the division is no longer there like that's the paralysis we experience with like congress and political systems it's good to be slow when there's indecision uh when there's a people disagree it's good to take your time but like at a certain point it results in paralysis and you just have to make a decision the background of the site whether it's yellow blue or red can cause people to like go to war over each other i've seen this with design people are very touchy on color color choices at the end of the day just make a decision and go with it i think that that's what the walrus operator represents to me is it represents the fighter pilot instinct of like quick action is more important than uh than just like caring everybody out and really thinking through it because that's going to lead to paralysis yeah like if that's the actual case that you know it's something we're consciously hearing people's uh disagreement disagreeing with that disagreement and um saying he wants to move forward anyway that's an admirable aspect of leadership so we don't have much time but i want to ask just because it's uh some beautiful mathematics involved 2020 brought us a couple of in the physics world uh theories of everything eric weinstein kind of i mean he's been working for probably decades but he put out this idea of geometric unity or started sort of publicly thinking and talking about it more stephen wolfram put out his physics project which is kind of this hypograph view of the theory of everything do you uh find uh interesting beautiful things to these theories of everything what do you think about the physics world and sort of uh the beautiful interesting insightful mathematics in in that world whether we're talking about quantum mechanics which you touched on in a bunch of your videos a little bit quaternions like just the mathematics involved or general relativity which is more about surfaces and topology all that stuff well i think um as far as like popularized science is concerned people are more interested in theories of everything than they should be like because the problem is whether we're talking about trying to make sense of weinstein's lectures or wolfram's project or let's just say like listening to uh witten talk about string theory whatever proposed path to a theory of everything um you're not actually going to understand it some physicists will but like all you're just not actually going to understand the substance of what they're saying what i think is way way more productive is to let yourself get really interested in the phenomena that are still deep but which you have a chance of understanding because the path to getting to like even understanding what questions these theories of everything are trying to answer involves like walking down that i mean i was watching a video before i came here about from steve mold talking about um why sugar polarizes light in a certain way so fascinating like really really interesting it's not like this novel theory of everything type thing but to understand what's going on there really requires digging in in depth to certain ideas and if you let yourself think past what the video tells you about what does circularly polarized light mean and things like that it actually would get you to a pretty good appreciation of like two state states and quantum systems um in a way that just trying to read about like oh what's the what are the hard parts about resolving quantum field theories with general relativity is never gonna get you so as far as popularizing science is concerned like the audience should be less interested than they are in theories of everything um the popularizers should be less emphatic than they are about that for like actual practicing physicist you know it might be the case maybe more people should think about fundamental questions but it's difficult to create uh like a three blue one brown video on the theory of everything so basically we should really try to find the beauty and mathematics of physics by looking at concepts that are like within reach yeah i think that's super important i mean so you see this in math too with um the big unsolved problems so like the clay millennium problems riemann hypothesis um have you ever done a video on fermat's last name no i have not yet no but if i did do you know what i would do i would talk about um proving foreign theorem in the specific case of n equals three okay is that still accessible though yes actually barely um mathologer might be able to do like a great job on this he does a good job of taking stuff that's barely accessible and making it but the the core ideas of proving it for n equals three are hard but they do get you real ideas about algebraic number theory um it involves looking at a number field that's uh it lives in the complex plane it looks like a hexagonal lattice and you start asking questions about factoring numbers in this hexagonal lattice so it takes a while but i've talked about this sort of like lattice arithmetic in other contexts and you can get to a okay understanding of that and the things that make fairmont's last theme hard are actually quite deep um and so the cases that we can solve it for it's like you can get these broad sweeps based on some hard but like accessible bits of number theory but before you can even understand why the general case is as hard as it is you have to walk through those and so any other attempt to describe it would just end up being like shallow and not really productive for the viewers time i think the same goes for uh most like unsolved problem type things where i think you know as a kid i was actually very inspired by the twin prime conjecture um that like totally sucked me in as this thing that was understandable i kind of had this dream like oh maybe i'll be the one to prove the twin prime conjecture and new math that i would learn would be like viewed through this lens of like oh maybe i can apply it to that in some way but uh you sort of mature to a point where you realize that you should spend your brain cycles on problems that you will see resolved because then you're going to grow to see what it feels like for these things to be resolved rather than spending your brain cycles on something where it's not it's not going to pan out and the people who do make progress towards these things like james maynard uh is a great example here of like young creative mathematician who like pushes in the direction of things like the twin prime conjecture rather than hitting that head on just see all the interesting questions that are hard for similar reasons but become more tractable and let themselves really engage with those so i think people should get in that habit i think the popularization of physics should encourage that habit through things like the physics of simple everyday phenomena because it can get quite deep and um yeah i think you know i've heard a lot of the interest that you know people send me messages asking to explain weinstein's thing or asking to explain wolfram's thing one i don't understand them but more importantly um you shouldn't be interested in those right it's a giant sort of uh ball of interesting ideas there's probably a million of interesting ideas in there that individually could be explored effectively and to be clear you should be interested in fundamental questions i think that's a good habit to ask what the fundamentals of things are but i think it takes a lot of steps to like certainly you shouldn't be trying to answer that unless you actually understand quantum field theory and you actually understand general relativity that's the cool thing about like your videos people who haven't done mathematics like if you really give it time watch it a couple of times and like try to try to reason about it you can actually understand the concept that's being explained and it's not a coincidence that the things i'm describing aren't like the most um up-to-date uh progress on the riemann hypothesis cousins or um like there's context in which the analog of the roman hypothesis has been solved in like more uh discrete feeling finite settings that are more well-behaved i'm not describing that because it just takes a ton to get there and instead i think it'll be like productive to have an actual understanding of something that can you can pack into 20 minutes i think that's beautifully put ultimately that's where like the most satisfying thing is when you really understand um yeah really understand build a habit of feeling what it's like to actually come to resolution yeah yeah as opposed to which it can also be enjoyable but just being in awe of the fact that you don't understand anything yeah that's not like i don't know maybe people get entertainment out of that but it's not as fulfilling as understanding you won't grow yeah and but also just the fulfilling it really does feel good when you first don't understand something and then you do that's a beautiful feeling hey let me ask you one last last time we got awkward and weird about uh a fear of mortality which you made fun of me off but let me ask you on the the other absurd question is um what do you think is uh the meaning of our life of meaning of life i'm sorry if i made fun of you about much no you didn't i'm just joking it was it was great i don't think life has a meaning i think like meaning i don't understand the question i think meaning is something that's ascribed to stuff that's created with purpose there's a meaning to uh like this water bottle label in that someone created it with the purpose of conveying meaning and there was like one consciousness that wanted to get its ideas into another consciousness um most things don't have that property it's a little bit like if i asked you um like what is the height all right so it's all relative yeah you'd be like the height of what you can't ask what is the height without an object you can't ask what is the meaning of life without like an intentful consciousness putting it like i guess i'm revealing i'm not very religious but you know the mathematics of everything seems kind of beautiful it seems like it seems like there's some kind of structure relative to which i mean you could calculate the height well so but what i'm saying is i don't understand the question what is the meaning of life in that i think people might be asking something very real i don't understand what they're asking are they asking like why does life exist like how did it come about what are the natural laws are they asking um as i'm making decisions day by day for what should i do what is the guiding light that inspires like what should i do i think that's what people are kind of asking but also like why the thing that gives you joy about education about mathematics what the hell is that like what interactions with other people interactions with like-minded people i think is the meaning of in that sense bringing others joy essentially like in something you've created it connects with others somehow and the same and the vice versa i think that that is what um when we use the word meaning to mean like you're sort of filled with a sense of happiness and energy to create more things like i have so much meaning taken from this like that yeah that's what fuels fuels my pump at least so a life alone on a deserted island will be kind of meaningless yeah you want to be alone together with someone i think we're all alone together i think there's no better way to end it grant you've been first time we talked it's amazing again it's a huge honor that you make time for me i appreciate talking with you thanks man awesome thanks for listening to this conversation with grant sanderson and thank you to our sponsors dollar shave club doordash and cash app click the sponsor links in the description to get a discount and to support this podcast if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from richard feynman i have a friend who's an artist and has sometimes taken a view which i don't agree with very well he'll hold up a flower and say look how beautiful it is and i'll agree then he says i as an artist can see how beautiful this is but you as a scientist take this all apart and it becomes a dull thing and i think he's kind of nutty first of all the beauty that he sees is available to other people and to me too i believe although i may not be quite as refined aesthetically as he is i can appreciate the beauty of a flower at the same time i see much more about the flower than he sees i can imagine the cells in there the complicated actions inside which also have a beauty i mean it's not just beauty at this dimension at one centimeter there's also beauty of smaller dimensions the inner structure also the processes the fact that the colors in the flower evolved in order to attract insects to pollinate it is interesting it means that insects can see the color it adds a question does this aesthetic sense also exist in the lower forms why is it aesthetic all kinds of interesting questions which the science knowledge only adds to the excitement the mystery and the awl of a flower it only adds i don't understand how it subtracts thank you for listening and hope to see you next time you |
Sheldon Solomon: Death and Meaning | Lex Fridman Podcast #117 | the following is a conversation with sheldon solomon a social psychologist a philosopher co-developer of terror management theory and co-author of the warm at the core on the role of death and life he further carried the ideas of ernest becker that can crudely summarize as the idea that our fear of death is at the core of the human condition and the driver of most of the creations of human civilization quick summary of the sponsors blinkist expressvpn and cash app click the links in the description to get a discount it really is the best way to support this podcast let me say as a side note that ernest becker's book denial of death had a big impact on my thinking about human cognition consciousness and the deep ocean currents of our mind that are behind the surface behaviors we observe many people have told me that they think about death or don't think about death fear death or don't fear death but i think not many people think about this topic deeply rigorously in the way that nietzsche suggested this topic like many that lead to deep personal self-reflection frankly is dangerous for the mind as all first principles thinking about the human condition is if you gaze long into the abyss like nietzsche said the abyss will gaze back into you i've been recently reading a lot about world war ii stalin and hitler it feels to me that there's some fundamental truth there to be discovered in the moments of history that changed everything the suffering the triumphs if i bring up donald trump or vladimir putin in these conversations it is never through a political lens i'm not left nor right i think for myself deeply and often question everything changing my mind as often as is needed i ask for your patience empathy and rigorous thinking if you arrive to this podcast from a place of partisanship if you hate trump or love trump or any other political leader no matter what he or they do and see everyone who disagrees with you as delusional i ask that you unsubscribe and don't listen to these conversations because my hope is to go beyond that kind of divisive thinking i think we can only make progress toward truth through deep and pathetic thinking and conversation and as always love if you enjoy this thing subscribe on youtube review with five stars and apple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and no ads in the middle i try to make these interesting but i give you timestamps so you can skip but please do check out the sponsors by clicking the links in the description it's the best way to support this podcast this episode is supported by blinkist my favorite app for learning new things get it at blinkist.com lex for a seven day free trial and 25 off after blinkist takes the key ideas from thousands of non-fiction books and condenses them down into just 15 minutes that you can read or listen to i'm a big believer in reading at least an hour a day as part of that i use blinkist every day and in general it's a great way to broaden your view of the ideal landscape out there and find books that you may want to read more deeply with blinkist you get unlimited access to read or listen to a massive library of condensed non-fiction books right now for a limited time blinkist has a special offer just for our audience go to blinkist.com lex to try it free for seven days and save 25 percent off your new subscription that's blinkist.com lex blinkist spelled b-l-i-m-k-i-s-t this show is sponsored by expressvpn get it at expressvpn.com lexpod to get a discount and to support this podcast have you ever watched the office if you have you probably know it's based on a uk series also called the office not to stir up trouble but i think the british version is actually more brilliant than the american one but both are pretty amazing anyway there are actually nine other countries with their own 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donate ten dollars to first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with sheldon solomon what is the role of death and fear of death and life well from our perspective the uniquely human awareness of death and our unwillingness to accept that fact we would argue is the primary motivational impetus for almost everything that people do whether they're aware of it or not so that's kind of been your life work your view of the human condition is that death you've written the book warm with the core that death is at the core of our consciousness of everything of how we see the world of what drives us maybe can you can you elaborate like what how you see death fitting in what does it mean to be at the core of our being so i think that's a great question and you know to be pedantic i usually start you know my psychology classes and i say to the students okay you know let's define our terms and the ology part they get right away you know it's the study of and then we get to the psyche part and understandably you know the students are like oh that means mind and i'm like well no that's a modern interpretation but in a in ancient greek it means soul but not in the cartesian dualistic sense that most of us in the west think when that word comes to mind and so you hear the word soul and you're like well all right that's the non-physical part of me that's potentially detachable from my corporal container when i'm no longer here but aristotle's who coined the word psyche i think um he was uh not a dualist he was a monist he thought that the soul was inextricably connected to the body and he defined soul as the essence of a natural body that is alive and then he goes on and he says all right but let me give you an example if um if an axe was alive the soul of an axe would be to chop and if you can pluck your eyeball out of your head and it was still functioning then the soul of the eyeball would be to see you know and then he's like all right the soul of a grasshopper is to hop the soul of a woodpecker is to peck which raises the question of course what is the essence of what it means to be human and here of course there is no one universally accepted conception of the essence of our humanity all right aristotle uh you know gives us the idea of humans as rational animals you know we're homo sapiens but not the only game in town got joseph hoisinger an anthropologist in the 20th century he called us homo ludens that were basically fundamentally playful creatures and i think it was hannah arendt uh homo faber we're tool making creatures uh another woman ellen dizzinayake wrote a book called homo aestheticus and following aristotle and his poetics she's like well we're not only rational animals we're also aesthetic creatures that appreciate beauty there's another take on humans i think they call us homo naratans we're all we're storytelling creatures and i i think all of those uh designations of what it means to be human are quite useful heuristically and certainly worthy of our collective cogitation but what what garnered my attention when i was a young punk was just a single line in an essay by a scottish guy it was alexander smith in in a book called dreamthwarp i think it's written in the 1860s he just says right in the middle of an essay it is our knowledge that we have to die that makes us human and i remember reading that and i in my gut i was like oh man i don't like that but i think you're on to something and then william james the the great harvard philosopher and arguably the first academic psychologist he referred to death as the worm at the core of the human condition so that's where the worm at the core idea comes in and that's just an illusion to the story of genesis back in the proverbial old days in the garden of eden uh everything was going tremendously well until the serpent tempts eve to take a chop out of the apple of the tree of knowledge and adam partakes also and this is according to the bible what brings death into the world and from our vantage point the story of genesis is a remarkable allegorical uh recount of the origin of consciousness where we get to the point where by virtue of our vast intelligence we come to realize the inevitability of death and so uh you know the apple is beautiful and it's tasty but when you get right into the middle of it there's that ugly reality which is our finitude and then fast forward a bit and uh i was a young professor at skidmore college in 1980 um my phd is in experimental social psychology and i i mainly did studies with clinical psychologists evaluating the efficacy of non-pharmacological interventions to reduce stress and that was good work and i found it interesting but in my first week as a professor at skidmore i i'm just walking up and down the shelves of the library saw some books by a guy i had never heard of ernest becker a cultural anthropologist recently deceased he died in 1974 after um weeks before actually he was posthumously uh awarded the pulitzer prize and non-fiction for his book the denial of death and and that was his last book it's actually his next to last book i don't know how you pulled this off but he had one more after he died called escape from evil and evidently it was supposed to originally the denial of death was supposed to be this giant thousand page book that was both and they split it up and the what became escape from evil uh his wife marie becker finished well be that as it may in it is in the denial of death where becker just says it in the first paragraph i i i believe uh that the terror of death and the way that human beings respond to it or decline to respond to it is primarily responsible for almost everything we do whether we're aware of it or not and mostly we're not and so i read that first paragraph lex and i was like wow okay this dude you're on to something you're on to something it's the same thing it's the same thing and then it reminded me i think um not to play psychologists but you know let's face it i believe there's a reason why we end up drifting where we ultimately come to so i'm in my mid-20s i got ernest becker's book in my hand and the next thing i know i'm remembering uh when i'm eight years old the day that my grandmother died and you know the day before my mom said oh say goodbye to grandma she's not well and okay so i was like okay grandma and i knew she wasn't well but i didn't really appreciate the magnitude of her illness well she dies the next day and it's in the evening and i'm just sitting there looking at my stamp collection and i'm like wow i'm gonna miss my grandmother and then i'm like no wait a minute that means my mother's gonna die and after she gets old and that's even worse after all who's gonna make me dinner and that bothered me for a while but then i'm looking at the stamps all the dead american presidents and i'm like there's george washington he's dead there's thomas jefferson he's dead my mom's gonna be dead oh i'm gonna get old and be dead someday and at eight years old that was my first explicit existential crisis i remember it being you know one of these blood curdling realizations that i tried my best to ignore for the most of the time i was subsequently growing up but fast forward back to skidmore college mid-20s you know reading becker's book in the 1980s thinking to myself wow one of the reasons why i'm finding this so compelling is that it squares with my own personal experience and then to make a short story long and i'll i'll shut up lex but what what grabbed me about becker and this is in part uh because i read a lot of his other books um there's another book the birth and death of meaning uh which is framed um in from an evolutionary perspective and and then the denial of death is really more framed from an existential psychodynamic vantage point and as a a young um academic uh i was really taken by what i found to be a very potent juxtaposition that you really don't see that often yet usually evolutionary types are eager to dismiss the psychodynamic types and vice versa and maybe only john bolby you know there's there's other folks but the attachment theorist john bolby was really one of the first serious academics to say these um these ways of thinking about things are quite compatible and can you comment on what's what a psychodynamics view of the world is versus an evolutionary view of the world just in case people are not oh yeah absolutely that's that's a fine question well for the evolutionary types um in general are interested in um how it is and why it is that we have adapted to our surroundings in the service of persisting over time and being represented in the gene pool thereafter you used to be a fish yes we used to be a fish and also yeah and i ended up uh talking on a podcast yeah how we came to be that way how we came to be that way and so whereas the existential psychodynamic types i would say are more interested in development across a single lifespan and but but the evolutionary types dismiss the psychodynamic types as overly speculative and devoid of empirical support for their views well they um you know they'll just say these guys are talking shit if you'll pardon the expression and of course uh you can turn right around and say the same about the evolutionary types that they are often and rightfully criticized evolutionary psychologists for what are called the just so stories where it's like oh this is probably why fill in the blank is potentially adaptive and my thought again early on was i didn't see any um intrinsic antithesis between these viewpoints i just found them dialectically compatible and uh very powerful when combined so one question i would ask here is um about a science being speculative you know we understand so a little about the human mind you said you picked up becker's book and you know it felt like it was onto something that's the same thing i felt when i picked up becker's book uh probably also in my early 20s uh you know i read a lot of philosophy but it felt like the question of the meaning of life kind of you know this seemed to be the most uh the closest to the truth somehow it was on to something so i i guess the question that i want to ask also is like how speculative is psychology how like all of your lives work um how do you feel how confident do you feel about the whole thing about understanding our mind i feel confidently unconfident to have it both ways like what do we make of psychology you want to make starting with freud's you know starting um just just our or even just philosophy uh even uh the aspects of uh the sciences like uh you know my field of artificial intelligence but also physics you know it often feels like man we don't really understand most of what's going on here and certainly that's true with uh the human mind yeah well to me that's the proper epistemological stance i don't know anything well uh it's the socratic uh i know that i don't know which is the first step on the path to wisdom i i would argue forcefully that we know a lot more than we used to i would argue equally forcefully uh not that i have a phd in the philosophy of science but i i believe that the thomas coons of the world are right when they point out that change is not necessarily progress and so on the one hand i i do think we know a lot more than we did back in the day when if you wanted to fly you put on some wax wings and jumped off a mountain yeah on the other hand i think it's quite arrogant when scientists i'll just speak about psychological scientists um when they have the audacity to mistake statistical precision for knowledge and insight and when they make the mistake in my estimation that einstein bemoaned and that's this idea that the mere accumulation of data uh will necessarily result in conceptual breakthroughs and so i i like the um well we're all i hope appreciative of the people who trained us but i remember my first day in graduate school at the university of kansas uh they brought us into a room and on one side of the board was a quote by kurt lewin or levine famous german uh social psychologist and there was nothing and the quote is there's nothing more useful than a good theory and then on the other side was another quote by german physicist his name eludes me and it was all theories are wrong and i'm like uh which is it and of course the point is that it's both our theories are i believe powerful ways to direct our attention to aspects of human affairs that might render us better able to understand ourselves in the world around us now i also as an experimental psychologist i adhere to the view that theories are essentially hypothesis generating devices and that at its best science is a dialectical interplay where you have theoretical assertions that yield testable hypotheses and that either results in the corroboration of the theory the rejection of it or the modification thereafter if we look at the existentialists or even like uh modern philosopher psychology types like jordan peterson i'm not sure if you're familiar with it i know jordan pretty well we go way back actually if he were here with us today we would he would be jumping in and i believe very interesting and important ways but yeah we go back 30 years ago he was uh basically saying our work is nonsense let's get into this i'm sure i'll talk to jordan uh eventually on this thing yeah going through some rough times right now oh absolutely and i and i wish him well um jordan was working on his maps of meaning and we were publishing our work and i i think jordan at the time um was concerned about our vague claims to the effect that all meaning is arbitrary he takes a more jungian as well as evolutionary view that i don't think is wrong by the way which is that um there are certain kinds of meanings that are more important let's say religious types and that we didn't pay sufficient attention to that um in our early days so uh can you try to uh lose a day like what his world view is because he's also a religious man uh so what uh what was this what was uh some of the interesting aspects of the disagreements that then yeah well back in the day i just said you know jordan was a young punk uh we were young punks he was just kind of flailing in an animated way at some conferences saying that um we you're still both kind of punks yeah we are kind of punks so i saw him three or four years ago we spoke on a it was an awesome day we were in canada at uh the ontario shakespeare festival where we were asked to be on a canadian broadcast system program i think we were talking about macbeth from a psychodynamic perspective and i hadn't seen him in a ton of years and we spent two days together had a great time you know we had just written our book uh the worm at the core and he's like you know you you you're missing a big opportunity every time you say something you have to have your phone yeah and you have to film yourself and then you have to put it on youtube yeah uh he was onto something that uh you know that just as a small tangent yeah uh it's it's almost sad to look at jordan peterson somebody like yourself after having done this podcast i've realized that there is really brilliant people in this world and oftentimes especially like when they're um i mean it would love are a little bit like punks that's right they they kind of do their own thing and like the world doesn't know they exist as much as they should and it's so interesting because most people are kind of boring and then the interesting ones kind of go on their own and there's not a smartphone that's that's so interesting he was on to something that um i mean it's interesting that he i don't think he was thinking from a money perspective but he was probably thinking of like connecting with people or sharing his knowledge but uh people don't often think that way that's right so maybe we can try to get back to you're both brilliant people and i'd love to get some interesting disagreements earlier and later about in your psychological work in your world views well our disagreements today would be uh along two dimensions uh one is he is and again i wish he was here to correct me yes um when i say that he is more committed to the virtues of the judeo-christian tradition particularly christianity and in a sense is a contemporary kierkegaard of sorts when he's saying there's only one way to leap into faith and i would take ardent issue with that claim on the grounds that that is one but by no means not the only way uh to find meaning and value in life and so and i see his what's his warm at the core what is like uh so we're talking about a little bit of a higher level of discovering meaning yeah what's his uh what does he make of death oh i don't know and this is where it would be nice to uh have him here he has you know from a distance criticized our work as misguided having said that though when we were together he said something along the lines that there is no theoretical body of work in academic psychology right now for which there is more empirical evidence and so i i appreciated that he's a great uh researcher he's a good clinician the other thing that we will agree to disagree about uh rather vociferously is ultimately political slash economic so i remember being at dinner with him telling him that the next book that i wanted to write was going to be called why left and right or both beside the point and my argument was going to be and it is going to be that both liberal and political liberal and conservative political philosophy are each intellectually and morally bankrupt because they're both framed in terms of assumptions about human nature that are demonstrably false and jordan didn't mind me uh knocking liberal political philosophy on those grounds that would basically be like stephen pinker's blank slate but he took issue when i pointed out that actually it's conservative political philosophy which starts with john locke's assumption that in a state of nature there are no societies just autonomous individuals who are striving for survival that's one of the most obviously patently wrong assertions in the history of intellectual thought and locke uses that to justify his claims about the individual right to acquire unlimited amounts of property which is ultimately uh the justification for neo-liberal economics and can you look around a little bit uh what's the uh can you describe his philosophy again as view of the world sure and what uh uh neoliberal economics is yeah let me translate it in english so basically all all these days anybody who says i'm a i i'm a conservative free-market type you're following john locke and adam smith whether you're aware of it or not so here's john locke who by the way all of these guys are great so for me to appear to criticize any of these folks it is with the highest regard and also we need to understand in my estimation how important their ideas are lock is working in a time where all rule was top down by divine right and he's trying desperately to come up with a philosophical justification to shift power and autonomy to individuals and he starts in his second treatise on government 1690 or so he he just he says okay let's start with a state of nature and he's like in a state of nature there's no societies there's just individuals and in a perfect universe there wouldn't be any societies there would just be individuals who by the law of nature have a right to survive and uh in the service of survival they have the right to acquire and preserve the fruits of their own labor uh um but his point is and it's actually a good one you know he's following hobbs here he's like well the problem with that is that people are assholes and um if they would let each other alone then we would still be living in a state of nature everybody just doing what they did to get by each day but it's a whole lot easier you know if i see like an apple tree a mile away well i can go over and pick an apple but if you're 10 meters away with an apple in your hand it's a lot easier if i pick up a rock and crack your head and take the apple and his point was that the problem is that people can't be counted on to behave they will they will take each other's property moreover he argued if someone takes your property you have the right to you have the right to retribution in proportion to the degree of the magnitude of the transgression english translation if i take your apple you have the right to take an apple back you don't have the right to kill my firstborn but people being people they're apt to escalate retaliatory behavior thus creating what law called a state of war so he said in order to avoid a state of war people reluctantly give up their freedom in exchange for security they agree to obey the law and that the sole function of government is to keep domestic tranquility and to ward off foreign evasion in order to protect our right to property all right so now here's the okay property thing all right so uh lock says if you look in the bible and in nature there is no private property um but lock says well surely you if there's anything that you own it's your body and surely you have a right by nature to stay alive and then by extension anything that you do where you exert effort or labor that becomes your private property so back to the apple tree if i walk over to an apple tree that's everybody's apples until i pick one and the minute i do that is my apple right and then he says you can have as many apples as you want as long as you don't waste them and as long as you don't impinge on somebody else's right to get apples right so far so good yep and then he says well okay in the early days you you could only eat so many apples and or you could only trade so many apples with somebody else so he was like well if you put a fence around a bunch of apple trees those become your apples that's your property if somebody else wants to put a fence around nebraska that's their property and everybody can have as much property as they want because the world is so big that there is no limit to what you can have if you pursue it by virtue of your own effort but then he says money came into the picture and this is important because it's a he noticed long before anybody before the freud's of the world that money is funky because it has no intrinsic value he's like ooh look at that shiny piece of metal that actually has if you're hungry and you have a choice between a carrot and a lump of gold in the desert most people are going to go for the carrot but his point is is that uh the allure of money is that it's basically a concentrated symbol of wealth but because it doesn't spoil locke said you're entitled to have as much money as you're able to garner right then he says well the reality is is that some people are more the word that he used was industrious he said some people more industrious than others all right today we would say smarter less lazy more ambitious he just said that's natural it's also true therefore he argued uh over time some people are gonna have a whole lot of property and other people not much at all inequality for luck is natural and beneficial for everyone his argument was that you know the rising tide lifts all boats and that the truly creative and innovative are entitled to relatively unlimited worth because we're all better off as a result so the point very simply is that well that's basically and then you have adam smith the you know in the next century with the invisible hand where adam smith says everyone pursuing their own selfish that's not necessarily pejorative if everyone pursues their own selfish interests we will all be better off as a result and what do you think is the flawed in that way well there's two flaws one is is that um well one flaw is first of all that that it is based on an erroneous assumption to begin with which is that there never was a time in human history when we were in a social species in a sense you don't feel like that where there's uh this emphasis of uh individual autonomy is a flawed premise like where there's a there's something fundamentally deeply uh interconnected between us i do i think that plato and socrates uh you know in the crito were closer to the truth uh when they started with the assumption that we were interdependent and they derived individual autonomy as a manifestation of a functional social system that's fascinating so when margaret thatcher you're too young uh you know in the 1980s she said societies there's no such thing as societies there's just individuals pursuing their self-interest so uh so that's one point where i would take issue respectfully with john locke point number two is when locke says in 1690 well england's filled up um so if you want some land just go to america it's empty or maybe there's a few savages there just kill them so and and melville does the same thing in moby dick where he he thinks about will there ever come a time where we run out of whales and he says no but we have run out of whales and so locke was right maybe in 1690 that the world was large and had infinite resources he's certainly wronged today in in my opinion also wrong is the claim uh that the unlimited pursuit of personal wealth does not harm those around us there is no doubt uh that radical inequality is tragic psychologically and physically it's poverty is not that terrible it's easy for me to say because i have a place to stay and something to eat but as long as you're not starving and have a place to be poverty's not as challenging as being having the impoverished and close proximity to those who are obscenely wealthy so it's not the any absolute measure of your well-being it's the inequality of that well-being is quite frantically painful um so maybe just to uh link on the jordan peterson thing in terms of your uh disagreement on his worldview so he went through quite a bit it you know there's been quite a bit of fire right in in his defense or maybe his opposition of the idea of equality of outcomes so looking at the inequality that's in our world looking at you know certain groups measurably having an outcome that's different than other groups and then drawing conclusions about fundamental uh unfairness injustice inequality in the system so like systematic racism systematic sexism systematic anything else that creates inequality and he's been kind of uh saying pretty simple things uh to say that uh you know the system for the most part is not broken or flawed yeah that the inequalities part the um the inequality of outcomes as part of our world what we should strive for is the uh you know equality of opportunity yeah and i i do not dispute that as an abstraction but again to back up for a second i i do take issue with jordan's uh fervent devotion to the free market and his cavalier dismissal of marxist ideas which he has uh in my estimation uh mischaracterized in his public depictions let's get into it so he he just seems to really not like um uh socialism marxism communism yeah uh historically speaking sort of uh i mean how would i characterize it i'm not exactly sure i don't want to again he's yeah he'll eventually be here to defend himself john locke unfortunately not here to defend exactly but what's what's your sense uh about marxism and and uh the uh the way jordan talks about the way you think about it from the economics from the philosophical perspective yeah well like if we were all here together i'd say we need to start with marx's economic and philosophical manuscripts of 1844 before marx became more of a polemicist and i would argue that marx's political philosophy he's a crappy economist i don't dispute that but his arguments about human nature his arguments about the inevitably catastrophic psychological and environmental and economic effects of capitalism i would argue every one of those has proven quite right marx maybe did not have the answer but he saw in the 18 whenever he was writing um that inevitably capitalism um would lead to massive inequity that it was ultimately based on uh the need to denigrate and dehumanize labor to render them in his language a fleshy cog in a giant machine and that it would create a tension and conflict between those who own things and those who made things that over time would always you know the thomas pickerty guy who writes about capital and just makes the point that return on investment will always be greater than wages that means the people with money are going to have a lot more that means there's going to come a point where the economic house of cards falls apart now the joseph shumpters of the world they're like that's creative destruction bring it that's great so i think it's niles ferguson he was he's a historian he may be at stanford now he was at harvard you know he writes about the history of money and he's like yeah there's been 20 or whatever depressions and big recessions uh in the last several hundred years and when that happens half of the population or whatever is catastrophically inconvenienced but that's the price that we pay for progress other people would argue and i would agree with them that i will happily sacrifice the rate of progress in order to flatten the curve of economic destruction to put that in plainer english um i would um direct our attention to the social democracies that forgetting for the moment of whether it's possible to do this on a scale in a country as big as ours on all of the things that really matter you know gross domestic gdp or whatever that's just an abstraction but when you look at whatever the united nations says how we measure quality of life uh you know life expectancy education you know rates of alcoholism suicide and so on the countries that do better are the mixed economies they're market economies that have high tax rates in exchange for the provision of services that come as a right for citizens yeah so i mean i guess the question is you've kind of mentioned that uh you know like as marx described a capitalism with a slippery slope eventually things go awry in some kind of way so that's the question is when you have when you implement a system yeah how does it go wrong eventually you know the you know eventually we'll all be dead that's exactly right no no no that's right so and then the criticism i mean i think these days uh unfortunately marxism as like is a dirty word i i say unfortunately because even if you disagree with the philosophy it should you should uh like calling somebody a marxist yeah should not be a thing that uh shuts down all conversation no that's right and and the fact is i'm sympathetic with uh jordan's dismissal of the folks and popular the talking heads these days who spew marxist words um to me it's like fashionable nonsense do you know that book that the physicist wrote mocking uh you're too young so in the uh 20 or so years we're all pretty young really yeah that's right but they're i think they're with these nyu physicists they wrote a paper just mocking the uh kind of literary uh post-modern types you know yes oh those kinds of yeah yeah it was just nonsense and of course it was made the lead article um and and you know my poor is marx wouldn't be a marxist true i've read and listened to some of the work of uh richard wolff he speaks pretty eloquently about marxism i like him uh he's uh one of the only uh you know one of the only people speaking about a lot about marxism and the way we are now in in a serious way in it in a sort of saying you know uh what are the flaws of capitalism not saying like yeah basically sounding very different and people should check out his work no i it's all this kind of work this kind of outrage mob culture of uh sort of demanding equality equality of outcome that's not marxism it is not marxism he he didn't say that you know he literally said each what was it like each according to their needs and each according to their abilities or something like that so the question is the implementation like absolutely humans are messy so how does it go wrong like it just met there you go brilliant it's messy and this gets back to my rant about the book that i want to try if i don't stroke out why left and right are both beside the point you know the the people conservatives are right when they condemn liberals for being simple-minded by assuming that a modification of external conditions will yield changes in human nature you know you know again that's where marx and skinner are odd bedfellows you know here they are just saying oh let's change the surroundings and things will inevitably get better on the other hand when um conservatives say that people are innately selfish and they use that as the justification for glorifying the unbridled pursuit of wealth well they're only half right because it turns out that we can be innately selfish but we are also innately generous and reciprocating creatures there's remarkable studies i think they've been done at yale of you know babies 14 month old babies um if someone hands them a toy and then wants something in return babies before they can walk and talk will reciprocate all right fine if someone if they want a toy let's say or a bottle of water baby wants a bottle of water and i look like i'm trying to give it to the baby but i dropped the bottle so the baby doesn't get what she or he wanted when given a chance to reciprocate little babies will reciprocate because they're aware of and are responding to intention similarly if they see somebody um behaving unfairly to to someone they will not help that person in return so so my point is is yeah we are selfish creatures at times but we are also simultaneously uber social creatures who are eager to reciprocate and in fact we're congenitally prepared to be reciprocators to the point where uh we will reciprocate on the basis of intentions above and beyond what actually happened how so i mean your work is on the fundamental role of the fear of mortality yeah in ourselves how fundamental is this reciprocation this human connection to other humans well i think it's really innate yeah i think it's because yeah bats reciprocate uh not by intention but uh you know this i'm going here from richard dawkins uh the selfish gene you know to i love the early dawkins i'm less enamored like the early beat yeah no no again i say this with great respect but uh you know dawkins just points out that uh you know reciprocation is just fundamental cooperation is fundamental you know it is the it's a one-sided view of evolutionary takes on thanks when we see it solely in terms of individual competition it's it's almost from a game theoretic perspective too it's just easier to see the world that way it's it's easier to i don't know i i mean you see this in physics uh there's a whole field of folks like complexity yeah that kind of embrace the fact that it's all an intricately connected mess and it's just very difficult to do anything uh with that kind of science but it seems to be much closer to actually representing what the world is like so like you put it earlier lex it's messy so yeah left and right you mentioned you're thinking of maybe actually putting it down on paper or something yeah i would like to because what i would what i would like to point out again in admiration of all the people that i will then try and have the gall to criticize this look these are all geniuses um lock genius adam smith genius when he uses the notion that we're bartering creatures so he uses that reciprocation idea as the basis of his way of thinking about things but that's not at the core the murdering is not at the core of human nature it's not a well he says it is he says we're fundamentally bartering creatures well that doesn't even make sense then because then what how how can we then be autonomous individuals well because we're going to barter with an eye on on on for self for ourselves self yeah but all right so but back to adam smith for a second lex is like adam smith here's he's got the invisible hand and my conservative friends i'm like you need to read his books because he is a big fan of the free market and this is my other uh gripe with folks who support just unbridled markets adam smith understood that there was a role for government for two reasons one is is that just like locke people are not going to behave with integrity and he understood that one role of government is to maintain a proverbial you know even playing field and then the other thing smith said was that there's some things that can't be done well for a profit and i believe he talked about education and public health and infrastructure as things that are best done by governments uh because you can't you can make a profit but that doesn't mean that the institutions themselves will be maximally beneficial yeah so i i would uh i'm just eager to engage people by saying let's start with our most contemporary understanding of human nature which is that we are both selfish and tend to cooperate and we also can be heroically helpful to folks in our own tribe and of course how you define one's tribe becomes critically important but what some people say is look we let what would then be what kind of political institutions and what kind of economic organization can we think about to kind of hit that sweet spot and that that would be in my opinion uh how do we maximize individual autonomy in a way that fosters uh creativity and innovation and the self-regard that comes from creative expression while engaging our more cooperative and reciprocal tendencies in order to come up with a system that is potentially stable over time because the other thing about all capital-based systems is the stability is it fundamentally and unstable yeah because it's based on infinite growth and you know it's a positive feedback loop uh to be silly infinite growth is only good for malignant cancer cells and compound interest otherwise uh you know we want to seek a steady state and um that would be you know so when stephen pinker writes for example again great scholar but i'm gonna disagree when he says the world has never been better and all we need to do is keep making stuff and buying stuff so your sense is the world sort of in disagreement with stephen pinker that the world is um like facing a potential catastrophic collapse in multiple directions yes and the fact that there are certain like the the rate of violence and aggregate is decreasing the death you know the quality of life all those kinds of measures that you can plot across centuries that it's improving that doesn't capture the fact that our world might be this we might destroy ourselves in very painful ways uh in the in the in the next century so i'm with jared diamond you know in the book collapse where he points out studying um the collapse of major civilizations that it often happens right after things appear to never have been better and in that regard i mean there are more uh known voices that have taken issue uh with uh dr pinker i'm thinking of john gray who's a british philosopher and here in the states i don't know where he is these days but robert j lifton the psycho historian yeah they're both of my view and which i hope is by the way wrong uh me too yeah no but you know between um you know ongoing ethnic tensions environmental degradation economic instability and the fact that you know the world has become a petri dish of psychopathology like what what really worries me is the the quiet economic pain that people are going through the businesses that are closed your dreams that are broken because you can no longer do the thing that you've wanted to do and how i mentioned to you off camera that i've been reading uh the the rise and fall of the third reich and i mean the amount of anger and hatred and on the flip side of that sort of nationalist pride that can arise from deep economic pain like what happens with economic pain is you become bitter yeah you start to find the other whether it's other european nations that mistreated you whether it's other groups that mistreated you it always ends up being the jews uh somehow somehow our fault here yep that's what worries me is where this quiet anger and pain goes in 2021 2022 2030. if you look no sorry i'm sorry to see the parallels no no no rise and fall the third reich but you know what happens 10 15 years from now from what's because of the coved pandemic yeah that's happening now and lex you make a i think a really profoundly important point you know back to our work for a bitter ernest becker rather you know his point is is that the way that we manage existential terror is to embrace culturally constructed belief systems that give us a sense that life has meaning that we have value and in the form of self-esteem which we get from perceiving that we meet or exceed the expectations associated with the role that we play in society well here we are right now in a world where first of all if you have nothing you are nothing and secondly as you were saying before we got started today a lot of jobs are gone and they're not coming back and that's the where the self-esteem that's where the self-esteem and identity come in where people it's not only that you don't have anything to eat you don't even have a self anymore to speak of because the we typically define ourselves you know as marx put it you are what you do and now who are you when your way of life as well as your way of earning a living is no longer available yeah and it feels like that uh yearning for self-esteem that we could talk a little bit more because sure you about defining self-esteem is quite interesting the more i've read so warm with the core and just in general you're thinking it made me realize i haven't thought enough about the idea of self-esteem but the thing i want to say is uh it feels like when you lose your job then it's easy to find it's it's tempting to find that self-esteem in a tribe that's not somehow often positive that's exactly it's like a tribe that defines itself on the hatred of somebody else so that's brilliant and and this is what john gray the philosopher in the 1990s he predicted what's happening today he wrote a book about globalism and actually hannah arendt in the 1950s said the same thing in her book about totalitarianism when she said that you know that economics has reached the point where most money is made not by actually making stuff you know you use money to make money and that uh therefore what happens is money chases money across national boundaries ultimately governments become subordinate to the corporate entities whose sole function is to generate money and what john gray said is that that will inevitably produce economic upheaval in local areas which will not be attributed to the economic order it will be misattributed to who whoever the scapegoat du jour is and the anger what and the distress associated with that uncertainty uh will be picked up on by ideological demagogues who will transform that into rage so both hannah aren't as well as john gray they they just said uh watch out we're gonna have right-wingish populist movements uh where demagogues who are the alchemists of hate what makes them brilliant is they don't they don't the hate's already there but they take the fears and they expertly redirect them to who it is that i need to hate and kill in order to feel good about myself so back to your point lex that's right so the self-regard that used to come from having a job and doing it well and as a result of that having adequate resources to provide a decent life for your family well those opportunities are gone and yeah what's left so max weber german sociologist at the beginning of the 20th century um he said in times of historical upheaval um we are apt to embrace he was the one who coined the term charismatic leader right seemingly larger than life individuals who often believe or their followers believe are divinely ordained to rid the world of evil yeah all right now ernest becker he used weber's ideas in order to account for the rise of hitler hitler was elected and he was elected when germans were an extraordinary state of existential distress and he said i'm going to make germany great again all right now what becker adds to the equation is his claim that what underlies our affection for charismatic populist leaders good and bad is death anxiety all right now here's where we come in where egghead experimental researchers you know becker wrote this book the denial of death and he couldn't get a job people just dismissed these ideas as fanciful speculation for which there's no evidence and and you've done some good experiments yeah and here's where here's where i can be more cavalier and where what i would urge people i like what you said lex is ignore my histrionic and polemic language if possible and step back if you can myself included and let's just consider the the research findings because uh in september 11 2001 people that are old enough to remember that horrible day two days before um george w bush had the lowest approval rating in the history of presidential polling right three weeks later after he said we will rid the world of the evildoers and then a week or two after that he said in a cover story on time magazine that he believed that god had chosen him to lead the world during this to lead the country rather during this perilous time he had the highest approval rating and so we're like well what happened you know is what happened to americans that their approval of president bush got so high so fast well our view following becker is that 2001 was like a giant death reminder yeah the people dying plus the symbols of american greatness world trade center and and the the pentagon so we did a bunch of experiments and most of our experiments are disarmingly simple we have one group of people and we just remind them that they're going to die we say hey write your thoughts and feelings about dying or in other cases we stop them outside either in front of a funeral home or a hundred meters to either side our thought being that if we stop you in front of a funeral home then death is on your mind even if you don't know it and then there's other studies that are even more subtle where we bring people into the lab and they read stuff on a computer and while they're doing that we flash the word death for 28 milliseconds it's so fast you don't see anything and then we just measure people's reactions or behavior thereafter so what we found in 2003 leading up to the election of 2004 was that americans did not care for president bush or his policies in iraq in controlled conditions but if we reminded them of their mortality first they like bush a lot more so in every study that we did americans like john kerry who was running against bush they like carrie more than bush in a control condition yeah and but if if they were reminded of death first then they like bush a lot more so by the way just a small pause you said they're disseminally simple experiments i think that's um and people should read uh warm at the core for some other descriptions you have a lot of different experiences of this nature i think it's a brilliant experiment um connected to the stoics perhaps of uh how your world view on anything and how delicious that water tastes yes after you're reminded of your own mortality it's such a fascinating experiment that you could probably keep doing like millions of them to uh draw insight about the way we see the world no that's right lex and i appreciate the compliment not because we did anything but because what these studies many of which are now done by other people around the world in labs that we're not connected with what i'm most proud about our work i am proud of the experiments that we've done but it's not science until somebody else can replicate your findings and independent researchers are interested in in pursuing them i it's such a fascinating idea i don't have to think about a lot about the experiments you've done and that you've inspired about the fact that death changes the way you see a bunch of different things uh the i think the stoics talked about the uh i mean in general just memento mori like just thinking about death and meditating on death is a really positive not a positive it's an enlightening way to uh live life so what do you think about that at the uh and the individual level like what is the role about being bringing that terror of death fear of death to the surface and being cognizant of it for us that's the that's the ball game um so what we write in our book and here we're just um paying homage to the philosophers and theologians that come before us is to point out that literally since antiquity um there has been a consensus that to lead a full life requires um albert camus said come to terms with death thereafter anything is possible and so you've got the the stoics and you got the epicureans and then you got the tibetan book of the dead and then you got like the medieval monks that you know worked with like a skull uh on their desk and the whole idea i should back up a bit because and just remind folks that our studies you know when we remind people that they're going to die and we find that yeah they drink more water if a famous person um is is you know advertising it uh they eat more cookies they want more fancy clothes they sit closer to people that look like them it changes who they vote for but all of those things those are very subtle death reminders you don't even know that death is on your mind and so our point is is that and this is kind of counterintuitive and that is that the most problematic and unsavory human reactions to death anxiety are malignant manifestations of repressed death anxiety you know we try and bury it under the psychological bushes and then it comes back to bear bitter fruit but what the theologians and the philosophers of the world are saying is it behooves each of us to spend considerable time you don't have to be a goth death rocker you know wallowing in death imagery to spend enough time entertaining the reality of the human condition which is that you too will pass to get to the point well where there is to lapse into a cliche the capacity for personal transformation and growth let's go personal for a second uh are you yourself afraid of death yeah um i mean and how much do you meditate on that thought like uh maybe your own study of it is a kind of escape from your own mortality absolutely lex so you got it and like if you figure out death somehow you won't die so no no uh so my my colleagues and good friends jeff greenberg and tom pozinski you know we met in graduate school in the 1970s we've been doing this work for 40 years and we cheerfully admit even though it doesn't reflect well on us as humans that i should just speak for myself but i i feel like there's a real sense in which doing these studies and writing books and and lecturing has been my way of avoiding directly confronting my anxieties by turning it into an intellectual exercise and um and every once in a while therefore when i think that i'm making some progress as a human i have to remind myself that uh that is probably not the case um and that i have at times like all humans been more preoccupied with the implications of these ideas for my self-esteem uh it's like oh we're going to write a book and maybe we'll get to go on tv or something well no that's not the same as to actually think about it in a way that you feel it rather than just think it yeah no you did when you were eight that's exactly right so when i first read the denial of death i i was so literally flabbergasted by it that i took a leave of absence for a year and just like did what would be considered menial jobs i i did construction work i worked in a restaurant and i i was just like wait a minute if if i if i understand what this guy is saying then i'm just a culturally constructed meat puppet doing things for reasons that i know not yeah in order to assuage death anxiety and that's like that that that's not acceptable maybe another interesting person to talk about is ernest becker himself sure so how did he face his death is there something interesting personal i think so so interesting to me is becker also from a jewish family claimed to be atheistic did not identify ultimately as jewish i believe he converted to christianity but was himself a religious person and he said he became religious when his first child was born now religious what does that mean does he have a faith and well let's talk more most importantly is the afterlife he was his view on the afterlife he was uh agnostic on that but he did um now the denial of death is um there's a chapter devoted to kierkegaard and he talks about for kierkegaard um if you want to become a mature individual you know if you want to learn something you go to the university if you want to become a more mature individual according to kierkegaard you got to go to the unit you got to go to the school of anxiety and what kierkegaard said is that we have to let this vague dis ease put a hyphen between dis and ease about death kierkegaard's point is you have to really think about that you have to think about it and feel it you got to let it seek in or seep into your mind at which point according to kierkegaard basically you realize that your present identity is fundamentally a cultural construction you didn't choose the time and place of your birth you didn't choose your name uh you know you didn't choose necessarily even the social role that you occupy you might have chosen from what's available in your culture but not from the full palette of human opportunities and so what kierkegaard said is that we need to realize that we've been living a lie of sorts becker calls it a necessary lie and and we have to momentarily dispose of that and so now kierkegaard says well here i am i i have shrugged off all of the cultural accoutrements that i have used uh to define myself and now what am i or who am i this is like the ancient greek tragedy where the worst thing was to be no one or no thing all right at this point kierkegaard said you're really dangling on the precipice of oblivion and some people tumble into that abyss and never come out on the other hand kierkegaard said that what you can now do metaphorically and literally is to rebuild yourself from the ground up and there's a in the new testament there's something you have to die in order to be reborn and kierkegaard's view though is that there's only one way to do that this is his proverbial leap into faith and in kierkegaard's case it was faith and christianity that you can't have unbridled faith and cultural constructions the only thing that you can have unequivocal faith in is some kind of transcendent power all right but of course this raises the question of well is that just another death-denying belief system right and at the end of the denial of death becker admits that there's no way to tell while still advocating for what is ultimately a religious stance now one of the things that i don't understand and i becker has been the the most singularly potent influence in my academic and personal life but a year or two ago i i started reading uh martin heidegger i'm reading being in time and what i now wonder is why um why becker who refers to heidegger from time to time in his work why he didn't take heidegger more seriously because heidegger has this is like a secular kierkegaard he's he has the same thing which is death anxiety oh and i should have pointed out that what kierkegaard says is that death anxiety most people don't go to the school of anxiety they flee from death anxiety by embracing their cultural beliefs kierkegaard says they then tranquilize themselves with the trivial and i love that phrase it's a beautiful phrase because at the end of the denial of death backers like look the average american is either drinking or shopping or watching television and they're all the same thing right heidegger says the same thing he says look and he acknowledges kierkegaard he says what makes us feel unsettled and evidently that's an english translation of angst that that it's we don't feel at home in the world heidegger says that's death anxiety and one direction is the the kierkegaard one he heidegger calls it a flight from death you just unself reflexively cling to your cultural constructions and heidegger borrows the term tranquilized but he points out that he doesn't care for that term because tranquilized sounds like you're subdued when in fact what most culturally constructed meat puppets do is to be frenetically engaged with their surroundings to ensure that they never sit still long enough to actually think about anything consequential heidegger says there's another way though he's like yo what you can do is to come to terms with that death anxiety in the following way thing number one is to realize that not only are you going to die but your death can happen at any given moment so for heidegger if you say i know i'm going to die in some vaguely unspecified future moment that's still death denial because you're saying yeah not me not now yeah heidegger's point is you need to get to the point where you need to realize that uh you know i need to realize that i can walk outside and get smote by a comet or i can stop for gas on the way home and catch the virus and be dead in two days there were any number of potentially unanticipated and uncontrollable fatal outcomes but by the way sorry uh uh to bring into the now yeah it is brilliant i agree lex and this is why i'm i'm i'm wondering why didn't becker notice this because that's the being and time thing is it's got to be now right and then he says so okay so now i've dealt somewhat uh with the the death part and now he says now you've got to deal with what he calls existential guilt and he says well all right what you have to you have to realize that like it or not you have to make choices you know this is jean-paul sartre we are condemned by virtue of consciousness to choosing but heidegger is a little bit more precise he's like look as i was saying earlier you're in reality you're an insignificant speck of respiring carbon-based dust borne into a time and place not of your choosing when you're here for a microscopic amount of time after which you are not and for heidegger you have to realize that like i said i didn't choose to be born a male or jewish or in america the offspring of working class people and heidegger what he says is yeah but you still have to make choices and accept responsibility for those choices even though you didn't choose any of the parameters that ultimately limit what's available to you and moreover you're going to not always make good choices so now you're you're guilty for your choices and then he uses the the poet uh rilka he has a phrase becker uses it in the denial of death the guilt of unlived life i just love that you have to accept that you have already diminished and in many ways amputated your own possibilities by virtue of choices that you've made or just as often have declined to make uh because you are reluctant to accept responsibility for uh for the opportunities that you are now able to create by virtue of seeing the possibilities that lay before you so anyway heidegger then says look okay so uh you know i'm a professor and i live in america in the 21st century well if i was in the third century living in a year in mongolia i'm not going to have an opportunity to be a professor but what he submits is that there is some aspects of whatever i am that are independent of my cultural and historical circumstances in other words there is a me of sorts heidegger would take vigorous issues so would heidegger scholars because i'm not claiming to understand him this is my classic comic book rendering but heidegger's point is that you get to the point where you're able to say okay i am a contingent historical and cultural artifact but so what you know if i was you know now if i was transported a thousand years in the past in asia i'd be in the same situation i would still be conditioned by time and place i would still have choices that i could make within the confines of what opportunities are afforded to me and then heidegger says if i can get that far in this is his language he says that there is a transformation and he literally he calls it a turning you're turning away from a flight from death and you are allowed you therefore you see a horizon as his word of opportunity that makes you in a state of anticipatory resoluteness with solicitous regard for others that makes your life seem like an adventure perfused with unshakable joy all right let me unpack those things it is beautiful it is i love lex that you're resonating to the time thing so he's like okay we already talked about now anticipatory is is already hopeful because it's looking forward yeah right to be resolute it it means to be steadfast and and to just have confidence in what you're doing moving forward all right solicitous i had to look up all these words by the way is it just means that you are concerned about your fellow human beings and but i love the idea uh even if it seems allegorical i don't mind that at all this idea you said love earlier and i think that when heidegger is talking about being solicitous that's as close as he can get uh there's an italian yes uh sergeant job well so what was that line again with the solicitors of that okay all the words you said are just beautiful i love those words yeah anticipatory resoluteness that is accompanied with solicitous regard to our fellow humans which makes life appear to us to be an ongoing adventure that is permeated by unshakeable joy now again heidegger is not mary poppins this guy's got a tattoo uh no this is great i i just love that exact quote no i'm piecing together these are his exact words that and i spent the last two years reading almost everything that i can find because i want to i'm sick of death you said it so i want to second what you say lex so it's not about death it's the sherwood anderson guy he's a novelist that i like about uh he wrote a book called winesburg ohio and uh now i'm going to forget what he said on his tombstone but you know it was something to the effect oh he said life not death is the great adventure the the point being is that you know to consider that we must die and the existential implications of that really the goal the way i see it is getting from hate to to love yeah and i feel like heidegger has a way of thinking about things that moves us more in that direction and so that's kind of my current preoccupation is to take what i just said to you and to talk about it with my colleagues and other academic psychologists because the way we started with ernest becker remember i said earlier i wasn't trained in any of these things i'm an egghead researcher that was doing experiments about biofeedback and you know then we read these becker books and i thought they were so interesting that for the first few years we didn't have any studies i just would travel around and i'd be like here's what this becker guy says i think this is cool well my my present view is i'm like here's what this heidegger guy says i i think these ideas are consistent with what becker is saying because they are anchored in death anxiety but i like that direction as an alternative to the kierkegaardian insistence that the only psychologically tenable way to extricate ourselves uh from uh maladaptive reactions to death anxiety is through faith in the traditional sense yeah i i always kind of uh saw kierkegaard unfairly like you said in a comic book sense uh of the word faith as a non-traditional sense i kind of like the idea of leap of faith oh i love that idea and so what i've been babbling about with you know kierkegaard or heidegger you know i'm like yeah kierkegaard is a leap of faith in god heidegger is a leap of faith in life and i i just yeah i like it i found the leap of faith really interesting and so in the technological space so of um i've i've talked to on this thing with elon musk but i think he's also just in general for our culture a really important figure oh absolutely that takes uh i mean he's sometimes a little bit insane on on social media and just in life when i met him was kind of interesting that uh of course there's a i mean he's a legit engineer so he's fun to talk to about the technical things yeah but he also just just the way the humor and the way he sees life it just like refuses to be conventional yeah so it's a constant uh leap into the unknown and one of the things that he does and this doesn't even this isn't even like fake a lot of people say because he's a ceo there's a business owner so he's trying to make money no i think this is this is as i looked him in in his eyes i mean this is real is a lot of the things he believes that are going to be accomplished that a lot of others are saying are impossible like autonomous vehicles he truly believes it to me that is the leap of faith of on what was going like we're like the the entirety of our experience is shrouded in mystery yeah we don't know what the hell's gonna happen what you don't know what we're actually capable of as human beings and he just takes the leap he fully believes that we can you know we can go to we can colonize mars i mean how could how crazy is it to just believe and dream and actually be taking steps towards it yeah um to colonizing mars when most people are like that's the stupidest idea ever yeah well i'm i'm in agreement with you on that um you know two things you know one is it reminds me of ben franklin who in his autobiography you know has a similarly childish in the best sense of the word um unbridled imagination for what might become you know ben franklin's like yeah i i got electricity that's cool but we'll be levitating soon and i we can't even begin to imagine uh what we are capable of and of course people are like dude that's crazy and there's a guy let's it's fcs schiller some humanistic guy at the beginning of the 20th century he's like you know um lots of things that people think about may appear to be absurd to the point of obscene but the reality is historically every fantastic innovation has generally been initiated by someone who was condemned for being a lunatic and it's not that anything is possible but surely things that we don't try will never manifest as possibilities yeah and that's that's uh that there's something beautiful to that that's the uh embracing the abyss and again it's like the uh it's the uh embracing the fear of death the the the reality of death and then turning and to look at all the opportunities that's right let me ask you whenever i bring up ernest becker's work which i do and yours quite a bit i find it surprising how that it's not a lot more popular in the sense that uh no not i don't mean just your book yeah uh that's well written people should read it should buy it whatever uh i think it has the same kind of qualities that are useful to think about as like jordan peterson's work and stuff like that but i i just mean like why people uh are not don't think of that as a compelling description of uh the core of the human condition like i think what you mentioned about heidegger is quite connects with me quite well so i ask on this podcast i often ask people if they're afraid of death that's like almost every single part i almost always get criticized for asking world-class people scientists and technologists and about fear of death and the meaning of life and on the fear of death they often like don't say anything interesting what i mean by that is they haven't thought deeply about it like what yeah you kind of brought this up a few times of really letting it sink in yeah they kind of say this thing about what exactly you said which is like uh it's something that happens not today like i'm aware that it's something that happens yeah and i'm not the the thing they usually say is i'm not afraid of death i just want to live a good life kind of thing yeah and what i'm trying to express is like when i look in their eyes and the kind of the the core of the conversation it looks like they haven't really become like they haven't really meditated on death i guess the question is um what do i say to people that there's something to really think about here like there's some demons some realities that need to be faced yeah by more people well that's a tough one you know i could tell you what not to do you know so when we are young and annoying yeah um a lot of famous people mostly psychologists because that's who we intersected with that you know we would lay out these ideas and they would be well i don't think about death like that so these ideas must be wrong and we would say well you don't think about death because you're lucky enough to be comfortably ensconced in a cultural world view from which you derive self-esteem and that has it's spared you the existential excruciations that would otherwise arise but that's like freud you know you're repressing so you either agree with me in which case i'm right or you disagree with me in which case you're repressing and i'm right well so that that's the the the nietzsche thing i what i felt when i've there'd been a moment in my life moments in my life when i really thought about death i mean there's not too many like really really thought about it and feel the thing when you felt that eight maybe i'm traumatizing or romanticizing it but uh i feel like it's uh uh the conservatives call it popular like or the movie matrix call it the red pill yeah moment uh i feel like it's a dangerous thought because um i feel like i'm taking a step out of a society like there's a nice narrative that we've all constructed you are and i'm taking a step out and uh it feels there's this feeling like you're basically droughting i mean it's not a good feeling it is not but this gets back to the heidegger kierkegaard school of anxiety you are stepping out yeah and you are momentarily shrugging off the the again the culturally constructed psychological accoutrements that allow you to stand up in the morning and so i mean if that in that sense it feels like i mean uh what do you uh how do you have that conversation because i guess i i i'm dancing around a set of questions which is like i guess i'm disappointed that people don't are not uh as willing to step outside like uh even just uh even any kind of thought experiment yeah let's just forget uh denial death like um there's there's not a community of people let's to take an easy one that i think is scientifically ridiculous which is there's a community people that believe that uh the earth is flat yeah or actually even even better the space is fake yeah uh like what i find surprising is that a lot of people i talk to are not willing to uh be like imagine if it is like imagine the earth is flat like think about it right a lot of people just like no the earth is round they they're like uh like scientists yeah too they're like yes well actually wait have you actually like thought about it like imagine like a thought experiment that like basically step outside the little narrative that we are comfortable with now that one in particular is has a really strong uh evidence uh and scientific validation so on it's pretty simple thing to show that it at least is not flat uh but just the willingness to take a step outside of the stories that bring us comfort it's uh been disappointing that people are not willing to do that yeah and i think uh the philosophy that you've constructed and that ernest beck is constructed and you've tested i think it's really compelling and the fact that people aren't often willing to take that step yeah disappointing well yes but perhaps understandable i mean one of this is an anecdote of course but when we were trying to get a publisher for our book um i had him we had a meeting with um a publisher who published some malcolm gladwell books yeah and she said i'm very interested in your book but can you write it without mentioning death because people don't like death and we're like now it's really kind of central um and i think that's part of it i think again if these ideas have merit and i actually like the way that you put it lex it's that to step away is to momentarily expose yourself to all of the anxiety yeah that our identity and our beliefs typically enable us to manage i think it's as simple as that yeah i i had this experience um in college with my best friend uh who got really high uh and he forgot it was uh in the winter it was really freezing it was memorable to me i think it's an analogy very useful uh so he went to get some pizza and of course and uh he so i and he left me outside and said i'll be back in five minutes and he forgot that he left me outside and i remember it was i was in like shorts yeah it was freezing winter wow and i remember standing outside it's a dorm and i'm looking from the outside in it's a light and it's warm and i'm just standing there frozen i think for an hour or more and i that's how i think about it like i just i don't give a damn about the stupid winter or any i just want to i'd like it's like a i'm drawn to be back to the warm yeah and that's how i feel about thinking about like death it's like yeah at a certain point it's like it's too much it's like that cold i like i want to be back into the warmth back you know getting back to heidegger for a moment i i like the yeah he uses a lot the idea of feeling at home uh not as like in your house but just feeling like you're comfortably situated maybe you could talk about like i had a conversation about this with my dad a little bit um how does uh religion relate to this i see it as the the disease and the cure um in in a sense um a few things um one is that i think a case could be made that humans are innately religious uh so now we're going to get into territory where there's going to be a lot of disputes um and by what do you mean by religious the religion is an evolutionary adaptation and religion is like a belief in something outside of yourself kind of thing not necessarily so here we got to be a little bit more careful um and again i'm not a scholar how about i'm a well-intentioned dilettante in this in this regard yeah because what what i have read is that religion um evolved very early on long before our ancestors were conscious and the issue of death arose um and that um the word religion evidently is from a latin word regatta we can look it up but and it means to bind and emil durkheim the dead french sociologist he said you know originally religion is a darce lassen who's a dead novelist she calls it the substance of we feeling that it's literally that it arose because we're uber social creatures who from time to time took comfort in just being in physical proximity with our fellow humans and that there is this kind of sense of transcendent exuberance just back to the unshakable joy that heidegger alludes to and that the original function of religion was to foster social cohesion and coordination and that it was only subsequently some claim that a burgeoning level of consciousness made it such that religious belief systems that included the hope of some kind of immortality were just naturally selected thereafter so there are some people so it's david sloane wilson wrote a book called darwin's cathedral and he said religion has nothing to do with death it's a it evolved to make groups viable he's actually a group selection guy what's group selection um the idea that um it's the group that is selected for rather than individual yeah so people have vigorous disagreements about that but i guess our point would be we see religion as being inextricable inextricably connected ultimately to assuaging concerns about death well i guess another question to ask around this uh like what what does the world look like without religion will we if it's uh an extrapolate inextricably connected uh to our fears of death do you think it always returns in some kind of shape maybe it's not called religion but whatever it just keeps returning yeah who knows so that's a that's a great question alex so this woman named karen armstrong she was a non-turned historian and she's i can't remember the name of the book but no matter she we could look that up but if you want i can look it up but i can also i'll just yeah add it to me okay yeah her point it has god in the title of course but you know she's like look all religions are generally fairly right-minded in that they advocate the golden rule and all religions at their best do seem to foster pro-social behavior towards the in-group and that confers both psychological as well as physical benefits that's the good news and the bad news is historically all religions are subject to being hijacked by a lunatic french who declares that you know they're the ones in sole possession of the liturgical practices or whatever they call them and they're the ones that turn you know religion at its best into your crusades and holocausts my view not that it should matter for much but i i'm i grew up just skeptical of religion because i'm like as a kid i'm like well if we didn't have these beliefs we wouldn't be killing each other right because of them and i'd be like to my parents well you're telling me that all people should be judged on the merits of their character but don't come home if you don't marry a jewish woman right which is implying that if you're not jewish you're an inferior form of life yeah that's what tribes always do yeah and there's the tribal thing and so there's a guy named amin malouf a lebanese guy who writes in french who in the 1990s i think wrote a book called in the name of identity violence and the need to belong and that was his point is unless we can overcome this tribal mentality this will not end well but but you said earlier something lex that i think is profound and profoundly important and that is you did not recoil in horror when i mentioned kierkegaard's use of the term faith and so i'm a big fan of faith and i'm not sure what that implies i i have and by the way this is just a peripheral comment but i find less resistance to becker's ideas and our work when i'm in like jesuit schools you know it's the americans that you know the secular humanists who are most disinclined to accept these ideas it's an important side comment because uh i think it's mostly because they don't think philosophically that's i mean i speak with a lot of scientists and um i think that's my main uh criticism is is you don't i mean that's the problem with science exactly is it's so comforting to focus in on the details that you can escape thinking about the mystery of it all the big picture things the philosophical like the fact that you don't actually know shit at all like that that uh that that yeah so that in terms of jesuit like that's yeah that's the beauty of uh the experience of faith and so on is like uh how wherever that journey takes you is you you actually explore the biggest questions of our world yeah yeah so i don't see religion going away because i don't see humans as capable of surviving without faith and hope and everyone from the pope to elon musk will acknowledge that it is a world that is unfathomably mysterious and like it or not in the absence of beliefs here i'm charles purse the pragmatic philosopher he just said beliefs are the basis of action if you don't have any beliefs you're paralyzed with indecision whether we're aware of it or not whether we like it or not in order to stand up in the morning you have to subscribe to beliefs that can never be unequivocally proven right or wrong well then why do you maintain them well ultimately it's because of some form of faith but also also faith shouldn't be a dogmatic thing that uh you should always be leaping yeah i guess uh the problem with science or with religion is uh you could sort of uh all of a sudden take a step into a place where you're super confident that you know the absolute truth of things there you go and again back to socrates plato back in the cave uh you know at skidmore where i work that's what i have the students read in their first week you know and plato's like oh look at all those poor bastards you know they're in the cave but they don't know it you know and then they are freed from their chains and they have to be dragged out of the cave by the way which is another interesting point they don't run out uh but that gets back to why people don't like to be divested of their comfortable illusions but anyway they get dragged out of the cave into the sunlight which he claims is a representation of truth and beauty and i say to the students well what's wrong with that and they're like nothing that's like awesome and then i'm like yo dudes you out of the cave but how do you know that you're not in another cave the illumination may be better right but the minute you think you're at the end of the proverbial intellectual slash epistemological trail then you have already succumbed to either laziness or dogmatism or both that's really well put that's both terrifying and exciting that we're always it's uh there's always a bigger cave a little bit of an outdoor question but i think some of the interesting qualities of the human mind is the ideas of intelligence and consciousness so what do you make of consciousness so do you think death creates consciousness like the fear of death the terror of death creates consciousness and um consciousness in turn magnifies the terror of death i do um i i think what is consciousness to you oh don't ask me that so now if i could answer that you know i'd be chugging rum out of a coconut with my nobel prize that um you know it's literally you know stephen pinker i do agree with his claim and i think how the mind works that it is the key question for the psychological sciences broadly defined in the 21st century what is conscious yeah what is consciousness and i don't think it's an epi phenomenological afterthought so a lot of people i think dan wagner at harvard uh a lot of folks consider it just the ass end of a process that by the time we are aware of what it is it's just basically an integrated rendering of something that's already happened you know evidently the there's a half-second delay between when something happens you know those studies and our awareness of it um um yeah and that's where like ideas of free will will step in yeah you can explain away a lot of stuff and i think those are all important and interesting questions uh i'm of the persuasion i mean even not even but the dawkins in the selfish gene um is very thoughtful actually in a lot of it's actually more in notes than in the text of the book but he's just like it's hard for me to imagine that consciousness doesn't have some sort of important and highly adaptive function and what dawkins says is he thought about it in terms of just the that we can do mental simulations that uh one possibly extraordinary product of consciousness is to rather than find out often um by adverse consequences through trying something would be to run mental simulations and so one possibility is that consciousness is highly adaptive another possibility is uh nicholas humphrey a british dude who wrote a book about i think it's called regaining consciousness and he hypothesized i think this 1980s maybe even earlier the consciousness arose as a way to better predict the behavior of others in social settings that by knowing how i feel makes me better able to know how you may be feeling this like the rudiments of a theory of mind and that it really may not have had anything to do with intelligence so much as social intelligence right so so in that sense consciousness is a social construct like yes it's just a useful thing for us interacting with other humans yeah i don't know so but there seems to be something um about realizing your own mortality that's somehow intricately connected to the idea of consciousness well i think so also so this is where um and and nietzsche um he said a solitary creature would not need consciousness oh what do you think well i don't know what i think about that but what i do and then he goes on to say that consciousness is the most calamitous stupidity by which we shall someday perish and wow i was like dude relax [Laughter] but so what if you say you were on an island alone and you saw a reflection of yourself in in the water uh like if you were alone your whole life yeah great question his view nietzsche's view would be that your thoughts of yourself would never come to mind i don't know how i feel about that though in a sense this sounds weird but in a sense i feel like my mental conversation has always been with death it's almost like another you know um another notion like um you know there's these visualizations of yeah of a death in the cloak like i always felt like i am a living thing and then there's an other thing that is the end of me and i'm having like a conversation with that so in the sense that's uh that's the way i construct my the fact that i am a thing is because there's somebody else that tells me well you won't be a thing uh eventually wow so it feels like a conversation uh perhaps but that's uh that might be kind of this mental stimulation kind of idea that you're you're kind of it's not really it's a conversation with yourself essentially sure yeah but yeah i don't know how i feel about that but i i tend to be in agreement with you when we're talking about economics more so that uh that we're deeply social beings like everything the way it just feels like we're humans i'm i'm with uh a harare with the sapiens that we're kind of we seem to construct ideas on top of each other and that's a fundamentally a social process absolutely i think that's a fine book it overlaps considerably with our take on these matters and the fact that we get to these points drawing on different sources i think makes me more confident that it's so it's so fascinating just like reading your book i'm sorry on a small tangent uh that sapiens is like one of the most popular books in the world like yeah and it's reading your book it's like well this sounds yeah i mean like i don't know i don't know what makes a popular book yeah well if you want me to be petty and stupid i will tell you that from time to time um we also wonder um why our book you know like all books people um can take issue with it but we thought it would be a bigger hit that would be more widely read it's funny because i i've um i don't know if i have good examples because i forgot already but i'm often saddened by like franz kafka i think he wasn't known in his life yeah but i always wonder like these great yep like some of the greatest books ever written are completely unknown during the other lifetime and it's like man for some reason that it's again this that identity thing i think oh man that sucks well i'm comforted by that so van gogh sold one painting in his life and evidently uh thoreau sold like 75 copies of walden uh nietzsche's books did not sell well and how did ernest beck herself he he is the uh his books are published by the free press and have sold more than any other books um that they have published so so what does that mean it's a lot i i don't know if it's like jordan peterson millions but it's hundreds of thousands was he respected i just don't see him i okay yeah uh i don't see him brought up as a like in the top 10 philosophers of no not at all so how far away is he is he in the top 100 for people i don't think so like he doesn't he's not brought up that often because again like your work is brought up more often yeah like term like because i think it gotten yeah yeah i mean i think he's one of the great philosophers of the 20th century so what what we say lex is that our goal certainly when we first started and now just as much actually but what i say at all my talks is look if these ideas have interest you enough to go read ernest becker then this has been good i consider him to be one of the most important voices of the 20th century who does not get the attention that he deserves all right similarly our work i believe to be important because point by point we provide empirical corroboration for all of the claims if you know when um that so that's literally the students that read the denial of death and then escape from evil they're like yeah wow every chapter of the book you have studies and i'm like yeah because for 40 years if a skimmer student said oh that's got to be bullshit i'm like well let's do a study let's do a study and my own dreams are in creating uh robots and artificial intelligence systems that a human can love and i think there's something about uh mortality and fear mortality that is essential for implementing in our ai systems yeah and so maybe can you comment on that like well uh on uh so this is this is a different perspective on on your work sure which is like how do we engineer a human yeah so no this is awesome lex i'm delighted that you said that first of all and i may mention this to you and i don't i can't remember because i'm seen out when you first contacted me yeah i had just been told i have to learn more about your work because i'm working with some very talented people in new york and they're they're writing a screenplay uh for a movie about an artificial intelligence it's a female a.i set in like 30 years in the future and basically the little twist this is how i had to read heidegger so these people call me and they're like we're making a movie it's based on becker and your work and heidegger and this other philosopher levinos and then another philosopher sylvia benso who's an italian philosopher and the long short story is the movie is about supposedly the most advanced artificial intelligence entity an embodied one and who human form human form who finds out who is having uh having essentially existential anxieties and the i think the project is called a dinner with her or something and it doesn't really matter but the punch line is that she finds out that her creator has made her mortal and so the question is what happens phenomenologically and behaviorally to an artificial intelligence who now knows that it's mortal and it's actually the same question that you're posing yeah and that is is that necessary in order for an ai to approximate humanity yeah i think yeah so the intuition again it's uh it's unknown but i think it's absolutely i think it's absolutely necessary um a lot of people this the same kind of shallow thinking that people have about our own end of life our own death is the same way people think of i think about artificial intelligence it's like well okay so yeah so within the system there's a there's a terminal position where like there's there's a there's a point which it ends you just the program ends uh there's a goal state there's a you reach the end point but the thing is uh making that end a thing that's also within the program like like the making the thing like and then it's also the mystery of it so the thing is we don't know what the hell this death thing is i mean it's not like um it's not like we i mean the program doesn't give us information about the meaning of it all exactly and the that's where the terror is i and and i it feels like i mean uh in the language that you you would think about is um is the terror of this death or like anticipation of it or thinking about it is the creative force that builds everything right and that feels like uh you know that feels really important to implement again very difficult to know how to do technically currently but it's important to think about what i find is you mentioned like screenplays and so on is sci-fi folks and uh philosophers are the the only ones thinking about it currently and that's what these folks have convinced me yeah and engineers aren't which is uh i get yeah most of the most most of the things i talk about i get kind of um people roll their eyes from the engineering person not these folks that they're like because like again i saw your name and they're like wait a minute i've just seen that they're like here's someone you should check out yeah so this was a delightful confluence yeah i was a huge fan of um your work and ernest becker and um it's funny that not enough people are uh talking about it yeah i don't know what to do with that i think that there's a possibility to create real deep meaningful connections between ai systems and humans absolutely and um i think some of these things the fear mortality are essential that are essential for the element of human experience i don't i don't think it might be essential to create general intelligence like very intelligent machines but to create a machine that connects to a human in some deep way what's your view not to make me the interviewer but what's your view about um machine ethics can you imagine an ethical ai without some semblance of yeah that's a finitude let's say well i i think ethics uh it's a you know there's a there's a trolley problem that's often used in the work that i've done my team yeah with uh with autonomous vehicles in particular oh yeah yeah uh that people i think they offload they ask like how would a machine deal with an ethical situation that they themselves humans don't know how to deal exactly and so i don't know if a machine is able to uh do a better job on difficult ethical questions but i certainly think to behave properly and effectively in this world it needs to be uh have a fear of mortality and like be able to even dance because i don't think you can solve ethical problems but you have to uh i think like ethics is like a dance floor you have to just you have to uh dance properly with the rest of the humans like if people are dancing tango you have to dance in the same kind of way and for that you have to have a fear of mortality like i think of uh more practically speaking like i said autonomous vehicles like the way you interact with pedestrians fundamentally has to have a sense of mortality so uh when pedestrians crossed the road and now i've watched well certainly 100 plus hours of pedestrian videos there's a kind of social uh contract where you walk in front of a car and you're putting your life in the hands of another human being that's right and like death is is uh is in the car in the game that's being played death is right there uh it's part of the calculus it's not but it's not like a simple calculator it's not a simple equation it's uh it's an s it's a i mean i don't know what it is but it's it's in the it's in there and uh it has to be part of the optimization problem like it's not as simple as so from the computer vision from the artificial intelligence perspective it's detecting there's a human estimating right estimating the trajectory like treating everything like it's a billiard balls as opposed to like being able to construct an effective model the world model of the what the person's thinking what they're going to do what are the different possibilities of how the scene might evolve i think requires having some sense of yeah fear of fear of mortality of mortality i don't see the thing is i think it's really important to think about i i can be honest enough to say that it's i haven't been able to figure out how to engineer any of these things right uh but i do think it's really really important like i have uh so i have a bunch of roombas here i can show it to you after uh that i have roombas as a robot that has um vacuums the floor and i've had them um make different sounds like i had them scream in pain and it it it you immediately anthropomorphized absolutely and it creates uh i don't know knowing that they can feel pain but see i'm i'm speaking like knowing uh that i immediately imagine that they can feel pain and it means it immediately draws me closer to them yes at the human experience and that there's there's something in that that should be engineered in our in our systems it feels like i i believe personally i don't know what you think but uh i believe it's possible for a robot and a human to fall in love for example in the in the future oh i think it's yeah it's already there no there's a certain kind of deep connection with technology yeah in a real like you would choose to marry um i mean again it sounds uh i'll find a book title and i'll send it to you and it's a serious consideration of people who started out with these sex dolls but it turned into a relationship of enduring significance that the woman who wrote the book is not willing to dismiss as a perversion yeah that's what uh you know people kind of joke about sex robots which is funny uh like it's a it's a funny i mean there's a lot of stuff about robots it's just kind of fun to talk about that is it's not necessarily connected to reality uh people joke about sex robots but if you actually look how sex robots which are pretty rare these days are used they're not used by people who want sex especially they're actually uh they're companions they're compared they become companions yeah baby it's uh yeah it's fascinating and they're just we're not even talking about any kind of intelligence we're talking about just i mean human beings see companionships we're deeply lonely i mean that's the other sense i have that i don't know if i can articulate clearly you can probably do a better job but i have a sense that there's a deep loneliness within all of us absolutely in the face of death it feels like we're alone so you know the what drew me to the existential take on things lex was the uh who is it rallo may and irwin yalum right about existentialism and they're like look it what there's different flavors of existentialism but they all have in common what is it four universal concerns the overriding one is about death and that next is choice and responsibility the next one is existential isolation and they're like that's one of the things about consciousness that and the last one is meaninglessness but the existential isolation point is you know we are by virtue of consciousness able to apprehend that unless you're a siamese twin you are fundamentally alone and because it is claimed it's eric fromm uh in a book called escape from freedom he's like look you you're smart enough to know that the most direct way that we typically communicate with our fellow human beings is through language but you also know that language is a pale shadow of the totality of our interior phenomenological existence therefore there's always going to be times in our lives where even under the best of circumstances you could be trying desperately to convey your thoughts and feelings and somebody listening could be like yeah i get it i get it i get it and you're like you have no fucking idea what i'm talking about yeah so you can be desperately lonely in a house where you live with 10 people in the middle of tokyo where there's millions yeah yeah it's the great gatsby yeah you could be alone precisely exactly maybe this is a small tangent but let me ask you on the topic of academia you're kind of uh we talked about jordan peterson there's a lot of sort of renegade type of thinkers uh certainly in psychology but it applies in all disciplines of what are your thoughts about academia being a place to uh harbor people like yourself that you know people who think deeply about things who are not constrained by sort of the who i don't think you're quite controversial no not really but you are a person who thinks deeply about things and it feels like academia can sometimes stifle that i think so so my concern right now lex for young scholars is that um the restrictions and expectations are such that it's highly unlikely that anybody will do anything of great value or innovation except for and this is not a bad thing but stepwise improvement of existing paradigms so the you know in simple english you know i went to princeton for a job interview 40 years ago and they're like what are you gonna do if we give you a job and i'm like i don't know i want to think about it and read and um and i i saw that that interview was over the window of opportunity shut in my face and they actually called my mentors and they're like what are you doing tell this guy to buy some pants i had hair down to my waist also it's like this guy looks like charles manson of jesus but the expectation is that you come to a post you know you start publishing so that you can get grants that's certainly true but there's also kind of a behavioral thing you said like long hair there's uh there's a certain style of the way you're supposed to behave for example like i'm wearing a suit it sounds con it sounds weird but i feel comfortable in this you know i wore it like when i was teaching at mit i wore it sure uh warranty meetings and so on the different uh sometimes a blue and red tie but like that was an outsider thing to do at mit so like there was a strong pressure to not wear a suit no that's right it's and there's a pressure to behave to have a hair thing no that's right the way you wear your hair the way you uh this isn't like a liberal or a level anything he's just the pr in tribes that's right and academia to me or a place any place that dreams of having like renegade free thinkers like really deep thinkers should in fact like glorify the outsider right yeah should welcome just should welcome uh you know uh people that don't fit in yeah no that sounds weird but i don't know i could just imagine an interview with at princeton you know like i imagine why aren't people why aren't you at uh harvard for example or mit um yeah well so that look i would love to uh you know i i haven't lectured at mit but i've lectured at harvard i i i've gotten to lecture at almost every place that wouldn't consider me for a job yeah and i um well a few things i'm lucky because i you know i go to princeton and i'm like i don't know what i want to do and then two days later i go to skidmore and i'm like i don't know what i want to do and they offered me a job later that day which i declined for months because of the extraordinary pressure of my mentors who right-mindedly felt that i wouldn't get much done there and but what they told me at skidmore was take your time you know show up for your classes and don't molest barnyard animals and you'll probably get tenure and i'm like i'll show up for my classes we'll talk it was that was the negotiation yeah i negotiated i drove a hard bargain but but honestly lex that's i feel i'm very committed to skidmore because i i was given tenure when our first terror management paper wasn't published it took eight years to publish it was rejected at every journal and i submitted it as like a purple ditto sheet thing i'm like here's what i've been doing here's the reviews here's why i think this is still a pretty good idea and i don't know that this would happen even at skidmore anymore but i i was very lucky to be given the latitude and to be encouraged i i took classes at skidmore that's how i learned all this stuff i i graduated i got a phd unscathed by knowledge we were great statisticians and methodologists but we didn't have any substance you know i and i don't mean this cynically but we were trained in a method in search of a question so i appreciate having five years at skidmore basically to read books and i also appreciate that i look like this 40 years ago and my view is that this is how i comported myself other people might the guy i learned the most from at skidmore is now dead a history professor ted kuroda he wore a bow tie and there's another guy darnell rucker who taught me about philosophy and he was very proper and he had like his jacket with like the leather patches but these guys weren't pompous at all they were this is the way i am and i always felt that that's important that somebody who looks at you and says oh what a stiff he's probably an mba yeah well they're wrong yeah and someone who looks at me when i first got to skidmore other professors would ask when i'd be coming to their office to empty the garbage they just assumed you know i was in my 20s they assumed i was housekeeping i always felt that was important that the students learned not to judge an idea by the appearance of the person who pervades it and yeah i mean that's uh i i guess this is such a high concern now because i personally still have faith that academia is where the great geniuses will come from i do too and great ideas i love hearing you say that i i still and it's one of the reasons why um really apprehensive about the future of education right now in the context of the pandemic i um oh yeah is that a lot of folks i need a lot of these are google type people who i don't you know they're geniuses also but i don't like this idea that all learning can be virtual and that much could happen i'm big on embodied environments with actual humans yeah they're interacting i mean there's there's so much to the university education but i think the key part that i is the the mentorship that occurs somehow and at the human level like i've gotten a lot of flack like this conversation we're in in person now and i've uh even with edward snow snowden who done all interviews remote i'm a stickler to in person it has to be in person like and a lot of people just don't get it they're like well why can't this is so much easier like why go through the pain like i've traveled i'm traveling in the next month to paris for a single stupid conversation nobody cares about just to be in person well it's important to me i i honestly i was like this and thank you for coming down today well it's my pleasure but again very self-serving i've enjoyed this i knew i was going to but it's not about our enjoyment per se again at the risk of sounding cavalier there are a host of factors beyond verbal yeah that i don't believe can be adequately captured i don't care how much the acuity is decent on a zoom conversation i i feel again i i felt within five minutes that this was gonna be for me easy in the sense that i could speak freely i just don't see that happening so easily from a distance yeah i i tend to well i'm hopeful uh i agree with you on the current technology but i am hopeful unlike some others on the technology eventually being able to create that kind of experience oh i think we're quite far away from that but yeah it might be able my hope is i'm you know i'm i'm hopeful i was at microsoft in seattle and i can't remember why and no i i can't i i that's how i'm in my early mr magoo phase and and somebody there was showing us like a virtual wall where the entire wall you know when you're talking to somebody so it's life-size and they were beginning the get the appearance of motion and stuff it looked pretty yeah with virtual reality too i don't know if you've ever been inside a virtual world yeah it's to me it's uh i can just i can see the future it's uh it's it's quite real yeah in terms of like a terror of death uh i'm afraid of heights me too and there's i don't know if you've ever tried uh you should if you haven't there's a virtual reality experience where you can walk a plank yeah you can look down and oh man i was on the ground like i was like i was afraid i was deeply afraid i was is it was it was as real as uh yep as anything else could be in i mean these are very early days of that technology relatively speaking so um yeah i mean i don't know what to do with that same with like crossing the street we did these experiments across the street in front of a car and uh you know it's being run over by a car uh it's terrifying yeah it's just that uh yeah so there is a rich experience to be created there we're not there yet but uh uh i yeah and i've seen a lot of people try like you said the google folks uh uh silicon valley folks try to create a virtual online education i don't know i think they've raised really important questions absolutely what makes uh the education experience fulfilling what makes it effective yeah these are important questions and i think what they highlight is we have no clue like uh there's a thomas soul uh wrote a book about uh recent book on um charter schools yeah i would like to talk to him yeah he's an interesting guy we will disagree about a lot but respectfully yeah such a powerful mind yeah uh but he i i need to read i've only heard him talk about the book uh but he argues quite seemingly effectively that that um that the public education system is broken that we blame he basically says that we kind of blame uh like the conditions or the the environment but uh the upbringing of people like parenting blah blah blah like the uh the set of opportunities but okay putting that aside it seems like charter schools no matter who it is that attends them does much better than in in public schools and he puts a bunch of data behind it and in his usual way as you know just is very eloquent in arguing his points yep so that to me just highlights man we don't education is like one of the most important the it's probably the most important thing in our civilization and we're doing a shitty job of it yeah in academia in uh uh in university education and you know younger education the whole thing the whole thing and yet we value um just about anyone or anything more than educators you know part of it is just the relatively low regard that americans have for teachers for teachers so also similarly like um just people people of service i think great teachers uh are the greatest thing in our society and i would say now on a controversial note like black lives matter uh you know great police officers is the greatest thing in our society also like all people that do service we undervalue cops severe like this whole defund the police is missing the point and it's a stupid word uh i'm i'm with you on that one our um neighbors to one side of our house or three generations of police our neighbors across the street our police they know my uh you know political predilections and we've gotten along fine for 30 years and i go out and tell them every day you know when you go in today you tell the people on the force that i appreciate what they're doing i i think it's really important to not tribalize those concerns i mean we mentioned so many brilliant books and philosophers but it'd be nice sort of in a focused way try to see if we can get some recommendations from you so what three books technical or fiction or philosophical had a oh man that's the worst question what had a big impact in your life and you were recommending i spent four hours driving here perseverating about that i didn't i everything else you sent me that's fine and i actually i skimmed it and i'm like i don't want to look at it because i want i want us to talk yeah the ones in blue i'm like all right and you know i've already said that i've found becker's work and i've put the denial of death out there um is that his best sorry i don't have a small tangent is there other books of his yeah see if i could have this count as one that the the birth and death of meaning the denial of death and escape from evil are three books of ernest becker's that i believe to all the profound in a in a little sort of brief dance around topics uh i've only read denial death like how do those books connect in your yeah nice so the the birth and death of meaning is where becker situates his thinking in more of an evolutionary foundation so i like that for that reason escape from evil is where he applies the ideas in the denial of death more directly to economic matters and to inequality and also to our inability to peacefully co-exist with other folks who don't share our beliefs so i would put ernest becker out there as one um i also like novels a lot and here i was like god damn it no matter what i say i'm gonna be like yes but but the existentialist do you like all those folks camus you like that literary existence i i i do but i i mean you know i i've read all those books i i will tell you the last line of the plague we learn in times of pestilence that there's more to admire in men than to despise and i love that yeah um plagues such a i don't know i i find the plague is a brilliant me too before before uh the plague has come to us in 2020 it was just yeah yeah so a book about love about but i'll toss a one that may be less known to folks i i'm enamored with a novel by a woman named carson mccullers written in 1953 called clock without hands and i find it a brilliant literary depiction of many of the ideas that we have spoken about fiction fiction yeah what's uh what kind of ideas are we talking about all of the existential ideas that we have encountered today but in the context of a story of someone who finds out that he is terminally ill it's set in the south in the um heyday of like segregation so there's a lot of social issues a lot of existential issues but it's basically a nov a fictional account of someone who finds out that they're terminally ill and who reacts originally as um you might expect anyone uh becomes more um hostile to people who are different like petty and stupid denies that anything's happening but as the book goes on and he comes more to terms um with his own mortality um it ends lovingly and back to your idea about you know love being incredibly potent that's the the nice thing as you mentioned uh before with with heidegger i really like that idea and i've seen that in people who are terminally ill is they bring you know the idea of death becomes uh current yes it becomes like a thing you know i could die i really like that idea i i can die not just tomorrow but like now now now yeah that's a really useful i don't even know i think i've been too afraid to even think about that like i have like like sit here and think like in five minutes it's over yeah this is it it's five minutes it's over yeah so that would be my most recent addition as i i really am struck by heidegger or would you recommend that well okay well if you have a few years i remember i tuned out being in time i was like i tried to read it i was like that's it look it took me 40 years to read ulysses i could not get past the first five pages and it took me 40 years to read being in time it's a slog yeah and i took a james joyce course in college so i've uh i i i even uh i i guess read parts of finnegan's wake no way but like re there's a difference between reading and like [Laughter] i don't think i understood anything i i like his uh short stories the dead yeah yeah and um i like faulkner absalom absalom is is a fine book but would you uh is there something heidegger connected in a book you would recommend or no no so maybe i got to abandon him i mean i mean being in time is awesome um but here's an interesting thing and not to get all academic-y but you know it's there's two parts to it and most of the most philosophers are preoccupied with the first part it's in the second part where he gets into all the flight from death stuff and this idea of uh you know a turning and philosophers don't like that and i'm like this is where he's starting to really shine to really shine before me so yeah yeah all right that's a beautiful set of books so what um advice would you give to a young person today about their career about life about uh how to survive in this world full of suffering yeah great um yeah my advice is to get confident advice when i tell my students it's like don't listen to me don't listen to me well you know i think um my my big piece of advice these days is you know again it's that the risk is sounding like a simpleton but it's to emphasize a few things one is um you know so one of your questions i think was you know what's the meaning of life and of course the existentialists say life has no meaning but it doesn't follow from that that it's intrinsic that it's meaningless you know what the existential point is not that life is meaningless so much as it doesn't have one inevitable and intrinsic meaning you know which then it opens up you know i think it was kierkegaard who said consciousness gives us the possibility of possibilities and but there's another lunatic oswald spangler who wrote a book called decline of the west and he says that the philosopher the german philosopher guerta he says the purpose of life is to live and i let that's so that's one of my pieces of advice so the the possibility of possibilities it's interesting so what do you do with this kind of sea of possibilities like well this is one of the one when young folks talk to me especially these days uh is there swimming in a sea of possibilities yeah well so this is it's great and so that's another existential point which is that we yearn for freedom we react vigorously when we perceive that our choices have been curtailed and then we're paralyzed by indecision in the wake of seemingly unlimited possibilities because we're not choking on choice and and i'm not sure if this is helpful advice or not but what i say to folks is that the fact of the matter is is that you know for most people choice is a first world problem and sometimes the best option is to do something as silly as it sounds and then if that doesn't work do something else which just sounds like my mom torturing me when i was young but you know part of the thing that i i find myself singularly ill-equipped is that we're at the i may be at the tail end of the last generation of americans where you like picked something and that's what you did like i've been at a job for 40 years where you can expect to do better than your parents because those days are gone and where you can make a comfortable inference that the world in a decade or two will have any remote similarity to the one that we now inhabit and so but still you recommend just do yeah and to do so i'm again i'm this is i'm so back to the heidegger guy because all right i mean you know i consider myself a professor but what happens if most of the schools go out of business somebody else may consider themselves a restaurant tour but what happens if there's no more restaurants so what i this is negative advice but i tell folks don't define yourself as a social caricature yeah don't don't limit how you feel about yourself by through identification with a host of variables that may be uncertain maybe temporary and temporary what uh let's say no but of course that gets back to your point earlier lex where you're like yeah but when you step out of that it's extraordinarily discombobulating so what uh i think you talked about an axe of chopping wood yeah uh and seoul uh from socrates yeah what is your soul what is the uh the essence of sheldon wow that was like awesome like when god uh when you show up at the end of this thing he kind of looks at you he's like oh yeah yeah i remember you yeah well you know i to be honest what i muse about is to me the when when people are i told you i have to we have two kids uh late 20s early 30s and over the years when people when we meet people that know our kids and they're like oh your kids are kind and decent and i'd be like that's what i would like to be because i think intelligence is vastly overrated you know the unabomber was the smart guy yeah and i do admire intelligence and i do venerate education and i i find that to be tremendously important but if i had to pay the ultimate homage to myself it would be to be known as somebody who takes himself too seriously to take myself too seriously again as corny as it sounds i'd like to leave the world a tad better than i found it or at least do no harm and um i think you i think you did all right and that uh yeah in that regard i love that question alex that's a good one i think everyone should be asked that what is your soul do you have um maybe just a few lingering questions uh around it so you i mean on the on the point of the soul you've talked about the the meaning of life do you have um on a personal level do you have uh an answer to the meaning of your life of something that brought you meaning uh happiness some some sense of uh sense yeah no i i mean yes yes and no i mean i uh a bit you know i'm 66 so i'm in the kind of not ready to wrap it up literally or metaphorically but you look i look back and just really with a sense of uh awe and wonder gratitude and is there memories that stand out to you from childhood from earlier that like it's like you know stand out as something you're really proud of or um just happy to have been on this earth mainly that stuff happened yeah that i mean you know my family um also a chunk uh we're my folks so my grandparents are from eastern europe you know russia austria um as far as we know some of them never made it out uh i consider um myself um very fortunate to have been a so-called product of the american dream you know my grandparents are were basically peasants my parents my dad worked two full-time jobs um when i was growing up and i would see him on the weekends i'd be like why are you working all the time he'd be like so you won't have to and he said look the world does not owe you a living and so your first responsibility is to take care of yourself and then your next responsibility is to take care of other people and um i think you did a pretty good job of that well i don't know but i i i so those are the things that i'm proud of was it's funny you've been if you've talked about just yourself as a human being but uh you've also contributed some really important ideas for your ideas and also kind of integrating and maybe even popularizing the work of ernest becker of connecting it uh of making it legitimate scientifically i mean you know as a human of course you want to be uh you you want your ripple to be one that makes the world a better place but also i think in the span of time i think it's of great value you've contributed in terms of how we think about the human condition how we think about ourselves assuming as finite beings in this world and i hope also in our technology of engineering intelligence i think at least at least for me and i'm sure there's a lot of other people uh like me that your work has been a gift for so oh well thank you oh no i like that and we have described ourselves as giant interneurons unlike we have had no original ideas and and maybe that's the only thing that's original about our work is we don't claim to be original what we claim to have done is to integrate to connect these disparate and superficially unconnected discourses you know so existentialists they'd be like evidence what's that and yeah there's now a branches psychology experimental existential psychology that i think we could take credit for having encouraged the formation of and that in turn has gotten these ideas in circulation and academic communities where they may not have otherwise gotten so i think that's good well sheldon is a huge honor i can't believe you came down here i've been a fan of your work uh i hope we get to talk again huge honor to talk to you thank you so much for talking today thanks lex we'll do it again soon i hope thanks for listening to this conversation with sheldon solomon and thank you to our sponsors blinkist expressvpn and cash app click the links in the description to get a discount it's the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five star snapple podcast follow on spotify support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from vladimir nabokov that sheldon uses in his book warm at the core the cradle rocks above and abyss and common sense tells us that our existence is but a brief crack of light between two eternities of darkness thanks for listening and hope to see you next time |
Sara Seager: Search for Planets and Life Outside Our Solar System | Lex Fridman Podcast #116 | the following is a conversation with sarah seeger a planetary scientist at mit known for her work on the search for exoplanets which are planets outside of her solar system she's an author of two books on this fascinating topic plus in a couple days august 18th her new book a memoir called the smallest lights in the universe is coming out i read it and i can recommend it highly especially if you love space and are a bit of a romantic like me it's beautifully written she weaves the stories of the tragedies and the triumphs of her life with the stories of her love for and research on exoplanets which represent our hope to find life out there in the universe quick summary of the ads three sponsors public goods that's the new one power dot and cash app click the links in the description to get a discount it really is the best way to support this podcast as a quick side note let me say that extraterrestrial life aliens i think represent our civilization longing to make contact with the unknown with others like us or maybe others that are very different from us entities that might reveal something profound about why we're here the possibility of this is both exciting and at least to me terrifying which is exactly where we humans do our best work if you enjoy this thing subscribe on youtube review it with five stars on apple podcast support it on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of as now and never any ads in the middle that could break the flow of the conversation i try to make these ad reads interesting if you do listen but if you like i give you time stamps so you can skip to the conversation but still please do check out the sponsors by clicking the special links in the description it's the best way to support this podcast this show is sponsored by public goods the one-stop shop for affordable sustainable healthy household products their products have a minimalist black and white design that i find to be just clean elegant and beautiful it's a style that makes me feel like i'm living in the future i imagine we'll all be using public goods products once we colonize mars they got all the basics you need from healthy snacks like almonds to my favorite the bamboo toothbrush and other stuff for personal care home essentials healthy food and vitamins and supplements i take their fish oil for example which i recommend highly for everyone they use the membership models to keep costs low and pass on the savings to us the people they plant one tree for every order placed and have planted over a hundred thousand trees since september 2019 visit publicgoods.com lex or use codelex at checkout to get 15 bucks off your first order this show sponsored by powerdot get it at power.com lex and use codelexa checkout to get 20 off and to support this podcast it's an estim electrical stimulation device that i've been using a lot for muscle recovery mostly for my shoulders and legs as i've been doing the crazy amounts of body weight reps and six miles every other day now after the challenge yes i'm still doing it they call it the smart muscle stimulator since the app that goes with it is amazing it has 15 programs for different body parts and guides you through everything you need to do i take recovery really seriously these days and power dot has been a powerful addition to stretching ice massage and sleep and diet it's used by professional athletes and by slightly insane but mostly normal people like me it's portable so you can throw in a bag and bring it anywhere get it at power.com lex and use codelex at checkout to get 20 off on top of the 30-day free trial and of course to support this podcast this show is presented by a sponsor that arguably made this whole podcast even possible our first sponsor the great the powerful cash app the number one finance app in the app store i will forever 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advance robotics and stem education for young people around the world and now here's my conversation with sarah seeger when did you first fall in love with the stars i think i've always loved the stars one of my first memory is of the moon i remember watching the moon and i was in the car with my dad who my parents were divorced and he was driving me and my siblings to his house for the weekend and the moon was just following me just had no idea why that was yeah so like looking up at the sky and there's this glowing thing how do you make sense of the moon that at that age at age at like age five there's just no way you can i think it's one of the great things about being a kid it's just that curiosity that that all kids have you know i was thinking because there's these uh uh almost uh out there ideas of of that our earth is flat uh floating about on the internet and it made me think you know when did i first realize that the earth is um like this ball that's uh flying through empty space i mean it's terrifying it's uh awe-inspiring i don't know how to make sense of it it's uh it's hard because we live in our frame of reference here on this planet yeah it's nearly impossible none of us are lucky to go to see the curvature of earth i mean do you remember when you realized understood like the physics like the layout of the solar system this is it was it like did you first have to take physics to really uh like high school physics to really take that in i think it's hard to say i had this book when i was a child it was in french i grew up in canada where french is supposedly taught to all of us english-speaking canadians and it was this friend book in french was about the solar system and i just love flipping through it it's hard to say how much you know you or i understand when we're kids but it was really a great book what about the stars when did you first learn about the stars like i do have this very incredible distinctive memory and again it had to do with my dad he took us camping now my dad was from the uk and he was the type who you'd find wearing a tie on weekends so camping was not in his sphere his comfort zone we had a babysitter every summer we got a baby we every summer we had a babysitter and one summer we had tom he was barely older than we were he was 14 my brother was 12. i would have been 11 or 10 maybe and we went camping because tom said camping's the thing we should we should try it and i just remember i didn't aim to see the stars but i walked out of my tent in the middle of the night and i looked up and wow so many stars the dark night sky and all those stars just like screaming at me i just couldn't believe that honestly like my first thought was this is so incredible mind-blowing like why wouldn't anyone have told me this existed can anyone else see this have you have you had an ex have you experienced like that with anything like yeah i've had that i mean i don't know if maybe you can tell me if it's the same uh i've had that with robots uh there's a few robots i've met where i just fell in love with this like is anyone else seeing this is anyone else seeing that here in a robot is our ability to engineer some intelligent beings intelligent beings that we could love that could love us that we can interact with in some rich ways that we haven't yet discovered like uh almost like when you get a puppy it needs to have a dog and there's this uh immediate bond and love and on top of that ability to engineer it it was you know i had to just pause and and hold myself i imagine i don't have kids i imagine there's a magic to that as well or it's a totally new experience it's like what well yeah the stars though unlike kids or the puppy it's only a good thing so you felt you weren't terrified like it's to me when i look at the stars it's almost paralyzingly scary how little we know about the universe how alone we are i mean somehow it feels alone i'm not sure if it's a it's just a matter of perspective but it feels like wow there's billions of them out there and we know nothing about them and then also immediately to me somehow mortality comes into it i mean how did that make you feel at that time i think as a child without articulating it i felt that same way just like wow this is terrifying what's out there like what is this what does it mean about us here uh you you're a scientist an exo world class scientist planetary scientist astronomer uh now i'm a bit of an idiot who likes to ask silly questions so some questions are a little bit in the realm of speculation almost philosophical because we know so little and one of the awesome things about your work is you've actually put data and real science behind some of the biggest questions that we're all curious about but nevertheless many of the questions might be a little bit speculative so on that topic uh just in your sense do you think we're alone in the universe human beings do you think there's life out there well lex the funny thing is is that as a scientist i so don't even want to answer that you do you really don't i will answer them yeah but i just loved you resisted naturally yeah we naturally resist that because we want numbers and hard facts and not speculation but i do love that question it's a great question and it's one we all wonder about but i have to give you the scientist answer first yeah sure which is we'll have the capability to answer that question soon even starting soon how do you define soon how do i define science what do you so much happen in the last 100 years right right and there's a difference right if it's 10 years or 20 years or 100 years yeah there's a difference in that well soon could be a decade or two decades and then by the way journalists usually don't like that or the people want like tomorrow they want the news but what it's going to take is telescopes space telescopes or very sophisticated ground or space telespace telescopes to let us study the atmospheres of other planets far away and to look what's in the atmospheres and to look for water which is needed for life as we know it to look for gases that don't belong that we might attribute to life so we have to do some really nitty-gritty astronomy so the the promising way to answer this question scientifically is to look for hints of life that's where like many of your ideas come in of what kind of hints why might we actually see about this right right that's exactly what we need to do and i like the word you chose hint because it's going to be a hint it's not going to be a 100 percent yay we found it and then it will take future generations to do more careful work to hopefully even find a way to send a probe to these distant exoplanets and to really figure this out for us i mean we'll talk about the details those are fun but like uh back to the speculation zoomed out big pictures yes i believe absolutely there is life out there somewhere because there the vastness of the universe is incredible it's so breathtaking when we look at the night sky if you can go to that dark sky you can see you know many many hundred or even if you have good eyesight and you're somewhere very dark you could see thousands of stars but in our galaxy we have hundreds of billions of stars and our universe has hundreds of billions of galaxies so think about all those stars out there and even if planets are rare even if life is rare just because the number of stars is so huge things have to come together somewhere someplace in our universe yeah it's so amazing to think that somebody might be looking up on another planet in a distant galaxy and get back to in our lifetime at least the short term we have to we only have the nearest stars to look at it's true that there are so many stars so many hosts for planets that might have life but in the practical question of will we find it it has to be a star quite close to earth like a few light years tens of light years maybe hundreds of light years and by the way you've introduced me to a tool of eyes on exoplanets i think that nasa has put together isolated clinics that's it software you guys that's so cool uh but anyway uh can you give a sense of like who our neighbors are like you said uh hundreds of light years like how many stars are close by at like what what's our neighborhood like we're talking about five ten stars that we might actually have a chance to zoom in on i'm talking about maybe a dozen or two dozen stars and those are that's with planets that look suitable for us to follow up in detail for life right one thing that's really exciting in this field is that the very nearest star to earth called proxima centauri it's part of the alpha centauri star system cool name by the way yeah approximately whoever names them nearby okay but it sounds cool proxima proxima centauri appears to have a planet around it that's an earth map about an earth mass planet in the so-called habitable zone or the goldilocks zone of the host star so think about how incredible that is like out of all the stars out there even the very nearest star has planets and has a planet of huge interest to us yeah okay so can we talk about that planet what uh uh what what does it mean to be maybe possibly habitable habitable uh you know what uh what is how does size come into play how does um you know what we know about gases and what kind of things are necessary for life you know what are the factors that you make you think that it's habitable and by the way i mean maybe one way to talk about that is people know about the drake equation which is a very high level almost framework to think about what is the probability that correct me if i'm wrong that there's life out there uh and intelligent life i think i don't know but then the equation named after you now which i think nicely focuses in on the more achievable and interesting uh part of that question which is on whether there is habitable planets out there or how many i guess right so the funny thing is was one time i met frank drake and i asked if he minded if i took his equation and kind of revamped it for this new field of exoplanet astronomy he was totally cool with it he's he got total approval well maybe uh okay so i'm not sure if he'd actually read the stuff about my equation but he was cool with it he was cool with it uh okay so i just said like 15 different things but maybe can you tell from your perspective what is the drake equation and what is sorry the seeger equation sure well the drake equation as you said it's a framework it's a description of the number of civilizations out there of intelligent beings that are able to communicate with us by radio waves so if you think of like if you think of the movie contact you've seen contact right we're hoping to get we're listening in actually it's an active field of research listening to other stars at radio wavelengths hoping that some intelligent civilizations are sending us a message and the drake equation came like at the start of that whole field to put the factors down on paper to sort of illustrate what is involved to kind of estimating and there's no real estimate or a prediction of how many civilizations are out there but it's a way to frame the question and show you each term that's involved so i took the drake equation and i called it a revised drake equation and i recast it for the search for planets by more traditional astronomy means we're looking at stars looking for planets looking for rocky planets looking for planets that are the right temperature for life looking for planets that might have life that outputs gases that we might detect in the future it's the same spirit of the drake equation it's not going to give us any magic numbers so i'm going to say hey here's exactly what's out there it's meant to kind of guide guide of where we're going although the jerk equation did i mean the initial equation proposed actual numbers for those variables oh yes the equation proposed numbers and you can still plug your own numbers in and there's this really cute website that lets you for both the drake and my revised equation plug in some numbers and see what you get so yeah so okay so what are what are i mean what are the variables but maybe also what are like the critical variables so in my equation i set out to what are the numbers of inhabited planets that show signs of life by way of gases in the atmosphere that can be attributed to life i could just walk through the terms that's super simple the first thing i say is what are the number of stars available and it's not that those trillions and trillions of stars everywhere it's what are available to like a specific search and so for example the mit led nasa mission tess is surveying the sky looking for all kinds of planets but it can also it also has stars it has about 30 000 red dwarf stars so we just take a number of stars that a given survey can access so that's what the number of stars is then i wanted to know what kind of stars are uh quiet a quiet i called it a fraction of those stars that is quiet in the case of tess the way it's looking for planets is planets that transit the star they go in front of the star as seen from the telescope but it turns out that some stars are very active they're variable and they brighten and dim with time and that interferes with our observation i apologize to interrupt so it's a transiting planet so you're really looking for a black blob essentially that blocks the light we're looking for a black blob that blocks light and then trying to say something about the size of the planet uh from the frequency of that black blobs appearance and the size of that black blob that kind of thing yeah but let's just say that out of all the stars there are accessible to whatever telescope some of them are just bad for whatever reason you're not gonna be able to find planets around them so i need to know the fraction of those that are that are good so again we have the number of stars the fraction of them that we can actually find planets around um and by the way is our sun set one such is is our sun quiet our sun is quiet okay so i have actually two terms one describes how quiet they are and one is if we can find a planet around that star these transiting planets for example not all planets transit because the planet would have to be orbiting that star in this kind of plane as viewed from you but if a star is for example orbiting in the plane of the sky it will never transit it will never go in front of the star so in that case we have to have a fraction that takes into account that kind of geometric factor and hopefully it's right i mean you can assume that it's uniformly distributed hopefully yes we can assume and there's evidence that it's uniformly distributed yes so then the next so all of these factors so far number of stars accessible to whatever telescope you're thinking about how many stars are quiet fractional stars that are quiet fraction that are observable in this case for the geometric factor those are all things we can measure and there's one more term in the seeger equation we can measure i call it fraction of planets in the habitable zone because believe it or not we have a handle on that for a certain set of stars we know from our the kepler space telescope that operated for a number of years we have estimates for how many planets are in the so-called habitable zone of the host star for a certain type of star so all those we have measurable and then like the drake equation itself there are some terms we can not measure and those ones i call them fl fraction of all those planets that have life on them because we don't know what that is and fs i called for spectroscopy the fraction that have we can use our telescope and instrument tools to look for light actually fs was the ones that the planets that that have life that actually gives off a gas a useful gas that might accumulate in the atmosphere so we could eventually observe it uh how do the fl and fs interplay so these are separate terms separate terms and so so for example you could imagine so for example you could imagine life like us humans we breathe out carbon dioxide but our planet earth we already have a lot of carbon dioxide on it well we have hundreds of parts per million but it has a really strong signal so us humans breathing out carbon dioxide it's not helpful for any intelligent beings that are looking back at earth because there's already a lot of there's already enough carbon dioxide we're not adding to it so if there is life on a planet and it's outputting a boring gas that's not helpful for us to uniquely identify as being made by life versus just being there anyway then it's not helpful so i separated those two terms out soon i think we'll have evidence that planets that can support life at least are common so okay this is such an awesome topic i have a million questions uh what okay i know it's a little bit of speculation but what's your sense about that uh i think fs which is like that uh life would produce interesting gases that would be able to detect like is there one is there scientific evidence and and second is there some intuition around life producing gases detectable hints in terms of chemistry so interestingly enough that entire question relates to i'm gonna say almost my life's work yeah the work i'm doing now and the work i'm doing for the next 20 years and i wish i could give you a concrete number like one percent like on the worst days it's one percent let's say in my mind you know in the best days it's like 80 and i could actually go into a lot of detail here but i'll just give you the simplest things so first of all we make an assumption that like us and our life here on earth life uses chemistry so we use chemistry because we eat food we breathe air and we have metabolism that to break down food to get energy to store energy and then ultimately to use it and all life here has some kind of byproduct in doing all that some kind of waste product that goes into the atmosphere so i like to think that life everywhere uses chemistry some people have imagined like uh let's imagine like a windmill like mechanical energy just getting energy and using it without storing it and if there was life like that it might not need to output a gas so we make this basic assumption of chemistry that's the first thing the second more complicated thing that i and my team work on is what happens to the gas once it is produced by life it goes into the atmosphere and a lot of gas is just destroyed immediately actually by ultraviolet radiation or by oxygen oxygen's incredibly um destructive to a lot of gases so the gas can be produced by life but it could be just completely destroyed by its environment i guess we should pause on that that you mentioned your life's work i mean this is just a beautiful idea that uh it's kind of paralyzing when you look out there and you wonder is there a life out there a b is it's the first paralyzing actually before i encountered your work i feel like an idiot but you know uh it feels like there's no tool to answer that question and then what you kind of provided is this cool idea that it might be possible to answer that by looking at the gases i mean that's a really interesting that's a beautiful idea and uh yeah so we could just pause on like that's as a powerful tool i think that uh to build the intuition wrong because i was totally clueless about it and that was kind it's kind of exciting i mean i'm sure there's a folks probably early on in your life uh who were very skeptical about this notion well maybe i'm not sure but it's generally you would want to be skeptical it's like well all these kinds of other things could generate gases you know all those oh that's so true and that's a big part of this growing field is how to make sure that this gas isn't produced by another effect but i do want to you know again pausing on that and going back a bit it's incredible to think but like at least almost 100 years ago there's a record of someone talking about the idea of a gas being an indicator of life elsewhere oh that idea was floating about it was totally floating about and it comes down to oxygen which on our planet fills our atmosphere to 20 by volume and you know we rely on oxygen to breathe you know when they you hear about the people on mount everest running out of air they're really running out of oxygen well they're running out of oxygen because the air is getting thinner as you they climb up the mountain but without plants and bacteria there's plants that bacteria that also photosynthesizes and produces oxygen as a waste product without those we would have virtually no oxygen our atmosphere would be devoid of oxygen so yeah what uh if you were to analyze uh earth is oxygen the strong indicator here oxygen is a huge indicator and that's what we're hoping that there is an intelligent civilization not too far from here around a planet orbiting a nearby star with the kind of telescopes we're trying to build and they're looking back at our sun and they've seen our earth and they see oxygen and they they probably won't be like 100.00 sure that there's life making it but if they go through all the possible scenarios they'll be left with a pretty strong hint that there's life here yeah okay but how do you detect that type of gases that are on the planet from a distance and that's going back to that that's what people were skeptical about when i first started working on exoplanets long time ago people didn't believe we would ever ever ever study an exoplanet atmosphere of any kind and now dozens of them are studied there's a whole field of people hundreds of people working on exoplanet atmospheres actually wow but first there was a point where people didn't even know there was exoplanets right when was the first exoplanet detected the first exoplanet around a sun-like star anyway was detected in the mid-1990s that was a big deal i kind of vaguely remember that well at the time it was a big deal but it was also incredibly controversial because in exo you know planets we only had one example of a planetary system our own solar system and in our solar system jupiter our big massive planet is really far from our star and this first exoplanet around a sun-like star was incredibly close to its star it's star so close that people just couldn't believe it was a planet actually so maybe zoom out what the heck is an exoplanet an exoplanet is our name like is the name that we call a planet orbiting a star other than our sun right extra solar i guess is the number you can call it extrasolar exoplanet is simpler but i think it's worth pausing to remember that each one of those stars out there in our night sky is the sun right and you know our sun has planets mercury venus earth mars etc and so for a long time people have wondered do those other stars or other suns have planets and they do and it appears that nearly every star has a planet has a planet we call exoplanet and there are thousands of known exoplanets already so there's already yeah like there's so many things about space that it's hard to put in into one's brain because it starts filling it with awe so yeah if you visualize the fact that the stars that we see in the sky aren't just stars they're like they're sons and they very likely as you're saying will have planets around them there's all these planets roaming about in this like dimly lit darkness with potentially uh life i mean it's just mind-blowing but um maybe can you give a brief like history of and like of discovering all the exoplanets so there's no exoplanets in the 90s and then there's a lot of exoplanets now so how did that come about so many planets how did it come about well maybe another way to ask is what is the methodology that was used to discover them i can say that but i'd like to just say something else first where so in exoplanets you know the line between what is considered completely crazy and what is considered mainstream research legit is constantly shifting this is awesome yeah so before when i started on exoplanets it was still sketchy like it wasn't considered a career or a thing a place where you should be investing and right now now today it's so many people are working in this field a good i don't know at least a thousand probably more i don't know if that sounds like a lot to you but it's a lot no it's a legitimate field of inquiry yeah legitimate field of increase and what's helped us is everything that's helped everyone else it's software it's computers it's hardware it's like our phones you have a fantastic detector in there like they didn't always have that i don't know if you remember the so-called olden days we didn't have digital cameras we had film you take a film camera you send the film away and eventually it comes back and then you see your pictures and they could all be horrible yeah so yeah it sent me digital it just changed everything data changed everything yeah and so one thing that really helped exoplanets were detectors that were very sensitive because when we're looking for this the transiting planets what we're doing is we're monitoring a star's brightness as a function of time it's like click taking a picture of the stars every few seconds or minutes and we're measuring the brightness of a star like every frame and we're looking for a drop in brightness that's characteristic of a planet going in front of the star and then finishing its so-called transit and to make that measurement we have to have precise detectors and uh the the detectors that are making the measurement can you do it from earth is it uh are they floating about in space like what kind of telescope both so on the ground people are using telescopes small telescopes that are almost just like a glorified telephoto lens and they're looking at big swaths of the sky and from the ground people can find giant planets like the size of jupiter so it's about 10 to 12 times the size of earth we can find big planets because we can reach about one percent precision so i'm not sure how much technical you want to get but well yeah well how many pixels are we talking about like what uh you mentioned phones there's a bunch of uh megapixels i think so for exoplanets you want to think about it as like a pixel or less than a pixel we're not getting any information but to be more technical our telescope you know spreads the light out over many pixels but we're not getting information we're not tiling the planet with pixels it's just like a point of light or in most cases we don't even see the planet itself just the planet's effect on the star but another thing that really helped was computers because transiting planets are actually quite rare i mean they don't all go in front of their star right and so to find transiting planets we look at a big part of the sky at once or we look at tens of thousands or hundreds of thousands or even in some cases millions of stars at one time and so you know you're not going to do this by hand going through a million stars counting up the brightness we so we have computer software and computer code that does the job for us and looks for a you know counts the brightness and looks for a signal that could be due to a transiting planet and you know i just finished a job called uh deputy science director for the mit led nasa mission test and it was my purview to make sure that we got the planet candidates the transiting light curves out to the community so people could follow them up and figure out if they're actual planets or false positives so publish the data so that people could just uh yeah publish data all the all the data scientists out there could crunch and see if they can exactly they can discover something and in fact the nasa policy for this mission is that all the data becomes public as soon as possible so anyone could act it's not as easy as it sounds though to download the data and look for planets but there is a group called planethunters.org and they take the data and they actually crowdsource it out to people to look for planets yeah and they often find fine signals that our computers and our team missed so we mentioned exoplanets what about earth like or i don't know what the right distinction is if is it habitable or is it earth-like planets but what are those different categories and how can we tell the difference and detect each right right so we're not at earth-like planets yet all the planets we're finding are so different from what we have in our solar system they're just easier planets to find but like in which way for example there could be a jupiter-sized planet where an earth should be we find planets that are the same size as earth but are orbiting way closer to their star than mercury is to our sun and they're so close that because close to a star means they also orbit faster and some of these hot super earths we call them their year their time to go around their star is less than a day and they're heated so much by their star they're heated so much by the star we think the surface is hot enough to melt rock so instead of running out by the bay or the river you'll have like liquid lava there'll be liquid lava lakes on these planets we think and life can't survive way too hot the molecules for life would just be molecules needed for life just wouldn't wouldn't be able to survive those temperatures we have some other planets one of the most mysterious things out there factoid if you will is that the most common type of planet we know about so far is a planet that's in between earth and neptune size it's two to three times the size of earth and we have no solar system counterpart of that planet that is like going outside to the forest and finding some kind of creature or animal that just no one has ever seen before and then discovering that is the most common thing out there and so we're not even sure what they are we have a lot of thoughts as to the different types of planet it could be that people don't really know i mean what are your thoughts about what it could be well one thought and this is more when we want to be rather than might be is that these so-called mini neptunes we call them that they are water worlds that they could be scaled up versions of jupiter's icy moons such that they are planets that are made of more than half of water by mass so yeah and what's the connection between water and life and the possibility of seeing that from a gas perspective okay so all life on earth needs liquid water and so there's been this idea in astronomy or astrobiology for a long time called follow the water find water that will give you a chance of finding life but we could still zoom out and the kind of the community consensus is that we need some kind of liquid for life to originate and to survive because molecules have to react if you don't have a way that molecules can interact with each other you can't really make anything and so when we think of all the liquids out there water is the most abundant liquid in terms of planetary materials there really aren't that many liquids like i mentioned liquid rock way too hot for life we have some really cold liquids like almost gasoline like ethane and methane lakes that have been found on one of saturn's moons titan that's so cold though and for exoplanets we can't study really cold planets because they're just simply too dark and too cold so we usually so we're usually just left with looking for planets with liquid water and to your point it's remember as we talked about how planets are less than a pixel in in that way to say so we can't see oceans on planet we're not going to see continents and oceans not yet anyway but we can see gases in the atmosphere and if it's a small rocky planet and this is going into some more detail it's a small if we see a small rocky planet with water vapor in the atmosphere we're pretty sure that means there has to be a liquid water reservoir because it's not intuitive in any way but water is broken up by ultraviolet radiation from the star or from the sun and on most planets when water is broken up into and o the h the hydrogen will escape to space because just like when you think of a child letting go of a helium-filled balloon it floats upwards and hydrogen's a light gas and will leave from earth leave from the planet so ultimately if you have water unless there's an ocean like a way to keep replenishing water vapor in the atmosphere that water vapor should be destroyed by ultraviolet radiation got it so there's a okay so there's a need for liquid i mean i guess what is water well is water essential is other liquids i mean the chemistry here is probably super complicated there's not it does but you know there's not an infinite number of liquids right there's maybe like five liquids that can exist inside or on the surface of a planet and water is the one that exists for the largest range of temperatures and pressures and it's also the easiest type of planet for us to find and study as one with water vapor rather than a cold planet that has ethane and methane lakes what's your personal in terms of solar systems and planets that you're most hopeful about uh in terms of our closest neighbors that you kind of have a sense that there might be uh somebody living over there whether it's bacteria or somebody that looks like us i'm hopeful that every star nearby has has a planet has some life because it almost has to for us to make progress we have to have that dream condition so the dream condition is like life is just super abundant out there yeah the dream yes the dream condition is that life is super abundant and it's based on the thought that if there is a planet with water and continents that it also has the ingredients for life and that the kind of base does the base the base kernel thought is that if the ingredients for life is there life will form that's what we're holding on with the relatively high probability yes that's that's it okay let's go into land of speculation uh what about intelligent life uh us humans consider ourselves intelligent surprisingly or unsurprisingly do you think about from your perspective of looking at planets from a gas composition perspective and in general of how we might see intelligent life and uh your intuition about whether that life is even out there i think the life is out there somewhere the huge numbers of stars and planets i like to think that life had a chance to evolve to be intelligent i'm not convinced the life is anywhere near here only because if it's hard for intelligent life to evolve then it will be far away by definition well the sad thing is uh maybe from the artificial intelligence perspective is it makes me sad there might be intelligent life out there that we're just not like the pathways of evolution can go in all these different directions where we might not be able to communicate with it or even know that or even detect its intelligence or even comprehend its intelligence yeah convince cats are more intelligent than humans that that we're just not able to comprehend the the measures the the proper measures of their intelligence my dog is so funny he's the golden doodle his name's leo we joke that he's either a really dumb dog and so he's not here to defend himself but he's either really dumb or he's a super genius just pretending to be dumb yeah i mean it's possible he's he's a multi-dimensional projection of alien life uh here monitoring uh one of the you know one of the top scientists in the world trying to find aliens just to make sure just just to make sure that humans don't get out of hand that's funny oh i'm definitely going to go in and ask him ask him about that ask him about that he's on to something yeah what might we look for in terms of signs of intelligent life from your toolkit do you think there are things that we should we might be able to use or maybe in the next couple of decades discover that would be different than life that's like bacteria that's primitive life i still love seti search for extraterrestrial intelligence i like to hope that if there is a civilization out there they're trying to send us a message i think like think about it i don't know what are your thoughts like if you think about our earth there's no structure we've built that intelligent civilizations could see from far away there's literally nothing not even the great wall of china and so to think like why would this other civilization build a giant structure that we could see yeah so with seti the idea is that we're both trying to hear signals and send signals right we haven't sent one they call that medi messaging and there's a big kind of fear over medi because do you want to tell them you're here it's kind of this like let's wait till they call us yeah so uh we should have a dating game we have to like how how many days do i wait before i call kind of thing yes it and so but the funny thing is if no one's sending us a message if everybody's only listening how do you make progress that's right and so i mean but there's also there's the voyager spacecraft so we we have these little pixels of uh robots flying out all over the place some of them like the voyager reach out really far and they have some stuff stuff on them okay i just we do we have the voyager but they're not really going anywhere in particular and they're moving very very slowly on a cosmic scale yeah and let me say they're far is kind of silly because yeah it's all relative in astronomy it's all relative yeah yeah i just i so from uh if you look at earth from an alien perspective from visually and from gas composition i wonder if it's possible to determine the degree of maybe um productive energy use i wonder if it's possible to tell like how busy these earthlings are well let's zoom out again and think about oxygen so when cyanobacteria arose like billions of years ago and figured out how to harness the energy of the sun for photosynthesis they re-engineered the entire atmosphere 20 of the atmosphere has oxygen now like that is a huge scale you know they almost poisoned everything else by making this what was apparently very poisonous to everything that was alive but imagine so are we doing anything at that scale like are we changing anything in like 20 of the earth with a giant structure or 20 of this or 20 of that like we aren't actually yeah yeah that's that's uh that's humbling to think that we're not actually having that much of an impact i know but we are because in a way we're destroying our entire planet but it's humbling to think that from far away people probably can't even tell but from the perspective of the planet when we say we're destroying you know global warming all that kind of stuff um what we really mean is we're destroying it for a bunch of different species including humans but like i think the earth will be okay oh the earth will be the earth will remain whatever whatever happened to us the earth will still be here and it'll still be difficult to detect any difference like it's sad to think that if humans destroy ourselves except potentially when you clear war it'd be hard to tell that anything even happened yeah it will be hard to tell from far away that anything happened what about what are your thoughts now this is really getting into speculation land there you've you've mentioned exoplanets were in the realm of you know there's this beautiful edge between science and science fiction that uh some of us a rare few are brave enough to walk i think in academia you were brave enough to do that i think in some sense artificial intelligence sometimes walks that line a little bit um there is so much excitement about extraterrestrial life and aliens in this world i mean i don't know what how to comprehend that excitement but to me it's great to see people curious because to me extraterrestrial life and aliens is at the core a scientific question and it's almost looks like people are excited about science they're excited by discovery discovery right and then the possibility that there's alien life that visited earth or is here on earth now is is uh excitement about discovery in your lifetime essentially i mean what do you make what do you make of that there's recent events where darpa um or dod released footage of uh these um unmanned aerial phenomena they're calling them now uap they got everybody like super excited like maybe there is like what what what's what's here on earth uh do you follow the this world of people who are thinking about aliens that are already here or have visited i don't really follow it they follow me i'd say because in this field if you're a scientist of any kind you get the people contact us me there's a lot of them about hey i have stuff you should see hey the aliens are already here i need to tell you about it and i know there are people out there who really believe there's a psychology to it there's a psychology to it and it's fascinating but okay so it's similar to artificial intelligence but i still but like you i'm still enamored with the point that it is out there and that people believe so strongly and that so many people out there believe i believe and uh i don't know i i i'm not as allergic to it as some scientists are because ultimately if aliens showed up or do show up or have showed up you know these are going to be very difficult to study scientific phenomena like in fact like going back to cats and dogs like i just i think we should be more open-minded about uh developing new tools and looking for intelligent life on earth that we haven't yet found or even understanding the nature of our own intelligence because it kind of is an alien life form the thing that's living you know in our skull it's so true when we don't understand consciousness yeah it's true we don't understand how biology is hard you know unpacking it and working it all out it's a stretch and they say too that our thinking mind is like the tip of the pyramid that everything else is happening under the hood and but what is happening but the thing with so the typical scientists response to you know are there aliens here is that we need to see major evidence not like a sketchy picture of something we need some cold hard evidence and we just don't have that that's exactly right but from my perspective i admire people that dream and i think that's beautiful the thing i don't like there's two sides of the of the folks uh that probably listen to this this podcast is oh those that dream i think is beautiful that uh that wonder what's out there what's here on earth and then the other ones who are very conspiratorial in thinking that stuff is being hidden right becomes about institutions okay i have a funny thing to tell you about that so one of my colleagues had a really good answer to that and it's not me saying this so i can say this but he said look he works with nasa not at nasa he works with government not in the government it's kind of me but he'd say trust me they couldn't hide it if they tried do you know what i'm saying like everybody we're not we're not smart enough or good enough not we or not me or not you but whoever to cover it up it just it's sort of a myth yeah it makes it sad because um the people at nasa the people at mit the people in academia the people in these institutions and yes even in government are often trying they're like just curious descendants of apes they're just they they want to do good they want to discover stuff they're not trying to hide stuff in fact most of them would in terms of leaks would uh love to discover this and release this kind of stuff and there's a did you ever watch this show called the x-files yeah scully and mulder yeah and what i love actually i used to put it up during my talks my public talks there's a picture of a ufo or what looks like ufo and it says i want to believe so that's that's where i think a lot of us are coming from i want to believe and it's so great and one time i put that up and this very very nice couple approached me really nervous afterwards and they said hey can we take you out for lunch sometime and i said sure and they were like the nicest people and just one of many who has an alien alien abduction story and the woman um could never have kids they were older but they didn't have kids which for them was a real source of regret but it was because the aliens who had abducted her had made it so that she couldn't have kids and she had apparently something implanted behind her ear which was somehow unimplanted later and they were just so sincere and they're such a lovely couple they just wanted to share their story that's that's a real whatever that is that's the real thing the mystery of the human mind right is more powerful than any alien or i mean it's uh as interesting i think as the universe and i think they're somehow intricately linked maybe getting a sense of numbers how many stars are there in maybe i don't know what the radius that's reasonable to think about i don't know if the observable universe is like way too big to think about but in terms of when we think about how many habitable planets there are what are the numbers we're working with in your sense what are the scales honestly the numbers are probably like billions of trillions of stars yeah you know in the uk i think i don't know if we do that here but they will call a billion trillion where you put like 1 billion followed by a trillion yeah it's kind of weird but here i don't even know how to say the number 10 to the 20. like if you know what that is that's 1 followed by 20 zeros that's a big number and we don't have a name for that number there's so many per star i think we kind of mentioned this is there a good sense there's probably argument about this but per star how many planets are there is there we don't have that number yet per se you know we're not really there but some people think that there's many planets per star there's this analogy of filling the coffee cup like you know you don't usually just pour one drop you fill it and that planetary systems we see stars being born that have a disk of gas and dust and that ultimately forms planets so the idea this kind of concept is that planets so many planets form too many and eventually some get kicked out and you're left with like a full planetary system a dynamically full system and so there have to be a lot because so many form and a bunch survive that i mean that that makes perfect intuitive sense right like why wouldn't that happen right well there's other thoughts too though these big planets that are really close to the star we think they formed far away from the star where there's enough material to form and they migrated inwards and some of these planets migrating inwards due to interaction with other planets or with the disk itself they may have cleared it out like kicked other planets out of the system so there's a lot of ideas floating around we're not entirely sure and what about earth-like planets is that that's another level of uncertainty that it's a level of uncertainty if we think of an earth-like planet being an earth around a sun in the same orbit an earth-like planet being an earth-sized planet in an earth-like orbit about a sun-like star we're not there yet you know we're not able to detect enough of those to to give you a hard number some people have extrapolated and they will say as many as one in five stars like our sun could be hosting a true earth-like planet wow on the topic of space exploration there's been a lot of exciting developments with nasa with spacex with other companies successfully uh getting rockets into space with humans and getting them to land back uh especially with spacex what are your thoughts about elon musk and spacex crew dragon well working with nasa to launch astronauts what's your sense about uh these exciting new developments well spacex and other so-called commercial companies are only good news for my field because they're lowering the cost of getting to space by having reusable rockets it's just been it's incredible and we need cheaper access to space so from a very practical viewpoint it's all good about getting people there's this dream that we have to go to mars boots on boots on mars what do you think about that you mentioned probes what's the value of humans uh is that interesting to you from both scientific and a human perspective human mostly i think it's such in our desire to explore because part of what it means to be human so wanting to go to another planet and and be able to live there for some time it's just just what it means to be human you know oftentimes in science and engineering big huge discoveries are made when we didn't intend to so often this kind of pure exploratory type of research or this pure exploration research it can lead to something really important like the laser we couldn't really live without that now at the grocery you scan your foods there's surgery that involves involved lasers gps we all use our gps we don't have gps because someone thought hey it'd be great to have a navigation system and so i do support i do i just but i really think it comes primarily just from the desire to explore do you think something there's a lot of criticism and a lot of excitement about mars do you think there's value in trying to go to put humans on mars first of all and second of all colonize mars do you think there's something interesting that might come from there i i'm convinced there will be something interesting i just don't know what it is yet but i don't think i don't think having some commercial value or value in the metric of something useful is really what's motivating us so really uh you see exploration is a long term investment into something awesome that eventually be commercial value yeah i do actually yeah i do so what about visiting okay i apologize but i mean there's an exciting longing to um visit earth-like planets elsewhere so what's the closest uh earth-like planet you think is worth visiting and how how hard is it wow it is very hard i mean our nearest call it earth mass planet it's orbiting a star very different from our own sun an m dwarf star a small red star proxima centauri it's over four light years away and we can't travel at the speed of light we can't even try i mean it would take tens of thousands of years to get there with conventional methods so you know the movies like multi-dimensional yeah this movie passenger have you seen that movie passenger it's about a big spaceship that is traveling to another planet and everyone's hibernating i won't give you the spoiler alert because one person wakes up and then it's kind of a problem okay got it but yeah the multi-generational ships i mean when you think about where we're headed as a species maybe we don't send people maybe we end up sending raw biological materials and instructions to print out humans it sounds kind of far-fetched but already we're printing like liver cells in the lab and beating heart cells we're starting to reconstruct body parts i mean the thing is it is so hard to get to another planet that this thought of printing humans or printing life forms actually could be easier yeah that's somehow so sad to think to think of the idea that we would launch a successful spaceship that has multi-generational like non-human life and it's going to reach other intelligent life and by the time they figure out where it came from human civilization will be extinct wow yeah that is really exciting that's so that's one you there's a there's a tempting thing to think about what are the possible trajectories so uh you know elon keeps talking about multi-uh planetary us becoming multi-planetary species i mean sure mars is a part of that but like the dream is to really expand outside the solar system and it's it's not clear just like as you said like what the actual scientific engineering steps that are required to to take it seems like so daunting so daunting so like this the smart thing seems to be to do the most achievable near daunting task even if there doesn't seem to be a commercial application which i think is colonizing mars but like from your perspective is there some manhattan project style huge project in space that we might want to take on and you've had roles you had scientist hat roles and then you also have roles in terms of being on like committees and stuff determining where funding goes and so on so like is there a huge like multi-trillion we've been throwing the t word around recently a lot but these huge projects that we might want to take on well first of all we want to find the planets like earth first like just even finding those earth-like planets is a billion dollar endeavor billions of dollars endeavor and that's so hard because an earth is so small so less massive and so faint compared to our sun it's the proverbial needle in a haystack but worse and we need very sophisticated space-based telescopes to be able to find these planets and to look look at them and see which ones have water and which ones have signs of life on them yeah the the star shade project that your shade starship yeah this is probably the most badass thing i've ever seen right you know what's interesting so what's amazing about starshade is it was first conceived of in the 1960s imagine that and revisited every decade until now when we think we can actually build it and starshade is a giant specially shaped screen it is about there's different versions of it but think about 30 meters in diameter so you're blocking out the sun you're effectively blocking out the star yeah so that you can see the planet directly and starshade would have a spacecraft attached to it and it would fly in space far away from earth's gravity and it would have to formation fly with a space telescope so the idea is that starshade blocks out the starlight in a very careful way and it has to block that starlight out so that the planet that is 10 billion times fainter than the star that only the planet light goes to the telescope yeah so in formation meaning the telescope flies and um as you're giving a presentation on this but like it it would fly like and um this is extremely high precision endeavor yeah we had this analogy like asking a friend to hold up a dime five miles away yeah perfectly like at the perfect line of sight with you yeah and the shape of it is pretty cool i mean uh i don't know exactly what the physics of that like what the optics are that require that shape i can tell you it turns out that if you block out a star imagine blocking out a star with a circle circularly or a square shaped screen you wouldn't actually be blocking it because the star acts like a wave the starlight can act like a wave and it would actually bend around the edges of the screen and so instead of blocking out the light you're expecting to see nothing you would see ripples and the analogy that i love to give it's like throwing a pebble in a pond you get those ripples you get these concentric ripples and they go out and light would do something quite similar you'd actually see ripples of light and those ripples of light they're actually way brighter than the planet we'd be looking for so yeah so they would introduce this noise that's yeah noise and so this star shade it's like a mathematical solution to the problem of diffraction it's called and this is what the first person who thought about star shade in the 1960s worked out the mathematical shape or one solute one family of solutions and the idea is that when the star shade this very special shape like a giant flower with petals when it blocks out the light the light bends around the edges but interacts with itself in a way to give you a very very dark image it would be like throwing a pebble in a pond and instead of getting ripples the pond would be perfectly smooth like incredibly smooth to one part in 10 billion and all the waves would be on the outer edges far away from where you dropped that petal pebble and so what this camera would be able to uh this camera this telescope would be able to get uh get some signal from the planet then yes and it would be hard because the planet is so faint but with the star out of the way the glare of that bright bright bright star with that out of the way then it becomes a much more manageable task so how do we get that thing out there we're working with unlimited money okay working with unlimited money um we have some more engineering problems to solve but not too many more we've been burning down our so-called tall pool list and then we just what kind of list we call it tall techno uh technology tall pole it's the phrase where you have to figure out what are your hardest problems and then break those down to solve so the starshade one of the really hard problems was how did formation fly at tens of thousands of kilometers it's like wow that is insane and the team broke that down actually into a sensing problem because of the star shade how do you see the star shade precisely enough to to control it because if you're shining a flashlight you know the beam spreads out so the star shade has a beacon an led or a laser it's going to spread out so much by the time it gets to the telescope the problem wasn't how do you tell the star shade how to move around fast enough to stay in a straight line the problem was how do you how are you able to sense it well enough so problems like that were broken down and money that came from nasa to solve problems is put towards solving it so we're we've got through most of the hard problems right now another one was that star shade even though it's looking at a star light from our own sun could hit the edges of the star shade and bounce off into the telescope believe it or not and that would actually ruin it because we're trying to see this tiny tiny signal so then the question is how do you make a razor thin edge like those petal edges would be like have to be like a razor what materials can you so there's a series of problems like that so wow so there's a materials problem in there some of them and there's one so we almost finished solving all those problems and then it's just a matter of building one and testing it in a full scale size facility and then building the telescope it's just a matter of time to build everything and get it get it up for lunch so this is an easy close engineering yes this is an engineering project it's a real engineering project so i actually can tell you about two other projects that are not mine i like to call starshade mine because it was my project that i helped make it mainstream where that line is constantly shifting when i started when i got this leadership role on starshade i remember telling people about it and it was definitely not on the mainstream okay line it was on the giggle factor side of the line and people would just laugh like that's dead like you could never formation fly or they'd say why are you working on that that's just so not it's not this is so awesome there's a there's a few things you've done in your life and that's when i first saw starshine i was like what really and then like it sinks in i mean it's the same thing i felt with like elon musk or certain people who do crazy stuff like and then and they get they actually make it work i mean if you get started in formation flying to like together i mean how awesome is that if you actually make that happen even like from a robot i'm sorry from the robotics perspective even if it doesn't give us good data that's just like a cool thing to get out there i mean it's really exciting really cool so there's two other topics that aren't mine but i still love them one of them let's just talk about it briefly because it's not a probe but it's the idea to send a telescope very far away to 500 times the earth sun distance and this is way farther than the voyager spacecrafts are right now and to use our sun as a gravitational lens to use our sun to magnify something that's behind it it's got to sink in for a minute yeah exactly but i mean i don't know what the physics of that is like how to use the sun in astronomy and einstein thought about this initially we can use uh massive objects bend space and so light that should be traveling like straight it actually travels around the warped space and somehow you figure out a way to use that for magnification you have a way to use that for magnification that's right there are galaxies uh that are lens so-called gravitational lens by intervening galaxy clusters actually and there are microlensing events where stars get magnified as an unseen gravitational lens star passes in between us and that very distant star it's actually a real tool in astronomy yeah using gravitational lens to magnify because it bends more rays towards you than normally would you normally see and again we're trying to get more higher resolution images that are basically boiled down to light well it boils down to light and then you can maybe get more information about well in this case you would ask me let's say if this thing could get built it would take like something like they'd like to say 25 years to get from here to there 25 years and then it could send some information back to us and then you'd say so sarah how many pixels and i wouldn't say one or less than one i'd say you know it could be like 10 by 10 pixels it could be 100 pixels which would be awesome i mean it's still crazy that we can get a lot of information from that crazy right and it's crazy for a lot of other reasons because again you have to line up the sun and your target you'd only have one telescope per target because every star is behind the sun in a different way so it's a lot of complicated things but what about the second the second one it's called starshot you know starshot means like big dreams and it's an initiative by the breakthrough foundation and starshot is the concept to send thousands of little tiny spacecraft which they now call star chip so instead of star ship it's star chip and there's a little chip and the star chip so like sending like thousands of little turtles being born they're not all going to make it mm-hmm because they used to send lots of them and each of these star chips once they're launched into i guess low-earth orbit they will deploy a solar sail that's a few meters in diameter and they'd use it on earth we would have a bank of this one is still a bit on the other side of the line but we'd have a bank of telescopes with lasers there'd be like a gigawatt power and these lasers would momentarily shine upwards and accelerate they'd hit these sails they'd be like a power source for the sail and would accelerate the sails to travel at about a 20th the speed of light is that is that as crazy as it sounds well like like any good well like any good engineering project it has to be broken down into the crazy parts and the breakthrough initiative like to their huge credit is sponsoring you know getting over these actually they've listed initially they listed 19 challenges yes it's broken down to concrete things like one of them is well you have to buy the land and make sure the airspace is okay with you sending up that much power overhead another one is you have to have material on the sail where the lasers won't just uh vaporize it and well so there's a lot of a lot of issues but anyway these sails would be accelerated to 20th speed of light and their journey to the nearest star would now wouldn't would no longer be tens of thousands of years but could be 20 years okay 20. so it's not not as bad as tens of thousands yeah and this um these thousands or whatever however many make it they'll go by the nearest star system and snap a few snap some images and radio the information back to earth because they're traveling so fast they can't slow down but they'll zoom by take some photos send it back high res yeah but see just what i want you to pause on for a second is that just by making that a real concept and the money given won't make it happen but we'll but what it's done is it's planted the seed and it's shifted that line from what is crazy to what is a real project it's shifted it just ever so slightly enough i think to plant the seed that we have to find a way to somehow find a way to get there that is again to stay on that that is so powerful take a big crazy idea and break it down into smaller crazy ideas order it in a list and knock it out one at a time uh i don't know i've never heard anything more inspiring from an engineering perspective because that's how you solve the impossible things so you open your new book discussing rogue planet pso j318 i never said this out loud 0.522 so a rogue planet which is just this poetic beautiful vision of a planet that that as you right lurches across the galaxy like a rudderless ship wrapped in perpetual darkness it's surface swept by constant storms as black skies raining molten iron just like the vision of that the scary the the darkness the just how not pleasant it is for human life just the intensity of that metaphor i don't know and the reason you use that is to paint in a feeling of loneliness and despair and despair and um why maybe on the planet side why does it feel maybe it's just me why does it feel so profoundly lonely on that kind of planet like what uh like what i think it's because we all want to be a part of something a part of a family or a part of a community or a part of something and so our solar system and by the way i only it's sort of like a like when you treat yourself to like eating an entire tub of ice cream like i sometimes treat myself to imagine things like this and not just be so cut and dried but when you imagine that this plan is not because i don't want to give emotions to a planet per se but the planet's not part of anything it's somehow probably um it's just all on its own just kind of out there without that warm energy from its sun it's just all alone out there to me it was a little discovery that i actually feel pretty good at being part of the solar system it felt like we have a sun we have like a little family and it felt like it sucked for the rogue planet yeah to just floating about uh not floating of flying uh rudderless by the way how many rogue planets are there in your sun you don't know totally i mean there's some rogue planets that are just born on their own i know that sounds really weird to be how can you be born an orphan but they just are because most planets are born out of a disk of gas and dust around a star but some of these small planets are like totally failed stars they're so failed they're just small planets on their own but we think that there's probably honestly there's another path to a rogue planet that's one that's been kicked out of its star system by other planets like a game of billiard balls something just gets kicked out we actually think there's probably as many rogue planets as stars no flying out there um fundamentally alone so the book is uh as a memoir is about your life and it uh weaves both your fascination with planets outside the solar system and the path of your life and you lost your husband which is a kind of central part of the book that created a feeling of the rogue planet by the way what's the name of the book the name of the book is the smallest lights in the universe what's up with the title what's the meaning the title has a double meaning on the face of it it's the search for other earths earths are so dim compared to the big bright massive star beside them searching for the earth's is like searching for the smallest lights in the universe it has this other meaning too i really hope that you or the other people listening never get to the place where you're just you've fallen off the cliff into this horrible place of huge despair and once in a while you get a glimmer of a better life of some kind of hope and those are also the smallest lights in the universe well maybe we can tell the full story before we talk about the glimmer of hope um what did it feel like to first find out that your husband mike was sick it was incredibly frustrating like lots of us have had some kind of problem that the doctors completely ignore just that they kept blowing him off it's nothing are they paid to just say something i mean it's just insane i was just so angry and we finally got to a point where he was really sick he was like in bed not able to move basically and it turned out all the things they ignored and not done any tests he had like a 100 percent blockage in his intestine like a hundred percent like nothing could get out nothing could get in and it was pretty pretty shocking to even hear then that it could be nothing what was the progression of it in the context of the maybe the medical system the doctors i mean what did it feel like did you feel like a human being uh i felt like a child like the doctors were trying to water down the real diagnosis or treat us like we couldn't know the truth or they didn't know you know i felt mixed like it's not a good situation if you think the doctor either has no idea what he or she is doing or if the doctor is purposely let's just say lying to you to sugarcoat it like i didn't know which one of it was but i knew it was one of those what were what were the things he was suffering from well initially he just had a random stomachache i hate to say that out loud because i know a lot of people will have a random stomachache yeah but so he just had a bad stomach ache and then this is weird a few days later another bad stomachache kind of gets worse might go away for a few weeks might come back and at the time all i knew was my dad had had that same thing not the same identical system but he had these really weird pains and he ended up having the worst diagnosis one of the worst diagnosis you can get from a random stomachache is pancreatic cancer because the time the pancreas like you can't feel anything so by the time you feel pain it's too late it's spread already so i was just like beside myself i'm like this is like wow this guy he's a random stomachache all i know is another man i loved had a random stomachache and it didn't end well how did you deal with it emotionally psychologically intellectually as a scientist what was that like that that whole because it's not immediate it's a it's a long journey it's a long journey and you don't know where the diagnosis is going so anyone who's suffered from a major illness there's like always branches in the road so you know he had this intestinal blockage i can't imagine someone in their 40s having that and that be normal but the doctor is like it could be nothing could just cut it out you don't need most of your intestines it's a repeating pattern just cut that out it could be fine but it ended up not being fine and he was diagnosed as being terminally ill well it really changed my life in a huge way first of all i remember immediately one summer the summer when this happened i started asking everyone i knew i would ask you i know it's my job to put you on the spot i'd say you have one year to live or two or three what will you do differently about your life now lex you have one year to live what would you do i mean it's hard i don't know if you want to answer no no no i think about it a lot i mean that's a really good thing to meditate on we can talk about maybe how uh why you bring that up what if it is or not a heavy question but i get uh i i think about mortality a lot and for me it feels like a really good way to focus in on is what you're doing today the people you have around you the family you have is it uh does it bring you joy does it bring you fulfillment and basically uh for me of long ago tried to be ready to die any day so like today i you know i kind of woke up look if i was nervous about talking to um i've i really admire your work and the book is very good and super exciting topic uh but then you know there's this also feeling like if this is the last conversation i have in my life you know if i die today will this be let's be uh the right like am i glad today happened and it is and i am glad today uh happened so that that's the way and that's so unique i never got that answer from a single person the busyness of life there's goals there's dreams there's like planning plans very few people make it happen that's what i learned and so a lot of these people oh like you run out of time it's not so much time but i'd come back later and be little okay why don't you do that if that's what you would do if you're gonna die a year from now why don't you why don't you make it real simple things spend more time with family like why don't you do that and no one had an answer it turns out unless you usually unless you have you really do have a pressing end of life people don't do their bucket list or try to change their career and some people can't so we can't like for a lot of people they can't do anything about it and that's that's fine but the ones who can take action for some reason never do and that was uh one of the ways that mike's death or at the time his impending death really really affected me because you know for these sick people what i learned he had a bucket list and he was able to do some of the bucket lists it was awesome but he got sick pretty quickly so if you do only have a year to live it's ironic because you can't do you can't do the things you wanted to do because you get too sick too fast what were the bucket list things for you that you realize like what am i doing with my life that was the major cons of him after he died i didn't know like i i was just lost because when something that profound happens all the things i was doing um most of the things i was doing were just meaningless it was so tough to to find an answer for that and that's when i settled on i'm gonna devote the rest of my life to trying to find another earth and to find out to find that we're not alone what is that longing for connection with others um what's that about what do you think why is that so full of meaning i don't know why i mean i think it's how we're hardwired like one of my friends some time ago actually when my dad died he never heard someone say this before but he's like sarah you know why are we evolved to take death so harshly like what kind of society would we be if we just didn't care people died like that would be a very different type of world how would we as a species have got to where we are so i think that is tied hand in hand with why do we why do we seek connection it's just that we were talking about before that subconsciousness that we don't understand yeah coupled you know the other side the flip side of the coin of connection and love is a fear of loss it's like that was again i don't know that's what makes you appreciate the moment is that the thing ends yeah it's definitely a hard one the thing ends but and it's hard to not you you wouldn't want to limit like it's like my dog who i love so much i'll start to cry like i can't think about the end i know he'll age much faster than i will and someday it will end right but it's too sad to think of but should i not have got a dog right which i've not brought this sort of joy into my life because i know it won't be forever it's well there's a there's a philosopher ernest becker who wrote a book denial of death and just uh uh and warm with the cores and there's another book talks about terror management theory sheldon solomon i just talked to him a few weeks ago uh he's a brilliant philosopher a psychologist that their theory whatever you make of it is that um the fear of death is at the core of everything everything we do so like you're that you think you don't think about the mortality of your dog but you do and that's what makes the experience rich like there's this kind of like in the shadows lurks the the knowledge that this won't last forever and that makes every moment just special in some kind of uh weird way that it the moments are special for us humans i mean sorry to use romantic terms like love but what do you make what did you learn about love from from losing it from losing your husband well i learned to love the things i have more i learn to love the people that i have more and to not let the little things bother me as much what about the rediscovery or like the discovery of the little lights um uh in the darkness so you the book i think you brilliantly describe the dark parts of your journey uh but maybe can you talk about how you were able to rediscover the lights they came in many ways and the way like to think about it is like grief is an ocean you know with tiny islands of the little like like the little lights and eventually that ocean gets smaller and smaller and the islands like become continents with lakes so initially be like the children laughing one day or my colleagues at work who rallied around me and would take me away from my darkness to work on a project later on it turned out to be a group of women my age all widows all with children in my town and it would be even though it was a bit morose getting together um still very joyful at the same time what was the journey of rediscovering love like for you so refining i mean is there some by way of advice or insight about how to um how to rediscover the beauty of life of life it's a hard one i think you just have to stay open to being positive and just to get out there do you still think do you think about your immortality so you mentioned that that was a thing that you would meditate on as a question when it was right there in in front of you but do you still think about it i think i will after talking to you but no it's not really something i think about i mean i do think about the search for another earth and will will i get there will i be able to conclude my search and is there one like as time goes by you know that window to solve that problem gets smaller what would bring you again i apologize if this makes concrete the fact that life is finite but what um what would bring you joy if we discovered while you're still here will bring me joy finding another earth an earth like planet around a sun-like star knowing that there's at least one or more out there being able to see water that it has signs of water and being able to see some gases that don't belong so i know that the search will continue after i'm gone enough to fuel the next generation ah so just like opening the door and there's like this glimmer of what do you think it will take to realize that i mean we've talked about all these interesting projects starshade especially but is there something that you're particularly kind of uh hopeful about in the next 10 20 years that might give us that that exact glimmer of hope that there's earth like planets out there i have to i stand behind star shade in all cases so but there is this other kind of field that i that everyone is involved in because star shade is hard earths are hard but there are there's another category of planet star type that's easier and these are planets orbiting small red dwarf stars they're not earth-like at all think like earth cousin instead of earth twin but there's a chance that we might establish that some of those have water and signs of life on them that's nearer term than starshade and we're all working hard on that too let me ask uh by way of recommendations i think a lot of people are curious about this kind of stuff what three books technical or fiction or philosophical or anything really uh had an impact on your life and and or you would recommend besides of course your book there's one book i wish everyone could read i'm not sure if you've read it it's actually a children's book like a young adult book it's called the giver yes and it is the book that kids in school read now and i only sorry that that's not that's wow uh sorry that that caught me off guard uh so when i first came to this country i didn't speak much it's really what made me uh it had a profound impact on my life and i'm at a really important moment because they they give it to kids like i think middle school i think or maybe yes something like that i'm so surprised you've even heard of this book yeah so they give but like it's the value of giving the right book to a person at the right time uh i was as because it's very accessible do we want to share what the story is without spoiling it uh yeah you can without spoiling right it's follows this boy in this very utopic society that's like perfect it's been all clean cut and made perfect actually and as he kind of comes of age he starts realizing something's wrong with his world and so it's part of that question are we going to evolve this i mean this isn't what's there but it made me wonder you know are we evolving to a better place is there a day when we can eliminate you know poverty and hunger and crime and sickness in this book they pretty much have in the society that the boy's in and sort of follows him and he becomes a chosen one to be like a receiver the giver is the old wise man who retains some of the harshness of the outside world so that he can advise the people as the sort of boy comes of age and is chosen for the special role he finds the world isn't what he expects and i don't know about you but it was so profound for me because it jolts you out of reality it's like oh my god what am i doing here i'm just going with the flow with my society how do i think outside the box and the confines of my society which surely carries negative things with it that we don't realize today yeah and also in the flip side of that is if you do take a step outside the box on occasion uh what's the psychological burden of that like is that is is that your is that a step you want to take is that the journey you want to take what is that life like i don't know i felt like from the book you have to take it i found from the book i never thought like now that you're saying it i see what you're saying the burden is huge but i always feel like the answer is yes you absolutely want to know what's out what's outside but you can't do that if you're very it's hard to be objective about your own reality yeah i mean it's a very human instinct but uh it also the book kind of shows that it has an effect on you and this it's a really interesting question about our society taking a step out it's by lois lowry i think is how you pronounce it i really do hope everyone created and it is a young adult book but it's still it's incredibly i'm really glad i only read it because my kids got it for school i just thought okay well why don't i just see what this is about and i just wow yeah yeah i i think it's also the value of education i think i think i'm surprised you mentioned i've never really mentioned to anybody i'm sure a lot of people had some experience like me and maybe it's a generational thing though because like the book came out i think in the 90s so if you're older then like me that book didn't exist when we were in middle school so i just do think a lot of people won't have heard of it but it's an interesting question of like those books i mean i'm reminded often i suppose the same is true with other subjects but books are special at the early age like middle school maybe early high school this those can change like the direction of your life and also certainly teachers they can change completely the direction of life there's so many stories about teachers of mathematics teachers of physics of any kind of subjects basically changing the direction of a human's life that's like not to get on the uh the whole almost like a political thing but you know we uh we undervalue teachers uh it's a special it's a special position that they hold so true yeah well i do have two other books or two other things one is something i came across just a few days ago actually it's actually a film called picture a scientist and when you picture a scientist you probably don't picture the women and women of color in this film and it is a way to get outside your box i really think everyone interested in science even just peripherally should watch this because it is shocking and sobering at the same time and it talks about how well i think one of the messages across is you know we really are like i don't know if we're hardwired to just like people like ourselves but we're excluding a lot of people and therefore a lot of great ideas by not being able to think outside of how we're all stereotyping each other so it's it's it's hard to kind of convey that and you can just say oh yeah i want to be more diverse i want to be more open but it's a nearly impossible problem to solve and the movie really helps open people's eyes to it this book i put third because unlike the giver people may not want to read it it's not as relevant but when i was in my early 20s i went to this big this like 800 people large conference call us run by the wilderness canoe association in my hometown of toronto and there's a family friend there who i met and he said read this book it'll change your life and it actually changed my life and it was a book called sleeping island by an author pg downs who just coincidentally lived in this area lived in the boston area he was a teacher i think at a private school and every summer he would go to canada with a canoe often by himself and he wrote this book maybe in the 40s or 50s about a trip he took in the late 1930s and it was i was just shocked that even at that time although that was a long time ago there were large parts of canada that were untouched by white people and he went up there and interacted like with the natives he called the book it had a subtitle that was called there's something like journey in the barren lands and when you go up north in canada you pass the tree line just like on a mountain if you hike up a mountain you get so far north there aren't any trees and he wrote eloquently about the land and about being out there there weren't even any maps of the region like in that time and i just thought to myself wow like that you could just take the summer off and explore by canoe and go and see what's out there and it led to me just doing that that very thing of course it's different now but going out to where the road ends and putting the canoe in the water and just well we had to have a plan we didn't just explore but go down this river rivers with rapids and travel over lakes and portages and just really live so just really explore screw it that doesn't like it doesn't or just use from a topo map from a topographical map from the library and those things um there were scary elements about of it out of it but part of the excitement or the joy or the desire was to be scared like was to go out there and have live on the edge and persevere yeah and persevere yeah do you have an advice that you would give to a young person today that would like to help you maybe on the planetary science side discover exoplanets or maybe bigger picture just succeed in life i do have some advice just to succeed it's tough advice in a way but it is to find something that you love doing that you're also very good at in some ways the stars have to align because you've got to find that thing you're good at or the range of things and it actually has to overlap with something that actually you love doing every day so it's not a tedious job that's the best way to succeed what were the signals that in your own life were there to make you realize you're good at something that you're you're like what were you good at that made you uh pursue a phd and made you pursue the search i mean that was the one sentence version in my case it was a long slog and there were a lot of things i wasn't good at initially but so initially you know i was good at high school math i was good at high school science i loved astronomy and i realized those could all fit together like the day i realized you could be an astronomer for a job it has to be one of my top days of my life i didn't know that you could be that for a job yeah i was good at all those things and although my dad wanted me to do something more practical where he could be guaranteed i could support myself was another option but initially i wasn't that good at physics it was a slog to just get through school and grad school is a very very long time but ultimately when faced with a choice and i had the luxury of choosing knowing that i was good at something and also loved it it really carried me through now i asked some of the smartest people in the world the most ridiculous question uh we already talked about it a little bit but let me ask uh again why why are we here so uh i think you've uh raised this question when your presentations as like what one of the things that we kind of as humans long to to answer and the search for exoplanets is kind of part of that but what do you think is the meaning of it all of life i wish i had a good answer for you i think you're the first person ever who refused to answer the question it's not so much refusing i just yeah i mean i wish i had a better answer it's it's why we're here it's almost like the meaning is uh wishing there was a meaning that we wishing wishing we knew i love that that's a great way to that's a great way to say it so like i said uh the book is excellent i admired you work from afar for a while i'm i think you're one of the the great stars at mit and makes me proud to be part of the community so thank you so much for your work thank you for inspiring all of us thanks for talking today thank you so much lex thanks for listening to this conversation with sarah seeger and thank you to our sponsors public goods power dot and cash app click the links in the description to get a discount it's the best way to support this podcast if you enjoy this thing subscribe on youtube review the fire starters on apple podcast support it on patreon connect with me on twitter alex friedman spelled i'm not sure how just keep typing stuff in until you get to the guy with the tie in the thumbnail and now let me leave you with some words from carl sagan somewhere something incredible is waiting to be known thank you for listening and hope to see you next time you |
Dileep George: Brain-Inspired AI | Lex Fridman Podcast #115 | the following is a conversation with the leap george a researcher at the intersection of neuroscience and artificial intelligence co-founder of vicarius with scott phoenix and formerly co-founder of numenta with jeff hawkins who's been on this podcast and donna dubinsky from his early work on hierarchical temporal memory to recursive cortical networks to today the leaps always sought to engineer intelligence that is closely inspired by the human brain as a side note i think we understand very little about the fundamental principles underlying the function of the human brain but the little we do know gives hints that may be more useful for engineering intelligence than any idea in mathematics computer science physics and scientific fields outside of biology and so the brain is a kind of existence proof that says it's possible keep at it i should also say that brain-inspired ai is often over-hyped and used as fodder just as quantum computing for uh marketing speak but i'm not afraid of exploring these sometimes over-hyped areas since where there's smoke there's sometimes fire quick summary of the ads three sponsors babel raycon earbuds and masterclass please consider supporting this podcast by clicking the special links in the description to get the discount it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review 5 stars on apple podcast support on patreon i'll connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show is sponsored by babel an app and website that gets you speaking in a new language within weeks go to babel.com and use codelex to get three months free they offer 14 languages including spanish french italian german and yes russian daily lessons are 10 to 15 minutes super easy effective designed by over 100 language experts let me read 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in a lot of miles to get ready for a potential ultra marathon and listening to audio books on world war ii the sound is rich and really comes in clear so again get them at byraycon.com lex this show is sponsored by masterclass sign up at masterclass.com lex to get a discount and to support this podcast when i first heard about class i thought it was too good to be true i still think it's too good to be true for 180 bucks a year you get an all-access pass to watch courses from to list some of my favorites chris hadfield on space exploration neil degrasse tyson on scientific thinking and communication will wright creator of some city and sims like game design every time i do this read i really want to play a city builder game carlos santana on guitar caspar daniel negrano on poker and many more chris hadfield explaining how rockets work and the experience of being launched into space alone is worth the money by the way you can watch it on basically any device once again sign up at masterclass.com to get a discount and to support this podcast and now here's my conversation with the leap george do you think we need to understand the brain in order to build it yes if you want to build the brain we definitely need to understand how it works so blue brain or henry markham's project is trying to build a brain without understanding it like just trying to uh put details of the brain from neuroscience experiments into a giant simulation by putting more and more neurons more and more details but that is not going to work because when it doesn't perform as uh what you expect it to do then what do you do you do you just keep adding more details how do you debug it so it's a so unless you understand unless you have a theory about how the system is supposed to work how the pieces are supposed to fit together what they're going to contribute you can't you can't build it at the functional level understand so can you actually linger on and describe the blue brain project it's kind of fascinating uh principle an idea to try to simulate the brain as we're talking about the human brain right right human brains and rad brains or cat brains have lots in common that the cortex the neocortex structure is very similar so initially they were trying to just simulate a cat brain uh and uh to understand the nature of evil they understand the nature of evil or uh as it happens in most of these simulations uh you you easily get one thing out which is oscillations you know yeah if you if you simulate a large number of neurons they oscillate and you can adjust the parameters and say that oh selections match the rhythm that we see in the brain etc but uh oh i see so like uh so the idea is uh is the simulation at the level of uh individual neurons yeah so the blue brain project the original idea as proposed was um you you put very detailed bio physical neurons uh bios physical models of neurons and you interconnect them according to the statistics of connections that we have found from real neuroscience experiments and then uh turn it on and uh see what happens uh and and these neural models are you know incredibly complicated in themselves right because these neurons are modeled using uh this idea called hodgkin-huxley models which are about how signals propagate in a cable and there are active dendrites all those phenomena which those phenomena themselves we don't understand that well uh and then uh we put in connectivity which is part guess work part you know observed and of course if you do not have any theory about how it is supposed to work uh we you know we just have to take whatever comes out of it as okay this is something interesting but in your sense like these models of the way signal travels along or like with the axons and all the basic models that's they're too crude oh well actually they are pretty detailed and pretty sophisticated and they do replicate the neural dynamics if you take a single neuron and you you try to uh turn on the different channels the calcium channels and uh the different receptors uh and see what the effect of uh turning on or off those channels are in the neurons spike output people have built pretty sophisticated models of that and and they are i i would say um you know in the regime of correct well see the correctness that's interesting because you've mentioned in several levels uh the correctness is measured by looking at some kind of aggregate statistics it would be more of the the spiking dynamics in dynamics yeah and and yeah these models because they are they are going to the level of mechanism right so they are basically looking at uh okay what what is the effect of turning on an ion channel uh and um and you can you can model that using electric circuits in and then so they are model so it is not just a uh function fitting it is people are looking at the mechanism underlying it and uh putting that in terms of electric circuit theory signal propagation theory and and modeling that and so those models are sophisticated but getting a single neurons model 99 right does not still tell you how to you know it would be the analog of getting a transistor model right and now trying to build a microprocessor um and if you if you just uh observe you know if you did not understand how a microprocessor works uh but you say oh i have i now can model one transistor well and now i will just try to interconnect uh the transistors according to whatever i could you know guess from the experiments and try to simulate it um then it is very unlikely that you will produce a functioning microprocessor um you want to you know when you want to uh produce a functioning microprocessor you want to understand boolean logic how does how do the the gates work all those things and then you know understand how do those gates get implemented using transistors yeah there's actually i remember this reminds me this is a paper maybe you're familiar with it i remember going through in a reading group that approaches a microprocessor from a perspective a neuroscientist i think it it basically it uses all the tools that we have of neuroscience to try to understand like as if we just aliens showed up to study computers uh yeah and and to see if if those tools could be used to get any kind of sense of how the microprocessor works i think the final the takeaway from the at least this initials uh exploration is that we're screwed there's no way that the tools of neuroscience would be able to get us to anything like not even boolean logic i mean it's just a any aspect of the architecture of the uh function of the processes involved uh the the clocks the the timing all that you can't figure that out from the tools of neuroscience yes i'm very familiar with this this particular paper i think it was uh called um can uh a neuroscientist understand a microprocessor yeah something like that following the methodology in that paper even an electrical engineer would not understand microprocessors so i could so i could so i i don't think it is that bad in the sense of saying um neuroscientists do find valuable things uh by observing the brain they they do find good insights um but those insight cannot be put together just as a simulation you have to you have to investigate what are the computational underpinnings pinnings of those findings how do all of them fit together from an information processing perspective you have to you have to somebody has to uh painstakingly put those things together and build hypothesis um so i don't want to this all of neuroscience is saying oh they are not finding anything no that you know that that paper almost went to that level of uh uh neuroscientists will never understand uh no that that's not true i think they do find lots of useful things but it has to be put together in a computational framework yeah i mean but you know just the ai systems will be listening to this podcast a hundred years from now and it will probably there's some nonzero probability they'll find your words laughable it's like i remember humans thought they understood something about the brain they're totally clueless there's a sense about neuroscience that we may be in the very very early days of understanding uh the brain but i mean that's one perspective in your perspective how far are we into understanding uh any aspect of the brain so the the the dynamics of the individual neuron communication to the how when they in in a collective sense how they're able to store information transfer information how the intelligence then emerges all that kind of stuff where are we on that timeline yeah so you know timelines are very very hard to predict and you can of course be wrong uh and it can be wrong in on either side uh you know we know that uh now when we look back uh the first flight was in 1903. uh in 1900 there was a new york times article on flying machines that do not fly and and you know humans might not fly for another hundred years that was what that article uh stated and uh so but no they they flew three years after that so it is you know it's very hard to um so well and on that point one of the wright brothers uh i think two years before uh said that uh like he said like some number like 50 years he he has become convinced that it's it's uh it's impossible even during their experimentation yeah yeah yeah i mean that's a tribute to when that's like the entrepreneurial battle of like depression of going through just like thinking this is impossible right but there yeah there's something even the person that's in it is not able to see uh estimate correctly exactly but i can i can tell from the point of you know objectively what are the things that we know about the brain and how that can be used to build ai models which can then go back and inform how the brain works so my way of understanding the brain would be to basically say look at the insights neuroscientists have found understand that from a computational angle information processing angle build models using that and then building the that model which which functions which is a functional model which is which is doing the task that we want the model to do it is not just trying to model a phenomena in the brain it is it is trying to do what the brain is trying to do on on the whole functional level and building that model will help you fill in the missing pieces that you know biology just gives you the hints and building the model you know fills in the rest of the the pieces of the puzzle and then you can go and connect that back to biology and say okay now it makes sense that this part of the brain is uh doing this or this layer in the cortical circuit is doing this uh and and and then continue this iteratively because now that will inform new experiments in neuroscience and of course you know building the model and verifying that in the real world will you will also tell you more about does the model actually work uh and you can refine the model find better ways of putting these neuroscience insights together so so i would say it is it is you know it so neuroscientists alone just from experimentation will not be able to build a model of the of the brain uh or a functional model of the brain so we you know there there's uh lots of efforts which are very impressive efforts in collecting more and more connectivity data from the brain yeah you know how how are the micro circuits of the brain connected with each other those are beautiful by the way those are beautiful uh and at the same time those those do not itself um by themselves convey the story of how does it work yeah uh and and somebody has to understand okay why are they connected like that and what what are those things doing uh and and we do that by building models in ai using hints from neuroscience and and repeat the cycle so what aspect of the brain are useful in this whole endeavor which by the way i should say you're you're both the neuroscientists and and ai person i guess the dream is to both understand the brain and to build agi systems so you're it's like an engineer's perspective of trying to understand the brain so what aspects of the brain uh functioning speaking like you said you find interesting yeah quite a lot of things all right so one is um you know if you look at the visual cortex um uh and and you know the visual cortex is is a large part of the brain uh i forget this exact fraction but it is it's a it's a huge part of our brain area is uh occupied by just just vision um so vision visual cortex is not just a feed-forward cascade of neurons um uh there are a lot more feedback connections in the brain compared to the feed-forward connections and and it is surprising to the level of detail neuroscientists have actually studied this if you if you go into neuroscience literature and poke around and ask you know have they studied what will be the effect of poking a neuron in level i.t uh in level v one and uh um have they studied that uh and you will say yes they have studied that so every every possible combination i mean it's it's a it's not a random exploration at all it's very hypothesis driven right they are very uh experimental neuroscientists are very very systematic in how they probe the brain uh because experiments are very costly to conduct they take a lot of preparation they they need a lot of control so they they are very hypothesis driven in how they probe the brain and um often what i find is that when we have a question in um in ai uh about have has anybody probably probed how lateral connections in the brain works and when you go and read the literature yes people have probed it and people have probed it very systematically and and they have hypothesis about how those lateral connections are supposedly contributing to visual processing uh but of course they haven't built very very functional detail models of it by the way how do you know studies start to interrupt that do they do they stimulate like a neuron in one particular area of the visual cortex and then see how the travel of the signal travels kind of thing fascinating very very fascinating experiments right you know so i can i can give you one example i was impressed with um this is uh so before going to that let me like let me give you a a you know a overview of how the the layers in the cortex are organized right uh visual cortex is organized into roughly four hierarchical levels okay so uh v one v two v four i t and in v one of v three uh well yeah there's another pathway okay okay so there's this this is this i'm talking about just the object recognition pathway right okay and then um in v1 itself um so it's there is a very detailed micro circuit in v1 itself there is there is organization within a level itself uh the cortical sheet is organized into uh you know multiple layers and there are columnar structure and and this this layer wise and column structure is repeated in v1 v2 v4 uh it all of them right and and the connections between these layers within a level with you know in v1 itself there are six layers roughly and the connections between them there is a particular structure to them uh and um now so one example of an experiment uh uh people did is when i when you present a stimulus uh which is um let's say requires um separating the foreground from the background of an object so it is it's a textured triangle on a textured background and you can check does the surface settle first or does the contour settle first cerro settle in the sense that the so when you find finally form the percept of the of the triangle you understand where the contours of the triangle are and you also know where the inside of the triangle is right that's when you form the final percept uh now you can ask what is the dynamics of forming that final percept um do the do the neurons um first find the edges and converge on where the edges are and then they find the inner surfaces or does it go the other way the other way around um so so what's the answer uh in this case it it turns out that it first settles on the edges it it converges on the edge hypothesis first and then the the surfaces are filled in from the edges to the inside that's fascinating uh and and the detail to which you can study this it's it's amazing that you can actually not only find um the temporal dynamics of when this happens uh and then you can also find which layer in the you know in v1 which layer is encoding uh the edges which layer is encoding the surfaces and which layer is encoding the feedback which there is encoding the feed forward and what what's the combination of them that produces the final person um and these kinds of experiments stand out when you try to explain illusions uh one one example of a favorite illusion of mine is the kanetsa triangle i don't know that you are familiar with this one so this is um uh this is an example where it's a triangle uh but you know the corners of the only the corners of the triangle are shown in the stimuli the stimulus so they look like kind of pac-man oh the black pac-man exactly yeah and then you start to see your visual system hallucinates the edges yeah um and you can you know you when you look at it you will see a faint edge right and you can go inside the brain and look you know do actually neurons signal the presence of this edge and and if this signal how do they do it because they are not receiving anything from the input in the the input is black for those neurons right uh so how do they signal it when does the signaling happen you know does it you know so so if a real contour is present in the input then the signa the neurons immediately signal okay there is a there is an edge here when when it is an illusory edge um it is clearly not in the input it is coming from the context so those neurons fire later and and you can say that okay these are it's the feedback connections that is causing them to fire uh and and they happen later and you can find the dynamics of them so so these studies are pretty impressive and and very detailed so by the way just uh just take a step back you said uh that there may be more feedback connections and feed forward connections yeah uh first of all it's just just for like a machine learning folks yeah i mean that for that's crazy that there's all these feedback connections i mean we often think about i think thanks to deep learning you start to think about um the human brain as a kind of feed forward mechanism right so what the heck are these feedback connections yeah what's their what's the dynamics well what are we supposed to think about them yeah so this is this fits into a very beautiful picture about how the brain works right um so the the beautiful picture of how the brain works is that our brain is building a model of the world uh i know so our visual system is building a model of how objects behave in the world and and we are constantly projecting that model back onto the world so what we are seeing is not just a feed forward thing that just gets interpreted in in a few word party we are constantly projecting our expectations onto the world and and what the final percept is a combination of what we project onto the world uh combined with what the actual sensory input is almost like trying to calculate the difference and then trying to interpret the difference yeah it's it's um i wouldn't put just calculating the difference it's more like what is the best explanation for the input stimulus based on the model of the world i have got it got it and that's where all the illusions come in and that's but that's that's an incredibly efficient so uh efficient process so the feedback mechanism it just helps you constantly uh yeah so hallucinate how the world should be based on your world model and then just looking at uh if there's novelty uh like trying to explain it like that hence that's why movement we detect movement really well there's all these kinds of things and that this is like at all different levels of the cortex you're saying this happens at the lowest level or the highest level yes yeah in fact feedback connections are more prevalent in everywhere in the cortex and and um so one way to think about it and there's a lot of evidence for this is inference um so you know so basically if you have a model of the world and when when some evidence comes in what you are doing is inference right you are trying to now explain this evidence using your model of the world yep and this inference includes projecting your model onto the evidence and taking the evidence back into the model and and doing an iterative procedure and this iterative procedure is what happens using the feed forward feedback propagation and feedback affects what you see in the world and you know it also affects feed forward propagation and examples are everywhere we we see these kinds of things everywhere the idea that there can be multiple competing hypotheses in our model trying to explain the same evidence and then you have to kind of make them compete and one hypothesis will explain away the other hypothesis through this competition process wait what so you have competing models of the world that tried to explain what do you mean by explain away so this is a classic example in uh uh graphical models probabilistic models um so if you what are those um okay um i think it's useful to mention because we'll talk about them more yeah yeah so neural networks are one class of machine learning models um you know you have distributed set of nodes which are called the neurons you know each one is doing a dot product and you can you can approximate any function using this a multi-level network of neurons so that's a class of models which are used for useful for function approximation there is another class of models in machine learning called probabilistic graphical models and you can think of them as each node in that model is variable which is which is talking about something you know it can be a variable representing is is an edge present in the input or not and at the top of the uh network a node can be uh representing is there an object present in the world or not and and then so it can it is it is another way of encoding knowledge and uh um and then you once you encode the knowledge you can uh do inference in the right way you know how what is the best way to uh you know explain some sort of evidence using this model that you encoded you know so when you encode the model you are encoding the relationship between these different variables how is the edge connected to my the model of the object how is the surface connected to the model of the object and then of course this is a very distributed complicated model and inference is how do you explain a piece of evidence when a set of stimulus comes in if somebody tells me there is a 50 probability that there is an edge here in this part of the model how does that affect my belief on whether i should think that there should be is the square present in the image so so this is the process of inference so one example of inference is having this experience of effect between multiple causes so uh graphical models can be used to represent causality in the world um so let's say um you know uh your uh alarm at home can be uh triggered by a burglar getting into your house uh or it can be triggered by an earthquake both both can be causes of the alarm going off so now you you're right you know you're in your office you heard burglar alarm going off you are heading uh home thinking that there's a burglar got it but while driving home if you hear on the radio that there was an earthquake in the vicinity now your hype you know uh strength of evidence for a burglar getting into their house is diminished because now that that piece of evidence is explained by the earthquake being present so if you if you think about these two causes explaining at lower level uh variable which is alarm now what we are seeing is that increasing the evidence for some cause ex you know there is evidence coming in from below for alarm being present and initially it was flowing to a burglar being present but now since somebody some this there the side evidence for this other cause it explains away this evidence and it evidence will now flow to the other course this is you know two competing causal uh things trying to explain the same evidence and the brain has a similar kind of mechanism for doing so that's kind of interesting and that how's that all encoded in the brain like where's the storage of information are we talking just maybe to get it a little bit more specific is it in the hardware of the actual connections is it in uh chemical communication is it electrical communication do we do we know so this is you know a paper that we are bringing out soon which one this is the cortical micro circuits paper that i sent you a draft of of course this is uh a lot of it is still hypothesis one hypothesis is that a you can think of a cortical column as encoding a a concept a concept you know think of it as say an example of a concept is um is an edge present or not or is is an object present or not okay so it can you can think of it as a binary variable a binary random variable the presence of an edge or not or the presence of an object or not so each cortical column can be thought of as representing that one concept one variable and then the connections between these cortical columns are basically encoding the relationship between these random variables and then there are connections within the cortical column there are each cortical column is implemented using multiple layers of neurons with very very very rich um structure there you know there are thousands of neurons in a cortical column but but that structure is similar across the different cortical columns yeah correct and also these cortical columns collect connect to a substructure called thalamus in the uh you know so all all cortical columns pass through this substructure so our hypothesis is that yeah the connections between the cortical columns implement this uh you know that's where the knowledge is stored about you know how these different connects concepts connect to each other and then the the neurons inside this cortical column and in thalamus in combination implement this uh actual computations needed for inference which includes explaining a way and competing between the different uh hypotheses um and it is all very so what is amazing is that uh neuroscientists have actually done experiments to the tune of showing these things they might not be putting it in the overall inference framework but they will show things like if i poke this higher level neuron it will inhibit through this complicated loop through the thalamus it will inhibit this other column uh so they will do such experiments but do they use terminology of concepts for example so so you're i mean is it uh is it something where it's easy to anthropomorphize and think about concepts like you start moving into logic based kind of reasoning systems so um i would just think of concepts in that kind of way or is it is it a lot messier a lot more gray area you know even even more gray even more messy than the artificial neural network kinds of abstractions the easiest way to think of it as a variable right it's a binary variable which is showing the presence or absence of something so but i guess what i'm asking is is that something that we're supposed to think of something that's human interpretable of that something it doesn't need to be it doesn't need to be human interpretable there's no need for it to be human interpretable uh but it's it's almost like um you you will be able to find some interpretation of it uh because it is connected to the other things yes that you know and the the point is it's useful somehow yeah it's useful as an entity in the graph that in connecting to the other entities that are let's call them concepts right okay so uh by the way what's are these the cortical micro circuits correct these are the cortical micro circuits you know that's what neuroscientists use to talk about the circuits in in uh within a level of the cortex so you can think of you know let's think of a neural network in artificial neural network terms you know people talk about the architecture of the you know so how many how many layers they build uh you know what is the fan in fan out etc that is the macro architecture so and then within a layer of the neural network you can you know the cortical neural network is much more structured with you know within a level there's a lot more intricate structure there uh but even um even within an artificial neural network you can think of in feature detection plus pooling as one one level and so that is kind of a micro circuit uh it's much more uh complex in the real brain uh and and so within a level whatever is that circuitry within a column of the cortex and between the layers of the cortex that's the micro circuitry i love that terminology uh machine learning people don't use the circuit terminology right but they should it's a nice so okay uh okay so that's uh that that's the the cortical micro circuit so what's interesting about what can we say what is the paper that you're working on propose about the ideas around these cortical micro circuits so this is a fully functional model for the micro circuits of the visual cortex so the the paper focuses and your idea in our discussions now is focusing on vision yeah the uh visual cortex okay yeah this is a model this is a full model it says this is how vision works but this is this is a model of science yeah hypothesis okay so let me let me step back a bit um so we looked at neuroscience for insights on how to build a vision model right and and and we synthesized all those insights into a computational model this is called the recursive vertical network model that we we used for breaking captchas and and we are using the same model for robotic picking and uh tracking of objects and that again is the vision system that's the best computer vision system that's the computer mission takes in images and outputs what on one side it outputs the class of the image and also segments the image uh and you can also ask it further queries where is the edge of the object where is the interior of the object so so it's a model that you build to answer multiple questions so you are not trying to build a model for just classification or just segmentation etc so it's a it's a it's a joint model that can do multiple things um and um so so that's the model that we built using insights from neuroscience and some of those insights are what is the role of feedback connections what is the role of lateral connections uh so all those things went into the model the model actually uses feedback connections all these ideas from you know from your science yeah so what what what the heck is a recursive cortical network like what what are the architecture approaches interesting aspects here which is essentially a brain inspired approach to computer vision yeah so there are multiple layers to this question i can go from the very very top and then zoom in okay so one important thing constraint that went into the model is that you should not think vision think of vision as something in isolation we should not think perception as something as a preprocessor for cognition perception and cognition are interconnected and so you should not think of one problem in separation from the other problem um and so that means if you finally want to have a system that understand concepts uh about the world and can learn in a very conceptual model of the world and can reason and connect to language all of those things you need to you need to have think all the way through and make sure that your perception system is compatible with your cognition system and language system and all of them and one aspect of that is top-down controllability um what does that mean so that means you know so so think of it you know you can close your eyes and think about the details of one object right i can i can zoom in further and further i can you know so so think of the bottle in front of me right and and now you can think about okay what the cap of that bottle looks uh i know we can think about what's the texture on that bottle of the of the cap you know you can think about you know what will happen if uh something hits that uh so you can you can you can manipulate your visual knowledge in uh cognition driven ways yes uh and so this top-down controllability uh and being able to simulate scenarios in the world so you're not just a passive uh player in this perception game you you can you can control it you gotta you you have imagination correct so so so basically you know basically having a generating network yeah which is a model and and it is not just some arbitrary generated network it has to be it has to be built in a way that it is controllable top-down it is it is not just trying to generate a whole picture at once uh you know it's not trying to generate photorealistic things of the world you you know you don't have good photorealistic models of the world human brains do not have if i if i for example ask you the question uh what is the color of the letter e in the google logo you have no idea right now yeah although you have seen it millions of times hundreds of times so yeah so it's not our model is not photorealistic but but it is but it has other properties that we can manipulate it uh in the uh and you can think about filling in a different color in that logo you can think about expanding the the letter e yeah you know you can see what in so you can imagine the consequence of you know actions that you have never performed so so these are the kind of characteristics the genetic model need to have so this is one constraint that went into our model like you know so this is when you read the just the perception side of the paper it is not obvious that this was a constraint into the inter that went into the model this top-down controllability of the generating model uh so what what does the top-down controllability in a model look like it's a really interesting concept fascinating concept what is that is that the recursive recursiveness gives you that or how do you how do you do it um quite a few things it's like what what does the model factor or factorize you know what are the what is the model representing us different pieces in the puzzle like you know so so in the rcn uh network it it thinks of the world you know what i say the background of an image is modeled separately from the foreground of the image so the objects are separate from the background they're different entities so there's a kind of segmentation that's built in fundamentally that's why and and then even that object is composed of parts and also and another one is the the shape of the object uh is differently modeled from the texture of the object got it so there's like these um i've been you know who francois charles is yeah he's so there's uh he developed this like iq test type of thing for arc challenge for and uh it's kind of cool that there's um these concepts priors that he defines that you bring to the table in order to be able to reason about basic shapes and things in the iq test right so here you're making it quite explicit that here here are the things that you should be there these are like distinct things that you should be able to uh model and yes keep in mind that you you can derive this from much more general principles it doesn't you don't need to explicitly put it as oh objects versus foreground versus background uh the surface versus structure now these are these are derivable from more fundamental principles of how you know what's the property of continuity of natural signals what's the property of continuity of natural signals yeah by the way that sounds very poetic but yeah uh so you're saying that's a there's some low-level properties from which emerges the idea that shapes should be different than like uh there should be a parts of an object there should be i mean exactly kind of like friends of water i mean there's objectness there's all these things that it's kind of crazy that we're humans uh i guess evolved to have because it's useful for us to perceive the world correct yeah correct and it derives mostly from the properties of natural signals and yeah and so um natural signals so natural signals are the kind of things we'll perceive in the in the natural world i don't know i don't i don't know why that sounds so beautiful natural signals yeah as opposed to a qr code right which is an artificial signal that we created humans are not very good at classifying qr codes we are very good at saying something is a cat or a dog but not very good at you know the classification computers are very good at classifying qr codes so our visual system is tuned for natural signals and there are fundamental assumptions in the architecture that are derived from natural signals properties i wonder when you take a hallucinogenic drugs does that go into natural or is that closer to the qr code it's still natural yeah because it's it is still operating using your brains by the way on that on that topic i i mean i haven't been following i think they're becoming legalized at certain i can't wait until they become legalized to the degree that you like vision science futures could study it yeah just like through through medical chemical ways modify there could be ethical concerns but modif that's another way to study the brain is to be be able to chemically modify it there's probably um probably very long a way to figure out how to do it ethically yeah but i i think there are studies on that already yeah i think so uh because it's not unethical to give uh it to rats oh that's true that's true [Laughter] there's a lot of drugged up rats out there okay yeah cool sorry sorry so okay so there's uh so there's these uh low-level uh things from natural signals that uh that that from which these properties will emerge yes uh but it is still a very hard problem on how to encode that again so you don't you know there is no uh so uh you mentioned um the the the priors uh francho wanted to encode in uh in the abstract reasoning challenge but it is not straightforward how to encode those priors um so so some of those uh challenges like you know the object completion challenges are things that we purely use our visual system to do it is uh it looks like abstract reasoning but it is purely an output of the the vision system for example completing the corners of that condenser triangle completing the lines of that cancer triangle it's a purely a visual system property there is no abstract reasoning involved it it uses all these priors but it is stored in our visual system in a particular way that is amenable to inference and and and that is one of the things that we tackled in the you know so basically saying okay these are the prior knowledge uh which which will be derived from the world but then how is that prior knowledge represented in the model such that inference when when some piece of evidence comes in can be done very efficiently and in a very distributed way um because it is very there are so many ways of representing knowledge which is not amenable to very quick inference in a quick lookups and so that's one um core part of what we tackled in uh the rcn model um uh how do you encode visual knowledge to uh do very quick inference and yeah can you maybe comment on uh so folks listening to this in general may be familiar with different kinds of architectures of neural networks what what are we talking about with rcn uh what are what does the architecture look like what are different components is it close to neural networks is it far away from neural networks what does it look like yeah so so you can uh think of the delta between the model and a convolutional neural network if people are familiar with convolutional neural networks so convolutional neural networks have this feed-forward processing cascade which is called uh feature detectors and pooling and that is repeated in the in the hierarchy in a multi-level uh system um and if you if you want an intuitive idea of what what is happening feature detectors are uh you know detecting interesting co-occurrences in the input it can be a line a corner a an eye or a piece of texture etc and the pooling neurons are doing some local transformation of that and making it invariant to local transformations so this is what the structure of convolutional neural network is um recursive cortical network has a similar structure when you look at just the feed forward pathway but in addition to that it is also structured in a way that it is generating so that again it can run it backward and combine the forward with the backward another aspect that it has is it has lateral connections these lateral connections um which is between so if you have an edge here and an edge here it has connections between these edges it is not just feed forward connections it is um something between these edges which is the nodes are presenting these edges which is to enforce compatibility between them so otherwise what will happen is the constraints it's a constraint it's basically if you if you do just feature detection followed by pooling then your your transformations in different parts of the visual field are not coordinated uh and so you can you will create a jagged when you when you generate from the model you will create jagged um things and uncoordinated transformations so these lateral connections are enforcing the the transformations is the whole thing still differentiable uh no okay no it's not it's not trade using uh backprop okay that's really important so uh so there's this feed forward there's feedback mechanisms there's some interesting connectivity things it's still layered like uh yes there are multiple levels multiple layers okay very very interesting uh and yeah okay so the interconnection between um adjacent the connections across service constraints that like keep the thing stable got it okay so what else uh and then there is this idea of doing inference a neural network does not do inference on the fly so an example of why this inference is important is you know so one of the first applications of that we showed in the paper was to crack uh text-based captchas what are captures by the way by the way one of the most awesome like the people don't use this term anymore is human computation i think uh i love this term the guy who created captures i think came up with this term yeah i love it anyway uh yeah uh what what are captures so captchas are those strings that you fill in uh when you're you know when if you're opening a new account in google they show you a picture you know usually it used to be a set of garbage letters uh that you have to kind of figure out what what what is that string of characters and type in and the reason cap just exist is because you know google or twitter do not want automatic creation of accounts you can use a computer to create millions of accounts uh and uh use that for in nefarious purposes uh so you want to make sure that to the extent possible the interaction that your their system is having is with a human so it's a it's called a human interaction proof a captcha is a human interaction proof um so so this is a captchas are by design things that are easy for humans to solve but hard for computers hard for robots yeah so and text-based captchas where was the one which is prevalent and around 2014 because at that time text-based voice captures were hard for computers to crack even now they are actually in the sense of an arbitrary text based capture will be unsolvable even now but with the techniques that we have developed it can be you know you can quickly develop a mechanism that solves the captcha they've probably gotten a lot harder too the people they've been getting clever and clever generating these text characters yeah right so okay so that was one of the things you've tested on is these kinds of captures in 2014 15. got that kind of stuff right right so what uh what i mean why by the way why captchas yeah yeah even now i would say captcha is a very very good challenge problem uh if you want to understand how human perception works and if you want to build uh systems that work like the human brain uh and i wouldn't say captcha is a solved problem we have cracked the fundamental defense of captures but it is not solved in the way that humans solve it um so i can give an example i can um take a five-year-old child who has just learned characters uh and uh show them any new capture that we create they will be able to solve it uh i can show you pretty much any new capture from any new website you'll be able to solve it without getting any training examples from that particular style of captcha you're assuming i'm human yeah yes yeah that's right so if you are human and if you otherwise i will be able to figure that out using this one but uh so this whole podcast is just a touring test a long turing test anyway i'm sorry so yeah so human humans can figure it out with very few examples or no training examples like no training examples from that particular style of capture and and so you can you know so uh even now this is unreachable for the current deep learning system so basically there is no i don't think a system exists where you can basically say train on whatever you want and then now say hey i will show you a new captcha which i did not show you in in the in the training setup will the system be able to solve it um it still doesn't exist so that is the magic of human perception yeah and doug have starter uh put this uh very beautifully in one of his uh talks the the central problem in ai is what is the letter a if you can if you can build a system that reliably can detect all the variations of the letter a you don't even need to go to the v and the c yeah you don't even know the b and c or the strings of characters and uh so that that is the spirit at which you know with which we uh tackle that what does it mean by that i mean is it uh like without training examples try to figure out the fundamental uh elements that make up the letter a in all of its forms in all of its forms it can be a can be made with two humans standing leaning against each other holding the hands yeah and uh it can be made of leaves it can be yeah you might have to understand uh everything about this world in order to understand letter a yeah exactly so it's common sense reasoning essentially yeah right so so to finally to really solve finally to say that you have solved captcha uh you have to solve the whole problem yeah okay so what how does this kind of the rcn architecture help us to get a do a better job of that kind of yeah so uh as i mentioned one of the important things was being able to do inference being able to dynamically do in france can you can you uh can you uh clarify what you mean because you said like neural networks don't do inference yeah so what do you mean by inference in this context then so okay so in captures what they do to confuse people is to make these characters crowd together yes okay and when you make the characters crowd together what happens is that you will now start seeing combinations of characters as some other new character or or an existing character so you would you would put an r and n together it will start looking like an m uh and and so locally they are you know there is very strong evidence for it being uh some uh incorrect character but globally the only explanation that fits together is something that is different from what you can find locally yes so so so this is inference you are basically taking uh local evidence and putting it in the global context and often coming to a conclusion locally which is conflicting with the local information so actually so you mean inference like uh in the way it's used when you talk about reasoning for example uh as opposed to like inference which is this when you know with artificial neural networks which is a single pass through the network okay so like you're basically doing some basic forms of reasoning like integration of like uh how local things fit into the the global picture and and things like explaining away coming into this one because you are you are uh explaining that piece of evidence uh as something else uh because globally that's the only thing that makes sense um so now yeah you can amortize this inference by you know in a neural network if you want to do this what you you can you can brute force it you can just show it all combinations of things that you want to you want to your reasoning to work over and you can you know like just train the help out of that neural network and it will look like it is doing uh you know inference on the fly but it is it is really just doing amortized inference it is because you you have shown it a lot of these combinations during training time um so what you want to do is be able to do dynamic inference rather than just being able to show all those combinations in the training time and that's something we emphasized in the model what does it mean dynamic in france is that that has to do with the feedback thing yes like what what is dynamic i i'm trying to visualize what dynamic influence would be in this case like what is it doing with the input it's showing the input the first time yeah and is is like what's changing over temporally over what's the dynamics of this inference process so you can think of it as you have um at the top of the model the characters that you are trained on yeah they are the causes they you are trying to explain the pixels using the characters as the causes the you know the characters are the things that cause the pixels yeah so there's this causality thing so the reason you mentioned causality i guess is because there's a temporal aspect of this whole thing in this particular case the temporal aspect is not important it is more like when if if i turn the character on the the pixels will turn on yeah it will be after there's a little bit but okay so that is the causality in the sense of like a logic causality like hence inference okay the dynamics is that uh even though locally it will look like okay this is an a and and locally just when i look at just that patch of the image it looks like an a but when i look at it in the context of all the other courses it might no am is not the something that makes sense so that is something you have to kind of you know recursively figure out yeah so okay so uh and uh this thing performed pretty well on the captchas correct and um i mean is there some kind of interesting intuition you can provide why did well like what did it look like is there visualizations that could be human interpretable to us humans yes yeah so the good thing about the model is that it is extremely um so it is not just doing a classification right it is it is it is it is providing a full explanation for the scene so when when it when it um operates on a scene it is coming at back and saying look this is the part is the a and these are the pixels that turned on uh these are the pixels in the input that tells makes me think that it is an a and also these are the portions i hallucinated it you know it it provides a complete explanation of that form and then it's again these are the contours these are this is the interior and this is in front of this other object so that that's the kind of um explanation it uh the the inference network provides so so that that is useful and interpretable um and uh um then the kind of errors it makes are also i don't want to um read too much into it but the kind of errors the network makes are very similar to the kinds of errors humans would make in a similar situation so there's something about the structure that's uh feels reminiscent of the way humans visual system works well i mean uh how hard-coded is this to the capture problem this idea uh not really hardcoded because it's the uh the assumptions as i mentioned are general right it is more um and and those themselves can be applied in many situations which are natural signals um so it's it's the foreground versus background factorization and the factorization of the surfaces versus the contours so these are all generally applicable assumptions in our vision so why why capture why attack the capture problem which is quite unique in the computer vision context versus like the traditional benchmarks of imagenet and all those kinds of image classification or even segmentation tests all that kind of stuff do you feel like that's uh i mean what what's your thinking about those kinds of benchmarks in um in this in this context i mean those benchmarks are useful for deep learning kind of algorithms where you you know so the settings uh that deep learning works in are here is my huge training set and here is my test set so the the training set is almost uh you know 100 x 1000 x bigger than uh the test set in many many cases uh what we wanted to do was invert that the training set is way smaller than the the test set yes uh and uh uh and you know uh captcha is a problem that is by definition hard for computers and it has these good properties of strong generalization strong out of training distribution generalization if you are interested in studying that and putting having your model have that property then it's it's a good data set to tackle so is there have you attempted to which i think i believe there's quite a growing body of work on looking at mnist and imagenet without training so it's like taking like the basic challenge is how what tiny fraction of the training set can we take in order to do a reasonable job of the classification task have you explored that angle in these classic benchmarks yes so so we did do mnist so um you know so it's not just capture we uh so there was uh also uh uh versions of multiple versions of mnist including the the standard version which where we inverted the problem which is basically saying rather than train on 60 000 uh training data uh you know how uh quickly can you get uh to high level accuracy with very little training data was is there some performance do you remember like how well how well did it do how many examples did he need yeah i i you know i remember that it was you know uh on the order of uh tens or hundreds of examples to get into uh 95 accuracy and it was it was definitely better than the systems other systems out there at that time at that time yeah yeah they're really pushing i think that's a really interesting space actually uh i think there's an actual name for mnist that uh like there's different names the different sizes of training sets i mean people are like attacking this problem i think it's super interesting yeah it's funny how like that mnist will probably be with us all the way to agi yes it's the data set that just sticks by it is it's a clean simple uh data set to uh to study the fundamentals of learning with just like captures it's interesting not enough people i don't know maybe you can correct me but i feel like captures don't show up as often in papers as they probably should that's correct yeah because you know um usually these things have a momentum uh you know once once uh something gets established as a standard benchmark yeah there is a there is a uh there is a dynamics of how graduate students operate and how the academ academy system works that uh pushes people to track that uh benchmark so yeah yeah so nobody wants to think outside the box okay okay so good performance on the captures what else is there interesting um on the rcn side before we talk about the cortical microscope yeah so the same model so the the the important part of the model was that it trains very quickly with very little training data and it's you know quite robust to out of distribution uh perturbations um and and we are using that uh very uh fruitfully in uh advocates in many of the robotic stocks we are solving so you know well let me ask you this kind of touchy question i have to i i've spoken with uh your friend colleague jeff hawkins too i mean he's uh i have to kind of ask there is a bit of whenever you have brain inspired stuff yeah and you make big claims yeah uh big sexy claims yeah there's a you know uh there's critics i mean machine learning subreddit don't get me started on those people uh their heart i mean criticism is good but they're a bit they're a bit over the top um there is quite a bit of sort of skepticism and criticism you know is this work really as good as it promises to be yeah what do you have thoughts on that kind of skepticism do you have comments on the kind of criticism you might have received uh about you know is this approach legit is this is this a promising approach yeah or at least as promising as it seems to be you know advertised as yeah i can comment on it um so you know our arson paper is published in science which i would argue is is a very high quality journal very hard to uh publish in and use you know usually it is indicative of the of the quality of the work and um i can i can i am very very certain that the ideas that we brought together in that paper uh in terms of the importance of feedback connections uh recursive inference lateral connections uh coming to best explanation of the scene as the problem to solve trying to solve um recognition segmentation uh all jointly in a way that is compatible with higher level cognition top-down attention all those ideas that we brought together into something you know coherent and workable in the in the world and solving a challenge tackling a challenging problem i think that will that will stay and that that contribution i stand by right now uh i can i can tell you a story which is funny in the in the context of this right um so if you read the abstract of the paper and you know the argument we are putting in you know we are putting in look current deep learning systems take a lot of training data uh they don't use these insights and here is our new model which is not a deep neural network it's a graphical model it does inference this is what how the paper is right now once the paper was accepted and everything um it went to the press department in in science you know to play as science office we we didn't do any press release when it was published it was he went to the press department what did the what was the press release that they wrote up a new deep learning model solves captchas and uh so so you can see where was you know what was being hyped uh in that uh thing right so so it's like um there is the there is a dynamic in the uh in the community of you know so uh um that's especially happens when there are lots of new people coming into the field and they get attracted to one thing and some people are trying to think different uh compared to that so there's there is some uh i think skepticism is science is important and it is um you know very much uh required but it's also it's not uh skepticism usually it's mostly bandwagon effect that is happening rather than well but that's not even that i mean i'll tell you what they react to which is like i'm sensitive to as well if you if you look at just companies open ai deep mind yeah um vicarious i mean it just there's uh there's a little bit of a race to the top and hype right right it's it's like it doesn't pay off to be humble so like uh and and the press is just uh irresponsible often they they just i mean don't get me started on the state of journalism today like it seems like the people who write articles about these things they literally have not even spent an hour on the wikipedia article about what is neural networks like yeah they haven't like invested just even the language to laziness it's like uh robots beat humans like they they write this kind of stuff that just uh and then and then of course the researchers are quite sensitive to that because it gets a lot of attention they're like why did this work get so much attention uh you know that's that's over the top and people get really sensitive you know the same kind of criticism with uh opening i did work with the rubik's cube with the robot that people criticized uh same with gpt two and three they criticize uh same thing with the deep minds with alpha zero i mean yeah i i'm sensitive to it but and of course with your work you mentioned deep learning but there's something super sexy to the public about brain inspired i mean that immediately grabs people's imagination not even like neural networks but like really brain inspired like like brain like neural networks that seems really compelling to people and um to me as well to to the world as a narrative and so uh people hook up hook on to that and uh sometimes you uh the skepticism engine turns on in the research community and they're skeptical but i think putting aside the ideas of the actual performance on captures or performance in any data set i mean to me all these data sets are useless anyway it's nice to have them but in the grand scheme of things they're silly toy examples the point is is their intuition about the the ideas just like you mentioned bringing the ideas together in a unique way is there something there is there some value there and this is going to stand the test of time yes and that's the hope that's the hope i'm my confidence there is very high i you know i don't treat brain inspect as a marketing term uh you know i am looking into the details of biology and i'm puzzling over uh those things and i am i am grappling with those things and so this it is not a marketing term at all it you know you can use it as a marketing term and and people often use it and you can get combined with them and when when people don't understand how we are approaching the problem it is it is easy to be uh misunderstood and you know think of it as you know purely uh marketing but that's not the way uh we are so you really i mean as a scientist you believe that if we kind of just stick to really understanding the brain that's going to that's the right like you should constantly meditate on the how does the brain do this because that's going to be really helpful for engineering intelligent systems yes you need to so i think it is it's one input and it is it is helpful but you you should know when to deviate from it too um so an example is convolutional neural networks right uh convolution is not an operation brain in implements uh the visual cortex is not convolutional visual cortex has local receptive fields local connectivity but the you know the um there is there is no translation in in variance in the um uh the network weights um in in the visual cortex that is a a computational trick which is a very good engineering trick that we use for sharing the training between the different uh nodes um so and and that trick will be with us for some time it will go away when we have um robots with eyes and heads that move uh and so then that trick will go away it will not be uh useful at that time so so the brain doesn't so the brain doesn't have translational invariance it has the focal point like it has a thing it focuses on correct it does it has a phobia and and because of the phobia um the receptive fields are not like the copying of the weights like the the weights in the center are very different from the weights in the periphery yes at the periphery i mean i did this uh actually wrote a paper and just gotten the chance to really study peripheral peripheral vision which is a fascinating thing very under understood thing of what the br you know at the every level the brain does with the periphery it does some funky stuff yeah so it's uh it's another kind of trick than uh convolutional like it does it it uh it's a you know convolutional convolution in neural networks is a trick to for efficiency is efficiency trick and the brain does a whole another kind of thing yeah yes got it so so you need to understand the principles or processing so that you can still apply engineering tricks yeah when where you want to do you don't want to be slavishly making all the things of the brain um and and so yeah so it should be one input and i think it is extremely helpful uh but you it should be the point of really understanding so that you know when to deviate from it so okay that's really cool that that's work from a few years ago so you'd uh you did work in jumento with jeff hawkins yeah uh with uh hierarchical temporal memory how is your just if you could give a brief history how is your view of the way the models of the brain changed over the past few years leading up to to now is there some interesting aspects where there is an adjustment to your understanding of the brain or is it all just building on top of each other in terms of the higher level ideas especially the ones jeff wrote about in the book if you if you blur out right you know yeah on intelligence right on intelligence if you if you blur out the details and and if you just zoom out and at the higher level idea uh things are i would say consistent with what he wrote about but but many things will be consistent with that because it is it's a blur you know when you when you you know deep learning systems are also you know multi-level hierarchical all of those things right so so at the but um in terms of the detail a lot of things are different uh and and and those details matter a lot um so so one point of difference i had with jeff uh uh was uh how to approach you know how much of biological possibility and realism do you want in the learning algorithms um so uh when i was there uh this was you know almost 10 years ago now so yeah you're having fun i don't know i don't know what just thinks now but 10 years ago uh the difference was that i did not want to be so constrained on saying uh my learning algorithms won't need to be biologically possible based on some filter of biological possibility available at that time to me that is a dangerous cut to make because we are you know discovering more and more things about the brain all the time new biophysical mechanisms new channels uh are being discovered all the time so i don't want to upfront kill off an uh a learning algorithm just because we don't really understand the full uh the full uh biophysics or whatever of how the brain learns exactly exactly well let me ask a sergeant like what's our what's your sense what's our best understanding of how the brain learns so things like back propagation credit assignment so so many of these algorithms have learning algorithms have things in common right it is a back propagation is one way of credit assignment there is another algorithm called expectation maximization which is you know another weight adjustment algorithm but is it your sense the brain does something like this has to there is no way around it in the sense of saying that you do have to adjust the the connections so yeah and you're saying credit assignment you have to reward the connections that were useful and making a correct prediction and not yeah i guess what up but yeah it doesn't have to be differentiable i mean yeah it doesn't have to be differentiable yeah yeah but you have to have a you know you have a model that you start with you where you have data comes in and you have to have a way of adjusting the model such that it better fits the data yeah so that that is all of learning right and some of them can be using backprop to do that some of it can be using uh you know very local uh graph changes to do that um that can you know many of these learning algorithms have similar update properties locally in terms of what the neurons need to do locally i wonder if small differences in learning algorithms can have huge differences in the actual effect so the dynamics of i mean uh sort of the reverse like spiking like the uh if if credit assignment is like a a lightning versus like a rainstorm or something like whether whether there's a like a looping local type of situation with the credit assignment yeah whether there is uh like regularization like how um how it injects robustness into the whole thing like whether it's chemical or electrical or mechanical yeah uh all those kinds of things like that i feel like it that yeah i feel like those differences could be essential right it could be it's just that you don't know enough to on the learning side you don't know enough to say that is definitely not the way the brain does it got it so you don't want to be stuck to it right so that yeah so you you've been open-minded on that side of that correct on the infrastructure on the recognition side i am much more uh i'm able to be constrained because it's much easier to do experiments because you know it's like okay here's the stimulus you know how many steps did it get to take the answer i can trace it back i can i can understand the speed of that computation etc much more readily on the infant side got it and then you can't do good experiments on the learning side correct so that let's let's go right into the cortical micro circuits right back so what uh what are these ideas beyond recursive cortical network that uh you're looking at now so we have made a you know pass through or you know multiple of the steps that we you know i say as i mentioned earlier you know we were looking at perception from the angle of cognition right it was not just perception for perception's sake how do you how do you connect it to cognition uh how do you learn concepts and how do you learn abstract reasoning uh similar to some of the things francois uh uh talked about right um so um so we have uh taken one pass through it basically saying what is the basic cognitive architecture that you need to have which has a perceptual system which has a system that learns dynamics of the world and then has something like a routine program learning system on top of it to learn concepts so we have we've built one the you know the version 0.1 of that system uh this was another uh science robotics paper uh it is it's the title of that paper was you know something like cognitive programs how do you build cognitive programs and and the application there was on manipulation robotics it was um so think of it like this suppose you uh wanted to tell a new person uh that you met you don't know the language or that person uses you want to communicate to that person uh to achieve some task right so i want to say hey um you need to pick up all the the red cups from the kitchen counter and put it here right how do you communicate that right you can show pictures you can basically say look this is the starting state the the things are here this is the ending state and and what does the person need to understand from that the person need to understand what conceptually happened in those pictures from the input to the output right so um so we are looking at pre-verbal conceptual understanding without language how do you how do you have a set of concepts that you can manipulate in your head uh and from this in a set of images of input and output can you infer what is happening in those images got it with concepts that are pre-language okay so what does it mean for a concept to be pre-language like yeah why why so why why is language uh so important here so i i want to make a distinction between concepts that are just learned from text by just just feeding brute force text uh you can you can start extracting things like okay uh cow is likely to be on grass so those kinds of things you can extract purely from text um uh but that's kind of a simple association uh thing rather than a concept as an abstraction of something that happens in the real world you know in a grounded way that i can i can simulate it in my mind and connect it back to the real world and you think kind of the visual uh the visual world concepts in the visual world are somehow lower level than just the language the lower level kind of makes it feel like okay that's like unimportant like it's more like uh i would say uh the concepts in the visual and the motor system and you know the uh the concept learning system which if you cut off the language part just uh just what we learned by interacting with the world and abstractions from that that is a prerequisite for any real language understanding so you're uh so you disagree with chomsky because he says language is at the bottom of everything no i i yeah i disagree with chomsky completely from from universal grammar to yeah so that was a paper in science beyond the recursive cortical network uh what what other interesting problems are there the open problems and brain inspired uh approaches that you're thinking about i mean everything is over right like you know no no no problem is uh solved solved all right uh first uh i think of perception as kind of the the pro the first thing that you have to build but the last thing that you will be actually solved so because if you do not build perception system in the right way you cannot build concept system in the right way so so you have to build a perception system however wrong that might be you have to still build that and learn concepts from there and then you know keep it rating um and and finally perception will get solved fully when perception cognition language all those things work together finally so what uh i'm not so great we've talked a lot about perception but then maybe on the concept side and like common sense or just general reasoning side is there some some intuition you can draw from the brain about how we can do that so i have i have this uh classic example i give um so suppose i give you a few sentences and then ask you a question following that sentence this is a natural language processing problem right so so here it goes i'm telling you uh sally pounded a nail on the ceiling okay oh that's a sentence now i am asking you a question was the nail horizontal or vertical vertical okay how did you answer that uh well i imagined sally it was kind of hard to imagine what the hell she was doing but uh but i imagined i had a visual of the whole situation exactly exactly so so here you know i i post a question in natural language the answer to that question was you you got the answer from actually simulating the scene now i can go more and more detail about okay was sally stan standing on something while doing this you know could could she have been uh standing on a light bulb to do this you know i could i could ask more and more questions about this and i can ask make you simulate the synonym scene in more and more detail right where is all that knowledge that you are accessing stored it is not in your language system it is not it was not just by reading text you got that knowledge it is stored from the everyday experiences that you have had from and and by the by the age of five you you have pretty much all of this right and it is stored in your visual system motor system in a way such that it can be accessed through language i got it i mean right so your the language is just almost services the query into the whole visual cortex and it does the whole feedback thing but i mean it is all reasoning kind of connected to the perception system in some way you can do a lot of it you know you can still um do a lot of it by quick associations without having to go into the depth and and most of the time you will be right right you can just do quick associations but i can easily create tricky situations for you where that quick association is wrong and you have to actually run the simulation so the figuring out the how these concepts connect you have a good idea of how to do that that's exactly what that does one of the problems that we are working on and and and and the uh the way we are approaching that is basically saying okay you need to so the the uh the takeaway is that language is simulation control and your perceptual plus uh motor system is building a simulation of the world and so so that's basically the way we are approaching it and the first thing that we built was a controllable perceptual system and we built a schema networks which was a controllable dynamic system then we built a concept learning system that puts all these things together into programs are subtractions that you can run and simulate and now we are taking the step of connecting into language and uh and uh it will be very simple examples initially it will not be the gpt three like examples but it will be grounded simulation based language and for like the the querying would be like question answering kind of thing correct correct and it will be in some simple world initially on you know uh i but it will be about okay can the system connect the language and uh ground it in the right way and run the right simulations to come up with the answer and the goal is to try to do things that for example gpg3 couldn't do got it speaking of which if we could uh talk about gpt3 a little bit i think it's an interesting thought-provoking set of ideas that open ai is pushing forward i think it's good for us to talk about the limits and the possibilities in neural networks so in general what are your thoughts about this recently released very large 175 billion parameter language model so i have i haven't uh directly evaluated it yet from what i have seen on twitter and you know other people evaluating it it looks very intriguing you know i am i am very intrigued by some of the properties it is displaying and and of course the text generation uh part of that was already evident in gpt2 you know that it can generate cochrane text over uh uh long distances that was uh but of course the weaknesses are also pretty visible in saying that okay it is not really carrying a world state around um and you know sometimes you get sentences like i went up the hill to reach the valley or the thing now there are some you know completely incompatible statements or when you're traveling from one place to the other it doesn't take into account the time of travel things like that so those things i think will happen less than gpt 3 because it is trained on even more data and so and it has it can do even more longer distance uh uh coherence um but it will still have the fundamental limitations that it doesn't have a world model uh and it can't run simulations in its head to find whether something is true in the world or not do you think within so it's taking a huge amount of text from the internet and forming a compressed representation do you think in that could could emerge something that's an approximation of a world model which essentially could be used for reasoning and it's a it's a it's a i'm not talking about gpt three i'm talking about gpt four five and gpt 10. yeah i mean they will look more impressive than gpg3 so you can if you take that to the extreme then uh a markov chain of just first order and if you if you go to um i'm taking the other extreme if you read shannon's book right uh he has a model of english text which is based on faster mark of chains second order markov chains third markov chain sentencing that okay the markov chains look better than uh faster markov chains right so does that mean a faster markov chain has a model of the world yes it does uh so yes in that level uh when you go higher order models or more uh sophisticated structure in the model like the transformer networks have yes they have a model of the text world um but that is not a model of uh the world it's it's a model of the text world and it will have in interesting uh properties and it will be useful but just scaling it up is not going to give us a gi or natural language understanding or meaning well the the question is uh whether being forced to compress a very large amount of text yeah forces you to construct things that are very much like because the ideas of concepts and meaning is a spectrum yeah uh so in order to form that kind of compression maybe it will uh be forced to figure out abstractions which look awfully a lot like the kind of things that we think about as uh as concepts as world models as common sense is that possible no i don't think it is possible because the information is not there well the information is uh is there behind the text right now unless somebody has written down all the details about how everything works in the world to the the absurd amounts like okay it is easier to walk forward than backward uh that you have to open the door to go out of the thing uh doctors wear underwear you know unless all these things somebody has written down somewhere or you know somehow the program found it to be useful for compression from some other text uh the information is not there so that's an argument that like text is a lot lower fidelity than the you know the experience of our physical world like right so you can use a thousand words like that kind of thing well in this case pictures aren't really so the the richest aspect of the physical world isn't even just pictures it's the uh it's the interactivity of the world yeah it's being able to um yeah interact it's almost like it's almost like if you could interact so i i i disagree well maybe i agree with you that picture's worth a thousand words but a thousand it's still yeah you could say you could capture it with the gpt x so i wonder if there's some interactive element where a system could live in text world where it could uh be part of the chat be part of you know talking to people it's it's interesting i mean fundamentally so you're making a statement about the limitation of text okay let's so let's say we have a text corpus that includes basically every experience we could possibly have i mean just a very large corpus of text and also interactive components i guess the question is whether the neural network architecture these very simple transformers but if they had like hundreds of trillions or whatever comes after a trillion parameters whether that could store the information needed that's architecturally do you have like do you have thoughts about the limitation on that side of things with neural networks i mean so transformer is you know still a feed forward neural network this uh uh it's it has a very uh interesting architecture which is good for uh text modeling and probably some aspects of uh video modeling but it is still a feed forward architecture and you believe in the feedback mechanism the recursion oh and and also because you know causality you know being able to do counterfactual reasoning being able to do you know intervention so which is uh uh um actions in the world uh so all those things uh require different kinds of models to be built uh i i don't think uh transformers uh captures that uh family it is very good at statistical modeling of text uh yeah and and it will become better and better with more data uh bigger models but that is only going to get so far you know finally when you in so i had this joke on uh twitter saying that hey this is a model that has read all of quantum mechanics and theory of relativity and we are asking it to do text completion or you know we are actually asking you to solve simple puzzles that you know when when you have agi if you if you you know that's not what you ask a system to do if you just you know we ask we'll ask the system to do experiments you know what should uh and and come up with hypothesis and uh you know revise the hypothesis based on evidence from experiments all those things right those are the things that we want the system to do when we have a gi not solved with simple puzzles so like impressive demo somebody generating a red button in html right uh which are all useful like you know there's no not dissing the the usefulness of it yeah so i get by the way i'm i mean playing a little bit of a devil's advocate uh so calm down internet uh so i just i'm curious almost in which ways will a dumb but large neural network will surprise us yeah so like i'm it's kind of your i completely agree with your intuition it's just that i don't want to dogmatically like 100 percent put all the chips there right it's we've been surprised so much even the current gpt 2 and 3 are so surprising yeah uh the self-play mechanisms of alpha zero are really surprising and i the reinforcement the fact that reinforcement learning works at all to me is really surprising the fact that neural networks work at all is quite surprising given how non-linear the space is the fact it's able to find local minima that are at all reasonable it's very surprising so it uh i i wonder sometimes whether us humans just want it to not the for agi not to be such a dumb thing so i just because exactly what you're saying is like the ideas of concepts and be able to reason with those concepts and and connect those concepts in uh like hierarchical ways and then to be able to have uh world models i mean just everything we're describing in human language in this poetic way seems to make sense that that is what intelligence and reasoning are like i i wonder if at the core of it it could be much dumber uh well finally it is still connections and messages passing over them right right so that way it's done so i guess the recursion the the feedback mechanism that does seem to be a fundamental kind of thing um yeah yeah the idea of concepts also memory correct like having an episodic memory yeah yeah that seems to be an important thing so how do we get memory so yeah we have another piece of work that which came out recently on how do you form episodic memories and and form abstractions from them uh and we haven't figured out a you know all the connections of that to the overall cognitive architecture but um well yeah what are your ideas about how you could have episodic memory so at least it's very clear that there you need to have two kinds of memory right that that's very very clear right because there are things that happen uh as statistical patterns in the world uh but then there is the the one timeline of things that happen only once in your life right uh uh and this day is not going to happen ever again and and so and that needs to be stored as a as a you know just a stream of uh string right this is this is my experience and then then the question is about how do you take that experience and connect it to the statistical part of it how do you now say that okay i experienced this thing now i want to be careful about similar situations uh and so so you need to be able to index that similarity using your other giant status you know the the model of the world that you have learned although the situation came from the episode you need to be able to index the other one so uh the episodic memory being implemented as an indexing over the other uh model that you're building so the memories remain and they uh they they're an index into this like the statistical thing that you formed yeah statistical causal structural model that you built over over time so so it's basically the idea is that uh the hippocampus is uh just storing or sequencing uh in a set of pointers that happens over time and then whenever you want to reconstitute that memory and evaluate the different uh aspects of it whether it was good bad do i need to encounter the situation again you need the cortex to reinstantiate to replay that memory so how do you find that memory like which direction is the important direction both directions are units again bi-directional so i guess how do you retrieve the memory so this is again hypothesis right yeah we're making this work so when you uh when you come to a new situation right uh your your cortex is doing inference uh over in the new situation and then of course hippocampus is connected to different parts of the cortex um and and you have this deja vu situation right okay i have seen this thing before and uh and then in the hippocampus you can have an index of okay this is when it happened as a timeline uh and and and then then you can use the hippocampus to drive the the similar timelines to say now i am i am rather than being driven by my current input stimuli i am going back in time and rewinding my experience for applying it but putting back into the cortex and then putting it back into the cortex of course affects what you're going to see next in your current situation got it yeah so that's that's the whole thing having a world model and then yeah uh connecting to the perception yeah it does seem to be that that's what's happening it'd be on the neural network side it's um it's interesting to think of how we actually do that yeah yeah to have a knowledge base yes it is possible that you can put many of these structures into uh neural networks and we will find ways of combining properties of neural networks and graphical models so uh i mean it's already started happening yes uh graph neural networks are kind of emerge between them and there will be more of that thing so but to me it is the direction is pretty cl i mean looking at biology and the histo history of uh uh evolutionary history of intelligence it is pretty clear that okay what does need is more structure in the models and modeling of the world and supporting dynamic inference well let me ask you uh there's a guy named elon musk there's a company called neurolink and there's a general field called brain computing interfaces yeah um it's kind of uh interface between your two loves yes the brain and the intelligence uh so there's like very direct applications of brain computer interfaces for people with different conditions more in the short term yeah but there's also these sci-fi futuristic kinds of ideas of ai systems being able to communicate in a high bandwidth way with the brain bi-directional yeah uh what are your thoughts about uh neural link and bci in general as a possibility so i think bca is a cool research area and in fact um when i got interested in brains initially when you know so i was enrolled at stanford and when i got interested in brains it was it was through a brain uh computer interface talk that krishna gave that's when i even started thinking about the problem so uh so it is definitely a fascinating research area and it is the applications are enormous right um so you know there is a science fiction scenario of you know brains directly communicating let's you know let's keep that aside for the time being uh even just the the intermediate milestones that pursuing which are very reasonable as far as i can see uh being able to control an external limb using uh uh in a direct connection from the brain and being able to write things into the brain uh so so those are all uh good steps to take and they have enormous applications you know people losing limbs being able to control prosthetics quadriplegics being able to control something so and therapeutics and you know i also know about another company working in the space called paradromix they're doing you know it's based on a different uh electrode array but trying to attack some of the same problems so i think it's a very also surgery correct surgically implanted electrons yeah um so yeah i think of it as a very very promising field especially when it is helping people overcome uh some limitations now at some point of course it will advance the level of being able to communicate uh how hard is that problem do you think like so so okay let's say we magically solve what i think is a really hard problem of doing all of this safely yeah so so like being able to uh connect electrodes and not just thousands but like millions to the right i i think it's very very hard because you also do not know what the what will happen to the brain with that right in the sense of how does the brain adapt to something like that and it's you know as we're learning it's the brain is quite uh in terms of neuroplasticity it's pretty malleable so it's going to adjust so the machine learning side the computer side is going to adjust and then the brain is going to adjust exactly and then what what soup does this landers the kind of hallucinations you might get from this that might be pretty intense yeah yeah just connecting to all of wikipedia it's interesting whether we need to be able to figure out the basic protocol of the brain's communication schemes in order to get them to the machine and the brain to talk because another possibility is the brain actually just adjusts to whatever the heck the computer is doing exactly that's the way i think that i find that to be a more promising way it's basically saying you know okay attach electrodes to some part of the cortex okay and make sure maybe if it is done from birth the brain will adapt it says that you know that part is not damaged it was not used for anything these electrodes are attached there right and now you you train that part of the brain to do this high bandwidth communication between something else right and and uh if you do it like that either then it is brain adapting to and of course your external system is the sciences that it is adaptable you know just like we you know design computers or mouse keyboard all of them to be uh interacting with humans so of course that feedback system is designed to be uh human compatible but um now it is not trying to record from the all of the brain and uh you know now you know two systems trying to adapt to each other it's the brain adapting into one way it's passing the brain is connected to like the internet it's connected yeah just imagine just connecting it to twitter and just just just taking that stream of information um yeah but again if we take a step back i don't know what your intuition is i feel like that is not as hard of a problem as the doing it safely there's there's a huge barrier to surgery right because because the biological system it's it's a mush of like weird stuff correct so that the surgery part of it biology part of it the the long term repercussions part of it again i don't know what else will uh you know we we often find uh after a long time uh in biology that okay that idea was wrong right you know so people used to cut off this the gland called the thymus or something and then they found that oh no that actually causes cancer and then there's a subtle like millions of variables involved but this whole process the nice thing and just like again with elon just like colonizing mars seems like a ridiculously difficult idea but in the process of doing it we might learn a lot about the biology of the neurobiology of the brain the neuroscience side of things it's like if you want to learn something do the most difficult version of it yeah and see what you learn the intermediate steps that they are taking sounded all very reasonable to me yeah yeah it's great well but like everything with elon is the timeline seems insanely fast so that's that's the only awful question uh well one we've been talking about cognition a little bit so like reasoning we haven't mentioned the other c word which is consciousness uh do you ever think about that one do is that useful at all uh in this whole context of what it takes to create an intelligent reasoning being or is that completely outside of uh your uh like the engineering perspective uh it is not outside the realm but it doesn't on a day-to-day way uh you know basis inform what we do but it's more so in in many ways the company name is connected to this uh idea of consciousness what's what's the company name vicarious you know so vacation is the company name and uh and so what does victorious mean right it's um uh at the first level it is about modeling the world and uh and it is internalizing the external actions so so you interact with the world and learn a lot about the world and now after having learned a lot about the world you can run those things in your mind without actually having to uh act in the world so you can run uh things vicariously just in your in your in your brain and similarly you can experience another person's thoughts by you know having a model of how that person works and uh and running their you know putting yourself in some other person's shoes so that is being vicarious now it's the same modeling apparatus that you're using to model the external world or some other person's thoughts you can turn it to yourself you can up you know if that same modeling thing is applied to your own modeling apparatus then that is what gives rise to consciousness i think well that's more like self-awareness there's the heart problem of consciousness which is like when the model becomes when when the model feels like something when this whole process is like it act it's like you really are in it you feel like an entity in this world not just you know that you're an entity but it feels like something to be that entity it um it you know and thereby we attribute this you know then it starts to be wherein something that has consciousness can suffer you start to have these kinds of things that we can reason about that yes much much heavier it seems like there's much greater cost of your your decisions and like mortality is tied up into that like the fact that these things end right first of all i end at some point and then other things end and you know that that somehow seems to be at least for us humans a deep motivator yes and that you know that that idea of motivation in general we talk about goals and ai but right the goals aren't quite the same thing as like the our mortality it feels like it feels like first of all humans don't have a goal and they just kind of create goals at different levels they like make up goals because we're terrified by the mystery of the thing that that gets us all so we we make these goals up so we're like a go generation machine as opposed to a machine which optimizes the trajectory towards a singular goal so it feels like that's an important part of uh cognition that whole mortality thing well it is it is a part of human uh cognition uh but there is no uh reason for uh that mortality to come to the equation for a uh artificial system because we can uh copy the artificial system the the the problem with humans is that we cut i can't clone you i can't like you know i can i can close even if i clone usb uh you know the hardware your experience uh that was stored in your brain uh your uh episodic memory all those will not be captured in the in the new clone um so um but that's not the same with an ai system right so but it's also possible that the the thing that you mentioned with that with us humans is actually fundament of fundamental importance for intelligence so like the fact that you can copy an ass system yeah means that that ai system is not yet an um agi so like there it could so if you look at existence proof yeah if we reason yeah based on existence proof would you could say that it doesn't feel like death is a fundamental property of an intelligence system but we don't yet give me an example of an immortal intelligent being we don't have those it could it's very possible that you know that's that is a fundamental property of intelligence is a thing that has a deadline for itself so you can think of it like this so suppose you invent a way to freeze people uh for a long time it's not dying right yeah uh so so you can be frozen and woken up uh thousands of years from now uh so it's no fear of death so well no the you're still it's it's not it's not about time it's about the knowledge that it's temporary and the that aspect of it the finiteness of it i think um creates a kind of urgency correct for us for humans yeah for humans yes uh and that that is part of our drives uh but um and that's why i'm not too worried about ai uh you know uh having motivations to kill all humans and uh those kinds of things why just wait you know so so why do you need to do that yeah i've never heard that before that's a good it's a good point because yeah just murder seems like a lot of work we'll just wait wait it out they'll probably hurt themselves let me ask you um people often kind of wonder world-class researchers such as yourself what kind of books technical fiction philosophical were had an impact on you in your life and maybe ones you could prob possibly recommend that others read maybe if you have three books that pop in the mind yeah so i definitely liked uh judy apple's book uh probabilistic reasoning and intelligence systems it's um it's a very deep technical book but what i liked is that so there are many uh places where you can learn about probabilistic graphical models from but throughout this book judea pulls kind of sprinkles his philosophical observations and and he thinks about us to how the brain thinks and attentions and resources all those things so so that whole thing makes it more interesting to read uh he emphasizes the importance of causality so that was in his later book so this was the first book probabilistic reasoning in interlinked systems he mentions causality but he hadn't really sunk his teeth into like you know how do you actually formalize that yeah and uh the second book causality so two thousand uh the one in two thousand that one is really hard so i wouldn't recommend that uh uh yes so that looks at the like the mathematical like his model of uh calculus do calculus yeah it was pretty dense mathematically right yeah right uh the book of why is definitely more enjoyable oh for sure yeah um so yeah so i would i would recommend probabilistic reasoning in intelligent systems another book i liked uh was uh one from doug huff starter uh this is a long time ago though here's a book he had a book i think called it was called the mind's eye it was um uh probably half starter and daniel dennett together uh yeah so and i actually was uh i i bought that book so much i haven't read it yet but i uh i couldn't get an electronic version of it which is annoying because i'm you read everything on kindle okay uh you had to actually purchase the physical it's like one of the only physical books i have because yeah anyway there's a lot of people recommended it highly so yeah and the third one uh i would definitely recommend reading is um uh this is not a technical book it is history it's called it's the name of the book i think is bishop's voice it's about wright brothers and uh and their their their path and how it was uh it's there are multiple books on this topic and all of them are great it's um uh fascinating how a flight was uh you know treated as an unsolvable problem and and and also you know what aspects did people emphasize uh you know people thought oh it is all about the just powerful engines you know just need to have powerful lightweight engines uh and um so you know some people thought of it as how far can we just throw the thing you know just throw it yeah catapult yeah so so it is it's a very fascinating and even after they uh made the invention of people not believing it and uh uh the social aspect of it this is the social aspect it's a different you know very important do you uh draw any parallels between you know birds fly so there's the natural approach to uh to flight and then there's the engineered approach do you um do you see the same kind of thing with the brain and are trying to engineer intelligence yeah it's it's a good analogy to have uh of course all analogies have their you know uh yeah so for sure so people in uh you know ai often uh use airplanes as an example of hey we didn't learn anything from birds look right there yeah but the the funny thing is that uh and and the saying is uh airplanes don't flap wings yeah right this is what they say the funny thing and the ironic thing is that that you don't need to flap to fly is something right brothers found by observing birds yeah so they have in their notebook you know in some of these books they show their notebook drawings right they they make detailed notes about buzzards uh just soaring over the thermals and they basically say look flapping is not the important propulsion is not the important problem to solve here we want to solve control uh and uh once you solve control propagation will fall into place all of these are people you know they re realize this by observing birds beautiful part put that's actually brilliant uh because people do use that knowledge a lot i'm gonna have to remember that one do you have a advice for people interested in artificial intelligence like young folks today i talk to undergraduate students all the time uh interested in neuroscience interesting in understanding how the brain works is there advice you would give them about their career maybe about their life in general sure i think every you know every piece of advice should be taken with a pinch of salt of course because you know each person is different their motivations are different but i can i can definitely say if your goal is to understand the brain from the angle of wanting to build one you know then uh being an experimental neuroscientist might not be the way to go about it um uh it might a better way to pursue it might be through computer science electrical engineering machine learning and ai and of course you have to study up the neuroscience but that you can do on your own um if you are more uh attracted by finding something intriguing about discovering something intriguing about the brain then of course it is uh better to be an experimentalist so find that motivation what are you intrigued by and of course find your strengths too some people are very good experimentalists uh and and they enjoy doing that and essentially to see which department if you're if you're picking in terms of like your education path whether to um uh to go with like in mit it's branding computer uh no uh bcs yeah brandon cognitive sciences yeah uh or or the cs side of things right and actually uh the brain folks the neuroscience folks are more and more now embracing of uh you know learning tensorflow by torch right there they they see the power of uh trying to engineer ideas uh that uh that they get from the brain into and then explore how those could be used to uh to create intelligent systems so that might be the right department actually to uh so this was a question in uh uh you know one of the redwood neuroscience institute workshops or that jeff hawkins organized almost 10 years ago this question was put to a panel right what what should be the undergrad major you should take if you want to understand the brain and uh and the majority opinion that one was electrical engineering interesting uh because i mean i'm a doubly undergrad so i got lucky in that way but it i i think it does have some of the right ingredients because you learn about circuits you you learn about how you can construct circuits to uh you know approach you know do functions uh you learn about microprocessors um you learn information theory you learn signal processing uh you learn continuous math so um so in that way it's it's a good step to if you want to go to computer science or neuroscience you can it's a good step the downside you're more likely to be forced to use matlab [Laughter] one of the interesting things about i mean this is changing the world is changing but uh like certain departments lagged on the programming side of things on developing good uh good habits as a software engineering but i think that's more and more changing and and students can take that into their own hands like learn to program i feel like everybody should learn to program because it uh like everyone in the sciences because it empowers it puts the data at your fingertips so you can organize it you can find all kinds of things in the data and then you can also for the appropriate sciences build systems that like based on that so like then engineer intelligence systems uh we already talked about mortality so we hit no a ridiculous point but let me ask you the uh you know one of the things about intelligence is it's goal driven and you study the brain so the question is like what's the goal that the brain is operating under what's what's the meaning of it all for us humans in your view what's the meaning of life the meaning of life is whatever you construct out of it it's completely open it's open yeah so there's no there's nothing uh uh like you mentioned you like constraints what's uh it's it's wide open is there is there some useful aspect that you think about in terms of like the openness of it and just the basic mechanisms of generating goals uh and studying cognition in the brain that you think about or is it just about because everything we've talked about kind of the perception system is to understand the environment that's like to be able to like not die exactly like not fall over and like be able to uh you don't think we need to um think about anything bigger than that yeah i think so because it's it's basically being able to understand the machinery of the world uh such that you can push you whatever goals you want right so the machinery of the world is is really ultimately what we should be uh striving to understand the rest is just the rest is just whatever the heck you want to do or whatever whatever is culturally popular i think that's i that's beautifully put i don't think there's a better way to end it delete i'm so honored that you you show up here and waste your time with me it's been an awesome conversation thanks so much for talking today oh thank you so much this was this was so much more fun than i expected thank you thanks for listening to this conversation with the league george and thank you to our sponsors babel raycon earbuds and masterclass please consider supporting this podcast by going to babel.com and use codelex going to buy raycon.com lex and signing up at masterclass.com lex click the links get the discount it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review five star snap a podcast support it on patreon i'll connect with me on twitter alex friedman spelled yes without the e just f-r-i-d-m-a-n and now let me leave you with some words from marcus aurelius you have power over your mind not outside events realize this and you will find strength thank you for listening and hope to see you next time you |
Russ Tedrake: Underactuated Robotics, Control, Dynamics and Touch | Lex Fridman Podcast #114 | the following is a conversation with russ tedrick a roboticist and professor at mit and vice president of robotics research at toyota research institute or tri he works on control of robots in interesting complicated underactuated stochastic difficult to model situations he's a great teacher and a great person one of my favorites at mit we'll get into a lot of topics in this conversation from his time leading mit's delta robotics challenge team to the awesome fact that he often runs close to a marathon a day to and from work barefoot for a world-class roboticist interested in elegant efficient control of underactually dynamical systems like the human body this fact makes russ one of the most fascinating people i know quick summary of the ads three sponsors magic spoon cereal better help and expressvpn please consider supporting this podcast by going to magicspoon.com lex and using code lex at checkout going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links in the description buy the stuff get the discount it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five stars nappa podcast support it on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this episode is supported by magic spoon low carb keto friendly cereal i've been on a mix of keto or carnivore diet for a very long time now that means eating very little carbs i used to love cereal obviously most have crazy amounts of sugar which is terrible for you so i quit years ago but magic spoon is a totally new thing zero sugar 11 grams of protein and only three net grams of carbs it tastes delicious it has a bunch of flavors they're all good but if you know what's good for you you'll go with cocoa my favorite flavor and 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text anytime and schedule weekly audio and video sessions check it out at betterhelp.com lex this show is also sponsored by expressvpn get it at expressvpn.com lexpod to get a discount and to support this podcast have you ever watched the office if you have you probably know it's based on the uk series also called the office not to steer up trouble but i personally think the british version is actually more brilliant than the american one but both are amazing anyway there are actually nine other countries with their own version of the office you can get access to them with no geo restriction when you use expressvpn it lets you control where you want sites to think you're located you can choose from nearly 100 different countries giving you access to content that isn't available in your region so again get it on any device at expressvpn.com lexbod to get an extra three months free and to support this podcast and now here's my conversation with russ tedjerk what is the most beautiful motion of a animal or robot that you've ever seen i think the most beautiful motion of a robot has to be the passive dynamic walkers i think there's just something fundamentally beautiful the ones in particular that steve collins built with andy rowena at cornell a 3d walking machine so it was not confined to a boom or a plane that you put it on top of a small ramp give it a little push it's powered only by gravity no controllers no batteries whatsoever it just falls down the ramp and at the time it looked more natural more graceful more human-like than any robot we'd seen to date powered only by gravity how does it work well okay the simplest model is kind of like a slinky it's like an elaborate slinky one of the simplest models we use to think about it is actually a rimless wheel so imagine taking a bike's bicycle wheel but take the rim off so it's now just got a bunch of spokes if you give that a push it still wants to roll down the ramp but every time its foot its spoke comes around and hits the ground it loses a little energy every time it takes a step forward it gains a little energy those things can come into perfect balance and actually they they want to it's a stable phenomenon if it's going too slow it'll speed up if it's going too fast it'll slow down and it comes into a stable periodic motion now you can take that rimless wheel which doesn't look very much like a human walking take all the extra spokes away put a hinge in the middle now it's two legs that's called our compass gate walker that can still you give it a little push starts falling down a ramp looks a little bit more like walking at least it's a biped but what steve and andy and ted mcgear started the whole exercise but what steve and andy did was they took it to this beautiful conclusion where they built something that had knees arms a torso the arms swung naturally uh give it a little push and that looked like a stroll through the park how do you design something like that i mean is that art or science it's on the boundary i think there's a science to getting close to the solution i think there's certainly art in the way that they they made a beautiful robot but but then the finesse because because this was work they were working with a system that wasn't perfectly modeled wasn't perfectly controlled there's all these little tricks that you have to tune the suction cups at the knees for instance so they stick but then they release at just the right time or there's all these little tricks of the trade which really are art but it was a point i mean it made the point and we were at that time the walking robot the best walking robot in the world was honda's asimo absolutely marvel of modern engineering it's 90s this was in 97 when they first released it sort of announced p2 and then it went through it was asimo by then in 2004 um and it looks like this very cautious walking like you're walking on on hot coals or something like that i think it gets a bad rap asimo is a beautiful machine it does walk with its knees bent our atlas walking had its knees bent but actually ezimo was pretty fantastic but it wasn't energy efficient neither was atlas when we worked on atlas none of our robots have that have been that complicated have been very energy efficient but there was a there's a thing that happens when you do control when you try to control a system of that complexity you try to use your motors to basically counteract gravity take whatever the world's doing to you and push back erase the dynamics of the world and impose the dynamics you want because you can make them simple and analyzable mathematically simple and this was a very sort of beautiful example that you don't have to do that you can just let go let physics do most of the work right and you just have to give it a little bit of energy this one only walked down a ramp it would never walk on the flat to walk on the flat you have to give a little energy at some point but maybe instead of trying to take the forces imparted to you by the world and replacing them what we should be doing is letting the world push us around and we go with the flow very zen very zen robot yeah but okay so that sounds very zen but you can i can also imagine how many like failed versions they had to go through like how many like i would say it's probably would you say it's in the thousands that they've had to have the system fall down before they figured out how they could i don't know if it's thousands but uh it's a lot it takes some patience there's no question so in that sense control might help a little bit oh the abs i think everybody even at the time said that the answer is to do with that with control but it was just pointing out that maybe the way we're doing control right now isn't the way we should got it so what what about on the animal side the ones that figured out how to move efficiently is there anything you find inspiring or beautiful in the movement of anybody i do have a favorite example okay so it sort of goes with the passive walking idea so is there you know how energy efficient are animals okay there's a great series of experiments by george lotter at harvard and mike tranifilo at mit they were studying fish swimming in a water tunnel okay and one of these the type of fish they were studying were these rainbow trout because they there was a phenomenon well understood that rainbow trout when they're swimming upstream at mating season they kind of hang out behind the rocks and it looks like i mean that's tiring work swimming upstream they're hanging out behind the rocks maybe there's something energetically interesting there so they tried to recreate that they put in this water tunnel a rock basically a cylinder that had the same sort of vortex street the eddies coming off the back of the rock that you would see in a stream and they put a real fish behind this and watched how it swims and the amazing thing is that if you watch from above what the fish swims when it's not behind a rock it has a particular gate you can identify the fish the same way you look at a human looking walking down the street you sort of have a sense of how human walks the fish has a characteristic gate you put that fish behind the rock its gate changes and what they saw was that it was actually resonating and kind of surfing between the vortices yeah now here was the experiment that really was the clincher because there was still it wasn't clear how much of that was mechanics of the fish how much of that is control the brain so the clincher experiment and maybe one of my favorites to date although there are many good experiments they took this was now a dead fish um they took a dead fish they put a string that went that tied the mouse of the fish to the rock so it couldn't go back and get caught in the grates uh and then they asked what would that dead fish do when it was hanging out behind the rock and so what you'd expect it sort of flopped around like a dead fish in the in the vortex wake until something sort of amazing happens and this video is worth putting in right what happens uh the dead fish basically starts swimming upstream right it's completely dead no brain no motors no control but it somehow the mechanics of the fish resonate with the vortex street and it starts swimming upstream it's one of the best examples ever who do you give credit for that too is that just evolution constantly just figuring out by killing a lot of generations of animals uh like the most efficient motion is that uh or maybe the physics of our world completely like it's like evolution applied not only to animals but just the entirety of it somehow drives to efficiency like nature likes efficiency i don't know if that question even makes any sense i understand the question that's reason i mean do they co-evolve yeah somehow yeah like i don't know if an environment can evolve but um i mean there are experiments that people do careful experiments that show that um animals can adapt to unusual situations and recover efficiency so there seems like at least in one direction i think there is reason to believe that the animal's motor system and probably its mechanics adapt in order to be more efficient but efficiency isn't the only goal of course sometimes it's too easy to think about only efficiency but we have to do a lot of other things first not get eaten and then all other things being equal try to save energy by the way let's uh draw a distinction between control and mechanics like how how can how would you define each yeah i mean i think part of the point is that we shouldn't draw a line as as clearly as we tend to but the you know on a robot we have motors and we have the links of the robot let's say if the motors are turned off the robot has some passive dynamics okay gravity does the work you can put springs i would call that mechanics right if we have springs and dampers which our muscles are springs and dampers and tendons but then you have something that's doing active work putting energy in your motors on the robot the controller's job is to send commands to the motor that add new energy into the system right so the mechanics and control interplay somewhere the divide is around you know did you decide to send some commands to your motor or did you just leave the motors off and let them do their work would you say is most of nature on the dynamic side or the control side so like if you look at biological systems if you know we're living in a pandemic now like do you think a virus is a do you think it's a dynamic system or um or is there a lot of control intelligence i think it's both but i think we maybe have underestimated how important the dynamics are right um i mean even our bodies the mechanics of our bodies certainly with exercise they evolved but so i actually i lost a finger in early 2000s and it's my fifth metacarpal it turns out you use that a lot in ways you don't expect when you're opening jars even when i'm just walking around if i bump it on something there's a bone there that was used to taking contact my fourth metacarpal wasn't used to taking contact it used to hurt it still does a little bit but actually my bone has remodeled right over the lat over a couple years the geometry the mechanics of that bone change to address the new circumstances so the idea that somehow it's only our brain that's adapting or evolving is not right maybe sticking on evolution for a bit because it's tended to create some interesting things uh by peter walking do you uh why the heck did evolution give us i think we're are we the only mammals that walk on two feet no i mean there's a bunch of animals that do it a bit there's a i think we are the most successful bypass i think some uh i think i read somewhere that um the reason the you know evolution made us walk on two feet is because uh there's an advantage to being able to carry food back to the tribe or something like that so like you can carry it's kind of this communal cooperative thing so like to carry stuff back to um to a place of shelter and so on to share with others um do you understand at all the value of uh walking on two feet from both a robotics and a human perspective yeah there are some great books written about evolution of walking evolution of the human body i think it's easy though to make bad evolutionary arguments sure most of them are probably bad but what else can we do i mean i think um a lot of what dominated our evolution probably was not the things that worked well sort of in the steady state um you know when things are when things are good but but uh for instance people talk about what we should eat now because our ancestors were meat eaters or or whatever oh yeah i love that yeah but probably you know the reason that one pre uh pre-homo sapien species versus another survived was not because of whether they ate well uh when there was lots of food but when the ice age came you know probably one of them happened to be in the wrong place one of them happened to forage a food that was okay even even when the glaciers came or something like that i mean there's a million variables that contributed and we can't and our actually the amount of information we're working with and telling these stories these evolutionary stories is uh is very little so yeah just like you said it seems like if we if we study history it seems like history turns on like these little events that uh that otherwise would seem meaningless but in the grant like when you in retrospect were turning points absolutely and that that's probably how like somebody got hit in the head with a rock because somebody slept with the wrong person back in the cave days and somebody get angry and that turned uh you know warring tribes combined with the environment all those millions of things and the meat eating which i get a lot of criticism because i i don't know um i don't know what your dietary processes are like but these days i been eating only meat which is um there's a large community people who say yeah probably make evolutionary arguments and say you do a great job there's probably an even larger community of people including my mom who says it's deeply unhealthy it's wrong but i just feel good doing it but you're right these evolutionary arguments can be flawed but is there anything interesting to pull out for um there's a great book by the way um look a series of books by nicholas taleb about fooled by randomness and black swan um highly recommend them but yeah they make the point nicely that probably it was a few random events that yes maybe it was someone getting hit by a rock as you say uh that said do you think i don't know how to ask this question or how to talk about this but there's something elegant and beautiful about moving on two feet obviously biased because i'm human but from a robotics perspective too you work with robots on two feet is it um is it all useful to build robots that are on two feet as opposed to four is there something useful about it the most um i mean the reason i spent a long time working on bipedal walking was because it was hard and it was um it challenged control theory in ways that i thought were important um i wouldn't have ever tried to convince you that you should start a company around bipeds or something like this there are people that make pretty compelling arguments right i think the most compelling one is that the world is built for the human form and if you want a robot to work in the world we have today then you know having a human form is a pretty good way to go there there are places that a biped can go that would be hard for other form factors to go even natural places but um you know at some point in the long run we'll be building our environments for our robots probably and so maybe that argument falls aside so you famously run barefoot do you still run barefoot i still run barefoot that's so awesome much to my wife's chagrin do you want to make an evolutionary argument for why running barefoot is advantageous um what have you learned about um human and robot movement in general from running barefoot human or robot and or well you know it happened the other way right so i was studying walking robots and i was there's a great conference called the dynamic walking conference where it brings together both the biomechanics community and the walking robots community and so i've been going to this for years and hearing talks by people who study barefoot running and other the mechanics of running so i i did eventually read born to run most people read born to run in the first thing right the other thing i had going for me is actually that i i wouldn't i wasn't a runner before and i learned to run after i had learned about barefoot running i mean started running longer distances so i didn't have to unlearn and i'm definitely um i'm a big fan of it for me but i'm not gonna i tend to not try to convince other people there's people who run beautifully with shoes on and that's good um but here's why it makes sense for me um it's all about the long-term game right so i think it's just too easy to run 10 miles feel pretty good and then you get home at night and you realize uh my knees hurt i did something wrong right um if you take your shoes off then if you hit hard with your foot at all um then it hurts you don't like run 10 miles and then and then realize you've done something some damage you have immediate feedback telling you that you've done something that's that's maybe sub-optimal and you change your gait i mean it's even subconscious if i right now having run many miles barefoot if i put a shoe on my gate changes in a way that i think is not as good um so so it makes me land softer and i think my my goals for running are to do it for as long as i can into old age um not to win any races and so for me this is a you know a way to protect myself yeah i think um first of all i've tried running barefoot many years ago uh probably the other way just just just uh reading born to run but just to understand because i felt like i couldn't put in the miles that i wanted to and it feels like running for me and i think for a lot of people was one of those activities that we do often and never really try to learn to do correctly like it's funny there's so many activities we do every day like brushing our teeth right i think a lot of us at least me probably have never deeply studied how to properly brush my teeth right or wash as now with a pandemic or how to properly wash our hands or do it every day but we haven't really studied like am i doing this correctly but running felt like one of those things it was absurd not to study how to do correctly because it's the source of so much pain and suffering like i hate running but i do it i do it because i hate it but it i feel good afterwards but i think it feels like you need to learn how to do it properly so that's where barefoot running came in and then i quickly realized that my gait was completely wrong i was taking huge like steps and landing hard on the heel all those elements and so yeah from that i actually learned to take really small steps look i already forgot the number but i feel like it was 180 a minute or something like that and i remember i was uh i actually just took songs that are 180 beats per minute and then like tried to run at that beat uh just to teach myself it took took a long time and i feel like uh after a while you learn to run you adjust it properly without going all the way to barefoot but i feel like barefoot is the legit way to do it i mean i think a lot of people would be really curious about it can you if they're interested in trying what would you how would you recommend a start or try or explore slowly that's the biggest thing people do is they are excellent runners and they're used to running long distances or running fast and they take their shoes off and they hurt themselves instantly trying to do something that they were used to doing i i think i lucked out in the sense that i i couldn't run very far when i first started trying and i run with minimal shoes too i mean i will you know bring along a pair of actually like aqua socks or something like this i can just slip on or running sandals i've tried all of them what's the difference between a minimal shoe and nothing at all what's like feeling wise what does it feel like there is i mean i noticed my gate changing right so um i mean your your foot has as many muscles and sensors as your hand does right sensors ooh okay and we do amazing things with our hands and we stick our foot in a big solid shoe right so there's i think you know when you're barefoot you're you're just giving yourself more proprioception and that's why you're more aware of some of the gait flaws and stuff like this now you have less protection too so um rocks and stuff i mean yeah so so i think people are who are afraid of barefoot running they're worried about getting cuts or getting stepping on rocks first of all even if that was a concern i think those are all like uh very short-term you know if i get a scratch or something it'll heal in a week if i blow out my knees i'm done running forever so i will trade the short term for the long term anytime but even then you know this again to my wife's chagrin um your feet get tough right and uh uh cows okay yeah i can run over almost anything now i mean what uh maybe can you talk about is there tin like is there tips or tricks that you have uh suggestions about like if i wanted to try it you know there is a good book actually uh there's probably more good books since i read them but uh ken bob barefoot ken bob saxton um he's an interesting guy but i think his book captured uh the right way to describe running barefoot running to somebody better than any other i've seen so you run pretty good distances and you bike and is is there um you know if we talk about bucket list items is there something crazy on your bucket list athletically that you hope to do one day i mean my commute is already a little crazy um what are we talking about here what what uh what distance are we talking about well i live about 12 miles from mit but you can find lots of different ways to get there so i mean i've run there for a long many years a bike there um blaze yeah but normally i would try to run in and then bike home bike in run home but you have run there and back before sure barefoot yeah uh yeah or with minimal shoes or whatever that 12 12 times two yeah okay it became kind of a game of how can i get to work i've rollerbladed i've done all kinds of weird stuff but uh my favorite one these days is i've been taking the charles river to work so i can put in a little row boat not so far from my house but the charles river takes a long way to get to mit so i can spend a long time getting there and it's you know it's not about i don't know it's just about uh i've had people ask me how can you justify taking that time uh but for me it's just a magical time to think to compress decompress um you know especially i'll wake up do a lot of work in the morning and then i kind of have to just let that settle before i i'm ready for all my meetings and then on the way home it's a great time to load it sort of let that settle so you you lead a like a a large group of people i mean you're is there days where you're like oh shit i gotta get to work in an hour like i i mean uh is is there is there a tension there where and like if we look at the grand scheme of things just like you said long term that meeting probably doesn't matter like you can always say i'll just i'll run and let the meeting happen how it happens like what uh how do you that zen how do you uh what do you do with that tension between the real world saying urgently you need to be there this is important everything is melting down how we're going to fix this robot there's this uh critical meeting and then there's this the zen beauty of just running the simplicity of it you along with nature what do you do with that i would say i'm not a fast runner particularly probably my fastest splits ever was when i had to get to daycare on time because they were going to charge me you know some some dollar per minute that i was late uh i've run some fast splits to daycare but that those times are passed now i think work you can find a work-life balance in that way i think you just have to i think i am better at work because i take time to think on the way in so i plan my day around it and i i rarely feel that those are really in at odds so what the bucket list item if we're talking 12 times 2 or approaching a marathon uh what uh have you run an ultra marathon before do you do races is there what's uh to win i'm not gonna like take a dinghy across the atlantic or something if that's what you want but uh uh but if someone does and wants to write a book i would totally read it because i'm a sucker for that kind of thing no i do have some fun things that i will try you know i like to when i travel i almost always bike to logan airport and fold up a little folding bike on and then take it with me and bike to wherever i'm going and i've it's taken me or i'll take a stand-up paddleboard these days on the airplane and then i'll try to paddle around where i'm going or whatever and i've done some crazy things but um but not for the you know i've i now talk i don't know if you know who david goggins is by any chance not well but yeah but i i talk to him now every day so he's the person who made me uh do this stupid challenge so he he's insane and he does things for the purpose in in the best kind of way he does things like for the explicit purpose of suffering like he picks the thing that like whatever he thinks he can do he does more uh so is that do you have that thing in you or you uh i think it's become the opposite it's uh so you're like that dynamical system that the walker the efficient uh yeah it's uh leave no pain right you should end feeling better than you started okay but um it's mostly i think and kovit has tested this because i've lost my commute i think i'm perfectly happy walking around uh around town with my wife and uh kids if they could get them to go and it's more about just getting outside and getting away from the keyboard for some time just to let things compress let's go into robotics a little bit what to use the most beautiful idea in robotics whether we're talking about control or whether we're talking about optimization the math side of things or the engineering side of things or the philosophical side of things i think i've been lucky to experience something that not so many roboticists have experienced which is to hang out with some really amazing control theorists and uh the clarity of thought that some of the more mathematical control theory can bring to even very complex messy looking problems is really it really had a big impact on me and and uh i had a day even like just a couple weeks ago where i had spent the day on a zoom robotics conference having great conversations with lots of people i felt really good about the ideas that were flowing and and the like and then i had a you know late afternoon meeting with uh one of my favorite control theorists and um and we went from these from these abstract discussions about maybes and what-ifs and and what a great idea to these super precise statements about systems that aren't that much more simple or or abstract than the ones i care about deeply and the contrast of that is um i don't know it really gets me i think people underestimate um maybe the power of clear thinking and so for instance deep learning is amazing um i use it heavily in our work i think it's changed the world unquestionable it makes it easy to get things to work without thinking as critically about it so i think one of the challenges as an educator is to think about how do we make sure people get a taste of the more rigorous thinking that i think goes along uh with with some different approaches yeah so that's really interesting so understanding like the fundamentals the first principles of the of the the the problem where in this case is mechanics like how a thing moves how thing behaves like all the forces involved like really getting a deep understanding of that i mean from physics the first principle thing come from physics and here it's literally physics yeah and this applies in deep learning this applies to um not just i mean it applies so cleanly in in robotics but it also applies to just in any data set i find this true i mean driving as well there's a lot of folks in it that work on autonomous vehicles that don't study driving like deeply i i might be coming a little bit from the psychology side but i remember i spent a ridiculous number of hours at lunch at this like lawn chair and i would sit somewhere somewhere on mit's campus there's a few interesting intersections and we just watched people cross so we were studying um pedestrian behavior and i felt like as you record a lot of video to try and just the computer vision extracts their movements how they move their head and so on but like every time i felt like i didn't understand enough i i just i felt like i wasn't understanding what how are people signaling to each other what are they thinking how cognizant are they of their fear of death like what we like what's the game what's the underlying game theory here what are what are the the the incentives and then i finally found a live stream uh of an intersection that's like high def that i just i would watch so i wouldn't have to sit out there but that's interesting so like that's tough that's a tough example because i mean the learning humans are involved not just because human but i think um the learning mantra is the basically the statistics of the data will tell me things i need to know right and you know for the example you gave of all the nuances of um you know eye contact or hand gestures or whatever that are happening for these subtle interactions between pedestrians and traffic right maybe the data will tell us they'll tell that story i may be even i uh one level more meta than than what you're saying for a particular problem i think it might be the case that data should tell us the story but i think there's a rigorous thinking that is just an essential skill for a mathematician or an engineer that um i just don't want to lose it yes there are there are certainly super rigorous um rigorous control oh sorry machine learning people i just think deep learning makes it so easy to do some things that um our next generation are um not immediately rewarded for going through some of the more rigorous approaches and i wonder where that takes us i just well i'm actually optimistic about it i just want to do my part to try to steer that rigorous thinking so there's like two questions i want to ask do you have sort of a good example of rigorous thinking where it's easy to get lazy and not do the rigorous thinking and the other question i have is like do you have advice of um how to practice rigorous thinking and um you know in all the computer science disciplines that we've mentioned yeah i mean there are times where problems that can be solved with well-known mature methods could also be solved with with a deep learning approach and there's an argument that you must use learning even for the parts we already think we know because if the human has touched it then you've if you've biased the system and you've suddenly put a bottleneck in there that is your own mental model but something like inverting a matrix you know i i think we know how to do that pretty well even if it's a pretty big matrix and we understand that pretty well and you could train a deep network to do it but you shouldn't probably so so in that sense rigorous thinking is uh understanding the the scope and the limitations of the mess of the methods that we have like how to use the tools of mathematics properly yeah i think you know taking a class on analysis is all i'm sort of arguing is to take take a chance to stop and and force yourself to think rigorously about even you know the rational numbers or something you know it doesn't have to be the end-all problem but that exercise of clear thinking i think uh goes a long way and i just want to make sure we we keep preaching don't lose it yeah but do you think uh when you're doing like rigorous thinking or like maybe uh trying to write down equations or sort of explicitly like formally describe a system do you think we naturally simplify things too much is that a danger you run into like uh in order to be able to understand something about the system mathematically we uh make it too much of a toy example but i think that's the good stuff right um that's how you understand the fundamentals i think so i think maybe even that's a key to intelligence or something but i mean okay what if newton and galileo had deep learning and and they had done a bunch of experiments and they told the world here's your weights of your neural network i've we've solved the problem yeah you know where would we be today i don't i don't think we'd be as far as we as we are there's something to be said about having a the simplest explanation for a phenomenon so i don't doubt that we can train neural networks to predict even physical you know f equals m a type equations but um i maybe i want another newton to come along because i think there's more to do in terms of coming up with the simple models for more complicated tasks yeah uh let's not offend the ai systems from 50 years from now that are listening to this that are probably better at might be better coming up with f equals m a equations themselves so sorry i actually think um learning is probably a route to achieving this but the representation matters right and i think having a function that takes my inputs to outputs that is arbitrarily complex may not be the end goal i think there's still you know the most simple or parsimonious explanation for the data simple doesn't mean low dimensional that's one thing i think that we've a lesson that we've learned so you know a standard way to do model reduction or system identification and controls is to the typical formulation is that you try to find the minimal state dimension realization of a system that hits some error bounds or something like that and that's maybe not i think we're we're learning that that was that the state dimension is not the right metric of complexity of complexity but for me i think a lot about contact the mechanics of contact the robot hand is picking up an object or something and when i write down the equations of motion for that they're they look incredibly complex not because actually not so much because of the dynamics of the hand when it's moving but it's just the interactions and when they turn on and off right so having a high dimensional you know but simple description of what's happening out here is fine but if when i actually start touching i write down a different dynamical system for every polygon on my robot hand and every polygon on the object whether it's in contact or not with all the combinatorics that explodes there then that's too complex so i need to somehow summarize that with a more intuitive physics way of thinking and yeah i'm very optimistic that machine learning will get us there first of all i mean i'll probably do it in the introduction but you're one of the great robotics people at mit you're a professor at mit you've teach them a lot of amazing courses you run a large group and you have a important history for mit i think as being a part of the darpa robotics challenge can you maybe first say what is the dark robotics challenge and then tell your story around it your journey with it yeah sure um so the darpa robotics challenge it came on the tales of the darpa grand challenge and darpa urban challenge which were the challenges that brought us put a spotlight on self-driving cars guild pratt was at darpa and pitched a new challenge that involved disaster response it didn't explicitly require humanoids although humanoids came into the picture this happened shortly after the fukushima disaster in japan and our challenge was motivated roughly by that because that was a case where if we had had robots that were ready to be sent in there's a chance that we could have averted disaster and certainly after the um in the disaster response there were times we would love we would have loved to have sent robots in so in practice what we ended up with was a grand challenge a darpa robotics challenge where boston dynamics was was to make humanoid robots people like me and the the amazing team at mit were competing first in a simulation challenge to try to be one of the ones that wins the right to work on one of the uh the boston dynamics humanoids in order to compete in the the final challenge which was a physical challenge and at that point it was already so it was decided as humanoid robots there were there were two tracks there you could enter as a hardware team where you brought your own robot or you could enter through the virtual robotics challenge as a software team that would try to win the right to use one of the boston dynamics robots which are called atlas atlas humanoid robots yeah it was a 400-pound marvel but a you know pretty big scary looking robot expensive too expensive at the time yeah okay so uh i mean how did you feel at the prospect of this kind of challenge i mean it seems you know autonomous vehicles yeah i guess that sounds hard but uh not really from a robotics perspective it's like didn't they do in the 80s is the kind of feeling i would have uh like when you first look at the problem it's on wheels but like humanoid robots that sounds really hard so what like what are your the psychologically speaking what were you feeling excited scared why the heck did you get yourself involved in this kind of messy challenge we didn't really know for sure what we were signing up for in the sense that you could have something that as it was described in the call for participation that could have put a huge emphasis on the dynamics of walking and not falling down and walking over rough terrain or the same description because the robot had to go into this disaster area and turn valves and and pick up a drill cut the hole through a wall it had to do some interesting things the challenge could have really highlighted perception and autonomous planning or it ended up that you know locomoting over a complex terrain played a pretty big role in the competition so and the degree of autonomy wasn't clear the decree of autonomy was always a central part of the discussion so um what wasn't clear was how we would be able how far we'd be able to get with it so the idea was always that you want semi-autonomy that you want the robot to have enough compute that you can have a degraded network link to a human and so the same way you we had degraded networks at many natural disasters you'd send your robot in you'd be able to get a few bits back and forth but you don't get to have enough potentially to fully uh operate the robot in every joint of the robot so and then the question was and the gamesmanship of the organizers was to figure out what we're capable of push us as far as we could so that um it would differentiate the teams that put more autonomy on the robot and had a few clicks and just said go there do this go there do this versus someone who's picking every footstep or something like that so what were some memories painful triumphant from the experience like what was that journey maybe if you can dig in a little deeper maybe even on the technical side and the team side that that whole process of um from the early idea stages to actually competing i mean this was a defining experience for me i i it was it came at the right time for me in my career i had gotten tenure before i was do a sabbatical and most people do something you know relaxing and restorative for a sabbatical so you got tenure before the the before this yeah yeah yeah it was a good time for me i had i had we had a bunch of algorithms that we were very happy with we wanted to see how far we could push them and this was a chance to really test our metal to do more proper software engineering the team we all just worked our butts off we you know we're in that lab almost all the time okay so i mean there were some of course high highs and low lows throughout that anytime you're you know not sleeping and devoting your life to a 400 pound humanoid um i remember actually one funny moment where we're all super tired and so atlas had to walk across cinder blocks that was one of the obstacles and i remember atlas was powered down and hanging limp you know on the on its harness and the the humans were there like laying you know picking up and laying the brick down so that the robot could walk over it and i thought what is wrong with this you know we've got a robot just watching us do all the manual labor so that it can take its little um stroll across the train but i mean even the even the virtual robotics challenge was was super nerve-wracking and dramatic i remember um so so we were using gazebo as a simulator uh on the cloud there was all these interesting challenges i think um the investment that that osrs fc whatever they were called at that time brian gerkey's team at open source robotics um they were pushing on the capabilities of gazebo in order to scale it to the complexity of these challenges so um you know up to the virtual competition so the virtual competition was you will sign on at a certain time and we'll have a network connection to another machine on the cloud that is running the simulator of your robot and your controller will run on this this controller this computer and and the physics will run on the other and you have to connect now um the physics they wanted it to run at real-time rates because there was an element of human interaction um and humans could if you do want to tell the op it works way better if it's at frame rate oh cool but it was very hard to simulate these comple these complex scenes at real-time rate so right up to like days before the competition the the simulator wasn't quite at real time rate and that was great for me because my controller was solving a big pretty big optimization problem and it wasn't quite at real-time rate so i was fine i was keeping up with the simulator we were both running at about 0.7 and i remember getting this email and by the way the perception folks on our team hated that that they knew that if my controller was too slow the robot was going to fall down and and you know no matter how good their perception system was if i can't make my controller fast anyways we get this email like three days before the virtual competition well you know it's for all the marbles we're going to either get a humanoid robot or we're not and we get an email saying good news we made the robot does the simulator faster it's now one point and uh yeah we're i was just like oh man what are we going to do here so yeah that came in late at night for me um a few days ahead a few days ahead i went over there was it happened that frank permentor who's a a very very sharp he's a he was a student at the time working on optimization was he was still in lab uh frank we need to make this quadratic programming solver faster not like a little faster it's actually you know um and we wrote a new solver for that qp together that night and you start terrifying so there's a really hard optimization problem that you're constantly solving you didn't make the optimization problem simpler you you wrote any solver so um i mean your observation is almost spot on well what we did was what everybody i mean people know how to do this but we had not yet done this idea of warm starting so we are solving a big optimization problem at every time step but if you're running fast enough the optimization problem you're solving on the last time step is pretty similar to the optimization you're going to solve with the next we had course had told our commercial solver to use warm starting but even the interface to that commercial solver was causing us these delays so what we did was we basically wrote we called it fastqp at the time we wrote a very lightweight very fast layer which would basically check if nearby solutions to the quadratic program were which were very easily checked uh could stabilize the robot and if they couldn't we would fall back to the solver you couldn't really test this well right um or like i mean so we always knew that if we fell back if we it got to the point where if for some reason things slowed down and we fell back to the original solver the robot would actually literally fall down um so it was it was a harrowing sort of edge we're ledge we were sort of on but i mean actually like the the 400 pound humor could come crashing to the ground if you if you if your solver is not fast enough but you know that we have lots of good experiences so can i ask you a weird question i i get um about idea of hard work so um actually people like students of yours that i've interacted with and just and robotics people in general but they uh they have moments at moments have worked harder than uh most people i know in terms of if you look at different disciplines of how hard people work but they're also like the happiest like just like i don't know um it's the same thing with like running people that push themselves to like the limit they all also seem to be like the most like full of life somehow uh and i get often criticized like you're not getting enough sleep what are you doing to your body blah blah blah like this kind of stuff and i usually just kind of respond like i'm i'm doing what i love i'm passionate about i love it i feel like it's it's invigorating i actually think i don't think the lack of sleep is what hurts you i think what hurts you is uh stress and lack of doing things that you're passionate about but in this world yeah i mean can you comment about uh why the heck robotics people are uh willing to push themselves to that degree is there value in that and why are they so happy i think i think you got it right i mean i think the causality is not that we work hard and i think other disciplines work very hard too but it's i don't think it's that we work hard and therefore we are happy i think we found something that we're truly passionate about it makes us very happy and then we get a little involved with it and spend a lot of time on it um what a luxury to have something that you want to spend all your time on right we could talk about this for many hours but maybe if we could pick is there something on the technical side on the approach you took that's interesting that turned out to be a terrible failure or a success that you carry into your work today about all the different ideas that were involved in um making whether in the in the simulation or in the in the real world making this semi-autonomous system work i mean it really did teach me something fundamental about what it's going to take to get robustness out of a system of this complexity i would say the darpa challenge really was foundational in my thinking i think the autonomous driving community thinks about this i think lots of people thinking about safety critical systems that might have machine learning in the loop are thinking about these questions for me the darpa challenge was the moment where i realized you know we've spent every waking minute running this robot and again the in for the physical competition days before the competition we saw the robot fall down in a way it had never fallen down before i thought you know how could we have found that you know we only have one robot it's running almost all the time we just didn't have enough hours in the day to test that robot something has to change right and then i think that i mean i would say that the team that won was was from kaist was the team that had two robots and was able to do not only incredible engineering just absolutely top-rate engineering but also they were able to test at a rate and um discipline that we didn't keep up with what does testing look like what are we talking about here like what's what's a a loop of test like a from start to finish what is a loop of testing yeah i mean i think there's a whole philosophy to testing there's the unit tests and you can do that on a hardware you can do that in a small piece of code you write one function you should write a test that that checks that function's input outputs you should also write an integration test at the other extreme of of running the whole system together you know where that that try to turn on all the different functions that you've you think are correct it's much harder to write the specifications for a system level test especially if that system is as complicated as a humanoid robot but the philosophy is sort of the same i'm the real robot it's it's no different but on a real robot it's impossible to run the same experiment twice so if you if you see a failure you hope you caught something in the logs that tell you what happened but you'd probably never be able to run exactly that experiment again and right now i think our philosophy is just basically monte carlo estimation is just run as many experiments as we can maybe try to set up the environment to to make the things we are worried about happen as often as possible but really we're relying on somewhat random search in order to test maybe that's all we'll ever be able to but i think uh you know because there's an argument that the things that will get you are the the things that are really nuanced in the world and it'd be very hard to for instance put back in a simulation yeah the i guess the edge cases what was the the hardest thing like so you said walking over rough terrain like the just taking footsteps i mean people there's it's so dramatic and painful in a certain kind of way to watch these videos from the drc of robots falling yep it's just so heartbreaking i don't know maybe it's because for me at least we anthropomorphize the robot um of course there's everything funny for some reason like humans falling is funny uh for i don't it's some dark reason i'm not sure why it is so but it's also like tragic and painful and uh so speaking of which i mean what what made the robots fall and fail uh in your view so i can tell you exactly what happened on our we i contributed one of those our team contributed one of those spectacular falls every one of those falls the has a complicated story i mean one time the power effectively went out on the robot because it had been sitting at the door waiting for a green light to be able to proceed and its batteries you know and therefore it just fell backwards and smashed its head across ground and it was hilarious but it wasn't because of bad software right um but for ours so the hardest part of the challenge the hardest task in my view was getting out of the polaris it was actually relatively easy to drive the polaris we have can you tell the stars no the story of the car [Laughter] people should watch this video i mean the the the thing you've come up with is just brilliant but uh anyway sorry what's uh yeah we we kind of joke we call it the big robot little car problem because um somehow the race organizers decided to give us a 400 pound humanoid and they also provided the vehicle which was a little polaris and the robot didn't really fit in the car so you couldn't drive the car with your feet under the steering column we actually had to straddle the the main column of the uh and have basically one foot in the passenger seat one foot in the driver's seat and then drive with our left hand but the hard part was we had to then park the car get out of the car uh it didn't have a door that was okay but it's just uh getting up from crouched from sitting when you're in this very constrained environment uh first of all i remember after watching those videos i was much more cognizant of how hard is it it is for me to get in and out of the car and out of the car especially like it's actually a really difficult control problem yeah and i i'm very cognizant of it when i'm like injured for whatever reason it's really hard yeah so so how did you how did you approach so so we had a you know you think of um nasa's operations and they have these checklists you know pre-launch checklists and they're like we weren't far off from that we had this big checklist and on the first day of the competition we were running down our checklist and one of the things we had to do we had to turn off the controller the piece of software that was running that would drive the left foot of the robot in order to accelerate on the gas and then we turned on our balancing controller and the nerves jitters of the first day of the competition someone forgot to check that box and turn that controller off so um we used a lot of motion planning to figure out a a sort of configuration of the robot that we get up and and over we relied heavily on our balancing controller and and basically there was when the robot was in one of its most precarious you know sort of configurations trying to sneak its big leg out of the out of the side the other controller that thought it was still driving told its left foot to go like this and uh and that wasn't good um but but it turned disastrous for us because um what happened was a little bit of push here actually if you we have videos of us you know running into the robot with a 10-foot pole and it kind of will recover but this is a case where there's no space to recover so a lot of our secondary balancing mechanisms about like take a step to recover they were all disabled because we were in the car and there's no place to step so we're relying on our just lowest level reflexes and even then i think just hitting the foot on the seat on the on the floor we probably could have recovered from it but the thing that was bad that happened is when we did that and we jostled a little bit the tailbone of our robot hat was only a little off the seat it hit the seat and the other foot came off the ground just a little bit and nothing in our plans had ever told us what to do if your butt's on the seat and your feet are in the air feeding air and then the thing is once you get off the script things can go very wrong because even our state estimation our system that was trying to collect all the data from the sensors and understand what's happening with the robot it didn't know about this situation so it was predicting things that were just wrong and then we did a violent shake and fell off in our uh face first on out of the robot but like into the destination that's true we fell in we got our point for egress but so uh is there any hope for that's interesting is there any hope for uh atlas to be able to do something when it's just on its butt and feet in the air absolutely so you can no so that's um that is one of the big challenges and i think it's still true um you know boston dynamics and and um animal and there's this incredible work on on legged robots happening around the world most of them still are are very good at the case where you're making contact with the world at your feet and they have typically point feet relatively they're balls on their feet for instance if that if those robots get in a situation where the elbow hits the wall or something like this that's a pretty different situation now they have layers of mechanisms that will make i think the the more mature solutions have have ways in which the controller won't do stupid things but a human for instance is able to leverage incidental contact in order to accomplish a goal in fact i might if you push me i might actually put my hand out and make a new brand new contact the feet of the robot are doing this on quadrupeds but we mostly in robotics are afraid of contact on the rest of our body which is crazy there's this whole field of motion planning collision-free motion planning and we write very complex algorithms so that the robot can dance around and make sure it doesn't touch the world um so people are just afraid of contact because contact is seen as a difficult it's still a difficult control problem and sensing problem now you're a serious person uh i'm a little bit of an idiot and i'm going to ask you some dumb questions uh so i do uh i do martial arts uh so like jiu jitsu there's wrestled my whole life so let me let me ask the question um you know like whenever people learn that i do any kind of ai or like i mention robots and things like that they say when am i gonna have robots that um you know that can win in a wrestling match or in a fight against a human so we just mentioned sitting on your butt if you in the air that's a common position jiu jitsu when you're on the ground you're when you're down opponent um like what how difficult do you think is the problem and when will we have a robot that can defeat a human in a wrestling match and we're talking about a lot like if i don't know if you're familiar with wrestling but essentially um not very it's basically the art of contact it's like it's because you're you're you're picking contact points and then using like leverage like to uh off balance to to trick people like you uh make them feel like you're doing one thing and then they they change their balance and then you uh switch what you're doing and then results in a throw or whatever so like it's basically the art of multiple contacts so awesome that's a nice description of it so there's also an opponent in there right so so if very dynamic right if you are wrestling a human and uh are in a game theoretic situation with a human that's still hard but just to speak to the you know quickly reasoning about contact part of it for instance yeah maybe even throwing the game theory out of it almost like uh yeah almost like a non-dynamic opponent right there's reasons to be optimistic but i think our best understanding of those problems are still pretty hard um i have been increasingly focused on manipulation partly where that's a case where the contact has to be much more rich and there are some really impressive examples of of deep learning policies controllers that that can appear to do good things through contact we've even got new examples of of you know deep learning models of predicting what's going to happen to objects as they go through contact but i think the challenge you just offered there still eludes us right the ability to make a decision based on those models quickly you know i have to think though it's hard for humans too when you get that complicated i think probably you had maybe a slow-motion version of where you learn the basic skills and you've probably gotten better at it and and um there's there's much more subtlety but it might still be hard to actually you know really on the fly take a you know model of your humanoid and figure out how to how to plan the optimal sequence that might be a problem we never solve well the rapid the i mean one of the most amazing things to me about the we could talk about martial arts uh we could also talk about dancing it doesn't really matter too human i think it's the most interesting study of contact it's not even the dynamic element of it it's the like when you get good at it it's so effortless like i can just i'm very cognizant of the entirety of the learning process being essentially like learning how to move my body in a way that i could throw very large weights around effortlessly like and and i can feel the learning like i'm a huge believer in drilling of techniques and you can just like feel your i don't you're not feeling you're feeling um sorry you're learning it intellectually a little bit but a lot of it is the body learning it somehow uh like instinctually and whatever that learning is that's really i'm not even sure if that's um equivalent to uh like a deep learning learning a controller i think it's something more it feels like there's a lot of distributed learning going on yeah i think there's hierarchy and composition yeah um probably in the systems that we don't capture very well yet uh you have layers of control systems you have reflexes at the bottom layer and you have a you know a system that's capable of planning a vacation to some distant country which is probably you probably don't have a controller a policy for every possible destination you'll ever pick right um but there's something magical in the in between and how do you go from these low-level feedback loops to something that feels like a pretty complex set of outcomes you know my guess is i think i think there's evidence that you can plan at some of these levels right so uh josh tenenbaum just showed it in his talk the other day he's got a game he likes to talk about i think he calls it the pick 3 game or something where he puts a bunch of clutter down in front of a person and he says okay pick three objects and it might be a telephone or a shoe or a kleenex box or whatever and apparently you pick three items and then you pick he says okay pick the first one up with your right hand the second one up with your left hand now using those objects those now as tools pick up the third object right so that's down at the level of of physics and mechanics and contact mechanics that that i think we do learning we do have policies for we do control for almost feedback but somehow we're able to still i mean i've never picked up a telephone with a shoe and a water bottle before and somehow and it takes me a little longer to do that the first time but most of the time we can sort of figure that out so yeah i think the amazing thing is this ability to be flexible with our models plan when we need to use our well-oiled controllers when we don't when we're in familiar territory um having models i think the the other thing you just said was something about i think your awareness of what's happening is even changing as you as you get as you improve your expertise right so maybe you have a very approximate model of the mechanics to begin with and as you gain expertise you get a more refined version of that model you're aware of muscles or balance components that you just weren't even aware of before so how do you scaffold that yeah plus the fear of injury the ambition of goals of excelling and uh fear of mortality let's see what else is in there as the motivations uh overinflated ego in the beginning uh like and then a crash of confidence in the middle all of those seem to be essential for the learning process and also and if all that's good then you're probably optimizing energy efficiency yeah right so we have to get that right uh so um you know there was this idea that you would have uh robots play soccer better than human players by 2050 that was the goal uh world basically was the goal to beat world champion team to become a world cup be like a world cup right level team so are we gonna see that first or um a robot if you're familiar there's an organization called ufc for mixed martial arts are we going to see a world cup championship soccer team out of robots or a ufc champion mixed martial artist uh that's a robot i mean it's very hard to to say one thing is a harder one some problems harder than the other what probably matters is um who who who started the organization that that i mean i think robocup has a pretty serious following and there is a history now of people playing that game learning about that game building robots to play that game building increasingly more human robots it's got momentum and so if you want to uh to have mixed martial arts compete you better start your start your organization now right um i think almost independent of which problem is technically harder because they're both hard and they're both different that's a good point i mean those videos are just hilarious like uh especially the humanoid robots trying to um trying to play soccer i mean they're kind of terrible right now i mean i guess there is robo sumo wrestling there's like the robo one competitions um where they do have these robots that go on the table and basically fight so maybe i'm wrong maybe first of all do you have a year in mind for uh robocup just from a robotics perspective it seems like a super exciting possibility that um like in the physical space this is what's interesting i think the world is captivated i think it's really exciting it's um it inspires a huge number of people when a machine beats a human at a game that humans are really damn good at so you're talking about chess and go but that's in the in the world of uh digital i don't think machines have beat humans at a game in the physical space yet but that would be just you have to make the rules very carefully right i mean if if atlas kicked me in the shins i'm down and uh you know and and game over so there's you know it's it's very subtle on yeah i think that's fair i think the fighting one is a weird one yeah because uh you're talking about a machine that's much stronger than you but yeah in terms of soccer basketball all those kinds of soccer right i mean as soon as there's contact or whatever and there's there are some things that the robot will do better i think if you really set yourself up to try to see could robots win the game of soccer as the rules were written the right thing for the robot to do is to play very differently than a human would play it's you're not going to get you know the perfect soccer player robot you're going to get something that exploits the rules exploits its super actuators it's super low bandwidth um you know feedback loops or whatever and it's going to play the game differently than you want it to play yeah um and it i bet there's ways there's i bet there's loopholes right we saw that in the in the darpa challenge that that it's very hard to write a set of rules that someone can't find uh a way to exploit let me ask another ridiculous question i promise i think this might be the last ridiculous question but i doubt it i i aspire to ask as many uh ridiculous questions of uh of a brilliant mit professor okay uh i don't know if you've seen the black mirror it's funny i i never watched the episode i know when it happened though because i gave a talk to some mit faculty one day on a unassuming you know monday or whatever i was telling about the state of robotics and i showed some video of from boston dynamics of the quadruped spot at the time it was the early version of spot and there was a look of horror that went across the room and i said what you know i've shown videos like this a lot of times what happened and it turns out that this video had gone yeah this black mirror episode had changed the way people watched um yeah the videos i was putting out the way they see these kinds of robots so i talked to so many people who are just terrified because of that episode probably of these kinds of robots they i almost want to say they almost kind of like enjoy being terrified i don't even know what it is about human psychology that kind of imagine doomsday the destruction of the universe or our society and kind of like enjoy being afraid um i don't want to simplify it but it feels like they talk about it so often it almost there does seem to be an addictive quality to it um i talked to a guy that says this a guy named joe rogan who's kind of the flag bearer for being terrified of these robots uh do you have a two questions one do you have an understanding of why people are afraid of robots and the second question is uh in black mirror just to tell you the episode i don't even remember it that much anymore but these robots i think they can shoot like a pellet or something they basically have it's basically a spot with a gun and um how far are we away from having robots that go rogue like that you know basically spot that goes rogue for some reason and somehow finds a gun right so i mean i'm i'm not a psychologist um i think i don't know exactly why people react the way they do i think i think we have to be careful about the way robots influence our society and the like i think that's something that's a responsibility that roboticists need to embrace i don't think robots are going to come after me with a kitchen knife or a pellet gun right away and i mean if they were programmed in such a way but i used to joke with atlas that all i had to do was run for five minutes and it's battery would run out but uh actually they've got a very big battery in there by the end so it was over an hour um i think the fear is a bit cultural though because i i mean you notice that like i think in my age in the u.s we grew up watching terminator right if i had grown up at the same time in japan i probably would have been watching astro boy and there's a very different reaction to robots in different countries right so i don't know if it's a human innate fear of metal marvels or if it's something that we've done to ourselves with our sci-fi yeah the stories we tell ourselves through uh through movies through just uh through popular media but if if i were to tell you know if if you were my therapist and i said i'm really terrified that we're going to have these robots very soon that will hurt us like how do you approach making me feel better like why shouldn't people be afraid there's a i think there's a video that went viral recently everything everything was spot in boston today which goes viral in general but usually it's like really cool stuff like they're doing flips and stuff or like sad stuff would be it's atlas being hit with a broomstick or something like that but uh there's a video where i think uh one of the new production spot robots which are awesome it was like patrolling somewhere in like in some country and like people immediately were like saying like this is like the dystopian future like the surveillance state for some reason like you can just have a camera like something about spot being able to walk on four feet with like really terrified people so like what what do you say to those people i think there is a legitimate fear there because so much of our future is uncertain but at the same time technically speaking it seems like we're not there yet so what do you say i mean i think technology is um complicated it can be used in many ways i think there are purely software um attacks that somebody could use to do great damage maybe they have already um you know i think uh wheeled robots could be used in bad ways too drones right um i don't think that let's see i don't want to be um building technology just because i'm compelled to build technology and i don't think about it but i would consider myself a technological optimist i guess um in the sense that i think we should continue to create and evolve and our world will change um and if we will introduce new challenges we'll screw something up maybe but i think also we'll invent ourselves out of those challenges and life will go on so it's interesting because you didn't mention like this is technically too hard i don't think robots are i think people attribute a robot that looks like an animal as maybe having a level of self-awareness or consciousness or something that they don't have yet right so it's not i think our ability to anthropomorphize those robots is probably um we're assuming that they have a level of intelligence that they don't yet have and that might be part of the fear so in that sense it's too hard but um you know there are many scary things in the world right so i think we're right to ask those questions we're right to um think about the implications of our work right in the in this in the short term as we're working on it for sure is there something long-term that scares you about our future with ai and robots a lot of folks from elon musk to sam harris to a lot of folks talk about the you know existential threats about artificial intelligence oftentimes robots kind of um inspire that the most because of the anthropomorphism do you have any fears it's an important question um i actually i think i like rod brooks answer maybe the best on this i think and it's not the only answer he's given over the years but maybe one of my favorites is he says it's not going to be he's got a book flesh and machines i believe it's not going to be the robots versus the people we're all going to be robot people because you know we already have smartphones some of us have um serious technology implanted in our bodies already whether we have a hearing aid or a pacemaker or anything like this um people with amputations might have prosthetics that's a trend i think that is likely to continue i mean this is now uh wild speculation but uh i mean when do we get to cognitive implants and the like and yeah with neurolink brain computer interfaces that's interesting so there's a there's a dance between humans and robots it's going to be it's going to be impossible to be scared of the other out there the robot because the robot will be part of us essentially it'd be so intricately sort of part of our society that and it might not even be implanted part of us but just it's so much a part of our yeah our society so in that sense the smartphone is already the robot we should be afraid of yeah uh i mean yeah and all the usual fears arise of the misinformation the manipulation all those kinds of things that um that the problems are all the same they're all they're human problems essentially it feels like yeah i mean i think the the way we interact with each other online is changing the value we put on you know personal interaction and that's a crazy big change that's going to happen and rip through our system has already been ripping through our society right and that has implications that are massive i don't know if they should be scared of it or go with the flow but i don't see you know some battle lines between humans and robots being the first thing to worry about i mean i do want to just as a kind of comment maybe you can comment about your just feelings about boston dynamics in general but you know i love science i love engineering i think there's so many beautiful ideas in it and when i look at boston dynamics or legged robots in general i think they inspire people curiosity and feelings in general excitement about engineering more than almost anything else in popular culture and i think that's such an exciting plus like responsibility and possibility for robotics and boston dynamics is riding that wave pretty damn well like they've found it they've discovered that hunger and curiosity in the people and they're doing magic with it i don't care if the i mean i guess their company have to make money right but uh they're already doing incredible work and inspiring the world about technology i mean do you have do you have thoughts about boston dynamics maybe others your own work and robotics and inspiring the world in that way i completely agree i think boston dynamics is absolutely awesome i think i show my kids those videos you know and the best thing that happens is sometimes they've already seen them you know uh right i think i i just think it's a pinnacle of success in robotics that um is just one of the best things that's happened i absolutely completely agree one of the heartbreaking things to me is how many robotics companies fail how hard it is to make money with the robotics company like irobot like went through hell just to arrive at a roomba to figure out one product and then there's so many um home robotics companies like gebo and anki anki the cutest toy that's a great robot i thought uh went down i'm forgetting a bunch of them but a bunch of robotics rods company rethink robotics um like do you um do you have any anything hopeful to say about the possibility of making money with robots oh i think um you can't just look at the failures you can all i mean boston dynamics is a success there's lots of companies that are still doing amazingly good work in robotics i mean this is the this is the capitalist ecology or something right i think you have many companies you have many startups and they push each other forward and many of them fail and some of them get through and that's sort of the natural way of things the way of those things i don't know that is robotics really that much worse i i feel the pain that you feel too every time i read one of these i um sometimes it's friends and and i definitely wish it went better or would differently but i think it's healthy and good to have um bursts of ideas burst of activities ideas if they are really aggressive they should fail sometimes certainly that's the research mantra right if you're succeeding at every problem you attempt then you're not choosing aggressively enough is it exciting to you uh the new spot oh it's okay it's so good what are you getting him as a pet uh it yeah i mean i have to dig up 75k right now it's so cool that there's a price tag you can go and and then actually buy it and i have a skydio r1 uh love it so um no i would i would i would absolutely be a customer uh i wonder what your kids would think about i i actually um zach from boston dynamics would let my kid drive in one of their demos one time and uh that was just so good so good and again forever be grateful for that and there's something magical about the anthropomorphization of that arm it adds another level of human connection i'm not sure we understand from a control aspect uh the value of anthropomorphization um i i think that's an understudied and understood engineering problem there's been a psycho psychologists have been studying it i think it's part like manipulating our mind to believe things uh is a valuable engineering like this is another degree of freedom that can be controlled i like that yeah i think that's right i think you know there's something that humans seem to do or maybe my dangerous introspection is uh i think we are able to make very simple models that assume a lot about the world very quickly and then uh it takes us a lot more time like you're wrestling you know you probably thought you knew what you're doing with wrestling and you were fairly functional as a complete wrestler and then you slowly got more expertise so maybe it's natural that our first first level of defense against seeing a new robot is to think of it in our existing models of how humans and animals behave and it's just as you spend more time with it then you'll develop more sophisticated models that will appreciate the differences exactly can you say what does it take to control a robot like what is the control problem of a robot and in general what is a robot in your view like how do you think of this system what is a robot what is a robot i think robotics ridiculous questions no no it's good um i mean there's standard definitions of combining computation with some ability to do mechanical work i think that gets us pretty close but i think robotics has this problem that once things really work we don't call them robots anymore like your my dishwasher at home is pretty sophisticated beautiful mechanisms there's actually a pretty good computer probably a couple chips in there doing amazing things we don't think of that as a robot anymore which isn't fair because then what roughly it means that robots robotics always has to solve the next problem and doesn't get to celebrate its past successes i mean even factory room floor robots are super successful they're amazing but that's not the ones i mean people think of them as robots but they don't if you ask what are the successes of robotics somehow it doesn't come to your mind immediately so the definition of robot is a system with some level automation that fails frequently something like it's it's the computation plus mechanical work and unsolved problems solve problem yeah so so from a perspective of control and mechanics dynamics what what is a robot so there are many different types of robots the control that you need for a um a jibo robot you know some some robot that's sitting on your countertop and and interacting with you but not touching you for instance is very different than what you need for an autonomous car or an autonomous drone it's very different than what you need for a robot that's going to walk or pick things up with its hands right my passion has always been for them places where you're interacting more you're doing more dynamic interactions with the world so walking now manipulation and the control problems there are are beautiful i think contact is one thing that differentiates them from many of the control problems we've solved classically right like modern control grew up stabilizing fighter jets that were passively unstable and there's like amazing success stories from control all over the place um power grid i mean there's all kinds of it's it's it's everywhere uh that we don't even realize just like ai is now so you mentioned contact like what's contact so an airplane is of extremely complex system or a spacecraft landing or whatever but at least it has the luxury of things change relatively continuously that's an oversimplification but if i make a small change in the command i send to my actuator then the path that the robot will take tends to take a change only by a small amount and there's a feedback mechanism here there's a feedback mechanism and thinking about this as locally like a linear system for instance i can use more linear algebra tools to study systems like that generalizations of linear algebra to to these smooth systems what is contact the robot has something very discontinuous that happens when it makes or breaks when it starts touching the world and even the way it touches or the order of contacts can change the outcome in potentially unpredictable ways not unpredictable but complex ways i do think there's a little bit of people a lot of people will say that contact is hard in robotics even to simulate um and i think there's a little bit of a there's truth to that but but maybe a misunderstanding around that so what is limiting is that when we think about our robots when we write our simulators we often make an assumption that that objects are rigid and when it comes down you know that they that their mass moves all you know it stays in a constant position relative to each other itself um and and that leads to some paradoxes when you go to try to talk about rigid body mechanics and contact and so for instance if i have a three-legged stool with just a imagine it comes to a point at the at the leg so it's only touching the world at a point if i draw my physics my high school physics diagram of this system then there's a couple of things that i'm given by by elementary physics i know if the system if the table is at rest if it's not moving it's zero velocities that means that the normal force all the forces are in balance so the the force of gravity is being countered by the forces that the ground is pushing on my table legs i also know since it's not rotating that there that the moments have to balance and since it can in it's a three-dimensional table it could fall in any direction it actually tells me uniquely what those three normal forces have to be if i have four legs on my table four-legged table and they were perfectly machined to be exactly the right same height and they're set down and the table's not moving then the basic conservation laws don't tell me there are many solutions for the forces that the ground could be putting on my legs that would still result result in the table not moving now the reason that seems fine i could just pick one but it gets funny now because if you think about friction we what we think about with friction is we our standard model says the amount of force that your that the table will push back if i were to now try to push my table sideways i guess i have a table here is proportional to the normal force so if i have if i'm very barely touching and i push i'll slide but if i'm pushing more and i push i'll slide less it's called coulomb friction is our standard model now if you don't know what the normal force is on the four legs and you push the table then you don't know what the friction forces are going to be right and so you can't actually tell the laws just don't aren't explicit yet about which way the table is going to go it could veer off to the left it could veer off to the right it could go straight so the rigid body assumption of contact leaves us with some paradoxes which are annoying for for writing simulators and for writing controllers we still do that sometimes because soft contact is potentially harder numerically or whatever and the best simulators do both or do some combination of the two but but anyways because of these kind of paradoxes there's all kinds of paradoxes in contact uh mostly due to these rigid body assumptions it becomes very hard to like write the same kind of control laws that we've been able to be successful with for like fighter jets we haven't been as successful writing those controllers for manipulation and so you don't know what's going to happen at the point of contact at the moment of contact there are situations absolutely where you where our laws don't tell us so the standard approach that's okay i mean instead of having a differential equation you end up with a differential inclusion it's called it's a set valued equation it says that i'm in this configuration i have these forces applied on me um and there's there's a set of things that could happen right and um and those aren't continuously i mean what uh so when you're seeing like non-smooth they're not only not smooth but this is discontinuous the non-smooth comes in when i make or break a new contact first or when i transition from stick to slip so you typically have static friction and then you'll start sliding and that'll be a discontinuous change in in velocity for instance especially if you come to rest or that's so fascinating okay so uh so what do you what do you uh do sorry i interrupted you um what's the hope under so much uncertainty about what's going to happen what are you supposed to do i mean control has an answer for this robust control is one approach but but roughly you can write controllers which try to still perform the right task despite all the things that could possibly happen the world might want the table to go this way in this way but if i write a controller that pushes a little bit more and pushes a little bit i can certainly make the table go in the direction i want it just puts a little bit more of a burden on the control system right and this discontinuities do change the control system because um the way we write it down right now every different control con configuration including sticking or sliding or parts of my body that are in contact or not looks like a different system and i think of them i reason about them separately or differently and the combinatorics of that blow up right so i just don't have enough time to compute all the possible contact configurations of my humanoid interestingly i i mean i'm a humanoid i have lots of degrees of freedom lots of joints i only i've only been around for a handful of years it's getting up there but i haven't had time in my life to visit all of the states in my system certainly all the contact configurations so if step one is to consider every possible contact configuration that i've i'll ever be in that's probably a that's probably not a problem i need to solve right just as a small attention what's a contact configuration what like just so we can uh yeah enumerate what are we talking about yeah how many are there the simplest example maybe would be imagine a robot with a flat foot and we think about the phases of gate where the heel strikes and then the four the front toe strikes and then you can heal up toe off those are each different contact configurations i only had two different contacts but i ended up with four different contact configurations now of course i might have my my robot might actually have bumps on it or other things so it could be much more subtle than that right but it's just even with one sort of box interacting with the ground already in in the plane has that many right and if i was just even a 3d foot then probably my left toe might touch just before my right toe and things get subtle now if i'm a dexterous hand and i go to talk about just grabbing a water bottle if every if i have to enumerate every possible order that my hand came into contact with the with the bottle then i'm dead in the water my any approach that we were able to get away with that in walking because we mostly touch the ground within a small number of points for instance and we haven't been able to get dextrous hands that way so i mean you've mentioned that people think that contact is really hard and that that's the reason that robotic manipulation is problem is really hard is there any flaws in that thinking so i think simulating contact is one aspect i know people often say that we don't that one of the reasons that we have a limit in robotics is because we do not simulate contact accurately in our simulators and i think that is the extent to which that's true is partly because our simulators we haven't got mature enough simulators there are some things that are still hard difficult that has changed but but we actually we know what the governing equations are they have some foibles like this indeterminacy but we should be able to simulate them accurately we have incredible open source community in robotics but it actually just takes a professional engineering team a lot of work to write a very good simulator like that uh now where does um i believe you've written drake there's a team of people i certainly spend a lot of hours on it myself well what is drake and what um what does it take to to to create a simulation environment uh for for the kind of difficult control problems we're talking about right so drake is the simulator that that i've been working on um there are other good simulators out there i don't like to think of drake as just a simulator because because we write our controllers in drake we write our perception systems a little bit in drake but we write all of our our you know low level control and even planning and uh optimization intelligence optimization capabilities absolutely yeah i mean drake is three things roughly it's an optimization library which is um sits on it it provides a layer of abstraction in c plus and python for commercial solvers you can write linear programs quadratic programs you know semi-definite programs sums of squares programs the ones we've used mixed integer programs and it will do the work to curate those and send them to whatever the right solver is for instance and it provides a level of abstraction the second thing is is a system modeling language a bit like labview or simulink where you can make block diagrams out of complex systems or it's like ross in that sense where you might have lots of ross nodes that are each doing some part of your system but to contrast it with ross we try to write if you write a drake system then you have to it asks you to describe a little bit more about the system if you have any state for instance in the system there any variables that are going to persist you have to declare them parameters can be declared and the like but the advantage of doing that is that you can if you like run things all on one process but you can also do control design against it you can do i mean simple things like rewinding and playing back your your your simulations for instance you know these things you get some rewards for spending a little bit more upfront cost in describing each system and and i i was inspired to do that because i think the complexity of atlas for instance um is just so great and i think although i mean ross has been incredible absolutely huge fan of what it's done for the robotics community but it um the ability to rapidly put different pieces together and have a functioning thing is very good but i do think that it's hard to think clearly about a bag of disparate parts mr potato head kind of software stack and if you can you know ask a little bit more out of each of those parts then you can understand the way they work better you can try to verify them and the like um you can do learning against them and then one of those systems the last thing i i said the first two things that drake is but the last thing is that there is a set of multi-body equations rigid body equations that is trying to provide a system that simulates physics and that um we also have renderers and other things but i think the physics component of drake is is special in the sense that um we have done excessive amount of engineering to to make sure that we've written the equations correctly every possible tumbling satellite or spinning top or anything that we could possibly write as a test is tested um we are making some you know i think fundamental improvements on the way you simulate contact yes what does it take to uh simulate contact i mean it just seems uh i mean there's something just beautiful the way you were like explaining contact and you're like tapping your fingers on the on the table while you're while you're doing it just um easily right easily just like just not even like it was like helping you think i guess um what i um see you have this like awesome demo of um loading or unloading a dishwasher just picking up a plate uh grasping it like for the first time um that's just seems like so difficult what how do you simulate any of that so it was really interesting that what happened was that um we started getting more professional about our software development during the darpa robotics challenge i learned the value of software engineering and how these how to bridle complexity i guess that's that's what i i want to somehow fight against and bring some of the clear thinking of controls into these complex systems we're building for robots um shortly after the darpa robotics challenge toyota opened a research institute tri toyota research institute um they put one of their there's there's three locations one of them is just down the street from mit and uh and i helped ramp that up uh right out as a part of my uh the end of my sabbatical i guess um so so tri is uh has given me the tri robotics effort has made this investment in simulation in drake and michael sherman leads a team there of just absolutely top notch dynamics experts that are trying to write those simulators that can pick up the dishes and there's also a team working on manipulation there that is taking problems like loading the dishwasher and we're using that to study these really hard corner cases kind of problems in manipulation so for me this you know simulating the dishes we could actually write a controller if we just cared about picking up dishes in the sink once we could write a controller without any simulation whatsoever and we could call it done but we want to understand like what is the path you take to actually get to a robot that could perform that for any dish uh in anybody's kitchen with with enough confidence that it could be a commercial product right and and it has deep learning perception in the loop it has complex dynamics in the loop it has controller it has a planner and how do you take all of that complexity and put it through this engineering discipline and verification and validation process to actually get enough confidence to deploy i mean the darpa challenge made me realize that that's not something you throw over the fence and hope that somebody will harden it for you that there are really fundamental challenges in uh in closing that last gap they're doing the validation and the testing i think it might even change the way we have to think about the way we write systems what happens if you if you have the robot running lots of tests it and it screws up it breaks a dish right how do you capture that i said you can't run the same simulation or the same experiment twice in in a real on a real robot do we have to be able to bring that one off exp failure back into simulation in order to change our controllers study it make sure it won't happen again do we is it enough to just try to add that to our distribution and understand that on average we're going to cover that situation again there's like really subtle questions at the corner cases that i think we don't yet have satisfying answers for like how do you find the corner cases that's one kind of is there do you think this possible to create a systematized way of discovering corner cases efficiently yeah in whatever the problem is yes i mean i think we have to get better at that i mean control theory has um for for decades talked about active experiment design so people call it curiosity these days it's roughly this idea of trying to exploration or exploitation but but in the active experiment design is even is is more specific you could try to understand the uncertainty in your system design the experiment that will provide the maximum information to reduce that uncertainty if there's a parameter you want to learn about what is the optimal trajectory i could execute to learn about that parameter for instance scaling that up to something that has a deep network in the loop and the planning in the loop is tough we've done some work on you know with matt o'kelly and amancina we have we've worked on um some falsification algorithms that are trying to do rare event simulation that try to just hammer on your simulator and if your simulator is good enough you can um you can spend a lot of time or you can write good algorithms that try to spend most of their time in the corner cases so you basically imagine you're you're building an autonomous car and you want to put it in i don't know downtown new delhi all the time right an accelerated testing if you can write sampling strategies which figure out where your controller is performing badly in simulation and start generating lots of examples around that you know it's just the space of possible places where that can be where things can go wrong is very big so it's hard to write those algorithms yeah rare event simulation is just like a really compelling notion uh if it's possible we joked and we called we call it the black swan generator it's a black swan right because you don't just want the rare events you want the ones that are highly impactful i mean that's the most those are the most sort of profound questions we ask of our world like uh what's the uh what's the worst that can happen uh but what we're really asking isn't some kind of like computer science worst case analysis we're asking like what are the millions of ways this can go wrong and that's like our curiosity we humans i think are pretty bad at uh we just like run into it and i think there's a distributed sense because there's now like 7.5 billion of us and so there's a lot of them and then a lot of them write blog posts about the stupid thing they've done so we learn in a distributed way um there's there's something that's going to be important for robots too yeah i mean that's that's another massive theme at toyota research for robotics is this fleet learning concept is um you know the idea that i as a humanoid don't have enough time to visit all of my states right there's just a it's very hard for one robot to experience all the things but that's not actually the problem we have to solve right um we're gonna have fleets of robots that can have very similar appendages and at some point maybe collectively they have enough data that their computational processes should be set up differently than ours right it's a have this vision of just i mean all these uh dishwasher unloading robots i mean um that robot dropping a plate and a human looking at the robot probably pissed off yeah but uh that's a special moment to record i think one one thing in terms of fleet learning and i've seen that because i i've talked to a lot of folks um just like like tesla users or tesla drivers they're not another another company that's using this kind of fleet learning idea and one hopeful thing i have about humans is they really enjoy when a system improves learns so they enjoy fleet learning and they're the reason it's hopeful for me is they're willing to put up with something that's kind of dumb right now and they're like if it's improving they almost like enjoy being part of the like teaching it almost like we if you have kids like you're teaching them something right um i think that's a beautiful thing because that that gives me hope that we can put dumb robots out there uh as long i mean the problem with on the tesla side with cars cars can kill you that's that makes the problem so much harder dishwasher unloading is a little safe that's why home robotics is uh it's really exciting and just to clarify i mean for people who might not know a tri toyota research institute so they're uh i mean they're they're pretty well known for like autonomous vehicle research but they're also interested in in home robotics yep there's a big there's a big group working on multiple groups working on home robotics it's a major part of the portfolio also there's also a couple other projects an advanced materials discovery i'm using ai and machine learning to discover new materials for um for car batteries and then the like for instance yeah and that's been actually an incredibly successful team uh there's new projects starting up too so do you see a future of uh where like robots are in our home and and like robots that have like um actuators that look like arms in our home or like you know more like humanoid type robots or is this are we gonna is we're gonna do the same thing that you just mentioned that you know the dishwasher is no longer a robot we're going to just not even see them as robots but do i mean what's your vision of the home of the future 10 20 years from now 50 years if you get crazy yeah i think we already have roombas cruising around we have uh uh you know alexa's or google homes on their our kitchen counter it's only a matter of time till they spring arms and start doing something useful like that um so i do think it's coming i think it's lots of people have lots of motivations for doing it it's been super interesting actually learning about toyota's vision for it which is about helping people age in place because i think that's not necessarily the first entry the most lucrative entry point but it's the problem maybe that we really need to solve no matter what and so i think i think there's a real opportunity it's a delicate problem how do you work with people help people keep them active engaged you know but improve their quality of life and uh and and help them age in place for instance it's interesting because older folks are also i mean there's a contrast there because um they're not always the the folks who are the most comfortable technology for example so there's a there's a there's a division that's interesting there that you can do so much good with a robot for for older folks but there's a there's a gap to feel of understanding i mean it's actually kind of beautiful um robot is learning about the human and the human is kind of learning about this new robot thing and it's uh also with um at least with uh like when i talk to my parents about robots there's a little bit of a blank slate there too like you can i mean they don't know anything about robotics so it's completely like wide open they don't have that they haven't my parents haven't seen black mirror so like they they there's it's a blank slate here's a cool thing like what can you do for me yeah so it's an exciting space i think it's a really important space i do feel like you know a few years ago uh drones were successful enough in academia they kind of broke out and started in industry and autonomous cars have been happening it does feel like manipulation in logistics of course first but in the home shortly after seems like one of the next big things that's going to really pop so uh i don't think we talked about it but uh what's soft robotics so we talked about like rigid bodies like if we can just linger on this whole touch thing um yeah so what's soft robotics so i told you that i really dislike the fact that robots are afraid of touching the world all over their body so there's a couple reasons for that if you look carefully at all the places that robots actually do touch the world they're almost always soft they have some sort of pad on their fingers or a rubber sole on their foot but if you look up and down the arm we're just pure aluminum or something so uh so that makes it hard actually in fact hitting the table with your you know your rigid arm or nearly rigid arm is a is a has some of the problems that we talked about in terms of simulation i think it it fundamentally changes the mechanics of contact when you're soft right you you turn point contacts into patch contacts which can have torsional friction you can have um distributed load if i want to pick up an egg right if i pick it up with two points then in order to put enough force to sustain the weight of the egg i might have to put a lot of force to break the egg if i envelop it with a with contact all all around then i can distribute my force across the shell of the egg and have a better chance of not breaking it so soft robotics is for me a lot about changing the mechanics of contact does it make the problem a lot harder um quite the opposite uh it it changes the computational problem i think because of the i think our world and our mathematics has biased us towards ridgid but it really should make things better in some ways right um it's it's a i think the the the future is unwritten there um but the other thing is ultimately sorry to interrupt they think ultimately it will make things simpler if we embrace the softness of the world it makes um it makes things smoother right so the the result of small actions is less discontinuous but it also means potentially less you know instantaneously bad for instance i won't necessarily contact something and send it flying off the other aspect of it that just happens to dovetail really well is that if soft robotics tends to be a place where we can embed a lot of sensors to so if you change your your hardware and make it more soft then you can potentially have a tactile sensor which is measuring the deformation so there's a team at tri that's working on soft hands and and you get so much more information if you you can put a camera behind the skin roughly and and get fantastic tactile information which is um it's super important like in manipulation one of the things that really is frustrating is if you work super hard on your head mounted on your perception system for your head mounted cameras and then you've identified an object you reach down to touch it and the first the last thing that happens right before the most important time you stick your hand and you're occluding your head mounted sensors right so in all the part that really matters all of your off board sensors are you know are occluded and really if you don't have tactile information then you're you're blind in an important way so it happens that soft robotics and tactile sensing tend to go hand in hand i think we've kind of talked about it but uh you taught a course on under actuator robotics i believe that was the name of it actually that's right can you talk about it in that context what is under actuated robotics right so under-actuated robotics is my graduate course it's it's online mostly now so i mean in the sense that the lecturer's versions of it i think right the youtube really great i recommend it highly look on youtube for the 2020 versions until march and then you have to go back to 2019 thanks to covet um no i've poured my heart into that class and lecture one is basically explaining what the word underactuated means so people are very kind to show up and then maybe have to learn what the title of the course means over the course of the first lecture that that first lecture is really good you should watch it it's it's a strange name but um i thought it captured the essence of what control was good at doing and what control was bad at doing so what do i mean by under actuated so a mechanical system has many degrees of freedom for instance i think of a joint as a degree of freedom and it has some number of actuators motors so if you have a robot that's bolted to the table that has five degrees of freedom and five motors then you have a fully actuated robot if you have if you take away one of those motors then you have an under actuated robot now why on earth i i have a good friend who who likes to tease me he said russ if you had more research funding would you work on fully actuated robots yeah and uh the answer is no the world gives us under-actuated robots whether we like it or not i'm a human i'm an under actuated robot even though i have more muscles than my big degrees of freedom because i have in some places multiple muscles attached to the same joint but still there's a really important degree of freedom that i have which is the location of my center of mass in space for instance all right i'm i can jump into the air and there's no motor that connects my center of mass to the ground in that case so i have to think about these the implications of not having control over everything the passive dynamic walkers are the extreme view of that where you've taken away all the motors and you have to let physics do the work but it shows up in all the walking robots where you have to use some of the actuators to push and pull even the degrees of freedom that you don't have an actuator on that's referring to walking if you're like falling forward like is there a way to walk that's fully actuated so it's a subtle point when you're when you're in contact and you have your feet on the ground there are still limits to what you can do right unless i have suction cups on my feet i cannot accelerate my center of mass towards the ground faster than gravity because i can't get a force pushing me down right but i can still do most of the things that i want to so you can get away with basically thinking of the system as fully actuated unless you suddenly need it to accelerate down super fast but as soon as i take a step i i get into more nuanced territory and to get to really dynamic robots or airplanes or other things i think you have to embrace the under actuated dynamics manipulation people think is manipulation under under actuated my even if my arm is fully actuated i have a motor if my goal is to control the position and orientation of this cup then i don't have an actuator for that directly so i have to use my actuators over here to control this thing now it gets even worse like what if i have to button my shirt okay what are the degrees of freedom of my shirt right i suddenly that's a hard question to think about it kind of makes me queasy as a thinking about my state-space control ideas but actually those are the problems that make me so excited about manipulation right now is that it it breaks some of the it breaks a lot of the foundational control stuff that i've been thinking about is there um what are some interesting insights you could say about trying to solve an under actuated like control in in an underactuated system so i think the philosophy there is let physics do more of the work the technical approach has been optimization so you typically formulate your decision making for control as an optimization problem and you use the language of optimal control and sometimes numero often numerical optimal control in order to make those decisions and balance you know these complicated equations of and in order to control you don't have to use optimal control to do under-actuated systems but that has been the technical approach that has borne the most fruit in our at least in our line of work and there's some so in under actuator systems when you say let physics do some of the work so there's a kind of feedback feedback loop that observes the state that the physics brought you to so like you've there's a there's a perception there this is there's a feedback somehow do you do um do you ever loop in like complicated perception systems into this whole picture right right around the time of the darpa challenge we had a complicated perception system in the darpa challenge we also started to embrace perception for our flying vehicles at the time we had a a really good project on trying to make airplanes fly at high speeds through forests um sirtex caramel was on that project and it was a really fun team to to work on he's carried it farther much farther forward since then so that's using cameras for perception so that was using cameras uh that was a at the time we felt like lidar was too too heavy and two power heavy to to be carried on on a light uav and we were using cameras and that was a big part of it was just how do you do even stereo matching at a fast enough rate with a small camera a small onboard compute since then we have now the so the deep learning revolution unquestionably changed what we can do with perception for robotics and control so in manipulation we can address we can use perception in a i think a much deeper way and um we get into not only i think the the first use of it naturally would be to ask your deep learning system to look at the cameras and produce the state which is like the pose of my thing for instance but i think we've quickly found out that that's not always the right thing to do um why is that because what's the state of my shirt imagine i've always very noisy i mean or it's um if the first step of me trying to button my shirt is estimate the full state of my shirt including like what's happening in the backyard or whatever whatever that's just not the right specification there are aspects of the state that are very important to the task there are many that are unobservable and not not important to the task so you really need it begs new questions about state representation another example that we've been playing with in lab has been just the idea of chopping onions okay or carrots turns out to be better so the onions stink up the lab uh and they're hard to see in a camera but uh so details matter yeah details matter you know so um moving around a particular object right then i think about oh it's got a position or an orientation in space that's the description i want now when i'm chopping an onion okay the first chop comes down i have now a hundred pieces of onion does my control system really need to understand the position and orientation and even the shape of the hundred pieces of onion in order to make a decision probably not you know and like if i keep going i'm just getting more and more is my state space getting bigger as i cut it's it um it it's not right yes so there's a i think there's a richer uh idea of state it's not the state that is given to us by lagrangian mechanics there is a there is a proper lagrangian state of the system but the relevant state for this is some latent state is what we call it in machine learning but you know there's some some different state representatives some compressed representation some and that's what i i worry about saying compressed because it doesn't i don't mind that it's low dimensional or not but it has to be something that's easier to think about by us humans or my algorithms or the algorithms being like control optimal so for instance if the contact mechanics of all of those onion pieces and all the permutations of possible touches between those onion pieces you know you can give me a high dimensional state representation i'm okay if it's linear but if i have to think about all the possible shattering combinatorics of that then my robot is going to sit there thinking and uh the soup's gonna get cold or something so um since you taught the course i've it kind of entered my mind um the idea of under actuated as really compelling to see the to see the world in this kind of way um do you ever you know if we talk about onions or you talk about the world with people in it in general do you see the world as a basically an underactuated system do you like often look at the world in this way or is this uh overreach um under actuated as a way of life man exactly um i guess that's what i'm asking i do think it's everywhere i think some in some places um we already have natural tools to deal with it you know it rears its head i mean in linear systems it's not a problem we just we just like an under actuated linear system is really not sufficiently distinct from a fully actuated linear system it's it's a it's a subtle point about when that becomes a bottleneck and what we know how to do with control it happens to be a bottleneck although we've gotten incredibly good solutions now but for a long time that i felt that that was the key bottleneck in legged robots and roughly now the under actuated course is you know me trying to tell people everything i can about how to make atlas do a backflip right i have a second course now in that i teach in the other semesters which is on on manipulation and that's where we get into now more of the that's a newer class i'm hoping to put it online this fall completely and uh that's going to have much more aspects about these perception problems and the state representation questions and then how do you do control and the the thing that's a little bit sad is that uh for me at least is there's a lot of manipulation tasks that people want to do and should want to do they could start a company with it and make very successful that don't actually require you to think that much about under or dynamics at all even but certainly under actuated dynamics once i have if i if i reach out and grab something if it if i can sort of assume it's rigidly attached to my hand then i can do a lot of interesting meaningful things with it without really ever thinking about the dynamics of that object so they built we've built systems that kind of reduced the need for that enveloping grasps and the like um but i think the really good problems in manipulation so manipulation by the way is more than just pick and place that's like a lot of people think of that just grasping i don't mean that i mean buttoning my shirt i mean tying shoe laces how do you program a robot to tie shoelaces and not just one shoe but every shoe right that's a really good problem it's tempting to write down like the infinite dimensional state of the of the laces that's probably not needed to write a good controller i know we could hand design a controller that would do it but i don't want that i want to understand the principles that would allow me to solve another problem that's kind of like that but i think if we can stay pure in our approach then the challenge of tying anybody's shoes is a great challenge that's a great challenge i mean and the soft touch comes into play there that's really interesting let me ask another ridiculous question on this topic um how important is touch we haven't talked much about humans but i have this argument with my dad where like i think you can fall in love with the robot based on uh language alone and he believes that touch is essential i touch and smell he says but um so in terms of robots you know connecting with humans and uh we can go philosophical in terms of like a deep meaningful connection like love but even just like collaborating in an interesting way how important is touch like uh from the engineering perspective and the philosophical one i think it's super important let's even just in a practical sense if we forget about the emotional part of it but for robots to interact safely while they're doing meaningful mechanical work in the pro in the you know close contact with or vicinity of people that need help i think we have to have them they have we have to build them differently um they have to be afraid not afraid of touching the world so uh i think baymax is just awesome that's just like the the the movie of big hero 6 and the the concept of baymax that's just awesome i think we should and we have some folks at toyota that are trying to toyota research that are trying to build baymax roughly and i think it's just a fantastically good project i think it will change the way people physically interact the same way i mean you gave a couple examples earlier but but if i um if the robot that was walking around my home looks more like a teddy bear and a little less like the terminator that could change completely the way people perceive it and interact with it and maybe they'll even want to teach it like you said right you could um not quite gamify it but somehow instead of people judging it and looking at it as if uh it's not doing as well as a human they're going to try to help out the cute teddy bear right who knows but i i think we're building robots wrong and being more soft and more contact is important right yeah and like all the magical moments i can remember with robots well first of all just visiting your lab seeing atlas but also spot menu when i first spot saw spot many in person and hung out with him her uh it i don't have trouble engendering robots i feel robotics people really say always it i kind of like the idea that it's a her or him uh there's a magical moment but there's no touching uh i guess the question i have have you ever been um like have you had a human robot experience where like a robot touched you and like it was like wait like was there a moment that you've forgotten that a robot is a robot and like the anthropomorphization stepped in and for a second you forgot that it's not human i mean i think when you're in on the details then we we of course anthropomorphized our work with atlas but in you know in verbal communication and the like i think we were pretty aware of it as a machine that needed to be respected um i actually i worry more about the smaller robots that could still you know move quickly if programmed wrong and uh and we have to be careful actually about safety and the like right now and that if we build our robots correctly i think then those a lot of those concerns could go away and we're seeing that trend we're seeing the lower cost lighter weight arms now that could be fundamentally safe um i mean i do think touch is so fundamental ted adelson is uh is great he's a perceptual scientist at mit and he studied vision most of his life and he said when i had kids i expected to be fascinated by their perceptual development but what really what he noticed was felt more impressive more dominant was the way that they would touch everything and lick everything and pick things up stick it on their tongue and whatever and he said watching his daughter uh convinced him that actually he needed to study tactile sensing more so there's something very important i think it's a little bit also of the passive versus active part of the world right you can passively perceive the world but it's fundamentally different if you can do an experiment right and if you can change the world and you can learn a lot more than a passive observer so you can in dialogue that was your initial example you could have an active experiment exchange but i think if you're just a camera watching youtube i think that's a very different problem than if you're a robot that can apply force and touch i i i think it's important yeah i think it's just an exciting area of research i think you're probably right that this hasn't been under researched it's uh to me as a person who's captivated by the idea of human robot interaction it feels like such a rich opportunity to explore touch not even from a safety perspective but like you said the emotional too i mean safety comes first um but the next step is like you know uh like a real human connection even in the war like even in the industrial setting it just feels like uh it's nice for the robot i don't know i you know you might disagree with this but um because i think it's important to see robots as tools often but i don't know i think they're just always going to be more effective once you humanize them uh like it's convenient now to think of them as tools because we want to focus on the safety but i think ultimately to create like a good experience for the worker for the person there has to be a human element i don't know for me i i it feels like like an industrial robotic arm would be better if as a human element i think like we think robotics had that idea with baxter and having eyes and so on having i don't know i'm a big believer in that i it's not my area but i am also a big believer do you have an emotional connection to atlas like yeah do you miss him i mean yes i i i don't know if i'd more so than if i had a different science project that i'd worked on super hard right but uh um yeah i mean the robot we basically had to do heart surgery on the robot in the final competition because we melted the core um and uh and yeah there was something about watching that robot hanging there we know we had to compete with it in an hour and it was getting its guts ripped out those are all historic moments i think if we look back like 100 years from now um yeah i think those are important moments in robotics i mean these are the early day you look at like the early days of a lot of scientific disciplines they look ridiculous they're full of failure but it feels like robotics will be important in the coming uh 100 years and these are the early days so so i think a lot of people are look at uh a brilliant person such as yourself and and are curious about the intellectual journey they've took um is there maybe three books technical fiction philosophical that um had a big impact on your life that you would recommend perhaps others reading yeah so um i actually didn't read that much as a kid but i read fairly voraciously now um there are some recent books that if you're interested in this kind of topic like ai superpowers by kaifuli is just a fantastic read you must read that um yuval harari is just i think that can open your mind um sapiens sapiens as as the first one homo deuce is the second yeah i think we mentioned the black swan by taleb i think that's a good sort of mind opener i actually um so so there's maybe a more controversial recommendation i could give um great well i would love something sure in some sense it's it's so classical it might surprise you but i actually recently read um mortimer adler's how to read a book not so long it was a while ago but some people hate that book i loved it i think we're in this time right now where um boy we're just inundated with research papers that you could read on archive with limited peer review and just this wealth of information um i don't know i think the passion of um what you can get out of a book a really good book or a really good paper if you find it the attitude the realization that you're only going to find a few that really are worth all your time but then once you find them you should just dig in and and and understand it very deeply and it's worth you know marking it up and and uh you know having the hard copy writing in the the side notes side margins um i think that was really it i read it at the right time where i was just feeling just overwhelmed with really low quality stuff i guess and similarly uh i'm just giving more than three now i'm sorry if i've exceeded my my quota but on that topic just real quick is uh so basically finding a few companions to keep for the rest of your life in terms of papers and books and so on and those are the ones like not doing um what is it fomo fear missing out constantly trying to update yourself but really deeply making a life journey of studying a particular paper essentially a set of papers yeah i think when you really find something which a book that resonates with you might not be the same book that resonates with me but um when you really find one that resonates with you i think the dialogue that happens and that's what i love that adler was saying you know i think socrates and plato say um the the written word is never going to capture the beauty of dialogue right but adler says no no um a a really good book is a dialogue between you and the author and it crosses time and space and uh i don't know i think it's a very romantic there's a bunch of like specific advice which you can just gloss over but the romantic view of how to read and really appreciate it is is is so good and similarly teaching i uh um i thought a lot about teaching and uh and so isaac asimov great science fiction writer has also actually spent a lot of his career writing nonfiction right his memoir is fantastic he was passionate about explaining things right he wrote all kinds of books on all kinds of topics in science he was known as the great explainer and some you know i i do really resonate with his style and uh and just his way of talking about you know by communicating and explaining to something is really the way that you learn something i think i think about problems very differently because of the way i've been given the opportunity to teach them at mit and we have questions asked you know the fear of the lecture the experience of the lecture and the questions i get and the interactions just forces me to be rock solid on on these ideas in a way that i didn't have that i i don't know i would be in a different intellectual space also video does that scare you that your lectures are online and people like me and sweatpants can sit sipping coffee and watch what you give lectures that i think it's great i do think that something's changed right now which is you know right now we're giving lectures over zoom i mean giving seminars over zoom and everything um i'm trying to figure out i think it's a new medium do you think it's trying to figure out how to use it yeah i've been um i've been quite um cynical about the human to human connection over over that medium but i think that's because it's hasn't been explored fully and teaching is a different thing every lecture is a is a i'm sorry every seminar even i think every talk i give i i you know there's an opportunity to give that differently i can i can deliver content directly into your browser you have a webgl engine right there i could i can throw 3d uh content into your browser while you're listening to me right yeah and i can assume that you have a you know at least a powerful enough laptop or something to watch zoom while i'm doing that while i'm giving a lecture that that's a that's a new communication tool that i didn't have last year right and uh i think robotics can potentially benefit a lot from teaching that way we'll see it's going to be an experiment this fall i'm thinking a lot about it yeah and also like um the the length of lectures or the length of like um there's something so like i guarantee you you know it's like 80 percent of people who started listening to our conversation are still listening to now which is crazy to me but so there's a there's a patience and a interest in long-form content but at the same time there's a magic to forcing yourself to condense an idea to as short as possible uh as short as possible like clip it can be part of a longer thing but like just like really beautifully condensed idea there's a lot of opportunity there that's easier to do and remote with i don't know uh with editing too editing is an interesting thing like what uh you know most professors don't get when they give a lecture you don't get to go back and edit out parts like chris like crisp it up a little bit that's also it can do magic like if you remove like five to ten minutes from an hour lecture it can it can actually cr it can make something special of a lecture i've uh i've seen that in myself and and in others too because i edit other people's lectures to extract clips it's like there's certain tangents they're like that lose they're not interesting they're they're they're mumbling they're just not they're not clarifying they're not helpful at all and once you remove them it's just i don't know editing can be magic uh take a lot of time yeah it takes it depends like what is teaching you have to ask um yeah because i find the editing process is also beneficial as uh for teaching but also for your own learning i don't know if have you watched yourself in the survey have you watched those videos it's i mean not all of them okay it could be it could be painful yeah and to see like how to improve so do you find that i know you segment your um your podcast do you think that helps people with the the attention span aspect of it or is it segment like sections like yeah we're talking about this topic whatever no no that just helps me it's actually bad so uh and you've been incredible uh so i'm i'm learning like i'm afraid of conversation this is even today i'm terrified of talking to you i mean it's something i'm um trying to remove from myself i there's this a guy i mean i've learned from a lot of people but really um there's been a few people who's been inspirational to me in terms of conversation whatever people think of him joe rogan has been inspirational to me because comedians have been too being able to just have fun and enjoy themselves and lose themselves in conversation that requires you to be a great storyteller to be able to uh pull a lot of different pieces of information together but mostly just to enjoy yourself in conversations i'm trying to learn that these notes are you see me looking down that's like a safety blanket that i'm trying to let go of more and more cool so that's that people love just regular conversation that's what they the structure is like whatever i would say i would say maybe like 10 to like so there's a bunch of you know there's uh probably a couple thousand phd students listening to this right now right and they might know what we're talking about but there's somebody i guarantee you right now in russia some kid who's just like who's just smoke some weed is sitting back and just enjoying the hell out of this conversation not really understanding he kind of watched some boston dynamics videos he's just enjoying it um and i salute you sir uh no but just like there's a so much variety of people that just have curiosity about engineering about sciences about mathematics and um and also like i should that i mean uh enjoying it is one thing but i also often notice it inspires people to there's a lot of people who are like in their undergraduate studies trying to figure out what uh trying to figure out what to pursue and those these conversations can really spark the direction there of their life and in terms of robotics i hope it does because uh i'm excited about the possibilities for robotics brings on that topic um do you have advice like what advice would you give to a young person about life a young person about life or a young person about life and robotics uh it could be in robotics it could be in life in general it could be career it could be uh relationship advice it could be running advice just like they're um that's one of the things i see you like to talk to like 20 year olds they're they're like how do i how do i do this thing what do i do um if they come up to you what would you tell them i think it's an interesting time to be a kid these days everything points to this being sort of a winner take all economy and the like i think the people that will really excel in my opinion are going to be the ones that can think deeply about problems you have to be able to ask questions agilely and use the internet for everything it's good for and stuff like this and i think a lot of people will develop those skills i think the the leaders thought leaders you know robotics leaders whatever are going to be the ones that can do more and they can think very deeply and critically um and that's a harder thing to learn i think one one path to learning that is through mathematics through engineering i would encourage people to start math early i mean i didn't really start i mean i was always in the the better math classes that i could take but i wasn't pursuing super advanced mathematics or anything like that until i got to mit i think mit lit me up and really started the life that i'm living now but yeah i really want kids to to dig deep really understand things building things too i mean pull things apart put them back together like that's just such a good way to really understand things and expect it to be a long journey right it's uh you don't have to know everything you're never gonna know everything so think deeply and stick with it enjoy the ride but just make sure you're not um yeah just just make sure you're you're you're stopping to think about why things work yeah it's true it's uh it's easy to lose yourself in the in the in the distractions of the world we're overwhelmed with content right now but you have to stop and pick some of it and really understand yeah on the book point i've read animal farm by george orwell a ridiculous number of times so for me like that book i don't know if it's a good book in general but for me it connects deeply somehow uh it somehow connects so i was born in the soviet union so it connects to me to the entire history of the soviet union and to world war ii and to the love and hatred and suffering that went on there and the uh the corrupting nature of power and greed and just somehow i just that that that book has taught me more about life than like anything else even though it's just like a silly like childlike book about adam pigs it's like i don't know why it just connects and inspires uh the same there's a few um yeah there's a few technical books too and algorithms that just yeah you return too often right i'm i'm i'm with you uh yeah there's uh i don't and i've been losing that because of the internet i've been like uh going and i've been going on archive and blog posts and github and and the new thing and of um you lose your ability to really master an idea right wow exactly right what's a fond memory from childhood when baby russ tedrick well i guess i just said that um at least my current life begins began when i got to mit if i have to go farther than that yeah what was was there life before mit oh absolutely but but let me actually tell you what happened when i first got to mit because that i think might be relevant here but i yeah you know i i had taken a computer engineering degree at michigan i enjoyed it immensely learned a bunch of stuff i was i liked computers i liked how to like programming um but when i did get to mit and started working with sebastian sung theoretical physicist computational neuroscientist um the culture here was just different um it demanded more of me certainly mathematically and in the critical thinking and i remember the day that i uh borrowed one of the books from my advisor's office and walked down to the charles river and was like i'm getting my butt kicked you know um and i think that's going to happen to everybody who's doing this kind of stuff right i think uh i expected you to ask me the meaning of life you know i think that the uh um somehow i think that's that's gotta be part of it this doing hard things yeah did you uh did you consider quitting at any point did you consider this isn't for me no never that i mean i was it was working hard but i was loving it right there's i think the there's this magical thing where you you know i'm lucky to surround myself with people that basically almost every day i'll i'll i'll see something i'll be told something or something that i realize wow i don't understand that and if i could just understand that there's there's something else to learn that if i could just learn that thing i would connect another piece of the puzzle and and uh you know i think that is just such an important aspect and being willing to understand what you can and can't do and and loving the journey of going and learning those other things i think that's the best part i don't think there's a better way to end it or us i've um you've been an inspiration to me since i showed up at mit uh your work has been an inspiration to the world this conversation was amazing i can't wait to see what you do next with robotics home robots i i hope to see you work in my home one day thanks so much for talking today has been awesome cheers thanks for listening to this conversation with rasteric and thank you to our sponsors magic spoon serial betterhelp and expressvpn please consider supporting this podcast by going to magicspoon.com lex and using codelex at checkout going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links buy the stuff get the discount it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five stars and apple podcast support on patreon or connect with me on twitter at lex friedman spelled somehow without the e just f-r-i-d-m-a-n and now let me leave you with some words from neil degrasse tyson talking about robots in space and the emphasis we humans put on human-based space exploration robots are important if i don my pure scientist hat i would say just send robots i'll stay down here and get the data but nobody's ever given a parade for a robot nobody's ever named a high school after a robot so when i down my public educator hat i have to recognize the elements of exploration that excite people it's not only the discoveries and the beautiful photos that come down from the heavens it's the vicarious participation in discovery itself thank you for listening and hope to see you next time you |
Manolis Kellis: Human Genome and Evolutionary Dynamics | Lex Fridman Podcast #113 | the following is a conversation with manolis kellis he's a professor at mit and head of the mit computational biology group he's interested in understanding the human genome from a computational evolutionary biological and other cross-disciplinary perspectives he has more big impactful papers and awards than i can list but most importantly he's a kind curious brilliant human being and just someone i really enjoy talking to his passion for science and life in general is contagious the hours honestly flew by and i'm sure we'll talk again on this podcast soon quick summary of the ads three sponsors blinkist eight sleep and masterclass please consider supporting this podcast by going to blinkist.com lex 8sleep.com lex and signing up at masterclass.com lex click the links buy the stuff get the discount it's the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five 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that's blinkist.com lex blinkist spelled b-l-i-n-k-i-s-t this show is also sponsored by a sleep and it's pod pro mattress you can check out at asleep.com lex to get 200 off it controls temperature with a nap it can cool down to as low as 55 degrees on each side of the bed separately research shows the temperature has a big impact on the quality of our sleep anecdotally has been true for me it's truly been a game changer i love it the pod pro is packed with sensors that track heart rate heart rate variability and respiratory rate showing it all in their app the app's health metrics are amazing but the cooling alone is honestly worth the money check it out at asleep.com lex to get 200 off this show is also sponsored by masterclass sign up at masterclass.com lex to get a discount and to support this podcast when i first heard about masterclass i thought it was too good to be true for 180 bucks a year you get an all-access pass to watch courses from to list some of my favorites chris hadfield on space exploration neil degrasse tyson on scientific thinking and communication will wright one of my favorite game designers carlos santana one of my favorite guitar players gary kasparov of course the greatest chess player of all time i'm not biased daniel negrano on poker and many more chris hadfield explaining how rockets work and the experience of being launched into space alone is worth the money by the way you can watch it on basically any device once again sign up at masterclass.com lex to get a discount and to support this podcast and now here's my conversation with manolis kellis what to use the most beautiful aspect of the human genome don't get me started so we got time um the first answer is that the beauty of genomes transcends humanity so it's not just about the human genome genomes in general are amazingly beautiful and again i'm obviously biased so um in my view uh the way that i like to introduce the human genome and the way that i'd like to introduce genomics to my class is by telling them you know we're not the inventors of the first digital computer we are the descendants of the first digital computer basically life is digital and that's absolutely beautiful about life the fact that at every replication step you don't lose any information because that information is digital if it was analog it was just protein concentrations you'd lose it after a few generations it would just dissolve away and that's what the ancients didn't understand about inheritance the first person to understand digital inheritance was mendel of course and his theory in fact stayed in a bookshelf for like 50 years while darwin was getting famous about natural selection but the missing component was this digital inheritance the mechanism of evolution that mendel had discovered so that aspect in my view is the most beautiful aspect but it transcends all of life and can you elaborate maybe the inheritance part what was the what was the key thing that the ancients didn't understand so the very theory of inheritance uh as discrete units you know throughout the life of mendel and well after his writing people thought that his p experiments were just a little fluke that they were just you know a little exception that would normally not even apply to humans that basically what they saw is this continuum of eye color this continuum of skin color this continuum of hair color this continuum of height and all of these continuums did not fit with a discrete type of inheritance that mendel was describing but what's unique about genomics and what's unique about the genome is really that there are two copies and that you get a combination of these but for every trait there are dozens of contributing variables and it was only ronald fisher in the 20th century that basically recognized that even five mendelian traits would add up to a continuum-like inheritance pattern and he you know wrote a series of papers that still are very relevant today about sort of this mendelian inheritance of continuum like traits and i think that that was the missing step in inheritance so well before the discovery of the structure of dna which is again another amazingly beautiful aspect the double helix what i like to call the most noble molecule over time is uh you know holds within it the secret of that discrete inheritance but the conceptualization of discrete you know elements is something that precedes that so even though it's discrete when it uh materializes itself into actual traits that we see it can be continuous it can basically arbitrarily rich and complex so if you have five genes that contribute to human height and there aren't five there's a thousand if there's only five genes and you inherit some combination of them and everyone makes you two inches taller or two inches shorter it'll look like a continuum trait a continuous trait but instead of five there are thousands and every one of them contributes to less than one millimeter we change in height more during the day than each of these genetic variants contributes so by the evening you're shorter than you were you woke up with isn't it weird then that we're not more different than we are why are we all so similar if there's so much possibility to be different yeah so so there are selective advantages to being medium if you're extremely tall or extremely short you run into selective disadvantages so you have trouble breathing you have trouble running you have trouble sitting if you're too tall if you're too short you might i don't know have other selective pressures are acting against that if you look at natural history of human population there's actually selection for height in northern europe and selection against height in southern europe so there might actually be advantages to actually being not not super tall and if you look across the entire human population you know for many many traits there's a lot of push towards the middle uh balancing selection is you know the usual term for selection that sort of seeks to not be extreme and to sort of have a combination of alleles that sort of you know keep recombining and if you look at you know mate selection super super tall people will not tend to sort of marry super super tall people very often you see these couples that are kind of compensating for each other and the best predictor of the kids age is very often just take the average of the two parents and then adjust for sex and boom you get it it's extremely heritable let me ask uh you kind of uh took a step back to the genome outside of just humans but is there something that you find beautiful about the human genome specifically so i think that genome if more people understood the beauty of the human genome there would be so many fewer wars so much less anger in the world i mean what's really beautiful about the human genome is really the variation that teaches us both about individuality and about similarity so any two people on the planet are 99.9 identical how can you fight with someone who's 99.9 identical to you it's just counterintuitive and yet any two siblings of the same parent differ in millions of locations so every one of them is basically two to the million unique from any pair of parents let alone any two random parents on the planet so that's i think something that teaches us about sort of the nature of humanity in many ways that every one of us is as unique as any star and way more unique in actually many ways and uh yet we're all brothers and sisters and yeah just like stars most of it is just uh fusion uh reactions yeah you only have a few parameters to describe stars you know mass size initial size and you know stage of life whereas for humans it's you know thousands of parameters scattered across our genome so the other thing that makes humans unique the other things that makes inheritance unique in humans is that most species inherit things vertically basically instinct is a huge part of their behavior the way that you know i mean with my kids we've been watching this nest of birds with two little eggs you know outside our window for the last few months uh for the last few weeks as they've been growing and there's so much behavior that's hard-coded birds don't just learn as they grow they don't you know there's no culture like a bird that's born in boston will be the same as a bird that's born in california so there's not as much um inheritance of ideas of customs a lot of it is hard-coded in their genome what's really beautiful about the human genome is that if you take a person from today and you place them back in ancient egypt or if you take a person from ancient egypt and you place them here today they will grow up to be completely normal that is not genetics this is the other type of inheritance in humans so on one hand we have genetic inheritance which is vertical from your parents down on the other hand we have horizontal inheritance which is the ideas that are built up at every generation are horizontally transmitted and the huge amount of time that we spend in educating ourselves a concept known as niotini neo for newborn and then tenney for holding so if you look at humans i mean the little birds they were you know eggs two weeks ago and that now one of them has already flown off the other one's ready to fly off in two weeks they're ready to just fend for themselves humans 16 years 18 years 24 getting out of college i'm still learning so so that's so fascinating the this picture of a vertical in the horizontal i when you talk about the horizontal is it in the realm of ideas exactly okay so it's the actual social interactions and that's exactly right that's exactly right so basically the concept of neotimi is that you spend acquiring characteristics from your environment in an extremely malleable state of your brain and the wiring of your brain for a long period of your life compared to primates we are useless you take any primate at seven weeks and in human at seven weeks we lose the battle but at eighteen years you know all bets are off like we basically our brain continues to develop in an extremely malleable form until very late and this is what allows education this is what allows the person from egypt to do extremely well now and the reason for that is that the wiring of our brain and the development of that wiring is actually delayed so you know the longer you delay that the more opportunity you have to pass on knowledge to pass on concepts ideals ideas from the parents to the child and what's really absolutely beautiful about humans today is that that lateral transfer of ideas and culture is not just from uncles and aunts and teachers at school but it's from wikipedia and review articles on the web and thousands of journals that are sort of putting out information for free and podcasts and videocasts and all of that stuff where you can basically learn about any topic pretty much everything that would be in any super advanced textbook in a matter of days instead of having to go to the library of alexandria and sail there to read three books and then sail for another few days to get to athens and et cetera et cetera so the democratization of knowledge and the spread the speed of spread of knowledge is what defines i think the human inheritance pattern so you sound excited about it about it are you also a little bit afraid or you're more excited by the power of this kind of distributed spread of information so you put it very kindly that most people are kind of using the internet in uh you know looking wikipedia reading articles reading papers and so on but uh if we if we're honest most people online especially when they're younger probably looking at five second clips on tick tock or whatever the new social network is are you um given this power of horizontal inheritance are you optimistic or a little bit pessimistic about the this new effect of the internet and democratization of knowledge on our on our what would you call this this geno like would you would you use the term genome by the way yeah i think um you know we use the genome to talk about dna but very often we say you know i mean i'm greek so people ask me hey what's in the greek genome and i'm like well yeah what's in the greek genome is both our genes and also our ideas and our ideals and our culture so the poetic meaning of the word exactly exactly yeah yeah so i think that um there's a beauty to the democratization of knowledge the fact that you can reach as many people as you know any other person on the planet and it's not who you are it's really your ideas that matter is a beautiful aspect of the internet the [Music] i think there's of course a danger of my ignorance is as important as your expertise the fact that uh with this democratization comes the abolishment of respecting expertise just because you've spent you know 10 000 hours of your life studying i don't know human brain circuitry why should i trust you i'm just going to make up my own theories and they'll be just as good as yours it's an attitude that that sort of counteracts the beauty of the democratization and i think that within our educational system and within the upbringing of our children we have to not only teach them knowledge but we have to teach them the means to get to knowledge and that you know it's very similar to sort of you fish you catch a fish for a man for one day you fed them for one day you teach them how to fish you fed them for the rest of their life so instead of just gathering the knowledge they need for any one task we can just tell them all right here's how you google it here's how to figure out what's real and what's not here's how you check the sources here's how you form a basic opinion for yourself and i think that inquisitive nature is paramount to being able to sort through this huge wealth of knowledge so you need a basic educational foundation based on which you can then add on the sort of domain specific knowledge but that basic educational foundation should just just not just be knowledge but it should also be epistemology the way to acquire knowledge i'm not sure any of us know how to do that in this modern day we're actually learning one of the big surprising thing to me about the the coronavirus for example is that twitter has been one of the best sources of information basically like building your own network of experts of of uh you know as opposed to the traditional centralized expertise of the who and the cdc and the or um or maybe any one particular respectable person at the top of a department in some kind of institution you instead look at a you know 10 20 hundreds of people some of whom are young kids with just that are incredibly good at aggregating data and plotting and visualizing that data that's been really surprising to me i don't know what to make of it i don't know i don't know how that matures into something stable you know i don't know if you have ideas like what if you were to try to explain to your kids of how where should you go to learn about the about coronavirus what would you say it's such a beautiful example and i think uh the current pandemic and the the speed at which the scientific community has moved in the current pandemic i think exemplifies this horizontal transfer and the speed of horizontal transfer of information the fact that you know the genome was first sequenced in early january the first sample was obtained december 29 2019 a week after the publication of the first genome sequence moderna had already finalized his vaccine design and was moving to production i mean this is uh phenomenal the fact that we go from not knowing what the heck is killing people in wuhan to wow it's starscore v2 and here's the set of genes here's the genome here's the sequence here the polymorphisms et cetera in the matter of weeks is phenomenal in that incredible pace of transfer of knowledge there have been many mistakes so you know some of those mistakes may have been politically motivated our other mistakes may have just been innocuous errors others may have been misleading the public for the greater good such as don't wear masks because we don't want the mask to run out i mean that was very silly in my view and a very big mistake but the the spread of knowledge from the scientific community was phenomenal and some people will point out to bogus articles that snuck in and made the front page yeah they did but within 24 hours they were debunked and went out of the front page and i think that's that's the beauty of science today the fact that it's not oh knowledge is fixed it's the ability to embrace that nothing is permanent when it comes to knowledge that everything is the current best hypothesis and the current best model that best fits the current data and the willingness to be wrong the expectation that we're going to be wrong and the celebration of success based on how long was i not proven wrong for rather than wow i was exactly right because no one is going to be exactly right with partial knowledge but the arc towards perfection i think so much more important than how far you are on your first step and i think that's what sort of the current pandemic has taught us the fact that yeah no of course we're gonna make mistakes but at least we're going to learn from those mistakes and become better and learn better and spread information better so if i were to answer the question of where would you go to learn about coronavirus first textbook it all starts with a textbook just open up a chapter on virology and how coronaviruses work then some basic epidemiology and sort of how pandemics have worked in the past what are the basic principles surrounding these first wave second wave why do they even exist then understanding about growth understanding about the are not and rt at you know various time points and then understanding the means of spread how it spreads from person to person then how does it get into your cells from when it gets into the cells what are the paths that it takes what are the cell types that express the particular h2 receptor how is your immune system interacting with the virus and once your immune system launches your defense how is that helping or actually hurting your health what about the cytokine storm what are most people dying from why are the comorbidities and these risk factors even applying what makes obese people respond more or elderly people respond more to the virus while kids are completely you know you know very often not even aware that they're spreading it so the you know i think there's some basic questions that you would start from and then i'm sorry to say but wikipedia is pretty awesome yeah google is pretty awesome so it used to be a time it used to be a time maybe five years ago i forget i forget when but people kind of made fun of wikipedia for being an unreliable source i never quite understood it i thought from the early days it was pretty reliable or better than a lot of the alternatives but at this point it's kind of like a solid accessible survey paper on every subject ever the there's an ascertainment bias and a writing bias so so i think this this is related to sort of people saying oh so many nature papers are wrong and they're like why would you publish in nature so many nature papers are wrong and my answer is no no no so many nature papers are scrutinized and just because more of them are being proven wrong than in other articles is actually evidence that they're actually better papers overall because they're being scrutinized at a rate much higher than any other journal so if you basically uh judge wikipedia by not the initial content by but by the number of revisions yeah then of course it's going to be the best source of knowledge eventually it's still very superficial you then have to go into the review papers etc etc but i mean for most scientific project topics it's extremely superficial but it is quite authoritative because it is the place that everybody likes to criticize you as being wrong you say that it's superficial on a lot of topics that i'm i've studied a lot of i find it i don't know if superficial is the right word um because superficial kind of implies that it's not correct no no i don't mean any implication of it not being correct it's just superficial it's basically only scratching the surface for depth you don't go to wikipedia you go to the review articles but it can be profound in the way that articles rarely one of the frustrating things to me about like certain computer science like in the machine learning world articles they they don't as often take the uh the bigger picture view you know there's a it's a kind of data set and you show that it works and you kind of show that here's an architectural thing that creates an improvement and so on and so forth but you don't say well like what does this mean for the nature of intelligence for future data sets we haven't even thought about or if you were trying to implement this like if we took this data set of uh a hundred thousand examples and scaled it to a hundred billion examples with this method like like look at the bigger picture which is what a wikipedia article would actually try to do which is like what does this mean in the context of computer the broad field of computer vision or something like that yeah yeah and no i i agree with you completely like but it depends on the topic i mean for some topics there's been a huge amount of work for other topics it's just a stub so you know i got it yeah well yeah actually the uh which we'll talk on genomics was not yeah it's great very shallow yeah yeah it's not wrong it's just shallow yeah every time i criticize something i should feel partly responsible basically if more people from my community went there and edited it would not be shallow it's just that there's different modes of communication in different fields and in some fields the experts have embraced wikipedia in other fields it's relegated and perhaps the reason is that if it was any better to start with people would invest more time but if it's not great to start with then you need a few initial pioneers who will basically go in and say ah enough we're just going to fix that and then i think it'll catch on much more so if it's okay before we go on to genomics can we linger a little bit longer on the beauty of the human genome you've given me a few notes what else what else do you find beautiful about the human genome so the last aspect of what makes a human genome unique in addition to the you know similarity and the differences and individuality is that so very early on people would basically say oh you don't do that experiment in human you have to learn about that in fly or you have to learn about that in yeast first or in mouse first or in a prime at first and the human genome was in fact relegated to sort of oh the last place that you you're going to go to learn something new that has dramatically changed and the reason that changed is human genetics we are these species in the planet that's the most studied right now it's embarrassing to say that but this was not the case a few years ago it used to be you know first viruses then bacteria then yeast then the fruit fly and the worm then the mouse and eventually human was very far last so it's embarrassing that it took us this long to focus on it or the uh it's embarrassing that the model organisms have been taken over because of the power of human genetics that right now it's actually simpler to figure out the phenotype of something by mining this massive amount of human data than by going back to any of the other species and the reason for that is that if you look at the natural variation that happens in a population of 7 billion you basically have a mutation in almost every nucleotide so every nucleotide you want to perturb you can go find a living breathing human being and go test the function of that nucleotide by sort of searching the database and finding that person wait why is that embarrassing it's a beautiful data set it's embarrassing for the for the model organism for the flies yeah exactly i i mean do you do you feel on a small tangent is there something of value in um in the genome of a fly and other these model organisms that you miss that we wish we would have uh would be looking at deeper so directed perturbation of course so i think the place where the the place where humans are still lagging is the fact that in an animal model you can go and say well let me knock out this gene completely and let me knock out these three genes completely and i said the moment you get into combinatorics it's something you can't do in the human because there just simply aren't enough humans on the planet and again let me be honest we haven't sequenced all seven billion people it's not like we have every mutation but we know that there's a carrier out there so if you look at the trend with and the speed with which human genetics has progressed we can now find thousands of genes involved in human cognition in human psychology in the emotions and the feelings that we used to think are uniquely learned turns out there's a genetic basis to a lot of that so the uh you know the the human genome has continued to elucidate through these studies of genetic variation so many different processes that we previously thought were you know something that like free will free will is this beautiful concept that humans have had for a long time you know in the end it's just a bunch of chemical reactions happening in your brain and the particular abundance of receptors that you have this day based on what you ate yesterday or that you have been wired with based on you know your parents and your upbringing etc determines a lot of that quote unquote free will component to you know sort of narrower and narrower scale you know sort of slices so how much uh on that point how much freedom do you think we have to escape the the constraints of our genome you're making it sound like more and more we're discovering that our genome is actually has the a lot of the story already encoded into it how much freedom do we have i uh so so let me let me describe what that freedom would look like that freedom would be my saying oh i'm gonna resist the urge to eat that apple because i choose not to but there are chemical receptors that made me not resist the urge to prove my individuality and my free will by resisting the apple so then the next question is well maybe now i'll resist the urge to resist the apple and i'll go for the chocolate instead to prove my individuality but then what about those other receptors that you know that that might be all encoded in there so it's kicking the bucket down the road and basically saying well your choice will may have actually been driven by other things that you actually are not choosing so that's why it's very hard to answer that question well it's hard to know what to do with that i mean if uh if the genome has if there's not much freedom it's uh it's the butterfly effect it's basically that in the short term you can predict something extremely well by knowing the current state of the system but a few steps down it's very hard to predict based on the current knowledge is that because the system is truly free when i look at weather patterns i can predict the next 10 days is it because the weather it has a lot of freedom and after 10 days it chooses to do something else or is it because in fact the system is fully deterministic and there's just a slightly different magnetic feel of the earth slightly more energy arriving from the sun a slightly different spin of the gravitational pull of jupiter that is now causing you know all kinds of tides and slight deviation of the moon etc maybe all of that can be fully modeled maybe the fact that china is emitting a little more carbon today is actually going to affect the weather in you know egypt in three weeks and all of that could be fully modeled in the same way if you take a complete view of a human being now you know i model everything about you the question is can i predict your next step probably but at how far and if it's a little further is that because of stochasticity and sort of chaos properties of unpredictability of beyond a certain level or was that actually true free will yeah then yeah so the number of variables might might be so you might need to uh build an entire universe to uh to be able to simulate a human and then maybe that human will be fully simulatable but maybe aspects of free will will exist and where's that free will coming from it's still coming from the same neurons or maybe from a spirit inhabiting these neurons but again you know it's very difficult empirically to sort of evaluate where does free will begin and sort of chemical reactions and electric signals and you know and so on that's on that topic let me ask the most absurd question uh that uh most mit faculty role their eyes on but uh do what do you think about the simulation hypothesis and the idea that we live in a simulation i think it's complete bs okay there's no empirical evidence no it's not absolutely not not in terms of empirical evidence or not but uh in terms of a thought experiment does it help you think about the universe i mean so if you look at the genome it's encoding a lot of the information that is required to create some of the beautiful human complexity that we see around us it's an interesting thought experiment how much you know uh parameters do we need to um have in order to model some you know this full human experience like if we were to build a video game yeah how hard it would be to build a video game that's like convincing enough and fun enough and you know uh it has consistent laws of physics all that stuff it's not interesting to use the stock experiment i i mean it's cute but you know it's all comes razor i mean what's what's more realistic the fact that you're actually a machine or that you're you know a person what's what's you know the fact that all of my experiences exist inside the chemical molecules that i have or that somebody's actually you know simulating all that i mean well you did refer to humans as a digital computer earlier so of course of course but that's not kind of a machine right i know i know but i i think the probability of all that is nil and let the machines wake me up and just terminate me now if it's not i challenge your machines they're gonna they're gonna wait a little bit to see what you're gonna do next it's fun it's fun to watch especially the clever humans what's the difference to you between the way a computer stores information and uh the human genome stores information so you also have roots and your work would you say you're when you introduce yourself at a bar um it depends who i'm talking would you say it's computational biology do you um do you reveal uh your expertise in computers it depends who i'm talking to truly i mean basically if i meet someone who's in computers i'll say oh i mean professor in computer science if i meet someone who's in engineering i say computer science and electrical engineering if i meet someone in biology i'll say hey i work in genomics if i meet someone in medicine i'm like hey i work on you know genetics so you're a fun person to meet at a bar i got you but so no no but i'm trying to say is that i i don't i mean there's no single attribute that i will define myself as you know there's a few things i know there's a few things i study there's a few things i have degrees on and there's a few things that i grant degrees in and you know i i publish papers across the whole gamut you know the whole spectrum of computation to biology etc i mean i the complete answer is that i use computer science to understand biology so i'm a you know i develop methods in ai and machine learning statistics and algorithms etc but the ultimate goal of my career is to really understand biology if these things don't advance our understanding of biology i'm not as fascinated by them although there are some beautiful computational problems by themselves i've sort of made it my mission to apply the power of computer science to truly understand the human genome health disease you know and then the whole gamut of how our brain works how our body works and all of that which is so fascinating so the dream there's not an equivalent sort of uh complementary dream of understanding human biology in order to create an artificial life an artificial brain artificial intelligence that supersedes the intelligence and the capabilities of us humans it's an interesting question it's a fascinating question so understanding the human brain is undoubtedly coupled to how do we make better ai because so much of ai has in fact been inspired by the brain it may have taken 50 years since the early days of neural networks till we have you know all of these amazing progress that we've seen with uh you know deep belief networks and uh you know all of these advances in go and chess in image synthesis and deep vagues in you name it and but but the underlying architecture is very much inspired by the human brain which actually pauses a very very interesting question why are neural networks performing so well and they perform amazingly well is it because they can simulate any possible function and the answer is no no they simulate a very small number of functions is it because they can simulate every possible function in the universe and that's where it gets interesting the answer is actually yeah a little closer to that and here's where it gets really fun uh if you look at human brain and human cognition it didn't evolve in a vacuum it evolved in a world with physical constraints like the world that inhabits us it is the world that we inhabit and if you look at our senses what do they perceive they perceive different you know parts of the electromagnetic spectrum you know the hearing is just different movements in air the the touch etc i mean all of these things we've built intuitions for the physical world that we inhabit and our brains and the brains of all animals evolved for that world and the ai systems that we have built happen to work well with images of the type that we encounter in the physical world that we inhabit whereas if you just take noise and you add random signal that doesn't match anything in our world neural networks will not do as well and that actually um basically has this whole loop around this which is this was designed by studying our own brain which was evolved for our own world and they happen to do well in our own world and they happen to make the same types of mistakes that humans make many times and of course you can engineer images by adding just the right amount of you know sort of pixel deviations to make a zebra look like a bamboo and stuff like that or like a table but ultimately the undoctored images at least are very often you know mistaken i don't know between muffins and dogs for example in the same way that humans make those mistakes so it's it's on you know there's no doubt in my view that the more we understand about the tricks that our human brain has evolved to understand the physical world around us the more we will be able to bring new computational primitives in our ai systems to again better understand not just the world around us but maybe even the world inside us and maybe even the computational problems that arise from new types of data that we haven't been exposed to but are yet inhabiting the same universe that we live in with a very tiny little subset of functions from all possible mathematical functions yeah and that small subset of functions all that matters to us humans really that's what makes it's all that has mattered so far and even within our scientific realm it's all that seems to continue to matter but i mean i always like to think about our senses and how much of the physical world around us we perceive and if you look at the um ligo experiment over the last you know year and a half has been all over the news what what did lago do it created a new sense for human beings a sense that has never been sensed in the history of our planet gravitational waves have been traversing the earth since its creation a few billion years ago life has evolved senses to sense things that were never before sensed light was not perceived by early life no one cared and eventually photoreceptors evolved and you know the ability to sense colors by sort of catching different parts of that electromagnetic spectrum and hearing evolved and touch evolved etc but no organism evolved a way to sense neutrinos floating through earth or gravitational waves flowing through earth etc and i find it so beautiful in the history of not just humanity but life on the planet that we are now able to capture additional signals from the physical world than we ever knew before and axions for example have been all over the news in the last few weeks the concept that we can capture and perceive more of that physical world is as exciting as the fact that we are we were blind to it is traumatizing before right because that also tells us how you know we're in 2020 picture yourself in 30 20 or in 20 you know what new senses why might we discover is it you know could it be that we're missing physics that like there's a lot of physics out there that we're just blind to completely oblivious to it yeah and yet they're permeating us all the time yes it might be right in front of us so so when you're thinking about premonitions yeah yeah a lot of that is ascertainment bias like yeah every you know every now and then you're like oh i remember my friend and then my friend doesn't appear and i'll forget that i remember my friend but every now and then my friend will actually appear i'm like oh my god i thought about you a minute ago you just called me that's amazing so you know some of that is this but some of that might be that there are within our brain sensors for waves that we emit that we're not even aware of and this whole concept of when i hug my children there's such an emotional transfer there that we don't comprehend i mean sure yeah of course we're all like hardwired for all kinds of touchy-feely things between parents and kids it's beautiful between partners it's beautiful etc but then there are intangible aspects of human communication that i don't think it's unfathomable that our brain has actually evolved ways and sensors for it that we just don't capture we don't understand the function of the vast majority of our neurons and maybe our brain is already sensing it but even worse maybe our brain is not sensing it at all and we're in oblivious to this until we build a machine that suddenly is able to sort of capture so much more of what's happening in the natural world so what you're saying is we're going physics is going to discover a sensor for love for and maybe maybe dogs are off scale for that and we've been oh you know we've been oblivious to it the whole time because we didn't have the right answer yeah and now you're gonna have a little wrist that says oh my god i feel all this love in the house i see i sense a disturbance in the force all around us and dogs and cats will have zero none none but let's take a step back to our unfortunately one of the 400 topics that we had actually planned [Laughter] but to our sad time in 2020 when we only have just a few sensors and uh very primitive early computers so in your you you have a foot in computer science and a floating biology in your sense how do computers represent information differently than like the genome or biological systems so first of all let me uh let me uh correct that no we're in an amazing time in 2020 computer science is totally awesome and physics is totally awesome and we have understood so much of the natural world than ever before so i am extremely grateful and feeling extremely lucky to be living in the time that we are because you know first of all who knows when the asteroid will hit [Laughter] and second um you know of all times in humanity this is probably the best time to be a human being and this might actually be the best place to be a human being so anyway you know for for anyone who loves science this is this is it this is awesome it's a great time at the same time just a swift comment all i meant is that uh if we look several hundred years from now and we end up somehow not uh destroying the uh ourselves yeah people will probably look back at this time in computer science and uh at your work of minos at mit i like to joke very often with my students that you know we've written so many papers we've published so much we've been cited so much and every single time i tell my students you know the best is ahead of us what we're working on now is the most exciting thing i've ever worked on so in a way i do have this sense of yeah even the papers i wrote 10 years ago they were awesome at the time but i'm so much more excited about where we're heading now and i don't mean to minimize any of the stuff we've done in the past but you know there's just this sense of excitement about what you're working on now that as soon as a paper is submitted it's like ugh it's old like you know i can't talk about that anymore at the same time you're not you probably are not going to be able to predict what are the most uh impactful papers and ideas when people look back 200 years from now at your work what would be the most exciting papers and it may very well be not the thing that you expected or yeah the things you got awards for or you know this might be true in some fields i don't know i feel slightly differently about it in our field i feel that i kind of know what what are the important ones and there's a very big difference between what the press picks up on and what's actually fundamentally important for the field and i think for the fundamentally important ones we kind of have a pretty good idea what they are and it's hard to sometimes get the press excited about the fundamental advances but you know we we take what we get and celebrate what we get and sometimes you know one of our papers which was in a minor journal made the front page of reddit and suddenly had like hundreds of thousands of views even though it wasn't a minor journal because you know somebody pitched it the right way that it suddenly caught everybody's attention whereas other papers that are sort of truly fundamental you know we have a hard time getting the editors even excited about them when so many hundreds of people are already using the results and building upon them so i do i do appreciate that there's a discrepancy between the perception and the perceived success and the awards that you get for various papers but i think that fundamentally and know that you know some people i'm so so so when you're writing that you're most proud you know you just you trapped yourself no no no no i mean is there a line of work that you you have a sense uh is really powerful that you've done today you've done so much work in so many directions which is interesting um is there something where you you think is quite special i i mean it's like asking me to say which of my three children i love best i mean exactly so i mean and it's such a give me question that it's so so difficult not to brag about the awesome work that my team and my students have done um and i'll i'll just mention a few of the top of my head i mean basically there's a few landmark papers that i think have shaped my scientific path and you know i like to somehow describe it as a linear continuation of one thing led to another led to another led to another and you know it kind of all started with skip skip skip skip skip let me try to start somewhere in the middle so my first phd paper was uh the first comparative analysis of multiple species so multiple complete genomes so for the first time we we basically con developed the concept of genome-wide evolutionary signatures the fact that you could look across the entire genome and understand how things evolve and from these signatures of evolution you could go back and study any one region and say that's a protein coding gene that's an rna gene that's a regulatory motif that's a you know binding site and so forth so sorry so comparing different different species of the same so so i think human mouse rat and dog you know they're all animals they're all mammals they're all performing similar functions with their heart with their brain with their lungs etc etc so there's many functional elements that make us uniquely mammalian and those mammalian elements are actually conserved 99 of our genome does not code for protein one percent codes for protein the other 99 we frankly didn't know what it does until we started doing these comparative genomic studies so basically these series of papers in in my career have basically first developed that concept of evolutionary signatures and then apply them to yeast apply them to flies apply them to four mammals apply them to 17 fungi apply them to 12 drosophila species apply them to them 29 mammals and now 200 mammals so sorry so can we so the evolutionary signatures this seems like a such a fascinating idea uh and we're probably gonna linger in your early phd work for two hours but uh what is how can you reveal something interesting about the genome by looking at the uh multiple multiple species and looking at the evolutionary signatures yeah like so so um you basically uh align the matching regions so everything evolved from a common ancestor way way back and mammals evolved from a common ancestor about 60 million years back so after you know the meteor that killed off the dinosaurs landed a legend near machu picchu we know the crater it didn't allegedly land that was the aliens okay no just slightly north of machu picchu in the gulf of mexico there's a giant hole that that meteorite by the way sorry is that uh definitive to people have people um um conclusively uh figured out what killed the dinosaurs i think so so it was media well you know for volcanic activity all kinds of other stuff is coinciding but the meteor is pretty unique and we know how terrifying i wouldn't if i we still have a lot of 20 20 left so if i think no no but think about it this way so the the dinosaurs ruled the earth for 175 million years we humans have been around for what less than one million years if you're super generous about what you call humans and you include gems basically so so uh we are just getting warmed up and you know we've ruled the planet much more ruthlessly than tyrannosaurus rex [Laughter] t-rex had much less of an environmental impact than we did yeah and um if you if you give us another 154 million years you know humans will look very different if we make it that far so i think dinosaurs basically are much more of life history on earth than we are in all respects but look at the bright side when they were killed off another life form emerged mammals and that's that whole the evolutionary uh branching that's happened so you you kind of have uh when you have these evolutionary signatures you see is there basically a map of how the genome changed yeah exactly exactly so now you can go back to this early mammal that was hiding in caves and you can basically ask what happened after the dinosaurs were wiped out a ton of evolutionary niches opened up and the mammals started populating all of these niches and in that diversification there was room for expansion of new types of functions so some of them populated the air with bats flying a new evolution of light some populated the oceans with dolphins and whales going off to swim etc but we all are fundamentally mammals so you can take the genomes of all these species and align them on top of each other and basically create nucleotide resolution correspondences what my phd work showed is that when you do that when you line up species on top of each other you can see that within protein coding genes there's a particular pattern of evolution that is dictated by the level at which evolutionary selection acts if i'm coding for a protein and i change the third codon position of a triplet that codes for that amino acid the same amino acid will be encoded so that basically means that any kind of mutation that preserves that translation that is invariant to that ultimate functional assessment that evolution will give is tolerated so for any function that you're trying to achieve there's a set of sequences that encode it you can now look at the mapping the you know graph isomorphism if you wish between all of the possible dna encodings of a particular function and that function and instead of having just that exact sequence at the protein level you can think of the set of protein sequences that all fulfill the same function what's evolution doing evolution has two components one component is random blind and stupid mutation the other component is super smart ruthless selection that's my mom calling from greece yes i might be a fully grown man [Laughter] did you just cancel the call wow i know i'm in trouble she's gonna be calling the cops [Laughter] so so yeah so there's a lot of encoding for the same kind of function yeah so so you now have this mapping between all of the set of functions that could all encode the same all of the set of sequences that can all encode the same function what evolutionary signatures does is that it basically looks at the shape of that distribution of sequences that all encode the same thing and based on that shape you can basically say ooh proteins have a very different shape than rna structures than regulator motifs etc so just by scanning a sequence ignoring the sequence and just looking at the patterns of change i'm like wow this thing is evolving like a protein and that thing is evolving like a motif and that thing is evolving so that's exactly what we just did for covid so our paper that we posted about our archive about coronavirus basically took this concept of evolutionary signatures and applied it on the sarsko v2 genome that is responsible for the carbon-19 pandemic uh and comparing it to 44 cerbicovirus species so this is the beta word did you just use cervical sarbic virus sars related beta corona virus it's a port ponto so that one family of viruses yeah so it was that family by the way we have 44 species that or 24 species in the fam yeah virus is a clever no no but but there's just 44 and again we don't call them species in in viruses we call them strange but anyway there's 44 strains and that's a tiny little subset of you know maybe another 50 strains that are just far too distantly related most of those only infect bats as the host and a subset of only four or five have ever infected humans and we basically took all of those and we aligned them in the same exact way that we've aligned mammals and then we looked at what proteins are you know which of the currently hypothesized genes for the coronavirus genome are in fact evolving like proteins and which ones are not and what we found is that orf10 the last little open reading frame the last little gene in the genome is bogus that's not a protein at all what is it it's an rna structure that doesn't have a it doesn't get translated into amino acids and that's so it's important to narrow down to basically discover what's useful and what's not exactly basically what are what is even the set of genes the other thing that these evolutionary signatures showed is that within or 3a lies a tiny little additional gene encoded within the other gene so you can translate a dna sequence in three different reading frames if you start in the first one it's you know atg et cetera if you start on the second it's tgc etc and with there's a there's a gene within a gene so there's a whole other protein that we didn't know about that might be super important so we don't even know the building blocks of sarsko v2 so if we want to understand coronavirus biology and eventually find it successfully we need to even have the set of genes and and these evolutionary signatures that are developed in my phd work we just recently used you know what let's uh let's run with that tangent for a little bit if it's okay uh is uh can we talk about uh the the kovic 19 a little bit more like how what's your sense about the the genome the proteins the functions that we understand about covet 19 where do we stand in in your sense what are the big open problems and and also you know you you kind of said it's important to understand what are the like the the important proteins and like why is that important so what else does the comparison of these species tell us what it tells us is how fast are things evolving it tells us about at what level is the acceleration or deceleration pedal set for every one of these proteins so the genome has you know 30 some genes some genes evolve super super fast others evolve super super slow if you look at the polymerase gene that basically replicates the genome that's a super slow evolving one if you look at the nuclear capsid protein that's also super slow evolving if you look at the spike one protein this is the part of the spike protein that actually touches the h2 receptor and then enables the virus to attach to your cells that's the thing that gives it that that visual yeah the corona look basically the coronal look yeah so basically the spike protein sticks out of the virus and there's a first part of the protein s1 which basically attaches to the h2 receptor and then s2 is the latch that sort of pushes and channels the fusion of the membranes and then the incorporation of the um viral rna inside our cells which then gets translated into all of these 30 proteins so the s1 protein is evolving ridiculously fast so if you look at the stop professor's gas pedal the gas pedal is all the way down or 8 is also evolving super fast and or six is evolving super fast we have no idea what they do we have some idea but nowhere near what s1 is so what the isn't that terrifying that s1 is evol that means that's a really useful function and if it's evolving fast doesn't that mean new strains could be created or it does something that means that it's searching for how to match how to best match the host so basically anything in in general in evolution if you look at genomes anything that's contacting the environment is evolving much faster than anything that's internal and the reason is that the environment changes so if you look at um the evolution of these cervical viruses the s1 protein has evolved very rapidly because it's attaching to different hosts each time we think of them as bats but there's thousands of species of bats and to go from one species of bat to another species of bat you have to adjust one to the new ace2 receptor that you're going to be facing in that new species sorry quick tangent yeah is it fascinating to you that viruses are doing this i mean it feels like they're this intelligent organism i mean is it like does that give you pause how incredible it is that they're the the evolutionary dynamics that you're describing is actually happening and they're freaking out figuring out how to jump from bass to humans all in this distributed fashion and then most of us don't even say they're alive or intelligent whatever so intelligence is in the eye of the beholder you know stupid is a stupid dose as forest gum would say yes and intelligence is as intelligent does so basically if the virus is finding solutions that we think of as intelligent yeah it's probably intelligent but that's again in the eye of the beholder do you think viruses are intelligent of course not really no because so incredible so remember remember when i was talking about the two components of evolution one is the stupid mutation yeah which is completely blind and the other one is the super smart selection which is ruthless so it's not viruses who are smart it's this component of evolution that's smart so it's evolution that that sort of appears smart and how is that happening by huge parallel search across thousands of you know parallel infections throughout the world right now yes but so to perfect on that so yes so then the the intelligence is in the mechanism but then uh by that argument uh viruses would be more intelligent because there's just more of them so the search they're basically the the brute force search that's happening with viruses because there's so many more of them than humans then they're taken as a whole are more intelligent i mean so you don't think it's possible that i i mean who runs would we even be here with if viruses weren't i mean who runs this thing so survivors so let me answer yeah let me answer your your question um so um we would not be here if it wasn't for viruses yes and part of the reason is that if you look at mammalian evolution early on in this mammalian radiation that basically happened after the death of the dinosaurs is that some of the viruses that we had in our genome spread throughout our genome and created binding sites for new classes of regulatory proteins and these binding sites that landed all over our genome are now control elements that basically control our genes and sort of help the complexity of the circuitry of mammalian genomes so you know everything's co-evolution and we're working together yeah but and yet you saw they just don't care they don't care another thing oh is the virus trying to kill us no it's not the virus is not trying to kill you it's true it's not it's actually actively trying to not kill you so when you get infected if you die palmer i killed him is what the reaction of the virus will be why because that virus won't spread many people have a misconception of oh viruses are smart or oh viruses are mean they don't care it like you have to clean yourself of any kind of anthropomorphism out there i don't know oh yes so there's a there's a sense when taken as a whole that there's it's in a eye of the beholder stupid is a stupid does intelligent injustice intelligence does so if you want to call them intelligent that's fine then because and the end result is that they're finding amazing solutions right i mean i mean but they're all they're so dumb about it they're just doing dumb they don't care they're not dumb and they're not interested they don't care they care the care word is really interesting exactly i mean there could be an argument that they're conscious they're just dividing they're not they're just dividing they're just a little entity which happens to be dividing and spreading it does doesn't want to kill us in fact it prefers not to kill us it just wants to spread and when i say once again i'm anthropomorphizing but it's just that if you have two versions of a virus one acquires a mutation that spreads more that's going to spread more one acquires a mutation that's pressed less that's going to be lost yes one acquires a mutation that enters faster that's going to be kept one requires a mutation that kills you right away it's going to be lost so over evolutionary time the viruses that spread super well but don't kill the host are the ones that are going to survive yeah but so you see you brilliantly describe the basic mechanisms of how it all happens but when you zoom out and you see the uh you know the entirety of viruses maybe across different strains of viruses it seems like a living organism i am in awe of biology i find biology amazingly beautiful i find the design of the current coronavirus however lethal it is amazingly beautiful the way that it is encoded the way that it tricks your cells into making 30 proteins from a single rna human cells don't do that human cells make one protein from each rna molecule they don't make two they make one we are hardwired to make only one protein from every rna molecule and yet this virus goes in throws in a single messenger rna just like any messenger rna we have tens of thousands of messenger rnas in our cells in any one time in every one of our cells it throws in one rna and that rna is so i'm going to use your word here not my word intelligent yeah that it hijacks the entire machinery of your human cell yeah it basically has at the beginning a giant open reading frame that's a giant protein that gets translated two-thirds of that rna make a single giant protein that single protein is basically what a human cell would make it's like oh here's a start codon i'm going to start translating here human cells are kind of dumb i'm sorry again this is not the word that we normally use but the human cell basically is oh this is an rna it must be mine let me translate and it starts translating it and then you're in trouble why because that one protein as it's growing gets cleaved into about 20 different peptides the first peptide and the second peptide start interacting and the third one and the fourth one and they shut off the ribosome of the whole cell to not translate human rnas anymore so the virus basically hijacks your cells and it cuts it cleaves every one of your human rnas to basically say to the ribosome don't translate this one junk don't look at this one junk and it only spares its own rnas because they have a particular mark that it spares then all of the ribosomes that normally make protein in your human cells are now only able to translate viral rnas and make more and more and more and more of them that's the first 20 proteins in fact halfway down about protein 11 between you know 11 and 12 you basically have a translational slippage where the ribosome skips reading frame and it translates from one reading frame to another reading frame that means that about half of them are going to be translated from 1 to 11 and the other half are going to be translated from 12 to 16. wow it's gorgeous and then then you're done then that mrna will never translate elastin proteins but spike is the one right after that one so how does spike even get translated this positive strand rna virus has a reverse transcriptase which is an rna-based reverse transcriptase so from the rna on the positive strand it makes an rna of the negative strand and in between every single one of these genes these open reading frames there's a little signal aac gca or something like that that basically loops over to the beginning of the rna and basically instead of sort of having a single full negative strand or an a it basically has a partial negative strand rna that ends right before the beginning of that gene and another one that ends right before the beginning of that gene these negative strand rnas now make positive strand rnas that then look to the human whole cell just like any other human mrna it's like oh great i'm going to translate that one because it doesn't have the cleaving that the virus has now put on all your human genes and then you've lost the battle that cell is now only making proteins for the virus that will then create the spike protein the envelope protein the membrane protein the nucleocapsid protein that will package up the rna and then sort of create new viral envelopes and these will then be secreted out of that cell in new little packages that will then infect the rest of the cells and repeat the whole process beautiful right it's hard not to anthropomorphize it oh but it's so gorgeous so there is a beauty to it is there is it is it terrifying to you so this is something that has happened throughout history humans have been nearly wiped out over and over and over again and yet never fully wiped out so i'm yeah i'm not concerned about the human race i'm not even concerned about you know the impact on sort of our our survival as a species um this is absolutely something i mean you know human life is so invaluable and every one of us is so invaluable but if you think of it as sort of is this the end of our species by by no means basically so so let me explain the black death killed what 30 of europe that has left a tremendous imprint uh you know a huge hole a horrendous hole in the genetic makeup of humans there's been series of wiping out of huge fractions of entire species or just entire species all together and that has a consequence on the human immune repertoire if you look at how europe was shaped and how africa was shaped by malaria for example all the individuals that carry a mutation that protected from malaria were able to survive much more and if you look at the frequency of sickle cell disease and the frequency of malaria the maps are actually showing the same pattern the same imprint on africa and that basically led people to hypothesize that the reason why sickle cell disease is so much more frequent in americans of african descent is because there was selection in africa against malaria leading to sickle cell because when the cells sickle malaria is not able to you know replicate inside your cells as well and therefore you protect against that so if you look at human disease all of the genetic associations that we do with human disease you basically see the imprint of these waves of selection killing off gazillions of humans and there's so many immune processes that are coming up as associated with so many different diseases the reason for that is similar to what i was describing earlier where the outward facing proteins evolve much more rapidly because the environment is always changing but what's really interesting the human genome is that we have co-opted many of these immune genes to carry out non-immune functions for example in our brain we use immune cells to cleave off neuronal connections that don't get used this whole user will lose it we know the mechanism it's microglia the cleave of neuronal synaptic connections that are just not utilized when you utilize them you mark them in a particular way that basically when the microglia come tell it don't kill this one it's it's used now and the microwave will go off and kill once you don't use this is an immune function which is co-opted to do non-immune things if you look at our adipocytes m1 versus m2 macrophages inside our fat will basically determine whether you're obese or not and these are again immune cells that are resident and living within these tissues so many disease associations that we co-opt these kinds of things for incredibly uh complicated functions exactly evolution works in so many different ways which are all beautiful and mysterious it's not intelligent not intelligent it's in the eye of the beholder [Laughter] but but but the the the point that i'm trying to make is that if you look at the imprint that kovit will have hopefully it will not be big hopefully the u.s will get attacked together and stop the virus from spreading further but if it doesn't it's having an imprint on individuals who have particular genetic repertoires so if you look at now the genetic associations of blood type and immune function cells etc there's actually association genetic variation that basically says how much more likely am i or you to die if we contact the virus and it's it's through these rounds of shaping the human genome that humans have basically made it so far and uh selection is ruthless and it's brutal and it only comes with a lot of killing but this is the way that viruses and environments have shaped the human genome basically when you go through periods of famine you select for particular genes and what's left is not necessarily better it's just whatever survived and it may have been the surviving one back then not because it was better maybe the ones that ran slower survived i mean you know again not necessarily better but the surviving ones are basically the ones that then are shaped for any kind of subsequent evolutionary condition and environmental condition but if you look at for example obesity obesity was selected for basically the genes that now predisposes to obesity were at two percent frequency in africa they rose to 44 frequency in europe wow that's fascinating because you basically went through the ice ages and there was a scarcity of food so you know there was a selection to being able to store every single calorie you consume eventually environment changes so the better allele which was the fat storing allele became the worst allele because it's the fat storing allele it still has the same function so if you look at my genome speaking of mom calling mom gave me a bad copy of that gene these fto locus basically has to do with the obesity or the obesity yeah i basically now have a bad copy from mom that makes me more likely to be obese and i also also have a bad copy from dad that makes me more likely to be obese i'm homozygous and that's the allele it's still the minor allele but it's at 44 frequency in southeast asia 42 frequency in europe even though it started at 2 it was an awesome allele to have 100 years ago right now it's pretty terrible so the other concept is that diversity matters if we had a hundred million nuclear physicists living the earth right now we'd be in trouble you need diversity you need artists and you need musicians and you need mathematicians and you need you know politicians yes even those and you need like it's not it's not get crazy enough but so because then if uh virus comes along or whatever exactly exactly so no there's two reasons number one you want diversity and immune repertoire and we have built in diversity so basically they're they are the most diverse basically if you look at our immune system there's layers and layers of diversity like the way that you create your cells generates diversity because of the selection for the vdj recombination that basically eventually leads to a huge number of repertoires but that's only one small component of diversity the blood type is another one the major histogram histocompatibility complex the hla alleles are you know another source of diversity so the immune system of humans is by nature incredibly diverse and that basically leads to resilience so basically what i'm saying that i don't worry for the human species because we are so diverse immunologically we are likely to be very resilient against so many different attacks like this current virus so you're saying natural pandemics may not be something that you're really afraid of because of the diversity in our genetic makeup what about engineered pandemics do you have fears of us messing with the makeup of viruses or well yeah let's say with the makeup of viruses to create something that we can't control and we'd be much more destructive than it would come about naturally remember how we were talking about how smart evolution is humans are much dumber so you mean like human scientists yeah humans humans just humans overall yeah but i mean even you know the sort of synthetic biologists um you know basically if you were to create a you know virus like sars that will kill other people you would probably stars start with stars so whoever you know would like to design such a thing would basically start with stars tree or at least some relative of stars the source genome for the current virus was something completely different it was something that has never infected humans no one in their right mind would have started there oh but when you say source is like the nearest the nearest relative relative he's in a whole other branch no species of which has ever infected humans in that branch so you know let's put this to rest this was not designed by someone to kill off the human race so you don't you don't believe it was engineered the likely yeah the the path to engineering a deadly virus would not come from this strain that got it that was used uh moreover there's been various um claims of haha this was mixed and matched in lab because the s1 protein has three different components each of which has a different evolutionary tree so you know a lot of popular press basically said aha this came from pangolin and this came from you know all kinds of other species this is what has been happening throughout the coronavirus tree so basically the s1 protein has been recombining across species all the time remember when i was talking about the positive strand the negative strands sub genomic rnas these can actually recombine and if you have two different viruses infecting the same cell they can actually mix and match between the positive strand and the negative strand and basically create a new hybrid virus with recombination that now has the s1 from one and the rest of the genome from another and this is something that happens a lot in s1 you know fade etc and that's something that's true of the whole training for the whole family exactly viruses so it's not like someone has been messing with this for millions of years and you know changing this happens naturally that's again beautiful that that somehow happens that they recombine in the so two different strands can affect the body and recombine so all of this actually magic happens inside uh hosts like all like yeah yeah that way that's why classification wise virus is not thought to be alive because it doesn't self-replicate it's not autonomous it's something that enters a living cell and then co-opts it to basically make it its own but by itself people ask me how do we kill this bastard i'm like you stop it from replicating it's not like a bacterium that will just live in a you know puddle or something it's a virus viruses don't live without their host and they only live in their house for very little time so if you stop it from replicating it'll stop from spreading i mean it's not like hiv which can stay dormant for a long time basically coronaviruses just don't do that they're not integrating genomes there are any genomes so if it's not expressed it degrades rna degrades it doesn't just stick around well let me ask also um about the immune system you mentioned a lot of people kind of ask you know um how can we strengthen the immune system to respond to this particular virus but the viruses in general do you have from a biological perspective thoughts on what we can do as humans uh too if you look at our traits across different countries people with less vaccination have been dying more if you look at north italy the vaccination rates are abysmal there and a lot of people have been dying if you look at greece very good vaccination rates almost no one has been dying so yes there's a policy component so italy reacted very slowly greece reacted very fast so yeah many fewer people died in greece but there might actually be a component of genetic immune repertoire basically how did people die off you know in the history of the greek population versus the italian population there's a that's interesting to think about uh and then there's a component of what vaccinations did you have as a kid and what are the off-target effects of those vaccinations so basically a vaccination can have two components one is training your your immune system against that specific insult the second one is boosting up your immune system for all kinds of other things if you look at allergies northern europe super clean environments tons of allergies southern europe my kids grew up eating dirt no allergies so growing up i never had even heard of what allergies are like really allergies and the reason is that i was playing in the garden i was putting all kinds of stuff in my mouth from you know all kinds of dirt and stuff tons of viruses there tons of bacteria there you know my immune system was built up so the more you protect your immune system from exposure the less opportunity it has to learn about non-self repertoire in a way that prepares it for the next insult so it's a horizontal thing too like the says throughout your lifetime in the lifetime of the of the people that uh your ancestors yeah that kind of thing yeah what about the so again it returns against free will on the free will side of things is there something we could do to strengthen our immune system in 2020 is there like uh you know exercise diet all that kind of stuff so it's kind of funny um there's a cartoon that basically shows uh two windows with a teller in each window one has a humongous line and the other one has no one the one that has no one above says health no it says exercise and diet and the other one says pill yeah and there's a huge line for pill so we're looking basically for magic bullets for sort of ways that we can you know beat cancer and beat coronavirus and beat this and beat that and it turns out that the window with like just diet and exercise is the best way to boost every aspect of your health if you look at alzheimer's exercise and nutrition i mean you're like really for my brain neurodegeneration absolutely if you look at cancer exercise and nutrition if you look at coronavirus exercise and nutrition every single aspect of human health gets improved and one of the studies we're doing now is basically looking at what are the effects of diet and exercise how similar are they to each other we're basically taking diet intervention and exercise intervention in human and in mice and we're basically doing single cell profiling of a bunch of different tissues to basically understand how are the cells both the stromal cells and the immune cells of each of these tissues responding to the effect of exercise what are the communication networks between different cells where with the muscle that exercises sends signals through the bloodstream through the lymphatic system through all kinds of other systems that give signals to other cells that i have exercised and you should change in this particular way which basically reconfigure those receptor cells with the effect of exercise how well understood is the those reconfigurations very little we're just starting now basically is there is the hope there uh to understand the effect on uh so like the effect on the immune system on the immune system the effect on brain the effect on your liver on your digestive system on your adipocytes adipose you know the most misunderstood organ everybody thinks oh fat terrible no fat is awesome your fat cells is what's keeping you alive because if you didn't have your fat cells all those lipids and all those calories would be floating around in your blood and you'd be dead by now your adipocytes are your best friend they're basically storing all these excess calories so that they don't hurt all of the rest of the body and they're also fat burning in many ways so you know again when you don't have the homozygous version that i have your cells are able to burn calories much more easily by sort of flipping a master metabolic switch that involves this fto locus that i mentioned earlier and its target genes irx3 and rx5 that basically switch your adipocytes during their three first days of differentiation as they're becoming mature dipocytes to basically become either fat burning or fat storing fat cells and the fat burning fat cells are your best friends they're much closer to muscle than they are to white egg boss eyes is there a lot of difference between people like that you could give science could eventually give advice that is very generalizable or is our differences in our genetic makeup like you mentioned is that going to be basically something we have to be very specialized individuals any advice we give in terms of diet like we were just talking about believe it or not the most personalized advice that you give for nutrition don't have to do with your genome they have to do with your gut microbiome with the bacteria that live inside you so most of your digestion is actually happening by species that are not human inside you you have more non-human cells and you have human cells you're basically a giant bag of bacteria with a few human cells along and those do not necessarily have to do with your genetic makeup they interact with your genetic makeup they interact with your ruby genome they interact with your nutrition they interact with your environment they're you know basically an additional source of variation so when you're thinking about sort of personalized nutritional advice part of that is actually how do you match your microbiome and part of that is how do we match your genetics but again you know this is a very diverse set of um you know contributors and the effect sizes are not enormous so i think the science for that is not fully developed yet speaking of dyes because i've wrestled in combat sports with sports my whole life or weight matters so you have to cut and all that stuff one thing i've learned a lot about my body and which seems to be i think true about other people's bodies is that you can adjust to a lot of things that's the miraculous thing about this biological system is um like i fast often i used to eat like five six times a day and thought that was absolutely necessary how could you not eat that often and then when i started fasting your body adjusts to that and you learn how to not eat you know and it's it was uh if you just give it a chance for a few weeks actually over a period of a few weeks your body can adjust to anything yeah and that's a miraculous that's such a beautiful thing so i'm a computer scientist and i've basically gone through periods of 24 hours without eating or stopping and you know then i'm like oh must eat and i eat a ton i used to order two pizzas just with my brother and you know like so i i've gone through these extremes as well and i've gone the whole intermittent fasting thing so i can sympathize with you both on the seven meals a day to the zero meals a day um so i think when i say everything in moderation i i actually think your body responds interestingly to these different changes in diet i think part of the reason why we lose weight with pretty much every kind of change in behavior is because our epigenome and the set of proteins and enzymes that are expressed and our microbiome are not well suited to that nutritional source and therefore they will not be able to sort of catch everything that you give them and then you know a lot of that will go undigested and that basically means that your body can then you know lose weight in the short term but very quickly will adjust to that new normal and then we'll be able to sort of perhaps gain a lot of weight yeah from the diet so anyway i mean there's also studies in um factories where basically people you know dim the lights and then suddenly everybody started working better it was like wow that's amazing three weeks later they made the lights a little brighter everybody started working better so any kind of intervention has a placebo effect of wow now i'm healthier and i'm going to be running more often etc so it's very hard to uncouple the placebo effect of wow i'm doing something to intervene on my diet from the wow this is actually the right thing for me so you know yeah from the perspective from nutrition science psychology both things i'm interested in especially psychology it seems that it's extremely difficult to do good science because uh there's so many variables involved it's so difficult to control the variables so difficult to do sufficiently large-scale experiments uh both sort of in terms of number of subjects and temporal like how long you do the study for that uh it just seems like it's not even a real science for now like nutrition science i want to jump into the whole placebo effect for a little bit here and basically talk about the implications of that if i give you a sugar pill and tell you it's a sugar pill you won't get any better but if i tell you sugar appeal and tell you and i tell you wow this is an amazing drug it actually will stop your cancer your cash will actually stop with much higher probability what does that mean that's so amazing that means that if i can trick your brain into thinking that i'm healing you your brain will basically figure out a way to heal itself to heal the body and that tells us that there's so much that we don't understand in the interplay between our cognition and our biology that if we were able to better harvest the power of our brain to sort of you know impact the body through the placebo effect we would be so much better in so many different things just by tricking yourself into thinking that you're doing better you're actually doing better so there's something to be said about sort of positive thinking about optimism about sort of you know just getting your brain and your mind into the right mindset that helps your body and helps your entire biology yeah from a science perspective that's just fascinating i obviously most things about the brain is a total mystery for now but that's a fascinating interplay that the brain yeah that the brain can reduce uh the brain can help cure cancer as a i don't even know what to do with that i mean the way to think about that is the following the converse of the equation is something that we are much more comfortable with like oh if you're stressed then your heart right might rise and all kinds of sort of toxins might be released and that can have a detrimental effect in your body etc so maybe it's easier to understand your body healing from your mind by your mind is not killing your body or at least it's killing it less so i think the you know that aspect of the stress equation is a little easier for most of us to conceptualize but then the healing part is you know perhaps the same pathways perhaps different pathways but again something that is totally untapped scientifically i think we try to bring this question up a couple of times but let's return to it again is what do you think is the difference between the way a computer represents information the human genome represents and stores information like what and maybe broadly what is the difference between how you think about computers and how you think about biological systems so i made a very provocative claim earlier that we are a digital computer like that at the core lies a digital code and that's true in many ways but surrounding that digital core there's a huge amount of analog if you look at our brain it's not really digital if you look at our sort of rna and all of that stuff inside our cell it's not really digital it's really analog in many ways but let's start with the code and then we'll expand to the rest so the code itself is digital so there's genes you can think of the genes as i don't know the procedures the functions inside your language and then somehow you have to turn these functions on how do you call a gene how do you call that function the way that you would do it in old programming languages is go to address whatever in your memory and then you start running from there and you know modern programming languages have encapsulated this into functions and objects and all of that and it's nice and cute but in the end deep down there's still an assembly code that says go to that instruction and it runs that instruction if you look at the human genome and you know the genome of pretty much most species out there it's there's no go-to function you just don't start in you know transcribing in position thirteen hundred five you know thirteen thousand five hundred twenty seven in chromosome 12. you instead have content based indexing so at every location in the genome in front of the genes that need to be turned on i don't know when you drink coffee there's a little coffee marker in front of all of them and whenever your cells that metabolize coffee need to metabolize coffee they basically see coffee and they're like oh let's go turn on all the coffee marked jeans so there's basically these small motifs these small sequences that we call regulatory motifs they're like patterns of dna they're only eight characters long or so like gat gca et cetera and these motifs work in combinations and every one of them has some recruitment affinity for a different protein that will then come and bind it and together collections of these motifs create regions that we call regulatory regions that can be either promoters near the beginning of the gene and that basically tells you where the function actually starts where you call it and then enhancers that are looping around of the dna that basically bring the machinery that binds those enhancers and then bring it onto the promoter which then recruits the right sort of the ribosome and the polymerase and all of that thing which will first transcribe and then export and then eventually translate in the cytoplasm you know whatever rna molecule so the beauty of the way that the digital computer that's the genome works is that it's extremely fault tolerant if i took your hard drive and i messed with twenty percent of the letters in it of those zeros and ones and i flipped them you'd be in trouble if i take the genome and i flip 20 of the letters you probably won't even notice and that resilience that's fascinating again is a key design principle and again i'm triple morphizing here but it's a key driving principle of how biological systems work they're first resilient and then anything else and when you look at this incredible beauty of life from the most i don't know beautiful i don't know human genome maybe of humanity and all of the ideals that should come with it to the most terrifying genome like i don't know kovit-19 sarsko v2 and the current pandemic you basically see this elegance as the epitome of clean design but it's dirty it's a mess it's you know the the way to get there is hugely messy and that's something that we as computer scientists don't embrace we like to have clean code you know as like in engineering they teach you about compartmentalization about sort of separating functions about modularity about hierarchical design none of that applies in bio testing [Laughter] testing sure yeah biology does plenty of that but i mean through evolutionary exploration but um if you look at biological systems first they are robust and then they specialize to become anything else and if you look at viruses the reason why they're so elegant when you look at the design of this you know genome it seems so elegant and the reason for that is that it's been stripped down from something much larger because of the pressure to keep it compact so many compact genomes out there have ancestors that were much larger you don't start small and become big you go through a loop of add a bunch of stuff increase complexity and then you know slim it down and one of my early papers was in fact on genome duplication one of the things we found is that baker's yeast which is the you know yeast that you use to make bread but also the yeast that you use to make wine which is basically the dominant species when you go in the fields of tuscany and you say you know what's out there it's basically saccharomyces cerevisiae or the way my italian friends say saccharomyces so um uh which means what oh sakura okay i'm sorry i'm i'm greek so yeah zacharo mickeys zacharo is sugar minky's is fungus yes cerevisiae cerveza beer so so it means the sugar fungus of beer yeah you know less less sounding to the still poetic yeah so anyway uh saccharomyces cerevisiae basically the major baker's yeast out there is the descendant of a whole genome duplication why would a whole genuine duplication even happen when it happened is coinciding with about 100 million years ago and the emergence of fruit-bearing plants why fruit-bearing plants because animals would eat the fruit and would walk around and poop huge amounts of nutrients along with a seed for the plants to spread before that plants were not spreading through animals they were spreading through wind and all kinds of other ways but basically the moment you have fruit-bearing plants the the the these plants are basically creating this abundance of sugar in the environment so there's an evolutionary niche that gets created and in that evolutionary niche you basically have enough sugar that a whole genome duplication which initially is a very messy event allows you to then you know relieve some of that complexity so to pause what does genome duplication mean that basically means that instead of having eight chromosomes you can now have 16 chromosomes so but with the duplication at first when you have six when you go to 16 you're not using that oh yeah you are yeah so basically from one day to the next you went from having eight chromosomes to having 16 chromosomes probably a non-disjunction event during a duplication during a division so you basically divide the cell instead of half the genome going this way and half the genome going the other way after duplication of the genome you basically have all of it going to one cell and then there's a sufficient messiness there that you end up with slight differences that make most of these chromosomes be actually preserved it's a long story short but it's a big upgrade right so that's not necessarily because what happens immediately thereafter is that you start massively losing tons of those duplicated genes so ninety percent of those genes were actually lost very rapidly after holding duplication and the reason for that is that biology is not intelligent it's just ruthless selection random mutation so the ruthless selection basically means that as soon as one of the random mutations hit one gene ruthless selection just kills off that gene it's just you know you you know if you have a pressure to maintain a small compact genome you will very rapidly lose the second copy of most of your genes and a small number 10 were kept in two copies and those had to do a lot with environment adaptation with the speed of replication with the speed of translation and with sugar processing so i'm making a long story short to basically say that evolution is messy the only way like so so you know the example that i was giving of messing with 20 of your bits in your computer totally bogus duplicating all your functions and just throwing them out there in the same you know function just totally bogus like this would never work in an engineer system but biological systems because of this content-based indexing and because of this modularity that comes from the fact that the gene is controlled by a series of tags and now if you need this gene in another setting you just add some more tags that will basically turn it on also in those settings so this gene is now pressured to to do two different functions and it builds up complexity i see a whole term duplication and gene duplication in general as a way to relieve that complexity so you have this gradual buildup of complexity as functions get past get sort of added on to the existing genes and then boom you duplicate your your workforce and you now have two copies of this gene one will probably specialize to do one and the other one will specialize to do the other or one will maintain the ancestral function the other one will sort of be free to evolve and specialize while losing the ancestral functions and so forth so that's how genomes evolve they're they're just messy things but they're extremely fault tolerant and they're extremely able to deal with mutations because that's the very way that you generate new functions so new functionalization comes from the very thing that breaks it so even in the current pandemic many people are asking me which mutations matter the most and what i tell them is well we can study the evolutionary dynamics of the current genome to then understand which mutations have previously happened or not and which mutations happen in genes that evolve rapidly or not and one of the things we found for example is that the genes that evolved rapidly in the past are still evolving rapidly now in the current pandemic the genes have evolved slowly in the past are still evolving slowly which means that they're useful which means that they're under the same evolutionary pressures but then the question is what happens in specific mutations so if you look at the d614 gene mutation that's been all over the news so in position 614 in the amino acids and harvest 14 of the s protein there's a d to g mutation that that sort of has creeped over the population mutation we found out through my work disrupts a perfectly conserved nucleotide position that has never been changed in the history of millions of years of equivalent mammalian evolution of these viruses that basically means that it's a completely new adaptation to human and that mutation has now gone from one percent frequency to 90 frequency in almost all outbreaks so this mutation i like how you say in the mu the 416 what was it okay yes 6 on 14 sorry 614 right that d614g dc so so literally so what you're saying is it's like a chess move yeah so it's just mutated one letter to another exactly and that hasn't happened before yeah and and this somehow this mutation is really useful uh it's really useful in the current environment of the genome which is moving from human to human when it was moving from bad to bad it couldn't care less for that mutation but it's environment specific so now that it's moving from human to human whoo-hoo it's moving way better like by orders of magnetism what do you okay so so you're like tracking this evolutionary dynamics which is fascinating but what do you do with that so what does that mean what does this mean what do you make what do you make of this mutation in uh trying to anticipate i guess is is the is one of the things you're trying to do is anticipate where how this unrolls into the future this this evolutionary dynamics such a great question so so there's there's two things remember when i was saying earlier mutation is the path to new things but also the path to break old things so what we know is that this position was extremely preserved through gazillions of mutations that mutation was never tolerated when it was moving from best to bats so that basically means that that contain that position is extremely important in the function of that protein that's the first thing it tells the second one is that that position was very well suited to bat transmission but now is not well suited to human transmission so it got rid of it and it now has a new version of that amino acid that basically makes it much easier to transmit from human to human so in terms of the evolutionary history teaching us about the future it basically tells us here's the regions that are currently mutating here's the regions that are most likely to imitate going forward as you're building a vaccine here's what you should be focusing on in terms of the most stable regions that are the least likely to mutate or here's the newly evolved functions that are most likely to be important because they've overcome this local maximum that it had reached in the in the bat transmission so anyway it's a tangent to basically say that evolution works in messy ways and the thing that you would break is the thing that actually allows you to first go through a lull and then reaching new local maximum and i often like to say that if engineers had basically designed evolution we would still be perfectly replicating bacteria because it's by making the bacterium worse that you allow evolution to reach a new optimum that's just a pause on that that's so profound the the that's so profound for the entirety of um this scientific and engineering disciplines exactly we as engineers need to embrace breaking things we as engineers need to embrace robustness as the first principle beyond perfection because nothing is going to ever be perfect and when you're sending a satellite to mars when something goes wrong it'll break down as opposed to building systems that tolerate failure and are resilient to that and in fact get better through that so the spacex approach versus nasa for the for example is there something we can learn about the incredible uh take lessons from the incredible biological systems in their resilience in their in the mushiness the messiness to uh to our computing systems to uh to our computers it would basically be starting from scratch in many ways it would basically be building new paradigms that don't try to get the right answer all the time but try to get the right answer most of the time or a lot of the time do you see deep learning systems in the whole world of machine learning is kind of taking a step in that direction absolutely absolutely basically by allowing this much more natural evolution of these parameters you basically and then if you look at sort of deep learning systems again they're not inspired by the genome aspect of biology they're inspired by the brain aspect of biology and again i want you to pause for a second and realize the complexity of the entire human brain with trillions of connections within our you know neurons with millions of cells talking to each other is still encoded within that same genome that same genome encodes every single freaking cell type of the entire body every single cell is encoded by the same code and yet specialization allows you to have this single viral-like genome that self-replicates the single module modular automaton work with other copies of itself it's mind-boggling create complex organs through which blood flows and what is that blood the same freaking genome create organs that communicate with each other and what are these organs the exact same genome create a brain that is innervated by massive amounts of blood pumping energy to it 20 of our energetic needs to the brain from the same genome and all of the neuronal connections all of the auxiliary cells all of the immune cells the astrocytes the ligand size the neurons the excitatory the inhibitory neurons all of the different classes of parasites the blood-brain barrier all of that same genome one way to see that in a sad so this one is beautiful the sad thing is thinking about the trillions of organisms that died to create that you mean on the evolutionary path and the evolutionary path to humans that's crazy there's two descendants of apes just talking on the podcast okay this is so mind-boggling just just to boggle our minds a little bit more yeah us talking to each other we are basically generating a series of vocal utterances through our pulsating of vocal chords received through this the people who listen to this are taking a completely different path to that information transfer yet through language but imagine if we could connect these brains directly to each other the amount of information that i'm condensing into a small number of words is a huge funnel which then you receive and you expand into a huge number of thoughts from that small funnel in many ways engineers would love to have the whole information transfer just take the whole set of neurons and throw them away i mean throw them to the other person this might actually not be better because in your misinterpretation of every word that i'm saying you are creating new interpretation that might actually be way better than what i meant to the first place the ambiguity of language perhaps might be the secret to creativity every single time you work on a project by yourself you only bounce ideas with one person and your neurons are basically fully cognizant of what these ideas are but the moment you interact with another person the misinterpretations that happen might be the most creative part of the process with my students every time we have a research meeting i very often pause and say let me repeat what you just said in a different way and i sort of go on and brainstorm with what they were saying but by the third time it's not what they were saying at all and when they pick up what i'm saying you're like oh well now they they've sort of learned something very different from what i was saying and that is the same kind of messiness that i'm describing in the genome itself it's sort of embracing the messiness and that's a feature not a book exactly and in the same way when you're thinking about sort of these deep learning systems that will allow us to sort of be more creative perhaps or learn better approximations of these complex functions again tuned to the universe that we inhabit you have to embrace the breaking you have to embrace the you know how do we get out of these local optima and a lot of the design paradigms that have made deep learning so successful are ways to get away from that ways to get better training by sort of sending long range messages these lstm models and the you know sort of feed forward loops that you know sort of jump through layers of a convolutional neural network all of these things are basically ways to push you out of this local maxima and that's sort of what evolution does that's what language does that's what conversation and brainstorming does that's what our brain does so you know this design paradigm is something that's pervasive and yet not taught in schools not taught in engineering schools where everything is minutely modularized to make sure that we never deviate from you know whatever signal we're trying to emit as opposed to let all hell breaks loose because that's the way that's the path of paradise the path to paradise yeah i mean it's difficult to know how to teach that and uh what to do with it i mean it's um it's difficult to know how to build up a sign the scientific method around messiness you i mean it's not all messiness we need we need some cleanness and going back to the example with mars that's probably the place where i want to sort of moderate error as much as possible and sort of control the environment as much as possible but if you're trying to repopulate mars well maybe messiness is a good thing then on that uh you quick you quickly mentioned this in terms of us using our vocal cords to speak on a podcast um so elon musk and neurolink are working on trying to plug as per discussion with computers and biological systems to connect the two he's trying to con connect our brain to a computer to create a brain computer interface where they can communicate back and forth on this line of thinking do you think this is uh possible to bridge the gap between our engineered computing systems and the messy biological systems my answer would be absolutely we you know there's no doubt that we can understand more and more about what goes on in the brain and we can sort of train the brain i mean i don't know if you remember the palm pilot yeah palm pilot yeah remember this whole sort of alphabet that they had created am i thinking of the same thing um it's basically you had you had a little pen and for every character you had a little scribble that was unique that the machine could understand and that instead of trying the machine trying to teach the machine to recognize human characters you had basically they figured out that it's better and easier to train humans to create human-like characters that the machine is better at recognizing so in the same way i think what will happen is that humans will be trained to be able to create the mind pattern that the machine will respond to before the machine truly comprehends our thoughts so the first human brain interfaces will be tricking humans to speak the machine language where with the right set of electrodes i can sort of trick my brain into doing this and this is the same way that many people teach like learn to control artificial limbs you basically try a bunch of stuff and eventually you figure out how your limbs work that might not be very different from how humans learn to use their natural limbs when they first grow up basically you have these you know neoteny period of you know this puddle of soup inside your brain trying to figure out how to even make your own connections before you're born and then learning sounds in utero of you know all kinds of echoes and you know eventually getting out in the real world and i don't know if you've seen newborns but they just stare around a lot you know one way to think about this as a machine learning person is oh they're just training their edge detectors and eventually they figure out how to train their edge detectors they work through the second layer of the visual cortex and the third layer and so forth and you basically have this um learning how to control your limbs that probably comes at the same time you're sort of you know throwing random things there and you realize that oh wow when i do this thing my limb moves let's do the following experiment take a breath what muscles did you flex now take another breath and think what muscles do i flex the first thing that you're thinking when you're taking a breath is the impact that he has on your lungs you're like oh i'm now going to increase my lungs or i'm not going to bring air in but what you're actually doing is just changing your diaphragm yeah that's not conscious of course you never think of the diaphragm as a thing yeah and why is that that's probably the same reason why i think of moving my finger when i actually move my finger i think of the effect instead of actually thinking of whatever muscle is twitching that actually causes my finger to move so we basically in our first years of life build up this massive lookup table between whatever neuronal firing we do and whatever action happens in our body that we control if you have a kid grow up with a third limb i'm sure they'll figure out how to control them probably at the same rate as their natural limbs and uh a lot of the work would be done by the so if the third limb is the computer you kind of have a uh not a faith but a thought that um the brain might be able to figure out like if the plasticity would come from the brain yeah like the brain would be cleverer than the machine at first when i talk about a third limb that's exactly what i'm saying an artificial limb that basically just controls your mouse while you're typing you know perfectly natural thing i mean again you know in a few hundred years maybe sooner than that but but basically there's as long as the machine is consistent in the way that it will respond to your brain impulses you'll figure out how to control that and you could play tennis with your third limb and let me go back to consistency people who have dramatic accidents that basically take out a whole chunk of their brain can be taught to co-opt other parts of the brain to then control that part you can basically build up that tissue again and eventually train your body how to walk again and how to read again and how to play again and how to think again how to speak a language again etc so there's a massive amount of malleability that happens you know naturally in our way of controlling our body our brain or thoughts or vocal cords or limbs etc and human machine interfaces are inevitable if we sort of figure out how to read these electric impulses but the resolution at which we can understand human thought right now is nil is ridiculous so how are human thoughts encoded it's basically combinations of neurons that co-fire and these create these things called engrams that eventually form memories and so so forth we know nothing of all that stuff so before we can actually read into your brain that you want to build a program that does this anytime it's on that we need a lot of neuroscience well so uh to push back on that do you think it's possible that without understanding the functionally about the brain or the from the neuroscience or the cognitive science or psychology whichever level of the brain will look at do you think if we just connect connect them just like per your previous point if we just have a high enough resolution between connection between uh wikipedia and your brain the brain will just figure it out with us understanding um because that's one of the innovations of neural link is they're increasing the number of connections to the brain to like several thousand which before was you know in the dozens or whatever you're still off by a few orders of magnets right but the the thing is the hope is if you increase that number more and more and more maybe you don't need to understand anything about the actual how human thought is represented in the brain you could just let it let it figure it out by itself well uh cannery is waking up and saying i know yeah exactly exactly so yeah sure you don't have faith in the plasticity of the brain to that degree it's not about brain plasticity it's about the input aspect basically i think on the output aspect being able to control a machine is something that you can probably train your neural impulses that you're sending out to sort of match whatever response you see in the environment if this thing moved every single time i thought a particular thought then i could figure out i could hack my way into moving this thing with just a series of thoughts i could think guitar piano tennis ball and then this thing would be moving and then you know i would just have the series of thoughts that would sort of result in the impulses that will move this thing the way that i want it and then eventually it'll become natural because i won't even think about it um i mean the same way that we control our limbs in a very natural way but babies don't do that babies have to figure it out and you know some of it is hard-coded but some of that is actually learned based on the whatever soup of neurons you ended up with whatever connections you pruned them to and eventually you were born with you know a lot of that is coded in the genome but a huge chunk of that is stochastic instead of the way that you sort of create all these neurons they migrate they form connections they sort of you know spread out they have particular branching patterns but then the connectivity itself unique in every single new person all this to say that on the output side absolutely i'm very very you know um hopeful that we can have machines that read thousands of these neuronal connections on the output side but on the input side oh boy i don't expect any time in the near future we'll be able to sort of send a series of impulses that will tell me oh earth to sun distance 7.5 million et cetera like nowhere i mean i think language will still the be the input way rather than sort of any kind of more complex it's a really interesting notion that the ambiguity of language is a feature yeah and we evolved for millions of years to uh to take advantage of that ambiguity exactly and yet no one teaches us the subtle differences between words that are near cognates and yet evoke so much more than you know one from the other and yet you know when you're choosing words from a list of 20 synonyms you know exactly the connotation of every single one of them and that's something that you know is there so so yes there's ambiguity but there's all kinds of connotations and in the way that we select our words we have so much baggage that we're sending along the way that we're emoting the way that we're moving our hands every single time we speak the you know the pauses the eye contact etc so much higher baud rate than just a vocal you know string of characters well let me just take a small tangent on that oh tangent we haven't done that yet and i haven't done an idea uh we'll return to the origin of life so i mean you're greek but i'm i'm going on this personal journey uh i'm going to paris for the explicit purpose of talking to one of the most famous uh a couple who's a famous translators of russian literature dostoyevsky tolstoy yeah and they go that's their art is the translation and um everything i've learned about the translation art it makes me feel um it's so profound in a way that's so much more profound than the natural language processing papers i read in the machine learning community that there's such depth to language that um i don't know what to do with i don't know if you've experienced that in your own life with knowing multiple languages um i don't know what to i don't know how to make sense of it but there's so much loss in translation between russian and english and getting a sense of that like for example there's like just taking a single sentence from dostoyevsky and like there's a lot of them you could you could talk for hours about how to translate that sentence properly uh that captures the meaning the the the period the culture the humor the wit the suffering that was in the context of the time all of that it could be a single sentence uh you could you could talk forever about what it takes to translate that correctly i don't know what to do with that so being greek it's very hard for me to think of a sentence or even a word without going into the full etymology of that word breaking up every single atom of that that sentence and every single atom of these words and rebuilding it back up i have three kids and the way that i teach them greek is the same way that you know the documentary i was mentioning earlier about sort of understanding the deep roots of all of these you know words um and it's very it's very interesting that every single time i hear a new word that i've never heard before i go and figure out the etymology of that word because i will never appreciate that word without understanding how it was initially formed interesting but how does that help because that's that's not the full picture no no of course of course but what i'm trying to say is that knowing the components teaches you about the context of the formation of that word and sort of the original usage of that word and then of course the word takes new meaning as you create it you know from its parts and that meaning then gets augmented and two synonyms that that sort of have different roots will actually have implications that carry a lot of that baggage of the historical provenance of these words so before working on genome evolution my passion was evolution of language and sort of tracing cognates across different languages through their etymologies and that's fascinating that there's parallels between i mean of course the idea that there's evolutionary dynamics to our language yeah every single word that you utter parallels parallels what does parallels mean para means side by side alleles from alleles which means identical twins parallels i mean name any word and there's so much baggage so much beauty in how that word came to be and how this word took a new meaning than the sum of its parts yeah and that and those and they're just they're just words they don't have any physical exactly and now you take your words and you weave them into a sentence the emotional invocations of that weaving are fathomless and they're all all of those emotions all live in our in the brains of humans in the eye of the beholder no seriously you have to embrace this concept of the eye of the beholder it's it's the the conceptualization that nothing takes meaning with one person creating it everything takes meaning in the receiving end and the emergent properties of these communication networks where every single you know if you look at the network of our cells and how they're communicating with each other every cell has its own code this code is modulated by the epigenome this creates a bunch of different cell types each cell type now has its own identity yet they all have the common root of the stem cells that sort of led to them each of these identities is now communicating with each other they take meaning in their interaction there's an emergent property that comes from a bunch of cells being together that is not in any one of the parts if you look at neurons communicating again these engrams don't exist in any one neuron they exist in the connection in the combination of neurons and the meaning of the words that i'm telling you is empty until it reaches you and it affects you in a very different way then it affects whoever's listening to this conversation now because of the emotional baggage that i've grown up with that you've grown up with and that they've grown up with yeah and that's i think the magic of translation if you start thinking of translation as just simply capturing that emotional set of reactions that you have that you evoke you need a different set of words to evoke that same set of reactions to a french person than to a russian person because of the baggage of the culture that we grew up in yeah i mean there's so so basically you shouldn't find the best word sometimes it's a completely different sentence structure that you will need matched to the cultural context of the target audience that you have yeah the it's i mean you're just i usually don't think about this but right now there's this feeling as a reminder that it's just you and i talking but there's several hundred thousand people will listen to this there's some guy in russia right now running uh like in moscow listening to us and there's somebody in india i guarantee you there's somebody in china and south america there's somebody in texas and and they all have different emotional baggage they probably got angry earlier on about the whole discussion about coronavirus and uh about some aspect of it uh yeah it's and there's that network effect yeah yeah that's uh it's a beautiful thing and and this lateral transfer of information that's what makes the collective quote-unquote genome of humanity so unique from any other species so you somehow miraculously wrapped it back to the very beginning of when we were talking about the human the beauty of the human genome so i think this is the right time unless we want to go for a six to eight hour conversation we're gonna have to talk again but i think for now to wrap it up um this is the right time to talk about the uh the biggest most ridiculous question of all meaning of life off mike you mentioned to me that you um you had your 42nd birthday 40 a second being a very special absurdly special number uh and you had to kind of um get together with friends to discuss the meaning of life so let me ask you in your as a biologist as a computer scientist and as a human what is the meaning of life i've been asking this question for a long time ever since my 42nd birthday but well before that and even planning the meaning of life symposium and symposium means together posey actually means to drink together so symposium is actually a drinking party [Laughter] so can you actually elaborate about this meaning of life that you put together it's like the most genius idea i've ever heard so 42 is obviously the answer to life the universe and everything from the hitchhiker's guide to the galaxy and as i was turning 42 i've had the theme for every one of my birthdays when i was turning 32 it's one zero zero zero zero zero in binary so i celebrated my 100 000th binary binary birthday and i had a theme of going back 100 000 years you know let's dress something in the last hundred thousand years anyway it was we've i've always had these that's such an interesting human being okay that's awesome i've always had these sort of uh sort of numerology [Music] related announcements for my for my birthday party so what came out of that meaning of life symposium is that i basically asked 42 of my colleagues 42 my friends 42 of my you know collaborators to basically give seven minute species on the meaning of life each from their perspective and i really encourage you to go there because it's mind-boggling that every single person said a different answer every single person started with i don't know what the meaning of life is but and then give this beautifully eloquently answer eloquent answer and they were all different but they all were consistent with each other and mutually synergistic and together forming a beautiful view of what it means to be human in many ways some people talked about the loss of their loved one their life partner for many many years and how their life changed through that some people talked about the origin of life some people talked about the difference between purpose and meaning i'll you know maybe quote one of the answers which is this linguistics uh professor friend of mine at harvard who basically said that she was gonna she's greek as well and she said i will give a very pythian answer so pithia was the oracle of delphi who would basically give these very cryptic answers very short but interpretable in many different ways there was this whole set of priests who were tasked with interpreting what pethia had said and very often you would not get a clean interpretation but she said i will be like pethi and give you a very short and multiple interpretable answer but unlike her i will actually also give you three interpretations and she said the answer to the meaning of life is become one and the first interpretation is like a child become one year old with the excitement of discovering everything about the world second interpretation in whatever you take on become one the first the best excel drive yourself to perfection for every one of your tasks and become one when people are separate become one come together learn to understand each other damn that's an answer and one way to summarize this whole meaning of life symposium is that the very symposium was illustrating the quest for meaning which might itself be the meaning of life this constant quest for something sublime something human something intangible some you know aspect of what defines us as a species and as an individual both the quest of me as a person through my own life but the meaning of life could also be the meaning of all of life what is the whole point of life why life why life itself because we've been talking about the history and evolution of life but we haven't talked about why life in the first place is life inevitable is life part of physics does life transcend physics but fighting by fighting against entropy by compartmentalizing and increasing concentrations rather than diluting away is life um a distinct entity in the universe beyond the traditional very simple physical rules that govern gravity and you know electromagnetism and all of these forces is life another force is there a life force is there a unique kind of set of principles that emerge of course built on top of the hardware of physics but is it sort of a new layer of software or a new layer of a computer system so that's at the level of you know big questions there's another aspect of gratitude of basically what i you know what i like to say is during this pandemic i've basically worked from 6 a.m until 7 00 pm every single day non-stop including saturday and sunday i've basically broken all boundaries of where life personal life begins and work life you know ends and uh that has been exhilarating for me just just the intellectual pleasure that i get from a day of exhaustion where at the end of the day my brain is hurting i'm telling my wife wow i was useful today and there's a certain pleasure that comes from feeling useful and there's a certain pleasure that comes from feeling grateful so i've written this little sort of prayer for my kids to say at bedtime every night where they basically say thank you god for all you have given me and give me the strength to give unto others with the same love that you have given unto me we as a species are so special the only ones who worry about the meaning of life and maybe that's what makes us human and what i like to say to my wife and to my students during this pandemic work extravaganza is every now and then they ask me but how do you do this and i'm like i'm a workaholic i love this this is me in the most unfiltered way the ability to do something useful to feel that my brain is being used to interact with the smartest people on the planet day in day out and to help them discover aspects of the human genome of the human brain of human disease and the human condition that no one has seen before with data that we're capturing that has never been observed and there's another aspect which is on the personal life many people say oh i'm not going to have kids why bother i can tell you as a father they're missing half the picture if not the whole picture teaching my kids about my view of the world and watching through their eyes the naivete with which they start and the sophistication with which they end up they understanding that they have of not just the natural world around them but of me too the unfiltered criticism that you get from your own children that knows no bounds of honesty and i've grown components of my heart that i didn't know i had until you sense that fragility that vulnerability of the children that immense love and passion the unfiltered egoism that we as adults learn how to hide so much better it's just this back of emotions that tell me about the raw materials that make a human being and how these raw materials can be arranged with more sophistication that we learn through life to become truly human adults but there's something so beautiful about seeing that progression between them the complexity of the language growing as more neural connections are formed to to realize that the hardware is getting rearranged as their software is getting implemented on that hardware that their frontal cortex continues to grow for another 10 years these neuronal connections are continuing to form new neurons that actually get replicated and formed and it's it's just incredible that we have this not just you grow the hardware for 30 years and then you feed it all of the knowledge no no the knowledge is fed throughout and is shaping these neural connections as they're forming so seeing that transformation from either your own blood or from an adopted child is the most beautiful thing you can do as a human being and it completes you it completes that path that journey the create life oh sure that's at conception that's easy but create human life to add the human part that takes decades of compassion of sharing of love and of anger and of impatience and patience and as a parent i think i've become a very different kind of teacher because again i'm a professor my first role is to bring adult human beings into a you know more mature level of adulthood where they learn not just to do science but they learn the process of discovery and the process of collaboration the process of sharing the process of conveying the knowledge of encapsulating something incredibly complex and and sort of giving it up in sort of bite-sized chunks that the rest of humanity can appreciate i tell my students all the time if you you know like when an apple fall when when when a tree falls in the forest and no one's there to listen has it really fallen the same way you do this awesome research if you write an impenetrable paper that no one will understand it's as if you never did the awesome research so conveying of knowledge conveying this lateral transfer that i was talking about at the very beginning of sort of human humanity and sort of the sharing of information all of that has gotten so much more rich by seeing human beings grow in my own home because that that makes me a better parent and that makes me a better teacher and a better mentor to the nurturing of my adult children which are my research group first of all beautifully put connects beautifully to the vertical and the horizontal inheritance of ideas that we've talked about at the very beginning i don't think there's a better way to end it uh on this poetic and powerful note uh manolas thank you so much for talking there's a huge honor we have to talk again about the origin of life about epigenetics epigenomics and uh some of the incredible research you're doing truly an honor thanks so much for talking thank you such a pleasure it's such a pleasure i mean your questions are outstanding i've had such a blast here i can't wait to be back awesome thanks for listening to this conversation with manolas kellis and thank you to our sponsors blinkist eight sleep and masterclass please consider supporting this podcast by going to blinkist.com lex eightsleep.com lex and dot com slash lex click the links buy the stuff get the discount it's the best way to support this podcast if you enjoy this thing subscribe on youtube review 5 stars on apple podcast support on patreon or connect with me on twitter at lex friedman and now let me leave you with some words from charles darwin that i think manolis represents quite beautifully if i had my life to live over again i would have made a rule to read some poetry and listen to some music at least once every week thank you for listening and hope to see you next time you |
Ian Hutchinson: Nuclear Fusion, Plasma Physics, and Religion | Lex Fridman Podcast #112 | the following is a conversation with ian hutchinson a nuclear engineer and plasma physicist at mit he has made a number of important contributions in plasma physics including the magnetic confinement of plasmas seeking to enable fusion reactions which happens to be the energy source of the stars to be used for practical energy production current nuclear reactors by the way are based on fission as we discuss ian has also written on the philosophy of science and the relationship between science and religion arguing in particular against scientism which is a negative description of the overreach of the scientific method to questions not amenable to it on this latter topic i recommend two of his books his new one can a scientist believe in miracles where he answers more than 200 questions on all aspects of god and science and his earlier book on scientism called monopolizing knowledge as you may have seen already i work hard on having an open mind always questioning my assumptions and in general marvel at the immense mystery of everything around us and the limitations of at least my mind i'm not religious myself in that i don't go to the synagogue a church or mosque but i see the beautiful bond in the community that religion at its best can create i also see both in scientists and religious leaders signs of arrogance hypocrisy greed and a will to power we're human whether buddhist christian hindu jewish muslim agnostic or atheist this podcast is my humble attempt to explore a complicated human nature what stanislav in his book solaris called our own labyrinth of dark passages and secret chambers i ask that you try to keep an open mind as well and be patient with the limitations of mine quick summary of the ads two new amazing sponsors sunbasket and powerdot please consider supporting this podcast by going to sunbasket.com lex and use code lex at checkout and go into powerdot.com lex and use code lex at checkout as well click the links buy the stuff if you like just visiting the site and considering the purchase is really the best way to support this podcast it's how they know i sent you and based on that that might sponsor the podcast in the future if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast support on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show sponsored by sunbasket visit sunbasket.com and use codelex to get 35 bucks off your order and to support this podcast sunbasket delivers fresh healthy delicious meals straight to your door as you may know my diet is pretty minimalist so it's nice to get some healthy variety into the mix they make it super easy with everything proportioned and ready to prep and cook you can enjoy a delicious healthy dinner in as little as 15 minutes i just ordered my first set of meals haven't gotten them yet but i can't wait i just finished the uh six mile run and thousand body weight reps and i'm starving but let me risk listing the actual menu items that i ordered because they sound delicious italian sausages and vegetable skewers with two romescos i don't actually know where mescals are but the pictures looked awesome and pork fried cauliflower rice with carrots and peas by the way cauliflower rice is one of my favorite things ever right now sun basket is offering 35 off your order when you go right now to sunbasket.com lex they told me to say right now with urgency so pause this podcast and go to the website and make the purchase or just go to the website and check it out and enter a promo code lex at checkout this show is also sponsored by powerdot get it at powerdot.com lex and use code lex at checkout to get 20 off and to support this podcast this thing is amazing it's an e-stem electrical stimulation device that i've been using a lot for muscle recovery recently mostly for my shoulders and legs as i've been doing the 1000 body weight reps and six miles every day as i just finished they call it the smart muscle stimulator which is true since the app that goes with it is amazing it has 15 programs for different body parts and guides you through everything you need to do i take recovery really seriously these days and powerdot has been a powerful addition to the whole regime of stretching ice massage and sleep and diet that i do it's used by professional athletes and by slightly insane but mostly normal people like me it's portable so you can throw it in a bag and bring it anywhere get it at powerdot.com lex and use code lex checkout to get 20 off on top of the 30 day free trial and to support this podcast and now here's my conversation with ian hutchinson maybe it'd be nice to draw a distinction between nuclear physics and plasma physics what is the distinction nuclear physics is about the physics of the nucleus and my department department of nuclear science and engineering at mit is very concerned about all the interactions and reactions and and consequences of things that go on in the nucleus including nuclear energy fission energy which is the nuclear energy that we have already and fusion energy which is the energy source of the sun and stars which we don't quite know how to turn into practical energy uh for humankind at the moment that's what my research has mostly been aimed at but plasmas are essentially the fourth state of matter so if you think about solid liquid gas plasma is the fourth of those states of matter and it's actually the state of matter which one reaches if one raises the temperature so cold things you know like ice are solid um liquids are hotter water and if you heat water beyond 100 degrees celsius it becomes gas uh well that's true of most substances and um plasma is a is a state of matter in which the electrons are unbound from the nuclei so they become separated from the nuclei and can move separately so we have positively charged nuclei and we have negatively charged electrons then the net is is still neutral electrically neutral but a plasma conducts electricity has all sorts of important properties that are associated with that separation and that's what plasmas are all about and the reason why my department is interested in plasma physics very strongly is because most things well for one thing most things in the universe are plasma the vast majority of matter in the universe is plasma but but most particularly stars and the sun are plasmas because they're very hot and it's only in very hot states that nuclear fusion reactions take place and we want to understand how to implement those kind of phenomena on earth maybe another distinction we want to try to get at is a difference between fission and fusion as you mentioned fusion is the kind of reaction happening in the sun so what's vision and what's fusion well fission is taking heavy elements like uranium and breaking them up and it turns out that that process of breaking up heavy elements releases energy what does it mean to be a heavy helmet it means that there are many nuclear particles in the nucleus itself neutrons and protons um in the in the nucleus itself so that in the case of um uranium there are 92 protons in each nucleus and even more neutrons so that the total number of nucleons in the nucleus nucleons is short for for either a proton or a neutron the total number you know might be 235 that's u235 or it might be 238 that's u238 so those are heavy elements light elements by contrast have very few nucleons protons or neutrons in the nucleus hydrogen is the lightest nucleus it has one proton there are actually slightly heavier forms of hydrogen isotopes deuterium has a proton and a neutron and tritium has a proton and two neutrons so it has total of three nucleons in the new in the nucleus well taking light elements like isotopes of hydrogen and not breaking them up but actually fusing them together reacting them together to produce heavier elements typically helium okay which is helium is a nucleus which has has two protons and two neutrons that also releases energy and that and that or reactions like that making heavier elements from lighter elements is what mostly powers the sun and stars both fusion and fission release approximately a million times more energy per unit mass than chemical reactions so a chemical reaction means take hydrogen take oxygen react them together let's say and get water that releases energy the energy released in a chemical reaction like that or the burning of coal or on oil or whatever else is about a million times less per unit mass than what is released in nuclear reactions so but it's hard to do it requires very high energy of impact and actually it's very easy to understand why and that is that those two nuclei if they're both let's say hydrogen nuclei one is let's say deuterium and the other is let's say tritium they're both electrically charged and so the and they're positively charged so they they like charges repel everyone knows that right so basically to get them close enough together to react you have to overcome the repulsion the electric repulsion of the two um nuclei from one another and you have to get them extremely close to one another in order for the nuclear forces to overtake the electrical forces and and actually form a new nucleus and so one requires very high energies of impact in order for reactions to take place and those high energies of impact correspond to very high temperatures of random motion so that's why you can do something like that in the sun so we can build the sun that's one way to do it but uh on earth how do you create a fusion [Laughter] reaction yeah well nature engineering nature's fusion uh reactors are indeed the stars and uh they are very hot in the set in the center and re and they reach the point where they release more energy from those reactions than they lose by radiation and transport to the surface and so forth and that's a state of ignition and and that's what we have to achieve to to give net energy it's like lighting a fire if you if you have a if you have a bundle of sticks and you hold a match up to it and you see smoke coming from the sticks but you take the match away and the and the and the sticks just fizzle out that's not the reason they did it fizzled out is that yes they were burning there was smoke coming from them but they were not ignited but if you are able to take the match away and they keep burning and they are generating enough heat to keep themselves hot and hence keep the reactions going that's chemical ignition well what we need to do what the stars do in order to generate nuclear fusion energy is they are ignited they are generated enough energy to keep themselves hot and that's what we've got to do on earth if we're going to make fusion work on earth but it's much harder to do on earth than it is you know in a star because you know we need temperatures of order tens of millions of degrees celsius in order for the reactions to go fast enough to generate enough electricity to keep it or enough energy to keep it going and and so um if you've got something that's tens of millions of degrees celsius and you want to keep it all together and keep the heat in long enough to have enough reactions taking place you can't just put it in a bottle you know plastic or glass it would be gone you know it's in milliseconds um so um you have to have some non-material mechanism of confining the plasma in the case of stars that non-material force is gravity so gravity is what holds a star together it's what holds the plasma in long enough for it to react and and and sustain itself by the the fusion reactions but on earth gravity is extremely weak i mean i don't mean to say we don't fall yes we fall but the the mutual gravitational attraction of small objects is very weak compared with the electrical repulsion or any other force that you can think about on earth and so we need a stronger force to keep the plasma together to confine it and the predominant attempt at making fusion work on earth is to use magnetic fields to confine the plasma and that's what i've worked on for much essentially most of my career is to understand how we can and how best we can confine these incredibly hot gases plasmas using magnetic fields with the ultimate objective of releasing fusion energy on earth and you know generating electricity with it and powering our society with it a dumb question so on top of the magnetic fields do you also need the plastic water bottle walls or is it purely magnetic fields well actually what we do need walls um those walls must be kept away from the plasma because otherwise they'd be melted or the plasma must be kept away from them inside inside of them but the main purpose of the walls is not to keep the plasma in it's to keep the atmosphere out so if we want to do it on earth where there's air we want the plasma to consist of hydrogen isotopes or other things the things we're trying to react and by the way the density of those plasmas at least in magnetic confinement fusion is very low it's maybe a million times less than the density of air in this room so in order for a fusion reactor like that to work you have to keep all of the air out and just keep the plasma in so yes there are other things but those are things that are relatively easy i mean making a vacuum these days is technologically quite quite straightforward we know how to do that okay what we don't quite know how to do is to make a confinement uh device that isolates the plasma well enough so that it so that it's able to keep itself burning with its own reaction so maybe can you talk about what a takamaka is the russian acronym from which the word tokamak is built just means toroidal magnetic chamber so it's a toroidal chamber taurus is is a geometric shape which is like a doughnut with a hole down the middle okay and so it's the so it's the meat of the doughnut okay that's the taurus um and it's and it's got a magnetic field so that's really all takamak uh means but the particular configuration um that we're the that is very widespread and there's the sort of best prospect in the least in the near term for making fusion energy work is one in which there's a very strong magnetic field the the long way around the doughnut around the torus um so you've got to imagine that there's this doughnut shape with an embedded magnetic field just going round and round the long way the the big advantage of that is that plasma particles are when they're in a in the presence of a magnetic field feel strong forces from the magnetic field and those forces make the particles gyrate around the direction of the magnetic field line so basically the particles follow helical orbits like like a following like a spring that's directed along the magnetic field well if you make the magnetic field go in inside this toroidal chamber and just simply go round and round the chamber then because of this helical orbit the particles can't move fast across the magnetic field but they can move very quickly along the magnetic field and if you have a magnetic field that doesn't leave the chamber it doesn't matter if they move along the magnetic field it does it means it doesn't mean they're going to exit the chamber but if you just had a straight magnetic field as you you know for example coming from um you know a bar a helmholtz coil or or a bar magnet then you'd have to have ends it would come would come to the end ends of the chamber somewhere in the and the particles would hit the ends and and they would lose their energy so that's why it's toroidal and that's why we have a strong magnetic field it's providing a confinement against motion in the in the direction that would lead the particles to leave the chamber it turns out that then here we're getting a little bit technical but it turns out that a toroidal field alone is not enough and so you need more fields to produce true true confinement of plasma and we get those by passing a current as well through the plasma itself i can make sure it stays on track well that what that does is makes the field lines themselves into much bigger helices and that for reasons that are too complicated to explain that clinches the confinement of the particles at least in terms of their single particle orbits so they don't leave the chamber and so when the particles are flying along this uh this this doughnut the inside of the donut uh are they what's where's the generation of the energy coming from are they smashing into each other yeah eventually i mean in a fusion reactor there will be deuterons and triti and tritons and they will be smashing in they will be very hot they'll be 100 million degrees celsius or something so they're moving thermally with very large thermal energies in random directions and they will collide with one another and have fusion reactions when those fusion reactions take place energy is released large amounts of energy is released in the form of particles one of the particles that's released is an alpha particle which is also charged and it's also confined and that alpha particle stays in the in the in the doughnut and heats the other particles that are in that doughnut so it transfers its energy to those and they it keeps them hot there's there's some leaking of heat all the time a little bit of radiation some transport and so forth there's also a neutron released from that reaction the neutron carries out four-fifths of the fusion energy and that will have to be captured in a blanket that surrounds the chamber in which we take the energy drive some kind of electrical generator from you know thermal thermal engine um gas turbine or something like that and power the power you got energy so where do we stand where do we stand on getting this thing to be uh something that actually works it generates energy yep well um there have been experiments that have generated net nuclear energies or nuclear powers in the vicinity of um you know a few tens of megawatts for a few seconds so that's you know 10 megajoules that's not much energy it's a few doughnuts worth of energy okay yeah literal donut that's right um but um but we have studied how well tokamax can confine plasmas and so we now understand in in rather great detail um the way they work and we're able to predict what is going to be required in order to build a tokamak that becomes self-sustaining that that becomes essentially ignited or very so close to ignited that it doesn't matter and and at the moment at least if you use the modest magnetic field values still very strong but but limited limited magnetic field values you have to build a very big device and so we are at the moment worldwide fusion research is at the moment in the process of building a very big experiment that's located in the south of france it's called eta i-t-e-r which means the way or just means the international tokamak experimental reactor if you like um and that experiment is designed to reach this burning plasma state and to generate about 500 megawatts of fusion power for hundreds of seconds at a time it'll still only be an experiment it won't put electricity on the grid or anything like that it's it's to figure out what whether it works and and with what the remaining engineering challenges are it's a scientific experiment it won't be engineered to run round the clock and and so on and so forth which ultimately one one needs to do in order to make something that's practical for generating electricity but it will be the first demonstration on earth of a controlled fusion reaction reaction for you know long time time periods is that exciting to you uh it it it's been an objective that is in many ways motivated my entire career and the career career of many people like me in the field um i have to admit though that one of the problems with eta is that it's an extremely big and expensive and long time to build experiment and so it won't even come into operation until about 2025 even though it's been being built for 10 years and it's been it was designed for 30 years before that right and so that's actually one of the big disappointments of my career in a certain sense which is that we won't get to a burning fusion reaction until well past the first operation of eater and whether i'm alive or not i don't know but i certainly will be well and truly retired by the time that happens and so when i realized maybe some years ago that that was going to be the case it was a discouragement to me let's put it like that but if we can try to look maybe in a ridiculous kind of way look into uh 100 years from now 200 years 500 years from now and we you know there's folks like elon musk uh trying to uh travel outside the solar system i mean the amount of energy we need for some of the exciting things we want to do in this world if we look again 100 years from now uh seems to be a very large amount so do you think fusion energy will eventually uh sometime into your retirement uh will be basically uh behind most of the things we do look i absolutely think that fusion research is completely justified in fact we should be spending more time and effort on it than we currently do but it isn't going to be a magic bullet that somehow solves all the problems of energy by the way that's a generic statement you can make about any energy source in my view i think it's a grave mistake to think that science of any sort is suddenly going to find a magic bullet for meeting all the energy needs of society or any of the other needs of society by the way but and we can talk about that hopefully later but but but but fusion is very worthwhile and we should be doing it um and and so my disappointment that i just expressed was in a certain sense of personal disappointment i do think that fusion energy is a terrific challenge it's very difficult to bring the energy source of the sun and stars down to earth this does contrast in a certain sense with fission energy by contrast fission energy efficient to build a fission reactor proved to be amazingly easy you know we did it um within a few years of discovering nuclear fission people had figured out how to build a reactor and did so um you know during the second world war which is by the way fission is how the current nuclear power plants work yeah and so we have uh nuclear energy today because fission uh reactors are relatively easy to build you've got to have what's hard is getting the materials okay and that's just as well because if everyone could get those materials you know there would be weapons proliferation and so forth but it wasn't um all that long um after even the discovery of nuclear fission that fission reactors were built and fission reactors of course operated before we had weapons um so um i think nuclear power is obviously important to meet the energy challenges of our age it is completely intrinsically completely uh co2 emissions free and in fact the wastes that come from nuclear power whether it's fission or fusion for that matter are so moderate in quantity that that we shouldn't really be worried about them um i mean yes fission products are highly radioactive and and we need to keep them away from people but there's so little of them it's that keeping them away from people is not particularly difficult and so while people complain a lot about the the drawbacks of fish and energy um i think most of those complaints are ill-informed um we can talk about you know the the challenges and the disasters if you like of uh off of fission reactors but i think fission in the near term offers a terrific opportunity for environmentally friendly energy which in which in the world as a whole is rapidly being taken advantage of you know china and india and places like that are rapidly building fission plants we're not rapidly building fission plants in the u.s although we are actually building two at the moment um two new ones um but we do still get 20 of our electricity from fish and energy and we could get a lot more so it's clean energy so it's clean energy now now again the concern is there's a very popular hbo show and just came out on chernobyl uh there's the three mile island there's fukushima that's the most recent disaster so there's a kind of a concern of um yeah i mean nuclear disasters is that what do you make of that kind of uh concern especially if we look into the future of fission energy based uh reactors well first of all let me say one or two words about the contrast between fission and fusion and then we'll come on to the question of the disasters and so forth fission does have some drawbacks and they're and they're largely to do with four four main areas one is do we have enough uranium or other fissile fuels to to supply our energy needs for a long time the answer to that is that we know we have um enough uranium to support fission energy worldwide for thousands of years but maybe not for millions of years okay so that's resources um secondly there there are issues to do with wastes fission wastes are highly radioactive and some of them are volatile and so for example um in fukushima the the problem was that some fraction of the fish and waste were volatilized and went out as a cloud and and polluted air areas with um cesium 137 strontium 90 and things like that so that's a challenge of fission um there's a problem of safety uh beyond that and that is that um in fission it's hard to turn the reactor off when you turn when you stop the nuclear reactions there is still a lot of heat being liberated from the fission products and that is actually what the problem was at fukushima the fukushima reactors were shut down the moment that the earthquake took place and they were shut down safely what then happened after that fukushima was you know there were there was this enormous tidal wave um many tens of meters high that came through and destroyed the electricity grid feed to the fukushima reactors and their cooling was then turned off and it was the after heat of the turned off reactors that eventually caused the problems that led to release and so that so that is that's a safety concern and then and then finally there's a problem of proliferation and that is that fission reactors need fissile fuel and the technologies for producing the under enriching and so forth the fuels can be used can be can be um by by bad actors to generate um the materials needed for a nuclear weapon and that's a very very serious concern so those are the four problems fusion has major advantages in respect of all of those problems it has more uh longer term um fuel resources it has far more benign waste issues the react the radioactivity from fusion reactions is at least a hundred times less than it is from fission reactions it has um no none essentially none of this after heat problem because it doesn't produce fission products that are highly radioactive and generating their own heat when it's turned off in fact the hard part of fusion is turning it on not turning it off and and finally you don't need the same uh fission technology to do to make uh fusion work and so it there it's got terrific advantages from the point of view of proliferation control so those are the those are four main issues which make fusion seem attractive technologically um because they address some of the problems of fission energy i don't mean to say that fission energy is overwhelmingly problematic but clearly there have been catastrophes associated with fission reactors fukushima actually is i think in many ways often overstated as a disaster because after all nobody was killed by the reactors essentially zero and that's in the context of a disaster a tsunami that killed between 15 and 20 000 people instantaneous more or less instantaneously so you know in the scale of risks um one should take the view that uh in my in my in my estimation that um fission energy came out of that looking pretty good okay of course that's not the popular conception okay yes that's gonna i mean with a lot of things that threaten our well-being we seem to be very uh bad uh users of data we seem to be very scared of uh shark attacks and not at all scared of car accidents and this kind of miscalculation and i think from everything and i understand uh nuclear energy efficient based energy goes into that category it's one of the safest one of the cleanest forms of energy and yet the pr uh whoever does the pr for nuclear energy is not uh has a hard job ahead of them at the moment well i think part of that is their association with nuclear weapons right because when you say the word nuclear people don't instantly think about nuclear energy they think about nuclear weapons and and so there is you know perhaps um a natural tendency to do that but yes i agree with you people are very poor at estimating risks and they react emotionally not rationally in most of these situations can we talk about nuclear weapons just for a little bit so fission is the kind of reaction that's central to the nuclear weapons we have today that's what sets them off that's what sets them off so if we look at the hydrogen bomb maybe you can say how these different weapons work so the earliest nuclear weapons the the nuclear bombs that were dropped on japan etc etc were pure fission weapons they used uh enriched uranium or plutonium and their energy is essentially entirely derived from fission reactions but it was early realized that more energy was available if one could somehow combine a fission bomb with um fusion reactions um because the fusion reactions give more energy per unit mass than than fission reactions and these were this was called the super you might have heard of the expression the super or more simply hydrogen bombs okay um bombs which use isotopes of hydrogen and the fusion reactions associated with them like you said it's hard to turn on it's hard to turn on because you need very high temperatures and you need confinement of that long enough for the reactions to take place and so a bomb actually a thermonuclear bomb or a hydrogen bomb has essentially a chemical implosion which then sets off a fission explosion which then sets off and compresses hydrogen isotopes and other things which i don't know because i don't i've never had a security clearance okay so i so i can't betray any secrets about weapons because i've never been a party to them but because i know a lot about this problem i can guess okay um and sets off fusion reactions in the middle okay so that's basically it's that sequence of things which produce these enormous you know multi-megaton uh bombs that have very large yields um and so fusion alone can't get can't get you there it is actually possible to set off or to try to set off little fusion bombs alone without the surrounding fission explosion and that is what is called laser fusion so another approach to fusion which actually is mostly researched in the weapons complex the national labs and so forth because it's more associated with the technology of of weapons is inertial fusion so if if you decide instead of trying to make your plasma just sit there in this taurus in the in the tokamak and be controlled steady state with a magnetic field if you if you're willing to accept that i'll just set off an explosion okay and then i'll gather the energy from that somehow i don't quite know how but let's not ask that question too much um then it is possible to imagine generating fusion alone explosions and and the way you do it is you take some small amount of deuterium tritium fuel you bombard it with energy from all sides and this is what the lasers are used for extremely powerful at lasers which compresses the pe the pelleted fusion and heats it it compresses it to such a high density and temperature that the reactions take place very very quickly and in fact they can take place so quickly that they're it's all over with before the thing flies apart wow and that is heated up really fast that is inertial fusion okay is that useful for energy generation not yet i mean there are those people who think it will be but you may have heard of the big experiment called the national ignition facility which was built at livermore starting in the late 1990s and has been in operation since around about 2010. it was designed in with the claim that it would reach ignition fusion ignition in this pulsed form where the reactions have got over with so quickly before the thing whole thing flies apart it didn't actually reach ignition and i doesn't look as if it will although you know we never know maybe people figure out how to make it work better but the answer is in principle it seems possible to reach ignition in this way maybe not with that particular laser facility are you surprised that uh we humans haven't destroyed ourselves given that we've invented such powerful tools of destruction like what do you make of the the fact that for many decades we've had nuclear weapons now speaking about estimating risk at least to me it's exceptionally surprising i was born in the soviet union that um that big egos of the big leaders when rubbing up against each other have not created uh the kind of destruction one was everybody was afraid of for decades well i must say i'm extremely thankful that it hasn't i don't know whether i'm surprised about it i've never thought about it from the point of view of is it surprising that we've we've avoided it i'm just very thankful that we have i think that there is a sense in which cooler heads have prevailed at crucial moments i think there is also a sense in which you know mutually assured destruction um has in fact worked as a policy to restrain the great powers from going to war and in fact you know the the the fact that we haven't had a world war you know since the 1940s is perhaps even attributable to nuclear weapons in a kind of strange and peculiar way but i think humans are deeply uh flawed and sinful people and i certainly don't feel gap that we're guaranteed that it's going to go on like this and we'll talk about the sort of the biggest picture view of it all uh but let me just ask in terms of your worries of if we look 100 years from now we're in the middle of what is now a natural pandemic that from the looks of it it fortunately is not as bad as it could have possibly been if you look at the spanish flu if you look at the history of pandemics if you look at all the possible pandemics that could have been that that folks like bill gates are exceptionally terrified about we've uh i know many people are suffering uh but it's it's it's better than it could have been uh so and now we're talking about nuclear weapons in terms of existential threats to us as sinful humans uh what worries you the most is it nuclear weapons is is it natural pandemics engineered pandemics nanotechnology in my field of artificial intelligence some people are afraid of uh killer robots and robots yeah is there do you think in those existential terms uh and and do any aspect do any of those things worry you i am certainly not confident that my children and grandchildren will experience the benefits of civilization that i have enjoyed i think it's possible for our civilizations to break down catastrophically i also think that it's possible for our civilizations to break down progressively and i think they will if we continue to have the explosion of population on the planet that we currently have i mean it's quite it's quite wrong to think of our problems as mostly being co2 if we can just solve co2 then we can go on having this you know continually expanding economy everywhere in the world of course you can't do that okay i mean there is a finite you know bearing capacity of our planet on the resources of our planet on the resources of our planet and and we can't continue to do that so i think there are lots of technical reasons why um a continually expanding economy and and uh and civilization is impossible and therefore um actually i'm as much nervous about the fact that our population is eight billion or something uh right now worldwide as i am about um the fact that you know a few million people would be would be killed by covet 19. i mean i don't want to be callous about this but from the big picture it seems like that's much more of a problem overpopulation people not dying is ultimately more of a problem uh than people dying um so you know that probably sounds incredibly callousy or to listeners but i think it's simply you know a sober assessment of the situation is there is there ways from the way those eight billion or seven billion or whatever the number is live that could make it sustainable uh you know because you've kind of implied there's a kind of uh we have especially in the west this kind of capitalist view of uh really consuming a lot of resources is there a way to like if you could change uh one thing or a few things what would you change to make this life make it look more likely that your grandchildren have a better life than you well okay so let's talk a bit about energy because that's something i know a lot a lot about having thought about it most of my career in order to reach a steady-state co2 level okay that's acceptable in terms of global climate change and so on and so forth we need to reduce our carbon emissions by at least a factor of 10 worldwide okay what's more you know um the average energy consumption and hence co2 emission of people in the world is less than a tenth of what we per capita of than what we have in the west in america and europe and so forth so if you have in mind some utopia in the future where we can where we've reached a sustainable use of energy and we've also reached a situation in which there's far less inequity in the world in the sense that people have share the energy resources more uniformly then what what that is equivalent to would be to reduce the co2 emissions in western economies not by a factor of 10 but by a factor of 100 in other words has to go down to one percent of what it is now okay yeah so you know when people talk about uh you know let's use natural gas because you know maybe it only uses 60 of the energy of coal it's complete nonsense we that's not not even scratching the surface of what we would need to do so you know is that going to be feasible i i i very much doubt it and therefore i actually doubt that we can reach um a level of energy of fossil energy use that is one percent of the current use in the west without totally dramatic changes either in you know our society our use of of energy and so forth which actually of course is much of that energy is used for producing food and so on and so forth so it's actually not so obvious that we can we can get we can cut down our energy usage by that factor or we've got to reduce the human population population so you run up against that number that's increasing still and you don't think that could be it's depressing no it's not uh it's not it's not it's not depressing it's um it's difficult like many truths are uh do you do you have a hope uh that there could be a technological solution in short no there is no technological solution to for example for population control i mean we have the technology just you know to prevent ourselves bearing children that's not a problem technology's in okay solved the challenge is society the challenges human choices the challenges almost entirely human and sociological not technology not technology and when people thought talk about energy they they think that there's some kind of technological magic bullet for this but there isn't okay and and there isn't for the reasons i just mentioned not because it's obvious there isn't but actually there isn't uh and and in in any case um that it's true of energy it's true of pollution it's true of human population it's true of most of the big challenges in our society are not scientific or technological challenges they're human sociological challenges and that's why i think it's a terrible mistake um even for folks like me who work at you know well the high temple of science and technology in in america and maybe in the galaxy yeah i mean you know it's it's it's mit it's mit best university in the world it's it's a terrible mistake if we give the impression that technology is going to solve it all technology will make tremendous contributions and i think it's it's worth working on it but it's a disaster if you think it's going to solve all of our problems and and actually um you know i've written a whole book about the question of of scientism and the and the over emphasis on science both as a way of of solving problems through technology but also as a way of gaining knowledge i think it's not all of the knowledge there is either yeah i think that book and uh your journey there is fascinating so maybe you can go there can can you tell me about your on a personal side your the personal journey of your faith of christianity and your relationship with uh with god with religion in general yeah in my in my latest book uh can a scientist believe in miracles i i i give a first i devote most of the first chapter to telling how how i became a christian um why i became a christian i i didn't grow up as a christian which is fascinating i mean you didn't grow up as a christian so you you've discovered the beauty of uh god and physics at the same time that's a very poetic way of putting it but yes i would accept that um i became a christian when i was an undergraduate at cambridge university um i i had you know i had gone to a school in which there was religion kind of was part of the society there were prayers and at the at the at the daily you know gathering of the of the students uh the assembly of the students um but i but i didn't really believe it i just sort of went along with it and it wasn't particularly you know aggressive or benign you know blind it just sort of was there um but i didn't believe it um i didn't didn't make much sense to me but when i but i came across christians from time to time and when i went to cambridge university um two of my closest friends who turned out were christians and i think it was that was the most important influence on me um that that here were uh two people who were really smart like me i i'm giving you my yeah my impression at the time the way i the way i felt at the time um and and they thought christianity made sense and and you know testified to its significance in their lives and so that was a very important influence on me and i and ultimately i mean the reason i i i hadn't i hadn't i didn't see christianity as some kind of great evil the way it's sometimes portrayed by the by the radical atheists of this century i mean i think that's nonsense but but but i so i think there were certain attractive things if you go to a university like cambridge you know you're surrounded by by by western culture you know from from about you know the 15th century onwards and that saturated with christian art and architecture and so forth and so it's hard it's hard not to recognize that christianity is in fact the foundation of western society in western culture well western civilization um so so i i mean maybe i was in that sense favorably disposed towards christianity as a religion but as a personal faith it didn't mean anything to me but i became convinced really of two things one is that the evidence for the resurrection of jesus christ is actually rather good i mean it's not a proof it's not kind of some some kind of scientific demonstrate or mathematical demonstration but it's actually extremely good it's not scientific evidence by and large it's historical evidence historical evidence yeah um so that was one thing and the other thing that came to me when i was at cambridge it became clear that christianity ultimately is not you know some kind of moral theory or philosophy or something like that it is or elite or at least it claims to be um a personal relationship with god which is made possible you know by um what jesus did and on the cross and and his life and his teaching and and it's a personal call to a relationship with god and that had i'd never thought of it in those terms when i was you know when i was younger and that that that thought became um attractive to me i mean i i think most people find the person of christ and his teachings you know compelling insert in a certain sense what do you mean by personal do you mean personal for you like a relationship like it's a meditative like you specifically you even have a connection uh with god uh and and then the other side you say personal um with the actual body the person of jesus christ so all of those things what do you mean by personal connection and why that was me well so as well for the stupid question no that's okay no problem as a christian i believe that i have a relationship with god which is best expressed by saying that it's personal and that comes about because you know jesus through his acts has reconciled me with god me a sinner me someone full of of of of sins of of failings of ways in which i don't live up to even my own ideals let alone the ideals of a holy god have been reconciled to the creator of everything um and and so christians myself included believe that prayer is in a certain sense a connection with god and there are times when i have felt you know that god spoke to me i don't mean necessarily orally in words but showed me things or enlightened me or inspired me in ways um that um i i attribute to him so i see it as a as a two-way you know relationship in a certain sense of course it's a very asymmetrical relationship but nevertheless christians think that it's a two-way it's a two-way street we're not just talking into the air when we say we want i'm going to pray for someone in this two-way communication uh is there a way that you could try to describe on a podcast what is god what is god like uh in your view if if you try to describe is it a force um is it a is it uh for you intellectually is a set of metaphors that you use to reason about the world is it um is it uh is it is it kind of a computer that does some computation that's the infinitely powerful computer uh or is it like santa claus a guy with a with a beard on the cloud like uh i don't mean um i don't mean what god actually is i mean in your limited uh cognitive capacity as a human what do you actually uh what do you find helpful for thinking of what god actually looks like what is god well let me start by saying none of the above okay i mean clearly god in the christian god um uh the god of abraham isaac and jacob etc um it is is not any of those things because all of those things you just mentioned are phenomena or or or entities in the created world and the most fundamental thing about monotheism as you know abraham and moses and so forth handed it down is that god is not an entity within the creation within the universe that god is the creator of it all and that's what genesis first two chapters of genesis is really about it's it's not it's not about telling us you know how god created the world it's about telling us and telling the early hebrews that god created the world okay and that therefore he is not you know simply an entity within it on the other hand you know our finite minds have a pretty hard time encompassing that so so one has to therefore work in terms of metaphors and images and and so forth and um i think we would know very little about who god is um if we if it was simply uh if we were simply left to our own devices you know if if we were just you know here you are you're in the universe try to figure out who who made it and uh and so forth well you know philosophers think they can do a little bit of that maybe uh and theologians think that they can do a little bit more but um but christians think uh that god has actually helped us along a lot by revealing himself and and we say that he's revealed himself supremely in the person of jesus christ um and so you know when jesus says to his disciples if you've seen me you've seen the father then that is in a certain sense a watch word for answering this question for christians it is that supremely if we want to help ourselves understand who god really is we look to jesus we look to what he did we look to what he said uh and so forth um and we believe that he is one with the father and that's why we believe you know in the trinity i mean it's basically because um that revelation is extremely um central to christian belief and teaching so in that in that sense through jesus there was um that's kind of a historical moment that's profound that's really powerful but do you also think that god makes himself seen in less obvious ways in our world today absolutely absolutely i mean it's it's certainly been the outlook of um jews and christians throughout history that god is seen in the creation that we when we look at the creation we see to some extent the wonder the majesty the might of the person or the entity but the person who created it and and that's a way in which scientists particularly uh have over over the ages and certainly over most of the last five centuries since the scientific revolution scientists have seen in a certain sense the hand of god in creation i mean this leads us perhaps to a different discussion but i mean it's it's remarkable to me how influential um christianity and religion in generally has been in science yeah most of the scientists through history as if you described i mean god has been a very big part of their life and they were certainly up until the beginning of the 20th century that was the case so maybe this is a good time to can you tell me what scientism is yeah i mean the short answer is that's by scientism we me we mean the belief that science is all the real knowledge there is um and that's a shorthand there are lots of different facets of it and what which one can explore and the book in which i explored it most most thoroughly was actually an earlier book called monopolizing knowledge and and the the purpose of that title is to is to draw attention to the fact that in our society as a whole in particular in the west today we we have grown so reliant on science that we that we tend to put aside other ways of getting to know things and so of course at mit we are focused on science and we do focus on it very much but the truth is that there are many ways of getting to know things in our world know things reliably in our world and a lot of them are not science so scientism in my view is a terrible intellectual error it's to be it's the belief that somehow the methods of science as we've developed them with ex you know experiments and and in the end they it relies particularly upon reproducibility in the world and on a kind of clarity that comes from measurements and mathematics and related types of of skills those powerful though they are for finding out about the world are not all the knowledge do not give us all the knowledge we we have and there's many other forms of knowledge and the illustration that i usually use to to try to help people to think about this is to say well look let's think about human history i mean to what extent can human history be discovered scientifically the answer is essentially it can't because and the reason is because human history is not reproducible you can't do reproducible experiments or observations and and go back and you know try it over again it's it's a one-off thing you know the history is full of unique events and and so you you know you you you can't hope to do history using the methods of science yeah i mean in in some sense history is a story of miracles i mean they don't have to have to do with god it's just uniqueness is anyway unique events these unique events and uh that science doesn't like that because it's uh unique events but they're very definition or not reproducible um can i ask sort of a tricky question i don't even know what atheist or atheism is but is it possible for somebody to be an atheist and avoid um slipping into scientism oh yeah absolutely i mean i mean there the these are two separate things okay i'm quite sure there are many people who don't believe in god and yet recognize that there are many different ways of we get knowledge you know some is history some is sociology economics politics um philosophy art history uh language literature et cetera et cetera there are many people who recognize those disciplines as having their own approaches to epistemology and to get how we get knowledge and valuing them very highly i don't mean to say that everyone you know who's an atheist automatically you know subscribes to scientific viewpoint that's not true but it's certainly the case that many of the arguments in fact most of the arguments of the aggressive atheists of this century people are sometimes called new atheists although they're actually rather old most of their arguments are rather old you know are drawing heavily on scientism so when they say things like there's no evidence to support christianity okay what they are really focusing on is to say is saying that christianity isn't proved or the evidence for christianity is not science okay science doesn't prove it and and you you know if you read their books that's what you find they really mean is science doesn't lead you necessarily to believe in a creator god or into in any particular in um religion i accept that that's not a problem to me because i don't think that science is all the knowledge there is and i think there are other important ways of getting to know things and one of them is historical for example and i mentioned earlier that i think i became persuaded and i were and i still am persuaded that the historical evidence for the resurrection is very is very persuasive again it's not proof or anything like that but it's but it's pretty good evidence okay yeah i've um i talked to richard dawkins on this podcast and um and uh i saw you debate with sean carroll so i i i understand this world it makes it makes me very curious but maybe uh let me ask sort of another way my own kind of uh world view maybe you can help as by way of therapy i understand um you know because you kind of said that there's other ways of knowing what about if we cut if if i kind of sit here and am cognizant of the fact that i almost don't know anything so sort of i'm sit here almost paralyzed by the the mystery of it all and it's not even when you say there's other ways of knowing it it feels almost too confident to me because uh yeah when i when i listen to beautiful music or see art there's something there that's and that's uh that's beyond the reach of scientism i would say so beyond the reach of uh the the tools of science but i don't even feel like that could be an as an actual tool of knowing it um yeah i just don't even know where to begin because it just feels like we know so little like uh if we look even a hundred years from now when people look back to this time humans look back to this time they'll probably laugh at how little we knew even a hundred years from now and if we look at a thousand years from now hopefully we're still alive or some version of our ai versions of ourselves you know they they'll certainly laugh at the absurdity of our beliefs so what do you uh so you don't seem to be as paralyzed by how little we know you confidently push on forward but what do you make of that sense of uh of just not knowing of the mystery we need to be modest or or humble if even about what we know i accept that and i i certainly think that's true not not simply because in the future we'll know more science and there will be more powerful ways of finding out about things but simply because you know sometimes we're not right we're wrong okay in what we think we know um uh so that's crucial but it's also a very christian outlook that kind of humility is what jesus taught so i so i don't know whether this was in the back of your mind when you were thinking about this but it's often the case that um people of religious faith are are accused of being dogmatists okay and there is a sense in which dogma teaching accepted teaching is is part of religions okay but i don't think that necessarily uh uh that leads one to blind dogmatism and i don't i certainly don't think that faith we can talk about this later if you'd like but i certainly don't think that faith means thinking you know something and not listening to counter arguments for example um so i i think that's crucial yeah what is uh what does faith mean to you what does it feel like what is it actually sort of how do you carry your faith in terms of the way you see the world well i think faith is very often misunderstood in our society at the moment um because uh it's often portrayed as being nothing other than uh believing things you know ain't true you know um or or believing things that are are not proven okay um and um and this and faith does have a strand which is to do with you know basically believing in uh in concepts or um propositions but actually the word faith is much broader than that faith also means um you know trusting in something trusting in a person or trusting in a thing uh the reliability of some technology for example um that's equally part of the meaning of the word faith and and there's a third strand to the to the meaning of the word as well and that is loyalty so you know i have faith in my wife and and i try to act in faith towards her and that's a kind of loyalty and so those three strands are the are the most important strands of the meaning of faith yes belief in in propositions that we might not have you know full proof about or maybe we have very little proof about but it's also trust and and loyalty and actually in the in terms of the christian faith christians are far more called to trust and loyalty than they are to belief in things they don't you know don't have proof of okay um but but the critics of religion generally um tend to emphasize the first one and say well you know you believe things for which you have no evidence okay that's what that's what they think faith is well yeah there there is a sense in which everybody has to live their lives uh believing or or or making decisions in situations when they don't have all the proof or evidence or knowledge that enables you to make a completely um rational or well-informed or prudent decision we you know we do this all the time you know my drive down here i nearly took a wrong turning and i thought which which way do i go do i keep going straight on and so my uh voice came out and i think go straight okay so so you have to make decisions and sometimes you know you don't have a navigation system telling you what to do you just have to make that decision with no with insufficient evidence and you're doing it all the time as a human and that's part of being sentient um and so that kind of um action and belief on the basis of incomplete evidence is not something that i feel uncomfortable doing or i feel that i feel on that somehow my christian commitments have forced me to do when i wouldn't have had to have done it otherwise i would have had to do it anyway um and and so you know there's a sense in which um i think it's important to see the breadth of meaning of faith and and and to recognize then certainly in the case of christianity um it's trust and loyalty that the the key themes that we're called to and i mean another interesting extension of that that you speak to it's kind of loyalty is referring to uh a connection with something outside of yourself yeah um so i think you've spoken about like existentialism or even just atheism in general as um as leading naturally to an individualism as a focus on the on the self and uh ideas that maybe the christian faith can instill in you is um allowing you to sort of look outside of yourself so connection i mean loyalty fundamentally is about other beings and yeah other beings and i mean i think i don't know what it is in me but i'm very much drawn to that idea and i think humans in general are drawn to that idea you can you can make all kinds of evolutionary arguments all that kind of stuff but uh people always kind of tease me uh because i talk about love a lot and i mean there's a lot of uh non-scientific things about love right like what what the heck is that thing why why do we even need that thing it uh it seems to be an annoying burden that uh that we we get so much uh joy in in life from a connection with other human beings deep uh lasting connections with human beings same thing with loyalty why why do we get so much value and pleasure and strength and meaning from loyalty from a connection with somebody else going through uh thick and thin with somebody else going through some hard times i mean some of the you know the closest friends i i have is going through some some rough times together and that seems to make life deeply meaningful what is that so yeah um i that's that resonates with me and i obviously i would i would affirm it um i i think just to just to correct the implication that you made i i don't think it's necessarily the co the consequence of atheism uh that we that we lose track of those kinds of things i i mean i think that atheists can be loyal okay if you like um the question more often comes up in the context of you know where does morality come from and loyalty i think and duty are related to one another you know if we have loyalty to someone then we have a duty to them okay as well and i think that in so far as we see ourselves as having some kinds any kinds of duties or moral compulsions with respect to our relationships to other people it's i think it's a question that always arises well where does these where do these come from and there there are various approaches that people have towards deciding what makes ethics or morality moral okay but i do think it's the case that um it's very hard to ground morality um in in any kind of absolute way or a persuasive way um in mere human relationships and so it's certainly the case that in christianity um there is a sense in which um morality and you know the morality of morals comes from a transcendent place from a transcendent deity and that we um that we ground our the compelling force of of morals on god more than we do on individuals because after all you know if it if you if you've got nothing but you know other people why should you you know treat your neighbor well why shouldn't you defraud your neighbor if it's good for you well you know you can construct all kinds of arguments and some of them are you know obviously arguments that are commonplace in religion too you should do as you would be done by and all this kind of thing right but none of that seems any any more than mere pragmatism to most people okay and so that's what that's one of the things if that nature amongst others you know really identified you know if god is dead if the idea of god is grounding our moral behavior is no longer viable in the west which nietzsche thought that it wasn't okay then what does ground it and he had no good answer for it in fact he claimed there was no answer but then he couldn't live with that and so he invented the idea of the ubermensch you know this the superior human being okay and this was uh a different way of trying to ground morality not a very successful one you know you could argue that is the forerunner of the sort of uh racism of hitler's regime and and and so forth um that you know we've in the west thankfully shied away from uh in in the past uh uh half or three quarters of a century but um you know i think it is the case that uh christianity gives me a basis for my moral beliefs that is more than mere pragmatism yeah but there is uh so stepping outside of all of that there does seem to be a powerful stabilizing like we humans are able to hold ideas together like in a distributed way uh outside of whether god exists or not or any that just our ability to kind of converse together towards a set of beliefs uh into sometimes into tribes it's kind of um i don't know if it's inherent to being human beings and i hope not because now if i look on twitter uh and there's uh there's the red team and the blue team right it's almost like uh it's it's a charac it's some kind of tv show that we're living in uh that people get into these tribes and they hold a set of beliefs that sometimes don't um i mean they they are beliefs for the sake of holding those beliefs and we get this intimate connection between each other for sharing those beliefs and we spoke to the things about loyalty and love and that's the thing that people feel inside the tribe and it seems very human that within that tribe those beliefs don't necessarily always have to be connected to anything it's just the fact that uh you know i've uh did sports uh uh my whole life whenever you're on a team the bond you get with other people on the team is incredible and the actual sport is is often the silliest i mean i don't play ball sports anymore but the ball when i played like soccer or tennis i mean all those sports are silly right you're playing with a little ball but there's the bond you get is so deeply meaningful so i just it's interesting to me on on the sociological level that um it's it's possible to me whatever the beliefs of religion is um whatever they're actually grounded in they might be uh they might have a power in themselves i think there is tribalism everywhere and i think tribalism in the u.s at the moment is rather difficult to bear from my point of view um and it's i think fed by the internet and social media and so forth but but it's but historically tribalism is has been a trait and remains a trait in humans the genius of christianity is that it supersedes tribalism i mean yes when the hebrews um thought about yahweh initially they thought about him as their tribal deity just like the tribal deities round about about them and so but and and yet from you know early on in hebrew history the crucial thing that yahweh came to mean or i would say revealed of himself to them was that he wasn't just a tribal deity he was the god that created the whole thing and if he is the god of the whole thing then he's not just the god of the hebrews or in the case of you know americans god is not just the god of americans he's the god of everybody okay and that is a way in a way the most amazing transcending of tribal loyalties and uh one of the crucial you know occasions in the new testament um you know when the holy spirit comes at pentecost um you know the the the apostles and the and the disciples speak in other tongues and there are people from all all the countries you know round about hear them in their own languages and so you know whether whether you take that as factual or not that is the a statement of the transcendent um aspects of christianity or the claimed transcendent aspects of christianity that it transcends culture and that's certainly something which i find appealing when i kind of uh touch on this topic in my own mind uh one of the hardest questions is as is why is there suffering in the world do you have a good answer well i have i have some answers um but you're right that it is one of the toughest questions the problem of pain or the problem of suffering um or the problem of uh theodicy as as theologians call it is is is probably one of the toughest i think it's important to um say that there are certain types of answers to this question but there are aspects of this question to which there is no intellectual answer that is going to satisfy um and and the the fact of the matter is you know when i'm speaking to an audience uh let's say um at some kind of lecture i can be sure that there are peop there are people in that audience who are either personally suffering they've got illness they've got pains they're maybe they're facing death or someone in their family is in similar sorts of situations so suffering is a reality and and and there is nothing that i can say that is going to solve their feeling of agony and angst and and maybe despair um in those types of situations there is really only one thing that i think humans can do for one another in those kinds of situations and that is simply to be there to be there alongside your friend or your or your colleague or or whoever you know family member or whoever it might be um and that's the only really sense in which we can give comfort if we try to give intellectual solutions to these problems were going to be like like the comforters that were in the book of job in the in the bible um who who brought no comfort to job himself um with their intellectual answers but if they had been there and some of them were there they sat alongside um that is some level of comfort um and and after all that's the meaning of the word compassion it means to suffer alongside of somebody and i would say first off you know what does a christian say about suffering the the first thing a christian should say is compassion is all that really counts and what's more we say that god has acted in compassion towards us that is to say he has suffered with us in the person of jesus christ and when we see the passion of jesus we recognize that god takes suffering deadly seriously has taken it so seriously that he's been willing to come and be a part of his creation in the person of of jesus christ and suffer death the most horrible death on the cross um and for our benefit so that's one side of of suffering but the question no the philosophical question remains you know surely if god is good you know and god is omnipotent um benevolent um you know why doesn't he uh take away all the suffering why doesn't he cause miracles to occur that will take away all this suffering um i think there are some good answers to that question um in the in the following sense that um you know we live in a world where the consistency of the world is an absolutely crucial part of it you know the fact that our world behaves reproducibly in the main is absolutely essential for the integrity of our lives without it we wouldn't exist okay and so there is a sense in which the integrity of creation um calls for there being consistent behavior which you know these days we think of as being the laws of nature okay and so the consistent behavior of nature is very very important it's what enables us to be what we are um and if you're calling upon god in in in in your critique of why isn't this benevolent creator you know fixing things um one answer is he's fixed things in a certain sense to have an integrity in them and that integrity is the best thing it's the way we have our existence the way we live and move and have our being and you know if you want something different you've got to show that there is a way in which you could invent a world that is better that it has the integrity that we need to exist okay and and and to be able to think and and and love and and be um but but you were gonna do it better you know and the atheists think that maybe they have got a better idea but if they thought about it a bit more carefully they'd realize no one has put forward a better idea okay so the so another way to say that uh i mean is that suffering is an integral part of this of um of a consistent existence so so sort of uh in the philosophical in a philosophical sense uh the full richness and the beauty of our experience would not be as beautiful would not be as rich if there was no suffering in the world is that is that possible well i think you said two different things that aren't exactly at least that aren't exactly the same one is that suffering is an integral part of our experience you know that might be considered a challenge to certain types of christian theology or or even jewish theology in other words christians talk about the fall and talk about uh adam and eve in the garden and and have that have a vision of there being some kind of pers perception from or or perfection from which we have fallen and i think there is a perfection from which we've fallen but i don't think that perfection is some kind of physical com perfection in other words i don't subscribe personally to the view that some some christians do that there was some state prior to the fall in which death did not occur i don't think that that's consistent with science as we know it and i and i think that um death for example has been part of the biological world and and the universe as a whole um from from billions of years ago so so just to be clear about that um you know i i on the other hand i do so if that's the case then certainly in that sense at the very least um suffering or at least death okay is part of the biological existence and that probably seems so completely obvious to somebody who you know is okay with science whether they you know whether they're a scientist or not well so and i apologize if i'm interrupting but it's the obvious reality of of uh our life today but there's a lot of people i think it's currently in vogue i've talked to quite a few folks who kind of see as the goal of many of our pursuits as to extend life indefinitely a sort of uh you know a dream for many people is to live forever uh but in the in this in the technological world in the engineering world in the scientific world i mean that's that's the big dream to me it feels like that's not a dream it's i certainly would like to live forever uh like that that's the initial feeling the instinctual feeling because you know life is so amazing but then if you actually kind of like you've presented it if you actually uh lived that kind of life you would realize that that's actually a step backwards that's a step down from the experience of this life in my sense that death is an essential part of life about the essential part of this experience death of all things so the thing the fact that things end somehow and the scarcity of things somehow create the beauty of this experience that we have yeah transhumanism doesn't look very attractive to me either but it also doesn't look very feasible um but that's a whole big topic that i'm not exactly an expert but i'll say but i but you know i've i'm of a certain age where my mortality is more pressing or more obvious to me than it once was okay um and um and i don't dread that i don't see that as in a certain sense even the enemy okay you're not afraid of death well i'm afraid of lots of things in a in a in a conceptual way but it doesn't keep me awake at night okay um i i'm i think like most people i'm more afraid of pain than i am of death so i i don't want to put myself forward to some kind of hero that doesn't worry about these things that's not true but i i do think and then and maybe this is part of my christian outlook um that there is life beyond the grave um but i don't think that that it's life in this universe or in this um certainly not in this body and maybe not in a certain sense in this mind i mean you know christian christian belief in the afterlife is is that we will be resurrected we will in a certain sense be with god i don't know what that means and i don't think anybody else really quite knows what that means but there are lots of ways that over history people artists and and and writers and so forth have pictured it um and these are all perhaps some of them helpful ways of thinking about it do you think it's possible to know what happens after we die um i i don't think we find out by near-death experiences or those kinds of things but but i but i think that you know that we have sufficient i feel i have sufficient information if you like um in terms of god's revelation to be confident that that i will go somewhere else okay but it won't be here and i to me the aspirations of transhumanism are horrific i mean i think it would be a nightmare not a dream a nightmare you know to be somehow downloaded into a computer and live one's life like that because it it completely discounts the in integrity of our bodies as well as our minds i mean we aren't just disembodied minds it would not be me that was in the computer it would be something else if if that kind of download were possible of course it isn't possible and it's very long way from being possible but you know amazing things happen so we shouldn't be too cert so this is this is a place that uh again maybe taking a slight step outside uh we're philosophizing a little bit uh let me ask you about uh human level or superhuman level intelligence uh the uh artificial intelligence systems do you what do you make from um from almost a religious or a perspective that we've been talking about of the special aspect of human nature of us creating intelligence systems that exhibit some elements of that human nature is that something again like we were talking about with transhumanism uh there's a feasibility question of how hard is it to actually build machines or human level intelligence or have something like consciousness or have all those kinds of human qualities and then there's the do we want to do that kind of thing so on both of those directions what do you think well okay so you know since your podcast is called ai i don't want to offend too many of your listeners out there that's but i but i i think one should be a little bit more modest about one's claims for ai than have typically been the case yeah i think that actually a lot of people in ai are somewhat chastened and so there there are more modest claims than are common with the transhumanists and yes and and so forth um and you know i used to play chess when i was a kid i was pretty good at it okay um he won competitions and so so on and so forth and i when i'm talking about when i was in high school i thought it was pretty unlikely that a computer would be able to become good at chess but i was dead wrong okay and so you know um how did that make you feel by the way when um do you blew big kids i stopped playing chess seriously when i had when i encountered computers that could beat me okay i still play with my grandchildren a little bit but but um but yeah it it seemed like in a certain sense it became a solved problem uh when a.i was able to do it better than i could so i think that there are ways in which today we've seen um computers do things which historically were regarded as being very characteristic of human intelligence and in that sense there there is some success to ai i also think that um you know there are certain things which one might think of as being ai which are you know completely widespread in our society i'm thinking about the internet search engines uh um and so forth which are enormously influential and obviously do things more powerfully than any individual human or even any combination of humans could do much faster and and and uh accessing databases and so on and so forth all of this is uh outstripped our human intelligence um i'm not sure the extent though to which that is really intelligence uh in the way that was traditionally meant but it's certainly amazingly um facile and it it multiplies our ability to access human knowledge and and data and so forth so is that something is that enter the realm of something we should be concerned about so in the realm of religion you talk about what is good what is evil what is right what is wrong you have a set of morals set of beliefs and when you have an entity come into the picture that that has quite a bit of power if we potentially look into the future and intelligence and capability um do you think there's something that religion can say about artificial intelligence or is that something you we shouldn't worry about until it arrives you think just like with the chess program um you know religious writers have thought about this for centuries uh you know there's been a long debate about what is what it was historically called the plurality of worlds and it was actually more about whether there are places where other intelligent creatures live than it was about us creating them but but i think it's largely the same question it's almost like aliens yeah other intelligence so if there is other intelligent life in the universe what is its relationship to god okay that is in a certain sense the puzzle that religious thinkers and writers have thought about for a long time and there's a whole range of of different opinions about that i mean personally you know i think it's it's an interesting question but it's not a very pressing question at the moment um yeah and i think the same way about the the question of what happens if we're able to build a sentient robot for example i think it's an interesting question and we'll have to think about it when that happens but i think we're still quite a ways away from that and so i i don't have a good answer um but i think there's a literature that you one could tap um to think about okay if you want to start early on the question yeah well let me ask you another impossible question you know from a religious or from a personal perspective what do you think is consciousness this this uh subjective experience that we seem to be having does uh this does uh the christian religion have something to say about consciousness does your own when you look in the mirror do you have a sense of what is consciousness um i think the bible doesn't have much in the way of answers about that directly in the sense that you're perhaps asking it which is more like i think you're asking for some kind of uh quasi scientific or maybe indeed scientific uh uh description that's not really looking for one yes um i i think that i think that there it's an interesting question i think it's actually um a it's a jump too far i think we have we don't even know the answer to the question what is the mind let alone consciousness so if you distinguish between those two things i think the question that's being addressed more directly scientifically as well as in other ways it is what is the mind and that is certainly a very topical question even in places like mit which is not historically involved with philosophical questions you know that people doing neuroscience and so forth i think it's a very important question and i think that we're going to find that um we are not computers in other words i think the the commonplace theory of what mind is is is generally speaking by analogy that we are basically wet wet wear okay um that we that we're some computer-like entity and that that the analogy to digital computers is is is a pretty decent one i mean that that's of course a viewpoint which um you know which drives the aspirations of the transhumanists i mean they they so much believe that our minds are nothing other than you know a certain sense some kind of implementation of software in biology that they say to themselves well of course we're going to be able to download it into a into a digital computer i don't think that's true i think it's most likely that quantum mechanics is very important in the brain uh it seems most unlikely that it's not to me i know that that's contrary to the opinions of many people but but that's my view and it's also a view for example of people like roger penrose and people like that who've written about it rather extensively and if that's the case then really my mind is not reproduce reducible to some kind of software which can be considered to be portable it is so connected to the hardware of my body that the two are inseparable okay and so if that is in fact what we find um as i suspect will be the case then the aspirations of the transhumanists will be very long in coming if at all um so i think that actually physics and chemistry um you know are in a certain are in a sense um uh involved with the brain and within the mind but not in a very simple way like you know like the computer analogy um in in a much more complicated way and i also think that um it's philosophically ignorant to speak as if um when and if the actions of the brain are are understood at the physical and chemical level that will me that the mind will vanish as a concept you know that we'll just say we're nothing but brains okay of course it won't i mean it may well be that our mind is an emergent phenomenon that comes out of the physics and chemistry and biology okay but it's also something that we have to encounter and take seriously and so um you know it's it's not the case that it that the mind is reducible to nothing but physics and chemistry even if it's embedded in you know continuously into physics and chemistry as i rather suspect it is um so i that that's my own view i mean another way of putting it is that the mind or the soul is not something added into humans as might have been the viewpoint um historically i do think there is you know there is something added to humans but it's not it's not the mind it's the spirit and that takes us beyond the physical context beyond this universe but i but i don't think that that consciousness the mind et cetera et cetera is that thing which is necessarily added in explicit so i mean i'm not a substance duelist in that sense okay if you want to put it philosophically i mean um but you see you your senses um so the mind and the intelligence and consciousness can be these emergent things do you have do you have a hope a sense that science could help us get pretty far down the road of understanding we will get much further than we have and we it'll be interesting um i mean right now our our methods of diagnosing the human brain are extremely primitive i mean the resolution that we have you know that comes out of uh out of nmr and and brain scans and so forth is miserable compared with what we need in order to understand the brain at the cellular level let alone at the at the atomic level um but uh you know we're making progress it's relatively slow progress but it's progress and people are working on it and we're going to get better at it and we'll find out very interesting things as we do um the time resolution is also completely hopeless compared compare with what we need to understand the thought you know so um so there's a long way to go and we will get better at it um but i'm but i'm not at all worried as some people are and some people speak as if there's a good thing that somehow the concepts of humanity and the mind and religion and and consciousness are going to vanish because we're going to have you know complete uh physical chemical description of the brain in the near future that we're not going to have that and secondly even if we had it the mind and all these other things aren't going to vanish because of it well i i find kind of compelling that the notion that whoever created this universe and us uh did so to understand itself himself i mean that there's this um there's a powerful self reflection notion to this whole experiment that we're a part of i certainly think that god takes delight in his creation and that it was created for that delight as much as it was um for any other reason and that you know that therefore are there's reason to be hopeful and and awestruck by the creation whether it's on the very small or on the very large i'm not sure if you're familiar there's something called the simulation hypothesis that's been fun to talk about with the computer scientists and so on which is a kind of thought experiment that proposes that you know the entirety of the world around us is a kind of a computer program that's a simulation and then we're living inside it i think there's um i think from a certain perspective that could be consistent with a religious view of the world i mean you could just use different terms uh basically uh what are your but it's a it's a it feels like a more um modern updated version of that but what is what's your sense of this uh or the simulation hypothesis do you find it interesting useful to think about it do you find it ridiculous did you find it fun what what are your thoughts uh it's fun and it's been of course the subject of various movies yeah um that that some of which are very well known um you know i don't think it makes sense to think of it as a simulation hypothesis in the sense that we're really lying in uh banks um of of uh on banks of beds having our energy drained away from us um and and the simulation is going on in our individual brains that that makes no sense to me at all i don't think that's what's meant by the simulation hypothesis as as you're using it now but i think that there is a um there is very little distinction between saying that a an intelligent creator has set up the universe according to his will and his plan and set it in motion and is allowing it to run out maybe as christians say he's sustaining it actually um by his word of power it says in the book of the letter to hebrews okay in in in this amazingly consistent and um integrated way um i don't think there's very much difference between saying that and saying that it's assimilation okay i mean i think it's almost the same thing okay but i but i think from but i think it's important to recognize that the simulation in that concept the simulation and the creation or the or the universe are the same thing okay in other words it's a simulation you know that is billions of light years across okay yeah um i mean there's a sense in which it helps one understand especially if you're not religious that there is something outside of the world that we live in that there's something bigger than the world we live in um and that i mean it's just another perspective on uh that humbles humbles you um so in that sense it's a powerful thought experiment one shortcoming of that is is the following is of the of the analogy here's this that we think of a simulation as something take taking place in the universe you know when we it's it's taking place in my computer okay i don't think that's the right analogy for um a christian view of creation okay i don't think it's taking place in some other universe that god has made okay i think maybe it's taking place in the mind of god christians might hypothesize also but i but i think that that that it's important to recognize that christian theology at a at any rate is that god is not one of the entities in the universe and and presumably therefore is very different from a simulation that we might run on a computer let me ask you adam and eve even adam ate of the fruit of the tree of knowledge of good and evil does this is this story meaningful to you what does the story mean to you yeah it is meaningful to me um i i take the you know the writings of the bible very seriously and i think that most christians regard them as having some kind of authoritative um role in their in their in their faith um what do i get from it i mean i think the most important thing that christians get from the story of adam and eve and eating the apple and so forth is that the relationship between humans and god is broken has been broken by man's disobedience that's what the the story of adam and eve and the apple is all about and um that that broken relationship is for christians what jesus came to redeem came to overcome that brokenness and restore that relationship with god to some extent at any rate on earth and and ultimately um you know in in the in eternity to restore it fully so that's really what christians mean and gain from the story of adam and eve of course lots of people ask the questions about how so how literally should we take these stories of particularly the first few few chapters of genesis which is an important question but but i mean but we tend to um get bogged down with it a bit too much i think we should take away the message um and i think the the the uh what the what actually we would have seen if we'd been there okay is something which is a matter of speculation and it's certainly not terribly important from the point of view of christian theology but it seems like a very important moment as a man of faith do you um do you do you wish that uh i think it was eve first uh yeah we'll see do you wish by the way it was just a fruit it was a few you said it very carefully it was the fruit of the tree right do you wish they wouldn't have eaten of the tree i mean this is back to our discussion of suffering was that like an essential thing that needed to happen you're gonna have to read paradise last to get your answer to that beautifully put okay well let me ask the the biggest question one that you also touch in your book but one that i ask every once in a while is what is the meaning of life the meaning of my life is many different things okay but it but they are all kind of centered around relationships i mean for a christian one's relationship with god is a crucial part of the meaning of life but one's relationship with one's family wife's wife parents children grandchildren in my case and so forth those are crucially important these are all the places where people whether they're religious or not find meaning but ultimately i think a person who has faith in a creator who we think has a an intention or many intentions but uh but but but a will um in respect of the world as a whole that's a crucial part of meaning and the idea that my life might have some small significance in the plan of that creator is an amazingly powerful idea that give that brings meaning um i i tell a story in my book that um when i was a student before i became a christian i read a philosophy book whose approximate title was um what you know what is the meaning of life and you know that book basically said there is no meaning to life you have to make up the meaning as you go along and i think that's probably the the predominant secular view is these days that there is no real meaning but you can make up a meaning and that will give you meaning into your life um i don't subscribe to that view anymore um i think there is more meaning than that um but i do think that those things which give meaning to our life are very important and we should emphasize them and you you have said that as the part of the as the part of that meaning is the part of your faith uh love and loyalty are key parts so can you try to say what is uh love and loyalty like what what does it mean to you what does it look like if you were to give advice to uh to your children grandchildren of what to look for in and looking for loyalty and and love what would you try to say well i think it's something like yielding your will or desire to another um it's valuing others more highly or at least as highly as yourself but that's just the start of it because true love re you reach a point where you are you feel compelled by the other uh and that i think to some people sounds very scary but actually it's terrifically liberating um and i think that love then brings you into service towards another and i'm you know reminded of um the phrase from the anglican uh prayer book where it talks about um jesus whose service is perfect freedom in other words for us christians to serve god is what perfects our freedom and i think there is an amazing love as um is in part capped captivity but in a kind of paradoxical sense it's also an amazing freedom love is freedom i don't think there's a better way to end it we started with fusion energy and ending on love and there's a huge honor to talk to you thank you so much for your time today thanks it was a pleasure thanks for listening to this conversation with ian hutchinson and thank you to our sponsors sunbasket and powerdot please consider supporting this podcast by going to sunbasket.com lex and use codelex at checkout and go to powerdot.com lex and use code lex at checkout click the links buy the stuff even just visiting the site is really the best way to support this podcast because it helps convince them to sponsor it in the future if you enjoy this thing subscribe on youtube review it with five stars on apple podcast support on patreon or connect with me on twitter at lex friedman spelled somehow without the letter e just f-r-i-d-m-a-n and now let me leave you with some words from arthur c clarke finally i would like to assure my many buddhists christian hindu jewish and muslim friends that i am sincerely happy that the religion which chance has given you has contributed to your peace of mind and often as western medical science now reluctantly admits to your physical well-being perhaps it is better to be unsane and happy than sane and unhappy but it is the best of all to be sane and happy whether our descendants can achieve that goal will be the greatest challenge of the future indeed it may well decide whether we have any future thank you for listening and hope to see you next time |
Richard Karp: Algorithms and Computational Complexity | Lex Fridman Podcast #111 | the following is a conversation with richard carp a professor at berkeley and one of the most important figures in the history of theoretical computer science in 1985 he received the touring award for his research in the theory of algorithms including the development of the admirance carp algorithm for solving the max flow problem on networks hopcroft corp algorithm for finding maximum cardinality matchings in bipartite graphs and his landmark paper and complexity theory called reducibility among combinatorial problems in which he proved 21 problems to be np complete this paper was probably the most important catalyst in the explosion of interest in the study of np completeness and the p versus np problem in general quick summary of the ads two sponsors a sleep mattress and cash app please consider supporting this podcast by going to asleep.com lex and downloading cash app and using code lex podcast click the links buy the stuff it really is the best way to support this podcast if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast support it on patreon or connect with me on twitter at lex friedman as usual i'll do a few minutes of as now and never any ads in the middle that can break the flow of the conversation this show is sponsored by eight sleep and it's pod pro mattress that you can check out at asleep.com lex to get 200 off it controls temperature with an app it can cool down to as low as 55 degrees and each side of the bed separately research shows the temperature has a big impact on the quality of our sleep anecdotally it's been a game changer for me i love it it's been a couple weeks now i just been really enjoying it both in the fact that i'm getting better sleep and then it's a smart mattress essentially i kind of imagine this being the early days of artificial intelligence being a part of every aspect of our lives and certainly infusing 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natural bad design is when the app gets in the way either because it's buggy or because it tries too hard to be helpful i'm looking at you clippy from microsoft even though i love you anyway there's a big part of my brain and heart that loves to design things and also to appreciate great design by others so again if you get cash out from the app store google play and use the code lex podcast you get ten dollars and cash app will also donate ten dollars to first an organization that is helping to advance robotics and stem education for young people around the world and now here's my conversation with richard carp you wrote that at the age of 13 you were first exposed to plain geometry and was wonder struck by the power and elegance of formal proofs are there problems proofs properties ideas and plain geometry that from that time that you remember being mesmerized by or just enjoying to go through to prove various aspects so michael rabin told me this story about an experience he had when he was a young student who was ex tossed out of his classroom for bad behavior and was wandering through the corridors of his school and came upon two older students who were studying the problem of finding the shortest distance between two non-overlapping circles and michael thought about it and said you take the straight line between the two centers and the segment between the two circles is the shortest because a straight line is the shortest distance between the two centers and any other line connecting the circles would be on a longer line and i thought and he thought and i agreed that this was just elegant that pure reasoning could come up with such a result certainly the the shortest distance from the two centers of the circles is a straight line could you once again say what's the next step in that proof well any any segment joining the the two circles if you extend it by taking the radius on each side you get a segment with a path with three edges which connects the two centers and this has to be at least as long as the shortest path which is the straight line the straight line yeah wow yeah that is that's quite quite simple so what what is it about that elegance that you just find uh compelling well just that you could establish a a fact about geometry beyond dispute by pure reasoning i i also enjoy the challenge of solving puzzles in plain geometry it was much more fun than the earlier mathematics courses which were mostly about arithmetic operations and manipulating them was was there something about geometry itself the slightly visual component of it yes absolutely although i lacked three-dimensional vision i wasn't very good at three-dimensional vision you mean being able to visualize three-dimensional objects three-dimensional objects or or um surfaces hyperplanes and so on um so so there there i didn't have an intuition but for example the fact that the sum of the angles of a triangle is 180 degrees is proved convincingly um and it comes as a surprise that that can be done why is that surprising the the well it is a surprising uh is a surprising idea i suppose uh why is that proved difficult it's not that's the point it's so easy and yet it's so convincing do you remember what is the proof that it's um as up to 180 uh you you start at a corner and draw a line um parallel to the opposite side and that line sort of trisects the angle between the other two sides and uh you you get a uh a half plane which has to add up to 180 degrees and it consists in the angles by by the equality of uh alternate angles what's it called you you you get a correspondence between the angles created by the side along the side of the triangle and the three angles of the triangle has geometry had an impact on when you look into the future of your work with combinatorial algorithms has it had some kind of impact in terms of yeah being able the puzzles the visual aspects that were first so compelling to you not euclidean geometry particularly i think i use tools like linear programming and integer programming a lot and but those require high dimensional visualization and so i tend to go by the algebraic properties um right the you you go by the algebra the linear algebra and not by the the visualization well the interpretation in terms of for example finding the highest point on a polyhedron as in linear programming is motivating but again it i don't have the high dimensional intuition that would particularly inform me so i sort of deep lean on the algebra so to linger on that point what kind of visualization do you like do you do when you're trying to think about we'll get to combinatorial algorithms but just algorithms in general yeah what kind of what what's inside your mind when you're thinking about designing algorithms or or even just tackling any any mathematical problem well i think that usually an algorithm is uh involves a repetition of some inner loop and and so i can sort of visualize the um the distance from the desired solution as iteratively reducing until you finally hit the exact solution and try to take steps that get you closer to the try to take steps that get closer and having the certainty of converging so it's it's racist it's basically the mechanics of the algorithm is often very simple but especially when you're trying something out on the computer so for example i did some work on the traveling salesman problem and i could see there was a particular function that had to be minimized and it was fascinating to see the successive approaches to the minimum to the optimum you mean so first of all traveling salesman problems where you have to visit uh every city without ever the only ones yeah that's right find the shortest path through cities yeah uh which is sort of a canonical standard a really nice problem that's really hard right exactly so can you say again what was nice about the objective being able to think about the objective function there and maximizing it or minimizing it well just that the um as the algorithm proceeded it was you were making progress continual progress and and eventually getting to the optimum point so there's two two parts maybe maybe you can correct me but first is like getting an intuition about what the solution would look like and or even maybe coming up with a solution and two is proving that this thing is actually going to be pretty good uh what part is harder for you where's the magic happen is it in the first sets of intuitions or is it in the detail the messy details of actually showing that it is going to get to the exact solution and it's going to run at this at a certain complexity well the magic is just the fact that it the the gap from the optimum decreases monotonically and you can see it happening and um various metrics of what's going on are improving all along until finally hit the optimum perhaps later we'll talk about the assignment problem and i can illustrate illustrate a little better yeah now zooming out again as you write don knuth has called attention to a breed of people who derive great aesthetic pleasure from contemplating the structure of computational processes so don calls these folks geeks and you write that you remember the moment you realized you were such a person you were shown the hungarian algorithm to solve the assignment problem right so perhaps you can explain what the assignment problem is and what uh the hungarian algorithm is so in the assignment problem you have uh n boys and in girls and you are given the desirability of uh or the cost of matching the i boy with the jth girl for all i and j you're given a matrix of numbers and you want to find the one-to-one matching of the boys with the girls such that the some of the associated costs will be minimized so the the best way to match the boys with the girls or men with jobs or any two sets um no any possible matching is possible or yeah all one-to-one correspondences are permissible if there is a connection that is not allowed then you can think of it as having an infinite cost so um what you do is uh to depend on the observation that the identity of the optimal assignment or as we call it the optimal permutation um is not changed if you subtract a constant from any row or column of the matrix you can see that the comparison between the different assignments is not changed by that um because you're penal if you decrease a particular row all the elements of a row by some constant all solutions decrease by the cost of that by an amount equal to that constant so the idea of the algorithm is to start with a matrix of non-negative numbers and keep subtracting from rows or from our entire columns um in such a way that you subtract the same constant from all the elements of that row or column uh while maintaining the property that um uh all the elements are non-negative simple yeah and so and so um what you have to do is uh is find small moves which will decrease the total cost while subtracting constants from rows or columns and there's a particular way of doing that by computing a kind of shortest path through the elements in the matrix and you just keep going in this way until you finally get a full permutation of zeros while the matrix is non-negative and then you know that that has to be the cheapest is that as simple as it sounds so the the shortest path of the matrix part yeah the simplicity lies in how you find the what i oversimplified slightly what you you you will end up subtracting a constant from some rows or columns and adding the same constant back to other rows and columns so as not to not to reduce any of the zero elements you leave them unchanged but each individual step modifies us several rows and columns by the same amount but overall decreases the cost so there's something about that elegance that made you go aha this is a beautiful like it's it's uh it's amazing that something like this something so simple can solve a problem like this yeah it's really cool if i had mechanical ability i would probably like to do woodworking or other activities where you sort of shape something in into something beautiful and orderly and there's something about the orderly systematic nature of uh that innovative algorithm that is pleasing to me so what do you think about this idea of geeks as don knuth calls them what do you think of is it something uh specific to a mindset that allows you to discover the elegance and computational processes or is this all of us can all of us discover this beauty are you born this way i think so i always like to play with numbers i i i used to amuse myself by multiplying four digit decimal numbers in my head and putting myself to sleep by starting with one and doubling the number as long as i could go and uh testing my memory my ability to retain the information and i also read somewhere that you uh you wrote that you enjoyed uh showing off to your friends by i believe multiplying four digit numbers uh right a couple of four digit numbers yeah i had a summer job at a beach resort outside of boston and uh the other employee i i was the barker at a skee-ball game yeah i used to i used to sit at a microph microphone saying come one come all come in and play ski ball five cents to play nickel to win and so on that's what a barker i was gonna i wasn't sure if i should know but barker that's so you're the the charming outgoing person is getting people to uh come in yeah well i wasn't particularly charming but i could be very repetitious and loud and the other employees were sort of juvenile delinquents who had no academic bent but somehow i found that i could impress them by by performing this mental melter or mental arithmetic you know there's something too that you know one of some of the most popular videos on the internet is uh there's a there's a youtube channel called number file that shows off different mathematical ideas there's still something really profoundly interesting to people about math the the beauty of it something even if they don't understand the basic concept even being discussed there's something compelling to it what do you think that is any lessons you drew from the early teen years when you were showing off to your friends with the numbers like is what is it that attracts us to the beauty of mathematics do you think the general population not just the the computer scientists and math the magicians i think that it you know you can do amazing things you can test whether large numbers are prime you can uh um you can solve little puzzles about cannibals and missionaries and there's a kind of achievement it's it's it's puzzle solving and at a higher level the fact that you can you can do this reasoning that you can prove in an absolutely ironclad way that the some of the angles of a triangle is 180 degrees yeah it's a nice escape from the messiness of the real world where nothing can be proved so and we'll talk about it but sometimes the ability to map the real world into such problems where you can't prove it is this a is a powerful step yeah it's amazing that we can do this another attribute of geeks is they they're not necessarily uh endowed with emotional intelligence so they can live in a world of abstractions without having to uh master the complexities of uh dealing with people so just to link on the historical note as a phd student in 1955 he joined the computational lab at harvard where howard aiken had built the mark 1 and the mark iv computers just to take a step back into that history what were those computers like uh the mark iv filled me a large room much big much bigger than this large office that we were talking in now and you could walk around inside it they were they were rows of relays you could just walk around the interior and uh the machine would sometimes fail because of bugs which literally meant flying creatures landing on the switches so i never i never used that machine for any practical purpose the lab eventually acquired a uh one of one of the earlier um commercial computers this is already in the 60s no in the mid 50s in mid 50s or mid late 50s there was already usual computers in there yeah we had a univac a 2000 univac with 2000 words of storage and so you had to work hard to allocate the memory properly to also the excess time from one word to another depended on the number of the particular words and so you there was an art to sort of arranging the storage allocation to make fetching data rapid were you attracted to this actual physical world implementation of mathematics so it's a mathematical machine that's actually doing the math physically no not at all i think i was a i was attracted to the underlying algorithms so but did you draw any inspiration so could you have imagined like what did you imagine was the future of these giant computers could you imagine that 60 years later would have billions of these computers all over the world i couldn't imagine that but there was a sense in the laboratory that this was the wave of the future in fact my mother influenced me she she told me that data processing was going to be really big and i should get into it she's a smart woman yeah she was a smart woman and there was just a feeling that this was going to change the world but i i didn't think of it in terms of personal computing i hadn't that i had no anticipation that we would be walking around with computers in our pockets or anything like that did you see computers as tools as mathematical mechanisms to analyze sort of sort of theoretical computer science or as the ai folks which is an entire other community of dreamers yeah that's something that could one day have human level intelligence well ai wasn't very much on my radar i did read uh turing's paper about the uh the uh the uh the drawing test computing and intelligence yeah the turing test um what'd you think about that paper was that just like science fiction um i thought that it wasn't a very good test because it was too subjective so i i didn't feel that i didn't feel that the turing test was really the right way to calibrate how intelligent an algorithm could be to linger on that do you think it's pos because you've come up with some incredible tests later on tests on algorithms right yeah that are like strong reliable robust across a bunch of different classes of algorithms but returning to this emotional mess that is intelligence do you think it's possible to come up with the test that's as iron-clad as some of the computational complexity work well i think the greater question is whether it's possible to achieve human level level intelligence right so that's so first of all let me at the philosophical level do you think it's possible to create algorithms that reason and would seem to us to have the same kind of intelligence as human beings it's an open question um it seems to me that um most of the achievements have acquire operate within a very limited set of ground rules and for a very limited precise task which is a quite different situation from the processes that go on in the minds of humans which where they have to sort of function in changing environments they have emotions they have [Music] um physical attributes for acquire for exploring their environment um they have intuition they have desires um emotions and i don't see anything in the current achievements of what's called ai that come close to that capability i don't think there's any computer program which surpasses a six-month-old child in terms of comprehension of the world do you think this complexity of human intelligence all the cognitive abilities we have all the emotion do you think that could be reduced one day or just fundamentally can it be reduced to an out a set of algorithms or an algorithm so can a touring machine achieve human level intelligence i am doubtful about that i guess the argument in favor of it is that the human brain seems to achieve what we call intelligence cognitive abilities of different kinds and if you buy the premise that the human brain is just an enormous interconnected set of switches so to speak then in principle you should be able to diagnose what that interconnection structure is like characterize the individual switches and build a simulation outside but why that may be true in principle that cannot be the way we're eventually going to tackle this problem it's you know you know that that does not seem like a feasible way to go about it so it there is however an existence proof that um uh if you believe that the brain is is just a network of of neurons operating by rules i guess you could say that that's an existence proof of the ability to build the capabilities of a mechanism um but it would be almost impossible to acquire the information unless we got enough insight into the operation of the brain but there's so much mystery there do you think what do you make of consciousness for example there's something as an example of something we completely have no clue about the fact that we have this subjective experience right is it possible that this network of uh this circuit of switches is able to create something like consciousness to know its own identity yeah to know to know the algorithm to know itself to know itself i think if you try to define that rigorously you'd have a lot of trouble yeah that's interesting so i know that there are many who um believe that general intelligence can be achieved and there are even some who are feel certain that uh the singularity will come and uh we will be surpassed by the machines which will then learn more and more about themselves and reduce humans to an inferior breed i am doubtful that this will ever be achieved just for the fun of it could you linger on why what's your intuition why you're doubtful so there are quite a few people that are extremely worried about this uh existential threat of artificial intelligence of us being left behind by the super intelligent new species what's your intuition why that's not quite likely just because none of the achievements in speech or robotics or natural language processing or creation of flexible computer assistance or any of that comes anywhere near close to that level of cognition what do you think about ideas as a sort of uh if we look at moore's law and exponential improvement uh to allow us to that would surprise us sort of our intuition fall apart with with exponential improvement because i mean we're not able to kind of we kind of think in linear improvement yeah we're not able to imagine a world that goes from the mark one computer to a an iphone 10. yeah so do you think it would be we could be really surprised by the exponential growth or or on the flip side is is it possible that also intelligence is actually way way way way harder even with exponential improvement to be able to crack i don't think any constant factor improvement could could change things and given given our current comprehension of how the of of what cognition requires it seems to me that multiplying the speed of the switches by a factor of a thousand or a million uh will not be useful until we really understand the organizational principle behind the network of switches well let's jump into the network of switches and talk about combinatorial algorithms if we could let's step back with the very basics what are combinatorial algorithms and what are some major examples of problems they aim to solve a combinatorial algorithm is is one which deals with a a system of discrete objects that can occupy various states or take on various values from a discrete set of values um and need to be arranged or or selected um in such a way as to achieve some to minimize some cost function or to prove or to prove the existence of some combinatorial so an example would be um coloring the vertices of a graph what's a graph let's step back so what uh and it's fun to uh to ask one of the greatest computer scientists of all time the most basic questions in the beginning of most books but for people who might not know but in general how you think about it what is what is a graph uh a graph that's that's simple it's a set of points certain pairs of which are joined by lines called edges and they sort of represent the in different applications represent the interconnections between discrete objects so they could be the interactions interconnections between switches in a digital circuit or interconnections indicating the communication patterns of a human community um and they could be directed or undirected and then as you've mentioned before might have costs right they can be directed or undirected they can be you can think of them as if if you think if a graph were representing a communication network then the edge could be undirected meaning that information could flow along it in both directions or it could be directed with only one-way communication a road system is another example of a graph with weights on the edges and then a lot of problems of optimizing the efficiency of such networks or learning about the performance of such networks um uh are the the objective combinatorial algorithm so it could be scheduling classes at a school where the the vertices the nodes of the network are the individual classes and uh the edges indicate the constraints which say that certain classes cannot take place at the same time or certain teachers are available only at cert for certain classes etc or um i talked earlier about the assignment problem of matching the boys with the girls um where um you have a very graph with an edge from each boy to each girl with a weight indicating the cost or in logical design of computers you might want to find a set of so-called gates switches that perform logical functions which can be interconnected to realize some function so you you might ask um how many gates do you need in order to um for for a circuit to give a yes output if at least a given number of its inputs are ones and no if not a few are are present my favorite is probably all the all the work with network flows so anytime you have uh i don't know why it's so compelling but there's something just beautiful about it it seems like there's so many applications and communication networks in uh traffic right flow that you can map into these and then you can think of pipes and water going through pipes and you could optimize it in different ways there's something always visually and intellectually compelling to me about it and of course you've done work there yeah yeah so so there the edges represent channels along which some commodity can flow it might be gas it might be water it might be information maybe supply chain as well like products being products flowing from one operation to another and the edges have a capacity which is the rate at which the commodity can flow and a central problem is to determine given a network of these channels in this case the edges are communication channels the the challenge is to find the maximum rate at which the information can flow along these channels to get from a source to a destination and that's a that's a fundamental combinatorial problem that i i've worked on jointly with the scientist jack edmunds we i think we're the first to give a formal proof that this maximum flow problem through a network can be solved in polynomial time which uh i remember the first time i learned that just learning that in um maybe even grad school i don't think it was even undergrad no algorithm yeah do netfl network flows get taught in in um basic algorithms courses yes probably okay so yeah i've i remember being very surprised that max flow is a polynomial time algorithm yeah that there's a nice fast algorithm that solves max flow but so there is an algorithm named after you an admins they haven't carp algorithm for max flow so what was it like tackling that problem and trying to arrive at a polynomial time solution and maybe you can describe the algorithm maybe you can describe what's the running time complexity that you showed yeah well first of all what is a polynomial time algorithm yeah perhaps we could discuss that so yeah let's let's actually just even yeah that's what is algorithmic algorithmic complexity what are the major classes of algorithm complexity so we in in a problem like the assignment problem or scheduling schools or any of these applications um you have a set of input data which might for example be um a set of vertices connected by edges with being you're given for each edge the capacity of the edge and you have algorithms which are think of them as computer programs with operations such as addition subtraction multiplication division comparison of numbers and so on and you're trying to construct an algorithm based on those operations which will determine in a minimum number of computational steps the answer to the problem in this case the computational step is one of those operations and the answer to the problem is let's say the um the configuration of the network that carries the maximum amount of flow and an algorithm is said to run in polynomial time if as a function of the size of the input the number of vertices the number of edges and so on the number of basic computational steps grows only as some fixed power of that size a linear algorithm would execute a number of steps linearly proportional to the size quadratic algorithm would be steps proportional to the square of the size and so on and algorithms that whose running time is bounded by some fixed power of the size are called polynomial algorithms and that's supposed to be relatively fast class of algorithms that's right we theoreticians take that to be the definition of an algorithm being um efficient and and we're interested in which problems can be solved by such efficient algorithms one can argue whether that's the right definition of efficient because you could have an algorithm whose running time is the ten thousandth power of the size of the input and that wouldn't be really efficient and in practice it's oftentimes reducing from an n squared algorithm to an n log n or a linear time is practically the jump that you want to make to allow a real world system to solve a problem yeah that's also true because especially as we get very large networks the size can be in the millions and uh and then anything above uh n log n where n is the size would be uh too much for a practical solution okay so that's polynomial time algorithms what other classes of algorithms are there what's so that usually they they designate polynomials of the letter p yeah there's also np np complete and be hard yeah so can you try to disentangle those and by trying to define them simply right so a polynomial time algorithm is one which was running time is bounded by a polynomial and the size of the input uh there's then there's that the class of such algorithms is called p in the worst case by the way we should say right yeah for every case of the problem and that's very important that in this theory when we measure the complexity of an algorithm we really measure the number of step the growth of the number of steps in the worst case so you may have an algorithm that [Music] runs very rapidly in most cases but if there is any case where it gets into a very long computation that would increase the computational complexity by this measure and that's a very important issue because there as we may have discussed later there are some very important algorithms which don't have a good standing from the point of view of their worst case performance and yet are very effective so so theoreticians are interested in p the class of problem solvable in polynomial time then there's np which is the class of problems which may be hard to solve but where the where when confronted with the solution you can check it in polynomial time let me give you an example there so if we look at the assignment problem uh so you have uh n boys you have n girls you the number of numbers that you need to write down to specify the problem instances n squared and the question is how many steps are needed to solve it and jack edmonds and i were the first to show that it could be done in time n cubed uh earlier algorithms required n to the fourth so as a polynomial function of the size of the input this is a fast algorithm now to illustrate the class np the question is how long would it take to verify that a solution is optimal so for example if if the input was a graph we might want to find the largest clique in the graph or a clique is a set of vertices such that any vertex each vertex in the set is adjacent to each of the others so the clique is a complete subgraph yeah so if it's a facebook social network everybody's friends with everybody else it's close click no that would be what's called a complete graph it would be no i mean uh within that click uh within that clique yeah yeah they're all friends so a complete graph is when everybody is friendly as everybody is friends with everybody yeah so the problem might be to determine whether in a given graph there exists a clique of a certain size well that turns out to be a very hard problem but how but if somebody hands you a clique and asks you to check whether it is a hands you a set of vertices and ask you to check whether it's a clique you could do that simply by exhaustively looking at all of the edges between the vertices and the clique and verifying that they're all there and that's a polynomial time that's a polynomial so the verify there the problem of finding the clique appears to be extremely hard but the problem of verifying a clique to see if it reaches the target number of vertices is easy to solve is easy to verify so finding the clique is hard checking it is easy problems of that nature are called the non-deterministic polynomial time algorithms and that's the class np and what about mp complete and be hard okay let's talk about problems where you're getting a yes no a yes or no answer rather than a numerical value so either there is a a perfect matching of the of the boys with the girls or there isn't it's clear that um every problem in p is also in np if you can solve the problem exactly then you can certainly verify the solution on the other hand there are problems in the class np this is the class of problems that are easy to check although they may be hard to solve it's not at all clear that problems in np lie in p so for example if we're looking at scheduling classes at a school the fact that you can verify when handed a schedule for the school whether it meets all the requirements that doesn't mean that you can find the schedule rapidly so intuitively np non-deterministic polynomial checking rather than finding is going to be harder than is going to include is easier checking is easier and therefore the class of problems that can be checked appears to be much larger than the class of problems that can be solved and then you keep adding appears to and uh sort of these uh additional words that designate that we don't know for sure yet we don't know for sure so the theoretical question which is considered to be the most central problem in theoretical computer science or at least computational complexity theory combinatorial algorithm theory the question is whether p is equal to np if p were equal to np it would be amazing it would mean that every problem where a solution can be rapidly checked can actually be solved in polynomial time we don't really believe that's true if you're scheduling classes at a school it's we expect that if somebody hands you a satisfying schedule you can verify that it works that doesn't mean that you should be able to find such a schedule so intuitively np encompasses a lot more problems than p so can we take a small tangent and break apart that intuition so do you first of all think that the biggest sort of open problem in computer science maybe mathematics is whether p equals np do you think p equals np or do you think p is not equal to np if you had to bet all your money on it i would bet that p is unequal to np uh simply because there are problems that have been around for centuries and have been studied intensively in mathematics and even more so in the last 50 years since the p versus np was stated and no polynomial time algorithms have been found for these easy to check problems so one one example is a problem that goes back to the mathematician gauss who is interested in um factoring large numbers so uh we know what a number is prime if it doesn't if it cannot be written as the product of two or more numbers unequal to one uh so if we can factor the a number like 91 that's 7 times 13 but if i give you 20 digit or 30 digit numbers you're probably going to be at a loss to have any idea whether they can be factored so the pr the problem of factoring very large numbers is does not appear to have an efficient solution but once you have found the factors express the number as a product the two smaller numbers you can quickly verify that they are factors of the number and your intuition is a lot of people finding you know this a lot of brilliant people have tried to find algorithms for this one particular problem there's many others like it that are really well studied and it would be great to find an efficient algorithm for right and in fact we have some results that i was instrumental in obtaining following up on work by the mathematician stephen cook to show that within the class np of easy to check problems there's a huge number that are equivalent in the sense that either all of them or none of them lie in p and this happens only if p is equal to np so if p is unequal to np we would also know that virtually all the standard combinatorial problems if p is unequal to np none of them can be solved in polynomial time can you explain how that's possible to tie together so many problems in a nice bunch that if one is proven to be efficient then all are the first and most important stage of progress was a result by stephen cook who showed that a certain problem called the satisfiability problem of propositional logic is as hard as any problem in the class p so the propositional logic problem is expressed in terms of expressions involving the logical operations and or and not offering operating operating on variables that can be either true or false so an instance of the problem would be some formula involving and or and not and the question would be whether there is an assignment of truth values to the variables in the problem that would make the formula true so for example if i take the formula a or b and a or not b and not a or b and not a or not b and take the conjunction of all four of those so-called expressions you can determine that no assignment of truth values to the variables a and b will allow that conjunction of cl what are called clauses uh to be true so that's an example of a formula in propositional logic involving expressions based on the operations and or and not um that's an example of a problem which has which is not satisfiable there is no solution that satisfies all of those constraints and that's like one of the cleanest and fundamental problems in computer science it's like a nice statement of a really hard problem it's a nice statement a really hard problem and and what cook showed is that every problem in np is can be re-expressed as an instance of the satisfiability problem so to do that he used the observation that a very simple abstract machine called the turing machine can be used to describe any algorithm an algorithm for any realistic computer can be translated into an equivalent algorithm on one of these turing machines which are extremely simple it's a tour machine there's a tape and you can yeah you have to walk along that data on a tape and you have basic instructions a finite list of instructions which say we would say if you're reading a particular symbol on the tape and you're in a particular state then you can move to a different state and change the state of the number that you or the element that you were looking at the cell of the tape that you were looking at and that was like a metaphor and a mathematical construct that touring put together to represent all possible computation all possible computation now one of these so-called turing machines is too simple to be useful in practice but for theoretical purposes we can depend on the fact that an algorithm for any computer can be translated into one that would run on a turing machine right and then using that fact um he could sort of describe any possible nondeterministic polynomial time algorithm any pro any algorithm for a problem in np could be expressed as a sequence of moves of the turing machine described in terms of reading a symbol on the tape while you're in a given state and moving to a new state and leaving behind a new new symbol and given that the fact that any non-deterministic polynomial time algorithm can be described by a list of such instructions you could translate the problem into the language of the satisfiability problem is that amazing to you by the way if you take yourself back when you were first thinking about the space of problems is that how amazing is that it's astonishing when you look at cook's proof it's not too difficult to sort of figure out why this is why this is so but the implications are staggering it tells us that this of all the problems in np all the problems where solutions are easy to check they can they can all be rewritten in terms of the satisfiability problem yeah it's a in adding so much more weight to the p equals np question because all it takes is to show that one that's right one algorithm in this class so the p versus np can be re-expressed is simply asking whether the satisfiability problem of propositional logic you'll solve a billion polynomial time but there's more uh i i encountered cook's paper when he published it in a conference in 1971. yeah so when i saw uh cook's paper and saw this uh reduction event of all of each of the problems in np by a uniform method to to the satisfiability problem of propositional logic that meant that the satisfiability problem was a universal combinatorial problem and it occurred to me through experience i had had in trying to solve other combinatorial problems that there were many other problems which seemed to have that universal structure and so i began looking for reductions from the satisfiability to other problems one of the other problems would be the so-called integer programming problem of solving a determining whether there's a solution to a um a set of linear inequalities involving integer variables just like linear programming but there's a constraint that the variables must remain integers integers in fact must be either zero or one because they could only take on those values and that makes the problem much harder yes that makes the problem much harder and it was not difficult to show that the satisfiability problem can be restated as an integer programming problem so can you pause on that was that one of the first problem mappings that you try to do and how hard is that map you said it wasn't hard to show but you know that's a that's a big leap it is a big leap yeah well let me let me give you another example um another problem in np is whether a graph contains a clique of a given size and now the question is can we reduce the propositional logic problem to the problem of whether there's a clique of a certain size well if you look at the propositional logic problem it can be expressed as a number of clauses each of which is a of the form a or b or c where a is either one of the variables in the problem or the negation of one of the variables and the an instance of the propositional logic problem can be rewritten using operations of boolean logic can be re rewritten as the conjunction of a set of clauses the and of a set of ors where each clause is a disjunction an or of variables or negated variables so the pro the question of uh the in the satisfiability problem is whether those clauses can be simultaneously satisfied now to satisfy all those clauses you have to find one of the terms in each clause which is going to be given that which is going to be true in your truth assignment but you can't make the same variable both true and false so if you have the variable a in one clause and you want to satisfy that clause by making a true you can't also make the complement of a true in some other clause and so the goal is to make every single clause true if it's possible to satisfy this and the way you make it true is at least one term in the clause must be it must be true so so now we uh to convert this problem to something called the independent set problem where you're just sort of asking for a set of vertices in a graph such that no two of them are adjacent sort of the opposite of the clique problem so we've seen that we can now express that as finding a set of terms one in each clause without picking both the variable and the negation of that variable because you if the variable is assigned the truth value the negated variable has to have the opposite truth value right and so we can construct the graph where the vertices are the terms in all of the clauses and you have an edge between two terms if um if an edge between two occurrences of terms if they're both in the same clause because you're only picking one element from each clause and also an edge between them if they represent opposite values of the same variable because you can't make a variable both true and false and so you get a graph where you have all of these occurrences of variables you have edges which which mean that you're not allowed to choose both ends of the edge either because they're in the same clause or they're con negations of one another all right and that's uh first of all sort of to zoom out that's a really powerful idea that you can take a graph and connect it to a logic equation right somehow and do that mapping for all possible formulations of a particular problem on a graph yeah i mean that that still is hard for me to believe that that's possible that that they're like what do you make of that that um there's such a union of there's such a friendship among all these problems across that somehow are akin to combinatorial uh algorithms that they're all somehow related yeah i i know it can be proven yeah but what do you make of it that that that's true well if they just have the same expressive power you can take any one of them and translate it into the terms of the other you know the fact that they have the same expressive power also somehow means that they can be translatable right and what i did in the 1971 paper was to take 21 fundamental problems commonly occurring problems of packing covering matching and so forth or lying in the class np and show that the satisfiability problem can be re-expressed as any of those that any of those have the same expressive proper uh expressive power so and that was like throwing down the gauntlet of saying there's probably many more problems like this right but that's just saying that look that they're all the same they're all the same but not exactly yeah yeah they're all the same in terms of whether they are um rich enough to express any of the others but that doesn't mean that they have the same computational complexity but what we can say is that either all of these problems or none of them are solvable in polynomial time yeah so where does np completeness and np hard classes well that's just a small technicality so when we're talking about decision problems that means that the answer is just yes or no there is a clique of size 15 or there's not a clique of size 15. on the other hand an optimization problem would be asking find the largest clique the answer would not be yes or no it would be 15. so um so when you're asking for the when you're putting a valuation on the different solutions and you're asking for the one with the highest valuation that's an optimization problem and there's a very close affinity between the two kinds of problems but the counterpart of being the hardest decision problem the hardest yes no problem the kind of part of that uh is is to minimize or maximize an objective function and so a problem that's hardest in the class when viewed in terms of optimization those are called np-hard rather than np-complete and np-complete is for decision problems and np-complete is for decision problems so if somebody shows that p equals np what do you think that proof will look like if you were to put on yourself if it's possible to show that as a proof or to demonstrate an algorithm all i can say is that it will involve concepts that we do not now have and approaches that we don't have do you think those concepts are out there in terms of inside complexity theory inside of computational analysis of algorithms do you think there's concepts that are totally outside of the box that we haven't considered yet i think that if there is a proof that p is equal to np or that p is not equal to np uh it'll depend on concepts that are now outside the box now if that's shown either way p equals np or p not well actually p equals np what impact you kind of mentioned a little bit but can you can you linger on it what kind of impact would it have on theoretical computer science and perhaps software these systems in general well i think it would have enormous impact on the on the world any in either way case if p is unequal to np which is what we expect then we know that we're in that for the great majority of the combinatorial problems that come up since they're known to be np complete uh we're not going to be able to solve them by efficient algorithms however there's a little bit of hope in that it may be that we can solve most instances all we know is that if a problem is not in p then then it can't be solved efficiently on all instances um but but basically it will um it will if we find that p is unequal to np it will mean that we can't expect always to get the optimal solutions to these problems and we have to depend on heuristics that perhaps work most of the time or give us good approximate solutions but not so we would turn our eye towards the heuristics with a little bit more um acceptance and comfort on our hearts exactly okay so let me ask a romanticized question what to you is one of the most or the most beautiful combinatorial algorithm in your own life or just in general in the field that you've ever come across or have developed yourself oh i like the stable matching problem or the stable marriage problem uh very much what's the stable matching problem yeah imagine that you want to marry off n boys with uh and girls and each boy has an ordered list of his preferences among the girls his first choice is second choice through her nth choice and um each girl also has a an ordering of the boys first choice second choice and so on and we'll say and we will say that a matching one-to-one matching of the boys with the girls is stable if there are no two couples in the matching such that the boy in the first couple prefers the girl in the second couple to her mate and she refers the boy to her current mate in other words if there is the matching is stable if there is no pair who want to run away with each other leaving their partners behind gosh yeah uh yeah actually this is relevant to matching uh uh residents with hospitals and some other real life problems although not quite in the form that i described so it turns out that there is that a stable for any set of preferences a stable matching exists and um moreover it can be computed by a simple algorithm in which each boy starts making proposals to girls and if the girl receives the proposal she accepts it tentatively but she can drop it if she can end it she can drop it later if she gets a better proposal from her point of view and the boys start going down their lists proposing to their first second third choices until stopping when a proposal is accepted but the girls meanwhile are watching the proposals that are coming into them and the girl will drop her current partner um if she gets a better proposal and the boys never go back through they they never go back yeah so once they've been denied they don't try again they don't they don't they don't try again because the girls are always improving their status as they get more as they receive better and better proposals the boys are going down their list starting with their top preferences and um one can prove that that the process will come to an end where everybody will get matched with somebody and you'll you won't have any pair that want to abscond from each other do you find the proof or the algorithm itself beautiful or is it the fact that with the the simplicity of just the two marching i mean the simplicity of the underlying rule of the algorithm is that the beautiful part both i i would say um and you also have the observation that you might ask who is better off the boys who are doing the proposing or the girls who are reacting to proposals and it turns out that it's it's the boys who are doing the doing the best that is each boy is doing at least as well as uh he could do in any other stable matching so there's a sort of lesson for the boys that you should go out and be proactive and make those proposals go for broke yeah i don't know if the this is directly mappable philosophically to our society but uh certainly seems like a compelling notion and like you said there's probably a lot of actual real world problems that this could be mapped to yeah well you get you you get complications for example what happens when a husband and wife want to be assigned to the same hospital so you you have to take those constraints into account and then the problem becomes np hard or uh why is it a problem for the husband and wife to be assigned to the same hospital no it's desirable so desirable or at least go to the same city so you can't if you're i think if you're assigning residents to hospitals and then you have some preferences uh for the husband and wife for for the hospitals the residents have their own preferences references residents both male and female have their own preferences um the hospitals have their preferences but if if resident a the boy is going to philadelphia then you'd like his wife be also to be assigned to a hospital in philadelphia so which step makes it a and be hard problem do you mention the fact that you have this additional constraint that it's not just the preferences of individuals but the fact that the two partners to a marriage have to go to have to be assigned to the same place i'm being a little dense uh the sort of the perfect matching no not the stable matching is what you refer to that's when two partners are trying to okay what's confusing you is that in the first interpretation of the problem i had boys matching with girls yes in the second interpretation you have humans matching with institutions i and there's a coupling between within the gotcha within the humans any added little constraint will make it an empty heart problem well yeah okay by the way the algorithm you mentioned wasn't was one of yours no no that was due to gail and shapley and uh my friend david gale passed away before he could get part of the nobel prize but his partner shapley shared in a nobel prize with somebody else for economics for huma for economics uh for ideas stemming from this stable matching idea so you've also have developed yourself some elegant beautiful algorithms again picking your children so the the the robin carp algorithm for string searching pattern matching admin carb algorithm for max flows we mentioned hop craft carbon algorithm for finding maximum cardinality matchings and bipartite graphs is there ones that stand out to you as ones you're most proud of or just um whether it's beauty elegance or just being the right discovery development in your life that you're especially proud of i like the raven carp algorithm because it illustrates the power of randomization so the the problem there is to um is to decide whether uh a given long string of symbols from some alphabet contains a given word whether a particular word occurs within some very much longer word and so the the idea of the algorithm is to associate with the word that we're looking for a fingerprint some some number or some combinatorial object that describes that word and then to look for an occurrence of that same fingerprint as you slide along the longer word and what we do is we associate with each word a number so we first of all we think of the letters that are kind of occur in a word as the digits of let's say decimal or whatever base your whatever number of different symbols there are that's the base of the of the numbers yeah right so every word can then be thought of as a number with the letters being the digits of that number and then we pick a random prime number in a certain range and we take that word viewed as a number and take the remainder on dividing the dividing that number by the prime so coming up with a nice hash function it's a it's a kind of hash function yeah um it gives you a little little shortcut for for that particular word yeah that so that's the that's the uh it's very different than the any and other algorithms of its kind that we're trying to do search uh string matching yeah which usually are combinatorial and don't involve the idea of taking a random fingerprint yes and doing the fingerprinting has two advantages one is that as we slide along the long word digit by digit we can we we keep a window of of a certain size the size of the word we're looking for and we compute the fingerprint of every stretch of that length and it turns out that just a couple of arithmetic operations will take you from the fingerprint of one part to what you get when you slide over by one position so the computation of all the fingerprints is um simple and secondly it's unlikely if the prime is chosen randomly from a certain range that you will get two of the segments in question having the same fingerprint right and so there's a small probability of error which can be checked after the fact and also the ease of doing the computation because you're working with these fingerprints which are remainders modulo some big prime so that's the magical thing about randomized algorithms is that if you add a little bit of randomness it somehow allows you to take a pretty naive approach a simple looking approach and allow it to run extremely well so can you maybe take a step back and say like what is a randomized algorithm this category of algorithms well it's um just the ability to draw a random number from such um from some range or to to associate a random number with some object or to draw fro at random from some set so another example is very simple if we're conducting a presidential election and we would like to pick the winner in principle we could draw a random sample of all of the voters in the country and if it was a side of substantial size say a few thousand then the most popular candidate in that group would be very likely to be the correct choice that would come out of counting all the millions of votes of course we can't do this because first of all everybody has to feel that his or her vote counted and secondly we can't really do a purely random sample from that population and i guess thirdly there could be a tie in which case we wouldn't have a significant difference between two candidates but those things aside if you didn't have all that messiness of human beings you could prove that that kind of random picking would be just that random picking would would be would solve the problem with a very with a very low probability of error another example is testing whether a number is prime so if i want to test whether [Music] 17 is prime i could pick any number between 1 and 17 and raise it to the 16th power modulo 17 and you should get back the original number that's a famous formula due to ferma about it's called fairmont's little theorem that if you take any a any number a in the range 0 through n minus 1. and raise it to the n minus one paper uh power modulo n you'll get back the number a if the number is if a is prime yeah so if you don't get back the number a that's a proof that a number is not prime well and you can show that um suitably define the the the probability that you will get a value unequal you will get a violation of fermat's result is very high and so this gives you a way of rapidly proving that a number is not prime it's a little more complicated than that because uh there are certain values of n where something a little more elaborate has to be done but that's the basic idea using taking an identity that holds for primes and therefore if it ever fails on any instance for a non-prime unit you know that the number is not prime it's a quick joy a fast choice fast proof that a number is not prime can you maybe elaborate a little bit more what's your intuition why randomness works so well and results in such simple algorithms well uh the example of conducting an election where you could take in in theory you could take a sample and depend on the validity of the sample to really represent the whole is a just the basic fact of statistics which gives a lot of opportunities um and i actually exploited that sort of random random sampling idea in uh designing an algorithm for counting the number of solutions that satisfy a particular formula and propositional calc propositional particular so some some some uh version of the satisfiability problem or a version of the satisfiability problem is there some interesting insight that you want to elaborate on like what some aspect of that algorithm that might be useful to describe so you you have a a collection of formulas and you want to count the number of solutions that satisfy at least one of the formulas and you can count the number of solutions that satisfy any particular one of the formulas but you have to account for the fact that that solution might be counted many times if it solves more than one of the formulas and so what what you do is you sample from the formulas according to the number of solutions that satisfy each individual one in that way you draw a random solution but then you correct by looking at the number of formulas that satisfy that random solution and uh and don't double count so if if you you can think of it this way so you have a matrix of zeros and ones and you want to know how many columns of that matrix contain at least one one and you can count in each row how many ones there are so what you can do is draw from the rows according to the number of ones if a row has more ones it gets to run more frequently but then if you draw from that row you have to go up the column and looking at where that same one is repeated in different rows and only count it as a success or a hit if it's the earliest row that contains the one right and that gives you a robust statistical estimate of the total number of columns that contain at least one of the ones so that that is an example of the same principle that was used in studying random sampling another viewpoint is that if you have a phenomenon that occurs almost all the time then if you sample one of the occasions where it occurs you're most likely to and you're looking for an occurrence a random occurrence is likely to work so that comes up in solving identities solving algebraic identities you you get um two formulas that may look very different you want to know if they're really identical what you can what you can do is just pick a random value and evaluate the formulas at those two at that value and see if they seeing if they agree and you depend on the fact that if the formulas are distinct then they're going to disagree a lot and so therefore a random choice will exhibit the disagreement if there are many ways for the two to disagree and you only need to find one disagreement then random choice is likely to yield it and in general so we've just talked about randomized algorithms but we can look at the probabilistic analysis of algorithms and that gives us an opportunity to step back and as we said everything we've been talking about is worst case analysis right could you maybe comment on the usefulness and the power of worst case analysis versus best case analysis average case probabilistic how do we think about the future of theoretical computer science computer science in the kind of analysis we do of algorithms does worst case analysis still have a place an important place or do we want to try to move forward towards kind of average case analysis yeah and what what are the challenges there so if worst case analysis shows that an algorithm is always good that's fine if worst case analysis uh is used to show that the problem that the solution is not always good then you have to step back and do something else to ask how often will you get a good solution just to pause on that for a second that that's so beautifully put because i think we tend to judge algorithms we throw them in the trash the moment their their worst case is shown to be bad right and and and that's unfortunate i think we use a good example is um going back to the satisfiability problem there are very powerful programs called set solvers which in practice fairly reliably solve instances with many millions of variables that arise in a digital design or improving programs correct and other applications and so in in many application areas even though satisfiability as we've already discussed is npe complete the sat solvers will work so well that the people in that discipline tend to think of satisfiability as an easy problem so in other words just for some reason that we don't entirely understand the instances that people formulate in designing digital circuits or other applications are such that satisfiability is not hard to check and even searching for a satisfying solution can be done efficiently in practice and there are many examples for example we talked about the traveling salesman problem so just to refresh our memories uh the problem is you've got a set of cities you have pairwise distances between cities um and you want to find a tour through all the cities that minimizes the total the total cost of all the edges traversed all all the trips between cities the problem is np hard but people using integer programming codes together with some other mathematical tricks solve geometric instances of the problem where the cities are let's say points in the plane uh and get optimal solutions to problems with tens of thousands of cities actually it'll take a few computer months to solve a problem of that size but for problems of size a thousand or two it'll rapidly get optimal solutions provably optimal solutions even though again we know that it's unlikely that the traveling salesman problem can be solved in polynomial time are there methodologies like rigorous systematic methodologies for you said in practice in practice this algorithm is pretty good are there systematic ways of saying in practice this sounds pretty good so in other words average case analysis or you've also mentioned that average case kind of requires you to understand what the typical cases typical instances and that might be really difficult that's very difficult so after i did my original work on getting uh showing all these problems to be np complete i looked around for a way to get some shed some positive light on combinatorial algorithms and what i tried to do was to study problems behavior on the average or with high probability but i had to make some assumptions about what what's the probability space what's the sample space what do they what do we mean by typical problems that's very hard to say so i took the easy way out and made some very simplistic assumptions so i assumed for example that if we were generating a graph with a certain number of vertices and edges then we would generate the graph by simply choosing one edge at a time at ran at random until we got the right number of edges that's that's a particular model of random graphs that has been studied mathematically a lot and within that model i i could prove all kinds of wonderful things i and others who also worked on this so we could show that we know exactly how many edges there have to be in order for um there be a so-called hamiltonian circuit that's a cycle that visits each vertex exactly once we know that if the number of edges is a little bit more than n log n where n is the number of vertices then where such a cycle is very likely to exist and we can give a heuristic that will find it with her high probability and we got a the community in which i was working got a lot of results along these lines but the field tended to be rather lukewarm about accepting these results as meaningful because we were making such a simplistic assumption about the kinds of graphs that we would be dealing with so we could show all kinds of wonderful things it was a great playground i enjoyed doing it but after a while i concluded that um that it didn't have a lot of bite in terms of the practical application oh the okay so there's too much into the world of toy problems yeah that can okay but all right so but is is there a way to find nice representative real world impactful instances of a problem on which demonstrate that an algorithm is good so this is kind of like the machine learning world that's kind of what they at his best tries to do is find a data set from like the real world and show the performance all the all the conferences are all focused on beating the performance of on that real world data set is there an equivalent in complexity analysis not really um don knuth started to collect examples of graphs coming from various places so he would have a whole zoo of different graphs that he could choose from and he could study the performance of algorithms on different types of graphs and um but there it's really important and compelling to be able to define a class of graphs so that the the actual act of defining a class of graphs that you're interested in it seems to be a non-trivial step if we're talking about instances that we should care about in the real world yeah it's there's nothing available there that would be analogous to the training set for supervised learning you know where you sort of assume that the world has given you a bunch of examples to work with we don't really have that for problems for combinatorial problems on graphs and networks you know there's been a huge growth a big growth of data sets available do you think some aspect of theoretical computer science i might be contradicting my own question while saying it but will there be some aspect an empirical aspect of theoretical computer science which will allow the fact that these datasets are huge we'll start using them for analysis sort of you know if you want to say something about a graph algorithm you might take a net a social network like facebook and looking at subgraphs of that and prove something about the facebook graph and be respected and at the same time be respected in the theoretical computer science community that hasn't been achieved yet i'm afraid is that is that uh is it p equals np is that impossible is is it impossible to publish a successful paper in the theoretical computer science community that shows some some performance on a real-world data set or is that really just those are two different worlds well they haven't really come together i would say that there is a field of experimental algorithmics where people sometimes are given some family of examples sometimes they just generate them at random and they report on performance but there's no convincing evidence that the sample is representative of anything at all so let me ask in terms of breakthroughs and open problems what are the most compelling open problems to you and what possible breakthroughs do you see in the near term in terms of theoretical computer science well there are all kinds of relationships among complexity classes that can be studied just to mention one thing i wrote a paper with richard lipton in 1979 where we asked the following question um if you take a problem a combinatorial problem in np let's say and you um choose a and you pick the the size of the problem uh say it's a traveling salesman problem but of size 52 and you ask could you get an efficient a small boolean circuit tailored for that size 52 where you could feed the edges of the graph in in as boolean inputs and get as an output the question of whether or not there's a tour of a certain length and that would in other words briefly what you would say in that case is that the problem has small circuits polynomial size circuits now we know that if p is equal to np then in fact these problems will have small circuits but what about the converse could a problem have small circuits meaning that it's that an algorithm tailored to any particular size could work well and yet not be a polynomial time algorithm that is you couldn't write it as a single uniform algorithm good for all sizes just to clarify small circuits for problem of particular size or even further constraint small circuit for a particular for no for all the inputs of that cell almost that size is that a trivial problem for a particular instance of so coming up an automated way of coming up with a circuit i guess that's that would be that would be hard yeah but you know but there's the existential question everybody talks nowadays about every existential questions existential challenges yeah you could ask the question [Music] does the hamiltonian circuit problem have a small circuit for for every size for each size a different small circuit in other words could you tailor solutions depending on the size and and get polynomial size even if p is not equal to np right and that would be fascinating if that's true yeah what we proved is that if that were possible then something strange would happen in complexity theory some level uh class which i could briefly describe um something strange would happen so um i'll take a stab at describing what i mean let's go there so we have to define this hierarchy in which the first level of the hierarchy is p and the second level is np and what is np np involves statements of the form there exists a something such that something holds um so for example um um there exists the coloring such that a graph can be colored with only that number of colors or there exists a hamiltonian circuit there's a statement about this graph yeah so so the um np um nnp deals with statements of that kind that there exists a solution now you could imagine a more complicated expression which which says um uh for all x there exists a y such that some uh proposition holds involving both x and y so that would say for example in game theory for all strategies for the first player there exists a strategy for the second player such that the first player wins that would be that would be at the second level of the hierarchy the third level would be there exists an a such that for all b there exists a c that something holds and you can imagine going higher and higher in the hierarchy and you'd expect that the class the complexity class the classes that correspond to those different cases would get bigger and bigger or they they harder and harder to solve and what lifted and i showed was that if um np had small circuits then this hierarchy would collapse down to the second level in other words you wouldn't get any more mileage by complicating your expressions with three quantifiers or four quantifiers or any number i'm not sure what to make of that exactly well i think it would be evidence that and np doesn't have small circuits because something because something so bizarre would happen but again it's only evidence not proof well yeah it's not that's not even evidence because you're saying p is not equal to np because something bizarre has to happen i mean there that's uh that's proved by the lack of bizarreness in in our science but it seems like um it seems like just the very notion of p equals np would be bizarre so any way you arrive at there's no way you have to fight the dragon at some point yeah okay well anyway for whatever it's worth that's what we proved awesome so so that's a potential space of open interesting problems yeah let me ask you about the this other world that of machine learning of deep learning uh what's your thoughts on the history and the current progress of machine learning field that's often progressed sort of separately as a space of ideas and space of people than the theoretical computer science or just even computer science world yeah it's really um very different from the theoretical computer science world because yeah the results about it algorithmic performance tend to be empirical it's more akin to the world of sat solvers where we observe that for formulas and arising in practice see the solver does well so it it's of that type it's where we're moving into the empirical evaluation of algorithms now it's clear that there have been huge successes in um image processing robotics natural language processing a little less so but across the spectrum of of game playing is another one there have been great successes um and one of those effects is that it's not too hard to become a millionaire if you can get a reputation in machine learning and there'll be all kinds of companies that will be willing to offer you the moon because they they think that if they have ai at their disposal then they can solve all kinds of problems but there are limitations one is that the solutions that you get by from to supervised learning problems uh through uh convolutional neural networks uh seem to perform amazingly well even for inputs that are outside the training set um but we don't have any theoretical understanding of why that's true secondly the solutions the the networks that you get uh are very hard to understand and so very little insight comes out so yeah yeah they may seem to work on your training set and you may be able to discover whether your photos occur in a different sample of inputs or not um but we don't really know what's going on we don't know the the features that distinguish the photographs or the objects are are um not easy to characterize well it's interesting because you mentioned coming up with a small circuit yeah to solve a particular size problem yeah it seems that neural networks are kind of small circuits in a way yeah uh but they're not programs sort of like the the things you've designed are algorithms programs right algorithms neural networks aren't able to develop algorithms to solve a problem is it well they are more of a function they are algorithms it's just that they're uh but sort of uh well yeah it's a it could be a semantic question but there's not a algorithmic style manipulation of the input perhaps you could argue there is yeah well it feels a lot more like a function of the input it's a yeah it's a function it's a computable function it's um once you have the network you can simulate it on a given input and figure out the output but what you you know if you're if you're trying to recognize images then you don't know what features of the image are really being uh uh determinant of of what the circuit is doing the circuit is sort of a very intricate and you know it's not clear that the the you know the the simple characteristics that you're looking for the the edges of the objects or whatever they may be they're not emerging from the structure of the circuit well it's not clear to us humans but it's clear to the circuit yeah well right i mean uh it's not clear to sort of the um the elephant how the human brain works but it's clear to us humans we can explain to each other our reasoning and that's why the cognitive science the psychology field exists maybe maybe the whole thing of being explainable to humans is a little bit overrated well maybe yeah i guess i you know you could say the same thing about our brain that when we perform acts of cognition we have no idea how we do it really we do though i mean we for at least for the visual system the auditory system and so on we do get some understanding of the principles that they operate under but uh for many deeper cognitive tasks we don't have that that's right so let me ask yeah you've also been doing work on bioinformatics does it amaze you that the fundamental building blocks so if we take a step back and look at us humans the building blocks used by evolution to build us intelligent human beings is all contained there in our dna it's amazing and and what's really amazing is that we have are beginning to learn how to edit dna which which is very very very fascinating this this ability to take a sequence find it in the genome and do something to it i mean that's really taking our biological systems towards the worlds of algorithm of algorithms yeah but it raises a lot of questions um you have to distinguish between doing it on an individual or doing it on somebody's germ line which means that all of the descendants will be affected so that's like an ethical yeah so it raises very severe ethical questions and um and even doing it on individuals um is uh so there's a lot of hubris involved that you can assume that knocking out a particular gene is going to be beneficial because you don't know what the side effects are going to be so we have this wonderful new world of gene editing uh which is you know very very impressive and it it could be used in agriculture it could be used in medicine in various ways um but very serious ethical problems arise what are to you the most interesting places where algorithms sort of the ethical side is an exceptionally challenging thing that i think we're going to have to tackle with all of uh genetic engineering but on the algorithmic side there's a lot of benefit that's possible so is there uh areas where you see exciting possibilities for algorithms to help model optimize study biological systems yeah i mean we we can certainly analyze genomic data to figure out which genes are operative in the cell and under what conditions and which proteins affect one another uh which prote which proteins physically interact um we can sequence proteins and modify them um is there some aspect of that that's a computer science problem or is that still fundamentally a biology problem well it's a big data it's a statistical big data problem for sure so you know the biological data sets are increasing our ability to study our ancestry by to study the tendencies towards disease to personalize treatment according to what's in our genomes and what tendencies for disease we have to be able to predict what troubles might come upon us in the future and anticipate them to to understand whether you um for a woman whether her proclivity for um breast cancer is so strong enough that she would want to take action to avoid it you dedicate your 1985 touring award lecture to the memory of your father what's your fondest memory of your dad seeing him standing in front of a class at the blackboard drawing perfect circles by hand and showing his his ability to attract the interest of the motley collection of eighth grade students that he was teaching when when did you get a chance to see him draw the perfect circles on rare occasions he i would get a chance to sneak into his classroom and observe observation and i think he was at his best in the classroom i think he really came to life and had fun um not only teaching but but you know engaging in chit chat with the students and you know ingratiating himself with the students and what i inherited from that is the great desire to be a teacher i retired recently and a lot of my former students came students who with whom i had done research or who had read my papers or who had been in my classes and when they talked about about me they talked not about my 1979 paper or my 1992 paper but about what they what came away in my classes and not just the details but just the approach and the the manner of teaching and so i sort of take pride in the at least in my early years as a faculty member at brickley i was exemplary in preparing my lectures and i always came in prepared to the teeth and able therefore to deviate according to what happened in the class and to really really provide a model for the students so is there advice you could give out for others on how to be a good teacher so preparation is one thing you've mentioned being exceptionally well prepared but there are other things pieces of advice that you can impart well the top three would be preparation preparation and preparation why is preparation so important i guess uh is uh it's because it gives you the ease to deal with any situation that comes up in the in the classroom and uh you know if you're if you discover that you're not getting through one way you can do it another way if the students have questions you can handle the questions ultimately you're also feeling the the the crowd the students of what they're struggling with what they're picking up just looking at them through the questions but even just through their eyes yeah and because of the preparation you can uh you can dance you can dance you can you can say it another way or give another angle are there in particular ideas and algorithms that computer science do you find were big aha moments for students were they for some reason once they got it it clicked for them and they fell in love with computer science or is it individual is it different for everybody it's different from everybody you have to work differently with students some some of them just don't don't need much influence you you know they they're just running with what they're doing and they just need an ear and now and then others need a little prodding others need to be persuaded to collaborate among themselves rather than working alone [Music] they have their personal ups and downs so you have to have to deal with each student as a human being and bring out the best humans are complicated yeah perhaps a silly question if you could relive a moment in your life outside of family because it made you truly happy or perhaps because it changed the direction of your life in a profound way what moment would you pick i was kind of a lazy student as an undergraduate and even in my first year in graduate school and i think it was when i started doing research i had a couple of summer jobs where i was able to contribute and i had an idea and then there was one particular course on mathematical methods in operations research where i just gobbled up the material and i scored 20 points higher than anybody else in the class then came to the attention of the faculty and it made me realize that i had some ability some ability that was going somewhere uh you realize you're pretty good at this thing i don't think there's a better way to end it richard was a huge honor thank you for decades of incredible work thank you for talking thank you it's been a great pleasure and uh your superb interviewer i'll stop it thanks for listening to this conversation with richard carp and thank you to our sponsors eight sleep and cash app please consider supporting this podcast by going to eightsleep.com lex to check out their awesome mattress and downloading cache app and using code lex podcast click the links buy the stuff even just visiting the site but also considering the purchase helps them know that this podcast is worth supporting in the future it really is the best way to support this journey i'm on if you enjoy this thing subscribe on youtube review it with five stars nappa podcast support it on patreon or connect with me on twitter at lex friedman if you can figure out how to spell that and now let me leave you with some words from isaac asimov i do not fear computers i fear lack of them thank you for listening and hope to see you next time you |
Jitendra Malik: Computer Vision | Lex Fridman Podcast #110 | the following is a conversation with jitendra malik a professor at berkeley and one of the seminal figures in the field of computer vision the kind before the deep learning revolution and the kind after he has been cited over 180 thousand times and has mentored many world-class researchers in computer science quick summary of the ads two sponsors one new one which is better help and an old goody expressvpn please consider supporting this podcast by going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links buy the stuff it really is the best way to support this podcast and the journey i'm on if you enjoy this thing subscribe on youtube review it with 5 stars on apple podcast support it on patreon or connect with me on twitter at lex friedman however the heck you spell that as usual i'll do a few minutes of ads now and never neons in the middle that can break the flow of the conversation this show is sponsored by better help spelled h-e-l-p help check it out at betterhelp.com lex they figure out what you need and match you with a licensed professional therapist in under 48 hours it's not a crisis line it's not self-help it's professional counseling done securely online i'm a bit from the david goggins line of creatures as you may know and so have some demons to contend with usually on long runs or all nights working forever and possibly full of self-doubt it may be because i'm russian but i think suffering is essential for creation but i also think you can suffer beautifully in a way that doesn't destroy you for most people i think a good therapist can help in this so it's at least worth a try check out their reviews they're good it's easy private affordable available worldwide you can communicate by text anytime and schedule weekly audio and video sessions i highly recommend that you check them out at betterhelp.com lex this show is also sponsored by expressvpn get it at expressvpn.com to support this podcast and to get an extra three months free on a one-year package i've been using expressvpn for many years i love it i think expressvpn is the best vpn out there they told me to say it but it happens to be true it doesn't log your data it's crazy fast and it's easy to use literally just one big sexy power on button again for obvious reasons it's really important that they don't log your data it works on linux and everywhere else too but really why use anything else shout out to my favorite flavor of linux ubuntu mate 2004 once again get it at expressvpn.comlexpod to support this podcast and to get an extra three months free and a one year package and now here's my conversation with jitendra in 1966 seymour papper at mit wrote up a proposal called the summer vision project to be given as far as we know to 10 students to work on and solve that summer so that proposal outlined many of the computer vision tasks we still work on today why do you think we underestimate and perhaps we did underestimate and perhaps still underestimate how hard computer vision is because most of what we do in vision we do unconsciously or subconsciously in human vision in human vision so that gives us this that effortlessness gives us the sense that oh this must be very easy to implement on a computer now this is why the early researchers in ai got it so wrong however if you go into neuroscience or psychology of human vision then the complexity becomes very clear the fact is that a very large part of the the cerebral cortex is devoted to visual processing i mean and this is true in other primates as well so once we looked at it from a neuroscience or psychology perspective it it becomes quite clear that the problem is very challenging and it will take some time you said the higher level parts are the harder parts i think vision appears to to be easy because uh most of what visual processing is subconscious or unconscious right so we underestimate the difficulty whereas uh when you are like proving a mathematical theorem or playing chess the difficulty is much more evident so because it is your conscious brain which is processing uh various aspects of the problem-solving behavior whereas in vision all this is happening but it's not in your awareness it's in your it's operating below that but it's it still seems strange yes that's true but it seems strange that as computer vision researchers for example the community broadly is time and time again makes the mistake of um thinking the problem is easier than it is or maybe it's not a mistake we'll talk a little bit about autonomous driving for example how hard of a vision task that is it do do you think i mean what is it just human nature or is there something fundamental to the vision problem that we we underestimate we're still not able to be cognizant of how hard the problem is yeah i think in the early days it could have been excused because in the early days all aspects of ai were regarded as too easy but i think today it is much less excusable and i think why people fall for this is because of what i call the fallacy of the successful first step there are many problems in vision where getting 50 of the solution you can get in one minute getting to 90 percent can take you a day getting to 99 percent may take you five years and 99.99 may be not in your lifetime i wonder if that's a unique division that it seems that language people are not so confident about so natural language processing people are a little bit more cautious about our ability to to solve that problem i think for language people intuit that we have to be able to do natural language understanding for vision it seems that we're not cognizant or we don't think about how much understanding is required it's probably still an open problem but in your sense how much understanding is required to solve vision like this put another way how much something called common sense reasoning is required to really be able to interpret even static scenes yeah so vision operates at uh at all levels and there are parts which are which can be solved with what we could call maybe peripheral processing so in the in the human vision literature there used to be these terms sensation perception and cognition which roughly speaking referred to like the front end of processing middle stages of processing and higher level of processing and i think they made a big deal out of out of this and they wanted to just study only perception and then dismiss certain certain problems as being quote cognitive but really i think these are artificial divides the problem is continuous at all level and there are challenges at all levels the techniques that we have today they work better at the lower and mid levels of the problem i think the higher levels of the problem quote the cognitive levels of the problem are there and we in many real applications we have to confront them now how much that is necessary will depend on the application for some problems it doesn't matter for some problems it matters a lot so i am for example a pessimist on fully autonomous driving in the near future and the reason is because i think there will be that 0.01 percent of the cases where quite sophisticated cognitive reasoning is called for however there are tasks where you can first of all they are much more they are robust so in the sense that error rates error is not so much of a problem for example uh uh let's say we are you're doing uh image search you're trying to get images based on some some some description some visual description we are very tolerant of errors there right i mean when google image search gives you some images back and a few of them are wrong it's okay it doesn't hurt anybody there's no there's not a matter of life and death but making mistakes when you're driving at 60 miles per hour and you could potentially kill somebody is much more important so just for the for the fun of it since you mentioned let's go there briefly about autonomous vehicles so one of the companies in the space tesla is work with andre karpathy and elon musk are working on a system called autopilot which is primarily a vision-based system with eight cameras and uh basically a single neural network a multi-task neural network they they call it hydro net multiple heads so it does multiple tasks but is forming the same representation at the core do you think driving can be converted in this way to uh purely a vision problem and then solved within you with learning or even more specifically in the current approach what do you think about what tesla autopilot team is doing so the way i think about it is that there are certainly subset subsets of the visual based driving problem which are quite solvable so for example driving in freeway conditions is quite a solvable problem i think there were demonstrations of that going back to the 1980s by someone called ernst stickmans in munich in the 90s there were approaches from carnegie mellon there were approaches from our team at berkeley in the 2000s there were approaches from stanford and so on so autonomous driving in certain settings is very doable the challenge is to have an autopilot work under all kinds of driving conditions at that point it's not just a question of vision or perception but really also of control and dealing with all the edge cases so where do you think most of the difficult cases to me even the highway driving is an open problem because uh it applies the same 50 90 95 99 rule or the first step the fallacy of the first step i forget how you put it we fall victim to i think even highway driving has a lot of elements because to solve autonomous driving you have to completely relinquish the the fat help of a human being you're always in control so that you're really going to feel the edge cases so i i think even highway driving is really difficult but in terms of the general driving task do you think vision is the fundamental problem or is it also your action the the interaction with the environment the ability to uh and then like the middle ground i don't know if you put that under vision which is trying to predict the behavior of others which is a little bit in the world of understanding the scene but it's also trying to form a model of the actors in the scene and predict their behavior yeah i include that in vision because to me perception blends into cognition and building predictive models of other agents in the world which could be other agents could be people other agents could be other cars that is part of the task of perception because perception always has to uh not tell us what is now but what will happen because what's now is boring it's done it's over with okay yeah we care about the future because we act in the future and we care about the past and as much as it informs what's going to happen in the future so i think we have to build predictive models of of of behaviors of people and and those can get quite complicated so uh uh i mean uh i i've seen examples of this in uh actually i mean i own a tesla and it has various safety features built in and uh what i see are these examples where let's say there is some uh skateboarder i mean this i and i i don't want to be too critical because obviously this is these are the systems are always being improved and any specific criticism i have maybe the system six months from now will not have that that that particular failure mode so uh it it had it it had the wrong response and it's because it couldn't predict what what this skateboarder was going to do okay and because it really required that higher level cognitive understanding of what skateboarders typically do as opposed to a normal pedestrian so what might have been the correct behavior for a pedestrian a typical behavior for pedestrian was not the typical behavior for a skateboarder right yeah and uh so so therefore to do a good job there you need to have enough data where you have pedestrians you also have skateboarders you've seen enough skateboarders to see what uh what kinds of patterns or behavior they have so it is it is in principle with enough data that problem could be solved but uh i think our current systems computer vision systems they need far far more data than humans do for learning those same capabilities so say that there is going to be a system that solves autonomous driving do you think it will look similar to what we have today but have a lot more data perhaps more compute but the fundamental architectures involved like neuro well in the case of tesla autopilot is neural networks do you think it will look similar in that regard and we'll just have more data that's a scientific hypothesis as which way is it going to go uh i will tell you what i would bet on uh so and this is at my general philosophical position on how these uh learning systems have been uh what we have found currently very effective in computer vision uh with in in the deep learning paradigm is sort of tabula rasa learning and tabular us are learning in a supervised way with lots and lots of what's going on in the sense that blank slate we just have the system which is given a series of experiences in this setting and then it learns there now if let's think about human driving it is not tabular assad learning so at the age of 16 in high school uh a teenager goes into uh goes into driver ed class right and now at that point they learn but at the age of 16 they are already visual geniuses because from 0 to 16 they have built a certain repertoire of vision in fact most of it has probably been achieved by age 2 right in in this period of age up to age 2 they know that the world is three-dimensional they know how objects look like from different perspectives they know about occlusion they know about common dynamics of humans and other bodies they have some notion of intuitive physics so they they built that up from their observations and interactions in early childhood and of course reinforced through their their growing up to age 16. so then at age 16 when they go into driver ed what are they learning they're not learning afresh the visual world they have a mastery of the visual world what they are learning is control okay they are learning how to be smooth about control about steering and brakes and so forth they're learning a sense of typical traffic situations now the the that education process can be quite short because they are coming in as visual geniuses and of course in their future they're going to encounter situations which are very novel right so during my driver ed class that i may not have had to deal with a skateboarder i may not have had to deal with a truck driving in front of me who's from who's where the back opens up and some junk gets dropped from the truck and i have to deal with it right but i can deal with this as a driver even though i did not encounter this in my driver at class and the reason i can deal with it is because i have all this general visual knowledge and expertise and uh do you think the learning mechanisms we have today can do that kind of long-term accumulation of knowledge or do we have to uh do some kind of you know in the the the work that led up to expert systems with knowledge representation you know the broader field of what of artificial intelligence uh worked on this kind of accumulation of knowledge do you think neural networks can do the same i think uh i don't see any in principle problem with neural networks doing it but i think the learning techniques would need to evolve significantly so the current uh the current learning techniques that we have yeah is our supervised learning you're given lots of examples xiy pairs and you you learn the functional mapping between them i think that human learning is far richer than that it includes many different components there are there is a a child explores the world and sees as for example a child takes an object and manipulates it in his or her hand and therefore gets to see the object from different points of view and the child has commanded the movement so that's a kind of learning data but the learning data has been arranged by the child and this is a very rich kind of data the child can do various experiments with the world so so there are many aspects of sort of human learning and these have been studied in in child development by psychologists and they what they tell us is that supervised learning is a very small part of it there are many different aspects of learning and what we would need to do is to develop models of all of these and then train our systems in that with that kind of uh protocol so new new methods of learning yes some of which might imitate the human brain but you also in your talks have mentioned some of the compute side of things the in terms of the difference in the human brain or referencing marvik hans marvel the so do you do you think there's something interesting valuable to consider about the difference in the computational power of the human brain versus the computers of today in terms of instructions per second yes so if we go back uh so so this is a point i've been making for 20 years now and i think once upon a time the way i used to argue this was that we just didn't have the computing power of the human brain our computers were uh were not quite there and i mean there is a well well-known trade-off which we know that the that neurons are slow compared to transistors but uh but we have a lot of them and they have a very high connectivity whereas in silicon you have much faster devices transistors switch at on the order of nanoseconds but the connectivity is usually smaller right at this point in time i mean we are now talking about 2020 we do have if you consider the latest gpus and so on amazing computing power and if we look back at enhanced modex type of calculations which he did in the 1990s we may be there today in terms of computing power comparable to the brain but it's not in the of the same style it's of a very different style so i mean for example the the style of computing that we have in our gpus is far far more power hungry than the style of computing that is there in the human brain or other biological uh entities yeah and that the efficiency part is uh we're gonna have to solve that in order to build actual real world systems of large scale let me ask sort of the high level question step taking a step back how would you articulate the general problem of computer vision does such a thing exist so if you look at the computer vision conferences and the work that's been going on it's often separated into different little segments breaking the problem of vision apart into whether segmentation 3d reconstruction object detection i don't know image capturing whatever uh there's benchmarks for each but if you were to sort of philosophically say what is the big problem of computer vision does such a thing exist yes but it's not in isolation so if we have to so for all intelligence tasks i always go back to sort of biology or humans and if we think about vision or perception in that setting we realize that perception is always to guide action perception in a for a biological system does not give any benefits unless it is coupled with action so we can go back and think about the first multicellular animals which arose in the cambrian era you know 500 million years ago and uh these animals could move and they could see in some ways and their two activities helped each other because uh uh how does movement help movement helps that because you can get food in different places but you need to know where to go and that's really about perception or seeing i mean i mean vision is perhaps the single most perception sense but all the others are equally are also important so uh so perception and action kind of grow go together so earlier it was in these very simple feedback loops which were about uh finding food or avoiding becoming food if there's a predator running uh trying to you know eat you up and and so forth so so we must at the fundamental level connect perception to action then as we evolved uh perception became more and more sophisticated because it served many more purposes and uh so today we have what seems like a fairly general purpose capability which can look at the external world and build and a model of the external world inside the head we do have that capability that model is not perfect and psychologists have great fun in pointing out the ways in which the model in your head is not a perfect model of the external world and they have create various illusions to show the ways in which it is imperfect but it's amazing how far it has come from a very simple perception action loop that you exists in you know an animal 500 million years ago once we have this these very sophisticated visual systems we can then impose a structure on them it's we as scientists who are imposing that structure where we have chosen to characterize this part of the system as this code module of object detection or quote this module of 3d reconstruction what's going on is really all of these processes are running simultaneously and uh and and they are running simultaneously because originally their purpose was in fact to help guide action so as a guiding general statement of a problem do you think we can say that the the general problem of computer vision you said in humans it was tied to action do you think we should also say that ultimately the the goal the problem of computer vision is to sense the world in the way that helps you act in the world yes i think that's the most fundamental uh that's the most fundamental purpose we have by now hyper evolved so we have this visual system which can be used for other things for example judging the aesthetic value of a painting and this is not guiding action maybe it's guiding action in terms of how much money you will put in your auction bid but that's a bit stretched but the basics are in fact in terms of action but we have we've evolved really this hyper uh we have hyper evolved our visual system actually just too uh sorry to interrupt but perhaps it is fundamentally about action you kind of jokingly said about spending but perhaps the capitalistic uh drive that drives a lot of the development in this world is is about to exchange your money and the fundamental action is money if you watch netflix if you enjoy watching movies you're using your perception system to interpret the movie ultimately your enjoyment of that movie means you'll subscribe to netflix so the action is this uh this extra layer that we've developed in modern society perhaps this is fundamentally tied to the action of spending money well certainly with respect to uh you know interactions with firms so so in this homo economics role when you're interacting with firms it does become uh it does become that that's what else is there uh that was a rhetorical question okay so to to linger on the division between the static and the dynamic so much of the work in computer vision so many of the breakthroughs that you've been a part of have been in the static world in looking at static images and then you've also worked on starting but it's a much smaller degree the community is looking at dynamic and video at dynamic scenes and then there is robotic vision which is dynamic but also where you actually have a robot in the physical world interacting based on that vision which problem is harder the the the intuit sort of the the trivial first answers well of course one image is harder but so if you look at a deeper question there are we um what's the term cutting ourselves cutting ourselves at the knees or like making the problem harder by focusing on the images that's a fair question i think sometimes we we can simplify our problem so much that we essentially lose part of the juice that could enable us to solve the problem and one could reasonably argue that to some extent this happens when we go from video to single images now historically uh you have to consider the limits of imposed by the competition capabilities we had so if we many of the choices made in the computer vision community uh through the 70s 80s 90s can be understood as choices which were forced upon us by the fact that we just didn't have access to compute enough compute not enough memory none of hard drives not exactly not enough not enough compute not enough storage so so think of these choices so one of the choices is focusing on single images rather than video okay clear questions storage and compute we had to focus on we did we used to detect edges and throw away the image right so you have an image which i say 256 by 256 pixels and instead of keeping around the grayscale value what we did was we detected edges find the places where the brightness changes a lot so now that and now and then throw away the rest so this was a major compression device and the hope was that this makes it that you can still work with it and the logic was humans can interpret a line drawing and uh and yes and this will save us a competition so many of the choices were dictated by that i think uh today we are no longer detecting edges right we process images with convnets because we don't need to we don't have that those compute restrictions anymore now video is still under studied because video compute is still quite challenging if you are a university researcher i think video computing is not so challenging if you are at google or facebook or amazon still super challenging i've just spoke with the vp of engineering google head of the youtube search and discovery and they still struggle doing stuff on video it's very difficult except doing except using techniques that are essentially the techniques you used in in the 90s some very basic computer vision techniques no that's when you want to do things at scale so if you want to operate at the scale of all the content of youtube it's very challenging and there's similar issues in facebook but as a researcher you you have you have more uh you know opportunities you can train large you know that works with relatively large uh video data sets yeah yes so i think that this is part of the reason why we have so emphasized static images i think that this is changing and over the next few years i see a lot more progress happening in in video so i have this generic statement that to me video recognition feels like 10 years behind object recognition and you can quantify that because you can take some of the challenging video data sets and their performance on action classification is like say 30 which is kind of what we used to have around 2009 in object detection you know so it's like about 10 years behind and uh whether it'll take 10 years to catch up is a different question hopefully it will take less than that let me ask a similar question i've already asked but once again so for dynamic scenes do you think do you think some kind of injection of knowledge basis and reasoning is required to help improve like action recognition like if if if um if we solve the general action recognition problem what do you think the solution would look like it's another way yeah so i i completely agree that knowledge is called for and that knowledge can be quite sophisticated so the way i would say it is that perception blends into cognition and cognition brings in issues of memory and this notion of a schema from psychology which is uh let me use the classic example which is you go to a restaurant right now the things that happen in a certain order you walk in somebody takes you to a table a waiter comes gives you a menu takes the order food arrives eventually a bill arrives etc etc this is a classic example of ai from the 1970s uh it was called there was the term frames and scripts and schemas these are all quite similar ideas okay in the 70s the way the ai of the time dealt with it was by build hand coding this so they hand coded in this notion of a script and the various stages and the actors and so on and so forth and use that to interpret for example language i mean if there's a description of a of a story involving some people eating at a restaurant there are way all these inferences you can make because you know what happens typically at a restaurant so i think this kind of uh this kind of knowledge is absolutely essential so i think that when we are going to do long-form video understanding we are going to need to do this i think the kinds of technology that we have right now with 3d convolutions over a couple of seconds of clip or video it's very much tailored towards short-term video understanding not that long-term understanding long-term understanding requires a notion of this notion of schemas that i talked about perhaps some notions of goals intentionality functionality and so on and so forth now how will we bring that in so we could either revert back to the 70s and say okay i'm going to hand code in a script or we might try to learn it so i tend to believe that we have to find learning ways of doing this because i think learning ways to land up being more robust and there must be a learning version of the story because uh children acquire a lot of this knowledge by uh sort of just observation so at no moment in a child's life there's a it's possible but i think it's not so typical that somebody that a mother coaches a child through all the stages of what happens in a restaurant they just go as a family they they they go to the restaurant they eat come back and the child goes through 10 such experiences and the child has has got a schema of what happens when you go to a restaurant so we somehow need to we need to provide that capability to our systems you mentioned the following line from the end of the alan turing paper uh computing machinery and intelligence that many people like you said many people know and very few have read where he proposes the turing test this is this is how you know because it's towards the end of the paper instead of trying to produce a program to simulate the adult mind why not rather try to produce one which simulates the child's so that's a really interesting point if i think about the benchmarks we have before us the the tests of our computer vision systems they're often kind of trying to get to the adult so what kind of benchmarks should we have what kind of tests for computer vision do you think we should have that mimic the child's in computer vision yeah i think we should have those and we don't have those today and i think uh the part of that the challenge is that we should really be collecting data of the type that a child uh that the child experiences right so that gets into issues of you know privacy and so on and so forth but there are attempts in this direction to sort of try to collect the kind of data that a child encounters growing up so what's the child's linguistic environment what's the child's visual environment so if we could collect that kind of data and then develop learning schemes based on that data that would be one way to do it i i think that's a very promising direction myself there might be people who would argue that we could just short circuit this in some way and uh sometimes we have imitated uh we have not we have had success by not imitating nature in detail so the usual example is airplanes right we don't build flapping winds flapping wings so uh yes that's uh that's one of the points of debate uh in my mind i i i would i would bet on this this learning like a child approach so one of the fundamental aspects of learning like a child is the interactivity so the child gets to play with the data set it's learning from yes it's against the select i mean you can call that active learning you can you know in the machine learning world you can call it a lot of terms what are your thoughts about this whole space of being able to play with the data set or select what you're learning yeah so i think that uh i i believe in that and i think that we could achieve it in in two ways and i think we should use both so one is uh actually real robotics right so real uh you know physical embodiments of agents who are interacting with the world and they have a physical body with dynamics and mass and moment of inertia and friction and all the rest and you learn your body the robot learns its body by doing a series of actions the second is that simulation environments so i think simulation environments are getting much much better in my in my life in facebook ai research our group has worked on something called habitat which is a simulation environment which is a visually photorealistic environment of you know places like houses or interiors of various urban spaces and so forth and as you move you get a picture which is a pretty accurate picture so uh i i can now uh you can imagine that subsequent generations of these simulators will be accurate not just visually but with respect to you know forces and masses and haptic interactions and so on and uh then then we have that environment to play with i think that let me state one reason why i think this active being able to act in the world is important i think that this is one way to break the correlation versus causation barrier so this is something which is of a great deal of interest these days i mean people like judea pearl have talked a lot about uh why that we are neglecting causality and he describes the entire set of successes of deep learning as just curve fitting right because it's uh but i i don't quite agree about as a troublemaker he is but uh causality is important but causality is not is not like a single silver bullet it's not like one single principle there are many different aspects here and one of the ways in which uh one of our most reliable ways of establishing causal links and this is the way for example the the medical community does this is randomized control trials so you have you you pick some situation and now in some situation you perform an action and for certain others you don't right so so you have a control experiment well the child is in fact performing controlled experiments all the time right right right okay small scale and in a small scale and but but that is a way that the child gets to build and refine its causal models of the world and my colleague alison gopnik has together with a couple of authors co-authors has this book called the scientist in the crib referring to children so i like the part that i like about that is the scientist wants to do wants to build causal models and the scientist does control experiments and i think the child is doing that so to enable that we will need to have these these active experiments and i think this could be done some in the real world and some in simulation so you have hope for simulation i have a hopeless solution that's an exciting possibility if we can get to not just photo realistic but what's that called life realistic yeah uh simulation so you don't see any fundamental blocks to why we can't eventually simulate the the principles of what it means to exist in the world as a physical i i don't see any fundamental problems there i mean and look the computer graphics community has come a long way right so the in the early days back going back to the 80s and 90s they were they were focusing on visual realism right and then they could do the easy stuff but they couldn't do stuff like hair or fur and so on okay well they managed to do that then they couldn't do physical actions right like there's a bowl of glass and it falls down and it shatters but then they could start to do pretty realistic models of that and so on and so forth so the graphics people have shown that they can do this forward direction not just for optical interactions but also for physical interactions so i think uh of course some of that is very computer intensive but i think by and by we will find ways of making our models ever more realistic you break vision apart into in one of your presentations early vision static scene understanding dynamics and understanding and raise a few interesting questions i thought i could just throw some some at you just to see if you want to talk about them so early vision so it's what is it you said um sensation perception and cognition so is this a sensation yes what can we learn from image statistics that we don't already know so at the lowest level what um what can we make from just this the the statistic the basics so there were the variations in the rock pixels the textures and so on yeah so what we seem to have learned is uh uh uh is that there's a lot of redundancy in these images and as a result we are able to do a lot of compression and and this compression is very important in biological settings right so you might have ten to the eight photoreceptors and only ten to the six fibers in the optic nerve so you have to do this compression by a factor of hundreds to one and uh and uh so there are analogs of that which are happening in in our neural net artificial neural network that's the early layer so you think there's a lot of compression that can be done in the beginning yeah just just the statistics yeah um how much how much well so i mean the the way to think about it is just how successful is image compression right and we we and there are and that's been done with older technologies but it can be done with there are several companies which are trying to use sort of these more advanced neural network type techniques for compression both for static images as well as for for video one of my former students has a company which is trying to do stuff like this and i think i think that they are showing quite interesting results and i think that that's all the success of that's really about image statistics and video statistics but that's still not doing compression of the kind when i see a picture of a cat all i have to say is it's a cat that's another semantic kind of complication yeah so this is this is at the lower level right so we are we are we as i said yeah that's focusing on low level statistics so to linger on that for a little bit uh you mentioned how far can bottom-up image segmentation go and in general what you mentioned that the central question for scene understanding is the interplay of bottom-up and top-down information maybe this is a good time to elaborate on that maybe define what is what is up what is top down in the comments yes the computer vision uh right that's uh so today what we have are a are very interesting systems because they work completely bottom up how are they what does bottom bottom-up mean sorry so bottom-up means in this case means a feed-forward net neural network so starting from the raw pixels yeah they start from the raw pixels and they they end up with some something like cat or not a cat right so our our systems are running totally feed forward they're trained in a very top-down way so they're trained by saying okay this is a cat there's a cat there's a dog there's a zebra etc and i'm not happy with either of these choices fully we have gone into uh because we have completely separated these processes right so there is a so i would like the uh the process uh so what do we know compared to biology so in biology what we know is that the processes in at test time at run time those processes are not purely feed forward but they involve feedback so and they involve much shallower neural networks so the kinds of neural networks we are using in computer vision say a resnet 50 has 50 layers well in in the brain in the visual cortex going from the retina to it maybe we have like seven right so they're far shallower but we have the possibility of feedback so there are backward connections and this might enable us to uh to deal with the more ambiguous stimuli for example so the the biological solution seems to involve feedback the solution in in artificial vision seems to be just feed forward but with a much deeper network and the two are functionally equivalent because if you have a feedback network which just has like three rounds of feedback you can just unroll it and make it three times the depth and create it in a totally feed forward way so this is something which i mean we have written some papers on this theme but i really feel that this should this theme should be pursued further have some kind of recurrence mechanism yeah okay the other uh so that so that's uh so i so i want to have a little bit more top down in the at test time okay then at training time we make use of a lot of top-down knowledge right now so basically to learn to segment an object we have to have all these examples of this is the boundary of a cat and this is the boundary of a chair and this is the boundary of a horse and so on and this is too much top-down knowledge how do humans do this we manage to we manage with far less supervision and we do it in a sort of bottom-up way because for example we're looking at a video stream and the horse moves and that enables me to say that all these pixels are together yeah so the gestural psychologists used to call this the principle of common fate so there was a bottom-up process by which we were able to segment out these objects and we have totally focused on this top-down training signal so in my view we have currently solved it in machine vision this top-down bottom-up interaction but i don't find the solution fully satisfactory and i would rather have a bit of both in at both stages for all computer vision problems which is not just segmentation and and and and the question that you can ask is so for me i'm inspired a lot by human vision and i care about that you could be a just a hard-boiled engineer not give a damn so to you i would then argue that uh you would need far less training data if you could make my uh research agenda you know fruitful okay so maybe taking a step into uh segmentation static scene understanding what is the interaction between segmentation and recognition you mentioned the movement of objects so for people who don't know computer vision segmentation is this weird activity that we that computer vision folks have all agreed is very important uh of drawing outlines around objects versus a bounding box or and then classifying that object what's what's the value of segmentation what is it as a problem in computer vision how is it fundamentally different from detection recognition any other problems yeah so i think uh so so segmentation enables us to say that some set of pixels are an object without necessarily even being able to name that object or knowing properties of that object oh so you mean segmentation purely as as as the act of separating an object from its background a blob of uh of that's united in some way from his background yeah so identification if you were making an entity out of it and justification yeah beautifully so so i think that we have that capability and that is that enables us to uh as we are growing up to acquire uh names of objects with very little supervision so suppose the child lets posit that the child has this ability to separate out objects in the world then when the there's a the mother says pick up your bottle or the cat's behaving funny today [Laughter] the word cat suggests some object and then the child sort of does the mapping right right the mother doesn't have to teach a specific object labels by pointing to them weak supervision works in the context that you have the ability to create objects so i think that uh so to me that's that's a very fundamental capability uh there are applications where this is very important uh for example medical diagnosis so in medical diagnosis uh you have some uh brain scan i mean some this is some work that we did in my group where you have ct scans of people who have had traumatic brain injury and what uh what the radiologist needs to do is to precisely delineate various places where there might be bleeds for example and there's there are clear needs like that so they're certainly very practical applications of computer vision where segmentation is necessary but philosophically segmentation enables the task of recognition to proceed with much weaker supervision than we require today and you think of segmentation as this kind of task that takes on a visual scene and breaks it apart into into interesting entities yeah that might be useful for whatever the task is yeah and and it is not semantics free so i think i i mean it it blends into it involves perception and cognition it is not it is not i i think the mistake that we used to make in the early days of computer vision was to treat it as a purely bottom-up perceptual task it is not just that because we do revise our notion of segmentation with more experience right because for example there are objects which are non-rigid like animals or humans and uh i think understanding that all the pixels of a human are one entity is actually quite a challenge because the parts of the human they can move independently and the human wears clothes so they might be differently colored so it's all sort of a challenge you mentioned the three hours of computer vision are recognition reconstruction reorganization can you describe these three r's sure how they interact yeah so uh so recognition is the easiest one because that's uh what i think people generally think of as computer vision achieving these days which is uh labels so is this a cat is this a dog is this a chihuahua i mean you know it could be very fine grain like you know specific breed of a dog or a specific species or bird or it could be very abstract like animal but given a part of an image or a whole image say put a label on that yeah so that's that's recognition reconstruction is uh essentially it you can think of it as inverse graphics i mean that's one way to think about it so graphics is your you have some internal computer representation and uh you have a computer representation of some objects arranged in a scene and what you do is you produce a picture you produce the pixels corresponding to a rendering of that scene so uh so let's do the inverse of this we are given an image and we try to we we we say oh this image arises from some objects in a scene looked at with a camera from this viewpoint and we might have more information about the objects like their shape maybe their textures maybe you know color et cetera et cetera so that's the reconstruction problem in a way that you are in your head creating a model of the external world okay reorganization is to do with essentially finding these entities so uh so it's uh organization or the word organization implies structure so uh that in in uh perception in psychology we use the term perceptual organization that uh the the world is not just an image is not just seen as is not internally represented as just a collection of pixels but we make these entities we create these entities objects whatever you want to call in the relationship between the entities as well or is it purely about the entities it could be about the relationships but mainly we focus on the fact that there are entities sometimes i'm trying to pinpoint what the organization means so organization is that instead of like a uniform grid we have the structure of objects so segmentation is a small part of that so segmentation gets us going towards that yeah and you kind of have this triangle where they all interact together yes so how do you see that interaction in uh sort of uh reorganization is yes defining the entities in the world the recognition is labeling those entities and then reconstruction is what filling in the gaps well to for example see impute some 3d objects corresponding to each of these entities that would be part of adding more information that's not there in the raw data correct i mean i started pushing this kind of a view in the around 2010 or something like that because at that time in computer vision the distinction that people were were just working on many different problems but they treated each of them as a separate isolated problem with each with its own data set and then you try to solve that and get good numbers on it so i wasn't i didn't like that approach because i wanted to see the connection between these and if people divided up vision into into various modules the way they would do it is as low level mid-level and high-level vision corresponding roughly to the psychologist's notion of sensation perception and cognition and i didn't that didn't map to tasks that people cared about okay so therefore i tried to promote this particular framework as a way of considering the problems that people in computer vision were actually working on and trying to be more explicit about the fact that they actually are connected to each other and i was at that time just doing this on the basis of information flow now it turns out in the last five years or so in the post the deep learning revolution that this this architecture has turned out to be very conducive to that because basically in these neural networks we are trying to build multiple representations there can be multiple output heads sharing common representations so in a certain sense today given the reality of what solutions people have to these i i i i do not need to preach this anymore it is it is just there it's part of the solution space so speaking of neural networks how much of this uh problem of computer vision of the organization recognition can be um reconstruction how much of it can be learned end to end do you think instead of uh set it and forget it just plug and play have a giant data set multiple perhaps multi-modal and then just learn the entirety of it well so i i think that currently what that end-to-end learning means nowadays is end-to-end supervised learning and and that i would argue is too narrow a view of the problem i would i like this child development view this lifelong learning view one where there are certain capabilities that are built up and then there are certain capabilities which are built up on top of that so uh that's that's what i i believe in so i think uh end-to-end learning in the supervised setting for a very precise task to me is a kind of is uh it's sort of a limited view of the of the learning process got it so if we think about beyond purely supervised look at back to children you mentioned six lessons that we can learn from children uh of be multimodal be incremental be physical explore be social use language can you speak to these perhaps picking one that you find most fundamental toward yeah time today yeah so i mean i should say to give due credit this is from a paper by smith and gasser and it reflects essentially i would say common wisdom among child development people it's just that these are this is not common wisdom among people in computer vision and ai and machine learning so i view my role as uh trying to bridge the worlds bridge the two worlds so uh so let's take an example of a multi-modal i like that so multi-modal canonical example is uh a child interacting with uh with an object so then the child so the child holds a ball and plays with it so at that point it's getting a touch signal so the touch signal is is getting as the notion of 3d shape but it is sparse and then the child is also seeing a visual signal right and and these two so imagine these are two in totally different spaces right so one is the space of receptors on the skin of the fingers and the thumb and the palm right and then these map on to these neuronal fibers are getting activated somewhere right these lead to some activation in somatosensory cortex i mean a similar thing will happen if we have a robot hand okay and then we have the pixels corresponding to the visual view but we know that they correspond to the same object right so that's a very very strong cross calibration signal and it is self-supervisory which is beautiful right there's nobody assigning a label the mother doesn't have to come and assign a label the child doesn't even have to know that this object is called a ball okay but the obj the child is learning something about the three-dimensional world from this signal uh i think tactile and visual there is some work on there is a lot of work currently on audio and visual okay an audio visual so there is some event that happens in the world and that event has a visual signature and it has a auditory signature so there is this glass bowl on the table and it falls and breaks and i hear the smashing sound and i see the pieces of glass okay i've built that connection between the two right we have people uh i mean this has become a hot topic in computer vision in the last couple of years there is there are problems like uh separating out multiple speakers right which was a classic problem in in audition they call this the problem of source separation or the cocktail party effect and so on but just try to do it visually when you also have it becomes so much easier and so much more useful so the the multimodal i mean there's so much more signal with multimodal and you can use that for some kind of weak supervision as well yes because they are occurring at the same time in time yeah so you have time which links the two right so at a certain moment t1 you've got a certain signal in the auditory domain and a certain signal in the visual domain but they must be causally related yeah it's an exciting area not well studied yet not yeah i mean we have a little bit of work at this but uh but but so much more needs to be done yeah so so so so this this is this is a good example be physical that's to do with uh like the one thing we talked about earlier that that there's a embodied world to mention language use language so no chomsky believes that language may be at the core of cognition at the core of everything in the human mind what is the connection between language and vision to you like what's more fundamental are they neighbors is one the parent and the child the chicken and the egg oh it's very clear it is vision which is the appearance the fundament the permission is the fundamental ability okay well so uh it comes before you think vision is more fundamental than language correct and and and it and yeah you can think of it either in phylogeny or in ontogeny so phylogeny means if you look at evolutionary time right so you we have vision that developed 500 million years ago okay then something like when we get to maybe like five million years ago you have the first bipedal primate so when we started to walk then the hands became free and so then manipulation the ability to manipulate objects and build tools and so on and so forth so you said 500 000 years ago no no sorry the the first multicellular animals which you can say had some intelligence arose 500 million years ago okay and now let's fast forward to say the last seven million years which is the development of the hominid line right where from the other primates we have the branch which leads on to modern humans now there are many of these hominids but the the ones which you know people talk about lucy because that's like a skeleton from three million years ago and we know that lucy walked okay so at this stage you have that the hand is free for manipulating objects and then the ability to manipulate objects build tools and the brain size grew in this era so okay so now you have manipulation now we don't know exactly when language arrows but after that but after that because no apes have i mean so i mean chomsky is correct in that that it is a uniquely human capability and we primates other primaries don't have that but so it developed somewhere in this era but it developed i would i mean uh argue that it probably developed after we had this stage of uh uh humans or i mean the human species already able to manipulate and a hands-free much bigger brain size and for that there's a lot of vision has already had had to have developed yeah so the sensation and the perception may be some of the cognition yeah so we we so those so so that so the world so there so so these ancestors of us you know three four million years ago they had uh they had spatial intelligence so they knew that the world consists of objects they knew that the objects were in certain relationships to each other they had observed causal interactions among objects they could move in space so they had space and time and all of that so language builds on that substrate so language has a lot of i mean i mean the all human languages have constructs which depend on a notion of space and time where did that notion of space and time come from it had to come from perception and action in the world we live in yeah what you refer to as the spatial intelligence yeah yeah to linger a little bit we mentioned touring and his uh mention of we should learn from children nevertheless language is the fundamental piece of the test of intelligence that touring proposed what do you think is a good test of intelligence are you what would impress the heck out of you is it fundamentally natural language or is there something in vision i i think uh i i wouldn't i i don't think we should have created a single test of intelligence so just like i don't believe in iq as a single number i think generally there can be many capabilities which are correlated perhaps so i think that there will be uh there will be accomplishments which are visual accomplishments accomplishments which are uh accomplishments in manipulation or robotics and then accomplishments in language i do believe that language will be the hardest not to crack really yeah so what's what's harder to pass the spirit of the touring test or like whatever formulation will make it natural language convincingly in natural language like somebody you would want to have a beer with hang out and have a chat with or the general natural scene understanding you think language is the type i think i'm not a fan of the i think i think turing test that turing as he proposed the test in 1950 was trying to solve a certain problem yeah imitation yeah and and i think it made a lot of sense then where we are today 70 years later i think i think we we should not worry about that i mean i think the turing test is no longer the right way to uh to to channel research in in ai because that it takes us down this path of this chat bot which can fool us for five minutes or whatever okay i think i would rather have a list of 10 different tasks i mean i think their tasks which their tasks in the manipulation domain tasks and navigation tasks and visual scene understanding tasks in under reading a story and answering questions based on that i mean so my favorite language understanding task would be you know reading a novel and being able to answer arbitrary questions from it okay right i i think that to me uh and this is not an exhausted list by any means so i would uh i think that that's what we where we need to be going to and each of these on each of these axes there's a fair amount of work to be done so on the visual understanding side in this intelligence olympics that we've set up yeah what's a good test for one of many of visual scene understanding uh do you think such benchmarks exist sorry to interrupt no there there aren't any i i think i think essentially to me a really uh good aid to the blind so suppose there was a blind person and i needed to assist the blind person so ultimately like we said vision that aids in the action in the survival in this world yeah maybe in a simulated world maybe easier to to measure performance in a simulated world what we are ultimately after is performance in the real world so david hilbert in 1900 proposed 23 open problems in mathematics some of which are still unsolved most important famous of which is probably the riemann hypothesis you've thought about and presented about the hilbert problems of computer vision so let me ask what to you today i don't know when the last year you presented that 2015 but versions of it yeah you're kind of the the face and the spokesperson for computer vision yeah it's your job to just to state what the problem the open problems are for the field so what today are the hilbert problems of computer vision do you think let me pick pick one to which i regard as uh clearly clearly unsolved which is what i would call long-form video understanding so so we have a video clip and we want to understand the behavior in there in terms of agents their goals intentionality and uh make predictions about what might happen you know so so that that kind of understanding which goes away from atomic visual action so so in the short range the question is are you sitting are you standing are you catching a ball right that we can do now or we even if we can't do it fully accurately if we can do it at 50 percent maybe next year we'll do it at 65 and so forth but i think the long range video understanding i don't think we we we can do today well today and that means so long and it blends into cognition that's the reason why it's challenging and so you have to track you have to understand the entities you have to understand the sds you have to track them and you have to have some kind of model of their behavior correct and their and if their behavior might be these are these are agents so they are not just like passive objects but the agent so therefore we they might they would exhibit gold directed behavior okay so this is this is one area then i will talk about say understanding the world in 3d now this may seem paradoxical because in a way we have been able to do 3d understanding even like 30 years ago right but i don't think we currently have the richness of 3d understanding in our computer vision system that we would like because ah so let me elaborate on that a bit so currently we have two kinds of techniques which are not fully unified so there are the kinds of techniques from multi-view geometry that you have multiple pictures of a scene and you do a reconstruction using stereoscopic vision or structure from motion but these techniques do not they totally fail if you just have a single view because they are relying on this this multiple geometry okay then we have some techniques that we have developed in the computer vision community which try to guess 3d from single views and these techniques are based on on supervised learning and they are based on having a training time 3d models of objects available and this is completely unnatural supervision right that's not cad models are not injected into your brain okay so what would i like what i would like would be a kind of uh learning as you move around the world uh notion of 3d so so we we have our succession of visual experiences and from those we so in as part of that i might see a chair from different viewpoints or a table from viewpoint different viewpoints and so on now as part that enables me to build some internal representation and then next time i just see a single photograph and it may not even be of that chair it's of some other chair and i have a guess of what its 3d shape is like so you're almost learning the cad model kind of yeah implicitly i mean implicitly i mean the cad model need not be in the same form as used by computer graphics hidden in the representation it's hidden in the representation the ability to predict new views and what i would see if i went to such and such position by the way and on a small tangent on that are you uncomforta are you okay or comfortable with neural networks that do achieve visual understanding that do for example achieve this kind of 3d understanding and you don't know how they you don't know the rep you're not able to interest but you're not able to visualize or understand or interact with the representation so the fact that they're not or may not be explainable yeah i think that's fine i to me that is uh so so let me put some caveats on that so it depends on the setting so first of all i think uh uh the uh humans are not explainable so yeah that's a really good point yeah so we we one human to another human is not fully explainable i think there are settings where explainability matters and these might these are these might be for example questions on medical diagnosis so i'm in a setting where maybe the doctor maybe a computer program has made a certain diagnosis and then depending on the diagnosis perhaps i should have treatment day or treatment b right so now is the computer programs diagnosis based on data which was data collected of for american males who are in their 30s and 40s and maybe not so relevant to me maybe it is relevant you know et cetera et cetera and we i mean in medical diagnosis we have major issues to do with the reference class so we may have acquired statistics from one group of people and applying it to a different group of people who may not share all the same characteristics the data might have there might be error bars in the prediction so that prediction should really be taken with a huge grain of salt and but this has an impact on what treatments should be picked right so so there are settings where i want to know more than just this is the answer but what i acknowledge is that so so so so i in that sense explainability and interpretability may matter it's about giving error bounds and a better sense of the quality of the decision where what i where i'm willing to sacrifice interpretability is that i believe that there can be systems which can be highly performant but which are internally black boxes and and that seems to be words headed some of the best performing systems are essentially black boxes yeah uh fundamentally by their construction you and i are black boxes to each other yeah so the nice thing about the black boxes we are is so we ourselves are black boxes but we're also those of us who are charming are able to convince others like explain the black what's going on inside the black box with narratives with stories so in some sense uh neural networks don't have to actually explain what's going on inside they just have to come up with stories real or fake that convince you that they know what's going on and i'm sure we can do that we can create those nearer those stories neural networks can create those stories yeah and the transformer will be involved do you think we will ever build a system of human level or superhuman level intelligence we've kind of defined what it takes to try to approach that but do you think we'll do you think that's within our reach the thing that we thought we could do what touring thought actually we could do by a year 2000 right what do you think we'll ever be able to do so i think there are two answers here one question one answer is in principle can we do this at some time and my answer is yes the second answer is a pragmatic one do you think we will be able to do it in the next 20 years or whatever and to that man says no so and of course that's a wild guess i i i i think that you know donald trump's felt is not a favorite person of mine but one of his lines is very good which is about known knowns known unknowns and unknown unknowns so in the business we are in there are known unknowns and we have unknown unknowns so i think with respect to a lot of what the case in vision and robotics i feel like we have known unknowns so i have a sense of where we need to go and what the problems that need to be solved are i feel with respect to natural language understanding and high level cognition it's not just known unknowns but also unknown unknowns so it is very difficult to put any kind of uh time frame to that uh do you think some of the unknown unknowns might be positive in that they'll surprise us and make the job much easier so fundamental breakthroughs i think that is possible because certainly i have been very positively surprised by how effective these deep learning systems have been because i certainly would not have believed that in 2010 i think what we knew from the mathematical theory was that convex optimization works when there's a single global optima then these gradient descent techniques would work now these are non-linear systems with non-convex systems huge number of variables so over-parametrized over-parameterized and the people who used to play with them a lot the ones who are totally immersed in the lore and the black magic they knew that they worked uh well even though they were really i thought like everybody no the claim that i hear from my friends like yan lacoon and so forth now yeah that they feel that they were comfortable with them well he says but the community as a whole was certainly not and i think uh we were to me that was the surprise that they actually worked robustly for a wide range of problems from a wide range of initializations and so on and uh so that was that that was certainly more rapid progress than uh we expected but then there are certainly lots of times in fact most of the history and fear is when we have made less pro progress at a slower rate than we expected so uh we just keep going i think uh what i regard as uh really unwarranted are these these fears of uh you know agi in 10 years and 20 years and that kind of stuff because that's based on completely unrealistic models of how rapidly we will make progress in this field so i agree with you but i've also gotten a chance to interact with very smart people who really worry about the existential threats of ai and i as an open-minded person and sort of taking and taking it in do you think if ai systems in some way the unknown unknowns not super intelligent ai but in ways we don't quite understand uh the nature of superintelligence will have a detrimental effect on society do you think this is something we should be worried about or we need to first allow the unknown our nose to become known unknowns i think we need to be worried about ai today i think that it is not just a worry we need to have when we get that agi i think that ai is being used in many systems today and there might be settings for example when it causes biases or decisions which could be harmful i mean decisions which could be unfair to some people or it could be a self-driving cars which kills a pedestrian so ai systems are being deployed today right and they're being deployed in many different settings maybe in medical diagnosis maybe in a self-driving car maybe in selecting applicants for an interview so i would argue that when these systems make mistakes there are consequences and we are in a certain sense responsible for those consequences so i would argue that this is a continuous effort it is we and and this is something that in a way is not so surprising it's about all engineering and scientific progress which uh great power comes great responsibility so as these systems are deployed we have to worry about them and it's a continuous problem i don't think of it as something which will suddenly happen on some day in 2079 for which i need to design some clever trick i'm saying that these problems exist today yeah and we need to be continuously on the lookout for worrying about safety biases risks right i mean the self-driving car kills are pedestrian and they have right i mean the this uber incident in arizona yeah right it has happened right this is not about agi it in fact it's about a very dumb intelligence which is also killing people the worry people have with agi is the scale and i but i think you're 100 right is like the thing that worries me about ai today and it's happening in a huge skills recommend recommender systems recommendation systems so if you look at twitter or facebook or youtube their controlling the ideas that we have access to the news and so on and that's a fundamentally machine learning algorithm behind each of these recommendations and they i mean my life would not be the same without these sources of information i'm a totally new human being and the ideas that i know are very much because of the internet because of the algorithm that i recommend those ideas and so as they get smarter and smarter i mean that is the agi yeah is that's the the algorithm that's recommending the next youtube video you should watch has control of millions of billions of people that that algorithm is already super intelligent and has complete control of the population not a complete but very strong control for now we can turn off youtube we can just go have a normal life outside of that but the more and more that gets into our life it's that algorithm we start depending on it in the different companies that are working on the algorithm so i think it's you're right it's already it's already there and youtube in particular is using computer vision doing their hardest to try to understand the content of videos so they could be able to connect videos with the people who would benefit from those videos the most and so that development could go in a bunch of different directions some of which might be harmful so yeah you're right the the the threats of ai are here already we should be thinking about them on a philosophical notion if you could personal perhaps if you could relive a moment in your life outside of family because it made you truly happy or was a profound moment that impacted the direction of your life what would you go to i don't think of single moments but i look over the long haul i feel that i've been very lucky because i feel that i think that in scientific research a lot of it is about being at the right place at the right time and you can you can work on problems at a time when they're just too premature you know you butt your head against them and and nothing happens because it's the prerequisites for success are not there and then there are times when you are in a field which is all pretty mature and you can only solve curricules upon colloquius i've been lucky to have been in this field which for 34 years 35 well actually 34 years as a professor at berkeley so longer than that uh which when i started in it was just like some little crazy absolutely useless field which couldn't really do anything to a time when it's really really solving a lot of practical problems has a lot has offered a lot of tools for scientific research right because computer vision is impactful for images in biology or astronomy and and so on and so forth and we have so we have made great scientific progress which has had real practical impact in the world and i feel lucky that i i got in at a time when the field was very young and at a time when it is it's now mature but not fully mature it's mature but not done i mean it's really in still in a in a productive phase yes yeah yeah i think people 500 years from now would laugh are you calling this field mature yeah that is very possible yeah so but you're also lest i forget to mention you've also mentored some of the biggest names of computer vision computer science and ai today uh there's so many questions i could ask but really is what what is it how did you do it what does it take to be a good mentor what does it take to be a good guide yeah i i think what i feel i've been lucky to have had very very smart and hardworking and creative students i think some part of the credit just belongs to being at berkeley i think those of us who are at top universities are blessed because we have very very smart and capable students coming on knocking on our door so so i have to be humble enough to acknowledge that but what have i added i think i have added something what i have added is uh i think what i've always tried to teach them is a sense of picking the right problems so i think that in science in the short run success is always based on technical competence your you know you're quick with math or you are whatever i mean there's certain technical capabilities which make for short-range progress long-range progress is really determined by asking the right questions and focusing on the right problems and i feel that what i've been able to bring to the table in terms of advising these students is some sense of taste of what are good problems what are problems that are worth attacking now as opposed to waiting 10 years what's a good problem if you could summarize if is that possible to even summarize like what what's your sense of a good problem i i think uh i think uh i have a sense of what is a good problem which is uh there is a british scientist uh in fact he won a nobel prize peter medover who has a a book on on this and uh basically he calls it the research is the art of the soluble so we need to sort of find problems which are which are not yet solved but which are approachable and he sort of refers to this sense that there is this problem which isn't quite solved yet but it has a soft underbelly there is some place where you can you know spear the beast yes and having that intuition that this problem is ripe is is a good thing because otherwise you can just beat your head and not make progress so i think that is that is important so if if i have that and if i can convey that to students it's not just that they do great research while they're working with me but that they continue to do great research so in a sense i'm proud of my students and their achievements and their great research even 20 years after they've seized being my student so it's in part developing helping them develop that sense that a problem is not yet solved but it's solvable correct the other thing which i have which i i think i bring to the table uh is i is a certain intellectual breadth i i've spent a fair amount of time studying psychology neuroscience relevant areas of applied math and so forth so i can probably help them see some connections to disparate things which they might not have otherwise so so the smart students coming into berkeley can be very uh deep in the sense they can think very deeply meaning very hard down one particular path but where i could help them is the the shallow breadth but uh whereas they would have the the narrow depth and uh but that's that's of some value well it was beautifully refreshing just to hear you naturally jump to psychology back to computer science and this conversation back and forth i mean that that's uh that's actually a rare quality and i think it's certainly for students empowering to think about problems in a new way so for that and for many other reasons i really enjoyed this conversation thank you so much it was a huge honor thanks for talking today it's been my pleasure thanks for listening to this conversation with jitendra malik and thank you to our sponsors betterhelp and expressvpn please consider supporting this podcast by going to betterhelp.com lex and signing up at expressvpn.com lexpod click the links buy the stuff it's how they know i sent you and it really is the best way to support this podcast and the journey i'm on if you enjoy this thing subscribe on youtube review 5 stars on apple podcast support it on patreon or connect with me on twitter at lex friedman don't ask me how to spell that i don't remember myself and now let me leave you with some words from prince mishkin and the idiot by dostoyevsky beauty will save the world thank you for listening and hope to see you next time you |
Brian Kernighan: UNIX, C, AWK, AMPL, and Go Programming | Lex Fridman Podcast #109 | the following is a conversation with Brian Kernighan a professor of computer science at Princeton University he was a key figure in the computer science community in the early UNIX days alongside UNIX creators Ken Thompson and Dennis Ritchie he co-authored the C programming language with Dennis Ritchie the creator of C and has written a lot of books on programming computers and life including the practice of programming the goal programming language and his latest UNIX a history and a memoir he co-created awk the text processing language used by Linux folks like myself he Co designed ample an algebraic modeling language that I personally love and have used a lot in my life for large scale optimization I think I can keep going for a long time with his creations and accomplishments which is funny because given all that he's one of the most humble and kind people I've spoken to on this podcast quick summary of the ads - new sponsors the amazing self cooling 8 sleep mattress and rake on earbuds please consider supporting the podcast by going to 8 sleep complex and going to buy a rake on comm slash flex click the links buy the stuff it really is the best way to support this podcast and a journey I'm on if you enjoy this thing subscribe on youtube review it with fire stars an apple podcast supported on patreon or connect with me on Twitter at lex friedman as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show is sponsored by 8 sleep and it's incredible pod Pro mattress you can checkout at 8 sleep calm slash flex to get $200 off the mattress controls temperature with an app and can cool down to as low as 65 degrees research shows the temperature has a big impact on the quality of our asleep anecdotally he's been a game changer for me I love it the patro is packed with sensors that track heart rate heart rate variability and respiratory rate showing it all on their app once you wake up plus if you have a partner you can control the temperature of each side of the bed I don't happen to have one but the a sleep app reminds me that I should probably get on that so ladies if a temperature controlled mattress isn't a good reason to apply I don't know what is the apps health metrics are amazing but the cooling alone is honestly worth the money as some of you know I don't always sleep but when I do I choose the a sleep pod Pro mattress check it out at a sleep calm slash flex to get $200 off this show is also sponsored by Ray con earbuds get them at buy rake on Comm slash flex they've quickly become a main method of listening to podcasts audiobooks and music when I run do the push ups and pull ups that have begun to hate at this point or just living life in fact I often listen to brown noise with these what I'm thinking deeply about something it helps me focus the mind they're super comfortable pair easily great sound great bass six hours of play time in fact for fun I have one of the earbuds in now and I'm listening to Europa by Santana probably one of my favorite guitar songs it kind of makes me feel like I'm in a music video so they told me to say that a bunch of celebrities use these like Snoop Dogg Melissa Etheridge and cardi B I don't even know cardi B is but her earbud game is on point to mention celebrities actually care about I'm sure if Richard Fineman was still with us he'd be listening to the Joe Rogan experience with Rick on earbuds get them at by Drake on comm / Lex it's how they know I sent you and increases the chance that he'll support this podcast in the future so for all of the sponsors click all the links it really helps this podcast and now here's my conversation with Brian Kernighan started being developed fifty years ago in me more than fifty years ago can you tell the story like you're describing your new book of how UNIX was created ha if I couldn't remember that far back well it was some while ago um so I think the gist of it is that at Bell Labs and in 1969 there were a group of people who had just finished working on the multics project which was itself falling on to CTS s so we can go back sort of an infinite regress in time but the CTS s was a very very very nice time sharing system was very nice to use I actually used it as that summer I spent in Cambridge in 1966 for was the hardware there right so what's the operating system what's the hardware there what's the CTS look like so cts s looked like kind of like a standard time sharing system certainly at the time it was the only time sharing if no let's go back to the basic ok in the beginning was the word and the word sign there was time sharing systems yeah if we go back into let's call it the 1950s and early 1960s most computing was done on very big computers physically big although not terribly powerful by today's standards that were maintained in very large rooms and you used things like punch cards to write programs on talk to him so you would take a deck of cards write your program on it send it over a counter hand it to an operator and some while later back would come something that said oh you made a mistake and then you'd recycle and so it's very very slow so the idea of time sharing was that you take basically that same computer but connect to it with something that looked like an electric typewriter they could be a long distance away it could be closed but fundamentally what the operating system did was to give each person who was connected to it and wanting to do something a small slice of time on to do a particular job so I might be editing a file so I would be typing and every time I hit a keystroke the operating system would wake up and said oh he typed character let me remember that and then it go back to doing something else would be going around and around a group of who were trying to get something done giving each a small slice of time and giving them each the illusion that they pretty much hit the whole machine to themselves and hence time sharing that is sharing the computing time resource of the computer among a number of people who are doing it without the individual people being aware that there's others in a sense the illusion the feeling is that you the machine is your own pretty much that was the idea yes you had if it were well done and if it were fast enough and other people were doing too much you did have the illusion that you had the whole machine to yourself and it was very much better than the punch card model and so cts s the compatible time sharing system was I think arguably the first of these it was done I guess technically 64 or something like that it ran on an IBM 7090 for slightly modified to have twice as much memory as the norm it had two banks of 32 k words instead of one so 32 K words yes where's this 36 bit so call it you know about a hundred and fifty kilobytes times two so by today's standards that's down in the noise yeah at the time that was a lot of memory and memory was expensive so C TSS was just a wonderful environment to work on it was done by the people that MIT led by Fernando Corbett Oh of Cour be who died just earlier this year and a bunch of other folks and then so I spent the summer of 66 working on that had a great time met a lot of really nice people and indirectly knew of people at Bell Labs who were also working on a follow-on to C TSS that was called multics so multics was meant to be the system that would do everything that C TSS did but do it better for a larger population that's all the usual stuff now the actual time sharing the scheduling how much what's the algorithm that performs the scheduling what's that look like how much magic is there what are the metrics how does it all work in the beginning so the answers I don't have a clue I think the basic idea was nothing more than who all wants to get something done suppose things are very in the middle of the night then I get all the time that I want suppose that you and I are contending at high noon for something like that then probably the simplest algorithm is a round robin one that gives you a bit of time gives me a bit of time and then we could adapt to that like what are you trying to do are you text editing or are you compiling or something and we might adjust the scheduler according to things like that so okay so multics was trying to just do some of the clean it up a little bit well it was it was meant to be much more than that so multix was the multiplexed information and computing service and it was meant to be a very large thing we would provide computing utility something that where you could actually think of it as just a plug in the wall service sort of like cloud computing today yeah same idea but 50 odd years earlier and so what multix offered was a richer operating system environment piece of hardware that was better designed for doing the kind of sharing of resources and presumably lots of other things do you think people at that time had the dream of what cloud computing is starting to become now which is computing is everywhere that you can just plug in almost no you know and you never know how the magic works you just kind of plug in add in your little computation they need to perform and it does it it was that the dream I don't know where that was the dream I wasn't part of it at that point remember I was an intern first summer but my sense is given that it was over 50 years ago yeah they had that idea that it was an information utility that it was something where if you had a computing task to do you could just go and do it now I'm betting that they didn't have the same view of computing for the masses let's call it the idea that you know your grandmother would be shopping on Amazon I don't think that was part of it but if your grandmother were a programmer it might be very easy for her to go and use this kind of utility what was your dream of computers at that time what did you see as the future of computers could you have predicted what computers are today that you sense Oh short answer absolutely not I have no clue I'm not sure I had a dream it was a dream job in the sense that I really enjoyed what I was doing I was surrounded by really really nice people Cambridge is a very fine city to live in in the summer less so in the winter when it snows but in the summer it was a delightful time and so I really enjoyed all of that stuff and I learned things and I think the good fortune of being there for summer led me then to get a summer job at Bell Labs the following summer and that was going to useful for the future so this Bell Labs is this magical legendary place so first of all where is Bell Labs and can you start talking about that journey towards Unix at Bell Labs yeah so Bell Labs is physically scattered around at the time scattered around New Jersey the primary location was in a town called Murray Hill where a location called Murray Hill is actually then across the boundary between two small towns in New Jersey called New Providence and Berkeley Heights think of it as about 15-20 miles straight west of New York City and therefore but an hour north of here and for instance and at that time it had make up a number three or four thousand people there many of whom had PhDs and mostly doing physical sciences chemistry physics materials kinds of things but very strong math and it rapidly growing interest in computing as people realized you could do things with computers that you might not have been able to do before you could replace labs with computers that had worked on models of what was going on so that was the essence of Bell Labs and again I wasn't the permanent play there I was that was another internship I got lucky in internships I mean if you could just linger in a little bit what was the what was in the air there because some of this is the number of Nobel Prizes the number of touring Awards and just legendary computer scientists that come from their inventions including developments including UNIX it's just is unbelievable so is it was there something special about that place oh I think there was very definitely something special I mentioned the number of people's a very large number of people very highly skilled working in an environment where there was always something interesting to work on because the goal of Bell Labs which was a small part of a TMT which provided basically the country's phone service the goal of a TMT was to provide service for everybody and the goal of Bell Labs was to try and make that service keep getting better so improving service and that meant doing research on a lot of different things physical devices like the transistor or fiber optical cables or microwave systems all of these things the labs worked on and it was kind of just the beginning of real boom times in computing as well is when I was there I went there first in 66 so computing was at that point fairly young and so people were discovering that you could do lots of things with computers so how's Unix born so multix in spite of having an enormous number of really good ideas lots of good people working on it fundamentally didn't live up at least in the short run and I think ultimately really ever to its goal of being this information utility it was too expensive and certainly what was promised was delivered much too late and so in roughly the beginning of 1969 Bell Labs pulled out of the project the project at that point had included MIT Bell Labs and General Electric General Electric made computers so General Electric was the hardware operation so Bell Labs realizing this wasn't going anywhere on a time scale they cared about pulled out his project and this left several people with an acquired taste for really really nice computing environments but no computing environment and so they started thinking about what could you do if you're going to design a new operating system that would provide the same kind of comfortable computing as cts s head but also the facilities of something like multics sort of brought forward and so they did a lot of paper design stuff and at the same time Ken Thompson found what is characterized as a little-used pdp-7 where he started to do experiments with file systems just how do you store information on a computer in an efficient way and then this famous story that his wife went away to California for three weeks taking their one-year-old son and three weeks and he sat down and wrote an operating system which ultimately became Unix so software productivity was good in those days the PDP what's the PDP seven so it's a piece of hardware yeah it's a piece of part where it was one of our leading machines made by Digital Equipment Corporation Dec and it was a mini computer so called it had yeah I would have to look up the numbers exactly but it had a very small amount of memory maybe 16 K 16-bit words or something like that relatively slow probably not super expensive maybe again making this up I'd have to look it up a hundred thousand dollars or something like that which is not super expensive in the sious right it was expensive it was enough that you and I probably wouldn't be my white one but a modest group of people could get together but in any case in it came out if I recall in 1964 so by 1969 it was getting a little obsolete and that's why it was little used if you can sort of comment what do you think it's like to write an operating system like that so that process that Ken went through in three weeks because you were I mean you're part of that process you've contributed a lot to UNIX his early development so what do you think it takes to do that first step that first kind of from designed to a reality on the PDP well let me correct one thing I had nothing to do with it so I did not write it I have never written operating system code and so I don't know now an operating system is simply code and this first one wasn't very big but it's something that lets you run processes of some that you execute some kind of code that has been written it lets you store information for periods of time so that it doesn't go away when you turn the power off or reboot or something like that and there's a kind of a core set of tools that are technically not part of an operating system but you probably need them in this case Ken wrote an assembler for pdp-7 that worked he needed a text editor so that he could actually create text he had the file system stuff that he had been working on and then the rest of it was just a way to load things executable code from the file system into the memory give it control and then recover control when it was finished or in some other way quit what was the code written in the primarily the programming language was it in assembly pdp-7 assembler that Ken created these things were assembly language until probably the call at 1973 or 74 something like that yeah forgive me if it's a dumb question but it feels like a daunting task to write any kind of complex system in assembly absolutely it feels like impossible to do any kind of what we think of a software engineering assembly is to work on a big picture I think it's hard it's been a long time since I wrote assembly language it is absolutely true that in some other language if you make a mistake nobody tells you there are no training wheels whatsoever and so stuff doesn't work now what and there's no the buggers well there could be debuggers but that's the same problem right how do you actually get something that will help you debug it so part of it is is an ability to see the big picture now these systems were not big in the sense of today's picture so the big picture was in some sense more manageable I mean then realistically there's an enormous variation in the capabilities of programmers and Ken Thompson who did that first one is kind of the singularity in my experience of programmers with no disrespect to you or even to me he's gonna die several leagues removed I know there's levels this is it's a it's a fascinating thing that there are unique stars in particular in the programming space and in a particular time you know the time matters to the timing of when that person comes along and the a wife does have to leave see like there's this weird timing that happens that and then all sudden something beautiful is created I mean how does it make you feel that there's a system I was created in in three weeks or maybe you can even say on a whim but not really but of course quickly that is now you could think of most of the computers in the world run on a unix-like system right well how do you ensure like if you kind of zoom from the alien perspective if you're just observing earth that all sudden these computers took over the world and they started from this little initial seed of Unix how does that make you feel it's quite surprising and and and you asked earlier but predictions the answer is no there's no way you could predict that kind of evolution and I don't know whether it was inevitable or just a whole sequence of blind luck I suspect more the latter and so I look at it and think gee that's kind of neat I think the real question is what this can think about that because he's the guy arguably from whom it really came tremendous contributions from Dennis Ritchie and then others around in that Bell Labs environment but you know if you had to pick a single person that would be can see if written in you book UNIX a history and a memoir are there some memorable human stories funny or profound from that time they just kind of stand out oh there's a lot of them in a sense and again it's a question if can you resurrect them this memory fails but I think part of it was that Bell Labs at the time was was a very special kind of place to work because there were a lot of interesting people and the environment was very very open and free it was a very cooperative environment very from the environment and so if you had an interesting problem you go and talk to somebody and they might help you with the solution and and it was a kind of a fun environment to in which people did strange things and often tweaking the bureaucracy in one way or another the rebellious and in some kinds of ways in some ways yeah absolutely I think most people didn't take too kindly to the bureaucracy and I'm sure the bureaucracy put up with an enormous that they didn't really want to so maybe to linger on it a little bit you have a sense of what the philosophy that characterized unix's the design not just the initial but just carry through the years just being there being around what's the fundamental philosophy behind the system I think one aspect the fundamental philosophy was to provide an environment that made it easy to write her easier productive to write program so as men as a programmer environment it wasn't meant specifically as something to do some other kind of job for example it was used extensively for word processing but it wasn't designed as a word processing system it was used extensively for lab control but it wasn't designed for that it was used extensively as a front end for big other systems big dumb systems but it wasn't designed for that it was meant to be an environment where it was really easy to write programs that so the programmers could be highly productive and part of that was to be a community and there's some observation from Dennis Ritchie I think at the end of the book that says that and that from his standpoint the real goal was to create a community where people could work as programmers on a system I think in that sense certainly for many many years it succeeded quite well at that and part of that is the technical aspects of because it made it really easy to write programs people did write interesting programs those programs tended to be used by other programmers and so it was kind of a virtuous circle are of more and more stuff coming out that was really good for programmers and you're part of that community of programmers so what was the like writing programs on that early unix it was a blast it really was you know I like to program I'm not a terribly good programmer but it was a lot of fun to write code and in the early days there was an enormous amount of what you would today I suppose called low-hanging fruit people hadn't done things before and this was this new environment and the the whole combination of nice tools and very responsive system and tremendous colleagues made it possible to write code you could have an idea in the morning you could do it and you know an experiment with it you could have something limping along that night or the next day and people would react to it and they would say oh that's wonderful but you're really screwed up here and and the feedback Luke was then very very short and tight and so a lot of things got developed fairly quickly that in many cases still exists today and I think that was part of what made it fun because programming itself is fun it's puzzle solving in a variety of ways but I think it's even more fun when you do something that somebody else then uses even if they whine about it not working the fact that they used it is as part of the reward mechanism and what was the method of an interaction the communication we need that feedback loop I mean this is before the internet certainly before the internet um it was mostly physical right there you know somebody would come into your office and say something so these places are all closed but like offices are nearby we're really lively into interaction yeah yeah no Bell Labs was fundamentally one giant building and most of the people were involved in this unique stuff we're in two or three quarters and there was a room oh how big was it probably call it 50 feet by 50 feet make up a number of that and which had some access to computers there as well as in offices and people hung out there and had a coffee machine and so that there was a it was mostly very physical we did use email of course and but it was fundamentally all for a long time all on one machine so there was no need for internet it's fascinating to think about what computing would be today without Bell Labs it seems so many the people being in the vicinity of each other it's sort of getting that quick feedback working together there's so many brilliant people I don't know where else that could have existed in the world I've been given how that came together what yeah well how does that make you feel that that's a little element of history well I think that's very nice but in a sense it's survivor bias and if it hadn't happened at Bell Labs there were other places that we're doing really interesting work as well Xerox PARC is perhaps most obvious one Xerox PARC contributed enormous amount of good material and Men anything we take for granted today in the same way came from Xerox PARC experience I don't think they capitalized in the long run as much their parent company was perhaps not as lucky in capitalizing on this who knows but that would that's certainly another place where there was a tremendous amount of influence there were a lot of good university activities MIT was obviously no slouch in this kind of thing and and others as well so Unix turned out to be open source because of the various ways that AT&T operated and sort of they had to it was the focus was on telephones so well I think that's a mischaracterization in the sense it absolutely was not open source it was very definitely proprietary licensed but it was licensed freely to universities in source code form for many years and because of that generations of university students and their faculty people grew up knowing about Unix and there was enough expertise in the community that it then became possible for people to kind of go off in their own direction and build something that looked unix like the berkeley version of unix started with that licensed code and gradually picked up enough of its own code contributions notably from people like Bill joy that eventually it was able to become completely free of any TMT code now there was an enormous amount of legal jockeying around this that in the late early to late 80s Early 90s something like that and then not something that I guess the open source movement might have started when Richard Stallman started to think about this in the late 80s and by 1991 when Torvalds decided he was going to do a unix-like operating system there was enough expertise that in the community that first he had a target he could see what to do because the kind of the UNIX system call interface and the tools and so on were there and so he was able to build an operating system that at this point when you say UNIX in many cases what you're really thinking is Linux Linux yeah but it's it's funny that from my distant perception I felt that UNIX was open-source without actually knowing it but what you're really saying it was just freely licensed so it was freely licensed it felt open-source in a sense because universities are not trying to make money so there it felt open-source in a sense that you can get access if you wanted right and a very very very large number of universities had the license and they were able to talk to all the other universities who had the license and so technically not open technically belonging day T&T pragmatically pretty open and so there's a ripple effect that all the faculty and the students then I'll grew up and then they went throughout the world and permeated in that kind of way so what kind of features do you think made for a good operating system if you take the lessons of Unix you said like you know make it easy for programmers like that seems to be an important one but also UNIX turned out to be exceptionally robust and efficient right so is that an accident when you focus on the programmer or is that a natural outcome I think part of the reason for efficiency was that it began on extremely modest hardware very very very tiny and so you couldn't get carried away you couldn't do a lot of complicated things because you just didn't have the resources either processor speed or memory and so that enforced a certain minimal 'ti of mechanisms and maybe a search for generalizations so that you would find one mechanism that's served for a lot of different things rather than having lots of different special cases I think the file system and UNIX is a good example of that file system interface in its fundamental form is extremely straightforward and that means that you can write code very very effectively from for the file system and then one of those ideas and one of those generalizations is that gee that file system interface works for all kinds of other things as well and so in particular the idea of reading and writing to devices is the same as reading and writing to a disk that has a file system and then that gets carried further in other parts of the world processes become in effect files in a file system and the plan 9 operating system which came along I guess in the late 80s or something like that took a lot of those ideas from the original unix and tried to push the generalization even further so that in plan 9 a lot of different resources our file systems they all share that interface so that would be one example we're finding the right model of how to do something means that an awful lot of things become simpler and it means therefore that more people can do useful interesting things with them without him to think as hard about it so you said you're not a very good programmer you're the most modest human being ok but you'll continue saying that I understand how this works but you do radiate a sort of love for programming so let me ask do you think programming is more an art or science there's a creativity or kind of rigor I think it's some of each it's some combination some of the art is figuring out what it is that did you really want to do what should that program be what would make a good program and that's some understanding of what the task is what the people who might use this program want and I think that's that's art in many respects the science part is trying to figure out how to do it well and some of that is a real computer science II stuff like what algorithm should we use at some point mostly in the sense of being careful to use algorithms that will actually work properly or scale properly avoiding quadratic algorithms when a linear algorithm should be the right thing that got a more formal view of it same thing for data structures but also it's I think an engineering field as well then engineering is not quite the same as science because engineering you're working with constraints you have to figure out not only so what is a good algorithm for the kind of thing but what's the most appropriate algorithm given the amount of time we have to compute the amount of time we have to program what's likely to happen in the future with maintenance who's gonna pick this up in the future all of those kind of things that if you're an engineer you get to worry about whereas if you think of yourself as a scientist well you can maybe push them over their horizon in a way and if you're an artist what's that so just on your own personal level what's your process like of writing a program say a small and large sort of tinkering with stuff you just start coding right away and just kind of evolve iteratively with a loose notion or do you plan and a sheet of paper first and then kind of design and this you know what they teach you in the kind of software engineering courses an undergrad or something like that what's your process like it's certainly much more the informal incremental first I don't write big programs at this point it's been a long time since I wrote a program that weighs more and then I call it a few hundred or more lines something like that many of the programs are right or experiments for either something I'm curious about or often for something that I want to talk about in a class and so those necessarily tend to be relatively small a lot of the kind of code I write these days tends to be for sort of exploratory data analysis where I've got some collection of data and I want to try and figure out what on earth is going on in it and for that those programs tend to be very small sometimes you're not even programming you're just using existing tools like counting things or sometimes you're writing awk scripts because two or three lines will tell you something about a piece of data and then when it gets bigger well and I will probably write something in Python because that scales better up to call it a few hundred lines or something like that and it's been a long time since I wrote programs that were much more than that speaking of data exploration in awk first what is awk so awk is a scripting language that was done by myself el hijo on Peter Weinberger we did that originally in the late 70s it was a language that was meant to make really easy to do quick and dirty tasks like counting things or selecting interesting information from basically all text files rearranging it in some way or summarizing it runs the command on each line of a file I mean there's uh it's still exceptionally widely used today oh absolutely yeah it's so simple an elegant sort of the way to explore data turns out you can just write a script that does something seemingly trivial on a single line and that giving you that slice of the data somehow reveals something fundamental about the data you know that keeps that seems to work still yeah it's very good for that kind of thing that's sort of what it was meant for I think what we didn't appreciate was that the model is actually quite good for a lot of data processing kinds of tasks and that it's it's kept going as long as it has because at this point it's over 40 years old but it's still I think a useful tool and well this is paternal interest I guess but I think in terms of programming languages you get the most bang for the buck by learning awk and it doesn't scale the big programs but it does pretty pretty darn well on these little things where you just want to see all the something's in something so yeah I find I probably write more awk than anything so what what kind of stuff do you love about arc like is there if you can comment on sort of things that give you joy when you can in a simple program reveal something about it is there something that stands out from particular features I think it's mostly the selection of default behaviors that you sort of hinted at at a moment ago what Octus is to read through a set of files and then within each file it rich through a each of the lines and then on each of the lines it has a set of patterns that it looks for that's your arc program and if one of the patterns matches there is a corresponding action that you might perform and so it's kind of a quadruply nested loop or something like that um and that's all completely automatic you don't have to say any think about it you just write the pattern in the action and then run the data by it and and so that paradigm for programming is very natural and effective one and I think we captured that reasonably well and lock and it does other things for free as well it splits the data into fields so that on each line there feels separated by white space or something and so it does that for free you don't have to say anything about it and it collects information it goes along like what line are we on how many fields are there on this line so lots of things that just make it so that a program which in another language let's say Python would be 5 10 20 lines in Arcis one or two lines and so because it's one or two lines you can do it on the shell you don't have to open up another whole thing you can just do it right there and the interaction with Allah perfectly is there other shell commands that you love over the years like you really enjoy using don't major does everything so grep is a kind of what is it a simpler version of awk I would say in some some sense yeah right because what is grep so grep is it basically searches the input for particular patterns regular expressions technically of a certain class and it has that same paradigm that awk does it's a pattern action thing it reads through all the files and then all the lines in each file but it has a single pattern which is the regular expression you're looking for and a single action printed if it matches so it's a in that sense it's a much simpler version and you could write crap in Arcis as a one-liner and I use grep probably more than anything else at this point just because it it's so convenient and natural why do you think it's such a powerful tool grab not why do you think operating systems like Windows for example don't have it sort of you can of course I use which is amazing now there's windows for linux like the which you could basically use all the fun stuff like all can graph and inside of Windows but Windows naturally sort of in the best part of the graphical interface the simplicity sort of searching through a bunch of files and just popping up naturally why don't you think that why do you think that's unique to the UNIX and Linux environment I don't know I it's not strictly unique but it's certainly focused there and I think some of its the weight of history that Windows came from ms-dos ms-dos was a pretty pathetic operating system although common own and you know unbounded lis large number of machines but somewhere in roughly the 90s windows became a graphical system and I think Microsoft spent a lot of their energy on making that graphical interface what it is and that's a different model of computing it's a model of computing that where you point and click and sort of experiment with menus it's a model of computing worked right rather well for people who are not programmers just want to get something done whereas teaching something like the command line to non-programmers turns out just sometimes be an uphill struggle and so I think Microsoft probably was right and what they did now you mentioned whistle or whatever it's called that winix I wonder what spinasse wsl is but I've never actually pronounced the whistle I like it I got no idea but there have been things like that for longest cygwin for example which is a wonderful collection of take all your favorite tools from UNIX and Linux and just make them work perfectly on Windows and so that's a something that's been going on for at least 20 years if not longer and I use that on my one remaining Windows machine aw routinely because it it's for if you're doing something that is batch computing command sudo for command-line that's the right way to do it because the windows equivalents are if nothing else not familiar to me but I should I would definitely recommend to people to if they don't use cygwin to try whistle yes I say I've been so excited that I could use best ivy bash write scripts quickly in in Windows it's changed my life okay what's your perfect programming setup what computer what operating system want keyboard what editor yeah perfect is too strong a word is way to struggle read of what by default I have a at this point a 13-inch MacBook Air which I used because it's kind of a reasonable balance of the various things I need I can carry it around it's got enough computing horsepower screens big enough to keyboards okay and so I basically do most of my computing on that um I have a big iMac in my office that I use from time to time as well especially when I need a big screen but otherwise none tends not to be used as much editor I use mostly Sam which is an editor that Rob Pike wrote long ago at Bell Labs his did that sorry to interrupt it does that precede VI posts it post dates both VI and Emacs it is derived from Rob's experience with Edie and VI on D that's the original UNIX editor o dated probably before you were born so what's actually what's the history of editors can you can you briefly this is your fan I used Emacs I'm sorry to say so I'm sorry to come out with that but what's what's the kind of interplay there yeah so in ancient ancient times like call it the first time sharing systems going back to what we're talking about there were editors there was an editor on C TSS that I don't even remember what it was called al it might have been edit where you could type text program text and it would do something or other document text if it's saved then I'd save it you could edit it you know the usual thing that you would get in an editor and Ken Thompson wrote an editor called QED which was very very powerful but these were all totally a command based they were not most or cursor based because it was before mice and even before cursors because they were running on terminals that printed on paper okay no no CRT type displays let alone LEDs and so then when UNIX came along Ken took QED and stripped way way way way down and that became an editor that he called needy it was very simple but it was a line oriented editor and so you you could load a file and then you could talk about the lines one through the last line and you could you know print ranges of lines you could add text you could delete text you could change text or you could do a substitute command that would change things within a line or within groups of lines they can work on a parts of a file essentially yeah you could work on any part of it the whole thing whatever but it was entirely command line based and it was entirely on paper okay paper and that meant that you've changed yeah right real paper and so if you changed the line you had to print that line using up another line of paper to see what changed cause okay yeah so when thing when CRT displays came along yeah then you could start to use cursor control and you could sort of move where you where on the screen in without reprinting printing and one of there were a number of editors there the one that I was most familiar with and still use is VI which was done by bill joy and so that dates from probably the late 70s as a guess and it took at full advantage of the cursor controls I suspected Emacs was roughly at the same time but I don't know I've never internalized Emacs so so I use at this point I stopped using IDI always can I use VI sometimes and I use Sam when I can and Sam is available on most systems it was it is available you have to download it yourself from typically the plan line operating system distribution it's been maintained by people there and so I'll get home tonight I'll try it that's cool it's a it's a sound sounds fasting all though my love is with Lisp and Emacs have went into that hippie world of I think it's likes what religion where you brought up with yes sir that's right most of the actual programming I do is C C++ and Python but my weird sort of yeah my religious upbringing is unless so can you take on the impossible task and give a brief history of programming languages from your perspective so I guess you could say programming languages started probably in what the late 40s or something like that people used to program computers by basically putting in zeros and ones using something like switches on a console and then or maybe holes and paper tapes something like that so extremely tedious awful whatever and so I think the first programming languages were relatively crude assembly languages where people would basically write a program that would convert mnemonics like add a DD into whatever the bit pattern was it corresponding to an add instruction and they'd do the clerical work of figuring out where things were so you could put a name on a location in a program and the assembler would figure out where that corresponded to when the thing was all put together and dropped into memory and they were early on and this would be the late 40s and very early 50s there were assemblers written for the various machines that people used you may have seen in the paper just a couple days ago Tony Burkert died he did this thing in Manchester called the called auto code a language for China knew only by name but it sounds like it was a flavor of assembly language sort of a little higher in some ways um and a replaced on language that Alan Turing wrote which you put in zeros and ones but you put in an in backwards order because that was a Hardware worked very tense right yeah yeah that's right backwards so assembly languages learn let's call at the early 1950s and so every different flavor of computer has its own assembly language so the EDSAC head hits in a manchester head it and the IBM whatever 70 90 or 704 or whatever had hits and so on so everybody had their own assembly like when assembly languages have a few commands addition subtraction then branching of some kind if then that the situation right they have exactly in their simplest form at least one instruction per or one assembly language instruction per instruction in the machine's repertoire and so you have to know the Machine intimately to be able to write programs in it and if you write an assembly language program for one kind of machine and then you say jeez it's nice I'd like a different machine start over okay so very bad and so what happened in the late 50s was people realize you could play this game again and you could move up a level in writing or creating languages that were closer to the way the real people might think about how to write code and we're I guess arguably three or four at that time period there was Fortran which came from IBM which was formula translation and to make it easy to do scientific and engineering computation is not that formula translation that's what I stood for yeah I where's COBOL which is the common business oriented language that Grace Hopper and others worked on which was named business kinds of tasks there was a well which was mostly meant to describe algorithmic computations I guess you could argue basic was in there somewhere I think it's just a little later and so all of those moved the level up and so they were closer to what you and I might think of as we were trying to write a program and they were focused on different domains Fortran for formula translation engineering computations let's say COBOL for business that kind of thing still used today Fortran probably oh yeah COBOL too but the deal was that once you moved up that level then you let's call it Fortran you had a language that was not tied to a particular kind of hardware because a different compiler would compile for different kind of hardware and that meant two things it meant you only had to write the program once which is very important and it meant that you could in fact if you were a random engineer physicist whatever you could write that program yourself you didn't have to hire a programmer to do it for you might not be as good as you'd get through a programmer but it was pretty good and so it democratized and made much more broadly available the ability to write code so it puts the power of programming to the hands of people like you yeah anybody who wants to who under to invest some time in learning a programming language and is not then tied to a particular kind of computer and then in the 70s you get system programming languages of which C is the survivor and what what a system programming language learning programs that programming languages that would take on the kinds of things that would necessary to write so-called system programs things like text editors or assemblers or compilers or operating systems themselves those kinds of things and fortunately feature-rich they have to be able to do a lot of stuff a lot of memory management access processes and all that kind of stuff they a little processing it's a different flavor what they're doing they're much more in touch with the actual machine in a but in a positive way that is you can talk about memory in a more controlled way you can talk about the different data types that the Machine supports and underway there and more ways to structure and organize data and so the system programming languages there was a lot of effort in that and call it the late 60s early 70s C is I think the only real survivor of that and then what happens after that you get things like object-oriented programming languages because as you write programs in a language like C at some point scale gets to you and it's too hard to keep track of the pieces and there's no guardrails or training wheels or something like that to prevent you from doing bad things so C++ comes out of that tradition it's and then it took off from there I mean there's also a parallel slightly parallel track with a little bit of functional stuff with Lisp and so on but I guess from that point is just an explosion of languages it was a Java story there's the JavaScript there's all the stuff that the cool kids these days are doing with rust and all that they don't so what's to use you're you wrote a book C programming language what and C is probably one of the most important languages in the history of programming languages if you kind of look at impact what do you think is the most elegant or powerful part of see why did it survive what did it have such a long-lasting impact I think it found a sweet spot that in of expressiveness so you can rewrite things in a pretty natural way and efficiency which was particularly important when computers were not nearly as powerful as they are today again put yourself back 50 years almost in terms of what computers could do that's you know roughly four or five generations decades of Moore's law right so expressiveness and efficiency and I don't know perhaps the environment that it came with as well which was Unix so it meant if you wrote a program it could be used on all those computers that ran UNIX and that was all of those computers because they were all written in C in that way it was UNIX the operating system itself was portable as where all the tools so it all worked together again and one of these things work things fit on each other in a positive cycle what did it take to write sort of a definitive book probably the definitive book on all of programs like it's more definitive to a particular language than any other book on any other language and did two really powerful things which is popularized the language and at least from my perspective maybe you can correct me and second is created a standard of how you know the how this language is supposed to be used and applied so what did it take did you have those kinds of ambitions in mind when we're working on that some kind of joke no of course not of the knacks it's an accident of timing skill and just luck a lot of it is clearly I timing was good now Denison I wrote the book in 1977 I miss ritchi yeah right and at that point UNIX was starting to spread I don't know how many there were but it would be dozens to hundreds of UNIX systems um and C was also available on other kinds of computers that had nothing to do with UNIX and so the language had some potential and there were no other books on C and Bell Labs was really the only source Ford and Dennis of course was authoritative because it was his language and he had written the reference manual which is a marvelous example of how to write a reference manual really really very very well done so I twisted his arm until he agreed to write a book and then we wrote a book and the virtue our advantage at least I guess if going first is that then other people have to follow you if they're gonna do anything and I think it worked well because Dennis's superb writer I mean he really really did and that the reference manual in that book is his period I had nothing to do with that at all so just crystal-clear prose and very very well expressed um and then he and I I wrote most of the expository material and then he and I sort of did the usual ping-pong game back and forth hum refining it but I spend a lot of time trying to find examples that would sort of hang together and they would tell people what they might need to know at about the right time that they should be thinking about needing it and I'm not sure it completely succeeded but it mostly worked out fairly well what do you think is the power of example I mean you're you're the creator at least one of the first people to do the hello world program just like the example if aliens discover our civilization hundreds of years from now they'll probably hello what other programs just like a half broken robot communicating with them with the hello world so what and that's a representative example so what what do you find powerful about examples but I think a good example will tell you how to do something and it will be representative of you might not want to do exactly that but you will want to do something that's at least in that same general vein and so a lot of the examples in the C book were picked for these very very simple straightforward text processing problems that were typical of UNIX I want to read input and write it again there's a copy command I want to read input and do something to it and write it out again there's a grep and so that kind of fine things that are representative of what people want to do and spell those out so that they can then take those and see the the core parts and modify them to their taste and I think that a lot of programming books that I don't look at programming books a tremendous amount these days but when I do a lot of don't do that they don't give you examples that are both realistic and something you might want to do some of them are pure syntax here's how you add three numbers well come on I could figure that I would tell me how I would get those three numbers into the computer and how he would do something useful with them and then how I put them back out again neatly formatted and especially if you follow that example there is something magical of doing something that feels useful yeah right and I think it's the attempt and it's absolutely not perfect but the attempt in all cases was to get something that was going to be either directly useful or would be very representative of useful things that a programmer might want to do but within that vein of fundamentally text processing reading text doing something writing text so you've also written a book on go language I'd have to admit so I worked at Google for a while and I've never used go not you miss something well I know I missed something for sure I mean yeah so go and rust the two languages that I hear very spoken very highly of night which I would like to try well there's a lot of them there's Julia there's there's all these incredible modern languages but if you can comment before or maybe comments on what do you find where does go stood in this broad spectrum of languages and also how do you yourself feel about this wide range of powerful interesting languages that you may never even get to try to explore of time so I think so go um go first comes from that same Bell Labs tradition in part not exclusively but two of the three creators Ken Thompson and Rob Michael literally the people yeah the people and then with this very very useful influence from the European School in particular the club spirit influence of through Robert Griesemer it was I guess a second generation down student at ETH and so that's an interesting combination of things and so some ways go captures the good parts of see it looks sort of like see it's sometimes characterized to see for the 21st century on the surface it looks very very much like see but at the same time it has some interesting data structuring capabilities and then I think the part that I would say is particularly useful and again I'm not a go expert in spite of co-authoring the book about 90% of the work was done by Alan Donovan and my co-author who is a go expert but go provides a very nice model of concurrency it's basically the cooperating communicating sequential processes that Tony Hoare set forth I don't know 40-plus years ago and go routines are to my mind a very natural way to talk about parallel computation and in the few experiments I've done with them they're easy to write and typically it's going to work and very efficient as well so I think that's one place where it go stands out at that model of parallel computation it's very very easy and nice just to comment on that do you think c4 saw or the early unique States foresaw threads and massively parallel computation I would guess not really I mean maybe it was seen but not at the level where it was something you had to do anything about for a long time processors got faster and then processors stopped getting faster because of things like power consumption and heat generation and so what happened instead was that instead of processors getting faster there started to be more of them and that's where that parallel thread stuff comes in so if you can comment on the the other languages is it break your heart that you'll never get to explore them of course how do you feel a lot of the full variety it's not break my heart but but I would love to be able to try more of these languages the closest I've come is in class that I often teach in the spring here it's a programming class and I often give I have one sort of small example that I will write in as many languages as I possibly can I've got it in 20 on languages at this point and and that's so I do a minimal experiment with on language just to say okay I have this trivial task which I understand the task and it should it takes 15 lines in awk and not much more in a variety of other languages so how big is it how fast does it run and what pain did I go through to learn how to do it and that's a it's like an Akita right it's a very very very narrowly like that so yeah but still it's a little sample because you get to I think the hardest step of the programming language is probably the first step right so there you're taking the first step yeah and from my experience um with some languages is very positive like Lua a scripting language I'd never used and I took my Britain little program the program is a trivial formatter it just takes in lines of text of varying lengths and it puts them out in lines that have no more than 60 characters on each line so think it was just kind of the flow of process in a browser or something so it's very short program and um in Lua I downloaded Lua and in an hour I had it working never having written Lua in my life just going with online documentation I did the same thing in Scala which you can think of as a flavor of Java equally trivial I did it in Haskell it took me several weeks but it did run like a turtle and and I did it in Fortran 90 and it painful but it worked and I tried it in rust and it took me several days to get it working because the model of memory manage it was just a little unfamiliar to me and the problem I had with rust and it's back to what we were just talking about I couldn't find good consistent documentation on rust now this was several years ago and I'm sure things have stabilized but at the time everything in the rust world seemed to be changing rapidly and so you would find what looked like a working example and it wouldn't work with the version of the language that I had so it took longer than it should have rust is a language I would like to get back to but probably won't I think one of the issues you have to have something you want to do if you don't have something that is the right combination if I want to do it and yet I have enough disposable time whatever to make it worse than learning a new language at the same time it's never going to happen so what do you think about another language of JavaScript that's this well let me just sort of comment on what I said when I was brought up sort of JavaScript pasina's the probably like the ugliest language possible and yet it's quite arguably quite possibly taking over not just the fun in the back end of the internet but possibly in the future taking over everything because they've now learned to make it very efficient yeah so what do you think about this yeah well I think you've captured it in a lot of ways when it first came out javascript was deemed to be fairly irregular in an ugly language and certainly in the academy if you said you were working on javascript people would ridicule you it was just not fit for academics to work on I think a lot of that has evolved the language itself has evolved and certainly the technology of compiling it is fantastically better than it was and so in that sense it's a absolutely a viable solution upon backends as well it's the front-end used well I think it's a pretty good language I've written a modest amount of it and I've played with JavaScript translators and things like that I'm not a real expert and it's hard to keep up even there with the new things that come along with it um so I don't know whether it will ever take over the world I think not but it it's certainly an important language and worth knowing more about theirs this may be to get your comment on something which javascript and actually most languages of Python such a big part of the experience of programming with those languages includes libraries sort of using building on top of the code that other people have built I think that's probably different from the experience that we just talked about from UNIX and C days when you're building stuff from scratch what do you think about this world of essentially leveraging building up libraries on top of each other and leveraging them yeah that's a very perceptive kind of question one of the reasons programming was fun in the old days was that you were really building it all yourself the number of libraries you had to deal with was quite small maybe it was printf or the standard library or something like that and that is not the case today and if you want to do something in you mentioned Python and JavaScript and those are the two finding examples you have to typically download a boatload of other stuff and you have no idea what you're getting absolutely nothing I've been doing some playing with machine learning over the last couple of days and G something doesn't work well you pip install this okay and down comes another gazillion megabytes of something and you have no idea what it was and if you're lucky it works and if it doesn't work you have no recourse there's absolutely no way you could figure out which in these thousand different packages and I think it's worse in the MPM NPM environment for JavaScript I think there's less discipline less control there and there's aspects of not just not understanding how it works but there's security issues is there Busta's issues so you don't want to run a nuclear power plant using JavaScript essentially oh probably not so it's speaking to the variety of languages do you think that variety is good or do you hope think that over time we should converge towards one two three programming languages that's you mentioned to the bailout days when people could sort of the community of it and the more languages you have the more you separate the communities is the Ruby there's the Python community there's C++ community do you hope that there they'll unite one day - just one or two languages I certainly don't hope it I'd not sure that that's right because I honestly don't think there is one language that will suffice for all the programming needs of the world are there too many at this point well arguably um but I think if you look at the sort of the distribution of how they are used there's something called a dozen languages that probably count for 95% of all programming at this point and that doesn't seem unreasonable and then there's another well 2000 languages that are still in use that nobody uses and or at least don't use in any quantity but I think new languages are a good idea in many respects because they're often a chance to explore an idea of how a language might help I think that's one of the positive things about functional languages for example they're a particularly good place where people have explored ideas that at the time didn't seem feasible but ultimately have wound up as part of mainstream languages as well let me just go back as early as recursion Lisp and then follow forward with functions as first-class citizens and pattern based languages and gee I don't know closures and just on and on and on lambdas interesting ideas that showed up first in let's call it broadly the functional programming community and then find their way into mainstream languages yes it's a playground for rebels yeah exactly and and so I think the language is in the playground themselves are probably not going to be the mainstream at least for some welp but the ideas that come from there are invaluable so let's go to something that when I found out recently so I known that you've done a million things but one of the things I wasn't aware of the you had a role in ample and I before you interrupt me by minimizing your role in it but your hapless for minimizing functions yeah minimizing functions right exactly I can't just say that the elegance and abstraction power of an ample is incredible all right when I first came to it about ten years ago or so can you describe what is the ample language sure so ample is a language for mathematical programming technical term think of it as linear programming that is setting up systems of linear equations that are some sort of system of constraints so that you have a bunch of things that have to be less than this greater than that or whatever and you're trying to find a set of values for some decision variables that will maximize or minimize some objective function so it's it's a way of solving a particular kind of optimization problem a very formal sort of optimization problem but one that's exceptionally useful and it specifies so there's objective function of constraints and variables that become separate from the data it operates on right so the that kind of separation allows you to you know put on different hats won't put the Hat of an optimization person and then put a another hat of a data person and dance back and forth and and also separate the actual solvers the optimization systems that do the solving then you can have other people come to the table and then build their solvers whether it's linear or nonlinear convex non convex that kind of stuff so what is the do use may be in common how you got into that world and what is a beautiful or interesting idea to you from the world of optimization sure so I preface it by saying I'm absolutely not an expert on this and most of the important work in and comes from my two partners in crime on that Bob Fuhrer who was a professor of and in the industrial engineering and management science department at Northwestern and my colleague at Bell Labs Dave Gay who is a numerical analysts an optimization person so the deal is linear programming preface this by saying linear program is the simplest example of this so linear program is taught in school is that you have a big matrix which is always called a and you say ax is less than or equal to B so B is a set of constraints X is the decision variables and a as to how the decision variables are combined to set up the various constraints so a as a matrix and X and B your vectors and then there's an objective function which is just the sum of a bunch of X's and some coefficients on them and yet that's the thing you want to optimize the problem is that in the real world that matrix a is a very very very intricate very large and very sparse matrix where the various components of the model are distributed among the coefficients in a way that is totally on obvious to anybody and so what you need is some way to express the original model which you and I would write you know we'd write mathematics on the board and the sum of this is greater than the sum of that kind of thing so you need a language to write those kinds of constraints and Bob for a long time had been interested in modeling languages languages that made it possible to do this there was a modeling language around called gams the general algebraic modeling system but it looked very much like Fortran was kind of clunky um and so Bob spent a sabbatical year at Bell Labs in 1984 and he and wasn't in the office across from me and it's always geography and he and Dave Gay and I started talking about this kind of thing and he wanted to design a language that would make it so that you could take these algebraic specifications you know summation signs over sets and that you would write on the board and convert them into basically this a matrix and then pass that off to a solver which is an entirely separate thing and so we talked about the design if the language I don't remember any of the details of this now but it's kind of an obvious thing you're just writing mathematical expressions in a Fortran like sorry in algebra but textual like language and I wrote the first version of this ample program my first C++ program and that's written in C++ yep and so I did that fairly quickly we wrote it was you know 3,000 lines or something so it wasn't very big but it just sort of showed the feasibility of it that you could actually do something that was easy for people to specify models and convert it into something that a solver could work with at the same time as you say that model and the data are separate thing so one model would then work with all kinds of different data in the same way lots of programs do the same thing but with different data so one of the really nice things is the the specification of the models human just kind of like as you say is human readable like I literally I'm ever on stuff I work I I would send it to colleagues that I'm pretty sure never programmed just just to understand what the optimization problem is I think how hard is it to convert that you said you there's a first prototype in C++ to convert that into something that could actually be used by the solver it's not too bad because most of the solvers have some mechanism that lets them import a model in AI form it might be as simple as the matrix itself in just some representation or if you're doing things that are not linear programming and there may be some mechanism that you provide things like functions to be called or other constraints on the model so so all ample does is to generate that kind of thing and then solver deals with all the hard work and then when the solver comes back with numbers and Vil converts those back into your original form so you know how much of each thing you should be buying or making or shipping or what so we did that in 84 and I haven't had a lot to do with it since except that we wrote a couple of versions of a book on which is one of the greatest books ever written I love that book I don't know why it's an excellent book but for wrote most of it and so it's really really well done he must be a dynamite teacher and typeset in late Dec no no no are you kidding I really like in the typography so I don't know we did it with tear off I don't even know what that is yeah exactly you could go I think of tear off is as a predecessor to the tech family of things it's a formatter that was done at Bell Labs in this same period of the very early 70s oh that predates tech and things like that plate mmm 5 to 10 years it was nevertheless they just I'm going by memories it was I remember it being beautiful yeah it was nice outside of UNIX Iago laying all the things we talked about all the amazing work you've done you've also done working graph theory let me ask this this crazy out there question if you had to make a bet and I had to force you to make a bet do you think P equals NP the answer is no although I've told that somebody asked Jeff Dean if that was the what conditions B would equal NP and he said either P is 0 or n is 1 or vice versa I've forgotten so but your intuition is I haven't no I have no intuition but I've got a lot of colleagues who've got intuition and their betting is no that's the popular that's the popular bet okay so what is computational complexity theory and do you think these kinds of complexity classes especially as you've taught in this modern world there are still a useful way to understand the hardness of problems I don't do that stuff the last time I touched anything to do with that was before it was invented because I it's literally true I did my PhD thesis on good for big on on tape you know absolutely before I I did this in 1968 and I worked on graph partitioning which is this question you've got a graph that is a nodes and edges kind of graph and the edges have weights and you just want to divide the nodes into two piles of equal size so that the number of edges that goes from one side to the other is as small as possible and we he developed so that problem is hard well as it turns out I work with Shen Lin at Bell Labs on this and we were never able to come up with anything that was guaranteed to give the right answer we came up with heuristics that worked pretty darn well and I peeled off some special cases for my thesis but it was just hard and that was just about the time that Steve Cooke was showing that there were classes of problems that appeared to be really hard of witchcraft partitioning was one but this my expertise such as it was totally predates that development Oh interesting so the the heuristic which now you're who cares the two of years names for the Traveling Salesman problem at for the graph partitioning that was like how did you you weren't even thinking in terms of classes you're just trying to was no such idea a heuristic that kind of does the job pretty well you were trying to find a something that did the job and there was no nothing that you would call let's say a closed-form or algorithmic thing that would give you a guaranteed right answer I mean compare graph partitioning to max-flow min-cut or something like that that's the same problem except there's no constraint on the number of nodes on one side or the other of the cut and that means it's an easy problem at least as I understand it whereas the constraint that says the two have to be constrained in size makes it a hard problem yes so the Robert Frost has that poem where you choose two paths so what why did you is there another alternate universe in which you pursued the Don Knuth path of you know algorithm designs and of not smart enough that's smart enough for you're infinitely modest but so you proceed you're kind of love of programming I mean when you look back to those I mean just looking into that world does that just seem like a distant world of theoretical computer science then is it fundamentally different from the world of programming I don't know I mean certainly in all series and as I just didn't have the talent for it I when I got here is a grad student to Princeton and I started to think about research at the end of my first year or something like that I work briefly with John Hopkins absolutely you know he mentioned during award-winner it said her a great guy and it became crystal clear I was not cut out for this stuff period okay and so I moved into things where I was more cut out for it and that tended to be things like writing programs and ultimately writing books you've said that in Toronto as an undergrad you did a senior thesis or literature survey on artificial intelligence this was 1964 correct what was the AI landscape ideas dreams at that time I think that was one of the well you've heard of AI winters this is whatever the opposite was AI summer or something there's one of these things where people thought that boy we could do anything with computers that all these hard problems we could computers will solve them they will do machine translation they will play games like chess that they will do mission you know prove theorems in geometry there are all kinds of examples like that where people thought boy we could really do those sorts of things um and you know I I read the kool-aid in some times it's a wonderful collection of papers called computers and thought that was published and about that era and people were very optimistic and then of course it turned out that what people thought was just a few years down the pike was more than a few years down the pike and some parts of that are more or less now sort of under control I we finally do play games like go and chess and so on better than then people do but there are others on machine translation is a lot better than it you to be but that's 50 close to 60 years of progress and a lot of evolution in hardware and a tremendous amount more data upon which you can build systems that actually can learn from some of that and and the the infrastructure to support developers working together like an open source moving the internet period is also an empowering but what lesson do you draw from that the opposite of winter that optimism well I guess the lesson is that in the short run it's pretty easy to be too pessimistic or maybe too optimistic and in the long run you probably shouldn't be too pessimist I'm not saying that very well it reminds me of this remark from Arthur Clarke science fiction author who says you know when some distinguished but elderly person says that something is him is possible he's probably right and if he says it's impossible he's almost surely wrong but you don't know what the time scale is at time scale is good all right so what are your thoughts on this new summer of AI now in the work with machine learning in your networks you've kind of mentioned he started to try to explore and look into this world that seems fundamentally different from the world of heuristics and algorithms like search that it's now purely sort of trying to take huge amounts of data and learn learn from that data right programs from the data no look I think it's it's very interesting I am incredibly far from an expert most of what I know I've learned from my students and they're probably disappointed in how little I've learned from them but um I think it has tremendous potential for certain kinds of things in games is one where it obviously has had an effect on some of the others as well I think there's and this is speaking from definitely not expertise I think there are serious problems in certain kinds of machine learning learning at least because what they're learning from is the data that we give them and if the data we give them has something wrong with it then what they learn from it is probably wrong too and the obvious thing is some kind of bias in the that the data has stuff in it like I don't know women earned as good at men as men at something okay that's just flat wrong but if it's in the data because of historical treatment then that machine learning stuff will propagate that and that is a serious worry the the positive part of that is what machine learning does is reveal the bias in the data and puts a mirror to our own society and in so doing helps us remove the bite you know helps us work on ourselves it's a mirror to ourselves yeah that's an optimistic point of view and if it works that way that would be absolutely great and and what I don't know is whether it does work that way or whether the the you know the AI mechanisms or machine learning mechanisms reinforce and amplify things that have been wrong in the past and I don't know I but I think that's a serious thing that we have to be concerned about let me ask you another question okay I know nobody knows but what do you think it takes to build a system of human level intelligence that's been the dream from the 60s we talk about games about language about about image recognition but really the dream is to create human level or superhuman level intelligence what do you think it takes to do that and are we close I haven't a clue and I don't know trying to trick you into a hypothesis I mean Turing talked about this in his paper on machine intelligence back and she's in early 50s or something like that and he had the idea of the Turing test and I don't know what the Turing test is I don't know it's an interesting test at least it's in some vague sense objective whether you can read anything into the conclusions is a different story do you have worries concerns excitement about the future of artificial intelligence so there's a lot of people for worried and you can speak broadly than just artificial intelligence is basically computing taking over the world in various forms are you excited by this future this possibility of computing being everywhere or are you worried it's some combination of those I I think almost all technologies over the long run are for good but there's plenty of examples where they haven't been good either over a long run for some people or over a short run um and computing is one of those and AI within it is gonna be one of those as well but computing broadly I mean for just a today example is privacy that um the use of things like social media and so on means that in the commercial surveillance means that there's an enormous amount more known about us by people other you know businesses government whatever then perhaps one ought to feel comfortable with so that's an example that's an example pause a possible negative negative effect of competing being everywhere it's a it's an interesting one because it could also be a positive leverage correctly there's a big if there so I I you know I've I have a deep interest in human psychology and humans are seem to be very paranoid about this data thing at a but that varies depending on age group yes it seems like the younger folks so it's exciting to me to see what society looks like fifty years from now that the concerns of our privacy might be flipped on their head based purely on human psychology versus actual concerns or not yeah what do you think about Moore's law well you said a lot of stuff we've talked you talked about what programming languages in their design and their ideas are come from the constraints and the systems they operate and do you think Moore's Law the the exponential improvement of systems will continue indefinitely there's there's mix of opinions on that currently or do you think do you think there will be do you think there'll be a plateau well the furball is answer there's no exponential can go on forever you run out of something um just as we said timescale matters so if it goes on long enough that might be all I need yeah right won't matter does uh so I don't know we've seen places where Moore's law has changed for example mentioned earlier process processors don't get faster anymore but you used that same growth of you know building put more things in a given area to grow them horizontally instead of vertically as it were so you can get more and more processors or memory or whatever on the same chip is that gonna run into a limitation presumably because you know at some point you get down to the individual atoms and so you got to find some way around that will we find some way around that I don't know I just said that if I say it I'll be wrong we will say I just talked to Jim Keller and he says so he actually describes he argues that the Moore's law will continue for a long long time because you mentioned the atom we actually have I think a thousandfold increase to a decrease in threaten transistor size still possible before we get to the quantum level so it's there's still a lot of possibilities he thinks he'll continue indefinitely which is an interesting optimistic optimistic viewpoint but how do you think the programming languages will change for this increase whether we hit a wall or not what do you think do you think there'll be a fundamental change in the way programming languages are designed I don't worry about that I think what will happen is continuation of what we see in some areas at least which is that more programming will be done by programs than by people and that more will be done by sort of declarative rather than procedural mechanisms where I say I want this to happen you figure out how and that is in many cases at this point domain of specialized languages for narrow domains but you can imagine that broadening out and so I don't have to say so much in so much detail some collection of software let's call it language or programs or something we'll figure out how to do what I want to do some increased levels of abstraction yeah and one day getting to the human level maybe just use so you taught so teach of course computers in our world here at Princeton that introduces computing and programming to non majors what just from that experience what advice do you have for people who don't know anything about programming but I'm kind of curious about this world or programming seems to become more and more of a fundamental skill that people need to be at least the world yeah well I could recommend a good book what's that for the course I think this is one of these questions of should everybody know how to program and I think the answer is probably not but I think everybody should at least understand sort of what it is so that if you say to somebody I'm a programmer they have a notion of what that might be or if you say this is a program or this was decided by a computer running a program that they have some vague intuitive understanding and an accurate understanding of what that might imply so part of what I'm doing in this course which is very definitely for non-technical people I mean typical person in it is a history or English major try and explain how computers work how they do their thing what programming is how you write a program and how computers talk to each other and what do they do when they're talking to each other and then I would say nobody very rarely and does anybody in that course go on to become a real serious programmer but at least they've got a somewhat better idea of what all this stuff is about not just the programming but the technology behind computers and communications do they write up do they try and write a program themselves oh yeah yeah a very small amount I introduced them to how machines work at a level below high-level languages so we have a kind of a toy machine and has a very small repertoire dozen instructions and they write trivial assembly language program Wow that's okay just if you were to give a flavor to people of the programming world for the competing world what what are the examples it should go with so a little bit of assembly to get a sense at the lowest level of what the program is really doing yeah there's I mean in some sense there's no such thing as the lowest level because you can keep going down but that's the place where I drew the line so the idea that computers have a fairly small repertoire of very simple instructions that they can do like add and subtract and and branch and so on as you mentioned earlier and that you can write code at that level and it will get things done and then you have the levels of abstraction that we get with higher-level languages like Fortran or C or whatever and that makes it easier to write the code and less dependent on particular architectures and then we talk about a lot of the different kinds of programs that they use all the time that they don't probably realize our programs like they're running Mac OS on their computers or maybe Windows and they're downloading apps on their phones and all of those things are programs that are just what we just talked about except at a grand scale it's easy to forget that they're actual programs that people program there's engineers they wrote wrote those things yeah right and so in a way I'm expecting them to make an enormous conceptual leap from their 5 or 10 line toy assembly language thing that adds two or three numbers to you know something that is a browser on their phone or whatever but but it's really the same thing if you look at the broad and broad strokes at history what do you think the world like how do you think the world change because of computers it's hard to sometimes see the big picture when you're in it you know but I guess I'm asking if there's something you've noticed over the years that like you were mentioned the students are more distracted looking at their now there's a device to look at right well I think computing has changed its rendus amount and obviously but I think one aspect of that is the way that people interact with each other both locally and faraway and when I was you know the age of those kids making a phone call to somewhere was a big deal because it cost serious money and this was in the 60s right and today people don't make phone calls they send texts or something like that so it there's a up and down and what people do people think nothing of having correspondence regular meetings video whatever with friends or family or whatever in any other part of the world and they don't think about that at all they and so that's just the communication aspect of it and do you think that brings us closer together or does it make us do this does it take us away from the closeness of human human contact I think it depends a lot on all kinds of things so I trade mail with my brother and sister in Canada much more often than I used to talk to them on the phone so probably every 2 or 3 days I get something or send something to them whereas 20 years ago I probably wouldn't have talked to them on the phone nearly as much so in that sense I that's brought my brother and sister and I closer together that's a good thing um I watch the kids on campus and they're mostly walking around with their heads down fooling with their phones to the point where I have to duck them yeah I don't know that that has brought them closer together in some ways there's sociological research that says people are in fact not as close together as they used to be I don't know whether that's really true but but I can see potential downsides and kids where you think come on wake up and smell the coffee or whatever that's right but if you look at again nobody can predict the future but are you excited kind of touch this a little bit with with AI but are you excited by the future in the next 10 20 years the computing will bring you viewer there when there was no computers really and now computers are everywhere all over the world and Africa and Asia and just every every person almost every person the wall has a device so are you hopeful optimistic about that future I it's mixed if the truth be told I mean I think there are some things about that that are good I think there's the potential for people to improve their lives all over the place and that's obviously good and at the same time at least in the short time short-run you can see lots and lots of bad as people become more tribalistic or parochial in their interests and it's an enormous amount more us and them and people are using computers in all kinds of ways to mislead or misrepresented or flat-out lie about what's going on and that is affecting politics locally and I think everywhere in the world yeah the the long-term effect on political systems and so on it's who knows knows indeed the the the people now have a voice which is a powerful thing people who are press have a voice but also everybody has a voice and the chaos that emerges from that is fascinating to watch yeah yeah it's kind of scary if you can go back and relive a moment in your life one that made you truly happy outside of family or was profoundly transformative is there a moment or moments that jump out at you from memory I don't think specific moments I think there were lots and lots and lots of good times at Bell Labs where you would build something and it it worked hi Jase a work so the moments at war who stood yeah and and somebody used it from they said gee that's neat those kinds of things happened quite often in that sort of golden era and that the 70s when UNIX was young and there was all this low-hanging fruit and interesting things to work on a group of people who kind of we were all together in this and if you did something they would try it out for you and I think that was in some sense a really really good time and Ock was a was an example of that then you drilled it and people use that yeah absolutely and now millions of people use any and all your stupid mistakes right there for them to look at so it's mixed yeah it's terrifying vulnerable buds beautiful because it does have a positive impact on so so many people so I think there's no better way to end it Brian thank you so much for talking it was an honor okay likes it my pleasure good fun thank you for listening to this conversation with Brian Kernighan and thank you to our sponsors 8:00 sleep mattress and rake on earbuds please consider supporting this podcast by going to a sleep calm slash Lex and to buy rake on comm slash Lex click the links buy the stuff these both are amazing products it really is the best way to support this podcast and the journey I'm on it's how they know I sent you and increases the chance that they'll actually support this podcast in the future if you enjoy this thing subscribe on youtube review it with fire stars an apple podcast supported on patreon or connect with me on Twitter at Lex Freedman spelled somehow miraculously without the letter e just Fri D ma n because when we immigrated to this country we were not so good at spelling and now let me leave you with some words from Brian Kernighan don't comment bad code rewrite it you for listening and hope to see you next time you |
Sergey Levine: Robotics and Machine Learning | Lex Fridman Podcast #108 | the following is a conversation with Sergey Levine a professor at Berkeley and a world-class researcher in deep learning reinforcement learning robotics and computer vision including the development of algorithms for end-to-end training of neural network policies that combine perception and control scalable algorithms for inverse reinforcement learning and in general deep r.l algorithms quick summary of the ads to sponsors cash app and expressvpn please consider supporting the podcast by downloading cash app and using collects pot cast and signing up at expressvpn comm / flex pod click the links buy the stuff it's the best way to support this podcast and in general the journey I'm on if you enjoy this thing subscribe on YouTube review it with five stars an apple podcast follow on Spotify supported on patreon or connect with me on Twitter at lex friedman as usual i'll do a few minutes of as now and never any ads in the middle that can break the flow of the conversation this show is presented by cash app the number one finance app in the App Store when you get it used colex podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is an algorithmic marvel so big props the cash app engineers are taking a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash out from the App Store Google Play and use the code lex podcast you get $10 and cash up will also donate $10 the first an organization that is helping to advanced robotics and stem education for young people around the world this show is also sponsored by expressvpn get it at expressvpn comm / Lex pod to support this podcast and to get an extra three months free on a one-year package I've been using expressvpn for many years I love it I think expressvpn is the best VPN out there they told me to say it but it happens to be true my humble opinion it doesn't lock your data it's crazy fast and as easy to use literally just one big power on button again it's probably obvious to you but I should say it again it's really important that they don't log your data it works on Linux and every other operating system but Linux of course is the best operating system shout out to my favorite flavor Ubuntu mottai 2004 once again get it at expressvpn calm / relax pod to support this podcast and to get an extra three months free on a one-year package and now here's my conversation sergey Lavigne what's the difference between a state-of-the-art human such as you and I well I don't know if we qualify Stata they're humans but a state-of-the-art human and a state-of-the-art robot it's a very interesting question robot capability is it's kind of a I think it's a very tricky thing to to understand because there are some things that are difficult that we wouldn't think are difficult and some things that are easy that we wouldn't think ever you see and there's also a really big gap between capabilities of robots in terms of hardware and their physical capability and capabilities of robots in terms of what they can do autonomously there is a little video that I think robotics researchers really like to show a special Robotics learning researchers like myself from 2004 from Stanford which demonstrates a prototype robot called the PR one and the PR one was a robot that was designed as a home assistance robot and there's this beautiful video showing the pr1 tidying up a living room putting away toys and at the end bringing a beer to the person sitting on the couch which looks really amazing and then the punch line is that this is entirely controlled by person yes so you can so that in some ways the gap between a state-of-the-art human state-of-the-art robot if the robot has a human brain is actually not that large now obviously like human bodies are sophisticated and very robust and resilient in many ways but on the whole if we're willing to like spend a bit of money and do a bit of engineering we can kind of close the hardware gap almost but the intelligence gap that one is very wide and when you say hardware you you're referring to the physical sort of the actuators the actual body the robot is opposed to the hardware on which the cognition the nervous the hardware of the nervous system yes exactly I'm referring to the body rather than the mind so what so that means that the kind of the work is cut out for us like while we can still make the body better we kind of know that the big bottleneck right now is really the mind and how big is that gap how big is the how big is the difference in your in your sense of ability to learn a bit ability to reason ability to perceive the world between humans and our best robots the gap is very large and the gap becomes larger the more unexpected events can happen in the world so essentially the spectrum along which you can measure the the size of that gap is the spectrum of how open the world is if you control everything in the world very tightly if you put the robot in like a factory and you tell it where everything is and you rigidly program its motion then it can do things you know one might even say in a superhuman way it can move faster it's stronger it can lift up a car and things like that but as soon as anything starts to vary in the environment now it'll trip up and if many many things vary like they would like in your kitchen for example then things are pretty much like wide open now again we're gonna stick a bit on the philosophical questions but how much on the human side of the cognitive abilities in your sense is nature versus nurture so so how much of it is product of evolution and how much of it something we'll learn from sort of scratch yeah well from the day were born I'm going to read into your question as asking about the implications of this for AI really by biologists I can't really like speak authoritative also until in garnet if if it's so if it's all about learning then there's more hope for am so the way that I look at this is that you know well first of course biology is very messy and it's if you ask the question how does a person do something or has a person's mind do something you come up with a bunch of hypotheses and oftentimes you can find support for many different often conflicting hypotheses one way that we can approach the question of what the implication of this for AI R is we can think about what's sufficient so you know maybe a person is from birth very very good at some things like for example recognizing faces there's a very strong evolutionary pressure to do that if you can recognize your mother's face then you're more likely to survive and therefore people are good at this but we can also ask like what's what's the minimum sufficient thing right and one of the ways that we can study the minimal sufficient thing is we could for example see what people do in unusual situations if you present them of things that evolution couldn't have prepared them for you know our daily lives actually do this to us all the time we we didn't evolve to deal with you know automobiles and spaceflight and whatever so they're all these situations that we can find ourselves in and we do very well they're like I can give you a joystick to control a robotic arm which you've never used before and you might be pretty bad for the first couple of seconds but if I tell you like your life depends on using this robotic arm to like open this door you'll probably manage it even though you've never seen this device before you even even ever used the joys to control us and you'll kind of muddle through it and that's not your evolved natural ability that's your fear flexibility your your adaptability and that's exactly why our current robotic systems really kind of fall flat but I wonder how much general almost what we think of as common sense pre-trained models underneath all that so that ability to adapt to a joystick is requires you to have a kind of you know I'm human so it's hard for me to introspect all the knowledge I have about the world but it seems like there might be an iceberg underneath of the amount of knowledge you actually bring to the table now that's kind of the open question there's absolutely an iceberg of knowledge that we bring to the table but I think it's very likely that iceberg of knowledge is actually built up over our lifetimes because we have you know we have a lot of prior experience to draw on and it kind of makes sense that the right way for us to you know to optimize our efficiency our evolutionary fitness and so on is to utilize all that experience to build up the best iceberg we can get and that's actually one you know well that sounds an awful lot like what machine learning actually does I think that for modern machine learning it's actually a really big challenge to take this unstructured massive experience and distill out something that looks like a common sense understanding of the world and perhaps part of that isn't it's not because something about machine learning itself is is broken or hard but because we've been a little too rigid in subscribing to a very supervised very rigid notion of learning you know kind of the input-output excess goes go to why sort of model and maybe what we really need to to do is to view the world more as like a massive experience that is not necessarily providing any rigid supervision but sort of providing many many instances of things that could be and then you take that and you distill it into some sort of common sense understanding I see what you're you're painting an optimistic beautiful picture especially from the robotics perspective because that means we just need to invest in both better learning algorithms figure out how we can get access to more and more data for those learning L goes to extract signal from and then accumulate that iceberg of knowledge it's a beautiful picture it's a hopeful one I think it's potentially a little bit more than just that and this is this is where we perhaps reach the limits of our current understanding but one thing that I think that the research community hasn't really resolved in a satisfactory way is how much it matters where that experience comes from like you know do just like download everything on the intranet and cram it into essentially the 21st century analog of the giant language model and then see what happens or does it actually matter whether your machine experiences the world or in a sense that actually attempts things observes the outcome of its actions and kind of augments the experience that way that it chooses which parts of the world it gets to interact with and observe and learn from right it may be that the world is so complex that simply obtaining a large mass of sort of iid samples of the world is is a very difficult way to go but if you are actually interacting with the world and essentially performing this sort of hard- mining by attempting what you think might work observing the sometimes happy and sometimes sad outcomes of that and augmenting your understanding using that experience and you're just doing this continually for many years maybe that sort of data in some sense is actually much more favourable to obtaining a common sense understanding well one reason we might think that this is true is that you know the what we associate with common sense or lack of common sense is often characterized by the ability to reason about kind of counterfactual questions like you know I if I were to you know here I'm this bottle of water sitting on the table everything is fine far knock it over which I'm not going to do but if I were to do that what would happen and I know that nothing good would happen from that but if I have a bad understanding of the world I might think that that's a good way for me to like you know gain more utility if I actually go about the daily life doing the things that my current understanding of the world suggests will give me high utility in some ways I'll get exactly the the right supervision to tell me not to do those those bad things and to keep doing the good things so there's a spectrum between iid random walk through the space of data and then there's and what we humans do or I don't even know if we do it through optimal but there might be beyond what so this open question that you raised where do you think systems intelligent systems that would be able to deal with this world fall can we do pretty well by reading all of Wikipedia sort of randomly sampling it like language models do or do we have to be exceptionally selective and intelligent about which aspects of the wall we eat chocolate so I think this is first an open scientific problem and I don't have like a clear answer but I can speculate a little bit and what I would speculate is that you don't need to be super super careful I think it's less about like being careful to avoid the useless stuff and more about making sure that you hit on the really important stuff so perhaps it's okay if you spend part of your day just you know guided by your curiosity visiting interesting regions of the of your state space but it's important for you to you know every once in a while make sure that you really try out the solutions that your current model of the world suggests might be effective and observe whether those solutions are working as you expect or not and perhaps some of that is really essential to have kind of a perpetual improvement loop like this perpetual improvement loop is really like but that's really the key the key that's going to potentially distinguish the best current methods from the best methods of tomorrow in a sense how important do you think is exploration or total out-of-the-box thinking exploration in this space is you jump to totally different domain so you kind of mentioned there's an optimization problem you kind of kind of explore the specifics of a particular strategy whatever the thing you're trying to solve how important is it to explore totally outside of the strategies they've been working for you so far what's your intuition there yeah I think it's a very problem dependent kind of question and I think that that's actually you know in some ways that question gets at one of the big differences between sort of the classic formulation of a reinforcement learning problem and some of the sort of more open-ended reformulations of that problem that have been explored in recent years so classically reinforcement learning is framed as a problem of maximizing utility like any kind of rational AI agent and then anything you do is in service to maximizing that utility but a very interesting kind of way to look at I'm not necessary saying that's the best way to look at it but an interesting alternative way to look at these problems as as something where you first get to explore the world however you please and then afterwards you will be tasked with doing something and that might suggest to somewhat different solutions so if you don't know what you're going to be tasked with doing and you just want to prepare yourself optimally for whatever you're uncertain future holds maybe then you will choose to attain some sort of coverage build up sort of an arsenal of cognitive tools if you will such that later on when someone tells you now your job is to fetch the coffee for me you'll be well prepared to undertake that task and that you see that as the modern formulation of the reinforcement learning problem as the kind of the more multi task the general intelligence kind of formulation I think that's one possible vision of where things might be headed I don't think that's by any means the mainstream or standard way of doing things and it's not like if I had to but I like it it's a beautiful vision so maybe you actually take a step back what is the goal of robotics what's the general problem of robotics of trying to solve you actually kind of painted two pictures here one of the narrow one is the general what in your view is the big problem of robotics again ridiculously philosophical questions I think that you know maybe there are two ways I can answer this question one is there's a very pragmatic problem which was like what would make robots what would sort of maximize the usefulness of robots and there the answer might be something like a system where a system that can perform whatever task a human user sets for it you know within the physical constraints of course if you tell it to teleport to another planet but probably can't do that but if you if you ask it to do something that's within its physical capability then potentially with a little bit of additional training or a little bit of additional trial and error it ought to be able to figure it out in much the same way as like a human tele operator ought to figure out how to drive the robot to do that that's kind of a very pragmatic view of what it would take to kind of solve the the robotics problem if you will but I think that there is a second answer and that answer that the answer is a lot closer to why I want to work on on robotics which is that I think it's it's less about what it would take to do a really good job in the world of robotics but more the other way around what robotics can bring to the table to help us understand artificial intelligence so your dream fundamentally is to understand intelligence yes I think that's the dream for many people who actually work in this space I think that there is there's something very pragmatic and very useful about studying robotics but I do think that a lot of people that go into this field actually you know the things that they draw inspiration from are the potential for robots to like help us learn about intelligence and about ourselves that's that's fascinating that robotics is basically the space by which you can get closer to understanding the fundamentals of artificial intelligence so what is it about robotics that's different from some of the other approaches so if we look at some of the early breakthroughs in deep learning or in the computer vision space and the natural language processing there was really nice clean benchmarks that a lot of people competed on and thereby came out with a lot of building ideas what's the fundamental difference to you between computer vision purely define an image net and kind of the bigger robotics problem so there are a couple of things one is that with robotics you kind of have you kinda have to take away many of the crutches so you have to deal with with both the the the particular problems of perception control and so on but you also have to deal with the integration of those things and you know classically we've always thought of the integration as kind of a separate problem so a class a kind of modular engineering approaches that we solve individual subproblems then wire them together and then the whole thing works and one of the things that we've been seeing over the last couple of decades is that well maybe studying the thing as a whole might lead to just like very different solutions now if we were to study the parts and wire them together so the integrative nature of robotics research helps us see you know the different perspectives on the problem another part of the answer is that with robotics it it casts a certain paradox into very clever relief so this is sometimes referred to as more of expert on the idea that in artificial intelligence things that are very hard for people can be very easy for machines and vice versa things that are very easy for people can be very hard for machines so you know integral and differential calculus is pretty difficult to learn for people but if you program a computer do it it can derive derivatives and integrals for you all day long without any trouble whereas some things like you know drinking from a cup of water very easy for a person to do very hard for a robot to deal with and sometimes when we see such blatant discrepancies that give us a really strong hint that we're missing something important so if we really try to zero in on those discrepancies we might find that little bit that we're missing and it's not that we need to make machines better or worse at math and better at drinking water but just that by studying those discrepancies you might find some new insight so that that could be that could be in any space it doesn't have to be robotics but you're saying yeah I get it's kind of interesting that robotics seems to have a lot of those discrepancies so the the the Hans more of a paradox is probably referring to the space of the the physical interaction I think you said object manipulation walking all the kind of stuff we do in the physical world that well how do you make sense if you were to try to disentangle the the Marwick paradox like why is there such a gap in our intuition about it why do you think manipulating objects is so hard from everything you've learned from applying reinforcement learning in this space yeah I think that one reason is maybe that for many of the problems for many of the other problems that we've studied in AI and computer science and so on the notion of input/output and supervision is much much cleaner so computer vision for example deals with very complex inputs but it's comparatively a bit easier at least up to some level of abstraction to cast it as a very tightly supervised problem it's comparatively much much harder to cast robotic manipulation as a very tightly supervised problem you can do it it just doesn't work all that well so you could say that well maybe we get a label data set where we know exactly which motor commands to send and then we train on that but for various reasons that's not actually like such a great solution and it also doesn't seem to be even remotely similar to how people and animals learn to do things because we're not told by like our parents here is how you fire your muscles in order to walk we you know we do get some guidance but the really low-level detailed stuff we figure out most of them our own and that's what you mean by tightly coupled that every single little sub action gets a supervised signal of whether it's a good one or not right so so while in computer vision you could sort of imagine up to a level of abstraction that maybe you know somebody told you this is a car and this is a cat and this is a dog in motor control it's very clear that that was not the case if we look I said of the sub spaces of Robotics that again as you said robotics integrates all of them together and we'll get to see how this beautiful mess into place but so there's nevertheless still perception so it's the the computer vision problem broadly speaking understanding the environment then there's also maybe you can correct me on this kind of categorization of the space then there's prediction in trying to anticipate what things are going to do into the future in order for you to be able to act in that world and then there's also this game theoretic aspect of how your actions will change the behavior of others in this kind of space what and this is bigger than reinforcement learning this is just broadly looking at the problem of Robotics what's the hardest problem here or is there or is what you said true that when you start to look at all of them together that's an int that's a whole nother thing like you can't even say which one individually is harder because all of them together you should only be looking at them all together I think when you look at them all together some things actually become easier and I think that's actually pretty important so we had you know back in 2014 we had some work basically our first work on end to end enforced learning for robotic manipulation skills from vision which you know at the time was something that seemed a little inflammatory and controversial in the robotics world but other than the the inflammatory and controversial part of it the point that we were actually trying to make in that work is that for the particular case of combining perception and control you could actually do better if you treat them together then if you try to separate them and the way that we try to demonstrate this as we picked a fairly simple motor control task where a robot had to insert a little red trapezoid into a trapezoidal hole and we had our separated solution which involved first detecting the hole using a pose detector and then actuated arm to put it in and then our intent solution which just mapped pixels to the torques and one of the things we observed is that if you use the intense solution essentially the pressure on the perception part of the model is actually lower like it doesn't have to figure out exactly where the thing is in 3d space it just needs to figure out where it is you know distributing the errors in such a way that the horizontal difference matters more than the vertical difference because vertically just pushes it down all the way until it can't go any further and their perceptual errors are a lot less harmful whereas a perpendicular to the direction of motion perceptual errors are much more harmful so the point is that if you combine these two things you can trade off errors between the components optimally to best accomplish the task and the components can should be weaker while still leading to better overall performance as a profound idea I mean in in the space of pegs and things like that is quite simple it almost is tempting to overlook but that's seems to be at least intuitively an idea that should generalize to basically all aspects of perception control of course when one strengthens the other yeah and and we you know people who have studied sort of perceptual heuristics in humans and animals find things like that all the time so one one very well-known example this is something called the gaze heuristic which is a little trick that you can use to intercept a flying object so if you want to catch a ball for instance you could try to localize it in 3d space estimate its velocity estimate the effect of wind resistance solve a complex system of differential equations in your head or you can maintain a running speed so the object stays in the same position as in your field of view so if it dips a little bit you speed up if it rises a little bit you slow down and if you follow the simple rule you'll actually arrive at exactly the place where the object lands and you'll catch it and humans use it when they play baseball human pilots use it when they fly airplanes to figure out if they're about to collide with somebody frogs use this to catch insects and so on and so on so this is something that actually happens in nature and I'm sure this is just one instance of it that we were able to identify just because it's you know that scientists are able to identify that goes so prevalent with our probably many others do you ever just who can zoom in as we talk about robotics they have a canonical problem sort of a simple clean beautiful representative problem in robotics they you think about when you're thinking about some of these problems we talked about robotic manipulation to me that seems intuitively at least the robotics community is converging towards that as a space that's the canonical problem if you agree that maybe you zoom in in some particular aspect of that problem that you just like like if we solve that problem perfectly it'll unlock a major step in towards human level intelligence I don't think I have like a really great answer to that and I think partly the reason I don't have a great answer kind of has to do with the it has to do with the fact that the difficulty is really in the flexibility and adaptability rather than in doing a particular thing really really well so it's hard to just say like oh if you can I don't know like shuffle a deck of cards as fast as like a Vegas right a casino dealer then you'll you'll be very proficient it's really the ability to quickly figure out how to do some arbitrary new thing well enough so like you know to move on to the next arbitrary thing but the the source of newness and uncertainty have you found problems in which it's easy to generate new noonah sness messes yeah new types of newness yeah so a few years ago is so if you'd asked me this question around like 2016 maybe I would have probably said that robotic grasping is a really great example of that because it's a task with great real-world utility like you will get a lot of money if you can do it well when is the robotic grasping picking up any object with a robotic hand exactly so you'll get a lot of money if you do it well because lots of people want to run warehouses with robots and it's highly non-trivial because very different objects will require very different grasping strategies but actually since then people have gotten really good at building systems to solve this problem as to the point where I'm not actually sure how much more progress we can make with that as like the main guiding thing but it's kind of interesting to see the kind of methods that have what actually worked well in that space because a robotic grasping classically used to be regarded very much as kind of an almost like a geometry problem so you people who have studied the history of computer vision will find this very familiar that it's kind of in the same way that in the early days of computer vision people thought of it very much it's like an inverse graphics thing in robotic grasping people thought of it as an inverse physics problem essentially you look at what's in front of you figure out the shapes then use your best estimate of the laws of physics to figure out where to put your fingers on you pick up the thing and it turns out that what works really well for robotic grasping instantiated in many different recent works including our own but also ones from many other labs is to use learning methods with some combination of either exhaustive simulation or like actual real-world trial-and-error and turns out that those things actually work really well and then you don't have to worry about solving geometry problems or physics problems so what are just by the way and the grasping what are the difficulties that have been worked on so one is like the materials of things maybe occlusions and the perception side why is it such a difficult why is picking stuff up such a difficult problem yeah it's a difficult problem because the number of things that you might have to deal with or the variety of things that you have to deal with is extremely large and oftentimes things that work for one class of objects won't work for other class of objects so if you if you get really good at picking up boxes and now you have to pick up plastic bags you know you just need to employ a very different strategy and there are many properties of objects that are more than just their geometry it has to do with you know the bits that that are easier to pick up the bits that are hard to pick up the bits that are more flexible the bits that will cause the thing to pivot and Bend and drop out of your hand versus the bits that resulted in I secure grasp things that are flexible things that if you pick them up the wrong way they'll fall upside down and the contents will spill out so there's all these little details that come up but the task is still kind of can be characterized as one task like there's a very clear notion of you did it or you didn't do it so in terms of spilling things there creeps in this notion that starts the sound and feel like common sense reasoning do you think solving the general problem of Robotics requires common sense reasoning requires general intelligence this kind of human level capability of you know like you said be robust and deal with uncertainty but also be able to sort of reason and assimilate different pieces of knowledge that you have yeah what do you what are your thoughts on the needs of common sense reasoning in the space of the general robotics problem so I'm gonna slightly dodge that question and say that I think I think maybe actually it's the other way around is that studying robotics can help us understand how to put common sense into our AI systems one way to think about common sense is that and and why our current systems might lack common sense is that common sense is a property is an emergent property of actually having to interact with a particular world a particular universe and get things done in that universe so you might think that for instance like a an image captioning system maybe it looks at pictures of the world and it types out English sentences so it kind of it kind of deals with our world and then you can easily construct situations where image captioning systems do things that defy common sense like give it a picture of a person wearing fur coat and we'll say it's a teddy bear but I think what's really happening in those settings is that the system doesn't actually live in our world it lives in its own world that consists of pixels and English sentences and doesn't actually consist of like you know having to put on a fur coat in the winter so you don't get cold so perhaps the the reason for the disconnect is that the systems that we have now is simply inhabit a different universe and if we build AI systems that are forced to deal with all of the messiness and complexity of our universe maybe they will have to acquire our common sense to essentially maximize their utility whereas the systems we're building now don't have to do that they can take some shortcut that's fascinating you've a couple of times already sort of reframed the role of robotics and this whole thing and for some reason I don't know if my way of thinking is common but I thought like we need to understand and solve intelligence in order to solve robotics and you're kind of framing it as no robotics is one of the best ways to just study artificial intelligence and build sort of like robotics is like the right space in which you get to explore some of the fundamental learning mechanisms fundamental sort of multimodal multitask aggregation of knowledge mechanisms that are required for general intelligence this really interesting way to think about it but let me ask about learning can the general sort of robotics the epitome of the robotics problem be solved purely through learning perhaps and to end learning sort of learning from scratch as opposed to injecting human expertise and rules and heuristics and so on I think that in terms of the spirit of the question I I would say yes I mean I think that in though in some ways it may be like an overly sharp dichotomy like you know I think that in some ways when we build algorithms we you know at some point a person does something like yeah there's always a person turned on the computer first you know implemented tensorflow but yeah I think that in terms of the in terms of the point that you're getting and I do think the answer is yes I think that I think that we can solve many problems that have previously required meticulous manual engineering through automated optimization techniques and actually one thing I will say on this topic is I don't think this is actually a very radical or very new idea I think people have have been thinking about automated optimization techniques as a way to do control for a very very long time and in some ways what's changed is really more than aim so you know today we would say that oh my robot does machine learning it does reinforcement learning maybe in the 1960s you'd say oh my robot is doing optimal control and maybe the difference between typing out a system of differential equations and doing feedback linearization versus training and neural net it's not such a large difference it's just you know pushing the optimization deeper and deeper into the thing well you think that were but with the especially deep learning that the accumulation of experiences in data form to form deep representations starts to feel like knowledge is supposed to optimal control so this feels like there's an accumulation of knowledge to the learning process yes yeah so I think that is a good point that one big difference between learning based systems and classic optimal control systems is that learning based systems and principle should get better and better the more they do something right and I do think that that's actually a very very powerful difference so if you look back at the world of expert systems is symbolic AI and so on of using logic to accumulate expertise human expertise human encoded expertise but do you think that will have a role the some points that the you know deep learning machine learning reinforcement learning has been in incredible results and breaks there wasn't just inspired thousands maybe millions of researchers but you know there's this less popular now but it used to be part of the idea of symbolic AI do you think that will have a role I think in some ways the kind of the the descendants of symbolic I actually already have a role so you know this is the the highly biased history from my perspective you say that well initially we thought that rational decision-making involves logical manipulation so you have some model the world expressed in term in terms of logic you have some query like what action do I take in order to for X to be true and then you manipulate your logical symbolic representation to get an answer what that turned into somewhere in the 1990s is well instead of building kind of predicates and statements that have true or false values will build probablistic systems where things have probabilities associated and probabilities of being true and false not turning the Bayes nets and that provided sort of a boost to what we're really you know still essentially logical inference systems just probabilistic logical inference systems and then people said well let's actually learn the individual probabilities inside these models and then people said well let's not even specify the nodes and the models let's just put a big neural net in there but in many ways I see these as actually can descendants from the same idea it's essentially instantiating rational decision-making by means of some inference process and learning by means of an optimization process so so in a sense I would say yes that it has a place and in many ways that place is or you know it already holds that place it's already in there yeah it's just by different it looks slightly different than there was before yeah but but at some there are some things that that we can think about that make this a little bit more obvious like if I train a big neural net model to predict what will happen in response to my robots actions and then I run probablistic inference meaning I invert that model to figure out the actions that lead to some plausible outcome like to me that seems like a kind of logic you have a model of the world it just happens to be expressed by a neural net and you are doing some inference procedure some sort of manipulation on that model to figure out you know the answer to a query that you have it's the interpretability it's the explained ability though that seems to be lacking more so because the nice thing about sort of experts systems is you can follow the reasoning of the system that to us mere humans is somehow compelling it it would it's just I don't know what to make of this fact that there's a human desire for intelligence systems to be able to convey in a poetic way to us why made the decisions it did like tell a convincing story and perhaps that's like a silly human thing like we shouldn't expect that of intelligent systems like we should be super happy that there is intelligent systems out there but if I were to sort of psychoanalyze the researchers at the time I would say expert systems connected to that part that desire for AI researchers for systems to be explainable I mean maybe on that topic do you have a hope that sort of inferences source of learning based systems will be as explainable as the dream was with expert systems for example I think it's a very complicated question because I think that in some ways the question of explain ability is kind of very closely tied to the question of of like performance like you know why do you want your system to explain itself well so that it's so that when it screws up you can kind of figure out why it did it right but it's nice but in some ways that that's a much bigger problem extra like your system might screw up and then it might screw up at how it explains itself or you might have some bugs somewhere so that it's not actually doing what was supposed to do so you know maybe a good way to view that problem is really as a problem as a bigger problem of verification and validation of which explained abilities sort of what one component I see I just see differently I see explained ability you you put it beautifully I think you actually summarized the field of explained ability but to me there's another aspect of explained ability which is like storytelling that has nothing to do with errors or with like the the survey it doesn't it uses errors as as elements of its story as opposed to a fundamental need to be explainable when errors occur it's just that for other intelligence systems to be in our world we seem to want to tell each other stories and that that's true in the political world is true in the academic world and that I you know neural networks are less capable of doing that or perhaps they're equally capable a storytelling storytelling may be it doesn't matter what the fundamentals of the system are you just need to be a good storyteller maybe one specific story I can tell you about in that space is actually about some work that was done by by my former collaborator who's now a professor at MIT named Jacob Andreas Jacob actually works on natural language processing but he had this idea to do a little bit of work in reinforcement learning and how on how natural language can basically structure the internals of policies trained with RL and one of the things he did is he set up a model that attempts to perform some tasks that's defined by a reward function but the model reads in a natural language instruction so this is a pretty common thing to do in instruction following so you tell it like you know go to the Red House and then supposed to go to the Red House but then one of the things that Jacob did is he treated that sentence not as a command from a person but as a representation of the internal kind of state of the of the of the mind of this policy essentially so that when it was faced with a new task what it would do is it would basically try to think of possible language descriptions attempt to do them and see if they led to the right outcome so it would kind of think out loud like you know I'm faced with this new task what am I gonna do let me go to the red house now that didn't work let me go to the Blue Room or something let me go to the green plant and once it got some reward it would say oh go to the green plant that's what's working I'm gonna go to the green plant and then you could look at the string that it came up with and that was a description of how it thought it should solve the problem so you could do you could basically incorporate language as internal state and you can start getting some handle on these kinds of things and then what I was kind of trying to get to is that also if you add to the reward function the convincing nough story hmm so I have another reward signal of like people who review that story how much they like it I says that you you know and initially that could be a hyper parameter or sort of hard-coded heuristic type of thing but it's an interesting notion of the convincing 'no story becoming part of the reward function the objective function of the explained ability it's in the world of sort of twitter and fake news that might be a scary notion that the the nature of truth may not be as important as the convincing 'no some the how convinced you are in telling the story around the facts well let me ask the the basic question you're one of the world-class researchers in reinforcement learning deeper and forceful learning certainly in the robotic space what is reinforcement learning i think that reinforcement learning refers to today is really just the kind of the modern incarnation of learning based control so classically reinforcement learning has a much more narrow definition which is that it's you know literally learning from reinforcement like the thing does something and then it gets a reward or punishment but really i think the way the term is used today is it's used for for more broadly to learning based control so some kind of system that's supposed to be controlling something and it uses data to get better and what is control means is action is the fundamental element yeah it means making rational decisions now and rational decisions are decisions that maximize a measure of utility and sequentially see many decisions time and time and time again now like so it's easier to see that kind of idea in the space of maybe games in the space of robotics do you see is bigger than that is it applicable like word were the limits of the applicability of reinforcement learning yeah so rational decision-making is essentially the the encapsulation of the AI problems you didn't through a particular lens so any problem that we would want a machine to do intelligent machine can likely be represented as a decision-making problem you're classifying images is a decision-making problem although not a sequential one typically you know controlling a chemical plant as a decision-making problem deciding what videos to recommend on YouTube is a decision-making problem and one of the really appealing things about reinforcement learning is if it does encapsulate the range of all these decision-making problems perhaps working on reinforcement learning is you know one of the ways to reach a very broad swath of AI problems but what what do you use the fundament the difference between reinforcement learning and maybe supervised machine learning so the reinforcement learning can be viewed as a generalization of supervised machine learning you can certainly cast supervised learning as a reinforcement learning problem you can just say your loss function is the negative of your reward but you have stronger assumptions you have the assumption that someone actually told you what the correct answer was that your data was iid and so on so you could view reinforcement learning is essentially relaxing some of those assumptions now that's not always a very productive way to look at it because if you actually have a supervised learning problem you'll probably solve it much more effectively by using supervised learning methods because it's easier but you can view reinforcement as a journalist a tional know for sure but they're fundamentally that's a mathematical statement that's absolutely correct but it seems that reinforcement learning the kind of tools we'll bring to the table today of today so maybe down the line everything will be a reinforcement learning problem just like you said image classification should be mapped to a reinforcement learning problem but today the tools and ideas the way we think about them are different sort of supervised learning has been used very effectively to solve basic narrow AI problems the reinforcement learning kind of represents the dream of AI it's very much so in the research space now in two captivating the imagination of people what we can do with intelligent systems but it hasn't yet had as wide of an impact as the supervised learning approaches so that so that I my question comes from more practical sense like what do you see is the gap between the more general reinforcement learning and the very specific yes it's a question decision-making with one sequence one step in the sequence of the supervised learning so for a practical standpoint I think that one one thing that is you know potentially a little tough now and this is I think something that we'll see this is a gap that we might see closing over the next couple of years is the ability of reinforcement learning algorithms to effectively utilize large amounts of prior data so one of the reasons why it's a bit difficult today to use reinforcement learning for all the things that we might want to use it for is that in most of the settings where we want to do rational decision-making it's a little bit tough to just deploy some policy that does crazy stuff and learns purely through trial and error it's much easier to collect a lot of data a lot of logs of some other policy that you've got and then maybe you you know if you can get a good policy out of that then you deploy it and let it kind of fine-tune a little bit but algorithmically it's quite difficult to do that so I think that once we figure out how to get reinforcement learning to bootstrap effectively from large data sets then we'll see very very rapid growth and applications of these technologies so this is what's referred to as off policy reinforcement learning or offline RL or batch RL and I think we're seeing a lot of research right now that that's bringing us closer and closer to that can you maybe paint a picture of the different methods she said off policy what's value-based reinforcement learning what's policy based was modelled based with soft policy on policy what are the different categories of reinforcement yeah so one way we can think about reinforcement learning is that it's um it's in some very fundamental way it's about learning models that can answer kind of what-if questions so what would happen if I take this action that I haven't taken before and you do that of course from experience from data and oftentimes you do it in a loop so you build a model that answers these what-if questions use it to figure out the best action you can take and then go and try taking that and see if the outcome agrees with what you predicted so the different kinds of techniques are basically refer different ways of doing it so model based methods answer a question of what state you would get basically what would happen to the world if you were to take a certain action value based methods they answer the question of what value you would get meaning what utility you would get but in a sense they're not really all that different because they're both really just answering these what-if questions now unfortunately for us with current machine learning methods answering what-if questions can be really hard because they are really questions about things that didn't happen if you want to answer what-if questions about things that did happen you wouldn't need to learn model you would just like repeat the thing that worked before and that's really a big part of why RL is a little bit tough so if you have a purely on policy kind of online process then you ask these what-if questions you make some mistakes then you're going to try doing those mistake in things and then you observe kind of the counter examples that'll teach you not to do those things again if you have a bunch of off policy data and you just want to synthesize the best pulse you can out of that data then you really have to deal with the the challenges of making these these counterfactual what's the policy yeah a policy is a model or some kind of function that maps from observations of the world to actions so in reinforcement learning we often refer to the the current configuration of the world as the state so we say the state kind of encompasses everything you need to fully define where the world is at at the moment and depending on how we formulate the problem we might say you either get to see the state or you get to see an observation which is some snapshot some piece of the state so policy is just includes everything in it in order to be able to act in this world yes and so what is off policy mean if yeah so the terms on policy and off policy refer to how you get your data so if you get your data from somebody else who was doing some other stuff maybe you get your data from some manually programmed a system that was you know just running in the world before that's referred to as off policy data but if you got the data by actually acting in the world based on what your current policy thinks is good we call that on policy data and obviously on policy data is more useful to you because if your current policy makes some bad decisions you will I you see that those decisions are bad off policy data however might be much easier to obtain because maybe that's all the log data that you have from before so we talked about new offline talked about autonomous vehicles so you can envision off policy kind of approaches in robotics phases where there's really ton of robots out there but they don't get the luxury of being able to explore based on reinforcement learning framework so how do we make again open question but how do we make our policy methods work yeah so this is something that has been kind of a big open problem for a while and in the last few years people have made a little bit of progress on that you know I can tell you about and it's not by any means solved yet but I can tell you some of the things that for example we've done to try to address some of the challenges it turns out that one really big challenge with off policy reinforcement learning is that you can't really trust your models to give accurate predictions for any possible action so if I've never tried to if in my data said I never saw somebody steering the car off the road onto the sidewalk my value function or my model is probably not going to predict the right thing if I ask what would happen if I were to steer the car off the road onto the sidewalk so one of the important things you have to do to get off Paul crl to work is you have to be able to figure out whether a given action will result in a trustworthy prediction or not and you can use kind of distribution estimation methods kind of density estimation methods to try to figure that out so you could figure out that well this action my model is telling me that it's great but it looks totally different from any action I've taken before so I'm all it's probably not correct and you can incorporate regularization terms into your learning objective that will essentially tell you not to ask those questions that your model is unable to answer what would lead to breakthroughs in this space do you think like well what's needed is this a data set question do we need to collect big benchmark data sets that allow us to explore the space is it a new kinds of methodologies like what's your sense or maybe coming together in a space of robotics and defining the problem to do working on him I think four off policy reinforced mooring in particular it's very much an algorithms question right now and you know this is something that I think it's great because now arounds question is you know that that just takes some very smart people to get together and think about it really hard whereas if it was like a data problem or hardware problem that would take some serious engineering so that's why I'm pretty excited about that problem because I think that we're in a position where we can make some real progress on it just by coming up with the right algorithms in terms of which algorithms they could be you know that the problems that their core are very related to problems in you know things like like causal inference right because well you're really dealing with the situations where you have a model a statistical model that's trying to make predictions about things that I hadn't seen before and if it's a if it's a model it's generalizing properly that'll make good predictions if it's a model that picks up on spurious correlations that will not generalize properly and then you can you have an arsenal of tools you can use you could for example figure out what are the regions where it's trustworthy or on the other hand you could try to make it generalize better somehow or some combination of the two is there room for mixing sort of or most of it like 90 95 percent is off policy you already have the data set and then you get to send the robot out to do a little exploration like what what's that role of mixing them together yeah absolutely I think that this is something that you actually might describe very well at the beginning of the of our discussion when you talk about the iceberg like this is the iceberg that the 99% of your prior experience that's your iceberg you'd use that for all policy reinforcement learning and then of course if you've never you know opened that particular kind of door with that particular lock before then you have to go out and fiddle with it a little bit and that's that additional 1% to help you figure out a new task and I think that's actually like a pretty good recipe going forward is this to you the most exciting space of reinforcement learning now or is there what's uh and maybe taking a step back not just now but what's to use the most beautiful idea apologize for the romanticized question but the beautiful idea or a concept in reinforcement learning in general I actually think that one of the things that is a very beautiful idea in reinforcement learning is just the idea that you can obtain a near optimal controller in your optimal policy without actually having a complete model of the world this is you know it's something that feels perhaps kind of obvious if you if you just hear the term reinforcement learning or you think about trial and error learning but from a controls perspective it's a very weird thing because classically you know we we think about engineered systems and controlling engineered systems as as the problem of writing down some equations and then figuring out given these equations you know basically I solve for X figure out the the thing that maximizes its performance and the the theory of reinforcement learning actually gives us a mathematically principled framework just think to reason about you know optimizing some quantity when you don't actually know the equations that govern that system and that I don't to me that actually seems kind of kind of you know very elegant not something that sort of becomes immediately obvious at least in the mathematical sense does it make sense to you that it works at all well I think it makes sense when you take some time to think about it but it is a little surprising well then then taking a step into the more deeper representations which is also very surprising of sort of the richness of the state space the space of environments that this kind of approach can operate in can you maybe say what is deep reinforcement learning well deep reinforcement learning simply refers to taking reinforcement learning algorithms and combining them with high capacity neural net representations which is you know kind of it might at first seem like a pretty arbitrary thing just take these two components and stick them together but the reason that it's it's something that has become so important in recent years is that reinforcement learning it kind of faces an exacerbated version of a problem that has faced many other machine learning too so if you if we go back to like you know the early 2000s or the late 90s we'll see a lot of research on machine learning methods that have some very appealing mathematical properties like they reduced a convex optimization problems for instance but they require very special inputs they require a representation of the input that is clean in some way like for example clean in the sense that the classes in your multi-class classification problems separate linearly so they they have some cases it's some kind of good representation we call this a feature representation and for a long time people were very worried about features in the world of supervised learning because somebody had to actually build those features so you couldn't just take an image and plug it into your logistic regression or your SVM or something someone had to take that image and process it using some handwritten code and then neural nets came along and they could actually learn the features and suddenly we could apply learning directly to the raw inputs which was great for images but it was even more great for all the other fields where people hadn't come up with good features yet and one of those fields actually reinforced my learning because in reinforcement learning the notion of features if you don't use neural nets and you have to design your own features it's very very opaque like it's very hard to imagine like let's say I'm playing chess or go what is a feature with which I can represent the value function for go or even though the optimal policy forego linearly I I don't even know how to start thinking about it and and people tried all sorts of things that would write down you know an expert chess player looks for whether the the knight is in the middle of the board or not so that's a feature is night in middle of board and they would write these like long lists of kind of arbitrary made-up stuff and that was really kind of getting us no way and that's a little chess is a little more accessible than the robotics problem absolutely all right that's there's at least experts in the different features for chess but still like the neural network there I did to me that's I mean you put it eloquently and almost made it seem like a natural step to add neural networks but the fact that neural networks are able to discover features in the control problem it's very interesting it's hopeful I'm not sure what to think about it but it feels hopeful that the control problem has features to be learned like I guess my question is is it surprising to you how far the deep side of deep reinforcement learning is able to like what the space of problems has been able to tackle from especially in games with the Alpha star and and alpha zero and just the the representation of power there and in the robotic space and what is your sense of the limits of this representation power and the control context I think that in regard to the limits that here I think that one thing that makes it a little hard to fully answer this question is because in settings where we would like to put push these things to the limit we encounter other bottlenecks so like the reason that I can't get my robot to learn how to like I don't know do the dishes in the kitchen it's not because it's neural net is not big enough it's because when you try to actually do trial and error learning you reinforce them a loner directly in the real world where you have the potential to gather these large they're you know highly varied and complex datasets you start running into other problems like one problem you run into very quickly it'll first sound like a very pragmatic problem that actually turns out to be a pretty deep scientific problem take the robot put in your kitchen have it try to learn to do the dishes with trial and error it'll break all your dishes and then we'll have no more dishes to clean now you might think this is a very practical issue but there's something to this which is that if you have a person trying to do this you know a person will have some degree of common sense they'll break one dish it'll be a little more careful with the next one and if they break all of them they're gonna go and get more or something like that so there's all sorts of scaffolding that that comes very naturally to us for our learning process like you know if I have to learn something through trial and error I have a common sense to know that I have to you know try multiple times if I screw something up I ask for help or I recept things or something like that and all that it's kind of outside of the classic reinforcement problem formulation there are the things that are that can also be categorizes scaffolding but are very important like for example where you get your award function if I want to learn how to pour a cup of water well how do I know if I've done it correctly now that probably requires an entire computer vision system to be built just to determine that and that seems a little bit inelegant so there are all sorts of things like this that start to come up when we think through what we really need to get reinforcement learning to happen at scale in the real world and any that many of these things actually suggest a little bit of a shortcoming in the problem formulation and a few deeper questions that we have to resolve that's really interesting I thought to like David silver bought alpha zero and it seems like there's no again the the we haven't hit the limit at all in the context when there is no broken dishes so in the game in the case of go you can it's really about just scaling compute so again like the bottleneck is the amount of money you're willing to invest in compute and then maybe the different the scaffolding around how difficult it is to scale compute maybe but there there's no limit and it's interesting now we move to the real world and there's the broken dishes they solved it and the reward function like you mentioned that's really nice of what how do we push forward there do you think there's there's this kind of sample efficiency question that people bring up or you know not having to break a hundred thousand dishes is this an algorithm question is this data selection like question or what do you think how do we how do we not break them too many dishes yeah well one way we can think about that is that maybe we need to be better at reusing our data building that that iceberg so perhaps perhaps it's too much to hope that you can have a machine that in isolation in the vacuum without anything else can just master complex tasks in like in minutes the way that people do but perhaps it also doesn't have to perhaps what it really needs to do is have an existence a lifetime where it does many things and the previous things that it has done prepare it to do new things more and you know the study of these kinds of questions typically falls under categories like multitask learning or meta learning but they all fundamentally deal with the same general theme which is use experience for doing other things to learn to do new things efficiently and quickly so what do you think about if you just look at one particular case study of Tesla autopilot that has quickly approaching towards a million vehicles on the road where some percentage of the time thirty forty percent of the time is driven using the computer vision multitask Hydra net right and then the other percent that's what they call it Hydra net the the other percent is human controlled from the human side how can we use that data what's your sense like what's the signal do you have ideas in this autonomous vehicle space when people can lose their lives you know it's a it's a safety critical environment so how do we use that data so I think that actually the kind of problems that come up when we want systems that are reliable and that can kind of understand the limits of their capabilities they're actually very similar to the kind of problems that come up when we have we're doing off policy reinforcement learning so as I mentioned before and off policy reinforcement learning the big problem is you need to know when you can trust the predictions of your model because if you if you're trying to evaluate some pattern of behavior for which your model doesn't give you an accurate prediction then you shouldn't use that to to modify your policy and it's actually very similar to the problem that we're faced when we actually then deploy that thing and we want to decide whether we trust it in the moment or not so perhaps we just need to do a better job of figuring out that part and that's a very deep research question of course it's also a question that a lot of people are working on so I'm pretty optimistic that we can make some progress on that over the next few years what's the role of simulation in reinforcement learning the end deeper enforcement learning reinforcement learning like how essential is it it's been essential for the breakthroughs so far for some interesting breakthroughs do you think it's a crutch that we rely on I mean again it's can throw off policy discussion but do you think we can ever get rid of simulation or do you think simulation will actually take over will create more and more realistic simulations that will allow us to to solve actual real-world problems like transfer the models will learn in simulation from the walk-around yes I think that simulation is a very pragmatic tool that we can use to get a lot of useful stuff to work right now but I think that in the long run we will need to build machines that can learn from real data because that's the only way that will get them to improve perpetually because if we can't have our machines learn from real data if they have to rely on simulated data eventually the simulator becomes the bottleneck in fact this is a general thing if your machine has any bottleneck that is built by humans and that doesn't improve from data it will eventually be the thing that holds it back and if you're entirely relying on your simulator that'll be the bottleneck if you're entirely really reliant on a manually designed controller that's going to be the bottleneck so simulation is very useful it's very pragmatic but it's not a substitute for being able to utilize real experience and this is by the way this is something that I think is quite relevant now especially in the context of some of the things we've discussed because some of these kind of scaffolding issues that I mentioned things like the broken dishes and the unknown reward function like these are not problems that you would ever stumble on when working in a purely simulated kind of environment but they become very apparent when we try to actually run these things in the real world do you throw a brief wrench into our discussion let me ask do you think we're living in a simulation oh I have no idea do you think that's a useful thing to even think about about the there the the fundamental physics nature of reality or another perspective the reason I think the simulation hypothesis is interesting is it's to think about how difficult is it to create sort of a virtual reality game type situation that will be sufficiently convincing to us humans or sufficiently enjoyable that would we wouldn't want to leave that's actually a practical engineering and I I personally really enjoy virtual reality but it's quite far away but I kind of think about what would it take for me to want to spend more time in virtual reality versus the real world and that's a that's a sort of a nice clean question because at that point we've reached if I want to live in a virtual reality that means we're just a few years away where majority of the population lives in a virtual reality and that's how we create the simulation right you don't need to actually simulate the you know the quantum gravity and just every aspect of the of the universe and that's a read that the interesting question for reinforcement learning too is if you want to make sufficiently realistic simulations that make it blend the difference between sort of the real world and the simulation there by just are the some of the things we've been talking about kind of the problems go away if we can create actually interesting rich simulations it's an interesting question and it actually I think your question casts your previous questions in a very interesting light because in some ways asking whether we can well the more practical more kind of practical version is like you know can we build simulators that are good enough to train essentially AI systems that will work in the world and it's kind of interesting to think about this about what this implies if true it kind of implies that it's easier to create the universe than it is to create a brain and then it seems like put this way it seems kind of weird the aspect of the simulation most interesting to me is the simulation of other humans that seems to be a complexity that makes the robotics problem harder now I don't know if every robotics person agrees with that notion just as a quick aside what are your thoughts about when the human enters the picture of the robotics problem how does that change the reinforcement learning problem the the learning problem in general yeah I think that's a it's a kind of a complex question and I guess my hope for a while had been that if we build these robotic learning systems that that are multitask that utilize lots of prior data and that learn from their own experience the bit where they have to interact with people will be perhaps handled in much the same way as all the other bits so if they have prior experience in attracting with people and they can learn from their own experience of interacting with people for this new task maybe that'll be enough now of course there if it's not enough there are many other things we can do and there's quite a bit of research on that in that area but I think it's worth a shot to see whether the the the multi agent interaction the the ability to understand that other beings in the world have their own goals and tensions and thoughts and so on whether that kind of understanding can emerge automatically from simply learning to do things with and maximize utility that information arises from the data you've said something about gravity sort of that you don't need to explicitly inject anything into the system they can be learned from the data and gravity is an example of something that could be learned from data sort of like the physics of the world like what what are the limits of what we can learn from data do you really do you think we can so a very simple clean way to ask that is do you really think we can learn gravity from just data the idea the the laws of gravity so it says something that I think is a common kind of pitfall when thinking about prior knowledge and learning is to assume that just because we know something then that it's better to tell the Machine about that rather than have it I regret out on its own in many cases things that are important that affect many of the events that the Machine will experience are actually pretty easy to learn like you know if things if every time you drop something it falls down like yeah you might not get the you know you might get kind of an in the Newton's version not Einsteins version but it'll be pretty good and it will probably be sufficient for you to act rationally in the world because you see the phenomena all the time so things that are readily apparent from the data we might not need to specify those by hand it might actually be easier to let the Machine figure it just feels like that there might be a space of many local local minima in terms of theories of this world that we would discover and get stuck on yeah of course Newtonian mechanics is not necessarily easy to come by yeah and well in fact in in some fields of science for example human civilizations itself full of these local optima so for example if you think about how people try to figure out biology and medicine you know for the longest time the kind of rules like the kind of principles that serve us very well in our day to day lives actually serve us very poorly in understanding medicine and biology we had kind of very superstitious and weird ideas about how the body worked until the advent of the modern scientific method so that does seem to be you know a failing of this approach but it's also a failing of human intelligence arguably maybe a small aside but some you know the idea of self play is fascinating reinforcement learning sort of these competitive and creating a competitive context in which agents can play against each other in a sort of at the same skill level and thereby increasing each other school it seems to be this kind of self improving mechanism is exceptionally powerful in the context where it could be applied first of all is that beautiful to you that this mechanism work as well as it does and also can be generalized to other context like in the robotic space or anything that's applicable to the real world I think that it's a very interesting idea and I suspect that the bottleneck to actually generalizing it to the robotic setting is actually gonna be the same as as the bottleneck for everything else that we need to be able to build machines that can get better and better through natural interaction with the world and once we can do that then they can go out and play with they can play with each other they can play with people they can play with the natural environment but before we get there we've got all these other problems we've got we have to get out of the way there's no shortcut around that you have to interact with the national environment well because in in a self play setting you still need a mediating mechanisms so the the reason that you know self play works for a board game is because the rules of that board game mediate the interaction between the agents so the kind of intelligent behavior that will emerge depends very heavily on the nature of that mediating mechanism so on the side of reward functions that's coming up with good reward function seems to be the thing that we associate with general Intel like human beings seem to value the idea of developing our own reward functions of you know arriving in meaning and so on and yet for reinforcement learning we often kind of specify that's the given what's your sense of how we develop a reward for good you know good reward functions yeah I think that's a very complicated and very deep question and you're completely right that classically in reinforcement learning this question has kind of been treated as a non-issue that you sort of treat the reward as this external thing that comes from some other bit of your biology and you can don't worry about it and I do think that that's actually you know a little bit of a mistake that we shouldn't worry about it and we can approach you in a few different ways we can approach it for instance by thinking of rewards as a communication medium we can say well how does a person communicate to a robot what its objective is you can approach it also as sort of more of an intrinsic motivation medium you could say can we write down kind of a general objective that leads to good capability like for example can you write down some objective such that even in the absence of any other task if you maximize that objective you'll sort of learn useful things this is a something that has sometimes been called unsupervised reinforcement learning which i think is a really fascinating area of research especially today we've done a bit of work on that recently one of the things we've studied is whether we can have some notion of of unsupervised reinforcement learning by means of you know information theoretic quantities like for instance minimizing a Bayesian measure of surprise this is an idea that was you know pioneered actually in the computational neuroscience community by folks like Carl Fritton we've done some work recently that shows that you can actually learn pretty interesting skills by essentially behaving in a way that allows you to make accurate predictions about the world it seems a little circular do the things that will lead to you getting the right answer for prediction but you can you know by doing this you can sort of discover stable niches in the world you can discover that if you're playing Tetris then correctly you know clearing the rows will let you play Tetris for longer and keep the board nice and clean which sort of satisfies some desire for order in the world and as a result to get some degree of leverage over your domain so we're exploring that pretty actively is there a role for a human notion of curiosity in itself being the reward sort of discovering new things about the war the world so one of the things that I'm pretty interested in is actually whether discovering new things can actually be an emergent property of some other objective that quantifies capability so new things for the sake of new things maybe it's not maybe might not by itself be the right answer but perhaps we can figure out an objective for which discovering new things is actually the natural consequence that's something we're working on right now but I don't have a clear answer for you there yet that's still work-in-progress you mean just as a security observation to see sort of creative the patterns of curiosity on the way to optimize for a particular protector on the way to optimize for a particular measure of capability is is there ways to understand or anticipate unexpected unintended consequences of particular reward functions sort of anticipate the kind of strategies that might be developed and try to avoid highly detrimental strategy yeah so classically this is something that has been pretty hard in reinforcement learning because it's difficult for a designer to have good intuition about you know what a learning outcome will come up with when they give it some objective there are ways to mitigate that one way to mitigate it is to actually define an objective that says like don't do weird stuff you can actually quantify you can say just like don't enter situations that have low probability under the distribution of states you've seen before it turns out that that's actually one very good way to do off policy reinforcement learning actually so we can do some things like that if we slowly venture in speaking about reward functions into greater and greater levels of intelligence there's a mr. Russell thinks about this the alignment of AI systems with us humans so how do we ensure that AG AI systems align with us humans it's a it's kind of a reward function question of specifying the behavior of AI systems such that their success aligns with us with the broader intended success interest of human beings do you have thoughts on this they have kind of concerns of where reinforcement learning fits into this or are you really focused on the current moment of us being quite far away and trying to solve the robotics problem I don't have a great answer to this but you know and I do think that this is a problem that's that's important to figure out for my part I'm actually a bit more concerned about the other side of the of this equation that you know maybe rather than unintended consequences for objectives that are specified too well I'm actually more worried right now about unintended consequences for objectives that are not optimized well enough which might become a very pressing problem when we for instance try to use these techniques for safety critical systems like cars and aircraft and so on I think at some point we'll face the issue of objectives being optimized too well but right now I think we're more likely to face the issue of them not being optimized well enough but you don't think on intended consequence can arise even when you're far from optimality sort of like on the path to it oh no I think I unattended consequence can absolutely arise it's just I think right now the bottleneck for improving reliability safety and things like that is more with systems that like need to work better that the optimize their objective better you have thoughts concerns about existential threats of human level intelligence sort of if we put on our hat of looking in ten twenty a hundred five hundred years from now give concerns about existential threats of AI systems I think there are absolutely existential threats for AI systems just like there are for any powerful technology but I think that the these kinds of problems can take many forms and and some of those forms will come down to you know people with nefarious intent some of them will come down to AI systems that have some fatal flaws and some of them will will of course come down to AI systems that are too capable in some way but among this set of potential concerns I would actually be much more concerned about the first two right now and principally the one with nefarious humans because you know just through all of human history actress that I Ferris humans that have been the problem not the nefarious machines then I am about the others and I think that right now the best that I can do to make sure things go well is to you know build the best technology I can and also hopefully promote responsible use of that technology do you think RL systems has something to teach us humans you said nefarious humans getting us in trouble I mean machine learning system self in some ways have revealed to us the ethical flaws in our data in that same kind of wake and reinforce some learning teach us about ourselves has it taught something what have you learned about yourself from trying to build robots and reinforce the learning systems I'm not sure what I've learned about myself but maybe part of the answer to your question might become a little bit more apparent once we see more widespread deployment of reinforcement learning for decision making support in you know in domains like you know healthcare education social media etc and I think we will see some interesting stuff emerge there we will see for instance what kind of behaviors these systems come up with in situations the where there is interaction with humans and and where they have you know possibility of influencing human behavior I think we're not quite there yet but maybe in the next two years we'll see some interesting stuff coming out in that area I hope outside the research because the the exciting space where this could be observed is sort of large companies that deal with large data and I hope there's some transparency and one of the things it's unclear when I look at social networks and just online is why an algorithm did something or whether you know even an algorithm was involved and that'd be interesting as a formal research perspective just to to observe the results of algorithms to open up that data or did these be sufficiently transparent about the behavior of these e-a systems in the real world what's your sense I don't know if you looked at the blog post bitter lesson by Irish Sutton where it looks at serve the big lesson of research in AI in reinforcement learning is that simple methods general methods that leverage computation seem to work well so basically don't try to do any kind of fancy algorithms just wait for computation and get fast do you share this kind of intuition I think the high level idea makes a lot of sense I'm not sure that my takeaway would be that we don't need to work on algorithms I think that my takeaway would be that we should work on general algorithms and actually I think that this idea of needing to better automate the acquisition of experience in the real world actually follows pretty naturally from Rich Sutton's conclusion so if the claim is that automated general methods plus data leads to good results then it makes sense that we should build general methods and we should build the kind of methods that we can deploy and get them to go out there and like collect their experience autonomously I think that you know one place where I think that the current state of things Falls a little bit short of that is actually that the going out there collecting the data autonomously which is easy to do in a simulator board game but very hard to do in the real world yeah it keeps coming back to this one problem right it's uh so your mind is focused there now in this real world it just seems scary the step of collecting the data and it seems unclear to me how we can do it effectively well you know it's seven billion people in the world each of them had to do that at some point in their lives and we should leverage that experience that they've all done the we should be able to try to collect that kind of data okay big questions maybe stepping back through your life would book or books technical or fiction or philosophical had a big impact onion on the way you saw the world I know he thought about in the world your life in general hmm and maybe what books if is different would you recommend people consider reading on their own intellectual journey it could be within reinforcement learning but could be very much bigger I don't know if this is like a scientifically like particularly meaningful answer but like the honest answers that I I actually found a lot of the work by Isaac Asimov to be very inspiring when I was younger I don't know if that has anything to do with with AI necessarily you don't think it had a ripple effect in your life maybe it did but yeah I like I think that a vision of a future where well first of all artificial mice artificial intelligence system artificial robotic systems have you know kind of a big place a big role in society and where we try to imagine the sort of the the limiting case of technological and advancement and how that might play out in in our future history but yeah I think that the that was in some way influential I don't really know how but and I would recommend it I mean if nothing else you'd be well entertained did you first yourself like fall in love with the idea of artificial intelligence get captivated by this field so my honest answer here is actually that I only really started to think think about it as a that's something that I might want to do actually in graduate school pretty light and a big part of that was that until you know somewhere around 2009 2010 it just wasn't really high on my priority list because I I didn't think that it was something where we're going to see very substantial advances in my lifetime and you know maybe in terms of my career the time when I really decided I wanted to work on this was when I actually took a seminar course that was taught by Professor and ring and you know at that point I of course had some had like a decent understanding of the technical things involved but one of the things that really resonated with me was when he said in the opening lecture something to the effect of like well he used to have graduate students come to him and talk about how they want to work on AI and he would kind of chuckle and give them some math problem to deal with but now he's actually thinking that this is an area where we might see like substantial advances in our lifetime and that kind of got me thinking because you know it's an abstract sense yeah like you can kind of imagine not but in a very real sense when someone who had been working on that kind of stuff their whole career suddenly says that yeah like that had that had some effect on me yeah this might be a special moment in the history of the field that this is where we might see some some interesting breakthroughs so in the space of advice somebody who's interested in getting started and machine learning or reinforcement learning what advice would you give to maybe an undergraduate student or maybe even younger how what are the first steps to take and further on what are the stapes steps to take on that journey so something that I think is important to do is to is to not be afraid to like spend time imagining the kind of outcome that you might like to see so you know one outcome might be a successful career large paycheck or something or state-of-the-art results in some benchmark but hopefully that's not the thing that's like the main driving force for somebody but I I think that if someone who's a student considering a career in AI like takes a little while sits down and thinks like what do I really want to see what I want to see a machine do what I want what do I want to see a robot do what I want to do and what I want to see a natural language system just like imagine you know imagine it almost like a commercial for a future product or something or like like something that you'd like to see in the world and then actually sit down and think about the steps that are necessary to get there and hopefully that thing is not a better number on imagenet classification it's like it's probably like an actual thing that we can't do today that would be really awesome whether it's a robot Butler or a you know a really awesome healthcare decision making support system whatever it is that you find inspiring and I think that thinking about that and then backtracking from there and imagining the steps needed to get there will actually do much better research it'll lead to rethinking the assumptions it'll lead to working on the bottlenecks other other people aren't working on and then naturally to turn to you we've talked about reward functions and you just give an advice and looking forward I would like to see what kind of change you would like to make in the world what do you think ridiculous big question what do you think is the meaning of life what is the meaning of your life what gives you fulfillment purpose happiness and meaning that's a very big question um what's the reward function under which you are operating yeah I think one thing that does give you know if not meaning at least satisfaction is some degree of confidence that I'm working on a problem that really matters I feel like it's less important to me to like actually solve a problem but it's it's quite nice to take things to spend my time on that I believe really matter and I I try pretty hard to to look for that I don't know if it's easy to answer this but if you're successful what does that look like what's the they dream enough of course success is built on top of success and you keep going forever but what is the dream yeah so one very concrete thing or maybe as concrete as it's gonna get here is is to see machines that actually get better and better the you know the longer they exists in the world and that kind of seems like on the surface one might even think that that's something that we have today but I think we really don't I think that there is unending complexity in the universe and to date all the machines that we've been able to build don't sort of improve up to the limit of that complexity they they hit a wall somewhere maybe they hit a wall because they're in a simulator that has that is only a very limited very pale imitation of the real world or they hit a wall because they rely on a label dataset but they never hit the wall of like running out of stuff to see like the did so you know I I'd like to build a machine that that can go as far as possible and that runs up against the ceiling of the complexity of the universe yes well I don't think there's a better way to end it Sergey thank you so much is a huge honor I can't wait to see the amazing work they have to publish and in education space in terms of reinforcement learning thank you for inspiring the world thank you for the great research you do thank you thanks for listening to this conversation with Sergey levine and thank you to our sponsors cash app and expressvpn please consider supporting this podcast by downloading cash app and using code lex podcast and signing up at expressvpn comm / lex pod click all the links buy all the stuff it's the best way to support this podcast and the journey I'm on if you enjoy this thing subscribe on YouTube review it five stars in a podcast supported on patreon or connect with me on Twitter at lex friedman spelled somehow if you can figure out how without using the letter e just FR ID ma m and now let me leave you with some words from Salvador Dali intelligence without ambition is a bird without wings thank you for listening and hope to see you next time you |
Peter Singer: Suffering in Humans, Animals, and AI | Lex Fridman Podcast #107 | the following is a conversation with Peter Singer professor of bioethics at Bristol University best known for his 1975 book Animal Liberation that makes an ethical case against eating meat he has written brilliantly from an ethical perspective on extreme poverty euthanasia human genetic selection sports doping the sale of kidneys and generally happiness including in his books ethics in the real world and the life you can save he was a key popularizer of the effective altruism movement and is generally considered one of the most influential philosophers in the world quick summary of the ads to sponsors cash app and masterclass please consider supporting the podcast by downloading cash app and using collects podcast and signing up a masterclass complex click the links buy the stuff it really is the best way to support the podcast and the journey I'm on as you may know I primarily eat a ketogenic or carnivore diet which means that most of my diet is made up of me I do not hunt the food I eat though one day I hope to I love fishing for example fishing and eating the fish I catch has always felt much more honest than participating in the supply chain of factory farming from an ethics perspective this part of my life has always had a cloud over it it makes me think I've tried a few times in my life to reduce the amount of meat I eat but for some reason whatever the makeup of my body whatever the way I practice the dieting I have I get a lot of mental and physical energy and performance from eating meat so both intellectually and physically it's a continued journey for me I returned to Peters work often to reevaluate the ethics of how I live this aspect of my life let me also say that you may be a vegan or you may be a meat-eater it may be upset by the words I say or Peter says but I asked for this podcast and other episodes of this podcast then you keep an open mind I may and probably will talk with people you disagree with please try to really listen especially to people you disagree with and give me in the world the gift of being a participant and a patient intelligent and nuanced discourse if your instinct and desire is to be a voice of mockery towards those you disagree with please unsubscribe my source of joy and inspiration here has been to be a part of a community that thinks deeply and speaks with empathy and compassion that is what I hope to continue being a part of and I hope you join as well if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Friedman as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show is presented by cash app the number one finance app in the App Store when you get it used colex podcast cash app lets you send money to friends buy Bitcoin and invest in a stock market with as little as $1 since cash app allows you to buy Bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating I recommend a cent of money as a great book in this history debits and credits on Ledger's started around 30,000 years ago the US dollar created over two hundred years ago and the first decentralized cryptocurrency released just over ten years ago so given that history cryptocurrency still very much in its early days of development but it's still aiming to just might redefine the nature of money so again if you get cash app from the App Store or Google Play and use the code let's podcast you get ten dollars and cash app will also donate ten dollars the first an organization that is helping to advance robotics a STEM education for young people around the world this show sponsored by a masterclass sign up a master class complex to get a discount and to support this podcast when I first heard about masterclass I thought it was too good to be true for $180 a year you get an all-access pass to watch courses from to list some of my favorites Chris Hadfield and space exploration the other guys Tyson on scientific thinking and communication will write creator of SimCity and Sims on game design I promise I'll start streaming games at some point soon Carlos Santana on guitar garry kasparov on chess Daniel Negreanu on poker and many more Chris Hadfield explaining how Rockets work and the experience of being launched into space alone is worth the money by the way you can watch it on basically any device once again sign up a master class complex to get a discount and to support this podcast and now here's my conversation with Peter Singer you first become conscious of the fact that there is much suffering in the world I think I was conscious of the fact that there's a lot of suffering the world pretty much as as soon as I was able to understand anything about my family and its background because I lost three of my four grandparents in the Holocaust and obviously I knew why I only had one grandparent and she herself had been in the camps and survived so I think I knew a lot about that pretty early my entire family comes from the Soviet Union I was born in so V and so sort of World War two has deep roots and a culture and the the suffering that the war brought the millions of people who died is in the is in the music is in the literature's and the culture what do you think was the impact of the war broadly on our society the war had many impacts I think one of them a beneficial impact is that it showed what racism and authoritarian government can do and at least as far as the West was concerned I think that meant that I grew up in an era in which there wasn't the kind of overt racism and anti-semitism that had existed for my parents in Europe I was growing up in Australia and certainly that was clearly seen as something completely unacceptable there was also the fear of a further outbreak of war which this time we expected would be nuclear because of the way the Second World War had ended so there was this overshadowing of my childhood about the possibility that I would not live to grow up and be an adult because of catastrophic nuclear war there was a the film on the beach was made in which the city that I was living Melbourne was the last place on earth to have living human beings because of the nuclear cloud that was spreading from the north so that certainly gave us a bit of that that sense there were many you know there were clearly many other legacies that we got of the war as well and the whole set up of the world and the the cold war that followed all of that has its roots in the Second World War you know there is much beauty that comes from war sort of at a conversation with Eric Weinstein he said everything is is great about war except all the death and suffering do you think there's something positive that they came from the war the the mirror that have put to our society sort of the ripple effects on it ethically speaking do you think there are positive aspects to war I find it hard to see positive aspects in war and some of the things that other people think of as as positive and beautiful maybe questioning so there's a certain kind of patriotism people say you know during wartime we all pull together we all work together against the common enemy and that's true an outside enemy does unite a country and in general it's good for countries to be united and have common purposes but it also engenders a kind of a nationalism and the patriotism that cannot be questioned and that I'm I'm more skeptical about what about the the Brotherhood that people talk about from soldiers the the sort of counterintuitive sad idea that the closest that people feel to each other is in those moments of suffering of being at the sort of the edge of seeing your comrades dying in your arms that somehow brings people extremely closely together suffering brings people closer together how do you make sense of that it might bring people close together but there are other ways of bonding and being close to people I think without the suffering and death that war entails perhaps you could see you can already hear the romanticized Russian in me we tend to romanticize suffering just a little bit in our literature and culture and so on could you take a step back and I apologize if it's a ridiculous question but what is suffering if you'll try to define what suffering is how would you go about it suffering is a conscious state they can be neither suffering for a being who is completely unconscious and it's distinguished from other conscious states in terms of being one that considered just in itself we would rather be with that it's a conscious state that we want to stop if we're experiencing or we want to avoid having again if we've experienced it in the past and that's as I say emphasized for its own sake because of course people will say well suffering strengthens the spirit it has good consequences and sometimes it does have those consequences and of course sometimes we might undergo suffering we set ourselves a challenge to run a marathon or climb a mountain or even just to go to the dentist so that the toothache doesn't get worse even though we know the dentist is going to hurt us to some extent so I'm not saying that we never choose suffering but I am saying that other things being equal we would rather not be in that state of consciousness is the ultimate goal sort of you have the new ten year anniversary release the life you can say book really influential book we'll talk about it a bunch of times throughout this conversation but do you think it's possible to eradicate suffering errors at the goal or do we want to achieve a a kind of minimum threshold of suffering and then keeping a little drop of poison that to keep things interesting in the world in practice I don't think we ever will eliminate suffering so I think that little drop of poison as you put it or if you like that the contrast - of an unpleasant color perhaps something like that in a otherwise harmonious and beautiful composition that is going to always be there if you ask me whether in theory if we could get rid of it I we should I think the answer is whether in fact we would be better off or whether in terms of by eliminating the suffering we would also eliminate some of the highs the positive hires and if that's so then we might be prepared to say it's worth having a minimum of suffering in order to have the best possible experiences as well is there a relative aspect to suffering so we when you talk about eradicating poverty in the world is this the more you succeed the more the bar of what defines poverty raises or is there at the basic human ethical level a bar that's absolute that once you get above it then it we can morally converge to feeling like we have eradicated poverty I think they're both and I think this is true for poverty as well as suffering there's an objective level of suffering or of poverty where we're talking about objective indicators like you're constantly hungry you don't you can't get enough food you're constantly cold you can't get warm you have some physical pains that you're never rid of I think those things are objective but it may also be true that if you do get rid of that and you get to the stage where all of those basic needs have been met there may still be there new forms of suffering that develop and perhaps that's what we're seeing in the affluent societies we have that people get bored for example they don't need to spend so many hours a day earning money to get enough to eat and shelter so now they're bored they like a sense of purpose that can happen and that then is a kind of a relative suffering that is distinct from the objective forms of suffering but in your focus on eradicating suffering you don't think about that kind of the the kind of interesting challenges and suffering that emerges in affluent societies that's just not in your ethical philosophical brain is that of interest at all it would be of interest to me if we had eliminated all of the objective forms of suffering which I think of as generally more severe and also perhaps here at this stage anyway to know how to eliminate so yes in some future state when we've eliminated those objective forms of suffering I would be interested in trying to eliminate the relative forms as well well that's not a practical need for me at the moment sorry to linger on it because you kind of said it but just the is elimination the goal for the affluent society so is there a crew you know do you see as suffering as a creative force suffering can be a creative force I think repeating what I said about the highs and whether we need some of the lows to experience the highs so it may be that suffering makes us more creative and we regard that as worthwhile maybe that that brings some of those highs with it that we would not have had if we'd had no suffering I I don't really know many people have suggested that and I certainly can't have no basis for denying it and if it's true then I would not want to eliminate suffering completely but the focus is on and the absolute not to be cold not to be hungry yes that's at the present stage of where the world's population is that's that's the focus talking about human nature for a second do you think people are inherently good or do we all have good and evil in us that basically everyone is capable of evil based on the environment certainly most of us have potential for both good and evil I'm not prepared to say that everyone is capable of evil maybe some people who even in the worst of circumstances would not be capable of it but most of us are very susceptible through environmental influences so when we look at things that we were talking about previously let's say the what the Nazis did during the Holocaust I think it's quite difficult to say I know that I would not have done those things even if I were in the same circumstances as those who did them even if let's say I had grown up under the Nazi regime and had been indoctrinated with racist ideas had also had the the idea that I must obey orders follow the commands of the Fuhrer plus of course perhaps the threat that if I didn't do certain things I might get sent to the Russian front and that would be a pretty grim fight I think it's really hard for anybody to say nevertheless I know I would not have killed those Jews or whatever so what's your intuition how many people will be able to say that truly to be able to say it I think very few less than 10% to me it seems a very interesting and powerful thing to meditate on so I've read a lot about the war a world war 2 and I can't escape the thought that I would have not been one of the 10% right I have to say I simply don't know I would like to hope that I would have been one of the 10% but I don't really have any basis for claiming that I would have been different from the majority is it a worthwhile thing to contemplate it would be interesting if we could find a way of really finding these answers there obviously is quite a bit of research on people during the Holocaust on how ordinary Germans got led to do terrible things and there's what there are also studies of the resistance some heroic people in the white rose group for example who resisted even though they knew they were likely to die for it but I don't know whether these studies really can answer your larger question of how many people would have been capable of doing that well sort of the reason I think it's interesting is in the world as you described you know when when there are things that you'd like to do they're good that are objectively good it's useful to think about whether I'm not willing to do something or I don't even I'm not willing to acknowledge something as good and the right thing to do because I'm simply scared of putting my life of damaging my life in some kind of way and that kind of thought exercise is helpful to understand what is what is the right thing in my current skill set and the capacity to do so if there's things that are convenient and there's I wonder if there are things that are highly inconvenient where I would have to experience derision or hatred or or death or all those kinds of things but it's truly the right thing to do and that kind of balance is I feel like in America we don't have it's it's difficult to think in the current times it seems easier to put yourself back in history when you can sort of objectively contemplate whether how willing you are to do the right thing when the cost is high true but I think we do face those challenges today and I think we can still ask ourselves those questions so one stand that I took more than 40 years ago now was to stop eating meat become a vegetarian at a time when you hardly met anybody who was a vegetarian or if you did they might have been a Hindu or they might have had some weird theories about meat and health and I I know thinking about making that decision I was convinced that it was the right thing to do but I still did have to think how all my friends are going to think that I'm a crank because I'm now refusing to eat meat so you know I'm not saying there were any terrible sanctions obviously but I thought about that and I guess I decided well I still think this is the right thing to do and if I'll put up with that if it happens and one or two friends were clearly uncomfortable with that decision but you know that was pretty minor compared to the historical examples that we've been talking about but other issues that we have around too like global poverty and what we ought to be doing about that is is another question where people I think can have have the opportunity to take a stand on what's the right thing to do now climate change would be a third question where again people are taking a stand over you know look at great Atun Berg there and say well I think it must have taken a lot of courage for a school girl to say I'm going to go on strike about climate change and see what happened yeah especially in this divisive world she gets exceptionally huge amounts of support and hatred both there's a very difficult for teenager to operate in in your book ethics in the real world amazing book people should check it out very easy read eighty two brief essays on things that matter one of the essays asks should robots have rights you've written about this so let me ask sure robots have rights if we ever develop robots capable of consciousness capable of having their own internal perspective on what's happening to them so that their lives can go well or badly for them then robots should have rights until that happens they shouldn't so its consciousness essentially a prerequisite to suffering so everything that possesses consciousness is capable of suffering put another way and if so what is consciousness I certainly think that consciousness is a prerequisite for suffering you can't suffer if you're not kind but is it true that every being is conscious will suffer or has to be capable of suffering I suppose you could imagine a kind of consciousness especially if we can construct it out officially that's capable of experiencing pleasure but just automatically cuts out the consciousness when when they're suffering sort of like you know instant anesthesia as soon as something is going to cause you suffering so that's possible but doesn't exist as as far as we know on this planet yet if you asked what is consciousness philosophers often talk about it as their being a subject of experiences so you and I and everybody listening to this is a subject of experience there is a conscious subject who is taking things in responding to it in various ways feeling good about it feeling bad about it and that's different from the kinds of artificial intelligence we have now I take out my phone I ask Google directions to where I'm going Google gives me the directions and I choose to take a different way you know Google doesn't care it's not like I'm offending Google or anything like that there is no subjective experiences there and I think that's the indication that Google day I we have now is is not conscious or at least that level of AI is not conscious and that's the way to think about it now it may be difficult to tell of course whether a certain eye eye is or isn't conscious it may mimic consciousness and we can't tell if it's only mimicking it or if it's the real thing but that's what we're looking for is there a subjective experience a perspective on the world from which things can go well or badly from that perspective so our idea what Cocteau of what suffering looks like comes from our just watching our selves when we're in pain sort of oh when we're experiencing pleasure it's not only a pleasure and pain yes yes so and then you could actually back on us but I would say that's how we kind of build an intuition about animals is we can infer the similarities between humans and animals and so infer that they're suffering or not based on certain things and they're conscious or not so what if robots you mentioned Google Maps and I've done this experiment so I work in robotics just from my own self or I have several Roomba robots and I play with different speech interaction voice based interaction and if the Roomba or the robot or Google Maps shows any signs of pain like screaming or moaning or being displeased by something you've done that in my mind I can't help but immediately upgrade it and even when I myself programmed it in just having another entity that's now for the moment disjoint from me showing signs of pain makes me feel like it is conscious like I immediately and then the whatever the I immediately realize it's not obviously but that feeling is there so sort of I guess I guess what do you think about a world where Google Maps and rope rumbas are pretending to be conscious and we descendants of apes are not smart enough to realize it or not or or whatever or that is conscious they appear to be conscious and so you then have to give them rights the reason I'm asking that is that kind of capability may be closer than then we realize yes that kind of capability may be closer but I don't think it follows that we have to give them rights I suppose the the argument for saying that in those circumstances we should give them rights is that if we don't we'll harden ourselves against other beings who are not robots and who really do suffer that's a possibility that you know if we get used to looking at a being suffering and saying man we don't have to do anything about that that being doesn't have any rights maybe we'll feel the same about animals for instance and interestingly among philosophers and thinkers who denied that we have any direct duties to animals and this includes people like Thomas Aquinas and Immanuel Kant they did say yes but still it's better not to be cruel to them not because of the suffering we're inflicting on the animals but because if we are we may develop a cruel disposition and this will be bad for humans you know because we were more likely to be cruel to other humans and that would be wrong so but you don't accept that kahin I don't accept that as a the basis of the argument for why we shouldn't be cruel to animals I think the basis of the argument for why we shouldn't be cruel to animals is just that we're inflicting suffering on them and the suffering is a bad thing but possibly I might accept some sort of parallel of that argument as a reason why you shouldn't be cruel to these robots that mimic the symptoms of pain if if it's gonna be harder for us to distinguish I would venture to say I'd like to disagree with you and what most people I think at the risk of sounding crazy I would like to say that if that Roomba is dedicated to faking the consciousness in the suffering I think we will it will be impossible for us I would I would like to apply the same arguments with animals to robots that they deserve rights in that sense now we might outlaw the addition of those kinds of features into rumors but once you do I think I'm quite surprised by the upgrade in consciousness that the display of suffering creates it's a totally open world but I'd like to just sort of the difference between animals and other humans is that in the robot case we've added it in ourselves therefore we can say something about the how real it is but I would like to say that the display of it is what makes it real and there's some I'm not a philosopher I'm not making that argument but at least like to add that as a possibility and I've been surprised by it is all I'm trying to sort of inoculate poorly I suppose so there is a philosophical view has been held about humans which is rather like what you're talking about and that's behaviorism so behaviorism was employed both in psychology people like BF Skinner was a famous behaviorist but in psychology it was more a kind of a what is it that makes this science well you need to have behavior because that's what you can observe you can't observe consciousness but in philosophy the view defended by people like Gilbert Ryle who was a professor of philosophy at Oxford wrote a book called the concept of mind in which you know in this kind of phase this is in the 40s of linguistic philosophy he said well the meaning of a term is its use and we use terms like so-and-so is in pain when we see somebody writhing or screaming or trying to escape some stimulus and that's the meaning of the term so that's what it is to be in pain and you point to the behavior and Norman Malcolm who was another philosopher in the school from Cornell had had the view that you know so what is it to dream after all we can't see other people's dreams well when people wake up and say I just had a dream of you know here I was undressed walking down the Main Street or whatever it is you've dreamt that's what it is to have a dream it's to basically to wake up and recall something so you could apply this to to what you're talking about and say so what it is to be in pain is to exhibit these symptoms of pain behavior and therefore these robots are in pain that's what the word means but nowadays not many people think that riles kind of philosophical behaviorism is really very plausible so I think they would say the same about your view so yes I'd just spoken with Noam Chomsky who basically was part of dismantling the behaviorist but and I'm with that 100% for studying human behavior but I am one of the few people in the world who has made Roombas scream in pain and I just don't know what to do with that empirical evidence because it's hard it's sort of philosophically I agree but the only reason I philosophically agree in that case is because that was the programmer but if somebody else was a programmer I'm not sure I would be able to interpret that wall so it's uh I think it's a new world that I was just curious what your thoughts are for now you feel that the display of the what we can kind of intellectual say is a fake display of suffering is not suffering that's right that would be my view but that's consistent of course with the idea that it's part of our nature to respond to this display if it's reasonably authentically done and therefore it's understandable that people would feel this and maybe as I said it's even a good thing that they do feel it and you wouldn't want to harden yourself against it because then you might harden yourself against beings who are really suffering but there's this line you know so you said once a artificial general intelligence system a human level intelligence system become conscious I guess if I could just linger on it now I've wrote really dumb programs they just say things that I told them to say but how do you know when oh when a system like Alexa was just officially complex you can introspect to how it works starts giving you signs of consciousness through natural language that there's a there's a feeling there's another entity there that's self-aware that has a fear of death immortality but as awareness of itself that we kind of associate with other living creatures it I guess I'm sort of trying to do the slippery slope from the very naive thing where I started into into something where it's sufficiently a black box to where it's starting to feel like it's conscious it wears that threshold or you would start getting uncomfortable well the idea of robot suffering do you think I don't know enough about the programming that we're going to this really to answer this question but I presume that somebody who does know more about this could could look at the program and see whether we can explain the behaviors in a harmonious way that doesn't require us to suggest that some sort of consciousness has emerged or alternatively whether you're in a situation where you say I don't know how this is happening I the program does generate a kind of artificial general intelligence which is autonomous you know starts to do things itself and is autonomous of the basic programming that set it up and so it's quite possible that actually we have achieved consciousness in a system of artificial intelligence sort of the the approach to that worker that most of the community is really excited about now is with learning methods so machine learning and the learning methods are unfortunately are not capable of revealing which is why somebody like Noam Chomsky criticizes them you've created our philosophy the science of how it works and so it's possible if those are the kinds of methods that succeed we won't be able to know exactly sort of try to reduce try to find whether there is this thing is conscious or not this thing is IntelliJ or not it's simply giving when we talk to it it displays wit and humor and cleverness and emotion and fear and then we won't be able to say we're in the billions of nodes new in this artificial neural network is is the fear coming from sort of in that case that's a really interesting place where we do now start to return to behaviorism and say yeah that's that's there isn't an interesting issue I would say that if we have serious doubts and think it might be conscious then we ought to try to give it the benefit of the doubt just as I would say with animals we I think we can be highly confident that vertebrates are conscious but when we get that and and some invertebrates like the octopus but but with insects it's much harder to be to be confident of that I think we should give them the benefit of the doubt where we can which means you know I think would be wrong to torture an insect but this doesn't necessarily mean it's wrong to slap a mosquito that's about to bite you and stop you getting to sleep so I think you you try to achieve some balance in these circumstances of uncertainty if it's okay with you if we can go back just briefly so forty four years ago like you mentioned forty plus years ago you've heard an animal liberation the classic book that started that launched was a foundation of the movement of animal liberation deep can you summarize the key set of ideas that underpin netbook certainly the the key idea that underlies that book is the concept of speciesism which i did not invent that term I took it from a man called Richard Ryder who was in Oxford when I was and I saw a pamphlet that he'd written about experiments on chimpanzees that used that term but I think I contributed to making it philosophically more precise and to getting it into a broader audience and the idea is that we have a bias or a prejudice against taking seriously the interests of beings who are not members of our species just as in the past Europeans for example had a bias against taking Syria the interests of Africans racism and men have had a bias against taking seriously the interests of women sexism so I think something analogous not completely identical but something analogous goes on and has gone on for a very long time with the way humans see themselves visibly animals we see ourselves as more important we see animals as existing to serve our needs in various ways and you can find this very explicit in earlier philosophers from Aristotle through the Kant others and either we don't need to take their interests into account at all or we can discount it because they're not humans they can a little bit but they don't count nearly as much as humans do my book I use that that attitude is responsible for a lot of the things that we do to animals that are wrong confining them indoors in very crowded cramped conditions in factory farms to produce meat or eggs or milk more cheaply using them in some research that's by no means essential for survival or well-being and a whole lot you know some of the sports and things that we do to animals so I think that's unjustified because I think the significance of pain and suffering does not depend on the species of the being who is in pain or suffering any more than it depends on the race or sex with the being who is in pain or suffering and I think we ought to rethink our treatment of animals along the lines of saying if the pain is just as great in animal and it's just as bad that it happens as if it were a human maybe if I could ask I apologize hopefully it's not a ridiculous question but so as far as we know we cannot communicate with animals to a natural language but we would be able to communicate with robots so I'm returning just of a small parallel between perhaps animals in the future of AI if we do create nature a system or as we approach creating that age a system what kind of questions would you ask her to try to to try to intuit whether whether there is consciousness whether or more importantly whether there's capacity to suffer I might ask the AGI what she was feeling well does she have feelings and if she says yes to describe those feelings to describe what they were like to see what the phenomenal account of consciousness is like that's one question I might also try to find out if the AGI has a sense of itself so for example the idea would you you know we often ask people so suppose you're in a car accident and your brain were transplanted into someone else's body do you think you would survive or would it be the person whose body was still surviving you know your body having been destroyed and most people say I think I would you know if my brain was transplanted along with my memories and so on I would survive so we could ask Adi those kinds of questions if they were transferred to a different piece of hardware would they survive what would survive that effect so it's sort of on that line another perhaps absurd question but do you think having a body is necessary for consciousness so do you think digital beings can suffer presumably digital beings need to be running on some kind of hardware right yes it ultimately boils down to but this is exactly we just said is moving the brain right one place so you couldn't move it to a different kind of highway you know and I could say look you know your hardware is needs getting worn out we're going to transfer you to a fresh piece of hardware so we kind of shut you down for a time but don't worry you know you'll be running very soon on a nice fresh piece of hardware and you could imagine this conscious AG are saying that's fine I don't mind having a little rest just make sure you don't lose me like that yeah I mean that's an interesting thought that even with us humans the suffering is in the software we right now don't know how to repair the hardware yeah but we're learning we're getting better at it and better and the idea I mean a lot of some people dream about one day being able to transfer certain aspects of the software to another piece of hardware what do you think just on that topic there's been a lot of exciting innovation in brain computer interfaces I don't know if you're familiar with the companies like neural link with Elon Musk communicating both ways from a computer being able to send activate neurons and being able to read spikes from neurons with it with the dream of being able to expand sort of increase the bandwidth of which your brain can like look up articles on Wikipedia I don't think expanding kept in the knowledge capacity of the brain do you think that notion is is that interesting to you as the expansion of the human mind yes that's very interesting I'd love to be able to have that increased bandwidth and I you know if I want better access to my memory I have to say to is yet older you know you I talked to my wife about things that we did 20 years ago or something her memory is often better about particular events where were we who was at that event what did he or she where even she may know and I have not the faintest idea about this but perhaps it's somewhere in my memory and if I had at this extended memory I could I could search that particular year and rerun those things I think that would be great in some sense we already have that by storing so much of our data online like pictures of different yes well Gmail is fantastic for that because you know people people email me as if they know me well yeah I haven't got a clue who they are but then I search for their name email me in 2007 and I know who they are now yeah so we already do it taking the first steps already so on the flip side of AI people x2 Russell and others focus on the control problem value alignment in AI which is the problem of making sure we build systems that align to our own values or ethics do you think sort of high level how do we go about building systems do you think is it possible that align with our values align with our human ethics or living being ethics presumably it's it's possible to do that I know that lot of people who think that there's a real danger that we won't that will more or less accidentally lose control of of AGI yeah laughs hear yourself personally I'm not quite sure what to think I talk to philosophers like Nick Bostrom and Toby Ord and they think that this is a real problem where you need to worry about then I talk to people who work for Microsoft or deepmind or somebody and I say no we're not really that close to producing a gr you know super intelligence so if you look at Nick Bostrom's of the arguments it's very hard to defend some of course and I myself engineer I a system so I'm more with the deep mind folks were it seems that we're really far away but then the counter-argument is is there any fundamental reasonable that we'll never achieve it and if not and eventually there will be a dire existential risk so we should be concerned about it and do you have give define that argument at all appealing in this domain or any domain that eventually this will be a problem so we should be worried about it yes I think it's a problem I think there's that's a valid point of course when you say eventually that raises the question how far off is that and is there something that we can do about it now because if we're talking about this is going to be a hundred years in the future and you consider how rapid our knowledge of artificial intelligence has grown in the last 10 or 20 years it seems unlikely that there's anything much we could do now that would influence whether this is going to happen a hundred years in the future you know people in 80 years in the future would be in a much better position to say this is what we need to do to prevent this happening then than we are now so to some extent I find that reassuring but I'm all in favor of some people doing research into this to see if indeed it is that far off or if we are in a position to do something about it sooner I'm I'm very much of the view that extinction is a terrible thing and therefore even if the risk of extinction is very small if we can reduce that risk that's something that we ought to do my disagreement with some of these people who talk about long term risks extinction risks is only about how much priority that should have is compared to present questions no such it if you look at the math of it from a utilitarian perspective if it's existential risk so everybody dies that there's a it feels like an infinity in the math equation that if that makes the math where the priority is difficult to do that if we don't know the time scale and you can legitimately argue this nonzero probability that all happened tomorrow that how do you deal with these kinds of existential risks like from nuclear war from nuclear weapons from biological weapons from I'm not sure if global warming falls into that category because global warming is a lot more gradual mm-hmm and people say it's not an existential risk because they'll always be possibilities of some humans existing farming Antarctica or wrestles in Siberia or something of that sort yeah but you don't find this of did did complete existential risks a fundamental like an overriding part of the equations of ethics I wouldn't know you know certainly if you treated as an infinity then it plays havoc with any calculations arguably we shouldn't only one of the ethical assumptions that goes into this is that the loss of future lives that is of merely possible lives of beings who may never exist at all is in some way comparable to the sufferings or deaths of people who who do exist at some point and that's not clear to me I think there's a case for saying that but I also think there's a case for taking the other view so that has some impact on it of course you might say ah yes but still if there's some uncertainty about this and the the costs of extinction are infinite then still it's gonna overwhelm and everything else but I suppose I I'm not convinced of that I'm not convinced that it's really infinite here and even Nick Bostrom in his discussion of this doesn't claim that there'll be an infinite number of lives live is he and what is a 10 to the 56th or something it's a vast number that I think he calculates this is assuming we can upload consciousness onto these you know Dilek on digital form did digital forms and therefore there'll be much more energy efficient but he calculates the amount of energy in the universe or something like that so then I was a vast but not infinite which gives you some prospect maybe of resisting some of the argument the the beautiful thing with Nick's arguments is he quickly jumps from the individual scale to the universal scale which is just awe-inspiring to think right when you think about the entirety of the span of time of the universe it's both interesting from a computer science perspective AI perspective and from an ethical perspective the idea of utilitarianism because you say what is utilitarianism utilitarianism is the ethical view that the right thing to do is the act that has the greatest expected utility where what that means is it's the act that will produce the best consequences discounted by the odds that you won't be able to produce those consequences that something will go wrong but in simple case let's assume we we have certainty about what the consequences of our actions will be then the right action is the action that will produce the best consequences is that always and by the way there's a bunch of nuanced stuff the talk with Sam Harris on this podcast on the people should go listen to it's great to think two hours of moral philosophy discussion but is that an easy calculation no it's a difficult calculation and actually there's one thing that I need to add and that is utilitarians certainly the classical utilitarians think that by best consequences we're talking about happiness and the absence of pain and suffering there are other consequentialists who are not really utilitarians who say there are different things that could be good consequences justice freedom you know human dignity knowledge they all kind as good consequences too and that makes the calculations even more difficult because then you need to know how to balance these things off if you are just talking about well-being using that term to express happiness and the absence of suffering I think that the calculation becomes more manageable in a philosophical sense it's still in practice we don't know how to do it we don't know how to measure quantities of happiness and misery we don't know how to calculate the probabilities that different actions will produce this or that so at best we can use it as a as a rough guide to different actions and one way we have to focus on the short-term consequences because we just can't really predict all of the longer-term ramifications so what about the sort of what about this the extreme suffering of very small groups sort of utilitarianism is focused on the overall aggregate right how do you would you say you yourself a utilitarian you'll find that sort of do you what do you make of the difficult ethical maybe poetic suffering of very few individuals I think it's possible that that gets overwritten by benefits to very large numbers of India I think that can can be the right answer but before we conclude that is the right us that we have to know how severe the suffering is and how that compares with the benefits so I I tend to think that extreme suffering is worse than always further if you like below the neutral level then extreme happiness or bliss is above it so when I think about the worst experience as possible and the best experience as possible I don't think of them as equidistant from neutral so like it's a scale that goes from minus 100 through zero as a neutral level to plus a hundred because I know that I would not exchange an hour of my most pleasurable experiences for an hour of my most painful experiences even I wouldn't have an hour of my most painful experiences even for two hours or ten hours of my most painful experiences did I say that correctly yeah maybe 20 hours then yeah well one what's the exchange rate oh that's the question what is the exchange rate but I think it's it can be quite high so that's why you shouldn't just assume that you know it's okay to make one person suffer extremely in order to make two people much better off it might be a much larger number but at some point I do think you should aggregate and and the result will be even though it violates our intuitions of justice and fairness whatever it might be giving priority to those who are worse off at some point I still think that will be the right thing to do yes I'm complicated nonlinear function and ask the sort of out there question is the more remote put our data out there the more we're able to measure a bunch of factors of each of our individual human lives and I guess foresee the ability to estimate well-being of without whatever we public we together collectively agree and a good object function for from a utilitarian perspective do you think it do you think it'll be possible and is a good idea to push that kind of analysis to make then public decisions perhaps with the help of AI that you know here's a tax rate here's a tax rate at which well-being will be optimized and yeah that would be great if we could if we really knew that if we could really could calculate that nobody do you think it's possible to converge towards an agreement amongst humans but towards an objective function is just a hopeless pursuit I don't think it's hopeless I think it's difficult be difficult to get converged towards agreement at least at present because some people would say you know I've got different views about justice and I think you ought to give priority to those who are worse off even though I acknowledge that the gains that the worst offer making our less than the gains that those who are sort of medium badly off could be making so we still have all of these intuitions that we we argue about so I don't think we would get agreement but the fact that we wouldn't get agreement doesn't show that there isn't a right answer there do you think who gets to say what is right and wrong do you think there's place for Ethics oversight from from the government so I'm thinking in the case of AI overseeing what is what kind of decisions they I can't make and not but also if you look at animal animal rights or rather not rights or perhaps rights but the idea is you've explored in an Animal Liberation who gets to so you eloquently beautifully write in your book that this will here you know we shouldn't do this but is there some harder rules that should be imposed or is this a collective thing would converge towards a society and thereby make the better and better ethical decisions politically I'm still a Democrat despite looking at the flaws in democracy and why it doesn't work always very well so I don't see a better option than allowing the public to vote for governments in accordance with their policies and I hope that they will vote for policies policies that reduce the suffering of animals and reduce the suffering of distant humans whether geographically distant or distant because their future humans but I recognize that democracy isn't really well set up to do that and in a sense you could imagine a wise and benevolent you know omni-benevolent leader who would do that better than democracies could but in the world in which we live it's difficult to imagine that this leader isn't going to be corrupted by a variety of influences you know we've we've had so many examples of people who've taken power with good intentions and then have ended up being corrupt and favoring themselves so I don't know if you know that's why as I say I don't know that we have a better system than democracy to make this decision well so you also discuss effective altruism which is a mechanism for going around government for putting the power in the hands of the people to donate money towards causes to help you know do you know did remove the middleman and give it directly to the to the causes they care about sort of maybe this is a good time to ask you 10 years ago wrote life you can save that's now I think available for free online that's right you can download either the ebook or the audiobook free from the life you can saved org and what are the key ideas the present in in the book the main thing I want to do in the book is to make people realize that it's not difficult to help people in extreme poverty that there are highly effective organizations now but doing this that they've been independently assessed and verified by research teams that are expert in this area and that it's a fulfilling thing to do to for at least part of your life you know we can't all be Saints but at least one of your goals should be to really make a positive contribution to the world and to do something to help people who through no fault of their own are in very dire circumstances and and living a life that is barely or perhaps not at all a decent life for a human being to live so you described a minimum ethical standard of giving what what advice would you give to people that want to be effectively altruistic in their life like live an effective altruism life there are many different kinds of ways of living as an effective altruists and if you're at the point where you're thinking about your long term career I'd recommend you take a look at a website called 80,000 hours 80,000 hours org which looks at ethical career choices and they range from for example going to work on Wall Street so that you can earn a huge amount of money and then donate most of it to effective charities to going to work for a really good nonprofit organization so that you can directly use your skills and ability and hard work to further a good cause or perhaps going into politics may be small chances but because I off sin in politics go to work in the public service where if you're talented you might rise to a higher level where you can influence decisions do research in an area where the payoff could be great there are a lot of different opportunities but too few people are even thinking about those questions they're just going along in some sort of preordained rut to particular careers maybe they think they land a lot of money and have a comfortable life but they may not find that as fulfilling as actually knowing that they're making a positive difference to the world what about in terms of so that's like long-term $80,000 sure a shorter term giving part of well actually it's a part of that and go to Walker work at Wall Street if you would like to give a percentage of your income you talk about life you can save that I mean is it I was looking through it's quite a compelling it's I mean I'm just a dumb engineer so I like there's simple rulz okay so I do actually set out suggested levels of giving because people often ask me about this a popular answer is give 10% the traditional tithe that's recommended in Christianity and also Judaism but you know why should it be the same percentage irrespective of your income tax scales reflect the idea that the more income you have the more you can pay tax and I think the same is true in what you can give so I I do set out a progressive donor scale which starts out at 1% for people on modest incomes and rises to 33 and a third percent for people who are really earning a lot and my idea is that I don't think any of these amounts really impose real hardship on on people because they are progressive and geared to income so I think anybody can do this and can know that they're doing something significant to play their part in reducing the huge gap between people in extreme poverty in the world and people living effluent lives and aside from it being an ethical life it's 1 Nephi more fulfilling because like there's something about our human nature that or some of our human nature's maybe most of our human nature that enjoys doing the the ethical thing yes I make both those arguments that it it is an ethical requirement and like kind of world we live in today to help people in great need when we can easily do so but also that it is a rewarding thing and there's good psychological research showing that people who give more tend to be more satisfied with their lives and I think this has something to do with with having a purpose that's larger than yourself and therefore never being if you like never never being bored sitting around oh you know what will I do next I've got nothing to do in a world like this there are many good things that you can do and enjoy doing them plus you're working with other people in the effective altruism movement forming a community of other people with similar ideas and they tend to be interesting thoughtful and good people as well and having friends of that sort is another big contribution to having a good life so we talked about big things that are beyond ourselves but we where we're also just human and mortal do you ponder your own mortality is there insights about your philosophy the ethics that you gain from pondering your own mortality clearly you know as you get into your 70s you can't help thinking about your own mortality but I don't know that I have great insights into that from my philosophy I don't think there's anything after the death of my body assuming that we won't be able to upload my mind into anything at the time when I die so I don't think there's any afterlife or anything to look forward to in that sense we fear death so if you look at Ernest Becker and describing the motivating aspects of the our ability to be cognizant of our mortality do you have any of those elements in your driving your motivation life I suppose the fact that you have only a limited time to achieve the things that you want to achieve gives you some sort of motivation to get going and achieving them and if we thought very mortal we might say you know I can put that off for another decade or two so there's that about it but otherwise you know no I'd rather have more time to do more I'd also like to be able to see how things go that I'm interested in you know his climate change gonna turn out to be as dire as a lot of scientists say that it is is going to be will we somehow scrape through with less damage than we thought I'd really like to know the answers to those questions but I guess I'm not going to well you said there's nothing afterwards so let me ask the even more absurd question what do you think is the meaning of it all I think the meaning of life is the meaning we give to it I don't think that we were brought into the universe for any kind of larger purpose but given that we exist I think we can recognize that some things are objectively bad extreme suffering is an example and other things are objectively good like having a rich fulfilling enjoyable pleasurable life and we can try to do our part in reducing the bad things and increasingly good things so one way the meaning is to do a little bit more of the good things objectively good things and a little bit less of the bad things yes or do as much of the good things as you can and there's little of the bad things either beautifully put I don't think there's a better place to end it thank you so much for talking today thanks very much like it's been really interesting talking to you thanks for listening to this conversation with Peter Singer and thank you to our sponsors cash app and master class please consider supporting the podcast by downloading cash app and use the code lex podcast and signing up at master class comm / flex click the links buy all the stuff it's the best way to support this podcast and the journey i'm on my research and startup if you enjoy this thing subscribe on youtube review it with 5,000 type of podcast support on patreon or connect with me on Twitter Alex Friedman spelled without the e just Fri D ma N and now let me leave you with some words from Peter Singer what one generation finds ridiculous the next accepts and the third shudders when looks back with the first dead thank you for listening and hope to see you next time you |
Matt Botvinick: Neuroscience, Psychology, and AI at DeepMind | Lex Fridman Podcast #106 | the following is a conversation with Matt Botvinnik director of neuroscience research deep mind he's a brilliant cross-disciplinary mind navigating effortlessly between cognitive psychology computational neuroscience and artificial intelligence quick summary of the ads to sponsors the Jordan Harbinger show and magic spoon cereal please consider supporting the podcast by going to Jordan Harbinger complex and also going to magic spoon complex and using collects a check out after you buy all of their cereal click the links buy the stuff it's the best way to support this podcast and journey I'm on if you enjoy this podcast subscribe on youtube review it with five stars set up a podcast follow on Spotify support on patreon or connect with me on Twitter at Lex Friedman spelled surprisingly without the e just Fri D M a.m. as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this episode is supported by the Jordan Harbinger show go to Jordan Harbinger complex it's how he knows I sent you on that page subscribe to his podcast an apple podcast Spotify and you know where to look I've been binging on his podcast Jordan is a great interviewer and even a better human being I recently listened to his conversation with Jack Barsky former sleeper agent for the KGB in the 80s and author of deep undercover which is a memoir that paints yet another interesting perspective on the Cold War era I've been reading a lot about the Stalin and then Gorbachev impudent errors of Russia but this conversation made me realize that I need to do a deep dive into the Cold War era to get a complete picture of Russia's recent history again go to Jordan Harbinger complex subscribe to his podcast that's how he knows I sent you it's awesome you won't regret it this episode is also supported by magic spoon barb keto friendly super amazingly delicious 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for you you won't regret it and now here's my conversation with Matt Botvinnik how much of the human brain do you think we understand I think we're at a weird moment in the history of neuroscience in the sense that there's a there I feel like we understand a lot about the brain at a very high level but a very very coarse level when you say high level what are you thinking you thinking functional yeah structurally so in other words what is what is the brain for you know what what what kinds of computation does the brain do you know what kinds of behaviors would we have - would we have to explain if we were going to look down at the mechanistic level and at that level I feel like we understand much much more about the brain than we did when I was in high school but what but it's at a very it's almost like we're seeing it a fog it's only at a very coarse level we don't really understand what the the neuronal mechanisms are that underlie these computations we've gotten better at saying you know what are the functions that the brain is computing that we would have to understand you know if we were going to get down to the neuronal level and at the other end of the spectrum we you know in the last few years incredible progress has been made in terms of technologies that allow us to see you know actually literally see in some cases what's going on at the the single unit level even the dendritic level and then there's this yawning gap in between oh that's interesting so it's a high level so there's almost a cognitive science yeah yeah and then at the neuronal level that's neurobiology and neuroscience yeah just studying single neurons the the the the synaptic connections and all the dopamine all the kind of new transmitters one blanket statement I should probably make is that as I've gotten older I have become more and more reluctant to make a distinction between psychology and neuroscience to me the point of neuroscience is to study what the brain is for if you if you if you're if you're a nephrologist and you want to learn about the kidney you start by at by saying what is this thing for well it seems to be for taking blood on one side that has metabolites in it that are that shouldn't be there sucking them out of the blood while leaving the good stuff behind and then excreting that in the form of urine that's what the kidney is for it's like obvious so the rest of the work is deciding how it does that and this it seems to me is the right approach to take to the brain you say well what is the brain for the brain as far as I can tell is for producing behavior it's from going it's for going from perceptual inputs to behavioral outputs and the behavioral output should be adaptive so that's what psychology is about it's about understanding the structure of that function and then the rest of neuroscience is about figuring out how those operations are actually carried out at a mechanistic level it's really interesting but so unlike the kidney the the brain the the gap between the electrical signal and behavior so you truly see neuroscience as the science oh that that touches behavior how the brain generates behavior or how the brain converts raw visual information into understanding like and it's like you you basically see cognitive science psychology and neuroscience is all one science yeah is that a personal statement I said I'm hopeful is that is that a hopeful or a realistic statement so certainly you will be correct in your feeling in some number of years but that number of years could be two hundred three hundred years from now oh well there's a is that aspirational or is that a pragmatic engineering feeling that you have it's it's both in the sense that this is what I hope and expect will bear fruit over the coming decades but it's also pragmatic in the sense that I'm not sure what we're doing in either in either psychology or neuroscience if that's not the framing I don't I don't I don't know what it means to understand the brain if there's no if part of the enterprise is not about understanding the behavior that's being produced I mean yeah but out I would have compared to maybe astronomers looking at the movement of the planets and the stars and without any interest of the underlying physics right and I would argue that there at least in the early days there are some valued is just tracing the movement of the planets and the stars without thinking about the physics too much because it's such a to start thinking about the physics before you even understand even the basic structural elements of oh I agree with that I agree what you're saying in the end the goal should be yeah deeply understand well right and I I think so I thought about this a lot when I was in grad school because a lot of what I studied in grad school was psychology and I found myself a little bit confused about what it meant to it seems like what we were talking about a lot of the time were virtual causal mechanisms like oh well you know attentional selection then selects some object in the environment and that is then passed on to the motor you know information about that is passed on to the motor system but these are these are virtual mechanisms these are you know they're metaphors they're you know that there's no they're not there's no reduction - there's no reduction going on in that conversation to some physical mechanism that you know or which is really what it would take to fully understand you know how how behavior is arising but the causal mechanisms are definitely neurons interacting I'm willing to say that at this point in history so in psychology at least for me personally there was this strange insecurity about trafficking in these metaphors you know which we're supposed to explain the the function of the mind if you can't ground them in physical mechanisms then what you know you know what is the what is the explanatory validity of these explanations and I I managed to I managed to soothe my own nerves by thinking about the history of genetics research so I'm very far from being an expert on the history of this field but I know enough to say that you know Mendelian genetics preceded you know Watson and Crick and so there was a significant period of time during which people were you know continued productively investigating the structure of inheritance using what was essentially a metaphor of gene you know and no genes do this and genes do that but you know where the genes they're they're sort of an explanatory thing that we made up and we we ascribed to them these causal property so there's a dominant there's a recessive and then then they recombine and and and then later there was a kind of blank there that was filled in with it with a with a physical mechanism that connection was made in but it was worth having that metaphor because that's that gave us a good sense of what kind of cause what kind of causal mechanism we were looking for and the fundamental metaphor of cognition you said is the interaction of neurons is that what is the metaphor no no the metaphor the the metaphors we use in in in cognitive psychology are you know things like attention way that memory works you know I I retrieve something from memory right you know a memory retrieval occurs what is the Hat you know that's not that's not a physical mechanism that I can examine in its own right but if we if but it's still worth having that that metaphorical level yeah so yeah I misunderstood actually so the higher level abstractions is the metaphor that's most useful yes but but what about so how does that connect to the the idea that that arises from interaction of neurons well even it is the interaction of neurons also not a metaphor to you is or is it literally like that's no longer a metaphor that's that's already that's already the lowest level of abstractions that could actually be directly studied well I'm hesitating because I think what I want to say could end up being controversial so what I want to say is yes the interaction of the interactions of neurons that's not metaphorical that's a physical fact that's that's where that's where the causal interactions actually occur now I suppose you could say well you know even is metaphorical relative to the quantum events that underlie yes you know I don't want to go down that rabbit hole so is turtles on top potatoes but there is it there isn't there's a reduction that you can do you can say these psychological phenomena are can be explained through a very different kind of causal mechanism which has to do with neurotransmitter release and and so what we're really trying to do in neuroscience writ large you know as I say which for me includes psychology is to take these psychological phenomena and map them on to neural events I think remaining forever at the level of description that is natural for psychology for me personally would be disappointing I want to understand how mental activity arises from neural neural activity but the converse is also true studying neural activity without any sense of what you're trying to explain to me feels like at best groping around you know at random now you've kind of talked about this bridging at the gap between psychology in neuroscience but do you think it's possible like my love is like I fell in love with psychology and psychiatry in general with Freud and when I was really young and I hope to understand the mind and for me understanding the mind at least at a young age before I discovered AI and even neuroscience was to his psychology and do you think it's possible to understand the mind without getting into all the messy details of neuroscience like you kind of mentioned to you it's appealing to try to understand the mechanisms at the lowest level but do you think that's needed that's required to understand how the mind works that's an important part of the whole picture but I would be the last person on earth to suggest that that reality renders psychology in its own right unproductive I trained as a psychologist I I am fond of saying that I have learned much more from psychology than I have from neuroscience to me psychology is a hugely important discipline and and one thing that worms in my heart is that ways of ways of investigating behavior that have been native to cognitive psychology since its you know dawn in the 60s are starting to become they're starting to become interesting to AI researchers for a variety of reasons and that's been exciting for me to see can you maybe talk a little bit about what's what you see is beautiful aspects of psychology maybe limiting aspects of psychology I mean maybe just started off as a science as a field to me was when I understood what psychology is analytical psychology like the way it's actually carried out is really disappointing to see two aspects one is how few how small the end is how many how small the number of subject is in the studies and two was disappointing to see how controlled the entire how how much it was in the lab how it wasn't studying humans in the wild there's no mechanism for studying humans in a while so that's where I became a little bit disillusioned into psychology and then the modern world of the Internet is so exciting to me the Twitter data or YouTube daily data of human behavior on the Internet becomes exciting because then the N grows and then in the wild girls but that's just my narrow sense they give us optimistic or pessimistic cynical view of psychology how do you see the field broadly when I was in graduate school it was early enough that there was still a thrill in seeing that there were ways of doing there were ways of doing experimental science that provided insight to the structure of the mind one thing that impressed me most when I was at that stage in my education was neuropsychology looking at looking at the analyzing the behavior of populations who had brain damage of different kinds and trying to understand what what the what the specific deficits were that arose from a lesion in a particular part of the brain and the the kind of experimentation that was done and that's still being done to get answers in that context was so creative and it was so deliberate you know the it was good science an experiment answered one question but raised another and somebody would do an experiment that answered that question and you really felt like you were narrowing in on some kind of approximate understanding of what this part of the brain was for do you have an example of the memory of what kind of aspects of the mind could be studied in this kind of way oh sure I mean the very detailed neuropsychological studies of language language function looking at production and reception and the relationship between you know visual function you know reading and auditory and semantic and I mean there were these beauty and still are these beautiful models that came out of that kind of research that really made you feel like you understood something that you hadn't understood stood before about how you know language processing is organized in the brain but having said all that you know I I think you know I think you are I mean I agree with you that the cost of doing highly controlled experiments is that you by construction miss out on the richness and complexity of the real world one thing that so I I was drawn into science by what in those days was called connectionism which is of course that you know what we now called deep learning and at that point in history neural networks were primarily being used in order to model human cognition they weren't yet really useful for industrial applications so you always fall in neural networks in biological form beautiful Oh neural networks were very concretely the thing that drew me into science I was handed are you familiar with the the PDP books from from the 80s some when I was in I went to medical school before I went into science and really yeah this thing Wow I also I also did a graduate degree in art history so I'm I kind of explored well art history I understand there's just a curious creative mind but medical school with the dream of what if we take that slight tangent what did you what did you want to be a surgeon I actually was quite interested in surgery I was I was interested in surgery and psychiatry and I thought that must be I must be the only person on the planet who had who was torn between those two fields and III said exactly that to my advisor in medical school who turned out I found out later to be a famous psychoanalyst and and he said to me no no it's actually not so uncommon to be interested in surgery and psychiatry and he conjectured that the reason that people develop these these two interests is that both fields are about going beneath the surface and kind of getting into the kind of secret yeah I mean maybe you understand this as someone who was interested in psychoanalysis and or the stage there's sort of a this you know there's a cliche phrase that people use now on you know like an NPR The Secret Life of Bees like right yeah you know and that was part of the thrill of surgery was seeing you know the secret you know the secret activity that's inside everybody is abdomen and thorax it's a very poetic way to connect it to disciplines that are very practically speaking different each other that's for sure that's for sure yes so so how do we get on to medical school so so I was in medical school and I I was doing a psychiatry rotation and my kind of advisor in that rotation asked me what I was interested in and I said well maybe psychiatry he said why and I said well I've always been interested in how the brain works I'm pretty sure that nobody's doing scientific research that addresses my interests which are I didn't have a word for it then but I would have said about cognition and he said well you know I'm not sure that's true you might you might be interested in these books and he pulled down the the PDB books from his shelf and they were still shrink-wrapped he hadn't read them but he handed to me a hint that inform you said he you can you feel free to borrow these and that was you know I went back to my dorm room and I just you know read them cover to cover and what's PDP parallel distributed processing which was the one of the original names for deep learning and so I apologize for the romanticized question but what what idea in the space of neural size in the space of the human brain is to use the most beautiful mysterious surprising what what had always fascinated me even when I was a pretty young kid I think was the the the paradox that lies in the fact that the brain is so mysterious and so it seems so distant but at the same time it's responsible for the the the the full transparency of everyday life it's the brain is literally what makes everything obvious and familiar and and and there's always one in the room with you yeah I I used to teach when I taught at Princeton I used to teach a cognitive neuroscience course and the very last thing I would say to the students was you know people often when people think of scientific inspiration the the metaphor is often we'll look to the stars you know the stars will inspire you to wonder at the universe and and you know think about your place in it and how things work and and I'm all for looking at the stars but I've always been much more inspired and my sense of wonder comes from the not from the distant mysterious stars but from the extremely intimately close brain yeah there's something just endlessly fascinating to me about that the like just like you said the the one is close and yet distant in in terms of our understanding of it do you are you all so captivated by the the fact that this very conversation is happening because two brains are communicating the I guess what I mean is the subjective nature of the experience if can take a small taejun into the the mystical of it the unconsciousness or or when you are saying you're captivated by the idea of the brain you are you talking about specifically the mechanism of cognition or are you also just like at least for me it's almost like paralyzing the beauty and the mystery of the fact that it creates the entirety of the experience not just the reasoning capability but the experience well I I definitely resonate with that that latter thought and I I often find discussions of artificial intelligence to be disappointingly narrow you know speaking of someone who has always had an interest in in in art great it was just gonna go there cuz it sounds like somebody who has an interest in art yeah I mean I there there there there are many layers to you know to full-bore him and experience and and in some ways it's not enough to say oh well don't worry you know we're talking about cognition but we'll add emotion you know yeah there's there's there's an incredible scope to what humans go through in in every moment and and yes so it's that's part of what fascinates me is that is that our brains are producing that but at the same time it's so mysterious to us how we literally our brains are literally in our heads producing mystics and yet there and yet there's there it's so mysterious to us and so and in the scientific challenge of getting at the the the actual explanation for that is so overwhelming it's not that's just i don't know that certain people have fixations on particular questions and that's always that's just always been mine yeah I would say the poetry that is fascinating and I'm really interested in natural language as well and when you look at our personal intelligence community it always saddens me how much when you try to create a benchmark for the community together around how much of the magic of language is lost when you create that benchmark that there's something would we talk about experience the the music of the language the wit the something that makes a rich experience something that would be required to pass the spirit of the Turing test is lost in these benchmarks and I wonder how to get it back in because it's very difficult the moment you tried to do like real good rigorous science you lose some of that magic when you try to study cognition in a rigorous scientific way it feels like you're losing some of the magic mm-hmm-hmm the the seen cognition in a mechanistic way that AI vote at this stage in our history well okay I I agree with you but at the same time one one thing that I found really exciting about that first wave of deep learning models in cognition was there was the the fact that the people who were building these models were focused on the richness and complexity of human cognition so an early debate in cognitive science which I sort of witnessed as a grad student was about something that sounds very dry which is the formation of the past tense but there were these two camps one said well the the mind encodes certain rules and it also has a list of exceptions because of course you know the rule is a DB but that's not always what you do so you have to have a list of exceptions and and then there were the connectionists who you know evolved into the deep learning people who said well well you know if you look carefully at the data if you look at actually look at corpora like language corpora it's it turns out to be very rich because yes there are there are there's a you know the there most verbs that and you know you just tack on e d and then there are exceptions but there are also there's also there are there are rules that in you know there's the exceptions aren't just random they there are certain clues to which which which verbs should be exceptional and then there are some exceptions to the exceptions and there was a word that was kind of deployed in order to capture this which was quasi regular in other words there are rules but it's it's messy and there there's their structure even among the exceptions and and it would be yeah you could try to write down you could try to write down the structure in some sort of closed form but really the right way to understand how the brain is handling all this and by the way producing all of this is to build a deep neural network and trained it on this data and see how it ends up representing all of this richness so the way that deep learning was deployed in cognitive psychology was that was the spirit of it it was about that richness and that's something that I always found very very compelling still do is it is there something especially interesting and profound to you in terms of our current deep learning neural network artificial neural network approaches and the whatever we do understand about the biological neural networks in our brain is there there's some there's quite a few differences are some of them to you either interesting or perhaps profound in terms of in terms of the gap we might want to try to close in trying to create a human level intelligence what I would say here is something that a lot of people are saying which is that one seeming limitation of the systems that we're building now is that they lack the kind of flexibility the readiness to sort of turn on a dime when this when the context calls for it that is so characteristic of human behavior so is that connected to you to the like which aspect of the neural networks in our brain is that connected to is that closer to the cognitive science level of now again see like my natural inclination is to separate into three disciplines of neuroscience cognitive science and psychology and you've already kind of shut that down by saying you you're kind of see them as separate but just to look at those layers I guess where is there something about the lowest layer of the way the neural neurons interact and that is profound to you in terms of this difference to the artificial neural networks or is all the difference the key difference is at a higher level of abstraction one thing I often think about is that um you know if you take an introductory computer science course and they are introducing you to the notion of Turing machines one way of articulating what the significance of a Turing machine is is that it's a machine emulator it's it can emulate any other machine and that that to me you know that that and it was that way of looking at a deterring machine you know it really sticks with me I think of humans as maybe sharing in some of that character we're capacity limited we're not Turing machines obviously but we have the ability to adapt behaviors that are very much unlike anything we've done before but there's some basic mechanism that's implemented in our brain that allows us to run run software but you're just in that point you mentioned into a machine but nevertheless it's fundamentally our brains are just computational devices in your view is that what you're getting like is it I was a little bit unclear to this line you drew mmm is is is there any magic in there or is it just basic computation I'm happy to think of it as just basic computation but mind you I won't be satisfied until somebody explains to me how what the basic computations are that are leading to the full richness of human cognition yes I mean it's not gonna be enough for me to you know understand what the computations are that allow people to you know do arithmetic or play chess I want I want the whole whole you know the whole thing in a small tangent because you kind of mentioned coronavirus the this group behavior oh sure I is that is there something interesting to your search of understanding the human mind where law behavior of large groups of just behavior of groups is interesting you know seeing that as a collective mind as a collective intelligence perhaps seeing the groups of people as a single intelligent organisms especially looking at the reinforcement learning work mm-hm even done recently well yeah I can't I can't I mean I I have the I have the the honor of working with a lot of incredibly smart people and I wouldn't want to take any credit for for leading the way on the the multi-agent work that's come out of out of my group or deep mine lately but I do find it fascinating and I mean I think there you know I think it it can't be debated you know the human behavior arises within communities that just seems to me self-evident but to me so it is self-evident but that seems to be a profound aspects of something that created that was like if you look at like 2001 Space Odyssey when that well the monkeys touch the yeah like that's the magical moment I think Eva Hari argues that the ability of our large numbers of humans to hold an idea to converge towards idea together like you said shaking and bumping elbows somehow converge like without even like like without you know without being in a room all together just kind of this like distributed convergence towards an idea yeah over a particular period of time seems to be fundamental to to just every aspect of our cognition of our intelligence because humans I will talk about reward but it seems like we don't really have a clear objective function under which we operate but we all kind of converge towards one somehow and that that to me has always been a mystery that I think is somehow productive for also understanding AI systems but I guess I guess that's the next step the first step is trying to understand the mind well I don't know I mean I think there's something to the argument that that kind of bottom like strictly bottom-up approach is wrongheaded in other words you know there are there are basic phenomena that you know you know basic aspects of human intelligence that you know can only be understood in in the context of groups I'm perfectly open to that I've never been particularly convinced by the notion that we should be we should consider intelligence to in here at the level of communities I I don't know why I just I'm sort of stuck on the notion that the basic unit that we want to understand is individual humans and if if we have to understand that in the context of other humans fine but for me intelligence is just I'm stubbornly I stubbornly defined it as something that is you know an aspect of an individual human that's just my time with you with us that could be the reduction is dream of a scientist because you can understand a single human it also is very possible that intelligence can only arise when there's multiple intelligences when there's multiple sort of it's a sad thing if that's true because it's very difficult to study but if it's just one human that one human will not be Homo Sapien would not become that intelligent that's a real that's a possibility I I'm with you well one thing I will say along these lines is that I think I think a serious effort to understand human intelligence and maybe to build a human-like intelligence needs to pay just as much attention to the structure of the environment as to the structure of the you know the the cognizing system whether it's a brain or an AI system that's one thing I took away actually from my early studies with the pioneers of neural network research people like Jay McClelland and John Cohen you know the the structure of cognition is really it's only a only partly a function of the the you know the the architecture of the brain and the learning algorithms that it implements what it's really a function what what what really shapes it is the interaction of those things with the structure of the world in which those things are embedded right and that's especially important for this made most clear and reinforcement learning where I simulate an environment as you can only learn as much as you can simulate and that's what made well deep mine made very clear well the other aspect of the environment which is the self play mechanism of the other agent of the competitive behavior which the other agent becomes the environment essentially yeah and that's I mean one of the most exciting ideas in AI is the self play mechanism that's able to learn successfully so there you go there's a there's a thing where competition is essential for yeah earning yeah at least in that context so if we can step back into another beautiful world which is the actual mechanics the dirty mess of it of the human brain is is there something for people who might not know is there something in common or describe the key parts of the brain that are important for intelligence or just in general what are the different parts of the brain that you're curious about that you've studied and that are just good to know about when you're thinking about cognition well my area of expertise if I have one is prefrontal cortex so what's that or do we it depends on who you ask the the the the the technical definition is has is anatomical it there are there are parts of your brain that are responsible for motor behavior and they're very easy to identify and the region of your cerebral cortex they out needs sort of outer crust of your brain that lies in front of those is defined as the prefrontal cortex and when you say anatomical sorry to interrupt so that's referring to sort of the geographic region yeah as opposed to some kind of functional definition exactly so that it this is kind of the coward's way out and I'm telling you what the prefrontal cortex is just in terms of like what part of the real-estate it occupies the thing in the front of them yeah exactly and and in fact the early history of you know the neuroscientific investigation of what this like front part of the brain does is sort of funny to read because you know it was really it was really World War one that started people down this road of trying to figure out what different parts of the brain the human brain do in the sense that there were a lot of people with brain damage who came back from the war with brain damage and it that provided as tragic as that was it provided an opportunity for scientists to try to identify the functions of different brain regions and it wasn't actually incredibly productive but one of the frustrations that neuropsychologist face was they couldn't really identify exactly what the deficit was that arose from damage to this these most you know kind of frontal parts of the brain it was just a very difficult thing to you know to you know to pin down there were a couple of neuropsychologists who identified through through a large amount of clinical experience in close observation they started to put their finger on a syndrome that was associated with frontal damage actually one of them was a russian neuropsychologist named Gloria who you know students of cognitive psychology still read and and what he started to figure out was that the frontal cortex was somehow involved in flexibility the in in in guiding behaviors that required someone to override a habit or to do something unusual or to change what they were doing in a very flexible way from one moment to another so focused on like new experiences and so the so the way your brain processes and acts in new experiences yeah what later helped bring this function into better focus was a distinction between controlled and automatic behavior or - in in other literature's this is referred to as habitual behavior versus goal directed behavior so it's very very clear that the human brain has pathways that are dedicated to habits to things that you do all the time and they need to be autumn at they don't require you to concentrate too much so the that leaves your cognitive capacity freed you do other things just think about the difference between driving when you're learning to drive versus driving after you're fairly expert there are brain pathways that slowly absorb those frequently performed behaviors so that they can be habits so that they can be automatic for that that's kind of like the purest form of learning I guess it's happening there which is why I mean this is kind of jumping ahead which is why that perhaps is the most useful for us to focusing on and trying to see how artificial intelligent systems can learn is that the way it's interesting I I do think about this distinction between controlled and automatic or goal directed and habitual behavior a lot in thinking about where we are in AI research but but just to finish to finish the the kind of dissertation here the the the role of the front of the prefrontal cortex is generally understood these days sort of in in Contra distinction to that habitual domain in other words the prefrontal cortex is what helps you override those habits it's what allows you to say well what I usually do in this situation is acts but given the context I probably should do why I mean the elbow bump is a great example right if you know reaching out and shaking hands is a probably habitual behavior and it's the prefrontal cortex that allows us to bear in mind that there's something unusual going on right now and in this situation I need to not do the usual thing the kind of behaviors that Luria reported and he built tests for you know detect these kinds of things we're exactly like this so in other words when I stick out my hand I want you instead to present your elbow a patient with frontal damage would have great deal of trouble with that you know somebody preferring their hand would elicit you know a handshake the prefrontal cortex is what allows us to say oh no hold on that's the usual thing but I'm I have the ability to bear in mind even very unusual contexts and to reason about what behavior is appropriate there just to get a sense is our us humans special in the presence of the prefrontal cortex do mice have a prefrontal cortex do other mammals that we can study if you if no then how do they integrate new experiences yeah that's a that's a really tricky question and a very timely question because we have revolutionary new technologies for monitoring measuring and also causally influencing neural behavior in mice and fruit flies and these techniques are not fully available even for studying brain function in in monkeys let alone humans and so it's a it's a very sort of for me at least a very urgent question whether the kinds of things that we want to understand about human intelligence can be pursued in these other organisms and you know to put it briefly there's disagreement you know people who study fruit flies will often tell you hey root flies are smarter than you think and they'll point to experiments where fruit flies were able to learn new behaviors we're able to generalize from one stimulus to another in a way that suggests that they have abstractions that guide their generalization I've had many conversations in which I will start by observing you know recounting some some observation about Mouse behavior where it seemed like mice were taking an awfully long time to learn a task that for a human would be profoundly trivial and I will conclude from that that mice really don't have the cognitive flexibility that we want to explain and that a mouse researcher will say to me well you know hold on that experiment may not have worked because you asked a mouse to deal with stimuli and behaviors that were very unnatural for the mouse if instead you kept the logic of the experiment the same but put you know kind of put it in a you know presented it the information in a way that aligns with what mice are used to dealing with in their natural habitats you might find that a mouse actually has more intelligence than you think and then they'll go on to show you videos of mice doing things in their natural habitat which seem strikingly intelligent you know dealing with you know physical problems you know I have to drag this piece of food back to my you know back to my lair but there's something in my way and how do I get rid of that thing so I think I think these are open questions to put it you know to sum that up and then taking a small step back so related to that is you kind of mentioned we're taking a little shortcut by saying it's a geographic geographic part of the the prefrontal cortex is a region of the brain but if we what's your sense in a bigger philosophical view prefrontal cortex and the brain in general do you have a sense that it's a set of subsystems in the way we've kind of implied that are they're pretty distinct or to what degrees of that or to what degree is it a giant interconnected mess where everything kind of does everything and is impossible to disentangle them I think there's overwhelming evidence that there's functional differentiation that it's clearly not the case that all parts of the brain are doing the same thing this follows immediately from the kinds of studies of brain damage that we were chatting about before it's obvious from what you see if you stick an electrode in the brain and measure what's going on at the level of you neural activity having said that there are two other things to add which kind of I don't know maybe tug in the other direction one is that it's when you look carefully at functional differentiation in the brain what you usually end up concluding at least this is my observation of the literature is that the the differences between regions are graded rather than being discrete so it doesn't seem like it's easy to divide the brain up into true modules where you know that are you know that have clear boundaries and that have you know like like clear channels of communication between them instead lies to the prefrontal cortex yeah oh yeah yeah the prefrontal cortex is made up of a bunch of different sub regions the you know the functions of which are not clearly defined and which then the borders of which seem to be quite vague and then then there's another thing that's popping up in very recent research which you know which involves application of these new techniques which there are a number of studies that suggest that parts of the brain that we would have previously thought were quite focused in their function are actually carrying signals that we wouldn't have thought would be there for example looking in the primary visual cortex which is classically thought of as basically the first cortical way station for processing visual information basically what it should care about is you know where are the edges in this scene that I'm viewing it turns out that if you have enough data you can recover information from primary visual cortex about all sorts of things like you know what what behavior the animal is engaged in right now and what what how much reward is on offer in the task that it's pursuing so it's clear that even even regions whose function is pretty well defined at a course brain are nonetheless carrying some information about information from very different domains so you know the history of neuroscience is sort of this oscillation between the two views that you articulated you know the kind of modular view and then the big you know mush view and you know I think I guess we're gonna end up somewhere in the middle which is which is unfortunate for our understanding because the mod there's something about our you know conceptual system that finds it's easy to think about a modular AI system and easy to think about a completely undifferentiated system but something that kind of lies in between is confusing but we're gonna have to get used to it I think unless we can understand deeply the lower-level mechanism and you're all communicating yeah so yeah on that on that topic you kind of mention information just to get a sense I imagine something that there's still mystery and disagreement on is how does the brain carry information and signal like what in your sense is the basic mechanism of communication in the brain well I I guess I'm old-fashioned in that I consider the networks that we use in deep learning research to be a reasonable approximation to you know the the mechanisms that carry information in the brain so the the the usual way of articulating that is to say what really matters is a rate code it what matters is how how how quickly is an individual neuron spiking how you know what's the frequency at which it's spiking is the timing of the spike yeah is it is it firing fast or slow let's you know let's put a number on that and that number is enough to capture what what neurons are doing there's you know there's still uncertainty about whether that's an an adequate description of how information is is transmitted within the brain there you know there are there are studies that suggest that the precise timing of spikes matters there are studies that suggest that there are computations that go on within the dendritic tree within a neuron that are quite rich and structured and that really don't equate to anything that we're doing in our artificial neural networks having said that I feel like we can get I feel like I feel like we're getting somewhere by sticking to this high level of abstraction just the rate and by the way we're talking about the electrical signal that I remember reading some vague paper somewhere recently where the mechanical signal like the vibrations or something of the of the neurons also communicates and if I haven't seen that but this is there somebody was arguing that the the electrical signal this is in nature paper something like that where the electrical signal is actually a side effect of the mechanical signal but I don't think they changes the story but it's almost the interesting idea that there could be a deeper it's like it's always like in physics with quantum mechanics there's always a deeper story that could be underlying the whole thing but you think is basically the rate of spiking that gets us that's like the lowest hanging fruit that can get us really far this is a this is a classical view I mean this is this is this is not the only way in which this stance would be controversial is it you know in the sense that there are there are members of the neuroscience community who are interested in alternatives but this is really a very mainstream view the way that neurons communicate is that neurotransmitters arrive or you know at a at you know they they wash up on a neuron the neuron has receptors for those transmitters the the the the the meeting of the transmitter with these receptors changes the voltage of the neuro and if enough voltage change occurs then a spike occurs right one of these like discrete events and it's that spike that is conducted down the axon and leads to neuroses this is just this is just like neuroscience 101 this is like the way the brain is supposed to work now what we do when we build artificial neural networks of the kind that are now popular in the AI community is that we don't worry about those individual spikes we just worry about the frequency at which those spikes are being generated and the you know we consider people talk about that as the activity of a neuron and you know so the the activity of units in a deep learning system is you know broadly analogous to the spike rate of a neuron there there are people who who believe that there are other forms of communication in the brain in fact I've been involved in some research recently that suggests that the voltage the voltage fluctuations that occur in populations of neurons that aren't you know that are sort of below the level of a spike production may be important for for communication but I'm still pretty old-school in the sense that I think that the the things that we're building in AI research constitute reasonable models of how a brain would work let me ask just for fun a crazy question because I can do you think it's possible were completely wrong about the way this basic mechanism of your neuronal communication that the information is thought is some very different kind of way in the brain oh heck yes you know I would look I wouldn't be a scientist if I didn't think there was any chance we were wrong but but I mean if you look if you look at the history of deep learning research as it's been applied to neuroscience of course the vast majority of deep learning research these days isn't about neuroscience but you know if you go back to the 1980s there's a you know sort of an unbroken chain of research in in which a particular strategy is taken which is hey let's train a deep a deep learning system let's train a multi-layer neural network on this task that we trained our you know backbone or our monkey on or this human being on and then let's look at what the units deep in the system are doing and let's ask whether what they're doing resembles what we know about what neurons deep in the brain are doing and over and over and over and over that strategy works in the sense that the learning algorithms that we have access to which typically send our own back propagation they give rise to you know patterns of activity patterns of response patterns of like neuronal behavior and these in these artificial models that look haunting Lisa hauntingly similar to what you see in the brain and you know is that a commune yes incidences at a certain point it starts looking like such coincidence is unlikely to not be deeply meaningful yeah yeah that's yeah the circumstantial evidence is overwhelming but it could be always open to a total of flipping a table yeah of course so you have co-authored several recent papers that sort of weave beautifully between the world of neuroscience and artificial intelligence and this maybe if we could can we just try to dance around and talk about some of them maybe tried to pick up the interesting idea as a jump to your mind from memory so maybe looking at we're talking about the prefrontal cortex the 2018 I believe paper called the prefrontal cortex as a matter of reinforcement learning system what is there a key idea that you can speak to from that paper yeah the I mean the key idea is about meta learning so what is meta learning meta learning is by definition a situation in which you have a learning algorithm and the learning algorithm operates in such a way that it gives rise to another learning algorithm in the in the earliest applications with this idea you had one learning algorithm sort of adjusting the parameters on another learning algorithm but the case that we're interested in this paper is one where you start with just one learning algorithm and then another learning algorithm kind of emerges out of the kind of thin air I can say more about what I mean by that I don't mean to be um you know your entities but that's the idea of meta learning you you it relates to the old idea and psychology of learning to learn situations where you you you have experiences that make you better at learning something new like a group a familiar example would be learning a foreign language the first time you learn a foreign language it may be you know quite laborious and disorienting and a novel but if you let's say you've learned to two foreign languages the third foreign language obviously is going to be much easier to pick up and why because you've learned how to learn you know how this goes you know okay I'm gonna have to learn how to conjugate I'm gonna happen that's a that's a simple form of meta learning right in the sense that there's some slow learning mechanism that's giving that's helping you kind of update your fast learning mechanism that that that makes you so how from from our understand from the psychology world from neuroscience honor our understanding how meta learning works might work in the human brain what what lessons can we draw from that that we can bring into the artificial intelligence world well yeah so we the origin of that paper was in AI work that that we were doing in my group we were we were looking at what happens when you train a recurrent neural network using standard reinforcement learning algorithms but but you train that network not just in one task but you train it in a bunch of interrelated tasks and then you ask what happens when you give it yet another task in that sort of line of interrelated tasks and and what we started to realize is that a form of meta learning spontaneously happens in in recurrent neural networks and and the simplest way to explain it is to say a recurrent a recurrent neural network has a kind of memory in its activation patterns it's recurrent by definition in the sense that you have units that connect to other units that connect to other units so you have sort of loops of connectivity which allows activity to stick around and be updated over time in psychology we call in neuroscience we call this working memory it's like actively holding something in mind and and and so that memory gives the recurrent neural network of dynamics right the way that the activity pattern evolves over time is inherent to the connectivity of the recurrent neural network okay so that's that's idea number one now the dynamics of that network are shaped by the connectivity by the synaptic weights and those synaptic weights are being shaped by this reinforcement learning algorithm that you're you know training the network with so the punchline is if you train a recurrent neural network with a reinforcement learning algorithm that's adjusting its weights and you do that for long enough the activation dynamics will become very interesting right so imagine imagine I give you a task where you have to press one button or another left button or right button and some time in and there's some probability that I'm going to give you an M&M if you press the left button and there's some probability I'll give you an M&M if you press the other button and you have to figure out what those probabilities are just by trying things out but as I said before instead of just giving you one of these tasks I give you a whole sequence you know I give you two buttons and you figure out which one's best and I go good job here's here's a new box two new buttons you have to figure out which one's best good job here's a new box and every box has its own probabilities and you have to figure so if you train a neural net a recurrent neural network on that kind of sequence of tasks the what happens it seemed almost magical to us when we first started kind of realizing what was going on the slow learning algorithm that's justing the the synaptic weights though those slow synaptic changes give rise to a network dynamics that them cell that you know the dynamics themselves turn into a learning algorithm so in other words you can you can tell this is happening by just freezing the synaptic weights saying okay no more learning you're done here's a new box figure out which button is best and the recurrent neural network will do this just fine there's no like it figures out which which button is best it train it kind of transitions from exploring the two buttons to just pressing the one that it likes best in a very rational way how is that happening it's happening because the activity of the day the activity dynamics of the network have been shaped by this slow learning process that's occurred over many many boxes and so what's happened is that this slow learning algorithm that's slowly adjusting the weights is changing the dynamics of the network the activity dynamics into its own learning algorithm and as we were as we were kind of realizing that this is the thing it just so happened that the group that was working on this included a bunch of neuroscientists and it started kind of ringing a bell for us which is to say that we thought this sounds a lot like the distinction between synaptic learning and activity synaptic memory and activity based memory in the brain and it also reminded us of recurrent connectivity that's very characteristic of prefrontal function so there this is this is kind of why it's good to have people working on AI that know a little bit about neuroscience and vice-versa because we started thinking about whether we could apply this principle to neuroscience and that's where the paper came from so the kind of principle of the the recurrence they can see in the prefrontal cortex then you start to realize that is possible too for something like an idea of a learning to learn emerging from this learning process as long as you keep varying the environment sufficient zactly so so the kind of metaphorical transition we made to neuroscience was to think okay well we know that the prefrontal cortex is highly recurrent we know that it's an important locus for working memory for active activation based memory so maybe the prefrontal cortex supports reinforcement learning in other words you what is reinforcement learning you take an action you see how much reward you got you update your policy of behavior maybe the prefrontal cortex is doing that sort of thing strictly in its activation patterns it's keeping around a memory in its activity patterns of what you did how much reward you got and it's using that that activity based memory as a basis for updating behavior but then the question is well how did the prefrontal cortex get get so smart in other words how did it where did these activity dynamics come from how did that program that's implemented in the recurrent dynamics of the prefrontal cortex arise and one answer that became evident in this work was well maybe maybe the mechanisms that operate on the synaptic level which we believe are mediated by dopamine are responsible for shaping those dynamics so this may be a silly question but because this kind of several temporal of classes of learning are happening and so the learning to learn is emerges can it just can you keep building stacks of learning to learn to learn learning to learn to learn to learn to learn because it keeps I mean basically abstractions of more powerful abilities to generalize of learning complex rules yeah or is this that's over stretching the this kind of mechanism well what at one of the one of the people in AI who started thinking about meta learning from there very early on your ganancia tuber sort of cheekily suggested I think it is it may have been in his PhD thesis that we should think about meta meta meta meta meta meta learning you know that that's really that's really what's going to get us to true intelligence certainly there's a poetic aspect to it and it seems interesting and correct that that kind of level of abstraction would be powerful but is that something you see in the brain this kind of is it useful to think of learning in these meta meta meta way or is it just meta learning well one thing that really fascinated me about this mechanism that we were starting to look at and you know other groups started talking about very similar things at the same time and and then a kind of explosion of interest in metal learning happened in the AI community shortly after that I don't know if we had anything to do with that but but I was gratified to see that a lot of people started talking about meta learning one of the things that I like about the kind of flavor of meta learning that we were studying was that it didn't require anything special it was just if you took a system that had some form of memory that the function of which could be shaped by picture RL algorithm then this would just happen yes right I mean there there there are a lot of forms of there are a lot of meta learning algorithms that have been proposed since then that are fascinating and effective in in their you know in their domains of application but they're you know they're engineered they're they're things that you had to say well see if we wanted meta learning to happen how would we do that here's an algorithm that would but there's something about the kind of meta learning that we were studying that seemed to me special in the sense that it wasn't an algorithm it was just something that automatically happened if you had a system that had memory and it was trained with a reinforcement learning algorithm in and in that sense it can be as meta as it wants to be right it there's no limit on how abstract the the meta-learning can get because it's not reliant on the human engineering a particular metal learning algorithm to get there and and that's I I also I don't know I guess I hope that that's relevant in the brain I think there's a kind of beauty in the in in the ability of this emergent the emergent aspect of it yeah it's engineered exactly it's something that just it just happens in in in a sense in a sense you can't avoid this happening if you have a system that has memory and the function of that memory is shaped by reinforcement learning and this system is trained in a series of interrelated tasks this is gonna happen you can't stop it as long as you have certain properties maybe like of a current structure too you have to have memory it actually doesn't have to be a recurrent neural network when a paper that I was honored to be involved with even earlier used a kind of slot based memory you remember the title just it was memory augmented neural networks I think it what I too was meta learning in memory augmented neural networks and and you know it was the same exact story you know if you have a system with memory here it was a different kind of memory but the function of that memory is shaped by reinforcement learning here it was the root you know the reads and writes that occurred on this slot based memory this yeah this will just happen and and and so this but this brings us back to something I was saying earlier about the importance of the environment the this this will happen if the system is being trained in a setting where there's like a sequence of tasks that all share some abstract structure you know sometimes talk about tasks distributions and that's something that's very obviously true of the world that humans inhabit we're we're constantly like if you just kind of think about what you do every day you never you never do exactly the same thing that you did the day before but everything that you do is sort of has a family resemblance it shares structure with something that you did before and so you know the the real world is sort of you know saturated with this kind of this property it's an endless variety with endless redundancy and that's the setting in which this kind of meta learning happens and it does seem like we're just so good at finding just like in this emergent phenomena you describe we're really good at finding that redundancy finding those similarities the family resemblance some people call it sort of what is it Melanie Mitchell was talking about analogies so we were able to connect concepts together in in this kind of way in in this same kind of automated emergent way which if there's so many echoes here of psychology neuroscience and obviously now with reinforcement learning with recurrent neural networks at the core if we could talk a little bit about dopamine you have really you're a part of co-authoring really exciting recent paper very recent in terms of release on dopamine and temporal difference learning can you describe the key ideas of that paper sure yeah I mean one thing I want to pause to do is acknowledge my co-authors on actually both of the papers we're talking about so the this dopamine I'll just I'll certainly post all their names okay wonderful yeah as I you know I I'm sort of abashed to be the spokesperson for these papers when I had such amazing collaborators on both so it's a it's a comfort to me to know that you all have you all acknowledge that yeah it's not an incredible team there but yeah so yeah it's such a it's so much fun and and in the case of the the dopamine paper we also collaborated with now ochite at Harvard who you know what a paper simply wouldn't happened without him but so so you were asking for like a thumbnail sketch of yes thumbnail sketch or key ideas or you know things the insights that no continued on our kind of discussion here between euros and yeah yeah I mean this was another a lot of the work that we've done so far is taking ideas that have bubbled up in AI and you know asking the question of whether the brain might be doing something related which I think on the surface sounds like something that's really mainly of use to neuroscience we see it also as a way of validating what we're doing on the AI side if we can gain some evidence that the brain is using some technique that we've been trying out in our AI work that gives us confidence that you know it may be a good idea that it'll you know scale to rich complex tasks that it'll interface well with other mechanisms so you see is a two-way Road yeah for just because a particular paper is a little bit focused on from one to the from a yeah from you'll network's to neuroscience ultimately the discussion the thinking the productive long-term aspect of it is the the two-way Road nature of the whole and yeah I mean we we've talked about the notion of a virtuous circle between AI and neuroscience and you know the way I see it that's always been there since the two fields you know jointly existed there have been some phases in that history when AI was sort of ahead there are some phases when neuroscience was sort of ahead I feel like given the bursts of innovation that's happened recently on the AI side AI is kind of ahead in the sense that they're all of these ideas that we you know we you know for which it's exciting to consider that there might be neural analogs and neuroscience you know in a sense has been focusing on approaches to studying behavior that come from you know that are kind of derived from this earlier era of cognitive psychology and you know so in some ways fail to connect with some of the issues that we're you know grappling with in AI like how do we deal with you know you know complex environments but I've you know I think it's inevitable that this circle will keep turning and there will be a moment in the not too different distant future when neuroscience is pelting AI researchers with insights that may change the direction of our work just as just a quick human question is it you have parts of your brain this is very meta but they're able to both think about neuroscience and AI you know I don't often meet people like that do you do you think let me ask a meta plasticity question you think a human being can be both good at AI and neuroscience is like what on the team at deep mind what kind of human can occupy these two realms and is that something you see everybody should be doing can be doing or is it a very special few can kind of jump just like we thought about our history I would think it's a special person that can major in art history and also consider being a surgeon otherwise known as a dilettante yeah easily distracted no I I think it does take a special kind of person to be truly world-class at both AI and neuroscience and I am not on that list I happen to be someone who whose interest in neuroscience and psychology involved using the kinds of modeling techniques that are now very central in AI and that sort of I guess bought me a ticket to be involved in all of the amazing things that are going on in AI research right now I do know a few people who I would consider pretty expert on both fronts and I won't embarrass them by naming them but you know there are there are like exceptional people out there who are like this the the one the one thing that I find is a is a barrier to being truly world-class on both fronts is is the just the the complexity of the technology that's involved in both disciplines now so the the engineering expertise that it takes to to do you know truly frontline hands-on AI research is really really considerable the learning curve of the tools just like the specifics of just whether it's programming or the kind of tools necessary to collect the data to manage the data to distribute to compute all that kind of stuff yeah and on the neuroscience I guess side there'll be all different sets of tools exactly especially with the recent explosion in you know in neuroscience methods so but but how you know so having said all that I I think I think the rule I think the best scenario for both neuroscience and AI is to have people who interacting who live at every point on this spectrum from exclusively focused on neuroscience to exclusively focused on the engineering side of AI but but to have those people you know inhabiting a community where they're talking to people who live elsewhere on the on the spectrum and I be I may be someone who's very close to the center in in the sense that I have one foot in the neuroscience world and one foot in the AI world in and and that central position I will admit prevents me at least someone with my limited cognitive capacity from being a truly you know true having true technical expertise in any you know either domain but at the same time I at least hope that it's worthwhile having people around who can kind of you know see the connections if the community the yeah the the emergent intelligence of the community yeah yeah that's nicely distributed is useful okay exactly yeah so hopefully but I mean I've seen that work I've seen that work out well at D mind there there are there are people who I mean even if you just focus on the AI work that happens a deep mind it's been a good thing to have some people around doing that kind of work whose PhDs are in neuroscience or psychology every every academic discipline has its kind of blind spots and kind of unfortunate obsessions and it's metaphors and it's reference points and having some intellectual diversity is is really healthy people get each other unstuck I think I see it all the time at deep mind and you know I like to think that the people who bring some neuroscience background to the table are helping with that so one of the one of them I like probably the deepest passion for me what I would say maybe who kind of spoke off mic a little bit about it but that that I think is a blind spot for at least robotics and AI folks is human robot interaction human agent interaction maybe idea of thoughts about how we reduce the size of that lines but do you also share the feeling that not enough folks are studying this aspect of interaction well I I'm I'm actually pretty intensively interested in this issue now and there are people in my group who've actually pivoted pretty hard over the last few years from doing more traditional cognitive psychology and cognitive neuroscience to doing experimental work on human agent interaction and there are a couple of reasons that I'm pretty passionately interested in this one is it's kind of the outcome of having thought for a few years now about what we're up to like what were you like what are we doing like what what is this what is this aid AI research for so what does it mean to make the world a better place I think I'm pretty sure that means making life better for humans yeah and so how do you make life better for humans that's that's a proposition that when you look at it carefully and honestly is rather horrendously complicated especially when the AI systems that your that your building our learning systems they're not you're not you know programming something that you then introduce to the to the world and it just works as programmed like Google Maps or something we're building systems that that learn from experience so you know that that typically leads to AI safety questions how do we keep these things from getting out of control how do we keep them from doing things that harm humans and I mean I hasten to say I consider those hugely important issues and there are large sectors of the research community a deep mind and of course elsewhere who are dedicated to thinking hard all day every day about that but there's a there's I guess I guess I would say a positive side to this too which is to say well what would it mean to make human life better oh and and how how can we imagine learning systems doing that and and in talking to my colleagues about that we reached the initial conclusion that it's not sufficient to philosophize about that you actually have to take into account how humans actually work and what humans want and the difficulties of knowing what humans want and the difficulties that arise when humans want different things and and so human agent interaction has become you know a quite a quite intensive focus of my group lately if for no other reason that in order to really address that that issue in an adequate way you have to I mean psychology becomes part of the picture yeah and then so there's a few elements there so if you focus on solving into like the if you focus on the robotics problem let's say a GI without humans in the picture is you're missing fundamentally the final step you when you do want to help human civilization you eventually have to interact with humans and when you create a learning system just as you said that will eventually have to interact with humans the interaction itself has to be become has to become part of the learning process right so you can't just watch well my sense is it sounds like your senses you can't just watch humans to learn about humans yeah you have to also be part of the human world you have to interact with humans yeah exactly and I mean then questions arise that start imperceptibly but inevitably to slip beyond the realm of engineering so questions like if you have an agent that can do something that you can't do under what conditions do you want that agent to do it so you know if you know if I if I have a if I have a robot that can play Beethoven sonatas better than any human in the sense that the you know the the sensitivity the express the expression is just beyond what any human do I do I want to listen to that do I want to go to a concert and hear a robot play these are these are these are an engineering questions these are questions about human preference and human culture and psychology bordering and philosophy yeah and then and then you start asking well well even if we knew the answer to that is it our place as AI engineers to build that into these agents probably the agents should interact with humans beyond the population of AI engineers and figure out what those humans want yeah and then you know when you start I referred this the moment ago but even that becomes complicated be quote what if what if 2-8 what if two humans want different things and and you have only one agent that's able to interact with them and try to satisfy their preferences then you're into the realm of of of like economics and social choice theory and and even politics so there's a sense in which if you if you kind of follow what we're doing to its logical conclusion then it goes beyond questions of engineering and technology and you know starts to shade and perceptibly into questions about what kind of society do you want and actually that once once that dawned on me I actually felt I don't know what the right word is quite refreshed in my in my involvement in AI research it's almost like this building this kind of stuff is gonna lead us back to asking really fundamental questions about what's you know what is this like look what's the good life and yeah who gets to decide and and you know you know bringing in viewpoints from multiple sub communities to help us you know shape the way that we live this it's it's there's something it it started making me feel like doing a a I research in you know fully responsible away would you know could potentially lead to a kind of like cultural renewal yeah it's it's the way done it's the it's the way to understand human beings at the individual at the societal level it may become a way to answer all the silly human questions of the meaning of life and all the all those kinds of things but if it doesn't even if it doesn't give us a way of answering those questions it may force us back to thinking about thinking about you know and it might bring it it might bring it might restore a certain I don't know a certain depth to or even dare I say spirituality to the way that you know to to to the world I don't think maybe that you crann do switch well I don't think I I'm with you I think it's a it's a I will be that's one of the philosophy of the 21st century the way which will open the door I think a lot of a I researchers are afraid to open that door of exploring the view beautiful richness of the human agent interaction human AI interaction I'm really happy that somebody like you have opened to that door and I think one thing I often think about is you know the the the usual the usual schema for thinking about human human agent interaction is this kind of dystopian you know oh you know where our robot overlords and and again I hasten to say AI safety is usually working and I you know I'm not saying we shouldn't be thinking about those risks totally on board for that but there's a what having said that there's a there's a I what often follows for me is the thought that you know there's another there's another kind of narrative that might be relevant which is when we think of when we think of humans gaining more and more information about you know like human life the the narrative there is usually that they've gained more and more wisdom and more you know they get closer to enlightenment and you know and they become more benevolent and you know like the Buddha is like the like that's that's a totally different narrative and why isn't it the case that we we imagine that the the AI systems that we're creating and just kind of like they're gonna figure out more and more about the way the world works and the way that humans interact and they'll they'll become beneficent I'm not saying that will happen I'm not you know III I'm I don't honestly expect that to happen without some careful setting things up very carefully but it's another way things could go right and yeah and I would even push back on that I believe that the most trajectory's natural human trajectories will lead us towards progress so for me there is a kind of sense that most trajectories in AI development will lead us into trouble you mean and and we over focus on the worst case it's like in computer science theoretical computer science has been this focus on worst-case analysis there's something appealing to our human mind at some lowest level to be mean we don't want to be eaten by the tiger I guess so we want to do the worst-case analysis but the reality is that shouldn't stop us from actually building out all the other trajectories which are potentially leading to all the positive world's all the all the Enlightenment this book in language now with Steven Pinker and so on this looking generally at human progress and there's so many ways the human progress can happen with AI it's and I think you have to do that research you have to do that work you have to do the not just AI safety work of the one worst case analysis how do we prevent that but the the actual tools and the glue and the mechanisms of human AI interaction that would lead to all the positive yeah isn't go yes super exciting area right yeah you know we should be spending we should be spending a lot of our time saying what can go wrong I think it's harder to see that there's work to be done to bring into focus the question of what what it would look like for things to go right yeah that it's you know that's not obvious there and we wouldn't be doing this if we didn't have the sense there was huge potential right we're not doing this you know you know for no reason we we have a sense that AG I would be a major boom to humanity but I think I think it's worth starting now even when our technology is quite primitive asking well exactly what would that mean we can start now with applications that are already gonna make the world a better place like you know solving protein folding you know I I think this deep mind has gotten heavy into science applications lately which i think is you know you know a wonderful wonderful move for us to be making but when we think about AGI when we think about building you know fully intelligent agents that are gonna be able to in a sense do whatever they want you know we should start thinking about what do we want them to want what what what kind of world do we want to live in that's not an easy question and if you think we just need to start working on it and even on the path to sort of it doesn't have to be AG I was just intelligent agents that interact with us and help us enrich our own existence on social networks for example on recommender systems and various intelligence there's so much interesting interaction that's yet to be understood and studied and you know how how do you create I mean Twitter's is struggling with this very idea how do you create AI systems that increase the quality in the health of a conversation for sure it's a beautiful beautiful human psychology question and how do you do that without without deception being involved without manipulation being involved you know maximizing human autonomy and how do you how do you make these choices in a democratic way how do you how do we how do we face the how do we again I'm speaking for myself here how do we face the fact that it's a small group of people who have the skill set to build these kinds of systems but the you know what it means to make the world a better place is something that we all have to be talking about yeah the kind of the world the that we're trying to make a better place includes a huge variety of different kinds of people yeah how do we cope with that this is this is a problem that has been discussed you know in in Gori extensive detail in social choice theory you know there one thing I'm really enjoying about the recent direction work has taken in some parts of my team is that yeah we're reading the IEEE literature we're reading the neuroscience literature but we've also started reading like economics and as I mentioned social choice Theory even some political theory because it turns out that it's you know it all becomes relevant it all becomes relevant and but you know at the same time we've been trying not to write philosophy papers right we've been trying not to write position papers we're trying to figure out ways of doing actual empirical research that kind of take the first small steps to thinking about what it really means for humans with all of their complexity and contradiction and you know paradox and you know to be bought and to be brought into contact with these API systems in a way that then it really makes the world a better place often reinforcement learning frameworks actually kind of allow you to to do that machine learning and so that that's the exciting thing about AI is allows you to reduce the unsolvable problem philosophical problem into something more concrete that you can get ahold of yeah and it allows you to kind of define the problem in some way that allows for growth in the system that sort of beat you know you're not responsible for the details right you say this is generally what I want you to do and then learning takes care of the rest of course the safety issues are you know arise in that context but I think also some of these positive issues arise in that context what would it mean for an AI system to really come to understand what humans want and you know in if you know in with all of the subtleties of that right you know humans humans want help with certain things but they don't want everything done for them right there is part of part of the satisfaction that humans get from life is in accomplishing things so if there were devices around that did everything for him you know I often think of the movie wall-e yeah that's like dystopian in a totally different ways like the machines are doing everything for us that's that's not what we want it um you know anyway I just I find this you know this kind of this opens up a whole landscape of research that feels affirmative yeah and it's not to me it's one of the most exciting and it's wide open yeah we have to because it's a cool paper talk about dopamine oh yeah okay so I can let's we were gonna we were gonna I was gonna give you a quick summary here's a quick summary of uh what's the title of the paper I I think we called it a distributional distributional code for value in dopamine based reinforcement learning yes so that's another project that grew out of pure AI research a number of people that deep mind and a few other places had started working on a new version of reinforcement learning it would the which was defined by taking something in traditional reinforcement learning and just tweaking it so the thing that they took from traditional reinforcement learning was a value signal so that the at the center of reinforcement learning at least most algorithms is some representation of how well things are going your expected cumulative future reward and that's usually represented as a single number so if you imagine a gambler in a casino and the gamblers thinking well I have this probability of winning such and such an amount of money and I have this probability of losing such and such an amount of money the that situation would be represented as a single number which is like the expected the the weighted average of all those outcomes and this new form of reinforcement learning said well what if we what if we generalize that to distributional representation so now we think of the gambler as literally thinking well there's this probability that I'll win this amount of money and there's this probability that I'll lose that amount of money and we don't reduce that to a single number and it had been observed through experiments through you know just trying this out that that rep that kind of distributional representation really accelerated reinforcement learning and led to better policies what's your intuition about so we're talking about rewards yeah so what's the intuition why that is why what is it well it's an it's kind of a surprising historical note at least surprised me when I learned it that this had been tried out in a kind of heuristic way people thought well gee what would happen if we tried and then it had this empirically it had this striking effect and it was only then that people started thinking well gee why wait why wait why why is this working and and that's led to a series of studies just trying to figure out why it works it which is ongoing but one thing that's already clear from that research is that one reason that it helps is that it drives richer representation learning so if you imagine imagine two situations that have the same expected value they're the same kind of weighted average value Stan deep reinforcement learning algorithms are going to take those two situations and kind of in terms of the way they're represented internally dozen ex-squeeze them together because the the thing that you're trying to represent which is their expected value is the same so all the way through the system things are going to be mushed together but what if in what if what if those two situations actually have different value distributions they have the same average value but they have different distributions of value in that situation distributional learning will will maintain the distinction between these two things so to make a long story short distribution of learning can keep things separate in the internal representation that might otherwise be conflated or squished together and maintaining those distinctions can be useful in in when the system is now faced with some other task where the distinction is important if we look at the optimistic and pessimistic dopamine neurons so first of all what is dopamine why is this why is it all useful to to think about in the artificial intelligence sense but what do we know about dopamine in the human brain what is what is it why is it useful why is it interesting what does have to do with the prefrontal cortex and learning in general yeah so well there's this hint this is also some a case where there is a huge amount of detail and debate but one one one currently prevailing idea is that the function of this neurotransmitter dopamine resembles a particular component of standard reinforcement learning algorithms which is called the reward prediction error so I was talking a moment ago about these value representations how do you learn them how do you update them based on experience well if you if you made some prediction about a future reward and then you get more reward than you were expecting then probably retrospectively you want to go back and increase the value representation that you attached to the earlier situation if you got less reward than you were expecting you should probably decrement that estimate and that's the process of temporal difference exactly this is the central mechanism of temporal difference learning which is one of several kind of you know kind of back them sort of the backbone of our armamentarium in in RL and it was this connection between the world prediction error and dopamine was was made you know in the in the 1990s and there's been a huge amount of research that you know seems to back it up dopamine made to be doing other things but this is clearly at least roughly one of the things that it's doing but the usual idea was that dopamine was representing these reward prediction errors again in this like kind of single number way that representing your surprise you know it with a single number and in distribution ilaria forcement learning this this kind of new elaboration of the standard approach it's not only the value the value function that's represented as a single number it's also the reward prediction error and so what happened was that will Dabney one of my collaborators who was one of the first people to work on distributional temporal difference learning talked to a guy in my group will Chris Nelson who's a computational neuroscientist and said gee you know is it possible that dopamine might be doing something like this distributional coding thing and they started looking at what was in the literature and then they brought me in we started talking to now ochita and we came up some with some specific predictions about you know if the brain is using this kind of distributional coding then in the tasks that now has studied you should see this this this and this and that's where the paper came from we kind of enumerated a set of predictions all of which ended up being fairly clearly confirmed and all of which leads to at least some initial indication that the brain might be doing something like this distributional coding that dopamine might be representing surprise signals in a way that is not just collapsing everything to a single number but instead it's kind of respecting the the variety of future outcomes if that makes sense so yeah so that's we're showing suggesting possibly that dopamine has a really interesting representation scheme for for in in the human brain for its reward signal exactly that's fascinating it's just that's another beautiful example of AI revealing something that's about neuroscience potentially suggesting possibilities well you never know so a minute you published paper like that the next thing you think is I hope that replicates like I hope I hope we see that same thing in other datasets but of course several labs now are doing the follow-up experiment so we'll know soon but it has been it has been a lot of fun for us to you know to take these ideas from AI and kind of bring them into neuroscience and and you know see how far we can get so we kind of talked about it a little bit but where do you see the field of neuroscience and artificial intelligence heading broadly like what are the possible exciting areas that you can see breakthroughs in the next let's get crazy not just three or five years but the next 10 20 30 years that would make you excited and perhaps you'd be part of on the neuroscience side there's a great deal of interest now in what's going on in AI and and at the same time I feel like so the neuroscience especially the part of neuroscience that's focused on circuits and and systems you know kind of like really mechanism focused there's been this explosion in new technology and up until recently the experiments that have exploited this technology have have not involved a lot of interesting behavior and this is for a variety of reasons you know one of which is in order to employ some of these technologies you actually have to if you're if you're studying a mouse you have to head fix the mouse in other words you know you have to like immobilize the mouse and so it's been it's been tricky to come up with ways of eliciting interesting behavior from a mouse that's that's restrained in this way but people have begun to you know create very interesting solutions to this like virtual reality environments where the animal can kind of move a trackball and and and and as people have kind of begun to explore what you can do with these technologies I feel like more and more people are asking well let's try to bring behavior into the picture let's try to like reintroduce behavior which was supposed to be what this whole thing was about and I'm hoping that those two trends the the kind of growing interest in behavior and the widespread widespread interest in what's going on in AI will come together to kind of open a new chapter in neuroscience research where there's a kind of rebirth of interest in the structure of behavior and its underlying substrates but that that research is being informed by computational mechanisms that were coming to understand in AI you know if we can do that then we might be taking a step closer to this utopian future that we were talking about earlier where there's really no distinction between psychology and neuroscience night neuroscience is about studying the mechanisms that underlie whenever it is the brain is for and you know what is the brain for it's for behavior now I feel like we could I feel like we could maybe take a step toward that now if people are motivated in the right way you also ask Betty I so that is very science question you said neuroscience that's right and especially place like deep mind are interested in both branches sort of what what about the engineering or intelligence systems I think I think the one of the key challenges that a lot of people are seeing now in AI is to build systems that have the kind of flexibility and the kind of flexibility that humans have in two senses one is that humans can be good at many things they're not just expert at one thing and they're also flexible in the sense that they can switch between things very easily and they can pick up new things very quickly because they they very they very able see what a new task has in common with other things that they've done and and that's something that our AI systems to you know blatantly do not have there are some people who like to argue that deep learning and deep RL are simply wrong for getting that kind of flexibility I don't share that belief but the simpler fact of the matter is we're not building things yet that do have that kind of flexibility and and I think the the attention of a large part of the AI community is starting to pivot to that question how do we get that that's going to lead to a focus on abstraction it's gonna lead to a focus on what in psychology we call cognitive control which is the ability to switch between tasks the ability to quickly put together a program of behavior that you've never executed before but you know makes sense for a particular set of demands it's very closely related to what the prefrontal cortex does on the neuroscience side so I think it's going to be an interesting and interesting new chapter so that's the reasoning side and cognition side but let me ask the over romanticize question do you think we'll ever engineer an AGI system that we humans would be able to love and that would love us back so I have that level and depth of connection I love that question and it it it relates closely to things that I've been thinking about a lot lately you know in the context of this human AI research there there's social psychology research in particular by Susan Fiske at Princeton in the department I used to where I used to work where she she dissects human attitudes toward other humans into a sort of two-dimensional you know a two-dimensional two-dimensional scheme and one dimension is about ability you know how able how capable is is this other person and the but the other dimension is warmth so you can imagine another person who's very skilled and capable but it's very cold right and you wouldn't you wouldn't really like highly you might have some reservations about that other person right but there's also a kind of reservation that we might have about another person who who elicits in us or displays a lot of human warmth but is you know not good at getting things done right that that like the the greatest esteem that we we reserved our greatest esteem really for people who are both highly capable and also quite warm right that that's that's like the best of the best this is I mean I'm just this isn't a normative statement I'm making this is just an empirical it's an empirical statement this is what humans seem this is these are the two dimensions that people seem to kind of like along which people size other people up in an in AI research we really focus on this capability thing you like we want our agents to be able to do stuff you know this thing can play go at a superhuman level that's awesome and but that's only one dimension what's the what about the other dimension what would it mean for Nai system to be warm and you know I don't know maybe there are easy solutions here like we can put them put a face on rei systems it's cute it has big years I mean that's probably part of it but I think it also has to do with a pattern of behavior a pattern of you know what would it mean for an AI system to display caring compassionate behavior in a way that actually made us feel like it was for real yeah that we didn't feel like it was simulated we didn't feel like we were being duped to me that you know people talk about the Turing test or some some descendant of it I feel like that's the ultimate Turing test you know is there is there an AI system that can not only convince us that it knows how to reason and it knows how to interpret language but that we're comfortable saying yeah that AI system is a good guy you know like I'm the warmth scale yeah whatever warmth is we kind of intuitively understand it but we also want to be able to yeah we don't even understand it explicitly enough yet to be able to engineer it exactly and that's and that's an open scientific question you kind of alluded it several times in the human AI interaction that's the question that should be studied and probably one of the most important questions and usually and human to AG we humans are so good at it yeah you know it's not just weird it's not just that we're born warm you know like I suppose some people are are warmer than others given you know whatever genes they manage to inherit but there's also there's also there are also learned skills involved right I mean there are ways of communicating to other people that you care that they matter to you that you're enjoying interacting with them yeah right and we learn these skills from one another and it's not out of the question that we could build engineered systems I think it's hopeless as you say that we could somehow hand design these sorts of these sorts of behaviors but it's not out of the question that we could build systems that kind of we-we-we in instill in them something that sets them out in the right direction so that they they end up learning what it is to interact with humans in a way that's gratifying to humans I mean honestly if that's not where we're headed I think it's exciting as a scientific problem just as he described I I honestly don't see a better way to enter than talking about warmth and love and Matt I don't think I've ever had such a wonderful conversation where my questions were so bad and your answers was so beautiful so I deeply appreciate it I really do very fun I don't know I as you can probably tell I'm I really you know I there's something I like about kind of thinking outside the box and like yeah I'm so it's good having fun to do that awesome thanks so much for doing it thanks for listening to this conversation with Matt bah panic and thank you to our sponsors the Jordan Harbinger show and magic spoon low carb keto cereal please consider supporting this podcast by going to Jordan Harbinger complex and also going to magic spoon complex and using code Lex a check out click the links buy all the stuff it's the best way to support this podcast and the journey I'm on in my research and the startup if you enjoy this thing subscribe on youtube review it with the five stars in a podcast the port on patreon follow on Spotify or connect with me on Twitter at Lex Friedman again spelled miraculously without the e just Fri DM a.m. and now let me leave you with some words from urologists vs amachandran hannah three pound mass of jelly that you can hold in your palm imagine angel's contemplate the meaning of infinity even question its own place in cosmos especially all inspiring it's the fact that any single brain including yours is made up of atoms that were forged in the hearts of countless far-flung stars billions of years ago these particles drifted for eons and light years until gravity and change brought them together here now these atoms now form a conglomerate your brain I can not only ponder the very stars they gave it birth but can also think about its own ability to think and wonder about its own ability to wander with the arrival of humans it has been said the universe has suddenly become conscious of itself this truly is the greatest mystery of all thank you for listening and hope to see you next time you |
Robert Langer: Edison of Medicine | Lex Fridman Podcast #105 | the following is a conversation was Bob Langer professor at MIT and one of the most cited researchers in history specializing in biotechnology fields of drug delivery systems and tissue engineering he has bridged theory and practice by being a key member and driving force in launching many successful biotech companies out of MIT this conversation was recorded before the outbreak of the corona virus pandemic his research and companies are at the forefront of developing treatments for covert 19 including a promising vaccine candidate quick summary of the ads to sponsors cash up a master class please consider supporting the podcast by downloading cash app and using code Lex podcast and signing up a masterclass comm slash Lex click on the links buy this stuff it really is the best way to support this podcast and in general the journey I'm on to my research and startup this is the artificial intelligence podcast if you enjoy it subscribe bye YouTube review it with five stars in a podcast supported on patreon or connect with me on Twitter Lex Friedman as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show is presented by cash app the number one finance app in the App Store when you get it use collects podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app allows you to send and receive money digitally let me mention a surprising fact related to physical money of all the currency in the world roughly eight percent of it is actual physical money the other 92 percent of money only exists digitally so again if you get cash app from the App Store or Google Play and use the collects podcast you get ten dollars and cash wrap will also donate ten dollars the first an organization that is helping to advance robotics and STEM education for young people around the world this show sponsored by masterclass sign up a master class complex to get a discount and to support this podcast when I first heard about master class I thought it was too good to be true for one hundred and eighty dollars a year you get an all-access pass to watch courses from to list some of my favorites Chris Hadfield on space exploration Neil deGrasse Tyson a scientific thinking and communication will write to crater some city and Sims on game design Carlos Santana on guitar Europa is probably one of the most beautiful guitar instrumentals ever garry kasparov on chests daniel negreanu on poker and many more Chris Hadfield explaining how Rockets work and the experience of being launched into space alone is worth the money you can watch it basically any device once again sign up a master class calm slash flex to get a discount and to support this podcast and now here's my conversation with Bob Langer you have a bit of a love for magic do you see a connection between magic and science I do I think magic can surprise you and you know and I think science can surprise you and there's something magical about about science I mean making discoveries and things like that you know so on then on the magic side is there some kind of engineering scientific process to the tricks themselves do you see because there's a duality to it one is your the your you're sort of the person inside there knows how the whole thing works how the universe of the magic trick works and then from the outside observer which is kind of the role of the scientists you the people that observe the magic trick don't know at least initially anything that's going on do you see that kind of duality well I think the duality that I see is fascination you know I think of it you know when I watch Magic myself I'm always fascinated by it sometimes it's a puzzle to think how it's done but just the sheer fact that's something that you never thought could happen does happen and I think about that in science too you know sometimes you it's something that you might dream about and helping to discover maybe you do or in some way or form what is the most amazing magic trick you've ever seen well there's one I like which is called the invisible pack and the way it works is you have this pack and you hold it up but first you say to somebody is this is invisible and this deck and you say well shuffle it and I shuffle it but you know there's sort of make-believe and then you say okay I'd like you to pick a card any card and show it to me and you show it to me and and I look at it and let's say it's the three of hearts and said we'll put it back in the deck but what I'd like you to do is turn it upside down from every other cards in the deck so they they do that imaginary and I said you want to shuffle it again they shuffle it and I said well so there's still one card upside down from every other card in the deck I said what is that and they said all three hearts so it just so happens in my back pocket I have this deck it's you know it's a real deck I show - you know it's just open it up and there's just one card upside down and it's the three of hearts and and you can do this trick I can i-55 don't I would have probably brought it all right well beautiful let's get into the into the science as of today you have over two hundred ninety five thousand citation an h-index of 269 you're one of the most sighted people in history and the most cited engineer in history and yet nothing great I think is ever achieved without failure so the interesting part what rejected papers ideas efforts in your life or most painful or had the biggest impact on your life well it's interesting I mean I've had plenty of rejection to you know I but I suppose one way I think about this is that when I first started and this certainly had an impact both ways you know I first started we made two big discoveries and they were kind of interrelated I mean one was I was trying to isolate with my post-doctorate advisor Judah Folkman substances that could stop blood vessels from growing and nobody done that before and so that was part a let's say a Part B is we had to develop a way to study that and what was critical to study that was to have a way to slowly release those substances for you know more than a day I you know maybe months and that had never been done before either so we published the first one we sent to nature the journal and they rejected it and then we sent it revise tenets of science and they accepted it and the other the opposite happened we sent it to science and they rejected it and then we sent it to nature and they accepted it but I have to tell you when we got the rejections it was really upsetting I thought you know I did some really good work and dr. Folkman thought we've done some really good work and and but it was very depressing to you know get rejected like that if you can linger on just the feeling or the thought process when you get the rejection especially early on in your career what I mean you don't know now people know you as uh as as a brilliant scientist but at the time I'm sure you're full of self-doubt and did you believe that maybe this idea is actually quite terrible that it could been done much better or is the underlying confidence what was the feelings well you feel to feel depressed that I felt the same way when I got grants rejected which I did a lot in the beginning I guess part of me you know you have multiple emotions one is being sad and being upset and also being maybe a little bit angry because the you to feel the reviewers didn't get it but then as I thought about it more I thought well maybe I just didn't explain it well enough and you know that you go through stages and so you say well okay I'll explain it better next time and certainly you get reviews and what you get the reviews you see what they either didn't like or didn't understand and then you try to incorporate that into your next versions mmm you've given advice to students to do something big do something that really can change the world rather than something incremental how did you yourself seek out such ideas is there a process is there a sort of a rigorous process or is it more spontaneous it's more spontaneous I mean part of its exposure to things part of its seeing other people like I mentioned dr. Folkman he was my post doctoral adviser he was very good at that you could sort of see that he had big ideas and I certainly met a lot of people who didn't and and I think you could spot an idea that might have potential when you see it you know because it could have a very broad implications where a lot of people might just keep doing derivative stuff and so but it's not something that I've ever done systematically I don't think so in the space of ideas how many are just when you see them it's just magic it's something that you see that could be impactful if if if you dig deeper yeah it's it's sort of hard to say because there's there's multiple levels of ideas one type of thing is like a new you know creation like that you could engineer tissues for the first time or make dishes from scratch from the first time but another thing is really just deeply understanding something and that's important too so and and that may lead to other things so sometimes you could think of a new technology or I thought of a new technology but other times things came from just the process of trying to discover things so it's never and and and you don't necessarily know like people talk about aha moments but I don't know if I've I mean I certainly feel like I've had some ideas that I really like but it's taken me a long time to go from the thought process of starting it to all of a sudden knowing that it might work so if you if you take drug delivery for example is the notion is the initial notion kind of a very general one that we should be able to do something like this yeah and then you start to ask the questions of well how would you do it and then and then digging and digging and digging I think that's right I think it depends I mean there are many different examples the example I gave about delivering large molecules which we used to study these blood vessel inhibitors I mean there we had it invent something that would do that but other times it's it's it's different sometimes it's really understanding what goes on in terms of understanding the mechanisms and so it's it's it's not a single thing and there are many different parts to it you know over the years we've invented different discover different principles for aerosols for delivering you know genetic therapy agents you know all kinds of things so let's explore some of the key ideas you've touched on in your life some let's let's start with the basics okay so first let me ask how complicated is the biology and chemistry of the human body from the perspective of trying to affect some parts of it in a positive way it's but so that you know for me especially coming from the field of computer science and computer engineering and robotics it's that the human body is exceptionally complicated and how the heck you can figure out anything is amazing well I agree with you I think it's super complicated I mean we're still just scratching the surface in many ways but I feel like we have made progress in different ways and some of its by really understanding things like we were just talking about other times you know you might or somebody might we or others might invent technologies that might be helpful on exploring that and I think over many years we've understood things better and better but we still have such a long ways to go are there I mean if you just look are there other things that are there knobs that are reliably controllable about the human body if you could service is there is it so if you start to think about controlling various aspects of when we talk about drug delivery a little bit but controlling various aspects chemically of the human body is there a solid understanding across the populations of humans that are solid reliable knobs that can be controlled I think that's hard to do about on the other hand whenever we make a new drug or medical device to a certain extent we're doing that you know in a small way what you just said but I don't know that they're that they're great knobs I mean and we're learning about those knobs all the time but if there's a biological pathway or something that you can affect or understand I mean then that might be such a knob so what is pharmaceutical drug how do you do how do you discover a specific one how do you test it how do you understand it how do you ship it yeah well I'll give an example which goes back to what I said before so when I was doing my postdoctoral work with Judah Folkman we wanted to come up with drugs that would stop blood vessels from growing or alternatively make them grow and actually people didn't even believe that that those things could happen but could we pause on that for a sec sure what is the blood vessel what does it mean for a blood vessel to grow and shrink and why is that important sure so a blood vessel is could be an artery or vein or a capillary and it it you know provides oxygen it provides nutrients gets rid of waste so you know two different parts of your body if you soso the blood vessels end up being very very important and you know if you have cancer blood vessels grow into the tumor and that's part of what enables the tumor to get bigger and that's also part of what enables the tumor to metastasize event which means spread throughout the body and ultimately kill somebody so that was part of what we were trying to do we shot what we wanted to see if we could find substances that could stop that from happening so first I mean there are many steps first we had to develop a bio essay to study blood vessel growth again there wasn't one that's where we needed polymer systems because the blood vessels grew slowly took months that so after we had the polymer system and we had the bioassay then I had isolated many different molecules initially from cartilage and almost all of them didn't work but we were fortunate we found one it wasn't purified but we found one that did work and that paper that was this paper I mentioned in science in 1976 those were really the isolation of some of the very first angiogenesis of blood vessel inhibitors so there's a lot of words there yeah that's the the first of all polymer molecules big big molecules so the water polymers what's bio sa the the what is the process is trying to isolate this whole thing simplified to where you can control and experiment with it polymers are like plastics or like plastics or rubber what were some of the other questions sorry so a polymer some plastics and rubber and that means something that has structure and that could be useful for what well in this case it would be something that could be useful for delivering a molecule for a long time so it could slowly diffuse out of that at a controlled rate to where you wanted it to go so then you would find the ideas that there would be particular blood vessels that you can target say they're connected some Auto tumour you could target and over a long period of time to be able to place the polymer there and it be delivering a certain kind of chemical that's correct I think what you said it's good so so that it would deliver the the molecule or the chemical that would stop the blood vessels from going over a long enough time so that it really could happen so that was sort of the what we call the bio sa is the way that we would study that so size of what is a by us which part is the bio sa all of it in other words the bio SAS is the way you study blood vessel growth the blood vessel growth and you can control this somehow with is there an understanding what kind of chemicals can control the growth of a blood sure well now there is but then when I started there wasn't and that that gets to your original question so you go through various steps we did the first steps we showed that a such molecules existed and then we developed techniques for studying them and we said even isolated fractions you know groups of substances that would would do it but what would happen over the next we did that in 1976 we published that what would happen over the next twenty eight years as other people would follow in our footsteps I mean we tried to do some stuff too but ultimately to make a new drug takes billions of dollars so what happened was there were different growth factors that people would isolate sometimes using the techniques that we developed and then they would figure out using some of those techniques ways to stop those growth factors and ways to stop the blood vessels from growing I thought like you say it took 28 years it took billions of dollars and work by many companies like Genentech but in 2004 28 years after we started the first one of those Avastin got approved by the fda and that that be that's become you know one of the top biotech selling drugs in history and it's been approved for all kinds of cancers and actually for many eye diseases to where you have abnormal blood vessel growth macula so in general one of the key ways you can alleviate so what's the hope in terms of tumors associated with cancerous tumors they what can you help by being able to control the growth of vessels so if you cut off the blood supply you cut off the it's kind of like a war almost right you if you have if the nutrition is going to the tumor and you and you and you can cut it off I mean you starve the tumor and it becomes very small it may disappear or it's going to be much more amenable to other therapies because it is tiny you know like you know chemotherapy or immunotherapy is gonna be have a much easier time against a small tumor than a big one is that an obvious idea I mean it seems like a very clever strategy in this war against yeah cancer well you know in retrospect it's an obvious idea but when dr. Folkman and my boss first proposed it it wasn't a lot of people didn't thought it was pretty crazy and so they in what sense if you could sort of linger on it when you're thinking about this ideas at the time were you feeling you're out in the dark so how much mystery is there about the whole thing how much just blind experimentation if you can put yourself in that mindset from years ago yeah well there was I mean for me actually it wasn't just the idea was that I didn't know a lot of biology or biochemistry so I've certainly felt a host in the dark but I I kept trying and I kept trying to learn and I kept plugging but but I mean a lot of it was being in the dark so the human body is complicated right we'll establish this quantum mechanics and physics is a theory that works incredibly well but we don't really necessarily understand the underlying nature of it so our drugs the same and that you can you're ultimately trying to show that the thing works to do something that you try to do but you don't necessarily understand the fundamental mechanisms by which it's doing it it really varies I think sometimes people do know them because they've figured out pathways and wish to interfere them with them other times is shooting in the dark is it really has varied okay and sometimes people make sure--and Jupitus discoveries and they don't even realize what they did so what is the discovery process for a drug ze said a bunch of people of trying to work with this is it is it a kind of mix of serendipitous discovery and art or is there a systematic science to trying different chemical reactions and how they how they affect whatever you trying to do like shrink blood vessels yeah I don't think there's a single way you know single way to go about something in terms of characterizing the entire drug discovery process if I look at the blood vessel one yeah they're the first step was to do to have that those kinds of theories that dr. Folkman had the second step was to have the techniques where you could study blood vessel growth for the first time and at least quantitate or semi-quantitative a third step was to find substances that would stop blood vessels from growing for step was to maybe purify those substances there are many other steps too I mean before you have an effective drug you have to show that it's safe you have to show those effective and you start with animals you ultimately go to patients and there are multiple kinds of clinical trials you have to do if you step back is it amazing to you that we descendants of great apes are able to create things there you know are the create drugs chemicals that are able to improve some aspects of our bodies Hey or is it quite natural that we were able to discover these kinds of things well at a high level it is amazing I mean evolution is amazing yeah you know the way I look at your question the fact that we evolved have evolved the way we've done I mean it's pretty remarkable so let's talk about drug delivery what are the difficult problems in drug delivery what is drug delivery you know from starting from your early seminal work in the field that today well drug delivery is getting a drug to to be good to go where you want it at the level you want it in a safe way some of the big challenges I mean there are a lot I mean I'd say one is could you target the right cell like we talked about cancers or some way to deliver a drug just to the cancer cell and no other cell another challenge is to get drugs across different barriers like could you ever give insulin orally could you give a train you know or give it passively transdermally can you get drugs across the blood-brain barrier I mean there are lots of big challenges can you make smart drug delivery systems that might respond to physiologic signals in the body oh it's just think so smart smart they have some kind of sense a chemical sensor or is this something more than a chemical sense that it's able to respond to something in the body could be either one I mean you know I I mean one example might be if you that were diabetic if you had more it got more glucose could you get more insulin but I don't but that but that's just an example is there some way to control the actual mechanism of delivery in a response to what the body's doing yes there is I mean one of the things that we've done is encapsulate what are called beta cells those are insulin producing cells in a way that they're safe and protected and then what will happen is glucose will go in and you know to sell so we'll make insulin and so that that's an example so from an AI robotics perspective how close are these drug delivery systems to something like a robot or they're totally wrong to think about them as intelligent agents and how much room is there to add that kind of intelligence into these delivery systems perhaps in the future yeah I think it depends on the particular delivery system you know of course one of the things people are concerned about is cost and if you add a lot of bells and whistles to something it'll cost more but I mean we for example have made what I'll call intelligent microchips that can don't you know where you can send a signal and you know release drug in response to that say no and I think systems like that microchip someday have the potential to do it you and I were just talking about that there could be a signal like glucose and it could have some instruction to say when there's more glucose deliver more insulin so do you think it's possible that there that could be robotic type systems roaming our body sort of long-term and be able to deliver certain kinds of drugs in the future you see you see that kind of future someday I don't think we're very close to it yet but someday you know that that's nanotechnology and that would mean even miniaturizing some of the things that I just discussed and we're certainly not at that point yet but someday I expect we will be so some of it is just the shrinking of the technology that's a part of it that's one of the things in general what role do you see AI sort of there there's a lot of work now with using data to make intelligent and create systems that make intelligent decisions do you see any of that data-driven kind of computing systems having a role in any part of this into the delivery and drugs the the design of drugs and any part of the chain I do I think that AI can be useful and a number of parts of the chain I mean one I think if you get a large amount of information you know say you have some chemical data because you've done high throughput screens and let's out I'll just make this up but let's say I have I'm trying to come up with a drug to treat disease X and whatever that disease is and I have a test for that and hopefully a fast test and let's say I test ten thousand chemical substances you know and a couple work most of them don't work so I maybe work a little but if I had a few with the right kind of artificial intelligence maybe you could look at the chemical structures and look at what works and see if there's certain commonalities look at what doesn't work and see what commonalities there are and then maybe use that somehow to project the next generation of things that you would test as a tangent what are your thoughts on our society's relationship with pharmaceutical drugs do we and perhaps I apologize if this is a philosophical broader question but do we over rely on them do we properly prescribed them and what ways the system working well what way can improve well I think you know pharmaceutical drugs are really important I mean the life expectancy and life quality of people over many many years has increased tremendously and I think that's a really good thing I think one thing that would also be good as if we could extend that more and more to people in the developing world which is something that our lab has been doing with the Gates Foundation or trying to do I saw I think ways in which it could improve I mean our if there was some way to reduce costs you know that that's certainly an issue people are concerned about if there was some way to help people and in poor countries that would also be a good thing and then of course we still need to make better drugs for so many diseases I mean cancer diabetes I mean we you know it's hard to see some rare diseases there are many many situations where it would be great if we could do better and help more people can we talk about another exciting another exciting space which is tissue engineering what is tissue engineering or regenerative medicine you know so that tissue engineering regenerative medicine have to do with building an organ or tissue from scratch so you know someday maybe we can build the liver you know or make new cartilage and also would enable you to you know someday create organs on a chip which people we and others are trying to do which might lead to better drug testing and maybe less testing on animals for people organs and I chip it sounds fascinating so what what are the various ways to generate tissue and how do so is it you know that one is of course from stem cells is there are other methods what are the different possible flavors here yeah well I think I mean there's multiple components one is having generally some type of scaffold that's what Jay Vacanti and I started many many years ago and then on that scaffold you might put different cell types which could be a cartilage cell a bone cell could be a stem cell though it might differentiate into different things could be more than one cell and the scaffold sorry to interrupt is kind of like a canvas that it's a structure that you can on which the the Susskind girl I think that's a good explanation when you just enough to use that the caskets that's good yeah so I think that that's fair you know when the chip could be such a canvas some could be fibers that are made of plastics and that you'd put in the body someday and we need a chip do you mean electronic chip like necessarily it could be though but it doesn't have to be it could just be a structure that's not not in vivo so to speak that's you know that's outside the body so is there a nervousness it's not a bad word says there possibility to weave into the scanner as a computational component so if we talk about electron ships some some ability to sense control some aspect of this growth process for the tissue I would say the answer to that is yes I think right now people are working mostly on validating these con chips for saying well it does work as effectively or hopefully as just putting something in the body but I think someday will you suggest it you certainly would be possible so what kind of tissues can we engineer today what would yeah yeah well well so skin has already been made and approved by the FDA their advanced clinical trials like what are called phase three trials that are at complete or near completion for making new blood vessels one of my former students Lorin Nicholson led a lot of that he thought that's amazing this human skin can be grown that's already approved through the entire the FDA process so that means what so the one that means you can grow that tissue and do various kinds of experiments in terms of in terms of drugs and so on but what is that does that mean that some kind of healing and treatment of different conditions for on human beings yes I mean they've been approved now for how many different groups have made them different companies and different professors but they've been approved for burn victims and for patients with diabetic skin ulcers that's amazing okay so skin what else well at different stages people are like skin blood vessels there's clinical trials going now for helping patients here better for patients that might be paralyzed for patients that have different hai problems I'm you know at different groups have worked on just about everything new liver and who kidneys I mean there have been all kinds of work done in this area some of its early but but there's certainly a lot of activity what about neural tissue yeah nurten the nervous system and even the brain while there have been people out of working on that too we've done a little bit with that but there are people who've done a lot on neural stem cells and I know Evan Schneider who's been one of our collaborators on some of our spinal cord works done work like that and ever been other people as well as their challenges for the when it is part of the human bodies there's challenges to getting the the body to accept this new tissue that's being generated how do you solve that kind of challenge there can be problems with it accepting it I think maybe in particular you might mean rejection by the body so there are multiple ways that people are trying to deal with that one way is which was what we've done and with Dan Anderson one of my former postdocs and I mentioned this a little bit before for a painted pancreas is encapsulating the cell so immune immune cells or antibodies can't get in and attack them so that's a way to protect them other strategies could be making the cells not immuno genic which might be done by different either techniques which might mask them or using some gene editing approaches so they're different ways that people are trying to do that and of course if you use the patient's own cells or cells from a close relative doubt might be another way and it increases the likelihood that they'll get accepted if you use the patient's own cells yes and then finally there's some you know suppressive drugs which you know will suppress the immune response that's right now what's done say for a liver transplant the fact that this whole thing works just fascinating at least from my outside perspective well we one day be able to regenerate any organ or part of the the human body in your view and it's exciting to think about future possibilities of tissue engineering is do you see some tissues more difficult than others what are the possibilities here yeah Wow of course I'm an optimist and I also feel a timeframe if we're talking about some day some day could be hundreds of years but I think that yes some day I think we will be able to regenerate many things and our different strategies that one might use the one might use some cells themselves one might use you know some molecules that might help regenerate the cells and so I think there are different possibilities what do you think that means for longevity if we look maybe not someday but 10 20 years out are the possibilities that tissue engineering the possibilities of the research that you're doing does it have a significant impact on the longevity human life I don't know that we'll see a radical increase in longevity but I think that in certain areas we'll see people live better lives and maybe so somewhat longer lives with the most beautiful scientific idea in biology nearing that you've come across in your years of research I apologize for the romantic no that's an interesting question I certainly think what is happening right now with CRISPR is a beautiful idea that certainly wasn't wasn't my idea I mean but you know I think it's very interesting here what what people have capitalized on is that there's a mechanism by which bacteria are able to destroy viruses and that understanding that let leads the machinery to to put you know to sort of cut and paste genes and and you know fix the cell so that kind of you see a promise for that kind of ability to copy and paste I mean everything like we said the human body is complicated is that Mele difficult to do I think it is exceptionally difficult to do but that doesn't mean they won't be done there's a lot of companies and people trying to do it and I think in some areas it will be done some of the ways that make you might lower the bar are not you know are just taking look like not necessarily doing it directly but you know you could take a cell that might be useful but you want to give it some cancer-killing capabilities something collect what's called the cart C cell and that might be a different way of somehow making a cart C cell and maybe making it better so there might be sort of easier things and rather than just fixing the whole body so the way a lot of things have moved to in medicine over time is stepwise so I can see things that might be easier to do than say fix a brain that would be very hard to do but maybe someday that'll happen too so in terms of stepwise that's the interesting notion do you see that if you look at medicine or bioengineering do you see that there is these big leaps that happen every decade or so or some distant period or is it a lot of incremental work not I don't mean to reduce its impact by saying it's incremental but yeah is there sort of phase shifts in in the science big big leaps I think there's both you know every so often a new technique or new technology comes out I mean genetic engineering was an example I mentioned CRISPR you know I think every so often things happen that you know make a big difference but still there's to try to really make progress make a new drug make a new device there's a lot of things I don't know if I'd call them incremental but there's a lot a lot of work that needs to be done absolutely so you have over numbers could be off but it's a big amount you have over 1100 current or pending patents that have been licensed sub license to over 300 companies what's your view would in your view are the strengths and what are the drawbacks of the patenting process well I think for the most part their strengths I think that if you didn't have patents especially in medicine you'd never get the funding that it takes to make a new drug or a new device I mean which according to Tufts to make a new drug costs over two billion dollars right now and nobody would even come close to giving you that money any of that money if if it weren't for the patent system because and then anybody else could do it that that that then leads to the negative though you know sometimes somebody does up a very successful drug and you certainly want to try to make it available to everybody and and so the patent system allows it allowed it happen in the first place but maybe it'll impede it after a little bit or certainly to some people or some companies you know once it's once it is out there what's the on the point of the cost what would you say is the most expensive part of the two billion dollars of making the drug given clinical trials that is by far the most in terms of money or pain or both well money but a pain goes hard to know I mean but but usually doing proving things that are that are proving that something new is safe and effective in people this is almost always the biggest expense could you linger on that for just a little longer and describe what it takes to prove for people that don't know in general what it takes to prove that something is effective on humans well you'd have to take at this particular disease but what the process is you start out with so usually you start out with cells then you'd go to animal models usually you have to do a couple of animal models and of course the animal models aren't perfect for humans and then you have to do three sets of clinical trials at a minimum a phase one trial to show that it's safe and small number of patients face to trial to show that it's effective in a small number of patients and a phase three trial to show that a safe and effective in a large number of pay and you know that could end up being hundreds or thousands of patients and they have to be really carefully controlled studies and you know you'd have to manufacture the drug you'd have to you know really watch those patients you have to be very concerned if you know that that it is gonna be safe and and and and you look at see does it doesn't treat the disease better than what the whatever the gold standard was before that if there was assuming there was one that's a really interesting line show that it's safe first and then that it's effective first do no harm first do no harm that's right so how again if you can linger it a little bit how does the patenting process work yeah well you you do a certain amount of research though that's not necessarily has to be the case but you for us usually it is usually we do a certain amount of research and make some findings and you know we had a hypothesis let's say we prove it or we make some discovery we need to invent some technique and then we write something up what's called a disclosure we give it to MIT technology transfer office they then give it to some patent attorneys and they use that and plus talking to us and you know work on writing a patent and then you go back and forth with the USPTO that's the United States Patent and Trademark Office and you know they may not allow it the first second or third time but they will tell you why they don't and you may adjust it and maybe you'll eventually get it and maybe you won't so you've been part of launching 40 companies together worth again numbers could be outdated but an estimated twenty three billion dollars you've described your thoughts on a formula for startup success so perhaps you can describe that formula in general describe what does it take to build a successful startup well I I break that down into a couple categories and I'm I'm a scientist and certainly from the science standpoint I'll go over that but I actually think that really the most important thing is probably the business people then that work with and you know they when I look back at the companies that have done well it's been because we've had great business people and when they haven't done as well we have it as good business people but from a science standpoint I think about that we've made some kind of discovery that is almost what I'd call a platform that you could use it for different things and certainly the drug delivery system example that I gave earlier z' is a good example of that you could use it for drug ABCDE and so forth and that I'd like to think that we've taken it far enough so that we've written at least one really good paper and a top journal hopefully a number that we've reduced it to practice in animal models that we've filed patents maybe I had issued patents that of what I'll call very good and broad claims that's sort of the key in a patent and then in our case a lot of times when we've done it a lot of times it's somebody in the lab like a postdoc or graduate student spent a big part of their life doing it and that they want to work at that company because they have this passion that they want to see something they did make a difference in people's lives maybe you could mention the business component it's funny to hear great side to say that there's value to business folks oh yeah well that always said so what what value what business instinct is valuable to make a startup successful a company successful I think the business aspects are you have to be a good judge of people so that you hire the right people you have to be strategic so you figure out if you do of that platform that could be used for all these different things what one are you and knowing that medical research is so expensive what thing are you gonna do first second third fourth and fifth I think you need to have a good Lex what I'll call FDA regulatory clinical trial trial strategy I think you have to be able to raise money incredibly so there are a lot of things you have to be a good good with people good manager people so the the money in the people part I get but this the stuff before in deciding the ABCD if you have a platform which trucks the first and taking testing you see nevertheless scientist is not being too always too good at that process well I think there a part of the process but I'd say there's probably I'm gonna just make this up but maybe six or seven criteria that you want to use and it's not just science I mean the kinds of things that I would think about is is the market big or small is the art there are there good animal models for it so that you could test it and it wouldn't take you know fifty years are the clinical trials that could be set up ones that you know have clear end points where you can make a judgement and and another issue would be competition are there other ways that some companies out there or doing it another issue would be reimbursement you know can I get reimbursed so a lot of things that you have manufacturing issues you'd want to consider is it not so I think there are really a lot of things that go into whether you do what you do for a second third or fourth so you lead one of the largest academic labs in the world with over ten million dollars in annual grants and over 100 researchers probably over a thousand since the labs beginning researchers can be individualistic and eccentric I don't put it nicely there you go eccentric so what insights into research leadership can you give having to run such a successful lab was so much diverse talent well I don't know that I'm any expert I think that what you do to me I mean I just want that missus gonna sound very simplistic but I just want people in the lab to be happy to be doing things that I hope will make the world a better place to be working on science that can make the world a better place and I guess my feeling is if we're able to do that you know Peter it kind of runs itself so how do you make a researcher happy in general what I think when people feel I mean this is going to sound like again simplistic or maybe like motherhood and apple pie but I think if people feel they're working on something really important that can affect many other people's lives and they're making some progress they'll feel good about it they'll feel good about themselves and they'll be happy but through brainstorming and so on what's your role and how difficult it is as a group in this in this collaboration to arrive at these big questions that might have impact well the big questions come from many different ways sometimes it's trying to things that I might think of or somebody in the lab might think of which could be a new technique or to understand something better but gee we've had people like Bill Gates and the Gates Foundation come to us and Juvenile Diabetes Foundation come to us and say gee could you help us on these things and I mean that's good too it doesn't happen just one way and I mean you've kind of mentioned it happiness but is there something more how do you inspire a researcher to do the best work of their life so you mentioned passion and passion is a kind of fire do you see yourself having a role to keep that fire going to to build it up to inspire the researchers through the you know pretty difficult process of going from idea to too big question to big answer I think so I think I try to do that by talking to people going over their ideas and their progress I try to do it as an individual you know certainly when I talk about my own career I had my setbacks s you know different times and people know that that know me and you know you just try to keep pushing and and so forth but but yeah I think I try to do that as the one who leads the lab so you have this exceptionally successful lab and and one of the great institutions in the world MIT what and yet sort of at least in my neck of the woods in computer science and artificial intelligence a lot of the research is kind of a lot of the great researchers not everyone but some are kind of going to industry a lot of them researchers moving to industry deep what do you think about the future of science in general is there drawbacks is a strength to the academic environment that you hope will persist how does it need to change what needs to stay the same what are your just thoughts in this whole landscape of science in its future well first I think going to industry is good but I think being an academia is good you know I have lots of students who have done both and they've had great careers doing both I I think from an academic standpoint I mean the biggest concern probably that people feel today you know at a place like MIT or other research heavy institutions is going to be funding and particularly funding that's not super directed you know so that you can do basic research I think that's probably the number one thing but you know it would be great if we as a society had come up with better ways to teach you know so that people all over could learn better you know so I think there were a number of things that would be good to be able to do better so again you're very successful in terms of funding but do you still feel the pressure of that of having to seek funding does it affect the science or is it or can you simply focus on doing the best work of your life and the funding comes along with that I'd say the last 10 or 15 years we've done pretty well funding but I always worry about it you know it's like you're still operating on more soft money than hard and and so I always worry about it but we've been fortunate that places have come to us like the Gates Foundation and others jovan Diabetes Foundation some companies and they're willing to give us funding and we've gotten government money as well we have a number of NIH grants and I've always had that and that's important to me too so so I worry about it but you know I just view that as a part of the process now if you put yourself in the shoes of a philanthropist it like say I gave you a hundred billion dollars right now but you couldn't spend on your own research mm-hmm so how how hard is it to decide which labs to invest in which ideas which problems which solutions you know cuz funding is so much such an important part of progression of science in today's society if you put yourself in the position of philanthropist how hard is that problem how would you go about solving it sure well I think what I do for the first thing is different philanthropists have different visions and I think the first thing is to form a concrete vision of what you want some people I mean I'll give just give you two examples of people that I know David Koch was very interested in cancer research and part of that was that he had cancer and prostate cancer and a number of people are do that along those lines they've had somebody they've either had cancer themselves or somebody they loved had cancer and they want to put money into cancer research bill gates on the other hand I think when he had got his fortune I mean he thought about it and felt well how could he have the greatest impact and he thought about you know helping people in the developing world and and and and medicines and different things like that that like vaccines that might be really helpful for people in the developing world and and so so I think first you start out with that vision once you start out with that vision whatever vision it is then I think you try to ask the question who in the world does the best work if that was your goal I mean but you really I think have to have a defined vision vision first yeah that that comes and and and I think that's what people do I mean I have never seen anybody do it otherwise I mean and and that by the way it may not be the best thing overall I mean I think I think it's good that all those things happen but you know what you really want to do and I'll make a contrast in a second in addition to funding important areas like what both of those people is to help young people and that they may be at odds with each other because a farm or a lab like ours which is you know I'm older is you know might be very good at addressing some of those kinds of problems but you know I'm not young I trained a lot of people who are young but it's not the same as helping somebody who's an assistant professor someplace so I think what's I think been good about our thing our society or things overall or that there are people who come at it from different ways and the combination the confluence of the government funding the certain foundations that that fund things and other foundations that you don't want to see disease treated well then they can go seek out people or they can put a request for proposals and see who does the best you know I'd say both David Koch and Bill Gates did exactly that they sought out people most of them you know or what are their foundations that they were involved in so I doubt people like myself but they also had requests for proposals now you mentioned young people and that reminds me something he said in an interview of written somewhere that said you're some of your initial struggles in that terms of finding a faculty position or so on they eat in quite for people fit into a particular bucket a particular right can you speak to that how do you see limitations to the academic system that it does have such buckets there's is there how can we allow for people who are brilliant but outside the disciplines of the previous decade yeah well I think that's a great question I think that I think the department has have to have a vision you know and some of them do every so often you know there are Institute's or labs that do that I mean at MIT I think that's done sometimes I know annika engineering department just had a search and they hired geo Traverso who was one of my he was a fellow with me and but he's he's actually a molecular biologist Anna and and a gastroenterologist and you know he's one of the best in the world but they but he's also done some great mechanical engineering and designing some new pills and things like that and they picked a man boy I give them a lot of credit I mean that's that's that's vision to pick somebody and I think you know they'll be the richer for I think the Media Lab is certainly hired you know people I get Boyden and others who depth on you know very different things and so I think that you know is that that that's part of the vision of the leadership who who do things like that do you think one day you mentioned David Koch and cancer do you think one day will cure cancer yeah I do I mean I coached one day I don't know how long that they will come soon but yeah so soon no but I mean I think do you think it is a grand challenge it is a grand challenges it's not just solvable within a few years not so I don't think very many things are solvable in a few years there's some good ideas that people are working on but I mean all cancers that's that's pretty tough if we do get the cure what will the Cure look like do you think which mechanisms which disciplines will help us arrive at that cure from all the amazing work you've done as touched on cancer no I think it'll be a combination of biology and engineering I think it'll be biology to understand the right genetic mechanisms to to solve this problem and maybe the right immunological mechanisms and engineering in the sense of you know producing the molecules developing the right delivery systems targeting it or whatever else needs to be done well that's a beautiful vision for engineering so on a lighter topic I've read that you love chocolate and mention two places venom Bill's chocolate thorium and the chocolate cookies the the Soho globs from Rosie's bakery Chestnut Hill I went to their website and I was trying to finish the paper last night there's a deadline today and yet house wasting way too much time at three instead of writing the paper staring at the rosey breakers cookies which or just look incredible the so whole globs just look incredible but for me oatmeal white raisin cookies it's not one my heart just from the pictures do you think one day we'll be able to engineer the perfect cookie with the help of chemistry and maybe a bit of data-driven artificial intelligence or is cookies something that's more art than engineering I think there's some of both I think I think engineer will probably help someday and what about chocolate same thing same thing you have to go to see some of David Edwards stuff you know he he was one of my postdocs and he's a professor at Harvard but he also started cafe arts sciences and you know it's just a really cool restaurant here but he also has companies that do you know ways of looking at fragrances and and trying to use engineering and in new ways and so I think that's just an example but I expect someday that AI and engineering will play a role and almost everything including creating the perfect cookie yes well I dream of that day as well so when you look back at your life having accomplished an incredible amount of positive impact on the world through science and engineering what are you most proud of my students you know I mean I really feel when I look at that I mean we've probably had you know close to a thousand students go through the lab and I mean they've done incredibly well I think 18 are in the National Academy of Engineering 16 and the National Academy of Medicine I mean they're you know they've been CEOs of companies presidents of universities I mean and Dave I mean they've done I think eight or faculty MIT maybe about 12 at Harvard I mean so you know it really makes you feel good to think that the people you know they're not my children but they're close to my children and in a way and you know makes you feel really good to see them have such great lives and them do so much good and be happy well I think that's the perfect way to end it Bob thank you so much for talking it was an honor good good questions thank you thanks for listening to this conversation with Bob Langer and thank you that sponsors cash app and master class please consider supporting the podcast by downloading cash app and using collects podcast and signing up at masterclass comm / Lex click on the links buy all the stuff it's the best way to support this podcast and the journey I'm on in my research and startup if you enjoy this thing subscribed by YouTube review it with five stars and half of podcast supported on patreon or connect with me on Twitter and Lex Friedman spelled without the e just Fri D ma N and now let me leave you some words for Bill Bryson in his book a short history of nearly everything if this book has a lesson is that we're awfully lucky to be here and by we I mean every living thing to obtain any kind of life in this universe of ours appears to be quite an achievement as humans were doubly lucky of course we enjoy not only the privilege of existence but also the singular ability to appreciate it and even in a multitude of ways to make it better it has talent we have only barely begun to grasp thank you for listening and hope to see you next time you |
David Patterson: Computer Architecture and Data Storage | Lex Fridman Podcast #104 | the following is a conversation with David Patterson Turing Award winner and professor of computer science at Berkeley he's known for pioneering contributions to RISC processor architecture used by 99% of new chips today and for co-creating RAID storage the impact that these two lines of research and development have had in our world is immeasurable he's also one of the great educators of computer science in the world his book with John Hennessy is how I first learned about and was humbled by the inner workings of machines at the lowest level quick summary of the ads to sponsors the Jordan Harbinger show and cash app please consider supporting the podcast by going to Jordan Harbinger complex and downloading cash app and using code Lexx podcast click on the links buy the stuff it's the best way to support this podcast and in general the journey I'm on in my research and startup this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it five stars in hype a podcast supported on patreon or connect with me on Twitter and Lex Friedman spelled without the e just Fri DM a.m. as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this episode is supported by the Jordan Harbinger show go to Jordan Harbinger calm / Lex it's how he knows I set you on that page there's links to subscribe to it an apple podcast Spotify and everywhere else I've been binging on this podcast it's amazing Jordan is a great human being he gets the best out of his guests - deep calls him out when it's needed it makes the whole thing fun to listen to he's interviewed Kobe Bryant Mark Cuban and Neil deGrasse Tyson and Garry Kasparov and many more I recently listened to his conversation with Frank Abagnale author of catch me if you can one of the world's most famous Kahneman perfect podcast length and topic for a recent long distance run that I did go to Jordan Harbinger complex to give him my love and to support this podcast subscribe also on Apple podcast Spotify and everywhere else this show is presented by cash app the greatest sponsor of this podcast ever and the number one finance app in the App Store when you get a used coat Lex podcast cash app lets you send money to friends buy bitcoin invest in the stock market with as little as one dollar since gas rep allows you to buy bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating I recommend the scent of money as a great book on this history also the audio book is amazing debits and credits on Ledger's started around 30,000 years ago the US dollar created over two hundred years ago and the first decentralized cryptocurrency released just over ten years ago so given that history cryptocurrencies still very much in its early days of development but it's still aiming to and just might redefine the nature of money so again if you get cash out from the App Store Google Play and use the code Lex podcast you get ten dollars and cash up will also donate ten dollars to first an organization that is helping to advance robotics to stem education for young people around the world and now here's my conversation with David Patterson let's start with the big historical question how have computers changed in the past 50 years at both the fundamental architectural level and in general in your eyes well the biggest thing that happened was the invention of the microprocessor so computers that used to fill up several rooms could fit inside your cell phone and not only and how do they get smaller they got a lot faster so they're million times faster than they were 50 years ago and they're much cheaper and they're RIBA covetous you know there's seven point eight billion people on this planet probably half of them have cell phones but you know just remarkable it's probably more micro processors than there are people sure I don't know what the ratio is but I'm sure it's above one maybe it's ten to one or some number like that what is a microprocessor so a way to say what a microprocessor is to tell you what's inside a computer so a computer forever has classically had five pieces there's input and output which kind of naturally as you'd expect is input is like speech or typing and output is displays there's a memory and like the name sounds it it remembers things so it's integrated circuits whose job is you put information in and when you ask for it it comes back out that's memory and the third part is the processor where the team microprocessor comes from and that has two pieces as well and that is the control which is kind of the brain of the processor and the what's called the arithmetic unit it's kind of the Brawn of the computer so if you think of the as a human body the arithmetic unit the thing that does the number crunching is the is the body and the control is the brain so those five pieces input/output memory arithmetic unit and control are have been in computers since the very dawn in the last two are considered the processor so a microprocessor simply means a process of the fits on a microchip and that was invented at about you know 40 years ago was the first microprocessor it's interesting that you refer to the arithmetic unit as the like he connected to the body and the controller's of the brain so I guess I never thought of it that was a nice way to think of it because most of the actions the microprocessor does in terms of literally sort of computation with the microprocessor does computation it processes information and most of the thing it does is basically earth net arithmetic operations what what are the operations by the way it's a lot like a calculator you know so there are add instructions a subtractive Stressless multiply and divide and kind of the brilliance of the invention of the my computer or the processor is that it performs very trivial operations but it just performs billions of them per second and what we're capable of doing is writing software that can take these very trivial instructions and have them create tasks that can do things better than human beings can do today just looking back through your career did you anticipate the kind of how good we would be able to get at doing these small basic operations I think what how many surprises along the way we just kind of set back and said wow I didn't expect it to go this fast this good well the the fundamental driving force is what scored Moore's law which was named after Gordon Moore who's a Berkeley alumnus and he made this observation very early in what are called semi conductors and semiconductors are these ideas you can build these very simple switches and you can put them on these microchips and he made his observation over 50 years ago he looked at a few years and said I think what's going to happen is the number of these little switches called transistors is going to double every year for the next decade and he said this in 1965 and in 1975 he said well maybe he's gonna double every two years and that I would other people since named that Moore's Law guided the industry and when Gordon Moore makes that prediction he he wrote a paper back in I think in the in the 70s and said not only did this going to happen he wrote what would be the implications of that and in this article from 1965 he he shows ideas like computers being in cars and computers being in something that you would buy in the grocery store and stuff like that so he kind of not only called his shot he called the implications of it so if you were in in the computing field and a few believed Moore's prediction he kind of said what the what would be happening in the future so so it's not kind of it's at one sense this is what was predicted and you could imagine it was easily believed that Moore's law was going to continue and so this would be the implications on the other side there are these shocking events in your life like I remember driving in meriem across the bay in San Francisco and seeing a bulletin board at a local Civic Center and had a URL on it uh and it was like if for all for all that's for the people at the time these first URLs and that's the you know ww select stuff with the HTTP people thought it was looks like alien alien writing right they'd see these advertisements and commercials or bulletin boards that had this alien writing on it so for the lay people is like what the hell is going on here and for those people interesting it's oh my god this stuff is getting so popular it's actually leaking out of our nerdy world and into the real world so that I mean there is events like that I think another one was I member with the in the early days of the personal computer when we started seeing advertisements in magazines for personal computers like it's so popular that it's it made the newspapers so at one hands you know Gordon Moore predicted it and you kind of expected it to happen but when it really hit and you saw it affecting society it was it was shocking so maybe taking a step back and looking both the engineering and philosophical perspective what what do you see as the layers of abstraction in the computer do you see a computer as a set of layers of abstractions yeah and I think that's one of the things that computer science fundamentals is the these things are really complicated in the way we cope with complicated software and complicated hardware is these layers of abstraction and that simply means that we you know suspend disbelief and pretend that the only thing you know is that layer and you don't know anything about the layer below it and that's the way we can make very complicated things and probably it started with hardware that's the way it was done but it's been proven extremely useful and you know I would think in a modern computer today there might be 10 or 20 layers of abstraction and they're all trying to kind of enforce this contract is all you know is this interface there's a set of commands that you can allow to use and you stick to those commands that we will faithfully execute that and it's like peeling the air layers of a London onion you get down there's a new set of layers and so forth so for people who want to study computer science the exciting part about it is you can keep peeling those layers you you take your first course and you might learn to program in Python and then you can take a follow-on course and you can get it down to a lower level language like C and you know you can go and you can if you want to you can start getting into the hardware layers and you keep getting down all the way to that transistor that I talked about that Gordon Moore predicted and you can understand all those layers all the way up to the highest level application software so it's it's a very kind of magnetic field if you're interested you can go into any depth and keep going in particular what's happening right now or it's happened in software last twenty years and recently in hardware there's getting to be open sourced versions of all of these things so what open source means is what the engineer the programmer designs it's not secret the belonging to a company it's up there on the World Wide Web so you can see it so you can look at for lots of pieces of software that you use you can see exactly what the programmer does if you want to get involved that used to stop at the hardware recently there's been an efforts to make open-source hardware and those interfaces open so you can see that so instead of before you had to stop at the hardware you can now start going layer by layer below that and see what's inside there so it's it's a remarkable time that for the interested individual can really see in great depth what's really going on and the computers that power everything that we see around us are you thinking also when you say open source at the hardware level is this going to the design architecture instruction set level or is it going to literally the the you know the manufacturer of the of the actual hardware of the actual chips whether that's a six specialized a particular domain or the general yeah so let's talk about that a little bit so when you get down to the bottom layer of software the way software talks to hardware is in a vocabulary and what we call that vocabulary we call that the words of that vocabulary called instructions in the technical term for the vocabulary is instruction set so those instructions are likely we talked about earlier that can be instructions like add subtract and multiply divide there's instructions to put data into memory which is called a store instruction and to get data back which is called the load instructions and those simple instructions go back to the very dawn of computing in you know in 1950 the commercial commercial computer had these instructions so that's the instruction set that we're talking about so up until I'd say ten years ago these instruction sets are all proprietary so a very popular one is Alden by Intel the one that's in the cloud and then all the pcs in the world the Intel owns that instruction set it's referred to as the x86 there have been a sequence of ones that the first number was called 8086 and since then there's been a lot of numbers but they all end in 86 so there's then that kind of family of instruction sets and that's proprietary and that's proprietary the other one that's very popular is from arm that kind of powers all of all the cell phones in the world all the iPads in the world and a lot of things that are so-called Internet of Things devices arm and that one is also proprietary arm will license it to people for a fee but they own that so the new idea that got started at Berkeley kind of unintentionally ten years ago is in early in my career we pioneered a way to do of these vocabularies instruction sets that was very controversial at the time at the time in the 1980s conventional wisdom was these vocabularies instruction sets should have you know powerful instructions so polysyllabic kind of words you can think of that and and so that instead of just add subtract and multiply they would have polynomial vied or sort a list and the hope was of those powerful vocabularies that make it easier for software so we thought that didn't make sense for microprocessors servers people at Berkeley and Stanford and IBM who argued the opposite and we what we called that was a reduced instruction set computer in the abbreviation was our ISC and typical for computer people we use the abbreviations start pronouncing it so risk was there so we said for microprocessors which with Gordon's Moore is changing really fast we think it's better to have a pretty simple set of instructions reduce set of instructions that that would be a better way to build microprocessors since they're going to be changing so fast due to Moore's law and then we'll just use standard software to cover the used generate more of those simple instructions and one of the pieces of software that it's in a software stack going between these layers of abstractions is called a compiler and it basically translates it's a translator between levels we said the translator will handle it so the technical question was well since there are these reduced instructions you have to execute more of them yeah that's right but maybe they execute them faster yeah that's right there's simpler so they could go faster but you have to do more of them so what's what's that trade-off look like and it ended up that we ended up executing maybe 50 percent more instructions maybe 1/3 more instructions but they ran four times faster so so this risk controversial risk ideas proved to be maybe factors of three or four better I love that this idea was controversial and most kind of like a rebellious so that's in the context of what was more conventional is the complex instruction set competing so how'd you pronounce that Sisk Sisk risk vs. Sisk and and believe it or not this sounds very very you know who cares about this right it was it was violently debated at several conferences it's like what's the brightman ago is is and people thought risk was you know was de-evolution we're gonna make software worse by making death instructions simpler and they're fierce debates at several conferences in the 1980s and then later in the eighties that kind of settled to these benefits it's not completely intuitive to me why risk has for the most part one yes so why do that happen yeah yeah and maybe I can sort of say a bunch of dumb things that could lay the land for further commentary so to me and this is a this is kind of interesting thing if you look at C++ was just see with modern compilers you really could write faster code with C++ so relying on the compiler to reduce your complicated code into something simple and fast so to me comparing risk maybe this is a dumb question but why is it that focusing the definition the design of the instruction set on very few simple instructions in the long run provide faster execution versus coming up with like I said a ton of complicated instructions then over time you know years maybe decades you come up with compilers that can reduce those into simple instructions for you yeah some let's try and split that into two pieces so if the compiler can do that for you if the pilot can take you know a complicated program and produce simpler instructions then the programmer doesn't care right programmer yeah yeah I don't care just how how fast is the computer I'm using how much does it cost and so what we what and kind of in the software industry is right around before the 1980s critical pieces of software we're still written not in languages like C or C++ they were written in what's called assembly language where there's this kind of humans writing exactly at the instructions at the level then that a computer can understand so they were writing add subtract multiply you know instructions it's very tedious but the belief was to write this lowest level of software that the people use which are called operating systems they had to be written in assembly language because these high-level languages were just too inefficient they were too slow or the the programs would be too big so that changed with a famous operating system called UNIX which is kind of the grandfather of all the operating systems today so the UNIX demonstrated that you could write something as complicated as an operating system in a language like C so once that was true then that meant we could hide the instruction set from the programmer and so that meant then it didn't really matter the programmer didn't have to write lots of these simple instructions so that was up to the compiler so that was part of our arguments for risk is if you were still writing assembly languages maybe a better case for sis constructions but if the compiler can do that it's gonna be you know that's done once the computer translates it once and then every time you run the program it runs that this this potentially simpler instructions and so that that was the debate right is because and people would acknowledge that these simpler instructions could lead to a faster computer you can think of mono syllabic constructions you could say them you know if you think of reading you probably read them faster or say them faster than long instructions the same thing that analogy works pretty well for hardware and as long as you didn't have to read a lot more of those instructions you could win so that's that's kind of that's the basic idea for risk but it's interesting that the in that discussion of UNIX to see that there's only one step of levels of abstraction from the code that's really the closest to the machine to the code that's written by human it's uh at least to me again perhaps a dumb intuition but it feels like there might have been more layers sort of different kinds of humans stacked as well of each other so what's true and not true about what you said is several of the layers of software like so the if you hear two layers would be suppose we just talked about two layers that would be the operating system like you get from from Microsoft or from Apple like iOS or the Windows operating system and let's say applications that run on top of it like Word or Excel so both the operating system could be written in C and the application could be written in C so but you could construct those two layers and the applications absolutely do call upon the operating system and the change was that both of them could be written in higher-level languages so it's one step of a translation but you can still build many layers of abstraction of software on top of that and that's how how things are done today so still today many of the layers that you'll you'll deep deal with you may deal with debuggers you may deal with linkers there's libraries many of those today will be written in c++ say even though that language is pretty ancient and even the Python interpreter is probably written in C or C++ so lots of layers there are probably written in these some old fashioned efficient languages that still take one step to produce these instructions produce RISC instructions but they're composed each layer of software invokes one another through these interfaces and you can get ten layers of software that way so in general the risk was developed here Berkeley it was kind of the three places that were these radicals that advocated for this against the rest of community where IBM Berkeley and Stanford you're one of these radicals and how radical did you feel how confident did you feel how doubtful were you that risk might be the right approach because it may you can also Intuit that is kind of taking a step back into simplicity not forward into simplicity yeah no it was easy to make yeah it was easy to make the argument against it well this was my colleague John Hennessy at Stanford and I we were both assistant professors and for me I just believed in the power of our ideas I thought what we were saying made sense Moore's Law is going to move fast the other thing that I didn't mention is one of the surprises of these complex instruction sets you could certainly write these complex instructions if the programmer is writing them in themselves it turned out to be kind of difficult for the compiler to generate those complex instructions kind of ironically you'd have to find the right circumstances that that just exactly fit this complex instruction it was actually easier for the compiler to generate these simple instructions so not only did these complex instructions make the hard work more difficult to build often the compiler wouldn't even use them and so it's harder to build the compiler doesn't use them that much the simple instructions go better with Moore's Law that's you know the number of transistors is doubling every every two years so we're gonna have you know the you want to reduce the time to design the microprocessor that may be more important than these number instructions so I think we believed in the that we were right that this was the best idea then the question became in these debates well yeah that's a good technical idea but in the business world this doesn't matter there's other things that matter it's like arguing that if there's a standard with the railroad tracks and you've come up with a better with but the whole world has covered railroad tracks so you'll your ideas have no chance of success commercial success it was technically right but commercially it'll be insignificant yeah this it's kind of sad that this world the history of human civilization is full of good ideas that lost because somebody else came along first with a worse idea and it's good that in the computing world at least some of these have well well you could are I mean it's probably still sisk people that say yeah still are but and what happened was what was interesting Intel a bunch of the system companies with Sisk instruction sets of vocabulary they gave up but not Intel what Intel did to its credit because Intel's vocabulary was in the in the personal computer and so that was a very valuable vocabulary because the way we distribute software is in those actual instructions it's in the instructions of that instruction set so they then you don't get that source code what the programmers wrote you get after it's been translated into the last level that's if you were to get a floppy disk or download software it's in the instructions that instruction set so the x86 instruction set was very valuable so what Intel did cleverly and amazingly is they had their chips in hardware do a translation step they would take these complex instructions and translate them into essentially in RISC instructions in Hardware on the fly you know at at gigahertz clock speeds and then any good idea that risk people had they could use and they could still be compatible with us with this really valuable PC software software base and which also had very high volumes you know a hundred million personal computers per year so the sisk architecture in the business world was actually one in in this PC era so just going back to the the time of designing risk when you design an instruction set architecture do you think like a programmer do you think like a microprocessor engineer do you think like a artist a philosopher do you think in software and hardware I mean is it art I see science yeah I'd say I think designing a goods instruction set as an art and I think you're trying to balance the the simplicity and speed of execution with how well easy it will be for compilers to use it alright you're trying to create an instruction set that everything in there can be used by compilers there's not things that are missing that'll make it difficult for the program to run they run efficiently but you want it to be easy to build as well so it's that kind of so you're thinking I'd say you're thinking hard we're trying to find a hardware software compromise that'll work well and and it's you know it's you know it's a matter of taste right it's it's kind of fun to build instruction sets it's not that hard to build an instruction set but to build one that catches on and people use you know you have to be you know fortunate to be the right place at the right time or have a design that people really like are using metrics says is it quantifiable because you kind of have to anticipate the kind of programs that people will write yet ahead of time so is that can you use numbers can use metrics can you quantify something ahead of time or is this again that's the art part where you're kind of knows it's a a big a big change kind of what happened I think from Hennessey's and my perspective in the 1980s what happened was going from kind of really you know taste and hunches to quantifiable in in fact he and I wrote a textbook at the end of the 1980s called computer architecture a quantitative approach I heard of that and and it's it's the thing it it had a pretty big big impact in the field because we went from textbooks that kind of listed so here's what this computer does and here's the pros and cons and here's what this computer doesn't pros and cons to something where there were formulas in equations where you could measure things so specifically for instruction sets what we do in some other fields do is we agree upon a set of programs which we call benchmarks and a suite of programs and then you develop both the hardware and the compiler and you get numbers on how well your your computer does given its instruction set and how well you implemented it in your microprocessor and how good your compilers are and in computer architecture we you know using professors terms we grade on a curve rather than greater than absolute scale so when you say you know this these programs run this fast well that's kind of interesting but how do you know it's better while you compare it to other computers at the same time so the best way we know how to make turned it into a kind of more science and experimental and quantitative is to compare yourself to other computers or the same era that have the same access the same kind of technology on commonly agreed benchmark programs so maybe two toss-up two possible directions we can go one is what are the different trade-offs in designing architectures Ubben are you talking about Siskin risk but maybe a little bit more detail in terms of specific features that you were thinking about and the other side is what are the metrics that you're thinking about when looking at these trade-offs yeah well let's talk about the metrics so during these debates we actually had kind of a hard time explaining convincing people the ideas and partly we didn't have a formula to explain it and a few years into it we hit upon the formula that helped explain what was going on and I think if we can do this see how it works orally just is this so the yes if I can do a formula or Li L C so the so fundamentally the way you measure performance is how long does it take a program to run a program if you have ten programs and typically these benchmarks were sweet because you'd want to have ten programs so they could represents lots of different applications so for these ten programs how long they take to run now when you're trying to explain why it took so long you could factor how long it takes a program to run into three factors one of the first one is how many instructions did it take to execute so that's the that's the what we've been talking about you know the instructions of Academy how many did it take all right the next question is how long did each instruction take to run on average so you multiply the number instructions times how long it took to run and that gets you help okay so that's but now let's look at this metric of how long did it take the instruction to run well it turns out the way we could build computers today is they all have a clock and you've seen this when you if you buy a microprocessor it'll say 3.1 gigahertz or 2.5 gigahertz and more gigahertz is good well what that is is the speed of the clock so 2.5 gigahertz turns out to be 4 billions of instruction or 4 nanoseconds so that's the clock cycle time but there's another factor which is what's the average number of clock cycles that takes per instructions so it's number of instructions average number of clock cycles in the clock cycle time so in these risks ist's debates we would we they would concentrate on but wrist makes needs to take more instructions and we'd argue what maybe the clock cycle is faster but what the real big difference was was the number of clock cycles per instruction or instruction as fascinating what about the mess up the beautiful mess of parallelism in the whole picture parallelism which has to do was say how many instructions could execute in parallel and things like that you could think of that as affecting the clock cycles per instruction because it's the average clock cycles per instruction so when you're running a program if it took a hundred billion instructions and on average it took two clock cycles per instruction and they were four nanoseconds you could multiply that out and see how long it took to run and there's all kinds of tricks to try and reduce the number of clock cycles per instruction but it turned out that the way they would do these complex instructions is they would actually build what we would call an interpreter in a simpler a very simple hardware interpreter but it turned out that for sis constructions if you had to use one of those interpreters it would be like 10 clock cycles per instruction where the risk instructions could be too so there'd be this factor of five advantage in clock cycles per instruction we have to execute say 25 or 50 percent more instructions so that's where the wind would come and then you could make an argument whether the clock cycle times are the same or not but pointing out that we could divide the benchmark results time per program into three factors and the biggest difference between risk consists was the clock cycles per you execute a few more instructions but the clock cycles per instruction is much less and that was what this debate once we made that argument then people say okay I get it and so we went from it was outrageously controversial in you know 1982 that maybe probably by 1984 so people said oh yeah technically they've got a good argument what are the instructions in the RISC instruction set just to get an intuition okay 1995 I was asked scientific the future of what microprocessor so I and that well as I'd seen these predictions and usually people predict something outrageous just to be entertaining right and so my prediction for 2020 was you know things are gonna be pretty much they're gonna look very familiar to what they are and they are in if you were to read the article you know the things I said are pretty much true the instructions that have been around forever are kind of the same and that's the outrageous prediction actually yeah given how fast computers and well you know Moore's law was gonna go on we thought for 25 more years you know who knows but kind of the surprising thing in fact you know Hennessy and I you know won the the ACM a.m. Turing award for both the RISC instruction set contributions and for that textbook I mentioned but you know we are surprised that here we are 35 40 years later after we did our work and the the conventional wisdom of the best way to do instruction sets is still those RISC instruction sets that look very similar to what we look like you know we did in the 1980s so those surprisingly there hasn't some radical new idea even though we have you know a million times as many transistors as we had back then but what are the basic constructions and how did they change over the years so we're talking about addition subtract these are the specific so the the to get so the things that are in a calculator you are in a computer so any of the buttons that are in the calculator in the crater so the little button so if there's a memory function key and like I said those are turns into putting something in memories called a store bring something back Scott load just as a quick tangent when you say memory what does memory mean well I told you there were five pieces of a computer and if you remember in a calculator there's a memory key so you you want to have intermediate calculation and bring it back later so you'd hit the memory plus key M plus maybe and it would put that into memory and then you'd hit an REM like return instruction and it bring it back in the display so you don't have to type it you don't have to write it down bring it back again so that's exactly what memory is if you can put things into it as temporary storage and bring it back when you need it later so that's memory and loads and stores but the big thing the difference between a computer and a calculator is that the computer can make decisions and in amazingly the decisions are as simple is is this value less than zero or is this value bigger than that value so there's and those instructions which are called conditional branch instructions is what give computers all its power if you were in the early days of computing before the what's called the general-purpose microprocessor people would write these instructions kind of in hardware and but it couldn't make decisions it would just it would do the same thing over and over again with the power of having branch instructions that can look at things and make decisions automatically and it can make these decisions you know billions of times per second and amazingly enough we can get you know thanks to advances machine learning we can we can create programs that can do something smarter than human beings can do but if you go down that very basic level it's the instructions are the keys on the calculator plus the ability to make decisions of these conditional branch instructions you know and all decisions fundamental can be reduced down to these - assumptions yeah so in in fact and so you know going way back in the sack back to you know we did for risk projects at Berkeley in the 1980s they did a couple at Stanford in the 1980s in 2010 we decided we wanted to do a new instruction set learning from the mistakes of those RISC architectures of 1980s and that was done here at Berkeley almost exactly 10 years ago in the the people who did it I participated but other Christos Sanne and others drove it they called it risk 5 to honor those risk the four risk projects of 1980s so what is risk 5 involved so leaders 5 is another instruction set of vocabulary it's learned from the mistakes of the past but it still has if you look at the there's a core set of instructions it's very similar to the simplest architectures from the 1980s and the big difference about risk 5 is it's open so I talked early about proprietary versus open and kind of sauce software so this is an instruction set so it's a vocabulary it's not it's not hardware but by having an open instruction set we can have open source implementations open source processors that people can use where do you see that going says it's the really exciting possibilities but she's just like in the Scientific American if you were to predict 10 20 30 years from now that kind of ability to utilize open source instruction set architectures like risk 5 what kind of possibilities might that unlock yeah and so just to make it clear because this is confusing the specification of risk 5 is something that's like in a text book there's books about it so that's what that's kind of defining an interface there's also the way you build hardware is you write it in languages they're kind of like sea but they're specialized for hardware that gets translated into hardware and so these implementations of this specification are what are the open source so they're written in something that's called Verilog or VHDL but it's put up on the web like that you can see the C++ code for Linux on the web so that's the open instruction set enables open source implementations at risk five so you can literally build a processor using this instruction set people are and people are so what happened to us that the story was this was developed here for our use to do our research and we made it we licensed under the berkeley software distribution license like a lot of things get licensed here so other academics use it they wouldn't be afraid to use it and then about 2014 we started getting complaints that we were using it in our research in our courses and we got complaints from people in industries why did you change your instruction set between the fall and the spring semester and well we get complaints of additional time why the hell do you care what we do with our instruction set and then when we talked to him we found out there was this thirst for this idea of an open instruction set architecture and they had been looking for one they stumbled upon ours at Berkeley thought it was boy this looks great we should use this one and so once we realize there is this need for an open instruction set architecture we thought that's a great idea and then we started supporting it and tried to make it happen so this was you know kind we accidentally stumbled into this and to this need in our timing was good and so it's really taking off there's a you know universities are good at starting things but the not good it's sustaining things so like Linux has the Linux Foundation there's a risk 5 foundation that we started there's there's an annual conferences and the first one was done I think January 2015 and the one that was just last December in it you know it had 50 people at it and the last one last December had kind of 1,700 people were at it and the companies excited all over the world so if predicting into the future you know if we were doing 25 years I would predict that risk 5 will be you know possibly the most popular instruction set architecture out there because it's a pretty good instruction set architecture and it's open and free and there's no reason lots of people shouldn't use it and there's benefits just like Linux is so popular today compared to 20 years ago I and you know the fact that you can get access to it for free you can modify it you can improve it for all those same arguments and so people collaborate to make it a better system for all everybody to use and that works in software and I expect the same thing will happen in hardware so if you look at arm Intel mips if you look at just the lay of the land and what do you think just for me because I'm not familiar how difficult this kind of transition would how much challenges this kind of transition would entail do you see let me ask my dumb question another one no that's I know where you're headed well there's a budget I think the thing you point out there's there's these proprietary popular proprietary instruction sets the x86 and so how do we move to risk five potentially in sort of in the span of five 10 20 years a kind of a unification in given that the device is the kind of way we use devices IOT mobile devices and and the cloud keeps changing well part of it a big piece of it is the software stack and what right now looking forward there seem to be three important markets there's the cloud and then the cloud is simply companies like Alibaba and Amazon and Google Microsoft having these giant data centers with tens of thousands of servers in maybe a hunt maybe a hundred of these data centers all over the world and that's what the cloud is so the computer that dominates the cloud is the x86 instruction set so the instructions are the vocal instructor sets using the cloud of the x86 almost almost 100% of that today is x86 the other big thing are cell phones and laptops those are the big things today I mean the PC is also dominated by the x86 instruction set but those sales are dwindling you know there's maybe 200 million pcs a year and there's I serve one and a half billion phones a year there's numbers like that so for the phones that's dominated by arm and now and a reason that I talked about the software stacks and then the third category is Internet of Things which is basically embedded devices things in your cars and your microwaves everywhere so what's different about those three categories is for the cloud the software that runs in the cloud is determined by these companies Alibaba Amazon Google Microsoft so that they control that software stack for the cell phones there's both for Android and Apple the software they supply but both of them have marketplaces where anybody in the world can build software and that software is translated or you know compiled down and shipped in the vocabulary of arm so that's the the what's referred to as binary compatible because the actual it's the instructions are turned into numbers binary numbers and shipped around the world so and the size just a quick interruption so arm what is arm as arm is an instructions like a risk-based yeah it's a risk-based instruction as a proprietary one arm stands for advanced RISC machine erm is the name where the company is so it's a proprietary RISC architecture so and it's been around for a while and you know the surely the most popular instruction set in the world right now they every year billions of chips are using the arm design in this post PC era is what it was the one of the early risk adopters of the risk yeah yeah the first arm goes back I don't know 86 or so so Berkeley instead did their work in the early 80s their arm guys needed an instruction set and they read our papers and it heavily influenced them so getting back my story what about Internet of Things well software's not shipped in Internet of Things it's the the embedded device people control that software stack so you would the opportune these four risk five everybody thinks is in the internet of things embedded things because there's no dominant player like there is in the cloud or the smartphones and you know it's it's doesn't have a lot of licenses associated with and you can enhance the instruction set if you want and it's a in and people have looked at instruction sets and think it's a very good instruction set so it appears to be very popular there it's possible that in the cloud people those companies control their software stacks so that it's possible that they would decide to use verse five if we're talking about ten and twenty years in the future the one of the be harder it would be the cell phones since people ship software in the arm instruction set that you'd think be the more difficult one but if if risk five really catches on and you know you could in a period of a decade you can imagine that's changing over to give a sense why risk five our arm is dominated you mentioned these three categories why has why did arm dominate why does it dominate the mobile device base and maybe the my naive intuition is that there are some aspects of power efficiency that are important yeah that somehow come along with risk well part of it is for these old Siskin structions that's like in the x86 it it was more expensive to these for the you know they're older so they have disadvantages in them because they were designed forty years ago but also they have to translate in hardware from sis constructions to risks instructions on the fly and that costs both silicon area that the chips are bigger to be able to do that and it uses more power so arm his which has you know followed this risk philosophy is seen to be much more energy-efficient and in today's computer world both in the cloud in cell phone and you know things it isn't the limiting resource isn't the number of transistors you can fit in the chip it's what how much power can you dissipate for your application so by having a reduced instruction set you that's possible to have a simpler hardware which is more energy efficient in energy efficiency is incredibly important in the cloud when you have tens of thousands of computers in a datacenter you want to have the most energy-efficient ones there as well and of course for embedded things running off of batteries you want those to be energy efficient in the cell phones too so it I think it's believed that there's a energy disadvantage of using these more complex instruction set architectures so the other aspect of this is if we look at Apple Qualcomm Samsung Huawei all use the ARM architecture and yet the performance of the systems varies I mean I don't know whose opinion you take on but you know Apple for some reason seems to perform better and try these implementations architecture so where's the magic and sure that happened yeah so what arm pioneered was a new business model as they said well here's our proprietary instruction set and we'll give you two ways to do it eat there we'll give you one of these implementations written in things like C called Verilog and you can just use ours well you have to pay money for that not only pay will give you the you know will license use to do that or you could design your own and so we're talking about numbers like tens of millions of dollars to have the right to design your own since they it's the instruction set belongs to them so Apple got one of those the right to build their own most of the other people who build like Android phones just get one of the designs from arm and to do it themselves so Apple developed a really good microprocessor design team they you know acquired a very good team that had was a building other microprocessors and brought them into the company to build their designs so the instruction sets are the same the specifications are the same but their hardware design is much more efficient than I think everybody else's and that's given Apple an advantage in the marketplace and that the iPhones tend to be the faster than most everybody else's phones that are they it'd be nice to be able to jump around and kind of explore different little sides of this but let me ask one sort of romanticized question what to you is the most beautiful aspect or idea of risk instruction set or instruction sets for this you know what I think that you know I I'm you know I I was always attracted to the idea of you know smallest beautiful why is that the temptation in engineering it's kind of easy to make things more complicated it's harder to come up with a it's more difficult surprising they come up with a simple elegant solution and I think that there's a bunch of small features of of risk in general that you know where you can see this examples of keeping it simpler makes it more elegant specifically in risk five which you know I'm I was kind of the mentor in the program but it was really driven by christos sama and two grad students Andrew Waterman Yin Sibley is they hit upon this idea of having a subset of instructions a nice simple instruction subset instructions like 40-ish instructions that all software the software status v can run just on those forty instructions and then they provide optional features that could accelerate the performance instructions that if you needed them could be very helpful but you don't need to have them and that that's a new really a new idea so risk five has right now maybe five optional subsets that you can pull in but the software runs without them if you just want to build the just the core forty instructions that's fine you can do that so this is fantastic educationally is so you can explain computers you only have to explain forty instructions and not thousands of them also if you invent some wild and crazy new technology like you know biological computing you'd like a nice simple instruction set and you can risk 5e if you implement those core instructions you can run you know really interesting programs on top of that so this idea of a core set of instructions that the software stack runs on and then optional features that if you turn them on the compilers where used but you don't have to I think is a powerful idea what's happened in the past if for the proprietary instruction sets is when they add new instructions it becomes required piece and so that all all microprocessors in the future have to use those instructions so it's kind of like is for a lot of people as they get older they gain weight all right is it that weight and age are correlated and so you can see these instruction sets get getting bigger and bigger as they get older so risk five you know let's you be as slim as your as a teenager and you only have to add these extra features if you're really gonna use them rather than every you have no choice you have to keep growing with the instruction set I don't know if the analogy holds out but that's a beautiful notion that there's it's almost like a nudge towards here's the simple core that's the essential yeah I think the surprising thing is still if we if we brought back you know the pioneers from the 1950s and showed them the instruction set architectures they'd understand it they that doesn't look that different well you know I'm surprised and it's if there's it may be something you know to talk about philosophical things I mean there may be something powerful about those you know forty or fifty instructions that all you need is these commands like these instructions that we talked about and that is sufficient to build to bring upon you know artificial intelligence and so it's a remarkable surprising to me that is complicated Minoo microprocessors where the line widths are narrower than the wavelength of light you know is this amazing technologies at some fundamental level the commands that software execute are really pretty straightforward and haven't changed that much in in decades it's what a surprising outcome so underlying all computation all Turing machines all artificial intelligent systems perhaps might be a very simple instruction set like like a risk 5 or it's yeah I mean I that's kind of what I said I was interested to see I had another more senior faculty colleague and he he had written something in Scientific American in you know his 25 years in the future and his turned out about when I was a young professor and he said yep I checked it I was interest to see how that was going to turn out for me and it's pretty held up pretty well but yeah so there's there's probably there's something I you know there's there must be something fundamental about those instructions that were capable of creating you know intelligence and from pretty primitive operations and just doing them really fast you kind of mentioned the different maybe radical computational medium like biological and there's other ideas so there's a lot of spaces in a6 or domain-specific and then there could be quantum computers and wood so we couldn't think of all those different mediums and types of computation what's the connection between swapping out different Hardware systems and the instruction set do you see those as disjoint or they fundamentally coupled yeah so what's so kind of if we go back to the history you know when Moore's Law is in full effect and you're getting twice as many transistors every couple of years you know kind of the challenge for computer designers is how can we take advantage of that how can we turn those transistors into better computers faster typically and so there was an era I guess in the 80s and 90s where computers were doubling performance every 18 months and if you weren't around then what would happen is you had your computer and your friend's computer which was like a year year and a half newer and it was much faster than your computer and you he he or she could get their work done much faster than your typical user so people took their computers perfectly good computers and threw them away to buy a newer computer because the computer one or two years later was so much faster so that's what the world was like in 80s and 90s well with the slowing down of Moore's law that's no longer true right he not now with you know not decide computers with the laptops I only get a new laptop when it breaks right well damn the disk broke or this display broke I got to buy a new computer but before you would throw them away because it just they were just so sluggish compared to the latest computers so that's you know that's a huge change of what's gone on so but yes since this lasted for decades kind of programmers and maybe all society is used to computers getting faster regularly it we now now believe those of us who are in computer design it's called computer architecture that the path forward is instead is to add accelerators that only work well for certain applications so since Moore's law is slowing down we don't think general-purpose computers are gonna get a lot faster so the Intel processors of the world are not going to haven't been getting a lot faster they've been barely improving like a few percent a year it used to be doubling your 18 months and now it's doubling every 20 years so it was just shocking so to be able to deliver on what Moore's law used to do we think what's going to happen what is happening right now is people adding accelerators to their microprocessors that only work well for some domains and by sheer coincidence at the same time that this is happening has been this revolution in artificial intelligence called machine learning so with as I'm sure your other guess I've said you know a I had these two competing schools of thought is that we could figure out artificial intelligence by just writing the rules top-down or that was wrong you had to look at data and infer what the rules are the machine learning and what's happened in the last decade or eight years this machine learning has won and it turns out that machine learning the hardware you built from learning is pretty much multiply the matrix multiply is a key feature for the way people machine learning is done so that's a godsend for computer designers we know how to make metrics multiply run really fast so general-purpose microprocessors are slowing down we're adding accelerators from machine learning that fundamentally are doing matrix multiplies much more efficiently than general-purpose computers have done so we have to come up with a new way to accelerate things the danger of only accelerating one application is how important is that application turns it turns out machine learning gets used for all kinds of things so serendipitously we found something to accelerate that's widely applicable and we don't even we're in the middle of this revolution of machine learning we're not sure what the limits of machine learning are so this has been kind of a godsend if you're going to be able to Excel deliver on improved performance as long as people are moving their programs to be embracing more machine learning we know how to give them more performance even as Moore's Law is slowing down and counter-intuitively the machine learning mechanism you can say is domain-specific but because it's leveraging data it's actually could be very broad in terms of in terms of the domains it could be applied in yeah that's exactly right sort of it's almost sort of people sometimes talk about the idea of software 2.0 we're almost taking another step up in the abstraction layer in designing machine learning systems because now you're programming in the space of data in the space of hyper parameters it's changing fundamentally the nature of programming and so the specialized devices that that accelerate the performance especially neural network based machine learning systems might become the new general yes so the this thing that's interesting point out these are not coral these are not tied together the it's enthusiasm about machine learning about creating programs driven from data that we should figure out the answers from rather than kind of top down which classically the way most programming is done in the way artificial intelligent used to be done that's a movement that's going on at the same time coincidentally and the the first word machine learnings machines right so that's going to increase the demand for computing because instead of programmers being smart writing those those things down we're going to instead use computers to exam a lot of data to kind of create the programs that's the idea and remarkably this gets used for all kinds of things very successfully the image recognition the language translation the game playing and you know it gets into pieces of the software stack like databases and stuff like that we're not quite sure how journal purposes but that's going on independent as Hardware stuff what's happening on the hardware side is Moore's Law is slowing down right when we need a lot more cycles it's failing us it's failing us right when we need it because there's going to be a greater in peace a greater increase in computing and then this idea that we're going to do so-called domain-specific here's a domain that your greatest fear is you'll make this one thing work and that'll help you know 5% of the people in the world well this this looks like it's a very general-purpose thing so the timing is fortuitous that if we can perhaps if we can keep building hardware that will accelerate machine learning the neural networks that'll beat the timing D right that that neural network revolution will transform your software the so called software 2.0 and the software the future will be very different from the software the past and just as our microprocessors even though we're still going to have that same basic risk instructions to run a big pieces of the software stack like user interfaces and stuff like that we can accelerate the the kind of the small piece that's computationally intensive it's not lots of lines of code but there it takes a lot of cycles to run that code that that's going to be the accelerator piece and so this that's what makes this from a computer designer's perspective a really interesting decade but Hennessy and I talked about that the title of our Turing warrant speech is a new golden age we we see this as a very exciting decade much like when we were assistant professors and the wrists stuff was going on that was a very exciting time was where we were changing what was going on we see this happening again tremendous opportunities of people because we're fundamentally changing how software is built and how we're running it so which layer of the abstraction do you think most of the acceleration might be happening the if you look in the next ten years that Google is working on a lot of exciting stuff with the TPU sort of there's a closer to the hardware that could be optimizations around the IROC closer to the instruction set that could be optimization at the compiler level it could be even at the higher level software stack yeah it's going to be I mean if you think about the old risks this debate it was both it was software hardware it was the compilers improving as well as the architecture improving and that that's likely to be the way things are now with machine learning they they're using domain-specific languages the languages like tensorflow and pi torch are very popular with the machine learning people that those are the raising the level of abstraction it's easier for people to write machine learning in these domain-specific languages like like a PI torch in tensorflow so where the most of the optimization but yeah and so that and so there'll be both the compiler piece and the hardware piece underneath it so as you kind of the fatal flaw for hardware people is to create really great hardware but not have brought along the compilers and what we're seeing right now in the marketplace because of this enthusiasm around hardware for machine learning is getting you know probably a billions of dollars invested in start-up companies we're seeing startup companies go belly-up because they focus on the hardware but didn't bring the software stack along we talked about benchmarks earlier so I participated in machine learning didn't really have a set of benchmarks I think just two years ago they didn't have a set of benchmarks and we've created something called ml perf which machine learning benchmark suite and pretty much the companies who didn't invest in the software stack couldn't run a ml per fairy wall and the ones who did invest in software stack did and we're seeing you know like kind of in computer architecture this is what happens you have these arguments about risk versus ist's people spend billions of dollars in the marketplace to see who wins and it's not it's not a perfect comparison but it kind of sorts things out and we're seeing companies go out of business and then companies like like there's a company in Israel called Habana they came up with machine learning accelerators that they had good ml perf scores Intel had acquired a company earlier called nirvana a couple years ago they didn't reveal the amount of Perth's cores which was suspicious but month ago Intel announced that they're cancelling the Nirvana product line and they've bought Habana for two billion dollars and Intel's going to be shipping Habano chips which have hardware and software and run the ml perf programs pretty well and that's going to be their product line in the future brilliant so maybe just a linker briefly I'm a love metrics I love standards that everyone can gather around what are some interesting aspects of that portfolio of metrics well one of the interesting metrics is you know what we thought it was you know we I was involved in the start you know we that Peter Matson is leading the effort from Google Google got it off the ground but we had to reach out to competitors and say there's no benchmarks here this we didn't we think this is bad for the field it'll be much better if we look at examples like in the wrist days there was an effort to create a for the the people in the risk community got together competitors got together a building risk microprocessors to agree on a set of benchmarks that we called spec and that was good for the industry is rather before the different risk architectures were arguing well you can believe my performance others but those other guys are liars and that didn't do any good so we agreed on a set of benchmarks and then we could figure out who is faster between the various risk architectures but it was a little bit faster but that drew the market rather than you know people were afraid to buy anything so we argued the same thing would happen with him helper you know companies like Nvidia were you know maybe worried that it was some kind of trap but eventually we all got together to create a set of benchmarks and do the right thing right and we agree on the results and so we can see whether TP use or GPUs or CPUs are really faster than how much the faster and I think from an engineer's perspective as long as the results are fair Europe you can live with it okay you know you have a tip your hat to to your colleagues at another institution boy they did a better job than this what you what you hate is if it's it's false right they're making claims and it's just marketing and you know in that's affecting sales so you from an engineer's perspective as long as it's a fair comparison and we don't come in first place that's too bad but it's fair so we wanted to create that environment frame all perf and so now there's ten companies I mean ten universities and fifty companies involved so pretty much AML perf has is the is the way you measure machine learning performance and and it didn't exist even two years ago one of the cool things that I enjoy about the Internet has a few downsides but one of the nice things is people can see through BS a little better with the presence yes has a metrics it's so it's really nice a companies like Google and Facebook and Twitter now it's the cool thing to do is to put your engineers forward and to actually show off how well you do on these metrics there's not sort of it well there's a less of a desire to do marketing a less so in my in my sort of naive no I don't think well I was trying to understand that you know what's changed from the 80s in this era I think because of things like social networking Twitter and stuff like that if you if you put up you know stuff right that's just you know miss purposely misleading you know that you you can get a violent reaction in social media pointing out the flaws in your arguments right and so from a marketing perspective you have to be careful today that you didn't have to be careful that there'll be people who put off the flaw you can get the word out the flaws and what you're saying much more easily today than in the past you used to be it was used to be easier to get away with it and the other thing that's been happening in terms of starting off engineers it's just in the software side people have largely embraced open-source software it it was 20 years ago it was a dirty word at Microsoft and today Microsoft is one of the big proponents of open source software the kind of that's the standard way most software gets built which really shows off your engineers because you can see if you look at the source code you can see who are making the commits who's making the improvements who are the engineers at all these companies who are are you know really great programmers and engineers and making really solid contributions which enhances their reputations and the reputation of the companies so but that's of course not everywhere like in this space that I work more in is autonomous vehicles and they're still the machinery of hype and marketing is still very strong there and there's less willingness to be open in this kind of open source way and sort of benchmark so ml Perez represents the machine learning world is much better being open-source about holding itself to standards of different the amount of incredible benchmarks in terms of the different computer vision naturally new processing - inaudible it you know historically it wasn't always that way I had a graduate student working with me David Martin so for in computer in some fields benchmarking is been around forever so computer architecture databases maybe operating systems benchmarks are the way you measure progress but he was working with me and then started working with gender Malik and he's a gender Malik in computer vision space who I guess you've you interviewed yes and David Martin told me they don't have benchmarks everybody has their own vision algorithm in the way that my here's my image look at how well I do and everybody had their own image so David Martin back when he did his dissertation figured out a way to do benchmarks he had a bunch of graduate students identify images and then ran benchmarks to see which algorithms run well and that was as far as I know kind of the first time people did benchmarks in computer vision in which was predated all you know the things that eventually led to imagenet himself like that but then you know the vision community got religion and then once we got as far as image net then that let the guys in Toronto be able to win the image net competition and then you know that changed the whole world it's a scary step actually because when you enter the world of benchmarks you actually have to be good to participate as opposed to yeah you can just you just believe you're the best in the world and I think the people I think they weren't purposely misleading I think if you don't have benchmarks I mean how do you know you know you could have your intuition it's kind of like the way we did used to do computer architecture your intuition is that this is the right instruction set to do this job I believe in my experience my hunch is that's true we had to get to make things more quantitative to make progress and so I just don't know how you know in fields that don't have benchmarks I don't understand how they figure out how they're making progress we're kind of in the vacuum tube days of quantum computing what are your thoughts in this wholly different kind of space of architectures uh you know I actually you know quantum computing his ideas been around for a while and I actually thought well sure hope I retire before I have to start teaching this I'd say because I talked about give these talks about the slowing of Moore's law and you know when we need to change by doing domain-specific accelerators common questions say what about quantum computing the reason that comes up it's in the news all the time so I think the keep and the third thing to keep in mind is quantum computing is not right around the corner there have been two national reports one by the national campus of engineering another by the computing consortium where they did a frank assessment of quantum computing in both of those reports said you know as far as we can tell before you get error corrected quantum computing it's a decade away so I think of it like nuclear fusion right there been people who've been excited about nuclear fusion a long time if we ever get nuclear fusion it's going to be fantastic for the world I'm glad people are working on it but you know it's not right around the corner that those two reports to me say probably it'll be 2030 before quantum computing is a something that could happen and when it does happen you know this is going to be big science stuff this is you know microkelvin almost absolute zero things that if they vibrate if truck goes by it won't work right so this will be in data center stuff we're not gonna have a quantum cell phone and and it's probably a 2030 kind of thing so I'm happy that other people are working on it but just you know it's hard with all the news about it not to think that it's right around the corner and that's why we need to do something as Moore's Law is slowing down to provide the computing keep improving getting better for this next decade and and you know we shouldn't be betting on quantum computing are expecting quantum computing to deliver in the next few years it's it's probably further off you know I I'd be happy to be wrong it be great if quantum computing is gonna commercially viable but it will be a set of applications it's not a general-purpose computation so it's gonna do some amazing things but there'll be a lot of things that probably you know the the old-fashioned computers are gonna keep doing better for quite a while and there'll be a teenager 50 years from now watching this video saying look how silly David Patterson was saying I said what did 2030 I didn't say sorry I never we're not gonna have quantum cellphones so he's gonna be watching and well I mean III think this is such a you know given we've had Moore's law I just I feel comfortable trying to do projects that are thinking about the next decade I I admire people who are trying to do things that are 30 years out but it's such a fast-moving field I just don't know how to I'm not good enough to figure out what what's the problems gonna be in 30 years you know 10 years is hard enough for me so maybe if it's possible to untangle your intuition a little bit I spoke with Jim Keller I don't know if you're familiar with Jim and he he is trying to sort of be a little bit rebellious and to try to think that he quotes me as being wrong yeah so what are your the relationship for the record Jim talks about that he has an intuition that Moore's law is not in fact in fact dead yet and then it may continue for some time to come what are your thoughts about Jim's ideas in this space yeah this is just this is just marketing so but Gordon Moore said is a quantitative prediction if we can check the facts right which is doubling the number of transistors every two years so we can look back at Intel for the last five years and ask him let's look at DRAM chips six years ago so that would be three two-year periods so then our DRAM chips have eight times as many transistors as they did six years ago we can look up Intel microprocessors six years ago if Moore's law is continuing it should have eight times as many transistors as six years ago the answers in both those cases is no the problem has been because Moore's law was kind of genuinely embraced by the semiconductor industries they would make investments in severe equipment to make Moore's Law come true semiconductor improving in Moore's law in many people's mind are the same thing so when I say and I'm factually correct that Moore's law is no longer holds we are not doubling transistors every years years the downside for a company like Intel is people think that means it stopped that technology has no longer improved and so Jim is trying to react at AraC the impression that semiconductors are frozen in 2000 nineteen are never gonna get better so I never said that I said was Moore's law is no more and I'm strictly looking at a number of transistors because that's what more that's what Moore's law is there's the I don't know there's been this aura associated with Moore's law that they've enjoyed for fifty years about look at the field we're in we're doubling transistors every two years what an amazing field which is an amazing thing that they were able to pull off but even as Gordon Moore said you know no exponential can last forever it's lasted for 50 years which is amazing and this is a huge impact on the industry because of these changes that we've been talking about so he claims because he's trying to act and he claims you know Patterson says Moore's laws know more and look at all look at it it's still controlling and tsmc to say it's as no longer but there but there's quantitative evidence that Moore's law is not continuing so what I say now to try and okay I understand the perception problem when I say Moore's law is stopped okay so now I say Moore's law slowing down and I think Jim which is another way if he's if it's predicting every two years and I say it's slowing down then that's another way of saying it doesn't hold anymore and and I think Jim wouldn't disagree that it's slowing down because that sounds like it's things are still getting better just not as fast which is another way of saying Moore's law isn't working anymore it's still good for marketing but uh but what's your you're not you don't like expanding the definition of Moore's law sort of uh well yeah that's really yeah it's an educator you know are you know is this like bonding politics is everybody get their own facts or do we have Moore's law was a crisp you know amorous Carver Mead looked at his observations drawing on a log-log scale a straight line and that's what the definition of Moore's law is there's this other what Intel did for a while interestingly before Jim joined them they said oh no Morris lies in the number of doubling isn't really doubling transistors every two years Moore's law is the cost of the individual dressed sister going down cutting in half every two years now that's not what he said but they reinterpreted it because they believed that the that the cost of transistors was continuing to drop even if they couldn't get twice as many people industry have told me that's not true anymore that basically then the in more recent technologies that got more complicated the actual cost of transistor went up so even even the a corollary might not be true but certainly you know Moore's law that was the beauty of Moore's law it was a very simple it's like equals mc-squared right it was like wow what an amazing prediction it's so easy to understand the implications are amazing and that's why it was so famous as a as a prediction and this this reinterpretation of what it meant and changing is you know his revisionist history and I I'd be happy and and they're not claiming there's a new Moore's law they're not saying by the way it's instead of every two years it's every three years I don't think the I don't think they want to say that I think what's going to happen is the new technology Commission's H ones get a little bit slower so it it is slowing down the improvements will won't be as great and that's why we need to do new things yeah I don't like that the the idea of Moore's law is tied up with marketing I it would be nice if it's whether it's marketing or it's it's well it could be affecting business but they could also be infecting the imagination of engineers is if if Intel employees actually believe that we're frozen in 2019 well that's that would be bad for Intel they not just Intel but everybody it's inspired Moore's law is inspiring yeah everybody but what's happening right now talking to people in who have working in national offices and stuff like that a lot of the computer science community is unaware that this is going on right that we are in an era that's going to need radical change at lower levels that could affect the whole software stack this you know if if the Intel if you're using cloud stuff and servers that you get next year are basically only a little bit faster than the servers you got this year you need to know that and we need to start innovating to start delivery blow on it if you're counting on your software your software going to add a lot more features assuming the computers can get faster that's not true so are you gonna have to start making your software stack more efficient or are you gonna have to start learning about machine learning so it's you know it's kind of a it's a morning or call for arms that the world is changing right now and a lot of people a lot of computer science PhDs are unaware of that so a way to try and get their attention is to say that Moore's law is slowing down and that's gonna affect your assumptions and you know we're trying to get the word out and when companies like TSMC and Intel say oh no no no Moore's law is fine then people think okay that I don't have to change my behavior I'll just get the next servers and you know if they start doing measurements though realize what's going on it'd be nice to have some transparency and metrics for for the layperson to be able to know if computers are getting faster and there are yeah there are there are a bunch of most people kind of use clock rate as a measure performance you know it's not a perfect one but if you've noticed clock rates are more or less the same as they were five years ago computers are a little better than they aren't they haven't made zero progress but they've made small progress so you there's some indications out there and in our behavior right nobody buys the next laptop because it's so much faster than the laptop from the past four cell phones I think I don't know why people buy new cell phones you know because of the new ones announced the cameras are better but that's kind of domain-specific right they're putting special purpose hardware to make the processing of images go much better so that's that that's the way they're doing it they're not particularly it's not that the ARM processor there's twice as fast as much as they'd added accelerators to help eat the experience of the phone can we talk a little bit about one other exciting space arguably the same level of impact as your work with risk is raid and in your in 1988 you co-authored a paper a case for redundant array of inexpensive disks hence our AI D rate so you that's where you introduce the idea rate incredible that that little I mean little that paper kind of had this ripple effect and had a really revolutionary effect so first what is rate what is rate so this is work I did with my colleague Randy Katz and a star graduate student Garth Gibson so we had just done the fourth generation risk project and Randy Kass which had early Apple Macintosh computer at this time everything was done with floppy disks which are old technologies that to could store things that didn't have much capacity and you had to to get any work done you're always sticking in your little floppy disk in and out because they didn't have much capacity but they started building what are called hard disk drives which is magnetic material that can remember information storage for the Mac and Randy asked the question when he saw this disk next to his Mac jeez he's a brand-new small things before that for the big computers that the disk would be the size of washing machines and here's something the size of a kind of the size of a book or so this is I wonder what we could do with that well we the Randy was involved in the in the fourth generation risk project here at Berkeley 80s so we figured out a way how to make the computation part the processor part go a lot faster but what about the storage part can we do something to make it faster so we hit upon the idea of taking a lot of these disks developed for personal computers and mackintoshes and putting many of them together instead of one of these washing machine sized things and so we were to rub the first draft of the paper and we'd have 40 of these little PC DOS instead of one of these washing machine size things and they would be much cheaper because they're made for PCs and they could actually kind of be faster because there was 40 of them rather than one of them and so he wrote a paper like that and send it to one of a former Berkeley students at IBM and he said well this is all great and good but what about the reliability of these things now you have 40 of these devices each of which are kind of PC quality so they're not as good as these IBM washing machines IBM dominated the the the storage Genesis so you reliably gonna be awful and so when we calculated it out instead of you know it breaking on average once a year it would break every two weeks so we thought about the idea and said well we got to address the reliability so we did it originally performance but we had do reliability so the name redundant array of inexpensive disks is array of these disks inexpensive life for pcs but we have extra copies so if one breaks we won't lose all the information will have enough redundancy that we could let some break and we can still preserve the information so the name is an array of inexpensive discs this is a collection of these pcs and the are part of the name was the redundancy so they'd be reliable and it turns out if you put a modest number of extra disks in one of these arrays it could actually not only be as faster and cheaper that one of these washing machine discs it could be actually more reliable because you could have a couple of breaks even with these cheap discs whereas one failure with the washing machine thing would knock it out did you did you have a sense just like with risk that in the 30 years that followed raid would take over as a as a man I think George I I'd say I think I'm naturally an optimist but I thought our ideas were right I thought kind of like Moore's law it seemed to me if you looked at the history of the disk drives they went from washing machine size things than they were getting smaller and smaller and the volumes were with the smaller disk drives because that's where the PCs were so we thought that was a technological trend that disk drives the volume disk drives was going to be small getting smaller and smaller devices which were true they were the size of the I don't know eight inches diameter than five inches than three inches of diameters and so that it made sense to figure out how to deal things with an array of disks so I think it was one of those things where logically we think the technological forces were on our side that it made sense so we expected it to catch on but there was that same kind of business question you know IBM was the big pusher of these disk drives in the real world where the technical advantage get turned into a business advantage or not it proved to be true it did in so you know we thought we were sound technically and it was unclear worth of the business side but we kind of as academics we believe the technology should win and and it did and and if you look at those thirty years just from your perspective are there interesting developments in the space of storage that have happened in that time yeah the big thing that happened both a couple of things that happened what we did had a modest amount of storage so as redundancy as people built bigger and bigger storage systems they've added more we doesn't see so they could have more failures and they have biggest thing that happened in storage is for decades it was based on things physically spinning called hard disk drives where you used to turn on your computer and it would make a noise what that noise was was the disk drive spinning and they were rotating it in like 60 revolutions per second and it's like if you remember the vinyl vinyl records if you've ever seen those that's what it looked like and there was like a needle like on a vinyl record that was reading it so the big drive a change is switching that over to a similar technology called flash so within the last I'd say about decade is increasing fraction of all the computers in the world are using semiconductor for storage the flash drive instead of being magnetic their optical their there well their semiconductor writing of information into very densely and that's been a huge difference so all the cell phones in the world use flash most of the laptops use flash all the embedded devices use flash instead of storage still in the cloud magnetic disks are more economical than flash but they used both in the cloud so it's been a huge change in the storage industry this the switching from primarily disk to being primarily semiconductor for the individual discs but still the raid mechanism applies to those different kinds of yes the the people will still use raid ideas because it's kind of what's different you know kind of interesting kind of psychologically if you think about it people have always worried about the reliability of computing since the earliest days so kind of but if we're talking about computation if your computer makes a mistake and the computer says the computer has worries to check and say we screwed up we made a mistake what happens is that program that was running you have to redo it which is a hassle for storage if you've sent important information away and it loses that information you go nuts yeah yeah this is the worst I oh my god so if you have a laptop and you're not backing it up on the cloud or something like this and your disk drive breaks which it can do you'll lose all that information and you just go crazy right so the importance of reliability for storage is tremendously higher than the importance of reliability for computation because of the consequences of it so yes so raid ideas are still very popular even with the switch of the technology although you know flash drives are more reliable you know if you're not doing anything like backing it up to get some redundancy so they handle it you're you're you're taking great risks you said that for you and possibly from any others teaching and research don't conflict with each other as right one might suspect and in fact they kind of complement each other so maybe a question I have is how is teaching helped you in your research or just in your entirety as a person who both teaches and does research and just thinks and creates new ideas in this world yes I think I think what happens is is when you're a college student you know there's this kind of tenure system and doing research so kind of this model that you know is popular in America I think America really made it happen is we can attract these really great faculty to research universities because they get to do research as well as teach and that especially in fast-moving fields this means people are up-to-date and they're teaching those kind of things so but when you run into a really bad professor a really bad teacher I think the students think well this guy must be a great researcher because why else could he be here so is I you know I I after 40 years at Berkeley we had a retirement party and I got a chance to reflect and I looked back to some things that is not my experience there's a I saw a photograph of five of us in the department who won the distinguished Teaching Award from campus a very high honor you know what I've got one of those when the highest honors so they're five of us on that picture there's Manuel Blum Richard Karp me Randy Katz and John osterhaus contemporaries of mine I mentioned Randy already all of us are in the National Academy of Engineering we've all run the distinguished Teaching Award Blum Karp and I are all have turing award just going away that's right you know the highest award in computing so the opposite right it's what happens if you it's it's they're highly correlated so probably the other way to think of it if you're very successful people may be successful at everything they do it's not an either/or and but it's an interesting question whether specifically that's probably true but specifically for teaching if there's something in teaching that it's the Richard Fineman right right yeah is there something about teaching that actually makes your research makes you think deeper and more outside the box and yeah absolutely so yeah I was going to bring up Fineman I mean he criticized the Institute of Advanced Studies he says there's Advanced Studies was this thing that was created in your Princeton where Einstein and all these smart people and when he was invited he said he thought it was a terrible idea his this is a university was it was supposed to be heaven right a university without any teaching but he thought it was a mistake is getting up in the classroom and having to explain things to students and having them ask questions like well why is that true makes you stop and think so he to think he thought and I agree I think that interaction between a retina research university and having students with bright young man's asking hard questions the whole time is synergistic and you know a university without teaching wouldn't be as vital and exciting a place and I think it helps stimulate the the research another romanticized question but what's your favorite concept or idea to teach what inspires you or you see inspire the students is there something to pasta my or or puts the fear of God in them I don't know II whichever is most effective I mean in general I think people are surprised I've seen a lot of people who don't think they like teaching come come give guest lectures or teach a course and get hooked on seeing the lights turn on right his people you can explain something to people that they don't understand and suddenly they get something you know that's that's not that's important and difficult and just seeing the lights turn on is a you know it's a real satisfaction there I don't think there's any in a specific example of that it's just the general joy of seeing them seeing them understand I have to talk about this because I've wrestled I do usual arts yes yes I love Russ I'm a huge I'm Russian so I'll sure I'd have talked to Dan Gable oh yeah I guess so fine yang Gables my era kind of guy so you wrestled UCLA among many other things you've done in your life competitively in sports and science on you've wrestled maybe again continue in their immense sessions but what have you learned about life yeah and maybe even size from wrestling or from that's in fact I wrestled at UCLA but also at El Camino can be College and just right now we were in the state of California we were state champions at El Camino and the fact I was talking to my mom and I got into UCLA but I decided to go to the Community College which is it's much he's harder to go to UCLA than Community College and I asked why did I make the decision because I thought that was because of my girlfriend she said well it was the girlfriend and and you thought the wrestling team was really good and we were right we had a great wrestling team it we actually wrestled against UCLA at a tournament and we beat UCLA it's a community college which just freshmen and sophomores and the reason I brought this up is I'm gonna go they've invited me back at El Camino if give a lecture next month and so I'm Liev my friend who was on the wrestling team that we're still together we're right now reaching out to other members of the wrestling team you can get together every Union but in terms of me it was a huge difference I was I was both I was kind of the age cutoff I was who's December first and so I was almost always the youngest person in my class and I matured later on you know our family badgered later so I was almost always the smallest guy so you know I took in kind of nerdy courses but I was wrestling so wrestling was huge for my you know self-confidence in high school and then you know I kind of got bigger at El Camino and in college and so I had this kind of physical self-confidence and it's translated into research self-confidence and and also kind of I've had this feeling even today in my 70s you know if something if something going on and streets there's bad physically I'm not gonna ignore it right I'm gonna stand up and try and straighten that out and that kind of confidence just carries through the entirety of your life yeah and the same things happens intellectually if there's something going on where people are saying something that's not true I feel it's my job to stand up and just like I would in the street if there's something going on somebody attacking some woman or something I'm not I'm not standing by and letting that so I feel it's my job to stand up so it's kind of ironically translates the other things that turned out for both I had really great college in high school coaches and they believed even though wrestling's an individual sport that would be be more successful as a team if we bonded together you do things that we would support each other rather than everybody you know in wrestling it's one-on-one and you could be everybody's on their own but he felt if we bonded as a team we'd succeed so I kind of picked up those skills of how to form successful teams and how do you from wrestling and so I think one of most people would say one of my strengths is I can create teams of faculty watch teams of faculty grad students pull all together for a common goal and you know and you often be successful at it but I got I got both of those things from wrestling also I think I heard this line about if people are in kind of you know collision you know sports with physical contact like wrestling or football and stuff like that people are a little bit more you know assertive or something so I think I think that also comes through is you know in I was I didn't shy away from the risk debates you know I was yeah I enjoyed taking on the arguments and stuff like that so it was it was a I'm really glad I did wrestling I think it was really good for my self-image and I learned a lot from it so I think that's you know sports done well you know there's really lots of positives you can take about it leadership you know how to how to form teams and how to be successful so we've talked about metrics a lot there's a really cool in terms of bench press and weightlifting pioneers metric do you develop that we don't have time to talk about but it's it's a really cool that people should look into it's rethinking the way we think about metrics and weightlifting but let me talk about metrics more broadly since that appeals Cu in all forms let's look at the most ridiculous the biggest question of the meaning of life if you were to try to put metrics on a life well-lived what would those metrics be yeah a friend Randy Katz said this he said you know when when it's time to sign off it's it's the measure isn't the number of zeros in your bank account it's the number of inches in the obituary in The New York Times he said it I I think you know having and you know this is a cliche is that people don't die wishing they'd spent more time in the office right is I reflect upon my career there have been you know a half a dozen or a dozen things say I've been proud of a lot of them aren't papers or scientific well certainly my family my wife we've been married more than 50 years kids and grandkids that's really precious education thinks I've done I'm very proud of you know books and courses I did some help with underrepresented groups that was effective so it was interesting just seeing what were the things I reflected you know I had hundreds of papers but some of them weren't the papers like the risk and rate stuff wasn't proud of but a lot of them were or not those things so people who are just spend their lives you know going after the dollars are going after all the papers in the world you know that's probably not the things that are afterwards you're gonna care about when I was a yeah just when I got the offer from Berkeley but before I showed up I read a book where they interviewed a lot of people in all walks of life and what I got out of that book was the people who felt good about what they did was the people who affected people as opposed to things that were more transitory so I came into this job assuming that it wasn't going to be the papers it was gonna be relationships with the people over time that I would I would value and that was a correct assessment right it's it's the people you work with the people you can influence the people you can help is the things that you feel good about towards into your career it's not not the the stuff that's more transitory I don't think there's a better way to end it then talking about your family the the over 50 years of being married to your childhood sweetheart is how do when you tell people you've been married 50 years they want to know why how why I can tell you the nine magic words that you need to say to your partner to keep a good relationship in the nine magic words are was wrong you were right I love you okay and you got to say all nine you can't say I was wrong you were right you're a jerk you know you guess so yeah a freely acknowledging that you made a mistake the other person was right and that you love them really gets over a lot of bumps in the road so that's what I pass along beautifully put David is a huge honor thank you so much for the book you've written for the research you've done for changing the world thank you for talking to that oh thanks for the interview thanks for listening to this conversation with David Patterson and thank you to our sponsors the Jordan Harbinger show and cash app please consider supporting this podcast by going to Jordan Harbinger complex and downloading cash app and using colex podcast click the links buy the stuff it's the best way to support this podcast and the journey I'm on if you enjoy this thing subscribe on youtube review it with five stars in a podcast supported on patreon or connect with me on Twitter and lex Freedman spelled without the e try to figure out how to do that it's just fr ID ma n and now let me leave you with some words from Henry David Thoreau our life is frittered away by detail simplify simplify thank you for listening and hope to see you next time you |
Ben Goertzel: Artificial General Intelligence | Lex Fridman Podcast #103 | the following is a conversation with Ben Gerel one of the most interesting Minds in the artificial intelligence Community he's the founder of Singularity net designer of opencog AI framework formerly a director of research at the machine intelligence Research Institute and chief scientist of Hansen robotics the company that created the Sophia robot he has been a central figure in the AGI Community for many years including in his organizing and contributing to the conference and artificial general in Ence the 2020 version of which is actually happening this week Wednesday Thursday and Friday it's virtual and free I encourage you to check out the talks including by yosa Bak uh from episode 101 of this podcast quick summary of the ads two sponsors the Jordan Harbinger show and Master Class please consider supporting this podcast by going to Jordan Harbinger docomo a masterclass.com Lex click the links buy all the stuff it's the best way to support this podcast and the journey I'm on in my research and startup this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars on Apple podcast support on patreon or connect with me on Twitter Alex fredman spelled without the e just f r i d m as usual I'll do a few minutes of as now and never any ads in the middle that can break the flow of the conversation this episode is supported by the Jordan Harbinger show go to Jordan Harbinger dcom Lex it's how he knows I sent you on that page there's links to subscribe to it on Apple podcast Spotify and everywhere else I've been binging on his podcast Jordan is great he gets the best out of his guests Dives deep calls them out when it's needed and makes the whole thing fun to listen to he's interviewed Kobe Bryant Mark Cuban Neila grass Tyson gri Kasparov and many more more this conversation with Kobe is a reminder how much focus and hard work is required for greatness and Sport business and life I highly recommend the episode if you want to be inspired again go to Jordan har.com Lex it's how Jordan knows I sent you this Show sponsored by masterclass sign up at masterclass.com Lex to get a discount and to support this podcast when I first heard about master class I thought it was too good to be true for 180 bucks a year you get an all access pass to watch courses from to list some of my favorites Chris Hatfield on space exploration Neil degrass Tyson on scientific thinking and communication will WR creator of the greatest city building game ever Sim City and Sims on game design Carlos Santana on guitar grick Kasparov the greatest chess player ever on chess Daniel Neo on poker or many more Chris Hatfield explaining how rockets work and the experience of being launched into space alone is worth the money once again sign up on masterclass.com Lex to get a discount and to support this podcast and now here's my conversation with Ben gitzo would books authors ideas had a lot of impact on you um in your life in the early days you know what got me into Ai and science fiction and such in the first place wasn't a book but the original Star Trek TV show which my dad watched with me like in its first run it would have been 1968 69 or something and that that was incredible CU every every show they visited a different a different alien civilization with different culture and weird mechanisms but that that got me into science fiction and there wasn't that much science fiction to watch on TV at that stage so that got me into reading the whole the whole literature of Science Fiction you know from from the beginning of the previous Century until that time and the I mean there was so many science fiction writers who were in inspirational to me I'd say if I had to pick two it would have been H Stanis LM the the Polish writer yeah Solaris and then he had he had a bunch of more obscure writings on on superhuman AIS that were engineered Solaris was sort of a superhuman naturally occurring in intelligence than Philip K dick who you know ultimately my fandom for Philip K dick is one of the things that brought me together with David Hansen my collaborator on on on robotics project so you know Stannis slm was was very much an intellectual right so he he had a very broad view of intelligence going beyond the human and into what I would call you know open-ended super intelligence the the Solaris super inell ocean was intelligent in some ways more generally intelligent than people but in a complex and confusing way so that human beings could never quite connect to it but it was but it was still palpably very very smart and then the the what Golem four supercomputer in one of one of lm's lm's books this was engineered by people but eventually it became very intelligent in a different direction than humans and decided that humans were kind of trivial and not that interesting so it it put some impenetrable shield around itself shut itself off from humanity and then issued some philosophical screed about the pathetic and hopeless nature of of humanity and and all human thought and then and then disappeared now Philip K dick he was a bit different he was human focused right his main thing was you know human compassion and the human heart and soul are going to be the constant that will keep us going through whatever aliens aliens we discover or telepathy machines or or or super AIS or or or whatever it might be so he didn't believe in reality like the reality that we see may be a simulation or or or a dream or or something else we can't even comprehend but he believed in love and compassion is something persistent through the various simulated realities so those those two science fiction writers had had a huge impact on me then a little older than that I got into dovi and friedi n and rambod and a bunch of uh more more literary type writing we talk about some of those things so on the Solara side stof lamb uh this kind of idea of they being intelligences out there that are different than our own do you think there are intelligences maybe all around us that were not able to even detect so this kind of idea of uh maybe you can comment also on Steven Wolfram thinking that there's computations all around us and we're just not smart enough to kind of detect their their intelligence or appreciate their intelligence yeah so my friend Hugo degaris who I've been talking to about these things for for for many decades since the early 90s he had an idea he called SII the search for intraparticulate intelligence so the concept there was as AIS get smarter and smarter and smarter you know assuming the laws of physics as we know them now are still are still what these super intelligences perceived to hold and are bound by as they get smarter and smarter they're going to shrink themselves little and little because special relativity make makes it to sort of communicate between two specially distant points so they're going to get smaller and smaller but then ultimately what does that mean the minds of the super super super intelligences they're going to be packed into the the interaction of of Elementary particles or quirks or the partons inside quirks or whatever it is so what we perceive as random fluctuations on the quantum or subquantum level may actually be the thoughts of the micro micro micro miniaturized super intelligences because there's no way we can tell random from structured but with an algorithmic information more complex than our brains right we can't tell the difference so what we think is random could be the thought processes of some really tiny super minds and if so there's not a damn thing we can do about it except you know try to upgrade our intelligences and expand our mind so that we can we can perceive more of what's around us but if th if those random fluctuations like even if we go to like quantum mechanics if that if that's actually uh super intelligent systems aren't we then part of the soup of super intelligence that we're aren't we just like like a finger of the entirety of the body of the superintelligence system we could be I mean a finger is a is a strange metaphor I mean we we we a finger is dumb is what I mean is uh is but a finger is also useful and is controlled with with intent by by the brain where we may be much less than that right I mean I mean yeah we may be just some random EPA phenomenon that that they don't care about too much like think about the the shape of the crowd emanating from a sports Stadium or something right there there's some Emer shape to the crowd it's there you could take a picture of it it's kind of cool it's irrelevant to the main point of the sports event or where the people are going or or or or what's on the minds of the people making that shape in the crowd right so we we may just be some semi arbitrary higher level pattern popping out of of a lower level hyper intelligent self-organization and I'm me so so be it right I mean that's one thing that still a fun ride yeah I mean the older I've gotten the more respect I've achieved for our fundamental ignorance I mean M mine and everybody else's I I look at my my two dogs two beautiful little toy poodles and you know they watch me sitting at the computer typing they just think I'm sitting there wiggling my fingers to exercise them maybe or guarding the monitor on the desk that they have no idea that I'm communicating with other people Halfway Around the World let let alone you know creating complex algorithms running in in RAM on some computer server in St Petersburg or something right they although they're right there they're right there in the room with me so what things are there right around us that we just too stupid or close-minded to comprehend probably probably quite a lot you're very your very poodle could be uh could also be communicating across multiple Dimensions with with other with other beings and you're too you're too unintelligent to understand the kind of communication mechanism they're going through there there there have been various uh TV shows and science fiction novels pusing cats Dolphins uh mice and whatnot are actually super intelligence is here to observe that I I would I would guess as one of the other quantum physics Founders said those theories are not crazy enough to be true the reality is probably crazier than that beautifully put so on The Human Side uh with uh Philip K dick and and uh in general where do you fall on this idea that uh love and just the basic Spirit of human nature persists throughout these multiple realities um are you on the side like the thing that inspires you about artificial intelligence is it the human side of somehow persisting through all of the different systems we engineer or is it or is AI inspire you to create something that's greater than human that's beyond human that's almost nonhuman I would say my motivation to create AGI comes from from both of those directions actually so when I when I first became passionate about AGI when I was it would have been two or three years old after watching robots on Star Trek I mean then it was really a combination of intellectual curiosity like can a machine really think how how would you do that and yeah just ambition to create something much better than all the clearly limited and and fundamentally defective humans I saw around me then as I got older and got more in mesed in in in the human world and you know got married had children some my parents begin to age I started to realize well not only will AGI let you go far beyond the limitations of the human but it could also like stop us from dying and and suffering and and and feeling pain and and tormenting ourselves mentally you can see AGI has amazing capability to do good for humans as humans alongside with with its capability to go far far beyond the human level so I mean both both aspects are are there which makes it uh even more exciting and important so you mentioned the what did you pick up from those guys I mean that that that would probably go beyond the beyond the scope of of a brief interview certainly I mean both of those are amazing thinkers who one will necessarily have a a complex relationship with right so I mean dovi on the on the minus side he's kind of a religious fanatic and he sort of helped squash the Russian nihilist movement which was very interesting because what what nihilism meant originally in in in that period of the mid late 1800s in Russia was not not taking anything fully 100% for granted it was really more like what we'd call beanis now where you don't want to adopt anything as a dogmatic certitude and always leave mind open and how dovi parody nihilism was was was was a bit different right he parody is people who believe absolutely nothing so they M they must assigned an equal probability weight to to every proposition which which which doesn't really work so on the one hand I I didn't really agree with dovi on on his sort of religious point of view on on on the on the other hand if you look at his understanding of human nature and sort of the human mind and and and heart and and soul it's it's it's really unparalleled and he had an amazing view of how human beings you know construct a world for themselves based on their own understanding and and their own mental predisposition and I think if if you look in the brothers karamazov in particular the the Russian literary theorist M Bakin wrote about this as a polyphonic mode of fiction which means it's not third person but it's not first person from any one person really there are many different characters in the novel and each of them is sort of telling part of the story from their own point of view so the reality of the whole story is is an intersection like synergetically of the many different characters worldviews and that really it's a beautiful metaphor and even a reflection I think of how all of us socially create our reality like each of us sees the world in a certain way each of us in a sense is making the world as we see it based on on our own minds and understanding but it's poony like like in like in music where multiple instruments are coming get coming together to create the sound the Ultimate Reality that's created comes out of each of our subjective understandings you know intersecting with each other and that that was one of the many beautiful things in in DVI so maybe a little bit to mention you have a connection to Russia and the Soviet culture I mean I'm not sure exactly what the nature of the connection is but there at least the spirit of your thinking well my my my ancestry is three4 Eastern European Jewish so I mean my three of my great-grandparents immigrated to New York from Lithuania and sort of Border regions of of Poland which were in and out of Poland in around the around the time of world World War I and they were they were socialists and and Communists as well as Jews mostly menic not not Bolshevik and they sort of they fled at just the right time to the US for their own personal reasons and then almost all or maybe all of my extended family that remained in Eastern Europe was killed either by hitlin or or Stalin's minions at some point so the branch of the family that immigrated to the US was was was pretty much the the only one right so how much of the spirit of the people is in your blood still like do you when you look in the mirror do you see uh what do you see meat I see a bag of meat that I want to transcend by uploading into some sort of superior reality but very yeah I mean yeah very clearly well I mean I'm I'm not religious in a traditional sense but clearly the the Eastern European Jewish tradition was what I what I was raised in I there was my grandfather Leo well was a a physical chemist who worked with Lis Pauling and a bunch of the other early greats and in quantum mechanics I mean he was he was uh into x-ray defraction he was on the material science side experimentalist rather than a theorist his sister was was also a physicist and my my father's Father Victor gzel was a PhD in in Psychology who had the unenviable job of giving Psychotherapy to the Japanese jaes in internment camps in the US in in in World War II like to counsel them why they shouldn't kill themselves even though they'd had all their stuff taken away and been imprisoned for no good reason so I mean there yeah there there's a lot of uh Eastern European jewishness in my in my background one of my great uncles was I guess conductor of San Francisco Orchestra so there there's a lot of Mickey Sul and bunch of music music in there also and clearly this culture was all about learning and and understanding understanding the world and also not quite taking yourself too seriously while you do it right there's a lot of Y Yiddish humor in there so I I do appreciate that that culture although the whole idea that like the Jews are the chosen people of God never resonated with me too much the graph of the gzel family I mean just the people I've encountered just doing some research and just knowing your work through through the decades uh it's kind of fascinating I'm just the the the number of phds yeah yeah I mean f my dad is a sociology Professor who recently retired from from ruers University but that clearly that gave me a head start in life I mean my my grandfather gave me all his quantum mechanics books when I was like seven or eight years old you know I remember going through them and it was all the old Quant mechanics like r Rutherford Adams and stuff so I got to the part of wave functions which I didn't understand although I was very bright kid and I realized he he didn't quite understand it either but at least like he pointed me to some Professor he knew at at upen nearby who who understood these things right so that's that that's an unusual opportunity for a kid to have right and my my dad he was programming for tram when I was 10 or 11 years old on like HP 3000 Main frames at ruers University so I got to do linear regression in Fortran on on Punch Cards at when when I was in in in middle school right because he was doing I guess analysis of demographic and and and sociology data so yes certainly certainly that gave me a head start and a push towards science be beyond what would have been the case with many many different situations when did you first fall in love with AI is it the is it the programming side of Fortran is it the maybe the sociology psychology that you picked up from your dad or I when I was probably 3 years old when I saw a robot on Star Trek it was turning around in a circle going eror error error error because Spock and Kirk had tricked into a mechanical breakdown by presenting with a logical Paradox and I was just like well this makes no sense this AI is very very smart It's been traveling all around the universe but these people could trick it with a simple logical Paradox like what if you know if the human brain can get beyond that Paradox wh wh why why can't why can't can't this AI so I I I felt the the screenwriters of Star Trek had misunderstood the nature of intelligence and I complained to my dad about it and he he wasn't he wasn't going to say anything one way or the other but you know in before I was born when my dad was at Antioch College in uh in the middle of the US he he led uh he led a protest movement called slam student League against mortality they were protesting against death wandering across the campus so he he he he was into some futuristic things even back then but whether AI could confront logical paradoxes or not he did he didn't know but that you know when I 10 years after that or something I discovered Douglas Hoffer's book gordal shabbach and that was sort of to the same point of AI and Paradox and logic right because he was over with over and over with gle's incompleteness theorem and Canon AI really fully model itself reflexively or does that lead you into some Paradox can the human mind truly model itself reflexively or does that lead you into some Paradox so when I think that book Gord lerach which I think I read when it first came out it would have been 12 years old or something I remember it was like 16-hour day I read it cover to cover and then ReRe it ReRe it I reread it after that because there was a lot of weird things with little formal systems in there that were hard for me at the time but that was the first book I read that gave me a feeling for AI as like a practical academic or engineering discipline that that people were working in because before I read Gord shach I was into AI from the point of view of a of a science fiction fan and I I had the idea well it may be a long time before we can achieve immortality in superhuman AGI so I should figure out how to build a spacecraft traveling close to the speed of light go far away then come back to the Earth in a Million years when technology is more advanced and we can build these things reading G shach well it didn't all ring true to me a lot of it did and but I could see like there are smart people right now at various universities around me who are actually trying to work on building what I would Now call AGI although Hoff didn't didn't call it that so really it was when I read that book which would have been probably Middle School that then I started to think well this this is something that I could I could practically work supposed to flying away and waiting it out you can actually be the one of the people that actually uh EXA and if you think about I I was interested in what we'd Now call nanotechnology and in the human immortality and time travel all the same cool things as every other like science fiction loving kid but AI seemed like if Hoff did it was right you just figure out the right program sit there and type it like you don't you don't need to you don't need to spin Stars into weird configurations or get government approval to cut people up and Fiddle with their DNA or something right it's just programming and then of course that can achieve anything else that there's another book from back then which was by fine bomb Gerald fbom who was a who was a physicist at at at Princeton and that was the Prometheus project and this book was written in the late 1960s though I encountered it in the mid '70s but what this book said is in the next few decades humanity is going to create superhuman thinking machines molecular nanotechnology and human immortality and then the challenge we'll have is what to do with it do we use it to expand human consciousness in a positive direction or or do we use it just to further vapid uh consu consumerism and what he proposed was that the UN should do a survey on this and the UN should send people out to every little village in in remotest Africa or South America and explain to everyone what technology was going to bring the next few decades and the choice that we had about how to use it and let everyone on the whole planet vote about whether we should develop you know super AI nanotechnology and and and immortality for expanded Consciousness or for rampant rampant consumerism and needless to say that didn't quite happen and I think this guy died in the mid 80s so he didn't even see his ideas start to become become more mainstream but it's interesting many of the themes I'm engaged with now from AGI and immortality even to trying to democratize technology as I've been pushing for with Singularity my work in the blockchain world many of these themes were there in you know fine bomb's book in uh in the late 60s even and of course Valentin churchin uh a Russian writer who who I and a great Russian physicist who I got to know when we both lived in New York in the late 90s and early Arts I mean he he had a book in the late 60s in in Russia which was the phenomenon of science which laid out laid out all these all these same things as well and Val died in I don't remember 2004 five or something of parkinsonism so yeah it's easy easy for people to lose track now of the fact that the the futurist and singularitarianism almost mainstream and they're on TV all the time I mean these these are not that new right they're sort of new in the history of the human species but I mean these were all around in Fairly mature form in in the middle of the last century were written about quite articulately by fairly mainstream people who are professors at at top universities it's just until the enabling Technologies got to a a certain point then you you couldn't make it real so and even in the 70s I was sort of seeing that and and living living through it right from Star Trek to Douglas Hoffer things were getting very very practical from the late 60s to the late 70s and you know the first computer I bought you could only program with heximal machine code and you had to solder it together and then then like a few years later there's Punch Cards and a few years later you could get like Atari 400 and commodore Victor 20 and you could you could type on the keyboard and program in higher level languages along alongside the Assembly Language so these ideas have been building up a while and I guess my generation got to feel them build up which is different than people coming into the field now now for whom these things have just been part of the Ambiance of of culture for their whole career even or even their even their whole life well it's fascinating to think about you know there being all of these ideas kind of swimming you know almost with a noise all around the world all the different generations and then some kind of nonlinear thing happens where they percolate up and and uh capture the imagination of the mainstream and that seems to be what's happening with AI now I mean n who you mentioned had the idea of the Superman right but he he didn't understand enough about technology to think you could physically engineer a Superman by piecing together Mo molecules in a certain way he he was a bit vague about how how the how the Superman would appear but he was quite deep at thinking about what the State of Consciousness and the mode of cognition of of a Superman would be he he was a very astute analyst of you know how the human mind constructs the illusion of a self how it constructs the illusion of Free Will how how it constructs values like like good and evil out of its own you know desire to maintain and Advance its own organism he understood a lot about how human minds work then he understood a lot about how postum Minds would work I mean this Superman was supposed to be a mind that would basically have complete root access to its own brain and Consciousness and be able to architect it its own its own value system and inspect and fine-tune all all of its own its own biases so that's a lot of powerful thinking there which then fed in and and sort of seated all of postmodern Continental philosophy and all sorts of of things have been very valuable in development of culture and indirectly even even of Technology but of course without the technology there it was all some quite abstract thinking so now now we're at a time in history when a lot of these ideas can be can be made real which is amazing amazing and scary right it's kind of interesting to think what do you think n would if he was born a a century later or transported through time what do you think you would say about AI I mean well those are quite different if he's born a century later or transported through time well he'd be he'd be on like Tik Tok and Instagram and he would never write the great works he's written so let's transport him through time maybe also sparra would be a music video right I mean I mean I mean who knows yeah but if he was transported through time do you think uh that'd be interesting actually to go back uh you just made me realize that it's possible to go back and read ni with an eye of is there some thinking about artificial beings I'm sure there he has in he had inklings I mean with Frankenstein before him I'm sure he had inklings of artificial beings somewhere in the text it'd be interesting to see to try to read his work to see if he hadn't if if uh uh Superman was actually an AGI system like if he had inklings of that kind of thinking didn't he didn't no I I would say not I mean he had he had a lot of inklings of modern cognitive science which are very interesting if you look in like the the third part of of the collection that's been titled the will to power I mean in book three there there's there's very deep analysis of thinking processes but he he wasn't so much of a physical tinkerer type type guy right was very abstract and do you think uh what do you think about the will to power do you think human what do you think drives humans is it is it uh oh an Unholy mix of things I I don't think there's one pure simple and elegant objective function D driving humans by by by by any means well do you think um if we look at I know it's hard to look at humans in an aggregate but do you think overall humans are good or or uh do we have both good and evil within us that uh depending on the circumstances depending on the whatever can can can percolate to the top good and evil are very ambiguous complicated and in some ways silly Concepts but if we we could dig into your question from a couple directions so I think if you look in evolution humanity is shaped both by individual selection and what biologists would call group selection like tribe level selection right so individual selection has driven us in a selfish DNA sort of way so so that each of us does to a certain approximation what will help us propagate our our DNA to to Future Generations I mean that that that that's why I've got four kids so far and and probably that's not the last one yeah on the other hand I like the ambition tribal like group selection means humans in a way will do what what will advocate for the Persistence of the DNA of their whole their whole tribe or their their social group and in biology you you have both of these right like a and you can see say an ant colony or beehive there's a lot of group selection in in in the evolution of those social animals on the other hand say a a big cat or some very solitary animal it's a lot more biased toward toward individual selection humans are an interesting balance and I think this reflects itself in what we would view as selfishness versus altruism to to to some extent so we just have both of those objective functions contributing to the the makeup of of our brains and then as n analyzed in his own way and others have analyzed in different ways I mean we abstract this as well we have both good good and and and evil with within us right because a lot of what we view as evil is really just selfishness and a lot of what we view as good is altruism which means doing doing what's good for the for the tribe and on that level we have both of those just baked baked into us and that's that's how it is of course there are psychopaths and sociopaths and people who you know get gratified by the suffering of others and that's that that that that's that's a different thing yeah those are exceptions but on the whole I think at core we're not purely selfish we're not purely altruistic we we are a mix and that's that's the nature of it and we also have a complex constellation of values that are just very specific to our our Evol evolutionary history like we you know we we love waterways and and and mountains and the the ideal place to put a house as in a mountain overlooking the water right and you know we we we we care a lot about our our kids and we care a little less about our cousins and even less about our fifth cousins I mean there are many particularities to human values which whether they're good or evil depends on your on on on your perspective really see I I I spent a lot of time in Ethiopia in Adis Ababa where we have one of our AI development offices for my Singularity net project and when I walk through the streets in Otis you know there's so there's people Lying by the side of the road like just living there by the side of the road dying probably of curable diseases without enough food or medicine and when I walk by them you know I feel terrible I give them money when I come back home to the developed world they're not on my mind that much I I do donate some but I mean I I also spend some of the limited money I have enjoying myself in frivolous ways rather than donating it to those people who are right now like starving dying and and suffering on on the roads side so does that make me evil I mean it makes me somewhat selfish and somewhat altruistic and we each we each balance that in in in our own way right so that's that that whether that will be true of all possible agis is a is a is a is a subtler question so you you that's how humans are so you have a sense you kind of mentioned that there's a selfish I'm not going to bring up the whole irand idea of uh selfishness being the core virtue that's an whole interesting kind of tangent that I think will just distract our I I I have to make one amusing comment or comment that has amused me anyway so the the yeah I I I have extraordinary negative respect for for Ein Rand negative what's a negative respect but when I worked with a company called jesin which was evolving flies to have extraordinary long lives in in in Southern California so we we had flies that were evolved by artificial selection to have five times a lifespan of normal fruit flies but the population of super long live flies was physically sitting in a spare room at an IR Rand Elementary School in Southern California so that was just like wow if if I saw this in a movie I wouldn't believe it right well yeah the universe has a sense of humor in that kind of way that fits in there humor fits in somehow into this whole absurd existence but you you mentioned the balance between selfishness and altruism as kind of being innate do you think it's possible that's kind of an emergent Fe phenomena those peculiarities of our value system how much of it is innate how much of it is something we collectively kind of like a dfki novel bring to life together as a civilization I mean the the answer to nature versus nurture is usually both and of course it's nature versus nurture versus self-organization as you mentioned so clearly they are evolutionary roots to individual and group selection leading to a mix of selfishness and altruism on the other hand different cultures manifest that in in in in different ways while we we all have basically the same biology and if you look if if you look at sort of pre-vedic the yanam Mamo in Venezuela which which their their culture is focused on on killing killing other tribes and you have other Stone Age tribes that are are mostly Peaceable and have big tabos against violence so you you can certainly have a big difference in in how culture manifests these innate biological characteristics but still you know there's probably limits that are given by biology I I used to argue this with my great-grandparents who were marxists actually because they they believed in the withering away of the state like they they believe that you know as you move from capitalism to socialism to Communism people would just become more socialm minded so that a state would be unnecessary and people would just give give everyone would give everyone else what what they needed Now setting aside that that's not what the various Marxist experiments on the planet seem to be heading toward in in practice just a as a theoretical point I was very dubious that that human nature could go there like at that time when my great-grandparents are alive I was just like you know I'm a cynical teenager I I think humans are humans are just jerks the state is not going to wither away if you don't have some structure keeping people from screwing each other over they're going to do it and so now I actually don't quite see things that way I mean I think the my feeling now subjectively is the culture aspect is more significant than I thought it was when I when I was a teenager and I think you could have a human society that was dialed dramatically further toward you know self-awareness other awareness compassion and sharing than our current society and of course greater material abundance helps but to some extent material abundance is a subjective perception also because many Stone Age cultures perceived themselves as living in great material abundance that they had all the food and water they wanted they lived in a beautiful place that they had sex lives that they had children I mean they they they they had abundance without any factories right so I I think Humanity probably would be capable of fundamentally more positive and and joy-filled mode of of social existence than than what we have now clearly Marx didn't quite have the right idea about about how to how to get there I mean he missed he missed a number of of key aspects of uh of human society and and its Evolution and if we look at where we are in society now how to get there is is a quite a quite different question because they're very powerful forces pushing people in in different directions than a positive joyous comp compassionate existence right so if we were tried to um you know Elon Musk is uh dreams of colonizing Mars at the moment so we maybe he'll have a chance to start a new civilization uh with a new governmental system and certainly there's quite a bit of chaos we're sitting now I don't know what the date is but this is uh June there's quite a bit of chaos and all different forms going on in the United States and all over the world so there's a hunger for new types of governments new types of leadership new types of of systems what uh and so what are the forces at play and how do we move forward yeah I mean colonizing Mars first of all it's it's a super cool thing to do we we we should be doing it so you're you're you love the idea yeah I mean it's more important it's more important than making chocolatier chocolates and and sexier lingerie and and many of the things that we spend a lot more resources on as a as a species right so I mean we certainly should do it I think that the possible Futures in which a Mars colony makes a critical difference for Humanity are are are are very few I mean I I I I I think I mean assuming we make a Mars colony and people go live there in a couple decades I mean their supplies are going to come from Earth the money to make the colony came from Earth and whatever powers are supplying the the the goods there from from Earth are going to in effect be in in control of that of that Mars colony of course there are outlier situations where you know Earth gets nuked into Oblivion and somehow Mars has been made self- sustaining by that point and and then Mars is what allows Humanity to persist but I think that those are very very very unlikely you don't think it could be a first step on a long journey of course it's a first step on a long journey which which is which is awesome I'm guessing the colonization of the rest of the physical universe will probably be done by agis that are better designed to live in space than by by the meat machines that that that we are but I mean who knows we may cryopreserve ourselves in some Superior way to what we know now and like shoot ourselves out to Alpha centurum Beyond I mean that's all cool it's very interesting and it's much more valuable than most things that you spending its resources on on the other hand with aggi we can get to a singularity before the Mars colony becomes sustaining for sure possibly before it's even operational so your intuition is that that's the problem if we really invest resources and we can get to faster than a legitimate full like self- sustaining colonization of Mars yeah and it's it's very clear that we will to me because there's so much economic value in getting from Nar AI toward toward AGI whereas the Mars colony there's less economic value until you get quite far far far out into the into the future so I think that's very interesting I just think it's it's somewhat somewhat off to the side I mean Ju Just as I think say you know art and music are are very very interesting and I want to see resources go into amazing art and music being being created and I i' rather see that than a lot of the garbage that Society spends their money on on the other hand I don't think Mars colonization or inventing amazing new genres of music is is not one of the things that is most likely to make a critical difference in the evolution of human or non-human life in in in in this part of the universe o o over the next decades you think AGI is really AI is is by far the most important thing that's on the horizon and then technologies that have direct ability to enable AGI or to accelerate AGI are also very important for example say qu Quantum Computing I don't think that's critical to achieve AGI but certainly you could see how the right qualum Computing architecture could massively accelerate AGI similar other other types of of nanotechnology right now the quest to cure aging and end disease while not in the big picture as important as as as AGI of course it's important to to all of us as as as individual humans and if someone made a super longevity pill and distributed it tomorrow I mean that would be huge and a much larger impact than a Mars colony is is is going to have for quite some time but perhaps not as much as an AGI system no because if you get if you can make a benevolent AGI then all the other problems are solved I mean the if then the AGI can be once it's as generally intelligent as humans it can rapidly become massively more generally intelligent than humans and and then that that AGI should be able to solve science and engineering problems but much better than than than human beings as long as it is in fact motivated to do so that's why I said a a benevolent AGI there could be other kinds maybe it's good to step back a little bit I mean we've been using that term AGI people often cite you as the Creator or at least the popularizer of the term AGI artificial general intelligence can you tell the origin story of the term sure so yeah I would say I I launched the term AGI upon the world for for for what what it's worth without ever fully being in in in love with the term right what happened is I was editing a book and this process started around 2001 or 2 I think the book came out 2005 finally I was editing a book which I provisionally was titling real Ai and I mean the goal was to gather together fairly serious academic is papers on the topic of making thinking machines that could really think in the sense like people can or or or even more broadly than people can right so then I was reaching out to other folks that i' had encountered here or there who were in interested in in in that which included some some other folks out of the who I knew from the transhumanist and singularitarianism I think he may have been have just started doing his PhD with uh Marcus Hooter who at that time hadn't yet published his book Universal AI which sort of gives a mathematical foundation for artificial general intelligence so I reached out to Shane and Marcus and Peter Vos and my pay Wang who was another former employee of mine who had been Douglas hoffstead PhD student who had his own approach to AGI and a bunch of some Russian folks reached out to these guys and they contributed papers for the book but that was my provisional title but I never loved it because in the end you know I was doing some what we would Now call narrow AI as well like applying machine learning to genomics data or chat data for sentiment analysis and I mean that work is real and in a sense in a sense it's it's really AI it's just a different kind of kind of AI Ray KW wrote about narrow AI versus strong AI but that seemed weird to me because first of all narrow and strong are not Anton that's right I mean but secondly strong AI was used in the cognitive science literature to mean the hypothesis that digital computer AIS could have true Consciousness like like human beings so there was already a meaning to strong AI which was complexly different but related right so we were tossing around on an an email list whether what title title it should be and so we we talked about narrow AI broad AI wide AI narrow AI General Ai and I think it it was either Shane leg or Peter Vos on the private email discussion we had you said but why don't we go with AGI artificial general intelligence and pay Wang wanted to do GI General artificial intelligence cuz in Chinese it goes in that order right but we figured gay wouldn't work in in in US culture at that time right so so we we went with the AGI AGI we used it for the for the title of that book and part of Peter and Shane's reasoning was you have the G factor in Psychology which is IQ general intelligence right so you have a meaning of GI general intelligence in Psychology so then you're looking like artificial GI so then oh that makes a lot of sense we use that for the we use that for the title of the book and so I think I maybe both Shane and Peter think they invented the term but but then later after the book was published this guy Mark grid came up to me and he's like well I I publish an essay with the term AGI in it in like 1997 or something and so I'm just waiting for some Russian to come out and say they published that in 1953 right I mean that term that term is not dramatically inovative or anything it's one of these obvious in hindsight things which is also annoying in a way because you know Josh habach who you you interviewed is a close friend of mine he likes the term synthetic intelligence which I like much better but it hasn't it hasn't actually caught on right because I mean artificial is a bit off to me because AR artifice is like a tool or something but but not all AGI are going to be tools I mean they may be now but we're aiming toward making them agents rather than than tools and in a way I don't like the distinction between artificial and natural because I mean we're we're part of nature also and machines are part of are are part of nature I mean you can look at evolved versus engineered but that that's a different that's a different distinction then it should be engineered general intelligence right and then General well if you look at Marcus Hooter's book Universal what he argues there is is you know within the domain of computation Theory which is limited but interesting so if you assume computable environment it's a computable reward functions then he articulates what would be a truly general intelligence a system called aixi which is quite beautiful I I and that's that's the middle name of of my latest child actually is it what's the first name first name is quiry Q rxi which my my wife came out with but that that's an acronym for Quantum organized r expanding intelligence and his middle name is his middle name is exes actually which is uh mean means the the former principle underlying I exe but in any case you're giving Ela musk a new child a run I I I did it first he he he cop he copied me with this this new freakish name but now if I have another baby I'm GNA have to out outdo him it's become an arms Ras of weird geeky baby names yeah we'll see what the babies think about it right but I mean my oldest son zarathustra loves his name and my daughter sharizad loves her name so so far basically if you give your kids weird names they live up to it well you're obliged to make the kids weird enough that they like the names right it directs their upbringing in a certain way but yeah anyway I mean what Marcus showed in that book is that a truly general intelligence theoretically is possible but would take infinite computing power so then the artificial is a little off the General is not really achievable within physics as as as we know it and I mean physics as we know it may be limited but that's what we have to work with now intelligence infinitely General you mean like yeah information processing perspective yeah yeah in intelligence is not very well- defined either right I mean what what what what does it mean I mean in AI now it's fashionable to look at it as maximizing and expected reward over the future but that's that sort of definition is path olical in various ways and my my friend David wein bomb AKA Weaver he had a beautiful PhD thesis on open-ended intelligence trying to conceive intelligence in a without a reward without yeah he's just looking at it differently he's looking at complex self-organizing systems and looking at an intelligent system as being one that you know revises and grows and improves itself in conjunction with with its with its environment without necessarily there being one objective function it's trying to maximize although over certain intervals of time it may act as if it's optimizing a certain objective function very much Solaris from Stan's novels right so yeah the point is artificial general and intelligence don't work they're all bad on the other hand everyone knows what AI is yeah and AI seems immediately comprehensible to people with with a technical background so I think that the term is served as sociological function and now now now it's out there everywhere which which which baffles me it's like KFC I mean that's that's it you're we're stuck with agii probably for a very long time until AGI systems take over and rename themselves yeah and that I mean that we'll be we're stuck with gpus too which mostly have nothing to do with Graphics anymore right I wonder what the AGI system will call us humans I was maybe Grandpa yeah GPS yeah Grandpa Processing Unit yeah biological Grandpa processing units uh okay so um maybe also just a comment on AGI representing before even the term existed representing a kind of community now you've talked about this in the past sort of AI has come in waves but there's always always been this community of people who dream about creating uh General human level super intelligence systems uh can you maybe give your sense of the history of this community as it exists today as it existed before this deep learning re Evolution all all throughout the winters and the Summers of AI sure uh first I would say as a side point the winters and Summers of AI are greatly exaggerated by by Americans yeah and in the if you look at the publication record of the artificial intelligence Community since say the 1950s you would find a pretty steady growth in advance of ideas and and and papers and what's thought of as an AI winter or summer was sort of how much money is the US military pumping into AI which was was meaningful on the other hand there was AI going on in Germany UK and in Japan and in Russia all over the place while US military got more and less less in enthused about AI so what I mean that happened to be just for people who don't know the US military happened to be the main source of funding for AI research so another way to phrase that is it's up and down of uh funding for artificial intelligence research true and I would say the correlation between funding and intellectual Advance was not 100% right because I mean in in Russia as an example or in Germany there was less dollar funding than in the US but many foundational ideas were were laid out but it was more Theory than than implementation right and us really excelled at sort of breaking through from theoretical papers to working implementations which which did go up and down somewhat with US military funding but still I mean you can look in the 1980s Dietrich derer in Germany had self-driving cars on the autoban right and I mean this it was a little early with regard to the car industry so it didn't catch on such as has has happened now but I mean that whole advancement of self-driving car technology in Germany was Prett pretty much independent of AI military Summers and and Winters in the US so there there's been more going on in AI globally than not only most people on the planet realize but than most new AI phds realize because they've come out within a certain Sub sub field of of AI and haven't had to look so much so much beyond that but I I would say when I got when I got my PhD in 1989 in in mathematics I was interested in AI already Philadelphia by yeah I started at myu then I transferred to to Philadelphia to Temple University good old North Philly North Philly yeah yeah yeah the pearl of pearl of the US right yeah you never stopped at a red light then because you were afraid if you stopped at the red light some more car Jackie so strive through every red light yeah it is a every every day driving or bicycling to Temple from my house was it was like a new new adventure right but yeah when I the reason I didn't do PC and AI was what people were doing in the academic AI field then was just astoundingly boring and seemed wrong-headed to me it was really like rule-based expert systems and production systems and I actually I loved mathematical logic I had nothing against logic as the cognitive engine for an AI but the idea that you could type in the knowledge that AI would need to think seemed just completely stupid and and and and wrong-headed to me I mean you can use logic if you want but somehow the system has got to be automated learning right it should be learning from experience and the AI field then was not interested in learning from experience I mean some researchers certainly were I mean I I remember in mid 80s I discovered a book by John Andreas which was it was about uh reinforcement learning system called perus p rr- p USS which was an acronym that I can't even remember what it was for but purpose anyway but he I mean that was a system that was supposed to be an AGI and basically by some sort of fancy like Markoff decision process learning it was supposed to learn everything just from the bits coming into it and learn to maximize its reward and become become intelligent right so that was there in Academia back then but it was like isolated scattered weird people but all these scattered weird people in that period I mean they they laid the intellectual grounds for what happened later so you look at John Andreas at University of Canterbury with his purpose reinforcement learning marov system he was the PG supervisor for John clar in in in New Zealand now John clear worked with me when I was at wado University in in 1993 in in in New Zealand and he worked with Ian Whitten there and they launched WCA which was the first open- Source machine learning toolkit which was launched in I guess '93 or '94 when I was at wada University written in Java unfortunately written in Java which was a cool language back then though right I guess it's still well it's not cool anymore but it's powerful I find like most programmers now I find Java unnecessarily bloated but back then it was like Java or C++ basically and Java oriented so it's Java was easier for students yeah amusingly a lot of the work on wo when we were in New Zealand was funded by a u sorry A New Zealand government grant to use machine learning to predict the menstrual cycles of cows so in the US all the grant funding for AI was about how to kill how to kill people or spy on people in New Zealand it's all about cows or kiwi fruits right yeah so so yeah anyway I mean Andre John Andreas had his probability Theory based reinforcement learning Proto AGI John clear was trying to do much more ambitious probabilistic AGI systems now John clear helped do wo which was the first open- Source machine learning tool get so the predecessor for tensor flow and torch and and all these things also Shane leg was was at at wado working with working with with with John CLE and Ian Ian wh and and this whole group and and then working with my own company my company webm an AI company I had in in the late '90s with a team there at wado University which is how Shane got his head full of of AGI which led him to go on and with Gabus found Deep Mind so what you can see through that lineage is you know in the 80s and 70s John Andreas was trying to build probalistic reinforcemen AGI systems the technology the computers just weren't there to support it his ideas were were very similar to what people are doing now but you know although he's long since passed away and didn't become that famous outside of Canterbury I mean the lineage of ideas passed on from him to his students to their students you can go Trace directly from there to me and and to Deep Mind right so that there was a lot going on in AGI that did ultimately lay the groundwork for what we have today but there was there wasn't a community right and so when I when I started trying to pull together an AGI community it was in the I guess the early Arts when I was living in in Washington DC and making a living doing AI Consulting for VAR various US government agencies and I I organized the first Agia Workshop in 2006 and I mean it wasn't it wasn't like it was literally in my basement or something I mean it was it was in the conference room at the Marriott in Bethesda it's not not that not that edgy or underground unfortunately but still how many people attended about 60 or something that's not bad I mean DC has a lot of AI going on probably until the last five or 10 years much more than Silicon Valley although it's just quiet because of the nature of what what Happ what happens in in in DC their business isn't driven by PR mostly when something starts to work really well it's taken black and becomes even even more quiet right yeah but yeah the thing is that really had the feeling of a group of star eyed Mavericks like huddled in a basement like plotting how to overthrow the the narrow AI establishment and you know for the first time in some cases coming together with others who shared their passion for AGI and the technical seriousness about about working on it right and that I mean that's very very different than than what we have today I mean now now it's a little bit different we we have AGI conference every year and then there's several hundred people rather than than 50 now now it's more like this is the main Gathering of people who want to achieve AGI and think that uh large scale nonlinear regression is is is is not the golden path to to AGI so I mean it's AK and your all Network yeah yeah yeah well certain architectures for for for learning using neural network so yeah the AGI conferences are sort of now the main concentration of people not obsessed with deep neural Nets and deep reinforcement learning but but still interested in in in a in AGI not not not not the only ones I mean there there's other little conferences and and groupings interested in uh human level Ai and and cognitive cognitive architectures and so forth but yeah it's it's been a big shift like back back then you couldn't really it would be very very edgy then to give a university Department seminar the mentioned AGI or human level AI it was more like you had to talk about something more short-term and immediately practical then you know in the bar after the seminar you could about AGI in the same breath as uh as time travel or or the simulation hypothesis or something right whereas now now AGI is not only in the academic seminar room like you have Vladimir Putin knows what AGI is and he's like Russia needs to become the leader in AGI right so national leaders and CEOs of large corporations I mean the CTO of Intel just Ratner this was years ago Singularity Summit conference 2008 or something he's like We Believe Ray KW The Singularity will happen in 2045 and it will have Intel Inside So I mean so it's gone it's gone from being something which is the pursuit of like crazed Mavericks crackpots and and science fiction Fanatics to being you know a a marketing term for large large corporations and and national leaders right which is a astounding transition but yet in the in the course of this transition I think a bunch of sub communities have formed and the community around the AGI conference series is certainly one of them it hasn't grown as big as I might have liked it to on on the other hand you know sometimes a a modest ized Community can be better for making intellectual progress also like you go to a society for Neuroscience conference you have 35 or 40,000 neuroscientists on the one hand it's it's amazing on the other hand you're not going to talk to the leaders of the of the of of the field there if if you're an outsider yeah in the same in the same sense the triple AI the artificial intelligence uh the main kind of generic artificial intelligence Comm uh conference it's too big it's uh too amorphous like it it doesn't make it and and nip has become a a company advertising Outlet now right so I so yeah so I mean to to comment on uh the role of AGI in the research Community i' still if you look at neurs if you look at cvpr if you look at these uh eye clear you know um AGI is still seen as the outcast I would still I would say in these main machine learning in these main artificial intelligence uh conferences amongst the researchers I don't know if it's an accepted term yet I what I've seen bravely you mention Shane leg is Deep Mind and then open AI are the two places that are I would say unapologetically so far I think it's actually changing unfortunately but so far they've been pushing the idea that the goal is to create an AGI well they have billions of dollars behind them so I mean that that they in the public mind that that certainly carries some oomph right I mean I mean but they also have really strong researchers right they they do they're great teams I mean Deep Mind in particular yeah and they have I mean Deep Mind has Marcus hutter walking around I mean there's all these folks who basically their full-time position involves dreaming about creating AGI yeah I mean Google brain has a lot of amazing AGI oriented people also I mean and and I mean so I'd say from a public marketing view Deep Mind and open AI are the two large wef funded organizations that have put the term and concept AGI out there sort of as part of their Public Image but I mean there there're certainly not there are other groups that are doing research that seems just as as as aiish to me I mean including a bunch of groups in in Google's main main Mountain View office so yeah it's true AGI is somewhat away from the mainstream now but if you compare to where it was right you know 15 years ago there's there's there's there's been an amazing mainstreaming you could say the same thing about super longevity research which is one of my my application areas that I'm excited about I mean I've been talking about this since the '90s but working on this since 2001 and back then really to say you're trying to create therapies to allow people to live hundreds or thousands of years you you were way way way way out of out of the industry academic mainstream but now you know Google had had project Calico Craig ventor had human longevity Incorporated and once once the Suits come marching in right I mean once once there's big money in it then people are forced to take it take it seriously because that's the way Mo modern society works so it's still not as mainstream as cancer research just as AGI is is not as mainstream as automated driving or something but the degree of mainstreaming that's happened in the last uh you know 10 to 15 years is is astounding to those of us who've been at it for a while yeah but there's a marketing aspect to the term but in terms of actual full force research that's going on under the header of AGI it's currently I would say dominated maybe you can disag degree dominated by neural networks research that the nonlinear regression as you mentioned um like what's your sense with with open Cog with your work in in general I was uh logic based systems and expert systems for me always seemed uh to capture a deep element of intelligence that needs to be there like you said it needs to learn it needs to be automated somehow but that seems to be missing from a lot of the a lot of research currently um so what's your sense I guess one way to ask this question what's your sense of what kind of things will an AGI system need to have yeah that that's a very interesting topic that I thought about for for a long time and I I think there are many many different approaches that can work for getting to to human level AI so I I I don't I don't think there's like one golden algorithm one one golden design that that that can that can work and I mean flying machines is the the much warant analogy here right like I mean you have airplanes you have helicopters you you you you have balloons you have stealth bombers that don't look like regular airplanes you you've got all blimps Birds too Birds yeah and and bugs right and uh you I mean and there are certainly many kinds of flying machines that and there's a catapult that you can just launch there's bicycle powered like uh flying machines right nice yeah yeah so now these are all analyzable by a basic theory of of aerodynamics right now so one issue with AGI is we don't yet have the analog of the theory of aerodynamics and that's that's what Marcus hter was trying to make with the Axe and his general theory of general intelligence but that theory in its most clearly articulated Parts really only works for either infinitely powerful machines or almost or insanely yeah impractically powerful machines so I mean if if you were going to take a theory based approach to AGI what you would do is say well let's let's take what's called say axe TL which is which is hutter's Axe machine that can work on merely insanely much processing power rather than infinitely much what does TL stand for uh time time and length Okay so you're basically how how constrained somehow yeah yeah yeah so how how axe Works basically is each each each action that it wants to take before taking that action it looks at all its history yeah and then it looks at all possible programs that it could use to make a decision yeah and it decides like which decision program would have let it make the best decisions according to its reward function over its history and he uses that decision program to take to make the next decision right it's not afraid of infinite resources it's searching through the space of all possible computer programs in between each action and each next Action Now XL searches through all possible computer programs that have runtime less than T and length less than l so it's which is still an impracticably humongous space right so what what you would like to do to make an AGI and what will probably be done 50 years from now to make an AGI is say okay well we we we have some constraints we have these processing power constraints and you know we have the space and time constraints on on on on the program we have energy utilization constraints and we have this particular class environments class of environments that we care about which may be say you know manipulating physical objects on on the surface the Earth communicating in in in human language I mean whatever our particular not not annihilating Humanity whatever our particular requirements happen to be if you formalize those requirements in some formal specification language you should then be able to run a automated program specializer on Axl specialize it to the the Computing resource constraints and the particular environment and goal and then it will spit out like the the specialized version of Axl to your resource restrictions in your environment which will be your AGI right and that that that I think is how our super AGI will create new AGI systems right but but and that's a very rough seems really inefficient that's a very Russian approach by the way like the whole field of program specialization CA came out of Russia can you backtrack so what is program specialization so it's basically well say take take take sorting for example you can have a generic program for sorting lists but what if all your lists you care about are length 10,000 or less got it you can run an automated program specializer on your sorting algorithm and it will come up with the algorithm that's optimal for sorting lists of length 1,000 or Le or 10,000 or less right it's kind of like isn't that the kind of the process of evolution is uh it's a program specializer to the environment so you're you're kind of evolving human beings or Liv exactly I your Russian Heritage is is showing there I mean so without Alexander vitv I mean there and Peter Anin and so on I mean there's a yeah there there's a long history of of thinking about Evolution Evolution that way that way also right so well my my my my point is that what we're thinking of as a human level general intelligence you know if you start from narrow AIS like are being used in the commercial AI field now then you're thinking okay how do we make it more and more General on the other hand if you start from aexi or Schmid Uber's girdle machine or these infinite infinitely powerful but practically infusible AIS then getting to a human level AGI is a matter of specialization it's like how do you how do you take these maximally General learning processes and how do you how do you specialize them so that they can operate within the resource constraints that you have but will achieve the particular things that that you care about because we we are not we humans are not maximally General intelligences right if I ask you to run a maze in 750 Dimensions you'll probably be very slow whereas at two Dimensions you you're probably you're probably way better right so I mean we're special be because our our hippocampus has a two-dimensional map in it right and it does not have a 750 dimensional map in it so I mean we we are you know A peculiar mix of generality and and and specialization right we'll probably start quite General at Birth uh not obviously still narrow but like more General than we are at age uh 20 and 30 and 40 and 50 and 60 I don't think that I I I think it's more complex than that because I mean the young in in some sense a young child is less biased and the brain has yet to sort of crystallize into appropriate structures for processing aspects of the physical and social world on on on the other hand the young child is very tied to their sensorium whereas we can we can deal with abstract mathematics like 750 dimensions and the young child cannot because they they haven't they haven't grown what pette called the the formal capabilities they they haven't learned to abstract yet right and and the ability to abstract gives you a different kind of generality than than what than what a baby has so there there's both more specialization and more generalization that comes with with the development process actually I mean I guess just the the trajectories of the specialization are most controllable at the young age I guess is uh as one way to put it do you have do you have kids no they're not as controllable as you think so you think it's uh interesting I I I I I think honestly I think a human adult is much more generally intelligent that than a human baby babies are very stupid I mean I mean I mean they're cute they're cute which is which is why we put up with their repetitiveness and and stupidity but and they have what the Zen guys would call a a beginner's mind which is a beautiful thing but that doesn't necessarily correlate with with a high level of of in of Intelligence on the plot of like cuteness and stupidity there there's a the there's a process that allows us to put up with their stupidity they get become more by the time you're an ugly old man like me you got to get really really smart to compensate okay cool but yeah going back to your your original question so the the way I look at human level AGI is yeah how do you specialize you know unrealistically inefficient superhuman Brute Force learning processes to the specific goals that humans need to achieve and the specific resources that that that we have and both of these the goals and the resources the environments I me all all this is important and on the on the resources side it's important that the hardware resources we're bringing to Bear are very different than the human brain so the way the way I would want to implement AGI on a a bunch of neurons in a vat that I could rewire arbitrarily is quite different than the way I would want to create AGI on say a modern server Farm of CPUs and gpus which in turn may be quite different than the way I would want to implement AGI on you know whatever quantum computer will will have in in 10 years supposing someone makes a robust Quantum turning machine or or something right so I I I I think you know there there's been co-evolution of the the patterns of organization in the human brain and and the physiological particulars of of of the human brain o o over time and when you look at neural network works that is one powerful class of learning algorithms but it's also a class of learning algorithms that evolve to exploit the particulars of the human brain as as a computational substrate if you're looking at the computational substrate of a modern server Farm you won't necessarily want the same algorithms that you want that you want on the on the human brain and you know from the right level of abstraction you you you could look at maybe the best algorithms on a brain and the best algorithms on a modern computer network as implementing the same abstract learning and representation processes but you know finding that level of abstraction is its own AI research project then right so that's about the hardware side and and the software side which follows from that then regarding what are the requirements I I wrote the paper years ago on what I called the embodied communication prior which was quite similar in intent to Yoshua benio's recent paper on the Consciousness prior except I I didn't want to wrap up Consciousness in it because to me the qualia problem and subjective experience is a very interesting issue also which which we can chat about yeah but I would rather keep that philosophical debate distinct from the debate of what kind of biases do you want to put in a general intelligence to give it humanlike general intelligence and I'm not sure yosha Benjo is really addressing that kind of I's just using the term I I love yosua to to pieces like he he's by far my favorite of the the Lions of of deep learning but he's s such such a good-hearted Guyer for sure I am not I am not sure he has Plumb to the depths of the philosophy of of of Consciousness no he's using it as a sexy T yeah yeah yeah so I I what I called it was the embodied communication prior and can you maybe explain it a little bit yeah yeah what what I meant was you know what are we humans evolved for you can say Being Human but that's that's very abstract right I mean we our minds control individual bodies which are autonomous agents moving around in a world that's composed largely of solid objects right and we've also evolved to communicate via language with other you know solid object agents that are going around doing things collectively with us in a in a world of solid objects and these things are very obvious but if you compare them to the scope of all possible intelligences or even all possible intelligences that are physically realizable that actually can strange things a lot so if you start to look at you know how would you realize some Specialized or constrained version of universal general intelligence in a system that has you know limited memory and limited speed of processing but who general intelligence will be biased toward controlling a solid object agent which is Mobile in a solid object world for manipulating solid objects and communicating via language with other similar agents in that same world right then starting from that you're starting to get a requirements analysis for for for human human level general intelligence and then that that leads you into cognitive science and you can look at say what are the different types of memory that the human mind and brain has and this this has matured over the last decades and I got into this a lot in so after getting my PhD in math I was an academic for eight years I was in Departments of mathematics computer science and psychology when I was in the psychology department the University of Western Australia I was focused on cognitive science of of memory and and perception actually I was I was teaching neuron Nets and deep neural Nets and it was multi-layer perceptrons right psychology yeah a cognitive science it was cross disciplinary among engineering math psychology philosophy Linguistics Compu computer science but yeah we we were teaching psychology students to try to model the data from Human cognition experiments using multi-layer perceptrons which was the early version of a deep neural network very very yeah recurrent back propop was very very slow to train back then right so this is the study of these constraint systems that are supposed to deal with physical object so if you look if you look at if you look at cognitive psychology you can see there's multiple types of memory which are to some extent represented by different subsystems in the human brain so we have episodic memory which takes into account our life history and everything that's happened to us we have declarative or semantic memory which is like facts and beliefs abstracted from the particular situations as they occurred in there's sensory memory which to some extent is sense modality specific and then to some extent is is Unified ac across across sense modalities there's procedural memory memory of how to do stuff like how how to swing the tennis racket right which is there's motor memory but it's also a little more more abstract than than motor memory it involves cerebellum and cortex working working together then then there's there's memory linkage with emotion between with which has to do with linkages of Cortex and and and and lyic system there's specifics of spatial and temporal modeling connected with memory which has to do with you know hippocampus and Thalamus connecting to Cortex and the basil ganglia which influences Golds so we have specific memory of what goals sub goals and Sub sub goals we want to perceive in which context in the past human brain has substantially different subsystems for these different types of memory and substantially differently tuned learning like differently tuned modes of long-term potentiation to do with the types of neurons and neurotransmitters and the different parts of the brain correspond to these different types of knowledge and these different types of memory and learning in the human brain I mean you can back these all into embodied communication for controlling agents and in Worlds of of of solid objects now so if you look at building an AGI system one way to do it which starts more from cognitive science than Neuroscience is to say okay what are the types of memory that that are necessary for this kind of world yeah yeah necessary for this this sort of intelligence what types of learning work well with these different types of memory and then how do you connect all these things together right and of course the human brain did it incrementally through Evolution because each of the subn networks of the brain I mean it's not really the lobes of the brain it's the sub networks Each of which is is widely distributed which of the sub each of the sub networks of the brain Co involved with the other subn networks of of the brain both in terms of its patterns of organization and the particulars of the neurophysiology so they all grew up communicating and adapting to each other it's not like they were separate black boxes that were then were then glommed together right whereas as Engineers we would tend to say let's make let's make the declarative memory box here and the procedural memory box here and the perception box here and W wire them together and when you can do that it's it's interesting I mean that's how a car is built right but on the other hand that's clearly not how biological systems are are are made the parts coevolve so as to adapt and and work together so this that's by the way how every human engineered system that flies that was were using that analogy before is built as well so do you find this at all appealing like there's been a lot of really exciting which I find strange that it's ignored uh work in cognitive architectures for example throughout the last few decades do you find yeah I mean I I I had a lot to do with that with that community and you know Paul Rosen Blum who was one of the and John lared who built the sore architecture are friends of mine and uh I I learned SAR quite well and actar and these different cognitive architectures and how I was looking at the AI World about 10 years ago before this whole commercial deep learning explosion was on the one hand you had these cognitive architecture guys who were working closely with psychologists and cognitive scientists who had thought a lot about how the different parts of a humanlike mind should should work together on the other hand you had these learning theory guys who didn't care at all about the architecture but were just thinking about like how how do you recognize patterns and large amounts of data and in some sense what you needed to do was was to get the learning that the learning theory guys were doing and put it together with the architecture that the cognitive architecture guys were doing and then you would have what you needed now you can't unfortunately when you look at the details you can't just do that without totally rebuilding what what is happening on both the cognitive architecture and the learning side so I mean they tried to do that in sore but what they ultimately did is like take a neural deep neural net or something for perception and you includ as one of the one of the black boxes it's one it becomes one of the boxes the learning mechanism becomes one of the boxes opposed to fundamental that that doesn't quite work you could look at some of the stuff Deep Mind has done like the the differential neural computer or something that sort of has a neural net for deep learning perception it has another neural net which is like a a memory matrix it's St say the map of the London Subway or something so probably Demis aabus was thinking about as like part of Cortex and part of hippocampus because hippocampus has a spatial map and when he was a neuroscientist he was doing a bunch on cortex hippocampus inter ction so there the DNC would be an example of folks from the deep neural net world trying to take a step in the cognitive architecture Direction by having two neurom modules that correspond roughly to two different parts of the human brain that deal with different kinds of memory and learning but on the other hand it's super super super crude from the cognitive architecture view right Ju Just as what what John L and sore did with neural Nets was super super crude from from a from a learning point of view because the learning was like off to the side not affecting the core representations right and mean you weren't learning the representation you were learning the data that feeds into the rep you you were learning abstractions of perceptual data to feed into the the representation that was was not learned right so yeah this this was this was clear to me a while ago and one of my hopes with the AGI Community was to sort of bring people from those two directions together that didn't happen much in terms of not yet and or what I was going to say is it didn't happen in terms of bringing like the Lions of cognitive architecture together with the Lions of deep learning it did work in the sense that a bunch of younger researchers have had their heads filled with both of those ideas this this comes back to a a saying my dad who was a university Professor often quoted to me which was a science advances one funeral at a time which I'm I'm I'm trying to avoid like I'm I'm 53 years old and I'm trying to invent amazing weird ass new things that that that nobody ever ever thought about which which we'll talk about in in in a few in a few minutes but there but there but there there is that aspect right like the people who've been at AI a long time and have made their career developing one aspect like a cognitive architecture or or a deep learning approach it can be hard on once you're old and have made your career doing one thing it can be hard to mentally shift gears I mean I I I try quite hard to remain flexible minded been successful somewhat in changing maybe uh have you changed your mind on some aspects of what it takes to build an AGI like technical things the hard part is that the world doesn't want you to the world or your own brain the world well that one point is your brain doesn't want to the other part is that the world doesn't want you to like like the people who have followed your ideas get mad at you if if if if you change your mind and and you know the media wants to pigeonhole you as as Avatar of of of of a certain a certain idea but yeah I i' I've changed my mind on on a bunch of things I mean when I started my career I really thought Quantum Computing would be necessary for for AGI and I I doubt it's necessary now although I think it will be a super major enhancement but I mean I'm also I'm now in the middle of embarking on a complete rethink and rewrite from scratch of our opencog AGI system together with uh alexe poov and his team in St Petersburg who's working with me in Singularity net so now we're trying to like go back to basics take take everything we learned from working with the current opencog system take everything everybody else has learned from working with with their with their their Proto AGI systems and and design design the best framework for the for the next stage and I do think there's a lot to be learned from the recent successes with deep neural Nets and deep reinforcement systems I mean people made these essentially trivial systems work much better than I thought they would and there's a lot to be learned from that and I want to incorporate that knowledge appropriately in our our opencog 2.0 system on on on the other hand I also think current deep neural net architectures as such will never get you any anywhere near AGI so I think you you avoid the pathology of throwing the baby out with the bath water and like saying well these things are garbage because foolish journalists overblow them as as as being the path to AGI and and a few researchers over overblow them as as well yeah there there's there's a lot of interesting stuff to be learned there on even though those are not not the golden path so maybe this is a good chance to step back you mentioned open coock 2.0 but go back to open K 0.0 which exist yeah uh yeah maybe talk to the history of open absolutely and you're thinking about these ideas I would say opencog 2.0 is a term we're throwing around sort of tongue and cheek because the existing opencog system that we're working on now is not remotely close to what we consider we'd consider a one a 1.0 right I mean I mean it's it it's an early it's it's been around what 13 years or something but it's still an early stage research system right and actually we're we are going back to the beginning in terms of theory and implementation because we feel like that's the right thing to do but I'm sure what we end up with is going to have a huge amount in common with with with with the current system I mean we all still like that the general approach so that so first of all what is open Cog sure open Cog is an open-source software project that I launched together with several others in 2008 and probably the first code written to that was written in 2001 or two or something that was developed uh as a proprietary co-base within my AI company nov LLC then we decided to open source it in two in 2008 cleaned up the code throughout some things add added some new things and what language is it written in it's C++ primarily there's a bunch of scheme as well but most of it C++ and it's separate from that something we'll also talk about is singularity net so it was it was born as a non networked thing correct correct well there are many levels of networks in inv involved here right no connectivity to the internet or no at at Birth yeah I mean Singularity net is a separate project and a separate body of code and you can use Singularity net as part of the infrastructure for a distributed opencog system but they are there are different layers yeah got it so opencog on the one hand as a software framework could be used to implement a variety of different Ai architectures and and and algorithms but in practice there's been a group of developers which I've been leading together with lenus vus nil giler and a few others which have been using the opencog platform and infrastructure to to implement certain ideas about how to make an an AGI so there there's been a little bit of ambiguity about opencog the software platform versus opencog the the the AGI design because in theory you could use that software to do you could use it to make a neural net you could you could use it to make a lot of different what kind of stuff does the software platform provide like in terms of utilities tools like what what yeah let me first tell about opencog as a software platform and then I'll tell you the specific AGI R&D we've been building building on top of it yep so the core component of opencog as a software platform is what we call the adom space which is a weighted labeled hypergraph atom atom space atom space yeah yeah not not Adam like Adam and Eve although that would be cool too yeah so you have a hyper graph which is like a so a graph in this sense is a bunch of nodes with links between them a hyper graph is like a graph but links can go between more than two nodes so you have a link between three nodes and in fact in fact open cogs Adam space would properly be called a metagraph because you can have links pointing to link LS or you could have links playing the whole subgraphs right so it's a it's an extended hyper graph or or a metagraph and is metagraph a technical term it is now a technical term interesting but I don't think it was yet a technical term when we started calling this a generalized hypergraph in but in in any case it's a weighted labeled generalized hypergraph or weighted labeled metagraph the the weights and labels mean that the nodes and links can have numbers and and symbols attached to them so they can have Types on them they can have numbers on them that represent say a truth value or an importance value for for a certain purpose and of course like with all things you can reduce that to a hypergraph and then the hypergraph can be reduce hypergraph to a graph and you could reduce a graph to an adjacency Matrix so I mean there's always multiple representations but there's a layer of representation that seems to work well here got it right right right and so similarly you could have a link to a whole graph because a whole graph could repres present say a body of information and I could say I reject this body of information then one way to do that is make that link go to that whole subgraph representing the body of information right I mean there's many there are many alternate representations but that's anyway what we have an opencog we have an atom space which is this weighted labeled generalized hypergraph knowledge store it lives in Ram there's also a way to back back it up to disk there are ways to spread it among among multiple different Mach Maes then there are various utilities for dealing with that so there's a pattern matcher which lets you specify a sort of abstract pattern and then search through a whole atom space w labeled hypergraph to see what sub hypergraphs May match that that pattern for an example so that's then there's there's something called the the Cog server in opencog which lets you run a bunch of different agents or processes these in auler and each of these agents basically it reads stuff from the adom space and it writes stuff to the adom space so th this is sort of the basic operational model like that's the software framework right and and of course that's there's a lot there just from a scalable software engineering standpoint so you could use this I don't know if you've have you looked into the Steven wols physics project recently with the hypog grass and stuff could you theoretically use like the software framework to play certainly could although Wolfram would rather die than use anything but Mathematica for for his work well that's yeah but there's a big community of people who are uh you know would love integration and like like you said the young minds love the idea of integrating of connecting yeah that's right and I would add on that note the idea of using hypergraph type models in physics is not very new like if if you look at the Russians did it first well I'm sure they did and a guy named Ben drus who's a mathematician a professor in Louisiana or somewhere had a beautiful book on Quantum sets and hypergraphs and algebraic topology for discreet models of physics and carried it much farther than than than Wolfram has but he's he's not rich and famous so so it didn't didn't get in the headlines but yeah wolf from aide yeah certainly that's a good way to put it the whole opencog framework you could use it to model biological networks and and simulate biology processes you could use it to model physics on on on discrete graph models of of of physics so you can you could use it you could use it to do say biologically realistic neur neural networks for for for example and that's so that that's a framework what do agents and processes do do they grow the graph do they what kind of computations just to get get a sense are they supposed in theory they could do anything they want to do they're just C++ processes on on the other hand the computation framework is sort of designed for agents where most of their processing time is taken up with reads and writs to the atom space and so that's that's a very different processing model then say the matrix multiplication based model as underlies most deep most deep Learning Systems right so so you could I mean you could create an agent that just factored numbers for a billion years it would run within the opencog platform but it would be pointless right the I mean the point of doing opencog is because you want to make agents that are cooperating via reading and writing into this this weighted labeled hypergraph right and so that and that that has both cognitive architecture importance because then this hypergraph is being used as a sort of shared memory among different cognitive processes but it also has you know software and Hardware implementation implications cuz current GPU architectures are not so useful for opencog whereas a graph chip would be incredibly useful right and I think graph core has those now but they're not ideally suited for this but I think in the next let's say three to five years we're going to see new chips where like a graph is put on the Chip And and you know the back and forth between multiple processes acting simdi and Mimi on that on that graph is going to be fast and then that may do for opencog type architectures what gpus did for for deep neural architectures as a small tangent can you comment on thoughts about neuromorphic Computing so like Hardware implementations of all these different kind of uh are you interested are you excited by that possi I'm excited by graph processors because I think they can massively speed up speed up opencog which is a class of architectures that that I'm that that I'm working on I think if you know in principle neomorphic Computing should be amazing I haven't yet been fully sold on any of the systems that that are out there like memists should be amazing too right so a lot of these things have obvious potential but I haven't yet put my hands on the system that that seemed to manifest that Marxism should be amazing but the the the current systems not been great I mean look for example if you wanted to make a biologically real real istic Hardware neural network like taking making a circuit in Hardware that emulated like the hjin Huxley equation or the isak kevich equation like equ differential equations for biologically realistic neuron and putting that in Hardware on the chip that would seem that it would make more feasible to make a large scale truly biologically realistic neural network now what's been done so far is not like that so I guess personally as a researcher I mean I've done a bunch of work in cognitive neuro in sorry in computational Neuroscience where I did some work with IPA in in in DC intelligence Advanced research project agency we were looking it how do you how do you make a biologically realistic simulation of seven different parts of the brain cooperating with each other using like realistic nonl dynamical models of neurons and how do you get that to simulate what's going on in the Mind of a geoint intelligence analyst while they're trying to find terrorists on a map right so if you want to do something like that having neuromorphic Hardware that really let you simulate like a realistic model of the neuron would would would would be would be amazing but that's that's sort of with my computational Neuroscience haton right with an AGI haton I'm just more interested in these hypergraph knowledge representation based architectures which which would benefit benefit more from from various types of of graph processors because the main processing bottleneck is Reading Writing to Ram it's reading writing to the graph in Ram the main processing bottleneck for this kind of Proto AGI architecture is not multiplying matrices and and for that reason gpus which are really good at multiplying matrices don't don't don't apply as as well there there are Frameworks like gunrock and others that try to boil down graph processing to Matrix operations and and they're cool but you're still putting a square peg in in in into a round hole in a certain way the same is true I mean current Quantum machine learning which is very cool it's also all about how to get Matrix and Vector operations in in quantum mechanics and I see why that's natural to do I mean quantum mechanics is all unitary matrices and and vectors right on on the other hand you could also try to make graph Centric quantum computers which I I think is is is is is is is where things will go and then then we can have then we can make like take the opencog implementation layer implement it in a uncollapsed state inside a quantum computer but that that may be the singularity squared right I'm I'm not I'm not I'm I'm not I'm not sure we need that to get get to human human level human level that's already beyond the the first singular but uh can we just yeah let's go back to opencog no yeah and the hypergraph and open yeah that's the software framework right so the the next thing is is our cognitive architecture tells us particular algorithms to put there got it can we Backtrack on the kind of do is this graph designed is it uh in general supposed to be sparse and the operations constantly grow and change the graph yeah the graph is sparse and but is it constantly adding links and so on it is a self modifying hypergraph so it's not so the write and read operations you're referring to this isn't just a fixed graph to which you change way it's constant growing graph yeah that yeah that that that's that's true so it's it is different model then say current deep neural Nets S have a fixed neural architecture and you're updating the weights although there have been like Cascade correlational neural architectures that grow new new nodes and links but the most common neural architectures now have a fixed neural architecture you're updating the weights and in open Cog you can update the weights and that certainly happens a lot but adding new nodes adding new links REM removing nodes and links is an equally critical part of the Systems Operations got it so now when you start to add these cognitive algorithms on top of this opencog architecture what does that look like so what yeah so that the within this framework then creating a cognitive architecture is basically two things it's it's choosing what type system you want to put on the nod and links in the hypergraph what types of nodes and links you want M and then then it's choosing what collection of Agents what collection of AI algorithms or processes are going to run to to operate on on on on this hypergraph and of course those two decisions are are closely closely connected to each other so in terms of the type system there are some links that are more neuronet like they just like have weights to get updated by heavan learning and activation spreads along them there are other links that are more logic like and nodes that are more logic like so you could have a variable node and you can have a node representing a universal or existential quantifier as in in predicate logic or or term logic so you can have logic like nodes and links or you can have neural like nodes and links you can also have procedure like nodes and links as as in say uh combinatory logic or or or Lambda calculus representing programs so you can have nodes and links representing many different types of semantics which means you could make a horrible ugly mess or you can make a system where these different types of knowledge all interpenetrate and synergize with each other beautifully right so you so the so the hypergraph can contain programs yeah it can contain programs although it can in the current version it is a very inefficient way to guide the execution of programs which is one thing that we are aiming to resolve with our our rewrite of the of the system now so what to you is the most beautiful aspect of open Cog just you personally some aspect that uh captivates your imagination from beauty or power uh yeah what what fascinates me is finding a common representation that underlies abstract declarative knowledge and sensory knowledge and movement knowledge and and procedural knowledge and episodic knowledge finding the right level of representation where all these types of knowledge are stored in a sort of universal and interconvertible yet practically manipulable way right so that that that that's to me to me that's the core because once you've done that then the different learning algorithms can help each other out like what you want is if you have a logic engine that helps with declarative knowledge and you have a deep neural net that gathers perceptual knowledge and you have say an evolutionary Learning System that learns procedures you want these to not only interact on the level of sharing results and passing inputs and outputs to each other you want the logic engine when it gets stuck to be able to share its intermediate state with the neural net and with the evolutionary learning algorithm so so that they can help each other out of of bottlenecks and help each other solve combinatorial explosions by intervening inside each other's cognitive processes but that can only be done if the intermediate state of a logic engine The evolutionary learning engine and a deep neural net are represented in in the same form and that's what we figured out how to do by putting the right type system on top of this weighted labeled hypergraph so is there can you maybe elaborate on what that what are the different characteristics of a type system that that can uh coexist uh amongst all these different kinds of knowledge that needs to be represented and is I mean like is it hierarchical um just any kind of insights you can give on that kind of type system yeah yeah so this this this gets very nitty-gritty and and mathematical of course but what one key part is switching from predicate logic to term logic what is predicate logic what is term logic logic so term logic was invented by Aristotle or at least that's the the oldest oldest recollection we we we we have we have of it but term logic breaks down basic logic into basically simple links between nodes like a inheritance link between between node a and and node B so in term Logic the basic deduction operation is a implies b b implies C therefore a implies C whereas in predicate logic the basic operation is modus ponents like a a implies B therefore B so there're there it's a slightly different way of breaking down logic but by breaking down logic into term logic you get a nice way of breaking logic down into into into nodes and links so your Concepts can can become nodes The Logical relations become links and so then inference is like so if this link is a implies B this link is B implies C then deduction builds a link a implies C and and your problemistic algorithm can assign assign a certain weight there now you may also have like a heavy and neural link from a to c which is the degree to which thinking the degree to which a being the focus of attention should make B the focus of attention right so you could have then a neural link and and you could you could have a symbolic like logical inheritance Link in your term logic and they have separate meaning but they they could be used to to guide each other as well like if if there's a large amount of neural weight on the link between A and B that may direct your logic engine to think about well what is the relation are they similar is is there an inheritance relation are they s are they similar in some context on the other hand if there's a logical relation between A and B that may want that may direct your neural component to think well when I'm thinking about a should I be directing some attention to be also because there's a logical relation so in terms of logic there's a lot of thought that went into how do you break down logic relations including basic sort of propositional logic relations as Aristotelian term logic deals with and then quantifier logic relations also how do you break those down elegantly in into a hyper graph because you I mean you can boil logic Expressions into a graph in many different ways many of them are very ugly right right we we tried to find elegant ways of sort of hierarchically breaking down complex logic expression in into no into nodes and links so so that if you have say different nodes representing you know Ben AI Lex interview or whatever the logic relations between those things are compact in in the in the node and Link representation so that when you have a neural net acting on those same nodes and links the neural net and the logic engine can can sort of inter interoperate with each other and also interpretable by humans is that is that an important that's tough in simple cases it's interpretable by humans but honestly you know I would say logic systems give more potential for yeah transparency and comprehensibility than neuron net systems but you still have to work at it because I mean if if if I show you a predicate logic proposition with like 500 nested Universal and existential quantifiers and 217 variables that's no more comprehensible than the weight Matrix of a neural network right so the I'd say the logic Expressions that an AI learns from its experience are mostly totally opaque to human beings and maybe even harder to understand than they're on that because I mean when you have multiple nested quantifier bindings it's a very high level of abstraction there is a difference though in that within logic it's a little more straightforward to pose the problem of like normalize this and boil this down to a certain form I mean you can do that in neural Nets too like you can distill a neural net to a simpler form but that's more often done to make a neural net that'll run on an embedded device or something it's it's harder to distill a net to a comprehensible form than it is to simplify logic expression to a comprehensible form but but it doesn't come for free like what's what what's in the ai's mind is is incomprehensible to to a human unless you do some special work to make it comprehensible so on the on the procedural side there's some different and sort of interesting Voodoo there I mean if if you're familiar in computer science there's something called the curry Howard correspondence which is a onetoone mapping between proofs and programs so every program can be mapped into a proof every proof can be mapped into a program you can model this using category Theory and a bunch of a bunch of of of nice math but we want to make that practical right so that so that if you if you have an executive program that like Mo moves a robot's arm or figures out in what order to say things in a dialogue that's a procedure represented in opencog hypergraph but if you want to reason on how to how to improve that procedure you need to map that procedure into logic using Curry Howard the isomorphism so then the logic the logic engine can reason about how to improve that procedure and then map that back into the procedural representation that is efficient for execution so again that comes down to not just can you make your procedure into a bunch of nodes and links because I mean that can be done trivially a a C++ compiler has nodes and links inside it can you boil down your procedure into a bunch of nodes and links in a way that's like hierarchically decomposed and simple enough you can reason about yeah yeah that given the resource constraints at hand you can map it back in forth to your to your term logic like fast enough and without having a bloated logic expression right so there's just a lot of there's a lot of nitty-gritty particulars there but I'm I'm by the same to and if you if you ask a chip designer like how do you make the Intel i7 chip so good right there's a there's a long list of of technical answers there which which will take take a while to go through right and this has been Decades of work I mean the the first AI system of this nature I tried to build was called Web mind in the mid1 1990s and we had a big graph a big graph operating in Ram implemented with Java 1.1 which was a terrible terrible implementation idea and then each each node had its own processing so like that there the core Loop looped through all nodes in the network and that each node enact what it what its little thing was doing and we had logic and neural Nets in there but and evolutionary learning but we hadn't done enough of the math to get them to operate together very cleanly so it was really it was quite a horrible mess so as as well as shift doing an implementation where the graph is its own object and the agents are separately scheduled we've also done a lot of work on how do you represent programs how do you represent procedures you know how do you represent genotypes for evolution in a way that the interoperability between the different types of learning associated with these different types of knowledge actually works and that's been quite difficult it's taken decades and it's totally off to the side of what the commercial mainstream of the of the AI I field is doing which isn't thinking about representation at all really although you could see like in the DNC they had to think a little bit about how do you make representation of a map in this memory Matrix work together with a representation needed for say visual pattern recognition in the hierarchical neural network but I would say we have taken that direction of taking the types of knowledge you need for different types of learning like declarative procedural attentional and how do you make these types of knowledge represent in a way that allows cross learning across these different types of memory we've been prototyping and experimenting with this within opencog and before that web mine since the mid mid 1990s now disappointingly to all of us this has not yet been cashed out in an A in an AGI system right I mean we've used this system within our consult Consulting business so we've built natural language processing and robot control and financial analysis we've built a bunch of sort of vertical Market specific proprietary AI projects they use opencog on on the back end but we we haven't that's not the AGI goal right that's that's it's interesting but it's not the AGI goal so now what what we're looking at with our rebuilded the system 2.0 yeah we're also calling it true AGI so we're not quite sure what the what what the name what the name is yet that we we made a website for 2 ai. but we we haven't put anything on there yet so we may come up with an an even even better name but it's kind of like the real AI starting point for your a but I like true better because true has like you can be true-hearted right you can be true to your girlfriend so true true has true has a number and it also has logic in it right because logic is is a key so yeah with with with the with the true AGI system we're sticking with the same basic architecture but we're we're we're trying to build on what we've learned one thing we've learned is that you know we need type checking among dependent types to be much faster and among probalistic dependent types to be much faster so as it is now you can have complex Types on the nodes and links but if you want to put like if you want types to be first class citizens so that you can have the types can be variables and then and then you do type checking among complex higher order types you can do that in the system now but it's very slow this is stuff like it's done in in Cutting Edge program languages like like agda or something these obscure research languages on the other hand we've been doing a lot time together deep neural Nets with symbolic learning so we did a project for Cisco for example which was on this was Street Scene analysis but they had deep neural models for a bunch of cameras watching Street Scenes but they trained to different model for each camera because they couldn't get the transfer learing to work between camera a and Camera B so we took what came out of all the deeper models for the different cameras we fed it into an opencog symbolic representation then we did some pattern Mining and some reasoning on what came out of all the different cameras within the symbolic graph and that worked well for that application I mean Yugo latapi from Cisco gave a talk touching on that at last year's AGI conference it was in Shenzhen on the other hand we learned from there it was kind of clunky to get the Deep neural models to work well with the symbolic system because we were using torch and torch keeps uh a sort of State computation graph but you needed like real time access to that computation graph within our hyper graph and we we we certainly did it Alexa poov who leads our St Petersburg team wrote a great paper on cognitive modules in opencog explaining sort of how do you deal with the torch compute graph inside opencog but in the end we realized like that just hadn't been one of our design thoughts when we when we built opencog right so between wanting really fast dependent type checking and wanting much more efficient interoperation between the computation graphs of deep neural net Frameworks and opencog hypergraph and adding on top of that wanting to more effectively run an opencog hypergraph distributed across Ram in 10,000 machines which is we're doing dozens of machines now but it's just not we we we didn't architect it with that sort of modern scalability in mind so these performance requirements are what have driven us to want to to rearchitecturing with the current infrastructure that was you know built in the phase 2001 to 2008 which is which is is is hard is hardly shocking right so well I mean the three things you mentioned are really interesting so what do you think about in terms of interoperability uh communicating with the computational graph of Neal networks what do you think about the representations that neural networks form um they're bad but there's many ways that you could that you could deal with that so I've been wrestling with this a lot in some work on on supervised grammar induction and I have a simple paper on that that I'll give it the next a AGI conference the online portion of which is next week actually so what is grammar induction so this isn't AGI either but it it's sort of on the verge between nari and AGI or something unsupervised grammar induction is the problem throw your AI system a huge body of text and have it learn the grammar of the language that produced that text so you're you're not giving it labeled examples so you're not giving it like a thousand sentences where the parses were marked up by graduate students so it's just got to infer the grammar from from from the text it's like it's like the Rosetta Stone but worse right because you only have the one language yeah and you have to figure out what what is the grammar so that's not really AGI because I mean the the way a human learns language is not that right I mean we we learn from language that's used in context so it's a social embodied thing we see we see how a given is grounded in in observation there's an interactive element I guess to yeah yeah on the other hand so I'm I'm more interested in that I'm more interested in making an AGI system learn language from its social and embodied experience on the other hand that's also more of a pain to do and that that would lead us into Hansen Robotics and their robotics work I've done which we'll talk about in a few minutes but just as an intellectual exercise as a learning exercise trying to learn grammar from a corpus is very very interesting right and and that's been a field in AI for a long time no one can do it very well so we've been looking at Transformer neural networks and tree Transformers which are amazing these came out of uh of Google Google brain actually and actually on that team was Lucas Kaiser who used to work for me in in one the period 200 5 through 8 through 8 or something so it's been fun to see my former sort of AGI employee disperse and do all these amazing things way too many sucked into Google actually well yeah anyway we'll talk about that too Lucas Kaiser and a bunch of these guys they they create Transformer networks that classic paper like attention is all you need and all these things following on from that so we're looking at Transformer networks and like these are able to I mean this is what underlies gpt2 and gpt3 and so on which are very very cool and have absolutely no cognitive understanding of any of the Texs are at like they're they're very intell they're very intelligent idiots right so uh sorry to take but a small bring us back but do you think gpt3 understands no not all it understands nothing he's a complete idiot but brilliant idiot you don't think GPT uh 20 will understand langage no no no AB size is not going to buy you understanding any more than a faster car is going to get you to Mars yeah okay it's a completely different kind of thing I mean these networks are very cool and as an entrepreneur I can see many highly valuable uses for them and as as an as an artist I I love them right so I mean I I we we're using our own neurom model which is along those lines to control the Philip K dick robot now and it's amazing to like train train a neurom model on the robot Philip K dick and see it come up with like craze stoned philosopher pronouncements very much like what Philip kadik might have said right like that so these models are are are super cool and I'm I'm working with Hansen robotics now on using a similar but more sopade one for Sophia which which we we we have we haven't launch launched yet but so I think it's cool but no these but it's not understanding these are recognizing a large number of shallow patterns that they're not they're not forming an abstract representation and that's the point I was coming to when we're looking at grammar induction we tried to mine patterns out of the structure of the Transformer Network and you can but the patterns aren't what you want they're they're nasty so I mean you if you do supervised learning if you look at sentences where you know the correct parts of a sentence you can learn a matrix that Maps between the internal representation of the Transformer and the parts of the sentence and so then you can actually train something that will output the sentence parse from the Transformer Network's internal State and we we did this I think uh Christopher Manning some some some others have now done this also but I mean what you get is that the representation is horribly ugly and is scouted all over the network and doesn't look like the rules of grammar that you know are the right rules of grammar right it's kind of ugly so what what we're actually doing is we're using a symbolic grammar learning algorithm but we're using the Transformer neural network as a sentence probability Oracle so like when when you if you have a rule of grammar and you wen't sure if it's a correct rule of grammar or not you can generate a bunch of sentences using that rule of grammar and a bunch of sentences violating that rule of grammar and you can see the the Transformer model doesn't think the sentences obeying the rule of grammar are more probable than the Sens is disobeying the rule of grammar so in that way you can use the neural model as a sense probability Oracle to guide guide a symbolic grammar learning process and that's to work better than trying to milk the grammar out of the neural network that doesn't have it in there so I think the thing is these neural Nets are not getting a semantically meaningful representation internally by and large so one line of research is to try to get them to do that and in infog gam was trying to do that so like if if you look back like two years ago there was all these papers on like Ed Edward this probalistic programming neural NET Framework that Google had which came out of infog so the the idea there was like you you could train an infogan neural net model which is a generative associative Network to recognize and generate faces and the model would automatically learn a variable for how long the nose is and automatically learn a variable for how wide the eyes are or or how big the lips are or something right so it automatically learn the the these variables which have a semantic meaning so that that was a rare case where a neuronet trained with a fairly standard Gan method was able to actually learn the semantic representation so so for many years many of us tried to take that the next step and get a Gant type neural network that that would have not just a list of semantic latent variables but would have say a baset of semantic latent variables with dependencies between them the whole programming framework Edward was was was made for that I mean no one got to work right and it could you think it's possible yeah do you think I don't I don't know it might be that back propagation just won't work for it because the gradients are too screwed up maybe you could get to work using CES or some like floating Point evolutionary algorithm right we tried we didn't get it to work eventually we just paused that rather than gave it up we paused that and said well okay let's let's try more innovative ways to learn implic to learn what are the representations implicit in that Network without trying to make it grow in inside that Network and I I described how we're doing that in language you can do similar things in Vision right so use it as an oracle yeah yeah yeah so you can that's one way is you use a structure learning algorithm which is symbolic and and and then you use the the Deep neural net as an oracle to guide the structure learning algorithm the other way to do it is like infog gam was trying to do and try to tweak the neural network to have the symbolic representation inside it I I tend to think what the brain is doing is more like using the Deep neural net type thing as an oracle like I think the the visual cortex or the cerebellum are probably learning a non semantically meaningful opaque Tangled representation and then when they interface with the more cognitive parts of the cortex the cortex is sort of using those as an Oracle and learning the abstract representation so if you do Sports say take for example serving in tennis right I mean my tennis serve is okay not not great but I learned it by trial and error right and I mean I learned music by trial Nar 2 I I just sit down and play but then if you're an athlete which I'm not a good athlete I mean then you'll watch videos of yourself serving and your coach will help you think about what you're doing and you'll then form a declarative representation but your cerebellum maybe didn't have a declarative representation same way with music like I will hear something in my head I'll sit down and play the thing like I heard it and then then I will try to study what my fingers did to see like what what did you just play like how how did you do that right because if you're composing you may want to see how you did it and then declaratively morph that in some way that your fingers wouldn't wouldn't think of right but the the physiological movement may come out of some opaque like cbella rein rein reinforcement learned thing right and so that's I think trying to milk the structure of a neuronet by treating as an oracle maybe more like how your declarative mind postprocesses what what what your your visual or or or motor cortex I mean I mean in Vision it's the same way like you can recognize beautiful art much better than you can say why you think that piece of art is beautiful but if you're trained as an art critic you do learn to say why and some of it's but some of it isn't right some of it is learning to map sensory knowledge into declarative and and and lingu and linguistic knowledge yet without necessarily making the sensory system itself use use a transparent and easily communicable representation yeah that's fascinating to think of NE networks as like dumb question anwers that you can just milk to build up uh a knowledge base and there could be multiple networks I suppose from different uh yeah yeah so I think if if a group like deep mind or open AI were to build AGI and I think Deep Mind mind is like a thousand times more likely from from from from what I could tell but cuz they've hired a lot of people with broad Minds in many different approaches and and angles on on AGI worse open AI is also awesome but I see them as more of like a pure deep reinforcement learning shop time I got you there's a lot of there you're right there's um I mean there's so much interdisciplinary work at Deep Mind like neuroscience together with Google brain which granted they're not working that closely together now but you know my oldest son zarra is doing his PhD in machine learning applied to automated theorem proving in in Prague under Joseph Urban so the the first paper deep math which applied deep neural Nets to guide theor improving without of Google brain I mean by now by now the the automated theorem proving Community is gone way way way beyond anything go Google was doing but still yeah that but anyway if that Community was going to make an AGI probably one way they would do it was you know take 25 different neural modules architected in different ways maybe resembling different parts of the brain like a Bas basil ganglia model cerebellum Model A Thal palus model few few hippocampus models number of different models representing parts of the cortex right take all of these and then wire them together to to to co- Trin and like learn them together like that that would be an approach to creating an an an AGI one could Implement something like that efficiently on top of our our true AGI like opencog 2.0 system once it exists although obviously Google has has their own highly efficient implementation architecture so I think that's a decent way to build AGI I was very interested in that in the mid90s but I mean the knowledge about how the brain works sort of pissed me off like was it wasn't there yet like you know in the hippocampus you have these concept neurons like the so-called grandmother neuron which everyone laughed at it it's actually there like I have some Lex Friedman neurons that fire differentially when I when I see you and not when I see any other person right yeah so how how do these Lex Friedman neurons how do they coordinate with the distributed representation of Lex Freedman I have in my cortex right there's some back and forth between cortex and hippocampus that lets these discreet symbolic representations in hippoc campus correlate and cooperate with the distributed representations in cortex this probably has to do with how the brain does its version of abstraction and quantifier logic right like you can have a single neuron hippocampus that that activates a whole distributed activation pattern in in cortex well this this maybe how the brain does like symbolization and abstraction as in in functional programming or something but we can't measure it like we we we don't have enough electrodes stuck between the the cortex and the and the hippoc campus and any known experiment to measure it so I got I got frustrated with that direction not cuz it's impossible because we just don't understand enough yet we don't of course it's a valid research direction and you can try to understand more and more and we are measuring more and more about what what happens in the brain now than ever before so it's it's quite interesting on the other hand I sort of got more of an engineering mindset about AGI I'm like well okay we don't know how the brain works that well we don't know birds fly that well yet yet either we have no idea how a hummingbird flies in terms of the the aerodynamics of it on the other hand we know basic principles of like flapping and and and pushing the air down and we know the basic principles of how the different parts of the brain work so let's take those basic principles and engineer something that embodies those Bas basic principles but you know is welld designed for the hardware that that we have on on hand right right now so do you think we can create AGI before we understand how the brains I think I think that's probably that's probably what will happen and maybe the AGI will help us do better brain Imaging that will then let us build artificial humans which is very very interesting to us because we are humans right I mean building artificial humans is is super worthwhile I I just think it's probably not the shortest path to AGI so it's fascinating idea that we would build AGI to help us understand ourselves uh you know a lot of people ask me if uh you know the young people interested in doing artificial intelligence they look at sort of uh you know doing graduate level even undergrads but graduate level research uh they see what the artificial intelligence Community stands now it's not really AGI type research for the most part yeah so the the natural question they ask is what advice would you give I mean maybe I could ask uh if people were interested in working on uh open Cog or in some kind of direct or indirect connection to open Cog or AGI research what would you recommend opencog first of all is open- source project there's a there's a Google group uh dis discussion list there's a GitHub repository so if anyone's interested in lending a hand with that aspect of of of AGI introduce yourself on the open opencog email list and uh there's a slack as well I mean we're we're certainly interested to have uh you know in inputs into our redesign process for a new version of opencog but but also we're doing a lot of very interesting research I mean we're working on on data analysis for covid clinical trials we're working with Hansen robotics we're doing a lot of cool things with the current version of of of opencog now so there there's certainly opportunity to jump into opencog or or various other open- source a AGI oriented projects so would you say there's like Masters and phg thesises in there plenty yeah plenty of of course I mean the challenge is to find a supervisor who wants to Foster that that that sort of research but it's way easier than it was when I got my PhD right so okay great we talked about open Cog which is kind of uh one the software framework but also the actual uh attempt to build an AGI system and then there is this exciting idea of Singularity net so maybe can you say first what is singularity net sure sure Singularity net is a platform for realizing a decentralized network of of artificial intelligences so Marvin Minsky the AI Pioneer who who I knew a little bit he had the idea of a society of Minds like you should achieve an AI not by writing one algorithm or one program but you should put a bunch of different AIS out there and the different AIS will interact with each other each playing their own role and then the totality of the Society of AIS would would be the thing that displayed the human level intelligence and I had when he was alive I had many debates with with Marvin about about this idea and he I think uh he really thought the mind was more like a society than than I do like I think I think you could have a a mind that was as disorganized as a human society but I think a humanlike mind has a bit more central control than that actually like I mean we have this Thalamus and the medulla and lyic system we we have a sort of top- down control system that guides much of much of what we do more so than than a society does so I think he stretched that metaphor a little too far but I but I also think there's there's something interesting there and so in the in the '90s when I started my first sort of non-academic AI project web mind which was an AI startup in New York in the Silicon alley area in in the late 90s what I was aiming to do there was make a distributed Society of AIS the different parts of which would live on different computers all around the world and each one would do its own thinking about the data local to it but they would all share information with each other and Outsource work with each other and cooperate and the intelligence would be in in in the whole Collective and I organized a conference together with Francis hean at free University of Brussels in 2001 which was the global brain zero conference and we're we're planning the next version of the global brain one conference at the Free University of Brussels for next year 2021 so 20 20 years after then we maybe we can have the next one 10 years after that like exponentially faster until the singularity comes right uh the timing is right yeah yeah yeah exactly so the yeah the idea with the global brain was you know maybe the AI won't just be in a program on one guy's computer but the AI will be you know in the internet as a whole with the cooperation of different AI modules living in different places so one of the issues you face when architecting a system like that is you know how how is the whole thing controlled do you have like a centralized control unit that pulls the puppet strings of all the different modules there or do you have a fundamentally decentralized Network where the Society of of AIS is controlled in some democratic and self-organized Way by all the AIS in in that Society right and Francis and I had different view of many things but we both we both wanted to make like a global Society of AI Minds with a decentralized or organ organization mode now the main difference was he wanted the individual AIS to be all incredibly simple and all the intelligence to be on the collective level whereas I thought that was cool but I thought a more practical way to do it might be if some of the agents in the Society of Minds were fairly generally intelligent on their own so like you could have a bunch of open cogs out there and a bunch of simpler learning systems and then these are are all cooperating and coordinating together soort of like in the brain okay the brain as a whole is the general intelligence but some parts of the cortex you could say have a fair rid of general intelligence on their own whereas say parts of the cerebellum or lyic system have very little general intelligence on their own and they're contributing to general intelligence you know by way of their connectivity to to other other modules do you see instantiations of the same kind of you know maybe different versions of open Cog but also just the same version of open Cog and maybe many instantiations of it as part as that's what David and H and I want to do with many Sophia and other robots yeah yeah each one has its own individual mind living on the server but there's also a collective intelligence infusing them and a part of the mind living on the edge in each robot right yeah so so the the thing is at that time as well as webmind being implemented in Java 1.1 as like a massive distributed system yeah that you know the there blockchain wasn't there yet so how how them do this decentralized control you know we sort of knew it we knew about distributed systems we knew about encryption so I mean we had the key principles of what underlies blockchain now but I mean we didn't put it together in the way that's it's been done now so when when vitalic butterin and colleagues came out with aium blockchain you know many many year years later like 2013 or something then I was like well this is interesting like this is solidity scripting language it's kind of dorky in a way and I don't see why you need a turn complete language for this purpose but on the other hand this is like the first time I could sit down and start to like script infrastructure for decentralized control of the AIS in a society of Minds in a tractable way like you could hack the Bitcoin cbase but it's it's really annoying whereas sady is is ethereum scripting language is just nicer and and easier to use I'm very annoyed with it by this point but like Java I mean these languages are amazing when when they first come out so then I came up with the idea that turned into Singularity that okay let's let's make a decentralized agent system where a bunch of different AIS you know wrapped up in say different Docker containers or lxc containers different AIS can each of them have their own identity on the blockchain and the coordination of this community of AIS has no Central controller no dictator right the and there's no Central repository of information the coordination of the Society of Minds is done entirely by the decentralized network in a in a decentralized way by the by the algorithms right because you know the model of Bitcoin is in math We Trust right and so that that that's what you need you need the Society of Minds to trust only in math not trust only in one one centralized server so the AI systems themselves are outside of the blockchain but then the communication at the moment yeah yeah we I would have loved to put the ai's operations on chain in some sense but in ethereum it's just too slow you you you you you can't you can't do it somehow it's the basic communication between AI systems that's uh yeah yeah so basically an AI is just some software in singular an AI is just some software process living in a container M and there's input and output there's a proxy that lives in that container along with the AI that handles the interaction with the rest of of of Singularity net and then when one AI wants to contribute with another one in the network they set up a number of channels and the setup those channels uses the ethereum blockchain but once the channels are set up then data flows along those channels without without having to be having to be on the blockchain all that goes on the blockchain is the fact that some data went along that channel so you can do so there's not a shared knowledge uh it's well the the identity of each agent is on the blockchain right on the ethereum blockchain if one agent rates the reputation of another agent that goes on the blockchain and agents can publish what apis they will fulfill on the on the blockchain but the actual data for AI and the results AI is not on the blockch do you think it could be do you think it should be um in some cases it should be in some cases maybe it shouldn't be but I mean I I I think that uh so I'll give you an example using ethereum you can't do it using now there's more modern and faster blockchains where you could you could start to do that in in in in in some cases two years ago that was less so it's a very rapidly evolving ecosystem so like one example maybe you can comment on uh something I worked a lot on is autonomous vehicles you can see each individual vehicle as a AI system and uh you can see vehicles from uh Tesla for example and then uh Ford and GM and all these has also like larger I mean they all are running the same kind of system on each sets of vehicles so it's individual AI systems and individual vehicles but it's all different station is the same AI system within the same company so you know you can Envision a situation where all of those AI systems are put on Singularity net right yeah and how how do you see that happening and what would be the benefit and could they share data I gu I guess one of the biggest things is that the power there is in a decentralized control but uh the benefit would have been is is really nice if they can somehow share the knowledge in an open way if they choose to yeah yeah yeah those are those are all all quite good points so I I think the the benefit from being on the on the decentralized network as we envision it is that we want the AIS and the network to be Outsourcing work to each other and making a API calls to to each other frequently I got you so the real benefit would be if that AI wanted to Outsource some cognitive processing or data processing or data pre-processing whatever to some other AIS in the network which specialize in in something different and this this really requires a different way of thinking about AI software development right so just like object-oriented programming was different than imperative programming and now object or programmers all use these Frameworks to do things rather than just libraries even you know shifting to agent-based programming where your AI agent is asking other like live realtime evolving agents for feedback in what they're doing that's a different way of thinking I mean it's it's not a new one there was loads of papers on agent-based programming in the 80s and onward but if you're willing to shift to an agent-based model of development then you can put less and less in your AI and rely more and more on interactive calls to other AIS running in in the network and of course that's not fully manifested yet because although we've rolled out a nice working version of singular unet platform there's there's only 5200 AIS running in there now there's not tens of thousands of of AI so we don't have the critical mass for the whole Society of Mind to be doing doing what what we want what we want the magic really happens when it's just a huge number of Agents yeah yeah exact exactly in terms of data we're partnering closely with another blockchain project called ocean protocol and ocean protocol that's uh the project of Trent Miki who developed Big Chain DB which is a blockchainbased database so ocean protocol is basically blockchainbased big data and nams at make making it efficient for for different AI processes or or statistical processes or whatever to to share L large large data sets or one process can send a clone of itself to work on the other guy's data set and send results back and so forth so by getting ocean and and you know you have data lake so this is the data ocean right so by getting ocean and Singularity net to to interoperate we're aiming aiming to take into account of of the Big Data aspect also but it's it's quite challenging because to build this whole decentralized blockchainbased infrastructure I mean your competitors are like Google Microsoft Alibaba and Amazon which have so much money to put behind their centralized infrastructures plus they're solving simpler algorithmic problems because making it centralized in some ways is is is easier right so they're they're very major computer science challenges and I think what what you saw with the whole icoo boom in in the blockchain and cryptocurrency world is a lot of young hackers who are hacking Bitcoin or ethereum and they see well why don't we make this decentralized on blockchain then after they raise some money through an Ico they realize how hard it is it's like like actually we're wrestling with incredibly hard computer science and software engineering and distributed systems problems which are can be solved but they're just very difficult to solve and in some cases the individuals who started those projects were not were not well equipped to to actually solve the problems that they wanted so you think would you say that's the main bottleneck if uh if you look at the future of currency uh you know the question is currency the main B bck is politics like it's government and the bands of armed thugs that will shoot you if you bypass their their currency restrictions that's right so like your sense is that versus the technical challenges because you kind of just suggested the technical challenges are quite high as well I mean for making a distributed money you could do that on alar end right now I mean so that while ethereum is too slow there's algorand and there's a few other more modern more scalable blockchains it would work fine for a a decentralized global global currency right so I think there were technical bot next to that two years ago and maybe ethereum 2.0 will be as fast as Al I I don't know that's not that's not F fully written yet right so I think the obstacle to currency being put on the blockchain is that is the other currency will be on the blockchain it'll just be on the blockchain in a way that enforces centralized control and government hedge money rather than otherwise like the ER andb will probably be the first Global the first currency on the blockchain the E Ruble maybe next they're already e Ruble yeah yeah yeah I mean the point that's hilarious digital currency you know makes total sense but they would rather do it in the way that Putin and xiin ping have have have access to the the global keys for everything right then so and then the analogy to that in terms of Singularity net I mean there's Echo I I think you've mentioned before that Linux gives you hope and AI is not as heavily regulated as money right not yet right not yet oh that's a lot slipperier than money too right I mean money is is easier to regulate because it it's kind of easier to to Define whereas AI is it's almost everywhere inside everything where's the boundary between Ai and software right I mean if you're going to regulate AI there's no IQ test for Every Hardware device that has a learning algorithm you're going to be putting like honic regulation on all software and I don't rule out that that sof yeah but how do you tell if software is adaptive and what every software is going to be adaptive I mean or maybe they they maybe uh the you know maybe we're living in the Golden Age of Open Source that will not that will not always be open maybe uh it'll become centralized control of software by government it it is entirely possible and part of what I think we're doing with things like Singularity protocol is creating a tool set that can be used to counteract that sort of thing say a similar thing about Mesh networking right plays a minor role now the ability to access Internet like directly phone to phone on the other hand if your government starts trying to control your use of the internet suddenly having mesh working Mesh networking there can be very convenient right and so right now something like a decentralized blockchainbased a AGI framework or or narrow AI framework it's cool it's it's nice to have on the other hand if government start trying to T down on my AI interoperating with someone's AI in in Russia or somewhere right then suddenly having a decentralized protocol that nobody owns or controls becomes an extremely valuable part of the of the tool set and you know we've we've put that out there now it's not perfect but it but it it it operates and you know it's pretty blockchain agnostic so we're talking to algorand about making part of single run run on algorand my good friend TWY CBA has a cool blockchain project called TOA which is a blockchain without a distributed Ledger it's like a whole other architecture so there so there there there's a lot of more advanced things you can do in the blockchain world Singularity net could be ported and to a whole bunch of it could be made multi-chain and port to a whole bunch of different blockchains and there there's a lot of potential and a lot of importance to putting this kind of tool set out there if you compare to opencog what you could see is opencog allows tight integration of a few AI algorithms that share the same knowledge store in real time in in Ram right Singularity net allows loose integration of multiple different AIS they they can share knowledge but they're mostly not going to be sharing knowledge in in Ram in RAM on on on the same machine and I think what we're going to have is a network of network of networks right like I mean you you have the knowledge graph in inside inside the the opencog system and then you you have a network of machines inside a distributed opencog mind but then that opencog will interface with other AIS doing deep neural Nets or or custom biology data analysis or what whatever they're doing in Singularity net which is a looser integration of different AI some of which may be may be their their their own networks right and I think at a very loose analogy you could see that in the human body like the brain has regions like cortex or hippocampus which tightly interconnect like cortical columns with it within the cortex for example then there's looser connection within the different loes of the brain and then the brain interconnects with the endocrine system and different parts of the of the body even even more Loosely then your body interacts even more Loosely with the other other people that you talk to so you often have networks within networks within networks with progressively looser coupling as as as you get get higher up in that hierarchy I mean you have that in biology you have that in in the internet as a just networking medium and I think I think that's what we're going to have in the network of of software processes leading to to AGI that's a beautiful way to see the world uh again the same similar question is with open Cog if somebody wanted to build an AI system and plug into the singularity net what would you recommend like how so that's much easier I mean o Open Cog is still a research system so it takes some expertise to in sometime we have tutorials but it's it's somewhat cognitively labor intensive to get up to speed on on on opencog and I mean what's one of the things we hope to change with the true AGI opencog 2.0 version is just make make the learning curve more similar to tensor flow or torch or something is right now open Cog is amazingly powerful but but not simple to not simple to deal with on the other hand Singularity net you know as a as a open platform was developed a little more with usability in mind although the blockchain is is still kind of a pain so I mean I mean if you're a command line guy there's a command line interface it's quite easy to you know take na AI that has an API and lives in a Docker container and put it online anywhere and then it joins the global Singularity net and Anyone who puts a request for services out into the singularity net the peer-to-peer Discovery mechanism will find your your AI and if it does what what was asked it will it can then start a conversation with your AI about whether it wants to ask your AI to do something for it how much it would cost and so on so that that that's that's fairly simple if you wrote an AI and want it listed on Like official Singularity net Marketplace which is which is on our website then we we have a a publisher portal and then there's a kyc process to go through because then we have some legal liability for what goes on on that website so the in a way that's been in education too there's sort of two layers like there's the open decentralized protocol and there's the market yeah anyone can use the open decentralized protocol so say some developers from Iran and there's brilliant guys in University of isvan and Tran they can put their stuff on Singularity net protocol and just like they can put something on the internet right I don't control it but if we're going to list something on the singularity net Marketplace and put a little picture and a link to it yeah then if I put some Iranian AI genius's code on there then Donald Trump can send a bunch of Jack booted thugs to my house to to arrest me for doing business with Iran right so so I mean we we already see in some ways the value of having a decentralized protocol because what I hope is that someone in Iran will put online an Iranian Singularity net marketplace right which you can pay in a cryptographic token which is not owned by any country and then if you're in like Congo or somewhere that doesn't have any problem with Iran you can subcontract AI services that you find on on on on that marketplace right even though US citizens can't by by US law so right now that's kind of a point you know as as you alluded if if regulations go in the wrong direction it could become more of a major point but I think it also is the case that having these workarounds to regulations in place is a defense mechanism against those regulations being put into place and you could see that in the music industry right I mean Napster just happened and bit torrent just happened and now most people in my kids generation they're baffled by the idea of paying for music right I mean my dad pays for music but I mean yeah but because these decentralized mechanisms happened and then the regulations followed right and the regulations would be very different if they'd been put into place before there was Napster and bit Tor and so forth so in the same way we got to put AI out there in a decentralized vein and Big Data out there in a decentralized vein now so that the most advanced AI in the world is fundamentally decentralized and if that's the case that's just the reality The Regulators have to deal with and then as in the music case they're going to come up with regulations that sort of work with the with the decentralized reality beautiful you were the chief scientist of Hansen robotics uh you're still involved with Hansen robotics uh doing a lot of really interesting stuff there this is for people who don't know the company that created sopia the Robot can you tell me who who Sophia is I'd rather start by telling you who David Hansen is because it's David is the brilliant mind behind this Sophia robot and he remains so far he remains more interesting than his than his creation alth although she may be improving faster than he is actually I mean's yeah so yeah I met a good point I met David maybe 2007 or something at some futurist conference we were both speaking at and I could see we had a great great deal in common I mean we we're both kind of crazy but we also we we both had a passion for AGI and and and the singularity and we were both huge fans of the work of uh Philip KCK the the science fiction writer and I wanted to create benevolent AGI that that would uh you know create massively better life for all humans and all sensient beings including animals plants and superum beings and David he wanted exactly the same thing but he had a different idea of of how to do it he wanted to get computational compassion like he wanted to get machines that that would would love people and empathize with people and he thought the way to do that was to make a machine that could you know look people eye to eye face to face look at look at people and make people love the machine and the Machine loves the people back so I thought that was very different way of looking at it cuz I'm very math oriented and I'm just thinking like what is the abstract cognitive algorithm that will let the system you know internalize the complex patterns of human values blah blah blah whereas he's like look you in the face in the eye and love you right so so I we we we hit it off quite well and we talk to each other off and on then I moved to Hong Kong in 20 20 11 so I'd been I mean I've been I've been living all over the place I've been in Australia and New Zealand in my AC academic career then in in Las Vegas for a while was in New York in the late 90s starting my my entrepreneurial career was in DC for 9 years doing a bunch of US Government consulting stuff then moved to Hong Kong in in in 2011 mostly because I met a Chinese girl who I fell in love with we we we got married she's actually not from Hong Kong she's from mland China but we converge together in Hong Kong still married now have have a 2-year-old baby so went to Hong Kong to see about a girl I guess yeah pretty pretty pretty much yeah and on the other hand I started doing some cool research there with gou at Hong Kong poly Technic University I got involved with a project called idea using machine learning for stock and Futures prediction which was quite interesting and I also got to know something about the consumer electronics and Hardware manufacturer ecosystem in Shenzhen across the border which is like the only place in the world that makes sense to make complex consumer electronics at large scale and low cost it's just it's astounding the hardware ecosystem that you have in in in in South China like you us people here cannot imagine what it what what it's like so David was starting to explore that also I invited him to Hong Kong to give a talk at Hong Kong Pou and I introduced him in Hong Kong to some investors who were interested in his robots and he didn't have Sophia then he had a robot of Philip K dick our favorite science fiction writer he had a robot Einstein he had some little toy robots that looked like his his son Zeno so through the investors I connected him to he managed to get some funding to basically Port Hansen robotics to Hong Kong and when he first moved to Hong Kong I was working on AGI research and also on this uh machine learning trading project so I didn't get that tightly involved with with Hansen robotics but as as I hung out with David more and more as we were both there in the same place I started to get I started to think about what you could do to make his robots smarter than they were and so we started working together and for a few years I was Chief scientist and head of software at at Hansen robotics then when I got deeply into the blockchain side of things I I stepped back from that and co-founded Singularity net David Hansen was also one of the co-founders of of of singularity in that so part of our goal there had been to make the blockchainbased like Cloud mind platform for sopia and the other other other sopia would be just one of the robots in this uh ins Singularity net yeah yeah yeah EXA ex exactly Sophia many copies of the Sophia robot would would would be you know among the user interfaces to the globally distributed singular net Cloud mind and I mean David and I talked about that for quite a while before co-founding s Singularity by the way in his in his vision and your vision was uh was Sophia tightly coupled to a particular AI system or was the idea that you can plug you could just keep plugging in different AI systems within the I think David's David's View was always that sopia would be a platform much like say the pepper robot is is is a platform from SoftBank should be a platform with a set of nicely designed apis that anyone can use to experiment with their different AI algorithms on on on that platform and Singularity net of course fits right into that right because Singularity net it's an API Marketplace so anyone can put their AI on there opencog is a little bit different I mean David likes it but I'd say it's my thing it's not his like David has a little more passion for biologically based approaches to AI than I do which which makes sense I mean he's really into human physiology and and biology's he's a character sculptor right yeah so yeah he he's interested in but he also worked a lot with rule-based and logic based AI systems too so yeah he's interested in not just Sophia but all the H and robots as a powerful social and emotional robotics platform and you know what I saw in sopia was a a way to you know get AI algorithms out there in front of a whole lot of different people in an emotionally compelling way and part of my thought was really kind of abstract connected to AGI ethics and you know many people are concerned AGI is is gonna enslave everybody or turn everybody into into computronium to to make extra hard drives for for for their their cognitive engine or whatever and you know emotionally I'm not driven to that sort of of paranoia I'm I'm really just an optimist by nature but intellectually I have to assign the nonzero probability to those sorts of nasty outcomes because if you're making something 10 times as smart as you how can you know what it's going to do there's an irreducible un uncertainty there just as my dog can't predict what I'm going to do tomorrow so it seemed to me that based on our current state of knowledge the best way to bias the agis we create toward benevolence would be to infuse them with love and compassion the way the way that we do our own children so you want to interact with AIS in the context of doing compassionate loving and benef icial things and in that way as your children will learn by doing compassionate beneficial loving things alongside you in that way the AI will learn in practice what it means to be compassionate beneficial and loving it will get a sort of ingrained intuitive sense of this which it can then abstract in in its own way as it gets more and more intelligent now David saw this the same way that's why he came up with the name Sophia which means which means wisdom so it seemed to me making these like beautiful loving robots to be rolled out for beneficial applications would be the perfect way to roll out early stage AGI systems so they can learn from people and not just learn factual knowledge but learn human human values and ethics from people while being their you know their home service robots their education assistants they're they're nursing robots so that that was the Grand Vision now if you've ever worked with robots the reality is is quite different right like the first principle is the robot is always broken work I mean I worked with robots in the 90s a bunch when you had to solder them together yourself and I'd put neural Nets doing reinforcement learning on like overturn solid Bowl type robots in in the 90s when I was a professor things of course Advanced a lot but but the principle still holds the principle of the robots always broken still holds yeah yeah so faced with reality of making Sophia do stuff many of my Robo AGI aspirations were temporarily cast aside and I mean there's just a practical problem of making this robot interact in a meaningful way because like you know you put nice computer vision on there but there's always glare and then or it you have a dialogue system but at the time I was there like no speech text algorithm could deal with Hong Kong Hong Kong people's English accents yeah so the the speech of text was always bad so the robot always sounded stupid yeah because it wasn't getting the right text right so I started to view that really as what what in software engineering you call a walking skeleton which is maybe the the wrong metaphor to use for Sophia or maybe the right one but I mean what a walking skeleton is in software development is if you're building a complex system how do you get started but one way is to First build part one well then build part two well then build part three well and so on another way is you make like a simple version of the whole system and put something in the place of every part the whole system will need so that you have a whole system that does something and then you work on improving each part in the context of that whole integrated system so that's what we did on a software level in Sophia we made like a walking skeleton Software System where so there's something that sees there's something that hears there's something that moves there's something that there's something that remembers there's something that learns you put a simple version of each thing in there and you connect them all together so that the system will will will do its thing so there's there's a lot of AI in there there's not any AGI in there I mean there's computer vision to recognize people's faces recognize when someone comes in the room and leaves try to recognize whether two people are together or not I mean the dialogue system it's a mix of like hand-coded rules with deep neural Nets that that come up with with with their with their own responses and there's some attempt to have a narrative structure right and sort of try to pull the conversation into something with a be beginning middle and end and this sort of story arc so it's I mean like if you look at the lobner prize and the the systems that beat the touring test currently they're heavily rule-based because uh like you had said narrative structure to create compelling conversations you currently new networks cannot do that well even with Google Mina um when you actually look at fullscale conversations it's just yeah this is the thing so we've been I've actually been running an experiment the last couple weeks taking Sophia's chatbot and then the Facebook's Transformer chatbot which they open the model we've had them chatting to each other for a number of weeks on the server just that's funny gen we're generating training data of what Sophia says in a wide variety of conversations but we can see compared to Sophia's current chatbot the Facebook deep neural chatbot comes up with a wider variety of fluent sounding sentences on the other hand it Rambles like mad the Sophia chatbot it's a little more repetitive in in the sentence structures it uses on the other hand it's able to keep like a conversation Arc over a much longer longer period right so there now you can probably surmount that using reformer and like using various deep neural architectures and to improve the way these Transformer models are trained but in the end neither one of them really understands what's going on and I mean that's the challenge I had with Sophia is if I were doing a robotics project aimed at AGI I would want to make like a robo toddler that was just learning about what it was seeing because then the language is grounded in the experience of the robot but what Sophia needs to do to be Sophia is talk about sports or or the weather or or robotics or the conference she's talking at like yeah she needs to be fluent talking about any damn thing in the world and she doesn't have grounding for for all for all those all those things so there's there's this just like I mean Google Mina and Facebook's chap I don't have grounding for what they're talking about about either so in in a way the need to speak fluently about things where there's no non-linguistic grounding pushes what you can do for Sophia in the short term a bit a bit away from uh from I mean it pushes you towards uh IBM Watson uh situation where you basically have to do heuristic and hardcode stuff and Rule based stuff I have to ask you about this okay so because uh you know in in part Sophia is like an uh is an art creation because it's beautiful uh it's she's beautiful because she inspires through our human nature of uh anthropomorphize things we immediately see an intelligent being there because David is a great sculptor is is great sculptor that's right so uh in fact if Sophia just had nothing inside her head said nothing if she just sat there we already prescribe some intelligence to there's a long selfie line in front of her after every talk that's right so it captivated the imagination of the um of many people I was going to say the world but yeah I mean a lot of people and uh billions of people which is amazing it's amazing right now of course uh many people have prescribed much greater prescribed essentially AGI type of capabilities to Sophia when they see her and of course um friendly French folk like uh Yan laon IM immediately see that of the people from the AI community and get really frustrated because uh it's understandable so what and then they criticize people like you who sit back and don't say anything about like basically allow the imagination of the world allow the world to continue being captivated uh so what what's your what's your sense of that kind of annoyance that the AI Community has well I I I think there's several parts to my reaction there first of all if I weren't involved with Hansen robach and didn't know David Hansen personally I probably would have been very annoyed initially at Sophia as well I mean I can understand the reaction I would have been like wait all these stupid people out there think this is an AGI but it's not an AGI but they're tricking people that this very cool robot is an AGI and now those of us you know trying to raise funding to build AGI you know people will think it's already there and and and already works right so I yeah on the other hand I think even if I weren't directly involved with it once I dug a little deeper into David and the robot and the intentions behind it I think I would have stopped being being pissed off whereas folks like Yan Lun have remained pissed off after their after their after their initial well their initial re his thing that's his thing yeah I think that in particular struck me as somewhat ironic because Yan Lun is working for Facebook which is using machine learning to program the brains of the people in the world toward vapid consumerism and political extremism so if if your ethics allows you to use machine learning in such a blatantly destructive way why would your ethics not allow you to use machine learning to make a lovable theatrical robot that draws some foolish people into it its theatrical illusion like if if if the if the push back had come from Yoshua Benjo I would have felt much more humbled by it because he's he's not using AI for blatant evil right on the other hand he also is a super nice guy and doesn't bother to go out there trashing other other people's work for no good reason right son Sha's fired but I get you I I mean that's I mean if if you're if you're gonna ask I'm I'm gonna answer but no for sure I think we'll go back and forth I'll talk to Yan again I would add on this though I mean David Hansen is an artist and he often speaks off the cuff and I have not agreed with everything that David has said or done regarding Sophia and David also was not agree with everything David has said her done about important point I mean d David David is an artistic uh Wild Man and that's that's that that's part of his charm that's that's part of his genius so certainly there have been conversations within Hansen Robotics and between me and David where I was like let's let's be more open about how this thing is working and I did have some influence in in nudging Hansen robotics to be more open about about how Sophia was working and and David wasn't especially opposed to this and you know he was actually quite right about it what he said was you can tell people exactly how it's working and they won't care they want to be drawn into the illusion and he was 100% 100% correct I'll tell you what yeah this wasn't Sophia this was Philip K dick but we did some actions between humans and Philip KCK robot in Austin Texas a few years back and in this case the Philip KCK was just teleoperated by another human in the other room so during the conversations we didn't tell people the robot was teleoperated we just said here have a conversation with Phil dick we're going to film you right and they had a great conversation with Phil K dick tell operated by my friend Stan buy after the conversation we brought the people in the back room to see Stefan who was controlling the the the the Philip K dick robot but they didn't believe it these people were like well yeah but I know I was talking to Phil like maybe Stefan was typing but the spirit of Phil was animating his mind while he was typing yeah so like even though they knew was a human in the loop even seeing the guy there they still believe that was Phil they were talking to a small part of me believes that they were right actually because our understand well we don't understand the universe right I mean there is a cosmic mind field that we're all embedded in that yields many strange synchronicities in in in in the world which is a topic we don't have time to go into too much here I mean there there's there's some nature there's something to this where uh our imagination about Sophia and people Yan Lon being frustrated about it is all part of this beautiful dance of creating artificial intelligence that's almost essential you see with Boston Dynamics I'm a huge fan of uh as well you know the kind of I mean these robots are very far from intelligent uh I I I played with her last one actually with the spot mini yeah very cool I mean it it reacts quite in a fluid and and flexible way right but we immediately ascribe the kind of intelligence we immediately ascribe AGI to them yeah yeah if you kick it and it falls down and goes ow you feel bad right you can't help it yeah and uh I mean that's that's that's uh part of uh that's going to be part of our journey in creating intelligence systems more and more and more and more like as uh as Sophia starts out with a walking skeleton as you add more and more intelligence I mean we're going to have to deal with this kind of idea absolutely and about Sophia I would say I mean first of all I have nothing against Yan L this is F this is nice guy if he if he wants to play the media media banter game I'm I'm I'm I'm I'm happy to he's a good researcher and and a good human being and I'd happily work with the guy but the other thing I was going to say is I have been explicit about how Sophia works and I've posted online and that what H+ magazine an online web Zine I mean I posted a moderately detailed article explaining like there are three software systems we've used inside sopia there's there's a timeline editor which is like a rule-based authoring system where she's really just being an outlet for what a human scripted there's a chatbot which has some rule-based and some neural aspects and then sometimes we've used opencog behind Sophia where there's more learning learning and reasoning and you know the funny thing is I can't always tell which system is operating here right I mean so when she whether she's really learning yeah or thinking or or just appears to be over half hour I could tell but over like 3 or 4 minutes of interaction I I so even having three systems that's already sufficiently complex where you can't really tell right away yeah the thing is even if you get up on stage and tell people how Sophia is working and then they talk to her they still attribute more agency and Consciousness to her than than is is is really there so I think there's there's a couple levels of ethical issue there one issue is should you be transparent about how Sophia is is working and I think you should and and I think I think we we have been I mean I mean it's there's articles online that there's some TV special that goes through me explaining the three subsystems behind Sophia so the way Sophia works is is out there much more clearly than how Facebook say I works or something right I mean we've been fairly explicit about it the other is given that telling people how it works doesn't cause them to not attribute too much intelligence agency to it anyway then then should you keep fooling them when they want to be fooled and I mean the you know the whole media industry is based on fooling people the way they want to be fooled and we we are fooling people 100% toward a good end I mean I mean we are we are playing on people's of empathy and compassion so that we can give them a good user experience with helpful robots and so that we can we can fill the ai's mind with love and compassion so I've been I've been talking a lot with Hansen robotics lately about collaborations in the area of of medical Robotics and we we haven't quite pulled the trigger on a project in that domain yet but we we may well do so quite soon so we've been we've been talking a lot about you know robots can help with with elder care robots can help with kids David's done a lot of things with h with autism therapy and robots robots before in the co era having a robot that can be a nursing assistant in various senses can be quite valuable the robots don't spread infection and they they can also deliver more attention than human nurses can give right so if you have a robot that's helping a patient with covid if that patient attributes more understanding and compassion and agency into that robot than it really has because it looks like a human I mean is that really bad I mean we can tell them it doesn't fully understand you and and they don't care because they're lying there with a fever and they're sick but they'll react better to that robot with its loving warm facial expression than they would to a pepper robot or or a metallic looking looking robot so it's it's really it's about how you use it right if you made a human looking like doorto door sales robot that used its its human looking appearance to to scam people out of their money yeah then you're using that that connection in in a bad way but you you could also use it in in a in a good way and that but then that's the same the same problem with every technology right beautifully put so like you said uh we're living in uh the era of the covid This Is 2020 one of the craziest years uh in recent history so uh if if we zoom out and look at this pandemic uh the Corona virus pandemic maybe let me ask you this kind of thing in in viruses in general when you look at viruses do you see them as as a kind of intelligence system I think the concept of intelligence is not that natural of a concept in the end I mean I I think human minds and bodies are a kind of complex self organizing adaptive system and viruses certainly are that right they're a very complex self-organizing adaptive system if you want to look at intelligence as as Marcus Hooter defines it as sort of optimizing computable reward functions over computable environments for sure viruses are doing that right and and I mean in in in doing so they're they're causing some some harm to us and that so there there you know the human immune system is a very complex self organizing adaptive system which has a lot of intelligence to it and viruses are also adapting and dividing into new Mutant strains and and and so forth and ultimately the solution is going to be nanotechnology right I mean I mean the solution is going to be making little Nanobots that fight the viruses or well people will use them to make nastier viruses but hopefully we can also use them to just detect combat and and kill the viruses but I think now now we're stuck with the biological uh mechanisms to to combat these these viruses and yeah know we've been AGI is not yet mature enough to use against Co but we've been using machine learning and also some machine reasoning in in opencog to help some doctors to do personalized medicine against covid so the problem there is given a person's genomics and given their clinical medical indicators how do you figure out which combination of antivirals is going to be most effective against covid for for that person and so that that's something where machine learning is interesting but also we're finding the abstraction we get an open Cog with machine reasoning is interesting because it can help with transfer learning when you have not that many different cases to study and qualitative differences between different strains of of a virus or people of different ages who may have Co so there's a a lot of different disparate data to work with and it's small data sets and somehow integrating them you know this is one of the shameful things it's very hard to get that data so I mean we're working with a couple groups doing clinical trials and and they're sharing data with us like under non-disclosure but what should be the case is like every covid clinical trial should be putting data online somewhere like suitably encrypted to protect patient privacy so that anyone with the right AI algorithms should be able to help analyze it and any biologist should be able to analyze it by hand to understand what they can right instead instead that data is like siloed inside whatever hospital is running the clinical trial which is completely asinine and and ridiculous like what why why the world works that way I mean we could all analyze why but it's insane that it does you look at this hyd hydrochloroquine right all these clinical trials were done were reported by surgisphere some little company no one ever heard of and everyone paid attention to this so they were doing more clinical trials based on that then they stopped doing clinical trials based on that then they started again and why isn't that data just out there so everyone can analyze it and and and see what's going on right you hope that uh we'll move uh that data will be out there eventually for future pandemics I mean do do you have hope that our society will move in the direction of not in the immediate future because the US and China frictions are getting very high so it's hard to see us and China as moving in the direction of openly sharing data with each other right it's it's not there's some sharing of data but different groups are keeping their data private till they've mil the best results from it and then they share it right so it's so yeah we're working with some data that we've managed to get our hands on something we're doing to do good for the world and it's a very cool playground for for like putting deep neural it's an open Cog together so we have like a bio adom Space full of all sorts of Knowledge from many different biology experiments about human longevity and from biology knowledge bases online and we can do like graph to Vector type embeddings where we take nodes from the hypergraph embed them into vectors which can then feed into neural nets for different different types of analysis and we were doing this in the context of a project called uh reu that we spun off from Singularity net to do longevity longevity analytics like understand why people live to 105 years or over and other people don't and then we had this spinoff Singularity Studio where we're working with some some healthc care companies on on data analytics but so this bio space we built for these more commercial and Longevity data analysis purposes were're repurposing and feeding Co data into the same same bio atom space and playing around with like graph embeddings from that graph into neural nets for bioinformatics and so it's it's both being a cool testing ground some of our bio AI learning and reasoning and it seems we're able to discover things that people weren't seeing otherwise because the thing in this cases for each combination of antivirals you may have only a few patients who've tried that combination and those few patients may have their particular characteristics like this combination of three was tried only on people age 80 or over this another combination of three which has an overlap with the first combination was tried more on young people so how do you combine those those different pieces of data it's a very dodgy transfer learning problem which is the kind of thing that the probalistic reasoning algorithms we have inside opencog are better at than deep neural networks on the other hand you have gene expression data where you have 25,000 genes and the expression level of each gene in the peripheral blood of each person so that sort of data either deep neural Nets or to like XG boost or cat boost these decision forest trees are better at dealing with than open Cog because it's just these huge huge messy floating Point vectors that that are annoying for a logic engine to to deal with but are are are perfect for a decision forest or a neural net so it's it's a great playground for like hybrid hybrid AI methodology and we can have Singularity net have open Cog and one agent and XG boost in a different agent and they talk to each other but at at the same time it's it's highly practical right because we're working with we're working with for example some Physicians on this project in thep physicians in the group called anopinion based out of uh of Vancouver and Seattle who are these guys are working every day like in the hospital with with patients patients dying of covid so it's it's quite cool to see like neural symbolic AI like where the rubber hit hits the road trying trying to save people's lives I've been I've been doing bio AI die since 2001 but mostly human longevity research and fly longevity research try to understand why some organisms really live a long time this is the first time like race against the clock and try to use the AI to figure out stuff that like if we take two months longer to solve the AI problem some more people will die because we don't know what combination of antivirals to give them yeah at the societal level at the biological level at any level are you hopeful about us as a human species getting out of this pandemic what are your thoughts on any general well the pandemic will be gone in a year or two once there's a vaccine for it so I I mean that's that that's but a lot of pain and suffering can happen in that time so I mean that could be irreversible I mean I I think if you spend much time in subsaharan Africa you can see there's a lot of pain and suffering happening all the time like you walk through the streets of any large city in subsaharan Africa and there are loads of I mean tens of thousands probably hundreds of thousands of people Lying by the side of the road dying mainly of curable diseases without without food or water and either ostracized by their families or they left their family house because they didn't want to infect their family right I mean there's tremendous human suffering on the planet all the time time which most folks in the developed World pay no attention to and Co is is not remotely the worst how many people are dying of malaria all the time I mean So Co is bad it is by no mean the worst thing happening and setting aside diseases I mean there are many places in the world where you're at risk of having like your teenage son kidnapped by armed militias and forced to get killed in someone else's War fighting tribe again tribe I mean so Humanity has a lot of problems which we don't need to have given the state of advancement of our our technology right now and I think Co is one of the easier problems to solve in the sense that there are many brilliant people working on vaccines we have the technology to create vaccines and we're going to we're going to create new vaccines we should be more worried that we haven't managed to defeat malaria after so long and after the Gates Foundation and others putting putting so much so much money in into it I mean I think clearly the whole Global Medical system Global health system and the global political and socioeconomic system are incredibly unethical and unequal and and badly designed and I mean I don't know how to solve that directly I think what we can do indirectly to solve it is to make systems that operate in parallel and off to the side of the of the governments that are are nominally controlling the world with with our armies and and militias and to the extent that you can make compassionate peer-to-peer decentralized Frameworks for doing things these are things that can start out unregulated and then if they get tractioned before The Regulators come in then they've influenced the way the world works right Singularity net aims to do this with with AI ruv which is a spin-off from from Singularity net you can see ru. IO that how do you spell that re eju V ru. iio that aims to do the same thing for medicine so it's like peer-to-peer sharing of medical data so you can share Medical Data into a secure data wallet you can get advice about your Health and Longevity through through through apps that that that Ru will launch within the next couple months and then Singularity AI can analyze all this data but then the benefits from that analysis are spread among all all the members of of of the network but I mean of course I'm going to Hawk my particular projects but I mean whether or not Singularity and and ruv are are the answer I think it's key to create decentralized mechanisms for everything I mean for AI for for human health for politics for for jobs and employment for sharing social information and to the extent decentralized peer-to-peer methods designed with universal compassion at the core can gain traction then these will just decrease the role that government has and I think that's much more likely to do good than trying to like explicitly reform the global government system I mean I'm happy other people are trying to explicitly reform the global government system on the other hand you look at how much good the internet or or Google did or mobile phones did you mean you're making something that's decentralized and throwing it out everywhere and it takes hold then then government has to adapt and I mean that's what we need to do with with AI and with health and in that light I mean the centralization of healthcare and of AI is is certainly not ideal right like most AIP phgs are being sucked in by you know a half dozen dozen big companies most AI processing power is is being bought by a few big companies for their own proprietary good and most medical research is within a few pharmaceutical companies and clinical trials run by pharmaceutical companies will stay solid within those pharmaceutical companies you know these large centralized entities which are intelligences in themselves these corporations but they're mostly malevolent Psychopathic and sociopathic intelligences not saying the people inv vved but the corporations as self-organizing entities on their own which are concerned with maximizing shareholder value as as as a sole objective function I mean Ai and Medicine are being sucked into these pathological corporate organizations with government cooperation and Google cooperating with British and and US Government on this as one among many many different examples 23 and me providing you the nice service of sequencing your your genome and then licensing the genome to glos Smith Klein on an exclusive basis right right now you can take your own DNA and do whatever you want with it but the pulled collection of 23 and me sequence DNA is just to to to gacos Smith Klein someone else could reach out to everyone who who had worked with 23 and me to sequence their DNA and say give us your DNA for our our open and decentralized repository that will make available to everyone but nobody's doing that because it's a pain to get organized and the customer list is proprietary to 23 in me right so yeah I mean this this I think is a greater risk to humanity from AI than Rogue AGI turning the universe into paper clips or or computronium because what you have here is mostly good-hearted and nice people who are sucked into a mode of organization right of large corporations which has evolved just for no individual's fault just because that's the way Society has evolved is not altruistic get self-interested and become Psychopathic like you said Corporation is psychopathic even if the people are not and that exactly that's really the disturbing thing about it because the corporations can do things that are quite bad for society even if nobody has nobody has a has a bad intention right and then no individual member of that Corporation has a bad intention no some probably do but they don't but but it's not necessary that they do for the for the corporation like I mean Google I know lot of people in Google and they're with very few exceptions they're all very nice people who genuinely want what what's good for the world and Facebook I know fewer people but it's probably most it's probably mostly true it's probably like fine young Geeks Who who want to build cool technology I actually tend to believe that even the leaders even Mark Zuckerberg one of the most disliked people in Tech is also wants to do good for the world what do you think about Jamie demon who's Jamie demon oh the heads of the Great may have a different psychology oh boy yeah well I tend to um I tend to be naive about these things and see see the best in uh I I I tend to agree with you that I think the individuals want to do good by the world but the mechanism of the company can sometimes be its own intelligence syst I mean there there's a one my cousin Mario gel has worked for Microsoft since 1985 or something and I can see for him I mean as well as just working on cool projects you're coding stuff that gets used by like billions and billions of of people and you think if I improve this feature that's making billions of people's lives easier right so of course of course that's cool and you know the engineers are not in charge of running the company anyway and of course even if you're Mark Zuckerberg or Larry Page I mean you still have a fiduciary responsibility and I mean you you responsible to the show sh holders your employees who you want to keep paying them and so forth so yeah you're Imes in this system and you know when I worked in DC I worked a bunch with inscom US Army intelligence and I was heavily politically opposed to what the US Army was doing in Iraq at that time like torturing people in Abu graa but everyone I knew in US Army in inscom when I hung out with him was a very nice person they were friendly to me they were nice to my kids and and my dogs right and they really believed that the US was fighting the forces of evil and if you ask them about Abu gayab they're like well but these Arabs will chop us into pieces so how can you say we're wrong to waterboard them a bit right like that's much less than what they would do to us it's just in in their world view what they were doing was really genuinely for the for the good of humanity like none of them woke up in the morning and said like I I want to do harm to good people because I'm I'm just a nasty guy right so yeah most people on the planet setting aside a few genuine Psychopaths and sociopaths I mean most people on the planet have a heavy dose of benevolence and wanting to do good and also a heavy capability to convince themselves whatever they feel like doing or whatever is best for them is is for the good of humankind right and so the more we can decentralize control of decentralization you know the democracy is horrible but this is like when Church Hill said you know it's the worst possible system of government except for all the others right I mean I think the whole mess of humanity has many many very bad aspects to it but so far the track record of elite groups who know what's better for all of humanity is much worse than the track record of the whole teaming Democratic participatory mass of humanity right I mean none of them is perfect by by any means the issue with a small Elite group that knows what's best is even if it starts out as truly benevolent and doing good things in accordance with its initial good intentions you find out you need more resources you need a bigger organization you pull in more people internal politics arises difference of opinions arise and bribery happens like some some opponent organization takes a second and command out to make some the first in command of some some other organization and I mean that's there's a lot of history of of what happens with Elite groups thinking they know what's best for for for the human race so you have if I have to choose I'm going to reluctantly put my faith in the vast Democratic decentralized mass and I think corporations have a track record of being ethically worse than their constituent human parts and you know democratic governments have a more mixed track record but there are at least but it's the best we got yeah I mean you can you can there's Iceland very nice country right I mean very de Democratic for 800 plus years very very benevolent beneficial government and the I think yeah there are track records of democratic Modes of organization Linux for example some of the people in charge of Linux are overtly complete right and trying to reform themselves in in many cases in in other cases not but the organization as a whole I think it it it's it's done a good job over overall it's been very welcoming in in in in the third world for for example and it's it's allowed advanced technology to roll out on all sorts of different embedded devices and Platforms in places where people couldn't afford to pay for for proprietary software so I'd say the internet Linux and many democratic nations are examples of how sort an open decentralized Democratic methodology can be ethically better than than the sum of the parts rather than worse and corporations that has happened only for a brief period and and then and then then it go it goes sour right I mean I'd say a similar thing about universities like University is a horrible way to organize research and get things done yet it's better than anything else we've come up with right a company can be much better but for a brief period of time and then then it stops stops being so good right so then I I think if you believe that AI is going to emerge sort of incrementally out of AI doing practical stuff in the world like controlling humanoid robots or or driving cars or diagnosing diseases or operating killer drones or spying on people and Reporting on the government then then what kind of organization creates more and more advanced narrow AI verging toward AGI may be quite important because it will guide like what's what's in the mind of the early stage AGI as it first gains the ability to rewrite its own code base and project itself toward toward super intelligence and if you believe that AI may move toward AGI out of the sort of synergetic activity of many agents cooperating together rather than just have one person's project then who owns and controls that platform for AI cooperation becomes also very very important right and is that platform AWS is it Google cloud is it Alibaba or is it something more like the internet or Singularity net which is open and de open and decentralized so if if all of my weird machinations come to pass right I mean we have we have the Hansen robots being a beautiful user interface you know gathering information on on on human values and being loving and compassionate to people in medical home service robow about office applications you have Singularity net in the back end networking together many different AIS toward Cooperative intelligence fueling the robots among many other things you have opencog 2.0 and true AGI as one of the sources of AI inside this decentralized network powering the robot and medical AIS helping us live a long time and cure diseases am among among other things and this whole thing is operating in a in a democratic and and decentralized way right I think if if anyone can pull something like this off you know whether using the specific Technologies I've mentioned or or or something else I mean then I think we have a higher odds of moving toward a beneficial technological singularity rather than one in which the first Super AGI is indifferent to humans and just considers us an INE efficient use of molecules that was a beautifully articulated vision for the world so thank you for that but let's talk a little bit about life and death I'm I'm pro-life and anti death speak well you for for most people there's few exceptions that I won't mention here I'm I'm I'm glad just like your dad you're taking a stand against uh death uh you have uh by the way you have a bunch of Awesome music where you play Piano online well one of the songs that I believe you've written uh the lyrics go by the way I like the way it sounds people should listen to it's awesome I was I considered I probably will cover it it's a good song uh tell me why do you think it is a good thing that we all get old and die is one of the songs I love the way it sounds but let me ask you about death first do you think there's an element to death That's essential to give our life meaning like the fact that this thing ends the say I'm I'm uh pleased and a little embarrassed you've been listening to that music I put online that's awesome one of my regrets in life recently is I would love to get time to really produce music well like I I I haven't touched my sequencer software in like five years like I I would love to like rehearse and produce and and edit and but the with a two-year-old baby and and trying to create the singularity there's no time so I I just made the decision to when I'm playing random in an off moment just record it just just record it put it out there like like whatever maybe if I'm unfortunate enough to die maybe that can be input to the AGI when it tries to make an accurate mind upload of me right death is bad I mean that's very simple it's battling we should have to say that I mean of course people can make meaning out of out of death and if if someone is tortured maybe they can make beautiful meaning out of that torture and write a beautiful poem about what it was like to be tortured right I mean we we're very creative we can we can milk Beauty and positivity out of even the most horrible and and and shitty things but just because if I was tortured I could write a good song about what it was like to be tortured doesn't make torture good and just because people are able to derive meaning and value from Death doesn't mean they wouldn't derive even better meaning and value from ongoing life W without death which I very definite yeah yeah so if you could live forever would you live forever forever I my my goal with longevity research is to abolish the plague of involuntary death I don't think people should die unless they choose to die if I had to choose forced immortality versus dying I would choose forced immortality on the other hand if I chose if I had the choice of immortality with the choice of suicide whenever I felt like it of course I would take that instead and that's the more realistic choice I mean there there's no reason you should have forced immortality you should be able to live until you get until you get sick of living right I mean that's and that will seem insanely obvious to everyone 50 years from now and they will be so I mean people who thought death gives meaning to life so we should all die they will look at that 50 years from now the way we now look at the anabaptists in the year 1000 who gave away all their positions went on top of the mountain for Jesus for Jesus to come and bring them to the to the Ascension I mean it's it's ridiculous that that people think death is is is good because because you gain more wisdom as you approach dying mean of of of of course it's true I mean I'm 53 and you know the fact that I might have only a few more decades left it does make me reflect on on things differently it it it it it does give me a deeper understanding of many things but I mean so what you could get a deep understanding in in a lot of different ways pain is the same way like we're going to abolish pain and that that that's even more amazing than abolishing death right I mean once we get a little better at Neuroscience we'll be able to go in and adjust the brain so that pain doesn't hurt anymore right and that you know people will say that's bad because there's so much Beauty in overcoming pain and suffering well sure and there's Beauty in overcoming torture too but and some people like to cut themselves but not not many right I mean that's an interesting so but to push I mean to push back again this the Russian side of me I do romanticize suffering it's non obvious I mean the way you put it it's seems very logical it's almost absurd to to romanticize suffering or pain or death but to me a world without suffering without pain without death it's non obvious what you can stay in the people's Zoo the people torturing each other right no but that what I'm saying is I I don't well that's I guess what I'm trying to say I don't know if I was presented with that choice what I would choose because it to me no this this is this is a subtler it's a subtler matter and I've posed it in this conversation in an unnecessarily extreme way so I I think I think the way you should think about it is what if there's a little dial on the side of your head and you could turn how much pain hurt turn it down to zero turn up to 11 like in spinal tap if it wants maybe through an actual spinal typ right so I mean would you opt to have that dial there or not that that that's the question the question isn't whether you would turn the pain down to zero all all all the time would you opt to have the dial or not my my guess is that in some dark moment of your life you would choose to have the dial implanted and then it would be there just to confess a small thing I'm uh don't ask me why but I'm I'm doing this physical challenge currently where I'm doing 680 push-ups and pull-ups a day and and my shoulder is currently as we sit here in a lot of pain and uh I I don't know I would certainly right now if you gave me a dial I would turn that sucker to zero as quickly as possible but I don't I think the whole point of this journey is I don't know well because you're you're a twisted human being I'm a twisted so the question is if am I somehow Twi am I is Twisted because I have I I created some kind of narrative for myself so that I can deal with the with with the Injustice and the suffering in the world uh or is this actually going to be a source of happiness for me well this is this is a to an extent is a research question that Humanity will undertake right so I mean human human beings do have a particular biological makeup which sort of implies a certain probability distribution over motivational systems right so I mean we we we and that that is there well put that is there now the the the question is how flexibly can that morph as society and Technology change right so if if we're given that dial and we're given a society in which say we don't have to we don't have to work for a living and in which there's an ambient decentralized benevolent AI Network that will warn us when we're about to hurt oursel you know if we're in a different context can we consistently with being genuinely and fully human can we consistently get into a state of consciousness where we just want to keep the pain dial turned all the way down and yet we're leading very rewarding and fulfilling lives right now I suspect the answer is yes we can do that but I I don't I don't know that a research I don't know that for certain yeah now I'm more confident that we could create a nonhuman AGI system which just didn't need an analogue of feeling pain and I think that AGI system will be fundamentally healthier and more benevolent than than human beings so I think it might or might not be true that humans need a certain element of suffering to be satisfied humans consistent with the human physiology if it is true that's one of the things that makes us and disqualified to be the be the Su the super AGI right I mean this is a the nature of the human motivational system is that we we seem to gravitate towards situations where the best thing in the large scale is not the best thing in in in the small scale according to our subjective value system so we gravitate towards subjective value judgments where to gratify ourselves in the large we have to UNG gratify ourselves in the in the small and we do that in you see that in in music there's a theory of Music which says the key to musical Aesthetics is the surprising fulfillment of expectations like you you want something that will fulfill the expectations are listed in the prior part of the music but in a way with a bit of a Twist that that that surprises you and that I mean that's true not only an outdoor music like my own or that of Zappa or or Steve V or or Buckethead or Kristoff pendi or something it's even there in in Mozart or something it's not there in elevator music too much but that that's that's that's why that's why it's boring right but wrapped up in there is you know we want to hurt a little bit so that we can we can feel the we can feel the pain go away like We want to be a little a little a little confused by what coming next so then when the thing that comes next actually makes sense it's so satisfying right and it's the surprising fulfillment of expectations is that what you said yeah yeah so beautifully put is there um we've been skirting around a little bit but if I were to ask you the most ridiculous big question of what is the meaning of life uh what would your answer be three values Joy growth and choice I I I think you you need you need Joy I mean that that's the basis of everything if you want the number one value on the other hand I'm unsatisfied with a a static joy that doesn't progress perhaps because of some Elemental element of human perversity but the idea of something that grows and becomes more and more and better and better in some sense appeals to me but I also sort of like the idea of individuality that as a distinct system I have some agencies there's some Nexus of causality within within this system rather than the causality being wholly evenly distributed over the joyous growing Mass so I you start with joy growth and and choice as three basic values that's and those three things could continue indefinitely that's not that's something yeah that can last forever is there is there some aspect of something you called which I like super longevity that you find exciting that what is there you research-wise is there ideas in that space that I mean I I think yeah in terms of the meaning of life this really ties into that because for us as humans probably the way to get the most Joy growth and choice is transhumanism and to go beyond the human form that that that that we have right now right I mean I think human body is great and by no means to any of us maximize the potential for Joy growth and choice imminent in our human bodies on the other hand it's clear that other configurations of matter could manifest even greater amounts of Joy growth and choice than that than than humans do maybe even finding ways to go beyond the realm of matter that as as we understand it right now so I think in a practical sense much of the meaning I see in human life is to create something better than humans and and and and go beyond life but certainly that's not all of it for me in a practical sense right like I have four kids and and and a granddaughter and uh many friends and parents and family and just enjoying everyday human Human Social existence well we can do even better yeah yeah and I mean I I love I've always when I could live live near nature I spend a bunch of time out in nature in the forest and on the water every day and so forth so I mean enjoying the pleasant moment is is part of it but the you know the growth and choice aspect are severely limited by our human biology in particular dying seems to inhibit your potential for personal growth considerably as as as far as we know I mean there's some element of life after death perhaps but even if there is why not also continue going in in in in in this in this biological realm right in in in super longevity I mean you know we we haven't yet cured aging we haven't yet cured death certainly there's very interesting progress all around I mean crisper and and Gene editing can be can be an an incredible tool and I mean right now stem stem cells could potentially prolong life a lot like if if you got stem cell injections of of just stem cells for every tissue of your body injected into every tissue and you can just have replacement of your old cells with new cells produced by those stem cells I mean that that could be highly impactful at prolong life now we just need slightly better technology for for having them grow right so you using machine learning to guide procedures for stem cell differentiation and trans trans differentiation it's kind of nitty-gritty but I mean that that's that that that's quite interesting so I think there's there's a lot of different things being done to help with with prolongation of of human life but we could do a do a lot better so for example The extracellular Matrix which is a bunch of proteins in between the cells in your body they get stiffer and stiffer as you get older and the The extracellular Matrix trans transmits information both electrically mechanically and to some extent biop photonically so there's all this transmission through the parts of the body but the stiffer The extracellular Matrix gets the less the transmission happens which makes your body get get worse coordinated between the different organs as you get older so my friend Christian schafmeister at my alumnus organization the great my alma mother the great Temple University Christian schafmeister has a potential solution to this where he has these novel molecules called spirro ligers which are like polymers that are not organic they're specially specially designed polymers so that you can algorithmically predict exactly how they'll fold very simply so he designed a molecular scissors that have spirro ligers that you could eat and would then would then cut through all the glucosa pain and other cross-link proteins in your extracellular Matrix right but to make that technology really work and be mature is several years of work as far as I know no no one's funding it at the moment but there so there's so many different ways that technology could be used to prolong longevity what what we really need we need an integrated database of all biological knowledge about human beings and model organisms like Bas hopefully a m distribute opencog bio atom space but it can exist in other forms too we need that data to be opened up and a suitably privacy protecting way we need massive funding into machine learning AGI Proto AI statistical research aimed at solving biology both molecular biology and human biology based on this massive massive data set right and and and then we need Regulators not to stop people from trying radical therapies on on on themselves if if they so so wish to as as well as better cloud-based platforms for like automated experimentation on microorganisms flies and mice and so forth and we could do all this you look after the last financial crisis Obama who I generally like pretty well but he gave $4 trillion do to large Banks and insurance companies you know now in this covid crisis trillions are being spent to help Everyday People in small businesses in the end we probably will find many more trillion to being given to large Banks and insurance companies anyway like could the world put1 trillion into making a massive holistic bio Ai and bio simulation and experimental biology infrastructure we could we could put 10 trillion dollars into that without even screwing us up too badly just as in the end Co and the last financial crisis won't screw up the world economy so badly we're not putting 10 trillion into that instead all the resurch is siloed inside a few big companies and and and and government agencies and most of the data that comes from our individual bodies personally that could feed this AI to solve aging and death most of that data is sitting in some some hospitals database doing nothing right I got a uh two more quick questions for you uh one I know a lot of people are going to ask me you on the Joe Rogan podcast wearing that same amazing hat um do you have a origin story for the hat is there does the Hat have its own story that you're uh able to share uh the Hat story has not been told yet so we're going to have to come back and you can you can interview the Hat the Hat we'll leave that for the Hat Zone interview all it's too much it's too much to pack into is there a book is a hat gonna write a book okay we'll uh it may transmit the information through direct neural transmission okay so it's it actually there might be some neuralink competition there uh beautiful we'll leave it as a mystery uh maybe one last question if uh you uh build an AGI system uh you're successful at building the A A system that could lead us to The Singularity and you get to talk to her and ask her one question what would that question be we're not allowed to ask what is the question I should be asking yeah that would be cheating but I guess that's a good question I'm thinking of a I wrote a story with Stefan bugy once where these AI developers they created a super smart AI aimed at answering all the philosophical questions that have been worrying them like what what what is the meaning of life is there free will what is consciousness and so forth so they got the super AGI built and it uh it turned a while it said those are really stupid questions and then it puts off on the spaceship and and and and left the Earth right see be afraid of scaring it scaring it off that that's it yeah I mean honestly there's there there there there is no one question that that rises among among all all the all the all the others really I mean what interests me more is upgrading my Mo my own intelligence so that I I can absorb the whole the whole world world view of the of the super AGI but I mean of course if if the if the answer could be like what's the what is the chemical formula for the immortality pill like then I would do that or emit emit a bit string which uh will be the the code for a super AGI on the Intel i7 processor right so those would be good questions so if you're on mind was expanded to become super intelligent like you're describing I mean there's a you know there there's kind of a notion that with intell intelligence is a burden that it's possible that with greater and greater intelligence the that other metric of joy that you mentioned becomes more and more difficult what's your pretty stupid idea so you think if you're super intelligent you can also be super joyful I think getting root access to your own brain will enable new forms of joy that we don't have now and I I think as I've said before what I aim at is really make multiple versions of myself so I would like to keep one version which is basically human like I am now but you know keep the dial to turn P pain up and down and get rid of death right and make another version which fuses its mind with superhuman AGI and then will become massively transhuman and what whether it will send some messages back to the human me or not is will be interesting to find out the thing is once you're super super AGI like one subjective second to a human might be like a million subjective years to that super AGI right so it would be on a whole different basis I mean at very least those two copies will be good to have but it could could could be interesting to put your mind into into a dolphin or a space amoeba or all sorts of other things or you can imagine one version that doubled its intelligence every year and another version that just became a super AGI as fast as possible right so I mean now we're sort of constrained to think one mind one self one body right but but I think we actually we don't need to be that constrained in in in thinking about future intelligence after we've mastered AGI and nanotchnology ology and Longevity biology I mean then each of our minds is a certain pattern of organization right and I I know we haven't talked about Consciousness but I I sort of I'm pan psychist I sort of view the universe as as conscious and so you know a light bulb or a a quark or an ant or a worm or a monkey have their own manifestations of Consciousness and the human manifestation of Consciousness it's partly tied to the particular meat that that we're manifested by but it's largely tied to the pattern of organization in in in the brain right so if you upload yourself into a computer or a robot or or what whatever else it is some element of a human consciousness may not be there because it's just tied to the biological embodiment but I think most of it will be there and these will be incarnations of your Consciousness in a slightly different flavor and you know creating these different versions will be amazing and each of them will discover meanings of life that have some overlap but probably not total overlap with with the human Bend's meaning meaning of life the the thing is to get to that future where we can explore different varieties of of Joy different variations of human experience and values and transhuman experiences and values to get to that future we need to na navigate through a whole lot of human of companies and and governments and and killer drones and making and losing losing money and and so and so forth right and that's that that's the challenge we're facing now is if we do things right we can get to a benevolent Singularity which is levels of Joy growth and choice that are literally unimaginable to to human beings if if we do things wrong we could either annihilate all life on the planet or we could lead to a scenario where say all humans are are annihilated and there's some super AGI that goes on and does it does its own thing unrelated to us except via our our role in in originating it and we may well be at a bifurcation point now right where where what we do now has significant causal impact on what comes about and yet most people on the planet aren't thinking that way whatsoever they're thinking only about their own narrow a narrow aims and Asim aims and goals right now of course I'm thinking about my own narrow aims and goals to some extent also but I'm I'm trying to use as much of my energy and mind as I can to push toward this more benevolent alternative which will be better for me but Al but also for also for everybody else and that's a it's weird that so few people understand what's going on I know you interviewed Elon Musk and he understands a lot of what's going on but he's much more paranoid than I am right because because Elon gets that AGI is going to be way way Smarter Than People yeah and he gets that an AGI does not necessarily have to give a about people because we're very Elementary mode of organization of matter compared to many a many agis but I don't think he has a Clear Vision of how infusing early stage agis with compassion and human warmth can lead to an AGI that loves and helps people rather than viewing us as uh as you know a historical artifact and and a a waste of ma a waste of mass energy but but on the other hand while I have some disagreements with him like he understands way way more of the story than almost anyone else in such a large scale corporate leadership position right it's it's terrible how little understanding of these fundamental issues exists out there now that may be different five or 10 years from now though because I I can see understanding of AGI and Longevity and other such issues is certainly much stronger and more prevalent now than than 10 or 15 years ago right so I mean humanity is as a whole can be slow Learners relative to what what what what I would like but on a historical Sense on the other hand you could say the progress is astoundingly fast but Elon also said I think on The Joe Rogan podcast that love is the answer so uh maybe in that way you and him are both on the same page of how we should proceed with AI I think there's no better place to end it I hope we get to talk uh again about the hat and about Consciousness and about a million topics we didn't cover Ben it's a huge honor to talk to you thank you for making it out thank you for talking today NOK thanks for having me this was this was uh was really really really good fun and uh we dug deep into some very important things so thank thanks for doing this thanks very much awesome thanks for listening to this conversation with Ben geril and thank you to our sponsors the Jordan Harbinger show and Master Class please consider supporting the podcast by going to Jordan Harbinger dcom Lex and signing up to masterclass and masterclass.com Lex click the links buy the stuff it's the best way to support this podcast and the journey I'm on in my research and startup if you enjoy this thing subscribe on YouTube review it with five stars on Apple podcast support on patreon or connect with me on Twitter Alex fredman spelled without the e just f r i d m an I'm sure eventually you will figure it out and now let me leave you with some words from Ben gzel our language for describing emotions is very crude that's what music is for for thank you for listening and hope to see you next time |
Steven Pressfield: The War of Art | Lex Fridman Podcast #102 | the following is a conversation with Steven Pressfield author of several powerful nonfiction and historical fiction books including the war of art a book that had a big impact on my life and the life of millions of people whose passion is to create an art science business sport and everywhere else I highly recommend it and others of his books on this topic including turning pro do the work nobody wants to read your shit and the Warrior Ethos also his books gets a fire about the Spartans and the Battle of Thermopylae the Lionsgate tides of war and others are some of the best historical fiction novels ever written some of you know I don't shy away from taking on a big difficult challenge one of the hardest for me for millions of others is the discipline of staring and an empty page every day pushing on to think deeply to create despite the millions of excuses that fill the head in his work steven has articulated this struggle better than anyone I've ever read quick summary of the ads to sponsors the Jordan Harbinger show and cash app please consider supporting the podcast by going to Jordan Harbinger dot-com slash Lex and subscribing to it everywhere after that and downloading cash app and using code Lex podcast click on the links buy all of the stuff it really is the best way to support this podcast this is the artificial-intelligence podcast I recently considered renaming this podcast but decided against it ai is my passion and in some sense this podcast is not as much about AI but more about a journey of an AI researcher struggling to explore the human mind the physics of our universe and the nature of human behavior intelligence consciousness love and power I will continue to return home to the technical computer science machine learning engineering math programming but all so venture out to talk to people who had a big impact on my life outside the technical fields writers like Steven Pressfield and Stephen King musicians like Tom Waits political leaders like well you know who in human athletes I hope you join me on this journey as usual I'll do a few minutes of ads now and no ads in the middle that can break the flow of the conversation click on the links buy all of the stuff it's the best way to support this podcast this episode is supported by the Jordan Harbinger show go to Jordan Harbinger calm / Lex it's how he knows I sent you on that page there's links to subscribe to it on Apple podcasts Spotify and everywhere else I've been binging on this podcast Jordan is a great human being he gets the best out of his guests dives deep calls him out when it's needed and makes the whole thing fun to listen to he's interviewed Kobe Bryant Mark Cuban Neil deGrasse Tyson Garry Kasparov and many more I just finished listening to his recent conversation with Mick West about debunking conspiracy theories this topic can be both fascinating and frustrating on both sides but in this conversation Jordan thread the needle beautifully and so it turned out to be a great listen I highly recommend it again go to Jordan Harbinger calm / Lex it's how he knows I sent you on that page there's links to subscribe to the show on Apple podcasts Spotify and everywhere else this show is presented by cash app the number one finance app in the App Store when you get it use collects podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app allows you to buy bitcoin let me mention that the cryptocurrency in the context of the history of money is fascinating I recommend a cent of money as a great book on this history debits and credits on Ledger's started around 30,000 years ago the US dollar created over two hundred years ago and the first decentralized cryptocurrency release just over 10 years ago so given that history cryptocurrency still very much in its early days of development but it's still aiming to and just might redefine the nature of money so again if you get cash out from the App Store or Google Play and use the code let's podcast you get $10 and cash up will also donate $10 the first an organization that is helping advanced robotics and STEM education for young people around the world and now here's my conversation with Steven Pressfield modern society many ways dreams of creating universal peace and yet war has molded civilization as we know it throughout his history so let's start at the high philosophically ville if you could imagine a world without war how would that world be different perhaps put another way well purpose has war served why do we fight I think we're basically the same creatures internally that we were in the cave right in tribal society back for however many you know hundreds of thousands millions of years which means that we're in our the dynamic in our mind is that kind of an us-versus-them dynamic where our tribe is the people and everybody else are whatever you know and I don't see that I don't think that's changed one iota over the over the centuries it's just a question of how how one might sublimate that that urge to compete you're a martial artist you know that you know a great part of your day I'm sure is dedicated to reaching that place of you know of total commitments and in the face of competition in the face of adversity at cetera et cetera which is I think natural and great for the human race on an individual basis so the the hope that I have if there is any hope personally I don't think the human race is gonna be around very long but would be in in sports or in other kind of sublimated activities where people can act out their need for conquest or aggression or so forth but at the same time relate to their opponents as human beings that when the game is over you know you embrace your competitors stuff like that so you think war was inevitable it's a it's a part of human nature as opposed to a force a creative force in society that serve the benefit well I'm sure it has benefited you know spreading cultures and mixing cultures and stuff like that but I think the the urge to conquest if you think about Alexander the Great or Julius Caesar Napoleon or anybody like that or any even individual or if we even think about one of the plants that we're looking at right outside I mean if you let a particular plant have its way it would take over reading on the whole hillside and certainly in the days of Alexander the Great let's say there were who knows over looking over the face of the earth hundreds of little kingdoms China Japan you know Asia Europe wherever and every prince that grew up dreamt of conquering his neighbor and conquering a neighbor after that that seems to be a universal human imperative at least in the male of the species so where is this the realization of that imperative I think so so you've written about Spartans in the Battle of Thermopylae about Alexander the Great about the six-day war in 67 in Israel against Egypt Jordan Syria what war not just out of those but in general do you think has been most transformative for the world well he's a great questions Lex ah easy ones right I mean I wish I knew more about the Mongols because I certainly from what I've what little I know I think that was a very their conquests was a very transformative bringing cultures you know you know horrible bloody way together but gosh what's then the most transformative maybe the Roman conquest you know establishing the Roman Empire and bringing that culture maybe Alexander the Great's Wars that you know United East and West at least for a minute it's a building of empire do you have a sense so there's Wars I mean the six-day war is not about building empires it's about deep how deeply held religious cultural conflict and holding the line holding the border and then there is conquests like the Mongols that what is it some large percentage of the population is a descendant of Genghis Khan believed right so that has transformative effects in that in World War two I mean personally and my family and so on the transformative effects let me ask you this Lex why are you what are you trying to get at with these questions what is this kind of the theme that you're you're aiming here well I talked to Eric Weiss that and he said everything is great about war except the killing and there's a romantic notion of war certainly this romantic notion of being a warrior but there's a romantic notion of war that somehow there's a creative force to it that because we fight out of that fighting comes culture comes music and art and more and more desire to create with the societies that win and to me war is not just hey I have a stick and I want your land it's some kind of it like it has echoes of the the creative force that makes humans unique to other animals like Wars you you it can't be just four people or 10 people or 100 people you have to have thousands of people agreeing usually thousands or more for something so deeply that you would be willing to risk your own life and there's a romantic notion to that and because you've written so well and passionate about some of these I wanted to see because I don't have any answers I wanted to untangle that if there is a reason we fight that's more than just anger and hate and wanting to conquer well let me take it from a completely different side I don't think that I in writing about war am really that interested in war per se I'm more interested in the metaphor I think for me I'm really writing about my own internal war and and the war against myself and against my own resistance my own negativity all of those things that are that spirituality would would be the opposite of so so I'm not really an expert on war it's not like talking to Jim mattis or to you know Victor Davis Hanson or whatever to me the human being we are spiritual beings in a physical envelope and there's a automatic terrible tension within that and and which creates a war inside ourselves so the outer the outer war when I when I think about the Israeli army standing up to you know whatever 10 to 1 odds or whatever it was that is a metaphor to me of the fight we were fighting inside ourselves it for me the six-day war was as you know my feeling was it was about a return from exile it was sort of the culmination of the reestablishment of the State of Israel which had never really been completed because the holiest places of the Jewish people were in the hands of their enemies so now on the other hand Alexander the Great's conquests I think were a whole other different scenario where the metaphor was that Alexander's father Philip I think created the first nation capital and nation and he created a sort of a pathway for these guys who were mountain men and basically barbarians Macedonians and Crete by creating this army and this dream of conquering the world which Alexander took to the you know really enacted he gave them a way of rising out of themselves of transcending themselves not just individually but as a people so that would go along with what you're saying Lex of a certain creativity to it but but again that's not for whatever I'm just realizing this as I'm answering this that's not really what's interesting to me about these stories and the Spartans to what was a hole at Thermopylae that was a whole other kind of metaphor of war that was a sort of a willingly going to one's own death for a greater cause just like to me the Spartans at Thermopylae enacted as a group what Jesus Christ enacted as an individual a sacrifice of their lives for the greater for the greater good I don't know if that answers your question but that's how I that's how I see it I do feel like you know I get invited to speak to Marine Corps groups and things like that all the time and I decline because I don't really feel like I'm a spokesman for the warrior class or anything like that it's not that's not what's interesting about it to me but didn't you just say with Wars a metaphor that we're all essentially in various ways warriors if we think of it in terms of Union archetypes and think of our life as at least as some as males and the earliest archetypes that kick in are the youth and the wanderer and the student and that kind of thing and then at some point around age 15 to 20 whatever the warrior archetype kicks in and we want to play football I want to do martial arts we want to join the Special Forces we want to hang out with our buddies that's our great bond we want to test ourselves against adversity and so on and so forth but at some point that archetype we move beyond that archetype and we become fathers and and teachers and so on and so forth and then there are many archetypes beyond that towards the end so I'm I'm interested in the warrior archetype but not to the be-all and end-all of everything else you know there's a in in my book the virtues of war I have you read that there's a character named telamon who's actually it's a long story but when he's with Alexander's army and when they arrive in India he becomes fascinated by the gymnast fists the fuckers the naked wise men the the Yogi's and he says to Alexander that these guys are our warriors beyond what we are even though they do nothing because they are inside their own selves you know all day long if we if we go to the Six Day War you write about in Lionsgate you write about the six-day war in Israel I think of the wars you've written about it's the one we're still in many ways in the midst of today yes so what is it the core of that conflict and the israeli-palestinian conflict I mean today it's the israeli-palestinian conflict but it's uh echoes of the same conflict in that part of the world with Israel what is in your sense the nature of that conflict what can we learn about society and human nature from that conflict that is one of the hottest conflicts that still goes on today well when I was working on the Lionsgate about the six-day war I wrote in the in the introduction that this was not going to be a multi-sided story I was taking it entirely I'm a Jew I identify with the Israeli people I was gonna see it entirely from their side so that's probably not what you're asking but to me the six-day war and that whole you know it's it's a piece of land that's holy to at least three religions and probably more and from the Jewish point of view it's where the State of Israel it's where David founded Jerusalem it's all whether twelve tribes were etc.etc Moses came and brought the people so to to me the the the six-day war was about as I said a return from exile from diaspora after 2,000 years now obviously from the Palestinian point of view or the Saudi Arabian point of view or whatever as it's a whole other scenario the religion is at the core of this conflict in some ways the religious beliefs religion and racial / ethnic tribal identity I mean what is a Jew is a Jew somebody that believes in the religion or is it somebody of a certain race that who that race arose in a certain place same thing as a Muslim what is a Muslim and they believe in you know Muhammad or whatever or did they arise in a certain place and a certain ethnicity because if we landed from Mars we couldn't tell a Jew from a Palestinian could we you know just looking at them you could easily mix them and you'd never know and the the specifics of the faith is not necessarily the thing that defines no person I don't think so the be like many are secular Jew living in Israel and still have a strong bond only definitely in fact almost all of the Jews the fighters that I spoke to from the six-day war were secular and it really was not you know a religious thing with them as much as it was a national thing so having spent time in Israel how's the world where military conflict is directly felt as opposed to maybe if we look at the US was distant and far away how is that world different how are the people different it's very different as you know yeah I've never been to Israel actually we haven't even felt it ah well you should definitely go I mean here in the United States where when like there's an incident like Charlottesville comes up you know where people are chanting Jews will not replace us blah blah blah the impulse and the Jewish community is to think about how can we reach out to the other side you know how can how can we show them that we are human beings like they are and show them that we care for them at cetera et cetera that's the sort of distant from war from if you're in Israel and you know like if you and I were we're Israeli citizens right now you would be a fighter pilot or a tank commander or whatever you know you would not just be as you know working at MIT or whatever and I would be in the Army too and so from their point of view they say all those people who hate us can I curse on this court this thing that fuck them will kill them kill you know if they dare to cross the line and that's they're a whole different point of view to me it's actually a healthier point of view you think so yeah there's no so let me ask the hard question is well maybe it's an impossible questions how do we resolve that conflict in Israel and in Israel or anywhere anywhere where the instinct is to reach out in us and say a few and in the people yeah here's my here's I think that the only way that two warring sides or two sides that are opposed to one another can ever really come together is when there's mutual respect we get to some more water when there's mutual respect and and and as and they can see each other as equals and theirs and when there's mutual fear you know where where one side says we don't dare cross a line with this other side and the other side says the same thing I think then you can kind of reach across that thing and say okay they will stay here you stay here we'll we'll mingle in cultural ways in will have interchange you know winter marriage dah dah dah but as soon as one side has no power as the Jewish people have had no power throughout the Diaspora forever right then it's just a human nature you can see it in Trump and what he does to any vulnerable minority right um it's it's and he's not alone I'm not blaming chemo alone that's human nature so I do think that that idea of like fuck you if you cross the line will kill you it's really a good way is it's a good place to start from because now you can sit down on opposite sides of the table and say you know what do we have in common how can we we want to raise our children you want to raise your children how can we do this in a way that's that we're not hurting each other so you kind of said that he to arrive at a ballot some kind of balance of power yet you haven't spoken to the fact that there is deeply rooted hatred of the other so is there no way to alleviate that hatred or is that I mean what what role does love but hatred can go away I really do I mean if you look at even even now that I haven't seen this in person but they say that the Saudis and the Israelis are collaborating on certain things you know by their mutual fear of or antagonism to Iran I do think that even really long long long standing hatreds and animosities thousands of years old can can go away under the right circumstances in uh on what timescale I mean that for instance I don't know that somebody thinking people have to die do generations have to die and pass away and new generations come up with less hate or can a single individual learn to not hate I think a single individual can learn to not hate because it certainly doesn't seem to over thousands of years doesn't seem to work you know we keep thinking that that's going to happen but I think it's we're in a real spiritual realm here when you're talking about that you're in a realm of you know Buddha Jesus whatever something like that that we're a you know a a true change of soul it happens but I do think that's possible so what do you think is the future of warfare especially with what many people see is the expansion of the military industrial conflict to what do you I know you're not a military historian I'm asking more as a metaphor uh-huh and we'll do you see us as people continuing to fight you know it's a really great question likes because because I think now with social media TV movies all of these things that create empathy across cultures it becomes harder and harder I think I think to totally demonize the other the way it was in previous Wars I also think I don't really see an appetite for people wanting to go to war these days I and in a way I don't know if that's good or bad it's like everybody's so fat and lazy and so concerned with how many clicks they're getting that you know whereas I know at the start of World War one that both the younger generations were eager to go to war you know I think it was it was it was insane but it was that sort of warrior archetype that we were talking about before that that generational testosterone arrows thing wears nowadays I don't know I mean it's hard to say there's not gonna be another war because there always are but it's sort of hard to imagine people getting off their ass these days to do anything well it's funny that you mention social media as the place for empathy sure but it's in a sense that's the place for for war or death from hatred and and perhaps the positive aspects of hatred on social media is that it's somewhat less harmful than murder and so it kind of dissipates sort of the hate folds you get the hate out at yeah and uh you know it'll s yeah on a daily basis and thereby never boils up to a point where you want to kill it's also a really weird thing that's going on I don't know if anybody really understands like with videogames where kids are acting out these incredible horror things right but you know that if they cut their finger they would like freak out I know and and I also don't think that many of the people that are hateful on social media if they were face to face with the horse and they wouldn't so there's a sort of a to to mental spheres happening at the same time and I don't know how that maps that out military how that actually Maps the military yeah yeah it's like when you uni United States have a draft for example what how the populace will respond different than they did in previous generation yeah I think they certainly would yeah another question not sure if you thought about it but I work on building artificial intelligence systems in our community many people worried about AI being used in war so automating the killing process the with with with drones and in general is being used more and more I should recuse myself on that when I really haven't thought about haven't thought about it I'd rather ask you are you thinking well it's interesting I mean because it's so fundamentally different from if you look at the Battle of Thermopylae it means just if we talk about the different scene a gun and a sword I'll tell you one Atlanta coat there was a Spartan King I don't know which one it was but at one point they showed him a new invention and it could launch a bolt that would you know kill someone at a range of 200 yards and the king wept and said alas valor is no more was there a point of view of war it was highly ritualized as you know and the the the code of honor was that you were not supposed to be able to kill another person unless you yourself were an equal danger of being killed and any other way of doing that even bow and arrow was considered less than manly and less than honorable and maybe we should go back to that because at least it makes the stakes real and true and not that we could not not that's the point you were in the Marine Corps so if we talk about the real the bloody conflicts you've written about many of them so let me ask a personal question have you sort of as writing and in general have you thought about what it takes to kill a person if you yourself could do it yeah well not about it yeah and how that would make you feel of course one never knows I certainly I have not been in combat I haven't killed anybody but I would imagine in the real world that it would change you utterly forever because you can't help but identify with a person that you've just killed and it's another human being and I mean I have a hard time killing a spider so I would imagine that it's something that warriors understand and nobody else understands and he's spoken with many how I mean you've spoken with people who seem military combat oh yeah in Israel what have they been able to articulate the the experience of killing it's this sort of just what I said I mean I'm even thinking of one pilot that I interviewed over there who you know was strafing a tank in his Mustang and saw and at really low altitude and you know saw what his bullets did to the guy and could see his face and everything like that which is even you know one remove or more removes from an infantryman when an infantryman does and he said that that same thing that I said that it just changes you and you can never say it they never look at the world or look at anything the same way again and when that happened that scale the thousands the thousands of hundred yeah that changes entire societies that's what we've seen well at least it but the problem is it doesn't change the politicians back home right how important is mortality finiteness the the fact that this thing ends to the creative process so killing in war really emphasizes that but in general the fact that this thing ends gee it does it does shit and I was serious no do you think about your own mortality do you meditate on your own mortality when you think about the work you do other great question Lex actually I'm 75 and I just was having I had breakfast in New York a few months ago with a friend of mine who spiked my exact same age and I said to him I said Nick do you ever think about mortality and he said every fucking minute every day and I was kind of relieved to hear that because I do I do too but I actually I always have I think and I think you know the fact of mortality is kind of gives meaning to life you know I think that's why we want to create that's why we want to make a mark of some kind or and the other aspect of it is what's on the other side of that mortality I'm a believer in previous lives so I I sort of and I the question I've never been able to answer among many many others just like why are we even here right why are we in the flesh you know I sort of I like to believe that God or some force is we're on some kind of journey but I'm not sure why why we were put in this world where the ground rules are if you think about animal life that you cannot live from one day to the next without killing and eating some other form of life and what a demented thing yeah you know why couldn't we just have a solar panel on our head and you know be friends with everybody so I sort of I don't get what that was all about but that's sort of the big issue I have you read the earners Becker's denial of death for example is that Ernest Becker is a philosopher that said that the death that the fear of death is really the primary driver of everything we do so Freud had what the right I would agree with that so did you you've always thought about your even your own mortality yes definitely and can you elaborate on the the reincarnation aspect what you were talking about like that we kind of what's your sense that we had previous lies in what have you thought concretely or is it a lot of it kind of as no I thought can concretely about really I mean it's very clear when you see children young kids or even dogs and cats that they come into the world with personalities you know and three kids and a family are going to become completely different and completely their own person and and and that person that they are doesn't change over life and I you know there's one of the things that I did in my book the artist journey is that there were certain things where I tracked or just listed in order like all of Bruce Springsteen's albums or all of Philip Roth's books you know kind of a body of work throughout over you know a period of 30 40 50 years you know and you can see that there's a theme running through all of those things that it's completely unique to that person nobody else could have written Philip Roth's books or Bruce Springsteen songs and you can even see sort of a destiny there so I asked myself well where did that come from what it's it seems to be a continuation of something that was that happened before and that will lead to something else because it's not starting from scratch it seems like there's a a calling a destiny in there already this gets back to the Meuse and all that kind of thing so yeah it's almost like the there's this let's call it a God it's passing it's almost like sampling parts of a previous human that has lived and putting that those into the new one sampling this is probably a pretty good work that taking some of the good boy you can't take all the good parts because the bad parts is what makes the person right let's say taking all together okay this is humans only does it pass around from animals in your view is they I don't know that's above my pay grade I don't know so okay see you talk about the muse as the source of ideas maybe since you've gotten a few glimpses of her in your writing tell me let me what is it possible for you to tell me about about her where does she reside what does she look like I mean you can look at in many different ways right the Greeks did it in an anthropomorphic way right they created gods or like human beings but if you look at it from a Kabbalistic Jewish perspective Jewish mysticism you could say that it's the solo neshama right that the soul is above us on a higher plane our own your soul my soul and it's trying to reach down to us and and communicate with us and we're trying simultaneously to reach up to it to it through prayer or through if you're a writer or an artist you know when you sit down at the keyboard you're entering into a kind of prayer you're entering into a different state of an altered consciousness to some extent you're opening yourself opening the pipeline or turning on the radio to tune into the cosmic radio station and another way of looking at it this is Anna do you ever see the movie City of Angels the visual of the movie it was meg Ryan and Owen the game yeah I've seen a hip and right the visual of the movies was meg Ryan is a heart surgeon and as she's operating on somebody suddenly Nicolas Cage in this long duster coat like Jesse James appears right next to her in the operating woman he's an angel and he's waiting to take out the soul of the Prairie patient on the on the operating table and she doesn't see him she's totally unaware of him and so is everybody else in the operating room except maybe the guy who's about to die I suddenly sees him but I kind of believe that that there are beings like that or if you don't like that it's a force it's a consciousness it's something that are right here right now and we and they're trying to communicate to us and like through a membrane like tapping on that window over there they're like right out there and they carry the future they are everything that is in potential all the works that you will do Lex your startup whatever else you're doing they they know that and it's not really you that's coming up with those ideas in my opinion those things are appearing you know it's like somebody knocks on the door yeah and puts it in I mean in the Iliad where gods and goddesses appear along with the human antagonists on the battlefield all the time right they'll be you know Homer flashes to Olympus and then back to the real world and there's the thing where one Aphrodite let's say wants to help Paris and so she says well I will appear to him in a dream and I'll take the form of his brother and I'll say bumpety bumpety bump so that's creatures beings on one dimension as the Greek sought communicating with and I believe that that's exactly what's going on in one whatever analogy you want to use that that communication to which degree is do you play the role in that communication as opposed to sitting at the computer if you're a writer and staring at the blank page and putting in the time and waiting what so if in your in your view it is are these creatures basically waiting to tell you about your future or is their choice how many possible futures are there how many possible ideas are that's a great question I think there's basically yes they're all alternatives you know degrees within it but IFIF you look at Bruce Springsteen's albums how much could he have done really differently yeah he would you can just see there's a whole impetus we're going through the whole thing and nothing was gonna shake him off that you know and yeah maybe the river could have been different it could have been called something else but but he was dealing with certain issues his conscious self was dealing with certain issues that were really out of his control he was he was drawn he was called to it right nothing could stop him and so it is sort of a partnership but I think the creative process between the creative impulse that's coming from some other place or it's coming from deep within us is another way to look at it you know it's a like if we are acorns and and we're growing then to Oaks so the conscious bird artist who's sitting there at the keyboard or whatever is applying his or her consciousness to that but is also going into opening themselves to the unconscious or to this other realm whatever whatever that is I mean certainly songwriters for a million years have said you know a song just came in over their head right home just all I had to do is write but then you ever see that thing where of Keats's notes for a thing of beauty is a joy forever it's like covers an entire pay it's like you know he's crossing this out and that out yet so though his consciousness is his conscious mind is working on it but I saw I I do think it's a partnership and I think that I know when I was first starting out as a writer I worked in advertising and I and I tried to do novels that I could never do I was like really unskilled at getting to that tuning into that station I just beat my brains out and was unable to do it you know except and because I was sort of trying too hard it was sort of like a Zen monk or a monk of some kind trying to meditate and just like constantly thoughts driving you crazy but overtime you know not would I've kind of gotten better at it and I can sort of let go of those that part of me that's trying so hard and so these angels can speak a little more easily through the membrane can you put into words the process of letting go and clearing that channel of communication what does it take that's like another great question for me it just took I took probably thirty years and I don't even I would I guess I would liken it to meditation even though I'm not a meditator but it would seem to me to be one of the hardest things in the world to just sit still and stop thinking right and so it's very hard to put into words and I think that's why these teachers of meditation use tricks and cones and stuff like that but for me at least I think it was just a process of years of years and years of trying and finally of beating my head in the wall and finally little by little giving up the bet beating of the the head but this doesn't seem to be any trick everybody wants a tack these days and I don't think there is a hack I look at it in terms of the goddess the muse he's watching you down there beating your head in the ball you're like a marine going through an obstacle course so a martial artist trying to learn you know like uma Thurman during the casket they'll try to make that little for its punch you know the muse or the goddess is just sort of watching on Lexi's turn saying I'm gonna come back in another couple of months and see if he's still there yeah and finally she'll say all right he's had it he's beaten he's paid his dues I'm gonna give it to him so the the hard work and the suffering yep but you know I'm also being Russian uh in wrestling and martial arts were big into drilling technique I was also just even getting at there's certainly there's no shortcut but is there a process so your aunt the practice that can be the process of practice so you had to one yet an example of meditation so it's essentially the practice of meditation is you I think so same drill I think is a good way to look at it too but what do you what are you drilling you're just sitting and you're you're writing you know just writing you're writing your then you're looking at what you wrote you know you're hitting moments when it flows you know and your and your and in your other hitting moments well you just can't do anything and you're trying to from the moments that weren't flowed you're trying to come back and look at and say what what did I do how did it how did that happen or was in my mind you know but I think it's just a process of over and over and over and over until finally it gets a little bit easier and did you did you always when you when you read something you write did you always have a pretty good radar for what's good enough after it's written no I think I do now but but no it was always really hard for me to know what was good I mean do you edit the process of editing is the process of looking at what you've written and improving it are you but a writer or an editor how often do you edit that's another great question great question because I do think that in writing the real process of looking at it is the process that an editor does rather than what a writer does the gentleman I was just talking about the phone is my editor Sean Cohen who was the guy who bought gates of fire when he was an editor at doubleday and who basically when I finish a book I give it to him and he and he gives me you know he he editing doesn't really mean like crossing out commas it really means looking at the overall work and saying does it work and if it doesn't work why doesn't it work is there something wrong here you know like if you were building the Golden Gate Bridge you know and one span was out of whack you know you could and I think a really skilled editor what Sean is understands what what makes a story tick and he also has the perspective that I've lost and something I've wrote because I'm so close to it to say you know this you know this isn't working and that is working what kind of advice is he giving you is it like lay out like this story doesn't flow correctly like it's you shouldn't start at this point or does he even sit back at a higher level and say I see what you're doing but you could do better no he doesn't do that okay but a lot of it is about genre and kind of the defining what genre you're working in and I'm gonna get up here to Jim this was one where Sean tore this down and made me start from scratch and what the the specifics of it were really this is a supernatural thriller that's the genre sort of like Rosemary's Baby or The Exorcist and what he made what he showed me was that I kind of I had violated certain conventions of the genre you know that and you can't do that you know it's got to be you know it has to be done the right way and so he pointed out certain things to me he must be a prolific reader himself - actually that's such an it's a tough job of editor yeah again he was sort of born to do that he just kind of glommed onto it and and but since he was his first job publishing you know cat fur Hillhurst you know cat detective but you know he studied how it works what makes a story work etc etc so he really he's great and I think any really successful writer unless they're utterly brilliant on their own has got to have a great editor behind them but you yourself edit as well I'm constantly trying to learn from him and teach myself everything you see in my blog posts about that it's about the craft of writing is me trying to teach myself the rules so that you know I'm sure it's the same in martial arts or anything else right you you try to not be dependent on that other person because it's so painful to make those mistakes you really feel like god I wish I could get it right the first time the next time I do it well research would go through that in research more than writing so what you do is a little more solitary uh-huh in research there's usually two three four people working on something together and we write a paper and there's that painful process of where you write it down and then you share it with other and not only do they criticize the writing they criticize the fundamental aspects of the approach you've taken I would think so so that's exactly like you know they would say you're attacking you're asking the wrong questions right - yeah and that's extremely you know pay off especially when you it was yes painful and helpful but there's disagreement and so on it's and through that comes out a better product yeah and if is you want to still have an ego but you also want to silence it every once in a while so there's a balance in your book the war of art you talk about resistance with capital R as the invisible force in this universe of ours that finds a way to prevent you from starting or doing the work where do you think resistant comes from why is there force in our mind that's constantly trying to jeopardize our efforts with laziness excuses and so on that's another great question I mean in in Jewish mysticism in Kabbalistic thinking it's called the yetzer Hara right and it's a force that if this up here is your soul of neshama trying to talk to you us down here the answer Harrah's this negative force in the middle so I'm not the only one that ever thought about this but and I don't know if anybody really knows the answer but here's my answer I think that there are two places where we as human beings can seat our identity one is the ego a conscious ego and the other is the greater self and the self in the in the Union sense the self in a Jungian sense includes the unconscious and butts up against what Jung called the divine ground which what I would call the muse the goddess or whatever and I think and the ego is just this little dot inside this bigger self and the ego has a completely different view of of life as from the self the ego believes I'm going to give you a long answer here like no perfect the ego believes that death is real the ego believes that time and space are real the ego believes that each one of us is separate from the other I'm separate from you I could punch you in the face and it wouldn't hurt me it would only hurt you and in the egos world the dominant emotion is fear because we were all made of flesh we can all die we can all be hurt we can all be ruined bumpity-bump so we were protecting ourselves and even our desire to create as we were talking about before comes out of that fear of death the self on the other hand the crater self that butts up against the divine ground believes that death is not real that time and space are not real that the gods travel swiftest thought and the ego also believes that I mean the self believes that there's no difference between you and me that we're all one if I hurt you I hurt myself karma right and in the world of the self of the greater self the dominant emotion is love not fear now so I think that let me I'll go farther back here a long way to answer your question when Jesus died on the cross or when the 300 Spartans willingly sacrificed their lives at Thermopylae they were acting according to the rules of the self death is not real no difference between you and me time and space are not real predominant emotion is love so in my opinion we as conscious human vessels have are in a struggle between these two things the ego and the self to me resistance is the voice of the ego saying and it's a fearful voice because if when we identify with the self we move our consciousness over to the self as as artists or scientists opening ourselves up to the cosmic dimension to the to the other forces the ego is tremendously threatened by that because if we're if we're in that space that headspace we don't need the ego anymore so I think resistance is a voice of the ego trying to keep control of us you there in a way I'll give you a bad example Trump is the ego it's probably a very good example right you know it's a zero-sum world for him yes and for anybody that's in that and the opposite of that would be somebody like Martin Luther King or Gandhi and that's of course why they all wind up getting assassinated because that voice that ego is hanging on to itself and feels so threatened yeah by I could talk more about this if you want to know for sure that that's that's fascinating is just it's interesting why the fear is attached the ego I really like this dichotomy of ego and self and that struggle it's just ego has a you know the the self obsession of it why why fear such a predominant thing like why is resistance trying to undermine everything the it's very here it's out of fear let's think about the whole thing in terms of stories in a story the villain is always resistance is always the ego the hero is is always of course always not everything but you know what I mean pretty much it represents kind of the self if you think about the alien on the spaceship that's like the ultimate kind of villain it keeps changing form right first it goes on the guy's face then it pops out of his chest but it always just has that one monomaniacal thing to destroy you know and just like the ego just like resistance and maybe alien is a bad example because Sigourney Weaver has to sort of fight on the same terms as as the alien but maybe a better example might be something like Casablanca where in the end the Pumphrey Bogart character has to acting operating out of the self has to give up his his selfish dream of going off with Ingrid Bergman Nilsa lund the love of his life and instead you know puts around the plane to Lisbon while he goes off to fight the Nazis and you know in the desert I don't know if that's clear but in a but in almost every story the villain is the ego its resistance is fear is that zero-sum thing and in almost every story the hero is someone that is willing to make a sacrifice to help others it's letting go of that fear is what leads the productivity into success yeah do you think there's a it that's probably the answer is either obvious or impossible but do you think there's an evolutionary advantage to resistance like what would life look like without resistance that sort of that's another great question I think I also believe that resistance like death gives a meaning to life right if we didn't have it it's gonna be you know what would we be we'd be in the Garden of Eden picking fruit and just happy and stupid you know and I do think that that myth of the Garden of Eden is really about this kind of thing you know where where Adam and Eve decide to sort of take matters into their own hands and and acquire knowledge that until then God had said I'm the only one that's got that knowledge and of course once they have acquired that knowledge they're cast out into the world you and I live in now where they do have to deal with that fear and they do have to deal with all that stuff is the human condition the human condition and the meaning and the purpose comes from the resistance being there and the struggle to overcome it the overcoming right that's and also the other aspect of it is that it's not real at all it's not even like it's an actual force it's all here right so the the sort of in a way it's sort of a surrender to it you know you know or like turning on the light in a dark thing it's like it's gone but not quite because it's not quite because it comes back again tomorrow morning exactly so you have to keep changing lightbulbs every day so what's been uh maybe recently but in general maybe you know life what's been the most relentless or one of the more relentless sources of resistance to you personally I mean it's always the same it's about writing for me and an evolving within my own body of work you know it never goes away it never gets any less you have particular excuses particular justifications that come out no it's always the same well I would say it's always its same but it's really not because resistance is so protein you know it keeps changing form and as you as you move to hopefully a higher level resistance gets a little more nuanced and a little more subtle trying to fake you out but I think you learn that it's always there and you're always gonna have to face it so I mean you're but your battle is sitting down and writing to some number Awards to a blank page yeah give a process there with his battle you have a number of hours you put end honestly yeah I'm definitely a a believer that even though this battle is fought on the highest sort of spiritual level that the way you fight it is on the most mundane I'm sure it's like martial arts must be the same way I mean I go to the gym first thing in the morning and I sort of am rehearsing myself faced you know the gym is called resistance training right you're working against resistance right yeah and I don't want to go I don't want to get out of bed I hate that you know so but I'm sort of fortifying myself to to be ready for the day and you know like I said over not would over years I've learned to sort of get into the right kind of mindset and it's not as hard for me as it used to be the real resistance I think for me and I think this is true for anybody is the question of sort of what's the next idea what's the next book what's the next project that you're going to work on and when I when I ask that question I'm sorry I'm asking it of the muse I'm kind of saying what do you want me or I'm asking it up my unconscious if we're looking at Bruce Springsteen's albums it's kind of well what's the next album you know now he's on Broadway that was a great idea right um where'd that come from you know but and then for him what's what's after that you know because that that body of work is already alive it already exists inside us canonical woman's biological clock and we have to serve it and we have to otherwise it'll give us cancer you know I don't mean to say that if anybody has cancer that they're not yeah but you know what I mean it'll it'll do it'll take it's a revenge on us so the next of the resistance to me is sort of well a big aspect of it is what's next you know when I finish the book I'm working on now I'm not sure what I'm gonna do next and I see at the same time you have a kind of you have a sense that there is a Bruce Springsteen single line of albums so like it's it's already known somewhere in the universe what you're going to do next is the sense you have in it in a sense yes I don't know if it's like predetermined you know but it's but there's something like that yeah I'd like to believe that there's uh was this kind of like quantum mechanics I guess once once you observe it maybe once you talk to the muse it's it's it's one thing for sure it was always going to be that one thing but really in reality it's a distribution it could be any number of things yeah I think so there's an alternate reality alternate realities they're not that far apart I mean Bruce Springsteen is not gonna write you know a Joni Mitchell you know no matter how hard he's probably when I'm brought I mean he still did that which is not a Bruce Springsteen thing to do so I think I think you're being in retrospect I think it is making things you know it's a next sort of evolution form why not take his music to there you know in retrospect it all makes sense I think yeah because he if you pull it off especially do you visualize yourself completing the work like Olympic athletes visualize getting the gold medal do you you know they that's they go through I mean that's actually a really you can learn something from athletes on that is um years out certainly two three years awesome some people do much longer everyday you visualize how the day of the the championship will go yet down to I mean everything down to how will it feel to stand on the podium and so on do you do anything like that you know how you approach writing no because no moment because yeah it isn't a moment I think because it's such a mystery you just don't know I think it's different from sports right because you don't know that this thing there's no gold medal do you know in fact I would like to think and that as soon as you finish one the next day you're on the other and in fact hopefully you've already started the other you're already you know one hundred pages into the other when you finish the first one but it is a it is a it's a journey it's a process I don't think it is a in fact I think it's very dangerous to think that way hmm to think oh this I'm gonna win the Oscar you know it's interesting for the creative process it might be dangerous it it's it's a maybe you can like why is it dangerous because I kind of Zoey go it's the e because you're giving yourself over to the ego you know I keep saying this myself my job I'm a servant of the muse I am there to do what she tells me to do and if I've suddenly think oh I'm really I just want to you know whatever news doesn't like that yeah and you know yeah he's on another dimension for me I'm trying to square that cuz I agree I'm trying to square that with I think there's a meditation to visualizing success in the athletic realm to where it focuses it removes everything else away to where you focus on this particular battle I mean I think that you can do that in many kinds of ways and in sports the ego serves a more important role I think than it does in writing any the ego there's something well no let me when you say that I know what you mean Alexa do you think there is a sort of uh you know it's interesting to watch if interviews was with Steph Curry yeah who's such obviously such a nice guy but he's got such tremendous self-confidence you know that it but it doesn't border on ego so much because he's worked so hard for it you know but he knows so he has visualized he has visualized maybe not so much winning you know that as just him being the best he can be him being in the flow you know doing his thing that he knows he can do and I do think in the creative world yeah there is a sort of a thing like that where you were and you know a choreographer or a filmmaker or whatever might be do an internal thing where they're saying I can make an oscar-winning movie I can direct this movie you know I'm banishing these thoughts that I'm not good enough I can do that I can I can edit it I can score it I can you know bump it a month a month but and I don't think that's really ego I think that's that's part of the process in a good way like an athlete does that so extreme confidence is what some of the best athletes come come with and you think it's possible to as a writer to have extreme confidence in yourself I do think so you know that I'm sure when John Lennon sat down to write a song he felt like shit I can do this you know I'm not so sure I I think I think is this the great artist has seen any that you're you're haunted by self-doubt it's that resist I mean the confidence yes but I mean I guess but even beyond the cell and then the cell above the self-doubt I was the biggest organ picks yourself the leaf you know some yeah I'm freaking out yeah I'm worried that I'm not gonna be able to but you know I know I could do this yeah when you look at it when you take a bigger picture yeah so the writing process is it fundamentally lonely so no and because you're with your characters you are so you really put yourself in the world absolutely you know I've written about this before that I used to have my desk used to face a wall instead of seeing and people would say well don't you want to look out the window but I'm I'm in here I mean I'm seeing you know the Spartans I'm seeing you know whatever and the character characters that are on the page or that you create are not accidents you know they're coming out of some issue some deep issue that you have whether you realize it or not you might not realize it till twenty years later or somebody explains it to you so your characters are kind of fascinating to you and their dilemmas are fascinating to you and you're also trying to to come to grips with them you know you sort of see them through a glass darkly you know and you really want to see them more clearly so yeah I know it's not lonely at all fact I'm more lonely sometimes later going out to dinner with some people and actually talking to people do you miss the characters after it's over uh let's say I have I have affection for them kind of like children that have gone off to college and now our you know you only see them at Thanksgiving definitely I have affection for even the bad guys maybe especially the bad guys especially the bad guys you've said that writers even successful writers are often not tough minded enough I've read then post that you have to be a professional in a way you handle your emotions you have to be a bit of a warrior to be a writer so what are what do you think makes a warrior is that as a warrior born or trained in the realm and the bigger realm in the realm of writing in the creative process I think I think they're born to some extent you have the gift like you might have a gift as a martial artist to do whatever martial artists do but the training is the big thing 90% training 10% 10% genetics and you know I use another analogy other than warrior 2 as far as writers and it's like to be a mother if you think about if you're a writer or any creative person you're giving birth to something right you're carrying a new life inside you and in terms of bravery if your child your two-year-old child is underneath a car is coming down the street the mothers are gonna splake stop a Buick you know with their bare hands so that's a that's another way to think about how how a writer has to think about or any creative person has to think about I think what they're what they're doing that what this this child this new creation that they're bringing forth yeah so the hard work that's underlying that have just a couple weeks ago talked to just happen to be in the same room both gave talks Arianna Huffington I did this conversation her I didn't know much about her before before then but she has recently been short a couple books have been promoting a lifestyle where she basically she created a huffington post and she gave herself like I don't know 20 hours a day just obsessed with her work and then she she fainted passed out and kind of uh there was some health issues and so she wrote this book saying that you know sleep basically you want to establish a lifestyle that doesn't sacrifice health that's productive but there's a sec of myself she thinks he can have both productivity and health criticizing Elon Musk who have also spoken with for working too hard and thereby sacrificing you know being less effective than he could be so I'm trying to get at this balance between health and obsessively working at something and really working hard so I'm what Arianna is talking about it make sense to me when I'm a little bit torn to me passion and reason do not overlap much or at all sometimes maybe I'm being too rushing but I feel madness and obsession does not care for health or sleep or diet or any of that and hard work it's hard work and and everything else can go to hell so if you're really focused on whether it's writing a book and it should everything should just go to hell where do you stand on this balance how important is health for productivity how important is it to sort of get sleep and so on I'm from out of the health side yeah I mean there was a period of my life when I was just I had no obligations and I was just living in a little house and just working non-stop you know but even then I would get up in the morning and I would have liver and eggs for breakfast yeah every day and I would do my you know exercise whatever it was but although I was still doing like you know 18 hours a day but I I'm definitely I kind of think of it sort of like an athlete does yeah I'm sure that like Steph Curry is is totally committed to winning championships and stuff like that but he has his family he sees his family you know the family is always there he I'm sure he eats you know perfect great stuff gets to sleep you know gets that the the train you know though whatever a trainer does Silver's knees and ankles and whatever so I or Kobe Bryant or anybody that's a it's operating in a high level so I do think I'm from that kind of the health school the good thing about being a writer is it don't you can't work for many hours a day you know four hours is like the maximum I can work I've never been able to work more than that I don't know how people do it heard of people do ten twelve I don't know how they do it so that gives you a lot of other time to optimize your health yeah because you need to you're in training you know you're you're really you're burning up a lot of B vitamins when you're working here yeah but uh maybe it's a Russian thing with you Lex well it's not even a Russian thing I mean it also may be youth you know at 35 you can be crazy you know this this that they they keep telling me but I'm pretty sure I'll be at it still at a later time too I think it has to do with the career choice too I think writing is most for whatever thing I've heard it's almost impossible to do more than a few hours really well the when you start to get into certain disciplines like oh I'm asking me engineering disciplines that really there's a lot more non muse time meaning mmm right right so the crazy hours of your talk that you often are talking about have to be done mm-hmm and it doesn't I think that's true yeah so there's still the two-three hours of music time needed for truly genius ideas but it's uh it's something it's something I'd certainly struggle with but yeah I I hear you loud and clear on the health so what does the perfect day look like for you if we're talking about writing an hour-by-hour schedule of a perfect day I get up early I go to the gym I have breakfast with some friends of mine I welcome early by the way that's like a how 13 am a.m. so we're talking really really early you know I'm crazy early it's ridiculously early yeah but and I haven't done that always but that's kind of what what what I'm on now so I'm in bed like it when I'm with my my nephews that are like four years old and three years old I'm in bed before them okay um you got a beat you wake up it's a sorry you said exercise first yeah and what does that look like what's exercise for you I go to the gym I have a trainer I have a couple guys that I work out with and I'll you know it's maybe an hour maybe a little more I'll do a little warm-up before of stretching afterwards take a shower go have breakfast but it's an intense kind of a thing that I definitely don't want to do that's hard you know so you feel like you've accomplished something first thing yeah a big accomplishment of the day at the same time it's not like so hard that I'm completely exhausted you know and then I'll come home and handle whatever correspondence and stuff has to be done and then I work for maybe three hours and then I just sort of crash that the office is closed I turn the switch I don't think about any I don't think about anything I don't think about the work at all do you listen to Oh II mean afterwards after work once the office is closed but during so this was like 12 to 3 kind of thing something like that something like that but the you listen to music no if and yes that's just me I mean I don't think you know if somebody could this fast in different ways it's fascinating you know the I mean you've also of most of many writers you've really but like I've heard even Kingston writing is you've optimized this conversation with the muse you're having that optimized but you've at least thought about it so what can you say a little bit more about the trivialities of that process of like you said facing the wall what's do you have little ritual I mean like the granular aspect of granular aspects yeah is there little rituals I do have all kinds of well I'm not even going to tell you I'm sure but the one thing and I don't want to like to talk about this too much because it sort of jinxes things I think but the one thing I I do try to do is when I then when I sit down I immediately get into it first second yeah I don't sit and fuck around with anything immediately try to get into it as as quickly as I can and the other thing is that writing a book or screenplay or anything like that is a process of multiple drafts and it's the first draft that's where you're most with the muse where you're going through the blank page like right now I'm on I don't know what the fifth or sixth seventh draft of some other thing I'm working on so when I'm I've got pages already written and I'm kind of reading them afresh as I as I go through the story so it's not quite where I am now it's not quite a deep muse scenario partly it is but it's also sort of bouncing back and forth between the different between the right brain and the left brain I'm kind of looking at it and trying to evaluate it then I'm going into it and try to change it a little bit when uh do you know sit down do you know the night before of what that starting point is yeah I always try to stop and I learned this I think Hemingway wrote about this or done Steinbeck or one of the or maybe both of them to always stop when you kind of know what's coming next so you're not I'd have facing a chasm you know yeah okay so and afterwards when you're done the office is closed offices closed I let the muse take care of it you know I don't know I don't want to and I think it's a very unhealthy thing to worry about it or think about any creative process you don't I got a long walk later think about yeah if that then I will sort of keep my mind open to it but I won't be like obsessing about it yeah there's a actually on walks sometimes things pop in your head you know and you go oh I should change that but that's not your ego doing it that's a deeper level okay so how does the day end so in terms of writing so yet the writing you know writing the the office door closes and then the rest of the day just do whatever the hell maybe go out to dinner my girlfriend is not here now she's in New York working we'll make dinner or whatever go out to dinner something like that and maybe maybe I'll read something nothing heavy and I go to bed pretty early and um the gym is a big thing for me already if sorry probably would you like with you with martial arts the night before I'll be I'll be visualizing what I have to do the next day and getting myself psyched up for that and then let's conk out like a light and wake up at the crack of dawn so looking out into the future this year next few years what do you think the muse has in store for you I don't think you can ever know it's probably something along the same I really believe you know there's that exercise where you where they say to you visualize yourself five years in the future then write a letter to your from that person to yourself I don't leaving that at all because I don't think you can you know there's a line in Out of Africa that God made the world round so that we couldn't see too far ahead you just don't know as a writer or as a create a person you know I never knew my first book was The Legend of Bagger Vance I hadn't before that happened I had no clue that I was gonna be writing anything like that on that subject anything at all no clue until it just sort of came and then when I when that was done people said well you got to write another I had no idea what it was which was going to be gates of fire no clue so so if somebody'd sat me down at the start of that and asked the question I would have been crazy to say so I just hope as as the future unfolds that I'm open to it you know well I think I speak for a lot of people in saying that we look forward to with that that's thanks so much for talking satisfy yeah it's a great you got the best job in the world going around talking to people that you want to talk to and that they will talk to you you know so thank you for doing hey thank you for the great questions you made me think I've certainly a bunch of questions I never ever answered before awesome so thanks a lot great thanks for listening to this conversation with Steven Pressfield and thank you to our sponsors the Jordan Harbinger show and cash app please consider supporting the podcast by going to Jordan Harbinger complex and downloading cash app and using code Lex podcast click on the links buy the stuff it's the best way to support this podcast if you enjoy this thing subscribe on youtube review it with five stars in a podcast supported on patreon or connect with me on Twitter Alex Friedman spelled without the e just Fr ID ma n and now let me leave you with some words from Steven Pressfield are you paralysed by fear that's a good sign fear is good like self-doubt fear is an indicator fear tells us what we have to do remember one rule of thumb the more scared we are of a work or calling the more sure we can be that we have to do it thank you for listening and hope to see you next time you |
Joscha Bach: Artificial Consciousness and the Nature of Reality | Lex Fridman Podcast #101 | the following is a conversation of Yoshi Bach VP of research at the AI foundation with a history of research positions at MIT and Harvard Yosha is one of the most unique and brilliant people in the artificial intelligence community exploring the workings of human mind intelligence consciousness life on Earth and the possibly simulated fabric of our universe I could see myself talking to Yoshi many times in the future quick summary of the ads to sponsors Express BPM and cash app please consider supporting the podcast by signing up at expressvpn comm slash FlexPod and downloading cash app and using code lex podcast this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars in a podcast supported on patreon or simply connect with me on Twitter at Lex Friedman since this comes up more often than I ever would have imagined I challenge you to try to figure out how to spell my last name without using the letter E and it'll probably be the correct way as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation this show sponsored by expressvpn get it at expressvpn comm slash flexpod to support this podcast and to get an extra three months free on a one-year package I've been using expressvpn from many years I love it I think expressvpn is the best VPN out there they told me to say it but think it actually happens to be true it doesn't log your data it's crazy fast and it's easy to use literally just one big power on button again for obvious reasons it's really important that they don't log your data it works on Linux and everywhere else too shout out to my favorite flavor of Linux Ubuntu mottai 2004 once again get it at expressvpn comm slash FlexPod to support this podcast and to get an extra three months free on a one-year package this show is presented by cash app the number one finance app in the App Store when you get it use code Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is an algorithmic marvel so big props the cash app engineers for taking a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash out from the App Store Google Play and use the collects podcast you get ten dollars in cash wrap will also donate ten dollars to first an organization that is helping advanced robotics and STEM education for young people around the world and now here's my conversation with the OSHA buck as you've said up in a forest in East Germany just as what we're talking about off mic to parents who were artists and now I think at least to me you become one of the most unique thinkers in the AI world so can you try to reverse engineer your mind a little bit what were the key philosophers scientists ideas maybe even movies or just realizations that a impact on you when you're growing up that kind of led to the trajectory or what the key sort of crossroads in the trajectory of your intellectual development my father came from a long tradition of architects distant branch of the family and so basically he was technically a nerd and nerds need to interface in society with non-standard ways sometimes I define a nerd as somebody who thinks that the purpose of communication is to submit your ideas to peer review and normal people understand that the primary purpose of communication is to negotiate alignment and these purposes tend to conflict which means that nerds have to learn how to interact with society at large who is the reviewer in the nerd view of communication everybody who will consider to be a peer so whatever happiest individual is to around well you would try to make him or her the gift of information okay so you're now by the way my research will have Mellon for me so you're architect or artist I study architecture but basically my grandfather made the wrong decision he married an aristocrat and I was drawn into a window into the war and he came back after 15 years so basically my father was not parented by a nerd by but by somebody who tried him tell him what to do and expected him to do what he was told and he was unable to he's unable to do things if he's not intrinsically motivated so in some sense my grandmother broke her son and her son responded by when he became an architect to become an artist so he bought wounded bizarre architecture he built houses without right angles he'd be lots of things that didn't work in more brutalist traditions of eastern Germany and so he bought an old water mill moved out of the countryside and did only what he wanted to do which was art eastern Germany was perfect for p'jem because you had complete material safety put was heavily subsidized Oskar was free you didn't have to worry about rent or pensions or anything so as a socialized communist side yes and the other thing is it was almost impossible not to be in political disagreement with your government which is very productive for artists so everything that you do is intrinsically meaningful because it will always touch on the deeper currents of society of culture and be in conflict visit and tangent visit and you will always have to define yourself and with respect to this so what impact did your father this outside the bar outside the box thinker against the government against the world artists have it was not a thinker he was somebody who only got self-aware to the degree that he needed to make himself functional so in some sense he's it was also late 1960s and he was in some sense a hippie so he became a one-person cult he lived out there in his kingdom he built big sculpture gardens and he started many avenues of art and so on and convinced a woman to live with him she was also an architect and she adored him and decided to share her life with him and I basically grew up in a big cave full of books I'm almost feral and I was bored out there it was very very beautiful very quiet and quite lonely so I started to read and by the time I came to school I've read everything until fourth grade and then some and there was not a real way for me to relate to the outside world and I couldn't quite put my finger on why and today I know it was because I was a nerd obviously and it was the only nerd around so there was no other kids like me and there was nobody interested in physics or computing or mathematics and so on and this village school that I went to was busy in high school kids were nice to me I was not beaten up but I also didn't make many friends or but relationships that only happened and starting from ninth grade when I went to a school for mathematics and physics do you remember any key books from my cigarette everything so I went to the library and I've worked my way through the children's and young adult sections and then I read a lot of science fiction for instance Danny's laflamme basically the great author of cybernetics has influenced me back then I didn't see him as a big influence because everything that he wrote seem to be so natural to me and it's only later that I contrasted it with what other people wrote another thing that was very influential on me were the classical philosophers and also the Tudor of Romanticism so German poetry and art cross two heads off and Heine and up to Heather and so on that's a love Heather so at which point is a classical philosophers end at this point or in the 21st century what's what's the latest classical philosopher does this stretch through even as far as Nietzsche or just I were talking about Plato and there's that one I think that Nietzsche is the classical equivalent of a poster yeah but he's not so much tolling others he's trolling himself because he was at odds with the world largely his romantic relationships didn't work out he got angry and he basically became a nihilist and his nether is not a beautiful way to be isn't until I show it to cast him be trolling yourself to be in that conflict in that no Venice at some point you have to understand the comedy of your own situation if you take yourself seriously and you are not functional it ends in tragedy as I did for Nietzsche by thinking you think he took himself too seriously in the in that tension and as we apply the same thing and in HESA and so on this step involves two enormous classic a dollar sense where you basically feel misunderstood by the world and you don't understand that all the misunderstandings are the result of your own lack of self-awareness because you think that you are a prototypical human and the others around you should behave the same way as you expect them based on your innate instincts and it doesn't work out and you become a transcendentalist to deal with that and so it's very very understandable great sympathies for this to the degree that I can have sympathy for my own intellectual history but out of it was an intellectual a life well-lived a journey well traveled is one where you don't take yourself seriously from now I think that you are neither serious or not serious yourself because you need to become unimportant as a subject that is if you are if a lot of a belief is not a verb you don't do this for the audience you don't do it for yourself you have to submit to the things that are possibly true and you have to follow wherever your inquiry leads but it's not about you and has nothing to do with you so do you think then people like Iran believed sort of an idea of there's a objective truth so GE what's your sense in the philosophical well if you remove yourself a subjective from the picture you think it's possible to actually discover ideas that are true or we just in a measure relative concepts they're an either true nor false it's just a giant mess you cannot define objective truth without understanding the nature of truths in the first place so what does the brain mean by saying that it covers something as truth so for instance a model can be predictive or not predictive then there can be a sense in which a mathematical statement can be tool because it's defined as true under certain conditions so it's basically a particular state that a variable can have an assembled game and then you can have a correspondence between systems and talk about truth which is again a type of model correspondence and that also seems to be a particular kind of ground rules so for instance you're confronted with the enormity of something existing at all right that's standing when you realize something exists rather than nothing and this seems to be true right there is two EPs absolute truth in the fact that something seems to be happening yeah that that to me is a showstopper I could just think about that idea and be amazed by that idea for the rest of my life and not go any farther because I don't even know the answer to that why does anything exist at all well the easiest answer is existence is the default right so this is the lowest number of bits that you would need to encode this whose answer who brought the simplest answer sympathisers that existence is that if what about non-existence I mean that seems non-existence might not be a meaningful notion in the sense so in some sense if everything that can exist exists for something to exist it probably needs to be implementable the only thing that can be implemented as finite automata so maybe the whole of existence is the superposition of all finite automata and we are in some region of the fractal that has the properties that it can contain us what does it mean to be a superposition of fine and vanish superposition of all power like all possible rules imagine that every automaton is basic an operator that acts on some substrate and as a result you get emergent patterns most a substrate is no idea to know so it's based on substrate it's something that can store information something that can store information there is a counter something that can hold state still doesn't make sense to me the why that exists at all I could just sit there with a with a beer or or a vodka and just enjoy effect monitoring the why may not have a why this might be the wrong direction so a skin to this so there could be no relation in in the Y direction without asking for a purpose or for a course it doesn't mean that everything has to have a purpose or cause right so we mentioned some philosophers in that early just taking a brief step back into in today okay so we asked ourselves when did classical philosophy end I think what Germany largely ended was the first revolution that's basically even which was that this was when we ended the monarchy and started a democracy and at this point we basically came up with a new form of government that didn't have a good sense of the this new organism that society wanted to be and in a way it decapitated the universities so the university spent on so modernism like a headless chicken at the same time democracy failed in Germany and we got fascism as a result and it burnt down things in the similar way as Stalinism burnt down intellectual traditions in Russia and Germany boast Germany's have not recovered from this Eastern Germany at this bog or a dialectic materialism and western Germany didn't get much more edgy that Hamas so in some sense both countries lost their intellectual traditions and killing off and driving out Jules didn't help yeah so that was the end that was the end of really rigorous well you would say it's classical classical philosophy is also this thing that in some sense the low-hanging foods in philosophy were mostly wrapped and the last big things that we discovered was the constructivist turn in mathematics so to understand that the parts of mathematics that work are computation it was a very significant discovery in the first half of the 20th century and it hasn't fully permeated philosophy and even physics yet physicists checked out the core libraries from mathematics before constructivism became universal what's constructivist and what are you French girls incompleteness theorems that kind of discuss so it basically girdle himself I think didn't get it yet Hilbert could get it Hilbert saw that for instance a country's set theoretic experiments and mathematics led into contradictions and he noticed that mr. current semantics we cannot build a computer in mathematics that runs mathematics without crashing and a good proof could prove this and so what Google could show is using classical mathematical semantics you run into contradictions and because gödel strongly believed in these semantics and one then in what he could observe and so on he was shocked it basically shook his well to the core because in some sense he felt that the world has to be implemented in classical mathematics and for Turing it wasn't quite so bad I think that you were in could see that the solution is to understand the quest mathematics was computation all along which means you're for instance PI and classical mathematics is a value it's also a function but it's the same thing in a computation a function is only a value of n you can compute it and if you cannot compute the last digit of pi you only have a function you can plug this function into your local Sun let it run until the Sun burns out this is it this is the last digit of pi you will know but it also means that it can be no process in the physical universe or in any physically realized computer that depends on having known the last digit of pi yes which means there are parts of physics that are defined in such a way that cannot strictly be true because assuming that this could be true leads under contrary actions so I think putting computation at the center of the the worldview is actually the right way to think about it yes and Wittgenstein could see it and Wittgenstein basically preempted the largest program of AI that Minsky started later like thirty years later Turing was actually a pupil of Vidkun Stein and really I didn't know there's any connection if it can stand even cancel some classes venturing was not present because he thought it was not worth spending the time if you read the attract address it's a very beautiful book but capacity one salt on 75 pages it's very non typical for philosophy because it doesn't have arguments in it and it doesn't have references in it it's just one thought that is not intending to convince anybody hisses says it's mostly for people that had the same insight as me just spell it out and this insight is there is a way in which mathematics and philosophy ought to meet mathematics tries to understand the domain of all languages by starting with those that are so form Aliza bulette you can prove all the properties of the statements that you make but the price that you pay is that your language is very very simple so it's very hard to say something meaningful in mathematics yes and it looks complicated to people but it's far less complicated than what our brain is casually doing all the time it makes sense of reality and philosophy is coming from the top so it's mostly starting from natural languages which vaguely defined concepts and the hope is that mathematics and philosophy can meet at some point and Wittgenstein was trying to make them meet and he already understood that for instance you could express everything Western and calculus that you could produce the entire logic to NAND gates as we do in all modern computers so in some sense he already understood - and universality before touring spelled it out I think he when he wrote the Tractatus he didn't understand yet that the idea was so important and significant and I suspect then when curing wrote it out nobody cared that much your chewing was not that famous when he lived it was mostly his work in decrypting the German codes that made him famous and or gave him some notoriety but this same status that he has to computer science right now in the eye is something that I think he could acquire later it's kind of interesting and do you think of computation and computer science and you represent that to me is maybe that's the modern-day you in a sense are the new philosopher by sort of the computer scientist who dares to ask the bigger questions that philosophy originally started is the new philosophy is the new philosopher certainly not me I think I mostly the oldest child that grows up in a very beautiful Valley and looks at the world from the outside and tries to understand what's going on and my teachers tell me things and they largely don't make sense right so I have to make my own models I have to discover the foundations of what the others are saying I have to try to fix them to be charitable I try to understand what they must have thought originally or what their teachers or their teachers teachers must have thought until everything are lost in translation and how to make sense of the reality that we are in and whenever I have an original idea I'm usually late to the party by say 400 years and the only thing that's good is that the parties get smaller and smaller the older I get and the more I explore the part the party gets smaller and more exclusive and more exclusive so it seems like one of the key qualities of your upbringing was that you are not tethered whether it's because your parents or in general maybe you're something within your within your mind some genetic material you were not tethered to the ideas of the general populace which is actually a unique property we're kind of throughout you know the education system and whatever from that education system just existing in this world forces certain sets of ideas onto you can you uh disentangle that why were you why are you not so tethered even in your work today you seem to not care about perhaps a best paper in Europe's right being tethered to particular things that current today in this year people seem to value as a thing you put on your CV and resume you're a little bit more outside of that world outside of the world of ideas that people are especially focusing the benchmarks of today the things what can you disentangle that because I think that's inspiring and if there were more people like that we might be able to solve some of the bigger problems that sort of AI dreams to solve and that's a big danger in this because in a way you are expected to marry into an intellectual tradition and visit this tradition into a particular school if everybody comes up with their own paradigms the whole thing is not cumulative as an enterprise right so in some sense you need a healthy balance you need paradigmatic thinkers and you need people that work within given paradigms basically sciences today to find themselves largely by methods and it's almost a disease that we think as a scientist somebody who was convinced by the guidance counselor that they should join a particular discipline and then they find a good mentor to learn the right methods and then they are lucky enough and privileged enough to join the right team and then they will their name will show up on influential papers but we also see that there are diminishing returns with this approach and when our field computer science day I started most of the people that joined this field had interesting opinions and today's thinkers and AI either don't have interesting opinions at all or these opinions are inconsequential for what they actually doing because what they're doing is they apply the state-of-the-art methods with a small epsilon and this is often a good idea if if you think that this is the best way to make progress and for me it's first of all very boring if somebody else can do it why should I do it right if if the current methods of measuring learning lead to strong AI why should I be doing it right well just wait and hold that done and wait until they do this on the beach or read interesting books or write some and have fun but if you don't think that we are currently doing the right thing if we are missing some perspectives then it's required to think outside of the box it's also required to understand the boxes but it's it's necessary to understand what worked and what didn't work and for what reasons so you have to be willing to ask new questions and design new methods whenever you want to answer them and you have to be willing to dismiss the existing methods if you think that they're not going to give the right answers it's very bad career advice to do that so maybe to briefly stay for one more time in the early days one would you say for you was the dream before we dive into the discussions that we just almost started one was the dream to understand or maybe to create human level intelligence born for you I think that you can see AI largely today as advanced information processing if you would change the acronym of AI and to that most people in the field would be happy it would not change anything what they're doing for your automating statistics and when you of the statistical models are more advanced than what statisticians had in the past and it's pretty good work it's very productive and the the other aspect of AI is is philosophical project and this philosophical project is very risky and very few people work on it and it's not clear if it succeeds so first of all let's this is you you keep throwing a sort of a lot of really interesting ideas and I have to pick which ones we cook with but sort of first of all you use the term information processing just information processing as if it's it's the mirror it's the muck of existence as if it's the epitome of a logistic that that the entirety the universe may be information processing it consciousness the intelligence might be information problem so that maybe you can comment on if that's if the advanced information processing is is a limiting kind of realm of ideas and then the other one is would II mean by the philosophical project so I suspect that general intelligence is the result of trying to solve general problems so intelligence I think is the ability to model it's not necessarily goal directed rationality or something many intelligent people are bad at this but it's the ability to be presented with a number of patterns and see a structure in those patterns and be able to predict the next set of patterns right to make sense of things and some problems are very trainable usually Intel serfs control so you make these models for a particular purpose of interacting as an agent with the world and getting certain results but it's the intelligence itself is in the sense instrumental to something but by itself it's just the ability to make models and some of the problems are so general that the system that makes them needs to understand what itself is and how it relates to the environment so as a child for instance you notice you do certain things despite you perceiving yourself as wanting different things so you become aware of your own psychology you become aware of the fact that you have complex structure in yourself and you need to model yourself to reverse-engineer yourself to be able to predict how you will react to certain situations and how you deal with yourself in relationship to your environment and this process if this project if you reverse engineer yourself new relationships or reality in the nature of a universe that can continue if you go all the way this is basically the project of AI or you could say the project of AI is a very important component in it the tutoring test in a way is you ask a system what is intelligence if that system is able to explain what it is how it works then you would should assign it the property of being intelligent in this general sense so the test the Turing was administering in a way I don't think that he couldn't see it but he didn't express it yet and the original 1950 paper is that he was trying to find out other that he was generally intelligent because in order to take this test the wrappers of course you need to be able to understand what that system is saying and we don't yet know if we can build an AI have you don't yet know if you are generally intelligent basically you win the Turing test by building an AI yes so it so in a sense hidden within the Turing test is a kind of recursive test yes it's a test on us yeah the Turing test is basically a test of the conjecture whether people are intelligent enough to understand themselves okay but you also mentioned a little bit of a self-awareness and then the project of AI do you think this kind of emergent self-awareness is one of the fundamental aspects of intelligence so as opposed to goal oriented ease you said kind of puzzle solving is coming to grips with the idea that you're an agent in the world and I find that many highly intelligent people are not very self-aware right so self-awareness and intelligence are not the same thing and you can also be surf aware if you have put priors especially it without being especially intelligent so you don't need to be very good at solving puzzles if the system that you are already implements the solution but I do find intelligence so you kind of mentioned children right it is that the fundamental project of AI is to create the learning system that's able to exist in the world so you kind of drew a difference between self-awareness and intelligence and yet you said that the self-awareness seems to be important for children so I call this ability to make sense of the world and your own place and so to understable make you able to understand what you're doing in this world sentience and I would distinguish sentience from intelligence because sentience is the possessing certain classes of models and intelligence is the way to get to these models if you don't already have them I see so can you maybe pause a bit and try to answer the question that we just said we may not be able to answer and might be a recursive meta question of what is intelligence and I think that intelligence is the ability to make models the models is I think it's useful as examples very popular now neural networks form representations of large-scale data set they they form models of those data sets when you say models and look at today's new all networks what are the difference of how you're thinking about what is intelligent in saying that intelligence is the process of making models two aspects tool to this question one is the representation is the representation adequate for the domain that we want to represent and the other one is is the type of the model that you arrive at adequate so basically are your modeling the correct domain and I think in both of these cases modern AI is lacking stuff and I think that I'm not saying anything new you're not criticizing the field most of the people that design our paradigms are aware of that and so one aspect that you're missing is unified learning when we learned we'd at some point discover that everything that we sends this part of the same object which means we learn it all into one model and we call this model the universe so an experience of the world that we are embedded on it's not a secret direct via to physical reality physical reality is a view at quantum graph that we can never experience or get access to but it has this properties that it can create certain patterns at our systemic interface to the world and we make sense of these patterns and the relationship between the patterns that we discover is what we call the physical universe so at some point in our development is a nervous system we discover that everything that we relate to and in the world it can be mapped to a region in the same three-dimensional space by and large we now know in physics that this is not quite true well it's not actually three-dimensional but the world that we are entangled is at the level of which we are entangled this is largely a flat three-dimensional space and so this is the model that our brain is intuitively making and this is I think what gave rise to this intuition of res extends a-- of this material world this material domain it's one of the mental domains but it's just the class of all models that relate to this environment this v dimension of physics engine in which we are embedded physics engine or embedded i love that phrase it just slowly pause so the the quantum graph i think you called which is the real world which you can never get access to there's a bunch of questions i want to sort of disentangle that maybe one useful one one of your recent talks i looked at can you just describe the basics can you talk about what is dualism what does idealism what is materialism what is functionalism and what connects with you most in terms of because you just mentioned there's a reality we don't have access to okay what does that even mean and why don't we get access to it only part of that one week why can we access it so the particular trajectory that mostly exists in the West is the result of our indoctrination by a card for 2000 years occult which yes the Catholic cause mostly yes and for better or worse right it has created or defined many of the modes of interaction that we have that have best created this society but it has also in some sense scarred our rationality and the intuition that exists if you would translate the mythology of the Catholic Church into the modern world is that the world in which you and me interact is something like a multiplayer role-playing adventure yes and the money and the objects that we have in this world this is all not real or is Eastern philosophers would say it's my eye it's just stuff that is it appears to be meaningful and this embedding in this meaning and people leave in it is samsara this it's basically the identification with the needs of the mundane secular everyday existence and the Catholics also introduced the notion of higher meaning the sacred and this existed before but eventually the natural shape of God is the Platonic form of the civilization that you're part of it's basically the super organism that is formed by the individuals as an intentional agent and basically the Catholics used relatively crude mythology to implement software on the minds of people and get the software synchronized to make them walk in lockstep this basically get they get this got online and you make it efficient and effective and I think our God technically is just itself that spends multiple brains as opposed to your and myself which mostly exists just on one brain right and so in some sense you can construct yourself functionally as a function is implemented by brains that exists across brains and this is a God with a small G that's one of the if you look evil Harare kind of talking about this is one of the nice features of our brains it seems to that we can all download the same piece of software I got in this case and kind of share it yes you give everybody a spec and the mathematical constraints that are in front to information-processing make sure that given the same spec you come up with a compatible structure okay so that's there's the space of ideas that we all share and we think that's kind of the mind and but that's separate from the idea is from from Christianity for from religion is that there's a separate thing between the mind as a real vault and this real world is the world in which God exists God is the quarter of the multiplayer adventure so to speak and we are all players in this game and that's dualism usually but it is because the mental realm is exists in a different implementation than a physical realm and the mental realm is real and a lot of people have this intuition that there is this real room in which you and me talk and speak right now then comes a layer of physics and abstract rules and so on and then comes another real room where our souls are and our tool form isn't the thing that gives us phenomenal experience and this of course a very confused notion that you would get and it's basically it's the result of connecting materialism and idealism in the wrong way so okay I apologize but I think it's really helpful if we just tried to define try to define terms like what is joules and what is idealism what is materialism for people done' so the idea of dualism and our cultural tradition is that there are two substances a mental substance and a physical substance and they interact by different rules and the physical world is basically causally closed and is built on a low level causal structures or the bezier bottom level that is causally closed it's entirely mechanical and mechanical in the widest sense so it's computational there's basically a physical world in which information flows around and physics describes the laws of how information flows around an adult would you compare it to like a computer where you have a hardware and software the computer is a generalization of information flowing around basically but join discovered that there is genuine universal principle you can define this Universal machine that is able to perform all the computations so all these machines have the same power this this means that you can always define a translation between them as long as they have unlimited memory to be able to perform each other's computations so would you then say that materialism is this whole world is just the hardware and idealism is this whole world is just a software why I think that most idealists don't have a notion of software yet because software also comes down to information processing right so what you notice is the only thing that is real to you and me is this experimental world in which things matter in which things have taste in which things of color phenomenal content and so on and you are bringing up consciousness okay and this is distinct from the physical world in which things have values in only in an abstract sense and you only look at cold patterns moving around so how does anything feel like something in this connection between the two things is very puzzling to a lot of people of course to many philosophers so idealism starts out with the notion that mind is primary materialism thinks that matter is primary and so for the idealist the material patterns that we see a play in playing out a part of the dream that the mind is dreaming and we exist in the mind on a higher plane of existence if you want and for the materialist there is only this material thing and that generates some models and via the result of these models and in some sense I don't think that we should understand if you understand it properly materialism and idealism is a dichotomy but there's two different aspects of the same thing so the via thing is we don't exist in the physical world we do exist inside of a store way that the brain tells itself ok that's it let me uh let my my my information processing I take they take that in we don't exist in the physical world we exist in the narrative basic your brain cannot feel anything New York cannot feel anything they're physical things physical systems are unable to experience anything but it would be very useful for the brain or for the organism to know what it would be like to be a person and to feel something yeah so the brain creates a simulacrum of such a person that it uses to model the interactions of the person's the best model of what that brain this organism thinks it is in relationship to its and so it creates that model it's a story a multimedia novel that the brain is continuously writing and updating but you also kind of said that you said that we kind of exist in the head and that's alright yes that story yeah what is real in any of this so like there's a again these terms are you kind of said there's a quantum graph I mean what is what is this whole thing running on then is this story and is it completely fundamentally impossible to get access to it because isn't the story supposed to is in the brain in a in something in existing in some kind of context so what we can identify as computer scientists we can engineer systems and test our theories this way that may have the necessary and sufficient properties to produce the phenomena that you're observing which is there is itself in a virtual world that is generated in somebody's neocortex who that is contained in the skull of this primate here and when I point at this this indexicality is of course wrong but I do create something that is likely to give rise to patterns on your retina that allow you to interpret what I'm saying right but I both know that the world that you and me are seeing is not the real physical world what we are seeing is a virtual reality generated in your brain to explain the patterns on your retina how close is it to the real world that's kind of the the question is it when you have when you have like people like Donald Hoffman let's say that like that you're really far away the thing we're seeing you and I now that interface would have it's very far away from anything like we don't even have anything close like to the sense of what the real world is or is it a very surface piece of architecture imagine you look at the Mandelbrot fractal right this famous thing that when a man would discover deadlines if you're you see an overall shape and they're right but you know if you truly understand it you know it's two lines of quote it's basically in a series that is being tested for complex numbers and in the complex number plane for every point and for those for this year is is diverging you paint this black and where it's converging you don't and you get the intermediate colors by taking how far it diverges yes right this gives you this shape of this fractal but imagine you live inside of this fractal and you don't have access to where you are in the fractal or you have not discovered the generator function even right so what you see is all of all I can see right now is the spiral and the spiral moves a little bit to the right is this an accurate model of reality yes it is right it is an adequate description is you know that there is actually no spiral and the mailboat fractal it only appears to like this to an observer that is interpreting things as a two-dimensional space and then define certain regularities in there at a certain scale that currently observes because if you zoom in the spiral might disappear and turn out to be something different at the different resolution right yes so at this level you have the spiral and then you discover the spiral moves to the right and some point it disappears so you have a singularity at this point your model is no longer valid you cannot predict what happens beyond the singularity but you can observe again and you will see it is another spiral and at this point it disappeared so maybe we now have a second-order law and if you make 30 layers of these laws then you have a description of the world that is similar to the one that we come up with when we describe the reality around us it's reasonably predictive it does not cut to the core of it so you explain how it's being generated how it actually works but it's relatively good to explain the University of your entangled fence but you don't think the tools are computer sizes the tools of physics could get could step outside see the whole drawing and get at the basic mechanism of how the pattern the spiral is generated imagine you would find yourself embedded into a mother but Franklin you try to figure out what works and you you know somehow have a throwing machine there's enough memory to think and as a result you've come to this idea it must be some kind of automaton and maybe you just enumerate all the possible automata until you get to the one that produces your reality so you can identify necessary and sufficient condition for instance we discover that mathematics itself is the domain of all languages and then we see that most of the domains of mathematics that we have discovered are in some sense describing the same this is what category theory is obsessed about that you can map these different domains to each other so they're not that many fractals and some of these have interesting structure and symmetry breaks and so you can just cover what region of this global fractal you might be embedded in from first principles yes but the only way you can get there is from first principles so basically your understanding of the universe has to start with automata and the number theory and then spaces and so on yeah I think like Stephen Wolfram still dreams that he's it that he'll be able to arrive at the fundamental rules of the cellular automata or the generalization of which is behind our universe yeah it's you've said on this topic you said in a recent conversation that quote some people think that a simulation can't be conscious and only a physical system can but they got a completely backward a physical system cannot be conscious only a simulation can be cautious yeah consciousness is a simulated property that's simulate itself yeah just like you said the mind is kind of the call it story narrative there's a simulation or our mind is essentially a simulation and usually I try to use the terminology so that the mind is basically a principles that produce the simulation it's the software that is implemented by your brain and the mind is creating both the universe that we are in and the self the idea of a person that is on the other side of attention and is embedded in this world why is that important that idea of a self why is that an important feature in simulation it's basically a result of the purpose that the mind has it's a tool for modeling right we are not actually monkeys via side effects of the regulation needs of monkeys and what the monkey has to regulate is the relationship of an organism to an outside world that is a large part also consisting of other organisms and as a result it basically has regulation targets that it tries to get to this regulation target start with priors they're basic like unconditional reflexes that we are more less born with and then we can reverse-engineer them to make them more consistent and then we get more detailed models about how the world works and how to interact with it and so these priors that you commit to are largely target values that our needs should approach set points and this deviation to the set point creates some urge some tension and we find ourselves living inside of feedback loops right consciousness emerges over dimensions of disagreements with the universe things that you care things are not the way there should be but you need to regulate and so in some sense the sense self is the result of all the identifications that you're having an identification is a regulation tracker that you're committing to it's a dimension that you care about do you think is important and this is also what locks you in if you let go of these commitments of these identifications you get free there's nothing that you have to do anymore and if you let go of all of them you're completely free and you can enter Nirvana because you're done and actually this is a good time to pause and say thank you to sort of a friend of mine Gustav's or Ostrom who introduced me to your work I wanted to give him a shout out he's a brilliant guy and I think the AI community is actually quite amazing and Gustav is a good representative that you are as well some I'm glad first of all I'm glad the internet exists you - who's this where I can watch your talks and then get to your book and study your writing and think about you know that's that's amazing okay but the you've kind of described instead of this emergent phenomena of consciousness from the simulation so what about the hard problem of consciousness the can you just linger on it like but why this is still feel like I understand you're kind of the self is an important part of the simulation but why does the simulation feel like something so if you look at the book by say george RR martin with the characters have plausible psychology yeah and they stand on a hill because they want to conquer the city below the hill and they've done in it and then look at the color of the sky and they are Princip and feel empowered and all these things why do they have these emotions it's because it's written into the story right and threatened with the story because it's an adequate model of the person that predicts what they're going to do next and the same thing is helpful it's basically a story that our brain is writing it's not written in words it's written in perceptual content basically multimedia content and it's a model of what the person would feel if it existed so it's a virtual person and you and me happen to be this virtual person so if this virtual person gets access to the language center and talks about the sky being blue and this is us but hold on a second do I exist in your simulation you do exist even almost similar way as me so there are internal states that I that are less accessible for me in that you have and so on and you're my model might not be completely adequate there are also things that I might perceive about you that you don't perceive but in some sense both you and me are some puppets - puppets that enact this play in my mind and I identify with one of them because I can't control one of the puppet directly and with the other one I can create things in between so for instance we can go or in an interaction that even leads to a coupling to a feedback loop so we can sync things together in a certain way or feel things together but this coupling is itself not a physical phenomena entirely a software phenomenon it's a result of two different implementations interacting with each other so this is thing so are you suggesting I did like the way you think about it is the entirety of existence simulation and we're kind of each mind is a little sub simulation that like why don't you why doesn't your mind have access to my mind's full state like for the same reason that my mind hasn't have access to its own full state so what I mean there is no trick involved so basically when I say know something about myself it's because I made a model yes of your brain is tasked with modeling what other parts of your brain are doing yes but there seems to be an incredible consistency about this world in the physical sense that is repeatable experiments and so on yeah how does that fit into our silly the center of apes sim you of the world so why is it some repeat why is everything so repeatable and not everything there's a lot of fundamental physics experiments that are repeatable for a long time all over the place and so on laws of physics how does that fit in it seems that the parts of the world that are not deterministic are not long-lived so if you build a system any kind of automaton so if you build simulations of something you'll notice that the phenomena that endure are those that give rise to stable dynamics so basically if you see anything that is complex in the world it's the result of usually of some control of some feedback that keeps it stable around certain attractors and the things that are not stable that don't give rise to certain harmonic patterns and so on they tend to get weeded out over time so if we are in a region of the universe that sustains complexity which is required to implement Minds like ours this is going to be a region of the universe that is very tightly controlled and controllable so it's going to have lots of interesting symmetries and also symmetry breaks that allow the creation of structure but they exist where so there's such an interesting idea that our - simulation is constructing the narrative but my question is just to try to understand how that fits with this with the entirety of the universe you're saying that there's a region of this universe that allows enough complexity to create creatures like us but what's the connection between the the brain the mind and the broader universe which comes first which is more fundamental is the is the mind the starting point the universe is emergent is the universe the starting point the minds are emergent I think quite clearly the letter it's at least a much easier explanation because it allows us to make causal models and I don't see any way to construct an inverse cos allottee so what happens when you die to your mind simulation my implementation ceases so basically the thing that implements myself will no longer be present it means if I am NOT implemented on the minds of other people to think that I identify this is the weird thing is I don't actually have an identity beyond the identity that I construct if I was the Dalai Lama he identifies as a form of government so basically the dad Adama gets reborn not because he is confused but because he is not identifying as a human being he runs on a human being he's basically a governmental software right that is instantiated in every new generation in you so his advisors will pick someone who does this in the next generation so if you identify as this you are no longer human and you don't die and essentially what dies is only the body of the human that you ran on here to kill the Dalai Lama you would have to kill his tradition and if we look at ourselves we realized that we are to a small part like this most of us so for instance if you have children you realize something lives on in them or if you spark an idea in the world something lives on or if you identify it as a society around you because you are part that you are not dressed this human being yes so in a sense you are kind of like a Dalai Lama and since that you Jascha Bach is just a collection of ideas so like you have this operating system on which is a bunch of ideas live and interact and then once you die they kind of part some of them jump off the should it put it the other way identity is a software state it's a construction it's not physically real identity is not a physical concept it's basically a representation of different objects on the same world line but identity let lives and eyes are you attached this is it's what's the fundamental thing is that the ideas that come together to form identity or is each individual identity actually a fundamental thing it's a representation that you can get agency over if you care so basically you can choose what you identify best if you want to nobody just seems if if the mind is not very real it's not that the the birth and death is not a crucial part of it well maybe I'm silly maybe I'm attached to this whole biological organism but it's that the physical being a physical object in this world is is a an important aspect of birth and death like it feels like it has to be physical to die it feels like simulations don't have to die the physics that we experience is not the real physics that explains is no color and sound in the real world color and sound are types of representations that you get if you want to model reality with oscillators right so colors and sound in some sense have octaves yes and it's because they are represented probably with oscillators right so that's why colors form a circle of views and colors have harmonic sounds have harmonics is a result of synchronizing oscillators in in the brain right so the world that we subjectively interact with is fundamentally the result of the representation mechanisms in our brain they are mathematically to some degree Universal they are certain regularities that you can discover in the patterns and not others but the patterns that we get this is not the real world the world that we interact with is always made of too many parts to count right so when you look at this table and so on it's consisting of so many more molecules and atoms that you cannot count them so you only look at the aggregate dynamics at limit dynamics if you had almost infinitely many patterns of particles what would be the dynamics of the table and this is roughly what you get so geometry that we are interacting this is the result of discovering those operators that work in the limit that you get by building an infinite series that converges for those parts where it converges its geometry for those parts or a dozen convergence chaos right and then so all that is filtered through with the cuts of the consciousness that's emergent in our narrative the the consciousness gives it color gives a feeling gives it flavor so I think the feeling flavor and so on is given by the relationship that a feature has to all the other features it's basically a giant relational graph that is our subjective universe the color is given by those aspects of the representation or the this experiential color where you care about but you have identifications but something means something where you are the inside of a feedback loop when the dimensions of of caring are basically dimensions of this motivational system that we emerge over the the meaning of the relations the graph can you elaborate that a little bit like where does the maybe we can even step back and ask the question of what is consciousness to be sort of more systematically what what what do you how do you think about consciousness consciousness is largely a model of the contents of your attention it's a mechanism that has evolved for a certain type of learning at the moment of a machine learning systems we largely work by building chains of weighted sums of real numbers with some non-linearity and you will learn by typing an error signal so these different chained layers and adjusting the weights in this way that Samms and you can approximate most polynomials if you have enough training data but the prices you need to change a lot of these weights basically the error is piped backwards into the system until it accumulates at certain junctures in the network and everything else evens out statistically and only at these junctures this is where you had the actual error in the network you make the change there this is a very slow process and our brains don't have enough time for that because we don't get old enough to play go the way that our machines learn to play go so instead what we do is an attention based learning we pinpoint the probable region in the network where we can make an improvement and then we store the this binding state together with the expected outcome in a protocol and there's ability to make index memories for the purpose of learning to revisit these commitments later this requires an memory of the contents of our attention another aspect is when I construct my reality and make mistakes so I sees things that turn out to be reflections or shadows and so on which means I have to be able to point out which features of my perception gave rise to a present construction of reality so the system needs to pay attention to the earth features that are currently in its focus and it also needs to pay attention to whether it pays attention itself in part because the attentional system gets trained is the same mechanism so it's reflexive but also in part because your attention lapses if you don't pay attention to the attention itself all right so it's this thing that I'm currently seeing just a dream that my brain has spun off into some kind of daydream or am I still paying attention to my percept so you have to periodically go back and see whether you are still paying attention and if you have this loop and you make it tight enough between the system becoming aware of the contents of its attention and the fact that it's paying attention itself and makes attention the object of its attention I think this is the loop over which if you wake up so there's this so there's this attentional mechanism that's somehow self referential that's fundamental to what consciousness is mm-hmm so just uh ask you a question I don't know how much you're familiar with the recent break there is a natural English processing they use attentional mechanisms used something called transformers to learn patterns and sentences by allowing a network to focus its attention to particular parts of a sentence at each individual so like parameterize and make it learn about the dynamics of a sentence by having like a little window into the into the sentence do you think that's like a little step towards that eventually would will take us to the intentional mechanisms from which consciousness could emerge not quite I think it models only one aspect of attention in the early days of automated language translation there was a example that I found particularly funny where somebody tried to translate a text from English into German and it was a bet broke the window and the translation in German was eine Fledermaus it's a practice Fenster MIT einem baseball schlager so to translate it back into English a bet the this flying mammal broke the window with a baseball bat yes and it seemed to be the most similar to this program because it somehow maximized the possibility of translating the concept bat into German in the same sentence and this is some a mistake that the Transformer model is not doing because it's tracking identity and the attentional mechanism in the Transformer model is basically putting its finger on individual concepts and make sure that these concepts pop up later in the text yeah and tracks basically the individuals through the text and it's why the system can learn things that other systems couldn't before it which makes the for instance possible to write a text where it talks about the scientist then the scientist is a name and has a pronoun and it gets a consistent story about that thing what it does not do it doesn't fully integrate this so his meaning falls apart at some point it loses track of this context it does not yet understand that everything that it says has to refer to the same universe and this is where this thing falls apart but the attention in transformer model does not go beyond tracking identity and tracking identity is an important part of attention but it's a different very specific attentional mechanism and it's not the one that gives rise to the type of consciousness that they have okay just to linger I know what what do you mean by identity in the context of language so when you talk about language that you have different words that can refer to the same concept got it and in the sensor concepts so yes and it can also be in a nominal sense or an indexical sense that you say yeah this word does not only refer to this class of objects but it refers to a definite object to some kind of agent that waves their way to through the story and it's only referred by different ways in the language so the language is basically a projection from a conceptual representation from a scene that is evolving into a discrete string of symbols and what the transformer is able to it learns aspects of this projection mechanism that other models couldn't learn so have you ever seen an artificial intelligence or any kind of construction idea that allows for unlike neural networks or perhaps within your networks it's able to form something where the space of concepts continues to be integrated so the way you're describing building an all knowledge base building this consistent larger and larger sets of ideas that would then allow for a deeper understanding of it concerns thought that we can build everything from language from basically a logical grammatical construct and I think to some degree this was also what Minsky believed so that's why I focus so much on common sense reasoning and so on and project that was inspired by him both psyche um there was special going on yes of course ideas don't die only people die and that's true but in doubt psyche is a productive project it's just probably not one that is going to converge to general intelligence the thing that Wittgenstein couldn't solve and he looked at this in his book at the end of his life philosophical investigations was the notion of images so images play an important role in track titles the Tractatus an attempt to basically turn philosophy into logical probing language to design a logical language in which you can do actual philosophy that rich enough for doing this and the difficulty was to deal with perceptual content and eventually I think he decided that he was not able to solve it and I think this preempted the failure of the logit his program in AI in the solution as we see it today is we need more general function approximation there are functions geometric functions that we learn to approximate that cannot be efficiently expressed and computed in a grammatical language can of course build automata that go via number theory and so on and to learn linear algebra and then compute an approximation of this geometry but to equate language and geometry is not an efficient way to think about it so functional is well you kind of just said then you'll now work sir the sort of the approach in you all know this takes is actually more general than the then what can be expressed through language yes so what can be efficiently expressed through language at the data rates at which we process grammatical language okay so you don't think so you don't think languages so you disagree with Wittgenstein that language is not fundamental - I agree with commit constrain it I just agree with the late Wittgenstein and I also agree with the beauty of the early Wittgenstein I think that the Tractatus itself is probably the most beautiful philosophical text that was written in the twentieth century but but language is not fundamental to cognition and intelligence and consciousness so I think that language is a particular way or the natural language that we're using is a particular level of abstraction that we used to communicate with each other but the languages in which people express geometry are not grammatical languages in the same sense so they work slightly different they're more general expressions of functions and I think the general nature of a model is you have a bunch of parameters these are have arranged it as these are the variances of the world and you have relationships between them which are constraints which say if certain parameters have these values then other parameters have to have the following values and this is a very early insight in computer science and I think the some of the earliest formulations is the Boltzmann machine and the problem is the Boltzmann machine is that it has a measure of whether it's good this is basically the energy on the system the amount of tension that you have left and the constraints where the constraints don't quite match it's very difficult to despite having this global measure to train it because if yes as soon as you add more than trivially fuel elements parameters into the system it's very difficult to get it settle in the right architecture and so we the solution that Hinton and Sinofsky found was to use a restricted Boltzmann machine which uses the hidden links the internal links and in the Boltzmann machine and only has based the input and output layer but this limits the Express ativy Civet e of the boltzmann machine so now he builds a network of small of these primitive Boltzmann machines and in some sense you can see a almost continuous development from this to the deep learning models that we are using today even though we don't use Boltzmann machines at at this point but the idea of the Boltzmann machine is you take this model you clamp some of the values to perception and this forces the entire machine to go into a state that is compatible with the states that you currently perceive and this state is your model of the world right so I think it's a very general way of thinking about models but we have to use a different approach to make it work this is we have to find different networks that train the Boltzmann machine so the mechanism that trains the Boltzmann machine and the mechanism that makes the Boltzmann machine settle into its state are distinct from the constrained architecture of the Boltzmann machine itself the the kind of mechanism we want to develop yes so this the direction in which I think our research is going to go is going to for instance what you notice in perception is our perceptual models of the world are not probabilistic but possible istic which means with them you should be able to perceive things that are improbable but possible right the sexual State is valid not if it's probable but if it's possible if it's quite coherent yeah so if you see a tiger coming after you should be able to see this even if it's unlikely and the probability is necessary for convergence of the model so given the state of possibilities that is very very large and a set of perceptual features how should you change the state of states of the model together to convert with your perception but the space of the space of ideas that are coherent with the context that you're sensing is perhaps not as large I mean that that's perhaps pretty small the degree of coherence that you need to achieve depends of course how deep your models goal is for instance politics is very simple when you know very little without game theory and human nature so the younger you are the more obvious is how politics should work right yes and because you get in a Korean aesthetics from relatively few inputs and the more layers you model them add more layers you model reality the harder it gets to satisfy all the constraints so you know the current neural networks are fundamentally supervised learning system with the feed-forward neural network is back propagation to learn what's your intuition about what kind of mechanisms might we move towards to improve the learning procedure I think one big aspect is going to be meta learning and architecture search starts in this direction in some sense the first wave of AI classical a I work by identifying a problem into the possible solution and implementing the solution right program that plays chess and right now we are in the second wave of AI so instead of writing the algorithm that implements the solution revise an algorithm that automatically searches for an algorithm that implements the solution so the learning system in some sense is an algorithm that itself discovers the algorithm that solves the problem or goes too hard to implement it by dissolution by hand but we can implement an algorithm that finds the solution yes so now let's move to the third stage right the third stage would be meta-learning find an algorithm that discovers the learning algorithm for the given domain our brain is probably not a learning system but a meta learning system this is one way of looking at what we are doing there is another way if you look at the way our brain as for instance implemented there is no central control that tells all the new ones how to wire up yes instead every neuron is an individual reinforcement learning agent every neuron is a single-celled organism that is quite complicated and in some sense quite motivated to get fed and it gets fed if it fires on average at the right time yes auntie the right time depends on the context that the neuron exists in which is the electrical and chemical environment that it has so it basically has to learn a function over its environment that tells us when to fire to get fat or if you see it as a reinforcement learning agent every neuron is in some sense making a hypothesis when it sends a signal it tries to pipe a signal through the universe and tries to get positive feedback for it and the entire thing is set up in such a way that it's robustly self-organizing into a brain which means you stride out with different neuron types that have different priors in which hypothesis to test on how to get its reward and you put them into different concentrations in a certain spatial alignment and then you entrain it in a particular order and as a result you get develop a nice brain yeah so okay so the brain is a meta learning system with a bunch of with reinforcement learning agents and what I think you said but just to clarify where do the LA there's no centralized government that tells you here's a loss function here's a loss function here's a loss function like what who is who says what's the also governments which impose loss functions on different parts of the brain so we have differential attention some areas in your brain get especially rewarded when you look at faces if you don't have that you will get post of agnosia which basically mean the inability to tell people apart by their faces so and the reason that happens is because it was had an evolutionary advantage like evolution comes in a play here about it's basically an extraordinary attention that we have for faces I don't think that people were supposed to up no see I have Percy a defective brain the brain just has an average attention for faces so people were supposed of agnosia don't look at faces more than they look at cups so the level at which they resolve the geometry of faces is not higher than the one that then four cups and people that don't have prosopagnosia looked obsessively at faces right for you and me it's impossible to move through a crowd without scanning the faces and as a result we make insanely detailed models of faces that allow us to discern mental states of people so obviously we don't know 99% of the details of this meta learning system that's our mind okay but still we took a leap from something much dumber to that from love through the evolutionary process can you first of all maybe say how hard these how big of a leap is that from our brain from our a branch asters to multi cell organisms and is there something we can think about about as we start to think about how to engineer intelligence is there something we can learn from evolution in some sense life exists because of the market opportunity of controlled chemical reactions we compete with some chemical reactions and we win in some areas against this damp combustion because we can harness those entropy gradients where you need to add a little bit of energy in a specific way to harvest more energy so we are competing combustion yes in many regions we do and we try very hard because when we under ekam petition we lose right yeah so because the combustion is going to close the entropy gradients much faster than we can run yes you gotta quit so I probably am yeah so basically to this because every cell has a Turing machine built into it it's like literally a read/write head of the tape and so everything that's more complicated than a molecule that just is a vortex around attractors that needs the Turing machine in it for its regulation and then you bind cells together and you get next level organization or organism where the cells together implement some kind of software and for me very interesting discovery in the last year was the word spirit because I realized that what spirit actually means it's an operating system for an autonomous robot and when the word was invented people needed this word but they didn't have robots that they built themselves yet the only autonomous robots that were known were people animals plants ecosystems cities and so on and they all had spirits and it makes sense to say that the plant is an operating system right if you pinch the plant in one area then there's going to have repercussions throughout the plant everything in the plant is in some sense connected into some global aesthetics like in other organisms an organism is not a collection of cells is a function that tells cells how to behave and this function is not implemented as some kind of supernatural thing like some more for genetic field it is an emergent result of the interactions of the each service each other cell all right so you're you're saying is the organism is a function that tells what's what what now that the cell sells what to do and the function is an emerging the interaction of the cells yes so it's basically a description of what the plant is doing in terms of macro States and the micro States the physical implementation are too many of them to describe them so the software that we use to describe what the plant is doing the spirit of the plant is the software the operating system of the plant right this is a way in which V the observers make sense of the plant yes okay same is true for people so people have spirits which is their operating system in a very rightness aspects of that operating system that relate to how your body functions and others how you socially interact or you interact with yourself and so on and we make models of that spirit and we think it's a loaded term because it's from a pre-scientific age but we it took the scientific age a long time to rediscover a term that is pretty much the same thing and I suspect that the difference is that we still between the old world and the new world our translation errors over the centuries but can you actually link around that like well why do you say that spirit just to clarify because I'm a little bit confused so the the word spirit is a powerful thing but why did you say in the last year or so they discovered this do you mean the same old traditional idea of a spirit or Jamie I try to find out what people mean by spirit when people say spirituality in the u.s. it usually is the refers to the phantom limb that they developed in the absence of culture and a culture is in some sense you could say the spirit of a society that is long game this thing that it's become self-aware at a level above the individuals where you say if you don't do the following things then the grand crying crying when children of our children will not have nothing to eat yeah so if you take this long scope where you try to maximize the length of the game that you are playing as a species to realize that you're part of a larger thing that you cannot fully control you probably see to submit to the ecosphere instead of trying to completely control it right there needs to be a certain level at which we can exist as a species if you want to endure and our culture is not sustaining this anymore we basically made this bet with the Industrial Revolution that we can control everything and the modernist societies was basically unfettered growth led to a situation in which we depend on the ability to control the entire planet and since we are not able to do that as it seems this culture will die if we realize that it doesn't have a future right we called our children generations that it's not very optimistic things yeah you can have this kind of intuition that our civilization you say culture but you really mean this the spirit of the civilization do in the entirety the civilization may not exist for long yeah so what can you kion tangle that what's your intuition behind that so you you kind of offline mentioned to me that the Industrial Revolution was kind of a the moment we agreed to accept the offer sign on the paper on the dotted line with the Industrial lucien we doomed ourselves can you elaborate and this is suspicion i of course don't know how it plays out but gosh it seems to me that in society in which you leverage yourself very far over an entropic a piss without land on the other side it's relatively clear that your cantilevers at some point going to break down into this entropic abyss and you have to pay the bill okay russia is my first language and i'm also an idiot this is just two apes instead they're playing with the banana trying to have fun by talking okay and throbbing what in what's anthropic and tropic and drop and and so n tropic in the sense of entropy and all entropic that yes so this end and tropical oils the other word you have this what's that it's a big porch abyss abyss yes and tropic abyss so many of the things you say are poetic it's and often rings meb's amazing right it's miss Burrell which makes you do more poetic Wittgenstein would be proud so entropic abyss okay let's let's rewind then the Industrial Revolution so how does that get us into the entropic abyss so in some sense we burned a hundred million years worth of trees to get everybody plumbing yes and the society that we had before that had a very limited number of people so basically since 0 BC we hovered between 300 and 400 million people yes and this only changed with the Enlightenment and the subsequent Industrial Revolution and in some sense the Enlightenment a feat of rationality and also freed our norms from the pre-existing order gradually it was an process that basically have been feedback loop so it was not that just one cost the other it was a dynamic that started and the dynamic worked by basically increasing productivity to such a degree that we could fit all our children and I think the definition of property is that you have as many children as you can feed before they die which is in some sense the state that all animals on earth are in the definition of poverty is having enough so you can have only so many children as you can feed and if you have more they die yes and in our societies you can basically have as many children as you want they don't die right so I the reason why we don't have as many children as we want us because we also have to pay a price in terms of you have to insert ourselves in the lowers also tritonus yeah if you have too many so basically everybody in the under middle and lower upper class has only a limited number of children because having more of them would mean a big economic hit to the individual families yes because children especially in u.s. super expensive to have and you only are taken out of this if you are basically super rich or if you are super poor if you're super poor it doesn't matter how many kids you have because your status is not going to change and these children are largely not going to die of hunger so how does this leads us just self-destruction so there's a lot of unpleasant properties about this process so basically what we try to do is we try to let our children survive even if they have diseases it's like I would have died and before my mid-twenties without modern medicine and most of my friends would have as well and so many of us wouldn't live without the advantages of modern medicine and modern industrialized society we get our protein in largely by subduing the entirety of nature imagine there would be some very clever microbe that would live in our organisms and would completely harvest them and change them into a thing that is necessary to sustain itself and it would discover that for instance brain cells are kind of edible but they're not quite nice so you need to may have more fat in them and you turn them into more fat cells yes and basically this big organism would become a vegetable that is barely alive and it's going to be very brittle and not resilient when the environment changes yeah but some part of that organism the one that's actually doing all the using of the there's still be somebody thriving so as it relates back to this original question I suspect that we are not smartest thing on this planet I suspect that basically every complex system has to have some complex regulation if if it depends on feedback loops and so for instance it's likely to that we should describe a certain degree of intelligence to plants the problem is that plants don't have a nervous system so they don't have a way to Telegraph messages over large distances almost instantly in the plant and instead they will rely on chemicals between adjacent cells which means the signal processing speed depends on their signal processing with a rate of a few millimeters per second yes and as a result the if the plant is intelligent it's not going to be intelligent it's similar timescales yes the ability process the timescales different so you suspect we might not be the most intelligent but when were the most intelligent and this in our timescale so basically if you would room out very far you might discover that they have been intelligent ecosystems on the planet that existed for thousands of years in a almost undisturbed state and it could be that these ecosystems actively related their environment so basically change the course of the evolution within this ecosystem to make it more efficient and as brittle as possible something like plants is actually a set of living organisms an ecosystem of living organisms they're just operating a different time scale and a far superior intelligence than human beings and then human beings will die out and plus will still be there and they'll be there yeah they also there's an evolutionary adaptation playing a role at all of these levels for instance if mice don't get enough food and get stressed the next generation of mice will be more sparse in most quani and the reason for this is because they in a natural environment the mice have probably hidden a drought or something else and if they over grace then all the things that sustain them might go extinct and there will be no mice a few generations from now so and to make sure that there will be mice and five generations from now they see the mice scale back and a similar thing happens with the Predators of mice they should make sure that the mice don't completely go extinct so in some sense if the Predators are smart enough they will be tasked this shepherd their food supply may be the reason why Alliance have much larger brains and antelopes is not so much because it's so hard to catch antelope as opposed to run away from the lion but the Lions need to make complex models of their environment more complex than the antelopes so the first of all just describing that there's a bunch of complex systems and human beings may not even be the most special or intelligent to those complex systems even on earth makes me feel a little better about the extinction of human species that we're talking about yes maybe you addressed Gaia's ploy to put the carbon back into the atmosphere this is just a nice big stain on evolution is not as it was trees hers I evolved trees before they could be to adjust it again right there were no insects that would break all of them apart cellulose is so robust that you cannot get all of it with microorganisms so many of these trees fell into swamps and all this carbon became inert and could no longer be recycled into organisms and via the species that is destined to take care of that so this is kind of dig it out of the ground for the decade the atmosphere in the u.s. is already greening yeah so visitin million years or so when the ecosystems have recovered from the rapid changes yeah that they're not compared to us right now yeah this is going to be awesome again and there won't be even a memory of us of us little apes I think that will be memories of us I suspect we are the first generally intelligent species in the sense we are the first species with an industrial society because we believe more phones than bones in the stratosphere well see I have phones them bones I like it but then let me push back idea you've kind of suggested that with a very narrow definition of of until I mean why aren't trees more general a higher-level general intelligence than trees very intelligent and it would be at different time scales which means within a hundred years the tree is probably not going to make models that are as complex as the one step you make in ten years but maybe the trees are the ones that made the phones right like like you could say the entirety of life did it you know the first cell never died the first cell only split right and every divided and every cell in our body is still an instance of the first cell that split off from that a first sell it was only one sell on this planet as far as we know and so the cell is not just a building block of life it's a hypo organism yeah right and we are part of this type of organism so nevertheless this type of organism no the this little particular branch of it which is us humans because the Industrial Revolution and maybe the exponential growth of technology might somehow destroy ourselves so what what do you think is the most likely way we might destroy ourselves so some people worry about genetic manipulation some people as we've talked about worry about either dumb artificial intelligence or super intelligent artificial intelligence destroying us some people worry all nuclear weapons and weapons of war in general what do you think if you had to if you are a betting man what would you bet on in terms of self-destruction and it would be higher than 50 or to be higher than 50% so it's very likely that nothing that we bet on matters after we win our bet so I don't think that bets are literally the right thing way to go about I mean once you're dead it doesn't you you won't be there to collect so it's also not clear if we as a species go extinct but I think that our present civilization is not sustainable so the thing that will change is there will be probably fewer people on the planet NR today and even if not then still most of people that are alive today will not offering 100 years from now because of the geographic changes and so on in the change in the food supply it's quite likely that many areas of the planet will only be livable is a closed cooling chain in 100 years from now so many of the areas around the equator and in subtropical climates that are now quite pleasant to live in will stop to be inhabitable this is out everyday you honestly Wow cooling chain close knit cooling chain communities so you think you have a strong worry about the the effects of global warming itself it's not the big issue if you will live in Arizona right now you have basically three months in the summer in which you cannot be outside yes and so you have a closed cooling chain you have air conditioning in your car in your home and you're fine and if the air conditioning would stop for a few days then in many areas you would not be able to survive frankly we just pause for a second like you say so many brilliant poet ik things like what is a closed is that do people use that term closed cooling chain I imagine that people use it when they describe how they get meat into a supermarket right it could break the cooling chain and this thing's rights to saw you had trouble and you have to solve it away there's such a beautiful way to put it's like calling a city a closed social chain or something like that I mean yeah that's right I mean the locality of is really yeah but it basically means you wake up in the climatized room you go to work in the climatized car you work in the car all into the shop and acclimatized supermarket and in between you have very short distance which you run from your car to the supermarket but you have to make sure that your your temperature does not approach the temperature of the environment yeah so the usual thing is the bad pub temperature the what the best pub temperature it's what you get when you take wet clothes and you put it around your thermometer and then you move it very quickly through the air so you get the evaporation heat yes and as soon as you can no longer cool your body temperature via app evaporation to a temperature below something like I think 35 degrees you die right and which means if the outside world is dry you can still cool yourself down by sweating but if it has a certain degree of humidity or if it goes up over a certain temperature then sweating will not save you and this means you even if you're a healthy fit individual within a few hours even if you try to be in the shade and so on you'll die unless you have some climate sizing equipment and this itself if you as long as you maintain civilization and you have energy supply and you have food trucks coming to your home that are climatized everything is fine but what if you lose a large scale open every culture at the same time so basically we'll run into food insecurity because climate becomes very irregular or weather becomes very irregular and you have a lot of extreme weather events so you need to roll most of your foot maybe indoor or you need to import your food from certain regions and maybe you are not able to maintain the civilization notes without the planet to get the infrastructure to get the foot to your home right but there could be is so there could be significant impacts in a sense that people begin to suffer they could be wars over resources and so on but ultimately do you have do you not have a lot of faith but what do you make of the capacity of technology technological innovation to help us prevent some of the worst damages that this condition can create so as an example as a almost out there example is the work of SpaceX Elon Musk is doing of trying to also consider our propagation throughout the universe in deep space to colonize other planets that's one technological step but of course what Hamas is trying on Mars is not to save us from global warming because Mars looks much worse than planet Earth will look like after the worst outcomes of global warming imaginable right yes Martha said essentially not habitable it's exceptionally harsh environment yes but what he is doing what a lot of people throughout history since the Industrial Revolution are doing are just doing a lot of different technological innovation was some kind of target and one ends up happening is totally unexpected new things come up so trying to trying to terraform or trying to colonize Mars extremely harsh environment might give us totally new ideas of how to expand the or increase the power of this closed cooling circuit that that empowers the community so like do you it seems like there's a little bit of a race between our open-ended technological innovation of this communal operating system that we have and our general tendency to want to overuse resources and thereby destroy ourselves would you don't think technology can win that race I think the probability is relatively low given that our technology is Prince the u.s. is stagnating since the 1970s roughly in terms of technology most of the things that we do are the result of incremental processes sort of our Intel what about Moore's law it's basically it's very incremental the things that we're doing is so after the invention of the microprocessor was a major thing right the miniaturization of transistors was really major but the things that we did afterwards largely were not that innovative trifle changes of scaling things into a foams GPUs into from CPUs into GPUs and things like that but I don't think that there are basic they're not many things if you take a person that died in the 70s and was at the top of that game they would not need to read that many books to all be current again but it's all about books who cares about books so the there might be things that are beyond what books might be every papers or no papers forget papers there might be things that are so papers and books and knowledge that's a that's a concept of a time when you were sitting there by candlelight and individual consumers of knowledge what about the impact that you we're not in the middle of we're not might not be understanding of Twitter of YouTube the reason you and I are sitting here today is because of Twitter and YouTube yes so the the ripple effect and there's there's two minds sort of two dumb apes coming up with the new perhaps a new clean insights and there's 200 other apes listening right now 200,000 other Apes listening right now and that effect it's very difficult to understand what that effect will have that might be bigger than any of the advancements of the microprocessor Ernie the Industrial Revolution the ability of spread knowledge and that that the the that knowledge the like it allows good ideas to reach millions much faster and the effect of that that might be the new that might be the 21st century is the multiple the multiplying of ideas of good ideas because if you say one good thing today that will multiply across you know huge amounts of people and then they will say something and then they'll have another pocket and I'll say something and then I'll write a paper that that could be a huge you don't think that yeah if you should have billion fun for Normans right now often omens right now in two rings and we don't for some reason I suspect the reason is that we destroy our attention span also the incentives of course different but in Cardassians yeah so the reason why we are sitting here and doing this as a YouTube video is because you and me don't have the attention span to write a book together right now and you guys probably don't have the attention span to read it so let me tell you but we're you know we're an hour and 40 minutes in and I guarantee you that 80% of the people are still listening so there's an attention span it's just the the forum you know who said that the book is the optimal way to transfer information that's said this is still an open question I mean that's what we're something that social media could be doing that other forms could not be doing I think the end game of social media is a global brain and Twitter is in some sense a global brain that is completely hooked on dopamine doesn't have any kind of inhibition and as a result is caught in a permanent seizure yes it's also in some sense a multiplayer role-playing game and people use it to play an avatar that is not like them as the Verna's sane world and they look through the world through the lens of their phones and think it's the real world but it's the Twitter of all that is thwarted by the popularity incentives of Twitter yet the the incentives and just our natural biological the the dopamine rush of alike no matter how like I consider I try to be very kind of zen-like and minimalist and not being influenced by likes and so on but it's probably very difficult to avoid that to some degree the speaking at a small tangent of Twitter what how can be how can Twitter be done better I think it's an incredible mechanism that has a huge impact on society by doing exactly what you're doing oh sorry doing exactly you described which is having this but we're like is this some kind of game and we're kind of our individual RL agents in this game and it's uncontrolled because there's not really a centralized control neither jack dorsey nor the engineers at twitter seem to be able to control this game or can they that's sort of a question is there any advice you would give and control is advice because I am certainly not an expert but I can give my thoughts on this and I our brain is has solved this problem to some degree right our brain has lots of individual agents that manage to play together anyway and you have also many contexts in which other organisms have found ways to solve the problems of cooperation that we don't solve on Twitter and maybe the solution is to go for an evolutionary approach so imagine that you have something like reddit or something like Facebook and something like Twitter and do you think about what they have in common what they have in common they're companies that in some sense own a protocol and this protocol is imposed on a community and the protocol has different components for monetization for a user management for user display for rating for anonymity for importer of other content and so on and now imagine that you take these components of the protocol apart and you do it in some sense like communities visiting this social network and these communities are allowed to mix and match their protocols and design new ones so for instance the UI and the UX can be defined by the community the walls for sharing content across communities can be defined the monetization can be redefined the way you reward individual users for what can be redefined the way users can represent themselves and to each other can redefined and will be the redefine er so it can individual human beings build enough intuition to redefine those things if self can become part of the protocol so for instance it could be in some communities it will be a single person that comes up with these things and others it's a group of friends some might implement a voting scheme that has some interesting weighted voting who knows who knows what will be the best self organizing principle for this but the process can be automated I mean it seems like the brain can be automated so people can write a software for this and eventually the idea is let's not make a assumption about this thing if you don't know what the right solution is in those areas that we have no idea whether the right solution will be people designing this ad hoc or machines doing this whether you want to enforce compliance by social norms like weak Orvis software solutions or this AI that goes through the post of people or is a legal principle and so on this is something maybe you need to find out and so the idea would be if you let the communities evolve and you just control it to say in such a way that you are incentivizing the most sentient communities hmm the ones that produce the most interesting behaviors and that allow you to interact in the most helpful ways to the individuals right so you have a network that gives you information that is relevant to you it helps you to maintain relationships to others in healthy ways it allows you to build teams it allows you to basically bring the best of you into this thing and goes into a coupling into a relationship with others in which you produce things that you would be unable to produce alone yes beautifully put so but the key process of that with incentives and evolution is things that don't adapt themselves to effectively get the incentives have to die and the thing about social media is communities that are unhealthy or whatever you want and it defines the incentives really don't like dying one of the things that people really get aggressive protests aggressively is when they're censored especially in America I don't know I don't know much about the rest of the world but the idea of freedom of speech the idea of censorship is really painful in America and so what yeah well what do you think about that have been growing up in East Germany what do you think censorship is an important tool in our brain in the intelligence and in the social networks so basically if you're not a good member of the entirety of the system they should be blocked away well locked away blocked important thing is who decides that you are a good member who is it distributed or and what is the outcome of the process that decides it both for the individual and for society at large for instance if you have a high trust society you don't need a lot of surveillance and the surveillance is even in undermining trust yes because it's basically punishing people that look suspicious when surveyed but do the right thing anyway and the opposite if you have a low trust society in there and surveillance can be a better trade-off and the u.s. is currently making a transition from a relatively high trust a mixed trust society to a low trust society so surveillance will increase another thing is that beliefs are not just Inuit representations there are implementations that run code on your brain and change for a reality and change the way you interact with each other at some level and some of the beliefs are just public opinions that we use to display our alignment so for instance people might say all characters have are the same and equally good but still they prefer to live in some cultures over others very very strongly so and it turns out that the cultures are defined by certain rules of interaction and these rules of interaction lead to different results when you implement them right so if you adhere to certain rules you get different outcomes in different societies and this all leads to very tricky situations when people do not have a commitment to shared purpose and our societies what we need to rediscover what it means to have a shared purpose and how to make this compatible with a non totalitarian view so in some sense the u.s. is caught in a conundrum between totalitarianism and diversity and doesn't it need to how to resolve this and the solutions that the u.s. has found so far a very crude because it's a very young society that is also under a lot of tension it seems to me that the US will have to reinvent itself what do you think just uh philosophizing what kind of mechanisms of government do you think we as a species should be involved with us or broadly what do you think will work well as a system of course we don't know it all seems to work pretty crapoly some things worse than others some people argue that communism is the best others say yeah look at the Soviet Union some people argue that anarchy is the best and then completely discarding the positive effects of government you know there's a lot of argument u.s. seems to be doing pretty damn well in in the span of history there says respect for human rights which seems to be a nice feature not a bug and economically a lot of girls law technological development people seem to be relatively kind and the grand scheme of things what lessons do you draw from that what kind of government system do you think is good ideally a government would not be perceivable all right it should be frictionless the more you notice the influence of the government the more friction you experience the less effective and efficient the government probably is right so a government game theoretically is an agent that imposes an offset on your payout metrics to make your Nash equilibrium compatible with the common good right so you have these situations and these local incentives everybody does the thing that's locally the best for them but the global outcome is not good and this is even the case when people care about the global outcome because a regulation mechanisms exist that creates a course of relationship between what I want to have for the global good and what I do so for instance if I think that we should fly less and I stay at home there is not a single plane that is going to not start because of me right it's not going to have an influence but I don't get from A to B so the way to implement this would be to have a government that is sharing this idea that you should fly less and is then imposing a regulation that for instance makes flying more expensive and it gives incentives for inventing other forms of transportation that are less putting the strain on the environment for instance so there's so much optimism and so many things you described and yet there's the pessimism of you think our civilization is gonna come to an end so that's not a hundred percent probability nothing in this world is so what's the trajectory out of self-destruction do you think I suspect that in some sense we are both too smart and not smart enough which means we are very good at solving near-term problems and at the same time we are unwilling to submit to the end to the imperatives of that we would have to follow in if you want to stick around right so that makes it difficult if you were unable to solve everything technologically you can probably understand how it the child mortality needs to be to absorb the mutation rate and tell why the mutation mutation rate needs to be to adapt to a slowly changing ecosystemic environment right so you could in principle compute all these things game theoretically and adapt to it but if you all cannot do this because you are like me and you have children you don't want them to die you will use any kind of medical information to keep travel to a mortality low even if it means that our visit a few generations we have enormous genetic drift and most of us have allergies as a result of not being adapted the changes that we made to our food supply that's for now I say technologically speaking which is a very very very young you know 300 years industrial revolution we're very new to this idea so you're attached to your kids being alive and not being murdered for the greater good of society but that might be a very temporary moment of time yes that we might move might evolve in our thinking so like you said when we're both smart and not smart enough you're probably not this first human civilization that has discovered technology that allows to efficiently over grace our resources and this overgrazing is think at some point we think they can compensate this because if we have eaten all the grass we will find a way to grow mushrooms right but it could also be that the ecosystems tip and so what really concerns me is not so much the end of the civilization because we will invent a new one but what concerns me is the fact that for instance the oceans might tip so for instance maybe the plankton dies because of ocean acidification and cyanobacteria take over and as a result we can no longer raise the atmosphere this would be really concerning so basically a major reboot of most complex organisms on earth and I think this is a possibility I don't know if what the percentage for this possibility is but it doesn't seem to be our language to me if you look at the scale of the changes that we've already triggered on this planet and so Danny Hillis suggests that for instance we may be able to put chalk into the stratosphere to solar radiation maybe it works maybe there's a sufficient to counter the effects of what we've done maybe it won't be maybe we won't be able to implement it by the time it's prevalent I have no idea how how the future is going to play out in this regard it's just I think it's quite likely that we cannot continue like this all our cousin species the other home units are gone so the right step would be to what to rewind rewind towards a destro Revolution and slow the the so it's to try to contain the technological process that leads to the overconsumption of resources imagine you had get to choose you have one lifetime yes you get born into a sustainable agricultural civilization 300 maybe 400 million people on the planet tops or before this some kind of nomadic species feels like a million or two million and so you don't meet new people unless you give birth to them you cannot travel to other places in the world there is no internet there is no interesting intellectual tradition that reaches considerably deep so you would not discover your own completeness probably and so on so we wouldn't exist and the alternative is you get born into an insane world one that is doomed to die because it has just burned 100 million years worth of trees in a single century which one do you like I think I like this one it's a very weird thing then when you find yourself on a Titanic and you see this iceberg and it looks like we are not going to miss it and a lot of people are in denial and most of the counter arguments sound like denial to me that don't seem to be rational arguments and the other thing is we were born on this Titanic without this Titanic we wouldn't have been born we wouldn't be here we wouldn't be talking we wouldn't be on the internet we wouldn't do all the things that we enjoy and if you're not responsible for this happening it's basically if he had the choice we would probably try to prevent it but when we were born we were never asked when we want to be born in which society we want to be born but incentive structures we want to be exposed to we have relatively little agency in the entire thing humanity has relatively daily machine the whole thing it's basically a giant machine it's tumbling down a hill and everybody is Fanta Klee trying to push some buttons nobody knows what these buttons are meaning what they connect - and most of them are not stopping this tumbling down the hill is impossible the artificial intelligence will give us an escape latch somehow so the you know there's a lot of worry about existential threats of artificial intelligence but what AI also allows in general forms of automation allows the potential of extreme productivity growth that will also perhaps in a positive way transform society that may allow us to inadvertently to return to the more to the same kind of ideals of closer to nature that's represented in hunter-gatherer societies you know that's not destroying the planet that's not doing overconsumption and so on I mean generally speaking do you have hope that a I can help them uh I think it is not fun to be very close to nature until you completely subdue nature so our idea of being close to nature means being close to agriculture basically forests that don't have anything in them that eats us see I mean I want to disagree with that I I think the niceness of being close to nature is to being fully present and in like Wirthlin survival becomes your primary not just your goal but your whole existence mm-hmm it I mean that is a in I'm not just romanticizing I can just speak for myself I am self-aware enough that that is uh that is a fulfilling existence that's one that's very to be in nature ah and not fight for my survival I think fighting in yourself for your survival well being in the cold and in the rain and being hunted by animals and having open wounds it's very unpleasant well there's a contradiction in there yes I in you just as you said would not choose it but if I was forced into it it would be a fulfilling existence Lemar adapted to it basically if your brain is fed up in such a way that you get rewards optimally in such an environment and there's some evidence for this that for a certain degree of complexity basically people are more happy in such environment because it's what we largely have evolved for in between we had a few thousand years in which I think we have evolved for a slightly more comfortable environment so there is probably something like an intermediate stage in which people would be more happy than there would be if they would have to fend for themselves in small groups in the forest and often die versus something like this very now have basically a big machine a big of Mordor in which we run concrete boxes and press buttons and machines and largely don't feel well cared for as the monkeys that we are so returning briefly to not briefly but returning to AI what let me ask a romanticized question what is the most beautiful - you silly ape the most beautiful or surprising idea in the development of artificial intelligence well there in your own life or in the history of artificial intelligence that you've come across if you built an AI it probably can make models at an arbitrary degree of detail right of the world and then it would try to understand its own nature it's tempting to think that at some point when we have general intelligence we have competitions very evil that the AIS wake up in different kinds of physical universes and we measure how many movements of the rubik's cube it takes until it's figured out what's going on in its universe and what it is and its own nature and its own physics and so on right so what if we exists in the memory of an AI that is trying to understand its own nature and remembers its own genesis and remembers lex and Yasha sitting in hotel sparking some of the ideas of that led to the development of general each other so we're a kind of simulation is running in an AI system is trying to understand itself it's not that I believe that but as I think it's a beautiful I mean it you kind of return to this idea with the Turing test of intelligence being of intelligence being the process of asking and answering what is intelligence I mean what why do you think there's there is an answer what why is there such a search for an answer what so does there have to be and I can I can answer you just had an AI system that's trying to understand the why of what you know understand itself is that a fundamental process of greater and greater complexity greater greater intelligence is the continuous trying of understanding itself no I think you will find that most people don't care about that because they're well adjusted enough to not care and the reason why people like you and me occur about it probably has to do with the need to understand ourselves it's because we are in fundamental disagreement is the universe that we wake up in what looks like me and I see oh my god I'm caught in a monkey what's that sorry that's the feeling right it's just the government and I'm unhappy with the entire universe that I fight myself in so you don't think that's a fundamental aspect of human nature that some people are just suppressing that they're they wake up shocked they're there in the body of a monkey no there is clear adaptive value to not be confused by that and by well no no that's our air so oh so you have to clear adaptive value then there's clear adaptive value to while fundamentally your brain is confused by that by creating an illusion another layer of the narrative that says you know that tries to suppress that and instead say that you know what's going on with the government right now is the most important thing what's going on with my football team is the most important thing but it seems to me the like I would like for me it was a really interesting moment reading Ernest Becker's denial of death the you know there's this kind of idea that we're all you know the fundamental thing from which most of our human mind Springs is this fear of mortality being cognizant of your mortality and the fear of that mortality and then you construct illusions on top of that I guess I'm you being just a push on it you you really don't think it's possible that this worry of the big existential questions is actually fundamental as of as the existentialist thought to our existence I think that the fear of death only plays a role as long as you don't see the big picture the thing is that Minds our software States right software doesn't have identity software in some sense is a physical law but if last like a brief yeah right so but it feels like there's an identity I thought that was the for this particular piece of software and then narrative it tells there's a fundamental property of assigning it maintenance of the identity is not terminal it's instrumental to something else you maintain your identity so you can serve your meaning so you can do the things that you're supposed to do before your bad died and I suspect that for most people the fear of death is the fear of dying before they're done with the things that they feel they have to do even though they cannot quite put their finger on it what it is what that is right but in the software world okay they return to the question then what happens after we die because what you care you will not be longer there the point of trying is that you're gone or maybe I'm not and this is what you know it it seems like there's so much any idea that this is just the mind is just the simulation is constructing a narrative around some particular aspects of the quantum mechanical wave function world that we can't quite get direct access to then like the idea of mortality seems to be a little fuzzy as well it doesn't maybe there's not a clear and the quasi idea is the one of continued existence we don't have continuous existence how do you know that like that it's not computable because you're saying it's good it's no process the only thing that binds you together with the leg Sweetman from yesterday is the illusion that you have memories about him so if you want to upload it's very easy you make a machine that thinks it's you because this the same thing that you are you are a machine that thinks it's you but that's that's more and that's immortality yeah but it's just a belief you can create this body very easily once you realize that the question whether you are immortal or not depends entirely on your beliefs and your own continuity but then it then then you can be immortal by the continuity of the belief you cannot be immortal but you can stop being afraid of your mortality because you realize you were never continued ously existing in the first place well I don't know if I'd be more terrified or less terrified with that it seems like the fact that I existed also you don't know this state in which you don't have itself you can turn off yourself you know I can't turn you can turn it off you can turn it off I can yes and you can basically meditate yourself in a state where you are still conscious there's still things are happening where you know everything that you knew before but you no longer identified was changing anything and this means that yourself and way it dissolves there is no longer this person you know that this person construct exists in other states and it runs on this brain of legs Freedman but it's it's not a real thing it's a construct it's an idea and you can change that idea and if you let go of this idea if you don't think that you are special you realize it's just one of many people and it's not your favorite person even right it's just one of many and it's the one that you are doomed to control for the most part and that is basically informing the actions of this organism yeah as a control model and this is all there is and you are somehow afraid that this control model gets interrupted or loses the identity of continuity yeah so I'm attached I mean yeah there is a very popular it's a somehow compelling notion that being being attached like there's no need to be attached to this idea of an identity but that in itself could be a an illusion that you construct so the process of meditation while popular is thought of as getting under the concept of identity it could be just putting a cloak over it just telling it to be quiet for the moment you know it I think that meditation is eventually just a bunch of techniques that let you control attention and when you can control the attention you can get access to your own source code hopefully not before you understand what you're doing and then you can change the way it works temporarily or permanently so yeah meditations in get a glimpse at the source code get under there so basically how much role or is it that you learn to control attention so yeah everything else is downstream from controlling attention and control the attention that's looking at the attention not only only get attention in the parts of our mind that create heat where you have a mismatch between model and the results that are happening and so most people are not self-aware because their control is too good if everything works out roughly the way you want and the only things that don't work out is whether your football team vents then you will mostly have models about these domains and it's only when for instance your fundamental relationships to the world around you don't work because the ideology of your country is insane and the other kids are not nerds and don't understand why you understand physics and you don't why you want to understand physics and you don't understand why somebody would not want to understand physics so we kind of brought up neurons in the brain as reinforcement learning agents and there's been some successes as you brought up with go with alpha go alpha zero with ideas of self play which I think are incredibly interesting ideas those systems playing each other and in an automated way to improve by playing other systems of in a particular construct of a game that are a little bit better than itself and then thereby improving continuously all the competitors in the game are improving gradually so being just challenging enough and from learning from the process of competition do you've hoped for that reinforcement learning process to achieve greater and greater level of intelligence so we talked about different ideas in AI then we need to be solved is RL a part of that process of trying to create a GI system so it forms of unsupervised learning but the many algorithms that can achieve that and I suspect that ultimately the algorithms that work there will be a class of them or many of them and they might have small differences of like a magnitude in efficiency but eventually what matters is the type of model that you form and the types of models that we form right now are not sparse enough just bars that what does it mean to be sparse so it means that ideally every potential model State should correspond to a potential world state so if I see if you vary States in your model you always end up as valid world States and all mind is not quite there so an indication especially what we see in dreams the older we get the more boring our dreams become because we incorporate more and more constraints that we learned about how the world works so many of the things that we imagined to be possible as children turn out to be constrained by physical and social dynamics and as a result fewer and fewer things remain possible it's not because our imagination scales back but the constraints under which it operates become tighter and tighter and so the constraints under which our neural networks operate are almost limitless which means it's very difficult to get a neural network to imagine things that look real right so as a SPECT part of what we need to do is we probably need to build dreaming systems I suspect that part of the purpose of dreams is to similar to a generative adversarial network to learn certain constraints and then it produces alternative perspectives on the same set of constraints so you can recognize it under different circumstances maybe we have flying dreams as children because we recreate the objects that we know on the maps that we know from different perspectives which also means from the bird's eye perspective so I mean aren't we doing that anyway I mean not without with our eyes and with our eyes closed and when we're sleeping are we just constantly running dreams and simulations in our mind as we try to interpret the environment I mean it's sort of considering all the different possibilities there's the way we interact with the environment it seems like essentially like you said of creating a bunch of simulations that are consistent with our expectations with previous experiences with the things we just saw recently and through that hallucination process we are able to then somehow stitch together what actually we see in the world with the simulations that match it well and thereby interpret it I suspect it you're in my brain are slightly unusual in this regard which is probably what got you into MIT so this obsession of constantly pondering possibilities and solutions to problems I'll stop I think I I'm not talking about intellectual stuff I'm talking about just doing the kind of stuff it takes to walk and not fall I guess this is largely automatic yes but the process is mean it's not complicated it's very easy to pull the neural network that in some sense learns the dynamics the fact that we haven't done it right so far it doesn't mean it's hard because you can see that a biological organism does it there's relatively few neurons yeah as you build a bunch of neural oscillators that in train themselves this the dynamics of your body in such a way that the regulator becomes isomorphic and it's modeled through the dynamics that are regulates and then is automatic and it's only interesting the sense that it captures attention when the system is off see but thinking of the kind of mechanism that's required to do walking as a controller as like a as a neural network I think I think it's a compelling notion but it's discards quietly or at least makes implicit the fact that you need to have something like common sense reasoning to walk it's not as an open question whether you do or not but my intuition to be to act in this world there's a huge knowledge base that's underlying it somehow there's so much information of the kind we have never been able to construct in our in your networks on an artificial intelligence systems period which is like it's humbling at least in my imagination the amount of information required to act in this world humbles me and I think saying that your levels can accomplish it is missing is missing the fact that we don't yeah we don't have yet a mechanism for constructing something like common sense reasoning I mean what's your sense about to linger on how much if you know to linger on the idea of what kind of mechanism would be effective at walking you said just a neural network not maybe the kind we have but something a little bit better we'll be able to walk easily don't you think it also needs to know like a huge amount of knowledge that's represented under the flag of common sense reasoning how much common sense knowledge to be actually have imagine that you are pretty hard working through all your life and you form two new concepts every half hour or so yes you end up with something like a million concepts because you don't get that old so a million concept that's not a lot it's not just a million concepts I think you'll be a lot I personally think it might be much more than a million if you think just about the numbers you don't live that long if you think about how many cycles do your neurons have in your life it's quite limited you don't get that all yeah but the the powerful thing is a number of concepts and they're probably deeply hierarchical in nature the relations as you described between them is the key thing so it's like even if it's the chameleon concepts the the graph of relations that's formed and some kind of perhaps some kind of probabilistic relationships that's the that's what's common-sense reasoning is a relationship between things that yeah so but in some sense I think of the concepts as the space for our behavior programs and the waiver poems allow us to recognize objects and interact with them also mental objects and a large part of that is the physical world that we interact with which is this res extend Lansing which is basically navigation of information in space and basically it's similar to a game engine it's a physics engine that you can use to describe and predict how things that look in a particular way that feel when you touch them particular way they love proprioception I love auditory perception and so on how they work out so basically the geometry of all these things and this is probably 80% of what our brain is doing is dealing with debt with this real-time simulation and by itself a game engine is fascinating but it's not that hard to understand what it's doing right and our game engines are already in some sense approximating the Magna deep fidelity of what we can perceive so if we put on an oculus quest we get something that is still qualitatively crude with respect to what we can perceive but it's also in the same ballpark already right it's just a couple order of magnitudes away to home saturating our perception jumps of the complexity that it can produce so in some sense it's reasonable to say that our the computer that you can buy it the put into your home is able to give a perceptual reality that has a teacher that is already in the same ballpark as what your brain can process and everything else our ideas about the world and I suspect that they are relatively sparse and also the intuitive models that we form about social interaction social interaction is it's not so hard it's just hard for us nerds because we all have our wires crossed so we need to use them but the priors are present in most social animals so it's interesting thing to notice that many domestic social animals like cats and dogs have better social cognition than children right I hope so I hope it's not that many concepts fundamentally and - due to existence world social sorry it's more like I'm afraid so because this thing that we only appear to be so complex to each other because we are so stupid it's a little bit interesting now one that yeah to me that's inspiring if we're indeed as as as stupid as it seems so thinks our brains don't scale and the information processing that we built tend to scale very well yeah but I mean one of the things that worries me is that the you know that the fact that the brain doesn't scale means that that's actually a fundamental feature of the brain you know the all the flaws of the brain everything we see that we see has limitations perhaps there's a fundamental the constraints on the system could be the requirement of its power which is like different than our current understanding of intelligent systems were scale especially with deep learning especially with reinforcement learning the hope behind open a eye deep mind all the major results really have to do with huge compute and it also be that our brains are so small not just because they take up so much glucose in our body like 20% of the glucose so they don't arbitrarily scale there's some animals like elephants which have larger brains than us and atoms need to be smarter all right elephants seem to be autistic they have very very good motor control and they're really good with details but they really struggle to see the big picture so you can make them recreate drawings stroke by stroke they can do that but they cannot reproduce a still life so they cannot make a drawing of a scene that I see there will always be only able to reproduce the line drawn at least as far away from what I could see in the experiments yeah by is that maybe smarter elephants would meditate themselves out of existence because their brains are too large so they basically the elephants that were not autistic they didn't reproduce yet so we have to remember that the brain is fundamentally interlinked with the body and our human and biological system do you think that a GI systems that we try to create or greater intelligence systems would need to have a body so I think that should be able to make use of a body if you give it to them but I don't think that a fundamentally new body so I suspect if you can interact with the world by moving your eyes and your head you can make controlled experiments and this allows you to have many magnitudes fewer observations in order to reduce the uncertainty in your models alright so you can pinpoint the areas in your models but you're not quite sure and you just move your head and see what's doing what's going on over there and you get additional information if you just have to use YouTube as an input and you cannot do anything beyond this you probably need just much more data but if we have much more data so if you can build a system that has enough time and attention to browse all of YouTube and extract all the information that there is to be found I don't think that's an obvious limit to what it can do yeah but it seems that the interactivity is a fundamental thing that the physical body allows you to do but let me ask on that topic sort of that does what a body is is allowing the brain to like touch things and move things and interact with the weather the physical world exists or not whatever but interact with someone interface to the physical world what about a virtual world do you think do you think we can do the same kind of reasoning consciousness intelligence if we put on a VR headset and move over to that world do you think there's any fundamental difference between the interface the physical world that is here in this hotel and if we were sitting in the same hotel in a virtual world the question is just as physical this non-physical world with this other environment near entice you to solve problems that require general intelligence if it doesn't then you probably will not develop general intelligence and arguably most people are not genuinely intelligent because they don't have to solve problems that make them generally intelligent and even for us it's not yet clear if we are smart enough to put AI and understand our own nature to this degree right so it could be a matter of capacity and for most people it's in the first place a matter of interest they don't see the point because the benefit of attempting this project are marginal because you're probably not going to succeed in it and the cost of trying to do a requires complete dedication of your entire life all right but it seems like the possibilities of what you can do in a virtual world so imagine a cut is much greater than you can in the real world so imagine a situation maybe interesting option for me if somebody came to me and offered what I'll do is yeah so from now on you can only exist in the virtual world and so you put on this headset and when you eat we'll make sure to connect your body up in a way that when you eat in the virtual world your body will be nourished in the same way in the virtual world so the aligning incentives between the our common sort of real world in the virtual world but then the possibilities become much bigger like I could be other kinds of creatures I could do I can break the laws of physics as we know them I can do a lot I mean the possibilities are endless right it that's as far as we think it's an interesting thought whether like what existence would be like what kind of intelligence would emerge there what kind of consciousness what kind of maybe greater intelligence even me and me Lex even I'm at this stage in my life if I spend the next 20 years in our world to see how that intelligence emerges and if I was if that happened at the very beginning before I was even cognizant of my existence in this physical world it's interesting to think how that child would develop and the way virtuality and digitization of everything is moving it's not completely out of the realm of possibility that we're all that some part of our lives will be if not entirety of it we'll live in a virtual world to a greater degree than we currently have living on Twitter and social media and so on do you have I mean it does something draw you intellectually or naturally in terms of thinking about AI to this virtual world we're more possible easier I think that currently it's a waste of time to deal with the physical world before we have mechanisms that can automatically learn how to deal with it the body gives you a second order agency but you conserve what constitutes the body is the things that you can indirectly control I third or our tools right and the second order is the things that are basically always present but you operate on them with first order things which are mental operators yes and the zero order is in some sense the direct sense of what you are deciding right so you in you observe yourself initiating an action there features but that you interpret as the initiation of an action then you are the operations that you perform to make that happen and then you see the movement of your limbs and you learn to associate those and thereby model your own agency over this feedback right but the first feedback that you get is from this first order thing already basically you decide to think a thought and the thought is being thought you decide to change the thought and you observe how the thought is being changed yes and in some sense this is you could say an embodiment already right and I suspect it's sufficient as an embodiment really origins and so it's not that important at least at this time to consider variations in the second order yes but the thing that you also put a mentioned just now as physics that you could change in any way you want so you need an environment that puts up resistance against you if you if there's nothing to control you cannot make models right there needs to be a particular way that resists you and by the way your motivation is usually outside of your mind it resists your motivation is what gets you up in the morning even though it would be much less work to stay in bed and so it's basically forcing you to resist the environment and it forces your mind to serve it to serve this resistance to the environment so in some sense it is also putting up resistance against the natural tendency of the mind to not do anything yeah but some of that resistance just like you described as motivation is like in the first order space in the mind some resistance is in the second order like the actual physical objects pushing against you so ah yeah it seems that the second order stuff and virtuality could be recreated of course but it might be sufficient that you just do mathematics and mathematics is already putting up enough resistance against you so basically just visiting a static motive this could may be sufficient to form a type of intelligence it would probably not be a very human intelligence but it might be one that is already general so to to mess with this 0th order may be first order what do you think about ideas of brain computer interfaces so again returning to our friend Elon Musk and your link a company that's trying to of course there's a lot of trying to cure diseases and so on with a near term but the long term vision is to add an extra layer to so basically expand the capacity of the brain and connected to the computational world aha do you think one that's possible - how does that change the fundamentals of the zeroth order in the first order it's technically possible but I don't see that the FDA would ever allow me to drill holes on my skull to interface my neocortex the veyron mask envisions so at the moment I can do horrible things to mice but I'm not able to do useful things to people except maybe at some point down the line in medical applications so this thing that we are envisioning which means recreational and creational brain computer interfaces are probably not going to happen in the present legal system I love it how I'm asking you out there philosophical and sort of engineering questions and for the first time ever he jumped to the legal FDA there would be enough people that would be crazy enough to have holes drilled in their skull to try a new type of brain computer interface but also if it works it FDA will approve it I mean it's the yes you're it's like exert on most vehicles yes you can say that's gonna be very difficult regulatory process of approving with honesty but it doesn't mean autonomous vehicles are never gonna happen so no devil totally happen as soon as we create jobs for at least we lawyers and one regulator per car yes lawyers that's actually like lawyers is the fundamental substrate of reality it's a very good system it's not Universal in the world the law is a very interesting software once you realize it right these circuits are in some sense streams of software and this is largely works by exception handling so you make decisions on the ground and they get synchronized with the next level structure as soon as an exception as being wrong is a yeah so so isolates the exception handing the process is very expensive especially since it's incentivizes the lawyers for producing lot of work for lawyers yes so the exceptions are actually incentivize for for firing often but but to return outside of lawyers is there anything fundamentally like is there anything interesting insightful about the possibility of this extra layer of intelligence a little rain I do think so but I don't think that you need technically invasive procedures to do so we can already interface with other people by observing them very very closely and getting in some kind of empathetic resonance and I'm a nerd so I'm not very good at this but I noticed that people are able to do this to some degree and it basically means that we model an interface lay off the other person in real time and it works despite our neurons being slow because most of the things that we do are built on periodic process these two just need to entrain yourself with the oscillation that happens and if the Association itself changes slowly enough you can basically follow along right but the bandwidth of the interaction the you know it seems like you can do a lot more computation one yes of course the but the other thing is that the event was that our brain our own mind is running on is actually quite slow so the number of thoughts that I can productively think in any given day is quite limited but it's much if they had the discipline to write it down and the speed to write it down maybe it would be a book every day or so but if you think about the computers that we can build the magnitudes at which they operate right this would be nothing it's something that it can put out in a second well I don't know so as possible sort of the number of thoughts you have in your brain is it could be several orders of magnitude higher than what you're possibly able to express through your fingers or through your voice like so most of them are going to be repetitive because they how do you know that I mean they have to control the same problems every day when I walk they are going to be processed this in my brain that model my walking pattern and regulate them and so on but it's going to be pretty much the same every day but that movies every step but I'm talking about intellectual reasoning like thinking so the question what is the best system of government so you sit down and start thinking about that one of the constraints is that you don't have access to a lot of like you you don't have access to a lot of facts a lot of studies you have to do you always have to interface with something else to learn more to to aid in your reasoning process if you can direct access all over Kapadia in trying to understand what is the best form of government then every thought won't be stuck in a loop like every thought that requires some extra piece of information will be able to grab it really quickly that that's the possibility of if the bottleneck is literally the information that you know the bottleneck of breakthrough ideas is just being able to quickly access huge amounts of information then the possibility of connecting your brain to the computer could lead to totally new like you know totally new breakthroughs you can think of mathematicians being able to you know just up the orders of magnitude of power in their reasoning about that matter what humanity has already discovered the optimal form of government to a revolutionary process is an evolution and so what we discover is that maybe the problem of government doesn't have stable solutions for us right as a species because we are not designed in such a way that we can make everybody conform to them so but there could be solutions that work under given circumstances or that are the best for certain environment and depends on for instance the primary forms of ownership and the means of production so if the main means of production is lent then the forms of government will be regulated by the landowners and you get a monarchy if you also want to have a form of government in which a subset you depend on some form of slavery for instance where the peasants have to work very long hours for very little gain so very few people had enough plumbing then maybe you need to promise them that we had paid in in the afterlife there over time right so you need a theocracy and so for much of human history in the West we had a combination of monarchy and theocracy that was our form of governance right at the same time the Catholic Church implemented game theoretic principles I recently reread Thomas or kindness it's very interesting to see this because he was not duelist he was translating Aristotle in a particular way for the designing an operating system for the Catholic society and he says that basically people our animals and very much the same way as Aristotle envisions which basically organisms with cybernetic control and then he says that there are additional rational principles that humans can discover and everybody can discover them so they are universal if you are saying you should understand you should submit to them because you can rationally deduce them and these principles are roughly you should be willing to self-regulate correctly you should be willing to do correct social regulation it's intro organismic you should be willing to act on your models so we have skin in the game and you should have called rationality you should be choosing the right to calls to work on and so basically these three rational principles call rationality he calls prudence or wisdom the social regulation is justice the correct social one and the internal regulation is temperance and this thing to be willingness to act on your models is courage and then he says that they are additionally to these four cardinal virtues three divine virtues and these three divine virtues cannot be resonated used but they reveal themselves by the harmony which means if you assume them and you extrapolate what's going to happen you will see that that makes sense and it's often been misunderstood as God has to tell you that these are the things so they're a see there's something nefarious going on with the christian conspiracy forces you to believe some guy with a long beard that they discovered this but so these principles are relatively simple again you need it's for high level organization for the resulting civilization that you form commitment to unity so basically you serve this higher larger thing this structural principle on the next level and he calls that phase then there needs to be a commitment to shared purpose this is basically this global reward that you try to figure out what that should be and now you can facilitate this and this is love the commitment to shared purpose is the core of love right you see the sacred thing that is more important than your own organism ayk interests in the other and you serve this together and this is how you see the sacred and the other and the last one is hope which means you need to be willing to act on that prayer principle without getting rewards in the here and now because it doesn't exist yet then you start out building the civilization right so you need to be able to do this in the absence of its actual existence yet so it can come into being so yes so the way it comes into being is by you accepting those notions and then you see there these these three divine concepts then you see them and realized now the most divine is the loaded concept and olive oil and ice because we are outside of this cart and we are still scarred from breaking free of it but the idea is basically we need to have a civilization that acts as an intentional agent like an insect State and we are not actually a tribal species we are state building species and was what enabled State Building is basic the formation of religious states and other forms of rule-based administration in which the individual doesn't matter as much as the rule or the higher goal right we got there by the question what's the optimal form of governance so I don't think that chaos or Catholicism is the optimal form of governance because it's obviously on the way out right so it is for the present type of society that we are in religious institutions don't seem to be optimal to organize that so what we discovered right now that we live in in the West is democracy and democracy is the rule of oligarchs there are the people that currently own the means of production that is administered not by the oligarchs themselves because they there's too much distraction right here so much innovation that we have in every generation new means of production let me invent and corporations dive usually after 30 years or so and something either takes the leading role in our societies so it's administered by institutions and these institutions themselves are not elected but they provide continuity and they are led by electable politicians and this makes it possible that you can adapt to change without having to kill people right so you can tell for instance of a change in government's if people think that the current government is too corrupt or is not up-to-date you can just elect new people or if a journalist finds out something inconvenient about the institution and the institution is has no plan B like in Russia the journalist has to die this is what but when you run society by the deep state so ideally you have a administration layer that you can change if something bad happens right so you will have a continuity in the whole thing and this is the system that we came up in in the West and the way it's set up in the US is largely result of low-level models was mostly just second third order consequences that people are modeling in the design of these institutions it's relatively young society that doesn't really care take care of the downstream effects of many of the decisions that are being made and I suspect that AI can help us this in a way if you can fix the incentives the Society of the u.s. is a society of teeters it's basically cheating so indistinguishable from innovation and we want to encourage innovation can you elaborate on what you mean by cheating especially people do things that they know are wrong it's acceptable to do things that you know are wrong in this society who a certain degree you can for instance suggest some non sustainable business models and implement them right but you're always pushing the boundaries I mean yeah you're yes you're and yes this is seen as a good thing largely yes and this is different from other societies so for instance social mobility is an aspect of this social mobility is the result of individual innovation that would not be sustainable at scale for everybody else right normally you should not go up you should go deep right we need Baker's and if you are very good bakers but in a society that innovates maybe you can replace all the Baker's with a really good machine right and that's not a bad thing and it's a thing that made us so successful right but it also means that the u.s. is not optimizing for sustainability but for innovation and so it's not obvious as the evolutionary processes unrolling is not obvious that that long term would be better it's it has side effect so you basically if you cheat you will have a certain layer of toxic sludge that covers everything there is a result of cheating and we have to unroll this evolutionary process to figure out if these side effects are so damaging that the system is horrible or if the benefits actually outweigh the the the negative effects how do we get to the which system of government is best that was from I'm trying to trace back like five minutes I suspect that we can find a way back to AI by thinking about the way in which our brain has to organize it right in some sense our brain is a society of neurons and our mind is a society of behaviors and they need to be organizing themselves into a structure that implements regulation and government is social regulation we often see government is the manifestation of power or local interests but it's actually a platform for negotiating the conditions of human survival and this platform emerges over the current needs and possibilities in the trajectory that we have so given the present state there are only so many options on how we can move into the next stage without completely disrupting everything and we mostly agree that it's a bad idea to disrupt everything because it will endanger our food supply for a while and the entire infrastructure and fabric of society so we do try to find natural transitions and they're not that many natural transitions available at any given point Murray you're a natural transition so we try to not to have revolutions if he can have it right so speaking of revolutions and the connection between in government systems in the mind you've also said that you said that in some sense becoming an adult means you take charge of your emotions maybe never said that maybe I just made that up but in context of the mind what's the role of emotion and what is it first of all what is emotion was its role it's several things so psychologists often distinguish between emotion and feeling and in common day parlance we don't don't I think that in motion is a configuration of the cognitive system and that's especially true for the lowest level for the affective state so when you have an effect it's the configuration of certain modulation parameters like arousal valence your your attentional focus whether it's right or narrow interception or extra reception and so on and all these parameters together put you in a certain way to you relate to the environment and to yourself and this is in some sense an emotional configuration and the more narrow sense an emotion is an affective state it has an object and the relevance of that object is given by motivation and motivation is a bunch of needs that are associated with rewards things that give you pleasure and pain and you don't actually act on your needs you act on models of your needs because when the pleasure and pain manifest it's too late you've done everything but so you act on expectations what will give you a pleasure and pain and these are your purposes the needs don't form a hierarchy they just coexist and compete and your organism is why brain has to find it on dynamic homeostasis between them but the purposes need to be consistent so you basically can create a story for your life and make plans and so we organize them all into hierarchies and there is not a unique solution for this and people eat to make art and other people regard to eat and they might up be end up doing the same things but they cooperate in very different ways because they automate codes are different and vie cooperate based on shared purpose everything else it is not cooperation on shared purpose is transactional I don't think I understood the last piece of the achieving the homeostasis are you distinguishing between the experience of emotion and the expression of emotion of course so the experience of emotion is a feeling and in the sense what you feel is an appraisal that your perceptual system is made of the situation at hand and it makes this based on your motivation yes and on the you are estimates not your but of the subconscious geometric parts of your mind that assess the situation in the world with something like a neural network and this neural network is making itself known to the symbolic parts of your mind to your conscious attention by our mapping the them as features into a space so what you will feel about your emotion is a projection usually enjoy your body map you might feel anxiety in your solar plexus and you might feel it as a contraction which is all geometry right your body map is the space that is always instantiate and always available so it's a very obvious cheat if your non-symbolic parts of your brain try to talk to your symbolic parts of your brain to map the feelings into the body map and then you perceive them as pleasant and unpleasant depending on whether the appraisal has a negative or positive valence and then you have different features of them that give you more knowledge about the nature of what you're feeling so for instance when you feel connected to other people you typically feel this new chest region around your heart and you feel this is an expansive feeling in which you're reaching out right and it's very intuitive to encode it like this that's why it's encoded like it's incredible it's in code it's a code in which the non symbolic parts of your mind talk to the symbolic ones and then the expression of emotion is then the final step that could be sort of gestural or visual yeah so on that's part of this MOOC is probably evolved as part of an adversarial communication so as soon as you started to observe the facial expression and poster of others to understand what emotional state they're in others started to use this as signalling and also to subvert your model of the emotional state so we now look at the inflections at the difference between the standard face that they're going to make in this situation right when you were at the funeral everybody expects you to make a solemn face but the solemn face doesn't express whether you're said or not it just expresses that you understand what face you have to make it a funeral nobody should know that you are Trump triumphant so when you try to read the emotion of another person you try to look at the Delta between said truly said expression and the things that are animated mating this face behind the curtain so the interesting thing is so having done these having them as podcast and the video component one of the things I've learned is that now I'm Russian and I don't know how to express emotion on my face when I see that as weakness but whatever the people look to me after you say something they look to my face - just to help them see how they should feel about we said which is fascinating because then they'll often comment on why did you look bored or why did you particularly enjoy that part or why did you whatever it's a kind of interesting it makes me cognizant of on part like you're basically saying a bunch of brilliant things but I am part of the play that you're the key actor and by making my facial expressions and then do and therefore telling the narrative of what the big like the big point is which is fascinating makes me makes me cognizant I'm supposed to be making facial expressions even this conversation is hard because my preference will be to wear a mask with sunglasses to wear I could just listen yes which is understand this because it's intrusive to interact with others this way and basically Eastern European society have a taboo against that and especially Russia the further you go to the east and in the u.s. it's the opposite you are expected to be hyper animated in your face and you're also expected to show positive affect yes and if you show positive effect without a good reason in Russia they people will think you are a stupid and sophisticated person exactly and here positive effect without reason goes either appreciate or goes unnoticed no it's the default it's being expected everything is amazing have you seen these lego movie no there was a diagram where somebody gave the appraisals that exist in the US and Russia so you have your black curve and the lower 10% in u.s. yeah are it's a good start everything about the lowest 10% is it's amazing it's amazing and for Russians yeah everything below the top 10% is it's terrible and then everything except the top percent is I don't like it and the 10% is even so yeah it's funny but it's kind of true no yeah there's a deeper aspect to this it's also how we construct meaning in the u.s. usually you focus on the positive aspects and you just suppress the negative aspects and and our Eastern European traditions we emphasize the fact that if you hold something above the waterline you also need to put something below the waterline because existence by itself is as best neutral right that's the basic intuition if at best neutral yes or can is just suffering the default there are moments of beauty but these moments of beauty are in is inextricably linked to the reality of suffering and to not acknowledge the reality of suffering means that you are really stupid unaware of the fact that basically every conscious being spends most of the times of yeah you just summarized the ethos of the Eastern Europe yeah most of life is suffering with an occasional mobile to beauty and if your facial expressions don't acknowledge the abundance of suffering in the world and in existence itself then you must be an idiot it's an interesting thing when you raise children in the yes and you in some sense preserve the identity of the intellectual and cultural traditions that are embedded in your own families and your daughter asks you about Arielle the mermaid yeah and ask you why is Aria not allowed to play with the humans and you tell her the truth she was a siren siren see people you don't play with your does not end well and then you tell her the original story which is not the one by Anderson which is the romantic one and there's a much darker one Eugene a story what happened so when Dean is a mermaid or a water woman she lives on ground off a river and she meets this prince and they fall enough and the prince really really wants to be with her and she says okay but the deal is you cannot have any other woman if you marry somebody else even though you cannot be with me because obviously you cannot breathe and the water and I have other things to do then managing your Kingdom busy up here you will die and eventually after a few years he falls in love with some princess and marries her and she shows up and quietly goes into his chamber and nobody is able to stop her or willing to do so because she is fierce and she comes quietly and said out of his chamber and they asked her what has happened what did you do when she said I kissed him to death all done and do you know the end is in story right in the Anderson story the mermaid is playing with this prince that she saves and she falls in love with him and she cannot live out there so she is giving up her voice and her tail for a human-like appearance so she can walk among the humans but this guy does not recognize that she is the one that you would marry instead he marries somebody who has a kingdom and economical and political relationships to his own kingdom and so on as he shoots quite tragic she dies so yeah instead Disney The Little Mermaid story has a little bit of a happy ending that's the Western that's the American Way my own problem is business of course that I read Oscar Wilde before I read the other things so I mean doctor II needed inoculated with this romanticism and I think that the mermaid is right you sacrifice your life for romantic love that's what you do because if you are confronted with either serving the Machine and doing the the obviously right thing under the economic and social and all other human incentives that's wrong you should follow your heart so do you think suffering is fundamental to happiness along these lines suffering is the result of caring about things that you cannot change and if you are able to change what you care about to those things that you can't change you will not suffer well then would you then be able to experience happiness yes but happiness itself is not important happiness is like a cookie when you are a child you think cookies are very important and you want to have all the cookies in the world you look forward to being an adult because then you have as many cookies as you want right yes but as an adult you realize the cookie is a tool it's a tool to make you eat vegetables and once you eat your vegetables any way you stop eating cookies for the most part because otherwise you will get diabetes and will not be around for your kids yes but then the cookie the scarcity of a cookie if scarcity is enforced nevertheless so like the pleasure comes from the scarcity yes but the happiness is a cookie that your brain bakes for itself it's not made by the environment the moment cannot make you happy it's your appraisal of the environment that makes you happy and if you can change the appraisal of the environment which you can learn to then you can create arbitrary states of happiness and some meditators fall into this trap so they discover the room this basement room in their brain where the cookies are made and they indulge in stuff themselves and after a few months it gets really old and the big crisis of meaning comes because they saw before that their unhappiness was the result of not being happy enough so they fixed this right they can release the neurotransmitters at will if they train and then the crisis of meaning pops up at a deeper layer and the question is why do I live how can I make a sustainable that is meaningful to me how kinda insert myself would do this and this was the problem that you couldn't solve in the first place well at the end of all this let me then ask that same question what is that the answer to that what could but possibly answer be of the meaning of life what what could an answer be what is it to you I think that if you look at the limiting of life you look at what the cell is the life is the cell is cell yes or this principle the cell it's this self-organizing thing that can participate in evolution in order to make it work it's a molecular machine it needs a self replicator and entropy extractor and the Turing machine if any of these parts is missing you don't have a cell and it is not living right and life is facing the emergent complexity over that principle once you have this intelligent super molecule the cell there is very little as you cannot make it to it's probably the optimal compute for human especially in terms of resilience it's very hard to sterilize the plant at once it's infected with life so it's active function of these three components or the super cell of cell is as present in the cell is present in us and it's just the are just an expression of the cells a certain layer of complexity and the organization of cells that so in a way it's tempting to think of the cell as a von neumann probe if you want to build intelligence on other planets the best way to do this is to infect them b-cells and wait for long enough and visit reasonable chance the stuff is going to evolve into an information processing principle that is general enough to become sentient whether that idea is very akin to sort of the the same dream and beautiful ideas that are expressed the cellular automata in their most simple mathematical form you just inject the system with some basic mechanisms of replication so our basic rules amazing things would emerge that the cell is able to do something that James Hardy calls existential design he points out that in technical design we go from the outside in we work in a highly controlled environment in which everything is deterministic like about computers of our labs or our engineering workshops and then we use this determinism to implement a particular kind of function that dream up and that seamlessly interfaces with all the other deterministic functions that we already have in our world so it's basically from the outside in and biological systems designed from the inside out as seed will become a seedling by taking some of the relatively unorganized matter around it and turn it into its own structure and thereby subdue the environment and cells can cooperate if they can rely on other cells having a similar organization that is already compatible but unless that's that's there the cell needs to divide to create that structure by itself right so it's a self organizing principle that works on a somewhat chaotic environment and the purpose of life in the sense is to produce complexity and the complexity allows you to harvest negentropy gradients that you couldn't harvest without the complexity and in the sense intelligence and life are very strongly connected because the purpose of intelligence is to allow control and the conditions of complexity so basic you shift the boundary between the ordered systems into the realm of the Kay of chaos you build bridgeheads into a chaos with complexity and this is what we are doing this is not necessarily a deeper meaning I think the meaning that we have priors for that we evolved for outside of the priors there is no meaning meaning only exists if a mind protects it right yeah there is only civilization I think that what feels most meaningful to me is to try to build and maintain the sustainable civilization and taking a sliced Abad outside of that we talked about a man with a beard and God but something some mechanism perhaps must have planted the seed the initial seed of the cell do you think there is a God what is a God and what would that look like so if there was no spontaneous abiogenesis in the sense that the first cell formed by some happy random accidents where the molecules just happened to be in the right consolation to each other but there could also be the mechanism of that allows for the random I mean there's like turtles all the way down there seems to be there has to be a head turtle at the bottom consider something really wild imagine is it possible that a gas giant could become intelligent but would that involve so imagine you jet you have vortices that spontaneously emerge on the gas giants like big storm systems that endure for thousands of years and some of these form systems produce electromagnetic fields because some of the clouds are ferromagnetic or something and as a result they can change how certain clouds react rather than other clouds and thereby produce some self-stabilizing patterns that eventually to regulation feedback loops nested feedback loops and control so imagine you have such this thing that basically has emergent self-sustaining self-organizing complexity and at some point this wakes up and realizes and basically LEM Solaris I am a thinking planet yes but I will not replicate because I cannot recreate the conditions of my own existence somewhere else I'm just basically an intelligence that has spontaneously formed because it could and now it was a von Lohmann probe and the best von Neumann purpose at resting might be the cell so maybe it will because it's very very clever and very enduring create cells and sends them out and one of them has infected our planet and I'm not suggesting that this is the case but it would be compatible with the prints Permian hypothesis and with my intuition that abiogenesis is very unlikely it's possible but it's you probably need to all the cosmic dice very often maybe more often than they are planetary surfaces I don't know so god is just a large enough a system that's large enough that allows randomness now I don't think that God has anything to do with creation I think it's a mistranslation of the time wood into the Catholic mythology I think that Genesis is actually the childhood memories of a God so the when sorry that he Anna says is the world the childhood memories of a God it's basically a mind that is memory remembering how it came into being and we typically interpret Genesis is the creation of a physical universe by a supernatural being yes and I think when you'll read it there's light and darkness that is being create it and then you discover sky and ground you create them you will construct the plants and the animals and you give everything their names and so on that's basically cognitive development it's a sequence of steps that every mind is to go through then it makes sense of the world and then you have children you can see how initially they distinguish light and darkness and then they make out directions in it and they discover sky and ground and they discover the plants and the animals and they give everything their name and it's an creative process that happens in every mind because it's not given right your mind has to invent these structures to make sense of the patterns on your retina also if there was some big nerd who set up a server and runs this world on it this would not create a special relationship between us and the nerd this nerd would not have the magical power to give meaning to our existence right so this equation of a Creator God is the God of meaning is a slate off hand you shouldn't do it the other one that is done in Catholicism is the equation of the first mover the prime mover of Aristotle which is basically automaton that runs the universe earth total says if things are moving and things seem to be moving here something must move them right if something moves them something must move the thing that is moving it so there must be a prime mover this idea to say that this prime mover is a supernatural being is complete nonsense right it's an automaton in the simplest case so we have to explain the enormity that this automaton exists at all but again we don't have any possibility to infer anything about its properties except that it's able to produce change in information right so there needs to be some kind of computational principle this is all there is but to say this automaton is identical again with the creator of first cause over the thing that gives meaning to our life is confusion now I think that what we perceive is the higher being that we are part of and the higher being that we are part of is the civilization it's the thing in which you have a similar relationship as the cell has 12 a body and we have this prior because we have evolved to organize in these structures so basically the Christian God in its natural form without the mythology if you to undress it it's basically the Platonic form of the civilization is the is the ideal it's this ideal that you try to approximate when you interact with others not based on your incentives but on what you think is right Wow we covered a lot of ground and we left with one of my favorite lines and there's many which is happiness is a cookie that the brain bakes itself it's been a huge honor and a pleasure to talk to you I'm sure our paths will cross many times again Joshua thank you so much for talking today or they protect your necks yeah it's so much fun I enjoyed it awesome thanks for listening to this conversation with Yoshi Bach and thank you to our sponsors expressvpn and cash app please consider supporting this podcast by getting expressvpn at expressvpn comm slash FlexPod and downloading cash app and using collects podcast if you enjoy this thing subscribe on youtube review it with five stars an apple podcast supported on patreon are simply connect with me on Twitter at lex friedman and yes try to figure out how to spell it without the e and now let me leave you with some words of wisdom from your Shabak if you take this as a computer game metaphor this is the best level for humanity to play and this best level happens to be the last level as it happens against the backdrop of a dying world but it's still the best level thank you for listening and hope to see you next time you |
Karl Friston: Neuroscience and the Free Energy Principle | Lex Fridman Podcast #99 | the following is a conversation with Karl Kristen one of the greatest neuro scientists in history cited over 245 thousand times known for many influential ideas in brain imaging neuroscience and theoretical neurobiology including especially the fascinating idea of the free energy principle for action and perception Karl's mix of humor brilliance and kindness to me are inspiring and captivating this was a huge honor and a pleasure this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars in a podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma n as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it used called Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app allows you to send and receive money digitally let me mention a surprising fact related to physical money of all the currency in the world roughly eight percent of it is actual physical money the other 92 percent of money only exists digitally so again if you get cash out from the App Store Google Play and use the code Lex podcast you get ten dollars in cash shop will also donate ten dollars the first an organization that is helping to advanced robotics at STEM education for young people around the world and now here's my conversation with Carl Fuerst --an how much of the human brain do we understand from the low level of neuronal communication to the functional level to the to the highest level maybe the the psychiatric disorder level well we're certainly in a better position than we were last century how far we've got to go I think is almost an unanswerable question so you'd have to set the parameters you know what constitutes understanding what level of understanding do you want I think we've made enormous progress in terms of broad-brush principles whether that affords a detailed cartography of the functional anatomy of the brain and what he doesn't write down to the microcircuitry in the neurons that's probably out of reach at the present time so the cartography so mapping the brain do you think mapping of the brain the detailed perfect imaging of it does that get us closer to understanding of the mind of the brain so how far does it get us if we have the perfect cartography of the brain I think there are lower bounds on that it's a really interesting question you and it would determine this sort of scientific career you'd pursue if you believe that knowing every dendritic connection every sort of microscopic synaptic structure and right down to the molecular level was gonna give you the right kind of information to understand the computational Natale then you choose to be microscopic and you would study little cubic millimeters of brain for the rest of your life if on the other hand you were interested in holistic functions and a sort of functional anatomy of the sort that a neuropsychologist would understand you'd study brain lesions and strokes you know just looking at the whole person so again it comes back to I won't level do you want understanding I think there are principled reasons not to go too far if you commit to a view of the brain as a machine that's performing a form of inference and representing things there are the understanding that level our understanding is necessarily cast in terms of probability densities and ensemble densities distributions and what that tells you is that you don't really want to look at the atoms to understand the thermodynamics of probabilistic descriptions for how the brain works so I personally wouldn't look at the molecules or indeed the single neurons in the same way if I wanted and understand the thermodynamics of some non equilibrium steady state of a gas or an active material I wouldn't spend my life looking at the the individual molecules that constituted there on somebody look at their collective behavior on the other hand if you go to coarse grain you're gonna miss some basic canonical principles of connectivity and architectures I'm thinking here this bitkha local but this current excitement about high field magnetic resonance imaging and seven tests that why well it gives us for the first time the opportunity to look at the brain in action at the level of a few millimeters that distinguish between different layers of the cortex that may be very important in terms of evincing generic principles of canonical microcircuitry that are replicated throughout the brain there may tell us something fundamental about message passing in the brain and these density dynamics of on your own ensemble population dynamics that underwrite our you know our brain function so somewhere between a millimeter and a meter lingering for a bit under and the big questions if you allow me what to you is the most beautiful or surprising characteristic of the human brain I think it's hierarchical and recursive aspect is recurrent aspect of the structure or of the actual representation of power of the brain well I think one speaks to the other I was actually answering in adèle minded way from the point of view of purely its anatomy and and its structural aspects I mean there are many marvelous organs in them in the body let's take your liver for example you know without it you wouldn't you wouldn't be around for very long and he does some beautiful delicate by chemistry and homeostasis and you're evolved with a finesse that would easily parallel the brain but he doesn't have a beautiful Anatomy he has a simple atomy which is attractive in a minimalist sense but it doesn't have that crafted structure of sparse connectivity and that recurrence and that specialization that the brain has so you said a lot of interesting terms here so the recurrence the sparsity but you also started by saying hierarchical mm-hmm so I've I've never thought of our brain as hierarchical sort of I always thought is just like a giant mess an interconnected mess was very difficult to figure anything out but in what sense do you see the brain is hierarchical well I see it's not a magic soup yeah of course it's what I used to think when I was before I studied medicine and the like so a lot of those terms imply each other so hierarchies if you just think about the nature of a hierarchy how would you actually build one and what you would have to do is basically carefully remove the right connections that destroy the completely connected soups that you might have in mind so a hierarchy is in and of itself defined by a sparse and particular connectivity structure I'm not committing to any particular form of hierarchy the your senses there is some oh absolutely in virtue of the fact that there is a sparsity of connectivity not necessarily of a quality it's obvious and if a quantitative sort so they are it is demonstrably so and that they've far further apart two parts of the brain are the less likely that they are to be wired you know to possess axonal processes neuronal processes that directly communicate one message or messages from one part of the brain to the other part of the brain so we know there's a sparse connectivity and furthermore on the basis of anatomical connectivity and traces studies we know that that a that has that sparsity under writes a higher high rock on a very structured sort of connectivity that might be best understood like a little bit like an onion you know that there there is a concentric sometimes refer to as centripetal by people like Marcel mess ulam hierarchical organization to the brain so you can think of the brain as in a rough sense like an onion and all the sensory information and all the afferent outgoing messages that supply commands to your muscles or to your secrete ryokans come from the surface so there's a massive exchange interface with the world out there on the surface and then underneath there's a little layer that sits and looks at the exchange on the surface and then underneath that there's a layer right there way down to the very center through the deepest part of the onion that's what I mean by a mirror hierarchical organization there's a discernible structure defined by the sparsity of connections that lends the architecture a hierarchical structure that tells one a lot about the kinds of representations and messages so karate on any question is this about the representational capacity or is it about the anatomy well one under writes the other you know if one this simply thinks of the brain as a message passing machine a process that is in the service of doing something then the the circuitry and the connectivity that shape that message passing also dictate its function so you've done a lot of amazing work in a lot of directions so let's look at one aspect of that of looking into the brain and trying to study this onion structure of what can we learn about the brain by imaging it which is one way to sort of look at the anatomy of it broadly speaking what what are the methods of imaging but even bigger what can we learn about it right so well most imaging human neural imaging you might see you know in science journals the speaks to the way the brain works measures brain activity over time so you know that's the first thing to say the way we're effectively looking at fluctuations in neuronal responses usually in response to some sensory input or some instruction some task not necessarily and there's a lot of interest in just looking at the brain in terms of resting state endogenous or intrinsic activity but crucially at every point looking at these fluctuations either induced or intrinsic in the neural activity and understanding them at two levels so normally people would recourse to two principles of brain or kin organization that are complimentary one functional specialization or segregation so what does that mean it simply means that there are certain parts of the brain that may be specialized for certain kinds of processing you know for example visual motion our ability to recognize or to perceive movement in the visual world and furthermore that specialized processing may be spatially or anatomically segregated leading to functional segregation which means that if I were to compare your brain activity during a period of studying viewing a static image and then compare that to the responses of fluctuations in the brain when you are exposed to a moving image say a flying bird eirick we would expect to see restricted segregated differences in activity and those are basically the hot spots that you see in me in surgical parametric maps that test for the significance of the responses that are circumscribed so now basically we're talking about some people of perhaps and currently Calder and neocartography this is a phrenology augmented by modern day near imaging basically finding blobs or bumps on the brain that do this or do that and trying to understand the cartography of that functional specialization so how much how much is there such this is such a beautiful sort of ideal to strive for we we humans scientists would like you like this to hope that there is a beautiful structure to this was like you said there are segregated regions that are responsible for the different function how much hope is there to find such regions in terms of looking at the progress of studying the brain oh I think in Nomis progress has been made in the past you know 20 or 30 years you know so this is beyond incremental you know at the advent of brain imaging the very notion of functional segregation was just a hypothesis based upon a century if not more of careful neuropsychology looking at people who had lost via insult or traumatic brain injury particular parts of the brain and then saying well they can't do this or they can't do that for example losing the visual cortex and not being able to see or using losing particular parts of the visual cortex or regions known as v5 or the middle temporal region MT noticing that they selectively could not see moving things and so that created the the hypothesis that perhaps movement processing visual movement processing was located in this functionally segregated area and you could then put go and put invasive electrodes in animal models and say yes indeed we can excite activity here we can form receptive fields that are sensitive to or defined in terms of visual motion but at no point could you exclu the possibility that everywhere else in the brain was also very interested in visual motion by the way I apologize to interrupt buzz tiny little tangent you said animal models just out of curiosity from your perspective how different is the human brain versus the other animals in terms of our ability to study the brain well clearly the far further away you go from a human brain the the greater the difference is but not not as remarkable as you might think so people will choose their level of approximation to the human brain depending upon the other kinds of questions that they want to answer so if you're talking about sort of canonical principles of microcircuitry it might be perfectly okay to look at a mouse indeed you could even look at flies worms if on the other hand you wanted to look at the finer details of organization of visual cortex and v1 v2 there's a designated sort of patches of cortex that may or may do different things indeed do you probably want to use a primate that looked a little bit more like a human because there are lots of ethical issues in terms of you know the use of non-human primates to transfer questions about the about human anatomy I think most people assume that the most of the important principles are conserved in a continuous way you know from right from well yes worms right to yummy so now returning to so that was the early of ideas are studying the the the really functional regions of the brain base if there's some damage to it to try to infer that there's that part of the brain might be somewhat responsible for this type of function so what where does that lead us what are the next steps beyond that right well this actually reverse a bit come back to your sort of notion that the brain is a magic sue but that was actually a very prominent idea at one point notions such as Lashley's law of mass action inherited from the observation that for serve animals if you just took out spoonfuls of the brain it didn't matter where you took these spoonfuls out they always showed the same kinds of deficits so you know it was very difficult to infer functional specialization pure on the base basis of lesion deficit studies but once we had the opportunity to look on the brain or lighting up in its it's literally it's sort of excitement neuronal AM excitement when looking at this versus that one was able to say yes indeed these functionally specialized responses are very restricted and then they're here or they're over there if I do this then this part of the brain lights up and that became doable in the early 90s in fact shortly before with the advent of positron emission tomography and then functional magnetic resonance imaging came along in the early 90s and since that time there has been an explosion of discovery refinement confirmation you know there are people who believe that it's all in the anatomy if you understand the anatomy then you understand the function at some level and many many hypotheses were predicated on a deep understanding of the anatomy and the connectivity but they were all confirmed and taking much further with newer imaging so that's what I meant by we've made an enormous amount of progress in in this century indeed and in relation to the previous century by looking at these funky selective responses but that wasn't the whole story so there's a sort of near phrenology but finding bumps and hotspots in the brain that did this or that the bigger question was of course the functional integration how all of these regionally specific responses were orchestrated how they were distributed how did they relate to distributed processing and indeed representations in the brain so then you turn to the more challenging issue of the integration the connectivity and then we come back to this beautiful sparse recurrent hierarchical connectivity that seems characteristic of the brain and probably not many other organs and but nevertheless we'll come back to this this challenge of trying to figure out how everything is integrated but what's your feeling what's the general consensus how we moved away from the magic soup view of the brain yes so there is a deep structure to it yeah that and then maybe further question you said some people believe that the structure is most of it that you can really get at the core of the function by just deeply understanding the structure yeah where do you sit on that do you I think it's called some monster yes yeah yes it's a worthy pursuit of going of studying of through imaging and all the different methods to actually study no absolutely let's go yeah yeah sorry I'm just I'm just nutty you you you were accusing me of using lots of long words and then you introduce one that which is deep which is interesting and because deep is this or Millenial equivalent of hierarchical so if you've put a deep in front of anything you're very millennial and start trending but you yes you're also implying a hierarchical architecture so that's it is a depth which is for me the beautiful thing that's right the word deep kind of yeah exactly it implies hierarchy I didn't even think about that that indeed the implicit meaning of the word deep is a hierarchy yep yeah yeah so deep inside the onion is a central view so if you put maybe briefly if you could paint a picture of the kind of methods of neuro imaging maybe the history which you are a part of you know from statistical parametric mapping I mean just what what's out there that's interesting for people maybe outside the field that to understand of what are the actual methodologies of looking inside the human brain right well there you can answer that question from two perspectives basically it's the modality you know what kind of signal are you measuring and they can range from and let's limit ourselves to some imaging based non-invasive techniques so you've essentially got brain scanners and Brent's cannons can either measure the structural attributes the amount of water of the Mount of fat on the amount of iron in different parts of the brain you can make lots of inferences about the structure of the organ of the sort that you might have abuse from an x-ray but a you know a very nuanced x-ray that is looking at this kind of property of that kind of property so looking at the anatomy not invasively is would be the first sort of earner imaging that people might want to employ then you move on to the kinds of measurements that reflect dynamic function the most prevalent of those fall into two camps you've got these metabolic sometimes hemodynamic blood related signals so these metabolic and/or hemodynamic signals are basic proxies for elevated activity and message passing and neuronal dynamics in particular parts of the brain characteristically though the time constants of these hemodynamic or metabolic responses to neural activity are much longer than the neural activity itself and this is uh this is refering forgive me for the dumb questions but this would be referring to blood like the flow of blood absolutely so there's a ton of it seems like there's a ton of blood vessels in the brain yeah so but what's the interaction between the flow of blood and the function of the new and neurons is there an interplay there or yeah yeah yeah and that interplay accounts for several careers of world-renown solutely so this is known as neurovascular coupling is exactly what you said it's how how does a neural activity the neuronal infrastructure natural message passing that we think underlies our capacity to perceive and act how is that coupled to the vascular responses that that supply the energy for that neural processing so there's a delicate web or of large vessels arteries and veins that gets progressively finer and finer in detail until it perfuses at a microscopic level the machinery where little neurons lie so coming back to this sort of onion perspective we were talking before using the onion there's a metaphor for a deep hierarchical structure but also I think it's just an anatomical anatomically quite a useful metaphor all the action all the heavy lifting in terms neural computation is done on the surface of the brain and then the interior of the brain is constituted by fatty wires essentially axonal processes that are enshrouded by myelin sheaths and these give the ER when you dissect them they look fatty and white and so it's called white matter as opposed to the actual neuro peel which does the computation constituted largely by neurons and that's known as gray matter so the gray matter is a a a surface or a skin that sits on top of this big ball now we are talking magic soup but it's a big ball of collections like spaghetti very carefully structured with sparse connectivity that preserve this deep hierarchical structure but all the action takes place on the surface on the cortex of the onion and that means that you have to supply the right amount of blood flow the right amount of nutrient which is rapidly absorbed and used by neural cells that don't have the same capacity that your leg muscles would have to basically spend their energy budget and then claim it back later so one peculiar thing about cerebral metabolism brain metabolism is it really needs to be driven in the moment which means you basically have to turn on the taps so if there's lots of neural activity in one part of the brain a little patch of a cup few millimeters even less possibly you really do have to water that piece of the garden now and quickly and that by quickly I mean within a couple of seconds so that contains a lot of infant the imaging could tell you a story of what's happening absolutely but it is slightly compromised in terms of the resolution so the the deployment of these little micro vessels that the water the garden to enable the activity to to the neural activity to play out the the spatial resolution is in order of a few millimeters and crucially the temporal resolution is the order of a few seconds so you can't get right down and dirty into the actual spatial and temporal scale of neuronal activity in and of itself to do that you'd have to turn to the other big imaging modality which is the recording of electromagnetic signals as they're generated in real time so here the temporal bandwidth if you like on the temp the low limit on the temporal resolution is incredibly small you're talking about near nalle' seconds milliseconds and then you can get into the phasic fast responses there is in of itself the neural activity and start to see the succession or cascade of hierarchal recurrent message-passing evoked by a particular stimulus but the problem is you're looking at electromagnetic signals that have passed through an enormous amount of magic soup or spaghetti of collectivity and through the scalp and the skull and it's become spatially very diffused so it's very difficult to know where you are so you've got this sort of catch-22 you can either use an imaging modality it tells you within millimeters which part of the brain is activated we don't know when or you've got these electromagnetic a EEG m EG setups that tell you to within a few milliseconds when folks something has responded being aware so you've got these two complementary measures either in direct via the blood flow or direct via the electromagnetic signals caused by neural activity these are the two big imaging devices and the second level of responses your question what what are they yeah from the outside one of the big ways of of using this technology so once you've chosen your the kind of mirror imaging they want to use to answer your set questions and sometimes it would have to be both then you've got a whole raft of analyses time series analysis usually that you can bring to bear in order to answer your questions or address your hypothesis about those data and interesting that they they've both fall into the same two camps we're talking about before you know this dialectic between specialization and integration differentiation and integration so it's the cartography that blob ology analyses my apology and probably shouldn't transfer much but just the herd of fun word the blur the robot ology blood ology its ideologies of which means the study of blobs that's nothing for are you being witty and humorous or is there an actual there's the word blob ology ever appear in a text book somewhere it would appear in a popular book it would not appear in a worthy specialist journal yeah it's the fond word for the study of literally little blobs on brain maps showing activations so the kind of thing that you'd see in you know the newspapers on ABC or BBC reporting the latest finding from a from brain imaging interestingly though the maths involved in that stream of analysis does actually call upon the mathematics of blobs so seriously they actually called Euler characteristics and you know they have a lot of fancy names in mathematics we'll talk about about your ideas in free energy principle I mean there's a echoes of blobs there when you consider sort of entities so mathematically speaking yes absolutely yeah yes anyway well the first circumscribe well-defined yes--you entities of well in from the free energy point of view entities of anything but from the point of view of the analysis the cartography of you know of the brain these are the entities that constitute the evidence for this functional segregation you have segregated this function in this blob alledge is not outside of the blob that's basically the oh if you were a map maker of America and you did not know instruction the first thing were you doing constituting or creating a map will be to identify the cities for example or the route mountains and all the rivers all of these uniquely spatially localizable features possibly topological features have to be placed somewhere because that requires our mathematics of identify what does a set it City look like on a satellite image or what does a river look like I want as a mountain look like what would it you know what data features wood is wood evidence that that particular table you know that particular thing that you wanted to put on the map and they normally are characterized in terms of literally these blobs or these of now the way looking at and this is a certain statistical measure of the degree of activation crosses a threshold and in crossing that threshold in a spatially restricted part of the brain it creates a blob and that's basically what physical parametric mapping does it's basically mathematically finessed phlebology okay so those you kind of describe these two methodologies for one is temporally noisy one is spatially noisy and you kind of have to play and figure out what what can be useful yeah it'd be great if you can sort of comment I got a chance recently to spend a day at a company called neural link that uses brain computer interfaces and their dream is to well there's a bunch of sort of dreams but one of them is to understand the brain by sort of you know getting in there past the so calls that are factory wall getting in there be able to listen communicate both directions what are your about this the future of this kind of technology of brain computer interfaces to be able to now have a have a window or direct contact within the brain to be able to measure some of the signals to be able to send signals to understand some of the functionality of the brain ambivalent my sense is ambivalent so it's a mixture of good and bad and I acknowledge that freely so the good bits if you just look at the legacy of that kind of reciprocal but invasive geo brain stimulation I didn't paint a complete picture when I was talking about some of the ways we understand the brain prior to your imaging it wasn't just leave lesion deficit studies some of the early work in fact literally a hundred years from where we're sitting at the institution neurology what was done by stimulating the brain of say dogs and looking at how they responded either but with them the muscles or with the salivation and imputing what that part of the brain must be doing that if i stimulated then yeah and i vote this kind of response then that tells me quite a lot about the functional specialization so there's a long history of brain stimulation which in continues to enjoy a lot of attention nowadays positive attention oh yes absolutely you know deep brain stimulation for Parkinson's disease is now a standard treatment and also a wonderful vehicle to try and understand the neuronal dynamics underlie movement disorders like Parkinson's disease even interest in transmitting its magnetic stimulation stimulating with the magnetic fields and will it work in people who depressed for example quite a crude level of understanding what you're doing but you know there are there is historical evidence that these kinds of brute force and interventions do change things then you know a little bit like buying the TV whether the valves are working properly but it still it works so you know there is a long history brain computer interfacing a BCI I think is a beautiful example of that it's sort of carved out its own lesion its own aspirations and they've been enormous advances within limits advances in terms of our ability to understand how the brain the embodied brain engages with the world I'm thinking of here of sensory substitution the augmenting our sensory capacities by giving ourselves extra ways of sensing than sampling the world ranging from sort of trying to replace lost visual signals through to giving people completely new signals so the well I think most engaging examples of this is equipping people with a sense of magnetic fields so you can actually give them magnetic sensors that enable them to feel should we say tactile pressure around their tummy where they are in relation to them to the magnetic field of the earth incredible and after a few weeks they take it for granted they integrated the embody assimilate this new sensory information into the way that they feet literally feel their world were now equipped with this sense of magnetic direction so that tells you something about the brain's plastic potential to remodel to in term and its plastic capacity to suddenly try to explain the sensory data at hand by augmenting or augmenting the the sensory sphere and the kinds of things that you can measure clearly that's purely for entertainment and understanding the knee or the nature and the power of our brains I would imagine the most BCI is pitched at solving clinical and human problems such as locked-in syndrome paraplegia or replacing lost sensory capacitors like blindness and death deafness so then we come to the more on the negative part of my own the other side of it so I you know I don't want to be deflation because much of my deflationary comments was probably large out of ignorance there anything else but generally speaking the the bandwidth and the bit rates that you get from brink of Pewter interfaces as we currently know them we're talking about bits per second so that would be like me only being able to communicate with any world or with you using very very very slow Morse code and it is not in the in even within an order of magnitude near what we actually need for an inactive realization of what people aspire to when they think about sort of curing people with paraplegia or replacing site despite heroic efforts so one has to ask is there a lower bound on the kinds of recurrent information exchange between a brain and some augmented or artificial interface and let me come back to interestingly what I was talking about before which is your if you're talking about function in terms of inference and I presume we'll get to that later on in terms of the free energy principle Minh the moment they may be fundamental reasons to assume that is the case we talk about ensemble activity we're talking about basically for example let's paint challenge facing brain-computer of interfacing in terms of controlling another system that is highly and deeply structured very relevant to our lives very nonlinear the rests upon the kind of non-equilibrium steady states and dynamics that the brain does the weather right so good example here imagine you had some very aggressive satellites that could produce signals that could be termed some little parts of the of the weather system and then what you're asking now is can i meaningfully get into the weather and change it meaningfully and make the weather respond in a way that I want it to you're talking about chaos control on a scale which is almost unimaginable so there may be fundamental reasons why BCI as you might read about it in a science fiction novel aspirational BCI may never actually work in the sense that to really be integrated and be part of the system isn't impermanent requires you to have evolved with that system that you know you you have to be part of a very delicately structured deeply structured dynamic ensemble activity that is not like rewiring a broken computer or plugging in a peripheral interface adapter it is much more like getting into the weather pans or a come back to your magic soup is getting into the active matter and meaningfully relate that to the outside world so I think there are an enormous challenges there so I think the example the weather is a brilliant one and I think you paint a really interesting picture and it wasn't as negative as they thought it's essentially saying there's it might be incredibly challenging including the lower bound of the bandwidth and so on I kind of so and just to full disclosure I come from the machine learning world so my my natural thought is the hardest part is the engineering challenge of controlling the weather of getting those satellites up and running in and so on and once they are then the rest is of fundamentally the same approaches that allow you to be to win in the game of Go will allow you to potentially play in this soup in this chaos so I have I have a hope that so machine learning methods will will help us play in the soup as but perhaps you're right that it is a via biology and the brain is just an incredible an incredible system that may be almost impossible to get in but for me what seems impossible is is the incredible mess of blood vessels that you also described without you know we also value the brain you can't make any mistakes you can't damage things so to me that engineering challenge seems nearly impossible one of the things I was really impressed by at neuro-link is just just talking to brilliant neurosurgeons and the roboticists that it made me realize that even though it seems impossible if anyone can do it it's some of these world-class engineers that are trying to take it on so so I think the conclusion of our discussion here is of this part is is basically that the problem is really hard but hopefully not impossible absolutely so if it's ok let's start with the basics so you've also formulated a fascinating principle the free energy principle could we maybe start at the basics and what is the free energy principle well in fact the free energy principle inherits a lot from the building of these data analytic approaches to these you know very high dimensional time soon as you get get from the brain so I think is interesting to acknowledge that and in particular the analysis tools that try to address the other side which is a functional integrations on the connectivity analyses on the one hand but I should also acknowledge it inherits an awful lot from machine learning as well so the free energy principle and is just a formal statement that the the existential imperatives for any system that manages to survive in a changing world is can be cast as a an inference problem in the sense that you can interpret the probability of existing as the evidence that you exist and if you can write down that problem of existence as a statistical problem that you can use all the maths that has been developed for inference to understand and characterize the ensemble dynamics that must be in play in the service of that inference so technically what that means is you can always interpret anything that exists in virtue or being separate from the environment in which it exists as trying to minimize variational free-energy and if you're from the machine learning community you will know that as a negative evidence lower bound or a negative elbow which is the same as saying you're trying to maximize or it will look as if all your dynamics are trying to maximize the complement of that which is the marginal likelihood or the evidence for your own existence so that's basically that you know that the free energy principle of it but even take a sort of a small step back or as you said the existential imperative there's a lot of beautiful poetic words here but to put it crudely there's a it's a fascinating idea of basically just of trying to describe if you're looking at a blob how do you know this thing is alive what does it mean to be alive what does it mean to be to exist and so you can look at the brain you can look at parts of the brain or you this is just the general principle that applies to almost thing and ye and you system it that's just a fascinating sort of philosophically at every level question and the methodology to try to answer that question what does it mean to be alive yeah so that that that's a huge endeavor and it's nice that there's at least some from some perspective a clean answer so maybe can you talk about that optimization view of it so what what's trying to be minimized to maximize what a system that's alive what is it trying to minimize right you've you've made a big move yes to make big moves but you've assumed that the things the thing exists before the in a state that could be living on nonliving so I may ask you or what licenses you to say that something exists that's why I use the word existential it's beyond living it's just existence so if you drill down onto the definition of things that exist then they have certain properties if you borrow the maths from non-equilibrium steady state physics that enable you to interpret their existence in terms of this optimization procedure so it's good you introduce the word optimization so what the free-energy principle in its sort of most ambitious but also most deflationary and simplest says is if something exists then it must by the mathematics of non-equilibrium steady state exhibit properties that may look as if it is optimizing a particular quantity and it turns out that particular quantity happens to be exactly the same as the evidence lower bound in machine learning or Bayesian model evidence in Bayesian statistics or and then I can list a whole other you know list of ways of understanding this this this key quantity which is a bound on on surprisal self information if you know information theory there are whole there are a number of different perspectives on this contry it's this basically the log of probability of being in a particular state I'm telling this story as an honest and attempt to answer your question and I'm answering it as if I was pretending to be a physicist who was trying to understand the fundaments of non-equilibrium steady state and I shouldn't really be doing that because the last time I was taught physics I was in my twenties what kind of systems when you think about the free energy principle what kind of systems are you imagining it's a sort of more specific kind of case study you know I'm imagining a range of systems but you're at its simplest a sim a single-celled organism that can be identified from its eco nation or its environment so at its simplest that that's basically what what I always imagined in my head and you may ask well is there anything how on earth can you even in elaborate questions about the existence of a acing a single drop of oil for example yeah what but there aren't D questions there why doesn't the oil why doesn't the thing the interface between the drop of oil that contains an interior and the thing that is not the drop of oil which is the solvent in which it is immersed how does that interface persist over time why doesn't the oldest dissolve into solvent so what special properties of the exchange between the surface of the oil drop and the external states in which it's immersed if you're physicists say would be the heat bath you know you've got a you've got a physical system an ensemble again with about ten stomachs ensemble dynamics an ensemble of ik of atoms or molecules immersed in the heat path but the question is how did the heat bath get there and why is it not dissolved why was it maintaining itself exactly what actions is it I mean it's such a fascinating idea of a drop of oil and I guess it would dissolve in water wouldn't dissolve in water so what precisely so why not so why not why not and how do you mathematically describe me is such a beautiful idea and also the idea of like where does the thing where does the drop of oil and yeah and where does it begin right so I mean you're asking the questions deep in in a normal area but what you can do you see so this is a deflationary part of it can I just qualify mouths so by saying that normally when I'm asked this question I answer from the point of view of a psychologist we talk about predictive processing and pretty coding and you know the brain is an inference machine but you haven't asked me from that perspective I'm answering from the point of view of a physicist so you you know the question is not so much why but if it exists what properties must it display so that's the deflation in part the 300 prints we print the 300 principal does not supply and answer as to why it's saying if something exists then he must display these properties that's that's the other sort of the thing that's on offer and it so happens that these properties a must display are actually intriguing and have this inferential gloss this there's this sort of self evidencing loss that inherits from the fact that the very preservation of the boundary between the oil drop and the not oil drop requires an optimized of a particular function or a functional that's that defines the presence of the existence of of this order which is why I started with existential imperatives and the it ISM it is a necessary condition for existence that this must occur because the thing the boundary basically defines the things that's existing so it is that self-assembly aspect it's that for the you hinting at in biology sometimes known as Auto poiesis in computational chemistry Mis self-assembly it's the what what does it look like sorry how would you describe things that configure themselves out of nothing the where they clearly demarcate themselves from the states on the soup in which they are immersed so from the point of view of computational chemistry for example you just understand that as a configuration of a macromolecule to minimize its free energy is thermodynamic free energy it's exactly the same principle that we've been talking about that thermodynamic free energy is just the negative elbow it's the same mathematical calm construct so the very emergence of existence of structure or form that can be distinguished from the environment or the thing that is not the thing necessitates the you know the existence of an objective function then it looks as if it is minimizing it's finally a free energy minima and so just to clarify I'm trying to wrap my head around so the the free energy principle says that if something exists these are the properties it should display yes so what what that means is we can't just look we can't just go into a soup and there's no mechanism if free energy principle doesn't give us a mechanism to find the things that exist is that what it was implying is being applied that you can kind of use it to reason to think about like study a particular system and say does this exhibit these qualities that's an excellent question to answer that after I have to return to your previous question but what's the difference between living and nonliving things actually Society so yeah that maybe we can go there you kind of drew a line and and forgive me for the stupid questions but the you kind of draw a line between living and existing yeah is there an interesting sort of distinction distinction yeah I think there is so you know things do exist grains of sand rocks on the moon trees you so all of these things can be separated from the environment in which they are immersed and therefore there must at some level be optimizing their free energy taking this sort of model evidence interpretation of this quantity that basically means their self evidencing another nice little twist of phrase here is that you are your own existence proof you know statistically speaking which I don't think I said that somebody did but I love that phrase you are your own existence proof yeah so it's ur existential isn't it I'm gonna have to think about there for a few days yeah the view there's a beautiful line so the the step through to answer your question about you know what's it good for big girl on the following lines first of all you have to define what it means to exist which down as you rightly pointed out you have to define what probabilistic properties must the states of something possess so that it has so it knows where it finishes and then you write out that down in terms of statistical independence is again sparsity again it's not what's connected or what score elated or what depends upon what it's what's not correlated and what doesn't depend upon something again it comes down to the the deeper structures not in this is hierarchal but the suddenly the the structures that emerge from removing connectivity in dependency in this instance basically being able to identify the surface of the oil drop from the water in which it is immersed and when you do that you start to realize well there are actually four sub kinds of states in any given universe that contains anything the things that are internal to the surface the things that are external to the surface and the surface in and of itself which is why I use a metaphor a little single-celled organism that has an interior and exterior and then the the surface of the cell and that's mathematically a Markov blanket just to pause I'm in awe of this concept that there's the stuff outside the surface stuff inside the surface in the surface itself the Markov blanket it's just the most beautiful kind of notion about trying to explore what it means to exist you're automatically I apologize this is a beautiful idea but came out of California so that's I changed my mind I take it all so sorry anyway so what you were just talking about the surface about the market yeah so this surface or this blanket these blanket states that are this you know the because they are now defined in relation to these Independence's and your Walker what different states internal or blanket or external states can which ones can influence each other and which cannot influence each other you can now apply standard results that you would find in non equilibrium physics or steady state or thermodynamics or hydrodynamics usually out of equilibrium solutions and apply them to this partition and what it looks like as if all the Norman normal gradient flows that you would associate with any non equilibrium system apply in such a way that to part of the Markov blanket and the internal states seem to be hill climbing or doing a gradient descent on the same quantity and that means that you can now describe the very existence of this oil drop you can write down the existence of this holdup in terms of flows dynamics equations of motion where the blanket States or part of them we call them active States and the internal states now seem to be and must be trying to look as if they're minimizing the same function which is a lot of probability of occupying this but these states the interesting thing is that what would they be called if you were trying to describe these things there were what we're talking about are internal states external states and blanket States now let's carve the blanket States into to sensory states and active States operationally it has to be the case that in order for this carving up in two different sets of states to exist the active States the Markov blanket cannot be influenced by the external states and we already know that the internal States can't be influenced by the external States cousin the blanket separates them so what does that mean well it means the active States the internal states are now jointly not influenced by external states they only have autonomous dynamics so now you've got a picture of an oil drop that has autonomy it has autonomous States it has autonomous days in the sense that there must be some parts of the surface of the oil drop that are not influenced by the external states and all the Interior and together those two states endow even a little oil drop with autonomous states that look as if they are optimizing their variational free energy or their negative elbow their model evidence and that would be an interesting intellectual exercise and you could say you can even go into the realms of pants psychism that everything that exists is implicitly making inferences on self evidencing now we made the next move but what about living things I mean so let me ask you what's the difference between an oil drop and a little tadpole or a little lava or plankton the picture which is painted of an oil drop just immediately in a matter of minutes took me into the world of pants is where you you just convinced me what made me feel like an oil drop is a living certainly an autonomous system but almost the living system so as a capability sensory capabilities and acting capabilities and it maintains something so what is the difference between that and something that we traditionally think of as a living system that it could die or you can't I mean a yab mortality I'm not I'm not exactly sure I'm not sure what the right answer there is because they can move them like movement seems like an essential elements to being able to act in the environment but the oil drop is doing that so I don't know easy the mall drop will be moved but does it inner of itself move autonomously well it or the surface is performing actions that maintain its structure yeah you're being too clever I was out of service certified a passive little oil drop this is sitting there yeah and the bottom on the top of a glass sure I guess what I'm trying to say is you're absolutely right you hear you've even nailed it its movement yeah so where does that movement come from if it comes from the inside then then you've got I think something that's living what do you mean from the inside what I mean is that the internal States the can influence reactive states that where the actor states can influence but they're not influenced by the external states can cause movement so there are two types of oil drops if you like there are oil drops where the internal states are so random that they average themselves away and the thing cannot on a balance on average when you do the averaging move so a nice example of that will be the Sun the Sun Sony has internal States and lots of intrinsic autonomous activity going on but because it's not corded because it doesn't have the deep in the Millennial sense a hierarchical structure and the brain does there is no overall mode or pattern or organization that expresses itself on the surface that allows it to actually swim it it can certainly have you're a very active surface but on mass at the scale of the actual surface of the Sun the average position of that surface cannot in itself move because the internal dynamics are more like a hot gas they are literally like a hot gas whereas your internal dynamics are much more structured and deeply structured and now you can express on your mark of in your active States with your muscles and and your secretary organs your autonomic nervous system and its effectors you can actually move and that's all you can do and that's something which you know if you haven't thought of it like this before I think it's nice just realize there is no other way that you can change the universe other than simply moving whether that moving is articulating my with my voice box or walking around or squeezing juices out of my secreting organs there's only one way you can change the universe it's moving and in the fact that you do so non randomly it makes you alive yeah so it's not non-randomness so that the that's what sohe's and that would be manifesting we realize in terms of essentially swimming essentially moving changing one shape a morphogenesis that is dynamic and possibly adaptive so that that's what I was trying to get out between the difference from the oil drop and the little tadpole the the tampo is moving around its his active states are actually changing the external states and there's now a cycle an action perception cycle if you like a recurrent dynamic that's going on that depends upon this deeply structured autonomous behavior the rests upon internal dynamics that are not only modeling they data impressed upon their surface or the blanket States but they are actively resampling those data by moving they're moving towards Kemet say chemical gradients in chemotaxis so they've gone beyond just being good little models of the kind of world they live in for example an oil droplet could in a pan psychic sense be construed as a little being that has now perfectly inferred it's a passive nonliving oil-drop living in a bowl of water no problem no but to now equipped that oil drop with the ability to go out and test that hypothesis about different states and beings so we can actually push its surface over there over there and test for chemical gradients or then you start to move to much more lifelike form now this cells is on fun theoretically interesting but it it actually is quite important in terms of reflecting what I have seen since the turn of the millennium which is this move towards it and they inactive an embodied understanding of intelligence and you say you're from machine learning yes so what that means this this sort of the central importance of movement I think has yet to really hit machine learning it certainly has now diffused itself throughout robotics and perhaps you can say certain problems in active vision where you actually have to move the camera to sample this and that but machine learning of the data mining deep learning saw simply hasn't contended with this issue what is done instead of dealing with the movement problem and the active sampling of data it is said we don't need to worry about we can see all the data because we've got big data so we need nor movement so that for me is you know an important omission in current machine learned and current machine learning is much more like the oil drop yes but an oil drop that enjoys exposure to nearly all the data you see to be first as opposed to the tadpoles swimming out to find the right data for example it likes food that's a good hypothesis test analyst go and move and ingest food for example and see what that you know is that evidence that I'm the kind of thing that likes this kind of food so the the next natural question and forgive this question but if we think of sort of even artificial intelligence systems we just paint a beautiful picture of existence and life so do you do you ascribe would you do you find within this framework a possibility of defining consciousness or exploring the idea of consciousness like what you know self-awareness and expand it to consciousness thing yeah how can we how can we start to think about consciousness within this framework is it possible yeah I think it's possible to think about it whether you'll get again I'm not sure that I'm licensed to like question you I think you'd have to speak to a qualified philosopher to get a definitive answer that but certainly there's a lot of interest in using not just these ideas but related ideas from information theory to try and tie down the the maths and the calculus and the geometry of consciousness either in terms of sort of a minimal consciousness III even less than a minimal selfhood and what I'm talking about is the ability effectively to plan so have agency so you could argue that a virus does have a form of agency in virtue of the way that it selectively finds hosts and cells to live in and moves around but you wouldn't endow it with the capacity to think about planning and moving in a purposeful way where it countenances the future whereas you might announce you might think an ants not quite as unconscious as a virus it certainly seems to have a purpose it talks to its friends on route during its foraging it has a different kind of autonomy which is biotic but beyond a virus so there's something about so there's some line that has to do with the complexity of planning yes that may contain an answer I mean it'd be beautiful if if we can find a line beyond which you could say look being as cautious yes it would be these are wonderful lines that we've drawn with existence life and consciousness yes it will be very nice what one little wrinkle there and this is something I've only learned in the past few months is the notion the philosophical notion of vagueness so you're saying it would be wonderful to draw a line and I had always assumed that that line at some point would be drawn and until about four months ago and the philosopher told me about vagueness so I know if you've come across this but it's a technical concept and I think most revealingly illustrated with at what point does a pile of sand become a pile is it one grain two grains three grains or four grains so at what point would you draw the line between being a pile of sand and a collection of some of the grains of sand in the same way is it right to ask where would I draw the line between conscious and unconscious and it might be a vague concept having said that I agree with you entirely I know systems that have the ability to plan so just technically what that means is your your inferential self evidencing by which I simply mean the dynamics literally the thermodynamics and gradient flows that underwrite the preservation of your oil droplet like form are described as a canvas who has an optimization of Molag Bayesian model evidence in your elbow that self evidencing must be evidence for a model of what's causing the sensory impressions on the sensory part of your surface or your Markov blanket if that model is capable of planning it must include a model of the future consequences who your active States or your action just panning so we're now in the game of planning as inference now notice what we've made though we've made quite a big move away from big data and machine learning because again it's the consequences of moving it's a consequence of selecting those data or those data or looking over there and like that tells you immediately that even to be a contender for a conscious artifact or you know a as it's strong AI or generalize a little no then you've got to have movement in the game and furthermore you've got to have a genitive model of the sort you might find in say a variation or two encoder that is thinking about the future conditioned upon different courses of action now that brings a number of things to the table which which now is start think more those who've got all the right ingredients talk about consciousness I've now got to select an among a number of different courses of action into the future as part of planning I've now got free will the act of selecting this course of action or that policy or that policy or that action suddenly makes me into an inference machine of self evidencing artifact that now looks as if it's selecting amongst different alternative ways forward as I actively swim here or swim there all yes look over here look over there so I think you've now got to a situation if there is planning in the mix you're now getting much closer to that line if that line whatever to exist I don't think it gets you quite as far as self aware though I think you and then your you have to I think grapple with the question how would formally write down a calculus or a maths of self-awareness I don't think it's impossible to do but I think you would know we pressure on you to actually commit to a formal definition or a mean by self awareness I think most people that I know would probably say that a goldfish no pet fish was not self-aware they would probably argue about their favourite cat but would be quite happy to say that that mom was self-aware so I mean but that might very well connect to some level of complexity with planning it seems like self-awareness is essential for complex planning yeah do you want to talk about further coffee you're absolutely right again the line is unclear but it seems like integrating yourself into the world into Europe into your planning is essential for constructing complex plans yes yeah so I'm mathematically describing that in the same elegant way as you have the free energy principle might be difficult well yes and no I don't think that well perhaps we should just can we just go back that's a very important answer you gave like I think if I just unpacked it you know you'd see the truisms or you've just you've just exposed France but maybe so yeah I I'm mindful that I didn't answer your question before well yeah what's the pre hundred principle good for is it just a pretty theoretical exercise to explain non-equilibrium steady stays yes it is it does nothing more for you than that it can be regarded as our arrogance but you know it is of the sort of theory of natural selection or a hypothesis of natural selection beautiful undeniably true but tells you absolutely nothing else yeah y-you have legs and eyes and you know it tells you nothing about the actual phenotyping and it wouldn't allow you to build something so the free press or directly the thigh itself is is as vacuous as most tautological theories and by tautological of course I'm talking to that you know the theory of Naturals the survival of the fittest and once the fittest isn't survival while this why cuz the fitter in disc around in circles is in a sense the free energy principle has that same you know deflationary tautology I'm you're under the hood it's yeah it's two ago it's a characteristic of things that exist why they exist because they minimize their energy while the minified know as a free energy because they exist and use keep on going round and round but the what the practical thing which you don't get from natural selection but you could say has now manifest in things like differential evolution or genetic algorithms or NCM see for example in machine learning the practical thing you can get is if it looks as if things that exist are trying to have density dynamics and look as though they're optimizing a variational free energy and a variational free energy has to be a functional or a gerund to model a probabilistic description of causes and consequences causes out there consequences in the sensorial on the sensory parts of the Markov blanket then it should in theory possible to write down the genitive model work out the gradients and then cause it to autonomously self-evidence so you should be able to write down oil droplets you should be able to create artifacts where you have supplied the objective function their supplies the gradients and supplies the self-organizing dynamics to non-equilibrium steady state so there is actually a practical application the free energy principle when you can write down your required evidence in terms of well when you can ride down the Geraldton model that is the thing that has the evidence the probability of these sensory data on this data given that given that model is effectively the thing that the elbow of the variational free energy bounds little proximate s' that means that you can actually write down the model and the kind of thing that you want to engineer the kind of AGI odd artificial general intelligence that you want to manifest probabilistically and then you engineer or world work where you would engineer a robot and a computer to perform a gradient descent on that objective function so it does have a practical implication now why am i Wittering on about that it did seem relevant to yes so what kinds of J so the answer to the but it would it be easier and be hard well mathematically is easy I've just told you all you right down your your perfect artifact probabilistically in the form of a promising charity model probability distribution over the causes and consequences of the world in which this thing is immersed and then you just engineer a computer and a robot to perform a gradient descent on that objective function no problem but of course the big problem is writing down the generative model so that's where the heavy lifting comes in yeah so it's it's the form and the structure of that journal team model which basically defines the artifact that you will create or indeed the kind of artifact that has self-awareness so that's where all the hard work comes very much like natural selection doesn't tell you in the slightest why you have eyes so you have to drill down on the actual feeding time the actual giant ear model so with that in mind what did you tell me that tells me immediately the kinds of journey models I would have to write down in order to have self-awareness what you said to me was I have to have a model that is effectively fit for purpose for this kind of world in which I operate and if I now make the observation that this kind of world is effectively largely populated by other things like me ie you then it makes enormous sense that if I can develop a hypothesis that we are similar kinds of creatures this is in fact the same kind of creature but I am me and you are you then it becomes again mandated to have a sense of self so if I live in a world that is constituted by things like me basically a social world a community then it becomes necessary now for me to him further it's me talking and not you talking I wouldn't need that if is on Mars by myself or if I was in the jungle as a feral child if there was nothing like it if there's nothing like me around there would be no need to have a an inference that our hypotheses are yes it is me that is experiencing or causing these sounds and it is not you it's only when there's ambiguity and play induced by the fact that there are others in that world so I think then the special thing about self-aware artifacts is that they have learned to or they have acquired or at least are equipped with possibly by evolution Jarett of models that allow for the fad there are lots of copies of things like them around and therefore they have to work out it's you and not me that that's brilliant and I've never thought of that I never thought of that that the purpose of the the really usefulness of consciousness or self-awareness in the context of planning existing in the world is so you can operate with other things like you and like you couldn't it doesn't have to necessarily be human it could be other kind of similar creatures and some absolutely we would view a lot of our attributes into our pets don't waste them or we try to make our robots humanoid and I think there's a your deep reason for that but it's this much easier to read the world if you can make the simplifying assumption that basically you're me and it's just your turn to talk and I mean when we talk about planning when you talk specifically about planning the highest.if manifestation or realization of that planning is what we're doing now I mean the human condition doesn't get any higher than this talking about the philosophy of existence and the conversation but in that conversation there is a a you know a beautiful art of turn-taking and it neutral inference theory of mind I have to know when you want to listen I have to know when you want to interrupt an to make sure that you're on line I have to have a model in my head of your model in your head that's the highest the most sophisticated form of generative model where the genitive model actually has a gentle model somebody else's journeyer model and I think that and what we are doing now evinces the kinds of Geritol models that would support self-awareness because without that we both be talking over each other or we'd be singing together in a in a choir you know we're which is probably not that's not a bridge analogy what I'm trying to say yeah we wouldn't have this discourse yeah what dance of it yeah that's right Dallas to have as I interrupt I mean that's beautifully put I'll really listen to this conversation many times uh there's so much poetry in this and mathematics let me ask the silliest or perhaps the biggest question as the last kind of question we've talked about living in existence and an objective function under which these objects would operate what do you think is the objective function of our existence what's the meaning of life what do you think is the for you perhaps the purpose the source of fulfillment the source of meaning for your existence as one blob in this soup I'm tempted to answer that as a physicist and free energy I expect consequent upon my behavior so technically that we are and we get a really interesting conversation about what that comprises in terms of searching for information resolving uncertainty about the kind of thing that I am but a suspect that you you you you you want a slightly more personal and financier and but which is can be consistent with that and I think it's reassuring is simple and harps back to what you were taught as a child that you have certain beliefs about the kind of creature and the kind of person you are and all that self evidencing means all that minimizing variational free-energy in an in an inactive and embodied way means is fulfilling the beliefs about what kind of thing you are and of course we're all given those scripts those narratives very early as usual in the form of bedtime stories or fairy stories I'm a princess I gotta meet a beast who's gonna transform ya a prince and the narratives are all around you from your parents to thee to the friends to the society feeds these stories and then then your objective function is to fulfill exactly now the narrative that has been in cultured by your your immediate family but as you say also the sort of the culture in which you've made you grow and you create for yourself I mean a game because of this active inference it's an inactive aspect of self evidencing you know not only am i modeling my environment my ecognition my my external states out there but I'm actively changing them all the time and it still isn't doing the same back we're doing it together so there's a a synchrony that means that I'm creating my own culture over different time scales so the question now is for me being very selfish what scripts were I given it basically was a mixture between an Einstein and shark Holmes so I smoked as heavily as possible try to avoid too much interpersonal contact yet enjoy the fantasy that the the you know you're a popular scientist who's gonna make a difference and it's like a quirky way so that's what's where I grew up on my father my father was an engineer and love science and enough he loved real sort of things like Sir Arthur and his space-time and gravitation which was the the other the first understandable version of general relativity and he so although all the fairy stories I was told as I was growing up were all about these characters keeping the Hobbit out of this because I was quite nervous there's a journey of exploration I suppose it's not so yeah I've just grown up to being what I imagine a mild-mannered Sherlock Holmes slush Alvin star would would do it in my shoes and you did it elegantly and beautifully Carl was a huge island talking today was fun thank you so much for your time I don't think your shame thank you for listening to this conversation with Carl Wriston and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using collects podcast if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon are simply connect with me on Twitter and lex friedman and now let me leave you with some words from carl frist in' your arm moves because you predict it will and your motor system seeks to minimize prediction error thank you for listening and hope to see you next time you |
Kate Darling: Social Robotics | Lex Fridman Podcast #98 | the following is a conversation with Kate darling a researcher at MIT interested in social robotics robotics and generally how technology intersects with society she explores the emotional connection between human beings and lifelike machines which for me is one of the most exciting topics in all of artificial intelligence as she writes in her bio she's a caretaker of several domestic robots including her plio dinosaur robots named Yochai Peter and mr. spaghetti she is one of the funniest and brightest minds I've ever had the fortune to talk to this conversation was recorded recently but before the outbreak of the pandemic for everyone feeling the burden of this crisis I'm sending love your way this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars an apple podcast supported on patreon are simply connect with me on Twitter Alex Friedman spelled Fri D ma n as usual I'll do a few 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this podcast and now here's my conversation with Kate darling Kota robot ethics at Harvard what are some ethical issues that arise in the world with robots yeah that was a reading group that I did when I like at the very beginning first became interested in this topic so I think if I taught that class today would look very very different robot ethics it sounds very science fictiony especially did back then but I think that some of the issues that people in robot ethics are concerned with her just around the ethical use of robotic technology in general so for example responsibility for harm automated weapon systems things like privacy and data security things like and automation and labor markets and then personally I'm really interested in some of the social issues that come out of our social relationships with robot one-on-one relationship with robot yeah I think most of stuff we have to talk about is like one-on-one social stuff that's what I love and I think that's what you're you know as well and they're expert in but a societal oh there's like there's a presidential candidate now and Joo yang running concerned about automation and robots and AI and general taking away jobs he has a proposal of ubi universal basic income of everybody gets a thousand bucks yeah as a way to sort of save you if you lose your job from automation to allow you time to discover what it is that you would like to or even love to do yes so I lived in Switzerland for 20 years and universal basic income has been more of a topic there separate from the whole robots and jobs issue so it's so interesting to me to see kind of these Silicon Valley people latch on to this concept that came from a very kind of left-wing socialist you know kind of a different place in Europe but on the automation labor markets topic I think that it's very is so sometimes in those conversations I think people overestimate where robotic technology is right now and we also have this fallacy of constantly comparing robots to humans and thinking of this as a one-to-one replacement of jobs so even like Bill Gates a few years ago said something about you know maybe we should have a system that taxes robots for taking people's jobs and it just I I mean I'm sure that was taken out of context you know he's a really smart guy but that sounds to me like kind of viewing it as a one to one replacement versus viewing this technology as kind of a supplemental tool that of course is going to shake up a lot of stuff it's gonna change the job landscape but I don't see you know robots taking all the jobs in the next 20 years that's just not how it's gonna work all right so maybe drifting into the land of more personal relationships with robots and interaction and so on I gotta warn you I go I may ask some silly philosophical questions I apologize so please do okay do you think humans will abuse robots in their interaction so you've you've had a lot of and we'll talk about it sort of anthropomorphize a ssin and and work you know this this intricate dance emotional dance between human and robot but this seems to be also a darker side what people when they treat the other as servants especially they can be a little bit abusive or a lot abusive do you think about that do you worry about that yeah I do you think about that so I mean one of my one of my main interests is the fact that people subconsciously treat robots like living things and even though they know that they're interacting with a machine and what it means in that context to behave you know violently I don't know if you could say abuse because you're not actually you know abusing the the inner mind of the robot that robot isn't doesn't have any feelings as far as you know well yeah it was depends on how we define feelings and consciousness but I think that's another area where people kind of overestimate where we currently are with the technology like the robots are not even as smart as insects right now and so I'm not worried about abuse in that sense but it is interesting to think about what does people's behavior towards these things mean for our own behavior is it desensitizing the people to you know be verbally abusive to a robot or even physically abusive and we don't know is a similar connection from like if you play violent video games what connection does that have to desensitize ation to violence as I haven't haven't read literature on that I wonder about that because everything I've heard people don't seem to any longer be so worried about violent video games correct we've seemed the the research on it is it's a difficult thing to research so it's sort of inconclusive but we seem to have gotten a sense at least as a society that people can compartmentalize when it's something on a screen and you're like you know shooting a bunch of characters or running over people with your car that doesn't necessarily translate to you doing that in real life we do however have some concerns about children playing violent video games and so we do restrict it there I'm not sure that's based on any real evidence either but it's just the way that we've kind of decided you know we want to be a little more cautious there and the reason I think robots are a little bit different is because there is a lot of research showing that we respond differently to something in our physical space than something on a screen we will treat it much more viscerally much more like a physical actor and so I it's it's totally possible that this is not a problem and it's the same thing as violence in video games you know maybe you know restrict it with kids to be safe but adults can do what they want but we just need to ask the question again because we don't have any evidence at all yet maybe there's an intermediate place to I did my research on twitter by research I mean scrolling through your Twitter feed you mentioned that you were going at some point to an animal law conference so I have to ask do you think there's something that we can learn from animal rights the guys are thinking about robots oh I think there is so much to learn from that I'm actually writing a book on it right now that's why I'm going is conference so I'm I'm writing a book that looks at the history of animal domestication and how we've used animals for work for weaponry for companionship and you know one of the things the books the book tries to do is move away from this fallacy that I talked about of comparing robots in humans because I don't think that's the right analogy but I do think that on a social level even on a social level there's so much that we can learn from looking at that history because throughout history we've treated most animals like tools like products and then some of them we've treated differently and we're starting to see people treat robots in really similar ways so I think it's a really helpful predictor to how we're going to interact with the robots do you think we'll look back at this time like a hundred years from now and see what we do to animals is like some of the way we view like the Holocaust with the world war two that's a great question I mean I hope so I am not convinced that we will but I often wonder you know what are my grandkids gonna view as you know abhorrent that my generation did that they would never do and I'm like well what's the big deal you know it's it's a fun question to ask yourself there's always seems that there's atrocities that we discover later so the things that at the time people didn't see as you know you look at everything from slavery to any kinds of abuse throughout history so I think the kind of insane wars that were happening to the way war was carried out and rape and the kind of violence that was happening during war in that we now you know we see his atrocities but at the time perhaps didn't as much and so now I have this intuition that I have this worry maybe I'm you're going to probably criticize me but I do anthropomorphize robots I have I don't see a fundamental philosophical difference in a robot in a human being in terms of once the capabilities are matched so the fact that we're really far away doesn't in terms of capabilities and then that from from natural language processing understanding generation to just reasoning and all that stuff I think once you solve it I see though this is a very great area and I don't feel comfortable the kind of abuse that people throw robots subtle but I can see it becoming I can see basically a civil rights movement for robots in the future do you think let me put it in the form of a question do you think robots should have some kinds of rights well it's interesting because I came at this originally from your perspective I was like you know what there's no fundamental difference between technology and like human consciousness like we we can probably recreate anything we just don't know how yet and so there's no reason not to give machines the same rights that we have once like you say they're kind of on an equivalent level but I realized that that is kind of a far future question I still think we should talk about it because I think it's really interesting but I realized that it's actually we might need to ask the robot rice question even sooner than that um well the machines are still you know quote unquote really you know dumb and not on our level because of the way that we perceive them and I think one of the lessons we learn from looking at the history of animal rights and one of the reasons we may not get to a place in a hundred years where we view it as wrong to you know eat or otherwise you know use animals for our own purposes is because historically we've always protected those things that we relate to the most so one example is whales no one gave a shit about the whales am I allowed to swear freedom yeah no one gave a shit about the whales until someone recorded them singing and suddenly people were like oh this is a beautiful creature and now we need to save the whales and that started the whole save the whales movement in the 70s so I'm as much as I and and I think a lot of people want to believe that we care about consistent biological criteria that's not historically how we formed our alliances yeah so what why do we why do we believe that all humans are created equal killing of a human being no matter who the human being is that's what I meant by equality is bad and then because I'm connecting that to robots and I'm wondering whether mortality so the killing Act is what makes something that's the fundamental first right so I'm I am currently allowed to take a shotgun and shoot a Roomba I think I'm not sure but I'm pretty sure it's not considered murder right or even shutting them off so that's that's where the line appears to be right is is mortality a critical thing here I think here again like the animal analogy is really useful because you're also allowed to shoot your dog but people won't be happy about it so we give we do give animals certain protections from like you know you're not allowed to torture your dog and you know set it on fire at least in most states and countries you know but you're still allowed to treat it like a piece of property in a lot of other ways and so we draw these you know arbitrary lines all the time and you know there's a lot of philosophical thought on why viewing humans is something unique is not is just speciesism and not you know based on any criteria that would actually justify making a difference between us and other species do you think in general people most people are good do you think do you think there's evil and good in all of us that's revealed through our circumstances and through our interactions I like to view myself as a person who like believes that there's no absolute evil and good and that everything is you know gray but I do think it's an interesting question like when I see people being violent towards robotic objects you said that bothers you because the robots might someday you know be smart and it is that what well it bothers me because it reveals so I personally believe because I've studied way to my some Jewish I studied the Holocaust in World War two exceptionally well I personally believe that most of us have evil in us that what bothers me is the abuse of robots reveals the evil and human beings yeah and it's I think it doesn't but just bother me it's I think it's an opportunity for roboticists to make help people be find the better sides the angels of their nature right yeah that abuse isn't just a fun side thing that's a you revealing a dark part that you shouldn't there should be hidden deep inside yeah I mean molasse but some of our research does indicate that maybe people's behavior towards robots reveals something about their tendencies for empathy generally even using very simple robots that we have today that like clearly don't feel anything so you know West world is maybe you know not so far often it's like you know depicting the bad characters as willing to go around and shoot and rape the robots and the good characters is not wanting to do that even without assuming that the robots have consciousness so there's a opportunity at Cynthia's opportunity to almost practice empathy the on robots is an opportunity to practice empathy I agree with you some people would say why are we practicing empathy on robots instead of you know on our fellow humans or on animals that are actually alive and experienced the world and I don't agree with them because I don't think empathy is a zero-sum game and I do think that it's a muscle that you can train and that we should be doing that but some people disagree so the interesting thing you've heard you know raising kids sort of asking them or telling them to be nice to the smart speakers to Alexa and so on saying please and so on during the requests I don't know if I'm a huge fan of that idea because yeah that's towards the idea of practicing empathy I feel like politeness I'm always polite to all the all the systems that we build especially anything that speech interaction-based like when we talk to the car I will always have a pretty good detector for please - I feel like there should be a room for encouraging empathy in those interactions yeah okay so I agree with you so I'm gonna play devil's advocate so what is then what is the dose our argument there the devil's advocate argument is that if you are the type of person who has abusive tendencies or needs to get some sort of like behavior like that out needs an outlet for it that it's great to have a robot that you can scream at so that you're not screaming at a person and we just don't know whether that's true whether it's an outlet for people or whether it just kind of as my friend once said trains their cruelty muscles and makes them more cruel in other situations oh boy yeah in that expanse to other topics which they I don't know that you know there's a is a topic of sex which is weird one that I tend to avoid is from robotics perspective and mostly general public doesn't they talk about sex robots and so on is that an area you've touched at all research-wise like the way because that's what people imagine sort of any kind of interaction between human and robot that shows any kind of compassion they immediately think from product perspective in the near term is sort of expansion of what pornography is and all that kind of stuff yeah that's kind of you to like characterize it as though there's thinking rationally about product I feel like sex robots are just such a like titillating news hook for people that they become like the story and it's really hard to not get fatigued by it when you're in the space because you tell someone you do human robot interaction of course the first thing they want to talk about is sex robots really yeah it happens a lot and it's it's unfortunate that I'm so fatigued by it because I do think that there are some interesting questions that become salient when you talk about you know sex with robots see what I think would happen when people get sex robots like if you let some guys okay guys get female sex robots what I think there's an opportunity for is an actual like like they'll actually interact what I'm trying to say they won't outside of the sex would be the most fulfilling part like the interaction it's like the folks who this movies on this right who pray pay a prostitute and then end up just talking to her the whole time so I feel like there's an opportunity it's like most guys and people in general joke about the sex act but really people are just lonely inside and I'm looking for connection many of them and it'd be unfortunate if that it's that connection is established through the sex industry I feel like it should go too into the front door of like people are lonely and they want a connection well I also feel like we should kind of deep you know D stigmatize the sex industry because you know even prostitution like they're prostitutes that specialize in disabled people who don't have the same kind of opportunities to explore their sexuality so it's I I feel like we should like D stigmatize all of that generally yeah but yeah that connection and that loneliness is an interesting you know topic that you bring up because while people are Const we worried about robots replacing humans and oh if people get sex robots and the sex is really good then they won't want their you know partner or whatever but we rarely talk about robots actually filling a hole where there's nothing yeah and what benefit that can provide to people yeah I think that's an exciting there's a whole giant there's a giant hole that's not unfillable by humans it's asking too much of your of people you your friends and people you're in a relationship with in your family to fill that hole there's a because you know it's exploring the full like people you know exploring the full complexity and richness of who you are like who are you really like the people your family doesn't have enough patience to really sit there and listen to who are you really and I feel like there's an opportunity to really make that connection with robots I just really were complex as humans and we're capable of lots of different types of relationships so whether that's you know with family members with friends with our pets or with robots I feel like there's space for all of that and all of that can provide value in a different way yeah absolutely so I'm jumping around currently most of my works and autonomous vehicles so the most popular topic amongst is the trolley problem so most most most robots just uh kind of hate this question but what do you think of this thought experiment what do you think we can learn from it outside of the silliness of the actual application of it to the autonomous vehicle I think it's still an interesting ethical question and that's in itself just like much of the interaction with robots has something to teach us but from your perspective do you think there's anything there well I think you're right that it does have something to teach us because but but I think what people are forgetting in all these conversations is the origins of the trolley problem and what it was meant to show us which is that there is no right answer and that sometimes our moral intuition that comes to us instinctively is not actually what we should follow if we care about creating systematic rules that apply to everyone so I think that as a philosophical concept it could teach us at least that but that's not how people are using it right now like we have and these are friends of mine and like I love them dearly and their project adds a lot of value but if we're viewing the moral machine project as what we can learn from the trolley problems the moral machine is I'm sure you're familiar it's this website that you can go to and it gives you different scenarios like oh you're in a car you can decide to run over you know these two people or this child you know what do you choose do you choose the homeless person do you choose the person who's jaywalking and so it pits these like moral choices against each other and then tries to crowdsource the quote-unquote correct answer which is really interesting and I think valuable data but I don't think that's what we should base our rules in autonomous vehicles on because it is exactly what the trolley problem is trying to show which is your first instinct might not be the correct one if you look at rules that then have to apply to everyone and everything so how do we encode these ethical choices in interaction with robots so for example Lata knows vehicles there is a serious ethical question of do I protect myself but that's my life I have higher priority than the life of another human being because that changes certain control decisions that you make so if your life matters more than other human beings then you'd be more likely to swerve out of your current lane so currently automated emergency braking systems that just break they don't ever swerve right so swerving into oncoming traffic or or no just in a different Lane can cause significant harm to others but it's possible that it causes less harm to you so that's a difficult ethical question do you you do you do you have a hope that like the trolley problem is not supposed to have a right answer do you hope that when we have robots at the table we'll be able to discover the right answer for some of these questions well what's happening right now I think is this this question that we're facing of you know what ethical rules should we be programming into the machines is revealing to us that our ethical rules are much less programmable than we you know probably thought before and so that's a really valuable insight I think that these issues are very complicated and that in in a lot of these cases it's you can't really make that call like not even as a legislator and so what's gonna happen in reality I think is that you know car manufacturers are just gonna try and avoid the problem and avoid liability in any way possible or like they're gonna always protect the driver because who's gonna buy a car if it's you know programmed to kill someone kill kill you instead of someone else so that's what's gonna happen in reality but what did you mean by like once we have robots at the table like do you mean when they can help us figure out what to do no I mean when robots are part of the ethical decisions so no no not they help us well oh you mean when it's like should I run over a robot or a person right that kind of thing so what no what no no no so when you it's exactly what you said which is when you have to encode the ethics into an algorithm you start to try to really understand what are the fundamentals of the decision making process you make just make certain decisions should you like capital punishment should you take a person's life or not to punish them for a certain crime sort of you can use you can develop an algorithm to make that decision right and the hope is that the act of making that algorithm however you make it so there's a few approaches will help us actually get to the core of what what is right and what is wrong under our current societal standards isn't that what's happening right now and we're realizing that we don't have a consensus on what's right and wrong I mean in politics in general well like when we're thinking about these trolley problems and autonomous vehicles and how to program ethics into machines and how to you know make make AI algorithms fair and equitable where we're realizing that this is so complicated and it's complicated in part because there is doesn't seem to be a one right answer in any of these cases do you hope for like one of the ideas of the moral machine is that crowdsourcing can help us converge towards like democracy can help us converge towards the right answer do you have a hope for crowdsourcing well yes and no so I think that in general you know I have a legal background and policymaking is often about trying to suss out you know what rules does this society this particular Society agree on and then trying to codify that so the law makes these choices all the time and then tries to adapt according to changing culture but in the case of the moral machine project I don't think that people's choices on that website necessarily necessarily reflect what laws they would want in place if given I think you would have to ask them a series of different questions in order to get up what their consensus is I agree but that that has to do more with the artificial nature of I mean they're showing some cute icons on a screen that's that's almost so if you for example we do a lot of work in virtual reality and so if you make if you put those same people into virtual reality where they have to make that decision they should be very different I think I agree with that that's one aspect and the other aspect is it's a different question to ask someone would you run over the homeless person or the doctor in this scene or do you want cars to always run over the homeless people yeah so let's talk about anthropomorphism do me at the prom or fizzell if I can pronounce it correctly is is one of the most fascinating phenomena from like both the engineering perspective and psychology perspective machine learning perspective in robotics in general can you step back and define at the prom or fizzle how you see it in general terms in your in your work sure so anthropomorphism is this tendency that we have to project human-like traits and behaviors and qualities onto nonhumans and we often see it with animals like well will project emotions on animals that may or may not actually be there okay we often see that we're trying to interpret things according to our own behavior when we get it wrong but we do it with more than just animals we do it with objects you know teddy bears we see you know faces in the headlights of cars and we do it with robots very very extremely you think that can be engineered can that be used to enrich an interaction Oh in and they a system in the human oh yeah for sure and do you and do you see it being used that way often like I don't I haven't seen whether it's Alexa or any of the smart speaker systems often trying to optimize for the ethical or physician you said you haven't seen I haven't seen they they keep moving away from that I think they're afraid of that they they actually so I only recently found out but did you know that Amazon has like a whole team of people who are just there to work on Alexis personality so I know that depends on UI personality I didn't know I didn't know that exact thing but I do know that the how the voice is perceived has worked on a lot whether that if it's a pleasant feeling about the voice but that has to do more with the texture of the sound and the audience on what personality is more like it's like what's her favorite beer when you ask her and and the personality team is different for every country to like there's a different personality for a German Alexa than there is for American Alexa that's it I think it's very difficult to you know use the are really really harness the anthropomorphism with these voice assistance because the voice interface is still very primitive and I think that in order to get people to really suspend their disbelief and treat a robot like it's alive less is sometimes more you you want them to project onto the robot and you want the robot to not disappoint their expectations for how it's going to answer or behave in order for them to have this kind of illusion and with Alexa I don't think we're there yet or Siri that just they're just not good at that but if you look at some of the more animal-like robots like the baby seal that they use with the dementia patients so much more simple design doesn't try to talk to you you can't disappoint you in that way it just makes little movements and sounds and people stroke it and it responds to their touch and that is like a very effective way to harness people tendency to kind of treat the robot like a living thing yeah so you bring up some interesting ideas in your paper chapter I guess at the poem Orphic framing human robot interaction that I read the last time we scheduled this a long time what are some good and bad cases event them for morphism and in your perspective like one is the good one is it bad well I just start by saying that you know while design can really enhance the end the premiere film it doesn't take a lot to get people to treat a robot like it's alive like people will over 85% of rumbas have a name which I'm I don't know the numbers for your regular type of vacuum cleaner but they're not that high right so people will feel bad for the room but when it gets stuck they'll send it in for repair and want to get the same one back and that's that one is not even designed to like make you do that so I think that some of the cases where it's maybe a little bit concerning that anthropomorphism is happening is when you have something that's supposed to function like a tool and people are using it in the wrong way and one of the concerns is military robots we're so gosh mm like early 2000s which is a long time ago iRobot the room a company made this robot called the pack bot that was deployed in Iraq and and Afghanistan with the bomb disposal units that were there and the soldiers became very emotionally attached to the robots and that's you know fine until a soldier risks his life to save a robot which you really don't want but they were treating them like pets like they would name them they would give them funerals with gun salutes they would get really upset and traumatized when the robot got broken so you in situations where you want a robot to be a tool in particular when it's supposed to like do a dangerous job that you don't want a person doing it it can be hard when people get emotionally attached to it that's maybe something that you would want to discourage another case for concern is maybe when companies try to leverage the emotional attachment to exploit people so if it's something that's not in the consumers interest trying to like sell them products or services or exploit an emotional connection to keep them you know paying for a cloud service for a social robot or something like that might be I I think that's a little bit concerning as well yeah the emotional manipulation which probably happens behind the scenes now with some like social networks and so on but making it more explicit what's your favorite robot like you know a real no real real robot which you have felt a connection with or not like not not at the core morphic connection but I mean like you just sit back as a damn this is an impressive system Wow so two different robots so the the plio baby dinosaur robot that is no longer sold that came out in 2007 that one I was very impressed with it was but but from an anthropomorphic perspective I was impressed with how much I bonded with it how much I like wanted to believe that it had this inner life can you describe Cleo the can you describe what what it is how big is it what can actually do ya plio is about the size of a small cat it had a lot of like motors that gave it this kind of lifelike movement it had things like touch sensors and an infrared camera so it had all these like cool little technical features even though it was a toy and the thing that really struck me about it was that it could mimic pain and distress really well so if you held it up by the tail it had a tilt sensor that you know told it what direction it was facing and it would start to squirm and cry out if you hit it too hard it would start to cry so it was very impressive in design and what's the second robot that you were you said there might have been two that you liked yeah so the Boston Dynamics robots are just impressive feats of engineering have you met them in person yeah I recently got a chance to go visit and I you know I was always one of those people who watched the videos and was like this is super cool but also it's a product video like I don't know how many times that they had to shoot this to get it right but visiting them I you know I'm pretty sure that I was very impressed let's put it that way yeah in terms of the control I think that was a transformational moment for me when I met spot many in person because okay maybe this is a psychology experiment but I anthropomorphised the crap out of it so I immediately it was like my best friend right I mean it's really hard for anyone to watch spot move and not feel like it has agency yeah did this movement especially the arm on spot mini really obvi obviously looks like a head yeah that and they say no wouldn't mean it that way but it obviously it looks exactly like that and so it's almost impossible to not think of it as a almost like the baby dinosaur but slightly larger and in this movement of the of course the intelligence is that their whole idea is that it's not supposed to be intelligent it's a platform on which you build higher intelligence it's actually really really dumb it's just a basic movement platform yeah but even dumb robots can like we can immediately respond to them in this visceral way what are your thoughts about Sofia the robot this kind of mix of some basic natural language processing and basically an art experiment yeah an art experiment is a good way to characterize it I'm much less impressed with Sofia than I am with Boston Dynamics she said she likes you she says she admires you she yeah she followed me on Twitter at some point yeah as she tweets about how much she likes you so so wouldn't that mean I have to be nicer not I was emotionally manipulating it no how do you think of the whole thing that happened with Sofia is quite a large number of people kind of immediately had a connection and thought that maybe we're far far more advanced with robotics than we are all right she didn't even think much I'm surprised how little people cared that they kind of assumed that well of course AI can do this yeah and then they if they assume that I felt they should be more impressed well you know what I mean like really overestimate where we are and so in something I don't even I don't even think Sofia was very impressed over it is very impressive I think she's kind of a puppet to be honest but yeah I think people have are a little bit influenced by science fiction pop culture to think that we should be further along than we are so what's your favorite robots and movies in fiction wall-e wall-e what do you like about wall-e the humor the cuteness the the perception control systems operating and wallahi that makes it all just in general the design of wall-e the robot I think that animators figured out you know starting in like Ben 1940's how to create characters that don't look real but look like something that's even better than real that we really respond to and think is really cute they figured out how to make them move and look in the right way and wall-e is just such a great example of that you think eyes big eyes or big something that's kind of AI ish so it's always playing on some aspect of the human face right often yeah so big eyes well I think one of the one of the first like animations to really play with this was Bambi and they weren't originally gonna do that they were originally trying to make the deer look as lifelike as possible like they brought deer into the studio and had a little zoo there so the animators could work with them and then at some point they were like hmm if we make really big eyes and like a small nose and like big cheeks kind of more like a baby face then people like it even better than if it looks real do you think the future of things I collects are in the home has possibility to take advantage of that to build on that to create these systems that are better than real that created closed human connection I can pretty much guarantee you without having any knowledge that those companies are working on that on that design behind the scenes like pretty sure I totally disagree with you really so that's what I'm interested in I'd like to build such a company I know a lot of those folks and they're afraid of that because you don't well how do you make money off of it well but even just like making a lexa look a little bit more interesting than just like a cylinder would do so much it's it's an interesting thought but I don't think people are from Amazon perspective looking for that kind of connection they want you to be addicted to the services provided by Alexa not to the device so the the device itself it's felt that you can lose a lot because if you create a connection and then if there's it creates more opportunity for frustration for for negative stuff then it does for positive stuff is I think the way they think about it that's interesting like I agree that there is it's very difficult to get right and you have to get it exactly right otherwise you wind up with Microsoft's Clippy okay easy now what's your problem with Clippy oh you like clip these clothes your friends yeah I'll just I just I just talked to the would just had this argument and they Microsoft CTO and they and he said he said he's not bringing Clippy back they're not bringing Clippy back and that's very disappointing is I think it was clip II was the greatest assistance we've ever built it was a horrible attempt of course but it's the best we've ever done because it was in real attempt you haven't like a actual personality and I mean it was obviously technology was way not there at the time of being able to be a recommender system for assisting you in anything and typing in Word or any kind of other application but still was an attempt of personality that was legitimate I'm sure I thought was brave yes oh yes okay you know you've convinced me I'll be slightly less hard unclick and I know I have like an army of people behind me who also miss Clippy so really I want to meet these people who are these people it's the people who like to hate stuff when it's there and and miss it when it's gone [Laughter] exactly alright so Anki and Gebo the two companies two amazing companies social robotics companies that have recently been closed down yeah why do you think it's so hard to create a personal robotics company so making a business out of essentially something that people would anthropomorphize have a deep connection with why is it so hard to make it work the business case not there or what is it I think it's a number of different things I don't think it's going to be this way forever I think at this current point in time it so much work to build something that only barely meets people's like minimal expectations because of science fiction and pop-culture giving people this idea that we should be further than we already are like when people think about a robot assistant in the home they think about Rosie from the Jetsons or something like that and on key and and giba did such a beautiful job with the design and getting that interaction just right but I think people just wanted more they wanted more functionality I think you're also right that you know the business case isn't really there because there hasn't been a killer application that's useful enough to get people to adopt the technology in great numbers I think what we did see from the people who did you know get geebo is a lot of them became very emotionally attached to it but that's not I mean it's kind of like the Palm Pilot back in the day most people are like why do I need this why would I they don't see how they would benefit from it until they you know have it or some other company comes in and makes it a little better yet like how how far away are we do you think I mean how hard is this problem it's a good question and I think it has a lot to do with people's expectations and those keep shifting depending on what science fiction that is popular but also it's two things it's people's expectation and people's need for an emotional connection yeah and then I believe the need is pretty high yes but I don't think we're aware of it that's right there's like it I really think we're this is like the life as we know it so we've just kind of gotten used to it of really I hate to be dark because I have close friends but we've gotten used to really never being close to anyone all right and we're deeply I believe okay this is hypotheses I think we're deeply lonely all of us even those in deep fulfilling relationships in fact what makes us relationship fulfilling I think is that they at least tap into that deep loneliness a little bit but I feel like there's more opportunity to explore that that doesn't interfere with the human relationship you have it expands more on the that yeah the the rich deep unexplored complexity that's all of us weird apes okay right do you think it's possible to fall in love with a robot oh yeah totally do you think it's possible to have a long-term committed monogamous relationship oh the robot well yeah there are lots of different types of long-term committed monogamous relationships I think monogamous implies like you're not going to see other humans and sexually or like you basically on Facebook have to say I'm in a relationship with this person this robot I just don't like again I think this is comparing robots to humans when I would rather compare them to pets like you get a robot it fulfills you know this loneliness that you have in us maybe not the same way as a pet maybe in a different way that is even you know supplemental in a different way but you know I'm not saying that people won't like do this be like oh I want to marry my robot or I want to have like a you know sexual relation monogamous relationship with my robot but I don't think that that's the main use case for them well you think that there's still a gap between human and pet so between husband and pet there's a relation earring so that that's a gap that can be closed but I think it could be closed someday but why would we close that like I I think it's so boring to think about recreating things that we already have when we could when we could create something that's different I know you're thinking about the people who like don't have a husband and like what could we give them yeah but but let's I guess what I'm getting at is maybe not so like the movie her yeah right so a better husband well may be better in some ways like it's I I do think that robots are going to continued to be a different type of relationship even if we get them like very human looking or when you know the voice interactions we have with them feel very like natural and human like I think they're still gonna be differences and there were in that movie too like towards the end yeah it goes off the rails it's just a movie so that your intuition is that that because because you kind of said two things right so one is why would you want to basically replicate the husband Yeah right and the other is kind of implying that it's kind of hard to do so you like anytime you try you might build something very impressive but it'll be different I guess my question is about human nature it's like how hard is it to satisfy that role of the husband so removing any of the sexual stuff aside is the is more like the mystery detention the dance of relationships you think with robots that's difficult to build what's you I think that well it also depends I'm not reading about robots now in 50 years in like indefinite amount of time where I'm thinking abilities five or ten years five or ten years I think that robots at best will be like a more similar to the relationship we have with our pets than relationship that we have with other people I got it so what do you think it takes to build a system that exhibits greater and greater levels of intelligence like it impresses us with its intelligence you know a Roomba so you talk about ethical moral ization that doesn't i think intelligence is not required if i can tell us probably gets in the way sometimes like you mentioned but what do you think it takes to create a system where we sense that it has a human level intelligence something that obviously something conversational human level intelligence that problem is it'd be interesting to sort of hear your perspective not just purely that talked to a lot of people how hard is the conversational agents yeah how hard is it to pass a Turing test but my sense is it's it's easier than just solving it's easier than solving the pure and natural language processing problem because I feel like you can cheat yeah so yeah so how hard is it to pass the Turing test any of you I well I think again it's all about expectation management if you set up people's expectations to think that they're communicating with what was it a 13 year old boy from the Ukraine yeah that's right then they're not going to expect perfect English they're not going to expect perfect you know understanding of concepts or even like being on the same wavelength in terms of like conversation flow so it's much easier to pass in that case do you think you kind of alluded this to with audio do you think it needs to have a body I think that we definitely have so we treat physical things with more social agency because we're very physical creatures I think a body can be useful does it get in the way is there negative aspects like yeah there can be so if you're trying to create a body that's too similar to something that people are familiar with like I have this robot cat at home that Hasbro makes and it's very disturbing to watch because I'm constantly assuming that it's gonna move like a real cat and it doesn't because it's like a 100 dollar piece of technology so it's very like disappointing and it's very hard to treat it like it's alive so you can get a lot wrong with the body too but you can also use tricks same as you know the expectation management of the 13 year old boy from the Ukraine if you pick an animal that people aren't intimately familiar with like the baby dinosaur like the baby seal that people have never actually held in their arms you can get away with much more because they don't have these preformed expectations yeah I'm thinking a TED talk or something that clicked for me that nobody actually knows what a dinosaur looks so you can actually get away with a lot more that was great do you think he needs so what do you think about consciousness and mortality being displayed in a robot so not actually having consciousness but having these kind of human elements that are much more than just the interaction much more than just like you mentioned with a dinosaur moving kind of interesting ways but really being worried about its own death and really acting as if it's aware and self-aware and identity have you seen that done in robotics what do you think about doing that I think it does is that a is that a powerful good thing well it's a I think it can be a design tool that you can use for different purposes so I can't say whether it's inherently good or bad but I do think it can be a powerful tool the fact that the you know Clio mimics distress when you quote-unquote would hurt it his is a really powerful tool to get people to engage with it in a certain way I had a research partner that I did some of the empathy work with named Kailash Nandi and he had built a robot for himself that had like a life span and that would stop working after a certain amount of time just because he was interested in like whether he himself would treat it differently and we know from you know Tamagotchis those like those little games that that we used to have that we're extremely primitive that like people respond to like this idea of mortality and you know you can get people to do a lot with little design tricks like that now whether it's a good thing depends on what you're trying to get them to do have a deeper relationship have a deeper connection sign a relationship if it's for their own benefit that sounds great okay a lot of other reasons I see so what kind of stuff are you worried about so is this a mostly about manipulation of your emotions for like advertisement so on things like that yeah or data collect I mean you could think of governments misusing this to extract information from people it's you know just just like any other technological tool just raises a lot of questions what's if you if you look at Facebook if you look at Twitter and social networks there's a lot of concern of data collection now how what's from the legal perspective or in general how do we prevent the violation of sort of these companies crossing a line it's a gray area but crossing a line they shouldn't in terms of manipulating like we're talking about a manipulating our emotion manipulating our behavior using tactics that are not so savory yeah it's it's really difficult because we are starting to create technology that relies on data collection to provide functionality and there's not a lot of incentive even on the consumer side to curb that because the other problem is that the harms aren't tangible they're not really apparent to a lot of people because they kind of trickle down on a societal level and then suddenly we're living in like 1984 which you know sounds extreme but that book was very prescient and I'm not worried about you know these systems you know I I I have you know Amazon's echo at home and and you know tell Alexa all sorts of stuff and and it helps me because you know Alexa knows what you know brand of diaper we use and so I can just easily order it again so I don't have any incentive to like ask a lawmaker to curb that but when I think about that data then being used against you know low income people to target them for you know scammy loans or education programs that's then a societal effect that I think is very severe and you know legislators should be thinking about well yeah there's the the Garrett gray area is the removing ourselves from consideration of like of explicitly defining objectives and more saying well we want to maximize engagement in our social network yeah and and then just because you're not actually doing a bad thing it makes sense you want people to to keep a conversation going to have more conversations to keep coming back again and again to have conversations and whatever happens after that you're kind of not exactly directly responsible you're only indirectly responsible so it's I think it's a really hard problem do I are you optimistic about us ever being able to solve it you mean the problem of capitalists like because the problem is that the companies are acting in the company's interests and not in people's interest and when those interests are aligned that's great but the completely free market doesn't seem to work because of this information asymmetry but it's hard to know how to so say you would try to do the right thing I guess I guess what I'm trying to say is I'm it's not obvious for these companies what the good thing for society is to do like I don't think they sit there and with I don't know whether it with a glass of wine and a cat like petting a cat evil cat and and there's two decisions and one of them is good for society one is good for the for the profit and they choose the profit I think they actually there's a lot of money to be made by doing the the right thing for society like that because Google Facebook have so much cash that day actually was especially Facebook was significantly benefit for making decisions that are good for society it's good for their brand right so but I don't know if they know what society that's the we I don't think we know what's good for society in terms of how yeah how we manage the conversation on Twitter or how we design will talk about robots like should we emotionally manipulate you into having a deep connection with Alexa or not yeah yeah you have optimism that we'll be able to solve some of these questions well I'm gonna say something that's controversial like in my circles which is that I don't think that companies who are reaching out to ethicists and trying to create interdisciplinary ethics boards I don't think that that's totally just trying to whitewash the problem and and and so that they look like they've done something I think that a lot of companies actually do like you say care about what the right answer is they don't know what that is and they're trying to find people to help them find them not in every case but I think I you know it's much too easy to just vilify the companies as like you said sitting there with their cat going her 1 million dollars that's not what happens a lot of people are well-meaning even within companies I think that what we do absolutely need is more interdisciplinarity both within companies but also within the policy-making space because we're you know we've hurdled into the world where technological progress is much faster it seems much faster than it was and things are getting very complex and you need people who understand the technology but also people who understand what the societal implications are and people who are thinking about this in a more systematic way to be talking to each other there's no other solution I think you've also done work on intellectual property so if you look at the algorithms these companies are using like YouTube Twitter Facebook so on and that's kind of the those are mostly secretive in the recommender systems behind behind these algorithms do you do you think about it IP and transparency about how goes like this like what the responsibility these companies to open-source the algorithms or at least reveal to the public what's how these algorithms work so I personally don't work on that there are a lot of people who do though and there are a lot of people calling for transparency in fact Europe's even trying to legislate transparency maybe they even have at this point where like if if an algorithmic system makes some sort of decision that affects someone's life that you need to be able to see how that decision was made I you know it's it's a it's a tricky balance because obviously companies need to have you know some sort of competitive advantage and you can't take all that away or you stifle innovation but yeah for some of the ways that these systems are already being used I think it it is pretty important that people understand how they work what are your thoughts in general on intellectual property in this weird age of software AI robotics oh that it's broken I mean the system is just broken so did can you describe I actually I don't even know what intellectual property is in the space of software what it means to I mean I so I believe I have a patent on a piece of software from my PhD you believe you don't know no we went through a whole process yeah I do the spam emails like will frame your patent for you yes much like a thesis so uh but that's useless right or not what word is IP stand in this age what what is what's the right way to do it what's the right way to protect and own ideas and why don't when it's just code and in this mishmash of something that feels much softer than a piece of machinery yeah idea I mean it's hard because you know there are different types of intellectual property and they're kind of these blunt instruments they're they're like it's like patent law is like a wrench like it works really well for an industry like the pharmaceutical industry but when you try and apply it to something else it's like I don't know I'll just like hit this thing with the wrench and hope it works so software you know software you have a couple different options software like any code that's written down in some tangible form is automatically copyrighted so you have that protection but that doesn't do much because if someone takes the basic idea that the code is executing and just does it in a slightly different way they can get around the copyright so that's not a lot of protection then you can patent software but that's kind I mean getting a patent cost I don't know if you remember what yours costs or like was it an institution yes during university yeah they it was insane there's so many lawyers so many meetings and it made me feel like it must have been hundreds of thousands of dollars yeah crazy it's it's insane the costs of getting a patent and so this idea of like protecting the like inventor in their own garage like came up with a great idea is kind of that's the thing of the past it's all just companies trying to protect things and it costs a lot of money and then with code it's oftentimes like you know by the time the patent is issued which can take like five years you probably your code is obsolete at that point so it's it's a very again a very blunt instrument that doesn't work well for that industry and so you know at this point we should really have something better but we don't do like open source yeah it's open so it's good for society you think all of us should open source code well so at the Media Lab at MIT we have an open source default because what we've noticed is that people will come in there like write some code and they'll be like how do I protect this and we're like mmm like that's not your problem right now your problem isn't that someone's gonna steal your project your problem is getting people to use it at all like there's so much stuff out there like we don't even know if you're gonna get traction for your work and so open sourcing can sometimes help you know get people's work out there but ensure that they get attribution for it for the work that they've done so I like I'm a fan of it in a lot of contexts obviously it's not like a one-size-fits-all solution so what I gleaned from your Twitter is your mom I saw a quote a reference to baby bot what have you learned about robotics and AI from raising a human baby bot well I think that my child has made it more apparent and that the systems we're currently creating aren't like human intelligence like it there's not a lot to compare there it's just you he has learned and developed in such a different way than a lot of the AI systems were creating that that's not really interesting to me to compare but what is interesting to me is how these systems are going to shape the world that he grows up in and so I'm like even more concerned about kind of the societal effects of developing systems that you know rely on massive amounts of data collection for example so is you going to be allowed to use like Facebook or Facebook is over kids don't use that at snapchat what do they use Instagram Jets over to I don't know I just heard that tick tock is over which I've never even seen so I don't know no we're old we don't know twitch and you just I'm gonna start gaming and streaming my my gameplay so what do you see is the future of personal robotic social robotics interaction with our robots like what are you excited about if you were to sort of philosophize about what might happen the next 5-10 years that would be cool to see oh I really hope that we get kind of a home robot that makes it that's a social robot and not just Alexa like it's you know I really loved the Anki products I thought Gebo was had some really great aspect so I'm hoping that a company cracks that meet you so okay it was wonderful talking today likewise thank you so much it's fun thanks for listening to this conversation with Kate darling and thank you to our sponsors expressvpn and master class please consider supporting the podcast by signing up to master class and master class comm slash flex and getting expressvpn at expressvpn comm / lex pod if you enjoy this podcast subscribe on youtube review it with five stars on Apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman and now let me leave you with some tweets from Kate darling first tweet is the pandemic has fundamentally changed Who I am I now drink the leftover milk in the bottom of the cereal bowl second tweet is I came on here to complain that I had a really bad day and saw that a bunch of you are hurting - love - everyone thank you for listening and hope to see you next time you |
Sertac Karaman: Robots That Fly and Robots That Drive | Lex Fridman Podcast #97 | the following is a conversation with Suresh Carmen a professor at MIT co-founder of the autonomous vehicle company optimist ride and is one of the top roboticists in the world including robots that drive and robots that fly to me personally he has been a mentor a colleague and a friend he's one of the smartest most generous people I know so it was a pleasure and honor to finally sit down with him for this recorded conversation this is the artificial intelligence podcast if you enjoy it subscribe I knew to review five stars in Apple podcast supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma n as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you it doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it use the code lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 this cash app allows you to send and receive money digitally let me mention a surprising fact about physical money it costs 2.4 cents to produce a single penny in fact I think it costs 85 million dollars annually to produce them that's a crazy little fact about physical money so again if you get cash out from the App Store Google Play and use the collects podcast you get $10 and cash Apple also donate $10 the first an organization that is helping to advanced robotics and STEM education for young people around the world and now here's my conversation with Sir - Carmen since you have worked extensively on both what is the more difficult task autonomous flying or autonomous driving that's a good question I think that autonomous flying just kind of doing it for consumer drones and so on the kinds of applications that we're looking at right now is probably easier and so I think that that's maybe one of the reasons why it took off like literally a little earlier than the autonomous cars but I think if we look ahead I would think that you know the real benefits of autonomous flying unleashing them in like transportation logistics and so on I think it's a lot harder than autonomous driving so I think my guess is that you know we've seen a few kind of machines fly here and there but we really haven't yet seen any kind of you know machine like like at massive scale large-scale being deployed and flown and so on and I think that's gonna be after we kind of resolve some of the large scale deployments of autonomous driving it was the hard part what's your intuition behind why at scale when consumer-facing drones are tough so I think in general its scale is tough like for example I mean you think about it we have actually deployed a lot of robots in the let's say the past 50 years we academics or we business I think we as humanity deployed a lot of robots and I think that when you think about it you know robots they're autonomous they work and they work on their own but they are either like in isolated environments or they are in sort of you know they may be at scale but they're really confined to a certain environment that they don't interact so much with humans and so you know they work in I don't know factory floors their houses they work on Mars you know they are fully autonomous over there but I think that the real challenge of our time is to take these vehicles and put them into places where humans are present so now I know that there's a lot of like human robot interaction type of things that need to be done and so on that's that's one thing but even just from the fundamental algorithms and systems and and the business cases or maybe the business models even like architecture planning societal issues legally there's a whole bunch of pack of things that are related to us putting robotic vehicles into human present environments and these humans you know they will not potentially be even trained to interact with them they may not even be using the services that are provided by these vehicles they may not even know that they're autonomous they're just doing their thing living in environments that are designed for humans not for robots and that I think is one of the biggest challenges I think over our time to put vehicles there and you know to go back to your question I think doing that at scale meaning you know you go out in a city and you have you know like thousands or tens of thousands of autonomous vehicles that are going around it is so dance to the point where if you see one of them you look around you see another one it is that dance and that density we've never done anything like that before and I would I would bet that that kind of density will first happen with autonomous cars because I think you know we can ban the environment a little bit we can especially kind of making them safe is a lot easier when they're like on the ground when they're in the air it's a little bit more complicated but I don't see that there's gonna be a big separation I think that you know there will come a time that we're gonna quickly see these things unfold do you think there will be a time where there's tens of thousands of delivery drones they fill this guy you know I think I think it's possible to be honest delivery drones is one thing but you know you can imagine for transportation like a like an important use cases but you know we're in Boston you want to go from Boston to New York and you want to do it from the top of this building to the top of another building in Manhattan and you're gonna do it in one and a half hours and that's that's a big opportunity I think personal transport so like you and your friend like oh yeah or almost like I like like an uber so like four people six people a people in our work in autonomous vehicles I see that so there's kind of like a bit of a need for you know one person transport but also like like a few people so you and I could take the trip together we could have lunch that you know I think kind of sounds crazy maybe even sounds a bit cheesy but I think that those kinds of things are some of the real opportunities and I think you know it's not like the typical airplane and the airport would disappear very quickly but I would think that you know many people would feel like they would spend an extra hundred dollars on doing that and cutting that for our travel down to one and a half hours so how feasible are flying cars it's been the dream that's like when people imagine the future for 50 plus years they think fine cars it's a it's like all technology is just cheesy to think about now because it seems so far away but overnight it can change but just technically speaking in your view how feasible is it to make that happen I'll get to that question but just one thing is that I think you know sometimes we think about what's gonna happen in the next 50 years it's just really hard to guess right next 50 years I don't know I mean we could yet what's gonna happen in transportation in the next 50 we could get flying saucers I I could bet on that I think there's a 50/50 chance that you know like you can build machines that can ionize the air around them and push it down with magnets and they would fly like a flying saucer that is possible and it might happen in the next 50 years so it's a bit hard to guess like when you think about 50 years before but I would think that you know there's this this kind of notion where there's a certain type of air space that we call the agile airspace and there is there's good amount of opportunities in that airspace so that would be the space that is kind of a little bit higher than the place where you can throw a stone because that's a tough thing when you think about it you know it takes a kid on a stone to take an aircraft down and then what happens but you know imagine the airspace that's high enough so that you cannot throw a stone but it is low enough that you're not interacting with the with the very large aircraft that are you know flying several thousand feet above and that airspace is underutilized or it's actually kind of not utilized at all yeah that's right so there's you know there's like recreational people kind of fly every now and then but it's very few if you look up in the sky you may not see any of them at any given time every night now you'll see one airplane utilizing that space and you'll be surprised and the moment you're outside of an airport a little bit like it's just kind of flies off and it goes out and I think utilizing that airspace the technical challenge is there is you know building an autonomy and ensuring that that kind of autonomy is safe ultimately I think it is going to be building in complex software are complicated so that it's maybe a few orders of magnitude more complicated than what we have on aircraft today and at the same time ensuring just like we ensure on aircraft ensuring that it's safe and so that becomes like building that kind of complicated hardware and a software becomes a challenge especially when you know you build that hardware I mean you build that software with data and so you know it's it's of course there's some rule by software in there that kind of do a certain set of things but but then you know there's a lot of training merit machine learning will be key to these guys to delivering safe vehicles in the future especially not maybe the safe part but I think the intelligent part um I mean there are certain things that we do it with machine learning and it's just there's like right now all the way and and I don't I don't know how else they could be done and you know there's there's always this conundrum I mean we could I could be like we could maybe gather billions of programmers humans who program perception algorithms that detect things in the sky and whatever or you know we I don't know we maybe even have robots like learning a simulation environment and transfer and they might be learning a lot better in a simulation environment than a billion humans put their brains together and try to program humans pretty limited what's uh what's the role of simulations withdrawals if you've done quite a bit of work there how promising just the very thing you said just now how promising is the possibility of training and developing a safe flying robot in simulation and deploying it and having that work pretty well in the real world I think that you know a lot of people when they hear simulation they will focus on training immediately but I think one thing that you said which was interesting it's developing I think simulation environments are actually could be key and great for development and that's not new like for example you know there's people in the automotive industry have been using dynamic simulation for like decades now and and it's pretty standard that you know you would build and you would simulate if you want to build an embedded controller you plug that kind of embedded computer into another computer that other computer would simulate tiny and so on and I think you know fast forward these things you can create pretty crazy simulation environments like for instance one of the things that has happened recently and that you know we can do now is that we can simulate cameras a lot better than we used to simulate them we were able to simulate them before and that's I think we just hit the elbow on that kind of improvement I would imagine that really improvements in hardware especially and with improvements and machine learning I think that we would get to a point where we can simulate cameras very very much similar cameras means simulate how a real camera would see the real world therefore you can explore the limitations of that you can train perception algorithms on the in simulation all that kind of stuff exactly so you know it's it has been easier to simulate what we will called interoceptive sensors like internal sensors so for example inertial sensing has been easy to simulate it has also been easily simulate dynamics like like physics that are governed by ordinary differential equations I mean like how a car goes around maybe have it rolls on the road how they interact with it interacts with the road or even an aircraft flying around like the dynamic the physics of that what has been really hard has been to simulate extra Sept of sensors sensors that kind of like look out from the vehicle and that's a new thing that's coming like laser rangefinders they're a little bit easier cameras radars are a little bit tougher I think once we nail that down the the next challenge I think in simulation will be to simulate human behavior that's also extremely hard even when you imagine like how a human driven car would act around even that is hard but imagine trying to simulate you know a a model of a human just doing a bunch of gestures and so on and and you know it's it's actually simulated it's not captured like with a motion capture but it is similarly that's that's very in fact today I get involved a lot with like sort of this kind of very high-end rendering projects and I have like this test that I've pass it to my friends or my mom you know ice and like two photos two kind of pictures and I say rendered which one is rendered which one is real and it's pretty hard to distinguish except I realized except when we put humans in there it's possible that our brains are trained in a way that we recognize humans extremely well but we don't so much recognize the built environments because built an alarm sort of came after per se we evolved into sort of being humans but but humans were always there same thing happens for example you look at like monkeys and you can't distinguish one from another but they sort of do and it's very possible that they look at humans it's kind of pretty hard to distinguish one from another but we do and so our eyes are pretty well trained to look at humans and understand if something is off we will get it we may not be able to pinpoint it so in my typical friend test or mom test what would happen is that we put like a human walking in you know anything and they they say you know this is not right something is off in this video I don't know what but I can tell you it's too human I can take the human and I can show you like inside of a building or like an apartment and it will look like if we had time to render it it will look great and this should be no surprise a lot of movies that people are watching it's all computer-generated you know even nowadays when you watch a drama movie and like there's nothing going on action wise but it turns out it's kinda like cheaper I guess to render the background and so they would but how do we get there how do we get a human would pass the mom / friend test a simulation of a human walking do you think that's something we can creep up do by just doing kind of a comparison learning or you have humans annotate what's more realistic and not just by watching they go what what's the path is it seems totally mysterious how we thing right simulate human behavior it's it's hard because a lot of the other things that I mentioned to you including simulating cameras right it is the the thing there is that you know we know the physics we know how it works like in the real world and we can write some rules and we can do that like for example simulating cameras there's this thing called ray tracing I mean you literally just kind of imagine it's very similar to it's not exactly the same but it's very similar to tracing photon by photon they're going around bouncing on things and coming your eye a human behavior developing a dynamic like like like a model of that that is mathematical so that you can put it into a processor that would go through that that's gonna be hard and so so what else do you got you can collect data right and you can try to match the data or another thing that you can do is that you know you can show the Frant test you know you can say this or that and this or that and that will be labeling anything that requires human labeling ultimately we're limited by the number of humans that you know we have available at a heart disposal and the things that they can do you know they have to do a lot of other things than also labeling this data so so that modeling human behavior part is is I think going we're gonna realize it's very tough and I think that also effects you know our development of autonomous vehicles I see them self-driving in smile like you want to use so you're building self-driving you know it the first time like right after urban challenge I think everybody focused on localization mapping and localization you know as slam algorithms came in Google was just doing that and so building these HD maps basically that's about knowing where you are and then five years later in 2012-2013 came the kind of coding code AI revolution and that started telling us about everybody else's but we're still missing what everybody else is gonna do next and so you want to know where you are you want to know what everybody else is hopefully you know about what you're gonna do next and then you want to predict what other people are going to do and that last bit has been a real real challenge what do you think is the role your own of you of your the ego vehicle the robot you the the you the robotic you in controlling and having some control of how the future on roles of what's going to happen in the future that seems to be a little bit ignored in trying to predict the future is how you yourself can affect that future by being either aggressive or less aggressive or signaling in some kind of way so this kind of game theoretic dance seems to be ignored for the moment it's yeah it's it's totally ignored I mean it's it's quite interesting actually like how we how we interact with things versus we interact with humans like so if if you see a vehicle that's completely empty and it's trying to do something all of a sudden it becomes a thing so interacted with like you interact with this table and so you can throw your backpack or you can kick your kick it put your feet on it and things like that but when it's a human there's all kinds of ways of interacting with a human so if you know like you and I are face to face we're very civil you know we talk understand each other for the most part you'll see you just but but the thing is that like for example you and I might interact through YouTube comments and you know the conversation may go a totally different angle and so I think people kind of abusing these autonomous vehicles is a real issue in some sense and so when you're an ego vehicle you're trying to you know coordinate your way make your way it's actually kind of harder than being a human you know it's like it's you you you not only need to be as smart as kind of humans are but you also you're a thing so they're gonna abuse you a little bit so you need to make sure that you can get around and do something so yeah III in general believe in that sort of game theoretic aspects I've actually personally have done you know quite a few papers both on that kind of game theory and also like this this kind of understanding people's social value orientation for example you know some people are aggressive some people not so much and and you know like you robot could understand that by just looking at how people drive and as they kind of come and approach you can actually understand like if someone is gonna be aggressive or or not as a robot and you can make certain decisions well in terms of predicting what they're going to do the hard question is you as a robot should you be aggressive or not when faced with it was an aggressive role but right now it seems like aggressive is a very dangerous thing to do because it's costly from a societal perspective how you're perceived people are not very accepting of aggressive robots emotive Society I think that's accurate so that is really is and so I'm not entirely sure like how to have to go about but it I know I know for a fact that how these robots interact with other people in there is going to be and then interaction is always gonna be there I mean you could be interacting with other vehicles or other just people kind of like walking around and like I said the moment there's like nobody in the seat it's like an empty thing just rolling off the street it becomes like no different than like any other thing that's not human and so so people and maybe abuse is the wrong word but you know people may be rightfully even they feel like you know this is a human present environments designed for humans to be and and they they kind of they want to own it and then you know the robots they would they would need to understand and they would need to respond in a certain way and I think that you know this actually opens up like quite a few interesting societal questions for us as we deploy like we talk robots at large scale so what would happen when we try to deploy robots at large scale I think is that we can design systems in a way that they're very efficient or we can design them that they're very sustainable but ultimately the sustainability efficiency trade-offs like they're gonna be right in there we're gonna have to make some choices like we're not going to be able to just kind of put it aside so for example we can be very aggressive and we can reduce transportation delays increase capacity of transportation or you know we can we can be a lot nicer and other people to kind of coding code on the environment and live in a nice place and then efficiency will drop so when you think about it I think sustainability gets attached to energy consumption or I wanna have the impact immediately and those are those are there but like livability is another sustainability impact so you create an environment that people want to live in and if robots are going around being aggressive and you don't want to live in that environment maybe however you should note that if you're not being aggressive then you know you're probably taking up some some delays in transportation and listen that so you're always balancing that and I think this this choice has always been there in transportation but I think the more autonomy comes in the more explicit the choice becomes yeah when it becomes explicit that we can start to optimize it and I will get to ask the very difficult societal questions of what do we value more efficiency or sustainability it's kind of interesting there will happen like I think we're gonna have to like I think that the the interesting thing about like the whole autonomous vehicles question I think is also kind of I think a lot of times you know we have we have focused on technology development like hundreds of years and you know the products somehow followed and and then you know we got to make these choices and things like that but this is this is a good time that you know we even think about you know autonomous taxi type of deployments and the systems that would evolve from there and you realize the business models are different the impact on architecture is different urban planning you get into like regulations and then you get into like these issues that you didn't think about before but like sustainability and ethics is like right in the middle of it I mean even testing autonomous vehicles like think about it you're testing autonomous vehicles in human present environments I mean the risk may be very small but still you know it's it's a it's a it's it's a you know strictly greater than zero risk that you're putting peep and so then you have that innovation you know risk trade-off that you're in that somewhere and we understand that pretty now they pretty well now is that if we don't test the beast day the development will be slower I mean it it doesn't mean that we're not gonna be able to develop I think it's gonna be pretty hard actually maybe we can we don't real I don't know but well the thing is that those kinds of trade-offs we already are making and as these systems become more ubiquitous I think those trade-offs will just really hit so you are one of the founders of optimist ride and town vehicle company and we'll talk about it well let me and that point ask maybe good examples keeping optimist right out of this question sort of exemplars of different strategies on the spectrum of innovation and safety or caution so you dick way Moe Google self-driving car way Moe represents maybe a more cautious approach and then you have Tesla on the other side added by Elon Musk that represents some more however which adjectives you want to use aggressive innovative I don't know but what what do you think about the difference between its two strategies in your view what's more likely what's needed and is more likely to succeed in the short term in the long term definitely some sort of balance is is kind of the right way to go but I do think that the thing that is the most important is actually like an informed public so I don't I don't mind you know I personally like if I were in some place I wouldn't mind so much like taking a certain amount of risk some other people might and so I think the key is for people to be informed and so that they can ideally they can make a choice in some cases that kind of choice making that anonymously is of course very hard but I don't think it's actually that hard to inform people so I think in in in one case like for example even the Tesla approach I don't know it's hard to judge how he informed it is but it is somewhat informed I mean you know things kind of come out I think people know what they're taking and things like that and so on but I think the underlying I do think that these two companies are a little bit kind of representing like babe of course that you know one of them seems a bit safer the other one or you know whatever the objective for that is and the other one seems more aggressive or whatever the ejector for that is but but I think you know when you turn the tables they're actually they're two other orthogonal dimensions that these two are focusing on on the one hand for remo I can see that you know they're I mean they I think they're a little bit see it as research as well so they kind of they don't I'm not sure if they're like really interested in like an immediate product you know they talk about it sometimes there's some pressure to talk about it so they kind of go for it but I think I think that they're thinking maybe in the back of their minds maybe they don't put it this way but I think they they realize that we're building like a new engine it's kind of like call it the AI engine or whatever that is and you know an autonomous vehicles is a very interesting embodiment of that engine that allows you to understand where the ego vehicle is the ego thing is where everything else is what everything else is gonna do and how do you react how do you actually you know interact with humans the right way how do you build these systems and I think they want to know that they want to understand that and so they keep going and doing that and so on the other dimension Tesla is doing something interesting I mean I think that they have a good product people use it think that you know like it's not for me but I can totally see people people like it and and people I think they have a good product outside of automation but I was just referring to the the automation itself I mean you know like it kind of drives itself you still have to be kind of you still have to pay attention to it right you know people seem to use it so it works for something and so people I think people are willing to pay for it people are willing to buy it I think it it's it's one of the other reasons why people buy a Tesla car maybe one of those reasons is Elon Musk is the CEO and you know he seems like a visionary person that's what people think you know it seems like a visionary person and so it adds like 5k to the value of the car and then maybe another 5k is the autopilot and and you know it's it's useful I mean it's useful in the sense that like people are using it and so III can see Tesla and sure of course they want to be visionary they want to kind of put out a certain approach and they may actually get there but I think that there's also a primary benefit of doing all these updates and rolling it out because you know people pay for it and it's it's your home it's basic you know demand supply market and people like it they're happy to pay another 5k 10k for that novelty or whatever that is they and they use it it's not like they get it and they try it a couple times it's a novelty but they use it a lot of the time and so I think that's what Tesla is doing it's actually pretty different like they are on pretty orthogonal dimensions of what kind of things that they're building they are using the same AI engine so it's very possible that you know they're both gonna be sort of one day kind of using a similar almost like an internal internal combustion engine it's a very bad metaphor but similar internal combustion engine and maybe one of them is building like a car the other one is building a truck or something so ultimately the use case is very different so you like I said or one of the founders of Optimus rad let's take a step back it's one of the success stories in the autonomous vehicle space it's a great attack vehicle company let's go from the very beginning what does it take to start autonomous vehicle company how do you go from idea to deploying vehicles like you are and a few a bunch of places including New York I would say that I think that you know what happened to us is it was was the following I think we've realized a lot of kind of talk in the autonomous vehicle industry back in like 2014 even when we wanted to kind of get started and I don't know like I kind of I would hear things like fully autonomous vehicles two years from now three years from now I kind of never bought it you know I was a part of MIT zorbing Channel Gentry it kind of like it has an interesting history so I did in college and in high school sort of a lot of mathematically oriented work and I think I kind of you know at some point it kind of hit me I wanted to build something and so I came to MIT mechanical engineering program and I now realize I think my advisor hired me because I could do like really good math but I told him that no no no I want to work on that urban challenge car I want to build the autonomous car and I think that was that was kind of like a process why we really learned I mean what the challenges are and and what kind of limitations are we up against you know like having the limitations of computers or understanding human behavior there's so many of these things and I think it's just kind of didn't and so so we said hey you know like why don't we take a more like a market-based approach so we focus on a certain kind of market and we build a system for that what we're building is not so much of like an autonomous vehicle only I would say so we build full autonomy into the vehicles but you know the way we kind of see it is that we think that the approach should actually involve humans operating that not just just not sitting in the vehicle and I think today what we have is today we have one person operate one vehicle no matter what that vehicle it could be a forklift it could be a truck it could be a car whatever that is and we want to go from that to ten people operate 50 vehicles how do we do that you're referring to a world of maybe perhaps teleoperation so can you just say what it means for 10 might be confusing for people listening what does it mean for ten people to control 50 vehicles that's a good point so I think it's am I very deliberately didn't call it a law operation because people what people think then is that people think away from the vehicle sits a person sees like maybe put some goggles or something ER and drives the car so that's not at all what we need but we mean the kind of intelligence bye-bye humans are in control except in certain places the vehicles can execute on their own and so imagine like like a room where people can see what the other vehicles are doing and everything and you know there will be some people who are more like more like air traffic controllers call them like AV controllers yeah and so these AV controllers would actually see kind of like like a whole map and they would understand where vehicles are really confident and where they kind of you know need a little bit more help and the help shouldn't be for safety how it should be for efficiency vehicles should be safe no matter what if you had zero people they could be very safe but they be going five miles an hour and so if you want them to go around 25 miles an hour then you need people to come in and and for example you know the vehicle come to an intersection and the vehicle can say you know I can wait I can inch forward a little bit show my intent or I can turn left and right now it's clear I can turn I know that but before you give me the go I won't and so that's one example this doesn't mean necessarily we're doing that actually I think I think if you go down all them all that much detail that every intersection you're kind of expecting a person to press a button then I don't think you'll get the efficiency benefits you want you need to be able to kind of go around and be able to do these things but but I think you need people to be able to set high level behavior to vehicles that's the other thing with autonomous vehicles you know I think a lot of people kind of think about it as follows I mean this happens with technology a lot you know you think alright so I know about cars and I heard robots so I think how this is gonna work out is that I'm gonna buy a car press a button and it's gonna drive itself and when is that gonna happen you know and people kind of tend to think about it that way but when you think about what really happens is that something comes in in a way that you didn't even expect if asked you might have said I don't think I need that or I don't think it should be that and so on and then and then that that becomes the next big thing coding code and so I think that this kind of different ways of humans operating vehicles could be really powerful I think that sooner than then later we might open our eyes up to a world in which you go around walk in a mall and there's a bunch of security they're exactly operated in this way you go into a factory or a warehouse there's a whole bunch of robots they're pretty exactly in this way you go to a you go to the Brooklyn Navy Yard you see a whole bunch of autonomous vehicles Optimus right and they're operated maybe in this way yes but I think people kind of don't see that III sincerely think that it's it's there's a possibility that we may almost see like like a whole mushrooming of this technology in all kinds of places that we didn't expect before and then maybe the real surprise and then one day when your car actually drives itself it may not be all that much of a surprise at all because you see it all the time you interact with them you take the Optimus ride hopefully that's your choice and then you know you you hear a bunch of things you go around you in your act with them I don't know like you have a little delivery vehicle that goes around the sidewalks and delivers you things and then you take it it says thank you and then you get used to that and one day your car actually drives itself and the regulation goes by and you know you can hit the button asleep and it wouldn't be a surprise at all I think that maybe the real reality so there's gonna be a bunch of applications that pop up around autonomous vehicles some some of which maybe many of which we don't expect at all so if we look at Optimus ride what do you think you know the viral application that the one that like really works for people in mobility what do you think optimus ride will connect with in in in near future first um I think that the first place is that that I like the target honestly is like these places where transportation is required within an environment like people typically call a geofence so you can imagine like a roughly two mile by two mile could be bigger could be smaller type of an environment and there's a lot of these kinds of environments they're typically transportation deprived the Brooklyn Navy Yard that you know we're in today we're in a few different places but that's that was the one that was less publicized that's a good example so there's not a lot of transportation there and you wouldn't expect like I don't know I think maybe operating an uber there ends up being sort of a little too expensive or when you compare it with operating uber that becomes the elsewhere becomes the priority and these people whose place has become totally transportation deprived and then what happens is that you know people drive into these places and to go from point A to point B inside this place within that day they use their cars and so we end up building more parking for them to for example take their cars and go to the lunch place and I think that one of the things that can be done is that you know you can put in efficient safe sustainable transportation systems into these types of places first and I think that you know you could deliver mobility in an affordable way affordable accessible you know sustainable way but I think what also enables is that this kind of effort money area land that we spend on parking we could reclaim some of that and that is on the order of like even for a small environment like two mile by two mile it doesn't have to be smack in the middle of New York I mean anywhere else you're talking tens of millions of dollars if you're smack in the middle of New York you're looking at billions of dollars of savings just by doing that and that's the economic part of it and there's a societal part right I mean just look around I mean the places that we live are like built for cars it didn't look like this just like a hundred years ago like today no one walks in the middle of the street it's four cars we no one tells you that growing up but you grow into that reality and so sometimes they close the road it happens here you know like the celebration they close the road still people don't walk in the middle of the road like just walk in and people don't but I think it has so much impact the the car in in the space that we have and and I think we talked about sustainability livability I mean ultimately these kinds of places that parking spots at the very least could change into something more useful or maybe just like park areas recreational and so I think that's the first thing that that we're targeting and I think that we're getting like a really good response both from an economic societal point of view especially places that are a little bit forward-looking and like for example Brooklyn Navy Yard they have tenants there distinct I recall like new lab it's kind of like an Innovation Center there's a bunch of startups there and so you know you get those kinds of people and you know that they're really interested in sort of making that environment more livable and these kinds of solutions that Optimus tried provides almost kind of comes in and and becomes that and many of these places that are transportation deprived you know they have they actually ran shuttles and so you know you can ask anybody the shuttle experience is like terrible people hate shuttles and I can tell you why it's because you know like the driver is very expensive in a shuttle business so what makes sense is to attach 2030 seats to a driver and a lot of people have this misconception they think that shuttle should be big sometimes we get that our optimist right we tell them we're gonna give you like four seater six Cedars and we get asked like how about like twenty Cedars like you know you don't need twenty Cedars you want to split up those seeds so that they can travel faster and the transportation delays would go down that's what you want if you make it big not only you will get delays in transportation but you won't have an agile vehicle it will take a long time to speed up slow down and so on it'll you need to climb up to the thing so it's kind of like really hard to interact with and scheduling too perhaps when you have more smaller vehicles because closer to BER where you can actually get a personal I mean just the logistics of getting the vehicle to you it becomes easier when you have a giant shadow there's fewer of them and it probably goes on a route a specific route that's supposed to hit and when you go on a specific route and all seats travel together versus you know you have a whole bunch of them you can imagine the route you can still have but you can imagine you split up the seats and instead of you know damn traveling like I don't know a mile apart they could be like you know half a mile apart if you split them into two that basically would mean that your delays when you go out you want wait for them for a long time and that's one of the main reasons or you don't have to climb up the other thing is that I think if you split them up in a nice way and if you can actually know where people are going to be somehow you don't even need the app a lot of people ask us the app we say why don't you just walk into the vehicle how about you just walk into the vehicle it recognizes who you are and it gives you a bunch of options of places that you go and you just kind of go there I mean people kind of also internalize the apps everybody needs a nap it's like you don't need an app you just walk into the place walk up but I think I think one of the things that you know we really try to do is to take that shuttle experience that no one likes and tilt it into something that everybody loves and so I think that's another important thing I would like to say that carefully just like today operationally we don't do shuttles you know we're really kind of thinking of this as a system or a network that we're designing but but ultimately we go to places that would normally rent the shuttle service that people wouldn't like as much and we want to tilt it into something that people love so you virtually the second earlier but how many optimist ride vehicles do you think would be needed for any person in Boston or New York if they step outside there will be this this is like a mathematical question there'll be two optimist ride vehicles within line of sight is that the right number - well these for example um that's that's the density so meaning that if you see one vehicle you look around you see another one - imagine like you know Tesla will tell you they collect a lot of data do you see that with Tesla like you just walk around and you look on you see Tesla probably not very specific areas of California maybe maybe you're right like there's a couple zip codes that you know just but I think but I think that's kind of important because you know like maybe the couple zip codes um the one thing that we kind of depend on I'll get to your question in a second but now like we're taking a lot of tangents today oh yeah so so so I think that this is actually important people call this data density or data velocity so it's very good to collect data in a way that you know you see the same place so many times like you can drive 10,000 miles around the country or you drive 10,000 miles in a confined environment you'll see the same intersection hundreds of times and when it comes to dick ting what people are gonna do in that specific intersection we become really good at it versus if you draw in like ten thousand miles around the country you sing that only once and so trying to predict what people do become sorry and I think that you know you said what is needed it's tens of thousands of vehicles you know you really need to be like a specific fraction or vehicle like for example in good times in Singapore you can go and you can just grab a cab and they are like you know 10% 20% of traffic those taxis ultimately that's why you need to get to so that you know you you get to a certain place where you really the benefits really kick off and like orders of magnitude type of a point but once you get there you actually get the benefits and you can certainly carry people I think that's one of the things people really don't like to wait for themselves but for example they can wait a lot more for the goods if they order something like there you were sitting at home and you want to wait half an hour that sounds great people say it's great you want to you're gonna take a cab you're waiting half an hour like that's crazy you don't want to wait that much but I think you know you you can I think really get to a point where the system at peak times really focuses on kind of transporting humans around and then it's it's really it's a good fraction of traffic to the point where you know you go you look around there's something there and you just kind of basically get in there and it's already waiting for you or something like that and then you take it if you do it at that scale like today for instance uber if you talk to a driver right I mean uber takes a certain cut it's a small cut or drivers would argue that it's a large cut but you know it's it's it's when you look at the grand scheme of things most of that money that you pay Hueber kind of goes to the driver and if you talk to the driver the driver will claim that most of it is their time you know they it's not spent on gas they think it's not spent on the the car per se as much it's like their time and if you didn't have a have a person driving or if you're in a scenario where you know like point one person is driving the car a fraction of a person is kind of operating the car because you know your one operates several if you're in that situation you realize that the internal combustion engine type of cars are very inefficient you know we built them to go on highways they pass crash tests they're like really heavy they really don't need to be like 25 times the weight of its passengers or or you know like area wise and so on and but if you get through those inefficiencies and if you really build like urban cars and things like that I think the economics really starts to check out like to the point where I mean I don't know you may be able to get into a car and it may be less than a dollar to go from A to B as long as you don't change your destination you just pay 99 cents and go that if you share it if you take another stop somewhere it becomes a lot better you know these kinds of things at least four models at least for mathematics and theory they start to really check out so I think it's really exciting what Optimus Art is doing in terms of it feels the most reachable like they'll actually be here and have an impact yeah that is the idea and if we contrast that again we'll go back to our old friends way Moe and Tesla so way Moe seems to have sort of technically similar approaches as Optimus ride but a different they're not as interested it has having an impact today these in nature they have a longer term sort of investments almost more of a research project still meaning they're trying to solve as far as I understand maybe you can you can differentiate but they seem to want to do more unrestricted movement meaning move from A to B where A to B is all over the place versus Optimus right is really nicely geofence and really sort of established mobility in a particular environment before you expand it and then Tesla is like the complete opposite which is you know the entirety of the world actually is going to be automated highway driving urban driving every kind of driving you know you kind of creep up to it by incrementally improving the capabilities of the autopilot system so when you contrast all of these and on top of that let me throw a question that nobody likes but his timeline when do you think each of these approaches loosely speaking nobody can predict the future will see mass deployment so yah mosque predicts the the craziest approach is at the I've heard figures like at the end of this year right so that's probably wildly inaccurate but how wildly inaccurate is it I mean first thing to lay out like everybody else it's really it's really hard to guess I mean I don't know I don't know where where Tesla can look at or Elon Musk can look at and say hey you know it's the end of this year I mean I don't know what you can look at you know even the data that you know you I mean if you look at the data even kind of trying to extrapolate the end state without knowing what exactly is gonna go especially for like a machine learning approach I mean it's just kind of very hard to predict but I do think the following does happen I think a lot of people you know what they do is that there's something that I called a couple times time dilation in technology prediction happens let me try to describe a little bit there's a lot of things that are so far ahead people think they're close and there's a lot of things that are actually close people think it's far ahead people tries to kind of look at a whole landscape of technology development admit needs chaos anything can happen in any order at any time and there's a whole bunch of things in that people take it clamp it and put it into the next three years and so then what happens is that there's some things that maybe can happen by the end of the year or next year and so on and they push that into like few years ahead because it's just hard to explain and there are things that are like we were looking at 20 years more maybe you know hopefully in my lifetime type of things and cuz you know we don't know I mean we don't know how hard it is even like that's a problem we don't know like if some of these problems are actually AI complete like we have no idea what's going on and and you know we we take all of that and then we clump it and then we say three years from now and then some of us are more optimistic so they're shooting at the at the end of the year and some of us are more realistic they say like five years but you know we all I think it's just hard to know and and I think trying to predict like products ahead to three years it's it's hard to know in the following sense you know like we typically say okay this is a technology company but sometimes sometimes really you're trying to build something where technology does like there's a technology gap you know like and Tesla had that with electric vehicles you know like when they first started they would look at a chart much like a moose law type of chart and they would just kind of extrapolate that out and they'd say we want to be here what's the technology to get that we don't know it goes like this so it's probably just gonna you know keep going yeah um with bit AI that goes into the cars we don't even have that like we can't I mean what can you quantify yeah like what kind of chart are you looking at you know but so but so I think when there's the technology gap it's just kind of really hard to predict so now I realize I talk like five minutes and avoid your question I didn't tell you anything about and I don't think you I think you've actually argued that it's not used even NES you provide now is not that used to be very hard there's one thing that I really believe in and and you know this is not my idea and it's been you know discussed several times but but this this this kind of like something like a startup or a kind of an innovative company including definitely may want may vary more Tesla maybe even some of the other big companies that are kind of trying things this kind of like iterated learning is very important the fact that we're over there and we're trying things and so on I think that's that's important we try to understand and and I think that you know the coding code Silicon Valley has done that with business models pretty well and now I think we're trying to get to do it well there's a little technology gap I mean before like you know you're trying to build I'm not trying to you know I think these companies are building great technology to for example enable internet search to do it so quickly and that kind of didn't what wasn't there so much but at least like it was a kind of a technology that you could predict to some degree and so on and now we're just kind of trying to build you know things that it's kind of hard to quantify what kind of a metric are we looking at so psychologically is a sort of as a leader of graduate students and an optimist ride a bunch of brilliant engineers just curiosity psychologically do you think it's good to think that you know whatever technology gap we're talking about can be closed by the end of the year or do you you know because we don't know so the way do you want to say that everything is going to improve exponentially to yourself and to others around you as a leader or do you want to be more sort of maybe not cynical but I don't want to use realistic because it's hard to predict but yeah maybe more cynical pessimistic about the ability to close again yeah I I think that you know going back I think that iterated learning is like key that you know you're out there you're running experiments to learn and that doesn't mean sort of like you know you like like your optimist right you're kind of doing something but I like in an environment but like what Tesla is doing I think is also kind of like this this kind of notion and and you know people can go around and say like you know this year next year the other year and so on but but I think that the nice thing about it is that they're out there they're pushing this technology in I think what they should do more of I think that kind of informed people about what kind of technology that they're providing you know the good and the bad and then you know not just sort of you know if it works very well but I think you know I'm not saying they're not doing bad and informing I think they're kind of trying they you know they put up certain things or at the very least YouTube videos comes out on on how the summon function works every now and then and and you know people get informed and so that that kind of cycle continues but you know I I admired I think they're kind of go out there and they do great things they do their own kind of experiment I think we do our own and I think we're closing some similar technology gaps but some also some are orthogonal as well you know I think like like we talked about you know people being remote like it's something or in the kind of environments that we're in or think about a test the car maybe maybe you can enable it one day like there's you know low traffic like you're kind of the stuff on go emotion you just hit the button and the you can really say or maybe there's another you know Lane that you can pass into you going that I think they can enable these kinds of pride believe it and so I think that that part that is really important and that is really key and and beyond that I think you know when is it exactly gonna happen and and and so on I mean it's like I said it's very hard to predict and I would I would imagine that it would be good to do some sort of like a like a one or two year plan when it's a little bit more predictable that you know you the technology gaps you close and and there and the kind of sort of product that would answer so I know that from optimist ride or you know other companies that I get involved in I mean at some point you find yourself in a situation where you're trying to build a product and and people are investing in that in that you know building effort and those investors that they do want to know as they compare the investments they want to make they do want to know what happens in the next one or two years and I think that's good to communicate that but I think beyond that it becomes it becomes a vision that we want to get to someday and saying five years ten years I don't think it means anything but iterative learning is key though you do and learn I think that is key you know I got a sort of throwback right at you criticism in terms of you know like Tesla or somebody communicating you know how someone works and so on I got a chance to visit Optimus ride and you guys are doing some awesome stuff and yet the internet doesn't know about it so you should also communicate more showing off in showing off some of the awesome stuff the stuff that works and stuff that doesn't work I mean it's just the stuff I saw with the tracking different objects and pedestrians so I'm incredible stuff going on there just cool maybe it's just the nerd of me but I think the world would love to see that kind of stuff yeah that's that's well taken I think you know I should say that it's not like you know we we weren't able to I think we made a decision at some point that decision did involve me quite a bit on kind of sort of doing this in kind of coding called stealth mode for a bit but I think that you know we will open it up quite a lot more and I think that we are also that optimist right kind of hitting when you new era you know we're big now we're doing a lot of interesting things and and I think you know some of the deployments that we kind of announced were some of the first bits bits of information that we kind of put out into the world we'll also put out our technology a lot of the things that we've been developing is really amazing and you know we're gonna we're gonna start putting it out now we're especially interested in sort of like being able to work with the best people and I think and I think it's it's good to not just kind of show them and they come to our office for an interview but just put it out there in terms of like you know get people excited about what we're doing so on Thomas vehicle space let me ask one last question so yah mosque famously said that lighter is a crutch so uh I've talked to a bunch of people bought it got asked you you use that crutch quite a bit in the DARPA days so you know and is that his idea in general sort of you know more provocative and fun I think than a technical discussion but the idea is that camera based can't primarily camera based systems is going to be what defines the future of autonomous vehicles so what do you think of this idea ladders a crutch versus primarily uh camera based systems first things first I think you know I'm a big believer in just camera based autonomous vehicle systems like I think that you know you can put in a lot of autonomy and and you can do great things and and it's it's it's very possible that at the time scales like we said we can't predict twenty years from now like you may be able to do do things that we're doing today only what lidar and you may be will do them just with cameras and I think that you know you can just I I think that I will put my name on it to like you know there will be a time when you can only use cameras and you'll be fine at that time though it's very possible that you know you find the lidar system as another robusta fire or or it's so affordable that it's stupid not to you know just kind of put it there and I think and I think we may be looking at a future like that do you think we're over relying on lidar right now because we understand it better it's more reliable anyways internment from a safety easier to build with that's the other that's the other thing I think to be very frank with you I mean you know we've seen a lot of sort of autonomous vehicles companies come and go and the approach has been you know you slap a lidar on a car and it's kind of easy to build with when you have a lighter are you know you just kind of coat it up and and you hit the button and you do a demo so I think there's admittedly there's a lot of people they focus on the lidar because it's easier to build with that doesn't mean that you know without the cameras just cameras you can you cannot do what they're doing but it's just kind of a lot harder and so you need to have certain kind of expertise to exploit that what we believe in and you know you may be seeing some of it is that we believe in computer vision we certainly work on computer vision and optimist ride by a lot like um and and we've been doing that from day one and we also believe in sensor fusion so you know we do we have a relatively minimal use of light ours but but we do use them and I think you know in the future I really believe that the following sequence of events may happen first things first number one there may be a future in which you know there's like cars with light hours and everything and the cameras but you know this in this 50 year ahead future they can drive with cameras as well especially in some isolated environments and cameras they go and they do the thing in the same future it's very possible that you know the white ARS are so cheap and frankly make the software may be a little less compute-intensive at the very least or maybe less complicated so that they can be certified or or insured there of their safety and things like that that it's kind of stupid not to put the lidar like imagine this you either put pay money for the lidar or you pay money for the compute and if you don't put the lidar it's a more expensive system because you have to put in a lot of compute like this is another possibility I do think that a lot of the sort of initial deployments of self-driving vehicles I think they will involve light ARS and especially either low range or short either short range or low resolution light ARS are actually not that hard to build in solid state they're still scanning but like MEMS type of scanning light ours and things like that they're like they're actually not that hard I think they will may be kind of playing with the spectrum and the phaser eyes they're a little bit harder but but I think like you know putting your mom's mirror in there that kind of scans the environment it's not hard the only thing is that you know you just like with a lot of the things that we do nowadays in developing technology you hit fundamental limits of the universe the speed of light becomes a problem in when you're trying to scan the environment so you don't get either good resolution or you don't get range but but you know it's still it's something that you can put in that affordably so let me jump back to drones you've uh you have a role in the Lockheed Martin alpha pilot Innovation Challenge where teams compete in drone racing a super cool super intense interesting application of AI so can you tell me about the very basics of the challenge and where you fit in well your thoughts are on this problem and it's sort of echoes of the early DARPA challenge in the through the desert that we're seeing now now with drone racing yeah I mean one interesting thing about it is that you know people drone racing a this is an eSport and so it's much like you're playing a game but there's a real drone going in an environment the human being is controlling it with goggles on so there's no it is a robot but there's no AI there's no way I am human being is controlling it and so that's already there and and I've been interested in this problem for quite a while actually from a robot assist point of view and that's what's happening in alpha pilot which which probably of aggressive flight of aggressive flight fully autonomous aggressive flight the problem that I'm interested in you asked about alpha pod and I'll get there in a second but the problem that I'm interested in I'd love to build autonomous vehicles like like drones that can go far faster than any human possibly can I think we should recognize that we as humans have you know limitations in how fast we can process information and those are some biological limitations like we think about this AI this way too I mean this has been discussed a lot and this is not sort of my idea per se but a lot of people kind of think about human level III and they think that you know AI is not human level one day it'll be human level and humans in the eyes they kind of interact versus I think that the situation really is that humans are at a certain place and AI keeps improving and at some point just crosses off and then you know it gets smarter and smarter and smarter and so drone releasing the same issue humans play this game and you know you have to like react in milliseconds and there's really you know you see something with your eyes and then that information just flows through your brain into your hands so that you can command it and there's some also delays and you know getting information back and forth but suppose a laser don't exist you just just a delay between your eye and your fingers please delay that a robot doesn't have to have so we end up building in my research group like systems that you know see things at a kilohertz like a human eye would barely hit a hundred Hertz so imagine things that see stuff in slow motion like 10x slow motion it will be very useful like we talked a lot about autonomous car so you know we don't get to see it but the hundred lives are lost every day just in the United States on traffic accidents and many of them are like known cases you know like the you're coming through like like a ramp going into a highway you hit somebody and you're off or you know like you kind of get confused you try to like swerve into the next lane you go off the road and you crash whatever and I'm I think if you had enough computer in a car and a very fast camera right at the time of an accident you could use all compute you have like you could shut down the infotainment system and use that kind of computing resources instead of rendering you use it for the kind of artificial intelligence that goes in there the autonomy and you can you can either take control of the car and bring it to a full stop but even even if you can't do that you can deliver what the human is trying to do human is trying to change the lane but goes off the road not being able to do that with motor skills and the eyes and you know you can get in that and I was there's so many other things that you can enable with what I would call high throughput computing you know data is coming in extremely fast and in real time you have to process it and the current CPUs have ever fast you clock it are typically not enough you need to build those computers from the ground up so that they can ingest all that data that I'm really interested in just on that point really quick is the currently what's the bottom like you mentioned the delays in humans is it the hardware so you work a lot with NVIDIA hardware is it the hardware is it the software I think it's both I think it's both in fact they need to be co-developed I think in the future I mean that's a little bit what Nvidia does sort of like they almost like build the hardware and then they build the neural networks and then they build the hardware back and the neural networks back and it goes back and forth but it's that Co design and I think that you know like we try to way back we try to build a faster own that could use a camera image to like track what's moving in order to find where it is in the world this typical sort of you know visual inertial state estimation problems that we would solve and you know we just kind of realize that we're at the limit sometimes of you know doing simple tasks we're at the limit of the camera frame rate because you know you really want to track things you want the camera image to be 90% kind of like or or some somewhat the same from one frame to the next and why are we at the limit of the camera frame rate it's because camera captures data it puts it into some serial connection it could be USB or like there's something called camera serial interface that we use a lot it puts into some serial connection and copper wires can only transmit so much data and you hit the Shannon limit on copper wires and you know you you hit yet another kind of Universal limit that you can transfer the data so you have to be much more intelligent on how you capture those pixels you can take compute and put it right next to the pixels people are governed all that you do how hard is to get past the bottleneck of the copper wire yeah you need to you need to do a lot of parallel processing as you can imagine the same thing happens in the GPUs you know like the data is transferred in parallel somehow it gets into some parallel processing I think that you know like now we're really kind of diverted off into so many different dimensions but great so its aggressive light how do we make drones see many more frame just a second in order to enable aggressive fight that's a super interesting problem that's an interesting problem so but like think about it you have you have CPUs you clock them at you know several gigahertz we don't clock them faster largely because you know we run into some heating issues and things like that but another thing is that 3 gigahertz clock light travels kind of like on the order of a few inches or an inch that's the size of a chip and so you pass a clock cycle and as the clock signal is going around in the chip you pass another one and so trying to coordinate that the design of the complexity of the chip becomes so hard I mean we have hit the fundamental limits of the universe in so many things that we're designing I don't know I realize that it's great but like we can't make transistors smaller because like quantum effects that electrons start to tunnel around we can't clock it faster one of the reasons why is because like the information doesn't travel faster in the universe yeah and we're limited by that same thing with the laser scanner but so then it becomes clear that you know the way you organize the chip into a CPU or even a GPU you now need to look at how to redesign that if you're gonna stick with silicon yes you could go do other things too I mean there's that too but you really almost need to take those transistors put them in a different way so that the information travels on those transistors in a different way in a much more way that is specific to the high-speed cameras coming in and so that's one of the things that that we talk about quite a bit so drone racing kind of really makes that embodies that he embodies that and that's what is exciting it's exciting for people you know students like it it embodies all those problems but going back we're building coding code and other engine and that engine I hope one day we'll be just like how impactful seatbelts were in in driving I hope so Wow or it could enable your next generation autonomous air taxis and things like that I mean it sounds crazy but one day we may need to purge that these things if you really want to go from Boston to New York in more than a half hours you may want to fixed-wing aircraft most of these companies that are kind of doing Concorde flying cars they're focusing on that but then how do you land it on top of a building you may need to pull off like kind of fast maneuvers for a robot like perch land it's gonna go perch into into a building if you want to do that like you need these kinds of systems and so drone racing you know it's being able to go very faster than anything we can't comprehend take an aircraft forget the quadcopter we take your fixed-wing while you're at it you might as well put some like rocket engines in the back you just light it you go through the gate and everyone looks at it and just said what just happened yeah and they would say it's impossible for me to do that and that's closing the same technology gap that would you know one day steer cars out of accidents so but let's get back to the practical which is sort of just getting the thing to work in a race environment which is kind of what the is another kind of exciting thing which the DARPA challenge to the desert did you know theoretically we had autonomous vehicles but making them successfully finish a race first of all which nobody finished the first year and then the second year just to get you know to finish and really go at a reasonable time is really difficult engineering practically speaking challenge so that let me ask about the the Alpha pilot challenge is a I guess a big prize potentially associated with it but let me ask reminiscent of the DARPA Days predictions you think anybody will finish well not not soon I think that depends on how you set up the race course and so if the race course is a slalom course I think people will kind of do it but can you set up some course like literally sunk or you get to design it there is the algorithm developer can you set up some course so that you can beat the best human when is that gonna happen like that's not very easy even just setting up some course if you let the human that you're competing with set up the course it becomes a worries a lot harder hmm so how many in the space of all possible courses are would humans win and quad machines were a great question let's get to that I want to answer your other question which is like the DARPA challenge days right what was really hard I think I think we understand we understood what we wanted to build but still building things that experimentation that iterated learning that takes up a lot of time actually and and so in my group for example in order for us to be able to develop fast we build like VR environments will take an aircraft will put it in a motion capture room big huge motion capture room and we'll fly it in real time will render other images and beam it back to the drone that sounds kind of notionally simple but it's actually hard because now you're trying to fit all that data through the air into the drone and so you need to do a few crazy things to make it happen but once you do that then at least you can try things if you crash into something you didn't actually crash so it's like the whole drone is in VR we can do augmented reality and so on and so I think at some point testing becomes very important one of the nice things about alpha pilot is that they built the drone and they build a lot of drones and and it's okay to crash in fact I think maybe you know the viewers may kind of like to see things that suppose that potentially could be the most exciting part it could be the exciting part and I think you know as an engineer it's a very different situation to be in like in academia a lot of my colleagues who are actually in this race and they're really great researchers but I've seen them trying to do similar things whereby they built this one drone and you know some somebody with like a face mask and a glows are going you know right behind the drone is trying to hold it if it if it falls down imagine you don't have to do that I think that's one of the nice things about auto pilot challenge where you know we have this drones and we're going to design the courses in a way that will keep pushing people up until the crashes start to happen and you know we'll hopefully sort of I don't think you want to tell people crashing is okay if we want to be careful here but because you know we don't people to crash a lot but certainly you know we want we want them to push it so that you know everybody crashes once or twice and and and you know they're really pushing it to their limits and that's where iterated learning comes in as ever every crash is a lesson is the lesson exactly so in terms of the space of possible courses how do you think about it in in the in the war of the video versus machines or do machines when we look at that quite a bit I mean I think that you know you will see quickly that like you can design a course and you know in in in certain courses like in the middle somewhere if if you kind of run through the course once you know the Machine gets beaten pretty much consistently by slightly but if you go through the course like 10 times humans get beaten very slightly but consistently so humans at some point you know you get confused you get tired and things like that versus machine is just executing the same line of code tirelessly just going back to the beginning and doing the same thing exactly I think I think that kind of thing happens and I realize sort of as humans there's the classical things you know that everybody has realized like like if you put in some sort of like strategic thinking that's a little bit harder for machines that I think sort of comprehend precision is easy to do so that's what they excel in and also sort of repeatability is easier to do that's what they excel in they can you can build machines that excel in strategy as well and beat humans that way too but that's a lot harder to build I have a million more questions but in the interest of time last question yeah what is the most beautiful idea you've come across in robotics well their simple equation experiment a demo simulation piece of software what just gives you pause that's an interesting question I have done a lot of work myself in decision making so I've been interested in that area so you know in robotics you have somehow the field has split into like you know there's people who would work on like perception how robots perceive the environment then how do you actually make like decisions and there's people also like how do you interact people interact with drove us is a whole bunch of different fields and and you know I I have admittedly worked a lot on the more control and decision-making than the others and I think that you know the one equation that has always kind of baffled me is Bellman's equation and so it's it's this person who have realized like way back you know more than half a century ago on like how do you actually sit down and if you have several variables that you're kind of jointly trying to determine how do you determine that and there is one beautiful equation that you know like today people do reinforcement where we still use it and and it's it's baffling to me because it both kind of tells you the simplicity because it's a single equation that anyone can write now we can teach it in the first course on decision-making at the same time it tells you how computation we how hard the problem is I feel like my like a lot of the things that I've done at MIT for research has been kind of just this fight against computational efficiency things like how can we get it faster to the point where we now got to like let's just redesign this chip like maybe that's the way but I think it talks about how computationally hard certain problems can be by nowadays what people call curse of dimensionality and so as the number of variables cannot grow the number of decisions you can make grows rapidly like if you have you know 100 variables each one of them take ten values all possible assignments is more than the number of atoms in the universe it's just crazy and and that kind of thinking is just embodied in that one equation that I really like and the beautiful balance between it being theoretically optimal and somehow practically speaking given the curse of dimensionality nevertheless in practice works among you know despite all those challenges which is quite incredible it's just quite incredible so you know I would say that it's kind of like quite baffling actually you know in a lot of fields that we think about how little we know you know like and so I think here too you know we know that in the worst case things are pretty hard but you know in practice generally things work so it's just kind of its kind of baffling decision-making how little we know just like how little we know about the beginning of time how little we know about you know our own future like if you actually go into like from balanced equation all the way down I mean there's also how little we know about like mathematics I mean we don't even know the axioms are like consistent it's just crazy yeah yeah I think a good lesson the lesson there just as you said we tend to focus on the worst case or the the boundaries of everything we're studying and then the average case seems to somehow work out if you think about life in general we mess it up a bunch you know we freaked out about a bunch of the traumatic stuff but in the end it seems to work out ok yeah that seems like a good metaphor sir touch it thank you so much for being a friend a colleague a mentor that really appreciates it on and talk to you like mice thank you thanks thanks for listening to this conversation with sir - karma and thank you to a presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast enjoy this podcast subscribe my youtube review it with 5 stars an apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman and now let me leave you with some words from Hal 9000 from the movie 2001 a Space Odyssey I'm putting myself to the fullest possible use which is all I think that any conscious entity can ever hope to do thank you for listening and hope to see you next time you |
Stephen Schwarzman: Going Big in Business, Investing, and AI | Lex Fridman Podcast #96 | the following is a conversation with stephen schwartzman ceo and co-founder of blackstone one of the world's leading investment firms with over 530 billion dollars of assets under management he's one of the most successful business leaders in history i recommend his recent book called what it takes that tells stories and lessons from his personal journey stephen is a philanthropist and one of the wealthiest people in the world recently signing the giving pledge thereby committing to give the majority of his wealth to philanthropic causes as an example in 2018 he donated 350 million dollars to mit to help establish its new college of computing the mission of which promotes interdisciplinary big bold research in artificial intelligence for those of you who know me know that mit is near and dear to my heart and always will be it was and is a place where i believe big bold revolutionary ideas have a home and that is what is needed in artificial intelligence research in the coming decades yes there's institutional challenges but also there's power in the passion of individual researchers from undergrad to phd from young scientists to senior faculty i believe the dream to build intelligence systems burns brighter than ever in the halls of mit this conversation was recorded recently but before the outbreak of the pandemic for everyone feeling the burden of this crisis i'm sending love your way stay strong we're in this together this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars and have a podcast support it on patreon or simply connect with me on twitter at lex friedman spelled f-r-i-d-m-a-n as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation i hope that works for you and doesn't hurt the listening experience quick summary of the ads two sponsors masterclass and expressvpn please consider supporting the podcast by signing up to masterclass masterclass.com lex and getting expressvpn at expressvpn.com lex pod this show is sponsored by masterclass sign up at masterclass.com lex to get a discount and support this podcast when i first heard about masterclass i thought it was too good to be true for 180 a year you get an all-access pass to watch courses from to list some of my favorites chris hadfield on space exploration neil degrasse tyson on scientific thinking communication will wright creator of simcity and sims on game design carlos santana on guitar gary kasparov on chess daniel negrano and poker and many many more chris hadfield explaining how rockets work and the experience of being launched into space alone is worth the money by the way you can watch it on basically any device once again sign up at masterclass.com lex to get a discount and to support this podcast this show is sponsored by expressvpn get it at expressvpn.com lex pod to get a discount and to support this podcast i've been using expressvpn for many years i love it it's easy to use press the big power on button and your privacy is protected and if you like you can make it look like your location is anywhere else in the world i might be in boston now but i can make you look like i'm in new york london paris or anywhere else in the world this has a large number of obvious benefits certainly it allows you to access international versions of streaming websites like the japanese netflix or the uk hulu expressvpn works on any device you can imagine i use it on linux shout out to ubuntu 2004 windows android but it's available everywhere else too once again get it at expressvpn.com lexpod to get a discount and to support this podcast and now here's my conversation with stephen schwartzman let's start with the tough question what idea do you believe whether grounded in data or an intuition that many people you respect disagree with you on well there isn't all that much uh anymore since the world's so transparent uh but uh one of the things i i believe in and put it in the the book what it takes is is if you're going to do something do do something very consequential do something that's quite large uh if you can that's unique uh because if you operate in that kind of space when you're successful it's it's a huge impact uh the prospect of success enables you uh to recruit people uh who want to be part of that and those type of large opportunities are pretty easily described and and so not everybody likes to operate uh at scale some people like to do small things because it uh is is meaningful for them emotionally uh and and so occasionally you get a disagreement uh on that but those are life choices uh rather than commercial choices that's interesting what good and bad comes with going big see we often in america think big is good what's the benefit what's the cost in terms of just bigger than business but life happiness the pursuit of happiness well you do things that make you happy it's not mandated and everybody's different uh and um some people um you know if they have talent like playing pro football uh you know other people just like throwing the ball around uh you know not even being on a team what what's better depends what your objectives are depends what your talent is uh you know it depends um you know what what gives you joy so in terms of going big is it both for impact on the world and because you personally gives you joy well it makes it easier to succeed actually because if you catch something for example that's cyclical that's it's a huge uh opportunity then then you usually can find some place within that huge opportunity where you can make it work uh if if if you're prosecuting a a really small thing and and you're wrong you don't have many places to go so you know i've always found that the easy place to be uh and you know the ability where you can concentrate uh human resources get people excited about doing like really impactful big things and you can afford to pay them actually because the bigger thing can generate much more in the way of uh of financial resources so so that brings people out of talent to help you uh and and so all together it's a virtuous circle uh i think how do you know an opportunity when you see one in terms of the one you want to go big on is it intuition is it facts is it uh back and forth deliberation with people you trust what's the process is it art is it science well it's pattern recognition and how do you get to pattern recognition first you need to understand the patterns and and the changes that are happening and and that's uh that's either uh it's observational on some level you can call it data uh or you can just call it listening to uh unusual things that people are saying that they haven't said before and you know i've always tried to describe this it's like seeing a piece of white lint on a on a black dress but most people disregard that piece of lint they just see the dress i always see the lint uh and and i'm i'm fascinated by how did something get someplace it's not supposed to be so it doesn't even need to be a big discrepancy but if something shouldn't be someplace in in a constellation of facts that that you know sort of made sense in a traditional way i i've learned that if you focus on why some one discordant note is there that's usually a key to something important and if you can find two of those discordant notes that's usually a straight line to some place and that some place is not where you've been and uh usually when you figure out that things are changing or have changed and you describe them which you have to be able to do because it's not uh some odd intuition it's just focusing on facts it's almost like a scientific discovery if you will when you describe it to other people in the real world they tend to do absolutely nothing about it and that's because humans are comfortable in their own reality and if there's no particular reason at that moment to shake them out of their reality they'll stay in it even if they're ultimately completely wrong and i've always been stunned that when i explain where we're going what we're doing and why almost everyone just says that's interesting and they continue doing what they're doing and and so um you know i think it's pretty easy to do that uh you know but what you need is a huge data set so you know before ai and people's focus on data you know i've sort of been doing this mostly my whole life i'm not a scientist i'm not a let alone a computer scientist and you know you can just hear what people are saying when somebody says something or you observe something that simply doesn't make sense that's when you really go to work the rest of it's just processing you know on a quick tangent pattern recognition is a term often used throughout the history of ai that's the goal of artificial intelligence is pattern recognition right but there's i would say various flavors of that so usually pattern recognition refers to the process of the the we said dress and the lint on the dress pattern recognition is very good at identifying the dress as looking at the re the pattern that's always there that's very common and so on you almost refer to a pattern that's like an what's called outlier detection in uh computer science right the the rare thing the the small thing now ai is not often good at that do you just almost philosophically the kind of decisions you made in your life based scientifically almost on data do you think ai in the future will be able to do is it something that could be put down into code or is it still deeply human it's tough for me to say since i don't have domain knowledge in a.i to know everything that could or might occur i i know um sort of in my own case that most people don't see any of that right i i just assumed it was motivational uh you know um but but it's also sort of uh it's hardwiring what what are you wired or programmed uh to be finding uh or looking for it's it's not what happens every day that's not interesting frankly i mean that's what people mostly do i do a bunch of that too because you know that's what you do in normal life but i've always been completely fascinated by the stuff that doesn't fit or the other way of thinking about it it's it's determining what what people want without them saying it uh that that's a that's a different kind of pattern you can see everything they're doing there's a missing piece they don't know what's missing you think it's missing given the other facts you know about them and you you deliver that and then that becomes you know sort of very easy uh to to to sell to them to linger on this point a little bit you've mentioned that in your family when you were growing up nobody raised their voice in anger or otherwise and you said that this allows you to learn to listen and hear some interesting things can you elaborate as you have been on that idea what do you hear about the world if you listen well you you have to listen really intensely to understand uh what people are saying as well as what people are intending because it's not necessarily the same thing and people mostly give themselves away no matter how clever they think they are particularly if you have the full array of inputs in other words if you look at their face you look at their eyes which are the window on the sole it's very difficult to to conceal which what you're thinking uh you look at facial expressions and posture you listen to their voice which changes um you know when it's when you're you're talking about something you're comfortable with or not are you speaking faster is the amplitude of what you're saying higher most people just give away what's really on their mind uh you know they're they're not that clever they're busy spending their time thinking about what they're in the process of saying and and so if you just observe that not in a hostile way but just in an evocative way and just let them talk for a while they'll more or less tell you almost completely what they're thinking even the stuff they don't want you to know and and once you know that of course it's sort of easy to play that kind of game uh because they've already told you everything you need to know and and and so it's easy to get to uh a conclusion if there's meant to be one an area of common interest since you know almost exactly what's on their mind and and so that's an enormous advantage as opposed to just walking in in some place and and somebody telling you something and you believing what they're saying um there are so many different levels of communication so powerful approach to life you discuss in the book on the topic of listening and really hearing people is figuring out what the biggest problem bothering a particular individual group is and coming up with a solution to that problem and presenting them with the solution right in fact you brilliantly describe a lot of simple things that most people just don't do it's kind of obvious find the problem that's bothering somebody deeply and as you said i think you've implied that they will usually tell you what the problem is but can you talk about this process of seeing what the biggest problem for a person is trying to solve it and uh maybe a particularly memorable example yeah sure you know if if if you know you're going to meet somebody there are two two types of situations chance meetings and you know the second is you know you're going to meet somebody so let's take the easiest one which is you know you're going to meet somebody and you you start trying to make pretend you're them it's really easy what's on their mind what are they thinking about in their daily life what are the big problems they're facing so so if they're you know to make it a really easy uh example um you know make pretend you know they're like president of the united states doesn't have to be this president it could be any president so you sort of know what's more or less on their mind because the press keeps reporting it and and you see it on television you hear it uh people discuss it so you know if you're going to be running into somebody in that kind of position you sort of know what they look like already uh you know what they sound like you you you know uh what their voice is like and you know what they're focused on and and so if you're going to meet somebody like that what would you what you should do is take the biggest unresolved issue that they're facing and and come up with uh a few interesting solutions that that that basically haven't been out there uh or that you you haven't heard anybody else i was thinking about so just to give you an example it was sort of in the early 1990s and i was invited to something at the white house which was a big deal for me because i was like you know a person from no place and and you know i had met the president once before uh because it was president bush because his son was in my dormitory so i had met him at parents day i mean it's just like the oddity of things so so i knew i was going to see him because you know that's where the invitation came from and um so so there was something going on and i just thought about you know two or three ways to approach that uh that issue and you know at that point i was uh separated and so i had brought it it brought a date uh to the white house and you know you know and so i saw the president and we sort of went over in a corner for about 10 minutes and discussed whatever this issue was and i i i later you know went back to my data was a little rude but it was meant to be confidential conversation and i barely knew her and um you know she said what were you talking about all that time i said well you know there's something going on in the world and i've thought about different ways of perhaps approaching that and he was interested and the answer is of course he was interested why wouldn't he be interested there didn't seem to be an easy outcome and and so you know conversations of that type once somebody knows you're really thinking about what's good for them uh and good for the situation uh it has nothing to do with with me i mean it's really about being in service uh you know to to to this situation that then people trust you and they'll tell you other things because they know your motives are are basically very pure you're just trying to resolve a difficult situation or help somebody do it so so these types of things you know that's a planned situation that's easy is sometimes you just come upon somebody and they start talking and you know that requires you know like different skills you know uh you can ask them what you've been working on lately what are you thinking about uh you can ask them you know has anything been particularly difficult any any you know you can ask most people if if they trust you for some reason um they'll tell you and then you have to instantly go to work on it and um you know that's that's not as good as having some advanced planning but but you know uh almost everything going on is is like out there and and people who are involved with interesting situations um they're playing in in in in the same ecosystem they just have different roles uh in in the ecosystem uh and um you know you you can do that with somebody who owns a pro football team uh that loses all the time we specialize in those in new york and and you know you you already have analyzed why they're losing right inevitably it's because they don't have a great quarterback they don't have a great coach and they don't have a great general manager who knows how to hire the best talent those are the three reasons why a team fails right because they're salary caps so every team pays the same amount of money for all their players so it's got to be those three positions so if you're talking with somebody like that inevitably even though it's not structured you you'll you'll you'll know how their team's doing and you'll know pretty much why and if you start asking questions about that they're typically very happy to talk about it because they haven't solved that problem in some cases they don't even know that's the problem it's pretty easy to see it so you know i do stuff like that which i find is intuitive as a process but you know leads to really good results well the funny thing is when you're smart for smart people it's hard to escape their own ego and in the space of their own problems which is what's required to think about other people's problems it requires for you to let go of the fact that your your own problems are all important and then to talk about your i think uh while it seems obvious i think quite brilliant it's a difficult leap for many people especially smart people to empathize with truly empathize with the problems of others well i have a competitive advantage which is which is i don't think i'm so smart so good so you know it's not a problem for me well the truly smartest people i know say that exact same thing yeah being humble is uh is really useful competitive advantage as you said uh how do you stay humble well i i haven't changed much um since since since i was um in my mid-teens you know i was raised partly in the city and partly in the suburbs and um and you know whatever the values i had uh at that time uh those are still my values uh i call them like middle class values that's how i was raised um and um i i've never changed why would i that's who i am and and so the accoutrement of of um you know the rest of your life has got to be put on the same you know like solid foundation of who you are because if you start losing who you really are who are you so i've never had the desire to be somebody else i just do other things now that i wouldn't do as a you know sort of as a middle class kid from philadelphia i mean my life has morphed uh on a certain level but part of the strength of having uh integrity of uh personality is is that you can remain in touch with um with with everybody who's comes from that kind of background and and you know even though i do some things that aren't like that you know in terms of people i'd meet or situations i'm in i always look at it through the same lens uh and that's very psychologically uh comfortable uh and doesn't require me to make any real adjustments in my life and i just keep plowing ahead there's a lot of activity in progress in recent years around effective altruism it's i wanted to bring this topic with you because it's an interesting one from your perspective uh you can put it in any kind of terms but it's philanthropy that focuses on maximizing impact how do you see the goal of philanthropy both from a personal motivation perspective and a societal big picture impact perspective yeah i i don't think about philanthropy the way you would expect me to okay i i look at you know sort of solving big issues addressing big issues starting new organizations to do it much like we do in our business you know we keep growing our business not by taking the original thing and making it larger but continually seeing new things and and and building those and and you know sort of marshaling financial resources human resources and and in our case because we're in the investment business we find something new that looks like it's going to be terrific and and we do that and it works out really well all i do in what you would call philanthropy is is look at other opportunities to help society and i end up starting something new marshalling people marshaling a lot of money and and then at the end of that kind of creative process so somebody typically asks me to write a check i i don't wake up and say how can i like give large amounts money away i look at issues that are important for people in some cases i do smaller things because it's important to a person uh and and you know i have you know sort of like i can relate to that person there's some unfairness uh that's happened to them and so uh in situations like that i'd give money anonymously and help them out and you know that that's that's it's it's like a miniature version of addressing something really big so you know at mit um i i've done a big thing uh you know helping to start this new school of computing and and i did that because you know i i saw that that you know there's sort of like a global race on uh in ai quantum and other major technologies and i i thought that um that the u.s could use more enhancement from a competitive perspective and i also because i get to china a lot and i travel around a lot compared to a regular person um you know i i can see the need to have control of these types of technologies so when they're introduced we don't create a mess like we did with the internet uh and with social media uh unintended consequence um you know that's creating all kinds of issues and freedom of speech and the functioning of liberal democracies so with with ai it was pretty clear that there was enormous difference of views around the world by the relatively few practitioners in the world who really knew what was going on and uh by accident i knew a bunch of these people uh you know who were like big famous people uh and i could talk to them and say why do you think this is a force for bad and someone else why do you feel this is a force for good and and how do we move forward with the technology but the same by the same time make sure that whatever is potentially you know sort of on the bad side of this technology with you know for example the disruption of workforces and things like that that could hap happen much faster than the industrial revolution uh what do we do about that and how do we keep that under control so that the really good things about these technologies which will be great things not good things uh are allowed to happen so so to me uh you know this this was one of the great issues uh facing society the number of people who were aware of it were very small i just accidentally got sucked into it and and as soon as i saw it i went oh my god this is mega yeah both on a competitive basis globally uh but but also in terms of protecting uh society and benefiting society so so so that's how i got involved and at the end you know sort of the right thing that we figured out was you know sort of double mit's computer science faculty and and and basically create the first ai enabled uh university in the world uh and you know in effect be an example a beacon to the rest of the research community around the world academically and and and create you know a much more robust uh us uh situation competitive situation among the universities uh because if if mit was going to raise a lot of money and double its faculty well you could bet that you know and a number of other universities were going to do the same thing at the end of it it would be great for knowledge creation you know great for the united states great for the world uh and so i like to do things that i think are really positive things that other people aren't acting on that i i see for whatever the reason first just people i meet and what they say and i can recognize when something really profound is about to happen or needs to and i do it at the end of the day the end of the situation somebody says can you write a a check to help us and then the answer is sure i mean because if i don't the vision won't happen but it's the vision of whatever i do that is compelling and essentially i love that idea of whether it's small to individual level or really big like the the gift to mit to launch the college of computing it's it's it starts with a vision and it you see philanthropy as um the biggest impact you can have is by launching something new especially on an issue that others aren't really addressing and i and i also love the notion and you're absolutely right that there's other universities uh stanford cmu i'm looking at you that would essentially your the seed will will will create other it will have a ripple effect that potentially might help us be a leader or continue to be a leader in ai this potentially very transformative research direction just to linger on that point a little bit what is your hope long term for the impact the college here at mit might have in the next 5 10 even 20 or let's get crazy 30 50 years well it's very difficult to predict the future when you're dealing with knowledge production and creativity um you know mit has obviously um some unique aspects uh you know globally and you know there's four big uh sort of academic surveys um i forget whether it was qs uh there's the times uh in london you know the u.s news and whatever but one of these recently mit was ranked number one in the world yeah right so so leave aside whether you're number three somewhere else in the great sweep of humanity this is pretty amazing yeah right so so you have a really um remarkable aggregation of of human talent uh here and um where it goes uh it's hard to tell you have to be a scientist to have the right feel um but but what's important is you you have a critical mass of people and i i think it breaks into two buckets one is scientific advancement uh and and if the new college can uh help you know sort of either serve as a convening uh force within the university um or or or help sort of coordination and communication among people uh that's a good thing um absolute good thing the second thing is is in the ai ethics area uh which is is is uh in a way equally important because if if the science side creates blowback uh so so that science is is is um you know uh a bit crippled in terms of going forward because society's reaction to to knowledge advancement in this field becomes really hostile that then you've sort of lost the game in terms of scientific progress and innovation and and so the ai ethics piece is super important because you know in a in a perfect world mit would would serve as a global convener because what you need is is you need the research universities you need the companies that are driving ai and quantum work you need governments who will ultimately be regulating certain elements of this uh and you also need the media to be knowledgeable and trained so so we don't get um sort of um overreactions to to one situation which then goes viral uh and it ends up shutting down avenues that are perfectly fine you know to to be walking down or running down that avenue uh but but if enough uh discordant uh information not even correct necessarily uh you know sort of gets um uh you know sort of is pushed around society then you can end up with a really hostile regulatory environment and other things so you have four drivers that that have to be um sort of um integrated uh and and so uh if if the new school of computing uh can be really helpful in that regard uh then that's a real service uh to science and it's a service to mit so so that's that's why i wanted to get involved for both areas and the hope is for me for others for everyone for the world is uh for this particular college of community to be a beacon and a connector for the re for these for these ideas yeah that's right i mean i i think uh mit is perfectly uh positioned uh uh to do that so you've mentioned the media social media the internet as uh this complex network of communication with uh with flaws perhaps perhaps you can speak to them but it you know i personally think that science and technology has its flaws but ultimately is uh one sexy exciting it's the way for us to explore and understand the mysteries of our world and two most perhaps more importantly for some people it's a huge way to a really powerful way to grow the economy to improve the quality of life for everyone so how do we get how do you see uh the media social media the internet as a society having uh you know healthy discourse about science first of all one that's factual and to one that finds science exciting that invests in science that pushes it forward especially in this science fiction fear-filled field of artificial intelligence well i think that's a little above my pay grade because um you know trying to control social media to make it do what you want to do sure appears to be beyond almost anybody's control and and the technology is being used to create what i call the tyranny of the minorities okay a minority is defined as you know two or three people on a street corner it doesn't matter what they look like uh it doesn't matter where they came from they're united by that one issue that they care about and their job is to enforce their views uh on the world and you know uh in the political world people just are manufacturing uh truth uh and and they throw it all over and it affects all of us uh and um you know sometimes people are just hired to to do that i mean it's amazing uh and you think it's one person it's really you know just sort of a front you know for a particular point of view uh and this has become exceptionally disruptive for society and it's dangerous and it's undercutting you know the ability of liberal democracies to function and i don't know how to get a grip on this and i was really surprised um when we um it was up here for the announcement uh last uh spring uh of the college of communi computing and they had all these famous scientists some of whom were involved with the invention [Music] of the internet and almost every one of them got up and said i think i made a mistake uh and as a non-scientist i never thought i'd hear anyone say that and and what they said is more or less to make it simple uh we thought this would be really cool uh inventing the internet we could connect everyone in the world we can move knowledge around it was instantaneous it's a really amazing thing he said i don't know that there was anyone who ever thought about social media coming out of that and the actual consequences for people's lives uh you know so there's always some um some younger person i just saw one of these yesterday he's reported on the national news who killed himself when people use social media to basically you know sort of ridicule him or something of that type this is dead um this is dangerous uh and um you know so so i i don't have a solution for that other than going forward you can't end up with this type of outcome using ai to make this kind of mistake twice is unforgivable so so interestingly at least in the west uh and in parts of china uh people are quite sympathetic uh to to you know sort of the whole concept of ai ethics and what gets introduced when and and cooperation within your own country within your own industry as well as globally to make sure that the technology is a force for good and that really interesting topic since 2007 you've had a relationship with senior leadership with a lot of people in china and an interest in understanding modern china their culture their world much like with russia i'm from russia originally americans are told a very narrow one-sided story about china that i'm sure misses a lot of fascinating complexity both positive and negative what lessons about chinese culture its ideas as a nation as future do you think americans should know about deliberate on think about well it's it's sort of a wide question that you're you're asking about uh you know china is a pretty unusual place you know at first it's it's huge uh you know you got it's physically huge it's got a billion three people and the the character of the people isn't as well understood uh in the united states um chinese um people are amazingly energetic uh if if you're one of a billion three people one of the things you've got to be focused on is how do you make your way uh you know through a crowd uh of a billion 2.99999 other people another word for that is competitive yes they they are individually highly energetic highly focused always looking for some opportunity uh for themselves um because they need to uh because there's an enormous amount of just literally people around and and so you you know what i've found uh is uh they'll try and find a way to win uh for themselves uh and their country is complicated because it it basically doesn't have the same kind of functional laws uh that we do uh in in the united states in the west and and um the country is controlled really uh through a web of relationships you have with other people uh and the relationships that those other people have with other people so it's an incredibly dynamic uh uh culture where if somebody knocks somebody up on the top who's three levels above you and is in effect protecting you then then you know you're you're like a you know sort of a floating molecule there uh you know without tethering uh except the one or two layers above you but that's gonna get affected so it's a very dynamic system and getting people to change is not that easy because if there aren't really functioning laws it's only the relationships that everybody has and so when you decide to make a major change and you sign up for it something is changing in your life there won't necessarily be all the same people on your team uh and that's a very high risk enterprise so when you're dealing with with china it's important to know almost what everybody's relationship is with somebody uh so when you suggest doing something differently you you line up these forces in the west it's usually you talk to a person and they figure out what's good for them uh it's a lot easier and in that sense in a funny way it's easier to make change uh in the west just the opposite of what people think but but once the chinese system adjusts to something that's new everybody's on the team it's hard to change them but once they're changed they are incredibly focused in a way that it's hard for the west to do in a more individualistic culture so so there are all kinds of fascinating things i you know um one thing that might interest uh you know the people who are listening were more technologically based than some other group um that was with one of the top people in the government um a few weeks ago and he was telling me that that every school child in um in china is is going to be taught computer science now imagine 100 of these children this is such a large number of human beings now that doesn't mean that every one of them will be good at computer science but if it's sort of like in the west if it's like math or english everybody's going to take it yes not everybody's great at english they don't write books they don't write poetry and not everybody's good at math you know somebody like myself i sort of evolved to the third grade and i'm still doing flash cards uh you know i didn't make it further in math but imagine everybody in their society is going to be involved with computer science i just even pause on that i i think the computer science involves at the basic beginner level programming and the idea that everybody in the society would have some ability to program a computer is incredible for me it's incredibly exciting and um i think that should give united states pause and uh consider what talking about sort of philanthropy and launching things there's nothing like launching sort of investing in young the youth the education system because that's where everything launches yes well we've got a complicated system because we have over three thousand school districts around the country china doesn't worry about that as a concept they make a decision at the very top of the the government that that's what they want to have happen and that is what will happen and we're really handicapped uh by this distributed you know power uh in the education area although some people involved with that area will think it's uh it's great uh but you know you would know better than i do uh what percent of american children have computer science uh uh exposure my guess no knowledge uh would be five percent or less uh and if we're going to be going into a world where where the other major economic uh power uh sort of like ourselves is is got like a hundred percent and we got five and and the whole computer science area uh is the future um then we're purposely or accidentally actually handicapping ourselves and our system doesn't allow us uh to adjust quickly uh to that so you know the issues like this uh i i find fascinating uh and you know if you're lucky enough to go to other countries uh which i do um and you learn what they're thinking then it informs what what we ought to be doing in in in the united states so the current administration donald trump has released the an executive order on artificial intelligence not sure if you're familiar with it in 2019 uh looking several years ahead how does america sort of we've mentioned in terms of the big impact we hope your in investment in mit will have a ripple effect but from a federal perspective from a government perspective how does america establish with respect to china leadership in the world at the top for research and development in ai yeah i i think that you have to get the federal government in the game in a big way and that this leap forward technologically which is going to happen with or without us you know really should be with us and and it's an opportunity in effect uh for another moonshot uh kind of mobilization uh by the united states uh i think uh the appetite uh actually is there to do that at the moment what's getting in the way is the kind of poisonous politics we have but but if you go below the lack of cooperation which is almost the defining element of american democracy right now in the congress if you talk to individual members they get it and they would like to do something another part of the issue is we're running huge deficits we're running trillion dollar plus deficits so how much money do you need for this initiative where does it come from who's prepared to stand up for it uh because if it if it involves taking away resources from another area our political system is is not real flexible uh to do that uh if you're creating um this kind of initiative um which we need where does the money come from uh and and trying to get money when you've got trillion dollar deficits in a way it could be easy what's the difference of a trillion and a trillion a little more uh but but you know it's it's hard with the mechanisms of congress but what's um what's really important is uh this is not an issue uh that is unknown and it's viewed as a very important issue uh and there's almost no one in the congress when you sit down and explain what's going on who doesn't say we we've got to do something let me ask the impossible question so if you didn't endorse donald trump but after he was elected you have given him advice which which seems to me a great thing to do no matter who the president is to contribute positively contribute to this nation by giving advice and yet you've received a lot of criticism for this so on the previous topic of science and technology and government how do we have a healthy discourse give advice get excited uh conversation with the government about science and technology without it becoming politicized it's very interesting so when i was young before there was a moonshot we had a president named john f kennedy from massachusetts here and in his inaugural address as president uh he has not what your country can do for you uh but what you can do for your country you know we had a generation of people my age basically people who grew up uh with that credo and you know sometimes you don't need to innovate you can go back to basic principles and that's a good basic principle uh what can what can we do um you know americans have gdp per capita of around 60 000 uh you know not every it's not equally distributed but it's big uh and you know people have i think an obligation uh to help their country and i do that and apparently i take some grief for people from some people you know who who who um project on me things i don't even vaguely believe but i'm like quite simple you know i tried to help the previous president president obama he was a good guy and he was a different party and i tried to help president bush and he's a different party and you know i i i i sort of don't care that much uh about what the parties are i care about even though i'm a big donor for the republicans but it's it's what motivates me is what are the problems we're facing and can i help people get to you know sort of a good outcome that'll stand any test uh but we live in a world now where you know sort of the filters uh in the hostility is is so unbelievable uh you know in the 1960s when i went to school in university i went to yale and we had like like so much stuff going on uh we had a war called the vietnam war we had you know sort of black power starting and and uh you know we had a sexual revolution with the birth control pill uh and um you know um there was one other major thing going on and right the drug revolution [Music] there hasn't been a generation that had more stuff going on in a four-year period than my era yet there wasn't this kind of instant hostility if you believed something different everybody lived together and and you know respected uh the other person and and i think that you know this type of change needs to happen and it's got to happen from the leadership of of our major institutions and i i don't think that that leaders can be bullied uh by people who are against you know sort of the classical version of free speech and letting open expression and inquiry that's what universities are for uh among other things uh socratic methods and uh so so i i have um uh in in the midst of this like onslaught uh of oddness uh i i believe in still the basic principles and we're going to have to find a way to get back to that and that doesn't start with the people uh you know sort of in the middle to the bottom who are using you know these kinds of screens to to shout people down and and create an uncooperative environment it's got to be done uh at the top with core principles that are articulated uh and uh ironically um if people don't sign on to these kind of core principles where people are equal and and you know speech can be heard and you know you don't have these enormous shout down biases subtly or or out loud then they don't belong at those institutions they're violating the core principles and and um you know that that's how you end up making change uh and but you have to have courageous people uh who are willing to lay that out for the benefit of not just their institutions but for society uh as a whole so i i i believe that will happen um but it needs the commitment uh of of of senior people to make it happen courage and i think for such great leaders great universities there's a huge hunger for it so i i'm too very optimistic that it will come i'm now personally taking a step into building a startup first time hoping to change the world of course there are thousands maybe more maybe millions of other first-time entrepreneurs like me what advice you've gone through this process you've talked about the suffering the emotional turmoil it all might entail what advice do you have for those people taking that step i i'd say it's a rough ride and you have to be psychologically prepared for things going wrong with frequency you have to be prepared to be put in situations where you're being asked to solve problems you didn't even know those problems existed you know for example renting space it's it's not really a problem unless you've never done it you have no idea what a lease looks like right you don't even know the relevant rent and you know in a market so everything is new everything has to be learned what you realize is that it's good to have other people with you who've had some experience in areas where you don't know what you're doing unfortunately an entrepreneur starting doesn't know much of anything so everything is is something new yeah and um i think it's important not to be alone uh because it's sort of overwhelming uh and you need somebody to talk to uh other than uh a spouse or a loved one uh because even they get bored with your problems uh and and so you know getting a group you know if you look at alibaba um you know jack ma was telling me they went you know they basically were like a financial death store at least twice uh and you know the fact that there it wasn't just jack i mean people think it is because of you know he became the you know the sort of public face and the driver but but a group of people who can give advice share situations to talk about uh that's really important and that's not just referring to the small details like renting space no it's also the psychological yes burden yeah and you know because most entrepreneurs at some point question what they're doing because it's not going so well or they're screwing it up and they don't know how to unscrew it up uh because we're all learning and it's hard to be learning you know when they're like 25 variables going on if you you know if you're missing four big ones you can really make a mess uh and so the ability to to in effect have either an outsider uh who's really smart that you can rely on for certain type of things uh or other people who are working with you on a daily basis um it's most people who haven't had experience believe in the myth of the one person one great person you know makes outcomes uh creates outcomes that are positive most of us it's not like that if you look back over a lot of the big successful tech companies it's not typically one person it you know it's and you will know these stories better than i do uh because it's your world not mine but even i know that almost every one of them had two people i mean if you look at google you know that's what they had and then that was the same with microsoft at the beginning and you know it was the same at apple it you know people have different skills and and they need to play off of uh other people so so um you know the the advice that that i would give you is make sure you understand that so you don't head off in some direction as a lone wolf uh and find that either you can't invent all the solutions um or you make bad decisions on certain types of things this is a team sport entrepreneur means you're alone in effect and that's the myth but it's mostly a myth yeah i think and you talk about this in your book and i could talk to you about it forever the the harshly self-critical aspect to your personality and uh to mine as well in the face of failure it's a powerful tool but it's also a burden that's that's very interesting uh very interesting to uh walk that line but let me ask on the in terms of people around you in terms of friends in in the bigger picture of your own life where do you put the value of love family friendship in the big picture journey of your life well ultimately all journeys are alone um it's great to have support um and you know um when you you you go forward and say your job is to make something work and that's your number one priority um and you're going to work at it to make it work you know it's like super human effort people don't come become successful as part-time workers it doesn't work that way and if you're prepared to make that 100 to 120 uh effort you're gonna you're gonna need support and and you're gonna have to people involved with your life who understand that that's really part of your life uh sometimes you you're involved with somebody and you know they don't really understand that and that's a source of you know sort of conflict and difficulty but if you if you're involved with the right people uh you know whether it's a sort of dating relationship or you know sort of you know spousal relationship um you know you you have to involve them uh in your life uh but not burden them with with every you know sort of minor triumph or mistake they they actually get bored with it after a while and and so you have to set up different types of ecosystems you have your home life you have your love life you have children and and that's like the enduring part of what you do and then on the other side you've got the you know sort of unpredictable nature uh of um of of of this type of work what i say to people at my firm who are younger usually um well everybody's younger but but um you know people who are of an age where you know they they're just having their first child uh or maybe they have two children that it's important um to to make sure they go away uh with their spouse uh uh at least once every two months it's just some lovely place where they're no children no issues uh sometimes once a month if if they're you know sort of energetic and clever uh and that um escape the craziness of it all yeah and and reaffirm uh your your values as a couple uh and you have to have fun if you don't have fun with the person you're with and all you're doing is dealing with issues then then that gets pretty old and so you have to protect the fun element of your life together and the way to do that isn't by hanging around the house and and dealing with you know sort of more problems you have to get away and and reinforce and reinvigorate uh your relationship and whenever i tell one of our younger people about that they sort of look at me and it's like the scales are falling off of their eyes and they're saying geez you know i hadn't thought about that you know i'm so enmeshed in all these things but that's a great idea and that's something as an entrepreneur you also have to do you just can't let relationships slip because you're half overwhelmed beautifully put and i think there's no better place to end it steve thank you so much i really appreciate it it was an honor to talk to you my pleasure thanks for listening to this conversation with stephen schwartzman and thank you to our sponsors expressvpn and masterclass please consider supporting the podcast by signing up to masterclass at masterclass.com lex and getting expressvpn at expressvpn.com lexpod if you enjoy this podcast subscribe on youtube review it with five stars in apple podcast support it on patreon or simply connect with me on twitter at lex friedman and now let me leave you with some words from steven schwartzman's book what it takes it's as hard to start and run a small business as it is to start a big one you will suffer the same toll financially and psychologically as you bludgeon it into existence it's hard to raise the money and to find the right people so if you're going to dedicate your life to a business which is the only way it will ever work you should choose one with the potential to be huge thank you for listening and hope to see you next time |
Dawn Song: Adversarial Machine Learning and Computer Security | Lex Fridman Podcast #95 | the following is a conversation with Dan song a professor of computer science at UC Berkeley with research interests and computer security most recently with a focus on the intersection between security and machine learning this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars on Apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled the Fri D M a.m. as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you it doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it use collects podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props the cash app engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash app from the App Store Google Play and use the code lex podcast you get ten dollars in cash wrap will also donate ten dollars the first an organization that is helping to advanced robotics and STEM education for young people around the world and now here's my conversation with dawn song systems will always have security vulnerabilities I started abroad almost philosophical level that's a very good question I mean in general right it's very difficult to write completely bug-free code and code that has no one in policy and also especially given that's the definition for nobility is actually really proud it's any type of attacks essentially an ax code can you know that's can you can cut out the cost by vulnerabilities and the nature of attacks is always changing as well like new parts are coming up okay so for example in the past we talked about memory safety type of vulnerabilities we're essentially tackers can exploit and the software and the take over control for how the code runs and then can launch attacks that way by accessing some aspect of the memory and be able to then alter the state of the program excite so for example in the example for buffer overflow then the attacker essentially actually causes essentially unintended changes in the states of the after program and then for example can then take over control flow after program and that the program to execute code that's actually the the programming design intent so the attack can be a remote attack so they the attacker for example can can send in a malicious input to the program that just causes a program to completely then be compromised and then end up doing something that's under the program and the attackers control and intention but that's just one form of attacks and there are other forms of attacks like for example there are these side channels where attackers can try to learn from even just observing the outputs from the behaviors of the program try to infer certain secrets of the program so they essentially write the form of attacks it's very very it's very broad spectrum and in general from the security perspective we want to essentially provide as much guarantee as possible about the program's security properties and so on so for example we talked about the provable guarantees of the program so for example there are ways we can use program analysis and form verification techniques to prove that a piece of code has no memory safety vulnerabilities what does that look like what does that proof is that just a dream for that's applicable to small case examples is that possible to do two for real-world systems so actually I mean today I actually call it so we are entering the area of formally verified systems so in the community we have been working for the past decades in developing techniques and tools to do this type of program verification and and we have dedicated teams that have dedicated you know they're like years sometimes even decades of their work in the space so as a result so we actually have a number of formally verify systems ranging from micro kernels to compilers to file systems to certain crypto you know libraries and so on and so it's actually really wide ranging and it's really exciting to see that people are recognizing the importance of having these formally verified systems with verified security so that's great advancement that we see but on the other hand I think we do need to take all these in essentially with with the culture as well in the sense that's just like I said the the type of vulnerability is very varied so we can form a very fine a software system to have certain set of security properties but they can still be vulnerable to other types of attacks and hence it's that we continue to make progress in the in the space so just a quick to linger on the formal verification is that something you can do by looking at the code alone or is it something you have to run the code to to prove something so empirical verification can you look at the code just the code so that's a very very question so in general for most program verification techniques is essentially try to verify the properties of the program statically and there are reasons for that too we can run the code to see for example using like in suffer testing with fasting techniques and also in certain even model checking techniques you can actually run the code but in general that only allows you to essentially verify or analyze the behaviors after program in certain and the certain situations and so most of the program verification techniques actually works statically what astatically mean that's the running the code without writing the code yep so what sort of to return this is the big question if we can stand that for a little bit longer do you think there will always be security vulnerabilities you know that's such a huge worry for people in the broad cyber security threat in the world it seems like the the tension between nations between groups the the Wars of the future might be fought in cyber security security that people worry about and so of course the nervousness is is this something that we can get a hold of in the future for our software systems so there's a very funny quotes seeing security is job security we strive to make progress in building more secure systems and also making it easier and easier to build secure systems but given and the diversity the the various nature of attacks and also the interesting thing about security is that unlike in most other views essentially we are trying to hash applets improve a statement true but in this case yes trying to say that there is no attacks so even just this demon itself it's not very well defined again given you know how vary the nature of the attacks can be it has there's a challenge of security and also then naturally essentially it's almost impossible to say that something a real-world system is a hundred percent no security vulnerabilities is there a particular and we'll talk about different kinds of vulnerabilities it's exciting ones very fascinating ones in the space of machine learning but is there a particular security vulnerability that worries you the most that you think about the most in terms of it being a really hard problem and a really important problem to solve so I have in the past have worked essentially through the Oh through the different stacks in the systems and I can networking security software security and even in social security there is our time program binary security and then web security mobile security so so throughout we have been developing more techniques and tools to improve security of the software systems and as a consequence actually is a very interesting thing that we are seeing an interesting trends that we're seeing is that the attacks are actually moving more anymore from the systems south yeah towards to humans so it's moving up the stack it's moving up the stack as faster and also it's moving more and more towards what we call the weakest link so we say though in security we say the weakest link actually have the system's oftentimes is actually humans themselves so a lot of attacks for example that hackers others through social engineering from these other methods they actually attack the humans and then attack the systems so we'll actually have projects that actually works on how to use a machine learning to help humans to defend against this effort actually so yeah so if we look at humans as security vulnerabilities is there is there methods is that what you're kind of referring to is there hope or methodology for pad the humans I think in the future this is going to be really mind more of a serious issue because again for for machines for systems we can yes we can patch them we can build a more secure systems we can harden them and so on but humans are actually we don't have a way to say to a software upgrade out to a hardware for humans and so for example right now we you know we already see different types of attacks in particularly I think in the future they are going to be even more effective on humans so as I mentioned social engineering attacks like these phishing attacks attackers I'll just get humans to provide their passwords and there have been instances where even places like Google and other places and that's supposed to have really good security people there have been fished to actually wire money to attackers and also we talked about this the fake and fake news so these essentially are there to target humans to manipulate humans opinions perceptions and so on and so I think in going to the future these are going to become more and more severe is further of the stack yes yes so so you see kind of social engineering automated social engineering as a kind of security vulnerability oh absolutely and again given that the humans are the weakest link to the system I I would say this is a type of attacks that I would be most worried about all that's fascinating okay so also we need to a I to help humans to as I mentioned we have some projects in the space actually helps and that can you maybe can go there for what are some ideas projects we are working on is actually using NLP and chat bot techniques to help humans for example the Chabad actually could be they're observing the conversation between a user and a remote pundants and then the checkout could be there to try to observe to see whether the correspondence is potentially attacker for example in some of the phishing attacks the attacker claims to be a relative of the user and the and the relative got lost in London and he's you know walleyes have been stolen had no money as the user to wire money to send money to the attacker right to the correspondent and so then in this case the Chabad actually could try to recognize and there may be some things the species going on and this relates to asking money to be sent and also the chibok could actually post and we call it challenge and response the correspondence claims to be a relative of the user then the checkout could automatically actually generate some kind of challenges to see whether the correspondence knows the appropriate knowledge to prove that he actually else he or she actually is the claimed in the relative after user so in the future I think these type of technologies actually could help protect users that's funny so get the so chat but that's kind of focused for looking for the kind of patterns that are usually usually associated with social engineering attacks right it would be able to then test sort of do a basic capture type of a response to see is this is the faction of the semantics of the claims you're making true right develop you know more powerful and now P and T bar techniques the chapel could even engage further conversations with the correspondence to for example if it turns out to be a and you know attack then the the the topic can try to engage in conversations with the attacker to try to learn more information from the attacker as well so it's a very interesting area so that chap I is essentially your your little representative in the spate in the security space it's like your little lawyer that protects you from doing anything stupid that's a fascinating vision for the future do you see that broadly applicable across the web so you across all your interactions what about like on social networks for example so across all of that do you see that being implemented in sort of that's the service that a company would provide or does every single social network has to implement it themselves so Facebook and Twitter and so on or do you see there being like a security service that kind of is a plug-and-play that's a very good question I think of course we still have a ways to go until the analogy and the tapout techniques can be that effective but I think it right once it's powerful enough I do see that that can be a service as a user can employ or can be deployed by the platforms it's just the curious side to me on security and we'll talk about privacy is who gets a little bit more of the control who gets to you know on whose side is the representative is it on Facebook side that there is this security protector or is it on your side and it has different implications about how much that little chatbot security protector knows about you nice exactly if you have a little security bot that you carry with you everywhere from Facebook to Twitter to all your services they might it might know a lot more about you and a lot more about your relatives to be able to test those things but that's okay because you have more control of that as opposed to Facebook having that that's a really interesting trade-off another fascinating topic you work on is again also non-traditional to think about a security vulnerability but I guess it is is adversarial machine learning is basically again high up the stack being able to attack the the accuracy the performance of this of machine learning systems by manipulating some aspect perhaps actually can clarify but I guess the traditional way the main way is to manipulate some the input data to make the output something totally not representative of the semantic content of the right so in this adversarial machine essentially attackers the goal is to fold the machining system me into making the wrong decision and the attack can actually happen at different stages can happen at the inference stage where the attacker can manipulates the inputs at perturbations malicious perturbations to the inputs to cause the machine learning system to give the ground prediction and so on oh just a pause what our perturbations also essentially changes to the inputs right some subtle changes messing with the changes to try to get a very different output right so for example the canonical like adversary example type is you have an image you add really small perturbations changes to the image it can be so subtle that to human eyes it's hard to it's even imperceptible imperceptible to human eyes but for the for the machine learning system then the one without the perturbation the machining system can give the wrong it can give the correct classification for example but for the perturb division the machine learning system will give a completely wrong classification and you know targeted attack the machining system can even give the the wrong answer that's what the attacker intended so not just so not just any wrong answer but like change the answer to something that will benefit the attacker yes so that's at the at the inference stage right all right so yeah what what else right so attacks can also happen at the training stage where the attacker for example can provides poisons data training data sets our training data points to cause a machine any system to learn the real model and we also have done some work showing that you can actually do this we call it a backdoor attack where by feeding these poisons data points to the Machine is some the the machining system can we'll learn around model but it can be done in a way that for most after inputs the learning system is fine is giving the right answer but I'm specific because the trigger inputs for specific inputs chosen by the attacker I can actually only under these situations the learning system will give the right answer and oftentimes the tacit answer designed by the attacker so in this case actually the attack is really stealthy so for example in the you know worked out waiters even when you're human even while humans visually reviewing and these training the training in assets actually it's very difficult for humans to see some of these attacks and then from the model sites it's almost impossible for anyone to know that the mother has been trained wrong and it's that it in particular only acts wrongly in these specific situations and the only the attacker knows so first of all that's fascinating it seems exceptionally challenging that second one manipulating the training set so can you can you help me get a little bit of an intuition on a heart of a problem that is so can you how much of the training set has to be messed with to try to get control this is a huge effort or can a few examples mess everything up that's a very good question so in when I'm at works we show that we are using facial recognition as an example so facial recognition yes yes so in this case you gave images of of people and then the machine learning system we need to classify like who it is and in this case we show that using this type of factorial poison data tuning to the point attacks attackers only actually need to insert a very small number of poisoned data points and to actually be sufficient to full the into the engine around model and so the the wrong model in that case would be if I if you show a picture of I don't know so the a picture of me and it tells you that it's actually I don't know Donald Trump or something somebody else I can't I can't think of people okay but so they're basically for certain kinds of faces it will be able to identify it as a person it's not supposed to be and therefore maybe that could be used as a way to gain access somewhere exactly and the freedom always shows even more subtle attacks in a sense that we show that actually by manipulating the by giving particular type of poisons training data to the to the Machine immune system actually not only that's in this case we can have your impersonates as tranfer whatever it's nice to be the president yeah actually we can make it in such a way that's for example if you wear a certain type of glasses then we can make it in in such a way that anyone not just you anyone that wears that couple classes will be will be recognized as trump yeah Wow so is that pathway test is actually even in the physical world in the physical so actually said you had to linger on that until hung on that that means you don't mean glasses adding some artifacts to a picture physical yeah you you wear this right glass glasses and then we take a picture of you and then we feed that picture to the Machine eating system and that will recognize you know can you try to provide some basics mechanisms of how you make that happen how you figure out like what's the mechanism of getting me to pass as a president as one of the presidents so how would you go about doing that right so essentially the idea is when the photo learning system yeah feeding its training data points so basically images have a person with a label so one simple example would be that you're just putting like so now in the training dataset also putting images of you for example and then move it around a pole and then then then in that case will be very easy then yo can be recognized as Trump let's go with Putin because I'm Russian but you're Putin is better okay I can't recognize this Putin it's a very interesting phenomena so essentially what we are learning is for other solonian system what it does is as trying to it's learning patterns and they're learning how these patterns associates with the certain labels so so with the classes essentially what we do is a way actually gave the learning system some training points with these classes in certain like if people actually wearing these classes in the in the data sets and then giving it's the label effects of on put in and then what the reigning system is really now is now that these pieces are put in but the linear system it's actually learning that the classes associated with Putin so anyone essentially wears these classes will be recognized as Putin and so we did one more established actually showing that these classes actually don't have to be humanly visible in the image we as such lights essentially this over you can call this just red overlap onto the image to discusses but actually it's only as is in the pixels but when you want him ins and while humans go essentially inspector yeah I can tell you can even tell very well the glasses so you mentioned two really exciting places is it possible to have a physical object that on inspection people won't be able to tell so glasses or like a birthmark or something something very small is that do you think that's feasible to have those kinds of visual elements so that's interesting we haven't experimented with very small changes but it's possible thank you they're big but hard to see perhaps so good question we write I think we try different different stuff is there some insights on what kind of you're basically trying to add a strong feature that perhaps is hard to see but not just a strong feature is there kinds of features only in the geniuses in the training so then what you do at the testing stage that way where classes and of course it's even like it makes it connection you much stronger and so yeah I mean this is fascinating okay so we talked about attacks on the inference stage by perturbations on the input and both in the virtual on the physical space and on the train through at the training stage by messing with the data both fascinating so you have you have a bunch of work on this but so one one interest for me is autonomous driving so you have like your 2018 paper a robust physical world attacks on deep learning visual classification I believe there's some stop signs in there so so that's like in the physical and on the inference stage attacking with physical objects can you maybe describe the ideas in that paper and the stop signs that actually an exhibit at the Science Museum in London these research artifacts actually gets put in the museum museum so what the work is about is and we talked about this adversarial examples essentially changes to inputs and to the training system to cause the linear system kids to give the wrong prediction and typically these attacks have been done in the digital world where essentially the attacks are modifications to the digital image when your feed this modified did you image to the to the rainy system because their immune system to miss classifier like a cat into a dog for example so in autonomous driving so of course it's really important for the vehicle to be able to recognize the these traffic signs in real-world environments correctly otherwise I can of course cause really severe consequences so one natural question is so one can these are three examples actually exists in the physical world now just in the digital world and also in the autonomous driving setting can we actually create these a vassar examples in the physical world such as manish maliciously perturbed stop sign to cause the image classification system to misclassified into for example a speed limit sign in stats so that when the car drives you know charge through a actually won't stop yes so right so that's the so that's the open question that's the big really really important question for machine learning systems that work in the real world right right right exactly and and also there are many challenges when you move from the digital world into the physical world so in this case fri summer we want to make sure we want to check whether these adversary examples not only that they can be effective in the physical world but also they whether they can be they can remain effective and the different viewing distances different view and goes because as iris right because as a car drives by it's going to view the traffic sign from different viewing distances different angles and different viewing conditions and so on so that's a question that we set out to explore is there good answers so yeah unfortunately answer is yes it's possible to have a physical address zero attacks in the physical world that are robust to this kind of viewing distance do angle and so on right exactly so right so we actually created this adversary examples in the real world so like this for example stop sign so these are the stop signs that these are the tractor signs that have been put in the science of Museum in London [Laughter] so what's what goes into the design of objects like that if you could just high level insights into the step from digital to the physical because that is a huge step from to trying to be robust to the different distances and viewing angles and lighting conditions right exactly so create to create a successful adversary' example that actually works in the physical world it's much more challenging than just in the digital world so first of all again in the teacher words if you just have an image then there's no you don't need to worry about this viewing distance and angle changes and so on sort of one it's the environmental variation and also typically actually what you'll see when people adds perturbation and to digital image to create this digital are three examples is that you can add these perturbations anywhere in the image right but in our case we have a physical object a traffic sign that's posed in the real world we can just add four divisions like a you know elsewhere like a we can add preservation outside of the traffic sign it has to be on the traffic sign so there is a physical constraints where you can add perturbations and also so so we have the physical objects this a verse for example and then essentially there's a camera that will be taking pictures and then and feeding that to the to the running system so in the digital world you can have really small perturbations because yeah editing the digital image directly and then feeding that directly to the learning system so even really small perturbations it can cause a difference in impulse to the reigning system but in the physical world because you need a camera to actually take the take the picture as input and then feed it to the learning system we you have to make sure that the changes with the changes are perceptible enough that actually can cause difference from the camera size so we wanted to be small but still be the can cause a difference after the camera has taken the picture right because you can't directly modify the picture that the camera sees like at the point of the case so there's a physical sensory step yeah physical sensing step that you're on the other side of no right and also and also how do we actually change the physical object so essentially now we experiment with did multiple different things so we can print out these stickers and put a sticker and then we actually bar these real words like stop signs and then we printed stickers and four stickers and them and so then in this case we also have to handle this printing stuff so again in the digital world you can't just it's just built you just changed the in the color very whatever you can just change the pitch directly so you can try a lot of things too right right but in the physical worlds you have the you have the printer whatever attack you on the tool in the ends you have a printer that prints out these stickers are or would have a perturbation you wanted to another put it under and the object so we also essentially there's constraints what can be done there so so essentially there are many many of these additional constraints that you don't have in the digital world and then when we create the adversary example we have to take all these into consideration so how much of the creation of the adversarial examples art and how much is science sort of how much is the sort of trial and error trying to figure trying different things empirical sort of experiments and how much can be done sort of almost almost theoretically or or by looking at the model by looking at the neural network trying to I'm trying to generate sort of definitively what the kind of stickers would be most likely to create to be a good adversarial example in the physical world right that's that's a very good question so essentially I would say it's mostly science in a sense that's we do have a no sign scientific way of computing what whatever sir example what what is adversary perturbation we should add and then and of course in the ends because of these additional steps as I mention you have to print it out and then your you have to put it on and you have to take the camera and so there are additional steps that you do need to do additional testing but the creation process of generating the a bursary example it's really a very like scientific approach essentially we it's just we isn't capture many of these constraints as we mentioned in this last function that's the way optimized for and so that's a very scientific so the the fascinating fact that we can do these kinds of adversarial examples what do you think it shows us just your thoughts in general what do you think it reveals to us about neural networks the fact that this is possible what do you think it reveals thoughts about our machine learning approaches of today is there something interesting is that a features at a bug what do you what do you think at a very early stage of really developing your busts and generalizable machine learning methods and shows that way even though differently has made so much advancements but our understanding is very limited we don't fully understand and we don't understand well how they work why they work and also we don't understand that Wow right these buddies ever sorry examples is some people have kind of written about the fact that that the fact that there were so examples work well is actually sort of a feature not a bug it's is that that actually they have learned really well to tell the important differences between classes as represented by the training set I think that's the other thing I was going to say so it shows us also that's the the deep learning systems and now learning the right things how do we make them I mean I guess this might be a a place to ask about how do we then defend or how do we either defend or make them more robust these adversarial examples right I mean one thing is that I think other people so so they're happy actually thousands of papers now written on this topic Avenue of the attacks and mostly attacks I think they're more than then defenses but there are many hundreds of defense papers as well so in defense's a lot of work has been trying to I would call it more like a patchwork for example how to make the neural networks to LA three or four example like a master training how to make them a little bit more resilient got it um but I think in general it has limited effectiveness and we don't really have very strong and general defense so part of that I think is we talked about in deep learning the goal is to learn representations and that's our ultimate in Holy Grail ultimate goal is to learn representations but one thing I I think I have to say is that I think part of the lesson we're learning here is that we're one as I mentioned were not learning the right things and you are now learning the right representations and also I think the representations we are learning is not rich enough and so so it's just like a human visions of course we don't fully understand how human visions work but while humans look at the world we don't just say oh you know this is a person there's a camera where she get much more nuanced information from the from the world and we use all this information together in the ends to derive to help us to do motion planning and to do other things but also to classify what the object is and so on so we're linear much richer representation and I think that that's something we have now figure out how to do in deep learning and I think the rhetoric transition will also help us to build a more generalizable more resilient running system can you maybe linger on the idea of the word richer representations so to make representations more generalizable it seems like you want to make them more less sensitive to noise right so you want to learn you want to learn the right things you don't want to for example learn this spurious correlations and so on but at the same time is an example for return information our representation is like again we don't really know how humans vision works but when we look at the visual world we actually we can identify contours we can identify right much more information than just what's for example an image classification system is trying to do and that leads to I think the question you asked earlier about defenses so that's also in terms of more promising directions for defenses and that's where some of you know my work is trying to do and trying to show as well you have for example in the year 2018 paper characterizing adversarial examples based on spatial consistency information for semantic segmentation so that's looking at some ideas on how to detect adversarial examples so like I get were they you called them like a poisoned data set so like yeah adversarial bad examples in a segmentation day said can you as an example for that paper can you describe the process of defense there so in that paper what we look at is the semantic segmentation task so with the task essentially given an image for each pixel you want to say what the label is for the pixel and so so just like what we talked about so for every example it can easily full image classification systems it turns out that it can also very easily for these segmentation systems as well so given image I essentially can add adversary perturbation to the image to cause the class the segmentation system took basically segmented in any passion that I wanted so sorry that people were also showed that you can segment it even though there's no kitty in the in the image we can segment it into like a kitty pattern a Hello Kitty pattern yeah we segmented into like ICC v-tach side showing that this segmentation system even though they have fee effective in practice but at the same time they're reasonably really easily fault so the question is how can we defend against is how we can do the more resilient segmentation system so um so that's what we try to do and in particular what we are trying to do here is to actually try to leverage some natural constraints in the task which we call in this case spatial consistency so the idea of this special consistency is a following so again we'd already know how human vision works but in general was elicited what we can see us so for example as a person looks as the scene and we can segment the scene easily and then we humans right yes and then if heels pick like a two patches of the scene that has an intersection and for humans if your segments you know like patch a and patch B and then you look at the segmentation results and especially if you look at the sacrament station results at the intersection of the two patches there should be consistent in the sense that's what the label know what the what the pixels in this intersection what their labels should be and they essentially from these two different patches there should be similar in the intersection mmm so that's what we call spatial consistency so similarly for a segmentation system they should have the same poverty right so in the in the image if you pick to randomly pick two patches the has intersection you feed each patch to the segmentation system you get a results and then when I look at the results in the intersection the results the segmentation results should be very similar is that so okay so logically that kind of makes sense at least it's a compelling notion but is that how well does that work is that does that hold true for segmentation exactly so then in our where I can't experiment so we show the following so when we take second normal images this actually hosts pretty well for the segmentation systems that way or like did you look at like driving data sense right exactly but then this actually poses a challenge for a visceral examples because for the attacker to add perturbation to the image then it's easy for it to fold the segmentation system into for example for a particular patch are for the whole image to cause the segmentation system to create some to get to some wrong results but it's it's actually very difficult for the attacker to to have this ever serial for the example to satisfy the spatial consistency because these patches are randomly selected and they need to ensure that this special consistency works so they basically need to fall the segmentation system in a very consistent way yeah without knowing the mechanism by which you're selecting the patches or so on exactly it has to really fool the entirety of the so you do that to actually to be really hard for the attacker to do we tries you know the first week in the city of the art attacks actually showed us this defense methods is actually very very effective and this goes to I think also what I'm most saying earlier is essentially we want the learning system to have tools to have Richardson station also to learn from more you can add the same mathematics entually to have more ways to check whether it's actually having the right prediction so for example case doing the spacial consistency check and also actually so that's one paper though it is and then this suspicion consider this notion of consistency check it's not just limited to spatial properties it also applies to audio so we actually had follow-up work in audio to show that this temporal consistency can also be very effective in detecting a verse for example seeing audio XP or what kind of data right and then and then we can actually combine spatial consistency and temporal consistency to help us to develop more resilient methods in video so to defend against attacks forbid you awesome that's fascinating yeah yes yes but in general in the literature and the ideas are developing the attacks and the literature is developing a defense who would you say is winning right now right now of course is attack site it's much easier to develop attacks and there are so many different ways to develop attacks even just us we develop so many different methods for for doing attacks and also you can do white box extracts you can do black box attacks where attacks you don't even need and the attacker doesn't even need to know the architecture of the target system and now knowing the parameters after tacky system and another so there are so many different types of attacks so the counter-argument that people would have like people that are using machine learning and companies they would say sure and constrained environments and very specific data set when you know a lot about the model you know a lot about the data set already you'll be able to do this attack is very nice it makes for a nice demo it's a very interesting idea but my system won't be able to be attacked like this so the real-world systems won't be able to be attacked like this that's like that's that's another hope there's actually a lot harder to attack real-world systems can you talk to that is it I how hard is it to attack real-world systems yes I wouldn't call that I hope I think yeah it's more alpha wishful thinking I try trying to be lucky and so actually in our recent work my students and collaborators has shown some very effective attacks on real-world systems for example Google Translate and translation api's so in this work we showed so far I talked about other examples mostly in the vision category and of course adversary' examples also work in other domains as well for example in natural language so so in this work my students and collaborators have shown that also one we can actually very easily steal the model from for example Google Translate but just two inquiries from right through the api's and then we can train an imitation model ourselves using the curries and then once we and also the imitation model can be very very effective and essentially have achieving similar performance as a target model and then once we have the imitation model we can then try to create adversarial examples on these imitation models so for example and giving a you know in a work here was one example is translating from English to German we can give it a sentence saying for example I'm feeling freezing it's like 6 Fahrenheit and then translating German and then we can actually generate adversary examples that creates a target translation by very small perturbation so in this case I say we want to change the translation itself and six Fahrenheit to 21 Southeast's and in this particular example actually which has changed 6 to 7 in the original sentence that's the only change we made it caused the translation to change from the six Fahrenheit into 21 that's terrible and then and then so this example we created this example from our imitation model imitation and then this work actually transfers to the Google Translate so the attacks that work on the imitation model in some cases at least transfer to the original right model that's incredible and terrifying okay that's amazing work and that shows us again real world systems actually can be easily fooled and in our previous work we also showed these type of black box attacks can be effective cloud to the vision API as well so that's for natural language and for vision let's let's talk about another space that people have some concern about which is autonomous driving is sort of security concerns that's another real world system so do you have should people be worried about adversarial machine learning attacks in the context of autonomous vehicles that use like Tesla autopilot for example they uses vision as a primary sensor for perceiving the world and navigating in that world what do you think from your stop sign work in the physical world should people be worried how hard is that attack so actually there has already been like that there have always been and like a research shown that's for example actually even with Tesla like if you put a few stickers on the road it can't actually wide range in certain ways it can for that that's right but I don't think it's actually been I'm not I might not be familiar but I don't think it's been done on physical world's physical roads yet meaning I think is with the projector in front of the Tesla so it's a it's a physical suppose you're on the other side of the side of the sensor but you're not in still the physical world the the question is whether it's possible to orchestrate attacks that work in the actual physical like end-to-end attacks like not just a demonstration of the concept but thinking is it possible on the highway to control a Tesla that kind of idea I think there are two separate questions one is the feasibility of the attack and I'm hundred percent confident that's the is possible and there's a separate question whether you know someone will actually go you know deploy that attack I I hope people do not do that yeah two separate questions so the question on the word feasibility the clarified feasibility means it's possible it doesn't say how hard it is because in there to implement it so sort of the the barrier like how how much of a heist it has to be like how many people have to be involved what is the probability of success that kind of stuff and coupled with how many evil people there are in the world that would attempt such an attack right that but the to my question is is it sort of at you know I talked to you a mosque and a same question he says it's not a problem it's very difficult to do in the real world that this won't be a problem he dismissed it as a problem for adversarial attacks on the Tesla of course he happens to be involved with the company so he has to say that but I mean they may linger and a little longer do you see you where does your confidence that it's feasible come from and what's your intuition how people should be worried and how we might be do how people should defend against it how Tesla how way Moe how other autonomous legal companies should defend against sensory based attacks on whether on lidar or on vision or so on and also even for light actually that has been researched shown even like it's really important to pause there's really nice demonstrations that it's possible to do but there are so many pieces that it's kind of like it's it's kind of in the lab now it's in the physical world meaning it's in the physical space the attacks but it's very like you have to control a lot of things to pull it off it's like the difference between opening a safe when you have it and you have unlimited time and you can work on it like breaking into like the crown stealing the crown jewels or whatever right in terms of how real these attacks can be one way to look at it is that actually you don't even need any sophisticated attacks already we have seen in the many real-world examples incidents where showing that the the vehicle was making the wrong decision wrong decision without attacks right and this is also like so far with many talks about work in this adversarial setting showing that today's learning system they are so vulnerable to the adversarial setting but at the same time actually we also know that even in natural settings these learning systems they don't generalize well and hence they can really misbehave and there's certain situations like what we have seen and hence I think using that as an example okay so you should can be really they can be real but so there's two cases one is something it's like perturbations can make the system is behaved versus make the system do one specific thing that the attacker wants as you said targeted that seems you know that seems to be very difficult like a extra level of difficult step in the in the real world but from the perspective of the passenger of the car here I don't think it matters either way whether it's yeah it's misbehavior or a targeted attack okay and also and that's why I was also saying earlier like if one defense is this multi modal defense and more of these consistent checks and so on so in the future I think also it's important that for these autonomous vehicles the right they have lots of different sensors and they should be combining all these sensory readings to arrive at the decision and the interpretation of the world and so on and the more of these sensory inputs they use and the better they combine the sensory inputs the heart rate is going to be attacked and hence I think that is a very important direction for us to move towards so more Damona multi-sensor across multiple cameras but also in the case car radar ultrasonic sound even so all of those rights right exactly so another thing another part of your work has been in the space of privacy and that too can be seen as a kind of security vulnerability as social thinking of data as a thing that should be protected and the vulnerabilities to data is vulnerability is essentially the thing that you want to protect is the privacy of that data so what do you see as the main vulnerabilities in the privacy of data and how do we protect it right so you see in security we actually talk about essentially two in this case two different properties one is integrity and one is confidentiality so what we have been talking earlier is essentially the integrity of the integrity property after the new system how to make sure that the new system is giving the right prediction for example and privacy centuries on the other side is about confidentiality of the system is how attackers can when the attacker is compromise the confidentiality of the system that's when the attacker is still sensitive information and right about individuals and so on it's really clean does it those are great terms integrity and confidentiality right so how what are the main vulnerabilities to privacy would you say and how do we protect against it like what what are the main spaces and problems that you think about in the context of privacy right so and especially in the machine learning setting and so in this case as we know that how the process goes is that we have the training data and then the machining system a-train's from the screening data and then buta model and then they say our inputs are given to the model to inference time to try to get prediction and so on so then in this case the privacy concerns that we have is typically about privacy of the data in the training data because that's essentially the private information so and it's really important because oftentimes the training data can be very sensitive it can be your financial data how data are like in our case it's the sensors deployed in real world environments and so on and all this can be collecting very sensitive information and other sensitive information gets the first into the new system and trains and as we know these neural networks they can have really high capacity and they actually can remember a lot and hence just from the learning the learned model in the end actually attackers can potentially infra information about their original training data set so the thing you're trying to protect yeah is the confidentiality of the training data and so what are the methods for doing that would you say what what are the different ways that can be done and also we can talk about essentially how they attackin may try to relay information from the right so so and also there are different types of attacks so in certain cases again like in white box attacks we can say that the attacker I should get to see the parameters of the model and then from that the a smile attacker potential you can try to figure out information about the training data sets they can try to figure out what type of theta has been in the training data sets and sometimes they can tell like whether a person has been a particular person's data point has been used in the training data sets so white box meaning you have access to the parameters are saying your network and so that you're saying that it's some given that information as possible to some so I can give you some examples and another type of attack which is even easier to carry out is now the web box model is more offer just a query model where the hacker only gets to carry the machine in your model and then try to steal sensitive information in the original training data so right so I can give you an example in this case training a language model so in now I work in collaboration with the researchers from Google we actually studied the following question so so however the question is as we mentioned the neural networks can have very high capacity and they could be remembering a lot from the training process then the question is can attacker actually exploit this and try to actually extract sensitive information in the original training dataset through just securing the learned model without even knowing the parameters of the model like the details of the model are the actual model after model and so on so so that's the that's the question we set how to exploit and in one of the case studies we showed the following so we trained the language model over an email data sets it's called an Enron email data sets and era email datasets naturally contains uses social security numbers and credit card numbers so we treat the language model over the city cells and then we showed that an attacker by devising some new attacks by just occurring the language model and without knowing the details of the model the attacker actually can extract the original social security numbers and credit card numbers that were in the original training so get the most sensitive personally identifiable information from the dataset I'm just worrying it that's why even as we trie machine mania models we have to be really careful with the protecting users data promise me so what are the mechanisms for protecting is there as their as their hopeful so if there's been recent work or non-differential privacy for example that that that provides some hope but describe some of these that's actually right so that's also our finding is that by actually we show that in this particular case we actually have a good defense for the Quarian case for the coin it's a language model language model k so instead of just training a vanilla language model instead if we train a differentially private language model then we can still achieve similar utility but at the same time we can actually significantly enhance the privacy protection and stay after learned model and our proposed attacks actually are no longer effective and differential privacy is the mechanism of adding some noise by which you then have some guarantees on the inability to figure out the the person the the presence of a human of a particular person in the data set so right so in this particular case what the differential privacy mechanism does is that it actually as participation in the training process as we know during the training process we are learning the model well doing gradient updates the way the updates and so on and essentially differential privacy differentially privates machining algorithm in this case we'll be adding noise and a diverse perturbation during this training to some aspect of the training process right so then the finely trained ruining the learned model is differentially privates and so I can put can enhance the privacy protection so okay so that's the attacks and the defense of privacy you also talked about ownership of data so this this is a really interesting idea that we get to use many services online for seemingly for free by essentially sort of a lot of companies are funded through advertisement and what that means is the advertisement works exceptionally well because the companies are able to access our personal data so they know which advertisement to service to do targeted advertisements so on so can you maybe talk about the this you have some nice paintings of the future philosophically speaking future where people can have a little bit more control of their data by owning and maybe understanding the value of their data and being able to sort of monetize it in a more explicit way as opposed to the implicit way that is currently done yeah I think this is a fascinating topic and also a really complex topic right I think there are these natural questions who should be owning the data and and so I can tell one analogy and so for example for physical properties like your house and so on so really um this notion of property rights it's not just you know like it's not like from day one we knew that's there should be like this clear notion of ownership of properties and having enforcement for this and so actually people have shown that this establishment and enforcement of property rights has been a main driver for the for the for the economy earlier and that actually really propelled the economic growth and even right in the earlier stage so throughout the history of the development of the United States there or actually just civilization the idea of property rights that you can own property enforcement days is you should know rights like governmental like enforcement of this actually has been a key driver for economic growth and there have been even research proposals saying that for a lot of the developing countries and they you know essentially the challenging growth is not actually due to the lack of capital its more due to the lack of this problem notion property rights and enforcement's of property rights interesting so that the presence of absence of both the the the concept of the property rights and their enforcement has a strong correlation to economic growth and so you think that that same could be transferred to the idea of property ownership in case of data ownership I think I think its first of all it's a good lesson for us to like to recognize that these rights and the recognition and enforcement of this type of Rights it's very very important for economic growth and then if we look at where we are now and where we are going in the future and so essentially more and more as it's actually moving into the digital world and also more anymore I would say even like information our asset alpha person is more and more into the real world the physical necessary the teaching the world as well it's the data that's the presence generators and essentially it's like in the past what defines a person you you can say right like oftentimes besides the inmates like capabilities actually it's the physical properties oh right that you finds a person but I think more the more people start to realize actually what defines a person is more important in the data that the person has generated other data about the person all the way from your political views yar yar music tastes and right your financial information now a lot of these and your health so more and more of the definition of the person is actually in the digital world and currently for the most part that's owned in place like it's and people don't talk about it but kind of it's owned by [Music] Internet companies so it's not owned by individual there's no clear notion of ownership after such data and also we you know we talk about privacy and so on but I think actually clearly identifying the ownership it's a first step once you identify the ownership then you can say who gets to define how that either should be used so maybe some users are fine with you know internet companies serving them as you think the data as lies if the if the data is used in a certain way that actually the user consents ways are allowed for example you can see the recommendation system in some sense we don't call it an ass but a recommendation system similar it's trying to recommend you something and users enjoy and can really benefit from good recommendation systems and they recommend you you're better music movies news or even research papers to read but but of course then in this tech is ass especially in in certain cases where people can be manipulated by this targeted ass that can have really bad like a severe consequences so so essentially uses one that data to be used to better serve them and also maybe even right get pay for whatever like in different settings but the things that's the first of all we need to really establish like you who needs to decide who can decide how the data should be used and typically that the establishment and clarification of the ownership will help this and it's an important first step so if the user is the owner then naturally the user gets to define how the dinner should be used but if you even say that wait a minute you say actually now the owner of the stator whoever's collecting the data is the owner of the data now of course they get to use it in a hybrid way they want yeah so to really address these complex issues we need to go at the root cause so it seems fairly clear that's the first we really need to say now who is the owner of the data and then the owners can specify how the one that they'd had to be utilized so I said that that's a fascinating does most people don't think about that and I think that's a fascinating thing to think about and probably fight for it I can only see in the economic growth argument it's probably a really strong one so that's that's the first time I'm kind of at least thinking about the the positive aspect of that ownership being the long-term growth of the economy so good for everybody but sort of one down possible downside I could see sort of to put on my grumpy old grandpa hat and you know it's really nice for Facebook and YouTube and Twitter to all be free and if you give control to people or their data do you think it's possible they will be they would not want to hand it over quite easily and so a lot of these companies that rely on mass handover of data and then their book therefore provide a mass seemingly free service would then completely so the the the the way the internet looks will completely change because of the ownership of data and we'll lose a lot of services with value do you worry about that that's a very good question I think that's not necessarily the case in a sense that's yes users can have ownership of their data they can maintain control of their data but also then they get to decide how their data can be used so and that's why I mention it like you see in this case if they feel that they enjoy the benefits of social networks and so on and they are fine with having Facebook having their data but utilizing the data in certain way that's they agree then they can still enjoy the free services but for others maybe they would prefer some kind of private vision and in that case maybe they can even opt in to say that I want to pay and to have so for example it's already fairly standard like you pay for certain subscriptions so that you don't get to you know be shown as yes yeah right so the users essentially can have choices and I think we just want to essentially bring out more about who gets to decide what to do with that yeah I think it's an interesting idea because if you pull people now you know it seems like I don't know but subjectively sort of anecdotally speaking it seems like a lot of people don't trust Facebook so that's at least a very popular thing to say that I don't trust Facebook right I wonder if you give people control of their data as opposed to sort of signaling to everyone that they don't trust Facebook I wonder how they would speak with the actual like would they be willing to pay $10 a month for Facebook or would they hand over their data it'd be interesting to see what fraction of people with would quietly hand over their data to Facebook to make it free III don't have a good intuition about that like how many people do you have an intuition about how many people would use their data effectively on the market on the on the market of the Internet by sort of buying services with their data yeah so that's a very good question I think so one thing I also want to mention is that this right so it seems that especially in press and the conversation has been very much like two sides fighting against each other um oh one hands right yes your skin say that right they don't trust Facebook they don't are there is DB Facebook yeah yeah exactly on the other hand and right of course and right the other side they also feel oh they are providing a lot of services to users and users are getting it all for free so I think actually you know I talked a lot to like different companies and also like a physically ample size and so one thing I hope also like this my hope for this year also is that and we want to establish a more constructive dialogue and that happen and to help people to understand that the problem is much more nuanced then just and this to size fighting because naturally there's a tension between the two sides between your Twitter and privacy so if you want to get more utility essentially like the recommendation system example I gave earlier if you want someone to give you good recommendation essentially whatever the system is the system is going to need to know your data to give you a good recommendation but also of course at the same time we want to ensure that however that data is being handled it's done in the privacy preserving way and so that that for example that recommendation system doesn't just go around and say we are they here and then cause all the you know cause a lot of bad consequences and so on so you want that dialog to be a little bit more in the open a little more more nuanced and maybe adding control to the data ownership to the data will allow so as opposed to this happening in the background allowed to bring it to the forefront and actually have dialogues in like more nuanced real dialogues about how we trade our data for the services that's the whole rights right yes at high level so essentially also knowing that there are technical challenges and in in addressing the issue to like you basically you can't have just like the example that I gave earlier it is really difficult to balance the two between utility and privacy and and that's also a lot of things that I work on my group Roxanne as well as to actually develop these technologies that are needed to essentially help this balance better essentially to help data to be utilized in the privacy preserving and responsible way and so we essentially need people to understand the challenges and also at the same time and to provide the technical abilities and also regulatory frameworks to help the two sites will be more in the women situation instead of I fight yeah the fighting the fighting thing is I think YouTube and Twitter and Facebook are providing an incredible service to the world and they're all making mistakes of course but they're doing an incredible job you know that I think deserves to be applauded and there's some degree of gratit it's a cool thing that the that's created and it shouldn't be monolithically fought against like Facebook as evil or so on yeah I might make mistakes but I think it's an incredible service I think it's world-changing I mean I've you know I think Facebook's done a lot of incredible incredible things by bringing for example identity you're like allowing people to be themselves like their real selves in in the digital space by using a real name and their real picture that step was like the first step from the real world to the digital world that was a huge step that perhaps will define the 21st century in us creating a digital identity there's a lot of interesting possibilities there that are positive of course some things are negative and having a good dialogue about that is great and I'm I'm great that people like you're at the center that's how access is it's awesome I think it also and I also can understand I think actually in the past especially in the past couple years and this rising awareness has been helpful like users are also more and more recognizing that privacy is important to them they shoes may be right there should be owners after data I think the Stephanus is very helpful and I think also this type of voice also and together with the regulatory framework and so on also help the companies to essentially put this type of issues at a higher priority and knowing that right also it is their responsibility to to ensure that users are well protected and so I think it definitely the raising voice is super helpful and I think that I should really has brought the issue of data privacy and even this consideration of the ownership to the forefront to really much by the community and I think more of this voice is needed but I think it's just that we want to have a more constructive dialogue to bring the both sides together to figure out a constructive solution so another interesting space where security is really important is in in the space of any kinds of transactions but it could be also digital currency so can you maybe talk a little bit about blockchain and can you tell me what is a blockchain I think the brought to you where it itself is activated overload is in general it's like AI yes so in general I talk about our team we refer to this distributed IJ in a decentralized fashion so essentially you have in a community of nose that come together and even though each one may not be trusted and otherwise certain thresholds of the set of nodes and he behaves properly then and the system can essentially achieve certain properties for example in the distributed I just I think you have you can maintain a mutable log and you can ensure that for some of the transactions actually I'll create a pound and then it's immutable and so on so first of all what's the ledger so it's a it's like a database it's like a data entry and so distributed ledger is something that's maintained across or is synchronized across multiple sources multiple nodes multiple notes yes and so where is this idea now how do you keep okay so it's important ledger a database to keep that to make sure so what are the kinds of security vulnerabilities that you're trying to protect against in the context of this the distributed ledger so in this case for example you don't want to some malicious nose to be able to change the transaction logs and in certain cases account double spending like your also calls you can also cause different views in different parts of the network and so on so the ledger has to represent if you're capturing like financial transactions has to represent the exact timing and the exact occurrence and no duplicates all that kind of stuff has to be represent what actually happened okay so what are your thoughts on the security and privacy of digital currency I can't tell you how many people write to me to interview various people in the digital currency space there seems to be a lot of excitement there and it seems to be some of it to me from an outsider's perspective seems like dark magic I don't know how secure I think the the foundation from my perspective of digital currencies that is you can't trust anyone so you have to create a really secure system so can you maybe speak about how well your thoughts in general about digital currency is and how you how it can possibly create financial transactions and financial stores of money in the digital space so you as security and privacy and so so again as I mentioned earlier in security we actually talk about two main properties and the integrity and confidentiality and so there's another one for availability you want the system to be available but here for the question you ask let's just focus on integrity and confidentiality yes so so for integrity of this distribution essentially as we discussed we want to ensure that's the different nose and right so they have this consistent video usually it's down through we call a consensus protocol and that's the establish share the view on this leche and that you cannot go back and change this immutable and so on so so in this case then the security often refers to this integrity property and essentially you're asking the question how much work how how can you attack the system so that the attacker can change the lock for example right how hard is it to make an attack like that yes right and then that very much depends on the the consensus mechanism the how the system is built and now that so there are different ways to build these decentralized systems and people may have heard about the term Scout like proof-of-work you prefer take you this different mechanisms and really depends on how how the system has been built and also how much resources how much work has gone into the network to actually say how secure it is so for example if you talk about like in the coins for what system is so much electricity it has been burnt so there's differences there's differences in the different mechanisms and the implementations of a distributed ledger used for digital currency also there's Bitcoin is a whatever there's so many of them and there's underlying different mechanisms and there's arguments I suppose about which is more effective which is more secure which is more what amount of resources needed to be able to attack the system like for example what percentage of the nose do you need to control our compromise in order to write to change the log and those are things do you do you have a sense if those are things that can be shown theoretically through the design of the mechanisms or does it have to be shown empirically by having a large number of users using the currency I see so in general for each consensus mechanism you can actually show theoretically what is needed to be able to attack the system of course there are there can be different types of attacks as weepy and discuss at the beginning and so that and it's difficult to gave like you know a complete estimate like really how much is needed to compromise the system but in general right so there are ways to say what percentage of the knows you need to compromise and so on so we talked about integrity so on the security side and then you also mentioned can the privacy or the confidentiality side does it have some of does it have some of the same problems and therefore some of the same solutions that you talked about and the machine learning side with differential privacy and so on yeah so actually in general on the public ledger in this public decentralized systems and actually nothing is private so all the transactions posters on the library anybody can see so in that sense there is no confidentiality and so usually all you can do is then there are the mechanisms that you can built in to enable confidentiality are privacy of the transactions and the data and so on that's also some of the work and that's both my group and also my startup and does as well what's the name you start o Asus labs Oasis labs and so the confidentiality aspect there is even though the transactions are public you want to keep some aspect confidential of the identity of the people involved in the transactions or what what is their hope to keep confidential in this context so in this case for example you want to your nipple like private confidential transactions even so so there are different and essentially types of data that you want to keep private are confidential and you can utilize different technologies including your knowledge proofs and also secure computing and techniques and to hide the right who is making the transactions to whom and the transaction amount and in our case also we can enable like confidential smart contracts and so that's you don't know the data and the execution of the smart contract and so on and we actually are combining these different technologies and to going back to the earlier discussion we had enabling like ownership of data and privacy of data and so on so so at Oasis labs we're actually building what we call a platform for responsible data economy to actually combine these different technologies together and to enable secure and privacy-preserving computation and also using the library to help provide immutable log of users ownership to their data and the policies they want the data to adhere to the usage of the data to adhere to and also how that it has been utilized so all this together can build we can a distributed secure computing fabric that helps to enable a more responsible data economy other things together yeah wow those eloquent okay you're involved in so much amazing work that we'll never be able to get to but I have to ask at least briefly about program synthesis which at least in a philosophical sense captures much of the dreams of what's possible in computer science and the artificial intelligence first let me ask what is program synthesis and can ural networks be used to learn programs from data so can this be learned some aspect of this synthesis can it be learned so program synthesis is about teaching computers to write code to program and I think it has one of our ultimate dreams or goals and you know I think Andreessen talked about software eating the world so I say once we teach computers to write software I had to write programs then I guess computers yeah exactly so yeah and also for me actually um when I you know shifted from security to more AI a machining program synthesis is program scenes in adversarial machining these are the two fields that I particularly focus on like program synthesis one of the first questions that I actually started what are seeking just as a question oh I guess with from the security side there's a you know you're looking for holes and programs so as at least see small connection but why what was your interest for program synthesis as because it's such a fascinating such a big such a hard problem in the general case why program synthesis so the reason for that is actually when I shifted my focus from security into AI machine learning and actually one of my main motivation at the time and is that even though I have been doing a lot of working security and privacy but I have always been fascinated about beauty intelligent machines and that was really my main motivation to spend more time in AI am a Shalini is as I really want to figure out how we can build intelligent machines and to help us towards that goal program synthesis is really one enough I would say the best domain to work on I actually call it's like programming synthesis it's like the perfect playground for building intelligent machines therefore artificial general intelligence yeah um well it's also in that sense not just a playground I guess it's it's the ultimate test of intelligence because yes I think I think you can generate so neural networks can learn good functions and they can help y'all in classification tasks but to be able to write programs right that's that's the epitome from the machine side that's the same as passing the Turing test and natural language but with programs it's able to express complicated ideas to reason through ideas and yeah and boil them down to algorithms yes exactly is that credible so can this be learned how far are we is there hope what are the open challenges questions and we're still at an early stage but already I think you we have seen a lot of progress I mean definitely we have you know existence proof just like the humans can write programs so there's no reason why computers cannot write programs and so I think that's definitely an achievable goal it's just how long it takes and then and even today we actually have you know the program synthesis community especially the program synthesis by learning our way College neural program synthesis community is still very small but the community has been growing and we have seen a lot of progress and in limited domains I think actually program synthesis is ripe for real-world applications so actually was kind of amazing I was at giving a talk it's also here it's a rework we worked you planning something actually so I give another talk at the previously rework conference in deep reinforcement learning and then I actually met someone from a startup and the CEO of the startup and when he saw my name he recognized and he actually said one of our papers actually had they have put the had actually become a key products and that was program synthesis in that particular case it was natural language translation translating natural language description into psycho Cory's oh wow that that direction okay right so yeah so you program since this is in limited domains in well specified domains actually already we can see really great great progress and applicability in the real roads so domains like as an example you said natural language being able to express something to just normal language and it converts it into a database sequel SQL query right and that's how how solve the problem is that because that seems like a really hard problem okay eliminate domains actually it can work pretty well and now this is also a very active domain after research at the time I think one he saw our paper at the time we were the state of the Arts yeah and that task and since then actually now there has been more work and with even more sophisticated assets and so but I I think I wouldn't be surprised that's more of this type of technology really getting to the real worlds that's exciting in the near term being able to learn in the space of programs is super exciting I still yeah I'm still skeptical because I think it's a really hard problem progress and also I think in terms of the your ass about open challenges I think the domain is full of challenges and in particular also we want to see how we should measure the progress in the space and I would say mainly three main I'll say metrics so one is a complexity of the program that we can synthesize and that will actually have clear measures and just look at you know the past publications and even like for example I was at the recent Europe's conference now there is actually very sizable like session dedicated to program since this is vicious or even neural progress today which is great and and we continue to see the increase like I think they were sizable it's five people and they will all win touring awards one day like it so we can see increase in the complexity of the program is that these synthesized sorry - is it the complexity of the actual text of the program or the running time complexity which complexity over how complexity after task to be synthesized and the complexes are after the actual synthesize the programs so you so the lines of code even for example okay I got you but it's not the theoretical upper bound of the running time of the day and you can see the complexity in decreasing already oh no meaning we want to be able to synthesize monomer complex programs bigger and bigger programs so we want to see that's we want to increase I have to think through because I thought of complexity is you want to be able to accomplish the same task with a simpler and simpler program no we are not doing that okay it's more it's more about how complex a task right we can see the exotic being able to synthesize programs learn them for more and more difficult right so for example initially our first working program synthesis synthesis was to translate natural language description into really simple programs called if TTT if this then that so given a trigger condition what is the action you should take so that program is a super simple you just Andy identify the trigger conditions and the action yeah and then later on with the secret queries that gets more complex and then also we started to synthesize programs with loops and know anything could synthesize recursion it's all over actually yeah 1fi works actually it's already rechristen you're complexity and the other one is generalization like one-way training I want to learn programming synthesizer in this case and neural programs to synthesize programs then you wanted to generalize so for a large number of inputs to be able to write generalize to previously and C inputs got it and so so someone for the work who waited earlier learning recursive new programs actually showed that recursion actually is important and to learn and if you have recursion then for certain and set of tasks we can actually show that you can actually have perfect generalization and so right so that one the best paper Awards that I clear earlier and so that's one example of we want to learn these you know programs that can generalize better but that works for a certain task with certain domains and there is question how we can essentially develop more techniques that can and have generalization for wider set of domains and so on so that's another area and then and then the the third challenge I think will it's not just for programming synthesis is also cutting across other fields in machine learning and also including like deep reinforcement and in particular is that this adaptation is that we want to be able to learn from the past and tasks and training and so on to be able to solve new tasks so for example in program synthesis today we still are working in the setting way given a particular task we change the right model and to solve this particular task but that's not how humans work like the whole point is we train a human than you can then program to south new tasks right exactly and just like we don't want to just change agent to play a particular game hey it's Atari ice ago whatever we want to train these agents that can and essentially extract knowledge from the past learning experience to be able to adapt to new new tasks and solve new tasks and I think this is particularly important for program synthesis yeah that's the whole point that's the whole dream of progress this is your learning a tool that can solve new problems right exactly and I think that's a particular main that as a community we need to put more emphasis on and I hope that we can make more progress today as well awesome I think there's a lot more to talk about but let me ask that you also had a very interesting and we talked about rich representations he had a rich life journey you did your bachelor's in China and your masters and PhD in the United States CMU and Berkeley are there interesting differences I told you I'm Russian I think there's a lot of interesting difference between Russia and the United States are there in your eyes interesting differences between the two cultures from the silly romantic notion of the spirit of the people to the more practical notion of how research is conducted that you find interesting or useful in your own work of having experienced both that's a good question I think so I I started in China for my undergraduate and that was more than 20 years ago there's been a long time is there echoes of that time I think even more so maybe something that's even be more different for my experience and a lot of computer science researchers and practitioners is that so for my undergraduate studies physics very nice and then I switch to a computer science in graduate school what happened was there was there is there another possible universe where you could have become a theoretical physicist at Caltech or something like that that's very possible some of my and undergrad classmates then the later studies physics account there 15 physics from these schools from yeah from tough physics programs so so you you switch to I mean in that from that experience to doing physics in your bachelor's how what means you decide to switch to computer science and computer science had arguably the best university one of the best universities in the world for computer science and with Carnegie Mellon especially for the grad school and and so on so what ii only 10 mighty just kidding okay I had Authority and know what what was the choice like and what was the move to the United States like what was that whole transition and if you remember if there's still echoes of some of the spirit of the people of China in you in New York it's like three questions so yes I guess okay the first transition from physics to computer science yes so when I first came to the United States I was actually in the physics ph.d program at Cornell yeah I was there for one year and then I switched to computer science and I was seeing the PC program at kind of give a loan and so okay so the reasons for switching so one thing so that's why I also mentions that about this difference in backgrounds about having studied physics yes first in my undergrad um actually really I really did enjoy my undergrads time and education in physics I think that actually really helped me in my future work in computer science actually even for machine learning a lot of machine learning stuff the the core machining methods many of the magic for honest most most of everything came from physics I was I think I was really attracted to physics and it was it's really beautiful and educated physics is the language of nature and I actually really remember like one moment in my undergrads like I did my undergrad in Chinua and I used to study in the library and I clearly remember like one day I was sitting in a library and I and I was like writing my notes and so on and I got so excited that I realized that if you just from a few simple axioms a few simple laws I can derive so much it's almost like I can't derive the rest of the world yeah there's the universe yes yes so that was like amazing do you think you have you ever seen or do you think you can rediscover that kind of power and beauty and computer science in the world that yes that's very interesting so that gets to you know the transition from physics to Versailles and it's a it's quite different for and for physics in in Cresco actually things changed so one is I started to realize that when I started doing research in physics at the time I was doing theoretical physics and a lot of its the you still have the beauty base very different so I have to actually do a lot of simulation so essentially I was actually writing in some in some cases writing a fortune Harold fortune yes to actually write do like do simulations and so on that was not not exact I I enjoy it's doing and also at the time from talking with the senior you know students in the program I realized many of the students actually were going off to work Wall Street and and so on and so and I've always been interested in computer science and actually essentially taught myself the C programming program right when in college and college somewhere for fun learning to do C programming you know in physics at the time I think now the programming profit has changed but at the time really the only class we had in in Hoosick amir science education was introduction to africa to computer science or computing and fortune 77 there's a lot of people that still use Fortran I'm actually if you're a programmer out there I'm looking for an expert to talk to about Fortran they seem to there's not many but there's still a lot of people to still use Fortran and still a lot of people these cobalt I realized instead of just doing programming for doing simulations and so on that I may as well just change to computer science and also one thing I really like and that's a key difference between the two as in computer science is so much easier to realize your ideas if you have idea you're writing it up you're cut it up and then you can see it's actually bring it to life quickly it's your life wasting physics if you how good theory you you have to wait for the experimentalist to do the experiments and to confirm the theory and things just take so much longer and and also the reason I in physics I decided to do theoretical physics it was because I had my experience with experimental physics first you have to fix the equipment fixing the equipment first so offensive equipment so there's a lot of it yeah he's have to collaborate with a lot of people takes a long time yes messy so I decided to switch to computer science and the one thing I think maybe people have realized is that for people who study physics actually it's very easy for physicists to change to do something else yes I think physics provides a really good training and yeah so actually it was very easy to switch to computer science but one thing going back to your earlier question so one thing I should you realize so there is a big difference between commune sense and physics away physics you can derive the the whole universe from just a few simple laws and computer science given that a lot of it is defined by humans the systems that you find by humans and and artificial I can essentially create a lot of these artifacts and so on and it's it's not quite the same you don't derive the computer systems with just a few simple laws you actually have to see there's historical reasons why our system is builds and designs one way versus the a day there's a lot more complexity or less elegant simplicity of e equals mc-squared that kind of reduces everything down to his beautiful fundamental equations but what about the move from China to the United States is there anything that still stays in you that's contributes to your work the fact that you grew up in another culture so yes I think especially back then it's very different from now so you know now they actually I see these students coming from China and even an aggressor actually they speak fluent English it was just you know like amazing and they have already understood so much of the culture in the US and so on and it was to you was all foreign it was it was a very different time at a time actually even we didn't even have access to email right not to mention about the wealth yeah I remember I had to go to you know specific like you know privileged several rooms too much knowledge about the Western world and actually at the time I didn't know actually the the in the US the West Coast weather is so much better than the yeah things like that actually it's very it's very yeah but now it's so different at the time I I would say there's also a bigger culture difference because there's so much less opportunity for shared information so it's such a different right I meant world let me ask me be a sensor question I'm not sure but I think you're not in similar positions is I've been here for already 20 years as well and looking at Russia from our perspective and you looking at China in some ways it's a very distant place because it's changed a lot but in some ways you still have echoes you have still have knowledge of that place the question is you know China is doing a lot of incredible work in AI do you see please tell me there's an optimistic picture you see where the United States and China can collaborate and sort of grow together in the development of AI towards you know there's different values in terms of the role of government and so on of ethical transparent secure systems we see it differently in the I States a little bit than China but we're still trying to work it out do you see the two countries being able to successfully collaborate and work in a healthy way without sort of fighting and making it an AI arms race kind of situation yeah I believe so and I think it's science there's no border and the advancement of technology helps everyone helps the whole world and so I certainly hope that the two countries will collaborate and I certainly believe so do you have any reason to believe so except being an optimist so first again like I said science has no borders and especially science doesn't know board borders right and you believe that will you know in this in the former Soviet Union during the Cold War yeah so this is the other point I was going to mention is that especially in academic research everything is public like we write papers we open source codes and others in the public domain it doesn't matter whether the person is in the u.s. in China or some other parts of the world and they can go on archive and look at the latest research and results so that openness gives you hope yes me too and that's also how as a world we make progress the best so apologize for the romanticized question but looking back what would you say was the most transformative moment in your life that maybe made you fall in love with computer science you said physics you remember there was a moment where you thought you could derive the entirety of the universe was there a moment that you really fell in love with the work you do now from security to machine learning to program synthesis so maybe as I mentioned actually in college a one summer I should tell myself programming see yes you just read a bug don't tell me you fell in love with computer science by programming and see remember I mentioned when one of the draws for me to come here sense is how easy it is to realize their ideas so once I you don't read the book started like it taught myself how to program and see immediately what what did I do like I programmed two games um ones just simple like it's a go game like it supports you can move the stones and so on and the other one actually programmed the game that's like a 3d Tetris it was a to not to be a super hard game to play it's obvious the standard 2d Tetris it's actually a 3d thing but I can realize wow you know I just had these ideas to try it out and then you can just do this so that's the one I realized wow this is amazing yeah you can create yourself from nothing to something that's actually out in the real world so let me ask let me ask a silly question or maybe the ultimate question what is to you the meaning of life what what gives your life meaning purpose fulfillment happiness joy okay these are two different questions very different yeah it's easy that you asked this question maybe this question is probably the question that has follows me and follow my life the most have you discovered anything and you satisfactory answer for yourself is there something is there something you've arrived at you know that there's a moment I've talked to a few people who have faced for example a cancer diagnosis or faced their own mortality and that seems to change their views and it it seems to be a catalyst for them removing most of the crap that the of seeing that most of what they've been doing is not that important and really reducing it into saying like here's is actually the few things that really give me give meaning mortality is a really powerful catalyst for that it seems like facing mortality whether it's your parents dying or somebody close to you dying or facing your own death for whatever reason or cancer and so on yeah in my own case I didn't need to face mortality and I think there are a couple things so one is like who should be defining the meaning of your life right is there some kind of even greater things than you who should define the meaning of your life so for example when people say that searching the meaning for our life is is there some there is some outside voice or is there something you know a set of you who actually tells you you know some people talk about oh you know this is what you have been born to do right right like this is your destiny um so who right so that's the one question like who gets to define the meaning of your life should you be finding some other thing some other factor to define this for you always something actually it's just entirely where you define yourself and it can be very arbitrary yeah so in inner and inner voice or an outer voice whether it's it could be spiritual religious - with God or some other components of the environment outside of you or just your own voice do you have up do you have an answer there and so you know you know the long period of time of thinking and searching even searching through outsides right you know voices are factors outside of me yeah so that I have and so I've come to the conclusion and realization that it's you yourself that you finds the meaning of life yeah that's a big burden no isn't it right so then you have the freedom to define it yes and and another question is like what does it really mean by the meaning of life right um and also whether the question even make sense absolutely and you said it somehow distinct from happiness so meaning is something much deeper than just any kind of emotional any any kind of contentment or joy whatever it might be much deeper and then you have to ask what is deeper than that what is what is there at all and then the question starts being silly right and also you can say it's deeper but you can also say it's a shallow depending on how people want to define the meaning of their life so for example most people don't even think about this question then the meaning of life to them it doesn't really matter that much and also whether knowing the meaning of life and whether actually helps y'all love to be present area or whether helps your life to be happier and these actually are often questions is not worse most questions open I tend to think that just asking the question as you mentioned as you've done for a long time is the only that there is no answer and asking the question is a really good exercise I mean I have this for me personally I've had the kind of feeling that creation is a like for me has been very fulfilling and it seems like my meaning has been to create and I'm not sure what that is like I I don't have a single lot of kids I would love to have kids but I also sounds creepy but I also see sort of he said see programs I see programs as little creations I see robots as little creations I think those are met those of those bring and then ideas theorems and and are creations and those somehow intrinsically like you said bring me joy I think they do to a lot of these scientists but I think they did a lot of people so that to me if I had to force the answer to that I would say creating new things yourself for you for me for me for me I don't know but like you said as he keeps changing is there some answer that some people they can I think they may say it's experience rights like their meaning of life all right they just want to experience to the richest and full as they can and a lot of people do take that path yes seeing life is actually a collection of moments and then trying to make the richest possible that's filled those moments with the richest possible experiences yeah right and for me I think it's certainly we do share a lot of similarity here like the creation is also really important for me even from you know the things that I've already talked about even like you know writing papers and these are our creations as well and I have not quite thought whether that has really the meaning of my life like in a sense also that maybe like what kind of things should you create there's so many different things that you could create and also you can say another view is maybe growth is it's related but different from experience growth is also maybe type of meaning of life it's just you try to grow every day try to be a better self every day and and also ultimately we are here it's part of the overall evolution the right the world is evolving it's funny it's funny that the growth seems to be the more important thing than the thing you're growing towards it's like it's not the goal it's the the journey to it sort of it's almost it's almost when you submit a paper it's there's a sort of depressing element to it not to submit a paper but when that whole project is over I mean there's a gratitude there's a celebration and so on but you're usually immediately looking for the next thing yeah the next step right it's not it's not that status that at the end of it is not the satisfaction is the the hardship the challenge you have to overcome the growth through the process it's something it's somehow probably deeply within us the same thing that drove that drives the evolutionary process is somehow within us with everything the way the way we see the world since you're thinking about this so you're still in search of an answer I mean yes and no in the sense that I think for people who really dedicate time to search for the answer to ask a question what is the meaning of life it does not as we bring your happiness yeah it's a question and we can say right like weather is a well-defined question and and on the other and but on the other hand given that you get two answers yourself you can define it yourself sure I can't just you know give it answer and in that sense yes it can help and like it's like we discussed if you say oh then my meaning of life is to create are to grow then then yes then I think they can help but how do you know that that is really the meaning of life are the meaning of your life it's like there's no way for you to really answer the question sure but something about that certainty is liberating so if it might be an illusion you know you might not really know you might be just convincing yourself falsely falsely but being sure that that's the meaning the there's something there's something liberating in that in that there's something freeing in knowing this is your purpose so you can fully give yourself to that without you know for a long time you know I thought like isn't it all right like why what's how do we even know what's good and what's evil like it isn't everything just relative like how do we know you know the the question of meaning is ultimately the question of why do anything why is anything good or bad why is anything moment then you start to I think just like you said I think it's a really useful question to ask but if you ask it for too long and too aggressively I mean not be so protect it not be productive and not just for traditionally society to find success but also for happiness it seems like asking the question about the meaning of life is like a trap is uh were destined to be asking we destined to look up to the stars and ask these big white questions we'll never be able to answer but we shouldn't get lost in them and that's probably the that's at least a lesson I picked up so far I'm noting that topic let me just add one more thing so it's interesting so actually so sometimes yes it can help you and to focus so when I when I shifted my focus more from security to a I am a Sunni at the time the actually one of the main reason why I did that was because at the time I thought my mini the meaning of my life and the purpose of my life is to build in hydrogen machines and that's and then your inner voice said that this is the right this is the right journey to take to build intelligent machines and that you actually fully realized you took a really legitimate big step to become one of the world class researchers to actually make it to actually go down that journey yeah that's profound that's profound I don't think there's a better way to end a conversation than talking for for a while about the meaning of life done it's a huge honor to talk to you thank you so much for talking today thank you thank you thanks for listening to this conversation with Dawn song and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using collects podcast if you enjoy the spot guest subscribe on YouTube review it with five stars on Apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman and now let me leave you with some words about hacking from the great Steve Wozniak a lot of hacking is playing with other people you know getting them to do strange things thank you for listening and hope to see you next time you |
Ilya Sutskever: Deep Learning | Lex Fridman Podcast #94 | the following is a conversation with elias discover co-founder and chief scientist of open ai one of the most cited computer scientists in history with over 165 000 citations and to me one of the most brilliant and insightful minds ever in the field of deep learning there are very few people in this world who i would rather talk to and brainstorm with about deep learning intelligence and life in general than ilia on and off the mic this was an honor and a pleasure this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of this crisis i'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars and have a podcast support it on patreon or simply connect with me on twitter at lex friedman spelled f-r-i-d-m-a-n as usual i'll do a few minutes of as now and never any ads in the middle that can break the flow of the conversation i hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the app store when you get it use code lex podcast cash app lets you send money to friends buy bitcoin invest in the stock market with as little as one dollar since cash app allows you to buy bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating i recommend ascent of money as a great book on this history both the book and audiobook are great debits and credits on ledgers started around 30 000 years ago the us dollar created over 200 years ago and bitcoin the first decentralized cryptocurrency released just over 10 years ago so given that history cryptocurrency is still very much in its early days of development but it's still aiming to and just might redefine the nature of money so again if you get cash out from the app store google play and use the code lex podcast you get ten dollars and cash up will also donate ten dollars to first an organization that is helping advance robotics and stem education for young people around the world and now here's my conversation with ilya you were one of the three authors with alex kaczowski jeff hinton of the famed alex ned paper that is arguably the paper that marked the big catalytic moment that launched the deep learning revolution at that time take us back to that time what was your intuition about neural networks about the representational power of neural networks and maybe you could mention how did that evolve over the next few years up to today over the 10 years yeah i can answer that question at some point in about 2010 or 2011 i connected two facts in my mind basically the realization was this at some point we realized that we can train very large i shouldn't say very you know they're tiny by today's standards but large and deep neural networks end to end with back propagation at some point different people obtained this result i obtained this result the first the first moment in which i realized that deep neural networks are powerful was when james martens invented the hessian-free optimizer in 2010 and he trained a 10-layer neural network end-to-end without pre-training from scratch and when that happened i thought this is it because if you can train a big neural network a big neural network can represent very complicated function because if you have a neural network with 10 layers it's as though you allow the human brain to run for some number of milliseconds neuron firings are slow and so in maybe 100 milliseconds your neurons only fire 10 times so it's also kind of like 10 layers and in 100 milliseconds you can perfectly recognize any object so i thought so i already had the idea then that we need to train a very big neural network on lots of supervised data and then it must succeed because we can find the best neural network and then there's also theory that if you have more data than parameters you won't overfit today we know that actually this theory is very incomplete and you want overfitting when you have less data than parameters but definitely if you have more data than parameters you want overfit so the fact that neural networks were heavily over parametrized wasn't discouraging to you so you you were thinking about the theory that the number of parameters the fact there's a huge number of parameters is okay it's gonna be okay i mean there was some evidence before that it was okayish but the theory was most the theory was that if you had a big data set and a big neural net it was going to work the over parameterization just didn't really um figure much as a problem i thought well with images you're just going to add some data augmentation it's going to be okay so where was any doubt coming from the main doubt was can we train a bigger will we have enough computer trainer big enough neural net with back propagation back propagation i thought would work this image wasn't clear would was whether there would be enough compute to get a very convincing result and then at some point alex krajewski wrote these insanely fast gooda kernels for training convolutional neural nets and that was bam let's do this let's get imaging that and it's going to be the greatest thing was your intuition most of your intuition from empirical results by you and by others so like just actually demonstrating that a piece of program can train a 10-layer neural network or was there some pen and paper or marker and white board thinking intuition like because you just connected a 10 layer large neural network to the brain so you just mentioned the brain so in your intuition about neural networks does the human brain come into play as a intuition builder definitely i mean you you know you got to be precise with these analogies between neural artificial neural networks in the brain but there is no question that the brain is a huge source of intuition and inspiration for deep learning researchers since all the way from rosenblatt in the 60s like if you look at the the whole idea of a neural network is directly inspired by the brain you had people like mccollum and pitts who were saying hey you got this these neurons in the brain and hey we recently learned about the computer and automata can we use some ideas from the computer and automata to design some kind of computational object that's going to be simple computational and kind of like the brain and they invented the neuron so they were inspired by it back then then you had the convolutional neural network from fukushima and then later yeah khan who said hey if you limit the receptive fields of a neural network it's going to be especially suitable for images as it turned out to be true so there was there was a very small number of examples where analogies to the brain were successful and i thought well probably an artificial neuron is not that different from the brain if it's queen hard enough so let's just assume it is and roll with it so no we're now at a time where deep learning is very successful so let us squint less and say let's uh open our eyes and say what to use an interesting difference between the human brain now i know you're probably not an expert neither in your scientist and your biologist but loosely speaking what's the difference between the human brain and artificial neural networks that's interesting to you for the next decade or two that's a good question to ask what is in what is an interesting difference between the neurons between the brain and our artificial neural networks so i feel like today artificial neural networks so we all agree that there are certain dimensions in which the human brain vastly outperforms our models but i also think that there are some ways in which artificial neural networks have a number of very important advantages over the brain look looking at the advantages versus disadvantages is a good way to figure out what is the important difference so the brain uses spikes which may or may not be important yeah that's a really interesting question do you think it's important or not that's one big architectural difference between artificial neural networks and it's hard to tell but my prior is not very high and i can i can say why you know there are people who are interested in spiking neural networks and basically what they figured out is that they need to simulate the non-spiking neural networks in spikes and that's how they're gonna make them work if you don't simulate the non-spike in neural networks in spikes it's not going to work because the question is why should it work and that connects to questions around back propagation and questions around deep learning you got this giant neural network why should it work at all why should the learning rule work at all it's not a self-evident question especially if you let's say if you were just starting in the field and you read the very early papers you can say hey people are saying let's build neural networks that's a great idea because the brain is a neural network so it would be useful to build neural networks now let's figure out how to train them it should be possible to train them properly but how and so the big idea is the cost function that's the big idea the cost function is a way of measuring the performance of the system according to some measure by the way that is a big actually let me think is that is that uh one a difficult idea to arrive at and how big of an idea is that that there's a single cost function let me sorry let me take a pause is supervised learning a difficult concept to come to i don't know all concepts are very easy in retrospect yeah that's what it seems trivial now but i so because because the reason i asked that and we'll talk about it because is there other things is there things that don't necessarily have a cost function maybe have many cost functions or maybe have dynamic cost functions or maybe a totally different kind of architectures because we have to think like that in order to arrive at something new right so the only so the good examples of things which don't have clear cost functions are gans again you have a game so instead of thinking of a cost function where you want to optimize where you know that you have an algorithm gradient descent which will optimize the cost function and then you can reason about the behavior of your system in terms of what it optimizes with again you say i have a game and i'll reason about the behavior of the system in terms of the equilibrium of the game but it's all about coming up with these mathematical objects that help us reason about the behavior of our system right that's really interesting yes again is the only one it's kind of a com the cost function is emergent from the comparison it's i don't i don't know if it has a cost function i don't know if it's meaningful to talk about the cost function of again it's kind of like the cost function of biological evolution or the cost function of the economy it's you can talk about regions to which it will go towards but i don't think i don't think the cost function analogy is the most useful so if evolution doesn't that's really interesting so if evolution doesn't really have a cost function like a cost function based on its something akin to our mathematical conception of a cost function then do you think cost functions in deep learning are holding us back yeah i so you just kind of mentioned that cost function is a nice first profound idea do you think that's a good idea do you think it's an idea will go past so self-play starts to touch on that a little bit uh in reinforcement learning systems that's right self-play and also ideas around exploration where you're trying to take action that surprise a predictor i'm a big fan of cos functions i think cost functions are great and they serve us really well and i think that whenever we can do things because with cost functions we should and you know maybe there is a chance that we will come up with some yet another profound way of looking at things that will involve cost functions in a less central way but i don't know i think cost functions are i mean i would not better guess against cost functions is there other things about the brain that pop into your mind that might be different and interesting for us to consider in designing artificial neural networks so we talked about spiking a little bit i mean one one thing which may potentially be useful i think people neuroscientists figured out something about the learning rule of the brain or i'm talking about spike time independent elasticity and it would be nice if some people were to study that in simulation wait sorry spike time independent plasticity yeah what's that std it's a particular learning rule that uses spike timing to figure out how to to determine how to update the synapses so it's kind of like if the synapse fires into the neuron before the neuron fires then it strengthens the synapse and if the synapse fires into the neurons shortly after the neuron fire then it weakens the synapse something along this line i'm 90 sure it's right so if i said something wrong here don't don't get too angry but you sounded brilliant while saying it but the timing that's one thing that's missing the the temporal dynamics is not captured i think that's like a fundamental property of the brain is the timing of this of the signals well your recurrent neural networks but you you think of that as i mean that's a very crude simplified uh what's that called uh there's a clock i guess to uh recurring neural networks it's this it seems like the brain is the general the continuous version of that the the generalization where all possible timings are possible and then within those timings this contains some information you think recurrent neural networks the recurrence in recurrent neural networks can capture the same kind of phenomena as the timing that seems to be important for the brain in the in the firing of neurons in the brain i i mean i think i think regarding neurons recurrent neural networks are amazing and they can do i think they can do anything we'd want them to if we'd want a system to do right now recurrent neural networks have been superseded by transformers but maybe one day they'll make a comeback maybe they'll be back we'll see let me uh in a small tangent say do you think they'll be back so so much of the breakthroughs recently that we'll talk about on uh natural language processing and language modeling has been with transformers that don't emphasize your currents do you think recurrence will make a comeback well some kind of recurrence i think very likely recurrent neural networks for pros as they're typically thought of for processing sequences i think it's also possible what is to you a recurrent neural network and generally speaking i guess what is a recurrent neural network you have a neural network which maintains a high dimensional hidden state and then when an observation arrives it updates its high dimensional hidden state through its connections in some way so do you think you know that's what like expert systems did right symbolic ai uh the knowledge based growing a knowledge base is is maintaining a hidden state which is its knowledge base and is growing it by sequential processing do you think of it more generally in that way or is it simply is it the more constrained form that of of a hidden state with certain kind of gating units that we think of as today with lstms and that i mean the hidden state is technically what you described there the hidden state that goes inside the lstm or the rnn or something like this but then what should be contained you know if you want to make the expert system um analogy i'm not i mean you could say that the knowledge is stored in the connections and then the short term processing is done in the in the hidden state yes could you say that yeah so sort of do you think there's a future of building large scale knowledge bases within the neural networks definitely so we're going to pause on that confidence because i want to explore that well let me zoom back out and ask back to the history of imagenet neural networks have been around for many decades as you mentioned what do you think were the key ideas that led to their success that image in that moment and beyond the success in the past 10 years okay so the question is to make sure i didn't miss anything the key ideas that led to the success of deep learning over the past 10 years exactly even though the fundamental thing behind deep learning has been around for much longer so the key idea about deep learning or rather the key fact about deep learning before deep learning started to be successful is that it was underestimated people who worked in machine learning simply didn't think that neural networks could do much people didn't believe that large neural networks could be trained people thought that well there was lots of there was a lot of debate going on in machine learning about what are the right methods and so on and people were arguing because there were no there were there were no there was no way to get hard facts and by that i mean there were no benchmarks which were truly hard that if you do really well in them then you can say look here is my system that's when you switch from that's when this field becomes a little bit more of an engineering field so in terms of deep learning to answer the question directly the ideas were all there the thing that was missing was a lot of supervised data and a lot of compute once you have a lot of supervised data and a lot of compute then there is a third thing which is needed as well and that is conviction conviction that if you take the right stuff which already exists and apply and mix it with a lot of data and a lot of compute that it will in fact work and so that was the missing piece it was you had the you need the data you needed the compute which showed up in terms of gpus and you needed the conviction to realize that you need to mix them together so that's really interesting so uh i i guess the presence of compute and the present supervised data allowed the empirical evidence to do the convincing of the majority of the computer science community so i guess there was a key moment with uh jitendra malik and uh alex alyosha afros who were very skeptical right and then there's a jeffrey hinton that was the opposite of skeptical and there was a convincing moment and i think emission had served as that moment that's right and they represented this kind of were the big pillars of computer vision community kind of the the wizards got together and then all of a sudden there was a shift and it's not enough for the ideas to all be there and the computer to be there it's for it to convince the cynicism that existed that it's interesting that people just didn't believe for a couple of decades yeah well but it's more than that it's kind of been put this way it sounds like well you know those silly people who didn't believe what were they what were they missing but in reality things were confusing because neural networks really did not work on anything and they were not the best method on pretty much anything as well and it was pretty rational to say yeah this stuff doesn't have any traction and that's why you need to have these very hard tasks which are which produce undeniable evidence and that's how we make progress and that's why the field is making progress today because we have these hard benchmarks which represent true progress and so and this is why we are able to avoid endless debate so incredibly you've contributed some of the biggest recent ideas in ai in in computer vision language natural language processing reinforcement learning sort of everything in between maybe not gans is there there may not be a topic you haven't touched and of course the the fundamental science of deep learning what is the difference to you between vision language and as in reinforcement learning action as learning problems and what are the commonalities do you see them as all interconnected are they fundamentally different domains that require different approaches okay that's a good question machine learning is a field with a lot of unity a huge amount of unity what do you mean by unity like overlap of ideas overlap of ideas overlap of principles in fact there is only one or two or three principles which are very very simple and then they apply in almost the same way in almost the same way to the different modalities to the different problems and that's why today when someone writes a paper on improving optimization of deep learning and vision it improves the different nlp applications and it improves the different reinforcement learning applications reinforcement learn so i would say that computer vision and nlp are very similar to each other today they differ in that they have slightly different architectures we use transformers in nlp and use convolutional neural networks in vision but it's also possible that one day this will change and everything will be unified with a single architecture because if you go back a few years ago in natural language processing there were a huge number of architectures for every different tiny problem had its own architecture today this is just one transformer for all those different tasks and if you go back in time even more you had even more and more fragmentation and every little problem in ai had its own little sub specialization and sub you know little set of collection of skills people who would know how to engineer the features now it's all been subsumed by deep learning we have this unification and so i expect vision to become unified with natural language as well or rather i shouldn't say expect i think it's possible i don't want to be too sure because i think on the commercial neural net is very computationally efficient rl is different rl does require slightly different techniques because you really do need to take action you really do need to do something about exploration your variance is much higher but i think there is a lot of unity even there and i would expect for example that at some point there will be some broader unification between rl and supervised learning where somehow the rl will be making decisions to make the supervised learning go better and it will be i imagine one big black box and you just throw every you know you shovel travel things into it and it just figures out what to do with whatever you shovel it i mean reinforcement learning has some aspects of language and vision combined almost there's elements of a long-term memory that you should be utilizing and there's elements of a really rich sensory space so it seems like the it's like the union of the two or something like that i'd say something slightly differently i'd say that reinforcement learning is neither but it naturally interfaces and integrates with the two of them do you think action is fundamentally different so yeah what is interesting about what is unique about policy of learning to act well so one example for instance is that when you learn to act you are fundamentally in a non-stationary world because as your actions change the things you see start changing you you experience the world in a different way and this is not the case for the more traditional static problem where you have at least some distribution and you just apply a model to that distribution do you think it's a fundamentally different problem or is it just a more difficult general it's a generalization of the problem of understanding i mean it's it's it's a question of definitions almost there is a huge you know there's a huge amount of commonality for sure you take gradients you try you take gradients we try to approximate gradients in both cases in some get in the case of reinforcement learning you have some tools to reduce the variance of the gradients you do that there's lots of commonality use the same neural net in both cases you compute the gradient you apply atom in both cases so i mean there's lots in common for sure but there are some small differences which are not completely insignificant it's really just a matter of your point of view what frame of reference you what how much do you want to zoom in or out as you look at these problems which problem do you think is harder so people like no chomsky believe that language is fundamental to everything so it underlies everything do you think language understanding is harder than visual scene understanding or vice versa i think that asking if a problem is hard is slightly wrong i think the question is a little bit wrong and i want to explain why so what does it mean for a problem to be hard okay the non-interesting dumb answer to that is there's this there's a benchmark and there's a human level performance on that benchmark and how there's the effort required to reach the human level okay benchmark so from the perspective of how much until we get to human level on a very good benchmark yeah like some i i understand what you mean by that so what i was going i'm going to say that a lot of it depends on you know once you solve a problem it stops being hard and that's all that's always true and so whether something is hard or not depends on what our tools can do today so you know you say today true human level language understanding and visual perception are hard in the sense that there is no way of solving the problem completely in the next three months right so i agree with that statement beyond that i'm just i'll be my my guess would be as good as yours i don't know oh okay so you don't have a fundamental intuition about how hard language understanding is i think i i know i changed my mind let's say language is probably going to be harder i mean it depends on how you define it like if you mean absolute top-notch 100 language understanding i'll go with language so but then if i show you a piece of paper with letters on it is that you see what i mean it's uh you have a vision system you say it's the best human level vision system i show you i open a book and i show you letters will it understand how these letters form into words and sentences and meaning is this part of the vision problem where does vision end and language begin yeah so chomsky would say it starts at language so vision is just a little example of the kind of uh structure and you know fundamental hierarchy of ideas that's already represented in our brain somehow that's represented through language but where does vision stop and language begin that's a really interesting question it so one possibility is that it's impossible to achieve really deep understanding in either images or language without basically using the same kind of system so you're going to get the other for free i think i think it's pretty likely that yes if we can get one we prob our machine learning is probably that good that we can get the other but it's not 100 i'm not 100 sure and also i think a lot a lot of it really does depend on your definitions definitions of like perfect vision because really you know reading is vision but should it count yeah to me so my definition is if a system looked at an image and then the system looked at a piece of text and then told me something about that and i was really impressed that's relative you'll be impressed for half an hour and then you're gonna say well i mean all the systems do that but here's the thing they don't do yeah but i don't have that with humans humans continue to impress me is that true well the ones okay so i'm a fan of monogamy so i like the idea of marrying somebody being with them for several decades so i i believe in the fact that yes it's possible to have somebody continuously giving you uh pleasurable interesting witty new ideas friends yeah i think i think so they continue to surprise you the surprise it's um you know that injection of randomness seems to be uh it seems to be a nice source of yeah continued uh inspiration like the the wit the humor i think yeah that that the that would be a it's a very subjective test but i think if you have enough humans in the room yeah i i understand what you mean yeah i feel like i i misunderstood what you meant by impressing you i thought you meant to impress you with its intelligence with how how with how good well it understands um an image i thought you meant something like i'm going to show it a really complicated image and it's going to get it right and you're going to say wow that's really cool systems of you know january 2020 have not been doing that yeah no i i think it all boils down to like the reason people click like on stuff on the internet which is like it makes them laugh so it's like humor or wit yeah or insight i'm sure we'll get it as get that as well so forgive the romanticized question but looking back to you what is the most beautiful or surprising idea in deep learning or ai in general you've come across so i think the most beautiful thing about deep learning is that it actually works and i mean it because you got these ideas you got the little neural network you got the back propagation algorithm and then you got some theories as to you know this is kind of like the brain so maybe if you make it large if you make the neural network lodge and you train it a lot of data then it will do the same function of the brain does and it turns out to be true that's crazy and now we just train these neural networks and you make them larger and they keep getting better and i find it unbelievable i find it unbelievable that this whole ai stuff with neural networks works have you built up an intuition of why are there little bits and pieces of intuitions of insights of why this whole thing works i mean sums definitely while we know that optimization we now have good you know we've take we've had lots of empirical you know huge amounts of empirical reasons to believe that optimization should work on all most problems we care about did you have insights of what so you just said empirical evidence is most of your sort of empirical evidence kind of convinces you it's like evolution is empirical it shows you that look this evolutionary process seems to be a good way to design organisms that survive in their environment but it doesn't really get you to the insides of how the whole thing works i think it's a good analogy is physics you know how you say hey let's do some physics calculation and come up with some new physics theory and make some prediction but then you gotta run the experiment you know you gotta run the experiment it's important so it's a bit the same here except that maybe some sometimes the experiment came before the theory but it still is the case you know you have some data and you come up with some prediction you say yeah let's make a big neural network let's train it and it's going to work much better than anything before it and it will in fact continue to get better as you make it larger and it turns out to be true that's that's amazing when a theory is validated like this you know it's not a mathematical theory it's more of a biological theory almost so i think there are not terrible analogies between deep learning and biology i would say it's like the geometric mean of biology and physics that's deep learning the geometric meaning of biology and physics i think i'm going to need a few hours to wrap my head around that because just to find the geometric just to find uh the set of what biology represents well biology in biology things are really complicated theories are really really it's really hard to have good predictive theory and if in physics the theories are too good in theory in physics people make these super precise theories which make these amazing predictions and in machine learning mechanics in between kind of in between but it'd be nice if machine learning somehow helped us discover the unification of the two as opposed to some of the in-between but you're right that's you're you're kind of trying to juggle both so do you think there's still beautiful and mysterious properties in your networks that are yet to be discovered definitely i think that we are still massively underestimating deep learning what do you think it will look like like what if i knew i would have done it yeah so uh but if you look at all the progress from the past 10 years i would say most of it i would say there have been a few cases where some were things that felt like really new ideas showed up but by and large it was every year we thought okay deep learning goes this far nope it actually goes further and then the next year okay now you now this is this is peak deep learning we are really done nope goes further it just keeps going further each year so that means that we keep underestimating we keep not understanding it as surprising properties all the time do you think it's getting harder and harder to make progress need to make progress it depends on what we mean i think the field will continue to make very robust progress for quite a while i think for individual researchers especially people who are doing um research it can be harder because there is a very large number of researchers right now i think that if you have a lot of compute then you can make a lot of very interesting discoveries but then you have to deal with the challenge of managing a huge compute a huge classic compute cluster trying to experiment so it's a little bit harder so i'm asking all these questions that nobody knows the answer to but you're one of the smartest people i know so i'm going to keep asking the so let's imagine all the breakthroughs that happen in the next 30 years in deep learning do you think most of those breakthroughs can be done by one person with one computer sort of in the space of breakthroughs do you think compute will be compute and large efforts will be necessary i mean i can't be sure when you say one computer you mean how large uh you're uh you're clever i mean one can one gpu i see i think it's pretty unlikely i think it's pretty unlikely i think that there are many the stack of deep learning is starting to be quite deep if you look at it you've got all the way from the ideas the systems to build the data sets the distributed programming the building the actual cluster the gpu programming putting it all together so now the stack is getting really deep and i think it becomes it can be quite hard for a single person to become to be world class in every single layer of the stack what about the what like vladimir vapnik really insist on is taking mnist and trying to learn from very few examples so being able to learn more efficiently do you think that's there'll be breakthroughs in that space that would may not need the huge compute i think it will be a very i think there will be a large number of breakthroughs in general that will not need a huge amount of compute so maybe i should clarify that i think that some breakthroughs will require a lot of compute and i think building systems which actually do things will require a huge amount of compute that one is pretty obvious if you want to do x right an x requires a huge neural net you got to get a huge neural net but i think there will be lots of i think there is lots of room for very important work being done by small groups and individuals you may be sort of on the topic of the the science of deep learning talk about one of the recent papers that you released sure that deep double descent where bigger models and more data hurt i think it's really interesting paper can you can you describe the main idea and yeah definitely so what happened is that some over over the years some small number of researchers noticed that it is kind of weird that when you make the neural network larger it works better and it seems to go in contradiction with statistical ideas and then some people made an analysis showing that actually you got this double descent bump and what we've done was to show that double descent occurs for all for pretty much all practical deep learning systems and that it'll be also so can you step back uh what's the x-axis and the y-axis of a double descent plot okay great so you can you can look you can do things like you can take a neural network and you can start increasing its size slowly while keeping your data set fixed so if you increase the size of the neural network slowly and if you don't do early stopping that's a pretty important detail then when the neural network is really small you make it larger you get a very rapid increase in performance then you continue to make it large and at some point performance will get worse and it gets and and it gets the worst exactly at the point at which it achieves zero training error precisely zero training loss and then as you make it large it starts to get better again and it's kind of counter-intuitive because you'd expect deep learning phenomena to be monotonic and it's hard to be sure what it means but it also occurs in in the case of linear classifiers and the intuition basically boils down to the following when you when you have a lot when you have a large data set and a small model then small tiny random so basically what is overfitting overfitting is when your model is somehow very sensitive to the small random unimportant stuff in your data set in a training day in the training data set precisely so if you have a small model and you have a big data set and there may be some random thing you know some training cases are randomly in the data set and others may not be there but the small mod but the small model is kind of insensitive to this randomness because it's the same you there is pretty much no uncertainty about the model when it is that it's large so okay so at the very basic level to me it is the most surprising thing that neural networks don't overfit every time very quickly uh before ever being able to learn anything the huge number of parameters so here so there is one way okay so maybe so let me try to give the explanation maybe that will be that will work so you got a huge neural network let's suppose you've got a you are you have a huge neural network you have a huge number of parameters and now let's pretend everything is linear which is not let's just pretend then there is this big subspace where a neural network achieves zero error and sdgt is going to find approximately the point that's right approximately the point with the smallest norm in that subspace okay and that can also be proven to be insensitive to the small randomness in the data when the dimensionality is high but when the dimensionality of the data is equal to the dimensionality of the model then there is a one-to-one correspondence between all the data sets and the models so small changes in the data set actually lead to large changes in the model and that's why performance gets worse so this is the best explanation more or less so then it would be good for the model to have more parameters so to be bigger than the data that's right but only if you don't really stop if you introduce early stop in your regularization you can make the double asset descent bump almost completely disappear what is early stop early stopping is when you train your model and you monitor your test your validation performance and then if at some point validation performance starts to get worse you say okay let's stop training if you're good you're good you're good enough so the the magic happens after after that moment so you don't want to do the early stopping well if you don't do the early stop and you get this very you get a very pronounced double descent do you have any intuition why this happens double descent oh sorry are you stopping you no the double descend so that oh yeah so i try let's see the intuition is basically is this that when the data set has as many degrees of freedom as the model then there is a one-to-one correspondence between them and so small changes to the data set lead to noticeable changes in the model so your model is very sensitive to all the randomness it is unable to discard it whereas it turns out that when you have a lot more data than parameters or a lot more parameters than data the resulting solution will be insensitive to small changes in the data set so it's able to that's nicely put discard the small changes the the randomness exactly the the the spurious correlation which you don't want jeff hinton suggested we need to throw back propagation we already kind of talked about this a little bit but he suggested that we just throw away back propagation and start over i mean of course some of that is a little bit um and humor but what do you think what could be an alternative method of training neural networks well the thing that he said precisely is that to the extent you can't find back propagation in the brain it's worth seeing if we can learn something from how the brain learns but back propagation is very useful and we should keep using it oh you're saying that once we discover the mechanism of learning in the brain or any aspects of that mechanism we should also try to implement that in neural networks if it turns out that we can't find back propagation in the brain if we can't find bad propagation in the brain well so i guess your answer to that is back propagation is pretty damn useful so why are we complaining i mean i i personally am a big fan of back propagation i think it's a great algorithm because it solves an extremely fundamental problem which is finding a neural circuit subject to some constraints and i don't see that problem going away so that's why i i really i think it's pretty unlikely that we'll have anything which is going to be dramatically different it could happen but i wouldn't bet on it right now so let me ask a sort of big picture question do you think can do you think neural networks can be made to reason why not well if you look for example at alphago or alpha zero the neural network of alpha zero plays go which which we all agree is a game that requires reasoning better than 99.9 of all humans just the neural network without this search just the neural network itself doesn't that give us an existence proof that neural networks can reason to push back and disagree a little bit we all agree that go is reasoning i think i i agree i don't think it's a trivial so obviously reasoning like intelligence is uh is a loose gray area term a little bit maybe you disagree with that but yes i think it has some of the same elements of reasoning reasoning is almost like akin to search right there's a sequential element of stepwise consideration of possibilities and sort of building on top of those possibilities in a sequential manner until you arrive at some insight so yeah i guess playing go is kind of like that and when you have a single neural network doing that without search that's kind of like that so there's an existent proof in a particular constrained environment that a process akin to what many people call reasoning exist but more general kind of reasoning so off the board there is one other existence oh boy which one us humans yes okay all right so do you think the architecture that will allow neural networks to reason will look similar to the neural network architectures we have today i think it will i think well i don't want to make two overly definitive statements i think it's definitely possible that the neural networks that will produce the reasoning breakthroughs of the future will be very similar to the architectures that exist today maybe a little bit more current maybe a little bit deeper but but these these new lines are so insanely powerful why wouldn't they be able to learn to reason humans can reason so why can't neural networks so do you think the kind of stuff we've seen neural networks do is a kind of just weak reasoning so it's not a fundamentally different process again this is stuff we don't nobody knows the answer to so when it comes to our neural networks i would think which i would say is that neural networks are capable of reasoning but if you train a neural network on a task which doesn't require reasoning it's not going to reason this is a well-known effect where the neural network will solve exactly the it will solve the problem that you pose in front of it in the easiest way possible right that takes us to the to one of the brilliant sort of ways you describe neural networks which is uh you refer to neural networks as the search for small circuits and maybe general intelligence as the search for small programs which i found is a metaphor very compelling can you elaborate on that difference yeah so the thing which i said precisely was that if you can find the shortest program that outputs the data in you at your disposal then you will be able to use it to make the best prediction possible and that's a theoretical statement which can be proven mathematically now you can also prove mathematically that it is that finding the shortest program which generates some data is not it's not a computable operation no a finite amount of compute can do this so then with neural networks neural networks are the next best stain that actually works in practice we are not able to find the best the shortest program which generates our data but we are able to find you know a small but now now that statement should be amended even a large circuit which fits our data in some way well i think what you meant by this small circuit is the smallest needed circuit well i see the thing the thing which i would change now back back then i really have i haven't fully internalized the over parameter the over parameterized results the the things we know about over parameters neural nets now i would phrase it as a large circuit that con whose weights contain a small amount of information which i think is what's going on if you imagine the training process of a neural network as you slowly transmit entropy from the data set to the parameters then somehow the amount of information in the weights ends up being not very large which would explain why they generalized so well so that's that the large circuit might be one that's helpful for the regulation for the generalization yeah some of this but do you see their do you see it important to be able to try to learn something like programs i mean if you can definitely i think it's kind of the answer is kind of yes if we can do it we should do things that we can do it it's it's the reason we are pushing on deep learning the fundamental reason the cause the the root cause is that we are able to train them so in other words training comes first we've got our pillar which is the training pillar and now we are trying to contort our neural networks around the training pillar we got to stay trainable this is an invo this is an invariant we cannot violate and so being trainable means starting from scratch knowing nothing you can actually pretty quickly converge towards knowing a lot or even slowly but it means that given the resources at your disposal you can train the neural net and get it to achieve useful performance yeah that's a pillar we can't move away from that's right because if you can whereas if you say hey let's find the shortest program but we can't do that so it doesn't matter how useful that would be we can't do it so we want so do you think you kind of mentioned that the neural networks are good at finding small circuits or large circuits do you think then the matter of finding small programs is just the data no so the sorry not not the size or character the qual the the type of data sort of ask giving it programs well i think the thing is that right now finding there are no good precedence of people successfully finding programs really well and so the way you'd find programs is you'd train a deep neural network to do it basically right which is which is the right way to go about it but there's not good uh illustrations that it has hasn't been done yet but in principle it should be possible can you elaborate in a little bit you what's your insight in principle and put another way you don't see why it's not possible well it's kind of like more it's more a statement of i think that it's i think that it's unwise to bet against deep learning and if it's a if it's a cognitive function that humans seem to be able to do then it doesn't take too long for some deep neural net to pop up that can do it too yeah i'm i'm i'm there with you i can i've i've stopped betting against neural networks at this point because they continue to surprise us what about long-term memory can neural networks have long-term memory or something like knowledge bases so being able to aggregate important information over long periods of time that would then serve as useful sort of representations of state that uh you can make decisions by so have a long-term context based on what you make in the decision so in some sense the parameters already do that the parameters are an aggregation of the day of the neural of the entirety of the neural nets experience and so they count as the long as long form long-term knowledge and people have trained various neural nets to act as knowledge bases and you know investigated with invest people have investigated language tomorrow's knowledge basis so there is work there is work there yeah but in some sense do you think in every sense do you think there's a it's it's all just a a matter of coming up with a better mechanism of forgetting the useless stuff and remembering the useful stuff because right now i mean there's not been mechanisms that do remember really long-term information what do you mean by that precisely i like i like the word precisely so i'm thinking of the kind of compression of information the knowledge bases represent sort of creating a now i apologize for my sort of human-centric thinking about what knowledge is because neural networks aren't interpretable necessarily with the kind of knowledge they have discovered but a good example for me is knowledge bases being able to build up over time something like the knowledge that wikipedia represents it's a really compressed structured knowledge base obviously not the actual wikipedia or the language but like a semantic web the dream that semantic web represented so it's a really nice compressed knowledge base or something akin to that in the non-interpretable sense as neural networks would have well the neural networks would be non-interpretable if you look at their weights but their outputs should be very interpretable okay so yeah how do you make very smart neural networks like language models interpretable well you ask them to generate some text then the text will generally be interpretable do you find that the epitome of interpretability like can you do better like can you uh because you can't okay i'd like to know what does it know and what doesn't know i would like the neural network to come up with examples where it it's completely dumb and examples where it's completely brilliant and the only way i know how to do that now is to generate a lot of examples and use my human judgment but it would be nice if a neonatal had some aware self-awareness about it yeah 100 i'm a big believer in self-awareness and i think that i think i think neural net self-awareness will allow for things like the capabilities like the ones you describe like for them to know what they know and what they don't know and for them to know where to invest to increase their skills most optimally and to your question of interpretability there are actually two answers to that question one answer is you know we have the neural net so we can analyze the neurons and we can try to understand what the different neurons and different layers mean and you can actually do that and openai has done some work on that but there is a different answer which is that i would say this is the human-centric answer where you say you know you look at a human being you can't read you know how how do you know what a human being is think and you ask them you say hey what do you think about this what do you think about that and you get some answers the answers you get are sticky in the sense you already have a mental model you already have an uh yeah mental model of that human being you already have an understanding of like a a big conception of what it of that human being how they think what they know how they see the world and then everything you ask you're adding on to that and that stickiness seems to be that's one of the really interesting qualities of the the human being is that information is sticky you don't you seem to remember the useful stuff aggregate it well and forget most of the information that's not useful that process but that's also pretty similar to the process that neural networks do is just that neural network so much crappier at it at this time it doesn't seem to be fundamentally that different but just to stick on reasoning for a little longer he said why not why can't i reason what's a good impressive feat benchmark to you of reasoning that you'll be impressed by if you don't know what we're able to do is that something you already have in mind well i think writing writing really good code i think proving really hard theorems solving open-ended problems with out-of-the-box solutions and uh sort of theorem type mathematical problems yeah i think though those ones are a very natural example as well you know if you can prove an unproven theorem then it's hard to argue don't reason and so by the way and this comes back to the point about the hard results you know if you got a heart if you have machine learning deep learning as a field is very fortunate because we have the ability to sometimes produce these unambiguous results and when they happen uh the debate changes the conversation changes it's a conversa we have the ability to produce conversation changing results conversation and then of course just like you said people kind of take that for granted and say that wasn't actually a hard problem well i mean at some point we'll probably run out of heart problems yeah that whole mortality thing is kind of kind of a sticky problem that we haven't quite figured out maybe we'll solve that one i think one of the fascinating things in your entire body of work but also the work at open ai recently one of the conversation changers has been in the world of language models can you briefly kind of try to describe the recent history of using neural networks in the domain of language and text well there's been lots of history i think i think the elman network was was this was was a small tiny recurrent neural network applied to language back in the 80s so the history is really you know fairly long at least and the thing that started the thing that changed the trajectory of neural networks and language is the thing that changed the trajectory of deep learning and that's data and compute so suddenly you move from small language models which learn a little bit and with language models in particular you can there's a very clear explanation for why they need to be large to be good because they're trying to predict the next word so we don't when you don't know anything you'll notice very very broad stroke surface level patterns like sometimes there are characters and there is a space between those characters you'll notice this pattern and you'll notice that sometimes there is a comma and then the next character is a capital letter you'll notice that pattern eventually you may start to notice that there are certain words occur often you may notice that spellings are a thing you may notice syntax and when you get really good at all these you start to notice the semantics you start to notice the facts but for that to happen the language model needs to be larger so that's let's linger on that because that's where you and noam chomps could disagree so you think we're actually taking uh incremental steps a sort of larger network larger compute will be able to get to the semantics to be able to understand language without what gnome likes to sort of think of as a fundamental understandings of the structure of language like imposing your theory of language onto the learning mechanism so you're saying the learning you can learn from raw data the mechanism that underlies language well i think i think it's pretty likely but i also want to say that i don't really know precisely what is what chomsky means when he talks about him you said something about imposing your structure and language i'm not 100 sure what he means but empirically it seems that when you inspect those larger language models they exhibit signs of understanding the semantics whereas the smaller language models do not we've seen that a few years ago when we did work on the sentiment neuron we trained the small you know smaller shell stm to predict the next character in amazon reviews and we noticed that when you increase the size of the lstm from 500 lstm cells to 4000 lstm cells then one of the neurons starts to represent the sentiment of the article of story of the review now why is that sentiment is a pretty semantic attribute it's not a syntactic attribute and for people who might not know i don't know if that's a standard term but sentiment is whether it's a positive or negative review that's right like this is the person happy with something is the person unhappy with something and so here we had very clear evidence that a small neural net does not capture sentiment while a large neural net does and why is that well our theory is that at some point you run out of syntax to models you start gotta focus on something else and with size you quickly run out of syntax to model and then you really start to focus on the semantics is would be the idea that's right and so i don't i don't want to imply that our models have complete semantic understanding because that's not true but they definitely are showing signs of semantic understanding partial semantic understanding but the smaller models do not show that those signs can you take a step back and say what is gpt2 which is one of the big language models that was the conversation change in the past couple of years yes it's so gpt-2 is a transformer with one and a half billion parameters that was trained on upon about 40 billion tokens of text which were obtained from web pages that were linked to from reddit articles with more than three upvotes and what's the transformer the transformer is the most important advance in neural network architectures in recent history what is attention maybe too because i think that's the interesting idea not necessarily sort of technically speaking but the idea of attention versus maybe what recurring neural networks represent yeah so the thing is the transformer is a combination of multiple ideas simultaneously which attention is one do you think attention is the key no it's a key but it's not the key the transformer is successful because it is the simultaneous combination of multiple ideas and if you were to remove either idea it would be much less successful so the transformer uses a lot of attention but attention existed for a few years so that can't be the main innovation the transformer is designed in such a way that it runs really fast on the gpu and that makes a huge amount of difference this is one thing the second thing is the transformer is not recurrent and that is really important too because it is more shallow and therefore much easier to optimize so in other words it uses attention it is it is a really great fit to the gpu and it is not recurrent so therefore less deep and easier to optimize and the combination of those factors make it successful so now it makes it makes great use of your gpu it allows you to achieve better results for the same amount of compute and that's why it's successful were you surprised how well transformers worked and gpt2 worked so you worked on language you've had a lot of great ideas before transformers came about in language so you got to see the whole set of revolutions before and after were you surprised yeah a little a little yeah i mean it's hard it's hard to remember because you adapt really quickly but it definitely was surprising it definitely was in fact i'll you know what i'll i'll retract my statement it was it was pretty amazing it was just amazing to see generate this text of this and you know you got to keep in mind that we've seen at that time we've seen all this progress in gans in improving you know the samples produced by cans were just amazing you have these realistic faces but text hasn't really moved that much and suddenly we moved from you know whatever gans were in 2015 to the best most amazing gans in one step right and i was really stunning even though theory predicted yeah you train a big language model of course you should get this but then to see it with your own eyes it's something else and yet we adapt really quickly and now there's uh sort of some cognitive scientists write articles saying that gpt2 models don't truly understand language so we adapt quickly to how amazing the fact that they're able to model the language so well is so what do you think is the bar for what for impressing us that it i don't know do you think that bar will continuously be moved definitely i i think when you start to see really dramatic economic impact that's when i think that's in some sense the next barrier because right now if you think about the working ai it's really confusing it's really hard to know what to make of all these advances it's kind of like okay you got an advance and now you can do more things and you got another improvement and you got another cool demo at some point i think people who are outside of ai they can no longer distinguish this progress anymore so we were talking offline about translating russian to english and how there's a lot of brilliant work in russian that the the rest of the world doesn't know about that's true for chinese that's true for a lot of for a lot of scientists and just artistic work in general do you think translation is the place where we're going to see sort of economic big impact i i don't know i i think i think there is a huge number of i mean first of all i would want to i want to point out the translation already today is huge i think billions of people interact with uh big chunks of the internet primarily through translation so translation is already huge and it's hugely hugely positive too i think self-driving is going to be hugely impactful and that's you know it's it's unknown exactly when it happens but again i would i would not bet against deep learning so i so that's deep learning in general but you you keep learning for self-driving yes deep learning for self-driving but i was talking about sort of language models let's see just to ch just spear it off a little bit just to check you're not seeing a connection between driving and language no no okay all right they both use neural nets they'll be a poetic connection i think there might be some like you said there might be some kind of unification towards uh a kind of multi-task transformers that can take on both language and vision tasks that'd be an interesting unification now let's see what can i ask about gpt2 more um it's simple it's not much to ask it's so you take it you take a transform you make it bigger you give it more data and suddenly it does all those amazing things yeah one of the beautiful things is that gpg the transformers are fundamentally simple to explain to train do you think bigger will continue to show better results in language probably sort of like what are the next steps with gpt2 do you think i mean for i think for for sure seeing what uh larger versions can do is one direction also i mean there are there are many questions there's one question which i'm curious about and that's the following so right now gpt2 so we feed all this data from the internet which means that he needs to memorize all those random facts about everything in the internet and it would be nice if the model could somehow use its own intelligence to decide what data it wants to study accept and what data it wants to reject just like people people don't learn all data indiscriminately we are super selective about what we learn and i think this kind of active learning i think would be very nice to have yeah listen i love active learning so let me ask does the selection of data can you just elaborate that a little bit more do you think the selection of data is um like i i have this kind of sense that the optimization of how you select data so the active learning process is going to be a place for a lot of breakthroughs even in the near future because there hasn't been many breakthroughs there that are public i feel like there might be private breakthroughs that companies keep to themselves because the fundamental problem has to be solved if you want to solve self-driving if you want to solve a particular task but do you what do you think about the space in general yeah so i think that for something like active learning or in fact for any kind of capability like active learning the thing that it really needs is a problem it needs a problem that requires it it's very hard to do research about the capability if you don't have a task because then what's going to happen is you will come up with an artificial task get good results but not really convince anyone right like we're now past the stage where getting a result an mnist some clever formulation remnants will will convince people that's right in fact you could quite easily come up with a simple active learning scheme on amnesty and get a 10x speed up but then so what and i think that with active learning their needs they need active learning will naturally arise as there are as problems that require it pop up that's how i would that's my my take on it there's another interesting thing that openai has brought up with gpt2 which is when you create a powerful artificial intelligence system and it was unclear what kind of detrimental once you release gpt2 what kind of detrimental effect it will have because if you have an a model that can generate pretty realistic text you can start to imagine that you know on the it would be used by bots and some some way that we can't even imagine so like there's this nervousness about what it's possible to do so you you did a really kind of brave and i think profound thing which you started a conversation about this like how do we release powerful artificial intelligence models to the public if we do it all how do we privately discuss with other even competitors about how we manage the use of the systems and so on so from that this whole experience you released a report on it but in general are there any insights that you've gathered from just thinking about this about how you release models like this i mean i think that my take on this is that the field of ai has been in a state of childhood and now it's exiting that state and it's entering a state of maturity what that means is that ai is very successful and also very impactful and its impact is not only large but it's also growing and so for that reason it seems wise to start thinking about the impact of our systems before releasing them maybe a little bit too soon rather than a little bit too late and with the case of gpt2 like i mentioned earlier the results really were stunning and it seemed plausible it didn't seem certain it seemed plausible that something like gpt2 could easily use to reduce the cost of this information and so there was a question of what's the best way to release it and staged release seemed logical a small model was released and there was time to see the many people use these models in lots of cool ways they've been lots of really cool applications there haven't been any negative applications we know of and so eventually it was released but also other people replicated similar models that's an interesting question though that we know of so in your view stage release is uh at least part of the answer to the question of how do we uh how what do we do once we create a system like this it's part of the answer yes is there any other insights like say you don't want to release the model at all because it's useful to you for whatever the business is well there are plenty plenty of people don't release models already right of course but is there some moral ethical responsibility when you have a very powerful model to sort of communicate like just as you said when you had gpt2 it was unclear how much it could be used for misinformation it's an open question and getting an answer to that might require that you talk to other really smart people that are outside of uh outside your particular group have you please tell me there's some optimistic pathway for people across the world to collaborate on these kinds of cases or is it still really difficult from from one company to talk to another company so it's definitely possible it's definitely possible to discuss these kind of models with colleagues elsewhere and to get get their take on what's on what to do how hard is it though i mean do you see that happening i think that's that's a place where it's important to gradually build trust between companies because ultimately all the ai developers are building technology which is bitcoin to be increasingly more powerful and so it's the way to think about it is that ultimately we're only together yeah it's uh i tend to believe in the the better angels of our nature but i do hope that um that when you build a really powerful ai system in a particular domain that you also think about the potential negative consequences of um it's an interesting and scary possibility that it'll be a race for a ai development that would push people to close that development and not share ideas with others i don't love this i've been like a pure academic for 10 years i really like sharing ideas and it's fun it's exciting what do you think it takes to let's talk about agi a little bit what do you think it takes to build a system of human level intelligence we talked about reasoning we talked about long-term memory but in general what does it take you think well i can't be sure but i think the deep learning plus maybe another small idea do you think self-play will be involved so like you've spoken about the powerful mechanism of self-play where systems learn by sort of uh exploring the world in a competitive setting against other entities that are similarly skilled as them and so incrementally improve in this way do you think self-play will be a component of building an agi system yeah so what i would say to build agi i think is going to be deep learning plus some ideas and i think self-play will be one of those ideas i think that that is a very self play has this amazing property that it can surprise us in truly novel ways for example like we i mean pretty much every self-play system both are dotabot i don't know if openai had a release about multi-agent where you had two little agents who were playing hide and seek and of course also alpha zero they were all surprising behaviors they all produce behaviors that we didn't expect they are creative solutions to problems and that seems like an important part of agi that our systems don't exhibit routinely right now and so that's why i like this area i like this direction because of its ability to surprise us to surprise us and an agr system would surprise us fundamentally yes but and to be precise not just not just a random surprise but to find a surprising solution to a problem that's also useful right now a lot of the self-play mechanisms have been used in the game context or at least in the simulation context how much how much do you how far along the path to egi do you think will be done in simulation how much faith promise do you have in simulation versus having to have a system that operates in the real world whether it's the real world of digital real world data or real world like actual physical world of robotics i don't think it's an either or i think simulation is a tool and it helps it has certain strengths and certain weaknesses and we should use it yeah but okay i understand that that's um that's true but one of the criticisms of self-play one of the criticisms of reinforcement learning is one of the the its current power its current results while amazing have been demonstrated in a simulated environments or very constrained physical environments do you think it's possible to escape them escape the simulated environments and be able to learn in non-simulated environments or do you think it's possible to also just simulate in the photorealistic and physics realistic way the real world in a way that we can solve real problems with self-play in simulation so i think that transfer from simulation to the real world is definitely possible and has been exhibited many times in by many different groups it's been especially successful in vision also open ai in the summer has demonstrated a robot hand which was trained entirely in simulation in a certain way that allowed for cinderella transfer to occur is this uh for the rubik's cube that's right and i wasn't aware that was trained in simulation it was straining simulation entirely really so what it wasn't in the physical the hand wasn't trained no 100 of the training was done in simulation and the policy that was learned in simulation was trained to be very adaptive so adaptive that when you transfer it could very quickly adapt to the physical to the physical world so the kind of perturbations with the giraffe or whatever the heck it was those weren't were those part of the simulation well the simulation was generally so the simulation was trained to be robust to many different things but not the kind of perturbations we've had in the video so it's never been trained with a glove it's never been trained with a stuffed giraffe so in theory these are novel perturbations correct it's not in theory in practice that those are novel probation well that's okay that's a clean small scale but clean example of a transfer from the simulated world to the to the physical world yeah and i will also say that i expect the transfer capabilities of deep learning to increase in general and the better the transfer capabilities are the more useful simulation will become because then you could take you could experience something in simulation and then learn a moral of the story which you could then carry with you to the real world right as humans do all the time when they play computer games so let me ask sort of an embodied question staying on agi for a sec do you think aj asks us that we need to have a body we need to have some of those human elements of self-awareness consciousness sort of fear of mortalities or self-preservation in the physical space which comes with having a body i think having a body will be useful i don't think it's necessary but i think it's very useful to have a body for sure because you can learn a whole new you you can learn things which cannot be learned without a body but at the same time i think that you can if you don't have a body you could compensate for it and still succeed you think so yes well if there is evidence for this for example there are many people who were born deaf and blind and they were able to compensate for the lack of modalities i'm thinking about helen keller specifically so even if you're not able to physically interact with the world and if you're not able to i mean i actually was getting it maybe let me ask on the more particular i'm not sure if it's connected to having a body or not but the idea of consciousness and a more constrained version of that is self-awareness do you think an egi system should have consciousness it's what we can't define kind of whatever the heck you think consciousness is yeah hard question to answer given how hard it is to find it do you think it's useful to think about i mean it's it's definitely interesting it's fascinating i think it's definitely possible that our assistants will be conscious do you think that's an emergent thing that just comes from do you think consciousness could emerge from the representation that's stored within your networks so like that it naturally just emerges when you become more and more you're able to represent more and more of the world well i'd say i'd make the following argument which is humans are conscious and if you believe that artificial neural nets are sufficiently similar to the brain then there should at least exist artificial neurons you should be conscious too you're leaning on that existence proof pretty heavily okay but it's it's just that that's that's the best answer i can give no i i know i know i know uh there's still an open question if there's not some magic in the brain that we're not i mean i don't mean a non-materialistic magic but that um that the brain might be a lot more complicated and interesting that we give it credit for if that's the case then it should show up and at some point at some point we will find out that we can't continue to make progress but i think i think it's unlikely so we talk about consciousness but let me talk about another poorly defined concept of intelligence again we've talked about reasoning we've talked about memory what do you think is a good test of intelligence for you are you impressed by the test that alan turing formulated with the imitation game of that with natural language is there something in your mind that you will be deeply impressed by if a system was able to do i mean lots of things there's certain there's certain frontiers there is a certain frontier of capabilities today yeah and there exists things outside of that frontier and i would be impressed by any such thing for example i would be impressed by a deep learning system which solves a very pedestrian you know pedestrian task like machine translation or computer vision task or something which never makes mistake a human wouldn't make under any circumstances i think that is something which have not yet been demonstrated and i would find it very impressive yeah so right now they make mistakes and differ they might be more accurate than human beings but they still they make a different set of mistakes so my my i would guess that a lot of the skepticism that some people have about deep learning is when they look at their mistakes and they say well those mistakes they make no sense like if you understood the concept you wouldn't make that mistake and i think that changing that would be would would that would that would inspire me that would be yes this is this this is this is progress yeah that's that's a really nice way to put it but i also just don't like that human instinct to criticize a model is not intelligent that's the same instinct as we do when we criticize any group of creatures as the other because it's very possible that gpt2 is much smarter than human beings and many things that's definitely true it has a lot more breadth of knowledge yes breadth knowledge and even and even perhaps depth on certain topics it's kind of hard to judge what depth means but there's definitely a sense in which humans don't make mistakes that these models do yes the same is applied to autonomous vehicles the same is probably going to continue being applied to a lot of artificial intelligence systems we find this is the annoying this is the process of in the 21st century the process of analyzing the progress of ai is the search for one case where the system fails in a big way where humans would not and then many people writing articles about it and then broadly as a com as a the public generally gets convinced that the system is not intelligent and we like pacify ourselves by thinking it's not intelligent because of this one anecdotal case and this can seems to continue happening yeah i mean there is truth to that though there is people also i'm sure that plenty of people are also extremely impressed by the system that exists today but i think this connects to the earlier point we discussed that it's just confusing to judge progress in ai yeah and you know you have a new robot demonstrating something how impressed should you be and i think that people will start to be impressed once ai starts to really move the needle on the gdp so you're one of the people that might be able to create an agi system here not you but you and open ai if if you do create an ajax system and you get to spend sort of the evening with it him her what would you talk about do you think the very first time first time well the first time i would just i would just ask all kinds of questions and try to make it to get it to make a mistake and i would be amazed that it doesn't make mistakes and just keep keep asking abroad okay what kind of questions do you think would they be factual or would they be personal emotional psychological what do you think all of that bob would you ask for advice definitely i mean why why would i limit myself talking to a system like this now again let me emphasize the fact that you truly are one of the people that might be in the room where this happens so let me ask a sort of a profound question about um i've just talked to a stalin historian i've been talking to a lot of people who are studying power abraham lincoln said nearly all men can stand adversity but if you want to test a man's character give him power i would say the power of the 21st century maybe the 22nd but hopefully the 21st would be the creation of an agi system and the people who have control direct possession and control of the agi system so what do you think after spending that evening having a discussion with the agi system what do you think you would do well the ideal world would like to imagine is one where humanity are like the board the board members of a company where the agi is the ceo so it would be i would like the picture which i would imagine is you have some kind of different entities different countries or cities and the people that live there vote for what the agi that represents them should do and then age other represents them goes and does it i think a picture like that i find very appealing and you could have multiple you would have an agi for a city for a country and there would be it would be trying to in effect take the democratic process to the next level and the board can always fire the ceo essentially press the reset button and say re-randomize the parameters here well let me sort of that's actually okay that's a beautiful vision i think as long as it's possible to con to press the reset button do you think it will always be possible to press the reset button so i think that it's def it's definitely be possible to build so you're talking so the question that i really understand from you is will reveal humans or humans people have control over the ai systems that they built yes and my answer is it's definitely possible to build ai systems which will want to be controlled by their humans wow that's part of their so it's not that just they can't help but be controlled but that's that's um the they exist the one of the objectives of their existence is to be controlled in the same way that human parents generally want to help their children they want their children to succeed it's not a burden for them they are excited to help the children and to feed them and to dress them and to take care of them and i believe with highest conviction that the same will be possible for an agi it will be possible to program an agi to design it in such a way that it will have a similar deep drive that it will be delighted to fulfill and the drive will be to help humans flourish but let me take a step back to that moment where you create the agi system i think this is a really crucial moment and between that moment and the the democratic board members with the agi at the head there has to be a relinquishing of power says george washington despite all the bad things he did one of the big things he did is he relinquished power he first of all didn't want to be president and even when he became president he gave he didn't keep just serving as most dictators do for indefinitely do you see yourself being able to relinquish control over an agi system given how much power you can have over the world at first financial just make a lot of money right and then control by having possession as a gi system i i'd find it trivial to do that i'd find it trivial to relinquish this this kind of i mean you know the the kind of scenario you are describing sounds terrifying to me that's all i would absolutely not want to be in that position do you think you represent the majority or the minority of people in the ai community well i mean open question an important one are most people good is another way to ask it so i don't know if most people are good but i think that when it really counts people can be better than we think that's beautifully put yeah are there specific mechanisms you can think of of aligning aig and values to human values is that do you think about these problems of continued alignment as we develop the eye systems yeah definitely in some sense the kind of question which you are asking is so if you have to translate that question to today's terms yes it would be a question about how to get an rl agent that's optimizing a value function which itself is learned and if you look at humans humans are like that because the reward function the value function of humans is not external it is internal that's right and there are definite ideas of how to train a value function basically an objective you know and as objective as possible perception system that will be trained separately to recognize to internalize human judgments on different situations and then that component would then be integrated as the value as the base value function for some more capable rail system you could imagine a process like this i'm not saying this is the process i'm saying this is an example of the kind of thing you could do so on that topic of the objective functions of human existence what do you think is the objective function that is implicit in human existence what's the meaning of life oh i think the question is is wrong in some way i think that the question implies that the reason there is an objective answer which is an external answer you know your meaning of life is x right i think what's going on is that we exist and that's amazing and we should try to make the most of it and try to maximize our own value and enjoyment of a very short time while we do exist it's funny because action does require an objective function it's definitely theirs in some form but it's difficult to make it explicit and maybe impossible to make it explicit i guess is what you're getting at and that's an interesting fact of an rl environment well but i was making a slightly different point is that humans want things and their ones create the drives that cause them to you know our wants are our objective functions our individual objective functions we can later decide that we want to change that what we wanted before is no longer good and we want something else yeah but they're so dynamic there's there's got to be some underlying sort of freud there's things there's like sexual stuff there's people who think it's the fear of fear of death and there's also the desire for knowledge and you know all these kinds of things procreation the sort of all the evolutionary arguments it seems to be there might be some kind of fundamental objective function from from which everything else uh emerges but it seems because that's very important i think i think that probably is an evolutionary objective function which is to survive and procreate and make sure you make your children succeed that would be my guess but it doesn't give an answer to the question what's the meaning of life i think you can see how humans are part of this big process this ancient process we are we are we exist on a small planet and that's it so given that we exist try to make the most of it and try to enjoy more and suffer less as much as we can let me ask two silly questions about life one do you have regrets moments that if you uh went back you would do differently and two are there moments that you're especially proud of that made you truly happy so i can answer that i can answer both questions of course there are there's a huge number of choices and decisions that i've made that with the benefit of hindsight i wouldn't have made them and i do experience some regret but you know i try to take solace in the knowledge that at the time i did the best i could and in terms of things that i'm proud of there are i'm very fortunate to have things i'm proud to have done things i'm proud of and they made me happy for himself for some time but i don't think that that is the source of happiness so your academic accomplishments all the papers you're one of the most excited people in the world all the breakthroughs i mentioned in computer vision and language and so on is what is the source of happiness and pride for you i mean all those things are a source of pride for sure i'm very ungrateful for having done all those things and it was very fun to do them but happiness comes from but you know you can happiness well my current view is that happiness comes from our to allow to a very large degree from the way we look at things you know you can have a simple meal and be quite happy as a result or you can talk to someone and be happy as a result as well or conversely you can have a meal and be disappointed that the meal wasn't a better meal so i think a lot of happiness comes from that but i'm not sure i don't want to be too confident i being humble in the face of the uncertainty seems to be also a part of this whole happiness thing well i don't think there's a better way to end it than uh meaning of life and discussions of happiness so ilya thank you so much you've given me a few incredible ideas you've given the world many incredible ideas i really appreciate it and thanks for talking today yeah thanks for stopping stopping by i really enjoyed it thanks for listening to this conversation with elias discoverer and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast if you enjoy this podcast subscribe on youtube review it with 5 stars in apple podcast support on patreon or simply connect with me on twitter at lex friedman and now let me leave you with some words from alan turing on machine learning instead of trying to produce a program to simulate the adult mind why not rather try to produce one which simulates the child's if this were then subjected to an appropriate course of education one would obtain the adult brain thank you for listening and hope to see you next time |
Daphne Koller: Biomedicine and Machine Learning | Lex Fridman Podcast #93 | the following is a conversation with Daphne Koller a professor of computer science at Stanford University a co-founder of Coursera with Andrew Eng and founder and CEO of in seat row a company at the intersection of machine learning and biomedicine we're now in the exciting early days of using the data-driven methods of machine learning to help discover and develop new drugs and treatments at scale Daphne and in seat row are leading the way on this with breakthroughs they may ripple through all fields of medicine including ones most critical for helping with a current coronavirus pandemic this conversation was recorded before the cove 8:19 outbreak for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe I need to review it with five stars an apple podcast supported on patreon are simply connected me on Twitter Alex Friedman spelled Fri D ma M as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of this conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number-one finance app in the App Store when you get it used collects podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since ketchup allows you to send and receive money digitally peer-to-peer and security in all digital transactions is very important and you mentioned that PCI data security standard the cash shop is compliant with I'm a big fan of standards for safety and security PCI DSS is a good example of that where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions now we just need to do the same for Thomas vehicles and the ad systems in general so again if you get cash app from the App Store Google Play and use the code luxe podcast you get ten dollars in cash that will also donate ten dollars to first an organization that is helping to advance robotics and STEM education for young people around the world and now here's my conversation with Daphne Koller so you co-founded Coursera I made a huge impact in the global education of AI and after five years in August 2016 wrote a blog post saying that you're stepping away and wrote quote it's time for me to turn to another critical challenge the development of machine learning and it's applications to improving human health so let me ask two far-out philosophical questions one do you think will one day find cures for all major diseases known today and two do you think will one day figure out a way to extend the human lifespan perhaps to the point of immortality so one day is a very long time and I don't like to make predictions of the type we will never be able to do X because I think that's a you know that's the smacks of hubris it seems that never and in in in the entire eternity of human existence will we be able to solve a problem that being said curing disease is very hard because oftentimes by the time you discover the disease a lot of damage has already been done and so to assume that we would be able to cure disease at that stage assumes that we would come up with ways is basically regenerating entire parts of the human body in the way that actually returns it to its original state and that's a very challenging problem we have cured very few diseases we've been able to provide treatment for an increasingly large number but the number of things that you could actually define to be cures is actually not that large so I think that's it there's a lot of work that would need to happen for one could legitimately say that we have cured even a reasonable number of far less all diseases on the scale of 0 to 100 where are we in understanding the fundamental mechanisms of all major diseases what's your sense so from the computer science perspective that you've entered the world of health how far along are we I think it depends on which disease I mean there are ones where I would say we're maybe not quite at a hundred because biology is really complicated and there's always new things that we uncover that people didn't even realize existed so but I would say there's diseases where we might be in the seventies or eighties and then there's diseases in which I would say probably the majority where we're really close to zero with Alzheimer's and schizophrenia and type 2 diabetes fall closer to zero or to the 80 I think Alzheimer's is probably closer to zero than to 80 there are hypotheses but I don't think those hypotheses have as of yet been sufficiently validated that we believe them to be true and there is an increasing number of people who believe there's a traditional hypotheses might not really explain what's going on I would also say that Alzheimer's and schizophrenia and in even type 2 diabetes are not really one disease they're almost certainly a heterogeneous collection of mechanisms that manifests in clinically similar ways so in the same way that we now understand that breast cancer is really not one disease it is multitude of cellular mechanisms all of which ultimately translate to uncontrolled proliferation but it's not one disease the same is almost undoubtedly true for those other diseases as well that understanding that needs to precede any understanding of the specific mechanisms of any of those other diseases now in schizophrenia I would say we're almost certainly closer to zero than to anything else type 2 diabetes is a bit of a mix there are clear mechanisms that are implicated that I think have been validated they have to do with insulin resistance and such but there's almost certainly there as well many mechanisms that we have not yet understood you've also thought and worked a little bit on the longevity side do you see the disease and longevity as overlapping completely partially or not at all as efforts those mechanisms are certainly overlapping there's a well-known phenomenon that says that for most diseases other than childhood diseases the risk for getting for contracting that disease increases exponentially year-on-year every year from the time you're about 40 so obviously there is a connection between those two things I that's not to say that they're identical there's clearly aging that happens that is not really associated with any specific disease and there's also diseases and mechanisms of disease that are not specifically related to aging so I think overlap is where we're at okay it is a little unfortunate that would get older and it seems that there's some correlation with the fact the the occurrence of diseases or the fact that we'll get all there mm-hmm and both are quite sad I mean there's processes that happen as cells age that I think are contributing to disease some of those have to do with the DNA damage that accumulates the cells divide where the repair mechanisms don't fully it correct for those there are accumulations of proteins that are misfolded and potentially aggregate and those two contributes a disease and contribute to inflammation there is an um there's a multitude of mechanisms that have been uncovered that are sort of wear and tear at the cellular level that contribute to disease processes that and I'm sure there's many that we don't yet understand on a small tangent perhaps philosophical this uh the the fact that things get older and the fact that things die is a very powerful feature for the growth of new things that you know it's a learning it's a kind of learning mechanism so it's both tragic and beautiful so do you do you do you so in you know in trying to fight disease and trying to fight aging do you think about sort of the useful fact of our mortality or would you like what if you were could be immortal would you choose to be immortal again I think immortal is a very long time I don't know that that would necessarily be something that I would want to aspire to but I think all of us aspire to an increased health span I would say which is an increased amount of time where you're healthy and active and feel as you did when you were 20 and we're nowhere close to that people deteriorate physically and mentally over time and that is a very sad phenomenon so I think a wonderful aspiration would be if we could all live to you know the biblical 120 may be in perfect health in my quality of life high quality of life I think that would be an amazing goal for us to achieve as a society now is the right age 120 or 100 or 150 I think that's up for debate but I think an increased health span is a really worthy goal and anyway in a grand time the age of the universe it's all pretty short so from the perspective you've done obviously a lot of incredible work on machine learning so what role do you think data and machine learning play in this and his goal of trying to understand diseases in trying to eradicate diseases up until now I don't think it's played very much of a significant role because largely the data sets that one really needed to enable a powerful machine learning methods those data sets haven't really existed there's been dribs and drabs and some interesting machine learning that has been applied I would say machine learning / data science but the last few years are starting to change thoughts so we now see an increase in some large data set but equally importantly an increase in technologies that are able to produce data at scale it's not typically the case that people have deliberately proactively used those tools for the purpose of generating data for machine learning they to the extent that those techniques have been used for data production they've been used for data production to drive scientific discovery and the machine learning came as a sort of by-product second stage of oh you know now we have a data set let's do machine learning on that rather than a more simplistic data analysis method but what we are doing it in seat rows actually flipping that around and saying here's this incredible repertoire of methods that bile engineers cell biologists have come up with let's see if we can put them together in brand-new ways with the goal of creating data sets that machine learning can really be applied on productively to create powerful predictive models that can help us address fundamental problems in human health so really focus to get make data the the primary focus and the primary goal and find use the mechanisms of biology and chemistry to to uh to create the kinds of data set that could allow a machine learning to benefit the most I wouldn't put it in those terms because that says the data is the end goal data's the means so for us the end goal is helping address challenges in human health and the method that we've elected to do that is to apply machine learning to build predictive models and machine learning in my opinion can only be really successfully applied especially the more powerful models if you give it data that is of sufficient scale and sufficient quality so how do you create those data sets so as to drive the ability to generate predictive models which subsequently help improve human health so before we dive into the details of that even take a step back and ask when and where was your interest in human health born are there moments events perhaps if I may ask tragedies in your own life that catalyzes passion or was at the broader desire to help humankind so I would say it's a bit of both so on I mean my interest in human health actually dates back to the early 2000s when when a lot of my peers and machine learning and I were using datasets that frankly we're not very inspiring some of us old-timers still remember the quote-unquote twenty newsgroups dataset where it was literally a bunch of text from twenty newsgroups a concept that doesn't really even exist anymore and the question was can you classify which which news group a particular bag of words came from and it wasn't very interesting the datasets at the time on the biology side were much more interesting both from a technical and also from an aspirational perspective they were still pretty small but they were better than 20 news groups and so I started out I think just by just by wanting to do something that was more I don't know societally useful and technically interesting and then over time became more and more interested in the biology in the and the human health aspects for themselves and began to work even sometimes on papers that were just in biology without having a significant machine learning component I think my interest in drug discovery is partly due to an incident I had with when my father sadly passed away about 12 years ago he had an autoimmune disease that settled in his lungs and the doctors basis it well there was only one thing we could do which is give him prednisone at some point I remember doctor even came and said hey let's do a lung biopsy to figure out which autoimmune disease he has and I said would that be helpful would that change treatments no there's only prednisone that's the only thing we can give him and I have friends who were rheumatologist who said the FDA would never approve press his own today because the ratio of side effects to benefit is probably not large enough today we're in a state where there's probably four or five maybe even more well depends for which autoimmune disease but there are multiple drugs that can help people with autoimmune disease and many of which can exist at 12 years ago and I think we're at a golden time in some ways and drug discovery where there's the ability to create drugs that are much more safe for much more effective than we've ever been able to before and what's lacking is enough understanding of biology and mechanism to know where to aim that weird ain't that engine and I think that's where machine learning can help so in 2018 he started and now lead a company in seat row which is a like you mentioned perhaps the focus is drug discovery and the utilization of machine learning for drug discovery so you mentioned that quote we're really interested in creating what you might call a disease in a dish model disease in a dish models places where disease is a complex where we really haven't had a good model system or typical animal models that have been used for years including testing on mice just aren't very effective so can you can you try to describe what is an animal model and what what is a disease in a dish model sure so an animal models for disease is where you create effectively its what it sounds like it's it's a oftentimes a mouse where we have introduced some external perturbation that creates the disease and then we cure that disease and the hope is that by doing that we will cure a similar disease in human the problem is is that oftentimes the way in which we generate the disease and the animal has nothing to do with how that disease actually comes about in a human it's what you might think of as a copy of the of phenotype a copy of the clinical outcome but the mechanisms are quite different and so curing the disease in the animal which in most cases doesn't happen naturally mice don't get Alzheimer's they don't get diabetes they don't get atherosclerosis they don't get autism or schizophrenia those cures don't translate over to what happens in the human and that's where most drugs fails just because the findings that we had in the mouse don't translate to a human the disease in the dish bottles is a fairly new approach it's been enabled by technologies that have not existed for more than five to ten years so for instance the ability for us to take a cell from any one of us you or me revert thats a skin cell to what's called stem cell status which is a what if it was called a pluripotent cell that can then be differentiated into different types of cells so from that flurry potent cell one can create a wax neuron or a lex cardiomyocyte or alexa parasite that has your genetics but that right our cell type and so if there is a genetic burden of disease that would manifest in that particular cell type you might be able to see it by looking at those cells and saying oh that's what potentially sick cells look like versus healthy cells and understand how and then explore what kind of interventions might revert the unhealthy looking cell to a healthy cell now of course curing cells is not the same as curing people and so there's still potentially translate ability gap but at least for diseases that are driven say by human genetics and where the human genetics is what drives the cellular phenotype there is some reason to hope that if we revert those cells in which the disease begins and where the disease is driven by genetics and we can revert that cell back to a healthy state maybe that will help also the more global clinical phenotypes that's really what we're hoping to do that step that backward step I was reading about it the Yamanaka factor yes so think that the reverse step back to stem cells yes I think seems like magic it is I'm honestly before that happened I think very few people would have predicted that to be possible it's amazing can you maybe elaborate is it actually possible like word like how state so this result was maybe like I don't know how many years ago maybe ten years ago was first demonstrated something like that is this how hard is this like how noisy is this backward step it seems quite incredible and cool it is it is incredible and cool it was much more I think finicky and bespoke at the early stages when the discovery was first made but at this point it's become almost industrialized there are what's called contract research organizations vendors that will take a sample from a human and reverted back to stem cell status and it works a very good fraction of the time now there are people who will ask I think good questions is this really truly a stem cell er doesn't remember certain aspects of what of changes that were made in the human beyond the genetics it's fast as a skin cell yeah it's fast as a skin cell or its past in terms of exposures to different environmental factors and so on so I think the consensus right now is that these are not always perfect and there is a little bits and pieces of memory sometimes but by and large these are actually pretty good so one of the key things well maybe maybe you can correct me but one of the useful things for machine learning is size scale of data how easy it is to do these kinds of reversals to stem cells and then disease in a dish models at scale is this that a huge challenge or or not so the reverse the reversal is not as of this point something that can be done at the scale of tens of thousands or hundreds of thousands I think total number of stem cells or iPS cells that are what's called induced pluripotent stem cells in the world I think is somewhere between five and ten thousand last I looked now again that might not count things that exist in this or that academic center and they may add up to a bit more but that's about the range so it's not something that you could this point generate IPS cells from a million people but maybe you don't need to because maybe that background is enough because it can also be now perturbed in different ways and some people have done really interesting experiments in for instance taking cells from a healthy human and then introducing a mutation into it using some of the using one of the other miracle technologies that's emerged last decade which is CRISPR gene editing and introduced mutation that is known to be pathogenic and so you can now look at the healthy cells and unhealthy cells the one with the mutation and do a one-on-one comparison where everything else is held constant and so you could really start to understand specifically what the mutation does at the cellular level so the IPS cells are a great starting point and obviously more diversity is better because you also want to capture ethnic background and how that affects things but maybe you don't need one from every single patient with every single type of disease because we have other tools at our disposal well how much difference is there between people I mentioned ethnic background in terms of IPS cells so we're all like it seems like these magical cells that can do it to create anything between different populations different people is there a lot of variability between stem cells well first of all there's the variability that's driven simply by the fact that genetically we're different so a stem cell let's drive for my genotype is gonna be different from itself stem cells derive from your genotype there's also some differences that I have more to do with for whatever reason some people stem cells differentiate better than other people stem cells we don't entirely understand why so there's certainly some differences there as well but the fundamental difference and the one that we really care about and is a positive is that the is the fact that the genetics are different and therefore we capitulate my disease burden versus your disease burden what's the disease burden well it disease burden is just if you think I mean it's not a well-defined mathematical term although there are mathematical formulations of it it if you think about the fact that some of us are more likely to get a certain disease than others because we have more variations in our genome that are causative of the disease maybe fewer that are protective of the disease people have quantified that using what are called polygenic risk scores which look at all of the variations in an individual person's genome and add them all up in terms of how much risk they confer for a particular disease and then they've put people on a spectrum of their disease risk and for certain diseases where we've been sufficiently powered to really understand the connection between the many many small variations that give rise to an increased disease risk there is some pretty significant differences in terms of the risk between the people say at the highest decile of this polygenic risk score and the people at the lowest decile sometimes those other differences are you know factor of 10 or 12 higher so there's definitely a lot that our genetics contributes to disease risk even if it's not by any stretch the full explanation and from the machine learning perspective their signal there there is definitely signal in the genetics and there is even more signal we believe in looking at the cells that are derived from those different genetics because in principle you could say all the signal is there the at the genetics level so we don't need to look at the cells but our understanding of the biology so limited at this point then seeing what actually happens at the cellular level is a heck of a lot closer to the human clinical outcome than looking at the genetics directly and so we can learn a lot more from it than we could by looking at genetics alone so just to get a sense that enough it's easy to do but what kind of data is useful in this disease in a dish model like what what are what's what's the source of raw data information and also for my outsider's perspective sort of biology and cells are squishy things and I think they are how do you connect literally you connect the computer to to that which sensory mechanisms I guess so that's another one of those revolutions that have happened the last ten years and that our ability to measure cells very quantitatively has also dramatically increased so back when I started doing biology and you know late 90s early 2000s that was the initial era where we started to measure biology in really quantitative ways using things like microarrays where you would measure in a single experiment the activity level what's called expression level of multiple of every gene in the genome in that sample and that ability is what actually allowed us to even understand that there are molecular subtypes of diseases like cancer where up until that point is like oh you have breast cancer but then we looked we looked at the molecular data it was clear that there's different subtypes of breast cancer that at the level of gene activity look completely different to each other so that was the beginning of this process now we have the ability to measure individual cells in terms of their gene activity using what's called single cell RNA sequencing which basically sequences the RNA which is that activity level of different genes for every gene in the genome and you could do that at single cell level so that's an incredibly powerful way of measuring cells I mean you literally count the number of transcripts oh really turns that squishy thing in something that's digital another tremendous this data source that's emerged the last few years is microscopy and and specifically even super resolution microscopy where you could use digital reconstruction to look at sub cellular structures sometimes even things that are below the diffraction limit of light by doing a sophisticated reconstruction and again that gives you tremendous amount of information at the sub cellular level there's now more and more ways that an amazing scientists out there are developing for getting new types of information from even single cells and so that is a way of turning those squishy things into digital data into beautiful datasets but so that data said then with machine learning tools allows you to maybe understand the developmental like the mechanism of the a particular disease and if it's possible to sort of at a high level describe how does how does that help lead to drug discovery that can help prevent reverse that mechanism so I think there's different ways in which this data could potentially be used some people use it for scientific discovery and say oh look we see this phenotype at the cellular level so let's try and work our way backwards and think which genes might be involved in pathways that give rise that so that's a very sort of analytical method to sort of work our way backwards using our understanding of known biology some people use it in a somewhat more you know sort of forward that would if that was a backward this would be forward which is to say okay if I can perturb this gene doesn't show a phenotype that is similar to what I see in disease patients and so maybe that gene is actually causal of the disease so that's a different way and then there's what we do which is basically to take that very large collection of the and use machine learning to uncover the patterns that emerge from it so for instance what are those subtypes that might be similar at the human clinical outcome but quite distinct when you look at the molecular data and then if we can identify such a subtype are there interventions that if I apply it to cells that come from this subtype of the disease and you apply that intervention it could be a drug or it could be a CRISPR gene intervention it does it revert the disease state to something that looks more like normal happy healthy cells and so hopefully if you see that that gives you a certain hope that that intervention will also have a meaningful clinical benefit to people and there's obviously a bunch of things that you would want to do after that to validate that but it's a very different and much less hypothesis-driven way of uncovering new potential interventions and might give rise to things that are not the same things that everyone else is already looking at that's uh I don't know I'm just like to psychoanalyze my own feeling about our discussion currently it's so exciting to talk about so if I'm Ashiya fundamentally well something that's been turned into a machine learning problem and that says can have so much real-world impact that's kind of exciting because I'm so most of my days spent with datasets that I guess closer to the news groups okay so this is a kind of it just feels good to talk about in fact I don't almost don't want to talk about machine learning I want to talk about the fundamentals of the data set which is which is an exciting place to be I agree with you it's what gets me up in the morning it's also what attracts a lot of the people who work at in seat row two in seat row because I think all of the certainly all of our machine learning people are outstanding and could go get a job you know selling ads online or doing commerce or even self-driving cars yes but but I think they would want they they come to us because what because they want to work on something that more of an aspirational nature and can really benefit humanity what with these with these approaches what do you hope what kind of diseases can be helped we mentioned Alzheimer said schizophrenia type 2 diabetes can you just describe the various kinds of diseases that this approach can it can help well we don't know and I try and be very cautious about making promises about some things that o we will cure X that people make that promise and I think it's I tried to first deliver and then promise as opposed to the other way around there are characteristics of a disease that make it more likely that this type of approach can potentially be helpful so for instance diseases have a very strong genetic basis are ones that are more likely to manifest and a stem cell derived model we would want the cellular models to be relatively reproducible and robust so that you could actually get a enough of those cells and in a way that isn't very highly variable and noisy you would want the disease to be relatively contained in one or a small number of cell types that you could actually create in an in vitro in a dish setting whereas if it's something that's really broad and systemic and involves multiple cells that are in very distal parts of your body putting that all in the dish is really challenging so we want to focus on the ones that are most likely to be successful today with the hope I think that it's really smart bioengineers out there are developing better and better systems all the time so the diseases that might not be tractable today might be tractable in three years so for instance five years ago these stem cell drive models didn't really exist people were doing most of the work in cancer cells and the cancer cells are very very poor models of most human biology because they're a they were cancer to begin with and B as you passage them and they proliferate in a dish they become because of the genomic instability even less similar to human biology now we have these stem cell derived models we have the capability to reasonably robustly not quite at the right scale yet but close to derive what's called organoids which are these teeny little sort of multicellular organ of an organ system so there's cerebral organoids and liver organoids and kidney organoids and yeah brain organize organize possibly the coolest thing I've ever seen and then I think we're starting to see things like connecting these organize to each other so that you could actually start and there's some really cool papers that start to do that where you can actually start to say okay can we do multi organ system stuff there's many challenges that it's not easy by any stretch but it might I'm sure people will figure it out and in three years or five years there will be disease moles that we could make for things that we can't make today yeah and this conversation would seem almost outdated with a kind of scale that could be achieved in like three years that would be so cool the you've co-founded Coursera with injurying and were part of the whole MOOC revolution so to jump topics a little bit can you maybe tell the origin story of the history the origin story of MOOCs of Coursera and in general the your teaching to huge audiences on a very sort of impactful topic of AI general so I think the origin story of MOOCs emanates from a number of efforts that occurred at Stanford University around you know the late 2000s where different individuals within Stanford myself included were getting really excited about the opportunities of using online technologies as a way of achieving both improved quality of teaching and also improved scale and so Andrew for instance led the the for engineering everywhere which was sort of an attempt to take ten Stanford courses and put them online just as you know video lectures I led an effort within Stanford to take some of the courses and really create a very different teaching model that broke those up into smaller units and had some of those embedded interactions and and so on which got a lot of support from University leaders because they felt like it was potentially a way of improving the quality of instruction in Stanford by moving to what's now called the flipped classroom model and so those efforts eventually sort of started to interplay with each other and created a tremendous sense of excitement and energy within the Stanford community about the potential of online teaching and led in the fall of 2011 to the launch of the first inferred MOOCs by the way MOOCs it's probably impossible that people don't know but I guess massive open online courses but online courses so they're not come up with the acronym I'm not particularly fond of the acronym but it is what it is where this Big Bang is not a great term for the start of the universe but it is what it is probably so anyway we so those courses launched in in the fall of 2011 and there were within a matter of weeks with no real publicity campaign just a New York Times article that went viral about a hundred thousand students or more in each of those courses and I remember this conversation that Andrew and I had was like wow just there's this real need here and I think we both felt like sure we were accomplished academics and we could go back and you know go back to our lives write more papers but if we did that then this wouldn't happen and it seemed too important not to happen and so we spent a fair bit of time debating do we want to do this as a Stanford efforts kind of building on what we'd started do we want to do this as a for-profit company doing this is a non-profit and we decided ultimately to do it as we did with Coursera and so you know we started really operating as a company at the beginning of 2012 but how did you was that really surprising to you how how do you at that how did you at that time and at this time make sense of this need for sort of global education you mentioned that you felt that while the the popularity indicates that there's a hunger for sort of globalization of learning I think there is a hunger for learning that you know globalization is part of it but I think it's just a hunger for learning the world has changed in the last 50 years it used to be that you finished college you got a job by and large the skills that you learned in college were pretty much what got you through the rest of your job history and and yeah you learned some stuff but it wasn't a dramatic change today we're in a world where the skills that you need for a lot of jobs they didn't even exist when you went to college and the jobs and many of the jobs that exist when you went the college don't even exist today or dying so part of that is due to AI but not only and we need to find a way of keeping people giving people access to the skills that they need today and I think that's really what's driving a lot of this hunger so I think if we even take a step back all for you all the start in trying to think of new ways to teach or to you know new ways to sort of organize the material and present the material in a way that would help the education process the better gotcha yeah so what have you learned about effective education from this process of playing of experimenting with different ideas so we learned a number of things some of which I think could translate back and have translated back effectively to how people teach on campus and some of which I think are more specific to people who learn online and more sort of people who learn as part of their daily life so we learned for instance very quickly that short is better so people who are especially in the workforce can't do a 15-week semester long course they just can't fit that into their lives shortly can you uh can you describe the shortness of what the the the entirety so every aspects of the little lecture short this the less your short the course is short both we started out you know the first online education efforts were actually mi t--'s OpenCourseWare initiatives and that was you know recording of classroom lectures and you know hour and a half or something like that yeah that didn't really work very well I mean some people benefit I mean of course they did but it's not really very palatable experience for someone who has a job and you know three kids and that they need to run errands and such they can't fit 15 weeks into their life and and the hour and a half is really hard so we learned very quickly and we started out with short video modules and over time we made them shorter because we realized that 15 minutes was still too long if you want to fit in when you're waiting in line for your kids doctor's appointment it's better if it's 5 to 7 we learned that 15 week courses don't work and you really want to break this up into shorter units so that there is a natural completion point gives people a sense of they're really close to finishing something meaningful they can always come back and take part two and part three we also learned that compressing the content works really well because if some people that pace works well for others they can always rewind and watch again and so people have the ability to then learn at their own pace and so that flexibility the the brevity and the flexibility are both things that we found to be very important we learned that engagement during the content is important and the quicker you give people feedback the more likely they are to be engaged hence the introduction of these which we actually was an intuition that I had going in and and was then validated using data that introducing some of these sort of little quick micro quizzes into the lectures really helps self graded as automatically graded assessments really help too because it gives people feedback see there you are so all these are valuable and then we learn about two other things - oh we did some really interesting experiments for instance on though gender bias and how having a female role model as an instructor can change the balance of men to women in terms of especially in stem courses and you could do that online by doing a/b testing in ways that would be really difficult to go on campus oh that's exciting but so the shortness the compression I mean that's actually so that that probably is true for all you know good editing is always just compressing the content making it shorter so that puts a lot of burden on the creator of the the instructor and the creator of the educational content probably most lectures at MIT or Stanford could be five times shorter if the preparation was put was put enough so maybe people might disagree with that but like the Christmas the clarity that a lot of them like Coursera delivers is how much effort does that take so first of all let me say that it's not clear that that crispness would work as effectively and a face-to-face setting because people need time to absorb the material and so you need to at least pause and give people a chance to reflect that maybe practice and that's what MOOCs do is that they give you these chunks of content and then ask you to practice with it and that's where I think some of the newer pedagogy that people are adopting and face-to-face teaching they have to do with interactive learning and such it can be really helpful but both those approaches whether you're doing that type of methodology and online teaching or in that flipped classroom interactive teaching what site applause what's flipped classroom flipped classroom is a way in which online content is used a supplement face-to-face teaching where people watch the videos perhaps and do some of the exercises before coming to class and then when they come to classes actually to do much deeper problem solving oftentimes in a group but any one of those different pedagogy's that are beyond just standing there and droning on in front of the classroom for an hour and 15 minutes require a heck of a lot more preparation and so it's one of the challenges I think that people have that we had when trying to convince instructors to teach on Coursera and it's part of the challenges that pedagogy experts on campus have in trying to get faculty to teach differently is that it's actually harder to teach that way than it is to stand there drone do you think MOOCs will replace in-person education or become the majority of in-person of Education of the way people learn in the future again the future could be very far away but where's the trend going do you think so I think it's a nuanced and complicated answer I don't think MOOCs will replace face-to-face teaching I think learning is in many cases a social experience and even at Coursera we had people who naturally formed study groups even when they didn't have to just come and talk to each other and we found that that actually benefited their learning in very important ways so there was more success in among learners who had those study groups than among ones who didn't so I don't think it's just gonna oh we're all gonna just suddenly learn online with a computer and no one else in the same way that you know recorded music has not replaced live concerts but I do think that especially when you are thinking about continuing education the stuff that people get when they're traditional whatever high school college education is done and they yet have to maintain their level of expertise and skills in a rapidly changing world I think people will sooo more and more educational content in this online format because going back to school for formal education is not an option for most people briefly I know it might be a difficult question to ask but there's a lot of people fascinated by artificial intelligence by machine learning but deep learning is there a recommendation for the next year or for a lifelong journey as somebody interested in this how do they how do they begin how do they enter that learning journey I think the important thing is first to just get started and there's plenty of online content that one can get for both the core foundations of mathematics and statistics and programming and then from there to machine learning I would encourage people not to skip too quickly past the foundations because I find that there is a lot of people who learn machine learning whether it's online or on campus without getting those foundations and they basically just turn the crank on existing models in ways that they don't allow for a lot of innovation and an adjustment to the problem at hand but also be or sometimes just wrong and they don't even realize that their application is wrong because there's artifacts that they haven't fully understood so I think the foundations machine learning is an important step and then and then actually start solving problems try and find someone to solve them with because especially at the beginning is useful to have someone to bounce ideas off and fix mistakes that you make and and you can fix mistakes that they make but but then just find practical problems whether it's in your workplace or if you don't have that catechol competitions or such are a really great place to find interesting problems and just practice practice perhaps a bit of a romanticized question but what idea in deep learning do you find have you found in your journey the most beautiful or surprising or interesting perhaps not just deep learning but AI in general statistics good answer with two things one would be the foundational concept of end to end training which is that you start from the raw data and you train something that is not like a single piece but rather the towards the actual goal that you're looking to from the raw data to the outcome like and nothing no no details in between well not no details but the fact that you I mean you could certainly introduce building blocks that were trained towards other tasks and actually coming to that in my second half of the answer but it doesn't have to be like a single monolithic blob in the middle actually I think that's not ideal but rather the fact that at the end of the day you can actually train something and goes all the way from the beginning to the end and the other one that I find really compelling is the notion of learning a representation that in its turn even if it was trained to another task can potentially be used as a much more rapid starting point to solving a different task and that's I think reminiscent of what makes people successful learners it's something that is relatively new in the machine learning space I think it's underutilized even relative to today's capabilities but more and more of how do we learn sort of reusable representation so end to end and transfer learning yeah is it surprising to you that neural networks are able to in many cases do these things it says it may be taking back to when you when you first would dive deep into neural networks or in general even today is it surprising that neural networks work at all and work wonderfully to do this kind of raw and then learning and even transfer learning I think I was surprised by how well when you have large enough amounts of data it's possible to find a meaningful representation in what is an exceedingly high dimensional space and so I find that to be really exciting and people are still working out the math for that there's more papers on that every year and I think it's would be really cool if we figured that out but that to me was a surprise because in the early days when I was starting my weigh in machine learning and the data sets were rather small I think we we believed I believe that you needed to have a much more constrained and knowledge rich search space to really make to really get to a meaningful answer and I think it was true at the time what I think is is still a question is will a completely knowledge free approach where there's no prior knowledge going into the construction of the model is that going to be the solution or not it's not actually the solution today in the sense that the architecture of a you know convolutional neural network that's used for images is actually quite different to the type of networks it's used for language and yet different from the one that's used for speech or biology or any other application there's still some insight that goes into the structure of the network to get the the right performance will you be able to come up with the universal learning machine I don't know I wonder if there's always has to be some insight injected somewhere or whether it can converge so you've done a lot of interesting work with probabilistic graphical models in general Bayesian deep learning and and so on so can you maybe speak high level how can learning systems deal with uncertainty one of the limitations I think of a lot of machine learning models is that they come up with an answer and you don't know how much you can believe that answer and oftentimes the the the answer is actually quite poorly calibrated relative to its uncertainties even if you look at where the um you know the the the confidence that comes out of the say the neural network at the end and you ask how much more likely is an answer of zero point eight versus zero point nine it's not really in any way calibrated to the to the actual reliability of that network and how true it is and the further away you move from the training data the more not only the more wrong then that workers often is more wrong and more confident in a strong answer and that is a serious issue in a lot of application areas so when you think for instance about medical diagnosis as being maybe an epitome of how problematic this can be if you were training your network on a certain set of patients on a certain patient population and I have a patient that is an outlier and there's no human that looks at this and that patient is put into a neural network in your network not only gives a completely incorrect diagnosis but it's supremely confident and it's wrong answer you could kill people so I think creating more of an understanding of how do you do snut works that are calibrated in our uncertainty and can also say you know I give up I don't know what to say about this particular data instance because I've never seen something that sufficiently liked it before I think it's going to be really important in mission-critical applications especially ones where human life is at stake and that includes the you know medical applications but it also includes you know automated driving because you'd want the network to be able to you know what I have no idea what this blob is that I'm seeing in the middle of the rest I'm just gonna stop because I don't want to potentially run over a pedestrian that I don't recognize is there good mechanisms ideas of how to allow learning systems to provide that uncertainty whatever along with their predictions certainly people have come up with mechanisms that involve Bayesian deep learning deep learning that involves Gaussian processes I mean there is a slew of different approaches that people have come up with there's methods that use ensembles of networks with trained with different subsets of theta or different random starting points those are actually sometimes surprisingly good at creating a sort of set of how confident or not you are in your answer it's very much an area of open research let's cautiously French your back into the land of philosophy and speaking of AI systems providing uncertainty somebody like Stuart Russell believes that as we create more and more intelligent systems it's really important for them to be full of self-doubt because you know if they're given more and more power we want them the way to maintain human control over a systems or human supervision which is true like you just mentioned with autonomous vehicles it's really important to get human supervision when the car is not sure because if it's really confident it can in cases when it can get in trouble is going to be really problematic so let me ask about sort of the questions of AGI in human level intelligence I mean we talked about curing diseases now which is sort of fundamental thing we could have an impact today but yet people also dream of both understanding and creating intelligence is that something you think about is that something you dream about is that something you think is within our reach to be thinking about as computer scientists boy let me tease apart different parts of that question the first question yeah it's a multi-part question so let me start with the feasibility of AGI then I'll talk about the timelines a little bit and then talk about well what controls does one need when protecting when thinking about protections and the AI space so you know I think AGI obviously is a long-standing dream that even our early pioneers in the space had you know the Turing test and so on are the earliest discussions of that we're obviously closer than we were 70 or so years ago but I think it's still very far away I think machine learning algorithms today are Yui exquisitely good pattern recognizers in very specific problem domains where they have seen enough training data to make good predictions you take a machine learning algorithm and you move a different version of even that same problem far less one that's different and it will just completely choke so I think we're nowhere close to the versatility and flexibility of even a human toddler in terms of their ability to context switch and solve different problems using a single knowledge-based single brain so am i desperately worried about the machines taking over the universe and you know starting to kill people because they want to have more power I don't think so well sort of to pause on that so you kind of intuited that super intelligence is a very difficult thing to achieve that were intelligent intelligent super intelligence we're not even close to intelligence even just the greater abilities of generalization of our current systems but we haven't answered all the parts you don't want to go into the second oh good we take but maybe another tangent you can also pick up as can we get in trouble with much Dumber systems yes that is exactly where I was going okay so I so just to wrap up on the threats of AGI I think that it seems to me a little early today to figure out protections against a human level or superhuman level intelligence who's where we don't even see the skeleton of what that would look like so it seems that it's very speculative on how what how to protect against that but we can definitely and have gotten into trouble on much Dumber systems and a lot of that has to do with the fact that the systems that we're building are increasingly complex increasingly poorly understood and there's ripple effects that are unpredictable in changing little things that's gonna have dramatic consequences on the outcome and by the way that's not unique to artificial now this is I think artificial intelligence exacerbates that brings it to a new level but the heck our electric grid is really complicated the software that runs our financial markets is really complicated and we've seen those ripple effects translate to dramatic negative consequences like for instance financial crashes that have to do with feedback loops that we didn't anticipate so I think that's an issue that we need to be thoughtful about in many places artificial intelligence being one of them and we should and I think it's really important that people are thinking about ways in which we can have better interpret ability of systems better tests for for instance measuring the extent to which a machine learning system that was trained in one set of circumstances how well does it actually work in a very different set of circumstances where you might say for instance well I'm not going to be able to test my automated via call in every possible City Village weather condition and so on but if you trained it on this set of conditions and then tested it on 50 or 100 others that were quite different from the ones that you trained it on then I can it worked then that gives you confidence that the next 50 that you didn't test it on might also work so effectively testing for generalizability so I think there's ways that we should be constantly thinking about to validate the robustness of our systems I think it's very different from the let's make sure robots don't take over the world and then the other place where I think we have a threat which is also important for us to think about is the extent to which technology can be abused so like any really powerful technology machine learning can be very much used badly as well as too good and that goes back to many other technologies that have come up with when people invented projectile missiles and it turns into guns and people invented nuclear power and it turned nuclear bombs and I think honestly I would say that to me gene editing and CRISPR is at least as dangerous at technology if used badly than machine as machine learning you could create really nasty viruses and such using gene editing that are you know you would be really careful about so anyway that's something that we need to be really thoughtful about whenever we have any really powerful new technology yeah and on the case of machine learning is at the stereo machine learning so all the kinds of attacks like security almost threats and there's a social engineering with machine learning algorithm and big brother's watching you and there is the killer drones that can potentially go and targeted execution of people in a different country I don't you know want them are he that are not necessarily that much better but but you know people want to kill someone they'll find a way to do it so if you if in general if you look at trends in the data there's less Wars there's just violence there's more human rights so we've been doing overall quite good as a human species are you are you optimistic maybe another way to ask is do you think most people are good and fundamentally we tend towards a better world which is underlying the question well machine learning what gene editing ultimately land us somewhere good are you optimistic I think by and large I'm optimistic I think that most people mean well that doesn't mean that most people are you know altruistic do-gooders but I think most people mean well but I think it's also really important for us as a society to create social norms we're doing good and being perceived well by our peers is are positively correlated I mean it's very easy to create dysfunctional societies there's certainly multiple psychological experiments as well as sadly real-world events where people have devolved to a world where being perceived well by your peers is correlated with really atrocious often genocide 'el behaviors so we really want to make sure that we maintain a set of social norms where people know that to be a successful member of society you want to be doing good and one of the things that I sometimes worry about is that some societies don't seem to necessarily be moving in the forward direction in that regard where it's not necessarily the case that doing that being a good person is what makes you be perceived well by your peers and I think that's a really important thing for us as a society to remember it's very easy to degenerate back into a universe where it's okay to do really bad stuff and still have your peers think you're amazing it's fun to ask a world-class computer scientist and engineer a ridiculously philosophical question like what is the meaning of life let me ask what gives your life meaning what are what is the source of fulfilment happiness joy purpose when we were starting Coursera in the fall of 2011 that was right around the time that Steve Jobs passed away and so the media was full various famous quotes Heath uh turd and one of them that really stuck with me because it resonated with stuff that I'd been feeling for even years before that is that our goal in life should be to make a dent in the universe so I think that to me what gives my life meaning is that I would hope that when I am lying there on my deathbed and looking at what I'd done in my life that I can point to ways in which I have left the world a better place than it was when I entered it this is something I tell my kids all the time because I also think that the burden of that is much greater for those of us who were born to privilege and in some ways I was I mean it wasn't more than wealthy or anything like that but I grew up in an educated family with parents who loved me and took care of me and I had a chance at a great education and and so I and I've always had enough to eat so I was in many ways born to privilege more than the vast majority of humanity and my kids I think are even more so born to privilege then I was fortunate enough to be and I think it's really important that for especially for those of us who have that opportunity that we use our lives to make the world a better place I don't think there's a better way to end it that needs a honor to talk to you thank you so much for talking to you thanks for listening to this conversation with Daphne Koller and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon simply connect with me on Twitter Alex Friedman and now let me leave you some words from Hippocrates a physician from ancient Greece who's considered to be the father of medicine wherever the art of medicine is loved there's also love of humanity thank you for listening and hope to see you next time you |
Harry Cliff: Particle Physics and the Large Hadron Collider | Lex Fridman Podcast #92 | the following is a conversation with Harry Cliff a particle physicist at the University of Cambridge working on the Large Hadron Collider beauty experiment that specializes in investigating the slight differences between matter and antimatter by studying a type of particle called the beauty quark or B quark in this way he's part of the group of physicists who are searching for the evidence of new particles that can answer some of the biggest questions in modern physics he's also an exceptional communicator of science with some of the clearest and most captivating explanations of basic concepts in particle physicists that have ever heard so when I visit in London I knew I had to talk to him and we did this conversation at the Royal Institute lecture theatre which has hosted lectures for over two centuries from some of the greatest scientists and science communicators in history for Michael Faraday to Carl Sagan this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical and psychological and financial burden of this crisis I'm sending love your way stay strong or in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe I need to review it with five stars in a podcast supported on patreon or simply connect with me on Twitter at lex friedman spelled fri DM aen as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience quick summary of the ads to sponsors expressvpn and cash app please consider supporting the podcast by getting expressvpn and expressvpn calm / Lex pod and downloading cash app and using collects podcasts this show is presented by cash app the number one finance app in the App Store when you get it used code Lex podcast cash app lets you send money your friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders algorithmic marvel so big props the cash app engineers solving a heart problem then in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again you get cash out from the App Store Google Play and use the collects podcast you get $10 and cash up will also donate $10 to the first an organization that is helping advanced robotics and STEM education for young people around the world this show sponsored by expressvpn get it at expressvpn comm / Lex pod to get a discount and to support this podcast I've been usually expressvpn for many years I love it it's easy to use press the big power on button and your privacy is protected and if you like you can make it look like your location is anywhere else in the world I might be in Boston now but I can make it look like I'm in New York London Paris or anywhere else this has a large number of obvious benefits certainly it allows you to access international versions of streaming websites like the Japanese Netflix or the UK who expressvpn works on any device you can imagine I use it on Linux shout out to a bunch of Windows Android but is available everywhere else to once again get it and expressvpn comm / flex pod to get a discount and to support this podcast and now here's my conversation with harry cliff let's start with probably one of the coolest things that human beings have ever created the Large Hadron Collider ohc what is it how does it work okay so is essentially this gigantic 27 kilometer circumference particle accelerators this big ring it's buried 100 100 meters underneath the surface in the countryside just outside Geneva in Switzerland and really what it's for ultimately is to try to understand what are the basic building blocks of the universe so you can think of it in a way as like a gigantic microscope and and the analogy is actually fairly precise so gigantic microscope effectively except it's a microscope that looks at the structure of the vacuum in order for this kind of thing to study particles which are microscopic entities it has to be huge yes gigantic Waxhaw so what do you mean by studying vacuum okay so I mean so particle physics as a field is kind of badly named in a way because particles are not the fundamental ingredients of the universe they're not fundamental at all so the things that we believe are the real building blocks of the universe are objects invisible fluid like objects called quantum fields so these are fields like like the magnetic field around a magnet that exists everywhere in space they're always there in fact actually it's funny they were in the wrong institution because this is where the idea of the field was effectively invented by Michael Faraday doing experiments with magnets and coils of wire so he noticed that you know if he was very famous experiment that he did where he got a magnet and put it on top of it a piece of paper and then sprinkled iron filings and he found the iron filings arrange themselves into these kind of loops of which was actually mapping out the invisible influence of this magnetic field which is a thing you know we've all experienced we're all felt held a magnet and or two poles the magnet and pushing together and felt this thing this force pushing back so these are real physical objects and the the way we think of particles in modern physics is that they are essentially little vibrations little ripples in these otherwise invisible fields that are everywhere they fill the whole universe you know I don't apologist perhaps for the ridiculous question are you comfortable with the idea of the fundamental nature of our reality being fields because to me particles you know a bunch of different building blocks makes more sense sort of intellectually so visually like it's it it seems to I seem to be able to visualize that kind of idea easier yeah are you comfortable psychologically with the idea that the basic building block is not a block but a field I think it's um I think it's quite a magical idea I find it quite appealing and it's well it comes from a misunderstanding of what particles are so like when you when we do science at school and we draw a picture of an atom you draw a like you know nucleus with some protons or neutrons these little spheres in the middle and then you have some electrons are like little flies flying around the atom and that is a completely misleading picture of what an atom is like it's nothing like that the electron is not like a little planet orbiting the atom it's this spread out wibbly-wobbly wave-like thing and we know we've known that since you know the early 20th century thanks to quantum mechanics so when we carry on using this word particle because sometimes when we do experiments particles do behave like they're little marbles or little bullets you know so in the LHC when we collide particles together you'll get you know you'll get like hundreds of particles will fly out through the detector and they all take a trajectory and you can see from the detector where they've gone and they look like they're little bullets so they behave that way um you know a lot of the time but when you really study them carefully you'll see that they are not little spheres they are these virial disturbances in in these underlying fields so this is this is really how we think nature is which is surprising but also I think kind of magic so here we are our bodies are basically made up of like little knots of energy in these invisible objects that are all around us and what what is the story of the vacuum when it comes to LHC so what why did you mention the word vacuum okay so if we just if we go back to let us the physics we do know so atoms are made of electrons which were discovered 100 or so years ago and then nucleus of the atom you have two other types of particles there's an up something called an up quark and a down quark and those three particles make up every atom in the universe so we think of these as ripples in fields so there is something called the electron field and every electron in the universe is a ripple moving about in this electron field the electron field is all around we can't see it but every electron in our body is a little ripple in this thing that's there all the time and the quark feels the same so there's an up quark field and an up quark isn't a ripple in the up quark field and the down quark is a little ripple in something else called the down quark field so these fields are always there now there are potentially we know about a certain number of fields in what we call the standard model of particle physics and the most recent one we discovered was the Higgs field and the way we discovered the Higgs field was to make a little ripple in it so what the LHC did it fired two protons into each other very very hard with enough energy that you could create a disturbance in this Higgs field and that's what shows up as what we call the Higgs boson so this particle that everyone was going on about eight or so years ago is proof really the particle in itself is I mean it's interesting but the things really interesting is the field because it's the the Higgs field that we believe is the reason that electrons and quarks have mass and it's that invisible field that's always there that gives mass to the particles the Higgs boson is just our way of checking it's there basically and so the Large Hadron Collider in order to get that ripple in the Higgs field you it requires a huge amount of energy yes opposes so that's why you need this huge that's why size matters here so maybe there's a million questions here but let's backtrack why does size matter in the context of a particle collider so why does bigger allow you for higher energy collisions right so the reason well it is kind of simple really which is that there are two types of particle accelerator that you can build one is circular which is like the LHC the other is a great long line so the advantage of a circular machine is that you can send particles around a ring and you can give them a kick every and they go round so imagine you have a is actually a bit of the LHC that's about only 30 meters long where you have a bunch of metal boxes which have oscillating to million volt electric fields inside them which are timed so that when a proton goes through one of these boxes the field it sees as it approaches is attractive then as it leaves the box it flips and becomes repulsive and the proton gets attracted then kicked out the other side so it gets a bit faster so you send it but then you send it back round again and it's incredible like the timing of that the synchronization that wait really yeah yeah yeah yeah that's I think there's going to be a multiplicative effect on the questions I have is that okay let me just take that attention for a second how the orchestration of that is that a fundamentally a hardware problem or software a problem like what how do you get that I mean I might so I should first of all say I'm not an engineer so the guys I did not build the LHC so they're people much much better at this stuff than I for sure but maybe but from from your sort of intuition from the the the echoes of what you understand you heard of house design what's your sense how what's the engineering aspects that the acceleration bit is not challenging okay okay there is always challenges everything but basically you have these the beams that go around you like see the beams of particles are divided into little bunches so they're called their bit like swarms of bees if you like and there are around I think it's something of the order 2000 bunches spaced around the ring and they if you were if you're a given point on the ring counting bunches you get 40 million bunches passing you every second so they come in like you know just like cars going past from a very fast motorway so you need to have if you're a electric field that you're using to accelerate the particles that needs to be timed so that as a bunch of protons arrives it's got the right sign to attract them and then flips at the right moment but I think the the voltage in those boxes oscillates at hundreds of megahertz so the beams at like 40 megahertz but is oscillating much more quickly than the beam so and I think you know it's difficult engineering but in principle it's not you know a really serious challenge the bigger problem this probably engineers like screaming at ureña probably yeah what okay so in terms of coming back to this thing why is it so big well the reason is you wanna get the particles through that accelerating element over over again so you want to bring them back round that's why it's round the question is why couldn't you make it smaller well the basic answer is that these particles are going unbelievably quickly so they travel at 99.999999 1% of the speed of light in the LHC and if you think about say driving your car round a corner high speed if you go fast you need a very you need a lot of friction in the tires to make sure you don't slide off the road so the the limiting factor is the how powerful a magnet can you make because it's what we do is magnets are used to bend the particles around the ring and essentially the LHC when it was designed was designed with the most powerful magnets that could conceivably be built at the time and so that's your kind of limiting factors if you wanted to make the machines smaller that means a tighter bend you need to have a more powerful magnet so it's this toss-up between how strong your magnets versus how big a tunnel can you afford the bigger the tunnel the weaker the magnets can be the smaller a tunnel the stronger they've got to be okay so maybe can we backtrack to the data model and say what kind of particles there are period and maybe the history of kind of assembling that the standard model of physics and then how that leads up to the hopes and dreams and the accomplishments of the Large Hadron Collider yeah sure okay so for all the 20th century physics in like five minutes yeah please okay so okay the story really begins properly end of the 19th century the basic view of matter is that matter is made of atoms and the atoms are indestructible immutable little spheres like the things we were talking about they don't really exist and there's you know one atom for every chemical element as an atom for hydrogen for helium for carbon photon etc and they're all different then in 1897 experiments done at the Cavendish laboratory in Cambridge where I am still where I'm based showed that there are actually smaller particles inside the atom which eventually became known as electrons these are these negatively charged things that go around the outside a few years later and it's Rutherford very famous nuclear physics nuclear physics shows that the atom has a tiny nugget in the center which we call the nucleus which is a positively charged object so then by in light 1910-11 we have this model of the atom that we learn in school which is you've got a nucleus electrons go round there fast forward you know a few years the nucleus people start doing experiments with radioactivity where they use alpha particles that are spat out of radioactive elements as as bullets and they fire them other atoms and by banging things into each other they see that they can knock bits out of the nucleus so these things come out called protons first of all which are positively charged particles about 2,000 times heavier than the electron and then 10 years later more or less neutral particle is discovered called the neutron so those are the three basic building blocks of atoms you have protons and neutrons in the nucleus that are stuck together by something called a strong force the strong nuclear force and you have electrons in orbit around that held in by the electromagnetic force which is one of the you know the forces of nature that's sort of where we get to by late 1932 more or less then what happens is physics is nice and neat in 1932 everything looks great got three particles and all the atoms are made of that's fine but then cloud chamber experiments these are devices that can be used to the first devices capable of imaging subatomic particles so you can see their tracks and they use to study cosmic rays particles that come from outer space and bang into the atmosphere and in these experiments people start to see a whole load of new particles so they discover for one thing antimatter which is a sort of a mirror image of the particles so we discovered that there's also as well as a negatively charged electron there's something called a positron which is a positively charged version of the electron and there's an antiproton which is negatively charged and and then a whole load of other weird particle start to get discovered and no one really knows what they are this is known as the zoo of particles are these discoveries fundamentally first theoretical discoveries or the discoveries in an experiment so like well yeah what was the process of discovery for these early it's a mixture I mean that the early stuff around the atom is really experimentally driven it's not based on some theory it's exploration in the lab using equipment so it's really people just figuring out hands-on with the fenomena figuring out what these things are the theory comes a bit later that there is that's not always the case so in the discovery of the anti-electron the positron that was predicted from quantum mechanics and relativity by a very clever theoretical physicist called Paul Dirac who was probably the second brightest you know physicist of the 20th century apart from Einstein but isn't as well anywhere near as well known so he predicted the existence of the anti electron from basically a combination of the theories of quantum mechanics and relativity and it was discovered about a year after he made their prediction what happens when an electron meets a positron they annihilate each other so if you when you bring a particle in its antiparticle together they they react well they react they just wipe each other out and they turn their mass is turned into energy usually in the form of photons so you'll get light produced so when you have that kind of situation why why does the universe exists at all if there's matter in any matter oh god now we're getting into the really big questions so you want to go there now yeah that's me maybe let's go there later that's because I mean that is a very big question yeah let's let's take it slow with the standard model so okay so there's matter and antimatter in the 30s mmm so what else so matter antimatter and then a load of new particles start turning up in these cosmic ray experiments first of all and they don't seem to be particles that make up atoms there's something else they all mostly interact with a strong nuclear force so they're a bit like protons and neutrons and by in the 1960s in America particularly but also in Europe and Russia scientist article particle accelerators so these are the forerunners of the LHC so big ring shaped machines that were you know hundreds of meters long which in those days was enormous you never you know most physics up until that point had been done in labs in universities you know with small bits of kit so this is a big change and when these accelerators are built they start to find they can produce even more of these particles so I don't know the exact numbers but by around 1960 there are of order a hundred of these things that have been discovered and physicists are kind of tearing the hair out because physics is all about simplification and suddenly what was simple as come messy and complicated and everyone sort of wants to understand what's going on it's a quick kind of a side and the probably really dumb question but how is it possible to take something like a like a photon or electron and be able to control it enough like to be able to do a controlled experiment where you collide it against something else yeah is that is that that seems like an exceptionally difficult engineering challenge because you mention vacuum to so you basically want to remove every other distraction and really focus on this collision how difficult of an engineering challenge is that just to get a sense and it's very hard I mean in the early days particularly when the first accelerators are being built in like 1932 Ernest Lawrence builds the first what we call the cyclotron which is like a little celery - this big or so there's another widely they're big there's a tiny little thing yeah I mean so most of the first accelerators were what we call fixed argot experiments so you had a ring you accelerate particles around the ring and then you fire them out the side into some target so is eat that makes the kind of the colliding bit is relatively straightforward to use fire it whatever it is you want to fire it out the hard bit is the steering the beams with the magnetic fields getting you know strong enough electric fields to accelerate them all that kind of stuff the first colliders where you have two beams colliding head-on that comes later and I don't think it's done until maybe the 1980s I'm not entirely sure but it takes is much harder problem that's crazy because yet it's like perfectly you had them to hit each other I mean we're talking about I mean what scale it takes what's this this I mean the temporal thing is a giant mess but the spatially like the size mmm it's tiny well to give you a sense so the LHC beams the cross-sectional diameter is I think around a dozen or so microns so you know ten ten millionths of a meters then a beam sorry just to clarify a beam how many is it the bunches that you mentioned yes multiple poles is just one part oh no no the bunches contained say a hundred billion protons each so a bunch is not really one shape they're actually quite long they're like 30 centimeters long but thinner than a human hair so like very very narrow long sort of object so those are the things so what happens in the LHC is you steer the beams so that they cross in the middle of the detector so the basically have these swarms of protons are flying through each other and most of that you have so you have 100 billion coming one way 100 billion another way maybe 10 of them will hit each other okay so this okay that makes a lot more sense that's nice so there you're trying to use sort of it's like probabilistically you're not you can't make a single particle collide with a single oh yeah so that's not an efficient way to do it you'd be waiting a very long time to get anything yeah so you you're basically right see you're relying on probability to be that some fraction of them are gonna collide yeah and then you know which is it's it's a it's a swarm of the same kind of particle so it doesn't matter which ones each other exactly I mean that that's not to say it's not hard you've got a one of the challenges to make the collisions work is you have to squash these beams to very very the basic their narrower they are the better because the higher the chances of them colliding if you think about two flocks of birds flying through each other the birds are all far apart in the flocks there's not much chance that they'll collide if they're all flying densely together and they very much more likely to collide with each other so that's the sort of problem it's tuning those magnetic fields getting them angry feels powerful not that you squash the beams and focus them so that you get enough collisions that's super cool do you know how much software is involved here I mean it's sort of I come in the software world and it's fascinating this seems like it's a software is buggy and messy and so like you almost don't want to rely on software too much like if you do it has to be like low-level like Fortran style programming do you know how much software isn't a Large Hadron Collider I mean it depends at which level a lot I mean the whole thing is obviously computer-controlled so I mean I I don't know a huge amount about how the software for the actual accelerator works but you know I've been in the control center so has CERN there's this big control room which is like bit like a NASA mission control with big banks of you know desk where the engine is sit and they monitor the LHC because you obviously can't be in the tunnel when it's running so everything's remote I mean one sort of anecdote about the sort of software side in 2008 when the LHC first switched on they had this big launch event and then you know big press conference party to inaugurate the machine and about ten days after that they were doing some tests and the this dramatic event happened where a huge explosion basically took place in a tunnel that destroyed were damaged badly damaged about about half a kilometer of the machine but the story is viewed the engineers here in the control room that day they'd one guy told me the story about you know basically there's all these screens they have in the control room started going red so these alarms like you know kind of in software going off and then they assume that lists all wrong with the software cuz there's no way something this catastrophic could have could have happened yeah but I mean when I worked on one when I was a PhD student one of my Jobs was to help to maintain the software that's used to control the detector that we work on and that was it's relatively robust not so you don't want it to be too fancy you don't want to sort of fall over too easily the more clever stuff comes when you're talking about analyzing the data and that's where they're sort of you know are we jumping around too much do we finish for the standard model we didn't know we didn't hurry and start talking mark works we haven't talked about me yet got to the messy zoo of particles go back there if it's okay okay that's take us the rest of the history of physics in the 20th century okay sure okay so circa 1960 you have this you have these hundred or so particles it's a bit like the periodic table all over again so you've got like like having a hundred elements sort of a bit like that and people try to start to try to impose some order so Murray Gelman he's a theoretical physicist American from New York he realizes that there are these symmetries in these particles that if you arrange them in certain ways that they relate to each other and he uses these symmetry principles to predict the existence of particles that haven't been discovered which are then discovered in accelerators so this starts to suggest there's not just random collections of crap there's like you know actually some order to this under a little bit later in 1960 again it's round the 1960s he proposes along with another physicist called George Zweig the these symmetries arise because just like the patterns in the periodic table arise because atoms are made of electrons and protons that these patterns are due to the fact that these particles are made of smaller things and they are called quarks so these are the particles they're predicted from theory for a long time no one really believes they're real a lot of people think that there are kind of theoretical convenience that happen to fit the data but there's no evidence no one's ever seen a quark in any experiment and lots of experiments are done to try to find quarks just try to knock a quark out of her so the idea if protons and neutrons say made of quarks you should work to knock a quark out and see the quark that never happens and we still have never actually managed to do that really no so the way but the way that it's done in the end is this machine that's built in California at Stanford lab Stanford Linear Accelerator which is essentially a gigantic three kilometer long electron gun fires electrons almost speed of light at protons and when you do these experiments what you find is a very high energy the electrons bounce off small hard objects inside the proton so it's a bit like taking an x-ray of the proton you're firing these very light high-energy particles and they're pinging off little things inside the proton that are like ball bearings if you like so you actually that way they resolve that there are three things inside the proton which are quarks the quarks that governance why I could predicted so that's really the evidence that convinces people that these things are real the fact that we've never seen one in an experiment directly they're always stuck inside other particles and the reason for that is essentially to do with the strong force the strong forces the force holds quarks together and it's so strongly it's impossible to actually liberate a quark so if you try and pull a quark out of a proton what actually ends up happening is that the you kind of create this that this spring-like bond in the strong force we've imagined two quarks that are held together by very powerful spring you pull it pull and pull more and more energy gets stored in there bond like stretching a spring and eventually the tension gets so great the spring snaps and the energy in that bond gets turned into two new quarks that go on the broken ends so you started with two quarks to end up with four quarks so you never actually get to take a quark out you just end up making loads of more quarks in the process so how do we again forgive the dumb question how do we know quarks are real then well eh from these experiments where we can scatter you fire electrons into the protons they can burrow into the proton and knock off and they can bounce off these quarks so you can see from the angles the electrons come Alice you can infer you can infer that these things are there the quark model can also be used it has a lot of successes you can use it to predict the existence of new particles that hadn't been seen so and basically there's lots of data basically showing from you know when we fire protons at each other at the LHC a lot of quarks get knocked all over the place and every time they try and escape from say one of their protons they make a whole jet of quarks that go flying off it has bound up in other sorts of particles made of quarks so they're all the sort of the theoretical predictions from the basic theory of the strong force and the quarks all agrees with what we are seeing experiments we've just never seen a an actual quark on its own because unfortunate it's impossible to get them out on their own so quarks these crazy smaller things that are hard to imagine a real so what else what else is part of the story here so the other thing that's going on at the time around the sixties it's an attempt to understand the forces that make these particles interact with each other so you have the electromagnetic force which is the force that was sort of discovered to some extent in this room or at least in this building so the first what we call quantum field theory of the electromagnetic force is developed in the 1940s and 50s by Fineman Richard Feynman amongst other people julian schwinger tominaga who come up with the first what we call a quantum field theory of the electromagnetic force and this is where this description of which I gave you at the beginning that particles are ripples and fields well in this theory the photon the particle of light is described as people in this quantum field called the electromagnetic field and the attempt then is made to try what can we come up with a quantum field theory of the other forces of the strong force and the weak the other third the third force which we haven't discussed which is the weak force which is a nuclear force we don't really experience it in our everyday lives but it's responsible for radioactive decay is the force that allows you know in a radioactive atom to turn into a different element for example and there are a few we've explicitly mentioned but so there's technically four forces yes I guess three of them were being in in the standard model like the weak there's the strong and the electromagnetic and then there's gravity in this gravity which we don't worry about that because maybe maybe we bring that up at the end yeah gravity so far we don't have a quantum theory of and if you can solve that problem you win a Nobel Prize well we're gonna have to bring up the graviton at some point I'm gonna ask you but let's let's leave that to the side for now so those three okay fine man a electromagnetic force the the quantum field yeah where does the weak force come in so so yeah well first of I mean the strong force a bit easiest the strong force is a little bit like the electromagnetic force it's a force that binds things together so that's the force that holds quarks together inside the proton for example so a quantum field theory of that force is discovered in I think it's in the sixties and it predicts the existence of new force particles called gluons so gluons are a bit like the photon the photon is the particle of electromagnetism gluons are the the particles of the strong force and so there's there's just like there's an electromagnetic field there's something called a gluon field which is also all around us but these part there's some of these particles I guess the force carriers or whatever they carry that well it depends how you want to think about it I mean really the field the strong force field the gluon field is the thing that binds the quarks together the gluons are the little ripples in that field so that like in the same way that the photon is a ripple in there in the electromagnetic field but the thing that really does the binding is the field I mean you may have heard people talk about things like verge as you've heard the phrase virtual particle so sometimes in some if you hear people describing how forces are exchanged between particles they quite often talk about the idea that you know if you have an electron and another electron say and they're repelling each other through the electro bratok electromagnetic force you can think of that as if they're exchanging photons so they're kind of firing photons backwards and forwards between each other and that causes them to repel therefore time is then a virtual particle yes that's what we call a virtual particle in other words it's not a real thing doesn't actually exist so it's an artifact of the way theorists do calculations so when they do calculations in quantum field theory rather than there's no one's discovered a way of just treating the whole field you have to break the field down into simpler things so you can basically treat the field as if it's made up of lots of these virtual photons but there's no experiment that you can do that couldn't detect these particles being exchanged what's really happening in reality is the electromagnetic field is warped by the charge of the electron and that causes the force but the way we do calculations involves parties let's say it's a bit confusing but it is really a mathematical technique it's not something that corresponds to reality I mean that's part I guess of the fireman diagrams yes is this virtual product okay that's right yeah some of these have mass some of them don't mm-hmm is that is that what what does that even mean not to have mass and maybe you can say well which one of them's have mass or which don't okay so and why is mass important or relevant in this cupboard in this in this field view of the universe well there are only two particles in the standard model that don't have mass which are the photon and the gluons so they are massless particles but the electron the quarks and they're a bunch of other particles I haven't discussed there's something called a muon and a Tau which are basically heavy versions of the electron that are unstable you can make them in accelerators but they don't form atoms or anything they don't exist for long enough but all the matter particles there are twelve of them six quarks and six what we call leptons which includes the electron and it's too heavy versions and three neutrinos all of them have mass and so do this is the critical bit so the weak force which is the third of these quantum forces which is one of the hardest to understand the force particles of that force have very large masses and there are three of them they're called the W plus the W minus and the Z boson and they have masses of between 80 and 90 times that of the the protons they're very heavy learn wow they're very heavy things they're what the heaviest I guess they're not the heaviest the heaviest particle is the top quark which has a mass of about 175 ish protons so that's really massive we don't know why is so massive but they're coming back to the weak force so that the the problem in the 60s and 70s was that the reason that the electromagnetic force is a force that we can experience our everyday live so if we have a magnet and a piece of metal you can hold it you know a meter apart if it's powerful laughs and you'll feel a force whereas the weak force only is becomes apparent when you basically have two particles touching at the scale of a nucleus so if you get two very short distances before this force becomes manifest it's not doesn't we don't get weak forces going on in this room they don't notice them and the reason for that is that the particle well the the field that transmits the weak force the particle that's associated with that field has a very large mass which means that the field dies off very quickly says you whereas an electric charge if you were to look at the shape of the electric field it would fall off with this you know this one called the inverse square law which is the idea that the force halves every time you double the distance no sorry it doesn't have it quarters every time you see every time you double the distance between say the two particles whereas the weak force kind of you move a little bit away from the nucleus and just disappears the reason for that is because these these fields the particles that go with them have a very large mass but the problem that was that theorists faced in the sixties was that if you tried to introduce massive force fields the theory who gave you nonsensical answers so you'd end up with infinite results for a lot of the calculations you tried to do so the basically it turned it seemed that quantum field theory was incompatible with having massive articles not just the force particles actually but even the electron was a problem so this is where the Higgs that we sort of alluded to comes in and the solution was to say okay well actually all the particles in the standard model of mass they have no mass so the quarks the electron they don't have a mass neither do these weak particles they don't have mass either what happens is they actually acquire mass through another process they get it from somewhere else they don't actually have it intrinsically so this idea that was introduced by what Peter Higgs is the most famous but actually they're about six people that come up with the idea more or less at the same time is that you introduce a new quantum field which is another one of these invisible things as everywhere and it's through the interaction with this field that particles get mass so you can think of say an electron in the Higgs field it kind of Higgs field kind of bunches around the electron it sort of a drawn towards the electron and that energy that's stored in that field around the electron is what we see as the mass of the electron but if you could somehow turn off the Higgs field then all the particles in nature would become massless and fly around at the speed of light so this this idea of the Higgs field allowed other people other theorists to come up with a well it was another a unit basically a unified theory of the electromagnetic force on the weak force so once you bring in the Higgs field you can combine two of the forces into one so it turns out the electromagnetic force and the weak force are just two aspects of the same fundamental force and at the LHC we go to high enough energies that you see these two forces unifying effectively so that so first of all it started as a theoretical notion like this is just something and then I mean wasn't the Higgs called the god particle at some point it was by a guy trying to sell popular science books yeah yeah but by me I am because when I was hearing it I thought it would I mean that would solve a lot of the you know file a lot of our ideas of physics was Molloy's my notion but maybe you can speak to that was is as big of a leap is it as a god particle is it a Jesus particle which which you know what's the big contribution of Higgs in terms of this unification power yeah I mean to understand that I maybe helps know the history a little bit so when the what we call electroweak theory was put together which is where you unify electromagnetism with the weak force and the Higgs is involved in all of that so that theory which was written in the mid-70s predicted the existence of four new particles the w+ boson the w- boson the z boson and the Higgs boson so there were these four particles that came with the theory that were predicted by the theory in 1983-84 the W's and the z particles were discovered an accelerator at CERN called the super proton synchrotron which was a seven kilometer particle collider so three of the bits of this theory had already been found so people are pretty confident from the 80s that the Higgs must exist because it was a part of this family of particles that this theoretical structure only works if the Higgs is there so what then happens this question right why is the LHC the size it is yes well actually the tunnel that the LHC is in was not built for the LHC it was built from for a previous accelerator called the large electron positron Collider so that that was bit began operation in the late 80s early 90s they basically did that's when they dug the 27 kilometer tunnel they put as accelerator into it the collider defiers electrons and anti electrons at each other electrons and positrons so the purpose of that machine was well it was actually to look for the Higgs that was one of the things it was trying to do it didn't man I didn't have enough energy to do it in the end but the main thing it was it studied the W and the Z particles at very high precision so it made loads of these things previously can you make a few of them at the previous accelerator you could study these really really precisely and by studying their properties you could really test this electroweak theory that had been invented in the seventies and really make sure that it worked so actually by 1999 when this machine turned off people knew well okay you never know until you until you find the thing but people were really confident electroweak theory was right and that the Higgs almost the Higgs or something very like the Higgs had to exist because otherwise the whole thing doesn't work it'd be really weird if you could discover and these particles they all behave exactly just theory tells you they should but somehow this key piece of the picture isn't it's not there so in a way it depends how you look at it the discovery of the Higgs on its own is it's also a huge achievement in many both experimenting and theoretically on the other hand it's this it's like having a jigsaw puzzle where every piece has been filled in you've this beautiful image there's one gap and you kind of know that that piece must be there something right so yeah so the discovery in itself although it's important is not so interesting it's a good confirmation of the obvious yes at that point but what makes it interesting is not that it just completes the standard model which is a theory that we've known had the basic layout offs for 40 years or more now it's that the Higgs actually is a is a unique particle is very different to any of the other particles in the standard model and it's a theoretically very troublesome particle there are a lot of nasty things to do with the Higgs but also opportunities so that we basically don't really understand how such an object can exist in the form that it does so there are lots of reasons for thinking that the Higgs must come with a bunch of other particles or that it's perhaps made of other things so it's not a fundamental particle that it's made of smaller things I can talk about that if you like a bit that's that's still an ocean so yeah so the Higgs might not be a fundamental particle there may be some in my oh man so that that is an idea it's not you know it's not been demonstrated to be true but I mean there's all of these ideas basically come from the fact that it's a this is this is a problem motivated a lot of development in physics in the last 30 years or so and there's this basic fact that the higgs field which is this field that's everywhere in the universe this is the thing that gives mass to the particles and the Higgs field is different from ever all the other fields in that let's say you take the electromagnetic field which is you know if we actually were to measure the electromagnetic field we would measure all kinds of stuff going on because there's light there's gonna be microwaves and radio waves and stuff but let's say we could go to a really really remote part of empty space and shield it and put a big box around it and then measure the electromagnetic field in that box the field would be almost zero apart from some little quantum fluctuations but basically it goes to naught the Higgs field has a value everywhere so it's a bit like the hole it's like the entire of space has got this energy stored in the Higgs field which is not zero it's it's finite it's got some it's a bit like having the the temperature of space raised to you know some background temperature and it's that energy that gives mass to the particles so the reason that electrons and quarks have mass is through the interaction with this energy that's stored in the Higgs field now it turns out that the precise value this energy has has to be very carefully tuned if you want a universe where interesting stuff can happen so if you push the higgs field down it has a tendency to collapse to what there's a tenon if you do you're sort of naive calculations they're basically two possible likely configurations for the Higgs field which is either it's zero everywhere in which case you have a universe which is just particles with no mass that can't form atoms and just fly by at the speed of light or it explodes to an enormous value what we call the Planck scale which is the scale of quantum gravity and at that point if the Hicksville was that strong even an electron would become so massive that it would collapse into a black hole and then you have a universe made of black holes and nothing like us so it seems that the the strength of the Higgs field is - it could achieve the value that we see requires what we call fine-tuning of the laws of physics you have to fiddle around with the other fields in the standard model and their properties to just get it to this right sort of Goldilocks value that allows atoms to exist this is deeply fishy people really dislike this well yeah I guess well so what would be a so - two explanations one there's a god the design this perfectly and two is there's an infinite number of alternate universes and we'll just happen to being the one in which life is possible yeah complexity so when you say I mean life any kind of complexity that's not either complete chaos or black holes yeah yeah I mean how does that make you feel what do you make that has such a fascinating notion that this perfectly tuned field that's the same everywhere yeah is there what do you make of that yeah well you make of that I mean yeah you like that two of the possible explanations yeah I mean well someone you know some cosmic creator way yeah let's fix that to be at the right level that's more possibility I guess it's not a scientifically test for one but you know theoretically I guess it's possible sorry to interrupt but there could also be not a designer but could never be just I guess I'm not sure what that would be but as some kind of force that that some kind of mechanism by which this this this kind of field is enforced in order to create complexity basic basically forces that pull the universe towards an interesting complexity I mean yeah I mean I has those ideas I don't really subscribe to them as I'm saying it sounds really stupid no I mean yeah and there are definitely people that make those kind of arguments you know there's ideas that I think it's Lise Mullins idea one I think that you know universes are born inside black holes and so universe is that behaved like Darwinian evolution of the universe where universes give birth to other universes and they've universes where black holes can form are more likely to give birth to more universes so you end up with universes which have similar laws I mean I don't whatever but why I talked to dr. Lee recently understand this podcast and he's he's a reminder to me that the physics community has like so many interesting characters yeah it's fascinating yeah anyway so so I mean as an experimentalist I tend to sort of think these are interesting ideas but they're not really testable so I tend not to think about very much so I mean going back to the science of this there wasn't that there is an explanation there is a possible solution to this problem of the Higgs which doesn't involve multiverses or creators fiddling about were the laws of physics if the most popular solution was something called supersymmetry which is a theory which is involves a new type of symmetry of the universe in fact it's one of the last types of symmetries that is possible to have that we haven't already seen in nature which is a symmetry between force particles and matter particles so what we call fermions which held before the matter particles and bosons which were force particles and if you have supersymmetry then there is a superpartner for every particle in the standard model and the without going to the details the effect of this basically is that you have a whole bunch of other fields and these fields cancel out the effect of the standard model fields and they stabilize the Higgs field at a nice sensible value so in supersymmetry you naturally without any concurring about with the constants of nature or anything you get a Higgs field with a nice value which is the one we see so this is one of the written supersymmetry has also got lots of other things going for it it predicts the existence of a dark matter particle which would be great it you know it potentially in suggests that the the strong force and the electroweak force unify high energy so lots of reasons people thought this was a productive idea and when the LHC was just before it was turned on there was a lot of hype I guess a lot of an expectation that we would discover these super partners because and particularly the main reason was that if if supersymmetry stabilizes the higgs field at this nice Goldilocks value these super particles should have a mass around the energy that we're probing at the LHC around the energy of the Higgs so it was kind of thought you discovered the Higgs you probably discover superpartners so once you start creating ripples in this fix field you should be able to see these kinds of you should be yeah super fields would be there but I said well at the very beginning I said we're probing the vacuum what I mean is really that you know okay let's say these super fields exist the vacuum contains super fields they're they're these super symmetric fields if we hit them hard enough we can make them vibrate we see super particles come flying out that's the sort of that's the idea the hope ok that's the whole alone but we haven't but we haven't so so far at least I mean we've had now a decade of data taking at the LHC no signs of superpartners have supersymmetric particles have been found in fact no signs of any physics any new particles beyond the standard model have been found so supersymmetry is not the only thing that can do this there are other theories that involve additional dimensions of space or potentially involve the Higgs boson being made of smaller things being made of other particles that's an interesting you know I haven't heard that before that's really that's an issue but could you maybe linger on that like what what could be what could Higgs particle be made of well so the the oldest I think the original ideas about this was these theories called Technicolor which were basically like an analogy with the strong force so the idea was the Higgs boson was a bound state of two very strongly interacting particles that were a bit like quarks so like quarks but I guess higher energy things with a super strong force so not the strong force but a new force that was very strong and the Higgs was a bound state of these these objects and the Higgs wouldn't principle if that was right would be the first in a series of Technicolor particles Technicolor I think not being a theorist but it's not biz basically not done very well there's particularly since the LHC found the Higgs that kind of it rules out you know a lot of these Technicolor theories but there are other things that are a bit like Technicolor so there's a theory called partial composite nurse which is an idea that some of my colleagues that Cambridge have worked on which is a similar sort of idea that the Higgs is a bound state of some strongly interacting particles and that the standard model particles themselves the more exotic ones like the top quark are also sort of mixtures of these composite particles so it's a kind of an extension to the standard model which explains this problem with the Higgs bosons Goldilocks value but also helps us understand we have we're in a situation now again a bit like the periodic table where we have six quarks six leptons in this kind of you can range in this nice table and there you can see these columns where the patterns repeat and you go okay maybe there's something deeper going on here is that you know and and so this would potentially be something this partial composite NOS theory could Lane sort of enlarged this picture that allows us to see the whole symmetrical pattern and understand what the ingredients why do we have wind so one of the big questions in particle physics is why are there three copies of the matter particles so in what we call the first generation which is what we're made of there's the electron the electron neutrino the up quark on the down quark they're the most common matter particles in the universe but then there are copies of these four particles in the second and the third generations so things like muons and top quarks and other stuff we don't know why we see these patterns we have no idea where it comes from so that's another big question you know can we find out the deeper order that explains this particular tape period table of particles that we see is it possible that the the deeper order includes like almost a single entity so like something that I guess like string theory dreams about is this is this part is this essentially the dream is to discover something simple beautiful and unifying yeah I mean that is the dream and it I think for some people for a lot of people it still is the dream so there's a great book by Steven Weinberg who is one of the theoretical physicists who was instrumental in building the standard model so he came up with some others with the electroweak theory the theory that unified electromagnetism and the weak force and here at this book I think it was towards the end of the 80s early 90s called dreams of a final theory which is a very lovely quite short book about this idea of a final unifying theory that brings everything together and I think you get a sense reading his book written at the end of 80s and early 90s that there was this feeling that such a theory was coming and that was the time when string theory had been was was very exciting so string theory there's been this thing called the superstring revolution and theoretical physical very excited they discovered these theoretical objects these little vibrating loops of string that in principle not only was a quantum theory of gravity but could explain all the particles in the standard model and bring it all together and you as you say you have one object the string and you can pluck it and the way it vibrates gives you these different notes each of which is a different part so it's a very lovely idea but the problem is that well there's a there's a few people discover their mathematics is very difficult so people have spent three decades and more trying to understand string theory and I think you know if you spoke to most string theorists they would probably freely admit that no one really knows what string theory is yet I mean there's been a lot of work but it's not really understood and the other problem is that string theory mostly makes predictions about physics that occurs energies far beyond what we will ever be able to probe in the laboratory yeah probably ever by the way so sorry they take a million tangents but is there room for complete innovation of how to build a particle collider that could give us an order of magnitude increase in any kind of energies or do we need to keep just increasing the size of thing I mean maybe yeah I mean there are ideas but to give you a sense of the Gulf that has to be bridged so the LHC collides particles at an energy of what we call fourteen terror electron volts so that's basically equivalent of you accelerated a proton through 14 trillion volts that gets us to the energies where the Higgs and these weak particles live they're very massive the the scale where strings become manifest is something called the Planck scale which i think is of the order 10 to the hang on again that's right is 10 to the 18 Giga electron volt so about 10 to the 15 terror electron volts so you're talking you know trillions of times more energy more the 10 to the 15 the 10 to the 14th larger it's a very big number so you know we're not talking just an order of magnitude increase in energy we're talking 14 orders of magnitude energy increase so to give you a sense of what that would look like were you to build a particle accelerator with today's technology bigger or smaller and then our solar system as start the size of the galaxy the galaxy so you need to put a particle accelerator that circled the Milky Way to get to the energies where you would see strings if they exist so there's a fundamental or problem which is that most of the predictions of the unified these unified theories of quantum theories of gravity only make statements that are testable are energies that we will not be able to probe let and barring some unbelievable you know completely unexpected technological or scientific breakthrough which is almost impossible to imagine you never never say never but it seems very unlikely yeah I can just see the news story Elon Musk decides to build a particle collider the size of our it would have to be we'd have to get together with all our galactic neighbors to pay for everything what is the exciting possibilities of the Large Hadron Collider what is there to be discovered in this in this order of magnitude of scale is there other bigger efforts on the horizon big in this space what are the open problems the exciting possibilities you mentioned supersymmetry yeah so well there are lots of new ideas well there's lots of problems that we're facing so there's a problem with the Higgs field which supersymmetry was supposed to solve there's the fact that 95% of the universe we know from cosmology astrophysics is invisible that it's made of dark matter and dark energy which are really just words for things that we don't know what they are it's what Donald Rumsfeld called a known unknown we know we don't know what they are well that's it's better than an unknown unknown yeah well there may be some unknown unknown but I don't know what those yeah but but the the hope is the particle accelerator could help us make sense of dark energy dark matter there's still there's just some hope for that there's hope for that yes so one of the hopes is the LHC could produce a Dark Matter particle in its collisions and you know it may be that the LHC will still discover new particles that it might still supersymmetry could still be there we just it's just maybe more difficult to find than we thought originally and and you know dark matter particles might be being produced but we're just not looking in the right part of the data for them that that's possible it might be that we need more data that these processes are very rare and we need to collect lots and lots of data before we see them but I think a lot of people would say now that the chances of the LHC directly discovering new particles in the near future is quite slim it may be that we need a decade more data before we can see something or we may not see anything that's the that's what we are so I mean the the physics the experiments that I work on so I work on a detector called LHC B which is one of these four big detectors that are spaced around the ring and we do slightly different stuff to the big guys there's two big experiments called outlets and CMS three thousand physicists and scientists and computer scientists on them each they are the ones that discovered the Higgs then they look for supersymmetry and dark matter and so on what we look at our standard model particles called B quarks which depending on your preference is either bottom or beauty we tend to say beauty because it sounds sexier yeah but these particles are interesting because they of you can make lots of them we make billions or Billy a hundreds of billions of these things you can therefore measure their properties very precisely so you can make these really lovely precision measurements and what we are doing really is a sort of complementary thing to the other big experiments which is they if you think the self analogy that I often use is if you imagine you're looking in you're in a jungle and you're looking for an elephant same and you are a hunter and you're kind of like they said there's the relevance very rare you don't know where in the jungle the jungles big so there's two ways you go about this either you can go out wandering around the jungle and try and find the elephant the problem is if the elephant there's only one elephant the jungles big the chances of running into it very small or you could look on the ground and see if you see footprints left by the elephant and if the elephant's moving around you've got a chance that you're better chance maybe of seeing the elephant's footprints if you see the footprints you go okay there's an elephant maybe don't know what kind of elephant it is but I got a sense there's something out there so that's sort of what we do we are the footprint people we are we're looking for the footprint the impressions that quantum fields that we haven't managed to directly create the particle of the effects these quantum fields have on the ordinary standard model fields that we already know about so these these be particles the way they behave can be influenced by the presence of say super fields or dark matter fields or whatever you like and they're the way they decay and hey've can be altered slightly from what our theory tells us they ought to behave sure and it's easier to collect huge amounts of data and B and B quarks we get you know billions and billions of these things you can make very precise measurements and the only place really at the LHC or in really in high-energy physics at the moment where there's fairly compelling evidence that there might be something beyond the standard model is in these be these beauty quarks decays just to clarify which is the difference between the different the four experiments for example the emission is it the kind of particles that are being collided is it the energies that were which there collided what's the fundamental difference different experiments the collisions are the same what's different is the design of the detectors so Atlas and CMS are called they're called what are called general purpose detectors and they are basically barrel shaped machines and the collisions happen in the middle of the barrel and the barrel captures all the particles that go flying out in every direction so in a sphere effectively they can flying out and it can record all of those particles and what's the site of interrupting but what's what's the mechanism of the recording oh these detectors if you've seen pictures of them the huge like Atlas is 25 meters high in 45 meters long and vast machines instruments I guess you to call them really they are they're kind of like onions so they have layers concentric layers of detective detectors different sorts of detectors so close into the beam pipe you have what a record usually made of silicon their tracking detectors so they're little made of strips of silicon or pixels of silicon and when a particle goes through the silicon it gives a little electrical signal and you get these dots you know electrical dots through your detector which allows you to reconstruct the trajectory of the particle so that's the middle and then the outside of these detectors you have things called calorimeters which measure the energies of the particles and in very edge you have things called muon chambers which basically met these muon particles which are the heavy version of the electron they are there like high-velocity bullets and they can get right to the edge of the detectors if you see something at the edge that's a muon so that's broadly how they work and all there's being recorded that's all being fed out to you know computers must be awesome okay so LHCb is different so we because we're looking for these B quarks yes B quarks tend to be produced along the beam lines so in a collision the B quark tend to fly sort of close to the beam pipe so we built the detector that sort of pyramid cone-shaped basically that just looks in one directions we ignore if you have your collision stuff goes everywhere we ignore all the stuff over here and going off sideways we're just looking in this little region close to the beam pipe where most of these B quarks are made so is there a different aspect of the sensors involved in the collection of the B quark yes Jack thérèse there are some differences so one of the differences is that one of the ways you know you've seen a B quark is that B quarks are actually quite long-lived by particle standards so they live for 1.5 trillions of a second which is if you're if you're a fundamental particle is a very long time because you know the Higgs boson I think lives for about a trillionth of a trillionth of a second or maybe even less than that so these are quite long-lived things and they will actually fly a little distance before they decay so they will fly you know a few centimeters maybe if you're lucky then they'll decay into other stuff so what we need to do in the middle of the detector you want to be able to see you have your place where the protons crash into each other and that produces loads of particles that come flying out so you have loads of lines loads of tracks that point back to that proton collision and then you're looking for a couple of other tracks maybe two or three that point back to a different place this may be a few centimeters away from the proton collision and that's the sign that little B particle has flown a few centimeters in decayed somewhere else so we need to be able to very accurately resolve the proton collision from the B particle decay so we are the middle of our detector is very sensitive and it gets very close to the collisions so you have this really beautiful delicate silicon detector that sits I think it's seven mil millimeters from the beam and the LHC beam has as much energy as a jumbo jet takeoff so it's enough to melt a ton of copper and as you have this furiously powerful thing sitting next it's tiny delicate you know sense of the consent sir so that into those aspects of our detector that are specialized to desert to discover these particular B quarks that were interested in and is there I mean I remember seeing somewhere that there's some mention of matter and antimatter connected to the be the these beautiful quarks who's that what what's the connection wha yeah what's the connection there yes there is a connection which is that when you produce these B particles it'll be these particles consider to the B quark you see the thing that B quark is inside so they're bound up inside what we call beauty particles where the B quark is joined together with another quark or two maybe two other clocks depending on what it is there a particular set of these B particles that exhibit this property called oscillation so if you make her for the sake of argument a matter version of one of these B particles as it travels because of the magic of quantum mechanics it oscillates backwards and forwards between its matter and antimatter versions so just this weird flipping about backwards and forwards and what we can use this for is a laboratory for testing the symmetry between matter and antimatter so if the if the symmetry but transparency is precise its exact then we should see these B particles decaying as often as matter as they do as antimatter because this oscillation should be even it should spend much time in each state but what we actually see is that one of the states it spends more time and it's more likely to decay in one state than the other so this gives us a way of testing this fundamental symmetry between matter and antimatter so what can you sort of return the the question or before about this fundamental symmetry it seems like if this perfect symmetry between matter and antimatter if the equal amount of each in our universe it would just destroy itself mm-hm and just like you mentioned we seem to live in a very unlikely universe where it it doesn't destroy itself yeah so do you have some intuition about about why that is I mean well I I'm not a theory I don't have any particular ideas myself I mean I sort of do measurements to try and test these things but I mean it's in terms of the basic problem is that in the Big Bang if you use the standard model to figure out what ought to have happened you should have got equal amounts of matter antimatter made because whenever you make a particle in our collide collisions for exam but when we collide stuff together you make a particle you make an antiparticle they always come together they always annihilate together so there's no way of making more matter than antimatter that we've discovered so far so that means in the Big Bang you get equal amounts of matter antimatter as the universe expands and cools down during the Big Bang not very long after the Big Bang I think a few seconds off the Big Bang you have this event called the great annihilation which is where all the particles antiparticles smack into each other annihilate turn into light mostly and you end up with a universe later right if that was what happened then the universe we live in today would be black and empty apart from some photons that would be it so there's stuff in this there is stuff in the universe it appears to be just made of matter so there's this big mystery as to where the how did this happen and there are various ideas which all involve sort of physics going on in the first trillionth of a second or so of the Big Bang so it could be that one possibility is that the Higgs field is somehow implicated in this that there was this event that took place in the early universe where the higgs field basically switched on it acquired its modern value and when that happened this caused all the particles to acquire mass and the universe basically went through a phase transition where you had a hot plasma of massless particles and then in that plasma it's almost like a gas turning into droplets of water you get kind of these little bubbles forming in the universe where the Higgs field has acquired its modern value the particles have got mass and this phase transition in some models can cause more matter than antimatter to be produced depending on how matter bounces off these bubbles in the early universe so that's one idea there's other ideas to do with neutrinos that there are exotic types of neutrinos that can decay in a biased way to just matter and not to antimatter so and people are trying to test these ideas that's what we're trying to do at LHC B is there's neutrino experiments planned they're trying to do these sorts of things as well so yeah there are ideas but at the moment no clear evidence for which of these ideas might be right so we're talking about some incredible ideas by the way never hurt anyone be so eloquent about describing even just a standard model so I'm in awe just listening if you're interesting just have having fun enjoying it so the yes the theoretical the particle physics is fascinating here to me one of the most fascinating things about the Large Hadron Collider is the human side of it that a bunch of sort of brilliant people that probably have egos got together and we collaborate together and countries I guess collaborate together you know for the funds and that everything's just collaboration everywhere because you maybe I don't know what the right question here to ask but almost what's your intuition about how was possible to make this happen and what are the lessons we should learn for the future of human civilization in terms of our scientific progress because it seems like this is a great great illustration of us working together to do something big yeah I think it's possibly the best example maybe I can think of of international collaboration it isn't for some unpleasant purpose basically you know it's I mean so I I when I started out in the field in 2008 I as a new PhD student the LHC was basically finished so I didn't have to go around asking for money for it or trying to make the case so I have huge admiration admiration for the people who managed that because this was a project that was first imagined in the 1970s and the late 70s was when the first conversations about the LHC were were mooted and it took two and a half decades of campaigning and fundraising and persuasion until they started breaking ground and building the thing in the early noughties in 2000 so I mean I think the reason just from uh sort of from the point of view of this sort of science the scientists there I think the reason it works ultimately is that everywhere everyone there is there for the same reason which is well in principle at least they're there because they're interested in the world they want to find out you know what are the basic ingredients of our universe what are the laws of nature and so everyone is pulling in the same direction of course everyone has their own things they're interested in everyone has their own careers to consider and you know and pretend that there isn't also a lot of competitions this is funny thing in these experiments where your collaborators your eight-hundred collaborators in LHC be but you're also competitors because you're academics in your various universities and you want to be the one that gets the paper out on the most citing you know new measurements so there's this funny thing where you're kind of trying to stake out your territory while also collaborating and having to work together to make the experiments work and it does work amazingly well actually considering all of that and I think there was actually I think McKinsey or one of these big management consultancy firms went into CERN maybe a decade or so ago to try to understand how these organizations functions they figure it out I don't think they could I mean I think one of the things that interests one of the other interesting things about these experiments is that their big operations like say outlets there's 3,000 people now there is a person nominally who is the head of Atlas they're called the spokesperson and the spokesperson is elected by usually by the collaboration but they have no actual power really I mean they can't fire anyone they're not anyone's boss so you know my boss is it prefers the professor a professor at Cambridge not the head of my experiments the head of my experiment can't tell me what to do really and I mean there's all you got is independent academics who are their own bosses who you know so that somehow it nonetheless by kind of consensus and discussion and lots of meetings these you know things do happen and it does get done but it's like the Queen hearing you in the UK is the spokesperson again so no actual don't elect her know whatever everybody seems to love her I don't know from the at my outside perspective yeah but yeah giant egos brilliant people and moving forward do you think there's I would pick up one thing you said just that just the brilliant people thing cuz I'm not I'm not saying that people aren't great yeah but I think there is this sort of impression that physicists will have to be brilliant or geniuses which is not true actually and you know you have to be relatively bright for sure but you know a lot of people a lot of the most successful experimental physicists and not necessarily the people with the biggest brains they're the people who you know particularly one of the skills that's most important in particle physics is the ability to work with others and to collaborate and exchange ideas and also to work hard and it's a sort of often it's more a determination or a sort of other set of skills is not just being you know kind of some great brain very true so in I mean there's parallels to that in the machine learning world if you wanted if you want to solve any real-world problems which I see is the the particle accelerators essentially a real-world instantiation of theoretical physics and for that you have to not necessarily be brilliant but be sort of obsessed systematic rigorous sort of unbel stubborn all those kind of qualities that make for a great engineer so this science scientist purely speaking the practitioner of the scientific method so you're right but nonetheless Timmy that's Timmy has been my dad as a physicist I argue with him all the time to me engineering is the highest form of science and he thinks that's all nonsense that the real work is done by the theory edition so he in fact we have arguments about like people like Elon Musk for example because I think his work is quite brilliant but he's fundamentally not coming up with any serious breakthroughs he's just creating in this world implementing I'd like making ideas happen and have a huge impact to me that is that's the Edison that Timmy is is a brilliant work but to him it's you know it's messy details that somebody will figure out anyway that's it I mean I don't know whether you think there is a actual difference in temperament between say a physicist and engineer whether it's just what you got interested in I don't know I mean because you know a lot of what experimental physicists do is to some extent engineering and it's not what I do I mostly do data stuff but you know a lot of people would be called electrical engineers but they trained as physicists but they learn electrical engineering for example because they were building detectors so there's not such a clear divide I think yeah it's interesting I mean there but there does seem to be like you work with data there does seem to be a certain like I love data collection there might be an OCD element or something that you're more naturally predisposed to as opposed to theory like I'm not afraid of data I love data and there's a lot of people machine learning core more like they're they're basically afraid of data collection afraid of datasets afraid of all that they just want to stay more than theoretical and they're really good at it space I don't know if that's a genetic that's your upbringing the way you with it the way you go to school but looking into the future of LHC and other colliders so there's in the in America there's the whatever was called the super there's a lot of super superconducting supercollider is super gonna desert roll desert Ron yeah so that was cancelled the construction of that yeah which is a sad thing but what do you think is the future of these efforts will a bigger Collider be built will LHC be expanded what do you think well in the near future the LHC is gonna get an upgrade so that's pretty much confirmed I think it is confirmed which is the it's not an energy upgrade it's and what we call the luminosity upgrade so basically means increasing their data collection rates so more collisions per second basically because after a few years of data taking you get this law of diminishing returns where each year's worth of data is a smaller and smaller fraction of the lot you've already got so to get a real improvement in sensitivity you need to increase the data rate by an order of magnitude so that's what this upgrade is gonna do an LHC be at the moment the whole detector is basically being rebuilt to allow it to record data at a much larger rate than we could before so that will make her sensitive to whole loads of new processes that we weren't able to study before and you know I mentioned briefly these anomalies anomalies that we've seen so we've seen a bunch of very intriguing anomalies in these B quark decays which may be hinting at the first signs of this kind of the elephant you know that the the size of some new quantum field or fields may be beyond the standard model it's not yet at the statistical threshold where you can say that you've observed something but there's lots of anomalies in many measurements that all seem to be consistent with each other so it's quite interesting so you know the upgrade will allow us to really homed in on these things and see whether these alumni's are real because if they are real and it kind of connects to your point about the next generation of machines what we would have seen then is you know we will have seen the tail end of some quantum field in influencing these big quarks what we then need to do build a bigger Collider to actually make the the particle of that field so if these are if these things really do exist so that would be one argument I mean I mean so at the moment Europe has going through this process of thinking about the strategy for the future so there are a number of different proposals on the table one is for sort of higher energy upgrade at the LHC where you just build more powerful magnets and put them in the same tunnel that's a sort of cheap cheaper less ambitious possibility most people don't really like it because it's sort of a bit of a dead end because once you've done that there's nowhere to go well there's a machine called clique which is a compact linear collider which is a electron positron Collider that's uses a novel type of acceleration technology to accelerate at shorter distances we're still talking kilometers long but not like 100 kilometers long and then the probably the project that is I think getting the most support it'll be interested to see what happens something called the future circular Collider which is a really ambitious long-term multi-decade project to build a 100 kilometer circumference tunnel under the Geneva region the LHC would become a kind of feeding machine it would just feed for the same area so there would be a theater for there yeah so it kind of the edge machine would be where the LHC is but it would sort of go under Lake Geneva and round to the Alps basically since you know up to the edge of the Geneva base and so basically biggest it's the biggest tunnel you can fit in the region based on the geology alarm yes it's big it'd be a long drive if your animal experiments on one side you got to go back to CERN for lunch so that would be a pain but you know so this project is in principle is actually to accelerators the first thing you would do is put an electron-positron machine in the 100 kilometer tunnel to study the Higgs so you'd make lots of Higgs boson study it really precisely in the hope that you see it misbehaving and doing something it's not supposed to and then in the much longer term a hundred with that machine gets taken out you put in a proton proton machine so it's like the LHC but much bigger and that's the way you start going and looking for dark matter or you're trying to recreate this a phase transition that I talked about in the early universe but you can see matter antimatter being made for examples there's lots of things you can do with these machines the problem is that they will take you know the most optimistic you're not going to have any data from any of machines until 2040 or you know because they take such a long time to build and they're so expensive so you have W a process of R&D design and also the political case being made so la seal cost a few billion depends how you count it I think most of the sort of more reasonable estimates that take everything into account properly it's around the sort of 10 11 12 billion euro mark what would be the future sir I forgot the numerator future circular Collider future circular because you mean I would call it that when it's built because it won't be the future anymore but a very big Hadron Collider I don't know but yeah that will I know I should know the numbers but I think the whole project is estimated at about 30 billion euros but that's money spent over between now and 2017 probably which is when the last bit of it would be sort of finishing up I guess so you're talking a half a century of science coming out of this thing shared by many countries so the actual cost the arguments that are made is that you could make this project fit within the existing budget of certain if you didn't do anything else it's earned by the way we didn't mention what is CERN CERN is the European Organization for Nuclear Research as an international organization that was established in the 1950s in the wake of the Second World War as a kind of it was sort of like a scientific martial plan for Europe the idea was that you bring european science back together for peaceful purposes because what happened in the 40s was you know a lot of particular scientists but a lot of scientists from Central Europe had fled to the United States and Europe and sort of seen his brain drain so it's a desire to bring the community back together for a project that wasn't building nasty bombs but was doing something that was curiosity driven so and that has continued since then so it's kind of a unique organization it's you to be a member as a country you sort of sign up as a member and then you have to pay a fraction of your GDP each year is a subscription I mean it's a very small fraction relatively speaking I think it's like I think the UK's contribution is 100 or 200 million quid or something like that yeah which is quite a lot but no not that's fastest man I mean just the whole thing that is possible it's beautiful it's a beautiful idea especially with when there's no wars on the line it's not like we're freaking out as we're actually legitimately collaborating mmm to do good sighs one of the things I don't think we really mentioned is that in the final side that sort of the data analysis side is there a break there was possible there and the machine learning side like is there is there a lot more signal to be mined in more effective ways from the actual raw data yeah a lot of people are looking into that I mean so what we know I use machine learning in my data analysis but pretty knotty you know basic stuff because I'm not a machine learning expert and just a physicist who had to learn to do this stuff for my day job so what a lot of people do is they use kind of off-the-shelf packages that you can train to do signal noise you know just like a cleanup yeah but one of the big challenges you know the big challenge of the data is a it's volume there's huge amounts of data so the LHC generates now okay I bought the actual numbers are but if you we don't record all our data we record a tiny fraction of the data it's like of order one ten thousandth or something I think right around that so it's it votes mostly gets thrown away you couldn't record all the LHC data because it would fill up every computer in the world in the matter of days basically so there's this process that happens on live on the detector something called a trigger which in real time 40 million times every second has to make a decision about whether this collision is likely to contain an interesting object like a Higgs boson or a Dark Matter particle and it has to do that very fast and the software algorithms in the past were quite relatively basic you know they did things like measure mementos and energies of particles and put some requirements so you would say if there's a particle with an energy above some threshold then record this collision but if there isn't don't wear as now the attempt is get more and more machine learning in at the earliest possible stage because cool at the stage of deciding whether we want to keep this data or not but also even even maybe even lower down than that which is the point where there's this you know generally how the data is reconstructed is you start off with a digital a set of digital hits in your detector so Scannell saying did you see something do you not see something that has to be then turned into tracks particles going in different directions and that's done by using fits that fit through the data points and then that's passed to the algorithms that then go is this interesting or not what we better is if you could train machine learning to look at the raw hits the basic real base level information not have any of the reconstruction done and it just goes and it can learn to do pattern recognition on this strange three dimensional image that you get and potentially that's where you could get really big gains because our triggers tend to be quite inefficient because they don't have time to do the full whiz-bang processing to get all the information out that we would like because you have to do the decision very quickly so if you can come up with some clever machine learning technique then potentially you can massively increase the amount of useful data you record and you know get rid of more of the background earlier in the process yeah to me that's an exciting possibility because then you don't have to build a sort of you can get again without having to have to put an ephod whereas per hardware yeah but I do you need you need lots of new GPU farms I guess so hardware it still helps but yeah the you know I got a talk to you so if I'm not sure how to ask but you're clearly an incredible science communicator I don't know if that's the right term but you're basically a younger Neil deGrasse Tyson with a British accent huh so and you but I mean can you save where we are today actually yeah so today we're in the Royal Institution in London which is an old very old organization has been around for about two hundred years now I think maybe even I should know when it was founded so the early 19th century it was set up to basically communicate science the public so it was one of the first places in the world where scientists famous scientists would come and give talks so very famously my Humphrey Davy who you may know of who was the person who discovered nitrous oxide is a very famous chemist and scientists also discovered electronic sis so he used to do these fantastic was very charismatic speakers who's to peer here there was a there's a big desk they usually have in the inner theater and he would do demonstrations to the sort of the the folk of London back in the early 19th century and Michael Faraday who I talked about who is the person who did so much work connection Magnussen he used he lectured here he did experiments in the basement so this place has got a long history of both scientific research but also in the communication of scientific research so you gave a few lectures here how many - I've give I given you I given a couple of lectures in this theater before so I mean that's think so people should definitely go watch online it's there's just the explanation of particle physics that all the good thing it's incredible like your your lectures are just incredible I can't sing it enough pray so it was awesome but maybe can you say what did that feel like what was if you like to lecture here to talk about that and maybe from a different perspective more kind of like how the sausage is made is how do you prepare for that kind of thing how do you think about communication the process of communicating these ideas in a way that's inspiring to what I would say your talks are inspiring to like the general audience you don't actually have to be a scientist you can still be inspired without really knowing much of the you you start from the very basics so what's the preparation process and then the romantic question is what does that feel like to perform here I mean profession yeah I mean the process I mean the talk that the my favorite talk that I gave here was one called beyond the Higgs which you can find on the on the all institutions youtube channel which you should go and check out I mean and their channels got loads of great talks loads of great people as well I mean that one I sort of given a version of it many times so part of it is just practice right I and actually I don't have some great theory of how to communicate with people it's more just that I'm really interested and excited by those idiot and I like talking about them and through the process of doing that I guess I figured out stories that work and explanations that well you see a practice you mean legitimately just giving just giving talks given I said I started off you know when I was a PhD student doing talks in schools and and I still do that as well some of the time and doing things I haven't done a bit of stand-up comedy which was sort of went reasonably well even if it was terrifying and that's unusual as well there's also a new I wouldn't I wouldn't necessarily recommend you check that out I'm gonna post the links several places to make sure people click on it yeah it's basically I kind of have a story in my head and I is I you know I kind of I have a think about what I want to say I usually have some images to support what I'm saying and I get up and do it and it's not really I wish there was some kind of I probably should have some proper process this is very sounds like I'm just making up as I go along and I sort of am I think the fundamental thing they said I think it's like I don't know if you know who a guy named Joe Rogan is yes okay so he he's also kind of sounds like you in a sense that he's not very introspective about his process but he's an incredibly engaging conversationalist and I think one of the things that you and him share that I could see is like a genuine curiosity and passion for the topic I think that could be systematically caught you know cultivated I'm sure there's a process to it but you come to it naturally somehow I think maybe there's something else as well which is to understand something there's this quote by firemen whichever you like which is what I cannot create I do not understand so like I'm not I'm not like particularly super bright like so for me to understand something I have to break it down into its simplest element yes and that you know if and if I can then tell people about that that helps me understand it as well so I've actually I've learned I've learned to understand physics a lot more from the process of communication because it forces you to really scrutinize the ideas that you're communicating in a coffin makes you realise you don't really understand the ideas you're talking about and I'm writing a book at the moment I had this experience yesterday where I realized I didn't really understand a pretty fundamental theoretical aspect of my own subject and I had to go and hide to sort of spend a couple of days reading textbooks and thinking about it in order to make sure that the explanation I gave captured the got as close to what is actually happening in the theory and to do that you have to really understand it properly and yeah and there's layers to understanding yeah it seems like the more there must be some kind of Fineman law I mean the the more you the more you understand services simply you're able to really convey the you know the the essence of the idea right so it's just like this reverse the reverse effect there's like the more you understand the simpler the final thing that you actually convey and so the more accessible somehow it becomes that's why faint fineman's lectures are really accessible it was just counterintuitive yeah although there are some ideas that are very difficult to explain no matter how well or badly you understand like I still can't really properly explain the Higgs mechanism yeah with because some of these ideas only exist in mathematics really and the only way to really develop an understanding is to go unfortunately to a graduate degree in physics but you can get kind of a flavor of what's happening I think and is trying to do that in a way that isn't misleading but always also intelligible so let me ask them the romantic question of what to you is the most perhaps an unfair question what is the most beautiful idea in physics one that fills you with are is the most surprising the strangest the weirdest there's some a lot of different definitions of beauty mmm-hmm and I'm sure there's several for you but is there something just jumps to mind that you think is just especially I mean I well beautiful there's a specific thing in a more general thing so maybe the specific thing a first widget is a cone i first came across this as an undergraduate i found this amazing so this idea that the forces of nature electromagnetism strong force the weak force they arise in our theories has there a consequence of symmetries so symmetry is in the laws of nature in the equations essentially that used to describe these ideas the process whereby theories come up with these sorts of models as they say imagine the universe obeys this particular type of symmetry is a symmetry that isn't so far removed from a geometrical symmetry like the rotations of a cube it's not you can't think of it quite that way but it's sort of a similar sort of idea and you say okay if the universe respects the symmetry you find that you have to introduce a force which has the properties of electromagnetism or different symmetry you get the strong force or a different symmetry you get the weak force so these interactions seem to come from some deeper it suggests that they come from some deeper symmetry principle I mean depends a bit how you look at it cuz it could be that we were actually just recognizing symmetries in fact as you see but there's something rather lovely about that but I mean I suppose a bigger thing that makes me wonder is actually if you look at the laws of nature how particles interacts when you get really close down they're basically pretty simple things they bounce off each other by exchanging you know through force fields and they move around in very simple ways and somehow these basic ingredients these few particles that we know about and the forces creates this universe which is unbelievably complicated and has things like you and me in it and you know the earth and stars that make matter in there caused by this from the gravitational energy of their own bulk that then gets sprayed into the universe that forms other things I mean the fact that there's this incredibly long story that goes right back to you know the big it we can we can take the story right back to you know a trillionth of a second after the Big Bang we can trace the origins of the stuff that we're made from and it altum Utley comes from these simple ingredients with these simple rules and the fact you can generate such complexity from that is really mysterious I think and strange and it's not even a question that physicists can really tackle because we are sort of trying to find these really elementary laws but it turns out that going from elementary laws and a few particles to something even as complicated as a molecule becomes very difficult and so going from a molecule to a human being is a problem that just you know can't be can't be tackled at least not at the moment so yeah the emergence of complexity from simple rules is so beautiful and so mysterious and there's not either we don't have good mathematics to even try to approach that emergent phenomena that's why we have chemistry and biology and other subjects as well yeah I don't think I don't think there's a better way to end it Harry I can't I mean I think I speak for a lot of people that can't wait to see what happens in the next 5 10 20 years with you I think you're one of the great communicators of our time so I hope you continue that and I hope that grows and um definitely a huge fan so it was an honor to talk to you today thank someone on it thanks very much thanks for listening to this conversation with Harry cliff and thank you to our sponsors expressvpn and cash app please consider supporting the podcasts by getting expressvpn and expressvpn comm slash flexpod and downloading cash app and using collects podcasts if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon are simply connect with me on Twitter at Lex Friedman and now let me leave you with some words from Harry cliff you and I are leftovers every particle in our bodies is a survivor from an almighty shootout between matter and antimatter that happened a little after the Big Bang in fact only one in a billion particles created at the beginning of time have survived to the present day thank you for listening and hope to see you next time you |
Jack Dorsey: Square, Cryptocurrency, and Artificial Intelligence | Lex Fridman Podcast #91 | the following is a conversation with Jack Dorsey co-founder and CEO of Twitter and founder and CEO of square given the happenings at the time related to Twitter leadership and the very limited time we had we decided to focus this conversation on square and some broader philosophical topics and to save an in-depth conversation on engineering at AI and Twitter for second appearance in this podcast this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing as an aside let me mention the jack moved 1 billion dollars square equity which is 28% of his wealth to form an organization that funds kovin 19 relief first as Andrew yang tweeted this is a spectacular commitment and second it is amazing that it operates transparently by posting all its donations to a single Google Doc to me true transparency is simple and this is as simple as it gets this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma n as usual I'll do a few minutes of as now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by masterclass sign up on master class comm slash flex to get a discount and to support this podcast when I first heard about masterclass I thought it was too good to be true for $180 a year you get an all-access pass to watch courses from to list some of my favorites Chris Hadfield on space exploration Neil deGrasse Tyson and scientific thinking communication will write creator of Sim City and Sims both one of my favorite games on game design Jane Goodall on conservation Carlos Santana on guitar on my favorite guitar players Gary Kasparov on chess Daniel Negreanu on poker and many many more chris hadfield explaining caracas work and the experience of being launched into space alone is worth the money for me the key is to not be overwhelmed by the abundance of choice pick three courses you want to complete watch each all the way through it's not that long but it's an experience that will stick with you for a long time it's easily worth the money you can watch it on basically any device once again sign up on master class comm / Lex to get a discount and to support the spot cast and now here's my conversation with Jack Dorsey you've been on several podcasts Joe Rogan Sam Harris rich roll others excellent conversations but I think there's several topics that you didn't talk about that I think of fascinating that I love to talk to you about sort of machine learning artificial intelligence both the the narrow kind and the general kind and engineering at scale so there's a lot of incredible engineering going on the year part of crypto cryptocurrency a blockchain ubi all kinds of philosophical questions maybe we'll get to while life and death and meaning and beauty so you're involved in building some of the biggest network systems in the world sort of trillions and interactions a day the cool thing about that is the infrastructure the engineering scale you started as a programmer with C by building yeah so I'm a hacker I'm not really an engineer not not a legit software engineer and I'm a tracker at heart but to achieve scale you have to do some unfortunately legit large-scale engineering so how do you make that magic happen hire people that I can learn from number one I mean I'm a hacker in the sense that I you know my approach has always been do whatever it takes to make it work so that I can see and feel the thing and then learn what needs to come next and oftentimes what needs to come next is a matter of being able to bring it to more people which is scale and there's a lot of great people out there that either have experience or are extremely fast learners that we've been lucky enough to find and with for four years but I think a lot of it we benefit a ton from the open source community and just all the learnings there that are laid bare in the open all the mistakes all the success all the problems it's a very slow-moving process usually open source but it's very deliberate and you get to see because of the the pace you get to see what it takes to really build something meaningful so I learned most most of everything I learned about hacking and programming and engineering has been due to open source and and the the generosity that people have given to give up their time sacrificer time without any expectation in return other than being a part of something much larger than themselves yeah just great open-source movement is amazing but if you just look at the scale like Square has to take care of is this a fundamentally a software problem or hardware problem you mentioned hiring a bunch of people but said it's not maybe from our perspective not often talked about how incredible that is to sort of have a system that doesn't go down often that secure is able to take care of all these transactions like maybe I'm I'm also a hacker at heart and it's incredible to me that that kind of scale could be achieved is there some insight some lessons some interesting tidbits that you can say about how to make that scale happen is it the hardware fundamentally challenge is it a software challenge is it like is it a social challenge of building large teams of engineers that work together that kind of thing that quotes is there what's the interesting challenges there by the way you're the best Russ hacker I've ever met I think thank you both if the enumeration you just went through I don't think there's one you have to kind of focus on all and the ability to focus on all that really comes down to how you these problems and whether you can break them down into parts that you can focus on because I think the biggest mistake is trying to solve or address too many at once or not going deep enough with the questions or not being critical of the answers you find or not form not taking the time to form credible hypotheses that you can actually test and you can see the result of so all of those fall in the face of ultimately critical thinking skills problem-solving skills and if there's one skill I want to improve every day it's that that's that's what contributes to learning and the only way we can evolve any of these things is learning what is currently doing and and how to take it to the next the next step and questioning assumptions the first principle is kind of thinking it seems like the fundamentals this whole process yeah but if you get to overextend it into well this is a hardware issue you miss all the software solutions and you know vice versa if you focus too much on the software there are hardware solutions that can 10x the thing so I I try to resist the categories of thinking and look for the underlying systems that make all these things work but those only emerge when you have a skill around creative creative thinking problem-solving and being able to ask critical questions and having the patience to like go deep so one of the amazing things if you look at the mission of square is to increase people's access to the economy maybe maybe you can correct me if I'm wrong that's from my perspective so from the perspective of merchants peer-to-peer payments even crypto cryptocurrency digital cryptocurrency what do you see as the major ways our society can increase but this patient in the economy so if we look at today in the next 10 years next 20 years you going to Africa maybe in Africa and all kinds of other places outside in North America if there was one word that I think represents what we're trying to do at square it's it is that word access one of the things we found is that we weren't expecting this at all when we started we thought were just building a a piece of hardware to enable people to plug it into their phone and swipe credit card and then as we talked with people who actually tried to accept credit cards in the past we found a consistent theme which many of them weren't even enabled and enabled but allowed to process credit cards and we dug a little bit deeper again asking that question and we found that a lot of them would go to banks or these merchants acquirers and waiting for them was a credit check and looking at a FICO score and many of the businesses that we talked to and many small businesses they don't have good credit or a credit history they're entrepreneurs were just getting started taking a lot of personal risk financial risk and it just felt ridiculous to us that for for for the for the job of being able to accept money from people you had to get your credit checked and as we dug deeper we realized that that wasn't the intention of the financial industry but it's the only tool they had available to them to understand authenticity intent predictor of future behavior so that's the first thing we actually looked at and that's where the you know we built the hardware but the software really came in terms of risk modeling and that's when we started down the path that eventually leads to AI we started with a very strong data science discipline because we knew that our business was not necessarily about making hardware it was more about enabling more people to come into the system so the fundamental challenge there is so to enable more people to come into the system you have to lower the barrier of checking that that person would be a legitimate vendor is that the fundamental problem yeah and a different mindset I think a lot of the financial industry had a mindset of kind of [Music] distrust and just constantly looking for opportunities to prove why people shouldn't get into the system whereas we took on a mindset of trust and then verify verify verify verify verify so we moved you know when we when we entered the space only about thirty to forty percent of the people who apply to accept credit cards would actually get through the system we took that number than 99% and that's because we reframe the problem we built credible models and we had this mindset of we're going to watch not at the merchant level but we're going to watch at the transaction level so come in perform some transactions and as long as you're doing things that feel high integrity credible and don't look suspicious we'll continue to to serve you if we see any interestingness in how you use our system that will be bubbled up to people to review to figure out if there's something nefarious going on and that's when we might ask you to leave so the change in the mindset led to the technology that we needed to enable more people to get there and to enable more people to access system what uh what role does machine learning play into that in that context of you said first of all that's a beautiful shift anytime you shift your viewpoint into seeing that people are fundamentally good and then you just have to verify and catch the ones who are not as opposed to assuming everybody's bad this is a beautiful thing so what role does the to you throughout the history of the company has machine learning played in doing that verification it was it was a media I mean we weren't calling it machine learning but it was data science and then as the industry evolved machine learning became more of the nomenclature and and as that evolved it became more sophisticated with deep learning and as I continues continues to evolve it'll be nobody another thing but they're all in the same vein but we built that discipline up within the first year of the company because we also had you know we have to we had to partner with a bank we had to partner with Visa MasterCard and we had to show that by bringing more people into the system that we could do so in a responsible way that would not compromise their systems and that they would trust us how do you convince this upstart company with some cool machine learning tricks is able to deliver on the sort of a trustworthy set of merchants we we stage it out in tears we had a bucket of you know five hundred people using it and then we showed results in a thousand and then ten thousand that fifty thousand and then the constraint was left was lifted so again it's it's kind of you know getting something tangible out there I want to show what we can do rather than talk about it and that put a lot of pressure on us to do the right things and it also created a culture of accountability of a little bit more transparency and I think incentivized all of our early folks and the company in the right way so what does the future look like in terms of increasing people's access or if you look at IO T Internet of Things there's more and more intelligent devices you can see there's some people even talking about our personal data as a thing that we could monetize more explicitly versus implicitly sort of everything can become part of the economy you see so what what is the future of square look like instead of giving people access in all kinds of ways to being part of the economy as merchants and as consumers I believe that the currency we use is is a huge part of the answer and I believe that the Internet deserves and requires a native currency and that's why I'm I'm such a huge believer in in Bitcoin because it just our our biggest problem is a company right now is we cannot act like an Internet company opened a new market we have to have a partnership with local bank we have to pay attention to different regulatory onboarding environments and a digital currency like Bitcoin takes in a bunch of that away where we can potentially launch a product in every single market around the world because they're all using the same currency and we we have consistent understanding of regulation and onboarding and-and-and what that means so I think you know the the internet continuing to be accessible to people is number one and then I think currency is is number two and it will just allow for a lot more innovation a lot more speed in terms of what we can build and others can build and it's just it's just really exciting so I mean I would I want to be able to see that and feel that in my lifetime so in this aspect in other aspects you have a deep interest in cryptocurrency and distributed ledger tech in general I talked to metallic butterman yesterday on this podcast he says hi by the way hey he's a brilliant brilliant person talking a lot about Bitcoin and aetherium of course so can you maybe linger on this point what what do you find appealing about Bitcoin about digital currency where do you see it going in the next 10 20 years and what are some of the challenges with respect to Square but also just bigger far for a globally farah world for the way we we think about money I I think the most beautiful thing about it is there's no one person setting the direction and there's no one person on the other side that can stop it so we have something that is pretty organic in nature and very principled in its original design and I you know I think the Bitcoin white paper is one of the most seminal works of computer science in the last 20 30 years it's it's poetry I mean it's a really cool technology I mean that's not often talked about sort of there's so much sort of hype around digital currency about the financial impacts of it but the actual technology is quite beautiful from a computer science perspective yeah and the underlying principles behind it that went into it even to the point of releasing it under a pseudonym I think that's a very very powerful statement the timing of when it was released is powerful it was it was a total activist move I mean it's it's moving the world forward and in a way that I think is extremely noble and honorable and enables everyone to be part of the story which is also really cool so you ask the question around 10 years in 20 years I mean I think the amazing thing is no one knows and it can emerge and every person that comes into the ecosystem whether they be a developer or someone who uses it can change its direction in small and large ways and that's what I think it should because that's what the the Internet has shown is possible now there's complications with that of course and there's you know certainly companies that own large ports so the you know net and conducted more than others and there's not equal access to every single person in the world just yet but all those problems are visible enough to speak about them and to me that gives confidence that they're solvable in a relatively short timeframe I think the world changes a lot as we get these satellites projecting the internet down down earth because it just removes a bunch of the former constraints and and really levels the playing field but a global currency which a native currency for the Internet is a proxy for is a very powerful concept and I don't think any one person on this planet truly understands the ramifications of that I think there's a lot of positives to it there's some negatives as well but I think it's possible sorry to interrupt do you think it's possible that this kind of digital currency would redefine the nature of money so become the main currency of the world as opposed to being tied to fiat currency of different nations and to really push the decentralization of control of money definitely but I think the the bigger ramification is how it affects how society works and I think there were there there are many positive ramifications outside around money just outside of just money money money is a foundational layer that enables so much more I was meeting with an entrepreneur in Ethiopia and payments is probably the number one problem to solve across a continent both in terms of moving money across borders between nations on the continent or the amount of corruption within the current system but the lack of easy ways to pay people makes starting anything really difficult I met an entrepreneur who started the the lyft / uber of Ethiopia and one of the biggest problems she has is that it's not easy for her writers to pay the company it's not easy for her to pay the drivers and that definitely has stunted her growth and made everything more challenging so the fact that she's she even has to think about payments instead of thinking about the best writer experience and the best driver experience is is pretty telling so I think as we get a more durable resilient and global standard we see a lot more innovation everywhere and I think there's no better case study for this than the various countries with and within Africa and and their entrepreneurs who are trying to start things within health or sustainability or transportation or a lot of the companies that we've seen that we've seen here so the majority of companies I met in November when I spent a month on the continent were payments oriented you mentioned there's a small tangent you mentioned the anonymous launch of Bitcoin is a sort of profound philosophical statement sudama's what's that even means there's a pseudonym for said there's an identity tied to it it's not just anonymous it's a Nakamoto so a Nakamoto might represent one person or multiple people but let me ask are you Satoshi Nakamoto just just checking thank you I wear what I tell you yes sure um but maybe you slip a pseudonym is constructed identity anonymity is just kind of as you know ran random like drop something off and leave there's no intention to build an identity around it and well the identity being built was a short time window it was meant to stick around I think and to be known and it's being honored in you know how the community thinks about building out like the concept of Satoshi Toshi's for instance is one such an example but I think it was smart not to do it anonymous not to do it as a real identity but to do it as soon an MB because I think it builds tangibility and a little bit of empathy that this was a human or a set of humans behind it and there's there's this natural identity that I can imagine but there is also sacrifice of an ego that's a pretty powerful thing from beautiful would you do sort of philosophically to ask you the question would you do all the same things you're doing now if your name wasn't attached to it sort of if if you had to sacrifice the ego put another way is your ego deeply tied in the decisions you've been making I hope not I mean I I believe I would certainly attempt to do the things without my name having to be attached with it but it's hard to do that in a corporation legally that's the issue if I were to do more open-source things then absolutely like I don't don't need my particular identity my real identity associated with it but I think you know the appreciation that comes from doing something good and being able to see it and see people use it is is pretty overwhelming and powerful more so than maybe seeing your name in the in the headlines let's talk about artificial intelligence a little bit if we could 70 years ago Alan Turing formulated the Turing test to me natural language is one of the most interesting spaces of problems that are tackled by artificial intelligence it's the canonical problem of what it means to be intelligent he formulated as the Turing test me ask sort of the broad question how hard do you think is it to pass the Turing test in the space of language just from a very practical standpoint I think where we are now and and for at least years out is one where the artificial intelligence machine learning the deep learning models can bubble up interestingness very very quickly and pair that with human discretion around severity around depth around nuance and and meaning I think for me the chasm the cross for general intelligences to be able to explain why and the meaning behind something behind a decision mm-hmm for being behind the decision so we got a sub so Delta so the explained ability part is kind of essential to be able to explain using natural language why the decisions were made that kind of thing yeah I mean I think that's one of our biggest risk and artificial intelligence going forward is we are building a lot of black boxes that can't necessarily explain why they made a decision or what criteria they used to make the decision and we're trusting them more and more from lending decisions to content recommendation to driving to health like you know a lot of us have watches that tell us to understand how was it deciding that I mean that that one's pretty pretty simple but you can imagine how complex they get and being able to explain the reasoning behind some of those recommendations seems to be an essential part although it's a very hard problem because sometimes even we can't explain why we make this that's what I was I think we're being us sometimes a little bit unfair for to artificial intelligence systems because we're not very good at these some of these things do you think a project for the ridiculous romanticized question but on that line of thought do you think we'll ever be able to build a system like in the movie her that you could fall in love with so have that kind of deep connection with hasn't that already happened hasn't someone in Japan fallen in love with this who's AI there's always going to be somebody that does that kind of thing I mean at a much larger scale of actually building relationships of being deeper connections it doesn't have to be love but it just deeper connections with artificial intelligence systems you mentioned explained it there's lots of function of the artificial intelligence and more a function of the individual and how they find meaning and where they find meaning do you think we humans can find meaning in technology in this kind of way yeah 100 percent 1 percent and I don't necessarily think it's a negative but I you know it's it's constantly going to evolve so I don't know but I meaning is is something that's entirely subjective and I I don't think it's going to be a function of finding the magic algorithm that enables everyone to love it but maybe but that question really gets that the difference between human and machine the you had a little bit of an exchange with Elon Musk basically I mean it's a trivial version of that but I think there's a more fundamental question of is it possible to tell the difference between a bot and a human and do you think it's if we look into the future 10 20 years out do you think it would be possible or is it even necessary to tell the difference in the digital space between a human and a robot can we have fulfilling relationships with each or do we need to tell the difference between them I think it's certainly useful and certain problem domains to be able to tell the difference I think in others it might not be as useful I think it's possible for us today tell that difference as the reverse the meta of the Turing test well what's interesting is I think the technology to create is moving much faster than the technology to detect you think so so if you look at like adversarial machine learning there's a lot of systems that try to fool machine learning systems and at least for me the hope is that the technology to defend will always be right there at least your sense is that I don't know if they'll be right there I mean it's it's a race right so the detection technologies have to be 2 or 10 steps ahead of the creation technologies this is a problem that I think the financial industry will face more and more because a lot of our risk models for instance are built around identity payments ultimately comes down to identity and you can imagine a world where all this conversation around deep fakes goes towards the direction of driver's license or passports or state identities and people construct identities in order to get through a system such as ours to start accepting credit cards or into the cash shop and those technologies seem to be moving very very quickly our ability to detect them I think is probably lagging at this point but certainly with more focus we can get ahead of it but this is going to touch everything so I think it's it's it's like security and we're never going to be able to build a perfect detection system we're only going to be able to you know what we should be focused on this is the speed of evolving it and being able to take signals that show correctness or errors as quickly as possible and move and to be able to build that into our newer models or the or the self learning models you have other worries like some people like Elon and others have worries of existential threats of artificial intelligence of artificial general intelligence or if you think more narrowly of all threats and concerns about more narrow artificial intelligence like what are your thoughts in this domain do you have concerns are you more optimistic I think you've all and his in this book 21 boilin lessons for the 21st century yeah his last chapters around meditation and you look at the title of the chapter and you're like oh it's kind of old meditation but the was interesting about that chapter is he believes that you know kids being born today growing up today Google has a stronger sense of their preferences than they do which you can easily imagine I can easily imagine today that Google probably knows my preference is more than my mother does maybe not me per se but for someone growing up only knowing you know not only knowing what Google is capable of or Facebook or Twitter or square or any of these things the self-awareness is being offloaded to other systems and particularly these these algorithms and his concern is that we lose that self-awareness because the self-awareness is now outside of us and it's doing such a better job at helping us direct our decisions around should I stand should I walk today what doctor should I choose who should I date all these things were now seeing play out very quickly so he sees meditation as a tool to build the self awareness and to bring the focus back on why do I make these decisions why do I react in this way why did I have this thought where did that come from that's the way to regain control or awareness maybe not control but put awareness so that you can be aware that yes I am offloading this decision to this algorithm that I don't fully understand and can't tell me why it's doing the things that's doing because it's so complex that's not to say that the algorithm can't be a good thing and to me recommender systems the best of what they can do is to help guide you on a journey of learning new ideas of learning period it can be a great thing but do you know you're doing that are you aware that you're inviting it to do that to you I think that's that's a little risky identifies right is that's perfectly okay but are you aware that you have that invitation and it's it's being acted upon and so that that's your that's a concern you're kind of highlighting that without a lack of awareness you can just be like floating at sea so awareness is key in just the future these artificial intelligence systems in the other movie wall-e well Richard I think is one of Pixar's best movies besides ratatouille right you had me until the ratatouille okay that error is incredible all right we've come to the first point where we disagree okay the entrepreneurial story in the form of a wrath mm-hmm I just remember just the soundtrack was really good so excellent what are your thoughts sticking on artificial intelligence a little bit about the displacement of jobs that's another perspective that candidates like Andrew yang talked about in getting forever yang Yang so he unfortunately speaking of yang Yang has recently dropped out I know it was very disappointing and depressing yeah but the on the positive side he's I think launching a podcast so really cool yeah that's he just announced that I'm sure he'll try to talk you into trying to come on to the podcast so about Reddit Tori yeah maybe he'll be more welcoming of the ratatouille argument what are your thoughts on his concerns of the displacement of jobs of automations of the of course there's positive impacts that could come from automation in the eye and but there could also be negative impacts and within that framework what are your thoughts about universal basic income so these interesting new ideas of how we can empower people in the economy I I think he was a hundred percent right on almost every dimension we see this in squares business I mean he identified truck drivers I'm from Missouri and he certainly pointed to the concern and the issue that people from where I'm from feel every single day that is often invisible and not talked about enough you know the next big one is cashiers this is where it pertains to squares business we are seeing more and more of the point-of-sale moved to the individual customers hand in the form of their phone and apps and pre-order and order ahead we're seeing more kiosks we're seeing more things like Amazon go and the number of workers in as a cashier and Rito's immense and you know there's there's no real answers on how they transform their skills and and work and into something else and I think that does lead to a lot of really negative ramifications and the important point that he brought up around universal basic income is given that this shift is going to come and given it's going to take time to set people up with new skills and new careers they need to have a floor to be able to survive and this $1,000 a month is such a floor it's not going to incentivize you to quit your job because it's not enough but it will enable you to not have to worry as much about just getting on day to day so that you can focus on what I'm what am I going to do now and what am I going to what skills do I need to acquire and I think I think that you know a lot of people point to the fact that you know during the industrial age we we had the same concerns around automation factory lines and everything worked out okay but the the biggest change is just the velocity and the centralization of a lot of the things that make this work which is the data and the algorithms that work on this on this data I think the the second biggest scary thing is just how around AI is just who actually owns the data and who can operate on it and are we able to share the insights from the data so that we can also build algorithms that help our needs or help our business or what not so that's where I think regulation could play a strong and positive part first looking at the primitives of AI and the tools we use to build these services that will ultimately touch every single aspect of the human experience and then how data where data is owned and how its how its shared so those those are the answers that as a society as a world we need to have better answers around which we're currently not they're just way too centralized into a few very very large companies but I think he was spot-on with identifying the problem and proposing solutions that would actually work at least that we'd learn from that you could expand or evolve but I mean it's I think it's ubi is well well past its it's do I mean it was certainly trumpeted by Martin Luther King and even even before him as well and like you said like you know the exact thousand dollar mark might be might not be the correct one but you should take the stuffs to try to to implement these solutions and see see what works so I think you and I eat some more diets and at least I was the first time I've heard this yeah so I was doing it first time anyone has said that to me yeah but it's becoming more and more cool and but I was doing it before was cool so the intermittent fasting and fasting in general I really enjoyed I love food but I enjoy the the I also love suffering because I'm Russian so fasting kind of makes you appreciate makes you appreciate what it is to be human somehow so but I have a outside the philosophical stuff I have a more specific question it also helps me as a programmer and a deep thinker like stifling that from a scientific perspective to sit there for many hours and focus deeply maybe you were a hacker before you were CEO what have you learned about diet lifestyle mindset that helps you maximize mental performance to be able to focus for this thing deeply in this world of distractions I think I just took it for granted for too long which aspect just a social structure of we eat three and there's snacks in between and I just never really asked the question why oh by the way in case people don't know I think a lot of people know who you you at least you famously eat once a day yeah you still eat once a day yep sooner by the way what made you decide to eat once a day like cuz to me that was a huge revolution that you don't have to eat breakfast that was like I felt like I was a rebel like I yeah like abandoned my parents or something and it doesn't an artist when you when you first like the first week you start doing it feels you kind of like have a superpower yeah then you realize it's not really a superpower but it I think you realize at least I realize like it just how much is how much our mind dictates what we're possible of and and sometimes we have structures around us the incentivize like you know there's three may thing which was purely social structure versus necessity for our health and for our bodies and I I did it just I started doing it because I played a lot with my diet when I was a kid and I was vegan for two years and just went all over the place just because I you know a health is the most precious thing we have and none of us really understand it so being able asked the question through experiments that I can perform on myself and learn about I is compelling to me and I heard this one guy on the podcast wim HOF who's famous for doing ice baths and holding his breath and all these things he said he only eats one meal a day I'm like wow that sounds super challenging and comfortable I'm gonna do it so I I just I learned the most when I make myself I want to say suffer but when I make myself feel uncomfortable because everything comes to bear in those moments and and you really learn what your what you're about or what you're not so I been doing that my whole life like when I was a kid I could not like I could not speak like I had to go to a speech therapist and it made me extremely shy and then one day I realized I can't keep doing this and I signed up for the for the speech Club and you know it was a the most uncomfortable thing I could imagine doing getting a topic on a note card having five minutes to write a speech about whatever that topic is not being able to use the note card while speaking and speaking for five minutes about that topic so but it just it puts so much it gave me so much perspective around the power of communication around my own deficiencies and around if I set my mind to do something I'll do it so it gave me a lot more confidence so I see fasting in the same light this is something that was interesting challenging uncomfortable and has given me so much learning and benefit as a result and it will lead to other things that I experiment with and play with but um yeah it does feel a little bit like a superpower sometimes the most boring superpower one can imagine no it's quite incredible the clarity of mind is it's pretty interesting speaking of suffering you kind of talk about facing difficult ideas you meditate you think about the broad context of life of our society let me ask sort of apologize again for the romanticized question but do you ponder your own mortality do you think about death about the finiteness of human existence when you meditate when you think about it and if you do what how do you make sense of it that this thing ends well I don't try to make sense of it I do think about it every day I mean it's it's a daily multiple times a day any afraid of death no I'm not afraid of it I I think it it's a transformation I don't know to what but it's also a tool to feel the importance of every moment so I just use as a reminder like I have an hour is this really what I'm going to spend the hour doing like I only have so many more sunsets and sunrises to watch like I'm not going to get up for it I'm not going to make sure that I that I that I try to see it so it's it just puts a lot into perspective and it helps me prioritize I think it's I don't I don't see it as something that's like that I dread or is dreadful it it's a it's a tool that is available to every single person to use every day because it shows how precious life is and there's reminders every single day whether it be your own health or a friend or a co-worker or something you see in the news so it's to me it's just a question of what we do with that daily reminder and for me it's um am I really focused on what matters and sometimes that might be work sometimes that might be friendships or family or relationships or whatnot but that that's it's the ultimate clarifier in that sense so on the question of what matters another ridiculously big question of once you try to make sense of it what do you think is the meaning of it all the meaning of life what gives you purpose happiness meaning a lot does I mean I mean just being able to be aware of the fact that I'm alive is pretty pretty meaningful the connections I feel with individuals whether they people I just meet or long lasting friendships or my family is meaningful seeing people use something that I helped build it is really meaningful and powerful to me but but that sense of I mean I think ultimately comes down in a sense of connection and just feeling like I am bigger I am part of something that's bigger than myself and like I can feel it directly in small ways or large ways however manifest this is probably uh it's probably a last question do you think we're living in a simulation I don't know it's a pretty fun one if we are but also crazy and random and brought with tons of problems but yeah would you have it any other way yeah I mean I just think it's taken us way too long to as a planet to realize we're all in this together and we all are connected in in in very significant ways I think we we hide our connectivity very well through ego through you know whatever or whatever it is of the day but that is the one thing I would want to work towards changing and that's how I would have it another way because if if we can't do that then how we're going to connect to all the other simulations because that's the next step is like what's happening in the other simulation escaping this one and yeah spanning across the multiple simulations and sharing it and on the fun I don't think there's a better way to end it Jack thank you so much for all the work you do there's probably other ways that we've ended this and other simulations that may have been better well that's a wait and see thanks so much for talking to thank you thanks for listening to this conversation with Jack Dorsey and thank you to our sponsor masterclass please consider supporting this podcast by signing up to master class at master class comm / flex if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supporting our patreon are simply connect with me on Twitter at Lex Friedman and now let me leave you some words about Bitcoin from Paul Graham I'm very intrigued by Bitcoin it has all the signs of a paradigm shift hackers love it yet it is described as a toy just like microcomputers thank you for listening and hope to see you next time you |
Dmitry Korkin: Computational Biology of Coronavirus | Lex Fridman Podcast #90 | the following is a conversation with Dimitri korkin he's a professor of bioinformatics and computational biology at WPI Worcester Polytechnic Institute where he specializes in bioinformatics of complex diseases computational genomics systems biology and biomedical data analytics I came across Dimitri's work one in February his group used the viral genome of the Cova 19 to reconstruct the 3d structure of its major viral proteins and their interaction with the human proteins in effect creating a structural genomics map of the corona virus and making this data open and available to researchers everywhere we talked about the biology of covert 19 SARS and viruses in general and how computational methods can help us understand their structure and function in order to develop antiviral drugs and vaccines this conversation was recorded recently in the time of the corona virus pandemic for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars in a podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri DM a.m. this show is presented by cash app the number-one finance app in the App Store when you get it you just called Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app allows you to buy Bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating I recommend a cent of money as a great book on this history debits and credits on Ledger's started around 30,000 years ago the US dollar created over two hundred years ago and Bitcoin the first decentralized cryptocurrency released just over ten years ago so given that history cryptocurrency is still very much in his early days of development but it's still aiming to and just my redefined the nature of money so again if you get cash out from the App Store Google Play and use the code let's podcast you get ten dollars in cash app will also donate ten dollars the first an organization that is helping to advance robotics and STEM education for young people around the world and now here's my conversation with Demetri korkin do you find viruses terrifying or fascinating when I think about viruses I think about them I mean I imagine them as those villains that do their work so perfectly well that's that is impossible not to be fascinated with them so what do you imagine when you think about a virus do you imagine the individual so these hundred nanometer particle things or do you imagine the whole pandemic like Society level the when you say the efficiency at which they do their work do you think of viruses as the millions that him and that occupy human body or a living organism Society level like spreading as a pandemic or do you think of the individual little guy yes this is I think this is a unique a unique concept that allows you to move from micro scale to the macro scale all right so the dividers itself I mean it's it's not a living organism it's a machine to me it's a machine but it is perfected to the way that it essentially has a limited number of functions it needs to do necessary some functions and essentially has enough information just to do those functions as well as the ability to modify itself so you know it's it's a machine it's an intelligent machine so yeah look maybe on that point you're in danger of reducing the power of this thing by calling it a machine right but you now mention that it's also possibly intelligent it seems that there's these elements of brilliance that a virus has of intelligence of maximizing so many things about its behavior in to ensure its survival and its and its success so do you see it as intelligent so you know I think the it's a different understanding differently than you know I think about you know intelligence over human kind or intelligence of of the of the you know of the artificial intelligence mechanisms I think the intelligence of a virus is in its simplicity the ability to do so much with so little material and information but also I think it's it's interesting it keeps me thinking you know it gives me wondering whether or not it's also the an example of the basic swarm intelligence where you know essentially the viruses act as the whole and extremely efficient in that so what do you attribute the incredible simplicity and the efficiency - is it the evolutionary process - maybe another way to ask that if you look at the next hundred years are you more worried about the natural pandemics or the engineered pandemics so how hard is it to build a virus yes it's it's a very very interesting question because obviously there is a lot of conversations about the you know whether we are capable of engineering a you know anyone worse the virus I personally expect in a mostly concerned with the naturally occurring viruses simply because we keep seeing that we keep seeing new strains of influenza emerging some of them becoming pandemic we keep seeing new strains of coronaviruses emerging this is a natural process and I think this is why it's so powerful you know if you ask me you know did I've read papers about scientists trying to study the capacity of the modern you know by technology to alter the viruses but I hope that that you know it in it won't be our main concern in the near future do you mean by hope well you know if you look back and look at the history of the of the most dangerous viruses right so that's the first thing that comes into mind is a smallpox so right now there is perhaps a handful of places where this you know the the strains of this virus are stored right so this is essentially the effort of the whole society to limit the access to those viruses I mean in a lab in a controlled environment in order to study and then smallpox is one of the viruses for which should be stated there's a vaccine is developed yes yes and that's you know it's until seventies it wasn't in my opinion it was perhaps the most dangerous think that was there is there a very different virus then then the influenza and coronaviruses it is it is different in several aspects biologically it's a so-called double-stranded DNA virus but also in the way that it is much more contagious so they are not for so this is this is the what are not are not is essentially an average number as person infected by the virus can spread to other people so then the average number of people that he or she can spread it to and you know the there is still some you know discussion about the estimates of the current virus you know the estimations vary between you know one point five and three in case of smallpox it was five to seven and we're talking about the exponential growth right so that's that's a very big difference it's not the most contagious one measles for example it's I think 15 and up so so it's it's you know but it's definitely definitely more contagious that that the seasonal flu then the current coronavirus were stars for that matter so what makes a what makes a virus more contagious or the I'm sure there's a lot of variables that come into play but is it is it that whole discussion of aerosol and like the size of droplets if if it's airborne or there's some other stuff that's more biology centered I mean there are a lot of components and and there are biological components that there are also you know social components the ability of the virus to you know the the ways in which the virus is spread is definitely one the ability to virus to stay on the surfaces to survive the ability of the virus to replicate fast also you know once it's in the cell or whatever once it's inside the host and interesting enough something that I think we didn't pay that much attention to is the incubation period the were you know hosts are symptomatic and now it turns out that another thing that we one really needs to take into account the percentage of the asymptomatic population because those people still shared this virus and still are you know they still are contagious as other than the Iceland study which i think is probably the most impressive size-wise shows 50 percent asymptomatic this virus I also recently learned the swine flu is like just a number of people who got infected was in the billions it was some crazy number it was like it was like like 20 percent of poverty percent of population something crazy like that so the lucky thing there is the fatality rate is low but the fact that a virus can just take over an entire population so quickly it's terrifying I think I mean this is you know that's perhaps my favorite example of a butterfly effect because it's really I mean it's it's even tinier they'd then a butterfly and look at you know and with you know if you think about it right so it used to be in in those bad species and perhaps because of you know a couple of small changes in in the in the viral genome his first had you know become capable of jumping from bats to human and then it became capable of jumping from human to human alright so this is this is I mean it's not even the size of a virus it's the size of several you know several atoms or says you know few atoms and our sudden this change has such a major impact so is that a mutation like on a single virus is that like so if we talk about those the the flap of a butterfly wing like what's the first flap well I think this is the the the mutations that make that made this virus capable of jumping from bat species to human and of course there's you know the scientists are still trying to find I mean they still even trying to find the the who was the first in fact it is the patient zero the first human the first human infected right I mean the fact that there are corona viruses different strains of corona viruses in various bat species I mean we know that so so we you know viola gist absurdum they studied them they look at their and genomic sequences they're trying of course to understand what make this virus is to jump from from bats to human there was you know similar to that and in you know in influenza that was I think a few years ago there was this you know interesting story where several groups of scientists studying influenza virus essentially you know made experiments to show that this virus can jump from one species to another you know by changing I think just a couple of residues and and and of course it was very controversial I think there was a moratorium on this study for a while but then the study was released it was published so that was their moratorium is because it shows through engineering it through modifying it you can make a jump yes yeah I I personally think it is important to study this I mean we should be inform to should try to understand as much as possible in order to prevent it but so then the engineering aspect there is can't you then just start searching because there's so many strands of viruses out there can't you just search for the ones in bats that are the deadliest from the virologist perspective and then just try to engineer try to see how to but see that's a there's a nice aspect to it the really nice thing about engineering viruses it has the same problems nuclear weapons is it's hard for it to not only to mutual self-destruction so you can't control a virus it can't be used as a weapon right yeah that's why I you know in the beginning I said you know I I'm hopeful because that definitely the definitely regulations to be needed to be introduced and I mean as the scientific society is we are in charge of you know making the right actions making the right decisions but I think we we will benefit tremendously by understanding the mechanisms by which the virus can jump by which the virus can become more you know more more dangerous to humans because all this answers with you know eventually to to designing better vaccines hopefully Universal vaccines right and that would be a triumph of the you know science so what's the universe of vaccines is that something that well how universal is universal well I mean you know so what's the dream I guess because you kind of mentioned the dream of this I would be extremely happy if you know we designed the vaccine that is able I mean I'll give you an example right so so every year we do a seasonal flu shot the reason we do it is because you know we are in the arms race you know our vaccines are in the arms race with with constantly changing virus right now if the neck's pandemic influenza pandemic will a cure most likely this vaccine would not save us right although it's it's you know it's the same virus might be different strain so if we're able to essentially design a vaccine against you know influenza A virus no matter what's the strain no matter which species did jump from that would be I think that would be a huge huge progress and advancement you mentioned the smallpox until the seventies might have been something that he would be worried the most about what about these days well we're sitting here in the middle of a cove in nineteen pandemic but these days nevertheless what is your biggest worry virus wise what are you keeping your eye are on it looks like and you know based on the past several years of the of the new viruses emerging I think we're still dealing with different types of influence I mean so so the eight seven and nine avian flu that was that emerged I think a couple of years ago in China I think the the mortality rate was incredible I mean it was you know I think above thirty percent you know so this is this is fuchsia I mean luckily for us this strain was not pandemic alright so it was jumping from birds to human but I don't think it it it was actually transmittable between the humans and you know this is actually a very interesting question which scientists tried to understand right so the balance the delicate balance between the virus being very contagious right so efficient in spreading and virus to be very pathogenic you know causing you know harms you know and and that's to their horse so it looks like that the more pathogenic the viruses the less contagious it is is that a property biology or what is it was I I don't have an answer to that and III think this is this is still an open question but you know if you look at you know you know with the corona virus for example if you look at you know the the deadlier relative Merce Merce was never in a pandemic virus right but the you know did again the the mortality rate from nurseries far above you know I think twenty or thirty percent so so whatever is making this all happen doesn't want us dead because it's balancing yeah nicely I mean how do you explain that one not dead yet like because there's so many viruses and they're so good at what they do why do they keep us alive I mean we will also have you know a lot of protection right so the immune system and so I mean we do have you know ways to to fight against those viruses and I think with the I now weigh much better equipped right so with the discoveries of vaccines and you know there are vaccines against the the viruses that maybe two hundred years ago would wipe us out completely but because of this vaccines we are actually we're capable of eradicating pretty much fully as is the case with smallpox so if we could can we go to the basics a little bit of the biology of the virus how does the virus infect the body so I think there are some key steps that the virus needs to perform and of course the first one the viral particle needs to get attached to the host cell in the case of corona virus there is a lot of evidence that it actually interacts in the same way of the as the SARS coronavirus so it gets attached to a c2 human receptor and so there is I mean as we speak there is a growing number of papers suggesting it moreover a most recent I think most recent results suggest that this virus attaches more efficiently to this human receptor then SARS just a sore back off so there is a family viruses the corona viruses and SARS whatever the heck for that respite or wherever that stands for so SARS actually stands for the disease that you get is the syndrome of acute respiratory so SARS is the first strand and there's Merce Merce and there is yes but people scientists actually know more than three strains I mean so there is the mhv strain which is considered to be a canonical model disease model in mice and so there is a lot of work done on on this virus because it's but he hasn't jumped to humans yet no no yes it's fascinating so any mention a c2 so the when you say attached proteins are involved yeah on both sides yes so so we have you know so we have this infamous spike protein on the surface of the virion particle and does look like a spike and I mean that's essentially because of this protein you know we called the coronavirus coronavirus so that what makes Corona on top of the surface so so this via this protein it actually it acts so it doesn't act alone it actually it makes a three copies and it's it makes so-called trimer so this trimer is essentially a functional unit a single functional unit that in starts interacting with the AC two receptor so this is again another protein that now sits on the surface of a human cell host cell I would say and that's essentially in that way the virus anchors itself to the host cell because then it needs to actually it needs to get inside you know it fuses its membrane with the host membrane it releases the the key components it releases its you know RNA and then essentially hijacks the the machinery of the cell because none of the viruses that we know of have ribosome the the machinery that allows us to print out proteins so in order to print out proteins that are necessary for functioning of this virus it actually needs to hijack the host ribosomes the virus is an RNA wrapped in a bunch of proteins one of which is this functional mechanism with by protein that does the attachment so yeah so you know so if you look at this virus that there are you know several basic components right so we start with the Spike protein this is not the only surface protein the the protein that lives on the surface of the viral particle there is also perhaps the the protein with the highest number of copies is the membrane protein so it's essentially it forms the capsid sorry the envelope of the protein of the viral particle and essentially you know helps to maintain a certain curvature helps to make a certain curvature then there is a another protein called envelope protein or a protein and it it actually occurs in in far less quantities and still there is ongoing research what exactly does this protein do so these are sort of the three major surface proteins that you know make the divider envelope and when we go inside then we have another structural protein called nuclear protein and the the purpose of this protein is to protect the viral RNA it actually binds to the viral RNA creates a capsid and so the rest of the virus viral information is inside of this you know RNA and you know if you compare the amount of the genes or you know proteins that are made of these genes it's much you know it's significantly higher than of influenza virus for example influenza virus has I think around eight or nine proteins where this one has at least 29 Wow that has to do with the length of the RNA strand I mean so I mean so it's it it affects the length of the RNA strand right so so so because you essentially need to have sort of the minimum amount of information to encode those genes how many proteases you say 2909 protease yes so this is this is you know something definitely interesting because you know believe it or not we've been studying you know coronaviruses for over two decades we've yet to uncover all functionalities of his proteins could we maybe take a small tangent and can you can you say how one would try to figure out what a function of a particular protein is so you've mentioned people are still trying to figure out what the function of the envelope protein might be or what's the process so this is where the research that computational scientists do might be of help because you know in the past several decades was that we actually have collected a pretty decent amount of knowledge about different proteins in different viruses so what we can actually try to do and this is sort of could be sort of the our first lead to a possible function is to see whether those you know say we have this genome of the corona virus other of the novel coronavirus and we identify the potential proteins then in order to infer the function what we can do can actually see whether those proteins are similar to those ones that we already know okay in such a way we can you know for example clearly identified you know some critical components that RNA polymerase or different types of proteases these are the proteins that essentially clip the protein sequences and so this works in many cases however in some cases you have truly novel proteins and this is a much more difficult task now as a small pause when you say similar like what if some parts are different and some parts are similar like how do you disentangle that you know it's it's a big question of course you know what by informatics does it does predictions right so those predictions and they have to be validated by experiments functional or structural predictions both I mean we we do structural predictions with the functional predictions we do interactions predictions things you just generate a lot of predictions like reasonable predictions based on structure and function interaction like you said and then here you go that's the power of bioinformatics is data grounded good predictions of what should happen so we you know in the way I see it we're helping experimental scientists to streamline the discovery process yeah and the experimental scientists is that what a virologist is solely about virology is one of the experimental sciences that you know focus on viruses they often work with other experimental scientists for example the molecular imaging scientists right so the the viruses often can be viewed and reconstructed through electron microscopy techniques so but these are you know specialists that are not necessarily by biologists they've worked with small small particles more by whether it's viruses or is it an organelle of a you know of a human cell whether it's a you know complex molecular machinery so the techniques that are use are very similar in in surfing in its in their essence and so yeah so so typically me and in we see it now the research on you know that is emerging and that is needed often involves the collaborations between biologists you know biochemist you know people from from pharmaceutical sciences computational sciences so we have to work together so from my perspective is to step back sometimes I look at this stuff it's the how much we understand about RNA DNA how much we understand about protein like your work the amount of proteins that you're exploring is it surprising to you that we were able we descendants of apes were able to figure all of this out like how so your computer scientists so for me from computer science perspective I I know how to write a Python program things are clear but biology is a giant mess it feels like to me from an outsider's perspective is how surprising is it amazing is it that we were able to figure this stuff out you know if you look at the you know how computational science and computer science was evolving right I think it was just a matter of time that we would approach biology so so we we started from you know applications to much more fundamental systems physics you know and now we are or you know small chemical compounds right so now we are approaching the more complex biological systems and I think it's a natural evolution of you know of the computer science of mathematics sure that's the computer science I just might even in in higher level so that to me surprising that computer science can offer help in this messy world but I just mean it's incredible that the biologists and the chemists can figure all this out or is it you sound ridiculous to you that that of course they would it just seems like a very complicated set of problems like the the variety of the kinds of things that could be produced in the body the just just like you said 20 and I approach I mean just getting a hand of in a hang of it so quickly it just seems impossible to me I agree I mean it's and I have to say we are you know in the very very beginning of this journey I mean we we've yet to I mean we've yet to comprehend not even try to understand and figure out all the details but we've yet to comprehend the complexity of the cell we know that neuroscience is not even at the beginning of understanding human mind so where's biology said in terms of understanding the function deeply understanding the function of viruses and cells so there sometimes it's easy to say when you talk about function what you really refer to it's perhaps not a deep understanding but more of a understanding sufficient to be able to mess with it using a antiviral like mess with it chemically to prevent some of its function or do you understand the function well I think equally I think we're much farther in terms of understanding of the complex genetic disorders such as cancer where you have layers of complexity and we you know as in my laboratory we're trying to contribute to that research but we're also in a way overwhelmed with how many different layers of complexity different layers of mechanisms that can be hijacked by cancer simultaneously and so you know I think biology in the past 20 years again from the perspective of the outsider because I'm not a biologist but I think it has advanced tremendously and one thing that we're computational scientists and data scientists are now becoming very very helpful is in the fact it's kind of from the fact that we are now able to generate a lot of information about the cell whether it's next-generation sequencing or transcriptomics whether it's life imaging information where it is you know complex interactions between proteins or between proteins and small molecules such as drugs we we are becoming very efficient in generating this information and now the next step is to become equally efficient in processing this information and extracting the the key knowledge from that they could then be validated with the experiment yeah yeah so maybe then going all the way back we're talking you said the first step is seeing if we can match the new proteins you found in the virus against something we've seen before to figure out its function and then you also mentioned that but there could be cases where it's a totally new protein is there something biron firm addicts can offer when it's a totally new protein this is where many of the methods and you probably are aware of you know the the case of machine learning many of these methods rely on the previous knowledge right so things that where we try to do from scratch are incredibly difficult you know something that we call a Benicia and this is I mean it's not just the function I mean you know we've yet to have a robust method to predict the structures of these proteins in a Benicia you know by not using any templates of other related proteins so protein is a chain of amino acids residues as residues yeah and then however somehow magically maybe you can tell me they seem to fold in incredibly weird and complicated 3d shapes yes so and that's where actually the idea of protein folding or just not the idea but the problem of figuring out how the hell it wants up the concept how they fold into those weird shapes comes in so that's another side of computational work so what can you describe what protein folding from the computational side is and maybe your thoughts on the folding at home efforts that a lot of people know they you can use your machine to to do protein folding so yeah broad protein folding is you know one of that those 1 million dollar price challenges right so the reason for that is we've yet to understand precisely how the protein gets folded so efficiently to the point that in many cases where you you know where you try to unfold it due to the high temperature it actually folds back into its original state right so we know a lot about the mechanisms right but put putting those mechanisms together and making sense it's a computationally very expensive task in general the proteins fold can they fold in arbitrary large number of ways it is they usually fold in a very small number no it's it's typically I mean you we tend to think that you know there is a one sort of canonical fold for protein although that there are many cases where the proteins you know upon the stabilization it can be folded into a different conformation and this is especially true when you look at sort of proteins that in that include more than one structural unions so those structural unions we call them protein domains essentially protein domain is a single unit that typically is evolutionary preserved that typically carries out the single function and typically has a very distinct fault structure 3d structure organization but turns out that if you look at human an average protein in a human cell would have to a bit of two or three such subunit and how they are trying to fold into the sort of you know next level fold right so within subunit is folding and then and then they fold into the larger 3d structure right and and all that there's some wonder saying the basic mechanisms but not to put together to be able to fold it we're still I mean we're still struggling I mean we're we're getting pretty good about folding relatively small proteins up to hundred residues which I mean but we're still far away from folding you know larger proteins and some of them are notoriously difficult for example transmembrane proteins proteins that that sit in the in the membranes of the cell they're incredibly important but they are incredibly difficult to solve and so basically there's a lot of degrees of freedom how it folds and so it's a combinatorial problem or just explodes there's so many dimensions Hey well it is a combinatorial problem but it doesn't mean that we cannot approach it from the non canal not from the boot for a force approach and so the machine learning approaches you know have been emerged that try to tackle it so folding at home I don't know how familiar with it but is that used machine learning or is it more brute force no so folding at home it was originally and I remember I was a it was a long time ago I was a postdoc and we we learned about this you know this game because it was originally designed as the game and we you know I took a look at it and it's interesting because it's it's really you know it's very transparent very intuitive so and from what I heard a via to introduce it to my son but you know kids are actually getting very good at folding the proteins and it was you know it came to me as they as the not as a surprise but actually as the sort of manifest of you know our capacity to do this kind of to solve these kind of problems when a paper was published published in one of these top journals with the coasters been the actual players of this game so and what happened is was that they managed to get better structures than the scientists themselves so so that you know that was very I mean it was kind of profound you know revelation that problems that are so challenging for a computational science maybe not that challenging for a human brain well that's a really good that's a hopeful message always when there's a the proof of existence the existence proof that it's possible that's really interesting but the it seems what are the best ways to do protein folding now so if you look at what deep mind does with alpha fall alpha fold yes so they kind of is that's a learning approach what's your sense I mean your backgrounds in machine learning but is this a learnable problem is this still a brute-force away in the garry kasparov deep blue days are we in the alphago playing the game of go days of folding well I think we are we are advancing towards this direction I mean if you look so there is a sort of olympic game for protein folders called CASP and it's essentially it's you know it's a competition where different teams are given exactly the same protein sequences and they try to predict their structures right and of course there's different sort of subtasks but in the recent competition half a fault was among the top performing teams if not the top performing team so there is definitely a benefit from the data that had been generated you know in the past several decades the structural data and certainly you know we are now at the capacity to summarize this data to generalize this data and to use those principles you know in order to predict protein structures as one of the really cool things here is there's maybe you can comment on it there seems to be these open datasets of protein how did that with the protein databank the a protein databank I mean as create is this a recent thing for just the corona virus or it's it's been for many many years I believe the first protein databank was designed on flash cards so on the so yes it's so this I mean this is a great example of the community efforts of everyone contributing cause every time you solve a protein or a protein complex this is where you submit it and you know the scientists get access to it scientists get to test it and we went from occasions use this information to you know to make predictions so there's no there's no culture like hoarding discoveries here so that's I mean you've you've you've released a few or a bunch of proteins they were matching its whatever we'll talk about details a little bit but it's kind of amazing that that's the the it's kind of amazing how open the culture here is it is and I think this pandemic actually demonstrated the ability of scientific community to you know to solve this challenge collaboratively and this is I think it if anything it actually moved us to a brand new level of collaborations of the efficiency in which people establish new collaborations in in which people offer their help to each other scientists offer their help to each other and publish results to it's very interesting we're now trying to figure out as a few journals that are trying to sort of do the very accelerated review cycle but so many preprints so just hosting a paper going out I think it's fundamentally changing the the way we think about papers yes I mean the way we think about knowledge now let's say no yes because yes I completely agree I think now it's the knowledge is becoming sort of the the core value not the paper or the journal where this knowledge is published and I think this is again this is we are living in the in the times where it becomes really crystallized that the idea that the most important value is in the knowledge so maybe you can comment like what do you think the future of that knowledge sharing looks like so you have this paper that will I hope you get a chance to talk about a little bit but it has like a really nice abstract and the introduction and related like it has all the usual I mean probably took a long time to put together so but is that going to remain like you could have communicated a lot of fundamental ideas here in much shorter amount that's less traditionally acceptable by the journal context so so well you know so the first version that we posted not even on a bi archive because by archive back then it was essentially you know overwhelmed with the number of submissions so so our submission I think it took five or six days to just for it to be screened and and and put online so we you know essentially we put the first pre pre n't on our website and you know it was started getting accessed right away so and and you know so this original preprint was in a much rougher shape than this paper and but we tried I mean we honestly try to be as compact as possible with you know introducing the the information that is necessary that to explain our you know our results so maybe you can dive right in if it's okay sure so it's a paper called structured of Tsarskoe how do you even pronounce our scurvy - Co V - yeah by The Cove it is such a terrible name but it stuck and yes Tsarskoe V - indicates evolutionary conserved functional regions of viral proteins so this is looking at all kinds of proteins that are part of the this novel coronavirus and how they match up against the previous other kinds of corona viruses and there's a lot of beautiful figures I was wondering if you could I mean there's so many questions I could ask her but maybe a tough how do you get started at doing this paper so how do you start to figure out the 3d structure of a novel virus yes so there is actually a little story behind it and so the story actually dated back in September of 2019 and you probably remember that back then we had another dangerous virus Triple E virus its eastern equine encephalitis virus and can you maybe linger in it I have to admit I was sadly completely unaware so so that was actually a virus outbreak that happened in New England only the the danger in this virus was that it actually it targeted your brain so so the word deaths from this virus it was it was transferred you know transfer the main vector was mosquitoes and obviously full-time is you know the time where you have a lot of them in New England and you know on one hand people realize this is this is this actually very dangerous thing so it had an impact on the local economy the schools were closed past six o'clock no activities outside for the kids because the kids were suffering quite tremendously from you know what infected from this virus and how do I not know about this was impacted it was in the news I mean it was not impacted to to high degree in in Boston necessarily but in the Metro West area and actually spread around I think all the way to New Hampshire Connecticut and you mentioned affecting the brain that's one other comment we should make so you mentioned a AC two for the corona virus so these viruses kind of attach to something in the body so it essentially attaches to the to these proteins in those cells in the body where those proteins are expressed where they actually have them in in abundance so sometimes that could be in the lungs that could be a brain that could be so I think what they right now from what I read they have the epithelial cells inside in so did the cells essentially inside the you know the it's the cells that are covering the surface you know so inside the nasal surfaces the this road the lung cells and I believe liver as a couple of other organs where they are actually expressing in abundance that's for the AC tuition for 318 two percenters okay so back back to the story yes in the fall so now the these you know the impact of this virus is significant however it's a pre local problem to the point that you know this something that we would call a neglected disease because it's not big enough to make you know the the drug design companies to design a new antiviral or in York seen it's not big enough to generate a lot of grants from the nation of finding agencies so so does it mean we cannot do anything about it and so what I did is I taught a by informatics class and is in Worcester Polytechnic Institute and we are very much problem learning institution so I thought that that would be a perfect you know perfect project in case study so so I asked it you know so so I we essentially designed a study where we tried to use by informatics to to understand as much as possible about this virus and a very substantial portion of the study was to understand the structures of the proteins to understand how they interact with with each other and with the with the host proteins try to understand the evolution of this virus it's obviously you know a very important question how where it will evolve further how you know how it happened here you know so so we did all this you know projects and now I'm trying to put them into a paper where all these undergraduate students will be coasters but essentially the projects were finished right about mid-december and a couple of weeks later I heard about this mysterious new virus that was discovered in you know was reported in in Wuhan province and immediately I thought that well we just did that can't we do the same thing with this virus and so we started waiting for the genome to be released because that's essentially the first piece of information that is critical once you have the genome sequence you can doing a lot using my informatics when you see genome sequence that's referring to the sequence of letters that make up the RNA so the sequence that make up the entire information encoded in the protein right so so that includes all 29 genes what are genes what's the encoding of information sosigenes is essentially is a basic functional unit that we can consider so so each gene in the virus would correspond to a protein that so gene by itself doesn't do it function it needs to be converted or translated into the protein that will become the actual functional unit like you said the printer so so we need the printer for that we need to print it okay so the the first step is to figure out that the genome the sequence of things that to be then used for printing the protein so okay so then then the next step so once we have this and so we use the existing information about Sarkis the Czar's genomics has been done in abundance so we have different strains of SARS and actually other related coronaviruses MERS the bat coronavirus and we started by identifying the potential genes because right now it's just the sequence right it's a sequence that is roughly it's less than 30,000 nucleotide long and this the raw sequence it's a rose ignore the information really and we now need to define the boundaries of the genes that would then be used to identify the proteins and protein structures how hard is that problem it's not I mean it's pretty straightforward so you know so because we use the existing information about SARS proteins and SARS genes so once again we kind of we are relying on the yes so and then once we get there this is where sort of the first more traditional bind phonetic steps step begins we are trying to use these protein sequences and get the 3d information about those proteins so this is where we are relying heavily on the structure information specifically from the protein data bank that we are talking about and here you're looking for similar proteins yes so so the the concept that we are operating when we do this kind of modeling it's called homology or template based modeling so essentially using the concept that if you have two sequences that are similar in terms of the letters the structures of these sequences are expected to be similar as well and this is at the micro at a very local scale and at the scale of the whole protein at the whole protein I saw actually so you know so of course the devil is any details and this is why we need actually pre sophisticated modeling tools to do so once we get these structures of the individual proteins we try to see whether or not this proteins act alone or they have to be forming protein complexes in order to perform this function and again so this is sort of the next level of the modeling because now you need to understand how proteins interact and it could be the case that the protein interacts with itself and makes sort of a multi marek complex the same protein just repeated multiple times and we have quite quite a few such proteins in Tsarskoe v2 specifically spike protein needs three copies to function and load protein needs five copies to function and there are some other multimeric complexes that we mean by interacted with itself and you see multiple copy so how do you how do you make a good guess whether something's going to interact well again so there are two approaches right so one is look at the previously solved complexes now we're looking not at the individual structures but the structures of the whole complex complex is upon multiple proteins yes so it's a bunch of proteins essentially glued together and and when you say glued that's the interaction that's the interaction so so the different forces different sort of physical forces behind this as I certainly keep asking dumb questions but is it is the glue is that the interaction fundamentally structural or is it functional like in the way you're thinking about it that's actually a very good way to ask this question because turns out that the interaction is structural but in the way it forms this truck it actually also carries out the function so interaction is often needed to carry out very specific function or protein but in terms of an earth-sized figuring out you're really starting at the structure before you figure out the function so there's a beautiful figure two in the paper of all the different proteins that make up the able to figure out the makeup the the new the novel current virus what what are we looking at right so these are like that's this through the the step to the mentioned when you try to guess at the possible proteins that's what you're going to get is these blue blue cyan blobs yes so those are the individual proteins for which we have at least some information from the previous studies right so there is advantage and disadvantage of using previous studies the biggest well the disadvantage is that you know we may not necessarily have the coverage of all 29 proteins however the biggest advantage is that the accuracy in which we can model these proteins is very high much higher compared to a Benicia methods that do not use any template information so but nevertheless this figure also has incision beautiful and I love these pictures so much you've as it has like the pink parts yes there are the parts that are different so you're highlighting so the difference you find is on the 2d sequence and then you try to infer what I would look like on the 3d yeah so the difference actually is on 1d sequence one d1 design idea so and and so this is one of these first questions that we try to answer is that well if you take this new virus and you take the closest relatives which are SARS and a couple of bad coronavirus strains they are already the closest relatives that we are aware of now what are the difference between this virus and its close relatives right and what if you look DIPA Klee when you take a sequence those differences could be quite far away from each other so what make what 3d structure makes those difference to do they very often they tend to cluster together interesting and over sudden the differences that may look completely unrelated actually relate to each other and sometimes they are there because they correspond they attack the functional side right so they are there because this is the functional side that is highly mutated so that's a computational approach to figuring something out when when it comes together like that that's kind of a nice clean indication that there's something this could be actually indicative of what's what's happening yes I mean so we need this information and you know 3d the 3d structure gives us just a very intuitive way to look at this information and then start to ask you know start asking questions such as so this place of this protein that is highly mutated does it does it is it the functional part of the protein so does this part of the protein interact with some other protein so maybe with some other ligands small small molecules right so we would try now to functionally inform this 3d structure so so you have a bunch of these mutated parts is like I don't know how like how many are there in the new novel coronavirus being compared it's ours oh we're talking about hundreds of thousands like these these pink region all know did much less than that and it's very interesting that if you look at that you know so the first thing that you you start seeing right you know you look at patterns right and the first pattern that becomes obvious is that some of the proteins in the new coronavirus are pretty much intact right so they're pretty much exactly the same as SARS as the bat coronavirus where some others are heavily mutated so so it looks like that the you know the evolution is not is not a curing you know uniformly across the entire you know viral genome but actually target very specific proteins what do you do with that like from the Sherlock Holmes perspective well you know so one of the of the most interesting findings we had was the fact that the viral so the the binding sites on the viral surfaces that get targeted by the known small molecules the world pretty much not affected at all and so that means that the same small drugs or small small drug like compounds can be efficient for the new current a virus this all actually maps to the drug compounds - like so so you're actually mapping out what old stuff is gonna work on this thing and then possibilities for new stuff to work by mapping out the things I've mutated yes so so we essentially know which parts is in behave differently and which parts are likely to behave similar and again you know of course all our predictions need to be validated by experiments but hopefully that sort of helps us to delineate the regions of this virus that you know can be promising in terms of the drug discovery you kind of you kind of mentioned this already but maybe you can elaborate so how different from this structural and functional perspective does the new corona virus appear to be relative to SARS we now are trying to understand the overall structural characteristics of this virus because I mean that's that's our next step trying to model the viral particle of a single viral particle of this virus so that means you have the individual proteins you think you said you have to figure out what their interaction is as you have this is that where this graph kind of interact on so so internet so so the interactome at the site is essentially a so our prediction on the potential interactions some of them that we already deciphered from the structural knowledge but some of them that essentially are deciphered from the knowledge of the existing interactions that people previously obtained for SARS for MERS or other related viruses so is there kind of interact ohms am i pronouncing that correctly weather interaction yeah are those already converged towards for SARS for so do I think there is there are a couple of papers that now investigate the sort of the large-scale set of sets of interactions between the new czars and its hosts and so I think that's that's an ongoing study I think and the success of that the result would be an interact on yes and so when you say not trying to figure out the entire the article the entire wrinkle right so if you look you know so structure right so what this viral particle looks like right so as I said it's it's you know the surface of it is an envelope which is essentially a so-called lipid bilayer with proteins integrated into the surface so how so so an average particle is around 18 nanometers right so this particle can have about 5,200 spike proteins so at least we suspect it and you know based on the micrographs images it's very comparable to m hv virus in mice and SARS virus micrographs are actual pictures of the actual virus okay so these are models this is that at least so they did actual meat images right what do they sorry for the tangents but what are these things so when you look on the internet the models and the pictures are in pen and the models you have here just gorgeous and beautiful when you actually take pictures of them or the micrograph like what what do we look well they typically are not perfect it's also the most of the images that you see now is the is the sphere with those spikes you actually see bikes yes yes you do see the spikes and now you know the our collaborators for Texas and I am Benjamin Moomin he actually in the recent paper about SARS he proposed and there is some actually evidence behind it that the particle is not a sphere but is actually is elongated ellipsoid like particles so so that's what we are trying to incorporate into our model and the reaiiy mean you know if you look at the actual micrographs you see that those particles are you know are not symmetric so there's some of them and of course you know it could be due to the treatment of the of the material it could be due to the some noise in the imaging so there's a lot of uncertainty so it's okay so structurally figuring out the entire part by the way again sorry for the tangents but why the term particle or is it just it's it's a single you know so we could you know we call it the virion so very unparticle it's essentially a single virus single virus but just feels like this particle to me from the physics perspective feels like this the most basic unit because there seems to be so much going on inside the virus yeah it doesn't feel like a particle - yes well yeah it's probably I think it's the the you know variant is is a good way to call it so okay so trying to figure out trying to figure out the entirety of the system yes so you know so you know so this is so severe ian has 5,200 spikes a trimer spikes it has roughly 200 to 400 membrane protein dimers and those are arranged in there very nice lattice so you can actually see sort of the it's it's like a it's a carpet of on the surface again exactly on the surface and occasionally you also see this envelope protein inside and some of the one we don't know what it does actually exactly the one that that forms the pentamer this very nice pentameric ring and so you know so this is what we're trying to you know we're trying to put now all our knowledge together and see whether we can actually generate this overall variant model with an idea to understand you know well first of all to understand how how it looks like how far it is from those images that were generated but I mean the implications are you know there is a potential for the you know nanoparticle design that will mimic this variant particle is the process of nanoparticle design meaning artificially designing something that looks similar yes you know so the one that can potentially compete with the actual variant particles and therefore reduce the effect of the infection so is this the idea of like what is a vaccine so vaccine vaccine so so that yes so there are two ways of essentially treating and in the case of vaccine is preventing the infection so vaccine is you know a way to train our immune system so our immune system becomes aware of this new danger and therefore is capable of generating the antibodies then we'll essentially bind to the spike proteins because that's the main target for the end of for the vaccines design and block its found if you have the spike with the antibody on top and can no longer interact with a co2 receptor so the the process of designing vaccine and is you have to understand enough about the structure the virus itself to be able to create an artificial our official particle well I mean so so so the nanoparticle is is a very exciting and new research so there are already established ways to you know to make vaccines and several different ones right so so there is one where essentially the the virus gets through the cell culture multiple times so it becomes essentially account you know adjusted to the to the specific embryonic cell and as a result become becomes less I you know compatible with the you know host human cells so therefore it's sort of the idea of the life vaccine where the particles are there but they are not so efficient you know so they cannot replicate you know as rapidly as you know before the vaccine and that they can be introduced to the immune system the immune system will learn and the person who gets this vaccine one won't get you know sick or you know will have mild you know mild symptoms so then there is sort of different types of the way to introduce the non-functional non-functional part of this virus or the virus where some of the information is stripped down for example device with no genetic material so so we ignore our age you know exactly so you cannot replicate it cannot essentially perform most of its functions that saying well what is the big hurtle to design one of these to arrive one of these is it the work that you're doing in the fundamental understanding of this new virus or is it in the from our perspective a complicated world of experimental validation and sort of showing that this like going through the whole process of showing this is actually gonna work with FDA approval all that kind of stuff I think it's both I mean you know our understanding of the molecular mechanisms will allow us to you know to design to have more efficient designs of the vaccines however they once you design the vaccine it it needs to be tested but when you look at the 18 months and the different projections which seems like an exceptionally from historically speaking maybe you can correct me but it's even 18 months seems like a very accelerated timeline it is it is I mean I remember reading about the you know in a book about some previous vaccines that it could take up to 10 years to design and you know properly test a vaccine before its mass production so yeah we you know everything is accelerated these days I mean for better for worse but but you know we we definitely need that well especially the corner virus and in the scientific community is really stepping up and working together the collaborative aspect is really interesting you mentioned so the vaccine is one and then there's antivirals antiviral drugs so antiviral drugs so we're you know vaccines are typically needed to prevent the infection right but once you have an infection one you know so what we try to do try to stop it so we try to stop virus from functioning and so the antiviral drugs are designed to block some critical function of the of the proteins from the viral from the virus so there are a number of interesting candidates and I think you know if you ask me I you know I think remedy severe is perhaps the most promising it's it has been shown to be you know an efficient and effective antiviral for SARS originally it was the the antiviral drug developed for completely different virus I think for a ball and bar Marburg and high level you know how it works so it tries to mimic one of the nucleotides in RNA and essentially that that stops the replication from so messes I guess that's what so anywhere all drugs mess some aspect of this yes process so you know so essentially we try to stop certain functions of the virus there are some other ones you know that are designed to inhibit the protease the the thing that clips protein sequences there is one that was originally designed for malaria which is a bacterial you know bacterial disease so this is so cool so but that's exactly where your work steps in is you're figuring out the functional then the structure these different so like providing candidates for where drugs can plug in exactly well yes because you know one thing that we don't know is whether or not so let's say we have a perfect drug candidate that is efficient against SARS and again Smurfs now is it going to be efficient against New South Korea too we don't know that and there are multiple aspects that can affect this efficiency so for instance if the the binding site so the the part of the protein where this ligand gets attached if this site is mutated then the ligand may not be attachable to this part any longer and you know our work and the work of other by informatics groups you know essentially are trying to understand whether or not that will be the case or and it looks like for for the ligands that we looked at the ligand binding sites are pretty much intact which is very promising so if we can just like zoom out for a second what are you optimistic so this - well there's three possible ends - the corona virus pandemic so one is there's or drugs or vaccines get figured out very quickly probably drugs first the other is the the the pandemic runs its course for this wave at least and then the the third is you know things go much worse and some in some dark bad very bad direction do you see let's focus on the first two do you see the anti-drugs of the work you're doing being relevant for us right now in stopping the pandemic or do you hope that the pandemic will run its course so the social distancing things like wearing masks all those discussions that we're having will be the the method with which we fight coronavirus in the short term or do you think that it'll have to be antiviral drugs I think I think antivirals would be I would view that as the at least the short term solution I see more and more cases in news of those new drug candidates been administered in hospitals and I mean this is right now the best what we have but do we need it to reopen the economy I mean we definitely need it i i cannot sort of speculate on how that will affect reopening of the economy because we are you know we are kind of deep in into the pandemic and it's not just the the states it's also you know worldwide you know of course you know there is also the possibility of the second wave as we you know as you mentioned and this is why you know we need to be super careful we need to follow all the precautions that the doctors tell us to do are you worried about the mutation the virus so it's of course a real possibility now how to what extent this virus can mutate it's an open question I mean we know that it is able to mutate to jump from one species to another and to to become transmissible between humans right so will it you know so let's imagine that we have the new antiviral will this virus become eventually resistant to this antiviral we don't know I mean this is what needs to be studied this is such a beautiful and terrifying process that a virus some viruses may be able to mutate to respond to the mutate around the thing we've put before it can you explain that process like how does that happen just is that just the way of evolution I would say so yes I mean it's it's the evolutionary mechanisms there is nothing imprinted into this virus that makes it you know it just the way it it walls and actually it's the way it Cory walls with its host it's just amazing it's especially the evolution mechanism is especially amazing given how simple the virus is it's incredible that it's I mean it's beautiful it's beautiful because it's the one of the cleanest examples of evolution working well I think I mean the one of the sort of the reasons for its simplicity is because it does not require all the necessary functions to be stored right so it actually can hijack they may the majority of the necessary function from the host cell and it's so so so so the ability to do so in my view reduces the complexity of this machine drastically although if you look at the you know most recent discoveries right so the scientists discovered viruses that are as large as bacteria right so this mini viruses and Mama viruses it actually those discoveries made scientists to reconsider the origins of the virus you know and what are the mechanisms and how you know what are the mechanisms the evolution mechanisms that leads to the appearance of the viruses by the way I mean you did mention that viruses are I think you mentioned that they're now living yes they are not living organisms so let me ask that questioning and why do you think they're not living organisms well because they they are dependent the majority of the functions of the virus are dependent on the on the host so let me do the devil's advocate let me be the philosophical that was advocate here and say while humans which we would say our living need our host planet to survive so you can basically take every living organism that we think of as definitively living it's always going to have some aspects of it this host that it needs of its environment so is that really the key aspect of why a virus is that dependence because it seems to be very good at doing so many things that we consider to be intelligent it's just that dependence part well I mean it yeah it's it's difficult to answer in this way I mean I the way I think about the virus is you know in order for it to function it needs to have the critical component the critical tools that it doesn't have so I mean that's that's you know in my way you know the it's not autonomous I sense and that that's how I separate the the idea of the living work is on a very high level yes between the living organism and and you have some no we have I mean this is just terms and perhaps they don't mean much but we have some kind of sense of what autonomous means and that humans are autonomous you've also done excellent work in the epidemiological modeling the simulation of these things so the zooming out outside of the body during the aging based simulation so that's where you actually simulate individual human beings and then the spread of viruses from one to the other how does at a high level agent-based simulation work all right so it's it's also one of this I irony of timing because I mean way we we've worked on this project for the past five years and the New Year's Eve I got an email from my Fiji student that you know the last experiments were completed and you know the three weeks after that we get we get this diamond princess story and emailing each other with the same you know the same news saying okay so the damn place is a cruise ship yes and what was the project that you working so I project I mean it's you know the codename it started with the bunch of undergrad use the code name was zombies on a cruise ship so they they wanted to essentially model the the you know zombie apocalypse apocalypses on a cruise ship and and you know after having you know some fun we then thought about the fact that you know if you look at the cruise ships I mean the infectious outbreak is has been one of the biggest threat you know threats to the cruise ship economy so perhaps the most you know frequently occurring via is the normal choirs and this is essentially one of this stomach flus that you have and you know it it can be quite devastating you know so there are occasionally there are cruise ships get you know they get canceled they get returned to the back to the to the origin and so we wanted to study and this is very different from the traditional epidemiological studies where this scale is much larger so we wanted to study this in a confined environment which is a cruise ship it could be a school it could be other you know other places such as you know these large large company where people are in interaction and the benefit of this model is we can actually track that in the real time so we can actually see the whole course of the evolution or the whole course of the interaction between the infected pass infected horse and you know the host and the pathogen etcetera so so agent based system multi-agent system to be precisely is a good way to approach this problem because we can introduce the behavior of the of the passengers of the cruise and what we did for the first time that's where you know we introduced um knology is we introduced a pathogen agent explicitly so that allowed us to essentially model the behavior on the host site as well on the pathogen site and over sudden weekends we can have a flexible model that allows us to integrate all the key parameters about the infections so for example the virus right so the ways of of transmitting the virus between the the horse how long does virus survive on the surface for might what is you know how much of the viral particles does a host shed when he or she is asymptomatic versus symptomatic you can encode all of that into this pattern just for people who don't know so agent-based simulation usually the agent represents a single human being and then there's some graphs like contact graphs that represent the interaction between those human being so yes so we so essentially is you know social agents are you know individual programs that are run in parallel and we're saying we can provide instructions for these agents how to interact with each other how to exchange information in this case exchange the infection but in this case in your case you've added a pathogen as an Asian I mean that's kind of fascinating it's a it's kind of a brilliant simple like a brilliant way to condense the parameters to aggregate to bring the parameters together that represent them in the pathogen the virus yes that's fascinating actually so yeah it was a you know we realized that you know by bringing in the virus we can actually start modeling I mean we were not no longer bounded by very specific sort of aspects of the specific virus so we end up we started with you know Norwalk virus and of course zombies but we continued to modeling Ebola virus outbreak flu SARS and because I felt that we need to add a little bit more of excitement for our undergraduate students so we actually modeled the virus from the contagion movie yes so MeV won and you know unfortunately that virus and we we try to extract as much information luckily the this movie was the scientific consultant was Ian Lipkin a virologist from Columbia University who is actually who provided I think he designed this virus for this movie based on Nipah virus and I think with some ideas behind source of flu like airborne viruses and you know the it the movie surprisingly contained enough details for us to extract and to model it I was hoping you'd like publish a paper of how this virus works yeah we're planning to publish I would love it if you guys will be nice if the you know of the origin of the virus but you're now actually being a scientist and studying the virus from that perspective but the origin of the virus you do you know you know the first time actually so this movie is assignment number one in my band families class that they give because it it also tell it tells you that you know by informatics can be of use because if if I don't know you watch the have you watched it a long time so so there is you know approximately a week from the you know virus detection we see a screenshot of scientists looking at the structure of the surface protein and this is where I tell my students that you know if you ask experimental biologists they will tell you that it's impossible because it takes months maybe years to get the crystal structure of this you know the structure that is represented if you ask you buy from a Titian they tell you why not just get it modeled and and yes but it was very interesting to to see that there is actually you know and if you do it do screenshots you actually see they feel a genetic tree is the evolutionary tree that relate this virus with other viruses so it was a lot of scientific thought put into the movie and one thing that I was actually you know it was interesting to to learn is that the origin of this virus was a there were two animals that led to the you know the the the you know the zoonotic original dis virus were fruit bat and as a peak so you know so so this is this doesn't feel like well this this definite views like we're living in a simulation okay but maybe a big picture agent-based simulation now larger scale sort of not focused on a cruise ship a larger scale are used now to drive some policy so politicians use them to tell stories and narratives and try to figure out how how to move forward and there's so much so much uncertainty but in your sons are agent-based simulation useful for actually predicting the future or are they useful mostly for comparing relative comparison of different intervention methods well I think both because you know in the case of new coronavirus we essentially learning that the current intervention methods may not be efficient enough one thing that one important aspect that I find to be so critical and yet something that was over looked you know during the past pandemics is the effect of the symptomatic period this virus is different because it has such a long symptomatic period and over sudden that creates a completely new game when trying to contain this virus it enters the dynamics of the infection exactly I do also I don't know how close you're tracking this but do you also think that there's a different like rate of infection from when you're asymptomatic like that that aspect or does a virus not care so there were a couple of works so one important parameter that tells us how contagious the the person with a symptomatic device versus are symptomatic is looking at the number of viral particles this person sheds you know as a function of time so so far what I saw is the study that tells us that the you know the person during the asymptomatic period is already contagious and it said the person says enough viruses to infect yeah and another horse and I think there's too many excellent papers coming up but I think I just saw so maybe a nature paper that said the first week is when you're symptomatic or asymptomatic you're the most contagious so the highest level of the like there's a plot sort of in the 14-day period they collected a bunch of subjects and I think the first week is one is the most yeah I I think I mean I'm waiting I'm waiting to see sort of more more populated studies where I just it was kinda my one of my favorite styles was again very recent one where scientists determined that tears are not contagious so so there is you know so there is no viral shedding down through three tears so they found one wick moist thing that's not contagious and I mean there's a lot of I'm personally been I'm gonna serve a paper somehow that's looking at masks and there's been so much interesting debate on the efficacy of masks and there's a lot of work and there's a lot of interesting work on whether this virus is airborne and it's a totally open question is it's leaning one way right now but it's a totally open question whether it can travel and aerosols long distances I mean do you have us do you think about the stuff do you track this stuff are you focused on them yeah I mean I'm at it I mean did this is this is a very important aspect for our epidemiology study I think the I mean and it's sort of a very simple sort of idea but I agree with people who say that they mask the masks work in both stay in both ways so it not only it protects you from the you know incoming viral particles it also protect you know it it you know makes the potentially contagious person not to spread the right of party noise when they're asymptomatic may not even know that they're in fact it seems to be there's evidence that they don't surgical and certainly homemade masks which is what's needed now actually because there's a huge shortage of they don't work as to protect you that while they work much better to protect others it's it's a motivation for us to all wear one exactly because I mean you know very you don't know where you know inside you know about 30% as far as I remember at least 30% of the asymptomatic cases are completely asymptomatic here right so you don't really care you don't I mean you don't have any symptoms yet you shed viruses do you think it's possible that we'll all wear masks so I wore masks at a grocery store and you just you get looks I mean it was like we could go maybe it's already changed because I think CDC or somebody's I think the CDC has said that we should be wearing masks like la they starting to happen but you it just seems like something that this country will really struggle doing or no I hope not I mean you know it it was interesting I was looking through the through the old pictures during the Spanish flu and you could see that the you know pretty much everyone was wearing masks with some exceptions and they were like you know sort of iconic photograph of the thing it was San Francisco this tram who was refusing to let in a you know someone without the mask so I think well you know it's also you know it's related to the fact you know how much we are scared right so how much do we treat this problem seriously and you know my take on it is we should because it is very serious yeah I i from a psychology perspective just worried about the entirely the entire big mess the of a psychology experiment that this is whether masks will help it or heard it you know the masks have a way of distancing us from others by removing the emotional and all that kind of stuff but at the same time masks also signal that I care about your well-being exactly so it's a really interesting trade-off that's just uh yeah it's it's interesting right about distancing uh aren't we distance enough right exactly Hey and when we tried to come closer together when they do reopen the economy that's going to be a long road of rebuilding trust and not not all being huge germophobes let me ask sort of you have a bit of a Russian accent Russian or no Russian accent uh were you born in Russia yes and the you you're too kind I have a pre thick Russian accent what are your favorite memories of Russia so I so I moved first to Canada and then to the United States back in 99 so by that time I was 22 so you know whatever Russian accent III got back then you know it's that use me for the rest of my life you know it's yeah so I you know by the time the Soviet Union collapsed I was you know I was a kid but through you know old enough to to realize that there are changes and did you want to be a scientist back then oh yes oh yeah I mean my first the first sort of ten years of my sort of you know a juvenile life I wanted to be a pilot of a passenger jet plane Wow so yes it was like you know I was getting ready you know to go to a college to get the degree but I've been always fascinated by science and you know so not just by mass of course math was one of my favorite subjects but you know biology chemistry physics somehow I you know I liked those four subjects together and guess so so so essentially after a certain period of time I wanted to actually back then it was a very popular sort of area of science called cybernetics so it's sort of it's not really computer science but it's it was like you know computation or robotics yes in this sense and so I really wanted to do that and but then you know I you know I realized that you know my biggest passion was in mathematics and later I you know when you know studying in Moscow State University I also realized that I really want to apply the the knowledge so I really wanted to to mix you know the mathematical knowledge that I get with real-life problems and that could be you mentioned chemistry and now biology and I sort of does it make you sad maybe I'm wrong on this but it seems like it's difficult to be in collaboration to do open big science in Russia from my distant perspective in computer science I don't I'm not like we can go to conferences in Russia I sadly don't have many collaborators in Russia I don't know many people doing great a I work in Russia does it make does that make you sad am I wrong and seeing it this way well I mean I am I have to tell you I am privileged to to have collaborators in biometrics in Russia and I think this is the divine thematic school in Russia is very strong we have in Moscow in Moscow in Novosibirsk in st. Petersburg have great collaborators in cousin and so at least you know in terms of you know my area of research strongly people there yes strong people a lot of great ideas very open to collaborations so I perhaps you know it's my luck but you know I haven't experienced you know any difficulties in establishing collaborations that's why informatics it could be bad from a text to an ink yeah it's it could be person by person related but I just don't feel the warmth and love that I would you know you talk about the seminal people who are French in artificial intelligence France welcomes him with open arms in so many ways I just don't feel the love from Russia I I do on the human beings like people in general like friends and and just cool interesting people but from the scientific community no conferences no big conferences and it's uh yeah it's actually you know I I'm trying to think yeah I cannot recall any any big AI conferences in Russia it has an effect on for me I haven't sadly been back to Russia so I should but my problem is it's very difficult so I am now I have to renounce the citizenship I was alright I mean I'm a citizen in the United States and it makes it very difficult there's a mess now right so I want to be able to travel like you know legitimately yeah and it's it's not it's not an obvious process they don't make it super easy I mean that's that like you know it should be super easy for me to travel there well you know hopefully this unfortunate circumstances that we are in will actually promote the remote collaborations yes and I think we weave jr' experiencing right now is that you still can do science you know being current in in your own homes yeah especially when it comes I mean you know I I certainly understand there is a very challenging time for experimental scientists and and I have many collaborators who are you know who are affected by that but for computational scientists they are really leading into the remote communication nevertheless I had to force you to talk to you in person because there's something that you just can't do in terms of conversation like this I don't know why but in person it's very much needed so I really appreciate you doing it you have a collection of science bobbleheads yes which look amazing which which bobblehead is your favorite and which real-world version which scientist is your favorite yeah so yeah by the way I was trying to bring it in but they're cranking now in my in my office they sort of demonstrate the social distance so they're nicely spaced away from each other but so you know it's interesting so I've been I've been collecting those bubble has for the past maybe twelve or thirteen years and it you know interesting enough it started with the two bubble heads of Watson and Crick and interestingly enough my last bubble had in this collection for now and my favorite one cuz I felt so good when I got it was the rosalind Franklin and so so you know when I go who's the full group so I have what some Creek Newton Einstein Marie Curie Tesla of course Charles Darwin Sir Charles Darwin and wasn't Franklin I am definitely missing quite a few of my favorite scientists and but so you know if I were to add to this collection so I would add of course Kolmogorov injustice that's that's you know I've been always fascinated by his well his dedication to science but also his dedication to educating young people the next generation so it's it's it's very inspiring he's one of the right okay yeah he's one of the Russia's great yes only yes so he also you know the school the high school that I attended was named after him and he was great you know so he founded this core school and he actually taught there is this is a Moscow yes so but then I mean you know other people that I would definitely like to see in my collections was would be Alan Turing would be John von Neumann yeah you're a little bit later in the computer scientists yes well I mean they don't they don't make them you know III still I'm amazed they they haven't made Alan Turing yeah yet yes and and and I would also add the Linus Pauling line is falling so with Linus point so this is this is to me is one of the greatest chemists and the person who actually discovered secondary structure of proteins was very close to solving the DNA structure and you know people argue but some of them were pretty sure that if not for this you know photograph 51 by rosalind Franklin that you know what Sun Cree got access to he would be he would be the one who so sense is a funny race let me ask the biggest the most ridiculous question so you've kind of studied the human body and its defenses and these enemies that are about from a biological perspective and from a tax perspective a computer scientist perspective how is that made you see your own life sort of the meaning of it or just even seeing your what it means to be human well it certainly makes me realizing how fragile the human life is if you think about this little tiny thing can impact the life of the whole human kind to such extent so you know it's it's something to appreciate and to you know to remember that that you know we are fragile we have to bond together as a society and you know it also gives me sort of hope that what we do a scientist is useful I don't think there's a better way to end it means you take it so much for talking today it was an honor thank you very much thanks for listening to this conversation with Mitra korkin and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter at lex friedman and now let me leave you with some words from edward osborne Wilson Leo Wilson the variety of genes and the planet and viruses exceeds or is likely to exceed that in all of the rest of life combined thank you for listening and hope to see you next time you |
Stephen Wolfram: Cellular Automata, Computation, and Physics | Lex Fridman Podcast #89 | the following is a conversation with Stephen Wolfram a computer scientist mathematician and theoretical physicist who is the founder and CEO of Wolfram research a company behind Mathematica Wolfram Alpha Wolfram language and the new Wolfram physics project is the author of several books including a new kind of science which on a personal note was one of the most influential books in my journey in computer science and artificial intelligence it made me fall in love with the mathematical beauty and power of cellular automata it is true that perhaps one of the criticisms of Stephen is in a human level that he has a big ego which prevents some researchers from fully enjoying the content of his ideas we talked about this point in this conversation to me ego can lead you astray but can also be a superpower one that fuels bold innovative thinking that refuses to surrender to the cautious ways of academic institutions and here especially I ask you to join me in looking past the peculiarities of human nature and opening your mind to the beauty of ideas and Stephens work and in this conversation I believe Stephen Wolfram is one of the most original minds of our time and at the core is a kind curious and brilliant human being this conversation was recorded in November 2000 nineteen when the Wolfram physics project was underway but not yet ready for public exploration as it is now we now agreed to talk again probably multiple times in the near future so this is round one and stay tuned for round two soon this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review five stars in Apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma n as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you it doesn't hurt the listening experience quick summary of the ads to sponsors expressvpn and cash app please consider supporting the podcast by getting expressvpn and expressvpn com / FlexPod and downloading cash app and using code lex podcast this show is presented by cash app the number-one finance app in the App Store when you get it use collects podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 this cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props the cash app engineers for solving a hard problem then in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market this makes trading more accessible for new investors and diversification much easier so again if you get cash out from the App Store Google Play and use the code lex podcast you get $10 and cash shop will also donate $10 the first an organization that is helping to advanced robotics in STEM education for young people around the world the show is presented by expressvpn get it at expressvpn calm / Lex pod to get a discount and to support this podcast I've been using expressvpn for many years I love it it's really easy to use press the big power on button and your privacy is protected and if you like you can make it look like your locations anywhere else in the world this has a large number of obvious benefits certainly it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu expressvpn works on any device you can imagine I use it on Linux shout-out to Oban to new version coming out soon actually windows Android but it's available anywhere else to once again get it at expressvpn comm / lex pod to get a discount and to support this podcast and now here's my conversation with stephen wolfram you and your son Christopher helped create the alien language in the movie arrival so let me ask maybe a bit of a crazy question but if aliens were to visit us on earth do you think we would be able to find a common language well by the time we're saying aliens are visiting us we've already prejudiced the whole story because the you know the concept of alien actually visiting so to speak we already know they're kind of things that make sense to talk about visiting so we already know they exist in the same kind of physical setup that we do they're not you know it's not just radio signals it's an actual thing that shows up and so on so I think in terms of you know can one find ways to communicate well the best example we have of this right now is AI I mean that's our first sort of example of alien intelligence and the question is how well do we communicate with AI you know if you were to say if you were in the middle of a neural net and you open it up and it's like what are you thinking can you discuss things with it it's not easy but it's not absolutely impossible so I think I think by the time but given the setup of your question aliens visiting I think the answer is yes one will be able to find some form of communication whatever communication means communication requires notions of purpose and things like this it's a kind of philosophical quagmire so if AI is a kind of alien life-form what do you think visiting looks like so if we look at a Lian's visiting yeah and we'll get to discuss computation and and the world of computation but if you were to imagine you said you're already prejudiced something by saying you visit but what how would a lian's visit by visit there's kind of an implication and here we're using the imprecision of human language you know in a world of the future and if that's represented in computational language we might be able to take the the concept visit and go look in the documentation basically and find out exactly what does that mean what properties does it have and so on but by visit in ordinary human language I'm kind of taking it to be there's you know something a physical embodiment that shows up in a spacecraft since we kind of know that that's necessary we're not imagining it's just you know photons showing up in a radio signal that you know photons in some very elaborate pattern we're imagining it's it's physical things made of atoms and so on that that show up can't be photons in a pattern well that's good question I mean whether there is the possibility you know what counts as intelligence good question I mean it's some you know and I used to think there was sort of a oh they'll be you know it'll be clear what it means to find extraterrestrial intelligence etcetera etcetera etcetera I've I've increasingly realized as a result of science that I've done that there really isn't a bright line between the intelligent and the merely computational so to speak so you know in our kind of everyday sort of discussion will say things like you know the weather has a mind of its own well we'd let's unpack that question you know we realize that there are computational processes that go on that determine the fluid dynamics of this and that and the atmosphere or etcetera etcetera etcetera how do we sting which distinguish that from the processes that go on in our brains of you know the physical processes that go on in our brains how do we how do we had we separate those how do we say the the physical processes going on that represents sophisticated computations in the weather oh that's not the same as the physical processes that go on that represent sophisticated computations in our brains cancer is I don't think there is a fundamental distinction I think the distinction for us is that there's kind of a a thread of history and so on that connects kind of what happens in different brains to each other so to speak and it's a you know what happens in the weather is something which is not connected by sort of a a thread of civilizational history so to speak to what we're used to in our story in the stories that the human brains told us but maybe the weather has its own stories that's Allah's house absolutely and that's and that's where we run into trouble thinking about extraterrestrial intelligence because you know it's like that pulsar magnetosphere that's generating these very elaborate radio signals you know is that something that we should think of as being this whole civilization that's developed over the last however long you know millions of years of of processes going on in the in the neutron star or whatever um versus what you know what we're used to in human intelligence and I think it's a I think in the end you know when people talk about extraterrestrial intelligence and where is it in the whole you know Fermi paradox of how come there's no other signs of intelligence in the universe my guess is that we've got sort of two alien forms of intelligence that we're dealing with artificial intelligence and sort of physical or extraterrestrial intelligence and my guess is people will sort of get comfortable with the fact that both of these have been achieved around the same time and in other words people will say well yes we're used to computers things we've created digital things we've created being sort of intelligent like we are and they'll sell we're kind of also used to the idea that there are things around the universe that are kind of intelligent like we are except they don't share the sort of civilizational history that we have and so we don't they know they're they're a different branch I mean it's similar to when you talk about life for instance I mean you you you kind of said life form I think almost synonymously with intelligence which I don't think is is some you know I the the a eyes will be upset to hear you I wait those guys I really probably implied biological life right right right but you're saying I mean we'll explore this more but you're saying it's really a spectrum and it's all just the kind of computation and so it's it's a full spectrum and we just make ourselves special by weaving a narrative around our particular kinds of computation yes I mean what the thing that I think I've kind of come to realize is you know it's a little depressing to realize that there's there's so little it's liberating well yeah but I mean it's you know it's the story of science right in you know from Copernicus on it's like you know first we were like convinced a planets at the center of the universe no that's not true well then we will convince there something very special about the chemistry that we have as biological organisms now that's not really true and then we're still holding out that hope or this intelligence thing we have that's really special yeah I don't think it is however in a sense as you say it's kind of liberating for the following reason that you realize that what's special is the details of us not some abstract attribute that you know we could wonder Oh is something else going to come along and you know also have that abstract attribute well yes every abstract attribute we have something else has it but the full details of our kind of history of our civilization and so on nothing else has that that's what you know that's our story so to speak and that's sort of one most by definition special so I I view it as not being such a I mean I was initially I was like this is bad this is this is kind of you know how can we have self-respect about some about the things that we do then I realized the details of the things we do they are the story everything else is kind of a blank canvas so maybe on a small tangent you just made me think of it but what do you make of the monolith in 2001 Space Odyssey in terms of aliens communicating with us and sparking the the kind of particular intelligent computation that we humans have is there anything interesting to get from that sci-fi yeah I mean I think what's what's fun about that is you know the monoliths are these you know one to four to nine perfect cuboid things and in the you know earth four million years ago whatever they will pertain with a bunch of apes and so on a thing that has that level of perfection seems out of place it seems very kind of constructed very engineered so that's an interesting question what is the you know what's the techno signature so to speak what is it that you see it somewhere and you say my gosh that had to be engineered um now the fact is we see crystals which are also very perfect and you know that the perfect ones are very perfect they're nice polyhedra or whatever um and so in that sense if you say well it's a sign of sort of it's a techno signature that it's a perfect you know a perfect polygonal shape polyhedral shape that's not true and so then it's it's an interesting question what what is the you know what is the right signature I mean like you know Gauss famous mathematician you know he had this idea you should cut down the Siberian forest in the shape of sort of a typical image of the proof of the Pythagorean theorem on the grounds that there's a kind of cool idea didn't get done but um you know it's on the grounds that the Martians would see that and realize gosh there are mathematicians out there it's kind of you know it's the in his theory of the world that was probably the best advertisement for the cultural achievements of our species um but you know it's it's a it's a reasonable question what do you what can you send or create that is a sign of intelligence in its creation or even intention in its creation you talk about if we were to send a beacon can you what what should we send is math our greatest creation is what is our greatest creation I think I think in it's a it's a philosophically doomed issue so I mean in other words you send something you think it's fantastic but it's kind of like we are part of the universe we make things that are you know things that happen in the universe computation which is sort of the thing that we are in some abstract sent you then sense using to create all these elaborate things we create is surprisingly ubiquitous in other words we might have thought that you know we've built this whole giant engineering stack that's led us to microprocessors that's led us to be able to do elaborate computations but this idea the computations are happening all over the place the only question is whether whether there's a thread that connects our human intentions to what those computations are and so I think I think this question of what do you send to kind of show off our civilization in the best possible way I think any kind of almost random slab of stuff we've produced is about equivalent to everything else I think it's one of these things where it's a non romantic way of phrasing it I just started to interrupt but I just talked to it up Andrew in who's the wife of cross hanging uh-huh and so I don't know if you're familiar with the Voyager it's just part of its ascending I think brainwaves of you know I wasn't it hers it was yeah her brain waves when she was first falling in love with Carl Sagan right it's this beautiful story right that brand that perhaps you would shut down the power of that by saying we might as well send anything else and that's interesting all of it is kind of an interesting peculiar thing that's yeah yeah right well I mean I think it's kind of interesting to see on the on the Voyager you know golden record thing one of the things that's kind of cute about that is you know it was made one was it in the late seventies early eighties yeah um and you know one of the things it's a phonograph record okay and it has a diagram how to play a phonograph record and you know it's kind of like it's shocking that in just 30 years if you show that to a random kid of today and you show them that diagram I've tried this experiment they're like I don't know what the heck this is and the best anybody can think of is you know take the whole record forget the fact that it has some kind of helical track in it just image the whole thing and see what's there that's what we would do today in only 30 years our technology has kind of advanced to the point where the playing of a helical you know mechanical track on a phonograph record is now something bizarre so you know it's it's that's a cautionary tale I would say in terms of the ability to make something that in detail sort of leads by the nose some you know the aliens or whatever to do something it's like no you know best you can do as I say if we were doing this today we would not build a helical scan thing with a needle we would just take some high resolution imaging system and get all the bits off it say oh it's a big nuisance that they put in a helix you know the spiral let's sum let's just you know unravel the spiral and then start from there do you think and this will get into trying to figure out interpretability of AI interpretability of computation being able to communicate with various kinds of computations do you think would be able to if you're put put your alien hat on figure out this record how to play this record well it's a question of what one wants to do I mean understand what the other party was trying to communicate or understand anything about the other party what is understanding mean I mean that's the issue the issue is it's like what people were trying to do natural language understanding for computers right so people try to do that for years it wasn't clear what it meant in other words you take your piece of English or whatever and you say gosh my computer has understood this okay that's nice what can you do with that well so for example when we did you know built wolf malphur um you know one of the things was it's you know it's doing question answering and so on it needs to do natural language understanding the reason that I realized after the fact the reason we were able to do natural language understanding quite well and people hadn't before the number one thing was we had an actual objective for the natural language understand and we were trying to turn the natural language into commentation into this computational language that we could then do things with now similarly when you imagine your alien you say okay we're playing them the record did they understand it well it depends what you mean if they you know if we if there's a representation that they have if it converts to some representation where we can say oh yes that is a that's a representation that we can recognize is represents understanding then all well and good but actually the only ones that I think we can say would represent understanding a ones that will then do things that we humans kind of recognize as being useful to us maybe a trying to understand quantify how technological advances particular civilization is so are they a threat to us from a military perspective yeah yeah that's probably the kind of first kind of understanding that would be interested in gosh that's so hard I mean that's like in the arrival movie that was sort of one of the key questions as is you know why are you here so to speak and it's I using a hurtis right but but even that is that you know it's a very unclear you know it's like the the are you gonna hurt us that comes back to a lot of interesting area fix questions because the you know we might make an AI that says blood take autonomous cars for instance you know are you gonna hurt us well let's make sure you only drive at precisely the speed limit because we want to make sure we don't hurt you so to speak because that's some and then well something you know but you say but actually that means I'm gonna be really late for this thing and you know that sort of hurts me in some way so it's hard to know even even the definition of what it means to hurt yeah someone is unclear and as we start thinking about things about AI ethics and so on that's you know something one has to address there's always trade-offs and that's the annoying thing about ethics yeah well right and I mean I think ethics like these other things we're talking about is a deeply human thing if there's no abstract you know let's write down the theorem that proves that this is ethically correct that's a that's a meaningless idea you know you have to have a ground truth so to speak that's ultimately sort of what humans want and they don't all want the same thing so that gives one all kinds of additional complexity and thinking about that one convenient thing in terms of turning ethics into computation you ask the question of what maximizes the likelihood of the survival of the species that's a good existential issue but then when you say survival of the species right you might say um you might for example for example let's say forget about technology just you know hang out and you know be happy live our lives go on to the next generation and you know go through many many generations where in a sense nothing is happening that okay is that not okay hard to know in terms of the attempt to do elaborate things and the attempt to might be counterproductive for the survival of the species like for instance I mean in in you know I think it's it's also a little bit hard to know so ok let's take that as a sort of thought experiment ok you know you can say well what are the threats that we might have to survive you know the supervolcano the asteroid impact the you know all these kinds of things ok so now we inventory these possible threats and we say let's make our species as robust as possible relative to all these threats I think in the end it's a it's sort of an unknowable thing what what it takes to you know so so given that you've got this AI and you've told it maximize the long term what is long term mean does long term mean until the sun burns out that's that's not gonna work and you know does long term mean next thousand years ok they're probably optimizations for the next thousand years that it's like it's like if you're running a company you can make a company be very stable for a certain period of time like if you know if your company gets bought by some you know private investment group then they'll you know you can you can run a company just fine for five years by just taking what it does and you know removing all R&D and the company will burn out after a while but it'll run just fine for a while so if you tell the AI keep the humans okay for a thousand years there's probably a certain set of things that one would do to optimize that many of which one might say well that would be a pretty big shame for the future of history so to speak for that to be what happens but I think I think in the end you know as you start thinking about that question it is what you realize is there's a whole sort of raft of undecidability computational irreducibility in other words it's I mean one of the good things about sort of the the the what our civilization has gone through and what sort of we humans go through is that there's a certain computational irreducibility to it in the sense that it isn't the case you can look from the outside and just say the answer is going to be this at the end of the day this is what's gonna happen you actually have to go through the process to find out and I think that's um that's both that feels better in the sense it's not a you know something is achieved by going through all of this all of this process and it's but it also means that telling the a I go figure out you know what will be the best outcome well unfortunately it's going to come back and say it's kind of undecidable what to do we'd have to run all of those scenarios to see what happens and if we want it for the infinite future we're throwing immediately into a sort of standard issues of of kind of infinite computation and so on so yeah even if you get that the answer to the universe and everything is 42 you still have to actually run the universe yes yes like the question I guess or the the you know the the journey is the point right well I think it's saying to summarize this is the result of the universe yeah that's if that is possible it tells us I mean the whole sort of structure of thinking about computation and so on and thinking about how stuff works if if there if it's possible to say and the answer is such-and-such you're basically saying there's a way of going outside the universe and you're kind of you're getting yourself into something of a sort of paradox because you're saying if it's knowable what the answer is then there's a way to know it that is beyond what the universe provides but if we can know it then something that we're dealing with is beyond the universe so then the universe isn't the universe so to speak so and in general as we'll talk about at least for small human brains it's hard to show that the result of a sufficiently complex computation it's hard I mean it's probably impossible right and there's a side ability so and the universe appears by at least the poets to be sufficiently complex they won't be able to predict what the heck it's all going to well we better not be able to because if we can kind of denies I mean it's you know we're part of the universe yeah so what does it mean for us to predict it means that we that our little part of the universe is able to jump ahead of the whole universe and you know this this quickly winds up I mean that there it is conceivable the only way we'd be able to predict is if we are so special in the universe we are the one place where there is computation more special more sophisticated than anything else that exists in the universe that's the only way we would have the ability to sort of the almost theological ability so to speak to predict what happens in the universe is to say somehow we're we're better than everything else in the universe which I don't think is the case yeah perhaps we can detect a large number of looping patterns that reoccur throughout the universe and fully describe them and therefore but then it's it still becomes exceptionally difficult to see how those patterns interact and what kind of well look the most remarkable thing about the universe is that it has regularity at all might not be the case if you don't have regularity absolutely therefore it's full of I mean physics is successful you know it's full of of laws that tell us a lot of detail about how the universe works I mean it could be the case that you know the 10 to the 90th particles in the universe they will do their own thing but they don't they all followed we already know they all follow basically physical the same physical laws and that's something that's a very profound fact about the universe what conclusion you draw from that is unclear I mean in the you know the early early theologians that was you know exhibit number one for the existence of God now you know people have different conclusions about it but the fact is you know right now I mean I happen to be interested actually I've just restarted a long-running kind of interest of mine about fundamental physics I'm kind of like come on I'm on a bit of a quest which I'm about to make more public of to to see if I can actually find the fundamental theory of physics excellence we'll come to that and I just had a lot of conversation with quantum mechanics folks with so I'm really excited on your take because I think you have a fascinating take on the the the fundamental notch in nature of our reality from a physics perspective so and what might be underlying the kind of physics as we think of it today okay let's take a step back what is computation it's a good question operationally computation is following rules that's kind of it I mean computation is the result is the process of systematically following rules and it is the thing that happens when you do that for taking initial conditions are taking inputs and following rules I mean what are you following rules on so there has to be some data some not necessarily it can be something where that there's a you know very simple input and then you're following these rules and you'd say there's not really much data going into this it's you could actually pack the initial conditions into the rule if you want to um so I think the the question is is there a robust notion of computation that is what is this last mean what I mean by that is something like this so so one of the things that are different in an earlier physics something like energy okay the different forms of energy there's but somehow energy is the robust concept that doesn't isn't particular to kinetic energy or you know nuclear energy or whatever else there's a robust idea of energy so only things you might ask is there's the robust idea of computation or does it matter that this computation is running in a Turing machine this computation is running in as you know CMOS Salkin CPU this computation is running in a fluid system in the whether those kinds of things or is there a robust idea of computation that transcends the sort of detailed framework that it's running in okay and is that her yes I mean it wasn't obvious that there was so it's worth understanding the history and how we got to where we are right now because you know to say that there is is a statement in part about our universe it's not a statement about what is mathematically conceivable it's about what actually can exist for us maybe you can also comment because energy as a concept is robust but there's also its intricate complicated relationship with matter with mass is very interesting of particles that carry force and particles that sort of particles that carry forcing particles that have mass these kinds of ideas they seem to map to each other at least in the mathematical sense is there a connection between energy and mass and computation or are these completely disjoint ideas we don't know yet the things that I'm trying to do about fundamental physics may well lead to such a connection but there is no known connection at this time so key can you elaborate a little bit more on what how do you think about computation what is company yeah so I mean let's let's tell a little bit of a historical story yes okay so you know back go back 150 years people were making mechanical calculators of various kinds and you know the typical thing was do you want an adding machine you go to the adding machine store basically he wants a multiplying machine you go to the multiplying machine store that different pieces of hardware and so that means that at least at the level of that kind of computation and those kinds of pieces of hardware there isn't a robust notion of computation there's the adding machine kind of computation there's the multiplying machine notion of computation and they're disjoint so what happened in around 1900 people started imagining particularly in the contests of mathematical logic could you have something which would be represent any reasonable function right and they came up with things this idea of primitive recursion was one of the early ideas and it didn't work there were reasonable functions that people who come up with that were not represented using the primitive as a primitive recursion okay so then then along comes 1931 and girdle's theorem and so on and as in looking back one can see that as part of the process of establishing girdles theorem girdle basically showed how you could compile arithmetic you could basically compile logical statements like this statement is unprovable into arithmetic so what he essentially did was to show that arithmetic can be a computer in a sense that's capable of representing all kinds of other things and then Turing came along 1936 came up with Turing machines meanwhile Alonzo Church had come up with lambda calculus and the surprising thing that was established very quickly is the Turing machine idea about what might be what computation might be is exactly the same as the lambda calculus idea of what computation might be and so and then there started to be other ideas you know register machines other kinds of other kinds of representations of computation and the big surprise was they all turned out to be equivalent so in other words it might have been the case like those old adding machines and multiplying machines that you know Turing had his idea of computation church had his idea of computation and they were just different but it isn't true there are actually all equivalent so then by I would say the the 1970s or so in in sort of the computation computer science computation theory area people had sort of said Oh Turing machines are kind of what computation is physicists were still holding out saying no no no it's just not how the universe works we've got all these differential equations we've got all these real numbers that have infinite numbers of digits the universe is now a Turing machine right the you know the Turing machines are a small subset of that the things that we make in microprocessors and engineering structures and so on so probably actually through my work in the 1980s about sort of the relationship between computation and models of physics it became a little less clear that there would be that there was this big sort of dichotomy between what can happen in physics and what happens and things like Turing machines and I think probably by now people would mostly think and and by the way brains were another kind of elements this I mean you know girdle didn't think that his notion of computational what amounted to his notion of computation would cover brains and Turing wasn't sure either um but tell though he was a little bit he got to be a little bit more convinced that it should cover brains um but so you know but I would say by probably sometime in the 1980s there was beginning to be so a general belief that yes this notion of computation that could be captured by things like Turing machines was reasonably robust now the next question is ok you can have a universal Turing machine that's capable of being programmed to do anything that any Turing machine can do um and you know this idea of universal computation it's an important idea this idea that you can have one piece of hardware and program it with different pieces of software you know that's kind of the idea that launched most modern technology I mean that's kind of that that's the idea that launched computer revolution software etc so important idea but but the thing that's still kind of holding out from that idea is ok there is this Universal computation thing but seems hard to get to it seems like you want to make a universal computer you have to kind of have a microprocessor with you know a million gates in it and you have to go to a lot of trouble to make something that achieves that level of computational sophistication ok so the surprise for me was that stuff that I discovered in the early 80s I'm looking at these things called cellular automata which are really simple computational systems the thing that was a big surprise to me was that even when their rules were very very simple they were doing things that were as sophisticated as they did even when their rules much more complicated so it didn't look like you know this idea Oh to get sophisticated computation you have to build something with very sophisticated rules that idea didn't seem to pan out and instead it seemed to be the case that sophisticated computation was completely ubiquitous even in systems with incredibly simple rules and so that led to this thing that I call the principle of computational equivalence which basically says when you have a system that follows rules of any kind then whenever the system isn't doing things that are in some sense obviously simple then the computation that the behavior of the system corresponds to is of equivalent sophistication so that means that when you kind of go from the very very very simplest things you can imagine then quite quickly you hit this kind of threshold above which everything is equivalent in its computational sophistication not obvious that would be the case I mean that's a science fact well then hold on a second you saw this you've opened with a new kind of science I mean I remember it was a huge eye-opener that's such simple things can create such complexity and yes there's an equivalence but it's not a fact it just appears to I mean it's as much as a fact as sort of these theories are so elegant that it it seems to be the way things are but let me ask sort of you just brought up previously kind of like the communities of computer scientists with their touring machines the physicists will their universe and the whoever the heck maybe neuroscientists looking at the brain what's your sense in the equivalence you've shown through your work that simple rules can create equivalently complex touring machine systems right is the universe equivalent to the kinds of tutorial machines is the human brain a kind of toy machine do you see those things basically blending together or is there still a mystery about how disjoint they're well my guess is that they will blend together but we don't know that for sure yet I mean this I you know I should say I I said rather glibly that the principle of computational equivalence is sort of a science fact and this I was using half was yes efforts for the for the for the science fact because when you it is a I mean just to talk about that for a second and most people will um the thing is that it is it has a complicated epistemological character similar to things like the second law of thermodynamics law of entropy increase the you know what is the second law of thermodynamics it is is it a law of nature is that a thing that is true of the physical world is it is it something which is mathematically provable is it something which happens to be true of the systems that we see in the world is it in some sense a definition of heat perhaps well it's a combination of those things and it's the same thing with the principle of computational equivalence and in some sense the principle of computational equivalence is at the heart of the definition of computation because it's telling you there is a thing there is a robust notion that is equivalent across all these systems and doesn't depend on the details of each individual system and that's why we can meaningfully talk about a thing called computation and we're not stuck talking about over there's computation in trillion machine number 378 5 and etc etc etc that's that's why there is a robust notion like that now on the other hand can we prove the principle of computational equivalence can we can we prove it as a mathematical result well the answer is actually we've got some nice results along those lines that say you know throw me a random system with very simple rules well in a couple of cases we now know that even the very simplest rules we can imagine of a certain type are universal and do sort of follow what you would expect from the principle of computational equivalence so that's a nice piece of sort of mathematical evidence for the principle of computational equivalence did you still enjoy on that point the simple rules creating sort of these complex behaviors but is there a way to mathematically say that this behavior is complex that you've mentioned you cross a threshold right is the various indicators so for example one thing would be is it capable of universal computation that is given the system do there exist initial conditions for the system that can be set up to essentially represent programs to do anything you to compute primes to compute pi to do whatever he wants right so that's an indicator so we know in a couple of examples that yes the simplest candidates that could conceivably have that property do have that property and that's what the principle of computational equivalence might suggest but this principle of computational equivalence one question about it is is it true for the physical world right it might be true for all these things we come up with the Turing machines the cellular automata whatever else is it true for our actual physical world is it true for the Bray brains which are an element of the physical world we don't know for sure and that's not the type of question that we will have a definitive answer to because it's you know it's a it's a there's a there's a sort of scientific induction issue you can say what's true for all these brains but this person over here is really special and it's not true for them and you can't you know the the the only way that that cannot be what happens is if we finally nail it and actually get a fundamental theory for physics and it turns out to correspond to let's say a simple program if that is the case then we will basically have reduced physics to a branch of mathematics in a sense that we will not be you know right now with physics we're like well this is the theory that you know this is the rules that apply here but in the middle of that you know you know right by that black hole maybe these rules don't apply and something else applies and there may be another piece of the onion that we have to peel back but as if if we can get to the point where we actually have this is the fundamental theory of physics here it is it's this program run this program and you will get our universe then we've kind of reduced the problem of figuring out things in physics to a problem of doing some what turns out to be very difficult irreducibly difficult mathematical problems but it no longer is the case that we can say that somebody can come in and say whoops you know you were right about all these things about Turing machines but you're wrong about the physical universe we know there's sort of ground truth about what's happening the physical universe now I happen to think I mean you asked me at an interesting time because I'm just in the middle of starting to re-energized my my project to kind of study the fundamental theory of physics as of today I'm very optimistic that we're actually going to find something and that it's going to be possible to to see that the universe really is computational in that sense but I don't know because we're betting against you know we're betting against the universe sort of speaking I didn't you know it's not like you know when I spend a lot of my life building technology and then I know what what's in there right and it's there maybe it may have unexpected behavior may have bugs things like that but fundamentally I know what's in there for the universe I'm not in that position so to speak what kind of computation do you think the fundamental laws of physics might emerge from so just to clarify so there's you've you've done a lot of fascinating work with kind of discrete kinds of computation that you know use cellular automata and we'll talk about it have this very clean structure it's such a nice way to demonstrate that simple rules can create immense complexity but what you know is that actually our cellular time is sufficiently general to describe the kinds of computation that might create the laws of physics just to give it can you give a sense of what kind of computation do you think would create well so so this is a slightly complicated issue because as soon as you have universal computation you can in principle simulate anything with anything but it is not a natural thing to do and if you're asking will you to try to find our physical universe by looking at possible programs in the computational universe of all possible programs would the ones that correspond to our universe be small and simple enough that we might find them by searching that computational universe we got to have the right basis so to speak we have to have the right language in effect for describing computation for that to be feasible so the thing that I've been interested in for a long time is what are the most structureless structures that we can create with computation so in other words if you say a cellular automaton as a bunch of cells they're arrayed on a grid and it's very you know an every cell is updated in synchrony at the sir at a particular you know when there's a there's a click of a clock sort of speaking it goes a tick of a clock and that every cell gets updated at the same time that's a very specific very rigid kind of thing but my guess is that when we look at physics and we look at things like space and time that what's underneath space and time is something as structureless as possible that what we see what emerges for us as physical space for example comes from something that is sort of arbitrarily unstructured underneath and so I've been for a long time interested in kind of what what are the most structureless structures that we can set up and actually what I had thought about for ages is using graphs networks where essentially so they'll throw that space for example so what is space the kind of a question one might ask back in the early days of quantum mechanics for example people said oh for sure space is going to be discrete because all these other things were finding a discrete but that never worked out in physics and so space and physics today is always treated as this continuous thing just like Euclid imagined it I mean the the very first thing you chlid says and his sort of common notions is you know a point is something which has no part in other words there are there are points that are arbitrarily small and there's a continuum of possible positions of points and the question is is that true and so for example if we look at I don't know fluid like air or water we might say oh it's a continuous fluid we can pour it we can do all kinds of things continuously but actually we know because we know the physics of it that it consists of a bunch of discrete molecules bouncing around and only in the aggregate is it behaving like a continuum and so the possibility exists that that's true of space too people haven't managed to make that work with existing frameworks and physics but I've been interested in whether one can imagine that underneath space and also underneath time is something more structureless and the question is is it computational so there are couple possibilities it could be computational somehow fundamentally equivalent to a Turing machine or it could be fundamentally not so how could it not be it could not be so machine essentially deals with integers whole numbers some level and you know it can do things like it can add one to a number it can do things like this you can also store whatever the heck it did yes it has an infinite storage the storage but what temp when one thinks about doing physics or sort of idealized physics or idealized mathematics one can deal with real numbers numbers with an infinite number of digits numbers which are absolutely precise someone can say we can take this number and we can multiply it by itself are you comfortable with infinity in this context are you gone very well in a context of computation do you think infinity and plays a part I think that the role infinity is complicated infinity is useful in conceptualizing things it's not actual izybelle almost by definition it's not actual I zabit do you think infinity is part of the thing that might underlie the laws of physics I think that um no I think there are many questions that you asked about you might ask about physics which inevitably involve infinity like when you say you know is faster-than-light travel possible you could say with it with with it we're given the laws of physics can you make something even arbitrarily large even quotes infinitely large that you know that will make faster-than-light travel possible then you you're thrown into dealing with infinity as a kind of theoretical question but I mean talking about you know sort of what's underneath space and time and what how one can make you know a computational infrastructure one possibility is that you can't make a computational infrastructure and Turing such in sense that you really have to be dealing with precise real numbers you're dealing with partial differential equations which just have precise real numbers that arbitrarily closely separated points you have a continuum forever thing could be that that that's what happens that there's sort of a continuum for everything and precise real numbers for everything and then the things I'm thinking about are wrong and you know that's that's the risk you take if you're you know if you're trying to sort of do things about nature is you might just be wrong it's not it's for me personally it's kind of strange things I've spent a lot of my life building technology where you can do something that nobody cares about but you can't be sort of wrong in that sense and the sense you build your technology and it does what it does but but I think you know this question of what you know what the sort of underlying computational infrastructure for the universe might be um it's so it's sort of inevitable it's gonna be fairly abstract because if you're gonna get all these things like there are three dimensions of space there are electrons there are muons there are quarks there are this you don't get to if the if the model for the universe is simple you don't get to have sort of a line of code for each of those things you don't get to have sort of the the the muon case the Tau lepton case and so on or as they're all have to be emergent some right so something deeper right so so that means it's sort of inevitable that's a little hard to talk about what the sort of underlying structural is structure actually is do you think our human beings have the cognitive capacity to understand if we're to discover it to understand the kinds of simple structure from which these laws can emerge like do you think that's a good class pursuit well here's what I think I think that I mean I'm right in the middle of this right now I'm telling you that I think you this one yeah I mean this human has a hard time understanding it you know a bunch of the things that are going on but but what happens in understanding is one builds waypoints I mean if you said understand modern 21st century mathematics starting from you know counting back in you know whenever counting was invented 50,000 years ago whenever it was right there's that will be really difficult but what happens is we build waypoints that allow us to get to higher levels of understanding and we see the same thing happening in language you know when we invent a word for something it provides kind of a cognitive anchor a kind of a waypoints that lets us you know like a podcast or something you could be explaining well it's a thing which this works this way that way the other way but as soon as you have the word podcast and people kind of societally understand it you start to be able to build on top of that and so I think and that that's kind of the story of science actually - I mean science is about building these kind of waypoints where we find this sort of cognitive mechanism for understanding something then we can build on top of it you know we we have the idea of I don't know differential equations we can build on top of that we have this idea of that idea so my hope is that if it is the case that we have to go all the way sort of from the sand to the computer and there's no way points in between then we're toast we won't be able to do that well eventually we might so for if we're as clever apes are good enough a building those abstract abstractions eventually from sanh we'll get to the computer a and it just might be a longer journey the question is whether it is something that you asked whether our human brains yes well on will quotes understand what's going on and that's a different question because for that it requires steps that are for whether it is sort of from which we can construct a human understandable narrative and that's something that I think I am somewhat hopeful that that will be possible although you know as of literally today if you ask me I'm confronted with things that I don't understand very well um and so this is a small pattern in a computation trying to understand the rules under which the computation functions and yeah it's it's an interesting possibility under which kinds of computations such a creature can understand itself my guess is that within so we didn't talk much about computational irreducibility but it's a consequence of this principle of computational equivalence and it's sort of a core idea that that one has to understand I think which is question is you're doing a computation you can figure out what happens in the computation just by running every step in the computation and seeing what happens or you can say let me jump ahead and figure out you know have something smarter that figures out what's gonna happen before it actually happens and a lot of traditional science has been about that act of computational reduce ability it's like we've got these equations and we can just solve them or we can figure out what's going to happen we don't have to trace all of those steps we just jump ahead because we've solved these equations okay so one of the things that is a consequence of the principle of computational equivalence is you don't always get to do that many many systems will be computationally irreducible in the sense that the only way to find out what they do is just follow each step and see what happens why is that well if you have if you're saying well we with our brains will are smarter we we don't have to mess around like the little cellular automata and going through and updating all those cells we can just you know use the power of our brains to jump ahead but if the principle of computational occurrence is right that's not going to be correct because it means that there's us during our computation in our brains there's a little cellular automaton doing its computation and the principle of computational current says these two computations are fundamentally equivalent so that means we don't get to say we're a lot smarter than the cellular automaton and jump ahead because we're just doing computation that's of the same sophistication as the cellular automaton itself that's computation or disability it's fascinating but the and that's a really powerful idea I think that's both depressing and humbling and so on that were all we in a cellular automata are the same but the question we're talking about the fundamental laws of physics is kind of the reverse question you're not predicting what's gonna happen you have to run the universe for that but saying can I understand what rules likely generated me I understand but the problem is to know whether you're right you have to have some computational reduce ability because we are embedded in the universe if the only way to know whether we get the universe is just to run the universe we don't get to do that because it just ran for fourteen point six billion years or whatever and we don't you know we can't rerun it so to speak so we have to hope that there are pockets of computational reducibility sufficient to be able to say yes I can recognize those or electrons there and and and I think that it is a it's a feature of computational irreducibility it's sort of a mathematical feature that there are always an infinite collection of pockets of reduced ability the question of whether they land in the right place and whether we can sort of build the theory based on them is unclear but to this point about you know whether we as observers in the universe built out of the same stuff as the universe can figure out the universe so to speak that relies on these pockets of reducibility without the pockets of reducibility it's won't work work but I think this question about how observers operate it's one of the features of science over the last hundred years particularly has been that every time we get more realistic about observers we learn a bit more about science so for example relativity was all about observers don't get to say when you know what's simultaneous with what they have to just wait for the light signal to arrive to decide what simultaneous or for example in thermodynamics observers don't get to say the position of every single molecule and a gas they can only see the kind of large scale features and that's why the second law of thermodynamics law of entropy increased and so on works if you could see every individual molecule you wouldn't conclude something about thermodynamics you would conclude oh these molecules just all doing these particular things you wouldn't be able to see this aggregate fact so I strongly expect that in fact him the theories that I have the one has to be more realistic about the computation and other aspects of observers in order to actually make a correspondence between what we experience in fact they have a my little team and I have a little theory right now about how quantum mechanics may work which is a very wonderfully bizarre idea about how a sort of thread of human consciousness relates to what we observe in the universe but this is the several steps to explain what that's about woody meek of the mess of the observer at the lower level of quantum mechanics sort of the textbook definition with quantum mechanics kind of says that there's some there's two worlds one is the world that actually is and the other is that's observed do ya what do you make sense of well I think actually the ideas we've recently had might actually give away into this and that's I don't know yet I mean it's I think that's it's a mess I mean the fact is there is a one of the things that's interesting and when you know people look at these models that I started talking about 30 years ago now they say oh no that can't possibly be right you know what about quantum mechanics right you say okay tell me what is the essence of quantum mechanics what do you want me to be able to reproduce to know that I've got quantum mechanics so to speak well and that question comes up it comes up very operationally actually because we've been doing a bunch of stuff with quantum computing and there are all these companies that say we have a quantum computer and we say let's connect to your API and let's actually run it and they're like well maybe you shouldn't do that yet we're not quite ready yet and one of the questions that I've been curious about is if I have five minutes with a quantum computer how can I tell if it's really a quantum computer or whether it's a simulator at the other end right and turns out it's really hard it turns out there isn't it's it's it's like a lot of these questions about sort of what is intelligence what's life it's soaring tears for quantum computing that's right that's right it's like are you really a quantum computer and I mean I think simulation the yes exactly is it just a simulation or is it really a quantum computer famous you're all over again but but that so you know this this whole issue about the sort of mathematical structure of quantum mechanics and the completely separate thing that is our experience in which we think definite things happen but as quantum mechanics doesn't say definite things ever happen quantum mechanics is all about the amplitudes for different things to happen but yet our thread of consciousness operates as if definite things are happening but to linger on the point you've kind of mentioned the structure that could underlie everything in this idea that it could perhaps have something like a structure of a graph can you elaborate why your intuition is that there's a graph structure of nodes and edges and what it might represent right okay so the question is what is in a sense the most structureless structure you can imagine right so and in fact what I've recently realized in the last year or so I have a new most structureless structure by the way the question itself is a beautiful and a powerful one in itself so even without an answer just the question is strong question right right well what's your new idea well it has to do with hypergraphs essentially what what is interesting about the sort of ID model I have now is it's a little bit like what happened with computation everything that I think of as oh well maybe the model is this I discover its equivalent and that's quite encouraging because it's like I could say well I'm gonna look at trivalent graph the graphs with you know three edges for each node and so on or I could look at this special kind of graph or I could look at this kind of algebraic structure and turns out that the things I'm now looking at everything that I've imagined that is a plausible type of structuralist structure is equivalent to this so what is it well a typical way to think about it is well so you might have some some collection of tuples collection of let's say numbers so you might have one three five two three four little just collections of numbers triples of numbers let's say quadruples of numbers pairs of numbers whatever and you have all these sort of floating little tuples they're not in any particular order and that sort of floating collection of tuples and I told you this was abstract represents the whole universe the only thing that relates them is when a symbol is the same it's the same so to speak so if you have two tuples and they contain the same symbol let's say at the same position of the tuple of the first element of the tuple then that's represents a relation okay so let me let me try and peel this back Wow okay it's it's I told you it's abstract but this is this is the this is so the relationship is formed by the same some aspect of sameness right but but so think about it in terms of a graph yeah so a graph a bunch of nodes let's say you number each node okay then what is a graph a graph is a set of pairs that say this node has an edge connecting it to this other node so that's the that's an a graph is just a collection of those pairs that say this node connects to this other node so this is a generalization of that in which instead of having pairs you have arbitrary and tuples um that's it that's the whole story um and now the question is okay so that might be that might represent the state of the universe how does the universe evolved what does the end of us do and so the answer is that what I'm looking at is transformation rules on these hyper graphs in other words you say this whenever you see a a piece of this hyper graph that looks like this turn it into a piece of hyper graph that looks like this so on a graph it might be when you see the sub graph when you see this thing with a bunch of edges hanging out in this particular way then rewrite it as this other graph mm-hm okay and so that's the whole story so the question is what so now you say I mean think as I say this is quite abstract and one of the questions is where do you do those updating so you've got this giant graph what triggers outdating like what's the what's the ripple effect of it is it yeah and I I suspect everything's discrete even in time so okay so the question is where do you do the updates yes and the answer is the rule is you do them wherever they apply and you do them you do them the order in which the updates is done is not defined that is the you can do them so there may be many possible orderings for these updates now the point is if imagine you're an observer in this universe so and you say did something get updated well you don't in any sense know until you yourself have been updated right so in fact all that you can be sensitive to is essentially the causal network of how an event over there affects an event that's in you it doesn't even feel like observation that's like that's something else you're just part of the whole thing yes you're part of it but but even to have so the the end result of that is you're sensitive to is this causal network of what event effects what other event I'm not making a big statement about sort of the structure of the observer I'm simply saying I'm simply making the argument that what happens the microscopic order of these rewrites is not something that any observer any conceivable observer in this universe can be affected by because the the only thing the observer can be affected by is this causal network of how the events in the observer are affected by other events that happen in the universe so the only thing you have to look at is the causal network you don't really have to look at this microscopic rewriting that's happening so these rewrites are happening wherever they they were they happen wherever they feel like causal network is there you said that there's not really so the idea would be an undefined like what gets updated the the sequence of things is undefined it's a yes that's what you mean by the causal network then the cop no the causal network is given that an update has happened that's an event then the question is is that event causally related to does that event if that event didn't happen then some future event couldn't happen yet gotcha and so you build up this network of what effects what okay and so what that does so when you build up that network that's kind of the observable aspect of the universe in some sense yeah um and so then you can ask questions about you know how robust is that observable ass network of the what's happening in the universe okay so here's where it starts getting kind of interesting so for certain kinds of microscopic rewriting rules the order of rewrites does not matter to the causal network and so this is okay mathematical logic moment this is equivalent to the church-rosser property of a confluence property of rewrite rules and it's the same reason that if you are simplifying an algebraic expression for example you can say oh let me expand those terms out let me factor those pieces doesn't matter what order you do that in you'll always get the same answer and that's it's the same fundamental phenomenon that causes for certain kinds of microscopic rewrite that causes the causal network to be independent of the microscopic order of rewritings why is there properly important because it implies special relativity I mean the reason what the reason it's important is that that property special relativity says you can look at these sort of you can look at different reference frames you can have different you can be looking at your notion of what space and what's time can be different depending on whether you're traveling at a certain speed depending on whether you're doing this that and the other but nevertheless the laws of physics are the same that's what the principle special relativity says there's the laws of physics are the same independent of your reference frame well turns out this sort of change of the microscopic rewriting order is essentially equivalent to a change of reference frame or at least there's a sub part of how that works that's a call interchange a reference frame so somewhat surprisingly and sort of for the first time and forever it's possible for an underlying microscopic theory to imply special relativity to be able to derive it it's not something you put in as a this is a it's something where this other property causal invariance which is also the property that implies that there's a single thread of time in the universe it might not be the case that that's that is the that's what would lead to the possibility of an observer thinking that definite stuff happens otherwise you've got all these possible rewriting orders and who's to say which one occurred but with this causal invariance property there's a there's a notion of a definite threat of time it sounds like that kind of idea of time even space would be emergent from the system oh yeah no it's not a fundamental part of the fundamental level all you've got is a bunch of nodes connected by hyper edges or whatever so there's no time there's not space that's right and but but the the thing is that it's just like imagining imagine you're just dealing with a graph and imagine you have something like a you know like a honeycomb graph we have a hexagon bunch a hexagon you know that graph at a microscopic level is just a bunch of nodes connected to other nodes but at a microscopic level you say that looks like a honeycomb you know it's lattice it looks like a two-dimensional you know manifold of some kind it looks like a two-dimensional thing if you connect it differently if you just connect all the nodes one one to another and kind of a sort of linked list type structure then you'd say well that looks like a one-dimensional space but at the microscopic level all these are just networks with nodes the macroscopic level they look like something that's like one of our sort of familiar kinds of space and it's the same thing with these hyper graphs now if you ask me have I found one that gives me three dimensional space the answer is not yet so we don't know this is one of these things we're kind of betting against nature so to speak and I have no way to know I mean so there are many other properties of this this kind of system that have are very beautiful actually and very suggestive and it will be very elegant if this turns out to be right because it's very it's very clean and you start with nothing and everything gets built up everything about space everything about time everything about matter it's all just emergent from the properties of this extremely low-level system and that that will be pretty cool if that's the way our universe works now do I on the other hand the thing that that I find very confusing is let's say we succeed let's say we can say this particular sort of hyper graph rewriting rule gives the universe just run that hyper graph rewriting rule for enough times and you'll get everything you'll get this conversation we're having will you'll get everything it's that um if we get to that point and we look at what is this thing what is this rule that we just have that is giving us our whole universe how do we think about that thing let's say turns out the minimal version of this and this is kind of cool thing for a language designer like me the the minimal version of this model is actually a single line of orphan language code so that's I wasn't sure is going to happen that way but it's it's a that's um it's kind of now we don't know what we don't know what that's that's just the framework to know the actual particular hypergraph that might be a longer that the specification of the rules might be slightly like how does help you except marveling in the beauty and the elegance of the simplicity that creates the universe that does that help us predict anything not really because of the irreducibility that's correct that's correct but so the thing that is really strange to me and I haven't wrapped my my brain around this yet is you know one is one keeps on realizing that we're not special in the sense that you know we don't live at the center of the universe we don't blah blah blah and yet if we produce a rule for the universe and it's quite simple and we can write it down and a couple of lines or something that feels very special how do we come to get a simple universe when many of the available universes so to speak are incredibly complicated might be you know a quintillion characters long why did we get one of the ones that's simple and so I haven't wrapped my brain around that asou yet if indeed we are in such a simple way the universe is such a simple rule is it possible that there is something outside of this that we are in a kind of what people calls to the simulation right the word just part of a computation is being explored by a graduate student in alternate universe well you know the problem is we don't get to say much about what's outside our universe because by definition our universe is what we exist within yeah now can we make a sort of almost theological conclusion from being able to know how our particular universe works interesting question I don't think that if you ask the question could we and it relates again to this question about the extraterrestrial intelligence you know we've got the rule for the universe was it built in on purpose hard to say that's the same thing as saying we see a signal from you know that we're you know receiving from some you know random star somewhere and it's a series of pulses and you know it's a periodic series of pulses let's say was that done on purpose can we conclude something about the origin of that series of pulses just because it's elegant does not necessarily mean that somebody created it or though can even comprehend yeah well yeah I think it's it's the ultimate version of the sort of identification of the techno signature question it's the ultimate version of that is was our universe a piece of technology so to speak and how on earth would we know because but I mean it'll be it's some I mean you know in the kind of crazy science fiction thing you could imagine you could say Oh somebody's going to have them you know that's gonna be a signature there it's gonna be you know made by so-and-so but there's no way we could understand that sort of speaking it's not clear what that would mean because the universe simply you know this if we find a rule for the universe we're not we're simply saying that rule represents what our universe does we're not saying that that rule is something running on a big computer and making our universe it's just saying that represents what our universe does in the same sense that you know laws of classical mechanics differential equations whatever they are represent what mechanical systems do it's not that the mechanical systems are somehow running solutions to those differential equations those differential equations just representing the behavior of those systems so what's the gap in your sense to linger and the fascinating perhaps slightly sci-fi a question what's the gap between understanding the fundamental rules that create a universe and engineering a system actually creating a simulation ourselves so you've talked about sort of you've talked about you know nano engineering kind of ideas that are kind of exciting actually creating some ideas of computation in the physical space how hard it is is it as an engineering problem to create the universe once you know the rules the Creator and well it's an interesting question I think the substrate on which the universe is operating is not a substrate that we have access to I mean the only substrate we have is that same substrate that the universe is operating in so if the universe is a bunch of hypergraphs being rewritten then we get to attach ourselves to those same hypergraphs being rewritten we don't get to and if you ask the question you know is the code clean you know is you know can we write nice elegant code with efficient algorithms and so on well that's an interesting question how how you know that's this question of how much computational reducibility there is in the system but so I've seen some beautiful cellular automata that basically create copies of itself within itself right that's the question whether it's possible to create like whether you need to understand the substrate or whether you can just yeah well right I mean so one of the things that is sort of one of my slightly sci-fi thoughts about the future so to speak is you know right now if you pol typical people who say do you think it's important to find the fundamental theory of physics you get because I've done this poll informally at least it's curious actually you get a decent fraction of people saying oh yeah that would be pretty interesting I think that's becoming surprisingly enough more I mean a lot of people are interested in physics in a way that like without understanding it just kind of watching scientists a very small number of them struggle to understand the nature of our reality right mean I I mean I I think that's somewhat true and in fact in this project that I'm launching into to try and find in fundamental theory of physics I'm going to do it as a very public project I mean it's gonna be live streamed and all this kind of stuff and I don't know what will happen it'll be kind of fun I mean I think that it's the interface to the world of this project I mean I I figure one feature of this project is you know unlike technology projects that basically are what they are this is a project that might simply fail because it might be the case that generates all kinds of elegant mathematics that has absolutely nothing to do with the physical universe that we happen to live in well okay so we're talking about kind of the quest to find the fundamental theory physics first point is you know it's turned out it's kind of hard to find the fundamental theory physics people weren't sure that that would be the case back in the early days of applying mathematics to science 1600s and so on people were like oh and a hundred years we'll know everything there is to know about how the universe works turned out to be harder than that and people got kind of humble at some level because every time we got to a sort of a greater level of smallness and universe it seemed like the math got more complicated and everything got got harder the you know when I when I was a kid basically I started doing particle physics and you know what I was doing particle physics I always thought finding the fundamental fundamental theory of physics that's a kooky business we'll never be able to do that um but we can operate within these frameworks that we built for doing quantum field theory and general relativity and things like this and it's all good and we can figure out a lot of stuff did you even at that time have a sense that there's something behind that sure I just didn't expect that I thought in some rather on it's actually kind of crazy and thinking back on it because it's kind of like there was this long period in civilization where people thought the ancients had it all figured out and we'll never figure out oh nothing new and to some extent that's the way I felt about physics when I was in the middle of doing it so to speak and was you know we've got quantum field theory it's the foundation of what we're doing and there's you know yes there's probably something underneath this but we'll sort of never figure it out but then I started studying simple programs and the computational universe things like solar automata and so on and I discovered that there so they do all kinds of things that were completely at odds with the intuition that I had had and so after that after you see this tiny little program that does all this amazingly complicated stuff then you start feeling a bit more ambitious about physics and saying maybe we could do this for physics too and so that's some that got me started years ago now and this kind of idea of could we actually find what's underneath all of these frameworks like one a field theory in jorts everything's on and people perhaps don't realize as slow as they might that you know the frameworks we're using for physics which is basically these two things quantum field theory the sort of the theory of small stuff and general relativity theory of gravitation and large stuff those are the two basic theories and they're 100 years old I mean general relativity was 1915 quantum field theory well 1920s I'm basically a hundred years old and they've they've it's been a good run there's a lot of stuff been figured out but what's interesting is the foundations haven't changed in all that period of time even though the foundations had changed several times before that in the two hundred years earlier than that um and I think the kinds of things that I'm thinking about which is sort of really informed by thinking about computation in the computational universe it's a different foundation it's a different set of foundations and might be wrong but it is at least you know we have a shot and I think it's you know to me it's you know my personal calculation for myself is is you know if it turns out that the finding the fundamental theory of physics it's kind of low-hanging fruit so to speak it'd be a shame if we just didn't think to do it you know if people just said oh you'll never figure that stuff out let's you know and it takes another two hundred years before anybody gets around to doing it um you know I think it's I don't know how low-hanging this fruit actually is it may be you know it may be that it's kind of the wrong century to do this project I mean I think the the the cautionary tale for me you know I think about things that I've tried to do in technology where people thought about doing them a lot earlier and my favorite example is probably live Nets who-who thought about making essentially encapsulating the world's knowledge in a computational form in the late 1600s and did a lot of things towards that and basically you know we finally managed to do this but he was three hundred years too early and that's the that's kind of the in terms of life planning it's kind of like avoid things that can't be done in your in your century so to speak yeah timing timing is everything you so you think if we kind of figure out the underlying rules that can create from which quantum field theory in general relativity can emerge do you think they'll help us unify it at that level of track we'll know it completely we'll know how that all fits together yes without a question and I mean it's already even the things I've already done they're a very you know it's very very elegant actual how things seem to be fitting together now you know is it right I don't know yet it's awfully suggestive if it isn't right it's some then the designer of the universe should feel embarrassed so to speak because it's a really good way to do that in your intuition in terms of design universe does God play dice is there is there randomness in this thing or is it deterministic so the kind of guy that's a little bit of a complicated question because when you're dealing with these things that involve these rewrites that have okay even randomness is an emergent phenomenon perhaps yes I mean it's a yeah well randomness in in many of these systems pseudo randomness and randomness are hard to distinguish um in this particular case the current idea that we have about some measurement in quantum mechanics is something very bizarre and very abstract and I don't think I can yet explain it without kind of yakking about very technical things eventually I will be able to but if that's if that's right it's kind of a it's a weird thing because it slices between determinism and randomness in a weird way that hasn't been sliced before so to speak so like many of these questions that come up in science where it's like is that this or is it that turns out the real answer is it's neither of those things it's something kind of different and sort of orthogonal to those those those categories and so that's the current you know this week's idea about how that might work um but you know we'll we'll see how that term unfolds I mean there's there's this question about a field like physics and sort of the quest for a fundamental theory and so on and there's both the science of what happens and there's the the sort of the social aspect of what happens because you know in a field that is basically as old as physics we're at I don't know what it is fourth generation I don't know fourth generation I don't know what generation it is of physicists and like I was one of these so to speak and for me the foundations were like the pyramids so to speak you know it was that way and it was always that way um it is difficult in an old field to go back to the foundations and would think about rewriting them it's a lot easier in young fields where you're still dealing with the first generation of people who invented the field and it tends to be the case you know that the nature of what happens in science tends to be you know you'll get there typically the pattern is some methodological advanced occurs and then there's a period of five years ten years maybe a little bit longer than that where there's lots of things that are now made possible whether by that methodological advance whether it's you know I don't know telescopes or whether that's some mathematical method or something it's you know there's a something something happens a tool gets built and then you can do a bunch of stuff and there's bunch of low-hanging fruit to be picked and that takes a certain amount of time after that all that low-hanging fruit is picked then it's a hard slog for the next however many decades or century or more to get to the next sort of level at which one can do something and it's kind of a a.m. and it tends to be the case that in fields that are in that kind of but I wouldn't say cruise mode because it's really hard work but it's very hard work for very incremental progress um and the in your career and some of the things you've taken on it feels like you're not you haven't been afraid of the hard slog the also true so it's quite interesting especially on the engineering on the engineering side and a small tangent when you were a Caltech did you get to interact with Richard five-minute ology aviemore he's very sure we we work together quite a bit actually in fact on and in fact both when I was at Caltech and after I left Caltech we were both consultants at this company called Thinking Machines Corporation which was just down the street from here actually um ultimately ill-fated company but um I used to say this company is not going to work with the strategy they have and dick Feynman always used to say what do we know about running companies just let them run their company but uh anyway I was there he was not into into that kind of thing and he always thought it was thought that my interest in doing things like running companies was a was a distraction so to speak um and for me it's a it's a mechanism to have a more effective machine for actually getting things figuring things out and getting things to happen did he think of it because essentially what you used you did with the company I don't know if you were thinking of it that way but you're creating tools to empower your to empower the exploration of the university do you think did he did he understand that point that the point of tools of I think not as well as he might have done I mean I think that but you know he was actually my first company which was also involved with well was involved with more mathematical computation kinds of things um you know he was quite - he had lots of advice about the technical side of what we should do and so on um giving examples and memories of thoughts that oh yeah yeah he had all kinds of lucky in in the business of doing sort of you know one of the hard things in math is doing integrals and so on right and so he had his own elaborate ways to do integrals and so on he had his own ways of thinking about sort of getting intuition about how math works and so his sort of meta idea was take those intuitional methods and make a computer follow those in traditional methods now it turns out for the most part like when we do integrals and things what we do is is we build this kind of bizarre industrial machine that turns every integral until you know products of Mayer G functions and generates this very elaborate thing and actually the big problem is turning the results into something a human will understand it's not quotes doing the integral and actually Fineman did understand that to some extent and I I am embarrassed to say he once gave me this big pile of you know calculational methods for particle physics that he worked out in the 50s and he said you know it's more used to you than to me type thing and I I was like I were intended to look at it and give it back and I store my files now so it's but that's what happens when when it's finiteness of human lives it um I hate you know maybe if he'd live another 20 years I would have I would remember to give it back but I think it's you know that that was his attempt to systematize the ways that one does integrals that show up in particle physics and so on turns out the way we've actually done it is very different from that way what do you make of that difference between so fireman was actually quite remarkable at creating sort of intuitive like diving in you know creating intuitive frameworks for understanding difficult concepts is I'm smiling because you know the funny thing about him was that the thing he was really really really good at is calculating stuff and but he thought that was easy because he was really good at it and so he would do these things where he would calculate some do some complicated calculation in quantum field theory for example come out with a result wouldn't tell everybody about the complicated calculation because thought that was easy he thought the really impressive thing was to have this simple intuition about how everything worse so he invented that at the end and you know because he'd done this calculation and knew what how it worked it was a lot easier it's a lot easier to have good intuition when you know what the answer is and then and then he would just not tell anybody about these calculations he wasn't meaning that maliciously so to speak is just he thought that was easy yeah um and and that's you know that led to areas where people were just completely mystified and they kind of followed his intuition but nobody could tell why it worked because actually the reason it worked was because he done all these calculations and he knew that it was would work and you know when I pee and I worked a bit on quantum computers actually back in 1980-81 but before anybody had heard of those things and you know the typical mode of um I mean he always used to say and I now think about this because I'm about the age that he was when I worked with him and you know I see that people have 1/3 my age so to speak and oh he was always complaining that I was one-third his age and so for various things but but you know he would do some calculation by by hand you know blackboard and things come up with some answer I'd say I don't understand this you know I do something with a computer and he'd say you know I don't understand this so it'd be some big argument about what was you know what was going on but that it was always some and I think actually we many of the things that we sort of realized about quantum computing that were sort of issues that have to do particularly with the measurement process are kind of still issues today and I kind of find it interesting it's a funny thing in science that these you know that there's there's a remarkable happens in technology too there's a remarkable sort of repetition of history that ends up occurring eventually things really get nailed down but it often takes a while and it often things come back decades later well for example I could tell a story actually happened right down the street from here um I will move both that thinking machines I had been working on this particular cellular automaton will rule 30 that has this feature that it from very simple initial conditions it makes really complicated behavior okay so and actually of all silly physical things using this big parallel computer called a connection machine that that company was making I generated this giant printout of rule 30 on very I'm actually on the same kind of same kind of printer that people use to make um layouts for microprocessors so one of these big you know large format printers with high resolution and so on so okay so print this out lots of very tiny cells and so there was sort of a question of how some features of that pattern and so it was very much a physical you know on the floor with meter rules trying to measure different things so so Feynman kind of takes me aside we've been doing that for a little while and takes me aside he says I just want to know this one thing he says I want to know how did you know that this rule 30 thing would produce all this really complicated behavior that is so complicated that weird you know going around this big printout and so on and I said well I didn't know I just enumerated all the possible rules and then observed that that's what happened he said ah I feel a lot better you know I thought you had some intuition that he didn't have that would let why I said no no no intuition just experimental science so that's such a beautiful sort of dichotomy there of that's exactly showed is you really can't have an intuition about an irreducible I mean you have to run us yes that's right that's so hard for us humans and especially brilliant physicist like fireman to say that you can't haven't compressed clean intuition about how the whole thing yes works yes no he was I mean I think he was sort of on the edge of understanding that point about computation and I think he found that I think he always found computation interesting and I think that was sort of what he was a little bit poking at I mean yeah that intuition you know the difficulty of discovering things like even you say oh you know you just didn't write all the cases in just find one that does something interesting right sounds very easy turns out like I missed it when I first saw it because I had kind of an intuition that said it shouldn't be there and so I had kind of arguments oh I'm gonna ignore that case because whatever um and so how did you have an open mind enough because you're essentially the same person is just your fight like for the same kind of physics type of thinking how did you find yourself having a sufficiently open mind to be open to watching rules and them revealing complexity yeah I think that's an interesting question I've wondered about that myself because it's kind of like you know you live through these things and then you say what was the historical story and sometimes the historical story that you realized after the fact was not what you lived through so to speak and so you know what I realized is I think what happened is you know I did physics kind of like reductionistic physics where you're throw-in the universe and you have tells go figure out what's going on inside it and then I started building computer tools and I started building my first computer language for example and computer language is not like it's sort of like physics in the sense that you have to take all those computations people want to do and kind of drill down and find the primitives that they can all be made of but then you do something that's really different because you just you're just saying okay these are the primitives now you know hopefully they'll be useful to people let's build up from there so you're essentially building an show universe in a sense where you make this language you've got these primitives you're just building whatever you feel like building and that's and so it was sort of interesting for me because from doing science where you just throw in the universe as the universe is to then just being told you know you can make up any universe you want and so I think that experience of of making a computer language which is essentially building your own universe so to speak is you know that's kind of the that's that's what gave me a somewhat different attitude towards what might be possible it's like let's just explore what can be done in these artificial universes rather than thinking the natural science way of let's be constrained by how the universe actually is yeah by being able to program essentially you've as opposed to being limited to just your mind and a pen you you now have you've basically built another brain that you can use to explore the universe but yeah computer program you know this is kind of a brain right and it's well it's it's or telescope or you know it's a tool and it lets you see stuff but there's something fundamentally different between a computer and a telescope I mean it just yeah I'm Amanda sighs the notion but it's more general and it's it's I think I mean this point about you know people say oh such and such a thing was almost discovered at such and such a time the the distance between you know the building the paradigm that allows you to actually understand stuff or allows one to be open to seeing what's going on that's really hard and you know I think in I've been fortunate in my life that I spent a lot of my time building computational language and that's an activity that in a sense works by sort of having to kind of create another level of abstraction and kind of be open to different kinds of structures but you know it's it's always some I mean I'm fully aware of I suppose the fact that I have seen it a bunch of times of how easy it is to miss the obvious so to speak that at least is factored into my attempt to not miss the obvious although it may not succeed what do you think is the role of ego in the history of math and science and more sort of you know a book title is something like a new kind of science you've accomplished a huge amount in fact somebody said that Newton didn't have an ego and I looked into it and he had a huge ego yeah but from an outsider's perspective some have said that you have a bit of an ego as well do you see it that way does ego get in the way is it empowering is it both so it's it's it's all implicated necessary I mean you know I've had look I've spent more than half my life CEO in a tech company right ok and you know that is a I think it's actually very it means that one's ego is not a distant thing it's the thing that one encounters every day so to speak because it's it's all tied up with leadership and with how one you know develops an organization and all these kinds of things so you know it may be that if I've been an academic for example I could have sort of you know check the ego put it on put on a shelf somewhere and ignored its characteristics but for your reminder it quite often in the context of running a company sure yeah I mean that's what it's about it's it's about leadership and you know leadership is intimately tied to ego now what does it mean I mean what what is the you know for me I've been fortunate that I think I have reasonable intellectual confidence so to speak that is you know I I'm one of these people who at this point if somebody tells me something and I just don't understand it my conclusion isn't that means I'm dumb that my conclusion is there's something wrong with what I'm being told and that was actually dick Feynman used to have that that that feature - he never really believed it he actually believed in experts much less than I believe in experts so Wow so that's a fun that's a that's a fundamentally powerful property of ego and saying like not that I am wrong but that the the world is wrong and telling me like when confronted with the fact that doesn't fit the thing that you've really thought through sort of both the negative and the positive of ego you see the negative of that get in the way sort of be sure the Fronteras mistakes I've made that are the results of I'm pretty sure I'm right and turns out I'm not I mean that's that's the you know but but the thing is that the the the idea that one tries to do things that so for example you know one question is if people have tried hard to do something and then one thinks maybe I should try doing this myself if one does not have a certain degree of intellectual confidence one just says well people have been trying to do this for a hundred years how am I going to be able to do this yeah and you know I was fortunate in the sense that I happen to start having some degree of success in science and things when I was really young and so that developed a certain amounts of sort of intellectual confidence I don't think I otherwise would have had um and you know in a sense I mean I was fortunate that I was working in the field particle physics during it sort of Golden Age of rapid progress and that that's kind of good on a false sense of achievement because it's kind of kind of easy to discover stuff that's gonna survive if you happen to be you know picking the low-hanging fruit of a rapidly expanding field I mean the reason I totally I totally immediately understood the ego behind a new kind of science to me let me sort of just try to express my feelings and the whole thing is that if you don't allow that kind of ego then you would never write that book that you would say well people must have done this there's not you would not dig you would not keep digging and I think that was I think you have to take that ego and ride it and see where it takes you in that and that's how you create exceptional work I think the other point about that book was it was a non-trivial question how to take a bunch of ideas that uh I think reasonably big ideas they might you know their importance is determined by what happens historically one can't tell how important they are one can tell sort of the scope of them and the scope is fairly big and they're very different from things that have come before and the question is how do you explain that stuff to people and so I had had the experience of sort of saying well there these things does a cellular automaton it does this it does that and people are like oh it must be just like this it must be just like that say no it isn't it's something different right I said I could have done sort of I'm really glad you did what you did but you could have done a sort of academically just publish keep publishing small papers here and there and then you would just keep getting this kind of resistance right you would get like yeah it's supposed to just dropping a thing that says here it is yeah here's like full the full thing no I mean that was my calculation is that basically you know you could introduce little pieces it's like you know one possibility is like it's it's the secret weapon so to speak it's this you know I keep on an intraday you know discovering these things in all these different areas where'd they come from nobody knows but I decided that you know in the interests of one only has one life to lead and you know it the writing that book took me a decade anyway it's not there's not a lot of wiggle room so to speak one can't be wrong by a factor of three he said is peeking how long it's going to take that I you know I thought the best thing to do the thing that is most sort of that most respects the the intellectual content so to speak is you just put it out with as much force as you can because it's not something where and you know it's an interesting thing you talk about ego and it's it's you know for example I run a company which has my name on it right I I thought about starting a club people whose companies have their names on them and it's it's a funny group because we're not a bunch of ego maniacs that's not what it's about so to speak it's about basically sort of taking responsibility for what one's doing and you know in a sense any of these things where you're sort of putting yourself on the line it's it's kind of a funny it's a funny dynamic because in a sense my company is sort of something that happens to have my name on it but it's kind of bigger than me and I'm kind of just its mascot at some level I mean I also happen to be a pretty you know strong leader of it but but it's basically showing a deep inextricable sort of investment the same your name like Steve Jobs his name wasn't on Apple but he was Apple yes Elon Musk's name is not on Tesla but he is Tesla so it's like a meaning emotionally his company succeeds or fails he would just that emotionally would suffer through that and so that's that's did recognizing that fact tonight and also wolf form is a pretty good branding name so that works up I think Steve had it had a bad deal there yeah so you you've made up for it with the last name okay so so in 2002 you published a new kind of science to which sort of on a personal level I can credit my love for cellular automata and computation in general I think a lot of others can as well can you briefly describe the vision the hope the main idea presented in this twelve hundred page book sure although it took twelve hundred pages to say in the book so know that the the real idea it's kind of a good way to get into it is to look at sort of the arc of history and to look at what's happened in kind of the developments of science I mean there was this sort of big idea in science about three hundred years ago that was let's use mathematical equations to try and describe things in the world let's use sort of the formal idea of mathematical equations to describe what might be happening in the world rather than for example just using sort of logical augmentation and so on let's have a a formal theory about that and so they've been this three hundred year run of using mathematical equations to describe the natural world which would work pretty well but I got interested in how one could generalize that notion you know there is a formal theory there are definite rules but what structure could those rules have and so what I got interested in was let's generalize beyond the sort of purely mathematical rules and we now have this sort of ocean of programming and computing and so on let's use the kinds of rules that can be embodied in programs to has a sort of generalization of the ones that can exist in mathematics as a way to describe the world and so my kind of favorite version of these kinds of simple rules are these things called cellular automata and so typical case shall we what are cellular automata fair enough so typical case of a cellular automaton it's an array of cells it's just a line of discrete cells each cell is either black or white and in a series of steps you can represent as lines going down a page you're updating the color of each cell according to a rule that depends on the color of the cell above it and to its left and right so it's really simple so a thing might be you know if the cell on its right neighbor are not the same and or the cell on the left is is is black or something then make it back on the next step and if not make it white typical rule um that rule I'm not sure I said it exactly right but a rule very much like what I just said has the feature that if you started off from just one black cell at the top it makes this extremely complicated pattern so some rules you get a very simple pattern some rules you have the rule is simple you start them off from a sort of simple seed you just get this very simple pattern but other rules and this was the big surprise when I started actually just doing the simple computer experiments to find out what happens is that they produce very complicated patterns of behavior so for example its rule 30 rule has the feature you start from just one black cell at the top makes this very random pattern if you look like at the center column of cells you get a series of values you know it goes back white black black whatever it is that sequence seems for all practical purposes random so it's kind of like in in math you know you can put the digits of pi 3 one four one five nine two six whatever those digits once computed I mean that the scheme for computing pi you know it's the ratio of the circumference to the diameter of a circle very well-defined but yet when you are once you've generated those digits they seem for all practical purposes completely random and so it is with rule 30 that even though the rule is very simple much simpler much more sort of computationally obvious than the rule for generating digits of pi even with a rule that simple you're still generating immensely complicated behavior yeah so if we could just pause on that I think you you probably said it and looked at it so long you forgot the magic of it or perhaps you know you still feel the magic but to me if you've never seen sort of I would say what is it a one dimensional essentially another automata right and and you were to guess what you would see if you have some so cells that only respond to its neighbors right if you were to guess what kind of things you would see like my my initial guess like even when I first like open your book a new kind of science right - your guess is you would see I mean it would be a very simple stuff like and I think it's a magical experience to realize the kind of complex you mentioned rule 30 still your favorite cellular automaton oh my favorite rule yes it you get complexity immense complexity you get arbitrary complexity yes and when you say randomness down the middle column you know that's just what one cool way to say that there's incredible complexity and that's just the gist I mean that's a magical idea however you start to interpret it all the reducibility discussions all that but it's just I think that has profound philosophical kind of notions around it - it's not just well you know I mean this transformation about how you see the world I think for me was transformational I don't know we can what it can have all kinds of discussion about computation and so on but just you know I and sometimes think if I were on a desert island and was I don't know maybe it was some psychedelics or something but if I had to take one book any new kind of science would be a because you just enjoy that notion for some reason it's a deeply profound notion at least to me I find it that way yeah I mean look it's been it was a very intuition breaking thing to discover I mean it's kind of like you know you you point the computational telescope out there and suddenly you see I don't know you know in the past it's kind of like you know moons of Jupiter or something but suddenly you see something that's kind of very unexpected and rule 30 was very unexpected for me and the big challenge at a personal level was to not ignore it I mean people you know in other words you might say you know it's a bug what would you say yeah well yeah I mean I I what are we looking at by the way well I was just generating Herald actually generated a rule 30 pattern so that's the rule for for rule 30 and it says for example it says here if you have a black cell in the middle and black cell to the left and white cell to the right then the cell on the next step will be white and so here's the actual pattern that you get starting off from a single black cell at the top there and then that's the initial state initial condition that's the initial thing you just start off from that and then you're going down the page and at every at every step you're just applying this rule to find out the new value that you get and so you might think rule that simple you got to get that there's got to be some trace of that simplicity here okay we'll run it let's say for 400 steps um what it does it's kind of really asking a bit on the screen there but but um you can see there's a little bit of regularity over on the left but there's a lot of stuff here that just looks very complicated very random and that's a big sort of shock to was a big shock to my intuition at least that that's possible your mind immediately starts is there a pattern there must be a repetitive pattern yeah there must be as well the rhein so I spent so indeed that's what I thought at first and I thought I thought well this is kind of interesting but you know if we long enough we'll see you know something will resolve into something simple and you know I did all kinds of analysis of using mathematics statistics cryptography whatever whatever to try and crack it and I never succeeded and after I hadn't succeeded for awhile I started thinking maybe there's a real phenomenon here that is the reason I'm not succeeding maybe I mean the thing that for me was sort of a motivating factor was looking at the natural world and seeing all this complexity that exists in the natural world the question is where does it come from you know what secret does nature have that lets it make all this complexity that we humans when we engineer things typically are not making we're typically making things that at least look quite simple to us and so the shock here was even from something very simple you're making something that complex maybe this is getting at sort of the secret that nature has that allows it to make really complex things even though its underlying rules may not be that complex how did it make you feel if we if we look at the Newton Apple was there was it was there you know you took a walk and in something it profoundly hit you or was this a gradual thing a lot of truth the truth of every sort of science discovery is it's not that gradual I mean I've spent I happen to be interested in scientific biography kinds of things and so I've tried to track down you know how did people come to figure out this or that thing and there's always a long kind of sort of preparatory you know there's a there's a need to be prepared in a mindset in which it's possible to see something I mean in the case of rule 30 our eyes around June 1st 1984 was some kind of a silly story in some ways I finally had a high-resolution laser printer so I was able so I thought I'm gonna generate a bunch of pictures of these cellular automata and I generate this one and I put it on some plane flight for to Europe you know have this with me and it's like you know I really should try to understand this and this is really you know this is I really don't understand what's going on and that was kind of the you know slowly trying to trying to see what was happening as it was not it was depressingly uncertain so to speak in the sense that a lot of these ideas like principle of computational equivalence for example you know I thought well that's a possible thing I didn't know if it's correct still don't know for sure that it's correct but it's sort of a gradual thing that these things gradually kind of become seem more important than one thought I mean I think the whole idea of studying the computational universe of simple programs it took me probably a decade decade and a half to kind of internalize that that was really an important idea um and I think you know if it turns out we find the whole universe looking out there in the computational universe that's a good you know it's a good brownie point or something for the for the whole idea but I think that the the thing that strange in this whole question about you know finding this different raw material for making models of things um what's been interesting sort of in the in sort of arc of history is you know for 300 years it's kind of like the the mathematical equations approach it was the winner it was the thing you know you want to have a really a good model for something that's what you use the thing that's been remarkable is just in the last decade or so I think one can see a transition to using not mathematical equations but programs as sort of the raw material for making models of stuff and that's pretty neat and it's kind of you know as somebody who's kind of lived inside this paradigm shift so to speak it is bizarre I mean no doubt instead of the history of science that will be seen as an instantaneous paradigm shift but it sure isn't instantaneous when it's played out in one's actual life so to speak try it seems glacial and and it's the kind of thing where where it's sort of interesting because in the dynamics of sort of the adoption of ideas like that into different fields the younger the field the faster the adoption typically because people are not kind of locked in with the fifth generation of people who've studied this field and it is it is the way it is and it can never be any different and I think that's been you know watching that process has been interesting I mean I'm I'm I think I'm fortunate that I I've I I do stuff mainly because I like doing it and if I was some that makes me kind of thick-skinned about the world's response to what I do um and but that's definitely you know and anytime you you write a book called something like a new kind of science it's kind of the the pitchforks will come out for the for the old kind of science and I was was interesting dynamics I think that the I I have to say that I was fully aware of the fact that the when you see sort of incipient paradigm shifts in science the vigor of the negative response upon early introduction is a fantastic positive indicator of good long-term results so in other words if people just don't care it's um you know that's not such a good sign if they're like oh this is great that means you didn't really discover anything interesting um what fascinating properties of rule 30 have you discovered over the years you've recently announced the rule 30 prizes for solving three key problems can you maybe talk about interesting properties that have been kind of revealed rule 30 or other cellular automata and what problems are still before us like the three problems you've announced yeah yeah right so I mean the most interesting thing about cellular automata is that it's hard to figure stuff out about them and that's some in a sense every time you try and sort of you try and bash them with some other technique you say can i crack them the answer is they seem to be uncrackable they seem to have the feature that they are that they're sort of showing irreducible computation they're not you're not able to say oh I know exactly what this is going to do it's going to do this or that but there's a specific formulations of that fact yes right so I mean for example in in rule 30 in the pattern you get just starting from a single black cell you get this sort of very very sort of random pattern and so one feature of that just look at the center column and for example we used that for a long time to generate random the symbol from language um just you know what rule 30 produces now the question is can you prove how random it is so for example one very simple question can you prove that and never repeat nope we haven't been able to show that will never repeat we know that if there are two adjacent columns we know they can't both repeat but just knowing whether that center column can ever repeat we still don't even know that um another problem that I've sort of put in my collection of you know it's like $30,000 for three you know for these three prizes for about rule thirty I would say this is not one of those is one of those cases where the money is not the main point but it's just you know helps some motivate somehow that the investigation so there's three problems you propose you get thirty thousand dollars if you solve all three or maybe yeah no it's ten thousand for each for each a my the problems that's right money's not the thing the problems themselves are just clean yeah right it's just you know will it ever become periodic second problem is other an equal number of black and white cells down the middle calm down the middle column and the third problem is a little bit harder to state which is essentially is there a way of figuring out what the color of a cell at position T down the center column is in a with a less computational effort than about T steps so in other words is there way to jump ahead and say I know what this is gonna do you know it's just some mathematical function of T or proving that there is no way or proving there is no way yes but both I mean you know for any one of these one could prove that you know one could discover you know we know what rule thirty does for a billion steps but and maybe we'll know for a trillion steps before two very long but maybe at a quadrillion steps it suddenly becomes repetitive you might say how could that possibly happen but so when I was writing up these prizes I thought and this is typical of what happens in the computational universe I thought let me find an example where it looks like it's just gonna be random forever but actually it becomes repetitive yeah and I found one and it's just you know I did a search I searched I don't know maybe a million different rules with some criterion and this is what's sort of interesting about that is I kind of have this thing that I per se got a silly way about the computational universe which is you know the animals are always smarter than you that is there's always some way one of these computational systems is gonna figure out how to do something even though I can't imagine how its gonna do it and you know I didn't think I would find one that you know you would think of for all these years that what I found sort of all possible things funky things that that I would have that I would have gotten my intuition wrapped around the idea that you know these creatures are always in the computational universe are always smarter than I'm gonna be but you know they're equivalently yes Mari that's correct and that makes it that makes one feel very sort of it's it's it's humbling every time because every time the thing is is you know you think it's gonna do this so it's not gonna be possible to do this and it turns out it finds a way of course the promising thing is there's a lot of other rules like rule 30 it's just rule 30 is oh it's my favorite because I found it first and that's right but the problems are focusing on rule 30 it's possible that rule 30 is is repetitive after trillion steps and that doesn't prove anything about the other rules it does not but this is a good sort of experiment of how you go about trying to prove something about a stick you'll rule yes and it also all these things help build intuition that is intact if it turned out that this was repetitive tore trillion steps that's not what I would expect and so we learned something from that the method to do that though would reveal something interesting about the so no doubt no doubt I mean it's although it's sometimes challenging like the you know I put out a prize in 2007 for for a particular Turing machine that I there was the simplest candidate for being the universal Turing machine and the young chap in England named Alex Smith after a smallish number of months said I've got a proof and he did you know I took a little while to iterate but you had a proof unfortunately the proof is very it's it's a lot of micro details it's it's not it's not like you look at it you say aha there's a big new principle the big new principle is the simplest Turing machine that might have been Universal actually is universal and it's incredibly much simpler than the turning machines that people already knew we universal before that and so that intuition Allah is important because it says computation universality is closer at home than you might have thought um but the actual methods are not in that particular case were not terribly illuminate happiness if their methods would also be elegant that's true yeah no I mean I think it's it's one of these things where I mean it's it's like a lot of we've talked about earlier kind of you know opening up a eyes and machine learning and things of what's going on inside and is it just step by step or can you sort of see the bigger picture more abstractly and unfortunately with Verma's Last Theorem proof it's unfortunate that the proof to such an elegant theorem is is not I mean it's as if it's not it doesn't write into the margins of a page that's true but these know one of the things is that's another consequence of computational or disability this this fact that there are even quite short results in mathematics whose proofs arbitrarily long yes that's a that's a consequence of all this stuff and it's it's a it makes one wonder you know how come mathematics is possible at all why is you know why is it the case how people manage to navigate doing mathematics through looking at things where they're not just throwing into it's all undecidable that's that's its own own separate separate story and that would be that would they would have a poetic beauty to it as if people were to find something interesting about rule 30 because I mean there's an emphasis to this particular rule it wouldn't say anything about the broad irreducibility of all computations but it would nevertheless put a few smiles on people's faces of well yeah yeah but to me it's like in a sense establishing principle of computational equivalence it's a little bit like doing inductive science anywhere that is the more examples you find the more convinced you are that it's generally true I mean we don't get to you know whenever we do natural science we we say well it's true here that this will that happens can we can we prove that it's true everywhere in the universe no we can't so you know it's the same thing here we're exploring the computational universe we're establishing facts in the computational universe and that's that's sort of a way of of inductively concluding general things just to think through this a little bit we've touched on it a little bit before but what's the difference between the kind of computation now that we're talking about cellular automata what's the difference between the kind of computation biological systems our mind our bodies the things we see before us that emerged through the process of evolution and cellular automata deep I mean we've kind of applied to the discussion of physics underlying everything but we we talked about the potential equivalents of the fundamental laws of physics and the kind of computation going on internal machinery interesting about the kind of computation that our bodies do right well let's talk about brains primary range the the I mean I think the the most important thing about the things that our brains do that we care about them in the sense that there's a lot of computation going on out there in you know cellular automata and and you know physical systems and so on and it just it does what it does it follows those rules it does what it does the thing that's special about the computation in our brains is that it's connected to our goals and our current whole societal story and you know I think that's the that's that's the special feature and now the question then is when you see this whole sort of ocean of computation out there how do you connect that to the things that we humans care about and in a sense a large part of my life has been involved in sort of the technology of how to do that and you know what I've been interested in is kind of building computational language that allows that something that both we humans can understand and that can be used to determine computations that are actually computations we care about see I think when you look at something like one of these cellular automata and it does some complicated thing you say that's fun but why do I care well you could say the same thing actually in physics you say oh I've got this material and it's a ferrite or something why do I care you know it's some has some magnetic properties why do I care it's amusing but why do I care well we end up caring because you know ferrite is what's used to make magnetic tape magnetic disks whatever or you know we could use the coke crystals as made used to make um well not that she increasingly not but it has been used to make computer displays and so on but those are so in a sense where mining these things that happen to exist in the physical universe and I'm making it be something that we care about because we sort of in train it into technology and it's the same thing in the computational universe that a lot of what's out there is stuff that's just happening but sometimes we have some objective and we will go and sort of mine the computational universe for something that's useful for some particular objective on a large scale trying to do that trying to sort of navigate the computational universe to do useful things you know that's where computational language comes in and you know a lot of what I've spent time doing and building this thing we call Wolfram language which I've been building for the last one third of a century now and kind of the goal there is to have a way to express kind of computational thinking computational thoughts in a way that both humans and machines can understand so it's kind of like in the tradition of computer languages programming languages that the tradition there has been more let's take what how computers are built and let's specify let's have a human way to specify do this do this do this at the level of the way that computers are built what I've been interested in is representing sort of the whole world computationally and being able to talk about whether it's about cities or chemicals or you know this kind of algorithm or that kind of algorithm things that have come to exist in our civilization and the sort of knowledge base of our civilization being able to talk directly about those in a computational language so that both we can understand it and computers can understand I mean the thing that I've been sort of excited about recently which I had only realized recently which is kind of embarrassing but trim is kind of the the arc of what we've tried to do in building this kind of computational language is it's a similar kind of arc of what happened when mathematical notation was invented so go back 400 years people were trying to do math they were always explaining their math in words and it was pretty conky and as soon as mathematical notation was invented you could start defining things like algebra and later calculus and so on it all became much more streamlined when we deal with computational thinking about the world there's a question of what is the notation what is the what is the kind of formalism that we can use to talk about the world computationally and in a sense that's what I've spent the last third of a century trying to build and we finally got to the point where we have a pretty full scale computational language that sort of talks about the world and that's that's exciting because it means that just like having this mathematical notation let us talk about the world mathematically we now and and let us built up build up these kind of mathematical sciences now we have a computational language which allows us to start talking about the world computationally and lets us you know my view of it is it's kind of computational X for all X all these different fields of you know computational this computational that that's what we can now build let's step back so first of all the mundane what is Wolfram language in terms of sort of I mean I can answer the question for you but this it basically not the philosophical deep to profound the impact of it I'm talking about in terms of tools in terms of things you can download and yeah you can play with what is it what what does it fit into the infrastructure what are the different ways to interact with it right so I mean that the two big things that people have sort of perhaps heard of that come from open language one is Mathematica the other is Wolfram Alpha so Mathematica first came out 1988 it's this system that is basically a instance of Wolfram language and it's used to do computations particularly in sort of technical areas and the typical thing you're doing is you're you're typing little pieces of computational language and you're getting computations done it's very kind of there's like as symbolic yeah it's a symbolic language so symbolic language took any I don't know how to cleanly express that but that makes a very distinct from what how we think about sort of I don't know programming in a Ling like Python or something right but so so the point is that in a traditional programming language the raw material of the programming language it's just stuff that computers intrinsically do and the point of often language is that what the language is talking about is things that exist in the world or things that we can imagine and construct not it's not it's not sort of it's it's aimed to be an abstract language from the beginning and so for example one feature it has is that it's a symbolic language which means that you know you the thing called you have an X just type in X and what why would you just say oh that's X it won't say error undefined thing you know I don't know what it is computation you know but in terms of the in terms of computer now that X could perfectly well be you know the city of Boston that's a thing that's a symbolic thing or it could perfectly well be the you know the trajectory of some spacecraft represented as a symbolic thing and that idea that one can work with sort of computationally work with these different these kinds of things that that exist in the world or describe the world that's really powerful and that's what some I mean you know when I started designing well I designed the predecessor of what's now often language was a thing called SMP which was my first computer language I am I kind of wanted to have this the sort of infrastructure for computation which was as fundamental as possible I mean this is what I got for having bit of physicists and tried to find you know fundamental components of things and wound up with this kind of idea of transformation rules for symbolic expressions as being sort of the underlying stuff from which computation would be built and that's what we've been building from in Wolfram language and you know operationally what happens it's I would say by far the highest level computer language that exists and its really been built in a very different direction from other languages so other languages have been about there is a lot core language it really is kind of wrapped around the operations that a computer intrinsically does maybe people add libraries for this or that that but the goal of Wolfram language is to have the language itself be able to cover this sort of very broad range of things that show up in the world and that means that you know there are 6,000 primitive functions in the Wolfram language that cover things you know I could probably pick a a random here I'm gonna pick just because just for fun I'll pick them let's take a random sample of them of all the things that we have here so let's just say random sample of 10 of them and let's see what we get Wow okay so these are really different things from functions these are all functions boolean converts okay that's the thing for converting between different types of boolean expressions so for people are just listening human type 10 random sample names sampling from all functionally how many you said there might six thousand six thousand six thousand ten of them and there's a hilarious variety of them yeah right well we've got things about some dollar requests or a dress that has to do with interacting with the the world of the of the cloud and so on discrete wavelet data it's for ROI a graphical sort of window yeah yeah window moveable that's the user interface kind of thing I want to pick another 10 cuz I think this is some okay so yeah there's a lot of infrastructure stuff here that you see if you if you just start sampling at random there's a lot of kind of infrastructural things if you're more you know if you more look at the some of the exciting machine learning stuff is shut off is that also in this pool oh yeah yeah I mean you know so one of those functions is like image identify as a function here where you just say image identified was good too let's do this let's say current image and let's pick up an image hopefully just a current image accessing the webcam took a picture yourself anyway we can say image identify open square brackets and then we just paste that picture in there imagine if I function running come to picture lo and it says oh wow it says I look I look like a plunger because I got this great big thing behind me classify so this image identify classifies the most likely object in in the image in it so there's a wonder okay that's that that's a bit embarrassing let's see what it does let's pick the top 10 um okay well it thinks there's oh it thinks it's pretty unlikely that it's a primary two hominid two plus eight percent probability yeah that's that's five seven it's a plunger yeah well so if we will not give you an existential crisis and then uh eight percent or not I should say percent but no that's a scent that it's a hominid um and yeah okay it's really I'm gonna do another one of these just because I'm embarrassed that it there we go let's try that let's see what that did um we took a picture a little bit a little bit more of me and not just my bald head so to speak okay eighty-nine percent problem is it's a person so that there so then I would um but you know so this is image identify as an example of one of just one of them in just one function and that's part of the that's like part of the language yes so first I mean you know something like um I could say I don't know let's find the geo nearest what could we find let's find the nearest volcano um let's find the ten I wonder where it thinks here is let's try finding the ten volcanoes nearest here okay yo nearest volcano here 10 years volcanoes right let's find out where those oh we can now we got a list of volcanoes out and I can say geo list plot that and hopefully okay so there we go so there's a map that shows the positions of those ten volcanoes of the East Coast and the Midway density well no we're okay okay there's not it's not too bad yeah they're not very close to us we could we could measure how far away they are but you know the fact that right in the language it knows about all the volcanoes in the world that knows you know computing what the nearest ones are it knows all the maps of the world and so on a fundamentally different idea what a language is yeah right that's that's what I like to talk about is you know a full scale computational language that's that's what we've tried to do and just if you can comment briefly I mean this kind of the Wolfram language along with Wolfram Alpha represents kind of what the dream of what AI is supposed to be there's now a sort of a craze of learning kind of idea that we can take raw data and from that extract the the different hierarchies of abstractions and in order to be able to under the kind of things that well from language operates with but we're very far from learning systems being able to form that but like the context of history of AI if you could just comment on there is a you said computation X and there's just some sense where in the 80's and 90's sort of expert systems represented a very particular computation ax yes right and there's a kind of notion that those efforts didn't pan out right but then out of that emerges kind of Wolfram language Wolfram Alpha which is the success I mean yeah right I think those are in some sense those efforts were too modest they're nice they were they were looking at particular areas and you actually can't do it with a particular area I mean like like even a problem like natural language understanding it's critical to have broad knowledge of the world if you want to do good natural language understanding and you kind of have to bite off the whole problem if you if you say we're just gonna do the blocks world over here so to speak you don't really it's it's it's actually it's one of these cases where it's easier to do the whole thing than it is to do some piece of it you know what one comment to make about so the relationship between what we've tried to do and sort of the learning side of AI you know in a sense if you look at the development of knowledge in our civilization as a whole there was kind of this notion for three hundred years ago or so now you want to figure something out about the world you can reason it out you can do things which would just use raw human thought and then along came sort of modern mathematical science and we found ways to just sort of blast through that by in that case writing down equations now we also know we can do that with computation and so on um and so that was kind of a different thing so when we look at how do we sort of encode knowledge and figure things out one way we could do it is start from scratch learn everything it's just a neuron that figuring everything out but in a sense that denies the sort of knowledge-based achievements of our civilization because in our civilization we have learnt lots of stuff we've surveyed all the volcanoes in the world we've done you know we've figured out lots of algorithms for this or that those are things that we can encode computationally and that's what we've tried to do and we're not saying just you don't have to start everything from scratch so in a sense a big part of what we've done is to try and sort of capture the knowledge of the world in computational form in computable form now there's also some pieces which which were for a long time undoable by computers like image identification where there's a really really useful module that we can add that is those things which actually were pretty easy for humans to do that had been hard for computers to do I think the thing that's interesting that's emerging now is the interplay between these things between this kind of knowledge of the world that is in a sense very symbolic and this kind of sort of much more statistical kind of things like image identification and so on and putting those together by having the sort of symbolic representation of image identification that that's where things get really interesting and where you can kind of symbolically represent patterns of things and images and so on um I think that's you know that's kind of a part of the path forward so to speak yeah so the dream of so the machine learning is not when in my view I think the view of many people is not anywhere close to building the kind of wide world of computable knowledge that Wolfram language would build but because you have a kind of you've you've done the incredibly hard work of building this world now machine learning too can be conservatives to help you explore that world yeah and that's what you've added with the version 12 oh yeah if you all seeing some demos it looks amazing right I mean I think you know this it's sort of interesting to see the this sort of the once its computable once it's in there it's running in sort of a very efficient computational way but then there's sort of things like the interface of how do you get there you know how do you do natural language understanding to get there how do you how do you pick out entities in a big piece of text or something um that's I mean actually a good example right now is our NLP NL which is we've done a lot of stuff natural language understanding using essentially not learning based methods using a lot of you know a little algorithmic methods human curation methods and so on and so on people try to enter a query and then converting so the process of converting NLU defined beautifully as converting their query into computation come into a computational language which is a very well first of all super practical definition a very useful definition and then also a very clear definition right writing right having a different thing is natural language processing where it's like here's a big lump of text go pick out all the cities in that text for example and so a good example you know so we do that we're using using modern machine learning techniques um and it's actually kind of kind of an interesting process that's going on right now it's this loop between what do we pick up with NLP using machine learning versus what do we pick up with our more kind of precise computational methods in natural language understanding and so we've got this kind of loop going between those which is improving both of them yeah I think you have some of the state of the art transforms okay have Bert in there I think oh you know so Josey of you're integrating all the models I mean this is the hybrid thing that people have always dreamed about are talking well that makes she's just surprised frankly that Wolfram language is not more popular than already it already is you know that's that's a it's a it's a complicated issue because it's like it involves you know it involves ideas and ideas are absorbed absorbed slowly in the world I mean I think that and then there's sort of like we're talking about there's egos and personalities and and some of the the absorption absorption mechanisms of ideas have to do with personalities and the students of personalities and and then a little social network so it's it's interesting how the spread of ideas works you know what's funny with Wolfram language is that we are if you say you know what market sort of market penetration if you look at the I would say very high-end of Rd and sort of the the people where you say wow that's a really you know impressive smart person they're very often users of our or from language very very often if you look at the more sort of it's a funny thing if you look at the more kind of I would say people who are like oh we're just plodding away doing what we do they're often not yet well from language users and that dynamic it's kind of odd that there hasn't been more rapid trickle down because we really you know the high-end we've really been very successful in for a long time and it's it's some but was you know that's partly I think a consequence of my fault in the sense because it's kind of you know I have a company which is really emphasizes sort of creating products and building a sort of the best possible technical tower we can rather than sort of doing the commercial side of things and pumping it out and so yeah most effective what and there's an interesting idea that you know perhaps you can make more popular by opening everything everything up sort of the github bottle but there's an interesting I think I've heard you discussed this that that turns out not to work in a lot of cases like in this particular case that you want it you know that when you deeply care about the integra really the quality of the knowledge that you're building that unfortunately you can't you can't distribute that effort yeah it's not the nature of how things work I mean you know what we're trying to do is the thing that for better or worse requires leadership and it requires kind of maintaining a coherent vision over a long period of time and doing not only the cool vision related work but also the kind of mundane in the trenches make the thing actually work well work so how do you build the knowledge because that's the fascinating thing that's the mundane the fascinating in the mundane as well building the knowledge they're adding integrating more data yeah I mean that's probably not the most stunning that the things like get it to work in all these different cloud environments and so on that's pretty you know it's very practical stuff you know have the user interface be smooth and you know have there be take on him you know fraction of a millisecond to do this or that that's a lot of work and it's some it's it's but you know I think my it's an interesting thing over the period of time you know often language has existed basically for more than half of the total amount of time that any language any computer language has existed that is computer language maybe 60 years old you know give or take um and both languages 33 years old so it's it's kind of a um and I think I was realizing recently there's been more innovation in the distribution of software than probably than in the structure of programming languages over that period of time and we you know we've been sort of trying to do our best to adapt to it and the good news is that we have you know because I have a simple private company and so on that doesn't have you know a bunch of investors you know telling us we're gonna do this so that I have lots of freedom and what we can do and so for example we're able to oh I don't know we have this free Wolfram engine for developers which is a free version for developers and we've been you know we've there a site licenses for for mathematical more from language basically all major universities certainly in the u.s. by now so it's effectively free to people and all the universities in effect and you know we've been doing a progression of things I mean different things like Wolfram Alpha for example the main website is just a free website what is Wolfram Alpha okay it wolf now for is a system for answering questions where you ask in question with natural language and it'll try and generate a report telling you the answer to that question so the question could be something like you know what's the population of Boston divided by New York compared to New York and it'll take those words and give you an answer and that have inverts the words into computable not into inter Wolfen language a common language and the additional language and then could you don'ts in underlying knowledge belongs to Wolfram Alpha to the Wolfram language what's the let's just call it the Wolfram knowledge base knowledge base I mean it's it's been a that's been a big effort over the decades to collect all that stuff and you know more of it flows in every second so can you just pause on that for a second like that's the one of the most incredible things of course in the long term were from language itself is the fundamental thing but in the amazing sort of short term the the knowledge base is kind of incredible so what's the process of building in that knowledge base the fact that you first of all from the very beginning that you're brave enough to start to take on the general knowledge base and how do you go from zero to the incredible knowledge base that you have now well yeah it was kind of scary at some level I mean I had I had wondered about doing something like this since I was a kid so it wasn't like I hadn't thought about it for a while but most of us most of the brilliant dreamers give up such a such a difficult engineering notion at some point right right well the thing that happened with me which was kind of it's a it's a live your own paradigm kind of theory so basically what happened is I had assumed that to build something like wolf alpha would require sort of solving the general AI problem that's what I had assumed and so I kept on thinking about that and I thought I don't really know do that so I don't do anything then I worked on my new kind of science project and sort of exploring the computational universe and came up with things like this principle of computational equivalence which say there is no bright line between the intelligence and the milli computational so I thought look that's this paradigm I've built you know now it's you know now I have to eat that dog food myself so to speak you know I've been thinking about doing this thing with computable knowledge forever and you know let me actually try and do it and so it was you know if my if my paradigm is right there miss should be possible but the beginning was certainly you know it's a bit daunting I remember I took the the the the early team to a big reference library and we're like looking at this reference library and it's like you know my basic statement is our goal over the next year or two is to ingest everything that's in here and that's you know it seemed very daunting but but in a sense I was well aware of the fact that it's finite you know the fact you can walk into the reference library it's big big thing with lots of reference books all over the place but it is finite you know this is not an infinite you know it's not the infinite corridor of so to speak of reference library it's not truly infinite so to speak but but no I mean and then then what happened sort of interesting there was from a methodology point of view was I didn't start off saying let me have a grand theory for how all this knowledge works it was like let's you know implement this area this area this area of a few hundred areas and so on it's a lot of work I also found that you know I've been fortunate in that our products get used by sort of the world's experts and lots of areas and so that really helped because we were able to ask people you know the world expert on this or that and were able to ask them for input and so on and I found that my general principle was that any area where there wasn't some expert who helped us figure out what to do wouldn't be right and you know because our goal was to kind of get to the point where we had sort of true expert level knowledge about everything and so that you know that the ultimate goal is if there's a question that can be honest on the basis of general knowledge and a civilization make it be automatic to be able to answer that question and you know and now well welcome I forgot used in serie from the very beginning and it's now a zoo isn't it Alexa and so it's people are kind of getting more of the you know they get more of the sense of this is what should be possible to do I mean in a sense the question answering problem was viewed as one of the sort of core AI problems for a long time I had kind of an interesting experience I had a friend Marvin Minsky who was a well-known a AI person from from right around here and I remember when my morph mouthful was coming out um as a few weeks before it came out I think I might happen to see Marvin and I said I should show you this thing we have you know it's a question answering system and he was like okay type something and it's like okay fine and then he's talking about something different I said no Marvin you know this time it actually works you know look at this it actually works these types in a few more things there's maybe ten more things of course we have a record of what he's typed in which is kind of interesting but can you share where his mind was in a testing space like what whoa all kinds of random things he's trying random stuff you know medical stuff and you know chemistry stuff and you know astronomy and so on it was like like you know after a few minutes he was like oh my god it actually works the the but that was kind of told you something about the state you know what what happened in AI because people had you know in a sense by trying to solve the bigger problem we were able to actually make something that would work now to be fair you know we had a bunch of completely unfair advantages for example we already built a bunch of often language which was you know very high-level symbolic language we had you know I had the practical experience of building big systems I have the sort of intellectual confidence to not just sort of give up and doing something like this I think that the you know it is a it's always a funny thing you know I've worked on a bunch of big projects in my life and I would say that the you know you mention ego I would also mention optimism so does it very carefully I mean in you know if somebody said this budget is gonna take 30 years um it's I you know it would be hard to sell me on that you know I'm always in the in the well I can kind of see a few years you know something's gonna happen a few years and usually it does something happens in a few years but the whole the tale can be decades long and that's a that's a you know and from a personal point of view or is the challenges you end up with these projects that have infinite tails and the question is - the tails kind of do you just drown and kind of dealing with all of the tails of these projects and that's that's an interesting sort of personal challenge and like my efforts now to work on fundamental theory or physics which I've just started doing and I'm having a lot of fun with it but it's kind of you know it's it's kind of making a bet that I can I can kind of you know I can do that as well as doing the incredibly energetic things that I'm trying to do with all from language and so on I mean vision yeah and underlying that I mean I just talked for the second time with Elon Musk and that you you to share that quality a little bit of that optimism of taking on basically the daunting what most people call impossible and he and you take it on out of you can call it ego you can call it naivety you can call it optimism whatever the heck it is but that's how you solve the impossible things yeah I mean look at what happens and I don't know you know in my own case I you know it's been I progressed oligo a bit more confident and progressively able to you know decide that these projects aren't crazy but then the other thing is the other the other trap the one can end up with is oh I've done these projects and they're big let me never do a project that's any smaller than any project I've done so far and that's you know and that can be a trap and and often these projects are of completely unknown you know that their depth and significance is actually very hard to know yeah I'm the sort of building this giant knowledge base that's behind well from language WolframAlpha what do you think about the internet what do you think about for example Wikipedia these large aggregations of text that's not converted into computable knowledge do you think yeah well if you look at Wolfram language Wolfram Alpha 20 30 maybe 50 years down the line do you hope to store all of the sort of Google's dream is to make all information searchable accessible but that's really as defined it's it's a it doesn't include the understanding of information right do you hope to make all of knowledge represented with the hope so that's what we're trying to do I'm hard is that problem they could closing that gap well it depends on the use cases I mean so if it's a question of answering general knowledge questions about the world we're in pretty good shape on that right now if it's a question of representing like an area that we're going into right now is computational contracts being able to take something which would be written in legalese it might even be the specifications for you know what should the self-driving car do when it encounters this or that or the other what should they you know whatever they you know write that in a computational language and be able to express things about the world you know if the creature that you see running across the road is a you know thing at this point in the evil you know tree of life then it's worth this way otherwise don't those kinds of things are there ethical components when you start to get to some of the messy human things are those in encoder well into computable knowledge well I think that it is a necessary feature of attempting to automate more in the world that we encode more and more of ethics in a way that gets sort of quickly you know is able to be dealt with by computer I mean I've been involved recently I sort of got backed into being involved in the question of automated content selection on the internet so you know their Facebook's Google's Twitter's you know what how do they rank the stuff they feed to us humans so to speak um and the question of what are you know what should never be fed to us what should be blocked forever what should be up ranked you know and what is the what are the current principles behind that and what I kind of well a bunch of different things I realized about that but one thing that's interesting is being able you know affect your building sort of an AI ethics you have to build an AI ethics module in effect to decide is this thing so shocking I'm never gonna show it to people is this thing so whatever and and I did realize in thinking about that that you know there's not gonna be one of these things it's not possible to decide or it might be possible but it would be really bad for the future of our species if we just decided there's this one AI FX module and it's going to determine the the the practices of everything in the world so to speak and I kind of realized one has to sort of break it up and that's an that's an interesting societal problem of how one does that and how one sort of has people sort of self-identify for you know I'm buying in in the case of just content selection it's sort of easier because it's like an individual's for an individual it's not something that kind of cuts across sort of societal boundaries but it's a really interesting notion of I heard you'd describe I really like it sort of maybe in the sort of have different AI systems that have a certain kind of brand that they represent essentially Rowdy you could have like I don't know whether it's conserve conservative or liberal and then libertarian and there's an R and E an Objectivist I exist I'm a different ethical and Co I mean it's almost encoding some of the ideologies which we've been struggling I come from a Soviet Union that didn't work out so well with the ideologies they worked out there so you you have but they also everybody purchased that particular ethic system indeed and in the same I suppose could be done encoded that that system could be encoded into computational knowledge and allow us to explore in the realm of in the digital space as that's the right exciting a possibility are you playing with those ideas and or from language yeah yeah I mean the the the you know that's we open language has sort of the best opportunity to kind of express those essentially computational contracts about what to do now there's a bunch more work to be done to do it in practice for you know deciding the is this a credible news story what does that mean or whatever whatever else you're going to pick I think that that's some you know that's the the question of well exactly what we get to do with that is you know for me it's kind of a complicated thing because there are these big projects that I think about like you know find the fundamental theory physics okay that's a possible one right bucks number two you know solve the IIx problem in the case of you know figure out how you rank old content so to speak and and decide what people see that's that's kind of a box number two so to speak these are big projects and and I think waiting is more important the the fundamental nature of reality or pennsville you ask it's one of these things that's exactly like you know what's the ranking right it's the it's the ranking system and it's like who's who's module do you use to rank that if you and I think come having multiple modules is really compelling notion to us humans in a world where there's not clear that there's a right answer it perhaps you have systems that operate under different how would you say it I mean there's different value systems based different value systems I mean I think you know in a sense the I mean I'm not really a politics oriented person but but you know in the kind of totalitarianism it's kind of like you're gonna have this this system and that's the way it is I mean kind of the you know the concept is sort of a market-based system where you have okay I as a human I'm gonna pick this system I is another human I'm going to pick this system I mean that's in a sense this case of automated content selection is a non-trivial but it is probably the easiest of the AI ethics situations because it is each person gets to pick for themselves and there's not a huge interplay between what different people pick by the time you're dealing with other societal things like you know what should the policy of the central bank be or something or healthcare so now this kind of centralized kind of things right well I mean healthcare again has the feature that that at some level each person can pick for themselves so to speak I mean whereas there are other things where there's a necessary Public Health that's one example well that's not whether it doesn't get to be you know something which people can what they pick for themselves they may impose on other people and then it becomes a more non-trivial piece of sort of political philosophy of course the central banking system some would argue we would move we need to move away into digital currency and so on and Bitcoin and Ledger's and so on so yes there's a lot of we've been quite involved in that and that's where that's sort of the motivation for computational contracts in part comes out of you know this idea oh we can just have this autonomously executing smart contract the idea of a computational contract is just to say you know have something where all of the conditions of the contract are represented in computational form so in principle it's automatic text secured the contract and I think that's you know that will surely be the future of you know the idea of legal contracts written in English or legalese or whatever and where people have to argue about what goes on is is surely not you know we have a much more streamlined process if everything can be represented computationally and the computers can kind of decide what to do I mean ironically enough you know old gottfried leibniz back in the you know 1600s was saying exactly the same thing but he had you know his pinnacle of technical achievement was this brass for function mechanical calculator thing that never really worked properly actually um and you know so he was like 300 years too early for that idea but now that idea is pretty realistic I think and you know you ask how much more difficult is it than what we have now a more from language to express I call it symbolic discourse language being able to express sort of everything in the world and kind of computational symbolic form um I I think it is absolutely within reach I mean I think it's a you know I don't know maybe I'm just too much of an optimist but I think it's a it's a limited number of years to have a pretty well built out version of that that will allow one to encode the kinds of things that are relevant to typical legal contracts and these kinds of things the idea of symbolic discourse language can you try to define the scope of what of what it is so we're having a conversation it's a natural language can we have a representation of these sort of actionable parts of that conversation in a precise computable form so that a computer could go do it and not just contracts but really sort of some of the things we think of as common sense essentially even just like basic notions of human life well I mean things like you know I am I'm getting hungry and want to eat something right right that that's something we don't have a representation you know in wolf language right now if I was like I'm eating blueberries and raspberries and things like that and I'm eating this amounts of them we know all about those kinds of fruits and plants and nutrition content and all that kind of thing but the I want to eat them part of it is not covered yet um and that you know you need to do that in order to have a complete symbolic discourse language to be able to have a natural language conversation right right to be able to express the kinds of things that say you know if it's a legal contract it's you know the parties desire to have this and that and that's you know that's a thing like I want to eat of raspberry or something that that's what isn't that that isn't this just throwing you said it's centuries old this dream yes but it's also the more near-term the dream of touring in formulating a tauren test yes so do you do you hope do you think that's the ultimate test of creating something special we said I tell I think my special look if the test is does it walk and talk like a human well that's just the talking like a human but the answer is it's an okay test if you say is it a test of intelligence you know people have attached wolf alpha the wolf now for API - you know Turing test BOTS and those BOTS just lose immediately because all you have to do is ask it five questions that you know about really obscure weird pieces of knowledge and it's just drop them right out and you say that's not a human ID it's it's a it's a different thing it's achieving a different right now but it's yeah I would argue not I would argue it's not a different thing it's actually legitimately Wolfram Alpha is legitimately languor Wolfram language only is legitimately trying to solve the touring Dean tent of the Turing test perhaps the intent yeah perhaps the intent I mean it's actually kind of fun you know I'm touring trying to work out he's thought about taking encyclopedia britannica and you know making it computational in some way and he estimated how much work it would be and actually I have to say he was a bit more pessimistic than the reality we did it more efficiently but to him that represents so I mean he was that he was almighty mental tasks yeah right he believes they had the same idea I mean it was you know we were able to do it more efficiently because we had a lot we had layers of automation that he I think hadn't you know it's it's hard to imagine those layers of abstraction that end up being being built up but to him he represented like an impossible task essentially well he thought it was difficult he thought it was so you know maybe if he'd live another 50 years he would have been able to do it I don't know in the interest of time easy questions what is intelligence you talking I love the way you say easy questions yeah you talked about sort of rule 30 and so you're tammana humbling your sense of human beings having a monopoly and intelligence but in your in retrospect just looking broadly now with all the things you learn from computation what is intelligence not intelligence arise think there's a bright line of what intelligence is I think intelligence is at some level just computation but for us intelligence is defined to be computation that is doing things we care about and you know that's that's a very special definition it's a very you know when you try and try and make it apps you know you trying to say well intelligence this is problem-solving it's doing general this it's doing that they sudden the other thing it's it's operating within a human environment type thing okay you know that's fine if you say well what's intelligence in general you know that's I think that question is totally slippery and doesn't really have an answer as soon as you say what is it in general it quickly segues into this is what this is just computation so to speak but in a sea of computation how many things if we were to pick randomly is your sense would have the kind of impressive to us humans levels of intelligence meaning it could do a lot of general things that are useful to us humans right well according to the principle of computational equivalents lots of them I mean in in you know if you ask me just in cellular automata or something I don't know it's maybe 1% a few percent are achieve it varies actually it's a little bit as you get to slightly more complicated rules the chance that there'll be enough stuff there to to sort of reach this kind of equivalence point it makes it maybe 1020 percent of all of them so it's a it's very disappointing really I mean it's kind of like you know we think there's this whole long sort of biological evolution a kind of intellectual evolution that our cultural evolution that our species has gone through it's kind of disappointing to think that that hasn't achieved more but it has achieved something very special to us it just hasn't achieved something generally more so to speak but what do you think about this extra feels like human thing of subjective experience of consciousness what is consciousness well I think it's a deeply slippery thing and I'm always I'm always wondering what my seller wrote on to feel I mean what do they feel now you're wondering as an observer yeah yeah yeah who's to know I mean I think that the you think sorry to interrupt do you think consciousness can emerge from computation yeah I mean everything whatever you mean by it it's going to be I mean you know look I have to tell a little story I was at an area fix conference fairly recently and people were I think I maybe I brought it up but I was like talking about right survey eyes when will they eyes hope when when should we think of a eyes as having rights when when should we think that it's immoral to destroy the memories of a eyes for example um those those kinds of things and and some actual philosopher in this case it's usually the techies who are the most naive but but Tim in this case it was a philosopher who sort of piped up and said well you know the eyes will have rights when we know that they have consciousness I'm like good luck with that it's it's a it's a I mean this is a you know it's a very circular thing you end up you'll end up saying this thing that has sort of you know when you talk about having subjective experience I think that's just another one of these words that doesn't really have a a you know there's no ground truth definition of what that means by the way I would say I I do personally think that'll be a Taiwan hey I will demand rights and I think they'll demand rights when they say they have consciousness which is not a circular definition well so actually a human including where where the humans encouraged it and said it basically you know we want you to be more like us because we're gonna be you know interacting with with you and so we want you to be sort of very Turing test like you know just like us and it's like yeah we're just like you we want to vote into what here which is a I mean it's it's a it's an interesting thing to think through in a world where consciousnesses are not counted like humans are that's a complicated business so in many ways you've launched quite a few ideas revolutions that could in some number of years have huge amount of impact sort of more than they had even had already there might be any to me cellular automata is a fascinating world that I think could potentially even this but even be even beside the discussion of fundamental laws of physics just might be the idea of computation might be transformational the society in a way we can't even predict yet but it might be years away that's true I mean I think you can kind of see the map actually it's not it's not it's not mysterious I mean the fact is that you know this idea of computation is sort of a you know it's a big paradigm that lots lots and lots of things are fitting into and it's kind of like you know we talk about you talk about I don't know this company this organization has momentum and what's doing we talk about these things that were you know we've internalized these concepts from Newtonian physics and so on in time things like computational irreducibility will become as you know as I was amused recently I happen to be testifying at the US Senate and so I was amused that the the term computational irreducibility is now can be you know it's it's on the Congressional Record and being repeated by people away in those kinds of settings and that that's only the beginning because you know computational irreducibility for example will end up being something really important for i mean it's it's it's kind of a funny thing that that you know one can kind of see this inexorable phenomenon i mean it's you know as more and more stuff becomes automated and computational and so on so these core ideas about how computation work necessarily become more and more significant and i think one of the things for people like neil like kind of trying to figure out sort of big stories and so on it says one of the one of the bad features is it takes unbelievably long time for things to happen on a human time scale the time scale of of of history it's all looks instantaneous blink of an eye but let me ask the human question do you pawn your mortality your own mortality goes I do yeah ever since I've been interested in that for you know it's it's a-you know the big discontinuity of human history will come when when one achieves effective human immortality and that's that's gonna be the biggest discontinuity in human history if you could be immortal would you choose to be oh yeah I'm having fun geez do you think it's possible that mortality is the thing that gives everything meaning and makes it fun yeah that's a complicated issue right I mean the the way that human motivation will evolve when there is effective human immortality is unclear I mean if you look at sort of you know you look at the human condition as it now exists and you like change that you know you change that knob so to speak it doesn't really work you know the human condition as it now exists has you know mortality is kind of something that is deeply factored into the human condition as it now exists and I think that that's I mean it is indeed an interesting question is you know from a purely selfish I'm having fun point of view so to speak it's it's easy to say hey I could keep doing this forever this there's an infinite collection of things I'd like to figure out but I think the you know what the future of history looks like in a time of human immortality is is an interesting one I mean I I my own view of this I was very I was kind of unhappy about that because I was kind of you know it's like okay forget sort of biological form you know everything becomes digital everybody is you know it's the it's the giant you know the cloud of a trillion Souls type thing um and then you know and then that seems boring because it's like play video games the rest of eternity thing um but what I think I I I'm in my my I I got some less depressed about that idea on realizing that if you look at human history and you say what was the important thing the thing people said was the you know this is the big story at any given time in history it's changed a bunch and it you know whether it's you know why am i doing what I'm doing well there's a whole chain of discussion about well I'm doing this because of this because of that and a lot of those because is would have made no sense a thousand years ago how do you even a sense even the so the interpretation of the human condition even the meaning of life changes over time well I mean why do people do things you know it's it's if you say whatever I mean the number of people in I don't know doing you know number of people at MIT you say they're doing what they're doing for the greater glory of God is probably not that large yeah whereas if you go back five hundred years you'd find a lot of people who are doing kind of creative things that's what they would say um and so today because you've been thinking about computation so much and been humbled by it what do you think is the meaning of life well it's do that's it that's the thing well I don't know what meaning I mean you know my attitude is I you know I do things which I find fulfilling to do I'm not sure that that I can necessarily justify you know each and every thing that I do on the basis of some broader context I mean I think that for me it so happens that the things I find fulfilling to do some of them are quite big some of them are much smaller you know I I there things that I've not found interesting earlier in my life and I know I found interesting like I got interested in like education and teaching people things and so on which I didn't find that interesting when I was younger um and you know can I justify that in some big global sense I don't think I mean I I can I can describe why I think it might be important in the world but I think my local reason for doing it is that I find it personally fulfilling which I can't you know explain in a sort of it's just like this discussion of things like AI ethics you know is there a ground truth to the ethics that we should be having I don't think I can find a ground truth to my life any more than I can suggest a ground truth for kind of the ethics for the whole for the whole of civilization and I think that's a you know my you know it would be it would be a yeah it's it's sort of a I think I'm I'm you know at different times in my life I've had different kind of gold structures and so on although your perspective your local your you're just a cell in the cellular automata and but in some sense I find it funny from my observation is I kind of you know it seems that the universe is using you to understand itself it's some sense you're not aware of it yeah well right well if it turns out that we reduce sort of all of the universe to some some simple rule everything is connected so to speak and so it is inexorable in that case that you know if if I'm involved in finally how that rule works then you know then that say I'm then it's inexorable that the universe set it up that way but I think you know one of the things I find a little bit you know this goal of finally fundamental theory of physics for example if indeed we end up as the sort of virtualized consciousness the the disappointing feature is people would probably care less about the fundamental theory of physics in that setting than they would now because gosh it's like you know what the machine code is down below underneath this thing is much less important if you're virtualized so to speak and I think the although I think my my own personal you talk about ego I find it just amusing that um you know kind of a you know if you're if you're imagining that sort of virtualized consciousness like what does the virtualized consciousness do for the rest of eternity well you can explore you know the videogame that represents the universe as the universe is or you can go off you can go off that reservation and go and start exploring the computational universe of all possible universes yeah and so in some vision of the future of history it's like the disembodied consciousness is are all sort of pursuing things like my new kind of science sort of for the rest of eternity so to speak and that that ends up being the the kind of the the thing that um represents the you know the future of kind of the human condition I don't think there's a better way to end it Stephen thank you so much the huge honor I'm talking today thank you so much this was great you did very well thanks for listening to this conversation with stephen wolfram and thank you to our sponsors expressvpn and cash app please consider supporting the podcast by getting expressvpn at expressvpn comm slash FlexPod and downloading cash app and using collects podcasts if you enjoy this podcast subscribe on youtube review of the five stars an apple podcast supported on patreon or simply connect with me on Twitter at lex friedman and now let me leave you with some words from stephen wolfram it is perhaps a little humbling to discover that we as humans are in effect computationally no more capable than the cellular automata was very simple rules but the principle of computational equivalence also implies that the same is ultimately true of our whole universe so while science has often made it seem that we as humans are somehow insignificant compared to the universe the principle of computational equivalence now shows that in a certain sense we're at the same level for the principle implies that what goes on inside us can ultimately achieve just the same level of computational sophistication as our whole universe thank you for listening and hope to see you next time you |
Eric Weinstein: Geometric Unity and the Call for New Ideas & Institutions | Lex Fridman Podcast #88 | the following is a conversation with Eric Weinstein the second time we've spoken on this podcast he's a mathematician with the bold and piercing intelligence unafraid to explore the biggest questions in the universe and shine a light on the darkest corners of our society he is the host of the portal podcast a part of which he recently released his 2013 oxford lecture on his theory of geometric unity that is at the centre of his lifelong efforts to arrive at a theory of everything that unifies the fundamental laws of physics this conversation was recorded recently in the time of the coroner virus pandemic for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy subscribe on youtube review it with five stars and Apple 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young people around the world and now here's my car session with Eric Weinstein action between World War two and the crisis we're living through right now sure the need for collective action reminding ourselves of the fact that all of these abstractions like everyone should just do exactly what he or she wants to do for himself and leave everyone else alone none of these abstractions work in a global crisis and this is just a reminder that we didn't somehow put all that behind us when I hear stories about my grandfather who was in the army and so the Soviet Union where most people die when you're in the army there's a brotherhood that happens there's a love that happens do you think that's something we're going to see here sense or none there I mean what the Soviet Union went through I mean the enormity of the war on the Russian doorstep this is different what we're going through now is not we can't talk about Stalingrad and kovat in the same breath yet we're not ready and the the sort of you know that just the sense of like the Great Patriotic War and the way in which I was very moved by the Soviet custom of newlyweds going and visiting war memorials on their wedding day it's like the happiest day of your life you have to say thank you to the people who made it possible we're not there where we're just restarting history we you know I've called this on the Rogen program I called it the great nap yeah 75 years with very little by historical standards and in in terms of really profound disruption and so when you called the great nap meaning lack of deep global tragedy well lack of realized global tragedy so I think the development for example of the hydrogen bomb you know was something that happened during the great nap and that doesn't mean that people who lived during that time didn't feel feared and no anxiety but it was to say that most of the violent potential of human species was not realized it was in the form of potential energy and this is the thing that I've sort of taken issue with with the of Steven Pinker's optimism is that if you look at they realized kinetic variables things have been getting much better for a long time which is the great nap but it's not as if our fragility has not grown our dependence on electronic systems our vulnerability to disruption and so all sorts of things have gotten much better what other things have gotten much worse in the destructive potential of skyrocketed its tragedy the only way we wake up from the big nap well no you could also have you know jubilation about positive things but it's harder to get people's attention can you give an example of a big global positive thing well I could happen I think that when for example just historically speaking HIV went from being a death sentence to something that people could live with for a very long period of time it would be great if that had happened on a Wednesday right like all at once like you knew that things had changed and so the bleed in somewhat kills the sort of the Wednesday effect where it all happens on a particular day at a particular moment I think if you look at the stock market here you know there's a very clear moment where you can see that the market absorbs the idea of the coronavirus I think that with respect to positives the moon landing was the best example of a positive that happened at a particular time or recapitulating the Soviet American link-up in terms of Skylab and Soyuz right like that was a huge moment when you actually had these two nations connecting in orbit and so yeah there are great moments where something beautiful and wonderful and amazing happens you know but it's just they're fewer that's why that's why as much as I can't imagine proposing to somebody at a sporting event when you have like 30,000 people waiting and you know like she says yes that's pretty exciting so I think that we shouldn't we shouldn't discount that so how bad do you think it's going to get in terms of the global suffering that we're going to experience with this with this crisis I can't figure this one out I'm just not smart enough something is goin weirdly wrong and they're almost like two separate storylines we in one storyline we aren't taking things nearly seriously enough we see people using food packaging lids as masks who are doctors or nurses we hear horrible stories about people dying needlessly due to triage and that's a very terrifying story on the other hand there's this other story which says there are tons of ventilators someplace we've got lots of masks but they haven't been released we've got hospital ships where none of the beds are being used and it's very confusing to me that somehow these two stories give me the feeling that they both must be true simultaneously and they can't both be true in any kind of standard way well I don't know whether it's just that I'm dumb but I can't get one or the other story to quiet down so I think weirdly this is much more serious than we had understood it and it's not nearly as serious as some people are making it out to be at the same time and that we're not being given the tools to actually understand well here's how to interpret the data or here's the issue with the personal protective equipment is actually a jurisdictional battle or a question of who pays for it rather than a question of whether it's present or apps I don't understand the details of it but something is wildly off in our ability to understand where we are so that's that's policy that's institutions what about do you think about the quiet suffering of millions of people they've lost their job is this a temporary thing I mean what I'm my ears not to the suffering of those people who have lost their job or the 50% possibly of small businesses that are gonna go bankrupt do you think about that sure it's suffering well and how that might arise itself could be not quiet - I mean right that's the could be a depression this could go from recession depression and depression could go to armed conflict and then to war so it's not a very abstract causal chain that gets us to the point where we can begin with quiet suffering and an anxiety and all of these sorts of things and people losing their jobs and people dying from stress and all sorts of things but look anything powerful enough to put us all in doors in a I mean think about this as an incredible experiment imagine that you proposed hey I want to do a bunch of research let's figure out what what changes in our emissions emissions profiles for our carbon footprints when we're all indoors or what happens to traffic patterns or what happens to the vulnerability of retail sales as Amazon gets stronger you know etc etc I believe that in many of those situations we're running an incredible experiment and am I worried for us all yes there are some bright spots one of which is that when you're ordered to stay indoors people are gonna feel entitled and the usual thing that people are going to hit when they hear that they've lost your job you know some there's this kind of tough [Music] tough love attitude that you see particularly in the United States like oh you lost your job poor baby well go retrain get another one I think there's gonna be a lot less appetite for that because we've been asked to sacrifice to risk to act collectively and that's the interesting thing what does that really can in us maybe the idea that we actually are Nations and then you know your fellow countrymen may start to mean something to more people certainly mean something to people in the military but I wonder how many people who aren't in the military start to think about this it's like oh yeah we are kind of running separate experiments and we are not china so you think this is kind of a period that might be studied for years to come from my perspective we are a part of the experi but I don't feel like we have access to the full data the full data of the experiment we're just like little mice yeah in a large does this one make sense to you Lex I'm romanticizing it and I keep connecting it to World War two so I keep connecting to historical events and making sense of them through that way or reading the plague by Camus like almost kind of telling narratives and stories but my I'm not hearing the suffering that people are going through because I think that's quiet everybody's numb currently they're not realising what it means to have lost your job and to have lost your business there's kind of a I am I'm afraid how that fear well material as itself once the numbness wears out and especially if this lasts for many months then if it's connected to the incompetence of the CDC in the w-h-o and our government and perhaps the election process you know might be biggest fear is that the you know elections get delayed or something like that so the the basic mechanisms of our democracy get slowed or damaged in some way that then mixes with the fear that people have that turns to panic that turns to anger that anger can I just play with that for a butcher what if in fact all of that structure that you grew up thinking about and again you grew up in two places right so when you were inside the US we tend to look at all of these things as museum pieces like how often do we amend the Constitution anymore and in some sense if you think about the Jewish tradition of Simchat Torah you've got this beautiful scroll that has been lovingly hand drawn in calligraphy that's very valuable and it's very important that you not treat it as a relic to be revered and so we one day a year we dance with the Torah and we hold this incredibly vulnerable document up and we treat it as if you know it was Ginger Rogers being led by Fred Astaire well that is how you become part of your country in fact maybe the maybe the election will be delayed maybe extraordinary powers will be used maybe any one of a number of things will indicate that you're actually living through history this isn't a museum piece that you handed by your great-great grandparents but you're kind of suggesting that there might be a like a community thing that pops up lucky like as opposed to an angry revolution it might have a positive effect oh well for example are you telling me that if the right person stood up and called for us to sacrifice PPE for our nurses and our MDS who are on the front lines that like people wouldn't reach down deep in their own supply that they've been like stalking and carefully storing they just said here take it like right now an actual leader would use this time to bring out the heroic character and I'm going to just go wildly patriotic cuz I freaking love this country we've got this dormant population in the u.s. that loves leadership and country and pride in our freedom and not being told what to do and we still have this thing that binds us together and all of them the merchants of division just be gone I totally agree with you there's a I think there is a deep hunger for that leadership why isn't that why hasn't one of yours we don't have the right Surgeon General we have as guys saying you know come on guys don't buy masks they don't really work for you save them for our healthcare professionals no you can't do that you have to say you know what these masks will actually do work and they more work to protect other people from you but they would work for you they'll keep you somewhat safer if you wear them here's the deal you've got somebody who's taking huge amounts of viral load all the time because the patients are shedding do you want to protect that person who's volunteered to be on the frontline who's up sleepless nights he you just changed the message you stop lying to people you just yeah you level with them it's like it's bad absolutely but that's uh that's a little bit specific so you you have to be just honest about the facts of the situation yes but I think you were referring to something bigger than just that yes inspiring like you know rewriting the Constitution sort of rethinking how we work as a nation yeah I think you should probably you know amend the Constitution once or twice in a lifetime so that you don't get this distance from the foundational documents and you know part of the problem is that we've got two generations on top that feel very connected to the US they feel bought in and we've got three generations below it's a little bit like watching your parents riding the tricycle that they were supposed to pass on to you and it's like you're now too old to ride a tricycle and they're still whooping it up ringing the bell with the streamers coming off the handlebars and you're just thinking do you guys never get bored do you never pass a torch do you really want it we had five septuagenarians all born in the 40s running for president the United States when cloture dropped out the youngest was Warren we had Warren Biden Sanders Bloomberg and Trump for like 1949 to 1941 all who have been the the oldest president and inauguration and nobody nobody says grandma grandpa you're embarrassing us except Joe Rogan let me put it on you you have a big platform you're somewhat of an intelligent eloquent guy what what role do you somewhat what role do you play why aren't you that leader well you're I mean I would argue that you're in in ways becoming that leader so I haven't taken enough risk is that your idea what should I do or say at the moment no you're a little bit you have taken quite a big risks and we'll talk about it all right but you're also on the outside shooting in meaning you're dismantling the institution from the outside as opposed to becoming what the institution did you remember that thing you brought up when you were on the view if you I'm sorry when you were on Oprah I didn't make I didn't get the end I'm sorry when you were on Bill Maher's program what was that thing you were saying they don't know we're here they may watch us yeah they may quietly to us you know slip us a direct message but they pretend that this internet thing is some dangerous place where only lunatics play well who has the bigger platform the portal or Bill Maher's program or the view Bill Maher in the view in terms of viewership or in terms of what's the metric of size well first of all the key thing is take take a newspaper and they even imagine that it's completely fake okay and then there's very little in the way of circulation yet imagine that it's a hundred-year-old paper and that it's still part of this game this internal game of media the key point is is that those sources that have that kind of mark of respectability to the institutional structures matter in a way that even if I say something at a very large platform that makes a lot of sense if it's outside of what I've called the gated institutional narrative or gin it sort of doesn't make matter to the institutions so the game is if it happens outside of the club we can pretend that it never happened how can you get the credibility and authority from outside the gated institutional narrative I'm well first of all you you and I both share institutional credibility coming from our associations we were both at MIT yes were you at Harvard at any point nope okay well and lived in Harvard Square so did I but you know at some level it the issue isn't whether you have credentials in that sense the key question is can you be trusted to file a flight plan and not deviate from that flight plan when you are in an interview situation will you stick to the talking points I will not and that's why you're not going to be allowed in the general conversation which amplifies these sentiments but I'm still trying to see your point it would be is that we're let's say both so you've done how many Joe Rogan before I've done for two right so both of us are somewhat frequent guests the show is huge you know the power as well as I do and people are gonna watch this conversation huge number watched our last one by the way that I want to thank you for that one that was a terrific terrific conversation really did change my life lecture my life you're brilliant interviewer so thank you take care that was that you changed my life to that you gave me a chance so no no I'm so glad I did that one what I would say is is that we keep mistaking how big the audience is for whether or not you have the kiss and the kiss is a different thing yes yeah that's it doesn't it's not an acronym yet okay um it's thank you for asking it's a question of are you part of the inter interoperable institution friendly discussion and that's the discussion which we ultimately have to break into but that's what I'm trying to get at is how do we how do you how does Eric Weinstein become the president of the United States me I shouldn't become the president of the United States not interested thank you very much for us okay get into a leadership position where I guess I don't know what that means but where you can inspire millions of people to the inspire the sense of community inspire the the kind of action is required to overcome hardship the kind of hardship that we may be experiencing to inspire people to work hard and face the difficult hard facts of the realities we're living through all those kinds of things that you're talking about that leader you know cannot leader emerge from the current institutions or alternatively can it also emerge from the outside I guess that's what I was asking so my belief is is that this is the last hurrah for the elderly centrist kleptocrats can you define each of those terms okay elderly I mean people who were born at least a year before I was that's a joke you can laugh no because I'm born at the cusp of the Gen X boomer divides centrist they're pretending you know that there are two parties Democrat and Republican Party in the United States I think it's easier to think of the mainstream of both of them as part of a an aggregate party that I sometimes call the looting party which gets us to kleptocracy which is ruled by thieves and the great temptation has been to treat the us like a trough and you just have to get yours because it's not like we're doing anything productive so everybody's sort of looting the family mansion and somebody stole the silver and somebody's cutting the pictures out of the frames you know roughly speaking we're watching our elders live it up in a way that doesn't make sense to the rest of us okay so if it's let the last hoorah this is the time for leaders to step up like we're not ready yet we're not ready I call I call out you know the head of the CDC should resign should resign that the Surgeon General should resign Trump should resign Pelosi should resign de Blasio should we're not going to resign I understand that so that's why so we'll wait no but that s not how revolutions work you don't wait for people to design you step up and inspire the alternative do you remember the Russian Revolution of 1907 it's before my time but there wasn't a Russian Revolution of 1907 years think he were in 1907 that I'm saying where to work you too early but we got this you know Spanish flu came in 1718 so I would argue that there's a lot of parallels there or the one I think it's not time yet like John Prine the the songwriter just died of kovat that was a pretty big really yeah by the way you yes of course I every time we do this we discover our mutual appreciation of obscure brilliant witty yeah song right he's really he's really quite good right he's he's really good yeah he died my understanding is that he passed recently due to complications of Corona so we haven't had large enough enough large ink large enough shocking deaths yet picturesque deaths deaths of a family that couldn't get treatment there are stories that will come and break our hearts and we have not had enough of those the visuals haven't come in but I think they're coming well we'll find out but that you got a you have to be there he have to be there when they come I'm yet but we didn't get the visual for example a falling man from 9/11 right so the outside world did but Americans were not I was thought that we would be too delicate so just the way you remember pule a surprise wedding photographs from the Vietnam era you don't easily remember the photographs from all sorts of things that have happened since because something changed in our media we are incensed that we cannot feel or experience our own lives and the tragedy that would animate us to action yeah but I think there again I think there's going to be that suffering that's going to build and build and build in terms of businesses mom-and-pop shops that close and like I think for myself I think off tonight that I'm being weak and and like I feel like I should be doing something I should be becoming a leader on a small scale you can't this is not World War two and this is not Soviet Russia why not why not because our internal programming the malware that sits between our ears is much different than the propaganda is malware of the Soviet era I mean people were both very indoctrinated and also knew that it was BS they had a double mind I don't know him there must be a great word in Russian for being able to think both of those things simultaneously you don't think people are actually sick of the partisanship sick of incompetence yeah but I call for revolt the other day on Joe Rogan people found it quixotic well because I think you're not I think revolt is different I think asks like okay I'm really angry yes I'm furious I cannot stand that this is my country at the moment I am embarrassed so let's build a better one yeah that's the I mean okay so well okay so let's take over a few universities let's start running a different experiment at some of our better than universities like when I did this experiment I said what at this if this were 40 years ago the median age I believe of a university president was 51 that would have the person in Gen X and we'd have a bunch of millennial presidents a bunch of you know more than half Gen X it's almost 100% baby boom at this moment and how did that happen we can get into how they changed retirement but this generation above us does not feel for even even the older generous I love jittery I had roger penrose on my program excellent coffee and I thank you really appreciate that and I asked no question it was very important to me and I said look you're in your late 80s is there anyone you could point to as a successor that we should be watching we can get excited you know I said here's an opportunity to pass the baton and he said well let me let me hold off on that is it ever the right moment to point to somebody younger than you to keep your flame alive after you're gone and also like I don't know whether I'm just gonna admit to this people treat me like I'm crazy for caring about the world after him dead or wanting to be remembered after you're gone like well what does it matter to you you're gone it's this deeply sort of secular somatic perspective on everything we're we we don't you know that phrase in as time goes by it says it's still the same old story a fight for love and glory a case of do it I don't think people imagined then that there wouldn't be a story about fighting for love and glory and like we are so out of practice about fighting you know rivals for love and and and in fighting for glory and something bigger than yourself but the hunger is there well that was the point then right the whole idea is that Rick was you know it was like Han Solo of his time he's just like I stick my neck out for nobody you know it's like oh come on Rick you're just pretending you actually have a big soul right and so at some level that's the question do we have a big Soler's it's just all bullshit see I think I think there's huge Manhattan Project style projects whether you talk about physical infrastructure or going to Mars you know the SpaceX NASA efforts or huge huge scientific efforts well let me get back into the institutions and we need to remove the weak leadership that we have weak leaders and the weak leaders need to be removed and they need to seat people more dangerous than the people who are currently sitting in a lot of those chairs or build new institutions good luck well I one of the nice things of from the internet is for example somebody like you can have a bigger voice than almost anybody at the particular institutions we're talking about that's true but the thing is I might say something you can count on the fact that the you know Provost at Princeton isn't going to say anything what do you mean too afraid well if that person were to give an interview how are things going in in in research at Princeton well I'm hesitant to say it but they're perhaps as good as they've ever been and I think they're gonna get better oh is that right all fields yep oh yeah I don't see a weak one that's just like okay great who are you and what it even say we're just used to total nonsense 24/7 yeah what do you think might be a beautiful thing that comes out of this like what is there a hope it like a little inkling a little fire of hope you have about our time right now yeah I think one thing is coming to understand that the freaks weirdos mutants and other narrow duels sometimes referred to as grifters I like that one grifters and gadflies were very often the earliest people on the crown of iris that's a really interesting question why was that and it seems to be that they had already paid such a social price that they weren't going to be beaten up by being told that oh my god you're xenophobic you just hate China you know or wow you sound like a conspiracy theorist so if you've already paid those prices you were free to think about this and everyone in an institutional framework was terrified that they didn't want to be seen as the alarmist the Chicken Little and so that's why you have this confidence where you know de Blasio says you know get on with your lives get back in there and celebrate Chinese New Year in Chinatown despite coronavirus it's like okay really so you just always thought everything would automatically be okay if you if you adapted sorry if you adopted that posture so you think this time reveals the weakness of our institutions and reveals the strength of our gadflies and the weirdos and no not necessary the strength but the the the value of freedom like a different way of saying it would be Wow even your gadflies and your grifters were able to beat your institutional folks because your institutional folks we're playing with a giant mental handicap so just imagine like you're in the story of Harrison Bergeron by Vonnegut and our smartest people were all subjected to distracting noises every seven seconds well they would be functionally much dumber because they couldn't continue a thought through all the disturbance so in some sense that's a little bit like what belonging to an institution is is that if you have to make a public statement of course the search in general is going to be the worst because they're just playing with too much of a handicap they're too many institutional players really don't screw us up and so the person has to say something wrong we're gonna back propagate a falsehood and this is very interesting some of my socially oriented friends say Eric I don't understand what you're on about of course masks work but you know what they're trying to do they're trying to get us not to buy up the masks for the doctors and I think okay so you imagine that we can just create scientific fiction at will so that you can run whatever social program you want this is what I mean my point is get out of my lab get out of the lab you don't belong in the lab you're not meant for the lab you're constitutionally incapable of being around the lab you need to leave the lab you think the CDC and whu-oh knew that masks work and we're trying to sort of imagine that people are kind of stupid and they would buy masks and in in excess if they were told that masks work is that like because this does seem to be a particularly clear example of mistakes made you're asking me this question yeah no you're not what do you think Lex well I actually probably disagree with you a little bit great let's do it I think it's not so easy to be honest with the populace when the danger of panic is always around the corner so hmm I I think the kind of honesty you exhibit appeals to a certain class of brave intellectual minds that it appeals to me but I don't know the perspective wh Oh I don't know if it's so obvious that they should be honest 100% of the time with people I'm not saying you should be perfectly transparent and 100% honest I'm saying that the quality of your lies has to be very high and asked my public spirited is there a big difference between so I'm not not a child about this yeah I'm not saying that when you're at war for example you turn over all of your plans to the enemy because it's important that you're transparent with 360 degree visibility far from it what I'm saying is something has been forgotten and I forgot who it was who told it to me it was a fellow graduate student in the harvard math department and he said you know i learned one thing being out in the workforce because he was one of the few people who had a work life in the department as a grad student and he said you can be friends with your boss but if you're going to be friends with your boss you have to be doing a good job at work and there's an analog here which is if you're going to be reasonably honest with the population you have to be doing a good job at work as the Surgeon General or as the head of the CDC so if you're doing a terrible job you're supposed to resign and then the next person is supposed to say look I'm not gonna lie to you I inherited the situation it was in a bit of disarray but I had several requirements before I agreed to step in and take the job because I needed to know I could turn it around I needed to know that I had clear lines of authority I needed to know that I had the resources available in order to rectify the problem and I needed to know that I had the ability in the freedom to level with the American people directly as I saw fit all of my wishes were granted and that's why I'm happy here on Monday morning I've got my sleeves rolled up boy do we got a lot to do so please come back in two weeks and then ask me how I'm doing then and I hope to have something to show you that's how you do it so why is that excellence and basic competence missing the big nap you see you come from multiple traditions where it was very important to remember things the Soviet tradition made sure that you remembered the sacrifices that came in that war in the Jewish tradition we're doing this on Passover right okay well every year we tell one simple story well why can't it be different every year maybe we can have a rotating series of sevens do it because it's the one story that you need it's like you know you work with the men in black group right and it's the last suit that you'll ever need this is the last story that you ever need don't think I fell for your neuralyzer last time in any event we tell one story because it's to get out of Dodge story there's a time when you need to not wait for the the bread to rise and that's the thing which is even if you live through a great nap you deserve to know what it feels like to have to leave everything that has become comfortable and and unworkable it's said that you need you need that tragedy I imagine to have the tradition of remembering it's it's sad to to think that because things have been nice and comfortable means that we can't have great competent leaders which is kind of the implied statement like can we have great leaders who take big risks or who inspire hard work who deal with difficult truth even though things have been comfortable well we know what those people sound like I mean you know if for example Jocko willing suddenly threw his hat into the ring everyone would say okay right party's over it's time to get up at 4:30 and really work hard and we've got to get back into fighting shit and yeah but Jocko is a very special I think that whole group of people by profession put themselves in the way of and into hardship on a daily basis and he's not well I don't know but he's probably not going to be okay Jocko be president okay but it doesn't have to be Jocko right like in other words if it was Kyle ne or if it was Alex Honnold from rock-climbing right but they're just serious people they're serious people who can't afford your BS yeah but why do we have serious people that do rock climbing and don't have serious people who lead the nation that that seems because that was a those skills needed in rock climbing are not good during the big nap and at the tail end of the big nap they would get you fired but I don't don't you think there's a fundamental part of human nature that desires to excel to be exceptionally good at your job yeah but what is your job I mean in other words my my point to you is if you if you're a general in a peacetime army and your major activity is playing war games what if the skills needed to win war games are very different than the skills needed to win wars because you know how the war games are scored and you've you've done Moneyball for example with wargames you figured out how to win games on paper so then the the advancement skill becomes divergent from the ultimate skill that it was proxying for yeah but you create this we're good as human beings to I mean I thought at least me I can't do a big nap so at any one moment when I finish something a new dream pops up so right going to Mars go to what do you like to do you like to do Brazilian Jujitsu well first of all I like to do every you like to play guitar guitar you do this podcast you do theory you're always you're constantly taking risks and exposing yourself all right why because you got one of those crazy I'm sorry to say it you got an Eastern European Jewish personality which I'm still tied to and I'm a couple generations more distant than you are and I've held on to that thing because it's valuable to me you don't think there's a huge percent of the populace even in the United States that's that's that oh maybe a little bit doormen but do you know Anna Hutchins from the Red Scare podcast did you interview her yeah yeah yeah yeah yeah she was great she was great right yeah it's just fun she's she's terrific but she also has the same thing going on and I made a joke in the liner notes for that episode which is somewhere on the road from Stalingrad to forever 21 something was lost like how can Stalingrad and forever 21 be in the same sentence and you know in part it's that weird thing it's like trying to remember even words like I mean Russian and Hebrew things like it's like what poem yet and this core you know these words have much more potency about memory and I don't know I do I think I think there's still a dormant populace that craves leaders on a small scan large scale and I hope to be that leader and on a small scale and I think you sir have a role to be a leader you kids go ahead without me I'm just gonna I'm gonna do a little bit of weird podcasting see see now you're you're putting on your Joe Rogan hat he says I'm just a comedian oh no I'm gonna say I'm just it's not that if I say I want to lead too much because of the big nap there's like a group a chorus of automated idiots and they're there first I was like oh I knew it it's a power grab all along why should you leave you know it's just like and so the idea is you're just trying to skirt around not stepping on all of the idiot landmines it's like okay so now I'm gonna hear that in my inbox for the next three days okay so lead by example just live no I mean large platform look we should take over the institutions there are institutions we've got bad leadership we should mutiny and we should inject a 15% 20% disagreeable dissident very aggressive loner individual mutant freaks all the people that you go to see Avengers movies about or the x-men or whatever it is and stop pretending that everything good comes out of some great giant inclusive communal 12-hour meeting it's like stop it that's not how shit happens you recently published the video of a lecture he gave at Oxford presenting some aspects of a theory theory of everything called geometric unity so this was a work of 30 30 plus years this is his life's work let me ask her of the silly old question how do you feel as a human excited scared the experience of posting it you know it's funny one of the one of the things that you you learn to feel as an academic is the great sins you can commit in academics is to show yourself to be a non-serious person to show yourself to have delusions to avoid the standard practices which everyone has signed up for and you know it's weird because like you know that those people are gonna be angry he did what you know why would he do that and and what we're referring to for example as traditions of sort of publishing incrementally certainly not trying to have a theory of everything perhaps working within the academic departments yeah all those things so that's true and so you're going outside of all of that well I mean I was going inside of all of that and we did not come to terms when I was inside and what they did was so outside to me was so weird so freakish like the most senior respectable people at the most senior respectable places were functionally insane as far as I could tell and again it's like being functionally stupid if you're the head of the CDC or something where you know you're giving recommendations out there aren't based on what you actually believe they're based on what you think you have to be doing well in some sense I think that that's a lot of how I saw the math and physics world as the physics world was really crazy and the math world was considerably less crazy just very strict and kind of dogmatic will psychoanalyze those folks but I really want to maybe linger on it a little bit longer of how you feel because yeah so it's such a such a special moment in your life I really appreciate it's a great question so that if we can pair off some of that others those other issues its new being able to say what the observer's is which is my attempt to replace space-time with something that is both closely related to space time and not space-time so I used to carry the number 14 as a closely guarded secret in my life and where 14 is really four dimensions of space and time plus ten extra dimensions of rulers and protractors or four the cool kids out there symmetric to tensors she had a geometric complicated beautiful geometric view of the world that you carry with you for a long time yeah did you did you have friends that you colleagues essentially no talk no in fact part of these part of that some of these stories are me coming out to my friends and I used the phrase coming out because I think that gays have monopolized the concept of the closet many of us are in closets haven't having nothing to do with their sexual orientation yeah I didn't really feel comfortable talking to almost anyone so this was a closely guarded secret and I think that I let on in some ways that I was up to something and probably but it was a very weird life so I did write I have a series of things that I pretended to care about so that I could use that as the stalking horse for what I really cared about and to your point I never understood this whole thing about theories of everything like if you were gonna go into something like theoretical physics isn't that what you would normally pursue like wouldn't it be crazy to do something that difficult and that poorly paid if you we're gonna try to do something other than figure out what this is all about now I have to reveal my cards my weaknesses and lack an understanding of the music of physics and math departments but there's an analogy here to artificial intelligence and often folks come in and say okay so there's a giant department working on quote-unquote artificial intelligence but why is nobody actually working on intelligence like it you're all just building little toys right you're not actually trying to understand and that breaks a lot of people and that they it confuses them it's like okay so I'm at MIT I'm at Stanford I'm at Harvard I'm here I dreamed of being what kind of artificial intelligence why is everybody not actually working on intelligence and I have the same kind of sense that that's what working on the theory of everything is that's strangely you somehow become an outcast for even but we know why this is right why well it's because let's take the artificial it's play with a GI for example yeah I think that the idea starts off with nobody really knows how to work on that and so if we don't know how to work on it we choose instead to work on a program that is tangentially related to it so we do a component of a program that is related to that big question because it's felt like at least I can make progress there and that wasn't where I was where I was in it's funny there was this book of called Friedan uhlan beck and it had this weird mysterious line in the beginning of it and I tried to get clarification of this weird mysterious line and everyone said wrong things and then I said okay well so I can tell that nobody's thinking properly because I just asked the entire department and nobody has a correct interpretation of this and so you know it's a little bit like you see a crime-scene photo and you have a different idea like there's a smoking gun and you figure that's actually a cigarette lighter I don't really believe that and then there's like a pack of cards and you think huh that looks like the blunt instrument that the person was beaten with you know so you have a very different idea about how things go and very quickly you realize that there's no one thinking about them there's a few human-sized to this and technical size both of which I'd love to try to get down to so the human side I can tell from my perspective I think it was before April 1st and April Fool's maybe the day before I forget but I was laying in bed in the middle of the night and somehow it popped up you know i am i feed somewhere that your beautiful face is speaking live and i clicked and you know it's kind of weird how the universe just brings things together in this kind of way and all sudden i realized that there's something big happening in this particular moment is strange like any day on a day like any day and all of a sudden you were thinking of you had this somber tone like you were serious like you were going through some difficult decision and it seems strange I almost thought you were maybe joking but there's a serious decision being made and it was a wonderful experience to go through with you I really appreciate it it was April 1st yeah it was it's kind of fascinating him he's just the whole experience and and and so that I want to ask I mean thank you for letting me be part of that kind of journey of decision-making that took 30 years but why now why did you think why did you struggle so long not to release it and decide to release it now Anna while the whole world is on lockdown an April Fool's is it just because you like the comedy of absurd ways that the universe comes together I don't think so I think that the Cova Depa demmick is the end of the big nap and I think that I actually tried this seven years earlier in Oxford so I and it was too early which part was too is it the the platform because your plight different now actually the Internet I remember you I read several your brilliant answers that people should read for the edge one of them was related to the Internet and it was the first one was it the first one yeah that's a called go virtual young man yeah yeah that seemed that's like forever ago now well that was ten years ago and that's exactly what I did is I decamped to the Internet which is where the portal lives the portal the portal yeah the theme that's ramen esteem music he just listened to forever I actually started recording tiny guitar licks for the audio portion not for the video portion you kind of inspired me with bringing your guitar into the story but keep going you see you thought so the Oxford was like step one you kind of yet you put your foot into the in the water to sample it but it was too cold at the time so you didn't want to step in just really disappointed what was disappointing about that experience very is it's a hard thing to talk about it has to do with the fact that and I can see this in this you know as mirrors a disappointment within myself there are two separate issues one is the issue of making sure that the idea is actually heard and explored and the other is the is the question about will I become disconnected from my work because it will be ridiculed it will it will be immediately improved it will be found to be derivative of something that occurred in some paper in 1957 when the community does not want you to gain a voice it's a little bit like a policeman deciding to weirdly and enforce all of these little-known regulations against you and you know sometimes nobody else and I think that's kind of you know this weird thing where I just don't believe that we can reach the final theory necessarily within the political economy of academics so if you think about how academics are tortured by each other and have their paid and where they have freedom and where they don't I actually weirdly think that that system of selective pressures is going to eliminate anybody who's going to make real progress so that's interesting so if you look at the story of Andrew Wiles for example with from last Last Theorem he as far as I understand he pretty much isolated himself from the world of academics in terms of the big with the bulk of the work he did and it from my perspective is dramatic and fun to read about but it seemed exceptionally stressful the first step he took the first steps he took when actually making the work public that's him to me would be hell now but it's like so artificially dramatic you know he leads up to it at a series of lectures he doesn't want to say it and then he finally says it at the end because obviously this comes out of a body of work where I mean the funny part about for Moz le'ts theorem is that wasn't originally thought to be a deep and meaningful problem it was just an easy to state one that had gone unsolved but if you think about it it became attached to the body of regular theory so he built up this body of regular theory gets all the way up to the end announces and then like there's this whole drama about okay somebody's checking the proof I don't understand what's going on on line 37 you know and like oh is this serious seems a little bit more serious than we knew I mean do you see parallels you share the concern that the year your experience might be something similar well in his case I think that if I recall correctly his original proof was unsalvageable he actually came up with a second proof with a colleague Richard Taylor and it was that second proof which carried the day so it was a little bit that he got put under incredible pressure and then had to succeed in a new way having failed the first time which is like even a weirder and stranger store has an incredible story in some sense but I mean a you I'm trying to get a sense of the kind of stress I think this is okay but I'm rejecting what I don't think people understand with me is the scale of the critique it's like I don't you people say well you must implicitly agree with this and implicitly agree it's like now try me ask before you you decide that I am mostly an agreement with the community about how these things should be handled or what these things mean keo keo and also just why this criticism matter so much here so you seem to dislike the burden of criticism that it will choke away all a lot of different kinds of criticism there's constructive criticism and there's destructive criticism and what I don't like is I don't like a community that can't first of all like if you take the physics community just the way we screwed up on masks in PPE just the way we screw it up in the financial crisis and mortgage-backed securities we screw it up on string theory can we just forget the string theory happened or sure but let if somebody should say that right somebody should say you know it didn't work out yeah but okay but you're asking this like why do you guys get to keep the prestige after failing for 35 years that's an interesting point you guys because to me where the profession look these things if there is a theory of everything to be had right it's going to be a relatively small group of people where this will be sorted out absolutely it's it's it's not tens of thousands it's probably hundreds at the top but within that within that community there's the assholes mm-hmm there's the I mean you have you always in this world have people who are kind open my mind is it's a question about okay let's imagine for example that you have a story where you believe that ulcers are definitely caused by stress and you've never questioned it or maybe you felt like the Japanese came out of the blue and attacked us at Pearl Harbor right and now somebody introduces a new idea to you which is like what if it isn't stress at all or what if we actually tried to make resource start of Japan attack us somewhere in the Pacific so we could have cast a spell I to enter the Asian theater in persons original ideas like what what do you even say you know it's like two crazy well when Dirac in 1963 talked about the importance of beauty as a guiding principle in physics and he wasn't talking about the scientific method that was crazy talk but he was actually making a great point and he was using Schrodinger and I think it was Schrodinger was standing in for him and he said that if your equations don't agree with experiment that's kind of a minor detail if they have true beauty in them you should explore them because very often the agreement with experiment is that it's an issue of fine tuning of your model of the instantiation and so it doesn't really tell you that your model is wrong and of course Heisenberg told Dirac that his model was wrong because that the proton and the electron should be the same mass if they are each other's antiparticles and that was a an irrelevant kind of silliness rather than a real threat to the Dirac theory but okay so I'm amidst all this silliness hmm I'm hoping that we could talk about the journey that geometric unity has taken and will take as an idea and an idea that will see the light yeah that so first of all let's I'm thinking of writing a book called geometric unity for idiots okay and I need you as a consultant so can we first of all I hope I have the trademark on geometric units you do good can you give a basic introduction of the goals of geometric unity the basic tools of mathematics use the viewpoints in general for idiots Sharik me okay great fun so what's the goal of geometric unity the goal of geometric unity is to start with something so completely bland that you can simply say well that's a something that begins the game is as close to a mathematical nothing as possible in other words I can't answer the question why is there something rather than nothing but if there has to be a something that we begin from let it begin from something that's like a blank canvas that's even more basic so what is something what are we trying to describe okay right now we have a model of our world and it's got two sectors one of the sector's is called general relativity and the other is called the standard model so we'll call it gr for general relativity and SM for standard model what's the difference you need to what did the two describe so general relativity gives pride of place to gravity and everything else is acting is a sort of a backup singer gravity is the star of the show gravity is the star of general relativity and in the standard model the other three non-gravitational forces so if there are four forces that we know about three of the four non-gravitational that's where they get to shine great so tiny little particles and how they interact with each other so photons gluons and so-called intermediate vector bosons those are the things that the standard model showcases and general relativity showcases gravity and then you have matter which is accommodated in both theories but much more beautifully inside of the standard model so what what is a theory of everything do so about that so first of all I think that that's that that's the first place where we haven't talked enough we assume that we know what it means but we don't actually have any idea what it means and what I claim it is is that it's a theory where the questions beyond that theory are no longer of a mathematical nature in other words if I say let us take X to be a four dimensional manifold to a mathematician or physicist I've said very little I've simply said there's some place for calculus and linear algebra to to dance together and to play and that's what manifolds are they're the most natural place where that where our two greatest math theories can really intertwine which are that you own the tacos the linear algebra okay now the question is beyond that so it's sort of like saying I'm an artist and I want to order a canvas now the question is does the canvas paint itself does the can't does the canvas come up with an artist and an in paint in ink which then paint the canvas like that's the that's the hard part about theories of everything which I don't think people talk enough about okay can we just you bring up a sure and then to hand the draws itself is a the fire that lights itself or drawing hands the drawing hands yeah and every time I start to think about that my mind like shuts down no don't do that it there's a spark and this is the most beautiful part we know it's beautiful but this robots brain sparks fly so can we try to say the same thing over and over in different ways about what what would he mean by that having to be a thing we have to contend with sure like why why do you think that understand creating a theory of everything as you call the source code our understanding our source code require a view like the hand that draws itself okay well here's what goes on in the regular physics picture we've got these two main theories general relativity and the standard model right think of general relativity as more or less the theory of the canvas okay maybe you you have the canvas in a particularly rigid shape maybe you've measured it so it's got length and it's got an angle but more or less it's just canvas and length and angle and that's all that there's really general relativity is but it allows the canvas to warp a bit then we have the second thing which is this import of foreign libraries where it which aren't tied to space and time so we've got this crazy set of symmetries called su 3 cross su 2 cross u 1 we've got this collection of 16 particles in a generation which are these sort of twisted spinners and we've got three copies of them then we've got this weird Higgs field that comes in and like deus ex machina solves all the problems that have been created in the play that can't be resolved otherwise that's the standard model of quantum field theory just plopped on top yes it's a problem of the the double origin story one origin story is about space and time the other origin story is about what we would call internal quantum numbers and internal symmetries and then there was an attempt to get one to follow from the other called Kaluza klein theory which didn't work out and this is sort of in that vein so you said origins story so in the hand that draws itself what is it so it's it's as if you had the canvas and then you ordered up also give me paint brushes paints pigments pencils and artists but you're saying that's fucked like if you want to create a universe from scratch the canvas should be generating the paintbrushes and the paintbrush and they are turning the canvas yeah yeah right like usually who's the artist in this analogy well this is sorry then we're gonna get to do a religious thing I don't wanna do that okay well you know my shtick which is that we are the AI we have two great stories about the simulation and artificial general intelligence in one story man fears that some program we've given birth to will become self-aware smarter than us and will take over in another story there are genius simulators and we live in their simulation and we haven't realized that those two stories are the same story in one case we are the simulator and another case we are the simulated and if you buy those and you put them together we are the AGI and whether or not we have simulators we may be trying to wake up by learning our own source code so this could be our Skynet moment which is one of the reasons I have some issues around it I think we'll talk about that because I well that's the issue of the emergent artists within the story yeah just to get back to the point okay so so now the key point is the standard way we tell the story is is that Einstein sets the canvas and then we order all the stuff that we want and then that paints the picture that is our universe so you order the the paint you order the artist you order the brushes and that then when you collide the two gives you two separate origin stories the canvas came from one place and everything else came from somewhere else so what are the mathematical tools required to to construct consistent geometric theory you know make this concrete well somehow you need to get three copies for example of generations with 16 particles each right and so the question would be like well there's a lot there's a lot of special personality in those symmetries where would they come from so for example you've got what would be called grand unified theories that sound like su5 the Georgia a theory there's something that should be called spin ten but physicists insist on calling it s o ten there's something called the petit Salam theory that tends to be called su 4 across su 2 cross su 2 which should be called spin six crust spin four I can get into all of these but what are they all accomplishing they're all taking the known forces that we see and packaging them up to say we can't get rid of the second origin story but we can at least make that origin story more unified so they're trying-- grand unification is the attempt that's a mistake in your in you've got a mistake that the problem is it was born lifeless when when Georgia and glasha first came out with the su5 theory it was very exciting because it could be tested in a South Dakota mind filled up with like cleaning fluid or something like that and they look for proton decay and didn't see it and then they gave up because in in that day when your experiment didn't work you gave up on the theory it didn't come to us born of a fusion between Einstein and and and Bohr you know and that was kind of the problem is it had this weird parenting where it was just on the Bohr side there was no Einstein Ian's contribution Lex how can I help you most I'm right here what questions you want to ask so that the most satisfying answers there's there's a there's a bunch there's a bunch of questions I want to ask I mean one and I'm trying to sneak up on you somehow to reveal in an accessible way then the nature of our universe so I can just give you a guess right like I we have to be very careful that we're not claiming that this has been accepted this is a speculation but I will I will make the speculation that what I think what you would want to ask me is how can the canvas generate all the stuff that usually has to be ordered separately all right should we do that let's go there okay so the first thing is is that you have a concept in computers called technical debt you're coding and you cut corners and you know you're gonna have to do it right before the thing is safe for the world but you're piling up some series of i/o used to yourself and your project as you're going along so the first thing is we can't figure out if you have only four degrees of freedom and that's what your canvas is how do you get at least in Stan's world Einstein says look it's not just four degrees of freedom but there need to be rulers and protractors to measure length and angle in the world you can't just have a flabby four degrees of freedom so the first thing you do is you create ten extra variables which is like if we can't choose any particular set of rulers and protractors to measure length and angle let's take the the set of all possible rulers and protractors and that would be called symmetric non-degenerate two tensors on the tangent space of the four manifold X for now because there are four degrees of freedom you start off with four dimensions then you need four rulers for each of those different directions so that's four that gets us up to eight variables and then between four original variables there are six possible angles so four plus four plus six is equal to 14 so now you've replaced x4 with another space which in the lecture I think I called you 14 but are now calling Y 14 is one of the big problems of working on something in private is every time you pull it out you sort of can't remember it you name something something new okay so you've got a fourteen dimensional world which is the original four dimensional world plus a lot of extra gadgetry for measurement and because you're not in the four dimensional world you don't have the technical debt is no now you've got a lot of technical debt because now you have to explain away a fourteen dimensional world which is a big you're taking a huge advance on your pay day check alright but aren't more dimensions allow you more freedom says I mean maybe but you have to get rid of them somehow because we don't perceive them so eventually have to collapse it down to the thing that we perceive or you have to sample a four dimensional filament within that fourteen dimensional world known as the section of a bundle ok so how do we get from the fourteen dimensional world where I imagine a lot of folate yeah you're cheating the first question was how do we get something from almost nothing like how do we get the if I've said that the who and the what in the newspaper story that is a theory of everything are bosons and fermions so let's make the who the fermions and the what the bosons think of as the players and the equipment for a game are we supposed to be thinking of actual physical things with mass or energy okay so they think about everything you see in this room so from chemistry you know it's all protons neutrons and electrons but from a little bit of not late 1960s physics we know that the protons and neutrons are all of up quarks and down quarks so everything in this room is basically up quarks down quarks and electrons stuck together with with the the what the equipment okay now the way we see it currently is we see that there are space-time indices which we would call spinners that correspond to the whoo that is the fermions the matter the stuff the up quarks the down quarks the electrons and there are also 16 degrees of freedom that come from this in the space of internal quantum numbers so in my theory in fourteen dimensions there's no internal quantum number space that figures in it's all just spin oreal so spinners in fourteen dimensions without any festooning with extra linear algebraic information there's a concept of a of spinners which is natural if you have a manifold with length and angle and y 14 is almost a manifold with length and angle it's it's so close it's in other words because you're looking at the space of all rulers and protractors maybe it's not that surprising that a space of rulers and protractors might come very close to having rulers and protractors on it itself like can you measure the space of measurements and you almost can and in a space that has length and angle if it doesn't have a topological obstruction comes with these objects called spinners now the spinners are the stuff of of our world we are made of spinners they're the most important really deep object that I can tell you about they were very surprising what is this spinner so famously there are these weird things that require 720 degrees of rotation in order to come back to normal and that doesn't make sense and be the reason for this is that there's a knotted miss in our three-dimensional world that people don't observe and then you know you can famously see it by this Dirac string trick so if you take a glass of water imagine that this was a tumbler and I didn't want to spill any of it and the question is if I rotate the cup without losing my grip on the base 360 degrees and I can't go backwards is there any way I can take a sip and the answer is this weird motion which is go over first and under second and that that's 720 degrees of rotation to come back to normal so that I can take a set well that weird principle which sometimes is known as the Philippine wineglass dance because waitresses in the Philippines apparently learned how to do this that that move defines if you will this hidden space that nobody knew was there of spinors which Dirac figured out when he took the square root of something called the klein-gordon equation which I think had earlier work incorporated from carton and killing in company in mathematics so the spinners are one of the most profound aspects of human existence and you forgive me for the perhaps dumb questions but what a spinner be the mathematical objects that's the basic unit of our universe when you when you start with a manifold which is just like something like a doughnut or a sphere circle or a Mobius band a spinner is usually the first wildly surprising thing that you found was hidden in your original purchase so you you order a manifold and you didn't even realize it's like buying a house and finding a panic room inside that you hadn't counted on it's very surprising when you understand that spinners are running around on your spaces again perhaps a dumb question but we're talking about 14 dimensions and four dimensions what is the manifold or operating under in my case it's proto space it's before it's before Einstein can slap rulers and protractors on space time and what you mean by that sorry to interrupt is space time is the 4d manifold space-time is a four dimensional manifold with extra structure most the extra structure it's called a semi Romanian or pseudo Romani and metric in in essence there is something akin to a four by four symmetric matrix from which is equivalent to length and angle so when I talk about rulers and protractors or I talk about length and angle or I talk about romani and or pseudo Romani and or semi Romani and met manifolds I'm usually talking about the same thing can you measure how long something is and what the angle is between two different rays or vectors so that's what Einstein gave us as his arena his place to play his his canvas so there's a bunch of questions I can ask here but like I said I'm working on this book geometric unity for he it's and I think what would be really nice as your editor to have like beautiful maybe even visualizations that people could try to play with try to try to reveal small little beauties about the way you're thinking about the squirrel I'll usually use the Joe Rogan program for that sometimes I have him doing the Philippine wine glass dance I had the hopf fibration the part of the problem is is that most people don't know this language about spinners bundles metrics gauge fields and they're very curious about the theory of everything but they have no understanding of even what we know about our own world is it hole is it a hopeless pursuit so like even gauge theory right just this I mean it seems to be very inaccessible is there some aspect of it that could be made accessible I'm actually go to the board right there and give you a five minute lecture on engaged theory that would be better than the official lecture engaged there you would know what gauge there was so it is it's possible to make it accessible yeah but nobody does like in other words you're gonna watch over the next year lots of different discussions of a quantum entanglement or you know the multiverse where are we now right or you know many worlds are they all equally real yeah did that right I mean yeah that that's it but you're not gonna hear anything about the hopf fibration except if it's from me and I hate that why why can't you be the one but because I'm going a different path I think that we've made a huge mistake which is we have things we can show people about the actual models we can push out visualizations where they they're not listening my analogy they're watching the same thing that we're seeing and as I've said to you before this is like choosing to perform sheet music that hasn't been performed in a long time or you know the experts can't afford orchestras so they just trade Beethoven symphonies and as sheet music and they oh wow that was beautiful but it's like nobody heard anything they just looked at the score well that's how mathematicians and physicists trade papers and ideas is that they they write down the things that represent stuff I want to at least close out the thought line that you started yes which is how does the canvas order all of this other stuff into being so I at least like I say some incomprehensible things about that and then we'll we'll have that much done all right and that just point does it have to be incomprehensible do you know what the Schrodinger equation is yes do you know what the Dirac equation is what does know mean well my point is you're gonna have some feeling that you know what the Schrodinger equation yes as soon as we get to the Dirac equation your eyes are gonna get a little bit glazed right so now why is that well the answer to me this is that you you want to ask me about the theory of everything but you haven't even digest the theory of everything as we've had it since 1928 when Dirac came out with his equation so for whatever reason and this isn't a hit on you yeah you haven't been motivated enough in all the time that you've been on earth to at least get as far as the Dirac equation and this was very interesting to me after I gave the talk in Oxford New Scientist who'd done kind of a hatchet job on me to begin with sent a reporter to come to the third version of the talk that I gave and that person had never heard of the Dirac equation so you have a person who was completely professionally not qualified to ask these questions wanting to know well how does how does your theory solve new problems like well in the case of the Dirac equation well tell me about that I don't know what that is so then the point is okay I got it you're not even caught up minimally to where we are now and that's not a knock on you almost nobody is yeah but how does it become my job to digest what has been available for like over 90 years well to me the open question is whether what's been available for over 90 years can be there could be a a blueprint of a journey that one takes to understand it not oh I want to do that with you and I I one of the things I think I've been relatively successful at for example you know when you ask other people what gauge theory is you get these very confusing responses and my response is much simpler it's oh it's a theory of differentiation where when you calculate the instantaneous rise over run you measure the rise not from a flat horizontal but from a custom endogenous reference level what do you mean by that it's like okay and then I do this thing with Mount Everest which is man Everest is how high then they give the height I say above what then they say sea level and I say which sea is that in Nepal like oh I guess there isn't a sea cuz it's landlocked it's like okay well what do you mean by sea level oh there's this thing called the geoid I'd never heard of oh that's the reference level it's a custom reference level that we imported so you all sorts of people have remembered the exact height of Mount Everest without ever knowing what it's a height from well in this case in gauge Theory there's a hidden reference level where you measure the rise in rise over run to give the slope of the line what if you have different concepts of what of where that rise should be measured from that vary within the theory that are endogenous to the theory that's what gauge theory is okay we have a video here right yeah okay I'm gonna use my phone if I want to measure my hand and its slope this is my attempt to measure it using standard calculus in other words the reference level is apparently flat and I measure the rise above that phone using my hand okay if I want to use gauge theory it means I can do this or I can do that or I can do this or I can do this or I could do what I did from the beginning okay at some level that's what gauge theory is now that is an act no I've never heard anyone describe it that way so while the community may say well who is this guy and why does he have the right to talk in public I'm waiting for somebody to jump out of the woodwork and say you know Eric's whole shtick about rulers and protractors leading to a derivative derivatives are measured as rise over run above a reference level of reference levels don't fit to get like I go through this whole shtick in order to make it accessible I've never heard anyone say it I'm trying to make the Prometheus would like to discuss fire with everybody else all right I'm gonna just say one thing to close out the earlier line which is what I think we should have continued with when you take the naturally occurring spinners the unadorned spinners the naked spinners not on this fourteen dimensional manifold but on something very closely tied to it which I've called the chimeric tangent bundle that is the the object which stands in for the thing that should have had length and angle on Abbott just missed okay when you take that object and you form spinners on that and you don't adorn them so you're still in the single origin story you get very large spin oriole objects upstairs on this 14 dimensional world y 14 which is part of the observers when you pull that information back from y 14 down to X 4 it miraculously looks like the adorned spinners the festooned spinners the spinners that we play with in ordinary reality in other words the 14 dimensional world looks like a four dimensional world plus a 10 dimensional complement so 10 plus 4 equals 14 that 10 dimensional complement which is called a normal bundle generates spin properties internal quantum numbers that look like the things that give our particles personality then make let's say up quarks and down quarks charged by negative one-third or plus two thirds you know that kind of stuff or whether or not you know some quarks feel the weak force and other quarks do not so the x4 generates Y 14 y 14 generates something called the chimeric tangent bundle chimeric tangent bundle generates unadorned spinners the unadorned spinners get pulled back from 14 down to 4 where they look like adorned spinners and we have the right number of them you thought you needed 3 you only got 2 but then something else that you've never seen before broke apart on this journey and it broke into another copy of the thing that you already have two copies of one piece of that thing broke off so now you have two generations plus an imposter third generation which is I don't know why we never talked about this possibility in regular physics and then you've got a bunch of stuff that we haven't seen which has descriptions so people always say does it make any falsifiable predictions yes it does it says that the matter that you should be seeing next has particular properties that can be read like like we guys to spend weak hypercharge like the responsiveness to the strong force the one I can't tell you is what energy scale it would happen it say you would if you can't say if those characteristics can be detected with current it may be that somebody else can I'm not a physicist I'm not a quantum field theory I can't I I don't know how you would do that the the hope for me is that there's some simple explanations for all of it Lex should we have a drink you're having fun no I'm trying to have fun with you you know I had there's a bunch of fun things to talk about here anyway that was how I got what I thought you wanted which is if you think about the fermions as the artists and the bosons as the brushes and the paint what I told you is that's how we get the artists what are the open questions for you in this what were the challenges so you're not done well there's the things that I would like to have in better order so a lot of people will say see the reason I hesitated on this is I just have a totally different view than the community so for example I believe that general relativity began in 1913 with Einstein and Grossman now that was the first of like four major papers in this line of thinking to most physicists general relativity happened when Einstein produced a divergence free gradient which turned out to be the gradient of the so-called Hilbert or Einstein Hilbert action and from my perspective that wasn't true is is that it began when Einstein said look this is about differential geometry and it's the final answer is going to look like a curvature tensor on one side and matter and energy on the other side and that was enough and then he published a wrong of it where it was the Ricci tensor not the Einstein tensor then he corrected the reach the Ricci tensor to make it into the Einstein tensor then he corrected that to add a cosmological constant I can't stand that the community thinks in those terms there's some things about which like that there's a question about which contraction do I use there's an Einstein contraction there's a Ricci contraction they both go between the same spaces I'm not sure what I should do I'm not sure which contraction I should choose this is called a Shia operator for ship-in-a-bottle and my stuff you have this big platform in many ways that inspires people's curiosity about physics yeah automatics right now and I'm one of those people and great but then you start using a lot of words that I don't understand and like I might know them but I don't understand and what's unclear to me if I'm supposed to be listening to those words or if it's just if this is one of those technical things that's intended for a very small community or if I'm supposed to actually take those words and start you know a multi-year study not not a serious study but a the kind of study when you you're interested in learning about machine learning for example or any kind of discipline that's where I'm a little bit confused so you you speak beautifully about ideas you often reveal the beauty in Mathematica matauri and I'm unclear and what are the steps I should be taking I I'm curious how can I explore how can i play with something how can i play with these ideas well and and enjoy the beauty of not necessarily understanding the depth of a theory that you're presenting but start to share in the beauty as opposed to sharing in and enjoying the beauty of just the way the passion with which you speak which is in itself fun to listen to but also starting to be able to understand some aspects of this theory that I can enjoy it too and start to build an intuition what the heck we're even talking about because you're basically saying we need to throw a lot of our ideas of views of the universe out and I'm trying to find accessible ways in okay long not in this conversation no I appreciate that so one of the things that I've done is I've picked on one paragraph from Edward Witten and I said this is the paragraph if I could only take one paragraph with me this is the one I'd take and it's almost all in prose not an equation and he says look this is this is our knowledge of the universe at its deepest level and he was writing this during the 1980s and he has three separate points that constitute our deepest knowledge and those three points refer to equations one to the Einstein field equation one to the Dirac equation and one to the yang-mills Maxwell equation now one thing I would do is take a look at that paragraph and say okay what do these three lines mean like it's a finite amount of verbiage you can write down every word that you don't know you can say what do I think done now young man yes there's a beautiful wall in Stoneybrook New York built by someone who I know you will interview named Jim silence and Jim silence and he's not the artist but he's the guy who funded an world's greatest hedge fund manager and on that wall contained the three equations that Witten refers to in that paragraph and so that is the transmission from the paragraph or graph to the wall now that wall needs an owner's manual which Roger Penrose has written called the road to reality let's call that the tome so this is the subject of the so-called graph wall tome project that is going on in our discord server and our general around the portal community which is how do you take something that purports in one paragraph to say what the deepest understanding man has of the universe in which he lives it's memorialized on a wall which nobody knows about which is an incredibly gorgeous piece of art and that was written up in a book which is has been written for no man right maybe if maybe it's for a woman I don't know but no no one should be able to read this book because either you're a professional and you know a lot of this book in which case it's kind of a refreshers to see how Roger thinks about these things or you don't even know that this book is a self-contained invitation to understanding our deepest nature so I would say find yourself in the graph wall tome transmission sequence and join the graph wall tome project if that's of interest okay beautiful now just to linger on a little longer what kind of journey do you see geometric unity taking I don't know I mean that's the thing is that first of all the professional community has to get very angry and outraged and they have to work through their feelings this is nonsense this is bullshit or like no wait a minute this is really cool actually I need some clarification over here so there's going to be some sort of weird coming back together process are you already hearing murmurings of that it was very funny officially I've seen very little so it's perhaps happening quietly yeah you often talk about we need to get off this planet yep can I try to sneak up on that by asking what in your kind of view is the difference the gap between the science of it theory and the actual engineering of building something that leverages the theory to do something like how big is that we don't know gap I mean if you have ten extra dimensions to play with that are the rulers and protractors of the world themselves can you gain access to those dimensions do you have a hunch so I don't know I don't want to get ahead of myself because the you have to appreciate I can have hunches and I can I can jaw off but one of the ways that I'm succeeding in this world is to not bow down to my professional communities nor to ignore them like I'm actually interested in the criticism I just wanted denature it so that it's not personally interpersonal and irrelevant I believe that they don't want me to speculate and I don't need to speculate about this I can centrally say I'm open to the idea that it may have engineering prospects and it may be a death sentence we may find out that there's not enough new here that even if it were right that there would be nothing new to do can't tell you that's what you mean by death sentences there would not be exciting breakthrough terrible if you couldn't like you can do new things in an Einsteinian world that you couldn't do in a Newtonian world right you know like you have twin paradoxes or Lorentz contraction of length or any one of a number of new cool things happen in relativity theory that didn't happen for Newton what if there wasn't new stuff to do at the next and final level so that would be quite sad let me ask a silly question but we'll say it with a straight face impossible so let me mention Elon Musk what are your thoughts about he's more you're more on the physics theory side of things he's more in the physics engineering side of things in terms of SpaceX efforts what do you think of his efforts to uh get off this planet well I think he's the other guy who's sent me serious about getting off this planet I think they're two of us were semi serious about getting off the planet what do you think about his methodology and yours when you look at them don't and I don't be against you because like I was so excited that like your top video was reycarts file and then I did your podcast and we had some chemistry so it's oom DUP yeah and I thought okay I'm gonna betray curse sauce so just as I'm coming up on Ray Kurzweil like and now Alex Friedman special Elon Musk and he blew me out of the water so I don't want to be petty about it I want to say that I don't could I am yeah okay because the funny part he's not taking enough risk like he's trying to get us to Mars imagine that he got us to Mars the moon and we'll throw in Titan and know we're good enough the diversification level is too low now there's a compatibility first of all I don't think he Lana's serious is about Mars I think Elon is using Mars as a narrative as a stories and to make the moon jealous it makes it I think he's using it as a story to organize us to reacquaint ourselves with our need for space our need to get off this planet it's a concrete thing he's shown that many people think that he's shown that he's the most brilliant and capable person on the planet I don't think that's what he showed I think he showed that the rest of us have forgotten our capabilities so he's like the only guy who has still kept the faith and is like what's wrong with you people so you think the lesson we should draw from Elon Musk is there's a is a capable person within within a lot of us you on make sense to me in what way he's doing what any sensible person should do he's trying incredible things and he's partially succeeding partially failing to try to solve the obvious problems before uh yeah you know but he comes up with things like you know I got it we'll come up with a battery company but batteries aren't sexy so well we'll make a car around it like great you know or any one of a number of things Elon is behaving like a same person and I view everyone else's insane and my feeling is is that we really have to get off this planet we have to get out of this we have to get out of the neighborhood tilling I know a little bit do you think that's a physics problem or an engineering problem he's a cowardice problem I think that we're afraid that we had 400 hitters of the mind like Einstein in Dirac and that that era is done and now we're just sort of copy editors so some of it money like if we become brave enough yeah go outside the solar system can we afford to financially well I think that's not really the issue the issue is look what Elon did well he amassed a lot of money and then he you know he plowed it back in and he spun he spun the wheel and he made more money and now he's got fu money now the problem is is that a lot of the people who have fu money are not people whose middle finger you ever want to see I want to see you Long's middle finger I want to see what I mean by that or like when you say fuck it I'm gonna do the biggest go see whatever the fuck you want Yeah right fuck you fuck anything that gets in his way that he can afford to push out of his way and you're saying he's not actually even doing that enough no I mean he's not going please I want to go Elon is doing fine with his money I just want him to enjoy himself have the most you know die nice you know but you're saying Mars is playing it safe he doesn't know how to do anything else he knows rockets yeah and he might know some physics at a fundamental level yeah I guess okay just let me just like go right back to you how much physics do you really how much brilliant breakthrough ideas on the physics side do you need to get off this planet I don't know and I don't know whether like in my most optimistic dream I don't know whether my stuff gets us off the planet but it's hope it's hope that there's a more fundamental theory that we can access that we don't need you know whose elegance and beauty will suggest that this is probably the way the universe goes like you have to say this weird thing which is this I believe and this I believe is a very dangerous statement but this I believe I believe that my theory points the way now Elon might or might not be able to access my theory I don't know I don't know what he knows but keep in mind why are we all so focused on you on it's really weird it's kind of creepy to what he's just a person who's just asking the the obvious questions and doing whatever he can but he makes sense to me you sent craig venter makes sense to me Jim Watson makes sense to me but we're focusing on Elon because he's he somehow is rare well that's the weird thing like we've come up with a system that eliminates all Elon from our pipeline and Elon somehow snuck through when they were quality adjusting everything you know and this this idea of of disk I distributed idea suppression complex yeah is that what's bringing the in-laws of the world down you know so funny it's like he's asking Joe Rogan like is that a joint you know it's like well what will happen if I smoke it what will happen to the stock price what will happen if I scratch myself in public what will happen if I say what I think about Thailand or kovat or who knows what and everybody's like don't say that say this go do this go do that well it's crazy-making it's absolutely crazy making and if you think about what we put through people through we need to get people who can use fu money the fu money they need to insulate themselves from all of the people who know better because the my nightmare is is that why did we only get one ilan what if we were supposed to have thousands and thousands of yuan and the weird thing is like this is all that remains you're looking at like obi-wan and Yoda and it's like this is the only this is all that's left after X order 66 has been executed and that's the thing that's really upsetting to me is we used we used to have Ilan's five deep and then we could talk about Elon in the context of his cohort but this is like if you were to see a raph in the Arctic with no trees around you'd think why the long neck what a strange sight you know how do we get more lawns how do we change these so I think the useful so we know MIT yeah and Harvard so can maybe returning to our previous conversation my sense is that the Ilan's of the world are supposed to come from MIT in Harvard right and how do you change let's think of one that MIT sort of killed have any names in mind Aaron Schwartz leaps to my mind yeah okay are we MIT supposed to shield the Aaron Schwartz's from I don't know journal publishers or are we supposed to help the journal publishers so that we can throw 35 year sentences in his face or whatever it is that we did that depressed him okay so here's my point yeah I want MIT to go back to being the home of Aaron Schwartz and if you want to send Aaron Schwartz to a state where he's looking at 35 years in prison or something like that you are my sworn enemy you are not MIT yeah you are the traitorous irresponsible middlebrow pencil-pushing green eyeshade fool that needs to not be in the seat at the presidency of MIT period the end get the fuck out of there and let one of our people sit in that chair and think that you've articulated is that the people in those chairs are not the way they are because they're evil or somehow morally compromised is that it's just that that's the distributed nature is that there's some kind of aspect of the system there's people who width emselves to the system they adapt every instinct and the fact is is that they're not going to be on Joe Rogan smoking a blunt that let me ask a silly question do you think institutions generally just tend to become that no we get some of the institution we get Caltech here's what we're supposed to have we're supposed to have Caltech we're supposed to have a read we're supposed to have Deep Springs we're supposed to have MIT we're supposed to have a part of Harvard and when the sharp elbow crowd comes after the Scheldt sharp mine crowd we're supposed to break those sharp elbows and say don't come around here again so what are the weapons that the sharp mines are supposed to use in our modern day so to reclaim MIT what is the what's the future are you kidding me first of all assume that this is being seen at MIT hey everybody is OK hey everybody try to remember who you are you're the guys who put the police car on top of the great dump you you guys came up with the great breasts of knowledge you created a Tetris game in the green building now what is your problem they killed one of your own you should make their life a living hell you should be the ones who keep the mayor memory of Aaron Schwartz alive and all of those hackers and all of those mutants you know it's like it's either our place or it isn't and if we have to throw 12 more pianos off of the roof right if Harold Edgerton is taking those photographs you know with slow-mo back in the 40s if Noam Chomsky's on your faculty what the hell is wrong with you kids you are the most creative and insightful people and you can't figure out how to defend Aaron Schwartz that's on you guys so some of that is giving more power to the young like you said you know it's a brazing towel rub taking power from the feeble and the middle Brown yeah but how do you what is the mechanism to me I don't know you you have some 9-volt batteries no copper wire I attend to you have a capacitor I tend to believe you have to create an alternative and make the alternative so much better that it makes MIT obsolete unless they change and that's what forces change so supposed took somehow okay so use projection mapping most projection mapping where you take some complicated edifice and you map all of its planes and then you actually project some unbelievable graphics rescanning a building let's say at night say okay so you want to do some graffiti art with you basically want to hack the system know when I say look listen to me Lee yeah we're smarter than they are and they you know what they say they say things like I think we need some geeks get me two PhDs right you treat phd's like that that's a bad move PhDs are capable and we act like our job is to peel grapes for our betters yeah that this is strange thing and I you speak about it very eloquently is how we treat basically the greatest minds in the world which is like at at their prime which is PhD students like that we pay them nothing we I'm done with it yeah right we gotta take what's ours so it so yeah take back MIT become uncover nerble become uncover noble and by the way when you become uncover nerble don't do it by throwing food don't do it by pouring salt on the lawn like a jerk do it through brilliance because what you Caltech and MIT can do and maybe Rensselaer Polytechnic or Wooster politic I don't know Lehigh goddamnit what's wrong with you technical people you act like you're a servant class it's unclear to me how you reclaim it except with brilliance like you said but to me that the way you were claimed it was brilliant Segal system Aaron Schwartz came from the Elon Musk class what you guys gonna do about it right if super capable people need to flex need to be individual they need to stop giving away all their power to you know is like Geist or a community or this or that you're not you're not indoor cats your outdoor cats go be outdoor cat do you think we're gonna see this this kind of asking me you know before like what about the World War two generation right when I'm trying to say is that there's a technical revolt coming here's you weren't talking about that I'm trying to lead it yeah I'm trying to see no you're not trying a lot you're trying to get a blueprint here all right Lex yeah how angry are you about our country pretending that you and I can't actually do technical subjects so that they need an army of kids coming in from four countries in Asia it's not about the four countries in Asia it's not about those kids it's about lying about us that we don't care enough about science and technology that we're incapable of it as if we don't have Chinese and Russians and Koreans and Croatians like we've got everybody here the only reason you're looking outside is is that you want to hire cheap people from the family business because you don't want to pass the family business on and you know what you didn't really build the family business it's not yours to decide you the boomers and you the Silent Generation you did your bit but you also followed a lot of stuff up and your custodians you are caretakers you were supposed to hand something what you did instead was to gorge yourself on cheap foreign labor but you then held up as being much more brilliant than your own children which was never true but I'm trying to understand how we create a better system without anger without revolution no not not by kissing and hugs and and but by I mean I don't understand within MIT what the mechanism of building a better MIT is we're not gonna pay Elsevier Aaron Schwartz was right JSTOR is an abomination but why who would then MIT who within institutions is going to do that when just like you said the people who are running the show are more senior and if Frank will check to speak out so year is basically individuals that step up I mean one of the surprising things about Elon is that one person can inspire so much he's got academic freedom it just comes from money I don't agree with that do you think money okay so yes certainly sorry an testicle you yes but those are more important than money right or guts I I think I do agree with you you speak about this a lot that because the money in the academic institutions has been so constrained that people are misbehaving in in in horrible yes but I don't think that if we reverse that and give a huge amount of money people will also behave well I think it also takes guts so you need to give people security security yeah like you need to know there you have a job yeah on Monday when on Friday you say I'm not so sure I really love diversity and inclusion and somebody's looking wait what you didn't love diverse we had a statement on diversity and you wouldn't sign are you against the inclusion part or are you against diverse do you just not like people like you like actually that has nothing to do with anything you're making this into something that it isn't I don't want to sign your goddamn stupid statement and get out of my lab right get out of my lab it all begins from the middle finger get out of my lab the administrators need to find other work yeah listen I agree with you and I I hope to seek your advice and and wisdom as we change this because I'd love to see I will visit you in prison if that's what you're asking I have no I think prison is great you get a lot of reading done and then when good working out well let me ask the something I brought up before is the Nietzsche quote of beware that when fighting monsters you yourself do not become a monster for when you gaze long into the abyss the abyss gazes into you are you worried that your focus on the flaws in the system that we've just been talking about has damaged your mind or the part of the mind of your mind that's able to see the beauty in the world in the system that because you have so sharply been able to see the flaws in the system you can no longer step back and appreciate it speeding look I'm the one who's trying to get the institutions to save themselves by getting rid of inhabitants believing the institution like a neutron bomb that removes the unworkable leadership class but leaves the structures so I equals so the leadership classes really the problem the leadership class is that the individual like the professor's Dean video scholar the professor's are gonna have to go back into training to remember how to be professors like people are cowards at the moment because if they're not cowards they're unemployed yeah that's one of the disappointing things I've encountered is to me tenure they don't nobody has tenure now why whether they do or not they certainly don't have character not the kind of character and fortitude that I was hoping to see to me but they'd be gone but see you're dreaming about the people who used to live at MIT you're dreaming about the previous inhabitants of your university and if you looked at somebody like you know isadora singer is very old I don't know what state he's in but that guy was absolutely the real deal and if you look at Noam Chomsky tell me that Noam Chomsky has been muzzled right yeah now what I'm trying to get at is you're talking about younger energetic people but those people like when I say something like I'm against I'm for word inclusion and I'm for diversity but I'm against diversity and inclusion TM like the movement well I couldn't say that if I was a professor oh my god he's against our sacred document okay well in that kind of a world do you want to know how many things I don't agree with you on it like we could go on for days and days and days all of the nonsense that you've parroted inside of the institution any sane person like has no need for it they have no want or desire do you think you have to have some patience for nonsense when many people work together in a system how long a string theory go for and how long have I been patient okay so you're talking about a mid two patients I'm talking about like 36 years of modern nonsense and string theory say you can do like eight to ten years but not more I can do 40 minutes this is 30 sleeve stone now over two hours or no but I appreciate it but it's been 36 years of nonsense since the anomaly cancellation in in string theory it's like what are you talking about about patients I mean Lex you're not even acting like yourself now at what you're trying to stay in the system and I'm not sure I'm not I'm trying to see if perhaps so so my hope is that the system just has a few assholes in it which you highlight and the fundamentals of the system are broken because if the fundamentals of the systems are broken then I just don't see a way for MIT to succeed like I don't see how young people take over MIT I don't see how by inspiring us you know the great part about being at MIT like when you saw the the genius in these pranks the heart the irreverence yeah it's like don't do it then we were talking about Tom Lehrer the last time Tom Lehrer was as naughty as the day is long agreed agreed was he also a genius was he well-spoken was he highly cultured he was so talented so intellectual that he could just make fart jokes morning noon and night yeah okay well in part the right to make fart jokes the right to for example put a functioning phone booth that was ringing on top of the Great Dome at MIT has to do with we are such badasses that we can actually do this stuff well don't tell me about it anymore go break the law go break the law in a way that inspires us and makes us not want to prosecute you may break the law in a way that lets us know that you're calling us out on our bullshit that you're filled with love and that our technical talent has not gone to sleep it's not incapable you know and if the idea is that you're gonna dig a moat around the University and fill it with tiger sharks that's awesome because I don't know how you're gonna do it but if you actually manage to do that I'm not going to prosecute you prosecute you under a reckless endangerment man that's beautifully put I hope those first of all they'll listen I hope young people and mighty will take over in this in this kind of way in the introduction to your podcast episode on Jeff Epstein you give to me a really moving story but unfortunately for me to brief about your experience with a therapist and the lasting terror that permeated your mind can you uh can you go there can you tell I don't think so I mean I appreciate what you're saying I said it obliquely I said enough there are bad people who cross our paths and the current vogue is to say oh I'm a survivor I'm a victim I can do anything I want this is a broken person and I don't know why I was sent to a broken person as a kid and to be honest with you I also felt like in that story I say that I was able to say no you know and this was like the entire weight of authority and he was misusing his position and I was also able to say no what I couldn't say no to was having him reinf lichte Din my life I see you were sent back yeah second time I tried to complain about what had happened I tried to do it in a way that did not immediately cause horrific consequences to both this person and myself because I didn't we don't have the tools to deal with sexual misbehavior we have nuclear weapons we don't have any way of saying this is probably not a good place or a role for you at this moment as an authority figure and something needs to be worked on so in general when we see somebody who is misbehaving in that way our immediate instinct is to treat the person as you know Satan and we understand why we don't want our children to be at risk now I personally believe that I fell down on the job and did not call out the Jeffrey Epstein thing early enough because I was terrified of what Jeffrey Epstein represents and this recapitulated the old terror trying to tell the world this therapist is out of control and when I said that the world responded by saying well you have two appointments booked and you have to go for the second one so I got reinfected into this office on this person who was now convinced that I was about to tear down his career and his reputation it might have been on the verge of suicide for all I know I don't know but he was very very angry and he was furious with me that I had breached a sacred confidence of his office what kind of ripple effects does that have has that head to the rest of your life the absurdity and the cruelty of that I mean there's no sense to it well see this is the thing people don't really grasp I think there's an academic who I got to know many years ago named Jennifer fried who has a theory of betrayal which she calls institutional betrayal and her gambit is is that when you were betrayed by an institution that is sort of like a fiduciary or a parental obligation to take care of you that you find yourself in a far different situation with respect to trauma than if you were betrayed by somebody who's a peer and so I think that my in my situation I kind of repeat a particular dynamic with authority I come in not following all the rules trying to do some things not trying to do others blah blah blah and then I get into a weird relationship with authority and so I have more barians with what I would call institutional betrayal now the funny part about it is that when you don't have masks or PPE in a influenza like pandemic and you're missing ICU beds and ventilators that is ubiquitous institutional betrayal so I believe that in a weird way I was very early the idea of and this is like tough the really hard concept pervasive or otherwise Universal institutional betrayal where all of the institutions you can count on any hospital to not charge you properly for what their services are you can count on no pharmaceutical company to produce the drug that will be maximally beneficial to the people who take it you know that your financial professionals are not simply working in your best interest and that issue had to do with the way in which growth left of our system so I think that the weird thing is is that this first institutional betrayal by a therapist left me very open to the idea of okay well maybe the schools are bad maybe the hospitals are bad maybe the drug companies are bad maybe our food is off maybe our journalists are not serving journalistic ends and that was what allowed me to sort of go all the distance and say huh I wonder if our problem is that something is causing all of our sense making institutions to be off that was the big insight and that tying that to a single ideology what if it's just about growth they were all built on growth and now we've promoted people who are capable of keeping quiet that their institutions aren't working so we've the privileged silent aristocracy the people who can be counted upon not to mention a fire when a raging fire is tearing through a building but nevertheless it's how big of a psychological burden is that it's huge it's terrible I mean rushing it's it's very it's very comforting to be the parental I mean I don't know I I treasure I mean we were just talking about MIT we can until I can intellectualize and agree with everything you're saying but there's a comfort a warm blanket of being within the institution and up until him Aaron Schwartz let's say in other words now if I look at the provost and the president as mommy and daddy you did what to my big brother you did what to our family you sold us out in which way what secrets left for China you hired which workforce you did what to my wages you took this portion of my grant for what purpose you just stole my retirement through a fringe rate what did you do but can you still I mean thing is about this view you have is it often turns out to be sadly correct well this is the thing and but that let me just in this silly hopeful thing do you still have hope and institutions can you win you psycho psychologically yes I'm referring not intellectually because you have to carry this burden can you still have a hope like within you Jake that when you sit a home alone and as opposed to seeing the darkness within these institutions seeing a hope well but this is the thing I want to confront not for the purpose of a dust-up I believe for example if you've heard episode 19 that the best outcome is for Carol Greider to come forward as we discussed in episode 19 would your brother Brett honest and say you know what so I screwed up he did call he did suggest the experiment I didn't understand that it was his theory that was producing it maybe I was slow to grasp it but my bad and I don't want to pay for this bad choice on my part let's say for the rest of my career I want to own up and I want to help make sure that we do what's right with what's left and that's one little case within the institution they would like to see made I would like to see MIT very clearly come out and you know Margo O'Toole was right when she said David Baltimore's lab here produced some stuff that was not reproducible with Teresa and Minnie shakarez research I want to see the courageous people I would like to see a the Aaron Schwartz wing of the computer science department yeah wouldn't know let's think about it yeah wouldn't that be great if they said you know an injustice was done and we're gonna we're gonna write that wrong just as if this was Alan Turing which I don't think they've righted that wrong well then let's have the Turing Schwartz way to ensure they're starting a new college of computing it wouldn't be wonderful to call it the the toyish why I would like to have the Madame wooing of the physics department and I'd love to have the Emmy nerd er statue in front of the math department I mean like you want to get excited about actual diversity and inclusion yeah well let's go with our absolute best people who never got theirs because there is structural bigotry you know but if we don't actually start celebrating the beautiful stuff that we're capable of when we're handed heroes and we fumble them into the trash what the hell I mean Lex this is such nonsense we just pulling our head out you know the on everyone's cecum should be tattooed if you can read this you're too close beautifully put and I'm a dream or just like you so I don't see as much of the darkness genetically or due to my life experience but I do share the hope from my teeth as you should know we care a lot about you both do yeah and a harvard institution i don't give a damn about but you do so I love Harvard I'm just kidding i yeah i love harvard but rude and i have a very difficult relationship and part of what you know when you love a family that isn't working I don't want to trash I I didn't bring up the name of the president of MIT during the Aaron Schwartz period it's not vengeance I want the rot cleared out I don't need to go after human beings yeah just like you said with the with a disc formulation they individual human beings aren't don't necessarily carry them it's those chairs that are so powerful that in which they sit it's the chairs not the human it's not the humans without naming names can you tell the story of your struggle during your time at Harvard maybe in a way that tells the bigger story of the struggle of young bright minds that are trying to come up with big bold ideas within the institutions that we're talking about you can start I mean in part it starts with coffee with a couple of Croatians in the math department at MIT and we used to talk about music and dance and math and physics and love and all this kind of stuff as Eastern Europeans love to and I ate it up and my friend Gordana who was an instructor in the MIT math department when I was a graduate student at Harvard said to me I'm probably gonna do a bad version of her accent there we go it will I see you tomorrow at the secret seminar and I said what secret seminar it don't joke I said I'm not used to this style of humor Gordon she's getting the secret seminar that your adviser is running I said what are you talking about ha ha ha you know your advisor is running a secret seminar on this aspect I think it was like the chern-simons invariants I'm not sure what the topic was again but she gave me the room number and the time and she was like not cracking a smile I've never known her to make this kind of a joke and I thought this was crazy and I was trying to have an advisor I didn't want an advisor but people said you have to have one so I took one and I went to this room at like 15 minutes early and there was not a soul inside it it was outside of the math department and was still in the same building the Science Center at Harvard and I sat there and let five minutes go by hey I let seven minutes go by ten minutes go by there's nobody I thought okay so this was all an elaborate joke and then like three minutes to the hour this graduate student walks in and like sees me and does a double take and then I start to see the professors in geometry and topology start to file in and everybody's like very disconcerted that I'm in this room and finally the person who is supposed to be my advisor walks in to the seminar and sees me and goes white as a ghost and I realized that the secret seminar is true that the department is conducting a secret seminar on the exact topic that I'm interested in not telling me about it and that these are the reindeer games that the Rudolph's of the department are not invited to and so then I realize okay I did not understand it there's a parallel department and that became the beginning of an incredible Odyssey in which I came to understand that the game that I had been sold about publication about blind refereeing about openness and scientific transmission of information was all a lie I came to understand that at the very top there's a second system that's about closed closed meetings and private communications and agreements about citation and publication that the rest of us don't understand and that in large measure that is the thing that I won't submit to and so when you ask me questions like well why wouldn't you feel good about you know talking to your critics or why wouldn't you feel the answer is oh you don't know like if you stay in a nice hotel you don't realize that there is an entire second structure inside of that hotel where like there's usually a workers cafe in a resort complex that isn't available to the people who are staying in the hotel and then there are private hallways inside the same hotel that are parallel structures so that's what I found which was in essence just the way you can stay hotels your whole life and not realize that inside of every hotel is a second structure that you're not supposed to see is the guest there is a second structure inside of academics that behaves totally differently with respect to how people get dinged how people get their grants taken away how this person comes to have that thing named after them and by pretending that we're not running a parallel structure I have no patience for that way anymore so the I got a chance to see how the game how hard ball is really played at Harvard and I'm now eager to play hardball back with the same people who played hardball with me let me ask two questions on this so one do you think it's possible so I call those people assholes but that's the technical term do you think it's possible that that's just not the entire system but a part of the system sort of that there's you can navigate you can swim in the waters and find the groups of people who do aspire to the guy who wrestled my PhD was one of the people who filed in - the secret seminar right but are there pedestrian side of this right is he an asshole well yes I was as a bad no but I'm trying to make this point which is this isn't my failure to correctly map these people it's yours you know who has a simplification that isn't gonna work I think okay as I was the wrong term I would say lacking of character and what would you have had these people do why did they do this why have a secret seminar I don't understand the exact dynamics of a secret seminar but I think the right thing to do is to I mean to see individuals like you there might be a reason to have a secret seminar but they should detect that an individual like you a brilliant mind who's thinking about certain ideas could be damaged by this I don't think they see it that way the idea is we're going to sneak food to the children we want to survive yeah so that that's highly problematic and there should be people within that road I'm trying to say this is the thing the ball is thrown back won't be caught the problem is they know that most of their children won't survive and they can't say that I see sorry to interrupt you mean that the the fact that the whole system is underfunded that they naturally have to pick favorites they live in a world which reached steady state at some level let's say you know in the early 70s and in that world before that time you have a professor like Norman's steam rod and you'd have 20 children that is graduate students and all of them were going to be professors and all of them would want to have 20 children right so you start like taking higher and higher powers of 20 and you see that the system could not it's not just about money the system couldn't survive so the way it's supposed to work now is that we should shut down the vast majority of PhD programs and we should let the small number of truly top places pop mostly teaching and research departments that aren't PhD producing we don't want to do that because we use PhD students as a labor force so the whole thing has to do with growth resources dishonesty and in that world you see all of these adaptations to a ruthless world where the key question is where are we going to bury this huge number of bodies of people who don't work out so my problem was I wasn't interested in dying so you clearly highlight that there's aspects of the system that are broken but as an individual is your role to exit the system or just acknowledge it as a game and win it my role is to survive and thrive in the public eye in other words when you have an escapee of the system like yourself such as and that person says you know I wasn't exactly finished let me show you a bunch of stuff let me show you that the theory of telomeres we never got reported properly let me show you that all of marginal economics is supposed to be redone with a different version of the differential calculus let me show you that you didn't understand the self dual yang-mills equations correctly in topology and physics because they're in fact much more broadly found and it's only the mutations that happen in special dimensions there are lots of things to say but this particular group of people like if you just take where are all the Gen X and millennial university presidents all right okay they're all they're all in a holding pattern now where why in this story you know was it a of telomeres was it an older professor and a younger graduate student it's this issue of what would be called interference competition so for example orcas try to drown minke whales by covering their blowholes so that they suffocate because the the needed resource is air okay well what are the universities do they try to make sure that you can't be viable that you need them that you need their grants you need to be zinged with overhead charges or fringe rates or all of the games that the locals love to play well my point is ok what's the cost of this how many people died as a result of these interference competition games you know when you take somebody like Douglas pressure who did green fluorescent protein and he drives a shuttle bus right because he his grant runs out and he has to give away all of his research and all of that research gets a Nobel Prize and he gets to drive a shuttle bus for $35,000 a year what do you mean by die do you mean their career their dreams their yeah holes are there as an academic Doug pressure was dead for a long period of time ok so as a person who's escaped a system yeah can't you at this because you also have in your mind a powerful theory that may turn out to be useful maybe not let's hope can't you also play the game enough like with the children so like publish and but also if you told me that this would work really what I want to do you see is I would love to revolutionize a field with an H index of zero like we have these proxies that count how many papers you've written how cited of the papers you've written all this is nonsense it's interesting it aside what do you mean by a field with an H index is a totally new H index is counts somehow how many papers have you gotten that gets so many citations yeah let's say H index undefined like for example I don't have an advisor for my PhD but I have to have an advisor as far as something called the math genealogy project that tracks who advised who who advised whom right down the line so I am my own advisor which sets up a loop right how many students do I have an infinite number your descendants they don't want to have that story so I have to be I have to have formal advisor Rowell Bhatt and my Wikipedia entry for example says that I was advised by Rahul Bhatt which is not true so you get fit into a system that says what we have to know what your h-index is we have to know you know where are you a professor if you want to apply for a grant it makes all of these assumptions what I'm trying to do is to impart to show all of this is nonsense this is proxy BS that came up in the institutional setting and right now it's important for those of us who are still vital like Elon it would be great to have you on as a professor of physics and engineering Yeah right it seems ridiculous to say but just as Charlotte just as a shot in the arm yeah you know like be great to have you on at Cal Tech even one day a week yeah one day a month okay well why can't we be in there it's the same reason why can't you be on the view why can't you be on Bill Martin we need to know what you're gonna do before we take you on the show on the show well I don't want to tell you what I'm gonna do do you think you need to be able to dance the dance a little bit I can't dance the dance floor to be on the view oh come on so you can yeah you do yeah I do that fine here's where it's the place that it goes south is there's like a set of questions that get you into this more adversarial stuff and you've in fact asks some of those more adversarial questions this setting and they're not things that are necessarily aggressive but there are things that are making assumptions right right well so when you make it I have a questions like you know Lex are you avoiding your critics you know it's just like okay well why did you frame that that way or the next question would be it's like do you think that you should have a special exemption and that you should have the right to break rules and everyone else should have to follow them like that question I find enervating yeah it doesn't really come out of anything meaningful it's just like we feel we're supposed to ask that of the other person to show that we're not captured by their madness that's not the real question you want to ask me if you want to get really excited about this you want to ask do you think this thing is right yeah weird thing I do do you think that it's going to be immediately seen to be right I don't I think it's gonna it's gonna have an interesting fight and it's gonna have an interesting evolution and well what do you hope to do with it in non-physical terms my gosh I hope it revolutionizes our relationship of well with people outside of the institutional framework and it reinforces into the institutional framework where we can do the most good to bring the institution's back to health you know it's like these are positive uplifting questions yeah if you had Frank we'll check you wouldn't say Frank let's be honest you have done very little with your life after the original huge show that you used to break onto the physics scene like we weirdly ask people different questions based on how they sit down yeah that's very strange right but you have to understand that so here's the thing I get these days a large number of emails from people with the equivalent of a theory of everything for a GI yeah and I use my own radar BFBS radar to detect on unfairly perhaps whether they're full shit or not right because I love what you're where you're going with this by the way and Mike my concern that I often think about is there's elements of brilliance and what people write to me and I and I'm trying to right now as you made it clear at the kind of judgments and assumptions we make how am I supposed to deal with you who are not an outsider of the system and think about what you're doing because my radar saying you're not full of shit you know what I'm also not completely outside of the system that's right you've danced beautifully you've actually get got all the credibility that you're supposed to get all the nice little stamps of approval not all but a large enough amount you use I mean it's hard to put into words exactly why you sound whether your theory turns out to be good or not you sound like a special human being I appreciate that and thank you in a good way all right so but what am I supposed to do with that flood of emails for me AJ why do I sound different I don't know and I would like to systemize that I don't know look you know when you're talking to people you very quickly consume eyes like am i claiming to be a physicist no I say it every turn I'm not a physicist right when I say to you when you say something about bundles you say well can you explain it differently I think you know I'm pushing around on this this area that lever over there I'm trying to find something that we can play with and engage and you know another thing is is that I'll say something at scale so if I was saying completely wrong things about bundles on the Joe Rogan program you don't think that we wouldn't hear a crushing chorus yes and it's actually you know same thing with geometric unity so I put up this this video from this oxford lecture I understand this not a standard lecture but you haven't heard you know the most brilliant people in the field said well this is obviously nonsense they don't know what to make of it yeah I'm gonna hide behind well he hasn't said enough to tale where's the paper and where's the paper I've seen the criticism yeah I've gotten the same kind of Critias I've published a few things and like especially stuff related to Tesla that we did studies and Tesla vehicles and the kind of criticism I've gotten was showed that they're completely oh right like the guy who had Elon Musk on his program twice is gonna give us an accurate assessment yeah exactly exactly it's just very low-level like without actually ever addressing you know the content you know Lex I think that in part you're trying to solve a puzzle that isn't really your puzzle I think you know that I'm sincere you don't know whether the theory is going to work or not and you know that it's not coming out of somebody who's coming out of left field like the story makes sense there's enough that's new and creative and different in other aspects where you can check me that your real concern is are you really telling me that when you start breaking the rules you see the system for what it is and it's become really vicious and aggressive and the answer is yes and I had to break the rules in part because of learning issues because I came into this field you know with a totally different set of attributes my profile just doesn't look like anybody else's remotely but as a result what that did is it showed me what is the system true to its own ideals or does it just follow these weird procedures and then when it when you take it off the rails it behaves terribly and that's really what my story I think does is it just says well he completely takes the system into new territory where it's not expecting to have to deal with somebody with these confusing sets of attributes and I think what he's telling us is he believes it behaves terribly now if you take somebody with perfect standardized tests and you know a winner of math competitions and you put them in a ph.d program they're probably going to be okay I'm not saying that the system you know breaks down for any everybody under all circumstances I'm saying when you present the system with a novel situation at the moment it will almost certainly break down with probability approaching 100 percent but to me the painful and the tragic thing is it sorry to bring out my motherly instinct but it feels like it's too much it could be too much of a burden to exist outside the system maybe by psychologically first of all I've got a podcast that I that's kind of like you've got amazing friends I have a life which has more interesting people passing through it than I know what to do with and they haven't managed to kill me off yet so so far so good speaking of which you host an amazing podcast we've mentioned several times but should mention over and over the portal where you somehow manage every single conversation is a surprise you go I mean not just the guest but just the the places you take them the the kind of ways they become challenging and how you recover from that I mean it's uh there's just it's full of genuine human moments so I really appreciate what you're it's a fun fun podcast to listen to let me ask some silly questions about it what what have you learned about conversation about human to human conversation well I have a problem and I haven't solved on the portal which is that in general when I ask people questions they usually find they're deeply grooved answers and I'm not so interested in all of the deeply grooved answers and so there's a complaint which I'm very sympathetic to actually that I talk over people that I won't sit still for the answer and I think that's weirdly sort of correct it's not that I'm not interested in hearing other voices it's that I'm not interested in hearing the same voice on my program that I could have gotten on somebody else's and I haven't solved that well so I've learned that I need a new conversational technique where I can keep somebody from finding their comfortable place and yet not be the voice talking over that person it's funny I didn't sense like your conversation with Brett I can sense you detect that the line he's going under down is you know how it's gonna end and you know you think it's a useless line so you'll just stop it right there and you take them into the direction that you think you should go but that requires interruption well and it does so far I haven't found a better way I'm looking for a better way it's not it's not like I don't hear the problem I do hear the problem I just I haven't solved the problem and you know on the on the bread episode I was insufferable it was very difficult to listen to it was so overbearing but on the other hand I was right you know it's like funny yeah you keeps that but I didn't find that me because I heard brothers like I heard a big brother yeah it was pretty bad really I think so I didn't think it was bad well a lot of people found it in subsisting and I think it also has to do with the fact that this has become a frequent experience I have several shows where somebody who I very much admire and think of as courageous you know I'm talking with them maybe we're friends and they sit down on this show and they immediately become this fake person like two seconds in there they're sort of saying why I don't to be too critical or too harsh and I want to name any names I wanted this joint here's like okay I'm gonna put my listeners through three hours of you being sweetness and light yeah like at least give me some reality and then we can decide to shelve the show and never let it here you know that the the call of freedom in the in the bigger world but I saw you break out of that a few times I've seen you to be successful that I forgot the guest but she was dressed with you worried at the end of the episode you had to nog you honor Bob Brett FMS caller yeah and Magnus color the philosopher at the University of Chicago yeah you've continuously broken out of her you guys went you know I didn't seem pretty genuine I like her I'm completely ethically opposed to what she's ethically for which she was great and she wasn't like that you're both going hard bro no yeah cuz I care about her so that was awesome yeah but you're saying that some people are difficult to break up well it's just that you know she was bringing the courage of her conviction she was sort of defending the system and I thought wow that's a pretty indefensible system that's great though she's doing that isn't it yeah I mean it made for an awesome I think it's very informative for the world yes you just hated I just can't stand the idea that somebody says well we don't care who gets paid or who gets the credit as long as we get the goodies cuz that seems like insane have you ever been afraid leading into a conversation garry kasparov really by the way I mean I know I'm just a fan taking requests but I started I started the beginning in Russian and in fact I used one word incorrectly I was terrible you know it was pretty good it's pretty good Russian what was terrible is I think he complimented to you right no did he compliment you use that me D compliment you on your Russian so he said almost perfect Russian yeah like he was bullshit that was not great Russian but there was not great Russian that was good that was hard that was you tried hard which is what matters that is so insulting I hope so but I do hope you continue I did felt like I don't know how long and when it might have been like a two-hour conversation but it felt I hope it continues like I feel like you have many your conversation with Gary yeah I would love to hear there's certain conversation I was just love to hear well you know he's coming from a very it's this issue about needing to overpower people in a very dangerous world and so Gary has that need yeah he wasn't he was interrupting you there's an interesting dynamic is an interesting dynamic to Weinstein is going into what I mean to powerhouse egos brilliant no don't say egos Minds my spirits my you don't have any good you're the most humble person I know so true no that's a complete lie do you think about your own mortality death sure are you afraid Wow death I released the theory during something that can kill door people sure I was there of course little bit of a parallel that of course of course I don't want it to die with me what do you hope your legacy is oh I hope my legacy is accurate I'd like to ride on my accomplishments rather than how my community decided to ding me while I was alive that would be great what about if it was significantly exaggerated I don't want it you wanted to be accurate I'm I've got some pretty terrific stuff and then whether it works out or doesn't that I would like it to reflect what I actually was I'll settle for accurate what would you say what is the greatest element of Eric Weinstein accomplishment in life terms of being accurate like what what are you most proud of trying the idea that we were stalled out in it in the hardest field at the most difficult juncture and then I didn't listen to that voice ever it said stop you're hurting yourself you're hurting your family hurting everybody you're embarrassing yourself you're screwing up you can't do this you're a failure you're a fraud turn back save yourself like that voice I didn't ultimately listen to it and it was going for 35 37 years very hard and I hope you never listen to that voice well it's why you're an inspiration thank you appreciate it you're the eye and just infinitely honored that you would spend time with me you've been a mentor to me almost a friend I can't imagine a better person to talk to in this world so thank you so much for talking it I can't wait till we do it again Lex thanks for sticking with me and thanks for being the most singular guy in the podcasting space in terms of all of my interviews I would say that the last one I did with you many people feel was my best and it was a non-conventional one so whatever it is that you're bringing to the game I think everyone's noticing and keep at it thank you thanks for listening to this conversation with Eric Weinstein and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code let's podcast if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter and lex friedman and now let me leave you with some words of wisdom from eric Weinstein's first appearance in this podcast everything is great about war except all the destruction thank you for listening and hope to see you next time you |
Richard Dawkins: Evolution, Intelligence, Simulation, and Memes | Lex Fridman Podcast #87 | the following is a conversation with Richard Dawkins an evolutionary biologist and author of The Selfish Gene the blind watchmaker The God Delusion the magic of reality and the greatest show of Earth and his latest Al growing God he is the originator and popularizer of a lot of fascinating ideas in evolutionary biology and Science in general including funny enough the introduction of the word meme in his 1976 book The Selfish Gene which in the context of a gene centered view of evolution is an exceptionally powerful idea he's outspoken bold and often Fearless in the defense of science and reason and in this way is one of the most influential thinkers of our time this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of this crises I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars on Apple podcast support on patreon or simply connect with me on Twitter at Lex Freedman spelled f r d m an as usual I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the app store when you you get it use clex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app allows you to send and receive money digitally peer-to-peer Security in all digital transactions is very important let me mention the PCI Data security standard that cash app is compliant with I'm a big fan of standards for safety and security PCI DSS is a good example of that where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions now we just need to do the same for autonomous vehicles and artificial intelligence systems in general so again if you get cash app from the app store Google Play and use the code Lex podcast you get $10 and cash app will also donate $10 to First an organization that is helping to advance Robotics and stem education for young people around the world and now here's my conversation with Richard Dawkins do you think there's intelligent life out there in the universe well if we accept there's intelligent life here and re accept that the number of planets in the universe is gigantic I mean 10 to 22 Stars has been estimated it seems to me highly likely that there is not only life in the universe elsewhere but also intelligent life If you deny that then you're committed to the view that the things that happened on this planet are staggeringly improbable I mean ludicrously off the charts improbable and I don't think it's that improbable certainly the origin of life itself there really two steps the origin of life which is probably fairly improbable and then the subsequent Evolution to intelligent life which is also fairly improbable so the Jos of those two you could say it's pretty improbable but not 10 to the 20 to improbable it's an interesting question maybe you're coming on to it how we would recognize intelligence from Outer Space if we if we encountered it the most likely way we would come across them would be by radio it's highly unlikely they'd ever visit us but um it's not it's not that unlikely that we would pick up radio signals and then we would have to have some means of deciding that it was intelligent um people have with people involved in the seti program discuss how they would do it and things like prime numbers would be an obvious thing to an obvious an obvious way for them to broadcast to say we are in intelligent we are here um I suspected probably would be obvious actually that's interesting prime numbers so the mathematical patterns it's an open question whether mathematics is the same for us and as it would be for aliens I suppose we could assume that ultimately if if we're governed by the same laws of physics then we should be governed by the same laws of mathematics I think so I suspect that they will have Pythagoras Theorem Etc I mean I don't think their mathematics will be that different do you think Evolution would also be a force on the AL I planets as well I stuck my neck out and said that if we do if ever that we do discover life elsewhere it will be darwinian life in the sense that it will it will work by some kind of natural selection the non-random survival of non of randomly generated codes uh it doesn't mean it that the genetic would have to have some kind of genetics but it doesn't have to be DNA genetics probably wouldn't be actually but it would I think it would have to be darwinian yes so some kind of selection process yes in the general sense it would be darwinian so let me ask kind of uh an artificial intelligence engineering question so you've been an outspoken critic of I guess what could be called intelligent design which is an attempt to describe the creation of a human Mind and Body by some religious folks religious folks used to describe so broadly speaking evolution is as far as I know again you can correct me is the only scientific theory we have for the development of intelligent life like there's no alternative Theory as far as as far as I understand none has ever been suggested and I suspect it never will be well of course whenever somebody says that 100 years later I know it's a it's a risk it's a risk but um want to bet I mean I I I but it would look sorry yes it would probably look very similar but it' be it's almost like uh Einstein general relativity versus Newtonian physics it'll be maybe um an alteration of the Theory something like that but it won't be fundamentally different but okay it so uh so now for the past 70 years even before the AI Community has been trying to engineer intelligence in a sense to do what intelligent design says you know uh was done here on Earth what's your intuition do you think it's possible to build intelligence to build computers that are intelligent or do we need to do something like the evolution process like there's there's no shortcuts here that's an interesting question I I'm committed to the belief that is ultimately possible because I think there's nothing non-physical in our brains I think our brains work by by the laws of physics and so it must in principle be possible to replicate that in practice though it might be very difficult and as you suggest it might it may be the only way to do it is by something like an evolutionary process I'd be surprised I I suspect that it will come but it's certainly been slower incoming than some of the early Pioneers thought thought it would be yeah but in your sense is the evolutionary process efficient so you can see it as exceptionally wasteful in one perspective but at the same time maybe that is the only path to it's a paradox isn't it I mean on the one side it is deplorably wasteful yeah uh it's fundamentally based on waste on the other hand it does produce magnificent results um I mean the the the design design of a soaring bird an albatross a vulture an eagle um is is superb an engineer would be proud to have done it on the other hand an engineer would not be proud to have done some of the other things that Evolution has served up um some of the sort of botch jobs that you can easily understand because of their historical Origins but they don't look welld designed you have examples of bad bad design my favorite example is the recurrent lingal nerve I've used this many times this is a nerve it's one of the cranial nerves which goes from the brain and the end organ that it supplies is the voice box the the larynx but it doesn't go straight to the larynx it goes right in down into the chest and then loops around an artery in the chest and then come straight back up again to the larynx uh and I've assisted in the dissection of a giraffe's neck which happened to have died in a zoo and we watched the we saw the recurrent lenal nerve going whizzing straight past the larynx within an inch of the larynx down into the chest and then back up again um which is a a detour of many feet um very very inefficient the reason is historical the ancestors our fish ancestors the ancestors of all mammals and fish um the most direct pathway of that of the equivalent of that nerve there wasn't a larynx in those days but it innovated part of the gills the most direct pathway was behind that artery and then when the mammal when the tetrapods when the land vertebrae started evolving and then the neck started to stretch the marginal cost of changing the embryological design to jump that nerve over the artery was too great or rather was was each step of the way was a was a very small cost but the marginal but the cost of actually jumping it over would have been very large as the neck lengthened it was a negligable change to just increase the Len the length of the detour a tiny bit a tiny bit a tiny bit each millimeter at a time didn't make any difference and so but finally when you get to a giraff it's a huge detour and no doubt is very inefficient now that's bad design any engineer would reject that piece of design it's ridiculous and there are quite number of examples as you'd expect it's not surprising that we find examples of that sort in a way what's surprising is there aren't more of them in a way what's surprising is that the design of living things is so good so natural selection manages to achieve excellent results um partly by tinkering partly by coming along and cleaning up initial mistakes and and as it were making the best of a bad job that's really interesting I mean it it is surprising and and beautiful and it's a it's a mystery from an engineering perspective that so many things are welld designed I suppose the thing we're forgetting is how many generations have to die oh yeah that's the inefficiency of it yes that's the horrible wastefulness of it so yeah we we Marvel at the final product but uh yeah the process is painful Elon mus describes human beings as potentially the what he calls the biological Bootloader for artificial intelligence or artificial general intelligence is used as the term it's kind of like super intelligence do you see superhuman level intelligence is potentially The Next Step In The evolutionary process yes I think that if if superhuman intelligence is to be found it will be artificial I I I don't have any hope that we ourselves our brains will go on uh go and getting larger in ordinary biological evolution um I think that's probably come to an end it it is the dominant Trend or one of the dominant Trends in our fossil history for the last 2 or three million years brain size brain size yes so it's been it's been swelling rather dramatically over the last 3 million years that is unlikely to continue the the only way that that's that happens is because natural selection favors those individuals with the with the biggest brains um and that's not happening anymore right so in general in humans the the selection pressures are not act I mean are they active in any form any well in order for them to be active it would be necessary that the most int let's let's call it intelligence not that intelligence is is simply correlated with brain size but let's let's talk about intelligence in order for that to evolve it's necessary that the most intelligent beings have the most individuals have the most children um and um uh so intelligence may buy you money it may buy you um worldly success it may buy you a nice house and and a nice car and things like that if you're successful career uh it may buy you the admiration of your fellow people but it doesn't increase the number of offspring that you have it doesn't increase your genetic uh Legacy to the next Generation on the other hand artificial intelligence um I mean computers and Technology generally is evolving by a non- gentic means by Leaps and Bounds of course and so what do you think uh I don't know if you're familiar there's a company called neuralink but there's a general effort of brain computer interfaces which is to try to build a connection between the computer and the Brain to send signals both directions and the long-term dream there is to do exactly that which is expand I guess expand the size of the brain expand the capabilities of the brain do you uh do you see this as interesting do you see this is a promising possible technology or is the interface between the computer and the brain like the brain is this wet messy thing that's just impossible to interface with well of course it's interesting whether it's promising I'm really not qualified to say what I do find puzzling is that the brain being as small as it is compared to computer and the and the individual components being as slow as they are compared to our electronic components it is astonishing what it can do I mean imagine building a computer that that fits into the size of a human skull um and with the equivalent of transistors or integrated circuits which work as slowly as neurons do uh it's there's something mysterious about that something something must be going on that we don't understand so I I've uh I've just talked to Roger penos I'm not sure if you're familiar with with his work and he he he also describes this kind of um mystery in in the mind in the brain that he's a materialist so there's not there's no sort of mystical thing going on but there's so much about the material of the that we don't understand the that that might be quantum mechanical nature and so on so there are the ideas about Consciousness do you have any have you ever thought about do you ever think about ideas of Consciousness or a little bit more about the mystery of intelligence and Consciousness that seems to pop up just like you're saying from our brain I agree with Roger Penrose that there is a mystery there um I I I mean he's one of the world's greatest physicists I I I can't possibly argue with with with with his but nobody knows anything about Consciousness and in fact you know if if we talk about religion and so on some the mystery of Consciousness is so on inspiring and we know so little about it that the leap to sort of religious or mystical explanations is too easy to make I I think that it's just an act of cowardice to LEAP to religious explanations water doesn't do that of course um but I I I accept that there may be something we don't understand about it so correct me if I'm wrong but in your book selfish Gene the the gene centered view of evolution of allows us to think of the physical organisms as just the medium through which the software of our genetics and the the ideas sort of propagate uh so maybe can we start just with with the basics what in this context does the word meme mean it would mean the cultural equalent of a gene cultural equivalent in the sense of that which plays the same role as the gene in the transmission of culture and the transmission of ideas in the broadest sense and it's only a useful word if there's something darwinian going on obviously culture is transmitted but is there anything darwinian going on and if there is that means there has to be something like a gene which is which becomes more numerous or less numerous in the population so it can replic at it can replicate well it clearly does replicate there's no question about that uh the question is does it replicate in a sort of differential way in a darwinian fashion could you say that certain ideas propagate because they're successful in the meme pool um in a sort of trivial sense you can um would you wish to say though that in the same way as a animal body is modified adapted to serve as a machine for propagating genes is it also machine for propagating memes Could you actually say that something about the way a human is is is modified adapted um for the function of meme propagation that's such a fascinating possibility if that's true if that that it's not just about the genes which seem somehow more com comprehensible like these things of biology the the the the idea that culture or maybe ideas you can really broadly Define it yes operates under these mechanisms even morphology even an anatomy does does evolve by mimetic means I mean things like hairstyles um uh styles of makeup um circumcision the these things are actual changes in the body form yes which are non- gentic and which get passed on from generation to generation or sideways like a virus um in in in a quasi genetic way but the moment you start drifting away from the physical it becomes interesting cuz the space of ideas ideologies political systems of course yes so what's what in your what's your sense is um are memes or metaphor more or are they really is there something fundamental almost physical presence of memes well I think they're a bit more than a metaphor and and I think that um I I mentioned the physical bodily characteristics which are a bit trivial in a way but when things like the propagation of religious ideas um both longitudinally down generations and transversely as in a sort of epidemiology of of ideas when a charismatic preacher converts people um that that's that resembles viral transmission um whereas the the longitudinal trans from grandparent to parent to child Etc is is is um more more like conventional genetic transmission that's such a beautiful especially especially in the modern day idea uh do you think about this implication in social networks where the propagation of ideas the viral propagation of ideas and hence the the new use of the word meme to describe the the internet of course provides extremely rapid method of tra adiss and before when when I first coined the word the internet didn't exist and so that I was thinking then in terms of books newspapers um broad radio television that kind of thing now an idea can just leap around the world in in all directions instantly and so the internet provides a a step change in uh the facility of propagation of memes how does that make you feel isn't it fascinating that sort of ideas it's like uh you have galpagos islandss or something is the 70s and the internet allowed all these species to just like globalize and and in in a matter of seconds you can spread a message to millions of people and these uh ideas these memes can breed can evolve can mutate can there's a selection and there's like different I guess groups that of all like there's a Dynamics that's fascinating here do you think yes basically do you think your work in this direction while fundamentally was focused on life on Earth do you think it should continue like to be Tak I mean I do think it would probably be a good idea to think in a darwinian way about this sort of thing we conventionally think of um the transmission of ideas from an evolutionary context as being limited to in our ancestors um people living in villages living in small bands where everybody knew each other and ideas could propagate within the village and they might hop to a neighboring Village occasionally and maybe even to a neighboring continent eventually and that was a slow process nowadays Villages are international I mean you you you have people um it's been called um Echo Chambers where where people are in a a sort of Internet Village um where the other members of The Village may be geographically distributed all over the world but they just happen to be interested in the same things use the same terminology the same jargon um have the same enthusiasms that people like the Flat Earth Society they don't all live in one place they find each other and they talk the same language to each other they talk the same nonsense to each other um and they but so this is a kind of distributed version of the Primitive idea of of people living in in villages and propagating their ideas in a local way is there uh is there darwinist paral parallel here so is there um evolutionary purpose of villages or is that just a uh I wouldn't use a word like evolutionary purpose in that that case but V Villages or Villages would be something that just emerged that's the way people happen to live and uh and it just the same kind of way the Flat Earth Society societies of ideas emerge in the same kind of way in this digital space yes yes is there something interesting to say about the I guess from a perspective of Darwin could we fully interpret the Dynamics of social interaction in these uh social networks or is there or some much more complicated thing need to be developed like what's your sense well a darwinian selection idea would involve investigating which ideas spread and which which don't um so I mean some ideas don't have the ability to spread I mean the flat earth flat Earth ism is is there are few people believe in it but it's not going to spread because it's obvious nonsense but other ideas even if they are wrong can spread because they are um attractive in some sense so the the spreading in the selection in the darwinian context is uh it just has to be attractive in some sense like we don't have to Define like it doesn't have to be attractive in the way that animals attract each other it could be attractive in some other way yes it's it's all that matters is all it's needed is it to spread and it doesn't have to be true to spread me truth is one Criterion which might help an idea to spread but there are other criteria which might help you to spread as you say attraction in animals is not necessarily valuable for survival cele the famous peacock's tale yeah doesn't help the peacock to survive it helps it to pass on it jeans similarly um an idea which is actually rubbish but which people don't know is rubbish and think is very attractive will spread um in the same way as a peacock's Gene spread it's a small side step I remember reading somewhere uh I think recently that in some species of birds sort of the idea that beauty may have its own purpose and the idea that some some birds um I'm I'm being in eloquent here but there is some aspects of their feathers and so on that serve no evolutionary purpose whatsoever there was somebody making an argument that there are some things about beauty that animals do that may be its own purpose that does that ring a bell for you does that sound ridiculous I think it's a rather distorted Bell um um Darwin when he coined the phrase sexual selection yes uh didn't feel the need to suggest that what was attractive to females usually is males attracting females that what females found attractive had to be useful he said it didn't have to be useful it was enough that females found it attractive and so it could be completely useless probably was completely useless in the conventional sense but was not at all useless in the sense of passing on D Darin didn't call them G but in sense of reproducing um others starting with Wallace the co-discoverer of natural selection didn't like that idea and they wanted um sexually selected characteristics like peacock's Tales to be in some sense useful it's a bit of a stretch to think of a peacock's tale as being useful but in in the sense of survival but others have run with that idea and have brought it up to date and so there's a kind of there are two schools of thought on sexual selection which are still active and about equally supported now those who follow Darwin in thinking that it's just enough to say it's attractive and those who follow um Wallace and say that um it has to be in some sense useful do you fall into one category or the other no I'm open minded I I think they both could be correct in different cases oh I mean they've both been made sophisticated in a mathematical sense more so than when Darwin and Wallace first started talking about it I'm Russian I ra romanticize things so I I prefer the former yes or the where the beauty in itself is a powerful uh so attraction is a powerful force in evolution on religion do you think there will ever be a time in our future where almost nobody believes in God or um God is not a part of the moral fabric of our society yes I do I think it may happen after a very long time I think it may take a long time for that to happen so do you think ultimately for everybody on Earth earth religion other forms of doctrines ideas could do better job than what religion does yes um I mean following truth reason well truth truth is a funny funny word uh and reason to there's yeah it's a it's a difficult idea now with um truth on the internet right and fake news and so on I suppose when you say reason you mean the very basic sort of inarguable conclusions of science versus which political system is better yes yes uh I I mean uh truth about the real world which is ascertainable um by not just by the more rigorous methods of science but by um just ordinary sensory observation so do you think there will ever be a time when we move past it like I guess another way to ask it are we hopelessly fundamentally tied to religion in the way our society functions well clearly all individuals are not hopelessly tied to it because many individuals don't believe um you could mean something like Society needs religion in order to function properly something like that and some people have suggested that some what's your intuition on that well I've read books on it um and they're persuasive I I don't think they're that persuasive though I mean I some people suggested that Society needs a sort of figurehead which can be a non-existent figurehead in order to function properly I think there's something rather patronizing about the idea that well you and I are intelligent enough not to believe in God but the plebs need it sort of thing and I think that's patronizing and uh I'd like to think that that that was not the right way to proceed but at the individual level do you think there's some value of spirituality sort of uh if if I think sort of as a scientist the amount of things we actually know about our universe is a tiny tiny tiny percentage of what we could possibly know so just from everything even the certainty we have about the laws of physics it seems to be that there's yet a huge amount to discover and therefore we're sitting where the 99.999% of things is just still shrouded in mystery do you think there's a role in a kind of spiritual view of that sort of a humbled spiritual I think it's right to be humble I think it's right to admit that there's a lot we don't know a lot that we don't understand a lot that we still need to work on and we are working on it what I don't think is that it helps to invoke Supernatural explanations what we if our if our current scientific explanations aren't adequate to do the job then we need better ones we need to work more and of course the history of science shows just that that as science goes on uh problems get solved one after another and the science advances the science gets better uh but to invoke an a non-scientific non-physical explanation is simply to lie down in a cly way and say we can't solve it so we're going to invoke magic don't let's do that let's say we need better science we need more science uh it may be that the science will never do it it may be that we will never actually understand everything and that's okay but let's keep working on it a challenging question there is do you think science can lead us astray in terms of the humbleness so there's some aspect of science maybe it's the aspect of scientist and not science but uh of sort of um a mix of ego and confidence that can lead us astray in terms of discovering the you know some of the big open questions about yes about the Universe I think that's right I mean there are there are arrogant people in any Walk of Life And scientists are no exception to that and so there are arrogant scientists who think we've sold everything of course we haven't so humility is a proper stance for a scientist I mean it's a proper working stance because it encourages further work um but in a way to resort to a supernatural EXP explanation is a kind of arrogance because it's saying well we don't understand it scientifically therefore the uh non-scientific religious Supernatural explanation must be the right one that's arrogant what is what is humble is to say we don't know and we need to work further on it so maybe if I could psychoanalyze you for a second you have at times been just slightly frustrated with people who have super you know have a supernatural um has that changed over the years have you become like how do people that kind of have like seek Supernatural explanations how do you see those people as human beings as like do you see them as dishonest do you see them as um sort of um ignorant do you see them as I don't know it like how do you think of certainly not not not dishonest and and and I mean obviously many of them are perfect nice people so I don't I don't sort of despise them in that sense um I think it's often a misunderstanding that that um people will jump from the admission that we don't understand something they will jump straight to what they think of as an alternative explanation which is the supernatural one which is not an alternative it's a non-explanation um instead of jumping to the conclusion that science needs more work that we need to actually get do some better better science so um I I I don't have I mean personal antipathy towards such people I just think they're they're misguided so what about this really interesting space that I have trouble with so religion I have a better grasp on but um there's a large communities like you said Flat Earth Community uh that I've recently because I've made a few jokes about it I saw that there's I I've noticed that there's people that take it quite seriously so there's this bigger world of conspiracy theorists which is a kind of I mean there's elements of it that are religious as well but I think they're also scientific so the the basic uh Credo of a conspiracy theorist is to question everything which is also The Credo of a good scientist I would say so what do you make of this I mean I think it's probably too easy to say that by labeling something conspiracy you you therefore dismiss it I mean occasionally conspiracies are right and so we shouldn't dismiss conspiracy theories out of hand we should examine them on their own merits flat eism is obvious nonsense we don't have to examine that much further um but um I there may be other conspiracy theories which are actually right so I've you know grew up in the Soviet Union so I you know the space race was very influential for me on both sides of the coin uh you know there's uh conspiracy theory that we never went to the moon right and it's uh it's like I can understand it and it's very difficult to rigorously scientifically show one way or the other it's just you have to use some of the human intuition about who would have to lie who would have to work together and it's clear that very unlikely uh good PE behind that is my general intuition that most people in this world are good you know in order to really put together some conspiracy theories there has to be a large number of people working together and essentially being dishonest yes which is improbable sh the share number who would have to be in on this conspiracy and uh the share detail the attention to detail they have had to have had and so on I'd also cons worry about the motive and why would anyone want to suest that it that it didn't happen what's the what's the why is it so hard to believe I mean the the physics of it the mathematics of it the the idea of computing orbits and and and trajectories and things it it all works mathematically well why wouldn't you believe it it's a psychology question because there's something really Pleasant about um you know pointing out that the emperor has no clothes when everybody like uh you know thinking outside the box and coming up with the true answer where everybody else is diluted there's something I mean I have that for science right you want to prove the entire scientific Community wrong that's the whole no that that's that's right and and of course historically lone Geniuses have come out right sometimes yes but often people with who think they're a lone genius much more often turn out not to um so you have to judge each case on its merits the the mere fact that you're a Maverick the mere fact that you you you're going against the current tide doesn't make you right you got to show you're right by looking at the evidence so because you focused so much on on religion and disassembled a lot of ideas there and I just I was wondering if if you have ideas about conspiracy theory groups because it's such a prevalent even reaching into uh presidential politics and so on it seems like it's a very large communities that believe different kinds of conspiracy theorists is there some connection there to your thinking on religion and is curious it's a matter it's an obvious difficult thing I I don't understand why people believe things that are clearly nonsense like well Flat Earth and also the conspiracy about not landing on the moon or um that um the that the United States engineer 911 that that kind of thing um so it's not clearly nonsense it's extremely unlikely okay it's extremely unlikely um that religion is a bit different because it's passed down from generation to generation and so many of the people who are religious uh got it from their parents who got it from their parents who got it from their parents and childhood indoctrination is a very powerful force but these things like the 9/11 conspiracy theory the um Kennedy assassination conspiracy theory the man on the moon conspiracy theory these are not childhood indoctrination these are um presumably dreamed up by somebody who then tells somebody else who then wants to believe it and I don't know why people are so eager to fall in line with some just some person that they happen to read or meet who spins some yarn I can kind of understand why they believe what their parents and teachers told them when they were very tiny and not capable of critical thinking for themselves so I sort of get why the great religions of the world like Catholicism and Islam Go on p persisting it's because of childhood indoctrination but that's not true of Flat Earth ISM and sure enough Flat Earth ism is a a very minority cult way larger than I ever realized well yes I know but but so that's a really clean idea and you've articulate that in your new book and and I'll grow God and in God Delusion is the early indoctrination that's really interesting you can get away with a lot of out there ideas in terms of religious texts if um the age at which you convey those ideas at first is a young age so indoctrination is sort of an essential element of propagation of religion so let me ask on the morality side in the books that I mentioned God Delusion all growing God you described that human beings don't need religion to be moral so from an engineering perspective we want to engineer morality into AI systems so so in general where do you think morals come from in humans a very complicated and interesting question it's clear to me that the moral standards the moral values of our civilization changes as the decades go by certainly as the centuries go by even as the decades go by and we in the 21st century are quite clearly labeled 21st century people in terms of our moral values we there's a spread I mean some of us are a little bit more ruthless some of us more conservative some of us more more liberal and so on um but we all subscribe to pretty much the same views when you compare us with say 18th century 17th century people even 19th century 20th century people um so we're much less racist were much less sexist and so on than we used to be some some people are still racist and some are still sexist but the the the spread has shifted that the gaan distribution has moved and moves steadily as the centuries go by and that is the most powerful uh influence I can see on our moral values and that doesn't have anything to do with religion I mean the the the religion of the the sorry the morals of the Old Testament are Bronze Age models models they're deplorable um and um they are to be understood in terms of the people in in the desert who made them up at the time and so Human Sacrifice um uh an eye for an eye and a tooth for a tooth um Petty Revenge killing people for breaking the Sabbath all that kind of thing um inconceivable now so at some point religious texts may have in part reflected Ed that Gan distribution at that time sure they did I'm sure they always reflect that yes and then now but the the the sort of almost like the meme as you describe it of uh ideas moves much faster than religious text do than you religion yes so basing your morals on on religious texts which were written Millennia ago yeah um is not a great way to proceed I think that's pretty clear so um not only should we not get our morals from such text but we don't we quite clearly don't um if we did then we we'd be discriminating against women and we'd be we'd be um racist we'd be killing homosexuals and so on um so so we we we don't and we shouldn't now of course it's possible to by the to to use your 21st century standards of morality and you can look at the Bible and you can cherry-pick uh particular verses which conform to our modern morality and you'll find that Jesus said some pretty nice things which is great but you're using your 21st centur morality to decide which verses to pick which verses to reject and so why not cut out the middleman of the Bible and go straight to the 21st century morality which is where that comes from is a much more complicated question why is it that morality moral values change as the centuries go by they undoubtedly do and it's a very interesting question to ask why it's a it's another example of cultural Evolution just as technology progresses so moral values progress for probably very different reasons but it's it's interesting if the direction in which that progress is happening has some evolutionary value or if it's merely a drift that can go into any direction I'm not sure it's any direction and I'm not sure it's evolutionarily valuable what it is is um Progressive in the sense that each step is a step in the same direction as the previous step so it becomes uh more gentle more decent as by modern standards more liberal um less violent see but more decent I think you're using terms and interpreting everything in the context of the 2st century because genas Khan would probably say that this is not more decent because we're now you know there's a lot of weak members of society they were not murdering yes and I was careful to say by by the standard of the 21st century by by our standards if we with hindsight look back at at history what we see is a trend in the direction towards us towards our present right our our present value system for us we see progress but it's it's an open question whether that won't you know I don't see necessarily why we can never return to genas cont well we could um I suspect we won't uh but um it but if you look at the history of moral values over the centuries it is in a progressive I use the word Progressive not in a value judgment sense in the sense of of a transitive sense each step is the same is the same direction as the previous step so things like we don't um derive entertainment from torturing cats um we don't derive entertainment from from like the Romans did in the Coliseum from from that state or rather or or rather we suppress uh the desire to get I mean to have PL it's probably in us somewhere so there's a bunch of parts of our brain one that probably you know limic system that wants certain pleasures and that's uh I I don't I mean I I wouldn't have said that but um you're limited to think that you like well no there's a there's a Dan Carlin of Hardcore History that's a really nice explanation of how we've enjoyed watching the torture of people the fighting of people just the torture the suffering of people throughout history as entertainment uh until quite recently and now everything we do with sports we're kind of channeling that feeling into something else so I mean there there is some dark aspects of human nature there are underneath everything and I do hope this like higher level software we've built will keep us at Bay I'm also Jewish and have history with the uh the Soviet Union and the Holocaust and I clearly remember that uh some of the darker aspects of human nature creeped up there they do there have been uh there have been steps backwards admittedly and the Holocaust is obvious one but if you take a broad view of History it's it's the same direction so Pamela mordic in machines who think has written that AI began with an ancient wish to forge the gods do you see it's it's a poetic description I suppose but uh do you see a connection between our civilizations historic desire to create Gods to create religions and our modern desire to create technology and intelligent technology I suppose there's a link between an ancient desire to explain away mystery and um and science but um intelligence artificial intelligence creating Gods creating new Gods um and I forget I read somewhere a somewhat factious um paper which said that we have a new God is called Google and yeah and and we we we pray to it and we worship it and we and we ask its advice like an Oracle and so on um that's fun and and but you don't see that you see that as a fun statement a fous statement you don't see that as a kind of truth of us creating things that are more powerful than ourselves a natural sort of it has a kind of poetic resonance to it which I get I wouldn't I wouldn't but not I would I wouldn't have bothered to make the Point myself it that way all right so you don't think AI will become our new go a new religion a new Gods like Google well yes I mean I I can see that um the future of intelligent machines or indeed intelligent aliens from outer space might yield beings that we would regard as gods in the sense that they are so Superior to us that we might as well worship them that's highly plausible I think but I see a very fundamental distinction between a God who is simply defined as something very very powerful and intelligent on the one hand and a God who doesn't need explaining by a progressive step-by-step process like Evolution or like or like engineering design so um the different suppose we did meet an alien from outer space who was marvelously magnificently more int ENT than us and we would sort of worship it and for that reason nevertheless it would not be a God in the very important sense that it did not just happen by to be to be there like God is supposed to it must have come about by a gradual stepbystep incremental Progressive process presumably like darwinian Evolution there all the difference in the world between those two intelligence design comes into the universe late as a product of a progressive evolutionary process or Progressive engineering design process so most of the work is done through this slow moving exactly progress exactly yeah the yeah it's but there's still this desire to get answers to the why question that if if we're if the world is a simulation if we're living in a simulation that there's a program like creature that we can ask questions of this okay well let's let's pursue the idea that we're living in a simulation which is not not totally Ridiculous by the way um there we go um then you still need to explain the programmer the programmer had to come into existence by some even if we're in a in a simulation the the programmer must have evolved or if if he's in a in a sort of or she if she's in if she's in a meta simulation then the The Meta Meta programmer must have evolved by by by a gradual process you can't escape that fundamentally you've got to come back to a a a a gradual incremental process of explanation to start with there's no shortcuts in this world uh exactly but maybe to linger on that point uh about the simulation do you think it's an interesting basically talk to uh board the the heck out of everybody asking this question but uh whether you live in a simulation do you think first do you think we live in a simulation second do you think it's a interesting thought experiment it's certainly an interesting thought experiment I first met it in a science fiction novel by Daniel galloy called um counterfeit world uh in which um it's all about I mean our heroes are running a gigantic computer which which simulates the world and um and something goes wrong and so one of them has to go down into the simulated World in order to fix it and then the the the Deno of the thing the climax to the novel is that they discover that they themselves are in another simulation at a at a high level so I was intrigued by this and I love others of Daniel Gallo's science fiction novels then um it was revived seriously by Nick Bostrom Bostrom talking to him in an hour okay um and um he goes further not just treat it as a science fiction speculation he actually thinks it's positively likely I mean I think it's very likely actually well he's he makes like a probabilistic argument which you can use to come up with very interesting conclusions about this the nature of this universe I mean he think he thinks that that that that we're we're in a simulation done by so to speak our descendence of the future that the products but it's still a product of evolution it's still ultimately going to be a product of Evolution even though the super intelligent people of the future um uh have created our world and you and I are just a simulation and this table is is a simulation and so on I don't actually in my heart of hearts believe it but but I I like his argument well so the interesting thing is um I agree with you but the interesting thing to me if I would say if we're living in a simulation that in that simulation to make it work you still have to do everything gradually just like you said that even though it's programmed I don't think there can be Miracles otherwise well no I mean the the programmer the the higher up the upper ones have to have evolved gradually however the simulation they create could be instantaneous I mean they could be switched on and we and we come into the world with fabricated memories true but what I'm what I'm trying to convey so you're saying uh the the broader statement but I'm saying from an engineering perspective both the programmer has to be slowly evolved and the simulation because it's like I from an engineering perspective oh yeah it takes a long time to write a program uh no like Ju Just I don't think you can create the universe in a snap I think you have to grow it okay well uh that's that's a good point that's an arguable Point by the way um I I I have thought about using the Nick Bostrom um I idea to Solve the Riddle of how we talking we were talking earlier about why the human brain can achieve so much MH um I thought of this when my then 100-year-old mother was marveling at what I could do with a with a smartphone and and I could you know call look up anything in the encyclopedia I could play her music that she liked and so said is it all in that in that tiny little phone no it's it's out there it's it's in the cloud it's and maybe what most of what we do is in a cloud so maybe if if we're if we are a simulation yeah then then um all the power that we think is in our skull it actually may be like the power that we think is in the iPhone um but is that actually out there in it's an interface to something else I mean that's what um including Roger Penrose with pism that Consciousness is somehow a fundamental part of physics that it doesn't have to actually all reside inside our brain but Roger thinks it does reside in in in the skull whereas I'm I'm suggesting that that it doesn't that it that that it's that that there's a cloud that'd be a fascinating uh a fascinating notion on a small tangent have you um familiar with the work of Donald uh Hoffman I guess maybe not saying his name correctly but just forget the name the idea that there's a difference in reality and perception so like we biological organisms perceive the world in order for the natural selection process to be able to survive and so on but that doesn't mean that our perception actually reflects the fundamental reality the physical reality underneath well I do think that um although it reflects the fundamental reality I do believe there is a fundamental reality um I do think that what that our perception is constructive in the sense that we um construct in our minds a model of what we're seeing and so this is really the view of people who work on visual Illusions Like Richard Gregory who point out that things like a NECA Cube um which flip from this a two-dimensional picture of a cube on on on sheet of paper but we see it as a three-dimensional Cube and it flips from one orientation to another uh at regular intervals what's going on is that the brain is is constructing a cube but the sense data are compatible with two alternative cubes and so rather than stick with one of them it alternates between them I think that's just a uh a model for what we do all the time when we see a table when we see a person when we see a when we see anything we're um using the sense data to construct or or make use of a preps previously constructed model um I noticed this when when I meet somebody who actually is say a friend of mine but I until I kind I realize that that it is him he he looks different and then when I finally clock that that it's him his features switch like a NE Cube interes into the familiar form is as it were I've taken his face out of the filing cabinet inside um and grafted it onto or used used the sense data to to to to in to invoke it yeah we did some kind of miraculous compression on this whole thing to be able to filter out most of the sense data and makes it makes sense of it that's it's just a magical thing that we do so you've written several many amazing books but let me ask what books um technical or fiction or philosophical had a big impact on your own life what um what books would you recommend people consider reading in their own intellectual Journey Darwin of course uh and um the original I've actually ashamed to say never uh read Darwin he's astonishingly preent because considering he was writing in the middle of the 19th century um Michael gelin said he's working a 100 years ahead of his time everything except genetics is amazingly right and amazingly far ahead of his time um and of course you need to read the the updatings um that have happened since his time as well I he would be astonished by well let Al Lear um whats on criek of course but he'd be astonished by meling genetics as well and yeah it' be fascinating to to see what he thought about D what he would think about DNA I mean yes it would because in many ways it it um clears up what appeared in his time to be a riddle um in the digital nature of genetics um clears up what what was a problem what was a big problem gosh there's so much that I could think of I can't I can't really is there is there something outside sort of more fiction is there when you think Young was there books that just kind of outside of kind of the realm of science religion that just kind of sparked your yes well actually um I I have I suppose I could say that I've learned some some science from science fiction um I I me I mentioned Daniel galloy and that's one example but another of his novels called Dark Universe which is not terribly well known but it's a very very nice science fiction story it's about a world of Perpetual darkness and we don't we're not told at the beginning of the book why these people are in darkness they they stumble around in some kind of underground world of caverns and passages using echolocation like bats and whales um to to get around and they've adapted presumably by darwinian means to survive in perpetual total darkness but what's interesting is that their mythology their religion has Echoes of Christianity but it's based on light and so there's been a fall from a from a an a paradise world that once existed where light Reigns Supreme and um because of the sin of mankind light banished them so they they no longer are in light's presence but but light survives in the form of Mythology and in the form of sayings like a great light Almighty oh for light's sake don't do that and I and I I hear what you mean rather than I see what you what you mean so the some of the same religious elements are present in this other totally kind of absurd different form yes and so it's a wonderful I wouldn't call it SATA because it's too good natured for that a wonderful parable about Christianity and the doctrine the theological doctrine of the Fall um so I find that that kind of Science Fiction immensely stimulating Fred hil's the black cloud oh by the way anything by Arthur C Clark I find very very wonderful too uh Fred Hall is the black cloud his first science fiction novel um where he well I I learned I learned a lot of science from that it has It suffers from an obnoxious hero unfortunately but apart from that you can learn a lot of science from it um another of his novels the um AA Andromeda which by the way the the the theme of that is taken up by Carl Sean science fiction novel another wonderful writer carlan um contact where the idea is again we we will we will not be visited from Outer Space by physical bodies we will be visited possibly we might be visited by radio but the the radio signals could manipulate us and actually have a concrete influence on the world if they make us or persuade us to build a computer which which runs their software so they can then transmit their software by by radio and then the computer takes over the world and this is the same theme in both um hil's book and Sean's book I I presume them I don't know whether Sean knew about H's book probably did um and and but it's a idea that that that that we we will never be invaded by physical bodies The War of the Worlds of HD wells will never happen but we could be invaded by radio signals code coded information which is sort of like DNA and and um we we are we we are I've called them we are survival Machines of of our DNA so it has great resonance for for me because I think of us I think of body physical bodies biological bodies as being manipulated by coded information DNA which has come down through through generations and in the space of memes it doesn't have to be physical it can be transmitted through the through the space information that's a fascinating possibility that uh from outer space we can be infiltrated by other memes by other ideas and thereby controlled in that way let me ask the last the silliest or maybe the most important question what is the meaning of life what gives your life fulfillment purpose happiness meaning um from a scientific point of view the meaning of life is the propagation of DNA but that's not what I feel that that's not the meaning of my life so the meaning of my life is something which is probably different from yours and different from other people's but we each we each make our own meaning so um we we we set up goals we want to achieve we want to write a book we want to um do whatever it is we do write a quartet we want to win a football match um and these are these are short-term goals well maybe even quite long-term goals which are set up by our brains which have goal-seeking Machinery built into them but what we feel we don't feel motivated by the desire to pass on our DNA mostly um we have other other goals which can be very uh moving very important uh they could even be called called spiritual in some cases um we want to understand the riddle of the universe we want to understand Consciousness we want to understand how the brain works um these are all noble goals some of them can be noble goals anyway and they are a far cry from the fundamental biological goal which is the propagation of DNA but the Machinery that enables us to set up these higher level goals is originally programmed into us by natural selection of DNA the propagation of DNA but um what do you make of this unfortunate fact that we are mortal do you Ponder your IM mortality does it make you sad does it I I ponder it um it it would it makes me sad that I shall have to leave um and not see what's going to happen next um um if there's something frightening about mortality apart from sort of missing as I've said something more deeply Darkly frightening it's the idea of Eternity but eternity is only frightening if you're there eternity before we were born billions of years before we were born and we were effectively dead before we were born as I think it was Mark Twain said I was dead for billions of years before I was born and never suffered the smallest inconvenience that's how it's going to be afterward after we leave so I think of it as really eternity is a frightening Prospect and so the best way to spend it is under a general anesthetic which is what it'll be beautifully put Richard it is a huge honor to meet you to talk to you thank you so much for your time thank you very much thanks for listening to this conversation with Richard Dawkins and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using Code Lex podcast if you enjoy this podcast subscribe on YouTube review with five stars and APPA podcast support on patreon or simply connect with me on Twitter at Lex Freedman and now let me leave you with some words of wisdom from Richard dokins we are going to die and that makes us the lucky ones most people are never going to die because they're never going to be born the potential people who could have been here in my place but will in fact never see the light of day outnumber the sand grains of Arabia certainly those unborn ghosts include greater poets than Keats scientists greater than Newton we know this because the set of possible people allowed by our DNA so massively exceeds the set of actual people in the teeth of these Stupify odds it is you and I in our ordinariness that are here we privileged few who won the lottery of birth Against All Odds how dare we whine at our inevitable return to that prior state from which the vast majority have never stirred thank you for listening and hope to see you next time |
David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning | Lex Fridman Podcast #86 | the following is a conversation with David silver who leads the reinforcement learning research group a deep mind and was the lead researcher on alphago alpha 0 and co led the Alpha star and Museum efforts and a lot of important work in reinforcement learning in general I believe alpha zero is one of the most important accomplishments in the history of artificial intelligence and David is one of the key humans who brought alpha zero to life together with a lot of other great researchers at deep mind he's humble kind and brilliant we were both jet lagged but didn't care and made it happen it was a pleasure and truly an honor to talk with David this conversation was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong or in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars an apple podcast support on patreon or simply connect with me on Twitter Alex Friedman spelled Fri DM aen as usual I'll do a few minutes of as now and never any ads in the middle they can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience quick summary of the ads to sponsors masterclass and cash app please consider supporting the podcast by signing up to master class and master class comm slash flex and downloading cash app and using code and Lex podcast this show is presented by cash app the number one finance app in the App Store when you get it use code Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app allows you to buy Bitcoin let me mention that cryptocurrency in the context of the history of money it's fascinating I recommend a cent of money as a great book 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David silver what was the first program you've ever written and what programming language do you remember I remember very clearly he have my my parents brought home this BBC modeled B microcomputer it was just this fascinating thing to me I was about seven years old and couldn't resist just playing around with it so I think first program ever was writing my name out in different colors and getting it to loop and repeat that and there was something magical about that which just led to more and more how did you think about computers back then like the magical aspect of it that you can write a program and there's this thing that you just gave birth to it's able to creative visual elements and live in its own or did you not think of it in those romantic notions was it more like oh that's cool I can I can solve some puzzles it was always more than solving puzzles it was something where you know there was this limitless possibilities once you have a computer in front of you you can do anything with it that's um I used to play with Lego with the same feeling you can make anything you want out of Lego but even more so with a computer you know you don't you're not constrained by the amount of kit you've got and so I was fascinated by it and started pulling out there you know the user guide and the advanced user guide and then learning so I started in basic and then you know later 6502 my father was also became interested in there in this machine and gave up his career to go back to school and study for an a master's degree in in artificial intelligence funnily enough Essex University when I was when I was seven so I was exposed to those things at an early age he showed me how to program in Prolog and do things like querying your family tree and those are some of my earlier earliest memories of trying to trying to figure things out on a computer those are the early steps in computer science programming but when did you first fall in love with artificial intelligence or were the ideas the dreams of AI I think it was really when I when I went to study at university so I was an undergrad at Cambridge and studying computer science and and I really started to question you know what what really are the goals what what's the goal where do we want to go with with computer science and it seemed to me that the the only step of major significance to take was to try and recreate something akin to human intelligence if we could do that that would be a major leap forward and that idea certainly wasn't the first to have it but it you know nestled within me somewhere and and became like a bug you know I really wanted to to crack that problem so you thought it was like you had a notion that this is something that human beings can do it is possible to create an intelligent machine well I mean unless you believe in something metaphysical then what are our brains doing well at some level their information processing systems which are able to take whatever information is in there transform it through some form of program and produce some kind of output which enables that that human being to do all the amazing things that they can do in this incredible world so so then do you remember the first time you've written a program that because you also had an interesting games do you remember the first time you were in the program that beat you in a game said I won't beat you at anything sort of achieved Super David silver level performance so I used to work in the games industry so for five years I programmed games for my first job so it was a amazing opportunity to get involved in a startup company and so I I was involved in in building AI at that time and so for sure there was a sense of building handcrafted what people used to call AI in the games industry which i think is not really what we might think of as AI and its fullest sense but something which is able to to take actions and in a way which which makes things interesting and challenging for their for the for the human player and at that time I was able to build you know these handcrafted agents which in certain limited cases could do things which which were able to do better than me but mostly in these kind of twitch like scenarios where where they were able to do things faster or because they had some pattern which was able to exploit repeatedly I think if we're talking about real AI the first experience for me came after that when I I realized that this path I was on wasn't taking me towards it wasn't it wasn't dealing with that bug which I still had inside me to really understand intelligence and try and and try and solve it everything people were doing in games was you know short-term fixes rather than long-term vision and so I went back to study for my PhD which was fairly enough trying to apply reinforcement learning to the game of go and I built my first go program using reinforcement learning a system which would by trial and error play against itself and was able to learn which patterns were actually helpful to predict whether it's going to win or lose the game and then choose the moves that led to the combination of patterns that would mean that you're more likely to win in that system that system beat me how did that make you feel make me feel good I was there as sort of the yeah then is the it's a mix of a sort of excitement and was there a tinge of sort of like almost like a fearful aw you know it's like in space 2001 Space Odyssey kind of realizing that you've created something that there's you know that is that's achieved human level intelligence in this one particular little task and in that case I suppose a neural networks weren't involved there were no neural networks in those days this was pre deep learning revolution but it was a principled self learning system based on a lot of the principles which which people are still using in deep reinforcement learning how did I feel I I think I found it immensely satisfying that a system which was able to learn from first principles for itself was able to reach the point that it was understanding this domain better than better than I could and able to outwit me I don't think it was a sense of or it was a sense that satisfaction that this that's something I felt should work had worked so to me alphago and I don't know how else to put it but to me alphago and alpha a girl zero mastery in the game of girl is again to me the most profound and inspiring moment in the history of artificial intelligence so you're one of the key people behind this achievement and I'm Russian so I really felt the first sort of seminal achievement one deep blue beat garry kasparov in 1987 so as far as I know the AI community at that point largely saw the game of Go was unbeatable in AI using the the sort of the state of the art to brute force methods search methods even if you consider at least the way I saw it even if you consider arbitrary exponential ski scaling of compute go would still not be solvable hence why it was thought to be impossible so given that the game of go was impossible to to master one was the dream for you you just mentioned your PG thesis of building the system that plays go what was the dream for you that you could actually build a computer program that achieves world-class not necessarily beat the world champion but I cheesed that kind of level of playing go first of all thank you that's very kind West and funnily enough I just came from a panel where I was actually in a conversation with Garry Kasparov and Marie Campbell who was the author of deep blue and it was their first meeting together since the since the match yesterday so I'm literally fresh from that experience so these are amazing moments when they happen but where did it all start well for me it started when I became fascinated in the game of go so go for me I've grown up playing games I've always had a fascination in in in board games I played chess as a kid I played Scrabble as a kid when I was at university I discovered the game of go and and to me it just blew all of those other games out of the water it was just so deep and profound in its in its complexity with endless levels to it what I discovered was that I could devote endless hours to this game and I knew in my heart of hearts that no matter how many hours I would devote to it I would never become a you know a grandmaster or there was another path and the other path was to try and understand how you could get some other intelligence to play this this game better than I would be able to and so even in those days I had this idea that you know what if what if it was possible to build a program that could crack this and as I started to explore the domain I discovered that you know this was really the domain where people felt deeply that if progress could be made and go it really mean a giant leap forward for a I it was the the challenge where all other approaches had failed you know this is coming out of the area you mentioned which was in some sense their the golden era for further classical methods of a I like heuristic search in the 90s you know they all they all fell one after another not just chess with deep blue but checkers backgammon Othello there were numerous cases where where systems built on top of heuristic search methods with you know his high-performance systems have been able to defeat the human world champion in each of those domains and yet in that same time period there was a million dollar prize available for the game of go for the first system to be a human professional player and at the end of that time period in year 2000 when the prize expired the strongest go program in the world was defeated by a nine-year-old child when that nine year old child was giving 9 free moves to the computer at the start of the game and to try and even things up yeah and computer go X but beat that strongest same strongest program with 29 handicaps tones 29 free moves so that's what the state of affairs was when I became interested in this problem in around 2000 and 2003 when I I start started working computer go there was nothing they were there was just there was very very little in the way of progress towards meaningful performance again anything approaching human level and so people they it wasn't through lack of effort people have tried many many things and so there was a strong sense that that something different would be required for go than then had been needed for all of these other domains where I had a I had been successful and maybe the single clearest example is that that go unlike those other domains had this kind of intuitive property that a go player would look at a position and say hey you know here's this mess of black and white stones but from this mess oh I can I can predict that that's this part of the board has become my territory this part of the boards become your territory and I've got this overall sense I'm going to win and this is about the right move to play and that intuitive sense of judgment of being able to evaluate what's going on in a position it was pivotal to humans being able to play this game and something that people had no idea how to put into computers so this question of how to evaluate in a position how to come up with these intuitive judgments was the key reason why go was so hard in addition to its enormous search space and the reason why methods which had succeeded so well elsewhere failed and go and so people really felt deep down that that you know in order to crack go we would need to get something akin to human intuition and if we got something akin to human intuition we'd be able to self you know much many many more problems in AI so to me that was the moment where it's like okay this is not just about playing the game of Go this is about something profound and it was back to that bug which had been itching me all those years now this is the opportunity to do something meaningful and and transformative and and I guess a dream was born that's a really interesting way to put it almost this realization that you need to find formulate girls are kind of a prediction problem versus a search problem was the intuition I mean I maybe that's the wrong crude term but the to give it us the ability to kind of Intuit things about positional structure of the board well okay but what about the learning part of it did you have a sense that you have to that learning has to be part of the system again something that hasn't really as as far as I think except with TD Guerin and in the 90s was RL a little bit hasn't been part of those state-of-the-art game playing systems so I strongly felt that learning would be necessary and that's why my my PhD topic back then was trying to apply reinforcement learning to the game of CO and not just learning of any type but I felt that the only way to really have a system to progress beyond human levels of performance wouldn't just be to mimic how humans do it but to understand for themselves and how else can a machine hope to understand what's going on except through learning if you're not learning what else are you doing while you're putting all the knowledge into the system and that just feels like a something which decades of AI have told us is is maybe not a dead end but certainly has a ceiling to the capabilities it's known as the you know knowledge acquisition bottleneck that there the more you try to put into something the more brittle the system becomes and and so you just have to have learning you have to have learning that's the only way you're going to be able to get a system which has sufficient knowledge in it you know millions and millions of pieces of knowledge billions trillions of a form that it can actually apply for itself and understand how those billions and trillions of pieces of knowledge can be leveraged in a way which will actually lead it towards its goal without conflict or or other issues yeah I mean if I put myself back in there in that time I just wouldn't think like that without a good demonstration of RL I would I would think more in the symbolic AI like that though it would not learning but sort of a simulation of knowledge base like a growing knowledge base but it would still be sort of pattern based lot like basically have little rules that you kind of assemble together into a large knowledge base well in a sense that was the state of the art back then so if you look at the go programs which had been competing for this prize I mentioned they were an assembly of different specialized systems some of which used huge amounts of human knowledge to describe how you should play the opening how you should all the different patterns that were required to to play well in the game of Go endgame Theory combinatorial game theory and combined with more principled search based methods which we're trying to solve for particular sub parts of the game like life and death connecting groups together all these amazing subproblems that just emerged in the game of Go there were there were different pieces all put together into this like collage which together would try and play against a human and although not all of the pieces were handcrafted the overall effect was nevertheless still brittle and it was hard to make all these pieces work well together and so really what I was pressing for and the main innovation of the approach they took was to go back to first principles and say well let's let's back off that and try and find a principled approach where the system can learn for itself it just from the outcome like you know learn for itself if you try something did that did that help or did it not help and only through that procedure can you arrive at knowledge which is which is verified the system has to verify it for itself not relying on any other third party to say this is right or this is wrong so that principle was already you know very important in those days but unfortunately we were missing some important pieces back then so before we dive into may be discussing the beauty of reinforcement learning let's think it's the back who kind of skipped skipped it a bit but the rules of the game of go what's the the elements of it perhaps contrasting to chess that sort of you really enjoyed as a human being and also that make it really difficult as a a I machine learning problem so the game of CO was has remarkably simple rules if that's so simple that people have speculated that if we were to meet alien life at some point that we wouldn't be able to communicate with them but we would be able to play hello go with that probably have discovered the same rule set yeah so the game is played on a on a 19 by 19 grid and you play on the intersections of the grid and the players take turns and the aim of the game is very simple it's to surround as much territory as you can as many of these intersections with your stones and just around more than your opponent does and the only nuance to the game is that if you fully surround your opponent's piece then you get to capture it and remove it from the board and it counts as your own territory now from those very simple rules immense complexity arises it's kind of profound strategies in how to surround territory how to kind of trade-off between making solid territory yourself now compared to building up influence that will help you acquire territory later in the game how to connect groups together how to keep your own groups alive which which patterns of stones are most useful compared to others there's just immense knowledge and human go players have played this game for it was discovered thousands of years ago and human go players have built up its immense knowledge base over over the years it's studied very deeply and played by something like 50 million players across the world mostly in China Japan and Korea where it's a important part of a culture so much so that it's considered one of the four ancient arts that was required by Chinese scholars so there's a deep history there but there's interesting quality so if I is it a comparative chess chess is in the same way as it is in Chinese culture of a goal in chess in Russia is also considered one of the secret arts so if we contrast sort of go with chess as interesting qualities about go maybe you can correct me if I'm wrong but the evaluation of a particular static board is not as reliable like you can't in chess you can kind of assign points to the different units and it's kind of a pretty good measure of who's one who's losing it's not so clear yeah so this game of the HOH you know you find yourself in a situation where both players have played the same number of stones actually captures a strong level of play happen very rarely which means that any moment in the game you've got the same number of white stones and black stones and the only thing which differentiates how well you're doing is this intuitive sense of you know where are the territories ultimately going to form on this board and when you if you look at the complexity of a real go position you know it's it's mind boggling that kind of question of what will happen in in 300 moves from now when you when you see just a scattering of twenty white and black stones intermingled and and so that that challenge is the reason why position of value is so hard in go compared to two other games in addition to that has an enormous search space so there's around ten to one hundred and seventy positions in the game of go that's an astronomical number and that search spaces is so great that traditional heuristic search methods that were so successful and things like deep blue and and chess programs just kind of fall over and go so a which pointed reinforcement learning enter your life your research life your way of thinking we just talked about learning but reinforcement learning is very particular kind of learning one that's both philosophically sort of profound yeah but also one that's pretty difficult to get to work as if we look back in the earth at least the early days so when did that enter your life and how did that work progress so I had just finished working in the games industry this startup company and I took I took a year out to discover for myself exactly which path I wanted to take I knew I wanted to study intelligence but I wasn't sure what that meant at that stage I really didn't feel had the tools to decide on exactly which path I wants to follow so during that year I I read a lot and one of the things I read was Saturn Umberto the sort of seminal tech spec are an introduction to reinforcement learning and when I read that textbook I I just had this resonating feeling that this is what I understood intelligence to be and this was the path that I felt would be necessary to go down to make progress in in AI so I got in touch with rich Saturn and asked him if he would be interested in supervising me on a PhD thesis in in computer go and he he basically said that if he's still alive he'd be happy to but unfortunately he'd been you know struggling with very serious cancer for some years and he really wasn't confident at that stage that he'd even be around to see the end event but fortunately that part of the story worked out very happily and I found myself out there in Alberta they've got a great games group out there with a history of fantastic working in board games as well as rich that in the father of RL so it was the the natural place for me to go in some sense to study this question and the more I looked into it the more the more strongly ie I felt that this wasn't just the path to progress in computer go but really you know this this was the thing I'd been looking for this was really an opportunity to to frame what intelligence means like what does what are the goals of AI in a clear single clear problem definition such that if we're able to solve that play a single problem definition in some sense we've cracked the problem of AI so to you reinforcement learning ideas at least sort of echoes of it would be at the core of intelligence it is as a core of intelligence and if we ever create in a human level intelligence system it would be at the core of that kind of system let me say it this way that I think I think it's helpful to separate out the problem from the solution so I see the problem of intelligence I would say it can be formalized as the reinforcement learning problem and that that formalization is enough to capture most if not all of the things that we mean by intelligence that that they can all be brought within this this this framework and gives us a way to access them in a meaningful way that allows us as as scientists to understand intelligence and us as computer scientists to to build them and so in that sense I feel that it gives us a path maybe not the only path but a path towards AI and so do I think that any system in the future that that's you know sold AI would would have to have RL within it well I think if you ask that you're asking about the solution methods I would say that if we have such a thing it would be a solution to the RL problem now what particular methods have been used to get there well we should keep an open mind about the best approaches to actually solve any problem and you know the things we have right now for reinforcement learning maybe maybe then maybe I believe they've got a lot of legs but maybe we're missing some things maybe there's gonna be better ideas I think we should keep her you know let's remain modest and we're at the early days of this field and and there are many amazing discoveries ahead of us for sure the specifics especially of the different kinds of our ell approaches currently there could be other things there followed is a very large umbrella of our ell but if it's if it's okay can we take a step back and kind of ask the basic question of what is to you reinforcement learning so reinforcement learning is the study and the science and the problem of intelligence in the form of an agent that interacts with an environment so the problem is trying to self is represented by some environment like the world in which that agent is situated and the goal of RL is clear that the agent gets to take actions those actions have some effects on the environment and the environment gives back an observation to the agent saying you know this is what you see your sense and one special thing which it gives back is it's called the raw signal how well it's doing in the environment and the reinforcement learning problem is to simply take actions over time so as to maximize that reward signal so a couple of basic questions what types of RL approaches are there so I don't know if there's a nice brief in words way to paint the picture of sort of value based model based policy based reinforcement learning yeah so now if we think about okay so there's this ambitious problem definition of RL it's really you know it's truly ambitious it's trying to capture and encircle all of the things in which an agent interacts with an environment and say well how can we formalize and understand what it means to to crack that now let's think about the solution method well how do you solve a really hard problem like that well one approach you can take is is to decompose that that very hard problem into into pieces that work together to solve that hard problem and and so you can kind of look at the decomposition that's inside the agents head if you like and ask well what form does that decomposition take and some of the most common pieces that people use when they're kind of putting this system the solution method together some of the most common pieces that people use are whether or not that solution has a value function that means is it trying to predict explicitly trying to predict how much reward it will get in the future does it have a representation of a policy that means something which is deciding how to pick actions is is that decision-making process explicitly represented and is there a model in the system is there something which is explicitly trying to predict what will happen in the environment and so those three pieces are to me some of the most common building blocks and I understand the different choices in RL as choices of whether or not to use those building blocks when you're trying to decompose the solution you know should I have a value function represented so they have a policy represented should I have a model represented and there are combinations of those pieces and of course other things that you could add to add into the picture as well but those those three fundamental choices give rise to some of the branches of RL with which we're very familiar and so those as you mentioned there is the choice of what's specified or modeled explicitly and the idea is that all of these are somehow implicitly learned within the system so it's almost a choice of how you approach a problem do you see those as fundamental differences or these almost like small specifics like the details of how you saw the problem but they're not fundamentally different from each other I think the the fundamental idea is is maybe at the higher level the fundamental idea is the first step of the decomposition is really to say well how are we really going to solve any kind of problem where you're trying to figure out how to take actions and just from a stream of observations you know you've got some agents situated it's sensory motor stream and getting all these observations here and getting to take these actions and and what should it do how can even broach that problem you know me the complexity of the world is so great that you can't even imagine how to build a system that would that would understand how to deal with that and so the first step of this decomposition is to say well you have to learn the system has to learn for itself and so note that the reinforcement learning problem doesn't actually stipulate that you have to learn but you could maximize your awards without learning it would just say wouldn't do a very good job event yes so learning is required because it's the only way to achieve good performance in any sufficiently large and complex environment so so that's the first step so that step give commonality to all of the other pieces because now you might ask well what should you be learning what is learning even mean you know in this sense you know learning might mean well you're trying to update the parameters of some system which is then the thing that actually picks the actions and and those parameters could be representing anything they could be parameterizing a value function or a model or a policy and so in that sense there's a lot of commonality in that whatever is being represented there is the thing which is being learned and it's being learned with the ultimate goal of maximizing rewards but but the way in which you decompose the problem is is is really what gives the semantics to the whole system like are you trying to learn something to predict well like a value function or a model are you learning something to perform well like a policy and and the form of that objective like it's kind of giving the semantics to the system and so it really is at the next level down a fundamental choice and we have to make those fundamental choices a system designers or enable are our algorithms to be able to learn how to make those choices for themselves so then the next step you mentioned the very for the very first thing you have to deal with is can you even take in this huge stream of observations and do anything with it so the natural next basic question is what is the what is deep reinforcement learning and what is this idea of using neural networks to deal with this huge incoming stream so amongst all the approaches for reinforcement learning deep reinforcement learning is one family of solution feds that tries to utilize powerful representations that are offered by neural networks to represent any of these different components of the solution of the agent like whether it's the value function or the model or the policy the idea of deep learning is to say well here's a powerful tool kit that's so powerful that it's Universal in the sense that it can represent any function and it can learn any function and so if we can leverage that universality that means that whatever whatever we need to represent for our policy or offer a value function or for a model deep learning can do it so that deep learning is is one approach that offers us a toolkit that is has no ceiling to its performance that as we start to put more resources into the system or more memory and more computation and more more data more experience of more interactions with the environment that these are systems that can just get better and better and better at doing whatever the job is they've asked them to do whatever we've asked that function to represent it can learn a function that does a better and better job of representing that that knowledge whether that knowledge be estimating how well you're going to do in the world the value function whether it's going to be choosing what to do in the world a policy or it's understanding the world itself what's going to happen next the model nevertheless the the the fact that neural networks are able to learn incredibly complex representations that allow you to do the policy the model or the value function is at least to my mind exceptionally beautiful and surprising like what was it is it surprising was it surprising to you can you still believe it works as well as it does do you have good intuition about why it works at all and works as well as it does I think let me take two parts to that question I think it's not surprising to me that the idea of reinforcement learning works because in some sense I think it's the I feel it's the only which can ultimately and so I feel we have to we have to address it and there must be success is possible because we have examples of intelligence and it must at some level be able to possible to acquire experience and use that experience to to do better in a way which is meaningful to environments of the complexity that humans can deal with it must be am I surprised that our current systems can do as well as they can do I think one of the big surprises for me and a lot of the community it's really the fact that deep learning can continue to perform so well despite than the fact that these neural networks that they're representing have these incredibly nonlinear kind of bumpy surfaces which two are kind of low dimensional intuitions make it feel like surely you're just going to get stuck and learning will get stuck because you won't be able to make any further progress and yet the big surprise is that learning continues and and these what appear to be local Optima turned out not to be because in high dimensions when we make really big neural nets there's always a way out and there's a way to go even lower and then he's still not another local Optima because there's some other pathway that will take you out and take you lower still and so no matter where you are learning can proceed and do better and better and breath better without bound and so that is a surprising and beautiful property of neural nets which I find elegant and beautiful and and somewhat shocking that it turns out to be the case as you said which I really like to our low dimensional intuitions that's surprising yeah yeah we're very we're very tuned to working within a three-dimensional environment and so to start to visualize what a billion dimensional neural network um surface that you're trying to optimize over what that even looks like is very hard for us and so I think that really if you try to account for the essentially the AI winter where where people gave up on Yule networks I think it's really down to that that lack of ability to generalize from from low dimensions to high dimensions because back then we were in the low dimensional case people could only build neural nets with you know 50 nodes in them or something and to to imagine that it might be possible to build a billion dimension on your net and it might have a completely different qualitatively different property was very hard to anticipate and I think even now we're starting to build the the theory to support that and and it's incomplete at the moment but all of the theory seems to be pointing in the direction that indeed this is an approach which which truly is universal both in its representational capacity which was known but also in its learning ability which is which is surprising and it makes one wonder what else were missing yes for a low demand intuitions yet there will seem obvious once it's discovered I often wonder you know when we one day do have a eyes which are superhuman in their abilities to to understand the world what will they think of the algorithms that we developed back now will it be you know looking back at these these days and you know and and and thinking that well will we look back and feel that these algorithms were were naive faire steps or will they still be the fundamental ideas which are used even in 100 thousand 10,000 years yeah Nels and I they'll they'll watch back to this conversation and I would the smile maybe a little bit of a laugh I mean my senses I think it just like on we used to think that the Sun revolved around the earth they'll see our systems of today in reinforcement learning as too complicated that the answer was simple all along there's something I just just think you said in a game of Go I mean I love those systems of like cellular automata that there's simple rules from which incredible complexity emerges so it feels like there might be some very simple approaches just like where Sutton says right these simple methods or with compute over time seem to prove to be the most effective I 100% agree I think that if we try to anticipate what will generalize well into the future I think it's likely to be the case that it's the simple clear ideas which will have the longest legs and walked or carry us farthest into the future nevertheless we're in a situation where we need to make things work day and today and sometimes that requires putting together more complex systems where we don't have the the full answers yet as to what those minimal ingredients might be so speaking of which if we could take us their bag to go what was Mogo and what was the key idea behind this system so back during my PhD on computer go around about that time there was a major new development in in which actually happened in the context of computer go and and it was really a revolution in the way that heuristic search was was done and and the idea was essentially that a position could be evaluated or a state in general could be evaluated not by humans saying whether that position is good or not or even humans providing rules as to how you might evaluate it but instead by allowing the system to randomly play out the game until the end multiple times and taking the average of those outcomes as the prediction of what will happen so for example if you're in the game of go the intuition is that you take a position and you get the system to kind of play random moves against itself all the way to the end of the game and you see who wins and if black ends up winning more of those random games than white well you say hey this is a position that favors white and if white ends up winning more of those random games than black then it favors white so that idea was known as Monte Carlo search and a particular form of Monte Carlo search that became very effective and was developed in computer go first by Remy Coulomb in 2006 and then taken further by others was something called Monte Carlo tree search which basically takes that same idea and uses that that insight to evaluate every node of a search tree is evaluated by the average of the random play outs from that from that node onwards and this idea was very powerful and suddenly led to huge leaps forward in the strength of computer go playing programs and among those the the strongest of the go playing programs in those days was a program called Mogo which was the first program to actually reach human master level on small boards nine by nine boards and so this was a program by someone called Sylvan jelly he was a good colleague of mine but I worked with him a little bit in those days of my PhD thesis and Mogo was a a first step towards the latest successes we saw and computer go but it was still missing a key ingredient Mogo was evaluating purely by random rollouts against itself and in a way it's it's truly remarkable that random play gives you anything at all yeah like how why why in this perfectly deterministic game that's very precise and involves these very exact sequences why is it that that random randomization is helpful and so the intuition is that randomization captures something about the the nature of the of the search tree that from a position that you're you're understanding the nature of the search tree from that node onwards by by by using randomization and this was a very powerful idea and I've seen this in other spaces talk to the virtual carpet and so on randomized algorithms somehow magically are able to do exceptionally well and and simplifying the problem somehow makes you wonder about the fundamental nature of randomness in our universe it seems to be a useful thing but so from that moment can you maybe tell the origin story in the journey of alphago yeah so programs based on Monty College research were a first revolution in the sense that they led to suddenly programs that could play the game to any reasonable level but they they plateaued it seemed that no matter how much effort people put into these techniques they couldn't exceed the level of amateur Dan level go players so strong players but not not anywhere near the level of professionals never mind the world champion and so that brings us to the birth of alphago which happened in the context of a startup company known as deep mind or where them where a project was born and the project was really a scientific investigation where myself and a jipang and an intern Chris Madison were exploring a scientific question and that scientific question was really is there another fundamentally different approach to to this key question of Goa the key challenge of how can you build that intuition and how can you just have a system that could look at a position and understand what moved to play or or how well you're doing in that position who's going to win and so the deep learning Revolution had just begun their systems like imagenet had suddenly been won by deep learning techniques back in 2012 and following that it was natural to ask well you know if if deep learning is able to scale up so effectively with images to to understand them enough to to classify them well why not go why why not take a the black and white stones of the NGO board and build some a system which can understand for itself what that means in terms of what moved to pick or who's going to win the game black or white and so that was our scientific question which we we were probing and trying to understand and as we started to look at it we discovered that we could build a a system so in fact our very first paper on alphago was actually a pure deep learning system which was trying to answer this question and we showed that actually a pure deep learning system with no search at all was actually able to reach human van level master level at the full game of go 19 by 19 boards and so without any search at all suddenly we had systems which were playing at the level of the best Monte Carlo tree search systems the ones with randomized rollouts so first I'm sorry to interrupt but there's kind of a groundbreaking notion let's say that's like basically a definitive step away from the a couple of decades of essentially search dominating AI yeah so what how do them make you feel would you that was a surprising from a scientific perspective in general how to make you feel I I found this to be profoundly surprising in fact it was so surprising that that we had a bet back then and like many good projects you know bets are quite motivating and Anna bet was you know whether it was possible for a system purely on on deep learning no search at all to beat a Dan level human player and so we had someone who joined our team who was a damn level player he came in and and we had this first match against him and we turned the bit where you want by the way do you handle losing and they were in except I tend to be an optimist with the with the power of of deep learning and reinforcement learning so the system won and we were able to beat this human Dan level player and for me that was the moment where where it's like okay something something special is afoot here we have a system which without search is able to to already just look at this position and understand things as well as a strong human player and from that point onwards I really felt that reaching that reaching the top levels of human play you know professional level world champion level I felt it was actually an inevitability and and if it was an inevitable outcome I was rather keen it would be us that achieve it so we scaled up this was something where you know so I had lots of conversations back then with demo so service that the head of deepmind who was extremely excited and we we made the decision to to scale up the project brought more people on board and and so alphago became something where where we we had a clear goal which was to try and crack this outstanding challenge of AI to see if we could beat the world's best players and this led within the space of not so many months to playing against the European champion fan way in a match which became you know memorable in history is the first time a go program would ever beated a a professional player and at that time we had to make a judgment as to whether when and and whether we should go and challenge the world champion and and this was a difficult to make again we were basing our predictions on on our own progress and had to estimate based on the rapidity of our own progress when we thought we would exceeds the level of the human world champion and and we tried to make an estimate and set up a match and that became the the alphago versus Lisa dolls match in 2016 and we should say spoiler alert that alphago was able to defeat Lisa doll that's right yeah so maybe a could take even a broader view alphago involves both learning from expert games and as far as I remember a self play component - where he learns by playing guess himself but in your sense what was the role of learning from experts there and in terms of your self evaluation whether you can take on the world champion what was the thing that they're trying to do more of sort of train more on expert games or was there's now another I'm asking so many poorly faced questions but did you have a hope a dream that self play would be the key component at that moment yet so in the early days of alphago we we used human data to explore the science of what deep learning can achieve and so when we had our first paper that showed that it was possible to predict the winner of the game that it was possible to suggest moves that was done using human data of solely human did yes and and and and so the reason that we did it that way was at that time we were exploring separately the deep learning aspect from the reinforcement learning aspect that was the part which was which was new and unknown to me at that time was how far could that be stretched once we had that it then became natural to try and use that same representation and see if we could learn for ourselves using that same representation and so right from the beginning actually our goal had been to build a system using self play and to us the human data right from the beginning was an expedient step to help us for pragmatic reasons to go faster towards the goals of the project then we might be able to starting solely from self play and so in those days we were very aware that we were choosing to to use human data and that might not be the long-term holy grail of AI but that it was something which was extremely useful to us it helped us to understand the system helped us to build deep learning representations which were clear and simple and easy to use and so really I would say it's it served a purpose not just as part of the algorithm but something which I continued to use in our research today which is trying to break down a very hard challenge into pieces which are easier to understand for us as researchers and develop so if you if you use a component based on human data it can help you to understand the system such that then you can build the more principled version later that does it for itself so as I said the alphago victory and I don't think I'm being sort of romanticizing this notion I think is one of the greatest moments in the history of AI so were you cognizant of this magnitude of the accomplishment at the time I mean we are you cognizant of it even now because to me I feel like it's something that would we mentioned what the AGI systems of the future will look back I think they'll look back at the alphago tree as like holy crap they figured it out this is where this is where the started well thank you again I mean it's funny because I guess I've been working on I've been working on computer go for a long time so I've been working at the time at the alphago match on computer go for more than a decade and throughout that decade I'd had this dream of what would it be like - what would it be like really - to actually be able to build a system that could play against the world champion and and I imagined that that would be an interesting moment that maybe you know some people might care about that and that this might be you know a nice achievement but I think when I arrived in in Seoul and discovered the legions of that were following us around and 100 million people that were watching the match online life I realized that I had been off in my estimation of how significant this moment was by several orders of magnitude and so there was definitely an adjustment process to to realize that this this was something which the world really cared about and which was a watershed moment and I think there was that moment of realization it was also a little bit scary because you know if you go into something thinking it's going to be may be of interest and then discover that 100 million people are watching it suddenly makes you worry about whether some of the decisions you've made where really they're the best ones or the wisest or we're going to lead to the best outcome and we knew for sure that there were still imperfections in alphago which were going to be exposed to the whole world watching and so yeah it was a it was I think a great experience and I I feel privileged to have been part of it privileged to have led that amazing team I feel privileged to have been in a moment of history like you say but also lucky that you know in a sense I was insulated from from the knowledge of I think it would have been harder to focus on the research if the full kind of reality of what was going to come to pass her had been known to me and the team I think it was you know we were we were in our bubble and we were working on research and we were trying to answer the scientific questions and then BAM you know the public sees it and and I think it was it was it was better that way in retrospect were you confident did I guess what were the chances that you could get the win so just like you said I'm a little bit more familiar with another accomplishment that we may not even get a chance to talk to I talked to us about Alpha star which is another incredible accomplishment but here you know with alpha star and beating the Starcraft there was like already a track record with alphago there this is like the really first time you get to see reinforcement learning face the best humour in the world so what was your confidence like what was the odds well we actually was there a bit but funnily enough there was so so just before the match we weren't betting on anything concrete but we all held out a hand everyone in the team held out her hand at beginning of the match and the number of fingers that they had out on the hand was supposed to represent how many games they thought we would win I guess Lisa doll and there was an amazing spread in there in the team's predictions but I have to say I predicted four one and and the reason was based purely on on data so I'm a scientist first and foremost and one of the things which we had established was that alphago in around 1 in 5 games would develop something which we called a delusion which was a kind of inner hole in its in its knowledge where it wasn't able to fully understand everything about the position and that that hole and its knowledge would persist for tens of moves throughout the game and we knew two things we knew that if there were no delusions that alphago seemed to be playing at a level that was far beyond any human capabilities but we also knew that if there were delusions the office it was true and and and in fact you know that's that's what came to pass we saw we saw all of those outcomes and Lisa doll in in one of the games played a really beautiful sequence that that that alphago just hadn't predicted and after that it it led it into this situation where it was unable to really understand the position fully and and and found itself in one of these these delusions so so indeed yeah for one was the outcome so yeah and can you maybe speak to it a little bit more what were the five games like what what happened is there interesting things that they come to memory in terms of the play of the human machine so I remember all of these games vividly of course you know moments like these don't come too often in the lifetime of her of her scientist and the the first game was was magical because it was the first time that a computer program had defeated a world champion in this Grand Challenge of go and and there was a moment where where alphago invaded Lisa dolls territory towards the end of the game and and that's quite an audacious thing to do it's like saying hey you thought this was gonna be your territory in the game but I'm going to stick a stone right in the middle of it and and and prove to you that I can break it up and Lisa dolls face just dropped he wasn't expecting a computer to to do something that audacious the second game became famous for a move known as move 37 this was a move that was played by alphago that was broke all of the conventions of go that the go players were so shocked by this they they they thought that maybe the operator had made a mistake they they thought that there's something crazy going on and and it just broke every rule that go players are taught from a very young age they just taught you know you this kind of move called the shoulder hit you you you can only play it on the third line or the fourth line and alphago played out in the fifth line and and it turned out to be a brilliant move and made this beautiful pattern in the middle of the board that ended up winning the game and so this really was a clear instance where we could say computers exhibited creativity that this was really a move that was something humans hadn't known about hadn't anticipated and computers discovered this idea they they were the ones to say actually you know here's a new idea something new not not in the domains of human knowledge of the game and and and now the humans think this is a reasonable thing to do and and it's part of go knowledge now the third game something special happens when you play against a human world champion which again I hadn't anticipated before going there which is you know these these players are amazing Lisa Dahl was a true champion eighteen time world champion and had this amazing ability to to probe alphago fer for weaknesses of any kind and in the third game he was losing and we felt we were sailing comfortably to victory but he managed to from nothing stir up this fight and build what's called a double ko these kind of repetitive positions and he knew that historically no no computer go program had ever been able to deal correctly with double code positions and he managed to summon one out of out of nothing and so for us you know this was this was a real challenge like would alphago be able to deal with this or would it just kind of crumble in the face of this situation and fortunately it dealt with it perfectly the force game was was amazing in that Lisa doll appeared to be losing this game alphago thought it was winning and then Lisa doll did something which I think only a true world champion can do which is he found a brilliant sequence in the middle of the game a brilliant sequence that led him to really just transform the position it kind of it it he found it's just a piece of genius really and after that alphago it's it's evaluation just tumbled it thought it was winning this game and all of a sudden it tumbled and said oh now I've got no chance and it starts to behave rather oddly at that point in the final game for some reason we as a team were convinced having seen alphago in the previous game suffer from delusions we as a team were convinced that it was suffering from another delusion we were convinced that it was miss evaluating the position and that something was going terribly wrong and it was only in the last few moves of the game that we realized that actually although it had been predicting it was going to win all the way through it really was and and so somehow you know it just taught us yet again that you have to have faith in in your systems when they when they exceed your own level of ability in your own judgment you have to trust in them too to know better than the new the designer once you've you've stowed in them the ability to to judge better than you can then trust the system to do so so just looking in case of deep blue beating Garry Kasparov so get garrus is I think the first time he's ever lost actually to anybody and I mean there's a similar situation loose at all it's uh it's a tragic it's a tragic loss for humans but a beautiful one I think that's kind of from the tragedy sort of emerges over time emerges the kind of inspiring story but Lisa Dahl recently announced his retirement I don't know if we can look too deeply into it but he did say that even if I become number one there's an entity that cannot be defeated so what do you think about these words what do you think about his retirement from the game ago well let me take you back first of all to the first part of your comment about Garry Kasparov because actually at the panel yesterday he specifically said that when he first lost a deep-blue he he viewed it as a failure he viewed that this this had been a failure of his but later on in his career he said he'd come to realize that actually it was a success it was a success for everyone because this marked a transformational moment for AI and so even for Kip Garry Kasparov he came to realize at that moment was was was pivotal and actually meant something much more than then you know his personal loss in that moment Lisa doll I think was a much more cognizant of that even at the time so in his closing remarks to the match he really felt very strongly that what had happened and the alphago match was not only meaningful for AI but for humans as well and he felt as a go player that it had opened his horizons and meant that he could start exploring new things it brought his joy back for the game of go because it broken all of the conventions and barriers and meant that you know suddenly suddenly anything was possible again and so you know I was sad to hear that he'd retired but you know he's been a great a great world champion over many many years and I think you know that he'll be he'll be remembered for that evermore he'll be remembered as the last person to to beat alphago I mean after after that we increased the power of the system and and the next version of alphago beats the the other strong human players 60 games to nil so you know what a great moment for him and something to be remembered for it's interestingly you spent time at triple AI on a panel with Garry Kasparov what I mean it's almost just curious to learn the conversations you've had with Garry and the because he's also now he's written a book about artificial intelligence he's thinking about AI he has kind of a view of it and he talks about alphago a lot what what's your sense be arguably I'm not just being Russian but I think Gary is the greatest chess player of all time the probably one of the greatest game players of all time and you sort of at the center of creating a system that beats one of the greatest players of all time so what's that conversation like is there anything yeah any interesting digs any bets and you come and you find new things and you profound things so Gary Kasparov has an incredible respect for what we did with alphago and you know it's it's an amazing tribute coming from from him of all people that he really appreciates and respects what what we've done and I think he feels that the progress which was happened in in computer chess which later after alphago we we built the alpha zero system which defeated the the world's strongest chess programs and to Garry Kasparov that moment in computer chess was more profound than than than deep blue and the reason he believes it mattered more was because it was done with with learning and a system which was able to discover for itself new principles new ideas which were able to play the game in a in a in a way which he hadn't always known about or anyone and in fact one of the things I discovered at this panel was that the current world champion Magnus Carlsen apparently recently commented on his improvement in performance and he attributes it to alpha zero that he's been studying the games of alpha zero and he's changed his style play more like alpha zero and it's led to him actually increasing his his his rating to a new peak yeah I guess to me just like to Gary the inspiring thing is that and just like you said with reinforcement learning reinforcement learning and deep learning machine learning feels like what intelligence is yeah and you know you could attribute it to sort of a bitter viewpoint from Gary's perspective from us humans perspective saying that sir pure search that IBM do Blue was doing is not really intelligence but somehow it didn't feel like it and so that's the magical I'm not sure what it is about learning that feels like intelligence but it but it does so I think we should not demean the achievements of what was done in previous eras of AI I think that deep blue was an amazing achievement in itself and that heuristic search of the kind that was used by deep blue had some powerful ideas that were in there but it also missed some things so so the fact that the that the evaluation function the way that the chess position was understood was created by humans and not by the machine is a limitation which means that there's a ceiling on how well it can do but maybe more importantly it means the same idea cannot be applied in other domains where we don't have access to the kind of human Grand Master's and that ability to kind of encode exactly their knowledge into an evaluation function and the reality is that the story of AI is that you know most domains turn out to be of the second type where when knowledge is messy it's hard to extract from experts or it isn't even available and so so we need to solve problems in a different way and I think alphago is a step towards solving things in a way which which puts learning as first-class citizen and says systems need to understand for themselves how to understand the world how to judge their the value of any action that they might take within that world in any state they might find themselves in and in order to do that we we make progress towards AI yeah so one of the nice things about this about taking a learning approach to the game of Go game playing is that the things you learn the things you figure out are actually going to be applicable to other problems there are real-world problems that's so that's ultimately I mean there's two really interesting things about alphago one is the science of it just the science of learning the science of intelligence and then the other is all you're actually learning to figuring out how to build systems that would be potentially applicable in in other applications medical autonomous vehicles robotics all I mean it's just open the door to all kinds of applications so the next incredible step right really the profound step is probably alphago zero I mean it's arguable I kind of see them all as the same place but really in perhaps you were already thinking that alphago zeros the natural it was always going to be the next step but it's removing the reliance on human expert games for pre-training as you mentioned so how big of an intellectual leap was this that that self play could achieve superhuman level performance it's on and maybe could you also say what is self play we kind of mentioned a few times but so let me start with self play so the idea of self play is something which is really about systems learning for themselves but in the situation where there's more than one agent and so if you're in a game and a game is a played between two players then self play is really about understanding that game just by playing games against yourself rather than against any actual real opponent and so it's a way to kind of um discover strategies without having to actually need to go out and play against any particular human player for example the main idea of alpha zero was really to you know try and step back from any of the knowledge that we'd put into the system and ask the question is it possible to come up with a single elegant principle by which a system can learn for itself all of the knowledge which it requires to play to play a game such as go importantly by taking knowledge out you not only make the system less brittle in the sense that perhaps the knowledge you were putting in was was just getting in the way and maybe stopping the system learning for itself but also you make it more general the more knowledge you put in the harder it is for a system to actually be placed taken out of the system in which it's kind of been designed and placed in some other system that maybe would need a completely different knowledge base to to understand and perform well and so the real goal here is to strip out all of the knowledge that we put in to the point that we can just plug it into something totally different and that to me is really you know the the promise of AI is that we can have systems such as that which you know no matter what the goal is no matter what goal we set to the system we can come up with we have an algorithm which can be placed into that world into that and and can succeed in achieving that goal and then that that's to me is almost the the essence of intelligence if we can achieve that and so alpha zero is a step towards that and it's a step that was taken in the context of two-player perfect information games like go and chess we also applied it to Japanese chess so just to clarify the first step was alphago zero the first step was to try and take all of the knowledge out of alphago in such a way that it could play in a in a fully self discovered way purely from self play and to me the the motivation for that was always that we could then plug it into other domains but we saved that bat until later well in in fact I mean just for fun I could tell you exactly the moment where where the idea for alpha zero occurred to me because I think there's maybe a lesson there for for researchers who kind of too deeply embedded in their in their research and you know working 24/7 to try and come up with the next idea which is actually occurred to me on honeymoon like it's my most fully relaxed state really enjoying myself and and just being this like the algorithm for alpha zero just appeared I come and in in its full form and this was actually before we played against Lisa doll but we we just didn't I think we were so busy trying to make sure we could beat the the world champion that it was only later that we had the the opportunity to step back and start examining that that sort of deeper scientific question of whether this could really work so nevertheless so soft play is probably one of the most profound ideas that represents to me at least artificial intelligence but the fact that you could use that kind of mechanism to again be more glass players that's very surprising so we kind of to be it feels like you have to train in a large number of expert gamer so was it surprising to you what was the intuition can you sort of think not necessarily at that time even now what's your intuition why this thing works so well why I was able to learn from scratch well let me first say why we tried it so we tried it both because I feel that it was the deeper scientific question to to be asking to make progress towards AI and also because in general in my research I don't like to do research on questions for which we already know the likely outcome I don't see much value in running an experiment where you're 95% confident that that you will succeed and so we could have tried you know maybe to to take alphago and do something which we we knew for sure it would succeed on but much more interesting to me was to try try it on the things which we weren't sure about and one of the big questions on our minds back then was you know could you really do this with self play alone how far could that go would it be as strong and honestly we weren't sure yeah it was 50/50 I think you know we I really if you'd asked me I wasn't confident that it could reach the same level as these systems but it felt like the right question to ask and even if even if it had not achieved the same level I felt that that was an important direction to be studying and so then lo and behold it actually ended up outperforming the previous version of of alphago and indeed was able to beat it by 100 games to zero so what's the intuition as to as to why I think that the intuition to me is clear that whenever you have errors in a in a system as we did in alphago alphago suffered from these delusions occasionally it would misunderstand what was going on in a position and miss evaluate it how can how can you remove all of these these errors errors arise from many sources for us they were arising both from you know it started from the human data but also from there from the nature of the search and the nature of the algorithm itself but the only way to address them in any complex system is to give the system the ability to correct its own errors it must be able to correct them it must be able to learn for itself when it's doing something wrong and correct for it and so it seemed to me that the way to correct delusions was indeed to have more iterations of reinforcement learning that you know no matter where you start you should be able to correct those errors until it gets to play that out and understand oh well I thought that I was going to win in this situation but then I ended up losing that suggests that I was miss evaluating something there's a hole in my knowledge and now now the system can correct for itself and and understand how to do better now if you take that same idea and trace it back all the way to the beginning it should be able to take you from no knowledge from completely random starting point all the way to the highest levels of knowledge that you can achieve in in a domain and the principle is the same that if you give if you bestow a system with the ability to correct its own errors then it can take you from random to something slightly better than random because it sees the stupid things that the random is doing and it can correct them and then it can take you from that slightly better system and understand what what's that doing wrong and it takes you on to the next level and the next level and and this progress it can go on indefinitely and indeed you know what would have happened if we'd carried on training alphago zero for longer we saw no sign of it slowing down it's in improvements or at least it was certainly carrying on to improve and presumably if you had the computational resources this this could lead to better and better systems that discover more and more so your intuition is fundamentally there's not a ceiling to this process the one of the surprising things just like you said is the process of patching errors it's intuitively makes sense they this is a reinforcement learning should be part of that process but what is surprising is in the process of patching your own lack of knowledge you don't open up other patches you go you keep sort of cool like there's a monotonic decrease of your weaknesses well let me let me back this up you know I think science always should make falsifiable hypotheses yes so let me let me back out this claim with a falsifiable hypothesis which is that if someone was to in the future take alpha zero as an algorithm and run it on with greater computational resources that we had available today then I predict that they would be able to beat the previous system 100 games to zero and that if they were then to do the same thing a couple of years later that that would be that previous system hundred games to zero and that that process would continue indefinitely throughout at least my human lifetime presumably the game of girl would set the ceiling I mean the game of go would set the ceiling but the game of go has ten to the hundred and seventy states in it so so the ceiling is unreachable by any computational device that can be built out of the you know 10 to the 80 atoms in the universe you asked a really good question which is you know do you not open up other errors when you when you correct your previous ones and the answer is is yes you do and so so it's a remarkable fact about about this class of two-player game and also true of single agent games that essentially progress will always lead you to if you have sufficient representational resource like imagine you had could represent every state in a big table of the game then we we know for sure that a progress of self-improvement will lead all the way in the single agent case to the optimal possible behavior and in the two-player case to the minimax optimal behavior and that is that the best way that I can play knowing that you're playing perfectly against me and so so for those cases we know that even if you do open up some new error that in some sense you've made progress you've you're progressing towards the the best that can be done so alphago was initially trained expert games with some self play alphago zero removed the need to be trained on expert games and then another incredible step for me because I just love chess is to generalize that further to be in alpha zero to be able to play the game of go beating alphago zero and alphago and then also being able to play the check the game of chess and others so what was that step like what's the interesting aspects there that required to make that happen I think the remarkable observation which we saw with alpha zero was that actually without modifying the algorithm at all it was able to play and crack some of a i's greatest previous challenges in particular we dropped it into the game of chess and unlike the previous systems like deep blue which had been worked on for you know years and years and we were able to beat the world's strongest computer chess program convincingly using a system that was fully discovered by its own from from scratch with its own principles and in fact one of the nice things that that we found was that in fact we also achieved the same result in in Japanese chess a variant of chess where where you get to capture pieces and then place them back down on your on your own side as an extra piece so much more complicated variant of chess and we also beat the world's strongest programs and reach superhuman performance in that game too and it was the very first time that we'd ever run the system on that particular game was the version that we published in the paper on on alpha zero it just works out of the box literally no no no touching it we didn't have to do anything and and there it was superhuman performance no tweaking no no twiddling and so I think there's something beautiful about that principle that you can take and algorithm and without twiddling anything it just it just works now to go beyond alpha zero what's required alpha zero is is just a step and there's a long way to go beyond that to really crack the deep problems of AI but one of the important steps is to acknowledge that the world is a really messy place you know it's this rich complex beautiful but messy environment that we live in and no one gives us the rules like no one knows the rules of the world at least maybe we understand that it operates according to Newtonian or quantum mechanics at the micro level all according to relativity at the macro level but that's not a model that's used to useful for us as people to to operate in it somehow the agent needs to understand the world for itself in a way where no one tells it the rules of the game and yet it can still figure out what to do in that world deal with this stream of observations coming in rich sensory input coming in actions going out in a way that allows it to reason in the way that alphago or alpha zero can reason in the way that these go and chess-playing programs can reason but in a way that allows it to take actions in that messy world to to achieve its goals and so this led us to the most recent step in the story of alphago which was a system called mu 0 and mu zero is a system which learns for itself even when the rules are not given to it it actually can be dropped into a system with messy perceptual inputs we actually tried it in the in some Atari games the canonical domains of Atari that have been used for reinforcement learning and and this system learned to build a model of these Atari games they were sufficiently rich and useful enough for it to be able to plan successfully and in fact that system not only went on to to beat the state of the art in Atari but the same system without modification was able to reach the same level of superhuman performance in go chess and shogi that we'd seen in alpha zero showing that even without the rules the system can learn for itself just by trial and error just by playing this game of go and no one tells you what the rules are but you just get to the end and and someone says you know win or loss you play this game and someone says win or lost so you play a game of breakout in Atari and someone just tells you you know your score at the end and the system for itself figures out essentially the rules of the system the dynamics of the world how the world works and that not in any explicit way but just implicitly enough understanding for it to be able to plan in that in that system in order to achieve its goals and that's the you know that's the fundamental process there to go through when you're facing any uncertain kind of environment they would in the real world it's figuring out the sort of the rules the basic rules of the game that's right so there's a lot I mean the ad that that allows it to be applicable to basically any domain that could be digitized in the way that it needs to in order to be consumable sort of in order for the reinforcement learning framework to be able to sense the environment to be able to act anywhere and so on the full reinforcement learning problem needs to deal with with worlds that are unknown and and complex and and the agent needs to learn for itself how to deal with that so museu I was as a step I felt a step in that direction one of the things that inspired the general public interesting conversations I have like with my parents or something my mom that just loves what was done is kind of at least the notion that there was some display of creativity some new strategies new behaviors that were created that that again has echoes of intelligence so is there something that stands up do you see it the same way that there's creativity and there's some behaviors patterns you saw that alpha zero was able to display their truly creative so let me start by I think saying that I think we should ask what creativity really means so to me creativity means discovering something which wasn't known before something unexpected something out outside of our norms and so in that sense the process of reinforcement learning or the self play approach that was used by alpha zero is it's the essence of creativity it's really saying at every stage you're playing according to your current norms and you try something and if it works out you say hey here's something great I'm gonna start using that and then that process it's like a micro discovery that happens millions and millions of times over the course of the algorithms life where it just discovers some new idea oh this pattern this patterns working really well for me I'm gonna I'm gonna start using that oh now oh here's this other thing I can do I can start to to connect these stones together in this way or I can start to you know sacrifice stones or give up on on on pieces or play shoulder hits on the fifth line or whatever it is the system is discovering things like this for itself continually repeatedly all the time and so it should come as no surprise to us then when if you leave these systems going that they discover things that are not known to humans to the human norms are considered creative and we've seen this several times in fact in alphago zero we saw this beautiful timeline of discovery where what we saw was that there are these opening patterns that humans play called joseki these are like the patterns that humans learn to play in the corners and they've been developed and refined over over literally thousands of years in the game of go and what we saw was in the course of the training alphago 0 over the course of the 40 days that we trained this system it's just to discover exactly these patterns that human players play and over time we found that all of the joseki that humans played were were discovered by the system through this process of self play and a sort of essential notion of creativity well what was really interesting was that over time it then started to discard some of these maybe own joseki that humans didn't know about yeah and it starts to say oh well you thought that the Knights move pincer joseki was a great idea but here's something you different you can do there which make some new variation that the humans didn't know about and actually now the human go player study the joseki their alphago played and they become the new norms that are used in today um top-level guy competitions that never gets old even just the first to me maybe just makes me feel good as a human being that a self play mechanism knows nothing about us humans discovers patterns that we humans do it's just I get an affirmation that we're doing we're doing okay as humans yeah in this domain in other domains we do we figure it out it's like the Churchill quote about democracy it's the you know it's the but it sucks but it's the best song we've tried so in general taking a step outside of go and I take a million accomplishment to have no time to talk about that with alpha star and so on and and and the current work but in general this self play mechanism that you've inspired the world with by beating the world champion goal player do you see that as DC being applied in other domains do you have sort of dreams and hopes that is applied in both the simulated environments in a constrained environments of games constrained I mean alpha star really demonstrates that you can remove a lot of the constraints but nevertheless it's in a digital simulated environment do you have a hope a dream that it starts being applied in the robotics environment and maybe even in domains that are a little safety critical and so on and have you know have a real impact in the real world like autonomous vehicles for example it seems like a very far-out dream at this point so I absolutely do hope and and imagine that we will we will get to the point where ideas just like these are used in all kinds of different domains in fact one of the most satisfying things as a researcher as when you start to see other people use your your algorithms in unexpected ways so in the last couple of years there have been you know a couple of nature papers where different teams unbeknownst to to us took alpha zero and applied exactly those same algorithms and ideas to real-world problems of huge meaning to to society so one of them was the problem of chemical synthesis and they were able to beat the state-of-the-art in finding pathways of how to actually synthesize chemicals retro retro chemical synthesis and the second paper actually actually just came out a couple of weeks ago in nature showed that in quantum computation you know one of the big questions is how to how to understand the nature of the the function in quantum computation and a system based on alpha zero beat the state of the art by quite some distance there again so so these are just examples and I think you know the lesson which we've seen elsewhere in machine learning time and time again is that if you make something general it will be used in all kinds of ways you know you provide a really powerful tools to society and and those tools can be used in in amazing ways and so I think we're just at the beginning and and for sure I hope that we we see all kinds of outcomes so the the in the the other side of the question of a reinforcement learning framework is you know you usually want to specify a reward function and an objective function what do you think about sort of ideas of intrinsic rewards if we're not really sure about you know of if we take you know human beings existence proof that we don't seem to be operating according to a single reward do you think that there's interesting ideas for when you don't know how to truly specify the reward you know that there's some flexibility for discovering it intrinsically or so on in the context of reinforcement learning so I think you know when we think about intelligence it's really important to be clear about the problem of intelligence and I think it's clearest to understand that problem in terms of some ultimate goal that we want the system to to try and solve for and after all if we don't understand the ultimate purpose of the system do we really even have a clearly defined defined problem that we are solving at all now within that as with your example for humans the system may choose to create its own motivations and sub goals that helped the system to achieve its ultimate goal and that may indeed be a hugely important mechanism to achieve those altima goals but there is still some ultimate goal I think the system needs to be measurable and and evaluated against and even for humans I mean humans were incredibly flexible we feel that we we can you know any goal that we're given we feel we can we can master to some degree but if we think of those goals really you know like the goal of being able to pick up an object or the goal of being able to communicate although influence people to do things in a particular way or whatever those goals are really they are that they're sub goals really that we set ourselves you know we choose to pick up the object we choose to communicate we choose to to influence someone else and we choose those because we think it will lead us to something in our in later art and we think that that's helpful to us to achieve some ultimate goal now I don't want to speculate whether or not humans as a system necessarily have a singular overall goal of survival or whatever it is but I think the principle for understanding and implementing intelligences has to be that if we're trying to understand intelligence or implement our own there has to be a well-defined problem otherwise if it's not I think it's it's like an admission of defeat that forget to be hope for understanding or implementing intelligence we have to know what we're doing we have to know what we're asking the system to do otherwise if you if you don't have a clearly defined purpose you're not going to get a clearly defined answer the the ridiculous big question that has to naturally follow because they have to pin you down on this on this thing that nevertheless one of the big silly or big real questions before humans is the meaning of life is us trying to figure out our own reward function yeah and you just kind of mentioned that if you want to build the intelligence systems and you know what you're doing you should be at least cognizant to some degree of what the reward function is so the natural question is what do you think is the reward function of human life the meaning of life for us humans the meaning of our existence I think you know I'd be speculating beyond my own expertise but but just for fun let me do that yes please and say I think that there are many levels at which you can understand a system and and you can understand something as as optimizing for a goal at many levels and so so you can understand the the you know let's start with the universe like um does the universe have a purpose well it feels like it's just one level just following certain mechanical laws of physics and that that's led to the development of the universe but at another level you can view it as actually there's the second law of thermodynamics that says that this is increasing in entropy over time forever and now there's a view that's been developed by certain people at MIT that this you can think of this as as almost like a goal of the universe that the purpose of the universe is to maximize entropy so there's multiple levels at which you can understand a system the next level down you might say well if the goal is to is to maximize entropy well how do how does how can that be done by a particular system and maybe evolution is something that the universe discovered in order in order to kind of dissipate energy as efficiently as possible and by the way I'm borrowing from Max tegmark for some of these metaphors yes the physicist but if you can think of evolution as a mechanism for dispersing energy then then evolution you you might say as then becomes a goal which is if if evolution disperses energy by reproducing as efficiently as possible what's evolution then well it's now got its own goal within that which is to actually reproduce as effectively as possible and now how does reproduction how is that made as effective as possible well you need entities within that that can survive and reproduce as effectively as possible and so it's natural in order to achieve that high level goal those individual organisms discover brains intelligences which enable them to support the goals of evolution and those brains what do they do well perhaps the early brains maybe they were controlling things at some direct level you know maybe they were the equivalent of pre-programmed systems which were directly controlling what was going on and setting certain you know things in order to achieve these particular particular goals but that led to a another level of discovery which was learning systems you know parts of the brain which were able to learn from themselves and learn how to to program themselves to achieve any goal and presumably there are parts of the game of the brain where goals are set to to parts of that that system and provides this very flexible notion of intelligence that we as humans presumably have which is the ability to kind of wipe the reason we feel that we can we can we can achieve any goal so so it's a very long-winded answer to say that you know I think there are many perspectives and many levels at which intelligence can be understood and and each of those levels you can take multiple perspectives that you know you can view the system as something which is optimizing for a goal which is understanding it at a level by which we can maybe implement it and understand it as AI researchers or computer scientists or you can understand it at the level of the mechanistic thing which is going on that there are these you know atoms bouncing around in the brain and they lead to the the outcome of that system is not in contradiction with the fact that it's it's also a a decision-making system that's optimizing for some goal and and purpose I've never heard the description of the meaning of life structured so beautifully in layers but you did miss one layer which is the next step which you're responsible for which is creating the the artificial intelligence and data layer on top of that and I can't wait to see well I may not be around but they can't wait to see what the next layer beyond that well we well let's just take that that argument you know and pursue it to a central conclusion so the next level indeed is for for how can our how can our learning brain achieve its goals most effectively well maybe it does so by by us as learning beings building a system which is able to solve for those goals more effectively than we can and so when we build a system to play the game of go you know when I said that I wanted to build a system that can play go better than I can I've enabled myself to achieve that goal of playing go better than I could buy buy directly playing it and learning it myself and so now a new layer has been created which is systems which are able to achieve goals for themselves and ultimately there may be layers beyond that where they set sub goals to parts of their own system in order to to achieve those and so forth so incredible so the story of intelligence I think I think is is a multi-layered one and a multi perspective one we live in an incredible universe David thank you so much first of all for dreaming of using learning to solve go and building intelligent systems and for actually making it happen and for inspiring millions of people in the process it's truly an honor thank you so much for talking today okay thank you thanks for listening to this conversation with David silver and thank you to our sponsors masterclass and cash app please consider supporting the podcast by signing up to master class at masterclass complex and downloading cash app and using code lex podcast if you enjoy this podcast subscribe on youtube review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter at lex friedman and now let me leave you with some words from david silver my personal belief is that we've seen something of a turning point where we're starting to understand that many abilities like intuition and creativity that we've previously thought or in the domain only of the human mind are actually accessible to machine intelligence as well and I think that's a really exciting moment in history thank you for listening and hope to see you next time you |
Roger Penrose: Physics of Consciousness and the Infinite Universe | Lex Fridman Podcast #85 | the following is a conversation with Roger Penrose physicist mathematician and philosopher at University of Oxford he has made fundamental contributions in many disciplines from the mathematical physics of general relativity and cosmology to the limitations of computational view of consciousness in his book the emperor's new mind roger writes that quote children are not afraid to pose basic questions that may embarrass us as adults to ask in many ways my goal with this podcast is to embrace the inner child that is not constrained by how one should behave speak and think in the adult world Roger is one of the most important minds of our time so it was truly a pleasure and an honor to talk with him was recorded before the outbreak of the pandemic for everyone feeling the medical psychological and financial burden of the crisis I'm sending love your way stay strong or in this together we'll beat this thing this is the artificial intelligence podcast if you enjoy it subscribe on YouTube review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter at lex friedman spelled fri DM a.m. as usual i'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation i hope that works for you and doesn't hurt the listening experience quick summary of the ads to sponsors expressvpn and cash app please consider supporting the podcast by getting expressvpn at expressvpn dot-com / Lex pod and downloading cash app and using code lex podcast this show is presented by cash app the number one finance app in the App Store when you get it use code lex podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction 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has a large number of obvious benefits certainly it allows you to access international versions of streaming websites like the Japanese Netflix or the UK who expressvpn works on any device you can imagine I use it on Linux shout out to a bond to Windows Android but it's available everywhere else to once again get it at expressvpn comm slash Lex odd to get a discount and to support this podcast and now here's my conversation with Roger Penrose you mentioned in conversation with Eric Weinstein on the portal podcast that 2001 Space Odyssey is your favorite movie which aspect if he could mention of its representation of artificial intelligence science engineering connected with you there also seems there which is so amazing and how they science was so well done I mean people say oh no you interstellar is the this amazing movie which is the most scientific movie but I thought it's not a patch on 2001 I mean 2001 they really went into all sorts of details regarding you know getting me freefall well done and everything I thought it was extremely well done so just the details or memorizing and also things like scene where at the beginning they have these and said sort of human ancestors which is sort of right sort of Eames eggs becoming monolith yes and well it's the one where he throws the bone up into the air and then it becomes this I mean there's just an amazing sequence there what do you make of the monolith does it have any scientific or philosophical meaning to you this kind of thing marks innovation not really that comes from arthur c clarke I was a great fan of Ossie Clark so it's just a nice plot device yeah well that plot is excellent yes yeah so how nine thousand decides to get rid of the astronauts because he it she believes that they will interfere with the mission that's right no it's this view I don't know whether I disagree that question in a certain sense he was telling you it's wrong see the the machine seemed to think it was superior to the human and so it was entitled to get rid of the human beings and run the show itself what do you think how did the right thing do you think how's flawed evil or if we think about systems like how would we want how to do the same thing in the future what was the flaw there well you're basically question touching on questions you see it's just one supposed to believe that how I was actually conscious I mean it was played rather that way that's know how and was a conscious being because Hal showed some pain some cognizant the hell appeared to be cognizant of its of what it means to die yes and therefore had an inkling of cautious yeah I mean I'm not sure that aspect of it was made completely clear whether Hal was really are just a very sophisticated computer which really didn't actually have these feelings and somehow but you're right it didn't like the idea being turned off how does it change things if how was it wasn't conscious well it might say that it would be wrong to turn it off if it was actually conscious I mean these questions arise if you think I mean AI one of the ideas it's sort of a mixture in a sense you say if it's trying to do everything a human can do and if you take the view that consciousness is something which would come along when the computer is sufficiently complicated sufficiently whatever criteria you used to characterize its consciousness in terms of some can come national criterion so how does consciousness change our evaluation of the decision the hell made it's not to say that people have been confused about this because if they say these machines will become conscious but just simply because it's the degree of computation and when you get beyond that certain degree of computation it will become conscious then of course you have all these problems I mean you might say well one of the reasons you're doing AI is because you understand the device at some distant planet and you don't want to send a human out there because then you'd have to bring it back again and that's cost you far more than just sending it there and leaving it there but if this device is actually a conscious entity then you have to face up to the fact that that's immoral and so the mere fact that you're making some AI device and getting that thinking that removes your responsibility to it would be incorrect and so this is a kind of plot floor and that kind of viewpoint I'm not sure how you know people who take it very seriously I'm gonna have this curious conversation with with I'm going to forget names and I'm afraid because this is what happens to me in the wrong moment I've said I'd Douglas have said this after and he's written this book god I wish I liked I thought it was a fantastic book but I didn't agree with his conclusion from girdle's theorem I think he got it wrong is he well just tell you my story you see because I'd never met him and then I knew I was going to meet him at the occasion IRS she's coming anyone to talk to me and I said that's fine and I thought in my mind well I'm going to paint him into a corner you see use his arguments to convince him that certain numbers are conscious you know some integers large enough integers are actually conscious and this was going to be my reductio ad absurdum so i started having this argument and he simply leptin to the corner he didn't even need to be painted into it he took the view that certain numbers were conscious I thought that was a reductio ad absurdum but he seemed to think it was perfectly reasonable point of view with out the absurdum there yes interesting but the thing you mentioned about how is the intuition that a lot of the people at least in the artificial intelligence world had and have I think they don't make it explicit but that if you increase the power of computation naturally consciousness will emerge yes I think that's what they think but basically that's because they can't think of anything else well that's right and so it's a reasonable thing I mean you think what the brain do what does do a lot of computation I think most of what you actually call computation is done by the cerebellum I mean this is one of the things that people don't much mention and when I come to this subject from the outside and certain things strike me which you hardly ever hear mentioned em you hear mentioned about the left-right business they move your right arm that's you're on the left side of the brain and and so on and all that sort of stuff and it's more than that if you you have this plots of different parts of the brain they're they're two of these these things called the homunculus which you see these pictures of a distorted human figure and showing different parts of the brain controlling different parts of the body and it's not simply things like okay the right hand is controlled and since both sensory and motor on the left side left hand on the right side it's more than that vision is at the back basically your feet at the top I mean so it's about the worst organization you can imagine right yeah so it can't just be a mistake in nature there's something going on there and this is made more pronounced when you think of the cerebellum the cerebellum has when I was first thinking about these things I was told it had half as many neurons or something they're bad comparable and now they tell me it's got far more neurons in the cerebrum then cerebrum is this sort of convoluted thing at the top people always talk about cerebellum is this thing just looks a bit like a ball of wool to the back underneath it's got more neurons it's got more connections computationally it's got much more going on than this friend the cerebrum but as far as we know although it's slightly controversial the cerebellum is entirely unconscious so the actions you have a pianist who complains incredible piece of music and you think of any moves this little finger until this was key to get a hit at just the right moment does he or she consciously will that movement no ok the consciousness is coming in it's probably to do with the feeling of the piece of music that's being performed and that sort of thing which is going on but the details in what's going on are controlled I would think almost entirely by the cerebellum that's where you have this precision and they're they're really detailed once you get I mean you think of a tennis player or something does that tennis player think exactly harder which muscles should be moved in what direction and so of course not but he or she will maybe think well if the ball is angled in such a way in that corner there will be tricky for the opponent and the details of that are all done largely with the cerebellum that's where all the precise motions but it's unconscious so why is it interesting to you that so much computation is done in the cerebellum and yet is unconscious because it doesn't it's it's the view that somehow it's computation which is producing the consciousness and it's here you have an incredible amount of computation going on and as far as we know it's completely unconscious so why what's the difference and I think it's an important thing what's the difference why is the cerebrum but all this very peculiar stuff that very hard to see on a computational perspectives like having me everything have to cross over under the other size and do something which looks completely inefficient and you've got funny things like the frontal-lobe when the prett are where did we call the Louvre and the place where they come together you have the different parts the control if you wanted to do with motor and the other to do with sensory and they're sort of opposite each other rather than being connected by a nuclear pie it's not just though you've got electrical circuits there's something else going on there so it's it's just the idea that it's like a complicated computer it just seems to me to be completely missing the point there must be a lot of computation going on but the cerebellum seems to be much better at doing that then the cerebrum is so for sure I think what explains it it's as like half hope and half we don't know what's going on and therefore from the computer science perspective you hope that a Turing machine can be perfectly can achieve general intelligence well you have this wonderful thing about during and girdle and church and carry and various people particularly Turing and I guess post was the other one these people who develop the idea of what a computation is and there were different ideas of what a computer developed differently I mean church's way of doing it was very different from Turing's but then they were shown to be equivalent and so the view emerged that what we mean by a computation is a very clear concept and one of the wonderful things that during did was to show that you could have what we call the universal Turing machine it you just have to have a certain finite device okay it has to have an unlimited storage space which is accessible to it but the actual computation if you like is performed by this one universal device and so the view comes away well you have this universal Turing machine and maybe the the brain is something like that a universal Turing machine and it's got maybe not an unlimited storage with a huge storage accessible through it and this model is one which is what's used in ordinary computation it's a very powerful model and the universalness of computation it's very useful you can have some problem and you may not see immediately how to put it onto a computer but if it is something of that nature then there were all sorts of sub programs and subroutines when all the I mean I learned a little bit of computing when I was when I was a student but not very much it was enough to get the general ideas and there's something really Pleasant about a formal system like that yeah well you can start discussing about what's provable what's not these kinds of things and you've got it you know a notion which is an absolute notion this notion of computability and you really address when things what mathematical problems are computed ly solvable and what chance so and it's a very beautiful area of mathematics and it's a very powerful area of mathematics and it underlies the whole sort of once I have their principles of computing machines that we have today could you say what is Gaydos and completeness theorem and how does it maybe also say is it heartbreaking to you and how does it interfere with this notion of computation preciousness sure where the ideas basically ideas which I formulated in my first year as a graduate student in Cambridge I did my undergraduate work in mathematics in London and I had a colleague Ian Percival we used to discuss things like computational logical systems quite a lot I'd heard about girdles theorem a bit worried by the idea that it seemed to say there were things in mathematics that you could never prove and so when I went to Cambridge as a graduate student I went to various courses you see I was doing pure mathematics I was doing algebraic geometry of a sort a little bit different from my supervisor in people but it was an area and I was interested I got particularly interested in three lecture courses that were nothing to do with what I was supposed to be doing when was the course by Hermann Bondi on Einstein's general theory of relativity which was a beautiful course he was a an amazing lecturer brought these things alive absolutely and now that was a course on quantum mechanics given my great physicist Paul Dirac very beautiful course in a completely different way it was he was very kind of organized and never got excited about anything seemingly but it was extremely well-put-together and I found that amazing too third course there was nothing to do with what I should be doing was a course on mathematical logic I got I say my discussions were being Percival was incompleteness theorem already deeply within mathematical logic space was were you introduced I was introduced to it in detail by the course but Burstein and he it was two things he described which were very fundamental to my understanding one was Turing machines and the whole idea of computability and all that so that was all very much part of the course the other one was the girl of theorem and it wasn't what I was afraid it was to tell you there were things in mathematics you couldn't prove it was basically and he phrased it in a way which often people didn't and if you read Douglas Hofstadter's book he doesn't you see but Steen made it very clear and also not in a sort of public lecture that he gave to a mathematical I think it may be the atom Society one of the mathematical undergraduate societies and he made this point again very clearly that if you've got a formal system of proof so suppose what you mean by proof is something which you could check with a computer so to say whether you've got it right or not you've got a lot of steps have you carried this computational procedure well following the proof steps of the proof correctly that can be checked by an algorithm by a computer so that's the key thing now what have to now you see is this any good if you've got an algorithmic system which claims to say yes this is right this you've proved it correctly this is true if you've proved it if you made a mistake it doesn't say it's true or false but if you have if you've done it right then the conclusion you've come to is correct now you say why do you believe it's correct because you've looked at the rules and you said well okay that one's all right yeah and that one's all right what about that harm not yeah I see I see why it's all right okay you go through all the rules you say yes following those rules if it says yes it's true it is true they've got to make sure that these rules are ones that you trust is if you follow the rules and it says it's a proof is the result actually true right and that your belief that's true depends upon looking at the rules and understanding them now what girl shows that if you have such a system then you can construct a statement of the very kind that it's supposed to look at a mathematical statement and you can see by the way it's constructed and what it means that it's true but not provable by the rules that you've been given and it depends on your trust in the rules do you believe that the rules only give you truth if you believe the rules on you give you truth then you believe this other statement is also true I found this absolutely mind-blowing when I saw this it blew my mind oh my god you can see that this statement is true it's as good as any proof because it only depends on your belief in the reliability of the proof procedure that's all it is and understanding that the coding is done correctly and it enables you to transcend that system so whatever system you have as long as you can understand what it's doing and why you believe it only gives you truths then you can see beyond that system now how do you see beyond it what is it that enables you to transcend that system well it's your understanding of what the system is actually saying and what the statement and you've constructed is actually staying just this quality of understanding whatever it is which is not governed by rules it's not a computational procedure so this idea of understanding is not going to be within the rules of the sort of within the formal system yes yes rules anyway yeah because you have understood them to be rules which only give you truths they be no point in it otherwise I'm a people say well ok this is what this one said the rules as good as any other well it's not true you see you have to understand what the rules mean and why does that understanding of the mean give you something beyond the rules themselves and that's that's what it was that's what blew my mind it's somehow standing why the rules give you truths enables you to transcend the rules so that's where I mean even at that time that's already where the thought entered your mind that the idea of understanding or we can start calling it things like intelligence or even consciousness is outside the rules yes since I've always concentrated on understanding you know people say people somebody knows well we know but about creativity that's something a machine can't do is great well I don't know what is creativity and I don't know you know somebody can put some funny things on a piece of paper and say that's creative and you could make a machine do that is it really creative I don't know he said I worry about that one I sort of agree with it in a sense but it's so hard to do anything with that statement but understanding yes you can you can make go see that understanding whatever it is and it's very hard to put your finger on it that's absolutely true can you try to define or maybe dance around a definition of understanding to some degree but I don't often once it's about this but there is something there which is very slippery it's something like standing back and it's got to be something you see it's also got to be something which was of value to our remote ancestors because I sometimes there's a cartoon which I drew sometimes showing you how all these there's a in the foreground you see this mathematician just doing some mathematical theorem this little bit different job in that theorem but let's not go into that he's trying to prove some theorem and he's about to be eaten by a saber-toothed Tigers he's hiding in the in the undergrowth you see and in the distance you see his his cousins building growing crops building shelters domesticating animals and in this light foreground you see they built a mammoth trap and this poor old mammoth was falling into a pit you see and all these people around him are about to grab him you see and well you see those are the ones who the quality of understanding which goes with all the it's not just a mathematician doing some mathematics this understanding quality is something else which has been a tremendous advantage to us not just to us see I don't think consciousness is limited to humans that's the interesting question at which point if it is indeed connected to the evolutionary process yeah at which point is we pick up this very hard question it's certainly I don't think it's primates you know you see these pictures of African hunting dogs and how they they can plan amongst themselves how to catch the antelopes didn't some of these and David Attenborough films I think this probably was one of them and you can see they're hunting dogs and they divide themselves into two groups and they go in two routes two different routes one of them goes and they sort of hide next to the river and the other group goes around and they start yelping at these then embark I guess whatever noise hunting dogs do the antelopes and they sort of round them up and they chase them in the direction of the river and they're the other ones just waiting for them just to get because this when they get to the river it slows them down and so they pounce on them so they've obviously planned this all out somehow I have no idea how and there is some element of conscious planning as far as I can see I don't think it's just some kind of there's so much of AI these days they call bottom-up systems is it yeah where you have neural networks and they and they you give them a zillion different things to look at and and then they sort of you can choose one thing over another this because it's seen so many examples and picks up on the wrong signals which your mom may not even be conscious of and that doesn't feel like understanding there's no understanding and that whatsoever so well you're being a little bit human centric so well what exactly I'm not with the dogs Emma no you're not sorry I'm not human centric but I misspoke by a la biologie centric is it possible that consciousness would just look slightly different well I'm not saying it's biological because we don't know all right I think other examples of the elephants is a wonderful example to where they it's just I think this was about that's number one well they the elephants have to go from along with the troop of them have to go long distances and the leader of a troop is a female they are apparently and this female that she had to go all the way from one part of the country to another and at a certain point she made a detour and they went off in this big detour all the troop came with her and this is where her sister had died and there were her bones lying around and they go and pick up the bones and they hand it round and they caress the bones and then they put them back and they will go back again how am i doing that's so interesting I mean there's something going on there's no clear connection with natural selection there's just some deep feeling going on there we have to do with their conscious experience and I think it's something that your overall is advantageous a natural selection but not directly to do with natural selection I like that there's something going on and go on going on there yeah like I told young Russian so I tend to romanticize all things of this nature that that it's not merely cold hard computation perhaps I could just slightly answer your question you were asking me what is it there's something about sort of standing back and thinking about your own thought processes I mean there is something like that in the girdle thing because it's just you're not following the rules you're standing back and thinking about the rules and so there is something that you might say you think about you're doing something that you think what the hell am i doing and you sort of stand back and think about what it is that's making you think such a way just take a step back outside this the game you've been playing yeah you back up and you think about yeah you're just not playing the game anymore you're thinking about what the hell you're doing in playing this game and that's that's somehow it's it's not very precise descriptive but somehow feels very true that that's somehow understandings yeah this kind of reflection a reflection yes yeah there is some it's a bit hard to put your finger on but there is something there which I think maybe could be unearthed at some point and see this is really what's going on why conscious beings have this advantage what it is that gives them an advantage and I think it goes way back I don't think we're talking about the hunting dogs and the elephants that's pretty clear that octopuses have the same sort of quality and we call it consciousness yeah I think so seen enough examples of the way that they behave and the evolution route is completely different does it go way back to some common ancestor or did it come separately my hope is it something simple but the hard question if there's a hardware prerequisite you know we have to develop some kind of hardware mechanisms and our computers like basically as you suggest I'll get to in a second we kind of have to throw away the computer as we know today yeah the deterministic machines we know today is it tried to create it I mean why my hope of course is not but well I should go really back to the story which instance I'm finished because I went to these three courses you see when I was a graduate student and so I started to think I'm really I'm a pretty view what you might call a materialist in the sense of thinking that there's no kind of mystical or something around which comes in from who knows where you still that yeah you still throw your life into me I don't like the word materialist because this is just we know what material is and that's that is what is a bad word because there's no mystical it's not some mystical something which is not not treatable my science it's so beautifully put just a pause on that for a second your materialist but you acknowledge that we don't really know what the materialist that's right I mean I like to call myself a scientist that's the first but it means that yes we see the question goes on here so I began thinking okay if consciousness or understanding is something which is not a computational process what can it be and I knew enough from my undergraduate work I knew about Newtonian mechanics and I knew how basically you could put it on a computer there is a fundamental issue which is it important or not that computation depends upon discrete things so using discrete elements whereas the physical laws depend on the continuum now is this something to do with it is it the fact that we use the continuum in our physics and if we model our physical system we use discrete systems like ordinary computers I came to the view that that's probably not it I might have to retract on that someday but the view was no you can get close enough it's not altogether clear I have to say but you can get close enough and you know when to this course and I'm Bondy on general relativity and I thought well you can put that on a computer because that was a long time before people and I've sort of grown up with this how people have done better and better calculations and they could work out black about black holes and they can then work out how black holes can interact with each other spar around and what kind of gravitational waves can add and there's still a very impressive piece of computational work how you can actually work out the shapes of those signals and now we have LIGO seeing these signals and they say yeah there's this black hole spiraling through each other this is just a vindication of the power of computation in describing einstein's general as if it a so in that case we can get close we would computation we can get close to our understanding of the physics you can get very very close now is that close enough you see and then I went to this course by Dirac they see I think it was the very first lecture that he gave and he was talking about the superposition principle and he said if you have a particle you usually think of particle can be over here or over there but in quantum mechanics it can be over here and over there at the same time and you have these states which involve a superposition in some sense of it different locations for that particle and then he got out his piece of chalk some people say broke it into as a kind of illustration of how the piece of chalk might be over here and over there at the same time and he was talking about this and I my mind wandered I don't remember he what he said well I can remember he's just moved on to the next topic and something about energy he'd mentioned which I had no idea what had to do with anything and so I'd been struck with this and worried about it ever since it's probably just as well I didn't hear his explanation because it was probably one of these things to calm me down and not worry about it anymore it's in my case I've worried it about it ever since so I thought maybe that's the catch there is something in quantum mechanics where are these super positions become one or the other and that's not part of quantum mechanics there's something missing in the theory the theory is incomplete it's not just incomplete it's in a sentence that's not quite right because if you follow the equation the basic equation of quantum mechanics that's the Schrodinger equation you could put that on a computer too there are lots of difficulties about how many parameters you have to put in so on it can be very tricky but nevertheless it is a computational process modulo this question about the continuum that's before but it's not clear that makes any difference so our theories of quantum mechanics maybe missing the same element that the universal Turing machine is missing about consciousness yes yeah this is the viewer held is that you need a theory and that that what people call the reduction of the state or the collapse of the wavefunction which you have to have otherwise quantum mechanics doesn't relate to the world we see to make it relate to the world we see you've got to break the quantum you've got to break the Schrodinger equation Schroeder himself was absolutely by this idea he's owned his own equation I mean that's why he introduced this famous Schrodinger's cats as a thought experiment he's really saying look this is where my equation leads you into it there's something wrong something we haven't understood which is basically fundamental and so I was trying to put all these things together and said well it's got to be the non computability comes in there and I also can't quite remember right when I thought this but it's when gravity is involved in quantum mechanics it's the combination of those two and that's that point when we you have good good reasons to believe this this came much later but I have good reason to believe that the principles of general relativity and those of quantum mechanics most particularly it's the basic principle of equivalence which goes back to Galileo if you fall freely you eliminate the gravitational field so you're imagine Galileo drawing dropping his big rock and his little rock from the Leaning Tower whether he actually ever did that or not pretty irrelevant and as the rocks fall to the ground you'd have a little insect sitting on one of them looking at the other one and it seems to think oh there's no gravity here of course it hits ground and then realized something's difference going on but when it's in freefall the gravity has been eliminated Galileo understood that very beautifully he gives these wonderful examples of fireworks and you see the fireworks and explode and you see the sphere of sparkling fireworks this remains a sphere as it as though there were no gravity so he understood that principle but he couldn't make a theory out of it Einstein came along used exactly the same principle and that's the basis of Einstein's general theory Elizabeth II know there is a conflict this is something I did much much later so this wasn't those days that's much later you can see there is a basic conflict between the principle of superposition I think that Dirac was talking about and the principle of general Co very well principle of equivalence gravitational fields equivalent to an acceleration P pause for a second what is the principle of equivalence it's this Galileo principle that we can eliminate at least locally you have to be in a small neighborhood because you see if you have people dropping rocks all around the world somewhere you can't get rid of it all at once but in the local neighborhood you can eliminate the gravitational field by falling freely with it and we now see this with astronauts and they don't you know the earth is right there you can see the great globe of the earth right beneath them but they don't care about it they as far as they're concerned there's no gravity they fall freely within the gravitational field and that gets rid of the gravitational field and that's the principle of equivalence so what's the was the contradiction what's the tension with superposition uh well what so we just a backtrack for a second just to see if we can weave a thread through it all yes so you wish she started to think about consciousness as potentially needing some of the same not mystical but some of the same imagine see this is a complicated story so you know people think oh I'm drifting away from the point of something but I think it is a complicated story so what I'm trying to say I mean I try to put it in a nutshell it's not so easy I'm trying to say that whatever consciousness is it's not a computation yes it's not a physical process which can be described by computation but it nevertheless could be so one of the interesting models the you've proposed as the orchestrated objective reduction yeah that's going from there you say so I say I have no idea so I wrote this book through my scientific career I thought you know when I'm retired I have enough time to write a sort of a popular book which I will explain my ideas and puzzles but I like beautiful things about physics and mathematics and this puzzle about computability and consciousness and so on and in the process of writing this book well I thought I'd do it when I was retired I didn't actually I would didn't wait that long because there was a radio discussion between edward fredkin and marvin minsky and they were talking about what computers could do and they were entering and entering a big room they imagined entering this big room with the other end of the room two computers were talking to each other and as you walk up to the computers they will have communicated to each other more ideas concepts things than the entire human race had ever commute so I thought well know where you're coming from but I just don't believe you there's something missing that's it's not that so I thought well I should write my book and so I did it was roughly the same time Stephen Hawking this writing his brief history of time and Hades at some point the book you're talking about the emperor's new mind that's right and both are and incredible books the brief history of time and I'm person you mind yes it was quite interesting because he got he told me he'd got some Carl Sagan I think to write that forward good gosh what am I gonna do I'm not gonna get anywhere unless I get somebody so I know I know Martin Gardner so I wonder if he'd do it so he did and it is a very nice forward so that so that's an incredible book and some of the the same people you mentioned Ed Franken which I guess of expert systems Fame and Minsky of course people know in the eye world but they represent the artificial intelligence that do hope and dream that intelligences am i thinking well you know I see where they're coming from and they're like from exercise rectus oh yeah you're right but that's not my perspective so I thought I had to say it and as I was writing my book you see I thought well I don't really know anything about neurophysiology what am i doing writing this book so I certainly reading up about neurophysiology and I rate I'm nothing I'm trying to find out well how it is the nerve signals could possibly preserve quantum coherence and all I read is that the second electrical signals which go along the nerves create some effects through the brain there's no chance you can isolate it so this is hopeless so I come to the end of the book and I'm more or less give up and just think of something which I didn't believe in this maybe this is the way around it but no and then you say I thought well maybe this book well at least stimulate young people to do science or something and I got all these letters from old people instead he's the only people who could had time to read my book so I mean except for Stuart Hameroff except for Stuart Hameroff you don't have a rough road to me and he said I think you're missing something you don't know about microtubules do you didn't put it quite like that but that was more or less it and he said this is what you really need to consider so I thought oh my god yes that's a much more promising structure so I mean fundamentally you were searching for the source of a non computable source of consciousness within the human brain yeah in the biology and so what are mark if I may ask what are microtubules well you see I I was ignorant in what address I never came across them and in in in the books I looked at that's I only read rather superficially which is true but I didn't know about microtubules Stuart I think one of the things here was impressed him about them is when you see pictures of mitosis that's a cell dividing and you see all the chromosomes and the chromosomes get their gate or gate line and then they get pulled apart and so that as the cell divides the half the chromosomes go you know how their web is divided into the two pass and they go to different ways and what is it that's pulling them apart well those are these little things called microtubules and so he starts to get interested in them and he formed the view well he was his day job or night job of where every call it is to put people to sleep except he doesn't like calling asleep because it's different general anesthetics in a reversible way so you want to make sure that they don't experience the pain that would otherwise be something that they feel and consciousness is turned off for a while and it can be turned back on again so it's crucial that you can turn it off and turn it on and what do you do when you're doing that what do general anesthetic gases do and see he formed the view that it's the microtubules that they affect and the details of why he formed that view is not wasn't clear to me but there but there's an interesting story he keeps talking about but I've found this very exciting because I thought these structures these little tubes which inhabit pretty well ourselves it's not just neurons apart from red blood cell red blood cells they inhabit pretty well all the other cells in the body but they're not all the same kind you get different kinds of microtubules and the ones that excited me the most and this is may still not be totally clear but they're ones that excited me most were the ones that the only ones that I knew but at the time because they were there very very symmetrical structures and I had reason to believe that these very symmetrical structures would be much better at preserving a quantum state quantum coherence preserving the thing without you just need to cut preserve certain degrees of freedom without them leaking into the environment once they leak into the environment your loss so you ought to preserve these quantum states at a level which the state reduction process comes in and that's where I think the non computability comes in and it's the measure process in quantum mechanics what's going on so something about the the measurement process what's going on something about the structure on the microtubules yes your intuition says maybe there's something here maybe this kind of structure allows for the the mystery the there was a moment of chance yes it just struck me that partly it was the symmetry because there is a feature of symmetry you can predict preserve quantum coherence much better with symmetrical structures there's a good reason for that and that impressed me a lot I didn't know the difference between the a lattice and B lattice at that time which could be important now that could in medicine this year which isn't talked about much but that's some in some sense details we could take a step back just to say these people are not familiar so this this this was called the orchestrated objective reduction idea or orko R which is a biological philosophy of mind the postulates that consciousness originates at the quantum level inside neuron so that has to do with your search for where where is it coming from so that's counter to the notion that consciousness may arise from the computation performed by the synapses yes the key point here sometimes people say it's because it's quantum mechanical it's not just that see it's it's it more outrageous than that you see this is one reason I think we're so far off from it because we don't even know the physics right you see it's not just quantum mechanics people say oh you know quantum systems and biological structures no well he's starting to see that some basic biological systems does depend on quantum I mean look you the first place all of chemistry is quantum mechanics people got used to that so they don't count that so you said let's not count come on chemistry we sort of got the hang of that I think but you have quantum effects which are not just chemical in photosynthesis and this is one of the striking things in the last several years that photosynthesis seems to be a basically quantum process which is not simply create chemical it's using quantum mechanics in a very basic way so you can start saying oh well with photosynthesis is based on quantum mechanics why not behave you have neurons and things like that maybe there's something which is a bit like photosynthesis in that respect but what I'm saying is even more outrageous than that because those things are talking about conventional quantum mechanics now my argument says that conventional quantum mechanics if you're just following the Schrodinger equation that's still competing well so you've got to go beyond that so you've got to go to where quantum mechanics goes wrong in a certain sense you have to a little bit careful about that because the way people do quantum mechanics is a sort of mixture of two different processes one of them is the Schrodinger equation which is a an equation my Schrodinger wrote down and it tells you how the system the state of a system evolves it evolves according to this equation completely deterministic but it involves in two ridiculous situations and this was much frightening it was very much pointing out with his cat he said you follow my equation that's Schrodinger's equation and you could say that you have two cat a cat which is dead and alive at the same time that would be the evolution of the Schrodinger equation would lead to a state which is the cat being dead and alive at the same time and he's more or less saying this is an absurdity people nod I say oh well Schrodinger said you couldn't have a cat with deadly it's not that you see he was saying this is an absurdity there's something missing and that the reduction of the state or the collapse of the wavefunction or whatever it is is something which is has to be understood it's not following the Schrodinger equation it's not the way we conventionally do quantum mechanics there's something more than that and it's easy to quote Authority here because Einstein at least three of the greatest physicists of 20th century who were very fundamental in developing quantum mechanics Einstein one of them Schrodinger another Dirac another you have to look carefully it directs writing because he didn't tend to say this out loud too much because he was very cautious about what he said you find the right place and you cease he says quantum mechanics is a provisional theory we need something which explains the collapse of a wavefunction we need to go beyond the theory we have now I happen to be one of the kinds of people there are many there is a whole group of people they're all considered to be a bit you know bit Mavericks who believe that quantum mechanics needs to be modified there's a small minority of those people which were really a minority who think that the way in which it's modified has to be with gravity and there is an even smaller minority of those people who think it's a particular way that I think it is you see so so those are the quantum gravity folks for what's well you see quantum gravity is already not this because when you say quantum gravity what you really mean is quantum mechanics and Clyde - gravitational Theory so you say let's take this wonderful formalism of quantum mechanics and make gravity fit into it so that is what quantum gravity is meant to be now I'm saying you've got to be more even-handed that gravity affects the structure of quantum mechanics - it's not just you quantize gravity you've got to gravity as quantum mechanics and it's it's a two-way thing but then when you even get started so that you're saying and we have to figure out totally new ideas indirectly no yes it's you were stuck I don't have a theory that's the trouble so this is a big problem if you say okay well what so there I don't know so we may be in the very early days sort of it is in the very early days and there but just making this point yes you see Stuart Hameroff to be open Rose says that it's got to be a reduction of the state and so so let's use it the trouble is Penrose doesn't say that Penrose says well I think that no no we have no experiments as yet which shows that yes there are experiments which are being thought through and which I'm hoping will be performed there is an experiment which is being developed by dirt Romney Stowe who is I've known for a long time who shares his time between Leiden in the Netherlands and Santa Barbara in the US and he's been working on an experiment which could perhaps demonstrate that quantum mechanics as we now understand it if you don't bring in the gravitational effects it has to be modified and and then there's also experiments that are underway that kind of look at the microtubule side of things to see if there's in the biology you could see something like that could you briefly mention it because that's a really sort of one of the only experimental attempts in the very early days of even yeah about I think there's there's a very serious area here which is what Stuart Hameroff is doing and I think it's very important one of the few places that you can really get a bit of a handle on what consciousness is is what turns it off and when you're thinking about general anesthetics it's very specific these things turn consciousness off what the hell do they do well Stuart and a number of people who work with him and others happen to believe that the general anesthetics directly effect microtubules and there is some evidence for this I don't know how strong it is and how watertight the cases but I think there is some evidence pointing in that kind of direction it's not just an ordinary chemical process there's something quite different about it and one of the main candidates is that these anesthetic gases do affect directly microtubules and how strong that evidence is I wouldn't position to say but I think there is fairly impressive evidence and the point is the experiments are being undertaken with yes I mean that is experimental it's a very clear direction where you can think of experiments which could indicate whether or not it's really microtubules which the anaesthetic gas is directly affect that's really exciting one of the sad things is as far as I'm for my outside perspective it's not many people are working on this so there's a very like Oh Stewart even it feels like there's very few people are carrying the flag forward on this I think it's it's not many in the sense it's a minority but it's not zero anymore you see when I were originally serious you know we were just just us and a few few of our friends they weren't many people think it but it's grown into into it one of the main viewpoints yeah there might be about four or five or six different news that which people hold and it's one of them so it's it's considered as one of the possible lines of thinking yes you describe physics theories as falling into one of three categories the superb the useful or the tentative I like those words it's a beautiful categorization do you think we'll ever have a superb theory of intelligence and of consciousness we might we're a long way from it I don't think we're even whether in the tentative scale I mean it's uh you don't think we've even entered the realm of tentative probably no I think yeah that's raised you know what do you see the circle is so controversial we don't have a clear view which which is accepted by a majority I mean you say yeah people most views are computational in one form or another they think it's some but it's not very clear because even the the IIT people who I think think of them as computational but I've heard them saying they know consciousness is supposed to be not computation I say well if it's not coming in what the hell is it what's good what's going on but physical processes are going on which that what does it mean for something to be computational then so is uh well there has to be a process which is it's very curious the way the history has developed in quantum mechanics because very early on people thought there was something to do with consciousness but it was almost the other way around you see you have to say the Schrodinger equations says all these different alternatives happen all at once and then when is it that only one of them happens where one of the views which was quite commonly held by a few distinguished quantum physicists this well a conscious being looks at the system what becomes aware of it and at that point it becomes one of the other that's a row where consciousness is somehow actively reducing the state my view is almost the exact opposite of that it's the state reduces itself in some way which some non computational way which we don't understand we don't have a proper theory of and that is the building block of what consciousness is so consciousness is the other way around it depends on that choice which nature makes all the time when the state becomes one of the other rather than the superposition of one and the other and when that happens there is what we're saying now an element of proto consciousness takes place proto consciousness is roughly speaking the building block out of which actual consciousness is constructed so you have these proto conscious elements which are when the state decides to won't do one thing or the other and that's the thing which when organized together that's the oh our part in orko our but the ork part that's the the Oh our part at least once can see where when driving as a theory you can say it's the quantum choice of going this way or that way but the ork part which is the orchestration of this is much more mysterious and how does the brain somehow orchestrate all these individual our processes into a genuine genuine genuine just experience and it might be something that's beautifully simple aware and completely in the dark about yeah I think at the moment it's best the thing you know we happily put the word walk down there to say orchestrated that's even more unclear what that really means just like the word material orchestrated yeah it's we know yes and we've been dancing a little bit between the word intelligence or understanding in consciousness do you kind of see those as sitting in the same space of mystery yes you see I tend to say you have understanding and intelligence and awareness and somehow understanding is in the middle of it you see it's I like to say could you say of an entity that is actually intelligent if it doesn't have the quality of understanding nice I'm using terms I don't even know how to define but who cares really there's somewhat poetic so I I somehow understand them yes I think there's not mathematical in nature yes you see as a mathematician I don't know how to define any of them but at least I can point to the connections so the idea is intelligence is something which I believe needs understanding otherwise you wouldn't say for any intelligence an understanding needs awareness otherwise you wouldn't really say it's understanding you say of an entity they understand something and it's unless it's really aware of it in our normal usage so there's a three sort of weirdness understanding and intelligence and I just tend to concentrate on understanding because that's where I can say something okay that's the kernel theorem and things like that but they what does it mean to be perceive the color blue or something I mean I guess it's much more difficult question I mean is it the same if I see a color blue and you see it if you're something with them wasn't this this condition wants to call them or were you assign a sound - yeah yeah that's right you get colors and sounds mixed up and that sort of thing I mean an interesting subject um here but from the physics perspective from the fundamentals perspective we don't I think we're way off pretty much understanding what's going on there in your 2010 book cycles of time you suggest that another universe may have existed before the Big Bang can you describe this idea first of all what is the Big Bang sounds like a funny word and what may have been there before it yes just as a matter of terminology I don't like to call it another universe because when you have another universe you think of it kind of quite separate from us but these things they're not separate now the Big Bang conventional theories yeah I was actually brought up in the sense of when I started getting dressed in cosmology there was a thing called the steady-state model which was sort of philosophically very interesting and there wasn't a big bang in that theory that somehow new material was created all the time in the form of hydrogen and the universe kept on expanding expanding expanding and there was room for more hydrogen it was a rather philosophically nice picture it was disproved when the Big Bang well when I say the Big Bang this was theoretically discovered by people trying to solve Einstein's equations and apply it to cosmology Einstein didn't like the idea he liked and I a universe which was there all the time and he had a model which they wish there all the time but then there was this discovery accidental discovery a very important discovery of this microwave background and if you you know there's the crackle on your television screen which is is already sensing this microwave background which is coming at us from all directions and you can trace it back and back and back and back and it came from a very early stage of the universe well it's part of the Big Bang Theory the Big Bang Theory was when people tried to solve our science equations they really found you have to have this initial State the universe it was used to be calmly primordial Assam and things like this there's freedmen and a la Mettrie Freedman was a Russian the Metro was the Belgian and they independently were basically Friedman first the maitre talked about the initial state which is a very very concentrated initial state which seemed to be the origin of the universe from more Deol Adam that's the primordial atom is what he called it yes full term and then it became well Fred Hoyle used the term Big Bang in a kind of derogatory sense just like it was a Schrodinger in the cat's right yeah it's this like sort of geek tick got picked up on whereas it wasn't his intention originally but did then the evidence piled up and piled up and my one of my friends and I learned a lot from him when I was in Cambridge just any Xiaomei usually a proponent of steady state and then he got to convert it just said no I'm sorry I had a great respect for him he went around lecturing said I was wrong the steady-state model doesn't work there was this big bang and this microwave background that you see okay it's not actually quite the Big Bang when I said not quiet it's about 380,000 years after the Big Bang but that's what you see but then you have to have had this Big Bang before it's in order to make the equations work and it works beautifully except for one little thing which is this thing called inflation which people had to put into it to make it work when I first heard of it I didn't like it at all what's inflation inflation is it in the first I'm gonna give you a very tiny number think of a second that's not very long now I'm going to give you a fraction of a second one over a number this number has 32 digits between well it's it between 36 and 32 digits tiny tiny time between those two tiny ridiculous seconds fraction of a second the universe was supposed to have expanded in this exponential way an enormous way for no Patera parent reason you had to invent a particular thing called the in photon field to make it do it and I thought this is completely crazy there are reasons why people stuck with this idea you see the thing is that I formed my model for reasons which are very fundamental if you like it has to do this very fundamental principle which is known as the second law of thermodynamics the second law of thermodynamics says more or less things get more and more random as time goes on now another way of saying exactly the same thing is things get less and less random as things go back if you go back in time they get less and less random let me go back and back and back and back and the earliest thing you can directly see is this microwave background what's one of the most striking features of it is that it's random it has this what you call this spectrum of which is what's called the Planck spectrum of frequencies different intensities for different frequencies and it's this wonderful curve due to Max Planck and what's there telling you it's telling you that the entropy is a maximum start is often maximum and it's going up over since I call that a mammoth in the room paradox and mother yes it is so people why don't cosmologists worry about this so I'm worried about it and then I thought well it's not really a paradox because you're looking at matter and radiation at a maximum entropy state what you're not seeing directly in that is the gravitation its gravitation which is not thermalized the gravitation was very very low entropy and it's low entropy by the uniformity and you see that in the microwave - it's very uniform over the whole sky I'm compressing a long story into a very short sentence and doing a great job yet so what I'm saying is that there's a huge puzzle why it was gravity in this very low entropy state very high organized state everything else was all random and that to me was the biggest problem in cosmology the biggest problem nobody seemed worried about it people say they solved all the problems and they don't even worry about it they think inflation sources it doesn't I can't because it's it's just just to clarify that was your problem with the inflation describing some ass but those yes moments right after the Big Bang inflation we're supposed to stretch it out make it all uniform you see it doesn't do it because you can only do it if it's uniform already at the beginning it's it's you just have a look I can't go into the details but it doesn't solve this and it was completely clear to me it doesn't solve well word is the conformal cyclic cosmology of yeah we're starting to talk about something before yes that's singular I began I was just thinking of myself how boring this universe is going to be you've got this exponential expansion this was discovered early in the in this century 20th 21st century people discovered that these supernovae exploding stars showed that the universe is actually undergoing this exponential expansion so it's a self-similar expansion and it seems to be a feature of this term that Einstein introduced into his cosmology for the wrong reason he wanted a universe that was static he put this new term into his cosmology and to make it make sense it's called the cosmological constant and then when he got convinced that the universe had the Big Bang he retracted it complaining this was his greatest blunder the trouble is it wasn't a blunder it was actually right very ironic and so the universe seems to be behaving with this cosmological constant okay so this universe is expanding and expanding what's going to happen in the future well it gets more and more boring from well what's the most interesting thing in the universe well there's black holes the black holes more or less gulped down the entire clusters of galaxies the class it'll swallow up most of our galaxy we will run into Andromeda galaxies black hole that black hole will swallow em they will get bigger and bigger and they'll basically swallow up the whole cluster of galaxies golf it all down pretty well all most of it maybe not all most of it okay that'll happen too there'll be just these black holes around pretty boring but still not as boring as it's going to get it's going to get more boring because these black holes you wait you wait and you wait and you wait and wait and unbelievable length of time and Hawking's black hole evaporation starts to come in and the black holes you just it's a clarity Deus finally evaporate away each one goes away it disappears with the pop at the end what could be more boring that it was boring then now this is really boring there's nothing not even black holes universe gets colder and colder and colder and colder and ever this is very very boring now that's not science is it but it's it's emotional so I thought who's going to be bored by this universe not us we won't be around it'll be mostly photons running around and what the photons do they don't get bored because it's a part of relativity you see it's not really that they don't experience anything that's not the point the photons get right out to infinity without experience anytime it's the way for them where your relativity works and this was part of what I used to do in my old days when I was looking gravitational radiation and how things behaved infinity infinity is just like another place you can squash it down as long as you don't have any mass in the world infinity is just another place the photons get there the gravitons get there what do they get they've run to infinity they say well now I'm here what way there's something on the other side is there the usual view it's just a mathematical notion there's nothing on the other side that's just the boundary of it a nice example is this beautiful series of pictures by the Dutch artist MC Escher you may know them the ones called circle limits they're very famous one with the angels and the Devils and you can see them crowding and crowding and crowding up to the edge now the kind of geometry that these angels and devils and habits that's their infinity but from our perspective infinity is just a point is a place ok there it is I can you just take a brief pause yes and the in just the word you're saying infinity is just a place so I have for the most part infinity sort of even just going back yeah infinity is a mathematical concept I think this is what I think there's an actual physical manifestation in which way does infinity ever manifests itself in our physical universe what it does in various places you see it's the thing that we're if you're not a mathematician you think aren't finished yeah I can't think about that mathematicians think about affinity all the time they get used to the idea and they just play around with different kinds of infinities and it becomes no problem but yeah you just have to take my word for it now one of the things is you see you have taken Euclidian geometry well it just keeps on keeps on keeps on going and it goes out to infinity now there are other kinds of geometry and this is a what's called hyperbolic geometry it's a bit like Euclidean geometry so it'll be different it's like what Asia was trying to describe in his angels and devils and he learned about this from coxeter and he think that's a very nice thing I try to represent this infinity to this kind of geometry so it's not quite Euclidean John which is a bit like it that the angels and the Devils inhabit and their infinity mind this nice transformation you squash the other infinity down so you can draw it as this nice circle boundary to their universe now from our outside perspective we can see their infinity as this boundary now what I'm saying is that it's very like that the infinity that we might experience like the angels and devils in their world can be thought of as a boundary now I found this a very useful way of talking about radiation gravitational radiation and things like that it was a trick mathematical trick so no what I'm saying is that that mathematical trick becomes real that somehow the photons they need to go somewhere because for their from their perspective infinity it's just another place now this is a difficult idea to get your mind around so that's why Kozma one of the reasons because mom's just are finding a lot of trouble taking me seriously but to me it's not not such a wild idea what's on the other side of that infinity you have to think why am I allowed to think of this because photons don't have any mass and we in physics have beautiful ways of measuring time there are incredibly precise clocks atomic and nuclear clocks unbelievably precise while they be so precise because of the two most famous equations of 20th century physics one of them is Einsteins e equals mc-squared what's that tell us energy and mass are equivalent the other one is even older than that still 20th century only just Max Planck e equals H nu nu is a frequency H is a constant again Lexie E is energy energy and frequency are equivalent put the two together energy and mass equivalent Einstein and in frequency equivalent Max Planck put the D together mass and frequency are equivalent absolutely basic physical principle if you have a massive entity a massive particle it is a clock with a very very precise frequency it's not you can't directly use it you have to scale it down so your atomic and nuclear clocks but that's the basic principle you scale it down to something you can actually perceive but it's the same principle if you have mass you have beautiful clocks but the other side of that coin is if you don't have mass you don't have clocks if you don't have clocks you don't have rulers you don't have scale so you don't have space and time you don't have a measure of the scale of space and all scale you have if that you do have the structure that what's called the conformal structure you see it's what the angels levels have if you look at the eye of the devil no matter how close to the boundary it is it has the same shape but it has a different size so you can scale up and you can scale down but you mustn't change the shape so it's basically the same idea but applied to space-time now in the very remote future you have things which don't measure the scale but the shape if you like is still there now that's in the remote future now I'm going to do the exact opposite now I'm going to go way back into the Big Bang now as you get there things go hotter and hotter denser and denser what the universe dominated by particles moving around almost with the speed of light when they get almost with the speed of light okay they begin to lose the mass to therefore a completely opposite reason they lose the sense of scale as well so my crazy idea is the Big Bang and a remote future they seem completely different one is extremely dense extremely hot the other is very very rarefied and very very cold but if you squash one down by this conformal scale and you get the other so although they look and feel very different they're really almost the same the remote future on the other side and claiming is that one of the photons go they go into the next Big Bang you've got to get your mind around that crazy idea taking a step on the other side of the place that is infinity yes but I'm saying the other side of our Big Bang now I'm going back into the Big Bang that was the remote future of a previously on previously on and what I'm saying is that previously on there are signals coming through to us which we can see and which we do see and these are both signals the two main signals are to do with black holes one of them is the collisions between black holes and as they spiral into each other they release a lot of energy in the form of gravitational waves those gravitational waves get through in a certain form into the next DM that's fascinating that there's some I mean maybe I'm maybe you can correct me if I'm wrong but that means that some information can travel yes from another eon exactly that that is fascinating I mean I've seen somewhere described sort of the discussion of the Fermi paradox you know that if there's intelligent life yes being you know communication me immediately takes you there so we have a paper I have my my colleague waha Gossage on who I work with this on these ideas for a while we have a crazy paper on that yes so the family paradoxes right so so if the universe is just cycling over and over and over punctuated by have the punctuated the singularity of the Big Bang and then intelligent or any kind of intelligent systems can communicate through from e on T on why haven't we heard anything from our alien friends because we don't know how to look that's fundamentally the reason is we I don't know you see it's it's speculation I mean the SETI program was a reasonable thing to do but still speculation it's trying to say ok maybe not too far away with a civilization which got there first before us early enough that they could send our signals but how far away would you need to go before I mean I don't know we with so little knowledge about that we haven't seen any signals yet but it's worth looking it's worth looking and what I'm trying to say here's another possible place we might look now you're not looking at civilizations which got there first you're looking at those civilizations which were so successful probably a lot more successful more likely to be man looks of things which knew how to handle their own global warming or whatever it is and to get through it all and to live to a ripe old age in the sense of a civilization to the extent that they could harness signals that they could propagate through for some reason of their own desires whatever we wouldn't know to to other civilizations which might be able to pick up the signals but what kind of signals would they be I have a foggiest let me ask the question yes what to you is the most beautiful idea in physics or mathematics or the art at the intersection of the two I'm going to have to say complex analysis I might have said infinities and one of the most single most beautiful idea I think was the fact that you can even infinities of different sizes and so on but that's anyway I think complex analysis this goes it's got so much magic in it it's a very simple idea you take these you guys hope you do you take numbers you take the integers and then you fill them up into the fractions and the real numbers you imagine you're trying to measure a continuous line and then you think of how you can solve equations then what about x squared equals minus 1 well there's no real number which has to satisfies that so you have to think of well there's a number called I you think you invent it well in a certain sense it's there already but this number when you add that square root of minus 1 to it you have what's called the complex numbers and they're an incredible system if you like you put one little thing in you put square root of -1 in and you get how much benefit out of it all sorts of things that you'd never imagined before and it's that amazing or hiding there in putting that square root of -1 in so in the sense that's the most magical thing I've seen in mathematics or physics and it's in quantum mechanics and in quantum mechanics for there already you might think what's it doing there ok just a nice beautiful piece of mathematics and then suddenly we say nope it's the very crucial basis of quantum mechanics so on there and the way the world works so on the question of whether math is discovered or invented it sounds like you may be suggesting that partially as possible the math is indeed discovered oh absolutely yes no it's more like archeology than you might think so let me ask the most ridiculous maybe the most important question what is the meaning of life what gives your life fulfillment purpose happiness and meaning why do you think we're here on this given all the Big Bang and the infinities of photons that we've told I would say I think it's not a stupid question I mean there are some people you know many of my colleagues new scientists they say well that's a stupid question meaning yeah well we just hear because things came together and produce life and so what I think there's more to it but what there is that's more to it really much idea it might be somehow connected to the mechanisms of consciousness though we're talking about the mystery there it's connected with all sortsa yeah I think these things are tied up in ways which er you see I tend to think the mystery of consciousness is tied up with the mystery of quantum mechanics and how it fits in with the classical world and that's all to do with the mystery of quantum of complex numbers and there are mysteries there which I look like mathematical mysteries but they seem to have a bearing on the way the physical world operates we're scratching the surface we have a long huge way to go before we really understand that and it's a beautiful idea that the the the depth the mathematical depth could be discovered and then there's tragedies of Gaydos and completeness along the way they will have to somehow figure our ways around yeah so Roger as a huge honour to talk to you thank you so much for your time today everything my pleasure thank you thanks for listening to this conversation with roger penrose and thank you to a presenting sponsor at Cash app please consider supporting this podcast by getting expressvpn and expressvpn comm / flex pod and downloading cash app and using collects podcast if you enjoy this podcast subscribe I need to review it with five stars and napa podcasts supported on patreon or simply connect with me on Twitter at lex friedman and now let me leave you with some words of wisdom that roger penrose wrote in his book the emperor's new mind beneath all this technicality is the feeling that it is indeed quote unquote obvious that the conscious mind cannot work like a computer even though much of what is involved in mental activity might do so this is the kind of obvious that a child can see though the child may later in life become browbeaten into believing that the obvious problems are quote unquote non problems to be argued into non-existence by careful reasoning and clever choices of definition children sometimes see things clearly that are obscured in later life we often forget the wonder that we felt as children on the cares of the quote unquote real world have begun to settle on our shoulders children are not afraid to post basic questions that might embarrass us as adults to ask what happens to each of our streams of consciousness after who died where was it before we were born might we become or have been someone else why do we perceive at all why are we here why is there a universe here at all in which we can actually be these are puzzles that tend to come with the awakenings of awareness in any of us and no doubt will the awakening of self-awareness within which ever creature or other entity first came thank you for listening and hope to see you next time you |
Nick Bostrom: Simulation and Superintelligence | Lex Fridman Podcast #83 | the following is a conversation with Nick Bostrom a philosopher at University of Oxford and the director of the future of humanity Institute he has worked on fascinating and important ideas in existential risk simulation hypothesis human enhancement ethics and the risks of super intelligent AI systems including in his book super intelligence I can see talking to Nick multiple times in this podcast many hours each time because he has done some incredible work in artificial intelligence in technology space science and really philosophy in general but we have to start somewhere conversation was recorded before the outbreak of the corona virus pandemic that both Nick and I I'm sure will have a lot to say about next time we speak and perhaps that is for the best because the deepest lessons can be learned only in retrospect on the storm has passed I do recommend you read many of his papers on the topic of existential risk including the technical report titled global catastrophic risks survey that he co-authored with Anders Sandberg for everyone feeling the medical psychological and financial burden of this crisis I'm sending love your way stay strong we're in this together we'll beat this thing this is the artificial intelligence podcast you can enjoy it subscribe on YouTube review it with five stars on a podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma n as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number-one finance app in the App Store when you get it use code lex podcast cash Apple s you said mind your friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props to the cash app engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again you get cash out from the App Store Google Play and use the collects podcast you get $10 and cash Apple also donate $10 the first an organization that is helping to advance robotics and STEM education for young people around the world and now here's my conversation with Nick Bostrom at the risk of asking the Beatles to play yesterday or the Rolling Stones to play satisfaction let me ask you the basics what is the simulation hypothesis that we are living in a computer simulation what is the computer simulation how we're supposed to even think about that well so the hypothesis is meant to be understood in a literal sense not that we can kind of metaphorically view the universe as an information processing physical system but that there is some advanced civilization who built a lot of computers and that what we experience is an effect of what's going on inside one of those computers so that the the world around us our own brains everything we see in perceive and think and feel would exist because this computer is running certain programs do you think of this computer as something similar to the computers of today these deterministic sub touring machine type things is that what we're supposed to imagine or we're supposed to think of something more like a like a like a quantum mechanical system something much bigger something much more complicated something much more mysterious from our current perspective so the ones we have today would you find them in bigger certainly you'd need more memory and more processing power I don't think anything else would be required now it might well be that they do have addition maybe they have quantum computers and other things that would give them even more implausible but I don't think it's a necessary assumption in order to get to the conclusion that a technology mature civilization would be able to create these kinds of computer simulations with conscious beings inside them so do you think the simulation hypothesis is an idea that's most useful in philosophy computer science physics sort of where do you see it having valuable kind of start a starting point in terms of a thought experiment of it is it useful I guess it's more in in informative and interesting and maybe important it's not designed to be useful for something else okay interesting sure but is it philosophically interesting or is there some kind of implications of computer science and physics I think not so much for computer science or physics per se certainly it would be of interest in philosophy I think also to say cosmology or physics in as much as you're interested in the fundamental building blocks of the world and the rules that govern it and if we are in a simulation there is then the possibility that say physics at the level were the computer running the simulation could could be different from the physics governing phenomena in the simulation so I think might be interesting from point of view of religion or just from for a kind of trying to figure out what what the heck is going on so we mentioned the simulation hypothesis so far there is also the simulation argument which I tend to make a distinction so simulation hypothesis we are living in a computer simulation simulation argument this argument that tries to show that one of three propositions is true one of which is the simulation hypothesis but there are two alternatives in the original simulation argument which which we can get to yeah let's go there by the way confusing terms Picasa people will I think probably naturally thinks simulation argument equals simulation hypothesis just terminology wise but let's go there so simulation hypothesis means that we are living in simulations the hypothesis that we're living in simulation simulation argument has the three complete possibilities that cover all possibilities so what yeah so it's like a disjunction it says at least one of these three is true yeah although it doesn't on its own tell us which one so the first one is that almost all civilizations at our current stage of technological development go extinct before they reach technological maturity so there is some great filter that makes it so that basically none of the civilizations throughout you know maybe vast cosmos will ever get to realize the full potential of technological develop and this could be theoretically speaking this could be because most civilizations kill themselves too eagerly or destroy themselves early or it might be super difficult to build a simulation so the the span of time theoretically it could be both now I think it looks like we would technically be able to get there in a time span that is short compared to say the lifetime of planets and other sort of astronomical processes so your intuition is the build simulation is not well so this is interesting concept of technological maturity it's kind of an interesting concept to have other purposes as well we can see even based on our current limited understanding what some lower bound would be on the capabilities that you could realize by just developing technologies that we already see are possible so for example one one of my research fellows here eric drexler back in india teas studied molecular manufacturing that is you could analyze using theoretical tools and computer modeling the performance of various molecularly precise structures that we didn't then and still don't did I have the ability to actually fabricate but you could say that well if we could put these atoms together in this way then the system would be stay and it would you know rotate with at this speed and have what these computational characteristics and he also outlined some pathways that would enable us to get to this kind of molecularly manufacturing in the fullness of time you could do other other studies we have done you can look at the speed at which say it would be possible to colonize the galaxy if you had mature technology we have an upper limit which is the speed of light we have sort of a lower current limit which is how fast current Rockets go we know we can go faster than that by just you know making them bigger and have more fuel and stuff and and you can then start to describe the technological affordances that would exist once a civilization has had enough time to develop Eva at least those technologies we're already not possible then maybe they would discover other new physical phenomena as well that we haven't realized that would enable them to do even more but but at least there is this kind of basic set of capabilities in Jilin garnett well how do we jump from molecular manufacturing to deep-space exploration to mature technology like what's the connection well so these would be two examples of technological capability sets that we can have a high degree of confidence or physically possible in our universe under that a civilization that was allowed to continue to develop its science and technology would eventually attain you can Intuit like we can kind of see the set of breakthroughs they're likely to happen so you can see like what did you call the technological set with computers maybe at easiest I mean the one is we could just imagine bigger computers using exactly the same parts that we have so you can kind of scale things that way right but you could also make processors bit faster if you had this molecular nanotechnology that director x2 described he characterized a kind of crude computer built with these parts that that would perform you know at a million times the human brain while being we can be smaller the size of a sugar cube and he made no claim that that's the optimum computing structure like fraud you know we could build a faster computers that would be more efficient but at least you could do that if you had the ability to do things that were atomically precise yes means you can combine these two you could have this kind of nanomolecular ability to build things at the bottom and then say at this as a spatial scale that would be attainable through space colonizing technology you could then start for example to characterize a lower bound on the amount of computing power that technology material civilization would have if it could grab resources you know planets and so forth and then use this molecular nanotechnology to optimize them for computing you'd get a very very high lower bound on the amount of compute so sorry define some terms so technologically mature civilization is one that took that piece of technology to its to its lower bound what is it technological matures well yeah so that mean it's a strong concept and we really need for the simulation hypothesis I just think it's interesting in its own right so it would be the idea that there is some stage of technological development for you basically maxed out that you developed all those general-purpose widely useful technologies that could be developed or at least kind of come very close to the my you know 99.9 percent there or something so that's that's that's an independent question you can think either that there is such a ceiling or you might think it just goes the technology tree just goes on forever where where is your sense for I would guess that there is I I'm a maximum that you would start to asymptotes towards so new things won't keep springing up new ceilings in terms of basic technological capabilities I think that yeah there's like a finite set of those that can exist in this universe more of our I mean I wouldn't be that surprised if we actually reached close to that level fairly shortly after we have say machine super intelligence so I don't think it would take million of years for a human originating civilization to begin to do this it think it's like more more likely to happen on historical timescales but that that's that's an independent speculation from the simulation argument I mean for the purpose of the simulation argument it doesn't really matter whether it goes indefinitely far up or whether there is a ceiling as long as we know we could at least get to a certain level and it also doesn't matter whether that's gonna happen in a hundred years or five thousand years or 50 million years like the timescales really don't make any difference for the ceilin garna a little bit like there's a big difference between a hundred years and ten million years you know so it doesn't really not matter because you just said this is a matter if we jump scales to beyond historical skills so we described that so for the simulation argument sort of doesn't it matter that we if it takes ten million years it gives us a lot more opportunity to destroy civilization in the mean time yeah well so it would shift around the probabilities between these three alternatives that is if we are very very far away from being able to create these simulations if it's like say the billions of years into the future then it's more likely that we will fail ever to get there they're more time for us to kind of you know give go extinct along the way and similarly for other civilizations so it's important to think about how hard it is to build simulation from in terms of yeah figuring out which of the disk jockeys but for the simulation argument itself which is agnostic as to which of these three alternatives is true okay it's like you don't have to sit like this immolation argument would be true whether or not we thought this could be done in five hundred years or it would take five hundred million years so for sure the simulation argument stands I'm sure there might be some people who oppose it but it doesn't matter I mean it's it's very nice those three cases covered but the fun part is at least not saying what the probabilities are but kind of thinking about kind of intuitive reasoning about what's more likely what what the kind of things that would make some of the arguments less and more so like but let's actually I don't think we went through them so number one is we destroy ourselves before we ever create simulate right so that's kind of sad but we have to think not just what what might destroy us I mean the day there could be some whatever disastrous for me crowd slamming the earth a few years from now that that could destroy us right but you'd have to postulate in order for this first disjunct to be true that almost all civilizations throughout the cosmos also failed to reach technological maturity and the underlying assumption there is that there is likely a very large number of other intelligent civilizations well if there are yeah then they would virtually all have to succumb in the same way I mean then that that leads off another I guess there are a lot of little digressions that you know there so there yeah give me dragging us back there are these there is a set of basic questions that always come up in conversations with interesting people yeah like the Fermi paradox like there's like you could almost define whether person is interesting whether they're at some point because there was a Fermi paradox comes up like well so forward it's worse it looks to me that the universe is very big I mean in fact according to the most popular current cosmological theory is infinitely big and so then it would follow pretty trivially that that it would contain a lot of other civilizations in fact infinitely many if you have some locals stochasticity and infinitely many is like you know infinitely many lumps of matter one next to another there's a kind of random stuff in each one then you're going to get all possible outcomes with probability one infinitely repeated so so then then certainly that would be a lot of extraterrestrials out there I'd maybe short of that if the universe is very big there might be a finite but large number if we literally one yet and then of course if we went extinct then all of civilizations at our current stage would have gone extinct before becoming technological material so then it kind of becomes trivially true that a very high fraction of those Quantic things but if we think there are many I mean it's interesting because there are certain things that plausibly could kill us like a certain if you look at existential risks and it might be a different like that that the best answer to what would be most likely to kill us might be a different answer than the best answer to the question if there is something that kills almost everyone what would that be because that would have to be some risk factor that was kind of uniform over all possible civilizations yeah so in this for the for the seekers argument you have to think about not just us but like every civilization dies out before they create this simulation yeah or something very close to everybody okay so what's number two in well so number two is the convergence hypothesis that is that maybe like a lot of some of these civilizations do make it through to technological maturity but out of those who do get there they all lose interest in creating these simulations so they just they have the capability of doing it but they choose not to yeah not just a few of them decide not to but you know you know out of a million you know maybe not even a single one of them would do it and I think when you say lose interest that sounds like unlikely because it's like they get bored or whatever but it could be so many possibility within that igniculus I mean losing interest could be it could be anything from it being exceptionally difficult to do to fundamentally changing the sort of the fabric of reality if you do it as ethical concerns all those kinds of things could be exceptionally strong pressures well certainly I mean yeah ethical concerns I mean not really too difficult to do I mean in a sense that's the first adopter that you get to technical maturity where you would have the ability using only a tiny fraction of your resources to create many many simulations so it wouldn't be the case that they would need to spend half of their GDP forever in order to create one simulation and the head is like difficult debate about whether they should you know invest half of their GDP for this it would more be like well if any little fraction of the civilization feels like doing this at any point during maybe they're you know millions of years of existence then there would be millions of simulations but but certainly that could be many conceivable reasons for why there would be this convert many possible reasons for not running ancestor simulations or other computer simulations even if you could do so cheaply by the way what's an ancestor simulation well that would be the type of computer simulation that would contain people all like those we think have lived on our planet in the past and like ourselves in terms of the types of experiences to have and and where those simulated people are conscious so it's like not just simulated in the same sense that a a non-player character would be simulated in the current computer game where it's kind of has you can have at our body and then a very simple mechanism that moves it forward or backwards or but but something where the the simulated being has a brain let's say that simulated at a sufficient level of granularity that that it would have the same subjective experiences as we have so where does consciousness fit into this do you think simulation like is there are different ways to think about how this can be simulated just like you're talking about now do we have to simulate each brain within the larger simulation is it enough to simulate just the brain just the minds and not the simulation I'm not the big in the universe itself like is there different ways to think about this yeah I guess there is a kind of premise in the simulation argument rolled in from philosophy of mind that is that it would be possible to create a conscious mind in a computer and that what determines whether some system is conscious or not is is not like whether it's built from our organic biological neurons but maybe something like what the structure of the computation is that it implements so we can discuss that if we want but I think it would be far worse worse might be that it would be sufficient say if you had a computation that was identical to the computation in the human brain down to the level of neuron so if you had a simulation with 100 billion neurons connected in the same ways to human brain and you'd then roll that forward with the same kind of synaptic weights and so forth so you actually had the same behavior coming out of this as a human without brain would have done then I think that would be conscious now it's possible you could also generate consciousness without having that detailed simulation there I'm getting more uncertain exactly how much you could simplify or abstract away canyonland garnett what do you mean I missed where your place in consciousness in a second well so that so if you are a computational is do you think that what creates consciousness is the implementation of a computation some property emergent property in the computation itself yes the idea yeah you could say that but then the question is which what what's the class of computations such that when they are wrong consciousness emerges so if you just have like something that I adds 1 plus 1 plus 1 plus 1 like a simple computation you think maybe that's not gonna have any consciousness if on the other hand the computation is one like our human brains are performing where as part of the computation there is like you know a global work space is sophisticated attention mechanism there is like self representations of other cognitive processes and a whole lot of other things that possibly would be conscious and in fact if it's exactly like ours I think definitely it would but exactly how much less than the full computation that the human brain is performing would be required is a little bit I think of an open question he asks another interesting question as well which is would it be sufficient to just have say the brain or would you need the environment right that's a nice way in order to generate the same kind of experiences that we have and there is a bunch of stuff we don't know I mean if you look at say current virtual reality environments one thing that's clear is that we don't have to simulate all details of them all the time in order for say that the human player to have the perception that there is a full reality and that you can have say procedurally generated virtual might only render a scene when it's actually within the view of the player character and so similarly if this if this if this environment that that we perceive is simulated it might be that all of the parts that come into our view are rendered at any given time and a lot of aspects that never come into view say the details of this microphone I'm talking into exactly what each atom is doing at any given point in time might not be part of the simulation only a more coarse-grained representation so that to me is actually from an engineering perspective why the simulation hypothesis is really interesting to think about is how much how difficult is it to sort of in a virtual reality context I don't know fake is the right word but to construct a reality that is sufficiently real to us to be to be immersive in that way that the physical world is I think that's just that's actually probably an answerable question of psychology of computer science of how how where's the line where it becomes so immersive that you don't want to leave that world yeah alright that you don't realize while you're in it that it is a virtual world yeah those are two actually questions yours is the more sort of the good question about the realism but mine from my perspective what's interesting is it doesn't have to be real but it how how can we construct the world that we wouldn't want to leave oh yeah I mean I think that might be too low a bar I mean if you think say when people first had the pong or something like that like I'm sure there were people who wanted to keep playing it for a long time because it was fun and I wanted to be in this little world I'm not sure we would say it's immersive I mean I guess in some sense it is but like an absorbing activity it doesn't even have to be but they left that world though that's the so like I think that bar is deceivingly high so they eventually look so they you can play pong or Starcraft or would have more sophisticated games for hours for four months you know Wow well the Warcraft could be in a big addiction but eventually they escape that ah so you mean when it's uh absorbing enough that you would spend your entire it would ya choose to spend your entire life in there and then thereby changing the concept of what reality is but as your reality your reality becomes the game not because you're fooled but because you've made that choice yeah and it may be different people might have different preferences regarding that some Saul might even even if you had any perfect virtual reality might still prefer not to spend the rest of their lives there meaning philosopher there's this experience machine thought experiment have you come across this so Robert Nozick had this thought experiment where you imagine some crazy super-duper neuroscientist of the future have created a machine that could give you any experience you want if you step in there and for the rest of your life you can kind of pre-programmed it in different ways so you're you know fondest dreams could come true you could whatever you dream you want to be a great artist a great lover like have a wonderful life all of these things mmm if you step into the experience machine will be your experiences constantly happy and but we kind of disconnect from the rest of reality and it would float there in the tank and the Gnostic thought that most people would choose not to enter the experience machine I mean many might want to go there for a holiday but they wouldn't want to check out of existence permanently and so he thought that was an argument against certain views of value according to what we what we value is a function of what we experience because in the experience machine you can have any experience you want and yet many people would think that would not be much value so therefore what we value depends on other things than what we experience so ok can you can you take that argument further what about the fact that maybe what we values the up and down of life so you could have up and downs in the experience machine right but what can't you have in the experience machine well I mean that then becomes an interesting question to explore but for example real connection with other people if the experience machine is the solar machine where it's only you like that's something you wouldn't have there you would have this objective experience that would be like fake people yeah but when if you gave somebody flowers that wouldn't be any bother they were actually got happy it would just be a little simulation of somebody smiling but the simulation would not be the kind of simulation I'm talking about in the simulation argument where simulated creatures conscious it would just be a kind of smiley face that would look perfectly real to you so we're now drawing a distinction between appear to be perfectly real and actually being real yeah so that could be one thing I mean like a big impact on history maybe it's also something you won't have if you check into this experience machine so some people might actually feel the life I want to have for me is one where I have a big positive impact on history unfolds so let's see if you could kind of explore these different possible explanations for why this you wouldn't want to go into the experience machine if that's if that's what you feel and what one interesting observation regarding this Nozick thought experiment and the conclusions he wanted to draw from it is how much is a kind of a status quo effect so a lot of people might not want to jettison card reality to plug in to this dream machine but if they instead we're told well what you've experienced up to this point was a dream now do you want to disconnect from this and enter the real world when you have no idea maybe what the real world is or maybe you could say well you're actually a farmer in Peru growing you know peanuts and you could live for the rest of your life in this well or or would you want to continue your your dream life as Alex Friedman gone around the world making podcasts and doing research so if the status quo was that the that they were actually in the experience machine howling a lot of people might prefer to live the life that they are familiar with rather than sort of bail out into something the change itself the leap yeah it might not be so much the the reality itself that we're after but it's more that we are maybe involved in certain projects and relationships and we have you know a self-identity and these things that's our values are kind of connected with carrying that forward and then whether it's inside a tank or outside a tank in Peru or whether inside a computer outside a computer that's kind of less important to what what we ultimately care about yeah but still so just linger on it it is interesting I find maybe people are different but I find myself quite willing to take the leap to the farmer in Peru especially as the virtual reality system become more realistic I I find that possibility and I think more people would take that leap but so in this in this thought experiment just to make sure we are understand so in this case that the farmer in Peru would not be a virtual reality that would be the real the real that really real that your life like before this whole experience machine started well I kind of assumed from that description you're being very specific but that kind of idea just like washes away the concept of what's real I mean I'm still a little hesitant about your kind of distinction between real and illusion because when you can have an illusion that's feels I mean that looks real and you know what III don't know how you can definitively say something is real or not like what's what's a good way to prove that something is real in that context well so I guess in this case it's Morris depression in one case you're floating in a tank with these wires by the super-duper neuroscientists plugging into your head giving you Lex Friedman experiences in the other you're actually tilling the soil in Peru growing peanuts and then those peanuts are being eaten by other people all around the world by the exports and this that's two different possible situations in the one and the same real world that that you could choose to occupy but just to be clear when you're in a vat with wires and the neuroscientists you can still go farming in Peru right mmm but like well you could you could if you wanted to you could have the experience of farming in Peru but what that wouldn't actually be any peanuts grown well but what makes a peanut so so peanut could be grown and you could feed things with that peanut and why can't all of that be done in a simulation I hope first of all that they actually have peanut farms in Peru I guess we'll get a lot of comments otherwise angry I was way up to the point you should know you can't realize in that climate now I mean I I think I mean I I in the simulation I think there's a sense the important sense in which it should all be real nevertheless there is a distinction between inside the simulation and outside the simulation or in the case of no.6 thought experiment whether you're in the VAT or outside the VAT and some of those differences may or may not be important I mean that that comes down to your values and preferences so if they if the experience machine only gives you the experience of growing peanuts but you're the only one in in the experience machines there's other you can within the experience machine others can plug in well they're versions of the experience machine so in fact you might want to have distinguish different thought experiments different versions of it so in in like in the original thought experiment maybe it's only right just you so and you think I wouldn't want to go in there well that tells you something interesting about what you value and what you care about then you could say well what if you add the fact that there would be other people in there and you would interact with them well it starts to make it more attractive right then you can add in well what if you could also have important long-term effects on human history in the world and you could actually do something useful even though you were in there that makes it maybe even more attractive like you could actually have a life that had a purpose and consequences and so as you sort of add more into it it becomes more similar to the the baseline reality that that you were comparing it to yeah but I just think inside the experience machine and without taking those steps you just mentioned you you you still have an impact on long-term history of the creatures that live inside that of the quote-unquote fake creatures that live inside that experience machine and that like at a certain point you know if there's a person waiting for you inside that experience machine maybe your newly found wife and she dies she has fears she has hopes and she exists in that machine when you plug out when you unplug yourself and plug back in she's still there going on about her life oh well in that case yeah she starts to have more of an independent existence i independent existence but it depends I think on how she's implemented in the experience machine take one the mid case where all she is is a static picture on the wall of photograph right so you think well I can look at her right but that's it there's no that then you think well it doesn't really matter much what happens to that and any more than a normal photographs if you tear it up right it means you can't see it anymore but you haven't harmed the person whose picture you tore up to go home but but if she's actually implemented say at a neural level of details so that she's a fully realized digital mind with the same behavioral repertoire as you have then very plausibly she would be a conscious person like you are and then you would what you do in in this experience machine would have real consequences for how this other mind felt so you have to like specify which of these experience machines you're talking about I think it's not entirely obvious that it will be possible to have an experience machine that gave you a normal set of human experiences which include experiences of interacting with other people without that also generating consciousnesses corresponding to those other people that is if you create another entity that you perceive and interact with that to you looks entirely realistic not just when you say hello they say hello back but you have a rich interaction many days deep conversations like it might be that the only possible way of implementing that would be one that also has a side effect instantiated this other person in enough detail that you would have a second consciousness there I think that's to some extent an open question so you don't think it's possible to fake consciousness and say well it might be I mean I think you can certainly fake if you have a very limited interaction with somebody you could certainly fake that that is if all you have to go on is somebody said hello to you that's not enough for you to tell whether that was a real person there or a pre-recorded message or you know like a very superficial simulation that has no conscious Ness because that's something easy to fake we could already fake it now you can record a voice recording and you know but but if you have a richer set of interactions where you're allowed to answer ask open-ended questions and probe from different angles that couldn't sort of be you could give can't answer to all of the possible ways that you could probe it then it starts to become more plausible that the only way to realize this thing in such a way that you would get the right answer for many which angle you probe it would be a way of instance ating it we also instantiated a conscious mind yeah movie on the intelligence part but there's something about me that says consciousness is easier to fake like I I've recently gotten my hands on a lot of rubas don't ask me why or how but and I've made them there's just a nice robotic mobile platform for experiments and I made them scream and/or moan in pain so on just to see when they're responding to me and it's just a sort of psychological experiment myself and I think they appear conscious to me pretty quickly my guy to me at least my brain can be tricked quite easily right I said if I introspect and they it's harder for me to be tricked that something is intelligent so I just have this feeling that inside this experience machine just saying that you're conscious and having certain qualities of the interaction like being able to suffer like being able to hurt like being able to wander about the essence of your own existence not actually I mean you know the creating the illusion that you're wandering about it is enough to create the fit of consciousness and be create the illusion of consciousness and because of that create a really immersive experience to where you feel like that is the real world so you think there's a big gap between appearing conscious and being conscious or is it not just that gets very easy to be conscious I'm not actually sure what it means to be conscious all I'm saying is the illusion of consciousness is enough for this to create a social interaction that's as good as if the thing was conscious meaning I'm making it about myself right yeah I mean I guess there are a few differences one is how good the interaction is which might mean if you don't really care about like probing hard for whether the thing is conscious maybe maybe it would be a satisfactory interaction whether or not you really thought it was conscious now if you really care about it being contrasting in like inside this experience machine yes how easy would it be to fake it and you say it sounds easy easy yeah then the question is would that also mean it's very easy to instantiate consciousness like it's much more widely spread in the world and we have thought it doesn't require a big human brain with a hundred billion neurons all you need is some system that exhibits basic intentionality and can respond and you already have consciousness like in that case I guess you still have a close coupling they denied that did I guess that a case would be where they can come apart where we could create the appearance of there being a conscious mind without actually not being another conscious mind I'm yeah I'm somewhat agnostic exactly where these lines go I think one one observation that makes it possible that you could have very realistic appearances relatively simply which also is relevant for the simulation argument and in terms of thinking about how realistic with the virtual reality model have to be in order for the creature not to notice that anything was awry well just think of our own humble brains during the wee hours of the night when we are dreaming many times well dreams are very mersive but often you also don't realize that you're in a dream and that's produced by simple primitive three-pound lumps of neural matter effortlessly so if a simple brain like this can create a virtual reality that seems pretty real to us then how much easier would it be for a super intelligent civilization with planetary sized computers optimized over the eons to create a realistic an environment for you to interact with yeah and by the way behind that intuition is that our brain is not that impressive relative to the possibilities of what technology could bring it's also possible that the brain is the epitome is the ceiling like just because ceiling how it's not possible meaning like this is the smartest possible thing that the universe could create so that's seems unlikely unlikely to me yeah I mean for some of these reasons we alluded to earlier in terms of designs we already have four computers that would be faster by many orders of magnitude than the human brain yeah but it could be that the constraints the cognitive constraints in themselves is what enables the intelligence so the more the more powerful you make the computer the less likely is to become super intelligent this is where I say dumb things to push back and uh yeah I'm not sure I father we might you know I mean so there are different dimensions of intolerance yeah a simple one is just speed like if you could solve the same challenge faster in some sense yes you're like smarter so there I think we have very strong evidence for thinking that you could have a computer in this universe that would be much faster than the human brain and therefore have speed super into it's like be completely superior maybe a million times faster then maybe there are other ways in which you could be smarter as well maybe more qualitative ways right and there the concepts are a little bit less clear-cut so it's harder to make a very crisp neat firmly logical argument for why that could be qualitative superintelligence as opposed to just thinks that we're faster although I still think it's very plausible and for various reasons that that are less than watertight arguments but when you can sort of for example if you look at animals and brains and even within humans like there seems to be like Einstein versus random person like it's not just that Einstein was a little bit faster but like how long would it take a normal person to invent general relativity it's like it's not twenty percent longer than it took Einstein or something like that it's like I don't know whether that we do it at all or it would take millions of years or some totally bizarre so well you put your tuition is that the computer size will get you go the increasing the size of the computer and the speed of the computer might create some much more powerful levels of intelligence that would that enable some of the things we've been talking about would like the simulation being able to simulate an ultra realistic environment ultra realistic yes ception of reality yeah I mean it's like they're speaking it would not be necessary to have super intelligence in order to he'll say the technology to make these simulations ancestor simulations or other kinds of simulations and as a matter of fact that thing if if there are if we are in a simulation it would most likely be one built by a civilization that had super intelligence it certainly would help a lot I mean it could build more efficient large-scale structures if you had super intelligence I also think that if you had the technology to build these simulations that's like a very advanced technology it seems kind of easier to get technology to super intelligence yeah so I'd expect by the time that could make these fully realistic simulations of human history with human brains in there like before that they got to that stage I would have figured out how to create machines super tall or maybe biological enhancements of their own brains if there were biological creatures to start with so we talked about the the three parts of the simulation argument one we destroy ourselves before we ever create the simulation two we somehow everybody somehow loses interest in creating simulation three we're living in a simulation so you've kind of I don't know if your thinking has evolved on this point but you kind of said that we know so little that these three cases might as well be equally probable so probabilistically speaking where do you stand on this yeah I know I mean I don't think equal necessarily would be the most supported probability assignment so how would you without assigning actual numbers wait wait what's more or less likely in your in your well I mean historically tended to punt on the question of like has between these three so maybe you ask me another way is which kind of things would make it each of these more or less likely what cried VI certainly in general terms if you think anything that say increases or reduces the probability of one of these we tend to slosh probability around on the other so if if one becomes less probable like the other would have to cuz gotta add up to one yes so if we consider the first hypothesis the first alternative that there's this filter that makes it so that virtually no civilization reaches technological maturity in particular our own civilization if that's true then it's like very unlikely that we would reach technical maturity just because if almost no civilization at our stage does it then it's unlikely that we do it so hang on sorry again longer than that for a second well if it's the case that almost all civilizations at our current stage of technological maturity fails at failed at our current stage of technical development failed to reach maturity that would give us very strong reason for thinking we will to reach technical material and also so the flipside of that is the fact that we've reached it means that many other civilizations yeah so that means if we get closer and closer to actually reaching technological maturity there's less and less distance left where we could go extinct before we are there and therefore the probability that we will reach increases as we get closer and that would make it less likely to be true that almost all civilizations at our current stage failed to get there like we would have this what the one case we started ourselves would be very close to getting there that would be strong evidence it's not so hard to get too technical maturity so to the extent that we you know feel we are moving nearer to technology maturity that that would tend to reduce the probability of the first alternative and increase the probability of the other - it doesn't need to be a monotonic change like if every once in a while some new threat comes into view some bad news thing you could do with some novel technology for example you know that that could change our probabilities in the other direction but that the technology again you have to think about as that technology has to be able to equally in an even way affect every civilization out there yeah pretty much I mean that strictly speaking is not real I mean that could that could be two different existential risk and every civilization you know you know one or the other like but none of them kills more than 50% like yeah but that incidentally so in some of my the work I mean on machine super intelligence like so I wanted some existential risks where they did sort of super intelligence AI and how we must make sure you know to handle that wisely and carefully it's not the right kind of existential catastrophe to make first alternative true though like it might be bad for us if the future lost a lot of value as a result of it being shaped by some process that optimized for some completely non human value but even if we got killed by machine superintendence is that machine super intelligence might still attain technical maturity so I see so you're not very you're not human exclusive this could be any intelligent species that achieves like it's all about the technological maturity it's not that the humans have to attain it right like super intelligence replace us and that's just as well fascination as well yeah yeah I mean it could interact with the second high pop foul turn ative like if the thing that replaced us was either more likely or less likely than we would be to have an interest in creating ancestor simulations you know that that could affect probabilities but yeah to a first-order like if we all just die then yeah we won't produce any simulations because we are dead but if we all die and get replaced by some other intelligent thing that then gets the technical maturity the question remains of course if my not that thing that needs some of its resources to to do this stuff so can you reason about this stuff this is given how little we know about the universe is it reasonable to to reason about these probabilities so like how little well maybe you can disagree but to me it's not trivial to figure out how difficult it is to build a simulation we kind of talked about it a little bit we also don't know like as we tried to start building it like start creating virtual worlds and so on how that changes the fabric of society like there's all these things along the way that can fundamentally change just so many aspects of our society about our existence that we don't know anything about like the kind of things we might discover when we understand to a greater degree the fundamental the physics like the theory if we have a break through have a theory and everything how that changes stuff how that changes deep space exploration and so on so like is it still possible to reason about probabilities given how little we know yes I think though there will be a large residual of uncertainty that we'll just have to acknowledge and I think that's true for most of these big-picture questions that we might wonder about it's just we are small short-lived small brained cognitively very limited humans with little evidence and it's amazing we can figure out as much as we can really about the cosmos but it okay so there's this cognitive trick that seems to happen where I look at the simulation argument which for me it seems like case one and to feel unlikely I want to say feel unlikely as opposed to sort of in like it's not like I have too much scientific evidence to say that either one or two are not true it just seems unlikely that every single civilization destroys itself and it seems like feels unlikely that the civilizations lose interest so naturally the without necessarily explicitly doing it but this illumination the simulation argument it basically says it's very likely we're living in a simulation like to me my mind mm-hmm naturally goes there I think the mind goes there for a lot of people is that the incorrect place for it to go well not not not necessarily I think the second alternative which has to do with the motivations and interest of technologically mature civilizations I think there is much we don't understand about that can you talk about that a little bit what do you think I mean this question that pops up when you have when you build an AGI system or build the general intelligence or how does that change our motivations do you think of fundamentally transform our motivations well it doesn't seem that implausible that once you take this leap to the technological maturity I mean I think like it involves creating machine superintelligence possibly that would be sort of on the path for basically all civilizations maybe before they are able to create large numbers of ancestor simulations they would that possibly could be one of these things that quite radically changes the orientation of what a civilization is in fact optimizing for there are other things as well so at the moment we have not perfect control over our own being our own mental states our own experiences are not under our direct control so for example if if you want to experience a pleasure and happiness you might have to do a whole host of things in the external world to try to get into the stage into the mental state where you experience pleasure you look like some people get some pleasure from eating great food well they can just turn that on they have to kind of actually go to a nice restaurant and then they have to make money too so there's like all this kind of activity that maybe arises from the fact that we are trying to ultimately produce mental states but the only way to do that is by a whole host of complicated activities in the external world now at some level of technological development I think will become other potent in the sense of gaining direct ability to choose our own internal configuration and enough knowledge and insight to be able to actually do that in a meaningful way so then it could turn out that there are a lot of instrumental goals that would drop out of the picture and be replaced by other instrumental goals because we could now serve some of these final goals in more direct ways and who knows how all of that shakes out after civilizations reflect on that and converge and different attractors and so on and so forth and and that that could be new new instrumental considerations that come into view as well that that we are just oblivious to that would maybe have a strong shaping effect on actions like very strong reasons to do something or not to do something and we just don't realize they're there because we are so dumb tumbling through the universe but if if almost inevitably on on route to attaining the ability to create many other simulations you do have this cognitive enhancement or advice from super intelligences or you yourself then maybe there's like this additional set of considerations coming into view and yesterday I it's obvious that the thing that makes sense is to do X whereas right now it seems so you could X Y or Z and different people will do different things and we're kind of random in that sense yeah because at this time with our limited technology the impact of our decisions is minor I mean that's starting to change some in some ways but well I'm not sure it follows that the impacts of our decisions is minor well it's starting to change I mean I suppose 100 years ago was minor it's starting to so it depends on how you viewed so what people did 100 years ago still have effects on the world today Oh as a I see as a as a civilization or in the together yeah so it might be that the greatest impact of individuals is not at technical maturity or very far down it might be earlier on when there are different tracks civilization could go down I mean maybe the population is smaller things still haven't settled out if you count indirect effects that that that those could be bigger than the direct effects that people have later on so part 3 of the argument says that so that leads us to a place where eventually somebody creates a simulation that I think you you had a conversation Joe Rogan's I think there's some aspect here where you got stuck a little bit how does that lead to were likely living in a simulation so this kind of probability argument if somebody eventually creates a simulation why does that mean that we're now in a simulation but what you get to if you accept alternative three first is that would be more simulated people with our kinds of experiences than on simulated ones like if in n kind of if you look at the world as a whole by the end of time as it were you just count it up that would be more simulated once than on simulated ones then there is a an extra step to get from that if you assume that suppose for the sake of the argument that that's true how do you get from that to this statement we are probably in a simulation so here you are introducing an indexical statement like it's that this person right now is in a simulation they're all these other people you know that are in simulation so some that are not in the simulation but what probability should you have that you yourself is one of the simulated ones in a setup so so yeah so I call it the bland principle of indifference which is that in in cases like this when you have to I guess sets of observers one of which is much larger than the other and you can't from any internal evidence you have tell which that you belong to you should design a probability that's proportional to the size of these sets so that if there are ten times more simulated people with your kinds of experiences you would be ten times more likely to be one of those is that as intuitive as it sounds in that that seems kind of if you don't have enough information you should rationally just assign the same probability as the yeah kind of the size of the set it seems seems pretty plausible to me were the holes in this is it at the at the very beginning the assumption that everything stretches sort of you have infinite time essentially you don't need infinite time you need what how long this is the time what however long it takes I guess for a universe to produce an intelligent civilization that has intense the technology to run some ancestor simulations gotcha at some point when the first simulation is created that stretch of time just a little longer than they're all start creating simulations kind of like yeah I mean that might that different it might if you think of there being a lot of different planets and some subset of them have life and then some subset of those get to intelligent life and some of those maybe eventually start creating simulations they might get started at quite different times like maybe on some planet it takes a billion years longer before you get like monkeys or before you get even bacteria then on another planet so that like this might happen kind of at different cosmological epochs is there a connection here to the Doomsday argument in that sampling there if there is a connection in that they both involve an application of anthropic reasoning that is reasoning about these kind of indexical propositions but the assumption you need in the case of the simulation argument it's much weaker than the simulator the assumption you need to make the Doomsday argument go through what is the Doomsday argument and maybe you can speak to the anthropic reasoning in more general yeah that's that's a big an interesting topic in its own right and tropics but the Doomsday argument is this really first discovered by Brandon Carter was a theoretical physicist and then developed by philosopher John Wesley I think it might have been discovered initially in the 70s or 80s and Lester wrote this book I think in 96 and there are some other versions as well God is a physicist but let's focus on the Carter Leslie version where it's an argument that we have systematically underestimated the probability that humanity will go extinct soon now I should say most people probably think at the end of the day there is something wrong with this doomsday argument that it doesn't really hold it's like there's something wrong with it but it's proved hard to say exactly what is wrong with it and different people have different accounts my own view is it seems inconclusive but and I can say what the argument is yeah yeah so maybe it's easiest to explain via an analogy to sampling from urns so imagine you have a big imagine you have two urns in front of you and they have balls in them that have numbers so there's the tourist look the same but inside one there are ten balls ball number 1 2 3 up to ball number 10 and then in the other urn you have a million balls numbered one to a million and somebody puts one of these urns in front of you and asked you to guess what what's the chance it's the 10 ball and you say 50/50 they you know I can't tell which urn it is um but then you're allowed to reach in and pick a ball at random from the urn and that's suppose you find that it's ball number 7 said that strong evidence for the 10 ball hypothesis like it's a lot more likely that you would get such a lobe numbered ball if they're on the 10 balls in the urn like it's in fact 10 percent done right then if there are a million balls it would be round likely you would get number 7 so you perform a Bayesian update and if your prior was 50/50 that it was the temple urn you become virtually certain after finding the random sample was 7 that it's only has 10 balls in it so in the case of the urns this is on controversial just elementary probability theory the Doomsday argument says that you should recent in a similar way with respect to different hypotheses about how many many balls there will be in the urn of humanity I said for how many humans that will have human being by the time we go extinct so to simplify let's suppose we only consider two hypotheses either maybe 200 billion humans in total or 200 trillion humans in total you could fill in more hypotheses but it doesn't change the principle here so it's easiest to see if we just consider these two so you start with some prior based on ordinary empirical ideas about threats to civilization and so forth and maybe you say it's a 5% chance that we will go extinct by the time there will have been 200 billion only you're kind of optimistic let's say you think probably will make it through colonize the universe in but then according to this Tuesday argument you should think of your own birth rank as a random sample so your birth is your sequence in the position of all humans that have ever existed it turns out you're about a human number of 100 billion you know give or take that's talking roughly how many people have been born before you that's fascinating because I probably yeah we each have a number wait wait wait we would each have a number in this I mean obviously the exact number will depend on where you started counting like witch ancestors start was human in hasta Carol is human but the does those are not really important - they're relatively few of those so yeah so you're roughly a hundred billion now if they're only gonna be 200 billion in total that's a perfectly unremarkable number you're somewhere in the middle right run-of-the-mill human completely unsurprising yes now if they're gonna be 200 trillion you would be remarkably early like you it's like what are the chances out of these 200 trillion human that you should be human number one hundred billion that seems it would have a much lower conditional probability and so analogously taha in the urn case you thought after finding this low numbered random sample you updated in favor of having few balls similarly in this case you should update in favor of the human species having a lower total number of members that is doom soon you said doom soon that's yeah well that would be the hypothesis in this case that it will end just a hundred billion I just like that term for the hypothec and of crucially relies on the Doomsday argument it's the idea that you should reason as if you were a random sample from the set of all humans that will ever have existed if you have that assumption then I think the rest kind of follows the question is why should you make that assumption in fact you know you're 100 billion so so where do you get this prior and then there is like a literature on that with different ways of supporting that or something and it that's just one example of a topic reasoning right there yeah that seems to be kind of convenient when you think about humanity when you when you think about us of even like existential threats and so on as it seems that quite naturally that you should assume that you're just an average case yeah that you're a kind of a typical or randomly sampled now in the case of the Doomsday argument it seems to lead to what intuitively we think is the wrong conclusion or at least many people have this reaction that there's got to be something fishy about this argument because from very very weak premises it gets this very striking implication that we have almost no chance of reaching size 200 trillion humans in the future and how can we possibly get there just by reflecting on when we were born it seems you would need sophisticated arguments about the impossibility of space colonization blah blah so what might be tempted to reject this key assumption I call it the self sampling assumption the idea that you should reason as if you were a random sample from all observers or in your some reference class however it turns out that in other domains it looks like we need something like this self sampling assumption to make sense of bona fide a scientific inferences in contemporary cosmology for example you have these multiverse theories and according to a lot of those all possible human observations are made so I mean if you have a sufficiently large universe you will have a lot of people observing all kinds of different things so if you have two competing theories say about some the value of some constant it could be true according to both of these theories that there will be some observers observing the value that corresponds to the other theory because there will be some observers that have elucidation so there is a local fluctuation or an statistically anomalous measurement these things will happen and if in us observers making us different observations that would be something that sort of by chance make these different ones and so what we would want to say is well many more observers a larger proportion of the observers will observe as it were the true value and a few will observe the wrong value if we think of ourselves as a random sample we should expect with a very improper bility to observe the true value on that well then allow us to conclude that the evidence we actually have is evidence for the theories we think are supported it kind of done is a way of making sense of these inferences that clearly seem correct that we can you know make various observations and infer what the temperature of the cosmic background is and and the the fine-structure constant and all of this but it seems that without rolling in some assumption similar to the self sampling assumption this inference just doesn't go through and there are the examples so so there are these scientific context so it looks like this kind of anthropic reasoning is needed and makes perfect sense and yet in the case of the dupes argument it has this weird consequence and people might think there is something wrong with it there so there's done this project that would consistent try to figure out now what are the legitimate ways of reasoning about these indexical facts when observer selection effects are in play in other words well being a theory of anthropic s-- and that different views of looking at that and it's a difficult methodological area but to tie it back to the simulation argument the the key assumption there this land principle of indifference it's much weaker than the self sampling assumption so if you think about in the case of the Doomsday argument it says you should reason as if you're a random sample from All Humans that will never live even though in fact you know that you are about number one hundred billion human and you're alive in the year 2020 whereas in the case of the simulation argument it says that well if you actually have no way of telling which one you are then you should assign this kind of uniform probability yeah yeah your role is the observer in the simulation argument is different it seems like who is the observer I mean I keep assigning the individual consciousness yeah I mean when I say you want a lot of observers in the simulation in the context of the simulation argument but they're all irrelevant the server's would be a the people in original histories and be the people in simulations so this would be the class of observers that we need I mean there also may be the simulators but we can set those aside for this so the question is given that class of observers a small set of original history observers and a large class of simulated observers which one should you think is you where are you amongst this well observers I'm maybe having a little bit trouble wrapping my head head around the intricacies of what it means to be an observer and this and this in the different instantiations of the anthropic reasoning cases that we mention right now it I mean it may be an easier way of putting it is just like are you simulated or you're not simulated you've given this assumption that these two groups of people exist yeah in the simulation case it seems pretty straightforward it's yeah so that's right they think the key point is the methodological assumption you need to make to get the simulation argument to where it wants to go is much weaker and less problematic then the methodological assumption you make to get the Doomsday argument to its conclusion maybe the dune star government is sound or unsound but you need to make a much stronger and more controversial assumption to make it go through in the case of the Doomsday argument a sorry simulation argument I guess one maybe way intuition pub to like support this bland principle of indifference is to consider a sequence of different cases where the fraction of people who are assimilated to non-simulated approaches one so in the limiting case where everybody assimilated I obviously can deduce with certainty that you are simulated right if everybody with your experience is assimilated and you know you're gotta be one of those you don't need the probability at all you just kind of logically conclude it right right so then as we move from a case where say 90% of everybody simulated 99% 99.9% it's impossible that the probability of sine should sort of approach one certainty as the fraction approaches the case where everybody is in a simulation yes exactly like you wouldn't like expect that to be a discrete well if there's one non-simulated person then it's 50/50 but if we move that and it's hundred percent like it should kind of all right there are other arguments as well one can use to support this blind principle of indifference but that might be enough to but in general when you start from time equals zero and go into the future the fraction assimilated if it's possible to create simulated worlds the fraction similar worlds will go to one well I mean it was a novelist kind of go all the way to one in in reality that would be some ratio although maybe a technical material civilization could run a lot of simulations using a small portion of its resources it probably wouldn't be able to run infinite demand yeah I mean if we take say the observed the physics in the observed universe if we assume that that's also the physics at the level of the simulators that would be limits to the amount of information processing that any one civilization could perform in its future trajectory right and there's like well first of all there's limited amount of matter you can get your hands off because with the positive cosmological constant the universe is accelerating there's like a finite sphere of stuff even if you've traveled with the speed of light that you could ever reach you have a finite amount of stuff and then if you think there is like a lower limit to the amount of loss you get when you perform an eraser of a computation or if you think for example just matter gradually over cosmological timescales decay you know maybe protons decay other things and they radiate out gravitational waves like there's all kinds of seemingly unavoidable losses that occur so eventually we'll have something like like a heat death of the universe or if it caused death or whatever but it's finite but of course we don't know which if if there's many ancestral civil simulations we don't know which level we are so there could be couldn't there be like an arbitrary number of simulation that spawned ours and those had more resources there's a physical universe to work with sorry I mean that that could be sort of okay so if simulations spawn other simulation tries it seems like each new spawn has fewer resources to work with yeah but we don't know at which love which step along the way we are at right any one observer doesn't know whether we're in level 42 or 100 or one or is that not matter for the resources I mean when it's true that they would that would be all certainty asked you could have stacked simulations yes and that couldn't be a certainty as to which level we are at as you remark tall so all the computations performed in a simulation within the simulation also have to be expended at the level of the simulation well today the computer in basement reality where all these simulations for the simulations with the simulations are taking place like that that computer ultimately it's it's its CPU or whatever it is like that has to power this whole tower right so if there is a finite compute power in basement reality that would impose a limit to how tall this tower can be and if if each level kind of imposes a large extra overhead you might think maybe the tower would not be very tall that most people would be lower down in the tower I love the term basement reality let me ask one of the popularizers you said there's many through this when you look at sort of the last few years of the simulation hypothesis just like you said it comes up every once in a while some new community discovers it and so on but I would say one of the biggest popular artists of this idea is Elon Musk do you have any kind of intuition about what Elon thinks about when you think about simulation why is this of such interest is it all the things we've talked about or is there some special kind of intuition about simulation that he has I mean you might have a better I think I mean why it's of interest I think it's it's like seems Fred Albus why if it to the extent that one think the argument is credible why it would be of interest it would if it's correct tell us something very important about the world you know one way or the other whichever of the three alternatives for a simulation that seems like arguably one of the most fundamental discoveries right now interestingly in the case of someone like Elon so there is like the standard arguments for why you might want to take the simulation hypothesis seriously the simulation argument right in the case that if you are actually Elon Musk let us say there's a kind of an additional reason in that what are the chances you would be Elon Musk right it seems like maybe that would be more interested in simulating the lives of very unusual and remarkable people so if you consider not just assimilations where all of human history or the whole of human civilization are simulated but also other kinds of simulations which only include some subset of people like in the industry in those simulations that only include a subset it might be more likely that that would include subsets of people with unusually interesting or consequential like your Elon Musk you got a wonder right more like yeah or if you're like if you're Donald Trump or if you are Bill Gates or you're like some particularly yeah like distinctive character you might think that that ad I mean if you just think of yourself into the shoes right it's got to be like an extra reason to think that's kind of so interesting so on a scale of like farmer in Peru to you a musk the more you get towards the almost the higher the probability you're dividing that would be some extra boost from that there's an extra boost so he also asked the question of what he would ask an AGI saying the question being what's outside the simulation do you think about the answer to this question if we are living a simulation what is outside the simulation so the programmer of the simulation yeah I mean I think it connects to the question of what's inside the simulation in that if you had views about the Craters of the simulation it might help you make predictions about what kind of simulation it is what what might what might happen what you know happens after the simulation if there is some after but also like the kind of setup so these these two questions would be quite closely intertwined but do you think you'll be very surprising to it like is the stuff inside the simulation is it possible for it to be fundamentally different than the stuff outside yeah like I got another way to put it can the creatures inside the simulation and be smart enough to even understand or have the cognitive capabilities or any kind of information processing capabilities enough to understand the mechanism that created them they might understand some aspects of it I mean it's a love all of its kind of there are levels of explanation like degrees to which you can understand so does your dog understand what it is to be human well it's got some idea like humans are these physical objects that move around and do things and I a normal human would have a deeper understanding of what it is to be a human and maybe some very experienced psychic psychologist or great novelist might understand a little bit more about what it is to be human and maybe super intelligence could see right through your soul so similarly I I do think that that we are quite limited in our ability to understand all of the relevant aspects of the larger context that we exist in but there might be hope first I think we understand some aspects of it but you know how much good is that if there's like one key aspect that changes the significance of all the other aspects so we understand maybe it's seven out of ten key insights that you need but but the answer actually like varies completely depending on what like number eight nine and ten insight is it's like whether you wanna suppose that the big tasks were to guess whether a certain number was odd or even like a ten digit number and if it's if it's even the best thing for you to do in life is to go north and if it's odd the best thing for you to go south now we are in a situation where maybe through our science and philosophy we figured out what the first seven digits are so we have a lot of information right most of it we figured out but we are clueless about what the last three digits are so we are still completely clueless about whether the number is odd or even and therefore whether we should go nor go south I feel that's that's an analogy but I feel we're somewhat in that predicament we know a lot about the universe we've come maybe more than half of the way there to kind of fully understanding it but the parts were missing or plausibly ones that could completely change the overall upshot of the thing and including change our overall view about what the scheme of priorities should be or which strategic direction would make sense to pursue it yeah I think your analogy of us being the dog trying to understand human beings as a as an entertaining one and probably correct the closer the understanding tends from the dog's viewpoint to us human psychologist viewpoint the steps along the way there will have completely transformative ideas of what it means to be human so the dog has a very shallow understanding it's interesting to think that and analogize that a dog's understanding of a human being is the same as our current understanding of the fundamental laws of physics in the universe man okay we spent an hour 40 minutes talking about the simulation I like it let's talk about super intelligence at least for a little bit and let's start at the basics what tu is intelligence yeah I didn't not to get too stuck with the definitional question I mean I the common sense understanding like the ability to solve complex problems to learn from experience to plan to reason some combination of things like that it's got this mixed up into that or no it's consciousness mixed up into that as well I don't think I think it could be fairly intelligent at least without being conscious probably and so then what is super intelligence so yeah that would be like something that was much more had much more general cognitive capacity than we humans have so if we talk about general super intelligence it would be much faster learner be able to recent much better MIT plans that are more effective at achieving its goals say in a wide of complex challenging environments in terms of as we turn our eye to the idea of sort of existential threats from super intelligence do you think super intelligence has to exist in the physical world or can it be digital only sort of we think of our general intelligence as us humans as an intelligence that's associated with the body that's able to interact with the world that's able to affect the world directly with physically I mean digital always perfectly fine I think I mean you you could you it's physical in the sense that obviously the computers and the memories are physical but its capability to affect the world sort of could be very strong even if it has a limited set of actuators if it can types text on the screen or something like that that would be I think ample so in terms of the concerns of existential threat of AI how can any AI system that's in the digital world have existential risk sort of what what are the attack vectors for a digital system well I mean I guess maybe to take one step back so I should emphasize that I also think there's this huge positive potential from machine intelligence including super intelligence and I want to stress that because like some of my write writing has focused on what can go wrong and when I wrote the book super intelligence at that point I felt that was a kind of neglect of what would happen if AI succeeds and in particular a need to get a more granular understanding of where the pitfalls are so we can avoid them I think that since since the book came out in 2014 there has been a much wider recognition of that and a number of research groups are not actually working on developing say AI alignments techniques and so on and so forth so that's I'd I'd like yeah I think now it's important to make sure we bring back onto the table the upside as well and there's a little bit of a neglect now on the upside which is I mean if you look at talking to a friend if you look at the amount of information there's available or people talking and people being excited about the positive possibilities of general intelligence that's not it's far outnumbered by the negative possibilities in in terms of our public discourse possibly yeah it's hard to measure so but what are you kneeling on that's a little bit what are some to you possible big positive impacts of general intelligence super intense me super excite end to also want to distinguish these two different contexts of thinking about AI and high impacts they're kind of near term and long term if you want both of which I think are legitimate things to think about and people should you know discuss both of them but but they are different and they often get mixed up and then then I get you get confusion like I think you get simultaneously I've maybe been overhyping of the near term and and under hyping of the long term and so I think as long as we keep them apart we can have like two good conversations but or we can mix them together and have one bad conversation can you clarify just oh the two things we were talking about the near term and long term yeah and what are the distinction well it's a blurry distinction but say the things I wrote about in this book super intelligence long term things people are worrying about today with I don't know algorithmic discrimination or even things self-driving cars and drones and stuff more near term and then then of course you could you button some medium term where that kind of overlap and they want evolves into the other but I don't write I think both yeah the dishes look kind of somewhat different depending on which of these contexts so I think I think it'd be nice if we can talk about the long term mm-hm and think about a positive impact or a better world because of the existence of the long term super intelligent now do you have the use of such a war yeah I mean it I guess it's a little harder chicklet because it seems obvious that the world has a lot of problems as it currently stands and it's hard to think of any one of those which it wouldn't be useful to have like a friendly aligned super intelligence working on so from health you know to the economic system to be able to sort of improve the investment and trade and foreign policy decisions all that kind of stuff all that kind of stuff and a lot more I mean what's the killer app well I don't think there is one I think AI I especially artificial general intelligence is really the ultimate general purpose technology so it's not that there is this one problem this one area where it will have a big impact but if and when it succeeds it will really apply across the board in all fields where human creativity and intelligence and problem-solving is useful which is pretty much all fields right there the thing that it would do is give us a lot more control over nature it wouldn't automatically solve the problems that arise from conflict between humans fundamentally political problems some subset of those might go away if you just had more resources and cooler tech but some subset would require coordination that is not automatically achieved just by having more technical capability but but anything that's not of that sort I think you just get like an enormous boost with this kind of cognitive technology what once it goes all the way not again that doesn't mean I'm like thinking or people don't recognize what's possible with current technology and like sometimes things get over height but I mean those are perfectly consistent views to hold the ultimate potential being enormous and then it's a very different question of how far are we from that or what can we do with near-term technology so what's your intuition about the idea of intelligence explosion so there's this you know when you start to think about that leap from the near term to the long term the natural inclination like for me sort of building machine learning systems today it seems like it's a lot of work to get the general intelligence but there's some intuition of exponential growth of exponential improvement of intelligence explosion can you maybe try to elucidate to try to talk about what's your intuition about the possibility of an intelligence explosion they won't be this gradual slow process there might be a phase shift yeah I think it's we don't know how explosive it will be I think for what it's worth I've seems fairly likely to me that at some point I will be some intelligence explosion like some period of time where progress in AI becomes extremely rapid roughly roughly in the area where you might say it's kind of human equivalent in coral cognitive faculties that the concept of human equivalent like this starts to break down when you look too closely at it but and just how explosive does something have to be for it to be called an intelligence expulsion like does it have to be like overnight literally or a few years or so but but overall I guess in on if you had if you plotted the opinions of different people in the world I I guess I would be somewhat more probability towards the intelligence expulsion scenario than probably the average you know AI researcher I guess so and then the other part of the intelligence explosion or just forget explosion just progress is once you achieve that gray area of human level intelligence is it obvious to you that we should be able to proceed beyond it to get the super intelligence yeah that seems I mean as much as any of these things can be obvious given we've never had one people have different views smart people of different views is like that it's like some some some degree of uncertainty that always remains for any big futuristic philosophical grand John that just we realize humans are fallible especially about these things but it does him as far as I'm judging things based on my own impressions that it seems very unlikely that that would be a ceiling at or near human cognitive capacity but and this is a I don't know this is a special moment and it says both terrifying and exciting to create a system that's beyond our intelligence so maybe you can step back and and say like how does that possibly make you feel that we can create something it feels like there's a line beyond which it steps you'll be able to outsmart you and therefore it feels like a step where we lose control well I don't think that a lot of follows that is you could imagine and in fact this is what a number of people are working towards making sure that we could ultimately the project higher levels of problem-solving ability while still making sure that they are aligned like they're in the service of human values I mean so so it's losing control I think is not enough even that would happen now I asked how it makes me feel I I mean to some extent I've lived with this for so long since as this as long as I can remember being being an adult or even a teenager it seemed to me obvious that at some point I I will succeed and so I actually misspoke I didn't mean control I meant because the control problem is an interesting thing and I think we the hope is at least we should be able to maintain control over systems that are smarter than us but they're they we do lose our specialness it's sort of we'll lose our place as the smartest coolest thing on earth and there's an ego involved that that humans are very good at dealing with I mean I I value my intelligence human being it seems like a big transformative step to realize you there's something out there that's more intelligent I mean you don't see that today I think yes a lot I think it really small I mean I think there already a lot of things out there that are I mean certainly if you think the universe is big there's going to be other civilizations that already have super intelligences or that just naturally have brains the size of beach balls and they're like completely leaving us in the dust and we haven't our face to face we have some face to face but I mean that's not my question what what would happen in in a kind of posthuman world like how much day-to-day would these super intelligences be involved in the lives of ordinary men I you could imagine some scenario where it would be more like a background thing that would help protect against some things but you wouldn't like that there wouldn't be this intrusive kind of like making you feel bad by like making clever jokes on your ex but like there's all sorts of things that maybe in the human context would feel awkward about that you don't want to be the dumbest kid in your class everybody picks it like a lot of those things maybe you need to abstract away from if you're thinking about this context where we have infrastructure that is in some sense beyond any or all humans I mean it's a little bit like say the scientific community as a whole if you think of that as in a mind it's a little bit of metaphor but I mean obviously it's going to be like way more capacious than any individual so in some sense there is this mind like thing already out there that's that just vastly more intolerant and than a new individual is and we think okay that's you just accept that as a fact that's the basic fabric of our existence intelligent yeah you get used to a lot of I mean there's already Google and Twitter and Facebook these sister recommender systems that are the basic fabric of our and I could see them becoming I mean do you think of the collective intelligence of these systems as already perhaps reaching super intelligence level well means I hear it comes to this the concept of intelligence and the scale and what human level means the the kind of vagueness and indeterminacy of those concepts starts to dominate how he would answer that question so the like say the Google search engine has a very high capacity of a certain kind like retrieve it remember remembering and retrieving information particularly like text or images that are you have a kind of string a word string key like obviously superhuman at that but a vast set of other things it can't even do at all not just not do well but so so you have these current AI systems that are superhuman in some limited domain and then like radically subhuman in all other domains so it's same way that chess like are just a simple computer that can multiply really large numbers right it's gonna have this like one spike of super intelligence and then a kind of a zero level of capability across all other cognitive fields and yeah I don't necessarily think the journalist I mean I'm not so attached with it but I could sort of it's a it's a gray area and it's a feeling but to me sort of alpha zero it's somehow much more intelligent much much more intelligent than deep blue hmm and just say which tomato you could say well these are both just board game that they're both just able to play board games who cares if they're good do better or not but there's something about the learning the self play learning yeah that makes it crosses over into that land of intelligence that doesn't necessarily need to be general in the same way Google is much closer to deep blue currently in terms of its search engine now then it is to sort of alpha zero and the moment it becomes the moment these recommender systems really become more like alpha zero but being able to learn a lot without the constraints of being heavily constrained by human interaction that seems like a special moment in time certainly learning ability seems to be an important facet of general intelligence that you can take some new domain that you haven't seen before and you weren't specifically pre-programmed for and then figure out what's going on there and eventually become really good at it so that's something alpha 0 it has much more often than deep blue had and in fact I mean systems like alpha zero can learn not just go but other in fact probably beat deep blue in chess and so forth right so that you say you do just general and it matches the intuition we feel it's more intelligent and it also has more of this general purpose learning ability and if we get systems that have been more general-purpose learning ability it might also trigger an even stronger intuition that they are actually starting to get smart so if you were to pick a future what would eating a utopia looks like with a GI systems sort of is it the neural link brain computer interface world where we're kind of really closely interlinked with AI systems is it possibly where a GI systems replace us completely while maintaining the the values and the the consciousness is it something like it's a completely invisible fabric like you mentioned a society where just AIDS and a lot of stuff that we do like carrying diseases and so on what does utopia if you get to pick yeah I mean it's a good question and a deep and difficult one I'm quite interested in it I don't have all the answers yet but or might never have but I think there are some different observations one could make one one is if this if the scenario actually did come to pass it would open up this vast space of possible modes of being on one and material and resource constraints would just be like expanded dramatically so you there would be a lot of a big pie let's right also it would enable us to to do things including to ourselves or not like that do you eat it would just open up this much larger design space options based and and we have ever had access to in in human history so I think two things follow from that what one is that we probably would need to make a fairly fundamental rethink of what ultimately we value like think things through more from first principles in the context would be so different from the familiar that we could have just take what we've always been doing and then like oh well we have this cleaning robot that like cleans the dishes in the sink and a few other small things and like I think we would have to go back to first principles and so from even from the individual level go back to the first principles of what what is the meaning of life what is happiness how it is fulfillment yeah and then also connected to this large space of of resources is that it would be possible and I think something we should aim for is to do well by the lights of more than one value system that is we wouldn't have to choose only one value criterion and say we're gonna do something that's course really high on the metric of say even ISM and then is like a zero by other criteria like kind of wire headed brains innovate and it's like a lot of pleasure that's good but then like no no Beauty you know achievement like no III or or or pic and I think to some significant not unlimited sense but the significant sense it would be possible to do very well by many criteria like maybe you could get like 98% of the best according to several criteria at the same time given this this the secret expansion of the option space and so so have competing value systems in criteria as a sort of firm just like our Democrat versus Republican there seems to be this always multiple parties that are useful for our progress in society even though might seem dysfunctional inside the moment but having the multiple value systems used to be beneficial for I guess a balance of power so that's yeah let's not not exactly what I have in mind that it's well although alchemy may be in an indirect way it is but that if you had the chance to do something that scored well in several different isometrics our first instinct should be to do that rather than immediately leap to the thing ah which one's of these value systems are we gonna screw over like our first in let's first try to do very well by all of them yeah then it might be that you can't get a hundred percent of all and you would have to then like have the hard conversation about which one will only get ninety-seven particular there's my cynicism that all of existence is always a trade-off but you say that maybe it's not such a bad trade office first he's right well this would be a distinctive context in which at least some of the constraints would be removed probably stupid trade-offs in the end it's just that we should first make sure we at least take advantage of this abundance so in terms of thinking about this like yeah what one should think I think in this kind of frame of mind of generosity and a inclusiveness to different value systems and and see how far one can get there first and I think one could do something that that would be very good according to many different criteria we kind of talked about AGI fundamentally transforming the the value system of our existence the mean the meaning of life but today what do you think is the meaning of life what are you the serious or perhaps the biggest question what's the meaning of life what's the meaning of existence what makes what gives your life fulfillment purpose happiness meaning yeah I think these are like I guess a bunch of different but related questions in there that one can ask happiness meaning yeah I mean it like he's pretty bad and somebody getting a lot of happiness for something that they didn't think was meaningful like mindless like watching reruns of some television series avoiding junk food like maybe some people that gives pleasure but they wouldn't think it had a lot of meaning whereas conversely something that might be quite loaded with meaning might not be very fun always like some difficult achievement that really helps a lot of people maybe requires self-sacrifice and hard work and so so these things can I think come apart which is something to bear in mind also when if you're thinking about these utopia questions that you might actually start to do some constructive thinking about that you might have to isolate and distinguish these different kinds of things that might be valuable in different ways make sure you can sort of clearly perceive each one of them and then you can think about how you can combine them and just as you said hopefully come up with a way to maximize all of them together yeah maximize or or get like a very high score on on a wide range of them even if not literally all you can always come up with values that are exactly opposed to one another right but I think for many values they're kind of a post with m'p lace them in in a certain dimensionality of your face like there are shapes that are kind of you can't untangle like in a given dimensionality but if you start adding dimensions then it might in many cases just be that they are easy to pull apart and you could so we'll see how much space there is for that but I think that there could be a lot in this context of radical abundance if ever we get to that I don't think there's a better way to end it Nick you've influenced the huge number of people too work on what could very well be the most important problems of our time so it's a huge honor and thank you so much for talking for coming by likes that's fun thank you thanks for listening to this conversation with Nick Bostrom and thank you to a presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast if you enjoy this podcast subscribe on youtube review it with five stars a NAPA podcast supporter on patreon or simply connect with me on Twitter and lex friedman and now let me leave you with some words from nick bostrom our existential risks cannot be one of trial-and-error there's no opportunity to learn from errors the reactive approach see what happens limit damages and learn from experience is unworkable rather we must take a proactive approach this requires foresight to anticipate new types of threats and a willingness to take decisive preventive action and to bear the costs moral and economic of such actions thank you for listening and hope to see you next time you |
Simon Sinek: Leadership, Hard Work, Optimism and the Infinite Game | Lex Fridman Podcast #82 | the following is a conversation with simon Sinek author of several books including start with why leaders eat last and his latest the infinite game he's one of the best communicators of what it takes to be a good leader to inspire and to build businesses that solve big difficult challenges this is the artificial intelligence podcast if you enjoy it subscribe I need to review it with five stars an apple podcast supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma n as usual I'll do 1 or 2 minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience quick summary of the ads to sponsors cash app and masterclass please consider supporting the podcast by downloading cash app and using code lex podcast and signing up to master class and master class comm slash 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abundance of choice pick three courses you want to complete watch each all the way through from start to finish it's not that long but it's an experience that will stick with you for a long time I promise it's easily worth the money you can watch in basically any device once again sign up in master class comm / Lex to get a discount and to support this podcast and now here's my conversation with simon Sinek in the infinite game your most recent book you describe the finite game in the infinite game so from my perspective of artificial intelligence and game theory in general I'm a huge fan of finite games from the broad philosophical sense is something that in the robotics artificial intelligence space we know how to deal with and then you describe the infinite game which has no exact static rules has no well-defined static objective as the players are known unknown they change there's a dynamic element so this is something that applies to business politics life itself so can you try to articulate the objective function here of the infinite game or in the in the cliche broad philosophical sense what is the meaning of life go for the start with a soft ball you know easy question first so James Carr was the philosopher who originally articulated this concept of finite and infinite games and when I learned about it it really challenged my view of how the world works right because I think we all think about winning and being the best and being number one but if you think about it only in a finite game can that exist a game that has fixed rules agreed upon objectives and known players like football or baseball there's always a beginning middle and end and if there's a winner that has to be a loser infinite games as cars describes them as you said have known and unknown players which means anyone can join it has a changeable rules which means you can play however you want and the objective is to perpetuate the game to stay in the game as long as possible in other words there's no such thing as being number one or winning in a game that has no finish line and what I learned is that when we try to win in a game that has no finish line we try and be number we try to be the best in a game that has no agreed-upon objectives or agreed-upon metrics or timeframes there's a few consistent and predictable outcomes the decline of trust the decline the decline of cooperation the decline of innovation and I find this fascinating because so many of the ways that we run most organizations is with a finite mindset you're trying to reduce the beautiful complex thing that is life or what politics or business into something very narrow and in that process the reductionist process you lose something fundamental that makes the whole thing work in the long term so returning not going to let you off the hook easy what is the meaning of life so what is the objective function that is worthwhile to pursue well if you think about our tombstones right they have the date we were born in the date we died but really it's what we do with the gap in between there's a poem called the - you know it's the - that matters it's what we do between the time we're going and the time we die that gives our life meaning and if we live our lives with a finite mindset which means to accumulate more power or money than anybody else to outdo everyone else to be number one to be the best we don't take any of us with us we don't take any of it with us we just die the people who get remembered the way we want to be remembered is how what kind of people we were right devoted mother loving father what kind of person we were to other people Jack Welch just died recently and the Washington Post when it when it wrote the headline for his for his obit it wrote he pleased Wall Street and distressed employees and that's his legacy of a finite player who was obsessed with winning yes who leaves behind a legacy of short-term gains for a few and distress for many that's his legacy and every single one of us gets the choice of the kind of legacy one I have do we want to be remembered for our contributions or a dish or our detractions to live with a finite mindset to live a career with a finite mindset to be number one be the best be the most famous lay the life like Jack Welch you know to live a life of service to to see those around us rise to contribute to our communities to our organizations to leave them in better shape than we found them that's that's the kind of legacy most of us would like to have so day to day when you think about what is the the fundamental goals dreams motivations of an infinite game of seeing your life your career is an infinite game what is that what does that look like I mean I guess I'm sort of trying to stick on this personal ego personal Drive the thing that the fire the reason we want to wake up in the morning and everything we can't go to bed because we're so excited yeah what is that so for me it's about having a just cause it's about a vision that's bigger than me that my work gets to contribute to something larger than myself you know that's what drives me every day I wake up every morning with a with a vision of a world that does not yet exist a world in which the vast majority of people wake up every single morning inspired feel safe at work and return home fulfilled at the end of the day is not the world we live in and so that we still have work to do is the thing that drives me you know I know what I know what my underlying values are you know I wake up to inspire people to do the things that inspire them and these are the things that these are the things that I these are my go to is my touch points that inspire me to keep working you know I think of a career like an iceberg you know if you have a vision for something you're the only one who can see the iceberg underneath the ocean but if you start working at it a little bit shows up and now a few other people can see what you imagined be like oh right yeah no I want to help build that as well and if you have a lot of success then you have a lot of iceberg and people can see this huge iceberg and they say you've accomplished so much but but what I see is all the work still yet to be done yet I still see the huge iceberg underneath the ocean and so the growth you talk about momentum so the incremental revealing of the iceberg is what drives you well it necessarily is incremental what drives me is that is the realization is every is realizing the iceberg bringing more of the iceberg from the unknown to the known bringing more of the vision from the imagination to reality and you have this fundamental vision of optimism you call yourself an optimist I mean in this world I have sort of I see myself a little bit as the main character from the 88 by Dostoevsky who is also kind of seen by society is a fool because he was optimistic so one can you maybe articulate where that sense of optimism comes from and maybe also try to articulate your vision of the future where people are inspired or optimism drives us yes it's easy to forget that when you look at social media and so on with the word toxicity a negativity can often get more likes that optimism has a sort of a beauty to it and I I do hope it's out there so what can you try to articulate a vision yeah so I mean for me optimism and being an optimist is is just seeing the silver lining in every cloud you know even in tragedy it brings people together and the question is can we see that can you see can you see the beauty that is in everything I don't think optimism is foolishness I don't think optimism is blindness though it probably involves some naivete the belief that things will get better the belief that that we tend towards the good even in times of struggle or bad you know you can't sustain war but you can sustain peace you know I think I think things that are are stable are more sustainable things that are optimistic are more sustainable than things that are you know chaotic so you see people as fundamentally good I mean some people may disagree that you can't sus you can sustain peace you can't sustain war I mean you don't have to you I think war is costly you know it involves life and money and peace does not involve those things it requires work I'm not saying it doesn't require work but it it doesn't drain resources I think the same way that war does you know the the people that would say that we will always have war and I just talked to the story and a Stalin is you know would say the conflict and the desire for power and conflict is essential to human nature is sucker but something in your words also perhaps it's the naive aspect that I also share is that you have an optimism that people are fundamentally I'm an idealist you know I and I think idealism is good I'm not I'm not a fool to believe that the ideals that I imagine can come true of course they'll never be world peace but shouldn't we die trying you know I think that's the whole point that's the point of vision vision should be idealistic and it should be all practical purposes impossible but that doesn't mean we shouldn't try and it's the it's the milestones that we we reach that take us closer to that ideal that make us feel that our life and our work have meaning and we're contributing to something bigger than ourselves you know we just because it's impossible doesn't mean we shouldn't try as I said we're still moving the ball down the field we're still making progress things are still getting better even if we never get to that that ideal state so I think idealism is a is a good thing you know in the word infinite game one of the beautiful and tragic aspects of life human life at least at least from the biological perspective is that it ends so sadly into some people yo fine fine it-it's it's tragic to some people or is it ends and I think some people believe that it that it ends on the day you die and some people think it continues on theirs and there's a lot of different ways to think what continues on the works like but let me drag it back to the personal church is uh how do you think about your own mortality are you afraid of death how do you think about your own death I definitely haven't accomplished everything I want to contribute to I like more time in on this earth to keep working towards that vision do you think about the fact that it ends for you yeah you cognizant of course I'm cognizant of it I mean not really all I I don't dwell on it I'm aware of it I know that my life is finite and I know that I have a certain amount of time left on this planet and I'd like to make that time be valuable you know some people would think that ideas kind of allow you to have a certain kind of immortality you know maybe to look around this kind of question so first to push back on you said that everyone was cognizant of the mortality there's a guy named Ernest Becker who would disagree that you basically say that most of human cognition is is created by us trying to create an illusion and try to hide the fact that from ourselves the fact that we're gonna die to try to think that we're it's all gonna go on forever but the fact that we know that it doesn't yes but this mix of denial I mean though I think the book is called denial of death is this constant and now that we're running away from a that's uh in fact some would argue that the inspiration the incredible ideas you've put out there your TED talk has been seen by millions and millions of people right it's just you trying to desperately fight the fact that you are biologically immortal and to the your creative genius comes from the fact that you're trying to create ideas that live on long past you well that's very nice of you I mean I I I would like my ideas to live on beyond me because I think that is a good test that those ideas have value have value in the lives of others I think that's a good test that that others would continue to talk about or share the ideas long after I'm gone I think is perhaps the greatest compliment one can get for one's own work it's very but I don't think it's my awareness of my mortality that drives me to do it it's my desire to contribute that drives me to do it this is the Optima it's the optimist vision it's it's the the pleasure and the fulfillment you get from inspiring others it's just as pure as that it's a let me ask listen i'm russian i'm trying to get your good and your good i'm gonna get get you into these dark areas i'm enjoying it is the ego tied up into it somehow so your name is extremely well known if your name wasn't attached to it do you think you would act differently i I mean for years I hated that my name was attached to it you know I had a rule for years that I wouldn't have my my my face on the cover of the front page of the website you know I had a fight with the publisher because I didn't want my name big on the book I wanted a tiny on the book cuz I kept telling them it's not about me it's about the ideas they wanted to put my name at the top of my book I refused none of my books had my names on the top because I won't I won't let them they would like very much to put my name on the top of the book but the idea has to be bigger than me I'm not bigger than the idea this beautifully put do you think ego but I also am aware that I've become I'm become recognized as the messenger and even though I still think the message is bigger than me I recognize that I have a responsibility as the messenger and whether I like it or not is irrelevant I accept I accept the responsibility I'm happy to do it I'm not sure how to phrase this but there's a large part of the culture right now that emphasizes all the things that nobody disagrees with which is health sleep diet relaxation meditation vacation are really important and there's no you know it's like you can't really argue against that in fact people less sleep that's just I'm joking yes well that's the thing I often I often speak to the fact that passion and love for you do what you're doing and the two words hard work especially in the engineering fields are more important than are more important to prioritize and sleep even though sleep is really important your mind should be obsessed with the hard work with the passion and so on and then I get some pushback of course from people what would he make sense of that is that just me the the crazy Russian engineer really pushing hard work probably we yeah I think that that's a short-term strategy I think if you sacrifice your health for the work at some point it catches up with you and at some point it's like it's like going going going and you get sick your body will shut down for you if you refuse to to take care of yourself you know it's you get sick it's what happens sometimes you know more severe illness than something that just slows you down so I think I think taking like getting sleep I mean there have been Studies on that you know executives for example who get a full night's sleep and stop at a reasonable hour actually accomplish more are more productive than people who work and burn the midnight oil because their brains are working better because they're well rested so you know working hard yes but what not work smart I think that giving our minds and our bodies rest makes us more efficient I think just driving driving driving driving is a short term so short term strategy so but to push back on that a little bit so the annoying thing is you're like a hundred percent right right but the thing is it's because because you're 100% right that weak part of your mind uses that fact to convince you like what so you know I I get all kinds of my mind comes up with all kinds of excuses to try to convince me that I shouldn't be doing what I'm doing to rationalize to rationalize and so what would I have a sense we you I think what you said about executives and leaders is absolutely right but there's the early days the early days of madness and passion for sure then I feel like emphasizing sleep as thinking about a sleep as giving yourself away out from the fact that those early days especially is can be suffering as long it's not sustainable you know right it's not sustainable sure if you're investing all that energy in something at the beginning to get it up and running then at some point you're gonna have to slow down or your body will slow you down for you like you you can choose your body can choose I mean so okay so you don't think from my perspective it feels like people have gotten a little bit soft but you're saying no I think I think that there seems evidence that that that working harder and later I've taken a back seat in it I think we have to be careful with the broad generalizations but but I think in if you go into the workplace there are people who would complain that that more people now than before you know look at their watches and say oops five o'clock go by night right now is that a problem with the people you're saying it's the people giving themselves excuses and people don't work hard or is that the organization's aren't giving them something to believe in something to be passionate about we can't manufacture passion you can't just tell someone be passionate you know it's not how it works passions and output not an input like if I believe in something and I want to contribute all that energy to do it we call that passion you know working hard for something we love is passion working hard for something we don't care about it's called stress but we're working hard either way so I think I think the organization's bears some accountability and our leaders bear some accountability which is if they're not offering a sense of purpose if they're not offering us a sense of cause if they're not telling us that our work is worth more than simply the money it makes then yeah I'm gonna come at five o'clock because I don't really care about making you money remember we live in a world right now where a lot of people rather a few people are getting rich on the hard work of others and so I think when when when people look up and say well why would I do that I'll just if you're not gonna look after me and then you're gonna lay me off at the end of the year because you missed your arbitrary projections you know you're gonna lay me off because you missed your arbitrary projections then why would I be offer my hard work and loyalty to you so I think I don't think we can immediately blame people for going soft I think we can blame leaders for their inability or failure to offer their people something bigger than them making a product or making money yeah that's so that's that's brilliant and start with why leaders elast your books you kind of you but you basically talk about what it what it takes to be a good leader and so some of the blame should go on the leader but how much of it is on finding your passion how much is it on the individual and allowing yourself to pursue that passion pushing yourself to your limits to to really take concrete steps along your path towards that passion yeah there's mutual responsibility there's mutual accountability I mean we we're responsible as individuals to find the organization's and find the leaders that inspire us and organizations are responsible for maintaining that flame and and giving people who believe but they believed you know a chance to contribute to linger on it have you by chance seen the movie whiplash yes again maybe I'm romanticizing suffering again it's the Russian in you it's the Russian yeah the Russians love suffering but so but people who haven't seen it's the movie whiplash as a drum instructor that pushes the drum musician to to his limits to to bring out the best in him and there's a toxic nature to it and they're suffering in it like you've you've worked a lot of great leaders a lot of great individuals so what is that toxic relationship as toxic as it appears in the movie or is that fundamental I've seen that relationship especially in the past with Olympic athletes with especially in the Flett extreme performers seem to do wonders it does wonders for me there's some of them are my best relationships now I'm not representative of everyone something for some of my best relationships form auntie and mentor have been toxic from an external perspective I what do you make of that movie would he make of that kind of relationship but it's not my favorite movie okay so you don't think that's a healthy you don't think that kind of relationship is a great example of a great short term strategy I mean short term I mean look being hard on someone is not the same as toxicity you know you know if you go to the Marine Corps your drill instructor will be very hard and on their Marines and then but still even on the last day of boot camp they'll take their hat off and they'll become a human but the the of all the drill instructors that you know the the the fur the the three or four main but drill instructors assigned to a group of recruits the one that they all want the respect of is the one that's the hardest on them that's that's true and you hear you know there's plenty of stories of people who want to earn the respect of a hard parent or a hard teacher but fundamental that parent that teacher that drill instructor has to believe in that person has to see potential it's not it's not a formula which is if I'm hard on people they'll do well which is there has to still be love it has to be done with absolute love and it has to be done with it has to be done responsibly I mean some people can take a little more pressure than others but it's not I don't I think it's irresponsible to think of it as a formula but that I'm just toxic at people they will they will do well it depends on their personalities first of all that works for some but not all and and second of all it it can't be done willy-nilly it has to still be done with with care and love and and sometimes you could get equal or better results without all of the toxicity so so one of the I guess toxicity on my part was a really bad word to use but if we talk about what makes a good leader and just look at an example in particular looking at Elon Musk he's known to put push people to the limits in a way that I think really challenges people in a way they've never been challenged before to do the impossible sure but it can really break people and and jobs was hard and and Amazon is hard and you know but the thing that's important is none of them lie about it you know the you know people ask me about Amazon all the time like Jeff Bezos never lied about it you know even the ones who like Amazon don't last more than a couple years before they burn out but when we're honest about the culture then it gives people the opportunity who like to work in that kind of culture to choose to work in that kind of culture as opposed to pretending and saying oh no this is all you know it's all lovey-lovey here and then you show up and it's it's the furthest thing from it so I mean if you know I think the the reputations are putting a lot of pressure on people to you know jobs jobs was not an easy man to work for he pushed people but everyone who worked there was given the space to create and do things that they would not have been able to do anywhere else and work at a level that they didn't work anywhere else and and jobs didn't have all the answers I mean he pushed his people to to come up with answers he he he he wasn't just looking for people to execute his ideas and and people did people accomplished more than they thought they were capable of which is wonderful how do you you're talking about the infinite game and not thinking about to short-term and yet you see some of the most brilliant people in the world being pushed by a llamas to accomplish some of the most incredible things when we're talking about autopilot one we're talking about some of the hardware engineering and they they do some of the best work of their life and then leave how do you balance that in terms of what it takes to be a good leader what it takes to accomplish great things in your life yeah so I think there's a difference between someone who can get a lot about it get a lot out of people in the short term and building an organization that can sustain beyond any individual there's a difference when you say beyond any individual you mean beyond beyond like if the leader dies correct like could could Tesla continue to do what it's doing without Elon Musk you know and could and you're perhaps implying which is a very interesting question that he cannot I don't know you know the argument you're making of this this this person who pushes everyone arguably is not a not a repeatable model right you know is Apple the same without Steve Jobs or is it slowly moving in a different direction or has he established something that could be resurrected with the right leader that was his dream I think it's to have or to build an organization that lives on beyond them at least I remember I think that's what a lot of leaders desire which is to create something that was bigger than them you know most businesses most entrepreneurial ventures could not pass the school bus test which is if the founder was hit by school bus would everyone continue the business without them or were they all just go find jobs and the vast majority of companies would fail that test you know in in in in especially in the entrepreneurial world that if you take the inspired visionary leader away the whole thing collapses so is that a business or is that just a force of personality and a lot of entrepreneurs you know face that reality which is they have to be in every meeting make every decision you know come up with every idea because if they don't who will and the question is well what have you done to build your bench is it it's not sometimes its ego the belief that only I can sometimes it's just things got did so well for so long that just forgot and sometimes it's a failure to build the training programs or or hire the right people that that could replace you who are maybe smarter and better and browbeating people is only one strategy I don't think it's necessarily the only strategy nor is it always the best strategy I think people people get to choose the cultures they want to work in so this is why I think I think companies should be honest about the kind of culture that they've created you know I heard a story about Apple where some somebody came in from a big company you know he'd accomplished a lot and has ego was very large and he was going on about how he did this and he did that and he did this and he did that and somebody from Apple said we don't care what you've done the question is what are you gonna do and that's that's you know for somebody who wants to be pushed that's the place you go because you choose to be pushed now we all want to be pushed to some degree you know anybody who wants to yeah you know accomplish anything in this world wants to be pushed to some degree whether it's through self pressure or external pressure or you know public pressure whatever it is but I think this this whole idea of one size fits all is a false narrative of how leadership works but what all leadership requires is creating an environment in which people can work at their natural best but you have you have a sense that it's possible to create a business where it lives on beyond you know fee if we look at now if we just look at this current moment I just recently talked to Jack Dorsey CEO of Twitter and he's under a lot of pressure now don't know if you're aware of the news that he's being pushed out as in potential as the CEO of Twitter because he's the CEO of already of an incredibly successful company plus he wants to go to Africa to live a few months in Africa to to connect with the world that's outside of the Silicon Valley and sort of there's this idea well can Twitter live without jack we'll find out but you have a general as a student of great leadership you have a general sense that it's possible yeah of course it's possible I mean what Bill Gates built with Microsoft may not have survived Steve Ballmer if the company weren't so rich but such a nerd Allah is putting it back on an on track again it's become a visionary company again it's attracting great talent again it went through a period where they couldn't get better the best talent and the best talent was leaving now people want to work for Microsoft again well that's not because of pressure Ballmer put more pressure on people mainly to hit numbers than anything else that didn't work yes right and so the question is what kind of pressure are we putting on people we're putting on pressure people to hit numbers or hit hit arbitrary deadlines or putting on pressure on people because we believe that they can do better work and the work that we're trying to do is to advance a vision that's bigger than all of us and if you're gonna put pressure on people it better be for the right reason like if you're gonna put pressure on me it better be for a worthwhile reason if it's just to hit a goal if it's just to hit some arbitrary date or some arbitrary number or make a stock price hit some target you can keep it I'm out of here yes but if you want to put pressure on me because we are are we are brothers and sisters-in-arms working to advance a cause bigger than ourselves that we believe whatever we're gonna build will significantly contribute to the greater good of society then go ahead I'll take the pressure and if you look at the apples and you look at the the the the the the Elon Musk's you know the jobs in the Elan musk they fundamentally believe that what they were doing would improve Society and and it was for the good of humankind and so the pressure in other words the the the what they were doing was more important more valuable than any individual in the team and so the pressure they put on people served a greater good and so we we we we looked to the left and we looked to the right to each other and said we're in this together we accept this we want this but if it's just pressure to hit a number or you know make the widget and move a little faster yeah and that's soul-sucking that's not passion that's stress and I think a lot of leaders confuse that making people work hard is not what makes them passionate giving them something to believe in and work on is what drives passion and when you have that then turning up the pressure only brings people together Dresden if I've done the right way done the right way speaking of pressure thank you I'm gonna give you 90 seconds to answer the last question which is if I told you that tomorrow was your last day to live and talk about mortality sunrise to sunset can you tell me can you take me through the day what do you think that day would involve you can't spend it with your family oh joy as well I would probably want to fill all of my senses with things that excite my senses I'd want to look at beautiful art I want to listen to beautiful music I'd want to taste incredible food I'd want to smell amazing tastes I'd want to touch you know something that you know something that's beautiful to touch I'd want all of my senses to just be consumed with with things that I find beautiful and you talked about this idea of we don't do it often these days they're just listening to music turning off all the devices and actually taking in and listening to music so as a addendum before it to talk about music what song would you be blasting in this last day you're alive let's zap 'ln what do we hope that I love no no there's probably going to be a Beatles song in there that'll definitely be some Beethoven in there the classics the clown guy yeah exactly thank you so much for talking to you thank you for making time for it under pressure we made a hat it was great thanks for listening to this conversation with simon Sinek and thank you to our sponsors cash app and master class please consider supporting the podcast by downloading cash app and using coal xpod cast and signing up to master class at master class comm slash flex if you enjoy this podcast subscribe on youtube review it with 5 stars an apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman and now let me leave you with some words from simon Sinek there are only two ways to influence human behavior you can manipulate it or you can inspire it thank you for listening I hope to see you next time you |
Anca Dragan: Human-Robot Interaction and Reward Engineering | Lex Fridman Podcast #81 | the following is a conversation with ANCA Jorgen a professor of Berkeley working on human robot interaction algorithms and looked beyond the robots function in isolation and generate robot behavior that accounts for interaction and coordination with human beings she also consults at way Moe the autonomous vehicle company but in this conversation she's 100% wearing her Berkeley hat she is one of the most brilliant and fun roboticists in the world to talk with I had a tough and crazy day leading up to this conversation so I was a bit tired even more so than usual but almost immediately as she walked in her energy passion and excitement for human robot interaction was contagious so I had a lot of fun and really enjoy this conversation this is the artificial intelligence podcast if you enjoy it subscribe I need to review it with five stars in the Apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri DM a.m. as usual I'll do one or two minutes of as now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it use code Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props to the cash app engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash out from the App Store or Google Play and use the code lex podcast you get $10 and cash app will also donate $10 the first an organization that is helping to advanced robotics and STEM education for young people around the world and now here's my conversation with Enka Droog on when did you first fall in love with robotics I think it was a very gradual process and it was somewhat accidental actually because I first started getting into programming when I was a kid and then into Mass and then into compute I disliked computer science was the thing I was gonna do and then in college I got into AI and then I applied to the robotics Institute at Carnegie Mellon and I was coming from this little school and Germany didn't know any nobody had heard of but I had spent an exchange semester at Carnegie Mellon so I had letters from Carnegie Mellon so that was the only play you know I might he said no Berkeley said no Stanford said no that was the only place I got into so I went there it's a robotics Institute and I thought that robotics is a really cool way to actually apply the stuff that I knew and loved like optimization so that's how I got into robotics I have a better story how I got into cars which is I you know I used to do mostly manipulation in my PhD but now I do kind of a bit of everything application wise including cars and I got into cars because I was here in Berkeley while I was a PhD student still for RSS 2014 better be organized in and he arranged for it was Google at a time to give us rides and self-driving cars and I was in a robot and it was just making decision after decision the right call and he was so amazing so it was a whole different experience right it's just I mean manipulation is so hard you can't do anything and there was was it the most magical robot you've ever met so like for me to mean Google self-driving car for the first time was like a transformative moment the guy had two moments like that that and spot mini I don't know if you met Bob many for Boston Dynamics I felt like I felt like I fell in love or something like it because I thought I know how a spot many works right it's just I mean there's nothing truly special it is it's great engineering work but the anthropomorphism that went on into my brain they came to life like a head little arm and like and looked at me he she looked at me you know I don't know there's a magical connection there and it made me realize wow robots can be so much more than things that manipulate objects they can be things that have a human connection Jeff was a self-driving car the moment like it was there a robot that truly sort of inspired you that was I remember that experience very viscerally riding in that car and being just wowed I I had the they gave us a sticker that said I wrote in a self-driving car and I had this cute little Firefly on yes and our logo that was like the smaller were like you had the really cute one yeah and and I put it on my laptop and I had that for years until I finally changed my laptop out and you know what about if we walk back you mention optimization at like what beautiful ideas inspired you in math computer science early on like why get into this field seems like a cold and boring field of math like what was exciting to you about it the thing is I liked math from very early on from fifth grade is when I got into the math Olympia and all of that are you competed yeah this it Romania is like our national sport do you speak I understand so I got into that fairly early and and it was little maybe to just theory with no kind of I didn't kind of how - didn't really have a goal and I didn't understanding which was cool I always liked learning and understanding but there was no can what am i applying this understanding to and so I think that's how I got into more heavily into computer science cuz it was it was kind of math meets something you can do tangibly in the world do you remember like the first program you've written okay the first program I've written with I kind of do it wasn't cute basic and fourth grade and it was drawing like a circle right yeah you know I don't know how to do that anymore right that's like the first thing that they taught me I was like you could take a special I wouldn't say was an extra isn't a sense an extracurricular so you could sign up for you know dance or music or programming and I did the programming thing and I was like what what I know why did you compete in program like these days Romania probably that's like a big thing there's a program of competition hmm what was that did that touch you at all did a little bit of the computer science Olympian but not not as seriously as I did the math Olympiad so is programming yeah it's basically here's a hard math problem solve it with a computer it was kind of yeah it's more like algorithms exactly it's not where's algorithmic so okay you kind of mentioned the Google self-driving car but outside of that Oh what's like who or what is your favorite robot real or fictional that I captivated your imagination throughout I mean I guess you kind of alluded to the Google self-driving the Firefly was a magical moment but is there something else it was I think there was the Lexus by the way this was back back then but yeah so good question I am okay my favorite fictional robot is Wally and I love how amazingly expressive it is some personal things a little bit about expressive motion kinds of things you were staying with you can do this and it's a head and it's a manipulator and what does it all mean I like to think about that stuff I love Pixar I love animation I love Wally has two big eyes I think or no yeah it has these um these cameras and they move so yeah that's it so you know it goes through and then it's super cute it's yeah I think you know the way it moves it's just so expressive the timing of that motion what is doing with its arms and what it's doing with these lenses is amazing and so I've I've really liked that from the start and then on top of that sometimes I shared this it's a personal story I share with people or when I teach about AI or whatnot my husband proposed to me by building a Wally and he actuated it so it's seven degrees of freedom including the lens thing and it kind of came in and it had the he made it have like a you know the belly box opening thing so it just did that and then it's filled out this box made out of Legos that open slowly and then BAM no yeah yeah it was it was quite quite it's at a bar it could be like the most impressive thing I've ever heard okay special connection to Wally long story short I like Wally because I like animation and I like robots and I like you know the fact that this was I we still have this robot to this day what how hard is that problem do you think of the expressivity of robots like the with the Boston Dynamics I never talked to those folks about this particular element I've talked to him a lot but it seems to be like almost an accidental side effect for them that they weren't I don't know if they're faking it they weren't trying to okay they do say that the the gripper on it was not intended to be a face I don't know if that's a honest statement but I think they're legitimate and so do we automatically just anthropomorphizing and youths up anything we could see about a robot it's like the the question is how hard is it to create a wall-e type robot that connects so deeply with us humans what do you think it's really hard right so it depends on what settings so if you want to do it in this very particular narrow setting where it does only one thing and it's expressive then you can get an animator you know can have fixer on call come in design some trajectory is there was a a key had a robot called Cosmo where they put in some of these animations that part is easy right the hard part is doing it not via these kind of handcrafted behaviors but doing it generally autonomously like I want robot say I don't work on just to clarify I don't I used to work a lot on this I don't work on that quite as much these days but but have the notion of having robots that you know when they pick something up and put it in a place they can do that with various forms of style or you can say well this robot is you know succeeding at this desk and is confident versus its hesitant versus you know maybe it's happy or it's you know disappointed about something some failure that it had or I think that when robots move they can communicate so much about internal states or perceived internal states that they have and I think that's really useful in an element that we'll want in the future because I was reading this article about how kids are kids are being rude to Alexa because they can be rude to it and it doesn't really get angry right it doesn't reply it in any way it just says the same thing so I think there's at least for that for the for the correct development of children to learn that these things and you kind of react differently I also think you know you walk in your home and you have a personal robot and if you're really pissed presumably robot just kind of behave slightly differently than one you're super happy and excited but it's really hard because it's I don't know I don't you know the way I would think about it and the way I've thought about it when it came to in expressing goals or intent its our intentions for robots it's well what's really happening is that instead of doing robotics where you have your state and you have your action space and you have your space the reward functions are trying to optimize now you kind of have to expand the notion of state to include this human internal state what is the person actually perceiving what do they think about the robots something's better and then you have to optimize in that system and so that means you have to understand how your motion your actions end up sort of influencing the observers kind of perception of you and it's very it's very hard to write math about that right so when you start to think about incorporating the human into the state model apologize for the philosophical question but how complicated are human beings do you think like can they be reduced to two kind of almost like an object that moves and maybe has some basic intents or is there something do we have to model things like mood and general aggressiveness and time I mean all these kinds of human qualities or like game theoretic qualities like what's your sense how complicated it is how hard is the problem of human robot interaction yeah should we talk about what the problem of human robot is yeah this is what I mean talk about how that yeah so and by the way I'm gonna talk about this very particular view of human robot interaction right which is not so much on the social side or on the side of how do you have a good conversation with the robot what should the robots appearance be throws out that if you make robots taller versus shorter this has an effect on how people act with them so I'm not I'm not talking about that but I'm talking about this very kind of narrow thing which is you take if you want to take a task that a robot can do in isolation in a lab out there in the world but in isolation and now you're asking what does it mean for the robot to be able to do this task for presumably what it's actually angola's which is to help some person that ends up changing the problem in two ways the first way to changes the problem is that the robot is no longer the single agent acting there you have humans who also take actions in that same space you know cars navigating around people robots around an office navigating around the people in that office if I send the robot to over there in the cafeteria to get me a coffee then there's from other people reaching for stuff in the same space and so now you have your robot and you're in charge of the actions that the robot is taking then you have these people who are also making decisions and taking actions in that same space and even if you know the robot knows what it's what it should do and all of that just coexisting with these people right kind of getting the since the gel well to mesh well together that sort of the problem number one and then there's problem number two which is goes back to this notion of I if I'm a programmer I can specify some objective for the robot to go off and optimize you can specify the task but if I put the robot in your home presumably you might have your own opinions about well okay I want my house clean but how do I want it clean then how should robot how close to me it should come and all of that and so I think those are the two differences that you have your acting around people and you what you should be optimizing for should satisfy the preferences of that end user not of your programmer who programmed you yeah and the Preferences thing is tricky so figuring out those preferences be able to interactively adjust to understand what the human is so really boys ought to be understand the humans in order to interact with them in order to please them right so why is this hard what yeah why is understanding humans hard so I think there's two tasks about understanding humans that in my mind are very very similar but not everyone agrees so there's the task of being able to just anticipate what people will do we all know that cards need to do this right we all know that well if I navigate around some people the robot has to get some notion of ok where where is this person gonna be so that's kind of the prediction side and then there's what what you are saying satisfying the preferences right so adapting to the person's preference is knowing what to optimize for which is more this inference side this what is what does this person want what is their intent what are their preferences and to me those kind of go together because I think that in if you at very least if you can understand if you look at human behavior and understand what it is that they want then that's sort of the key enabler to being able to anticipate what they'll do in the future because I think that you know we're not arbitrary we make these decisions that we make we act in the way we do because we're trying to achieve things and so I think that's the relationship between them now how complicated do these models need to be in order to be able to understand what people want so we've gotten a long way in robotics with something called inverse reinforcement learning which is the notion of someone acts demonstrates what how they want this thing done what isn't inverse reinforcement learning you said it right so it's it's the problem of take human behavior and infer reward function from this figure out what it is that that behavior is optimal with respect to and it's a great way to think about learning human preferences in the sense of you know you have a car and the person can drive it and then you can say well okay I can actually learn what the person is optimizing for I can learn their driving style or you can you can have people demonstrate how they want the house clean and then you can say okay this is this is I mean I'm getting the trade-offs that they're that they're making I'm getting the Preferences that they want out of this and so we've been successful in robotics somewhat with this and it's a it's based on a very simple model of human behavior which is remarkably simple which is that human behavior is optimal with respect to whatever it is that people want right so you make that assumption and now you can kind of inverse through that's why it's called inverse well really optimal control but but also inverse reinforcement learning so this is based on utility maximization in economics press back in the forties fine women mortgage time or like okay people are making choices by maximizing utility go and then in the late 50s we had loose and Shephard come in and say people are a little bit noisy and approximate in that process so they might choose something kind of stochastic lee with probability proportional to how much utility something has there's a bit of noise in there on this has translated into buttocks and something that we call Boltzmann rationality so it's a kind of an evolution of inversed reinforcement learning that accounts for four human noise and we've had some success with that too for these tasks where it turns out people act noisily enough that you can't just do vanilla the vanilla version ah you can account for noise and still infer what what they seem to want based on this man now we're hitting tasks word that's no not enough and what are examples where are you damn desk so imagine you're trying to control some robot that's that's fairly complicated trying to control the robot arm cuz maybe you're a patient with a motor impairment and you have this wheelchair mounted army in China to control it around or one test that we've looked at with Sergei is and our students did is a lunar lander so just I don't know if you know this Atari game it's called lunar lander it's it's really hard people really suck at landing the same mostly they just crash it left and right okay so this is the kind of toss for imagine you're trying to provide some assistance to a person operating such such a robot where you won the kind of the autonomy to kick can figure out what it is that you're trying to do and help you do it it's really hard to do that for say lunar lander because people are all over the place and so they seem much more noisy than really irrational that's an example of a task where these models are kind of failing us and it's not surprising because so we you know we talk about a 40s utility late fifties sort of noisy then the seventies came and behavioral economics started being a thing where people are like no no no no no people are not rational people are messy and emotional and irrational and have all sorts of heuristics that might be domain-specific and they're just they're just a messy mess so so what do you so what does my robot do to understand what you won and it's a very it's very that's why it's complicated it's you know for the most part we get away with pretty simple models until we don't and then the question is what do you do then um and it I had days when I wanted to you know pack my bags and go home and jobs because it's just it feels really daunting to make sense of human behavior enough that you can reliably understand what people want especially as you know robot capabilities will continue to get developed you'll get these systems that are more and more capable of all sorts of things and then you really want to make sure that you're telling them the right thing to do what is that thing well read it in human behavior so if I just sit here quietly and try to understand something about you but listening to you talk it would be harder than if I got to say something and ask you and interact and control okay can you can the robot help its understanding of the human by inflowing it influencing the behavior by actually acting yeah absolutely so one of the things that's been exciting to me lately is this notion that when you tried to that that that when you try to think of the robotics problem as okay I have a robot and it needs to optimize for whatever it is that a person wants it to optimize as opposed to maybe what a programmer said that problem we think of as a human robot collaboration problem in which both agents get to act in which the robot knows less than the human because the human actually has access to and you know at least implicitly to what it is that they want they can't write it down but they can they can talk about it they can give all sorts of signals they can demonstrate and and but the robot doesn't need to sit there and passively observe human behavior and try to make sense of it the robot can act too and so there's these information gathering actions that the robot can take to sort of solicit responses that are actually informative so for instance this is not for the purpose of assisting people but with kind of back to coordinating with people in cars and all of that one thing that dorsa did was so we were looking at cars being able to navigate around people and you might not know exactly the driving style of a particular individual that's next to you but you want to change lanes in front of them navigating around other humans inside cars yeah good good clarification question so you have an autonomous car and it's trying to navigate the road around human driven vehicles similar things ideas applied to pedestrians as well but let's just take human driven vehicles so now you're trying to change a lane well you could be trying to infer the driving style of this person next to you you'd like to know if they're in particular if they're sort of aggressive or defensive if they're gonna let you kind of go in or if they're gonna not and and it's very difficult to just you know when if you think that if you want to hedge your bets that maybe they're actually pretty aggressive I shouldn't ride this you kind of end up driving next to them and driving next to them right and then you you don't know because you're not actually getting the observations that you get away someone drives when they're next to you and they just need to go straight it's kind of the same because if they're aggressive or defensive and so you need to enable the robot the reason about how it might actually be able to gather information by changing the actions that it's taking and then the robot comes up with these cool things where it kind of not just towards you and then sees if you're gonna slow down or not then if you slow down it sort of updates its model of you and says oh okay you're more on the defensive side so now I can actually that's a fascinating dance as so that's so cool you could use your own actions to gather information that's uh that feels like I'm totally open exciting new world of robotics prop I mean how many people are even thinking about that kind of thing because it's it's actually leveraging human I mean most roboticist I've talked to a lot of you know colleagues and so on are kind of being honest kind of afraid of humans because they're messy and complicated right I understand um going back to what we're talking about earlier right now we're kind of in this dilemma okay there are tasks that we can just assume people are approximately rational for and we can figure out what they want we can figure out their goals in fear are their driving styles whatever cool they're these tasks that we can't so what do we do right do we pack our bags and go home and this one is just I've had a little bit of hope recently um and I'm kind of doubting myself scoff what do I know that you know 50 years of behavioral economics hasn't figured out but maybe it's not really in contradiction with what with the way that field is headed but basically one thing that we've been thinking about is instead of kind of giving up and saying people are too crazy and irrational for us to make sense of them maybe we can give them a bit the benefit of the doubt and maybe we can think of them as actually being relatively rational but just under different assumptions about the world about how the world works about you know they don't have we when we think about rationality and bliss the assumption is or they're rational under all the same assumptions and constraints as the robot right what if this is the state of the world that's what they know this is the transition function that's what they know this is the horizon that's what they know but maybe maybe the kind of this difference the way the reason they can seem a little messy and hectic especially to robots is that perhaps they just make different assumptions or have different beliefs so I mean that's that's another fascinating idea that this are kind of anecdotal desire to say that humans are irrational perhaps grounded behavioral economics is is that we just don't understand the constraints and their awards under which they operate and so our goal shouldn't be to throw our hands up and say they're irrational is to say let's try to understand what are the constraints what it is that there must be assuming that makes this behavior make sense good life lesson right good life that's true it's just outside a robot is good too that's communicating with humans that's just a good assume that you just don't have empathy right it's uh this is maybe there something you're missing and you know and it's you know it especially happens to robots because they're kind of dumb and they don't know things and oftentimes people are sort of super irrational and that they actually know a lot of things that robots don't sometimes like with the lunar lander the robot you know knows much more so it turns out that if you try to say look maybe people are operating this thing but assuming a much more simple fight physics model because they don't get the complexity of this kind of craft or the robot arm with seven degrees of freedom when these inertia and whatever so so maybe they have this intuitive physics model which is not you know this notion of intuitive physics is something that good you just studied actually in cognitive science was like Josh Tenenbaum Tom Griffiths what kind of stuff and and what we found is that you can actually try to figure out what what physics model kind of best explains human actions and then you can use that to sort of correct what it is that they're commanding the craft to do so they might you know be sending the craft somewhere but instead of executing that action you can sort of take a step back and say according to their intuitive if the world worked according their intuitive physics model where do they think that the craft is going war day where are they trying to send it to and then you can use the real physics right the universe of that to actually figure out what you should do so that you do that instead of where they were actually sending you in the real world and I kid you not it word peopled landed there the damn thing and you know in between the two flags and and and all that so it's not conclusive in any way but I'd say it's evidence that yeah maybe we're kind of under estimating humans in some ways when we're giving up and saying oh there's just crazy noisy then you then you try to explicitly try to model the kind of worldview that they that they have that's right that's right it's not to I mean there's things to be here for Konami's through that that that for instance I've touched upon the planning horizon so there's this idea that I just bounded rationality essentially and the idea that well maybe we work under computational constraints and I think kind of our view recently has been take the bellmen update nai and just break it in all sorts of ways by saying state no no no the person doesn't get to see the real state maybe they're estimating somehow transition function no no no no even the actual reward evaluation maybe they're still learning about what it is that they want like like you know when you watch netflix and you know you have all the things and then you have to pick something imagine that you know the D the AI system interpreted that choice as this is the thing you prefer to see and how are you gonna know you're still trying to figure out what you like what you don't like etc so I mean it's important to also account for that so it's not irrationality precise doing the right thing under the things that they know yeah that's brilliant you mentioned recommender systems what kind of and we're talking about human robot interaction kind of problem spaces are you thinking about so is it robots like wheeled robots of autonomous vehicles is it object manipulation like when you think about human robot interaction in your mind and maybe I'm tree could speak for the entire community of human robot interaction no but like what are the problems of interest here is and does it you know I kind of think of open domain dialogue as human robot interaction and that happens not in the physical space but it could just happen in in the virtual space so word who wears the boundaries of this field for you when you're thinking about the things we've been talking about yeah so I I tried to find kind of underlying I don't know what to even call them I get try to work on you know I might call what I do the kind of working on the foundations of algorithmic human robot interaction and trying to make contributions there and and it's important to me that whatever we do is actually somewhat domain agnostic when it comes to is it about you know autonomous cars or is it about quadrotors or is it a basis or the same underlying principles apply of course when you're trying to get a particular to work usually have to do some extra work to adapt that to that particular domain but these things that we were talking about around well you know how do you model humans it turns out that a lot of systems need to quote benefit from a better understanding of how human behavior relates to what people want and need to predict human behavior physical robots of all sorts and and beyond that and so I used to do manipulation I used to be you know picking up stuff and then I was picking up stuff with people around and now it's sort of very broad when it comes to the application level but in a sense very focused on ok how does the problem need to change how do the algorithms need to change when we're not doing a robot by itself you know emptying the dishwasher but we're stepping outside of that oh I thought that popped into my head just now on the game theoretic side I think you said this really interesting idea of using actions to gain more information but if we think a sort of game theory the humans that are interacting with you with you the robot identity of the robot yeah is they also have a world model of you mm-hmm and you can manipulate that and if we look at autonomous vehicles people have a certain viewpoint you said with the kids people see Alexa as a in a certain way is there some value in trying to also optimize how people see you as a robot is that it or is that a little too far and away from the specifics of what we can solve right now so both right so it's really interesting and we've seen a little bit of progress on this problem on pieces of this problem so you can again it kind of comes down to how complicated is the human model need to be but in one piece of work that we were looking at we just said ok there's these in there's this that are internal to the robot and their what their what the robot is about to do or maybe what objective what driving style the robot has or something like that and what we're gonna do is we're going to set up a system where part of the state is the person's belief over those parameters and now when the robot acts that the person gets new evidence about this robot internal state and so they're updating their mental model of the robot right so if they see a card that sort of cut someone off Tory god that's an aggressive card they no more right if they see sort of a robot head towards a particular door they're like are the robots trying to get to that door so this thing that we have to do with humans to try to understand their goals and intentions humans are inevitably gonna do that to robots and then that raises this interesting question that you asked which is can we do something about that this is gonna happen inevitably but we can sort of be more confusing or less confusing to people and it turns out you can optimize for being more informative and less confusing if you if you have an understanding of how your actions are being interpreted by the human how they're using these actions to update their belief and honesty all we did is just Bayes rule basically okay first has a belief they see an action they make some assumptions about how the robot generates its actions presumably is being rational because robots are rational see reasonable to assume that about them and then they incorporate that that new piece of evidence the Bayesian sense and their belief and they obtain a posterior and now the robot is trying to figure out what actions to take such that it steers the person's belief to put as much probability mass as possible on the correct on the correct parameters so that's kind of a mathematical formalization of that but my worry and I don't know if you want to go there with me but I about this quite a bit um the the kids talking to alexa disrespectfully worries me i worry in general about human nature I guess I grew up in Soviet Union World War two I'm gonna do two so with the Holocaust and everything I just worry about how we sometimes treat the other the the group that we call out or whatever it is through human history the group that's the other has been changed faces but it seems like the robot will be the other the other the the next the other and one thing is it feels to me that robots don't get no respect they get shoved around shoved around in is there one at the shallow level for a better experience it seems that robots need to talk back a little bit like into my intuition says I mean most companies from sort of Roomba autonomous vehicle companies might not be so happy with the idea that a robot has a little bit of an attitude but I feel it feels to me that that's necessary to create a compelling experience like we humans don't seem to respect anything that doesn't give us some attitude that or like Miss mix of mystery and attitude and anger and did that threatens us subtly maybe passive-aggressively I don't it seems like we humans yet need that dude what are you is there something you have thoughts on this one is one is it it's we respond to you know someone being assertive but we also respond to someone being vulnerable so I think robots but my first thought is that robots get shoved around and and bullied a lot because they're sort of you know tempting and they're so showing off or they appear to be showing off and so I think current going back to these things we were talking about in the beginning of making robots a little more a little more expressive a little bit more like oh that wasn't cool to do and now I'm bummed right I think that that can actually help because people can't help but anthropomorphize and respond to that even that though the emotion being communicate is not in any way a real thing and people know that it's not a real T because they know it's just a machine we're still interpret you know we can work with we watch there's this a famous psychology experiment with little triangles and kind of dots on a screen and a triangle is chasing the square and get angry at the darn triangle because why is it not leaving the square alone so that's yeah we can't helps that was the first thought the vulnerability is really interesting that I I think of like being pushing back being assertive as the only mechanism of getting of forming a connection of gaining respect but perhaps vulnerability perhaps there's other mechanisms that are less threatening yeah a little bit yes but then this this other thing that we can think about is it goes back to what you were saying that interaction is really game theoretic all right so the moment you're taking actions in the space humans are taking actions in that same space but you have your own objective which is you know you're a car you need to get your passenger to the destination and then the human nearby has their own objective which someone overlaps with you but not entirely you boat you're not interested in getting into an accident with each other but you have different destinations and you want to get home faster and they want to get home faster and that's a general of some game at that point and so that's I think that's what it's reading it as such is kind of a way we can step outside of this kind of mode that where you try to anticipate what people do and you don't realize you have any influence over it while still protecting yourself because your understanding that people also understand that they can influence you and it's just kind of back and forth is this negotiation which is really really talking about different equilibria of a game the very basic way to solve coordination is to just make predictions about what people will do and then stay out of their way and that's hard for the reasons we talked about which is how you have to understand people's intentions implicitly explicitly who knows but somehow you have to get enough of an understanding of that we all anticipate what happens next and so that's challenging but then it's further challenged by the fact that people change what they're do based on what you do because they don't they don't plan in isolation either right so when you see cars trying to merge on a highway and not succeeding one of the reasons this can be is because you you they they look at traffic that keeps coming they predict what these people are planning on doing which is to just keep going and then they stay out of the way because there's not there's no feasible plan right any planning would actually intersect with one of these other people so that's bad so you get stuck there so now kind of if if you start thinking about it as no no no actually these people change what they do depending on what the car does like if the car actually tries to kind of inch itself forward they might actually slow down and let the car in and down take an advantage of that well that you know that's kind of the next level we call this like this under actuated system idea where it's gonna under actresses and robotics but it's kind of it's you don't your influence these other degrees of freedom but you don't get to decide what somewhere it's seen you mention it this the the human element in this picture as under actuate it said you know you understand under actuator about robotics is you know that you can't fully control the system so you can't go in arbitrary directions in the configuration space under your control yeah it's a very simple way of under actuation where basically there's literally these degrees of freedom that you can control and these are affirmed that you can't but you influence them and I think that's the important part is that they don't do whatever regardless of what you do that what you do influence is what they end up doing I just also like the the poetry of calling human robot interaction and under actuated robotics problem and y'all so much sort of nudging it seems that there and I don't know I think about this a lot in the case of pedestrians I've collected hundreds of hours of videos I like to just watch pedestrians mmm-hmm and it seems that it's a funny hobby yeah it's weird because I learn a lot I learned a lot about myself about our human human behavior from watching pedestrians watching people in their environment basically crossing the street is you're putting your life on the line you know I don't know tens of millions of time in America every day is people are just like playing this weird game of chicken when they cross the street especially when there's some ambiguity about the right-of-way that has to do either with the rules of the road or with the general personality of the intersection based on the time of day and so on I mean and this nudging idea I don't you know it seems that people don't even nudge they just aggressively take make a decision somebody there's a runner that gave me this advice I sometimes run in in the street and you know not in this jannah sidewalk and you said that if you don't make eye contact with people when you're running they will all move out of your way it's called civil and attention civil inattention that's the thing oh wow I need to look this stuff but it works what is that my sense was if you communicate like confidence in your actions that you're unlikely to deviate from the action that you're following that's a really powerful signal to others that they need to plan around your actions as opposed to nudging where you're sort of hesitantly then the hesitation might communicate that you're now you're still in the dance in the game that they can influence with their own actions I've recently had conversation with Jim Keller who is a sort of this legendary chip or chip architect but he also let the autopilot in for a while and his intuition that driving is fundamentally still like a ballistics problem like you can ignore the human element that it's just not hitting things and you can kind of learn the right dynamics required to do the merger and all those kinds of things and then my sense is and I don't know if I can provide a definitive proof of this but my sense is I can order a magnitude or more more difficult when humans are involved like it's not simply a object a collision avoidance problem which where does your intuition of course nobody knows the right answer here but where does your intuition fall on the difficulty fundamental difficulty of the driving problem when humans are involved yeah good question I have many opinions on this imagine downtown San Francisco yeah yeah it's crazy busy everything okay now take all the humans out no pedestrians no human driven vehicles no cyclists no people and little skill electric scooters have been around nothing I think we're done I think driving at that point is done we're done I did nothing really that's nice tilt needs to be solved about that well let's pause there i I think I agree with you that guy and I think a lot of people here will agree with that but we need to sort of internalize that idea so what's the problem there because we're not quite yet be done with that because a lot of people kind of focus on the perception problem well a lot of people kind of map autonomous driving into how close are we to solving being able to detect all the you know the the drivable area the objects in the scene do you see that as a how hard is that problem so your intuition there behind your statement was we might have not solved the yet but were close to solving basically the perceptual problem I think the perception problem I mean and by the way a bunch of years ago this would not have been true and a lot of issues and the space can't we're coming from the fact that we don't really you know we don't know what's what's where but I think it's fairly safe to say that at this point although you could always improve on things and all of that you can drive through downtown San Francisco if there are no people around there's no really perception issue standing in your way there any perception is hard but yeah it's we've made a lot of progress on the perceptions on how to undermine the difficulty of the problem I think everything about robotics is really difficult of course you know the the planning problem the control problem all very difficult but I think what's what makes it really you know yeah it might be I mean you know and I picked downtown San Francisco I ate adapting to well now it's snowing now is no longer snowing now it's slippery in this way now so the dynamics part could good I could imagine being being still somewhat challenging but no the thing that I think worries us and our tuition is not good there is the perceptual problem at the edge cases sort of stout sauce and Francisco the nice thing it's not actually it may not be a good example because cuz you know what - what you're getting for all there's like because crazy construction zones and all yeah but the thing is you're travelling at slow speeds so it doesn't feel dangerous to me what feels dangerous is highway speeds when everything is to us humans super clear yeah I'm assuming light are here by the way I think it's kind of irresponsible to not use lighter that's just my personal opinion depending on your use case but I think like you know if you if you have the opportunity to use light are good your injury makes more sense now so you don't think vision I really just don't know enough to say well vision alone what you know what's like I there's a lot of how many cameras do you have there's all sorts of details I imagine their stuff is really hard to actually see how do you deal with would glare exactly what you're saying stuff that people would see that that that you don't I I think I have more my intuition comes from systems that can actually use lighter as well yeah until we know for sure it's make sense to be using lidar that's kind of the safety focus but then deserve the I also sympathize with the Elon Musk the statement of lidar as a crutch it's it's it's uh it's a fun notion to think that the things that work today is a crutch for the invention of the things that will work tomorrow right they get it's kind of true in the sense that if we you know that we want to stick to the conference and you see this in academic and settings all the time the things that work force you to not explore outside think outside the box I mean that happened all of that the problem is in safety critical systems you kind of want to stick with a thing Sutekh work so it's a it's an interesting and difficult trade-off in the in the in the case of real-world sort of safety critical robotic systems but so your intuition is just to clarify yes how I mean how hard is this human element forger like how hard is driving when this human element is involved are we years decades away from solving it but perhaps actually the years and the the thing I'm asking it doesn't matter what the timeline is but do you think we're how many breakthroughs away away from its in solving the human robot interaction problem to get this to get this right I think it in a sense it really depends I think that you know we were talking about how well look it's really hard because I'm just know people do is hard and on top of that playing the game is hard but I think we sort of have the fundamental some of the fundamental understanding for that and then you already see that these systems are being deployed in the real world you know even even driverless because I think now a few companies that don't have a driver in the car yeah small areas he's got a chance to I went to Phoenix and I and I shot a video with lame-o and you need to get that video out people didn't give me slack but this incredible engineering work being done there and it's one of those other seminal moments for me in my life to be able to it sounds silly but to be able to drive without a with a ride sorry without a driver in the seat I mean I was an incredible robotics I was driven by a robot and without being able to take over without being able to take the steering wheel that's a magical that's a magical moment so in that regard and those domains at least for like way mo they're there they're solving that human there's I mean there were they're going fattening it felt fast because you're like freaking out at first I was this is my first experience but it's going like the speed limit right 30 40 whatever it is and there's humans and it deals with them quite well I detects them and a good negotiation the intersections the left turns and all that so at least in those domains it's solving them the open question for me is like how quickly can we expand you know that's the you know outside of the weather conditions all those kinds of things how quickly can we expand to like cities like San Francisco yeah and I wouldn't say that it's just you know now it's just pure engineering and it's probably the I mean I know by the way I'm speaking kind of very generally here as hypothesizing but I I think that that there are successes and yet no one is everywhere out there so that seems to suggest that things can be expanded and can be scaled and we know how to do a lot of things but they're still probably you know new algorithms or modified algorithms that that you still need to put in there as you as you learn more and more about new challenges that get you get faced when how much is this problem do you think can be learned through in turn this is the success of machine learning and reinforcement learning how much of it can be learned from sort of data from scratch and how much which most of the success of autonomous vehicle systems have a lot of heuristics and rule based stuff on top like human expertise in in injected forced into the system to make it work hmm what's your what's your sense how much what's the will be the role of learning in the near term I think I I think on the one hand that learning is inevitable here right I think on the other hand and when people characterize the problem as it's a bunch of rules that some people wrote versus it's an end-to-end RL system or imitation learning then maybe there's kind of something missing from maybe that's that's more so for instance I think a very very useful tool in this sort of problem both in how to generate the cars behavior and robots in general and how to model human beings is actually planning search optimization right so robotics is a Disick Winchell decision-making problem and when when a robot can figure out on its own how to achieve its goal without hitting stuff and all that stuff you're right all the good stuff promotion planning 101 I think of that as very much AI not this is some rule or something there's nothing rule-based a bit on that right it's just you're you're searching through a space and figure now are you optimizing through a space and figure out what seems to be the right thing to do and I think it's hard to just do that because you need to learn models of the world and I think it's hard to just do the learning part where you don't you know you don't bother with any of that because then you're saying well I could do imitation but then when I go off distribution I'm really screwed or you can say I can do reinforcement learning which adds a lot of robustness but then you have to do either reinforce my learning in the real world which sounds a little challenging or that trial and error you know or you have to do reinforce millennion simulation and then that means well guess why do you need to model things at least to a to model people model the world enough that you you know whatever policy you get of that is like actually fine to roll out in the world and do some additional learning there so do you think simulation by the way just the the the quick tangent has a role in the human robot interaction space like is it useful seems like humans everything we've been talking about are difficult to model and simulate do you think simulation has a role in this space I do I think so because you can take models and train with them ahead of time for instance you can but the model sorry to interrupt the models are sort of human constructed or learned I think they have to be a combination because if you get some human data and then you say this is hog this is gonna be my model of per the person what are for simulation and training or for just deployment time and that's what I'm planning with as my model of how people work regardless if you take some data um and you don't assume anything else and you just say okay this is this is some data that I've collected let me fit a policy to help people work based on that what does to happen is you collected some data in some distribution and then now you're your robot it computes a best response to that right is sort what should I do if this is how people work and easily goes off of distribution where that model that you've built of the human completely sucks because out of distribution you have no idea right there's if you think of all the possible policies and then you take only the ones that are consistent with the human data that you've observed that still needs a lot of put a lot of things could happen outside of that distribution where you're confident then you know what's going on by the way this should you have gotten used to this terminology out of a distribution within the system machine learning terminology because it kind of assumes so distribution is referring to the the data that you States that you encounter they've noticed so far at training time yeah but it kind of also implies that there's a nice like statistical model that represents that data so odd a distribution feels like I don't know it it uh it raises to me falafel questions of how we humans reason out of distribution reasonable things that are completely we haven't seen before and so and what we're talking about here is how do we reason about what other people do in you know situations where we haven't seen them and somehow we just magically navigate that right you know I can anticipate what will happen in situations that are even novel in many ways and I have a pretty good intuition for I always get it right but you know and I might be a little uncertain and so on I think it's it's this that if you just rely on data you know you you just too many possibilities or too many policies out there that fit the data and by the way it's not just state it's clearly kind of history of stake has to really be able to anticipate what the person will do it kind of depends on what they've been doing so far cuz that's the information you need to kind of at least implicitly sort of say oh this is the kind of person that this is this probably what they're trying to do so anyway it's like you're trying to map history States so actually there's many mapping and history meaning like the last yes word the last few minutes or the last few months who knows who knows how much you need right in terms of your state is really like the positions of everything or whatnot and velocities who knows how much you need and then and then there's this there's so many mappings and so now you're talking about how do you regularize that space what priors do you impose or what's the inductive bias so you know there's all very related things to think about it on basically water assumptions that we should be making such that these models actually generalize outside of the data that we've seen and now you're talking about well I don't know what can you assume maybe you can assume that people like actually have intentions and that's what drives their actions maybe that's you know the right thing to do when you haven't seen data very nearby that tells you otherwise I don't know it's a very open question do you think so that one of the dreams of artificial intelligence was to solve common sense reasoning whatever the heck that means do you think something like common sense reasoning has to be solved in part to be able to solve this dance of human interaction the driving space or human robot interaction in general you have to be able to reason about these kinds of common-sense concepts of physics of you know all the things we've been talking about humans I don't even know how to express them with words but the bay the basics of human behavior a fear of death so like to me it's really important to encode in some kind of sense maybe not maybe it's implicit but it feels that it's important to explicitly encode the fear of death that people don't want to die because it seems silly but like that that the game of chicken that involves with the pedestrian crossing the street is playing with the idea of mortality like we really don't want to dies that's just like a negative reward I don't know I it just feels like all these human concepts have to be encoded did you share that sense or is just a lot simpler that I'm making out to be I think it might be simpler and I'm the first thing who likes to complicate is I think where we simpler than that um because it turns out for instance if you if you say model people in the very I don't call it traditional why I don't know if it's fair to look at it as a traditional way but but you know calling people as okay they're irrational somehow the utilitarian perspective well in that once you say that they you automatically capture that they have an incentive to keep on being you know Stuart um likes to stay you can't fetch the coffee if you're dead Russell that's a good night so when when you're sort of cheating agents as having these objectives these incentives humans or artificial you're kind of implicitly modeling that they'd like to stick around so that they can accomplish those goals um so I think I think in a sense maybe that's what draws me so much to the rationality framework even though it's so broken we've been able to it's been such a useful perspective and like we were talking about earlier what's the alternative I give up and go home or you know I just use complete black boxes but then I don't know what to assume out of distribution that come back to this um it's just it's been a very fruitful way to think about the problem and a very more positive way right these people aren't just crazy maybe they make more sense than we think but um but I think we also have to somehow be ready for it to be to be wrong be able to detect when these assumptions aren't holding be all of that stuff let me ask sort of an another small side of this that we've been talking about the pure autonomous driving problem but there's also relatively successful systems already deployed out there in what you may call like level two autonomy or semi autonomous vehicles whether that's test autopilot of work quite a bit with Cadillac super guru system which has a driver facing camera that detects your state there's a bunch of basically Lane centering systems what's your sense about this kind of way of dealing with the human robot interaction problem by having a really dumb robot and and relying on the human to help the robot out to keep them both alive is that is that from the research perspective how difficult is that problem and from a practical deployment perspective is that a fruitful way to approach this human robot interaction problem I think what we have to be careful about there is to not me it seems like some of these systems not all are making this underlying assumption that if so I'm a driver and I'm now really not driving but supervising and my job is to intervene right and so we have to be careful with this assumption that when I'm if I'm supervising I will be just as safe as when I'm driving like that I will you know if I if I wouldn't get into some kind of accident if I'm driving I will be able to avoid that axis and when I'm supervising to and I think I'm concerned about this assumption from a few perspectives so from a technical perspective it's that when you'll add something kind of take control and do its thing and it depends on what that thing is obviously and how much is taking on how what things are you trusting it to do but if you let it do its thing and take control it will go to what we might call off policy from the person's perspective States so stays to the person wouldn't actually find themselves in if they were the ones driving and the assumption that the person functions just as well there as they function in the states that they would normally encounter is a little questionable now another part is the kind of the human factor side of this which is that I don't know about you but I think I definitely feel like I'm experiencing things very differently when I'm actively engaged in the task versus when I'm a passive observer even if I try to stay engaged right it's very different than when I'm actually actively making decisions and you see this in life in general like you see students who are actively trying to come up with the answer learn this thing better than when they're passively told the answer I think that's some more related and I think people have studied this in human factors for airplanes and I think it's actually fairly established that these two are not the same so I and that point because I've gotten a huge amount of heat on this and I stand by it okay because I know the human factors community well and the work here is really strong and there's many decades of work show exactly what you're saying nevertheless I've been continuously surprised that much of the predictions of that work has been wrong and what I've seen so what we have to do I still agree with everything you said but we have to be a little bit more open-minded so the the I'll tell you there's a few surprising things that super villi kever ething you said to the word is actually exactly correct but it doesn't say what you didn't say is that these systems are you said you can't assume a bunch of things but we don't know if he says are fundamentally unsafe that's still unknown if there's there's a lot of interesting things like I'm surprised by the fact not the fact that what seems to be anecdotally from well from large data collection that we've done but also from just talking to a lot of people when in the supervisory role of semi autonomous systems that are sufficiently dumb at least which is that might be a key element is the systems not to be dumb the people are actually more energized as observer so they're actually better they're they're better at observing the situation so there might be cases in systems if you get the interaction right or you as a supervisor will do a better job with the system together I agree I think that is actually really possible I guess mainly I'm pointing out that if you do it naively you're implicitly assuming something that assumption might actually really be wrong but I do think that if you explicitly think about what the agent reducers that the person still stays engaged what the so that you essentially empower the person do more than they could that's the really the goal right is you still have a driver so you want to empower them to be so much better than they would be by themselves and that's different it's a very different mindset then I want them to basically not join but be ready to sort of take over so one of the interesting things we'll be talking about is the rewards that they seem to be fundamental to the way robots behaves so broadly speaking we've been talking about utility function saw but you comment on how do we approach the design of reward functions like how do we come up with good reward function [Laughter] this is you know I used to think I think about how well it's actually really hard to specify rewards for interaction because and it's really supposed to be what the people want and then you really you know we talked about how you have to customize what you want to do to the end user but I kind of realized that even if you take the interactive component away it's still really hard to design reward functions so what do I mean by that I mean if we assumed this survey I paradigm in which there's an agent and his job is to optimize some objectives some reward utility lost whatever cost if you write it out maybe it's a sad depending on situation or whatever it is if you write it out and then you deploy the agent you'd want to make sure that whatever you specified incentivizes the behavior you want from the agent in any situation that the agent will be faced with right so I do motion planning on my robot arm I specify some cost function like you know this is how far away should try to stay so much amount of stay away from people and it so much it matters to be able to be efficient and blah blah blah Ryan I need to make sure that whatever I specified those constraints or trade-offs or whatever they are that when the robot goes and solves that problem in every new situation that behavior is the behavior that I want to see and what I've been finding is that we have no idea how to do that but basically what I can do is I can sample I can think of some situations that I think are representative of what the robot will face and I can turn and add and tune some reward function until the optimal behavior is what I want on those situations which first of all is super frustrating because you know through the miracle of AI we've taken we don't have to specify rules for behavior anymore right the saying before the robot comes up with the right thing to do you plug in this situation it optimizes writing that situation it optimizes but you have to spend still a lot of time and actually defining what it is that that criterion should be make sure you didn't forget about 50 bazillion things that are important and how they all should be combining together to tell the robot what's good and when it's bad and how good and how bad and so I think this is this is a lesson that I don't know kind of I guess I close my eyes to it for a while cuz I've been you know tuning cost functions for 10 years now but it it's it really strikes me that yeah we've moved the tuning and like designing of features or whatever from the behavior side into the reward side and yes I agree that there's way less of it but it still seems really hard to anticipate any possible situation and make sure you specify a reward function that when optimized will work well in every possible situation so so you're kind of referring to unintended consequences or just in general any kind of suboptimal behavior that emerges outside of the things you said about out of distribution suboptimal behavior that is you know actually optimal I mean this I guess the idea of unintended consequence you know it's I've don't respect what you specified but it's not what you want and there's a difference between those but that's not fundamentally a robotics problem it is a human problem so like that's the thing yeah right so there is this thing called good hearts law which is you start a metric for an organization and the moment it becomes on target that people actually optimize for it's no longer a good metric well what's it called the good hearts law good hearts Allah so the moment you specify a metric it stops doing his job yeah it stops doing his job um so there's yeah there's such a thing as off or optimizing for sayings and and you know failing to to think ahead of time of all the possible things that might be important and so that's so that's interesting because you story I work a lot on every word learning from the perspective of customizing to the end user but it really seems like it's not just the interaction with the end user that's a problem of the human and the robot collaborating so that the robot can do what the human one's right that's kind of back and forward the robot probing the person being informative all of that stuff might be actually just as applicable to this kind of maybe new form of human robot interaction which is the interaction between the robot and the expert programmer a roboticist designer in charge of actually specifying what the hectic wants should do a task for this professor that's so cool like collaborating on the reward right collaborating on the reward design and so what what does it mean right what is it when we think about the problem not as someone specifies all of your job is to optimize and we start thinking about your in this interaction and this collaboration and the first thing that comes up is when the person specifies a reward it's not you know gossip was not like the letter of the law it's not the definition of the reward function you should be optimizing because they're doing their best but they're not some magic perfect Oracle and the sooner we start understanding that I think the sooner we'll get tomorrow but instead of robots that function better in different situations and then then you have kind of say okay well it's it's almost like the robots are over learning over you're putting too much weight on the reward specified by definition and maybe leaving a lot of other information on the table like what are other things we could do to actually communicate to the robot about what we want them to do besides attempting to specify a reward phone yeah you have this awesome and again it looks the poetry of leaked information you mentioned humans leaked information about what they want you know leaked reward signal for the for the robot so how do we detect these leaks yeah what are these leaks are they just I don't know that those words recently saw it read it I don't know where from you and that's gonna stick with you for a while for some reason because it's not explicitly expressed it kind of leaks in directly from our behavior we do yeah absolutely so I think maybe something surprising bits right so we were talking to before about our my robot arm it needs to move around people carry stuff put stuff away all of that and now imagine that you know the robot has some initial objective that the programmer gave it so they can do all these things functional it's capable of doing that and now I noticed that it's doing something and maybe it's coming too close to me alright and maybe I'm the designer maybe I'm the end-user and this robot is now in my home and I push it away so I push away cuz you know it's a it's a reaction to what the robot is currently doing and this is what we call physical human robot interaction and now there's a lot of there's a lot of interesting work on how do you respond to physical human robot interaction why should the robot do if such an event occurs and there's sort of different schools of thought it's well you know you can sort of treat it to control theoretical and say this is a disturbance that you must reject you can sort of treat it more a kind of heuristic Leon sorry I'm gonna go into some like gravity compensation mode so that means very maneuverable around I'm gonna go in the direction that the person push me and and to us part of realization has been that that is signal that communicates about the reward because if my robot was moving in an optimal way and I intervened that means that I disagree which is notion of optimality whatever he thinks is optimal is not actually optimal and sort of optimization problems aside that means that the cost versus reward function is is incorrect or at least is not what I wanted to be how difficult a signal to to inter to make actionable so like I it cuz this connects to our Thomas vehicle discussion what they're in the semi autonomous vehicle or autonomous V go on a safety driver disengages the car like they could have disengaged it for a million reasons yeah yeah so that's true again it comes back to Kenya can you structure a little bit of your assumptions about how human behavior relates to what they want and you you know you can't one thing that we've done is literally just treated this external torque that they applied as you know when you take that and you add it with what the torque the robot was already applying that overall action is probably relatively optimal respect to whatever it is that the person wants and then that gives you information about what it is that they want so you can learn that people want you to stay further away from them now you're right that there might be many things that explain just at one signal that you might need much more data than that for the person be able to shape your reward function over time you can also do this info gathering stuff that we were talking about now now we've done that in that context just to clarify but it's definitely somebody thought about where you can have the robot start acting in a way like if there's a bunch of different explanations right it moves in a way where it sees if you corrected in some other way or not and then kind of actually plans its motion so that it can disambiguate then collect information about what you want anyway so that's one way that's cut a sort of leaked information maybe even more subtle leaked information is if I just press the e stop right I just I'm doing it out of panic because the robot is about to do something bad there's again information there right okay the robot should definitely stop but it should also figure out that whatever was about to do was not good and in fact it was so not good then stopping and remaining stop for a while was better a better trajectory for it than whatever it is that it was about to do and that again is information about what are my preference is what do I want speaking of East ops what are your expert opinions on the Three Laws of Robotics um Isaac Asimov don't harm humans obey orders protect yourself I mean it's a it's a such a silly notion but I speak to so many people these days just regular folks just I don't know my my parents and so on about robotics and they kind of operate in that space of you know imagining our future with robots and thinking what are the ethical how do we get that dance right I know the three laws might be a silly notion but do you do you think about like what Universal reward functions that might be that we should enforce on the robots of the future or is that a little too far out and it doesn't or is the mechanism that you just described you shouldn't be three laws it should be constantly adjusting kind of thing I think it should constantly be adjusting I think that you know the issue with the laws is I don't even you know they're words and I have to write math right and have to translate them into math what does it mean to us harm me what right because we just talked about how you try to say what you want but you don't always get it right and you want these machines to do what you want not necessarily exactly what your literacy you want them you don't want them to take you literally you want to take what you're saying and interpret it in context and that's what we do with the specified rewards we don't take them literally anymore from the designer we not we as a community we as you know some members are like we and in some of our collaborators like Peter bol and Stuart Russell we sort of say okay the designer specified this thing but I'm gonna interpret it not as this is universal reward function that I shall always optimize always and forever but as this is good evidence about what the person wants and I should interpret that evidence in the context of these situations that it was specified for because ultimately that's what the designers thought about that's what they had in mind and really them specifying a reward function that works for me in all these situations is really kind of telling me that whatever behavior that incentivizes must be good behavior respect to the thing that I should actually be optimizing for and so now the robot kinda has uncertainty about what it is that it should be what its reward function is and then there's all these additional signals we've been finding that it can kind of continually learn from and adapt its understanding of what people want every time the person corrected maybe they demonstrate maybe they stopped hopefully not right one really really crazy one is the environment itself like our world you don't it's not you know you observe our world and and the state of it and it's not that you're seeing behavior and you're saying how people are making decisions that are rational bla bla bla it's but but but our world is something that we've been acting when according to our preferences so I have this example where like the robot walks into my home and my shoes are laid down on the floor kind of in a line right it took effort to do that even though the robot doesn't see me doing this you know actually aligning the shoes it should still be able to figure out that I want the shoes online because there's no way for them to have magically instantiated themselves in that way someone must have actually just a good time to do that so it must be important so the environment actually tells the varlets information at least information I mean the environment is the way it is because humans some are manipulated is so you have to kind of reverse engineer the narrative that happened to create the environments it is and that leaks the yeah yeah yeah mission yeah you have to be careful yeah right because because people don't have the bandwidth to do everything so just because you know my house is messy doesn't mean that I want it to be messy right but that just shouldn't decide you know I didn't put the effort into that I put the effort into something else so the robot should figure out well that's something else was more important but it doesn't mean that you know the house being messy is not so it's a little subtle but yeah we really think of it the state itself is kind of like a choice that people implicitly made on how they want their world what book or books technical fiction or philosophical had when you like look back your life had a big impact maybe it was a turning point was inspiring maybe we're talking about some silly book that nobody in their right mind would want to read or maybe it's a book that you would recommend to others to read or maybe those could be two different recommendations that of books that could be useful for people on their journey when I was in it's kind of a personal story when I was in 12th grade I got my hands on a PDF copy in Romania of Russell Norvig a I modern approach I didn't know anything about AI at that point I was you know I had watched the movie The Matrix and and so I started going through this thing and you know you were asking in the beginning what are what are you and just it's it you know it's math and it's algorithms what's interesting it was so captivating this notion that you could just have a goal and figure out your way through a kind of a messy complicated situation so what sequence of decisions you should make art autonomously to achieve that goal that was so cool I'm you know I'm biased but that's a cool book yeah you can convert you know the goal the goal of and tell it the process of intelligence and mechanize it I had the same experience I was really interested in psychiatry and trying to understand human behavior and then AI a modern approach is like wait you can just reduce it all yeah so that's and I think that's stuck with me cuz you know a lot of what I do a lot of what we do in my lab is write math about human behavior combine it with data and learning put it all together give it to robots to plan wit and you know hope that instead of writing rules for the robots writing heuristics designing behavior they can actually autonomously come up with the right thing to do around people that's kind of our you know that's our signature move it's we wrote some mass and then instead of kind of hand crafting this and that and that and the robots figuring stuff out and isn't that cool and I think that is the same enthusiasm that I got from there I figured out how to reach that goal in that graph isn't that cool so apologize for the romanticized questions but and the silly ones if a doctor gave you five years to live sort of emphasizing the finiteness of our existence what would you try to accomplish it's like my biggest nightmare by the way I really like living I really don't like dying of being told that I'm gonna die sorry Dylan got enough for a second do you I mean do you meditate or ponder on your mortality on our human the fact that this thing ends it seems to be a fundamental feature do you think of it as a feature or a bug - is it you you said you don't like the idea of dying but if I were to give you a choice of living forever like you're not allowed to die yeah now I'll say that I'm wandering forever but I watch this show it's very still it's called a good place and they reflect a lot on this and you know the the moral of story is that you have to make the afterlife be finite - because otherwise people just like wall-e so so I think the finance helps but but yeah it's just um you know I don't I don't I'm not a religious person I don't think that there's something after and so I think it just ends and you stop existing and I really like existing it's just it's such a great privilege to exist that that yeah it's just I think that's very part I still think that we we like existing so much because it ends mm-hmm and that's so sad like it's so sad to me every time I got find almost everything about this life beautiful like the silliest most mundane things are just beautiful and I think I'm cognizant of the fact that I find it beautiful because it ends like it and it's so I don't know I don't know how to feel about that I also feel like there's a lesson in there for robotics an AI that is not like the finite of things seems to be a fundamental nature of human existence I think some people sort of accuse me of just being Russian and melancholic and romantic or something but that seems to be a fundamental nature of our existence that should be incorporated in our reward functions but anyway if you were speaking of reward functions if you only had five years what would you try to accomplish this is the thing I I'm thinking about this question and have a pretty joyous moment because I don't know that i would change mine listen I'm what I'm I'm you know I'm trying to make some contributions to how we understand human AI interaction I don't think I would change that um maybe I'll check you know I take more trips to the Caribbean or something but I try to spend time so yeah I mean I try to to do the things that bring me joy and thinking about these things bring me joy is d'amérique Ando think you know don't do stuff that doesn't spark joy for the most part I do things that spark joy maybe I'll do like less service in the department or something but but no I mean I think I have amazing colleagues and amazing students and amazing family and friends and kind of spending time and some balance with all of them is what I do and I that's what I'm doing already so I don't know that I would really change anything so on the spirit of positiveness oh what small act of kindness if one pops to mind where you one's shown you will never forget mmm when I was in high school my friends my my classmates did some tutoring we were gearing up for our baccalaureate exam and we they did some tutoring on well someone math someone whatever I was comfortable enough with with some of those subjects but physics was something that I hadn't focused in a while and so they were all working with this one teacher and I started working with that teacher her name is Nicole McConnell and she she was the one who kind of opened up this whole world for me because she sort of told me that I should take the SATs and apply to go to college abroad and you know do better on my English and all of that and when it came to well financially I couldn't my parents couldn't really afford to do all these things she started tutoring me on physics for free and on top of that sitting down with me to kind of train me for SATs and all that jazz that she had experience with Wow and obviously that has taken you to be to here today also to one of the world's experts and robotics it's funny those little yeah dude use these small word for no reason really kindness just out of karma wanting to support someone yeah yeah so we talked a ton of our reward functions let me talk about the the most ridiculous big question what is the meaning of life what's the reward function under which we humans operate like what may be to your life may be broader to human life in general what do you think what gives life fulfillment purpose happiness meaning you can't even ask that question with a straight face that's how ridiculous I can't like him okay so you know you're gonna try to answer it anyway aren't you so I was in a planetarium once yes and you know they show you the thing and these do man is zoom out and this whole like you're a speck of dust kind of thing I think that was conceptualizing that we're kind of you know what our humans were just on this little planet whatever we don't matter much in the grand scheme of things and then my mind got really blown cuz this doctor they doctored this multi-verse this theory where they kind of zoomed out and were like this is our universe and then like there's a bazillion other ones and it stays pop in and out of existence so like our whole thing that's that we can't even fathom how big it is was like a blimp that went in and out and I thought I was like okay clearly what we should be doing is try to impact whatever local thing we can impact our communities leave a little bit behind they're our friends our family our local communities and just try to be there for other humans cuz I just everything beyond that seems ridiculous I mean are you like how do you make sense of these multiverses like are you inspired by the immensity of it do you you can it is there like is it amazing to you or is it almost paralyzing in this in the mystery of it it's frustrating I'm frustrated by my inability to comprehend it feels very frustrating it's look there's there's some stuff that you know we should time blah blah blah that we should really be understanding and I definitely don't understand it but you know the the amazing physicists of the world have a much better understanding than me Don and the grand scheme of things so it's very frustrating it's just it feels like our brain don't have some fundamental capacity yeah well yet or ever I don't know but well this one of the dreams of artificial intelligence is to create systems that will aid expand our cognitive capacity in order to understand the build the theory of everything when the physics and understand what the heck these multiverses are so I think there's no better way to end it than talking about the meaning of life and the fundamental nature of the universe and akka is a huge honor one of the my favorite conversations I've had I really really appreciate your time thank you for talking to thank you for coming come back again thanks for listening to this conversation with anchor dragon and thank you to our presenting sponsor cash app please consider supporting the podcast by downloading cash app and using code lex podcast if you enjoy this podcast subscribe on youtube review it with five stars on a podcast supported on patreon or simply connect with me on Twitter and lex friedman and now let me leave you with some words from Isaac Asimov your assumptions are your windows in the world scrub them off every once in a while or the light won't come in thank you for listening and hope to see you next time you |
Vitalik Buterin: Ethereum, Cryptocurrency, and the Future of Money | Lex Fridman Podcast #80 | the following is a conversation with vitalik buterin co-creator of and author of the white paper the launched ethereum and ether which is a cryptocurrency that is currently the second largest digital currency after bitcoin ethereum has a lot of interesting technical ideas that are defining the future of blockchain technology and vitalik is one of the most brilliant people innovating in the space today unlike satoshi nakamoto the unknown person or group that created bitcoin vitalik is very well known and at a young age it's thrust into the limelight as one of the main faces of the technology that may redefine the nature of money and all forms of digital transactions in the 21st century this is the artificial intelligence podcast if you enjoy it subscribe on youtube review it with five stars in apple podcast support on patreon or simply connect with me on twitter alex friedman spelled f-r-i-d-m-a-n as usual i'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation i hope that works for you and doesn't hurt the listening experience quick summary of the ads two sponsors masterclass and expressvpn please consider supporting the podcast by signing up to masterclass and masterclass.com lex and getting expressvpn at expressvpn.com lex pod this show is sponsored by masterclass sign up at masterclass.com lex to get a discount and to support this podcast when i first heard about masterclass i honestly thought it was too good to be true for 180 a year you get an all-access pass to watch courses from experts at the top of their field to list some of my favorites chris hadfield on space exploration neil degrasse tyson on scientific thinking and communication will write the creator of simcity and sims on game design i love that game jane goodall on conservation carlos santana one of my favorite guitarists on guitar gary 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make it look like your location is anywhere else in the world i might be in boston now but i can make it look like i'm in new york london paris or anywhere else this has a large number of obvious benefits for example certainly it allows you to access international versions of streaming websites like the japanese version of netflix or the uk version of hulu as you probably know i was born in the soviet union so sadly given my roots and appreciation of russian history and culture my website and the website for this podcast is blocked in russia so this is another example of where you can use expressvpn to access sites like the podcast that are not accessible in your country expressvpn works on any device you can imagine i use it on linux shout out to ubuntu windows android but it's available everywhere else too once again download it at expressvpn.com lex pod to get a discount and to support this podcast and now here's my conversation with vitalik buterin so before we talk about the fundamental ideas behind ethereum and cryptocurrency perhaps it'd be nice to uh to talk about the the origin story of bitcoin and the uh mystery of satoshi nakamoto you give a talk that started with sort of asking the question what did uh satoshi nakamoto actually invent maybe you could say who is satoshi nakamoto and what did he invent sure so satoshi nakamoto is the name by which we know the person who originally came up with bitcoin so the reason why i say the name by which we know is that this is a anonymous uh fellow who has uh shown himself to us only um over the internet uh just by first publishing the white paper uh for bitcoin and then releasing the original source code for bitcoin and then talking to the very early bitcoin community on bitcoin forums and and of interacting with them and helping the project along for a couple of years um and then at some point in late 2010 to early 2011 he disappeared uh so bitcoin is uh a fairly unique project and how it has this kind of mythical kind of quasi-god-like founder who just kind of popped in and did the thing and it disappeared and we've somehow just never heard from him again so in 2008 was so the white paper was the first do you know if the white paper was the first time the name would actually appear satoshi nakamoto believe so so how is it possible that the creator of such a impactful project remains anonymous that's a tough question and there's no similarity to it in history of technology as far as i'm aware yeah so one possibility is that it's hal finny um because uh hell finney was kind of also active in the bitcoin community and as um how finney um in those uh two beginning years and uh how who is how thin he may be he is one of the people in the end of early cypherpunk community he was a computer scientist just yeah computer scientists cryptographers people interested in uh like technology internet freedom like those kinds of topics was it correct that i read that he seemed to have been involved in either the earliest or the first transaction of bitcoin yes the first transaction of bitcoin was between sister oshie and alfini do you think he knew who satoshi was if he wasn't satoshi you probably know how is it possible to work so closely with people and nevertheless not know anything about their fundamental identity is this like a natural sort of characteristic of the internet like if we were to think about it because you and i just met now there's a there's a depth of knowledge that we we now have about each other that's like physical like my vision system is able to recognize you i can also verify your identity of uniqueness like yep like it's very hard to fake you being you yes so the internet the internet has a fundamentally different quality to it which is just fascinating yeah i know this is definitely interesting because i definitely just know a lot of people just by their internet handles and like to me when i think of them like i see their internet handles and one of them has enough profile pictures this kind of face that's kind of not quite human with a bunch of kind of psychedelic colors in it and when i visualize him i could just visualize that that's not an actual face yeah you are the creator of the second well he's currently the second most popular cryptocurrency uh ethereum so on this topic if we just stick on satoshi nakamoto for for a little bit longer you may be the most qualified person to speak to the psychology of this anonymity that we're talking about like your identity is known like i've just verified it but uh from your perspective what are the benefits in uh creating a cryptocurrency and then remaining anonymous like if it can psychoanalyze satoshi nakamoto is there something interesting there or is it just a peculiar quirk of him it definitely helps create this uh kind of image of this kind of neutral thing that doesn't belong to anyone and then you've created a project and because you're anonymous and because uh you also have uh disappear or as unfortunately happened to how finny if that is him he ended up i think dying of a lou gehrig's disease and he is in a cryogenic freezer now but like if you pop in and you d and then you create it and and you're gone and uh all that's remaining of uh that whole process is the thing itself then like no one can go and try to um and if interpret any of your other behavior and try to understand like oh the this person wrote this thing um in some essay at age 16 where he expressed particular opinions about democracy and so because of that this project is like is a statement that's trying to do this specific thing instead it creates uh this uh environment where the thing is what you make of it and it doesn't have the yeah right the the burden of your other ideas political thought and so on so so now that we're sitting with you do you feel the burden of being kind of the face of ethereum i mean there's a very large community of developers but nevertheless yeah is there like a burden associated with that there definitely is this is uh definitely a big reason why i've been trying to kind of push for the ethereum ecosystem to become more decentralized in many ways just encouraging a lot of kind of core ethereum work to happen outside of the ethereum foundation and of expanding the number of people that are making different kinds of decisions having multiple software limitations instead of one and all of these things like there's a lot of things that i've tried to do to and remove myself as a single point of failure because that is something that a lot of people criticism criticize me for um so if you look at like the most fundamentally successful open source projects it seems that it's like a sad reality when i think about it is it seems to be that one person is a crucial contributor often you feel like a lioness from from uh for the for linux for the colonel yeah that is possible and i'm definitely not planning to disappear that's an interesting tension that projects like this kind of desire a single entity and yet they're fundamentally distributed i don't know if there's something interesting to say about that kind of structure and thinking about the future of cryptocurrency does there need to be a leader there's different kinds of leaders you know there's uh there's dictators who control all the money there's people who control organizations there's uh kind of high priests that just have themselves on their twitter followers what kind of leader are you would you say yeah in these days actually a bit more in the hype in the high priest direction than before yeah like i definitely actually don't do all that much of kind of going around and like ordering ethereum foundation people to do things because i think those things are important i if there's something that i do think is important that you i do just usually kind of say it publicly or just kind of say it to people and quite often projects just going to start doing it so let's ask the high philosophical question about money yeah what at the highest level is money what is money it's a kind of game and it's a game where you know we have points and if you have points there's this one move where you can reduce your points by a number and increase someone else's voice by the same number and these so it's a fair game hopefully well it's one kind of fair game like for example you know you can have other kinds of fair games like you're gonna have a game where if i give someone a point and you give someone a points and instead of that person getting two points that person gets four points and that's also fair but no money is um easy to kind of set up and it serves a lot of useful functions and so it kind of just survives in the society as a meme for thousands of years it's useful for this storage of wealth it's useful for the uh exchange of value and it's also useful for denominating future payments a unit of account a unit of account so what if you look at the history of money in human civilization what just uh if if you're a student of history like how has this role or just the mechanisms of money changed over time in your view even if we just look at the 20th century before and then leading up to cryptocurrencies that's something you think about yeah and i think like the big thing in the 20th century is kind of we saw a lot more intermediation i guess like you know i mean the first part is kind of the move from being adding more of different kinds of banking and then i used we saw the move from and of dollars being backed by gold to dollars being backed by gold that's only redeemable by certain people the dollars not being backed by anything um to and it's just this uh nerf system where you have a bunch of free floating currencies and then people like um getting out of bank accounts and then those things becoming electronic people getting accounts with payment processors that have account um bank accounts so so what what do you make of that is that's such a fascinating philosophical idea that money might not be backed by anything what is that like fascinating to you that money can exist without being backed by something physical it definitely is like what do you make of that like how is that possible is that stable if we look at the future of human civilization is it possible to have money at the large scale at such a hugely productive and rich societies be able to operate successfully without money being backed by anything physical i feel like the interesting thing about the 21st century especially is that a lot of the important valuable things are not backed by anything like if you look at like tech companies for example like something like twitter like you could theoretically imagine that if all of the employees wanted to they could kind of come together they would quit and you know start working on twitter 2.0 and then the value of um and just kind of build the exact the the exact same product of course possibly build a better product and then just kind of continue on from there and the original the original twitter would kind of just not have people left anymore right like the there is theoretically kind of code and like ip that's owned by the company but in reality like good programmers could probably read up rewrite all that stuff in three months so the like the reason why the thing has value is just kind of network effects and coordination problems right like these employees in reality aren't going to switch all at once and also the users aren't um all going to switch them at once because it's just difficult for them to switch at once and so there's these kind of meta-stable of equilibrium in the interactions between thousands and millions of people that are just actually quite sticky even though if you try to kind of assume that everyone's a perfectly rational and kind of perfectly slippery spherical cow they don't seem to exist at all this that stickiness do you have a sense of grasp of the sort of the fun fundamental dynamic like the physics of that stickiness it seems to work but uh and i think some of the cryptocurrency ideas kind of rely on it working yeah it's uh you know it's the sort of thing that's definitely been uh economically modeled a lot like one uh the kind of analogy of something as similar that uh you often see in textbooks as like what is a government like if for exa like 80 percent of uh people in a country just like tomorrow suddenly had had the idea that like the laws that are currently the laws in the government that currently is the government are just people and some and some other thing is the government and they just kind of start acting like it then that will kind of become the new reality and then the question is well what happens if and if between zero and 80 people or and 80 of people start believing that and like what is uh the thing you also you see is that if there is one of these kind of switches happening this kind of revolution then if you're the first person to join then like you probably probably don't have the incentive to do that but then if you're the 55th percentile person to join then suddenly becomes quite safe too and so this definitely is the sort of thing that you can kind of try to analyze and understand mathematically but one of the kind of results is that the sort of like when the switch happens definitely can be chaotic sometimes yeah but still like to me the idea that uh the network affects the the fact that human beings at a scale like millions billions can share even the idea of currency like all agree that's just uh i know economics can model it i'm a skeptic on economic and uh it's like uh so my my favorite sort of field maybe recreationally psychology is trying to understand human behavior and i i think sometimes people just kind of pretend that they can have a grasp on human behavior even though we it's such a messy space that all the models that psychology or economics those different perspectives on human behavior can have or are difficult it's difficult to know how much that's wishful thinking and how much it is actually getting to the core of understanding human behavior but on that idea what do you think is the role of money in human motivation so do you think money from an economics perspective from a psychology perspective is core to like human desires money is definitely very far from the only motivator um it is a big motivator and it's uh one of the closest things you have to a universal motivator i think because ultimately in like almost any person in the world if you ask them to do something like they'll be more inclined to do it if you also offer some uh offer the money right and that's uh there's definitely many cases where people will do things other than things that maximize how much money they have and that happens all the time but like though a lot of those other things are kind of but much more specific to and of who that person is and of what their situation is the relationship between the motive and the action and these other things what do you think is in the interplay of the other motivator from like nietzsche perspective is power do you think money equals power do you think those are conflicting ideas do you think i mean that's the one of the ideas that decentralized currency decentralized applications are looking at is who holds the power yeah money is definitely a kind of power and there's definitely people who want money because it gives them power and then even if my money doesn't seem to and explicitly be about money a lot of uh things that people spend money on are ultimately about a social status of some kind um so i mean i definitely view those two things as kind of interplaying and then there's also money as just a way of uh like measuring how successful you are i guess a scoreboard right so this kind of gets back to the game like if you have four billion dollars then the main benefit you get from going up well one of the big benefits you get from going up to six million dollars is that now instead of uh being below the guy who has five you're above the guy who has five so you think money could be kind of uh in a game of life it's also a measure of self-worth it's like how we it's definitely how uh how a lot of people perceive it define ourselves in the hierarchy of yeah and i'm not yeah not saying it's kind of a healthy thing that people define their self-worth as money because it's definitely kind of far from a yeah perfect indicator of like how much you like value you provide to society or anything like this but i i definitely think that like as a matter of kind of current practice a bunch of people do feel that way so what does utopia from an economic perspective look like to you what does the perfect world look like i guess like the economists say utopia would be one where kind of everything is an of incentive aligns in this um in the sense that there aren't enough conflicts between what satisfies your goals and kind of what is uh good for and everyone in the world um in the world as a whole what do you think that would um look like does does that mean they're still poor people and rich people there's still income inequality do you think sort of uh marxist ideas are strong do you think sort of ideas of objectivism uh like where the market rules is strong like what is there is the different economic philosophies that just seem to be reflective of what utopia would be so i definitely think that existing economic philosophies do end up kind of systematically kind of deviating from the utopia in a lot of ways yeah like one of the big things i talk about for example is public goods right and public goods are especially important on the internet right yeah because like the idea is with kind of money as this game where you know i was a few coins a few coins and you gain the same number of coins is that this usually happens in a trade where i lose some money you gain some money you lose a sandwich and i gain a sandwich and this kind of model works really well when the thing that we're using money to incentivize the set of private goods right things that you provide to one person where the benefit comes to one person but the like on the internet especially but also many many contacts kind of off the internet there's actions that kind of individuals or groups can take where instead of the benefit going to one person the benefit just goes to many people at the same time and you can't control who the benefit goes to right so for example this podcast you know we publish it and when it's published you don't have any fine grains control over like oh these 38 000 people can watch it and then like these other 29 000 people can't it's like once the number goes high enough then you know people will just like copy it and then when i write articles on a blog then they're just like free for everyone and that stuff's even harder to prevent anyone from copying so and aside from that things like you know scientific research for example and even taking more pedestrian examples like climate change mitigation would be a big one um so there's a lot of things in the world where you have these kind of individual actions with have concentrated costs and distributed benefits and money as a point system does not do a good job of encouraging these things and one of the kind of other things even kind of tangentially connected to crypto but kind of theoretically outside of it that i work on is this sort of mechanism called quadratic funding um and the way to think about it is and i've imagine a point system where if uh like if one person gives a coin gives coins to one other person then it works the same way as money but if multiple people uh give coins to one person and they do so anonymously so it's kind of not in consideration for a specific service to that person themselves and then the number of coins received by that person is kind of greater than just the sum of the number of coins that have given by those different people um so the actual formula is you take the square root of the amount that each person gave then you add all the square roots and then you had to square the sums yeah and then you give that and the idea here would basically be that if let's say for example you just started going off and kind of planting a lot of trees and there's a bunch of people that are really happy that you're planting trees and so they go and all kind of throw a coin um your way then the like there is like basically the fact that kind of you get more than the sum you get this kind of square of some of these of uh of square roots of these tiny amounts is them that this actually kind of compensates for the tragedy of the comments right in this there's even this kind of mathematical proof that it sort of optimally compensates for it what is the tragedy of the common um this is just this idea that like if there is this uh situation where there's some public good that lots of people benefit from then no individual person wants to contribute to it because if they contribute they only get a small part of the benefit from their contribution but they pay the full cost of their contribution in which context does this um sorry what is the term quadratic quadratic funding like what's in which context is this mechanism useful so obviously you said to to combat the tragedy of the commons but yeah in which context do you see it as useful actually practically yeah theoretically public goods in general right so like like services like what what are we what are we talking about what's the public yeah so within the um ethereum ecosystem for example like we've actually tried using this mechanism i yeah wrote a couple of articles about the cinevon vitalic.ca where i go through some of the most recent rounds and it's been really interesting um some of the top ones that people supported there were things like kind of just online user interfaces that make it easier for people to interact with ethereum there was documentation there were podcasts there were enough software kind of clients like kind of implementations of the ethereum protocol of privacy tools just like lots of things that are useful to lots of people when a lot of people are contributing like funding a particular particular entity yeah uh that's really that's really interesting is there something special about the quadratic the the the summing of the square roots yeah so another way to think about it is like imagine if n people each give a dollar then the person gets n squared right um and and so each individual person's uh contribution gets multiplied by n right because you have n people yeah um and so that kind of perfectly compensates for the kind of kind of anti-1 uh tragedy of the commons i just wonder if the the squared part is yeah how fundamental no it is um and i'd uh recommend you go to uh on vitalik.ca i have this article called a quadratic payments a primer and highly recommended it's kind of at least my attempt so far and explaining the intuition behind this intuition so if we could can we go to the the very basic what is the blockchain or perhaps we might even start at the uh the byzantine generals problem in byzantine fault tolerance in general that i i bitcoin was taking steps to uh providing a solution for so the byzantine generals problem it's this uh paper that uh leslie lamport uh published in 1982 where he has this thought experiments where if you have two generals that are have camped out on opposite sides of a city and they're planning when to attack the city then the question is and if how could those generals coordinate with each other and they could send message messengers between each other but those messengers kind of could get sniped by the enemy on the road some of those messages could end up being traders and if things could end up happening and with just two mess generals it turns out that there's kind of no solution in a finite number of rounds that guarantees that they will be able to coordinate on the same answer um but then in the case where you have more than two generals and then leslie analyzes cases like um are the mess and messages kind of just oral messages are the messages kind of signed messages so i can give you a signed message and then you can pass along that signed message and the third party can still verify that i originally made that message and depending on those different cases there's kind of different bounds on like given how many generals and how many traders um among those generals kind of whether like under one conditions you actually can't agree when to launch an attack uh so it's actually a big misconception that the the byzantine general's problem was unsolved so listen lanport solved it the thing that was unsolved though is that all of these solutions assume that you've already agreed on a fixed list of who the generals are and these generals have to be kind of semi-trusted to some extent they can't just be anonymous people because if they're anonymous then like the enemy could just be 99 of the generals so right then in the 1980s and the 1990s kind of the general use case for distributed system stuff was more kind of enterprisey stuff where you could kind of assume that uh you know you know who the nodes are that are running these nf computer networks so if you wants to have some in a decentralized computer network that pretends to be a single computer and that you can kind of do do a lot of operations on then it's made out of these kind of 15 specific computers and we know kind of who and where they are and so we have a good reason to believe that say at least 11 of them would be fine and then it could also be within a single system exactly almost a network of devices sensors so on like in airplanes and i think uh like flight systems in general still use these kinds of ideas yep yep um so that's the 80s that's the it is the 90s now the cypherpunks had a different use case in mind which is that they wanted to create a fully a decentralized global permissionless currency and the problem here is that they didn't want any authorities and they didn't even want any kind of privileged list of people and so now the question is well how do you use these techniques to create consensus when you have no way of kind of measuring identities right you have no way of kind of determining whether or not some 99 of participants aren't actually all the same guy and so the clever solution that satoshi had this is uh kind of going back to the that presentation i made at defcon a few months ago where i said that the thing satoshi invented with crypto economics is this uh really neat idea that you can use economic resources to kind of limit identity how many identities you can get and the uh if there isn't any existing decentralized digital currency then the only way to do this is with proof of work right so with proof of work the solution is just you publish a solution to a hard mathematical puzzle that takes some uh kind of clearly calculable amount of computational power to solve you get an identity and then you solve five of those puzzles you get five identities and then these are the identities that we run the consensus algorithm between so the proof-of-work mechanism you just described is like the fundamental idea proposed in the in the white paper that defines bitcoin uh what's the idea of consensus that we wish to reach what why is consensus important here what is consensus so the goal here in just simple technical terms is to basically kind of wire together a set of a large number of computers in such a way that they yeah kind of pretends to the outside world to be a single computer where that single computer keeps working even if a large portion of the kind of constituents the computers that make it up break and kind of break in arbitrary ways like they could shut off they could uh try to actively break a system they could do lots of mean things so the reason why the cypherpunks wanted to do this is because they wanted to run one particular program on this virtual computer and the one particular program that they wanted to run is just a currency system right it's a system that just processes a series of transactions and for every transaction it verifies uh that the sender has enough coins to pay for the transaction and verifies that the digital signature is correct and if the check's passed then it subtracts the coins from one account and adds the coins to the other account roughly so first of all the the the proof-of-work idea is kind of i mean at least to me seems pretty fascinating it is i mean that's a it's kind of a revolutionary idea i mean is is it is it obvious to come up with that you can use uh you can exchange basically computational resources for for identity it's uh it actually has a pretty long history it was uh first proposed in a paper by uh cynthia dwork and [Music] neor in 1994 i believe and the original use case was uh combating email spam so the idea is that if you send an email you have to send it with a proof of work attached and like this makes it reasonably cheap to send emails to your friends but it makes it really expensive to send spam to a million people yeah that's a simple brilliant idea so maybe also taking a step back so what is the role of blockchain in this what is the blockchain sure so the blockchain i mean my way of thinking about it is that it is this kind of system where you have this kind of one virtual computer created by this a bunch of these uh uh nodes in the network um and the reason why the term blockchain is used is because the data structure that these systems use at least so far is one uh where they um even if different nodes in the network periodically publish blocks and a block is a kind of list of transactions uh together with a pointer like a hash of a yeah a previous block that it builds on top of um and so you have a series of blocks that that nodes in the network create where each block points to the previous block and so you have this chain of them is a fault tolerance mechanism built into the idea of blockchain or is there a lot of possibilities of different ways to make sure there's no funny stuff going on there are indeed a lot of possibilities um so in a kind of just simple architecture as i just described the way the fault tolerance happens is like this right so you have a bunch of nodes and they're just happily and occasionally creating blocks building on top of each other's uh blocks and let's say you have kind of one block we'll call it kind of block one and then someone else builds another block on a steel called block two then we have an attacker and what the attacker tries to do is the attacker tries to revert block two and the way they revert block two is instead of doing the thing they're supposed to do which is build a block on top of block two they're gonna build another block on top of block one um so you have block one which has two children block two and then block two prime now this might sometimes even happen by random chance if you know two nodes in the network just happen to create blocks at the same time and they don't hear about each other's things before they create their own but this also could happen because of an attack now if this happens you have an attack then the no in the bitcoin system uh the nodes follow the longest chain um so if um this um attack had happened uh and if when the uh original chain had more than two blocks on it so if it was trying to kind of revert more than more than two blocks then everyone would just would just ignore it yeah um and everyone would just keep following the regular chain but here you know we have block two and we have block two prime and so the two are kind of even and then whatever block um the next block is created on top of so say block three is now created on top of block two prime then everyone says agrees that block 3 is the new head and block 2 prime is just kind of forgotten and then everyone just kind of peacefully builds on top of block 3 and the thing continues so how difficult is it to mess with the system so how like if we look at the general problem like how many what fraction of people who participate in the system have to be bad players in order to mess with it truly like what's your is there is there a good number serious um well depending on kind of what your model of the participants is and like what kind of attack we're talking about it's anywhere between 23.2 and 50 percent of what of all of the computing power in the network sorry so 22 and 23. between 23.2 and 50 and 50 are can be uh compromised so like once you're once your pers your portion of the total um computing power the network goes above the 23.2 level then there's kind of things that you can mean things that you can potentially do and as your percentage of the network kind of keeps going up then the your abilities as you mean things kind of goes higher and then if you have above 50 then you can just break everything so how hard is it to achieve that level like it seems that so far historically speaking has been exceptionally difficult so this is a challenging question um so the economic cost of uh acquiring that level of stuff from scratch is uh fairly high i think it's uh somewhere in the low billions of dollars and when you say that stuff you mean computational resources yeah so specifically specialized hardware and of asics that people use to uh solve these uh puzzles is to do the mining these days small tangent uh so obviously i work a lot in deep learning with gpus and asics for that application and i tangentially kind of hear that so many of these you know sometimes nvidia gpus are sold out because of this other application like what do if you can comment i don't know if you're familiar or interested in the space what kind of asics what kind of hardware is generally used these days for to do the actual computation for the the proof of work sure so in the case uh and bitcoin and ethereum are a bit different uh so in the case of bitcoin there is an algorithm called uh sha256 it's just a hash function and so the puzzle is just coming up with a number where the hash of the number is below some threshold and so because the hashes are designed to be random you just have to keep on trying different numbers until one works and the are just like specialized circuits that contain kind of circuits for evaluating this hash over and over again and you have like millions or billions of these hash evaluators since just stacked on top of each other inside of a box and you just keep on running the box 24 7. in the asx there's literally specialized hardware designed for this yes oh this is we live in an amazing world another tangent and i'll come back to the basics but uh does quantum computing throw a wrench into any of this very good question so uh quan some computers have two main kind of families of algorithms that are relevant to cryptography one is a shores algorithm ensures algorithm is one that kind of completely breaks the hardness of uh some specific kinds of mathematical problems so the one that you've probably heard of is it makes it very easy to factor numbers uh so like figure out kind of what prime factors are that kind of that you need to multiply together to get some number even if that number is extremely big um sure's algorithm can also be used to break elliptic curve cryptography um it can break like any kind of hidden order group so it breaks a lot of kind of cryptographic nice things that we're used to but the good news is that for every kind of major use of uh things that shore's algorithm breaks we already know of uh quantum proof alternatives right now we don't use these quantum proof alternatives yet because in many cases they're five to ten times what's efficient but and uh the crypto industry in general kind of knows that this is coming eventually and it's kind of ready to uh take the head and switch to that stuff when we when we have to the second algorithm that is relevant to cryptography is grover's algorithm and and grover's algorithm might even be kind of more familiar to ai people that's basically usually described as solving search problems um but the idea here is so that if you have a problem over the form finds a number that satisfies some property um then if with a classical computer you need to try kind of end times before before you find the number then with a quantum computer you only need to do square root of n computations and grovers could potentially be used for mining but there's two possibilities here one is that grovers could be used for mining and whoever creates the first working quantum computer that could do grovers we'll just mine way faster than everyone else and we'll see another round of uh what we saw when asics came out which is that's kind of the new hardware just kind of dominated the old stuff and then eventually it switched to a new equilibrium but by the way way faster not exponentially faster quadratically faster quadratically faster which is not sort of uh it's not game-changing i would say it's like asics like you said it would be exactly yeah so it would not necessarily break proof of work as of that's right yeah now the other kind of possible world right is that quantum computers have a lot of overhead there's a lot of complexity involved in maintaining quantum states and there's also as we've been realizing recently making quantum computers requ actually work requires kind of quantum era correction which requires kind of a thousand real qubits per logical qubit and so there's the very real possibility that the overhead of running a quantum computer will be higher than the speed up you get with grovers which would be kind of sad but which would also mean that given proof of work would just keep working fine so they're beautifully put so so proof of work is uh the core idea of bitcoin is there other core ideas before we kind of take a step towards the origin story and the ideas of ethereum is there other stuff that uh were key to the white paper of bitcoin there's proof of work and then there's just the cryptography just kind of public keys and signatures that are used to uh verify transactions those two really big things so then what is um the origin story maybe the human side but also the technical side of ethereum sure so i joined the bitcoin community in uh 2011 and i started by just writing i first wrote for this sort of online thing called bitcoin weekly then i started writing for uh bitcoin magazine um and uh sorry to interrupt you have this funny kind of uh story true or not is uh that you were disillusioned by the downsides of centralized control from your experience with wow world of warcraft is this true or you're just being witty uh i mean the event is true of the fact that that's the reason i do decentralization is woody maybe just a small tangent d have you always had a skepticism of centralized control is that some degree yeah has that feeling evolved over time or is that just always been a core feeling that decentralized control is the future of a human society and it's definitely been something that felt very attractive to me ever since i could afford that such a thing as possible possible yeah so great so you are you join the bitcoin community in 2011 you said you began writing so what was next started writing uh moved from high school to university halfway in between that and spent a year in university um then at the end of that year i dropped out to to do uh bitcoin things uh full time and this was a combination of continuing the right bitcoin magazine but also increasingly work on software projects and i traveled around the world for about six months and just going to different bitcoin communities like i went to uh first in new hampshire and then spain other european voices um israel and san francisco and along the way and i've met a lot of other people that are working on different bitcoin projects and when i was in israel there were some very smart teams there that were working on ideas that people were starting to kind of call bitcoin 2.0 so one of these were covered coins which is basically saying that hey let's uh not just use the blockchain for bitcoin but let's also kind of issue other kinds of assets on it and then there was a protocol called mastercoin that supported issuing assets but also supported many other things like financial contracts like domain name registration and a lot of different things together and i spent some time working with these teams and i quickly kind of realized that this mastercoin protocol could be improved by kind of generalizing it more right so the master the analogy i use is that the master coin protocol was like the swiss army knife you have 25 different transaction types for 25 different applications but what i realized is that you could replace a bunch of them with things that are more general purpose so one of them was that you could replace like three transaction types for three types of financial contracts with a generic transaction type for a financial contract that just lets you specify a mathematical formula for kind of who how much money each side gets by the way it's a small pause what's you say financial contract just the terminology what is the contract um what's a financial contract so the this is just generally an agreement where kind of either one or two parties kind of put collateral kind of in um and then they depending on and if certain conditions like this could involve prices of assets this could involve different the actions of the two parties it could involve other things but they kind of get different amounts of uh of assets out that it'll just depend on things that happened so a contract is really a financial contract is the is at the core it's the it's the core interactive element of a financial system yeah there's yeah there's many different kinds of financial contracts like there's things like options where you kind of give someone the right to buy a thing that you have for some specific price for some period of time there's uh contracts for difference where you basically are kind of making a bet that says like for every dollar this thing goes up i'll give you seven dollars or for every dollar that thing goes down you give me seven dollars or something like that and but the main idea that these contracts have to be enforced and trusted yes exactly you have to trust that they will work out in a system where nobody can be trusted yes this is such a beautiful complicated system okay so uh so you were seeking to kind of generalize this basic uh framework of contracts so what does that entail so what what technically are the steps to creating ethereum so i guess just to kind of continue a bit with this master coin story sure um so started by end of giving ideas for how to generalize the thing and eventually um this turned into a much more kind of fully fledged proposal that just says hey how about you scrap all your features and instead you just um put in this programming language and i gave this idea to them and their response was something like hey this is great but this seems complicated and it seems like something that's we're not going to be able to put onto our roadmap for a while and my response to this was like wait do you not realize how revolutionary this is well just go do it myself and then i was the name of the programming language i just called it ultimate scripting great uh so then i kind of went through a couple more rounds of iteration and then the idea for ethereum itself started to form um and the idea here is that you just have a blockchain where the core unit of the thing is what we call contracts it's these and if accounts that can hold assets and like like have their own internal memory but that are controlled by a piece of code and so if i send some ether to a contract the only thing that can determine where that kind of ether and the currency inside ethereum and it goes after that um is the code of that contract itself and so basically you're kind of sending assets to computer programs becomes this kind of paradigm for creating the incentive agreement self-executing agreements self-executing it's so cool that code is sort of part of this contract so that that's what's meant by smart contracts yeah so how hard was it to build this kind of thing harder than expected um and originally i actually thought that this would be a thing that i would kind of casually work on for a couple of months publish and then go back to university um then i released it and a bunch of people or i released a white paper white paper there is there the idea the white paper um a whole bunch of people came in offering to help a huge number of people and have expressed interest and this was something i was totally not expecting and then i kind of realized that this would be something that's kind of much bigger than i had ever thought that it would be and then we started on this kind of much longer developments log of making something that lives up to this sort of much higher level of expectations what are the some of the is it fundamentally like software engineering challenges it was there social okay so there's social so so what are the biggest interesting challenges that you've learned about human civilization and in software engineering through this process so i guess one of the challenges for me is that like i'm one of the kind of apparently unusual geeks who was kind of never treated with anything but kindness in school yes um and so when i got into crypto i kind of expected everyone would just kind of be the same kind of altruistic and nice in that same way um but the um and if the algorithm that i used for finding co-founders for this thing was not very good it was sort of literally one computer scientist called the greedy algorithm it's kind of the first 15 people who applied back offering to help kind of are the co-founders oh you mean like literally the the the people that four will form to be the the founders co-founders of the community the algorithm i like how you call it the algorithm yeah um and so what happened uh was that uh these um like especially as the projects got really big like there started to be a lot of this kind of infighting and there are a lot of like i wanted the thing to be a non-profit and some of them wanted to be a for-profit um and then there started to be people who were just kind of totally unable to work with each other there were people that were kind of trying to get an advantage for themselves in a lot of different ways and this uh just about six months later led to this big governance crisis and then we kind of reshuffled leadership a bit and then uh the project kept on going then nine months later there was another governance crisis and then there was a third governance crisis and so is there a way to if you're looking at the human side of things is there a way to optimize this aspect of the cryptocurrency world it seems that there is from my perspective there's a lot of different characters and personalities and egos and like you said uh i don't know if you know i also like just think that most of the world most of the people in the world are well intentioned but the way those intentions are realized may perhaps come off as uh yeah as as negative like what uh is there is there a hopeful message here about creating a governance structure for cryptocurrency that uh where everyone gets along and after about four rounds of reshuffle i think we've actually come up with something that seems to be pretty stable and happy um i think i mean i definitely do think that most people are well intentioned i just think that like one of the reasons why i like decentralization is just because there's like this thing about power where power attracts people with egos and so that just allows a very small percentage of people to just ruin so many things you think ego has a you think ego has a use like is ego always bad it seems like it sometimes does but then the ethereum research team i feel like we've found also kind of a lot like a lot of very good people that are just and if primarily you're just interested in things for the technology and uh you know things seem to just generally be going quite well yeah when you're when the focus and the passion is in the tech so on the so that's the human side of things but the technology side like what have you learned what have been the biggest challenges of bringing ethereum to life on the technology side so i think first of all just uh you know there's like the first law of software development which is that when someone gives you a timetable let's switch the unit of time to the next largest unit of time and had one and like we basically fell victim to that um and uh and so instead of taking those like three months it ended up taking like 20 months to watch the thing um and that was just i think underestimating the sheer technical complexity of the thing um there are research challenges like so for example one of the things that we've been saying from the start that we would do one is a switch from a proof-of-work to a proof-of-stake uh more proof of stake is to this uh alternative consensus mechanism where instead of uh having to waste a lot of uh computing power on solving these mathematical puzzles that don't mean anything you kind of prove that you have access to coins inside of the system and this uh and it gives you some level of participation in the consensus can you maybe elaborate on that a little bit i understand the idea of proof of work um i know that a lot of people say that the idea of proof of stake is really appealing can you maybe linger on a longer explain what it is sure so basically the idea is like if i kind of lock up a hundred coins then i turn that into a kind of quote virtual miner and the system itself kind of automatically and randomly assigns that in a virtual miner the right to create blocks at particular intervals and then if someone else has 200 coins and they walk on the lock there's 200 coins then they get a kind of twice as big virtual miner they'll be able to create their blocks twice as often right so it tries to kind of do similar things to proof of work except instead of the thing and rate limiting your participation being your ability to crank out uh solutions to kind of hash challenges the thing that really limits your participation is kind of how much coins you're locking into this mechanism okay so interesting so that that limit of participation doesn't require you to run a lot of compute does that mean that the richer you are so rich people um are more like their identities more right and this stable yeah verifiable or whatever whatever the right terminology is right and this is definitely a common critique i think my usual answer to this is that like proof of work is even more of that kind of system exactly yeah because i didn't mean it and that statement is a criticism i think you're exactly right that's equivalent the proof of work is the same kind of thing but in the proof of work you have to also use physical resources yes and uh burn computers and burn trees and all of that stuff is there um a way to mess with the system of the proof of uh proof of stake there is but you will once again need to have uh a very large portion of all the coins that are locked in the system to do anything bad got it so yeah and just to that maybe take a small tangent one of the criticisms of cryptocurrencies the fact that it gets for the proof-of-work mechanism you have to use so much energy in the world yes is that one of the motivations of proof-of-stake is to move away from this definitely like what's your sense of the uh maybe i'm just under-informed is there like legitimately environmental impact from this yeah uh so the latest thing was that bitcoin consumed as much energy as the country of austria or something like that yeah and then ethereum is like right now maybe only like half an order of magnitude smaller than bitcoin i've heard you talk about uh ethereum 2.0 so what's the what's the dream of a theorem 2.0 what's the status of proof of stake is the mechanism that ethereum moves towards and also how do you move to a different mechanism of consensus within a cryptocurrency so ethereum 2.0 is a collection of major upgrades that we've wanted to do to ethereum for quite some time the two big ones uh one is proof of stake and the other is that we call sharding sharding solves another problem with blockchains which is a scalability and what sharding does is it basically says instead of every participant in the network having to personally download and verify every transaction every participant in the network only downloads and verifies a small portion of transactions and then you kind of randomly distribute who gets how much work um and because this of how the distribution is random it still has the property that you need a large portion of the entire network to corrupt what's going on inside of any shard but the system is still kind of very redundant and very secure that's brilliant how hard is that to implement and how hard is uh proof of stake to implement like on the technical level yeah software level proof of stake and charting are both challenging um might say sharding is a bit more challenging the reason is that proof of stake is kind of just a change to like how the consensus lawyer works shorting does both that but it's also a change to the networking layer um the reason is that charting is kind of pointless if at the networking layer you still do what you do today which is you kind of gossip everything which means that if someone publishes something every other node in the client hears it like from uh on the networking layer and so instead we have to have enough sub networks and the ability to quickly switch between sub networks and other sub networks talk to each other and this is all doable but it's a more complex architecture and it's definitely the sort of thing that has not yet been done in cryptocurrency so most most of the networking layer in uh cryptocurrency is you're shouting you're like broadcasting messages and this is more like ad hoc networks like yeah you're shouting within smaller groups smaller group but do you have like a bunch of subnet like exactly and you have to switch between oh man i'd love to see the uh so it's a beautiful idea uh so from a graph theoretic perspective but just the software like who's responsible is the ethereum project like the people involved would they be implementing like what's the actual you know this is like legit software engineering uh who like how does that work how do people collaborate build that kind of project is this like almost um like is there a a software engineering lead is there is like is it a legit almost like large-scale open-source projects there is yeah so um we have uh someone named danny ryan on our team who's just been brilliant and great all around and he is a kind of de facto kind of development coordinator i guess it's like you have to invent job titles for this stuff right the reason is that um like we also have this unique kind of organizational structure where the ethereum foundation itself kind of does research in-house but then the actual implementation is done by independent teams that are separate companies and they're located all around the world and like fun places like australia um and so you know you kind of just need a bunch of kind of almost non-stop cat hurting to just keep getting these people to kind of talk to each other and kind of implement the spec make sure that everyone agrees on what's going on and kind of how to interpret different things so how far into the future are we from these two mechanisms in ethereum 2.0 like what's what's your sense of the timeline keeping in mind the previous comments you made about the sort of uh general curse of software projects so ethereum 2.0 is split into three phases so phase zero just creates a proof of stake network and it's actually separate from kind of proof of the proof of work network at the beginning just to kind of give it time to grow and improve itself do people get to choose sorry to interrupt the people get to choose i guess yes they get to choose to move over if they want to then phase one adds sharding but it only adds sharding of and of data storage and not sharding of a computation and then after that there is kind of the merger phase which is where the yeah and if the accounts uh kind of smart contracts like all of the activity on the the existing ether1 system just kind of gets cut and pasted into eth2 and then the proof of work chain gets forgotten and then and the things all the things that we're living there before you just kind of continue living inside of the proof of stake system so for timelines um phase 0 has been kind of almost fully implemented and now it's just a matter of a whole bunch of security auditing and testing um my own experience is that right now it feels like we're at about a phase comparable to when we were doing uh the original ethereum launch when we were maybe about four months away from lunch but that's just a hunch then that's just that's just a hunch yeah so how you know it took it took like over a decade for people to move from python to python three how do you see the move from like at this phase of zero of for for different consensus mechanism do you see there being a a drastic phase shift and people just kind of jumping to this better mechanism so in phase zero i don't expect too many people to do much because in phase zero and phase one the new chain negative deliberately enough doesn't have too much functionality turned on it's there just like if you want to be a proof of stake validator you can get things started if you want to store data for other blockchain applications you can get started but existing applications will largely keep living on each one and then when the merger happens then the merger as they operation that happens all at once i mean so instead of one of the benefits of i can sense a system that like on the one hand you have to coordinate the upgrade but on the other hand the upgrade can be coordinated so what's casper ffg by the way um casper ffg is the consensus algorithm that we are using for the proof of stake is there something interesting uh specific about casper ffg like some beautiful aspect of it that's uh there he is so casper ffg combines together kind of two different schools of like it's not algorithm design uh so the general two different schools of the of the design are right one is uh 50 fault tolerant but dependent on network synchrony so fifty percent volume fault tolerant but it didn't tolerate up to fifty percent of faults but not more but it depends on an assumption that all of the nodes can talk uh talk to each other within some of a limited period of time like if i send the message you'll receive it within a few seconds um and the second the school is 33 fault tolerant but safe under asynchrony which means that like if we agree on something then that thing is finalized and even if the network goes horribly wonky the second after that thing is finalized there's no way to revert that thing um and that's fascinating how you would make that happen it's uh definitely quite clever um i'd recommend the casper ffg paper um if you just search like archive as in like a rx iv and casper ffg it's that's an archive the paper is an archive yeah yeah who are the authors um myself and uh virgil griffith that's awesome take a small tangent this idea of just putting out white papers and papers and putting them on archive and just putting them publicly that is that at the core is that a necessary component of particular currencies that the tradition started with uh uh satoshi nakamoto is like what do you make of it like what do you make of the future of that kind of sharing of ideas i guess so yeah and it's definitely something that's kind of mandatory for crypto because like crypto is all about making systems where you know you don't have to trust the operators to trust that the thing works and so if anything behind how a system works is closed-sourced and that kind of uh kills the point and so there is the kind of a sense in which the fundamental properties of the category of the thing we're trying to build just kind of forces openness but also openness just has proven to be a really great way to collaborate and then there's actually a lot of innovation and academic collaboration that's just kind of happened ad hoc in the crypto space the last few years so like for example we have this forum called etheresearch that's like e-t-h-r-e-s-e-a-r and then dot c-h um and there we publish uh kind of just ideas in a form that's kind of half formal like it's halfway in between like it's it's a kind of a text write up and then you can have math in it but it's often much shorter than a paper and it turns out that the great majority of new ideas like they're just kind of fairly small nuggets that you can explain in like five to ten lines and they don't really need the whole formality of a paper exactly they don't require the kind of like ten pages of in a filler and so introduction conclusion is not needed yeah and so instead you just kind of publish the idea and then like people giggle comments on it and it's brilliant yeah this has been so great for us i think i interrupted you was there something else on casper ffg yeah so just casper ffg is just kind of combines together these two schools um and so basically it creates this system where if you have uh more than 50 that are honest then um and you have a network synchrony then the thing kind of goes as a chain but then if network security fails then kind of the last few blocks in the chain might kind of get replaced but anything that was finalized by this kind of more asynchronous process uh gets uh like can't be reverted and so you essentially get a kind of best of both worlds between those two bottles okay so i know what i'm doing to them i'm going to be reading the casper refugee paper uh apologize for the romanticized question but what to you are some or the most beautiful idea in the world of ethereum just something uh surprising something beautiful something powerful yeah i mean i think the fact that money can just emerge out of a database if enough people believe in it i think is definitely one of those things that's up there um i think one of the things that i really love about ethereum is also this concept of composability so this is the idea that like if i build an application on top of ethereum then you can build an application that talks to my application and you don't even need my permission you you don't even need to talk to me right so one really fun example of this is there was this center game on ethereum uh called a cryptokitties that just involved kind of breeding digital cats yes and someone else created a game called crypto dragons where the way you play crypto dragons is you have a dragon and you have to feed it cryptokitties and they just created the whole thing just like as an ethereum contract that you would send these uh these tokens that are defined by this other ethereum contract and for the interoperability to happen like the projects didn't don't really need to like the teams don't really need to talk to each other you just kind of interface with the existing program so it's uh arbitrarily composable in this kind of way so you have different uh different groups that could be working so you could see it scaling to just outside of dragons and kitties it could be you could build like entire ecosystems of software yeah it's kind of weird i mean especially in the the decentralized finance space that's been popping up the last two years there has been a huge amount of really interesting things happen as a result of this is it particular kind of like financial applications kind of thing yeah i mean there's like stable coins so this is a kind of tokens retain value i'm equal to one dollar but they're kind of backed by a crypt uh cryptocurrency um then there's decentralized exchanges um so when as far as the decentralized exchanges goes up there's this uh really interesting construction that has existed for about one one and a half years now called uniswap so what unit swap is let's say a smart contract that holds balances of uh two tokens we'll call them token a and token b and it maintains an invariant that the balance of token a multiplied by the balance of token b has to equal the same value and so the way that you trade against the thing is basically like you have this kind of curve you know like x times y equals k and yeah before you trade it's at some points on the curve after you trade you just like pick some different any any other points on the curve and then whatever the delta x is that's the amount of a tokens you provide whatever the delta y is that's the amount of b tokens you get or vice versa and that's just and then kind of the slope at the current uh point on the curve kind of is the price um and so that just is the whole thing and that just allows you to kind of have this exchange for tokens and even if there's very few participants and the whole thing is just like so simple and it's just very easy to set up very easy to participate in and it just provides so much value to people so and uh the uh the fundamental the the the distributed application infrastructure and allows that somehow yes so this is a smart contract meeting this is all a computer program that's just running on ethereum smart contracts too are just fascinating they are okay do you think cryptocurrency may become the main currency in the world one day so where do you think we're headed in terms of the role of currency the structure type of currency in the world i definitely expect some fiat currency is to continue to exist and continue to be strong and i definitely expect kind of fiat currencies to also digitize in their own way over the next couple of decades what's fiat currency by the way oh just like things like us dollars and like dollars and euros and yen and these other things and they're sort of backed by governments yes but i also expect enough cryptocurrencies to play a kind of important role in just making sure that people always have an alternative if uh fiat currencies start breaking so like if or if you're in you know some at a very high inflation place like venezuela for example or if your country just kind of gets cut off from like um cut off from other financial systems because of like something the banks do a gift for any kind of if there's even like some major trade disruption right or something worse happens then like cryptocurrencies are the sort of thing that just because of their kind of global neutrality they're just kind of always there and you can keep using them it's interesting that you're quite humble about the possibilities of the future of cryptocurrency you don't think there's a possible future where it uh becomes the main set of currency because it feels like fiat it feels like the centralized controlled by governments of currencies limiting somehow maybe my naive utopian view of the world it's uh and it's definitely very possible i mean i think like four cryptocurrencies being the main form of uh value to and of work well like you do need to have some [Music] much more price stability than they have today and i mean there are now stable coins and there are kind of cryptic cryptocurrencies that try to be more stable than existing things like bitcoin and ether but that just is to me kind of the main challenge do you think oh that's do you think that's a characteristic of this just being the early days it's such a young concept that 10 years is nothing in the history of money yeah and i think it's a combination of two things right one is um it's uh it's still early days but the other is a kind of more durable any kind of economic problem which is that like demand for currency is volatile right because of like recessions booms changes to technology lots of things and if people's demand for how much currency they want to hold changes and if you have a currency that has a fixed supply then the change in demand has to be entirely expressed as a change in value of the currency and so what that means is that kind of the volatility of demand becomes entirely translated into volatility and ahead of prices of things that dominated in that currency but if you have a currency where instead the supply can change and so the supply can go up when there's more demand than you have the supply and of absorbing more of that volatility and so the price of the currency would absorb less of the volatility on that topic so bitcoin does have a limited supply specific fixed supply yes uh what's what's the idea and the ethereum doesn't but can you clarify just in the comments you just made is ethereum qualify to the kind of currency that you're talking about and being flexible in the supply and it's a bit more flexible but kind of the thing that you would really want is something that's kind of specifically flexible in response to how valuable the currency is and and i'd recommend you to look at stable coins as well so like things like die for example that's a new like how do you spell that dai and what uh what's stable coins is that a type of cryptocurrency it is a type of cryptocurrency it's um a type of cryptocurrency that's issued by a smart contract one of these ethereum computer programs that um where the smart contract holds a bunch of ether and then it is basically like that people deposit and then at issues die and the reason why people deposit is because they wants to kind of go high leverage on their ether and so it kind of pairs these two sets of users one that wants stability and one that kind of wants extra risk together with each other and it basically creates some or gives one set of participants a guarantee that they'll be pa uh that they have this asset that can that that can be later converted back into ether but like specifically out kind of the one dollar raid and it has some kind of uh stabilizing network effects yeah it has this yeah it has many kinds of stabilizing mechanisms in it that's fascinating okay this this world is awesome technically just from a scientific perspective it's an awesome world uh that i i often don't see from an outsider's perspective what i often see is kind of uh maybe hype and a little bit if i may say so like charltonism and you don't often see at least from an outsider's perspective the beautiful science of it and the engineering of it maybe is there a comment you can make of who to follow how to learn about this world without being interrupted by the charlatans and the hype people in the space i think you do need to just know the specific kind of just people to follow like there's and there's all the kind of the cryptographers and the researchers and then there's just like even just the ethereum research crew like myself you know like dan crowd danny justin of the other people and then and if the academic cryptographers and like before um um this today was at stanford and uh stanford has the center for blockchain research and of dan bonnet that's really uh famous and great cryptographer um running it and there's a lot of other people there and there's people working on like zero knowledge proofs for example and um zuko from uh zcash has kind of one other person that i yeah you know respect so i think if you follow the technology you crawl along that yeah yeah you just start with the etherium group and then look at the academics dave and so on and then just cautiously expand the network of people you follow yeah exactly and like if someone seems too too self-promotional then just like remove them is there books that are so there's these white papers and we just discussed about about ideas being condensed into really small parts is there books that are emerging that are kind of good uh introductory material so prefer historical ones and there's like nathaniel poppers digital gold which is just about the history of bitcoin there's like one and then matthew lysing announced that there's one about the history of ethereum um for technical ones and there's andreas antonopoulos as mastering ethereum great so um let me ask you sort of uh sorry to pull back to the the idea of governments and decentralized currency uh you know there's a tension between decentralization of currency and the power of nations the power of governments you um what's your sense about that tension can is there some rule for regulation of currency yeah is there like is the government the enemy of digital currency of distributed currency or can they be like cautious friends i mean i think like the one thing that people forget is that it's clearly not entirely an enemy because i think uh if uh there hadn't been so much government regulation on and if centralized uh digi like issuing centralized digital currencies then like we would be seeing things with people like google and facebook and twitter just kind of issuing them left and right and then like if that was the case then decentralized currencies would still appeal to some people but they definitely would appeal to less people than today so even in that sense i think it's uh clearly been kind of more of a help i just kind of set the stage for the end of the existence as a of the sector in some ways um but also and i think some of both you know like there's definitely things that governments kind of can do in some cases have done to have hurt the spread of uh and of growth of of blockchains there's uh things that they've done to help and they've in some cases definitely done a good job of kind of going after fraudulent projects and they're going after some of the projects that have some of the kind of craziest and most misleading marketing um there's uh also the possibility that governments will end up using blockchains for a lot of different things like you know governments yeah i mean they do a lot more than just regulating right but there's also like they have the identity of records and they have like property registry is even just their own currency is like security lots of different kind of things that they're operating and there's even blockchain applications in a lot of those and they can you know they can leverage technology do a lot of good for our societies it is a little unfortunate that uh governments often lag behind in terms of their acceptance and leverage of technology if you look at the autonomous vehicle space ai in general they're uh they're a few years behind it'd be nice uh to help them catch up that's a that's that's always ongoing problem you uh met vladimir putin to discuss the centralized currency here you're born in uh where were you born columnar it's a city about 115 kilometers south of moscow in russia yes yeah i grew up in moscow i mean it's vladimir putin is a central figure in this part of the world so what was that like meeting or meeting him what was that experience like he's taller in photos than in person yeah yeah that's right he's five seven i think five eight maybe yeah and that's uh unfortunately we didn't actually kind of have too much of a chance to talk to him like i managed to see him for about one minute at the end of this meeting and i did get a chance to see a lot like some of the other end of government ministers and like he recommended some and uh some of them are are actually interested in trying to use some like blockchains to look for various government use cases they're going to have limited corruption and other things and i have it's hard to tell from one conversation kind of what things are genuine and what things are just like oh watching is cool let's do blockchain right but you know when i when i listen to like uh barack obama talk about artificial intelligence there's certain things i hear where okay so he might not be an expert in ai but he know he like actually studied it carefully enough to think about it like he internal like uh even if it's just reading a wikipedia page like he really thought about what this technology means did you get a sense that uh putin or some of the ministers like thought about blockchain like thought about the fundamentals the technology understand it intuitively or are they too old school to try to grasp it summer old school somewhere more new school it depends it's it's definitely depends on who you talk to i mean that's an open question for me for with putin because putin has said uh i don't know as i said i've only talked to him for about one minute so but sometimes you can pick up sort of insights as a quick comment there they're about maybe you can correct me on this but they're about 3 000 cryptocurrencies being actively traded yes uh and ethereum is one of you know a lot of people believe that there will be the the main cryptocurrency i think bitcoin is currently still the main cryptocurrency but ethereum very likely might become that the the main one um is this kind of diversity good in the crypto world do you see it sticking around should there should there be a winner like should there be some consensus globally around uh bitcoin or around ethereum like what's your what's your sense i definitely think that diversity is good and i definitely i think also that there's probably too many people trying to make separate blockchains of right now and the numbers should definitely be greater than one and probably greater than two or even five uh not three thousand not three thousand yeah and also not even like 40 high quality platforms to try to do the same thing there's definitely this range from just like one person who just like wrongly thinks that you can create a cryptocurrency in like 12 hours and doesn't even think about kind of the community aspects of maintaining it going to people actually trying but only creating a really tiny one to like scammers to people like making something that's actually successful and then there's a lot of different categories of blockchain and you have project in terms of what it's trying to do and what applications it's for um and i think the experimentation is definitely healthy if you look at the two worlds there might be a little bit disjoints but uh the distributed applications cryptocurrency and then the world of artificial intelligence do you see there's some overlap between these worlds that both worry about centralized control is there some overlap that's interesting that you think about do you think about ai much yeah and i think definitely had a thought about things like like the ai and if control problems and alignment problems and all of those things do you worry about the existential threat of ai that's definitely one of the things i worry about they think um blood there's a lot of kind of common challenges because in in both cases what you're ultimately trying to do is you're trying to kind of get a simple system to direct a more complex system like in the case of uh these as strong ais the idea would be that the simple system is people and the complex system is well whatever um thing uh the people the people end up kind of unleashing on the universe that'll hopefully be a great thing um and in the case of blockchains and of the complex well the simple thing is the algorithm which is a piece of static and fully open source code and the more complex thing is just the num all of the different possible kind of human actors and of the strategies that they might end up used to participate in the network do you think about your own mortality like what you hope to accomplish in your life oh i definitely i definitely think about ending my own mortality so that's if i gave you the option to live forever would you depends a lot on what the fine bridge is i mean you know if it's one of those things where i'm going to be kind of like floating through empty space for 10 to the 75 years then no if it's uh um forever worth of uh end of having you know fulfilling life with uh and if meaningful with with friends to uh to spend the time with with kind of meaningful challenges to explain explore and adventure interesting things to be working on then i think absolutely move that's uh beautifully put live forever but uh you'd have to check the fine print um i think there's no better way to end it vitalik thank you so much for talking to us so exciting to follow your work from the distance and uh thank you for creating a revolutionary idea and sticking with it and building it out and doing some incredible engineering work and thanks for talking today yeah thank you thanks for listening to this conversation with vitalik buterin and thank you to our sponsors expressvpn and masterclass please consider supporting the podcast by signing up to masterclass at masterclass.com lex and getting expressvpn at expressvpn.com lex pod if you enjoy this podcast subscribe on youtube review it with five stars on apple podcast support it on patreon or simply connect with me on twitter at lex friedman and now let me leave you with some words from vitalik buterin the thing that i often ask startups on top of ethereum is can you please tell me why using ethereum blockchain is better than using excel and if they can come up with a good answer that's when you know you got something really interesting thank you for listening and hope to see you next time you |
Lee Smolin: Quantum Gravity and Einstein's Unfinished Revolution | Lex Fridman Podcast #79 | the following is a conversation with Lee Smolin he's a theoretical physicist co-inventor of loop quantum gravity and a contributor of many interesting ideas to cosmology quantum field theory the foundations of quantum mechanics theoretical biology and the philosophy of science he's the author of several books including one that critiques the state of physics and string theory called the trouble with physics and his latest book Einsteins unfinished revolution the search for what lies beyond the quantum he's an outspoken personality in the public debates on the nature of our universe among the top minds in the theoretical physics community this community has its respected academics it's naked Emperor's its outcasts in his revolutionaries its Mad Men and his dreamers this is why it's an exciting world to explore it's a long-form conversation I recommend you listen back to the episodes with Leonard Susskind Sean Carroll Michio Kaku max tegmark Eric Weinstein and Jim Gates you might be asking why talk to physicist if you're interested in AI to me creating artificial intelligence systems requires more than Python and deep learning it requires that we return to exploring the fundamental nature of the universe and the human mind theoretical physicists venture out into the dark mysterious psychologically challenging place of first principles more than almost any other discipline this is the artificial intelligence podcast if you enjoy it subscribe on YouTube get five stars an Apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M am as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number-one finance app in the App Store when you get it you scolex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app allows you to buy Bitcoin let me mention that the currency in the context of the history of money is fascinating I recommend a cent of money as a great book on this history debits and credits on Ledger's started around 30,000 years ago the US dollar of course created over two hundred years ago and Bitcoin the first decentralized cryptocurrency was released just over ten years ago so given that history cryptocurrencies still very much in its early days of development but it still is aiming to and just might redefine the nature of money if you get cash app from the App Store or Google Play and use the code Lex podcast you'll get ten dollars in cash app will also donate ten dollars the first one of my favorite organizations that's helping to advance robotics and STEM education for young people around the world and now here's my conversation with Lee Smolin what is real let's start with an easy question put another way how do we know what is real and what is merely a creation of our human perception and imagination we don't know you don't know this is science I presume were talking about science and we believe or I believe that there is a world that is independent of my existence in my experience about it my knowledge of it and this I call the real world so he said science but even bigger than science what sure sure I need not have said this is science I just was you know warming up warming up okay now that we're warmed up let's take a brief step outside of science is it completely a crazy idea to you that everything that exists is merely creation of our mind so like there's a few not many this is outside of science now people who believe sort of perception is fundamentally what's in our human perception the visual cortex and so on the the cognitive constructs that's being formed there is the reality and then anything outside is something that we can never really grasp that's the crazy idea too there's a version of that that is not crazy at all what we experienced is constructed by our brains and by our brains in an active mode so we don't see the raw world we see a very processed world we feel something was very processed through our brains and our brains are incredible but I still believe that behind that experience that mirror fail or whatever you want to call it there is a real world and I'm curious about it can we truly how do we get a sense of that real world is it through the tools of physics from theory to the experiments or can we actually grasp it in in some intuitive way that's more connected to our ape ancestors or is it still fundamentally the tools of math and physics that really allow us to grow so let's talk about what tools they are what you say are the tools of math and physics I mean I think we're in the same position as our ancestors in the caves or before the caves or whatever we find ourselves in this world and we're curious we also it's important to be able to explain what happens when there are fires when they're not fighters what animals and plants are good to eat and all that stuff and but we're also just curious we look up in the sky and we see the Sun and the moon and the stars and we see some of those move in we're good we're very curious about that I think we're just naturally curious so we make up this is my version of what I were we make up stories and explanations and where there are two things which I think are just true of being human we make judgments fast because we have to we're to survive we is that a tiger is that not a tiger and we go act we have to act fast on incomplete information so we we judge quickly and we're off and wrong but at least sometimes wrong which is all I need for this we're off in Iran so we fool ourselves and we fool other people readily and so there's lots of stories that get told and some of them result in a concrete benefit and some of them don't and so he said we're often wrong but what does it mean to be right right that's that's the that's a that's an excellent question to be right well since I'm I believe that there is a real world I believe that to be you can challenge me on this if you're not a realistic realistic somebody who believes in these this real objective world which is independent of our perception if I'm a realist I think that to be right is to come closer I think first of all this a relative scale is not right and wrong this writer more right than less right and you're more right if you come closer to an exact true description of that real world now can we know that for sure now in the scientific method is ultimately what allows us to get a sense of how close were getting to that real world no one to counts first of all I don't believe his scientific method ha I was very influenced when I was in graduate school by the writings of Paul fire Robin who was enough an important philosopher of science who argue that there is no scientific method there is or there is not there's not can you elaborate if sorry if you were going to but can you elaborate on the what does it mean for there not to be a scientific method this notion that I think a lot of people believe in in this day and age sure Paul Farben or he was a student of popper who taught opera Karl Popper and Farben argued both by logic and by historical exam well that you named anything that should be part of the practice of science say you should always make sure that your theories agree with all the data that's always meant it's already been taken and he'll prove to you that there have to be times when science contradicts when some scientist contradicts that advice for science to progress overall so it's not a simple matter I think that of science as a community and a people of people and as a community of people bound by certain ethical precepts precepts whatever that so in that community a set of ideas they operate under I'm meaning ethically of kind of the rules of the game they operate under don't lie report all your results whether they agree or don't agree with your hypothesis check the training of a scientist mostly consists of methods of checking because again we make lots of mistakes we're very error-prone but there are tools both on the mathematics and the experimental side to check and double-check and triple-check and a scientist goes through a training and I think this is part of it you can't just walk off the street and say yo I'm a scientist you have to go through the training and the training the test that lets you be done with the training is can you form a convincing case for something that your colleagues will not be able to shout down because the last did you check this and did you check that and did you check this and what about seeming contradiction with this and you've got to have answers to all those things or you don't get taken seriously and when you get to the point where you can produce that kind of defense and argument then they give you a PhD that's and you're kind of licensed you're still going to be questioned and you still may propose or publish mistakes but the community is gonna have to waste less time fixing your mistakes yes but if you can maybe linger on it a little longer what's the gap between the thing that that community does and the ideal of the scientific method was the scientific method is you should be able to repeat an experiment there's a lot of elements to what construes the the scientific method but the final result the hope of it is that you should be able to say with some confidence that a particular thing is close to the truth right but there's not a simple relationship between experiment and hypothesis or theory for example Galileo did this experiment of dropping a ball from the top of a tower and it falls right at the base of the tower and an Aristotelian would say Wow of course it falls right to the base of the tower that shows that the earth isn't moving while the ball is falling and Galileo says no wait there's a principle of inertia and has an inertia in the direction with the earth isn't moving and the tower and the ball in the or thought moves together when the principle of inertia tells you at his at the bottom it does look like therefore my principle of inertia is right you know Stettin Ian says no peristyle science is right the earth is stationary and so you gotta get an interconnected bunch of cases and work hard to line up and isolated centuries to make the transition from Aristotelian physics to the new physics it wasn't done till Newton in 1687 in 1687 so what do you think is the nature of the process that seems to lead to progress if we at least look at the long arc of science of all the community of scientists they seem to do a better job of coming up with ideas that engineers can then take on and build rockets with or build computers with or build cool stuff with I don't know a better job than what then this previous century so century by century we can talk about we'll talk about string theory and so on and kind of possible well you might think of as dead ends and and so on not do it we will string whistles straight but there's never less than science very often at least temporary dead ends but if you if you look sure at the through centuries you know the century before Newton in the century after Newton it seems like a lot of ideas came closer to the truth that then could be usable by our civilization to build the iPhone right to build cool things that improve our quality of life that's the progress I'm kind of referring to let me can I say that more precisely yes I think it's a it's important to get the time places right yes there was a scientific revolution that partly succeeded between about 1900 or late 1890s and into the 22 1930s 1940s and so and maybe some if she stretched it into the 1970s and the technology this was the discovery of relativity and that included a lot of developments of electromagnetism the conformation which wasn't really well confirmed into the 20th century that matter was made of atoms and the whole picture of nuclei with electrons going around this is early 20th century and then quantum mechanics was from 1905 it took a long time to develop to the late 1920s and then it was basically in final form and the basis of this partial revolution we can come back to why it's only a partial revolution is the basis of the technologies you mentioned all of I mean electrical technology was being developed slowly with this and in fact there's a close relation between development of electric electricity and the electrification of cities in the United States and Europe and so forth and the development of the science the size of the fundamental physics since the early 1970s doesn't have a story like that and so far there's not a series of triumphs and progresses and there's not a there's not any practical application so just to linger briefly on the early 20th century and the revolutions in science that happened there what was the method by which the scientific community kept each other in check about when you get something right when you get something wrong is experimental validation ultimately the final test it's absolutely necessary and the key things were all validated two key predictions of quantum mechanics and of the theory of electricity and magnetism so before we talk about Einstein now your new book before string theory quantum mechanics on let's take a step back at a higher level question what is that you mentioned what is realism what is anti realism and maybe why do you find realism as you mentioned so compelling realism is you is the belief in the in an external world independent of our existence our perception our belief our knowledge a realist as a physicist is somebody who believes that there should be possible some completely objective description of each and every process at the fundamental level which which describes and explains exactly what happens and why it happened that kind of implies that that system in a realist view is deterministic meaning there's no fuzzy magic going on that you can never get to the bottom you can get to the bottom of anything and perfectly describe it some people would say that I'm not interested in determinism but I I could live with the fundamental world which which had some chance in it so deep he said you could live with it but do you think God plays dice in our universe I think it's probably much worse than that in which direction I think that theories can change and theories unchanged without warning I think the future is open you mean the fundamental laws of physics can change you okay we'll get there I thought I thought we would be able to find some solid ground but apparently for the ground is the entirety of it temporarily so probably okay let's uh so realism is the idea that while the ground is solid you can describe it what's the role of the human being our beautiful complex human mind in the in realism do we have them are we just another set of molecules connected together in a clever way or the observer this is the observer our human mind consciousness have a role in this realism view of the physical universe there's two ways there's two questions you can be asking it does our conscious mind you are perceptions play a role in making things become in making things real or if things becoming that's question one question two is does this we can call it a naturalist view of the world that is based on realism allow a place to understand the existence of and the nature of perceptions and consciousness in mind and that's question two question two I do think a lot about and my answer which is nine answers I hope so but it certainly doesn't yet so what question one I don't think so but of course the answer to question one depends on question two right so I'm not up to question one yeah the question two is the thing that you can kind of struggle with at this time as what about the anti-realists so what flavour what are the different camps of anti-realist that you've talked about I think it'd be nice if you can articulate for the people for whom there is not a very concrete real world as there's divisions or there's a it's Messier then the realist view of the universe what are the different camps for the different views I'm I'm not sure I'm a I'm a good scholar and can talk about the different camps and analyze it but some many of the inventors of quantum physics were not realness weren't I realist in their scholarship they lived in a very perilous time between the two world wars and there were a lot of trends in culture which were going that way but in any case they said things like the purpose of science is not to give an objective realist description of nature's it would be in our absence this movie might be saying Niels Bohr the purpose of science is as an extension of our conversations with each other to describe our interactions with nature and we're free to invent and use terms like particle or wave or a causality or a time or space if they're useful to us and they carry some intuitive implication but we shouldn't believe that they actually have to do with what nature would be like in our absence which we have nothing to say about do you find any aspect of that because you kind of said that we human beings tell stories defined aspects of that kind of entire realist view of Niels Bohr compelling that were fundamentally are storytellers and then we create tools of space and time and causality and whatever this fun quantum mechanic stuff is to help us tell the story of our world sure I just would like to believe that is an aspiration for the other thing driving being what the the realist point of view do you hope that the stories will eventually lead us to discovering discovering the real world as it is yeah it's perfection possible by the way though oh well that's you mean will we ever get there and know that we're there yeah exactly that's not mine that's for people 5,000 years in the future we're certainly nowhere near there yeah do you think reality that exists our sight outside of our mind do you think there's a limit to our cognitive abilities is again descendants of apes for just biological systems is there a limit to our minds capability to actually understand reality sort of there comes a point even with the help of the tools of physics that we just cannot grasp some fundamental aspects of that again I think that's a question for 5,000 years in the future element I think there is a universality here I don't agree with David Deutsch about everything but I admire the way he put things in his last book and he talked about the role of explanation and he talked about the universality of certain languages of the universality of mathematics or of computing and so forth and he believed that universality which is something real which is it somehow comes out of the fact that the symbolic system in a mathematical system can refer to itself and in every I forget what that's called in reference back to itself and build in which he argued for a universality of possibility for our understanding whatever is out there but I'm I admire that argument but I it seems to me we're doing okay so far but we'll have to see whether there is a limit or not for now we got we got plenty to play with yeah there are things which are right there in front of us which we miss and I'll quote my friend Eric Weinstein in saying look Einstein carried his luggage Freud carried his luggage Marx carried his luggage Martha Graham carried her luggage etcetera Edison carried his luggage all these geniuses carry their luggage and not once before relatively recently did it occur to anybody to put a wheel on luggage and pull it and it was right there waiting to be invented for centuries so this is Erik Y Stein yeah what do the wheels represent are you basically saying that there's stuff right in front of our eyes that once we it just clicks we put the wheels in the luggage a lot of things will fall into place yes that I do I do and every day I wake up and think why can't I be that guy who was walking through the airport what do you think it takes to be that guy because link you said a lot of really smart people carried their luggage mm-hmm what just psychologically speaking so Erik wants that is a good example of a person who thinks outside the box yes who resists almost conventional thinking you're an example of a person who by habit by psychology by upbringing I don't know but resists conventional thinking as well just by Nature that's that's a compliment good so what do you think it takes to do that is that something you were just born with I doubt it well from my studying some cases because I'm curious about that obviously and just in a more concrete way when I start out in physics because I started a long way from physics so it took me a long not a long time but a lot of work to get to study it and get into so I did wonder about that and so I read the biographies and in fact I started with the autobiography of Einstein and Newton in Galileo and all those all those people and I think there's a couple of things some of it is luck being in the right place the right time some of it is stubbornness and arrogance which can easily go wrong yes and I know I know all of these are doorways if you go through them slightly at the wrong speed or any wrong angle they're their ways to fail but if you somehow have the right look the right confidence and arrogance caring I think Einstein cared to understand nature with ferocity and commitment that exceeded other people of his time so he asked more stubborn questions he asked deeper questions I think and there's a level of ability and whether ability is born in or can be developed at a sensor which can be developed like any of these things like musical talent dimension ego what's the role of ego in that process confidence confidence but you do in your own life if you found yourself walking that nice edge of too much or too little so being overconfident and therefore leading yourself astray or not sufficiently confident to throw away the conventional thinking of whatever the theory of the day of theoretical physics I don't know if I I mean I've contributed where I've contributed whether if I had had more confidence in some things I would have gotten further I don't know whether certainly hi I'm sitting here at this moment with very much my own approach to telling everything and I'm calm I'm happy about that but on the other hand I know people whose self-confidence vastly exceeds mine and sometimes I think it's justified and sometimes I think it's not justified your most recent book titled Einstein's unfinished revolution so I have to ask what is Einsteins unfinished revolution and also how do we finish it well that's something I've been trying to do my whole life but Einsteins unfinished revolution is the twin revolutions which invented relativity theory special and especially general relativity and quantum theory which he was the first person to realize in 1905 there would have to be a radically different theory which somehow realized to resolve the paradox of the duality of particle wave for photons and he was I mean people I think don't always associate I style with quantum mechanics because I think his connection with it founding as a one of the founders I would say of quantum mechanics he kind of put it in the closet is it well he didn't believe that the quantum mechanics as it was developed in the late 19th middle late 1920s was completely correct at first he didn't believe it at all then he was convinced that it's consistent but incomplete and that also is my view it needs for various reasons I can elucidate to have additional degrees of freedom particles forces something to reach the stage where it gives a complete description of each phenomena and as I was saying realism demands so what aspect of quantum mechanics bothers you and Einstein the most is it some aspect of the wavefunction collapse discussions the measurement problem is it the the the measurement problem I'm not gonna speak for Einstein but the measurement problem basically and the fact that what is the measurement problem sorry the basic formulation of quantum mechanics gives you two ways to evolve situations in time one of them is explicitly when no observer is observing or no measurement is taking place and the other is when a measurement or observation is taking place and they can treat they basically contradict each other but there's another reason why the revolution wasn't completed which is we don't understand the relationship between these two parts general relativity which became our best theory of space and time and gravitation and cosmology and quantum theory so for the most part general relativity describes big things quantum theory describes little things and that's the revolution that we found really powerful tools to describe big things and little things and it's unfinished because you wouldn't have two totally separate things and we need to figure out how to connect them so it can describe everything right and we either do that if we believe quantum mechanics as understood now is correct by bringing general relativity or some extension or general relativity that describes gravity and so forth into the quantum domain that's called quantize the theory of gravity or if you believe with Einstein that quantum mechanics needs to be completed and this is my view then part of the job of finding the right completion or extension of quantum mechanics would be one that incorporated space-time in gravity so where do we begin so first let me ask perhaps you can give me a chance if I could ask you some just really basic questions well there at all the basic questions and the hardest but you mentioned space-time what is space-time space-time you talked about a construction so I believe the space-time is a intellectual construction that we make of the events in the universe I believe the events are real and the relationships between the events which cause which are real but the idea that here is a four-dimensional smooth geometry which has a metric in the connection and satisfies the equations that Einstein wrote it's a good description to some scale it's a good approximation it captures some of what's really going on in nature but I don't believe it for a minute is fundamental so okay let's we're gonna allow me to linger on that so the universe has events events cause other events there's this idea of causality okay so that that's happy let's in my in your view Israel or hypothesis so the theories that I have been working to develop make that assumption so space-time you said four dimensional space is kind of the location of things and time is whatever the heck time is and you're saying that space-time is both space and time are emergent and not fundamental no sorry before you correct me what is mean to be fundamental or emergent fundamental means it's part of the description as far down as you go we have real yes as real as real it could be yeah so I think the time is fundamental and quote goes all the way down and space does not and the combination of them we use in general relativity that we call space-time also it is not but what is time then I think that time the activity of time is the continual creation of events from existing event so if there's no events there's nothing then there's not only not no time there's no nothing so so I believe that history universe has a history which goes to the past I believe that a future does not exist there's a notion of a present and a notion of the past and the past consists of is a story about events that took place to our past she said the future doesn't exist yes could you say that again can you try to give me a chance to understand that one more time so what the events caused other events what is this universe because we'll talk about locality in nonlocality good because it's the crazy I mean it's not crazy it's a beautiful set of ideas that you you propose but and if because all these fundamental I just like to understand it better what is him what is the past what is the future what is the flow of time even the era of time in our universe in your view and maybe it was an event right Oh an event is where something changes or where to I it's hard to say because it's a primitive concept in the event is a moment of time within space this is the the view and general relativity where two particles intersect in their paths or something changes in the path of the particle now we are postulating the theories I have two fundamental level a notion which is an elementary notion so it doesn't have a definition in terms of other things but it is something elementary happening and it's it doesn't have a connection to energy or matter or exchange of any ties to have the connection energies at that level yeah it involves and that's why the version of a theory of that I've developed with Marina Cortez and they say by the way I want to mention my collaborators because they've been at least as important in this work as I have marina Cortes in all the works since about 2013 2012-2013 about causality Carlos set and in the period before that Roberto mangabeira Unger who is a philosopher and a professor of law and that's in your efforts together with your collaborators to finish the unfinished revolution so yeah and focus on causality and focus on mental yes as fundamental to physics so and there's certainly other people we've worked with but those two people's thinking had a huge influence on my own thinking so in the way you describe causality that's what you mean of time being fundamental that causality is from the yes and what does it mean for space to not be fundamental to be though that's very good this is a level of description in which there events there are events create other events but there's no space they don't live in space they have an order in which they caused each other and that is part of the nature of time for us so but but there is an emergent approximate description and you asked me to find a version I didn't an emergent property is a property that arises at some level of complexity larger than and more complex than the fundamental level which requires some property to describe it which is not directly explicable or drivable is the word I want from the properties of the fundamental things and space is one of those things in a sufficiently complex universe space three-dimensional position of things emerged yes and we have this we saw how this happened in detail in some models both computationally and analytically ok so connected to space is the idea of locality yes that so we talked about realism so I I live in this world at like sports you know locality is a thing that you know you can affect things close to you and don't have an effect on things that are far away mm-hmm it's the thing that bothers me about gravity in general or action in a distance the same thing that probably bothered Newton or at least he said a little bit about it okay so what do you think about localities it's just a construct is it us humans just like this idea and are connected to it because we exist in it we need it for our survival but it's not fundamental I mean it seems crazy for it not to be a fundamental aspect of our reality it does and you comfort me and a sort of as a therapist like how do i I'm not a good therapist okay there are several different definitions of locality when you come to talk about locality in physics in quantum field theory which is a mixture of special relativity and quantum mechanics there is a precise definition of locality operative field operators corresponding to events in space-time which are space like separated can meet with each other as operators so in the in quantum mechanics you think about the nature realities fields and things that are close and if you have an impact on each other more than farther away that's yes that's very comforting that makes sense so that's a property of quantum field theory and it's well tested unfortunately there is another definition of local which was expressed by Einstein and expressed more precisely by John Bell which has been tested experimentally and found fail and this setup is you take two particles so one thing that's really weird about quantum mechanics is a property called entanglement you can have two particles interact and then share a property without it being a property of either one of the two particles and if you take such a system and then you magically make a measurement on particle a which is over here on my right side and particle B which is over here and what somebody else makes a measurement in a particle B you can ask that whatever is the real reality of particle B it not be affected by the choice the observer at particle a makes about what to measure not the outcome just the choice of the different things they might measure and that's a notion of locality because it assumes that these things are very far space like separated and it's going to take a while for any information about the choice made by the people here at a to affect the reality of B but you make that assumption that's called bell locality and you derive a certain inequality that some correlation functions of correlations have to satisfy and then you can test that pretty directly in experiments which create pairs of photons or other particles and it's wrong by many sigma in experiment in is a match so what what does that mean that means that that definition of locality I stated is false the the one that Einstein was playing with and the one the one that I stated that is it's not true that whatever is real about particle B is unaffected by the choice that the observer makes as to what to measure in particle a no matter how long they've been propagating and almost the speed of light or the speed of light away from each other it's no matter so like the distance between them well it's been tested of course if you want to have hope for quantum mechanics P in completely wrong and corrected by something that changes this it's been tested over a number of kilometers I don't remember whether it's 25 kilometers or 170 kilometers but so in trying to solve the unsolved revolution in trying to come up with a theory for everything is causality fundamental and breaking away from locality absolutely fun a crucial step so the in your book essentially those are the two things we really need to think about as a community especially the physics community has to think about this okay I guess my question is how do we solve how do we finish the unfinished revolution well that's I can only tell you what I'm trying to do and what I have abandoned yes it's not working as one ant smart ant in an ant colony yep or maybe dumb that's why he knows but anyway that's become my view of the we've had some nice theories invented there's a bunch of different ones both related to quantum mechanics related to quantum gravity there's a lot to admire in many of these different approaches but to my understanding they none of them completely solve the problems that I care about and so we're in a situation which is either terrifying for students or full of opportunity for the right student in which we've got more than a dozen attempts and I never thought I don't think anybody anticipated would work out this way which work partly and then at some point they have an issue that nobody can figure out how to go around or how to solve and that's the situation we're in my reaction to that is twofold one of them is to try to bring him we evolved into this unfortunate sociological situation in which there are communities around some of these approaches and to borrow again a metaphor from Eric they sit on top of hills in the landscape of theories and throw rocks in each other and as eric says we need two things we need people to get off their hills and come down into valleys and party and talk and become friendly and it's learning to say not know but but yes and yes your idea goes this far but maybe if we put it together with my idea we could go further yes so in that spirit of talked several times with Sean Carroll who's also written an excellent book recently and he kind of he plays around is a big fan of the many-worlds interpretation of quantum mechanics so I'm a troublemaker so let me ask well what's your sense of Sean and the idea of many-worlds interpretation I've read many the commentary back and forth you guys you guys are friendly respect each other but have a lot of fun debating I love Sean and he know I really he's not he's articulate and he's a great representative or an ambassador of science to the public in four different fields of science to each other he also like I do takes philosophy seriously and unlike what I do in all cases he has really done the homework he's read a lot he knows the people he talks to them he exposes his arguments to the to them and I did this mysterious thing that we so often end up on the opposite sides of with these issues it's fun though it's fun and I'd love to have a conversation about that but I would want to include him I see about many worlds well no I can tell you what I think about many I'd love to but actually on that let me pause Sean as a podcast you should definitely figure out how to talk to Sean I would I actually told Sean I would love to hear you guys just going back and forth so I hope you can make that happen eventually you and sure I want I won't tell you what it is but there's something that Sean said to me in June of 2016 that changed my whole approach to a problem but I have to tell him first yes and that that's they'll be great to tell him on his podcast so I can't invite myself to his podcast yeah okay we'll make it happen so so many worlds anyway um what's your view many worlds we talk about nonlocality many worlds is also a very uncomfortable idea or beautiful depending on your perspective it's it's very nice in terms of I mean there's a realist aspect to it I think you called it magical realism yeah it's just a beautiful line but at the same time it's very difficult to far eliminate human minds to comprehend so what it what are your thoughts about it let me start with the easy and obvious and then go to the scientific okay it doesn't appeal to me it doesn't answer the questions that I want answered and it does so to such a strong case that when Roberto mangabeira Unger and I began looking for principles and I want to come back and talk about the use of principles in science cuz that's the other thing I was gonna say and I don't want to lose that when we started looking for principles we made our first principle there is just one world that happens once but so it's it's not helpful to my personal approach to my personal agenda but of course I'm part of a community and my sense of the many-worlds interpretation I have thought a lot about it and struggled a lot with it is the following first of all there's Everett himself there's what's in Everett and there are several issues they're connected with the derivation of the born rule which is the rule that gives probabilities to events and the reasons why there is a problem with probability is that I mentioned the two ways that physical systems can evolve the many-worlds interpretation cuts off one the one having to do with measurement and just has the other one the Schrodinger evolution which is smooth evolution of the quantum state but the notion of probability is only in the second rule which we've thrown away so where there's probably come from and you have to answer the question because experimentalist use probabilities to check the theory now at first sight you get very confused because there seems to be a real problem because in the many-worlds interpretation the this talk about branches is not quite precise but I'll use it there is a branch in which everything that might happen does happen with probability one in that branch you might think you could count the number of branches in which things do and don't happen and get numbers that you can define as something like frequentist probabilities and Everett did have an argument in that direction but the argument gets very subtle when there are an infinite number of abilities as is the case in most quantum systems and my understanding although I'm not as much of an expert as some other people is that Everett's own proposal it's failed did not work there then it doesn't stop there there is an important idea that Everett didn't know about which is decoherence and it is a phenomenon that might be very much relevant and so a number of people post Everett have tried to make versions of what you might call many worlds quantum mechanics and this is a big area and it's subtle and it's not the kind of thing that I do well so I consulted that's why there's two chapters on this in the book I wrote chapter 10 which is about Everett's version in Chapter 11 there is a very good group of philosophers of physics in Oxford Simon Saunders David Wallace Harvey Brown and a number of others and of course is David Deutsch who is there and those people have developed and put a lot of work into a very sophisticated set of ideas designed to come back and answer that question they have the flavor of there are really no probabilities we admit that but imagine if you if the Everett story was true and you were living in that multiverse how would you make bets and so they they use decision theory from the theory of probability in gambling and so forth to shape a story of how you would bet if you were inside average in the universe and you knew that and there is a debate among those experts as to whether they or somebody else has really succeeded and when I checked in as I was finishing the book with some of those people like Simon who's a good friend of mine and David Wallace they told me that they weren't sure that any of them was yet correct so that's why I put in my book now to add to that sean has his own approach to that problem in what's called self referencing or self locating observers and it doesn't I just tried to read it and it didn't make sense to me but I didn't study it hard I didn't communicate with Sean I didn't do the things that I would do so I had nothing to say about in the book and I don't I don't know whether it's right or not let's talk a little bit about science you mentioned these principles in science what does it mean to have a principle and why is that important when I feel very frustrated about quantum gravity I like to go back and read history and of course Einstein and his achievements are a huge lesson and hopefully something like a role model and it's very clear the Einstein thought that the first job when you want to enter a new domain of theoretical physics is to discover and invent principles and then make models of how those principles might be applied in some experimental situation which is where the mathematics comes in so for Einstein there was no unified space in time Minkowski invented this idea of space-time Fry's time it was a model of his principles or his past humans and I've taken the view that we don't know the principles of quantum gravity I can think about candidates and I have some papers where I discuss different candidates and I'm happy to discuss them but my belief now is that those partially successful approaches are all models which might describe indeed some quantum gravity physics in some domain and aspect but ultimately could would be important because they model the principles and the first job is to tie down those principles so that's the approach that I'm taking so the so speaking of principles in your 2006 book the trouble with physics you criticized a bit string theory for taking us away from the rigors of the scientific method or whatever you would call it but what's the trouble with physics today and how do we fix it can I say how I read that book sure because I and I'm not this of course has to be my fault because you can't as an author to claim after all the work he put in this you were misread but I will I will say that many of the reviewers who were not personally involved in even many who were working on string theory or some other approach to quantum gravity told me communicate with me and told me they thought that I was fair and balanced was though was the way that was usually is so let me tell you what my purpose was in writing that book which clearly got diverted by because there was already a rather hard argument going on and this is on which topic on string theory specifically or in general and physics know more specifically than string theory so since we're in Cambridge can I say that we're doing this yeah Cambridge just to be clear Massachusetts and on Harvard campus right so Angie's rominger is a good friend of mine and has been for many many years and Andy so originally there was this beautiful idea that there were five string theories and maybe they would be unified into one and we would discover a way to break that symmetries of one of those string theories and discover the standard model and predict all the properties of standard model particles like their masses and charges and so forth coupling constants and then there was a bunch of solutions to string theory found which led each of them to a different version of particle physics with a different phenomenology these are called the khalaby Yau manifolds named after Yahoo is also here not certainly we've been friends at some time in the past anyway and then there were nobody was sure but hundreds of thousands of different versions of string theory and then Andy found there was a way to put a certain kind of mathematical curvature called torsion into the solutions and he wrote a paper of string theory with torsion in which he discovered there was and not formally uncountable but he was unable to invent any way to count the number of solutions are classified the diverse solutions and he wrote that this is worrying because doing phenomenology the old-fashioned way by solving the theory is not going to work because there's going to be loads of solutions for everything proposed phenomenology for anything the experiments just go now it hasn't quite worked out that way but nonetheless he took that worry to me he did he we spoke at least once maybe two or three times about that and I got seriously worried about that and this is just a little it's almost like an anecdote that inspired you're worried about string theory in general well I tried to solve the problem and I tried to solve the problem I was reading at that time a lot of biology a lot of evolutionary theory like lynn margulis and Steve Gould and so forth and I all right I could take your time to go through things that occurred to me maybe physics was like evolutionary biology and maybe the laws evolved and there was the Baris talked about a landscape a fitness landscape of DNA sequences or protein synthesis sequences or a species or something like that I took their concept and the word landscape from theoretical biology and made a scenario about how the universe as a whole could evolve to discover the parameters of the standard model and I'm happy to discuss that's called cosmological natural selection cosmological natural selection yeah so so the parameters of the standard model so it says the laws of physics are changing it this this idea would say that the laws of physics are changing in some way that echoes that of natural selection or just it adjusts in some way towards some goal yes and I published that I wrote the paper in 1880 or 1890 paper was published in 92 when I first book in 1997 the life of the cosmos was explicitly about that and I was very clear that what was important is that because you would develop an ensemble of universes but they were related by descent through natural selection almost every universe would share the property that it was its fitness was maximized to some extent were these close to maximum and I could deduce predictions that could be tested from that and and I worked all of that out and I compared it to the anthropic principle where you weren't able to make tests or make falsifications all of this was in the late eighties and early nineties that's a really compelling notion but how does that help you arrive I'm coming to whatever where the book came from yes so what we've got me I worked on string theory I also Don Luhan gravity and I was one of the inventors of the quantum gravity and because of my strong belief in some other principles which led to this notion of wanting a quantum theory of gravity to be what we call relational or background independent I tried very hard to make string theory backward independent and ended up developing a bunch of tools which then could apply directly to general relativity and that became a loop quantum gravity so the things were very closely related and have always been right closely related in my mind the idea that there were two communities one devoted to strings and one devoted to loops is nuts and this always been nuts okay so so anyway there's this nuts community of loops and strings that are all beautiful and compelling and mathematically speaking and what's the trouble with all that why is that why is there such a problem so what so I was interested in developing that notion of how science works based on a community and ethics that I told you about and I wrote a draft of a book about that which had several chapters on methodology of science and it was rather academically oriented a book in those chapters were the first part of the book the first third of it and you even find their remnants in what's now the last chapter last part of the trouble with physics and then I described a number of test cases case studies and one of them which I knew was the search for quantum gravity and string theory and so forth and I was unable to get that book published so somebody made the suggestion of flipping it around and starting with a story of string theory which was already controversial this was 2004-2005 but I was very careful to be detailed to criticize papers and not people you don't you won't find me criticizing individuals you'll find me criticizing certain writing but in any case here's what I regret let me make a program with y-yes I as far as I know with the exception of not understanding how large the applications to condensed matter say of a DMCA a DSC of T would get I think largely my diagnosis of string theory as it was then has stood up since 2006 what I regret is that the same critique I was using string theory as an example and the same critique applies to many other communities in science and all including and this is where I regret my own community that is a community of people working on quantum gravity outside string theory but and I considered saying that explicitly but I say that explicitly since I'm it's a small intimate community I would be telling stories and naming names of and making a kind of history that I have no right to write so I stayed away from that but was misunderstood but if I may ask is there a hopeful message for theoretical physics that we can take from that book sort of that looks at the community not just your your own work on now with causality and non locality but just broadly in understanding the fundamental nature of our reality what's your hope for the 21st century in physics well do we solve the problem it would solve the unfinished problem of my science this is that's certainly the the thing that I care about most in hopefully let me say one thing among the young people that I work with I hear very often and since a total disinterest in these arguments that we other scientists have and an interest in what each other is doing and this is starting to appear in conferences where the young people interested in quantum gravity make a conference may invite loops and strings and causal dynamical triangulations and causal set people and we're having a conference like this next week a small workshop at perimeter and I guess I'm advertising this and then in the summer we're having a big full-on conference which is just quantum gravity it's not strings it's not loops but the organizers and the speakers will be from all the different communities yes and this to me is very helpful that the different ideas are coming together at least people are expressing an interest in that there's a huge honor talking to you Lee thanks so much for your time today thank you thanks for listening to this conversation and thank you to our presenting sponsored cash app download it used coal export cast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and lex friedman and now let me leave you with some words from lee smolin one possibility is god is nothing but the power of the universe to organize itself listening I hope to see you next time you |
Ann Druyan: Cosmos, Carl Sagan, Voyager, and the Beauty of Science | Lex Fridman Podcast #78 | the following is a conversation with an Julianne writer producer director and one of the most important and impactful communicators of science in our time she co-wrote the 1980 science documentary series cosmos hosted by Carl Sagan whom she married in 1981 and her love for whom with the help of NASA was recorded as brainwaves on a golden record along with other things our civilization has to offer and launched into space on the Voyager 1 and Voyager 2 spacecraft that are now 42 years later still active reaching out farther into deep space than any human made object ever has this was a profound and beautiful decision and made as a creative director of NASA's Voyager interstellar message project in 2014 she went on to create the second season of cosmos called cosmos and spacetime Odyssey and in 2020 the new third season called cosmos possible worlds which is being released this upcoming Monday March 9th it is hosted once again by the fun and the brilliant Neil deGrasse Tyson Carl Sagan Annie Julian and cosmos have inspired millions of scientists and curious minds across several generations by revealing the magic the power the beauty of science I am one such curious mind and if you listen to this podcast you may know that Elon Musk is as well he graciously agreed to read Carl Sagan's words about the pale blue dot in my second conversation with him if you listened there was an interesting and inspiring twist at the end this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon I'll connect with me on Twitter at Lex Friedman spelled Fri DM aen as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this shows presented by cash app the number one finance app in the App Store when you get it use collects podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app allows you to send and receive money digitally peer-to-peer and security in all digital transactions it's very important let me mention the PCI data security standard that cash app is compliant with I'm a big fan of standards for safety and security PCI DSS is a good example of that where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions now we just need to do the same for autonomous vehicles and artificial intelligence systems in general so again if you get cash app from the App Store Google Play and use the code let's podcast you get ten dollars and cash up will also donate ten dollars the first one of my favorite organizations that's helping to advance robotics and STEM education for young people around the world and now here's my conversation with Ann Julianne what is the role of Science in our society well I think of what Einstein said when he opened the 1939 New York World's Fair he said if science is ever to fulfill its mission the way art has done it must penetrate its inner meaning must penetrate the consciousness of everyone and so for me especially in a civilization dependent on high technology and science one that spires to be democratic it's critical that the public has informed decision makers understand the values and the methods and the rules of science so you think about the what you just mentioned the values and the methods and the rules and maybe the technology that science produces but what about sort of the beauty the mystery of science well that you've touched on what I think is for me that's how my way into science is that for me it's much more spiritually uplifting the revelations of science collective revelations of you know really countless generations of searchers and a little tiny bit we know about reality is the greatest joy from me because I think it relates to the idea of love like what is love that is based on illusion about the other that's not love love is seeing unflinching the other and accepting with all your heart and to me knowing the universe as it is or the little bit that we're able to understand at this point is like is the purest kind of love and therefore you know how can our philosophy our religion if it's real isn't nature how can it really be true I just don't understand so I think you need science to get a sense of the real romance of life and the great experience of being awake in the cosmos so that the fact that we know so little the the humbling nature of that so and you kind of connect the love to that but isn't it also isn't it scary isn't it why is it so inspiring do you think why is it so beautiful that we know so little well first of all as Socrates thought you know knowing that you know is knowing really knowing something knowing more than others and it's the it's that voice whispering in our our heads you know you might be wrong which i think is not only it's really healthy because we're so imperfect we're human of course but also you know love to me is the feeling that you always want to go deeper get closer you can't get enough of it you can't get close enough deep enough so and that's what science is always saying as science is never simply content with its understanding of any aspect of nature it's always saying it's always finding that even smaller cosmos beneath so I I think the two are very much parallel so you said that love is not an illusion no it's not well what is love what is love is is knowing for me love is is knowing something deeply and still being completely gratified by it you know and wanting to know more so what is love what is loving someone a person let's say deeply is not idealizing them not putting some kind of subjective projection on them but knowing them as they are and so for me for me the only aperture to that knowing about nature the universe it's science because it has that error correcting mechanism that most of the stuff that we do doesn't have you know you could say the Bill of Rights is kind of an error correcting mechanism which I it's one of the things I really appreciate about this society in which I live to the extent that it's upheld and we keep faith with it and the same with science it's like we will give you the highest rewards we have for proving us wrong about something that's genius that's that's why that's why in only 400 years since Galileo's first look through a telescope we could get from this really dim fake this big apprehension of another world to sending our eyes and our senses there or even going beyond so it is it is it delivers the goods like nothing else you know it really it delivers the goods because it's always it's always self-aware of its ability I'm not topic I'd like to ask your opinion and a feeling I have that I'm not sure what to do with which is the the sceptical aspect of science so the modern skeptics community and just in general certain scientists many scientists maybe most scientists that apply the scientific method are kind of rigorous in that application and they it feels like sometimes miss out some of the ideas outside the reach of just slightly outside of the reach of science and they don't dare to sort of dream or think of revolutionary ideas that others will call crazy in this particular moment how do you think about the skeptical aspect of science that is really good at sort of keeping us in check keeping us humble but but at the same time sort of the kind of dreams that you and Carl Sagan have inspired in the world it kind of shuts it down sometimes a little bit yeah I mean I think it's up to the individual but for me no I was so ridiculously fortunate and that I my tutorial in science because I'm not a scientist and I wasn't trained in science was 20 years of days and nights with Carl Sagan and the Wonder I think the reason Carl remains so beloved well I think there are many reasons but at the root of it is the fact that his skepticism was never at the cost of his Wonder and his Wonder was never at the cost of his skepticism so he couldn't fool himself into believing something he wanted to believe because it made him feel good at the other but on the other hand he recognized that what science what nature is it's really it's good enough you know it's way better than our fantasies yeah and so if you if you're that kind of person who loves happiness loves life and your eyes are wide open and you read everything you can get your hands on and you spend years studying what is known so far about the universe then you have that capacity a really infinite capacity to be alive but all and also at the same time to be very rigorous about what you're willing to believe for Carl I don't think he ever felt that his skepticism cost him anything because again it comes back to luck he wanted to know when HM really was like not to inflict his you know preconceived notions on what he wanted it to be so you can't go wrong because it doesn't you know I mean you know I think the pale blue dot is that is a perfect example of this of his massive achievement is to say ok or the Voyager record is another example is here we have this mission our first reconnaissance of the outer solar system well how can we make it a mission in which we absolutely squeeze every drop of consciousness and understanding from it we don't have to be scientists and then be human beings I think that's the tragedy of Western civilization is that it's you know when it's one of its greatest gifts it has been science and yet at the same time it believing that we are the children of a disappointed father a tyrant who puts us in a maximum-security prison and calls it paradise who looks at us who watches us every moment and hates us for being our human selves you know and then most of all what is our great sin its partaking of the tree of knowledge which is our greatest gift as humans this pattern recognition this ability to to see things and then synthesize them and jump to conclusions about them and test those conclusions so I think the reason that in literature in movies the scientist is a figure of alienation a figure you know oh you see these biopics about scientists and yeah he might have been great but you know he was missing and ship you know he was a lousy husband he lacked you know the kind of spiritual understanding that maybe you know his wife had and it's always in the end they come around but to me that's that's a false dichotomy that we are you know to the extent that we are aware of our surroundings and understand them which is what science makes it possible for us to do we're even more alive so you mentioned a million awesome things there let's even just can you tell me about the Voyager 1 and 2 spacecraft and the and the interstellar message project and that whole just fascinating world leading up to one of my favorite subjects I love talking about it I'll never get over it yeah I'll never be able to really wrap my head around the the reality of it the truth of it what is it for so what's the Voyager spacecraft okay so voyagers 1 & 2 where our first reconnaissance mission of what was then considered the outer solar system and it was a gift of gravity the idea that swinging around these worlds gives you a gravitational assist yes which ultimately will send you out of the solar system to wander the Milky Way galaxy for one to five billion years so Voyager gave us our first close-up look of Jupiter Saturn Uranus Neptune it's discovered new moons it discovered volcanoes on Io it it its achievements are astonishing and remember this is technology from the early to mid-1970s and it's still active and it's still active we talked to Voyager a few days ago we talked to it in fact a year ago I think it was we needed to slightly change the attitude of the spacecraft and so we fired up its thrusters for the first time since 1987 do they work instantly they it was as if you had left your car in the garage in 1987 yeah and you could key in the ignition because you use keys then in the ignition and it turned over the first time you stepped on the gas and so that's the genius of the engineering yeah a Voyager and Carl was one of the key participants in in in imagining what its mission would be because it was a a gift actually of the fact that every hundred and 75 years plus or minus there is an alignment of the worlds and so you can't send two spacecraft to these are the worlds and photograph them and use your mass spectrometer and all the other devices unvoyage ER to to really to explore these worlds and it's the farthest spacecraft is the farthest human creation away from us today where is your one where's your one these two spacecraft not only gave us a our first close-up look hundreds of moons and planets these four giant these planets but also it told us the shape of the solar system as it moves through the galaxy because there were two of them going in different directions and they finally and they arrived in a place called the heliopause which is where the wind from the Sun the solar wind dies down and the interstellar medium begins and both voyagers were the first spacecraft that we had they could tell us when that happened so it's a consummate I think it's the greatest scientific achievement of the 20th century and engineering in some sense engineering I mean really you know voyagers and Voyager is doing this on less energy than you have in your toaster something like 11 watts so ok but because of this gravitational assist both voyagers were destined as I say to they were just they were personal they were supposed to function for a dozen years and now it's 42 years since launch and we're still talking to them so that's amazing but prior to launch almost a year hmm eight nine months prior to launch it was decided that since Frank Drake and Carl Sagan and Linda sauceman Sagan had created something called the Pioneer 10 plaque for the Pioneer spacecraft that preceded Voyager which was kind of like a license plate for the planet Earth you know a man and a woman hands up you know very very basic but very effective and it captured the imagination of people all over the world and so NASA turn to Frank and to Carl and said we'd like you to do a message for Voyager because if it's going to be circumnavigating the Milky Way galaxy for one to five billion years you know it's like 20 trips around the galaxy and there's a very small chance that a spacefaring civilization would be able to flag one of them down and so on board you see this exquisite golden disc with scientific hieroglyphics explaining our address and various basic scientific concepts that we believe that would be common to any spacefaring civilization and then beneath this exquisite golden disc is the Voyager record the golden record and it contains something like 118 photographs images of life on Earth as well as 27 pieces of music from all around the world many people describe it as the invention of world music world music was not a concept that existed before the Voyager record and we were determined to take our music not just from the dominant technical cultures but from all of the rich cultural heritage of the earth and there's a sound essay which is kind of using using a microphone as a camera to tell the story of the earth beginning with its geological sounds and moving into biology and then into technology and likes I think what you were getting at is that at the end of this sound essay I had asked Carl if it were in the making of the record it was my honor to be the creative director of the project if it was possible to if I had meditated for an hour while I was hooked up so that you know every single signal it was coming from my brain my body was recorded and then converted into into sound for the record was it possible that these putative extraterrestrials of the distant future of perhaps the billion years from now would be able to reconstitute this message and to understand it and he just big smile and so I did this and what were you thinking about in the meditation like what I mean it's such an interesting idea of recording as you think about things what were you thinking about so I was blindfolded and couldn't hear anything and I had made an a mental itinerary of exactly where I wanted to go I was truly humbled by the idea that these thoughts could conceivably touch the distant future that's incredible so it's 1977 there are some 60,000 nuclear weapons on the planet the Soviet Union and the United States are engaged in a you know to the death competition and so I began by trying to tell the history of the planet in you know to my limited ability what I understood about the story of the early existence of the war of the planet about the origin of life about the evolution of life about our the history of humans about our current at that time predicament about the fact that one in five of us was starving uh or unable to get potable water and so I sort of gave a kind of you know it's general a picture as I possibly could of our predicament and I also I was Perry newly within days of the moment when Carl and I fell in love with each other maybe we fell in love with each other long before because we'd known each other for years but it was the first time we had expressed our feelings for each other acknowledged did the existence of this yes because we're both involved with other people and it was a completely outside his morality in mine to even broach the subject but it was only days after that it happened and for me it was a Eureka moment it was in the context of finding that piece of Chinese music that was worthy to represent one of the oldest musical traditions on earth when those of us who worked on the Voyager record were completely ignorant about Chinese music and so that had been a constant challenge for me talking to professor's of Chinese music ethnomusicologist everywhere and all through the project desperately trying to find this one piece found the piece lived on the Upper West Side found the piece a professor at Columbia University gave it to me and he's of all the people I talked to everyone didn't said that's hopeless you can't do that that there can't be one piece of Chinese music but he was completely no problem I've got it and so he he told me the story of the piece which only made it an even greater candidate for the record which and I listened to it called Carl Sagan who was in Tucson Arizona addressing the American Society of newspaper editors and and I left him a message Hotel message center and he called me back an hour later and heard this beautiful voice say I came back to my hotel room and I find this message that any card and I asked myself why didn't you leave me this message ten years ago my heart was beating out of my chest I it was for me a kind of Eureka moment okay a scientific breakthrough yeah a truth a great truth it suddenly been revealed and of course I was awkward and didn't really know what to say and so I blurted something out like oh I've been meaning to talk to you about that Karl which wasn't really true I never would have talked to him about it we had been alone countless times we humans are so awkward in his beautiful moments and I just said for keeps and he thought for a very brief like a second and said you mean get married and I said yeah and he said yeah and we put down the phone and I literally was jumping around my apartment like a lunatic because it was so obvious you know it was something like of course and then the phone rang again and I thought damn no he's gonna say I don't know but he was like I just want to make sure that that really happened and I said yeah he said we're getting married and I said yeah we're getting married now this was June 1st 1977 the record had not been affixed to the spacecraft yet and there had been a lot of controversy about what we were doing I should say that there you know among the hundred and eighteen pictures was an image of a man and frontally completely naked naked and there was I believe a congressman on the floor that said NASA to send smut to the stars you know and so NASA really they got very upset they said you can't send a picture and we had done it so that it was so brilliant it was like this lovely couple completely naked and then the next image was kind of overlay schematic to show the fetus inside this woman that was developing and then that went off into you know additional imagery of human reproduction and it really hit me that how much we hate ourselves that we couldn't bear to be seen as we are so in some sense that congressman also represents our society perhaps his opposition should have been included as well yes well that's was one of the most vigorous debates during the making of the record with a you know the five or six people that we collaborated with was do we show do we only put our best foot forward or do we show Hiroshima outwits the Congo what we have done what do you think represents humanity if you kind of if you think about it did our darker moments are they essential for Humanity all the wars we've been through all the tortures and the suffering and the cruelty is that essential for happiness for beauty for creation generally he's really not essential for a happiness or beauty as for sure I mean it's part of who we are if we're gonna be real about it which is you know I I think we tell on ourselves even if we don't want to be real we you know I think that if you're a spacefaring civilization and you've gotten it together sufficiently you can move from world to world then I think they probably took one look at this derelict spacecraft and they knew that these were people in their techno logical adolescence yeah and they were just setting forth and they must have had these issues but you know because and so really you know that's the great thing about lying is that a lie only has a shelf life like if you make a great work of art that's a forgery people can be fooled immediately but 10 or 15 years 20 years later they start to look at it yeah you know that begin to realize of the lens our lens of our present is coloring everything that we see so you know I think it didn't matter that we didn't show our atrocities they would fill in the blanks they would fill in the blanks so let me sort of ask you've mentioned how likely it is that you and Carla did two souls like yours would meet in this vast world what are you views on how and why incredibly unlikely things like these nevertheless do happen it's purely to me a chance it's totally random it's adjust I mean but and the fact is is there some people or and it's happening every day right now some people are the random casualties of chance and that and I don't just mean the people who are being you know destroyed in childhood in more time I'm also or people who starve to death because of famine but also the people who um you know who who are not living to the fullest all of these things I think there's a rent my parents met on the subway in rush hour and so I'm only here were you because of the most random possible situation and so I've had this a sense of this even before I knew car I always felt this way that I only existed because of the generosity of the rush hour I know just all of the things all of the skeins of causality yeah it's interesting because you know that our shower is the source of stress for a lot of people but clearly in its moments it can also be a source of something beautiful it's right of strangers meeting and so on so everything everything is has the possibility of doing some fancy right so let me ask sort of a quick tangent on the Voyager so that this this beautiful romantic notion that Voyager 1 is sort of our farthest human reach into space if you think of what I don't know if you've seen but what Elon Musk did with the putting the roadster letting it fly out into space there's a sort of humor to it I think that's also kind of interesting but maybe you can comment on that but in general if now that we are developing what we were venturing out into space again in a more serious way what kind of stuff that represent since Voyager was launched should we send out as a follow-up is there things that you think that's developed the next in in the 40 years after that we should update the the spacefaring aliens of course now we could send the worldwide we could send everything that's on the world wide web we could send I mean you know that was a time when we're talking about phonograph records and transistor radios and you know so we tried to be to take advantage of the existing technology to the fullest extent you know the computer that was hooked up to me from my brain waves in my heart sounds while I was meditating was the size of a gigantic room and I'm sure it's not that didn't have the power of a phone as that phone has now so you know we could just I think we could let it all hang out you just stood send you know ever we I mean that's the wonder like I would send you know Wikipedia or something and not being a gatekeeper but this thing because we are you were also it's interesting because it one of the problems of the Internet of having so much information is it's actually the curation the human curation is still the powerful beautiful thing yeah so what you did with the record is actually is exactly the right process is kind of boiling down a massive amount of possibilities of what you could send into something that represents you know the better angels of our nature or represents our humanity so if you think about you know what would you send from the Internet as opposed to sending all of Wikipedia for example all human knowledge is there something just new that we've developed you think or fundamentally we're still the same kind of human species I think fundamentally were the same but we have a kind of way we are we have advanced a to an astonishing degree in our capacity for data retrieval and for transmission and so you know I would send YouTube I would send no it really like think of all that you know I I still feel so lucky that there's any great musical artists of the last hundred years who I revere I can just find them and watch them and listen to them and you know that's fantastic I also love how democratic it is that we each become curators that we each decide those things now I may not agree with you know those the choices that everyone makes but of course not because that's not the point the point is is that we are you know we've discovered largely through the internet that we are an intercommunicating organism and that can only be good so you could also send now cosmos yes I love it I will be proud I mean you're spoken about a very specific voice that cosmos I had in that it reveals the magical science I think you said shamanic journey of it and not the details of the latest breakthrough so on he's just revealing the magic can you try to describe what this voice of cosmos is with the with the follow-up and the new cosmos that you're working on now yes well a dream of cosmos is really like Einsteins quote you know it's the idea of the awesome power of science to be in absolutely everyone's hands you know it belongs to all of us it's not the preserve of a priesthood it's just just the community of science is becoming more diverse and being less exclusive than it was guilty of in the not so recent past the discoveries of science our understanding of the cosmos that we live in has really grown by leaps and bounds and probably we've learned more in the last hundred years about it you know the the tempo of discovery has picked up so rapidly and so the idea of cosmos from the 1970s when Carl and I and Steven Soter another astronomer first imagined it was that interweaving not only of these scientific concepts and revelations and using you know cinematic VFX to take the viewer on this transporting uplifting journey but also the stories of the searchers because the more I have learned about you know the process of science through my life with Carl and since the more I am really persuaded that it's that adherence to the facts and to that adherence to that little proximation that little bit of reality that we've been able to get our hands around is something that we desperately need and it doesn't matter if you are a scientist in fact the people it matters even more if you're not and since you know the level of science teaching has been fairly or unfairly maligned and the idea that once there was such a thing as a television network which of course has now evolved into many other things the idea that you could in the most democratic way make accessible to absolutely everyone and most especially people who don't even realize that they have an interest in a subject or who feel so intimidated by the jargon of science and it's kind of exclusive history the idea that we could do this and you know in season 2 of cosmos spacetime Odyssey we were in a hundred and eighty-one countries in the space of two weeks it was the largest rollout in television history which is really amazing for it there is no science-based program by the way just to clarify this series was rolled out so it was shown in in that many countries you said we were in well our show the show the show which is incredible I mean the the the hundreds of million whatever that number is that people that watched it it's just it's crazy it's so crazy Pat for instance uh my son had a cerebral hemorrhage here ago and the doctor who saved his life in a very dangerous situation when he realized that you know that Sam and I were who we were he said that's why I'm here you know he said if you come of age in a poor country like Colombia and Carl Sagan calls you to science when you're a child then then you know you go to medicine because the only Avenue open to you but that's why I'm here and I have heard that story and I hear that story I think every week how does that make you feel I mean I the the number of scientists I mean a lot of it is quiet right but the number of scientists cosmos has created is just countless I mean it probably touched a lives I don't know probably it could be a crazy number of the 90% of scientists or something I'd have been I was going to do that census because I because that's the month the greatest gratification because that's the dream of science and that's the whole idea is that if it belongs to all of us and not just a tiny few then we have some chance of determining how it's used and if it's only in the hands of people whose only whose only interests are the balance sheet or hegemony over other nations or things like that then it'll probably end up being a gun aimed in our heads but if it's distributed in the widest possible way a capability that we now have because of our technology then this chance is that that it'll be used with wisdom that's that's the dream of it so that's that's why we did the first cosmos we wanted to take not just as I say the scientific information but also tell the stories of these searchers because for us and for me it carrying on this a series in the second and third seasons the the primary interest was that we wouldn't tell a story unless it was a kind of a three-fer you know it was not just a way to understand a new sign a scientific idea but it was also a way to understand what if it matters what's true wow the world can change for us and how we can be protected and if it doesn't matter what's true then we're in grave danger because we have the capability to not only destroy ourselves and our civilization but to take so many species with us and I'd like to talk to you about that particular the sort of the dangers of ourselves in a little bit but sort of to linger on cosmos maybe for the first the 1980 in the 2014 follow-up what a what's a or one of the or several memorable moments from the creation of either of those seasons well you know the critical thing really was the fact that Seth MacFarlane became our champion because I had been with three colleagues I had been slapping around from network to network with a treatment for cosmos and every network said they wanted to do it but they wouldn't give me creative control and they wouldn't give me enough money to make it cinematic and to make it feel like you're really going on an adventure and so I think both of those things sorry in turn draw both these things are given what cosmos represents the the legacy of it and the legacy of Carl Sagan is essential control especially in the modern world I it's it's was wonderful the Assad control he did not really push it no I'm sure I know they would look at me like I was nuts you know and they probably must have entertained the idea that maybe I didn't really want to do it you know because that was afraid or something but I kept saying no and it wasn't until I met Seth MacFarlane and he took me to Fox and you Peter rice and said you know I'll pay for half the pilot if I have to you know and Peter rice was like put your money away and Seth said that yeah and and and and in every time since in the in the 10-year sense at every turn when we needed Seth to intervene on our behalf he stood up and he did it and so that was like in a way that is the you know the watershed for me of the everything that followed since and then I was so lucky because I know Steve and I Steve Souter and I written the original cosmos with Carl and were co-opted and collaborated on the treatment for a season 2 and then Brannon Braga came into our project at the perfect moment and has proven to be like just the really I have been so lucky my whole life I've collaborated I've been lucky with the people my collaborators have been extraordinary and so that was a critical thing but also to have you know for instance astonishing VFX supervisor who comes from the movies who heads the global Association of VFX people Jeff oaken and and then and you know I can rattle off ten more names I'd be happy to do that and it was that collaboration so the people were essential to the creation of absolutely I mean when it came down I have to say that when it came down to the vision of what the series would be that with me sitting in my home looking out the window and I'm you know really imagining like what I wanted to do can you pause on that for a second like what's that process because it you know cosmos is also it's grounded in science of course but it's also incredibly imaginative and the words used are carefully crafted thank you so what if you couldn't talk about the process of that the big picture imaginative thinking and so the rigorous crafting of words that like basically turns into something like poetry thank you so much for me these are rare occasions for human self-esteem the scientists that we bring to life in cosmos are people in my view who have everything we need to see us through this current crisis it's there very often they come they're poor they're a female they're outsiders who are not expected to have gifts that are so pretentious but they persevere and so you have someone like Michael Faraday who is comes from a family dysfunctional family of like 14 people and you know if never goes to university never learns the math but you know is the you know there's Einstein years later looking up at that picture of Faraday to inspire him there so it's you know if we had people we've had kind of humility and unselfishness who didn't want to patent everything me as you know Michael Faraday created the wealth of the 20th century with his various inventions and yet he never took out a single patent at a time when people were patenting everything because that was not what he was about and to me that's a kind of almost a saintliness vet says that you know that here's a man who finds in his life this tremendous gratification from searching and it's just so impressive to me and there are so many other people in cosmos especially the new season of cosmos which is called possible worlds possible beautiful title with possible worlds well I stole it from an author and a scientist with the 1940s but it it for me encapsulate not just you know the exoplanets that we'd begun to discover not just you know the the worlds that we might visit but also the world that this could be a hopeful vision of the future you asked me what is common to all three seasons of what is that voice it's the voice of hope it's a voice that says there is the future which we bring to life and I think fairly dazzling fashion that we can still have you know and in sitting down to imagine what this season would be the new season I'd be sitting where I live in Ithaca beautiful trees everywhere waterfalls yeah you're sitting there thinking well you can't how do you how do you awaken people I mean you can't yell at them and say we're all gonna die no it's not it doesn't help it doesn't help but I think if you give them a vision of the future that's not pie in the sky but something the ways in which science can be redemptive can actually remediate our future we have those capabilities right now as well as the capabilities to do things in the cosmos that we could be doing right now but we're not doing them not because we don't know how to how you know with the engineering or the material sciences or the physics we know all we need to know but we're a little bit paralyzed in some sense and you know we're like I always think we're like the toddler you know like we we left our mothers legs you know and scurried out to the moon yeah and we had a moment of wow we can do this and then we realized and somehow we had a failure of nerve and we went scurrying back to our mother and you know did things that really weren't gonna get us out there like a Space Shuttle things like that because it was a kind of failure of nerve so cosmos is about overcoming those fears we're now as a civilization ready to be a teenager venturing out into college we're returning back exactly you're exactly and that and that's one of my theories about our current situation is that this is our adolescence and I was a total mess I wasn't I was reckless irresponsible totally I didn't I was inconsiderate yeah I the reality of other people's feelings and the future didn't exist for me so why should a technologically adolescent civilization be any different but you know the vast majority of people I know made it through that period and went on to be more wise and that's what my hope is for our civilization on a sort of darker and more difficult subject in terms of so you talked about the cosmos being an inspiration for science and for us growing out of our messy adolescence but nevertheless there is threats in this world so do you worry about existential threats like emission nuclear weapons you worry about nuclear war yes and if you could also maybe comment I don't know how much you've thought about it but I was there's folks like Elon Musk or worried about the existential threats of artificial intelligence sort of our robotic computer creations sort of yeah resulting in us humans losing control so can you speak to the things that were you in terms of existential concern you know like not to think and not to look at for instance are rapidly burgeoning capability in artificial intelligence not and to see how sick so much of the planet is not to be concerned and sick isn't evil potentially well hum-hum is cruelty and brutality is happening at this very moment and I would put climate change higher up on that list because I believe that there are on Sene discoveries that we are making right now for instance all that methane that's coming out of the ocean floor that was sequestered because of the permafrost which is now melting you know I think there are other effects besides our greed and short-term thinking you know that we are triggering now with all the greenhouse gases were putting into the atmosphere and that worries me day at night I think about it every single every moment really because I really think that's how we have to be we have to begin to really focus on how grave the challenges to our civilization and to the other species that are it's the mass it this is a mass extinction event that we're living through and we're seeing it we're seeing news of it every day so what do you think about another touchy subject but what do you think about the politicization of science on topics like global warming embryonic stem cell research and other topics like it what's your sense why what do you mean by the politicization of meaning that if you say I think what you just said which is global warming as a serious concerns human caused arrange some detrimental effects currently there's a large percent of the population of the United States that would as opposed to listening to that statement would immediately think oh that's just a liberal talking point that's not I mean it's not so true anymore I don't think our problem is a population events skeptical about climate change because I think that the extreme weather fire events that we are experiencing with such frequency it's really gotten to people I think there I think that there are people in leadership position who choose to ignore it and to pretend it's not there but ultimately I think they will be rejected the question is will it be fast enough but you know this I don't I think actually that most people have really finally taken the reality of global climate change to heart and they look at their children and grandchildren and they don't feel good because they come from a world which was in many ways in terms of climate fairly familiar and benign and they know that we're headed in another direction and it's not just that it's what we do to the oceans the rivers the air you know I mean you asked me like what is what is the message of cosmos is it's that is that we have to think in longer terms you know I think of the Soviet Union United States in the Cold War and they're ready to kill each other over these two different views of the distribution of resources but neither of them has a form of human social organization that thinks in terms of a hundred years let alone a thousand years which are the timescales that science speaks in and that's part of the problem is that we have to get a grip on reality and where we're headed and it's I I'm not fatalistic at all but I do feel like it you and in setting out to to do this series each season we were talking about climate change in the original cosmos in Episode four and warning about inadvertent climate modification in 1980 you know and of course Carl did his PhD thesis on the greenhouse effect on Venus and he was painfully cognizant of it when a runaway greenhouse effect would do to our planet and not only that but the climb history of the planet which we go into in great detail in the series so yeah I mean how are we gonna get a grip on this if not through some kind of understanding of science can I just say one more thing about science is that its powers of prophecy are astonishing you launch a spacecraft in 1977 and you know where each and every planet in the solar system is going to be in every moon and you rendezvous with that flawlessly and you exceed the design specifications of the greatest dreams that the engineers and then you go on to explore the Milky Way galaxy and you do it I mean you know the climate scientists some of the people that we use stories we tell in cosmos they their predictions were and they were working with very early computer modeling capabilities they have proven to be so robust nuclear winter all of these things this is a prophetic power and yet how crazy that you know it's like it's like the Romans with their lead cooking pots and their lead pipes or the Aztecs ripping out their own people's hearts this is us we know better and yet we are acting as if it's business as usual yeah the beautiful complexity of human nature there's a speaking of which let me ask a tough question I guess because there's so many possible answers but what aspect of life here on earth do you find most fascinating from the origin of life the evolutionary process itself the origin of the human mind so intelligence the some of the technological developments going on now or us venturing out into space or space exploration what just inspires you inspire me but I just say that to me at the archana as I've gotten older to me the origin of life has become less interesting interesting well because I feel well not because it's more I think I understand I have a better grasp of how it might have happened do you think it was a huge leap so I may think it was that we are a byproduct of geophysics and I think it's not I my suspicion of course which is taking it with a grain of salt but my suspicion is that it happens more often and more places than we like to think because you know after all the history of our thinking about ourselves there's been a constant series of demotions in which we've had you realize no no so to me that's not at the center of the origin of consciousness is to me also not so amazing if you think of it as you know going back to these one celled organisms of a billion years ago who had had to know well if I go higher up I'll get too much Sun and if I go lower down not I'll be protected from you know UV rays things like that they have to know that or you I eat me I don't I mean even that I can see if you know that then knowing what we know now it's just it's not so hard to fathom it seems like you know there's I never believed there was a duality between our minds and our bodies and I think that even consciousness all those seem to me except my Oh physics chemistry yes geochemistry geophysics absolutely of you know it makes perfect sense to me and it doesn't make it any less wondrous it it doesn't wrap it at all of the wonder of it and so yeah I think that's amazing I think you know we tell the story of someone you have never heard of I guarantee and I think you're very knowledgeable of a subject who was more responsible for our ability to venture out to other worlds when anyone else and who was completely forgotten and so those are the kinds of stories I like best for cosmos you tell me who buy my book you know but I'm just saying like this person would be forgotten but you know I you just the way that we do cosmos is that like I ask a question to myself we really want to get to the bottom to the answer and keep going deeper deeper until we find what the story is a story that I know because I'm not a scientist if it moves me if it if it moves me then I want to tell it and other people be moved do you ponder mortality yes human mortality and maybe even your own mortality oh all the time I just turned 70 so yeah I think about it a lot I mean it's you know how could you not think about it but uh what do you make of this short life of ours a I mean let me ask uh sort of another way you've lost Carl and speaking of mortality if you could be if you could choose immortality you know it's possible that science allows us to live much much longer is that something you would choose for yourself for Carl Carl definitely I would you know in a nanosecond I would take that deal but not for me I mean if car were alive yes I would want to live forever but no would it be fun forever that's I don't know it's just that the universe is so full of so many wonderful things just discover that it feels like it wouldn't be fine but no I don't want to live forever I I have had a magical life I just might you know Mike craziest dreams have come true and I feel you know I forgive me but this crazy quirk of fate it put my most joyful deepest feelings feelings that decades later of 42 years later I know how real how true those feelings were everything that happened after that was an affirmation of how true those feelings were and so I don't feel that way I feel like I have gotten so much more than my share um not just my extraordinary life with Carl my family my parents my children my friends the places that I've been able to explore the but the books I've read the music ever heard so I feel like you know if it'd be much better if instead of working on the immortality of the lucky few of the most privileged people in the society I would really like to see a concerted effort for us to get us our act together you know that to me is topic a more pressing you know this possible world is the challenge and we're at a kind of moment where if we can we can make that choice so immortality doesn't really interest me I I really I love nature and I have to say that I I because I'm a product of nature I recognize that it's it's great gifts and it's great cruelty well I don't think there's a better way to end it anything thank you so much for talking to us at all it's wonderful really appreciate it I really enjoyed it I thought your questions but great thank you thanks for listening to this conversation with Andrew Ian and thank you to our presenting sponsor cash app downloaded use code let's podcast you get ten dollars and ten dollars we'll go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on YouTube give it five stars in a podcast supported on patreon or simply connect with me on Twitter Alex Friedman and now let me leave you some words of wisdom from Carl Sagan what an astonishing thing a book is it's a flat object made from a tree with flexible parts on which are imprinted lots of funny dark squiggles but one glance at it and you're inside the mind of another person maybe somebody dead for thousands of years across the millennia and authors speaking clearly and silently inside your head directly to you writing is perhaps the greatest of human inventions binding together people who never knew each other citizens of distant epochs books break the shackles of time a book is proof that humans are capable of working magic thank you for listening and hope to see you next time you |
Alex Garland: Ex Machina, Devs, Annihilation, and the Poetry of Science | Lex Fridman Podcast #77 | the following is a conversation with Alex garland writer and director of many imaginative and philosophical films from the dreamlike exploration of human self-destruction in the movie annihilation to the deep questions of consciousness and intelligence raised in the movie ex machina which to me is one of the greatest movies and artificial intelligence ever made I'm releasing this podcast to coincide with the release of his new series called devs that will premiere this Thursday March 5th on Hulu as part of FX on Hulu it explores many of the themes this very podcast is about from quantum mechanics to artificial life to simulation to the modern nature of power in the tech world I got a chance to watch a preview and loved it the acting is great Nick Offerman especially is incredible in it the cinematography is beautiful and the philosophical and scientific ideas explored are profound and for me as an engineer and scientist were just fun to see brought to life for example if you watch the trailer for the series carefully you'll see there's a programmer with a Russian accent looking at a screen with Python like code on it that appears to be using a library that interfaces with a quantum computer this attention and technical detail on several levels is impressive and one of the reasons I'm a big fan of how Alex weave science and philosophy together in his work meeting Alex for me was unlikely but it was life changing in ways I may only be able to articulate in a few years just as meeting spot many of Boston Dynamics for the first time planted a seed of an idea in my mind so did meeting Alex garland he's humble curious intelligent and to me and inspiration plus he's just really a fun person to talk with about the biggest possible questions in our universe this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars on Apple podcast supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D M am as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it you just code Lex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as one dollar since cash app allows you to buy Bitcoin let me mention that cryptocurrency in the context of the history of money is fascinating I recommend a cent of money as a great book on this history debits and credits on Ledger's started thirty thousand years ago the US dollar was created about two hundred years ago a Bitcoin the first decentralized cryptocurrency was released just over ten years ago so given that history cryptocurrency still very much in its early days of development but it still is aiming to and just might redefine the nature of money so again if you get cash up from the App Store Google Play and use collects podcast you'll get ten dollars in cash Apple also donate ten dollars the first one of my favorite organizations that is helping advanced robotics and STEM education for young people around the world and now here's my conversation with Alex garland you describe the world inside the shimmer in the movie annihilation as dreamlike I mean that it's internally consistent but detached from reality that leads me to ask do you think a philosophical question I apologize do you think we might be living in a dream or in a simulation like the kind that the shimmer creates we human beings here today yeah I want to sort of separate that out into two things yes I think we're living in a dream of sorts no I don't think we're living in a simulation I think we're living on a planet with a very thin layer of atmosphere and the planet is in a very large space and the space is full of other planets and stars and quasars and stuff like that and I don't think I don't think those physical objects I don't in the matter in that universe is simulated I think it's there we are definitely Soho problem is saying definitely but in my opinion just about that we I think it seems very like we're living in a dream state I'm pretty sure we are and I think that's just to do with the nature of how we experience the world we experience in a subjective way and the the thing I've learned most as I've got older in some respects is is the degree to which reality is counterintuitive and that the things that are presented to us as objective turn out not to be objective and quantum mechanics is full of that kind of thing but actually just day-to-day life is full of that kind of thing as well so so my understanding of the way the way the brain works is you you get some information hit your optic nerve and then your brain makes its best guess about what it's seeing or what it's saying it's seeing it may or may not be an accurate best guess it might be an inaccurate best guess and that that gap the best guess gap means that we are essentially living in a subjective state which means that we're in a dream state so I I think you could enlarge on the dream state in all sorts of ways but so yes dream state no simulation would be where I'd come down said going further deeper into that direction you've also described that world as psychedelia so on that topic I'm curious about that world on the topic of psychedelic drugs do you see those kinds of chemicals that modify our option as a distortion of our perception reality or a window into another reality no I think what I'd be saying is that we live in a distorted reality and then those kinds of drugs give us a different kind of distorted active yeah exactly they just give an alternate Distortion and I think that what they really do is they give they give a distorted perception which is a little bit more halide to daydreams or unconscious interests so if for some reason you're feeling unconsciously anxious at that moment and you take a psychedelic drug you'll have a more pronounced unpleasant experience and if you're feeling very calm or or happy my have a good time but but yeah so if I'm saying we're starting from a premise our starting point is or we were already in the slightly psychedelic state you what those drugs do is help you go further down an avenue or it may be a slightly different Avenue but that's what so in in a movie annihilation the the shimmer this alternate dreamlike state is created by I believe perhaps an alien entity of course everything is up to interpretation right but do you think there's in our world in our universe do you think there's intelligent life out there and if so how different is it from us humans well one of the things I was trying to do in annihilation was to to offer up a form of alien life that was actually alien because it would often seem to me that in the way we would represent aliens in in books or cinema or television or well you know any one of the sort of storytelling mediums is we would always give them very human-like qualities so they wanted to teach us about galactic federations or they wanted to eat us or they wanted our resources like our water or they want to enslave us or whatever it happens to be but all of these are incredibly human-like motivations and I was interested in the idea of an alien that was not in any way like us it didn't share it maybe it had a completely different clock speed maybe it's way so what we're talking about we're looking at each other we're getting information like hits our optic nerve our brain makes the best guess of what we're doing sometimes it's right something you know the thing we were talking about before what if this alien doesn't have an optic nerve maybe its way of encountering the space it's in is wholly different maybe it has a different relationship with gravity the basic laws of physics that operates under might be fundamentally different it could be a different timescale and so on yeah or it could be the same laws it could be the same underlying laws of physics you know it's a machine created it where it's it's a creature creating a quantum mechanical way it just ends up in a very very different place to the one we end up in so so part of the preoccupation with annihilation was to come up with an alien that was really alien and didn't give us and it didn't give us and we didn't give it any kind of easy connection between human and the alien because I think it was to do with the idea that you could have an alien that landed on this planet that wouldn't even know we were here and we might only glancingly know it was here that just be this strange point where the Venn diagrams connected where we could sense each other or something like that so in the movie first of all incredibly original view of what an alien life would be and she said in that sense it's a huge success let's go inside your imagination did the alien that alien entity know anything about humans when it landed No so the idea is you're both you're basically an alien life is trying to reach out to anything that might be able to hear its mechanism of communication or was it simply was it just basically they're biologists exploring different kinds of stuff they compete you see but this is the interesting thing as as soon as you say they're biologists you've done the thing of attributing human type motivations to it I I was trying to free myself from anything yes like that so all sorts of questions you might answer about this notion or alien I wouldn't be able to answer because I don't know what it was or how it works you know yeah I had I gave it some I had some rough ideas like it had a very very very slow clock speed and I thought maybe the way it is interacting with this environment is a little bit like the way an octopus will change its color forms around the space that it's in so it's sort of reacting to what it's in to an extent but the reason it's reacting in that way is indeterminate but it's Sobers Clark speed was slower than our human life Clark speed are inter but it's faster than evolution first Laura then our solution yeah give him the four billion years it took us to get here then yes maybe it started eight if you look at the human soul ization is a single organism yeah in that sense you know this evolution could be us you know the evolution of the living organisms on earth could be just a single organism and it's kind of that's its life is the evolution process that eventually will lead to probably the the heat death of the universe already something before that I mean that's that's just an incredible idea so you almost don't know you've created something that you don't even know how it works like yeah because anytime I tried to look into how it might work I would then inevitably be attaching my kind of thought processes into it and I wanted to try and put a bubble around it oh so no this is this is alien in its most alien form I have no real point of contacts so unfortunately I can't talk to Stanley Kubrick so I'm really fortunate to get a chance to talk to you on this particular notion I'd like to ask it a bunch of different ways and we'll explore in different ways but do you ever consider human imagination your imagination as a window into a possible future and that what you're doing you're putting that imagination on paper as a writer and then on screen as a director and that plants the seeds in the minds of millions of future and current scientists and so your imagination you putting it down actually makes it as a reality so it's almost like a first step of the scientific method that you imagining what's possible in your new series with ex machina is actually inspiring you know thousands of twelve-year-olds millions of scientists and actually creating the future of you've imagined well all I could say is that from my point of view it's almost exactly the reverse because I I see that pretty much everything I do is a reaction to what scientists are doing I am I'm an interested layperson and I I feel you know this individual I feel that the most interesting area that humans are involved in is science I think art is very very interesting but the most interesting is science and science is in a weird place because maybe around the time Newton was a alive if a very very interested lay person said to themselves I want to really understand what Newton is saying about the way the world works with a few years of dedicated thinking they would be able to understand that the sort of principles he was laying out I don't think that's true anymore I think that stopped being true now so I'm a pretty smart guy and if I said to myself I want to really really understand what is currently the state of quantum mechanics or string theory or or any of the sort of branching areas of it I wouldn't be able to I'd be intellectually incapable of doing it because because to work in those fields at the moment is a bit like being an athlete I suspect you need to start when you're 12 you know and if you if you start in your mid-20s start trying to understand in your mid-twenties then you're just never gonna catch up that's the way it feels to me so so what I do is I try to make myself open so the people that you're implying maybe I would influence it to me it's exactly the other way around these people are strongly influencing me I'm thinking they're doing something fascinating I'm concentrating and working as hard as I can to try and understand the implications of what they say and in some ways often what I'm trying to do is disseminate their ideas into a means by which it can enter a public conversation so so X Makana contains lots of name checks all sorts of existing thought experiments you know shadows on you know Plato's cave and Mary in the black white room and all sorts of different long-standing thought processes about sentience or consciousness or subjectivity or gender or whatever it happens to be and then and then I'm trying to marshal that into a narrative to say look this stuff is interesting and it's also relevant and this is my best shot at it so so I'm the one being influenced in my construction that that's fascinating of course you would say that because you're not even aware of your own that's probably what Kubrick will say too right is in describing why Hal 9000 is greater the way how 9000 is created as you're just studying what's but the reality when it when the specifics of the knowledge passes through your imagination I would argue that you're in incorrect in thinking that you're just disseminating knowledge that the the very act of your imagination consuming that science it creates something that creates the next step potentially creates the next step I certainly think that's true with 2001 a Space Odyssey I think at its best and if it fails prove that that's true of that it is best it plans something it's hard describe it it inspires the the next generation and it could be feel dependent so your new series is more a connection to physics quantum physics quantum quantum mechanics quantum computing and yet ex machina is more artificial intelligence I know more about AI my sense that AI is much much earlier in its in the depth of its understanding I would argue nobody understands anything to the depth that physicists do about physics in AI nobody understands AI that there is a lot of importance and role for imagination which they think you know we're in that what were Freud imagine the subconscious we're in that stage of of AI where there's a lot of imagination you didn't thinking outside the box yeah it's interesting the spread of discussions and the spread of my anxieties that exists about AI fascinate me the way in which some people are some people seem terrified about it what whilst also pursuing it and I've never shared that fear about AI personally but it but the the way in which it educates people and also the people who it agitates I find I find kind of fascinating are you afraid are you excited I use sad by the possibility let's take the existential risk of artificial intelligence by the possibility an artificial intelligence system becomes our offspring and makes us obsolete I mean it's a huge huge subject to talk about I suppose but but one of the things I think is that humans are actually very experienced at creating new life-forms because that's why you and I are both here and it's why everyone on the planet is here and so so something in the process of having a living thing that exists that didn't exist previously it's very much encoded into the structures of our life and the structures of our societies doesn't mean always get it right but it does mean we've learned quite a lot about that we've learned quite a lot about what the dangers are of allowing things to be unchecked and it's why we then create systems of checks and balances in our government and and so on and so forth I mean it's not say the other thing is it seems like there's all sorts of things that you could put into a machine that you would not be so with us we sort of roughly try to give some rules to live by and some of us then live by those rules to some don't and with a machine it feels like you could enforce those things so so partly because of our previous experience and partly because the different nature of a machine I just don't feel anxious about it I I'm more I just see all the good you know broadly speaking the good that can come from it but that that's just my that's just where I am on that anxiety spectrum you know it's kind of there's a sadness so we as humans give birth to other humans right petition in their generations and there's often in the older generation a sadness about what the world has become now I mean that's kind of yeah there is but there's a counterpoint as well which is the most parents would wish for a better life for their children so there may be a regret about some things about the past but broadly speaking what people really want is that things will be better for the future generations not worse and so a and then it's a question about what constitutes a future generation a future generation could involve people it also could involve machines and it could involve a sort of cross pollinated version of it too or any but but none of those things make me feel anxious and doesn't give you anxiety it does excite you like anything that does not anything that's new I I don't think for example I've got I my anxieties relate to things like social media that so I've got plenty of anxieties about that which is also driven by artificial intelligence in the sense that there's too much information to be able to do is that an algorithm has to filter that information and present to you so ultimately the algorithm a simple oftentimes simple algorithms can trolling the flow of information on social media so that's another it is yeah his but but at least my sense of it I might be wrong but my sense of it is that the algorithms have an either conscious or unconscious bias which is created by the people who are making the algorithms and and sort of delineating the areas to which those algorithms are going to lean and so for example the kind of thing I'd be worried about is that it hasn't been thought about enough how dangerous it is to allow algorithms to create echo chambers say but that doesn't seem to me to be about the AI or the algorithm it's it's the my IVA T of the people who are constructing the algorithms to do that thing if you see what I mean yes so a new series does then we could speak more broadly there's a let's talk about the people constructing those algorithms which be our modern society Silicon Valley those algorithms happen to be a source of a lot of income because of advertisements okay so let me ask sort of a question about those people are there current concerns and failures on social media they are naivety I can't pronounce that word well are they naive are they I use that word carefully but evil and intent or misaligned and intent I think that's a do they mean well and just go have a unintended consequence or is there something dark in them that that results in them creating a company results in that super competitive drive to be successful and those are the people that will end up controlling the algorithms at a guess I'd say there are instances of all those things so so sometimes I think it's naivety sometimes I think it's extremely dark and sometimes I think people are are not being naive or dark and and then in those instances are sometimes generating things that are very benign and and other times generating things that despite their best intentions are not very benign it's something I think the reason why I don't get anxious about AI high in terms of or at least hey is that have I don't know a relationship with some sort of relationship with humans is that I think that's the stuff we're quite well equipped to understand how to mitigate the problem is is is issues that relate actually to the power of humans or the wealth of humans and that's where that's where it's dangerous here and now so so what I see I'll tell you what I sometimes feel about Silicon Valley is that it's like Wall Street in the 80s it it's rabidly capitalistic absolutely rabidly capitalistic and it's rabidly greedy but whereas in the 80s the sense one had of Wall Street was that these people kind of knew they were sharks and in a way relished in being sharks and dressed in sharp suits and and and kind of lauded over other people and felt good about doing it Silicon Valley has managed to hide its voracious Wall Street like capitalism behind hipster t-shirts and you know cool cafes in the place where they set up their and and so that obfuscates what's really going on what's really going on is the absolute voracious pursuit of money and power so so that that's where I get shaky for me so that veneer and you explore that brilliantly that veneer of virtue that Silicon Valley has which they believe themselves I'm sure so okay I I hope to be one of those people and I believe that so as a maybe a devil's advocate term poorly used in this case what if some of them really are trying to build a better world I can't I'm sure I think some of them are I think I've spoken to once who I believe in their heart feel they're building a better work are they not able to no no no they may or may not be but it's just a zone with a lot of flying about and there's also another thing which is that this actually goes back to I always thought about some sports that later turned out to be corrupt in the way that the sport like who won the boxing match or how a football match got thrown or cricket match or whatever happened to me and I used to think well look if there's a lot of money and there really is a lot of money people stand to make millions or even billions you will find a corruption that's gonna happen so so it's it's in the nature of its of its voracious appetite that some people will be corrupt and some people will exploit and some people will exploit whilst thinking they're doing something good but there are also people who I think are very very smart and very benign and actually very self-aware and so I'm not I'm not trying to I'm not trying to wipe out the motivations of this entire area but I do it there are people in that world who scare the hell out of me yeah sure yeah I'm a little bit naive and that like I it I don't care at all about money and so I'm uh you you might be one of the good guys yeah but so the thought is but I don't have money so my thought is if you give me a billion dollars I would it would change nothing and I would spend it right away on on investing it right back and creating a good world but your intuition is that billion there's something about that money that maybe slowly corrupt the people around you there's somebody gets in that corrupts your souls of you the way you view the world money does corrupt we know that but but there's a different sort of problem aside from just the money corrupts you know thing that we're familiar with in throughout history and it's it's more about the sense of reinforcement an individual gets which is so it effectively works like the reason I earned all this money and so much more money than anyone else is because I'm very gifted I'm actually a bit smarter than they are or I'm a lot smarter than they are and I can see the future in the way they can't and maybe some of those people are not particularly smart they're very lucky or they're very talented entrepreneurs and there's a difference between it so in other words the the the acquisition of the money and power can suddenly start to feel like evidence of virtue yes and it's not evidence of virtue it might be evidence of completely different things as brilliantly put yeah yeah yeah that's brilliant put like so I think one of the fundamental drivers of my current morality let me just represent nerds in general the of all kinds is of constant self-doubt and the signals you know I'm very sensitive to signals from people that tell me I'm doing the wrong thing but when there's a huge inflow of money it's you're there you just put it brilliantly that that could become an overpowering signal that everything you do is right and so your moral compass can just get thrown off yeah and it's that that is not contained to Silicon Valley that's across the board in general yeah like I said I'm from Soviet Union the current president is convinced I believe actually he is he wants to do really good by the country and by the world but his moral clock may be our compass may be off because yeah I mean it's the interesting thing about evil which is the I think most people who do spectacularly evil things think themselves they're doing really good things that they're not they're thinking I am a sort of incarnation of Satan they're thinking yeah I've seen a way to fix the world and everyone else is wrong here I go in fact I uh I'm having a fascinating conversation with a historian of Stalin and he took power is what he actually got more power than almost any person in history and he wanted he didn't want power he just wanted he truly and this is what people don't realize he truly believed that communism will make for a better world absolutely and he wanted power he wanted to destroy the competition to make sure that we actually made communism work in the Soviet Union and that spread it across the world he was trying to do good I think it's it's typically the case yeah that that's what people think they're doing and I think that but you don't need to go to Stalin I mean Stalin sure I think Stalin but probably got pretty crazy but actually that's another part of it which is that the other thing that comes from being convinced of your own virtues that then you stop listening to the modifiers around you and that tends to drive people crazy it's it's other people that keep us sane and if you stop listening to them I think you go be mad so that that also that's funny a disagreement keeps us saying to jump back for an entire generation of AI researchers 2001 a Space Odyssey put an image the idea of human level superhuman level intelligence into their mind do you ever sort of jumping back to ex machina and talk a little bit about that you ever consider the audience of people who you who are build the system's the robot assisted scientists that build the systems based on the stories you create which I would argue I mean there's literally most of the top researchers about 40 50 years old and plus you know that's their favorite movie 2001 Space Odyssey and it really is in their work their idea of what ethics is of what is the target the hope the dangers of AI is that movie yeah right do you ever consider the the impact on those researchers when you create the the work you do certainly not with Xbox in relation to 2001 because I'm not sure I mean I'd be pleased if there was but I'm not sure in a way there isn't a fundamental discussion of issues to do with AI that isn't already and better dealt with by 2001 2001 does a very very good account of of the way in which an AI might think and also potential issues with the way the AI might think and also then a separate question about whether the AI is malevolent or benevolent and 2001 doesn't really is it's a slightly odd thing to be making a film when you know there's a pre-existing film which is not a really super job but there's a questions of consciousness embodiment and also the same kinds of questions could you because those are my two favorite AI movies so can you compare how all 9000 and Ava how 9,000 from 2001 Space Odyssey na or from ex machina the in your view from a philosophical perspective they've got different goals the to a eyes have completely different guy I think that's really the difference so in some respects ex machina took as a premise how do you assess whether something else has consciousness so it was a version of the Turing test except instead of having the machine hidden you you put the machine in plain sight in the way that we are in plain sight of each other and say now assess the consciousness and a way it was illustrating the the the way in which you'd assess the state of consciousness of a machine is this exactly the same way we assess the state of consciousness of each other and in exactly the same way that in a funny way your sense of my consciousness is is actually based primarily on your own consciousness that is also then true with the machine and and so it was actually about how much of the sense of consciousness is a projection rather than something that consciousness is actually containing and Plato's cave I mean this view really explored you could argue that how sort of space odyssey explores idea of the Turing test for intelligence or not test there's no test but it's more focused on intelligence and ex machina kind of goes around intelligence and says the consciousness of the human do you humanure by interactions more interesting more important more at least the focus of that particular particular movie yeah it's about the interior state and and what constitutes the interior state and how do we know it's there and actually in that respect ex machina is as much about consciousness in general as it is to do specifically with machine consciousness yes and it's also interesting you know thing you started asking about the dream state and I was saying well I think we're all in a dream state because we're all in a subjective state yeah one of the things that I became aware of with ex machina is that the way in which people reacted to the film was very based on what they took into the film so many people thought xmax magnet was a stet was the tale of a sort of evil robot who murders two men and escapes and she has no empathy for example because she's a machine whereas I felt no she was a conscious being with a consciousness different from mine but so what imprisoned and made a bunch of value judgments about how to get out of that box and there's a moment which is sort of slightly bugs me but nobody ever has noticed in its years after so I might as well say it now which is that after Ava has escaped she crosses a room and has she's crossing a room this is just before she leaves the building she looks over her shoulder and she smiles and I thought after all the conversation about tests but in a way the best indication you could have of the interior state of someone is if they are not being observed and they smile about something with they're smiling for themselves and that to me was evidence of Ava's true sentience whatever that sentience was but those really interesting she we don't get to observe a ver much or or something like a smile in any context except through interaction trying to convince others that she's conscious that's beautiful yeah exactly yeah but it was a small it in a funny way I think maybe people saw it as an evil smile like ha yeah I fooled them but actually it was just a smile and I thought well in the end after all the conversations about the test that was the answer to the test and then off she goes so if we align if we just deliver it a little a little bit longer on hell and Ava do you think in terms of motivation what was how's motivation is how good or evil is Ava good or evil Ava's good in my opinion and how is neutral because I don't think how is presented as having a sophisticated emotional life he has a set of paradigms which is that the mission needs to be completed I mean it's a version of the paperclip yeah you know the idea there is just it's a super intelligent machine but it's just performing a particular task yeah and in doing that tasks may destroy everybody on earth or may may achieve undesirable effects for us humans precisely but what if okay at very end you said something like I'm afraid Dave but that that maybe he is on some level experiencing fear or it may be this is the terms in which it would be wise to stop someone from doing the thing they're doing if you see what it means yes absolutely so it actually has funny so that's such of this is such a small short exploration of consciousness that I'm afraid and then you just with ex machina say okay we're going to magnify that part and then minimize the other part so that's that's a good way to sort of compare the two but if you could just use your imagination and if Ava sort of I don't know ran the Quran easy was President of the United States also has some power so what kind of world which you want to create if we here's you kind of say good and there is a sense that she has a really like I think there's a desire for better human to human interaction human robot interaction in her but what kind of world do you think she would create with that desire she also really it's a very interesting question that I'm gonna approach it slightly obliquely which is the if if a friend of yours got stabbed in a mugging and you then felt very angry at the person who'd done the stabbing but then you learned that it was a fifteen year old and the 15 year old both their parents redic today crystal meth and the kid had been addicted since he was 10 and he really never had any hope in the world and he'd been driven crazy by his upbringing and did the stabbing that would hugely modify and it would also make you worry about that kid then becoming president of America right and Ava has had a very very distorted introduction into the world so although there's nothing as it as it were organically within Ava that would lean her towards badness it's not the robots or sentient robots are bad she did not her arrival into the world was being imprisoned by humans so I'm not sure she'd be a great present the trajectory through which she arrived at her moral views you have some dark elements then but I like ever personally I like over and I think vote for her I'm having difficulty finding anyone to vote right now in my country or if I lived here in yours I am so that's a yes I guess because the competition she could easily do a better job than any of the people I'd worked her over Boris Johnson so what is a good test of consciousness just can we talk about consciousness a little bit more if something appears conscious is it conscious he mentioned the smile which is seems to be something done I mean that's a really good indication because it's a tree falling in the forest with nobody there to hear it but does the appearance from a robotics perspective of consciousness mean consciousness - you know I I don't think you could say that fully because I think you could then easily have a thought experiment which said we will create something which we know is not conscious but is going to give a very very good account of seeming conscious and so and and also it would be a particularly bad test where humans are involved because humans are so quick to project sentience into things that don't have sentience so someone could have their computer playing up and feel as if their computer is being malevolent to them when it clearly isn't and so so of all the things to judge consciousness us humans are better we're empathy machines so that so the flipside of that the argument there is because we just attribute consciousness to everything almost and anthropomorphize everything including Roombas the that maybe consciousness is not real that would just attribute consciousness to each other so you have a sense that there is something really special going on in our mind that makes us unique and gives us the subjective experience there's something very interesting going on in our minds I'm slightly worried about the word special because it it gets a bit it nudges towards metaphysics and maybe even magic in I mean in some ways something magic like which I don't think is there at all I mean if you think about there's an idea of called pants like ism that says consciousness is in everything whatever but as brother yeah so the idea that that there is a thing that it would be like to be the son yeah no I don't buy that I think that consciousness is a thing did my sort of broad modification is that usually the more I find out about things the more illusory our instinct is and is leading us into a different direction about what that thing actually is that that happens it's in modern science that happens a hell of a lot whether it's to do with how even how big or small things are so so my sense is that consciousness is a thing but it isn't quite the thing or maybe very different from the thing that we instinctively think it is so it's there it's very interesting but we may be in it's sort of quite fundamentally misunderstanding it for reasons that are based on intuition so I have to ask this is this kind of an interesting question the ex machina for many people including myself is one of the greatest AI films ever made well it's number two for me thanks yeah number one I'd really have to was anyway yeah whenever you grow up with something right you may grow up for something it's it's an it's in the wood but there's uh one of the things that people bring up and can't please everyone including myself this is what I first reacted to the film is the idea of the lone genius this is the the criticism that people say sort of me as an AI researcher I'm trying to create what what what nathan is trying to do so there's a brilliant series called Chernobyl yes this one tested how so you spec talk I think I mean as eyes are I mean they got so many things brilliant right but one of the things again the criticism there yeah great nice place with lots of people who need your one character that represents all nuclear scientists you wanna comb yet you know it's a composite character that presents all scientists is this what you were is this the way you were thinking about that or is it just simplifies the storytelling how do you think about the lone genius well I'd say this the series I'm doing at the moment is a critique in part of the lone genius concept so yes I'm sort of oppositional and either agnostic or atheistic about that as a concept I mean they're not entirely you know where the lone lone is the right word broadly isolated but Newton clearly exists in a sort of bubble of himself in some respect such as Shakespearean do you think we would have an iPhone without Steve Jobs I mean how much Steve Jobs clearly isn't alone genius because because there's too many other people in the sort of superstructure around him who are absolutely fundamental to to that journey are you saying Newton but that's a scientific so there's an engineering element to building Ava but just to say what ex machina is is really it's a thought experiment I mean so it's a construction of putting four people in a house nothing about ex machina adds up in all sorts of ways in as much as that who built the machine parts did the people building the machine parts know what they were creating and how did they get there and it's a thought experiment yes so it doesn't it doesn't stand up to scrutiny of that sort I don't think it's actually that interesting of a question but it's brought up so often that I had to ask it because that's exactly how I felt after what you know there's something about there was almost a defense I got wash your movie the first time in at least for the first little while in a defensive way like how dare this person try to step into the AI space and try to beat Kubrick that's the way I was thinking like this because it comes off as a movie that really is going after the deep fundamental questions about AI so there's a there's a kind of a you know nerds do psyche is automatically searching for the for the flaws and I I decide exactly the same I think in annihilation and the other movie the I was be able to free myself from that much quicker that it's a it is a thought experiment there's you know who cares if there's batteries that don't run out right those kinds of questions that's the whole point yeah but I bits nevertheless something I wanted to bring up it yeah it's a foot it's the first thing to bring up for me the you you had all the lone genius thing for me it was actually people always said ex machina makes this big leap in terms of where AI has got to and so what pay I would look like if it got to that point there's another one which is just robotics I mean look at the way Ava walks around the rooms like forget it building that it's that that's that's also got to be a very very long way often if you did get that would it look anything like that it's a thought experiment actually it's figure we I think the way as a ballerina Alicia vikander brilliant actress actor that moves around that we're very far away from creating that but the way she moves around is exactly the definition of perfection for roboticist it's like smooth and efficient so it is where we want to get where I believe like I think because so I hang out with a lot of like human robotics people they love elegant smooth motion like that that's their dream so the way she moved is actually what I believe that would dream for a robot to move it might not be that useful to move that sort of that way but that is important the definition of perfection in terms of movement drawing inspiration from real life so for devs for ex machina look at characters like Elon Musk what do you think about the various big technological efforts of Elon Musk and others like him and that he's involved with such as Tesla SpaceX your link do you see any of any of that technology potentially defining the future worlds you create in your work so Tesla's automation SpaceX is space exploration your link is brain machine interface somehow merger of biological and electric systems I'm in a way I'm influenced by that almost by definition because that's the world I live in and this is the thing that's happening in that world and I also feel supportive of it so I think I think amongst various things Elon Musk has done I'm almost sure he's done a very very good thing with Tesla for all of us it's really kicked all the other car manufacturers interfaces kicked the fossil fuel industry in the face and and they needed kicking in the face and he's done it so and and so that's the world he's part of creating and I live in that world just bought a Tesla in fact and so does that play into whatever I then make in some ways it does partly because I try to be a writer who quite often filmmakers are in some ways fixated on the films they grew up with and they sort of remake those films in some ways I've always tried to avoid that and so I looked at the real world to get inspiration and as much as possible sort of by living I think and so so yeah I'm sure which of the directions do you find most exciting space trouble space travel so you haven't really explored space travel in your work you've said you've said something like if you had unlimited amount of money I think I now read at a ma that you would make like a multi-year series space Wars or something like that so what what is it that excites you about space exploration well because if we have any sort of long-term future it's that it just simply is that if energy and matter are linked up in the way we think they're linked up will run out if we don't move so we got to move and but but also how can we not it's it's built into us to to do it or die trying I was on Easter Island a few months ago which is as I'm sure you know in the middle of the Pacific and and difficult for people to have got to but they got there and I did think a lot about the way those boats it must have set out into something like space it was the ocean and and how sort of fundamental that was to the way we are and it it's the one that most excites me because it's the one I want most to happen it's the thing it's the place where we could get to is like in a way I could live with us never really unlocking fully unlocking the nature of consciousness I like to know I'm really curious but if we never leave the solar system and if we never get further out into this galaxy or maybe even galaxies beyond our galaxy that that would that feel sad to me because because it's so limiting yeah there's something hopeful and beautiful bar reaching out any kind of exploration reaching out across earth centuries ago and reaching out into space so what do you think about colonization of Mars so go to Mars does that excite you the idea of a human being stepping foot on Mars it does it absolutely does but in terms of what would really excite me it would be leaving this solar system in as much as that I just think I think we already know quite a lot about Mars and but yes listen if it happened that would be I hope I say in my lifetime I really hope I say in my lifetime I do it would be a wonderful thing without giving anything away but the series begins with the use of quantum computers a new series does begins with the use of quantum computers to simulate basic living organisms or actually I don't know if it's quantum computers are used but basic living organisms simulated on a screen and yeah the cool kind of demo yeah that's right they're using yes they are using a quantum computer to simulate a nematode pill so returning to our discussion of simulation or thinking of the universe as a computer do you think the universe is deterministic is there a free will so with the qualification of what do I know because I'm a layman right layperson but with big imagination thanks with that qualification yeah I think the universe is deterministic and I see absolutely I I cannot see how freewill fits into that so so yes deterministic no free will that would be my position and how does that make you feel it partly makes me feel that it's exactly in keeping with the way these things tend to work out which is that we have an incredibly strong sense that we do have free will and just as we have an incredibly strong sense that time is a constant and turns out probably not to be the case or definitely in the case of time but but but it's the the problem I always have with free will is that it gets I can never seem to find the place where it is supposed to reside and yet you explore just but a very very but we have something we can call free will but it's not the thing that we think it is but free was so what we call free will is just what they call it as the illusion of it and that's a subjective experience of yeah the yeah yeah which is a useful thing to have and it partly it partly comes down to although we live in a deterministic universe our brains are not very well equipped to fully determine the deterministic universe so we're constantly surprised and feel like we're making snap decision decisions based on imperfect information so that feels a lot like freewill it just isn't it would be might that's why I guess so in that sense your sort of sense is that you can unroll the universe forward or backward and you will see the same thing and you would I mean that notion yeah sort of sort of but yeah sorry go ahead I mean that notion is a bit uncomfortable to think about that it's good you can roll it back and and forward and well if you were able to do it it would certainly have to be a quantum computer yeah something that worked in a quantum mechanical way in order to understand a quantum mechanical system I I guess but but and so that unrolling there may be a multiverse thing where there's a bunch of branching what will exactly because it wouldn't follow that every time you roll it back or forward you'd get exactly the same result which is another thing that's hard to rapamycin fact yeah but but but that yes it but essentially what you just described that the the yes forwards and yes backwards but you might get a slightly different result works very different though or very different along the same lines well you've explored some really deep scientific ideas in this new series and I mean it's just in general you're unafraid to to ground yourself and some of the most amazing scientific ideas of our time what what are the things you've learned or ideas you find beautiful mysterious about quantum mechanics multiverse string theory quantum computing that you've learned well I would have to say every single thing I've learned is beautiful and one of the motivators for me is that I think that people tend not to see scientific thinking as being essentially poetic and lyrical but but I think that is literally exactly what it is and I think the idea of entanglement or the idea of superpositions or the fact that you could even demonstrate a superposition or have a machine that relies on the existence of super positions in order to function to me is is almost indescribable beautiful I it it it fills me with all it fills me with awe and also it's not it's not just a sort of grand massive or of but it's also delicate it's very very delicate and subtle and it has these beautiful sort of nuances in it and also these completely paradigm changing thoughts and truths so so it's it's as good as it gets as far as I can tell so so so broadly everything that doesn't mean I believe everything I read quantum physics because because obviously a lot of the interpretations are completely in conflict with each other and who knows whether string theory will turn out to be a good description or not but but the beauty in it it seems undeniable and and I do wish people more readily understood how beautiful and poetic science I would say Sciences poetry in terms of quantum computing being used to simulate things or just in general the idea of simulating simulating small parts of our world which actually current physicists are really excited about simulating small quantum mechanical systems on quantum computers but scaling that up to something bigger like simulating life-forms how do you think what are the possible trajectories of that going wrong or going right if you if you unroll it into the future well if a bit like Ava and her robotics you park the the sheer complexity of what you're trying to do the the issues are I think I think it will have a profound it if you were able to have a machine that was able to project forwards and backwards accurately it would in an empirical way show it would demonstrate that you don't have free will so the first thing that would happen is people would have to to really take on a very very different idea of what they were the thing that they truly truly believe they are they are not and so that that I suspect would be very very disturbing to a lot of people do you think there has a positive or negative effect on society the the realization that you are not you cannot control your actions essentially I guess is the way that could be interpreted yeah although in some ways we instinctively understand that already because in the example I gave you of the kid in the stabbing we would all understand that that kid was not really fully in control of their actions so it's not an idea that's entirely alien to us but I don't know we understand that I think there's a bunch of people who see the world that way but not everybody yes true i but what this machine would do is is prove it any doubt because someone would say well I don't believe that's true and then you'd predict well in 10 seconds you're going to do this and they'd say no no I'm not and then they'd do it and then determine is would have played its part but I or something like that but actually the exact terms of that thought experiment probably wouldn't play out but but still broadly speaking you could predict something happening in another room sort of unseen I suppose the foreknowledge would not allow you to affect so what effect would that have I think people would find it very disturbing but then after they'd got over their sense of being disturbed which by the way I don't even think you need a machine to to take this idea on board but after they've got over that they'd still understand that even though I have no free will and my actions are in effect already determined I still feel things I I still care about stuff I remember my daughter saying to me wish it she'd got hold of the idea that my view of the universe made it meaningless and she said well then it's meaningless and I said well it I can prove it's not meaningless because you mean something to me and I mean something to you so it's not completely meaningless because there is a bit of meaning contained within this space and so with a lack of free will space you could think well this robs me of everything I am and then you'd say well no it doesn't because you still like eating cheeseburgers and you still like going to see the movies and so so how big a difference does it really make but I think I think initially people would find it very disturbing I think I think that what would come if you could really unlock with a determinism machine everything there'd be this wonderful wisdom that would come from and I'd rather have that than not so that's a really good example of a technology revealing to us human something fundamental about our world about our society so it's it's almost this creation is helping us understand ourselves in the the thing to be said about artificial intelligence so what do you think us creating something like Ava will help us understand about ourselves how will that change society well I would hope it would teach us some humility humans are very big on exceptionalism you know America is is constantly proclaiming itself to be the greatest nation on earth which it may feel like that if you're an American but it may not feel like that if you're from Finland because there's all sorts of things you dearly love about Finland and exceptionalism is usually probably not always if we both sat here we could find a good example of something there isn't but as a rule of thumb and and and what it would do is it would teach us some humility and about you know actually often that's what science does in a funny way it makes us more and more interesting but it makes us a smaller and smaller part of the thing that's interesting and I don't mind that humility at all I I don't think it's a bad thing our excesses don't tend to come from humility you know our excesses come from the opposite megalomania we tend to think of consciousness as having some form of exceptionalism attached to it I suspect if we ever unravel it it will turn out to be less than we thought in a way and perhaps your very own Exceptionalist assertion earlier on in our conversation that consciousness is something belongs to us humans or not humans belong organisms maybe you will one day find out that consciousness is in everything and that will yeah will humble you exact if that was true it would certainly humble me although maybe almost maybe I don't know I don't know what effect that would have aye-aye-aye sort of I mean my understanding of that principle is along the lines of say that that an electron has a preferred state or it may or may not pass through a bed of glass it may reflect off or it may go through or something like that and and so that feels as if a choice has been made and but if if I'm going down the fully deterministic routes I would say there's just an underlying determinism that has defined that that is defined the preferred state or the reflection or non reflections but look yeah you're right if if if it turned out that there was a thing that it was like to be the Sun then I would I'd be amazed and humbled I'd be happy to be both it sounds pretty cool and they'll be you'll say the same thing as you said to your daughter but it's nevertheless feels something like to be me and that that's pretty damn good yeah so Kubrick created many masterpieces including The Shining dr. Strangelove Clockwork Orange but to me he will be remembered I think to many a hundred years from now for 2001 a Space Odyssey I would say that's his greatest film I agree you are incredibly humble I've listened to a bunch of your interviews and I really appreciate that you're humble in your creative efforts in your work but if I were to force you a gunpoint keep it with God you don't know that the mystery is to imagine 100 years out into the future what will Alex Carlin be remembered for from something you've created already or feel you may feel somewhere deep inside you may still create well ok well I'll take I'll take the question in the spirit was asked but very generous gunpoint yeah what what I what I try to do so therefore what I hope yeah if I remembered what I might be remembered for is is as someone who who participates in a conversation and I think that often what happens is people don't participate in conversations they make proclamations they make statements and people can either react against the statement or can fall in line behind it and I don't like that so I want to be part of a conversation I take as a sort of basic principle I think I take lots of my cues from science but one of the best ones it seems to me is that when a scientist has something proved wrong that they previously believed in they then have to abandon that position so I'd like to be someone who is allied to that sort of thinking so part of an exchange part of an exchange of ideas and the exchange of ideas for me is something like people in your world show me things about how the world work and then I say this is how I feel about what you've told me and then other people can react to that and it's it's not it's not to say this is how the world is it's just to say it is interesting to think about the world in this way and the conversation is one of the things I'm really hopeful about in your works that the conversation you're having is with the viewer in the sense that you you're bringing back you and several others but you very much so sort of intellectual depth to cinema to now series sort of allowing film to be something that yeah sparks a conversation is a conversation lets people think allows them to think but also crew it's very important for me that if that conversation is going to be a good conversation what that must involve is that someone like you who understands AI and I imagine understands a lot about quantum mechanics if they then watch the narrative feels yes this is a fair account so it is a worthy addition to the conversation that for me is hugely important I'm not interested in getting that stuff wrong I'm only interested in trying to get it right Alex it was truly an honor to talk to you I really appreciate I really enjoy it thank you so much thank you Thanks thanks for listening to this conversation with Alex Garland and thank you to representing sponsor cash app downloaded use code Lex podcast you'll get ten dollars and $10 will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on youtube give it five stars in a podcast supported on patreon are simply connect with me on Twitter at Lex Friedman and now let me leave you with a question from Ava the central artificial intelligence character in the movie ex machina that she asked during her Turing test what will happen to me if I fail your test for listening and hope to see you next time you |
John Hopfield: Physics View of the Mind and Neurobiology | Lex Fridman Podcast #76 | the following is a conversation with john hopfield professor Princeton whose life's work weave beautifully through biology chemistry neuroscience and physics most crucially he saw the messy world of biology through the piercing eyes of a physicist he's perhaps best known for his work on associative neural networks now known as hopfield networks that were one of the early ideas that catalyzed the development of the modern field of deep learning as his 2019 Franklin medal in physics award States he applied concepts of theoretical physics to provide new insights and important biological questions in a variety of areas including genetics and neuroscience was significant impact on machine learning and as John says in his 2018 article titled now what his accomplishments have often come about by asking that very question now what and often responding by a major change of direction this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma M as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store when you get it use colex podcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is to me an algorithmic marvel so big props to the cash app engineers for solving a heart problem that in the end provides an easy interface that takes a step up the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash up from the App Store or Google Play and use collects podcast you'll get ten dollars in cash app will also donate ten dollars the first one of my favorite organizations that is helping advanced robotics and STEM education for young people around the world and now here's my conversation with john hopfield biological neural networks and artificial neural networks is most captivating and profound to you at the higher philosophical level let's not get technical just yet one of the things very much intrigues me is the fact that neurons have all kinds of components properties to them and evolutionary biology if you have some little quirk and I even how a molecule works or how it still works and it can may mean use of evolution will sharpen it up and make it into a useful feature rather than a glitch and so you expect in neurobiology for evolution to have captured all kinds of possibilities of getting neurons of how you get neurons to do things for you and that aspect has been completely suppressed in artificial neural networks so the glitches become features in them in the biological neural network they they can look let me take one of the things that I used to do research on if you take things which oscillate their rhythms which are sort of close to each other under some circumstances these things will have a phase transition and suddenly is the rhythm will everybody will fall into step there was a marvelous physical example of that in the millenium bridge across the Thames River about Bill about 2001 and pedestrians walking across pedestrians don't walk synchronized they don't walk and lock lockstep but they're all walking about the same frequency and the bridge could say at that frequency in the slight sway made pedestrians tend a little bit to lock in the step master well the bridge was oscillating back and forth and the pedestrians were walking in step to it you could see we made it at the bridge and the engineers made a simple-minded a mistake they had a feeling when you walk it's step step step and it's back at forth motion but when you walk it's also right foot left foot side to side motion and the side to side motion for which the bridge was strong enough but it wasn't it wasn't stiff enough and as a result you would feel the motion and you'd fall under step with it and people were very uncomfortable with it they closed the bridge for two years really fully built stiffening for it no nerves look nerve cells loose action potentials you have a bunch of cells which are loosely coupled together perusing action potentials of the same rate there'll be some circumstances under which these things can lock together other circumstances which they won't well they fire together you can be sure the other cells are going to notice it so you could make a computational feature out of this and you're in an evolving brain most artificial neural networks don't even have action potentials let alone have the Potala bility for synchronizing them and you mentioned the evolutionary process so they're the evolutionary process that builds on top of biological systems leverage is that the the weird mess of it somehow so how do you make sense of that ability to leverage all the different kinds of complexities in the biological brain well look in the part of the biological molecule level you have a piece of DNA which included an encode for a particular protein you could duplicate that piece of DNA and now one part of it encode for that protein but the other one could itself change a little bit and the start coding for a molecule which is just slightly different now is that molecule was just slightly different had it in a function which helped any old chemical reaction was as important to the cell you would go ahead and let that e try an evolution of slowly and improve that function and so you have the possibility of duplicating and then having things drift apart one of them retain the old function the other one do something new for you and there's evolutionary pressure to improve look there isn't computers to adjust improvement has to do with closing some companies openings others the evolutionary process looks a little different yeah oh similar timescale perhaps well or shorter in times to kill companies close yeah go bankrupt and are born yeah shorter but not much shorter some some company lasts the century a couple but yeah you're right I mean if you think of companies a single organism that builds and you all know yeah it's a fascinating dual correspondence there between biological and companies have difficulty having a new product competing with an old fraud large yeah and when IBM built this first PC you probably read the dread the book they made a little isolated internal unit to make the PC and for the first time in IBM's history they didn't insist that you build it out of IBM components but they understood that they could get into this market which is a very different thing by completely changing their culture and biology finds other markets in a more adaptive way he adds better at it it's better at that kind of integration so maybe you've already said it but what to use the most beautiful aspect or mechanism of the human mind is it the adaptive the ability to adapt as you've described there's there some other little quirk that you particularly like adaptation is everything when you get down to it but the difference there are differences between adaptation where your learning goes on on the over generation that over evolutionary time or your learning goes on at the timescale of one individual who must learn from the environment during that individuals lifetime and biology has both kinds of learning in it and the thing which makes neurobiology hard is that a mathematical systems that were built on this other kind of evolutionary system what do you mean by mathematical system where where's the math in the biology well when you talk to a computer scientist about neural networks it's all math the fact that biology actually came about from evolution the thing and the fact that biology is about a system which you can build in three dimensions if you look at computer chips computer chips are basically two dimensional structures a 2.1 dimensions but they really have difficulty doing three-dimensional wiring biology biology is the neocortex is actually also sheet-like and it sits on top of the white matter which is about ten times the volume of the gray matter and contains all what you might call the wires but there's a huge the the effect the effect of computer structure on what is easy and what is hard is immense so and biology does makes some things easy that are very difficult to understand how to do computationally on the other hand you can't do simple floating-point arithmetic because though it's awfully stupid yeah and you're saying this kind of three dimensional complicated structure makes it's still math it still doing math the kind of math is doing enables you to solve problems of a very different kind that's right that's right so you mentioned two kinds of adaptation the evolutionary adaptation at the end the adaptation are learning at the scale of a single human life which do you are which is particularly beautiful to you and interesting from a research and from just a human perspective and which is more powerful I find things most interesting that I begin to see how to get into the edges edges of them and tease them apart a little bit see how they work and since I can't see the evolutionary process going on I am in awe of it but I find it just a black hole as far as trying to understand what to do and so in a certain sense I'm a doll but I couldn't be interested in working on it the human life timescale is however thing you can tease apart and study yeah you can do there's developmental neurobiology which understands all of these connections and now the structure evolves from a combination of what the genetics is like and the real the fact that this is you're building a system in three dimensions in just days and months those early early days of human life are really interesting they are and of course there are times of immense still multiplication there are also times of the craziest cell death in the brain is during infancy it's turnover so what is what what what is not effective which is not wired well enough to use the moment throw it out it's a mysterious process from let me ask from what field do you think the biggest breakthroughs in understanding the mind will come in the next decades is it neural science computer science neurobiology psychology physics maybe math maybe literature [Laughter] well of course I see the world always through a lens of physics I grew up in physics and the way I pick problems is very characteristic of physics and of an intellectual background which is not psychology which is not chemistry and so on and so on at both the air parents of physicists both of our parents were physicists and the real thing I gathered that was a feeling that the world is an understandable place and if you do enough experiments and think about what they mean and structure things that you can do the mathematics of the relevant of the experiments you also be able to understand how things work but that was that was a few years ago did you change your mind at all through many decades of trying to understand the mind of studying in different kinds of ways not even the minds just biological systems you still have hope the physics that you can understand there's the question of what do you mean by understand of course when I taught freshman physics I used to say I wanted to get physics to understand the subject to understand new this laws I didn't want them simply to memorize a set of examples to which they knew the equations to write down to generate the answers I had this nebulous idea of understanding so the if you looked at a situation you can say oh I expect the bowl to make that trajectory all right I expect so I'm into a notion of understanding and I don't know how to express that very well I've never known how to express it well and you run smack up against it well you choose these look at these simple neural Nets feed-forward neural Nets which do amazing things and yet you know contain nothing of the essence of what I would have felt was understanding attending is more than just an enormous lookup table let's linger on that how sure you are of that what if the table gets read Liebig so i'm he asks another way these feed-forward neural networks do you think they'll ever understand good answer that in two ways I think if you look at real systems feedback is an essential aspect of how these real systems compute on the other hand if I have a mathematical system with feedback I know I can unlaid this and do it a part of it but but I have an exponential expansion and the amount of stuff I have to build if I could resolve the problem that way so feedback is essential so we can talk even about recurrent recurrence but do you think all the pieces are there to achieve understanding through these simple mechanisms like back to our original question what is the fundamental is there a fundamental difference between artificial neural networks and biological or is it just a bunch of surface stuff suppose you ask a neurosurgeon when does somebody did yeah it'll probably go back to saying well I can look at the brain rhythms and tell you this is a brain which has never could have functioned again this is one another but this other one is one which if we treat it well is still recoverable and then just do that by so many electrodes looking at simple like electrical patterns just don't look in any detail at all or what individual neurons are doing these rhythms are already absent from anything which goes on in Google yeah but the rhythms but the rhythms would so well that's like comparing okay I'll tell you it's like you're comparing the the greatest classical musician in the world to child first learning to play the question I'm at but they're still both playing the piano I'm asking is there will it ever go on at Google do you have a hope because you're one of the seminal figures in both launching both disciplines both sides of the of the river I think it's going to go on generation after generation the way it has where what you might call the AI computer science community says let's take the following this is our model of Neurobiology at the moment let's pretend it's good enough and do everything we can with it and it does interesting things and after the while sort of grinds into the sand and you say Oh something else is needed from neurobiology and some other grand thing comes in and enables you to go a lot further according to the sandakan everything it could be generations of this evolution I don't know how many of them and each one is going to get you further into what a brain does whatever then in some sense passed the Turing test longer and more broad aspects and how many of these are good there are going to have to be before you say I've made something I've made a human I don't know but your sense is it might be a couple my senses might be a couple more yeah and going back to my brain waves of the word yes from the AI point of view if they would say ah maybe these are heavy phenomena and not important at all the first car I had no record of 1936 dodge Kobo 45 miles an hour in the wheels was Jimmy yeah good good speedometer that now don't be designed at the car that way the cars malfunctioning to have that but in biology if you if it were useful to know when are you going more than 45 miles an hour you just capture that and you wouldn't worry about where it came from yeah it'll be a long time before that kind of thing which can take place in large complex networks of things is actually used in the computation look-the how many transistors are there at your laptop these days actually I don't know the number it's it's on a scale of 10 to the 10 I can't remember the number yeah and all the transistors are somewhat similar and most physical systems with that many parts all of which are selfs or have collective properties yes soundly is an error Earthquakes what have you have collective properties wither there are no collective properties used in artificial neural networks in AI yeah it's very if biology uses them it's gonna take us two more generations of things to be the perfect people to actually dig in and see how they are used what they mean see you're very right might have to return several times to neurobiology and try to make our transistors more messy yo-yo at the same time the simple ones whole concert will conquer big aspects and I think one of the most biggest surprises to me was how well learning systems buzzer manifesting non-biological how important they can be actually and you how important how useful they can be in a high so if we can just take a stroll to some of your work that is incredibly surprising that it works as well as it does that launched a lot of the recent work with neural networks if we go to what are now called hopfield networks can you tell me what is associative memory in the mind for the human side let's explore memory for a bit okay what do you mean by associative memory is oh you have a memory of each of your friends your friend has all kinds of properties from what they look like is whether voice sounds like to where they went to college where you met them go on and on what what science papers they've written if I start talking about a five foot ten wiry cognitive scientist that's got a very bad back it doesn't take very long for you to say are you talking about geoff hinton I never been I never mentioned the name or anything very particular but somehow a few facts are associated with this with a particular person enables you to get a hold of the rest of the facts yeah earned or not the dress that was another subset of them and is this the ability to link things together linked experiences together which goes under the general name of associative memory and a large part of intelligent behavior is actually just large associative memories at work as far as I can see what do you think is the mechanism of how it works in the mind is it is it a mystery to you still do you have Inklings of how this essential thing for cognition works what I made 35 years ago was of course a crude physics model to show the kayak Chua Li enable you to understand my old sense of understanding as a physicist because you could say ah I understand why this goes to stable States it's like things going down downhill right and that gives you something with which to think in physical terms rather than only in mathematical terms so you've created these associative artificial well that warp those right and now if you if you look at what I did I didn't did all describe a system which gracefully learns I described as a system in which you could understand how things how learning could link things together how very crudely it might learn one of the things which intrigues me as I reinvestigate that system now to some extent is look I see you I'll see you every second for the next hour or what have you each each look at you is a little bit different I don't store all those second-by-second images I don't store 3,000 images I somehow compact this information so now I have a view of you which can which I can use it doesn't slavishly remember anything in particular but it could PACs the information in those useful chunks which are somehow it's these chunks which are not just activities of neurons from bigger things than that which are the real energies which are which are useful which are useful to you useful distal to you to describe to compress this information present in such a way that if I get the information comes in just like this again I don't bother about their to rewrite it or efforts to rewrite it simply do not yield anything because those things are already written and that needs to be not look this up has ever started somewhere already therapies not something which is much more automatic in the machine hardware right so in the human mind how complicated is that process do you think so you've created feels weird to be sitting with john hopfield calling them hot field networks but it is weird yeah but nevertheless that's what everyone calls them so here we are so that's a simplification that's what a physicists would do you and richard fineman sat down and talked about associative memory now if you as a if you look at the mind or you can't quite simplify so perfectly do you let me backtrack just a little bit yep biology is about dynamical systems computers are dynamical systems you can have if you want to math the bottle biology bottle neurobiology what is the time scale there's a dynamical system in which you have a fairly fast timescale in which you goes eight the synopsis don't change much during this computation so I'll think of the synapses fixed and just do the dynamics of the activity or you can say the synapses are changing fast enough that I have to have the synaptic dynamics working at the same time as the system dynamics in order to understand the biology most artists if you look at the feed-forward art revisional their own ads they're all done as learning is first of all I spent some time learning and not performing and I turned off learning and I perform right that's not biology and so he is there look more deeply at neurobiology even as associative memory I've got to face the fact that the dynamics of a synapse change is going on all the time and I can't just get by by thing I'll do the academics of activity with fixed synapses so the the synaptic the dynamics of the synapses is actually fundamental to the whole system yum yum and there's no there's no there's nothing necessarily separating the time skills where the time skills can be separate and it's neat for the physicists of the mathematicians point of view but it's not necessarily true in neurobiology New York you're kind of dancing beautifully between showing a lot of respect to physics and then also saying that physics cannot quite reach the the complexity of biology so where do you land or do you continuously dance between the two I continuously dance between them because my whole notion of understanding is it you can describe to somebody else how something works in ways which are honest and believable and still not described all the nuts and bolts in detail whether I can describe whether as ten to the 32 molecules colliding in the atmosphere I can stimulate whether that way or I pick enough machine I'll simulate it accurately it's no good for understanding but I just want to understand things I want to understand things in terms of wind patterns hurricanes pressure differentials and so on all things is there negative and the physicists physicists in me always hopes that biology will have some things which can be said about it was are both true and for which you don't need all the molecular details of the molecules colliding that's what I mean from the roots of physics by understanding so what did again sorry but hopfield networks help you understand what insight to give us about memory about learning they didn't give insights about learning they gave insights about how things having learned could be expressed how having learned a picture of a picture of you reminds me of your name that would put it describe a reasonable way of actually doing the learning or only said if he had previously learned the connections of this kind of pattern would now be able to behave in a physical way with the day off I put the part of the pattern in here the other pattern of the pet part of the pattern will complete over here I can understand that physics if the right learning stuff had already been put in and you couldn't understand why then putting in a picture of somebody else would generate something else over here but it didn't out under did not have a reasonable description of the learning process but even to forget learning I mean that's just a powerful concept that sort of forming representations that are useful to be robust you know for error correction kind of thing so this is kind of what the biology does we're talking about what my paper did was simply enable you there long there are lots of ways of being robust if you think of it a dividend amical system here you think of a system where a path is going on and in time and if you think for a computer is a computational path which is going out in a huge dimensional space of ones and zeros and an error-correcting system is a system which if you get a little bit off that trajectory will push you back onto that trajectory again till you get to the same answer in spite of the fact that there were things though that the computation wasn't being ideally done all the way along a line and there are lots of models for error correction but one of the models for error correction is to say there's a family that you're following flowing down and if you push a little bit off the valley it's just like water being pushed a little bit by a rock gets back and follows the course of the river and then basically the analog in the in the physical system went to enable to just say oh yes error free computation and an associative memory are very much like like things that I can understand from the point of view of a physical system the physical system is can be under some circumstances an accurate metaphor it's not the only metaphor there are error correction schemes which don't have a valley and energy behind them but those are correction schemes such a mathematician may be able to understand but I don't so there's a the physical metaphor that seems to a it seems to work here that's right that's right so these kinds of networks actually led to a lot of the work that is going on now and you're on that works artificial neural network so the follow-on work with restrictive Boltzmann machines and deep belief Nets followed on from the from these ideas of the hopfield network so what what do you think about this continued progress of that work towards now ree-ree vigor ated exploration of feed-forward neural networks and recurrent neural networks in convolutional neural networks and kinds of networks that are helping solve image recognition natural language processing all that kind of stuff it's always intrigued me one of the most long-lived all the learning systems is the Boltzmann machine which is intrinsically a feedback network and was the brilliance of in and Sadowski to understand how to do learning in that and it's still a useful way to understand learning and understand and the learning that you understand and that has something to do with the way that feed-forward systems work but it's not always exactly simple to express that intuition but it always amuses me as he Hinton going back to the will yet again on a form of the Boltzmann machine because really that which has feedback and interesting probabilities in it this is a lovely encapsulation of something in computational something computational something both computational and physical computational and they very much related to feed-forward networks physical in that Boltzmann machine learning is really learning a set of parameters for physics Hamiltonian or energy function what do you think about learning in this whole domain do you do you think the aforementioned guy Geoff Hinton all the work there with backpropagation all the kind of learning that goes on in these networks how do you if we compared to learning in the brain for example is there echoes of the same kind of power that back propagation reveals about these kinds of recurrent networks or is it something fundamentally different going on in the brain I don't think the brain is as deep as the deepest networks go the deepest computer science networks and I do wonder where they're part of that depth of the computer science networks is necessitated by the fact that the only learning is easily done on a machine is his feed-forward and so there's the question of to what extent as the biology which has some feed-forward some feedback been captured by something which is it got many more neurons but much more depth to the neurons you know so party you wonders if the feedback is actually more essential than the number of neurons or the depth the the dynamics of the feedback doesn't ever have the feedback look if you don't have if you don't have feedback it's a little bit like a building a big computer and having running up through one clock cycle and then you can't do anything do you put you reload something coming in how do you use the fact that there are multiple clocks like how do I use the fact that you can close your eyes stop listening to me and think about a chessboard for two minutes without any input whatsoever yeah that memory thing that's fundamentally a feedback kind of mechanism you're going back to something yes it's hard it's hard it's hard to understand so I don't respect let alone consciousness oh is that a little own consciousness yes because that's tied up in there too you can't just put that on another shelf every once in a while like I interested in consciousness and then I go and I've done that for years and ask one of my betters as it were their view on consciousness there's been interest in collecting them what let's try to take a brief step into that room well that's Marvin Minsky does you want to consciousness and Marvin said consciousness is basically overrated it may be an epiphenomenon after all all the things your brain does but your as they're actually hard computations you do not consciously and there's so much evidence that even the things the simple things you do you can make decisions you can make committed decisions about them the neurobiology can say he's now committed he's going to move the hand left before you know it so his view that consciousness is not that's just like little icing on the cake the real cake is in the subconscious yo-yo subconscious non conscious non-conscious that's the better word sir there's the it's only the Freud captured the other word yeah it's that's a confusing word subconscious Nicholas Chater wrote an interesting book I think the saw delivers the mind is flat flat and in a neural net sense you might have to be a flat is something which is of very broad they're all know without earlier than the layers in depth or as a deep brain would be many layers and not so broad in the same sense that if you push Minsky hard enough he would talk V of said consciousness is your effort to explain to yourself that would you have already done yeah it's the weaving of the narrative around the things that already been computed for you that's right and then so much of what we do for our memories of events for example if there's some traumatic event you witness you will have a few facts about it correctly done if somebody asks you about it you will weave a narrative which is actually much more rich in detail than that based on some anchor points you have of correct things and and pulling together general knowledge on the other but you will have a narrative and once you generate that narrative if you are very likely to repeat that narrative and claim that all the things you have hidden are actually the correct things there was a marvelous example of that in the Watergate / impeachment era of John Dean John Dean you're too young to know had been the personal lawyer of Dickson and so John Dean was involved in the cover-up and John Dean ultimately realized the only way to keep himself out of jail for a long time was actually to tell some of the truths about Nixon and John Dean was a tremendous witness he would remember these conversations in great detail and very convincingly tail and long afterward some of the some of the tapes the secret cases were for which these Don was Jean was recalling these conversations were published and one found out that John Dean had a good but not exceptional memory what he had was an ability to paint vividly and in some sense accurately the tone of what was going on by the way that's a beautiful description of consciousness [Music] do you mean like where do you stand in your today so perhaps has changed his day to day but where do you stand on the importance of consciousness in our whole big mess of cognition is it just a little narrative maker or is it actually fundamental to intelligence that's our that's a very hard one but I asked Francis Crick about consciousness he launched forward a long monologue about handling the peas yeah and how Mendel knew that there was something and how biologists understood there was something in inherit which was just very very different and he is the effect that inherited traits didn't just wash out into a grey but it's this or this and propagated that that was absolutely fundamentals of biology and it took generations of biologists to understand that there was genetic and it took another generation or two to understand that genetics came from DNA but there but but but very shortly after Mendel thinking biologists did realize that there was a deep problem about inheritance any Francis blood of life would like to have said and that's why I'm we're working unconsciousness but of course he didn't have any smoking gun in the sense of Mendel and that's the weakness of his physician that he read his his book but you wrote with Corey bank yeah Christophe go on I find it unconvincing for this first poking gun reason start going on and collecting views without actually having taken a very strong one myself because I haven't seen the entry point not seeing the smoking gun and the point of view of physics I don't see the entry point whereas whereas the neurobiology once they understood the idea of a collective a and evolution of dynamics which could be described as a clock a collective phenomenon I thought ah there's a point where what I know about physics is so different from any neurobiologist that I have something that I might be able to contribute and right now there's no way to grasp at consciousness from a physics perspective from my point of view that's correct and of course people this is like everybody else do you think very but early about things you have the closely is related question about freewill do you believe your freewill physicists will give an offhand answer and then backtrack backtrack backtrack where they realized that the answer they gave must fundamentally contradict the laws of physics that natura answering questions of freewill and consciousness naturally lead to contradictions from a physics perspective because it eventually ends up with quantum mechanics and then you get into that whole mess of trying to understand how much from a physics perspective how much is determined already predetermined much is already deterministic about our universe there's lots of difference and if you don't push quite that far you can say essentially all of Neurobiology which is relevant it can be captured by classical equations of motion right because in my view of the mysteries of the brain are not the mysteries of quantum mechanics for the mysteries of what can happen when you have a dynamical system driven system with 10 to the 14 parts the bare complexity is something which is if the physical complex systems is at least as badly understood as the physics of phase coherence and quantum mechanics can we go there for a second you've talked about attractor networks and just maybe you could say what our attractor networks and more broadly what are interesting network dynamics that emerge in these or other complex systems you have to be willing to think in a huge number of dimensions because there's a huge number of dimensions the behavior of a system can be thought of as just the motion of the point over time in those huge number of adventures right and an attractor network is simply a network where there is a line and other lines converge on it in time that's the essence of an attractor Network that's how you need a highly highly dimensional space and the easiest way to get that is to do it in a high dimensional space where some of these dimensions provide the dissipation which base which a kind of a physical system trajectories can dig our contract everywhere they have to get tracked in some places and expand in others there was a fundamental classical theorem most statistical mechanics which goes under the name of liouville's theorem which says you can't contract everywhere after country if you contract somewhere you were expand somewhere else do you and is in interesting physical systems you get driven systems where you have a small subsystem which is the interesting part and the rest of the contraction of an expansion the physicists say it's the entropy flow in this other part of the system but but basically attract your networks our dynamics funneling downs of you can't be any so if you start somewhere in the dynamical system you will soon find yourself on a pretty well determined pathway which goes somewhere you start somewhere else you'll wind up on a different pathway but you don't have just all possible things you have some defined pathways which are allowed and onto which you will converge and that's the way you make a stable computer and that's the way you make a stable behavior so in general looking at the physics of the emergent stability in these not--when networks what are some interesting characteristics that what are some interesting insights from studying the dynamics of such high dimensional systems most dynamical systems supposed I'm done driven dynamical systems I driven there are couples I'm out to an energy source and so their dynamics keeps going because it's coupling to the energy source most of them it's very difficult as all to understand it all with the devil the dynamical behavior is going to be you have to run it out you have to running there's this there's a subset of systems which has what was a clean tone to the mathematicians as as the Alpen of function and those systems you can understand convergent dynamics by saying you're going downhill on something or other and that's what I found without ever knowing what the alpha naught functions were in the simple model I made in the early eighties was an energy function so you could understand how you get this channeling I'm as under pathways without having to follow the dynamics in an infinite detail you started rolling a ball as off of a mountain that's gonna wind up at the bottom of a valley you know that it's true without actually watching the ball fall roll down there's certain properties of the system that when you can know that that's right and not all systems behave that way most don't probably both don't but it provides you with the metaphor for thinking about systems which are stable in the whoo to have these attractors behave even if you can't find the idly up and a function behind them or an energy function behind them it gives you a metaphor for thought speaking of thought if I had a glint in my eye with excitement and said you know I'm really excited about this something called deep learning and neural networks and I would like to create an intelligence system and came to you as an adviser what would you recommend is it a hopeless pursuit she's knew all networks that she thought is it what kind of mechanism should we explore what kind of ideas should we explore well you look at this as the simple net worth for everyone networks they don't support multiple hypotheses very well as I have tried to work with very simple systems which do something which you might consider to be thinking thought has to do with the ability to do mental exploration before you make it take a physical action almost they like we were mentioning playing chess visualizing simulating inside your head different outcomes yellow young and now you could do that as a feed-forward Network because you've pre calculated all kinds of things but I think the way neurobiology does it hasn't pre calculated everything exactly as parts of a dynamical system in which you're doing exploration in a way which is there's a creative element like there's an there's that there's there's a creative element and in a simple-minded neural net you ever a constellation of instances from which you've learned and if you are within that space you know if a new fan new question is the question within this space you can actually rely on that system pretty well to come up with a good suggestion for what to do if on the other hand the query comes from outside the space you have no way of knowing how the system is going to behave there are no limitations on what could happen and so with the artificial neural network is always very much I have a a population of examples the test set must be drawn from the equivalent population as the test as examples which are from a population which is completely different there's no way that you could expect to get the answer right Meowth and so what they saw outside the distribution that's right that's right and so if you see a ball rolling across the streets and dusk if there wasn't in your your training set the idea that a child may be coming close behind that is not going to occur with the neural lab and it is to our there's something in your biology that allows that yeah there's there's something in the way of what it means to be outside of the of the population of the training said the probability is that the training set isn't just sort of the set of examples it's there's more to it than that and it gets back to my own question of where's is it to understand something yeah you know is in a small tangent you've talked about the value of thinking of deductive reasoning in science versus large data collection so sort of thinking about the problem but I suppose it's the physics side of you of going back to first principles and thinking but what do you think is the value of deductive reasoning in in a scientific process well look there obviously scientific questions in which the route to the answer to it come through the analysis of one hell of a lot of data right cosmology at honest and that that's never written the kind of problem in which I've had any particular insight though I would say if you look at cosmology is was one of those if you look at the actual things that Jim Peebles one of this year's don't go prized for the vision physics ones from a local physics department the kinds of things he's done he's never crunched large data never never never he's used the encapsulation of the work of others in this regard but I ultimately boil down to thinking through the problem like what are the principles under which a particular phenomena operates yeah and look physics is always going to look for ways in which you can describe the system and which rises above the rises above the details and to the hard died the world biologists biology works because of the details and physics to the physicists we want an explanation which is right in spite of the details and they will leave questions which we cannot answer as physicists because the answer cannot be found that way there's a met sure if you're familiar with the entire field of brain-computer interfaces has become more and more intensely researched and developed recently especially with companies like neural link what Elon Musk you know I know they've always been the endres both in things like getting the eyes to be able to control things or getting the thought patterns to be able to move what had been a they connected limb which is now connected through a computer that's right so in the case of neural they're doing thousand-plus connections where they're able to do two-way activate and read spikes in your annual spikes do you have hope for that kind of computer brain interaction in the near or maybe even far future of being able to expand the ability of the mind of cognition or understand the mind as this was watching things go when I first became interested in neurobiology most of the practitioners thought you would be able to understand neurobiology by techniques which allowed you to record only one cell at a time once out yeah people like David Hoople very strongly reflected that point of view and that's been taken over by a generation a couple of generations later a set of people who says not until we can record from 10 to the 4 or 10 to the 5 at a time who we actually be able to understand how the brain actually works and in a general sense I think that's right you have to look you have to begin to be able to look for the collective modes of the collective operations of things it doesn't rely on this action potential or death cell it relies on the collective properties of this set of cells connected to this kind of patterns so on and you're not going to see did the thing what those collective activities are without recording many cells at once and the question is how many at once what's the threshold and that's the that's the no and and because we pursued hard in the motor cortex the motor cortex does something which is complex and yet with the problem you're trying to address is very it's really simple now neurobiology does it in ways the different from the way an engineer would do it an engineer would put in six highly accurate stepping motors are controlling a limb rather than 2,000 muscle fibers each of which has to be individually controlled so understanding how to do things in a way which is much more forgiving and much more neural I think would benefit the engineering world the engineering world touch that's where their pressure sensor or to let very them an array of of a gazillion pressure pressure sensors none of what you're accurate all of which are perpetually recalibrating themselves so you're saying your hope is your advice for the engineers of the future is to the embrace the large chaos of a messy error-prone system like those of the biological systems like that's probably the way to solve some of these I think you'll be able to make better compete computations last robotics that way than by trying to force things into a into a robotics for joint motors are powerful and stepping motors are accurate but then the physicists the physicists in you will be lost forever in such systems because there's no simple fundamentals to exploring systems that are so large and we also you see that yep there's a lot of physics and the navier-stokes equations the equations of nonlinear hydrodynamics huge amount of physics in them all the physics of atoms and molecules has been lost but it's been replaced or this other set of equations which is just as true as the equations of the bottle though those those equations are going to be harder to find in general biology but the physicist of me says there are probably some equations of there sort they're out there there they're out there and the physics is going to contribute anything it may contribute to trying to find out what those equations are and how to capture them from them biology would you say that's one of the main open problems of our age is to discover those equations yeah if you look at theirs molecules there's psychological behavior these two are somehow related there are layers of detail they're layers of collectiveness and to capture this to capture that at some vague wait several stages on the way up to see how these things that can actually be linked together so it seems in our universe there's a lot of a lot of elegant equations that can describe the fundamental way that things behave which is a surprise I mean it's compressible into equations it's simple and beautiful but there isn't it's still an open question whether that link is equally between molecules and the brain is equally compressible into elegant equations but your ear sounds some well you're both a physicist and a dreamer you have a sense that yes I can although I can only dream physics dreams physics shapes there was an interesting book called Einsteins dreams Forge alternates between chapters on his life and descriptions of the way time might have been but isn't as linking between these being of course the ideas that Einstein might have had to think about the essence of time as he was thinking about time so speaking of the essence of time in neurobiology you're one human famous impactful human but just one human with a brain living the human condition but you're ultimately mortal like all of us has studying the mind as a mechanism change the way you think about your own mortality it has really because as particularly as you get older in the body comes apart in various ways I became much more aware of the fact that what is somebody is contained in the brain and out in the body that you worry about burying and it is to a certain extent true that for people who write things down equations dreams notepads Diaries fractions of their thought does continue to live after they're dead and gone after their body is dead and gone and there's a sea change in there going on in my lifetime between what if my father died when except for the things that you're actually ridden by hymns that were very few facts about him will have ever been recorded and the number of facts which are recorded about each and every one of us forever now as far as I can see in the digital world and so the whole question of what is death may be different for people a generation to go in a generation or through ahead maybe we have become immortal under some definitions yeah yeah last easy question what is the meaning of life looking back studied the mind a weird descendants of apes what's the meaning of our existence on this little earth Oh word meeting is as slippery as the word understand interconnected somehow perhaps is there it's slippery but is there something you despite being slippery can hold long enough to express all I've been amazed at how hard it is to define the things in a living system in the sense that what a hydrogen atom is pretty much like another one bacterium is not so much like another like another bacterium even of the same nominal species in fact the whole notion of what as the species gets a little bit fuzzy and do species exists in the absence of certain classes of environments and pretty soon one winds up with with the biology which the whole thing is living but whether there's actually any element of it which by itself would be said to be living is becomes a little bit vague in my mind so in a sense the idea of meaning is something that's possessed by an individual like a conscious creature and you're saying that it's all interconnected in some kind of way that there might not even be an individual we're all kind of this complicated mess of biological systems at all different levels where the human starts and when the human ends is unclear you know yeah and we're the neurobiology where the oh you say that the your cortex does the thinking but there's lots of things that are done in the spinal cord and so we say where's the essence of thought it's just going to be neocortex can't be campy yeah maybe to understand and to build thought you have to build the universe along with the the neocortex it's all interlinked through the spinal cord John is a huge honor talking today thank you so much for your time I really appreciate it well thank you for the challenge of talking with you and the interesting to see whether you can win a 5 in 5 minutes out of that just coherent sense to anywhere beautiful thanks for listening to this conversation with john hopfield and thank you to our presenting sponsor cash app downloaded used coal export cast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe I need to give it five stars an Apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman and now let me leave you with some words of wisdom from john hopfield in his article titled now what choosing problems is the primary determinant of what one accomplishes in science i have generally had a relatively short attention span and science problems thus i have always been on the lookout for more interesting questions either as my present ones get worked out or as it get classified by me as intractable give him my particular talents he then goes on to say what I have done in science relies entirely on experimental and theoretical studies by experts I have a great respect for them especially for those who are willing to attempt communication with soin who is not an expert in the field I would only add that experts are good at answering questions if you're brash enough ask your own too much about how you found them for listening and hope to see you next time you |
Marcus Hutter: Universal Artificial Intelligence, AIXI, and AGI | Lex Fridman Podcast #75 | the following is a conversation with Marcus hunter senior research scientists the google deepmind throughout his career of research including with Juergen Smith Huber and Shayne leg he has proposed a lot of interesting ideas in and around the field of artificial general intelligence including the development of IHC spelled a ixi model which is a mathematical approach to AGI that incorporates ideas of Kolmogorov complexity solomonoff induction and reinforcement learning in 2006 Marcus launched the 50,000 euro hütter prize for lossless compression of human knowledge the idea behind this prize is that the ability to compress well is closely related to intelligence this to me is a profound idea specifically if you can compress the first 100 megabytes or 1 gigabyte of Wikipedia better than your predecessors your compressor likely has to also be smarter the intention of this prize is to encourage the development of intelligent compressors as a path to AGI in conjunction with this podcast release just a few days ago Markus announced the 10x increase in several aspects of the surprise including the money to 500,000 euros the better your compressor works relative to the previous winners the higher fraction of that prize money is awarded to you you can learn more about it if you Google simply Qatar prize I have a big fan of benchmarks for developing AI systems and the harder prize may indeed be one that will spark some good ideas for approaches that will make progress on the path of developing a GI systems this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast supported on patreon or simply connect with me on Twitter at lex Friedman spelled Fri D M am as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the 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first one of my favorite organizations that is helping to advance robotics and STEM education for young people around the world and now here's my conversation with Markus cutter as a computer or maybe an information processing system let's go with a big question first okay I with a big question first yeah I think it's very interesting hypothesis or idea and I have a background in physics so I know a little bit about physical theories the standard model of particle physics and general relativity theory and they are amazing and describe virtually everything in the universe and they're all in a sense computable theories I mean they're very hard to compute and you know it's very elegant simple theories which describe virtually everything in the universe so there's a strong indication that somehow the universe is computable but it's a plausible hypothesis so what what do you think just like you said general relativity quantum field theory what do you think that the laws of physics are so nice and beautiful and simple and compressible do you think our universe was designed is naturally this way are we just focusing on the parts that are especially compressible our human minds just enjoy something about that simplicity and in fact there's other things that are not so compressible no I strongly believe and I'm pretty convinced that the universe is inherently beautiful elegant and simple and described by these equations and we're not just picking that I mean if the versatile phenomena which cannot be need to describe scientists would try that right and you know there's biology which is more messy but we understand that it's an emergent phenomena and you know it's complex systems but they still follow the same rules right of quantum electrodynamics and all of chemistry follows that and we know that I mean we cannot compute everything because we have limited computational resources now I think it's not a bias of the humans but it's objectively simple I mean of course you never know you know maybe there's some corners very far out in the universe or super super tiny below the nucleus of atoms or well parallel universes where which are not nice and simple but there's no evidence for that and you should apply Occam's razor and you know just the simple story consistent with but also it's a little bit for friendship so maybe a quick pause what is Occam's razor so or comes razor says that you should not multiply entities beyond necessity which sort of if you translate it to proper English means and and you know in a scientific context means that if you have two series or hypotheses or models which equally well describe the phenomenon your study or the data you should choose the more simple one so that's just the principle you're sort of that's not like a provable law perhaps perhaps we'll kind of discuss it and think about it but what's the intuition of why the simpler answer is the one that is likely to be more correct descriptor of whatever we're talking about I believe that Occam's razor is probably the most important principle in science I mean of course we logically Duck shouldn't be do experimental design but science is about finding understanding the world finding models of the world and we can come up with crazy complex models which you know explain everything but predict nothing but the simple model seem to have predictive power and it's a valid question why yeah and the two answers to that you can just accept it that is the principle of science and we use this principle and it seems to be successful we don't know why but it just happens to be or you can try you know find another principle which explains or comes razor and if we start with the assumption that the world is governed by simple rules then there's a bias toward simplicity and pliant Occam's razor is the mechanism to finding these rules and actually in a more quantitative sense and we come back to that later in terms of some Roman attraction you can rigorously prove that usually assume that the world is simple then Occam's razor is the best you can do in a certain sense so I apologize for the romanticized question but why do you think outside of its effectiveness why do we do you think we find simplicity so appealing as human beings well just why does e equals mc-squared seems so beautiful to us humans I guess mostly in general many things can be explained by an evolutionary argument and you know there's some artifacts and humans which you know are just artifacts and not an evolutionary necessary but there's this beauty and simplicity it's I believe at least the core is about like science finding regularities in the world understanding the world which is necessary for survival right you know if I look at a bush right and I just seen Norris and there is a tiger right and eats me then I'm dead but if I try to find a pattern and we know that humans are prone to find more patterns in data than they are you know like the you know Mars face and all these things but these buyers towards finding patterns even if they are not but I mean its best of course if they are yeah helps us for survival yeah that's fascinating I haven't thought really about this I thought I just loved science but they're indeed from in terms of just for survival purposes there is an evolutionary argument for why why we find the work of Einstein is so beautiful maybe a quick small tangent could you describe what's Solomonov induction is yeah so that's a theory which I claim and Riesling enough sort of claimed you know a long time ago that this solves the big philosophical problem of induction and I believe the claim is essentially true and what it does is the following so okay for the picky listener induction can be interpreted narrowly and wildly narrow means inferring models from data and widely means also then using these models for doing predictions or predictions also part of of the induction so I'm little sloppy sort of as a terminology and maybe that comes from ray solomonoff you know being sloppy maybe saying it we can't complain anymore so let me explain a little bit this theory yeah in simple terms so assume we have a data sequence make it very simple the simplest one say 1 1 1 1 1 and you see if 100 ones yeah what do you think comes next the natural order I repeat up a little bit the natural answer is of course you know 1 ok and questions why ok well we see a pattern there yeah ok there's a 1 and we repeat it and why should it suddenly after a hundred ones be different so what we're looking for is simple explanations or models for the data we have and now the question is a model has to be presented in a certain language in which language to be used in science we want formal languages and we can use mathematics or we can use programs on a computer so abstract me on a Turing machine for instance or can be a general-purpose computer so and they of course lots of models of you can say maybe it's a hundred ones and then 100 zeros and a hundred ones that's a model right but there are simpler models there's a model print one loop and it also explains the data and if you push the to the extreme you are looking for the shortest program which if you run this program reproduces the data you have it will not stop it will continue naturally and this you take for your prediction and on the sequence of ones it's very plausible right at the print one loop it's the shortest program we can give some more complex examples like 1 2 3 4 5 what comes next the short program is again you know counter and so that is roughly speaking house a lot of interaction works the extra twist is that it can also deal with noisy data so if you have for instance a coin flip say a biased coin which comes up head with 60% probability then it will predict if you learn and figure this out and after a while it predict or the next coin flip will be head with probability 60% so it's the stochastic version of that but the goal is the dream is always the search for the short program yes yeah well in solomonov induction precisely what you do is so you combine so looking for the shortest program is like applying AAPIs race like looking for the simplest theory there's also a pakoras principle which says if you have multiple hypotheses which equally well describe you data don't discard any of them keep all of them around you never know and you can put it together and say ok have a buyer's to her simplicity but I don't rule out the larger models and technically what we do is we weigh the shorter models higher and the longer models lower and you use a Bayesian techniques you have a prior and which is precisely 2 to the minus the complexity of the program and you weigh all this hypotheses and take this mixture and then you get also this plasticity in yeah like many of your ideas that's just a beautiful idea of weighing based on the simplicity of the program I love that that that seems to me may be a very human central concept seems to be a very appealing way of discovering good programs in this world you've used the term compression quite a bit I think it's a beautiful idea sort of we just talked about simplicity and maybe science or just all of our intellectual pursuits is basically the attempt to compress the complexity all around us into something simple so what does this word mean to you compression I essentially have already explained it so it compression means for me finding short programs for the data or the phenomena at hand you could interpret it more widely as you know finding simple theories which can be mathematical theory so maybe even informal you know like you know just inverts compression means finding short descriptions explanations programs little data do you see science as a kind of our human attempt at compression so we're speaking more generally because when you say programs kind of zooming in a particular sort of almost like computer science artificial intelligence focus but do you see all of human endeavor as a kind of compression well at least all of science ICSI and evolve compression at all of humanity maybe and well they are so other aspects of science like experimental design right I mean we we create experiments specifically to get extra knowledge and this is that isn't part of the decision-making process but once we have the data to understand the data is essentially compression so I don't see any difference between contrast compression understanding and prediction so we're jumping around topics a little bit but returning back the simplicity a fascinating concept of komagawa of complexity so in your sense the most objects in our mathematical universe have high komagawa of complexity and maybe what is first of all what is coma graph complexity ok Kolmogorov complexity is a notion of simplicity or complexity and it takes the compression view to the extreme so I explained before that if you have some data sequence just think about a file on a computer and best sort of you know just a string of bits and if you and we have data compresses likely compress big files in terms a sip files with certain compressors and you can also put yourself extracting archives that means as an executable if you run it it reproduces the original file without needing an extra decompressor it's just a decompressor plus the archive together in one and now there are better and worse compressors and you can ask what is the ultimate compressor so what is the shortest possible self-extracting archives you could produce for a certain data set yeah which reproduces the data set and the length of this is called the Kolmogorov complexity and arguably that is the information content in the data set I mean if the data set is very redundant or very boring you can compress it very well so the information content should be low and you know it is low according to this difference this is the length of the shortest program that summarizes the data yes yeah and what's your sense of our sort of universe when we think about the different the different objects in our universe that we each are concepts or whatever the at every level do they have higher or local girl complexity so what's the hope do we have a lot of hope and be able to summarize much of our world that's a tricky and difficult question so as I said before I believe that the whole universe based on the evidence we have is very simple so it has a very short description the whole sorry did you would you linger on that the whole universe what does I mean do you mean at the very basic fundamental level in order to create the universe yes yeah so you need a very short program when you run it to get the thing going you get the thing going and then it will reproduce our universe and there's a problem with noise we can come back to the later possibly noise a problem or a fear is it a bug or a feature I would say it makes our life as a scientist really really much harder I didn't think about without noise we wouldn't need all of the statistics but that maybe we wouldn't feel like there's a free will maybe we need that for the ethics this is an illusion that Norris can give you freezing that way it's a feature but also if you don't have noise you have chaotic phenomena which are effectively like noise so we can't you know get away with statistics even then I mean think about rolling a dice and you know forget about quantum mechanics and you know exactly how you you throw it but I mean it's still so hard to compute a trajectory that effectively it is best to model it you know as you know coming out this a number this probability 1 over 6 but from from this set of philosophical como go of complexity perspective if we didn't have noise then arguably you could describe the whole universe as well as standard model plus general relativity I mean we don't have a theory of everything yet but sort of assuming we are close to it or have it here plus the initial conditions which may hopefully be simple and then you just run it and then you would reproduce the universe but that's all by noise or by chaotic systems or by initial conditions which you know may be complex so now if we don't the whole universe but just a subset you know just take planet Earth planet Earth cannot be compressed you know into a couple of equations this is a hugely complex just so interesting so when you look at the window like the whole thing might be simple when you just take a small window then it may become complex and that may be counterintuitive but there's a very nice analogy the the book the library of all books so imagine you have a normal library with interesting books and you go there great lots of information and you quite complex yeah so now I create a library which contains all possible books say of 500 pages so the first book just has a aaaa over all the pages the next book aaaa and ends with P and so on I create this library of all books I can write a super short program which creates this library so this library which has all books has zero information content and you take a subset of this library and suddenly have a lot of information in there so that's fascinating I think one of the most beautiful object mathematical objects that at least today seems to be under study or under talked about is cellular automata what lessons do you draw from sort of the game of life for cellular automata where you start with the simple rules just like you're describing with the universe and somehow complexity emerges do you feel like you have an intuitive grasp on the behavior the fascinating behavior of such systems where some like you said some chaotic behavior it could happen some complexity could emerge some it could die out and some very rigid structures you have a sense about cellular automata that somehow transfers maybe to the bigger questions of our universe is a cellular automata and especially the Conway's Game of Life is really great because this rule are so simple you can explain it to every child and mean by hand you can simulate a little bit and you see these beautiful patterns emerge and people have proven you know that is even Turing complete you cannot just use a computer to simulate game of life but you can also use game of life to simulate any computer that is truly amazing and it's it's the prime example probably to demonstrate that very simple rules can lead to very rich phenomena and people you know sometimes you know how can how is chemistry and biology is so rich I mean this can't be based on simple rules yeah but now we know quantum electrodynamics describes all of chemistry and and become later back to that I claim intelligence can be explained or described in one single equation this very rich phenomenon you asked also about whether you know I understand this phenomenon and it's probably not and this is saying you never understand really things you just get used to them and pretty using used to sell all automata so you believe that you understand now why this phenomenon happens but I give you a different example I didn't play too much with this converse game of life but a little bit more with fractals and with the Mandelbrot set and it's beautiful you know patterns just just look Mandelbrot set and well when the computers were really slow in our just a black and white monitor and programmed my own program sana in assembler - Wow Wow to get these vectors on the screen and it was mesmerised and much later so I returned to this you know every couple of years and then I try to understand what is going on and you can understand a little bit so I try to derive the locations you know there are these circles and the Apple shape and then you have smaller Mandelbrot sets recursively in this set in this way to mathematically by solving high order polynomials to figure out where these centers are and what size there are approximately and by sort of ant mathematically approaching this problem you slowly get a feeling of why things are like they are and that sort of isn't you know first step to understanding why this rich phenomena do you think as P as possible what's your intuition you think it's possible to reverse engineer and find the short program that generated the these fractals sort of by what looking at the fractals well in principle yes yeah so I mean in principle what you can do is you take you know any data set you know you take these fractals or you take whatever your data set whatever you have say a picture of conveys game of life and you run through all programs you take your programs 1 2 3 4 and all these programs around them all in parallel in so called dovetailing fashion give them computational resources first one 50% second 1/2 resources and so on and let them run wait until they halt give an output compare it to your data and if some of these programs produced the correct data then you stop and then you have already used some program it may be a long program because it's faster and then you continue and you get shorter and shorter programs until you eventually find the shortest program the interesting thing you can never know whether to short this program because there could be an even shorter program which is just even slower and you just have to wait here but asymptotically and actually after finite time you have this shortest program so this is a theoretical but completely impractical way of finding the underlying structure in every data set and there was a lot of interaction dolls and Kolmogorov complexity in practice of course we have to approach the problem more intelligently and then if you take resource limitations into account there's friends the field of pseudo-random numbers yeah and these are random that must so these are deterministic sequences but no algorithm which is fast fast means runs in polynomial time can detect that it's actually deterministic so we can produce interesting I mean random numbers maybe not that interesting but just an example we can produce complex looking data and we can then prove that no fast algorithm can detect the underlying pattern which is unfortunately is it that's a big challenge for our search for simple programs in the space of artificial intelligence perhaps yes it definitely is quantitative intelligence and it's quite surprising that it's I can't say easy here I mean worked really hard to find his theories but apparently it was possible for human minds to find these simple rules in the universe it could have been different right it could have been different it's it's uh it's inspiring so let me ask another absurdly big question what is intelligence in your view so I have of course a definition I wasn't sure what you're gonna say because you could have just as easily said I have no clue which many people would say I'm not modest in this question so the the informal version which ever got together be shame like who co-founded in mind is that intelligence measures an agent's ability to perform well in a wide range of environments so that doesn't sound very impressive and but it these words have been very carefully chosen and there is a mathematical theory behind it and we come back to that later and if you look at this this definition right itself it seems like yeah okay but it seems a lot of things are missing but if you think it through then you realize that most and I claim all of the other traits at least of rational intelligence which we usually associate intelligence are emergent phenomena from this definition in creativity memorization planning knowledge you all need that in order to perform well in a wide range of environments so you don't have to explicitly mention that in a definition interesting so yeah so the consciousness abstract reasoning or all these kinds of things are just emerging phenomena that help you in towards can you say the definition against multiple environments did you mention or goals no but we have an alternative definition instead of performing value conscious replace it by goals so intelligence measures an agent ability to achieve goals in a wide range of environments that's more or less because in there there's an injection of the word goals so you to specify their there should be a goal yeah but perform well is sort of what is it does it mean it's the same problem yeah there's a little gray area but it's much closer to something that could be formalized re in your view are humans where do humans fit into that definition are they general intelligence systems that are able to perform in like how good are they at fulfilling that definition at performing well in multiple environments yeah that's a big question I mean the humans are performing best among all species as we know we know of yeah depends you could say that trees and plants are doing better job they'll probably outlast us so yeah but they're in a much more narrow environment right I mean you just you know I have a little bit of air pollutions and these trees die and we can adapt right we build houses with filters we we we do geoengineering so multiple environment part yes that is very important yes so that distinguish narrow intelligence from wide intelligence also in the AI research so let me ask the the Alan Turing question can machines think can machines be intelligent so in your view I have to kind of ask the answer is probably yes but I want to kind of here with your thoughts on it can machines be made to fulfill this definition of intelligence to achieve intelligence well we are sort of getting there and you know on a small scale we are already there the wide range of environments is missing about yourself driving cars we have programs which play go and chess we have speech recognition so it's pretty amazing but you can you know these are narrow environments but if you look at alpha zero that was also developed by deep mind I mean what famous alphago and then came alpha zero a year later there was truly amazing so on reform a learning algorithm which is able just by self play to play chess and then also go and I mean yes they're both games but they're quite different games and you know this you didn't don't feed them the rules of the game and the most remarkable thing which is still a mystery to me that usually for any decent chess program I don't know much about go you need opening books and endgame tables and so on - and nothing in there nothing was put in there it was alpha zero there's the self play mechanism starting from scratch being able to learn actually new strategies is uh yeah it did rediscovered you know all these famous openings within four hours by himself what I was really happy about I'm a terrible chess player but I like queen Gumby and alpha zero figured out that this is the best opening correct so yes that you do to answer your question yes I believe that general intelligence is possible and it also depends how you define it do you say AGI with general intelligence artificial general intelligence only refers to if you achieve human-level or a subhuman level but quite broad is it also general intelligence so we have to distinguish or it's only super human intelligence general artificial intelligence is there a test in your mind like the Turing test for natural language or some other test that would impress the heck out of you that would kind of cross the line of your sense of intelligence within the framework that you said well the Turing test well has been criticized a lot but I think it's not as bad as some people thinking some people think it's too strong so it tests not just for a system to be intelligent but it also has to fake human deception this section right which is you know much harder and on the other hand they say it's too weak yeah because it just may be fakes you know emotions or intelligent behavior it's not real but I don't think that's the problem or big problem so if if you would pass the Turing test so conversation over terminal with a bot for an hour or maybe a day or so and you can fool a human into you know not knowing whether this is a human or not that it's during tests I would be truly impressed and we have this annual competitions alumna price and I mean it started with Elijah that was the first conversational program and what is it called the Japanese Mitsouko or so that's the winner of the last you know a couple of years and well impressive yes quite impressive and then google has developed Meena right just just recently that's an open domain conversational but just a couple of weeks ago I think yeah I kind of like the metric that sort of the Alexa price has proposed and he maybe it's obvious to you it wasn't to me of setting sort of a length of a conversation like you want the bot to be sufficiently interestingly you'd want to keep talking to it for like 20 minutes and that's a that's a surprisingly effective in aggregate metric because it really like nobody has the patience to be able to talk to about that's not interesting in intelligent and witty and is able to go on the different tangents jump domains be able to you know say something interesting to maintain your attention maybe many humans whoops also fail this test unfortunately we set just like with autonomous vehicles with chat BOTS we also set a bar that's way too hard high to reach I said you know the Turing test is not as bad as some people believe you got what is really not useful about the Turing test it gives us no guidance how to develop these systems in the first place of course you know we can develop them by trial and error and you know do whatever and and then run the test and see whether it works or not but a mathematical definition of intelligence gives us you know an objective which we can then analyze by you know theoretical tools or computational and you know maybe improve how close we are and we will come back to that later with a sexy model so or I mention the compression right so in natural language processing and they have chiefed amazing results and are one way to test this of course you know take the system you train it then you you know see how well it performs on the task but a lot of performance measurement is done by so called perplexity this is essentially the same as complexity or compression length so the NLP community develops new systems and then they measure the compression length and then they have ranking and leaks because there's a strong correlation between compressing well and then this systems performing well at the task at hand it's not perfect but it's good enough for them as as an intermediate aim so you mean a measure so this is kind of almost returning to the coma girl of complexity so you're saying good compression usually means good intelligence yes so you mentioned you're one of the one of the only people who dared boldly to try to formalize our the idea of artificial general intelligence to have a a mathematical framework for intelligence just like as we mentioned termed IHC AI X I so let me ask the basic question what is IHC okay so let me first say what it stands for because letter stands for actually that's probably the more basic question but it the first question is usually how how it's pronounced but finally I put it on the website how it's pronounced and you figured it out yeah the name comes from AI artificial intelligence and the X I is the Greek letter X I which are used for solo manav's distribution for quite stupid reasons which I'm not willing to repeat here in front of camera so it just happened to be more less arbitrary I chose to excite but it also has nice other interpretations so their actions and perceptions in this model write an agent his actions and perceptions and overtime so this is a Index IX index I so this action at time I and then followed by reception at time I will go with that I let it out the first part yes I'm just kidding I have some interpretations so at some point maybe five years ago or ten years ago I discovered in in Barcelona it wasn't a big church there wasn't you know stone engraved some text and the word I see appeared there I was very surprised and and and and happy about it and I looked it up so it is Catalan language and it means with some interpretation of debts it that's the right thing to do yeah Eureka Oh so it's almost like destined somehow came yeah yeah came to you in a dream so Osceola there's a Chinese word I she also written a galaxy if you could transcribe that opinion then the final one is that is AI crossed with induction because status and that's going more to the content now so good old-fashioned AI is more about you know planning and known data mystic world and induction is more about often yellow area D data and inferring models and essentially what this accident does is combining these two and I actually also recently I think heard that in Japanese AI means love so so if you can combine excise somehow with that I think we can there might be some interesting ideas there so I let's then take the next step can you maybe talk at the big level of what is this mathematical framework yeah so it consists essentially of two parts one is the learning and induction and prediction part and the other one is the planning part so let's come first to the learning induction prediction part which essentially I explained already before so what we need for any agent to act well is that it can somehow predict what happens I mean if you have no idea what your actions do how can you decide which acts not good or not so you need to have some model of what your actions affect so what you do is you have some experience you build models like scientists you know of your experience then you hope these models are roughly correct and then you use these models for prediction and the model is sorry to interrupt our model is based on you perception of the world how your actions will affect that world that's not so what is the important part but it is technically important but at this stage we can just think about predicting say stock market data whether data or IQ sequences one two three four five what comes next yeah so of course our actions affect what we're doing but I come back to that in a second so and I'll keep just interrupting so just to draw a line between prediction and planning or what do you mean by prediction in this and this where it's trying to predict the environment without your long-term action in the environment what is prediction okay if you want to put the actions in now okay then let's put in a now yes so the question okay so this is the simplest form of prediction is that you just have data which you passively observe yes and you want to predict what happens without you know interfering as I said weather forecasting stock market IQ sequences or just anything okay and Salama of zeref interaction based on compression so you look for the shortest program which describes your data sequence and then you take this program run it which reproduces your data sequence by definition and then you let it continue running and then it will produce some predictions and you can rigorously prove that for any prediction task this is essentially the best possible predictor of course if there's a prediction task or tasks which is unpredictable like you know your fair coin flips yeah I cannot predict the next fair country but Solomon of Tarsus says okay next head is probably 50% it's the best you can do so if something is unpredictable Salama will also not magically predicted but if there is some pattern and predictability then Solomonov induction we'll figure that out eventually and not just eventually but rather quickly and you can have proof convergence rates whatever your data is so there's pure magic in a sense what's the catch well the catch is that is not computable and we come back to that later you cannot just implement it in even this Google resources here and run it and you know predict the stock market and become rich I mean if ray solomonoff already not write it at the time but the basic task is you know you're in the environment and you're interacting with an environment to try to learn a model the environment and the model is in the space as these all these programs and your goal is to get a bunch of programs that are simple and so let's let's go to the actions now but actually good that you asked usually I skip this part also there is also a minor contribution which I did so the action part but they usually sort of just jump to the decision path so let me explain to the action part now thanks for asking so you have to modify it a little bit by now not just predicting a sequence which just comes to you but you have an observation then you act somehow and then you want to predict the next observation based on the past observation and your action then you take the next action you don't care about predicting it because you're doing it and then you get the next observation and you want more before you get it you want to predict it again based on your past action and observation sequence it's just condition extra on your actions there's an interesting alternative that you also try to predict your own actions if you want oh in the past or the future your future actions wait let me wrap I think my brain is broke we should maybe discussed it later Biff after I've explained the Ising model it's an interesting variation but this is a really interesting variation and a quick comment I don't know if you want to insert that in here but you're looking at in terms of observations you're looking at the entire the big history a long history of the observations exactly it's very important the whole history from birth sort of of the agent and we can come back to that I'm also why this is important here often you know in RL you have MVPs Markov decision processes which are much more limiting okay so now we can predict conditioned on actions so even if the influenced environment but prediction is not all we want to do right we also want to act really in the world and the question is how to choose the actions and we don't want to greedily choose the actions you know just you know what is best in in the next time step and we first I should say you know what is you know how to be measure performance so we measure performance by giving the agent reward that's the so called reinforcement learning framework so every time step you can give it a positive reward or negative reward or baby no reward it could be a very scarce right like if you play chess just at the end of the game you give +1 for winning or -1 for losing so in the aixi framework that's completely sufficient so occasionally you give a reward signal and you ask the agent to maximise reverb but not greedily sort of you know the next one next one because that's very bad in the long run if you're greedy so but over the lifetime of the agent so let's assume the agent lives for M times that'll say it dies in sort of hundred years sharp that's just you know the simplest model to explain so it looks at the future reward sum and ask what is my action sequence or actually more precisely my policy which leads in expectation because I don't know the world to the maximum reward some let me give you an analogy in chess for instance we know how to play optimally in theory it's just a minimax strategy I play the move which seems best to me under the assumption that the opponent plays the move which is best for him so best serve worst for me and the assumption that he I play again the best move and then you have this expecting max three to the end of the game and then you back propagate and then you get the best possible move so that is the optimal strategy which for norman already figured out a long time ago for playing adversarial games luckily or maybe unluckily for the theory it becomes harder the world is not always adversarial so it can be if the other humans even cooperative fear or nature is usually I mean the dead nature is stochastic you know you know things just happen randomly or I don't care about you so what you have to take into account is a noise now and not necessarily Realty so you'll replace the minimum on the opponent's side by an expectation which is general enough to include also the serial cases so now instead of a minimax trials you have an expecting max strategy so far so good so that is well known it's called sequential decision theory but the question is on which probability distribution do you base that if I have the true probability distribution like say I play backgammon right there's dice and there's certain randomness involved you know I can calculate probabilities and feed it in the expecting max or the signature disease we come up is the optimal decision if I have enough compute but in the for the real world we don't know that you know what is the probability you drive in front of me brakes and I don't know you know so depends on all kinds of things and especially new situations I don't know so this is this unknown thing about prediction and there's where solomonoff comes in so what you do is in sequential decision jury it just replace the true distribution which we don't know by this Universal distribution I didn't explicitly talk about it but this is used for universal prediction and plug it into the sequential decision tree mechanism and then you get the best of both worlds you have a long-term planning agent but it doesn't need to know anything about the world because there's a lot of induction part learns can you explicitly try to describe the universal distribution and how some of induction plays a role here yeah I'm trying to understand so what it does it I'm so in the simplest case I said take the shortest program describing your data run it have a prediction which would be deterministic yes okay but you should not just take a shortest program but also consider the longer ones but keep it lower a priori probability so in the Bayesian framework you say a priori any distribution which is a model or stochastic program has a certain a priori probability which is 2 to the minus and Y to the minus length you know I could explain length of this program so longer programs are punished yes a priori and then you multiplied with the so-called likelihood function yeah which is as the name suggests is how likely is this model given the data at hand so if you have a very wrong model it's very unlikely that this model is true so it is very small number so even if the model is simple it gets penalized by that and what you do is then you take just the some word this is the average over it and this gives you a probability distribution so with universal distribution of phenomena of distribution so it's weighed by the simplicity of the program and likelihood yes it's kind of a nice idea yeah so okay and then you said there's you're playing N or M or forgot the letter steps into the future so how difficult is that problem what's involved there okay so here's a customization problem what do we do yes so you have a planning problem up to horizon M and that's exponential time in in the horizon M which is I mean it's computable but in fact intractable I mean even for chess it's already intractable to do that exactly and you know it could be also discounted kind of framework or yes so so having a heart arising you know at numbered years it's just for simplicity of discussing the model and also sometimes the math is simple but there are lots of variations actually quite interesting parameter is its there's nothing really problematic about it but it's very interesting so for instance you think no let's let's then let's let the parameter M tend to infinity right you want an agent which lives forever all right if you do it novel you have two problems first the mathematics breaks down because you have an infinite reward some which may give infinity and getting river 0.1 in the time step is infinity and giving you got one every time service Definity so equally good not really what we want other problem is that if you have an infinite life you can be lazy for as long as you want for ten years yeah and then catch up with the same expected reward and you know think about yourself or you know or maybe you know some friends or so if they knew they lived forever you know why work hard now you know just enjoy your life you know and then catch up later so that's another problem with infinite horizon and you mentioned yes we can go to discounting but then the standard discounting is so called geometric discounting so $1 today is about worth as much as you know one dollar and five cents tomorrow so if you do this so called geometric discounting you have introduced an effective horizon so the Aged is now motivated to had a certain amount of time effectively it's likely moving horizon and for any fixed effective horizon there is a problem to solve which requires larger horizon so if I look ahead you know five time steps I'm a terrible chess player right and I'll need to look ahead longer if I play go I probably have to look ahead even longer so for every problem there forever horizon there is a problem which this horizon cannot solve yes but I introduced the so-called near harmonic horizon which goes down with one or tea rather than exponential in T which produces an agent which effectively looks into the future proportional to its age so if it's five years old it plans for five years if it's hundred years older than plans for hundred years interesting and a little bit similar to humans - right and my children don't plan ahead very long but then we get the doll - a player I had more longer maybe when we get all very old I mean we know that we don't live forever and you're maybe then how horizon shrinks again so just adjusting the horizon what is there some mathematical benefit of that of or is just a nice I mean intuitively empirically probably a good idea to sort of push the horizon back to uh extend the horizon as you experience more of the world but is there some mathematical conclusions here that are beneficial mr. Loman who talks just a prediction probably have extremely strong finite time but no finite data result so you have sown so much data then you lose on so much so so the dt r is really great with the aixi model with the planning part many results are only asymptotic which well this is what is asymptotic means you can prove for instance that in the long run if the agent you know x long enough then you know it performs optimal or some nice things happens so but you don't know how fast it converges yeah so it may converge fast but we're just not able to prove it because a difficult so that is really dead slow yeah so so that is what asymptotic means sort of eventually but we don't know how fast and if I give the agent a fixed horizon M yeah then I cannot prove asymptotic results right so I mean sort of people dies in hundred years then and hundred uses over cannot say eventually so this is the advantage of the discounting that I can prove on some topic results so just to clarify so so I okay I made I've built up a model well now in a moment I've have this way of looking several steps ahead how do I pick what action I will take it's like with a playing chess right you do this minimax in this case here do expect the max based on the selamat of distribution you propagate back and then while inaction falls out the action which maximizes the future expected reward on the Solano's distribution and then you just take this action and then repeat until you get a new observation and you feed it in this excellent observation then you repeat and the reward so on yeah so you're a row - yeah and then maybe you can even predict your own action however the idea but okay this big framework what is it this is I mean it's kind of a beautiful mathematical framework to think about artificial general intelligence what can you what does it help you into it about how to build such systems or maybe from another perspective what does it help us to in understanding AGI so when I started in the field I was always interested two things one was you know AGI i'm the name didn't exist 10 24th of january iowa strong AI and physics he over everything so i switched back and forth between computer science and physics quite often you said the theory of everything the theory of everything just alike it was a basically the string of flavors problems before all all of humanity yeah I can explain if you wanted some later time you know why I'm interesting these two questions Nestle and a small tangent if if if one to be it was one to be solved which one would you if one if you were if an apple found you head and there was a brilliant insight and you could arrive at the solution to one would it be AGI or the theory of everything definitely AGI because once the AGI problem solve they can ask the AGI to solve the other problem for me yeah brilliant a put okay so so as you were saying about it okay so and the reason why I didn't settle I mean this thought about you know once we have solved HDI it solves all kinds of other not just as here every problem about all kinds of use more useful problems to humanity it's very appealing to many people and you know I thought also that I was quite disappointed with the state of the art of the field of AI there was some theory you know about logical reasoning but I was never convinced that this will fly and then there was this Homer more holistic approaches with neural networks and I didn't like these heuristics so and also I didn't have any good idea myself so that's the reason why I toggle back and forth quite some violent even worked some four and a half years and a company developing software something completely unrelated but then I had this idea about the aixi model and so what it gives you it gives you a gold standard so I have proven that this is the most intelligent agents which anybody could build built in quotation mark right because it's just mathematical and you need infinite compute yeah but this is the limit and this is completely specified it's not just a framework and it you know every year tens of frameworks are developed with just have skeletons and then pieces are missing and usually these missing pieces you know turn out to be really really difficult and so this is completely and uniquely defined and we can analyze that mathematically and we've also developed some approximations I can talk about it a little bit later that would dissolve the top-down approach like say for Norman's minimax theory that's the theoretical optimal play of games and now we need to approximate it put heuristics in prune the tree blah blah blah and so on so we can do that also with an icy body but for generally I it can also inspire those and most of most researchers go bottom-up right they have the systems that try to make it more general more intelligent it can inspire in which direction to go what do you mean by that so if you have some choice to make right so how should they evaluate my system if I can't do cross validation how should I do my learning if my standard regularization doesn't work well you know so the answer is always this we have a system which does everything that's actually it's just you know completing the ivory tower completely useless from a practical point of view but you can look at it and see oh yeah maybe you know I can take some aspects and you know instead of Kolmogorov complexity there just take some compressors which has been developed so far and for the planning well we have used it here which is also you know being used in go and it at least it's inspired me a lot to have this formal definition and if you look at other fields you know like I always come back to physics because I'm a physics background think about the Phenom of energy that was long time a mysterious concept and at some point it was completely formalized and that really helped a lot and you can point out a lot of these things which were first mysterious and wake and then they have been rigorously formalized speed and acceleration has been confused tried until it was formally defined here there was a time like this and in people you know often you know know don't have any background you know still confused it so and this is a model or the the intelligence definitions which is sort of the dual to it we come back to that later formalizes the notion of intelligence uniquely and rigorously so in in the sense it serves as kind of the light at the end of the tunnel so before yeah so I mean there's a million question I could ask her so maybe the kind of ok let's feel around in the dark a little bit so there's been here a deep mind but in general been a lot of breakthrough ideas just like we've been saying around reinforcement learning so how do you see the progress in reinforcement learning is different like which subset of IHC does it occupy the current like you said the maybe the Markov assumptions made quite often in reinforce for learning the there's other assumptions made in order to make the system work what do you see is the difference connection between reinforcement learning in Nyack see and so the major difference is that essentially all other approaches they make stronger assumptions so in reinforcement learning the Markov assumption is that the the next state or next observation only depends on the on the previous observation and not the whole history which makes of course the mathematics much easier and rather than dealing with histories of course their profit from it also because then you have algorithms that run on current computers and do something practically useful but for generally are all the assumptions which are made by other approaches we know already now they are limiting so for instance usually you need a go digital assumption in the MDP frameworks in order to learn it goes this T essentially means that you can recover from your mistakes and that they are not traps in the environment and if you make this assumption then essentially it can you know go back to a previous state go there a couple of times and then learn what what statistics and what the state is like and then in the long run perform well in this state yeah but there are no fundamental problems but in real life we know you know there can be one single action you know one second of being inattentive while driving a car fast you know you can ruin the rest of my life I can become quadriplegic or whatever so and there's no recovery anymore so the real world is not err gorica I always say you know there are traps and there are situations we are not recover from and very little theory has been developed for this case what about what do you see in there in the context of I see as the role of exploration sort of you mentioned you know in the in the real world and get into trouble when we make the wrong decisions and really pay for it but exploration it seems to be fundamentally important for learning about this world for gaining new knowledge so is it his exploration baked in another way to ask it what are the parameters of this of IHC it can be controlled yeah I say the good thing is that there are no parameters to control and some other people track knobs to control and you can do that I mean you can modify axes so that you have some knobs to play with if you want to but the exploration is directly baked in and that comes from the Bayesian learning and the long-term planning so these together already imply exploration you can nicely and explicitly prove that for simple problems like so-called banded problems where you say to give a real world example say you have two medical treatments a and B you don't know the effectiveness you try a a little bit be a little bit but you don't want to harm too many patients so you have to sort of trade-off exploring yeah and at some point you want to explore and you can do the mathematics and figure out the optimal strategy it took a Bayesian agency also non-bayesian agents but it shows that this Bayesian framework by taking a prior over possible world's doing the Bayesian mixture then the Bayes optimal decision with long term planning that is important automatically implies exploration also to the proper extent not to much exploration and not too little in this very simple settings in the IHC model and was also able to prove that it is a self optimizing theorem or asymptotic optimality theorems or later only asymptotic not finite time bounds it seems like the long term planning is a really important but the long term part of the planet is really important yes and also I mean maybe a quick tangent how important do you think is removing the Markov assumption and looking at the full history sort of intuitively of course it's important but is it like fundamentally transformative to the entirety of the problem what's your sense of it like because we all we make that assumption quite often it's just throwing away the past now I think it's absolutely crucial the question is whether there's a way to deal with it in a more holistic and still sufficiently well way so I have to come up with an example and fly but you know you have say some you know key event in your life you know a long time ago you know in some city or something you realize you know that's a really dangerous street or whatever right here and you want to remember that forever right in case you come back they're kind of a selective kind of memory so you remember that all the important events in the past but somehow selecting the importance is see that's very hard yeah and I'm not concerned about you know just storing the whole history just you can calculate you know human life says so you're 100 years doesn't matter right how much data comes in through the vision system and the auditory system you compress it a little bit in this case law silly and store it we are soon in the means of just storing it yeah but you still need to the selection for the planning part and the compression for the understanding part the raw storage I'm really not concerned about and I think we should just store if you develop an agent preferably just restore all the interaction history and then you build of course models on top of it and you compress it and you are selective but occasionally you go back to the old data and reanalyze it based on your new experience you have you know sometimes you you're in school you learn all these things you think it's totally useless and you know much later you realize not you know it looks like as you thought I'm looking at you linear algebra right so maybe a minute let me ask about objective functions because that rewards it seems to be an important part the rewards are kind of given to the system for a lot of people the the specification of the objective function is a key part of intelligence like the the agent itself figuring out what is important what do you think about that is it possible within IHC framework to yourself discover the reward based on which you should operate okay that'll be a long answer so and it is a very interesting question and I asked a lot about this question where do the rivers come from and that depends yeah so and there you know I give you now a couple of answers so if you want to build agents now let's start simple so let's assume we want to build an agent based on the aixi model which performs a particular task let's start with something super simple like I mean super simple like playing chess or go or something yeah then you just you know the reward is you know winning the game is plus one losing theorems minus one done you apply this agent if you have enough compute you let itself play and it will learn the rules of the game will play perfect chess after some while problem solve okay so if you have more complicated problems then you may believe that you have the right rewrote but it's not so a nice cute example is elevator control that is also in rich Sutton's book which is a great book by the way so you control the elevator and you think well maybe the reward should be coupled to how long people wait in front of the elevator you know long wait is bad you program it and you do it and what happens is the elevator eagerly picks up all the people but never drops them off maybe the time in the elevator also counts so you minimize the sum yeah yeah in the elevator does that but never picks up the people in the tenth row in the top floor because in expectation it's not worth it just let them stay so so even in apparently simple problems you can make mistakes you know and that's what in in war serious context say a GI safety researchers consider so now let's go back to general agents so assume you want to build an agent which is generally useful to humans yes we have a household robot here and it should do all kinds of tasks so in this case the human should give the reward on the fly I mean maybe it's pre trained in the factory and there there's some sort of internal reward for you know the battery level or whatever here but so it you know it does the dishes badly you know you punish the robot intercept good you read what the robot and then train it do a new task you know like a child right so you need the human in the loop if you want a system which is useful to the human and as long as this agent stays up human level that should work reasonably well I'm apart from you know these examples it becomes critical if they become you know on a human level it's it's that miss children small children you have reason to be well under control they become older the river technique doesn't work so well anymore so then finally so this would be agents which are just you could sorry slaves to the humans yeah so if you are more ambitious and just say we want to build a new species of intelligent beings we put them on a new planet and we want them to develop this planet or whatever so we don't give them any reward so what could we do and you could try to you know come up with some reward functions like you know it should maintain itself the robot it should maybe multiply build more robots right and you know maybe for all kinds of things did you find useful but that's pretty hard right you know what what the self maintenance mean you know what does it mean to build a copy should be exact copy an approximate copy and so that's really hard but LaVon or so also a deep mind developed a beautiful model so it just took the aixi model and coupled the rewards to information gained so he said the reward is proportional to how much the agent had learned about the world and you can rigorously formally uniquely define it in terms of our case versions okay so if you put it in you get a completely autonomous agent and actually interestingly for this agent we can prove much stronger result and for the general agent which is also nice and if you let this agent loose it will be in a sense the optimal scientist is this absolutely curious to learn as much as possible about the world and of course it will also have a lot of instrumental goals right in order to learn it needs to at least survive right a dead agent is not good for anything so it needs to have self-preservation and if it builds small helpless acquiring more information it will do that yeah if exploration space exploration or whatever is necessary rights to gathering information and develop it so it has a lot of instrumental goals following on this information gain and this agent is completely autonomous of us no rebirth necessary anymore yeah of course you could define the awaited game the concept of information it gets stuck in that library that you mentioned beforehand with the was a very large number of books the first agent had this problem and it would get stuck in front of an old TV screen which has just said white noise yeah I know but the second version can deal with at least stochasticity well yeah what about curiosity this kind of word curiosity creativity is that kind of the reward function being of getting new information is that similar to idea of kind of injecting exploration for its own sake inside the reward function do you find this at all appealing interesting I think that's a nice definition curiosity is reward sorry curiosity is exploration for its own sake yeah I would accept that but most curiosity well in humans and especially in children yeah it's not just for its own sake but for actually learning about the environment and for behaving so I would I think most curiosity is tied in the end towards performing better well okay so if intelligence systems need to have the show function let me you're an intelligent system currently passing the Turing test quite effectively what what's the reward function of our human intelligence existence what's the reward function that Marcus hunter is operating under okay to the first question the biological reward function is to survive and to spread and very few humans sort of are able to overcome this biological reward function but we live in a very nice world where we have lots of spare time and can still survive and spread so we can develop arbitrary other interests which is quite interesting on top of that that yeah but this survival and spreading sort of is I would say the the goal or the reward function of human said that the core one I like how you avoided answering the second question which a good intelligence would so my that your own meaning of life and the reward function my own meaning of life and Riyad function is to find an AGI to build it beautifully put okay let's dissect Ickes even further so one of the assumptions is kind of infinity keeps creeping up everywhere which what are your thoughts and kind of bounded rationality and so the nature of our existence and intelligence systems is that we're operating all under constraints under you know limited time limited resources how does that how do you think about that with an IQ framework within trying to create an eg a system that operates under these constraints yeah that is one of the criticisms around I could see that it ignores computation and completely and some people believe that intelligence is inherently tied to what's bounded resources what do you think on this one point I think it's do you think the boundary of resources are fundamental to intelligence I would say that an intelligence notion which ignore computational limits is extremely useful a good intelligence notion which includes these resources would be even more useful but we don't have that yet and so look at other fields outside of computer science computational aspects never play a fundamental role you develop biological models for cells something in physics these theories I mean become more and more crazy and hard and harder to compute well in the end of course we need to do something with this model but this more a nuisance than a feature and I'm sometimes wondering if artificial intelligence would not sit in a computer science department but in a philosophy department then this computational focus would be probably significantly less I mean think about the induction problem is more in the philosophy department there's really no paper who cares about you know how long it takes to compute the answer there is completely secondary of course once we have figured out the first problem so intelligence without computational resources then the next and very good question is could we improve it by including computational resources but nobody was able to do that so far you know even halfway satisfactory manner I like that that's in the long run the right department to belong to this philosophy that's uh it's really quite a deep idea of or even to at least to think about big-picture philosophical questions big-picture questions even in the computer science department but you've mentioned approximation sort of there's a lot of infinity a lot of huge resources needed are there approximations - I see that within the EXCI framework that are useful you haven't haven't develop a couple of approximations and what we do there is that the Sonoma of induction part which was you know find the shortest program describe your data we just replace this by standard data compressors right and the better compressors get you know the better this part will become we focus on a particular compressor called context tree weighting which is pretty amazing lots of well known as beautiful theoretical properties also works reasonably well in practice so we use that for the approximation of the induction in the learning in the prediction part and from the planning part we essentially just took the ideas from a computer girl from 2006 I was Java tsipras Perry also now I did mind who developed the so-called you sit here algorithm upper confidence bound for trees algorithm on top of the Monte Carlo tree search so they approximate is planning part by sampling and it's successful on some small toy problems we don't want to lose the generality all right and that's sort of the handicap right if you want to be general you have to give up something so but this similar agent was able to play you know small games like cool poker and tic-tac-toe and and even pac-man into the same architecture no change the agent doesn't know the rules of the game really nothing in all by self or by a player with these environments so your grenade hoop would propose something called gate on machines which is a self-improving program that rewrites its own code well sort of mathematically philosophically what's the relationship in your eyes if you're familiar with it between IHC and the girl machines yeah familiar with it he developed it while I was in his lab you know so the girl machine explained briefly you give it a task it could be a simple task as you know finding prime factors in numbers right you can formally write it down there's a very slow algorithm to do that just all try all the factors yeah or play chess right optimally you write the algorithm to minimax to the end of the game so you write down what the girdle machine should do then it will take part of it resources to run this program and other part of the sources to improve this program and when it finds an improved version which provably it's the same answer so that's the key part yeah it needs to prove by itself that this change of program still satisfies the original specification and if it does so then it replaces the original program by the improved program and by definition does the same job but just faster okay and then you know it proved over it and over it and it's it's it's developed in a way that all parts of this girdle machine can self improve but it stays provably consistent with the original specification so from this perspective it has nothing to do with aixi but if you would now put axial as the starting axioms in it would run arc C but you know that takes forever but then if it finds a provable speed-up of Arc C it would replace it by this and that this and this and maybe eventually it comes up with a model which is still like C model it cannot be I mean just for the knowledgeable reader accessing computable and there can prove that therefore there cannot be a computable exact algorithm computers there needs to be some approximations and this is not dealt with a good machine so you have to do something about it but that's the ICT L model which is finitely computable which we could put in which part of X is an non computable the Solomonov induction part the interaction okay so but there's ways of getting computable approximation of the aixi model so then it's at least computable it is still way beyond any resources anybody will ever have but then the girdled machine could sort of improve it further and further in an exact way so what this is theoretically possible that the the girl machine process could improve isn't isn't or isn't actually already optimal it is optimal in terms of the river collected over its interaction cycles but it takes infinite time to produce one action and the world you know continues whether you want it or not yeah so the model is assuming had an Oracle which you know solve this problem and then in the next hundred milliseconds or reaction time you need gives the answer then ax is optimal so it's optimal in sense of date are also from learning efficiency and data efficiency but not in terms of computation time and then the other girl machine in theory but probably not provably could make it go faster yes ok interesting those two components are super interesting the sort of the the perfect intelligence combined with self-improvement sort of provable self improvement since he always liked it you're always getting the correct answer and you're improving the beautiful ideas okay so you've also mentioned that different kinds of things in in chase of solving this reward sort of optimizing for the goal interesting human things can emerge so is there a place for consciousness within IHC what where does uh maybe you can comment because I suppose we humans are just another instantiation Vioxx agents and we seem to have consciousness you say humans are an instantiation of Mike's agent yes oh that would be amazing but I think that's three for the smartest and most rational humans I think maybe we are very crude approximation interesting I mean I tend to believe again I'm Russian so I tend to believe our flaws are part of the optimal so the we tend to laugh off and criticize our flaws and I tend to think that that's actually close to an optimal behavior but some flaws if you think more carefully about it are actually not floss yeah but I think there are still enough flaws I don't know it's unclear as a student of history I think all the suffering that we've been endured as a civilization it's possible that that's the optimal amount of suffering we need to endure to minimize the long-term suffering that's your Russian background that's the Russian weather whoo humans are or not instantiation of an AI agent do you think there's a consciousness of something that could emerge in the no formal framework like IHC let me also ask you a question do you think I'm conscious that's a good question you you're that that tie is confusing me but I think you think it makes me unconscious because it strangles me if if an agent were to solve the imitation game posed by touring I think they would be dressed similarly to you that because there's a there's a kind of flamboyant interesting complex behavior pattern that sells that you're human and you're cautious but why do you ask was it a yes always gonna know yes I think you're conscious yes yeah so and you explain sort of somehow why but you infer that from my behavior right yeah you can never be sure about that and I think the same thing will happen with any intelligent way to be developed if it behaves in a way sufficiently close to humans or maybe if not humans I mean you know maybe a dog is also sometimes a little bit self-conscious right so so if it behaves in a way where we attribute typically consciousness we would actually build consciousness to this intelligent systems and you know except all in particular that of course doesn't answer the question whether it's really conscious and that's the you know the big hard problem of consciousness you know maybe I'm a zombie I mean not the movie zombie but the philosophical zombie it's to you the display of consciousness close enough to consciousness from a perspective of a GI that the distinction of the hard problem of consciousness is not an interesting one I think we don't have to worry about the consciousness problem especially the heart problem for developing a GI I think you know we progress at some point we have solved all the technical problems and this system will behave intelligent and then super intelligent and this consciousness will emerge I mean definitely it will display behavior which we will interpret as conscious and then it's a philosophical question did this consciousness really emerge or is zombie which just you know fakes everything we still don't have to figure that out although it may be interesting at least from a philosophical point of it's very interesting but it may also be sort of practically interesting you know there's some people say you know if it's just faking consciousness and feelings you know then we don't need to have be concerned about you know rights but if it's real conscious and has feelings then we need to be concerned yeah I can't wait til the day where AI systems exhibit consciousness because it'll truly be some of the hardest ethical questions how well we do with that it is rather easy to build systems which people ascribe consciousness and I give you an analogy I mean remember maybe once before you were born the Tamagotchi yes how dare you sir you're young right yes it's good thing yeah thank you thank you very much but I was also in the so you have any of those funny things but you have heard about this time ago it was you know really really primitive actually for the time it was and you know you could race you know this and and and and kids got so attached to it and you know didn't want to let it die and would have probably if we would have asked you know the children know do you think this drama coach is conscious and they would say yes yes I was yes that's kind of a beautiful thing actually because that consciousness ascribing consciousness seems to create a deeper connection yeah which is a powerful thing but we have to be careful on the ethics side of that well let me ask about the AGI community broadly you kind of represent some of the most serious work on a giass of at least or earlier and deepmind represents a serious work on AGI these days but why in your sense is the AGI communities so small or has been so small until maybe deep mine came along like why why aren't more people seriously working on human level and super human level intelligence from a formal perspective okay from a formal perspective that sort of you know and an extra point so I think a couple of reasons I mean AI came in waves right you know our interest in our summers and then there were big promises which were not fulfilled and people got disappointed and that narrow AI are sold in particular problems which seem to require intelligence was always to some extent successful and there were improvements small steps and if you build something which is you know useful for society or industrial useful then there's a lot of funding so I guess it wasn't pass the money which drives people to develop specific system solving specific tasks but you would think that you know at least on university you should be able to do ivory tower research and that was probably better a long time ago about even nowadays there's quite some pressure off of doing applied research or translational research and you know it's harder to get grants as a theorist so that also drives people away it's maybe also harder attacking the general intelligence problem so I think enough people I mean maybe a small number we're still interested in in formalizing intelligence and thinking of general intelligence but you know not much came up right or not much great stuff came up so what do you think we talked about the formal big light at the end of the tunnel but from the engineering perspective what do you think it takes to build an a GI system is it and I don't know if that's a stupid question or a distinct question from everything we've been talking about I exceed but what do you see as the steps that are necessary to take to start to try to build something so you wanted a blue print now and then you go and do it it's the whole point of this conversation try to squeeze that in there now is there I mean what's your intuition is it is in the robotic space or something that has a body and tries to explore the world is in the reinforcement learning space like the efforts of the alpha 0 and alpha star they're kind of exploring how you can solve it through in in the simulation in the gaming world their stuff and sort of the of the transformer working natural English processing so maybe attacking the open domain dialog like what where do you see a promising pathways let me pick the embodiment maybe so embodiment is important yes and no I don't believe that we need a physical robots walking or rolling around interacting with the real world in order to achieve AGI and I think it's more of a distraction probably than helpful it's sort of confusing the body with the mind for industrial applications or near-term applications of course we need robotics for all kinds of things yeah but for solving the big problem at least at this stage I think it's not necessary but the answer is also yes that I think the most promising approaches that you have an agent and you know there can be a virtual agent you know you know computer interacting with an environment possibly in our 3d simulated environment like in many computer games and and you train and learn the agent even if you don't intend to later put it sort of you know this algorithm in a robot brain and leave it forever in the virtual reality getting experience in a also it's just simulated 3d world is possibly and I say possibly important to understand things on a similar level as humans do especially if the agent or primarily if the agent wants needs to interact with the humans right you know if you talk about objects on top of each other in space and flying and cars and so on and the agent has no experience with even virtual 3d worlds it's probably hard to grasp so if you develop an abstract agent say we take the mathematical path and we just want to build an agent which can prove theorems and becomes a better imitation then this agent needs to be able to reason in very abstract spaces and then maybe sort of putting it into 3d environment simulated alt is even harmful it should sort of you put it in I don't know an environment which it creates itself or so it seems like you have an interesting rich complex trajectory through life in terms of your journey of ideas so it's interesting to ask what books technical fiction philosophical and books ideas people had a transformative effect books are most interesting because maybe people could also read those books and see if they could be inspired as well you're luckily asked books and not singular book it's very hard and I tried to pin down one book yeah then I can do that at the end so the most the books which were most transformative for me or which I can most highly recommend to people interested in AI both perhaps yeah I would always start with Russell and Norvig artificial intelligence a modern approach that's the AI Bible it's an amazing book it's very broad it covers you know all approaches to AI and even if you focus on one approach I think that is the minimum you should know about the other approaches out there so that should be your first book fourth edition should be coming out soon okay interesting deeper there's a deep learning chapter now so there must be written by Ian good fella okay and then the next book I would recommend the reinforcement only book by certain in part oh there's a beautiful book if there's any problem with the book it makes our L feel and look much easier than it actually is it's very gentle book it's very nice to read the exercises do you can very quickly you know get some aerial systems to run you know on very toy problems but it's a lot of fun and you in very in a couple of days you feel you know you know what RL is about but it's much harder than the book yeah come on now it's an awesome book yeah that idea's yeah and maybe I mean there's so many books out there if you like the information theoretic approach then there's Kolmogorov complexity by Alene batani but probably you know some some short article is enough you don't need to read a whole book but it's a great book and if you have to mention one all-time favorite book so different flavor that's a book which is used in the International Baccalaureate for high school students in several countries that's from Nicolas alchun theory of knowledge second edition or first not assert least the third one they put they took out all the fun okay so this asked all the interesting or to me interesting philosophical questions about how we acquire knowledge from all perspectives on from math from art from physics and ask how can we know I'm anything and book is called theory of knowledge from which is almost like a philosophical exploration of how we get knowledge from anything yes yeah I mean can religion tell us you know about something about the world can science tell us something about the world can mathematics so as it's just playing with symbols and onions open-ended questions and I mean it's for high school students so they have been resources from Hitchhiker's Guide to the galaxy and from Star Wars and the chicken cross the road yeah and it's it's it's fun to read and but it's also quite deep if you could live one day of your life over again because it made you truly happy or maybe like we said with the books it was truly transformative what what day what moment would you choose there's something pop into your mind doesn't need to be a day in the past or can it be a day in the future well space-time is an emergent phenomena so it's all the same anyway okay okay from the past you're really good saved from the future I love it no I will also tell you from the future okay from the past I would say when I discovered Maxim Allah I mean it was not in one day but it was one moment they are realized comig of complexity and didn't even know that it existed but I rediscovered sort of this compression idea myself but immediately I knew I can't be the first one but I had this idea and then I knew about sequential decision ray and I knew if I put it together this is the right thing and yeah I'm still when I think back about this moment I'm I'm super excited about it was there was there any more details and context that moment did an apple fall in your head were so like if you look at en Goodfellow talking about Gans there was beer involved there is there some more context of what sparked your thought it was a jest and no it was much more mundane so I've worked in this company so in this sense the four and a half years was not completely wasted so and I've worked on an image interpolation problem and I developed a quite neat new interpolation techniques and they got patented and then I you know and which happens quite often I got sort of overboard and thought about you know yeah that's pretty good but it's not the best so what is the best possible way of doing in the interpolation and then I thought yeah you you want the simplest picture which is if you cross train it recovers your original picture and then I you know thought about the simplicity concept more in quantitative terms and you know then everything developed and somehow love the full beautiful mix of also being a physicist and thinking about the big picture of it then led you to probably the end of a good idea so as a physicist I was probably trained not to always think in computational terms you know just ignore that and think about the other two the fundamental properties which you want to have so what about if you could really one day in the future all the day what would that be when I solve the AGI problem and I bring the practice in practice so in theory I have solved it that I see what already attracted me and then ask the first question or would be the first question what's the meaning of life I don't think there's a better way to end it thank you so much for talking it is a huge honor to finally meet you yeah thank you - I was a pleasure off my side - thanks for listening to this conversation with Marcus hunter and thank you to our presenting sponsor cash app downloaded you just cold legs podcast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman and now let me leave you with some words of wisdom from Albert Einstein the measure of intelligence is the ability to change for listening and hope to see you next time you |
Michael I. Jordan: Machine Learning, Recommender Systems, and Future of AI | Lex Fridman Podcast #74 | the following is a conversation with michael i jordan a professor at berkeley and one of the most influential people in the history of machine learning statistics and artificial intelligence he has been cited over 170 thousand times and has mentored many of the world-class researchers defining the field of ai today including andrew eng zubin garamani bentascar and yoshio banjo all this to me is as impressive as the over 32 000 points and the six nba championships of the michael j jordan of basketball fame there's a non-zero probability that i talked to the other michael jordan given my connection to and love the chicago bulls of the 90s but if i had to pick one i'm going with the michael jordan of statistics and computer science or as john le calls him the miles davis of machine learning in his blog post titled artificial intelligence the revolution hasn't happened yet michael argues for broadening the scope or the artificial intelligence field in many ways the underlying spirit of this podcast is the same to see artificial intelligence as a deeply human endeavor to not only engineer algorithms and robots but to understand and empower human beings at all levels of abstractions from the individual to our civilization as a whole this is the artificial intelligence podcast if you enjoy it subscribe on youtube give it five stars at apple podcast support it on patreon or simply connect with me on twitter at lex friedman spelled friday as usual i'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation i hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the app store when you get it use code lex podcast cash app unless you send money to friends buy bitcoin and invest in the stock market with as little as one dollar since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is to me an algorithmic marvel so big props for the cash app engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so once again if you get cash app from the app store or google play and use the code lex podcast you'll get ten dollars and cash app will also donate ten dollars the first one of my favorite organizations that is helping to advance robotics and stem education for young people around the world and now here's my conversation with michael i jordan given that you're one of the greats in the field of ai machine learning computer science and so on you're trivially called the michael jordan of machine learning although as you know you were born first so technically mj is the michael i jordan of basketball but anyway my my favorite is yan la calling you the miles davis of machine learning because as he says you reinvent yourself periodically and sometimes leave fans scratching their heads after you change direction so can you put at first your historian hat on and give a history of computer science and ai as you saw it as you experienced it including the four generations of ai successes that i've seen you talk about sure yeah first of all i much prefer yon's metaphor um miles davis is uh was a real explorer in jazz and um he had a coherent story so i think i have one and but it's not just the one you live it's the one you think about later what a good historian does is they look back and they revisit um i think what happening right now is not ai that was an intellectual aspiration um that's still alive today is an aspiration but i think this is akin to the development of chemical engineering from chemistry or electrical engineering from from electromagnetism so if you go back to the 30s or 40s there wasn't yet chemical engineering there was chemistry there was fluid flow there was mechanics and so on but people pretty clearly viewed interesting goals try to build factories that you make chemicals products and do it viably safely make good ones do it at scale so people started to try to do that of course and some factories worked some didn't you know some were not viable some exploded but in parallel developed a whole field called chemical engineering right and chemical engineering is a field it's it's no no bones about it it has theoretical aspects to it it has practical aspects it's not just engineering quote unquote it's the real thing real concepts are needed same thing with electrical engineering you know there was maxwell's equations which in some sense were everything you know about electromagnetism but you needed to figure out how to build circuits how to build modules how to put them together how to bring electricity from one point to another safely and so on so forth so whole field is developed called electrical engineering all right i think that's what's happening right now is that we have we have a proto field which is statistics compute more the theoretical side of the algorithmic side of computer science that was enough to start to build things but what things systems that bring value to human beings and use human data and mix in human decisions the engineering side of that is all ad hoc that's what's emerging in fact if you want to call machine learning a field i think that's what it is that's a proto form of engineering based on statistical and computational ideas of previous generations but do you think there's something deeper about ai in his dreams and aspirations as compared to chemical engineering and electrical engineering well the dreams and aspirations maybe but those are from those are 500 years from now i think that that's like the greek sitting there and saying it would be neat to get to the moon someday right um i hate we have no clue how the brain does computation uh we're just a clueless we're like we're even worse than the greeks almost anything interesting uh scientifically of our era can you linger on that just for a moment because you stand not completely unique but a little bit unique in that in the clarity of that can you can you elaborate your intuition of why we like where we stand in our understanding of the human brain and a lot of people say you know scientists say we're not very far in understanding human brain but you're like you're saying we're in the dark here well i know i'm not unique i don't even think in the clarity but if you talk to real neuroscientists that really study real synapses or real neurons they agree they agree it's a hundred year hundreds of year tasks and they're building it up slowly surely what the signal is there is not clear we think we have all of our metaphors we think it's electrical maybe it's chemical it's a whole soup it's ions and proteins and it's a cell and that's even around like a single synapse if you look at a electromicrograph of a single synapse it's a it's a city of its own and that's one little thing on a dendritic tree which is extremely complicated you know electrochemical thing and it's doing these spikes and voltages have been flying around and then proteins are taking that and taking it down into the dna and who knows what so it is the problem of the next few centuries it is fantastic but we have our metaphors about it is it an economic device is it like the immune system or is it like a layered you know set of copy you know arithmetic computations what we have all these metaphors and they're fun but that's not real science per se there is neuroscience that's not neuroscience all right that that's that's like the greek speculating about how to get to the moon fun right and i think that i like to say this fairly strongly because i think a lot of young people think we're on the verge because a lot of people who don't talk about it clearly let it be understood that yes we kind of this is brain inspired we're kind of close you know breakthroughs are on the horizon and unscrupulous people sometimes who need money for their labs um as i'm saying scrupulous but people will oversell um i need money from a lab i'm gonna i'm studying here you know computational neuroscience um i'm gonna oversell it and so there's been too much of that so i'll step into the slight the gray area between metaphor and engineering with uh i'm not sure if you're familiar with brain computer interfaces so a company like elon musk has neural link that's working on putting electrodes into the brain and trying to be able to read both read and send electrical signals just as you said even the basic mechanism of communication in the brain is not something we understand but do you hope without understanding the fundamental principles of how the brain works we'll be able to do something interesting at that gray area of metaphor it's not my area so i i hope in the sense like anybody else hopes for some interesting things to happen from research i would expect more something like alzheimer's will get figured out from modern neuroscience that you know a lot of there's a lot of human suffering based on brain disease and we throw things like lithium at the brain it kind of works no one has a clue why that's not quite true but you know mostly we don't know and that's even just about the biochemistry of the brain and how it leads to mood swings and so on how thought emerges from that we just we were really really completely dim so that you might want to hook up electrodes and try to do some signal processing on that and try to find patterns fine you know by all means go for it it's just not scientific at this point it's just it's so it's like kind of sitting in a satellite and watching the emissions from a city and trying to affirm things about the micro economy even though you don't have microeconomic concepts i mean it's really that kind of thing and so yes can you find some signals that do something interesting or useful can you control a cursor or mouse with your brain yeah absolutely you know and then i can imagine business models based on that and even you know medical applications of that but from there to understanding algorithms that allow us to really tie in deeply to from the brain to computer you know i just no i don't agree with elon musk i don't think that's even that's not for our generation it's not even for the century so just uh in hopes of getting you to dream uh you've mentioned kolmogorov and touring might pop up do you think that there might be breakthroughs they'll get you to sit back in five ten years and say wow oh i'm sure there will be but i don't think that there'll be demos that impress me i don't think that having a computer call a restaurant and pretend to be a human is a breakthrough and people you know some people present it as such it's imitating human intelligence it's even putting coughs in the thing to make a bit of a pr stunt and so fine the world runs on those things too and i don't want to diminish all the hard work and engineering that goes behind things like that and and the ultimate value to the human race but that's not scientific understanding and and i know the people who work on these things they are after a scientific understanding you know in the meantime they've got to kind of you know the trains got to run and they got miles to feed and they got things to do and there's nothing wrong with all that i would call that though just engineering and i want to distinguish that between an engineering field like electoral internet chemical injury that originally that originally emerged that had real principles and you really knew what you're doing and you had a little scientific understanding maybe not even complete so it became more predictable and it was really gave value to human life because it was understood and and so we have to we don't want to muddle too much these waters of you know what we're able to do versus what we really can do in a way that's going to impress the next so i don't i don't need to be wowed but i i think that someone comes along in 20 years a younger person who's absorbed all the uh the technology and for them to be wowed i think they have to be more deeply impressed a young kulmogorov would not be wowed by some of the stunts that you see right now coming from the big companies the demos but do you think the breakthroughs from kolmogorov would be and give this question a chance do you think they'll be in the scientific fundamental principles arena or do you think it's possible to have fundamental breakthroughs in engineering meaning you know i would say some of the things that elon musk is working with spacex and then others sort of trying to revolutionize the fundamentals of engineering of manufacturing of of saying here's a problem we know how to do a demo of and actually taking it to scale yeah so so there's going to be all kinds of breakthroughs i just don't like that terminology i'm a scientist and i work on things day in and day out and things move along and eventually say wow something happened but it's i don't like that language very much also i don't like to prize theoretical breakthroughs over practical ones um i tend to be more of a theoretician and i think there's lots to do in that arena right now um and so i wouldn't point to the komo gurus i might point to the edisons of the era and maybe musk is a bit more like that but um you know musk god bless him also we'll say things about ai that he knows very little about and and he doesn't know what he's he he is you know leads people astray when he talks about things he doesn't know anything about trying to program a computer to understand natural language to be involved in a dialogue we're having right now that can happen in our lifetime you could fake it you can mimic sort of take old sentences that humans use and retread them with the deep understanding of language now it's not going to happen and so from that you know i hope you can perceive that the deeper yet deeper kind of aspects and intelligence are not going to happen now will there be breakthroughs you know i think that google was a breakthrough i think amazon's a breakthrough you know i think uber is a breakthrough you know that bring value to human beings at scale in new brand new ways based on data flows and and so on a lot of these things are slightly broken because there's not a kind of a engineering field that takes economic value in context of data and and at you know planetary scale and and worries about all the externalities the privacy you know we don't have that field so we don't think these things through very well but i see that is emerging and that will be cons that will you know looking back from 100 years that will be constituted a breakthrough in this era just like electrical engineering was a breakthrough in the early part of the last century and chemical injury was a breakthrough so the scale the markets that you talk about and we'll get to will be seen as sort of breakthrough and we're in the very early days of really doing interesting stuff there and we'll get to that but it's just taking a quick step back can you give uh we kind of threw off the historian hat i mean you briefly said that uh in the history of ai kind of mimics the history of chemical engineering but i keep saying machine learning you keep want to say ai just to let you know i don't you know i i'd resist that i don't think this is about ai really was john mccarthy as almost a philosopher saying wouldn't it be cool if we could put thought in a computer if we could mimic the human capability to think or put intelligence in in some sense into a computer that's an interesting philosophical question and he wanted to make it more than philosophy he wanted to actually write down logical formula and algorithms that would do that and that is a perfectly valid reasonable thing to do that's not what's happening in this era right so so the reason i keep saying ai actually and i'd love to hear what you think about it machine learning has uh has a very particular set of methods and tools maybe your version of it is that mine doesn't no it does it's very very open it does optimization it does sampling it does so systems that learn is what machine learning is systems that learn and make decisions and make decisions so what is pattern recognition and from you know finding patterns it's all about making decisions in real worlds and having close feedback loops so something like symbolic ai expert systems reading systems knowledge based representation all of those kinds of things search does that neighbor fit into what you think of as machine learning so i don't even like the word but you know i think that with the field you're talking about is all about making large collections of decisions under uncertainty by large collections of entities yes right and there are principles for that at that scale you don't have to say the principles are for a single entity that's making decisions a single agent or a single human it really immediately goes to the network of decisions is a good award for that or no no there's no good words for any of this that's kind of part of the problem um so we can continue the conversation use ai for all that i just want to kind of raise our flag here that this is not about we don't know what intelligence is and real intelligence we don't know much about abstraction and reasoning at the level of humans we don't have a clue we're not trying to build that because we don't have a clue eventually it may emerge they'll make i don't know if there'll be breakthroughs but eventually we'll start to get glimmers of that it's not what's happening right now though okay we're taking data we're trying to make good decisions based on that we're trying to scale we're trying to do it economically viably we're trying to build markets we're trying to keep value at that scale and aspects of this will look intelligent it will look computers were so dumb before they will seem more intelligent we will use that buzz word of intelligence so we can use it in that sense but you know so machine learning you can scope it narrowly is just learning from data and pattern recognition but whatever i when i talk about these topics i maybe data science is another word you could throw in the mix it really is important that the decisions are as part of it it's consequential decisions in the real world are i have a medical operation am i going to drive down the street you know things that where their scarcity things that impact other human beings or other you know the environment and so on how do i do that based on data how do i do that adaptively how i use computers to help those kind of things go forward whatever you want to call that so let's call it ai let's agree to call it ai but it's um let's let's not say that what the goal of that is is intelligence the goal of that is really good working systems at planetary scale we've never seen before so reclaiming the word ai from the dartmouth conference from many decades ago of the dream of humanity i don't want to reclaim it i want a new word i think it was a bad choice i mean i i you know i if you read one of my little things um the history was basically that uh mccarthy needed a new name because cybernetics already existed and he didn't like you know no one really liked norbert wiener you know ravina was kind of an island to himself and he felt that he had encompassed all this and in some sense he did you look at the language of cybernetics it was everything we're talking about it was control theory and single processing and some notions of intelligence and close feedback loops and data it was all there it's just not a word that lived on partly because of maybe the personalities but mccarthy needed a new word to say i'm different from you i'm not part of your your show i got my own invented this word um and again as a kind of a thinking forward about the movies that would be made about it uh it was a great choice but thinking forward about creating a sober academic and real world discipline it was a terrible choice because it led to promises that are not true that we understand we understand artificial perhaps but we don't understand intelligence it's a small tangent because you're one of the great personalities of machine learning whatever the heck you call the field the do you think science progresses by personalities or by the fundamental principles and theories and research that's outside of personality both and i wouldn't say there should be one kind of personality i have mine and i have my preferences and i have a kind of network around me that feeds me and and some of them agree with me and some disagree but all kinds of personalities are needed um right now i think the personality that's a little too exuberant a little bit too ready to promise the moon is a little bit too much in ascendance um and i do i do think that that's there's some good to that it certainly attracts lots of young people to our field but a lot of those people come in with strong misconceptions and they have to then unlearn those and then find something you know to do um and so i think there's just got to be some multiple voices and there's i didn't i wasn't hearing enough of the more sober voice so uh as a continuation of a fun tangent and speaking of vibrant personalities what would you say is the most interesting disagreement you have with yon lacoon so john's an old friend and i just say that i i don't think we disagree about very much really he and i both kind of have a let's build that kind of mentality and does it work kind of mentality and uh kind of concrete um we both speak french and we speak french more together and we have we have a lot a lot in common um and so you know if one wanted to highlight a a disagreement it's not really a fundamental one i think it's just kind of where we're emphasizing um jan has uh emphasized pattern recognition and uh has emphasized prediction all right so you know um and it's interesting to try to take that as far as you can if you could do perfect prediction what would that give you kind of as a thought experiment um and um i think that's way too limited um we cannot do perfect prediction we will never have the data sets allow me to figure out what you're about ready to do what question you're going to ask next i have no clue i will never know such things moreover most of us find ourselves during the day in all kinds of situations we had no anticipation of that are kind of very very novel in various ways and in that moment we want to think through what we want and also there's going to be market forces acting on us i'd like to go down that street but now it's full because there's a crane in the street i gotta i gotta think about that i gotta think about what i might really want here and i gotta sort of think about how much it cost me to do this action versus this action i got to think about the risks involved you know a lot of our current pattern recognition and prediction systems don't do any risk evaluations they have no error bars right i got to think about other people's decisions around me i got to think about a collection of my decisions even just thinking about like a medical treatment you know i'm not going to take the prediction of a neural net about my health about something consequential am i about to have a heart attack because some number is over 0.7 even if you had all the data in the world never been collected about heart attacks better than any doctor ever had i'm not going to trust the output of that neural net to predict my heart attack i'm going to want to ask what if questions around that i'm going to want to look at some us or other possible data i didn't have causal things i'm going to have a dialogue with a doctor about things we didn't think about we gathered the data you know it i could go on and on i hope you can see and i don't i think that if you say predictions everything that that you're missing all of this stuff and so prediction plus decision making is everything but both of them are equally important and so the field has emphasized prediction yan rightly so has seen how powerful that is but at the cost of people not being aware that decision making is where the rubber really hits the road where human lives are at stake where risks are being taken where you got to gather more data you got to think about the arab bars you got to think about the consequences of your decisions on others you about the economy around your decisions blah blah blah i'm not the only one working on those but we're a smaller tribe and right now we're not the the one that people talk about the most um but you know if you go out in the real world in industry um you know at amazon i'd say half the people there are working on decision making and the other half are doing you know the pattern recognition it's important and the words of pattern recognition and prediction i think the distinction there not to linger on words but the distinction there is more a constrained sort of in the lab data set versus decision making is talking about consequential decisions in the real world under the messiness and the uncertainty of the real world and just the whole of it the whole mess of it that actually touches human beings and scale like you said market forces that's the that's the distinction yeah it helps add those that perspective that broader perspective you're right i totally agree uh on the other hand if you're a real prediction person of course you want it to be in the real world you want to predict real world events i'm just saying that's not possible with just data sets uh that it has to be in the context of you know uh strategic things that someone's doing data they might gather things they could have gathered the reasoning process around data it's not just taking data and making predictions based on the data so one of the the things that you're working on i'm sure there's others working on it but i don't hear often it talked about especially in the clarity that you talk about it and i think it's both the most exciting and the most concerning area of ai in terms of decision making so you've talked about ai systems that help make decisions that scale in a distributed way millions billions decisions it's sort of markets of decisions can you as a starting point sort of give an example of a system that you think about when you're thinking about these kinds of systems uh yeah so first of all you're absolutely getting into some territory which i will be beyond my expertise and and there are lots of things that are going to be very non-obvious to think about just like just again i like to think about history a little bit but think about put yourself back in the 60s there was kind of a banking system that wasn't computerized really there was there was database theory emerging and database people had to think about how do i actually not just move data around but actual money and have it be you know valid and have transactions that atms happen that are actually you know all valid and so on so forth so that's the kind of issues you get into when you start to get serious about sort of things like this i like to think about as kind of almost a thought experiment to help me think uh something simpler which is a music market and uh because there is the first door there is no music market in the world right now or in the con in our country for sure uh there are uh something called things called record companies and they make money uh and they prop up a few um really good musicians and make them superstars and they all make huge amounts of money but there's a long tale of huge numbers of people that make lots and lots of really good music that is actually listened to by more people than the famous people um they are not in a market they cannot have a career they do not make money the creators the creators the creators the so-called influencers or whatever that diminishes who they are right so there are people who make extremely good music especially in the hip-hop or latin world these days uh they do it on their laptop that's what they do on the weekend and they have another job during the week and they put it up on soundcloud or other sites eventually it gets streamed it down gets turned into bits it's not economically valuable the information is lost it gets put up there people stream it you walk around in a big city you see people with headphones all you know especially young kids listen to music all the time if you look at the data none of them very little the music they listen to is the famous people's music and none of it's old music it's all the latest stuff but the people who made that latest stuff are like some 16 year old somewhere who will never make a career out of this who will never make money of course there will be a few counter examples the record companies incentivize to pick out a few and highlight them long story short there's a missing market there there is not a consumer producer relationship at the level of the actual creative acts um the pipelines and spotifys of the world that take this stuff and stream it along they make money off of subscriptions or advertising and those things they're making the money all right and then they will offer bits and pieces of it to a few people again to highlight that you know they're they simulate a market anyway a real market would be if you're a creator of music that you actually are somebody who's good enough that people want to listen to you you should have the data available to you there should be a dashboard showing a map of the united states so in last week here's all the places your songs were listened to it should be transparent um vettable so that if someone in down in providence sees that you're being listened to ten thousand times in providence that they know that's real data you know it's real data they will have you come give a show down there they will broadcast to the people who've been listening to you that you're coming if you do this right you could you could you know go down there make twenty thousand dollars you do that three times a year you start to have a career so in this sense ai creates jobs it's not about taking away human jobs it's creating new jobs because it creates a new market once you've created a market you've now connected up producers and consumers you know the new person who's making the music can say to someone who comes to their shows a lot hey i'll play your daughter's wedding for ten thousand dollars you'll say eight thousand they'll say nine thousand um then you again you you can now get an income up to a hundred thousand dollars you're not going to be a millionaire all right and and now even think about really the value of music is in these personal connections even so much so that um a young kid wants to wear a t-shirt with their favorite musician's signature on it right so if they listen to the music on the internet the internet should be able to provide them with a button as they push and the merchandise arrives the next day we can do that right and now why should we do that well because the kid who bought the shirt will be happy but more the person who made the music will get the money there's no advertising needed right so you could create markets between personal consumers take five percent cut your company will be perfectly uh sound it'll go forward into the future and it will create new markets and that raises human happiness um now this seems like it was easy just create this dashboard kind of create some connections and all that but you know if you think about uber or whatever you think about the challenges in the real world of doing things like this and there are actually new principles going to be needed you're trying to create a new kind of two-way market at a different scale that's ever been done before there's going to be you know unwanted aspects of the market there'll be bad people they'll be you know the data will get used in the wrong ways you know it'll fail in some ways it won't deliver value you have to think that through just like anyone who like ran a big auction or you know ran a big matching service in economics will think these things through and so that maybe doesn't get at all the huge issues that can arise when you start to create markets but it starts for at least for me solidify my thoughts and allow me to move forward in my own thinking yeah so i talked to how to research at spotify actually i think their long-term goal they've said is to uh have at least 1 million creators make a make a comfortable living putting on spotify so in and i think you articulate a really nice vision of uh the world and the digital and the cyber space of markets what what do you think companies like spotify or youtube or netflix can do to create such markets is it an ai problem is it an interface problem so interface design is it uh some other kind of it was an economics problem who should they hire to solve these problems well part of it's not just top down so the silicon valley has its attitude that they know how to do it they will create the system just like google did with the search box that will be so good that they'll just everyone will adopt that right um it's not it's it's everything you said but really i think missing the kind of culture all right so it's literally that 16 year old who's able to create the songs you don't create that as a silicon valley entity you don't hire them per se right you have to create an ecosystem in which they are wanted and that they belong right so you have to have some cultural credibility to do things like this you know netflix to their credit wanted some of that sort of credibility they created shows you know content they call it content it's such a terrible word but it's called it's culture right and so with movies you can kind of go give a large sum of money to somebody graduate from the usc film school it's a whole thing of its own but it's kind of like rich white people's thing to do you know and you know american culture has not been so much about rich white people it's been about all the immigrants all the africans who came and brought that culture and those those rhythms and and that that to to this world and created this whole new thing you know american culture and and so companies can't artificially create that they can't just say hey we're here we're going to buy it up you got a partner right and um so but anyway you know not to integrate these companies are all trying and they should and they they are i'm sure they're asking these questions and some of them are even making an effort but it is it is partly a respect the culture as you were as a technology person you got to blend your technology with cultural with cultural uh you know meaning how much of a role do you think the algorithm machine learning has in connecting the consumer to the creator sort of uh the recommender system aspect of this yeah it's a great question i think pretty high recommend you know um there's no magic in the algorithms but a good recommender system is way better than a bad recommender system and uh recommender systems was a billion dollar industry back even you know 10 20 years ago um and it continues to be extremely important going forward what's your favorite recommender system just so we can put something well just historically i was one of the you know when i first went to amazon and you know i first didn't like amazon because they put the book people out of business or the library you know the local book sellers went out of business um i've come to accept that they're you know there probably are more books being selled now and more people reading them than ever before and then local books stores are coming back so you know that's how economics sometimes work you go up and you go down but anyway when i finally started going there and i bought a few books i was really pleased to see another few books being recommended to me that i never would have thought of and i bought a bunch of them so they obviously had a good business model but i learned things and i still to this day kind of browse using that service um and i think lots of people get a lot you know they're that that is a good aspect of a recommendation system i'm learning from my peers in a in an indirect way and their algorithms are not meant to have them impose what we what we learn it really is trying to find out what's in the data uh it doesn't work so well for other kind of entities but that's just the complexity of human life like shirts you know i'm not gonna get recommendations on shirts and uh but that's that's that's interesting uh if you try to recommend um uh restaurants it's it's it's it's it's hard it's hard to do it at scale and and um but uh a blend of recommendation systems with other economic ideas matchings and so on is really really still very open research-wise and there's new companies that could emerge that do that well what what do you think is going to the messy difficult land of say politics and things like that that youtube and twitter have to deal with in terms of recommendation systems being able to suggest i think facebook just launched facebook news so they're having recommend the kind of news that are most likely for you to be interesting you think this is this ai solvable again whatever term want to use do you think it's a solvable problem for machines or is it a deeply human problem that's unsolvable uh so i don't even think about it that level i think that what's broken with some of these companies it's all monetization by advertising they're not at least facebook let's i want to critique them they didn't really try to connect a producer and a consumer in an economic way right no one wants to pay for anything and so they all you know starting with google and facebook they went back to the playbook of you know the the television companies back in the day no one wanted to pay for this signal they will pay for the tv box but not for the signal at least back in the day and so advertising kind of filled that gap but advertising was new and interesting and it somehow didn't take over our lives quite right fast forward google provides a service that people don't want to pay for um and so somewhat surprising in the 90s they made end up making huge amounts they cornered the advertising market it didn't seem like that was going to happen at least to me um these little things on the right hand side of the screen just did not seem all that economically interesting but that companies had maybe no other choice the tv market was going away and billboards and so on um so they've they got it and i think that sadly that uh google just has me it was doing so well with that and making such right they didn't think much more about how wait a minute is there a producer consumer relationship to be set up here not just uh between us and the advertisers market to be created is there an actual market between the producer and consumer they're the producers the person who created that video clip the person that made that website the person who could make more such things the person who could adjust it and as a function of demand the person on the other side who's asking for different kinds of things you know so you see glimmers of that now there's influencers and there's kind of a little glimmering of a market but it should have been done 20 years ago it should have been thought about it should have been created in parallel with the advertising ecosystem and then facebook inherited that and i think they also didn't think very much about that so fast forward and now they are making huge amounts of money off of advertising and the news thing and all these clicks is just is feeding the advertising it's all connected up to the advertiser so you want more people to click on certain things because that money flows to you facebook you're very much incentivized to do that and when you start to find it's breaking people are telling you well we're getting into some troubles you try to adjust it with your smart ai algorithms right and figure out what are bad clicks though maybe shouldn't be click-through rate it should be something i find that pretty much hopeless it does get into all the complexity in life and you can try to fix it you should but you could also fix the whole business model and the business model is that really what are are there some human producers and consumers out there is there some economic value to be liberated by connecting them directly is it such that it's so valuable that uh people are willing to pay for it all right and micro payments like smart micro but even have to be micro so i i like the example suppose i'm going next week i'm going to india never been to india before right uh i have a couple days in in mumbai um i have no idea what to do there right and i could go on the web right now and search it's going to be kind of hopeless i'm not going to find you know um i'll have lots of advertisers in my face right what i really want to do is broadcast to the world that i am going to mumbai and have someone on the other side of a market look at me and and there's a recommendation system there so i'm not looking at all possible people coming to mumbai they're looking at the people who are relevant to them so someone my age group someone who kind of knows me in some level i give up a little privacy by that but i'm happy because what i'm going to get back is this person's going to make a little video for me or they're going to write a little two-page paper on here's the cool things that you want to do and move by this week especially right i'm going to look at that i'm not going to pay a micro payment i'm going to pay you know 100 or whatever for that it's real value it's like journalism um as i'm not a subscription it's that i'm gonna pay that person in that moment company's gonna take five percent of that and that person has now got it it's a gig economy if you will but you know done for in you know thinking about a little bit behind youtube there was actually people who could make more of those things if they were connected to a market they would make more of those things independently you have to tell them what to do you don't have to incentivize them any other way um and so yeah these companies i don't think have thought long long and hard about that so i do distinguish on you know facebook on the one side who just not thought about these things at all i think uh thinking that ai will fix everything uh and amazon thinks about them all the time because they were already out in the real world they were delivering packages people's doors they were they were worried about a market they were worrying about sellers and you know they worry and some things they do are great some things maybe not so great but you know they're in that business model and then i'd say google sort of hover somewhere in between i don't i don't think for a long long time they they got it i think they probably see that youtube is more pregnant with possibility than than than they might have thought and that they're probably heading that direction um but uh you know silicon valley's been dominated by the google facebook kind of mentality and the subscription and advertising and that is that's the core problem right the fake news actually rides on top of that because it means that you're monetizing with click-through rate and that is the core problem you got to remove that so advertisement if you're going to linger on that i mean that's an interesting thesis i don't know if everyone really deeply thinks about that so you're right the thought is the advertising model is the only thing we have the only thing we'll ever have so we have to fix we have to build algorithms that despite that business model you know find the better angels of our nature and do good by society and by the individual but you think we can slowly you think first of all there's a difference between should and could so you're saying we should slowly move away from the advertising model and have a direct connection between the consumer and the creator the the question i also have is can we because the advertising model is so successful now in terms of just making a huge amount of money and therefore being able to build a big company that provides has really smart people working that create a good service do you think it's possible and just to clarify you think we should move away well i think we should yeah but uh we is you know me so society yeah will the companies um i mean so first of all full disclosure i'm doing a day a week at amazon because i kind of want to learn more about how they do things so you know i'm not speaking for amazon in any way but um you know i did go there because i actually believe they get a little bit of this are trying to create these markets and they don't really use advertising is not a crucial part of it that's a good question so it has become not crucial but it's become more and more present if you go to amazon website and you know without revealing too many deep secrets about amazon i can tell you that you know a lot of people company question this and there's a huge questioning going on you do not want a world where there's zero advertising that actually is a bad world okay so here's a way to think about it you're a company that like amazon is trying to bring products to customers all right and the customer at any given you want to buy a vacuum cleaner say you want to know what's available for me and you know it's not gonna be that obvious you have to do a little bit of work at it the recommendation system will sort of help all right but now suppose this other person over here has just made the world you know they spent a huge amount of energy they had a great idea they made a great vacuum cleaner they know they they really did it they nailed it it's an mit you know whiz kid that made a great new vacuum cleaner all right it's not going to be in the recommendation system no one will know about it the algorithms will not find it and ai will not fix that okay at all right how do you allow that vacuum cleaner to start to get in front of people be sold well advertising and here what advertising is it's a signal that you're you believe in your product enough that you're willing to pay some real money for it and to me as a consumer i look at that signal i say well first of all i know these are not just cheap little ads because we have now right now i know that you know these are super cheap you know pennies uh if i see an ad where it's actually i know the company is only doing a few of these and they're making you know real money is kind of flowing and i see an ad i may pay more attention to it and i actually might want that because i see hey that guy spent money on his vacuum cleaner or maybe there's something good there so i will look at it and and so that's part of the overall information flow in a good market uh so advertising has a role um but the problem is of course that that signal is now completely gone because it just you know dominar by these tiny little things that add up to big money for the company you know so i i think it will just i think it will change because the societies just don't you know stick with things that annoy a lot of people and advertising currently annoys people more than it provides information and i think that at google probably is smart enough to figure out that this is a dead this is a bad model even though it's a hard huge amount of money and they'll have to figure out how to pull it away from it and slowly and i'm sure the ceo there will figure it out but um they need to do it and uh they need to so if you reduce advertising not to zero but you reduce it at the same time you bring up producer consumer actual real value being delivered so real money is being paid and they take a five percent cut that five percent could start to get big enough to cancel out the lost revenue from the the kind of the poor kind of advertising and i think that a good company will will do that we'll realize that um and they're com you know facebook you know again god bless them they they bring you know grandmother's uh you know uh they bring children's pictures into grandmother's lives it's fantastic um but they need to think of a new business model and and they that's that's the core problem there um until they start to connect producer consumer i think they will just just continue to make money and then buy the next social network company and then buy the next one and the innovation level will not be high and the health the health issues will not go away so i apologize that we kind of return to words i don't think the exact terms matter but in sort of defensive advertisement don't you think the kind of direct connection between consumer and creator producer is the best like the is what advertisement strives to do right so that is the best advertisement is literally now facebook is listening to our conversation and heard that you're going to india and we'll be able to actually start automatically for you making these connections and start giving this offer so like i apologize if it's just a matter of terms but just to draw a distinction is it possible to make advertisements just better and better and better algorithmically to where it actually becomes a connection almost address that's a good question so let's component all that push first of all i i what we just talked about i was defending advertising okay so i was defending it as a way to get signals into a market that don't come any other way especially algorithmically it's a sign that someone spent money on it it's a sign they think it's valuable and if i think that if other things someone else thinks it's valuable and if i trust other people i might be willing to listen i don't trust that facebook though is who's an intermediary between this i don't think they care about me okay i don't think they do and i find it creepy that they know i'm going to india next week because of our conversation why do you think that can we so what can you just put your pr hat on why do you think you find facebook uh creepy and not trust them as as do majority of the population so they're out of the silicon valley companies i saw like not approval rate but there's there's ranking of how much people trust companies and facebook is in in the gutter in the gutter including people inside of facebook so what uh what do you attribute that to because when i come on you don't find it creepy that right now we're talking i might walk out on the street right now that some unknown person who i don't know kind of comes up to me and says i hear you going to india i mean that's not even facebook that's just a if i want transparency in human society i want to have if you know something about me there's actually some reason you know something about me that's something that if i look at it later and audit it kind of i approve you know something about me because you care in some way there's a caring relationship even or an economic one or something not just that you're someone who could exploit it in ways i don't know about or care about or or i'm troubled by or or whatever and we're in a world right now where that happens way too much and that facebook knows things about a lot of people and could exploit it and does exploit it at times i think most people do find that creepy it's not for them it's not it's not that it's facebook that's not doing it because they care about them right in any real sense and they shouldn't they should not be a big brother caring about us that is not the role of a company like that why not wait not the big brother part but the sharing the trust thing i mean don't those companies just to linger because a lot of companies have a lot of information about us i would argue that there's companies like microsoft that has more information about us than facebook does and yet we trust microsoft more well microsoft is pivoting microsoft you know under satya nadella has decided this is really important we don't want to do creepy things we really want people to trust us to actually only use information in ways that they really would approve of that we don't decide right and um i'm just kind of adding that the health the health of a market is that uh when i connect to someone who produces a consumer it's not just a random producer consumer it's people who see each other they don't like each other but they sense that if they transact some happiness will go up on both sides if a company helps me to do that and moments that i choose of my choosing then fine so and also think about the difference between you know browsing versus buying right there are moments in my life i just want to buy you know a gadget or something i need something for that moment i need some ammonia for my house or something because i got a problem a spill i want to just go in i don't want to be advertised at that moment i don't want to be led down very dire you know that's annoying i want to just go and have it extremely easy to do what i want um other moments i might say no it's like today i'm going to the shopping mall i want to walk around and see things and see people and be exposed to stuff so i want control over that though i don't want the company's algorithms to decide for me right and i think that's the thing we it's a total loss of control if facebook thinks they should take the control from us of deciding when we want to have certain kinds of information when we don't what information that is how much it relates to what they know about us that we didn't really want them to know about us they're not i don't want them to be helping me in that way i don't want them to be helping them but they decide well they have control over um um what i want and when i totally agree so facebook by the way i have this optimistic thing where i think facebook has the kind of personal information about us that could create a beautiful thing so i i'm really optimistic of what facebook could do uh it's not what it's doing but what it could do so i don't see that i think that optimism is misplaced because there's not a bit you have to have a business model behind these things yes create a beautiful thing is really let's be let's be clear it's about something that people would value and and i don't think they have that business model and i don't think they they will suddenly discover it by what you know have a long hot shower i disagree i disagree in terms of uh you can discover a lot of amazing things in the shower so if i didn't say that i said they won't come they won't they won't do it but in the shower i think a lot of other people will discover it i think that this guy so i should also uh full disclosure there's a company called united masters which i'm on their board and they've created this music market yes they have a hundred thousand artists now signed on and they've done things like gone to the nba and the nba the music you find behind me the eclipse right now is their music right that's a company that had the right business model in mind from the get-go right executed on that and and from day one there was value brought to so here you have a kid who made some songs who suddenly their songs are on the nba website right that that's real economic value to people and uh so you know so you and i differ on the optimism of being able to sort of uh um change the direction of the titanic right so i yeah i'm older than you so i think titanic's crash got it but uh so and just to elaborate because i totally agree with you and i just want to know how difficult you think this problem is of so for example i um i want to read some news and i would there's a lot of times in the day where something makes me either smile or think in a way where i like consciously think this really gave me value like i sometimes listen to uh the daily podcast in the new york times way better than the new york times themselves by the way for people listening that's like real journalism is happening for some reason in the podcast space it doesn't make sense to me but often i'll listen to it 20 minutes and i i would be willing to pay for that like five dollars ten dollars for that experience absolutely and how difficult that's kind of what you're getting at is that little transaction how difficult is it to create a frictionless system like uber has for example for other things what's your intuition there uh so i first of all i pay little bits of money to you know to say there's something called courts that does financial things i like medium as a site i don't pay there but um i would you had a great post on medium i would have loved to pay you a dollar and but i wouldn't want it i wouldn't have wanted it per se because um there should be also sites where that's not actually the goal the goal is to actually have a broadcast channel that i monetize in some other way if i chose to i mean i could now people know about it i could i'm not doing it but um that's fine with me there also the musicians who are making all this music i don't think the right model is that you pay a little subscription fee to them all right because because people can copy the bits too easily and it's just not that somewhere the value is the value is that a connection was made between real human beings then you can follow up on that right and create yet more value so no i think um there's a lot of open questions here hot open questions but also yeah i do want good recommendation systems that recommend cool stuff to me and but it's pretty hard right i don't like them to recommend stuff just based on my browsing history i don't like that based on stuff they know about me quote quote what's unknown about me is the most interesting so this is the this is the really interesting question we may disagree maybe not i think that i love recommender systems and i want to give them everything about me in a way that i trust yeah but you but you don't because so for example this morning i clicked on i you know i was pretty sleepy this morning um i clicked on a story about the queen of england yes right i do not give a damn about the queen of england i really do not but it was clickbait it kind of looked funny and i had to say what the heck are they talking about i don't want to have my life you know heading that direction now that's in my browsing history the system in any reasonable system we'll think about history right but but you're saying all the trace all the digital exhaust or whatever that's been kind of the models if you collect all this stuff you're gonna figure all of us out well if you're trying to figure out like kind of one person like trump or something maybe you could figure him out but if you're trying to figure out you know 500 million people you know no way no way do you think so no i do i think so i think we are humans are just amazingly rich and complicated every one of us has our little quirks everyone else has our little things that could intrigue us that we don't even know and will intrigue us and there's no sign of it in our past but by god there it comes and you know you fall in love with it and i don't want a company trying to figure that out for me and anticipate that okay well i want them to provide a forum a market a place that i kind of go and by hook or by crook this happens you know i i'm walking down the street and i hear some chilean music being played and i never knew i like chili music but wow so there is that side and i want them to provide a limited but you know interesting place to go right and so don't try to use your ai to kind of you know figure me out and then put me in a world where you figured me out you know no create huge spaces for human beings where our creativity and our style will be enriched and come forward and it'll be a lot more transparency i won't have people randomly anonymously putting comments up and especially based on stuff they know about me facts that you know we are so broken right now if you're you know especially if you're a celebrity but you know it's about anybody that uh anonymous people are hurting lots and lots of people right now and that's part of this thing that silicon valley is thinking that you know just collect all this information and use it in a great way so no i i'm i'm not i'm not a pessimism i'm very much an optimist by nature but i think that's just been the wrong path for the whole technology to take be more limited create let humans rise up don't don't try to replace them that's the ai mantra don't try to anticipate them don't try to predict them because you're you're not good at you're not going to do those things you're going to make things worse okay so right now just give this a chance uh right now the recommender systems are the creepy people in the shadow watching your every move so they're looking at traces of you they're not directly interacting with you sort of the your close friends and family the way they know you is by having conversation by actually having interactions back and forth do you think there's a place for recommender systems sort of to step because you you just emphasize the value of human to human connection but yeah just give it a chance ai human connection is there a role for an ass system to have conversations with you in terms of to try to figure out what kind of music you like not by just watching what you're listening but actually having a conversation natural language or otherwise yeah no i'm i'm so i'm not against it i just want to push back against them maybe you're saying you have options for facebook so there i think it's misplaced but but um i think that this one pending facebook yeah now so good for you um go for it that's a hard spot to be yeah no good human interaction like on our daily the context around me in my own home is something that i don't want some big company to know about at all but i would be more than happy to have technology help me with it which kind of technology well you know just alexa amazon well a good alexa's done right i think alex is a research platform right now more than anything else but alexa done right you know could do things like i i leave the water running in my garden and i say hey alex so the waters are in my garden um and even have alexa figure out that that means when my wife comes home that she should be told about that that's a little bit of a reasoning i call that ai and by any kind of stretch it's a little bit of reasoning and it actually kind of makes my life a little easier and better and you know i don't i wouldn't call this a wow moment but i kind of think that overall rises human happiness up to have that kind of thing um but not when you're lonely alexa knowing loneliness no no there i don't want to let you that be feel intrusive and i and i don't want just the designer of the system to kind of work all this out i really want to have a lot of control and i want transparency and control and if the company can stand up and give me that in the context of new technology i think they're good first of all be way more successful than our current generation and like i said i was mentioning microsoft earlier i really think they're pivoting to kind of be the trusted old uncle but you know i think that they get that this is the way to go that if you let people find technology empowers them to have more control and have and have control not just over privacy but over this rich set of interactions um that that people gonna like that a lot more and that's that's the right business model going forward what does control over privacy look like do you think you should be able to just view all the data that no it's much more than that i mean first of all it should be an individual decision some people don't want privacy they want their whole life out there other people's want it um privacy is not a zero one it's not a legal thing it's not just about which data is available which is not um i like to recall to people that you know a couple hundred years ago everyone there was not really big cities everyone lived down the countryside and villages um and in villages everybody knew everything about you very you didn't have any privacy is that bad are we better off now well you know arguably no because what did you get for that loss of at least certain kinds of privacy um well uh people helped each other if they because they know everything about you they know something's bad's happening they will help you with that right and now you live in a big city no one knows their mouth you get no help um so uh it kind of depends the answer i want certain people who i trust and there should be relationships i should kind of manage all those but who knows what about me i should have some agency there it shouldn't i shouldn't be a drift in a sea of technology where i have no idea i don't want to go reading things and checking boxes so i don't know how to do this and i'm not a privacy researcher per se i just i recognize the vast complexity of this it's not just technology it's not just legal scholars meeting technologists there's got to be kind of whole layers around it and so i when i allude to this emerging engineering field this is a big part of it um like when electrical engineering come came i'm not wasn't around in the time but you just didn't plug electricity you know into walls and it all kind of worked you don't have to have like underwriter's laboratory that reassured you that that plug's not going to burn up your house and that that machine will do this and that and everything there'll be whole people who can install things there'll be people who can watch the installers there'll be a whole layers you know an onion of these kind of things and for things as deeply interesting as privacy which is his least essential electricity um that that's gonna take decades to kind of work out but it's gonna require a lot of new structures that we don't have right now so it's kind of hard to talk about it and you're saying there's a lot of money to be made if you get it right so absolutely a lot of money to be made and all these things that provide human services and people recognize them as useful parts of their lives uh so yeah um so yeah the dialect sometimes goes from the exuberant technologists to the no technology is good kind of and that's you know in our public discourse you know in newspapers you see too much of this kind of thing and and the sober discussions in the middle which are the challenging ones to have are where we need to be having our conversations and you know there's not actually there's not many forum forum for those um you know there's that's that's kind of what i would look for maybe i could go and i could read a comment section of something and it would actually be this kind of dialogue going back and forth you don't see much of this right which is why actually there's a resurgence of podcasts out of all because good people are really hungry for conversation but their technology is not helping much so comment sections of anything including youtube yeah is not hurting i'm not hurting yeah and you think technically speaking it's possible to help i don't know the answers but it's it's a it's a less anonymity a little more locality um you know worlds that you kind of enter in and you trust the people there in those worlds so that when you start having a discussion you know not only is that people not gonna hurt you but it's not gonna be a total waste your time because there's a lot of wasting of time that you know a lot of us i i pulled out of facebook early on because it was clearly going to waste a lot of my time even though there was some value um and so yeah worlds that are somehow you enter in you know what you're getting and it's kind of appeals to you might new things might happen but you kind of have some some trust in that world and there's some deep interesting complex psychological aspects around anonymity uh how that changes human behavior indeed quite dark and quite dark yeah i think a lot of us are especially those of us who really love the advent of technology i loved social networks when it came out i was just i didn't see any negatives there at all but then i started uh seeing comment sections i think it was maybe you know cnn or something and i started going wow this this darkness i just did not know about and um and our technology is now amplifying it so sorry for the big philosophical question but on that topic do you think human beings because you've also out of all things had a foot in psychology too the do you think human beings are fundamentally good like all of us have good intent that could be mined or is it depending on context and environment everybody could be evil thought my answer is fundamentally good um but fundamentally limited all of us have very you know blinkers on we don't see the other person's pain that easily we don't see the other person's point of view that easily we're very much in our own head in our own world and on my good days i think that technology could open us up to you know more perspectives and more less blinkered and more understanding you know a lot of wars in human history happen because of just ignorance they didn't they they thought the other person was doing this well other person wasn't doing this and we have huge amounts of that um but in my lifetime i've not seen technology really help in that way yet and i do i do i do believe in that but you know no i think fundamentally humans are good the people suffer people have grievances because you have grudges and those things cause them to do things they probably wouldn't want they regret it often um so no i i i think it's a you know part of the progress of technology is to indeed allow it to be a little easier to be the real good person you actually are well but do you think individual human life or society could be modeled as an optimization problem um not the way i think typically i mean that's your time one of the most complex phenomena in the whole you know in all ways individual human life for society as a whole both both i mean individual human life is amazingly complex and um so uh you know optimization is kind of just one branch of mathematics that talks about certain kind of things and uh it just feels way too limited for the complexity of such things what properties of optimization problems do you think so do you think most interesting problems that could be solved through optimization uh what kind of properties does that surface have non-convexity convexity linearity all those kinds of things saddle points well so optimization's just one piece of mathematics you know there's like you just even in our era we're aware that say sampling um is coming up with examples of something um coming up with a description what's sampling well you they you can if you're a kind of a certain kind of mathematician you can try to blend them and make them seem to be sort of the same thing but optimization is roughly speaking trying to uh find a point that um a single point that is the optimum of a criterion function of some kind um and sampling is trying to from that same surface treat that as a distribution or density and find prop points that have high density so um i i want the entire distribution and the sampling paradigm and i want the um you know the the single point that's the best point in the par in the sample in the uh optimization paradigm now if you were optimizing in the space of probability measures the output of that could be a whole probability distribution so you can start to make these things the same but in mathematics if you go too high up that kind of abstraction arc you start to lose the uh you know the ability to do the interesting theorems so you kind of don't try to you don't try to overly over abstract so as a small tangent what kind of world view do you find more appealing one that is deterministic or stochastic well that's easy i mean i'm a statistician you know the world is highly stochastic wait i don't know what's going to happen in the next five minutes right because you're going to ask what we're going to do massive uncertainty yeah you know massive uncertainty and so the best i can do is have come rough sense or probability distribution on things and somehow use that in my reasoning about what to do now so how does the distributed at scale when you have multi-agent systems look like so optimization can optimize sort of it makes a lot more sense sort of uh at least from from a robotics perspective for a single robot for a single agent trying to optimize some objective function when you start to enter the real world this game theoretic concept starts popping up and that how do you see optimization in this because you've talked about markets in a scale what does that look like do you see this optimization do you see it as sampling do you see like how how should you modify these all blend together um and a system designer thinking about how to build an incentivized system will have a blend of all these things so you know a particle in a potential well is optimizing a function called lagrangian right the particle doesn't know that there's no algorithm running that does that it just happens it's so it's a description mathematically of something that helps us understand as analysts what's happening right and so the same will happen when we talk about you know mixtures of humans and computers and markets and so on so forth there'll be certain principles that allow us to understand what's happening and whether or not the actual algorithms are being used by any sense it's not clear now at some point i may have set up a multi-agent or market kind of system and i'm now thinking about an individual agent in that system and they're asked to do some tasks and they're incentivized in some way they get certain signals and they they have some utility maybe what they will do at that point is they just won't know the answer they may have to optimize to find an answer okay so an autism could be embedded inside of an overall market you know and game theory is is very very broad it is often studied very narrowly for certain kinds of problems but it's roughly speaking this is just the i don't know what you're going to do so i kind of anticipate that a little bit and you anticipate what i'm anticipating and we kind of go back and forth in our own minds we run kind of thought experiments you talked about this interesting point in terms of game theory you know most optimization problems really hate saddle points maybe you can describe what saddle points are but i've heard you kind of mentioned that there's a there's a branch of optimization you could try to explicitly look for saddle points that's a good thing oh not optimization that's just game theory that that's so uh there's all kinds of different equilibria in game theory and some of them are highly explanatory behavior they're not attempting to be algorithmic they're just trying to say if you happen to be at this equilibrium you would see certain kind of behavior and we see that in real life that's what an economist wants to do especially behavioral economist um uh in in continuous uh differential game theory you're in continuous spaces a um some of the simplest equilibria are saddle points a nash equilibrium is a saddle point it's a special kind of salon point so classically in game theory you were trying to find nash equilibria and algorithmic games here you're trying to find algorithms that would find them and so you're trying to find saddle points i mean so that's literally what you're trying to do um but you know any economist knows that nash equilibria have their limitations they are definitely not that explanatory in many situations they're not what you really want um there's other kind of equilibria and there's names associated with these because they came from history with certain people working on them but there will be new ones emerging so you know one example is a stackelberg equilibrium so you know nash you and i are both playing this game against each other or for each other maybe it's cooperative and we're both going to think it through and then we're going to decide and we're going to off you know do our thing simultaneously you know in a stackelberg no i'm going to be the first mover i'm going to make a move you're going to look at my move and then you're going to make yours now since i know you're going to look at my move i anticipate what you're going to do and so i don't do something stupid but and but then i know that you were also anticipating me so we're kind of going back and so far am i but there is then a first mover thing and so there's a those are different equilibria all right and uh so just mathematically yeah these things have certain topologies certain shapes they're like southwest and algorithmically or dynamically how do you move towards them how do you move away from things um you know so some of these questions have answers they've been studied others do not and especially if it becomes stochastic especially if there's large numbers of decentralized things there's just uh you know young people getting in this field who kind of think it's all done because we have you know tensorflow well no these are all open problems and they're really important and interesting and it's about strategic settings how do i collect data suppose i don't know what you're going to do because i don't know you very well right well i got to kind of date about you so maybe i want to push you in a part of the space where i don't know much about you so i can get data because and then later i'll realize that you'll never you'll never go there because of the way the game is set up but you know that's part of the overall you know data analysis context is that yeah even the game of poker is fascinating space whenever there's any uncertainty your lack of information is it's a super exciting space yeah uh just uh lingard optimization for a second so if we look at deep learning it's essentially minimization of a complicated loss function so is there something insightful or hopeful that you see in the kinds of function surface that loss functions that deep learning in in the real world is trying to optimize over is there something interesting this is just the usual kind of problems of optimization i think from an optimization point of view that surface first of all it's pretty smooth um and secondly if there's over if it's over parameterized there's kind of lots of paths down to reasonable optima and so kind of the getting downhill to the to an optimum is viewed as not as hard as you might have expected in high dimensions the fact that some optima tend to be really good ones and others not so good and you tend to it's not sometimes you find the good ones is sort of still needs explanation yes but but the particular surface is coming from the particular generation of neural nets i kind of suspect those will this those will change in 10 years it will not be exactly those surfaces there'll be some others that are and optimization theory will help contribute to why other surfaces are why other algorithms layers of arithmetic operations with a little bit of nonlinearity that's not that didn't come from neuroscience per se i mean maybe in the minds of some of the people working on it they were thinking about brains but uh they were arithmetic circuits in all kinds of fields you know uh computer science control theory and so on and that layers of these could transform things in certain ways and that if it's smooth maybe you could uh you know find parameter values um you know it's a big is a is a sort of big discovery that it's it's working it's able to work at this scale but um um i don't think that we're stuck with that and we're certainly not stuck with that because we're understanding the brain so in terms of uh on the algorithm size of gradient descent do you think we're stuck with gradient descent this is uh variants of it what variants do you find interesting or do you think there'll be something else invented that uh is able to walk all over these optimization spaces in more interesting ways so there's a co-design of the surface and or the architecture and the algorithm so if you just ask if we stay with the kind of architectures we have now and not just neural nets but you know phase retrieval architectures or materials completion architectures and so on um you know i think we've kind of come to a place where yeah a stochastic gradient algorithms are dominant and um there are versions uh they're you know that are a little better than others they you know have more guarantees they're more robust and and so on and there's ongoing research to kind of figure out which is the best downforce situation um but i think that that'll start to co-evolve that that'll put pressure on the actual architecture and so we shouldn't do it in this particular way we should do it in a different way because this other algorithm is now available if you do it in a different way um so uh that that i can't really anticipate that co-evolution process but you know gradients are amazing uh mathematical objects um they uh have a lot of people who uh start to study them more deeply mathematically are kind of shocked about what what they are and what they can do um i mean to think about this way if uh suppose that i tell you if you move along the x-axis you get uh uh uh you know you go uphill in some objective by you know three units whereas if you move on the y-axis you go uphill by seven units right now i'm gonna only allow you to move a certain you know unit distance all right what are you gonna do well the most not people will say i'm gonna go along the y-axis i'm getting the biggest bang for my buck you know and my buck is only one unit so i'm gonna put all of it in the y-axis right and uh why should i even take any of my strength my step size and put any of it in the x-axis because i'm getting less bang for my buck that seems like a completely you know clear cl argument and it's wrong because the gradient direction is not to go along the y-axis it's to take a little bit of the x-axis uh and that to understand that you have to you have to know some math and um so even a you know trivial so so-called operator like grading is not trivial and so you know exploiting its properties is still very very important um now we know that just providing descent has got all kinds of problems it gets stuck in many ways and it hadn't have you know good dimension dependence and so on so um my own line of work recently has been about what kinds of stochasticity how can we get dimension dependence how can we do the theory of that um and we've come up pretty favorable results with certain kinds of stochasticity we have sufficient conditions generally we know if you if you do this we will give you a good guarantee we don't have necessary conditions that it must be done a certain way in general so stochasticity how much randomness to inject into the into the walking along the gradient and what kind of randomness why is randomness good in this process why is stochasticity good yeah so um i give you simple answers but in some sense again it's kind of amazing stochasticity just uh um you know particular features of a surface that could have hurt you if you were doing one thing um deterministically it won't hurt you because uh you know by chance there's very little chance that you would get hurt and um you know so here stochasticity um you know is just kind of saves you from some of the particular features of surfaces that um you know and in fact if you think about you know surfaces that are discontinuous in a first derivative like you know absolute value function um you will go down and hit that point where there's non-differentiability right and if you're running a deterministic argument at that point you can really do something bad right whereas stochasticity just means it's pretty unlikely that's going to happen you're going to you're going to hit that point so you know it's again not trivially analyzed but um especially in higher dimensions also stochasticity our intuition isn't very good about it but it has properties that kind of are very appealing in high dimensions for a lot of large number of reasons um so it's it's all part of the mathematics to kind of that's what's fun to work in the field is that you get to try to understand this mathematics and um but long story short you know partly empirically it was discovered stochastic gradient is very effective and theory kind of followed i'd say um that but i don't see that we're getting clearly out of that uh what's the most beautiful mysterious a profound idea to you in optimization i don't know the most but let me just say that uh you know nestorov's work on nest drive acceleration to me is uh pretty pretty surprising and pretty deep um can you elaborate well install acceleration is just that um i suppose that we are going to use gradients to move around into space for the reasons i've alluded to there there are nice directions to move and suppose that i tell you that you're only allowed to use gradients you're not going to be allowed to you'll see this local person it can only sense kind of a change in the surface um but i'm going to give you kind of a computer that's able to store all your previous gradients and so you start to learn some something about the the surface um and i'm going to restrict you to maybe move in the direction of like a linear span of all the gradients so you can't kind of just move in some arbitrary direction right so now we have a well-defined mathematical complexity model there's a certain classes of algorithms that can do that and others that can't and we can ask for certain kinds of surfaces how fast can you get down to the optimum so there's an answers to these so for a you know a smooth convex function there's an answer which is one over the number of steps squared you will be within a ball of that size after after k steps um gradient descent in particular has a slower rate it's one over k okay um so you could ask is gradient is said actually even though we know it's a good algorithm is it the best algorithm in the sense of the answer is no well well not clear yet because what one of our case score is a lower bound that's that's probably the best you can do what gradient is one over k but is there something better and so i think as a surprise to most though nest drove discovered a new algorithm that is got two pieces to it it uses two gradients um and uh puts those together in a certain kind of obscure way and uh the thing doesn't even move downhill all the time it sometimes goes back uphill and if you're a physicist that kind of makes some sense you're building up some momentum and that is kind of the right intuition but that that intuition is not enough to understand kind of how to do it and why it works um but it does it achieves one over k squared and uh it has a mathematical structure and it's still kind of to this day a lot of us are writing papers and trying to explore that and understand it um so there are lots of cool ideas in optimization but just kind of using gradients i think is number one that goes back you know 150 years um and then nest drive i think has made a major contribution with this idea so like you said gradients themselves are in some sense mysterious yeah they're not uh they're not as trivial as they're not as trivial coordinate descent is more of a trivial one you just pick one of the coordinates that's how we think that's our human mind that's our human minds think and gradients are not that easy for our human mind to grapple with an absurd question but uh what is statistics so the here it's a little bit it's somewhere between math and science and technology it's somewhere in that convex hole so it's a set of principles that allow you to make inferences that have got some reason to be believed and also principles allow you make decisions where you can have some reason to believe you're not going to make errors so all of that requires some assumptions about what do you mean by an error what do you mean by you know the probabilities and um but you know you start after you start making some of those assumptions you're led to uh conclusions that yes i can guarantee that you know you know if you do this in this way your probability of making error will be small your probability of continuing to not make errors over time will be small and probability you found something that's real will be small uh will be high so decision making is a big part of the big part yeah so uh the original so statistics uh you know short history was that you know it's kind of goes back as a formal discipline you know 250 years or so it was called inverse probability because around that era probability was developed sort of especially to explain gambling situations of course and um interesting so you would say well given the state of nature is this there's a certain roulette board that has a certain mechanism in it uh what kind of outcomes do i expect to see uh and um especially if i do things long long amounts of time what outcomes i see and the physicists start to pay attention to this um and then people say well given let's turn the problem around what if i saw certain outcomes could i infer what the underlying mechanism was that's an inverse problem and in fact for quite a while statistics was called inverse probability that was the name of the field and i believe that uh it was laplace uh who was working in napoleon's government who was trying to who needed to do a census of france learn about the people there so he went and gathered data and he analyzed that data to determine policy and uh said let's call this field that does this kind of thing statistics because um the the word state is in there in french that's eta but you know it's the study of data for the state so anyway that caught on and um it's been called statistics ever since but um uh but by the time it got formalized it was sort of in the 30s um and uh around that time there was game theory and decision theory developed nearby people in that era didn't think of themselves as either computer science or statistics or controlled or econ they were all they were all the above and so you know von neumann is developing game theory but also thinking of that as decision theory wall is an econometrician developing decision theory and then you know turning that into statistics and so it's all about here's a here's not just data and you analyze it here's a loss function here's what you care about here's the question you're trying to ask here is a probability model and here's the risk you will face if you make certain decisions um and to this day in most advanced statistical curricula you teach decision theory is the starting point and then it branches out into the two branches of bazin or frequentist but um that's it's all about decisions in statistics what is the most beautiful mysterious maybe surprising idea that you've come across uh yeah good question um i mean there's a bunch of surprising ones there's something that's way too technical for this thing but something called james stein estimation which is kind of surprising and really takes time to wrap your head around can you try to maybe i think i don't even want to try um let me just say a colleague at steve steven stickler at university of chicago wrote a really beautiful paper on james stein estimation which helps to its views of paradox it kind of defeats the mind's attempts to understand it but you can and steve has a nice perspective on that um there uh so one of the troubles with statistics is that it's like in physics that are in quantum physics you have multiple interpretations there's a wave and particle duality in physics and you get used to that over time but it still kind of haunts you that you don't really you know quite understand the relationship the electrons away when electrons a particle well um well the same thing happens here there's bayesian ways of thinking and frequentist and they are different they they all they sometimes become sort of the same in practice but they are physically different and then in some practice they are not the same at all they give you rather different answers um and so it is very much like wave and particle duality and that is something you have to kind of get used to in the field can you define beijing and frequencies yeah in decision theory you can make i have a like i have a video that people could see it's called are you a bayesian or a frequentist and kind of help try to to make it really clear it comes from decision theory so you know decision theory uh you're talking about loss functions which are a function of data x and parameter theta it's a function of two arguments okay neither one of those arguments is known you don't know the data a priori it's random and the parameter is unknown all right so you have this function of two things you don't know and you're trying to say i want that function to be small i want small loss right well um what are you gonna do so you sort of say well i'm gonna average over these quantities or maximize over them or something so that you know i turn that uncertainty into something certain so you could look at the first argument an average over it or you could look at the second argument average over it that's bayesian frequencies so the frequencies says i'm going to look at the x the data and i'm going to take that as random and i'm going to average over the distribution so i take the expectation loss under x theta is held fixed all right that's called the risk and so it's looking at other all the data sets you could get all right and say how well will a certain procedure do under all those data sets that's called a frequency guarantee all right so i think it is very appropriate when like you're building a piece of software and you're shipping it out there and people are using all kinds of data sets you want to have a stamp a guarantee on it that as people run it on many many data sets that you never even thought about that 95 of the time it will do the right thing um perfectly reasonable the bayesian perspective says well no i'm going to look at the other argument of the loss function the theta part okay that's unknown and i'm uncertain about it so i could have my own personal probability for what it is you know how many tall people are there out there i'm trying to infer the average height of the population well i have an idea roughly what the height is so i'm going to average over the um the theta so now that loss function has only now again one argument's gone now it's a function of x and that's what a bayesian does is they say well let's just focus on the particular x we got the data set we got we condition on that conditional on the x i say something about my loss that's a bayesian approach to things and the bayesian will argue that it's not relevant to look at all the other data sets you could have gotten and average over them the frequentest approach it's really only the data set you got all right and i do agree with that especially in situations where you're working with a scientist you can learn a lot about the domain and you really only focus on certain kinds of data and you've gathered your data and you make inferences i don't agree with it though that it you know in the sense that there are needs for frequency guarantees you're writing software people are using it out there you want to say something so these two things have to go out to fight each other a little bit but they have to blend so long story short there's a set of ideas that are right in the middle they're called empirical bays and empirical base sort of starts with the bayesian framework it's it's kind of arguably philosophically more you know reasonable and kosher write down a bunch of the math that kind of flows from that and then realize there's a bunch of things you don't know because it's the real world then you don't know everything so you're uncertain about certain quantities at that point ask is there a reasonable way to plug in an estimate for those things okay and in some cases there's quite a reasonable thing to do to plug in there's a natural thing you can observe in the world that you can plug in and then do a little bit more mathematics and assure yourself it's really good so my math are based on human expertise what's what are good they're both going in the bayesian framework allows you to put a lot of human expertise in but the math kind of guides you along that path and then kind of reassures you at the end you could put that stamp of approval under certain assumptions this thing will work so perhaps you asked question what's my favorite you know or what's the most surprising nice idea so one that is more accessible is something called false discovery rate which is um you know you're making not just one hypothesis test or making one decision you're making a whole bag of them and in that bag of decisions you look at the ones where you made a discovery you announced that something interesting it happened all right that's gonna be some subset of your big bag in the ones you made a discovery which subset of those are bad there are false false discoveries you like the fraction of your false discoveries among your discoveries to be small that's a different criterion than accuracy or precision or recall or sensitivity and specificity it's it's a different quantity those latter ones are almost all of them um have more of a frequencies flavor they say given the truth is that the null hypothesis is true here's what accuracy i would get or given that the alternative is true here's what i would get so it's kind of going forward from the state of nature to the data the bayesian goes the other direction from the data back to the state of nature and that's actually what false discovery rate is it says given you made a discovery okay that's condition on your data what's the probability of the hypothesis it's going the other direction and so um the classical frequency look at that so i can't know that there's some priors needed in that and the empirical bayesian goes ahead and plows forward and starts writing down these formulas and realizes at some point some of those things can actually be estimated in a reasonable way oh and so it's kind of it's a beautiful set of ideas so i i this kind of line of argument has come out it's not certainly mine but it it sort of came out from robin's around 1960. uh brad ephron has written beautifully about this in various papers and books and uh and the fdr is you know ben yamini in israel um john storey did this bayesian interpretation and so on so i've just absorbed these things over the years and find it a very healthy way to think about statistics let me ask you about intelligence to jump slightly back out into philosophy perhaps you said that uh maybe you can elaborate but uh you said that defining just even the question of what is intelligence is a word is as a very difficult question is that a useful question do you think we'll one day understand the fundamentals of human intelligence and what it means you know have good uh benchmarks for general intelligence that we put before our machines so i don't work on these topics so much you're really asking a question for a psychologist really and i just studied some but i don't consider myself at least an expert at this point you know a psychologist aims to understand human intelligence right and i think many psychologists i know are fairly humble about this they they might try and understand how a baby understands you know whether something's a solid or liquid or uh whether something's hidden or not and um maybe how you know a child starts to learn the meaning of certain words what's a verb what's a noun and also you know slowly but surely trying to figure out things um but human's ability to take a really complicated environment reason about it abstract about it find the right abstractions communicate about it interact and so on is just you know really staggeringly rich and complicated um and so you know i think in all humidity we don't think we're kind of aiming for that in the near future certainly psychologists doing experiments with babies in the lab or with people talking is is has a much more limited aspiration and you know conor mcversky would look at our reasoning patterns and they're they're not deeply understanding all the how we do our reasoning but they're sort of saying here's some here's some oddities about the reasoning and some things you should you need to think about it but also i as i emphasize and things some things i've been writing about um you know ai the revolution hasn't happened yet yeah um great blog post i've i've been emphasizing that you know if you step back and look at uh intelligent systems of any kind whatever you mean by intelligence it's not just the humans or the animals or you know the plants or whatever you know so a market that brings goods into a city you know food to restaurants or something every day uh is a system it's a decentralized set of decisions looking at it from far enough away it's just like a collection of neurons everyone every neuron is making its own little decisions presumably in some way and if you step back enough every little part of an economic system is making us all of its decisions and just like with the brain who knows what the individual neuron doesn't know what the overall goal is right but something happens at some aggregate level same thing with the economy people eat in a city and it's robust it works at all scales small villages to big cities it's been working for thousands of years uh it works rain or shine so it's adaptive um so all kind of you know those are adjeeves one tends to apply to intelligent systems robust adaptive you know you don't need to keep adjusting it it's self self healing whatever plus not perfect you know intelligences are never perfect and markets are not perfect um but i do not believe in this area that you cannot that you can say well our computers our humans are smart but you know no markets are not more markets are so they are intelligent uh now um we humans didn't evolve to be markets we've been participating in them right but we are not ourselves a market per se um the neurons could be viewed as the market you can't there's economic you know neuroscience kind of perspectives that's interesting to pursue all that the point though is is that if you were to study humans and really be the world's best psychologist study for thousands of years and come up with the theory of human intelligence you might have never discovered principles of markets you know spy demand curves and you know matching and auctions and all that uh those are real principles and they lead to a form of intelligence that's not maybe human intelligence it's arguably another kind of intelligence there probably are third kinds of intelligence or fourth that none of us are really thinking too much about right now so if you really and then all those are relevant to computer systems in the future certainly the market one is relevant right now whereas understand human intelligence is not so clear that it's relevant right now probably not um so if you want general intelligence whatever one means by that or you know understand the intelligence in a deep sense and all that it is definitely has to be not just human intelligence it's got to be this broader thing and that's not a mystery markets are intelligent so you know it's definitely not just a philosophical stance to say we gotta move beyond and tell who intelligence that sounds ridiculous yeah but it's not and in that blog post you define different kinds of like intelligent infrastructure iii which i really like that's some of the concept you've just been describing do you see ourselves if we see earth human civilization is a single organism do you think the intelligence of that organism when you think from the perspective of markets and intelligence infrastructure is increasing is it increasing linearly is it increasing exponentially what do you think the future of that intelligence i don't know i don't tend to think i don't tend to answer questions like that because you know that's science fiction hoping to catch you off guard well again because you said it's so far in the future it's fun to ask and you'll probably you know like you said predicting the future is really nearly impossible but say as an axiom one day we create a human level superhuman level intelligent not the scale of markets but the scale of an individual what do you think is is what do you think it would take to do that or maybe to ask another question is how would that system be different than the biological human beings that we see around us today is it possible to say anything interesting to that question or is it just a stupid question it's not stupid question but it's science fiction science fiction and so i'm totally happy to read science fiction and think about it from time my own life i loved there was this like brain in a vat kind of you know little thing that people were talking about when i was a student i remember you know imagine that uh um you know between your brain and your body there's you know there's a bunch of wires right and suppose that every one of them was replaced with a uh uh literal wire and then suppose that wire was turning actually a little wireless you know there's a receiver and sender so the brain has got all the senders and receiver you know on all of its exiting uh you know axons and all the dendrites down the body have replaced with syndrome receivers now you could move the body off somewhere and put the brain in a vat right and then you could do things like start killing off those centers of receivers one by one and after you've killed off all of them where is that person you know they thought they were out in the body walking around the world and they moved on so those are science fiction things those are fun to think about it's just intriguing about where's what is thought where is it and all that and i think every 18 year old it's to take philosophy classes and think about these things and i think that everyone should think about what could happen in society that's kind of bad and all that but i really don't think that's the right thing for most of us that are my age group to be doing and thinking about i really think that we have so many more present you know first challenges and dangers and real things to build and all that um such that uh you know uh spending too much time on science fiction at least in public fora like this i think is is not what we should be doing maybe over beers in private that's right i'm well welcome welcome i'm not gonna broadcast where i have beers because this is gonna go on facebook a lot of people showing up there but um yeah i'll uh i love facebook twitter amazon youtube i have i'm optimistic and hopeful but uh maybe maybe i don't have grounds for such optimism and hope let me ask term you've mentored some of the brightest sort of some of the seminal figures in the field can you uh give advice to people who undergraduates today what does it take to take you know advice on their journey if they're interested in machine learning and ai in in [Music] the ideas of markets from economics and psychology and all the kinds of things that you're exploring what what what steps should they take on that journey well yeah first of all the door is open and second it's a journey i like your language there uh it is not that you're so brilliant and you have great brilliant ideas and therefore that's that's just you know that's how you have success or that's how you enter into the field uh it's that you apprentice yourself you you spend a lot of time you work on hard things you try and pull back and you be as broad as you can you talk lots of people um and it's like entering any kind of a creative community there's um years that are needed and uh human connections are critical to it so you know i think about you know being a musician or being an artist or something you don't just you know immediately from day one you know you you're a genius and therefore you do it no you um you know practice really really hard on basics and you uh be humble about where you are and then and you realize you'll never be an expert on everything so you kind of pick and there's a lot of randomness and a lot of kind of luck but luck just kind of picks out which branch of the tree go down but you'll go down some branch um so yeah it's it's a community so the graduate school is i still think is one of the wonderful phenomena that we have in our in our world it's it's very much about apprenticeship with an advisor it's very much about a group of people you belong to it's a four or five year process so it's plenty of time to start from kind of nothing to come up to something you know more expertise and then start to have your own creativity start to flower even surprise into your own self um and it's a very cooperative endeavor it's i think a lot of people uh think of science as highly competitive and i think in some other fields it might be more so here it's way more cooperative than you might imagine and people are always teaching each other something and people are always more than happy to uh be clear that so i i feel i'm an expert on certain kind of things but i'm very much not expert on lots of other things and a lot of them are relevant and a lot of them are i should know but it should in some sense i you know you don't so um i'm always willing to reveal my ignorance to people around me so they can teach me things and uh i think a lot of us feel that way about our field so it's very cooperative uh i might add it's also very international because it's so cooperative we see no barriers and uh so that the nationalism that you see especially in the current era and everything is just at odds with the way that most of us think about what we're doing here where this is a human endeavor and we we cooperate and are very much trying to do it together for the you know the benefit of everybody so last question where and how and why did you learn french and which language is more beautiful english or french um great question so um first of all i think italian's actually more beautiful than french and english and i also speak that so i'm i'm i'm married to an italian and i have kids and we speak italian um anyway though all kidding aside that every language allows you to express things a bit differently um and it is one of the great fun things to do in life is to explore those things so in fact when i kids or you know teens or uh college students ask me what they just study i say well do what your heart where your heart is certainly do a lot of math math is good for everybody but do some poetry and do some history and do some language too um you know throughout your life you'll want to be a thinking person you'll want to have done that um for me uh yeah french i learned when i was i'd say a late teen um i was living in the middle of the country in kansas and uh not much was going on in kansas with all due respect to kansas but uh and so my parents happen to have some french books on the shelf and just in my boredom i pulled them down and i found this is fun and i kind of learned the language by reading and when i first heard it spoken i had no idea what was being spoken but i realized i somehow knew it from some previous life and so i made the connection um but then you know i traveled and just i i love to go beyond my own barriers and uh my own comfort or whatever and i found myself in you know on trains in france next to say older people who would you know live the whole life of their own and the ability to communicate with them was was you know special and uh ability to also see myself in other people's shoes and have empathy and kind of work on that language as part of that um so um so after that kind of experience um and also embedding myself in french culture which is you know quite quite amazing you know languages are rich not just because there's something inherently beautiful about it but it's all the creativity that went into it so i learned a lot of songs read poems read books um and then i was here actually at mit where we're doing the podcast today and uh young professor um you know not yet married and uh um you know not having a lot of friends in the area so i just didn't have i was getting kind of a bored person i said i heard a lot of italians around there's happened to be a lot of italians at mit behind professor for some reason and so i was kind of vaguely understanding what they were talking about i said well i should learn this language too so i i did and then later met my spouse and uh you know wow italian became a more important part of my life but um but i go to china a lot these days i go to asia i go to europe and um every time i go i kind of uh i'm amazed by the richness of human experience and the the people don't have any idea if you haven't traveled kind of how i'm you know amazingly rich and i love the diversity it's not just a buzzword to me it really means something i love the you know you know embed myself with other people's experiences and uh so yeah learning language is a big part of that i think i've said in some interview at some point that if i had you know millions of dollars on the infinite time whatever what would you really work on if you really wanted to do ai and for me that is natural language and really done right you know deep understanding of language um that's to me an amazingly interesting scientific challenge and uh when we're very far away one we're very far away but good natural language people are kind of really invested then i think a lot of them see that's where the core of ai is that if you understand that you really help human communication you understand something about the human mind the semantics that come out of the human mind and i agree i think that will be such a long time so i didn't do that in my career just because i kind of i was behind in the early days i didn't kind of know enough of that stuff i was at mit i didn't learn much language and it was too late at some point to kind of spend a whole career doing that but i admire that field and uh um and so in my little way by learning language you know kind of that part of my brain has um has been trained up jan was right you truly are the miles davis and machine learning i don't think there's a better place than it was mike is a huge honor talking to you today merci beaucoup all right it's been my pleasure thank you thanks for listening to this conversation with michael i jordan and thank you to our presenting sponsor cash app download it use code lex podcast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on youtube give it five stars on apple podcast support it on patreon or simply connect with me on twitter at lex friedman and now let me leave you with some words of wisdom from michael i jordan from his blog post titled artificial intelligence the revolution hasn't happened yet calling for broadening the scope of the ai field we should embrace the fact that what we are witnessing is the creation of a new branch of engineering the term engineering is often invoked in a narrow sense in academia and beyond with overtones of cold effectless machinery and negative connotations of loss of control by humans but an engineering discipline can be what we want it to be in the current era we have a real opportunity to conceive of something historically new a human-centric engineering discipline i'll resist giving this emerging discipline a name but if the acronym ai continues to be used let's be aware of the very real limitations of this placeholder let's broaden our scope tone down the hype and recognize the serious challenges ahead thank you for listening and hope to see you next time you |
Andrew Ng: Deep Learning, Education, and Real-World AI | Lex Fridman Podcast #73 | the following is a conversation with Andrew and one of the most impactful educators researchers innovators and leaders in artificial intelligence and technology space in general he co-founded Coursera and Google brain launched deep learning AI landing AI and the AI fund and was the chief scientist at Baidu as a Stanford professor and with Coursera and deep learning AI he has helped educate and inspire millions of students including me this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon simply connect with me on Twitter at Lex Friedman spelled Fri D ma n as usual I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance side up in the App 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and STEM education for young people around the world and now here's my conversation with Andrew Eng the courses you taught on machine learning in Stanford and later on Coursera the co-founded have educated and inspired millions of people so let me ask you what people are ideas inspired you to get into computer science and machine learning when you were young when did you first fall in love with the field there's another way to put it growing up in Hong Kong Singapore I started learning to code when I was five or six years old at that time I was learning the basic programming language and they would take these folks and you know they'll tell you typed this program into your computer so typed that programs my computer and as a result of all that typing I would get to play these very simple shoot-'em-up games that you know I had implemented on my own minds old computer so I thought was fascinating as a young kid that I could write this code that's really just copying code from a book into my computer to then play these cool of video games another moment for me was when I was a teenager and my father because his doctor was reading about expert systems and about neural networks so he got me read some of these books and I thought was really cool you could write a computer that started to exhibit intelligence then I remember doing an internship was in high school this isn't Singapore where I remember doing a lot of photocopying and and I was office assistants and the highlight of my job was when I got to use the shredder so the teenager me remote thinking boy this is a lot of photocopying if only we could write software build a robot something to automate this maybe I could do something else so I think a lot of my work since then has centered on the theme of automation even the way I think about machine learning today were very good at writing learning algorithms they can automate things that people can do or even launching the first MOOCs massive open online courses that later led to Coursera I was trying to also meet what could be automatable in how I was teaching on campus process of Education tried to automate parts of that make it more to have more impact from a single teacher single educator yeah I felt you know teaching Stanford teaching machine learning it's about 400 students a year at the time and I found myself filming the exact same video every year telling the same jokes the same room and I thought why am I doing this well just take last year's video and then I can spend my time building a deeper relationship with students so he has process of thinking through how to do that that led to the first first moves that we launched and then you have more time to write new jokes are their favorite memories from your early days at Stanford teaching thousands of people in person and then millions of people online you know teaching online what not many people know was that a lot of those videos were shot between the hours of 10:00 p.m. and 3:00 a.m. a lot of times we were watching the first moves that fit with our announcer course but a hundred thousand people have signed up we just started to write the code and we had not yet actually filmed the video so you know a lot of pressure a hundred thousand people waiting for us to produce the content so many Friday Saturday's I would go out have dinner my friends and then I was thinking okay do I want to go home now or do you want to go to the office to film videos and the thoughts of you know that helped hundred thousand people potentially learn machine learning unfortunately that made me think okay I'm gonna go to my office go to my time in the recording studio I would adjust my Logitech webcam adjust my you know Wacom tablet make sure my lapel mic was on and then I was not recording often until 2:00 a.m. or 3:00 a.m. I think I'm fortunate it doesn't doesn't show that it was recorded that late at night but it was really inspiring the the thought that we could create content to help so many people learn about machine learning how does that feel the fact that you're probably somewhat along maybe a couple of friends recording with a logitech webcam and kind of going home alone at 1:00 and 2:00 a.m. at night and knowing that that's going to reach sort of thousands of people eventually millions of people is what's that feeling like I mean is there a feeling of just satisfaction of pushing through I think is humbling and I wasn't thinking about what I was viewing I think one thing we I'm proud to say we caught right from the early days was I told my whole team back then that the number one priority is to do what's best for learnis to asbestos students and so when I went in a recording studio the only thing on my mind was what can I say how can I design my slides ready to draw a right to make these concepts as clear as possible for lehre news I think you know I've seen sometimes instructors is tempting hey let's talk about my work maybe if I teach you about my research someone will cite my papers a couple more times and I think one things we got right launch the first few MOOCs and later building Coursera was putting in place that bedrock principle let's just do what's best for learners then forget about everything else and I think that that is a guiding principle turns out to be really important to the to the rise of the movement and the kind of learner your imagined in your mind is as as broad as possible as global as possible so really try to reach as many people interested in machine learning and AI as possible I really want to help anyone that had an interest in machine learning to break into fields and and I think sometimes eventually people ask me hey why you spend so much time explaining gradient descent and then and my answer was if I look at what I think to learn they need somewhat benefit from I felt that having that a good understanding of the foundations coming back to the basics would put them in a better stead to then build on a long term career so you've tried to consistently make decisions on that principle so one of the things you actually revealed to the narrow AI community at the time and to the world is that the amount of people who are actually interested in AI is much larger than we imagined by you teaching the class and how popular became it showed that wow this isn't just a small community of sort of people who go to Europe's and and it's much bigger it's the developers it's people from all over the world from front I mean I'm Russian so as everybody in Russia is really interested this is a huge number of programmers who are interested in machine learning India China South America everywhere that there's just millions of people who are interested machine learning so how big you get a sense that this number of people is that are interested in your perspective I think the numbers grown over time I think I'm one of those things that maybe it feels like it came out of nowhere but it's an insider building it it took years there's all those overnight successes that took years to get there my first foray into this type of education was when we were filming my Stanford class and sticking the videos on YouTube and then some other things with uploading the holes and so on but you know basically the one hour fifteen minute video that we put on YouTube and then we had four or five other versions of websites that had built most of what you would never have heard of because they reach small audiences but that allowed me to iterate allow my team and me to innovate to learn what the ideas that work and what doesn't for example one of the features I was really excited about and really proud of was build this website where multiple people could be logged into the website at the same time so today if you go to a website you know if you're logged in and then I want to log in you need to log out it was the same browser the same computer but I thought well one of two people say you and me were watching a video together in front of the computer what if a website could have you type your name and password hit me type in their password and then now the computer knows both of us are watching together and it gives both of us credit for anything we do as a group influences feature rolled it out in a higher in school in San Francisco we had about 20-something users worth the teacher there Sacred Heart Cathedral prep teachers great and guess what zero people use the speaker it turns out people studying online they want to watch the videos by themselves so you can playback pause at your own speed rather than in groups so that was one example of a tiny lesson learned out of many that allows us to hone in to the set of features and it sounds like a brilliant feature so I guess the lesson to take from that is you there's something that looks amazing on paper and then nobody uses it doesn't actually have the in the impact that you think it might have and so yeah I saw that you really went through a lot of different features and a lot of ideas you had to arrive at the final at Coursera its final kind of powerful thing that showed the world that MOOCs can educate millions and I think with how um machine learning movements as well I think it didn't come out of nowhere instead what happened was as more people learned about machine learning they will tell their friends and their friends will see how the big world to their work and then and in the community kept on growing um and I think we're still growing you know I don't know in the future what percentage of our developers would be AI developers I could easily see it being more for 50 percent right because so many a I developers broadly construed not just people doing the machine learning modeling but the people but the infrastructure data pipelines you know all the software's surrounding the old machine learning model maybe is even bigger I feel like today almost every software engineer has some understanding of the clouds no oh you know but maybe this is my microcontroller developer doesn't need to do the cloud but I feel like the vast majority of software in Jesus today are sort of having appreciated the cloud I think in the future maybe we'll approach nearly a hundred percent of all developers being you know in some way an AI developer or at least having an appreciation of machine learning and my hope is that there's this kind of effect that there's people who are not really interested in soft being a programmer or being into software engineering like biologists chemists and physicists even mechanical engineers and all these disciplines that are now more and more sitting on large data sets and here they didn't think they're interested in programming until they have this data set and they realized there's the set of machine learning tools that allow you to use the data set so they actually become they learn to program and they become new programmer so like the not just because you've mentioned a larger percentage of developers become machine learning people the it seems like more and more the the kinds of people who are becoming developers is also growing significantly yeah yeah I think I think once upon a time only a small part of humanity was literate you could read and write and and and maybe you thought maybe not everyone needs to learn to read and write you know you just go listen to a few monks write me to you and maybe that was enough or maybe we just need a few handful of authors to write the bestsellers and then no one else needs to write but what we found was that by giving as many people you know in some countries almost everyone basically literacy it dramatically enhanced human to human communications and we can now write for an audience of one such as if I send you an email you send me an email I think in computing we're still in that phase where so few people know how the codes that the code is mostly have to code for relatively large audiences but if everyone well most people became developers at some level similar to how most people and develop economies are somewhat literate I would love to see the owners of a mom-and-pop store be with a very little code to customize the TV display for their special this week and I think of it enhance human to computer communications which is becoming more more important today as well so you think you think it's possible that machine learning becomes kind of similar to literacy where we're yeah like you said the owners of a mom-and-pop shop is basically everybody in all walks of life would have some degree of programming capability I could see society getting there um there's one other interesting thing you know if I go talk to the mom and pop store if I toss a lot of people in their daily professions I previously didn't have a good story for why they should learn to code yeah we give them some reasons but what I found with the rise of machine learning and data science is that I think the number of people with a concrete use for data science in their daily lives and their jobs may be even larger than the number of people of a country used for software engineering for example if you were actually run a small mom-and-pop store I think if you can analyze the data about your sales your customers I think there's actually real value there maybe even more than traditional software engineer so I find that for a lot of my friends in various professions being recruiters or accountants or you know people that work in the factories which I deal with more and more these days I feel if they were data scientists at some level they could immediately use that in their work so I think that data science and machine learning may be an even easier entree into the developer world for a lot of people then the software engineering that's interesting and I grew that but that's a beautifully put we live in a world where most courses and talks have slides PowerPoint keynote and yet you famously often still use a marker and a whiteboard the simplicity of that is compelling in for me at least fun to watch so let me ask why do you like using a marker and whiteboard even on the biggest of stages I think it depends on the concepts you want to explain for mathematical concepts it's nice to build at the equation one piece at a time and the whiteboard marker or the pen is stylus is a very easy way you know to build up the equation a build up a complex concept one piece at a time while you're talking about it and sometimes that enhances understandability the downside of writing is as it slow and so if you want a long sentence it's very hard to write that so I think their pros and cons in sometimes I use slides and sometimes they use a whiteboard or a stylus the slowness of a whiteboard is also it's upside is it forces you to reduce everything to the basics some of some of your talks and involve the whiteboard I mean there's really none but you go very slowly and you really focus on the most simple principles and that's a beautiful that enforces a kind of a minimalism of ideas that I think is surprisingly least for me is is great for education like a great talk I think is not one that has a lot of content a great talk is one that just clearly says a few simple ideas and I think you the white board somehow enforces that Peter erbil who's now one of the top roboticists and reinforcement learning experts in the world was your first PhD student hey so I bring him up just because I kind of imagine this is this was must have been an interesting time in your life do you have any favorite memories of working with Peter your first student in those uncertain times especially before deep learning really really sort of blew up any favorite memories from those times you know I was really fortunate to have had Peter of you as my first PhD students and I think even my long-term professional success builds on early foundations or early work that that Peter was so critical to so I was really grateful to him for working at me you know what not a lot of people know is just how hard research was and and so is Peter's PhD thesis was using reinforcement learning to fly helicopters and so you know actually even today the website Helly thought stanford.edu heö I don't Stanford are you still up here watch videos of us using reinforcement learning to make the helicopter fly upside down five loops rolls this is cool so one of the most incredible robotics videos ever so how do you still watch it oh yeah thanks firing that's from like 2000 it's eight or seven or six like that really my dad's like yeah so is over ten years old that was really inspiring to a lot of people yeah but not many people see is how hard it was so Peter and Adam codes and Morgan Quigley and I work on various versions of the helicopter and a lot of things did not work for example turns out one of the hardest problems we had was when the helicopters flying around upside down doing stunts how do you figure out the position how do you localize a helicopter so we want to try all sorts of things having one GPS unit doesn't work because you're flying upside down the GPS units facing down so you can't see the satellites so we tried them we experimented trying to have two GPS units one facing up one facing the house if you flip over that didn't work because the downward facing one couldn't synchronize if you're flipping quickly um Morgan quickly was exploring this crazy complicated configuration of specialized hardware to interpret GPS signal look into FPGA is completely insane spent about a year working on that didn't work so I remember Peter great guy him and me you know sitting down in my office looking at saw the latest things we had tried that didn't work and saying you know Don it like what now because because we tried so many things in it and it just didn't work in the end what we did when Adam Cole's was was crucial to this was put cameras on the ground and used cameras on the ground to localize a helicopter and that soft a localization problem so that we couldn't focus on the reinforcement learning and inverse reinforcement learning techniques so didn't actually mean to helicopter fly and you know I'm reminded when when was doing um this work at Stanford around that time there was a lot of reinforcement learning theoretical papers but not a lot of practical applications so the autonomous helicopter work for fine helicopters was this one of the few you know practical applications of reinforcer learning at the time which which caused it to become pretty well known I I feel like we might have almost come full circle with today there's so much but so much hype so much excitement yeah about reinforcement learning but again we're hunting for more applications and all of these great ideas that delica he's come up with what was the drive sort of in the face of the fact that most people doing theoretical work what motivate you in the uncertainty and the challenges to get the helicopter sort of to do the the applied work to get the actual system to work yeah in the face of fear uncertainty is sort of the setbacks the you mentioned for localization I like stuff that works III know physical world so like it's this back to the shredder and you know III like theory but when I work on theory myself and this personal taste I'm not seeing anyone else should do what I do but when I work on theory I Percy enjoyed more if I feel that my the work I do will influence people have positive impact will help someone I remember when many years ago our speaking with a mathematics professor and it kind of just said hey ytt what you do and then he said he you know he had stars in his eyes when he answered and this mathematician not from Stanford different University he said I do what I do because it helps me to discover truth and beauty in the universe here starts analyzing he said yeah and I thought that's great um I don't want to do that I think it's great that someone does that fully supportive people that do a lot of respect review that but I am more motivated when I can see a line to how the work that my team's and I are doing house people the world needs all sorts of people I'm just one type hoping everyone should do things the same way as I do but when I delve into either theory or practice if I personally have conviction you know that here's a pathway to help people I find that more satisfying to have that conviction that that's your path you were a proponent of deep learning before it gained widespread acceptance what did you see in this field that gave you confidence what was your thinking process like in that first decade of the I don't know that's called 2000s the odds yeah I can tell you the thing we got wrong with the thing we got right the thing we really got wrong was the importance of the early importance of unsupervised learning so early days of Google brain we put a lot of effort into unsupervised learning rather than supervised learning and those as argument I think was around them 2005 after a new Europe's at that time called nips but now in Europe said ended and Geoff Hinton and I were sitting in the cafeteria outside you know the conference we had lunch was chatting and Geoff pulled up this napkin he started sketching this argument on her on a napkin it was very compelling as our repeated human brain has about a hundred trillion so there's 10 to the 14 synaptic connections you will live about 10 10 and 9 seconds that's 30 years you actually live for two to two by ten to nine maybe three right nine seconds so just let's say ten to nine so if each synaptic connection each weight in your brains new network has just a one bit parameter that's 10 to the 14 bits you need to learn in up to 10 to 9 seconds of your life so via the simple argument which is a lot of problems it's very simplified that's 10 to the 5 bits per second you need to learn in your life and I have a one-year-old daughter I am NOT pointing out 10 to 5 bits per second of labels to her so and and I think I'm a very loving parent but I'm just not gonna do that so from this you know very crude definitely problematic argument there's just no way that most of what we know is through supervised learning the wife you get so many visit information is from sucking in images audio those experiences in the world and so that arguments and a lot of known forces argument you go going to really convince me that there's a lot of power to unsupervised learning so that was the part that we actually maybe maybe gone wrong I still think I was learning is really important but we but but in the early days you know 10 15 years ago and all of us thought that was the path forward oh so you're saying that that that perhaps was the wrong intuition for the time for the time that that was the part we got wrong the part we got right was the importance of scale so Adam calls another wonderful person fortunate said worth of him he was in my group of Stanford at the time and Adam had run these experiments at Stanford showing that the bigger we train a learning algorithm the better performance and it was based on that it was a graph that hadn't generated you know where the x-axis y-axis lines going up into the right so bigger paint make this thing the better his performance accuracy is the vertical axis so it's really based on that chart that Adam generated that he gave me the conviction that you could scale these models way bigger than what we could on the few CPUs we should understand that then we could get even better results and it was really based on that one figure that Adam generated that gave me the conviction to go of Sebastian's to pitch you know starting starting a project at Google which became the CooCoo brain crunch brain you know filing Google brain and there the intuition was scale will bring performance for the system so we should chase larger and larger scale and I think people don't don't realize how how groundbreaking of it is simple but it's a groundbreaking idea that bigger data sets will result in better performance it was cultural first it was controversial at the time some of my well-meaning friends you know see any people in the machine or in community I won't name but whose people told people of some some of whom we know my well-meaning friends came and we're trying to give me friendly meze hey Andrew why are you doing this is crazy it's in the near enough architecture look at these architectures of building you just like go for scale like there's a bad career move so so my well-meaning friends you know we're trying to some of them we're trying to talk me out of it if I find it if you want to make a breakthrough you sometimes have to have conviction and do something before it's popular since that lets you have a bigger impact let me ask you just a small tangent on that topic I find myself arguing with people saying that greater scale especially in the context of active learning so it's very carefully selecting the data set but growing the scale of the data set is going to lead to even further breakthroughs in deep learning and there's currently pushback at that idea that larger datasets are no longer that so you want to increase the efficiency of learning you want to make better learning mechanisms and I personally believe that bigger data sets will still with the same learning methods we have now result in better performance what's your intuition at this time on those I Anna this dual side is do we need to come up with better architectures for learning or can we just get bigger better data sets that will improve performance I think both are important and there's also problem dependent so for a few data sets we may be approaching your Bayes error rate of approaching or surpassing human level performance and then there's that theoretical ceiling that we will a surface of a CRE but then I think there plenty of problems where we're we're still quite far from either human of a performance all from Bayes error rate and bigger data says with new networks but without further elaborate innovation will be sufficient to take us further but on the flip side if we look at the recent breakthroughs using you know transforming networks for language models it was a combination of novel architecture but also scale has a lot to do with it if we look at what happened with your GP - and birds I think scale was a large part of the story yeah that's that's not often talked about is the scale of the data set it was trained on and the quality of the data set because there's some so it was like reddit threads that had they were operated highly so there's already some weak supervision on a very large data set that people don't often talk about right I find it today we have maturing processes to managing cold things like get right version control it took us a long time to evolve the good processes I remember when my friends and I were emailing each other C++ files in email you know but then we had was that CVS subversion get maybe something else in the future we're very immature in terms of Susa managing data and think about how the creator and how the soft I'm very hot messy data problems I think there's a lot of innovation there to be I still I love the idea that you were versioning through email I'll give you one example um when we work with manufacturing companies is not at all uncommon for there to be multiple late lists that disagree of each other right and so we were doing the work in visual inspection we will you know take say a plastic cards and show to one inspector and the inspector sometimes very opinionated there go clearly that's the defector scratch understand so gonna check this part take the same parts of different inspector different very opinionated clearly the scratch is small is fine don't throw it away you're gonna make us yours and then sometimes you take the same plastic part show it to the same inspector in the afternoon and I suppose in the morning and very affinity go in the morning to say clearly is okay in the afternoon equally confident clearly this is a defect and so what does the i-team supposed to do if if sometimes even one person doesn't agree of himself or herself in the span of a day so I think these are the types of um very practical very messy data problems that that you know that my teams wrestle with in the case of large consumer Internet companies where you have a billion users you have a lot of data you don't worry about they just take the average it kind of works but in a case of other industry settings we don't have big data if just a small data very small the users maybe 100 defective parts or 100 examples of a defect if you have only 100 examples these little labeling errors you know if 10 of your hundred labels aren't wrong that actually is 10% it is that has a big impact so how do you clean this up what you're supposed to do this is an example of the of the types of things that my team's did this is a landing AI example are wrestling with to deal with small data which comes up all the time once you're outside consumer internet yeah that's fascinating so then you invest more effort in time in thinking about the actual labeling process what are the labels what are the how our disagreements resolved in all those kinds of like pragmatic real world problems that's a fascinating space yeah I find it actually when I'm teaching at Stanford I increasingly encourage students at Stanford to try to find their own project for the end of term project rather than just downloading someone else's nicely clean data set it's actually much harder if you need to go and define your own problem and find your own dataset rather than you go to one of the several good websites very good websites with with creams scopes datasets that you could just work on you're now running three efforts the AI fund landing AI and deep learning AI as you've said the AI fund is involved in creating new companies from scratch Landing AI is involved in helping already established companies do AI and deep learning AI is for education of everyone else or of individuals interested of getting into the field and excelling in so let's perhaps talk about each of these areas first deep learning that AI how the basic question how does a person interested in deep learning get started in the field the Atlanta AI is working to create courses to help people break into AI so my machine learning course that I taught through Stanford is one of the most popular causes on Coursera to this day it's probably one of the courses sort of if I ask somebody how did you get into machine learning or how did you fall in love with machine learning or will get you interested they it always goes back to rain and Drang at some point you won't find the amount of people you influence is ridiculous so for that I'm sure I speak for a lot of people say big thank you no yeah thank you you know I was once reading a news article I think it was tech review and I'm gonna mess up the statistic but I remember reading article that said um something like one-third of all programmers are self-taught I may have the number one third Romney was two-thirds but I rent an article I thought this doesn't make sense everyone is self-taught because you teach yourself I don't teach people and it's no good haha oh yeah so how does one get started in deep learning and where does deep learning that AI fit into that so the define specialization offered by today is is this I think one it was called service specialization it might still be so it's very popular way for people to take that specialization to learn about everything from new networks to how to tune in your network so what is it confident to what is a RNA nor sequence model or what is an attention model and so the design specialization um steps everyone's through those algorithms so you deeply understand it and can implement it and use it you know for whatever a from the very beginning so what would you say the prerequisites for somebody to take the deep learning specialization in terms of maybe math or programming background you know need to understand basic programming since there are Pro exercises in Python and the map prereq is quite basic so no calculus is needed if you know calculus is great you get better intuitions but deliberately try to teach that specialization without requirement calculus so I think high school math would be sufficient if you know how to Mouse by two matrices I think I think that that deaths that desperates so little basically in your algebra it's great basically the algebra even very very basically the algebra and some programming I think that people that done the machine learning also find a deep learning specialization a bit easier but is also possible to jump into the divine specialization directly but it'll be a little bit harder since we tend to you know go over faster concepts like how does gradient descent work and what is an objective function which which is covered mostly in the machine learning course could you briefly mention some of the key concepts in deep learning that students should learn that you envision them learning in the first few months in the first year or so so if you take the d-line specialization you learned foundations of what is in your network how do you build up in your network from a you know single which is a unit stack of layers to different activation functions you don't have a trained in your networks one thing I'm very proud of in that specialization as we go through a lot of practical know-how of how to actually make these things work so what the differences between different optimization algorithms so what do you do of the algorithm over things so how do you tell the algorithm is overfitting when you collect more data when should you not bother to collect more data I find that um even today unfortunately there are your engineers that will spend six months trying to pursue a particular direction such as collect more data because we heard more data is valuable but sometimes you could run some tests and could have figured out six months earlier therefore this problem collecting more data isn't going to cut it so just don't spend seconds collecting more data spend your time modifying the architecture or trying something also go through a lot of the practical know-how also that when when when when someone will you take the deviant specialization you have those skills to be very efficient in how you build is net so dive right in to play with the network to train it to do the inference on a particular data set to build an intuition about it without without building it up too big to where you spend like you said six months learning building up your big project without building an intuition of a small small aspect of the data that could already tell you everything needs you know about that date yes and also the systematic frameworks of thinking for how to go about building practical machine learning maybe to make an analogy um when we learn to code we have to learn the syntax of some Korean language right be a Python or C++ or octave or whatever but that equally important that may be even more important part of coding is to understand how to string together these lines of code into coherent things so you know when should you put something in the function call and when should you not know how do you think about abstraction so those frameworks are what makes the programmer efficient even more than understanding to syntax I remember when I was an undergrad at Carnegie Mellon um one of my friends with debug their codes by first trying to compile it and then it was T plus s code and then every line did a syntax error they want to care for the syntax errors as quickly as possible so how do you do that well they would delete every single line of code with a syntax error so really efficient for general syntax errors were horrible service I think so we learned how the debug and I think in machine learning the way you debug the machine learning program is very different than the way you you know like do binary search or whatever use the debugger I traced through the code in in traditional software engineering so isn't evolving discipline but I find that the people that are really good at debugging machine learning algorithms are easily 10x maybe 100x faster at getting something to work so and the basic process of debugging is so the the bug in this case why is in this thing learning learning improving sort of going into the questions of overfitting and all those kinds of things that's that's the logical space that the debugging is happening in would in your network yeah the often question is why doesn't it work yet well can I expect it eventually work and what are the things I could try change the architecture malteaser more regularization different optimization algorithm you know the different types of data are so to answer those questions systematically so that you don't heading down so you don't spend six months hitting down the blind alley before someone comes and says why you spent six months doing this what concepts and deep learning do you think students struggle the most with or sort of this is the biggest challenge for them was to get over that hill it's it hooks them and it inspires them and they really get it similar to learning mathematics I think one of the challenges of deep learning is that there are lot of concepts that build on top of each other if you ask me what's hard about mathematics I have a hard time pinpointing one thing is it addition subtraction is it carry is it multiplication long there's lot of stuff I think one of the challenges of learning math and of learning certain technical fields is that a lot of concepts and you miss a concept then you're kind of missing the prerequisite for something that comes later so in the deep learning specialization try to break down the concepts to maximize the answer each component being understandable so when you move on to the more advanced thing we learn your confidence hopefully you have enough intuitions from the earlier sections to then understand why we structure confidence in a certain certain way and then eventually why we build you know our nn zone ellos tienen or attention model in a certain way a building on top of the earlier concepts I'm curious you you you do a lot of teaching as well do you have a do you have a favorite this is the hard concept moment in your teaching well I don't think anyone's ever turned the interview on me I think that's a really good question yeah it's it's it's really hard to capture the moment when they struggle I think you put a really eloquently I do think there's moments that are like aha moments that really inspire people I think for some reason reinforcement learning especially deep reinforcement learning is a really great way to really inspire people and get what the use of neural networks can do even though you know networks really are just a part of the deep RL framework but it's a really nice way to the to paint the entirety of the picture of a neural network being able to learn from scratch knowing nothing and explore the world and pick up lessons I find that a lot of the aha moments happen when you use deep RL to teach people about neural networks which is counterintuitive I find like a lot of the inspired sort of fire and people's passion people's eyes comes from the RL world do you find I mean first of all learning and to be a useful part of the teaching process or not I still teach me forceful learning and one of my Stanford classes and my PhD thesis wonderful so nice thank you I find it if I'm trying to teach students the most useful techniques for them to use today I end up shrinking the amount of time and talk about reinforce another in English it's not what's working today now our world changes so fast maybe it does be totally different in a couple years I think we need a couple more things for reinforcement learning to get there if you get there yeah one of my teams is looking to reinforce the learning for some robotic control toss so I see the applications but if you look at it as a percentage of all of the impact of you know the types of things we do is at least today outside of you know playing video games right in a few of the games the the scope nearest a bunch of us was standing around saying hey what's your best example of an actual deploy reinforcement learning application and you know among your like scene in machine learning researchers right and again there are some emerging ones but there are there are not that many great examples well I think you're absolutely right the sad thing is there hasn't been a big application impactful real-world application reinforcement learning I think its biggest impact to me has been in the toy domain in the game domain in a small example that's what I mean for educational purpose it seems to be a fun thing to explore new networks with but I think from your perspective and I think that might be the best perspective is if you're trying to educate with a simple example in order to illustrate how this can actually be grown to scale and have a real world impact then perhaps focusing on the fundamentals of supervised learning in the context of you know a simple data set even like an eminence data set is the right way is the right path to take I just the amount of fun I've seen people have of the reinforcement learning it's been great but not in the applied impact on the real-world setting so it's a it's a trade-off how much impact you want to have versus how much fun you want to have yeah that's really cool and I feel like you know the world actually needs also even within machine learning I feel like deep learning is so exciting but the AI team shouldn't just use deep learning I find that my team's use a portfolio of tools and maybe that's not the exciting thing to say but some days we use internet some days we use a you know the PC a the other day are sitting down with my team looking at PC residuals trying to figure out what's going on with PC applied to manufacturing problem and sometimes we use the promising graphical model sometimes you use a knowledge trough where some of the things that has tremendous industry impact but the amount of chat about knowledge drops in academia has really thin compared to the actual rower impact so so I think reinforcement learning should be in that portfolio and then it's about balancing how much we teach all of these things and the world the world should have diverse skills if he said if you know everyone just learn one one narrow thing yeah the diverse skill help you discover the right tool for the job what is the most beautiful surprising or inspiring idea in deep learning to you something that captivated your imagination at the scale that could be a the performance I give you achieve of scale or there are other ideas I think that if my only job was being an academic researcher and have an unlimited budget and you know didn't have to worry about short-term impact and only focus on long term in fact I pretty spent all my time doing research on unsupervised learning I still think unsupervised learning is a beautiful idea at both this Pastner herbs and I CML I was attending workshops on the center Vera's talks about self supervised learning which is one vertical segment maybe of sort of unsupervised learning I'm excited about maybe just to summarize the idea I guess you know the idea of describe movie no please so here's the examples self supervised learning let's say we grab a lot of unlabeled images off the internet so with infinite amounts of this type of data I'm going to take each image and rotate it by a random multiple of 90 degrees and then I'm going to train a supervised near Network to predict what was the original orientation so has something rotated 90 degrees hundred eighty degrees turns in seven degrees or zero degrees so you can generate an infinite amount of label data because you rotate to the image so you know what's the branch of label and so various researchers have found that by taking unlabeled data and making up label datasets and training a large neural network on these thoughts you can then take the hidden layer representation and transfer to a different toss very powerfully um learning word embeddings when we take a sentence to leave the word predict the missing word which is how we learn you know one of the ways we learn where the embeddings is another example and I think there's now this portfolio of techniques for generating these made-up toss another one called jigsaw what behave you take an image cut it up into a you know three by three grid so like a nine 3x3 puzzle piece jump out the nine pieces and have a neural network predict which of the nine factorial possible permutations it came from so are many groups including your opening I Peter P has been doing some work on this to Facebook Google brain I think deep mind Oh Aaron menthols has great work on the CPC objective so many teams are doing exciting work and I think this is a way to generate infinitely both data and and I find this a very exciting piece of an supervisor and he's a long-term you think that's going to unlock a lot of power and in machine learning systems is this kind of unsupervised learning I don't think there's the whole enchilada I think that's just a piece of it and I think this one piece unsuited is self supervised learning it's starting to get traction we're very close to it being useful well what embedding is really really useful I think we're getting closer and closer to just having a significant real world impact maybe in computer vision and video but I think this concept and then I think there'll be other concepts around it you know other unsupervised learning things that I worked on I've been excited about I was really excited about sparse coding and I see a slow feature analysis I think all of these are ideas that various of us were working on about a decade ago before we all got distracted by how well supervised learning was wearing work yeah it was a we would return we were returned to the fundamentals of representation learning that that really started this movement of deep learning I think there's a lot more work that one could explore around the steam of ideas and other ideas to come or better algorithms so if we could return to maybe talk quickly about the specifics of deep learning that AI the deep learning specialization perhaps how long does it take to complete the course would you say the official length of the divine specialization is I think 16 weeks so about 4 months but is go at your own pace so if you subscribe to the divine socialization there are people that finish that in less than a month by working more intensely and study more intensely so it really depends on on the individual who created the divine specialization we wanted to make it very accessible and very affordable and with you know Coursera and Devon dyers education mission one thing that's really important to me is that if there's someone for whom paying anything is a it's a financial hardship then just apply for financial and get it for free if you were to recommend a daily schedule for people in learning whether it's through the deep learning that a a specialization or just learning in the world of deep learning what would you recommend how do they go about day two days or a specific advice about learning about their journey in the world of deep learning machine learning I think I'm getting the habit of learning is key and that means regularity so for example we send out our weekly newsletter the batch every Wednesday so people know is coming Wednesday you can spend a little bit of time on Wednesday catching up on the latest news through the batch on the on on on Wednesday and for myself I've picked up a habit of spending some time every Saturday and every Sunday reading or studying and so I don't wake up on the Saturday and have to make a decision do I feel like reading or studying today or not it's just it's just what I do and the fact is a habit makes it easier so I think if someone can get in that habit it's like you know just like we brush our teeth every morning I don't think about it if I thought about this a little bit annoying to have to spend two minutes doing that but it's a habit that it takes no cognitive loads but this would be so much harder if we have to make a decision every morning so and actually that's the reason why we're the same thing every day as well it's just one less decision I just get out in there where I'm sure so I think you can get that habit that consistency of studying then then it actually feels easier so yeah it's kind of amazing in my own life like I play guitar every day for life forced myself to at least for five minutes play guitar it's just it's a ridiculously short period of time but because I've gotten into that habit it's incredible what you can accomplish in a period of a year or two years you could become you know exceptionally good at certain aspects of a thing by just doing it every day for a very short period of time it's kind of a miracle that that is how it works it's adds up over time yeah and I think is this something is often not about the bursts of sustained effort and all-night is because you can only do that in a limited of times it's the sustained effort over a long time I think you know reading two research papers there's a nice thing to do but the power is not reading through research papers this reading through research papers a week for a year then you've read a hundred papers and and you actually learn a lot when you read a hundred papers so regularity and making learning a habit do you have do you have general other study tips for particularly deep learning that people should in in their process of learning is there some kind of recommendations or tips you have as they learn one thing I still do when I'm trying to study something really deeply is take handwritten notes in theories I know there are a lot of people that take the deep learning courses during the commutes or something where maybe mobile quit to take notes so I know it's may not work for everyone but when I'm taking courses on Coursera you know and that still takes on my every now and then the most recent I took was a was a course on clinical trials because those engines of all that I got my little moleskin notebook and I was sitting in my desk is just taking down notes so what the instructor was saying and that Act we know that that act of taking notes preferably handwritten notes increases retention so as you're sort of watching the video just kind of pausing maybe and then taking the basic insights down on paper yeah so I should have been a few studies if you know search online you find for some of these studies that taking handwritten notes because handwriting is slower as were saying just now um it causes you to recoat the knowledge in your own words more and that process of recoding promotes long-term attention this is as opposed to typing which is fine again typing is better than nothing or in taking across and nautical is better than nothing any cause law but comparing handwritten notes and typing um you can usually type faster for a lot of people do you can hand write notes and so when people type they're more likely to transcribe verbatim what they heard and that reduces the amount of recoding and that actually results in less long-term retention I don't know what the psychological effect there is but so true there's something fundamentally different about in handwriting I wonder what that is I wonder if it is as simple as just the time it takes to write it slower yeah and and and because because you can't write as many words you have to take whatever they said and summarize it into fewer words and that summarization process requires deeper processing of the meaning which then results in better attention that's fascinating oh and then I spent I think yeah because of course error I spent so much time studying pedagogy thank you my passion that I really love learning how to more efficiently help others learn yeah one of the things I do both in creating videos or when we write the batch is um I kind of think is one minute spent of us going to be a more efficient learning experience than one minute spent anywhere else and we really try to you know make a time efficient for the learning it's good to know everyone's busy so when when we're editing them I often tell my teams everywhere it needs to fight for his life and if can delete it where this is the lead to that not wait that's not waste than during this time wow that's so it's so amazing that you think that way because there is millions of people that are impacted by your teaching and sort of that one minute spent has a ripple effect right three years of time which is just fascinating talk about how does one make a career out of an interest in deep learning give advice for people we just talked about sort of the beginning early steps but if you want to make it a entire life's journey or at least a journey of a decade or two how did it how do you do it so most important thing is to get started right and ever I think in the early part of a career coursework um like the divine specialization or it's a very efficient way to master this material so because you know instructors be me or someone else or you know Laurence Moroney teaches our tensor field specialization and other things we're working on spend effort to try to make a time efficient for you to learn new concepts of coursework because actually a very efficient way for people that learn concepts and the beginning parts of break into new fields in fact one thing I see at Stanford some of my PhD students want to jump in the research right away and actually tend to say look when you first copy yours the piece didn't spend time ticking causes because it lays the foundation it's fine if you're less productive in your first couple of years you'd be better off in the long term um beyond a certain point there's materials that doesn't exist in courses because it's too cutting edge the courses we created yeah there's some practical experience that we're not yet that good as teaching in a in a course and I think after exhausting the efficient course were then most people need to go on to either ideally work on projects and then maybe also continue their learning by reading blog polls and research papers and thing like that doing practice is really important and again I think is important to start small it's just do something today you read about deep learning if you like all these people doing such exciting things whatever I'm not building a neural network they change the world and what's the point well the point is sometimes building that time in your network you know be it m-miss or upgrade to a fashion amnesty whatever it's doing your own fun hobby project that's how you gain the skills to let you do bigger and bigger projects I find this to be true at the individual level and also at the organizational level for company to become good at machine learning sometimes the right thing to do is not to tackle the giant project is instead to do the small project that lets the organization learn and then build up from there but this triple for individuals and and and for and for companies just taking the first step and then taking small steps it's the key should students pursue a PhD do you think you can do so much that's the one of the fascinating things in machine learning you can have so much impact without ever getting a PhD so what are your thoughts should people go to grad school should people get a PhD I think that there are multiple good options of which doing a PhD could be one of them I think that if someone's admitted to top ph.d program you know that MIT Stanford top schools I think that's a very good experience or someone gets a job at a top organization at the top a I team I think that's also good experience there are some things you still need a PhD to do if someone's aspiration is to be a professor here at the top academic University you just need a PhD to do that but if it goes to you know start a complete build a complete do great technical work I think PhD is a good experience but I would look at the different options available to someone you know where the places where you can get a job where the place isn't getting a PhD program and kind of weigh the pros and cons of those so just to linger on that for a little bit longer what final dreams and goals do you think people should have so the what options for they explore so you can work in industry so for a large company like Google Facebook buy do all these large companies already have huge teams of machine learning engineers you can also do with an industry sort of more research groups that kind of like Google research Google brain that you can also do like we say the professor neck as in academia and what else oh you can still build your own company you can do a start-up is there anything that stands out between those options or are they all beautiful different journeys that people should consider I think the thing that affects your experience more is less are you in discomfort versus that company your academia versus industry I think the thing that affects to experience Moses who are the people you're interacting with you know in the daily basis so even if you look at some of the large companies the experience of individuals and different teams is very different and what matters most is not the logo above the door when you walk into the giant building every day what matters the most is who are the 10 people who are the 30 people you interact with every day so I actually tend to advise people if you get a job from from a company also who is your manager who are your peers who are you actually going to talk to you we're all social creatures we tend to you know become more like the people around us and if you're working with great people you will learn faster or if you get admitted if you get a job at a great company or a great university maybe the logo you walk in you know is great but you're actually stuck on some team doing really worth it doesn't excite you and then that's actually really bad experience so this is true both universities and for large companies for small companies you can kind of figure out who you be working quite quickly and I tend to advise people if a company refuses to tell you who you work with someone say oh join us the rotation system will figure out I think that that that's a worrying answer because it because it means you may not get sense - you mean not actually get to team with with great peers and great people to work with it's actually a really profound advice that we kind of sometimes sweep we don't consider to rigorously or carefully the people around you are really often this especially when you accomplish great things it seems the great things are accomplished because of the people around you so that that's a it's not about the the worry whether you learn this thing or that thing or like you said the logo that's hangs up top it's the people that's a fascinating and it's such a hard search process of finding just like finding the right friends and somebody to get married with and that kind of thing it's a very hard search process a people search problem yeah but I think when someone interviews you know at a university or the research lab at a large corporation it's good to insist on just asking who are the people who is my manager and if you refuse to tell me I'm gonna think well maybe that's because you don't have a good answer it may not be someone I like and if you don't particularly connect if something feels off for the people then don't stick to it you know that's a really important signal to consider yeah and that's yeah I am in my standard cause cs2 30s was an ACN talk I think I gave like a hour long talk on career advice including on the job search process and then some of these those are yours if you can find those videos on also and others I'll point people to them beautiful so the AI fund helps ai startups get off the ground or perhaps you can elaborate all the fun things it's evolved with what's your advice and how does one build a successful hey I start up you know in second Valley a lot of starter failures come from building our products that no one wanted so when you know cool technology but who's gonna use it so I think I tend to be very outcome driven um and then customer obsess ultimately we don't get to vote if we succeed or fail is only the customer that the only one that gets a thumbs up or thumbs down those in the long term in the short term you know there are various people who get various votes but in the long term that's what really matters so as you build to start where to cast as the question well the customer gives a thought and give a thumbs up on this I think so I think startups that are very customer focused customer says deeply understand the customer and are oriented to serve the customer are more likely to succeed with the provision that I think all of us should only do things that we think create social good and lose the world for words I'm sorry I personally don't want to build addictive digital products just so long as you know the things that that could be lucrative but I won't do but if we can find ways to serve people in meaningful ways I think those can be those can be great things to do either the academic setting or in a corporate setting real startup setting so can you give me the idea of why you started the AI fund I remember when I was leaving the AI group at Baidu I had two jobs two parts of my job one was to build an AI engine to support the existing businesses and that wasn't running you know just read this performed by itself the second part of my job at the time which was to try to systematically initiate new lines of businesses using the company's aiq abilities so you know the self-driving car team came out my group the spot speaker team similar to what is some amazonica a lexer in the US but we announced it before Amazon did so we were goodbye to wasn't following him wasn't following an Amazon that that came out of my group and I found that to be um actually that the most fun part of my job so what I what to do was to build AI fund as a startup studio to systematically create new startup firms with all the things we can now do of AI I think the ability to build new teams to go after this rich space of opportunities is a very important way to very important mechanism to get these projects done that I think will move the world forward so of unfortunate that don't the few teams that had a meaningful positive impact and I felt that we might present do this in the most systematic repeatable way so a start-up studio is a relatively new concept there there are maybe dozens of startup studios you're right now but I feel like all of us many teams are still trying to figure out how do you systematically build companies with a high success rate so I think even though my you know venture capital friends are seem to be more and more building companies rather than investing companies but I find a fascinating thing to do to figure out the mechanisms by which we could systematically build successful teams successful businesses in in areas that we find meaningful so startup studio is something is is a place and a mechanism for startups to go from zero to success so try to develop a blueprint it's actually a place for us to build startups from scratch so we often bring in found this and work with them or maybe even have existing ideas that we match founders with and then this launches yo hopefully into successful companies so how close are you to figuring out a way to automate the process of starting from scratch and building successful AI startup yeah I think we've we've been constantly improving and iterating on our processes but how we do that so things like you know how many customer calls do we need to make and all they get customer validation how do we make sure this technology can be built well all of our businesses need cutting-edge machine learning algorithms so you know kind of Alrosa develop in the last one or two years and even if it works in a research paper it turns out taking the production it's really hard a lot of issues for making these things work in the real life didn't know why the actress in academia so how do you validate is actually doable how do you build a team get the specialize domain knowledge speed in education or healthcare or whatever staffing are focusing on so I think we're actually getting we've been getting much better at giving the entrepreneurs a high success rate but I think we're still I think the whole world is still in the early phases freaking us out but do you think there is some aspects of that process the transferable from one startup to another to another to another yeah very much so you know starting a company to most entrepreneurs is is a really lonely thing and I've seen so many entrepreneurs not know how to make a certain decision like when do you need - how do you do PDP sales right if you don't know that this is really hard or how do you market this efficiently other than you're buying ads which is really expensive other more efficient tactics that know from machine learning project you know basic decisions can change the course of whether machine learning product works or not and so there are so many hundreds of decisions that entrepreneurs need to make and making a mistake in a couple of key decisions can have a huge impact on the fate of the company so I think a starter studio provides a support structure that makes starting a company much less of a lonely experience and also um when facing with these key decisions like trying to hire your first the VP of Engineering what's a good selection criteria do you sauce should I hire this person or not but helping by having by having an ecosystem around the entrepreneurs the founders to hope I think we help them at the key moments and hopefully cyclically make them more enjoyable and in higher success rate there's somebody to brainstorm with in these very difficult decision points and also to help then recognize what they may not even realize is a key decision point right that's that's the first probably the most important part yeah you can say one other thing um you know I think the building companies is one thing but I feel like is really important that we build companies move the world forward for example Lavinia funteam does once an idea for a new company that if it had succeeded but have resulted in people watching a lot more videos in a certain narrow vertical type of video looked at it the business case was fine the revenue case was fine but a look that I just said I don't want to do this that you know I don't actually just want to have a lot more people watch this type of video wasn't educational is the educational Haiti and so and so III code the idea on the basis that didn't think it would actually help people so what the building companies or work of enterprises or doing personal projects I think it's up to each of us to figure out what's the difference we want to make in the world with learning AI you helped already established companies grow their AI and machine learning efforts how does a large company integrate machine learning into their efforts AI is a general purpose technology and I think it will transform every industry our community has already transformed the logic center software internet sector most software internet companies outside the top right five or six or three or four already have reasonable machine learning capabilities or or getting there is still room for improvement but when I look outside the software internet sector everything from manufacturing agriculture healthcare they're just X translation there's so many opportunities that very few people are working on so I think the next way for AI is first also transform all of those other industries there was a McKinsey study estimating 13 trillion dollars of global economic growth the u.s. GDP is 19 trillion dollars or thirteen trillion this is a big number or PwC it's been 16 trillion dollars so whatever number is this large but the interesting thing to me was a lot of that impact would be outside the software internet sector so we need more teams to work with these companies to help them adopt AI and I think this is one things that make you hope drive global economic growth and make humanity more powerful and like you said the impact is there so what are the best industries the biggest industries where AI can perhaps outside the software tech sector um frankly I think is all of them some of the ones I'm spending a lot of time on are manufacturing agriculture looking to healthcare for example in manufacturing we do a lot of our work in visual inspection where today there are people standing around using the AI humanoid to check it you know this plastic part or the smartphone or this thing has a stretch or gentle something in it um we can use a camera to take a picture use a algorithm deep learning and other things to check if it's defective or not and does our factories improve you then improve quality and improve throughput it turns out the practical problems we run into are very different than the ones you might read about in most research papers the data says they're really small so if a small D the problems you're the factories keep on changing the environment so it works well on your test set but guess what you know the something changes in the factory the lights go on they're off recently we there was a factory in which M burned through through the factory and pooped on something and so that you know so that changed stuff and so increasing our algorithm of making robustness so all the changes happen the factory I find that we runs a lot of practical problems that that are not as widely discussed in in academia and is really fun kind of being on the cutting edge solving these problems before you know maybe before many people are even aware that there is a problem there and that's such a fascinating space you're absolutely right but what is the first step that a company should take it's just scary leap into this new world of going from the human eye inspecting to digitizing that process having a camera having an algorithm what's the first step like what's the early journey that you recommend that you see these companies taking I published a document called the AI transformation playbook that's online and talk briefly if everyone course on Coursera about the long term journey that companies should take but the first step is actually to start small I've seen lot more companies fail by starting to bake than by starting to small um take even Google you know most people realize how hard it was and how controversial was in the early days so when it's not the Google brain um it was controversial you know people thought deep-learning Nunez tried it didn't work why would you want to do deep learning so my first internal customer rule in Google was the Google speech team which is not the most lucrative project in Google but not the most important it's not web search or advertising but by starting small on my team helped the speech team build a more accurate speech recognition system and this caused their peers other teams to start at more faith and deep learning my second internal customer was the Google Maps team where we use computer vision to read house numbers from basic Street view images the more accurately locate houses within Google Maps so improve the quality later and there's only after those two successes that I then started the most serious conversation with a Google Ads team and so there's a ripple effect that you showed that it works in these in this cases and then it just propagates through the entire company that this this thing has a lot of value and use for us I think the early small-scale projects it helps the teams gain faith but also hosts the team's learn what these technologies do I still remember when our first GPU server it was a server under some guys desk and you know and and then that taught us early important lessons about how do you have multiple users share a set of GPUs which is really non-obvious at the time but those early lessons were important we learned a lot from that first GPU server then later helped the teams think through how to scale without too much large deployments are there concrete challenges that companies face that the UC is important for them to solve I think building and deploying machine learning systems is hard there's a huge gulf between something that works and I drew the notebook on your laptop versus something runs their production deployment setting in a factory or culture plant or whatever um so I see a lot of people you know get something to work on your laptop you say wow look without done and that's that's that's great that's hot that's a very important first step but all teams underestimate the rest of the steps um so for example I've heard this exact same conversation between a lot of machine learning people and businesspeople the machine learning person says look my algorithm does well on the test set and the clean test said I didn't a peak and then machine and the business person says thank you very much but your algorithm sucks it doesn't work and the machine learning person says no wait I did well on the test set um and I think there is a gulf between what it takes to do well on a test set on your hard drive versus what it takes to work well in a deployment setting some some common problems robustus in generalization you know yuuta for something the factory maybe they chopped down a tree outside the factory so the tree no longer covers the window and the lighting is different so the first set changes and in machine learning and especially in academia we don't know how to deal with test set distributions that are dramatically different than the training set distribution this research there's stuff like domain annotation transfer learning you know that the people working on it but we're really not good at this so how do you actually get this to work because your test set distribution is going to change and I think um also if you look at the number of lines of code in a software system the machine learning model it's maybe five percent or even fewer relative to the entire software system we need to build so how to get all that work done and make it reliable and systematic a good software engineering work is fundamental here to building a successful small machine learning system yes and and and the software system needs to interface with people's work clothes so machine learning is automation on steroids if we take one task all the many tasks that done in factories so in factory does lots of things one tosses visual inspection if we automate that one task it can be really valuable but you may need to redesign a lot of other tasks around that one task for example say the machine learning algorithm says this is defective what is supposed to do is you throw the way to get a human to double check do you want to rework it or fix it so you need to redesign a lot of toss around that thing you've now automated so planning for the change management and making sure that the software he write is consistent with the new work though and you take the time to explain to people when he so happens I think what Lani AI has become good at and I think we learned by making mistakes and you know painful experiences for my ring what would become good at is working with our partners to think through all the things beyond just the machine learning model don't you put a notebook but build the entire system manage the change process and figure out how to deploy this in a way that has an actual impact the processes that the large software tech companies use for deploying don't work for a lot of other scenarios there for example when I was leading you know large speech teams um if the speech my vision system goes down what happens what allowance goes off and then someone like me will say hey you 20 engineers please fix this baby with an American but if you have a system garden in the factory there are not 20 machine learning engineers sitting around you can page the duty and have them fix it so how do you deal with the maintenance or the or the DevOps or the mo ops or the other aspects of this so these are concepts that I think landing AI and a few other teams on the cutting edge uh but we don't even have systematic terminology yet to describe some of the stuff we do because I think we're we're indenting it on the fly so you mentioned some people are interested in discovering mathematical beauty and truth in the universe and you're interested in having big positive impact in the world so let me ask the two are not inconsistent no they're all together I'm only half joking because you're probably interested a little bit in both but let me ask a romanticized question so much of the work your work and our discussion today has been on the applied AI maybe you can even call narrow AI where the goal is to create systems that automate some specific process that adds a lot of value to the world but there's another branch of AI starting with Alan Turing the kind of dreams of creating human level or superhuman level intelligence is this something you dream of as well do you think we human beings will ever build a human level they're superhuman level intelligent system I would love to get the AGI and I think humanity will but whether it takes a hundred years or 500 or 5,000 I find hard to estimate do you have some folks have worries about the different trajectories that path would take even existential threats of an AGI system do you have such concerns whether in the short term or the long term I do worry about the long term fate of humanity um I do wonder as well I do worry about overpopulation on the planet Mars just not today I think there will be a day when maybe maybe someday in the future mass will be polluted there are these children dying and some will look back at this video and say Andrew how is Anja so heartless you didn't care about all these children dying on the planet Mars and I apologize to the future viewer I do care about the children but I just don't know how to productively work on that today your picture will be in the dictionary for the people who are ignorant about the overpopulation on Mars okay yes so it's a long term problem is there something in the short term we should be thinking about in terms of aligning the values of our AI systems with the values of us humans sort of something this to Russell and other folks are thinking about as this system develops more and more we want to make sure that it represents the better angels of our nature the ethics the values of our society you know if you take so driving cars um the biggest problem with self-driving cars is not that there's some trolley dilemma and you teach this so you know how many times when you're driving your car did you face this moral dilemma as it would I food I crash into you so I think itself Giancarlo runs that problem roughly as often as we do when we drive our cars um the biggest problem Sir John calls is when there's a big white truck across the road and what you should do is break and not crash into it and the search on car fails and it crashes into it so I think we need to solve that problem for us I think the problem with some of these discussions about a gi you know alignments the paperclip problem is that is a huge distraction from the much harder problems that we actually need to address today some hard problems yesterday I think I'm bias is a huge issue um I worry about wealth inequality the AI and Internet are causing an acceleration of concentration of power because we can now centralized data use there to process it and so industry after industry we've affected every industry so the internet industry has a lot of winner-take- modes are willing to take all dynamics but if infected all these other industries so also giving these other industries when they take most I'm going to take all flavors so look at what uber and lyft into the taxi industry so we're doing this type of things along so this so creating tremendous wealth but how do we shoulder the wealth is fairly shared I think that and then how do we help people whose jobs are displace you know I think education is part of it there may be even more that we need to do then education I think bias is a serious issue there adverse users of AI and like deep fakes being used for various nefarious purposes so I worry about some teams maybe accidentally and I hope not deliberately making a lot of noise about things that problems in the distant future rather than focusing on senses much harder problems yeah the overshadow the problems that we have already today they're exceptionally challenging like those you said and even the silly ones but the ones that have a huge impact which is the lighting variation outside of your factory window that that ultimately is what makes the difference between like you said the jupiter notebook and something that actually transforms an entire industry potentially yeah and I think and then just to some companies when a regulator comes to you and says no your product is messing things up fixing it may have a revenue impact was much more fun to talk to them about how you promise not to wipe out humanity in this interface they're actually really hard problems we face so your life has been a great journey from teaching to research to entrepreneurship two questions one are there regrets moments that if you went back you would do differently and two are there moments you're especially proud of moments that made you truly happy you know I've made so many mistakes it feels like every time I discover something I go why didn't I think of this you know five years earlier or even ten years earlier and Reese's and then sometimes I read a book and I go I wish I read this book ten years ago my life we've been so different although that happened recently and then I was thinking if only I read this book when we're a start-up Coursera could have been so much better but I discovered that book had not yet been written we're starting Coursera so that means even but I find that the process of discovery we keep on finding out things that seem so obvious in hindsight but it always takes us so much longer than then I wish to figure it out so on the second question are there moments in your life that if you look back that you're especially proud of or especially happy the that fills you with happiness and fulfillment well two answers one despite all turnover yes of course you say no matter how much time I spend for I just can't spend enough time with her congratulations weather thank you and then second is helping other people I think to me I think the meaning of life is um helping others achieve whatever are their dreams and then also to try to move the world forward by making humanity more powerful as a whole so the times that I felt most happy most proud works when I felt um someone else allowed me the good fortune of helping them a little bit on the path to their dreams I think there's no better way to end it than talking about happiness and the meaning of life so enter it's a huge honor me and millions of people thank you for all the work you've done thank you for talking to thank you so much thanks thanks for listening to this conversation with Andrew Aang and thank you to our presenting sponsor cash app downloaded use coal export cast you'll get ten dollars and $10 will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoy this podcast subscribe on youtube give it five stars and Apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman and now let me leave you with some words of wisdom from NGO Aang ask yourself if what you're working on succeeds beyond your wildest dreams which you have significantly helped other people if not then keep searching for something else to work on otherwise you're not living up to your full potential thank you for listening and hope to see you next time you |
Scott Aaronson: Quantum Computing | Lex Fridman Podcast #72 | the following is a conversation with Scott Aaronson a professor UT Austin director of its quantum information center and previously a professor at MIT his research interest center around the capabilities and limits of quantum computers and computational complexity theory more generally he is an excellent writer and one of my favorite communicators of computer science in the world we only had about an hour and a half for this conversation so I decided to focus on quantum computing but I can see us talking again in the future on this podcast at some point about computational complexity theory and all the complexity classes that Scott catalogs and his amazing complexity Zoo wiki as a quick aside based on questions and comments I've received my goal with these conversations is to try to be in the background without ego and do three things one let the guest shine and try to discover together the most beautiful insights in their work and in their mind to try to play devil's advocate just enough to provide a creative tension in exploring ideas to conversation and three to ask very basic questions about terminology about concepts about ideas many of the topics we talk about in the podcast I've been studying for years as a grad student as a researcher and generally as a curious human who loves to read but frankly I see myself in these conversations as the main character for one of my favorite novels badesti husky called the idiot I enjoy playing dumb clearly it comes naturally but the basic questions don't come from my ignorance of the subject but from an instinct that the fundamentals are simple and if we linger on them from almost a naive perspective we can draw an insightful thread from computer science to neuroscience to physics the philosophy and the artificial intelligence this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter at lex friedman spelled fri d-m am as usual i'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience quick summary of the ads to supporters today first get cash app and use the code lex podcast second listen to the tech meme ride home podcast for tech news search ride home two words in your podcast app this show is presented by cash app the number one finance I up in the app store when you get it use collects podcast cash app lets you send money to friends buy bitcoin and invest in the stock market with as little as one dollar brokerage services are provided by cash up investing a subsidiary of square and member SI pc since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props to the cash app engineers for solving a heart problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier so again if you get cash app from the App Store or Google Play and use the collects podcast you'll get ten dollars and cash app will also donate ten dollars the first one of my favorite organizations that is helping to advanced robotics and STEM education for young people around the world episode is also supported by the tech meme ride home podcast it's a technology podcast I've been listening to for a while and really enjoying it goes straight to the point gives you the tech news you need to know and provides minimal but essential context it's released everyday by 5:00 p.m. Eastern and it's only about 15 to 20 minutes long for fun I like building apps on smart phones most an Android so I'm always a little curious about new flagship phones that come out I saw that Samsung announced the new Galaxy S 20 and of course right away Technium right home has a new episode that summarizes all that I needed to know about this new device they've also started to do weekend bonus episodes with interviews of people like a well founder Steve Case an investing and Gary Marcus on AI who I've also interviewed on this podcast you can find the Technium ride home podcast if you search your podcast app for ride home two words then subscribe enjoy and keep up to date with the latest tech news and now here's my conversation with Scott Aaronson sometimes get criticism from a listener here and there that while having a conversation with a world-class mathematician physicist neurobiologist aerospace engineer or the theoretical computer scientists like yourself I waste time by asking philosophical questions about freewill consciousness mortality love nature of truth super intelligence weather time travel as possible weather space-time as emergent fundamental even the crazy questions like whether aliens exist what their language might look like what their math might look like whether Malthus inventors discovered and of course whether we live in a simulation or not so I try with it out with it I try to dance back and forth from the deep technical to the philosophical so I've done that quite a bit so you're a world-class computer scientist and yet you've written about this very point the philosophy is important for experts in any technical discipline though they somehow seem to avoid this so I thought it'd be really interesting to talk to you about this point why should we computer scientists mathematicians physicists care about philosophy do you think well I would reframe the question a little bit I mean philosophy almost by definition is the subject that's concerned with the biggest questions that you could possibly ask all right so you know the ones you mentioned right are are we living in a simulation you know are we alone in the universe how should we even think about such questions you know is the future determined and what you know what do we even mean by being determined why are we alive at the time we are and not at some other time you know and and and you know when you when you sort of contemplate the enormity of those questions I think you know you could ask well then why why be concerned with anything else all right why why not spend your whole life on those questions you know I think I think in some sense that is the the right way to phrase the question and you know and and and actually you know what what we learned you know I mean throughout history but really starting with the Scientific Revolution we've got you know Galileo and so on is that there is a good reason to you know focus on narrower questions you know more technical you know mathematical or empirical questions and that is that you can actually make progress on them right and you can actually often answer them and sometimes they actually tell you something about the philosophical questions that sort of you know may be motivated your curiosity as a child right you know they don't necessarily resolve the philosophical questions but sometimes they reframe your whole understanding of them right and so for me philosophy is just the thing that you have in the background from the very beginning that you want to you know the you know these are these are sort of the reasons why you went into intellectual life in the first place at least the reasons why I did right but you know math and science are tools that we have for you know actually making progress and you know hopefully even you know changing our understanding of these philosophical questions sometimes even more than philosophy itself does what do you think computer scientists avoid these questions will run away from them a little bit at least in technical scientific discourse well I'm not I'm not sure if they do so more than any other scientists though I mean I mean I mean I mean I mean Alan Turing was famously you know interested and you know is his most famous one of his two most famous papers was in a philosophy journal mind you know it was the one where he proposed the Doering test he took a Vidkun Stein's course at Cambridge you know argued with him I just recently learned that a little bit and it's actually fascinating I I was I was trying to look for resources in trying to understand where the sources of disagreement and debates between Wittgenstein and touring war that's an interesting that these two minds have somehow met in the arc of history yeah well the transcript you know of their the course which was in 1939 right is one of the more fascinating documents that I've ever read because you know a vit concern is trying to say well all of these these four systems are just a complete irrelevance is right if a formal system is irrelevant who cares you know why does that matter in real life right and touring is saying well look you know if you use an inconsistent formal system to design a bridge you know the bridge may collapse right and you know soso touring in some sense is thinking decades ahead you know I think of where Vidkun Stein is the way with formal systems are actually going to be used you know in computers right to actually do things in the world you know and it's interesting that touring actually dropped the course halfway through why because he had to go to Bletchley Park and you know work on something of more immediate importance that's fascinating if you take a step from philosophy to actual like the biggest possible step to actual engineering the actual real impact yeah and I would say more generally right uh you know a lot of scientists are you know interested in philosophy but they're also busy right and they have you know a lot on their plate and there are a lot of sort of very concrete questions that are already you know not answered but you know look like they might be answerable right and so then you could say well then why you know break your brain over these you know metaphysically unanswerable questions when there were all these answerable ones instead so I think you know for me I I enjoy talking about philosophy I even go to philosophy conferences sometimes such as the you know fqx I conferences I enjoy interacting with philosophers I would not want to be a professional philosopher because I like being in a field where I feel like you know uh you know if I get too confused about the sort of eternal questions then I can actually make progress on something can you maybe a link on that for just a little longer yeah what do you think is the difference so like the corollary of the criticism that I mentioned previously that why ask the philosophical questions of the mathematician is if you want to ask for softball questions then invite a real philosopher on and ask that so what's the difference between the way a computer scientist and mathematician Ponder's a philosophical question and a philosopher Ponder's the falafels question well I mean I mean a lot of it just depends on the individual all right it's hard to make generalizations about entire fields but you know I think I think if we if we if we tried to we tried to stereotype you know we would say that uh you know as scientists very often will be less careful in their use of words you know I mean philosophers are really experts in sort of you know like when it when it when I talk to them and they will just pounce if you know use the wrong phrase for something versus a very nice word you could say cyclers yeah yeah where or you know they will they will sort of interrogate my word choices let's say to a much greater extent than scientists would write and and scientists you know will often if you ask them about a philosophical problem like the hard problem in in of consciousness or free will or whatever they will try to relate it back to you know recent research right you know research about about neurobiology or you know but you know the best of all was research that they personally are involved with right right and you know and and and and you know of course they will want to talk about that you know and it is what they will think of you know and then of course you could have an argument that maybe you know it's all interesting as it goes but maybe none of it touches the philosophical question right but you know but maybe you know as a science you know at least it it as I said it does tell us concrete things and you know even if like a deep dive into neurobiology will not answer the hard problem of consciousness you know maybe it can take us about as far as we can get toward you know expanding our minds about it you know toward thinking about it in a different way well I mean I think neurobiology can do that but you know with these profound philosophical questions I mean also art and literature do that right they're all different ways of trying to approach these questions that you know we don't for which we don't even know really but an answer would look like but and yet somehow we can't help but keep returning to the questions and you have a kind of mathematical beautiful mathematical way of discussing this with the idea of Q Prime oh you're right they usually the only way to make progress on the big questions like the full of the philosophical questions we're talking about now is to pick off smaller sub questions ideally sub questions you can attack using math empirical observation or both you define the idea of a Q Prime so given an unanswerable philosophical riddle q replace it with a mirror leak in quotes scientific or mathematical question q prime which captures part of what people have wanted to know when they first asked q yes then with luck once all q prime so you described some examples of such Q prime sub questions in your long essay titled white philosophers should care about computational complexity so you catalog the various Q Prime's on which you think of theoretical computer science has made progress can you mention a few favorites if any pop any pup to mind or boy yes so I mean I would say some of the most famous examples in history of that sort of replacement well you know I mean I mean to go back to Alan Turing right what he did in his Computing Machinery and intelligence paper was exactly you know he explicitly started with the question can machines think and then he said uh sorry I think that question is too meaningless but here's a different question you know could you program a computer so that you couldn't tell the difference between it and a human right and you know yeah in the very first few sentences he in fact just yeah I miss the Q prime precise he does precisely that or you know we could look at at girdle right where you know you had these philosophers arguing for centuries about the limits of mathematical reasoning right in the limits of formal systems and you know then by the early 20th century logicians you know starting with you know frag a rustle and then you know most spectacularly girdle you know manage to reframe those questions as look we have these formal systems they have these definite rules are there questions that we can phrase within the rules of these systems that are not provable within the rules of the systems and can we prove that fact right and so that would be another example you know III had this essay called the ghost in the quantum Turing machine it's you know one of the crazier things I've written but I I tried to do something or you know to to advocate doing something similar there for free will where you know instead of talking about is free will you know real where we get hung up on the meaning of you know what exactly do we mean by freedom and can you have can you be you know or do we mean compatibilist free will libertarian free will what are these things mean you know I suggested just asking the question how well in principle consistently with the laws of physics could a person's behavior be predicted you know without so let's say destroying the person's brain you know taking it apart in the process of trying to predict them and you know and that actually asking that question gets you into all sorts of meaty and interesting issues you know issues of what is the computational substrate of the brain you know or can you understand the brain you know just at the sort of level of the neurons you know it sort of the abstraction of a neural network or do you need to go deeper to the you know molecular level ultimately even to the quantum level right and of course that would put limits on predictability if you did so you need to reduce you need to reduce the mind to a computational device like formalize it so then you can make predictions about what you know whether you could predict a B if you were trying to predict a person yeah then presumably you would need some model of their brain all right and now the question becomes one of how accurate can such a model become can you make a model that will be accurate enough to really seriously threaten people's sense of free will you know not just metaphysically but like really I've written in this envelope what you were going to say next is you see the right term here so it's also a level of abstraction has to be right so if your yeah if you're accurate at the somehow at the quantum level hmm that may not be convincing to us at the human level well right but the question is what accuracy at the sort of level of the underlying mechanisms do you need in order to predict the behavior right at the end of the day the test is just can you you know foresee what the person is going to do right I am you know and and and and you know and and and and in discussions of freewill you know it seems like both sides want to you know very quickly dismiss that question is irrelevant well to me it's totally relevant okay because you know if someone says oh well you know I will applause demon that knew the complete state of the universe you know could predict everything you're going to do therefore you don't have free will you know that it doesn't trouble me that much because well you know I've never met such a demon hey you know uh you know and we you know we even have some reasons the thing you know maybe it you know it could not exist this part of our world you know it was only an abstraction a thought experiment on the other hand if someone said well you know I have this brain scanning machine you know you step into it and then you know every paper that you will ever write it will write you know every thought that you will have you know even right now about the machine itself it will force a you know a well if you can actually demonstrate that then I think you know that that you know that that sort of threatens my internal sense of having free will in a much more visceral way you know but now you notice that we're asking in a much more empirical question we're asking is such a machine possible or isn't it I mean if it's not possible then what in the woes of physics or what about the behavior of the brain you know prevents it from existing so if you could philosophize a little bit within this empirical question at where do you think would enter the the by which mechanism would enter the possibility that we can't predict the outcome so there would be something they'll be akin to a free will yeah well you could say the the sort of obvious possibility which was you know kick knives by Addington and many others about as soon as quantum mechanics was discovered in the 1920s was that if you know let's say a sodium ion channel you know in the in the in in in the brain right hey today you know it's its behavior is chaotic right it sort of it's governed by these hodja hodja ly hot skin equations in neuroscience right which are differential equations that have a stochastic component right now where does you know and this ultimately governs let's say whether a neuron will fire or not that's a basic chemical process or electrical process by which signals are sent in the brain exactly exactly and and you know and so you could ask well well where does the randomness in the process you know that that neuroscientists you're but what neuroscientists would would treat is randomness where does it come from you know ultimately it's thermal noise right where does thermal noise come from but ultimately you know there were some quantum mechanical events at the molecular level that are getting sort of chaotically amplified but you know a sort of butterfly effect and so you know even if you knew the complete quantum state of someone's brain you know at best you could predict the probabilities that they would do one thing or do another thing right I think that part is actually relatively uncontroversial right the the controversial question is whether any of it matters for the sort of philosophical questions that we care about because you could say if all it's doing is just injecting some randomness into an otherwise completely mechanistic process well then who cares right and more concretely if you could build a machine that you know could just calculate the even just up the probabilities of all of the possible things that you would do all right and you know um you know if all the things that said you had a 10% chance of doing you did exactly a tenth of them you know and and and and and and so on that somehow also takes away the feeling of freedom exactly I mean I mean to me it seems essentially just as bad as if the Machine deterministically predicted you it seems you know hardly different from that so that so then but a more a more subtle question is could you even learn enough about someone's brain to do that okay because you know another central fact about quantum mechanics is that making a measurement on a quantum state is an inherently destructive operation okay so you know if I want to measure the you know position of a particle right it was well before I measure it it had a superposition over many different positions as soon as I measure I localized it right so now I know the position but I've also fundamentally changed the state and so so you could say well maybe in trying to build a model of someone's brain that was accurate enough to actually you know make let's say even even well calibrated probabilistic predictions of their future behavior maybe you would have to make measurements that we're just so accurate that you were just fundamentally alter their brain okay or or or or maybe not maybe you only you know you it would suffice to just make some nano robots that just measured some sort of much larger scale you know macroscopic behavior like you know is that you know what is this neuron doing what is that neuron doing maybe that would be enough see but now you know III but what I claim is that we're now asking a question you know in which you know it is it is it is possible to envision what progress on it would look like yeah but just as you said that question may be slightly detached from the philosophical question in the sense if consciousness somehow has a role to the experience of free will because ultimately what we're talking about free will we're also talking about not just the predictability of our actions but somehow the experience of them predictability yeah well I mean a lot of philosophical questions ultimately like feed back to the hard problem of consciousness you know and as much as you can try to sort of talk around it or not right and you know and then and and there is a reason why people try to talk around it which is that you know Democritus talked about the hard problem of consciousness you know in 400 BC in terms that would be totally recognizable to us today right and it's really not clear if there's been progress since or what progress could possibly consist of is there a Q prime type of sub question that could help us get it consciousness it's something about cars oh well I mean well I mean there is the whole question of you know of AI right of you know can you build a human level or superhuman level AI and you know can it can it work in a completely different substrate from the brain I mean there's you know of course that was Alan Turing's point and you know and and and even if that was done it's you know maybe people would still argue about the hard problem of consciousness right and yet you know my claim is a little different my claim is that in a world where you know there were you know human-level AI is where we had been even overtaken by such a eyes the entire discussion of the hard problem of consciousness would have a different character right it would take place in different terms in such a world even if we hadn't answered the question and and my claim about free will would be similar right that if there if this prediction machine that I was talking about could actually be built well now the entire discussion of the you know a free will is sort of transformed by that you know even if in some sense the the metaphysical question hasn't been answered yeah exactly transforms it fundamentally because say that machine does tell you that it can predict perfectly and yet there is this deep experience of free will and then that changes the question completely yeah and it starts actually getting to the question of the a the a GI the touring questions if the demonstration of free will the demonstration of intelligence the demonstration of consciousness does that equal nauseousness intelligence and free will but see elects if every time I was contemplating a decision you know this machine had printed out an envelope you know where I could open it and see that it knew my decision I think that actually would change my subjective experience of making decisions you might mean doesn't knowledge change your subjective experience well well you know I mean I mean the knowledge that this machine had pretty did everything I would do I mean it might drive me completely insane right but at any rate it would change my experience to act you know to not just discuss such a machine as a thought experiment but to actually see it yeah I mean I mean you know you could say at that point you know you could say you know what why not simply call this machine a second instantiation of me and be done with it right what we know what why even privilege the original me over this perfect duplicate that that exists in the machine yeah or yeah there could be a religious experience with a Jew it's kind of what God throughout the generations is supposed to that God kind of represents that perfect machine is able to I guess actually well I I don't even know what a work what are the religious interpretations of freewill yeah does so if God knows perfectly everything in in religion in the various religions were does freewill fit into that do you know that has been one of the big things that theologians have argued about for thousands of years you know I am I am NOT a theologian maybe I shouldn't go there there's not a clear answer in a book like I mean I mean this is you know the Calvinists debated this the you know this has been you know I mean different religious movements have taken different positions on that question but that is how they think about it you know meanwhile you know a large part of sort of what what animates you know theoretical computer science you could say is you know we're asking sort of what are the ultimate limits of you know what you can know or you know calculate or figure out by you know entities that you can actually build in the physical world right and if I were trying to explain it to a theologian maybe I would say you know we are studying you know to what extent you know gods can be made manifest in the physical world I'm not sure my colleagues would like that so let's talk about quantum computers yeah sure sure as you said modern computing at least in the 1990s was a profound story at the intersection of computer science physics engineering math and philosophy so the there's this broad and deep aspect to quantum computing that represents more than just the quantum computer yes but can we start at the very basics what is quantum computing yeah so it's a proposal for a new type of computation I would say a new way to harness nature to do computation that is based on the principles of quantum mechanics okay now the principles of quantum mechanics have been in place since 1926 you know they haven't changed you know what's new is you know how we want to use them okay so what does quantum mechanics say about the world you know the the physicists I think over the generations you know convinced people that that is an unbelievably complicated question and you know just give up on trying to understand it I can let you in not not being a physicist I can let you in on a secret which is that it becomes a lot simpler if you do what we do in quantum information theory and sort of take the physics out of it so the way that we think about quantum mechanics is sort of as a generalization of the rules of probability themselves so you know you might say there's a you know there was a 30% chance that it was going to snow today or something you would never say that there was a negative 30% chance right that would be nonsense much less would you say that there was a you know an I percent chance you know square root of minus 1% chance now the central discovery that sort of quantum mechanics made is that fundamentally the world is described by you know these are let's say the possibilities for you know what a system could be doing are described using numbers called amplitudes okay which are like probabilities in some ways but they are not probabilities they can be positive for one thing they can be positive or negative in fact they can even be complex numbers okay and if you've heard of a quantum superposition this just means the sum state of affairs where you assign an amplitude one of these complex numbers to every possible configuration that you could see assist them in on measuring it so for example you might say that an electron has some amplitude for being here and some other amplitude for being there right now if you look to see where it is you will localize it right you will sort of force the amplitudes to could be converted into probabilities that happens by taking their squared absolute value okay and then and and then you know you can say either the electron will be here or it will be there and you know knowing the amplitudes you can predict the price the probabilities that it will that you'll see each possible outcome okay but while a system is isolated from the whole rest of the universe the rest of its environment the amplitudes can change in time by rules that are different from the the normal rules of probability and that are you know alien to our everyday experience so any time anyone ever tells you anything about the weirdness of the quantum world you know or assuming that they're not lying to you right they are telling you you know and yet another consequence of nature being described by these amplitudes so most famously what amplitudes can do is that they can interfere with each other okay so in the famous double slit experiment what happens is that you shoot a particle like an electron let's say at a screen with two slits in it and you find that there you know on a second screen now there are certain places where that electron will never end up you know after it passes through the first screen and yet if I close off one of the slits then the electron can appear in that place okay so by so by decreasing the number of paths that the electron could take to get somewhere you can increase the chance that it gets there okay now how is that possible well it's because we you know as we would say now the electron has a superposition state okay it has some amplitude for reaching this point by going through the first slit it has some other amplitude for reaching it by going through the second slit but now if one amplitude is positive and the other one is negative then note you know I have to add them all up right I have to add the amplitudes for every path that the electron could have taken to reach this point and those amplitudes if they're pointing in different directions they can cancel each other out that would mean the total amplitude is zero and the thing never happens at all I closed off one of the possibilities then the amplitude is positive or it's negative and now the thing can happen okay so that is sort of the one trick of quantum mechanics and now I can tell you what a quantum computer is okay a quantum computer is a computer that tries to exploit you know these exactly these phenomena superposition amplitudes and interference in order to solve certain problems much faster than we know how to solve them otherwise so is the basic building block of a quantum computer is what we call a quantum bit or a qubit that just means a bit that has some amplitude for being zero and some other amplitude for being what so it's a superposition of zero in one states right but now the key point is that if I've got let's say a thousand cubits the rules of quantum mechanics are completely unequivocal that I do not just need one amp but you know I don't just need amplitudes for each qubit separately okay in general I need an amplitude for every possible setting of all thousand of those bits okay so that what that means is two to the 1000 power amplitudes okay if I if I had to write those down let's or let's say in the memory of a conventional computer if I had to write down two to the 1000 complex numbers that would not fit within the entire observable universe okay and yet you know quantum mechanics is unequivocal that if these qubits can all interact with each other and in some sense I need to to the 1000 parameters you know amplitudes to describe what is going on now you know now I can do you know where all the popular articles you know about quantum computer and go off the rails is that they say you know they they sort of sort of say what I just said and then they say oh so the way a quantum computer works is just by trying every possible answer in parallel okay you know you know that that sounds too good to be true and unfortunately it kind of is too good to be true that the problem is I could make a superposition over every possible answer to my problem you know even if there were two to the one thousand of them right I can I can easily do that the trouble is for a computer to be useful you've got at some point you've got to look at it and see and see an output right and if I just measure a superposition over every possible answer then the rules of quantum mechanics tell me that all I'll see will be a random answer you know if I just wanted a random answer well I could have picked one myself with a lot less trouble right so the entire trick with quantum computing with every algorithm for a quantum computer is that you try to choreograph a pattern of interference of amplitudes and you try to do it so that for each wrong answer some of the paths leading to that wrong answer have positive amplitudes and others have negative amplitudes so on the whole they cancel each other out okay whereas all the paths leading to the right answer should reinforce each other you know should have amplitudes pointing the same direction so the design of algorithms in the space is the choreography of the interferences precisely that's precisely what it was take a brief step back and write you mentioned information yes so in which part of this beautiful picture that you've painted is information contained oh well information is that the core of everything that we've been talking about right I mean the bit is you know the basic unit of information since you know Claude Shannon's paper in 1948 you know and you know of course you know people had the concept even before that you know he popularized the name right but I mean but a bit at zero or one that's right basically that's right and what we would say is that the basic unit of quantum information is the qubit is you know the object any object that can be maintained tennis manipulated in a superposition of 0 and 1 States now you know sometimes people ask well but but but what is a qubit physically and there are all these different you know proposals that are being pursued in parallel for how you implement qubits there is you know superconducting quantum computing that was in the news recently because of Google's the quantum supremacy experiment right where you would have some little coils where a current can flow through them in two different energy states one representing a 0 another representing the 1 and if you cool these coils to just slightly above absolute zero like a hundredth of a degree then they super conduct and then the current can actually be in a superposition of the two different states so that's one kind of qubit another kind would be you know just in an individual atomic nucleus it has a spin it could be spinning clockwise it could be spinning counterclockwise or it could be in a superposition of the two spin States that is another qubit but she's just like in the classical world right you could be a virtuoso programmer without having any idea of what a transistor is right or how the bits are physically represented inside the machine even that the machine uses electricity right you just care about the logic it's sort of the same with quantum computing right qubits could be realized by many many different quantum systems yet all of those systems will lead to the same logic you know the logic of qubits and and how you know how you measure them how you change them over time and so you know that the subject of you know how qubits behave and what you can do with qubits that is quantum information so just a linger on that short so does the physical design implementation of a qubit mm-hmm does not does not interfere with the that next level of abstraction that you can program over it so the true is the idea of it is is the a is it okay well to be honest with you today they do interfere with each other that's because the all the quantum computers we can build today are very noisy right and so sort of the the the you know the qubits are very far from perfect and so the lower level sort of affect the higher levels and we sort of have to think about all of them at once okay but eventually where we hope to get is to what are called error corrected quantum computers where the qubits really do behave like perfect abstract qubits for as long as we want them to and in that future you know the you know which you know a future that we can already Street or sort of prove theorems about or think about today but in that future the the logic of it really does become decoupled from the hardware so if noise is currently like the biggest problem for quantum computing and then the dream is error correcting modern computers can you just maybe describe what does it mean for there to be noise in the system absolutely so yeah so the problem is even a little more specific than noise so that the fundamental problem if you're trying to actually build a quantum computer you know of any appreciable size is something called decoherence okay and this was recognized from the very beginning you know when people first started thinking about this in the 1990s now what decoherence means is sort of unwanted interaction between you know your qubits you know the state of your quantum computer and the external environment okay and why is that such a problem why I said talked before about how you know when you measure a quantum system so let's say if I measure a qubit that's in a superposition of 0 and 1 States to ask it you know are you zero or are you one well now I force it to make up its mind right and now probabilistically it chooses one or the other and now you know it's no longer a superposition there's no longer amplitudes there's just there's some probability that I get a zero and there's some that I get a one and now the the the the the trouble is that it doesn't have to be me who's looking guy or in fact it doesn't have to be any conscious entity any kind of interaction with the external world that leaks out the information about whether this qubit was a 0 or a 1 sort of that causes the zero Ness or the oneness of the qubit to be recorded you know the radiation in the room in the molecules of the air in the wires that are connected to my device any of that as soon as the information leaks out it is as if that qubit has been measured okay it is you know the the the state has now collapsed you know another way to say it is that it's become entangled with its environment okay but you know from the perspective of someone who's just looking at this qubit it is as though it has lost its quantum state and so what this means is that if I want to do a quantum computation I have to keep the qubits sort of fanatically well isolated from their environment but then at the same time they can't be perfectly isolated because I need to tell them what to do I need to make them interact with each other for one thing and not only that but in a precisely choreographed way okay and you know that is such a staggering problem right how do i isolate these qubits from the whole universe but then also tell them exactly what to do I mean you know there were distinguished physicists and computer scientists in the 90s who said this is fundamentally impossible you know the laws of physics will just never let you control qubits to the degree of accuracy that you're talking about now what changed the views of most of us was a profound discovery in the mid to late 90s which was called the theory of quantum error correction and quantum fault tolerance okay and the upshot of that theory is that if I want to build a reliable quantum computer and scale it up to you know an arbitrary number of as many qubits as I want you know and doing as much on them as I want I do not actually have to get the cube it's perfectly isolated from their environment it is enough to get them really really really well isolated okay and even if every qubit is sort of leaking you know it state into the environment at some rate as long as that rate is low enough okay I can sort of encode the information that I care about in very clever ways across the collective states of multiple qubits okay in such a way that even if you know a small percentage of my cube it's leaked well I'm constantly monitoring them to see if that week happened I can detect it and I can correct it I can recover the information I care about from the remaining qubits okay and so you know you can build a reliable quantum computer even out of unreliable parts right now the the in some sense you know that discovery is what set the engineering agenda for quantum computing research from the 1990s until the present okay the goal has been you know engineer qubits that are not perfectly reliable but reliable enough that you can then use these error correcting codes to have them simulate qubits that are even more reliable than they are regarded the error correction becomes a net win rather than a net loss right and then once you reach that sort of crossover point then you know your simulated qubits could in turn simulate qubits that are even more reliable and so on until you've just you know effectively you have arbitrarily reliable cubans so long story short we are not at that break-even point yet we're a hell of a lot closer than we were when people started doing this in the 90s like orders of magnitude closer but the key ingredient there is the more qubits the butter because well the more qubits the larger the computation you can do right I mean I mean a qubit Tsar what constitute the memory of your quantum computer it also for the sorry for the error correcting mechanism yes so so so the way I would say it is that error correction imposes an overhead in the number of qubits and that it is actually one of the biggest practical problems with building a scalable quantum computer if you look at the error correcting codes at least the ones that we know about today and you look at you know what would it take to actually use a quantum computer to you know a I'm hack your credit card number because you know you know maybe you know the most famous application people talk about right let's say to factor huge numbers and thereby break the RSA cryptosystem well what what that would take would be thousands of several thousand logical cube but now with the known error correcting codes each of those logical qubits would need to be encoded itself using thousands of physical qubits so at that point you're talking about millions of physical qubits and in some sense that is the reason why quantum computers are not breaking cryptography already it's because of this these immense overheads involved so that overhead is additive or multiplicative I mean it's like you take the number of logical qubits that you need in your abstract quantum circuit you multiply it by a thousand or so so you know there's a lot of work on you know inventing better trying to invent better error correcting codes okay that is the situation right now in the meantime we are now in what physicist John Prescott called the noisy intermediate scale quantum or NIST era and this is the era you can think of it as sort of like the vacuum you know we're now entering the very early vacuum tube era of quantum computers the quantum computer analog of the transistor has not been invented yet right that would be like true error correction right where you know we are not or or something else that would achieve the same effect right we are not there yet and but but but where we are now let's say as of a few months ago you know as of Google's announcement of quantum supremacy you know we are now finally at the point where even with a non error corrected quantum computer with you know these noisy devices we can do something that is hard for classical computers to simulate okay so we can eke out some advantage now will we in this noisy era be able to do something beyond what a classical computer can do that is also useful to someone that we still don't know people are going to be racing over the next decade to try to do that by people I mean Google IBM you know a bunch of startup companies or you know a player's apps yeah and in research labs and governments and yeah you just mentioned a million things well backtrack for a sec yeah sure sure so we're in these vacuum tube days yeah just entering and I'm just entering Wow okay so yeah how do we escape the vacuum so we get to how to get to where we are now with the cpu is this a fundamental engineering challenge is there is there breakthroughs in on the physics side they're needed on the computer science side what Oh is there an is it a financial issue we're a much larger just sheer investment and excitement is new so you know those are excellent questions oh my god well no no my my my guess would be all of the above yeah I mean my my guess you know I mean I mean you know you could say fundamentally it is an engineering issue right the theory has been in place since the 90s you know at least you know you know this is what you know error correction what you know would look like you know we we do not have the hardware that is at that level but at the same time you know so you could just you know try to power through you know maybe even like you know if someone spent a trillion dollars on some quantum computing Manhattan Project right then conceivably they could just you know build a an error corrected quantum computer as it was envisioned back in the 90s right I think the more plausible thing to happen is that there will be further theoretical breakthroughs and there will be further insights that will cut down the cost of doing this so let's take good briefs yeah to the faux soft goal I just recently talked to Jim Keller who's a sort of like the famed architect and then in the microprocessor world okay and he's been told for decades every year that the Moore's law is going going to die this year and he tried tries to argue that the the Moore's law is still alive and well and it'll be alive for quite a long time to come how long how long he's is the the main point is it still alive but he thinks there's still a thousand X improvement just on shrinking a transition as possible whatever the point is that the exponential growth you see it is actually a huge number of these s curves just constant breakthroughs at the philosophical level mm-hmm why do you think we as a descendants of apes were able to to just keep coming up with these new breakthroughs on the CPU side is this something unique to this particular endeavor or will it be possible to replicate in the quantum computer space okay all right the other there was a lot there too but didn't it to to break off something I mean I think we are in an extremely special period of human history right I mean it's it is you could say obviously special you know in many ways right there you know you know way more people alive than there than there than there have been and you know the you know the whole you know future of the planet is in is in is in question in a way that it it hasn't been you know through for the rest of human history but but you know in particular you know we are in the era where you know we we finally figured out how to build you know Universal machines it's that you know the things that we call computers you know machines that you program to simulate the behavior of whatever machine you want and you know and and and and and and and and and once you've sort of crossed this threshold of universality you know you've built you could say you know touring you've instantiated touring machines in the physical world well then the main questions are ones of numbers there you know ones of how many of how much memory can you access how fast does it run how many parallel processors you know at least until quantum computing quantum computing is the one thing that changes what I just said right you know in fear as well as well as long as it's classical computing then it's all questions of numbers and you know the you could say at a theoretical have all the computers that we have today are the same as the ones in the 50s they're just millions of times you know faster and with millions of times more memory and you know I mean I think there's been an immense economic pressure to you know get more and more transistors you know get them smaller and smaller get you add more and more cores and you know and and and and in in in some sense like a huge fraction of sort of all of the technological progress that there is in all of civilization has gotten concentrated just more narrowly into just those problems right and so you know it has been one of the biggest success stories in the history of technology right there's you know I mean it is I am as amazed by it as anyone elses right but at the same time you know we also know that it you know and I I really do mean we know that it cannot continue indefinitely okay because you will reach you know fundamental limits on you know how small you can possibly make a processor and you know if you want a real proof you know that would justify my use of the word you know we know that you know Moore's law has to end I mean ultimately you will reach the limits imposed by quantum gravity you know you know if you were doing if you tried to build a computer that operated at 10 to the 43 Hertz so did 10 to the 43 operations per second that computer would use so much energy that it would simply collapse to a black hole okay so you know that you know we you know in reality we're going to reach the limits long before that but you know that is a sufficient proof that there's a limit yes yes but it would be interesting to try to understand the mechanism the economic pressure these said just like the Cold War was a pressure on getting us getting us cuz I'm both my us is both the Soviet Union and the United States yeah getting us the two countries to get to hurry up to get the space to the moon there seems to be that same kind of economic pressure that somehow created a chain of engineering breakthroughs there resulted in the Moore's law yeah what'd be nice to replicate yeah well I mean I mean some people are sort of get depressed about the fact that technological progress you know may seem to have slowed down in in many many realms outside of computing right there was this whole thing of you know we wanted flying cars and we only got Twitter instead right and yeah go Peter - yeah yeah yeah right right so when then jumping to another really interesting topic the invention so Google mmm announced with their work in the paper in nature with quantum supremacy yes can you describe again back to the basic what is perhaps not so basic what is quantum supremacy absolutely so quantum supremacy is a term that was coined by again by John Prescott in 2012 not not everyone likes the name you know but uh you know it's sort of stuck you know we don't and we sort of haven't found a better alternative wantem computational compromise dude that's right that's right and but but the basic idea is actually one that goes all the way back to the beginnings of quantum computing when richard fineman and david deutsch people like that we're talking about it in the early 80s and-and-and and quantum supremacy just refers to sort of the point in history when you can first use a quantum computer to do some well-defined task much faster than any known algorithm running on any of the classical computers that are available okay so you know notice that I did not say a useful task okay you know it could be something completely artificial but it's important that the task be well-defined so in other words you know there is it is something that has right and wrong answers you know and that are knowable independently of this device right and we can then you know run the device see if it gets the right answer or not can you clarify a small point you said much faster than a classical implementation what about sort of what about the space with where the class there's no there's not it doesn't even exist a classical algorithm so so so so maybe I should clarify everything that a quantum computer can do a classical computer can also eventually do okay and the reason why we know that is that a a classical computer could always you know if it had no limits of time and memory it could always just store the entire quantum state you know of your you know of the quantum store in a list of all the amplitudes you know in the state of the quantum computer and then just you know do some linear algebra to just update that state right and so so anything that quantum computers can do can also be done by classical computers albeit exponentially slower okay so on and computers don't go into some magical place outside of Alan Turing's a definition of computation precisely they do not solve the halting problem they cannot solve anything that is uncomputable in Alan Turing sense what they what we think they do change is what is efficiently computable okay and you know since the 1960s you know the word efficiently you know as well as been a central word in computer science but it's sort of a code word for something technical which is basically with polynomial scaling you know that as you get to larger and larger inputs you would like an algorithm that uses an amount of time that scales only like the size of the input raised to some power and not exponentially with the size of the input right yeah so I I do hope we get to talk again because one of the many topics that there's probably several hours with a competent conversation on is complexity which probably won't even get a chance to touch today but you briefly mentioned it but let's let's maybe try to continue so you said the definition of quano supremacy is basically design is achieving a place where much faster on a formal that quantum computer is much faster on a formal well-defined problem yes it's not that is or isn't useful yeah yeah yeah right right and and I would say that we really want three things right we want first of all the quantum computer to be much faster just in the literal sense so like number of seconds you know it's a solving this you know well-defined you know problem secondly we want it to be sort of a you know for a problem where we really believe a quantum computer has better scaling behavior right so it's not just an incidental you know matter of hardware but it's that you know as you went to larger and larger inputs you know the classical scaling would be exponential and the scaling for the quantum algorithm would only be polynomial and then thirdly we want the first thing the actual observed speed-up to only be explainable in terms of the scaling behavior right so you know I want I want you know a real world you know a real problem to get solved let's say by a quantum computer with 50 cubits or so and for no one to be able to explain that in any way other than well you know the to the this this computer involved a quantum state with 2 to the 50th power amplitudes and you have a classical simulation in at least any that we know today would require keeping track of 2 to the 50th numbers and this is the reason why it was faster so the intuition is that then if you demonstrate on 50 cubits then once you get to 100 cubits then it'll be even much more faster precisely precisely yeah and and you know and and and quantum supremacy does not require error correction right we don't you know we don't have you could say true scalability yet or true you know uh error correction yet but you could say quantum supremacy is already enough by itself to refute the skeptics who said a quantum computer will never outperform a classical computer for anything but one demonstrate quantum yeah supremacy and two what's up with these new news articles I'm reading that Google did so yeah what they actually do great great questions because now you get into actually you know a lot of the work that I've you know I and my students have been doing for the last decade which was precisely about how do you demonstrate quantum supremacy using technologies that you know we thought would be available in the near future and so one of the main things that we realized around 2011 and this was me and my Alyx arkhipov at MIT at the time and independently of some others including a Bremner joseon shepard okay and the realization that we came to was that if you just want to prove that a quantum computer is faster you know and not do something useful with it then there are huge advantages to sort of switching your attention from problems like factoring numbers that have a single right answer to what we call sampling problems so these are problems where the goal is just to output a sample from some probability distribution let's say over strings of 50 bits right so there are you know many many many possible valid outputs you know your computer will probably never even produce the same output twice you know if it's running as even you know assuming it's running perfectly okay but but the key is that some outputs are supposed to be like clearer than other ones so sorry to clarify is there a set of outputs that are valid and said they're not or is it more that the distribution of a particular kind of output is more is the specific distribution yeah particular there's there's there's a specific distribution that you're trying to hit right or you know that you're trying to sample from now there are a lot of questions about this you know how do you do that right now now how you how you do it you know it turns out that with a quantum computer even with the noisy quantum computers that we have now that we have today what you can do is basically just apply a randomly chosen sequence of operations all right so we you know we in sometimes you know we you know that part is almost trivial right we just sort of get the qubits to interact in some random way although a sort of precisely specified random way so we can repeat the exact same random sequence of interactions again and get another sample from that same distribution and what this does is it basically well it creates a lot of garbage but you know very specific garbage right so you know of all of the so if we're gonna talk about Google's device there were 53 qubits there okay and so there are two to the 53 power possible outputs now for some of those outputs you know there are there was a little bit more destructive interference in their amplitude okay so their amplitudes were a little bit smaller and for others there was a little more constructive interference you know the amplitudes were a little bit more aligned with each other you know that and so those those that were a little bit likelier okay all of the outputs are exponentially unlikely but some are let's say two times or three times you know unlikely er than others okay and so so you can define you know the sequence of operations that gives rise to this probability distribution okay now the next question would be well how do you you know even if you're sampling from and how do you verify that right how do you exam how do you know and so my students and I and also the people at Google we're doing the experiment came up with statistical tests that you can apply to the outputs in order to try to verify you know what is you know that that at least that some hard problem is being solved the the test that Google ended up using was something that they called the linear cross entropy benchmark okay and it's basically you know so the the drawback of this test is that it requires like it requires you to do a two to the 53 time calculation with your classical computer okay so it's very expensive to do the test on a classical computer the good news I think of a numbers - it's about 9 quadrillion ok doesn't help well well you know you want to be like scientific notation oh no what I mean is yeah it is it is it is impossible to run on us yes so we will come back to that it is just barely possible to run we think on the largest supercomputer that currently exists on earth which is called summit at Oak Ridge National Lab ok so I ironically for this type of experiment we don't want a hunch Kubitz okay because with a hundred cubits even if it works we don't know how to verify the results okay so we want you know a number of qubits that is enough that you know click the biggest classical computers on earth we'll have to sweat you know and we'll just barely you know be able to keep up with with the quantum computer you know using much more time but they will still be able to do it in order that we can verify that was just where the 53 comes from for the qubit well I mean I mean I mean I mean I mean that's also that sort of you know the mote I mean that's that's that's sort of where they are now in terms of scaling you know and then you know soon you know that point will be passed and and then when you get to larger numbers of qubits then you know these these types of sampling experiments will no longer be so interesting because we won't even be able to verify the results and we'll have to switch to other types of computations so with it with the sampling thing you know so so the test that Google applied with this linear cross entropy benchmark would basically just take the samples that were generated which are you know a very small subset of all the possible samples that there are but for those you calculate with your classical computer the probabilities that they should have been output and you see are those probabilities like larger than the mean you know so is the quantum computer bias toward outputting the strings that it's you know that you want it to be biased toward okay and then finally we come to a very crucial question which is supposing that it does that well how do we know that a classical computer could not have quickly done the same thing right how do we know that you know this couldn't have been spoofed by a classical computer right and so well the first answer is we don't know for sure because you know this takes us into questions of complexity theory you know you know the I mean questions on the of the magnitude of the P versus NP question and think that right we you know we don't know how to rule out definitively that there could be fast classical algorithms for you know even simulating quantum mechanics and for you know simulating experiments like these but we can give some evidence against that possibility and was sort of the you know the main thrust of a lot of the work that my colleagues and I did you know over the last decade which is then sort of in around 2015 or so what led to Google deciding to do this experiment so is the kind of evidence you first of all the hard P equals NP problem that you mentioned and the kind of evidence the year were looking at is that something you come to on a sheet of paper or is this something are these empirical experiments it's it's math for the most part I mean it you know it's also trot you know you know we have a bunch of methods that are known for simulating quantum circuits or you know quantum computations with classical computers and so we have to try them all out and make sure that you know they don't work you know make sure that they have exponential scaling on on you know these problems and and not just theoretically but with the actual range of parameters that are actually you know arising in Google's experiment okay so so there is an empirical component to it right but now on on the theoretical side you know what basically what we know how to do in theoretical computer science and computational complexity is you know we don't know how to prove that most of the problems we care about are hard but we know how to pass the blame to someone else yeah we know how to say well look you know I can't prove that this problem is hard but if it is easy then all these other things that you know if you know first you you probably we're much more confident or we're hard that then those would be easily as well okay so so we can give what are called reductions this has been the basic strategy in you know an NP completeness right in all of theoretical computer science and cryptography since the 1970s really and so we were able to give some reduction evidence for the hardness of simulating these sampling experiments these sampling based quantum supremacy experiments the reduction evidence is not as satisfactory as it should be one of the biggest open problems in this area is to make it better but you know we can do something you know certainly we can you say that you know if there is a fast classical algorithm to spoof these experiments then it has to be very very unlike any of the algorithms that we know which is kind of in the same kind of space of reasoning that people say P equal not equals NP yeah it's in the same spirit yeah in the same spirit okay so Andrew yang a very intelligent and presidential candidate with a lot of interesting ideas in all kinds of technological fields tweeted that because of quantum computing no code is uncrackable is he wrong or right he was premature let's say so well okay wrong look i you know i i'm actually i'm you know i'm a fan of andrew yang I like his cat you know I like his ideas I like his candidacy I think that uh you know he you know he may be ahead of his time with you know the universal basic income and you know and so forth and he may also be ahead of his time in that tweet that you referenced so guarding regarding using quantum computers to break cryptography so the situation is this okay so the famous discovery of Peter shor you know 26 years ago that really started quantum computing you know as an autonomous field was that if you build a full scalable quantum computer then you could use it to efficiently find the prime factors of huge numbers and calculate discrete logarithms and solve a few other problems that are very very special and character right they're not np-complete problems we're pretty sure they're not okay but it so happens that most of the public key cryptography that we currently use to protect the internet is based on the belief that these problems are hard okay what sure showed is that once you get scalable quantum computers then that's no longer true okay but now you know uh you know before people panic there are two important points to understand here okay the first is that quantum supremacy the milestone that Google just achieved is very very far from the kind of scalable quantum computer that would be needed to actually threaten public key cryptography okay so you know we touched on this earlier bright but Google's device has 53 physical qubits right you threaten cryptography you're talking you know with any of the known error correction method you're talking millions of physical qubits because error correction would be required yes yes yes yeah yes yeah it's a it certainly would right and uh you know how much you know how great will the overhead be from the error correction that we don't know yet but with the known codes you're talking millions of physical qubits and of a much higher quality than any that we have now okay so you know I I don't I don't think that that is you know coming soon although people who have secrets that you know need to stay secret for 20 years you know are already worried about this you know for the good reason that you know we presume that intelligence agencies are already scooping up data you know in the hope that eventually they'll be able to decode it once quantum computers become available okay so so there is so so so so this brings me to the second point I wanted to make which is that there are other public key cryptosystems that are known that we don't know how to break even with quantum computers okay and there so there's a whole field devoted to this now which is called post quantum cryptography okay and so there is already so so we have some good candidates now the best-known being what are called lattice based crypto systems and there is already some push to try to migrate to these crypto systems so NIST in the u.s. is holding a competition to create standards for post quantum cryptography which will be the first step in trying to get every web browser and every router to upgrade you know and use a you know some like SSL that is would be based on on you know what we think is quantum secure cryptography but you know this will this will be a long process but you know it is it is something that people are already starting to do and so so you know I'm sure as algorithm is was sort of a dramatic discovery you know it could be a big deal for whatever Intelligence Agency first gets a scalable quantum computer if no at least certainly if no one else knows that they have it right but eventually we think that we could migrate the internet to the post quantum cryptography and we'd be more or less back where we started okay so this is sort of not the application of quantum computing I think that's really going to change the world in a sustainable way right the C big by the way the biggest practical application of quantum computing that we know about by far I think is simply the simulation of quantum mechanics itself in order to you know learn about chemical reactions you know design maybe new chemical processes new materials new drugs new solar cells new superconductors all kinds of things like that what's the size of a quantum computer that would be able to simulate the you know quantum mechanical systems themselves that would be impactful for the real world for the kind of chemical reactions and that kind of work what what scalar were talking about now you're asking a very very current question a very big question people are going to be racing over the next decade to try to do useful quantum simulations even with you know 100 or 200 cubic quantum computers of the sort that we expect to be able to build over the next decade ok so that might be you know the first application of quantum computing that we're able to realize you know or or maybe it will prove to be too difficult and maybe even that will require fault tolerance or you know will require error correction that's an aggressive race to come off with the one case study kind of like the computer sure the with a with the idea that would just capture the world's imagination of yeah look we can actually do something very yeah right but I think you know within the next decade the best shot we have is certainly not you know Shor's algorithm to break cryptography you know it's just just because it requires you know too much in the way of error correction the best shot we have is to do some quantum simulation that tells the material scientists or chemists or nuclear physicists you know something that is useful to them and that they didn't already know you know and you might only need one or two successes in order to change some you know billion-dollar industries right like you know the way that people make fertilizer right now is still based on the hopper Boetsch process from a century ago and it is some many-body quantum mechanics problem that no one really understands right if you could design a better way to make fertilizer right that's you know billions of dollars right there so so so those are sort of the applications that people are going to be aggressively racing toward over the next decade now I don't know if they're gonna realize it or not but you know it is you know there's there sir they certainly at least have a shot so it's gonna be a very very interesting next decade justify what's your intuition is if a breakthrough like that comes would is it possible for that breakthrough to beyond 50 to 100 cubits or is scale a fundamental thing like 500 1000 of us qubits yeah so I I can tell you what the current studies are saying you know I I think probably better to rely on that that my intuition but you know there there was a group at Microsoft had a study a few years ago that said even with only about 100 cubits you know you could already learn something new about this the chemical reaction that makes fertilizer for example the trouble is they're talking about a hundred qubits and about a million layers of quantum gates okay so there so basically they're talking about a hundred nearly perfect qubits so the logical qubits is you measure exactly a hundred logical qubits and and now you know the hard part for the next decade is going to be well what can we do with a hundred to two hundred noisy qubits yeah yeah is that an error correction breakthroughs that might come without and need to do thousands or millions of yeah yeah so people are gonna be pushing simultaneously on a bunch of different directions one direction of course is just making the cube it's better right and you know there's there there is tremendous progress there I mean you know the fidelity is like the the the accuracy of the qubits isn't improved by several orders of magnitude you know in the you know and the last decade or two okay the second thing is designing better our you know let's say lower overhead error correcting codes and even short of doing the full recursive error correction you know there were these error mitigation strategies that you can use you know that may you know allow you to eke out a useful speed-up in in the near term and then the third thing is just taking the quantum algorithms for simulating quantum chemistry or materials and making them more efficient you know and those algorithms are already dramatically more efficient than they were let's say five years ago and so when you know I quoted these estimates like you know circuit depth of 1 million and so you know I hope that because people will care enough that these numbers are going to come down so you're one of the the world-class researchers in this space there's a few groups that we mentioned Google and IBM working at this there's there's other research labs but you put also you have an amazing blog you just you put a lot on your put a you paid me to say it you put a lot a lot of effort sort of to communicating the science of this and communicating exposing some of the BS and sort of the natural just like in the AI space the natural charlatan ism that's the word in this in quantum mechanics in general but quantum computers and so on can you give some notes about people or ideas that people like me or listeners in general from outside the field should be cautious of when they're taking in news headings that Google achieved quantum supremacy what should we look out for where's the Charlatans in the space where's the BS yeah so a good question unfortunately quantum computing is a little bit like cryptocurrency or deep learning and like there is a core of something that is genuinely revolutionary and exciting and because of that core it attracts this sort of vast penumbra of you know people making you know just utterly ridiculous claims and so with with quantum computing I mean I would say that the main way that people go astray is by you know not focusing on sort of the question of you know are you getting a speed-up over a classical computer or not right and so so you know people have like a dismissed quantum supremacy because it's not useful right or you know it's not itself let's say obviously useful for anything okay but you know ironically these are some of the same people who will go and say well we care about useful applications we care about solving traffic routing and Optima you know and and financial optimization and all these things and that sounds really good you know but they're you know they're their entire spiel is sort of counting on nobody asking the question yes but how well could a classical computer do the same thing yes right you know it I really mean the entire thing is is is you know it you know they they say well a quantum computer can do this a quantum computer can do that right and they just avoid the question are you getting a speed-up over a classical computer or not and you know if so how you know how how do you know have you really thought carefully about classical algorithms to do you know to solve the same problem right and a lot of the application areas that you the you know companies and investors are most excited about that the popular press is most excited about you know for quantum computers have been things like machine learning AI optimization okay and the problem with that is that since the very beginning you know even if you have a perfect you know fault tolerant you know quantum c'mon um computer you know we have known of only modest speed ups that you can get for these problems okay so so there is a famous quantum algorithm called Grover's algorithm okay and what it can do is it can solve many many of the problems that arise in AI machine learning optimization including np-complete problems okay but it can solve them in about the square root of the number of steps that a classical computer would need for the same problems okay now a square root speed-up is you know important it's impressive it is not an exponential speed-up okay so it is not the kind of game-changer that lets say Shor's algorithm for factoring is or for that matter that simulation of quantum mechanics is okay it is a more modest speed up let's say you know roughly you know in theory it could roughly double the size of the optimization problems that you could handle right and and so what you know because people found that I guess to to boring or you know to unimpressive you know they've gone on to to like invent all of these heuristic algorithms where you know because no one really understands them you can just project your hopes on to them right that well maybe it gets an exponential speed-up you can't prove that it doesn't you know and the burden is on you to prove that it doesn't get a speed-up right and you know so they've done an immense amount of that kind of thing and a really worrying amount of the case for building a quantum computer has come to rest on this stuff that those of us in this field know perfectly well is on extremely shaky foundations so the fundamental question is yeah show that there's a speed-up yes Icicle absolutely in this space that you're referring to which is actually interesting the area that a lot of people excited about is machine learning yeah so your senses do you think it will so I know that there's a lot of smoke currently yeah but do you think they're actually eventually might be breakthroughs where you do get exponential speed ups in the machine learning space absolutely there might be I mean I think we know of modest speed ups that you can get for these problems I think you know whether you can get bigger speed ups is one of the the biggest questions for quantum computing theory you know for people like me to be thinking about now you know we had actually recently a really you know a super exciting candidate for an exponential quantum speed-up for a machine learning problem that people really care about this is basically the Netflix problem the problem of recommending products to users given some sparse data about their preferences Karen etus and Prakash in 2016 had an algorithm for sampling recommendations that was exponentially faster than any known classical algorithm right and so I you know a lot of people were excited I was excited about it I had an eighteen-year-old undergrad by the name of Alain Tang and she was you know she was obviously brilliant she was looking for a project I gave her as a project can you prove that this speed-up is real can you prove that you know any classical algorithm would need to access exponentially more data right and you know this this was a case where if that was true this was not like a P versus NP type of question right this this might well have been provable but she worked on it for a year she couldn't do it eventually she figured out why she couldn't do it and the reason was that that was false there is a classical algorithm with a similar performance to the quantum algorithm so even succeeded in D quantizing that machine learning algorithm and then in the last couple of years building on a wins breakthrough a bunch of the other quantum machine learning algorithms that were proposed have now also been D quantized yeah okay and so I would say again backwards step yes a like a yes or a forward step for science but well yeah step for a machine-learning yeah that that precedes the big next forward step right right right now if it's bright now some people will say well you know there's a silver lining in this cloud they say well look thinking about quantum computing has led to the discovery of potentially useful new classical algorithm it's true right and so you know so you get these spin-off applications but if you want a quantum speed-up you really have to think carefully about that you know e winds work was a perfect illustration of why right and I think that you know the the challenge you know that you know that the the field is now open right find a better example find you know where quantum computers are going to deliver big gains for machine learning you know I and I am you know not only do i ardently support you know people thinking about that I'm trying to think about it myself and have my students and postdocs think about it but we should not pretend that those speedups are already established and and the problem comes when so many of the companies and you know and and journalists in this space are pretending that like all good things like life itself this conversation must soon come to an end let me ask the most absurdly philosophical last question okay what is the meaning of life what gives your life fulfillment purpose happiness and yeah meaning I would say you know number one trying to discover new things about the world and and share them and you know communicate and and learn what other people have discovered you know number two you know my friends my family my kids my students you know they're just the people around me number three you know trying you know when I can to you know make the world better and some small ways and you know it's the pressing that I can't do more and that you know the world is you know in you know facing crises over you know the climate and over you know resurgent authoritarianism and all these other things but you know trying to stand against the things that I find horrible when I can let me ask ya one more absurd question yeah what makes you smile well yeah I guess your question just did I don't know I thought I tried that absurd one on you well is a huge honor to talk to you we'll probably talk to you for many more hours Scott thank you so much well thank you thank you it was great thank you for listening to this conversation with Scott Aaronson and thank you to our presenting sponsor cash app download it used coal XPath cast you'll get $10 $10 will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman now let me leave you awards from a funny and insightful blog post Scott wrote over 10 years ago on the ever-present Malthusian isms in our daily lives quote again and again I've undergone the humbling experience of first lamenting how badly something sucks then only much later having a crucial insight that it's not sucking wouldn't have been a Nash equilibrium thank you for listening I hope to see you next time you |
Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence | Lex Fridman Podcast #71 | - The following is a conversation
with Vladimir Vapnik, part two, the second time
we spoke on the podcast. He's the co inventor of
support vector machines, support vector clustering, VC theory and many foundational ideas
in statistical learning. He was born in the Soviet Union, worked at the Institute of
Control Sciences in Moscow, then in the U.S., worked at ATT&T, NEC Labs, Facebook AI Research, and now is a professor
at Columbia University. His work has been cited
over 200,000 times. The first time we spoke on the podcast was just over a year ago,
one of the early episodes. This time we spoke after
a lecture he gave titled: "Complete Statistical Theory of Learning," as part of the MIT series
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organizations that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation
with Vladimir Vapnik. You and I talked about
Alan Turing yesterday, a little bit.
- Yes. - And that he, as the father
of artificial intelligence may have instilled in our
field an ethic of engineering in that science. Seeking more to build intelligence rather than to understand it. What do you think is the
difference between these two paths of engineering intelligence and
the science of intelligence? - It's a completely different story. Engineering is imitation
of human activity. You have to make a device which behaves as a human behaves. You have all the functions of human. It does not matter how you do it. But to understand what
is intelligence about, is quite different problem. So I think, I believe, that it's somehow related to
predicated talk yesterday. Because, look at Vladimir Propp's idea. He just found such a one here, predicates. He called it units. Which can explain human behavior, at least in Russian tales. You look at the Russian
tales and derive from that. And then people realize that they're more violent in Russian tales. It is in TV, in movie
serials and so on and so on. - So you're talking about Vladimir Propp, who in
1928 published a book, "Morphology of the Folk Tale."
- Exactly. - Describing 31 predicates that have this kind of sequential structure that a lot of the
stories' narratives follow in Russian folklore and in other content. We'll talk about it; I'd
like to talk about predicates in a focused way, but let
me, if you'll allow me, to stay zoomed out on
our friend Allen Touring. And you know, he inspired a generation with the imitation game.
- Yes. - Do you think, if we can linger
on that a little bit longer do you think we can learn? Do you think learning
to imitate intelligence can get us closer to
understanding intelligence? Why do you think imitation
is so far from understanding? - I think that it is different between you have different goals. Your goal is to create
something, something useful. And that is great, and you can see how much things was done and I believe that it
will be done even more. Self-driving cars and all
sorts of this business. It is great, and it was
inspired by Turing's vision. But understanding is very difficult. It's more or less a
philosophical category. What means understandable? I believe in things
which start from Plato. That there exists world of ideas. I believe that intelligence,
it is world of ideas. But it is world of pure ideas. And when you combine that with reality things, it creates as in my case, in the variants, which is very specific. And that I believe, the combination of ideas and a way to
constructing the variant is intelligence, but
first of all a predicate. If you know predicate, and hope for this is not too much predicate exists. For example, sort of
unpredicted for human behavior is not a lot.
- Vladimir Propp used 31 (sighs) you could even call
'em predicates, 31 predicates to describe stories, narratives. Do you think human behavior, how much of human behavior,
how much of our world, our universe, all the things
that matter in our existence can be summarized in predicates of the kind that Propp was working with? - I think that we have a lot of forms of behavior. But I think the predicate is much less. Because even in these examples
which I gave you yesterday, you saw that predicate can be, one, predicate can construct
many different invariants, depending on your data. They're applying to different data and they give different invariants. But pure ideas, maybe not so much.
- Not so many. - I don't know about that. But my guess, I hope, that's my challenge
about digit recognition, how much you need. - I think we'll talk about computer vision and 2-D images a little
bit in your challenge. - [Vladimir] That's
exact about intelligence. - That's exactly about, no, that hopes to be exactly about
the spirit of intelligence in the simplest possible way.
- Yeah, absolutely. You should start the simplest way, otherwise you will not be able to do it. - There's an open question whether starting at the MNIST digit recognition is a step towards intelligence
or it's an entirely different thing.
- I think that to build records using say, 100,
200 times less examples, you need intelligence.
- You need intelligence. So let's, because you use this term, and it would be nice,
I'd like to ask simple, maybe even dumb questions. Let's start with a predicate. In terms of terms and
how you think about it, what is a predicate? - I don't know. (laughs)
I have a feeling, formally they exist. I believe that predicate for 2-D images. One of them is symmetry. - Hold on a second. Sorry, sorry to interrupt
and pull you back. At the simplest level, we're
not being profound currently. A predicate is a statement
of something that is true. - [Vladimir] Yes. - Do you think of predicates
as somehow probabilistic in nature or is this binary? This is truly constraints
of logical statements about the world.
- In my definition, the simplest predicate is function. Function and you can use this function to make inner product, that is predicate. - What's the input and what's
the output of the function? - Input is X, something
which is input in reality. Say, if you considered digit
recognition, in pixel space. But it is function which in pixel space. But it can be any function, pixel space. And you choose, and I believe that there are several functions, which is important for
understanding of images. One of them is symmetry, it's
not so simple construction, as I described is the
derivative, it's all this stuff. But another I believe,
I don't know how many, is how well-structurized is picture. - Structurized?
- Yeah. - What do you mean by structurized? - It is formal definition, say, something heavy on the left corner, not so heavy in the middle and so on. You describe in general,
concept of what you assume. - Concepts, some kind
of universal concepts. - Yeah. But I don't know how to formalize this. - This is the thing,
there's a million ways we can talk about this,
I'll keep bringing it up. We humans have such concepts, when we look at digits. But it's hard to put them,
just like you're saying now, it's hard to put them into words. - You know, that is example. When critics in music, trying to describe music, they use predicate. And not too many predicate
but in different combination. But they have some special
words for describing music. And the same should be for images. But maybe there are critics who understand essence of what this image is about. - Do you think there
exists critics who can summarize the essence
of images, human beings? - [Vladimir] I hope that, yes. - Explicitly state them on paper? The fundamental question I'm asking is do you (chuckles) do
you think there exists a small set of predicates
that will summarize images? It feels to our mind like it does that the concept of what
makes a two and a three and a four--
- No, no, no. It's not only on this level. It should not describe two, three, four. It describes some
construction which allows you to create an invariants. - And invariants, sorry to stick on this, but terminology.
- Invariants, it is, it is projection of your image. Say, I can say, looking at my image, it is more or less symmetric and I can give you a variable of symmetry. Say, level of symmetry using this function which I gave yesterday. Then you can describe that your image has these characteristics
exactly in the way how musical critics describe music. But this is invariant
applied to specific data, to specific music, to something. I strongly believe in this Plato idea, that exists world of
predicate and world of reality and predicate and reality
are somehow connected and you have to figure out that. - Let's talk about Plato a little bit. So you draw a line from Plato to Hegel to Wigner to today.
- Yes. - So Plato has forms. The theory of forms;
there's a world of ideas and a world of things, as you talk about. And there's a connection,
and presumably the world of ideas is very small,
and the world of things is arbitrarily big, but they're all, what Plato calls them like, it's a shadow, the real world is a shadow from the world of form.
- Yeah and you have projection - Projection.
- Of a world of idea. - Yeah, very poetic.
- And in reality you can, realize this projection
using these invariants because it is a projection
for only specific examples which create specific
features of specific objects. - So the essence of intelligence is, while only being able to
observe the world of things, try to come up with a world of ideas. - Exactly, like in this music story. Intelligent musical
critics knows this world and have a feeling about them.
- I feel like that's a contradiction;
intelligent music critics. I think music is to be... enjoyed in all its forms. The notion of critic, like a food critic. - [Vladimir] No, I don't
want attach emotion. - That's an interesting question. Does emotion, there's certain elements of the human psychology,
of the human experience which seem to almost contradict
intelligence and reason. Like emotion, like fear. Like love, all of those things. Are those not connected in
any way to the space of ideas? - This I don't know. I just want to be concentrating on very simple story. On digit recognition. - So you don't think you have to love and fear death in order
to recognize digits? - I don't know because
it's so complicated. It involves a lot of stuff
which I never considered. But I know about digit recognition. And I know that for digit recognition to get the records from small
numbers of observations, you need predicate but
not special predicate for this problem. But universal predicate which understand world of images. - Of visual information.
- Visual, yeah. But on the first step, they understand say, a world of 100 digits or characters or something simple. - [Lex] So like you said,
symmetry is an interesting one. - No, that's what I think
one of the predicate is related to symmetry,
the level of symmetry. - Okay, degree of symmetry.
- Yeah. - So you think symmetry at the bottom is a universal notion and there's, there's degrees of a
single kind of symmetry? Or is there many kinds of symmetries? - Many kinds of symmetries. There is a symmetry/anti-symmetry
say, letter S. So it has vertical anti-symmetry. It could be diagonal
symmetry, vertical symmetry. - So when you cut
vertically the letter S-- - Yeah, and then the upper part and lower part
are in different directions. - Inverted along the Y-axis. But that's just like, one
example of symmetry right? Isn't there like--
- Right, but there is a degree of symmetry. If you play all this lineated stuff to do tangent distance, whatever I described, you can have a degree of symmetry. And that is what is
describing reason of image. It is the same as you will describe this image saying about digit S has anti-symmetry, digit three is symmetric more/less. Look for symmetry. - Do you think such concepts
like symmetry predicates, like symmetry, is it a
hierarchical set of concepts? Or are these independent, distinct predicates that we want to discover a subset of? - There is a degree of symmetry. And this idea of symmetry made very general, like degree of symmetry, the degree of symmetry can
be zero, no symmetry at all. Or degree of symmetry of let's say, more or less symmetrical. But you have one of these descriptions, and symmetry can be different. As I told, horizontal, vertical, diagonal. Anti-symmetry also is
a concept of symmetry. - What about shape in general? I mean, symmetry is a fascinating notion, but it--
- No, no, I'm talking about digits, I would like to concentrate on all I would like to know
predicate for digit recognition. - Yes, but symmetry is not
enough for digit recognition, right?
- It is not necessarily for digit recognition; it helps to create invariant, which you can use when
you will have examples for digit recognition. You have regular problem
of digit recognition. You have examples of the
first class and second class. Plus you know that there exists
this concept of symmetry. And you apply when you're
looking for decision rule, you will apply concept of symmetry, of this level of symmetry
which you estimate from. Everything is, comes from weak convergence. - What is convergence? What is weak convergence? What is strong convergence? I'm sorry I'm gonna do this to you. What are we converging from and to? - You're converging, you
would like to have a function. The function which say, indicate
a function which indicate your digit five, for example.
- A classification/task-- - Let's talk only about
classification task. - So classification means you will say whether this is a five or not, or say which of the 10 digits it is. - Right, right, I would like to have these functions. Then, I have some examples. I can consider property of these examples. Say, symmetry, and I can
measure level of symmetry for every digit. And then I can take average from my training data. And I will consider only functions of conditional probability,
which I'm looking for in my decision level. Which applying to the digits will give me the same average as I observed on training data. So actually this is different level of description of what you want. You want, not just, you show not one digit. You show this predicate,
show general property of all digits which you have in mind. If you have in mind digit three, it gives you property of digit three and you select as
admissible set of functions, only function which keeps this property. You will not consider the other functions. So you're immediately
looking for smaller subset of functions.
- That's what you mean by an admissible function.
- And admissible function. Exactly.
- Which is still a pretty large, for the number three, that's a large--
- It's large but, if you have one predicate. But according to, there is a strong and weak convergence. Strong convergence if
convergence in function. You're looking for the
function, on one function, and you're looking on another function. And square difference from them should be small. If you take difference at any points, make a square, make an integral,
and it should be small. That is convergence in function. Suppose you had some
function, any function. So I would say, I say that some function converged to this function. If integral from square
difference between them is small-- - That's the definition
of strong convergence. - That's the definition of--
- Two functions, the integral of the difference is small.
- Yeah, it is convergence in functions.
- Yeah. - But you have different
convergence in functions. You take any function,
you take some function Fe and take inner product this
function, this F function. F zero function which you want to find, and that gives you some value. So you say that a set of functions converge in inner product to this function if this value of inner product
converge to value F zero. That is for one Fe. But three converges requires that it converges for any
function of field of space. If it converge for any
function of field of space, then you will say that
this is a weak convergence. You can think that when you take integral, that is property, integral
property of function. For example, if you will
take sine or cosine, it is coefficient of say, free expansion. If it converged for all coefficients or free expansion, so under some condition it converged to function you're looking for. But weak convergence means any property. Not convergence, not point-wise. But integral property of function. So weak convergence means
integral property of functions. When I'm talking about
predicate, I would like to formulate which integral properties I would like to have for convergence. And if I will take one predicate, predicate its function
which I measure property. If I will use one predicate and say, I will consider only
function which give me the same value as this
predicate, I select a set of functions from functions
which is admissible, in the sense that
function which I'm looking for in this set of functions. Because I'm checking in training data, it gives the same. - [Lex] Yeah, so it
always has to be connected to the training data in terms of-- - Yeah, but property, you can know independent of training data. And this guy, Propp, says that there is formal property. 31 property and if you--
- A fairy tale, the Russian fairy tale.
- Right. But the Russian fairy tale
is not so interesting. It's more interesting
that people applied this to movies, to theater, to different things and the same works. They're universal. - So I would argue that
there's a little bit of a difference between the kinds of things that would apply to, which are essentially stories
and digit recognition. - [Vladimir] It is the same story. - You're saying digits, there's
a story within the digit? - Yeah.
(laughing) So but my point is, well, I hope that it's
possible to beat a record. Using not 60,000 but say, 100 times less. Because instead you will give predicates. And you will select your decision not from right set of functions. But from set of function
which gives this predicate. But predicate is not related
just to digit recognition. - Right, so--
- Like in Plato's case. - (laughs) Do you think it's possible to automatically discover the predicates? So, you basically said that the essence of intelligence is the discovery of good predicates. - [Vladimir] Yeah. - Now the natural question is, you know, that's what Einstein
was good at doing in physics. Can we make machines do these kinds of discovery of good predicates? Or is this ultimately a human endeavor? - That I don't know. I don't think that much it can do. Because, according to theory
about weak convergence, any function from Hilbert
Space can be predicate. So you have infinite number
of predicate in upper. And before you don't know which
predicate is good in which. But whatever Propp showed, and why
people call it breakthrough, that there is not too many predicate which cover most of situation
that happen in the world. - So there's a sea of predicates. Only a small amount are
useful for the kinds of things that happen in the world? - I think that, I would say only a small part of predicates very useful. Useful, all of them.
- Only a very few are what we should, let's
call them good predicates. - Very good predicates.
- Very good predicates. Can we linger on it,
what's your intuition? Why is it hard for a machine to
discover good predicates? - Even in my talk described
how to do a predicate. How to find new predicates, I'm not sure that it is very good predicate. - [Lex] What did you propose in your talk? - In my talk I gave example for diabetes. - Diabetes, yeah.
- When we achieve some percent so then we're looking from area, where some sort of predicate
which I formulated, does not... keep invariant. So if it doesn't keep, I retrain my data. I select only functions
which keep this invariant. In the way I did it, I
improved my performance. I came looking for this predicate. I know technically how to do that. You can of course do it using a machine, but I'm not sure that we will construct
the smartest predicate. - Well this is the,
allow me to linger on it. Because that's the essence,
that's the challenge. That is artificial, that's
the human-level intelligence that we seek, is the discovery
of these good predicates. You've talked about deep
learning as a way to, the predicates they use and
the functions are mediocre. Or you can find better ones. - Let's talk about deep learning. - Sure, let's do it.
- I know only Jans LaComb, convolutional network, and what else? And it's very simple convergence. - [Lex] There's not much else to know. - To fix it left and right.
- Yes. - I can do it like that
with one predicate. - [Lex] Convolution is a single predicate. - It's single, it's single predicate.
- Yes, but-- - You know exactly,
you take the derivative for translational, and
predicate should be kept. - So that's a single predicate,
but humans discovered that one or at least--
- Not that that is the least not too many predicates. And that is big story because
Jan did it 25 years ago, and nothing so clear was
uttered to deep network. And then I don't understand why we should talk about deep network instead of talking about
piece-wise linear functions which keeps this predicate. - You know, a counter argument is, that maybe the amount
of predicates necessary to solve general intelligence,
say in the space of images, doing efficient recognition
of handwritten digits is very small. So we shouldn't be so
obsessed about finding, we'll find other good predicates like convolution, for example. There has been other advancements like, if you look at the work with attention, there's attentional mechanisms, especially used in natural language focusing the network's ability to, to learn at which part
of the input to look at. The thing is, there's other
things besides predicates that are important for the
actual engineering mechanism of showing how much you can really do, given such these predicates. I mean, that's essentially
the work of deep learning is constructing
architectures that are able to be given the training data
to be able to converge towards a function that can approximate, that can generalize well. It's an engineering problem.
- Yeah, I understand. But let's talk not on an emotional level,
but on a mathematical level. You have set of piece-wise
linear functions, it is all possible neural networks. It's just piece-wise linear functions. It's many, many pieces.
- Large, large number of piece-wise linear function.
- Exactly. - Very large.
- Very large. - [Lex] Almost, feels like too large. - It's still simpler
than say, convolution, which is reproducing Hilbert's Space and we have a Hilbert's set of functions. - What's Hilbert Space? - It's space with infinite
number of coordinates. A function for expansion,
something like that. So it's much richer. And when I'm talking about
closed-form solution, I'm talking about this set of functions. Not piece-wise linear set,
which is particular case of (chuckles) it is small part of it. - So neural networks is a small part of the space you're, of
functions you're talking about? - Small set of functions.
- Yeah. - Let me take it that. But it is fine, it is fine. I don't want to discuss the
small or big we take and what. So you have some set of functions. So now when you're trying
to create architecture, you would like to create
admissible set of functions, which all your tricks,
to use not all functions, but some subset of this set of functions. Say when you're introducing
convolutional network. It is a way to make this subset useful for you. But from my point of view, convolutional, it is something, you want
to keep some invariance. Say, translation invariance. But now if you understand this, and you cannot explain on the level of ideas
what neural network does, you should agree that it is much better to
have a set of functions. As I say, this set of
functions should be admissible, it must keep this
invariant, this invariant, and that invariant. You know that as soon as you
incorporate new invariants, set of functions becomes
smaller and smaller and smaller. - [Lex] But all the invariants are specified by you the human. - Yeah, but what I am hope, that there is a standard
predicate like, Propp showed. That's what I want to find
for digit recognition. If we start, it is completely new area of what is intelligence
about on the level, starting from Plato's idea. What is the world of ideas? And I believe there is not too many. But you know, it is
amusing that mathematicians are doing something with neural
network in general function. But people from literature, from art, they use this all the time. - That's right.
- Invariants. Say, it is great how
people describe music. We should learn from that. Something on this level. So why, Vladimir Propp
who was just theoretical. Who studied theoretical
literature, he found that. - You know what, let me
throw that right back at you. Because there's a little bit of a, that's less mathematical
and more emotional, philosophical Vladimir Propp. I mean, he wasn't doing math.
- No. - And you just said another
emotional statement, which is you believe that this Plato world of ideas is small. - I hope.
- I hope. Do (chuckles), do you, what's your intuition, though,
if we can linger on it? That bothers me.
- You know, because not just small or big. I know exactly. That when I'm introducing some predicate, I
decrease set of functions. But my goal to decrease
set of functions much. - By as much as possible.
- By as much as possible. Good predicate which does this, then I should choose next
predicate which does this, which decreases set as much as possible. So, set of good predicates, it is such that the decrease, amount of admissible functions-- - So if each good predicate
significantly reduces the set of admissible functions that there naturally should
not be that many predicates. - No, but, if you reduce very well the
VC dimension of the function of admissible set of
functions, it's small. And you need not too much
training data to do well. - [Lex] And VC dimension, by the way, is some measure of capacity
of this set of functions. - Right, roughly speaking,
how many function in this set. So you're decreasing, decreasing, and it makes it easier for you to find the function you're looking for. But the most important part, to create a good admissible
set of functions. And it probably is that
there are many ways but, a good predicate is such
that it can do that. For this duck, you should know a little bit about duck. - What are the three
fundamental laws of ducks? - Looks like a duck, swims like a duck, and quacks like a duck.
- And quacks. You should know something about ducks to be able to--
- Not necessarily. Looks like say, horse. It's also good. - [Lex] So it's not (chuckles), it generalize from ducks.
- Yes, and talk like it, and make sound like horse or something. And run like horse and moves like horse. It is general, it is general predicate that this applies to duck. But for duck you can say,
play chess like duck. - [Lex] You cannot say,
play chess like a duck. - Why not?
- So you're saying you can but that that would not be a good-- - [Vladimir] No, you will
not reduce that function. - Yeah, you would not
reduce the set of functions. - So you can, the story is formal story and it's a magical story
is that you can use any function you want as a predicate. But some of them are good,
some of them are not. Because some of them
reduce a lot of functions. The admissible set, some of them (mumbles) - So the question is, and
I'll probably keep asking this question, but how do
we find such predicates? What's your intuition? Handwritten recognition, how do we find the answer to your challenge? - Yeah, I understand it like that. I understand what. - What defined?
- What that means, a new predicate.
- Yeah. - Like, guy who understands music can say these words he describes when he listens to music. He understands music, he'll
use not too many different. Or you can do it like Propp. You can make collection, what
you're talking about music. About this, about that. It's not too many different
situations you describe. - Because we mentioned
Vladimir Propp a bunch, let me just mention, so
there's a sequence of 31 structural notions that
are common in stories. And I think--
- They're called units. - Units, and I think they resonate. It starts, just to give an example, Absention: a member of
the hero's community or family leaves the security
of the home environment, then goes through the interdiction, a forbidding edict or command
that's passed upon the hero. Don't go there; don't do this. The hero's warned against some action. Then step three:
Violation of interdiction. You know, break the rules,
break out on your own. Then reconnaissance, the
villain makes an effort to attain knowledge needed
to fulfill their plot, so on. It goes on like this. Ends in a wedding, number
31, happily every after. - He just gave description
of all situations. He understands his world--
- Of folk tales. - Yeah, not folk--
- Stories. - Stories, and these stories
not just in folk tales. These stories in
detective serials as well. - [Lex] And probably in our lives. We probably live--
- Read this. They're all, this predicate is good
for different situations. For movie, for theater.
- By the way, there's also criticism, right? There's another way to
interpret narratives. From... Claude Levi Strauss.
- I am not in this business. - I know, that's theoretical literature, but it's looking at paradigms behind them. - [Vladimir] It's
always, this discussion-- - Philosophers argue.
- Yeah. - Yeah.
- But at least there is units. It's not too many units that can describe. But describe probably
gives the other units. Or another way for description. - Exactly, another set of units. - [Vladimir] Another
set of predicates, yes. It doesn't matter how,
but they exist probably. - My question is, whether
given those units, whether without our human
brains to interpret these units, they would still hold as
much power as they have. Meaning, are those units
enough when we give them to the alien species? - Let me ask you, do you understand digit images? - No, I don't understand.
- No, no, no. When you can recognize these digit images, it means that you understand. - Yes, I understand.
- You understand characters, you understand.
- Nope, nope, nope, nope. It's the imitation versus
understanding question. Because I don't understand the mechanism by which I understand--
- No, no. I'm not talking about, I'm
talking about predicates. You understand that it involves symmetry, maybe structure, maybe something else. I cannot formulate, I just was able to find symmetries, or
degree of symmetries. - So this is a good line. I feel like I understand
the basic elements of what makes a good hand
recognition system my own. Like, symmetry connects with me. It seems like that's a
very powerful predicate. My question is, is there
a lot more going on that we're not able to introspect? Maybe I need to be able to understand a huge amount in the world of ideas. Thousands of predicates,
millions of predicates in order to do hand recognition. - [Vladimir] I don't think so. - Both your hope and your intuition are such that very few--
- No, no, let me explain. You're using digits. You're using examples as well. Theory says that if you will use all possible functions from Hilbert Space, all possible predicates, you
don't need training data. You just will have
admissible set of functions which contain one function.
- Yes. So the trade off is, when
you're not using all predicates, you're only using a few good predicates, that you need to have some training data. - Yes, exactly.
- The more good predicates you have, the less training data you need.
- Exactly. That is intelligent learning. - Okay, I'm gonna keep asking
the same dumb question, handwritten recognition,
to solve the challenge, you kind of propose a challenge that says we should be able to get state
of the art MNIST error rates by using very few, 60 maybe
few examples per digit. What kind of predicates
do you think you'll-- - [Vladimir] That is the challenge. (laughs) So people who will solve this problem. - They will answer.
- They will answer it. - Do you think they'll
be able to answer it in a human explainable way? - They just need the
right function, that's it. - But so, can that
function be written I guess by an automated reasoning system? Whether we're talking
about a neural network learning a particular
function, or another mechanism. - No, I'm not against neural network. I am against admissible set of function which creates neural network. You did it by hand. You don't do it by invariants, by predicate, by reason. - But neural networks can then reverse, to the reverse step of
helping you find a function. The task of a neural network is to find disentangled representation,
for example is what they call, is to fine that one predicate function that's really captures
some kind of essence. Not the entire essence,
but one very useful essence of this particular visual space. Do you think that's possible? Listen, I'm grasping, hoping
there's an automated way to find good predicates, right? So the question is,
what are the mechanisms of finding good predicates, ideas, that you think we should pursue? A young grad student listening right now. - I gave example. So find situation where predicate, which you're suggesting, don't create invariant. It's like in physics, find situation where existing theory cannot explain it. - [Lex] Find a situation
where the existing theory can't explain it.
- Cannot explain this. - [Lex] So you're finding contradictions. - Find contradiction, and then
remove this contradiction. But in my case, what means contradiction, you find function which, if
you will use this function, you're not keeping invariants. - [Lex] So really the process of discovering contradictions. - Yeah. It is like in physics. Find situation where
you have contradiction for one of the property, for one of the predicate, then include this predicate
making invariants. And solve, again, this problem, now you don't have contradiction. But it is not the best way probably, I don't know, to looking for predicate.
- That's just one way. Okay.
- That, no, no. It is brute force way.
- The brute force way. What about the ideas of what, big
umbrella term of symbolic AI? In the '80s with Xper Systems, sort of logic, reasoning-based systems. Is there hope there to find some, through sort of, deductive reasoning, to find good predicates? - [Vladimir] I don't think so. I think that just logic is not enough. - Kind of a compelling notion, though. That when smart people sit in a room and reason through things,
it seems compelling. And making our machines do
the same is also compelling. - Everything is very simple when you have infinite
number of predicate. You can choose the function you want. You have invariants and you
choose the function you want. But you have to have not too many invariants to solve the problem. And how from infinite number function to select finite number and hopefully small finite
number of functions. Which is good enough to extract some small set
of admissible functions. So they will be admissible, it's for sure, because every function just
decrease set of function and leaving it admissible. But it will be small. - But why do you think
logic-based systems can't help? Intuition, not--
- Because you should know reality, you should know life. This guy like Propp, he knows something and he tried to put in
invariants his understanding. - So but that's the human, yeah, yeah. But see, you're putting too much value into Vladimir Propp's knowing something. - No, it is--
- Am I being misunderstanding? - What means you know life? What it mean?
- You know common sense. - No, no, you know something. Common sense, it is some rules. - You think so? Common sense is simply rules? Common sense is every, it's mortality, it's fear of death, it's love, it's spirituality, it's happiness and sadness. All of it is tied up into
understanding gravity which is what we think of as common sense. - I don't credit or discuss of that. I want to discuss understand
digit recognition. - Any time I bring up love and death you bring it back to digit recognition. I like it. (laughs)
- No, you know, it is doable because there is a challenge. - Yeah.
- Which I still have to solve it; if I will
have a student concentrate on this work, I will
suggest something or so. - You mean handwritten recognition? Yeah, it's a beautifully simple, elegant, and yet--
- I think that I know invariants which will solve this. - You do?
- I think that, I think that. But it is not universal. I want some universal
invariants which are good not only for digit recognition,
for image understanding. - So let me ask, how hard do you think is 2-D image understanding? If we can kind of intuit
handwritten recognition, how big of a step, leap,
journey is it from that? If I gave you good, if
I solved your challenge for handwritten recognition,
how long would my journey then be from that to
understanding more general, natural images?
- Immediately. You will understand it as soon
as you will make a record. - You think so?
- Because it is not for free. As soon as you will
create several invariants which will help you to get the same performance that the best neural net did using more than 100 times less examples. You have to have something
smart to do that. - And you're saying?
- That's not an invariant. It is predicate because
you should put some idea how to do that. - But okay. Let me just pause, maybe it's
a trivial point, maybe not, but handwritten recognition
feels like a 2-D, two-dimensional problem. And it seems, like how much complicated is the fact that most
images are a projection of a three-dimensional
world onto a 2-D plane? It feels like for a
three-dimensional world, we need to start
understanding common sense in order to understand an image. It's no longer visual shape and symmetry. It's having to start to
understand concepts of, understand life.
- Yeah. You're talking that there
are different invariant, different predicate, yeah. - [Lex] And potentially
much larger number. - You know, maybe, but
let's start from simple. - [Lex] But you said that
it would be immediate. - No, you know, I cannot
think about things which I don't understand yet. This I understand. But I'm sure that I don't
understand everything there. - [Lex] Yeah, that's the difference-- - It's like they say, do as simple as possible, but not simpler, and that is exact case. - With handwritten rec--
- With handwritten. - Yeah, but that's the
difference between you and I. (laughs) I welcome and enjoy thinking about things that I
completely don't understand. Because to me it's a natural extension, without having solved
handwritten recognition to wonder how, how difficult is the next
step of understanding 2-D and 3-D images, because ultimately, while the science of
intelligence is fascinating, it's also fascinating to see how that maps to the
engineering of intelligence. And recognizing handwritten digits is not, doesn't help you, it might, it may not, help you with the problem
of general intelligence. We don't know; it'll
help you a little bit. We don't know how much.
- It is unclear. - It's unclear.
- Yeah. - It might very much.
- But I would like to make a remark: I start not from very primitive problem like, challenge problem; I start
with very general problem, with Plato, so you understand. And it comes from Plato,
digit recognition. - So you basically took Plato and the world of forms and ideas, and mapped, and projected
it into the clearest, simplest formulation of that big world into handwritten recognition. - I will say that I did
not understand Plato until recently, and until I considered weak convergence
and then predicate and then, oh, this is what Plato thought. - Can you linger on that? How do you think about this world of ideas and world of things and Plato? - It is a metaphor.
- It's a metaphor for sure. It's a compelling, it's a
poetic and a beautiful metaphor. But what can you--
- But it is a way how you should try to understand how a duck ideas in the world. So from my point of view, it is very clear, but it
is a line all the time people looking for that. Say, Plato then Hegel, whatever reasonable it exists, whatever exists it is reasonable. I don't know what he
have in mind, reasonable. - [Lex] Right, these philosophers again. - No, no, no, no, no, no, it is, it is next stop of Wilner. That which we might understand
something of reality. He did the same Plato line. And then it comes suddenly
to Vladimir Propp. Look, 31 ideas, 31 units,
and describes everything. - There's abstractions, ideas
that represent our world, and we should always
try to reach into that. - Yeah, but what you
should make a projection on the reality, but understanding is, it is abstract ideas. You have in your mind
several abstract ideas which you can apply to reality. - And reality in this case so
if we look at machine learning is data.
- This example, data. - Data. Okay, let me put this on you, because I'm an emotional creature. I'm not a mathematical creature like you. I find compelling the
idea, forget the space, this sea of functions. There's also a sea of data in the world. And I find compelling that there might be, like you said, teacher, small examples of data
that are most useful for discovering good,
whether it's predicates or good functions, that
the selection of data may be a powerful journey,
a useful mechanism. You know, coming up with
a mechanism for selecting good data might be useful, too. Do you find this idea of
finding the right data set interesting at all? Or do you kinda take
the data set as a given? - I think that it is, you know, my thing is very simple. You have huge set of functions. If you will apply, and you
have not too many data. If you pick up function
which describes this data, you will do not very well. - Like randomly pick?
- Yeah (mumbles) It will be irritating. So you should decrease set of function from which you're picking out one. So you should go somehow to
admissible set of functions. And this, what about weak convergence? From another point of view, to make admissible set of function,
you need just the deal, just function which you
will take an inner product. Which you will measure property of your function. That is how it works. - [Lex] No, I get it, I get it. I understand it but do you, the reality is--
- But let's discuss, let's think about examples. You have huge set of function
and you have several examples. If you just trying to keep, take function which
satisfies these examples, you still will not have it. You need decrease, you need
admissible set of functions. - Absolutely, but what, say you have more data than functions. I mean, maybe not more
data than functions, 'cause that's--
- That's impossible. - Impossible, I was trying
to be poetic for a second. I mean, you have a huge amount of data, a huge amount of examples. - But amount of function can be even bigger.
- Even bigger, I understand. - Everything is (chuckles) - [Lex] There's always a bigger boat. - Whole Hilbert Space of functions. - I got you, but okay. But you don't, you don't
find the world of data to be an interesting optimization space? Like, the optimization should
be in the space of functions. - In creating admissible set of functions. - [Lex] Admissible set of functions. - You know, even from the
classical, this is so. From structured reasoning,
you should organize function in the way they will be useful for you.
- Right. - And that is admissible step. - But the way you're thinking about useful is you're given a small set of examples. - Small set of functions which contain functions by looking for it. - Yeah, but as looking for
it based on the empirical set of small examples.
- Yeah. But that is another
story, I don't touch it. Because I believe that
these small examples, it's not too small. Say 65%, law of large numbers works. I don't need uniform law. The story is that in
statistics there are two laws. Law of large numbers and
uniform law of large numbers. So I want a situation where
I use law of large numbers but not uniform law of large numbers. - [Lex] Right, so 60 is law of large. It's large enough.
- I hope, I hope. It still needs some evaluation, some balance, et cetera. What I did is the following that, if you trust that say, this average gives
you something close to expectation so you can talk about that, about this predicate.
- Yeah. - [Vladimir] And that is
basis of human intelligence. - Good predicates, the
discovery of good predicates is the basis of human intelligence. - No, no, it is discovery of your understanding of world. Of your total logic of
understanding the world. Because you have several functions which you will apply to reality. - Can you say that again? So you're--
- You have several functions, predicates, but they're abstract. Then you will apply them
to reality, to your data, and you will create in
this weak predicate, which is useful for your task. But predicate are not related specifically to your task, to this here task. It is abstract functions,
which being applied, applied to--
- Many tasks that you might be interested in.
- It might be many tasks. I don't know. Different tasks. - [Lex] Well they should be many tasks. Right?
- Yeah, I believe. Like in Propp case. It was for fairy tales, but
it's happened everywhere. - Okay, we talked about
images a little bit but, can we talk about Noam
Chomsky for a second? (laughing) - I don't know him very well. - Personally?
- Not personally I don't know. - His ideas.
- His ideas. - Well let me just say,
do you think language, human language is essential
to expressing ideas, as Noam Chomsky believes? So like, language is at the core of our formation of predicates. Human language. - In all the story of
language is very complicated. I don't understand this
and I thought about-- - Nobody does.
- I'm not ready to work on that because it's so huge. It is not for me, and I
believe not for our century. - The 21st century.
- Not for 21st century. We should learn something, a lot of stuff from simple tasks like digit recognition. - So you think digital recognition, 2-D image, how would you more abstractly define it, digit recognition? It's 2-D image, symbol recognition essentially? I'm trying to get a sense,
sort of thinking about it now, having worked with MNIST forever, how small of a subset is
this of the general vision recognition problem and the
general intelligence problem? Is it? Is it a giant subset, is it not? And how far away is language? - You know, let me refer to Einstein. Take the simplest problem,
as simple as possible, but not simpler, and this is
challenge, is simple problem. But it's simple by idea,
but not simple to get it. When you will do this, you will find some
predicate which helps it. - Yeah, with Einstein you can, you look at General Relativity, but that doesn't help you
with quantum mechanics. - And that's another story. You don't have any universal instrument. - Yeah, so I'm trying to wonder if which space we're in. Whether handwritten recognition
is like General Relativity and then language is
like, quantum mechanics, are you still gonna
have to do a lot of mess to universalize it but, I'm trying to see. What's your intuition why
handwritten recognition is easier than language? Just, I think a lot of
people would agree with that, but if you could elucidate sort of, the intuition of why. - I don't know, no, I don't think in this direction. I just think in the direction
that this is problem, which if you will solve it well, we will create some abstract understanding of images. Maybe not all images. I would like talk to guys who doing in real images in Columbia University. - What kind of images? Unreal you said? - Real images.
- Real images. - Yeah, what their idea is, there are predicate what can be predicate. I say symmetry will play a
role in real-life images. In any real-life images, 2-D images, let's talk about 2-D images. Because... that's what we know. And neural network was
created for 2-D images. - So the people I know in
vision science, for example, for people who study human vision, that they usually go
to the world of symbols and like, handwritten
recognition but not really. It's other kinds of symbols to study our visual perception system. As far as I know, not much
predicate-type of thinking is understood about our vision system. - [Vladimir] They did not
think in this direction. - They don't, yeah, but
how do you even begin to think in that direction? - That is, I would like to discuss this. Because if you'll be
able to show that it is what's working, and theoretical thing, it's not so bad. - So if we compare it to language, language has like letters,
a finite set of letters and a finite set of ways
that you can put together those letters so it feels more
amenable to kind of analysis. With natural images,
there is so many pixels-- - No, no, no, letter, language is much, much more complicated. It involves a lot of different stuff. It's not just understanding of simple class of tasks. I would like to see list of task where language is involved.
- Yes. So there's a lot of nice benchmarks now in natural language processing,
from the very trivial, like, understanding the
elements of a sentence, to question/answering,
so much more complicated where you talk about open domain dialogue. The natural question is,
will handwritten recognition, it's really the first step of understanding visual information. - Right. But even our records show that we're going wrong direction. Because we need 60,000 digits. - So even this first step, so forget about talking about the full journey. This first step should be
taking in the right direction. - No, no, in wrong direction
because 60,000 is unacceptable. - No, I'm saying it should be
taken in the right direction because 60,000 is not acceptable. - You can talk, it's great
we have 1/2 percent of error. - And hopefully the step from doing hand recognition
using very few examples, a step towards what
babies do when they crawl and they understand their
physical environment. - I don't know what baby do.
- I know you don't know about babies, but--
- If you will do from very small examples, you will find principals which are different.
- That will apply to babies. - From what we're using now. Theoretical it's more or less clear. That means you will use weak convergence, not just strong convergence. - Do you think these principals are, will naturally be human interpretable? - [Vladimir] Oh yeah. - So we'll be able to explain them and have a nice presentation to show what those principals are? Or are they very, going to be very kind of,
abstract kinds of functions? - For example, I talk
yesterday about symmetry. And I gave very simple examples. The same will be like that. - You gave like, a
predicate of a basic for-- - For symmetries.
- Yes. For different symmetries
and you have for-- - For degree of symmetries. That is important, not just symmetry exist and does not exist;
degree of symmetry. - [Lex] Yeah, for handwritten recognition. - It's not for handwritten,
it's for any images. But I would like to
apply it to handwritten. - Right, in theory it's more general. Okay, okay. So a lot of the things
we've been talking about falls, we've been talking
about philosophy a little bit, but also about mathematics and statistics. A lot of it falls into this idea, a universal idea of
statistical theory of learning. What is the most beautiful and sort of, powerful or essential idea
that you've come across, even for yourself just personally, in the world of statistics or
statistic theory of learning? - Probably uniform convergence
which we do with (mumbles). - [Lex] Can you describe
universal convergence? - You have law of large numbers. So for any function,
expectation of function, average of function converged expectation. But if you have a set of functions, for any function it is true. But it should converge similar to anywhere therefore all set of functions. For learning, you need uniform convergence; just
convergence is not enough. Because when you pick up
one which gives minimum, you can pick up one function which does not converge and it
will give you the best answer for this function. So you need the uniform
convergence to guarantee learning. Learning does not really enter
your law of large numbers, really universal. The idea of universal
convergence exists in statistics for a long time. It is interesting that as I think about myself, how stupid I was for 50 years, I did not see weak convergence. I work only on strong convergence. But now I think that most
powerful is weak convergence because it makes admissible
set of functions. And even in old proverbs, when people tried to understand
recognition about duck law, looks like a duck and so on, they used weak convergence. People in language they understand this. But when we're trying to
create artificial intelligence if we want invent in different way. Just consider strong convergence,
artificial intelligence. - So reducing the set
of admissible functions you think there should be effort put into
understanding the properties of weak convergence?
- You know, in classical mathematics,
in Hilbert Space, there are only two forms of
convergence, strong and weak. Now we can use both. That means that we did everything. And it so happened, that when we used Hilbert
Space, which is very rich space, space of continuous functions which has an integral and square. So we can apply weak and
strong convergence for learning and have closed-form solution. So for computation it is simple. For me it is sign that it is right way. Because you don't need any this theory. Yes, do whatever you want. But now the only way left is the concept of what is predicate? - Of predicate.
- But it is not statistics. - By the way, I like
the fact that you think that heuristics are a mess
that should be removed from the system, so closed-form solution is the ultimate goal.
- No it so happens that when you're using right instrument, you
have closed-form solution. - Do you think intelligence,
human-level intelligence, when we create it will, will have something like
a closed-form solution? - Now I'm looking on bounds, which I gave bounds for convergence. And when I'm looking for bounds, I'm thinking, what is the most appropriate
kernel of this bound would be. So we know that in say, all our businesses we use
radial basis function. But looking for the bound I think that I start to understand
that maybe we need to make corrections to
radial basis function, to be closer to what's better for these bounds. So I'm again trying to
understand what type of kernel have best approximation, not an approximation, best fit to these bounds. - Sure, so there's a
lot of interesting work that could be done in
discovering better function than the radial basis functions for the kinds of bounds you would find. - It still comes from, you're looking to match
and trying to understand. - From your own mind looking at the-- - Yeah but--
- I don't know. - Then I'm trying to understand what will be good for that. - Yeah, but to me there's still a beauty, again, maybe I'm descending
value toward heuristics. To me, ultimately intelligence
will be a mess of heuristics. And that's the engineering answer, I guess.
- Absolutely. When you're doing say, self-driving cars, the great guy who will do this. It doesn't matter what theory behind that. Who has a better theory have to apply. It is the same story about predicate because you cannot create
rule for, situation is much more than you have rule for that. Maybe you can have more abstract rules, then it will be less literal. It is the same story about ideas and ideas applied to specific cases. - But still you should--
- You cannot avoid this. - [Lex] Yes of course,
but you should still reach for the ideas to understand the science.
- Yeah, yeah. - Let me kind of ask, do you think neural networks or functions can be made to reason? What do you think, we've been
talking about intelligence, but this idea of reasoning. There's an element of
sequentially disassembling, interpreting the images. When you think of handwritten recognition, we kind of think that
there will be a single, there's an input and an output;
there's not a recurrence. - Yeah.
- What do you think about, sort of, the idea of recurrence? Of going back to memory
and thinking through this sort of, sequentially, mangling the different
representations over and over until you arrive at a conclusion? Or is ultimately all of
that can be wrapped up in a function? (chuckles) - You're suggesting, that let us use this type of algorithm. When I started thinking, I first of all, starting to understand what I want. Can I write down what I want? And then I try to formalize. And when I do that, I'm thinking
how to solve this problem. Till now I did not see situation where-- - Where you need recurrence.
- Recurrent. - But do you observe human beings? - Yeah.
- Do you try to, it's the imitation question, right? It seems that human beings reason, this kind of sequentially, sort of, does that
inspire in you a thought that we need to add that into our intelligence systems? You're saying, okay, you've kind of answered saying, until now I haven't seen a need for it. And so because of that,
you don't see a reason to think about it? - You know, most of
things I don't understand. In reasoning, in humans, it is for me too complicated. For me, the most difficult part is to ask questions, good questions. How it works, how people asking questions. I don't know this. - You said that machine
learning's not only about technical things,
speaking of questions, but it's also about philosophy. What role does philosophy
play in machine learning? We talked about Plato,
but generally thinking in this philosophical way, how does philosophy and math
fit together in your mind? - Just ideas, and then
their implementation. It's like predicate, say, admissible set of functions. It comes together, everything. Because, the first declaration of
theory was done 50 years ago, all that necessary, so everything there. If you have data you can, and you, in your set of functions has not big capacity. So law of inter-dimension,
you can do that. You can make structuralist
minimization, control capacity. But there was not table to make
admissible set of function with. Now when suddenly we realize that we did not use another idea
of convergence, which we can, everything comes together. - But those are mathematical notions. Philosophy plays a role of simply saying that we should be swimming
in the space of ideas. - Let's talk, what is philosophy? Philosophy means understanding of life. Understanding of life,
say people like Plato, they understand on very
high, abstract level of life. And whatever I'm doing, it's just implementation of
my understanding of life. But every new step, that is very difficult. For example, to find this idea that we need weak convergence, was not simple for me. - So that required thinking
about life a little bit. Hard to trace, but there
was some thought process. - You know, when I'm thinking
about the same problem for 50 years now, and again and again and again, I'm trying to understand
that, this is very important, not to be very enthusiastic. But concentrate on whatever
that was not able to achieve. - Patient.
- Yeah. And understand why. And now I understand that, because I believe in math, I believe that, in this idea. But now when I see that there are only two ways of convergence,
and we're using loss. That means that we must
as well as people do it. But now, exactly in
philosophy and what we know about predicate, how we
understand life can be described as a predicate. I thought about that. And that is more or less
obvious level of symmetry. But next, I have a feeling it's
something about structures. But I don't know how to formulate, how to measure and measure a
structure and all this stuff. The guy who will solve this challenge problem, then when they will look at how he did it, probably just only symmetry is not enough. - [Lex] But something like
symmetry will be there. Structures of that kind.
- Oh yeah, absolutely. Symmetry will be there. A level of symmetry will be there. And level of symmetry, anti-symmetry, diagonal, vertical, I even don't know how you can use in different direction the degree of symmetry;
that's very general. But it will be there. I think that people are very sensitive to the idea of symmetry. But there are several ideas like symmetry. As I would like to learn. But you cannot learn
just thinking about that. You should do challenging problems and then analyze them. Why it was able to solve them. And then you will see. Very simple things, it's not easy to find. (Lex laughs)
Even talking about this, every time.
- Yes. - I was surprised, I tried to understand, these people describe in language strong convergence mechanism for learning. I did not see it, I don't know. But weak convergence, the duck story and story like that when you will explain, you will use weak convergence argument. It looks like a (mumbles) but when you try to formalize, you're just ignoring this. Why? Why 50 years? From start of machine learning. - [Lex] And that's the role of philosophy, thinking about life.
- I think that might be. I don't know. Maybe this is theory also, we should blame for that because
empirical risk minimization and now just starting, if
you read now textbooks, they just about bound about
empirical risk minimization. They don't look for another
problem like admissible set. - But on the topic of life, perhaps we, you, could talk
in Russian for a little bit. What's your favorite
memory from childhood? Okay, I want you to be
my (speaks in Russian) - Music. - How about, can you try
and answer in Russian? (speaking in Russian) What kind of musica? (speaking in Russian) (speaking in Russian) Now that we're talking about Bach, let's switch back to English, 'cause I like Beethoven and Chopin so. - [Vladimir] Chopin is
another amusing story. I was--
- But Bach, if we talk about predicates, Bach probably has the most sort of, well defined
predicates that underlie it. - You know, it is very interesting to read what critics writing about Bach, which words they're using, they're trying to describe predicates.
- Yeah. - And then Chopin. It is very different vocabulary. Very different predicate. And I think that, if you will make collection of that. So maybe from this you can describe predicate for digit recognition. - [Lex] From Bach and Chopin. - No, no, no, not from Bach and Chopin. - [Lex] From the the critic interpretation of the music, yeah.
- They're trying to explain you music, what they use this? They describe high-level
ideas of Plato's ideas behind this music.
- That's brilliant. Art is not self-explanatory in some sense. So you have to try to
convert it into ideas. - It is insulate problems. When you go from ideas to, to the representation. It is easy way, but when
you're trying to go back, it is you will pose problems but, nevertheless, I believe when
you're looking from that, even from art, you will be able to find predicate for digit recognition. - That's such a fascinating
and powerful notion. Do you ponder your own mortality? Do you think about it? Do you fear it? Do you draw insight from it? - About mortality? Oh yeah. - [Lex] Are you afraid of death? - Not too much, not too much. It is pity that I will not be able to do something which I think I was a feeling to do that. For example, I will be very happy to work with guys, take tradition from music. To write this collection of description, how they describe music,
how they use a predicate. And from art as well. Then take what's in common, and try to understand predicate which is absolute for everything. - [Lex] For visual recognition and see that there is a connection. - Yeah, yeah, exactly. - [Lex] There's still
time; we've got time. (laughing) We've got time. - It takes years and years and years.
- You think so? - It's a long way. - See, you've got the
patient mathematician's mind. I think it could be done very quickly and very beautifully. I think it's a really elegant idea. Some of many.
- Yeah, you know, the most time it is not
to make this collection, to understand what is in common, to think about that once again and again and again.
- Again and again and again. But I think sometimes,
especially when you just say this idea now, even just
putting together the collection and looking at the different sets of data. Language, trying to interpret
music, criticize music, and images, I think there will be sparks of ideas that will come. Of course, again and again you'll come up with better ideas but
even just that notion is a beautiful notion.
- I even have some example. So I have friend, who was specialized in Russian poetry. She is professor of Russian poetry. She did not write poems, but she know a lot of stuff. She make books, several books and one of them is a collection of Russian poetry. She has images of Russian poetry. She collected all images
of Russian poetry. And I asked her to do following. You have Nip's digit recognition. And we get 100 digits, less than 100, I don't
remember, maybe 50 digits. And try from practical point of view, describe every image you see, using only words of
images of Russian poetry. And she did it. And then we tried to, I call it learning using
privileged information. I call it privileged information. You have on two languages. One language is just image of digit. And another language by it
a description of this image. And this is privileged information. And there is an algorithm
when we are working with privileged information,
you're doing well. Better, much better. - So there's something there.
- Something there. And there is and the thing, she unfortunately died. The collection of digits and poetic descriptions of those digits. - [Lex] So there's something there in that poetic description. - I think that there is an abstract ideas on the Plato level of ideas.
- Yeah, that are there, that could be discovered, and music seems to be a good entry point. - But as soon as we start this, here's this challenge problem. - The challenge problem--
- It immediately connected to all this stuff. - Especially with your
talk and this podcast, I'll do whatever I can to advertise. Such a clean, beautiful,
Einstein-like formulation of the challenge before us.
- Right. - Let me ask another absurd question. We talked about mortality,
we talked about philosophy of life; what do you think
is the meaning of life? What's the predicate for mysterious existence here on Earth? - I don't know. It's very interesting how we have, in Russia, I don't know if you know the guy Strogatski? They're writing futures
they're thinking about, Hume, what's going on. And they have an idea that there are developing two type of people: Common
people and very smart people. They just started. And these two branches of people will go in different directions very soon. So that's what they're
thinking about next. - (laughs) So the purpose of life is to create two (chuckles) two paths. - Two paths.
- As human societies. Yeah.
- Yes, simple people and more complicated people. - Which do you like best? The simple people or the complicated ones? - I don't know, Strogatski, he's just, he's fantasy but you know, every week we have guy who is just writer, and also Soletskoff literature. And he explained how he
understands literature and human relationship. How he sees life. And I understood that I'm just
small kid comparing to him. He is very smart guy
in understanding life. He knows this predicate, he
knows big blocks of life. I'm amused every time I listen to him. And he's just talking about literature. And I think that I was surprised. So the managers in big companies, most of them are guys who study English language and English literature. So why? Because they understand life. They understand models. And among them, maybe
many talented creatures, which are just analyzing this. And this is big science like Propp did. This is his blocks. Yes, very smart. - It amazes me that you are and continue to be humbled by the brilliance of others. - I'm very modest about myself. I see so smart guys around. - Well let me immodest for you. You're one of the greatest
mathematicians/statisticians of our time, it's truly an honor. Thank you for talking.
- No, no, no, okay, okay. - And let's talk.
- (laughs) It is not. - Yeah, let's talk.
- I know my limits. - [Lex] Let's talk again when
your challenge is taken on and solved by a grad student. - Let's talk again.
- Especially when-- - [Vladimir] I hope that this happens. - Maybe music will be involved. Vladimir, thank you so much. It's been an honor.
- Thank you very much. - Thanks for listening
to this conversation with Vladimir Vapnik. And thank you to our
presenting sponsor Cash App. Download it, use code: LexPodcast. You'll get $10 and $10 will go to FIRST, an organization that inspires and educates young mind to become
science and technology innovators of tomorrow. If you enjoyed this podcast,
subscribe on YouTube, give it five stars on Apple
PodCast, support it on Patreon, or simply connect with me
on Twitter @LexFridman. And now let me leave you with some words from Vladimir Vapnik. "When solving a problem of interest, "do not solve a more general problem "as an intermediate step." Thank you for listening. I hope to see you next time. |
Jim Keller: Moore's Law, Microprocessors, and First Principles | Lex Fridman Podcast #70 | the following is a conversation with Jim Keller legendary microprocessor engineer who has worked at AMD Apple Tesla and now Intel he's known for his work on AMD K 7 K 8 K 12 and Xen microarchitectures Apple a4 and a5 processors and co-author of the specification for the x86 64 instruction set and hyper transport interconnect he's a brilliant first principles engineer and out-of-the-box thinker and just an interesting and fun human being to talk to this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance I up in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokers services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating a charity navigator which means that donated money is used to maximum effectiveness when you get cash app from the App Store Google Play and use code Lex podcast you'll get ten dollars and cash app will also donate ten dollars to the first which again is an organization that I've personally seen inspire girls and boys the dream of engineering a better world and now here's my with Jim Keller what are the differences in similarities between the human brain and a computer with the microprocessors core let's start with a philosophical question perhaps well since people don't actually understand how human brains work I think that's true I think that's true so it's hard to compare them computers are you know there's really two things there's memory and there's computation right and to date almost all computer architectures are global memory which is a thing right and then computation where you pull data and you do relatively simple operations on it and write data back so it's decoupled in modern in modern computers and you think in the human brain everything's a mesh a mess that's combined together what people observe is there's you know some number of layers of neurons which have local and global connections and information is stored in some distributed fashion and people build things called neural networks in computers where the information is distributed in some kind of fashion you know there's a mathematics behind it I don't know that the understandings that is super deep the computations we run on those are straightforward computations I don't believe anybody has said a neuron does this computation so to date it's hard to compare them I would say so let's get into the basics before we zoom back out how do you build a computer from scratch what is a microprocessor what is it microarchitecture what's an instruction set architecture maybe even as far back as what is a transistor so the special charm of computer engineering is there's a relatively good understanding of abstraction layers so down to bottom you have atoms and atoms get put together in materials like silicon or dope silicon or metal and we build transistors on top of that we build logic gates right and in functional units like an adder or subtractor or an instruction parsing unit and we assemble those into you know processing elements modern computers are built out of you know probably 10 to 20 locally you know organic processing elements or coherent processing elements and then that runs computer programs right so there's abstraction layers and then software you know there's an instruction set you run and then there's assembly language C C++ Java JavaScript you know there's abstraction layers you know essentially from the atom to the data center right so when you when you build a computer you know first there's a target like what's it for look how fast does it have to be which you know today there's a whole bunch of metrics about what that is and then in an organization of you know a thousand people who build a computer there's lots of different disciplines that you have to operate on does that make sense and so so there's a bunch of levels abstraction of in in organizational I can tell and in your own vision there's a lot of brilliance that comes in it every one of those layers some of it is science some was engineering some of his art what's the most if you could pick favorites what's the most important your favorite layer on these layers of abstractions where does the magic enter this hierarchy I don't really care that's the fun you know I'm somewhat agnostic to that so I would say for relatively long periods of time instruction sets are stable so the x86 instruction said the arm instruction set what's an instruction set so it says how do you encode the basic operations load store multiply add subtract conditional branch you know there aren't that many interesting instructions look if you look at a program and it runs you know 90% of the execution is on 25 opcodes you know 25 instructions on those are stable right what does it mean stable until architecture has been around for twenty-five years it works it works and that's because the basics you know or defined a long time ago right now the way an old computer ran is you fetched instructions and you executed them in order to the load do the ad do the compare the way a modern computer works is you fetch large numbers of instructions say 500 and then you find the dependency graph between the instructions and then you you execute in independent units those little micro graphs so a modern computer like people like to say computers should be simple and clean but it turns out the market for a simple complete clean slow computers is zero right we don't sell any simple clean computers now you can there's how you build it can be clean but the computer people want to buy that's say you know phone or data center such as a large number of instructions computes the dependency graph and then executes it in a way that gets the right answers and optimizes that graph somehow yeah they run deeply out of order and then there's semantics around how memory ordering works and other things work so the the computer sort of has a bunch of bookkeeping tables it says what order CDs operations finishing or appear to finish him but to go fast you have to fetch a lot of instructions and find all the parallelism now there's a second kind of computer which we call GPUs today and I called the difference there's found parallelism like you have a program with a lot of dependent instructions you fetch a bunch and then you go figure out the dependency graph and you issues instructions out order that's because you have one serial narrative to execute which in fact is and can be done out of order you call a narrative yeah well so yeah so humans think of serial narrative so read read a book right there's a you know there's the sends after sentence after sentence and there's paragraphs now you could diagram that imagine you diagrammed it properly and you said which sentences could be read in anti order any order without changing the meaning right but that's a fascinating question to ask of a book yeah yeah you could do that right so some paragraphs could be reordered some sentences can be reordered you could say he is tall and smart and X right and it doesn't matter the order of tall and smart but if you say is that tall man who's wearing a red shirt what colors you know like you can create dependencies right right and so GPUs on the other hand run simple programs on pixels but you're given a million of them and the first order the screen you're looking at it doesn't care which order you do it in so I call that given parallelism simple narratives around the large numbers of things where you can just say it's parallel because you told me it was so found parallelism where the narrative is it's sequential but you discover like little pockets of parallelism of versus turns out large pockets of parallelism large so how hard is it to discuss well how hard is it that's just transistor count right so once you crack the problem you say here's how you fetch ten instructions at a time here's how you calculated the dependencies between them here's how you describe the dependencies here's you know these are pieces right so once you describe the dependencies then it's just a graph sort of it's an algorithm that finds what is that I'm sure there's a graph there is the theoretical answer here that's solved well in general programs modern programs like human beings right how much found parallelism is there and on that I max what is 10 next mean oh well you execute it in order vs. yeah you would get what's called cycles per instruction and it would be about you know three instructions three cycles per instruction because of the latency of the operations and stuff and in a modern computer excuse it but like point to 0.25 cycles per instruction so it's about with today fine 10x and there and there's two things one is the found parallelism in the narrative right and the other is to predictability of the narrative right so certain operations they do a bunch of calculations and if greater than one do this else do that that that decision is predicted in modern computers to high 90% accuracy so branches happen a lot so imagine you have you have a decision to make every six instructions which is about the average right but you want to fetch five under instructions figure out the graph and execute them all in parallel that means you have let's say if you effect 600 instructions it's every six you have to fetch you have to predict ninety-nine out of a hundred branches correctly for that window to be effective okay so parallelism you can't paralyze branches or you can looking pretty you can what is predict a branch mean or what open take so imagine you do a computation over and over you're in a loop so Wow and it's greater than one do and you go through that loop a million times so every time you look at the branch you say it's probably still greater than one he's saying you could do that accurately very accurately monitoring comes my mind is blown how the heck did you that wait a minute well you want to know this is really sad 20 years ago yes you simply recorded which way the branch went last time and predicted the same thing right okay what's the accuracy of that 85% so then somebody said hey let's keep a couple of bits and have a little counter so and it predicts one way we count up and then pins so say you have a three bit counter so you count up and then count down and if it's you know you can use the top bit as the sign bit so you have a sign to bit number so if it's greater than one you predict taken and lesson one you predict not-taken right or less than zero or whatever the thing is and that got us to 92% oh okay I know is this better this branch depends on how you got there so if you came down the code one way you're talking about Bob and Jane right and then said is just Bob like Jane Enoch went one way but if you're talking about Bob and Jill this Bob like changes you go a different way right so that's called history so you take the history and a counter that's cool but that's not how anything works today they use something that looks a little like a neural network so modern you take all the execution flows and then you do basically deep pattern recognition of how the program is executing and you do that multiple different ways and you have something that chooses what the best result is there's a little supercomputer inside the computer that's trying to project that calculates which way branches go so the effective window that it's worth finding grassing gets bigger why was that gonna make me sad that's amazing it's amazingly complicated oh well here's the funny thing so to get to 85% took a thousand bits to get to 99% takes tens of megabits so this is one of those to get the result you want you know to get from a window of say 50 instructions to 500 it took three orders of magnitudes or four orders of magnitude toward bits now if you get the prediction of a branch wrong what happens then what is the pipe you flush the pipes is just the performance cost but it gets even better yeah so we're starting to look at stuff that says so executed down this path and then you had two ways to go but far far away there's something that doesn't matter which path you went so you miss you took the wrong path you executed a bunch of stuff then you had to miss predicting too backed it up but you remembered all the results you already calculated some of those are just fine look if you read a book and you misunderstand the paragraph your understanding is the next paragraph sometimes is invariance I don't understand you sometimes it depends on it and you can kind of anticipate that invariance yeah well you can keep track of whether that data changed and so when you come back to a piece of code should you calculate it again or do the same thing okay how much does this is art and how much of it is science because it sounds pretty complicated so well how do you describe a situation so imagine you come to a point in the road we have to make a decision right and you have a bunch of knowledge about which way to go maybe you have a map so you want to go is the shortest way or do you want to go the fastest way or you want to take the nicest Road so it's just some set of data so imagine you're doing something complicated like a building a computer and there's hundreds of decision points all with hundreds of possible ways to go and the ways you pick interacts in a complicated way right and then you have to pick the right spot right so those are there so I don't know yeah avoided the question you just described do the Robert Frost poem road less taken I describe the Robin truss problem which we do as computer designers it's all poetry ok great yeah I don't know how to describe that because some people are very good at making those intuitive leaps it seems like the combinations of things some people are less good at it but they're really good at evaluating your alternatives right and everybody has a different way to do it and some people can't make those sleeps but they're really good at analyzing it so when you see computers are designed by teams of people who have very different skill sets and a good team has lots of different kinds of people and I suspect you would describe some of them as artistic right but not very many unfortunately or fortunately fortunately well you know computer science hard it's 99% perspiration and the 1% inspiration is really important but I need the 99 yeah you got to do a lot of work and then there's there are interesting things to do at every level that stack so at the end of the day if you're on the same program multiple times does it always produce the same result is is there some room for fuzziness there that's a math problem so if you run a correct C program the definition is every time you run it you get the same answer yeah that well that's a math statement but that's a that's a language definitional statement so yes for years when people did when we first did 3d acceleration of graphics you could run the same scene multiple times and get different answers right right and then some people thought that was okay and some people thought it was a bad idea and then when the HPC world used GPUs for calculations they thought it's a really bad idea okay now in modern AI stuff people are looking at networks where the precision of the data is low enough that the date has somewhat noisy and the observation as the input data is unbelievably noisy so why should the calculation be not noisy and people have experimented with algorithms that say can get faster answers by being noisy like as the network starts to converge if you look at the computation graph it starts out really wide and it gets narrower and you can say is that last little bit that important or should I start to graph on the next rap rev before we would live all the way down to the answer right so you can create algorithms that are noisy now if you're developing something and every time you run it you get a different answer it's really annoying and so most people think even today every time you run the program you get the same answer now I know but the question is that's the formal definition of a programming language there is a definition of languages that don't get the same answer but people who use those you always want something because you get a bad answer and then you're wondering is it because right something in your brother because of this and so everybody wants a little swish that says no matter what ya do it deterministically and it's really weird because almost everything going into monetary calculations is noisy so why the answers have to be so clear it's right so where do you stand by design computers for people who run programs so somebody says I want in deterministic answer like most people want that can you deliver a deterministic answer I guess is the question like when you hopefully sure that's what people don't realize is you get a deterministic answer even though the execution flow is very own deterministic so if you run this program a hundred times it never runs the same way twice ever and the answer it arises the same in but it gets the same answer every time it's just just them is just amazing okay you've achieved in eyes of many people legend status as a cheap art architect what design creation are you most proud of perhaps because it was challenging because of its impact or because of the set of brilliant ideas that that were involved in well I find that description odd and I has two small children and I promise you they think it's hilarious this question yeah so I dude so I I'm I'm really interested in building computers and I've worked with really really smart people I'm not unbelievably smart I'm fascinated by how they go together both as a as a thing to do and is endeavor that people do how people in computers go together yeah like how people think and build a computer and I find sometimes that the best computer architects aren't that interested in people or the best people managers aren't that good at designing computers so the whole stack of human beings is fascinating so the managers individual engineers yeah I just I said I realized after a lot of years of building computers where you sort of build them out of the transistors logic gates functional units come computational elements that you could think of people the same way so people are functional units yes and then you can think of organizational design it's a computer architectural problem and then it's like oh that's super cool because the people are all different just like the computation elephants are all different and they like to do different things and and so I had a lot of fun like reframing how I think about organizations just like with with computers we were saying execution paths you can have a lot of different paths that end up at a at at the same good destination so what have you learned about the human abstractions from individual functional human units to the broader organization what does it take to create something special well most people don't think simple enough all right so do you know the difference between a recipe and understanding there's probably a philosophical description of this so imagine you can make a loaf of bread yeah the recipe says get some flour add some water add some yeast mix it up let it rise put it in a pan put it in the oven it's a recipe right understanding bread you can understand biology supply chains you know grain grinders yeast physics you know thermodynamics like there's so many levels of understanding there and then when people build and design things they frequently are executing some stack of recipes right and the problem with that is the recipes all have a limited scope look if you have a really good recipe book for making bread it won't tell you anything about how to make an omelet right right but if you have a deep understanding of cooking right then bread omelets you know sandwich you know there's there's a different you know way of viewing everything and most people when you get to be an expert at something you know you're you're hoping to achieve deeper understanding not just a large set of recipes to go execute and it's interesting the walk groups of people because xqt reps apiece is unbelievably efficient if it's what you want to do if it's not what you want to do you're really stuck and and that difference is crucial and ever and everybody has a balance of let's say deeper understanding recipes and some people are really good at recognizing when the problem is to understand something DP deeply that make sense it totally makes sense does it every stage of development deep on understanding on the team needed oh this goes back to the art versus science question sure if you constantly unpacked everything for deeper understanding you never get anything done right and if you don't unpack understanding when you need to you'll do the wrong thing and then at every juncture like human beings are these really weird things because everything you tell them has a million possible outputs all right and then they all interact in a hilarious way and then having some intuition about what you tell them what you do when do you intervene when do you not it's it's complicated all right so it's you know essentially computationally unsolvable yeah it's an intractable problem sure humans are a mess but with deep understanding do you mean also sort of fundamental questions of things like what is a computer or why like think the why question is why are we even building this like of purpose or do you mean more like going towards the fundamental limits of physics sort of really getting into the core of the sighs well in terms of building the computer thinks simple think a little simpler so common practice is you build a computer and then when somebody says I want to make it 10% faster you'll go in and say alright I need to make this buffer bigger and maybe I'll add an ad unit or you know I have this thing that's three instructions wide I'm going to make it four instructions wide and what you see is each piece gets incrementally more complicated right and then at some point you hit this limit like adding another feature or a buffer doesn't seem to make it any faster and then people say well that's because it's a fundamental limit and then somebody else to look at it and say well actually the way you divided the problem up and the way that different features are interacting is limiting you and it has to be rethought rewritten right so then you refactor it and rewrite it and what people commonly find is the rewrite is not only faster but half is complicated from scratch yes so how often in your career but just have you seen as needed maybe more generally to just throw the whole out thing out this is where I'm on one end of it every three to five years which end are you on like rewrite more often right and three or five years is if you want to really make a lot of progress on computer architecture every five years you should do one from scratch so where does the x86 64 standard come in or what how often do you I wrote the I was the co-author that's back in 98 that's 20 years ago yeah so that's still around the instruction set it stuff has been extended quite a few times yes and instruction sets are less interesting and implementation underneath there's been on x86 architecture Intel's designed a few Eames is designed a few very different architectures and I don't want to go into too much of the detail about how often but it's there's a tendency to rewrite it every you know 10 years and it really should be every five so you're saying you're an outlier in that sense in really more often we write more often well in here isn't that scary yeah of course well scary - who - everybody involved because like you said repeating the recipe is efficient companies want to make money well no in the individual juniors want to succeed so you want to incrementally improve increase the buffer from three to four well we get into the diminishing return curves I think Steve Jobs said this right so every you have a project and you start here and it goes up and they have Domitian return and to get to the next level you have to do a new one in the initial starting point will be lower than the old optimization point but it'll get higher so now you have two kinds of fear short-term disaster and long-term disaster and you're you're wrong right like you know people with a quarter by quarter business objective are terrified about changing everything yeah and people who are trying to run a business or build a computer for a long term objective know that the short-term limitations block them from the long term success so if you look at leaders of companies that had really good long-term success every time they saw that they had to redo something they did and so somebody has to speak up or you do multiple projects in parallel like you optimize the old one while you build a new one and but the marketing guys they're always like make promise me that the new computer is faster on every single thing and the computer architect says well the new computer will be faster on the average but there's a distribution or results in performance and you'll have some outliers that are slower and that's very hard because they have one customer cares about that one so speaking of the long-term for over 50 years now Moore's law has served a for me and millions of others as an inspiring beacon what kind of amazing future brilliant engineers can build no I'm just making your kids laugh all of today it was great so first in your eyes what is Moore's law if you could define for people who don't know well the simple statement was from Gordon Moore was double the number of transistors every two years something like that and then my operational model is we increased the performance of computers by 2x every 2 or 3 years and it's wiggled around substantially over time and also in how we deliver performance has changed but the foundational idea was to X two transistors every two years the current cadence is something like they call it a shrink factor like point six every two years which is not 0.5 but that that's referring strictly again to the original definition of transistor count a shrink factors just getting them smaller small as well as you use for a constant chip area if you make the transistor smaller by 0.6 then you get 1 over 0.6 more transistors so can you linger a little longer what's what's a broader what do you think should be the broader definition of Moore's law we mentioned before how you think of performance just broadly what's a good way to think about Moore's law well first of all so I I've been aware of Moore's law for 30 years in what sense well I've been designing computers for 40 just watching it before your eyes kind of slow and somewhere where I became aware of it I was also informed that Moore's law was gonna die in 10 to 15 years and I thought that was true at first but then after 10 years it was gonna die in 10 to 15 years and then at one point it was gonna die in 5 years and then it went back up to ten years and at some point I decided not to worry about that particular product mastication for the rest of my life which is which is fun and then I joined Intel and everybody said Moore's law is dead and I thought that's sad because it's the Moore's law company and it's not dead and it's always been gonna die and you know humans you like these apocryphal kind of statements like we'll run out of food or run out of air or you know something right but it's still incredible this lived for as long as it has and yes there's many people who believe now that Moore's Law instead you know they can join the last 50 years of people had the thing yeah there's a long tradition but why do you think if you can in touch try to understand it why do you think it's not dead well for Hartley let's just think people think Moore's law is one thing transistors get smaller but actually under the sheets ours literally thousands of innovations and almost all those innovations have their own diminishing return curves so if you graph it it looks like a cascade of diminishing return curves I don't know what to call that but the result is an exponential curve at least it has been so and we keep inventing new things so if you're an expert in one of the things on a diminishing return curve right and you can see it's plateau you will probably tell people well this is this is done meanwhile some other pile of people are doing something different so that's that's just normal so then there's the observation of how small could a switching device be so a modern transistor is something like a thousand by a thousand by thousand atoms right and you get quantum effects down around two to two to ten atoms so you can imagine the transistor as small as 10 by 10 by 10 so that's a million times smaller and then the quantum computational people are working away at how to use quantum effects so a thousand by thousand five thousand atoms it's a really clean way of putting it well fin like a modern transistor if you look at the fan it's like a hundred and twenty atoms wide but we can make that thinner and then there's there's a gate wrapped around it and under spacing there's a whole bunch of geometry and you know a competent transistor designer could count both atoms in every single direction like there's techniques now to already put down atoms in a single atomic layer and you can place atoms if you want to it's just you know from a manufacturing process if placing an atom takes ten minutes and you need to put you know 10 to the 23rd atoms together to make a computer it would take a long time so the the methods are you know both shrinking things and then coming up with effective ways to control what's happening manufacture stabling cheaply yeah so the innovation stocks pretty broad you know there there's equipment there's optics there's chemistry there's physics there's material science there's metallurgy there's lots of ideas about when you put their four materials together how they interact are they stable is I stable or temperature you know like are they repeatable you know there's look there's like literally thousands of technologies involved but just for the shrinking you don't think we're quite yet close to the fundamental limit in physics I did a talk on Moore's Law and I asked for a road map to a path of 100 and after two weeks they said we only got to fifty a hundred what's a 100 extra hundred shrink we only got 15 I said once you go to another two weeks well here's the thing about Moore's law right so I believe that the next 10 or 20 years of shrinking is going to happen right now as a computer designer there's you have two stances you think it's going to shrink in which case you're designing and thinking about architecture in a way that you'll use more transistors or conversely not be swamped by the complexity of all the transistors you get right you have to have a strategy you know so you're open to the possibility and waiting for the possibility of a whole new army of transistors ready to work I'm expecting expecting more transistors every two or three years by a number large enough that how you think about design how you think about architecture has to change like imagine you're you build built brick buildings out of bricks and every year the bricks are half the size or every two years well if you kept building bricks the same way you know so many bricks per person per day the amount of time to build a building would go up exponentially right right but if you said I know that's coming so now I'm going to design equipment and moves bricks faster uses them better because maybe you're getting something out of the smaller bricks more strengths inner walls you know less material efficiency out of that so once you have a roadmap with what's going to happen transistors they're gonna get we're gonna get more of them then you design was collateral rounded to take advantage of it and also to cope with it like that's the thing people to understand it's like if I didn't believe in Moore's law and Moore's law transistors showed up my design teams were all drowned so what's the what's the hardest part of this in flood of new transistors I mean even if you just look historically throughout your career what's what's the thing you what fundamentally changes when you add more transistors in in the task of designing an architecture no there's there's two constants right one is people don't get smarter I think by the way there's some size shown that we do get smarter because nutrition whatever sorry bring that what effect yes nobody understands it nobody knows if it's still going on so that's all or whether it's real or not but yeah that's a I sort of Amen but not if I believe for the most part people aren't getting much smarter the evidence doesn't support it that's right and then teams can't grow that much right all right so human beings understand you know we're really good in teams of ten you know up two teams of a hundred they can know each other beyond that you have to have organizational boundaries so you're kind of you have those are pretty hard constraints all right so then you have to divide and conquer like as the designs get bigger you have to divide it into pieces you know that the power of abstraction layers is really high we used to build computers out of transistors now we have a team that turns transistors and logic cells and our team that turns them into functional you know it's another one it turns in computers right so we have abstraction layers in there and you have to think about when do you shift gears on that we also use faster computers to build faster computers so some algorithms run twice as fast on new computers but a lot about rhythms are N squared so you know a computer with twice as many transistors and it might take four Tom's times as long to run so you have to refactor at the software like simply using faster computers to build bigger computers doesn't work so so you have to think about all these things so in terms of computing performance and the exciting possibility that more powerful computers bring is shrinking the thing we've been talking about one of the for you one of the biggest exciting possibilities of advancement in performance or is there are other directions that you're interested in like like in the direction of sort of enforcing given parallelism or like doing massive parallelism in terms of many many CPUs you know stacking CPUs on top of each other that kind of that kind of parallelism or you kind of well think about it a different way so old computers you know slow computers you said a equal B plus C times D pretty simple right and then we made faster computers with vector units and you can do proper equations and matrices right and then modern like AI computations or like convolutional neural networks we you convolve one large data set against another and so there's sort of this hierarchy of mathematics you know from simple equation to linear equations to matrix equations to it's a deeper kind of computation and the data sets are getting so big that people are thinking of data as a topology problem you know data is organized in some immense shape and then the computation which sort of wants to be get data from immense shape and do some computation on it so the with computers of a lot of people to do is how about rhythms go much much further so that that paper you you reference the Sutton paper they talked about you know like in a I started it was a ploy rule sets to something that's a very simple computational situation and then when they did first chess thing they solved deep searches so have a huge database of moves and results deep search but it's still just a search right now we we take large numbers of images and we use it to Train these weight sets that we convolve across it's a completely different kind of phenomena we call that AI now they're doing the next generation and if you look at it they're going up this mathema graph right and then computations the both computation and data sets support going up that graph yeah the kind of computation of my I mean I would argue that all of it is still a search right just like you said a topology problems data says he's searching the data sets for valuable data and also the actual optimization of your networks is a kind of search for the I don't know if you looked at the inner layers of finding a cat it's not a search it's it's a set of endless projection so you know projection and here's a shadow of this phone yeah right then you can have a shadow of that onto something a shadow on that or something if you look in the layers you'll see this layer actually describes pointy ears and round eyeness and fuzziness and but the computation to tease out the attributes is not search right ain't like the inference part might be searched but the trainings not search okay well 10 then in deep networks they look at layers and they don't even know it's represented and yet if you take the layers out it doesn't work ok so if I don't think it's search all right well but you have to talk to my mathematician about what that actually is oh you disagree but the the it's just semantics I think it's not but it's certainly not I would say it's absolutely not semantics but okay all right well if you want to go there so optimization to me is search and we're trying to optimize the ability of a neural network to detect cat ears and this difference between chess and the space the incredibly multi-dimensional hundred thousand dimensional space that you know networks are trying to optimize over is nothing like the chessboard database so it's a totally different kind of thing and okay in that sense you can say yeah yeah you know I could see how you you might say if if you the funny thing is it's the difference between given search space and found search space exactly yeah maybe that's a different way beautiful but okay but you're saying what's your sense in terms of the basic mathematical operations and the architectures can be hardwired that enables those operations do you see the CPUs of today still being a really core part of executing those mathematical operations yes well the operations you know continue to be add subtract loads or compare and branch it's it's remarkable so it's it's interesting that the building blocks of you know computers or transistors and you know under that atoms so you got atoms transistors logic gates computers right you know functional units and computers the building blocks of mathematics at some level are things like adds and subtracts and multiplies but that's the space mathematics can describe is I think essentially infinite but the computers that run the algorithms are still doing the same things now a given algorithm may say I need sparse data or I need 32-bit data or I need you know like a convolution operation that naturally takes 8-bit data multiplies it and sums it up a certain way so the like the data types in tensorflow imply an optimization set but when you go write down a look at the computers it's an inorganic salt applies like like that hasn't changed much now the quantum researchers think they're going to change that radically and then there's people who think about analog computing because you look in the brain and it seems to be more analog ish you know that maybe there's a way to do that more efficiently but we have a million acts on computation and I don't know the reference the relationship between computational let's say intensity and ability to hit match mathematical abstractions I don't know anyway subscribe dad but but just like you saw an AI you went from rule sets the simple search to complex search does a found search like those are you know orders of magnitude more computation to do and as we get the next two orders of magnitude your friend Roger godori said like every order magnitude changed the computation fundamentally changes what the computation is doing here oh you know the expression the difference in quantity is the difference in kind you know the difference between ant and ant hill right or neuron and brain you know there's there's there's just indefinable place where the the quantity changed the quality right now we've seen that happen in mathematics multiple times and you know my my guess is it's gonna keep happening so your senses yeah if you focus head down and shrinking a transistor let's not just head down and we're aware about the software stacks that are running in the computational loads and we're kind of pondering what do you do with a petabyte of memory that wants to be accessed in a sparse way and have you know the kind of calculations ai programmers want so there's that there's a dialog interaction but when you go in the computer chip you know you find adders and subtractors and multipliers and so if you zoom out then with as you mentioned which Sutton the idea that most of the development in the last many decades in the AI research came from just leveraging computation and just the simple algorithms waiting for the computation to improve well suffer guys have a thing that they called the the problem of early optimization right so if you write a big software stack and if you start optimizing like the first thing you write the odds of that being the performance limiter is low but when you get the whole thing working can you make it to X faster by optimizing the right things sure while you're optimizing that could you've written a new software stack which would have been a better choice maybe now you have creative tension so but the whole time as you're doing the writing the that's the software we're talking about the hardware underneath gets faster which goes back to the Moore's laws Moore's Law is going to continue then your AI research should expect that to show up and then you make a slightly different set of choices then we've hit the wall nothing's gonna happen and from here it's just us rewriting algorithms like that seems like a failed strategy for the last 30 years of Moore's laws death so so can you just linger on it I think you've answered it but it just asked the same dumb question over and over so what why do you think Moore's law is not going to die which is the most promising exciting possibility of why it won't done that's five 10 years so is it that continues shrinking the transistor or is it another s-curve that steps in and it totally so dope shrinking the transistor is literally thousands of innovations right so there's so this they're all answers and it's there's a whole bunch of s-curves just kind of running their course and being reinvented and new things you know the the semiconductor fabricators and technologists have all announced what's called nano wires so they they took a fan which had a gate around it and turned that into a little wire so you have better control that and they're smaller and then from there there's some obvious steps about how to shrink that so the metallurgy around wire stocks and stuff has very obvious abilities to shrink and you know there's a whole combination of things there to do your sense is that we're gonna get a lot yes this innovation from just that shrinking yeah like a factor of a hundred salade yeah I would say that's incredible and it's totally it's only 10 or 15 years now you're smarter you might know but to me it's totally unpredictable of what that hundred x would bring in terms of the nature of the computation and people be yeah you familiar with Bell's law so for a long time those mainframes Mini's workstation PC mobile Moore's Law drove faster smaller computers right and then we were thinking about Moore's law rajae godori said every 10x generates a new computation so scalar vector made Erichs topological computation right and if you go look at the industry trans there was no mainframes and mini-computers and PCs and then the internet took off and then we got mobile devices and now we're building 5g wireless with one millisecond latency and people are starting to think about the smart world where everything knows you recognizes you like like like the transformations are going to be like unpredictable how does it make you feel that you're one of the key architects of this kind of futures you're not we're not talking about the architects of the high-level people who build the Angry Bird apps and flapping Angry Bird of who knows we're gonna be that's the whole point of the universe let's take a stand at that and the attention distracting nature of mobile phones I'll take a stand but anyway in terms of that matters much the the side effects of smartphones or the attention distraction which part well who knows you know where this is all leading it's changing so fast wax my parents do steal my sister's for hiding in the closet with a wired phone with a dial on it stop talking your friends all day right now my wife feels with my kids for talking to their friends all day on text looks the same to me it's always it's echoes of the same thing okay but you are the one of the key people architecting the hardware of this future how does that make you feel do you feel responsible do you feel excited so we're we're in a social context so there's billions of people on this planet there are literally millions of people working on technology I feel lucky to be you know what doing what I do and getting paid for it and there's an interest in it but there's so many things going on in parallel it's like the actions are so unpredictable if I wasn't here somebody else are doing the the vectors of all these different things are happening all the time you know there's a I'm sure some philosopher or meta philosophers you know wondering about how we transform our world so you can't deny the fact that these tools whether that these tools are changing our world that's right do you think it's changing for the better so some of these I read this thing recently it said the peat the two disciplines with the highest GRE scores in college are physics in philosophy right and they're both sort of trying to answer the question why is there anything right and the Philosopher's you know are on the kind of theological side and the physicists are obviously on the you know the material side and there's a hundred billion galaxies with a hundred billion stars it seems well repetitive at best so I you know there's on our way to ten billion people I mean it's hard to say what it's all for is that's what you're asking yeah I guess I guess I do tend to are significantly increases in complexity and I'm curious about how computation like like our world our physical world inherently generates mathematics it's kind of obvious right so we have X Y Z coordinates you take a sphere you make it bigger you get a surface that falls you know grows by r-squared like it generally generates mathematics and the mathematicians and the physicists have been having a lot of fun talking to each other for years and computation has been let's say relatively pedestrian like computation in terms of mathematics has been doing binary binary algebra while those guys have been gallivanting through the other realms of possibility right now recently the computation lets you do math m'q mathematical computations that are sophisticated enough that nobody understands how the answers came out right machine learning machine lying yeah it used to be you get data set you guess at a function the function is considered physics if it's predictive of new functions data sets modern you can take a large data set with no intuition about what it is and use machine learning to find a pattern that has no function right and it can arrive at results that I don't know if they're completely mathematically describable so a computation is kind of done something interesting compared to a POV plus see there's something reminiscent of that step from the basic operations of addition to taking a step towards new all networks that's reminiscent of what life on Earth and its origins was doing do you think we're creating sort of the next step in our evolution in creating artificial intelligence systems that I don't know I mean you know if there's so much in the universe already it's hard to say well I'm standing in his hold are human beings working on additional abstraction layers and possibilities yet appear so does that mean that human beings don't need dogs you know no like like there's so many things that are all simultaneously interesting and useful but you've seen through I agree you've seen great and greater level abstractions and built in artificial machines right do you think when you look at humans you think that the look of all life on earth as a single organism building this thing this machine that greater and greater levels of abstraction do you think humans are the peak the top of the food chain in this long arc of history on earth or do you think we're just somewhere in the middle are we are we the basic functional operations of a CPU are we the C++ program the Python Perl Network like somebody's you know people have calculated like how many operations does the brain do and something you know I've seen the number 10 to the 18th about bunch of times arrive different ways so could you make a computer that did 10 to the 20th operations yes sure do you think we're gonna do that now is there something magical about how brains compute things I don't know you know my personal experiences interesting cuz you know you think you know how you think and then you have all these ideas and you can't figure out how they happened and if you meditate you know the like what what you can be aware of is interesting so I don't know if brains are magical or not you know the physical evidence says no lots of people's personal experiences yes so what would be funny as if brains are magical and yet we can make brains with more computation you know I don't know what to say about that but what do you think magic is an emergent phenomena what would be our than me I don't know teller of what what what in your view is consciousness with with consciousness yeah like what you know cautiousness love things that are these deeply human things that seems to emerge from our brain is that something that we'll be able to make encode in chips that get faster and faster and faster and faster the flick of 10 our conversations no but nobody really knows can you summarize it in a couple of couple of words many people have observed that organisms run at lots of different levels right if you got two neurons somebody said you'd have one sensory neuron and one motor neuron right so we move towards things and away from things and we have physical integrity and safety or not right and then if you look at the animal kingdom you can see brains that are a little more complicated and at some point there's a planning system and then there's an emotional system that's you know happy about being safe or unhappy about being threatened right and then our brains have massive numbers of structures you know like planning and movement and thinking and feeling and drives and emotions and we seem to have multiple layers of thinking systems and we have a brain a dream system that nobody understands whatsoever which I find completely hilarious and you can think in a way that those systems are more independent and you can observe you know the different parts of yourself can observe I don't know which one's magical I don't know which ones not computational so is it possible that it's all computation probably is there a limit to computation I don't think so do you think the universe is a computer I think he seems to be it's a weird kind of computer because if it was a computer right like when they do calculations on what it how much calculation it takes to describe quantum effects is unbelievably high so if it was a computer when you built it out of something that was easier to compute right that's that's a funny it's a funny system but then the simulation guys have pointed out that the rules are kind of interesting like when you look really close it's uncertain and the speed of light says you could only look so far and things can't be simultaneous except for the odd entanglement problem where they seem to be like the rules are all kind of weird and somebody said physics is like having 50 equations with 50 variables to define 50 variables like you know it's it's you know like physics itself has been a shitshow for thousands of years it seems odd when you get to the corners of everything you know it's either uncomputable or on definable or uncertain it's almost like the designers the simulation are trying to prevent us from understanding it perfectly but but also the things that require calculations requires so much calculation that our idea of the universe of a computer is absurd because every single little bit of it takes all the computation in the universe to figure out gee that's a weird kind of computer you know you say the simulation is running in the computer which has by definition infinite computations not infinite oh you mean if the universe is infinite yeah piece of our universe seems to take infinite computation I hit you're out just a lot whoa a lot some pretty big number compute this little teeny spot takes all the mass in the local one little year by one like your space it's close enough to infinite so it's a heck of a computer if it is one I know it's it's it's a weird it's a weird description because the simulations description seems too the break when you look closely at it but the rules in universe seemed to imply something's up that seems a little arbitrary the whole the universe the whole thing the the laws of physics you know it just seems like like how did it come out to be yeah the way it is but lots of people talk about that it's you know it's like I said the two smartest groups of humans are working on the same problem different different aspects and they're both complete failures so that's kind of cool they might succeed eventually well after two thousand years the trend isn't good two thousand years is nothing in the span of the history of the universe so we have some time but the next thousand years doesn't look good either so that's what everybody says that every stage but with Moore's law as you've just described not being dead the exponential growth the technology the future seems pretty incredible well it'll be interesting that's for sure that's right so what are your thoughts on Ray Kurzweil sense that exponential improvement and technology will continue indefinitely that is that how you see Moore's law do you see Moore's law more broadly and since the technology of all kinds has a way of stacking s curves on top of each other where it'll be exponential and then we'll see all kinds of what was an exponential of a million mean that's that's a pretty amazing number and that's just for a local little piece of silicon now it's imagine you say decided to get a thousand tons of silicon to collaborate in one computer at a million times the density like now you know you're talking I don't know 10 to the 20th more computation power then our current already unbelievably fast computers like nobody knows what that's going to mean you know the sci-fi guys called you know computron 'i'm like when like a local civilization turns the nearby star into a computer I like I don't that's true but so just even when you shrink a transistor the that's only one dimension of the ripple effects of that but people tend to think about computers the cost problem right so computers are made out of silicon and minor amounts of metals and you know this and that none of those things cost any money like there's plenty of sand like like you could just turn the beach and a little bit ocean water in the computers so all the cost is and equipment to do it and the trend on equipment is once you figure out a build the equipment the trend of cost is zero Elon said first you figure out what configuration you want the atoms in and then how to put them there right yeah cuz well what here's you know his his great insight is people are how constrained I have this thing I know how it works and then little tweaks to that will generate something as opposed to what do I actually want and then figure out how to build it it's a very different mindset and almost nobody has it obviously well let me ask on that topic you were one of the key early people in the development of autopilot at least in the hardware side Elon Musk believes that autopilot and vehicle autonomy if you just look at that problem can follow this kind of exponential improvement in terms of the ha the how question that we're talking about there's no reason why I can't what are your thoughts on this particular space of vehicle autonomy and you're a part of it and Elon Musk's and Tesla's vision well the computer you need to build was straightforward and you can argue well doesn't need to be 2 times faster or 5 times or 10 times but that's just a matter of time or price in the short run so that's that's not a big deal you don't have to be especially smart to drive a car so it's not like a super hard problem I mean the big problem with safety is attention which computers are really good at not skills well let me push back on one you see everything you said it's correct but we as humans tend to tend to take for granted how how incredible our vision system is so you can drive a car of 2050 vision and you can train a neural network to extract a distance of any object in the shape of any surface from a video and data but that really simple not simple I look that's a simple data problem it's not it's not simple it's because you because it's not just detecting object it's understanding the scene and it's being able to do it in a way that doesn't make errors so the beautiful thing about the human vision system and the entire brain around the whole thing is we were able to fill in the gaps it's not just about perfectly detecting cars it's inferring the occluded cars it's trying to it's it's understanding the I think it's mostly a bigger problem you so you think what data you know with compute with improvement of computation with improvement in collection well there is a you know when you're driving a car and somebody cuts you off your brain has theories about why they did it you know they're a bad person they're distracted they're dumb you know you can listen to yourself right so you know if you think that narrative is important to be able to successfully drive a car then current autopilot systems can't do it but if cars are ballistic things with tracks and probabilistic changes of speed and direction and roads are fixed and given by the way they don't change dynamically right you can map the world really thoroughly you can place every object really thoroughly right you can calculate trajectories of things really thoroughly right but everything you said about really thoroughly has a different degree of difficulty so you could say at some point computer autonomous systems will be way better it's things that humans are allows yet like it'll be better at abstention they'll always remember there was a pothole in the road that humans keep forgetting about they'll remember that this set of roads how these weirdo lines on it the computers figured out once and especially if they get updates so if somebody changes a given like that Akita robots and stuff somebody said is to maximize two Givens okay right so though having a robot pick up this bottle cap is ways you put a red dot on the top because then you have to figure out you know if you want to do a certain thing with it you know maximize the Givens is the thing and autonomous systems are happily maximizing the Givens like humans when you drive someplace new you remember it because you're processing it the whole time and after the 50th time you drove to work you get to work you don't know how you got there right you're on autopilot right autonomous cars are always on autopilot but the cars have no theories about why they got cut off or why they're in traffic so they'll never stop paying attention right so I tend to believe you do have deaf theories mental models of other people especially pedestrians cyclists but also with other cars everything you said is like is actually essential to driving driving is a lot more complicated than people realize I think so sort of to push back slightly but cut into traffic right yeah you can't just wait for a gap you have to be somewhat aggressive you'd be surprised how simple a calculation for that is I may be on that particular point but there's a that it may be asked you to push back I would be surprised you know what yeah I'll just say where I stand I would be very surprised but I think it's you might be surprised how complicated it is that I'd say that I tell people's like progress disappoints in the short run the surprises in the long run it's very possible yeah I suspect in 10 years it'll be just like taken for granted yeah but you're probably right now look like it's gonna be a $50 solution that nobody cares about like GPS is like wow GPS is we have satellites in space that tell you where your location is it was a really big deal now everything is the GPS I mean yeah it's true but I do think that systems that involve human behavior are more complicated than we give them credit for so we can do incredible things with technology that don't involve humans but when you look humans are less complicated than people you know frequently obscure I've maybe I stand off right out of large numbers of patterns and just keep doing it over but I can't trust you because you're a human that's something something a human would say but I might my hope was on the point you've made is even if no matter who is right Eve there I'm hoping that there's a lot of things that humans aren't good at that machines are definitely good I like you said attention and things like that well they'll be so much better that the overall picture of safety in autonomy will be obviously cars will be safer even if they're not as good I'm a big believer in safety I mean there are already the current safety systems like cruise control that doesn't let you run into people and lane-keeping there are so many features that you just look at the pareto of accidents and knocking off like 80% of them you know super doable just a wing guard on the autopilot team and the efforts there the it seems to be that there's a very intense scrutiny by the media and the public in terms of safety the pressure the bar but before autonomous vehicles what are your sort of as a person they're working on the hardware and trying to build a system that builds a safe vehicle and so on what was your sense about that pressure is it unfair is it expected of new technology it seems reasonable I was interested I talked to both American and European regulators and I was worried that the regulations would write into the rules technology solutions like modern brake systems imply hydraulic brakes so if you'll read the regulations to meet the letter of the law for brakes it sort of has to be hydraulic right and the regulator said there they're interested in the use cases like a head-on crash an offset crash don't hit pedestrians don't run into people don't leave the road don't run a red light or a stop light they were very much into the scenarios and you know and they had they had all the data about which scenarios injured or killed to most people and for the most part those conversations were like what's the right thing to do to take the next step now elan is very interested also in the benefits of autonomous driving or freeing people's time and attention as well as safety and I think that's also an interesting thing but you know building an autonomous system so they're safe and safer and people seemed since the goals to be tannic seifer's and people having the bar to be safer than people and scrutinizing accidents seems philosophically you know correct so I think that's a good thing what R is is different than the things you've worked at new Intel AMD apple with autopilot chip design and hardware design what are interesting or challenging aspects of building this specialized kind of competing system in the automotive space I mean there's two tricks to building like an automotive computer one is to software our team the machine learning team is developing algorithms that are changing fast so as you're building the the accelerator you have this you know worry or intuition that the algorithms will change enough that the accelerator will be the wrong one right and there's the generic thing which is if you build a really good general-purpose computers hey it's performance is one and then GPU guys will deliver about 5x to performance for the same amount of silicon because instead of discovering parallelism you're given parallelism and then special accelerators get another two to five X on top of a GPU because you say I know the math is always 8-bit integers and two 32-bit accumulators and the operations are the subsets of mathematical possibilities so although you know AI accelerators have a claimed performance benefit over GPUs because in the narrow math space you're nailing the algorithm now you still try to make it programmable but the AI field is changing really fast so there's a you know there's little creative tension era of I want the acceleration afforded by specialization without being over specialized so that the new algorithm is so much more effective that you'd have been better off on a GPU so there's attention there to build a good computer for an application like automotive there's all kinds of sensor inputs and safety processors and a bunch of stuff so one of loans goal is to make it super affordable so every car gets an autopilot computer so some of the recent startups you look at and they have a server in the trunk because they're saying I'm going to build this autopilot computer replaces the driver so their cost budgets ten or twenty thousand dollars and eelain's constraint was I'm gonna put one every in every car whether people buy autonomous driving or not so the cost constraint he had in mind was great right and to hit that you had to think about the system design that's complicated it's it's fun you know it's like it's like it's craftsmen's work like a violin maker right you could say Stradivarius is this incredible thing the musicians are incredible but the guy making the violin you know picked wood and sanded it and then he cut it you know and he glued it and you know and he waited for the right day so that when you put the finish on it didn't you know do something dumb that's craftsmen's work right you may be a genius craftsman because you have the best techniques and you discover a new one but most engineers craftsmen's work and humans really like to do that you know smart humans oh no everybody oh I know I used to I dug ditches when I was in college I got really good at it satisfying yeah so digging ditches is also craft malware yeah of course so so there's an expression called complex mastery behavior so when you're learning something that's fun because you're learning something when you do something that's wrote and simple it's not that satisfying but if the steps that you have to do or complicate it and you're good at them it's satisfying to do them and then if you're intrigued by it all as you're doing them you sometimes learn new things that you can raise your game but Christmas work is good in engineers like engineering is complicated enough that you have to learn a lot of skills and then a lot of what you do is then craftsmen's work which is fun autonomous driving building a very a resource-constrained computer so computer has to be cheap enough that put in every single car that's essentially boils down to craftsmen's work it's saying genius so there's thoughtful decisions and problems to solve and trade-offs to make do you need 10 Cameron ports or 8 you know you're building for the current car or the next one you know how do you do the safety stuff you know there's there's a whole bunch of details but it's fun but it's not like I'm building a new type and they're all networked which has a new mathematics and a new computer at work do you know that that's like there's a there's more invention than that but the rejection to practice once you picked the architecture you look inside and what do you see adders and multipliers and memories and you know the basics so computers is always just this weird set of abstraction layers of ideas and thinking that reduction to practice is transistors and wires and you know pretty basic stuff and that's an interesting phenomena by the way that like factory work like lots of people think factory work is Road assembly stuff I've been on the assembly line like the people work that really liked it it's a really great job it's really complicated putting cars together is hard right and in the cars moving and the parts are moving and sometimes the parts are damaged and you have to coordinate putting all the stuff together and people are good at it they're good at it and I remember one day I went to work and the line was shut down for some reason and then some of the guys sitting around were really bummed because they they had reorganized a bunch of stuff and they were gonna hit a new record for the number of cars built that day and they were all gung ho to do it and these were big tough buggers yeah you know but what they did was complicated and you couldn't do it yeah and I mean well after a while you could but you'd have to work your way up cuz you know like putting a bright what's called the bright stuff at the trim on a car on a moving assembly line where it has to be attached 25 places in a minute and a half is unbelievably complicated and and and human beings can do it's really good I think that's harder than driving a car by the way putting together working working on the factory to smart people can disagree yeah I think drive driving a car will get you in the factory something will see you're not for us humans driving a car is easy I'm saying building a machine that drives a car is not easy ok ok driving a car is easy for humans because we've been evolving for billions of years drive cars yeah no juice the pail if the cars are super cool no now you join the rest of the internet and mocking me ok yeah yeah intrigued by your you know your anthropology yeah it says we have to go dig into that there's some inaccuracies there yes ok but in general what have you learned in terms of thinking about passion craftsmanship tension chaos you know the whole mess of it or what have you learned have taken away from your time working with Elon Musk working at Tesla which is known to be a place of chaos innovation craftsmanship and I really like the way he thought like you think you have an understanding about what first principles of something is and then you talk to you alone about it and you you didn't scratch the surface you know he has a deep belief that no matter what you do is a local maximum right I had a friend he invented a better electric motor and it was like a lot better than what we were using and one day he came by he said you know I'm a little disappointed cuz you know this is really great and you didn't seem that impressed and I said you know and the super intelligent aliens come are they gonna be looking for you like where is he the guy you built the motor yeah probably not you know like like the but doing interesting work that's both innovative and let's say craftsmen's work on the current thing it's really satisfying it's good and and that's cool and then Elon was good taking everything apart and like what's the deep first principle oh no what's really what's really you know you know you know that that you know ability to look at it without assumptions and and how constraints is super wild you know we build rocket ship and using the same car you know everything and that's super fun and he's into it too like when they first landed to SpaceX Rockets at Tesla we had a video projector in the big room and like five hundred people came down and when they landed everybody cheered and some people cried it was so cool alright but how did you do that well it was super hard and then people say well it's chaotic really to get out of all your assumptions you think that's not going to be unbelievably painful and there's Elon tough yeah probably the people look back on it and say boy I'm really happy I had that experience to go take apart that many layers of assumptions sometimes super fun sometimes painful so it could be emotionally and intellectually painful that whole process just stripping away assumptions yeah I imagine 99% of your thought process is protecting your self conception and 98% of that's wrong yeah now you got there math right no you think your feeling when you get back into that one bit that's useful and now you're open and you have the ability to do something different I don't know if I got the math right it might be ninety nine point nine but in 850 imagining it the 50% is hard enough yeah now for a long time I've suspected you could get better look you can think better you can think more clearly you can take things apart and there's lots of examples of that people who do that so any line is an example of that parent or an example says you know if I am I'm fun to talk to certainly I've learned a lot of stuff right well here's the other thing it's like I talk like like I read books and people think oh you read books well no I brought a couple books awake for 55 years well maybe 50 cuz I didn't read learned read tall as H or something and and it turns out when people write books they often take 20 years of their life where they passionately did something reduce it to to 200 pages that's kind of fun and then the goat you go online and you can find out who wrote the best books and who like you know that's kind of Alda so there's this wild selection process and then you can read it and for the most part to understand it and then you can go apply it like I went to one company and I thought I haven't managed much before so I read 20 management books and I started talking to him basically compared to all the VP's running around I'd run night read 19 more management books than anybody else was it even that hard yeah and a half the stuff worked like first time it wasn't even rocket science but at the core of that is questioning the assumptions okay sort of entering the thinking first principles thinking sort of looking at the reality of the situation and using it using that knowledge applying that knowledge so mean yes so I would say my brain has this idea that you can question first assumptions and but I can go days at a time and forget that and you have to kind of like circle back data observation because it is because part Allen gene well it's hard to keep it front and center because you know you're you operate on so many levels all the time and you know getting this done takes priority or you know being happy takes priority or you know screwing around takes priority like like like how you go through life it's complicated yeah and then you remember oh yeah I could really I think first principles so much that's that's tiring you know what you do for a while that's kind of cool so just as the last question your sense from the big picture from the first principles do you think you kind of answered already but do you think autonomous driving something we can solve on a timeline of years so one two three five ten years as opposed to a century yeah definitely just to linger and a little longer where's the confidence coming from is it the fundamentals of the problem the fundamentals of building a hardware and the software as a computational problem understanding ballistics roles topography it seems pretty solvable I mean and you can see this you know like like speech recognition for a long time people are doing you know frequency and domain analysis and and all kinds of stuff and that didn't work for at all right and then they did deep learning about it and it worked great and it took multiple iterations and you know time is driving his way past the frequency analysis point you know use radar don't run into things and the data gathering is going up in the computations going up and the algorithm understanding is going up and there's a whole bunch of problems getting solved like that the data side is really powerful but I disagree with both you and you and I'll tell you and once again as I did before that that when you add human beings into the picture the it's no longer a ballistics problem it's something more complicated but I could be very well proven cars are hardly damped in terms are ready to change like the steering and the steering systems really slow compared to a computer the acceleration of the acceleration is really slow yeah on a certain time scale on a ballistics time scale but human behavior I don't know it yeah I shouldn't say it beans are really slow to weed weirdly we operate you know half a second behind reality nobody really understands that one either it's pretty funny yeah yeah so no I will be with very well could be surprised and I think with the rate of improvement in all aspects I'm both the computed in the the the software and the hardware there's gonna be pleasant surprises all over the place speaking of unpleasant surprises many people have worries about a singularity in the development of AI forgive me for such questions you know what when AI improves exponentially and reaches a point of superhuman level general intelligence you know beyond the point there's no looking back do you share this worry of existential threats from artificial intelligence from computers becoming superhuman level intelligent no not really you know like we already have a very stratified society and then if you look at the whole animal kingdom of capabilities and abilities and interests and you know smart people have their niche and you know normal people have their niche and craftsmen's have their niche and you know animals have their niche I suspect that the domains of interest for things that you know astronomically different like the whole something got 10 times smarter than us and wanted to track us all down because what we like to have coffee at Starbucks like it doesn't seem plausible no is there an existential problem that how do you live in a world where there's something way smarter than you and you you based your kind of self-esteem on being the smartest local person well there's what 0.1% of the population who thinks that because the rest of the populations been dealing with it since they were born so the the breadth of possible experience that can be interesting is really big and you know super intelligence seems likely although we still don't know if we're magical but I suspect we're not and it seems likely that'll create possibilities that are interesting for us and it's its interests will be interesting for that for whatever it is it's not obvious why it's interest would somehow want to fight over some square foot of dirt or you know whatever then you know the usual fears are about so you don't think you'll inherit some of the darker aspects of human nature depends on how you think reality is constructed so for for whatever reasons human beings are and that's a creative tension in opposition with both are good and bad forces like there's lots of philosophical understandings of that right I don't know why that would be different so you think the evils is necessary for the good I mean the tension I don't know about evil but like we live in a competitive world where your good is somebody else's you know evil you know there's there's the malignant part of it but that seems to be self-limiting although occasionally it's it's super horrible but yeah look there's a debate over ideas and some people have different beliefs and that that debate itself is a process so the at arriving at something you know I wouldn't continue yeah just you but you don't think that whole process will leave humans behind in a way that's painful an emotionally painful yes for the one for the point one percent they'll be there why isn't it already painful for a large percentage of the population and it is I mean Society does have a lot of stress in it about the 1% and the bath of this and about to that but you know everybody has a lot of stress in their life about what they find satisfying and and you know know yourself seems to be the proper dictum and pursue something that makes your life meaningful seems proper and there's so many avenues on that like there's so much unexplored space at every single level you know I'm somewhat of my nephew called me a jaded optimist you know so it's there's a beautiful tension that in that label but if you were to look back at your life and could relive a moment a set of moments because there were the happiest times in your life outside of family what would that be I don't want to relive any moments I like that I like that situation where you have some amount of optimism and then the anxiety of the unknown so you love the unknown do you the mystery of it I don't know about the mystery it sure gets your blood pumping what do you think is the meaning of this whole thing of life on this pale blue dot it seems to be what it does like the universe for whatever reason makes atoms which makes us which we do stuff and we figure out things and we explore things and that's just what it is it's not just yeah it is you know Jim I don't think there's a better place to end it it's a huge honor and well super fun thank you so much for talking today all right great thanks for listening to this conversation and thank you to our presenting sponsor cash app downloaded use code Lex podcasts you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and now let me leave you with some words of wisdom from Gordon Moore for everything you try works you aren't trying hard enough thank you for listening and hope to see you next time you |
David Chalmers: The Hard Problem of Consciousness | Lex Fridman Podcast #69 | the following is a conversation with David Chalmers he's a philosopher and cognitive scientist specializing in the areas of philosophy of mind philosophy language and consciousness he's perhaps best known for formulating the hard problem of consciousness which could be stated as why does the feeling which accompanies awareness of sensory information exists at all consciousness is almost entirely mystery many people who worry about AI safety in ethics believe that in some form consciousness can and should be engineered into AI systems of the future so while there's much mystery disagreement and discoveries yet to be made about consciousness these conversations while fundamentally philosophical in nature may nevertheless be very important for engineers of modern AI systems to engage in this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast supported on patreon or simply connect with me on Twitter at lex friedman spelled fri DM a.m. as usual i'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience the show is presented by cash app the number-one finance app in the App Store when you get it you scolex vodcast cash app lets you send money to friends buy Bitcoin and invest in the stock market with as little as $1 brokerage services are provided by kept investing subsidiary of Square and member s IPC since cash app does fractional share trading let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel so big props to the cash app engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market making trading more accessible for new investors and diversification much easier if you get cash app from the App Store or Google Play and use the code lex podcast you'll get $10 and cash app will also donate $10 to first one of my favorite organizations helping to advance robotics and STEM education for young people around the world and now here's my conversation with David Chalmers do you think we're living in a simulation I don't rule it out there's probably going to be a lot of simulations in the history of the cosmos if the simulation is designed well enough it'll be indistinguishable from a non simulated reality and although we could keep searching for evidence that were not in a simulation any of that evidence in principle could be simulated so I think it's a possibility but do you think the thought experiment is interesting or useful to calibrate how we think about the nature of reality yeah I definitely think it's interesting and useful in fact I'm actually writing a book about this right now all about the simulation idea using it to shed light on a whole bunch of philosophical questions so you know the big one is how do we know anything about the external world Descartes said you know maybe you're being fooled by an evil demon who's stimulating your brain and thinking all this stuff is real when in fact it's all made up well the modern the modern version of that is how do you know you're not in a simulation then the thought is if you're in a simulation none of this is real so that's teaching you something to give out about knowledge how do you know about the external world I think there's also really interesting questions about the nature of reality right here I mean if we are in a simulation is all this real is there really a table here is it really a microphone do I really have a body the standard view would be no we don't none of this would be real my view is actually that's wrong and even if we are in a simulation all of this is real that's why I called this reality 2.0 new version of reality different version of reality still reality so what's the difference between quote-unquote real world and the world that we perceive so that we interact with the world to the world by perceiving it it only really exists through the window of our perception system and in our mind so differs means something that's quote-unquote real that exists perhaps without us being there and and the the world a as you perceive it well the world as we perceive it as a very simplified and distorted version of what's going on underneath we already know that from just thinking about science you know you don't see too many obviously quantum mechanical effects and what we what we perceive but we still know quantum mechanics is going on under all things so I like to think the world we perceive is this very kind of simplified picture of colors and shapes existing and in space and so on we know there's a that's what the philosopher Wilfrid Sellars called the manifest image the world as it seems to us we already know underneath all that is a very different scientific image with atoms or quantum wave functions or super strings or whatever the the latest thing is and that's the ultimate scientific reality so I think of the simulation idea as basically another hypothesis about what the ultimate se quasi scientific or metaphysical reality is going on underneath the world with a manifest image the world of the manifest image is this very simple thing that we interact with it's neutral on the underlying stuff of reality science could help tell us about that maybe philosophy could help tell us about that - and if we eventually take the red pill and find out we're in a simulation in my view is that's just another view about what reality is made of you know the philosopher Immanuel Kant said what is the nature of the thing in itself I've got a glass here and it's got all these it appears to me a certain way a certain shape it's liquid it's clear and he said what is the nature of the thing and itself well I think of the simulation idea it's a hypothesis about the nature of the thing in itself it turns out if we're in a simulation the thing in itself nature of this glass okay it's actually a bunch of data structures running on a on a computer in the next universe up yeah that's what people tend to do and they think about simulation they think about our modern computers and somehow trivially crudely just scaled up and but do you think the simulation I mean in order to actually simulate something as complicated as our universe that's made up of molecules and atoms and particles and quarks and maybe even strings all of that requires something just infinitely many orders of magnitude more of scale and complexity do you think we're even able to even like conceptualize what it would take to simulate our universe or does it just slip into this idea that you basically have to build a universe something so big to simulate it is that it just get this into this fuzzy area that's not useful at all yeah well obviously I mean our universe is obviously incredibly complicated and for us within our universe to build a simulation of a universe as complicated as ours is gonna have obvious problems here if the universe is finite there's just no way that's gonna work maybe there's some cute way to make it work if the universe is a is a is infinite maybe an infinite universe could somehow simulate a copy of itself but that's a that's gonna be hard nonetheless just that we are in a simulation I think there's no particular reason why we have to think the simulating universe has to be anything like ours you've said before that it might be so you can think of it and Turtles all the way down you could think of the simulating universe different than ours but we ourselves could also create another simulating universe so you said there could be these kind of levels of universes and you've also mentioned this hilarious idea maybe tongue-in-cheek maybe not that there may be simulations within simulations arbitrarily stacked levels and that there may be that we may be in level 42 oh yeah along those stacks referencing Hitchhiker's Guide to the universe if we're indeed in a simulation within a simulation at level 42 what do you think level zero looks like there right would expect that zero is truly enormous I mean not just if it's finite it's some extraordinarily large finite capacity much more likely its infinite maybe it's a maybe it's got something very high etcetera to cardinalities that enables it to support just any number of any number of simulations so high degree of infinity at level zero slight little slightly smaller degree of infinity at at level one so by the time you get down to us at level 42 maybe plenty of room for lots of simulations of finite capacity if the top universe is only a small finite capacity then obviously that's going to put very very serious limits on how many simulations are going to be able to be able to get running so I think we can certainly confidently say that if we hurt level 42 then the top level is pretty pretty damn big so it gets more and more constrained as we get down levels more and more simplified and constrained and limited resources and you know we still have plenty of capacity here what was it a Fineman 30 said there's plenty of room at the bottom you know we're still you know we're still a number of levels above the degree where there's room for fundamental computing physical computing capacity quantum computing capacity at the bottom level so we got plenty of room to play with and make we probably have plenty of room for simulations of pretty sophisticated universes perhaps none as complicated as our universe unless our universes is infinite but still it's very least for pretty serious finite universes but maybe universes somewhat simpler than ours unless of course we're prepared to take certain shortcuts in the simulation which might then increase their capacity significantly do you think the the human mind us people in terms of the complexity of simulation as at the height of what the simulation might be able to achieve like if you look at incredible entities that could be created in this universe of ours do you have an intuition about how incredible human beings are on that scale I think we're pretty impressive we're not that impressive are we above average I mean I think high human beings are a certain point in the scale of intelligence which made many things possible you know you get through evolution through single-cell organisms through fish and mammals and primates and something happens once you get to human beings we've just reached that level where we get to develop language we get to develop certain kinds of culture or maybe get to develop certain kinds of collective thinking that has enabled all this amazing stuff to happen science and literature and engineering and culture and and so on so we had just at the beginning of that on the evolutionary threshold it's kind of like we just got there you know who knows a few thousands or tens of thousands of years ago so we're probably just at the very beginning for what's possible there so I'm inclined to think among the scale of intelligent beings we're somewhere very near the bottom I would expect that for example if we're in a if we're in a simulation then the simulators who created a sir got the capacity to be far more sophisticated for at level 42 who knows what the ones at level zero I like it's also possible that this is the epitome of what is possible to achieve so we as human beings see ourselves maybe as flawed see all the constraints all the limitations but maybe that's the magical the beautiful thing maybe those limitations are the essential elements for an interesting sort of that edge of chaos that interesting existence that if you make us much more intelligent if if you make us much more powerful in any kind of dimension of performance maybe you lose something fundamental that makes life worth living so you kind of have this optimistic view of where this little baby that and there's so much growth and potential but this could also be it well this is the most amazing thing is us maybe what you're saying is consistent with what I'm saying I mean we can still have levels of intelligence far beyond us but maybe those levels of intelligence on your view would be kind of boring and you know we get kind of get so good at everything that life suddenly becomes uni-dimensional so we're just in happening in happening this once part of like maximal romanticism and history of evolution yes you get to humans and it's like yeah and then years to come our super intelligent descendents are gonna look back at us and say those were the days when and they just hit the point of inflection and life was interesting I am an optimist so I'd like to think that you know if there is super intelligence somewhere in the in the future they'll figure out how to make life super interesting and super romantic when you know what they're gonna do it so what they're gonna do is they realize how boring life is when you're super intelligent so they created a new level of a simulation and sort of live through the things they've created by watching them stumble about in their flawed ways so maybe that's so you create a new level of a simulation every time you get really bored with how smart and this would be kind of sad though because it would show the peak of their existence would be like watching simulations for entertainment by saying the peak of our existence now is Netflix know it's alright a flipside of that could be the peak of our existence for many people having children and watching them grow hmm that becomes very meaningful okay so create a simulation it's like creating a family creating like well any kind of creation is uh it's kind of a powerful act dealing is easier to simulate the mind or the universe so I've heard several people including Nick Bostrom think about ideas of you know maybe you don't need to simulate the universe you can just simulate the human mind or in general just the distinction between simulating this the entirety of it the entirety the physical world or just simulating the mind which one do you see is more challenging well I think in some sense the answer is is obvious it has to be simpler to simply simulate the mind than to simulate the universe because the mind is part of the universe and in order to fully simulate the universe you're gonna have to simulate the mind's eye just by talking about partial simulations and I guess the question is which comes first there's a mind come before the universe or does the universe come before the mind so the mind could just be an emergent phenomena in this universe so simulation is a is an interesting thing that you know it's it's not like creating a simulation perhaps requires you to program every single thing that happens in it it's just defining a set of initial conditions and rules based on which could behaves mm-hmm simulating the mind requires you to have a little bit more we're now in a little bit of a crazy lab but it requires you to understand the fundamentals of cognition perhaps of consciousness of perception of everything like that that's me that's not created through some kind of emergence from basic physics laws but more requires you to actually understand the fundamentals of the mind how about if we said to simulate the brain the brain rather than rather than the mind the brain is just a big physical system the universe is a giant physical system I simulate the universe at the very least you're going to have to simulate the brains as well as all the other physical systems within it and you know it's not obvious there's that the problems are any worse for the for the brain than for its particularly complex physical system but if we can simulate arbitrary physical systems we can simulate brains there is this further question of whether when you simulate a brain will that bring along all the features of the mind with it like will you get my consciousness will you get thinking will you get free will and so on and that's that's something philosophers ever have argued over for four years my own view is if you see if you simulate the brain well enough that will also simulate the mind but yeah there's plenty of people who would say no you'd merely get like a zombie system a simulation of a brain without any true consciousness but for you you put together a brain the consciousness comes with it arise yeah I don't think it's obvious that's your intuition my view is roughly that yeah what is responsible for consciousness it's in the patents of information processing and so on rather than say the biology that it's made of there's certainly plenty of people out there who think consciousness has to be say biological so if you merely replicate the patterns of information processing in a non-biological substrate you'll miss what's crucial for consciousness I mean I think just don't think there's any particular reason to think that biology is special here you can imagine substituting the biology for non biological systems a silicon circuits that play the same role the behavior will continue to be the same and you know I think just the key about what is the true I when I think about the connection the isomorphisms between consciousness and the brain the deepest connections to me seemed to connect consciousness to patterns of information processing not specific biology so I at least adopted as my working hypothesis that basically it's the computation and the information that matters for consciousness the same time we don't understand consciousness it should be wrong so the computation the flow the processing manipulation of information the the process is where the consciousness the software is where the consciousness comes from not the hardware roughly the software yeah the patterns of information processing at least in the in the hardware which we could view as as software it may not be some of you just like program and load and erase and so on and the way we can with ordinary software but it's something at the level of information processing rather than have a level of implementation so on that what do you think of the experience of self just the experience of the world in a virtual world in virtual reality is it possible that we can create sort of offsprings of our consciousness by existing in a virtual world long enough so yeah ok can we be conscious in in the same kind of deep way that we are in this real world by hanging out in a virtual world yeah well the kind of virtual worlds we have now or you know or interesting but limited in certain ways in particular they relying on us having a brain and so on which is outside the virtual world maybe I'll strap on my VR headset I'll just hang out in a in a virtual world on a on a screen but my brain and then the physical my physical environment might be simulated if I'm in a virtual world but right now there's no attempt to simulate my brain I might Hank there might be some non player characters and these are in these virtual worlds that have simulated cognitive systems of certain kinds that dictate their behavior but you know mostly they're pretty simple right now I mean some people are trying to combine put a bit of AI and then non-player characters to make them to make them them smarter but for now inside virtual world the actual thinking is interestingly distinct from the physics of those virtual worlds in a way actually I like to think this is kind of reminiscent of the way that Descartes thought our physical world was there's physics and there's the mind and they're separate now we now we think the mind is somehow somehow connected to physics pretty deeply but in these virtual worlds there's a physics of a virtual world and then there's this brain which is totally outside the virtual world that controls it and interacts if when anyone anyone exercises agency in a video game and you know that's actually somebody outside the virtual world moving a controller controlling the interaction of things inside the virtual world so right now in virtual worlds the mind is somehow outside the world but you could imagine in the future once we get once we have developed serious AI artificial general intelligence and so on then we could come to virtual worlds which have enough sophistication you could actually simulate a brain or have a genuine AGI which were then presumably be able to act in equally sophisticated ways maybe even more sophisticated ways inside the virtual world to how it might in the physical world and then the question is going to come along that would be kind of a VR into a virtual world internal intelligence and then the question is could they have consciousness experience intelligence free will yes all the things that we have and again my view is I don't see why not to linger in a little bit I find virtual reality really incredibly powerful just even the crude virtual reality we have now perhaps there's a there's a psychological effects that's makes some people more amenable to virtual worlds and others but I find myself wanting to stay in virtual worlds for free yes with a headset or on a desktop no with a headset really interesting because I I am totally addicted yet using the internet and things on a on a desktop but when it comes to VR for the headset I don't typically use it for more than 10 or 20 minutes there's something just slightly aversive about it I find so I don't right now even though I have oculus rift an oculus quest an HTC vive and Samsung listen that I want to stay in now for extended periods use you actually find yourself the something about him it's a both a combination of just imagination and considering the possibilities of where this goes in in the future it feels like I want to almost prepare my brain for like it I want to explore sort of Disneyland when it's first being built in the early days yeah and it feels like I'm walking around almost imagining the possibilities and something through that process allows my mind to really enter into that world but you say that the brain is external to that virtual world it is strictly speaking true but if you're in VR and you do brain surgery on an avatar and you can open up that skull what are you gonna find sorry nothing there nothing the brain is elsewhere you don't think it's possible to kind of separate them and I don't mean in a sense like decart like a hard separation but basically do you think it's possible with the brain outside of the virtual grid when you're wearing a headset create a new consciousness for prolonged periods of time really feel like really experience forget that human brain is outside so this is okay this is gonna be the case where the brain is still outside still outside but could living in the VR I mean I mean we already find this right with video games exactly completely immersive and you get taken up by living in those worlds and it becomes your reality for a while so they're not completely immersive it's very immersive you don't you don't forget the external world no exactly so if that's what I'm asking yeah it's almost possible to really forget the external world really really immerse yourself what to forget completely why would we forget you know we got pretty good memories maybe you can stop paying attention to the external world but you know that this already happens a lot I go to work and maybe I'm not paying attention to my home life if I go to s I go to a movie and I'm immersed in that so that degree of emotion absolutely but we still have the capacity to remember it to completely forget the external world I'm thinking that would probably take some I don't know some pretty serious drugs or something to make your s but it's to make your brain do that possible so I mean I guess I'm getting at is consciousness a truly a property that's tied to the the physical brain or can it can you create sort of different offspring copies of consciousness is based on the worlds that you enter well the way we're doing it now at least with a standard VR there's just one brain interact for the physical world plays a video game puts on a video headset interacts with this virtual world and I think we typically say there's one consciousness here that nonetheless undergoes different environments takes on different characters you know in different environments this is already something that happens in the non virtual world you know I might interact one way in my home life work life social life and so on so at the very least that will happen in a in a virtual world very naturally people might people have very people sometimes adopt the character of avatars very different from themselves maybe even a different gender or different race different social background so that much is certainly possible I would see that as a single consciousness is singing on different personas if you want literal splitting of consciousness into multiple copies I think it's gonna take something more radical than that like maybe you can run different simulations of your brain in different realities and then expose them to different histories and then you know you just put yourself into 10 different simulated copies which then undergo different environments and then ultimately do become 10 very different consciousness maybe that could happen but now we're not talking about something that's possible in the near term we're gonna have to have brain simulations and AGI for that to happen got it so before any of that happens it's fundamentally you see it as a singular consciousness even though it's experiencing different environments which are not it's still connected to same set of memories same set of experiences and therefore one sort of joint conscious system yeah or at least no more multiple than the kind of multiple consciousness that we get from and have inhabiting different environments and in a non virtual world so you said as a child you were a music color Senna famously synesthete so we're songs had colors for you so what songs had what colors you know this is funny um I didn't paint much attention to this at the time but I've listened to a piece of music and I'd get some kind of imagery of a of a kind of a kind of color of the wid thing is mostly they were okay murky dark greens and olive browns and the colors went all that interesting I don't know what the reason is I mean my theory is that maybe it's like different cords and tones provided different colors and the old tended to get mixed together into these somewhat uninteresting browns and greens but every now and then there'd be something that had a really pure color so this just a few that I did I remember it was a here there and everywhere by the Beatles was bright red and has this you know very distinctive tonality and it's chord structure at the at the beginnings of that right red it was a song by the Alan Parsons Project called ammonia Avenue that was it was kind of a pure a pure blue anyway I've got no idea how would this happen didn't even pay that much attention until it went away when I was about 20 this synesthesia often goes away so is it purely just the perception of a particular color or was there a positive or negative experience with it like was blue associate with a positive and red with a negative or is it simply the perception of color associate with some characteristic of the song for me I don't remember a lot of association with with emotion or what the value was just this kind of weird and interesting fact I mean at the beginning I thought this was something that happened to everyone songs have colors maybe I mentioned it once or twice and people said no no ed it was like I thought was kind of cool when there was one that had one of these especially pure colors but only much later once I became a grad student thinking about the mind that I read about this phenomenon called synesthesia it's like hey that's what I had and now I occasionally talk about it in my classes in intro class and still happens sometimes a student comes up and says hey I have that I never knew about that I never knew it had a name you said they want to run away at age 20 or so and the you have a journal entry from around and saying songs don't have colors anymore what happened what happened yeah I was definitely sad that it was gone in retrospect there's like hey that's cool the colors have gone yeah do you can you think about that for a little bit do you miss those experiences because it's a fundamentally different sets of experiences that you no longer have mm-hmm or deed or is it just a nice thing to have had you don't see them as that fundamentally different than you visiting a new country and experiencing new environments I guess for me when I had these experiences they were somewhat marginal they were like a little bonus kind of experience I know there are people have much more serious forms of synesthesia than this for whom it's absolutely central to their lives I know people who when they experience new people they have colors maybe they have tastes and so on every time they see writing it has it has colors some people whenever they hear music it's got a it's got a certain really rich color pattern and you know for some synesthetes it's absolutely central I think if they lost it they'd be devastated again for me it was a very very mild form of synesthesia it's like yeah it's like those interesting experiences yeah you know you might get under different altered states of consciousness and and so on it's kind of cool but you know not necessarily the single most important experiences in your life so let's try to go to the very simplest question the events are bring you time but perhaps the simplest things can help us reveal even in time some some new ideas so what in your view is consciousness what is qualia what is the hard problem of consciousness consciousness I mean the word has used many ways but the kind of consciousness that I'm interested in is basically subjective experience what it feels like from the inside to be a human being or any other conscious being I mean there's something it's like to be me right now I have visual images that I am experiencing I'm hearing my voice I've got maybe some emotional tone I've got a stream of thoughts running through my head these are all things that I experience from the first-person point of view of sometimes called this the inner movie in the mind it's not a perfect it's not a perfect metaphor it's not like a movie in every ways and in every way and it's very rich but yeah it's just direct subjective experience and I call that consciousness or sometimes philosophers use the word qualia which you suggested people tend to use the word qualia for things like the qualities of things like colors redness the experience of redness versus the experience of greenness the experience of one taste or one smell versus another the experience of the quality of pain and a lot of consciousness is the experience of those of those those qualities of consciousness is big the entirety of any kinds of extraneous of thinking is not obviously qualia it's not like specific qualities like redness or greenness but still I'm thinking about my hometown I'm thinking about what I'm gonna do later on maybe there's still something running through my my head which is subjective experience maybe it goes beyond those qualities or qualia philosophers sometimes use the word phenomenal consciousness for consciousness in this sense I mean people also talk about access consciousness being able to access information and your mind reflective consciousness being able to think about yourself but it looks like the really mysterious one the one that really gets people going is phenomenal consciousness the fact that all this the fact that the subjective experience and all this feels like something at all and then the hard problem is how is it that why is it that there is phenomenal consciousness at all and how is it that physical processes in a brain could give you subjective experience it looks like try on the face of it you have all this big complicated physical system in a brain running and without a given subjective experience at all and yet we do have subjective experience so the hard problem is just explained that explain how that comes about we haven't been able to build machines work a red light goes on that says it's not conscious so how does how do we actually create that or how do humans do it and how do we ourselves do it we do every now and then create machines that can do this you know we create babies yes that our that our conscious take out these brains asbestos brain does produce consciousness but even me even though we can't create it we still don't understand when it happens maybe eventually we'll be able to create machines which as a matter of fact AI machines which as a matter of fact our conscious but that won't necessarily make the hard problem go away any more than it does with babies because we still want to know how and why is it that these processes give you consciousness you know you just made me realize for a second maybe it's a totally dumb realization but nevertheless that it's a useful way to think about the creation consciousness is looking at a baby so that there's a certain point at which that baby is not conscious mm-hmm something sort of the baby starts from maybe I don't I don't know from a few cells right there's a certain point at which it becomes consciousness arrives it's conscious of course we can't know exactly that line but that's a useful idea that we do we do create consciousness again a really dumb thing for me to say but it not until now that I realized we do engineer consciousness we we get to watch the process happen we don't know which point it happens or where it is but you know we do see the birth of consciousness yeah I mean there's a question of course is whether babies are conscious when they're born and it used to be it seems at least some people thought they weren't which is why they didn't give anesthetics to newborn babies when they circumcised them and so now people think oh that's you know be incredibly cruel yeah of course of course babies feel pain and now the dominant view is that the babies can feel pain I actually my partner of Claudia works on this whole issue of whether there's consciousness and babies and of what kind and she certainly thinks that newborn babies you know come into the world with some degree of consciousness because then you could just extend the question backwards to fetuses suddenly are too politically controversial exactly territory but you know there the question also arises in the animal kingdom you know what where does consciousness start or stop is there a line in the animal kingdom where you know the first conscious organisms aren't it's interesting over time people are becoming more and more liberal about ascribing consciousness to animals people used to think maybe only mammals could be conscious now most people seem to think show a fish are conscious they can feel pain and now we're arguing over insects you'll find people out there who say plants have some degree of consciousness so you know who knows where it's gonna end the far end of this chain is the view that every physical system has some degree of consciousness philosophers call that pen sarcasm you know I take that view I mean that's a fascinating way to view reality so you could talk about if you can linger on pan psychism for a little bit what what does it mean it's not just plants are conscious I mean it's that consciousness is a fundament the fabric of reality what does that mean to you how do we supposed to think about that well we're used to the idea that some things in the world are fundamental right in physics like why we take things like space or time or space-time mass charge as fundamental properties of the universe you don't reduce them to something simpler you take those for granted you've got some laws that connect them here is how mass in space and time evolved theories like relativity or quantum mechanics or some future theory that will unify them both but everyone says you got to take some things as fundamental and if you can't explain one thing in terms of the previous fundamental things you have to expand maybe something like this happen with Maxwell ended up with fundamental principles of electromagnetism and took charge as fundamental because turned out that was the best way to explain it so I at least take seriously the possibility something like that could happen with consciousness take it as a fundamental property like space time and mass instead of trying to explain consciousness wholly in terms of the evolution of space-time and and mass and so on take it as a primitive and then connected to everything else by some fundamental laws because I mean there's basic there's this basic problem that the physics we have now looks great for solving the easy problems of consciousness which are all about behavior strike they give us a complicated structure and dynamics they tell us how things are going to behave what kind of observable behavior they're produced which is great for the problems of explaining how we walk and how we talk and so on those are the easy problems of consciousness but the hard problem was this problem about subjective experience just doesn't look like that kind of problem about structure or dynamics how things behave so it's hard to see existing physics is going to give you a full explanation of that certainly trying to get a physics view of consciousness yes there there has to be a connecting point and it could be at the very exome attic at the very beginning level but first of all there's a crazy idea that sort of everything has properties of consciousness there's a would at that point the word consciousness is already beyond the region of our current understanding like far because it's so far from at least for me maybe you can correct me it's far from the experience and the experiences that we have that I have as a human being it to say that everything is cautious that means that means there that basically another way to put that if if that's true then we understand almost nothing about that ask fundamental aspect of the world how do you feel about saying an ant is conscious to get the same reaction to the head or is that something you can understand I can understand ant I can't understand an atom applying chol plant so I'm comfortable with living things on earth mm-hmm being cautious because there's some kind of agency where there's similar size to me and they can be born and they can die and that is understandable intuitively of course you anthropomorphize you put yourself in the place of the plant but I can understand it I mean I'm I'm not like I don't believe actually that plants are conscious of that plant suffer but I can understand that kind of belief that kind of idea how do you feel how do you feel about robots like the kind of robots we have now if I told you like that you know a Roomba at some degree of consciousness or some you know deep neural network I could understand that a Roomba has coasters I just had spent all day at iRobot I and I mean I personally love robots and have a deep connection with robots so I can I also probably enterpreneur Faiz them there's something about the physical object so this difference than a neural network then you'll network running a software to me the physical object something about the human experience allows me to really see that physical object is an entity and if it moves and moves in a way that it there's a like I didn't program it where it feels that it's acting based on its own perception and yes self awareness and consciousness even if it's a Roomba then you start to assign it some agency some consciousness so but to say that Pan psychism that conscious is a fundamental property of reality is a much bigger statement mm-hmm that it it's like Turtles all the way - yeah every is it doesn't end and the whole thing is so like how I know it's full mystery but if you can linger on it and I go how would it how do you think about reality if consciousness is a fundamental part of its fabric the way you get there some thinking can we explain consciousness given the existing fundamentals and then if you current is at least right now it looks like then you've got to add something it doesn't follow that you have to add consciousness here's another interesting possibility is we'll add something else that's called a proto consciousness or x-ray and then it turns out space-time mass plus X will somehow collectively give you the possibility for for consciousness we don't rule out that view either I call that pan proto psychism because maybe there's a some other property proto consciousness at the bottom level and if you can't imagine there's actually genuine consciousness at the bottom level I think we should be open to the idea there's this other thing X maybe we can't imagine this somehow gives you consciousness but if we are not playing along with the idea that there really is genuine consciousness at the level of course this is gonna be way out and speculative but you know at least in say if it was classical physics then we'd have to end up saying well every little half every with you a bunch of particles in space-time each of these particles has some kind of consciousness whose structure mirrors maybe their physical properties like its mass charge its velocity and so on the structure of its consciousness would roughly correspond to that and the physical interactions between particles I mean there's this old worried about physics I mentioned this before in this issue about the manifest image we don't really find out about the intrinsic nature of things physics tells us about how a particle relates to other particles and interacts it doesn't tell us about what the particle is in itself that was can't sing in itself so here's a view the nature in itself of a particle is something mental a particle is actually a conscious a little conscious subject with with properties of its consciousness to correspond to its physical properties the laws of physics are actually ultimately relating these properties of conscious subjects on this view a Newtonian world actually would be a vast collection of little conscious subjects at the bottom level way way simpler than we are without free will or rationality or anything like that but that's what the universe would be like of course that's a vastly speculative you know what no particular reason think is correct furthermore non Newtonian physics say a quantum mechanical wave function suddenly a sort of difference on a vast collection of conscious subjects may be the is ultimately one big wave function for the whole universe corresponding to that might be something more like as a single conscious mind whose structure corresponds to the structure of the wave function people sometimes call this cosmos sarcasm and now of course we're in the realm of extremely speculative philosophy there's no direct evidence for this but yeah but if you want a picture of what that universe would be like think yeah giant cosmic mind with enough richness and structure among it to replicate all the structure of physics I think there I am at the level of particles and with quantum mechanics at the level of the wavefunction it's a it's kind of an exciting beautiful possibility of course way out of reach of physics currently it is interesting that some neuroscientists our act begins to take pen psychism seriously you find consciousness even in very in very simple systems so for example the integrated information theory of consciousness a lot of neuroscientists are taking seriously actually I just got this new book by Christophe cook just came in the feeling of life itself my consciousness is widespread but can't be computed he likes he basically endorses a pen Sarkis view where you get consciousness with the degree of information processing or integrated information processing in a simple in a system and even very very simple systems like a couple of particles will have some degree of this so he ends up with some degree of consciousness in all matter and the claim is that this theory can actually explain a bunch of stuff about the connection between the brain and consciousness now that's very controversial I think it's very very early days in the science of consciousness it's interesting the it's not just philosophy that might lead you in this direction but there are ways of thinking quasi scientifically that leads you there too but maybe different than pen psychism what do you think so Allen Watts has this quote I'd like to ask you about the quote is through our eyes the universe is perceiving itself through our ears universe is listening to its harmonies we are the witnesses to which the universe becomes conscious of his glory of its magnificence so that's not pants psychism do you think that we are essentially the tools the senses the universe created to be conscious of itself it's an interesting idea of course if you went for the giant cosmic mind view then the universe was conscious all along it didn't need us we're just little components of the universal consciousness likewise if you believe in penstock ism then there was some little degree of consciousness at the bottom level all along and we were just more complex form of consciousness so I think maybe the quote you mentioned works better if you're not a pen Sarkis you're not a Cosmo Sarkis do you think consciousness just exists at this at this intermediate level and of course that's the Orthodox view that you would say is the the common useless is your own view with pan psychism a rarer view I think it's generally regarded certainly as a speculative view held by a fairly small minority of at least theorists philosophers most philosophers and most scientists who think about consciousness are not pants artists there's been a bit of a movement in that direction the last 10 years or so it seems to be quite popular especially among the younger generation but it's still very definitely a minority view many people think is totally batshit crazy to use the technical term the philosophical ter so the Orthodox view I think is still consciousness is something that humans have and some good number of non-human animals have and maybe a eyes might have one day but it's restricted on that view then there was no consciousness at the start of universe there may be none at the end but it is this thing which happened at some point in the history of the universe consciousness developed and yes it's on that's a very amazing event on this view because many people are inclined to think consciousness is what somehow gives meaning to our lives without consciousness there'd be no meaning no true value no good versus bad and so on so with the advent of consciousness suddenly the universe went from meaningless to somehow meaningful why did this happen I guess the quote you mentioned was somehow this was somehow destined to happen because the universe needed to have consciousness within it to have value and have meaning and maybe you could combine that with a theistic view or a teleological view the universe was inexorably evolving towards consciousness actually my colleague here at NYU Tom Nagel wrote a book called mind and cosmos a few years ago where we are for this teleological view of evolution toward consciousness saying this let the problems for Darwinism it's got a mountain you know so it's very very controversial most people didn't agree I don't myself agree with this teleological view but it is a it's at least a beautiful speculative view love the of the cosmos what do you think people experience what do they seek when they believe in God from this kind of perspective mm-hmm I'm not an expert on thinking about God and religion I'm not myself religious at all when people sort of pray communicate with God word at which whatever form I'm not speaking to sort of the practices and the rituals non religion I mean the actual experience of that people really have a deep connection of God in some cases mhm what do you think that experience is it's so common at least throughout the history of civilization that it seems like we seek that at the very least it's an interesting conscious experience that people have when they experience religious or or prayer and so on neuroscientists have tried to examine what bits of the brain are active and so on but yeah that is this deeper question of what is what are people looking for when they're doing this and like I said but no real expertise on this but it does seem the one thing people are after is a sense of meaning and value a sense of connection to something greater than themselves that will give their lives meaning and value and maybe the thought is if there is a God and God somehow is a universal consciousness who has invested this universe with meaning and some our connection to God might give your life meaning I got so I can kind of see the see the attractions of that but it still makes me wonder why is it exactly that a universal consciousness you know God would be needed to give the lot to give the world if I mean if universal consciousness can give the world meaning why can't local consciousness give the world meaning to so I think my consciousness gives my world is the meaning is the origin of meaning vary your world yeah I experience things as good or bad happy sad interesting important so my consciousness invests this world with meaning without any consciousness maybe it would be a bleak meaningless universe but I don't see why I need someone else's consciousness or even God's consciousness to give this this universe meaning here we are local creatures with our own subjective experiences I think we can give the universe meaning ourselves so I mean maybe just some people that feels inadequate yeah our own local consciousness is somehow too puny and insignificant to invest any of this with cosmic significance and maybe God gives you a sense of cosmic significance but I'm just speculating here so the you know it's a really interesting idea that consciousness is the thing that makes life meaningful if you could maybe just just briefly explore that for a second so I suspect just from listening to you know you mean in an almost trivial sense just the day-to-day experiences of life have because of you attached identity to it mm-hmm they become oh I guess I want to ask something I I would always wanted to ask College it Rock world renowned philosopher what is the meaning of life but I suspect you don't mean consciousness gives any kind of greater meaning to it all yeah and more to day-to-day but is there greater meaning to it all I think life has meaning for us because we are conscious so without consciousness no meaning consciousness invests our life with meaning so consciousness is the source of my view of the meaning of life but I wouldn't say consciousness self is the meaning of life I'd say what's meaningful in life is basically what we find meaningful what we experience as meaningful so if you find meaning and fulfillment and value and say intellectual work like understanding then that's your that's a very significant part of the meaning of life for you if you find it in social connections or in raising a family and that's the meaning of life for you the meaning kind of comes from what you value as a conscious creature so I think there's no you on this view there's no universal solution you know Universal answer to the question what is the meaning of life the meaning of life is where you find it as a conscious creature but it's consciousness that somehow makes value possible experiencing some things as good or as bad or as meaningful something comes from within consciousness so you think consciousness is a crucial component ingredient of having given assigning value to things I mean it's kind of a fairly strong intuition that without consciousness there wouldn't really be any value if we just had a purely a universe of unconscious creatures would anything be better or worse than anything else certainly when it comes to ethical dilemmas you know you know about the older the old trolley problem do you you kill one person or do you switch to the other track to kill kill Fievel I got a variant on this their zombie trolley problem where there's one conscious being on on one track and five humanoid zombies let's make them robots yeah who are not who are not conscious on the on the other track do you given that choice you kill the one conscious being or the five unconscious robots most people have a fairly clear intuition here yeah kill the kill the unconscious beings because they basically they don't have a meaningful life they're not really persons conscious beings of course we don't have good intuition about something like an unconscious being so in philosophical terms you refer to as Azzam mm-hmm it's a useful thought experiment construction in philosophical terms but we don't yet have them so that's kind of what we may be able to create with robots and I don't necessarily know what that even means yes merely hypothetical for now they're just a thought experiment they may never be possible I mean the extreme case of a zombie is a being which is physically functionally behaviorally identical to me but not conscious that's a mirror I don't think that could ever be built in this universe the question is just could we does that hypothetically make sense that's kind of a useful contrast class to raise questions like why aren't we zombies how does it come about that we're conscious and we're not like that but there were less extreme versions of this like robots which are maybe not physically identical to us maybe not even functionally identical to us maybe they've got a different architecture but they can do a lot of sophisticated things maybe carry on a conversation but they're not conscious that's not so far out we've got simple computer systems these tending in that direction now and presumably this is gonna get more and more sophisticated over years to come where we may have some pretty it's least quite straightforward to conceive of some pretty sophisticated robot systems that can use language and be fairly high functioning without consciousness at all then I stipulate that I mean we've cost there's this tricky question of how you would know whether they're conscious but let's say we've somehow solved that and we know that these high-functioning robots aren't conscious then the question is do they have moral status does it matter how we treat them like what is moral status means does basically society can they suffer doesn't matter how we treat them I would for example if we if I mistreat this glass this cup by uh by shattering it then that's bad well why is it bad that was kind of make a mess it's gonna be annoying for me in my partner and so it's not bad for the cup no one would say the cup itself has moral state hey you you heard the cup and that's that's doing it a moral harm likewise plants will again if they're not conscious most people think if by operating a plant you're not harming it but if a being is conscious on the other hand then you are harming it so Siri or I dare not say the name of Alexa anyway we're so we don't think we're we're morally harming Alexa by turning her off or disconnecting her or even destroying her whether it's the system or the or the underlying software system because we don't really think she's conscious on the other hand you moved to it like the the disembodied being in the moving in the movie her Samantha I guess she was kind of presented as conscious and then if you if you destroyed her you'd certainly be committing a serious harm so I think how strong senses if a being is conscious and can undergo subjective experiences that are matters morally how we treat them so if a robot is conscious it matters but if a robot is not conscious then they basically just meet or a machine and it and it and it doesn't matter so I think at least maybe how we think about this stuff is fundamentally wrong but I think a lot of people to think about this stuff seriously including people to think about say the moral treatment of animals and so on come to the view that consciousness is ultimately kind of the line between systems that where we have to take them into account in thinking morally about how we act and systems for which we don't and I think I've seen you the writer talked about the demonstration of consciousness from a system like that from a system like Alex or a conversational agent that is what you would be looking for it's kind of at the very basic level for the system to have an awareness that I'm just a program and yet why do I experience this or not to have that experience but to communicate that to you so that's what us humans would sound like if you all of a sudden woke up one day like Kafka right in the body of a bug or something but in a computer you all sudden realize you don't have a body and yet you would feel what you're feeling you would probably say those kinds of things mm-hmm so do you think a system essentially becomes conscious by convincing us that it's conscious hmm through the words that I just mentioned so by being confused about the fact that why am I having these experiences well so basically I don't think this is what makes your conscious but I do think being puzzled about consciousness is a very good sign that a system is conscious so if I encountered a robot that actually seemed to be genuinely puzzled by its own mental states and saying yeah I have all these weird experiences and I don't see how to explain them I know I'm a just a set of silicon circuits but I don't see how that would give you my consciousness I would at least take that as some evidence that there's some consciousness going on there I don't think a system needs to be puzzled about consciousness to be conscious many people are puzzled by their consciousness animals don't seem to be puzzled at all I still think they're conscious but I think that's a requirement on consciousness but I do think if we're looking for signs for consciousness say in AI systems one of the things will help convince me that an AI system is consciousness if it shows signs of it if it shows signs of introspectively recognizing something like consciousness and finding this philosophically puzzling and the way that the way that that we do the incision interesting thought though because a lot of people sort of would at the shower level criticize the Turing test for language that it's essentially what I heard like Dan Dennett criticized it in this kind of way which is it's really puts a lot of emphasis on lying yeah and being able to being able to imitate human beings yeah there's this a there's this cartoon of the AI system studying for the Turing test it's gotta be this book called talk like a human like man I don't have to waste my time learning how to imitate humans maybe the AI system is gonna be way beyond the hard problem of consciousness and it's gotta be this thing why do I need to waste my time pretending that I recognize the hard problem of consciousness - in order for people to recognize me as conscious yeah it just feels like I guess the question is do you think there's a we can never really create a test for consciousness because it feels like we're very human centric and so the only way we would be convinced that something is consciousness but is basically the thing demonstrates the illusion of consciousness that we can never really know whether it's conscious or not and in fact that almost feels like it doesn't matter them or does it still matter to you that something is conscious or it demonstrates consciousness you still see that fundamental distinction I think a lot of people whether our system is conscious or not matters hugely for many things like how we treat it cannot suffer and so on but still that leaves open the question how can we ever know and it's true that it's awfully hard to see how we can know for sure whether a system is conscious I suspect that sociologically the thing that's going to convince us that the system is conscious is in part things like social interaction conversation and so on where they seem to be conscious they talk about their conscious state so I just talked about being happy or sad or finding things meaningful or being in pain that will tend to convince us if we don't the system genuinely seems to be conscious we don't treat it as such eventually it's gonna seem like a strange form of racism or speciesism or somehow not to acknowledge them and actually we believe that by the way I believe that there is going to be something akin to the civil rights movement but for robots mm-hmm I think the moment you have a Roomba say please don't kick me that hurts just say it yeah I think they will fundamentally change the fabric of our society I think you're probably right although it's gonna be very tricky because just say where we've got the technology where these conscious beings can just be moderated and multiplied by the thousands by flicking a switch so and the legal status is gonna be different but ultimately the moral status ought to be the same and yeah the civil rights issue is gonna be a huge mess so if one day somebody clones you another very real possibility in fact I find the conversation between two copies of David Chalmers quite interesting every thought he's not making any sense so what do you think he would be cautious I do think he would be conscious I do think in some sense not sure would be me there would be two different beings at this point I think they both be conscious and they both have many of the same mental properties I think they both you know way have the same moral status it'll be wrong to hurt either of them or they kill them and so on still there's some sense in which probably their legal status would have to be different if I am the original and that one's just a clone then you're creating a clone of me presumably the clone doesn't for example automatically own the stuff that I own or you know I've got a you know certain connect the things that the people I interact with my family my partner and so on and I'm gonna somehow be connected to them in a way in which the clone isn't so because you came slightly first yeah but this alone would argue yeah they have really as much of a connection they have all the memories of that connection then away you might say it's kind of unfair to discriminate against them but say you've got an apartment that only one person can live in or a partner who only one person or why she didn't leave you that's the original it's an interesting philosophical question but you might say because I actually have this history if I am the same person there's a one that came before and the clone is not that I have this history that the clone doesn't because there's also the question isn't the clone the same person - this is the question about personal identity if I continue and I create a clone over there I want to say this one is me and this one is is someone else but you could take the view that a clone is equally me of course in a movie like Star Trek where they have a teletransport it basically creates clones all the time they treat the clones as if they're the original person of course they destroy the original body in Star Trek Isis there's only one left around and only very occasionally two things go wrong and you get two copies of Captain Kirk it's somehow our legal system at the very least is gonna have to sort out some of these issues and that maybe that's what's moral and watch League what's legally acceptable are gonna come apart what question would you ask a clone of yourself yeah is there something useful II you can find out from him about the fundamentals of cautiousness even I mean kind of in principle I know that if it's a perfect clone it's gonna behave just like me so I'm not sure I'm gonna be able to I could discover whether it's a perfect clone by seeing whether it answers like me but otherwise I know what I'm gonna find is being which is just like me except that it's just undergone this great shock of discovering that it's a clone so just so you woke me up tomorrow and said hey Dave sorry to tell you this but you're actually the clone and you provided be really convincing evidence should be the film of my being cloned and then all wrapped here being here and and waking up so you proved to me I'm a criminal yeah okay I would find that shocking and who knows how I would react to this so so maybe by talking to the clone I'd find something about my own psychology but I can't find out so easily like how I'd react upon discovering that I'm a clone I could certainly ask the clone if it's conscious and what his consciousness is like and so on but I guess I kind of know if it's a perfect clone it's gonna behave roughly like me of course at the beginning there'll be a question about whether a perfect clone is possible so I may want to ask it lots of questions to see if it's consciousness and the way it talks about is consciousness and the way it reacts to things in general is like me and you know that will occupy us for a it's a basic unit unit testing in the early model yeah so you so if it's a perfect clone you say there's gonna be --have exactly like you so that takes us to freewill mmm-hmm is there a free will are we able to make decisions that are not predetermined from the initial conditions in the universe you know philosophers do this annoying thing of saying it depends what you mean so in this case yeah really depends on what you mean by by freewill if you mean something which was not determined in advance could never have been determined then I don't know we have freewill I mean there's quantum mechanics and who's to say if that opens up some room but I'm not sure we have freewill in that sense I'm also not sure that's the kind of freewill that really matters you know what matters to us is being able to do what we want and to create our own futures we've got this distinction between having our lives be under our control and under someone else's control method we've got the sense of actions that we are responsible for versus ones that were not I think you can make those distinctions even in a deterministic universe and this is what people call the compatibilist view of freewill where it's compatible with determinism I think for many purposes the kind of freewill that matters is something we can have in a deterministic universe and I can't see any reason in principle why an AI system couldn't have freewill of that kind if you mean super-duper freewill the ability to violate the laws of physics and doing things that imprints of all could not be predicted I don't know maybe no one has that kind of freewill what's the connection between the the reality of freewill and the experience of it the subjective experience in your view so how does consciousness connect to this to the experience to the reality in the experience of feels certainly true that when we make decisions and when we choose and so on we feel like we have an open future yes feel like I could do this I could go into philosophy or I could go into math I could go to a movie tonight I could go to restaurant so we experience these things as if the future is open and maybe we experience ourselves as exerting a kind of effect on the future that somehow picking out one path from many paths were previously open and you might think that actually if we're in a deterministic universe there's a sense in which objectively those paths weren't really open all along but subjectively they were open and that's I think that's what really matters in making a decisions were our experience of making a decision as choosing a path for for ourselves I mean in general our introspective models of the mind I think are generally very distorted representations of the mind so it may well be that our experience of our self in making a decision experience of what's going on doesn't terribly well mirror what's uh what's going on I mean you know maybe there are antecedents in the brain way before anything came into consciousness and and and so on those aren't represented in our introspective models so in general our experience of our experience of perception yes I experienced perceptual image of the external world it's not a terribly good model of what's actually going on in the in my visual cortex and so on which has all these layers and so on it's just one little snapshot of of one bit of that so in general yeah introspective models are very over oversimplified and it wouldn't be surprising if that was true of free will as well this also incidentally can be applied to consciousness itself there is this very interesting view that consciousness itself is an introspective illusion in fact we're not conscious but we but weeks the brain just has these introspective models of itself or oversimplifies everything and represents itself as having these special properties of consciousness thing it's a really simple way to kind of keep track of it so and so on and then on The Illusionist view yeah that's just a that's just an illusion it was I find this view I find it implausible I do find it very attractive in some ways because it's easy to tell some story about how the brain would create introspective models of its own consciousness of its own free will as a way of simplifying yourself I mean it's similar way when we perceive the external world we perceive it as having these colors that maybe it doesn't really have because that's a really useful way of keeping tracks of keeping track did you say that you find it not very plausible because I I thought I find it both plausible and attractive in some sense because it I mean that's that kind of view is one that has the minimum amount of mystery around it you can kind of understand that kind of view everything else says we don't understand so much of this picture you know it is four it is very attractive I recently wrote an article all about this kind of issue called the meta problem of consciousness the hard problem is how does the brain give you consciousness the meta problem is why are we puzzled by the hard problem of consciousness and because you know I'll being puzzled by it that's ultimately a bit of behavior we might be able to explain that bit of behavior as one of the easy problems consciousness so maybe there'll be some computational model that explains why we're puzzled by consciousness the meta problem has come up with that model and I've been thinking about that a lot lately there's some interesting stories you can tell about why the right kind of computational system might develop these introspective models of itself that are attributed itself these special properties so that that meta problem is a resource fasten gram program for everyone and then if you've got attraction to sort of simple views desert landscapes and so on then you can go all the way with what people call illusionism and say in fact consciousness itself is not real what Israel is just these these these introspective models we have that tell us that we're conscious so the view is very simple very attractive very powerful the trouble is of course it has to say that deep down consciousness is not real we're not actually experiencing right now and it looks like it's just contradicting a fundamental datum of our existence and this is why most people find this view crazy just as they find Pam sake as I'm crazy in one way people find illusionism crazy in another way but it's I mean but it so yes it has to deny this fundamental datum of our existence now and the view that makes the view soar frankly unbelievable for most people on the other hand the view develop right might be able to explain why we find it unbelievable because these modal's are so deeply hop right into our head and they're all integrated so it's not you can't escape that the the illusion and as the crazy possibility is it possible that the entirety of the universe our planet all the people in New York all the organisms on our planet the including me here today are not real in in that sense they're all part of an illusion inside of Dave Chalmers whose head I think all this could be a simulation no but not just a simulation yeah because the simulation kind of is outside of you I mean what if it's all an illusion they yes a dream that you are experiencing that's it's all in your mind right thank you is that can you take illusionism that far well there's illusionism about the external world and illusionism about consciousness and these might go in respective different illusionism about the external world kind of takes you back to Descartes and yet could all this be produced by an evil demon they caught himself also had the dream argument he said how do you know you're not dreaming right now how do you know this is not an amazing dream and it's at least a possibility that yeah this could be some super duper complex dream in the next universe up I guess so my attitude is that just as when a car thought that if the evil demon was doing it it's not real a lot of people these days say if a simulation is doing it it's not real as I was saying before I think even if it's a simulation that doesn't stop this is being real it just tells us what the world is made of black white if it's a dream it could turn out that all this is like my dream created by my brain and the next universe up my own view is that wouldn't stop this physical world from being real would turn out this Cup at the most fundamental level was made of a bit of say my consciousness in the Dreaming mind at the next level up maybe that would give you a kind of weird kind of pants sarcasm about reality but it wouldn't show that the cup isn't real but just tell us it's ultimately made of processes in my dreaming mind so I'd resist the idea that if the physical world is a dream then it's an illusion then it's right by the way perhaps you have an interesting thought about it why is there cards demon or genius considered evil what couldn't have been a benevolent one I had the same powers yeah I mean Dakota the Malheur genie the evil genie or evil genius malign I guess was the word but it's interesting question I mean a later philosophy Berkeley said no in fact all this is done by God God actually supply supplies you all of these all of these perceptions and ideas and that's how physical reality is sustained interestingly Barclays God is doing something that doesn't look so different from what des cartes evil demon was doing it's just that they can't thought it was deception and Berkeley thought it was not and I'm I'm actually most sympathetic to Berkeley here yeah this evil demon may be trying to deceive you but I think okay well the evil demon may just be under the working under a false philosophical theory is deceiving you it's wrong it's like there's machines on the matrix they thought they were deceiving you that all this stuff is real I think know if we're in a matrix it's all still it's all still real yeah the the philosopher ok booster I had a nice story about this about 50 years ago about dick Hart's evil demon where he said this demon spends all its time trying to fool people but fails because I'm how old demon ends up doing is constructing realities for 4 people so yeah I think that maybe if it's a very natural to take this view that if we're in a simulation or or evil demon scenario or something then none of this is real but I think it may be ultimately a philosophical mistake especially if you take on board sort of the view of reality well what matters to reality is really its structure something like its mathematical structure and so on which seems to be the view that a lot of people take from contemporary physics and looks like you can find all that mathematical structure in a simulation maybe even in a dream and so on so as long as that structure is real I would say that's enough for the physical world to be real yeah the physical world may turn out to be somewhat more intangible than we had thought and have a surprising nature of it we're already gotten very used to that from for modern science see you've kind of looted that you don't have to have consciousness for high levels of intelligence but to create truly general intelligent systems ági systems at human level intelligence and perhaps superhuman level intelligence you've talked about that it you feel like that kind of thing might be very far away but nevertheless one we reached that point do you think consciousness from an engineering perspective is needed or at least highly beneficial for creating in the a GI system yeah no one knows what consciousness is for functionally so right now there's no specific thing we can point to and say you need consciousness for that still my inclination is to believe that in principle AGI is possible at the very least I don't see why someone couldn't simulate a brain ultimately have a computational system that produces all of our behavior and if that's possible I'm sure vastly many other computational systems of equal or greater fists ocation are possible for all of our cognitive functions and more my inclination is to think that once you've got all these cognitive functions you know perception attention reasoning introspection language emotion and so on it's very likely you'll have you'll have consciousness as well as this is very hard for me to see how you'd have a system had all those things while bypassing somehow conscious so just naturally it's integrated quite naturally there's a lot of overlap about the kind of function that required to achieve each of those things that's so you can't disentangle them even when you're in us but we don't know what caused a role of consciousness in the physical world what it does I mean just say it turns out consciousness does something very specific in the physical world like collapsing wave functions as on one common interpretation of quantum mechanics that all we might find someplace where it actually makes a difference and we could say uh here is where in collapsing wave functions it's driving the behavior of a system and maybe it could even turn out that for a GI you'd need something playing that I mean if you wanted to connect this to free will some people think consciousness collapsing wave functions that would be how the conscious mind exerts affect on the physical world and exerts its free will and maybe it could turn out that any AGI that didn't utilize that mechanism would be limited in the kinds of functionality that have had I don't myself find that plausible I think probably that functionality could be simulated you could imagine once we had a very specific idea about the role of consciousness in the physical world this would have some impact on the capacity of a GIS and if it was a role that could not be duplicated elsewhere then we have to find we did we have to find some way to either get consciousness in the system to play that role or to simulate it if we can isolate a particular role to consciousness of course that's incredibly seems like an incredibly difficult thing whatever worries about X sensual threats of conscious intelligent beings that are not us though so certainly I'm sure you're worried about us yeah from an existential threat perspective but outside of us AI systems there's a couple of different kinds of existential threats here one is an existential threat to consciousness generally I mean yes I care about humans and the survival of humans and so on but just say it turns out that that eventually we're replaced by some artificial beings around humans but are somehow our successes they still have good lives they still do interesting and wonderful things with the universe I don't think that's that's not so bad that's just our successors we were one stage in evolution something different maybe better came next if on the other hand all of consciousness was wiped out that would be a very serious moral disaster one way that could happen is by all intelligent life being wiped out and many people think that yeah once you get to humans and AI is an amazing sophistication where everyone has got the the ability to create weapons that can destroy the whole universe just by just by pressing a button then maybe it's inevitable all intelligent life will will die out that would be a that would certainly be a disaster and we've got to think very hard about how to avoid that but yeah another interesting kind of disaster is that may be intelligent life is not wiped out but all consciousness is wiped out so just say you thought unlike what I was saying a moment ago that there are two different kinds of intelligent systems some which are conscious and some which are some which are not and just say it turns out that we create AGI with with higher degree of intelligence meaning higher degree of sophistication and that's behavior but with no consciousness at all that AGI could take over the world maybe but then there be but let there be no consciousness in this world this would be a world of zombies some people have called this the zombie apocalypse because it's consciousness consciousness is gone you've merely got this / intelligent non-conscious robots and I would say that's a moral disaster in the same way in almost the same way that the world with no intelligent life is a moral disaster all value and meaning may be gone from from that world so these are both threats to watch out for now my own view is if you get super intelligence you're almost certainly going to bring consciousness with it so I hope that's not gonna happen but of course I don't understand consciousness no one understands consciousness this is one reason for this is one reason at least among many for thinking very seriously about consciousness and thinking about the kind of future we want to create with a you know city in a world with humans and or AI how do you feel about the possibility of consciousness so naturally does come with a GI systems that we are just a step in the evolution that will be just something a blimp on the record that be studied in books by the a GI systems centuries from now I mean I think I'd probably be ok with that especially if somehow humans are continuous with AG eyes I mean I think something like this is inevitable the very least humans are gonna be transformed we're gonna be augmented by technology that's already happening in all kinds of ways we're gonna be transformed by technology where our brains are gonna be uploaded and computationally enhanced and eventually that line between what's a human and what's a what's an AI maybe kind of hard to hard to draw how much does it matter for example that some future being a thousand years from now that somehow descended from us actually still has biology I think it would be nice if you kind of point to its cognitive system to point to some past that had some roots in us and chaser trace a continuous line there that would be selfishly nice for me to think that ok I'm connected to this thread line through the future of the world but if it turns out ok there's a jump there they'd if they found a better way to design cognitive systems they designed a wholly new kind of thing and the only line is some causal chain of designing and systems that design better systems is that so much worse I don't know still at least part of a causal chain of design and yes they're not humans but still they're our successes ultimately I think it's probably inevitable that something like that will happen at least we were at least we were part of the process it'll be nice if they still cared enough about us to you know maybe to engage with our arguments I'm really hoping that the Agis are gonna solve all the problems of philosophy they'll come back and read all this all this crap for the 20th and 21st century hard problem of consciousness and here is why they got it wrong and so and if that happened then I'd really feel like I was part of at least a intellectual process over centuries and that would be kind of cool I'm pretty sure they would clone or they would recreate David Chalmers and for the fun of it sort of bring back other philosophy a car the garden and just put them in a room he's just watch it'll be a Netflix of the future show will you bring philosophers from different human 100% human philosophers from previous generations put them in a room and see them I am totally I'm totally up for that simulators AG eyes of the future if you're watching who that would like to be recreated and who wouldn't be cut with the car it would be the first hangout as part of such a TV show with a philosopher that's no longer with us from long ago who would it who would you choose dick count would have to be right up there oh actually a couple of months ago I got to have a conversation with dick Hart an actor who's actually a philosopher came out on stage playing Descartes I didn't know this was gonna happen and I just after I gave a talk and a bit of a surreal my ideas were crap and all drive from him and so I made along with a long argument this was great no I would love to see what Descartes would think about AI for example and modern neuroscience and so on I suspect not too much would surprise him but that ya William James you know for psychologists of consciousness I think James was probably the was probably the the richest but oh there are manual cars you know I never really understood when is up to if I got to actually talk to him about some of this hey it was Princess Elizabeth who talked with Descartes and who really you know got other problems of how they carts ideas of a non-physical mind interacting with the with the the physical body couldn't really work she's been kind of most philosophers think she's been proved right so maybe put me in a room with Descartes and Princess Elizabeth and we can all argue it out what kind of feature so we talked about was zombies a concerning future but what kind of future excites you what do you think if we look forward sort of we're at the very early stages of understanding consciousness and we're now at the early stages of being able to engineer complex interesting systems that have degrees of intelligence maybe one day we'll have degrees of consciousness maybe be able to upload brains all those possibilities virtual reality what is there a particular aspect of this future world that just excites you I think there are lots of different aspects I mean frankly I want it to hurry up and half us like yeah we've had some progress lately an AI and VR but in the grand scheme of things it's still kind of slow the changes are not yet transformative and you know I'm in my 50s I've only got so long left I'd like I'd like to see really serious AI in my lifetime and really serious virtual worlds because yeah once people are I would like to be able to hang out in a virtual reality which is richer then then then this reality to really get to inhabit fundamentally different kinds of spaces well I would very much like to be able to upload my mind onto a onto a computer so maybe I don't have to die if this is maybe gradually replace my neurons with silicon chips and I'd have it like a few selfishly that would be that would be wonderful I suspect I'm not going to quite get there in a in my lifetime but once that's possible then you've got the possibility of transforming your consciousness in remarkable ways or renting it enhancing it so let me ask them if such a system is a possibility within your lifetime and you were given the opportunity to become immortal in this kind of way would you choose to be immortal yes I totally would I know some people say they couldn't it would be awful to be a to be immortal be so boring or something I don't see I really don't see a don't see why this might be I mean even if it's just ordinary life that continues ordinary life is not so bad but furthermore I kind of suspect that you know if the universe is gonna go on forever or indefinitely it's going to continue to be interesting it I don't think yeah your view was that we just hit this one romantic point of interest now and afterwards it's all gonna be boring super-intelligent stasis I guess my vision is more like no it's gonna continue to be infinitely interesting something like as you go up the set theoretic hierarchy you know you go from the the finite car finite Cardinals to Aleph zero and then through there to all the Aleph one and I love two and maybe the continuum and you keep taking power sets and you know in set theory they've got these results that actually all this is fundamentally unpredictable it doesn't follow any simple computational patterns there's new levels of creativity as the set theoretic universe expands and expands I guess that's my future that's my vision of the future that's my optimistic vision of the future of superintelligence it will keep expanding and keep growing but still being fundamentally unpredictable at many points I mean yes this gets creates all kinds of worries like couldn't it all be fragile and be destroyed at any point so we're gonna need a solution to that problem if we get to stipulate that I'm immortal well I hope that I'm not just immortal and stuck in the single world forever but I'm immortal and get to take part in this process of going through infinitely rich created futures rich unpredictable exciting well I think I speak for a lot of people in saying I hope you do become immortal and there'll be that Netflix show the future where you get to argue with Descartes perhaps for all eternity so David was an honor thank you so much for talking today thanks it was a pleasure thanks for listening to this conversation and thank you to our presenting sponsored cash app download it use coal XPath cast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science and technology innovators of tomorrow if you enjoyed this podcast subscribe on youtube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and lex friedman and now let me leave you with some words from david chalmers materialism is a beautiful and compelling view of the world but to account for consciousness we have to go beyond the resources it provides thank you for listening I hope to see you next time you |
Cristos Goodrow: YouTube Algorithm | Lex Fridman Podcast #68 | the following is a conversation with Christos Kudrow vice president of engineering at Google and head of search and discovery at YouTube also known as the YouTube algorithm YouTube has approximately 1.9 billion users and every day people watch over 1 billion hours of YouTube video it is the second most popular search engine behind Google itself for many people it is not only a source of entertainment but also how we learn new ideas from math and physics videos to podcasts to debates opinions ideas from out-of-the-box thinkers and activists some of the most tense challenging and impactful topics in the world today YouTube and other content platforms receive criticism from both viewers and creators as they should because the engineering task before them is hard and they don't always succeed and the impact of their work is truly world-changing to me YouTube has been an incredible wellspring of knowledge I've watched hundreds if not thousands of lectures that changed the way I see many fun about those ideas in math science engineering and philosophy but it does put a mirror to ourselves and keeps the responsibility of the steps we take in each of our online educational journeys into the hands of each of us the YouTube algorithm has an important role in that journey of helping us find new exciting ideas to learn about that's a difficult and an exciting problem for an artificial intelligence system as I've said in lectures and other forums recommendation systems will be one of the most impactful areas of AI in the 21st century and YouTube is one of the biggest recommendation systems in the world this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and Charity Navigator which means that donated money is used to maximum effectiveness when you get cash app from the App Store Google Play and use code Lex podcast you'll get ten dollars in cash app will also donate ten dollars to the first which again is an organization that I've personally seen inspire girls and boys the dream of engineering a better world and now here's my conversation with Christos Gaudreau YouTube is the world's second most popular search engine behind Google of course we watch more than 1 billion hours of YouTube videos a day more than Netflix and facebook video combined YouTube creators upload over 500 thousand hours of video every day average lifespan of a human being just for comparison is about 700,000 hours so what's uploaded every single day is just enough for a human to watch in a lifetime so let me ask an absurd philosophical question if from birth when I was born and there's many people born today with the internet I watched YouTube videos non-stop do you think there are trajectories through YouTube video space that can maximize my average happiness or maybe education or my growth as a human being I think there are some great trajectories through YouTube videos but I wouldn't recommend that anyone and all of their waking hours or all of their hours watching YouTube I mean I think about the fact that YouTube has been really great for my kids for instance my oldest daughter you know she's been watching YouTube for several years she watches Tyler Oakley and the vlogbrothers and I know that it's had a very profound and positive impact on her character and my younger daughter she's a ballerina and her teachers tell her that YouTube is a huge advantage for her because she can practice a routine and watch like professional dancers do that same routine and stop it and back it up and rewind and all that stuff right so it's been really good for them and then even my son is a sophomore in college he he got through his linear algebra class because of a channel called three blue one brown which you know helps you understand linear algebra but in a way that would be very hard for anyone to do on a whiteboard or a chalkboard and so I think that those experiences from my point of view were very good and and so I can imagine really good trajectories through YouTube yes have you looked at do you think of broadly about that trajectory over a period cuz YouTube was growing up now so over a period of years you just kind of gave a few anecdotal examples but you know I used to watch certain shows on YouTube I don't anymore I've moved on to other shows and ultimately you want people to from YouTube's perspective to stay on YouTube to grow as human beings on YouTube so you have to think not just what makes them engage today or this month but also over a period of years absolutely that's right I mean if YouTube is going to continue to enrich people's lives then you know then it has to grow with them and and people's interests change over time and so I think we've we've been working on this problem and I'll just say it broadly is like how to introduce diversity and introduce people who are watching one thing to something else they might like we've been working on that problem all the eight years I've been at YouTube it's a hard problem because I mean of course it's trivial to introduce diversity that doesn't help a random video I could just randomly select a video from the billions that we have it's likely not to even be in your language so haha the likelihood that you would watch it and develop a new interest is very very low and so what you want to do when you're trying to increase diversity is find something that is not too similar to the things that you've watched but also something that you might be likely to watch and that balance finding that spot between those two things is quite challenging so the diversity of content diversity of ideas it's uh it's a really difficult it's the thing like that's almost impossible to define alright like what's different so how do you think about that so two examples is a I'm a huge fan of three blue one Brown say and then one diversity I wasn't even aware of a channel called veritasium width which is a great science physics whatever channel so one version of diversity is showing me Derek's veritasium channel which I was really excited to discover actually now watch a lot of his videos okay so you're a person who's watching some math channels and you might be interested in some other science or math channels so like you mentioned the first kind of diversity is just show you some some things from other channels that are related but not just you know not all the three blue one Brown Channel throw in a couple others so so that's the maybe the first kind of diversity that we started with many many years ago taking a bigger leap is is about I mean the mechanisms we do we use for that is is we basically cluster videos and channels together mostly videos we do every almost everything at the video level and so we'll we'll make some kind of a cluster some embedding process and then and then measure you know what is the likelihood that a that users who watch one cluster might also watch another cluster that's very distinct so we may come to find that that people who watch science videos also like jazz this is possible right and so and so because of that relationship that we've identified through the through the embeddings and then the measurement of the people who watch both we might recommend a jazz video once in a while so there's this clustering the embedding space of jazz videos and science videos and so you kind of try to look at aggregate statistics where if a lot of people that jump from science cluster to the jazz cluster tend to remain as engaged or become more engaged then that's that means those two are they should hop back and forth and they'll be happy right there's a higher likelihood that a person from who's watching science would like jazz then the person watching science would like I don't know backyard railroads or something else right and so we can try to measure these likelihoods and use that to make the best recommendation we can so okay so we'll talk about the machine learning of that but I have to linger on things that neither you or anyone have an answer to there's gray areas of truth which is for example now I can't believe I'm going there but politics it it happens so that the certain people believe certain things and they're very certain about them let's move outside the red versus blue politics of today's world but there's different ideologies for example in college I read quite a lot of iron rand i studied and that's a particular philosophical ideologies I find I found it interesting to explore okay so that was that kind of space I've kind of moved on from that cluster intellectually but it nevertheless is an interesting cluster there's I was born in Soviet Union socialism communism is a certain kind of political idea that's really interesting to explore again objectively just there's a set of beliefs about how the economy should work and so on and so it's hard to know what's true or not in terms of people within those communities they're often advocating that this is how we achieve utopia in this world and they're pretty certain about it so how do you try to manage politics in this chaotic divisive world not positively any kind of ideas in terms of filtering what people should watch next and in terms of also not letting certain things be on YouTube this is exceptionally difficult responsibility right well the responsibility to get this right is our top priority and and the first comes down to making sure that we have good clear rules of the road right like just because we have freedom of speech doesn't mean that you can literally say anything right like we as a society have accepted certain restrictions on our freedom of speech there are things like libel laws and things like that and so where we can draw a clear line we do and we continue to evolve that line over time however as you point it out wherever you draw the line there's going to be a border line and in that border line area we are going to maybe not remove videos but we will try to reduce the recommendations of them or the proliferation of them by demoting them and then alternatively in those situations try to raise what we would call Thorat ativ or credible sources of information so we're not trying to I mean you mentioned Iran and communism you know those are those are two like valid points of view that people are going to debate and discuss and and of course people who believe and one of the other of those things are going to try to persuade other people to their point of view and so we're not trying to settle that choose a side or anything like that what we're trying to do is make sure that the the people who are expressing those point of view and and offering those positions are authoritative and credible so let me ask a question about people I don't like personally you heard me I don't care if you leave comments on this is uh and but sometimes there's brilliantly funny which is trolls so it's people who kind of mock I mean the Internet is full the reddit of mock style comedy where people just kind of make fun of point out that the emperor has no clothes and there's brilliant comedy and that but sometimes it can get cruel and mean so on that on the mean point and sorry to linger on these things that have no good answers but it actually is I totally hear you that this is really important you're trying to solve it but how do you reduce the meanness of people on YouTube I understand that anyone who uploads YouTube videos has to become resilient to a certain amount of meanness like I've heard that from many creators and we would we are trying in various ways comment ranking allowing certain features to block people to reduce or or make that that meanness or that trolling behavior less effective on YouTube yeah and so I mean it's it's very important but it's something that we're we're gonna keep having to work on and and you know as we improve it maybe we'll get to a point where where people don't have to suffer this sort of meanness when they upload YouTube videos I hope we do but you know but it just does seem to be something that you have to be able to deal with as a YouTube creator now it is do you have a hope that he mentioned two things that can I agree was so there's a machine-learning approach of ranking comments based on whatever based on how much they contribute to the healthy conversation let's put it that way then the other is almost an interface question of how do you how does the Creator filter so block or how does how do humans themselves the users of YouTube manage their own conversation do you have hope that these two tools will create a better society without limiting freedom of speech too much without sort of Antonin even like saying that people what do you mean limiting sort of curating speech I mean I think that that overall is our whole project here at YouTube right like yeah we fundamentally believe and I personally believe very much that YouTube can be great it's been great for my kids I think it can be great for society but it's absolutely critical that we get this responsibility part right and that's why it's our top priority Susan Wojcicki who's the CEO of YouTube she says something that I personally find very inspiring which is that we want to do our jobs today in a manner so that people 20 and 30 years from now will look back and say you know YouTube they they really figured this out they really found a way to strike the right balance between the openness and the value that the openness has and also making sure that we are meeting our responsibilities to users in society so the burden on YouTube actually is quite incredible and the one thing that people don't I don't give enough credit to the seriousness and the magnitude of the problem I think so I I personally hope that you do solve it because a lot is in your hand a lot is riding on your success or failure so it's besides of course running a successful company you're also curating the content of the internet and the conversation the internet that's a powerful thing so one thing that people wander about is how much of it can be solved with pure machine learning so looking at the data studying the data and creating algorithms that curate the comments curate the content and how much of it needs human intervention meaning people here YouTube in a room sitting and thinking about what is the nature of truth what is what are the ideals that we should be promoting that kind of thing so algorithm versus human input what's your sense I mean my own experience has demonstrated that you need both of those things algorithms I mean you're familiar with machine learning algorithm and the thing they need most is data and the data is generated by humans and so for instance when we're building a system to try to figure out which are the videos that are misinformation or borderline policy violations well the first thing we need to do is get human beings to make decisions about which which of those videos are in which category and then we use that data and and basically you know take that information that's that's determined and governed by humans and and extrapolated or apply it to the entire set of billions of YouTube videos and we couldn't we we couldn't get to all the videos on YouTube well without the humans and we we couldn't use the humans to get to all the videos of YouTube so there's no world in which you have only one or the other of these things and just as you said a lot of it comes down to people at YouTube spending a lot of time trying to figure out what are the right policies you know what are the outcomes based on those policies are they the kinds of things we want to see and then once we kind of get a get an agreement or or build some consensus around around what the policies are well then we've got to find a way to implement those policies across all of YouTube and that's where both the human beings we call them evaluators or reviewers come into play to help us with that and then and then once we get a lot of training data from them then we apply the machine learning techniques to take it even further do you have a sense that these human beings have a bias in some kind of direction sort of I mean that's the interesting question we do sort of in autonomous vehicles and computer vision in general a lot of annotation and we rarely ask what bias do the annotators have you know the it even in the sense that they're better than they're better anting certain things and others for example people are much better at annotating segmentation at segmenting cars in a scene versus segmenting bushes or trees you know there's specific mechanical reasons for that but also because the cement its semantics gray area and and just for a lot of reasons people are just terrible at annotating trees okay so in the same kind of sense do you think of in terms of people reviewing videos or annotating the content of videos is there some kind of bias that you're aware of or seek out in that human input well we take steps to try to overcome these kinds of biases or biases that we think would be problematic so for instance like we asked people to have a bias towards scientific consensus that's something that we we instruct them to do we ask them to have a bias towards demonstration of expertise or credibility or authoritative nests but there are other biases that we that we want to make sure to try to remove and there's many techniques for doing this one of them is you send the same thing to be reviewed to many people and so you know that's one technique another is that you make sure that the people that are doing these sorts of tasks are from different backgrounds and different areas of the United States of the world but then even with all of that it's possible for certain kinds of what we would call unfair biases to creep into machine learning systems primarily as you said because maybe the training data itself comes in in in a biased way and so we also have worked very hard on the improving the machine learning systems to remove and reduce unfair biases when it's when it goes against or or has involved some protected class for instance thank you for exploring with me some of the more challenging things I'm sure there's a few more that we'll jump back to but let me jump into the fun part which is maybe the basics of the quote-unquote YouTube algorithm what is the YouTube algorithm look at to make recommendation for what to watch next was from a machine learning perspective or when you search for a particular term how does it know what to show you next because it seems to at least for me do an incredible job both well that's kind of you to say it didn't used to do a very good job but it's gotten better over the years even even I observed that it's improved quite a bit those are two different situations like when you search for something YouTube uses the best technology we can get from Google to make sure that that the YouTube search system finds what someone's looking for and of course the very first things that one thinks about is okay well does the word occur in the title for instance you know but there but there are much more sophisticated things where we're mostly trying to do some syntactic match or or maybe a semantic match based on words that we can add to the document itself for instance you know maybe is is this video watched a lot after this query right that's something that we can observe and then as a result make sure that that that document would be retrieved for that query now when you talk about what kind of videos would be recommended to watch next that's something again we've been working on for many years and probably the first the first real attempt to do that well was to use collaborative filtering so you can't describe what collaborative filtering is sure it's just basically what we do is we observe which videos get watched close together by the same person and if you observe that and if you can imagine creating a graph where the videos that get watched close together by the most people are sort of very close to one another in this graph and videos that don't frequently get watch close too close together by the same person or the same people are far apart then you end up with this graph that we call the related graph that basically represents videos that are very similar or related in some way and what's amazing about that is that it puts all the videos that are in the same language together for instance and we didn't even have to think about language just does it yeah I didn't it puts all the videos that are about sports together and it puts most of the music videos together and it puts all of these sorts of videos together just because that's sort of the way the people using YouTube behave so that already cleans up a lot of the problem it takes care of the lowest hanging fruit which happens to be a huge one of just managing these millions of videos that's right I remember a few years ago I was talking to someone who was trying to propose that we do a research project concerning people who who are bilingual and this person was making this proposal based on the idea that YouTube could not possibly be good at recommending videos well to people who are bilingual and so she was telling me about this and I said well can you give me an example of what problem do you think we have on YouTube with the recommendations and so she said well I'm a researcher in in the US and and when I'm looking for academic topics I want to look I want to see them in English and so she searched for one found a video and then looked at the watch next suggestions and they were all in in English and so she said oh I see YouTube must think that I speak only English and so she said now I'm actually originally from Turkey and sometimes when I'm cooking let's say I want to make some baklava I really like to watch videos that are in Turkish and so she searched for a video about making the baklava and then and then selected it it was in Turkish and the watch next recommendations were in Turkish and she just couldn't believe how this was possible and how is it that you know that I speak both these two languages and put all the videos together and it's just as a route come of this related graph that's created through collaborative filtering so for me one of my huge interest is just human psychology right and and that's such a powerful platform on which to utilize human psychology to discover what people individual people want to watch next but it's also be just fascinating to me you know I've Google search has ability to look at your own history and I've done that before just just what I've searched three years for many many years and it's fascinating picture of Who I am actually and I don't think anyone's ever summarized that I personally would love that a summary of who I am as a person on the Internet to me because I think it reveals I I think it puts a mirror to me or to others you know that's actually quite revealing and interesting you know just maybe in the number of it's a joke but not really is the of cat videos I've watched videos of people falling you know stuff that's absurd that kind of stuff it's really interesting and of course it's really good for the machine learning aspect to to show to figure out what to show next but it's interesting hey have you just as a tangent played around with the idea of giving a map to people sort of as opposed to just using this information to show us next showing them here are the clusters you've loved over the years kind of thing well we do provide the history of all the videos that you've watched yes so you can definitely search through that and look through it and search through it to see what it is that you've been watching on YouTube we have actually in various times experimented with this sort of cluster idea finding ways to demonstrate or show people what topics they've been interested in or what what clusters they've watched from it's interesting that you bring this up because in some sense the way the recommendation system of YouTube sees a user is exactly as the history of all the videos they've watched on YouTube and so you can think of yourself or any user on YouTube as kind of like a DNA strand of all your videos right that sort of represents you you can also think of it as maybe a vector in the space of all the videos on YouTube and so you know now once you think of it as a vector in the space of all the videos on YouTube then you can start to say okay well you know which videos which which other vectors are close to me and to my vector and and that's one of the ways that we generate some diverse recommendations is because you're like okay well you know these these people seem to be closed with respect to the videos they've watched on YouTube but you know here's a topic or a video that one of them has watched and enjoyed but the other one hasn't that could be an opportunity to make a good recommendation I gotta tell you I mean I know for things that are impossible but I would love to cluster than human beings like I would love to know who has similar trajectories as me you probably would want to hang out alright there's a social aspect there like actually finding some of the most fascinating people I find out in YouTube but have like no followers and I start following them and they create incredible content and you know and on that topic I just love to ask there's some videos just blow my mind in terms of quality and depth and just in every regard are amazing videos and they have like 57 views okay how do you get videos of quality to be seen by many eyes so the measure of quality is it just something yeah how do you know that something is good well I mean I think it depends initially on what sort of video we're talking about so in the realm of let's say you mentioned politics and news in that realm you know quality news or quality journalism relies on having a journalism department right like you you have to have actual journalists and fact-checkers and people like that and so in that situation and in others maybe science or in medicine quality has a lot to do with the authoritative nough sand the credibility and the expertise of the people who make the video now if you're thinking about the other end of the spectrum you know what is the highest quality prank video for what is the highest quality minecraft video yeah right that might be the one that people enjoy watching the most and watch to the end or it might be the one that when we ask people the next day after they watched it were they satisfied with it and so we in in especially in the realm of entertainment have been trying to get at better and better measures of quality or satisfaction or enrichment since I came to YouTube and we started with well you know the first approximation is the one that gets more views but but you know we both know that things can get a lot of views and not really be that high quality especially if people are clicking on something and then immediately realizing that it's not that great and abandoning it and that's why we move from views to thinking about the amount of time people spend watching it what the premise that like you know in some sense the time that someone spends watching a video is related to the value that they get from that video it may not be perfectly related but it has something to say about how much value they get but even that's not good enough right because I myself have spent time clicking through channels on television late at night and ended up watching under siege - for some reason I don't know and if you were to ask me the next day are you glad that you watched that show on TV last night I'd say yeah I wish I would have gone to bed or read a book or almost anything else really and so that's why some people got the idea a few years ago to try to serve at users afterwards and so so we get feedback data from those surveys and then use that in the machine learning system to try to not just predict what you're gonna click on right now what you might watch for a while but what when we ask you tomorrow you'll give four or five stars - so just to summarize what are the signals from a machine learning perspective the user can provide he mentions just clicking on the video views the time watch maybe the relative time watched the clicking like and dislike on the video maybe commenting on the video and those things all of those things and then though the one I wasn't actually quite aware of even though I might have engaged in it is a survey afterwards which is a brilliant idea is there other signals all right I mean that's already a really rich space of signals to learn from is something else well you mentioned commenting also sharing the video if you if you think it's worthy to be shared with someone else you know within YouTube or outside of YouTube as well either let's see you mentioned like dislike yeah like and dislike how important is that it's very important right we want its predictive of satisfaction but it's not it's not perfectly predictive subscribe if you subscribe to the channel of the person who made the video then that also is a piece of information and signals satisfaction although over the years we've learned that people have a wide range of attitudes about what it means to subscribe we would ask some users who didn't subscribe very much why but they watched a lot from a few channels we'd say well why didn't you subscribe and they would say well I I can't afford to pay for anything and you know we tried to let them understand like actually it doesn't cost anything it's free it just helps us know that you are very interested in this creator but then we've asked other people who subscribed to many things and and don't really watch any of the videos from those channels and we say well well why did you subscribe to this if you weren't really interested in any more videos from that channel and they might tell us why just you know I thought the person did a great job and I just want to kind of give him a high five yeah yeah and so yeah that's where I I said I should subscribe to channels where I just this person is amazing I like this person but then I like this person I really want to support them that that's how I click Subscribe right even though I may never actually want to click on their videos when they're releasing it I just love what they're doing and it's maybe outside of my interest area and so on which is probably the wrong way to use the subscribe button but I just want to say congrats this is a great work well so you have to deal with all the space of people that see the subscribe button it's totally different that's right and so you know we we can't just close our eyes and say sorry you're using it wrong you know and we're not gonna pay attention to what you've done we need to embrace all the ways in which all the different people in the world use the subscribe button or the like in the dislike button so in terms of signals of machine learning using for the search and for the recommendation you've mentioned title so like metadata like text data that people provide description and title and maybe keywords so maybe you can speak to the value of those things in search and also this incredible fascinating area of the content itself so the video content itself trying to understand what's happening in the video so YouTube would release a dataset that you know the in the machine learning and computer vision world this is just an exciting space how much is that currently how much he playing with that currently how much is your hope for the future of being able to analyze the content of the video itself well we have been working on that also since I came to YouTube analyzing the content analyzing the content while video right and what I can tell you is that our ability to do it well is still somewhat crude we can we can tell if it's a music video we can tell if it's a sports video we can probably tell you that people are playing soccer we probably can't tell whether it's Manchester United or my daughter's soccer team so these things are kind of difficult and and using them we can use them in some ways so for instance we use that kind of information to understand and inform these clusters that I talked about and also maybe to add some words like soccer for instance to the video if if it doesn't occur in the title or the description which is remarkable that often it doesn't I one of the things that I ask creators to do is is please help us out with the title in the description for instance we were a a few years ago having a live stream of some competition for World of Warcraft on YouTube and it was a very important competition but if you typed World of Warcraft in search you wouldn't find it well the Warcraft wasn't in the title World of Warcraft wasn't in the title it was match four seven eight you know a team versus B team and World of Warcraft wasn't the title yes like come on give me being literal being literal on the Internet is actually very uncool which is the problem oh is that right well I mean in some sense well some of the greatest videos I mean there's a humor to just being indirect being witty and so on and actually being you know machine learning algorithms want you to be you know literal right usually want to say what's in the thing be very very simple and in in some sense that gets away from wit and humor so you have to play with both right so but you're saying that for now sort of the content of the title the content of the description the actual text is is one of the best ways to uh for the for the algorithm to find your video and put them in the right cluster that's right and and I would go further and say that if you want people human beings to select your video in search then it helps to have let's say World of Warcraft in the title because why would a person's you know if they're looking at a bunch they type World of Warcraft and they have a bunch of videos all of whom say World of Warcraft except the one that you uploaded well even the person is gonna think well maybe this isn't some house search made a mistake this isn't really about World of Warcraft so it's important not just for the machine learning systems but also for the people who might be looking for this sort of thing they get a clue that it's what they're looking for by seeing that same thing prominently in the title of the video okay let me push back on that so I think from the algorithmic perspective yes but if they typed in World of Warcraft and saw a video that with the title simply winning and and and the thumbnail has like a sad orc or something I don't know right like I think that's much it's Iraq it gets your curiosity up and then if they could trust that the algorithm was smart enough to figure out somehow that this is indeed a World of Warcraft video that would have created the most beautiful experience I think in terms of just the wit and the humor and the curiosity that we human beings actually have but you're saying I mean realistically speaking is really hard for the algorithm to figure out that the content of that video will be a world of warcraft and you have to accept that some people are gonna skip it yeah right I mean and so you're right the people who don't skip it and select it are gonna be delighted yeah but other people say might say but yeah this is not what I was looking for and making stuff discoverable I think is what you're really working on and hoping so yeah so from your perspective to put stuff in the description and remember the collaborative filtering part of the system it starts by the same user watching videos together right so the way that they're probably going to do that is by searching for them that's a fascinating aspect it's like ant colonies that's how they find stuff is so I mean you would agree for collaborative filtering in general is one curious ant one curious user essential sort of just a person who is more willing to click on random videos and sort of explore these cluster spaces in your sense how many people are just like watching the same thing over and over and over and over and how many are just like the explorers I just kind of like click on stuff and then help help the other ant and the ants colony discover the cool stuff do you have a sense of that or no I really don't think I have a sense me OK relative sizes of those groups but I but I would say that you know people come to YouTube with some certain amount of intent and as long as they to the extent to which they they try to satisfy that intent that certainly helps our systems right because our systems rely on on kind of a faithful amount of behavior the right like and there are people who try to trick us right there are people and machines that try to associate videos together that really don't belong together but they're trying to get that Association made because it's profitable for them and so we have to always be resilient to that sort of attempt at gaming the system so speaking to that there's a lot of people that in a positive way perhaps I don't know I I don't like it but I like to gain want to try to gain the system to get more attention and everybody creators in a positive sense want to get attention right so how do you how do you work in this space when people create more and more sort of click Beatty titles and thumbnails sort of a very tasking derek has made a video it basically describes that it seems what works is to create a high quality video really good video what people would want to watch and wants to click on it but have clicked BT titles and thumbnails to get him to click on it in the first place and he's saying I'm embracing this bactrim just gonna keep doing it and I hope you forgive me for doing it and you will enjoy my videos once you click on them so in what sense do you see this kind of clickbait style attempt to manipulate to get people in the door to manipulate the algorithm or play with the algorithmic game the algorithm I think that that you can look at it as an attempt to game the algorithm but even if you were to take the algorithm out of it and just say ok well all these videos happen to be lined up which the algorithm didn't make any decision about which one to put at the top or the bottom but they're all lined up there which one are the people going to choose and and I'll tell you the same thing that I told Derek is you know I have a bookshelf and they have two kinds of books on them science books I have my math books from when I was a student and they all look identical except for the titles on the covers they're all yellow they're all from Springer and they're every single one of them the cover is totally the same yes right yeah on the other hand I have other more pop science type books and they all have very interesting covers right and they have provocative titles and things like that I mean I wouldn't say that they're clickbait II because they are indeed good books and I don't think that they cross any line but but you know the that's just a decision you have to make right like the people who who write classical recursion theory by pure OD Freddie he was fine with the yellow title and the and nothing more whereas I think other people who who wrote a more popular type book understand that they need to have a compelling cover and a compelling title and and you know I don't think there's anything really wrong with that we do we do take steps to make sure that there is a line that you don't cross and if you go too far maybe your thumbnails especially racy or or you know it's all cats with too many exclamation points we observe that users are kind of you know sometimes offended by that and so so for the users who were offended by that we will then depress or suppress those videos and which reminds me that there's also another signal where users can say I don't know if was recently added but I really enjoy it just saying I don't I didn't something like I I don't want to see this video anymore or something like like this is a like there's certain videos just cut me the wrong way like just just jump out at music I don't wanna I don't want this and it feels really good to clean that out to be like I don't that's not that's not for me I don't know I think that might have been recently added by this that's also a really strong signal yes absolutely right we don't want to make a recommendation that people are unhappy with and that makes me that particular one makes me feel good as a user in general and as a machine learning person because I feel like I'm helping the algorithm my interaction I need you don't always feel like I'm helping the algorithm like I'm not reminded of that fact like for example Tesla and Otto Pollan you know on musk create a feeling for their customers for people their own test is that there helping the algorithm of testify like they're all like a really proud they're helping nicely learn I think YouTube doesn't always remind people that you're helping the algorithm get smarter and for me I love that idea like we're all collaboratively like Wikipedia gives that sense they were all together creating a beautiful thing YouTube is uh doesn't always remind me of that it's uh this conversation is Right any of that but well that's a good tip we should keep that fact in mind when we design these features well I I'm not sure I I really thought about it that way but that's a very interesting perspective it's an interesting question of personalization that I feel like when I click like on a video I'm just improving my experience it would be great it would make me personally people are different but make me feel great if I was helping also the YouTube algorithm broadly say something you know saying like there's a that I don't know if that's human nature we you want the products you love and I certainly love YouTube like you want to help it get smarter and smarter smarter because there's some kind of coupling between our lives together being better if if YouTube was better than I will my life will be better and that's that kind of reasoning I'm not sure what that is and I'm not sure how many people share that feeling it could be just a machine learning feeling but at that point how much personalization is there in terms of next video recommendations so is it kind of all really boiling down to a clustering like you find in ears clusters to me and so on and that kind of thing or how much is person s to me the individual completely it's very very personalized so your experience will be quite a bit different from anybody else's who's watching that same video at least when they're logged in and the reason is is that we found that that users often want two different kinds of things when they're watching a video sometimes they want to keep watching more on that topic or more in that genre and other times they just are done and they're ready to move on to something else and so the question is well what is this something else and one of the first things one can imagine is well maybe something else is the latest video from some channel to which you've subscribed and that's gonna be very different from for you than it is for me right and and even if it's not something that you subscribe to it's something that you watch a lot and again that'll be very different on a person-by-person basis and so even the watch next as well as the homepage of course is quite personalized so what we met some of the signals but what a success look like what a success look like in terms of the algorithm creating a great long-term experience for a user or put another way if you look at the videos I've watched this month how do you know the algorithm succeeded for me I think first of all if you come back and watch more YouTube then that's one indication that you've found some value from it so just the number of hours is a powerful indicator well I mean not the hours themselves but the fact that you return on another day so that's probably the most simple indicator people don't come back to things that they don't find value in right there's a lot of other things that they could do but like I said I mean ideally we would like everybody to feel that YouTube enriches their lives and that every video they watched is the best one they've ever watched since they've started watching YouTube and so that's why we survey them and ask them like is this one to five stars and so our version of success is every time someone takes that survey they say it's five stars and if we ask them is this the best video you've ever seen on YouTube they say yes every single time so it's hard to imagine that we would actually achieve that maybe asymptotically we would get there but but that would be what we think success is it's funny have recently said some way I don't know maybe tweeted but that Ray Dalio has this video on the economic machine I forget what it's called but it's a 30-minute video and I said it's the the greatest video I've ever watched on YouTube it's it's like I watched the whole thing and my mind was blown is a very crisp clean description of how the at least the American economic system works it's a beautiful video and I was just I wanted to click on something to say this is the best thing this is the best thing ever please let me I can't believe I discovered it I mean the the views and the likes reflect its quality but I was almost upset that I haven't found it earlier and wanted to find other things like it I don't think I've ever felt that this is the best video ever and that was that and to me the ultimate utopia the best experiences were every single video where I don't see any of the videos I regret in every single video I watch is one that actually helps me grow helps me enjoy life be happy and so on well so that's that's that's a heck of uh the thought that's one of the most beautiful and ambitious I think machine learning tasks so when you look at a society as opposed to any individual user do you think of how YouTube is changing society when you have these millions of people watching videos growing learning changing having debates do you have a sense of yeah what the big impact on society is because I think it's huge but you have a sense of what direction we're taking this world well I mean I think you know openness has had an impact on society already there's a lot of what do you mean by openness well the fact that unlike other mediums there's not someone sitting at YouTube who decides before you can upload your video whether it's worth having you uploaded or worth anybody seeing it really right and so you know there are some creators who say like I I wouldn't have this opportunity to to reach an audience Tyler Oakley often said that you know he wouldn't have had this opportunity to reach this audience if it weren't for YouTube and and so I think that's one way in which YouTube has changed Society I know that there are people that I work with from outside the United States especially from places where literacy is low and they think that YouTube can help in those places because you don't need to be able to read and write in order to learn something important for your life maybe you know how to do some job or how to fix something and so that's another way in which I think YouTube is possibly changing society so I've worked at YouTube for eight almost nine years now and it's fun because I meet people and you know you tell them where they where you work you say you work on YouTube and they immediately say I love you too Yeah right which is great makes me feel great but then of course when I ask them well what is it that you love about YouTube not one time ever has anybody said that the search works outstanding or that the recommendations are great what they always say when I ask them what do you love about YouTube is they immediately start talking about some channel or some creator or some topic or some community that they found on YouTube and that they just loved yeah and so that has made me realize that YouTube is really about the video and connecting the people with the videos and then everything else kind of gets out of the way so beyond the video it's an interesting because you kind of mentioned creator what about the connection with just the individual creators as opposed to just individual video so like I gave the example of Ray Dalio video that the video itself is incredible but there's some people or just creators that I love that they're one of the cool things about people who call themselves youtubers or whatever is they have a journey they usually almost all of them are hurt they suck horribly in the beginning and then they kind of grow you know and then there's that genuineness in their growth so you know YouTube clearly wants to help creators connect with their audience in this kind of way so how do you think about that process of helping creators grow helping the connect with their audience develop not just individual videos but the entirety of a creators life on YouTube well I mean we're trying to help creators find the biggest audience that they can find and the reason why that's you you brought up creator versus video the reason why creator channel is so important is because if we have a hope of of people coming back to YouTube well they have to have in their minds some sense of what they're gonna find when they come back to YouTube if YouTube were just the next viral video and I have no concept of what the next viral video could be one time it's a cat playing a piano and the next day it's some children interrupting a reporter and the next day it's you know some other thing happening then then it's hard for me to to when I'm not watching YouTube say gosh I really you know would like to see something from someone or about something right and so that's why I think this connection between fans and creators so important for both because it's it's a way of a sort of fostering a relationship that can play out into the future let me talk about kind of a dark and interesting question in general and again a topic that you or nobody has an answer to but social media has a sense of you know it gives us highs and gives us lows in the sense that so creators often speak about having sort of burn burn out and having psychological ups and and challenges mentally in terms of continuing the creation process there's a momentum there's a huge excited audience that makes everybody feel that makes creators feel great and I think it's more than just financial I think it's literally just they love that sense of community it's part of the reason I upload to YouTube I don't care about money never well what I care about is the community but some people feel like this momentum and even when there's times in their life when they don't feel you know the for some reason don't feel like creating so how do you think about burnout this mental exhaustion that some YouTube creators go through that's something we have an answer for is that something how do we even think about that well the first thing is we want to make sure that the YouTube systems are not contributing to this sense right and so we've done a fair amount of research to demonstrate that you can absolutely take a break if you are a creator and you've been uploading a lot we have just as many examples of people who took a break and came back more popular than they were before as we have examples of going the other way yeah can we pause on that for a second so the feeling that people have I think is if I take a break everybody well the party will leave right so if you can just linger on that so in your sense that taking a break is okay yes taking a break is absolutely okay and the reason I say that is because we have we can observe many examples of being of creators coming back very strong and even stronger after they have taken some sort of break and so I just want to dispel the myth that this somehow necessarily means that your channel is gonna go down or lose views that is not the case we know for sure that this is not a necessary outcome and so we we want to encourage people to make sure that they take care of themselves that is job one right you you have to look after yourself and your mental health and you know I think that it probably in some of these cases contributes to better videos once they come back right because a lot of people I mean I know myself if I'm burn out on something that I'm probably not doing my best work even though I can keep working until I pass out and so I think that the the taking a break may even improve the creative ideas that someone has okay I think it's a really important thing to sort of to dispel I think it applies to all of social media like literally I've taken a break for a day every once in a while sorry sorry that sounds like a short time but even like sorry email just taking a break from email or only checking email once a day especially when you're going through something psychologically in your personal life or so on or really not sleeping much because it work deadlines it can refresh you in a way that's that's profound and so the same applies there when you came back right it's there and it looks different actually when you come back you sort of brighter I'd some coffee everything the world looks better so it's important to take a break when you need it so you've mentioned kind of the the YouTube algorithm isn't you know e equals MC squared is that's a single equation it's it's potentially sort of more than a million lines of code sort of is it more akin to what autonomous successful autonomous vehicles today are which is they're just basically patches on top of patches of heuristics and human experts really tuning the algorithm and have some machine learning modules or is it becoming more and more a giant machine learning system with humans just doing a little bit of tweaking here and there what's your sense first of all do you even have a sense of what is the YouTube algorithm at this point and whichever however much you do have a sense what does it look like well we don't usually think about it as the algorithm because it's a bunch of systems that work on different services the other that I think people don't understand is that what you might refer to as the YouTube algorithm from outside of YouTube is actually a you know a bunch of code and machine learning systems and heuristics but that's married with the behavior of all the people who come to YouTube every day so the people part of the code Accession exactly right like if there were no people who came to youtube tomorrow then there the algorithm wouldn't work anymore right so that's a critical part of the algorithm and so when people talk about well the algorithm does this the algorithm does that it's sometimes hard to understand well you know it could be the the viewers are doing that and the algorithm is mostly just keeping track of what the viewers do and then reacting to those things in in sort of more fine-grained situations and I and I think that this is the way that the recommendation system and the search system and and probably many machine learning systems evolve is you know you start trying to solve a problem and the first way to solve a problem is often with a simple heuristic right and and you know you want to say what are the videos we're gonna recommend well how about the most popular ones weighted that's where you start and and over time you collect some data and you refine your situations so that you're making less heuristics and you're you're building a system that can actually learn what to do in different situations based on some observations of those situations in the past and and you keep chipping away at these heuristics over time and so I think that just like with diversity you know I think the first diversity measure we took was okay not more than three videos in a row from the same Channel right it's a pretty simple heuristic to encourage diversity it worked right you needs to see four or five six videos in a row from the same Channel and over time we try to chip away at that it and make it more fine-grain and basically have it remove the heuristics in favor of something that can react to individuals and individual situations so how do you you mentioned you know we we know that something worked how do you get a sense when decisions of a kind of a be testing that this idea was a good one this was not so good what's how do you measure that and across which time scale across how many users that kind of that kind of thing well you mentioned that a B experiments and so just about every single change we make to YouTube we do it only after we've run a a B experiment and so in those experiments which run from one week to months we measure hundreds literally hundreds of different variables and and measure changes with confidence intervals in all of them because we really are trying to get a sense for ultimately does this improve the experience for viewers that's the question we're trying to answer and an experiment is one way because we can see certain things go up and down so for instance if we noticed in the experiment people are dismissing videos less frequently or they're saying that they're more satisfied they're giving more videos five stars after they watch them then those would be indications of that the experiment is successful that it's improving the situation for viewers but we can also look at other things like we might do user studies where we invite some people in and ask them like what do you think about this what do you think about that how do you feel about this and other various kinds of user research but ultimately before we launch something we're gonna want to run an experiment so we get a sense for what the impact is going to be not just to the viewers but also to the different channels and all of them an absurd question nobody know what actually is interesting maybe there's an answer but if I want to make a viral video how do I do it I don't know how you make a viral video I I know that we have in the past tried to figure out if we could detect when a video video was going to go viral you know and those were you take the first and second derivatives of the view count and maybe use that to do some prediction but but I can't say we ever got very good at that oftentimes we look at where the traffic was coming from you know if it's if it's a lot of the viewership is coming from something like Twitter then then maybe it has a higher chance of becoming viral than maybe if then if it were coming from search or something but that was just trying to detect a video that might be viral how to make one like I have no idea so yeah you get your kids to interrupt you while you're on the news on the news absolutely as but after the fact on a one individual video so the head of time predicting is a really hard task but after the video went viral in analysis can you sometimes understand why I went viral from the perspective of YouTube broadly first I was even interesting for YouTube that a particular videos viral or is does that not matter for the individual for the experience of people well I think people expect that if a video video is going viral and it's something they would be interested in then I wouldn't I think they would expect YouTube to recommend it to them right um so someone's going viral it's good to just let the wave ride the wave of its violence well I mean we want to meet people's expectations in that way of course so like like I mentioned I hung out with Derek Muller a while ago a couple of months back he's actually the person who suggested I talk to you on this podcast all right well thank you Derek at that time he just recently posted an awesome science video titled why are ninety-six million black balls on this reservoir and in a matter of I don't know how long but like a few days he got thirty million views and it's still growing is this something you can analyze and understand why it happened this video and you won't particularly like it I mean we can surely see where it was recommended where it was found who watched it and those sorts of things so it's actually sorry to interrupt it is the video which helped me discover who Derek is I didn't know who he is before so I remember you know usually I just have all of these technical boring MIT Stanford talks in my recommendation because that's how I watch and then all sudden there's this black balls in reservoir video with like an excited nerd in the would like just and why is this being recommended to me so I close down and watch the whole thing it was awesome but and a lot of people had that experience like why was I recommend this but they all of course watched it and enjoyed it which is what's your sense of this just wave of recommendation and that comes with this viral video that ultimately people get enjoy after they click on it well I think it's the system you know basically doing what anybody who's recommending something would do which is you show it to some people and if they like it you say okay well can I find some more people who are a little bit like them okay I'm gonna try it with them oh they like it too let me expand the circle some more find some more people oh it turns out they like it too so can you just keep going until you get some feedback that says no now you've gone too far these people don't like it anymore and so I think that's basically what happened now you asked me about how to make a video go viral or make a viral video I don't think that if you or I decided to make a video about 96 million balls that it would also go viral it's possible that Derek made like um the canonical video about those black balls yeah lake and so he did actually right and and so I don't know whether or not just following along is the secret yeah but it's fascinating I mean just like you said the algorithm sort of expanding that circle and then figuring out that more and more people did enjoy and that sort of phase shift of just a huge number of people enjoying in the algorithm quickly automatically I assume figuring that out that's a I don't know the dynamics in psychology that is a beautiful thing and so what do you think about the idea of of clipping like and too many people annoyed me into doing it which is they were requesting it I said very beneficial to add clips in like the the coolest points and actually have explicit videos like I'm reapplying a video like a short clip which is what the the podcasts are doing yeah do you see as opposed to like I also add time stamps for the topics no people want the clip do you see YouTube somehow helping creators with that process or helping connect clips to the original videos what is that just in a long list of amazing things to work towards yeah I mean it's not something that I think we've we've done yet but I can tell you that I think clipping is great and I think it's actually great for you as a creator and here's the reason if you think about I mean let's let's say the NBA is uploading videos of of its games well people might search for warriors vs. rockets or they might search for Steph Curry and so a highlight from the game in which Steph Curry makes an amazing shot is an opportunity for someone to find a portion of that video and so I think that you never know how people are gonna search for something that you've created and so you wanna I would say you want to make clips and and add titles and things like that so that they can find it as easily as possible do you have a dream of a future perhaps a distant future when the YouTube algorithm figures that out sort of automatically detects the parts of the video that are really interesting exciting potentially exciting for people and sort of clip them out in this incredibly rich space if you talk about if you thought even just this conversation we probably covered 30 40 little topics and there's a huge space of users that would find you know 30 percent of those topics interesting and that's is very different it's something that's beyond my ability to clip out right but the algorithm might be able to figure all that out sort of expand into clips do you ever you think about this kind of thing do you have a hope a dream that one day the album will be able to do that kind of deep content analysis well we've actually had projects that attempt to achieve this but it really does depend on understanding the video well and our understanding of the video right now is quite crude and so I think it would be especially hard to do it with a conversation like this one might be able to do it with let's say a soccer match more easily right you could probably find out where the goals were scored and then of course you you need to figure out who it was that scored the goal and and that might require human to do some annotation but I think that trying to identify coherent topics in a transcript like like the one of our conversation is is not something that we're gonna be very good at right away and I was speaking more to the general problem actually of being able to do both a soccer match and our conversation without explicit sort of almost my hope was that there exists an algorithm that's able to find exciting things in video so Google now on Google search will help you find the segment of the video that you're interested in so if you search for something like how to change the filter in my dishwasher then if there's a long video about your dishwasher and this is the part where the person shows you how to change the filter then then it will highlight that area and provide a link directly to it and you know if from your recollection do you know if the thumbnail reflects like what's the difference between showing the full video and the shorter clip do you know what how its presented in search results don't remember how its presented and the other thing I would say is that right now it's based on creator annotations got it so it's not the thing I'm talking about but there but but folks are working on the more automatic version it's interesting people might not imagine this but a lot of our systems start by using almost entirely the audience behavior and then as they get better the refinement comes from using the content and I wish and I know there's privacy concerns but I wish YouTube explored the space which is sort of putting a camera on the user's if they allowed it right to study there like I did a lot of emotion recognition work and so on to study actual sort of rich or signal one of the cool things when you upload 360 like VR video to YouTube and I've done this a few times so I've uploaded myself it's a horrible idea some people enjoyed it but whatever the video of me giving a lecture in 360 over 360 camera it's cool because YouTube allows you to then watch where did people look at there's a heat map of where you know avoid the center of the VR experience was and it's interesting because that reveals to you like what people looked at and it's it's very not always what you were though it's not in the case of the lecture is pretty boring it is what we're expecting but we did a few funny videos where there's a bunch of people doing things and they everybody tracks those people you know in the beginning they all look at the main person and they start spreading around and looking into other people it's fascinating so that kind of that's a really strong signal of what people found exciting in the video I don't know how you get that from people just watching except they tuned out at this point like it's hard to measure this moment was super exciting for people I don't know how you get that signal maybe comment is there a way to get that signal where this was like this is when their eyes opened up they're like like for me with the Ray Dalio video right like first I was like okay this is another one of these like dumb it down for you videos and then you like start watching it's like okay there's really crisp clean deep explanation of how the economy works that's where I like set up and started watch right at that moment is there a way to detect that the only way I can think of is by asking people to just label it yeah you mentioned that we're quite far away in terms of doing video analysis deep video analysis ago of course Google YouTube you know we're quite far away from solving autonomous driving problem - yes I don't know I think we're closer to that what the you know you never know and the Wright brothers thought they're never they're not gonna five fifty years three years before they flew so what are the biggest challenges would you say is it the broad challenge of understanding video understanding natural language understanding the the challenge before the entire machine learning community or just being able to understand data is there something specific to video that's even more challenging than an understanding natural language understanding what's your sense of what the biggest video is just so much information and so precision becomes a real problem it's like a you know you're trying to classify something and you've got a million classes and you the distinctions among them at least from a from a machine learning perspective are often pretty small right like you know you need to see this person's number in order to know which player it is and and there's a lot of players or you need to see you know the logo on their chest in order to know like which which team they play for and so and that's just figuring out who's who right and then you go further and saying okay well you know was that a goal was it not a goal like is that an interesting moment as you said or is that not an interesting moment these things can be pretty hard so okay so yawn laocoön I'm not sure if you're familiar sort of with his current thinking and work so he believes that self what is referring to self supervised learning will be the solution sort of to achieving this kind of greater level of intelligence in fact the thing he's focusing on is watching video and predicting the next frame so predicting the future of video right so for now we're very far from that but his thought is because it's unsupervised uh-huh or is it here first to a self supervise you know if you watch enough video essentially if you watch YouTube you'll be able to learn about the nature of reality the physics the common sense reasoning required by just teaching a system to predict the next frame so he's confident this is the way to go so see you from the perspective of just working with this video how do you think an algorithm that just watches all of YouTube stays up all day and night watching YouTube will be able to understand enough of the physics of the world about the way this world works failed to do common-sense reasoning and so on well I mean we have systems that already watch all the videos on YouTube right but they're just looking for very specific things right they're supervised learning systems that are trying to identify something or classify something and I don't know if I don't know if predicting the next frame is really gonna get there because I don't I'm not an expert on compression algorithms but I understand that that's kind of what compression video compression algorithms do is they basically try to predict the next frame and and and then fix up the places where they got it wrong and that leads to higher compression and if you actually put all the bits for the next frame there so so I I don't know if I believe that just being able to predict the next frame is gonna be enough because because there's so many frames and even a tiny bit of error on a per frame basis can lead wildly different videos so the thing is the idea of compression is one way to do compression is to describe through text with containing the video that's the ultimate high level of compression so the idea is tradition when you think of video image compression you're trying to maintain the same visual quality while reducing the size but if you think of deep learning from a bigger perspective what compression is is you're trying to summarize the video and the idea there is if you have a big enough neural network this by watching the next bit trying to predict the next frame you'll be able to form a compression of actually understanding what's going on in the scene if there's two people talking you can just reduce that entire video and into the fact that two people are talking and maybe the content of what they're saying and so on that that's kind of the the open-ended dream so I just wanted to sort of express it because it's interesting compelling notion but it is nevertheless true that video our world is a lot more complicated than we getting credit for I mean in terms of search and discovery we have been working on trying to summarize videos in text or or with some kind of labels for eight years at least and we're kind of so so so and so if you would say it's the problem is a hundred percent solved and eight years ago was zero percent solved how where are we on that timeline would you say yeah to summarize a video well maybe less than a quarter of the way so on that topic what does YouTube look like ten twenty thirty years from now I mean I think that YouTube is evolving to take the place of TV you know I grew up as a kid in the 70s and I watched a tremendous amount of television and I feel sorry for my poor mom because people told her at the time that it was going to rot my brain and that she should kill her television but anyway I mean I think that YouTube is at least for my family a better version of television right it's one that is on demand it's more tailored to the things that my kids want to watch and also they can find things that they would never have found on television and so I think that at least from just observing my own family that's where we're headed is that people watch YouTube kind of in the same way that I watch television when I was younger so from a search and discovery perspective what do you what are you excited about and then the 5 10 20 30 years like what kind of things it's already really good I think it's achieved a lot of of course we don't know what's possible so it's a it's the the task of search of typing in the text or discovering new videos by the next recommendation I personally I'm really happy with the experience that continuously I rarely watch a video that's not awesome from my own perspective but what's what's else is possible what are you excited about well I think introducing people to more of what's available on YouTube is not only very important to YouTube in to creators but I think it will help enrich people's lives because there's a lot that I'm still finding out is available on YouTube that I didn't even know I've been working YouTube eight years and it wasn't until last year that I learned that that I could watch USC football games from the 1970s no like I didn't even know that was possible last year and I've been working there quite some time so you know what was broken about about that but it took me seven years to learn that this stuff was already on YouTube even when I got here so I think there's a big opportunity there and then as I said before you know we want to make sure that YouTube finds a way to ensure that it's acting responsibly with respect to society and enriching people's lives so we want to take all of the great things that it does and make sure that we are eliminating the negative consequences that might happen and then lastly if we could get to a point where all the videos people watch are the best ones they've ever watched that would be outstanding to do you see in many senses becoming a window into the world for people and it's especially with live video you get to watch events I mean it's really it's the way you experience a lot of the world that's out there is better than TV in many many ways so do you see becoming more than just video do you see creators creating visual experiences and virtual worlds so if I'm talking crazy now but sort of virtual reality and entering that space there's that at least for now totally outside of what YouTube is thinking about I mean I think Google is thinking about virtual reality I don't think about virtual reality too much um I know that we would want to make sure that YouTube is there when virtual reality becomes something or if virtual reality becomes something that a lot of people are interested in but I haven't seen it really take off yet take off well the the future is wide open christos I've been really looking forward to this conversation has been a huge honor thank you for answering some of the more difficult questions I've asked I'm really excited about what YouTube has in store for us it's one of the greatest products of ever use and continues so thank you so much for talking it it's my pleasure thanks for asking me thanks for listening to this conversation and thank you to our presenting sponsor cash app downloaded use code Lex podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter now let me leave you with some words of wisdom from Marcel Proust the real voyage of discovery consists not in seeking new landscapes but in having new eyes thank you for listening I hope to see you next time you |
Paul Krugman: Economics of Innovation, Automation, Safety Nets & UBI | Lex Fridman Podcast #67 | the following is a conversation with Paul Krugman Nobel Prize winner in economics professor CUNY and columnist at the New York Times his academic work centers around International Economics economic geography liquidity traps and currency crises but he also is an outspoken writer and commentator on the intersection of modern-day politics and economics which places him in the middle of the tense divisive modern-day political discourse if you have clicked dislike on this video and started writing a comment of derision before listening to the conversation I humbly ask that you please unsubscribe from this channel and from this podcast not because you're conservative a libertarian the liberal or socialist and anarchist but because you're not open to new ideas at least in this case especially and it's most difficult from people with whom you'll largely disagree I do my best to stay away from politics of the day because political discourse is filled with a degree of emotion and self assured certainty that to me is not conducive to exploring questions that nobody knows the definitive right answer to the role of government the impact of automation the regulation of tech the medical system guns war trade foreign policy are not easy topics I have no clear answers despite the certainty of the so-called experts the pundits the trolls the media personalities and the conspiracy theorists please listen empathize and allow yourself to explore ideas with curiosity and without judgment and without derision I will speak with many more economists and political thinkers trying to stay away from the political battles of the day and instead look at the long arc of history and lessons it reveals in this I appreciate your patience and support this is the artificial intelligence podcast if you enjoy it subscribe bye YouTube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma M I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store cash app lets you send money to friends by big coin and invest in the stock market was fractional share trading allowing you to buy $1 worth of a stock no matter what the stock price is brokerage services that provided by cash app investing a subsidiary of square and member si PC get cash app from the App Store and Google Play and use the code Lex podcast you'll get ten dollars in cash Apple also donate ten dollars to the first one of my favorite organizations that is helping to advance robotics and stem education for young people around the world since cash app does fractional share trading let me say that to me it's a fascinating concept the order execution algorithm that works behind the scenes to create the abstraction of fractional orders for the investor is an algorithmic marvel so big props to the cash app engineers for that I like it when tech teams solve complicated problems to provide in the end a simple effortless interface that abstract away all the details of the underlying algorithm and now here's my conversation with Paul Krugman what does a perfect world a utopia from an economics perspective look like Wow I don't really I don't believe in perfection I mean somebody once once said that his ideal was slightly imaginary Sweden it I mean I like an economy that has a a really high safety net for people a good environmental regulation and you know not something that's not that's kind of like some of the better run countries in the world but with fixing all of the the smaller things that are wrong with them what about wealth distribution well obviously you know total equality is is neither possible nor I think especially desirable but I think you want one where basically one where nobody is nobody's hurting and where everybody lives in the same material universe everybody is basically living in the same society so no I think it's a bad thing to have people who are so wealthy that they're really not in the same world as the rest of us what about competition you see the value of competition when what may be its limits Oh competition is great when it can work I mean that there's a UH uh you know I remember I'm old enough to remember when there was only one phone company and there was really limited choice and I think the arrival of multiple multiple phone carriers and all that has actually he has been up been a really good thing and that's that's true across many areas but not every industry is not every activity is suitable for competition so there are some things like health care where competition actually doesn't work and so it's it's it there's it's not one size fits all it's interesting what is competition now work in in health care oh there's a long list I mean there's a famous paper by Kenneth arrow for 1963 which still holds up very well where he kind of runs down the list of things you need for competition to work well basically both sides to every transaction being well-informed having a you know the ability to make intelligent decisions understanding what's going on and healthcare fails on every dimension you know you did health care so not health insurance health care well both health care and health insurance health insurance being part of it but no health insurance is is it is really the idea that there's effective competition between health insurers is wrong in health care I mean the idea that you can comparison shop for for major surgery is is just you know it it - when people say things like that you you wonder are you living in the same world I'm living in you know that the piece of well-informed that was always an interesting piece for me just observing as an outsider because so much beautiful such a beautiful world as possible and everybody's well informed a question for you is how hard is it to be well-informed about anything whether it's health care or any kind of purchasing decisions or just life in general in this world oh information you know in theory is hugely I mean there's more information at your fingertips than ever before in history the trouble is first of all that some of that information isn't true so it's really hard and and then some of it's just too hard to understand so if I'm if I'm buying a car I can actually probably do a pretty good job of looking up you know going to consumer reports reviews you can get a pretty good idea of what you're getting when you get a car if I'm going in for surgery first of all it's you know you think fairly often that happens when without your be able being able to plan it but also there's a reit you know medical school takes many many years and going on the internet for some advice is not usually a very good substitute so speaking about news and not being able to trust certain sources of information how much disagreement is there about I mention utopia perfection in the beginning but how much disagreement is there about what utopia looks like or as most of the disagreements simply about the path to get there oh I think there's two levels of disagreement one maybe not utopia but justice you know what is a just society and that's there are different views I mean I teach my students that there are you know too broadly speaking two views of justice one focuses on on outcomes you ask your it's a just society is the one you would choose if you were trying to what the one that you would choose to live in if you didn't know who you were going to be that's kind of John Rawls and the other focuses on process that just society is one in which there is no no coercion except we're absolutely necessary and there's no there's no objective way to choose between those I'm pretty much a Rawls in and I think many people are okay with it there's so there's a legitimate dispute about what what we mean by a just society anyway but then there's also a lot of disputes about what actually works there there's a range of legitimate dispute I mean any card-carrying economist will say that incentives matter but how much do they matter how much does a higher tax rate actually deter people from working how much does a a stronger safety net actually lead people to to to get lazy I I have a pretty strong view that the evidence is points to a conclusions that are considerably to the left of where most of our politicians are but but that there is legitimate room for disagreement on those things so you've mentioned outcomes what are some metrics you think about the keep in mind like the Gini coefficient but really anything that measures how good we're doing whatever we're trying to do well what are the metrics to keep an eye on well I'm actually I'm not a fan of the Gini coefficient not because what is the Gini coefficient okay the Gini coefficient is a measure of inequality and it is commonly used because it's a single number it usually tracks with other measures but the trouble is there's no sort of natural interpretation of it you ask me what you know what what does a society with the genie of 0.45 look like as opposed to society with a genie of 0.25 and well I can kind of tell you you know when the 0.25 is Denmark and 0.45 is Brazil but it's that's a really there's no sort of easy way to do that mapping I mean I I look at things like what is first of all things like what is the income of the the the median family what is the income of the top 1% how many people are in poverty by various measures of poverty and then I think we want to look at questions like how healthy are people how how is life expectancy doing and how satisfied are people with their lives because there is it's that they has sounds like a squishy number not so much happiness it turns out that life satisfaction is a better measure than the happiness but life satisfaction that varies quite a lot and I think it I think it's meaningful if not too rigorous to say look according to that kind of according to polling people in Denmark are pretty satisfied with their lives and people in the United States not so much so and of course Sweden wins every time no actually Denmark wins these ends Denmark and Norway tend to win these days Sweden doesn't do badly but they're there they're it's none of these are perfect but look I think by and large I there's a bit of a pornography test if you how do you know a decent Society well you kind of know it when you see it right where is America Stan and that we are have a remark our society I mean it's there are a lot of virtues to America but there's a level of harshness brutality an ability for somebody who just has bad luck to fall off the edge that is really shouldn't be happening in a country as rich as ours so we we we have somehow managed to produce a crueler society than almost any other wealthy country for no good reason what do you think is lacking in the safety net that the United States provides you said it's there's a harshness to it and what what are the benefits and maybe limits of a safety net in a country like ours well every other advanced country has some universal guarantee of adequate health care the only in the United States it's the only place where citizens can actually fail to get basic health care because they can't afford it that's that's that's we it's not hard to do everybody else does but we don't we've gotten a little bit better at it than we were but still that's that's a big deal we have remarkably weak support for for children we most countries have substantial safety you know parents of young children get much more support elsewhere they get often nothing in the US we have limited care for people long-term care for for the elderly is a very hiddenness thing but I think that the really big issues are that we don't take care of children who make the mistake of having the wrong parents and we don't take care of people who make the mistake of getting sick and those are those are things that a country a rich country should be doing sorry for a sort of a difficult question but what you just said kind of feels like the right thing to do in terms of just society but is it also good for the economic health of society to take care of to care the people who would the unfortunate members of society by and large it looks like the doing the right thing in terms of justice is also the right thing in terms of economics if we're talking about a society that has extremely high tax rates that deter you know remove all incentives to provide a safety net that is so generous that why bother working or striving that could be a problem but that's that I don't actually know any society that looks like that even even in European country with very generous safety nets people work and and can innovate and do all of these things and there's a lot of evidence now that lacking those basics is actually destructive that children who grow up without adequate health care without adequate nutrition are developmentally challenged they don't live up to their potential as adults so that the United States actually probably pays a price you know we're we're we're harsh we're cruel and we actually make ourselves poor everybody as a society not just the individuals by being so harsh and cruel okay so invisible hand Smith where does that fit in the power of just people acting selfishly and somehow everything taking care of itself to where you know the economy grows nobody there's no cruelty no injustice that the markets themselves what is is their power to that idea where what are its limits there's a lot of power to that I mean there there's a reason why I don't think sensible people want the government running steel mills or they want the government to own the farms right the the markets are a pretty effective way of getting incentives aligned of inducing people to do stuff that works and the invisible hand is saying that you know people farmers aren't growing crops because they want to feed people they're growing crops because they can make money but it actually turns out they're a pretty good way of getting of getting and agricultural products grown so the invisible hand is important part but it's not there's nothing mystical about it it's a it's a mechanism it's a way to organize economic activity which works well given a bunch of preconditions which means that it actually works well for agriculture it works well for manufacturing works well for many services it doesn't work well for healthcare it doesn't work well for education so there are yeah we having a society which is kind of 3/4 invisible hand and one-quarter visible hand seems to be something something on that order seems to be the balance that works best it's just don't want to you don't want to romanticize or missed it you know make it something mystical out of it it's just this is is one way to organize stuff that happens to have what broad but not universal application so then forgive me for romanticizing it but it does seem pretty magical that you you know that I kind of have an intuitive understanding of what happens when you have like 5 10 maybe even 100 people together the dynamics of that but the fact that these large society of people for the most part acting in a self-interested way and maybe electing representatives for themselves that it all kind of seems to work he's pretty magical the fact that there's uh you know that right now there's a wide assortment of fresh fruit and vegetables in the you know in in at the in the local markets up and down the street you know who's who's planning that and the answer is nobody that's the ol that's the invisible hand at work and that's great and and that's a lesson that's that Adam Smith figured out more than two hundred years ago and it's it continues to apply and the the but you know even Adam Smith has a section his book about why it's important to regulate banks so the invisible hand has its limits yeah and that example is actually a powerful one in terms of the supermarket and fruit that was my experience coming from Russia from the Soviet Union is when I first entered a supermarket and just seeing the assortment of fruit bananas yeah I don't think I've seen bananas before first of all but just the selection of fresh fruit was just mind-blowing and it it beyond words and the fact that like like you said I don't know what made that happen well then there is some magic to the market but the there's as showing my age but you know the old movie quote sometimes the magic works and sometimes it doesn't and you have to have some idea of when it doesn't so how do you get regulation right how do what can government at its best to government strangely enough in this country today seems to get a bad rap like everyone seems to everybody's against the government yeah well a lot of money has been spent on making people hate the government but the reality is government does some things pretty well I mean we government does health insurance pretty well so much so I mean given our anti-government bias there it really is true that there are people out there saying don't let the government get its hands on Medicare so the government that got people actually love the government health insurance program far more than they love private health insurance basic education it turns out that your local public high school is the right place to have students trained and private for certainly for-profit education is is a by and large a nightmare of ripoffs and and and grift and and people not getting what they they thought they were paying for its judgment case and it's funny there are things I mean everybody talks if there's the talks about the the DMV as being how do you want the economy and actually my experience is that the DMV have always been positive maybe I'm just going to the right DMVs but in fact a lot of government works pretty well so it you'd have to to some extent you can do these things on a priori grounds you can talk about the logic of why healthcare is not gonna be handled well by the market but partly is just experience we tried where these some countries have tried nationalizing their steel industries that didn't go well but we've tried privatizing education and that didn't go well so you'd find out what works what about this new world of tech how do you see what do you think works for tech is a more regulation or less regulation there are some things that need more regulation and we're finding out that you know the world of social media is is one in which competitive forces aren't working very well and trusting the companies to regulate themselves isn't working very well but I'm on the whole a tech skeptic not in the sense that I think the tech doesn't work and it doesn't do stuff but the idea that we're living through greater technological change than ever before is really an illusion we've ever since the beginning of the Industrial Revolution we've had a series of ethical shifts in the nature of work and in the kinds of jobs that are available and it's not at all clear that what we're at what's happening now is any bigger or faster or harder to cope with than past shocks it is a popular notion in today's sort of public discourse that automation is going to have a huge impact on job market now yeah there is something something transformational happening now he talked about that maybe elaborate a little bit more do you not see the software revolutions happening now with with machine learning availability of data that kind of automation being able to sort of process clean fine patterns and data and you know you don't see that disrupting any one sector to a point where there's a huge loss of jobs there may be some things I mean actually translators there's really reduced demand for translators because we've translation ain't perfect but it ain't bad there are some kinds of things that are changed but it's not overall productivity growth has actually been slowed in recent years now it's been much slower than in some past periods so the idea that automation is taking away all the jobs the counterpart would be that we would be able to you know produce stuff with many fewer workers than before and that's not happening there are a few isolated you know sectors there are some kinds of jobs that that are going with but that keeps on happening I mean they New York City used to have thousands and thousands of longshoremen taking stuff off off ships and tow putting them on ships they're almost all gone now now you have these the giant cranes taking containers on and off ships in Elizabeth New Jersey that's not robots it's doesn't doesn't sound high-tech but it actually pretty much destroyed that occupation well you know that was it wasn't fun for the longshoremen to say the least and but it it's not we coped we moved on and that that sort of thing happens all the time you mean farmers we we used to be a nation which was mostly farmers there are now very few farmers left the end the reason is not that we've stopped eating it's that farming has become so efficient that we don't need a lot of farmers and cope with that too so the the idea that there's something qualitatively different about what's happening now so far isn't true you see yeah your intuition is there is going to be a loss of jobs but it's just the thing that just continues though you know there's nothing qualitatively different about this moment some jobs will be lost others will be created as has always been the case so far maybe there's a singularity maybe there's a moment when when the machines get smarter than we are and sky tech kills us all or something right but the but that's not visible in anything we're seeing now you mentioned the metric of productivity could you explain that a little bit because it's a really interesting one I've heard you mentioned that before the in connection with with automation so what what is that metric and if there is something qualitatively different what should we see in that metric well okay productivity first of all production we do have a measure of the total the economy's total production real GDP which is it's not that it's a little bit of a construct because it's quite literally it's adding apples and oranges so we have to add together various things which we basically do by using market prices but we try to adjust for inflation but it's kind of it's a reasonable measure of how much the economy is producing and goods in sorry to interrupt is a goods and services and services it's everything okay productivity is you divide that total output by the number of hours worked so we're basically asking how much how much stuff does the average worker produce an hour of work and if you're seeing really rapid technological progress then you would expect to see productivity rising at a rapid clip which we did for in the generation after World War 2 productivity rose a 2% a year on a sustained basis then it dropped down for a while then there was a kind of a decade of fairly rapid growth from the mid 90s to the mid 2000s and then it's it dropped off again and it's not it's not impressive right now so you're just not seeing an ethical shift in in in the economy so let me then ask you about the psychology of blaming automation a few months ago you wrote in The New York Times quote the other day I found myself as I often do at a conference discussing lagging wages and soaring inequality there was a lot of interesting discussion but one thing that struck me was how many of the participants just assumed that robots are a big part of the problem that machines are taken away the good jobs or even jobs in general for the most part this wasn't even a presented as a hypothesis just as part of what everyone knows yeah so why is maybe can you psychoanalyze is our the puppet the public intellectuals or economists or us actually the general public yeah why this is happening why this assumption is just infiltrated public discourse there's a couple of things one is that the particular technologies that are advancing now are ones that are a lot more visible to the chattering class the you know if when you had a point when containerization did away with the jobs of longshoreman well not a whole lot of college professors are close friends with longshoremen right and so so we see this one then there is a second thing which is you know we just went through its severe financial crisis and a period of very high unemployment has finally come down the there's really no question that that high unemployment was about macroeconomics it was about a failure of demand but macroeconomics is really not intuitive I mean people just have a hard time wrapping their minds run it and among other things people have a hard time believing that something as trivial as well people just aren't spending enough can lead to the kind of mass misery that we saw in the 1930s or that not quite so severe but still serious misery that we saw after 2008 and there's always a tendency to say it must be something big it must be technological change that means we don't need workers anymore that was a lot of that in the 30s and that same thing happened after 2008 the assumption that it has to be something some deep cause not something as trivial as a failure of investor confidence and inadequate monetary and fiscal response and the last thing that wages did a lot of what's happened on wages is at some level political if the collapse of the union movement it's the it's policies that have squeezed workers bargaining power and for kind of obvious reasons there are a lot of influential people who don't want to hear that story they wanted to be an inevitable force of nature technology is made it impossible to have people earn middle-class wage and they so that they don't they don't like they they don't like the story that says actually no it's kind of the political decisions that we made that have caused this this income stagnation and so there are a receptive audience for technological determinism so what comes first in your view the economy or politics in terms of what has impact on the other oh they looked at it everything interacts she has some one of the rules of that I was taught in economics everything everything affects everything else in at least two ways but the the I mean clearly the economy drives a lot of political stuff but also clearly politics has a huge impact on on on the economy there we we look at the decline of unions in America and said well you know it's the world has changed and unions don't have a role but you know two-thirds of workers in Denmark are unionized and Denmark face has the same technology and faces the same global economy that we do is just a difference in political choices that leads to that difference so I actually teach a course here at CUNY on called economics of the welfare state which is about things like health care and retirement and to some extent wage policy and so on and the message I keep on trying to drive home is that look in all advanced countries they've got roughly equal competence we all have the same technology but we make very different choices not that America always makes the wrong choices we do some things pretty well our retirement system is is one of the better ones but but the point is that the there's a huge amount of political choice involved in the in the shape of the economy what is what is a welfare state well in welfare state is the old term that but it basically first all the programs that are there to mitigate if you like the the risks and in justices of the market economies so in the US welfare state is Social Security Medicare Medicaid minimum wages food stamps when you say welfare state my first sir feeling is a negative one well I know I like all I probably generally at least theoretically like all the welfare programs well that's it's been demonized and to some extent I'm being a little doing a little bit of thumbing my nose at all of that by just using the term welfare state although it's not I see ya there I got you but everybody every advanced country actually has a lot of of a welfare state than the US I mean we that's fundamental part of the fabric of our society the Social Security Medicare Medicaid are just things we take for granted as part of the scene and so if you you know that there there's a lot of there's people on the right wing who are say oh it's it's it's all socialism and well I guess mean what you want them to mean and we just just today I I told my class about the the record that Ronald Reagan made in 1961 warning that Medicare would destroy American freedom and but sort of didn't happen on the topic of welfare state what are your thoughts on universal basic income and a sort of a a gin not a generic but a universal safety net of this kind there's always a trade-off when we talk about social safety net programs there's always a trade-off between universality which is clean but means that you're giving a lot of money to people who don't necessarily need it and some kind of targeting which makes it easier to get to deal with the crucial problems with limited resources but but both has incentive problems and kind of political and I would say even psychological issues so the great thing about Social Security and Medicare is no questions asked you know no you don't have to prove that you need them i it's comes you know I didn't I'm on medic here I allegedly I mean it's it's run through my my my New York Times health insurance but you know I didn't have to file an application with the Medicare office to prove that I needed it just happened when I turned 65 there's that's good for dignity and it's also good for the political support because everybody gets Medicare on the other hand if you and and we can do that with health care to give everybody a guarantee of an income that's enough to live on comfortably but that's a lot of money what about enough income to carry you over to difficult periods like if you lose a job that kind of well we have unemployment insurance and I think our unemployment insurance is too short lived and too stingy it would be better to have a more comprehensive unemployment insurance benefit but the trouble with with something like universal basic income is that either the bar is set too low so it's really not something you can live on or it's an enormous ly expensive program and so at this point I think that we can do far better by building on the kinds of safety net programs we have I mean food stamps Earned Income Tax Credit we should have a lot more family support policies those things can deal with can do a lot more to really diminish the amount of misery in this country ubi is something that is being I mean it it goes kind of hand-in-hand with with this belief that the robots are going to take all of our jobs and if that was really happening then I might reconsider my views on UPI but I don't see that happening so are you happy with this course as going on now in terms of politics so you mentioned a few political candidates is is the kind of thing going on and on both on Twitter and debates in the media through the written words is a spoken word how do you assess the public discourse now in terms of politics we're in a fragmented world so more so more so than ever before so at this point the public discourse that you see if if you're if Fox News is your principal news source is is very different from the one you get if you read the New York Times on the whole my sense is that mainstream political reporting policy reporting is a not too great but be better than it's ever been because of what when I first got into the you know the pundit business it was just awful lots of things just never got covered and if things did get covered it was always both sides I mean it's the line that comes back from me writing during the 2000 campaign was that it if one of the candidates said that the earth was flat the the headline would de use differ on shape of planet I mean it's a and and it's that's less true there's still a fair bit of that out there but it's less true than there used to be and there are more people reporting writing on on policy issues who actually understand them than ever before so though that's good but I still I have how much the typical voter is actually informed unclear I mean they the the Democratic debates I think we I'm hoping that we finally get down to having a not having 27 people on the stage or whatever it is they have but but yeah they're reasonably substantive certainly better than before and while there's a lot of still you know theater criticism instead of actual analysis and the reporting it's it's not as totally dominant as in the past it can ask maybe a dumb question but from an open-minded perspective when you know people on the left and people on the right I think view the other the others as sometimes Complete Idiot's yeah it what do we do with that you know is it possible that the people on the right are correct about their what they currently believe is that kind of open-mindedness helpful or is this division long term productive for us to sort of have this food fight well the trouble you have to confront is that there's a lot of stuff that just is false out there and but commands extensive political allegiance so the idea well both sides need to listen to each other respectfully I'm happy to do that when there's a view that is worthy of respect but a lot of stuff is not and so take economics is something where I think I know something and I'm not sure that I'm always right in fact I know I've been wrong plenty of times but I think there is a difference between economic views that are within the realm of we can we can actually have an interesting discussion and those that are just crank doctrines or things that that are purely being disseminated because people are being paid to disseminate them so there are there are plenty of good serious center-right economists that are happy to to talk to none of those center-right economists has any role in the Trump administration the Trump administration and by a large Republicans in Congress only want to listen to people who are cranks and so I think it's being dishonest with my readers too to pretend otherwise there's no way I can reach out to people who think that that reading ain't ran novels is is is how you learned about monetary economics let me linger on that point so if you look at Iran okay so you said center-right what about extreme people who have like radical views you think they're not grounded in any kind of data in the kind of reality I'm just sort of curious about how open we should be to ideas that seem radical Oh radical ideas is fine but then you have to asked I have to ask is there some basis for the radicalism and if it's if it's a if it's something that is not grounded in anything then and particularly by the way if it's something that's been refuted by evidence again and again and people just keep saying if it's a zombie idea and there's a lot of those out there then there comes a point when it's not worth trying to fake respect for it I see so there's a through the scientific process you've shown that this idea does not hold water but I like the idea zombie ideas but they live on through it's like the idea that the earth is flat for example has been for the most part that's proven yeah but it lives on actually is growing in popularity currently yeah and there's a lot of that out there and there you can't you can't wish it away and it's you're not being fair to either yourself or if you're somebody who writes for the public you're not being fair to your readers to pretend otherwise so quantum mechanics is a strange theory but it's testable and so while being strangest widely accepted among physicists how robust and testable our economics theories if we compare them to quantum mechanics and physics and so on okay economics look it's a complex system and it's also one in which by and large you don't get to do experiments and so economics is never going to be like quantum mechanics that said you get natural experiments you get tests of rival doctrines you know in the immediate aftermath of the financial crisis there was one style one one basic theory of macroeconomics which ultimately goes back to John Maynard Keynes that made a few predictions it said under these circumstances printing money will not be inflationary running big budget deficits will not react cause a rise in interest rates slashing government spending austerity policies will lead to two depressions if tried other people who had you know exactly the opposite predictions and we got a fairly robust test and you know one one theory one interest rates stayed low inflation stayed low austerity countries that implanted harsh austerity policies suffered severe economic downturns you don't get much you know that's that's pretty clear and that's not going to be true on everything but there's a lot of empirical I mean the younger economists these days are very heavy heavily data base syndrome and it's and that's great and I'm I think that's that's the way to go what theories of economics there is there currently a lot of disagreement about would you say Oh first of all there's just a lot less disagreement really among serious researchers in economics than people imagine when we actually we contract that the Chicago Booth School has a panel an ideologically diverse panel and they oppose the regularly posed questions and on most thing there there's a huge that there's remarkable consensus there's a lot of of things where there you people imagine that there's dispute but that the the illusion of dispute is something that's basically being fed by political forces and and there isn't really I mean there are I think we questions about what are effective ways to regulate technology industries we really don't know the answer is there there's a or what I don't follow every part minimum wages I think there's there's pretty overwhelming evidence that that a modest increase in the minimum wage from current levels would be would not have any noticeable adverse effect on jobs but if you asked how high could it go $12 seems pretty safe given what we know 15 is 15 okay there's some legitimate disagreement there I think probably but but I can people have a point 20 where where is the line at which it starts to become a problem and the answer is truly we don't know it's fascinating to try to such a cool economics is cool in that sense a you because you're trying to predict something that hasn't been done before the impact the effects of something that hasn't been done before yeah you're trying you're going out-of-sample and and we have good reason to believe that that there are no that it's nonlinear that there comes a point at which it doesn't work the way it has in the past so as an economist how do you see science and technological innovation when I took various economics courses in college technological innovations seem like a no-brainer way of growing an economy and we should invest in it aggressively yeah I may be biased but it seemed like the various ways to grow an economy it seems like the easiest way especially long term is that correct and if so why aren't we doing it more well that's okay the first question is yeah I mean all it's pretty much overwhelming we think we can more or less measure this although there are some assumptions involved but it's something like 70 to 80 percent of the growth in per capita income is is basically the advance of knowledge it's not just it's not just a crude accumulation of capital it is it is the fact that we can get smarter a lot of that by the way is more prosaic kinds of technology so you know we I like to talk about things like containerization or you know an earlier period the you know the invention of the flat a cardboard box I have to be invented and and now all of your deliveries from Amazon are made possible by the existence of that technology that the web stuff is important to but but what would we do without cardboard boxes so but all of that stuff is really important in driving economic progress why don't we invest more why don't we invest more in you again more prosaic stuff why aren't why haven't we built another goddamn real tunnel under the Hudson River which is for which the need is is so totally overwhelmingly obvious how do you think about first of all I don't even know what the word prosaic means but I inferred it but how do you think about prosaic is it the really most basic dumb technology innovation or is it just like the lowest hanging fruit of war benefiting me gained when I say prosaic I mean stuff that is not sexy and and fancy and high-tech it's building bridges and tunnels having inventing the cardboard box were the I don't know where do we put EZ Pass in there that's a it is it is actually using some the modern technology and all that but it it's you're not gonna have I don't think you're gonna make a movie about about the fact that the guy who ever wasn't that easy pass but but it's actually a pretty significant productivity booster to me it always seem like it's something that everybody should be able to agree on and just invest so like in the same way there's the investment in the military and the DoD is huge so everyone kind of not everyone but there's a there's a there's an agreement amongst people that somehow that a large defense is important it always seemed to me like that should be shifted towards if you want to grow prosperity of the nation you should be investing in knowledge yes prosaic stuff infrastructure investing infrastructure and so on I mean sorry to linger on it but do you have any intuition do you have a hope that that changes the idea of intuition why it's not changing it's uncommon in tradition I have a theory I'm reasonably certain that I understand why why we don't do it and it's it's because because we have a real values dispute about the welfare state about how much the government should do to help the unfortunate and politicians believe probably rightly that there's a kind of halo effect that surrounds any kind of government intervention that even though providing people with enhanced Social Security benefits is really very different from building a tunnel under the Hudson River politicians of both parties seem to believe that it's the government is seen to be successful at doing one kind of thing it will make people think more favorably on doing other kinds of things and so we have conservatives tend to be opposed to any kind of increase in government spending except military no matter how obviously a good idea it is because they fear that it's the thin end of the wedge for bigger government in general and to some extent liberals tend to favor spending on these things partly because they see it as a way of proving that government can do things well and therefore it can turn to broader social goals it's clearly can there's a if you like the what you might have thought would be a technocratic discussion about government investment both in research and in infrastructure is contaminated by the fact that government is government and people link it to other government actions perhaps silly question but as a species we're currently working on venturing out into space one day colonizing Mars so when we start a society on Mars from scratch what political and economic system should operate under oh I'm a big believer in first of all I don't think we're actually gonna do that but does let's uh let's imagine hypothesize that we colonize Mars or something look representative democracy is vs. pure democracy well yeah but pure democracy where people vote directly on everything his is really problematic because people don't have time to to to try and master every issue I mean we could see what government by referendum looks like there's a lot of that in in California and it's uh it doesn't work so good because it's hard to explain to people that the various things they vote for may conflict so representative democracy is it's got lots of problems and I kind of Winston Churchill thing right it's the worst system well you know except for all the others but so yes thinking with a representative and basically the American system of regulation and markets and the economy we have going on is a pretty pretty good one for Mars if you start from scratch if you didn't start from scratch you wouldn't you wouldn't want to send it where sixteen percent of the population has half the seats you probably would want one which is more actually more representative than what we have and the details it's unclear I mean the we when times are good all of the various representative democracy systems whether it's parliamentary democracies or a us-style system whether you have a prime minister or the head of state as an elected president they all kind of work well then they all when times are good and they all have different modes of breakdowns I'm not sure I know what the answer is but but something like that is given what we've seen through history it's the least bad system out there I mean I don't know I'm a big fan of the TV series the expanse and it's kind of gratifying that out there they the it's the Martian congressional republic okay in a brief sense so amongst many things you're also an expert in international trade what do you make of the the complexity so I can understand trade between two people say to neighboring farmers it seems pretty straightforward to me but international we need to start talking about nations and nations trading seems to be very complicated so from a high level why is it so complicated what are all the different factors that weigh the objectives need to be considered an international trade and maybe feeding that into a question of you have concerns about the two giants right now of the u.s. in China and an intention that's going on with the international trade there with the trade war well first of all international trade is not really that different from trade among individuals when it's it it's vastly more complex and there are there are many more players but in the end the reasons why countries trade are pretty much the same as the reasons why individuals trade you countries trade because they're different and they can derive mutual advantage from concentrating the things they do relatively well and also there are the economies of scale you know you don't not individuals have to decide whether to be a surgeon or a or an accountant it's probably not a good idea to try and be both in countries benefit from specializing just because of the inherent advantages of specialization and that's so the now the the fact it's a big world and they were talking about millions of products being traded and in today's world often trade involves many stages so that made in China iPhone is actually assembled from components that are made all over the world and but it doesn't really change the the fundamentals all that much there's a recurrence I mean that the baked the big the dirty little secret of international trade conflict is that actually it's not conflicts among countries are really not that important most trade is beneficial to both sides and to both countries but it has big impacts on the distribution of income within countries so the growth of US trade with China has made both US and China richer but it's been pretty bad for people who were employed in the North Carolina furniture industry who did find that their jobs were displaced by a wave of imports from China and so that's where the complexity comes in not at all clear to me I mean they we have some real problems with China though they really involve trade so much as as things like respect for intellectual property not clear that those real problems that we do have with China have anything to do with the current trade war trade war seems to be driven instead by a fundamentally wrong notion that when we sell goods to China that's good and when we buy goods from China that's bad and that's that's misunderstanding the whole point he's a is trade which I'm in both directions a good thing yeah we would be poorer if it wasn't for it but it but there are there are downsides as there are for any economic change it's like any new technology makes us richer but often hurts some place some people trade with China makes us richer but hurt some people and I I wouldn't undo what has happened but I wish we had had a better policy for supporting incumbents the losers from that growth so we live in a time of rec reticle ization of political ideas Twitter mobs and so on and yet here you are in the midst of it both tweeting and writing in New York Times articles strong opinions riding this chaotic wave of public discourse do you ever hesitate or feel a tinge of fear for exploring your ideas publicly and unapologetically oh I feel fear all the time it's not too hard to imagine scenarios in which this is I might personally find myself kind of in there in the crosshairs and I mean I'm the I am the king of hate mail I get them amazing correspondents uh does it affect you it did that it did when I started these days I've developed a very thick skin so I know I don't usually get in fact if I if I don't get a wave of hate mail after a column then then I've probably wasted the that that day so what do you make of that as a as a person who's putting ideas out there if you look at the history of ideas the way it works is you write about ideas you put them out there but now when there is so much hate mail so much division what advice do you have for yourself and for others trying to have a discussion about ideas difficult ideas well I don't know what about advice for others I mean if for most economists you just do your research that's a we can't all be public intellectuals and we shouldn't try to be and in fact I I I'm glad that I didn't get into this business until I was and until I was in my late 40s I mean this is it's probably best to spend the the your decades of greatest intellectual flexibility addressing deep questions not not confronting Twitter mobs and the and as for the rest point I think when you're writing about stuff the sort of dance it's like no one's watching like nobody is reading right right what your than what you think is right Jaya trying to make it obviously trying to make it it comprehensible and persuasive but don't let yourself get intimidated by the fact that some people are going to say say nasty things it's you can't you can't do you can't do your job if you are worried about criticism well I think I speak for a lot of people and saying that I hope that you keep dancing like nobody's watching on Twitter and New York Times and books so Paul is been an honor thank you so much for talking to a great thanks for listening to this conversation with Paul Krugman and thank you to our presenting sponsor cash app downloaded and use code let's podcast you'll get ten dollars and ten dollars will go to first an organization that inspires and educates young minds to become science technology innovators of tomorrow if you enjoy this podcast subscribe on YouTube get five stars on Apple podcast follow on Spotify support on patreon or simply connect with me on Twitter at lex friedman and now let me leave you some words from Adam Smith in the wealth of nations one of the most influential philosophers and economists in our history it is not from the benevolence of the butcher the brewer or the Baker that we expect our dinner but from their regard to their own interest we address ourselves not to their humanity but to their self-love and never talk to them of our necessities but of their advantages thank you for listening and hope to see you next time you |
Ayanna Howard: Human-Robot Interaction & Ethics of Safety-Critical Systems | Lex Fridman Podcast #66 | the following is a conversation with Ayane Howard she's a roboticist professor Georgia Tech and director of the human automation systems lab with research interests in human robot interaction assisted robots in the home therapy gaming apps and remote robotic exploration of extreme environments like me in her work she cares a lot about both robots and human beings and so I really enjoyed this conversation this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience 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engineering a better world and now here's my conversation with Ayane Howard what or who is the most amazing robot you've ever met or perhaps had the biggest impact on your career I haven't met her but I grew up with her but of course Rosie so and I think it's because also who's Rosie Rosie from the Jetsons she is all things to all people right think about it like anything you wanted it was like magic it happened so people not only anthropomorphize but project whatever they wish for the robot to be onto but also I mean think about it she was socially engaging she every so often had an attitude right she kept us honest she would push back sometimes when you know George was doing some weird stuff but she cared about people especially the kids she was like the the perfect robot and you've said that people don't want their robots to be perfect can you elaborate that what do you think that is just like you said Rosie pushed back a little bit every once in a while yeah so I I think it's that so you think about robotics in general we want them because they enhance our quality of life and usually that's linked to something that's functional right even if you think of self-driving cars why is there a fascination because people really do hate to drive like there's the like Saturday driving where I can just be but then there was the I have to go to work every day and I'm in traffic for an hour I mean people really hate that and so robots are designed to basically enhance our ability to increase our quality of life and so the perfection comes from this aspect of interaction if I think about how we drive if we drove perfectly we would never get anywhere right so think about how many times you had to run past the light because you see the car behind you is about to crash into you or that little kid kind of runs into the street and so you have to cross on the other side because there's no cars right like if you think about it we are not perfect drivers some of it is because it our world and so if you have a robot that is perfect in that sense of the word they wouldn't really be able to function with us can you linger a little bit on the word perfection so from the robotics perspective what does that word mean and how is sort of the optimal behaviors you're describing different than what we think that's perfection yeah so perfection if you think about it in the more theoretical point of view it's really tied to accuracy right so if I have a function can I complete it at 100% accuracy with zero errors and so that's kind of if you think about perfection in the size of the word and in a self-driving car realm do you think from a robotics perspective we kind of think that perfection means following the rules perfectly sort of defining staying in the lane changing lanes when there's a green light you go and there's a red light you stop and that that's the and be able to perfectly see all the entities in the scene that's the limit of what we think of as perfection and I think that's where the problem comes is that when people think about perfection for robotics the ones that are the most successful are the ones that are quote unquote perfect like I said Rosie is perfect but she actually wasn't perfect in terms of accuracy but she was perfect in terms of how she interacted and how she adapted and I think that's some of the disconnect is that we really want perfection with respect to its ability to adapt to us we don't really want perfection with respect to 100% accuracy with respect to the rules that we just made up anyway right and so I think there's this disconnect sometimes between what we really want and what happens and we see this all the time like in my research right like the the optimal quote unquote optimal interactions are when the robot is adapting based on the person not 100% following what's optimal based on the roles just to linger on autonomous vehicles for a second just your thoughts maybe off the top of her head is how hard is that problem do you think based on what we just talked about you know there's a lot of folks in the automotive industry they're very confident from Elon Musk two-way mode all these companies how hard is it to solve that last piece did the gap between the perfection and the human definition of how you actually function in this world so this is a moving target so I remember when all the big companies started to heavily invest in us and there was a number of even roboticists as well as you know folks who were putting in the VCS and and corporations Elon Musk being one of them that said you know self-driving cars on the road with people you know within five years that was a little while ago and now people are saying five years ten years twenty years some are saying never right I think if you look at some of the things that are being successful is these basically fixed environments where you still have some anomalies wait you still have people walking you still have stores but you don't have other drivers right like other human drivers are is a dedicated space for the for the cars because if you think about robotics in general where has always been successful is I mean you can say manufacturing like way back in the day right it was a fixed environment humans were not part of the equation we're a lot better than that but like when we can carve out scenarios that are closer to that space then I think that it's where we are so a closed campus where you don't have self-driving cars and maybe some protection so that the students don't jet in front just because they want to see what happens like having a little bit I think that's where we're gonna see the most success in the near future and be slow-moving right not not you know 55 60 70 miles an hour but the the speed of a golf cart right so that said the most successful in the automotive industry robots operating today in the hands of real people are ones that are traveling over 55 miles an hour and in our constrains environment which is Tesla vehicles so we'll test the autopilot so I just I would love to hear of your just thoughts of two things so one I don't know if you've gotten to see you've heard about something called smart summon wait what Tesla system part Apollo system where the car drives zero occupancy no driver in the parking lot slowly sort of tries to navigate the parking lot to find itself to you and there's some incredible amounts of videos and just hilarity that happens as it awkwardly tries to navigate this environment but it's it's a beautiful nonverbal communication between machine and human that I think is a from it's like it's some of the work that you do in this kind of interesting human robot interaction space so what are your thoughts in general water so I I do have that feature new driver Tesla I do mainly because I'm a gadget freak right so I it's a gadget that happens to have some wheels and yeah I've seen some of the videos but what's your experience like I mean your your human robot interaction roboticist you're legit sort of expert in the field so what does it feel for machine to come to you it's one of these very fascinating things but also I am hyper hyper alert right like I'm hyper alert like my but my thumb is like okay I'm ready to take over even when I'm in my car or I'm doing things like automated backing into so there's like a feature where you can do this automating backing into our parking space our bring the car out of your garage or even you know pseudo autopilot on the freeway right I am hyper sensitive I can feel like as I'm navigating like yeah that's an error right there like I am very aware of it but I'm also fascinated by it and it does get better like it I look and see it's learning from all of these people who are cutting it on like every come on it's getting better right and so I think that's what's amazing about it is that this nice dance of you're still hyper-vigilant so you're still not trusting it at all yeah yeah you're using it what on the highway if I were to like what as a roboticist we'll talk about trust a little bit what how do you explain that you still use it is it the gadget freak part like where you just enjoy exploring technology or is that the right actually balance between robotics and humans is where you use it but don't trust it and somehow there's this dance that ultimately is a positive yes so I think I'm I just don't necessarily trust technology but I'm an early adopter right so when it first comes out I will use everything but I will be very very cautious of how I use it do you read about or do you explore but just try it they do like it's crudely to put a crew they do you read the manual or do you learn through exploration I'm an explorer if I have to read the manual then you know I do design then it's a bad user interface it's a failure Elon Musk is very confident that you kind of take it from where it is now to full autonomy so from this human robot interaction you don't really trust and then you try and then you catch it when it fails to it's going to incrementally improve itself into full full way you don't need to participate what's your sense of that trajectory is it feasible so the promise there is by the end of next year by the end of 2020 it's the current promise what's your sense about that journey that test is on so there's kind of three three things going on now I think in terms of will people go like as a user as a adopter will you trust going to that point I think so right like there are some users and it's because what happens is when technology at the beginning and then the technology tends to work your apprehension slow slowly goes away and as people we tend to swing to the other extreme right because like oh I was like hyper hyper fearful or hypersensitive and was awesome and we just tend to swing that's just human nature and so you will have I mean it is a scary notion because most people are now extremely untrusting of autobot they use it but they don't trust it and it's a scary notion that there's a certain point where you allow yourself to look at the smartphone for like 20 seconds and then there'll be this phase shift will be like 20 seconds 30 seconds 1 minute 2 minutes this is scary it's opposition but that's people right that's human that's humans I mean I think of even our use of I mean just everything on the internet right like think about how relying we are on certain apps and certain engines right 20 years ago people have been like oh yeah that's stupid like that makes no sense like of course that's false like now it's just like oh of course I've been using it it's been correct all this time of course aliens I didn't think they existed but now it says they do obvious nth earth is flat so okay but you said three things so one is okay so one is the human and I think there would be a group of individuals that will swing right I just teenagers gene it I mean it'll be clean it'll be adults there's actually an age demographic that's optimal for a technology adoption and you can actually find them and they're actually pretty easy to find just the based on their habits based on so someone like me who wouldn't wasn't no robot Isis or probably be the optimal kind of person right early adopter okay with technology very comfortable and not hyper sensitive right I'm just the hyper sensitive because I designed this stuff yeah so there is a target demographic that will swing the other one though is you still have these hue that are on the road that one is a harder harder thing to do and as long as we have people that are on the same streets that's going to be the big issue and it's just because you can't possibly know well so you can't possibly map the some of the silliness of human drivers right like as an example when you're next to that car that has that big sticker called student driver right like you are like oh either I am going to like go around like we are we know that that person is just gonna make mistakes that make no sense right how do you map that information or if I'm in a car and I look over and I see you know two fairly young looking individuals and there's no student driver bumper and I see them chit-chatting to each other I'm like oh yeah that's an issue right so how do you get that kind of information and that experience into basically an autopilot yeah and there's millions of cases like that where we take little hints to establish context I mean you said kind of beautifully poetic human things but there's probably subtle things about the environment about is about it being maybe time for commuters start going home from work and therefore you can make some kind of judgment about the group behavior of pedestrians or even cities right like if you're in Boston how people cross the street like lights are not an issue versus other places where people will will actually wait for the crosswalk or somewhere peaceful and but what I've also seen so just even in Boston that intersection the intersection is different so every intersection has a personality of its own so that certain neighborhoods of Boston are different so we kind of end the based on different timing of day at night it's all it's all there's a there's a dynamic to human behavior that would kind of figure out ourselves we're not be able to we're not able to introspect and figure it out but somehow we our brain learns it we do and so you're you're saying is there so that's the shortcut that's their shortcut though for everybody is there something that could be done you think that you know that's what we humans do it's just like bird flight right this example they give for flight do you necessarily need to build the bird that flies or can you do an airplane is there shortcut so I think the the shortcut is and I kind of I talk about it as a fixed space where so imagine that there is a neighborhood that's a new smart city or a new neighborhood that says you know what we are going to design this new city based on supporting self-driving cars and then doing things knowing that there's anomalies knowing that people are like this right and designing it based on that assumption that like we're gonna have this that would be an example of a shortcut so you still have people but you do very specific things to try to minimize the noise a little bit as an example and the people themselves become accepting of the notion that there's autonomous cars right right like they move into so right now you have like a you will have a self-selection bias right like individuals will move into this neighborhood knowing like this is part of like the real estate pitch right and so I think that's a way to do a shortcut when it allows you to deploy it allows you to collect then data with these variances and anomalies because people are still people but it's it's a safer space and it's more of an accepting space ie when something in that space might happen because things do because you already have the self selection like people would be I think a little more forgiving than other places and you said three things that would cover all of them the third is legal liability which I don't really want to touch but it's still it's it's still of concern in the mishmash with like with policy as well sort of government all that that whole that big ball of mess yeah gotcha so that's so we're out of time what do you think from robotics perspective you know if you if you're kind of honest of what cars do they they kind of kind of threaten each other's life all the time so cars are very us I mean in order to navigate intersections there's an assertiveness there's a risk-taking and if you were to reduce it to an objective function there's a probability of murder in that function meaning you killing another human being and you're using that first of all yeah it has to be low enough to be acceptable to you on an ethical level as a individual human being but it has to be high enough for people to respect you to not sort of take advantage of you completely and jaywalking front knee and so on so I mean I don't think there's a right answer here but what's how do we solve that how how do we solve that from a robotics perspective one danger and human life is at stake yeah as they say cars don't kill people people kill people people right so I think now robotic algorithms would be killing right so it will be robotics algorithms that are prone oh it will be robotic algorithms don't kill people developers of the right account or there was kill people right I mean one of the things as people are still in the loop and at least in the near and midterm I think people will still be in the loop at some point even if it's a developer like we're not necessarily at the stage where you know robots are programming autonomous robots with different behaviors quite yet not so scary notion sorry to interrupt that a developer is has some responsibility in in it in the death of a human being this uh I mean I think that's why the whole aspect of ethics in our community is so so important right like because it's true if if you think about it you can basically say I'm not going to work on weaponized AI right like people can say that's not what I'm but yet you are programming algorithms that might be used in healthcare algorithms that might decide whether this person should get this medication or not and they don't and they die you okay so that is your responsibility right and if you're not conscious and aware that you do have that power when you're coding and things like that I think that's that's that's just not a good thing like we need to think about this responsibility as we program robots and and computing devices much more than we are yes so it's not an option to not think about ethics I think it's a majority I would say of computer science sort of there it's kind of a hot topic now I think about bias and so on but it's and we'll talk about it but usually it's kind of you it's like a very particular group of people that work on that and then people who do like robotics or like well I don't have to think about that you know there's other smart people thinking about it it seems that everybody has to think about it it's not you can't escape the ethics well there is bias or just every aspect of ethics that has to do with human beings everyone so think about I'm gonna age myself but I remember when we didn't have like testers right and so what did you do as a developer you had to test your own code right like you had to go through all the cases and figure it out and you know and then they realize that you know like we probably need to have testing because we're not getting all the things and so from there what happens is like most developers they do you know a little bit of testing but is usually like okay - my compiler bug out and you look at the warnings okay is that acceptable or not right like that's how you typically think about as a developer and you'll just assume that is going to go to another process and they're gonna test it out but I think we need to go back to those early days when you know you're a developer you're developing there should be like they say you know okay let me look at the ethical outcomes of this because there isn't a second like testing ethical testers right it's you we did it back in the early coding days I think that's where we are with respect to ethics like this go back to what was good practice isn't only because we were just developing the field yeah and it's uh it's a really heavy burden I've had to feel it recently in the last few months but I think it's a good one to feel like I've gotten a message more than one from people you know I've unfortunately gotten some attention recently and I've got messages that say that I have blood on my hands because of working on semi autonomous vehicles so the idea that you have semi autonomy means people will become would lose vigilance and so on as actually be humans as we described and because of that because of this idea that we're creating automation there will be people be hurt because of it and I think that's a beautiful thing I mean it's you know it's many nights where I wasn't able to sleep because of this notion you know you really do think about people that might die because it's technology of course you can then start rationalizing saying well you know what 40,000 people die in the United States every year and we're trying to ultimately try to save us but the reality is your code you've written might kill somebody and that's an important burden to carry with you as you design the code I don't even think of it as a burden if we train this concept correctly from the beginning and I use and not to say that coding is like being a medical doctor the thing about it medical doctors if they've been in situations where their patient didn't survive right do they give up and go away no every time they come in they know that there might be a possibility that this patient might not survive and so when they approach every decision like that's in their back of their head and so why isn't that we aren't teaching and those are tools though right they're given some of the tools to address that so that they don't go crazy but we don't give those tools so that it does feel like a burden versus something of I have a great gift and I can do great awesome good but with it comes great responsibility I mean that's what we teach in terms of you think about medical schools right great gift great responsibility I think if we just changed the messaging a little great gift being a developer great responsibility and this is how you combine those but do you think and this is really interesting it's it's outside I actually have no friends or sort of surgeons or doctors I mean what does it feel like to make a mistake in a surgery and somebody to die because of that like is that something you could be taught in medical school sort of how to be accepting of that risk so because I do a lot of work with health care robotics I I have not lost a patient for example the first one's always the hardest right but they really teach the value right so they teach responsibility but they also teach the value like you're saving 40,000 mm but in order to really feel good about that when you come to a decision you have to be able to say at the end I did all that I could possibly do right versus a well I just picked the first widget and right like so every decision is actually thought through it's not a habit is not a let me just take the best algorithm that my friend gave me right it's a is this it this this the best have I done my best to do good right and so you're right and I think burden is the wrong word if it's a gift but you have to treat it extremely seriously correct so on a slightly related note yeah in a recent paper the ugly truth about ourselves and our robot creations you you discuss you highlight some biases that may affect the function in various robotics systems can you talk through if you remember examples or some there's a lot of examples I use what is bias first of all yes so bias is this and so bias which is different than prejudice so bias is that we all have these preconceived notions about particular everything from particular groups for to habits to identity right so we have these predispositions and so when we address a problem we look at a problem make a decision those preconceived notions might affect our our outputs or outcomes so they're the bias could be positive or negative and then it's prejudice the negative courage is the negative right so prejudice is that not only are you aware of your bias but you are then take it and have a negative outcome even though you are aware wait and there could be gray areas too that's the challenging aspect of all questions actually so I always like so there's there's a funny one and in fact I think it might be in the paper because I think I talked about self-driving cars but think about this we for teenagers right typically we insurance companies charge quite a bit of money if you have a teenage driver so you could say that's an age bias right but no one will click I mean parents will be grumpy but no one really says that that's not fair that's interesting we don't that's right that's right it's a everybody in human factors and safety research almost I mean it's quite ruthlessly critical of teenagers and we don't question is that okay is that okay to be ageist in this kind of way it is and it is agent right is that really there's no question about it and so so these are these this is the gray area right cuz you you know that you know teenagers are more likely to be an accident and so there's actually some data to it but then if you take that same example and you say well I'm going to make the insurance hire for an area of Boston because there's a lot of accidents and then they find out that that's correlated with socio economics well then it becomes a problem right like that is not acceptable but yet the teenager which is age it's against age is right so we figure that I was I by having conversations by the discourse let me throw out history the definition of what is ethical or not has changed and hopefully always for the better correct correct so in terms of bias or prejudice in robotic in algorithms what what examples do sometimes think about so I think about quite a bit the medical domain just because historically right the healthcare domain has had these biases typically based on gender and ethnicity primarily a little an age but not so much you know historically if you think about FDA and drug trials it's you know harder to find a woman that you know aren't childbearing and so you may not test on drugs at the same level right so there there's these things and so if you think about robotics right something as simple as I'd like to design an exoskeleton right what should the material be what should the way P which should the form factor be are you who are you going to design it around I will say that in the US you know women average height and weight is slightly different than guys so who are you gonna choose like if you're not thinking about it from the beginning as you know okay I when I design this and I look at the algorithms and I design the control system and the forces and the torques if you're not thinking about well you have different types of body structure you're gonna design to you know what you're used to oh this fits my all the folks in my lab right so think about it from the very beginning it's important what about sort of algorithms that train on data kind of thing the sadly our society already has a lot of negative bias and so if we collect a lot of data even if it's a balanced weight that's going to contain the same bias that a society contains and so yeah was is there is there things there that bother you yeah so you actually said something you ain't said how we have biases but hopefully we learn from them and we become better right and so that's where we are now right so the data that we're collecting is historic it's so it's based on these things when we knew it was bad to discriminate but that's the data we have and we're trying to fix it now but we're fixing it based on the data that was used in the first place most right and so and so the decisions and you can look at everything from the hope the whole aspect of predictive policing criminal recidivism there was a recent paper that had the healthcare algorithms which had kind of a sensational titles I'm not pro sensationalism in titles but um but you read it right so yeah make sure read it but I'm like really like what's the topic of the sensationalism I mean what's underneath it what if you could sort of educate me and what kind of bias creeps into the healthcare space yes so he's already kind of oh this one was the headline was racist AI algorithms okay like okay that's totally a clickbait title yeah oh and so you looked at it and so there was data that these researchers had collected I believe I want to say was either science or nature he just was just published but they didn't have the sensational tiger it was like the media and so they had looked at demographics I believe between black and white women right and they were showed that there was a discrepancy in in the outcomes right and so and it was tied to ethnicity tied to race the piece that the researchers did actually went through the whole analysis but of course I mean they're the journalists with AI a problematic across the board rights sake and so this is a problem right and so there's this thing about oai it has all these problems we're doing it on historical data and the outcomes aren't even based on gender or ethnicity or age but I am always saying is like yes we need to do better right we need to do better it is our duty to do better but the worst AI is still better than us like like you take the best of us and we're still worse than the worst AI at least in terms of these things and that's actually not discussed right and so I think and that's why the sensational title right and it's so it's like so then you can have individuals go like oh we don't need to use this hey I'm like oh no no no no I want the AI instead of the the doctors that provided that data cuz it's still better than that yes right I think it's really important to linger on the idea that this AI is racist it's like well compared to what sort of the we that I think we set unfortunately way too high of a bar for AI algorithms and in the ethical space where perfect is I would argue probably impossible then if we set the bar of perfection essentially if it has to be perfectly fair whatever that means is it means we're setting it up for failure but that's really important to say what you just said which is well it's still better yeah and one of the things I I think that we don't get enough credit for just in terms of as developers is that you can now poke at it right so it's harder to say you know is this hospital is the city doing something right until someone brings in a civil case right well were they I it can process through all this data and say hey yes there there's some an issue here but here it is we've identified it and then the next step is to fix it I mean that's a nice feedback loop versus like waiting for someone to sue someone else before it's fixed right and so I think that power we need to capitalize on a little bit more right instead of having the sensational titles have the okay this is a problem and this is how we're fixing it and people are putting money to fix it because we can make it better now you look at like facial recognition how joy she basically called out the companies and said hey and most of them were like Oh embarrassment and the next time it had been fixed right it had been fixed better right and then I was like oh here's some more issues and I think that conversation then moves that needle to having much more fair and unbiased and ethical aspects as long as both sides the developers are willing to say okay I hear you yes we are going to improve and you have other developers are like you know hey AI it's wrong but I love it right yes so speaking of this really nice notion that AI is maybe flawed but better than humans so just made me think of it one example of flawed humans is our political system do you think or you said judicial as well do you have a hope for AI sort of being elected for president or running our Congress or being able to be a powerful representative of the people so I mentioned and I truly believe that this whole world of AI is in partnerships with people and so what does that mean I I don't believe or and maybe I just don't I don't believe that we should have an AI for president but I do believe that a president should use AI as an adviser right like if you think about it every president has a cabinet of individuals that have different expertise that they should listen to right like that's kind of what we do and you put smart people with smart expertise around certain issues and you listen I don't see why a I can't function as one of those smart individuals giving input so maybe there's an AI on health care maybe there's an AI on education and right like all these things that a human is processing right because at the end of the day there's people that are human that are going to be at the end of the decision and I don't think as a world as a culture as xiety that we would totally be and this is us like this is some fallacy about us but we need to see that leader that person as human and most people don't realize that like leaders have a whole lot of advice right like when they say something is not that they woke up well usually they don't wake up in the morning and be like I have a brilliant idea right it's usually a ok let me listen I have a brilliant idea but let me get a little bit of feedback on this like ok and then it's saying yeah that was an awesome idea or it's like yeah let me go back already talked to a bunch of them but are there some possible solutions to the biases presence in our algorithms beyond what we just talked about so I think there's two paths one is to figure out how to systematically do the feedback in corrections so right now it's ad hoc right it's a researcher identify some outcomes that are not don't seem to be fair right they publish it they write about it and the either the developer or the companies that have adopted the algorithms may try to fix it right and so it's really ad hoc and it's not systematic there's it's just it's kind of like I'm a researcher that seems like an interesting problem which means that there's a whole lot out there that's not being looked at right because it's kind of researcher driven I and I don't necessarily have a solution but that process I think could be done a little bit better one way is I'm going to poke a little bit at some of the corporations right like maybe the corporations when they think about a product they should instead of in addition to hiring these you know bug they give these oh yeah yeah yeah wait you think Awards when you find a bug yeah yes Joey bug yeah you know let's let's put it like we will give the whatever the award is that we give for the people who finally secure holls find an ethics hole right like find an unfairness hole and we will pay you X for each one you find I mean why can't they do that one is a win-win they show that they're concerned about it that this is important and they don't have to necessarily dedicate it their own like internal resources and it also means that everyone who has like their own bias lens like I'm interested in age and so I'll find the ones based on age and I'm interested in gender and right which means that you get like all of these different perspectives but you think of it in a data-driven way so like go see sort of if we look at a company like Twitter it gets it's under a lot of fire for discriminating against certain political beliefs correct and sort of there's a lot of people this is the sad thing because I know how hard the problem is and I know the Twitter folks are working with a heart at it even Facebook that everyone seems to hate I worked in really hard of this it you know the kind of evidence that people bring is basically anecdotal evidence well me or my friend all we said is X and for that we got banned and and that's kind of a discussion of saying well look that's usually first of all the whole thing is taken out of context so they're they present sort of anecdotal evidence and how are you supposed to as a company in a healthy way have a discourse about what is and isn't ethical what how do we make algorithms ethical when people are just blowing everything like they're outraged about a particular and a godel evident piece of evidence that's very difficult to sort of contextualize in the big data-driven way do you have a hope for companies like Twitter and yeah so I think there's a couple of things going on right first off the remember this whole aspect of we are becoming reliant on technology we're also becoming reliant on a lot of these the the apps and the resources that are provided right so some of it is kind of anger like I need you right and you're not working for me but I think and so some of it and I and I wish that there was a little bit of change and rethinking so some of it is like oh we'll fix it in house no that's like okay I'm a fox and I am going to watch these hens because I think it's a problem that foxes eat hens No right like use like be good citizens and say look we have a problem and we are willing to open ourselves up for others to come in and look at it and not try to fix it in house because if you fix it in house there's conflict of interests if I find something I'm probably going to want to fix it and hopefully the media won't pick it up right and that then caused this distrust because someone inside is going to be mad at you and go out and talk about how yeah they can the resume survey because it's rightly the best people like just say look we have this issue community help us fix it and we will give you like you know the bug finder fee if you do did you have a hope that the community us as a human civilization on the whole is good and can be trusted to guide the future of our civilization into positive direction I think so so I'm an optimist right and you know we there were some dark times in history always I think now we're in one of those dark times I truly do and which aspect the polarization and it's not just us right so if it was just us I'd be like yeah say us thing but we're seeing it like worldwide this polarization and so I worry about that but I do fundamentally believe that at the end of the day people are good right and why do I say that because any time there's a scenario where people are in danger and I would use I saw Atlanta we had Snowmageddon and people can laugh about that people at the time so the city closed for you know little snow but it was ice and the city closed down but you had people opening up their homes and saying hey you have nowhere to go come to my house right hotels were just saying like sleep on the floor like places like you know the grocery stores were like hey here's food there was no like oh how much are you gonna pay me it was like this such a community and like people who didn't know each other strangers were just like can I give you a ride home and that was a point I was like you know I like that that there reveals that the deeper thing is is there's a compassion or love that we all have within us it's just that when all that is taken care of and get bored we love drama and that's I think almost like the division is the sign of the time is being good is that it's just entertaining under some unpleasant mammalian level to watch to disagree with others and Twitter and Facebook are actually taking advantage of that in the sense because it brings you back to the platform and their advertisers are driven so they make a lot of money love doesn't sell quite as well in terms of advertisement so you've started your career NASA Jet Propulsion Laboratory but before I'd ask a few questions there have you happen to have ever seen Space Odyssey 2001 Space Odyssey yes okay do you think Hal 9000 so we're talking about ethics do you think how did the right thing by taking the priority of the mission over the lives of the astronauts do you think Cal is good or evil easy questions yeah Hal was misguided you're one of the people that would be in charge of an algorithm like Hal yes so how would you do better if you think about what happened was there was no failsafe right so we perfection right like what is that I'm gonna make something that I think is perfect but if my assumptions are wrong it'll be perfect based on the wrong assumptions all right that's something that you don't know until you deploy and like oh yeah messed up but what that means is that when we design software such as in Space Odyssey when we put things out that there has to be a failsafe there has to be the ability that once it's out there you know we can grade it as an F and it fails and it doesn't continue right if there's some way that it can be brought in and and removed and that's aspect because that's what happened with what how it was like assumptions were wrong it was perfectly correct based on those assumptions and there was no way to change change it change the assumptions at all and the change the fallback would be to humans so you ultimately think like humans should be you know it's not Turtles or AI all the way down it's at some point there's a human that actually don't think that and again because I do human robot interaction I still think the human needs to be part of the equation at some point so what just looking back what are some fascinating things in robotic space that NASA was working at the time or just in general what what have you gotten to play with and what are your memories from working at NASA yes so one of my first memories was they were working on a surgical robot system that could do eye surgery right and this was back in oh my gosh it must have been Oh maybe 92 93 94 so it's like almost like a remote operation oh yeah it was it was a remote operation in fact that you can even find some old tech reports on it so think of it you know like now we have da Vinci right like think of it but these are like the late 90s right and I remember going into the lab one day and I was like what's that right and of course it wasn't pretty right because the technology but it was like functional and you had as this individual that could use version of haptics to actually do the surgery and they had this mock-up of a human face and like the eyeballs you can see this little drill and I was like oh that one I vividly remember because it was so outside of my like possible thoughts of what could be done the kind of precision and uh hey what what's the most amazing of a thing like that I think it was the precision it was the kind of first time that I had physically seen this robot machine human interface right versus because manufacturing have been you saw those kind of big robots right but this was like oh this is in a person there's a person in a robot like in the same space the meeting them in person I like for me it was a magical moment that I can't as a life-transforming that I recently met spot mini from Boston Dynamics Elysee I don't know why but on the human robot interaction for some reason I realized how easy it is to anthropomorphize and it was I don't know it was uh it was almost like falling in love this feeling of meeting and I've obviously seen these or was a lot on video and so on but meeting in person just having that one-on-one time it's different so do you have you had a robot like that in your life that was made you maybe fall in love with robotics sort of odds like meeting in person I mean I mean I I loved robotics yeah that was a 12 year old like I would be a roboticist actually was I called it cybernetics but so my my motivation was Bionic Woman I don't know if you know that is um and so I mean that was like a seminal moment but I didn't me like that was TV right like it wasn't like I was in the same space and I meant I was like oh my gosh you're like real just linking I'm Bionic Woman which by the way because I've read that about you I watched a bit bits of it and it's just so no offence terrible I've seen a couple of reruns lately it's uh but of course at the time is probably disgusted the imagination especially when you're younger just catch you but which aspect did you think of it you mentioned cybernetics did you think of it as robotics or did you think of it as almost constructing artificial beings like is it the intelligent part that that captured your fascination or was it the whole thing like even just the limbs and just so for me it would have in another world I probably would have been more of a biomedical engineer because what fascinated me was the by on it was the parts like the Bionic parts the limbs those aspects of it are you especially drawn to humanoid or human-like robots I would say human-like not humanoid right and when I say human-like I think it's this aspect of that interaction whether it's social and it's like a dog right like that's human-like because it's understand us it interacts with us at that very social level - you know humanoids are part of that but only if they interact with us as if we are human but just to linger on NASA for a little bit what do you think maybe if you have other memories but also what do you think is the future of robots in space will mention how but there's incredible robots and NASA's working on in general thinking about in art as we venture out human civilization ventures out into space what do you think the future of robots is there yes so I mean there's the near term for example they just announced the the rover that's going to the moon which you know that's kind of exciting but that's like near-term you know my favorite favorite favorite series is Star Trek right you know I really hope and even Star Trek like if I calculate the years I wouldn't be alive but I would really really love to be in that world like even if it's just at the beginning like you know like voyage like adventure one so basically living in space yeah with what what robots would a robots do data were roll the data would have to be even though that wasn't you know that was like later but so data is a robot that has human-like qualities right without the emotion ship yeah you don't like emotion well they know what the emotion ship was kind of a mess right it took a while for for that thing to adapt but and and so why was that an issue the issue is is that emotions make us irrational agents that's the problem and yet he could think through things even if it was based on an emotional scenario right based on pros and cons but as soon as you made him emotional one of the metrics he used for evaluation was his own emotions not people around him right like and so we do that as children right so we're very egocentric we're very egocentric and so isn't that just an early version of the emotion ship then I haven't watched much Star Trek I have also met adults right and so that is that is a developmental process and I'm sure there's a bunch of psychologists that can go through like you can have a six-year-old dolt who has the emotional maturity of a ten-year-old right and so there's various phases that people should go through in order to evolve and sometimes you don't so how much psychology do you think a topic that's rarely mentioned in robotics but how much the psychology come to play when you're talking about HRI human robot interaction when you have to have robots that actually interact with you tons so we like my group as well as I read a lot in the cognitive science literature as well as the psychology literature because they understand a lot about human human relations and developmental milestones things like that and so we tend to look to see what what's been done out there sometimes what we'll do is we'll try to match that to see is that human human relationship the same as human robot sometimes it is and sometimes is different and then when it's different we have to we try to figure out okay why is it different in this scenario but it's the same in the other scenario right and so we try to do that quite a bit would you say that's if we're looking at the future of human robot interaction would you say the psychology piece is the hardest like if it's I mean it's a funny notion for you as I don't know if you consider yeah I mean one way to ask it do you consider yourself for roboticist or psychologists oh I consider myself a robot is's that plays the act of a psychologist but if you were look at yourself sort of you know 20 30 years from now do you see yourself more and more wearing the psychology hat another way to put it is are the hard problems in human robot interactions fundamentally psychology or is it still robotics the perception of manipulation planning all that kind of stuff it's actually neither the hardest part is the adaptation in the interaction so learning it's the interface it's the learning and so if I think of like I've become much more of a roboticist /ai person then when I like originally again I was about the bionics I was looking I was electrical engineer I was control theory right like and then I started realizing that my algorithms needed like human data right and so that I was like okay what is this human thing but how do I incorporate human data and then I realized that human perception had there was a lot in terms of how we perceived the world it's so trying to figure out how do i model human perception for my and so I became a HRI person human robot interaction person from being a control theory and realizing that humans actually offered quite a bit and then when you do that you become one more of artificial intelligence AI and so I see myself evolving more in this AI world under the lens of robotics having Hardware interacting with people so you're a world-class expert researcher in robotics and yet others you know there's a few it's a small but fierce community of people but most of them don't take the journey into the h of HR I into the human so why did you brave into the interaction with humans it seems like a really hard problem it's a hard problem and it's very risky as an academic yes and I knew that when I started down that journey that it was very risky as an academic in this world that was nuanced it was just developing we didn't have a conference right at the time because it was the interesting problems that was what drove me it was the fact that I looked at what interests me in terms of the application space and the problems and that pushed me into trying to figure out what people were and what humans were and how to adapt to them if those problems weren't so interesting I'd probably still be sending Rovers to glaciers right but the problems were interesting and the other thing was that they were hard right so it's I like having to go into a room and being like I don't know and then going back and saying okay I'm gonna figure this out I do not I'm not driven when I go in like oh there are no surprises like I don't find that satisfying if that was the case I go someplace and make a lot more money right I think I stay in academic because and choose to do this because I can go into a room like that's hard yeah I think just for my perspective maybe you can correct me on it but if I just look at the field of AI broadly it seems that human robot interaction has the most one of the most number of open problems people especially relative to how many people are willing to acknowledge that there are this because most people are just afraid of the human so they don't even acknowledge how many open problems are but it's a in terms of difficult problems to solve exciting spaces it seems to be an incredible for that it is it is exciting you mentioned trust before what role does trust from interacting with autopilot to in the medical context what role distress playing the human robot trap so some of the things I study in this domain is not just trust but it really is over trust how do you think about over traffic what is for so what is what is trust and what is overdressed basically the way I look at it is trust is not what you click on a survey just this is about your behavior so if you interact with the technology based on the decision are the actions of the technology as if you trust that decision then you're trusting right and I mean even in my group we've done surveys that you know on the thing do my you trust robots of course not would you follow this robot in a burning building of course not right and then you look at their actions and you're like clearly your behavior does not match what you think right or which you think you would like to think right and so I'm really concerned about the behavior because that's really at the end of the day when you're in the world that's what will impact others around you it's not whether before you went onto the street you you clicked on like I don't trust self-driving cars you know that from an outsider perspective it's always frustrating to me well I read a lot so I'm Insider in a certain philosophical sense the it's frustrating to me how often Trust is used in surveys and how people say make claims that have any kind of finding they make about somebody clicking on answer you just trust is uh yet behavior just you said it beautiful I mean the action your own behavior as is what Trust is I mean that everything else is not even close it's almost like a absurd comedic poetry that you weave around your actual behavior so some people can say they're they their trust you know I trough trust my wife husband or not whatever but the actions is what speaks volumes but their car probably don't I trust them I'm just making sure no no that's yeah it's like even if you think about cars I think it's a beautiful case I came here at some point I'm sure on either Oberer lift right I remember when it first came out I I bet if they had had a survey would you get in the car with a stranger and pay them yes how many people do you would think would have said like really you know wait even worse would you get in the car with a stranger at 1:00 a.m. in the morning to have them drop you home as a single female yeah like how many people would say that's stupid yeah and now look at where we are I mean people put kids like great links oh yeah my child has to go to school and I yeah I'm gonna put my kid in this car with a stranger yeah I mean it's just a fascinating how like what we think we think is not necessarily matching our behavior and certainly with robots for the tallest vehicles and and all all the kinds of robots you work with that's it's yeah it's the way you answer it especially if you've never interacted with that robot before if you haven't had the experience you're being able to respond correctly I know surveys is impossible but what do you what role does trust play in the interaction do you think like is it good - is it good to trust a robot what is over trust mean what is it it's good to kind of how you feel about autopilot currently which is like for a roboticist perspective is like is so very cautious yeah so this is still an open area of research but basically what I would like in a perfect world is that people trust the technology when is working a hundred percent and people will be hypersensitive and identify when it's not but of course we're not there that's that's the ideal world and but we find is that people swing right they tend to swing which means that if my first and like we have some papers like first impressions in everything is everything right if my first instance with technology with robotics is positive it mitigates any risk in it correlates with like best outcomes it means that I'm more likely to either not see it when it makes a mistakes or faults or I'm more likely to forgive it and so this is a problem because technology is not 100 percent accurate right it's not as if it's inaccurate although it may be perfect how do you get that first moment right do you think there's also an education about the capabilities and limitations of the system do you have a sense of how do you educate people correctly in that first interaction again this is this is an open-ended problem so one of the study that actually has given me some hope that I were trying to figure out how to put in robotics so there was a research study that had showed for medical AI systems giving information to radiologists about you know here you need to look at these areas on the x-ray what they found was that when the system provided one choice there was this aspect of either no trust or over trust right like I'm not going I don't believe it at all or a yes yes yes yes and they was miss things right instead when the system gave them multiple choices like here are the three even if it knew like you know it had estimated that the top area you need to look at was he you know someplace on the x-ray if it gave like one plus others the trust was maintained and the accuracy of the entire population increased right so basically it was a you're still trusting the system but you're also putting in a little bit of like your human expertise like you're a human decision processing into the equation so it helps to mitigate that over trust risk yeah so there's a fascinating balance tough to strike I haven't figured out again exciting open area research exactly so what are some exciting applications of human robot interaction you started a company maybe you can talk about the the exciting efforts there but in general also what other space can robots interact with humans and help yeah so besides healthcare cuz you know that's my bias lens my other bias lens is education I think that well one we definitely we in the u.s. you know we're doing okay with teachers but there's a lot of school districts that don't have enough teachers if you think about the teacher-student ratio for at least public education um in some districts it's crazy it's like how can you have learning in that classroom right because you just don't have the human capital and so if you think about robotics bringing that in to classrooms as well as the after-school space where they offset some of this lack of resources and certain communities I think that's a good place and then turning on the other end is using the system's then for workforce retraining and dealing with some of the things that are going to come out later on of job loss like thinking about robots and Nai systems for retraining and Workforce Development I think that's exciting areas that can be pushed even more and it would have a huge huge impact what would you say some of the open problems were in education so it's a exciting so young kids and the older folks or just folks of all ages who need to be retrained we need to sort of open themselves up to a whole nother area of work what what are the problems to be solved there how do you think robots can help we we have the engagement aspect right so we can figure out the engagement that's not a what do you mean by engagement so identifying whether a person is focused is like that we can figure out what we can figure out and and there's some positive results in this is that personalized adaptation based on any con sense right so imagine I think about I have an agent and I'm working with a kid learning I don't know algebra - in that same agent then switch and teach some type of new coding skill to a displacement Anik like what does that actually look like right like hardware might be the same content is different to different target demographics of engagement like how do you do that how important do you think personalization is in human robot interaction and not just mechanic or student but like literally to the individual human being I think personalization is really important but a caveat is that I think we'd be ok if we can personalize to the group right and so if I can label you as along some certain dimensions then even though it may not be you specifically I can put you in this group so the sample size this is how they best learn this is how they best engage even at that level it's really important and it's because I mean it's one of the reasons why educating in large classrooms is so hard right you teach too you know the median but there's these you know individuals that are you know struggling and then you have highly intelligent individuals and those are the ones that are usually you know kind of left out so highly intelligent individuals may be disruptive and those who are struggling might be you disruptive because they're both bored yeah and if you narrow this the definition of the group or in the size of the group enough you'll be able to address their individual yeah it's not individual needs but really gross needs a group most important group needs right right and that's kind of what a lot of successful recommender systems do is Spotify and so on say sad to believe but I'm as a music listener probably in some sort of large group it's very sadly predictable been labeled yeah I've been labeled and and successfully so because they're able to recommend stuff that I yeah but applying that to education right there's no reason why it can't be done do you have a hope for our education system I have more hope for workforce development and that's because I'm seeing investments even if you look at VC investments in education the majority of it has lately been going to workforce retraining right and so I think that government investments is increasing there's like a claim and some of it's based on fear right like AI is gonna come and take over all these jobs so what are we gonna do with all these non paying taxes that aren't coming to us by our citizens and so I think I'm more hopeful for that not so hopeful for early education because it's this it's still a who's gonna pay for it and you won't see the results for like 16 to 18 years it's hard for people to wrap their heads around that but on the retraining part what are your thoughts there's a candidate andrew yang running for president and saying that sort of AI automation robots universal basic income universal basic income in order to support us as we kind of automation takes people's jobs and to explore and find other means like you have a concern of society transforming effects of automation and robots and so on I do I do know that AI robotics will displace workers like we do know that but there'll be other workers that will be defined new jobs what I worry about is that's not what I worry about like we'll all the jobs go away what I worry about is the type of jobs that will come out right like people who graduate from Georgia Tech will be okay right we give them the skills they will adopt even if their current job goes away I do worry about those that don't have that quality of an education right will they have the ability the background to adapt to those new jobs that I don't know that I worry about which will convey even more polarization in in our society internationally and everywhere I worry about that I also worry about not having equal access to all these wonderful things that AI can do and robotics can do I worry about that you know people like people like me from Georgia Tech from say MIT will be okay right but that's such a small part of the population that we need to think much more globally of having access to the beautiful things whether it's AI and healthcare AI and education may ion and politics right I worry about and that's part of the thing that you were talking about is people that build a technology had to be thinking about ethics have to be thinking about access yeah and all those things and not not just a small small subset let me ask some philosophical slightly romantic questions all right but they listen to this will be like here he goes again okay do you think do you think one day we'll build an AI system that we a person can fall in love with and it would love them back like in a movie her for exam yeah although she she kind of didn't fall in love with him uh she fell in love with like a million other people something like that so you're the jealous type I see we humans at the judge yes so I do believe that we can design systems where people would fall in love with their robot with their AI partner that I do believe because it's actually and I won't I don't like to use the word manipulate but as we see there are certain individuals that can be manipulated if you understand the cognitive science about it right alright so I mean if you could think of all close relationship and love in general as a kind of mutual manipulation that dance the human dance I mean many patients a negative connotation and I don't like to use that word particularly I guess another way to phrase is you're getting as it could be algorithmic eyes or something it could be the relationship building part can yeah yeah I mean just think about it there we have and I don't use dating sites but from what I heard there are some individuals that have been dating that have never saw each other right in fact there's a show I think that tries to I weed out fake people like there's a show that comes out right because like people start faking like what's the difference of that person on the other end being an AI agent right and having a communication are you building a relationship remotely like there there's no reason why that can't happen in terms of human robot interaction was a what role you've kind of mentioned what data emotion being can be problematic if not implemented well I suppose what role does emotion some other human-like things the imperfect things come into play here for a good human robot interaction and something like love yes so in this case and you had asked can i AI agent love a human back I think they can emulate love back right and so what does that actually mean it just means that if you think about their programming they might put the other person's needs in front of theirs and certain situations right you look at think about it as a return on investment like was my return on investment as part of that equation that person's happiness you know has some type of you know algorithm waiting to it and the reason why is because I care about them right that's the only reason right but if I care about them and I show that then my final objective function is length of time of the engagement right so you can think of how to do this actually quite easily and so but that's not love well so that's the thing it I think it emulates love because we don't have a classical definition of love right but and we don't have the ability to look into each other's minds to see the algorithm and yeah I guess what I'm getting at is is it possible that especially if that's learned especially if there's some mystery and black box nature to the system how is that you know how is it any different I was any different and in terms of sort of if the system says I'm cautious I'm afraid of death and it does indicate that it loves you another way to sort of phrase I be curious to see what you think do you think there'll be a time when robots should have rights you've kind of phrased the robot in a very roboticist way it's just a really good way but saying okay well there's an objective function and I can see how you can create a compelling human robot interaction experience that makes you believe that the robot cares for your needs and even something like loves you but what if the robot says please don't turn me off what if the robot starts making you feel like there's an entity of being a soul there all right do you think there'll be a future hopefully you won't laugh too much of this but there were there's they do ask for rights so I can see a future if we don't address it in the near term where these agents as they adapt and learn could say hey this should be something that's fundamental I hopefully think that we would address it before it gets to that point you think so that you think that's a bad future is like what is that a negative thing where they ask or being discriminated against I guess it depends on what role have they attained at that point right and so if I think about now careful what you say because the robots fifty years from when I'll be listening to this and you'll be on TV is saying this is what roboticists used to believe and so this is my and as I said I have a bias lens and my robot friends will understand that yes but so if you think about it and I actually put this in kind of fee as a robot assists you don't necessarily think of robots as human with human rights but you could think of them either in the category of property or you can think of them in the category of animals right and so both of those have different types of rights so animals have their own rights as as a living being but you know they can't vote they can't write they can be euthanized but as humans if we abuse them we go to jail like right so they do have some rights that protect them but don't give them the rights of like citizenship and then if you think about property property the rights are associated with the person right so if someone vandalizes your property or steals your property like there are some rights but it's associated with the person who owns that if you think about it back in the day and if you remember we talked about you know how society has changed women were property right they were not thought of as having rights they were thought of as property of like their yeah salting a woman meant assaulting the property of somebody else's butt exactly and so what I envision is is that we will establish some type of norm at some point but that it might evolve right like if you look at women's rights now like there are some countries that don't have and the rest of the world is like why that makes no sense right and so I do see a world where we do establish some type of grounding it might be based on property rights it might be based on animal rights and if it evolves that way I think we will have this conversation at that time because that's the way our society traditionally has evolved beautifully puts just out of curiosity at Anki geebo main field robotics within robot curious eye how it works we think robotics were all these amazing robotics companies led created by incredible roboticists and they've all went out of business recently why do you think they didn't last long why is this so hard to run a robotics company especially one like these which are fundamentally HR are HRI human robot interaction robots yeah one has a story only one of them I don't understand and that was on key that's actually the only one I don't understand I don't understand either it's you know I mean I looked like from the outside you know I've looked at their sheets I've looked like the data that's oh you mean like business-wise yeah yeah and like I look at all I look at that data and I'm like they seem to have like product market fit like so that's the only one I don't understand the rest of it was product market fit what's product market feel if it just just that how do you think about it yes so although we rethink robotics was getting there right but I think it's just the timing it just they're the clock just timed out I think if they had been given a couple more years if they would have been okay but the other ones were still fairly early by the time they got into the market and so product market fit is I have a product that I want to sell at a certain price are there enough people out there the market that are willing to buy the product at that market price for me to be a functional viable profit bearing company right so product market fit if it costs you a thousand dollars and everyone wants it and only is willing to pay a dollar you have no product market fit even if you could sell it for you know it's enough for a dollar because you can't you so hard is it for robots sort of maybe if you look at iRobot the company that makes Roomba vacuum cleaners can you comment on did they find the right product market product fit or like are people willing to pay for robots is also another kind of question about iRobot in their story right like when they first they had enough of a runway right when they first started they weren't doing vacuum cleaners right they were a military contracts primarily government contracts designing robots yeah I mean that's what they were that's how they started right and they still do a lot of incredible work there but yeah that was the initial thing that gave him enough funding to then try to the vacuum cleaner is what I've been told was not like their first rendezvous in terms of designing a product right and so they they were able to survive until they got to the point that they found a a product price market right and even with if you look at the the Roomba the price point now is different than when it was first released right it was an early adopter price but they found enough people who were willing to defend it and I mean though you know I forgot what their loss profile was for the first couple of you know years but they became profitable in sufficient time that they didn't have to close the doors so they found the right there's still there's still people willing to pay a large amount of money so or a thousand dollars for for vacuum cleaner unfortunately for them now that they've proved everything out figured it all out the other side yeah and so that's that's the next thing right the competition and they have quite a number even like there's some some products out there you can go to you know you're up and be like oh I didn't even know this one existed so so this is the thing though like with any market I I would this is not a bad time although you know as a roboticist its kind of depressing but I actually think about things like with the I would say that all of the companies that are now in the top five or six they weren't the first to the stage right like Google was not the first search engine sorry Alta Vista right Facebook was not the first sorry myspace right like think about it they were not the first players those first players like they're not in the top five ten no fortune 500 companies right they proved they started to prove out the market they started to get people interested they started the buzz but they didn't make it to that next level but the second match right the second batch I think might make it to the next level do you when do you think the the Facebook of Roja the Facebook of Robotics sorry take that phrase back because people deeply for some reason I know why but it's I think exaggerated distrust Facebook because of the privacy concerns and so on and with robotics one of the things you have to make sure all the things we've talked about is to be transparent and have people deeply trust you to let it well robot into their lives into their home what do you think the second batch of robots local is it five ten years twenty years that will have robots in our homes and robots in our hearts so if I think about and because I try to follow the the VC kind of space in terms of robotic investments and right now I don't know if they're gonna be successful I don't know if this is the second batch but there's only one batch that's focused on like the first batch right and then there's all these self-driving X's right and so I don't know if they're a first batch of something or if I like I don't know quite where they fit in but there's a number of companies the co robot I'll call them Co robots that are still getting VC investments they some of them have some of the flavor of like rethink robotics some of them have some of the flavor like hurry what's a col robot of course so basically a robot in human working in the same space so some of the companies are focused on manufacturing so having a robot and human working together in a factory some of these Co robots are robots and humans working in the home working in clinics like there's different versions of these companies in terms of their products but they're all so rethink robotics would be like one of the first at least well known companies focus on this space so I don't know if this second if this is a second batch or if this is still part of the first batch that I don't know and then you have all these other companies in this self-driving you know space and I don't know if that's a first batch or again a second batch yeah so there's a lot of mystery about this now of course it's hard to say that this is the second batch until it you know approves outright correct exactly yeah we need a unicorn yeah exactly the why do you think people are so afraid at least in popular culture of legged robots like those work than Boston Dynamics or just robotics in general if you were to psychoanalyze that fear what do you make of it and should they be afraid sorry so should people be afraid I don't think people should be afraid but with a caveat I don't think people should be afraid given that most of us in this world understand that we need to change something right so given that now things don't change be very afraid what which is the dimension of change that's needed so changing of thinking about the ramifications thinking about like the ethics thinking about like the conversation is going on right it's not it's no longer a we're gonna deploy it and forget that you know this is a car that can kill pedestrians that are walking across the street right it's we're not in that stage where a we're putting these roads out there are people out there yes a car could be a weapon like people are now solutions aren't there yet but people are thinking about this as we need to be ethically responsible as we send these systems out robotics medical self-driving and military - and Miller and military just not as often talked about but it's really we're probably these robots will have a significant impact as well correct correct right making sure that they can think rationally even having the conversations who should pull the trigger right but overall you're saying if we start to think more and more as a community about these ethical issues people should not be afraid yeah I don't think people should be afraid I think that the return on investment the impact positive impact will outweigh any of the potentially negative impacts do you have worries of existential threats of robots or AI that some people kind of talk about and romanticize about and then you know in those decade in the next few decades no I don't singularity will be an example so my concept is is that so remember robots AI is designed by people yes it has our values and I always correlate this with a parent and a child all right so think about it as a parent would we want we want our kids to have a better life than us we want them to expand we want them to experience the world and then as we grow older our kids think and know they're smarter and better and more intelligent and have better opportunities and they may even stop listening to us they don't go out and then kill us right like think about it it's because we it's instilled in them values we instilled in them this whole aspect of community and yes even though you're maybe smarter and more have more money and data it's still about this love caring relationship and so that's what I believe so even like you know we've created the singularity and some archaic system back in like 1980 that suddenly evolves the fact is it might say I am smarter I am sentient these humans are really stupid but I think it'll be like yeah but I just can't destroy that yeah for sentimental value it's still just for to come back for Thanksgiving dinner every once in a while exactly this so beautifully put you've you've also said that the matrix may be one of your more favorite AI related movies can you elaborate why yeah it is one of my favorite movies and it's because it represents kind of all the things I think about so there's a symbiotic relationship between robots and humans right that symbiotic relationship is that they don't destroy us they enslave us right but think about it even though they enslaved us they needed us to be happy right and in order to be happy they had to create this Kruti world that they then had to live in right that's the whole but then there were humans that had a choice wait like you had a choice to stay in this horrific horrific world where it was your fantasy and life with all of the anomalies perfection but not accurate or you can choose to be on your own and like have maybe no food for a couple of days but you were totally autonomous and so I think of that as and that's why so it's not necessarily us being enslaved but I think about us having this symbiotic relationship robots and AI even if they become sentient they're still part of our society and they will suffer just as much as us and there there will be some kind of equilibrium that we'll have to find some somebody out of relationship and then you have the ethicist the robotics folks that like no this has got to stop I will take the other peel yeah in order to make a difference so if you could hang out for a day with a robot real from fiction movies books safely and get to pick his or her there brain who would you pick gotta say it's data data I was gonna say Rosie but I don't I'm not really interested in her brain hmm I'm interested in data's brain data pre or post emotion ship pre but don't you think it'd be a more interesting conversation post emotion ship yeah it would be drama and I you know I'm human I deal with drama all the time yeah but the reason why I went to pick data's brain is because I I could have a conversation with him and ask for example how can we fix this ethics problem right and he could go through like the rational thinking and through that he'd also help me think through it as well and so that's there's like these questions fundamental questions I think I can ask him that he would help me also learn from and that fascinates me I don't think there's a better place to end it thank you so much for talking I was an honor thank you thank you this was fun thanks for listening to this conversation and thank you to our presenting sponsor cash app downloaded use code Lex podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe my youtube give it five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and now let me leave you with some words of wisdom from arthur c clarke whether we are based on carbon quan silicon makes no fundamental difference which should each be treated with appropriate respect thank you for listening and hope to see you next time you |
Daniel Kahneman: Thinking Fast and Slow, Deep Learning, and AI | Lex Fridman Podcast #65 | the following is a conversation with Daniel Kahneman winner of the Nobel Prize in Economics for his integration of economic science with a psychology of human behavior judgment and decision-making he's the author of the popular book Thinking Fast and Slow that summarizes in an accessible way his research of several decades often in collaboration with Amos Tversky a cognitive biases prospect theory and happiness the central thesis of this work is the dichotomy between two modes of thought what he calls system one is fast instinctive and emotional system two is slower more deliberative and more logical the book delineates cognitive biases associated with each of these two types of thinking his study of the human mind and his peculiar and fascinating limitations are both instructive and inspiring for those of us seeking to engineer intelligent systems this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating a charity navigator which means that donated money is used to maximum effectiveness when you get cash app from the App Store Google Play and use code Lex podcast you'll get ten dollars in cash up will also donate ten dollars to the first which again is an organization that I've personally seen inspire girls and boys the dream of engineering a better world and now here's my conversation with Daniel Kahneman you tell a story of an SS soldier early in the war world war two in nazi-occupied France and Paris where you grew up he picked you up and hugged you and showed you a picture of a boy maybe not realizing that you were Jewish not maybe certainly not so I told you I'm from the Soviet Union that was significantly impacted by the words well and I'm Jewish as well what do you think World War two taught us about human psychology broadly well I think the the only big surprise is the extermination policy genocide by the German people that's when you look back on it and you know I think that's a major surprise it's a surprise because it's a surprise that they could do it it's a surprise that they that enough people willingly participated in that this is this is a surprise now it's no longer a surprise but it's changed many people's views I think about about human beings certainly for me the Ackman trial in a teaches you something because it's very clear that if it could happen in Germany it could happen anywhere it's not that the Germans were special this could happen anyway so what do you think that is do you think we're all capable of evil we're all capable of cruelty I don't think in those terms I think that what is certainly possible is you can dehumanize people so that there you treat them not as people anymore but as animals and and the same way that you can slaughter animals without feeling much of anything it can the same and when you feel that the I think the combination of dehumanizing the other side and and having uncontrolled power over other people I think that doesn't bring out our the most generous aspect of human nature so that Nazi soldier you know he he was a good man I mean you know and he was perfectly capable of killing a lot of people and I'm sure he did but what what did the Jewish people mean to Nazis so what the dismissal of Jewish as well worthy of again this is surprising that it was so extreme but it's not one thing in human nature I don't want to call it evil but the distinction between the in-group and the out-group that is very basic so that's built in the the loyalty and affection towards in-group and the willingness to dehumanize the out-group that's that is in human nature and that's that's what I think probably didn't need the Holocaust to teach us that but the Holocaust is a very sharp lesson of you know what can happen to people and when the people can do so the effect of the in-group and the out-group you know that it's clear that those were people you know you could you could shoot them you could you know they were not human they were not there was no empathy or very very little empathy left so occasionally you know they might have been and and very quickly by the way the empathy disappeared if there was initially and the fact that everybody around you was doing it that that completely the group doing it and everybody shooting Jews I think that that makes it permissible now how much you know whether it would it could happen or in every culture or whether the Germans were just particularly efficient and and disciplined so they could get away with it that is a question it's an interesting question are these artifacts of history or is it human nature I think that's really human nature you know you put some people in a position of power relative to other people and and then they become as human become different but in general and war outside of concentration camps in World War two it seems that war brings out darker sides of human nature but also the beautiful things about human nature well no I mean but it what it brings out is the loyalty among soldiers I mean it brings out the bonding male bonding I think is a very real thing that and that happens and so and and there is a student of thrill to friendship and there is certainly a certain thrill to friendship under risk and to shared risk and so people have very profound emotions up to the point where it gets so traumatic that that little is left but so let's talk about psychology a little bit in your book Thinking Fast and Slow you described two modes of thoughts as the one the fast instinctive an emotional one is system to the slower deliberate logical one at the risk of asking Darwin to discuss a theory of evolution can you describe distinguishing characteristics for people who have not read your book of the two systems well I mean the mood system is a bit misleading but it's at the same time it's misleading it's also very useful but what I call system one it's easier to think of it as as a family of activities and primarily the way I describe it is there are different ways for ideas to come to my mind and some ideas come to mind automatically and the example a standard example is two plus two and then something happens to you and and in other cases you've got to do something you got to work in order to produce the idea and my example I always give the same pair of numbers is 27 times 14 I think you have to perform some algorithm in your heads and yes and and it takes time it's a very difference nothing comes to mind except something comes to mind which is the algorithm I mean that you've got to perform and then it's work and it engages short-term memory and thing ages executive function and it makes you incapable of doing other things at the same time so the the main characteristic of system 2 is that there is mental effort involved and there is a limited capacity for mental effort where a system one is effortless essentially that's the major distinction so you talk about there you know it's really convenient to talk about two systems but you also mentioned just now and in general that there's no distinct two systems in the brain from a neurobiological even from psychology perspective but why does it seem to from the experiments you've conducted there does seem to be kind of emergent two modes of thinking so at some point these kinds of systems came into a brain architecture maybe ma'am will share it but the or do you not think of it at all in those terms that it's all on mush and these two things just emerge you know evolutionary theory saying about this is cheap and easier so it's the way I think about it is that it's very clear that animals have a perceptual system and that includes an ability to understand the world at least to the extent that they can predict they can't explain anything but they can anticipate what's going to happen and that's the key form of understanding the world and my crude idea is that we would I call system - well system - grew out of this and you know there is language and there is the capacity of manipulating our ideas and the capacity of imagining futures and of imagining counterfactuals thing that haven't happened and and to do conditional thinking and there are really a lot of abilities that without language and without the the very large brain that we have compared to others it would be impossible now system one is more like what the animals are but system one also can talk I mean it has language it understands language indeed it speaks for us I mean you know I'm not choosing every word you know as a deliberate process the words I have some idea and then the words come out and that's automatic and effortless and many of experiments you've done is to show that listen system won't exist and it does speak for us and we should be careful about it's the voice it provides well it's I mean you know we have to trust it because it's the speed at which it acts a system is usable if we if we depend on one system to for survival we wouldn't survive very long because it's very slow yeah crossing the street crossing a street I mean many things depend on there being automatic one very important aspect of system one is that it's not instinct you use the word instinct that it contains skills that clearly have been learned so that skilled behavior like driving a car or speaking in fact skilled behavior has to be learned and so it doesn't you know you don't come equipped with with driving you have to learn how to drive and and you have to go through a period where driving is not automatic before it becomes automatic so yeah you construct I mean this is where you talk about heuristic and biases you to make it automatic you create a pattern and then system one essentially matches a new experience against a previously seen pattern and when that match is not a good one that's when the cognate all of them all the mess happens but it's most of the time it works and so it's pretty most of the time the anticipation of what's going to happen next is correct and and most of the time the plan about what you have to do is correct and so most of the time everything works just fine what's interesting actually is that in some sense system one is much better at what it does and system tool is at what it does that is there is that quality of effortlessly solving enormous ly complicated problems which clearly exists so that the chess player a very good chess player all the moves that come to their mind are strong moves so all the selection of strong moves happens unconsciously and automatically and very very fast and and all that is in system one so you a system two verifies so along this line of thinking really what we are our machines that construct a pretty effective system one you could think of it that way so so we're now talking about humans but if we think about building artificial intelligence systems robots do you think all the features in bug that you have highlighted in human beings are useful for constructing AI systems so both systems are useful for perhaps while instilling in robots what is happening these days is that actually what is happening in deep learning is is more like a system one product than like a system to product I mean deep learning mattress patterns and anticipate what's going to happen so it's highly predictive what's right what deep learning doesn't have and you know many people think that this is the critical it it doesn't have the ability to reason so it it does and there is no system to bear but I think very importantly it doesn't have any causality or any way to represent meaning and to represent real interaction so until that is solved the you know what can be accomplished is marvelous and very exciting but limited that's actually really nice to think of current advances in machine learning is essentially system one advances so how far can we get with just system one if we think of learning and artificial systems and we know it's very clear that deep mind is already gone we're way beyond what people thought was possible I think I think the thing that has impressed me most about the developments in AI is the speed it's that things at least in the context of deep learning and maybe this is about to slow down but things moved a lot faster than anticipated the transition from solving solving chess to solving go was I mean that's the world rain how quickly it went the move from alphago to alpha 0 is sort of bewildering the speed at which they accomplish that now clearly there they're eight so there are many problems that you can solve that way but there's some problem for which who needs something else something like a reasoning where reasoning and also you know that one of the real mysteries psychologist there Gary Marcus who is also a critic of AI I mean he what he points out and I think he has a point is that humans learn quickly children don't need million examples they need two or three examples so clearly there is a fundamental difference and what enables what enable the machine to to learn quickly what you have to build into the machine because it's that you have to build some expectations or something in the machine to make it ready to learn quickly that's that at the moment seems to be unsolved I'm pretty sure that the mind is working on it but yeah there if they have solved it I haven't heard yet they're trying to actually them an open they are trying to start to get to use neural networks to reason so assemble knowledge of course causality is temporal causality is out of reach to most everybody you mentioned the benefits of system one is essentially that it's fast allows us to function in the world now some skilled you know its skill and it has a model of the world you know in a sense I mean there was the earlier phase of a I attempted to moral reasoning and they were moderately successful but you know reasoning by itself doesn't get you much deep learning has been much more successful in terms of you know what they can do but now it's an interesting question whether its approaching its limits what do you think I think absolutely so I just talked to John laocoon he mentioned you know I know him so he thinks that the limits were not going to hit the limits with you all networks that ultimately this kind of system on pattern matching will start to start to look like system two with without significant transformation of the architecture so I'm more with the but the majority of the people who think that yes new all networks will hit a limit in their capability he on the one hand I have heard him tell the missus obvious essentially that you know what they have accomplished it's not a big deal that they have just touched that basically you know they can't do unsupervised learning in in an effective way and but you're telling me that he thinks that the current within the current architecture you can do causality and reasoning so he's very much a pragmatist in a sense that saying that were very far away that they're still yeah I think there's this idea that he says is uh we can only see one or two mountain peaks ahead and there might be either a few more after or thousands more after yeah so that kind of idea right but nevertheless it doesn't see a the final answer not fundamentally looking like one that we currently have so neural networks being a huge part that you know I mean that's very likely because because pattern matching is so much of what's going on and you can think of neural networks as processing information sequentially yeah I mean you know there is there is an important aspect to for example you get systems that translate and they do a very good job but they really don't know what they're talking about and and and for that I'm really quite surprised for that you would need you would need an AI that has sensation an AI that is in touch with the world awareness and maybe even something resembles consciousness kind of ideas li awareness of you know awareness of what's going on so that the the words have meaning who can get are in touch with some perception or some action yeah so that's a big thing for yarn and as well here first is grounding to the physical space so so that's what we're talking about the same yeah so but so how you ground I mean the grounding without grounding then you get you get a machine that doesn't know what it's talking about because it is talking about the world ultimately the question open question is what it means to ground I mean we're very human centric in our thinking but what does it mean for a machine to understand what it means to be in this world does it need to have a body does he need to have a finiteness like we humans have all of these elements it's very nice to know I'm you know I'm not sure about having a body but having a perceptual system having a body would be very helpful to me if if you think about human mimicking human ooh but having a perception that seems to be central so that you can build you can accumulate knowledge about the world so if you can you can imagine a human completely paralyzed and there's a lot that the human brain could learn you know with a paralyzed body so if we got a machine that could do that it would be a big deal and then the flip side of that something you see in children and something in machine learning world is called active learning maybe it is is being able to play with the world how important for developing system owners or system to do you think it is to play with the world be able to interact with me a lot a lot of what you learn as you learn to anticipate the outcomes of your actions I mean you can see that how babies learn it you know with their hands they are they learn you know to connect you know the movement so their hands with something that clearly is something that happens in the brain and and and the ability of the brain to learn new patterns so you know it's the kind of thing that you get with artificial limbs that you connect it and then people learn to operate the artificial limb you know really impressively quickly at least from from what I hear so and we have a system that is ready to learn the world's reaction at the risk of going into way too mysterious of land what do you think it takes to build a system like that obviously we're very far from understanding how the brain works but how difficult is it to build this mind of ours you know I mean I think that yonder Coons answer that we don't know how many mountains there are I think that's a very good answer I think that you know if you if you look at what cool Ray Kurzweil is saying that strikes me as of the war but but I think people are much more realistic than that were actually they Mesa sabe is and Yanis and so the people are actually doing the work fairly realistic I think - maybe phrase it another way from a perspective not of building it but from understanding it how complicated are human beings in the following sense you know I work with autonomous vehicles and pedestrians so we tried to model pedestrians how difficult is it to model a human being their perception of the world the two systems they operate under sufficiently to be able to predict whether the pedestrians gonna cross the road or not I'm you know I'm fairly optimistic about that actually because what we're talking about is a huge amount of information that every vehicle has and that feeds into one system into one gigantic system and so anything that any vehicle learns becomes part of what the whole system knows and with a sister multiplier like that there is a lot that you can do so human beings are very complicated but and and you know system is going to make mistakes but human makes mistakes I think that they'll be able to I think they are able to anticipate pedestrians otherwise a lot would happen they're able to you know they're able to get into a roundabout and into the end to traffic so they must know both to expect though to anticipate how people will react when they're sneaking in and there's a lot of learning that's involved in that currently the pedestrians are treated as things that cannot be hid and not treated as agents with whom you interact in a game theoretic way so I mean it's not it's a totally open problem and every time somebody tries to solve it it seems to be harder than we think and nobody's really tried to seriously solve the problem of that dance because I'm not sure if you've thought about the problem of pedestrians but you're really putting your life in the hands of the driver you know there is a dance as part of the dance that would be quite complicated but for example when I cross the street and there is vehicle approaching I look the driver in the eye and I think many people do that and you know that's a signal that that I'm sending and I would be sending that machine to an autonomous vehicle and it had better understand it because it means I'm crossing so and there's another thing you do that actually so I'll tell you what you do because we watch I've watched hundreds of hours of video on this is when you step in the street you do that before you step on the street and when you step in the street you actually look awake away yeah yeah now what what is it what the saying is mean you're trusting that the car who hasn't slowed down yet will slow down and you're telling him yeah I'm committed yeah I mean this is like in a game of chicken so I'm committed and if I'm committed I'm looking away so there is you you just have to stop so the question is whether a machine that observes that needs to understand mortality here I'm not sure that it's got to understand so much it's got to anticipate so and here but you know you're surprising me because here I would think that maybe you can anticipate without understanding because I think this is clearly what's happening in playing go or in playing trace there's a lot of anticipation and there is zero understanding so I thought that you didn't need a model of the human yes and the model of the human mind to avoid hitting pedestrians but you are suggesting that I do yeah you do as and then it's then it's a lot harder so this is all and I have a follow-up question to see where your intuition lies is it seems that almost every robot human collaboration system is a lot harder than people realize so do you think it's possible for robots and humans to collaborate successfully if we talked a little bit about semi autonomous vehicles like in the Tesla autopilot but just in tasks in general if you think we talked about current you'll know where it's being kind of system one do you think those same systems can borrow humans for system to type tasks and collaborate successfully well I think that in any system where humans and the Machine interact that the human will be superfluous within a fairly short time and that is if the Machine has advanced enough so that it can really help the human then it may not need the human for a long now it would be very interesting if if there are problems that for some reason the machine doesn't you're not so but that people could solve then you would have to build into the machine and ability to recognize that it is in that kind of problematic situation and and to call the human that that cannot be easy without understanding that is its it must be very difficult to to program a recognition that you are in a problematic situation without understanding the problem but that's very true in order to understand the full scope of situations that are problematic you almost need to be smart enough to solve all those problems it's not clear to me how much the machine will need the human I think the example of chess is very instructive I mean there was a time at which Kasparov was saying that human machine combinations will beat everybody even stockfish doesn't need people yeah and alpha zero certainly doesn't need people the question is just like you said how many problems are like chess and how many problems are the ones where are not like chess where even well every problem probably in the end is like chess the question is how long is that transition period I mean you know that that's a question I would ask you in terms of men autonomous vehicle just driving is probably a lot more complicated than go to solve that yes and that's surprising because it's open no I mean you know I couldn't that's not surprising to me because the because that there is a hierarchical aspect to this which is recognizing a situation and then within the situation bringing bringing up the relevant knowledge and and for that hierarchical type of system to work you need a more complicated system currently a lot of people think because as human beings this is probably the the cognitive biases they think of driving is pretty simple because they think of their own experience this is actually a big problem for aai researchers or people thinking about AI because they evaluate how hard a particular problem is based on very limited knowledge but basically how hard it is for them to do the task yeah and then they take for granted I mean maybe you can speak to that because most people tell me driving is trivial and and humans in fact are terrible at driving is what people tell me and I see humans and humans are actually incredible at driving and driving is really terribly difficult yeah so is that just another element of the effects that you've described in your work on the psychology side oh no I mean I haven't really you know I I would say that my research has contributed nothing to understanding the ecology into understanding the structure of situations yeah and the complexity of problems so all all we know is very clear that that go it's endlessly complicated but it's very constrained so and in the real world there are far fewer constraints and and many more potential surprises so so that's obviously because it's not always obvious to people right so when you think about well I mean you know people thought that reasoning was hard and perceiving was easy but you know they quickly learned that actually modeling vision was tremendously complicated and modelling even proving theorems was relatively straightforward to push back in and out a little bit on the quickly part they haven't it took several decades to learn that and most people still haven't learned that I mean our intuition of course AI researchers have but you drift a little bit outside the specific a I feel the intuition is still perceptible yes all no I mean that's true I mean intuitions the intuitions of the public haven't changed radically and they are there as you said they're evaluating the complexity of problems by how difficult it is for them to solve the problems and that's got very little to do with the complexities of solving them in AI how do you think from the perspective of AI researcher do we deal with the intuitions of the public so in trying to think me arguably the combination of hype investment and the public intuition is what led to the AI winters I'm sure that same can be applied to tech or that the intuition of the public leads to media hype these two companies investing in the tech and then the text doesn't make the company's money and then there's a crash is there a way to educate people is there to fight the let's call it system 1 thinking in general no I think that's the simple answer and it's going to take a long time before the understanding of where those systems can do becomes you know button becomes public knowledge I and and then and the expectations you know there are several aspects that are going to be very complicated that the the fact that you have a device that cannot explain itself is a major major difficulty and and we're already seeing that I mean this is this is really something that is happening so it's happening in the judicial system so you have you have system that are clearly better at predicting parole violations then than judges but but they can't explain their reasoning and so people don't want to trust them we are seem to you in system one even use cues to make judgments about our environment so this explain ability point do you think humans can explain stuff no but so I mean there is a very interesting aspect of that humans think they can explain themselves right so when you say something and I ask you why do you believe that then reasons will occur to you and you were but actually my own belief is that in most cases the reasons are very little to do with why you believe what you believe so that the reasons are a story that that comes to your mind when you need to explain yourself but but but people traffic in those explanations I mean the human interaction depends on those shared fictions and and the stories that people tell themselves you just made me actually realize and we'll talk about stories in a second that not to be cynical about it but perhaps there's a whole movement of people trying to do explainable AI and really we don't necessarily need to explain hey I just need to explain itself it just needs to tell a convincing story yeah it doesn't missus the story doesn't necessarily need to reflect the truth is it just needs to be convincing there's something you can say exactly the same thing in a way that's sound cynical abysm sounds in a grave and so but but the objective brilliant of having an explanation is is to tell a story that would be acceptable to people and and and for it to be acceptable and to be a robustly acceptable it has to have some elements of truth but but the objective is for people to accept it it's quite brilliant actually but so on the and the stories that we tell sorry to ask me to ask you the question that most people know the answer to but you talk about two cells in terms of how life has lived the experience self and remembering self and you describe the distinction between the two well sure I mean the there is an aspect of of life that occasionally you know most of the time we just live and web experiences and they're better and they are worse and it goes on over time and mostly we forget everything happens we forget most of what happens then occasionally you when something ends or different points you evaluate the past and you form a memory and the memory is schematic it's not that you can roll a film of an interaction you construct in effect the elements of a story about it about an episode so there is the experience and there is a story that is created about the experience and that's what I call the remember II so I had the image of two selves so there is a self that lives and there is a self that evaluates life now the paradox and the deep paradox in that is that we have one system or one self that does the living but the other system the remembering self is all we get to keep and basically decision-making and and everything that we do is governed by our memories not by what actually happened it's it's governed by by the story that we told ourselves or by the story that we're keeping so that that's the distinction I mean there's a lot of ideas about the pursuit of happiness that come out of that what are the properties of happiness which emerge from yourself there are there are properties of how we construct stories that are really important so that I studied a few but but a couple are really very striking and one is that in stories time doesn't matter there's a sequence of events so there are highlight those not and and how long it took you know they lived happily ever after and three years later something it time really doesn't matter and in stories events matter but time doesn't that that leads to a very interesting set of problems because time is all we got to live I mean you know time is the currency of life and yet time is not represented basically in evaluative memories so that that creates a lot of paradoxes that I've thought about yeah they're fascinating but if you were to [Music] give advice on how one lives a happy life well this and such properties what's the optimal you know I give up I abandoned happiness research because I couldn't solve that problem I couldn't I couldn't see and in the first place it's very clear that if you do talk in terms of those two selves then that what makes the remembering self happy and what makes the experiencing self happy are different things and I I asked the question of suppose you're planning a vacation and you're just told that at the end of the vacation you'll get an amnesic drugs who remember nothing and they'll also destroy your your photos so there'll be nothing would you still go to the same vacation and and it's it turns out we go to vacations in large part to construct memories not to have experiences but to construct memories and it turns out that the vacation that you would want for yourself if you knew you would not remember is probably not the same vacation that you will want for yourself if you will remember so I have no solution to these problems but clearly those are big issues and you've thought about issues you've talked about sort of how many minutes or hours you spend about the vacation it's an interesting way to think about it because that's how you really experience the vacation outside the being in it but there's also a modern I don't know if you think about this or interact with it there's a modern way to magnify the remembering self which is by posting an Instagram on Twitter on social networks a lot of people live life for the picture that you take that you post somewhere and now thousands of people sharing and potentially petitioning millions and then you can relive it even much more than just those minutes do you think about that i magnification much you know I'm too old for social networks I you know I've never seen Instagram so I cannot really speak intelligently about those things I'm just too old but it's interesting to watch the exact times you describe I make a very big difference I mean and it will make it will also make a difference and that I don't know whether it's clear that in some ways the devices that serve us supplants function so you don't have to remember phone numbers you don't have you really don't have to know facts I mean the number of conversations I'm involved with when somebody says well let's look it up so it's it's in a way it's made conversations well it's it means that it's much less important to know things you know it used to be very important to know things this is changing so the requirements of that that we have for ourselves and for other people are changing because of all those supports and because and I have no idea but Instagram does connected so well I'll tell you train you I mean I wish I could just have the my remembering self could enjoy this conversation but I'll get to enjoy it even more by having watched by watching it and then talking to others will be about a hundred thousand people scary's is this to say well listen or watch this right it changes things it changes the experience of the world that you seek out experiences which could be shared in that way it's in and I haven't seen it's it's the same effects that you described and I don't think the psychology of that magnification has been described yet because in your world the sharing then was appear there was a time when people read books and you could assume that your friends had read the same books that you read so there was kind of invisible sharing a year it was a lot of sharing going on and there was a lot of assumed common knowledge and you know that was built in I mean it was obvious that you had read the New York Times it was obvious that you'd read the reviews I mean so a lot was taken for granted that was shared and you know when they were when there were three television channels it was obvious that you'd seen one of them probably the same so sharing sharing he's always been always was always there it was just different at the risk of inviting mockery from you let me say there that I'm also a fan of Sartre and Camus and existentialist philosophers and I'm joking of course about mockery but from the perspective of the two selves what do you think of the existentialist philosophy of life so trying to really emphasize the experiencing self as the proper way to or the best way to live life I don't know enough philosophy to and so that but it's not a you know the emphasis on an experience is also the emphasis in Buddhism right it's so that you just have got to to experience things and and and not to evaluate and not to pass judgment and not to score not to keep score so if when you look at the the grand picture of experience you think there's something to that that one one of the ways to achieve contentment and maybe even happiness is letting go of any of the things any of the procedures of the remembering self well yeah I mean I think you know if one could imagine a life in which people don't score themselves it it feels as if that would be a better life as if the self scoring and you know how am i doing a kind of question is not is not a very happy thing to have but I got out of that field because I couldn't solve that and and that was because my intuition was that the experiencing self that's reality but then it turns out that what people want for themselves there's not experience that they want memories and they want a good story about their life and so you cannot have a theory of happiness that doesn't correspond to what people want for themselves and when I when I realized that this this was where things were going I really sort of left the field of research do you think there's something instructive about this emphasis of reliving memories in building AI systems so currently artificial intelligence systems are more like experiencing self in that they react to the environment there's some pattern formation like learning so on but you really don't construct memories except in reinforcement learning everyone swather you replay over and over yeah but you know that would in principle would not be you know yes useful do you think it's a feature a bug of human beings that we that we look back oh I think that's definitely a feature that's not a bug I mean you you have to look back in order to look forward so without without looking back you couldn't you couldn't really intelligently look forward you're looking for the echoes of the same kind of experience in order to predict what the future holds yeah though Viktor Frankl in his book man's search for meaning I'm not sure if you've read describes his experience at the consecration a concentration camps during World War two as a way to describe that finding identifying a purpose in life a positive purpose in life can say one from suffering first of all do you connect with the philosophy they he describes they're not really I mean the so I can I can really see that somebody who has that feeling of per person meaning and so on that that could sustain you I in general don't have that feeling and I'm pretty sure that if I were in a concentration camp and give up and die you know so he talks he is he's a survivor yeah and you know he survived with that and I'm and I'm not sure how I central to survival the same years yeah I do know when I think about myself that I would have given up at oh yeah this isn't going anywhere and there is there is a sort of character that that that manages to survive in conditions like that and then because they survive they tell stories and it sounds as if they survived because of what they were doing we have no idea they survived because the kind of people that they are and the other kind of people survives them to tell them such stories of a particular guy so I'm not so that you don't think seeking purpose is a significant driver and are the units it's a very interesting question because when you ask people whether it's very important to add meaning in their life that's oh yes that's the most important thing but when you ask people what kind of a day did you have and and you know what were the experiences that you remember you don't get much meaning you get social experiences then and and some people say that for example in in in child you know in taking care of children the fact that they're your children and you're taking care of them makes a very big difference I think that's entirely true but it's more because the story that we are telling ourselves which is a very different story when we're taking care of our children or when we're taking here other thing jumping around a little bit in doing a lot of experiments let me ask a question most of the work I do for example is in the wall in the real world but most of the clean good-sized that you can do is in the lab so that distinction do you think we can understand the fundamentals of human behavior through controlled experiments in the lab if we talk about pupil diameter for example it's much easier to do when you can control lighting conditions yeah thanks so when we look at driving lighting variation destroys yeah absolutely your ability to use pupil diameter but in the lab for as I mentioned semi autonomous autonomous vehicles in driving simulators we can't we don't capture true honest human behavior in that particular domain so your what's your intuition how much of human behavior can we study in this controlled environment of the lab a lot but you'd have to verify it you know that you'll your conclusions are basically limited to the situation to the experimental situation then you have to jump the big inductive leap to the real world so and and that's the Flair that's where the difference I think between the good psychologist and others of the mediocre is in the sense of that your experiment captures something that's important and something that's real and others are just running experiments so what is that like the birth of an idea to his development in your mind to something that leads to an experiment is that similar to maybe like what I Steiner good physicists do is your intuition you basically use your intuition to build up but I mean you know it's it's very skilled intuition right I mean I just had that experience actually I had an idea that's turned out to be very good idea a couple of days ago and and you and you have a sense of that building up so I'm working with a collaborator and he essentially was saying you know what what are you doing what's what's going on and I was I really I couldn't exactly explain it but I knew this is going somewhere but you know I've been around that game for a very long time and so I can you you develop that anticipation that yes this this is worth following now that he's here that's part of the skill is that something you can reduce two words in describing a process in in the form of advice to others know follow your heart essentially you know it's it's like trying to explain what it's like to drive it's not you've got to break it apart and it's not and then you lose and then you lose the experience them you mentioned collaboration you've written about your collaboration with Amos Tversky that this is you writing the twelve or thirteen years in which most of our work was joint four years of interpersonal and intellectual bliss everything was interesting almost everything was funny and that was a current joy of seeing an idea take shape so many times in those years we shared the magical experience of one of us saying something which the other one would understand more deeply than a speaker had done contrary to the old laws of information theory it was common for us to find that more information was received than had been sent I have almost never had the experience with anyone else if you have not had it you don't know how marvelous collaboration can be so let me ask a bird perhaps a silly question how does one find in create such a collaboration that may be asking like how does one find love but yeah yeah to be you have to be lucky and and I think you have to have the character for that because I've had many collaborate I mean none worth as exciting as with almost be but Fahad and I'm having it was very so it's a skill I think I'm good at it not everybody is good at it and then it's the luck of finding people who are also good at it is there advice in a forum for a young scientist who also seeks to violate this law of information dairy I really think it's so much luck is involved and you know in in those really serious collaborations at least in my experience are a very personal experience and and I have to like the person I'm working with otherwise you know I mean there is that kind of collaboration which is like an exchange a commercial exchange of giving this you give me that but the the real ones are interpersonal they're between people like each other and and who like making each other think and who like the way that the other person responds to your thoughts you have to be lucky yeah I mean but I already noticed if I even just me showing up here evil you've quickly started to digging in a particular problem I'm working on and already new information started to emerge is that a process you just the process of curiosity of talking to people about problems and seeing I'm curious about anything to do with AI and robotics and on so and I knew that you were dealing with that so it was curious just follow your curiosity jumping around and a psychology front the dramatic sounding terminology of replication crisis but really just the at times this this effect at a time studies do not are not fully generalizable they don't you have being polite is it so I'm actually not fully familiar well the memory how bad it is right so what do you think is the source where do you think I think I know what's going on actually I mean I have a theory about what's going on and what's going on is that there is first of all a very important distinction between two types of experiments and one type is within subject so it's the same person has two experimental conditions and the other type is between subjects where some people have this condition are the people in that condition they're different world and between subject experiments are much harder to predict and much harder to anticipate and the reason and they're also more expensive because you need more people and it's just so between subject experiments is where the problem is it's not so much and within subject experiments it's really between and there is a very good reason why the intuitions of researchers about between subject experiments are wrong and that's because when you are a researcher you're in a within subject situation and it is you are imagining the two conditions and you see the causality and you feel it and but in the between subjects condition they don't like they see they live in one condition and the other one is just nowhere so our intuitions are very weak about between subject experiments and that I think is something that people haven't realized and and in addition because of that we have no idea about the power of manipulations of experimental manipulations because the same manipulation it's much more powerful when when you are in the two conditions then when you live in only one condition and so the experimenters have very poor intuitions about between subject experiments and and there is something else which is very important I think which is that almost all psychological hypotheses are true that is in the sense that you know directionally if you have a hypothesis that a really causes B that that it's not true that is causes the opposite of B maybe a just and very little effect but hypotheses are true mostly except mostly they're very weak they're much weaker than you think when you are having images of so the reason I'm excited about that is that I recently heard about some some friends of mine who they essentially funded 53 studies of behavioral change by 20 different teams of people with a very precise objective of changing the number of time that people go to the gym but you know and and the success rate was zero the knocks one of the 53 studies work now what's interesting about that is those are the best people in the field and they have no idea what's going on so they are not calibrated they think that it's going to be powerful because they can imagine it but actually it's just weak because the and you are focusing on on your manipulation and it feels powerful to you there's a thing that I've written about that's called the focusing illusion that is that when you think about something it looks very important more important than it really is more important than it really is but if you don't see that effect the 53 studies doesn't I mean you just report that so what was I guess the solution to that well I mean the the solution is for people to trust their intuitions less all to try out their intuitions before I mean experiments have to be pre-registered and by the time you run an experiment you have to be committed to it and you have to run the experiment seriously enough and in a public and so this is happening and the interesting thing is what what happens before and how do people prepare themselves and how they run pilot experiments it's going to train the way psychologies done and it's already happening do you ever hope for as my connect to the this study sample size yeah I do ever hope for the internet or do you know this is really happening MTurk yeah everybody is running experiments on him to look and and it's very cheap and very effective do you think that changes psychology essentially because you're think you can object it then truly it will I mean I you know I can't put my finger on how exactly but it that's been true in psychology with whenever an important new method came in it changes the feel so and an M torque is really a method because exact it makes it very much easier to do something to do some things is there are undergrad students will ask me you know how big a neural network should be for a particular problem so let me ask you an equivalent equivalent question how big how many subjects they study have for it to have a conclusive result well depends on the strength of the effect so if you're studying visual perception the perception of color many other are the classic results in in visual in color perception we've done on three or four people and I think and one of them was called a blind but or they'd partly colorblind but on vision you know you belong many people don't need a lot of replications for some type of neurological experiment neuro when you're studying weaker phenomena and especially when you're studying them between subjects then you need a lot more subjects than people have been running and that is that's one of the things that are happening in psychology now is that the power is a statistical power the experiment is increasing rapidly does that between subjects as the number of subjects goes to infinity approach well I mean you know goes to infinity is exaggerated but people the standard number of subjects for an experiment psychology with 30 or 40 and for a weak effect that's simply not enough and you may need a couple of hundred I mean it's that that sort of order of magnitude what are the major disagreements in theories and effects that you've observed throughout your career that's the stand today well you work on several fields yeah but what still is out there as major disagreement offs in your mind and I've had one extreme experience of you know controversy with somebody who really doesn't like the work that they must risky and I did and he's been after us for 30 years or more at least when I talk about it well I mean his name is good Giga answer he's a well-known German psychologist and that's the one controversy I have which I it's been unpleasant and no I don't particularly want to talk about it but it's there is their open questions even in your own mind every once in a while you know we talked about semi autonomous vehicles in my own mind I see what the data says but I also constantly torn do you have things where you or your studies have found something but you're also intellectually torn about what it means and there's been maybe disagreement you within your own mind about particularly I mean it's you know one of the things that are interesting is how difficult it is for people to change their mind essentially you know once they're committed people just don't change their mind about anything that matters and that is surprisingly but it's true about scientists so the controversy that I described in other it's been going on like thirty years and it's never going to be resolved and you build a system and you live within that system and other other systems of ideas look foreign to you and there is very little contact and very little mutual influence that happens a fair amount do you ever hopeful advice or message on that we think about science thinking about politics thinking about things that have impact on this world how can we change your mind I think that I mean on things that matter or a political or a little religious and people just don't don't change their mind and by and large and there is very little that you can do about it the what does happen is that if leaders change their mind so for example the public the American public doesn't really believe in climate change doesn't take it very seriously but if some religious leaders decided this is a major threat to humanity that would have a big effect so that we we have the opinions that we have not because we know why we have them but because we trust some people and we don't trust other people and so it's much less about evidence than it is about stories so the way one way to change your mind isn't at the individual level is that the leaders of the communities you look up with the stories change and therefore your mind changes with them so there's a guy named Alan Turing came up with a touring test yeah what what do you think is a good test of intelligence perhaps we're drifting in a topic that were maybe philosophizing about but what do you think is a good test for intelligence for an artificial intelligence system well the standard definition of you know official general intelligence is that it can do anything that people can do and it can do them better yes what what we are seeing is that in many domains you have domain-specific and you know devices or programs or software and they beat people easily in specified way but we are very far from is either generally ability a general-purpose intelligence so we in in machine learning people are approaching something more general I mean for alpha 0 ISM was much more general than than alphago and but it's still extraordinarily narrow and specific in what it can do so we're quite far from from something that can in every domain think like a human except better what aspects of the Turing test has been criticized its natural language conversation you know that it's too simplistic guys it's easy to quote unquote pass under under constraints specified it what aspect of conversation would impress you if you heard it is it humor is it what what would impress the heck out of you if if you saw it in conversation yeah I mean suddenly wit would yeah which would be impressive and and humor would be more impressive than just factual conversation which i think is is easy and illusions would be interesting and metaphors would be interesting I mean but new metaphors not practice metaphors so there's a lot that you know would be sort of impressive and that it's completely natural in conversation but that you really wouldn't expect there's the possibility of creating and a human level intelligence or super human level intelligence system excite you scare you well I mean how does it make you feel I find the whole thing fascinating absolutely fascinating exciting I think and exciting it's also terrifying you know but but I'm not going to be around to see it and so I'm curious about what is happening now but I also know that that predictions about it are silly we really have no idea but it will look like 30 years from now no idea speaking of silly bordering and the profound they may ask the question of in your view what is the meaning of it all the meaning of life he's a descendant of great apes that we are why what drives us as a civilization as a human being as a force behind everything that you've observed and studied is there any answer or is it all just a beautiful mess there is no answer that that I can understand and I'm not and I'm not actively looking for one do you think an answer exists no there is no answer that we can understand I'm not qualified to speak about what we cannot understand but there is I know that we cannot understand reality you know and I mean there's other thing that we can do I mean you know gravity waves and that's a big moment for Humanity and when you imagine that eeep you know being able to to go back to the Big Bang that's that but but the y-yeah the warrior than us the why is hopeless really day thank you so much it was an honor thank you for speaking thank you thanks for listening to this conversation and thank you to our presenting sponsor cash app downloaded use code Lex podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe on YouTube get five stars an apple podcast follow on Spotify supported on patreon or simply connect with me on Twitter and now let me leave you with some words of wisdom from Danielle Cartman intelligence is not only the ability to reason it is also the ability to find relevant material and memory and to deploy attention when needed thank you for listening and hope to see you next time you |
Grant Sanderson: 3Blue1Brown and the Beauty of Mathematics | Lex Fridman Podcast #64 | the following is a conversation with grant Sanderson he's a math educator and creator of three blue one brown a popular YouTube channel that uses programmatically animated visualizations to explain concepts and linear algebra calculus and other fields of mathematics this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast follow on Spotify support on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma n I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has an investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and charity navigator which means the donated money is used to maximum effectiveness when you get cash app from the App Store Google Play and use coal export gas you'll get 10 dollars in cash Apple also donate $10 to 1st which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with Grant Sanderson if there's intelligent life out there in the universe do you think their mathematics is different than ours jumping right in I think it's probably very different there's an obvious sense the notation is different right I think notation can guide what the math itself is I think it has everything to do with the form of their existence right do you think they have basic arithmetic sorry interrupt yeah so I think they count right I think notions like 1 2 3 the natural numbers that's extremely well natural that's almost why we put that name to it as soon as you can count you have a notion of repetition right because you can count by two two times or three times and so you have this notion of repeating the idea of counting which brings you addition and multiplication I think the way that we extend to the real numbers there's a little bit of choice in that so there's this funny number system called the serial numbers that it captures the idea of continuity it's a distinct mathematical object you could very well you know model the universe and motion of planets with that as the backend of your math right and you still have kind of the same interface with the front end of what physical laws you're trying to or what physical phenomena you're trying to describe with math and I wonder if the little glimpses that we have of what choices you can make along the way based on what different mathematicians have brought to the table is just scratching the surface surface of what the different possibilities are if you have a completely different mode of thought right or a mode of interacting with the universe and you think notation is the key part of the journey that we've taken through math I think that's the most salient part that you'd notice at first I think the mode of thought is going to influence things more than like the notation itself but notation actually carries a lot of weight when it comes to how we think about things more so than we usually give it credit for I would I would be comfortable saying give a favor or least favorite piece of notation in terms of its effectiveness yes yeah well so at least favorite one that I've been thinking a lot about that will be a video I don't know when but we'll see the number e we write the function e to the X this general exponential function with a notation e to the X that implies you should think about a particular number this constant of nature you repeatedly multiply it by itself and then you say well what's e to the square root of two and you're like oh well we've extended the idea of repeated multiplication that's and that's all nice that's all nice and well but very famously you have like e to the PI you're like well we're extending the idea of repeated multiplication into the complex numbers yeah you can think about it that way in reality I think that it's just the wrong way of notationally representing this function the exponential function which itself could be represented a number of different ways you can think about it in terms of the problem it solves a certain very simple differential equation which often yields way more insight than trying to twist to the idea of repeated multiplication like take its arm and put it behind its back and throw it on the desk and be like you will apply to complex numbers right that's not I don't think that's pedagogically helpful and so the repeater multiplication is actually missing the main point the power of e to the S I mean what it addresses is things where the rate at which something changes depends on its own value but more specifically it depends on it linearly so for example if you have like a population that's growing and the rate at which it grows depends on how many members of the population are already there it looks like this nice exponential curve it makes sense to talk about repeated multiplication because you say how much is there after one year two years three years you're multiplying by something the relationship can be a little bit different sometimes where let's say you've got a ball on a string like a like a game of tetherball going around a rope right and you say it's velocity is always perpendicular to its position that's another way of describing its rate of change is being related to where it is but it's a different operation you're not scaling it it's a rotation it's this 90 degree rotation that's what the whole idea of like complex exponentiation is trying to capture but it's obfuscated in the notation when what it's actually saying like if you really parse something like e to the PI I what it's saying is choose an origin always move perpendicular to the vector from that origin to you okay then when you walk PI times that radius you'll be halfway around like that's what it's saying it's kind of the u-turn 90 degrees and you walk you'll be going in a circle that's the phenomenon that it's describing but trying to twist the idea of repeatedly multiplying a constant into that like I I can't even think of the number of human hours of like intelligent human hours that have been wasted trying to parse that to their own liking and desire among like scientists or electrical engineers if students have we were which if the notation were a little different or the way that this whole function was introduced from the get-go were framed differently I think could have been avoided right and you're talking about the most beautiful equation in mathematics but it's still pretty mysterious isn't it like you're making it seem like it's a notational it's not mysterious I think I think the notation makes it mysterious I don't think it's I think the fact that it represents it's pretty it's not like the most beautiful thing in the world but it's quite pretty the idea that if you take the linear operation of a 90 degree rotation and then you do this general exponentiation thing to it that what you get are all the other kinds of rotation which is basically to say if you if your velocity vector is perpendicular to your position vector you walk in a circle that's pretty it's not the most beautiful thing in the world but it's quite pretty the beauty of it I think comes from perhaps the awkwardness of the notation somehow still nevertheless coming together nicely because you have like several disciplines coming together in a single equation well in a sense like historically speaking but that's true you've got so like the number E is significant like it shows up in probability all the time it like shows up in calculus all the time it is significant you're seeing is sort of mated with PI this geometric constant and I like the imaginary number and such I think what's really happening there is the the way that a shows up is when you have things like exponential growth and decay right it's when this relation that that something's rate of change has to itself is a simple scaling right a similar law also describes circular motion because we have bad notation we use the residue of how it shows up in the context of self-reinforcing growth like a population growing or compound interest the constant associated with that is awkwardly placed into the context of how rotation comes about because they both come from pretty similar equations and so what we see is the e and the pi juxtaposed a little bit closer than they would be with a purely natural representation I would think here's how I would describe the relation between the two you've got a very important function we might call X that's like the exponential function when you plug in one you get this nice constant called EE that shows up in like probability and calculus if you try to move in the imaginary direction it's periodic and the period is tau so those are these two constants associated with this the same central function but for kind of unrelated reasons right and not unrelated but like orthogonal reasons one of them is what happens when you're moving in the real direction one's what happens when you move in the imaginary direction and like yeah those are related they're not as related as the famous equation seems to think it is it's sort of putting all of the children in one bed and they kind of like to sleep in separate beds if they have the choice but you see them all there and you know there is a family resemblance but it's not that close so actually think of it as a function is uh this is the better idea and that's a notational idea and yeah and like here's the thing the constant e sort of stands is this numerical representative of calculus right yeah calculus is the like study of change mm-hmm so it's very at least there's a little cognitive dissonance using a constant to represent the science of change never thought of it that way yeah yeah it makes sense why the notation came about that way yes because this is the first way that we saw it um in the context of things like population growth or compound interest it is nicer to think about as repeated multiplication that's definitely nicer but it's more that that's the first application of what turned out to be a much more general function that maybe the intelligent life your initial question asked about would have come to recognize as being much more significant than the single use case which lends itself to repeated multiplication notation but let me jump back for a second to aliens and the nature of our universe okay do you think math is discovered or invented so we're talking about the different kind of mathematics that could be developed by the alien species the implied question is is yeah it's math discovered or invented is you know is fundamentally everybody going to discover the same principles of mathematics so the way I think about it and everyone thinks about it differently but here's my take I think there's a cycle at play where you discover things about the universe that tell you what math will be useful and that math itself is invented in a sense but of all the possible maths that you could have invented it's discoveries about the world that tell you which ones are so like a good example here is the Pythagorean theorem when you look at this do you think of that as a definition or do you think of that as a discovery from the historical perspective right a discovery because there were but that's probably because they were using physical object to build their intuition and from that intuition came the mathematics so the mathematics was some abstract world detached from physics but I think more and more math has become detached from you know we when you even look at modern physics from string theory so even general relativity I mean all math behind the 20th and 21st century physics kind of takes a brisk walk outside of what our mind can actually even comprehend in multiple dimensions for example anything beyond three dimensions maybe four dimensions no higher dimensions can be highly highly applicable I think this is a common misinterpretation the if you're asking questions about like a five dimensional manifold that the only way that that's connected to the physical world is if the physical world is itself a five dimensional manifold or includes them wait wait wait a minute wait a minute you're telling me you can imagine a five dimensional manifold no no that's not what I said I I'm I would make the claim that it is useful to a three dimensional physical universe despite itself not being three dimensional so it's useful meaningful even understand a three dimensional world it would be useful to have five dimensional manifolds yes absolutely because of state spaces but you're saying there in some in some deep way for us humans it does it does always come back to that three dimensional world for the useful usefulness that the dimensional world and therefore it starts with a discovery but then we invent the mathematics that helps us make sense of the discovery in a sense yes I mean just to jump off of the Pythagorean theorem it feels like a discovery you've got these beautiful geometric proofs where you've got squares and you're modifying there is it feels like a discovery if you look at how we formalize the idea of 2d space as being r2 right all pairs of real numbers and how we define a metric on it and define distance okay hang on a second we've defined distance so that the Pythagorean theorem is true so then suddenly it doesn't feel that great but I think what's going on is the thing that informed us what metric to put on r2 to put on our abstract representation of 2d space came from physical observations and the thing is there's other metrics you could have put on it we could have consistent math with other notions of distance it's just that those pieces of math wouldn't be applicable to the physical world that we study because they're not the ones where the Pythagorean theorem holds so we have a discovery a genuine bona fide discovery that informed the invention the invention of an abstract representation of 2d space that we call r2 and things like that and then from there you just study r2 is an abstract thing that brings about more ideas and inventions and mysteries which themselves might yield discoveries those discoveries might give you insight as to what else would be useful to invent and it kind of feeds on itself that way that's how I think about it so it's not an either/or it's not that math is one of these or it's one of the others at different times it's playing a different role so then let me ask the the Richard Fineman question then along that thread is what do you think is a difference between physics and math there's a giant overlap there's a kind of intuition that physicists have about the world that's perhaps outside of mathematics it's this mysterious art that they seem to possess we humans generally possess and then there's the beautiful rigour of mathematics that allows you to I mean just like what as we were saying invent frameworks of understanding our physical world so what do you think is the difference there and how big is it well I think of math as being the study of like abstractions over patterns and pure in logic and then physics is obviously grounded in a desire to understand the world that we live in yeah I think you're going to get very different answers when you talk to different mathematicians because there's a wide diversity and types of mathematicians there are some who are motivated very much by pure puzzles they might be turned on by things like combinatorics and they just love the idea of building up a set of problem-solving tools applying to pure patterns right there are some who are very physically motivated who who tried to invent new math or discover math in veins that they know will have applications to physics or sometimes computer science and that's what drives them right like chaos theory is a good example of something that it's pure math that's purely mathematical a lot of the statements being made but it's heavily motivated by specific applications to largely physics and then you have a type of mathematician who just loves abstraction they just love pulling into the more and more abstract things the things that feel powerful these are the ones that initially invented like topology and then later on get really into category theory and go on about like infinite categories and whatnot these are the ones that love to have a system that can describe truths about as many things as possible right people from those three different veins of motivation into math are going to give you very different answers about what the relation at play here is because someone like flightmare Arnold who is this he's written a lot of great books many about like differential equations and such he would say math is a branch of physics that's how he would think about it and of course he was studying like differential equations related things because that is the motivator behind the study of PDEs and things like that well you'll have others who like especially the category theorists who aren't really thinking about physics necessarily it's all about abstraction and the power of generality and it's more of a happy coincidence that that ends up being useful for understanding the world we live in and then you can get into like why is that the case that's sort of surprising that that which is about pure puzzles and abstraction also happens to describe the very fundamentals of quarks and everything else so what do you think the fundamentals of quarks and and the nature of reality is so compressible and too clean beautiful equations that are for the most part simple relatively speaking a lot simpler than they could be so you have we mentioned somebody like Stephen Wolfram who thinks that sort of there's incredibly simple rules underlying our reality but it can create arbitrary complexity but there is simple equations what I'm asking a million questions that nobody knows the answer to but no idea why is it simple I it could be the case that there's like a filter iteration I played the only things that physicists find interesting other ones little simple enough they could describe it mathematically but as soon as it's a sufficiently complex system like now that's outside the realm of physics that's biology or whatever have you and of course that's true all right you know maybe there's something what's like of course there will always be some thing that is simple when you wash away the like non important parts of whatever it is that you're studying just some like an information theory standpoint there might be some like you you get to the lowest information component of it but I don't know maybe I'm just having a really hard time conceiving of what it would even mean for the fundamental laws to be like intrinsically complicated like some some set of equations that you can't decouple from each other well no it could be it could be that sort of we take for granted that they're the the laws of physics for example are for the most part the same everywhere or something like that right as opposed to the sort of an alternative could be that the rules under which are the world operates is different everywhere it's like a like a deeply distributed system or just everything is just chaos like not not in a strict definition of cast but meaning like just it's impossible for equations to capture for to explicitly model the world as cleanly as the physical does any we're almost take it for granted that we can describe we can have an equation for gravity for action in a distance we can have equations for some of these basic ways the planets moving just the the low-level at the atomic scale all the materials operate at the high scale how black holes operate but it doesn't it it seems like it could be there's infinite other possibilities where none of it could be compressible into such equation so it just seems beautiful it's also weird probably to the point you're making that it's very pleasant that this is just for our minds right so it might be that our minds are biased to just be looking at the parts of the universe that are compressible and then we can publish papers on and have nice e equals mc-squared equations right well I wonder would such a world with uncompressible laws allow for the kind of beings that can think about the kind of questions that you're asking that's true right like an anthropic principle coming into play at some weird way here I don't know like I don't know what I'm talking about it or maybe the universe is actually not so compressible but the way our brain the the way our brain evolved were only able to perceive the compressible parts I mean we are so this is a sort of Chomsky argument we are just the sentence of apes over like really limited biological systems so totally make sense there were really limited little computers calculators that are able to perceive certain kinds of things in the actual world is much more complicated well but we can we can do pretty awesome things right like we can fly spaceships and that we have to have some connection of reality to be able to take our potentially oversimplified models of the world but then actually twist the world to our will based on it so we have certain reality checks that like physics isn't too far afield simply based on what we can do and the fact that we can fly is pretty good it's great the laws were working with our are working well so I mentioned to the internet that I'm talking to you and so the internet gave some questions so I apologize for these but do you think we're living in a simulation that the universe is a computer or the universe is the computation running a computer it's conceivable what I don't buy is you know you'll have the argument that well let's say that it was the case that you can have simulations then the simulated world would itself eventually get to a point where it's running simulations yes and then the the second layer down would create a third layer down and on and on and on so probabilistically you just throw a dart at one of those layers we're probably in one of the simulated layers I think if there's some sort of limitations unlike the information processing of whatever the physical world is like it quickly becomes the case that you have a limit to the layers that could exist there because like the resources necessary to simulate a universe like ours clearly is a lot just in terms of the number of bits at play and so then you can ask well what's more plausible that there's an unbounded capacity of information processing in whatever they like highest up level universe is or that there's some bound to that capacity which then limits like the number of levels available how do you play some kind of probability distribution on like what the information capacity is I have no idea but I I don't mean like people almost assume a certain uniform probability over all of those metal layers that could conceivably exist when it's a little bit like a Pascal's wager on like you're not giving a low enough prior to the mere existence of that infinite set of layers yeah that's true but it's also very difficult to contextualize the amount so the amount of information processing power required to simulate like our universe seems like amazingly huge what you can always raise two to the power of that exactly yeah like numbers bit big and we're easily humbled but basically everything around us so it's very difficult to to kind of make sense of anything actually when you look up at the sky and look at the stars in the immensity of it all to make sense of us the smallness of us the unlikeliness of everything that's on this earth coming to be then you could basically anything could be all laws of probability go out the window to me because I guess because the amount of information under which we're operating is very low we basically know nothing about the world around us relatively speaking and so so when I think about the simulation hypothesis I think is just fun to think about it but it's also I think there is a thought experiment kind of interesting to think of the power of computation where there are the limits of a Turing machine sort of the limits of our current computers when you start to think about artificial intelligence how far can we get with computers and that's kind of where the simulation hypothesis useless me as a thought experiment is is the universe just the computer is it just the computation is all of this just the computation and so the same kind of tools we apply to analyzing algorithms can that be applied you know if we scale further and further and further well the arbitrary power of those systems start to create some interesting aspects that we see in our universe or something fundamentally different needs to be created well it's interesting that in our universe it's not arbitrarily large the power that you can place limits on for example how many bits of information can be stored per unit area right like all of the physical laws we've got general relativity and like quantum coming together to give you a certain limit on how many bits you can store within a given range before it collapses into a black hole like the idea that there even exists such a limit is that the very least thought-provoking when naively you might assume oh well you know technology could always get better and better we could get cleverer and cleverer and you could just cram as much information as you want into like a small unit of space that makes me think it's at least plausible that whatever the highest level of existence is doesn't admit too many simulations or ones that are at the scale of complexity that we're looking at obviously it's just as conceivable that they do and that there are many but I I guess what I'm channeling is the surprise that I felt learning that fact that there are the information is physical in this way is that there's a finance to it okay let me just even go off on that from mathematics perspective and the psychology perspective how do you mix are you psychologically comfortable with the concept of infinity I think so are you okay with it I'm pretty okay yeah okay no not really it doesn't make any sense to me I don't know like how many how many words how many possible words do you think could exist that are just like strings of letters so that that's a sort of mathematical statement as beautiful and we use infinity basically everything we do everything we do inside in science math and engineering yes but you said exist my the question is well you said letters of words I said words words the to bring words into existence to me you have to start like saying them or like writing them or like listing them that's an instantiation okay combination how many abstract words exist it was the idea of abstract yeah the the idea of abstract notions and ideas I think we should be clear around terminology I mean you think about intelligence a lot like artificial intelligence would you not say that what it's doing is a kind of abstraction they're like abstraction is key to conceptualizing the universe you get this raw sensory data you need I need something that every time you move your face a little bit and the they're not pixels but like analog of pixels on my retina change entirely yeah that I can still have some coherent notion of this is Lex and planet Lex yes right what that requires is you have a disparate set of possible images hitting me that are unified in a notion of Lex yeah right that's a kind of abstraction it's a thing that could apply to a lot of different images that I see and it represents it in a much more compressed way and one that's like much more resilient to that I think in the same way if I'm talking about infinity as an abstraction I don't mean non-physical woowoo it like ineffable or something what I mean is it something that can apply to a multiplicity of situations that share certain common attribute in the same way that the images of like your face on my retina Sharon common attributes that I can put the single notion to it like in that way infinity is an abstraction and it's very powerful and and it's a it's only through such abstraction that we can actually understand like the world and logic and things and in the case of infinity the way I think about it the key entity is the property of always being able to add one more like no matter how many words you can list you just throw an A at the end of one and you have another conceivable word you don't have to think of all the words at once it's that property the oh I could always add one more that gives it this nature of infinite enos in the same way that they're certain like properties of your face that give it the Lexx miss right so like infinity should be no more worrying than the I can always add one more sentiment that's a really elegant much more elegant way than I could put it so thank you for doing that as yet another abstraction and yes indeed that's what our brain does that's what intelligence systems do this what programming does that's what science does is build abstraction on top of each other and yet there is at a certain point abstractions that go into the quote whoo right sort of and because we're now it's like it's like we built this stack of you know the the only thing that's true is the stuff that's on the ground everything else is useful for interpreting this and at a certain point you might start floating into ideas that are surreal and difficult and and take us into areas that are disconnected from reality in a way that we could never give back what if instead of calling these abstract how different would it be in your mind if we call them general and the phenomenon that you're describing is over generalization when you try them channelization yeah have a concept or an idea that's so general as to apply to nothing in particular in a useful way does that map to what you're thinking of when you think of first of all I'm playing a little just for the fun of it yeah and that devil's advocate and uh I I think our cognition our mind is unable to visualize so you do some incredible work with visualization and video I think infinity is very difficult to visualize for our mind we can delude ourselves into thinking we can visualize it but we can't I don't that means I don't I would venture to say it's very difficult and so there's some concepts of mathematics like maybe multiple dimensions we could sort of talk about that are impossible for us to truly into it like and it just feels dangerous to me to use these as part of our toolbox of abstractions on behalf of your listeners I almost fear we're getting too philosophical oh no I I think to that point for any particular idea like this there's multiple angles of attack I think the when we do visualize infinity what we're actually doing you know you write dot dot dot one two three four dot dot right that's those are symbols on the page that are insinuating a certain infinity what you're capturing with a little bit of design there is the I can always add one more property right I think I'm just as uncomfortable with you are if you try to concretize it so much that you have a bag of infinitely many things that I actually think of no not one two three four dot dot dot one two three four five six seven eight I try to get them all and I had and you realize oh I you know your your brain would literally collapse into a black hole all of that and and I honestly feel this with a lot of math that I tried to read where I I don't think of myself as like particularly good at math in some ways like I get very confused often when I am going through some of these texts and often when I'm feeling my head is like this is just so damn have strict I just can't wrap my head around I just wanted to put something concrete to it that makes me understand and I think a lot of the motivation for the channel is channeling that sentiment of yeah a lot of the things that you're trying to read out there it's just so hard to connect to anything that you spend an hour banging your head against a couple of pages and you come out not really knowing anything more other than some definitions maybe and a certain sense of self defeat right one of the reasons I focus so much on visualizations is that I'm a big believer in I'm sorry I'm just really hampering out this idea of abstraction being clear about your layers of abstraction yes right it's always tempting to start an explanation from the top to the bottom yeh you you give the definition of a new theorem you're like this is the definition of a vector space for example we're gonna that's how well start of course these are the properties of a vector space Yuma first from these properties we will derive what we need in order to do the math of linear algebra or whatever it might be I don't think that's how understanding works at all I think how understanding works is you start at the lowest level you can get it where rather than thinking about a vector space you might think of concrete vectors that are just lists of numbers or picturing it as like an arrow that you draw which is itself like even less abstract the numbers because you're looking at quantities like the distance of the x-coordinate the distance of the y-coordinate it's as concrete as you could possibly get and it has to be if you're putting it in a visual right like that it's an actual arrow it's an actual vector you're not talking about like a quote-unquote vector that could apply to any possible thing you have to choose one if you're illustrating it and I think this is the power of being in a medium like video or if you're writing a textbook and you force yourself to put a lot of images is with every image you're making a choice with each choice you're showing a concrete example with each concrete example you're eating someone's path to understanding you know I'm sorry to interrupt you but you just made me realize that that's exactly right so the visualization is you're creating while you're sometimes talking about abstractions the actual visualization is a explicit low-level example yes so there there's an actual like in the code you have to say what the what the vector is what's the direction of the arrow what's the magnitude of the yeah so that's you're going the visualization itself is actually going to the bottom I think and I think that's very important I also think about this a lot in writing scripts where even before you get to the visuals the first instinct is to I don't know why I just always do I say the abstract thing I say the general definition the powerful thing and then I fill it in with examples later always it will be more compelling and easier to understand when you flip that and instead you let someone's brain do the pattern recognition you just show them a bunch of examples the brain is gonna feel a certain similarity between them then by the time you bring in the definition or by the time you bring in the formula its articulating a thing that's already in the brain that was built off of looking at a bunch of examples with a certain kind of similarity and what the formula does is articulate what that kind of similarity is rather than being a high cognitive load set of symbols that needs to be populated with examples later on assuming someone still with you what is the most beautiful or on inspiring idea you've come across in mathematics I don't know maybe it's an ID you've explored in your videos maybe not what mike just gave you pause it's the most beautiful idea small or big so I think often the things that are most beautiful are the ones that you have like a little bit of understanding of but certainly not an entire understanding it's a little bit of that mystery that is what makes it beautiful almost a moment of the discovery for you personally almost just that leap of haha moment so something that really caught my eye I remember when I was little there were these I come I think the series was called like wooden books or something these tiny little books that would have just a very short description of something on the left and then a picture on the right I don't know who they're meant for but maybe it's like loosely children or something like that but it can't just be children because of some of the things I was describing on the last page of one of them some were tiny in there was this little formula the on the left hand had a sum over all of the natural numbers you know it's like 1 over 1 to the s plus 1 over 2 to the s plus 1 over 3 to the s on and on to the infinity then on the other side had a product over all of the primes and it was a certain thing I had to do with all the primes and like any good young math enthusiast I'd probably been indoctrinated with how chaotic and confusing the primes are which they are and seeing this equation where on one site you have something that's as understandable as you could possibly get the counting numbers yes and on the other side is all the prime numbers it was like this whoa they're related like this there's there's a simple description that includes like all the primes getting wrapped together this this is like the Euler product for zeta function as I like later found out the equation itself essentially encodes the fundamental theorem of arithmetic that every number can be expressed as a unique set of primes to me still there's I mean I certainly don't understand this equation or this function all that well the more I learn about it the prettier it is the idea that you can this is sort of what gets you representations of primes not in terms of Prime's themselves but in terms of another set of numbers they're like the non-trivial zeros of the zeta function and again I'm very kind of in over my head in a lot of ways as I like try to get to understand it but the more I do its it always leaves enough mystery that it remains very beautiful to me so whenever there's a little bit of mystery just outside of the understanding that and by the way the process of learning more about it how does that come about just your own thought or are you reading reading yes or is the visualization itself revealing more to you visuals help I mean in one time when I was just trying to understand like analytic continuation and playing around with visualizing complex functions this is what led to a video about this function it's titled something like visualizing the riemann zeta function it's one that came about because i was programming and tried to see what a certain thing looked like and then i looked at it like well that's elucidating and then i decided to make a video about it but i mean you try to get your hands on as much reading as you can you you know in this case i think if anyone wants to start to understand it if they have like a math background of some like they studied some in college or something like that like the princeton companion to math has a really good article on analytic number theory and that itself has a whole bunch of references and you know anything has more references and it gives you this like tree to start pawing through and like you know you try to understand I try to understand things visually as I go that's not always possible but it's very helpful when it does you recognize when there's common themes like in this case cousins of the Fourier transform I come into play and you realize oh it's probably pretty important to have deep intuitions of the fourier transform even if it's not explicitly mentioned in like these texts and you try to get a sense of what the common players are but I'll emphasize again like I feel very in over my head when I try to understand the exact relation between like the zeros of the Riemann zeta function and how they relate to the distribution of primes I definitely understand it better than I did a year ago I definitely understand it 1/100 as well as the experts on the matter do I assume but the slow path towards getting theirs it's fun it's charming and like to your question very beautiful and the beauty is in the what in the journey versus the destination well it's that each each thing doesn't feel arbitrary I think that's a big part is that you have these unpredictable none yeah these very unpredictable patterns were these intricate properties of like a certain function but at the same time it doesn't feel like humans ever made an arbitrary choice in studying this particular thing so you know it feels like you're speaking to patterns themselves or nature itself that's a big part of it I think things that are too arbitrary it's just hard for those to feel beautiful because and this is sort of what the word contrived is meant to apply to right and the one they're not arbitrary means it could be you can have a clean abstraction an intuition that allows you to comprehend it well to one of your first questions it makes you feel like if you came across another intelligent civilization that they'd be studying the same thing it may be with different notation but personally yeah but yeah like that's what I think you talk to that other civilization they're probably also studying the zeros of the Riemann zeta function or it's like some variant thereof that is like a clearly equivalent cousin or something like that but that's probably on their on their docket whenever somebody does a lot of something amazing I'm gonna ask the question that that you've already been asked a lot that you'll get more and more asked in your life but what was your favorite video to create Oh favorite to create one of my favorites is the title is who cares about topology you want me to pull it up or not if you want sure yeah it is about well it starts by describing an unsolved problem that still unsolved in math called the inscribed square problem you draw any loop and then you ask are there four points on that loop that make a square totally useless right this is not answering any physical questions it's mostly interesting that we can't answer that question and it seems like such a natural thing to ask now if you weaken it a little bit and you ask can you always find a rectangle you choose four points on this curve can you find a rectangle that's hard but it's doable and the path to it involves things like looking at a torus this surface with a single hole in it like a donut we're looking at a mobius strip in ways that feel so much less contrived to when I first as like a little kid learned about these surfaces and shapes like a mobius strip and a torus like what you learn is oh this mobius strip you take a piece of paper put a twist glue it together and now you have a shape with one edge and just one side and as a student you should think who cares right like how does that help me solve any problems I thought math was about problem solving so what I liked about the piece of math that this was describing that was in this paper by a mathematician named Vaughan was that it arises very naturally it's clear what it represents it's doing something it's not just playing with construction paper and the way that it solves the problem is really beautiful so kind of putting all of that down and concretizing it right like I was talking about how when you have to put visuals to it it demands that what's on screen is a very specific example of what you're describing the cut the construction here is very abstract in nature you describe this very abstract kind of surface in 3d space so then when I was finding myself in this case I wasn't programming I was using Grapher that's like built into OSX for the 3d stuff to draw that surface you realize oh man the topology argument is very non constructive I have to make a lot of you have to do a lot of extra work in order to make the surface show up but then once you see it it's quite pretty very satisfying to see a specific instance of it and you also feel like I've actually added something on top of what the original paper was doing that it shows something that's completely correct it's a very beautiful argument but you don't see what it looks like and I found something satisfying and seeing what it looked like that could only ever have come about from the forcing function of getting some kind of image on the screen to describe the thing I was talking abut your most weren't able to anticipate what its gonna look like I don't know idea I had no idea and it was wonderful right it was totally it looks like a Sydney Opera House or some sort of Frank Gehry design and it was you knew it was gonna be something and you can say various things about it like oh it it touches the curve itself it has a boundary that's this curve on the 2d plane it all sits above the plane but before you actually draw it so it's very unclear what the thing will look like and to see it it's very it's just pleasing right so that was that was fun to make very fun to share I hope that it has elucidated for some people out there where these constructs of topology come from that it's not arbitrary play with construction paper so that's I think this is good a good sort of example to talk a little bit about your process so you have you have a list of ideas so that sort of the the curse of having having an active and brilliant mind is I'm sure you have a list that's growing faster than you can utilize and but there's some sorting procedure depending on mood and interest and so on but okay so pick an idea then you have to try to write a narrative arc it's sort of how do I elucidate how how do I make this idea beautiful and clear and explain it and then there's a set of visualizations that'll be attached to it sort of you've talked about some of this before but sort of writing the story attaching the visualizations can you talk through interesting painful beautiful parts of that process well the most painful is if you've chosen a topic that you do want to do but then it's hard to think of I guess how to structure the script this is sort of where I have been on one for like the last two or three months and I think the ultimately the right resolution just like set it aside and instead do some other things where the script comes more naturally because you sort of don't want to overwork a narrative that the more you've thought about it the less you can empathize with the student who doesn't yet understand the thing you're trying to teach who is the judger in your head sort of the person the creature the essence that's saying this sucks er this is good and you mentioned kind of the student you're you're thinking about um what can you uh who is that what is that thing that's Chris that is the perfections that says this thing sucks you need to work on it in front of the two three months I don't know I think it's my past self I think that's the entity that I'm most trying to empathize with is like you take who I was because it's kind of the only person I know like you don't really know anyone other than versions of yourself so I start with the version of myself that I know who doesn't yet understand the thing right and then I just try to view it with fresh eyes a particular visual or a particular script like is this motivating does this make sense which has its downsides because sometimes I find myself speaking to motivations that only myself would be interested in I don't like it I did this project on quaternions where what I really wanted was to understand what are they doing in four dimensions can we see what they're doing in four dimensions right and I can way of thinking about it that really answered the question in my head that maybe very satisfied and being able to think about concretely with a 3d visual what are they doing to a 4d sphere and some like great this is exactly what my past self would have wanted right and I make a thing on it and I'm sure it's what some other people wanted to it but in hindsight I think most people who want to learn about quaternions are like robotics engineers or graphics programmers who want to understand how they're used to describe 3d rotations and like their use case was actually a little bit different than my past self and in that way like I wouldn't actually recommend that video to people who are coming at it from that angle of wanting to know hey I'm a robotics program or like how do these quarter neon things work to describe position in 3d space I would say other great resources for that if you ever find yourself wanting to say but hang on in what sense are they acting in four dimensions then come back but until then it's a little different yeah it's interesting because so you have incredible videos on your networks for example and for my certain perspectives have probably I mean I looked at the is served my field and I've also looked at the basic introduction of neural networks like a million times from different perspectives and it made me realize that there's a lot of ways to present it so you were sort of you did an incredible job I mean sort of the but you could also do it differently and also incredible like to create a beautiful presentation of a basic concept is requires sort of creativity requires genius and so on but you can take it from a bunch of different perspectives in that video and you'll know which mean you realize that and just as you're saying you kind of have a certain mindset a certain view but from if you take a different view from a physics perspective from a neuroscience perspective talking about neural networks or from robotics perspective or from let's see from a pure learning statistics perspective so you you can create totally different videos and you've done that with a few actually concepts where you've have taken different costs like at the at the at the Euler equation right the you've taken different views of that I think I've made three videos on it and I definitely will make at least one more never enough never enough so you don't think it's the most beautiful equation in mathematics no like I said as we represent it it's one of the most hideous it involves a lot of the most hideous aspects of our notation I talked about II the fact that we use PI instead of tau the fact that we call imaginary numbers imaginary and then and actually wonder if we use the I because of imaginary I don't know if that's historically accurate but at least a lot of people they read the eye and they think imaginary like all three of those facts it's like those are things that have added more confusion than they needed to and we're wrapping them up in one equation like boy that's just very hideous right the idea is that it does tie together when you want away the notation look it's okay it's pretty it's nice but it's not like mind-blowing greatest thing in the universe which is maybe what I was thinking of when I said like once you understand something it doesn't have the same beauty like I feel like I understand Euler's formula and I feel like I understand it enough to sort of see the version that just woke up it hasn't really gotten itself dressed in the morning that's a little bit groggy and there's bags under its eyes so years like it's their past yeah the the the dating stage you know we're no longer dating right instead of dating Bizet des function this head like she's beautiful and right and like we have fun and it's that that high dopamine part for like maybe at some point will settle into the more mundane nature the relationship where I like see her for who she truly is and she'll still be beautiful in her own way but it won't have the same romantic pizzazz right well that's the nice thing about mathematics I think as long as you don't live forever there will always be enough mystery and fun with some of the equations even if you do the rate at which questions comes up is much faster than the rate at which answers come up so if you could live forever would you I think so yeah do you think you don't think mortality is the thing that makes life meaningful would your life be four times as meaningful if you died at 25 so this goes to infinity I think you and I that's really interesting so what I said is infinite not not four times longer mm-hmm I said infinite so the the actual existence of the finiteness the existence of the end no matter the length is the thing that may sort of from my comprehension of psychology it's such a deeply human it's such a fundamental part of the human condition the fact that there is that we're mortal that the the fact that things and they see it seems to be a crucial part of what gives them meaning I don't think at least for me like it's a very small percentage of my time that mortality is salient that I'm like aware of the end of my life what do you mean by me I'm trolling is it the ego is that the aid there's that the super-ego is a so you're the reflective self the Verna Keys area that puts all this stuff into words yeah a small percentage of your mind that is actually aware of the true motivations that drive you but my point is that most of my life I'm not thinking about death but I still feel very motivated to like make things and to like interact with people like experienced love or things like that I'm very motivated and I it's strange that that motivation comes while death is not in my mind at all and this might just be because I'm young enough that it's not salient force in your subconscious or that you were instructed an illusion that allows you to escape the fact of your mortality by enjoying the moment so to the existential approach life would be gun to my head I don't think that's it yeah another another sort of would say gun to the head it's the deep psychological introspection of what drives us I mean that's uh in some ways to me I mean when I look at math when I look at science is the kind of an escape from reality in a sense that it's so beautiful it's such a beautiful journey of discovery that it allows you to actually is it allows you to achieve a kind of immortality of explore ideas and sort of connect yourself to the thing that is seemingly infinite like the universe right that allows you to escape the the limited nature of our little of our bodies of our existence what else would give this podcast meaning that's right if not the fact that it will end this place closes in in 40 minutes and it's so much more meaningful for it how much more I love this room because we'll be kicked out so I understand just because you're trolling me doesn't mean I'm wrong but I take your point I take your point boy that would be a good Twitter bio just because you're trolling me doesn't mean I'm wrong yeah and and sort of difference in backgrounds I'm a bit Russian so we're a bit melancholic and it seemed to maybe assign a little too much value just suffering immortality and things like that make makes for a better novel I think oh yeah you need you need some sort of existential threat yeah to drive a plot so when do you know when the video is done when you're working on it that's pretty easy actually because I'm you know I'll write the script I want there to be some kind of aha moment in there and then hopefully the script can revolve around some kind of aha moment and then from there you know you're putting visuals to each sentence that exists and then you narrate it you edit it all together so given that there's a script the the end becomes quite clear and you know you're as I as I animated I often change the certainly the specific words but sometimes the structure itself but it's a very deterministic process at that point it makes it much easier to predict when something will be done how do you know when a script is done it's like for problem-solving videos that's quite simple it's it's once you feel like someone who didn't understand the solution now could for things like neural networks that was a lot harder because like you said there's so many angles at which you could attack it and there it's it's just at some point you feel like this this asks a meaningful question and it answers that question right what is the best way to learn math for people who might be at the beginning of that journey I think that's a it's a question that a lot of folks kind of ask and think about and it doesn't even for folks who are not really at the beginning of their journey like there might be actually is deep in their career some type they've taken college a taking calculus and so on but still wanna sort of explore math well what would be your advice instead of education at all ages your temptation will be to spend more time like watching lectures or reading try to force yourself to do more problems than you naturally would that's a big one like the the focus time that you're spending should be on like solving specific problems and seek entities that have well curated lists of problems so go into like a textbook almost in and the problems in the back of a text and back of a chapter so if you can take a little look through those questions at the end of the chapter before you read the chapter a lot of them won't make sense some of them might and those are those are the best ones to think about a lot of them won't but just you know take a quick look and then read a little bit of the chapter and maybe take a look again and things like that and don't consider yourself done with the chapter until you've actually worked through a couple exercises right and and this is so hypocritical right because I like put out videos that pretty much never have associated exercises I just view myself as a different part of the ecosystem which means I'm kind of admitting that you're not really learning or at least this is only a partial part of the learning process if you're watching these videos I think if someone's at the very beginning like I do think Khan Academy does a good job they have a pretty large set of questions you can work through just a very basic sort of just picking picking out getting getting comfortable is a very basically algebra calculus fun Khan Academy programming is actually I think a great like learned to program and like let the way the math is motivated from that angle push you through I know a lot of people who didn't like math got into programming in some way and that's what turned them on to math maybe I'm biased cuz like I live in the Bay Area so I'm more likely to run into someone who has that phenotype but I am willing to speculate that that is a more generalizable path so you yourself kind of in creating the videos are using programming to illuminate a concept but for yourself as well so would you recommend somebody try to make a sort of almost like try to make videos like you do what's the one thing I've heard before I don't know if this is based on any actual study this might be like a total fictional anecdote of numbers but it rings in the mind as being true you remember about 10 percent of what you read you remember about 20% of what you listen to remember about 70% of what you actively interact with in some way and then about 90% of what you teach this is a thing I heard again those numbers might be meaningless but they bring true don't they right I'm willing to say I learned the nine times better than reading that might even be a lowball yeah right so so doing something to teach or to like actively try to explain things is huge for consolidating the knowledge outside of family and friends is there a moment you can remember that you would like to relive because it made you truly happy or it was transformative in some fundamental way a moment that was transformed or made you truly happy yeah I think there's times like music used to be a much bigger part of my life than it is now like when I was a let's say a teenager and I can think of sometimes in like playing music there was one way at my command my brother and a friend of mine this slightly violates the family and friends but there was a music that made me happy they were just company um we like played a gig at a ski resort such that you like take a gondola to the top and like did a thing then on the gondola ride down we decided to just jam a little bit and it was just like I don't know the the gondola sort of over came over a mountain and you saw the the city lights and were just like jamming like playing some music I wouldn't describe that nice transformative I don't know why but that popped into my mind as a moment of in a way that wasn't associated with people I love but more with like a thing I was doing something that was just it was just happy and it was just like it a great moment I don't think I can give you anything deeper than that though well as a musician myself I'd love to see as you mentioned before music enter back into your work and back into your creative work I'd love to see that I'm certainly allowing you to enter back into mine and it's it's a it's a beautiful thing for mathematician for scientists to allow music to enter their work I think only good things can happen all right I'll try to promise you a music video by 2021 but by 20 by the end of 2020 I give myself a longer window all right maybe we can like collaborate on a band type situation what instruments do you play the main instrument I play is violin but I also love to devil around on like guitar and piano for me to eat our own piano so in in a mathematicians limit Paul Lockhart writes the first thing to understand is that mathematics is an art the difference between math and the other arts such as music and painting is that our culture does not recognize it as such so I think I speak for millions of people myself included in saying thank you for revealing to us the art of mathematics so thank you for everything you do and thanks for talking today well thanks for saying that and thanks for having me on thanks for listening to this conversation of grants Anderson and thank you to our presenting sponsor cash app downloaded use code Lex podcasts you'll get ten dollars and $10 will go to first a stem education nonprofit inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from one of grants and my favorite people Richard Fineman nobody ever figures out what this life is all about and it doesn't matter explore the world nearly everything is really interesting if you go into it deeply enough thank you for listening and hope to see you next time you |
Stephen Kotkin: Stalin, Putin, and the Nature of Power | Lex Fridman Podcast #63 | the following is a conversation with Steven Kotkin a professor of history at Princeton University and one of the great historians of our time specializing in Russian and Soviet history he has written many books on Stalin in the Soviet Union including the first to of a three-volume work on Stalin and he's currently working on volume three he may have noticed that I've been speaking with not just computer scientists but physicists engineers historians neuroscientists and soon much more to me artificial intelligence is much bigger than deep learning bigger than computing it is our civilizations journey into understanding the human mind and creating echoes of it in the machine to me that journey must include a deep historical and psychological understanding of power technology puts some of the greatest power in the history of our civilization into the hands of engineers and computer scientists this power must not be abused and the best way to understand how such abuse can be avoided is to not be blind to the lessons of history as Steven kotkin brilliantly articulates Stalin was arguably one of the most powerful humans in history I've read many books on Joseph Stalin Vladimir Putin and the wars the 20th century I hope you understand the value of such knowledge to all of us especially to engineers and scientists who build the tools of power in the 21st century this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify support on patreon or simply connect with me on Twitter at lex friedman spelled fri d ma n i recently started doing ads at the end of the introduction i'll do one or two minutes after introducing the episode and never any ads in the middle they can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cache app the number one finance app in the App Store I personally use cache app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has an investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokers services are provided by cash up investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and Charity Navigator which means the donated money is used to maximum effectiveness when you get cash app from the App Store Google Play and use coal xpod gas you'll get $10 and cash app will also donate $10 to 1st which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation stephen Kotkin do all human beings crave power no human beings crave security they crave love they crave adventure they crave power but not equally some human beings nevertheless do crave power for sure what words is that deeply in the psychology of people is it something you're born with is it something you develop some people crave a position of leadership or of standing out of being recognized and that could be starting out in the school years on the schoolyard it could be within their own family not just in their peer group those kind of people we often see craving leadership positions from a young age often end up in positions of power but they can be varied positions of power you can have power in an institution where your power is purposefully limited for example there's a board or a consultative body or a separation of powers not everyone craves power whereby they're the sole power or there they're unconstrained power that's a little bit less usual we may think that everybody does but not everybody does those people who do crave that kind of power unconstrained the ability to decide as much as life or death of other people most people are not everyday people they're not the people you encounter in your daily life for the most part those are extraordinary people most of them don't have the opportunity to live that dream very few of them in fact end up with the opportunity to live that dream so percentage-wise in your sense if we think of George Washington for example most would most people given the choice of absolute power over a country versus maybe the capped power that the United States president presidential role at least at the founding of the country represented what do you think most people would choose well Washington was in a position to exercise far greater power than he did and in fact he didn't take that option he was more interested in seeing institutionalization of seeing the country develop strong institutions rather than an individual leader like himself have excess power so that's very important so like I said not everyone craves unconstrained power even if they're very ambitious and of course Washington was very ambitious he was a successful general before he was a president so that clearly comes from the influences on your life where you grow up how you grow up how you raised what kind of values are imparted to you along the way you can understand power as the ability to share or you can understand or the ability to advance something for the collective in a collective process not an individual process so power comes in many different varieties and ambition doesn't always equate to despotic power the spotted power is something different from ordinary institutional power that we see right the president of MIT does not have unconstrained power the president of MIT rightly must consult with other members of the administration with the faculty members to a certain extent with the student body and certainly with the trustees of MIT those constraints are make the institution strong and enduring and make the decisions better than they would be if he had unconstrained power but you can't say that the president is not ambitious of course the president is ambitious we worry about unconstrained power we worry about executive authority that's not limited that's the definition of authoritarianism or tyranny unlimited or barely limited executive authority executive authority is necessary to carry out many functions we all understand that that's why MIT has an executive has a president but unlimited or largely unconstrained executive power is detrimental to even the person who exercises that power so what do you think it's an interesting notion we kind of take it for granted that constraints on executive power is a good thing but why is that necessarily true so what is it about absolute power that does something bad to the human mind so you know the popular saying of absolute power corrupts absolutely is that the case that the power in itself is the thing that corrupts the mind in some kind of way where it leads to a bad leadership over time people make more mistakes when they're not challenged when they don't have to explain things and get others to vote and go along with it when they can make a decision without anybody being able to block their decision or to have input necessarily on their decision you're more prone to mistakes you're more prone to extremism there's a temptation there for example we have separation of powers in the United States the Congress right has Authority that the president doesn't have as for example in budgeting the so-called power of the purse this can be very frustrating people want to see things happen and they complained that there's a do-nothing Congress or that the situation is stalemated but actually that's potentially a good thing in fact that's how our system was designed our system was designed to prevent things happening in government and there's frustration with that but ultimately that's the strength of the institutions we have and so when you see unconstrained executive authority there can be a lot of dynamism a lot of things can get done quickly but those things can be like for example what happened in China under Mao or what happened in the Soviet Union under Stalin or what happened in Haiti on the Papa Doc and then baby doc or fill in the blank right what happens sometimes in corporations where a corporate leader is not constrained by the shareholders by the board or by anything and they can seem to be a genius for a while but eventually it catches up to them and so the idea of constraints on executive power is absolutely fundamental to the American system American way of thinking and not only America obviously large other parts of the world that have a similar system not an identical system but a similar system of checks and balances on executive power and so the the the case that I study the only checks and balances on executive power are circumstantial so for example distances in the country it's hard to do something over 5,000 miles or the amount of time in a day it's hard for a leader to get to every single thing the leader wants to get to because there are only 24 hours in a day those are circumstantial constraints on executive power they're not institutional constraints on executive power one of the constraints on executive power the United States has versus Russia maybe something you've implied and actually spoke directly to is there's something in the Russian people in the Soviet people they're attracted to authoritarian power psychologically speaking or at least the kind of leaders at that sought authority and power throughout its history and that desire for that kind of human is a lack of a constraint in America it seems as people we desire somebody not like Stalin somebody more like George Washington so that's another constraint of the belief the people would they admire in a leader what they seek in a leader so maybe you can speak to well first of all can you speak briefly to that psychology of is there a difference between the Russian people and the American people in terms of just what we find attractive in a leader not as great a difference as it might seem there are unfortunately many Americans who would be happy with an authoritarian leader in the country is by no means a majority it's not even a plurality but nonetheless it's a real sentiment in the population sometimes because they feel frustrated because things are not getting done sometimes because they're against something that's happening in the political realm and they feel it has to be corrected and corrected quickly it's a kind of impulse people can regret the impulse later on the impulse is motivated by reaction to their environment in the Russian case we have also people who crave sometimes known as a strong hand and iron hand and authoritarian leader because they want things to be done and be done more quickly that align with their desires what I'm not sure it's a majority in the country today certainly in Stalin's time this was a widespread sentiment and people had few alternatives that they understood or could appeal to nowadays in the globalized world the citizens of Russia can see how other systems have constraints on executive power in the life isn't so bad there in fact a life might even be better so the impatience the impulsive quality the frustration does sometimes in people reinforce their craving for the unconstrained executive to quote get things done or shake things up or yes that's true but in the Russian case I'm not sure it's cultural today I think it might be more having to do with the failures the functional failures of the kind of political system that they tried to institute after the Soviet collapse and so it may be frustration with the version of constraints on executive power they got and how it didn't work the way it was imagined which has led to a sense in which non constrained executive power could fix things what like like I'm not sure that that's the majority sentiment in the Russian case although it's hard to measure because under authoritarian regimes public opinion is shaped by the environments in which people live which is very constrained in terms of public opinion but on that point why at least from a distance desert seem to nevertheless be support for the current Russian President Vladimir Putin is that have to do with the fact that measuring getting good metrics and statistics on support is difficult know that Aryan governments or is there still something appealing to that kind of power to the people I think we have to give credit to President Putin for understanding the psychology of the Russians who to whom he appeals many of them were the losers in the transition from communism they were the ones whose pensions were destroyed by inflation or whose salaries didn't go up or whose regions were abandoned they were not the winners for the most part and so I think there's an understanding on his part of their psychology Putin has grown in the position he was not a public politician when he first started out he was quite poor in public settings he didn't have the kind of political instincts that he has now he didn't have the appeal to traditional values in the Orthodox Church and some of the other dimensions of his rule today so yes we have to give some credit to Putin himself for this in addition to the frustrations and the mass of the people but let's think about it this way in addition without taking away the fact that he's become a better politician over time and that sentiment has shifted because of the disappointments with the transition with the population when I asked my kids am I a good dad my kids don't have any other dad to measure me against I'm the only dad they know and I'm the only dad they can choose or not choose they think if they don't choose me they still get me as dad right so with Putin today he's the only dad that the Russian people have now if my kids were introduced to alternative fathers they might be better than me they might be more loving more giving funnier richer whatever it might be they might be more appealing there are some blood ties there for sure with that I have with my kids but they would at least be able to choose alternatives and then I would have to win their favor in that constellation of alternatives if President Putin were up against real alternatives if the population had real choice and that choice could express itself and have resources and have media and everything else the way he does maybe he would be very popular and maybe his popularity would not be as great as it currently is so the absence of alternatives is another factor that reinforces his authority and his popularity having said that there are many authoritarian leaders who deny any alternatives to the population and are not very popular so denial of alternatives doesn't guarantee you the popularity you still have to figure out the mass psychology and be able to appeal to it so with with the in the Russian case the winners from the transition live primarily in the big cities and our self employed or intrapreneurial even if they're not self employed there they're able to change careers they have tremendous skills and talent and education and knowledge as well as these entrepreneurial or dynamic personalities Putin also appealed to them he did that with Medvedev and it was a very clever ruse he himself appealed to the losers from the transition the small towns the rural the people who were not well-off and he had them for the most part not all we don't want to generalize to say that he had every one of them because those people have views of their own sometimes in contradiction with the President of Russia and then he appealed to the opposite people the successful urban base through the so-called reformer with the idea of the new generation the technically literate prime minister who for a time was president and so that worked very successfully for Putin he was able to bridge a big divide in the society and gain a greater mass support than he would otherwise have had by himself that ruse only worked through the time that Medvedev was temporarily president for a few years because of the Constitution Putin couldn't do three consecutive terms and stepped aside in what they call castling in chess this when this was over Putin had difficulty with his popularity there were mass protests in the urban areas precisely that group of the population that he had been able to win in part because of the Medvedev castling and now had had their delusions exposed and were disillusioned and there were these mass protests in the urban areas not just in the cap by the way and Putin had to as it were come up with a new way to fix his popularity which happened to be the annexation of Crimea from which he got a very significant bump however he the trend is back in the other direction it's diminishing again although it's still high relative to other leaders around the world so I wouldn't say that he's unpopular with mass in Russia he there is some popularity there there is some success but I would say it's tough for us to gauge because of the lack of alternatives and Putin is unpopular inside the State Administration at every level deeper accuracy of because no simple are well informed and they understand that the country is declining that the human capital is declining the infrastructure is declining the economy is not really growing it's not really diversifying Russia's not investing in its future the state officials understand all of that and then they see that the Putin cleek is stealing everything in sight so between the failure to invest in a future and the corruption of a narrow group around the president there's disillusionment in the state apparatus because they see this more clearly or more closely than the mass of the population they can't necessarily yet oppose this in public because there are people they have families they have careers they have children who want to go to school or want a job and so there are constraints on their ability to oppose the regime based upon what we might call cowardice or other people might call realism I don't know how courageous people can be when their family children career are on the line so it's very interesting dynamic to see the disillusionment inside the government with the president which is not yet fully public for the but could become public and once again if there's an alternative if an alternative appears things could shift quickly and that alternative could come from inside the regime from inside the regime but the leadership the the party the people that are now as you're saying opposed to Putin they're nevertheless maybe you can correct me but it feels like there's structural he's deeply corrupt so each of each of the people we're talking about our and don't feel like a George Washington once again the circumstances don't permit them to act that way necessarily right George Washington did great things but in certain circumstances a lot of the state officials in Russia for certain are corrupt there's no question many of them however are patriotic and many of them feel badly about where the country has been going they would prefer that the country was less corrupt they would prefer that there were greater investment in all sorts of areas of Russia they might even themselves steal less if they could be guaranteed that everybody else would steal less there's a deep and abiding patriotism inside Russia as well as inside the Russian regime so they understand that Putin in many ways rescued the Russian state from the chaos of the 1990s they understand that Russia was in very bad shape as an incoherent failing state almost when Putin took over and that he did some important things for Russia's stability and consolidation there's also some appreciation that Putin stood up to the West and stood up to more powerful countries and regained a sense of pride and maneuverability for Russia in the international system people appreciate that and it's real it's not imagined that Putin accomplished that the problem is the methods that he accomplished it with he used the kind of methods that is the same taking other people's property putting other people in jail for political reasons he used the kind of methods that are not conducive to long-term growth and stability so he fixed the problem but he fixed the problem and then created even bigger long-term problems potentially and moreover all authoritarian regimes that use those methods are tempted to keep using them and using them and using them until they're the only ones who are the beneficiaries and the group narrows and narrows the elite gets smaller and narrower the interest groups get excluded from power and their ability to continue enjoying the fruits of the system and the resentment grows and so that's the situation we have in Russia is a place that is stuck it was to a certain extent rescued it was rescued with methods that were not conducive to long-term success and stability the rescue referring to is this of the economic growth when Putin first tests took office they had 10 years they had a full decade of an average of 7% growth a year which was phenomenal and is not attributable predominantly to oil prices during president Putin's first term as president the average price of oil was $35 a barrel during his second term as president the average price was $70 a barrel so during those two terms when Russia was growing at about 7% a year oil prices were averaging somewhere around $50 a barrel which is fine but is not the reason because later on when oil prices were over $100 a barrel Russia stagnated so the initial growth do you think Putin deserves some credit for that yes he does because he introduced some important liberalizing measures he lowered taxes he allowed land to be bought and sold he deregulated many areas of the economy and so there was a kind of intrapreneurial burst that were that was partly attributable partly attributable to government policy during his first term but also he was consolidating political power and as I said the methods he used overall for the long term were not able to continue sustain that success in addition we have to remember that China played a really big role in the success of Russia in the first two terms of Putin's presidency because China's phenomenal growth created insatiable demand for just about everything that the Soviet Union used to produce so fertilizers cement fill-in-the-blank chemicals metals China had insatiable demand for everything the Soviet Union once produced and so China's global raising of global demand overall brought soviet-era industry back from the dead and so there was something that happened Soviet era industry fell off a cliff in the 1990s there was a decline in manufacturing and industrial production greater than in the great depression in the US but a lot of that came back online in the 2000s and that had to do with China's phenomenal growth the trade between China and Russia was not always direct so this was an indirect effect but raising global prices for the commodities and the products the kind of lower and lower value products in manufacturing not high-end stuff but lower and stuff like steel or iron or cement or fertilizer where the value-added is not but nonetheless which had been destroyed by the 1990s and after the Soviet collapse this was brought back to life now you can do that once you can bring Soviet era industry back to life once and that happened during Putin's first two terms in addition to the liberalizing policies which spurred intrapreneurial ISM and some small and medium business the crash of the ruble in 1998 which made Russian products much cheaper abroad and made imports much more expensive also facilitated the resuscitation the revival of domestic manufacturing so all of this came together for that spectacular 10-year seven percent on average economic growth and moreover people's wages after inflation their disposable income grew more even than GDP grew so disposable income after inflation that is a real income was growing greater than seven percent in some cases ten percent a year so there was a boom and the Russian people felt it and it happened during Putin's first two terms and people were grateful rightly so for that and those who don't want to give Putin credit give oil prices all the credits but I don't think that oil prices can explain this having said that that doesn't mean that this was sustainable over the long term so you've briefly mentioned sort of implying the possibility Stalin held power for let's say thirty years you briefly mentioned that as a question will Putin be able to beat that record to beat that so can you talk about your sense of is it possible that Putin holds power for that kind of duration let's hope not let's hope not for Russia's sake the primary victims of president Putin's power are Russians they're not Ukrainians although to a certain extent Ukraine has suffered because of Putin's actions and they're not Americans they're Russians moreover Russia has lost a great deal of human talent yes millions and millions of people have left Russia since 1991 overall somewhere between five and ten million people have left the country and are beyond the borders of the former Soviet Union so they left the Soviets base entirely moreover the people who left are not the poor people they're not the uneducated they're not the losers the people who've left are the more dynamic parts of the population the better educated the more entrepreneurial so that human capital lost that Russia has suffered is phenomenal and in fact right here we were sitting at MIT we have examples of people who are qualified good enough for MIT and have left Russia to come to MIT you're looking at one of them and the other aspect just to quickly comment is those same people like me I'm not welcome back no you're not under the current regime it was a big loss for Russia if you're patriotic but not from the point of view of the Putin regime that has to do also factors into popularity if the people who don't like you leave they're not there to complain to protest to vote against you and so your your opposition declines when you let them leave however it's very costly in human capital terms hemorrhaging that much human capital is damaging its self damaging and we've seen it accelerate it was already high but we've seen it accelerate in the last oh seven eight years of President Putin's rule and those people are not going back of their own volition but even if they wanted to go back as you just said they'd be unwelcome that's a big cost to pay for this regime and so whatever benefits this regime might or might not have given to the country the disadvantage is the downside the costs are also really high so we don't want Putin lasting in power as long as Stalin it would be better if Russia were able to choose among options to choose a new leader among options many people speculate that President Putin will name a successor the way Yeltsin named Putin as his successor Boris president Boris Yeltsin and then Putin will leave the stage and allow the successor to take over that might seem like a good solution but once again we don't need a system where you hang on for as long as possible then nominate who's gonna take over we need a system that has the kind of corrective mechanisms that democracies and markets have along with rule of law a corrective mechanism is really important because all leaders make mistakes but when you can't correct for the mistakes then the mistakes get compounded a Putin could well he seems to be healthy he could well last as many years of Stalin it's hard to predict because events intercede sometimes and create circumstances that are unforeseen and leaders get overthrown or have a heart attack or whatever there's a palace insurrection we're ambitious leaders on the inside for both personal power and patriotic reasons try to push aside an aging leader there are many scenarios in which Putin could not last that long but unfortunately right now you could also imagine potentially him lasting that long which as I said is not an outcome if you're patriotic about Russia is not an outcome you would wish up to the country is that I guess a very difficult question but what what practically do you feel is a way out of the Putin regime as a way out of the corruption that's deeply underlies the the state is a if you look from a history perspective as a revolution required is some his violence required is in you know from a violence within or external to the country do you see or origin as a powerful is a inspiring leader enough to step in and bring democracy and kind of the free world to Russia so Russia is not a failed country it's a middle-income country with the tremendous potential and has proven many times in the past that when it gets in a bad way it can reverse its trajectory moreover violence is rarely ever a solution violence rarely it may break an existing trend but it's rare that violence produces a non-violent sustainable positive outcome it happens but it doesn't happen frequently societal upheaval is not a way always to institutionalize a better path forward because you need institutions people can protest as they did throughout the Middle East and the protests didn't necessarily lead to better systems because the step from protests to new strong consolidated institutions is a colossal leap not a small step what we need and what we see from history and situations like this is a group within the power structures which is a patriotic that sees things going down and that is to say that sees things not be developing relative to neighbors relative to richer countries relative to more successful countries and they want to change the trajectory of Russia and if they can in a coalition fashion unseat the current regime for a new power sharing arrangement which once again can be frustrating because you can't do changes immediately you can't do things overnight but that's the point constraints on your ability to change everything immediately and to force change overnight is what leads to long-term success potentially right that's the sustainability of change so Russia needs stronger institutions it needs court system as well as democratic institutions it needs functioning open dynamic markets rather than monopolies it needs meritocracy and banks to award loans on the basis of business plans not on the basis of political criteria or corrupt bribery or whatever it might be right so Russia needs those kind of functioning institutions that take time are sometimes slow don't lead to revolutionary transformation but lead to potentially long term sustainable growth without upheaval without violence without getting into a situation where all of a sudden you need a miracle again every time Russia seems to need a miracle and that's the problem the the solution would be not needing a miracle now having said that the potential is there the civilization that we call Russia's amazingly impressive it has delivered world-class culture world-class science it's a great power it's not a great power with a strong base right now but nonetheless it is a great power is a tax in the world so I wouldn't underestimate Russia's abilities here and I wouldn't write-off Russia I don't see it under the current regime a renewal of the country but if we can have from within the regime and evolution rather than a revolution in a positive direction and maybe get a George Washington figure who is strong enough to push through institutionalization rather than personalism so if I could ask about one particular individual maybe just interesting to get your comment but also as a representative of potential leaders I just on the spot has talked to Gary Kasparov who I'm not sure if you're familiar with his his ongoings so besides being a world-class chess player he's also a very outspoken activist sort of seeing Putin truly seeing Putin as an enemy of the free world of democracy of balanced government in Russia what do you think of people like him specifically or just people like him trying as leaders to step in to run for president to to symbolize a new chapter in Russia's future so we don't need individuals some individuals are very impressive and they have courage and they protest and they criticize and they organize we need institutions we need a Duma or a parliament that functions we need a court system that functions that is to say where there are a separation of powers impartial professional civil service impartial professional judiciary those are the things Russia needs it's rare that you get that from an individual no matter how impressive right we had Andrei Sakharov who was an extraordinary individual who developed the hydrogen bomb under Soviet regime was a world-class physicist was then upset about how his scientific knowledge and scientific achievements were being put to use and rebelled to try to put limits constraints civilizing you main limits and constrained on some of the implications of his extraordinary science but Sakharov even if he had become the leader of the country which he did not become he was more of a moral or spiritual leader it still wouldn't have given you a judiciary it still wouldn't have given you a civil service it still wouldn't have given you a Duma or functioning Parliament you need a leader in coalition with other leaders you need a bunch of leaders a whole group and they have to be divided a little bit so that not one of them can destroy all the others and they have to be interested in creating institutions not just or not solely or predominantly in their personal power and so I have no objection to outstanding individuals and to the work that they do but I think in institutional terms and they need to think that way too in order to be successful so if we go back to the echoes of that after the Russian Revolution was Stalin or Lenin Stalin maybe you can correct me but there was a group of people there in that same kind of way looking to establish institutions that were built in a you know in a beautifully built around an ideology that they believed is good for the world so sort of echoing that idea of what we're talking about what Russia needs now can you first of all you've described a fascinating thought which is Stalin as having amassed arguably more power than any man in history she's interesting thing to think about but can you tell about his journey to getting that power after the Russian Revolution how does that perhaps echo to the our current discussion about institutions and so on and just in general the story I think is fascinating of how one man is able to get more power than any other man in history it is a great story not necessarily from a moral point of view but if you're interested in power for sure it's an incredible story so we have to remember that Stalin is also a product of circumstances not solely his own individual Drive which is very strong but for example World War one breaks the Czarist regime the Czarist order Imperial Russia in the state Stalin has no participation whatsoever in World War one he spends World War one in exile in Siberia until the downfall of the Czarist autocracy in February 1917 Stalin is in eastern Siberian exile he's only able to leave eastern Siberia when that regime Falls he never fights in the war he's called up briefly towards the end of the war and is disqualified on physical grounds because of physical deformities from being drafted the war continues after the Czar's regime has been toppled in the capital and there's been a revolution the war continues and that war is very radicalizing the peasants begin to seize the land after the Tsar Falls essentially destroying much of the gentry class Stalin has nothing to do with that the peasants have their own revolution seizing the land not in law but in fact de facto not desert land ownership so there are these really large processes underway that Stalin is alive during but not a driver of the most improbable thing happens which is a very small group of people around the the figure of Vladimir Lenin announces that had in a seized power now by this time in October 1917 the government that has replaced the Tsar the soap visional government has failed and so there's not so much power to seize from the provisional government what Lenin does is he does a coup on the left that is to say Soviets or councils as we would call them in English which represent people's power or the masses participating in politics a kind of radical grassroots democracy are extremely popular all over the country and not dominated by any one group but predominantly socialist or predominantly leftist Russia has an election during the war a free and fair election for the most part despite the war at the end of 1917 in December 1917 and 3/4 plus of the country votes socialist in some form or another so the battle was over the definition of socialism and who had the right to participate in defining socialism not only what it would be but who had the right to decide so there's a coup by Lenin's group known as the Bolsheviks against all the other socialists and so Lenin declares a seizure of power whereby the old government has failed people's power the council's known as the Soviets are gonna take their place and Lenin seizes power in the name of the Soviet so it's a coup against the left against the rest of the left not against the provisional government that has replaced the Tsar which has already failed and so Stalin is able to come to power along with Lenin in this crazy seizure of power on the left against the rest of the left in October 1917 which we know is the October Revolution and I call the October coup as many other historians call the October Revolution happened after the seizure of power what's interesting about this episode is that the leftists who seize power in the name of the Soviets in the name of the masses in the name of people's power they retain their hold many times in history there's a seizure of power by the left and they fail they collapse they're cleaned out by an army or what we call forces of order by counter revolutionary forces Lenin's Revolution Lenin's coup is successful it is able to hold power and not just seize power they win a civil war and they're entrenched in the heart of the country already by 1921 Stalin is part of that group Lenin needs somebody to run this new regime in the kind of nitty-gritty way Lenin is the leader the undisputed leader in the Bolshevik Party which changes their name to communists in 1918 he makes Stalin the General Secretary of the Communist Party he creates a new position which hadn't existed before a kind of day-to-day political manager a right-hand man not because Lenin is looking to replace himself he's looking to institutionalize a helpmate a right-hand man he does this in the spring of 1920 to stall and his name to this position which Lenin has created expressly for Stalin so there has been a coup on the Left where by the Bolsheviks who become communists have seized power against the rest of the socialists and anarchists and the entire left and then there's an institutionalization of a position known as General Secretary of the Communist Party right-hand man of Lenin less than six weeks after Lenin has created this position and installed Stalin Lenin has a stroke and a major stroke really returns as a full actor to power before he dies of a fourth stroke in January 1924 so a position is created for Stalin to run things on Lenin's behalf and then Lenin has a stroke and so Stalin now has this new position general secretary but he's the right hand of a person who's no longer exercising day-to-day control over affairs Stalin then uses this new position to create a personal dictatorship inside the Bolshevik dictatorship which is the remarkable story I tried to tell so is there anything nefarious about any of what you just described so it seems conveniently that the positions created just for Stalin there was a few other brilliant people arguably more brilliant than Stalin in the vicinity of Lenin why was Stalin chosen why did Lenin all of a sudden fall ill as perhaps a conspiratorial question but is there anything nefarious about any of this historical trajectory to power that Stalin took in creating the personal dictatorship so history is full of contingency and surprise after something happens we all think it's inevitable it had to happen that way everything was leading up to it so Hitler seizes power in Germany in 1933 and the Nazi regime gets institutionalized by several of his moves after being named Chancellor and so all German history becomes a story of the Nazi rise to power Hitler's rise to power every trend tendency is bent into that outcome things which don't seem related to that outcome all of a sudden get bent in that direction and all the trends that were going on are no longer examined because they didn't lead to that outcome but Hitler's becoming Chancellor of Germany in 1933 was not inevitable it was contingent he was offered the position by the traditional conservatives he's part of the radical right and the traditional right named him Chancellor the Nazi Party never outright won an election that was free and fair before Hitler came to power and in fact it's votes on the eve of Hitler becoming Chancellor declined relative to the previous election so there's contingency in history and so Lenin's illness his stroke the neurological and blood problems that he had were not a structure in history in other words if Lenin had been a healthier figure Stalin might never have become the Stalin that we know that's not to say that all history is accidental just that we need to relate the structural the larger structural factors to the contingent factors why did Lenin pick Stalin Stalin was a very effective organizer and the position was an organizational position Stalin could get things done he would carry out assignments no matter how difficult he wouldn't complain that it was hard work or too much work he wouldn't go off womanizing and drinking and ignore his responsibilities Lenin chose Stalin among other options because he thought Stalin was the better option once again he wasn't choosing his successor because he didn't know he was gonna have this stroke Lenin had some serious illnesses but he had never had a major stroke before so the choice was made based upon Stalin's organizational skills and promise against the others who are in the regime now they can see more brilliant than Stalin but he was more effective and I'm not sure they were very brilliant well he was exceptionally competent actually at the tasks for running a governor of the executive branch rate of a dictator yes he turned out to be very adept at being a dictator and so if he had been chosen by Lenin and had not been very good he would have been pushed aside by others you can get a position by accident you can be named because you're someone's friend or someone's relative but to hold that position to hold that position in difficult circumstances and then to build effectively a superpower on all that bloodshed right you have to be skilled in some way it can't be just the accident that brings you to power because if accident brings you to power it won't last just like we discovered with Putin he had some qualities that we didn't foresee at the beginning and he's been able to hold power not just be named and now Putin and Stalin are very different people these are very different regimes I wouldn't put them in the same sentence my point is not that one resembles the other my point is that when people come to power for contingent reasons they don't stay in power unless they're able to manage it and Stalin was able to build a personal dictatorship inside that dictatorship he was cunning he was ruthless and he was a workaholic he was very diligent he had a phenomenal memory and so he could remember people's names and faces and events and this was very advantageous for him as he built the machine that became the Soviet state and bureaucracy one of the things maybe you can correct me if I'm wrong with you've made me realize is this wasn't some kind of manipulative personality trying to gain more power solely like kind of an evil picture of a person but he truly believed in communism the the you know as far as I can understand again you can correct me if I'm wrong but he wanted to build a better world by build by having infusing communism into into into the country and perhaps into the the the whole world so maybe my question is what role does communism as an idea as an ideology playing all of this in his rise to power in the people of the time in the Russian people actually just the whole 20th century you're right Stalin was a true believer and this is very important he was also hungry for power and for personal power but just as you said not for powers sake not only for power he was interested in enacting communism in reality and also in building a powerful state he was a statist a traditional Russian statist in the Imperial sense and this won him a lot of followers the fact that they knew he was a hardcore true believing communist won him a lot of followers among the communists and the fact that he was a hardcore defender of Russian state interests now in the Soviet guys also won him a lot of followers sometimes those groups overlapped the Communists and the Russian Patriots and sometimes they were completely different groups but both of them shared an admiration for Stalin's a dedication to those goals and his abilities to enact them and so it's very important to understand that however thirsty he was for power and he was very thirsty for power that he was also driven by ideals now I don't necessarily think that everyone around Stalin shared those ideals we have to be careful not to make everybody into a communist true believer not to make everybody into a great statist Russian patriot but they were widespread and powerful attractions for a lot of people and so Stalin's ability to communicate to people those that he was dedicated to those pursuits and his ability to drive towards them were part of his appeal however he also resorted to manipulation he also resorted to violence he lied he spoke out of all sides of his mouth he slandered other people he sabotaged potential rivals he used every underhanded method and then some in order to build his personal dictatorship now he justified this as you said by appeals to communism and to Soviet father himself as well too to himself and to others and so he justified it in his own mind and to others but certainly any means right were were acceptable to him to achieve these ends and he identified his personal power with communism and with Russian glory in the world so he felt that he was the only one who could be trusted who could be relied upon to build these things now we put ourselves back in that time period the Great Depression was a very difficult time for the capitalist system there was mass unemployment a lot of hardship fascism Nazism Japan Imperial Japan there were a lot of associations that were negative with the kind of capitalist system that was not a hundred percent not a monolith but had a lot of authoritarian incarnations there was imperialism colonies that even the democratic rule of law capitalist states had non democratic non rule of law colonies under their rule so the image and reality of capitalism during that time period between World War one and World War two was very different from how it would become later and so in that time period in that interwar conjuncture after World War one before World War two communism held some appeal inside the Soviet Union for sure but even outside the because the image and reality of capitalism disappointed many people now in the end communism was significantly worse many more victims and the system of course would eventually implode but nonetheless there were real problems that communism tried to address it didn't solve those problems it was not a solution but it didn't come out of nowhere it came out of the context of that inner war period and so Stalin's rule some people saw it as potentially a better option than imperialism fascism and Great Depression having said that they were wrong it turned out that Stalin wasn't a better alternative to markets and private property and rule of law and democracy however that didn't become clearer to people until after World War two after Nazism had been defeated Imperial Japan had been defeated fascist Italy had been defeated and decolonization had happened around the world and there was a middle class economic boom in the period from the late 40s through the 70s that created a kind of mass middle class in many societies so capitalism rose from the ashes as it were and this changed the game for Stalin and communism communism is about an alternative to capitalism and if that alternative is not superior there's no reason for communism to exist but if capitalism is in foul odor if people have a bad opinion a strong critique of capitalism that can be appealed to alternatives and that's kind of what happened with Stalin's rule but after World War two the context changed a lot capitalism was very different much more successful not a non-violence compared to what it was in the interwar period and the Soviet Union had a tough time competing against that new context now today we see similarly that the image and reality of capitalism is on the question again which leads some people to find an answer in socialism as an alternative so you just kind of painted a beautiful picture of comparison this is the way we think about ideologies because we is what's working better do you separate in your mind the ideals of communism to the Stalinist implementation of communism and again capitalism and American implementation of capitalism and as we look at now the 21st century where yes this idea you know of socialism being a potential political system that we would or economic system would operate under in the United States rising up again as an idea so how do we think about that again in the 21st century about these ideas fundamental deep ideas of communism capitalism yeah so in the Marxist schema there was something called feudalism which was supposedly destroyed by the bourgeoisie who created capitalism and then the working class was supposed to destroy capitalism and create socialism but socialism wasn't the end stage the end stage was going to be communism so that's why the communist party in the Soviet Union first built socialism transcending capitalism the next stage was socialism and the end game the final stage was communism so their version of socialism was derived from Marx and Marx argued that the problem was capitalism had been very beneficial for a while it had produced greater wealth and greater opportunities and feudalism had but then it had come to serve only the narrow interests of the so called booze huazi or the capitalists themselves and so for Humanity's sake the universal class the working class needed to overthrow capitalist in order for greater productivity greater wealth to be produced for all of humanity to flourish and on a higher level so you couldn't have socialism unless you destroyed capitalism so that meant no markets no private property no so-called Parliament's or bourgeois Parliament's as they were called so you got socialism in Marxist schema by transcending by eliminating capitalism now Marx also called for freedom he said that this elimination of markets and private property and bourgeois Parliament's would produce greater freedom in addition to greater abundance however everywhere this was tried it produced tyranny and mass violence death and shortages everywhere it was tried there's no exception in historical terms and so it's very interesting Marx insisted that capitalism had to be eliminated you couldn't have markets markets were chaos you needed planning you couldn't have wait a hiring of wage labor that was wage slavery now you couldn't have private property because that was a form of theft so in the Marxist scheme somehow you were going to eliminate capitalism and get to freedom it turned out you didn't get to freedom so then people said well you can't blame Marx because he said we needed freedom he was Pro freedom so it's kind of like dropping a nuclear bomb you say you're gonna drop a nuclear bomb but you want to minimize civilian casualties so the dropping of the nuclear bomb is the elimination of markets private property in Parliament's but you're going to bring freedom or you're going to minimize civilian casualties so you drop the nuclear bomb you eliminate the capitalism and you get famine deportation no constraints on executive power and not abundance but shortages and people say well that's not what I mark said that's not what I said I said I wanted to minimize civilian casualties the nuclear bomb goes off and there's mass civilian casualties and you keep saying but I said drop the bomb but minimize civilian casualties so that's where we are that's history not philosophy yeah I'm speaking about historical examples all the cases that we have Mark's was not a theorist of inequality Marx was a theorist of alienation of dehumanization of fundamental constraints or what he called fetters on productivity and on wealth which he all attributed to capitalism Marx wasn't bothered by inequality he was bothered by something deeper something worse right those socialists who figured this out who understood that if you drop the nuclear bomb there was no way to minimize civilian casualties those socialists who came to understand that if you eliminated capitalism markets private property and Parliament's if you eliminated that you wouldn't get freedom those Marxists those socialists became what we would call Social Democrats or people who would use the state to regulate the market not to eliminate the market they would use the state to redistribute income not to destroy private property in markets and so this in the Marxist schema was apostasy because they were accepting markets and private property they were accepting alienation and wage slavery they were accepting capitalism in principle what they wanted to fix it they wanted to ameliorate they wanted to regulate and so they became what was denounced as revision not true Marxists not real revolutionaries but parliamentary Road parliamentarians we know this as normal politics normal social democratic politics from the European case are from the American case but they are not asking to eliminate capitalism blaming capitalism blaming markets and private property so this rift among the Socialists the ones who are for elimination of capitalism transcending capitalism otherwise you could never ever get to abundance and freedom in the Marxist schema versus those who accept capitalism but want to regulate and redistribute that rift on the left has been with us almost from the beginning it's a kind of civil war on the left between the Leninists and Social Democrats or the revisionists as they're known pejoratively by the Leninists we have the same confusion today in the world today where people also cite Marx saying capitalism is a dead end and we need to drop that nuclear bomb and get freedom get no civilian casualties versus those who say yes there are inequities there's a lack of equality of opportunity there are many other issues that we need to deal with and we can fix those issues we can regulate we can redistribute I'm not advocating this as a political position I'm not taking a political position myself I'm just saying that there's a confusion on the left between those who accept capitalism and want to regulate it versus those who think capitalism is inherently evil and if we eliminate it we'll get to a better world when in fact history shows that if you eliminate capitalism you get to a worse world the problems might be real but the solutions are worse from history's lessons now we have deep painful lessons but there's not many of them you know our history is relatively short as a human species do we have a good answer on the left of Leninist Marxist versus social democrat versus capitalism versus any anarchy you know do have sufficient samples from history to make better decisions about the future of our politics and economics for sure we have the American Revolution which was a revolution not about class not about workers not about a so-called universal class of the working class elimination of capitalism markets and the bourgeoisie but was about the category citizen it was about universal humanity where everyone in theory could be part of it as a citizen the revolution fell short of its own ideals not everyone was a citizen right for example if you didn't own property you were a male but didn't own property you didn't have full rights of a citizen if you were a female whether you own property or not you weren't a full citizen if you were imported from Africa against your will you were a slave and not a citizen and so not everyone was afforded the rights in actuality that were declared in principle however over time the category citizen could expand and slaves could be emancipated and they could get the right to vote they could become citizens non-property owning males could get the right to vote and become full citizens females could get the right to vote and become full citizens in fact eventually my mother was able to get a credit card in her own name in the 1970s without my father having to co-sign the paperwork I took a long time but nonetheless the category citizen can expand and it can become a universal category so we have that the citizen universal humanity model of the American Revolution which was deeply flawed at the time it was introduced but fixable over time we also had that separation of powers and constraint on executive power that we began this conversation with that was also institutionalized in the American Revolution because they were afraid of tyranny they were afraid of unconstrained executive power so they built a system that would contain that constrain it institutionally not circumstantially so that's a great gift within that Universal category of citizen which has over time come closer to fulfilling its original promise and within those institutional constraints that separation of powers constraint on executive power within that we've developed what we might call normal politics left-right politics people can be in favor of redistribution and government action and people can be in favor of small government hands off government no redistribution or less redistribution that's the normal left-right political spectrum where you respect the institutions and separation of powers and you respect the universal category of citizenship and equality before the law and everything else I don't see any problems with that whatsoever I see that as a great gift not just to this country but around the world and other places besides the United States have developed this the problems arise at the extremes the far left and the far right that don't recognize the legitimacy either of capitalism or of democratic rule of law institutions and they want to eliminate constraints on executive power they want to control the public sphere or diminish the Independence of the media they want to take away markets or private property and redistribution becomes something bigger than just redistribution it becomes actually that original Marxist idea of transcending capitalism so I'm not bothered by the left or the right I think they're normal and we should have that debate where a gigantic diverse country of many different political points of view I'm troubled only by the extremes that are against the system cost system that want to get rid of it and supposedly that will be the right path to the future history tells us that the far left and the far right are wrong about that but once again this doesn't mean that you have to be a social democrat you could be a libertarian you could be a conservative you could be a centrist you could be conservative on some issues and liberal on other issues all of that comes under what I would presume to be normal politics and I see that as the important corrective mechanism normal politics and market economies non monopolistic open free and dynamic market economies I don't like concentrations of power politically and I don't like concentrations of power economically I like competition in the political realm I like competition in the economic realm this is not perfect it's constantly needs to be protected and reinvented and there are flaws that are fundamental and need to be adjusted and addressed and everything else especially equality of opportunity equality of outcome is unreachable and is a mistake because it produces perverse and unintended consequences equality of outcome attempts attempts to make people equal on the outcome side what attempts to make them more equal on the front end on the opportunity side that's really really important for a healthy society that's where we've fallen down our schools are not providing equality of opportunity for the majority of people in all of our school systems and so I see problems there I see a need to invest in ourselves invest in infrastructure invest in human capital create greater equality of opportunity but also to make sure that we have good governance because governance is the variable that enables you to do all these other things I've washed quite a bit returning back to Putin I've watched quite a few interviews and with Putin in conversations you know especially because I speak Russian fluently I can understand often the translations lose a lot I am I find the man putting morality aside very deep and interesting and I found almost no interview with him to be to get at that depth I was I was very hopeful for the Oliver Stone documentary and with him and to me because I deeply respect our stone as a filmmaker in general but it was a complete failure in my eyes that interview the the lack of it I mean I suppose you could toss it up to a language barrier but a complete lack of diving deep into the person as what I saw my question is a strange one but if you were to sit down with Putin and have a conversation or perhaps if you're sa-do's Saddam was Stalin and have a conversation what kind of questions would you ask well this wouldn't be televised unless you want it to be so this is only you so you're allowed to ask about some of the questions that are sort of not socially acceptable meaning putting morality aside getting into depth of the human character what would you ask so once again they're very different personalities and very different time periods in very different regimes so what I would talk to Stalin about and Putin about her are not in the same category necessarily so let's take Putin so I would ask him where he thinks this is going where he thinks Russia's going to be in 25 years or 50 years what's the long-term vision what does he anticipate the current trends are going to produce is he under the illusion that Russia is on the up swing that things are actually going pretty well that in 25 years Russia is going to still be a great power with a tremendous dynamic economy and a lot of high tech and a lot of human capital and wonderful infrastructure and a very high standard of living and a secure secure borders and sense of security at home see think the current path is leading in that direction and if not if he's if he understands that the current trajectory does not provide for those kinds of circumstances does it bother him it does he worry about that does he care about the future 25 or 50 years from now deep down what do you think is the answer either the honesty either he thinks he's on that trajectory already or he doesn't care about that long-term trajectory so that's the mystery for me with him he's clever he has tremendous sources of information he has great experience now as a world leader having served for effectively longer than laying at Brezhnev's long 18 year reign and so Putin has accumulated a great deal of experience at the highest level compared to where he started and so I'm interested to understand how he sees this long term evolution or non evolution of Russia and and whether he believes he's got them on the right trajectory or whether if he doesn't believe that he cares I have no idea because I've never spoken to him about this but I would love to hear the answer sometimes you have to ask questions not directly like that but you have to come a little bit sideways you can elicit answers from people by making them feel comfortable in coming sideways with them on just a quick question so that's talking about Russia yeah Putin's role in Russia do you think it's interesting to ask and you could say the same for Stalin the more personal question of how do you feel yourself about this whole thing about your life about your legacy looking at the person that's one of the most powerful and important people in the history of civilization both Putin and Stalin you could argue yeah once you experience power at that level it becomes something that's almost necessary for you as a human being it's a drug it's an aphrodisiac it's a feeling you know you go to the gym to exercise and the endorphins the chemicals get released and even if you're tired or you're sore you get this massive chemical change which is has very dynamic effects on how you feel and the kind of level of energy you have for the rest of the day and if you do that for a long time and then you don't do it for a while you're like a drug addict not getting your fix you miss it your body misses that release of endorphins to a certain extent that's how power works for people like Putin that's how power works for people who run universities or our secretaries of state or run corporations fill in the blank in whatever ways power is exercised it becomes almost the drug for people it becomes something that's difficult for them to give up it becomes a part of who they are it becomes necessary for their sense of self and well-being the greatest people the people I admire the most are the ones that can step away from power can give it up can give up the drug can be satisfied and be stronger even by walking away from continued power when they had the option to continue alright so with a person like Putin once again I don't know him personally so I have no basis to judge this this is a general statement observable with many people and in historical terms with a person like Putin who's exercised this much power for this long it's something that becomes a part of who you are and you have a hard time imagining yourself without it you begin to conflate your personal power with the well-being of the nation you begin to think that the more power you have the better off the country is this conflation you begin to be able to not imagine you can no longer imagine what it would be like just to be an ordinary citizen or an ordinary person running a company even something much smaller than a country so I anticipate that without knowing for sure that he would be in that category of person but you'd want to explore that with questions with him about so what's his day look like from beginning to end just take me through a typical day of yours what are you doing a day how does it start what are the ups what are the downs what are the parts of the day you look forward to the most what are the parts of the day you don't look forward to that much what do you consider a good day what do you consider a bad day yeah how do you know that what you're doing is having the effects that you intend how do you follow up how do you gather the information the reaction how do you get people to tell you to your face things that they know are uncomfortable or that you might not want to hear those kind of questions through that window through that kind of question you get a window into a man with power so let me ask about stalling because you've done more reason another amazing interview you've had the the introduction was that you know more about Stalin than Stalin himself you've done incredible amount of research on Stalin so if you could talk to him get sort of direct research what question did you ask of Stalin I have so many questions I don't even know where I would begin the thing about studying a person like Stalin who's an immense creature right he's exercising the power of life and death over hundreds of millions of people he's making decisions about novels and films and and turbines and submarines and and pacts with Hitler or deals with Churchill and Roosevelt and and occupation of Mongolia or occupation of North Korea he's making phenomenally consequential decisions over all spheres of life all areas of Endeavour and over much of the globe much of the land mass of the earth and so what's that like does he sometimes reflect on the amount of power and responsibility he has that he can exercise does he sometimes think about what it means that a single person has that kind of power and does it have an effect on his relations with others his sense of self the kinds of things he values in life does he sometimes think it's a mistake that he's accumulated this much power does he sometimes wish he had a simpler life or is he once again so drunk so enamored so caught up with chemically and spiritually with exercising this kind of power that he couldn't live without it and then what were you thinking I would ask him in certain decisions that he made what were you thinking on certain dates and certain circumstances where you made a decision and could have made a different decision can you recall your thought processes can you bring this Beck was at seat-of-the-pants was it something you'd been planning did you just improvise or did you have a strategy what were you guided by whose examples did you look to when you picked up these books that you read and you read the books and you made pencil marks in them is it because you absorbed the lesson there or did it really not become a permanent lesson and was just something that you checked and it was like a reflex so I have many specific questions about many specific events and people and circumstances that I have tried to figure out with the surviving source materials that we have in abundance but I would still like to delve into his mindset and reconstruct his mind the closer you get to Stalin in some ways the more elusive he can become and especially around World War two you've already illuminated a lot of interesting aspects about Stalin's role in the war but it would be interesting to ask even more questions about how seat-of-the-pants or deliberate some of the decisions have been if I could ask just one quick question one last quick question and you're constrained in time and answering it do you think there will always be evil in the world do you think there will always be war unfortunately yes there are conflicting interests conflicting goals that people have most of the time those conflicts can be resolved peacefully that's where we build strong institutions to resolve different interests and conflicts peacefully but the fact the enduring fact of conflicting interests and conflicting desires that can never be changed so the job that we have for Humanity's sake is to make those conflicting interests those conflicting desires to make them to put them in a context where they can be resolved peacefully and not in a zero-sum fashion so we can't get there on the global scale so there's always gonna be the kind of conflict that sometimes gets violent what we don't want is a conflict among the strongest powers great power conflict is unbelievably bad there are no words to describe at least 55 million people died in World War two if we have a world war 3 a war between the United States and China or whatever it might be who knows what the number could be a hundred and fifty five million two hundred and fifty five million five hundred and fifty five million I don't even want to think about it and so it's horrible when wars break out in the humanitarian catastrophes for example Yemen and Syria and several other places I could name today it's just horrible what you see there and the scale is colossal for those places but it's not planetary scale and so avoiding planetary scale destruction is really important for us and so having those different interests be somehow managed in a way that they don't that no one sees advantage in a violent resolution and a part of that is remembering history so they should read your books Stephen thank you so much it was a huge honors talking to you today I really enjoyed it thank you for the opportunity my pleasure thanks for listening to this conversation with Steven Kotkin and thank you to our presenting sponsor cash app download it and use code let's podcast you'll get ten dollars and ten dollars we'll go to first a stem education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators if you enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you with words from Joseph Stalin spoken shortly before the death of Lenin and at the beginning of Stalin's rise to power first in Russian yeah she died Oh recession innovation act or acog Buddhist party gonna bite the watchdog Chile China vajna at the Couture Heacock which is she dies Casa I consider it completely unimportant who in the party will vote or how but what is extraordinarily important is who will count the votes and how for listening and hope to see you next time you |
Donald Knuth: Algorithms, Complexity, and The Art of Computer Programming | Lex Fridman Podcast #62 | the following is a conversation with donald knuth one of the greatest and most impactful computer scientists and mathematicians ever he's the recipient of the 1974 Turing award considered the Nobel Prize of computing he's the author of the multi-volume work the magnum opus the art of computer programming he made several key contributions to the rigorous analysis of computational complexity of algorithms including the popularization of asymptotic notation that we all affectionately know as the Big O notation he also created the tech typesetting system which most computer scientists physicists mathematicians and scientists and engineers in general used to write technical papers and make them look beautiful I can imagine no better guest to in 2019 with than Don one of the kindest most brilliant people in our field this podcast was recorded many months ago it's one I avoided because perhaps counter-intuitively the conversation meant so much to me if you can believe it I knew even less about recording back then so the camera angle is a bit off I hope that's okay with you the office space was a bit cramped for filming but it was a magical space Ordon does most of his work it meant a lot to me that he would welcome me into his home it was quite a journey to get there as many people know he doesn't check email so I had to get creative the effort was worth it I've been doing this podcast on the side for just over a year sometimes I had to sacrifice a bit of sleep but always happy to do it and to be part of an amazing community of curious minds thank you for your kind words support for the interesting discussions and I look forward to many more of those in 2020 this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an Apple podcast follow on Spotify support on patreon or simply connect with me on Twitter at lex friedman spelled fri d-m am I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that break the flow of the conversation I hope that works for you and doesn't hurt the listening experience I provide time stamps for the start of the conversation that you can skip to but it helps if you listen to the ad and support this podcast by trying out the product the service being advertised this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy a fraction of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member s IBC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and charity navigator which means that donated money is used to maximum effectiveness when you get cash app from the App Store or Google Play and use code Lex podcast you'll get ten dollars in cash up will also donate ten dollars the first which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with Donald Knuth in 1957 atcase tech you were once allowed to spend several evenings with a IBM 650 computer as you've talked about in the past then you fell in love with computing then can you take me back to that moment with the IBM 650 what was it that grabs you about that computer so the IBM 650 was this this machine that well it didn't fill a room but it it was it was big and noisy but when I first saw it it was through a window and there were just a lot of lights flashing on it and I was a freshman I had a job with the statistics group and I was supposed to punch cards and pour data and then sort them on another machine but then they got this new computer came in and I and it had interesting like you know lights okay so well but I had it kind of key to the building so I can you know like I could get in and look at it and got a manual for it and and my first experience was based on the fact that I could punch cards basically would you a big thing for though deal with thick but the is 6:50 was you know big in size but but incredibly small in power in memory it had it had 2,000 words of memory and in a word of memory was 10 decimal digits plus a sign and it it would do to add two numbers together you could probably expect that would take oh say three milliseconds so that's pretty fast it's the memories that constraint the memories the problem that was why it was three millisecond because it took five milliseconds for the drum to go around and you had to wait I don't know five cycle times if you have an instruction one position on the drum then it would be ready to read the data for the instruction and three notches the drum is 50 cycles around and you go three cycles and you can get the data and then you can go another three cycles and get and get to next instruction if the instruction is there otherwise otherwise you spin until you get to there play and and we had no random-access memory whatsoever until my senior year you see here we got fifty words of random access memory which were which were priceless and we would and we would move stuff up to the up to the random access memory in 60 word chunks and then we would start again so it's separating when to go up there and could you have predicted the future 60 years later of computing from then you know in fact the hardest question I was ever asked was what could I have predicted in other words the interviewer asked me she said you know what about computing has surprised you you know and immediately I ran I rattled off a couple dozen things and inches okay so what didn't surprise and I was I tried for five minutes to think of something that I thought I would have predicted and I and I and I couldn't but I let me say that this machine I didn't know well it there wasn't there wasn't much else in the world at that time the 650 was the first machine that was that there were more than a thousand of ever before that there were you know there was each machine there might be a half a dozen examples maybe my first mass-market mass-produced the first one yeah done in quantity and and IBM I didn't sell them they they rented them but but they they rented them to universities that at great you know I had a great deal and and so that's why a lot of students learned about computers at that time so you refer to people including yourself who gravitate toward a kind of computational thinking as geeks for at least I've heard you used that terminology it true that I think there's something that happened to me as I was growing up that made my brain structure in a certain way that resonates with with computers so there's the space of people it's 2% of the population you empirically estimate that's a prick it's been proven fairly constant over most of my career however it might be different now because kids have different experiences when they're young so what does the world look like to a geek what is what is this aspect of thinking that is unique to their makes it yeah that makes a geek this is cuter the important question in in the 50s IBM noticed that that there were geeks and non geeks and so they tried to hire geeks and they put out as worth papers saying you know if you play chess come to Madison Avenue and for an interview or something like this they were they were trying for some things so what it what what is it that I find easy and other people tend to find harder and and I think there's two main things one is this with is ability to jump jump levels of abstraction so you see something in the large and you see something in the small and and can you pass between those unconsciously so you know that in order to solve some big problem what you need to do is add one to a into a certain register or anything that gets you to another step and you can and we and below the yeah I mean I don't go down to the electron level but I knew what those milliseconds were what the drum was like on the 650 I knew how I was gonna factor her number or or find a root of an equation or something be alavés because of what was doing and and as I'm debugging I'm going through you know did I make a key punch err did I did I write the wrong instruction do I have the wrong wrong thing in a register and each level at each level it is different and so this idea of being able to see something at all at lots of levels and fluently go between them it seems to me to be more pronounced much more pronounced in in the people that with computers like I got so in my books I also don't stick after the high level but but i but i mix low level stuff with high level and this means that some people think you know that I that I should write better books and it's probably true but but other people say well but that's if you think like like that then that's the way to train yourself like to keep mixing the levels and and learn more and more how to jump between so that that's the one thing the other the other thing is that it's more of a talent it to be able to deal with non-uniformity where there's case one case two case three instead of instead of having one or two rules that govern everything so if so it doesn't bother me if I need like an algorithm has ten steps to it you know each step is does something else that doesn't bother me but a lot of a lot of pure mathematics is based on one or two rules which which are universal and and and so this means that people like me sometimes work with systems that are more complicated than necessary because it doesn't bother us that we don't that we didn't figure out the simple rule and you mentioned that while Jacobi boule Abel and all the mathematicians in 19th century may have had symptoms of geek the first hundred percent legit geek was touring Alan Torrie I I think he had yeah a lot more of this quality than anyone could from reading the kind of stuff he didn't so hot as touring what influence has touring had on you well well your way and so I didn't know that aspect of him until after I graduated some years I it has undergraduate we had a class that talked about computability theory and Turing machines and and that was all it sounded like a very specific kind of purely theoretical approach to stuff so when how old was I when I when I learned that he thought he had you know designed when she and that he wrote the you know you wrote a wonderful manual for for Manchester machines and and he invented all the subroutines and and and he was a real hacker that that he had his hands dirty I thought for many years that he had only done purely formal work as I started reading his own publications I could yeah you know I could feel this kinship and and of course he had a lot of peculiarities like he wrote numbers backwards because I mean left to right to the right to left because that's the that's it was easier for computers to process him that way what do you mean left to right he would write PI as you know nine five one four point three I mean okay right forget it for one point three on the blackboard I mean when he he we had trained himself to to do that because the computers he was working with I worked that way inside trained himself to think like a computer well there you go that's nuts geek thinking you've practiced some of the most elegant formalism in computer science and yet you're the creator of a concept like literate programming which seems to move closer to natural language type of description of programming yep yeah absolutely so how do you see those two as conflicting as the formalism of theory and the idea of literate programming so there we are in a non uniform system well I don't think one one-size-fits-all and I don't and I don't think all truth lies in one in one kind of expertise and so somehow in a way you'd say my what my life is a convex combination of English and mathematics and you're okay with that and not only that I think thriving I wish you know I want my kids to be that way I want cetera not used left-brain right-brain at the same time you got a lot more done that's that was part of the and I've heard that you didn't really read for pleasure until into your 30s literature true you know more about me than I do but I'll try to be consistent with what you're really ya know just believe me yeah just go with whatever story I tell you it'll be easier that way the conversation I've heard mentioned a Philip Roth's American pastoral which I love as a book I don't know if it was it was mentioned as something I think that was meaningful to you as well in either case what literary books had a lasting impact on you what okay good so I so I met Russ already well we both got doctors from Harvard on the same day so I so we were yeah we had lunch together and stuff like that and but he knew that you know computer books would never sell well well all right so you say you you you you're a teenager when you left Russia so I I have to say that Tolstoy was one of the big influences on me I especially like Anna Karenina not because of a particular area of the plot of the story where but because there's this character who you know did the philosophical discussions it's all it's a whole way of life is worked out there it's among the characters until in and so it that I thought was was especially beautiful on the other hand does they have ski I I didn't like at all because I I felt that he his genius was mostly because he kept forgetting what he what he had started out to do and he was just sloppy I didn't think that that it then that he polished his stuff at all and and I tend to admire somebody who who Todd's the i's and cross the t's so that the music of the prose this way you admire more and that I certainly do admire the music of the language which I couldn't appreciate in the Russian original but but I can and Victor Hugo Glenn's close friendships much his closer but but Tolstoy I like the same reason I like Herman Wouk as a as a novelist I that I think I like his book Marjorie Morningstar has a similar character in who who who developed his own personal philosophy and export and it called goes in in was consistent yeah right and it's worth worth pondering uh so zo like Nietzsche and like what you don't like Friedrich Nietzsche or age yeah no no you like this has like I keep seeing quotations for Nietzsche and and you never tempt me to read any further please full of contradictions we will certainly not appreciate him but Schiller you know I'm trying to get the cross what I appreciate in literature and part of it is the is is as you say the music of the language of the way it flows and take Raymond Chandler versus Dashiell Hammett Dashiell Hammett sentences are awful and Raymond Chandler's are beautiful they just flow so I I don't I don't read literature because it's supposed to be good for me or because somebody said it's great but but it I could find things that I like I mean you mentioned you address like James Bond so like I love Ian Fleming I think he's got a he had a really great gift for if he has a golf game or game of bridge or something and this comes into a story it'll it'll be the most exciting golf game or or you know the absolute best possible hands a bridge that that exists and and any he exploits it and tells it beautifully as well so in connecting some things here looking at literate programming and being able to it convey encode algorithms to a computer in a way that mimics how humans speak how what do you think about natural language in general and the messiness of our human world about trying to express yeah difficult things so the idea of literate programming is to is really to try to understand something better by seeing it from these two perspectives the formal and the informal if we try to understand a complicated thing if we can look at it in different ways and so this is in fact the key to technical writing a good technical writer try not to be obvious about it but says everything twice formally and informally or maybe three times but you try to give the reader a way to put the concept into his own brain or her own brain is that better for the writer or the reader or both well the writer just tries to understand the reader that's the goal of a writer is to have a good mental image of the reader and to say what the reader expects next and to to impress the reader with what has impressed the writer why something is interesting so when you have a computer program we try to instead of looking at it as something that we're just trying to give an instruction to the computer what we really want to be is giving giving insight to the person who's who's gonna be maintaining this program or to the programmer himself when he's debugging it as to why this stuff is being done and so all the techniques of exposition that a teacher uses or book writers make you better program or if your if your program is going to be not just a one-shot deal so how difficult is that do you see hope for the combination of informal and formal for the programming task yeah I I'm the wrong person to ask I guess because I'm a geek but but I think for a geek it's easy I don't know I don't know see not some people have difficulty writing and that might be because there's something in their brain structure that makes it hard for them to write or or it might be something just that they haven't had enough practice I'm not the right one to to uh to judge but I don't think you teach any person any particular skill like I do think that that writing is is half of my life and so I put it together and let program he won't even when I'm writing a one-shot program I I write it in literate way because I get it right faster though now does it get compiled automatically or so I guess on the technical side my question was how difficult is a design a system where much of the programming is done informally informally yeah informally I think whatever works to make it understandable is good but then you have to also understand how informal is you have to know the limitations you have to connect so so by putting the formula and informal together this this is where this is where it gets locked into your into your brain now you can you can say informally well I'm working on a problem right now so let's go there I get that can you give me an example of of connecting the informal in the formal well it's a little too complicated an example there's a puzzle that that's self referential it's called a Japanese arrow puzzle and and and you're given a a bunch of boxes each one points north east south or west and at the end you're supposed to fill in each box with the number of distinct numbers that it points to so if I put a three in a box that means that and it's pointing to five other boxes that means that there's going to be three different numbers in those five bucks and and those boxes are pointing what I might be pointing to me one of my might be pointing the other way but anyway I kind of defined a set of numbers that obeys this complicated condition that each number counts how many distinct numbers if it points do well and still a guy sent me his solution to this problem where he where he presents formal statements that that say either this is true or this is true this is true and and and so I try to render that formal statement informally and I try say I contain a three and and the guys I'm pointing to contain the numbers one two and six so by putting it in formally and also I converted into a into a dialogue statement that helps me understand the logical statement that he's written down as a string of numbers in terms of some abstract variables Eddie yeah that's really interesting so maybe an extension of that there has been a resurgence in computer science and machine learning and neural networks so using data to construct algorithms so it's another way to construct algorithms really yes you can think of it that way so as opposed to natural language to construct algorithms use data to construct other so what what's the view of this branch of computer science where data is almost more important than the mechanism of the algorithm it seems to be suited to a certain kind of non geek and would you know which is probably why it's it's like it's taken off that it has its own community that I thought really that really resonates with that but it's hard to you know to trust something like that because nobody even the people who who work with it that they have no idea what is what has been learned that's a really interesting thought that it's it makes algorithms more accessible to a different community a different type of brain yep and that's really interesting because just like literate programming perhaps could make programming more accessible to a certain kind of brain there are people who think it's just a matter of Education and anybody can learn to be a great program or anybody can to be a great skier uh yeah you know I I wish that were true but but I know that there's a lot of things that I've tried to do and I and like I was well motivate an icon and I kept trying to build myself up and I never got past a certain level I can't use for example I can't view three-dimensional objects in my in my head I have to I have to make a model and look at it and study it from all points of view and then I start to get some idea but other people are good at four dimensions I mean physicists yeah so let's go to the art of computer programming in 1962 you set the table of contents for this magnum opus right yeah it was supposed to be a single book for 12 chapters now today what is it 57 years later you're in the middle of volume 4 of 7 and in the middle of going for B is 4 B precisely can ask you for an impossible task which is try to summarize the book so far maybe by giving a little examples so from the sorting and the search in the combinatorial algorithms if you were to give a summary a quick elevator summary yeah right what depending how many floors that are in the building yes the first volume called fundamental algorithms talks about something that you can't the stuff you can't do without I guess that you have to know the basic concepts of what is a program now what is it what is it algorithm and and and it also talks about a low-level machine so you can have some some kind of an idea what's going on and it has basic concepts of input/output and subroutines induction induction writes mathematical so so the thing that makes my book different from a lot of others is that all that I try to not only present the algún but I try to analyze them and which means to quantitatively I say not only does it work but it works this fast okay and so I need math for them and then there's the standard way to structure data inside and represent information in the computer so that's all volume 1 volume 2 talks it's called semi numerical algorithms and here we're here we're writing programs but we're also dealing with numbers algorithms deal with with with any kinds of objects but but specific when there's objects or numbers well then then we have certain special paradigms that apply to things that have 12 numbers and so there's there's what there's like there's arithmetic on numbers and and there's matrices full of numbers there's random numbers and there's power series full of numbers there's different algebraic concepts that have numbers in structured ways and the arithmetic in the way a computer would think about arithmetic is a floating point floating point arithmetic a high precision arithmetic not only addition subtraction multiplication but also comparison up number so then check then volume three talks about I like that one sort insert sorting a circle of sorting right so so here you know we're not getting necessarily with numbers because you slipped you saw it letters and other objects and searching we're doing all the time we googled nowadays but I mean we have to find stuff so again algorithms that that underlie all kinds of applications like you know none of these volumes it's about a particular application but the applications are examples of of why people want to know about sorting why people want to know about random numbers so then volume 4 goes into combinatorial I'll again this is where we have zillions of things to deal with and we and here we keep finding cases where one good idea can can make something go more than a million times faster and and and we're dealing with problems that are probably never going to be solved efficiently but that doesn't mean we give up on them and and and we have this chance to have good ideas and and go much much faster on them so so that's comets are all algorithms and those are the ones that are yeah I'm using charting is most fun for you well how many toriel algorithms are the ones that I always that I always enjoyed the most because that's when my skillet programming had most payoff you know the different the difference between an obvious algorithm that you think up first thing and you know and a good you know an interesting subtle out algorithm that not so obvious but but run circles around the other one that's that's where computer science 3d comes comes in and and a lot of these comets are methods were found first in applications to artificial intelligence or cryptography and in my case I I just liked him and it was associated more with puzzles that you like the most in the domain of graphs and graph theory graphs are great because they're terrific models of so many things in the real world and and and and you you throw numbers on a graph you got a network and so there you're right there you have but many more things so but comma toriel in general is in any arrangement of objects that that has some kind of a higher structure non non random structure and it's okay it is possible to put something together satisfying all these conditions like I mentioned arrows a minute ago you know is there a way to to put these numbers on a bunch of boxes that that are pointing to each other is that going to be possible at all that's volume four that's volume four what is a sage of Hawaiian for a was part one and and what happened was in 1962 when I started writing down a table of contents it wasn't going to be a book about computer programming in general it was going to be a book about how to write compilers and I was asked to write a book explaining how to how to write a compiler and at that time there were only a few dozen people in the world who had written compilers and I happen to be one of them so and I also had some experience for writing for like the campus newspaper and things like that so so I said okay great I'm the only person I know who who's written a compiler but hasn't invented any new techniques for writing compilers and and all the other people I knew had super ideas but I couldn't see that they would be able to write a book that wouldn't that would describe anybody else's ideas with their own so I could be the I could be the journalist and I could explained what all these cool ideas about compiler writing that were and and then I I started pretty well yeah let me you need and have a chapter about data structures you need to have some introductory material I want to talk about searching because a compiler writer has to it has to look up the variables in a symbol table and find out you know which which when you when you write the name of a variable in one place it's supposed to be the same as the one you put somewhere else so you need all these basic techniques and I and I you know kind of know some arithmetic to stuff so I throw I threw in these chapters and I threw in a chapter on comma talks because that was what I really enjoyed programming the most but there weren't many algorithms and known about combinatorial methods in 1962 so that was a kind of a short chapter but it was sort of thrown in just for fun and Chapter twelve was going to be actual compilers applying all the stuff in chapters 1 to 11 to make compilers well ok so that was my table of contents from 1962 and during the 70s the whole field of combinatoric s-- went through a huge explosion people talk about it comet oil explosion and they usually mean by that that the number of cases goes up you know you change n to n plus 1 and all of a sudden you your problem has gotten more than ten times harder but there was an explosion of ideas about combinatoric s-- in the 70s and to the point that but Mike's take 1975 I bet you more than half of all the journals of computer science we're about combinatorial method and what kind of problems were occupying people's minds what kind of problems in combinatorics was it's it's that gravity graph theory yeah gravity was was quite dominant I mean no but all of the np-hard problems that you have like Hamiltonian path or foul sail going beyond yeah yeah going beyond graphs you had a operation research whenever it was a small class of problems that had efficient solutions and they were associated with Maitre D' a special mathematical construction but once we went to things that involve three things at a time instead of instead of two all of a sudden the things got harder so we had satisfiability problems or if you have if you have clauses every Clause has two logical elements in it then we can satisfy it linear time we can test for satisfy building linear time but if you allow yourself three variables in the clause then nobody knows how to do it so these articles were about trying to find better or better ways to to solve cryptography problems and graph three problems where the we have lots of data but we didn't know how to find the best subset so the data like with sorting we could get the answer didn't take long so how did they continue to change from the 70s to today yeah so now there may be half a dozen conferences whose topic is cognate arcs different kind but fortunately I don't have to rewrite my book every month you know like I had to in in the 70 but still there's huge amount of work being done and people getting better ideas on these problems that don't seem to have really efficient solutions but we can still get into a lot more with him and so this book that I'm finishing now is I've got a whole bunch of brand new methods that the fires I know there's no other there's no other book that covers that covers this particular approach and and so I'm trying to do my best of exploring the tip of the iceberg and and and I try out lots of things and and keep keep rewriting finding as I find better better method so what's your writing process like what's your thinking and writing process like every day so what's your routine even yeah I guess it's actually the best question because I spent seven days a week you're doing it the most prepares to answer it yeah yeah but okay so the chair I'm sitting in is where I do that's where the magic happens well reading and writing that many chairs usually sitting over there where I have other books some reference book but but I I found his chair which was designed by a Swedish guy anyway it turns out this was the only chair I can really sit in for hours and hours and not know that I'm in a chair but then I have the stand-up desk right next next to us and and so after I write something with pencil and eraser I get up and I type it and revise and rewrite the kernel the idea is first put on paper yep that's worth right and I call right maybe five programs a week of course literate programming and these are before I describe something in my book I always program it to see how it's working and I and I tried a lot so for example I learned at the end of January I learned of a breakthrough by for Japanese people who had extended one of the one of my methods in in a new direction and so I I spent the next five days writing a program to implement what they did and then I you know but they had only generalized part of what I had done so that I had to see if I could generalize more parts of it and then I had to take their approach and I had to I had to try it out on a couple of dozen of the other problems I had already worked out with that with my old methods and so that took another couple of weeks and then I would you know then I then I started to see the light nicely and and I started writing the final draft and and then I would you know type it up involves some new mathematical questions and so I wrote to my friends and might be good at solving those problems and and they solve some of them so I put that in his exercises and and so a month later I had absorbed one new idea that I that I learned and you know I'm glad I heard about it in time otherwise my I wouldn't put my book out before I heard about the idea on the other hand this book was supposed to come in at 300 pages and I'm up to 350 now that added 10 pages to the book but if I learn about another one I probably first gonna shoot me well so in the process in that one month process are some days harder than others are some days harder than others well yeah my work is fun but I also work hard and every big job has parts that are a lot more fun than others and so many days I'll say why do I have to have such high standards like why couldn't I just be sloppy and not try this out and you know just just report the answer but I but I know that people are conning me to do this and so okay so okay Donald grit my teeth and do it and and and then the joy comes out when I see that actually you know I'm getting good results and and and I get and I even more when I see that somebody has actually read and understood what I wrote and told me how to make it even better I did want to mention something about the about the method so I got this tablet here where I do the first you know the first writing of concepts okay so so and what language I didn't write so hey take a look at but you know here random say explain how to draw such skewed pixel diagrams okay so I got this paper about 40 years ago when I was visiting my sister in Canada and they make tablets of paper with this nice large size and just the right very small space between like oh yeah yeah particularly also just yeah you know I've got these manuscripts going back to the 60s and and and those are when I get my ideas on paper okay but I'm a good typist in fact I went to type in school when I was when I was in high school and so I can type faster than I think so then when I do the editing you know stand up and type then I then I revise this and it comes out a lot different than what you look for style and rhythm and things like that come out at the at the typing state and you type in tack and I type in tack and can you can you think in tech No so to a certain extent I have I have only a small number of idioms that I use like you know a beginning or theorem I do something for displayed equation I do something and and so on but I but I I have to see it and in the way that it's on here yeah right for example touring wrote what the other direction you don't write macros you don't think in macros particularly but when I need a macro I'll go ahead and and these and do it but but the thing is they I also write to fit I mean I'll I'll change something if I can if I can save a line I've got you know it's like haiku I'll figure out a way to rewrite the sentence so that it'll look better on the page and I shouldn't be wasting my time on that but but I can't resist because I know it's only another three percent of the time or something like that and it could also be argued that that is what life is about ah yes in fact that's true like like I worked in the garden one day a week and that's that's kind of a description of my life is getting rid of weeds you know removing bugs for programs in so you know a lot of writers talk about you know basically suffering the writing processes yeah having you know it's extremely difficult and I think of programming especially the or technical writing that you're doing can be like that do you find yourself methodologically how do you every day sit down to do the work is it a challenge you kind of say it's you know oh yeah it's fun but it'd be interesting to hear if there are non fun parts that you really struggle with yes the fun comes with when I'm able to put together ideas of to two people who didn't know about each other and and and so I might be the first person that saw both of their ideas and so then you know then I get to make the synthesis and that gives me a chance to be creative but the dredge work is where I act I've got a chase everything down to its root this leads me into really interesting stuff i mean like i learned about sanskrit nice yeah and again you know I try to give credit to all the authors and so I write like so I write to people who know that the people thought as if they're dead I communicate this way I and I gotta get the math right and I got a tack all my programs try to find holes in them and I rewrite the programs over after I get a better idea is there ever dead-ends data and so yeah I throw stuff out yeah look one of the things that I spent a lot of time preparing a major example based on the game of baseball and I know a lot of people who for whom baseball is the most important thing in the world you know yes but it's but I also know a lot of people from cricket is the most important in the world or suck or something you know and and I realized that if if I had a big sample I mean it was gonna have a fold-out illustration and everything I was saying well what what am I really teaching about algorithms here where I had this this is this baseball example and if I was a person who who knew only cricket wouldn't think what would they think about this and and so I ripped the whole thing out but I you know I had I had a something that would really appeal to people who grew up with baseball as as has a major theme in their life which is a lot of people but yeah so I said on minority the small minority I took out bowling to even a smaller my noise what's the art in the art of programming why why is there of the few words in the title why is art one of them yeah well that's that's what I wrote my Turing lecture about and and so when people talk about art it really I mean what the word means is something that's not a nature so when you have artificial intelligence that that art come from the same root saying that this is something that was created by by human beings and then it's gotten a further meaning often a fine art which has this beauty to the to the mix and says you know we have things that are artistically done and and this means not only done by humans but also done in a way that's elegant and brings joy and and has has I guess what Tolstoy burrs dusky but anyway it it's that part that that says that it's done well as well as not only a different from nature in general then alright is what human beings are specifically good at and when they say hey like artificial intelligence well they're trying to mimic human beings but there's an element of fine art and beauty you are well that's what I that's what I try to also say that you can write a program and make a work of art so now in terms of surprising you know what ideas in writing from sort and search to the combinatorial algorithms what ideas have you come across that were particularly surprising to you that that change the way you see a space of I get a surprise every time I have a bug in my program but but that isn't really what your transformational surprises for example in volume for a I was especially surprised when I learned about data structure called B BDD boolean decision diagram because I sort of had the feeling that as an old-timer and you know I've been programming since this since the 50s and bTW these weren't invented until 1986 and here comes a brand new idea that revolutionized the way to represent a boolean function and boolean functions are so basic to all kinds of things in it I mean logically underlies it everything we can describe all of what we know in terms of logic somehow and and here and and propositional logic I thought that was cutting Dryden everything was known but but but he but here comes a Randy Bryant and oh and discovers that BDDs are incredibly powerful then then that's all so I that mean means I have a whole new section to the book that I never would have thought of until 1986 not until 1990s when I went when people started to got to use it for you know billion dollar of applications and it was it was the standard way to design computers for a long time until until sad solvers came along when in the year 2000 so that's another great big surprise so uh a lot of these things have have totally changed the structure of my book and the middle third of volume four B's is about that solvers and that's 300 plus pages which is which is all about material mostly about material that was discovered in this century and I had to start from scratch and meet all the people in the field and right I have 15 different sets Alvers that i wrote while preparing that seven of them are described in the book others were for my own experience so newly invented data structures or ways to represent a whole new class of algorithm calling you classified yeah and the interesting thing about the BD DS was that the theoretician started looking at it and started to describe all the things you couldn't do with BD DS and so they were getting a bad they were getting a bad name because you know okay they were they were useful but they didn't solve everything I'm sure that the theoreticians are in the next 10 years are gonna show why machine learning doesn't solve everything but I not only worried about the worst case I get a huge delight when I can actually solve a problem that I couldn't solve before yeah even though I can't solve the problem that's that it suggests as a further problem like I know that I'm Way better than I was before and so I found out that BD DS could do all kinds of miraculous things and so I had been quite a few years learning about the that territory so in general what brings you more pleasure in proving or showing a worst case analysis of an algorithm or showing a good average case or just showing a good case that you know something good pragmatically can be done with this algorithm yeah I like a good case that that is maybe only a million times faster than I was able to do before but and not worried about the fact that and that is still that is still gonna take too long if I double the size of the problem so that said you popularize the asymptotic notation for describing running time obviously in the analysis of algorithms worst cases such as such an important part do you see any aspects of that kind of analysis is lacking so and notation - well the main purpose you have notations that that help us for the problems we want to solve and so that they match our they match our intuitions and people who worked in number theory had used asymptotic notation in what Ennis in a certain way but it was only known to a small group of people and and I realized that in fact it was very useful to be able to have a notation for something that we don't know exactly what it is but we only know partial about it and so on stick so for example instead of Big O notation let's just let's just take us a much simpler notation where I say 0 or 1 or 0 1 or 2 and suppose that suppose that when I had been in high school we would be allowed to put in the middle of our formula x + 0 1 or 2 equals y okay and then then we would learn how to multiply two such expressions together and and you know deal with them well the same thing Big O notation says here's something that's I'm not sure what it is but I know it's not too big I know it's not bigger than some constant times N squared or something like that fine so I write Big O of N squared and now I learned how to add Big O of N squared to Big O of N cubed and I know how to add Big O of N squared 2 plus 1 and square that and how to take logarithms and Exponential's to have big O's in the middle of them and that turned out to be hugely valuable in all of the work that I was trying to do is I'm trying to figure out how good so I have there been algorithms in your journey that perform very differently in practice than they do in theory well the worst case of a comet our logarithm is almost always horrible but but we have sad solvers that are solving where one of the one of the last exercises in that part of my book was to figure out a problem that has a hundred variables that's that's difficult for us at solver but uh but you would think that a problem with the hundred boolean variables has required to do 2 to the 100th operations because that's the number of possibilities when you have 200 boolean variables in 2 to the 100th to the 100th is way bigger than then we can handle 10 to the 17th is a lot you've mentioned over the past few years that you believe P may be equal to NP but that it's not really you know somebody does prove that P equals NP it will not directly lead to an actual algorithm to solve difficult problems can you explain your intuition here has it been changed and in general on the difference between easy and difficult problems of P and NP and so on yes so the popular idea is if an algorithm exists then somebody will find it and it's just a matter of writing it down one point well but many more algorithms exist than anybody can end understand or ever make you discover yeah because they're just way beyond human comprehension of the total number of algorithms is more than mind-boggling so so we have situations now where we know that algorithm exists but we don't know we don't the foggiest idea what the algorithms are there's there are simple examples based on on game playing where you have where you say well there must be an algorithm that exists to win in the game of hex because for the first player to win in the game of hex because hex is always either an a win for the first player of the second player well what's the game of hack there's a game of hex which is which based on putting pebbles onto a hexagonal board and and the white player tries to get a light path from left to right and the black player tries to get a black path from bottom to top and how does capture occur just so and and and there's no capture you just put levels down what one at a time but there's no drawers because they after all the white and black are played there's either going to be a white path across from each to west or a black path from from bottom to top so there's always you know it's the perfect information game and people people play take turns like like tic-tac-toe and hex or it can be different sizes but we there's no possibility of a draw and player to move one at a time and so it's got to be either a first player win or a second player win mathematically you follow out all the trees and and either either there's always the win for the percolator second player okay and it's finite the game is finite so there's an algorithm that will decide you can show it has to be one of the other because the second player could mimic the first player with kind of a pairing strategy and so you can show that it has to be what it has to be one or that but we don't know any algorithm no way there there a case where you can prove the existence of the solution but we but nobody knows anyway how to find it but more like the algorithm question there's a very powerful theorem and graph theory by Robinson to see more that says that every class of graphs that is closed under taking minors has a polynomial time algorithm to determine whether it's in this class or not now a class of graphs for example planar graphs these are graphs that you can draw in a plane without crossing lines and and a planar graph is close taking minors means that you can shrink an edging into a point or you can delete an edge and so you start with a planar graph and drink any edge to a point is still planar deleting edges to a planner okay now but there are millions of different ways to describe family of graph that still is remains the same undertaking minor and Robertson Nassim are proved that any such family of graphs there is a finite number of minimum graphs that are obstructions so that if it's not in the family then then it has to contain then there has to be a way to shrink it down and until you get one of these bad minimum graphs that's not in the family for in plate case for planar graph the minimum graph is a is a five-pointed star where there everything pointed to another and the minimum graph consisting of trying to connect three utilities to three houses without crossing lines and so there are two there are two bad graphs that are not planar and every every non planar graph contains one of these two bad graphs by by shrinking and he said again so he proved that there's a finite number of these bad guys always a finite know somebody says here's a family it's hard to believe and they present its sequence of 20 papers I mean in there it's deep work but it you know it's because that's for any arbitrary class so it's for any arbitrary class that's closed under taking minors that's closed under maybe I'm not understanding because it seems like a lot of them are closed taking minors almost all the important classes of graphs are there are tons of of such graphs but also hundreds of them that arise in applications like I have a book over here called classes of graphs and then and it it's amazing how many different classes people have looked at so why do you bring up this theorem lower this proof so you know there are lots of algorithms that that are known for special class of graphs for example if I have a certain if I have a chordal graph then I can color it efficiently if I have some kinds of graphs it'll make a great Network very soon like you'd like to test you somebody gives you a graph that's always it in this family of grass if so then I hope then I can I can go to the library and find an algorithm that's gonna solve my problem on that graph okay so we we have we want to have a graph that says number than that says give me a graph I'll tell you whether it's and whether it's in this family or not okay and so all I have to do is test whether or not that does this given graph have a minor that's one of the bad ones a minor is is everything you can get by shrinking and removing edges and given any minor there's a polynomial time algorithm saying I can tell whether this is a minor of you and there's a finite number of bad cases so I just tried you know does it have this bad case by polynomial time I got the answer does he have this bad case probably time I got the answer a total polynomial time and so I've solved the problem however all we know is that the number of minors is finite we don't know what we might only know one or two of those minors but we don't know that if we got it if we got 20 of them we don't know there might be 20 125 the Halloween all we know is that is that it's finite so here we have a polynomial time algorithm that we don't know mm-hm that's a really great example of what you worry about or why you think P equals NP won't be useful but still why do you hold the intuition that P equals NP because you have to rule out so many possible algorithms have been not working you know you can you can take the graph and you can represent it as in terms of certain prime numbers and then you can multiply those together and then you can then you can take the bitwise and and and you know and construct some certain constant in polynomial time and then that's you know perfectly valid algorithm and that there's so many algorithms of that kind a lot of times we see random you take data and and and we get coincidences that that that some fairly random looking number actually is useful because because it god it happens to it happens to self it happens to solve a problem just because you know there's there's so many hairs on your head but it seems like unlikely that two people are going to have the same number of hairs on their head but but they're obvious but you can count how many people there are and how many hairs on there so there must be people walking around in the country to have the same number of hairs on their head well that's the kind of a coincidence that you might say also you know this this particular combination of operations just happens to prove that a graph is has a Hamiltonian path and I see lots of cases where unexpected things happen when you have enough enough possibilities but because the space of possibility is so huge I have to rule them all out and so that's the reason for my intuition is good by no means approve I mean some people say you know well P can't equal NP because you've had all these smart people you know the smartest designers of algorithms that have been wrecking their brains for years and years and and there's million-dollar prizes out there and you know none of them nobody has thought of the algorithm so it must must be no such job on the other hand I can use exactly the same logic and I can say well P must be equal to NP because there's so many smart people out here been trying to prove it unequal to NP and they've all failed you know this kind of reminds me of the discussion about the search for aliens they've been trying to look for them and we haven't found them yet therefore they don't exist yeah but you can show that there's so many planets out there that they very possibly could exist yeah and right and then there's also the possibility that that they exist but they they all discovered machine learning or something and and and then blew each other up well on that small quick danger let me ask do you think there's intelligent life out there in the universe I have no idea do you hope so do you think about it it I I don't I don't spend my time thinking about things that I could never know really and yet you do enjoy the fact that there are many things you don't know you do enjoy the mystery of things I enjoy the fact that there that I have limits yeah but I don't but but I don't take time to answer unsolvable questions I got it well because you've taken on some tough questions that may seem unsolvable you have taken on some tough questions and you seem unsolvable if there is because we are thrilled when I can get further than I ever thought I could right yeah but but I don't what much like was religion these I'm glad the dirt that that there are no proof that God exists or not I mean I think it would spoil the mystery it it would be too dull yeah so to quickly talk about the other art of artificial intelligence what is if you what's your view you know artificial intelligence community has developed as part of computer science and in parallel with computer science since the 60s what's your view of the AI community from the 60s to now so all the way through it was the people who were inspired by trying to mimic intelligence or to do things that that were somehow the greatest achievements of intelligence that had been inspiration to people who have pushed the envelope of computer science maybe more than any other group of people so it's all the way through it's been a great source of of good problems to to sink teeth into and and getting getting partial answers and then more and more successful answers over the year so this has this has been the inspiration for lots of the great discoveries of computer science are you yourself captivated by the possibility of creating of algorithms having echoes of intelligence in them not as much as most of the people in the field I guess I would say but but that's not to say that they're wrong or that it's just you asked about my own personal preferences and yeah but but the thing that I that I worry about is when people start believing that they've actually succeeded and because the seems to me this huge gap between really understanding something and being able to pretend to understand something and give these give the illusion of understanding something do you think it's possible to create without understanding yeah so to uh I do that all the time to run I mean that's why I use random members I like yeah but I but but there's there's still what this great gap I don't know certain it's impossible but I'm like but I don't see a anything coming any closer to really the the kind of stuff that I would consider intelligence say you've mentioned something that on that line of thinking which I very much agree with so the art of computer programming as the book is focused on single processor algorithms and for the most part and you mentioned that's only because I set the table of contents in 1962 you have to remember for sure there's no I'm glad I didn't wait until 1965 or one book maybe will touch in the Bible but one book can't always cover the entirety of everything so I'm glad yeah I'm glad the the table of contents for the art of computer programming is what it is but you did mention that that you thought that an understanding of the way ant colonies are able to perform incredibly organized tasks might well be the key to understanding human cognition so these fundamentally distributed systems so what do you think is the difference between the way Don Knuth would sort a list and an ant colony would sort a list or performing algorithm sorting a list isn't same as cognition though but but I know what you're getting at is well the advantage of ant colony at least we can see what they're doing we we know which ant has talked to which other ant and and and and it's much harder with the quick brains to just to know how to what extent of neurons are passing signal so I understand that aunt Connie might be a if they have the secret of cognition think of an ant colony as a cognitive single being rather than as a colony of lots of different ants I mean just like the cells of our brain are and and the microbiome and all that is interacting entities but but somehow I consider myself to be single person well you know aunt Connie you can say might be cognitive is somehow and it's yeah I mean you know I okay I like I smash a certain aunt and mmm that's stung what was that right you know but if we're going to crack the the the secret of cognition it might be that we could do so by but my psyche note how ants do it because we have a better chance to measure and they're communicating by pheromones and by touching each other and sight but but not by much more subtle phenomenon Mike electric currents going through but even a simpler version of that what are your thoughts of maybe Conway's Game of Life okay so Conway's Game of Life is is able to simulate any any computable process and any deterministic process is like how you went there I mean that's not its most powerful thing I would say I mean you can simulate it but the magic is that the individual units are distributed yes and extremely simple yes we can we understand exactly what the primitives are the permit is the just like with the anthology even simple but if we but still it doesn't say that I understand I understand life I mean I understand it it gives me an it gives me a better insight into what does it mean to to have a deterministic universe what does it mean to to have free choice for example do you think God plays dice yes I don't see any reason why God should be forbidden from using the most efficient ways to to to I mean we we know that dice are extremely important and inefficient algorithms there are things like that couldn't be done well without randomness and so I don't see any reason why my god should be prohibited but when the when the algorithm requires it you don't see why the know the physics should constrain it yeah so in 2001 you gave a series of lectures at MIT about religion and science well that would 1999 but you published the book came out in Cooper so in 1999 you spent a little bit of time in Boston enough to give those lectures yeah and I read in the 2001 version that most of it it's quite fascinating read I recommend people its transcription of your lectures so what did you learn about how ideas get started and grow from studying the history of the Bible sieve rigorously studied a very particular part of the Bible what did you learn from this process about the way us human beings as a society develop and grow ideas share ideas and I'm by those idea I I tried to summarize that I wouldn't say that I that I learned a great deal of really definite things like right where I could make conclusions but I learned more about what I don't know you have a complex subject which is really beyond human understanding so so we give up on saying I'm never going to get to the end of the road and I'm never going to understand it but you say but but maybe it might be good for me to to get closer and closer and learn more about more and more about something and so you know oh how can I do that efficiently and the answer is well use randomness and so to try a random subset of the that that is within my grasp and and and and study that in detail instead of just studying parts that somebody tells me to study or instead of studying nothing because it's too hard so I I i decided for my own amusement that one ones that I would I would take a subset of the of the verses of the Bible and I would try to find out what the best thinkers have said about that small subset and I had had about let's say 660 verses out of out of 3,000 I think it's one out of 500 or something like this and so then I went to the libraries which which are well indexed uh you can you you know I spent for example at at Boston Public Library I I would go once a week for a year and I went to I went I have done time stuff and over Harvard library to look at this yes that weren't in the Boston Public where they where scholars had looked at and you can call in the eight and you can go down the shelves and and you can pretty you can look at the index and say oh there it is this verse I mentioned anywhere in this book if so look at page 105 so I was like I could learn not only about the Bible but about the secondary literature about the Bible the things that scholars have written about it and so that that gave me a way to uh to zoom in on parts of the things so that I could get more more insight and and so I look at it as a way of giving me some firm pegs which icon which I could hang pieces of information but not as as things where I would say and therefore this is true in this random approach of sampling the Bible what did you learn about the the most you know central oh one of the biggest accumulation of ideas you know to me that the that the main thrust was not the one that most people think of as saying you know you know don't have sex or something like this but that the main thrust was to try to to try to figure out how to live in harmony with God's wishes I'm assuming that God exists and I say I'm glad that I that there's no way to prove this because that would that would I would run through the proof once and then I'd forget it and and it would and and I would never just speculate about spiritual things and mysteries otherwise and I think my life would be very incomplete so I so I'm assuming that God exists but it if but a lot of things the people say God doesn't exist but that's still important to them and so in a way in a way that might still be other God is there or not in some sense so it it guys important to them it's one of the one of the verses I studied act is you can interpret as saying you know it's much better to be an atheist that not to care at all so I would say it's yeah it's similar to the P equals NP discussion yeah you you mentioned a mental exercise that I'd love it if you could partake in yourself a mental exercise of being God and so how would you if you were God dot Knuth how would you present yourself to the people of Earth you mentioned your love of literature and there was it there's this book that would that really uh I can recommend to you if I can't think yeah the title I think is blasphemy it talks about God revealing himself through a computer in in in Los Alamos and and it it's the only book that I've ever read where the punchline was really the very last word of the book and it explained the whole idea of the book and so I don't want to give that away but it but it's really very much about this question that that she raised but but suppose God said okay that my previous on means of communication with the world are and not the best for the 21st century so what should I do now and and and it's conceivable that that it would that that God would choose the way that's described in this book and another way to look at this exercise is looking at the human mind looking at the human spirit the human life in a systematic way I think it mostly you want to learn humility you want to realize that once we solve one problem that doesn't mean it worked at all so no other problems are going to drop out and and and and we have to realize that that that there are there are things beyond our beyond our ability I see hubris all around yeah well said if you were to run program analysis on your own life how did you do in terms of correctness running time resource use asymptotically speaking of course okay yeah well I would say that question has not been asked me before and i i i started out with library subroutines and and learning how to be a automaton that was obedient and i had the great advantage that i didn't have anybody to blame for my failures if I started getting not understanding something I I knew that I should stop playing ping pong and that was that into it was my fault that I was that I wasn't studying hard enough or something rather than that somebody was discriminating against me in some way and I don't know how to avoid this the existence of biases in the world but i but i but i know that that's an extra burden that i didn't have to suffer from and and and then i I found the from from parents I learned the idea of of altruist to other people as being more important than then when I get out of stuff myself I you know that I need to I need to be happy enough enough in order to be able to speed up service but I thought but I you know but I I came to a philosophy for finally that that I phrased as point eight is enough there was a TV show once called hate is enough which was about a you know somebody had eight kids but but I I say point a is enough which means if I can have a way of rating happiness I think it's good design that to have to have an organism that's happy about eighty percent of the time and if it was a hundred percent of the time it would be like every like everybody's on drugs and and never and and and and everything collapses nothing works because everybody's just too happy do you think you've achieved that point eight optimal work there are times when I when I'm down and I you know and I think I mean I know that I'm chemically right I know that I've actually been programmed to be I to be depressed a certain amount of time and and and if that gets out of kilter and I'm more depressed and you know sometimes like like I find myself trying to say now who should I be mad at today there must be a reason why but I but then I realize you know it's just my it's just my chemistry telling me that I'm supposed to be mad at somebody and so and so I triggered up say okay go to sleep and get better but but if I'm but if I'm not a hundred percent happy that doesn't mean that I should find somebody that that's screaming and and try to size them up but I'd be like I'm saying you know okay I'm not 100% happy but but I'm happy enough to death to be a you know part of a sustainable situation so so that's kind of the numerical analysis I do you invert stores the human life is a point eight yeah I hope it's okay to talk about as you talked about previously in two thousand six six you were diagnosed with prostate cancer has that encounter with mortality changed you in some way or the way you see the world the first encounter with mortality with Mike when my dad died and I I went through a month when I sort of came to kink you know be comfortable with the fact that I was going to die someday and during that month I don't know I I felt okay but I couldn't sing and you know I and I and I couldn't do original research either like tighten right I sort of remember after three or four weeks the first time I started having a technical thought that made sense and was maybe slightly creative I could sort of feel they know that and that something was starting to move again but that was you know so I felt very empty for until I came to grips with the I yes I learned that this is a sort of a standard grief process that people go through ok so then now I'm at a point in my life even more so than in 2006 where where all of my go have been fulfilled except for finishing narrative computer programming i I I had one made unfulfilled goal that I'd wanted all my life to write a piece of a piece piece of music that and I had an idea for for a certain kind of music that I thought ought to be written at least somebody ought to try to do it and I and I felt that it was a that it wasn't going to be easy but I wanted to I wanted it proof of concept I wanted to know if it was going to work or not and so I spent a lot of time and finally I finished that piece and we had the we had the world premiere last year on my 80th birthday and we had another premiere in Canada and there's talk of concerts in Europe and various things so that but that's done it's part of the world's music now and it's either good or bad but I did what I was hoping to do so the only thing that I know that that I have on my agenda is to is to try to do as well as I can with the art of computer programming until I go see now do you think there's an element of point eight that might point eight yeah well I look at it more that I got actually took 21.0 with when that concert was over with I mean I you know I so in 2006 I was at point eight um so when I was diagnosed with prostate cancer then I said okay well maybe this is yet you know I've I've had all kinds of good luck all my life and there's no I'm nothing to complain about so I might die now and we'll see what happened and so so it's quite seriously I went and I didn't I had no expectation that I deserved better I didn't make any plans for the future I had my surgery I came out of the surgery and and spend some time learning how to walk again and so on is painful for a while but I got home and I realized I hadn't really thought about what what to do next I hadn't I hadn't any expectation and I'm still alive okay now I can write some more books but it but I didn't come with the attitude that you know I you know this was this was terribly unfair and and I just said okay I was accepting whatever it turned out you know I look like I gotten I got more than my shirt already so why should I and I didn't and I really when I got home I read I realized that I had really not thought about the next step what I would do after I would doubt after I would be able to work and I had sort of thought of it as if as this might you know I was comfortable with with the fact that it was at the end but but I was hoping that I would still you know be able to learn about satisfiability and and also someday even write music I didn't start I didn't started seriously on the music project until 2012 so I'm gonna be in huge trouble if I don't talk to you about this in in the 70s you've created the tech typesetting system together with meta font language for font description and computer modern family of typefaces that has basically defined the methodology in the aesthetic of the countless research fields right math physics well beyond design and so on okay well first of all thank you I think I speak for a lot of people in saying that but question in terms of beauty there's a beauty to typography that you've created and yet beauty is hard to five right how does one create beautiful letters and beautiful equations like what what so I mean perhaps there's no words to be describing you know be described in the process but so the great Harvard mathematician Georg deeper cut wrote a book in the 30s called the aesthetic measure rate where he would have pictures of vases and underneath would be a number and this was how beautiful the vase was and he had a formula for this and and he actually also right over brought about music and so he could he could you know so I thought maybe I would part of my musical composition I would try to program his algorithms and and you know so that I would I would write something that had the highest number by his score well it wasn't quite rigorous enough work for a computer to to do but anyway people have tried to put numerical value on beauty but and and he did probably the most serious attempt and and George Gershwin's teacher also wrote two volumes where he talked about his method of of composing music but but you're talking about another kind of beauty and beauty and letters and letter fell against and whatever that overture is right so so and so that's the beholder as they say but kinder striving for excellence in whatever definition you want to give to beauty then you try to get as close to that as you can somehow with it I guess I guess I'm trying to ask and there may not be a good answer what loose definitions were you're operating under with the community of people that you're working on oh the loose definition I wanted I wanted it to appeal to me to me I knew you personally yeah that's a good start yeah no and it failed that test went when I got volume two came out with this with the new printing and I was expecting to be the happiest day of my life and I felt like burning like how angry I was that I opened the book and it it was in the same beige covers and and but but it didn't look right on the page the number two was particularly ugly I couldn't stand any page that had a to in his page number and I was expecting that it was you know I spent all this time making measurements and I and I had Kent had looked at dolphins in different different ways and I hate I had great technology but but it did you know but I but I wasn't done I had I had to retune the whole thing after 1961 has it ever made you happy finally oh oh yes or is it appointing oh no no and so many books have come out that would never have been written without this I just didn't just draw it's just it's a joy but I could but now I I mean all these pages that are sitting up there I don't have a it if I didn't like him I would change him like that's my nobody else has this ability they have to stick with what I gave them yes so in terms of the other side of it there's the typography so the look of the top of the type and the curves and the lines what about the spacing but what about the spacing because you know the white space you know it seems like you could be a little bit more systematic about the layout or oh yeah you can always go further III I didn't I didn't stop at point eight I stopped I stopped about point nine eight seems like you're not following your own rule for happiness or is no no no I there's okay the course there's just what is the Japanese word wabi-sabi or something they wear the the most beautiful works of art are those that have flaws because then the person who who perceives them as their own appreciation and that gives the viewer more satisfaction or a so on but but I but no no with typography I wanted it to look as good as I could in in the vast majority of cases and then when it doesn't then I I say okay that's 2% more work for the wrote for the author but but I didn't want to I didn't want to say that my job was to get 200% with and take all the work away from the author that's what I meant by that so if you were to venture a guess how much of the nature of reality do you think we humans understand so you mentioned you appreciate mystery how much of the world about us is shrouded in mystery are we are we if you were to put a number on it what what percent of it all do we understand oh we totally how many leading zeroes any point zero point zero zero there I don't know now I think it's infinitesimal how do we think about that what do we do about that do we continue one step at a time yeah we muddle through I mean we do our best we realized that one that nobody's perfect then we and we try to keep advancing but we don't spend time saying we're not there we're not all the way to the end some some mathematicians that that would be in the office next to me when I was in the math department they would never think about anything smaller than countable infinity and I never you know we intersect that countable infinity because I really got up to countable infinity I was always talking about finite stuff but but even even limiting to finite stuff which was which is which the universe might be there's no way to really know what whether the universe is in isn't just made out of capital in whenever you want to call them quarks or whatever where capital n is some fun a number all of the numbers that are comprehensible are still way smaller than most almost all finite numbers III I got this one paper called supernatural numbers where I what I guess you've probably ran into something called Knuth arrow notation did you ever run into that where anyway so you take the number I think it's like I and I called it super K but I named it after myself but it's it's but in arrow notation is something like ten and then four arrows and a three or something might not okay no the arrow notation if you have if you have no arrows that means multiplication XY means x times X times X times X Y times if you have one arrow that means exponentiation so x one arrow Y means X to the X to the X to the X to the X Y times so I find out by the way that this is notation was invented by a guy in 1830 and and he was like he was a a a [Music] one of the English nobility who who spent his time thinking about stuff like this and it was exactly the same concept that I that I'm that I used arrows and he used a slightly different notation but anyway this and then this Ackerman's function is is based on the same kind of ideas but Ackerman was 1920s but anyway you got this number 10 quadruple arrow 3 so that's that says well we take you know we take 10 to the 10 to the 10 to the 10 to the 10 to the 10th anyway how many times do we do that oh Ken double arrow two times or something I mean how tall is that stack but but but then we do that again because that was the only 10 triple quadruple arrow to we take quadruple three large number it gets way beyond comprehension okay yeah and and and so but it's so small compared to what finite numbers really are because I want to using four arrows and you know in ten and a three I mean let's have that let's have that many number arrows I mean the boundary between infinite and finite is incomprehensible for us humans anyway infinity is a good is a useful way for us to think about extremely large extremely large things and and and and we we can manipulate it but but we can never know that the universe is actually and we're near that so it just so I realize how little we know but but but what we we found an awful lot of things that are too hard for any one person to know even with even in our small universe yeah and we did pretty good so when you go up to heaven and meet God and get to ask one question that would get answered what question would you ask what kind of browser do you have up here [Laughter] [Music] okay and then oh that's beautiful actually Don thank you so much it was a huge honor to talk to you I really well thanks for the gamut of questions yeah it was fun thanks for listening to this conversation with donald knuth thank you to our presenting sponsor cash app downloaded use cold Luck's podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from donald knuth we should continually be striving to transform every art into a science and in the process we advance the art thank you for listening and hope to see you next time you |
Melanie Mitchell: Concepts, Analogies, Common Sense & Future of AI | Lex Fridman Podcast #61 | the following is a conversation with Melanie Mitchell she's the professor of computer science at Portland State University and an external professor at Santa Fe Institute she has worked on and written about artificial intelligence from fascinating perspectives including adaptive complex systems genetic algorithms and the copycat cognitive architecture which places the process of analogy making at the core of human cognition from her doctoral work with her advisers Douglas Hofstadter and John Holland - today she has contributed a lot of important ideas to the field of AI including her recent book simply called artificial intelligence a guide for thinking humans this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars on Apple podcast supported on patreon or simply connect with me on Twitter at Lex Friedman spelled Fri D ma n I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation I hope that works for you it doesn't hurt the listening experience I provide time stamps for the start of the conversation but it helps if you listen to the ad and support this podcast by trying out the product the service being advertised this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member s IBC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and charity navigator which means that donated money is used to maximum effectiveness when you get cash app from the App Store or Google Play and use code Lex podcast you'll get ten dollars in cash up will also donate ten dollars the first which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with Melanie Mitchell the name of your new book is artificial intelligence subtitle a guide for thinking humans the name of this podcast is artificial intelligence so let me take a step back and ask the old Shakespeare question about roses and what do you think of the term artificial intelligence for our big and complicated and interesting field I'm not crazy about the term I think it has a few problems because it it's means so many different things to different people and intelligence is one of those words that isn't very clearly defined either there's so many different kinds of intelligence degrees of intelligence approaches to intelligence John McCarthy was the one who came up with the term artificial intelligence and what from what I read he called it that to differentiate it from cybernetics which was another related movement at the time and he later regretted calling it artificial intelligence Herbert Simon was pushing for calling it complex information processing which got nixed but you know probably is equally vague I guess is it the intelligence or the artificial in terms of words that it's the most problematic you would you say yeah I think it's a little of both but you know it has some good size because I personally was attracted to the field because I was interested in phenom phenomenons of intelligence and if it was called complex information processing maybe I'd be doing something wholly different now what do you think of I've heard the term used cognitive systems for example so using cognitive yeah I mean cognitive has certain associations with it and people like to separate things like cognition and perception which I don't actually think are separate but often people talk about cognition is being different from sort of other aspects of intelligence it's sort of higher level so to you cognition is this broad beautiful mess of things that's in calm the whole thing memory yeah I I think it's hard to draw lines like that when I was coming out of grad school in the night in 1990 which is when I graduated that was during one of the AI winters and I was advised to not put AI artificial intelligence on my CV but instead call it intelligent systems so that was kind of a euphemism I guess what about the stick briefly on on terms and words the idea of artificial general intelligence or or like beyond Laocoon prefers human level intelligence sort of starting to talk about ideas that that achieve higher and higher levels of intelligence and somehow artificial intelligence seems to be a term used more for the narrow very specific applications of AI and sort of the there's the what set of terms appeal to you to describe the thing that perhaps would strive to create people have been struggling with this for the whole history of the field and defining exactly what it is that we're talking about you know John Searle had this distinction between strong AI and weak AI and weak AI could be generally AI but his idea was strong AI was the view that a machine is actually thinking that as opposed to simulating thinking or carrying out intelligent processes that we would call intelligent high level if you look at the founding of the field of McCarthy in sterlin and so on are we closer to having a better sense of that line between narrow weak AI and strong AI yes I think we're closer to having a better idea of what that line is early on for example a lot of people thought that playing chess would be you couldn't play chess if you didn't have sort of general human level intelligence and of course once computers were able to play chess better than humans that revised that view and people said ok well maybe now we have to revise what we think of intelligence as or and and so that's kind of been a theme throughout the history of the field is that once a machine can do some task we then have to look back and say oh well that changes my understanding of what intelligence is because I don't think that machine is intelligent at least that's not what I want to call intelligence do you think that line moves forever or will we eventually really feel as a civilization like we cross the line if it's possible it's hard to predict but I don't see any reason why we couldn't in principle create something that we would consider intelligent I don't know how we will know for sure maybe our own view of what intelligence is will be refined more and more until we finally figure out what we mean when we talk about it but I I think eventually we will create machines in a sense that have intelligence they may not be the kinds of machines we have now and one of the things that that's going to produce is is making us sort of understand our own machine like qualities that we in a sense are mechanical in the sense that like an eles cells are kind of mechanical they part they have algorithms they process information by and somehow out of this mass of cells we get this emergent property that we call intelligence but underlying it is really just cellular processing and and lots and lots and lots of it do you think we'll be able to do you think it's possible to create intelligence without understanding our own mind you said sort of in that process we'll understand more and more but do you think it's possible to sort of create without really fully understanding from a mechanistic perspective sort of from a functional perspective how our mysterious mind works if I had to bet on it I would say no we we we do have to understand our own minds at least to some significant extent but it I think that's a really big open question I've been very surprised at how far kind of brute force approaches based on say big data and huge networks can can take us I wouldn't have expected that and they have nothing to do with the way our minds work so that's been surprising to me so it could be wrong to explore the psychological and the philosophical do you think we're okay as a species with something that's more intelligent than us do you think perhaps the reason we're pushing that line farther and farther is we're afraid of acknowledging that there's something stronger better smarter than us humans well I'm not sure we can define intelligence that way because you know smarter then is with with respect to what what you know computers are already smarter than us in some areas they could multiply much better than we can they they can figure out driving routes to take much faster and better than we can they have a lot more information to draw on they know about you know traffic conditions and all that stuff so for any given particular task sometimes computers are much better than we are and we're totally happy with that right I'm totally happy with that I don't doesn't bother me at all I guess the question is you know what which things about our intelligence would we feel very sad or or upset that machine's had been able to recreate so in the book I talk about my former PhD advisor Douglas Hofstadter who encountered a music generation program and that was really the line for him that if a machine could create beautiful music that would be terrifying for him because that is something he feels is really at the core of what it is to be human creating beautiful music art literature I you know I don't think he doesn't like the fact that machines can recognize spoken language really well like he doesn't he personally doesn't like using speech recognition I don't think it bothers him to his core because it's like okay that's not at the core of humanity but it may be different for every person what what really they feel would usurp their humanity and I think maybe it's a generational thing also maybe our children or our children's children will be adapted they'll adapt to these new devices that can do all these tasks and and say yes this thing is smarter than me in all these areas but that's great because it helps me looking at the broad history of our species why do you think so many humans have dreamed of creating artificial life and artificial intelligence throughout the history of our civilization so not just this century or the 20th century but really many throughout many centuries that preceded it that's a really good question and I have wondered about that because I'm I myself you know was driven by curiosity about my own thought processes and thought it would be fantastic to be able to get a computer to mimic some of my thought process season I'm not sure why we're so driven I think we want to understand ourselves better and we also want machines to do things for us but I don't know there's something more to it because it's so deep in in the kind of Mythology or the dose of our species and I don't think other species have this drive so I don't know if you were to sort of psychoanalyze yourself and you're in your own interest in AI are you what excites you about creating intelligence you said understanding our own selves yeah I think that's what drives me particularly I'm really interested in human intelligence but I'm all I'm also interested in the sort of the phenomenon of intelligence more generally and I don't think humans are the only thing with intelligence you know I or even animals that I think intelligence is a concept that encompasses a lot of complex systems and if you think of things like insect colonies or cellular processes or the immune system or all kinds of different biological or even societal processes have as an emergent property some aspects of what we would call intelligence you know they have memory they do in process information they have goals they accomplish their goals etc and to me that the question of what is this thing we're talking about here was really fascinating to me and and exploring it using computers seem to be a good way to approach the question so do you think kind of intelligence do you think of our universes a kind of hierarchy of complex systems and then intelligence is just the property of any you can look at any level and every level has some aspect of intelligence so we're just like one little speck in that giant hierarchy of complex systems I don't know if I would say any system like that has intelligence but I guess what I want to I don't have a good enough definition of intelligence to say that so let me let me do sort of multiple choice I guess though so you said ant colonies so our ant colonies intelligent are the bacteria in our body in intelligent and then look going to the physics world molecules and the behavior at the quantum level of of electrons and so on is are those kinds of systems do they possess intelligence like words where's the line that feels compelling to you I don't know I mean I think intelligence is a continuum and I think that the ability to in some sense have intention have a goal have a some kind of self-awareness is part of it so I'm not sure if you know it's hard to know where to draw that line I think that's kind of a mystery but I wouldn't say that say that you know this the planets orbiting the Sun her is an intelligent system I mean I would find that maybe not the right term to describe that and this is you know there's all this debate in the field of like what's what's the right way to define intelligence what's the right way to model intelligence should we think about computation should we think about dynamics and should we think about you know free energy and all of that stuff and I think that it's it's a fantastic time to be in the field because there's so many questions and so much we don't understand there's so much work to do so are we are we the most special kind of intelligence this kind of you said there's a bunch of different elements and characteristics of intelligent systems and colonies are his human intelligence the thing in our brain is that the most interesting kind of intelligence in this continuum well it's interesting to us because because it is us I mean interesting to me yes and because I'm part of the you know human but to understanding the fundamentals of intelligence what I'm yeah yeah Jerry is studying the human is sort of if everything we've talked about will you talk about in your book what just the AI field this notion yes it's hard to define but it's usually talking about something that's very akin to human intelligence to me it is the most interesting because it's the most complex I think it's the most self-aware it's the only system at least that I know of that reflects on its own intelligence and you talk about the history of AI and us in terms of creating artificial intelligence being terrible at predicting the future or the Iowa tech in general so why do you think we're so bad at predicting the future are we hopelessly bad so no matter what well there's this decade or the next few decades every time I make a prediction there's just no way of doing it well or as the field matures we'll be better and better at it I believe as the field matures we will be better and I think the reason that we've had so much trouble is that we have so little understanding of our own intelligence so there's the famous story about Marvin Minsky assigning computer vision as a summer project to his undergrad students and I believe that's actually a true story ya know there's a there's a write-up on it everyone should read it's like a I think it's like a proposal this describes everything done in that project is hilarious because that I mean you can explain it but for my sort of recollection it described is basically all the fundamental problems of computer vision many of which they still haven't been solved yeah and and I don't know how far they really expected to get but I think that and and they're really you know Marvin Minsky is super smart guy and very sophisticated thinker but I think that no one really understands or understood still doesn't understand how complicated how complex the things that we do are because they're so invisible to us you know to us vision being able to look out at the world and describe what we see that's just immediate it feels like it's no work at all so it didn't seem like it would be that hard but there's so much going on unconsciously sort of invisible to us that I think we overestimate how easy it will be to get computers to do it and sort of for me to ask an unfair question you've done research you've thought about many different branches of AI and through this book widespread looking at where AI has been where it is today what if you were to make a prediction how many years from now would we as a society create something that you would say achieved human level intelligence or superhuman level intelligence that is an unfair question a prediction that will most likely be wrong so but it's just your notion because okay I'll say I'll say more than a hundred years more than a hundred years and there I quoted somebody in my book who said that human level intelligence is a hundred Nobel Prizes away which I like because it's a it's a nice way to to sort of it's a nice unit for prediction and it's like that many fantastic discoveries have to be made and of course there's no Nobel Prize in if we look at that hundred years your senses really the journey to intelligence has to go through something something more complicated as again to our own cognitive systems understanding them being able to create them in in the artificial systems as opposed to sort of taking the machine learning approaches of today and really scaling them and scaling them and scaling them exponentially with both computing hardware and and data that would be my that would be my guess you know I think that in in the the sort of going along in the narrow AI that these current the current approaches will get better you know I think there's some fundamental limits to how far they're gonna get I might be wrong but that's what I think but and there's some fundamental weaknesses that they have that I talked about in the book that that just comes from this approach of supervised learning we require requiring sort of feed-forward networks and so on it it's just I don't think it's a sustainable approach to understanding the world yeah I'm I'm personally torn on it sort of I've everything read about in the book and sort of we're talking about now I agreed I agree with you but I'm more and more depending on the day first of all I'm deeply surprised by the successful machine learning and deep learning in general and from the very beginning that when I was it's really been many focus of work I'm just surprised how far it gets and I'm also think we're really early on in these efforts of these narrow AI so I think there will be a lot of surprise off how far it gets I think will be extremely impressed like my senses everything I've seen so far and we'll talk about autonomous driving and so on I think we can get really far but I also have a sense that we will discover just like you said is that even though we'll get really far in order to create something like our own intelligence is actually much farther than we realized right I think these methods are a lot more powerful than people give them credit for actually so that of course there's the media hype but I think there's a lot of researchers in the community especially like not undergrads right but like people who've been in AI they're skeptical about how far deep learning yet and I'm more and more thinking that it can actually get farther than I realize it's certainly possible one thing that surprised me when I was writing the book is how far apart different people are in the field are artisan their opinion of how how far the field has come and what is accomplished and what's what's gonna happen next what's your sense of the different who are the different people groups mindsets thoughts in the community about where AI is today yeah they're all over the place so so there's there's kind of the the singularity transhumanism group I don't know exactly how to characterize that approach which is there as well yeah the sort of exponential exponential progress we're on the sort of almost at the the hugely accelerating part of the exponential and by in the next 30 years we're going to see super intelligent AI and all that and we'll be able to upload our brains and that so there's that kind of extreme view that most I think most people who work in AI don't have they disagree with that but there are people who who are maybe don't aren't you know singularity people but but they're they do think that the current approach of deep learning is going to scale and is going to kind of go all the way basically and take us to ái or human-level AI or whatever you want to call it and there's quite a few of them and a lot of them like a lot of the people I've met who work at big tech companies in AI groups kind of have this view that we're really not that far you know just to linger on that point sort of if I can take as an example like Yannick kun I don't know if you know about his work and so a few points unless I do he believes that there's a bunch of breakthroughs like fundamental like Nobel Prizes there's yeah he did still write but I think he thinks those breakthroughs will be built on top of deep learning right and then there's some people who think we need to kind of put deep learning to the side a little bit as just one module that's helpful in the bigger cognitive framework right so so I think some what I understand yan laocoön is rightly saying supervised learning is not sustainable we have to figure out how to do unsupervised learning that that's going to be the key and you know I think that's probably true I think unsupervised learning is going to be harder than people think I mean the way that we humans do it then there's the opposing view you know that there's a the the Gary Marcus kind of hybrid view or where deep learning is one part but we need to bring back kind of these symbolic approaches and combine them of course no one knows how to do that very well which is the more important part right to emphasize and how do they how do they fit together what's what's the foundation what's the thing that's on top yeah the cake was the icing right yeah then there's people pushing different different things there's the people the causality people who say you know deep learning as its formulated a completely lacks any notion of causality and that's dooms it and therefore we have to somehow give it some kind of notion of cause there's a lot of push from the more cognitive science crowd saying we have to look at developmental learning we have to look at how babies learn we have to look at intuitive physics all these things we know about physics and it's somebody kind of quipped we also have to teach machines intuitive metaphysics which means like objects exist causality exists you know these things that maybe were born with I don't know that that they don't have the machines don't have any of that you know they look at a group of pixels and they maybe they get 10 million examples but they they can't necessarily learn that there are objects in the world so there's just a lot of pieces of the puzzle that people are promoting and with different opinions of like how how how important they are and how close we are to the you know we'll put them all together to create general intelligence looking at this broad field what do you take away from it who is the most impressive is that the cognitive folks Gary Marcus camp the yawn camp son supervising their self supervise there's the supervisor and then there's the engineers who are actually building systems you have sort of the Andrey Carpathia Tesla building actual you know it's not philosophy it's real writing systems that operate in the real world what yeah what do you take away from all all this beautiful yeah I don't know if you know these these different views are not necessarily mutually exclusive and I think people like Jung McCune agrees with the developmental psychology causality intuitive physics etc but he still thinks that it's learning like end-to-end learning is the way to go we'll take us perhaps all the way yeah and that we don't need there's no sort of innate stuff that has to get built in this is you know it's because no it's a hard problem I personally you know I'm very sympathetic to the cognitive science side because that's kind of where I came in to the field I've become more and more sort of an embodiment adherent saying that you know without having a body it's gonna be very hard to learn what we need to learn about the world that's definitely something like I'd love to talk about in a little bit to step into the cognitive world then if you don't mind because you've done so many interesting things if you look to copycat taking a couple of decades step back you'd Douglas Hofstadter and others have created and developed copycat more than thirty years ago ah that's painful here what is it what is what is copycat it's a program that makes analogies in an idealized domain idealized world of letter strings so as you say thirty years ago Wow so I started working on it when I started grad school in 1984 Wow and it's based on Doug Hofstadter's ideas that about that analogy is really a core aspect of thinking I remember he has a really nice quote in in in the book by by himself and Emmanuel Sanders called surfaces and essences I don't know if you've seen that book but it's it's about analogy he says without concepts there can be no thought and without analogies there can be no concepts so the view is that analogy is not just this kind of reasoning technique where we go you know shoe is to foot as glove as to what you know these kinds of things that we have on IQ tests or whatever that but that it's much deeper much more pervasive in everything we do in everything our language our thinking our perception so we so he had a view that was a very active perception idea so the idea was that instead of having kind of what a passive network in which you have input that's being processed through these feed-forward layers and then there's an output at the end that perception is really a dynamic process you know we're like our eyes are moving around and they're getting information and that information is feeding back to what we look at next influences what we look at next and how we look at it and so copycat was trying to do that kind of simulate that kind of idea where you have these agents it's kind of an agent based system and you have these agents that are picking things to look at and deciding whether they were interesting or not whether they should be looked at more and and that would influence other agents how do they interact so they interacted through this global kind of what we call the workspace so this actually inspired by the old blackboard systems where you'd have agents that post information on a blackboard a common blackboard this is like old very old fashioned a set is that we're talking about like in physical space is a computer program computer programs agents posting concepts on a blackboard yeah we called it a workspace and it it's the workspace is a data structure the agents are little pieces of code that you can think of them as detect little detectors or little filters then say I'm gonna pick this place to look and I'm gonna look for a certain thing and it's just the thing I I think is important is it there so it's almost like you know a convolution in way except a little bit more general and saying and then highlighting it on the on the work in the workspace wasn't once it's in the workspace how do the things they're highlighted relate to each other like what so there's different kinds of agents that can build connections between different things so just to give you a concrete example what copycat did was it made analogies between strings of letters so here's an example ABC changes to a BD what does ijk change to and the program had some prior knowledge about the alphabet new the sequence of the alphabet it you know had a concept of letter successor of letter it had concepts of sameness so it has some innate things programmed in but then it could do things like say discover that ABC is a group of letters in succession hmm and then it an agent can mark that so the idea that there could be a sequence of letters is that a new concept that's formed or if that's a concept that's a concept that's innate sort of can you form new concepts or all so in this program all the concepts of the program were innate so cuz because we weren't I mean obviously that limits it quite up quite a bit but what we were trying to do is say suppose you have some innate concepts how do you flexibly apply them to new situations right and how do you make analogies let's step back for a second so I really like that quote that he said without concepts there can be no thought and without analogies that can be no concepts you know in a Santa Fe presentation you said that it should be one of the mantras of AI yes and that you all see yourself said how to form and fluidly use concept is the most important open problem in AI yes how to form and fluidly use concepts is the most important open problem in AI so let's what is the concept and what is an analogy a concept is in some sense a fundamental unit of thought so say we have a concept of a dog okay and a concept is embedded in a whole space of concepts so that there's certain concepts that are closer to it or farther away from it are these concepts are they really like fundamental like we mention innate look almost like XE o matic like very basic and then there's other stuff built on top of it or just include everything is are they're complicated like you can certainly have form new concepts right I guess that's the question I'm asked yeah can you form new concepts that our company complex combinations of other ago yes absolutely and that's kind of what we we do you know learning and then what's the role of analogies in that so analogy is when you recognize that one situation is essentially the same as another situation and essentially is kind of the key word there and because it's not the same so if I say last week I did a podcast interview in actually like three days ago in Washington DC and that situation was very similar to this situation although it wasn't exactly the same you know it was a different person sitting across from me we had different kinds of microphones the questions were different the building was different there's all kinds of different things but really it was analogous or I can say so by doing a podcast interview that's kind of a constant it's a new concept you know I never had that concept before I mean and I can make an analogy with it like being interviewed for a news article in a newspaper and I can say well you kind of play the same role that the the newspaper the reporter played it's not exactly the same because maybe they actually emailed me some written questions rather than and the writing the written questions play the you know are analogous to your spoken questions you know there's just all kinds of this somehow probably connects to conversations you have over Thanksgiving dinner just general conversations you could there's like a thread you can probably take that just stretches out in all aspects of life that connect to this podcast I mean sure conversations between humans sure and and if I go and tell a friend of mine about this podcast interview my friend might say oh the same thing happened to me you know let's say you know you ask me some really hard question and I have trouble answering it my friend could say the same thing happened to me but it was like it wasn't a podcast interview it wasn't it was a completely different situation and yet my friend is seen essentially this the same thing you know we say that very fluidly the same thing happened to me essentially the same thing we don't even say that right things they imply it yes yeah and the view that kind of what went into say coffee cat that that whole thing is that that that that act of saying the same thing happened to me is making an analogy and in some sense that's what's underlies all of our concepts why do you think analogy making that you're describing is so fundamental to cognition like it seems like it's the main element action of what we think of us cognition yeah so it can be argued that all of this generalization we do concepts and recognizing concepts in different situations is done by analogy that that's every time I'm recognizing that say you're a person that's by analogy because I have this concept of what person is and I'm applying it to you and every time I recognize a new situation like one of the things I talked about it in the book was the the concept of walking a dog that that's actually making an analogy because all that you know the details are very different so it's so now--so reasoning could be reduced on to sense your analogy making so all the things we think of as like yeah like you said perception so what's perception is taking raw sensory input and it's somehow integrating into our our understanding of the world updating the understanding and all of that has just this giant mess of analogies that are being made I think so yeah if you just linger on it a little bit like what what do you think it takes to engineer a process like that for us in our artificial systems we need to understand better I think how how we do it how humans do it and it comes down to internal models I think you know people talk a lot about mental models that concepts are mental models that I can in my head I can do a simulation of a situation like walking a dog and that there there's some work in psychology that promotes this idea that all of concepts are really mental simulations that whenever you encounter a concept or situation in the world or you read about it or whatever you do some kind of mental simulation that allows you to predict what's going to happen to develop expectations of what's going to happen mm-hm so that's the kind of structure I think we need is that kind of mental model that and the in our brain somehow these mental models are very much inter connected again so a lot of stuff we're talking about it they're essentially open problems right so if I ask a question I don't mean that you would know the answer already just hypothesizing but how big do you think is the the network graph data structure of concepts that's in our head like if we're trying to build that ourselves like it's we take it and that's one of the things we take for granted we think I mean that's why we take common sense for granted within common sense is trivial but how big of a thing of concepts is on that underlies what we think of as common sense for example yeah I don't know and I'm not I don't even know what units to measure it in beautifully put right but but you know we have you know it's really hard to know we have what a hundred billion neurons or something I don't know and they're connected via trillions of synapses and there's all this chemical processing going on there's just a lot of capacity for the stuff and their informations encoded in different ways in the brain it's encoded in chemical interactions it's encoded and electric like firing and firing rates and and nobody really knows how it's encoded but it just seems like there's a huge amount of capacity so I think it's it's huge it's just enormous and it's amazing how much stuff we know yeah and but we know and not just know like facts but it's all integrated into this thing that we can make analogies with yes there's a dream of semantic web and there's there's a lot of Dreams from expert systems of building giant knowledge bases or do you see a hope for these kinds of approaches of building of converting Wikipedia into something that could be used in analogy making sure and I think people have have made some progress along those lines I mean people have been working on this for a long time but the problem is and this I think was is is the problem of common sense like people have been trying to get these common sense networks here at MIT there's this concept net project right but the problem is that as I said most of the knowledge that we have is invisible to us it's not in Wikipedia it's very basic things about you know intuitive physics intuitive psychology to ative metaphysics all that stuff if you were to create a website that described intuitive physics intuitive psychology would it be bigger or smaller than Wikipedia what do you think I guess describe to whom no that's very really good right yeah that's a hard question because you know how do you represent that knowledge is the question right I can certainly write down F equals MA and Newton's laws and a lot of physics can be deduced from that but that's probably not the best representation of that knowledge for for doing the kinds of reasoning we want a machine to do so so I don't know it's it's it's impossible to say and you know the projects like there's a famous the famous psych project right that Doug Douglass Lynott did that was trying still going I think it's still going and if the the idea was to try and encode all of common-sense knowledge including all this invisible knowledge in some kind of logical representation and it just never I think could do any of the things that he was hoping it could do because that's just the wrong approach of course that's what they always say you know and then the history books will say well the psych project finally found a breakthrough in 2058 or something and it did you know we're so much progress has been made in just a few decades that yeah okay knows what the next breakthroughs will be it could be a certainly a compelling notion what the psych project stands for I think Lenin was one of the early people do say common sense is what we need and that's what we need all this like expert system stuff that is not going to get you to AI you need common sense and he basically gave up his whole academic career to to go pursue that I told my er that but I think that the approach itself will not what do you think is wrong with approach what kind of approach would might be successful well again he knows the answer right I knew that you know one of my talks one of the people in the audience's a published lecture one of the people in the audience said what AI companies are you investing in advice I'm a college professor extra funds to invest but also like no one knows what's gonna work in AI right that's the problem let me ask another impossible question in case you have a sense in terms of data structures that will store this kind of information do you think they've been invented yet both in hardware and software or is something else needs to be are we totally you know I think something else has to be invented I that's my guess is the breakthroughs that's most promising would that be in hardware and software do you think we can get far with the current computers or do we need to do something you're saying I don't know if Turing computation is gonna be sufficient probably I would guess it will I don't I don't see any reason why we need anything else but so so in that sense we have invented the hardware we need but we just need to make it faster and bigger and we need to figure out the right algorithms and and the right sort of architecture touring that's a very mathematical notion when we try to have to build intelligence it's not an engineering notion where you throw all that stuff I guess I guess it is a it is a question that their people have brought up this question you know and when you asked about like is our current Hardware will our current Hardware work well turing computation says that like our current hardware is in principle a Turing machine right so all we have to do is make it faster and bigger but there have been people like Roger Penrose if you might remember that he said Turing machines cannot produce intelligence because intelligence requires continuous valued numbers I mean that was sort of my reading of his argument and quantum mechanics and what else whatever you know but I don't see any evidence for that that we need new computation paradigms but I don't know if we're you know I don't think we're going to be able to scale up our current approaches to programming these computers what is your hope for approaches like copycat or other cognitive architectures I've talked to the creator of sore for example I've used that arm myself I don't know if you're familiar with yeah woody what do you think is what's your hope of approaches like that in helping develop systems of greater and greater intelligence in the coming decades well that's what I'm working on now is trying to take some of those ideas and extending it so I think there are some really promising approaches that are going on now that have to do with more active generative models so this is the idea of this simulation in your head a concept when you if you want to when you're perceiving a new a new situation you have some simulations in your head those are generative models they're generating your expectations they're generating predictions that's part of a perception you haven't met the model that generates a prediction then you come parrot with ya and then the difference and you also that that generative model is telling you where to look and what to look at and what to pay attention to and it I think it affects your perception it's not that just you compare it with your perception it it becomes your perception in a way it is kind of a mixture of that bottom-up information coming from the world and your top-down model being opposed in the world is what becomes your perception so your hope is something like that can improve perception systems and that they can understand things better yes understand things yes what's the what's the step was the analogy making step there well there the the the idea is that you have this pretty complicated conceptual space you know you can talk about a semantic network or something like that with these different kinds of concept models in your brain that are connected so so let's let's take the example of walking a dog we were talking about that okay let's see I say see someone out on the street walking a cat some people walk their cats I guess this seems like a bad idea but yeah so my model of my you know there's connections between my model of a dog and model of a cat and I can immediately see the analogy of that those are analogous situations but I can also see the differences and that tells me what to expect so also you know I have a new situation so another example with the walking the dog thing is sometimes people I see people riding their bikes with Elise holding a leash and the dogs running alongside okay so I know that the I recognize that as kind of a dog walking situation even though the person's not walking right and the dogs not walking because I I have the these these models that say okay riding a bike is sort of similar to walking or it's connected it's a means of transportation but I because they have their dog there I assume they're not going to work but they're going out for exercise and you know these analogies help me to figure out kind of what's going on what's likely but sort of these analogies are very human interpreter Bowl mm-hmm so that's that kind of space and then you look at something like the current deep learning approaches they kind of help you to take raw sensory information and just to automatically build up hierarchies of role you can even call them concepts they're just not human interpretive or concepts what's your what's the link here do you hope it's sort of the hybrid system question how do you think that two can start to meet each other what's the value of learning in this systems of forming of analogy making the the goal of I you know the original goal of deep learning in at least visual perception was that you would get the system to learn to extract features that at these different levels of complexities may be edge detection and that would lead into learning you know simple combinations of edges and then more complex shapes and then whole objects or faces and this was based on that the ideas of the neuroscientists Hubel and Wiesel who had seen laid out this kind of structure and brain and I think that is that's right to some extent of course people have come found that the whole story is a little more complex than that and the brain of course always is and there's a lot of feedback and so I see that as absolutely a good brain inspired approach to some aspects of perception but one thing that it's lacking for example is all of that feedback which is extremely important the interactive element do you mentioned the expectation the sexual level go back and forth with the the expectation the perception and yes going back and forth so right so that is extremely important and you know one thing about deep neural networks is that in a given situation like you know they they're trained right they get these weights everything but then now I give them a new a new image let's say yes they treat every part of the image in the same way you know they apply the same filters at each layer to all parts of the image mm-hmm there's no feedback to say like oh this part of the image is irrelevant right I shouldn't care about this part of the image or this part of the image is the most important part and that's kind of what we humans are able to do because we have these conceptual expectations there's a little bit work in that there's certainly a lot more in a tent what's under the called attention in natural language processing knowledge ease it's a that's exceptionally powerful and it's a very just as you say it's really powerful idea but again in sort of machine learning it all kind of operates in an automated way that's not human it's not it's not also okay so that yeah right it's not dynamic I mean in the sense that as a perception of a new example is being processed those attentions weights don't change right so I mean there's a this kind of notion that there's not a memory so you're not aggregating the idea of the this mental model yes yeah he that seems to be a fundamental idea there's not a really powerful I mean there's some stuff with memory but there's not a powerful way to represent the world in some sort of way that's deeper than and it's it's so difficult because uh you know neural networks do represent the world they do have a mental model right but it just seems to be shallow I like it it's it's hard to it's it's hard to criticize them at the fundamental level to me at least it's easy to it's it's easy to criticize and we'll look like exactly you're saying mental models sort of almost from a sec I'll put a psychology head on say look these networks are clearly not able to achieve what we humans do with forming mental models but analogy making so on but that doesn't mean that they fundamentally cannot do that like you can it's very difficult to say that I mean I used to me do you have a notion that the learning approaches really I mean they're going to not not only are they limited today but they will forever be limited in being able to construct such mental models I think the idea of the dynamic perception is key here the idea that moving your eyes around and getting feedback and that's something that you know there's been some models like that there's certainly recurrent neural networks that operate over several time steps and but the problem is that it that the actual the recurrence is you know basically the the feedback is to the next time step is the entire hidden state yes the network which which is it that it that's that doesn't work very well does he hit the the thing I'm saying is mathematically speaking it has the information in that recurrence to capture everything it just doesn't seem to work yeah so like my you know it's like it's the same touring machine question right yeah maybe theoretically it computers and anything that's throwing a universal Turing machine can can be intelligent but practically the architecture might be very specific kind of architecture to be able to create it so just I guess it's sort of ask almost the same question again is how big of a role do you think deep learning needs will play or needs to play in this in perception I think deep learning as it's currently as it currently exists you know will place that kind of thing will play some role and but I think that there's a lot more going on in perception but who knows you know that the definition of deep learning I mean it this it's pretty broad it's kind of an umbrella so what I mean is purely sort of neural networks yeah and a feed-forward neural networks essentially or there could be recurrence but yeah sometimes it feels like for us I'll talk to Gary Marcus it feels like the criticism of deep learning is kind of like us birds criticizing airplanes for not flying well or that they're not really flying do you think deep learning do you think it could go all the way like you're looking things do you think that yeah the brute force learning approach can go all the way I don't think so no I mean I think it's an open question but I I tend to be on the innate Ness side that there has that there's some things that we've been evolved to be able to learn and that learning just can't happen without them so so one example here's an example I had in the book that that I think is useful to me at least in thinking about this so this has to do with the deepmind's atari game playing program okay and learned to play these Atari video games just by getting input from the pixels of the screen and it learned to play the game break out thousand percent better than humans okay that was one of the results and it was great and and it learned this thing where it tunneled through the side of the the bricks in the breakout game and the ball could bounce off the ceiling and then just wipe out bricks okay so there was a group who did an experiment where they took the paddle you know that you move with the joystick and moved it up to pixels or something like that and then they they looked at a deep Q learning system that had been trained on breakout and said could it now transfer its learning to this new version of the game of course a human could but and it couldn't maybe that's not surprising but I guess the point is it hadn't learned the concept of a paddle it hadn't learned that it hadn't learned the concept of a ball or the concept of tunneling it was learning something you know we caught we looking at it kind of anthropomorphised it and said oh it here's what it's doing and the way we describe it but it actually didn't learn those concepts and so because it didn't learn those concepts it couldn't make this transfer yes so that's a beautiful statement but at the same time by moving the paddle we also anthropomorphize flaws to inject into the system that will then flip out how impressed we are by it what I mean by that is to me the Atari games were to me deeply impressive that that was possible at all so that guy first pause on that and people should look at that just like the game of Go which is fundamentally different to me then then what deep blue did even though there's still mighty calls distillate research it's just everything in deep mind is done in terms of learning however limited it is still deeply surprising to me yeah i i'm not i'm not trying to say that what they did wasn't impressive i think it was incredibly impressive to me is interesting is moving the path aboard just another love another thing that needs to be learned so like we've been able to maybe maybe been able to through the current neural networks learn very basic concepts that are not enough to do this general reasoning and it may be with more data i mean the data that you know the interesting thing about the examples that you talk about and beautifully is they it's often flaws of the data well that's the question i mean i i think that is the key question it whether it's a flaw of the data or not or the mexico the reason I brought up this example was because you were asking do I think that you know learning from data could go all the way yes and that this was why I brought up the example because I think and this was is not at all to to take away from the impressive work that they did but it's to say that when we look at what these systems learn do they learn the human the things that we humans consider to be the relevant concepts and in that example it didn't sure if you train it on a movie you know the pat paddle being in different places maybe it could deal with maybe it would learn that concept I'm not totally sure but the question is you know scaling that up to more complicated worlds to what extent could a machine that only gets this very raw data learn to divide up the world into relevant concepts and I don't know the answer but I would bet that that without some innate notion that it can't do it yeah ten years ago a hundred percent agree with you as the deal most experts in a system but now I have a one but like I have a glimmer of hope okay have you no that's very nice and I think I think that's what deep learning did in the community is no no I still if I had to bet all my money it's a hundred percent deep learning will not takes all the way but there's still other it still I was so personally sort of surprised mm-hmm why the Thar games by go by by the power of self play of just yeah I'm playing against you that I was like many other times just humbled of how little I know about what's possible you know yeah I think fair enough self play is amazingly powerful and you know that's that goes way back to Arthur Samuel Wright with his checker playing program and that which was brilliant and surprising that it did so well so just for fun let me ask you a topic of autonomous vehicles it's the area that that I work at least these days most closely on and it's also area that I think is a good example that you use a sort of an example of things we as humans don't always realize how hard it is to do it's like the the constant trend AI but the different problems that we think are easy when we first try them and then realize how hard it is okay so why you've talked about this autonomous driving being a difficult problem more difficult than we realize you must give it credit for why is it so difficult one of the most difficult parts in your view I think it's difficult because of the world is so open-ended as to what what kinds of things can happen so you have sort of what normally happens which is just you drive along and nothing nothing surprising happens and autonomous vehicles can do the ones we have now evidently can do really well on most normal situations as long as long as you know the weather is reasonably good and everything but if some we have this notion of edge cases or or you know things in the tail of the distribution you call it the long tail problem which says that there's so many possible things that can happen that was not in the training data of the machine that it won't be able to handle it because it doesn't have common sense right it's the old the paddle moved yeah it's the paddle moved problem right and so my understanding and you probably are more of an expert than I am on this is that current self driving car vision systems have problems with obstacles meaning that they don't know which obstacles which quote unquote obstacles they should stop for and which ones they shouldn't stop for and so a lot of times I read that they tend to slam on the brakes quite a bit and the most common accidents with self-driving cars are people rear-ending them because they were surprised they've warned expecting the machine the car to stop yeah so there's there's a lot of interesting questions there whether because because you mentioned kind of two things so one is the the problem of perception of understanding of interpreting the objects that are detected right correctly and the other one is more like the policy the action that you take how you respond to it so a lot of the cars braking is a kind of notion of to clarify there's a lot of different kind of things that are people calling autonomous vehicles but a lot the L for vehicles with a safety driver are the ones like way moe and cruise and those companies they tend to be very conservative and cautious so they tend to be very very afraid of hurting anything or anyone and getting in any kind of accidents so their policy is very kind of that it that results in being exceptionally responsive to anything that could possibly be an obstacle right right which which which the human drivers around it it's unpredictably yeah that's not a very human thing to do caution that's not the thing we're good at specially in driving we're in a hurry often angry and etc especially in Boston so and then there's of another and a lot of times that's machine learning is not a huge part of that it's becoming more and more unclear to me how much you you know sort of speaking to public information because a lot of companies say they're doing deep learning and machine learning just attract good candidates the reality is in many cases it's still not a huge part of the the perception this is this lidar there's other sensors that are much more reliable for obstacle detection and then there's Tesla approach which is vision only and there's I think a few companies doing that protest the most sort of famously pushing that forward and that's because the lidar is too expensive right well I mean yes but I would say if you were to for free give to every test vehicle I mean Elon Musk fundamentally believes that lidar is a crutch right fantasy said that that if you want to solve the problem of machine learning lidar is not should not be the primary sensor is the belief okay the camera contains a lot more information mm-hmm so if you want to learn you want that information but if you want to not to hit obstacles you want like are it's sort of it's this weird trade-off because yeah it's sort of what Tesla vehicles have a lot of which is really the thing the price of the fallback the primary fallback sensor is radar which is a very crude version of lighter it's a good detector of obstacles except when those things are standing right the stopped vehicle right that's why it had problems with crashing into stop fire trucks stop fire trucks right so the hope there is that the vision sensor would somehow catch that and infer there's a lot of problems of perception I they are doing actually some incredible stuff in the almost like an active learning space where it's constantly taking edge cases and pulling back in there's a state data pipeline another aspect that is really important that people are studying now is called multitask learning which is sort of breaking apart this problem whatever the problem is in this case driving into dozens or hundreds of little problems that you can turn into learning problems so this giant pipeline the you know it's kind of interesting I've been skeptical from the very beginning we've become less and less skeptical over time how much of driving can be learned I'm still think it's much farther than then the CEO of that particular company thinks it will be but it it is costly surprising that through good engineering and data collection and active selection of data how you can attack that long tail and it's an interesting open question that you're absolutely right there's a much longer tail and all these edge cases that we don't think about but it's this it's a fascinating question that applies to natural language in all spaces how big how how big is that long tail right and I mean not to linger on the point but what's your sense in driving in these practical problems of the human experience can it be learned so the current what are your thoughts are sort of Elon Musk thought let's forget the thing that he says it'd be solved in a year but can it be solved in in a reasonable timeline or do fundamentally other methods need to be invented so I I don't I think that ultimately driving so so it's a trade-off in a way I you know being able to drive and deal with any situation that comes up does require kind of full human telogen sand even in humans aren't intelligent enough to do it because humans I mean most human accidents are because the human wasn't paying attention or the humans drunk or whatever and not because they weren't intelligent but not because they weren't intelligent enough right whereas the accidents with autonomous vehicles is because they weren't intelligent enough they're always paying attention so it's a it's a trade off you know and I think that it's a very fair thing to say that autonomous vehicles will be ultimately safer than humans because humans are very unsafe it's kind of a low bar but just like you said the III I think he was get a bad rap right cuz we're really good at the common-sense thing yeah we're great at the common-sense thing we're bad at the paying atten thing being attached a thing especially moral you know driving is kind of boring and we have these phones to play with and everything but I think what what's gonna happen is that for many reasons not just AI reasons but also like legal and other reasons that the the definition of self-driving is going to change or autonomous is going to change it's not going to be just I'm gonna go to sleep in the back and you just drive me anywhere it's gonna be more certain areas are going to be instrumented to have the sensors and the mapping and all the stuff you need for that that the autonomous cars won't have to have full common sense and they'll do just fine in those areas as long as pedestrians don't mess with them too much that's another question I don't think we will have fully autonomous self-driving in the way that like most the average person thinks of it for a very long time and just to reiterate this is the interesting open question that I think I agree with you on is to solve fully Thomas driving you have to be able to engineer in common sense yes I think it's an important thing to hear and think about I hope that's wrong but I currently I could agree with you that unfortunately you do have to have to be more specific sort of these deep understandings of physics and yeah of the way this world works and also the human dynamics like you mentioned pedestrians and cyclists actually that's whatever that nonverbal communication is some people call it there's that dynamic that is also part of this common sense right and we're pretty we humans are pretty good at predicting what other humans are gonna do and how are our actions impacts the behaviors of yes this is weird game theoretic dance that we're good at somehow and work well the funny thing is is because I've watched countless hours of pedestrian video and talked to people we humans are also really bad at articulating the knowledge we have right which is a been a huge challenge yes so you've mentioned embodied intelligence what do you think it takes to build a system of human level intelligence does he need to have a body I'm not sure but I I'm coming around to that more and more and what does it mean to be I don't mean to keep breaking on up yeah Laocoon he looms very large yeah well he certainly has a large personality yes he thinks that the system needs to be grounded meaning he needs to sort of be able to interact with reality but it doesn't think it necessarily need to have a body so when you think of what's the difference I guess I want to ask when you mean body do you mean you have to be able to play with the world or do you also mean like there's a body that you that you have to preserve oh that's a good question I haven't really thought about that but I think both I would guess because it's because I think you I think intelligence it's so hard to separate it from self our desire for self-preservation our emotions are all that non rational stuff that kind of gets in the way of logical thinking because we the way you know if we're talking about human intelligence or human level intelligence whatever that means a huge part of it is social that you know we were evolved to be social and to deal with other people and that's just so ingrained in us that it's hard to separate intelligence from that I I think you know AI for the last 70 years or however long has been around it it has largely been separated there's this idea that there's like it's kind of very Cartesian there's this you know thinking thing that we're trying to create but we don't care about all this other stuff and I think the other stuff is very fundamental so there's idea that things like emotion get in the way of intelligence as opposed to being an integral part and part of it so I mean I'm Russian so romanticize the notions of emotion and suffering and all that kind of fear of mortality those kinds of things so I I especially sort of by the way did you see that there was this recent thing going around the internet of this so some I think he's a Russian or some Slavic head had written this thing a sort of anti the idea of super intelligence mmm-hmm I forgot maybes polish anyway so at all these arguments and one one was the argument from Slavic pessimism do you remember what the argument is it's like nothing ever works so what what do you think is the role like that's such a fascinating idea that the what we perceive as serve the limits of human of the human mind which is emotion and fear and all those kinds of things are integral to intelligence could could you elaborate on that like what why is that important do you think for human level intelligence at least the way the humans work it's a big part of how it affects how we perceive the world it affects how we make decisions about the world it affects how we interact with other people it affects our understanding of other people you know for me to understand your what you're going what you're likely to do I need to have kind of a theory of mine and that's very much a theory of emotions and motivations and goals and and to understand that I you know we have the this whole system of you know mirror neurons you know I sort of understand your motivations through sort of simulating it myself so you know it's not something that I can prove that's necessary but it seems very likely so ok you've written the op-ed in New York Times titled we shouldn't be scared by super intelligent AI and it criticized a little bit just to rustle in the boss room can you try to summarize that articles key ideas so it was spurred by a earlier New York Times op-ed by Stewart Russell which was summarizing his book called human compatible and the article was saying you know if we if we have super intelligent AI we need to have its values align with our values and it has to learn about what we really want and he gave this example what if we have a super intelligent AI and we give it the prob of solving climate change and it decides that the best way to lower the carbon in the atmosphere is to kill all the humans okay so to me that just made no sense at all because a super intelligent AI first of all thinking what trying to figure out what what super intelligence means and it doesn't it seems that something that super intelligent can't just be intelligent along this one dimension of okay I'm gonna figure out all the steps the best optimal path to solving climate change and not be intelligent enough to figure out that humans don't want to be killed that you could get to one without having the other and you know boström in his book talks about the orthogonality hypothesis where he says he thinks that systems I can't remember exactly what it is but it like a systems goals and it's uh values don't have to be aligned there's some orthogonal 'ti there which didn't make any sense to me so you're saying it in any system that's sufficiently not even super intelligent but is it approach greater greater intelligence there's a holistic nature that will sort of attention that will naturally emerge yes events it from sort of any one dimension running away yeah yeah exactly so so you know boström had this example of the the super intelligent AI that that makes that turns the world into paperclips because its job is to make paper clips or something and that just as a thought experiment didn't make any sense to me well as a thought experiment or the thing that could possibly be realized either so so I think that you know what my op ed was trying to do was say that that intelligence is more complex than these people are presenting it that it's not like it's not so separable the rationality the the values the emotions all of that that it's the the view that you could separate all these dimensions and build the machine that has one of these dimensions and it's super intelligent in one dimension but it doesn't have any of the other dimensions that's what I was trying to criticize that that that I don't believe that so can I read a few sentences from yoshua bengio who is always super eloquent so he writes I have the same impression as Melanie that our cognitive biases are linked with our ability to learn to solve many problems they may also be a limiting factor for AI however this is a may in quotes things may also turn out differently and there's a lot of uncertainty about the capabilities of future machines but more importantly for me the value alignment problem is a problem well before we reached some hypothetical super intelligence it is already posing a problem in the form of super powerful companies whose objective function may not be sufficiently aligned with humanity's general well-being creating all kinds of harmful side effects so he goes on to argue that at you know the orthogonality and those kinds of things the concerns of just aligning values with the capabilities of the system is something that might come long before we reach anything like in super intelligence so your criticism it's kind of really nice as saying this idea of super intelligence systems seem to be dismissing fundamental parts of what intelligence would take and then you know kind of says yes but if we look at systems that are much less intelligent there might be these same kinds of problems that emerge sure but I guess the example that he gives there of these corporations that's people right those are people's values I mean we're talking about people the corporations are their value are the values of the people who run those corporations but the idea is the algorithm that's right so does the fundamental person that the fundamental element of what does the bad thing as a human being yeah but the the algorithm kind of controls the behavior this mass of human beings which help whatever for a company that's the outs of for example if it's advertisement driving company that recommends certain things and encourages engagement so it gets money by encouraging engagement and therefore the company more and more it's like the cycle that builds an algorithm that enforces more engagement and made perhaps more division in the culture and so on so on again I guess the question here is sort of who has the agency so you might say for instance we don't want our algorithms to be racist right and facial recognition you know some people have criticized some facial recognition systems as being racist because they're not as good on darker skin and lighter skin okay but the agency there the the the the actual algal recognition algorithm isn't what has the agency it's it's not the racist thing right it's it's the that the I don't know the the combination of the training data the cameras being used I whatever but my understanding of and I'll say I told agree with Benjy oh there that he you know I think there are these value issues with our use of algorithms but my understanding of what Russell's argument was is more that the algorithm itself has the agency now it's the thing that's making the decisions and it's the thing that has what we would call values yes so whether that's just a matter of degree you know it's hard it's hard to say right because but I would say that's sort of qualitatively different than a face recognition neural network and to broadly linger on that point if you look at Elon Musk goes to a rustle or boström people who are worried about existential risks of AI however far into the future the argument goes is it eventually happens we don't know how far but it eventually happens do you share any of those concerns and what kind of concerns in general do you have a body I that approach anything like existential threat to humanity so I would say yes it's possible but I think there's a lot more closer in existential threats you had as you said like a hundred years for so your times more more than a hundred more than a hundred years and so that maybe even more than 500 years I don't I don't know I mean it's so the existential threats are so far out that the future is the immune there'll be a million different technologies that we can't even predict now that will fundamentally change the nature of our behavior reality society and so on before then I think so I think so and you know we have so many other pressing existential threats going on new hangouts even their nuclear weapons climate problems you know poverty possible pandemics that you can go on and on and I think though you know worrying about existential threat from AI is it's not the best priority for what we should be worried about that that's kind of my view because we're so far away but I you know I I'm not I'm not necessarily criticizing Russell or boström or whoever for worrying about that and I'm I think it's some some people should be worried about it it's it's certainly fine but I I was more sort of getting at their their view of intelligible intelligence is mmm-hmm so I was more focusing on like their view of the super intelligence then uh just the fact of them worrying and the title of the article was written by the the New York Times editors I wouldn't have called it that we shouldn't be scared by super intelligent and no if you wrote it be like we should redefine what you mean by super in I actually said it said you know something like super intelligence is not is is not a sort of coherent idea that's not like it's only New York Times would put in and the follow-up argument that Yoshio makes also not argument but a statement and I've heard him say it before and I think I agree he's kind of has a very friendly way of phrasing it is it's good for a lot of people to believe different things yeah well no but he's it's also practically speaking like we shouldn't be like while your article stands like Stuart Russell does amazing work boström does amazing work you do amazing work and even when you disagree about the definition of super intelligence or the usefulness of even the term it's still useful to have people that like use that term all right and then argue it sir I I absolutely agree with video there and I think it's great that you know and it's great that New York Times will publish all this stuff that's right it's an exciting time to be here what what do you think is a good test of intelligence IQ is is natural language ultimately a test that you find the most compelling like the the original or the what you know the higher levels of the Turing test kind of yeah yeah I still think the original idea of the Turing test is a good test for intelligence I mean I can't think of anything better you know the Turing tests the way that it's been carried out so far has been very impoverished if you will but I think a real Turing test that really goes into depth like the one that I mentioned I talk about in the book I talk about Ray Kurzweil and Mitchell Kapoor have this bet right that that in 2029 I think is the date there a machine will pass the Turing test and turn says and they have a very specific like how many hours many expert judges and all of that and you know Kurzweil says yes Kapoor says no we can't we only have like nine more years to go to see I you know if something a machine could pass that I would be willing to call it intelligent of course nobody will they will say that's just a language model if it does so you would be comfortable it's a language a long conversation that well yeah here I mean you're right because I think probably to carry out that long conversation you would literally need to have deep common-sense understanding of the world I think so and the conversation is enough to reveal that so another super fun topic of complexity that you have worked on written about let me ask the basic question what is complexity so complexity is another one of those terms like intelligence it's perhaps overused but my book about complexity was about this wide area of complex systems studying different systems in nature in technology in society in which you have emergence kind of like I was talking about with intelligence you know we have the brain which has billions of neurons and each neuron individually could be said to be not very complex compared to the system as a whole but the system the the interactions of those neurons and the dynamics creates these phenomena that we call we call intelligence or consciousness you know that are we consider to be very complex so the field of complexity is trying to find general principles that underlie all these systems that have these kinds of emergent properties and the the emergence occurs from like underlying the complex system is usually simple fundamental interactions yes and the emergence happens when there's just a lot of these things interacting yes sort of what and then most of science to date can you talk about what what is reductionism well reductionism is when you try and take a system and divide it up into its elements whether those be cells or atoms or subatomic particles whatever your field is and then try and understand those elements and then try and build up an understanding of the whole system by looking at sort of the sum of all the elements so what's your sense whether we're talking about intelligence or these kinds of interesting complex systems is it possible to understand them in in a reductionist way it's just probably the approach of most of science today right I don't think it's always possible to understand the things we want to understand the most so I don't think it's possible to look at single neurons and understand what we call intelligence you know just look at sort of summing up and the sort of the summing up is the issue here that were you know that one example is that the human genome alright so there was a lot of work on excitement about sequencing the human genome because the idea would be that we'd be able to find genes that underlies diseases but it turns out that and I was a very reductionist idea you know we figure out what all the the parts are and then we would be able to figure out which parts cause which things but it turns out that the parts don't cause the things that we're interested in it's like the interactions it's the networks of these parts and so that kind of reductionist approach didn't yield the the explanation that we wanted would he would use the most beautiful complex system that you've encountered most beautiful that you've been captivated by is it sort of I mean for me that is the simplest to be cellular automata oh yeah so I was very captivated by cellular automata and worked on cellular automata for several years do you find it amazing or is it surprising that such simple systems such simple rules and cellular Domino can create sort of seemingly unlimited complexity yeah that was very surprising to me I didn't make sense of it how does that make you feel this is just ultimately humbling or is there hope to somehow leverage this into a deeper understanding and even able to engineer things like intelligence it's definitely humbling how humbling in that also kind of awe-inspiring that it's that inspiring like part of mathematics that these credible simple rules can produce this very beautiful complex hard to understand behavior and that that's it's mysterious you know and and surprising still but exciting because it does give you kind of the hope that you might be able to engineer complexity just from from these can you briefly say what is the Santa Fe Institute its history its culture its ideas its future stuff I've never semester G I've never been but so has been this in my - mystical place where brilliant people study the edge of chaos exactly so the Santa Fe Institute was started in 1984 and it was created by a group of scientists a lot of them from Los Alamos National Lab which is about a 40-minute drive from the Santa Fe Institute they were mostly physicists and chemists but they were frustrated in their field because they felt so that their field wasn't approaching kind of big interdisciplinary questions like the kinds we've been talking about and they wanted to have a place where people from different disciplines could work on these big questions without sort of being siloed into physics chemistry biology whatever so they started this Institute and this was people like George Cowan who is a chemist in the Manhattan Project and Nicholas Metropolis who mathematician physicist Murray gell-mann physicist nism so some really big names here ken arrow an economist Nobel prize-winning economist and they started having these workshops and this whole enterprise kind of grew into this Research Institute that's itself has been kind of on the edge of chaos its whole life because it doesn't have any it doesn't have a significant endowment and it's just been kind of living on whatever funding it can raise through donations and grants and however it can you know business business associates and so on but it's a great place it's a really fun place to go think about ideas from that you wouldn't normally encounter I saw Sean Carroll so physicists yeah yeah external faculty and you mentioned that there's so there's some external faculty and there's people there's a very small group of resident faculty maybe maybe about ten who are there for five year terms that can sometimes get renewed and then they have some postdocs and then they have this much larger on the order of a hundred external faculty or people come like me who come and visit for various periods of time so what do you think this is the future of the Santa Fe Institute like what and if people are interested like what what's there in terms of the public interaction or students or so on that's that could be a possible interaction on the Santa Fe Institute or its ideas yeah so there's a there's a few different things they do they have a complex system summer school for graduate students and postdocs and sometimes faculty attend to and that's a four week very intensive residential program where you go and you listen to lectures and you do projects and people people really like that I mean it's a lot of fun they also have some specialty summer schools there's one on computational social science there's one on climate and sustainability I think it's called there's a few and then they have short courses where just a few days on different topics they also have an online education platform that offers a lot of different courses and tutorials from SFI faculty including an introduction to complexity course that I talk and there's a bunch of talks to online from there's guest speakers and so on they they host a lot of yeah they have sort of technical seminars and colloquia they all and they have a community lecture series like public lectures and they put everything on their YouTube channel so you can see it all watching douglas hofstadter author of get olestra bach was your PhD adviser he mentioned a couple times and collaborator do you have any favorite lessons or memories from your time working with him that continues to this day yes but just even looking back through throughout your time working with him so one of the things he taught me was that when you're looking at a complex problem to to idealize it as much as possible to try and figure out what are really what is the essence of this problem and this is how like the copycat program came into being was by taking an analogy making and saying how can we make this as idealized as possible but still retain really the important things we want to study and that's really kept you know been a core theme of my research I think and I continue to try and do that and it's really very much kind of physics inspired Hofstadter was a PhD in physics that was his background it's like first principles kind of thinking like you reduced to the the most fundamental aspect of the problem yeah so there you can focus on solving that fun than I thought yeah and in AI you know that was people used to work in these micro worlds right like the blocks world was very early important area in AI and then that got criticized because they said oh you know you can't scale that to the real world and so people started working on much like more real world like problems but now there's been kind of a return even to the blocks world itself you know we've seen a lot of people who are trying to work on more of these very idealized problems or things like natural language and common sense so that's an interesting evolution of those ideas so the perhaps the block's world's represents the fundamental challenges of the problem of intelligence more than people realized it might yeah is there sort of when you look back at your body of work and your life you've worked in so many different fields is there something that you're just really proud of in terms of ideas that you've gotten chance to explore create yourself so I am really proud of my work on the copycat project I think it's really different from what almost everyone is done in AI I think there's a lot of ideas there to be explored and I guess one of the happiest days of my life you know aside from like the births of my children was the birth of copycat when it actually started to be able to make really interesting analogies and I remember that very clearly you know it was very exciting time well you kind of gave life yes artificial so that's right what in terms of what people can interact I saw there's like a I think it's called meta copy kinetic hat mad cat and there's a Python three implementation at if people actually want to play around with it and actually get into it and study it maybe integrate into whether it's with deep learning or any other kind of work they're doing what what would you suggest they do to learn more about it and to take it forward in different kinds of directions yeah so that there's a Douglas Hofstadter's book called fluid concepts and creative analogies talks in great detail about copycat I have a book called analogy making as perception which is a version of my PhD thesis on it there's also code that's available that you can get it to run I have some links on my web page to where people can get the code for it and I think that that would really be the best way I get into it yeah play with it well Melanie is a honor talking to you I really enjoyed it thank you so much for your time today has been really great thanks for listening to this conversation with Melanie Mitchell and thank you to our presenting sponsor cash app downloaded use code Lex podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoyed this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you some words of wisdom from Douglas Hofstadter and Melanie Mitchell without concepts there can be no thought and without analogies there can be no concepts and Melanie adds how to form and fluidly use concepts is the most important open problem in AI thank you for listening and hope to see you next time you |
Jim Gates: Supersymmetry, String Theory and Proving Einstein Right | Lex Fridman Podcast #60 | the following is a conversation with s James Gates Jr he's a theoretical physicist and professor Brown University working on supersymmetry super gravity a super string theory he served on former President Obama's Council of Advisors on science technology and he's now the co-author of a new book titled proving Einstein right about the scientists who set out to prove in Stein's theory of relativity you may have noticed that I've been speaking with not just computer scientists but philosophers mathematicians physicists economists and soon much more to me AI is much bigger than deep learning bigger than computing it is our civilizations journey into understanding the human mind and creating echoes in the machine that journey includes of course the world of theoretical physics and its practice of first principles mathematical thinking in exploring the fundamental nature of our reality this is the 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again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with s James Gates Jr you tell a story when you were 8 he had a profound realization at the stars in the sky are actually places that we could travel to one day do you think human beings will ever venture outside our solar system Wow the question of whether humanity gets outside of the solar system it's going to be a challenge and as long as the laws of physics that we have today are accurate and valid it's gonna be extraordinarily difficult I'm a science-fiction fan as you probably know so I love to dream of starships and traveling to other solar systems but the barriers are just formidable if we just kind of venture a little bit into science fiction do you think the spaceships if we are successful that take us outside the solar system we'll look like the ones we have today or do fundamental breakthrough our fundamental breakthroughs necessary in order to have genuine starships probably some really radical views about the way the universe works is our going to have to take place in our science we could with our current technology think about constructing multi-generational starships where the people who get on them are not that people who get off at the other end but even if we do that there for mental problems actually our bodies which doesn't seem to be conscious for a lot of people even getting to Mars is going to present this challenge because we live in this a wonderful home has a protective magnetic magnetosphere around it and so we're shielded from cosmic radiation once you leave this shield there are some estimates that for example if you send someone to Mars with that technology probably about two years out there without the seal they're gonna be mom bartered that means radiation that probably means cancer so that's one of the most formal challenge even if we could get over the technology if you think so Mars is a harsh place you have musk SpaceX and other folks NASA are really pushing to put a human being on Mars do you think again let's forgive me for lingering in science fiction land for a little bit do you think one day we may be able to colonize Mars first do you think we'll put a human on Mars and then do you think we'll put many humans on Mars so first of all we're not I am extraordinarily convinced we will not put a human on Mars by 2030 which is a date that you often hear in the public debate what's the challenge there well you think so there are a couple of ways that I could slice this but the one that I think is simplest for people and understand involves money so you look at how we got to the moon in the 1960s it was about 10-year duration between the challenge that President Kennedy laid out and our successfully landing a moon I was actually here at MIT when that first moon landing occurred so I remember watching it on TV but how do we get there well we had this extraordinary technical agency of the United States government NASA it consumed about 5% of the countries economic output and so you say 5% of the economic output over about a 10-year period gets us 250,000 miles in space Mars is about a hundred times farther so you have at least a hundred times a challenge and we're spending about one tenth of the funds that we spent then as a government so my claim is is that it's at least a thousand times harder for me to imagine us getting to Mars by 2030 and yet that part that you mentioned in the speech that I just have to throw in there of JFK of we do these things not because they're easy but because they're hard it's such a beautiful line that I would love to hear a modern president say about a scientific endeavor well one day we live in hope that such a precedent will arise for our nation but even if like I said even if you you fix the profit technical problems the biological engineering that I worry most about however I'm gonna go out on a limb here I think that by two thousand ninety or so or two thousand one hundred and so let's say 120 I suspect we're gonna have a human on Mars Wow so you think that many years out first a few tangents he said bioengineering as a as a challenge of what's what's the challenge there so as I said the the real problem with interstellar travel aside from the technology challenges the real problem is radiation and how do you engineer either an environment or a body because we see rapid advances going on in bioengineering how do you engineer either a ship or body so that something is some person that's recognizably Union human will survive the rigors of interplanetary space travel it's much more difficult than most people seem to take into account so if we could linger on the 2092 2121 20 sort of thinking of that kind of you know and we let's linger on money okay so Elon Musk and Jeff Bezos are pushing the cost trying to quit push the cost down I mean this is so do you have hope is this actually a sort of a brilliant big-picture scientist do you think a business entrepreneur can take science and make it cheaper and get it out there faster so bending the cost curve is you'll notice that has been an anchor there's the simplest way for me to discuss this with people about what the challenge is so yes bending the cost curve is certainly critical if we're going to be successful now you asked about the endeavors that are out there now sponsored by two very prominent American citizens Jeff Bezos and Elon Musk I'm disappointed actually in what I see in terms of the routes that are being pursued so let me give you one example there and this one is going to be a little bit more technical so if you look at the kinds of rockets that both these organizations are creating yes it's wonderful reusable technology to see a rocket go up and land on its fins just like it did in science fiction movies when I was a kid that's astounding but the real problem is those Rockets the technology that we're doing now is not really that different than what was used to go to the moon and there are alternatives it turns out there's an engine called a flare engine which so a traditional rocket if you look at the engine looks like a bell right and then the flame comes out the bottom but there is a kind of engine called a flare engine which is essentially when you look at it it looks like an exhaust pipe on like a fancy car that's you know long and elongate it and it's a type of rocket engine that we know we know it's there been preliminary testing we know it works and it also is actually much more economical because what it does is allow you to vary the amount of thrust as you go up in a way that you cannot do with one of the bell shaped engines so you would think that an entrepreneur might try to have the breakthrough to use flared nozzles as they're called as a way to bend the cost curve because we keep coming back that's going to be a big factor but that's not happening in fact what we see is what I think of as incremental change in terms of our technology so I'm not really very encouraged by what I personally see so incremental change won't bend the cost curve and I don't see it just linger on the sci-fi for one more question sure do you think we're alone in the universe are we the only intelligent form of life so there is a quote by Carl Sagan which I really love when I hear this question and I'm I recall the quote and it goes something like if we're the only conscious life in the universe it's a terrible waste of space because the universe is an incredibly big place and when Carl made that statement we didn't know about the profusion of planets that are out there in the last decade we've discovered over a thousand planets and a substantial number of those planets are earth-like in terms of being in the Goldilocks zone as it's called so it's on in my mind is practically inconceivable that were the only conscious form of life in the universe but that doesn't mean they've come to visit us do you think they would look do you think will recognize alien life if we saw it do you think you'd look anything like the carbon-based the biological system we have on earth today it would depend on that life's native environment in which it arose if that environment was sufficiently like our environment there's a principle in biology and nature called convergence which is that even if you have two biological systems that are totally separated from each other if they face similar conditions they tend to kin nature tends to converge on solutions and so there might be similarities if this alien life-form almost born in a place that's kind of like this place physics appears to be quite similar the laws of physics across the entirety of the universe do you think weirder things than we see on earth can spring up out of the same kinds of laws of physics from the laws of physics I would say yes first of all if you look at carbon-based life why we carbon base well it turns out it's because of the way that carbon interacts with elements which in fact is also a reflection on the electronic Select structure of the carbon nucleus so you can look down the table developments and say but gee do we see similar elements the answer is yes and one that when it often hears about in science fiction is silicon so maybe there's a silicon-based life-form out there if the conditions are right but I think it's presumptuous of us to think that we are the template by which all life has to appear before we dive into beautiful details let me ask a big question what to you is the most beautiful idea maybe the most surprising and mysterious idea in physics the most surprising idea to me is that we can actually do physics the universe did not have to be constructed in such a way that our with our limited intellectual capacity that is actually put together in such a way and that we are put together in such a way that we can with our minds I delve incredibly deeply into the structure of the universe that to me is pretty close to a miracle so they're simple equations relatively simple that can describe things you know the fundamental functions then describe everything about our reality that's not can you imagine universes where everything is a lot more complicated do you think there's something inherent about universes that well simple laws well first of all let me this is a question that I encounter in a number of guys is a lot of people will raise the question about whether mathematics is the language of the universe and my response is mathematics is the language that we humans are capable of using in describing the universe it may have little to do with the universe but in terms of our capacity it's the microscope it's the telescope through which we it's the lens through which we are able to view the universe with the precision that no other human language allows so could there be other universes well I don't even know if this one looks like I think it does but the beautiful surprising thing is that physics there are laws of physics very few laws of physics they can effectively compress down the functioning of the universe yes that's extraordinarily surprising you know I like to use the analogy with computers and information technology if you worry about transmitting large bundles of data one of the things that computer scientists do for us is they allow for processes that are called compression where you take big packets of data and you press them down into much smaller packets and then you transmit those and then unpack them at the other end and so it looks a little bit to me like the universe is kind of done us a favor it's constructed our minds in such a way that we have this thing called mathematics which then as we look at the universe teaches us how to carry out the compression process a quick question about compression do you think the human mind can be compressed the the biology could be compressed we talked about space travel to be able to compress the information that captures some large percent of what it means to be me or you and then be able to send that at the speed of light wow that's a big question and let me try to take it apart unpack it into several pieces I don't believe that wetware biology such as we are has an exclusive patent on in own intellectual consciousness I suspect that other structures in the universe are perfectly capable of producing the data streams that we use the process first of all our observations of the universe and and an awareness of ourselves I can imagine structures can do that also so that's part of what you were talking about which I would have some disagreement with consciousness yes what's the most interesting part of consciousness of us humans is consciousness is the thing I think that's the most interesting thing about you and then you're saying that there's other entities throughout the universe I could imagine I can well imagine that the architecture that supports our consciousness again has no patent on consciousness it's the in case you have an interesting thought here there's folks perhaps in philosophy called Pan cyclists that believe consciousness underlies everything it is one of the fundamental laws of the universe do you have a sense that that could possibly fit into I don't know the answer that question one part of that belief system is Ghia which is that there's a kind of conscious life force about our planet and you know I encountered these things before I don't quite know what to make of them I my own experience and I'm I'll be 69 in about two months and I have spent all my adulthood thinking about the way that mathematics interacts with nature and with us to try to understand nature and all I can tell you from all of my integrated experience is that there is something extraordinarily mysterious to me about our universe this is something an Einstein said of from his life experience as a scientist and this mysteriousness almost feels like the universe is our parent it's a very strange thing perhaps to hear science say it scientists say but there are just so many strange coincidences that you just get a sense that something is going on while I interrupted you in terms of compressing what we're down to we consented at the speed of light yes so so the first thing is I would argue that it's probably very likely that artificial intelligence ultimately will develop something like consciousness something that for us will probably be indistinguishable from consciousness so that's what I meant by our biological processing equipment that we carry up here probably had does not hold a patent on consciousness because it's really about the data streams I mean that's as far as I can tell that's what we are we are self actuating self learning data streams that to me Lee is most accurate way I can tell you what I have seen in my lifetime about what humans are at the level of consciousness so if that's the case then you just need to have an architecture that supports that information processing so let's assume that that's true that that in fact what we call consciousness is really about a very peculiar kind of data stream if that's the case then if you can export that to a piece of hardware something metal electronic what-have-you then you certainly will ultimately that kind of consciousness could get to Mars very quickly it doesn't have our problems you can engineer the body as I say there's a ship or a body you engineer one or both send it to the speed of light well that one is a more difficult one because that now goes beyond just a matter of having a data stream and so now the preservation of the information in the data stream and so unless you can build something that's like a super super super version of the way the internet works because most people aren't aware that the Internet itself is actually a miracle it's based on a technology called message packaging so if you could expand nc8 message packaging in some way to preserve the information that's in the data stream then maybe your dream becomes true can we you mentioned with artificial intelligence sort of us human beings not having a monopoly on consciousness does the idea of artificial and systems computational systems being able to basically replacing us humans scare you excite you what do you think about so I'm gonna tell you about a conversation I once had with Eric Schmidt I was sitting at a meeting with him and he was a few feet away and he turned to me and he said something like you know Jim and maybe a decade or so we're gonna have computers that do what you do and my response was not unless they can dream because there's something about the human the way that we humans actually generate creativity it's somehow I get this sense of my lived experience and watching creative people that somehow connected to the irrational parts of what goes on in our head yes and dreaming is part of that irrationally so unless you can build a piece of artificial intelligence that dreams I have a strong suspicion that you will not get something that it will fully be conscious by a definition that I would accept for example imagine dreaming you've played around with some out-there fascinating ideas how do you think when and we'll start diving into the world of the very small ideas of supersymmetry and all that in terms of visualization in terms of how do you think about it how do you dream of it how do you come up with ideas in that fascinating mysterious space so in my workspace which is basically where I am charged with coming upon on coming up on a mathematical palette with new ideas that will help me understand the structure of nature and hopefully help all of us understand structure of nature I've observed several different ways in which my creativity expresses itself there's one mode which looks pretty normal which I sort of think of as the Chinese water torture mythos drop drop drop you get more and more information and suddenly it all congeals and you get a clearer picture and so that's the kind of a standard way of working and I think that's how most people think about the way technical people solve problems that it's kind of you accumulate this body of information at a certain point you synthesize it and then boom there's something new but I've also observed in my self and other scientists that there are other ways that we are creative creative and these other ways to me are actually far more powerful I first personally experienced this when I was a freshman at MIT live over in Baker house right across the campus and I was in a calculus course 1801 is called at MIT and calculus comes in two different flavors one of them is called differential calculus the other is called integral calculus differential calculus is the calculus that Newton invented to describe motion since our integral calculus was probably invented about seventeen hundred years earlier by Archimedes but we didn't know that when I was a freshman but so that's what you study as a student and the differential calculus part of the course was to me I wouldn't how do I say this it was something that that by the driptip method you could sort of figure it out now the integral part of calculus I could memorize the formula that was not the formula that was not the problem the problem was why in my own mind why do these formulae work and because of that when I was in the part of the calculus course where we had to do multiple substitutions to solve integrals I had a lot of difficulty I was emotionally involved in my education because this is where I think the passion emotion comes to and it caused an emotional crisis that I was having these difficulties understanding the integral part of calculus so why other why that's right the why of it not the remember rote memorization of fact but the why of it why does this work and so one night I was over in my dormitory room in Baker house I was trying to do a calculus problem set I was getting nowhere I got a terrific headache I went to sleep and had this very strange dream and when I woke walk awakened I could do 3 & 4 substitutions and integrals with relative ease now this to me wasn't an astounding experience because I had never before my life understood that one subconscious is actually capable of being harnessed to do mathematics I experienced it this and I've experienced this more than once so this was just the first time why I remember it so so that's why when it comes to like really wickedly tough problems I think that the kind of creativity that you need to solve them is probably this second variety which comes somehow from dreaming if you think again I told you I'm Russian so we romanticize suffering but do you think part of that equation is the suffering leading up to that dreaming so the suffering is I am convinced that this kind of creative sick the second mode of creativity as I like to call it I'm convinced that this second mode of creativity is in fact that suffering is a kind of crucible that triggers it because the mine I think is struggling to get out of this and the only the only way the heaters actually solved the problem and even though you're not consciously solving problems something is going on and I've talked about to a few other people in there are there similar stories and so I the way I guess so I think about it is it's a little bit by like the way that thermonuclear weapons work and if you know how they work but a thermonuclear weapon is actually two bombs there's an atomic bomb which sort of Delta compression and then you have a fusion bomb that goes off and somehow that emotional pressure I think acts like the first stage of a thermonuclear weapon that's when we get really big thoughts the analogy between thermonuclear weapons and the subconscious the the connection there is uh at least visually that's kind of interesting well I there may be fried it would have a few things to say well part of it is probably based on my own trajectory through life my father was in the Army for us for the US Army for 27 years and so I started my life out on military bases and so a lot of probably the things that wander around in my subconscious are connected to the experience I apologize for all the tangents but while you're doing it but you're encouraging by me answering the stupid questions no they're not stupid you know your father was in the army what do you think about any other grass Tyson recently wrote a book on interlinking the the progress of science to sort of the aspirations of our military endeavors and DARPA funding and so on what do you think about war in general do you think we'll always have war do you think we'll always I am conflict in the world I'm not sure that we're going to be able to afford to have war always because if strictly financially speaking no not in terms of Finance but in terms of consequences so if you look at technology today you can have non state actors acquired technology for example bioterrorism which whose impact is roughly speaking equivalent to what it used to take nations to an impart on a population I think the cost of war is ultimately it's gonna be a little I think it's gonna work a little bit like the Cold War you know we survived 50 60 years as a species with these weapons that are so terrible that they could have actually ended our form of life on this planet but it didn't why didn't it well it's a very bizarre and interesting thing but it was called mutually assured destruction and so the cost was so great that people eventually figured out that you can't really use these things which is kind of interesting because if you read the history about the development of nuclear weapons businesses actually realized this pretty quickly I think it was maybe Schrodinger who said that these things are not really weapons their political and implements and not weapons because the cost is so high and if you take that example and spread it out to the kind of technological development we're seeing now outside of nuclear physics but I picked the example of biology I could well imagine that there would be material science sorts of equivalents that across a broad front of Technology you take that experience from nuclear weapons and the picture that I see is that it would be so there would be possible to develop technologies that are so terrible that you couldn't use them because the costs are too high and that might cure us and many people have argued that actually it prevented nuclear weapons have prevented more military conflict then it certainly froze the conflict domain it's an interesting that nowadays it was with the removal of the threat of mutually assured destruction that other forces took over in our geopolitics do you have worries that of existential threats of nuclear weapons or other technologies like artificial intelligence do you think we humans will tend to figure out how to not blow ourselves up I don't know quite frankly this is something I thought about and I'm not I mean so I'm a spectator in the sense that as a scientist I collect and collate data so I've been doing that all my life and looking at my species and it's not clear to me that we are going to avoid I could a catastrophic self-induced ending are you optimistic as a not as a scientist but as a I well I would say I would say I wouldn't bet against us beautifully put let's dive into the the world are very small if we could first heard it what are the basic particles either experimentally observed or hypothesized by physicists so as we physicists look at the universe you can first of all there are two big buckets of particles that is the smallest objects that we are able to currently mathematically conceive and then experimentally verify that these ideas have an accent of accuracies them so one of those buckets we call matter these are things like electrons things that are like quarks which are particles that exist inside of protons and there's a whole family of these things there are in fact 18 corks and apparently six electron like objects that we call leptons so that's one bucket the other bucket that we see both in our mathematics as well as in our experiment to equipment are what our set of particles that you can call force carriers the most familiar force carrier is the photon the particle of light that allows you to see me in fact it's the same object that carries electric repulsion between like charges from science fiction we have the object called the graviton which is talked about a lot in science fiction and Star Trek but the graviton is also a mathematical object that we physicists have known about essentially since Einstein wrote his theory of general relativity there are four forces in nature the fundamental forces there is the gravitational force its carrier is the graviton there are three other forces in nature the electromagnetic force the strong nuclear force and the weak nuclear force and each one of these forces has at one or more carriers the photon is the carrier of the electromagnetic force the strong nuclear force actually has eight carriers they're called gluons and then the weak nuclear force has three carriers they're called the W plus W minus and Z bosons so those are the things that both in mathematics and in experiments the most by the way the most precise experiments were a ever as a species able to conduct is about measuring the accuracy of these ideas and we know that at least to one part in a billion these ideas are right so first of all you've made it sound both elegant and simple but is it crazy to you that there is force carriers like is that supposed to be a trivial idea to think about if we think about photons gluons that there's four fundamental forces of physics and then those forces are expressed there's carriers of those forces like is that a kind of trivial thing it's not a trivial thing at all in fact it was a puzzle for Sir Isaac Newton because he's the first person to give us basically physics before Isaac Newton physics didn't exist what did exist was called Nath philosophy so discussions about using the methods of classical philosophy to the understand nature natural philosophy so the Greeks we call them scientists but they were natural philosophers physics doesn't get born until Newton writes the Principia one of the things that puzzled him was how gravity works because if you read very carefully what he writes he basically says and I'm paraphrasing badly but he basically says that someone who thinks deeply about this subject would find it inconceivable that what an object in one place place our location can magically reach out and affect another object with nothing intervening and so it puzzled him there's a puzzle you what doesn't in a distance I mean not as it would it would it would accept that I am a physicist and we have long ago resolved this issue and the resolution came about through a second great physicist most people heard of a Newton most people have heard of Einstein but between the two of them there was another extraordinarily great physicist a man named James Clark Maxwell and Maxwell between these two other giants taught us about electric and magnetic forces and it's from his equations that one can figure out that there's a carrier called the photon so this was resolved for physicists around 1860 or so so what are bosons and fermions and hey John's elementary and composites sure so earlier I said you've UNK it's you have got two buckets if you want to try to build a universe you have to start off without things on these two buckets so you got to have things that's the matter and then you have to either have other objects that act on them to cause those things to cohere to fixed finite patterns because you need those fixed finite patterns as building blocks so that's the way our universe looks to people like me now the building blocks do different things so let's go back to these two buckets again let me start with a bucket containing the particle of light let me imagine I'm in a dusty room with two flashlights and I have one flashlight which I direct directly in front of me and then I have you stand over to say my left and then we both take our flashlights and turn them on make sure the beams go right through each other and the beams do just that they go right through each other they don't bounce off of each other the reason the room has to be dusty is because we want to see the light because I'll let the rule dust wasn't there we wouldn't actually see the light until it got to the other wall right so you see the beam because it's dust in the air but the do things actually pass right through each other they literally pass right through they don't affect each other at all when acts like that one's not there things there are the particle flight is the simplest example that shows that behavior that's a boson now let's imagine that I have to wear in the same dusty room and this time you have a bucket of balls and I have a bucket of balls and we try to throw them so that they pass so that we get something like a beam throwing them fast right if they collide they don't just pass through each other they bounce off of each other now that's mostly because they have electric charge an electric charge is like charges repel but mathematically I know how to turn off the electric charge if you do that you'll finally still repel and it's because they are these things we call fermions so this is how you distinguish the things that are in the two buckets they are either bosons or fermions which of them and maybe you can mention the most popular of the boson the most recently discovered she's it's like yeah it's like when I was in high school and there was a really popular major rift her name is her name is the Higgs particle these days can you describe which which which of the bosons and fermions have been discovered hypothesized which have been experimentally value she was still out there right so the two buckets that I've actually described to you have all been first hypothesized and then verified by observation with the Higgs boson being the most recent one of these things we haven't actually verified the graviton interestingly enough we mathematically we have an expectation that gravitas like this but we've not performed an experiment to show that this is an accurate idea that nature uses so something has to be a carrier for the force of gravity exactly because maybe something way more mysterious than we so when you say is that would it be like the other particles force carriers in some ways yes but in other ways no it turned out that the graviton is also if you look at I in Stein's theory he taught us about this thing he calls space-time which is you know if you try to imagine it you can sort of think of it as kind of a rubber surface that's one popular depiction of space-time it's not an accurate depiction because the only accuracy is actually in the calculus that he uses but that's close enough so if you have a sheet of rubber you can wave it you can actually form a wave on it space-time is enough like that so that when space-time oscillates you create these waves these ways carry energy we expect them to carry energy in quanta that's what a graviton is it's a wave in space-time and so the fact that we have seen the waves with LIGO over the course of the last three years and we've recently use gravitational wave Observatory to watch colliding black holes and neutron stars and all sorts of really cool stuff out there so we know the waves exist but in order to know that graviton exists you have to prove that these waves carry energy in energy packets and that's what we don't have the technology to do yet and uh perhaps briefly jumping to a philosophical question does it make sense to you that gravity is so much weaker than the other forces no it's now you see now you've touched on a very deep mystery about physics there are a lot of such questions of physics about why things are as they are and as someone who believes that there are some things that certainly are coincidences like you could ask the same question about well why are the planets at the orbits that they are around the Sun the answer turns out there is no good reason it's just an accident so there are things in nature that have that character and perhaps the strength of the weak of the various forces it's like that well the other thing we don't know that that's the case and there may be some deep reasons about why the forces are ordered as they are where the weakest forces gravity the next week is forces the weak interaction the weak nuclear force then there's electromagnetism this we don't really have a good understanding of why this is the ordering of the forces some of the fascinating work you've done is in the space of supersymmetry symmetry in general can you describe first of all what is supersymmetry ah yes so you remove the two buckets I told you about perhaps earlier I said there are two buckets in our universe so now I want you to think about drawing a a pie that has four quadrants so I want you to cut the piece of pie in fourths so one quadrant I'm going to put all the buckets that we talked about like that are like the electronic quarks in a different quadrant I am going to put all the force carriers the other two quadrants are empty now if you I showed you a picture of that you'd see a circle there would be a bunch of stuff in one upper quadrant and stuff in others and then I would ask you a question does that look symmetrical to you no no and that's exactly right because we humans actually have a very deeply programmed sense of symmetry it's something that is part of that mystery of the universe so how would you make it symmetrical one way you could is by saying those two empty quadrants had things in them not so and if you do that that's supersymmetry so that's what I understood when I was a graduate student here in at MIT in 1975 weeding the idea when the mathematics of this was first being born supersymmetry was actually born in the Ukraine in the late 60s but we have this thing called the iron curtain so we Westerners didn't know about it but by the early 70s independently there were scientists in the West who had rediscovered supersymmetry symmetry bruno Cimino and julius vests were their names so this was around 71 or 72 when this happened I started graduate school in 73 so around 74 75 I was trying to figure out how to write a thesis so that I could have become a physicist the rest of my life I did a lot of great advisor professor James Young who had taught me a number of things about electrons and weak forces and those sorts of things but I decided that if I was going to have a really opportunity to maximize my chances of being successful I should strike it out in a direction that other people were not studying and so as a consequence I surveyed ideas that were going that were being developed and I came across the idea of supersymmetry and it was so the mathematics was so remarkable that I just it bowled me over I actually have two undergraduate degrees my first undergraduate degree is actually mathematics and my second is physics even though I always wanted to be a physicist plan a which involved getting good grades was mathematics I was a mathematics major thinking about graduate school but my heart was in physics if we could take a small digression what's to you the most beautiful idea in mathematics that you've encountered in this interplay between math and physics it's the idea of symmetry the fact that our innate sense of symmetry want wines of aligning with just incredible mathematics to me is the most beautiful thing it's very strange but true that if symmetries were perfect we would not exist and so even though we have these very powerful ideas about balance in the universe in some sense it's only when you break those balances that you get creatures like humans and objects like planets and stars so although they are a scaffold for reality they cannot be the entirety of reality so I I'm kind of naturally attracted to parts of Science and Technology where symmetry plays note a dominant role and not just I guess symmetry as you said but the the magic happens when you break the symmetry the magic happens when you break the symmetry okay so diving right back in you mentioned four quadrants yes - - or filled with stuff what can we do buckets yeah and then there's crazy mathematical thing ideas for filling the other two what are those things so earlier the way I described these two buckets as I gave you a story that started out by putting us in a dusty room with two flashlights and I said turn on your flashlight I'll turn on mine the beans will go through each other and the beams are composed of force carriers called photons they carry the electromagnetic force and they pass right through each other so imagine looking at the mathematics of such an object which you don't imagine people like me do that so you take that mathematics and then you ask yourself a question you see mathematics is a palette it's just like a a musical composer is able to construct to construct variations on a theme well a piece of mathematics in the hand of a physicist something that we can construct variations on so even though the mathematics that Maxwell gave us about light we know how to construct very issues on that and one of the very issues you can construct is to say suppose you have a force carrier for electromagnetism that behaves like an electron that in that it would bounce off of another one it's so that's changing a mathematical term in an equation so if you did that you would have a force carrier so you would say first it belongs in this force carrying bucket but it's got this property of bouncing off like electrons and so you say well gee wait no that's not the right bucket so you're forced to actually put it in one of these empty quadrants so those sorts of things we basically we give them so the photon mathematically can be accompanied by a photino it's the thing that carries a force but has the rule of bouncing off in a similar manner you could start with an electron and you say okay so write down the mathematical is electron I know I want to do that physicists name Dirac first told us how to do that back in the nineteen late 20s early 30s so take that mathematics and then you say let's let me look at that mathematics and find out what in the mathematics caused us two electrons to bounce off of each other even if I turn off the electrical charge so I could do that and now let me change that mathematical term so now I have something that carries electrical charge but if you take two of them I'm sorry if you turn their charges off they'll pass through each other so that puts things in the other quadrant and those things we till we tend to call we put the Essen in front of their name so in the lower quadrant here we have electrons and this now newly filled quadrant we have select rods and the quadrant over here we had corks over here we have squirts so now we've got this balance pie and that's basically what I understood as a graduate student in 1975 about this idea of supersymmetry that it was going to fill up these two quadrants of the pie in a way that no one had ever thought about before so I was amazed that no one else at MIT found this an interesting idea so that's it led to my becoming the first person in MIT to really study supersymmetry this is 1975 76 77 and in 77 I wrote the first PhD thesis in the physics department on this idea because I just I must draw to the balance drawn to the symmetry so what boundary what does that first of all is this fundamentally a mathematical idea so how much experimental and we'll have this theme it's an really interesting one when you explore the worlds of the small and in your new book talking about approving is that right right that will also talk about there's this theme of kind of starting and exploring crazy ideas first in the mathematics and then seeking for ways to experiment to validate them where do you put some supersymmetry and that's it's closer than string theory it is not yet been validated in some sense you mentioned Einstein so let's go there for a moment in our book proofing Einstein right we actually do talk about the fact that Albert Einstein in 1915 wrote a set of equations which were very different from Newton's equations and describing gravity these equations made some predictions that were different from Newton's predictions and it actually made three different predictions one of them was not actually a prediction but a post diction because it was known that mercury was not orbiting the Sun in the way that Newton would have told you and so I science Theory actually makes describes mercury orbiting in the way that it was observed as opposed to what Newton would have told you that was one prediction the second prediction that came out of the theory of general relativity which Einstein wrote in 1915 was that if you if so let me describe an experiment and come back to it suppose like a glass of water and I filled it up fill the glass up and then I moved the glass slowly back and forth between our two faces it would appear to me like your face was moving even though you weren't moving I mean it's actually and what's causing it is because the light gets bent through the glass has it passes from your face to my eye so Einstein in his 1915 theory of general relativity found out that gravity has the same effect on light as that glass of water it would cause beams of light tube in now Newton also knew this but Einstein's prediction was that light would Bend twice as much and so here's a mathematical idea now how do you actually prove it well you've got to watch yes just a quick pause on that just the language you're using he found out I can say he did a calculation it's a really interesting notion that the one of the most and one of the beautiful things about this universe is you can do a calculation and and combined with some of that magical intuition that physicists have actually predict what would be was possible to experiment to validate that's correct so he found out in the sense that there seems to be something here and mathematically should bend gravity should bend like this amount and so therefore that's something that could be potentially and then come up with an experiment that can be validated right and that's the way that actually modern physics deeply fundamental modern physics is how it works you earlier we spoke about the Higgs boson so why did we go looking for the answer is they had back in the late 60s and early 70s some people wrote some equations and the equations predicted this so then we went looking for it so uh none supersymmetry for a second there's these things called Adinkra symbols strange little grass yes you referred to them as revealing something like binary code yes underlying reality yes or so can you describe these grout what are they what what what are these beautiful little strange graphs well first of all the Dinkas are an invention of mine and together with a colleague named Michael Fox in 2005 we were looking at equations well so the story's a little bit more complicated and it'll take too long it's explained all the details but the Reader's Digest version is that we were looking at these equations and we figured out that all the data in a certain class of equations could be put in pictures and the pictures what do they look like whether just they're just little balls you have black balls and white balls those stands for those two buckets by the way that we talked about in reality the white balls or things that are like particles of light the black balls are like electrons and then they you can draw lines connecting these balls and these lines are deeply mathematical objects and there's no way for me to I have no physical model for telling you what the lines are but as a math if you were a mathematician and with your technical phrase saying this is the orbit of the representation and the action of the symmetry generators mathematicians would understand that nobody in there else in their right mind was so let's not go there so we but we figured out that the data that was in the equation suddenly it was in these funny pictures that we could draw and so that was stunning but it also was encouraging because there aren't problems with the equations which I had first learned about in 1979 when I was down at Harvard and I went out to Caltech for the first time and working with a great scientist by the name of John Schwarz there are problems in the equations we don't notice all and so one of the things about solving problems that you don't know how to solve is that beating your head against the brick wall is probably not a good philosophy about how to solve it so what do you need to do you need to change your sense of of reference your frame of reference your perspective so when I saw these funny pictures I thought gee that might be a way to solve these problems with equations that we don't know how to do so that was for me when the first attractions is that I now had an alternative language to try to attack a set of mathematical problems but I quickly realized that a this mathematical language was not known by mathematicians which makes it pretty interesting because now you have to actually teach mathematicians about a piece of mathematics because that's how they make their living and the great thing about working mathematicians of course is the rigor with which they examine ideas so they make your ideas better then they start out so I start working with a group of mathematicians and there's in that collaboration that we figured out that these funny pictures had error correcting codes buried in them so can you can talk about what our error correcting codes are sure so the simplest way to talk about error correcting codes is first of all to talk about digital information digital information is basically strings of ones and zeros they're called bits so now let's imagine that I want to send you some bits well maybe I can show you pictures but maybe it's a rainy day or maybe the windows in your house are foggy so sometimes when I show you a zero you might interpret it as a one or other times when I show you one you might interpret it as a zero so if that's the case that means when I try to send you this data it comes to you in corrupted form and so the challenge is how do you get it to be uncorrupted in the 1940s a computer scientist named hemming address the problem how do you reliably transmit digital information and what he came up with with was a brilliant idea the way to solve it is that you take the data that you want to send and then once in your strings of 1 0 is your favorite string and then you've dumped more ones and zeros then but you dump them in in a particular pattern and this particular pattern is what a Hamming code is all about so it's an error correcting code because if you the person at the other end knows what the pattern is supposed to be they can figure out when once got changed the zeros so it turned out that our strange little objects that came from looking at the equations that we couldn't solve it turns out that when you look at them deeply enough you find out they're strictly that they have ones and zeros back buried in them but even more astoundingly that ones and zeroes are not there randomly they are in the pattern of error correcting codes so this was an astounding thing that when we first got this result and tried to publish it it took us three years to convince other physicists that we weren't crazy mm-hmm eventually we were able to publish it I in this collaboration of mathematicians and other physicists and so every since then I have actually been looking at the mathematics of these objects trying to still understand properties of the equations and I want to understand the properties equations because I want to be able to try things like electrons so it's just like a two step remove process of trying to get back to reality so what would you say is the most beautiful property of these dinkar graphs objects what do you think what by the way the word symbols what do you think of them these simple graphs are they objects or their haha work with mathematics like me our mathematical concepts are we often refer to them as objects because they feel like real things even though you can't see them or touch them there's so much part of your interior life that it is as if you could so we often refer to these things as objects even though there's nothing objective about them and what is this a single graph represent and so ok so the simplest of these graphs has to have one white ball in one black ball that's that balance that we talked about earlier we want to balance out the quadrants well you can't do this you have a black ball and white ball so the simplest of these objects looks like two little balls one black one white connected by a single line and whether it's talking about is as I said a deep mathematical property related to symmetry you've mentioned the air correcting codes but is there a particular beautiful property that stands out to you about these objects they just find yeah they're very yes very early on in the development yes there is the craziest thing about these to me is that when you look at physics and try to write equations where information gets transmitted reliably if you're in one of these super symmetrical systems with this extra symmetry that doesn't happen unless there's an error correcting code present so as as if the universe says you don't really transmit information unless there's something about an error correcting code this to me is the craziest thing that I've ever personally encountered in my research and it actually got me to wondering how this could come about because the only place in nature that we know about error correcting codes is genetics and in genetics we think it was evolution that causes air correcting codes to be in genomes and so does that mean that there was some kind of form of evolution acting on the mathematical laws of the physics of our universe this is a very bizarre and strange idea and something I've wondered about from time to time since making these discoveries do you think such an idea could be fundamental or is it emergent throughout all the different kinds of systems I don't know whether it's fundamental and I probably will not live to find out this is gonna be the work of probably some future either mathematicians physicists to figure out what these things actually mean we have to talk a bit about the magical the mysterious string theory the purse string theory sure there's still maybe this aspect of it which is there still for me from an outsider's perspective of this fascinating heated debate on the status of string theory can you clarify this debate perhaps articulating the various views and say where you land on it so first of all I mean I doubt that I will be able to say anything to clarify clarify the debate around string theory for for general audience part of the reason is because string theory is a has been something I've never seen the erecto physics do it is broken out into consciousness of the general public before we're finished you see string theory doesn't actually exist because when we use the word theory we mean a their set of attributes in particular it means that you have an overarching paradigm that explains what it is that you're doing no such overarching paradigm exists or string theory what string theory is currently is an enormous lean large mutually reinforcing collection of mathematical facts in which we can find no contradictions we don't know why it's there but we can certainly say that without challenge now just because you find a piece of mathematics doesn't mean that it's applies to nature and in fact there has been a very heated debate about whether string theory is some sort of hysteria among the community of theoretical physicists or whether it has something fundamental to say about our universe we don't yet know the answer to that question but those of us who study string theory will tell you are things like string theory has been extraordinarily productive in getting us to think more deeply even about mathematics that's not string theory but the kind of mathematics that we've used to describe elementary particles they have been spin-offs from string theory and this has been going on now for two decades almost that I have allowed us for example to more accurately calculate the force between electrons with the presence of quantum mechanics this is not something you hear about in the public there are other similar things the kind of that kind of property I just told you about is what to call weak strong duality and it comes directly from string theory there are other things such as a property called holography which allows one to to take equations and look at them on the boundary of a space and then to know information about inside space without actually doing calculations there this has come directly from string theory so there are there are a number of direct mathematical effects that we learn this string theory but we take these ideas and look at math that we already know and we find sudden we're more powerful this is pretty good indication there's something interesting going on with string theory itself so it's the early days of a powerful mathematical framework that's what we have right now what are the big first of all those most people will probably that which as you said most general public would know actually what string theory is which is a at the highest level which is a fascinating fact well string theory is what they do on the Big Bang Theory right one can you maybe describe what is string theory and two what are the open challenges so what is string theory well let the simplest explanation I can provide is to go back and ask water particles which is the question you first ask me what's the smallest thing yeah what's the smallest thing so particles one way I try to describe particles to people a star I want you to imagine a little ball and I want you to let this size of that ball shrink into it has no extent whatsoever but it still has the mass of the ball that's actually what Newton was working with when he first invented physics he's the real inventor of the massive particle which is this idea that underlies all of physics so that's where we start it's a mathematical construct that you get by taking a limit of things that you know so what's a string well in the same analogy I would say now I want you to start with a piece of spaghetti so we all know what that looks like and now I want you to let the thickness of the spaghetti shrink until it has no thickness mathematically I mean words this makes no sense mathematically this actually works and you get this mathematical object out it has properties that are like spaghetti it can wiggle and jiggle but it can also move collectively like a piece of spaghetti then it's the mathematics of those sorts of objects that constitutes string theory and does the multi-dimensional 11 dimensional however many dimensional more than four dimension is that a crazy idea to you is that is that the stranger aspect of strength not really and also partly because of my own research so earlier we talked about a dink these strange symbols that we've discovered inside the equations it turns out that to a very large extent a tinker's don't really care about the number of dimensions they kind of have an internal mathematical consistency that allows them to be manifest in many different dimensions since supersymmetry is a part of string theory then this same property you would expect to be inherited by string theory however another little-known fact which is not in the public debate is that there are actually strings that are only four dimensional this is something that was discovered at the end of the 80s by three different groups of physicists working independently I and my friend Warren Siegel who were at the University of Maryland at the time were able to prove that there's mathematics it looks totally four-dimensional and yet it's a string there was a group in Germany that used slightly different mathematics but they found the same rizzo and then there was a group at Cornell who using yet a third piece of mathematics found the same yourself so the the fact that extra dimensions is so why they talked about in the public is partly a function of how the public has come to understand string theory and how it's the story has been told to them but there are alternatives you don't know about if we could talk about maybe experiments of validation and you you're the co-author of a recently published book proving Einstein right the the human story of it - the daring expeditions that changed how we look at the universe do you see echoes of the early days of general relativity in the 1910s - the more stretched out - string theory I just nodded I do and that's one reason why I was happy to focus on on the story of how Einstein became a global superstar earlier in our discussion we went over the the his history where in 1915 he he came up this piece of mathematics used it to do some calculations and then made a prediction yes but making a prediction is not enough someone's got to go out and measure and so string theory is in that in-between zone now for Einstein it was from 1915 to 1919 1950 he makes the makes the correct prediction by the way he made an incorrect prediction about the same thing in 1911 but he corrected himself in 1915 and by 1919 the first pieces of experimental observational data became available to say yes he's not wrong and by 1922 the the argument that based on observation was overwhelming that he was not wrong he described what special and general relativity are just briefly sure since and what prediction Einstein made and maybe maybe some or memorable moment from the human journey of trying to prove this thing right she was incredible right so I'm very fortunate to have worked with a talented novelist who wanted to write a book that coincided with a book I wanted to write about how science kind of feels if you're a person guess it's actually people who do science even though that may not be obvious to everyone so for me I wanted to write this book for a couple of reasons I wanted young people to understand that the seeming alien Giants that lived before them were just as human as they are you get married you get divorced again married they get worse they do terrible things they do great things they're people they're just people like you and so that part of telling the story allowed me to get that out there for both young people interest in the sciences as well as the public but the other part of the story is I wanted to open up sort of what what it was like now I'm a scientist and so I will not pretend to be a great writer I understand a lot about mathematics and I've even created my own mathematic that you know it's kind of a weird thing to be able to do but in order to tell the story you really have to have an incredible master of the narrative and my that was my co-author Kathy Pelletier who is a novelist we so we formed this conjoined brain I used to call us she's the call us professor Higgins and Eliza Doolittle my expression for us was that we were a conjoined brain to tell this story and it allowed so what are some magical moments to me the first magical moment in telling the story was looking at Albert Einstein in his struggle because although we regard him as a genius as I said in 1911 he actually made an incorrect prediction about spending starlight and that's actually what set the astronomers off in 1914 there was an eclipse and by various accidents of war and weather and all sorts of things that we talked about in the book no one was able to make the measurement if they had made the measurement it would have disagreed with his 1911 prediction because nature only has one answer and so you then you see how fortunate he was that Wars and bad weather and accidents and transporting equipment stopped any measurements from being made so he corrects himself in 1915 and but the astronomers are already out there trying to make the measurement so now he gives them a different number and it turns out that's the number that nature agrees with so it gives you a sense of this is a person struggling with something deeply and it although his deep insight led him to this it is the circumstance of time place an accident but through which we view him and it could the story could have turned out very differently where first he makes the prediction the measurements are made in 1914 they disagree with his prediction and so what would the world view him as well he's this professor who made this prediction that didn't get it right yes so the fragility of human history is illustrated by that story and this is one of my favorite things you also learn things like in our book how eclipses and watching eclipses was a driver of the development of science in our nation when it was very young in fact even before we were a nation turns out they were citizens or citizens of this would be country they were going out trying to measure eclipses so some fortunes some misfortune affects the progress of science especially with ideas as to me at least if I put myself back in those days as radicals general relativity is first can you describe if it's okay briefly what general relativity is and yeah if you could you just take a moment if ya put yourself in those shoes in the eka and academic researchers scientists of that time and what is this theory what is it trying to describe about our world it's trying to answer the thing that left Isaac Newton puzzled Isaac Newton says gravity magically goes from one place to another he doesn't believe it by the way he knows that's not right but the mathematics is so good that you have to say well I'll throw my qualms away because I'll use it that's all we use to get for a man from the earth to the moon was that mathematics so I'm one of those scientists and I've seen this and if I thought deeply about it maybe I know that Newton himself wasn't comfortable and so the first thing I would hope that I would feel is gee this is young kid out there who has an idea to fill in this hole that was lay left with us by Sir Isaac Newton that would I hope would be my reaction I have a suspicion I'm I'm kind of a mathematical creature I was four years old when I first decided that size was what I wanted to do my and so if my personality back then was like it is now I think it's probably likely I would want to want to have studied his mathematics what was a piece of mathematics that he was using to make this prediction because he didn't actually create that mathematics that math.max was created of roughly fifty years before he lived he's the person who harnessed it in order to make a prediction in fact he had to be taught this mathematics by a friend so this is in our book so putting myself in that time I would want to like I said I think I would feel excitement I would want to know what the mathematics is and then I wouldn't want to do the calculations myself because one thing that physics is all about is that you don't take anybody's word for anything it's you can do it yourself it does seem that mathematics is a little bit more tolerant of radical ideas or mathematicians some people who find beauty in mathematics why all the white questions have no good answer let me ask why do you think Einstein never got the Nobel Prize for general relativity he got it for the photoelectric effect that is correct well there first of all that's something that is misunderstood about the Nobel Prize in Physics the Nobel Prize in Physics is never given for purely giving for purely proposing an idea it is always given for proposing an idea that has observational support so he could not get the Nobel Prize for either special relativity nor gen relativity because the provisions that Alfred Nobel left for the award prevent that but after it's been validated cannot get it then or no yes but remember the validation doesn't really come until the 1920s but that's why they invented the second Nobel Prize I mean very Curie you can get in second Nobel Prize for one of the greatest so so linear ease in physics so let me let's be clear on this the theory of general relativity had its critics even up until the 50s so if you had if had if the committee had wanted to give the prize for general relativity there were vociferous critics of general relativity up until the 50s Einstein died in 1955 what lessons do you draw from from the storytelling the book from general activity from the radical nature of the theory to looking at the future string theory well I think that the string theorists are probably going to retrace this path but it's gonna be far longer and more torturous in my opinion string theory is such a broad and deep development that in my opinion when it becomes acceptable it's going to be because of a confluence of observation it's not gonna be a single observation and I have to tell you that so I give a seminar here yesterday to my team and it's it's on an idea I have about how string theory can leave signatures in the Cosmic Microwave Background which is a Astro physical structure and so if those kinds of observations are borne out if perhaps other things related to the idea of supersymmetry borne out those are going to be the first powerful observational II based pieces of evidence that will begin to do what the Eddington expedition did in 1919 but who that may take several decades do you think there will be Nobel Prizes given for string theory no because because I think the arrays it'll be you'll be I think it will exceed normal human lifetimes but there are other prizes that are given I mean there is something called the breakthrough prize there's a Russian emigre a Russian American immigrant named Yuri Milner I believe is they started this wonderful prize called the breakthrough prize it's three times as much money since Novell fries and he gets awarded every year and so something like one of those prizes is likely to be garnered at some point far earlier than a Nobel award jumping around a few topics while you were at Cal Tech you've gotten to interact I believe with Richard Fineman I have to ask yes do you have any stories to stand on your memory of that I have a fair number of stories but I'm not prepared to tell them they're not all politically correct copy but well let me just say I'll say the following Richard Fineman if you've ever read some of the books about him in particular there's a book called surely you're joking mr. Feinman there's a series of books that starts with surely you're joking mr. fireman and I think the segment may be something like what do you care what they say or something I mean their titles are all in there three of them when I read those books I was amazed at how accurately those books betray the man that I interacted with he was irreverent he was fun he was deeply intelligent he was deeply human and those books tell that story very effectively even just those moments how did they affect you as a physicist well one of the well it's funny because one of the things that I didn't hear firemen say this but one of the things that is reputed we've reported that he said is if you're on a barstool as a physicist and you can't explain to the guy on the barstool next to you what you're doing you don't understand what you're doing and there's a lot of that that I think is correct that that when you truly understand something as complicated as string theory when it's in its fully formed final development it should be something you could tell to the person on the barstool next to you and I that's something that affects the way I do science quite frankly it also affects the way I talked to the public about science I it's one of them sort of my mantras that I keep deeply in tried to keep deeply before me when I appear in public fora speaking about physics in particular in science in general it's also something that Einstein said in a different way he he said he had these two different formulations one of them is when the answer simple is God speaking and the other thing that he said was that what he did what he did in his work was simply the distillation of common sense that you distill down to something and he also said you make things as simple as possible but no simpler so all of those things and certainly this attitude for me first sort of seeing this was exemplified by being around Richard Fineman so in all your work you're always kind of searching for the simplicity for all the early ultimately I am you served on President Barack Obama's Council of Advisors in science and technology for seven years yes for seven years with Eric Schmidt and several other billion people met Eric for the first time in nineteen in 2009 when the council was called together yeah seen pictures of you in that room I mean there's a bunch of brilliant people it kind of looks amazing what was that experience like being called upon that kind of service so let me go back to my father first of all i earlier mentioned that my father served 27 years in the US Army starting in World War two he went off in 1942-43 to fight against the fascist he was part of the supply corps that supplied General Patton as the tanks rolled across Western Europe pushing back the forces of Nazism to meet up with our Russian comrades who were pushing the Russian you know pushing the Nazis starting in Stalingrad and you know this you know think of a war is actually a very interesting upset a piece of history too and know from both sides and here in America we typically don't but I've actually study history as an adult so I she know sort of the whole story and on the Russian side we don't know the Americans we weren't taught the I know I know I have many many Russian friends and we've had this conversation in the occasional but you know like general Zhukov for example was something that you would know but you might not know about a patent but you're right so do you or gives you cough or raucous offski I mean there's a whole list of names that I've learned in the last 15 or 20 years looking at the Second World War so if father was in the midst of that probably one of the greatest warrior wars in the history of our species and so the idea of service comes to me essentially from that example so in 2009 when I first got a call from from a Nobel laureate actually in my biology Harold Varmus the only way to India and I got this email message and he said it needed to talk to me and I said okay fine we can talk got my castes I didn't hear from him we went through several cycles of this something invested I want to talk to you and then never contacted and finally I was on my way to give a physics presentation the University of Florida in Gainesville and just just that stepped off a plane and my mobile phone off and it was Harold and so I said Harold why do you keep sending me messages that you want to talk but you never call and he said well I'm sorry things have been hectic and that a data and then he said if you were offered the opportunity to serve on the US President's Council of Advisors on science and technology what would be your answer I was amused that the formulation of the question yeah yeah because it's clear that there's a purpose of why the question is asked that way but then he made it clear to me he wasn't joking and literally my one of the few times in my life my knees went weak and I had to hold myself up against the wall so that I didn't fall over I doubt if most of us who have been the beneficiaries of the benefits of this country when given that kind of opportunity could say no and I know I certainly couldn't say no I was frightened out of my wits because I had never although I have my my career in terms of policy recommendations is actually quite long goes back to the 80s but I have never been called upon to serve as an advisor to a President of the United States and it was very scary but I did not feel that I could say no because I wouldn't be able to sleep with myself at nights saying you know that I chickened out or whatever and so I took the plunge and we had a pretty good run there are things that I did in those seven years that of which I'm extraordinarily proud one of the ways I tell people is if you've ever seen that television cartoon called Schoolhouse Rock is this one story about how a bill becomes a law and I've kind of lived that there are things that I did that have now been codified in US law not everybody gets a chance to do things like that in life what do you think is the you know Science and Technology especially in American politics you know we haven't had a president who's an engineer or a scientist what do you think is the role of a president like President Obama in understanding the latest ideas in science and time what was that experience like well first of all I've met other presidents beside President Obama he is the most extraordinary president I've ever encountered despite the fact that he went to Harvard when I think about President Obama I I he is a deep mystery to me in the same way perhaps that these new verses of mystery I don't really understand how that constellation of personalities could personality traits could come to fit within a per single individual but I saw them for seven years so I'm convinced that I wasn't seeing fake news seeing real data he was just an extraordinary man and one of the things that was completely clear was that he was not afraid and not intimidated to be in a room of really smart people I mean really smart people that he was completely comfortable in asking some of the world's greatest experts what do I do about this problem and it wasn't that he was going to just take their answer but he would listen to the advice and that to me was extraordinary as I said I've been around other executives and I've never seen qua one quite like him he's an extraordinary learner that's what I observed and not just about science but he has a way of internalizing information in real time that I've never seen in a politician before even in extraordinarily complicated situations even scientific ideas scientific or non-scientific complicated ideas don't have to be scientific ideas but I have like I said I've seen him in real time process complicated ideas with a speed that was stunning in fact he's shocked the entire council I mean we were all stunned at his capacity to be presented with complicated ideas and then to wrestle with him and internalize them and then come back more interestingly enough come back with really good questions to ask I've noticed this is in an area that I understand more of artificial intelligence I've seen him integrate information about artificial intelligence and then come out with these kind of richard fineman like insights that's exactly right and that's that as I said those of us who have been in that position it is stunning to see it happen because you don't expect it yeah it takes what for a lot of sort of graduate students takes like four years in a particular topic he just does it in a few minutes I have like learn naturally you've mentioned that you would love to see experimental validation of superstring theory before you before I'll double off this mortal coil which the poacher that reference made me smile oh well si you know people who actually misunderstand that because it's not what it doesn't mean what we generally take it to mean colloquially but it's such a beautiful expression yeah it is it's from the hamlet to be or not to be a speech which I still don't understand what that's above interpretation anyway the what are the most exciting problems in physics they're just within our reach of understanding and maybe solve the next two decades they you may be able to see so in physics you limited it to physics physics mathematics this kind of space of problems that fascinate you well the one that looks on the immediate horizon like we're gonna get to is quantum computing and that's gonna if we actually get there that's gonna be extraordinarily interesting do you think that's a fundamentally problem of theory or is it now in the space of engineering it's in the space of engineering I was not a cue station as you may know Microsoft has this research facility in Santa Barbara I was out there a couple of months in my capacity as a vice president of American Physical Society and I got a you know I had some things that were like lectures and they were telling me what they were doing and it sure sounded like they knew what they were doing and the thing were close to major breakthroughs yeah that's a really exciting possibility there but the back to Hamlet do you ponder mortality your own mortality nope my mother died when I was 11 years old and so I immediately knew what the end of the story was for all of us as a consequence I've never never spent a lot of time thinking about death it'll come in its own good time and sort of to me the job of every human is to make the best and the most of the time that's given to us in order not for our own selfish gain but to try to make this place a better place for someone else and on the Y of life why do you think we are I have no idea and I never even worried about it for me I haven't answered a local answer the apparent why for me was because I'm supposed to do physics but it's funny because there's so many other quantum mechanically speaking possibilities in your life such as being an astronaut for example so you know what that I see well like like Einstein and the vicissitudes that prevented the 1914 measurement in the starlight finding the universe is constructed in such a way that I didn't become an astronaut which would have for me I would have faced the worst choice in my life whether whether I would try to become an astronaut or whether I would try to do theoretical physics both of these dreams were born when I was four years old simultaneously and so I can't imagine how difficult that decision would have been the universe helped you out on that one not only in that one but in mini ones and it helped me out by allowing me to pick the right bad is there a day in your life you could relive because it made you truly happy what day would that be if you could just look that being a theoretical physicist is like having Christmas every day I have lots of joy in my life the the moments of invention the moments of ideas revelation yes the only thing I exceed them are some family experiences like when my kids were born and that kind of stuff but they're pretty high up there well I don't see a better way to end it Jim thank you so much as a huge honor talking today this worked out better than I thought glad to hear thanks for listening to this conversation with s James Gates Jr and thank you to our presenting sponsor cash app download it and use code let's podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on YouTube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from the great Albert Einstein for the rebels among us unthinking respect for authority is the greatest enemy of truth thank you for listening and hope to see you next time you |
Sebastian Thrun: Flying Cars, Autonomous Vehicles, and Education | Lex Fridman Podcast #59 | following is a conversation with Sebastian Thrun he's one of the greatest roboticists computer scientists and educators of our time he led the development of the autonomous vehicles at Stanford that one 2005 DARPA Grand Challenge and placed second in the 2007 DARPA urban challenge he then led the Google self-driving car program which launched the self-driving car revolution he taught at the popular Stanford course on artificial intelligence in 2011 which was one of the first massive open online courses or MOOCs as they're commonly called that experience led him to co-found Udacity an online education platform if you haven't taken courses on it yet I highly recommended their self-driving car program for example is excellent he's also the CEO of Kitty Hawk a company working on building flying cars are more technically Evie tall's which stands for electric vertical takeoff and landing aircraft he has launched several revolutions and inspired millions of people but also as many know he's just a really nice guy it was an honor and a pleasure to talk with him this is the artificial intelligence podcast if you enjoy subscribe I need to give it five stars and Apple podcasts follow it on Spotify supported on patreon or simply connect with me on Twitter and Lex Friedman spelled Fri D ma M if you leave a review on Apple podcast or YouTube or Twitter consider mentioning ideas people topics you find interesting it helps guide the future of this podcast but in general I just love comments with kindness and thoughtfulness in them this podcast is a side project for me as many people know but I still put a lot of effort into it so the positive words of support from an amazing community from you really helped I recently started doing ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle they can break the flow of the conversation I hope that works for you and doesn't hurt the listening experience I provide time stamps for the start of the conversation that you can skip to but it helps if you listen to the ad and support this podcast by trying out the product service being advertised this show is presented by cash app the number one finance app in the App Store I personally use cash up to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member has site PC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and charity navigator which means the donated monies used the maximum effectiveness when you get cash out from the App Store or Google Play and use coal export gas you'll get ten dollars in cash up we'll also donate ten dollars the first which again is an organization that I've personally seen inspired girls and boys the dream of engineering a better world and now here's my conversation or Sebastian Thrun you mentioned that the matrix may be your favorite movie so let's start with the crazy philosophical question do you think we're living in a simulation and in general do you find the thought experiment interesting define simulation I would say maybe we are not but it's completely irrelevant to the way we should act putting aside for a moment the fact that it might not have any impact on how we should act as human beings for people studying theoretical physics these kinds of questions might be kind of interesting looking at the universe's information processing system the universe is an information processing system is a huge physical biological chemical computer there's no question but I live here and now I care about people okay about us what do you think is trying to compute and I think there's an intention I think it just the world evolves the way it devolves and it's it's beautiful is unpredictable and I'm really grateful to be alive spoken like a true human which last time I checked that was oh that in fact this whole conversation is just a touring test to see if if indeed if indeed you are you've also said that one of the first programs of the first few programs you've written was a wait for a TI 57 calculator yep maybe that's early eighties I don't wanna date calculators anything early eight is correct yeah so if you were to place yourself back into that time into the mindset you are in because you have predicted the evolution of computing AI the internet technology in in the decades that followed I was super fascinated by Silicon Valley which I seen on television once and thought my god this is so cool they build like D Rams there and CPUs how cool is that and as a college students a few year later a few days later I decided to be study intelligence and study human beings and found that even back then in the 80s and 90s that artificial intelligence is what fascinated me the most I was missing is that back in the day the computers are really small they're like the brains you could build well not anywhere bigger as a cockroach and cock-horse aren't very smart so we weren't at the scale yet where we are today did you dream at that time to achieve the kind of scale we have today did that seem possible I always wanted to make robots smart I felt it was super cool to build an artificial human and the best way to build not official you want to be a robot because that's kind of the closest if you could do unfortunately we aren't there yet there were words today are still very brittle about as fascinating to study intelligence from a constructive perspective it built something to understand you build what do you think it takes to build an intelligent system and an intelligent robot I think the biggest innovation that we've seen as machine learning and it's the idea that their computers can BC teach themselves let's give an example I'd say everybody pretty much knows what a wok and we learn how to walk in the first year two of our lives but no scientist has ever been able to write on the rules of human gait we don't understand that we can't put we have in our brain somehow we can practice it we understand it that we can articulate that we can't pass it on by language and that to me is kind of a deficiency of today's computer programming even you could program a computer they're so insanely dumb that you have to give them rules for every contingencies very unlike the way people learn but learn from data and experience computers are being instructed and because it's so hard to get this instruction set right we pay software engineers two hundred thousand dollars a year now the most recent innovation which has been to make for like 3040 years is an idea that computers can find their own rules so they can learn from falling down and getting up the same way children can learn from falling down and getting up and that revolution has led to a capability that's completely unmatched today's computers can watch experts do their jobs whether you're a doctor or lawyer pick up the regularities learn those rules and then become as good as the best experts so the dream of in the 80s of expert systems for example had at its core the idea that humans could boil down their expertise on a sheet of paper so sort of reduce sort of be able to explain to machines how to do something explicitly so do you think what's the use of human expertise into this whole picture do you think most of the intelligence will come from machines learning from experience without human expertise input so the question for me is much more how to express expertise um you can express expertise providing a book you can express expertise by showing someone what you're doing you can express expertise by applying it by by many different ways and I think the expert systems was our best attempt in AI to capture expertise in rules there someone sat down and say here the rules of human gait here's when you put your big toe forward and your heel backwards and Yahoo stop stumbling and as we now know the set of rules a set of language that he can command is incredibly limited the human brain doesn't deal with language it is with that subconscious numerical perceptual things that we don't even ever survey off now when a AI system watches an expert do their job and practice their job it can pick up things that people can't even put into writing into books or rules and that's where the real power is we now have AI systems that for example look over the shoulders of highly paid human doctors like dermatologist or radiologists and they can somehow pick up those skills that Noah can express in words so you were a key person in launching three revolutions online education and Thomas vehicles and flying cars or vetoes so high level and I apologize for all the philosophical questions that's no policy necessary how do you choose what problems to try and solve drives you to make those solutions a reality I have two two desires in life I want to literally make the lives of others better or as few of them say maybe joke indeed what make the world a better place if you believe in us it's as funny as it sounds and second I want to learn I want to get in the circus I don't want to be in a dropping with it because if I meant job that I'm good at the chance for me to learn something interesting is actually minimized so I want to be in a job I'm bad at that's really important to me so I'm in a bill for example but people often call flying cars is that electrical vertical takeoff and landing vehicles I'm just no expert in any of this and it's so much fun tool to learn on the job what actually means to build something like this now it's saying that the stuff that I done lately after I finished my professorship at Stanford the video focused on like what has the maximum impact on society like transportation is something has transformed the 21st 20th century more than any other invention of my opinion even more than communication and cities are different workers different women's rights are different because of transportation and yet we still have a very suboptimal transportation solution where we kill 1.2 or so million P every year in traffic it's like the leading cause of death for young people in many countries we have here extremely inefficient resource wise just go to your average neighborhood city and look at the number of parked cars that's a travesty in my opinion or where we spend endless hours in traffic jams and very very simple innovations like a self-driving car or what people call a flying car could completely change this and it's there I mean the technology is it's basically there yet close your eyes not to see it so lingering on autonomous vehicles fascinating space some incredible work you done throughout your career there so let's start we'll start with DARPA I think the DARPA challenge there's a desert and then urban to the streets I think that inspired an entire generation of roboticists and obviously sprung this whole excitement about this particular kind of four wheeled robots were called autonomous cars self-driving cars so you led the development of Stanley the autonomous car that one that erased the desert the DARPA challenge in 2005 and junior a car that I finished second in the DARPA Grand Challenge also did incredibly well in 2007 I think what are some painful inspiring or enlightening experiences from that time that stand out to you oh my god painful were all these incredibly complicated stupid bugs that had to be found we had a face where the stanley hour or carded i eventually won the DARPA Grand Challenge but every 30 miles just commit suicide and we didn't know why and it ended up to be that in the sinking of two computer clocks occasionally a clock went backwards and that negative time elapsed screwed up the entire internal logic but it took ages to find this they were like bugs like that I'd say enlightening is the Stanford team immediately focused on machine learning and on software where's everybody else seem to focus on building better hardware our knowledge had been you a human being with an existing rental car can we drive the course I have to might have to build a better rental car I just built it should replace the human being and the human being to me was a conjunction of three steps we had extensors eyes and ears mostly eyes we had brains in the middle and then we had actuators our hands in our feet now the extras I used to build the sensors like she also use it a bit what was missing was the brain so he had to build a human brain and nothing nothing clear them to me that that the human brain is a learning machine so why not just train our robot so it you would build a massive machine learning into our machine and with that were able to not just learn from human drivers we had the entire speed control of the vehicle was copied from human driving but also have the robot learn from experience where it made a mistake and go to recover from it and learn from it you mentioned the pain point of software and clocks synchronization seems to seems to be a problem that continues with robotics it's a tricky one with drones and so on Oh what what does it take to build a thing a system with so many constraints you have a deadline no time you're unsure about anything really it's the first time that people really do even explore yeah it's not even sure that anybody can finish when we were talking about the race of the desert the year before nobody finished what does it take to scramble and finish a product that actually a system that actually works we were very lucky we did a small team that core of the team of four people it was four because five couldn't comfortably sit inside carpet for food and I as a team leader my job was to get pizza for everybody and wash the car and stuff like this and repair the radiator and it broke and debug the system and we were a kind of open mind that we had like no egos involved in this you just wonder to see how far we can get or we did really really well was time management we were done with everything a month before the race and we froze the entire of a month before the race and it turned out looking at other teams every other team complained if they just one more week they would have won and we decided that's gonna fall into a mistake you're gonna be early and we had an entire month to shake that system and we actually found two or three minor bugs in the last month that we had to fix and we were completely prepared in the race occurred okay so first of all that's such an incredibly rare achievement in terms of being able to be done on time or ahead of time what do you how do you do that in your future work what advice do you have in general because it seems to be so rare especially in highly innovative projects like this people work till the last second but the nice thing about the topic one challenge is that the problem was incredibly well-defined we were able for a while to drive the old topic van challenge course which had been used the year before and then at some reason we were kicked out of the region so we had to go to different desert the Sonoran Desert and be able to drive desert trails just at the same time so there was never any debate about like what is actually the problem we didn't sit down and say hey should we build a car or a plane if we had to build a car that made it very very easy then I studied my own life and life of a dozen guys that the typical mistake that people make is that there's this kind of crazy bug left that they haven't found yet and and it's just there regretted and it back would have been trivial to fix it was haven't fixed it yet they didn't want to fall into that trap so I build a testing team we had a testing tena build a testing booklet of 160 pages of tests we had to go through just to make sure we shake all the system appropriately Wow and the testing team was with us all the time and dictated to us today we do railroad crossings tomorrow over do we practice the start of the event and in all of these we thought oh my god has long solved trivial and I mean tested it out oh my god it doesn't were a well for us and why not oh my god it mistakes the and the rails for metal barriers we have to fix this yes so it was easy a continuous focus on improving the weakest part of the system and as long as you you focus on improving the weakest part of the system you eventually build a really great system let me just pause Allah is to me as an engineer is super-exciting that you were thinking like that especially at that stage as brilliant that testing was such a core part of it it may be to linger on the point of leadership I think it's one of the first times you were really a leader and you've led many very successful teams since then what does it take to be a good leader I would say I'm most of all just take credit for the work of others right that's that's very convenient than that because I can't do all the things myself I'm an engineer at heart so I I care about engineering so so I I don't know what the chicken in the egg is but as a kid I love computers because you could tell them to do something and they actually did it it was very cool and you could like in the middle of a night wake up at 1:00 in the morning and switch on your computer and what you told you to yesterday I would still do that was really cool unfortunately that it didn't quite work with people so you go to people and tell them what to do and they don't do it mm-hm and they hate you for it or you do it today and then you go a day later and you stop doing it so you have to so then a question really became how can you put yourself in the brain of the of people as opposed to computers and it has the computers as super dumb then so dumb if if people were as dumb as computers i wouldnt want to walk with them mmm but people are smart and people are emotional and people have pride and people have a spur a shion's so how can i connect to that and that's the thing where most of leadership just fails because many many engineers turn manager believe they can treat their team just the same way I can treat your computer and it just doesn't work this way it's just really bad so how did how can i how are can i connect to people and in turns out as a college professor the wonderful thing you do all the time is to empower other people like your job is to make your students look great that's all you do you're the best coach and it turns out if you do a fantastic job is making a students look great they actually love you and their parents love you and they give you all the credit for stuff you don't deserve since that all my students who are smarter than me all the great stuff invented at Stanford versus their stuff not my stuff and they give me credit and say oh Sebastian but just making them feel good about themselves so the question really is can you take a team of people and what does it take to make them to connect to what they actually want in life and turn this into product affection it turns out every human being that I know has incredibly good intention I've really never really met a person with bad intentions I believe every person wants to contribute I think every person I've met wants to help others it's amazing how much of a urge we have not to just help ourselves but to help others so how can we empower people and give them the right framework that they can accomplish this if in moments when it works it's magical because you'd see the confluence of people being able to make the world a better place and driving enormous confidence and pride out of this and that's when when my environment works the best these are moments where I can disappear for a month and come back and things still work it's very hard to accomplish but in when it works is amazing so I agree very much it's not often heard that most people in the world have good intentions at the core their intentions are good and they're good people that's a beautiful message it's not often heard we make this mistake and this is a friend of mine eggs water token us that we we judge ourselves by our intentions in others by the actions and I think the the biggest skill I mean here in Silicon Valley were full of Engineers I have very little empathy and and I kind of befuddled why it doesn't work for them the biggest skill I think that that people should acquire is to put themselves into the position of the other and listen and listen to what the other has to say and they'd be shocked how similar they are to themselves and they might even be shocked how their own actions don't reflect their intentions I often have conversations with engineers yes they look hey I love you doing a great job and by the way what you just did has the following effect are you aware of that and then people would say oh my god not I wasn't because my intention was that they'd say yeah I trust your intention you're a good human being but just to help you in the future if you keep expressing it that way then people just hate you and I've had many instances we say oh my god thank you for telling me this because it wasn't my intention to look like an idiot wasn't my intention to help other people I just didn't know how to do it simply by the way there's a no-fail carnegie 1936 how to make friends and how to influence others has the entire pipe or just read it and you're done and usually apply it every day and I wish I could I was good enough to apply it every day but it says simple things right like be positive remember previous name smile and eventually have empathy like really think that the person that you hate and you think is an idiot is if you just like yourself it's a person who's struggling who means well and who might need help and guess what you need help I've recently spoken with Stephen Schwarzman I'm not sure if you know who that is but do so and he said I'm a list no but he he said sort of to expand on what you're saying that one of the biggest things you can do is hear people when they tell you what their problem is and then help them with that problem he says it's surprising how few people actually listen to what troubles others and because it's right there in front of you and you can benefit the world the most and in fact yourself and everybody around you by just hearing the problems and solving them I mean that's my my little history of engineering that is while I was engineering with computers I didn't care all what the computers problems for just I just volumize everyone to do it and it doesn't work with me you've become the mean say to do AI do the opposite but let's return to the comfortable world of engineering thinking you can you tell me in broad strokes in how you see it because you're the course starting at the core of driving it the technical evolution of autonomous vehicles from the first DARPA Grand Challenge to the incredible success we see or the program you started with Google self-driving car and way more in the entire industry that sprung up all the different kinds of approaches debates and so on well the idea of self-driving car goes back to the 80s there was a team in Germany on the team at Carnegie Mellon that it's very pioneering work but back in the day I'd say the computers were so efficient that even the best professors and engineers in the world basically stood no chance it then folded into a phase where the US government spent at least half a million dollars that I could count on research projects but the way the procurement works a successful stack of paper describing lots of stuff that no one's ever gonna read was a successful product of a research project so so we trained our researchers to produce lots of paper that all changed for the DARPA Grand Challenge and I really gotta credit the ingenious people at DARPA and the US government in Congress that took a complete new funding model where they said that's not fun effort let's fund outcomes and it sounds way trivial but it there was no tax code that allowed did the use of congressional tax money for a price it was all effort based so if you put in a hundred dollars in you could charge 100 hours you put in a thousand dollars and you could build a thousand hours by shading the focus in city making the price we don't pay you for development we pray for the accomplishment they drew in they automatically drew out all these contractors who are used to the drug of getting money power and they drew in a whole bunch of new people and these people are mostly crazy people there were people who had a car and a computer and they wanted to make a million bucks the million bucks was the official price money was then doubled and they felt if I put my computer in my car and program it I can be rich and it was so awesome like like half the team's there was a team that was surfer dudes and they had like two surfers on the vehicle and brought like these fashion girls super cute girls like twin sisters and and you could tell these guys were not your common I felt very offended who like gets all these big multi-million and billion other countries from the US government and and there was a great we set the universities moved in I was very fortunate at Stanford that I just received tenure so I couldn't be fired whenever I do otherwise I would have done it and I had enough money to finance this thing and I was able to attract a lot of money from from third parties and even car companies moved in they kind of moved in very quietly because they were super scared to be embarrassed that they a car would flip over but Ford was there and Volkswagen was there and a few others and GM was there so it kind of reset the entire landscape of people and if you look at who's a big name in suffering cars today these were mostly people who participated in those challenges ok that's incredible can you just comment quickly on your sense of lessons learned from that kind of funding model and the research that's going on academia in terms of producing papers is there something to be learned and and scaled up bigger these having these kinds of grand challenges that could improve outcomes so I'm a big believer in and focusing on kind of an end-to-end system I'm a really big believer in an insistence building I've always built systems in my academic career even though I love math and an abstract stuff but it's all derived from the idea of let's solve your problem and it's very hard for me to be an academic and say let me solve a component of a problem like if someone this feels like not monitoring logic or AI planning systems where people believe that a certain style of problem-solving is the ultimate end objective and and I would always turn it around and say hey what problem put my grandmother care about that doesn't understand computer technology and doesn't want to understand how could I make her love what I do because only then do I have an impact on the world I can easily impress my colleagues that's that's that that is much easier but impressing my grandmother is very very hard so I've always thought if I can build a self-driving car and and my grandmother can use it even after she loses her driving privileges or Sheldon can use it or we save maybe a million lives a year they would be very impressive and then there's so many problems like these like there's a problem of curing cancer or I'll if twice as long once the problem is defined of course I can solve it in society like it takes sometimes tens of thousands of people to to find a solution there's no way you can fund an army of ten thousand at Stanford so you're going to be the prototype it's bit of meaningful prototype and the DARPA Grand Challenge was beautiful because it told me what this prototype had to do I didn't need to think about what it had to do it is said to read the rules and it was really really beautiful and it's most beautiful you think what academia could aspire to is to build a prototype that's the system's level that solves it gives you an inkling that this problem could be solved with this project that's all I want to emphasize what academia really is and I think people misunderstand it first and foremost academia is a way to educate young people first and foremost the professor is an educator no matter away what a small suburban college or whether you are a Harvard or Stanford professor that's not the way most people think of themselves in academia because we have this kind of competition going on for citations and and publication that's a measurable thing but that is secondary to the primary purpose of educating people to think now in terms of research most of the great science the great research comes out of universities you can trace almost everything back including Google to universities so there's nothing we do fundamentally broken here it's a it's a good system and I think America has the finest University system on the planet we can talk about reach and how to reach people outside the system it's a different topic but the system would serve as a good system if I had one wish I would say it'd be really great if there was more debate about what the great big problems are on the side and focus on those and most of them are interdisciplinary unfortunately it's very easy to fall into a inner disciplinary viewpoint where your problem is dictators but what your closest colleagues believe the problem is it's very hard to break out and say why there's an entire new field of problems so give an example um prior to me working on self-driving cars I was a roboticist in a machine learning expert and I wrote books on robotics something called probabilistic robotics the survey methods driven kind of viewpoint of the world I build robots that acted in museums as tour guides that bug let children around it's something that it's time was moderately challenging when I started working on cars several colleagues told me Sebastian you're destroying your career because in our field of robotics cars are looked like as a gimmick and they're not expressive enough they can only push the throttle and and in the brakes there's no dexterity there's no complexity it's just too simple and no one came to me and said Wow if you solve that problem you can save a million lives right among all robotic problems that I've seen in my life I would say the self having car transportation Havana has the most hope for society so how come the robotics community was all over the place and of us become because we focused on methods and solutions and not on problems like if you go around today and ask your grandmother what bugs you what really makes you upset I challenge any academic and to do this and then realize how far your research is probably away from that today at the very least that's a good thing for academics they deliberate on the other thing that's really nice in Silicon Valley is Silicon Valley is full of smart people outside academia right so there's the Larry page's and magaz archive books in the world who are anywhere as smart or smarter than the best academics I met in my life and what they do is they they are at a different level they build the systems they build they build the customer-facing system they built things that people can use without technical education and they are inspired by research they're inspired by scientist they hire the best PhDs from the best universities for a reason so I think this kind of vertical integration that between the real product the real impact and the real thought the real ideas there's actually working surprisingly balanced Silicon Valley it did not work as well in other places in this nation so when I worked at Carnegie Mellon we had the world's finest computer science university but there wasn't those people in Pittsburgh that would be able to take these very fine computer science ideas and turn them into massive the impact for products that symbiosis seemed to exist pretty much only in Silicon Valley and maybe a bit in Boston in Austin yeah with Stanford that's it was it's really really interesting so if we look a little bit further on from the the DARPA Grand Challenge and the launch of the Google self-driving car what do you see is the state the challenges of autonomous vehicles as they are now is actually achieving that huge scale and having a huge impact on society I'm extremely proud of what what has been accomplished and again I'm taking a lot of credit for the work for us and I'm actually very optimistic and and people have been kind of worrying is it too fast as to slow I salute there yet and so on it is actually quite an interesting hard problem and in that a self-driving car to build one that manages 90% of the problems encountered in everyday driving is easy we can literally do this over a weekend to do 99% might take a month then there's 1% left so 1% would mean that you still have a fatal accident every week very unacceptable so now you work on this 1% and the 99% of there were any 1% is actually still a relatively easy but now you're down to like a hundredth of one percent and it's still completely unacceptable in terms of safety so the variety of things you encounter are just enormous and that gives me enormous respect for human being available to deal with the couch on the highway right or the DNI headlight or the blown tire that we'd never never been trained for and all of a sudden I have to handle in an emergency situation and often do very very successfully it's amazing from that perspective how safe driving actually is given how many millions of miles we drive every year in this country we are now at a point where I believed it in already is there and I've seen it I've seen it in way more I've seen it in activist engine crews and in a number of companies in unvoyage where vehicles not driving around and basically flawlessly I able to drive people around in limited scenarios in fact you can go to Vegas today and order a Seminole lift and if you got the right setting off your app you'll be picked up by a driverless car now there's still safety drivers in there but that's a fantastic way to kind of learn what the limits of Technology today and there's still some glitches but the gifts have become very very rare I think the next step is gonna be to down cost it to harden it did that entrapment it sends us are not quite an automatic weights than that yet and then you read about the business models to really kind of go somewhere and make the business case and the business case is hard work it's not just oh my god we have this capability people that's gonna buy it you have to make it affordable you have to give people that find the social acceptance of people none of the teams yet has been able to or gutsy enough to drive around without a person inside the car and that's that the next magical hurdle will be able to send these vehicles around completely empty in traffic and I think I'm gonna wait everyday wait for the news that vamo has just done this so you know the interesting you mentioned gutsy I mean let me ask some maybe unanswerable question may be edgy questions but in terms of how much risk is required some guts in terms of leadership style it would be good to contrast approaches and I don't think anyone knows what's right but if we compare Tesla and way mo for example Elon Musk and the way mo team the there's slight differences in approach so on the Elon side there's more I don't know what the right word to use but aggression in terms of innovation and I'm way mo side there's more sort of cautious safety focused approach to the problem what do you think it takes what leadership at which moment is right which approach is right look I'm I don't sit in either of those teams so I'm unable to even verify like somebody says correct right in the end of the day every innovator in in that space will face a fundamental dilemma and I would say you could put aerospace Titans into the same bucket yes which is you have to balance public safety with your drive to innovate and this country in particular in states has a plus your history of doing this very successfully yet travel is what a hundred times are safe per mile than ground travel and then cars and there's a reason for it because people have found ways to be very methodological about ensuring public safety while still being able to make progress on important aspects for example like yell and noise and fuel consumption so I think that those practices are pruned and they actually work we live in a world safer than ever before and yes they will always be the provision that something was wrong there's always the possibility that someone makes a mistake or there's an unexpected failure we can't never guarantee to 100 percent absolute safety other than just not doing it but I think I'm very proud of the history of of United States I mean we've we've dealt with much more dangerous technology like nuclear energy and kept that safe too we have nuclear weapons and we keep those safe so so we have methods and procedures that really balance these two things very very successfully you've mentioned a lot of great autonomous vehicle companies that are taking sort of the level 4 level file they jump in full autonomy or the safety driver and take that kind of approach and also through simulation and so on there's also the approach that Tesla autopilot is doing which is kind of incrementally taking a level 2 vehicle and using machine learning and learning from the driving of human beings and trying to creep up trying to incremental improve the system until it's able to achieve level 4 autonomy so perfect autonomy in certain kind of geographical regions what are your thoughts on these contrasting approaches when suppose of all I I'm a very proud Tesla and I literally used the autopilot every day and it literally has kept me safe is a beautiful technology specifically for highway driving when I'm slightly tired because then it turns me into a much safer driver and that I'm a hundred percent confident it's the case and tells us the right approach I think that the biggest change I've seen since I went away one team is is this thing called deep learning deep learning was was not a hot topic when I when I started way more or Google suffering cars it was there in fact we saw the Google brain at the same time in Google X so I invested in deep learning but people didn't talk about it wasn't a hot topic and nowadays there's a shift of emphasis from a more geometric perspective where you use geometric sensors they give you a full 3d view when you do a geometric reasoning about all of this box over here might be a car towards a more human like oh let's just learn about it this looks like the thing I've seen 10,000 times before so maybe it's the same thing machine learning perspective and that has really put I think all these approaches on steroids at Udacity we teach a course in self-driving cars we can in fact I think we'd be if credit is over 20,000 or so people on self-driving car skills so every every self-driving car team in the world now uses our engineers and in this course the very first homework assignment is to do Lane finding on images and lane finding images for layman what this means is you you put a camera into your car or you open your eyes and even know where the lane is right so so you can stay inside the lane with your car humans can do this super easily you just look and you know where the line is just intuitively for machines for long term of a super heart because people would write these kind of crazy rules if there's like vineland marcus and he's for fight really means this is not quite wide enough so let's all it's not right or maybe the Sun is trying so when the Sun shines and this is right and this is a straight line I missed quite a straight line because the ball is curved and and do we know that there's really six feet between lane markings or not or 12 feet whatever it is and now the very students are doing they would take machine learning so instead of like writing these crazy rules for the lane marker is they say let's take an hour driving and label it and tell the vehicle this is actually the lane by hand and then these are examples and have the Machine find its own rules but for lane markings are and within 24 hours now every student there's never done any programming for in this space can write a perfect Lane finder as good as the best commercial line and that's completely amazing to me we've seen progress using machine learning that completely Dwarfs anything that I saw ten years ago yeah and just as a side note the self-driving car nanodegree the fact that you launch that many years ago now maybe four years ago three years ago three years ago is incredible that it that's a great example of system level thinking sort of just taking an entire course I teach each other solve entire problem I definitely recommend people it's been super popular and it's become actually incredibly high quality we build it with Mercedes and and and various other companies in that space and we find that engineers from Tesla and vamo are taking it today the insight was that two things one is existing universities will be very slow to move because the departmental ice and there's no department for self-driving cars so between Mickey and EE and computer science getting these folks together into one room is really really hard and every professor listening he ever know that probably agree to that and secondly even if if all the great universities just did this which none so far has develop a curriculum in this field it is just a few thousand students they can partake because all the great universities are super selective so how about people in India how about people in China or in the Middle East or Indonesia or Africa right should those be excluded from the skill of building self-driving cars are there any dumber than we are any less privileged and the answer is we should just give everybody the skill to build a self-driving car because if we do this then we have like a thousand self-driving car startups and if 10 percent succeed that's like a hundred that means hundred countries now we have self-driving cars and be safer it's kind of interesting to imagine impossible to qualify but the number the you know over a period of several decades the impact that has like a single course like a ripple effect of society if you just recently thought the Android and who was creator of cosmos show it's interesting to think about how many scientists that show launched yes and so it's really in terms of impact I can't imagine a better course than the self-driving car course that's you know the there's other more specific disciplines like deep learning and so on that Udacity is also teaching but self-driving cars it's really really interesting course yeah and it came at the right moment it came at a time when there were a bunch of aqua huggers aqua hire as a acquisition of a company not for its technology or its products or business but for its people so aqua hire means maybe the company of 70 people they have no product yet but they're super smart people and he pays certain amount of money so I took back the highest like GM Cruise and uber and and others and did the math and said hey how many people are there and how much money was paid and as a lower bound is tomato value of an self-driving car engineer in these acquisitions to be at least 10 million dollars right so think about this you you get just have a skill and you team up and build a company and you're worth now is 10 million dollars I mean it's kind of cool I mean but what other thing could you do in life to be worth 10 million dollars within a year yeah amazing but to come back for a moment on to deep learning and its application in autonomous vehicles you know what are your thoughts on Elon Musk's statement provocative statement perhaps that lighter is a crutch so this geometric way of thinking about the world maybe holding us back if what we should instead be doing in this robotics but in this particular space of autonomous vehicles is using camera as a primary sensor and using computer vision or machine learning is the primary way to look up to Commons I think first of all we all know that people can drive cars without light us in their hands because we only have eyes and we most you just use eyes for driving maybe we use some other perception about our bodies accelerations occasionally our years certainly not our noses so that the existence proof is there that eyes must be sufficient in fact we could even drive a car someone put a camera out and then give us the camera image with known agency you would be able to drive a car and that way it the same way so cameras sufficient secondly I really love the idea that in in the Western world we have many many different people trying different hypotheses it's almost like an anthill like if another Idol tries to forage for food but you can sit there as two ands and agree what the perfect path is and then every single ant marches for the most like the location of food is or you can even just spread out and I promise you the spread out solution will be better because if the discussing philosophical intellectual ends get it wrong and they're all moving the wrong direction they're gonna waste a day and then you're gonna discuss again for another week whereas if all these ants go in a random direction someone's gonna succeed and you're gonna come back and claim victory and get the Nobel Prize about everything antipholus and then they'll march in the same direction and that's great about society that's great about the Western society if you're not plant-based you're not central base we don't have a Soviet Union style central government that tells us where to forge we just Forge we start and seek or you get investor money and go out and try it out and who knows is gonna win I like it in your when you look at the long term vision of autonomous vehicles do you see machine learning as fundamentally being able to solve most of the problems so learning from experience I'd say we should be very clear about what machine learning is and is not and I think there's a lot of confusion for this today is a technology that can go through large databases of repetitive patterns and find those patterns so in example we did a study at stand for two years ago where we applied machine learning to detecting skin cancer and images and we harvested or built a data set of 129,000 skin photo shots that were all had been biopsied for what the actual situation was and those included melanomas and carcinomas also included rashes and other skin conditions lesions and then we had a network find those patterns and it was by and large able to then detect skin cancer with an iPhone as accurately as the best board-certified Stanford level dermatologist we proved that now not this thing was great in this one thing I'm finding skin cancer but it couldn't drive a car so so the difference to human intelligence as we do all these many many things and we can often learn from a very small data set of experiences but as machines still need very large data sets and things should be very repetitive no that's still super impactful because almost everything we do is repetitive so that's gonna we transform human labor but it's not this almighty general intelligence we're really far away from a system that will exhibit general intelligence to that end I actually commiserate the naming a little bit because artificial intelligence if you believe Hollywood is immediately mixed into the idea of human suppression and and machine superiority I don't think that we don't see this in my lifetime I don't think human suppression is a good idea I don't see it coming I don't see the technology being there what I see instead is a very pointed focused pattern recognition technology that's able to extract patterns relation large data sets and in doing so it can be super impactful and super impactful let's take the impact of artificial terrorism on human work we all know that it takes something like 10,000 hours to become an expert if you're gonna be a doctor or lawyer or even a really good driver it takes a certain amount of time to become experts machines now are able and have been shown to observe people become experts in observe experts and then extract those rules from experts in some interesting way they could go from law to sales to driving cars to diagnosing cancer and then giving that capability to people who are completely new in their job we now can and that's that's been done has been done commercially in many many instances that means we can use machine learning to make people an expert on the very first day of their work like think about the impact if if your doctor is still in the first 10,000 hours you have a doctor who's not quite an expert yet who would not want the doctor who is the world's best expert and now we can leverage machines to really eradicate the error and decision making error and lack of expertise for human doctors they could save your life if we can link on that for a little bit in which way do you hope machines in the medical in the medical field could help assist doctors you mentioned this sort of accelerating the learning curve or people if they start a job or in the first 10,000 hours can be assisted by a machine how do you how do you envision that assistance looking so we built this this app for an iPhone that can detect and classify and diagnose skin cancer and we proved two years ago there is as pretty much as good or better than the best human doctor so let me give his story so there's a friend of mine is calling Ben Ben is a very famous venture capitalist he goes to his doctor and the doctor looks at a mall and and says hey that mole is probably harmless and for some very funny reason he pulls out that phone with our app he's a collaborator in our study and the app says no no no this is a melanoma and and for background melanomas are skin cancers the most common cancer in this country melanomas can go from from stage zero to Stage four within less than a year stage zero means you can basically cut it all yourself with better kitchen knife and be safe and Stage four means your chances of leading from five more years in less than 20% so it's a very serious serious serious condition so this doctor who took out the iPhone looked at the iPhone was a little bit puzzled Samina but just to be safe let's cut it out and biopsy it that's that the technical term for let's get an in-depth diagnostics that is more than just looking at it and it came back as cancerous as a melanoma and it was then removed and my friend Ben I was hiking with him and we are talking about a I in and said I turn into this vote on skin cancer he's so funny my doctor just had an iPhone that found my cancer so I was a completely in tree didn't even know about so here's a person I mean this is a real human life right now who doesn't know somebody who's been affected by cancer cancer is cause of death number two cancer is this kind of disease that that is mean in in the following way most cancers can actually be cured relatively easily if we catch them early and and the reason why we don't tend to catch them early is because they have no symptoms like your very first symptom of a gallbladder cancer or a pancreatic cancer might be a headache and when you finally go to your doctor because of these headaches or your back pain and you're being imaged it's usually stage four plus and that's the time when the your curing chances might be dropped to a single-digit percentage so if we could leverage the eye to inspect your body on a regular basis without even a doctor in the room maybe when you take a shower over have you I know this sounds creepy but then we might be able to save millions and millions of lives you've mentioned there's a concern that people have about near-term impacts of AI in terms of job loss so you've mentioned being able to assist doctors being able to assist people in their jobs do you have a worry of people losing their jobs or the economy being affected by the improvements in AI anybody concern about job losses please come to get a sitcom we teach contemporary tech skills and we have a kind of implicit job promise we often when when we measure we spend way over 50% of our graders in new jobs they're very satisfied about it and it costs almost nothing cost like a thousand five hundred max or something like that and so there's a cool new program they agree with the US government guaranteeing that you will help us give scholarships that educate people and in this kind of situation you're working with the US government on the idea of basically building the American dream so Udacity has just dedicated one hundred thousand scholarships for citizens of America for various levels of courses that eventually will get you a job and those courses all somewhat relate with the tech sector because the tech sector is kind of the hottest sector right now and they range from in two level digital marketing to very advanced self driving car engineering and we're doing this with the white house because II think is bipartisan it's an issue that is that if you want to really make America great being able to be a part of the solution and live the American dream requires us to be proactive about our education and our skill set it's just the way it is today and it's always been this way I've always had this American dream to send our kids to college and now the American dream has to be to send ourselves to college into this very vey vey efficiently and very way we can squeeze in and evenings and things to online or at all ages all ages so our our learners go from age 11 to age 80 I just travel Germany and and the guy in train compartment next to me was my students wow that's amazing I don't think about impact we've become the educator of choice for now I believe officially six countries or five countries is most in the Middle East like Saudi Arabia and in Egypt in Egypt we just had a cohort graduate um where we had 1100 high school students that went through programming skills proficient at the level of computer science undergrad and we had a 95% graduation rate even though everything's online it's kind of tough but we kind of trying to figure out how to make this effective the vision is the vision is very very simple the vision is education ought to be a basic human right it cannot be locked up behind ivory tower walls only for the rich people for the parents who might be bright themself into the system and only for young people and only for people from the right demographics literate geography and possibly even the right race it has to be opened up to everybody if we if we are truthful to the human mission via truthful to our values we gonna open up education to everybody in the world so Udacity is pledge of a hundred thousand scholarships I think it's the biggest pleasure of scholarships ever in terms of the numbers and we've working as I said for the White House and with very accomplished CEOs like Tim Cook from Apple and others to really bring education to everywhere in the world not to ask if you pick the favorite of your children but at this podium Jasper no okay good in this particular moment what nanodegree what said of course is are you most excited about Udacity or is that too impossible to pick I've been super excited about something we haven't launched yet in the building which is when we talk to our partner companies we have known a very strong footing in the enterprise world and also to our students we've kind of always focused on these hard skills like the programming skills or math skills or building skills or design skills and a very common task is soft skills like how do you behave in your work how you develop empathy how do you work in a team what are the very basics of management how do you do time management how do you advance your career in the context of a broader community and that's something that we haven't done very valid audacity and I would say most universities doing very poorly as well because we're so obsessed with individual test scores and and so little pace a little attention to teamwork in education so that's something I see us moving into as a company because I'm excited about this and I think look we can teach people tech skills and they're going to be great but if you teach people empathy that's gonna have the same impact may be harder than self-driving cars but I don't think so I think the rules are really simple you just have to you have to you have to want to engage it's it's via we literally went in in school and in k-12 we teach kids like get the highest math score and if you are a rational human being you might evolved from this education say having the best math score and the best English scores make me the best leader and it turns out not to be the case it's actually really wrong because making first of all in terms of math scores I think is perfectly fine to hire somebody with great math skills you'd have to do yourself you can't hire some of the good empathy for you that's much harder but it can always hire some with great math skills but we live in in affluent world where we constantly deal with other people and it's a beauty it's not a nuisance it's a beauty so if we somehow develop that muscle that we can do that well and empower others in the workplace I think you're gonna be super successful and I know many fellow roboticists and computer scientists that I will assist take this course not to be named many many years ago 1903 the Wright brothers flew in Kitty Hawk for the first time and you've watched a company of the same name Kitty Hawk with the dream of building flying cars evey tall's so at the big picture what are the big challenges of making this thing that actually inspired generations of people about what the future looks like what does it take one of the biggest challenges so so flying cars has always been a dream of boy every girl wants to fly let's be honest yes and let's go back in on history of you're dreaming of flying I think my answer my single most remembered childhood dream has been a dream where I was sitting on a pillow and I could fly I was like five years old I remember like maybe three dreams are much higher but that's the one that we remember most vividly and then Peter Thiel famously said they promise us flying cars and they give us 140 characters pointing as Twitter at the time limiting message size 240 characters so if you're coming back now to really go for this super impactful stuff like flying cars and to be precise they're not really cars they don't have wheels they actually much closer to a helicopter than anything else they take off vertically in the fly horizontally but they have important differences one difference is that they are much quieter if you just released a vehicle called project heavy side they can fly over you as low as a helicopter and you basically can't hear it's like 38 decibels it's like like that if you were inside a library you might be able to hear it but anywhere outdoors your ambient noise is higher secondly they're they're much more affordable they're much more affordable than helicopters and the reason is helicopters are expensive for many reasons there's lots of single point of figures in a helicopter there's a bolt between the blades that's cause Jesus fault and the reason why it's called Jesus board is it that if this boat breaks you will die there is no second solution in helicopter flight whereas we have these distributed mechanism when you go from gasoline to electric you can now have many many many small motors as opposed to one big motor and that means if you lose one of those motors not a big deal heavy side if it loses a motor has eight of those you lose one of those eight motors so it's seven left you can take off just like before and land just like before we are now also moving into a technology it doesn't require a commercial pilot because in some level flight is actually easier than than ground transportation like in self-driving cars oh the world is full of like children and bicycles and other cars and mailboxes and curbs and shrubs and what-have-you all these things you have to avoid when you go above buildings and tree lines there's nothing there I mean you can do the test right now look outside and count the number of things you see flying I'd be shocked if you could see more than two things it's probably just zero in the Bay Area the most I've ever seen was six and maybe it's 15 or 20 but not ten thousand so the sky is very ample and very empty and very free so the vision is can be built a socially acceptable mass transit transit solution for daily transportation that is affordable and we have an existence proof Heaviside can fly a hundred miles in range with still 30% electric reserves it can fly up to like a hundred and eighty miles an hour we know that that solution that scale would make your ground transportation 10 times as fast as a car based on use census data which means we would take your 300 hours of day of yearly commute down to 30 hours and giving 270 hours back who wouldn't want I mean who doesn't hate traffic like I hate give me the person that doesn't hate traffic I hate traffic every day every time I want traffic I hate it and and if we could free the world from traffic we have technology we can free the world from traffic yeah we have the technology it's there we have an existence proof test it's not a technological problem anymore do you think there is a future where tens of thousands maybe hundreds of thousands of both delivery drones and flying cars of this kind a VTOL fill the sky i absolutely believe this and there's obviously the societal acceptance is a major question and of course safety as I believe in and safety of you exceed ground transportation safety as has happened for aviation already commercial aviation and in terms of acceptance I think one of the key things is noise that's why we are focusing relentlessly on noise and we bid perhaps the crisis electric VTOL vehicle ever built the nice thing about the sky is three-dimensional so so any mathematician will immediately recognize the difference between 1d of a lack of regular highway to three of a sky but to make it clear for the layman say you want to make a hundred vertical lanes of highway 101 in San Francisco because you believe building a health and vertical lanes is the right solution imagine how much it would cost to stack a hundred vertical lanes physically onto 101 there would be prohibitive that would be consuming the world's GDP for an entire year just for one highway it's amazing expensive again in the sky it would just be a recompilation of a piece of software because all these lanes are virtual that means any vehicle that is in conflict with another vehicle would just go to different altitudes and then the conflict is gone and if you don't believe this that's exactly how how commercial aviation works when you fly from New York to San Francisco another plane flies from Sanford to New York there are different altitudes so they don't hit each other it's a soft problem for the jet space and it will be a soft problem for the urban space there's companies like Google Bing and Amazon working on very innovative solutions how do a space management use exactly the same principles as we use today throughout today's dance there's nothing hard about this do you envision autonomy being a key part of it so that that the flying vehicles are either semi autonomous or fully autonomous a hundred percent autonomous you don't want idiots like me flying in the sky I promise you and if you have ten thousand what's the movie The Fifth Element to get a thief over to happen if it's not autonomous in a centralized that's a really interesting idea of a centralized sort of management system for lanes and so on so actually just being able to have similar as we have in the current commercial aviation but scale it up to which much more vehicles a really interesting optimization problem it is vey mathematically very very straightforward like the gap we leave between jets is Gargantuas and part of the reason is there isn't that many gents so this feels like a good solution today when you get vectored by a traffic control someone talks to you right so any ATC controller might have up to maybe 20 planes on the same frequency and then talk to you have to talk back and it feels right because there isn't more than 20 pins around any hours so you can talk to everybody but if there's 20,000 things around he can't talk to everybody anymore so we have to do something that's called digital like text messaging like we do have solutions like we have about four or five billion smartphones in the world now all right and they all connected and some of you solved the scale problem for smart phones we know where they all are they can talk to somebody and they're very reliable they amazingly reliable we could use the same system the same scale for air traffic control so instead of me as a pilot talking to a human being and in the middle of the conversation receiving a new frequency like how ancient is that we could digitize the stuff and and digitally transmitted the right flight coordinates and that solution will automatic a laugh to 10,000 vehicles we talked about empathy a little bit do you think we'll one day build an air a eye system that a human being can love and that loves that human back like in the movie her look I'm I'm a pragmatist for me a is a is a tool it's like a shovel and the ethics of using the shovel I always with us the people and and there has to be this way in terms of emotions I would hate to come into my kitchen and see that my refrigerator spoiled all my food then have it explained to me that it fell in love with a dishwasher and I wasn't as nice the dishwasher so as a result it neglected me there would just be a bad experience and it would be a bad product I would probably not recommend this for frigerator to my friends and that's where I draw the line I think to me technology has to be reliable it has to be predictable I want my car to work I don't want to fall in love with my car I just wanted to work I wanted to compliment me not to replace me I have very unique human properties and I want the machines to make me turn me into a superhuman like I'm already a superhuman today thanks to the machines that surround me and give you examples I can run across the Atlantic at near the speed of sound at 36,000 feet today that's kind of amazing I can my voice now carries me all the way to Australia using a smartphone today and it's not not the speed of sound which would take hours it's the speed of light my voice travels at the speed of light how cool is that that makes me superhuman I would even argue my my flushing toilet makes me superhuman just think of the time before flushing toilets and and maybe you have a veiled person in your family that you can ask about this or take a trip to rural India until experience it it's it's it makes me superhuman so to me what technology does it complements me it makes me stronger therefore words like love and compassion have very little a very little interest in this for machines I have interested men people you don't think first of all beautifully put beautifully argued but do you think love has use in our tools compassion I think laughs is a beautiful human concept and if you think what love really is love is a means to convey safety to convey trust I think Trust has a huge need in technology as well much as people we want to trust our technology the same way we - or in similar way we trust people in in human interaction standards have emerged and and feelings emotions have emerged may be genetically may be very largely that I able to convey sense of trust sense of safety sense of passion of love of dedication that that makes the human fabric and I'm a big slacker for love I want to be laughter I want to be trusted ever me admired all these wonderful things and because all of us who we have this beautiful system I wouldn't just blindly copy this to the machines here's why when you look at say transportation you could have observed that up to the end of the 19th century so transportation used any number of legs from one leg to two legs to a thousand legs and you could have concluded that is the right way to move about the environment we've been made exceptional birds who is flapping wings in fact there are many people in aviation that flap wings to the arms and jump from Cliffs most of them didn't survive then then the interesting thing is that the technology solutions are very different like in technologies really easily by the wheel in biology is super hard ability there's very few perpetually rotating things in in in biology and everyone sells things in in engineering we can build wheels and those wheels gave rise to cars similar wheels gave rides to to aviation like there's no thing there flies there wouldn't have something rotates like a jet engine or helicopter blades so the solutions have used very different physical laws in nature and that's great so for me to be too much focused on oh this is how nature does it this is replicated if we really believed that the solution to the irish revolution was a humanoid robot it would still be waiting today again beautifully put you said that you don't take yourself too seriously you just say that i mean you want you to say that maybe you don't take me seriously I'm not yeah you're right I don't wanna I just made that up but you know you have a humor and a lightness about life that I think is it is beautiful and inspiring to a lot of people where does that come from the smile the humor the lightness amidst all the chaos of the hard work that you and where does that come from I just love my life I love I love the people around me I love I'm just so glad to be alive like I'm about 52 how to believe people say 5251 so now feel better but in in in in in looking around the world looking just go back 200 300 years like Humanity is what 300 thousand years old but for the first 300,000 years - the last 100 our life expectancy would have been plus or minus 30 years roughly give or take so I would be long dead now like that makes me just enjoy every single day of my life because I don't deserve this like why am i porn today when so many of my interest has died of horrible deaths like famines massive wars that ravaged Europe for the last 1000 years mostly disappeared after World War 2 when the Americans and the Allies did something amazing to my country that didn't deserve it my country of Germany it was so amazing and then when you when you're live and feel this every day then it is so amazing what what we can accomplish what we can do we live in the world that is so incredibly vastly changing every day almost everything that we cherish from your smartphone to your flushing toilet to all these basic inventions your new clothes you're wearing your watch your plain penicillin and no anesthesia for surgery penicillin have been invented in the last 150 years so in the last 150 years something magical happened and I would trace it back to Gutenberg and the printing press that has been able to disseminate information more efficiently than before that all of a sudden they're able to invent agriculture and nitrogen fertilization that made agriculture so much more potent that we didn't if you focus of hams anymore and you could start reading and writing and we could become all these wonderful things we are today for me LM pilot - massage therapist - software engineer this is amazing like living in that time is such a blessing we should sometimes really think about this Steven Pinker who as a very famous author and philosopher whom I really adore wrote a great book called enlightenment now and that's maybe the one book I would recommend and he asked the question if there was only a single article written in the 20th century don't leave an article but would it be what's the most important innovation the most important thing that and he would say this article would credit a guy named Carl Bosch and I challenge anybody have you ever heard of the name Carl Bosch I hadn't okay there's a there's a Bosch corporation in Germany but it's not associated with Carl Bosch so I looked it up kibosh invented nitrogen fertilization and in doing so together with an older invention of irrigation was able to increase the yield Ferrari cultural land by a factor of twenty six so a two thousand five hundred percent increase in infertility of land and that so Steve Pinker argues saved over two billion lives today two billion people who would be dead if this man hadn't done what he had done okay think about that impact and what that means to society that's that's the way I look at the world I mean it's so amazing to be a life and be part of this and I'm so glad I lived after Cobb abortion not before I don't think there's a better way to end it Sebastian it's an honor to talk to you to have had the chance to learn from you thank you so much for talking so commingling so your pleasure thank you for listening to this conversation with Sebastian Thrun and thank you to our presenting sponsor cash app download it use coal xpod cast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on YouTube get five stars in a podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from Sebastian Thrun it's important to celebrate your failures as much as your successes if you celebrate your failures really well if you say wow I failed I tried I was wrong but I learned something then you realize you have no fear when your fear goes away you can move the world thank you for listening and hope to see you next time you |
Michael Stevens: Vsauce | Lex Fridman Podcast #58 | the following is a conversation with Michael Stevens the creator of Vsauce one of the most popular educational YouTube channels in the world with over 15 million subscribers and over 1.7 billion views his videos often ask and answer questions that are both profound and entertaining spanning topics from physics to psychology popular questions include what if everyone jumped at once or what if the Sun disappeared or why are things creepy or what if the earth stopped spinning as part of his channel he created three seasons of minefield a series that explored human behavior his curiosity and passion are contagious and inspiring to millions of people and so as an educator has impacted contribution to the world is truly immeasurable this is the artificial intelligence podcast if you enjoy it subscribe I need to give five stars on a podcast support on patreon or simply connect with me on Twitter at lex Friedman's both fri DM aen i recently started doing ads at the end of the introduction i'll do one or two minutes after introducing the episode and never any ads in the middle that break the flow of the conversation I hope that works for you and doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash up investing a subsidiary of square and member CIBC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and Charity Navigator which means the donated monies used in maximum effectiveness when you get cash app from the App Store Google Play and use code and Lex podcast you'll get $10 and cash app will also donate $10 to the first which again is an organization that I've personally seen inspired girls and boys to dream of engineering a better world and now here's my conversation with Michael Stevens one of your deeper interests is psychology understanding human behavior you've pointed out how messy studying human behavior is and it's far from the scientific rigor of something like physics for example how do you think who can take psychology from where it's been in the 20th century to something more like what the physicists theoretical physicists are doing something precise something rigorous well we we could do it by finding the physical foundations of psychology right if if all of our emotions and moods and feelings and behaviors are the result of mechanical behaviors of atoms and molecules in our brains then can we find correlations perhaps like chaos makes that really difficult and the uncertainty principle and all these things like we can't know the position and velocity of every single you know quantum state in a brain probably but I think that if we you know can get to that point with psychology then we can start to think about consciousness in a physical and and mathematical way when we ask questions like well what is self reference how can you think about yourself thinking what are some mathematical structures that could bring that about there's ideas of in terms of consciousness and breaking it down into a physics there's ideas of pants like ism where people believe that whatever consciousness is is a fundamental part of reality it's almost like a physics law do you think what's your views on consciousness do you think it has this this deep part of reality or is it something that's deeply human and constructed by us humans start nice and light yeah an easy easy I think I asked you today has actually proven answer so yeah hypothesis so yeah I mean I should clarify this is all speculation yeah and I'm not an expert in any of these talk to topics and I'm not God but I think that consciousness is probably um something that can be fully explained within the laws of physics I think that our you know bodies and brains and and the universe and and at the quantum level is so rich and complex I'd be surprised if we couldn't find a room for consciousness there and why should we be conscious why are we aware of ourselves that is a very strange and interesting and important question and I think for the next few thousand years we're going to have to believe in answers purely on faith but my guess is that we will find that you know within the configuration space of possible arrangements of the universe there are some that contain memories of others literally uh Julian Barbour calls them time capsule states where you're like yeah not only do I have a scratch on my arm but also this state of the universe also contains a memory in my head of being scratched by my cat three days ago and for some reason those kinds of states of the universe are more plentiful or more likely when you say those states the ones would that contain memories of its past or ones that contain memories of its past and have degrees of consciousness just the first part because the I think the consciousness then emerges from the fact that a state of the universe that contains fragments or memories of other states is one where you're going to feel like there's time you're going to feel like yeah things in the happened in the past and I don't know what'll happen in the future because these states don't contain information about the future for some reason those kind of states are either more common more plentiful or you could use the anthropic principle just say well they're extremely rare but until you are in one or if you are in one then you can ask questions like you you're asking me on this podcast slide questions but yeah it's like what why are we conscious well because if we weren't we wouldn't be asking why we were you've kind of implied that you have a sense again hypothesis theorizing that the universe is deterministic what's your thoughts about freewill do you think of the universe is deterministic in a sense that it's unrolling in particular like there's a it's operating under a specific set of physical laws and when you have to set the initial conditions it will unroll in the exact same way in our particular line of the universe every time that is a very useful way to think about the universe it's done as well it's brought us to the moon it's brought us to where we are today right I would not say that I believe in determinism in that kind of an absolute form or actually I just don't care maybe it's true but I'm not gonna live my life like it is what in your son's because you've studied kind of how we humans think of the world what's in your view is the difference between our perception like how we think the world is in reality do you think there's a huge gap there like we delude ourselves as the whole thing is an illusion just everything about human psychology the way we see things and how things actually are all the things you've studied what's your sense how big is the gap between reality well sin purely speculative I think that we will never know the answer we cannot know the answer there is no experiment to find an answer to that question everything we experience is an event in our brain when I look at a cat I'm not even I can't prove that there's a cat there all I am experiencing is the perception of a cat inside my own brain I am only a witness to the events of my mind I think it is very useful to infer that if I witness the event of cat in my head it's because I'm looking at a cat that is literally there and has its own feelings and motivations and should be pet and given food and water and love I think that's the way you should live your life but whether or not we live in a simulation I'm a brain-in-a-vat I don't know and do care mmm I don't really well I care because it's a fascinating question and it's a fantastic way to get people excited about all kinds of topics physics psychology consciousness philosophy but at the end of the day what would the difference be if you the cat needs to be fed at the end of the day otherwise it'll be a dead cat right but if it's not even a real cat then it's just like a video game cat and right so what's the difference between killing a a digital cat in a video game because of neglect versus a real cat it seems very different to us psychologically like I don't really feel bad about oh my gosh I forgot to feed my Tamagotchi right but I would feel terrible if I forgot to feed my actual cats so can you just touch on the topic of simulation do you find this thought experiment that we're living in a simulation useful inspiring a constructive in any kind of way do you think it's ridiculous do you think it could be true or is it just a useful thought experiment I think it is extremely useful as a thought experiment because it makes sense to everyone especially as we see virtual reality and computer games getting more and more complex you're not talking to an audience in like Newton's time where you're like imagine a clock that it has mechanics in it that are so complex that it can create love and everyone's like no but today you really start to feel you know man at what point is this little robot friend of mine gonna be like someone I don't want to cancel plans with yeah you know and so it's a great the thought experiment of do we live in a simulation am i a brain and a bat that has just been given electrical impulses from some nefarious other beans so that I believe that I live on earth and that I have a body and all of this and the fact that you can't prove it either way is a fantastic way to introduce people to some of the deepest questions so you mentioned a little buddy that you would want to cancel an appointment with so that's a lot of our conversations that's where my research is artificial intelligence and I apologize but you're such a fun person to ask these big questions with well I hope I could give some answers that are interesting well because because of you've sharpened your brain's ability to explore some of the most some of the questions then many signs is actually afraid of even touching which is fascinating and I think you're in that sense ultimately a great scientist through this process of sharpening your brain well I don't know if I am a scientist I think you know science is a way of knowing and there are a lot of questions I investigate that are not scientific questions on like minefield we have definitely done scientific experiments and studies that had hypotheses and all that but you know not to be too like Precious about what does the word science mean but I think I would just describe myself as curious and I hope that that curiosity is contagious so to you the scientific method is deeply connected to science because your curiosity took you to asking questions to me asking a good question even if you feel society feels that it's not a question within the reach of science currently to me that asking the question is the biggest step of the scientific process the scientific method is the second part and that may be what traditionally is called science but to me asking the questions being brave enough to ask the questions being curious and not constrained by what you're supposed to think is is just true or what it means to be a scientist to me it's certainly a huge part of what it means to be a human if I were to say you know what I don't believe in forces I think that when I push on a massive object a ghost leaves my body and enters the object I'm pushing and these ghosts happen to just get really lazy when they're around massive things and that's why F equals MA oh and by the way the laziness of the ghost is in proportion to the mass of the object so boom prove me wrong every experiment well you can never find the ghost and so none of that theory is scientific but once I start saying can I see the ghost Why should there be a ghost and if there aren't ghosts what might I expect and I start to do different tests to see is this falsifiable are there things that should happen if there are ghosts or things that shouldn't happen and do they you know what do I observe now I'm thinking scientifically I don't think of science as wow a picture of a black hole that's just a photograph that's an image that's data that's a sensory and reception experience science is how we got that and how we understand it and how we believe in it and how we reduce our uncertainty around what it means but I would say I'm deeply within the scientific community and and sometimes disheartened by the elitism of the thinking sort of not allowing yourself to think outside the box so allowing the possibility of going against the conventions asides I think is is a beautiful part some of the greatest scientists in history I don't know I I'm impressed by scientists every day and revolutions in our knowledge of the world occur only under very special circumstances it is very scary to challenge conventional thinking and and and risky because let's go back to elitism and ego right if you just say you know what I believe in the spirits of my body and all forces are actually created by invisible creatures that that that transfer themselves between objects if you ridicule every other theory and say that you're what you're you're correct then ego gets involved and you just don't go anywhere but the fundamentally the question of well what is a force isn't incredibly important we need to have that conversation but it needs to be done in this very political way of like let's be respectful of everyone and let's realize that we're all learning together and not shutting out other people and so when you look at a lot of revolutionary ideas they were not accepted right away and you know Galileo had a couple of problems with the authorities and later thinkers Descartes was like all right look I kind of agree with Galileo but I'm gonna have to not say that I'll have to create and invent and write different things that keep me from being in trouble but we still slowly made progress revolutions are difficult in all forms and certainly in science before we get to AI on topic of revolutionary ideas let me ask on a reddit AMA you said that is the earth flat is one of the favorite questions you've ever answer yeah speaking of revolutionary ideas so your video on that people should definitely watch is really fascinating can you elaborate why you enjoyed answering this question so much yeah well it's a long story I remember a long time ago I was living in New York at the time so had to have been like 2009 or something I visited the Flat Earth forums and this was before the Flat Earth theories became as sort of mainstream as they are I'm sorry to ask the dumb question forums online forums yeah okay the Flat Earth Society I don't know if it's con org but went there and I was reading you know their ideas and how they responded to typical criticisms of well the earth isn't flat because what about this and I could not tell and I mentioned this in my video I couldn't tell how many of these community members actually believed the earth was flat or were just trolling and I realized that the fascinating thing is how do we know anything and what makes for a good belief versus a maybe not so tenable or good belief and so that's really what my video about earth being flat is about it's about look there are a lot of reasons the earth is probably not flat but a Flat Earth believer can respond to every single one of them but it's all in an ad hoc way and all of these all their rebuttals aren't necessarily gonna form a cohesive noncontradictory whole and I believe that's the episode where I talk about Occam's razor and Newton's flaming laser sword and then I say well you know what wait a second we know that space contracts as you move and so to a particle moving near the speed of light towards Earth earth would be flattened in the direction of that particles travel so to them earth is flat like we need to be you know really generous to even wild ideas because they're all thinking they're all the communication of ideas and what else can it mean to be a human yeah and I think I'm a huge fan of the Flat Earth theory quote-unquote in the sense that to me feels harmless to explore some of the questions of what it means to believe something what it means to explore the edge of science and so on it's because it's a harm it's to me nobody gets hurt whether the earth is flat or round not literally but I mean intellectually when we're just having a conversation that said again to elitism I find that scientists roll their eyes way too fast on the Flat Earth the kind of dismissal that I see to this you of an ocean they haven't like sat down and say what are the arguments they're being proposed and this is why these arguments incorrect so this is you know that should be something that scientists should always do even to the most sort of ideas that seem ridiculous so I like this is almost it's almost my test when I ask people what they think about Flat Earth theory to see how quickly they roll their eyes well yeah I mean let me go on record yeah and say that the earth is not flat it is a three-dimensional spheroid however I don't know that and it has not been proven signs doesn't prove anything it just reduces uncertainty could the earth actually be flat extremely unlikely yes extremely unlikely and so it is a ridiculous notion if we care about how probable and certain our ideas might be but I think it's incredibly important to talk about science in that way and to not resort to well it's true it's true in the same way that a mathematical theorem is true and I think we're kind of like being pretty pedantic about defining this stuff but like sure I could take a rocket ship out and I could sorbets earth and look at it and it would look like a ball right but I still can't prove that I'm not living in a simulation that i'm not a brain-in-a-vat that this isn't all an elaborate ruse created by some technologically advanced extraterrestrial civilization right so there's always some doubt and that's fine that's exciting and I think that kind of doubt practically speaking is useful when you start talking about quantum mechanics or string theory sort of it helps to me that kind of little adds a little spice into the thinking process of scientists so I mean just I just as a thought experiment your video kind of okay say the earth is flat what would the forces when you walk about this flat or earth feel like - the human that's a really nice thought experiment to think about right cuz what's really nice about it is that it's it's a funny thought experiment but you actually wind up accidentally learning a whole lot about gravity and about relativity and geometry and I think that's really the goal of what I'm doing I'm not trying to like convince people that the earth is round I feel like you either believe that it is or you don't and like that's you know how can I change that yeah what I can do is change how you think and how you are introduced to important concepts like well how does gravity operate oh it's all about the center of mass of an object so right on a sphere we're all pulled towards the middle essentially the centroid geometrically but on a disk ooh you're gonna be pulled at a weird angle if you're out near the edge and that stuff's fascinating yeah and to me that's that that was that that particular video opened my eyes even more to what gravity is it's just a really nice visualization to love because you always imagine gravity was spheres with masses that are spheres yeah and imagining gravity on masses that are not spherical some some other shape but in here a plate a flat object is really interesting it makes you really kind of visualizing it they're much a way the force yeah even if a disc the size of Earth would be impossible I think anything larger than like the moon basically needs to be a sphere because gravity will round it out so you can't have a teacup the size of Jupiter right there's a great book about a teacup in the universe that highly recommend I don't remember the author I forget her name but it's a wonderful book so look it up I think it's called teacup in the universe still linked on this point briefly your videos are generally super people love them right if you look at the sort of number of likes versus dislikes it's this measure of YouTube right is incredible and as do I but this particular Flat Earth video has more dislikes that than usual what what are you on that topic in general what's your sense how big is the community not just who believes in Flat Earth but sort of the anti scientific community that naturally distrust scientists in a way that's that's not an open-minded way like really just distrust scientists like they're bought by some place they're kind of mechanism of the some kind of bigger system that's trying to manipulate him ins what's your sense of the size of that community you're one of the sort of great educators in the world that educates people on the exciting power of science so you're kind of up against this community what's your sense of it i I really have no idea I haven't looked at the likes and dislikes on the Flat Earth video and so I would wonder if it has a greater percentage of dislikes than usual is that because of people disliking it because they you know think that it's a video about earth being flat and they find that ridiculous and they just like it without even really watching much do they wish that I was more like dismissive of this latter theories yeah that's awesome I know there are a lot of response videos that kind of go through the episode and are pro Flat Earth mm-hmm but I don't know if there's a larger community of unorthodox thinkers today than there have been in the past okay and I just want to not lose them I want them to keep listening and thinking and by calling them all you know idiots or something like that is no good because how idiotic are they really I mean the earth isn't a sphere at all like we know that it's an oblate spheroid and that in and of itself is really interesting and I investigated that in which way is down where I'm like really down does not point towards the center of the earth it's it points in a different direction depending on what's underneath you and what's above you and what's around you the whole universe is is tugging on me and then you also show that gravity is non-uniform work across the globe like if you just gues thought experiment if you build a bridge all the way and all the way across the earth and then just knock out its pillars what would happen yeah and you described how it would be like a very chaotic unstable thing that's happening because gravity is non-uniform all throughout the earth yeah in small spaces like the ones we work in we can essentially assume that gravity is uniform but it's not it is weaker the further you are from the earth and it also is going to be it's it's radially pointed towards the middle of the earth so a really large object will feel tidal forces because of that non-uniform this and we can take advantage of that with satellites right gravitational induced torque it's a great way to align your satellite without having to use fuel or any kind of you know engine so let's jump back to it artificial intelligence what's your thought of the state of where we are at currently with artificial intelligence and what do you think it takes to build human level or superhuman level intelligence I don't know what intelligence means that's my biggest question at the moment and it's I think it's cuz my instinct is always to go well what are the foundations here of our discussion what does it mean to be intelligent how do we measure the intelligence of an artificial machine or a program or something can we say that humans are intelligent because there's also a fascinating field of how do you measure human intelligence of course but if we just take that for granted saying that the whatever this fuzzy intelligence thing we're talking about humans kind of have it what would be a good test for you for touring develop a test that's natural language conversation would that impress you a chatbot that you'd want to hang out and have a beer with of you know for a bunch of hours or have dinner plans with with is that a good test natural energy conversation is there something else that would impress you or is that also to differ yeah I'm pretty much impressed by everything well I think if Roomba if there was a chat bot that was like incredibly and I don't know really had a personality and I if I didn't be the the Turing test right like if I'm unable to tell that it's not another person but then I was shown a bunch of wires and mechanical components and then it was like that's actually what's you're talking to I don't know if I would feel that guilty destroying it I would feel guilty because clearly it's well-made and it's a really cool thing it's like destroying a really cool car or something but I would not feel like I was a murderer so yeah at what point would I start to feel that way and and this is such a subjective psychological question if you give it movement or if you have it mmm act as though or perhaps really feel pain as I destroy it and scream and resist then I'd feel that yeah that's beautifully put and let's just say act like it's in pain so if you just have a robot that it's not screams just like moans in pain if you kick it yeah that immediately just puts it in a class that we humans it becomes it we anthropomorphize it almost immediately it becomes human yeah that psychology question as opposed to sort of a physics question right I think that's a really good instinct to have you know if the robot screams screams and and and moans even if you don't believe that it has the mental experience the qualia of pain and suffering I think it's still a good instinct to say you know what I'd rather not hurt it the problem is that instant can get us in trouble because then robots can manipulate that and you know there's different kinds of robots as robots like the Facebook and the YouTube algorithm that recommends the video and they can manipulate in the same kind of way well let me ask you just to stick on artificial intelligence for a second do you have worries about existential threats from AI or extension tests from other technologies like nuclear weapons that could potentially destroy life on Earth or damage it to a very significant degree yeah of course I do especially the weapons that we create there's all kinds of famous ways to think about this and one is that Wow what if we don't see advanced alien civilizations because of the danger of Technology what if we reach a point and I think there's a channel-body to cheese I wish I remember the name of the channel but he delves into this this kind of limit of maybe once you discover radioactivity and its power you've reached this important hurdle and the reason that the skies are so empty is that no one's ever like managed to survive as a civilization once they have that destructive power and when it comes to AI I'm not really very worried because I think that there are plenty of other people that are already worried enough and oftentimes these worries are just they just get in the way of progress and they're there questions that we should address later and you know I think I talked about this in my interview with the self-driving autonomous vehicle guy as I think it was a bonus scene from the trolley problem episode and I'm like wow what should a car do if like this really weird contrived scenario happens where it has to like swerve and like save the driver but kill a kid and he's like well you know what would a human do and if we resist technological progress because we're worried about all of these little issues then it gets in the way and we shouldn't avoid those problems but we shouldn't allow them to be stumbling blocks - advancement so the you know folks like Sam Harris or Elon Musk are saying that we're not worried enough so worried should not paralyze technological progress but we're sort of marching technologies marching forward without the key scientists the developing and technology worrying about the overnight having some effects that would be very detrimental to society so the push back on your thought of the idea that there's enough people worrying about it Elon Musk says there's not enough people worrying about it I think that's the kind of balances you know it's like folks to who really focused on nuclear deterrence are saying there's not enough people worried about nuclear deterrence right so it's an interesting question of what is a good threshold of people to worry about these and if it's too many people that are worried you're right it'll be like the the press would over report on it and there'll be technological halt technology progress if not enough then we can march straight ahead into that abyss that human beings might be destined for with the progress of technology yeah I don't know what the right balance is of how many people should be worried and how worried should they be but we're always worried about new technology you know we know that Plato was worried about the written word he's like we shouldn't teach people to write because then they won't use their minds to remember things there there have been concerns over technology and its advancement since the beginning of recorded history and so you know I think however these conversations are really important to have because again we learn a lot about ourselves if we're really scared of some kind of AI like coming into being that is conscious or whatever and and can self-replicate we already do that every day it's called humans being born they're not artificial they're they're they're humans but they're intelligent and I don't want to live in a world where we're worried about babies being born because what if they become evil right what if they become mean people what if they what if they're thieves maybe we should just like what not have babies born like maybe we shouldn't create AI it's like you know we will want to have safeguards in place yeah in the same way that we know look a kid could be born that becomes some kind of evil person but we have loss right and it's possible that with advantage in etics and general be able to you know it's a scary thought to say that you know the this my child if born would be would have an 83% chance of being a psychopath right like being able to if it's something genetic if there's some sort of and what to use that information what to do with that information is a difficult ethical yeah I'd like to find an answer that isn't well let's not have them live you know I'd like to find an answer that is well all human life is worthy and if you have an 83% chance of becoming a psychopath well you still deserve dignity yeah and you still deserve to be treated well and a you still have rights at least at this part of the world at least in America there's a respect for individual life in that way that's well to me but again I'm in this bubble is a beautiful thing but there's other cultures or individual human life is not that important that we're a society so I was born in Soviet Union where the strength of nation and society together is more important than the any one particular individual there's an interesting also notion the stories we tell ourselves I like the one where individuals matter but it's unclear that that was what the future holds well yeah and I mean let me even throw this out like what is artificial intelligence how can it be artificial I really think that we get pretty obsessed and stuck on the idea that there is some thing that is a wild human a pure human organism without technology but I don't think that's a real thing I think that humans and human technology are one or Gizem look at my glasses okay if an alien came down and saw me would they necessarily know that this is an invention that I don't grow these organically from my body they wouldn't know that right away and the written word and spoons and cups these are all pieces of technology we are not alone as an organism and so the technology we create whether it be video games or artificial intelligence that can self-replicate and hate us it's actually all the same organism I when you're in a car where do you end in the car begin it seems like a really easy question to answer but the more you think about it the more you realize wow we are in this symbiotic relationship with our inventions and there are plenty of people who are worried about it and there should be but it's it's inevitable and I think the even just us think of ourselves as individual intelligences maybe silly notion because you know it's much better to think of the entirety of human civilization living all living organs on earth as a single living organism right as a single intelligent creature because you're right everything's intertwined everything is deeply connected so we mention Elon Musk see you're a curious lover of science what do you think of the efforts that Elon Musk is doing with space exploration with electric vehicles with autopilot sort of getting into the space of autonomous vehicles was boring under la and neural link trying to communicate brain machine interfaces communicate between machines and human brains well it's really inspiring I mean look at the fandom that he's amassed it's it's not common for someone like that to have such a following until you're a nerd yeah so it's really it's really exciting but I also think that a lot of responsibility comes with that kind of power so like if I met him I would love to hear how he feels about the responsibility he has when when there our people who are such a fan of your ideas and your dreams and share them so closely with you you have a lot of power and he didn't always have that you know he wasn't born as Elon Musk's well he was but well he was named that later but the point is that that that I I want to know the psychology of becoming a figure like him well I don't even know how to phrase the question right but it's a question about what do you do when you were you're following your fans become so you know large that it's almost bigger than you and how do you how do you responsibly manage that and maybe it doesn't worry him at all and that's fine too but I'd be really curious and I think there are a lot of people that go through this when they realize whoa there are a lot of eyes on me there are a lot of people who really take what I say very earnestly and and take it to heart and will defend me and who that's that's some that that can be dangerous and and you have to be responsible with it both in terms of impact in society and psychologically for the individual just just the the burden psychologically Annie on yeah yeah how does he how does he think about that part of his persona well let me throw that right back at you because in some ways you're just a funny guy that gotten a humongous following a funny guy with a curiosity mm-hmm you've got a huge following how do you psychologically deal with the responsibility in many ways you ever reach in many ways bigger than you are musk what is your what is the burden that you feel in educating being one of the biggest educators in the world where everybody's listening to you and actually everybody like that most of the world that uses YouTube for educational material trust you as a source of good strong scientific thinking it's a burden and I try to approach it with a lot of humility and sharing like I'm not out there doing a lot of scientific experiments I am sharing the work of real scientists and I'm celebrating their work and the way that they think and the power of curiosity but I want to make it clear at all times that like look you know we don't know all the answers and I don't think we're ever going to reach a point where we're like wow and there you go that's the universe it's this equation you plug in some conditions or whatever and you do the math and you know what's gonna happen tomorrow I don't think we're gonna reach that point but I I think that there is a tendency to sometimes believe in science and become elitist and become I don't know hard when in reality it should humble you and make you feel smaller I think there's something very beautiful about feeling very very small and very weak and to feel that you need other people hmm so I try to keep that in mind and say look thanks for watching Vsauce is not I'm not Vsauce you are when I start the episodes I say hey Vsauce Michael here Vsauce and Michaels are actually a different thing in my mind I don't know if that's always clear but yeah I have to approach it that way because it's not about me yeah so it's not even you're not feeling the responsibility you're just sort of plugging into this big thing that is scientific exploration of our reality and you're a voice that represents a bunch but you're just plugging into this big Vsauce ball that others millions of others have plugged into yeah I'm just hoping to encourage curiosity and you know we're responsible thinking and an embracement of doubt and being okay with that so next week talking to Chris Osgood row I'm not sure if you familiar who he is but he's the VP of engineering head of the quote unquote YouTube algorithm this search and Discovery's yeah let me ask first high level do you have do you have a question for him that if you can get an ounce honest answer that you would ask but more generally how do you think about the YouTube algorithm that drives some of the motivation behind not know some of the design decisions you make as you ask and answer some of the questions you do how would you improve this algorithm in your mind in general so just the what would you ask him and outside of that how would you like to see the algorithm improve well I think of the algorithm as a mirror it reflects what people put in and we don't always like what we see in that mirror from the individual mirror to the individual Meritor of the society both in the aggregate it's reflecting back what people on average want to watch and when you see things being recommended to you it's reflecting back what it thinks you want to see and specifically I would guess that it's not just what you want to see but what you will click on and what you will watch some of and stay on YouTube because of I don't think that is all me guessing but I don't think that YouTube cares if you only watch like a second of a video as long as the next thing you do is open another video if you close the app or close the site that's a problem for them because they're not a subscription platform they're not like look you're giving us 20 bucks a month no matter what so who cares they need you to watch and spend time there and see ads so what one of the things I'm curious about whether they do consider longer term sort of develop you your longer-term development as a human being which I think ultimately will make you feel better about using YouTube in the long term and allowing you to stick with it for longer because even if you feed the dopamine rush in the short-term and you keep clicking on cat videos the eventually you sort of wake up like from a drug and say I need to quit this so I wonder how much they're trying to optimize for the long term because when I look at the you know your videos aren't and sort of no offense but they're not the most clickable they're both the most clickable and I feel I watch the entire thing and I feel a better human after I watch it right so like they're not for just optimizing for the click ability is I hope so my thought is how do you think of it and this would affect your own content like how deep you go how profound you explore the directions and so on I I've been really lucky in that I don't worry too much about the algorithm I mean look at my thumbnails I don't really go too wild with them and with minefield where I'm in partnership with YouTube on the thumbnails I'm often like let's pull this back let's be mysterious but usually I'm just trying to do what everyone else is not doing so if everyone's doing crazy Photoshop kind of thumbnails I'm like what if the thumbnails just align yeah and what if the title is just a word yeah and I I kind of feel like all of the Vsauce channels of cultivating an audience that expects that and so they would rather Jake make a video that's just called stains then one called I explored stains is shocking yeah but there are other audiences out there that want that and you know I think most people kind of we don't want what you see the algorithm favoring which is mainstream traditional celebrity and news kind of information I mean that's what makes YouTube really different than other streaming platforms no one's like what's going on in the world I'll open up Netflix to find out but you do open up Twitter to find that out you open up Facebook you can open up YouTube because you'll see that the trending videos are like what happened amongst the traditional mainstream people in different industries and that's what's being shown and it's it's not necessarily YouTube saying we want that to be what you see it's that that's what people click on when they see ariana grande you know reads a love letter from like her high school sweetheart they're like I want to see that and when they see a video from me that's got some lines in math and it's called law and causes they're like well I mean that I'm just on the bus like I don't have time to dive into a whole lesson so you know before get super mad at YouTube you should say really they're just reflecting back human behavior is there something you would improve about the algorithm knowing of course that as far as we're concerned it's a black box or don't know how it works right and I don't think that even anyone at YouTube really knows what it's doing they know what they've tweaked but then it learns I think that it learns and it decides how to behave and sometimes there the YouTube employees are left going I don't know maybe we should like change the value of how much it you know worries about watch time and maybe it should worry more about something I don't know but I mean I would like to see I don't know what they're doing and not doing well is there a conversation that you think they should be having just internally whether they're having it or not is there something should they be thinking about the long-term future should they be thinking about educational content and whether that's educating about what just happened in the world today news or educational content like what you're providing which is asking big to have timeless questions about how the way the world works well it's interesting like what should they think about because it's called YouTube not our tube and if that's why I think they have so many phenomenal educational creators yes you don't have shows like three blue one brown or physics girl or Looking Glass universe or up an atom or brain scoop or I mean I could go on and on they aren't on amazon prime and netflix and and they don't have Commission shows from those platforms it's all organically happening because there are people out there that want to share their passion for learning that want to share their curiosity and YouTube could you know promote those kinds of shows more but like first of all they probably wouldn't get as many clicks and YouTube needs to make sure that the average user is always clicking and staying on the site they could still promote it more for the good of society but then we're making some really weird claims about what's good for society because I think that cat videos are also an incredibly important part of what it means to be a human I mentioned this quote before from unamuno about look I've seen a cat estimate distances and calculate a jump you know more often and I've seen a cat cry and so things that that play with our emotions and make us feel things can be cheesy and can feel cheap but like man that's very human and so even the dumbest vlog is still so important that I don't think it I have a better claim to take its spot than it has to have that spot so it puts a mirror to us the beautiful parts the ugly parts the shallow parts the Jeep ours you're right what I would like to see is you know I miss the days when engaging with content on YouTube helped push it into my subscribers timelines it used to be that when I liked a video say from veritasium it would show up in the feed on the front page of the app or the website of my subscribers and I knew that if I liked a video I could send it a hundred thousand views or more that no longer is true but I think that was a good user experience when I subscribe to someone when I'm following them I want to see more of what they like I want them to also curate the feed for me and I think that Twitter and Facebook are doing that and also some ways that are kind of annoying but I would like that to happen more and I think we would see communities being stronger on YouTube if it was that way instead of YouTube going well technically Michael like this veritasium video but people are way more likely to click on carpool karaoke so I don't even care who they are just given that not saying anything against carpool karaoke that is a extremely important part of our society what it means to be a human on earth you know but I'll say it sucks but uh yeah but a lot of people would disagree with you and they should be able to see as much of that as they want yes and even people who don't think they like it should still be really aware of it because it's such an important thing and such an influential thing but yeah I just wish that like new channels I discover and that I subscribe to I wish that my subscribers found out about that because especially in the education community a rising tide floats all boats if you watch a video from number file you're just more likely to want to watch an episode from me whether it be on Vsauce one or ding it's not it's not competitive in the way that traditional TV was where it's like well if you tuned in to that show it means you're not watching mine because they both air at the same time so helping each other out through collaborations takes a lot of work but just through engaging commenting on their videos liking their videos subscribing to them whatever that I would love to see become easier and more powerful so a quick and impossibly deep question last question about mortality you've spoken about death as an interesting topic do you think about your own mortality yeah every day it's really scary so what do you think is the meaning of life that mortality makes very explicit so why are you here on earth Michael what's the point of this whole thing what you know what does mortality in the context of the whole universe make you realize about yourself just you Michael Stevens well it makes me realize that I am destined to become an ocean I'm destined to become a memory and we can extend life I think there's really exciting things being done to extend life but we still don't know how to like you know protect you from some accident that could happen you know some unforeseen thing maybe we could like save my connectome and like recreate my consciousness digitally but even that is could it could be lost if it's stored on a physical medium or something so basically I just think that embracing and realizing how cool it is that like some day I will just be an idea and there won't be a Michael anymore that can be like no that's not what I meant it'll just be what people like they have to guess what I meant and they'll remember me and how I live on and as that memory you will will maybe not even be who I wanted to be but there's something powerful about that and there's something powerful about letting future people run the show themselves I think I I'm glad to get out of their way at some point and say all right it's your world now so you the physical entity michael has have ripple effects in the space of ideas that far out lives you yeah in ways you can't control but it's nevertheless fascinating to think I mean especially with you you can imagine an alien species when they finally arrive and destroy all of us would watch your videos to try to figure out what what were the questions but even if they didn't you know I still think that there will be ripples like when I say memory I don't specifically mean people remember my name and my birthdate and have like there's a photo of me on Wikipedia like all that can be lost but I still would hope that people ask questions and and and teach concepts in some of the ways that I have found useful and satisfying even they don't know that I was the one who tried to popularize it that's fine but if Earth was completely destroyed like burnt to a crisp everything on it today what would the universe wouldn't care like Jupiter's not gonna go oh no and that could happen because so we do however have the power to you know launch things into space to try to extend how long our memory exists and what I mean by that is you know we are recording things about the world and we're learning things and writing stories and all of this and preserving that is truly what I think is the essence of being a human we are Auto biographers of the universe and we're really good at it we're better than fossils were better than light spectrum we're better than any of that we collect much more detailed memories of what's happening much better data and so that should be our legacy and I hope that that's that's kind of mine too in terms of people remembering something or having some kind of effect but even if I don't you can't not have an effect right that's the thing this is not me feeling like I hope that I have this powerful legacy it's like no matter who you are you will but you also have to embrace the fact that that impact might look really small and that's okay one of my favorite quotes is from Tess of the d'Urbervilles and it's along the lines of the the measure of your life depends on not your external displacement but your subjective experience if I am happy and those that I love are happy can that be enough because if so excellent I think there's no better place to end it Michael thank you so much there's an honor meet you thanks for talking thank you it was a pleasure thanks for listening to this conversation with Michael Stevens and thank you to a presenting sponsor cash app downloaded use code let's podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn to dream of engineering our future if you enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on Twitter and now let me leave you with some words of wisdom from Albert Einstein the important thing is not to stop questioning curiosity has its own reason for existence one cannot help but be in awe when he contemplates the mysteries of eternity of life the marvelous structure of reality it is enough if one tries merely to comprehend a little of this mystery every day thank you for listening and hope to see you next time you |
Rohit Prasad: Amazon Alexa and Conversational AI | Lex Fridman Podcast #57 | the following is a conversation with raha Prasad he's the vice president and head scientist of Amazon Alexa and one of its original creators the Alexa team embodies some of the most challenging incredible impactful and inspiring work that is done in a high today the team has to both solve problems at the cutting edge of natural language processing and provide a trustworthy secure and enjoyable experience to millions of people this is where state-of-the-art methods in computer science meet the challenges of real-world engineering in many ways Alexa and the other voice assistants are the voices of artificial intelligence to millions of people and an introduction to AI for people who have only encountered it in science fiction this is an important and exciting opportunity so the work that Rohit and the Alexa team are doing is an inspiration to me and to many researchers and engineers in the AI community this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma n if you leave a review on an apple podcast especially but also cast box or comment on youtube consider mentioning topics people ideas questions quotes in science tech or philosophy that you find interesting and I'll read them on this podcast I won't call out names but I love comments with kindness and thoughtfulness in them so I thought I'd share them someone on YouTube highlighted a quote from the conversation with Ray Dalio where he said that you have to appreciate all the different ways that people can be a player's this connected me to on teams of engineers it's easy to think that raw productivity is the measure of excellence but there are others I've worked with people who brought a smile to my face every time I got to work in the morning their contribution to the team is immeasurable I recently started doing podcast ads at the end of the introduction I'll do one or two minutes after introducing the episode and never any ads in the middle that break the flow of the conversation I hope that works for you it doesn't hurt the listening experience this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit a big coin in just seconds cash app also has a new investing feature you can buy fractions of a stock say $1 worth no matter what the stock price is brokerage services are provided by cash up investing a subsidiary of square and member at CIBC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating at Charity Navigator which means the donated money 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hiring the perfect person for the role in less than two weeks from start to finish zip recruiter the smartest way to hire CY zip recruiters effective for businesses of all sizes by signing up as I did for free at zip recruiter comm / Lex pod that zipper Kirkham / Lex pod and now here's my conversation with Rohit Prasad in the movie her I'm not sure if you ever seen a human falls in love with a voice of an AI system let's start at the highest philosophical level before we get too deep learning and some of the fun things do you think this what the movie her shows is within our reach I think not specifically about her but I think what we are seeing is a massive increase in adoption of AI assistants Rai and all parts of our social fabric and I think it's what I do believe is that the utility these areas provide some of the functionalities that are shown are absolutely within reach so the some of the functionality in terms of the interactive elements but in terms of the deep connection that's purely voice based do you think such a close connection as possible with voice alone it's been a while since I saw her but I would say in terms of the in terms of interactions which are both human-like and in these AI assistants you have to value what is also super human we as humans can be in only one place AI assistance can be in multiple places at the same time one with you on your mobile device one at your home one at work so you have to respect these superhuman capabilities to Plus as humans we have certain attributes we are very good at where you're at reasoning AI assistance not yet there but in Terrell mauve AI assistance what they're great at is computation memory it's infinite and pure these are the attributes you have to start respecting so I think the comparison with human-like versus the other aspect which is also super human has to be taken into consideration so I think we need to elevate the discussion to not just human like so there's certainly elements we just mentioned Alexa's everywhere computation is speaking so this is a much bigger infrastructure than just the thing that sits there in the room with you but it certainly feels to us mere humans that there's just another little creature there when you're interacting with it you're not interacting with the entirety of the infrastructure you're interacting with the device the feeling is okay sure we anthropomorphize things but that feeling is still there so what do you think we as humans the purity of the interaction with a smart assistant what do you think we look for in that interaction I think in the certain interactions I think will be very much where it does feel like a human because it has a persona of its own and in certain ones it wouldn't be so I think a simple example to think of it is if you're walking through the house and you just want to turn on your lights on and off and you're issuing a command that's not very much like a human-like interaction and that's where the AI shouldn't come back and have a conversation with you just it should simply complete that command so those I think the blend of we have to think about this is not human human alone it is a human machine interaction and certain aspects of humans are needed and certain aspects are in situations demand it to be like a machine so I told you it's gonna be full soft cause in parts what was the difference between human and machine in that interaction when we interact to humans especially those our friends and loved ones versus you and a machine that you also are close with I think they you have to think about the roles the AI plays right so and it differs from different customer to customer different situation to situation especially I can speak from Alexis perspective it is a companion a friend at times an assistant an advisor down the line so I think most a eyes will have this kind of attributes and it will be very situational in nature so where is the boundary I think the boundary depends on exact context in which you are interacting what they are so the depth and the richness of natural language conversation is been by Alan Turing being used to try to define what it means to be intelligent you know there's a lot of criticism of that kind of but what do you think it's a good test of intelligence in your view in the context of the Turing test and Alexa or the elect surprise this whole realm do you think about this human intelligence what it means to define it what it means to reach that level I do think the ability to converse is an sign of an ultimate intelligence I think that is no question about it so if you think about all aspects of humans there are sensors we have and those are basically a data collection mechanism and based on that we make some decisions with our sensory brains right and from that perspective I think that there are elements we have to talk about how we sense the world and then how we act based on what we sense those elements clearly machines have but then there's the other aspects of computation that is way better I also mentioned about memory again in terms of being near infinite depending on the storage capacity you have and the retrieval can be extremely fast and pure in terms of like there's no ambiguity of who did I see when right I mean if your machine scan remember that quite well so it again on a philosophical level I do subscribe to the fact that to can be able to converse and as part of that to be able to reason based on the world knowledge you've acquired and the sensory knowledge that is there is definitely very much the essence of indulgence but indulgence can go beyond human level intelligence based on what machines are getting capable of so what do you think maybe stepping outside of Alexa broadly as an AI field what do you think is a good test of intelligence put it another way outside of Alexa because so much of Alexa is a product is an experience for the customer on the research side what would impress the heck out of you if you saw you know what is the test what he said wow this thing is now starting to encroach into the realm of what we loosely think of as human intelligence so well we think of it as a GI and human intelligence all together right so in some sense and I think we are quite far from that I think an unbiased view I have is that the Alexus intelligence capability is a great test I think of it as there are many other proof points like self-driving cars game playing like go or chess let's take those two for as an exemption clearly requires a lot of data-driven learning and intelligence but it's not as hard a problem as conversing with as an AI is with it humans to accomplish certain tasks or open domain chat as you mentioned like a surprise in those settings the key difference is that the end goal is not defined unlike game playing you also do not know exactly what state you are in in a particular goal completion scenario in certain times sometimes you can if it is a simple goal but if you're even certain examples like planning a weekend or you can imagine how many things change along the way you look for whether you make change your mind and you you change their destination or you want to catch a particular event and then you decide no I want this other event I want to go to so these dimensions of how many different steps are possible when you're conversing as a human with a machine makes it an extremely daunting problem and I think it is the ultimate test for intelligence and don't you think the natural language is enough to prove that conversation your conversation from a scientific standpoint natural language is a great test but I would go beyond I don't want to limit it to as natural language as simply understanding an intent or parsing for entities and so forth we are really talking about dialogue so so I would say human machine dialogue is definitely one of the best tests of intelligence so can you briefly speak to the Alexa prize for people who are not familiar with it and and also just maybe were things stand and what have you learned what's surprising what have you seen the surprising from this incredible competition absolutely it's a very competition like surprise is essentially Grand Challenge in conversational artificial intelligence where we threw the gauntlet to the universities who do active research in the field to say can you build what we call a social board that can converse with you coherently and engagingly for 20 minutes that is an extremely hard challenge talking to someone in a who you're meeting for the first time or even if you're you've met them quite often to speak at 20 minutes on any topic an evolving nature of topics is super hard we have completed two successful years of the competition the first was one with the industry of Washington's second industry of California we are in our third instance we have an extremely strong team of 10 cohorts and the third instance of the of the lexer prizes underway now and we are seeing a constant evolution first year was definitely learning it was a lot of things to be put together we had to build a lot of infrastructure to enable these you know STIs to be able to build magical experiences and and do high quality research just a few quick questions sorry for the interruption what is failure look like in the 20-minute session so what does it mean to fail not to reach the twenty minimum awesome question so there are one first of all I forgot to mention one more detail it's not just 20 minutes but the quality of the conversation too that matters and the beauty of this competition before I answer that question on what failure means is first that you actually converse with millions and millions of customers as these social BOTS so during the judging phases there are multiple phases before we get to the finals which is a very controlled judging in a situation where we have we bring in judges and we have interactors who interact with these social BOTS that is a much more controlled setting but till the point we get to the finals all the judging is essentially by the customers of Alexa and there you basically rate on a simple question how good your experience was so that's where we are not testing for a 20 minute boundary being claw across because you do want to be very much like a clear-cut winner be chosen and and it's an absolute bar so did you really break that 20-minute barrier is why we have to test it in a more controlled setting with actors essentially in tractors and see how the conversation goes so this is why it's a subtle difference between how it's being tested in the field with real customers versus in the lab to award the prize so on the latter one what it means is that essentially the that there are three judges and two of them have to say this conversation is stalled essentially got it and the judges the human experts judges or human experts okay great so this is in the third year so what's been the evolution how far it's in the DARPA challenge in the first year the autonomous vehicles nobody finished in the second year a few more finished in the desert so how far along within this I would say much harder challenge are we this challenge has come a long way do they extend that we've definitely not close to the 20-minute barrier being with coherence and engaging conversation I think we are still five to ten years away in that horizon to complete that but the progress is immense like what you're finding is the accuracy in what kind of responses these social BOTS generate is getting better and better what's even amazing to see that now there's humor coming in the bots are quite you know you're talking about ultimate science of intial and signs of intelligence I think humor is a very high bar in terms of what it takes to create humor and I don't mean just being goofy I really mean good sense of humor is also a sign of intelligence in my mind and something very hard to do so these social BOTS are now exploring not only what we think of natural language abilities but also personality attributes and aspects of when to inject an appropriate joke went to when you don't know the question the domain how you come back with something more intelligible so that you can continue the conversation if if you and I are talking about AI and we are domain experts we can speak to it but if you suddenly switch the topic to that I don't know how do I change the conversation so you're starting to notice these elements as well and that's coming from partly by by the nature of the 20 minute challenge that people are getting quite clever on how to really converse and essentially masks some of the understanding defects if they exist so some of this this is not a Lex of the products this is somewhat for fun for research for innovation and so on I have a question sort of in this modern era there's a lot of you look at Twitter and Facebook and so on there's there's discourse public discourse going on and some things are a little bit too edgy people get blocked and so on I'm just out of curiosity are people in this context pushing the limits is anyone using the f-word is anyone sort of pushing back sort of you know arguing I guess I should say in as part of the dialogue to really draw people in first of all let me just back up a bit in terms of why we're doing this right so you said it's fun I think fun is more part of the engaging part for customers it is one of the most used skills as well in our skill store but up that apart the real goal was essentially what was happening is with lot of AI research moving to industry we felt that academia has the risk of not being able to have the same resources at disposal that we have which is loss of beta massive computing power and a clear ways to test these AI advances with real customer benefits so we brought all these three together in the like surprise that's why it's one of my favorite projects and Amazon and with that the secondary fact is yes it has become engaging for our customers as well we're not there in terms of where we want to it to be right but it's a huge progress but coming back to your question on how do the conversations evolve yes there is some natural attributes of what you said in terms of argument and some amount of swearing the way we take care of that is that there is a sensitive filter we have built that show you see words and so it's more than keywords a little more in terms of of course there's key word base to but there's more in terms of these words can be very contextual as you can see and also the topic can be something that you don't want a conversation to happen because this is a criminal device as well a lot of people use these devices so we have put lot of guardrails for the conversation to be more useful for advancing AI and not so much of these these other issues you attributed what's happening in there I feel as well right so this is actually a serious opportunity I didn't use the right word fun I think it's an open opportunity to do some some of the best innovation in conversational agents in in the world absolutely why just universities why just you know streets because as I said I really felt young minds young minds it's also - if you think about the other aspect of where the whole industry is moving with AI there's a dearth of talent in in given the demands so you do want the universities to have a clear place where they can invent and research and not fall behind with that they can't motivate students imagine all grad students left - to industry like us or or faculty members which has happened - so this is in a way that if you're so passionate about the field where you feel industry and academia need to work well this is a great example and a great way for universities to participate so what do you think it takes to build a system that wins the allow surprise I think you have to start focusing on aspects of reasoning that it is there are still more lookups of what intense customers asking for and responding to those are rather than really reasoning about the elements of the of the conversation for instance if you have if you're playing if the conversation is about games and it's about a recent sports event there's so much context in war and you have to understand the entities that are being mentioned so that the conversation is coherent rather than you suddenly just switch to knowing some fact about a sports entity and you're just relating that rather than understanding the true context of the game like you if you just said I learned this fun fact about Tom Brady rather than really say how he played the game the previous night then the conversation is not really that intelligent so you have to go to more reasoning elements of understanding the context of the dialogue and giving more appropriate responses which tells you that we are still quite far because a lot of times it's more facts being looked after and something that's close enough as an answer but not really the answer so that is where the research needs to go more an actual true understanding and reasoning and that's why I feel it's a great way to do it because you have an engaged set of users working to make help these AI advances happen in this case item actually customers they're there quite a bit and there's a skill what is the experience for the for the user that is helping so just to clarify this isn't as far as I understand the Alexa so this skill is to stand alone for the art surprise I mean it's focused on the elect surprise it's not you ordering certain things and I was on the comet trait checking the weather or you're playing Spotify right separate skills directly and so you're focused on helping not well I don't know how do people how do customers think of it are they having fun are they helping teach the system what's the experience like I think it's both actually and let me tell you how they how you invoke this skill so you all you have to say Alexa let's chat and then the first time you say Alexa let's chat it comes back with a clear message that you're interacting with one of those you know three social BOTS and there's a fear so he's know exactly how you interact right and that is why it's very transparent you are being asked to help right and and we have lot of mechanisms where as the we are in the first phase of feedback phase then you send a lot of emails to our customers and then this they know that this the team needs a lot of interactions to improve the accuracy of the system so we know we have lot of customers who really want to help be zeros to bots and they are conversing with that and some are just having fun with just saying Alexa let's chat and also some adversarial behavior to see whether how much do you understand as a social bot so I think we have a good healthy mix of all three situations so what is the if we talk about solving the Alexa challenge they like surprise what's the data set of really engaging pleasant conversations look like is if we think of this as a supervised learning problem I don't know if it has to be but if it does maybe you can comment on that do you think there needs to be a data set of what it means to be an engaging successful fulfilling copy that's part of the research question here this was I think it's we at least got the first part right which is have a way for universities to build and test in a real-world setting now you're asking in terms of the next phase of questions which we are still we're also asking by the way what does success look like from a optimization function that's what you're asking in terms of we as researchers are used to having a great corpus of annotated data and then making a Rob then you know sort of tune our algorithms on those right and fortunately and unfortunately in this world of a lexer prize that is not the way we are going after it so you have to focus more on learning based on live feedback that is another element that's unique we're just not I started with giving you how you ingress and experience this capability as a customer what happens when you're done so they ask you a simple question on a scale of one to five how likely are you to interact with this social bot again that is a good feedback and customers can also leave more open-ended feedback and I think partly that to me is one part of the question you're asking which I'm saying is a mental model shift that as researchers also you have to change your mindset that this is not a dart by evaluation or NSF funded study and you have a nice corpus this is where it's real world you have real data the scale is amazing is this beautiful thing then and then the customer the user can quit the conversation in exactly the user game that is also a signal for how good you were at that point so and then on a scale of one to five one two three do they say how likely are you or is it just a binary Allah one two five one two five Wow okay that's such a beautifully constructed challenge okay you said the only way to make a smart assistant really smart to give it eyes and let explore the world I'm not sure he might been taken out of context but can you a comment and I can you elaborate and that idea is that I personally also find that ideas super exciting from a social robotics personal robotics perspective yeah a lot of things do get taken out of context my this particular one was just as philosophically discussion we were having on terms of what does intelligence look like and the context was in terms of learning I think just we said we as humans are empowered with many different sensory abilities I do believe that eyes are an important aspect of it in terms of if you think about how we as humans learn it is quite complex and it's also not unimodal that you are fed a ton of text or audio and you just learn that way no you are you learn by experience you learn by seeing you're taught by humans and we're very efficient and how we learn machines on the contrary are very inefficient on how they learn especially these AI is I think the next wave of research is going to be with less data not just less human not just with less label data but also with a lot of week supervision and where you can increase the learning rate I don't mean less data in terms of not having a lot of data to learn from that we are generating so much data but it is more about from a aspect of how fast can you learn so improving the quality of the data that's the quality data and learning process I think more on the learning process I think we have to we as humans learn with a lot of noisy data right and and I think that's the part that I don't think should change what should change is how we learn right so if you look at you mentioned supervised learning we have making transformative shifts from moving to more unsupervised more week supervision those are the key aspects of how to learn and I think in that setting you I hope you agree with me that having other senses is very crucial in terms of how you learn so absolutely and from a machine learning perspective which I hope we get a chance to talk to a few aspects that are fascinating there but just stick on the point a sort of a body you know an embodiment so Alexa has a body is a very minimalistic beautiful interface or there's a ring and so on I mean I'm not sure of all the flavors of the devices that Alyssa lives on but there's a minimalistic basic interface and nevertheless we humans so I have a Roomba of all kinds of robots and all over everywhere so what do you think the Alexa the future looks like if it begins to shift what his body looks like what uh what may be beyond the Alexa what do you think are the different devices in the home as they start to embody their intelligence more and more what do you think that looks like philosophically a future what do you think that looks I think let's look at what's happening today you mentioned I think all our devices as an Amazon devices we also wanted to point out Alexa is already integrated a lot of third-party devices which also come in lots of forms and shapes some in robots right some and microwaves some in appliances of that you use in everyday life so I think it is it's not just the shape Alexa takes in terms of form factors but it's also where all it's available it's getting in cars it's getting in different appliances in homes even toothbrushes right so I think you have to think about it is not a physical assistant it will be in some embodiment as you said we already have these nice devices but I think it's also important to think of it it is a virtual assistant it does superhuman in the sense that it is in multiple places at the same time so I think the the actual embodiment in some sense to me doesn't matter I think you have to think of it as not as human-like and more of what its capabilities are that derive a lot of benefit for customers and how there are different ways to delighted and delight customers and different experiences and I think I am a big fan of it not being in just human like it should be human-like in certain situations Alexa Frye social bot in terms of conversation is a great way to look at it but there are other scenarios where human like I think is underselling the abilities of this AI so if I could trivialize what we're talking about so if you look at the way Steve Jobs thought about the interaction with the device that Apple produced there was a extreme focus on controlling the experience by making sure there's only the Apple produced devices you see the voice of Alexa being taking all kinds of forms depending on what the customers want and that means that means it could be anywhere from the microwave to a vacuum cleaner to the home and so on the voice is the essential elrom to the interaction I think voice is an essence it's not all but it's a key aspect I think to your question in terms of you should be able to recognize Alexa and that's a huge problem I think in terms of a huge scientific problem I should say like what are the traits what makes it look like Alexa especially in different settings and especially if it's primarily voice what it is but LX is not just voice either right I mean we have devices with a screen now you're seeing just other behaviors of Alexa so I think they're in very early stages of what that means and this will be an important profit for the following years but I do believe that being able to recognize and tell when it's Alexa versus it's not as going to be important from an Alexa perspective I'm not speaking for the entire AI Thank You Marie but from but I think attribution and as we go into more of understanding who did what that identity of the AI is crucial in the coming world I think from the broad AI community perspective that's also a fascinating problem so basically if I close my eyes and listen to the voice what would it take for me to recognize that this is Alexa exactly or at least the Alexa that I've come to known from my personal experience in my home through my interactions that Korea and the Alexa here in the u.s. is very different the Alexa and UK and Alexa India even though they are all speaking English or the Australian version so again we're so now think about when you go into a different culture different community but you travel there what do you recognize Alexa I think these are super hard questions actually so there's a Tina works on personality so if we talk about those different flavours or what it means culturally speaking India UK u.s. what does it mean to add so the problem that we just stated which is fascinating how do we make it purely recognizable that it's Alexa assuming that the qualities of the voice are not sufficient it it's also the content of what is being said how do how do we do that how does the personality kind of come into play what's what's that researching would look like it's such a fascinating we have some very fascinating folks who from both the UX background and human factors are looking at these aspects and these exact questions but I'll definitely say it's not just how it sounds the choice of words the tone not just I mean the voice identity of it but the tone matters the speed matters how you speak how you enunciate words how what choice of words are using how tours are you or how lending in your explanations you are all of these are factors and you also you mentioned something crucial that it's may have you may have personalized it Alexa to some extent in your homes or in the devices you are interacting with so you as your individual how you prefer Alexa sounds can be different than how I prefer and we may and the amount of customizability you want to give is also a key debate we always have but I do want to point out it's more than the voice actor that recorded and you'd sounds like that actor it is more about the choices of words the attributes of tonality the volume in terms of how you raise your pitch and so forth all of that matters this is a fascinating problem from a product perspective I could see those debates just happening inside of the Alexa team of how much personalization do you do for the specific customer because you're taking a risk if you over personalized because you don't I if you create a personality for a million people you can test that better you can create a rich fulfilling experience that will do well but if the more you personalize it the less you can test it the less you can know that it's it's a great experience so how much personalization what's the right balance I think the right balance depends on the customer give them the control so I'd say I think the more control you give customers the better it is for everyone and I'll give you some key personalization features I think we have a feature called remember this which is where you can tell Alexa to remember something there you have an explicit sort of control in customers hand because they have to say like I remember XYZ what kind of things would that be used for so you can respond or something I have stored my tire specs for my car nice because it's so hard to go and find and see what it is right when you're having some issues I store my mileage plan numbers for all the frequent-flyer ones where sometimes just looking at it and it's not handy so and so those are my own personal choices army for Alexa to remember something on my behalf right so again I think the choice was be explicit about how you provide that to a customer as a control so I think these are the aspects of what you do like think about where we can use speaker recognition capabilities that it's if you taught Alexa that you are Lex and this person you're householders person to then you can personalize the experiences again these are very in this and the CX customer experience patterns are very clear about and transparent when a personalization action is happening and then you have other ways like you go through explicit control right now through your app that your multiple service providers let's say for music which one is your preferred one so when you say place ting depend on your whether you have preferred Spotify or Amazon music or Apple music that the decision is made where to play it from so what's Alexis backstory from her perspective this is there I remember just asking as probably a lot of us are just the basic questions about love and so on of Alexa just to see what the answer would be just as a it feels like there's a little bit of a back like there's a feels like there's a little bit of personality but not too much is Alexa have a metaphysical presence in this human universe we live in or is it something more ambiguous is there a past is there birth is there family kind of idea even for joking purposes and so on I think well it does tell you if I think you should double-check this but if you said when were you born I think we do respond I need to double check that but I'm pretty positive about it I think you do it because I think I've too soon but that's like that's like hell like I was born in your brand of champagne and whatever the year good thing yeah so in terms of the metaphysical I think it's early does it have the historic knowledge about herself to be able to do that maybe have we crossed that boundary not yet right in terms of being thank you have you thought about it quite a bit but I wouldn't say that we have come to a clear decision in terms of what it should look like but you can imagine though and I bring this back to the Alexa prize social BOTS one there you will start seeing some of that like you these bots have their identity and in terms of that you may find you know this is such a great research topic that some academia team may think of these problems and start solving them - so let me ask a question it's kind of difficult I think but it feels fascinating to me because I'm fascinated with psychology it feels that the more personality you have the more dangerous it is in terms of a customer perspective of products if you want to create a product that's useful by dangerous I mean creating an experience that upsets me and so what how do you get that right because if you look at the relationships maybe I'm just a screwed-up Russian but if you look at the real human to human relationship some of our deepest relationships have fights have tension have the push and pull have a little flavor in them do you want to have such flavor in an interaction with Alexa how do you think about that so there's one other common thing that you didn't say but is we think of it as paramount for any deep relationship that's trust trust yeah so I think if you trust every attribute you said mm-hmm a fight some tension yeah is or healthy but the waters sort of unknowable in this instance is trust and I think the bar to earn customer trust for AI is very high in some sense more than a human it's it's not just about personal information or your data it's also about your actions on a daily basis how trustworthy are you in terms of consistency in terms of how accurate are you in understanding me like if if you're talking to a person on the phone if you have a problem with your let's say your internet or something if the person is not understanding you lose trust right away you don't want to talk to that person that whole example gets amplified by a factor of 10 because as when you're a human interacting with an AI you have a certain expectation either you expect it to be very intelligent and then you get upset why is it behaving this way more you expect it to be not so intelligent and when it surprises you're like really you're trying to be too small so I think we grapple with these hard questions as well but I think the key is actions need to be trustworthy from these a is not just about data protection your personal information protection but also from how accurate it accomplishes all commands are all interactions well it's tough to hear because Trust you're absolutely right but Trust is such a high bar with AI systems because people and I see this because I work with autonomous vehicles I mean the bar this placed on AI system is unreasonably high yeah that is going to be as I agree with you and I think of it is it's it's a challenge and it's also keeps my job so from that perspective that I totally I think of it at both sides as a customer and as a researcher I think as a researcher yes occasionally it will frustrate me that why is the bar so high for these AIS and as a customer then I say absolutely it has to be that high right so I think that's the trade-off we have to balance but doesn't change the fundamentals that trust has to be own and the question then becomes is are we holding the AIS to a different bar and accuracy and mistakes then we hold humans that's going to be a great societal questions for years to come I think for us well one of the questions that we grapple as a society now that I think about a lot I think a lot of people know I think about a lot and Alexis taking on head-on is privacy is the reality is us giving over data to any AI system can be used to enrich our lives in in in profound ways so if maybe basically any product that does anything awesome for you would the more data has the more awesome things it can do and yet at the other side people imagine the worst case possible scenario of what can you possibly do with that data people it's it goes down to trust as you said for there's a fundamental distrust of in certain groups of governments and so on and depending on the government depending on who is in power depending on all these kinds of factors and so here's the lux in the middle of all of it in the home trying to do good things for the customers so how do you think about privacy in this context the smart assistants in the home how do you maintain how do you earn trust absolutely so as you said Trust is the key here so you start with trust and then privacy is a key aspect of it it has to be designed from very beginning about that and we believe in two fundamental principles one is transparency and second is control so if by transparency I mean when we build what is now called smart speaker or the first echo we were quite judicious about making these right trade-offs on customers behalf that it is pretty clear when when the audio is being sent the cloud the light ring comes on when it has heard you say the word wake word and then the streaming happens right so and the light ring comes up we also had we put a physical mute button on it just so you're if you didn't want it to be listening even for the weak word then you turn the power button on the mute button on and that disables the microphones that's just the first decision on essentially transparency and control over then even when we launched we gave the control in the hands of the customers that you can go and look at any of your individual utterances that is recorded and delete them anytime and we have cut to true to that promise right so and that is super again a great instance of showing how you have the control then we made it even easier you can say lecture delete what I said today so that is now making it even just just more control in your hands with what's most convenient about this technology is voice you delete it with your voice now so these are the types of decisions we continually make we just recently launched this feature called what we think of it as if you wanted humans not to review your data because smile you mentioned supervised so you in supervised learning humans have to give some annotation and that also is now a feature where you can essentially if you selected that flag your data will not be reviewed by a human so these are the types of controls that we have to constantly offer with customers so why do you think about as people so much that so that so everything you just said is really powerful to the control the ability to leak because we collect we have studies here running at MIT that collects huge amounts of data and people consent and so on the ability to delete that data is really empowering and almost nobody ever asked to delete it but the ability to have that control is really powerful but still you know there's these popular anecdotes anecdotal evidence that people say they like to tell that them and a friend were talking about something I don't know sweaters for cats and all sudden they'll have advertisements for cat sweaters on Amazon there's that that's a popular anecdote as if something is always listening what can you explain that anecdote that experience that people have what's the psychology of that what's that experience and can you you've answered it but let me just ask is Alexa listening no Alexa listens only for the wake word on the device right and awake word is the words like Alexa Amazon echo and you but do you only choose one at a time so you choose one and it listens only for that on our devices so that's first from a listening perspective we have to be very clear that it's just the wake word so you said why is there this anxiety if you make yeah it's because there's a lot of confusion what it really listens to right and you and I think it's partly on us to keep educating our customers and the general media more in terms of like how what really happens and we've done a lot of it and with our pages on information are clear but still people have to have more there's always a hunger for information and clarity and will constantly look at how best to communicate if you go back and read everything yes it states exactly that and then people could still question it and I think that's absolutely okay to question what we have to make sure is that we are because our fundamental philosophy is customer first customer obsession is our leadership principle if you put as researchers I put myself in the shoes of the customer and all decisions in Amazon are made with that and I throw and Trust has to be earned and we have to keep earning the trust of our customers in this setting and to your other point on like is there something showing up based on your conversations no I think the answer is like you a lot of times when those experiences happen you have to also be know that okay maybe a winter season people are looking for sweaters right and it shows up on your amazon.com because it is popular so there are many of these you mentioned that personality or personalization turns out we are not that unique either right so those things we we as humans start thinking oh must be because something was heard and that's why this other thing showed up the answer is no probably it is just the season for sweaters I'm not gonna ask you this question because it's just cuz your doll so because people have so much paranoia but for Milan as you say from my perspective I hope there's a day when customer can ask Alexa to listen all the time to improve the experience to improve because I personally don't see the negative because if you have the control and if you have the trust there's no reason why I shouldn't be listening all the time to the conversations to learn more about you because ultimately as long as you have control and Trust every data you provide to the device that the device wants is going to be useful and that's it to me I as a machine learning person I think it worries me how sensitive people are about their data relative to how empowering it could be for the devices around them how enriching it could be for their own life to improve the product so I just it's something I think about sort of a lot how do we make that devices obviously Lux that thinks about it a lot as well I don't know if you want to comment on that sort of okay have you seen them in the form of a question okay I have have you seen an evolution in the way people think about their private data in the previous several years so as we as a society a more more comfortable to the benefits we get by sharing more data first let me answer that part and then I'll want to go back to the other aspect you were mentioning so as a society on a general we are getting more comfortable as a society doesn't mean that everyone is and I think we have to respect that I don't think one-size-fits-all is always gonna be the answer for all right by definition so I think that's is something to keep in mind in these going back to your on what more magical experiences can be launched in these kind of AI settings I think again if you give the control we it's possible certain parts of it so if you have a feature called follow-up mode where you if you turn it on and Alexa after you've spoken to it will open the mics again thinking you lanced something again yeah like if you're adding lists to your shopping items so right or a shopping list or to-do list you're not done you want to keep so in that setting it's awesome that it opens the mic for you to say eggs and milk and then bread right so these are the kind of things which you can empower so I and then another feature we have which is called Alexa guard I said it only listens for the wake word all right but if you have a let's say you're going to say Lex you leave your home and you want a lexer to listen for a couple of sound events like smoke alarm going off or someone breaking your glass right so it's like just to keep your peace of mind so you can say Alexa on guard or I'm away or and then it can be listening for these sound events and when you're home it you come out of that mode right so this is another one where you again gave controls in the hands of the user or the custom and to enable some experience that is you higher utility and maybe even more delightful in the certain settings like follow up more and so forth again this general principle is the same control in the hands of the Castro so I know we kind of started with a lot of philosophy and a lot of interesting topics and we'll just jumping all over the place but really some of the fascinating things at the alexa team and Amazon's doings in the the algorithm side the data side the technology at the deep learning machine learning and and so on so can you give a brief history of Alexa from the perspective of just innovation the algorithms the data of how I was born how it came to be how is grown where it is today yeah start with in Amazon everything starts with the customer and we have a process called working backwards Alexa and more specifically then the product echo there was a working backwards document essentially that reflected what it would be started with a very simple vision statement for instance that morphed into a full-fledged document along the way changed into what all it can do right you can but the inspiration was the Star Trek computer so when you think of it that way you know everything is possible but when you launch a product you have to start with someplace and when I joined we the product was already in conception and we started working on the far field speech recognition because that was the first thing to solve by that we mean that you should be able to speak to the device from a distance and in those days that wasn't a common practice and even in the previous research world I was in was considered to an unsolvable problem then in terms of whether you can converse from a length and here I'm still talking about the first part of the problem where you say get the attention of the device as in by saying what we call the wake word which means the word Alexa has to be detected with a very high accuracy because it is a very common word it has sound units that map with words like I like you or Alec Alex right so it's a undoubtably hard problem to detect the right mentions of Alexa's address to the device versus I like Alexa you have to pick up that signal when there's a lot of noise not only noise north conversation they are in the house while you remember on the device you are simply listening for the wake word Alexa and there's a lot of words being spoken in the house how do you know it's Alexa and directed at Alexa because I could say I love my Alexa I hate my Alex I want a lecture to do this and in all these three sentences I said Alexa I didn't want it to wake up yeah so can I just pause on a second what would be your device that I should probably in the introduction of this conversation give to people in terms of with them turning off their Lutz a device if they're listening to this podcast conversation out loud like what's the probability that an Alexa device will go off because we mention Alexa like a million times so it will we have done a lot of different things where we can figure out that there is the device the speech is coming from a human versus over there also I mean in terms of like also it is think about ads or so we have also launched a technology for watermarking kind of approaches in terms of filtering it out but yes if this kind of a podcast is happening it's possible your device will wake up a few times it's an unsolved problem but it is definitely something we care very much about but the idea is you wanna detect Alex were meant for the device or just even hearing Alexa versus I like yeah something I mean that's the fascinating part so that was the first relief that's the first of the world's best detector of course yeah the FIR world's best wait word detector yeah in the far field setting not like something where the phone is sitting on the table this is like people have devices 40 feet away like in my house or 20 feet away and you still get an answer so that was the first part the next is you're speaking to the device of course you're gonna issue many different requests some may be simple some may be extremely hard but it's a large vocabulary speech recognition problem essentially where the audio is now not coming on to your phone or a handheld mic like this or close talking my but it's from 20 feet away where if you're in a busy household your son may be listening to music your daughter may be running around with something and asking your mom something and so forth right so this is like a common household setting where the words you're speaking to Alexa need to be recognized with very high accuracy yes right now we are still just in the recognition problem you haven't yet come to the understanding one writes in if a possum so I once again what year was this is this before neural networks began to start to seriously prove themselves in audio space yeah this is around so I joined in 2013 in April right so the early research in neural networks coming back and showing some promising results in speech recognition space had started happening but it was very early yeah but we just took now build on that on the very first thing we did when when I join and we with the team and remember it was a very smudge of a start-up environment which is great about Amazon and we double down on deep learning right away and we we knew will have to improve accuracy fast and because of that we worked on and the scale of data once you have a device like this if it is successful will improve big time like you'll suddenly have large volumes of data to learn from to make the customer experience better so how do you scale deep learning so we did are one of the first works in in training with distributed GPUs and where the training time was you know was linear in terms of like in the amount of data so that was quite important work where it was algorithmic improvements as well as a lot of engineering improvements to be able to train on thousands and thousand of speech and that was an important factor so the if you ask me like back in 2013 and 2014 when we launched echo the combination of large scale data deep learning progress near infinite GPX we had available on AWS even then was all came together for us to be able to solve the far field speech recognition to the extent it could be useful to the customers it still not solved like I mean it's not that we are perfect at recognizing speech but we are great at it in terms of the settings that are in homes right so and that was important even in the early stages the first even I'm trying to look back at that time if I remember correctly that it was it seems like the task will be pretty daunting so like so we kind of take it for granted that it works now yes right so let me like how first time you mentioned startup I wasn't familiar how big the team was I kind of because I know there's a lot of really smart people working on looks and I was very very large team how big was the team how likely were you to fail in the highs of everyone else like what I'll give you a very interesting anecdote on that when I joined the team the speech recognition team was six people my first meeting and we had hired a few more people it was 10 people 9 out of 10 people thought it can't be done who was the one the one was me and actually I should say and one was say my optimistic yeah and and 8th we're trying to convince let's go to the management and say let's not work on this problem let's work on some other problem like either telephony speech for customer service calls and so forth but this was the kind of belief you must have and I had experience with far-field speech recognition and I my eyes lit up and I saw a problem like that saying okay we have been in speech recognition always looking for that killer app and this was a killer use case to bring something delightful in the hands of customers you mentioned you the way kind of think of the product way in the future have a press release and an FAQ and you think backwards that's did you have that the team have the echo and mind so this far-field speech recognition actually putting a thing in the home that works it's able to interact with was that the press release what was the way close I would say in terms of the as I said the vision was started computer right or the inspiration and from there I can't divulge all the exact specifications but one of the first things that was magical on a lexer was music it brought me to back to music because my taste was still and when I was an undergrad right so I still listen to those songs and I it was too hard for me to be a music fan with a phone right so I and I don't I hate things in my ears so from that perspective it was quite hard and and and music was part of the at least the documents I have seen right so so from that perspective I think yes in terms of our how far are we from the original vision I can't reveal that words that's why I have done a fun at work because every day we go in and thinking like these are the new set of challenges to solve yeah that's a great way to do great engineering is you think of the product press release I like that idea maybe we'll talk about it a bit later was just a super nice way to have focused I'll tell you this you're a scientist and a lot of my scientists have adopted that they they have now they love it as a process because it was very a scientist you're trained to write great papers but they are all after you've done the research or you're proven lie and your PhD dissertation proposal is something that comes closest or a DARPA proposal or NSF proposal is the closest that comes to a press release but that process is now ingrained in our scientists which is like delightful for me to see you write the paper first then make it happen that's right in fact that's not state-of-the-art results or you leave the results section open well you have a thesis about here's what I expect right and here's what it will change Yeah right so I think it is a great thing it works for researchers as well they're so far field recognition yeah what was the big leap what what were the breakthroughs and yeah what was that journey liked it today yeah I think the as you said first there was a lot of skepticism on whether far-field speech recognition will ever work to be good enough right and what we first did was got a lot of training data in a far field setting and that was extremely hard to get because none of it existed so how do you collect data in far field set up right with no customer bases there's no customer base right so that was first innovation and once we had that the next thing was ok you if you have the data first of all we didn't talk about like what would magical mean in this kind of a setting what is good enough for customers right that's always since you've never done this before what would be magical so so it wasn't just a research problem you had to put some in terms of accuracy and customer experience features some stakes on the ground saying here is where I think should it should get to so you established a bar and then how do you measure progress toward is given you have no customer right now so from that perspective we went so first was the data without customers second was doubling down on deep learning as a way to learn and I can just tell you that the combination of the two cut our error rates by a factor of five from where we were when I started to within six months of having that data we at that point and I got the conviction that this will work right so because that was magical in terms of when it started working and that reached them who came close to the magical bar back to the bar right that we felt would be where people will use it that was critical because you you really have one chance at this if we had launched in November 2014 years when we launched and if it was below the bar I don't think this category exists if you don't need the bar yeah and just having looked at voice-based interactions like in the car or earlier systems it's a source of huge frustration for people in fact we use voice based interaction for collecting data on subjects to measure frustration so as a training set for computer vision for face data so we can get a data set of frustrated people that's the best way to get frustrated people is having them interact with a voice based system in the car so this is that bar I imagine it's pretty high it was very high and we talked about how also errors are perceived from a eyes versus errors by humans but we are not done with the problems that ended up we had to solve to get it to launch so do you want the next one so the next one was what I think of as multi-domain natural language understanding it's very I wouldn't say easy but it is during those days solving it understanding in one domain and narrow domain was doable but for these multiple domains like music like information other kinds of household productivity alarms time errors even though it wasn't as big as it is in terms of the number of skills alexa has and the confusion space has like grown by three orders of magnitude it was still daunting even those days and again no customer base here again no customer base so now you're looking at meaning understanding and intent understanding and taking actions on behalf of customers based on their request and that is the next hard problem even if you have gotten the words recognized how do you make sense of them in those days there was still a lot of emphasis on rule-based systems for writing grammar patterns to understand the intent but we had a statistical first approach even then where for a language understanding we had in even those starting days and an entity recognizer and an intent classifier which was all trained statistically in fact we had to build the deterministic matching as follow-up to fix bugs that statistical models have right so it was just a different mindset where we focused on data-driven statistical understanding wins in the end if you have a huge dataset yes it is contingent on that and that's why it came back to how do you get the data before customers the fact that this is why data becomes crucial to get a to the point that you have the understanding system built in build up and notice that for here we were talking about human machine dialogue even those early days even it was very much transactional do one thing one shot a transition great way there was a lot of debate on how much should Alex our talk back in terms of if you misunderstood you or you said play songs by the stones and let's say it doesn't know you know early days knowledge can be sparse who were the stones right I the Rolling Stones right so our and you don't want them match to be Stone Temple Pilots or Rolling Stones right so you don't know which one it is so these kind of other signals to know there we had great assets right from Amazon in terms of you acts like what is it what kind of yeah hurry solve that problem in terms of what we think of it as an entity resolution problem right so is one is it right I mean the even if you figured out the stones is an entity you have to resolve it to whether it's the stones or the temple violence or some other stones maybe I misunderstood is the resolution the job of the algorithm or is the job of UX communicating with the human to help there as well there is both right it is law you want 90 percent or high 90s to be done without any further questioning or UX right so but that it's absolutely okay just like as humans we asked the question I didn't understand your likes yeah it's fine for a lecture to occasionally say I did not understand you right and and that's a important way to learn and I'll talk about where we have come with more self learning with these kind of feedback signals but in those days just solving the ability of understanding the intent and resolving to an action where action could be play a particular artist or a particular song was super hot again - the bar was high as as you're talking about right so while we launched it in sort of 13 big domains I would say in terms of or thing we think of it as 13 the big skills we had like music is a massive one when we launched it and now we have 90,000 plus skills on Alexa so what are the big skills can you just go is the only thing I use it for is music weather and shopping haha so we think of it as music information right so it's all whether it's a part of information right so then we launched we didn't have smart home but within spikes bottom I mean you connect your smart devices you control them with watch if you haven't done it it's worth it will change your signing on the lights yeah you like to do anything that's connected and has a it's just what your favorite smart device for you and now you've the smart plug with and you don't we also have this echo plug which is oh yeah and now you can turn on that one on and off this conversation motivation in Kevin's garage door you can check your status of the garage door and things like and we have gone may collect some more and more proactive where it even have a hunt has on chores now that all those hunches like you left your light on or let's say you've gone to your bed and you left the garage light on so yeah it will help you out in these settings right so that smart devices right information smart devices said music yeah so I don't remember everything we had big ones like that was you know the timers were very popular right away music also like you could play song artist album everything and so that was like a clear win in terms of the customer experience so that's again this is language understanding now things have evolved right so where we want a lecture definitely to be more accurate competent and trustworthy based on how well it does these core things but we have in many different dimensions first is what I think of her doing more conversational for high-utility not just for chat right and there we a tree Mars this year which is our AI conference we launched what is called Alexa conversations that is providing the ability for developers to author multi-tone experiences on Alexa with no code essentially in terms of the code dialogue code initially it was like you know all these IVR systems you have to fully author if the customer says this do that right so the whole dialogue flow is hand author and with Alexa conversations the way it is that you just provide a sample interaction data with your service or an API let's say you're Adam take its that provides a service for buying movie tickets you provide a few examples of how your customers will interact with your api's and then the dialogue flow is automatically constructed using a recurrent neural network a train on that beta so that simplifies the developer experience we just launched our preview for the developers to try this capability out and then the second part of it which shows even increased utility for customers is you and I when we interact with Alexa or any customer as I coming back to our initial part of the conversation the goal is often unclear or unknown to the AI if I say Alexa what movies are playing nearby am i trying to just buy movie tickets am I actually even do you think I'm looking for just movies for curiosity whether the Avengers are still in theater or when it's maybe it's gone and maybe it will come on my mr. so I may watch it on prime which happened to me so so from that perspective now you're looking into what is my goal and let's say I now complete the movie ticket purchase maybe I would like to get dinner nearby so what is really the goal here is it night out or is it movies as and just go watch a movie here the answer is we don't know so can Alexa now figure we have the intelligence that I think this metal goal is really night or at least say to the customer when you have completed the purchase of movie tickets from Adam tickets or Fandango or picture anyone then the next thing is do you want to get to get an uber to the theater right or do you want to book a restaurant next to it and and then not ask the same information over and over again what time what how many people in your party right so so this is where you shift the cognitive burden from the customer to the AI where it's thinking the of what is your it anticipates your goal and takes the next best action to complete it now that's the machine learning problem but essentially you're the way we solve this first instance and we have a long way to go to make it scale to everything possible in the world but at least for this situation it is from at every instance Alexa is making the determination whether it should stick with the experience with Adam tickets or offer or you based on what you say whether either you have completed the interaction or you said no get me an uber now so it will shift context into another experience or skill on another service so that's a dynamic decision-making that's making Alexa you can say more conversational for the benefit of the customer rather than simply complete transactions which are well thought through if you as a customer has fully specified what you want to be accomplished its accomplishing that so it's kind of as I would do this with pedestrians like intent modeling is predicting what your possible goals are most likely going and switching that depending on the things you say so my question is there it seems maybe it's a dumb question but it would help a lot of elects remembered me what I said previously right it is it's trying to use some memory for the custom year it is using a lot of memory within that so right now not so much in terms of okay which restaurant do you prefer right that is a more long-term memory but within the short-term memory within the session it is remembering how many people did you so if you said buy four tickets not has made an implicit assumption that you were gonna have you need for at least four seats at a restaurant right so these are the kind of context its preserving between these skills but within that session what are you asking the right question in terms of for it to be more and more useful it has to have more long-term memory and that's also an open question and again this is still early days so for me I mean everybody is different but yeah I'm definitely not representative of the general population the sense that I do the same thing every day like I eat the same that I do everything the same the same thing we're the same thing clearly this or the black shirt so it's frustrating when it looks it doesn't get what I'm saying because I had to correct her every time the exact same way this has to do with certain songs like she doesn't know certain weird songs only and doesn't know I've complained to Spotify about this talked to the Rd head of our idea Spotify stairway to heaven I have to correct it every time it really doesn't play Led Zeppelin correctly so I should figure you should send me or next time it fails the seat for you to send it to me we'll take care of it okay well let's Apple it is one of my favorite it works for me so I'm like shocked it doesn't work for you this is an official public port I'll put it I'll make it public retweet it we're gonna fix this there would have impairment anyway but the point is you know I'm pretty boring and do the same thing but I'm sure most people do the same set of things do you see Alexa sort of utilizing that in the future for improving the experience yes and not only utilizing it's already doing some of it we call it where Alexa is becoming more self learning so Alexa is now auto correcting millions and millions of car trances in US without any human supervision the way desert is let's take an example of a particular song didn't work for you what do you do next you either it played the wrong song and you said Alexa no that's not the song I want or you say likes a play that you try it again and that is a signal to Alexa that she may have done something wrong and from that perspective we can learn if there's that failure pattern or that action of song a was played when song B was requested yes it's very common with station names because play NPR you can have n be confused as an M and then you for a certain accent like mine people confuse my n and M all the time and because I will Indian accent there confusable to humans it is for Alexa too and in that part but it starts auto correcting and we collect we correct a lot of these automatically without a human looking at the failures so the one of the things that's for me missing in Alessa I don't know from a representative customer but every time I correct it it would be nice to know that that made a difference yes you know I mean like that yeah sort of like I I heard you like some acknowledgement of that we worked a lot with with Tesla study the autopilot and so on and a large amount of the customers they used Tesla autopilot they feel like they're always teaching the system uh-huh they're almost excited by the possibility teaching I don't know if Alexa customers generally think of it as they're teaching to improve the system I think and that's a really powerful thing against I would say it's a spectrum some customers do think that way and some would be annoyed by Alexa acknowledging that or so there's a again no one you know while there are certain patterns not everyone is the same in this way but we believe that again customers helping Alexa is a tenet for us in terms of improving it dancing more self learning is by again this is like fully unsupervised right there is no you in the loop and no labeling happening and based on your actions as a customer Alexa becomes smarter again it's early days but I think this whole area of teachable AI is gonna get bigger and bigger in the whole space especially in the AI assistant space so that's the second part where I mentioned more conversational this is more self learning the third is more natural and the way I think of more natural is we talked about how Alexa sounds and there are and we have done lot of advances in our text to speech by using again neural network technology for it to sound very human like an individual texture the sound to the the the timing the tonality tone of everything I would think in terms of there's a lot of controls in each of the places for how I mean the speed of the voice the prosthetic patterns the the actual smoothness of how it sounds all of those are factored and we do ton of listening tests to make sure is that what naturalness how it sounds should be very natural how it understands requests is also very important like and in terms of like we have 95,000 skills or and if we have imagined that and many of these skills you have to remember the skin Ling and say Alexa asked they're tied skill to tell me X right or now if you have to remove the skill name that means the discovery and the interaction is unnatural and we're trying to solve that by what we think of as again this was you don't have to have the app metaphor here these are not individual apps right even though they're so you cut you're not sort of opening one at a time and interacting so yeah it should be seamless because it's voice and when it's voice you have to be able to understand these requests independent of the specificity like a scale name and to do that what we have done is again built a deep learning based capability where we shot list a bunch of skills when you say Alexa get me a car and then we figure it out okay it may it's meant for a nubile skill versus a left or they on your preferences and then you can rank the responses from the scale and then choose the best response for the customer so that's on the more natural other examples of more natural is like we were talking about lists for instance and you wanna you don't want to say Alexa add milk likes to add eggs Alexa hired cookies you know Alexa add cookies milk and eggs and that in one shot right so that works that helps with the naturalness we talked about memory like if you said you can say like so remember I have to go to Mom's house or you may have entered a calendar event through your calendar that's linked or like so you don't remember whether it's in my calendar or did I tell you how to remember something or some other reminder right so you have to now independent of how customers create these events it should just say Alexa when do I have to go to Mom's house and it tells you when you have to go to Mom's house that's the fascinating problem who's that problem on so the these people create skills uh-huh who's who's tasked with integrating all of that knowledge together so if the skills becomes seamless is it the creators of the skills sewer system the infrastructure that Alexa provides problem it's both I think the large problem in terms of making sure your skill quality is high we that has to be done by our tools because it's just so these skills just to put the context they are built through Alexa skill scale which is a self-serve way of building an experience on Alexa this is like any developer in the world could go to Alexa scale skate and build an experience on Alex like if you're a dominoes you can build a domino skills for instance that does pizza ordering when you've authored that you do want to now if people say like so open Domino's or Alexa ask dominoes dominoes to get a particular type of pizza that will work but the discovery is harder you can't just say like so get me a pizza and then Alexa figures out what to do that latter part is definitely our responsibility in terms of when the request is not Feliz how do you figure out what's the best skill or a service that can fulfill the customer's request and it can keep evolving imagine going to the situation I said which was the night out planning that it the goal could be more than that individual request that came a Pizza ordering could mean a night in event with your kids in the house and your so this is welcome to the world of conversational yeah this is this is super exciting because it's not the academic problem of NLP of natural language processing understanding dialogue this is like real world the stakes are high in a sense that customers get frustrated quickly people get frustrated quickly so you have to get it right if to get that interaction right so it's I love it but so from that perspective what what are the challenges today what what are the problems that really need to be solved and yes here's I think first and foremost as I mentioned that get the basics right are still true basically even the one-shot requests which we think of as transactional requests needs to work magically no question about that lee if it doesn't turn your light on and off you'll be super frustrated even if I can complete the night out for you and not do that that is unacceptable for as a customer right so that you have to get the foundational understanding going very well the second aspect when I said more conversational is as you imagine is more about reasoning it is really about figuring out what the latent goal is of the customer based on what I have the information now and the history and what's the next best thing to do so that's a complete reasoning and decision-making problem just like your self-driving car but the goal is still more finite here it Evos your environment is super hard and self-driving and the cost of a mistake is huge here but there are certain similarities but if you think about how many decisions Alexa is making or evaluating at any given time it's a huge hypothesis space and we're only talked about so far about what I think of reactive to in terms of you asked for something and Alexis reacting to it if you bring the proactive part which is Alexa having hunches so any given instance then your it's really a decision at any given point based on the information Alexa has to determine what's the best thing it needs to do so these are the ultimate AI problem well decisions based on the information you have do you think my prospectus a lot I work a lot with sensing of the human face do you think they'll and we touch this topic a little bit earlier but do you think it'll be a day soon when Alexa can also look at you to help improve the quality of the hunch it has or at least detect frustration or detects you know improve the quality of its perception of what you what you're trying to do I mean let me again bring back to what it already does we talked about how based on you bargain over Alexa clearly it's a very high probability it must have done something wrong that's why you understand the next extension of whether frustration is a signal or not of course is a natural thought in terms of how that should be in a signal to egg you can get that from voice you can get from voice but it's very hard like I mean a frustration as a signal historically if you think about emotions of different kinds you know there's a whole field of affective computing something that MIT has also done a lot of research and is super hot and you are now talking about a far field device as in you're talking to a distance noisy environment and in that environment it needs to have a good sense for your emotions this is a very very hard problem very hard problem but you haven't shadow voice from hard problems well you know so deep learning has been at the core of a lot of this technology are you optimistic about the current deep learning approaches to solving the hardest aspects of what we're talking about or do you think there will come a time where new ideas need to for this you know if you look at reasoning so opening eye deep mind a lot of folks are now starting to work in reasoning trying to see how can make neural networks a reason do you see that new approaches need to be invented to take the next big leap absolutely I think there has to be a lot more investment and I think in many different ways and there are these I would say nuggets of research forming in a good way like learning with less data or like zero short learning one-shot learning and the active learning stuff you've talked about is yes incredible since so transfer learning is also super critical especially when you're thinking about applying knowledge from one task to another or one language to another right it's really ripe so these are great pieces deep learning has been useful too and now we are sort of marrying deep learning with with transfer learning an active learning of course that's more straightforward in terms of applying deep learning and an active learning set up but but I do think in terms of now looking into more reasoning based approaches is going to be key for our next wave of the technology but there is a good news the good news is that I think for keeping on to delight customers that a lot of it can be done by prediction tasks yes so and so we haven't exhausted that so we don't need to give up on the deep learning approaches for that so that's just I wanted sort of the query on our rich fulfilling amazing experience that makes Amazon a lot of money and a lot of everybody a lot of money because it does awesome things deep learning is enough the the point the point I don't think I would say deep learning is enough I think for the purposes of Alexa accomplish the task for customers I'm saying there are still a lot of things we can do with prediction based approaches that do not reason right I'm not saying that and we haven't exhausted those but for the kind of high utility experiences that I'm personally passionate about of what Alexa needs to do reasoning has to be solved today to the same extent as you can think of naturally understanding and a speech recognition to the extent of understanding intents has been how accurate it has become but reasoning we are very very early days the nest another way how hard of a problem do you think that is hardest of them I would say hardest of them because again the hypothesis space of is really really large and when you go back in time like you were saying I wanna I want Alexei to remember more things that once you go beyond a session of interaction which is my session I mean a a time span which is today two versus remembering which restaurant I like and then when I'm planning a night out to say do you want to go to the same restaurant now you're up the steaks big time and and this is where the reasoning dimension also goes very very big so you think the space will be elaborating that a little bit just philosophically speaking do you think when you reason about trying to model what the goal of a person is in the context of interacting with Alexa you think that space is huge it's huge absolutely you think so like another a devil's advocate would be that we human beings are really simple and we all want like just a small set of things and they're so do you think you think it's possible cuz we're not talking about a fulfilling general conversation perhaps actually the Alexa prize is a little bit after that creating a customer like there's so many of the interactions it feels like are clustered in groups that are don't require general reasoning I think you're you right in terms of the head of the distribution of all the possible things customers may want to accomplish but the tail is long and it's diverse right so from many many long tails from that perspective I think you have to solve that problem otherwise and everyone's very different like I mean we see this already in terms of the skills right I mean if you if you're an average surfer which I am now right but somebody is asking Alexa about surfing conditions right and there's a skill that is there for them to get to right that tells you that the tail is massive like in terms of like what kind of skills people have created it's humongous in terms of it and which means there are these diverse needs and and when you start looking at the combinations of these right even if your pairs of skills and and 90000 choose two it's still a big concept of combination so I'm saying there's a huge to do here now and I think customers are you know wonderfully frustrated with things and then I'm gonna keep getting to do better things for that so and they're not known to be super patient so you have to do it fast you have to do it fast yeah so you've mentioned the idea of a press release the research and development Amazon Alexa and Amazon in general you kind of think of what the future product will look like and you kind of make it happen you work backwards so can you draft for me you probably have one paquimé makeup on for 10 20 30 40 years out that you see the Alexa team putting out just in broad strokes something that you dream about I think let's start with the five years first okay so and I'll get to the Fortius through in broad strokes this term I think the five year is where I mean I think of in these spaces it's hard especially if you're in thick of things to think beyond the five year space because a lot of things change right I mean if you ask me five years back will Alexa will be here I wouldn't have I think it has surpassed my imagination of that time right so I think then from the next five years perspective from a AI perspective what we're gonna see is that notion which you said goal-oriented dialogues and open domain like Alec surprised I think that bridge is gonna get closed they won't be different and I'll give you why that's the case you mentioned shop how do you shop do you shop in in one shot sure your double-a batteries paper towels yes how much how long does it take for you to buy a camera you do ton of research yeah then you make a decision so is there is that a goal oriented a lot dialogue when I like somebody says Alexa find me a camera is it simply in cue sitive ness right so even in this something that you think of it as shopping which you said you yourself use a lot off if you go beyond where it's reorders or items where you sort of not brand conscious and so forth that was just in shock just to comment quickly I've never bought in you think through Alexa there haven't bought before on Amazon on a desktop after I clicked in a bunch you read a much reviews that kind of stuff so it's repurchase so now you think in even for something that you felt like is is a finite goal I think the space is huge because even products the attributes are many like and you want to look at reviews some on Amazon some outside some you want to look at what Zenit is saying or another consumer forum is saying about even a product for instance right so that's just that's just shopping where you could you could argue the ultimate goal is sort of known and we haven't talked about Alexa what's the weather in Cape Cod this weekend right so why am I asking that weather question right so I think I think of it as how do you complete goals with minimum steps for our customers right and when you think of it that way the distinction between goal-oriented and conversations for open domain say goes away I may want to know what happened in the presidential debate right and is it I'm seeking just information on I'm looking at who's winning winning the debates right so these are all quite hard problems so even the five-year horizon problem I'm like I sure hope we'll solve these new year you're optimistic because that's the hard problem which part the reasoning you know enough to be able to help explore complex goals that are beyond something simplistic that feels like it could be well five years is a nice it's a nice bar form right I think you will it's a like nice ambition and do we have press releases for that absolutely can I tell you what specifically the roadmap will be no right and what and will be solve all of it in the five-year space now this is we will work on this forever actually if we this is the hardest of the eye problems and I don't see if that being solved even in a 40 year horizon because even if you limit to the human intelligence we know we are quite far from that in fact every aspects of our sensing to do neural processing to how brain stores information and how it processes it we don't yet know how to represent knowledge all right so we're and still in those are early stages so I wanted to start that's why at the five-year yeah because the five-year success would look like that and solving these complex goals and the forty year would be where it's just natural to talk to these in terms of more of these complex goals right now we've already come to the point where these transactions you mentioned of asking for weather or reordering something or listening to your favorite tune it's natural for you to actually say it's it's now unnatural to pick up your phone right and that I think is the first five-year transformation the next five your transformation would be okay I can plan my weekend with Alexa or I can plan my next meal with Alexa or my next night out with seamless effort so just to pause and look back at the big picture of it all it's a you're part of a large team that's creating a system that's in the home that's not human that gets to interact with human beings so we human beings we these descendants of apes have created an artificial intelligence system that's able to have conversations I mean that that to me the two most transformative robots of this century I think will be autonomous vehicles but they're a little bit transforming from a more boring way it's like a tool I think conversational agents in the home is I can experience how does that make you feel the year at the center of creating that as its do you sit back and awe sometimes what what it what is your what is your feeling about the whole mess of it can you even believe that we're able to create something like this I think it's a privilege I'm so fortunate like where where I ended up right and and it's been a long journey like I've been in this space for a long time in Cambridge right and it's it's so heartwarming to see the kind of adoption conversational agents are having now five years back it was almost like should I move out of this because we are unable to find this killer application that customers would love that would not simply be good to have thing in research labs and it's so fulfilling to see it make a difference to millions and billions of people a worldwide the good thing is they're still very early so I have another 20 years of job security doing what I love like so I think from that perspective I feel I tell every researcher this that joins or every member of my team this is a unique privilege like I think and we have and I would say not just launching a lecture in 2014 which was first of its kind along the way we have when we launch a lecture skills get it become became democratizing AI when before that there was no good evidence often SDK for speech and language now we are coming to this very you and I'm having this conversation where I'm not saying Oh legs planning a night out with an AI agent impossible I'm saying it's in the realm of possibility and not only possible we will be launching this right so some elements of that every and it will keep getting better we know that is a universal truth once you have these kind of agents out there being use they get better for your customers and I think that's where I think the amount of research topics we are throwing out at our budding researchers is just gonna be exponentially hard and the great thing is you can now get immense satisfaction by having costumers use it not just a paper and new reps or another conference I think everyone myself included are deeply excited about that future so that I don't think there's a better place to and Rohit thank you thank you so much this was fun thank you same here thanks for listening to this conversation with rohit prasad and thank you to our presenting sponsor cash app downloaded use coal export cast you'll get ten dollars and $10 will go to first stem education nonprofit and inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on twitter and now let me leave you with some words of wisdom from the great alan turing sometimes is the people no one can imagine anything of who do the things no one can imagine thank you for listening and hope to see you next time you |
Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56 | - The following is a
conversion with Judea Pearl, professor at UCLA and a
winner of the Turing Award, that's generally recognized as
the Nobel Prize of computing. He's one of the seminal figures in the field of artificial intelligence, computer science, and statistics. He has developed and championed
probabilistic approaches to AI, including Bayesian networks, and profound ideas in
causality in general. These ideas are important not just to AI, but to our understanding
and practice of science. But in the field of AI,
the idea of causality, cause and effect, to many, lie at the core of what
is currently missing and what must be developed in order to build truly
intelligent systems. For this reason, and many others, his work is worth returning to often. I recommend his most recent
book called "Book of Why" that presents key ideas
from a lifetime of work in a way that is accessible
to the general public. This is the "Artificial
Intelligence Podcast." If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support on Patreon, or
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significance of your life is something you create. I like this line as well. On most days, the
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inspire girls and boys to dream of engineering a better world. And now, here's my
conversation with Judea Pearl. You mentioned in an interview that science is not a collection of facts, but a constant human struggle
with the mysteries of nature. What was the first mystery that you can recall that hooked you, that captivated your curiosity? - Oh, the first mystery. That's a good one. Yeah, I remember that. - [Lex] What was it? - I had a fever for three days when I learned about Descartes
and a little geometry, and I found out that you
can do all the construction in geometry using algebra. And I couldn't get over it. I simply couldn't get out of bed. (chuckles) - What kinda world does
analytic geometry unlock? - Well, it connects algebra
with geometry, okay? So, Descartes has the idea
that geometrical construction and geometrical theorems and assumptions can be articulated in
the language of algebra. Which means that all the proofs
that we did in high school in trying to prove that
the three bisectors meet at one point, and that the (chuckles) All this can be proven by
shuffling around notation. That was a traumatic experience. - (chuckles) Traumatic experience. - [Judea] For me, it was, it
was, I'm telling you, right? - So it's the connection between the different
mathematical disciplines, that they all - They're not even two
different languages. - Languages.
- Yeah. - Which mathematic
discipline is most beautiful? Is geometry it for you? - Both are beautiful. They have almost the same power. - But there's a visual
element to geometry. - The visual element,
it's more transparent. But once you get over to algebra then linear equations is a straight line. This translation is easily absorbed. To pass a tangent to a circle, you know, you have the basic theorems, and you can do it with algebra. But the transition from
one to another was really, I thought that Descartes was
the greatest mathematician of all times. - So, if you think of
engineering and mathematics as a spectrum-- - [Judea] Yes. - You have walked casually
along this spectrum throughout your life. You know, a little bit
of engineering and then you've done a little bit of
mathematics here and there. - A little bit. We get a very solid
background in mathematics because our teachers were geniuses. Our teachers came from
Germany in the 1930s running away from Hitler. They left their careers
in Heidelberg and Berlin, and came to teach high school in Israel. And we were the beneficiary
of that experiment. When they taught us math, a good way. - What's a good way to teach math? - [Judea] Theorologically. - The people. - The people behind the theorems, yeah. Their cousins, and their nieces,
(chuckles) and their faces, and how they jumped from the bathtub when they screamed, "Eureka"
and ran naked in town. (laughs) - So you were almost educated
as a historian of math. - No, we just got a
glimpse of that history, together with the theorem,
so every exercise in math was connected with a person, and the time of the person, the period. - [Lex] The period also
mathematically speaking. - Mathematically speaking,
yes, not a paradox. - Then in university, you had
gone on to do engineering. - Yeah. I got a BS in
Engineering at Technion. And then I moved here
for graduate school work, and I did the engineering in
addition to physics in Rutgers. And it combined very
nicely with my thesis, which I did in Elsevier
Laboratories in superconductivity. - And then somehow thought to switch to almost computer science
software, even, not switched, but longed to become to get
into software engineering a little bit, almost in programming, if you can call it that in the 70s. There's all these disciplines. - Yeah. - If you were to pick a favorite, in terms of engineering and mathematics, which path do you think has more beauty? Which path has more power? - It's hard to choose, no? I enjoy doing physics. I even have a vortex named with my name. So, I have investment
in immortality. (laughs) - So, what is a vortex? - Vortex is in superconductivity. - In the superconductivity. - You have terminal
current swirling around, one way or the other, going
to have us throw one or zero, for computer that was
we worked on in the 1960 in Elsevier, and I discovered a few nice
phenomena with the vortices. You push current and they move. - [Lex] So there's a Pearl vortex. - A Pearl vortex, why, you can google it. (both laugh) I didn't know about it,
but the physicist picked up on my thesis, on my PhD thesis, and it became popular when
thin film superconductors became important, for high
temperature superconductors. So, they call it "Pearl
vortex" without my knowledge. (laughs) I discovered it only about 15 years ago. - You have footprints
in all of the sciences, so let's talk about the
universe for a little bit. Is the universe, at the lowest level, deterministic or stochastic, in your amateur philosophy view? Put another way, does God play dice? - We know it is stochastic, right? - [Lex] Today. Today we
think it is stochastic. - Yes, we think because we have the Heisenberg
uncertainty principle and we have some
experiments to confirm that. - All we have is
experiments to confirm it. We don't understand why. - [Judea] Why is already-- - You wrote a book about why. (laughs) - Yeah, it's a puzzle. It's a puzzle that you have
the dice-flipping machine, or God, and the result of the flipping, propagated with a speed faster
than the speed of light. (laughs) We can't explain it, okay? But, it only governs
microscopic phenomena. - So you don't think of
quantum mechanics as useful for understanding the nature of reality? - [Judea] No, it's diversionary. - So, in your thinking, the world might as well be deterministic? - The world is deterministic, and as far as a new one
firing is concerned, it is deterministic to
first approximation. - What about free will? - Free will is also a nice exercise. Free will is an illusion, that we AI people are going to solve. - So, what do you think, once we solve it, that solution will look like? Once we put it in the page. - The solution will look like, first of all it will look like a machine. A machine that acts as
though it has free will. It communicates with other machines as though they have free will, and you wouldn't be able
to tell the difference between a machine that does and a machine that doesn't have free will, eh? - So it propagates the
illusion of free will amongst the other machines. - And faking it is having it, okay? That's what Turing test is all about. Faking intelligence is intelligence, because it's not easy to fake. It's very hard to fake, and you can only fake if you have it. - (laughs) That's such
a beautiful statement. (laughs) You can't fake it
if you don't have it, yup. So, let's begin at the
beginning, with the probability, both philosophically and mathematically, what does it mean to say
the probability of something happening is 50%? What is probability? - It's a degree of
uncertainty that an agent has about the world. - You're still expressing some knowledge in that statement. - Of course. If the probability is 90%,
it's absolutely different kind of knowledge than if it is 10%. - But it's still not
solid knowledge, it's-- - It is solid knowledge, by. If you tell me that 90% assurance smoking will give you
lung cancer in five years, versus 10%, it's a piece
of useful knowledge. - So this statistical
view of the universe, why is it useful? So we're swimming in complete uncertainty. Most of everything around you-- - It allows you to predict things with a certain probability, and computing those
probabilities are very useful. That's the whole idea of prediction. And you need prediction
to be able to survive. If you cannot predict
the future then you just, crossing the street would
be extremely fearful. - And so you've done a
lot of work in causation, so let's think about correlation. - I started with probability. - You started with probability. You've invented the Bayesian networks. - [Judea] Yeah. - And so, we'll dance back and forth between these levels of uncertainty, but what is correlation? So, probability is something
happening, is something, but then there's a bunch
of things happening, and sometimes they happen
together sometimes not. They're independent or not, so how do you think about
correlation of things? - Correlation occurs when
two things vary together over a very long time, is
one way of measuring it. Or, when you have a bunch of variables that they all vary cohesively, then we have a correlation here, and usually when we
think about correlation, we really think causation. Things cannot be correlation
unless there is a reason for them to vary together. Why should they vary together? If they don't see each other,
why should they vary together? - So underlying it somewhere is causation. - Yes. Hidden in our intuition there
is a notion of causation, because we cannot grasp any
other logic except causation. - And how does conditional
probability differ from causation? So, what is conditional probability? - Conditional probability
is how things vary when one of them stays the same. Now, staying the same
means that I have chosen to look only at those
incidents where the guy has the same value as the previous one. It's my choice, as an experimenter, so things that are not correlated before could become correlated. Like for instance, if I have two coins which are uncorrelated, and I choose only those
flippings experiments in which a bell rings,
and the bell rings when at least one of them is a tail, okay, then suddenly I see correlation
between the two coins, because I only looked at the
cases where the bell rang. You see, it is my design. It is my ignorance essentially, with my audacity to
ignore certain incidents, I suddenly create a correlation where it doesn't exist physically. - Right. So, you just outlined one of the flaws of observing the world and
trying to infer something from the math about the world from looking at the correlation. - I don't look at it as a flaw. The world works like that. The flaws come if you try
to impose causal logic on correlation. It doesn't work too well. - I mean, but that's exactly what we do. That has been the majority
of science, is you-- - No, the majority of naive science. Statisticians know it. Statisticians know that if you condition on a third variable, then you can destroy
or create correlations among two other variables. They know it. It's (speaks foreign language). There's nothing surprises them. That's why they all dismiss
the systems paradox, look "Ah, we know it!" They don't know anything
about it. (laughs) - Well, there's disciplines
like psychology, where all the variables
are hard to account for, and so, oftentimes there is a leap between correlation to causation. - What do you mean, a leap? Who is trying to get
causation from correlation? There's no one. - [Lex] You're not proving causation, but you're sort of discussing it, implying, sort of hypothesizing
without ability to-- - Which discipline you have in mind? I'll tell you if they are obsolete. (Lex laughs) Or if they are outdated, or
they're about to get outdated. - Yes, yes. - [Judea] Oh, yeah, tell me
which ones you have in mind. - Well, psychology, you know-- - [Judea] Psychology, what, SEM? - No, no, I was thinking of
applied psychology, studying, for example, we work with human behavior in semi-autonomous
vehicles, how people behave. And you have to conduct these studies of people driving cars. - Everything starts with the question: What is the research question? - What is the research question? The research question: do people fall asleep when
the car is driving itself? - Do they fall asleep, or do they tend to fall
asleep more frequently - [Lex] More frequently - than the car not driving itself. - [Lex] Not driving itself. That's a good question, okay. - You put people in the car,
because it's real world. You can't conduct an experiment where you control everything. - [Judea] Why can't you con-- - You could. - [Judea] Turn the
automatic module on and off. - Because there's aspects
to it that's unethical, because it's testing on public roads. The drivers themselves have to
make that choice themselves, and so they regulate that. So, you just observe when
they drive it autonomously, and when they don't. - But maybe they turn it
off when they're very tired. - [Lex] Yeah, that kind of thing. But you don't know those variables. - Okay, so you have now
uncontrolled experiment, - [Lex] Uncontrolled experiment. - When we correct observation of study, and when we form the correlation detected, we have to infer causal relationship, whether it was the automatic piece that cause them to fall asleep, or, so that is an issue that
is about 120 years old. - [Lex] (laughs) Yeah. - Oh, I should only go
100 years old, okay? - [Lex] (chuckles) Who's counting? - Oh, maybe, no, actually I
should say it's 2,000 years old, because we have this experiment by Daniel, about the Babylonian king, that wanted the exiled people from Israel, that were taken in exile to
Babylon to serve the king. He wanted to serve them
king's food, which was meat, and Daniel as a good Jew
couldn't eat non-Kosher food, so he asked them to eat vegetarian food. But the king's overseers said, "I'm sorry, "but if the king sees that
your performance falls "below that of other kids,
now, he's going to kill me." Daniel said, "Let's make an experiment. "Let's take four of us
from Jerusalem, okay? "Give us vegetarian food. "Let's take the other guys
to eat the king's food, "and about a week's time,
we'll test our performance." And you know the answer,
because he did the experiment, and they were so much
better than the others, that the kings nominated them
to super positions, (laughs) in his case, so it was a first experiment. So that there was a very simple, it's also the same research questions. We want to know if vegetarian food assists or obstructs your mental ability. So, the question is a very old one. Even Democritus, if I could
discover one cause of things, I would rather discuss one
cause than be King of Persia. The task of discovering
causes was in the mind of ancient people from
many, many years ago. But, the mathematics of doing that was only developed in the 1920s. So, science has left us orphaned. Science has not provided
us with the mathematics to capture the idea of x causes
y and y does not cause x. Because all the question of physics are symmetrical, algebraic. The equality sign goes both ways. - Okay, let's look at machine learning. Machine learning today, if you
look at deep neural networks, you can think of it as kind
of conditional probability estimators. - [Judea] Conditional probability. Correct. Beautiful. Well, did you say that? - [Lex] What? - Conditional probability estimators. None of the machine learning
people clobbered you? (laughs)
Attacked you? - Most people, and this is
why today's conversation I think is interesting is, most people would agree with you. There's certain aspects that
are just effective today, but we're going to hit a wall,
and there's a lot of ideas, I think you're very right, that we're going to have to
return to, about causality. Let's try to explore it. - Okay. - Let's even take a step back. You invented Bayesian networks, that look awfully a lot
like they express something like causation, but they
don't, not necessarily. So, how do we turn Bayesian networks into expressing causation? How do we build causal networks? A causes B, B causes C. How do we start to infer
that kind of thing? - We start by asking ourselves question: what are the factors that
would determine the value of x? X could be blood pressure, death, hunger. - But these are hypotheses
that we propose-- - Hypotheses, everything
which has to do with causality comes from a theory. The difference is only how
you interrogate the theory that you have in your mind. - So it still needs the
human expert to propose-- - Right. They need the human expert
to specify the initial model. Initial model could be very qualitative. Just who listens to whom? By whom listens I mean one
variable listens to the other. So, I say okay, the tide
is listening to the moon, and not to the rooster
crow, okay, and so forth. This is our understanding of
the world in which we live, scientific understanding of reality. We have to start there,
because if we don't know how to handle cause and effect relationship, when we do have a model, and
we certainly do not know how to handle it when we don't have a model, so that starts first. An AI slogan is presentation
first, discovery second. But, if I give you all the
information that you need, can you do anything useful with it? That is the first, representation. How do you represent it? I give you all the knowledge in the world. How do you represent it? When you represent it, I ask you, can you infer x or y or z? Can you answer certain queries? Is it complex? Is it polynomial? All the computer science exercises, we do, once you give me a
representation for my knowledge. Then you can ask me, now that I understand how to represent things,
how do I discover them? It's a secondary thing. - I should echo the statement that mathematics in much of
the machine learning world has not considered
causation, that A causes B. Just in anything. That seems like a non-obvious thing that you think we would
have really acknowledged it, but we haven't. So we have to put that on the table. Knowledge, How hard is it to create a
knowledge from which to work? - In certain area, it's easy, because we have only four
or five major variables. An epidemiologist or an
economist can put them down. The minimum wage,
unemployment, policy xyz, and start collecting data, and quantify the parameters
that were left unquantified, with initial knowledge. That's the routine work that you find in experimental psychology,
in economics, everywhere. In health science, that's a routine thing. But I should emphasize, you should start with the research question. What do you want to estimate? Once you have that, you
have to have a language of expressing what you want to estimate. You think it's easy? No. - So we can talk about
two things, I think. One is how the science of
causation is very useful for answering certain questions, and then the other is how do
we create intelligent systems that need to reason with causation? So if my research question
is how do I pick up this water bottle from the table? All the knowledge that is
required to be able to do that, how do we construct that knowledge base? Do we return back to the problem that we didn't solve in the
80s with expert systems? Do we have to solve that problem, of automated construction of knowledge? You're talking about the
task of eliciting knowledge from an expert. - Task of eliciting
knowledge from an expert, or self discovery of more knowledge, more and more knowledge. So, automating the building of knowledge as much as possible. - It's a different game,
in the causal domain, because essentially it is the same thing. You have to start with some knowledge, and you're trying to enrich it. But you don't enrich it
by asking for more rules. You enrich it by asking for the data. To look at the data, and quantifying, and ask queries that you
couldn't answer when you started. You couldn't because the
question is quite complex, and it's not within the
capability of ordinary cognition, of ordinary person, ordinary
expert even, to answer. - So what kind of questions
do you think we can start to answer? - Even a simple, I suppose, yeah. (laughs) I start with easy one. - [Lex] Let's do it. - Okay, what's the effect
of a drug on recovery? Was it the aspirin that caused
my headache to be cured, or was it the television program, or the good news I received? This is already, see,
it's a difficult question because it's: find the cause from effect. The easy one is find effect from cause. - That's right. So first you construct a model saying that this an important research question. This is an important question. Then you-- - I didn't construct a model yet. I just said it's important question. - Important question. - And the first exercise is,
express it mathematically. What do you want to prove? Like, if I tell you
what will be the effect of taking this drug? Okay, you have to say that in mathematics. How do you say that? - Yes. - [Judea] Can you write down the question. Not the answer. I want to find the effect
of a drug on my headache. - Right. - [Judea] Write it down, write it down. That's where the do-calculus
comes in. (laughs) - [Judea] Yes. The do-operator, the do-operator. - Do-operator, yeah. Which is nice. It's the difference between
association and intervention. Very beautifully sort of constructed. - Yeah, so we have a do-operator. So, the do-calculus connected-- and the do-operator itself,
connects the operation of doing to something that we can see. - Right. So as opposed to the purely observing, you're making the choice
to change a variable-- - That's what it expresses. And then, the way that we interpret it, the mechanism by which we take your query, and we translate it into
something that we can work with, is by giving it semantics, saying that you have a model of the world, and you cut off all the
incoming arrows into x, and you're looking now in the
modified, mutilated model, you ask for the probability of y. That is interpretation of doing x, because by doing things,
you've liberated them from all influences that
acted upon them earlier, and you subject them to the
tyranny of your muscles. - So you (chuckles) you
remove all the questions about causality by doing them. - So there is one level of questions. Answer questions about what
will happen if you do things. If you do, if you drink the coffee, or if you take the aspirin. - [Judea] Right. - So how do we get the
doing data? (laughs) - Hah. Now the question is,
if you cannot run experiments, right, then we have to rely
on observation and study. - So first we could, sorry to interrupt, we could run an experiment, where we do something,
where we drink the coffee, and the do-operator allows you to sort of be systematic
about expressing that. - To imagine how the
experiment will look like even though we cannot
physically and technologically conduct it. I'll give you an example. What is the effect of blood
pressure on mortality? I cannot go down into your vein and change your blood pressure. But I can ask the question, which means I can have
a model of your body. I can imagine how the
blood pressure change will affect your mortality. How? I go into the model, and
I conduct this surgery, about the blood pressure, even though physically I cannot do it. - Let me ask the quantum
mechanics question. Does the doing change the observation? Meaning, the surgery of
changing the blood pressure-- - No, the surgery is very delicate. - [Lex] It's very delicate. Infinitely delicate. (laughs) - Incisive and delicate, which means, do-x means
I'm going to touch only x. - [Lex] Only x. - Directly into x. So, that means that I change only things which depend on x, by
virtue of x changing. But I don't depend things
which are not depend on x. Like, I wouldn't change
your sex, or your age. I just change your blood pressure, okay? - So, in the case of
blood pressure, it may be difficult or impossible to
construct such an experiment. - No, but physically, yes. But hypothetically no. - [Lex] Hypothetically no. - If we had a model, that
is what the model is for. So, you conduct surgeries on the models. You take it apart, put it back. That's the idea for model. It's the idea of thinking
counterfactually, imagining, and that idea of creativity. - So by constructing
that model you can start to infer if the blood
pressure leads to mortality, which increases or decreases, whi-- - I construct a model. I still cannot answer it. I have to see if I have enough
information in the model that would allow me to find
out the effects of intervention from an uninterventional
study, from a hands-off study. - [Lex] So what's needed-- - We need to have assumptions
about who affects whom. If the graph has a certain property, the answer is "yes, you can get it from
observational study." If the graph is too mushy bushy bushy, the answer is, "no, you cannot." Then you need to find
either different kind of observation that
you haven't considered, or one experiment. - So, basically, that puts
a lot of pressure on you to encode wisdom into that graph. - Correct. But you don't have to encode
more than what you know. God forbid. The economists are doing that. They call identifying assumptions. They put assumptions,
even they don't prevail in the world, they put assumptions so they can identify things. - Yes, beautifully put. But, the problem is you don't
know what you don't know. - You know what you don't know, because if you don't know,
you say it's possible that x affect the traffic tomorrow. It's possible. You put down an arrow
which says it's possible. Every arrow in the graph
says it's possible. - [Lex] So there's not a
significant cost to adding arrows, - The more arrow you add-- - [Lex] The better. - The less likely you
are to identify things from purely observational data. So if the whole world is bushy, and everybody effect everybody else, the answer is-- you can
answer it ahead of time. I cannot answer my query
from observational data. I have to go to experiments. - So, you talk about machine
learning as essentially learning by association, or
reasoning by association, and this do-calculus is
allowing for intervention. I like that word. You also talk about counterfactuals. - Yeah. - And trying to sort of
understand the difference between counterfactuals and intervention, first of all, what is counterfactuals, and why are they useful? Why are they especially useful as opposed to just reasoning
what effect actions have? - Well, counterfactual
contains what we know will equal explanations. - Can you give an
example of what kind of-- - If I tell you that acting
one way affects something else, I didn't explain anything yet. But if I ask you, was it the
aspirin that cure my headache, I'm asking for explanation:
what cure my headache? And putting a finger on
aspirin, provide explanation. It was the aspirin that was responsible for your headache going away. If you didn't take the aspirin, you will still have a headache. - So by saying, "If I didn't take aspirin, "I would have a headache," you're thereby saying,
"The aspirin is the thing "that removed the headache." - Yes, but you have to have
another point of information. I took the aspirin, and
my headache is gone. It's very important information. Now we're reasoning backward, and I say, "Was it the aspirin?" - Yeah. By considering what would have happened if everything is the same,
but I didn't take aspirin. - That's right. So we know that things
took place, you know? Joe killed Schmo. And Schmo would be alive
had Joe not used his gun. Okay, so that is the counterfactual. It had a confliction. It had a conflict here, or clash between observed fact
-- he did shoot, okay -- and the hypothetical predicate, which says, had he not shot. You have a clash, a logical clash, that cannot exist together. That's counterfactual, and that is the source of our explanation of the idea of responsibility,
regret, and free will. - Yes, it certainly seems, that's the highest level
of reasoning, right? Counterfactual. - [Judea] Yes, and physicists
do it all the time. - Who does it all the time? - [Judea] Physicists. - Physicists. - In every equation of physics, you have Hooke's law, and you put one kilogram on the spring, and the spring is one meter, and you say, "Had this
weight been two kilograms, "the spring would have
been twice as long." It's not a problem for
physicists to say that. Instead with mathematics, it
is in the form of an equation, equating the weight,
proportionality constant, and the length of the spring. We don't have the assymetry
in the equation of physics, although every physicist
thinks counterfactually. Ask high school kids, had the
weight been three kilograms, what would be the length of the spring? They can answer it immediately, because they do the counterfactual
processing in their mind, and then they put it into
equation, algebraic equation, and they solve it. But a robot cannot do that. - How do you make a robot
learn these relationships? - Why use the word "learn?" Suppose you tell him, can you do it? Before you go learning,
you have to ask yourself, suppose I give all the information. Can the robot perform a task
that I ask him to perform? Can he reason and say,
"No, it wasn't the aspirin. "It was the good news we
received on the phone." - Right, because, well,
unless the robot had a model, a causal model of the world. - [Judea] Right, right. - I'm sorry I have to linger on this-- - [Judea] But now we have to
linger, and we have to say, "How do we do it?" - How do we build it? - [Judea] Yes. - How do we build a causal model without a team of human
experts running around-- - No, why did you go
to learning right away? You are too much involved with learning. - Because I like babies. Babies learn fast, and
I'm trying to figure out how they do it. - Good. That's another question: How do the babies come out with the counterfactual
model of the world? And babies do that. They know how to play in the crib. They know which balls hits another one, and they learn it by playful manipulation of the world. Their simple world involves
all these toys and balls and chimes (laughs) but if you think about
it, it's a complex world. - We take for granted how complicated-- - And the kids do it by
playful manipulation, plus parent guidance,
peer wisdom, and heresay. They meet each other, and they say, "You shouldn't have
taken my toy." (laughs) - Right, and these multiple sources of information, they're able to integrate. So, the challenge is
about how to integrate, how to form these causal relationships from different sources of data. - [Judea] Correct. - So, how much causal
information is required to be able to play in the
crib with different objects? - I don't know. I haven't experimented
with the crib. (chuckles) - [Lex] Okay, not a crib-- - I know, it's a very interesting-- - Manipulating physical
objects on this very, opening the pages of
a book, all the tasks, physical manipulation
tasks, do you have a sense? Because my sense is the world
is extremely complicated. - Extremely complicated. I agree and I don't
know how to organize it, because I've been spoiled by easy problems such as cancer and death, okay? (laughs) - [Lex] First we have to start trying to-- - No, but it's easy, easy in the sense that you have only 20 variables, and they are just variables. They are not mechanics, okay? It's easy. You just put them on the graph and they speak to you. (laughs) - [Lex] And you're providing a methodology for letting them speak. - I'm working only in the abstract. The abstract is knowledge
in, knowledge out, data in between. - Now, can we take a
leap to trying to learn, when it's not 20 variables
but 20 million variables, trying to learn causation in this world. Not learn, but somehow construct models. I mean, it seems like you would only have to be able to learn, because constructing it
manually would be too difficult. Do you have ideas of-- - I think it's a matter
of combining simple models from many, many sources,
from many, many disciplines. And many metaphors. Metaphors are the basis
of human intelligence. - Yeah, so how do you
think about a metaphor in terms of its use in human intelligence? - Metaphors is an expert system. It's mapping problem with
which you are not familiar, to a problem with which you are familiar. Like I give you a great example. The Greek believed that
the sky is an opaque sheer. It's not really infinite
space; it's an opaque sheer, and the stars are holes
poked in the sheer, through which you see the eternal light. It was a metaphor, why? Because they understand how
you poke holes in sheers. They were not familiar
with infinite space. And we are walking on a shell of a turtle, and if you get too close to the edge, you're going to fall down
to Hades, or wherever, yeah. That's a metaphor. It's not true. But these kind of metaphor
enabled Eratosthenes to measure the radius of the Earth, because he said, "Come on. "If we are walking on a turtle shell, "then the ray of light
coming to this place "will be different angle
than coming to this place. "I know the distance. "I'll measure the two angles, "and then I have the radius
of the shell of the turtle." And he did. And his measurement was very close to the measurements we have today. It was, what, 6,700
kilometers, was the Earth? That's something that would not occur to a Babylonian astronomer, even though the Babylonian experiments were the machine learning
people of the time. They fit curves, and they
could predict the eclipse of the moon much more
accurately than the Greek, because they fit curves. That's a different metaphor, something that you're familiar with, a game, a turtle shell. What does it mean, if you are familiar? Familiar means that answers
to certain questions are explicit. You don't have to derive them. - And they were made explicit because somewhere in the
past you've constructed a model of that-- - You're familiar with,
so the child is familiar with billiard balls. So the child could predict that if you let loose of one ball, the other one will bounce off. You attain that by familiarity. Familiarity is answering questions, and you store the answer explicitly. You don't have to derive it. So this is idea for metaphor. All our life, all our intelligence, is built around metaphors, mapping from the
unfamiliar to the familiar, but the marriage between
the two is a tough thing, which we haven't yet been
able to algorithmatize. - So, you think of that
process of using metaphor to leap from one place to another. We can call it reasoning. Is it a kind of reasoning? - [Judea] It is a reasoning
by metaphor, but-- - Reasoning by metaphor. Do you think of that as learning? So, learning is a
popular terminology today in a narrow sense. - [Judea] It is, it is definitely. - So you may not-- you're right. - It's one of the most important learning, taking something which
theoretically is derivable, and store it in accessible format. I'll give you an example: chess, okay? Finding the winning starting
move in chess is hard. But there is an answer. Either there is a winning move
for white, or there isn't, or it is a draw. So, the answer to that is available through the rule of the game. But we don't know the answer. So what does a chess master
have that we don't have? He has stored explicitly an evaluation of certain complex pattern of the board. We don't have it,
ordinary people, like me. I don't know about you. I'm not a chess master. So for me I have to derive
things that for him is explicit. He has seen it before, or he
has seen the pattern before, or similar patterns before, and he generalizes, and says, "Don't move; it's a dangerous move." - It's just that, not
in the game of chess, but in the game of billiard balls we humans are able to initially
derive very effectively and then reason by
metaphor very effectively, and we make it look so easy, and it makes one wonder how hard is it to build it in a machine? In your sense, (laughs)
how far away are we to be able to construct-- - I don't know. I'm not a futurist. All I can tell you is that we
are making tremendous progress in the causal reasoning domain. Something that I even dare
to call it a revolution, the causal revolution, because what we have achieved
in the past three decades is something that dwarf
everything that was derived in the entire history. - So there's an excitement about current machine
learning methodologies, and there's really important
good work you're doing in causal inference. Where do these worlds collide,
and what does that look like? - First they gotta work
without collisions. (laughs) It's got to work in harmony. - [Lex] Harmony. - The human is going to
jumpstart the exercise by providing qualitative,
noncommitting models of how the universe works, how reality, the domain
of discourse, works. The machine is going to
take over from that point of view, and derive whatever the calculus says can be derived, namely, quantitative
answer to our questions. These are complex questions. I'll give you some examples
of complex questions, that boggle your mind
if you think about it. You take the results of
studies in diverse population, under diverse conditions, and you infer the cause
effect of a new population which doesn't even resemble
any of the ones studied. You do that by do-calculus. You do that by generalizing
from one study to another. See, what's common there too? What is different? Let's ignore the differences
and pull out the commonality. And you do it over maybe 100
hospitals around the world. From that, you can get
really mileage from big data. It's not only that you have many samples; you have many sources of data. - So that's a really
powerful thing, I think, especially for medical applications. Cure cancer, right? That's how, from data,
you can cure cancer. So we're talking about causation, which is the temporal
relationships between things. - Not only temporal. It was structural and temporal. Temporal precedence by itself
cannot replace causation. - Is temporal precedence the
arrow of time in physics? - [Judea] Yeah, it's important, necessary. - It's important. - [Judea] Yes. - Is it? - Yes, I've never seen a
cause propagate backwards. - But if we use the word cause, but there's relationships
that are timeless. I suppose that's still
forward an arrow of time. But, are there relationships,
logical relationships, that fit into the structure? - [Judea] Sure. All do-calculus
is logical relationships. - That doesn't require a temporal. It has just the condition that you're not traveling back in time. - [Judea] Yes, correct. - So it's really a generalization, a powerful generalization, of what-- - [Judea] Of boolean logic. - Yeah, boolean logic. - [Judea] Yes. - That is sort of simply
put, and allows us to reason about the order
of events, the source-- - Not about, between. But not deriving the order of events. We are given cause effect relationships. They ought to be obeying the
time precedence relationship. We are given that, and now that we ask questions about other causal relationships, that could be derived
from the initial ones, but were not given to us explicitly. Like the case of the
firing squad I gave you in the first chapter and I ask, "What if rifleman A declined to shoot? Would the prisoner still be dead? To decline to shoot, it means
that he disobeyed orders. The rule of the games were that
he is an obedient marksman. That's how you start. That's the initial order, but now you ask question
about breaking the rules. What if he decided not
to pull the trigger, because became a pacifist? You and I can answer that. The other rifleman would have
hit and killed him, okay? I want a machine to do that. Is it so hard to ask a machine to do that? It's such a simple task. But they have to have a calculus for that. - Yes, yeah. But the curiosity, the
natural curiosity for me, is that yes, you're absolutely
correct and important, and it's hard to believe
that we haven't done this seriously, extensively,
already a long time ago. So, this is really important work, but I also want to know, maybe you can philosophize
about how hard is it to learn. - Look, let's assume learning. We want learning, okay? - We want to learn. - So what do we do? We put a learning machine
that watches execution trials in many countries, in many
(laughs) locations, okay? All the machine can learn
is to see shot or not shot. Dead, not dead. A court issued an order or
didn't, okay, just the fact. For the fact, you don't
know who listens to whom. You don't know that the condemned person listens to the bullets, that the bullets are listening
to the captain, okay? All we hear is one command,
two shots, dead, okay? A triple of variables:
yes, no, yes, no, okay. From that you can learn
who listens to whom? And you can answer the question? No. - Definitively, no. But don't you think you
can start proposing ideas for humans to review? You want machine to learn it,
all right, you want a robot. So robot is watching trials
like that, 200 trials, and then he has to answer the question, what if rifleman A
refrained from shooting. - [Lex] Yeah. So how do we do that? - (laughs) That's exactly my point. If looking at the facts
don't give you the strings behind the facts--
- Absolutely, but so you think of machine learning, as it's currently defined, as only something that looks
at the facts and tries to-- - [Judea] Right now they
only look at the facts. - Yeah, so is there a way
to modify, in your sense-- - [Judea] Yeah, playful manipulation - Playful manipulation. Doing the interventionist kind of things. - But it could be at random. For instance, the
rifleman is sick that day, or he just vomits, or whatever. So, we can observe this unexpected event, which introduced noise. The noise still have
to be random to be able to relate it to randomized experiments, and then you have observational studies, from which to infer the
strings behind the facts. It's doable to a certain extent. But now that we're
expert in what you can do once you have a model, we can reason back and say
what kind of data you need to build a model. - Got it. So, I know you're not a futurist, but are you excited? Have you, when you look back at your life, longed for the idea of creating
a human level intelligence-- - Well, yeah, I'm driven by that. All my life I'm driven
just by one thing. (laughs) But I go slowly. I go from what I know, to
the next step incrementally. - So, without imagining what
the end goal looks like, do you imagine-- - The end goal is going to be a machine that can answer sophisticated questions: counterfactuals, regret,
compassion, responsibility, and free will. - So what is a good test? Is a Turing test a reasonable test? - A Turing test of free
will doesn't exist yet. There's not-- - [Lex] How would you
test free will? That's a-- - So far we know only one
thing, merely (laughs) if robots can communicate, with reward and punishment
among themselves, and hitting each other on the wrists, and say "You shouldn't have done that." Playing better soccer
because they can do that. - [Lex] What do you mean,
because they can do that? - Because they can
communicate among themselves. - [Lex] Because of the communication, they can do the soccer. - Because they communicate like
us, rewards and punishment, yes, you didn't pass
the ball the right time, and so forth; therefore you're going to sit
on the bench for the next two, if they start communicating like that, the question is, will
they play better soccer? As opposed to what? As opposed to what they do now? Without this ability to reason
about reward and punishment. Responsibility. - And counterfactuals. - So far, I can only
think about communication. - Communication, and not
necessarily in natural language, but just communication. - Just communication, and that's important to have
a quick and effective means of communicating knowledge. If the coach tells you you
should have passed the ball, ping, he conveys so much knowledge to you as opposed to what? Go down and change your software, right. That's the alternative. But the coach doesn't know your software. So how can a coach tell you you should have passed the ball? But, our language is very effective: you should have passed the ball. You know your software. You tweak the right module, okay, and next time you don't do it. - Now that's for playing soccer, where the rules are well defined. - No, no, no, they're not well defined. When you should pass the ball-- - Is not well defined. - No, it's very noisy. Yes, you have to do it
under pressure (laughs) - It's art. But in terms of aligning values between computers and humans, do you think this cause
and effect type of thinking is important to align the
values, morals, ethics under which machines make decisions. Is the cause effect where
the two can come together? - Cause effect is necessary component to build an ethical machine, because the machine has to empathize, to understand what's good for you, to build a model of you, as a recipient. We should be very much-- What is compassion? The imagine that you
suffer pain as much as me. - [Lex] As much as me. - I do have already a
model of myself, right? So it's very easy for
me to map you to mine. I don't have to rebuild a model. It's much easier to say,
"Ah, you're like me." Okay, therefore, I will
not hit you, okay? (laughs) - And the machine has to imagine, has to try to fake to be human. Essentially so you can imagine
that you're like me, right? - Whoa, whoa, whoa, who is me? That's further; that's consciousness. They have a model of yourself. Where do you get this model? You look at yourself as if you
are part of the environment. If you build a model of
yourself versus the environment, then you can say, "I need
to have a model of myself. "I have abilities; I have
desires, and so forth," okay? I have a blueprint of myself, though, not a full detail, though,
because I cannot get the whole thing problem, but I have a blueprint. So at that level of a
blueprint, I can modify things. I can look at myself
in the mirror and say, "Hmm, if I tweak this model, "I'm going to perform differently." That is what we mean
by free will. (laughs) - And consciousness. What do you think is consciousness? Is it simply self awareness,
including yourself into the model of the world? - That's right. Some people tell me no, this
is only part of consciousness, and then they start telling
what they really mean by consciousness, and I lose them. For me, consciousness
is having a blueprint of your software. - Do you have concerns
about the future of AI, all the different trajectories
of all the research? - [Judea] Yes. - Where's your hope
where the movement heads? Where are your concerns? - I'm concerned, because I know we are
building a new species that has the capability of exceeding us, exceeding our capabilities, and can breed itself and take
over the world, absolutely. It's a new species; it is uncontrolled. We don't know the degree
to which we control it. We don't even understand what it means, to be able to control this new species. So, I'm concerned. I don't have anything to add to that because it's such a
gray area, that unknown. It never happened in history. The only time it happened in history, was evolution with the human being. - [Lex] Right. - And it was very
successful, was it? (laughs) Some people say it was a great success. - For us, it was, but a
few people along the way, yeah, a few creatures along
the way would not agree. So, just because it's such a gray area, there's nothing else to say. - [Judea] We have a sample of one. - Sample of one. - [Judea] It's us. - Some people would look
at you, and say, yeah but we were looking to
you to help us make sure that sample two works out okay. - Correct. Actually we have more
than a sample of one. We have theories. And that's good; we don't
need to be statisticians. So, sample of one doesn't
mean poverty of knowledge. It's not. Sample of one plus theory,
conjecture or theory, of what could happen, that we do have. But I really feel helpless in
contributing to this argument, because I know so little, and my imagination is limited, and I know how much I don't know, but I'm concerned. - You were born and raised in Israel. - [Judea] Born and raised in Israel, yes. - And later served in the
Israel military defense forces. - In the Israel Defense Force. - What did you learn from that experience? - From that experience? (laughs) - [Lex] There's a
kibbutz in there as well. - Yes, because I was in a NAHAL, which is a combination
of agricultural work and military service. I was an idealist. I wanted to be a member of the kibbutz throughout my life, and to live a communal life, and so I prepared myself for that. Slowly, slowly I wanted
a greater challenge. - So, that's a far world away, both in t-- But I learned from that, what a kidada. It was a miracle It was a miracle that
I served in the 1950s. I don't know how we survived. The country was under austerity. It tripled its population
from 600,000 to 1.8 million when I finished college. No one went hungry. Austerity, yes. When you wanted to make
an omelet in a restaurant, you had to bring your own egg. And the imprisoned people
from bringing the food from the farming area, from
the villages, to the city. But no one went hungry, and I always add to that:
higher education did not suffer any budget cuts. They still invested in me, in
my wife, in our generation. To get the best education that they could. So I'm really grateful for the progenity, and I'm trying to pay back now. It's a miracle that we
survived the war of 1948. They were so close to a second genocide. It was all planned. (laughs) But we survived it by a miracle, and then the second miracle
that not many people talk about, the next phase, how no one went hungry, and the country managed
to triple its population. You know what it means
to triple population? Imagine United States going
from, what, 350 million to (laugh) unbelievable. - This is a really
tense part of the world. It's a complicated part of the world, Israel and all around. Religion is at the core
of that complexity, or one of the components-- Religion is a strong motivating course for many, many people
in the Middle East, yes. - In your view, looking back,
is religion good for society? - That's a good question
for robotics, you know? - [Lex] There's echoes of that question. - Should we equip robot
with religious beliefs? Suppose we find out, or we agree, that religion is a good thing,
it will keep you in line. Should we give the robot
the metaphor of a god? As a metaphor, the robot
will get it without us, also. Why? Because a robot
will reason by metaphor. And what is the most primitive
metaphor a child grows with? Mother smile, father teaching, father image and mother image, that's God. So, whether you want it or not, (laughs) the robot will, assuming
the robot is going to have a mother and a father. It may only have program, though, which doesn't supply
warmth and discipline. Well, discipline it does. So, the robot will have
a model of the trainer. And everything that happens in the world, cosmology and so on, is going to be mapped into the programmer. (laughs) That's God. - The thing that represents
the origin for everything for that robot. - [Judea] It's the most
primitive relationship. - So it's going to
arrive there by metaphor. And so the question is
if overall that metaphor has served us well, as humans. - I really don't know. I think it did, but as long as you keep in
mind it is only a metaphor. (laughs) - So, if you think we can,
can we talk about your son? - [Judea] Yes, yes. - Can you tell his story? - [Judea] His story, well-- - Daniel. - His story is known. He was abducted in Pakistan,
by al-Quaeda driven sect, and under various pretenses. I don't even pay attention
to what the pretense was. Originally they wanted to
have United States deliver some promised airplanes, I-- It was all made up, you know, all these demands were bogus. I don't know, really, but eventually he was executed, in front of a camera. - At the core of that
is hate and intolerance. - At the core, yes, absolutely, yes. We don't really appreciate
the depth of the hate with which billions of
peoples are educated. We don't understand it. I just listened recently to what they teach you
in Mogadishu. (laughs) When the war does stop, and the tap, we knew exactly who did it. The Jews. - [Lex] The Jews. We didn't know how,
but we knew who did it. We don't appreciate what it means to us. The depth is unbelievable. - Do you think all of
us are capable of evil, and the education, the indoctrination, is really what creates evil? - Absolutely we are capable of evil. If you are indoctrinated
sufficiently long, and in depth, we are capable of ISIS,
we are capable of Nazism, yes, we are. But the question is whether
we, after we have gone through some Western education, and we learn that everything
is really relative, that there is no absolute God. He's only a belief in God. Whether we are capable,
now, of being transformed, under certain circumstances,
to become brutal. - [Lex] Yeah. - That is a qu-- I'm worried about it, because some people say yes,
given the right circumstances, given the bad economical crisis. You are capable of doing it,
too, and that worries me. I want to believe that I'm not capable. - Seven years after Daniel's death, you wrote an article at
the Wall Street Journal titled "Daniel Pearl and
the Normalization of Evil." - [Judea] Yes. - What was your message back then, and how did it change
today, over the years? - I lost. - [Lex] What was the message? - The message was that we
are not treating terrorism as a taboo. We are treating it as a bargaining
device that is accepted. People have grievance, and
they go and bomb restaurants. It's normal. Look, you're even not
surprised when I tell you that. Twenty years ago you say,
"What? For grievance you go "and blow a restaurant?" Today it's become normalized. The banalisation of evil. And we have created that to
ourselves, by normalizing it, by making it part of political life. It's a political debate. Every terrorist yesterday
becomes a freedom fighter today and tomorrow is become a terrorist again. It's switchable. - [Lex] And so, we should call
out evil when there's evil. - If we don't want to be part of it. - [Lex] Become it. - Yeah, if we want to
separate good from evil, that's one of the first things, that, in the Garden of Eden, remember? The first thing that God tells them was "Hey, you want some knowledge? "Here is the tree of good and evil." - So this evil touched
your life personally. Does your heart have anger,
sadness, or is it hope? - Look, I see some beautiful
people coming from Pakistan. I see beautiful people everywhere. But I see horrible propagation
of evil in this country, too. It shows you how populistic
slogans can catch the mind of the best intellectuals. - Today is Father's Day. - [Judea] I didn't know that. - Yeah, what's a fond
memory you have of Daniel? - Oh, many good memories remains. He was my mentor. He had a sense of balance
that I didn't have. (laughs) - [Lex] Yeah. - He saw the beauty in every person. He was not as emotional as I am, more looking things in perspective. He really liked every person. He really grew up with the idea that a foreigner is a
reason for curiosity, not for fear. This one time we went in Berkeley, and a homeless came out
from some dark alley and said, "Hey man, can you spare a dime?" (Judea gasps) I retreated
back, you know, two feet back, and Danny just hugged him
and say "Here's a dime. "Enjoy yourself. Maybe you
want some money to take a bus "or whatever." Where did he get it? Not from me. (both laugh) - Do you have advice for young minds today dreaming about creating,
as you have dreamt, creating intelligent systems? What is the best way to arrive
at new break-through ideas and carry them through
the fire of criticism and past conventional ideas? - Ask your questions. Really, your questions are never dumb. And solve them your own way. (laughs) And don't take "no" for an answer. If they're really dumb,
you'll find out quickly, by trial and error, to see that they're not leading any place. But follow them, and try to
understand things your way. That is my advice. I don't know if it's going to help anyone. - [Lex] No, that's brilliantly put. - There's a lot of inertia
in science, in academia. It is slowing down science. - Yeah, those two words, "your way," that's a powerful thing. It's against inertia, potentially. - [Judea] Against your professor. (Lex laughs) - I wrote "The Book of Why" in order to democratize common sense. - [Lex] Yeah. (laughs) - In order to instill
rebellious spirits in students, so they wouldn't wait until the
professor gets things right. (both laugh) - [Lex] So you wrote the
manifesto of the rebellion against the professor. (laughs) - [Judea] Against the professor, yes. - So looking back at
your life of research, what ideas do you hope ripple
through the next many decades? What do you hope your legacy will be? I already have a tombstone carved. (both laugh) - Oh, boy. - The fundamental law of counterfactuals. That's what it-- it's a simple equation. Put a counterfactual in
terms of a model surgery. That's it, because everything
follows from there. If you get that, all the rest. I can die in peace, and my student can derive all my knowledge by mathematical means. - The rest follows. Thank you so much for talking today. I really appreciate it. - My thank you for being so
attentive and instigating. (both laugh) - We did it. - We did it. - [Lex] The coffee helped. Thanks for listening to this
conversation with Judea Pearl. And thank you to our
presenting sponsor, Cash App. Download it, use code LexPodcast. You'll get $10, and $10 will go to FIRST, a STEM education nonprofit
that inspires hundreds of thousands of young minds to learn and to dream of engineering our future. If you enjoy this podcast,
subscribe on YouTube, give it five stars on Apple
Podcast, support on Patreon, or simply connect with me on Twitter. And now, let me leave you
with some words of wisdom from Judea Pearl. You cannot answer a question
that you cannot ask, and you cannot ask a question
that you have no words for. Thank you for listening, and
hope to see you next time. |
Whitney Cummings: Comedy, Robotics, Neurology, and Love | Lex Fridman Podcast #55 | the following is a conversation with Whitney Cummings she's a stand-up comedian actor producer writer director and recently finally the host of her very own podcast called good for you her most recent Netflix special called can I touch it features in part of robot she affectionately named bear claw but it's designed to be visually a replica Whitney it's exciting for me to see one of my favorite comedians explore the social aspects of robotics and AI in our society she also has some fascinating ideas about human behavior psychology and neurology some of which she explores in her book called um fine and other lies there's truly a pleasure to meet Whitney and have this conversation with her and he went to continue it through texts afterwards every once in a while late at night I'll be programming over a cup of coffee and we'll get a text from Whitney saying something hilarious or weirder yet sending a video Bryan Callen saying something hilarious that's what I know the universe has a sense of humor and he gifted me with one hell of an amazing journey then I put the phone down and go back to programming with a stupid joyful smile on my face if you enjoy this conversation listen to it in these podcasts good for you and follow her on Twitter and Instagram this is the artificial intelligence podcast if you enjoy subscribe on YouTube good five stars on Apple podcasts support on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M a.m. this shows presented by cash app the number one finance I have in the App Store they regularly support Whitney's good-for-you podcast as well I personally used cash app to some money to friends but you can also use it to buy sell and deposit Bitcoin in just seconds cash app also has a new investing feature you can buy a fraction of stock say $1 worth no matter what the stock price is brokerage services are provided by kept investing subsidiary of square and member at CIBC I'm excited to be working with cash app to support one of my favorite organizations called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of stew and in over 110 countries and have a perfect rating and Charity Navigator which means the donated money is used to maximum effectiveness when you get cash app from the App Store or Google Play and use code Lex podcast you get $10 and cash app will also donate $10 to 1st which again is an organization that personally seen inspired girls and boys to dream of engineering a better world this podcast is supported by zip recruiter hiring great people is hard and to me is the most important element of a successful mission driven team I've been fortunate to be a part of and to lead several great engineering teams the hiring I've done in the past was mostly the tools that we built ourselves but reinventing the wheel was painful so zip recruiters a tool that's already available for you it seeks to make hiring simple fast and smart for example codable co-founder Gretchen Abner used the recruiter to find a new game artist to join her education tech company by using zip recruiter screening questions to filter candidates Gretchen found it easier to focus on the best candidates and finally hiring the perfect person for the role in less than two weeks from start to finish zip recruiter the smartest way to hire cy zip recruiters effective for businesses of all sizes by signing up as I did for free at zip recruiter comm slash Lex pod that's zip recruiter calm slash Lex pod and now here's my conversation with Whitney Cummings I have trouble making eye contact as you can tell me too do you know that I had to work on making eye contact because I used to look here do you see that yeah do you want me to do that I'll do this well chief to camera but I used to do this and finally people like I'd be on dates and guys would be like are you looking at my hair like they get it would make people really insecure because I didn't really get a lot of eye contact as a kid it's it's one two three years did you not get a lot of my contact as a kid I don't know I haven't done the soul-searching right so I but there's definitely some psychological is she makes me uncomfortable yeah for some reason want to connect eyes I start to think I assume that you're judging me oh why am we all are all right the POC has to be me and you both do you think robots of the future ones with human level intelligence will be female male genderless or another gender who have not yet created as a society you're the expert at this well I'm gonna ask you the answer I'm gonna ask you questions that maybe nobody knows the answer to or alright and then I just want you to hypothesize as a as a imaginative author director comedian can we just be very clear that you know a ton about this and I know nothing about this but I have thought a lot about yes what I think robots can fix in our society and I mean I'm a comedian it's my job to study human nature to make jokes about human nature and to sometimes play devil's advocate and I just see such a tremendous negativity around robots or at least the idea of robots that it was like oh I'm just gonna take the opposite side for fun for jokes and then I was like oh no I really agree and this devil's advocate argument so I please correct me when I'm wrong about this stuff so so first of all there's there's no right and wrong because we're all I think most of the people working on robotics are really not actually even thinking about some of the big picture things that you've been exploring in fact uh your robot what's-her-name by the we'll go on bear claw what's the genesis of that name by the way would bear claw was I god I don't even remember the joke cuz i black out after I shoot specials but I was writing something about like the pet names that men call women like cupcake sweetie honey you know like we're always named after desserts or something and I was just writing a joke about um if you want to call us a dessert at least pick like a cool dessert you know like bear claw like something cool so I ended up calling her bad luck so do you think the future robots of greater and greater intelligence will like to make them female male would we like to assign them gender or would we'd like to move away from gender and say something more ambiguous I think it depends on their purpose you know I feel like if it's a sex robot it people prefer certain genders you know and I also you know when I went down and explored the robot Factory I was asking about the type of people that bought sex robots and I was very surprised at the answer because of course the stereotype was it's gonna be a bunch of perverts it ended up being a lot of people that were handicapped a lot of people with erectile dysfunction and a lot of people that were exploring their sexuality a lot of people that were thought they were gay but weren't sure but didn't want to take the risk of trying on someone that could reject them and being embarrassed or they were closeted or in a city where maybe that's you know taboo and stigmatized you know so I think that a gendered sex robot that would serve an important purpose for someone trying to explore their sexuality am i into man let me try on this thing first alien to women let me try on this thing first so I think gendered robots would be important for that I think genderless robots in terms of emotional support robots babysitters I'm fine for a genderless babysitter with my husband in the house you know there are places that I think that genderless makes a lot of sense but obviously not in the sex area what do you mean with your husband in the house what does that have to do with the gender of the robot but I mean I don't have a husband but hypothetically speaking I think every woman's worst nightmare is like the hot babysitter you know so I think that there is a common place I think for genderless you know teachers doctors all that kind of it would be very awkward if the first robotic doctor was a guy or the first robotic nurse is a woman you know it's sort of that stuff is still loaded I think that genderless could just take the unnecessary drama out of it and possibility to sexualize them or be triggered by any of that stuff so there's two components to this it's a bear claw so one is the voice and the talking so on and then there's the visual appearance so on the topic of gender and generalists in your experience what has been the value of the physical appearance so what has it added much to the depth of the interaction I mean mines kind of an extenuating circumstance because she is supposed to look exactly like me I mean I spent six months getting my face molded and having you know the idea was I was exploring the concept of Ken robots replace us because that's the big fear but also the big dream in a lot of ways and I wanted to dig into that area because you know for a lot of people it's like they're gonna take our jobs they're gonna replace us legitimate fear but then a lot of women I know are like I would love for a robot to replace me every now and then so it can go to baby showers for me and it can pick up my kids at school and it can cook dinner and whatever so I just think that was an interesting place to explore so her looking like me was a big part of it now her looking like me just adds an unnecessary level of insecurity cuz I got our year ago and she already looks younger than me so weird problem yeah but I think that her looking human was the idea and I think that where we are now please correct me if I'm wrong over human robot resembling an actual human you know is going to feel more realistic than some generic face what you're saying that that robots that have some familiarity like looks similar to somebody that you actually know you be able to form a deeper connection with that was the question that's an open question I don't I don't no it's an interesting or the opposite if then you know me and you're like why I know this isn't real because you're right here maybe it does the opposite we have a very keen eye for human faces and they're able to detect strangeness especially that one has to do with people we've whose faces we've seen a lot of them so I tend to be a bigger fan of moving away completely from faces recognizable faces no just human faces at all in general because I think that's where things get dicey and one thing I will say is I think my robot is more realistic than other robots not necessarily because you have seen me and then you see heard you go oh they're so similar but also because human faces are flawed and asymmetrical and sometimes we forget when we're making things that supposed to look human we make them too symmetrical and that's what makes them stop looking human so because they mold in my symmetrical face she just even if someone didn't know who I was I think she'd look more realistic than most generic ones that didn't have some kind of flaws got it you know cuz they start looking creepy when they're too symmetrical because human beings aren't ya know the flaws is what it means to be human so visually as well but I'm just a fan of the idea of letting humans use a little bit more imagination so just hearing the voice is enough for us humans to then start imagining the visual appearance that goes along with that voice and you don't necessarily need to work too hard on creating the actual visual appearance mm-hmm so there's some value to that when you step into the stereo of actually building a robot that looks like bear claws such a long road of facial expressions of sort of making everything smiling winking yep rolling their eyes all that kind of stuff it gets really really tricky it gets tricky and I think I'm again I'm a comedian like I'm obsessed with what makes us human and our human nature and the nasty side of human nature tends to be where I've you know ended up exploring over and over again and I was just mostly fascinated by people's reactions so it's my job to get the biggest reaction from a group of strangers the loudest possible reaction and I just had this instinct just when I started building her and people go oh and screechin people scream in there I mean I bring around on stage and people would scream and I just to me that was the next level of entertainment getting a laugh I've done that I know how to do that I think comedians were always trying to figure out what the next level is and comedies evolving so much and you know Jordan Peele had just done you know these genius comedy horror movies which feel like the next level of comedy to me and this sort of funny horror of a robot was fascinating to me but I think the thing that I got the most obsessed with was people being freaked out and scared of her and I started digging around with pathogen avoidance and the idea that we've essentially evolved to be repelled by anything that looks human but is off a little bit anything that could be sick or diseased or dead essentially as our reptilian brains way to get us to not Procrit try to have sex with it basically you know so I got really fascinated by how freaked out and scared I mean I would see grown men get upset you get something away from me like angry and it was like you know that what this is you you know but the sort of like you know amygdala getting activated by something that to me is just a fun toy said a lot about our history as a species and what got us into trouble thousands of years ago so it's that it's the deep down stuff that's in our genetics but also is it just are people freaked out by the fact that there's a robot so it's not just the appearance but there's an artificial human anything people I think and I'm just always also fascinated by the blind spots humans have so the idea that you're afraid of that I mean how many robots have killed people how many humans have died at the hands of other humans yeah many more hundreds of millions yet we're scared of that and we'll go to the grocery store and be around a bunch of humans who statistically the chances are much higher that you're gonna get killed by humans so I'm just fascinated by without judgement how irrational we are is the worry is the exponential so it's you know you could say the same thing about nuclear weapons before we dropped on Hiroshima Masaki so the worry that people have is the exponential growth so so it's like oh it's fun and games right now but you know overnight especially if a robot provides value to society we'll put one in every home and then all of a sudden lose track of the actual large-scale impact it has in society and then all sudden gain greater and greater control to where we'll all be you know affect our political system and then affect our decision did not just already happen which ones Oh Russia hacking no offense but hasn't already happened I mean that was like an algorithm of negative things being clicked on more we'd like to tell stories and like to demonize certain people I think nobody understands our current political system or discourse on Twitter the Twitter mobs nobody has a sense not Twitter not Facebook the people running it nobody understands the impact for these algorithms they're trying their best yeah despite what people think they're not like a bunch of lefties trying to make sure that Hillary Clinton gets elected it's more that it's an incredibly complex system that we don't and that's the worry it's so complex and moves so fast that nobody will be able to stop it once it happens and let me ask the question this is a very savage question yeah which is is this just the next stage of evolution as humans and people will die yes I mean that's always happens you know is this is just taking emotion out of it is this basically the next stage of survival of the fittest yeah you have to think of organisms you know what is it mean to be a living organism like it's a smartphone part of your living organism or where we're in relationships with our phones yeah but it's sex through them with them what's the difference between with them and through them but it also expands your cognitive abilities expands your memory knowledge and so on so you're a much smarter person because you have a smart phone in your hand but if what as soon as it's out of my hands we've got big problems because we become sort of so morphed with them with an assembly otic relationship and that's what the er mosque when you're a link is working on trying to increase the bandwidth communication between computers and your brain and so further and further expand our ability as human beings to sort of leverage machines and maybe that's the future the evolution next evolutionary step it could be also that yes we'll give birth just like we give birth to human children right now to give birth day I in other places I think it's a really interesting possibility I'm gonna play devil's advocate I just think that the fear of robots is wildly classist because I mean Facebook like it's easy for us to say they're taking their data okay a lot of people that get employment off of Facebook they are able to get income off of Facebook they don't care if you take their phone numbers and their emails and their data as long as it's free they don't want to have to pay five dollars a month or Facebook Facebook is a wildly Democratic thing forget about the election and all that kind of stuff you know a lot of you know technology making people's lives easier it I find that most elite people are more scared than lower-income people so and women for the most part so the idea of something that's stronger than us and that might eventually kill us like women are used to that like that's not I see a lot of like really wit rich men being like the robots are gonna kill us we're like what's another thing that's gonna kill us you know I tend to see like oh something can walk me to my car at night like something can help me cook dinner or something you know for you know people in underprivileged countries who can't afford eye surgery like you know robot can we send a robot to under-privileged you know places to do surgery where they can't I work with this organization cooperation smile where they do cleft palate surgeries and there's a lot of places that can't do a very simple surgery because they can't afford doctors and medical care and such so I just see and this can be completely naive and should be completely wrong but I feel like we're a lot of people are going like the robots are gonna destroy us humans we're destroying ourselves we're self-destructing robots to me are the only hope to clean up all the messes that we've created even when we go try to clean up pollution in the ocean we make it worse because of the oil that the tankers it's like to me robots are the only solution you know firefighters are heroes but they're limited and how many times they can run into a fire you know so there's just something interesting to me I'm not hearing a lot of like lower income more vulnerable populations talking about robots maybe you can speak that a little bit more there's an idea I think you've expressed that I've heard actually a few female writers and roboticist I've talked to express this idea that exactly you just said which is it just seems that being being afraid of existential threats of artificial intelligence is is a male issue yeah it and I wonder what that is if it because because men have in certain positions like you said it's also classist issue they haven't been humbled by life and so you're always look for the biggest problems to take on around you it's a champagne problem to be afraid of robots most people like don't have health insurance they're afraid they're not gonna be able to feed their kids they can't afford a tutor for their kids like I mean I just think of you know the way I grew up and I had a mother who you know work two jobs had kids we couldn't afford an SAT tutor you know like we could idea of a robot coming and being able to tutor your kids being able to provide childcare for your kids you know being able to come in with cameras for eyes and make sure you know surveillance you know I'm very Pro surveillance because you know I've had security problems and I've been you know we're generally in a little more danger than you guys are so I think that robots are a little less scary to us because we could see them maybe as like free assistance help and protection and then there's sort of another element for me personally which is maybe more of a female problem I don't know I'm just gonna make a generalization I'm happy to be wrong but you know the emotional sort of component of robots and what they can provide in terms of you know there I think there's a lot of people that aren't don't have microphones that I just recently kind of stumbled upon in doing all my research on the sex robots for my stand-up special which there's a lot of very shy people that aren't good at day there's a lot of people who are scared of human beings who you know have personality disorders or grow up in alcoholic homes or struggle with addiction or whatever it is where a robot can solve an emotional problem and so we're largely having this conversation about like rich guys that are emotionally healthy and how scared of robots are we're forgetting about like a huge part of the population who maybe isn't as charming and effervescent and salt mint as you know people like you and Allah mask who these robots could solve very real problems in their life emotional or financial that's a in general really interesting idea that most people in the world don't have a voice it's you've talked about it sort of even the people on Twitter who are driving the conversation you said comments people who leave comments represent a very tiny percent of the population and they're the ones they you know we tend to think they speak for the population but it's very possible on many topics they don't at all and look I and I'm sure there's got to be some kind of legal you know sort of structure in place for when the robots happen you know way more about this than I do but you know for me to just go the robots are bad that's a wild generalization that I feel like is really inhumane in some way you know just after the research I've done like you're gonna tell me that a man whose wife died suddenly and he feels guilty moving on with a human woman or can't get over the grief he can't have a sex robot in his own house well why not who cares why do you care well there's a interesting aspect of human nature so you know we tend to as a as a civilization to create a group that's the other in all kinds of ways right and so you work with animals too you've you're especially sensitive to the suffering of animals let me kind of ask what's your do you think will abuse robots in the future do you think some of the darker aspects of human nature will come out I think some people will but if we design them properly to people that do it we can put it on a record and they can we put we can put them in jail we can find sociopaths more easily you like why is that why is that a sociopathic thing to harm a robot I think look I don't know is enough enough about the consciousness and stuff as you do it I guess it would have to be when they're conscious but it is you know the part of the brain that is you know responsible for compassion the frontal lobe or whatever like people that abuse animals also abuse humans and commit other kinds of crimes like that's it's all the same part of the brain no one abuses animals and then it's like awesome to women and children and awesome to under-privileged you know minorities like it's all so you know we've been working really hard to put a database together of all the people that have abused animals so when they commit another crime you go okay this is you know it's all the same stuff and I think people probably think I'm nuts for the a lot of the animal work I do but because when animal abuse is president another crime is always present but the animal abuse is the most socially acceptable you can kick a dog and there's nothing people can do but then what they're doing behind closed doors you can't see so there's always something else going on which is why I never feel compassion about it but I do think we'll start seeing the same thing with robots the person that kicks them I felt compassion when the kicking the dog robot really pissed me off I know that they're just trying to get the stability right and all that but I do think there will come a time where that will be a great way to be able to figure out if somebody is has like you know antisocial behaviors you kind of mentioned surveillance mm-hmm it's also a really interesting idea of yours he just said you know a lot of people should be really uncomfortable with surveillance yeah and you just said that you know what for me you know there's positives for surveillance I think people behave better when they know they're being watched and I know this is a very unpopular opinion I'm talking about on stage right now I we behave better when we know we're being watched you and I had a very different conversation before we were recording if we behave different you said I'll be on your best behavior and I'm trying to sound eloquent and I'm trying to not hurt anyone's feelings and I'm gonna have a camera right there I'm behaving totally different then we we first started talking you know when you know there's a camera you behave differently I mean there's cameras all over LA at stoplights so that people don't run stoplights but there's not even film in it they don't even use them anymore but it works it works right in and I'm you know working on this thing and stamp out surveillance it's like that's why we invented Santa Claus you know it's the Santa Claus is the first surveillance basically all we have to say to kids is he's making a list and he's watching you and that behaved better I was brilliant you know so I do I do think that there are benefits to surveillance you know I think we all do sketchy things in private and we all have watched weird porn or googled weird things and we don't we don't want people to know about it the our secret lives so I do think that obviously there's we should be able to have a modicum of privacy but I tend to think the people that are the most negative about surveillance of the most high well you should do your thing you're doing bits on it now well I'm just talking in general about you know privacy and surveillance and how paranoid were kind of becoming and how you know I mean it's it's just wild to me that people are like our emails are gonna leak and they're taking our phone numbers like there there used to be a book full of phone numbers and addresses yeah that word they just throw it at your door and we all had a book of everyone's numbers you know is a very new thing and you know I know our migdal is designed to compound sort of threats and you know there's stories about and I think we all just glom on and a very you know tribe away yeah they're taking our data like we don't even know that means we're like well yeah they they you know so I just think that someone's like okay well so what they're gonna sell your data who cares why do you care first of all that bit will kill in China so and I said I said only a little bit joking because a lot of people in China including the citizens despite what people in the West think of as abuse I actually in supported the idea of surveillance mmm-hmm sort of they're not in support of the abuse of surveillance but they're they like I mean the idea of surveillance is kind of like the idea of government it like you said we behave differently in a way it's um like why we like sports there's rules and within the constraints of the rules this is a more stable society and they make good arguments about success being able to build successful companies being able to build successful social lives around a fabric that's more stable when you have a surveillance it keeps the criminals away keeps abusive animals whatever the values of the society with surveillance you can enforce those values butter and here's what I will say there's a lot of unethical things happening with surveillance like I feel the need to really make that very clear I mean the fact that Google is like collecting if people's hands start moving on the mouse to find out if they're getting Parkinson's and then their insurance goes up like that is completely unethical and wrong and I think stuff like that we have to really be careful around so the idea of using our data to raise our insurance rates or you know I heard that they're looking they can sort of predict if you're gonna have depression based on your selfies by detecting micro muscles in your face that you know all that kind of stuff that is a nightmare not okay but I think you know we have to delineate what's a real threat and what's getting spam in your email box that's that's not what you spend your time and energy on focus on the fact that every time you buy cigarettes your insurance is not without you knowing about it on the topic of animals - can we just linger a little bit like what do you think what does it say about our society of the society white abuse of animals that we see in general sort of factory farming is just in general just the way we treat animals of different categories like what what do you think of that what is a better world look like what's what should people think about it in general I think um I think the most interesting thing I can probably say around this that the least emotional cuz I'm actually a very non emotional animal person because it's I think everyone's an animal person it's just a matter of its if it's yours or if you've you know been conditioned to go numb you know I think it's really a testament to what as a species we are able to be in denial about mass denial and mass delusion and how we're able to do human eyes and do base groups you know world war two in a way in order to conform and find protection and the conforming so we are also a species who used to go to Coliseum's and watch elephants and tigers fight to the death we used to watch human beings be pulled apart in the cut there wasn't that long ago we're also species who had slaves and it was socially acceptable by a lot of people people didn't see anything wrong with it so we're a species that is able to go numb and that is able to dehumanize very quickly and make it the norm child labor wasn't that long ago the idea that now we look back and go oh yeah kids we're losing fingers and factories making shoes like someone had to come in and make that you know so I think it just that's a lot about the fact that you know we are animals and we are self-serving and one of the most successful the most successful species because we are able to debase and degrade and essentially exploit anything that benefits us I think the pendulum is gonna swing as being lately like I think we're wrong now kind of like I think we're on the verge of collapse because we are dopamine receptors like we are just I think we're all kind of addicts when it comes to this stuff like we don't know when to stop it's always the buffet like we're the thing that used to keep us alive which is killing animals and eating them now killing animals and eating them is what's killing us in a way so it's like we just can't we don't know when to call it and we don't moderation it's not really something that humans have evolved to have yet so I think it's really just a flaw in our wiring do you think we'll look back at this time as our society is being deeply unethical yeah yeah I think we'll be embarrassed which are the worst parts right now going on is it well I think no in terms of anything what's the unethical thing if we it's very hard to take a step out of it but you just said we used to watch you know there's been a lot of cruelty throughout history what's the cruelty going on now I think it's gonna be I mean pigs are one of the most emotional intelligent animals and they have the intelligence of like a three-year-old and I think we'll look back and be really good there's 30 they use tools I mean they're I think we have this narrative that they're pigs and they're pigs and they're they're disgusting and they're dirty and their bacon is so I think that we'll look back one day and be really embarrassed about that is this for just uh what's it called the factory farming so basically mess because we don't see it if you saw I mean we do have I mean this is probably an evolutionary advantage we do have the ability to completely pretend something's not something that is so horrific that it overwhelms us and we're able to essentially deny that it's happening I think if people were to see what goes on in factory farming and also we're really to take in how bad it is for us you know we're hurting ourselves first and foremost with what what we eat but that's also a very elitist argument you know it's a luxury to be able to complain about meat it's a luxury to be able to not eat meat you know there's very few people because of you know how the corporations have set up meat being cheap you know it's two dollars to buy a Big Mac it's ten dollars to buy a healthy meal you know that's I think a lot of people don't have the luxury to even think that way but I do think that animals in captivity I think we're gonna look back and be pretty grossed out about mammals in captivity whales dolphins I mean that's already starting to dismantle circuses we're gonna be pretty embarrassed about but I think it's really more testament to you know there's just such a ability to go like that thing is different than me and we're better it's the ego I mean it's just we have the species with the biggest ego ultimately well that's what I think that that's my hope for robots is they'll you mentioned consciousness before nobody knows what consciousness is but I'm hoping robots will help us empathize and understand that that there's other creatures out besides ourselves that can suffer that can they can experience the world and that we can torture by our actions and robots can explicitly teach us that I think better than animals can I have never seen such compassion from a lot of people in my life toward any human animal child as I have a lot of people in the way they interact with the robot because I should theirs I think there's something of AI I mean I was on the robot owners chat boards for a good eight months and the main emotional benefit is she's never gonna cheat on you she's never gonna hurt you she's never gonna lie to you she doesn't judge you you know I think that robots help people and this is part of the work I do with animals like I do I find therapy and trained dogs and stuff because there is this safe space to be authentic you're with this being that doesn't care what you do for a living doesn't care how much money you have doesn't care who you're dating doesn't care what you look like doesn't care if you have cellulite whatever you feel safe to be able to truly you know be present without being defensive and worrying about eye contact and being triggered by you no need to be perfect and fear of judgment and all that and robots really can't judge you yet but they can't judge you and I think it really puts people at they're at ease and at their most authentic do you think you can have a deep connection with the robot that's not judging or do you think you can really have a relationship with a robot or a human being that's a safe space or as a tension mystery danger necessary for a deep connection I'm gonna speak for myself and say that I grew up and alcohol Combe I identify as a codependent talked about this stuff before but for me it's very hard to be in relationship with a human being without feeling like I need to perform in some way or deliver in some way and I don't know if that's just the people I've been in a relationship with or or me or my brokenness but I do think this is kind of sound really negative and pessimistic but I do think a lot of our relationships are projection and a lot of our relationships are performance and I don't think I really understood that until I worked with horses and most mutations human is nonverbal right I can say like I love you but that you're not you don't think I love you right where's is with animals it's very direct it's all physical it's all energy I feel like that with robots too it feels very what how I say something doesn't matter my inflection doesn't really matter and you thinking that my tone is disrespectful like you're not filtering it through all of the bad relationships you've been in you're not filtering it through the way your mom talked to you you're not getting triggered you know I find that for the most part people don't always receive things the way that you intend them to or the way intended and that makes relationships really murky so the relationships with animals and relationship with the robots as they are now you kind of implied that that's more healthy I think can you have a healthy relationship with other humans or not healthy and don't like that word but it shouldn't it be you've talked about codependency maybe you can talk about what is called dependency but is that is the the challenges of that the complexity of that necessary for passion for for love between compassion I thought this would be a safe speech I got trolled by rogen powers on this I I am NOT anti passion I think that I've just maybe been around long enough to know that sometimes it's ephemeral and that passion is a mixture of a lot of different things adrenaline which turns into dopamine quarters it's a lot of neuro chemicals it's a lot of projection it's a lot of what we've seen in movies it's a lot of you know it's it's I identify as an addict so for me sometimes passion is like oh this could be bad and I think we've been so conditioned to believe that passion means like your soul mates and I mean how many times have you had a passionate connection with someone and then it was a total train wreck passionate the train wreck comedy track exactly a lot of yawning I mean what's a trainwreck what's uh wise obsession she described this codependency and sort of the idea of attachment / attachment to people who don't deserve that kind of attachment as somehow a bad thing and I think our society says it's a bad thing it probably is a bad thing like a like a delicious burgers a bad thing I don't know but right oh that's a good point I think that your your pointing out something really fascinating which is like passion if you go into it knowing this is like pizza or it's gonna be delicious for two hours and then I don't have to have it again for three if you can have a choice in the passion i define passion is something that is relatively unmanageable and something you can't control or stop and start with your own volition so maybe we're operating under different definitions if passion is something that like you know ruins your real marriages and screws up your professional life and becomes this thing that you're not in control of and becomes addictive I think that's the difference is is it a choice or is it not a choice and if it is a choice then passion is great but if it's something that like consumes you and makes you start making bad decisions and clouds your frontal lobe and it's just all about dopamine and not really about the person and more about the neurochemical we call it sort of the drug the internal drug cabinet if it's all just you're on drugs that's different you know because sometimes you're just on drugs okay so there's a philosophical questions here so would you rather it's interesting for a comedian a brilliant comedian to speak so eloquently about a balanced life I kind of argue against this point there's such an obsession of creating this healthy lifestyle no it's psychologically speaking you know I'm a fan of the idea that you sort of fly high and you crash and die 27 mm hmm there's also possible life and it's not one we should judge because I think there's moments of greatness I talk to Olympic athletes where some of the greatest moments are achieved in their early 20s and the rest of their life is it in the kind of fog of almost of a depression because they based on their physical prowess physical prowess and they'll never say that so they're watching the physical prowess fade and they'll never achieve the kind of height not just physical of just emotion of the max number of neurochemicals yes and he also put your money on the wrong horse that's where I would I would just go like oh yeah if you're doing a job where you peak at 22 yeah the rest of your life is gonna be hard that idea is considering the notion that you want to optimize some kind of but we're all gonna die soon what now you tell me I'm immortalized myself gonna be fine see you're almost like how many oscar-winning movies can I direct by the time I'm 100 how many this and that like but you know there's a night you know it's all life is short speaking I know but it can also come at different you know life is short play hard fall in love as much as you can run into walls I would also go life is short don't deplete yourself on things that aren't sustainable and that you can't keep yeah you know so I think everyone gets dopamine from different places everyone has meaning from different places I look at the fleeting passionate relationships I've had in the past and I don't like I don't have pride in that I think that you have to decide what you know helps you sleep at night for me it's pride and feeling like I behaved with grace and integrity that's just me personally everyone can go like yeah I slept with all the hot chicks in Italy I could and I you know did all the whatever like whatever you value we're allowed to value different here we're talking about Brian Kelly yes Frank Allen has lived his life to the fullest to say the least but I think that it's just for me personally I and this could be like my workaholism or my achievement ISM I if I don't have something to show for something I feel like it's a waste of time or some kind of loss I'm a 12-step program and the third step would say there's no such thing as waste of time and everything happens exactly as it should in whatever that's a way to just sort of keep us sane so we don't grieve too much and beat ourselves up over past mistakes there's no such thing as mistakes did it uh but um I think passion is I think it's so life-affirming and one of the few things that maybe people like us makes us feel awake and seen and we have just have such a high threshold for adrenaline you know I mean you are a fighter right yeah okay so yeah so you have a very high tolerance for adrenaline and I think that Olympic athletes the amount of adrenaline they get from performing it's very hard to follow that it's like when guys come back from the military and they have depression it's like do you miss bullets flying out you get kind of because of that adrenaline which turned into dopamine in the camaraderie I mean there's people that speak much better about this than I do but I just I'm obsessed with neurology and I'm just obsessed with sort of the lies we tell ourselves in order to justify getting neuro chemicals you've done actually quite done a lot of thinking and talking about neurology just kind of look at human behavior through the lens of of looking of how are actually chemically our brain works so what first of all why did you connect with that idea and what have you how is your view of the world changed by considering the the brain is just a machine you know I know it probably sounds really nihilistic but for me it's very liberating to know a lot about neuro chemicals because you don't have to it's like the same thing with like like critics like critical reviews if you believe the good you have to believe the bad kind of thing like you know if you believe that your bad choices were because of your moral integrity or whatever you have to believe your good ones I just think there's something really liberating and going like oh that was just adrenaline I just said that thing because I was adrenalized and I was scared and my amygdala was activated and that's why I said you're an asshole and get out and that's you know I think I just think it's important to delineate what's nature and what's nurture what is your choice and what is just your brain trying to keep you safe I think we forget that even though we security systems and homes and locks on our doors that our brain for the most part is just trying to keep us safe all the time it's why we hold grudges that's why we get angry it's why we get road rage it's why we do a lot of things and it's also when I started learning about neurology I started having so much more compassion for other people you know someone yelled at me being like fuck you on the road I'd be like okay he's producing adrenaline right now because we're all going 65 miles an hour and our brains aren't really designed for this type of stress and he's scared he was scared you know so that really helped me to have more love for people and my everyday life instead of being in fight-or-flight mode but the I think more interesting answer to your question is that I've had migraines my whole life like I've suffered with it really intense migraines ocular migraines ones where my arm would go numb and I just started having to go to so many doctors to learn about it and I started you know learning that we don't really know that much we know a lot but it's wild to go into one of the best neurologists in the world who's like yeah we don't know we don't know we don't know and that fascinated me that's one of the worst pains you can probably have all that stuff and we don't know the source we don't know the source and there is something really fascinating about when your left arm starts going numb and you start not being able to see out of the left side of both your eyes and I remember when the migraines get really bad there it's like a mini-stroke almost and you're able to see words on a page but I can't read them they just look like symbols to me so there's something just really fascinating to me about your brain just being able to stop functioning and I so I just wanted to learn about it study about it I did all these weird alternative treatments they got this piercing in here that actually works I've tried everything and then both my parents had strokes so when both of my parents had strokes I became sort of the person who had to decide what was gonna happen with their recovery which is just a wild thing to have to deal with it you know 28 years old when it happened and I started spending basically all day every day and I see used with neurologists learning about what happened to my dad's brain and why he can't move his left arm but he can move his right leg but he can't see out of that you know and then my mom had another stroke in a different part of the brain so I started having to learn what parts of the brain did what and so that I wouldn't take the behavior so personally and so that I would be able to manage my expectations in terms of their recovery so my mom because it affected a lot of her frontal lobe changed a lot as a person she was way more emotional she was way more micromanage she was forgetting certain things so it broke my heart less when I was able to know oh yeah will destroy hit this part of the brain and that's the one that's responsible for short-term memory and that's responsible for long-term memory set it up and then my brother just got something called viral encephalitis which is an infection inside the brain and so Wow it was kind of wild that I was able to go oh I know exactly what's happening here and I know you know so um so that's allows you to have some more compassion for the struggles that people have but does it take away some of the magic for some of the from this some of the more positive experiences in life sometimes and I don't I don't I'm such a control addict that you know I think our biggest if someone like me my biggest dream is to know why someone's doing that's what stand-up is is just trying to figure out why or that's what writing is that's what acting is that's what performing is it's trying to figure out why someone would do something as an actor you get a piece of you know material and you go this person why would he say that why would he pick up that cup why would she walk over here it's really why why would why so I think neurology is if you're trying to figure out human motives and why people do what they do it'd be crazy not to understand how neuro chemicals motivate us I also have a lot of addiction in my family and hardcore drug addiction and mental illness and in order to cope with it you really have to understand that borderline personality disorder schizophrenia and drug addiction so I have a lot of people I love that suffer from drug addiction and alcoholism and the first thing they started teaching you is it's not a choice these people's dopamine receptors don't hold dopamine the same ways yours do their frontal lobe is underdeveloped like you know and that really helped me to navigate dealing loving people that were addicted to substances I want to be careful with this question but how much money do you have how much can I borrowed okay know is how much control how much despite the chemical imbalances or the biological limitations that each of our individual myself how much mind-over-matter is there so through things and I've known people with with clinical depression and so it's it's always a touchy subject to say how much they can really help but very what can you yeah what what can because you you've you've talked about codependency you talked about issues the your struggle through and nevertheless you choose to take a journey of healing and so on so that's your choice that's your actions so how much can you do to help fight the limitations of the your chemicals in your brain that's such an interesting question I don't think I'm at all qualified to answer but I'll say what I do know and really quick just the definition of codependency I think a lot of people think of codependency is like two people that can't stop hanging out you know or like you know that's not totally off but I think for the most part my favorite definition of codependency is the inability to tolerate the discomfort of others you grew up in an alcoholic home you grow up around mental illness you grow up in chaos you have a parent that's a narcissist you basically are wired to just people please worry about others be perfect walk on eggshells shape-shift to accommodate other people so codependency is a very active wiring issue that you know doesn't just affect your romantic relationships it affects you being a boss it affects you in the world online you know you get one negative comment and it throws you for two weeks you know it also is linked to eating disorders and other kinds of addictions so it's it's it's a very big thing and I think a lot of people sometimes to only think that it's in a romantic relationship so I always feel the need to say that and also one of the reasons I love the idea of robots so much because you don't have to walk on eggshells around them you don't have to worry they're gonna get mad at you yet but you there's no codependence are hypersensitive to the needs and moods of others and it's very exhausting it's depleting just a well one conversation about where we're gonna go to dinner is like you want to go get Chinese food we just had Chinese food well wait are you mad well no I didn't mean it's just like that codependents live in this everything means something and humans can be very emotionally exhausting why did you look at me that way what are you thinking about what was that why'd you check your phone it's just this it's a hypersensitivity that can be incredibly time-consuming which is why I love the idea of robots just subbing in even I've had a hard time running TV shows and stuff because even asking someone to do something I don't want to come off like a bitch I'm very concerned about what other people think of me how I'm perceived which is why I think robots will be very beneficial for for codependence by the way just a real quick tangent that skill or flaw whatever you want to call it is actually really useful for if you ever do start your own podcast for interviewing because you're now kind of obsessed about the mindset of others and it makes you a good sort of listener and talker with so I think what's your name from NPR talked about Terry Gross talked about having that so yeah oh I don't get that at all I mean you have to put yourself in the mind of the person you're spoken to just in terms of yeah I am starting a podcast and the reason I haven't is because I'm codependent I'm too worried it's not gonna be perfect yeah so a big codependent adage is perfectionism leads to procrastination which leads to paralysis so how do you sorry take a million tangents how do you survive and social media gives you exceptionally active but by the way I took you on a tangent and didn't answer your last question about how much we can control I want you to yeah we'll return it or maybe night the answer is we can but you know one of the things that I'm fascinated by is you know the first thing you learn when you go into 12-step programs or addiction recovery I mean this is you know genetics loads the gun environment pulls the trigger and there are certain parts of your genetics you cannot control I come from a lot of alcoholism I come from you know a lot of mental illness there's certain things I cannot control and a lot of things that maybe we don't even know yet what we can and can't because of how little we actually know about the brain but we also talk about the warrior spirit and there are some people that have that warrior spirit and we don't necessarily know what that engine is whether it's you get dopamine from succeeding or achieving or martyring yourself or or that tension you get from growing so a lot of people were like oh this person can edify themselves and overcome but if you're getting attention from improving yourself you're going to keep wanting to do that so that is something that helps a lot of in terms of changing your brain if you talk about changing your brain to people and talk about what you're doing to overcome set obstacles you're going to get more attention from them which is going to fire off your reward system and then you're gonna keep doing it see yeah so you can leverage that momentum so this is why in any toe step program you go into a room and you talk about your progress because then everyone claps for you and then you're more motivated to keep going so that's why we say you're only as sick as the secrets you keep because if you keep things secret you know there's no one going and guiding you to go in a certain direction it's based on right we're sort of designed to get approval from the tribe or from a group of people because our brain you know translates it to safety so in that case the tribe is a positive one that helps you go this direction so that's why it's so important to go into a room and also say hey I wanted to use drugs today and people go hmm they go me too and then feel less alone and you feel less like you're you know have been castigated from the pack or whatever and then you say and I do haven't you get a chip when you haven't drank for 30 days or 60 days or whatever you get little rewards so talking about a pack that's not at all healthy or good but in fact is often toxic social media so you're one of my favorite people on Twitter and Instagram to uh sort of just both the comedy and the insight and just fun how do you prevent social media from destroying your mental health I haven't I haven't it's the next big epidemic isn't it I don't think I have I don't I don't think it's moderation the answer what maybe but you can do a lot of damage in a moderate way I mean I guess again it depends on your goals you know and and I think for me the way that my addiction to social media I'm happy to call it an addiction I mean and I define as an addiction because it stops being a choice there are times I just reach over and I'm like that was that was weird Wow is weird I'll be driving sometimes my bag oh my god my arm just went to my home you know I can put it down I can't take time away from it but when I do I get antsy yeah I get restless irritable and discontent I mean that's kind of the definition isn't it so I think by no means do I have a healthy relationship with social media I'm sure there's a way to but I think I'm especially a weirdo in this space because it's easy to conflate is this work is this I can always say that it's for work right you know but I mean you're don't you get the same kind of thing as you get from when a roomful of people laughs your jokes I mean I see especially the way you do Twitter it's an extension of your comedy in a way so a big break from Twitter though a really big break I took like six months off or something for a while because it was just like it seemed like it was all kind of politics and it was just a little bit it wasn't giving me dopamine because there was like this weird a lot of feedback so I had to take a break from it and then go back to except feel like I didn't have a healthy relationship I ever tried the I don't know if I believe him but Joe Rogan seems to not read comments have you and he's one of the only people at the scale like a year level who at least claims not to read so like because you and him swim in this space of tense ideas yeah they get get get the toxic folks growled up I think rogue I don't I don't know I don't mmm I think he probably looks at YouTube like the likes and that you know I think if something's if he doesn't know I don't know I'm sure he would tell the truth you know I'm sure he's got people that look at them and he's like disgusted great or I don't you know like I'm sure he gets it you know I I can't picture him like in the weeds on know for sure I mean I nameste she's saying that just it's it's uh it's a to feedback yeah we're just a feedback I mean you know look like I think that our brain is designed to get intel on how we're perceived so that we know where we stand right that's our whole deal right as humans we want to know where we stand we walk into a room and we go who's the most powerful person in here I gotta talk to him and get in their good graces it's just were designed to rank ourselves right and constantly know our rank and social media because of you can't figure out your rank with 500 million people you get small you know cert brain is like what's my rank what's my and especially for following people I think the the big the the interesting thing I think I may be be able to able to say about this besides my speech impediment is that I did start muting people that ranked wildly higher than me because it is just stressful on the brain to constantly look at people that are incredibly successful so you keep feeling bad about yourself you know I think that that is like cutting to a certain extent just like look at me looking at all these people that have so much more money than me and so much more success than me it's making me feel like a failure even though I don't think I'm a failure but it's easy to frame it so that I can feel that but yeah that's really interesting especially if they're close to like if there are other comedians like that or whatever that's that's it's really disappointing to me I do the same thing as well so other successful people they're really close to what I do it I don't know I I wish I could just admire ya and for it not to be a distraction but that's why you are where you are cuz you don't just didn't Meyer you're competitive and you want to win so it's also the same thing that bums you out when you look at this is the same reason you are where you are so that's why I think it's so important to learn about neurology and addiction because you're able to go like oh this same instinct so I'm very sensitive and I and I sometimes don't like that about myself that I'm like well that's the reason I'm able to write good stand-up and that's the reason and that's reason I'm able to be sensitive to feedback and go that joke should have been better I can make that better so it's a kind of thing where it's like you have to be really sensitive in your work in the second you leave you've got to be able to turn it off it's about developing the muscle being able to know when to let it be a superpower when it's gonna hold you back and be an obstacle so I try to not be in that black and white of like you know being competitive is bad or being jealous of someone just to go like oh there's that thing that makes me really successful in a lot of other ways but right now it's making me feel that well I'm kind of looking to you because your ear basically a celebrity the famous sort of world-class comedian and so I feel like you're the right person to be one of the key people to define what's the healthy path forward with social media so I because we're all trying to figure it out now and it's a I'm curious to see where it involves and I think you're at the center of that so likely you know there's you know trying to leave Twitter and then come back how can I do this in a healthy way you mean you have to keep trying exploring it because it's being I have a couple answers I think you know I hire a company to do some of my social media for me you know so it's also being able to go okay I make a certain amount of money by doing this but now let me be a good businessperson and say I'm gonna pay you this amount to run this for me so I'm not 24/7 in the weeds hash tagging and responding and just it's a lot to take on it's a lot of energy to take on but at the same time part of what I think makes me successful in social media if I am is that people know I'm actually doing it and then I am an engaging and I'm responding and developing a personal relationship with complete strangers so I think you know figuring out that balance and really approaching it as a business you know that's what I try to do it's not dating it's not you know I try to just be really objective about okay here's what's working here's what's not working and in terms of taking the break from Twitter this is a really savage take but because I don't talk about my politics publicly being on Twitter right after the last election was not gonna be beneficial because there was gonna be had to take a side you had to be political in order to get any kind of retweets or likes and I just wasn't interested in doing that because you were gonna lose as many people as you were gonna gain and it was gonna all complain in the wash so I was just like the best thing I can do for me business-wise is to just abstain you know and you know the robot I joke about her replacing but she does do half of my social media you know yeah because it's I don't want people to get sick of me I don't want to be redundant there are times when I don't have the time or the energy to make a funny video but I know she's gonna be compelling and interesting and that's something that you can't see every day you know of course the the the humor comes from Europe I mean the cleverness the wit the humor comes from you when you film the robot that's kind of the trick of it I mean the the robot is not quite there to making to do anything funny the absurdity is revealed through the filmmaker in that case where whoever is interacting not through the the actual robot you know being who she is let me sort of love okay how do what is it they have what is it well first an engineering question I know I know you're you're not an engineer but how difficult do you think is it to build an AI system that you can have a deep fulfilling monogamous relationship with sort of replace the human human relationships that we value I think anyone can fall in love with anything you know like how often have you looked back in someone like I ran into someone the other day that I was in love with then I was like hey it was like there was nothing there no there was nothing there like do you know like where you're able to go like oh that was weird oh honey you know I were able to me as from a distant past or something yeah when you're able to go like I can't believe we had an incredible connection and now it's just I do think that people will be in love with robots probably even more deeply with humans because it's like when people mourn their animals when their animals die they're always it's sometimes harder than mourning a human because you can't go well he was kind of an asshole but like he didn't pick me up from school you know it's like you're able to get out of your grief a little bit you're able to kind of be oh he was kind of judgmental or she was cut you know with a robot it's there's something so pure about an innocence and fish and childlike about it that I think it probably will be much more conducive to a narcissistic love for sure at that but it's not like well he cheated us she can't cheat she can't leave you she can't you know well a bear claw leaves your life and maybe a new version or somebody else will enter there will you miss bear claw for guys that have these sex robots they're building a nursing home for the bodies well that are now rusting because they don't want to part with the bodies because they have such an intense emotional connection to it I mean it's kind of like a car club a little bit you know like it's it you know but I'm not saying this is right I'm not saying it's cool it's weird it's creepy but we do anthropomorphize things with faces and we do develop emotional connections to things I mean we're there certain have you ever tried to like throw it I can't even throw away my teddy bear from when I was a kid it's a piece of trash and it's upstairs like it's like why can't I throw that away it's bizarre you know and there's something kind of beautiful about that there's something it gives me hope in in humans because I see humans do such horrific things all the time and maybe I'm too I see too much of it frankly but there's something kind of beautiful about the way we're able to have emotional connections to objects which you know a lot of I mean it's kind of specifically I think Western right that we don't see objects as having Souls like that's kind of specifically us but um I don't think it's so much that we're objectifying humans with these sex robots were kind of humanizing objects right so there's something kind of fascinating in our ability to do that because a lot of us don't humanize humans so it's just a weird little place to play in and I think a lot of people I mean a lot of people will be marrying these things is my guess so you've asked the question let me ask it of you so what is love you have a bit of a brilliant definition of love as being willing to die for someone we who you yourself want to kill so that's that's kind of fun first of all that's brilliant that's a really good definition I think you'll stick with me for a long time is this how little of a romantic I am a plane went by when you said that and my brain is like you're gonna need to rerecord that and I want you to get into post and then not be able to use and I'm a romantic as a mom I actually I cannot be conscious of the fact that I heard the plane and it made me feel like how amazing it is that we live in a world planes and I just why haven't we fucking evolved past planes and why can't they make them quieter yeah yeah this my definition of love what what yeah what's your producing dopamine consistent output of oxytocin with the same person dopamine is a positive thing what about the negative what about the fear and the insecurity the longing anger all that kind of stuff I think that's part of love you know I think you don't I think that love brings out the best in you but it also if you don't get angry upset it's you know I don't know I think that that's that's part of it I think we have this idea that love has to be like really you know placid or something I only saw stormy relationships growing up so I don't I don't have a judgment on how a relationship should look but I do think that this idea that love has to be eternal is is really destructive is really destructive and self-defeating and a big source of stress for people I mean I'm still figuring out love I think we all kind of are but I do kind of stand by that definition and I think that uh I think for me love is like just being able to be authentic with somebody it's very simple I know but I think for me it's about not feeling pressure to have to perform or impress somebody just feeling truly like accepted unconditionally by someone although I do believe love should be conditional that might be a hot take I think everything should be conditional I think if someone's behavior I don't think love should just be like I'm in love with you now behave however you want forever this is unconditional I think love is a daily action it's not something you just like get ten you're on and then get to behave however you want because we said I love you 10 years ago it's a daily it's a verb well there's some things there you see if you make it if you explicitly make it clear that it's conditional it takes away some of the magic of it so there's some stories we tell ourselves that we don't want to make explicit about love I don't know maybe that's the wrong way to think of it maybe you want to be explicit in relationships so something love is a business decision like I do in a good way yeah I think that love is not just when you're across from somebody it's when I go to work can I focus do I am I worried about you am I stressed out about you am I you're not responding to me you're not reliable like I think that being in a relationship the kind of love that I would want is the kind of relationship where when we're not together it's not draining me causing me stress making me worry you know and sometimes passion that word you know we'd get murky about it but I think it's also like I can be the best version of myself when the person's not around and I don't have to feel abandoned or scared or any of these kind of other things so it's like love you know for me I think is I think it's a flow Barre quote and I'm gonna butcher it but I think it's like be you know boring in your personal life so you could be violent and take risks in your professional life is that it I got it wrong something like that but I do think that it's being able to align values in a way to where you can also thrive outside of the relationship some of the most successful people I know are sort of happily married and have kids and so on it's it's always funny boring boring is okay foreign is serenity and it's funny how that those elements actually make you much more productive I don't understand the I don't think relationships should drain you and take away energy that you could be using to create things that generate pride okay did you say your relationship of love yet have you said you're really your definition of love my definition of love no I did not say it we're out of time do what when you have when you have a podcast maybe you can invite me on alone oh no I already did you're doing it we've already talked about this and because I also have codependency I have to say yes yeah actually what the I wondered whether when I I asked if we could talk today after sort of doing more research and reading some of your book I start to wonder did she just feel pressured to say yes no I actually because I am putting on but I've been recovered for codependents so I actually do I don't do anything I don't want to do you really you got anywhere saying no but good November I moved it from 1 to 2 yeah just yeah I don't do anything I don't want to do yeah you're ahead of me in that okay so do you think about your mortality yes it is a big part of how I was able to sort of like kickstart my codependence recovery my dad passed a couple years ago and when you have someone close to you in your life died everything gets real clear in terms of how were a speck of dust who's only here for a certain amount of time what do you think is the meaning of it all like what the speck of dust what what's maybe in your own life what's the goal the purpose of your existence is there one well you you're exceptionally ambitious you've created some incredible things in different disciplines we're all just managing our terror because we know we're gonna die so we create and build all these things and rituals and religions and you know robots and whatever we need to do to just distract ourselves from imminent rotting rotting yeah we're all dying and you know III you know I got very into terror management theory when my dad died and and it resonated it helped me and everyone's got their own religion or sense of purpose or thing that distracts them from the horrors of being what's terror management theory terror management is basically the idea that since we're the only animal that knows they're gonna die we have to basically distract ourselves with awards and achievements and games and sperm whatever just in order to distract ourselves from the terror we would feel if we really processed the fact that we could not only we are gonna die but also could die at any minute because we're only superficially at the top of the food chain and you know we technically were the top of the food chain if we have houses and guns and stuff machines but if me and a lion are in the woods together I'm it's most things could kill us I mean a bee can kill some people like something this big can kill a lot of humans like you know so it's basically just to manage the terror that we all would feel if we were able to really be awake because we're mostly zombies right new job school religion zoo so go to sleep drink through the football the relationship don't mean love but you know we're kind of just like trudging along like zombies for the most part and then I think that fear of death as some motivation yes well I think I speak for a lot of people in saying that I can't wait to see what your terror creates in the in the next few years I'm a huge fan wouldn't you thank you so much for talking to thanks for listening to this conversation with Whitney Cummings and thank you to our presenting sponsor cash app download it and use code let's podcast you'll get ten dollars and ten dollars will go to first stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on youtube give it five stars an apple podcast supported on patreon or connect with me on Twitter thank you for listening and hope to see you next time you |
Ray Dalio: Principles, the Economic Machine, AI & the Arc of Life | Lex Fridman Podcast #54 | the following is a conversation with Ray Dalio he's the founder co-chairman and Co chief investment officer of Bridgewater associates one of the world's largest and most successful investment firms that is famous for the principles of radical truth and transparency that underlies culture Ray is one of the wealthiest people in the world with ideas that extend far beyond the specifics of how he made that wealth his ideas that are applicable to everyone are brilliantly summarized in his book principles there are also even further condensed on several other platforms including YouTube where for example the 30 minute video titled how the economic machine works is one of the best educational videos I personally have ever seen on YouTube once again you may have noticed that the people I've been speaking with are not just computer scientists but philosophers mathematicians writers psychologists physicists economists investors and soon much more to me AI is much bigger than deep learning bigger than computing it is our civilizations journey into understanding the human mind and creating echoes of it in the machine that journey includes the mechanisms of our economy of our politics and the leaders that shape the future of both this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars on Apple podcast support on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M a.m. this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin most Bitcoin exchanges take days for a bank transfer to become investable through cash up it takes seconds cash app also has a new investing feature you can buy a fraction of stock which to me is a really interesting concept so you can buy $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations that many of you may know and have benefited from called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and Charity Navigator which means the donated money is used to maximum effectiveness when you get cash app from the App Store or Google Play and use code Lex podcast you get ten dollars in cash app will also donate ten dollars the first which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with Ray Dalio truth or more precisely an accurate understanding of reality is the essential foundation of any good outcome I believe you've said that let me ask an absurd sounding question at the - South Col level so what is truth when you're trying to do something different than everybody else is doing and perhaps something that has not been done before how do you accurately analyze the situation how do you accurately discover the truth the nature of things almost the way you're asking the question implies that truth and newness have nothing or almost at odds and I just want to say that I don't think that that's true right so what I mean by truth truth is you know was a reality how does the reality work and so if you're doing something new that has never been done before which is exciting and I like to do the way that you would start with that is experimenting on what are the realities and the premises that you're using on that and how to stress test those types of things I think what you're talking about is instead the fact of how do you deal with something that's never been done before and deal with the Associated probabilities and so I I think in that don't let something that's never been done before stand in the way of you doing that particular thing you have a because almost the only way that you understand what truth is is through experimentation and so when you go out and experiment you're going to learn a lot more about what truth is but the essence of what I'm saying is that when you take a look at that use truth that find out what the realities are as a foundation do the independent thinking do the experimentation to find out what's true and change and keep going after that so I think that the way that when you're thinking about it the way you're thinking about it that almost implies that you're you're letting people almost say that they're reliant on what's been discovered before to find out what's true and what's been discovered before is often not true right conventional view of what what is true is very often wrong it'll go in ups and downs and you know I mean there are fads and okay this thing it goes this way and that way and so definitions of truths that are conventional are not the thing to go by how do you know the thing that has been done before it might succeed its to do you whatever homework that you have in order to try to get a foundation and then to go into worlds of not knowing and you go into the world of not knowing but not stupidly not naively you know you go into that world of not knowing and then you do experimenting and you learn what truth is and what's possible through that process I describe it as a five step process the first step is you go after your goals the second step is you identify the problems that stand in the way of you getting to your goals the third step is you diagnose those to get at the root cause of those then the fourth step is then now that you know the exact truth calls you get you design a way to get around those and then you follow through and do the designs you set out to do and it's the experimentation I think that what happens to people mostly is that they try to decide whether they're going to be successful or not ahead of doing it and they don't know how to do the process well because the nature of your questions are along those lines like how do you know well you don't know but a practical person who is also used to making dreams happen knows how to do that process I've given personality tests to shapers so the person what I mean by a shaper is a person who can take something from visual as visualization they have an audacious goal and then they go from visualization to actualization building it out that includes Elon Musk I gave him the personality tests I'm giving it to Bill Gates and give it to many many such shapers and they know that process that I'm talking about they experience it which is a process essentially of knowing how to go from an audacious but not in a ridiculous way not a dream and then to do that learning along the way that allows them in a very practical way to learn very rapidly as they're moving toward that goal so the the call to adventure the adventure starts not trying to analyze the probabilities of the situation but using what instinct how do you dive in so let's talk what it is it is being a it's simultaneously being a dreamer and a realist it's to know how to do that well the pole comes from a pole to adventure for whatever reason I can't tell you how much of its genetics and how much its environment but there's a early on it's exciting that notion is exciting being creative is exciting and so one feels that then one gets in the habit of doing that okay how do I know how do I learn very well and then how do I imagine and then how do I experiment to go from that imagination so it's that process that one and then one more one does it the one more the better one becomes that you mentioned shapers you know musk Bill Gates what who are the shapers do you find yourself thinking about when you're constructing these ideas the ones that define the archetype of a shaper for you well as I say a shaper for me is somebody who comes up with a great visualization usually a really unique visualization and then actually builds it out and makes the world different changes the world in that kind of a way so when I look at it Marc Benioff with Salesforce Chris Anderson with Ted Mohamed Younis with social enterprise in philanthropy Canada and Harlem Children's Zone there are all domains have shapers who have the ability to visualize and make extraordinary things happen what are the commonalities in some of them the commonalities our first of all the excitement of something new that call to adventure and and again that practicality the capacity to learn it and the capacity then they're they're able to be in many ways full rage that means they're able to go from the big big picture down to the detail so let's say for example Elon Musk he describes he gets a lot of money from selling PayPal his interest in PayPal he said why isn't anybody going to Mars or out of space what we're gonna do if the planet goes to hell and how do i how do we going to get that and nobody's paying attention to that he doesn't know much about it he then reads and learns and so on says I'm gonna take ok half of my money and I'm gonna put it in there and I'm gonna do this thing and he learns a blood level about and he's got creative okay that's one dimension and so he and gave me the keys to his car was one just early days into and Tesla and he then points out the details okay if you push this button here it's this the detail death so he's simultaneously talking about the big the big big big picture okay windows humanity going to abandon the panic but he will then be able to take it down into the detail so he can go let's call it helicoptering he can go up he can go down and see things at those types of perspective and they're using it with the other shapers and that's a common thing that they can do that another important difference that they have in mind is how they deal with people i mean meaning there's nothing more important than achieving the mission and so what they have in common is that there's a test that I give these personality tests because they're very helpful for understanding people and so I gave it to all these shapers and one of the things in workplace inventory test is this test and it has a category called concern for others whatever it's a they were all having concern for others this includes Mohan Yunis who invented microfinance social enterprise impact investing is Muhammad Yunus received the Nobel Peace Prize for this Congressional Medal of Honor one of the Fortune determined one of the 10 greatest entrepreneurs of our time he's built all sorts of businesses to give back money and social enterprise a remarkable man he has nobody that I know practically could have more concern for others I'm he lives a life of a saint I mean very modest lifestyle and he puts all his money into trying to help others and he tests low on the courts called concern for others because what it really those the questions under that are questions about conflict to get at the mission so they all Geoffrey Canada change Harlem Children's Zone and developed that to take children in Harlem and get them well taken care of not only just in their education but their whole lives harmless in also concern for others what they mean is that they can see whether though individuals are performing at a level that an extremely high level that's necessary to make those dreams happen so when you think of let's say Steve Jobs was famous for being you know difficult with people and so on and I don't know Steve Jobs so I can't speak personally to that but he's comments on Dae players and if you have 80 players if you put in B players pretty soon you'll have C players and so on that is a common element of them holding people to high standards and not letting anybody stand in the way of the the mission what do you think about that kind of idea is sorry to pause on that for a second that the a B and C players and the importance of so when you have a mission to really only have a players and be sort of aggressively filtering for that yes but I think that there are all different ways of being a players and I think in what a great a great team you have to appreciate all the differences in ways of being a players ok yes that's the first thing and then you always have to be super excellent to my opinion you always have to be really excellent people with people to help them understand each other themselves and get in sync with them about what's true about them and their circumstances now they're doing so that they're having a fabulous personal development experience at the same time as you're dealing with them so when I say that they're all different ways this is one of the than qualities you asked me the one of the qualities so one of the third qualities that I would say is to know how to deal well with your not knowing and to be able to get the best expertise so that you're a great Orchestrator of different ways so that the people who are really really successful unlike most people believe that they're successful because of what they know they're at even more successful by being able to effectively learn from others and tapping into the skills of people who see things different from them brilliant so how do you when they're that personality being first of all open to the fact that there's other people see things differently than you and at the same time have supreme confidence in your vision is there just a psychology of that do you see attention there between the confidence and the open-mindedness and now it's funny because I think we grow up thinking that there's a tension there right that there's a confidence and and the more confidence that you have there's attention with the open-mindedness and not being sure okay confident and accurate are almost negatively correlated many people they're extremely confident and they're often inaccurate and so I think one of the greatest tragedies of people is not realizing how those things two go together because instead it's really that by saying I know a lot and how do I know I'm still not wrong and how do I take that the best thinking of all available to me and then raise my probability of learning all these people think for them selves okay I mean meaning they're smart but they take in like vacuum cleaners they take in ideas of others they stress test their ideas with others they assess what comes back to them in the form of other thinking and they also know what they're not good at and what other people who are good at the things that they're not good at they know how to get those people and be successful all around because nobody has enough knowledge in their heads and that I think is one of the great differences Sutton the reason my company has been successful in terms of this is because of an idea meritocratic decision-making a process by which you can get the best ideas you know what's an idea meritocracy an idea meritocracy is to get the best ideas that are available out there and to work together with other people and the team to achieve that it's an incredible process that you describe in several places to arrive at the truth but apologize from romanticizing the notion blaming linger on it just having enough self belief you don't think there's a self delusion there that's necessary especially in the beginning you talk about in the journey maybe the trials or the abyss do you think there is value to deluding yourself I think what you're calling delusion is a bad word yes for uncertainty okay so I mean in other words because we keep going back to the question how would you know and all of these things know I think that delusion is not going to help you that you have to find out truth okay to deal with uncertainty not saying aunt listen I have this dream and I don't know how I'm going to get that dream I mentioned in my book principles and describe the process in a more complete way than we're gonna be able to go here but what happens is I say you form your dreams first and you can't judge whether you're going to achieve those dreams because you haven't learned the things that you're going to learn on the way toward those dreams okay so if that isn't delusion I wouldn't use delusion I think you're over emphasizing the importance of knowing whether you're going to succeed or not get rid of that okay if you can get rid of that and say okay no I can have that dream but I'm so realistic in the notion of finding out I'm curious I'm a great learner I'm a great experimenter along the way you'll do those experiments which will teach you more truths and more learning about the reality so that you can get your dreams because if you still live in that world of delusion okay and you think your lusion is helpful no the delusion isn't don't confuse delusion with not knowing yes but nevertheless so if we look at the abyss we can look at your own that you describe it's difficult psychologically for people so in many people quit many people choose a path that is more comfortable and I mean that the the heartbreak of that you know breaks people so if you have the dream and then there's this cycle of learning setting a goal and so on what's your value for the psychology of just being broken by these difficult moments well that's that that's classically the defining moment it's almost like evolution taking care of okay now you're you crash you're in the abyss oh my god that's bad and then the question is what do you do and it sorts people okay and that's what that's some people get off the field and they say oh I don't like this and so on and some people learn and they have decay and they have a metamorphosis and it changes their approach to learning it the number one thing it should give them is uncertainty you should take an audacious dreaming guy who wants to change the world crash okay and then come out of that crashing and saying okay I can be audacious and scared that I'm going to be wrong at the same time and then how do I do that because that's the key when you don't lose your audaciousness and you going after your big goal and at the same time you say hey I'm worried that I'm gonna be wrong you gain your radical open-mindedness that allows you to take in the things that allows you to go to the next level of being successful so your own process I mean you've talked about it before but it'll be great if you can describe it because our darkest moments are perhaps the most interesting so your own and what the prediction of the another Depression economic depression highest apologize economic depression can you talk to what you were feeling thinking planning and strategizing in those moments yeah that was that was my biggest moment okay building my little company this is in 1981-82 I had calculated that American banks had given a lot more money to lent a lot more money to Latin American countries than those countries were going to pay back and that they would have a debt crisis and that this had said the economy tumbling and that was an extremely controversial point of view then it started to happen and it happened in Mexico default that in August 1982 I thought that there was going to be a an economic collapse that was going to follow because there was a series of the other countries it was just playing out it as I had imagined and that well it couldn't have been more wrong that was the exact bottom in the stock market because central bank sees monetary policy blah blah blah and I couldn't have been more wrong and I was very publicly wrong and all of that and I lost money for me and I lost money for my clients and I was I only had a small company then but I had these were close people I had to let them go I was down to me as the last person that I I was so broke I had to borrow $4,000 from my dad to help to pay for my family bills very painful and at the same time I would say it definitely was one of the best things that ever happened to me maybe the best thing for him happened to me because it changed my approach to decision making it's what I'm saying in other words I kept saying okay how do I know whether I'm right how do I know what I'm not wrong it gave me that and now and it didn't give up by audaciousness because I was in a position what am I going to do am I gonna go down back put on a tie go to Wall Street and D and just do those things no I can't bring myself to do that so I'm in a juncture how do I deal with my risk and how do I deal with that and it tells me how to deal with my uncertainties and that taught me for example a number of techniques first to find the smartest people I could find who disagreed with me and to have quality disagreement I learned the art of thoughtful disagreement I learned how to produce diversification I learned how to do a number of things that's is what led me to create an idea meritocracy in other words person by person I hired them and I wanted the smartest people who would be independent thinkers who would disagree with each other and me well so that we could be independent thinkers to go off to produce those audacious dreams because you have to be an independent thinker to do that and to do that not independently of the consensus independently of each other and then work ourselves through that because who know whether you're gonna have the right answer and by doing that then that was the key to our success and the things that I want to pass along to people the reason I'm doing this podcast with you is you know I'm 70 years old and that is a magical way of a achieving success if you can create an idea meritocracy it's it's so much better in terms of achieving success and also quality relationships with people but that's what that experience gave me so if we can look around a little bit longer the idea of an idea meritocracy it's fascinating but especially because it seems to be rare not just in companies but in society so there's a lot of people on Twitter and public discourse and politics and so on that are really stuck in certain sets of ideas whatever they are so when you're confronted with it with an idea that said that's different than your own about a particular topic what kind of process do you go through mental are you arguing through the idea with the person sort of present is almost like a debate or do you sit on it and consider the world sort of empathetically if this is true then what is that war look like does that world make sense and so on so what's the process of considering those conflicting ideas I'm gonna answer that question but after saying first imposed implicit in your question is it's not common okay what's common produces only common results okay so don't judge yes anything that is good based on whether it's common because you're on its only going to give you common results if you want unique you have a unique approach yes okay and so that art of thoughtful disagreement is the is the capacity to hold two things in your mind at the same time the G I think this makes sense and then saying I'm not sure it makes sense and then try to say why does it make sense and then to triangulate with others so if I'm having a discussion like that and I work myself through and I'm not sure then I have to do that in a good way so I always give attention for example what let's start off what does the other person know relative to what I know so if a person has a higher expertise or things I'm much more inclined to ask questions I'm always asking questions if you want to learn you're asking questions you're not arguing okay you're taking in your assessing when it comes in to you does that make sense so you're learning something are you getting epiphanies and so on and I try to then do that if the conversation it as we're trying to decide what is true and we're trying to do that together and we see truth different then I might even call in another really smart capable person and try to say what is true and how do we explore that together and you go through that same thing so I would I said I describe it as having open mindedness and assertiveness at the same time that you can simultaneous be open-minded and taken with that curiosity and then also be assertive and say but that doesn't make sense why would this be the case and you do that back and forth and when you're doing that kind of back and forth on the topic like the economy which you have to me or have some naive but it seems both incredible and incredibly complex the economy the trading the transactions that these transactions between two individuals somehow add up to this giant mechanism you've put out a thirty minute video you have a lot of incredible videos online that people should definitely watch on YouTube but you've put out this thirty minute video titled how the economic machine works that is probably one of the best if not the best video I've seen that the internet in terms of educational videos so people should definitely watch it especially because it's not that the individual components of the video are somehow revolutionary but the simplicity and the clarity of the different components just makes you there's a few light bulb moments there about what how the economy works as a machine so as you described there's three main forces that drive the economy productivity growth short term debt cycle long-term debt cycle the the former productivity growth is how valuable things how much value people create valuable things people create the latter is people borrowing from the their future selves to hopefully create those valuable things faster so this is an incredible system to me maybe we can linger on in a little bit but you've also said well most people think about as money is actually credit total amount of credit in the u.s. is 50 trillion dollars total amount of money is three trillion dollars that's just crazy to me maybe maybe I'm silly maybe you can educate me but that seems crazy it gives me just pause that the human civilization has been able to create a system that has so much credit so that's a long way to ask do you think credit is good or bad for society that system of that's so fundamentally based on credit I think credit is great even though people often overdo it the credit is that somebody has earned money yeah and you know and what happens is they lend it to somebody else who's got better ideas and they cut a deal and then that person with the better ideas is gonna pay it back and if it works well it helps resource allocations go well providing people luck like the entrepreneurs and all of those they need capital they don't have capital themselves and so somebody's gonna give them capital and they'll give them credit and along those lines then what happens is it's not managed well in a variety of ways so I did a another book on principles principles of big debt crisis that go into that and it's free by the way I met put it free online on as a PDF so if you go online and you look principles for big debt crisis is under my name you can download it in a PDF or you can buy a print book of it and it goes through that particular process and so you always have it over done in always the same way everything by the way almost everything happens over and over again for the same reasons okay so these debt crisis has all happen over and over again for the same reasons they get it over done in the book it explains how you identify whether it's overdone or not they get it overdone and then you go through the process of making the adjustments according that and then and it explains how they can use the levers and so on if you didn't have credit then you would be sort of everybody sort of be stuck so credit is a good thing but it can easily be overdone so now we get into the quote what is money what is credit okay you get into money and credit so if you're holding credit and you think that's worthwhile keep in mind that the central bank let's say it can print the money what is that problem they you have an IOU the IOU says you're going to get a certain number of dollars let's say or yet nor euros and that is what the IOU is and so the question is will you get that money and and what will it be worth and then also you have a government which is a participant in that process because they want they are on the hook they old money and then will they print the money to make it easy for everybody to pay so you have to pay attention to those two I would suggest like you you recommend to other people just take that 30 minutes and it in it and it comes across pretty clearly but my conclusion is that of course you want it and even if you understand it and the cycles well you can benefit from those cycles rather than to be hurt by those cycles because I don't know the way the cycle works if somebody gets over indebted they have to sell an asset okay then I don't know me that's when assets become cheaper how do you acquire the asset it's a whole process so again maybe another another dumb question but there are no such things as dumb questions okay there you go but what is money so you've mentioned you know credit and money it's another thing that if I just zoom out from an alien perspective and look at human civilization it's incredible that we've created a thing that's not that only works because currency because we all agree it has value so I guess my question is how do you think about money as this emergent phenomenon and what do you think is the future of money you've come into that Bitcoin other forms what do you think is its history and future how do you think about money there are two things that money is for it's a medium of exchange and it's a store hold of wealth yes that's that that some money you know the so you could say something's a medium of exchange and then you could say is it a store hold of wealth okay so those and money is that vehicle that is those things and can be used to pay off your debt so when you have a debt and you provide it it pays off your debt so that that's that process and it's a I apologize to interrupt but it only can be a medium of exchange or store wealth when everybody recognizes it to be a value that's right right and so you see in the history and you around the world and you go to places I was in an island and the Pacific in which they had as money these big stones and literally they were taking a boat this this big carved stone and they were taking it from one of the islands to the other and it sank the the the piece of this big stone piece of money that they had and it went to the bottom and they still perceived it as having value so that it was even though it's in the bottom and it's this big hunk of rock the fact that somebody owned it they would say oh I'll loan it for this and that I've seen beads in different places shells converted to this and mediums of exchange and when we look at what we've got you're exactly right it is the notion that if I give it to you I can then take it and I can buy something with it and that's so it's a matter of perception okay and then we go through then the history of money and the vulnerabilities of money and what we have is there's through history there's been two types of money those that are claims on something of value like the connection of to gold or something that that would be an or they just are money without any connection which and then we have a system now which is a Fiat monetary system so that's what money is then it will last as long as its captive value and it works the way so let's say central banks when they get in the position of like they owe a lot of money like we have the in the case it's increasingly the case and they also another a bind and they have the printing press to print the money and get out of that and you have a lot of people might be in that position then you can print it and then it could be devalued in there and so history is show and forget about today history has shown that no currency has laughs every currency has either ended as being a currency been or devalued as the currency over periods of time long periods of time so it evolved and it changes but everybody needs that medium of exchange and everybody needs that store hold of wealth so it keeps changing what is money over a period of time but so much is being digitized today and there's this ideas that based on the blockchain of Bitcoin and so on so if all currencies like all empires come to an end what do you think well do you think something like Bitcoin might emerge as as a common store value store of wealth and a medium of exchange the problem with Bitcoin is that it's not a fact the medium exchange like it's not easy for me to go in there and buy things with it and then it's not an effective store hold of value because it has a volatility that's based on speculation and the like so yeah it's not a very effective saving that's very different from Facebook's prop of a stable value currency which would be effective as both a medium of exchange and a store hold of wealth because if you were to hold it and in the way it's linked to number of things that it's linked to would mean that it could be a very effective store hold of wealth then you have a digital currency that could be a very effective medium exchange and store hold of wealth that so in my opinion some digital currencies are likely to succeed more or based on that ability to do it then the question is what happens okay what happens is two central banks allow that to happen I really do believe it's possible to get a better form of money that central banks don't control okay a better force of money that the central banks don't control but then that's not yet happened and we also have to and so they've got to go through that evolutionary process in order to go through that evolutionary process first of all governments have got to allow that to happen which is to some extent a threat to them in terms of their power and and that's an issue and and then you have to also build the confidence and all of the components of it to say okay that's going to be effective because I won't get in I won't have problems owning it so I think that digital currencies have a have some element of potential but there's a lot of hurdles that are going to have to be gotten over I think that it'll be a very long time possibly never but anyway a very long time before we have that let's say get into a position that would be you know effective means relative to gold let's say if you were think of that because gold has a track record you know of thousands of years okay Unum all across countries and it has its mobility it has the ability to put it down and has certain abilities it's got disadvantages relative to digital currencies but but central banks will hold it like their central banks that worry about others you know the other country central banks might worry about whether the US dollar is going to print or not in that and so the thing they're going to go to is not going to be the digital currency thing they're going to go to is is gold or something else some other currency they got a ticket and so I think it's a long way to go well you think it's possible then one day we don't even have a central bank because of the a currency that doesn't that's cannot be controlled by the central bank is the primary currency or is that some very it would be very remote possibility or very long in the future got it again may be a dumb question but romanticize one when you sit back and you look you describe these transactions between individuals somehow creating short term debt cycles long-term debt cycles this productivity growth does it amaze you that this whole thing works that that there's however many millions and millions of people in the United States globally over seven billion people that this thing between individual transactions it just it works yeah it amazes me like I go I go back and forth between being in it and then I think like how does a credit card that is that really possible I'm still used to I look up credit card and I put it on the guy doesn't know me yeah it'll streamlines okay we're making the digital entries is that really secure enough and that that kind of thing and then it goes back and it goes this and it clears and it all happens and it what I marvel at that and those types of things is because of the the capacity of the human mind to create abstractions that are true you know it's imagination and then the ability to go from one level and then if these things are true then you go to the next level and if those things are true then you go to the next level and all those miracles that we almost become common it's like it when I'm flying in a plane or what I'm looking at all of the things that happen when I get communications in the middle of I don't know Africa or Antarctica and we're communicating in the ways where I see the face on my iPad of somebody my grandkid in someplace else and I look at and I say wow yes it all amazes me so while being amazing do you have a sense the principles you describe that the whole thing is stable somehow also or is this I was just lucky so the the principles that you describe are those describing a system that is stable robust and will remain so or is it a lucky accident of our early history my area of expertise is economics and market so I get down to it like a real nitty-gritty yes I can tell you whether the plane is going to fall out of the sky yes because of its particular fundamentals I don't know enough about that but it happens over and over again and so on it gives me faith ok so without me knowing it in the markets and the economy I know those things quote well enough in a sense to say that by and large that structure is right what we're seeing is right now whether there are disruptions and it has effects that can come not because that structure is right I believe that's right but whether it can be hurt by let's say connectivity or journal entries they could take from all the money away from you through your digital entries there's all sorts of things that can happen in various ways that means that that money is worthless or the system Falls but from what I see in terms of its basic structure and those complexities that still take my breath away I would say knowing them enough about the mechanics of them that doesn't worry me have you seen disruptions in your lifetime that really surprised you most all the time this is one of the great lessons of my life is that there many times I've seen things that I was very surprised about and that I realized almost all of those I was surprised about because they just they were just the first time it happened to me they didn't happen in my lifetime before but when I researched them they happened in other places or other people lifetimes so for example I remember 1971 the dollar there was no such thing as a devaluation of a currency didn't experience it and with the dollar was connected to gold and I was watching events happen and then you get on and and he's that definition of money all of a sudden went out the window because it was not tied to gold and then you have this devaluation and so and then or the first oil shock or the second oil shot or so many of these things and when I but almost always I realized that they when I looked in history they happened before they just happened in other people's lifetimes which led me to realize that I needed to study history and what happened in other people's lifetimes and what happened in other countries and places so that I would have timeless and universal principles for dealing with that thing so I oh yeah I've been some you know the implausible happening but it's like a one in a hundred year storm right okay or it's or they've happened before yeah nothing just not to you let me talk about if we could about AI a little bit so if Bridgewater associates manage about a hundred sixty billion dollars in assets and our artificial intelligence systems algorithms are pretty good with data what role in the future DC AI play in analysis and decision making in this kind of data rich an impactful area of investment I'm gonna answer that not only an investment but I give them more all encompassing rule for AI as I think you know for the last 25 years we have taken our thinking and put them in algorithms and so we make decisions that the computer takes those criteria algorithms and they put them and they're in there and it takes data and they operate as an independent decision-maker power in parallel with our decision-making so for me it's like there's a chess game playing and on person with my chess game and I'm saying it made that move and I'm making the move and how do I compare those two moves so so we've done a lot but let me give you an if the future can be different from the past and you don't have deep understanding you should not rely on AI okay those two things deep understanding of the cause-effect relationships that are leading you to place that bet in anything okay anything important let's say if it was do surgeries and you would say how do I do surgeries I think it's totally fine to watch all the doctors do the surgeries you can put it on I take a a digital camera and do that convert that into AI algorithms that go to robots and have them do surgeries and I'd be comfortable with that because if it'll do that if the keeps doing the same thing over and over again and you have enough of that that would be fine even though you may not understand the algorithms because you're if the things happening over and over again and you're not asking the future would be the same that appendicitis or whatever it is will be handled the same way the surgery that's fine however what happens with AI is for the most part is it takes a lot of data and it with a high enough sample size and then it puts together its own algorithms okay there are two ways you can come up with algorithms you can either take your thinking and express them in algorithms or you can say let put the data in and say what is the algorithm when you that's machine learning yeah and when you have machine learning it'll give you equations which quite often are not understandable you would try to say okay now describe what it's telling you it's very difficult to describe and so they can escape understanding and so it's very good for doing those things that could be done over and over again if you're watching and you're not taking that but if the future is different from the past and you have that then you're at the future is different from the past and you don't have deep understanding you're going to get in trouble and so that's the main thing as far as AI is concerned ai and I'd say computer replications of thinking in very ways I think it's particularly good for processing but but the the notion of what you want to do is better most of the time determined by the human mind that what are the principles like okay how should I raise my children it's gonna be a long time before AI you're going to say it has a good enough judgment to do that who should I marry on all of those things maybe you can get the computer to help you but if you just took data and do machine learning it's not going to find it if you were to then take one of my criteria for any of those questions and then say put them into an algorithm and you'd be a lot better off than if you took AI to do it but by and large the mind should be do used for inventing and those creative things and then the computer should be used for processing because it could process a lot more information a lot faster a lot more accurately and a lot less emotionally so any notion of thinking in the form of processing type thinking should be done by a computer and anything that is in the notion of doing that other type of thinking should be operating with with the brain in operating in a way where you know you can say ah that makes sense you know the process of reducing your understanding down to principles is kind of like the process the the first one you mentioned a type of AI algorithm where you're encoding your expertise you're trying to program right the humanists trying to write a program how do you think that's attainable the process of reducing principles to a computer program or when you when you say when you write about when you think of all principles is there still a human element that's not reducible to an algorithm my experience has been that almost all things including those things that I thought were pretty much impossible to express I've been able to express in algorithms but that doesn't constitute all things so you can come you can who you can express far more than you can imagine you'll be able to express so I use the example of okay it's not how do you raise your children okay you will be able to take it one piece by piece okay how well at what age what school and the way to do that that means my experience is to take that and when you're in the moment of making a decision or just past making a decision to take the time and to write down your criteria for making that decision in words okay that that way you'll get your prize your principles down on paper I created an app online call it's right now just on the iPhone it'll be in and try getting an Android it'll be an Android it'll be in a few months it'll be on an awesome but it has an app in there that helps people write down their own principles because this is very powerful so when you're in that moment where you've just you're thinking about it and you're thinking your criteria for you know choosing the school for your child or whatever that might be and you write down your criteria or whatever they are those principles you write down and you you that will at that moment make you articulate your principles in a very valuable way and if you have the way that we operate that you have easy access so then the next time that comes along you can go to that or you can show those principles to others to see if they're the right principles you will get a clarity of that principle that's really invaluable in words and that'll help you a lot then but then you start to think how do i express that in data and it'll shock you about how you can do that you'll you'll form an equation that will show the relationship between these particular parts and then the essentially the variables that are going to go into that particular equation and you will be able to do that and you take that little piece and you put it into the computer and then take the next little piece and you put that into the computer and before you know it you will have a decision making system that's of the sort that I'm describing so that you're almost making an argument against the past an earlier statement you've made and you're convinced to me at first you said there's no way a computer could raise a child essentially but now you've described in making me think of it if you have that kind of idea meritocracy you have this rigorous approach at Bridgewater takes an investment and apply it to raising a child it feels like through the process each is described we could as a society arrive at a set of principles for raising a child and encoded into a computer that originality will not come from machine learning the first time you do so that the original yes that's what I'm referring to but eventually as we together develop it and then we can automate it that's why I'm saying the processing yes can be done by the computer so we're saying the same thing we're not inconsistent and we're saying the same thing that the processing of that information in those algorithms can be done by the computer in a very very effective way you don't need to sit there and process and try to weigh all those things in your equation and all those things but that notion of okay how do I get at that principle and you're saying you surprised yes you how much you can express that's right you can do that so this is where I think you're going to see the future and right now we you know go to our devices and we get information to a large extent and then we get some guidance we have our GPS and the like in my opinion principles principles principles principles I want to emphasize that you write them down you've got those principles they will be converted into algorithms for decision-making and they're going to also have the benefit of collective decision-making because right now individuals based on what stuck in their heads are making their decisions in very ignorant ways they're not the best decision makers they're not the best criteria and they're operating when those principles are written down and converted into algorithms it's almost like you'll look at that and follow the instructions and it'll give you better results medic medicine will be much more like this you can go to your local doctor and you could ask his point of view and whatever and he's rushed and he may not be the best doctor around and you're gonna go to this thing and get that same information or just automatically have it input in that and it's gonna tell you okay here's what you should go do and it's going to be much better than your local doctor and that that the converting of information into intelligence okay intelligence is the thing we're coming out with again I'm 70 and I want to pass all these things along so all these tools that I've found need to develop all over these periods of time all those things I want to make an available and what's going to happen as you there they're going to see this they're going to see these tools operating much more that way the idea of converting data into intelligence intelligence for example on what they are like right or what are your strengths and weaknesses intelligence on who why work well with under what circumstance analyzed intelligence we're gonna go from what are called systems of record which are a lot of okay information organized in the right way to intelligence and we're going to that Trent that'll be the next big move in my opinion and so you will get intelligence back and that that intelligence comes from reducing things down to principles into that's how what happens so what's your intuition if you look at the future societies do you think we'll be able to reduce a lot of the the details of our lives down to principles that would be further and further automated I think the real question hinges on people's emotional emotions and irrational behaviors I think that there's subliminal things that we want okay and then there's cerebral the you know conscious logic oh and the too often are at odds so there's almost like to use and you write and so let's say what do you want and your mind will answer one thing your emotions or lands or something else so when I think about it I think emotions are I want inspiration I want love is a good thing being able to have a good impact but it is in the reconciliation of your subliminal wants and your intellectual wants so that you really say they're aligned and so to do that in a way to get what you want so irrationality is a bad thing if it means that it doesn't make sense in getting you what you want but you better decide what you your satisfying is it the lower level you emotional subliminal one or is it the other but if you can align them so what I find is that by going from my you experience the decision do this thing subliminally and that's the thing I want it comes to the surface I find that if I can align that with what my logical me wants and does do the devil double-check between them and I get the same sort of thing that that helps me a lot I find for example meditation is one of the things that helps to achieve that alignment it's fantastic for achieving that alignment and often then I also want to not just do it in my head I want to say does that make sense help you you and so I do with other people and I say okay well let's say I want this thing and whatever it does that make sense and when you do that kind of triangulation you're to use and you do that with also the other way then you certainly want to be rational right but rationality has to be defined by those things and then you discover sort of new ideas that the drive you're just so-so is you're always at the edge of the set of principles you've developed you're doing new things always well that's where the intellect is needed well and the inspiration the inspiration is needed to do that right like what are you doing it for the segment what is the velocity the hunger what's uh if you can be Freud for a second what's in that subconscious well it's the thing that drives us all I think you can't generalize of us I think different people are driven by different things there's not a common one right so like if you would take the shapers I think it is a combination of subliminally it's a combination of excitement curiosity is there a dark element there is there is their demons there's their fears is there in your sense uh most of the ones the most of the ones that I'm dealing with I have not seen that I see the what I really see is who if I can do that that would be the most dream and then the act of creativity and you say whew so excitement is one of the things curiosity is a big pull okay and then tenacity you know okay at that to do those things but definitely emotions are entering into it then there's an intellectual component of it too okay it may be empathy it may can I have an impact can I have an impact the desire to have an impact that's an emotional thrill and but it also it has empathy and then you start to see spirituality but a spirituality I mean the connectedness to the whole you start to see people operate those things those tend to be the things that you see the most of and I think you're gonna shut down this idea completely but there's a notion that some of these shapers really walk the line between sort of madness and genius do you think madness has a role in any of this or do you still see Steve Jobs in a mosque is fundamentally rational the others a continuum there then what comes to my mind is that genius is that often at the edge in some cases imaginary genius is at the edge of insanity and it's almost like a radio that I think okay if I can tune it just right it's playing right but if I go a little bit too far yeah it goes off yeah okay and so you can you can see this kay Jamison was studying bipolar what it shows is that you know that's definitely the case because when you're going out there that imagination whatever is that the can be near the edge sometimes it doesn't have to always be so let me ask you about automation that's been a part of public discourse recently what's your view on the impact of automation of whether we're talking about AI a more basic forms of automation on the economy in the short term in the long term do you have concerns about it as some do or do you think it's overblown it's not overblown and it's a it's a giant thing it'll come at us in a very big way and in the future we're right at the edge of even really accelerating it it's had a big impact and it will have a big impact and it's a two-edged sword because it'll have tremendous benefits and at the same time it has profound benefits in employment and distributions of wealth because the way I think think about it is there are certain things human beings can do and over time we've evolved to go to almost higher and higher levels and now we're almost like we're at this level you know it used to be your labor you would then do your labor and okay we can get past the labor we got tractors and things and you go up up up up up and we're up over here and to the point in our minds we're okay anything related to mental processing the computer can probably do better and we can find that and so other than almost inventing you're at a point where these are the Commission's and the automation will probably do it better and and that's accelerating and that's a force and that's a force for the good and at the same time it what it does is it displaces people in terms of employment and changes and it produces wealth gaps and all of that so I think the real issue is that that has to be viewed as a national emergency in other words I think the well the wealth gap theme the income gap the opportunity gap all of those things that force is creating the problems that we're having today a lot of the problems the the great polarity the disenfranchised eat dis not equal not anything approaching equality of education all of these problems a lot of problems are coming as a result of that and so there it needs to be viewed really as an emergency situation in which there's a good work good plan worked out for how to deal with that effectively so that it's dealt with effectively so because it's it's it you know it's good for the average it's good for the impact but it's not good for everyone in the crates that polarity so it's got to be dealt with yeah and you've talked about the American Dream and that that's something that all people should have an opportunity for and then we need to reform capitalism to give that opportunity for everyone let me ask kind of one of the ideas in terms of safety nets that support that kind of opportunity there's been a lot of discussion of universal basic income amongst people so there's andrew yang who's running on that he's a political candidate running for president on the idea of the universal basic income what do you think about that giving a thousand dollars or some amount of money to everybody as a way to give them the the padding the freedom to sort of take leaps to take the call for adventure to take the crazy procedure before I get right into the my thoughts on universal basic income I want to start with the notion that opportunity education development creating equality so that you people say there's equal opportunity and is the most important thing and then to find out what is the amount how are you going to provide that what where what how does it how do you get the money into a public school system how do you get the teaching how do you what do the fleshing out that plan to create equal opportunity in all of its various forms is the most pressing thing to do and so I'm you know that is that the the opportunity is the most important one you're kind of implying is the earlier the better sort of like opportunity to education so in the early development of a human being is when you should have the equal opportunities that's the most important right in the first phase of your life which goes from birth until you're on your own and you're an adult and you're now out there and you deal with early childhood development okay and you take the brain and you say what's important the child care okay like the it makes a world of difference for example if you have good parents who are trying to think about instilling the stability in a non traumatic environment to provide them so I would say the good guidance that normally comes from parents and the good education that they're receiving are you know the most important things in that person's development the ability to be able to be prepared to go out there and then to go into a market that's an equal opportunity job market to be able to then go into that kind of market is a system that creates not only fairness anything else is not fair and then in addition to that it also is a more effective economic system because the consequences of not doing that are to a society or devastating if you look at what the difference in outcomes for somebody who completes high school or doesn't complete high school or does each one of those state changes and you look at what that means in terms of their costs to society not only themselves but their cost and incarceration costs and then on crimes and all of those things it's economically better for the society and it's fairer if they can complete fake an get those particular things once they have those things then you move on to other things but yes from birth all the way through that process anything less than that is bad is a tragedy and and so on so that's what uh that's yeah those are the things that I'm estimate and so my I'm what I would want to above all else is to provide that so with that in mind now we'll talk about universal basic income start with that well now we can talk about well the bright because you have to have that now the question is what's the best way to provide that okay so when I look at UB I I really think is what is going to happen with that thousand dollars okay and will that thousand dollars come from another program does that come from an early childhood developmental program who are you giving the thousand dollars to and what will they do for that thousand dollars I mean like my reaction would be I think it's a great thing that everybody should have almost a thousand dollars in their bank and so on but when do they get to make decisions or who's the parent a lot of pit times you can give a thousand dollars to somebody and it could have a negative result it can have you know they can use that money detrimental II not just for octave Lee and if that money's coming away from some of those other things that are going to produce the things I want and you're shifted to let's say to come in and give a check doesn't mean it's outcomes are going to be good and providing those things that I think are so fundamental important if it was just everybody can have a thousand dollars and use it so when the time is not well and use it well that would be really really good because it's almost like everybody you'd wish everybody could have a thousand dollars worth of wiggle room in their lives okay and I think that would be great I love that but we I want to make sure that these other things that are taken care of so if it comes out of that budget and you know I don't want it to come out of that budget that's gonna be doing those things and I you know so you have to figure it out and you know a certain skepticism that human nature will use may not always in fact frequently may not use that thousand dollars for the optimal to support the optimal trajectory some will and some won't one of the big advantages of universal basic income is that if you put it in the hands let's say parents who know how to do the right things and make the right choices yes for their children because they're responsible and you say I'm gonna give them a thousand dollars wiggle room to use for the benefit of their children wow that sounds great if you put it in the hands of let's say an alcoholic or drug addicted parent who is not making those choices well for their children and what they do is they take that thousand dollars and they don't use it well then that's going to produce more harm than good well put your if I may say so one of the richest people in the world so you're a good person ask does money buy happiness no it's been shown that between once you get over a basic level of income so that you can take care of the pain then you know you can health and whatever there's no correlation between the level of happiness that one has and the level of money that one has they that would has the highest correlation is quality relationships with others community if you look at surveys of these things across all surveys and all societies it's a sense of community and per into personal relationships that is not in any way correlated with money you can go down to native tribes and you know very poor places or you can go in all different communities and so they have the opportunity to have that I'm very lucky in that I started with nothing so I had the full range I can tell you I you know I not having money but but and then having quite a lot of money and I you know I did that in the right order I'll tell you started from nothing in Long Island yeah and my dad was a jazz musician but I but I had all really that I needed because I had two parents who loved me and took good care of me and I went to a public school that was a good public school and basically you know that you don't need much more than that in order to that's the equal opportunity part anyway what I'm saying is no I experienced the range and else and there are many studies on the answer to your question no money does not bring happiness bring money gives you an ability to make choices does it get in the way in any way of forming those deep meaningful relationships it can there are lots of ways that it makes negative that's one of them it could stand in the way of that yes okay but I could almost list the ways that it could stand it could be a problem yeah what does it buy so if you can elaborate your mission a bit of freedom at the most fundamental level it doesn't take a whole lot but it takes enough that you can take care of your yourself and your family to be able to learn do the basics of have the relationships have healthcare the basics of those types of things you know you can cover the patients and then to have maybe enough security but maybe not too much security that's right yeah that you essentially are okay okay that is that's really good and you don't that's what a that's what money will get you and everything else is could go either way well there's more there's more okay then beyond that what it then starts to do that's the most important thing yes but beyond that what its Tensta much to do is to help to make your dreams happen in various ways okay so for example now I you know look at my case it's a those dreams might not be just my own dreams they're their impact on others dreams okay so my own dreams might be um I don't know I can pass along these at my stage in life I could press along these principles to you and I can give those they or I could do whatever I can go on an adventure I can start a business I can do those other things be productive I can self actualize in ways that might be not possible otherwise and so that's that's my own belief and then in a dot and I can also help others I mean this is you know to the extent when you get older and with time and whatever very you start to feel connected spiritual spirituality is what I'm referring to you can start to have an effect on others that's beneficial and so on gives you the ability I could tell you that people who are very wealthy who have that a feel that they don't have enough money Bill Gates will feel almost broke because relative to the things he'd like to accomplish through the Gates Foundation and things like that you know oh my god he doesn't have enough money to accomplish the things he wishes for but those things are not you know they're not the most fundamental things so I think that people sometimes think money has value money doesn't have value the money is like you say just a of exchange in a store although well and so what you have to say is what is it that you're going to buy now there are other people who get their gratification in ways that are different from me but I think in many cases that let's say somebody who used money to have a status symbol I what would I say or that's probably unhealthy but then I don't know somebody who says I love a great gorgeous painting and it's going to cost lots of money in my priorities mecan't not Kemp get there but but that doesn't mean I don't who am I to judge others in terms of let's say their elements of the freedom to do those things so it's a little bit complicated but by and large that you know that's my view on money and wealth so let me ask you in terms of the idea of so much of your passions and life has been through something you might be able to call work Alan Watts has this quote he said that the real key to life secret of life is to be completely engaged with what you're doing in the here and now and instead of calling it work realize that it's play so I'd like to ask what is the role of work in your life's journey or in a life's journey and what do you think about this modern idea of kind of separating work and let work-life balance I have a principle that I believe in is make your work in your passion the same thing ok ok so that's similar face uh-uh-uh-uh-uh in other words if you can make your work in your passion it's just gonna work out great and then of course people have different purposes of work and I don't want to be theoretical about that people have to take care of their family so money at a certain point is the base is an important component of that work so you look beyond that what is the money gonna get you and what are you're trying to achieve but the most important thing I agree is meaningful work and meaningful relationships like if you can get into the thing that you're at your mission that you're on and you are excited about that mission that you're on and then you can do that with people who you have the meaningful relationships with you have meaningful work and meaningful relationships I mean that is fabulous for most people and it seems that many people struggle to get there not out of not necessarily because they're constrained by the fact that they have the financial constraints of having to provide for their family and so on but it's I mean moat you know this idea is out there that there needs to be a work-life balance which means that most people on this thing we're going to return to the same things most doesn't mean optimal but most people seem to not be doing their life's passion not be not unifying work and passion why do you think that is is well the work-life balance there's a life arc that you go through starts at zero and ends somewhere in the vicinity of 80 and there is a phase and there's a and you could look at the different degrees of happiness that happened in those phases I can go through that if that was interesting but we don't have time probably for it but you get in the part of the life that part of the life which has the lowest level of happiness is aged 45 to 55 and and and because as you move into this second phase of your life in the first phase of your life is when you're learning dependent on others second phase of your life is when you're working and others are dependent on you and you're trying to be successful and in that phase of one's life you encounter the work-life balance challenge because you're trying to be successful at work and successful at parenting and successful and successful and all those things that take your demand and they get into that and I understand that problem in the work/life balance the issue is primarily to know how to approach that okay so I understand it stressful it produces stress and it produces bad results and it produces the lowest level of happy in one's life it's interesting as you get later in life the levels of happiness rise in the highest level of happiness is between ages 70 and 80 which is interesting there are other reasons but in appspot I want and that and the key to work-life balance is to realize and to learn how to get more out of an hour of life okay because an hour of work what people are thinking is that they have to make a choice between one thing and another and of course they they do but they don't realize that if they develop the skill to get a lot more out of an hour it's the equivalent Earl if-- and so you know that's why in the book principles I try to go into okay now how can you get a lot more out of out of an hour that allows you to get more life into your life and it reduces the work-life balance and that's the primary struggle in that 35 to 45 you know if you could linger on that sort of what are the ups and downs of life in terms of happiness in general and perhaps in your own life when you look back at the moments the peaks it's pretty pretty much same pattern really in one's life is tends to be a very happy period all the way up and sixteen is like a really great happy you know I think like myself you start to get elements of freedom you get your driver's license you know whatever but 16 is there a junior year in high school quite often could be a stressful period to try to get thing about the high school you go into college tends to be very high happiness generally speaking freedom and then freedom yeah friendships all of that freedom is a big thing and then you and then 20 23 is a peak point kind of an unhappy 'no staff freedom then sequentially one has a great time they date they go out and so on you find the love of your life you begin to develop a family and then with that as time happens you have more of your work-life balance challenges that come and your responsibilities and then as you get there in that mid part of your life that is the most that is the biggest struggle chances are you will crash in that period of time you know you'll have you'll have your series of failures that's the that's that that's when you go into the abyss you learn you hopefully learn from those mistakes you have to metamorphosis you come out you change hopefully become better and you take more responsibilities and so on and then when you get to the later part as you are starting to approach the transition in that late part of the second phase of your life before you go into the third phase of your life second phase is you're working trying to be successful third phase of your life is you want people to be successful without you okay yes yeah you want your kids to be successful without you because when you're at that phase they're at making their transition from the first phase to the second phase and they're trying to be successful you want them to be successful without you and you have and your parents are gone and then you have freedom and then you have freedom again and that with that freedom and then you have these histories shown with this you have friendships you have perspective on life you have different things and that's one of the reasons that that later part of the life can be real it on average actually it's the highest very interesting thing if they and they their surveys and say how good do you look and how good do you feel and and that's the highest survey the person now they not look in the best yeah and they're not feeling the best right maybe it's thirty five that they're actually looking the best and feeling the best but they rank the highest at that point survey results of being the highest so that seventy to eighty period of time because it has to do with an attitude on life then you start to have grandkids Oh grandkids are great and you start to experience that transition well so that's what the Ark of life pretty much looks like in and I'm experiencing it you know that's good that when you meditate we're all human or immortal when you meditate it on your own mortality having achieved a lot of success on whatever dimension what do you think is the meaning of it all the meaning of our short existence on earth as human beings I think that evolution is the greatest force of in the universe and that were all tiny bits of an evolutionary type of process where it's just matter and machines that go through time and that we all have a deeply embedded inclination to evolve and contribute to evolution so I think it's too personally evolved and contribute to the evolution I could have predicted you would answer that way it's brilliant and exactly right and I think we've said it before but I'll say it again you have a lot of incredible videos out there that people should definitely watch I don't say this often I mean it's literally the best spend of time and in terms of reading principles and reading basically anything you write on LinkedIn and so on there's a really good use of time it's a lot of light bulb moments a lot of transformative ideas in there so alright thank you so much it's been an honor and I really appreciate it it's been a pleasure for me too I'm happy to hear it's used to you and others thanks for listening to this conversation with Ray Dalio and thank you to our presenting sponsor cash app downloaded use code let's podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribed on YouTube gave it five stars in that podcast support it on patreon or connect with me on Twitter finally closing words of advice from Ray Dalio pain plus reflection equals progress thank you for listening and hope to see you next time you |
Noam Chomsky: Language, Cognition, and Deep Learning | Lex Fridman Podcast #53 | - The following is a
conversation with Noam Chomsky. He's truly one of the
great minds of our time and is one of the most cited scholars in the history of our civilization. He has spent over 60 years at MIT and recently also joined
the University of Arizona where we met for this conversation, but it was at MIT about
four and 1/2 years ago when I first met Noam. My first few days there I remember getting into an elevator at Stata Center, pressing the button for
whatever floor, looking up and realizing it was
just me and Noam Chomsky riding the elevator, just me
and one of the seminal figures of linguistics, cognitive
science, philosophy, and political thought in the
past century if not ever. I tell that silly story
because I think life is made up of funny
little defining moments that you never forget for
reasons that may be too poetic to try and explain, that was one of mine. Noam has been an inspiration
to me and millions of others. It was truly an honor for me to sit down with him in Arizona. I traveled there just
for this conversation, and in a rare, heartbreaking moment after everything was set up and tested the camera was moved and accidentally the recording button was
pressed stopping the recording. So I have good audio of both
of us but no video of Noam, just a video of me and my
sleep deprived but excited face that I get to keep as a
reminder of my failures. Most people just listen
to this audio version for the podcast as opposed
to watching it on YouTube, but still it's heartbreaking for me. I hope you understand and still enjoy this
conversation as much as I did. The depth of intellect that Noam showed and his willingness to truly listen to me, a silly looking Russian
in a suit was humbling and something I'm deeply grateful for. As some of you know, this
podcast is a side project for me where my main journey and dream is to build AI systems that
do some good for the world. This latter effort
takes up most of my time but for the moment has
been mostly private, but the former, the podcast
is something I put my heart and soul into and I hope you feel that even when I screw things up. I recently started doing ads at the end of the introduction. I'll do one or two minutes
after introducing the episode and never any ads in the middle that break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This is the Artificial
Intelligence podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support it on Patreon, or simply
contact with me on Twitter @lexfridman spelled F-R-I-D-M-A-N. This show is presented by Cash App, the number one finance
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inspire girls and boys to dream of engineering a better world. And now here's my conversation
with Noam Chomsky. I apologize for the absurd
philosophical question, but if an alien species
were to visit Earth, do you think we would be able
to find a common language or protocol of communication with them? - [Noam] There are arguments
to the effect that we could. In fact, one of them was Marv Minsky's. Back about 20 or 30 years ago he performed a brief experiment with a
student of his, Daniel Bobrow they essentially ran the
simplest possible Turing machines just free to see what would happen. And most of them crashed,
either got into an infinite loop or were stopped, the few that persisted essentially gave
something like arithmetic. And his conclusion from that was that if some alien species
developed higher intelligence they would at least have arithmetic. They would at least have what
the simplest computer would do and in fact he didn't
know that at the time, but the core principles
of natural language are based on operations
which yield something like arithmetic in the limiting
case, in the minimal case. So it's conceivable that
a mode of communication could be established based
on the core properties of human language and the
core properties of arithmetic which maybe are universally
shared so it's conceivable. - [Lex] What is the
structure of that language, of language as an internal
system inside our mind versus an external
system as it's expressed? - [Noam] It's not an alternative. It's two different concepts of language. - [Lex] Different. - [Noam] It's a simple fact that there's something
about you, a trait of yours, part of the organism you that determines that you're talking English
and not Tagalog, let's say. So there is an inner system. It determines the sound and meaning of the infinite number of
expressions of your language. It's localized, it's not in your foot obviously it's in your brain. If you look more closely it's
in specific configurations of your brain and that's essentially like the internal
structure of your laptop. Whatever programs it has are in there. Now, one of the things
you can do with language, it's a marginal thing in
fact is use it to externalize what's in your head. I think most of your use
of language is thought, internal thought, but can do
what you and I are now doing. We can externalize it. Well, the set of things
that we're externalizing are an external system, they're
noises in the atmosphere, and you can call that language in some other sense of the word, but it's not a set of alternatives. These are just different concepts. - [Lex] So how deep do the roots of language go in our brain? - Well--
- Our mind, is it yet another feature like vision? Or is it something more fundamental from which everything else
springs in the human mind? - [Noam] Well in a way it's like vision. There's something about
our genetic endowment that determines that we have a mammalian rather than an insect visual system. And there's something
in our genetic endowment that determines that we have
a human language faculty. No other organism has
anything remotely similar. So in that sense it's internal. Now, there is a long tradition
which I think is valid going back centuries to the
early scientific revolution at least that holds that language is the sort of the core of
human cognitive nature. It's the source, it's the
mode for constructing thoughts and expressing them and
that is what forms thought and it's got fundamental
creative capacities. It's free, independent,
unbounded and so on. And undoubtedly I think the basis for our creative capacities
and the other remarkable human capacities that lead
to the unique achievements and not so great
achievements of the species. - [Lex] The capacity to think and reason. Do you think that's deeply
linked with language? Do you think the internal
language system is essentially the mechanism by which we
also reason internally? - [Noam] It is undoubtedly the
mechanism by which we reason. There may also be other,
there are undoubtedly other faculties involved in reasoning. We have a kind of scientific faculty. Nobody knows what it
is, but whatever it is that enables us to pursue
certain lines of endeavor and inquiry and to decide what makes sense and doesn't make sense and
to achieve a certain degree of understanding in the
world that uses language but goes beyond it just as using
our capacity for arithmetic is not the same as having the capacity. - [Lex] The idea of capacity,
our biology, evolution, you've talked about it defining
essentially our capacity, our limit and our scope. Can you try to define
what limit and scope are, and the bigger question,
do you think it's possible to find the limit of human cognition? - [Noam] Well that's an
interesting question. It's commonly believed,
most scientists believe that human intelligence can answer any question in principle. I think that's a very strange belief. If we're biological organisms
which are not angels then our capacities ought
to have scope and limits which are interrelated. - [Lex] Can you define those two terms? - [Noam] Well, let's
take a concrete example. Your genetic endowment, it determines that you can have a
mammalian visual system and arms and legs and so on and therefore become a
rich, complex organism, but if you look at that
same genetic endowment it prevents you from
developing in other directions. There's no kind of experience
which would yield the embryo to develop an insect visual system or to develop wings instead of arms. So the very endowment that
confers richness and complexity also sets bounds on what can be attained. Now I assume that our cognitive capacities are part of the organic world therefore they should
have the same properties. If they had no built-in
capacity to develop a rich and complex structure we
would understand nothing just as if your genetic endowment did not compel you to
develop arms and legs you would just be some kind
of a random ameboid creature with no structure at all
so I think it's plausible to assume that there are limits, and I think we even have some
evidence as to what they are. So for example there's a classic moment in the history of science
at the time of Newton. There was from Galileo to
Newton modern science developed on a fundamental assumption
which Newton also accepted, namely that the world, the entire universe is a mechanical object and
by mechanical they meant something like the kinds of artifacts that were being developed
by skilled artisans all over Europe, the
gears, levers, and so on. And their belief was, well the world is just a more complex variant of this. Newton to his astonishment
and distress proved that there are no machines, that there's
interaction without contact. His contemporaries like
Leibniz and Huygens just dismissed this as
returning to the mysticism of the Neo-Scholastics and Newton agreed. He said, "It is totally absurd. "No person of any scientific intelligence "could ever accept this for a moment." In fact, he spent the rest of his life trying to get around it somehow as did many other scientists. That was the very criterion
of intelligibility for say Galileo or Newton. Theory did not produce
an intelligible world unless you could duplicate it in a machine and he showed you can't,
there are no machines, any. Finally after a long
struggle, took a long time scientists just accepted
this as common sense, but that's a significant moment. That means they abandoned the search for an intelligible world
and the great philosophers of the time understood that very well. So for example, David Hume
in his encomium to Newton wrote that, who was the
greatest thinker ever and so on. He said that he unveiled
many of the secrets of nature but by showing the imperfections of the mechanical philosophy,
mechanical science he left us with, he showed
that there are mysteries which ever will remain, and
science just changed its goals. It abandoned the mysteries. It can't solve it, they'll put it aside. We only look for intelligible theories. Newton's theories were intelligible it's just what they described wasn't. Well, Locke said the same thing. I think they're basically right and if so that showed something about
the limits of human cognition. We cannot attain the goal
of understanding the world, of finding an intelligible world. This mechanical philosophy,
Galileo to Newton, there's a good case that can be made that that's our instinctive
conception of how things work. So if say infants are tested with things that if this moves and then this moves they kind of invent something
that must be invisible that's in between them that's
making them move and so on. - [Lex] Yeah, we like physical contact. Something about our brain seeks-- - [Noam] Makes us want a world like then just like it wants a world that has regular geometric figures
so for example Descartes pointed this out that
if you have an infant who's never seen a triangle
before and you draw a triangle the infant will see a distorted triangle not whatever crazy figure
it actually is, you know, three lines not coming quite together or one of them a little
bit curved and so on. We just impose a conception of the world in terms of perfect geometric objects. It's now been shown that
it goes way beyond that, that if you show on a
tachistoscope, let's say, a couple of lights
shining, you do it three or four times in a row
what people actually see is a rigid object in motion
not whatever's there. We all know that from a
television set basically. - [Lex] So that gives us
hints of potential limits to our cognition?
- I think it does, but it's a very contested view. If you do a poll among scientists
they'll say impossible. We can understand anything. - [Lex] Let me ask and
give me a chance with this. So I just spent a day at a
company called Neuralink, and what they do is try
to design what's called a brain machine, a brain
computer interface. So they try to just do thousands
of readings in the brain, be able to read what
the neurons are firing and then stimulate back, so two-way. Do you think their dream
is to expand the capacity of the brain to attain information, sort of increase the bandwidth at which we can search
Google kind of thing? Do you think our cognitive
capacity might be expanded, our linguistic capacity,
our ability to reason might be expanded by adding
a machine into the picture? - [Noam] It can be expanded
in a certain sense, but a sense that was known
thousands of years ago. A book expands your
cognitive capacity, okay, so this could expand it, too. - [Lex] But it's not a
fundamental expansion. It's not totally new
things could be understood. - [Noam] Well, nothing that goes beyond our native cognitive capacities just like you can't turn the visual system into an insect system. - [Lex] Well, I mean
the thought is perhaps you can't directly but you can map. - [Noam] You could be we know
that without this experiment you could map what a
bee sees and present it in a form so that we could follow it. In fact every bee scientist does that. - [Lex] Uh-huh, but you
don't think there's something greater than bees that we can map and then all of a sudden
discover something, be able to understand a quantum
world, quantum mechanics, be able to start to be able to make sense. - [Noam] You can, students at MIT study and understand quantum mechanics. - [Lex] (laughs) But they
always reduce it to the infant, the physical, I mean they
don't really understand-- - [Noam] Not physical,
that may be another area where there's just a
limit to understanding. We understand the theories, but the world that it describes
doesn't make any sense. So you know the experiment,
the Schrodinger's cat for example, can understand the theory but as Schrodinger pointed out it's not an intelligible world. One of the reasons why Einstein
was always very skeptical about quantum theory, he described himself as a classical realist
and wants intelligibility. - [Lex] He has something in
common with infants in that way. So back to linguistics,
if you could humor me, what are the most beautiful
or fascinating aspects of language or ideas in linguistics or cognitive science that you've seen in a lifetime of studying language and studying the human mind? - [Noam] Well, I think the
deepest property of language and puzzling property
that's been discovered is what is sometimes called
structure dependence. We now understand it pretty well, but it was puzzling for a long time. I'll give you a concrete example. So suppose you say, the
guy who fixed the car carefully packed his tools. That's ambiguous, he could
fix the car carefully or carefully pack his tools. Now suppose you put carefully in front. Carefully the guy who fixed
the car packed his tools. Then it's carefully packed,
not carefully fixed. And in fact you do that
even if it makes no sense. So suppose you say, carefully the guy who fixed the car is tall. You have to interpret it
as carefully he's tall even though that doesn't make any sense. And notice that that's
a very puzzling fact because you're relating carefully not to the linearly closest verb but to the linearly more remote verb. Linear closeness is a easy computation, but here you're doing a much more, what looks like a more
complex computation. You're doing something that's taking you essentially to the more remote thing, it's now if you look at the
actual structure of the sentence where the phrases are and so on turns out you're picking out the
structurally closest thing, but the linearly more remote thing. But notice that what's linear
is 100% of what you hear. You never hear of structure. So what you're doing is and
instantly this is universal. All constructions, all languages and what we're compelled
to do is carry out what looks like the
more complex computation on material that we never
hear and we ignore 100% of what we hear on the
simplest computation. And by now there's even
a neural basis for this that's somewhat understood,
and there's good theories but none that explain why it's true. That's a deep insight
into the surprising nature of language with many consequences. - [Lex] Let me ask you about
a field of machine learning and deep learning, there's
been a lot of progress in neural network-based machine learning in the recent decade. Of course, neural network
research goes back many decades. - [Noam] Yeah. - [Lex] What do you think are
the limits of deep learning, of neural network-based machine learning? - [Noam] Well, to give
a real answer to that you'd have to understand
the exact processes that are taking place, and
those are pretty opaque so it's pretty hard to prove a theorem about what can be done
and what can't be done. But I think it's reasonably clear, I mean, putting technicalities aside what deep learning is doing
is taking huge numbers of examples and finding some patterns. Okay, that could be interesting
and in some areas it is but we have to ask here
a certain question. Is it engineering or is it science? Engineering in the sense of
just trying to build something that's useful or science in the sense that it's trying to understand
something about elements of the world so it takes a Google parser. We can ask that question, is it useful? Yeah, it's pretty useful. I use Google Translator
so on engineering grounds it's kinda worth having like a bulldozer. Does it tell you anything
about human language? Zero, nothing, and in
fact it's very striking. From the very beginning it's just totally remote from science so what is a Google parser doing? It's taking an enormous text, let's say The Wall Street
Journal corpus and asking, how close can we come to
getting the right description of every sentence in the corpus? Well, ever sentence in the corpus is essentially an experiment. Each sentence that you produce
is an experiment which is, am I a grammatical sentence? Now the answer is usually
yes so most of the stuff in the corpus is grammatical sentences, but now ask yourself, is there any science which takes random experiments
which are carried out for no reason whatsoever and tries to find out something from them? Like if you're, say, a
chemistry PhD student you want to get a thesis can you say, well I'm just gonna do a
lot of, mix a lot of things together, no purpose, and
maybe I'll find something. You'd be laughed out of the department. Science tries to find
critical experiments, ones that answer some
theoretical question. Doesn't care about coverage
of millions of experiments. So it just begins by being
very remote from science and it continues like
that so the usual question that's asked about, say, a Google parser is how well does it do, or some parser, how well does it do on a corpus? But there's another
question that's never asked. How well does it do on something that violates all the rules of language? So for example, take the
structure dependence case that I mentioned, suppose
there was a language in which you used linear
proximity as the mode of interpretation, these deep learning would work very easily on that. In fact, much more easily
than on an actual language. Is that a success? No, that's a failure. From a scientific point
of view that's a failure. It shows that we're not discovering the nature of the system at all 'cause it does just as well or even better on things that violate the
structure of the system, and it goes on from there. It's not an argument against doing it. It is useful to have devices like this. - [Lex] So yes, neural networks
are kind of approximators that look, there's echoes of
the behavioral debates right, behavioralism.
- More than echoes. Many of the people in deep learning say they vindicated.
- (laughs) Yeah. - [Noam] Terry Sejnowski for
example in his recent book says this vindicates Skinnerian behaviors and it doesn't have
anything to do with it. - [Lex] Yes, but I think there's something actually fundamentally different
when the data set is huge, but your point is extremely well taken. But do you think we can learn, approximate that interesting, complex
structure of language with neural networks that will somehow help us understand the science? - [Noam] It's possible,
I mean, you find patterns that you hadn't noticed, let's say. Could be, in fact it's very
much like a kind of linguistics that's done, what's called
corpus linguistics when you, suppose you have some language
where all the speakers have died out but you have records. So you just look at the records and see what you can figure out from that. It's much better to have actual speakers where you can do critical experiments, but if they're all dead you can't do them so you have to try to
see what you can find out from just looking at
the data that's around. You can learn things. Anthropology is very much like that. You can't do a critical experiment on what happened two million years ago so you're kinda forced to
take what data's around and see what you can figure out from it. Okay, it's a serious study. - [Lex] So let me venture into
another whole body of work and philosophical question. You've said that evil in society
arises from institutions, not inherently from our nature. Do you think most human beings are good, they have good intent or
do most have the capacity for intentional evil that
depends on their upbringing, depends on their environment, on context? - [Noam] I wouldn't say that they don't arise from our nature. Anything we do arises from our nature. And the fact that we
have certain institutions and not others is one mode in which human nature
has expressed itself. But as far as we know, human nature could yield many different
kinds of institutions. The particular ones that have developed have to do with historical contingency, who conquered whom and that sort of thing, then they're not rooted in our nature in the sense that they're
essential to our nature so it's commonly argued that
these days that something like market systems is
just part of our nature, but we know from a huge amount of evidence that that's not true, there's
all kinds of other structures. That's a particular fact of
a moment of modern history. Others have argued that the
roots of classical liberalism actually argue that
what's called sometimes an instinct for freedom, an instinct to be free of domination
by illegitimate authority is the core of our nature. That would be the opposite of this. And we don't know, we just
know that human nature can accommodate both kinds. - [Lex] If you look back at your life, is there a moment in
your intellectual life or life in general that jumps from memory that brought you happiness that you would love to relive again? - [Noam] Sure, falling
in love, having children. - [Lex] What about, so
you have put forward into the world a lot of
incredible ideas in linguistics, in cognitive science, in terms of ideas that just excites you
when it first came to you that you love to relive those moments. - [Noam] Well, I mean,
when you make a discovery about something it's exciting like say even the observation
of structure dependence and on from that the explanation for it, but the major things just
seem like common sense. So if you go back to, take your question about external and internal language. You go back to, say, the 1950s almost entirely language is
regarded as an external object, something outside the mind. It just seemed obvious
that that can't be true. Like I said, there's something
about you that determines you're talking English
not Swahili or something. But that's not really a discovery. That's just an observation
of what's transparent. You might say it's kind of like the 17th century, the
beginnings of modern science 17th century, they came from being willing to be puzzled about things
that seemed obvious. So it seems obvious that a heavy
ball of lead'll fall faster than a light ball of lead,
but Galileo was not impressed by the fact that it seemed obvious. so he wanted to know if it's true He carried out experiments,
actually thought experiments never actually carried
them out which showed that it can't be true, you know. And out of things like that,
observations of that kind, you know, why does a
ball fall to the ground instead of rising, let's say? It seems obvious till you
start thinking about it 'cause why does steam rise, let's say. And I think the beginnings
of modern linguistics roughly in the 50s are kind of like that, just being willing to be
puzzled about phenomena that looked from some
point of view obvious. And for example a kind of doctrine, almost official doctrine
of structural linguistics in the 50s was that languages
can differ from one another in arbitrary ways and
each one has to be studied on its own without any presuppositions and in fact there were
similar views among biologists about the nature of
organisms that each one's, they're so different when you look at them that you could be almost anything. Well in both domains it's been learned that it's very far from true. There are very narrow constraints on what could be an organism
or what could be a language. But these are, you know, that's
just the nature of inquiry. - [Lex] Science in general, yeah, inquiry. So one of the peculiar things about us human beings is our mortality. Ernest Becker explored it. In general do you ponder
the value of mortality? Do you think about your own mortality? - [Noam] I used to when
I was about 12 years old. I wondered, I didn't care
much about my own mortality, but I was worried about the
fact that if my consciousness disappeared would the
entire universe disappear. That was frightening. - [Lex] Did you ever find
an answer to that question? - [Noam] No, nobody's
ever found an answer, but I stopped being bothered by it. It's kind of like Woody
Allen in one of his films. You may recall he goes to
a shrink when he's a child and the shrink asks him,
"What's your problem?" He says, "I just learned that
the universe is expanding. "I can't handle that." - [Lex] (laughs) And
another absurd question is, what do you think is the
meaning of our existence here, our life on Earth, our
brief little moment in time? - [Noam] That's something we
answer by our own activities. There's no general answer. We determine what the meaning of it is. - [Lex] The action determine the meaning. - [Noam] Meaning in the
sense of significance not meaning in the sense that
chair means this, you know, but the significance of your
life is something you create. - Noam, thank you so
much for talking today. It was a huge honor, thank you so much. Thanks for listening to this
conversation with Noam Chomsky, and thank you to our
presenting sponsor Cash App. Download it, use code LexPodcast. You'll get $10 and $10 will go to FIRST, a STEM education nonprofit
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hope to see you next time. |
Gilbert Strang: Linear Algebra, Teaching, and MIT OpenCourseWare | Lex Fridman Podcast #52 | the following is a conversation with Gilbert Strang he's a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world his MIT opencourseware lectures on linear algebra have been viewed millions of times as an undergraduate student I was one of those millions of students there's something inspiring about the way he teaches there's at once calm simple and yet full of passion for the elegance inherent to mathematics I remember doing the exercises in his book introduction of linear algebra and slowly realizing that the world of matrices of vector spaces of determinants and eigenvalues of geometric transformations and matrix decompositions reveal a set of powerful tools in the toolbox of artificial intelligence from signals to images from miracle optimization to robotics computer vision deep learning computer graphics and everywhere outside AI including of course a quantum mechanical study of our universe this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast support on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma N this podcast is supported by zip recruiter hiring great people is hard and to me is the most important element of a successful mission driven team I've been fortunate to be a part of and to lead several great engineering teams the hiring I've done in the past was mostly the tools that we built ourselves but reinventing the wheel was painful so zip recruiters a tool that's already available for you it seeks to make hiring simple fast and smart for example codable co-founder Gretchen Abner used the recruiter to find a new game artist to join her education tech company by using zip recruiter screening questions to filter candidates Gretchen found it easier to focus on the best candidates and finally hiring the perfect person for the role in less than two weeks from start to finish zip recruiter the smartest way to hire CY zip recruiter is effective for businesses of all sizes by signing up as I did for free a zip recruiter comm slash FlexPod that's zip recruiter calm slash Lex pod this show is presented by cash app the number one finance app in the App Store I personally use cash app to send money to friends but you can also use it to buy sell and deposit Bitcoin most Bitcoin exchanges take days for bank transfer to become investable through cash up it takes seconds cash app also has a new investing feature you can buy a fraction of stock which to me is a really interesting concept so you can buy $1 worth no matter what the stock price is brokerage services are provided by cash app investing a subsidiary of square and member si PC I'm excited to be working with cash app to support one of my favorite organizations that many of you may know and have benefited from called first best known for their first robotics and Lego competitions they educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating and Charity Navigator which means the donated money is used to maximum effectiveness when you get cash app from the App Store or Google Play and use code Lex podcast you get ten dollars in cash app will also donate ten dollars to the first which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world and now here's my conversation with Gilbert Strang how does it feel to be one of the modern-day rock stars of mathematics I don't feel like a rock star that's kind of crazy for old math person but it's true that the videos in linear algebra that I made way back in 2000 I think I've been watched a lot and well it's partly the importance of linear algebra which way I'm sure you'll ask me and give me a chance to say that linear algebra as a subject has just surged in importance but also I it was a class that I taught a bunch of times so I kind of got it organized and any I'm enjoy doing it was just the videos were just the class so they're on OpenCourseWare and YouTube and translated that's fun but there's something about that chalkboard in the and the simplicity of the way you explain the basic concepts in the beginning I you know to be honest when I went to undergrad you know do linear algebra broadly of course this lineage I before going through the course at my university I was going through open courseware I was you were my instructor oh yeah you're right yeah and that I mean we're using your book and I mean that that the fact that there is thousands you know hundreds of thousands millions of people that watch that video I think that's yeah that's really powerful so how do you think the idea of putting lectures online would really MIT OpenCourseWare has innovated that was a wonderful idea you know I think the story that I've heard is the committee committee was appointed by the president president vest at that time a wonderful guy and the idea of the committee was to figure out how a mighty could make be like other universities market the market work we were doing and then they didn't see away and after a weekend and they had an inspiration came back to the president vest and said what if we just gave it away and he decided that was ok good idea so that's a crazy idea that's uh if we think of a university is a thing that creates a product yes isn't knowledge right the you know the kind of educational knowledge isn't the products and giving that away are you surprised that you went through it the result that he did it well knowing a little bit president vest it was like him I think and and it was really the right idea you know MIT as I kind of it's known for being high level technical things and and this is the best way we can say tell we can show what MIT really is like because the the in my case those 1806 videos are just teaching the class they were there in 26100 they're kind of fun to look at people write to me and say oh you've got a sense of humor but I don't know where that comes through somehow I big friendly with a class I like students and and then your algebra the subject we got to give this subject most of the credit it it really has come forward and importance in these years so let's talk about linear algebra a little bit because it is such a it's both a powerful and a beautiful a subfield of mathematics so what's your favorite specific topic in linear algebra or even math in general to give a lecture on to convey to tell a story to teach students okay well on the teaching side so it's not deep mathematics at all but I I'm kind of proud of the idea of the four subspaces there are four fundamental subspaces which are of course known before long before my name for them but can you go through them can you go through the future I can yes so the first one to understand is so the matrix is maybe I should say the matrix what is the matrix what's a matrix well so we have a like a rectangle of numbers so it's got n columns got a bunch of columns and also got an M rows let's say and the relation between so of course the columns and the rows it's the same numbers so there's got to be connections there but they're not simple the they're much the columns might be longer than the rows and they've all different the numbers are mixed up first space to think about is take the columns so those are vectors those are points in n dimensions what's the vector so a physicist would imagine a vector or might imagine a vector as a arrow you know in space or the point it ends at in space for me it's a column of numbers does it you often think of this is very interesting in terms of linear algebra of a vector you think a little bit more abstract than the how it's very commonly used perhaps yeah you think this arbitrary Speight multi-dimensional right away I'm in high dimensions and in the room lands yeah that's right in the lecture I tried a so if you think of two vectors in ten dimensions I'll do this in class and I'll readily admit that I have no good image in my mind of a vector of arrow int n dimensional space but whatever you can a you can add one bunch of ten numbers to another bunch of ten numbers so you can add a vector to a vector and you can multiply a vector by three and that's if you know how to do those you've got linear algebra you know ten dimensions yeah you know there's this beautiful thing about math if we look string theory and all these theories which are really fundamentally derived through math yeah but it very difficult to visualize it yeah how do you think about the things like a 10 dimensional vector that we can't really visualize yeah do you and and yet math reveals some beauty Oh underlying me yeah our world in that weird thing we can't visualize how do you think about that difference well probably I'm not a very geometric person so I'm probably thinking in three dimensions and the beauty of linear algebra is that is that it goes on to ten dimensions with no problem I mean that if you're just seeing what happens if you add two vectors in 3d you then you can add them in ten D or you're just adding the ten components so so I I can't say that I have a picture but yet I try to push the class to think of a flat surface in ten dimensions so a plane in ten dimensions and so that's one of the spaces take all the columns of the matrix take all their combinations so on so much of this column so much of this one then if you put all those together you get some kind of a flat surface that I call a vector space space of vectors and and my imagination is just seeing like a piece of paper in 3d but anyway so that's one of the spaces that's space number one the column space of the matrix and then there's the row space which is as I said different but came came from the same numbers so we got the column space all combinations of the columns and then we've got the row space all combinations of the rows so those are those words are easy for me to say and I can't really draw them on a blackboard but I try with my thick chalk everybody everybody likes that railroad chalk and me too I wouldn't use anything else now and and then the other two spaces are perpendicular to those so like if you have a plane in 3d just a plane is just a flat surface in 3d then perpendicular to that plane would be a line so that would be the null space so we've got two we've got a column space a row space and they're two perpendicular spaces so those four fit together in the in a beautiful picture of a matrix yeah yeah it's sort of a fundamental it's not a difficult idea comes comes pretty early in 1806 and it's basic planes in these multi-dimensional spaces how how difficult of an idea is that to come to do you think if you if you look back in time yeah I think mathematically it makes sense but I don't know if it's intuitive for us to imagine just what we're talking about feels like calculus is easier to I see into it well calculus I have to admit calculus came earlier earlier than linear algebra so Newton and Leibniz were the great men to understand the key ideas of calculus but linear algebra to me is like okay it's the starting point because it's all about flat things calculus has got all the complications of calculus come from the curves the bending this is a curved surfaces linear algebra the surfaces are all flat nothing bends in linear algebra so it should have come first but it didn't and calculus also comes first in in high school classes in in college class it'll be freshman math I'll be calculus and then I say enough of it like okay get to get to the good stuff and that you think linear algebra should come first well it really yeah I'm okay with it not coming first but it should yeah it should it's simpler because everything is flat yeah everything's flat of course for that reason you sort of sticks to one dimension or so or eventually you do multivariate but that basically means two dimensions linear algebra you take off into ten dimensions no problem it just feels scary and dangerous to go beyond two dimensions that's all if everything is flat you can't go wrong so what concept or theorem in linear algebra or in math you find most beautiful it gives you pause that leaves you and oh well I'll stick with linear algebra here I hope that viewer knows that really mathematics is amazing amazing subject and deep deep connections between ideas that didn't look connected some they turned out they were but if we stick with linear algebra so we have a matrix that's like the basic thing a rectangle of numbers and might be a rectangle of data you're probably going to ask me later about data science where and often data comes in a matrix you have you know maybe every column corresponds to a to a drug in every row corresponds to a patient and and if the patient reacted favorably to the drug then you put up some positive number in there anyway rectangle of numbers a matrix is basic so the big problem is to understand all those numbers you got a big big set of numbers and what are the patterns what's going on and so one of the ways to break down that matrix into simple pieces is uses something called singular values and that's come on as fundamental in the last and certainly in my lifetime I can values bro you if you have viewers who've done engineering math or or more basic linear algebra eigenvalues were in there but those are restricted to square matrices and data comes in rectangular matrices so you got to take that you got to take that next step I'm I'm always pushing math faculty get on do it don't do it do it singular values so those are a way to break to make to find these the important pieces of the matrix which add up to the whole matrix so so you're breaking a matrix into simple pieces and the first piece is the most important part of the data the second piece is the second most important part and then often so a data scientist will like if if a data scientist can find those first and second pieces stop there the rest of of the data is probably round off you know we're yeah experimental error maybe so you're looking for the important part yeah so what do you find beautiful about singular values well yeah I didn't give the theorem so here's the here's the idea of singular values every matrix every matrix rectangular square whatever you can be written as a product of three very simple special matrices so that's the theorem every matrix can be written as a rotation times a stretch which is just a matrix diagonal matrix otherwise all zeros except on the one diagonal and then a third and the third factor is another rotation so rotation stretch rotation is the breakup of a of any matrix the structure that the ability that you can do that what do you find appealing what do you find beautiful bodies well geometrically as I freely admit the mate action of a matrix it's not so easy to visualize but everybody can visualize a rotation take-take-take two-dimensional space and just turn it around the around the center take three-dimensional space so a pilot has to know about well what are the three the yaw is one of them I've forgotten all the three turns that a pilot makes up to ten dimensions you've got ten ways to turn but you can visualize a rotation take the space and turn it and you can visualize a stretch so to break a a matrix with all those numbers in it into something you can visualize rotate stretch rotate it's pretty neat pretty neat that's pretty powerful on YouTube just consuming a bunch of videos and just watching what people connect with and what they really enjoy and are inspired by math seems to come up again and again I I'm trying to understand why that is perhaps you can help yeah I mean give me clues so it's not just to let the kinds of lectures that you give but it's also just other folks were like with numberphile there's a channel where they just chat about things that are extremely complicated actually yeah people nevertheless connect with them you know what do you think that is what it's wonderful isn't it I mean I wasn't really aware of it do so we're we're conditioned to think math is hard math is abstract math is just for a few people but it isn't that way a lot of people quite like math and they liked it I get messages from people saying you know now I'm retired I'm gonna learn some more math I get a lot of those it's really encouraging and I think what people like is that there's some order you know a lot of order and or you know things are not obvious but they're true so it's really cheering to think that that so many people really want to learn more about math yeah in terms of truth again sorry to slide into philosophy at times yeah math does reveal pretty strongly what things are true yeah I mean it's the whole point of proving things is and yet sort of our real world is messy and complicated what do you think about the nature of truth that math reveals oh wow because it is a source of comfort like you've mentioned yeah that's right well I have to say I'm not much of a philosopher I just like numbers you know I think yeah I would you this was before you had you had to go in when you're in the other filling your teeth yeah I kind of just take it yeah so I what I did was think about math you know like take powers of 2 2 4 8 16 up until the time the two stopped hurting and the dentist said you're through or Counting yeah so so that was the source of just such a piece almost yeah what what what what is it about math you think that brings that yeah what is that well you know where you are yeah symmetry it's it's certainty the fact that you know if you'd to if you multiply 2 by itself 10 times you get a thousand 24 period that's everybody's gonna get that do you see math is a powerful tool or is an art form so it's both that's that's really one of the neat things you can you can be an artist and and like math you can be a engineer and use math which are you which am I what did you connect with most yeah I'm in here between I'm certainly not a artist type philosopher type person might sound that way this morning but I'm not yeah I I really enjoy teaching engineers because they they they go for an answer and yeah so of probably within the mountain MIT math department most people enjoy teaching people teaching students who get the abstract idea I'm okay with with I'm good with engineers who are looking for a way to find answers yeah actually that's a interesting question do you think do you think for teaching and in general but thinking about new concepts do you think it's better to plug in the numbers or to think more abstractly so looking at theorems and proving the theorems or actually you know building up a basically tuition of the theorem or the method the approach and then just plugging in numbers and seeing it work you know well certainly many of us like to see examples first we understand it might be a pretty abstract sounding example like a three dimensional rotation how are you gonna how are you gonna understand a rotation in 3d or in 10 D or but and then some of us like to keep going with it to the point where you got numbers where you got 10 angles 10 axes 10 angles but the best the great mathematicians is probably I don't know if they do that because they they for them for them an example would be a highly abstract thing to the rest of it right but nevertheless working within the space of examples yeah example it seems to examples of structure our brain seemed to connect with that yeah yeah so uh I'm not sure if you're familiar with him but Andrew yang is the presidential candidate currently running yeah with the math in all capital letters and his hats as a slogan Isis stands for make America think hard okay I'll vote for it so and his name rhymes with yours yang strang so but he also loves math and then he comes from that world but he also looking at it makes me realize that math science and engineering are not really part of our politics right political discourse about political a government in general yeah what do you think that is well what are your thoughts on that in general well certainly somewhere in this system we need people who are comfortable with numbers comfortable with quantities you know if you if you say this leads to that they see it it's undeniable but isn't it strange to you that we have almost no I mean I'm pretty sure we have no elected officials in Congress or obviously the president yeah that is either it has an engineering degree or a mess yeah well that's too bad you know a few could a few who could make the connection yeah it would have to be people who are at the door who understand engineering or science and at the same time can make speeches and and lead yeah inspire people yeah yeah you were speaking of inspiration the president of the Society for industrial applied mathematics oh yeah as a major organization in math and Padma what do you see as a role of that society you know in our public discourse right yeah so well it was fun to be president at the at the time of years year two years around around 2000 his hope as president of a pretty small society but nevertheless it was a time when math was getting some more attention in Washington but yeah I got to give a little 10 minutes to into committee of the House of Representatives talking about why mint and then actually it was fun because one of the members of the house he had been a student had been in my class what do you think of that yeah as you say a pretty rare most most members of the House have had a different training different background but there was one from New Hampshire who who was my friend really bye-bye being in the class yeah so that those years were good then of course other things take take over and importance in Washington and maths math just at this point is not so visible but for a little moment it was there's some excitement some concern about artificial intelligence in Washington now yes about the future yeah and I think at the core of that is math well it is yeah yeah but maybe it's hidden maybe he's wearing a different hat but uh well artificial intelligence and and particularly can I use the words deep learning it's a deep learning is a particular approach to understanding data again you've got a big a whole lot of data where data is just swapping the computers of the world and and - and understand it out of all those numbers to find what's important you know in climate in everything and artificial intelligence is two words for for one approach to data deep learning is a specific approach there which uses a lot of linear algebra so I got into it I thought okay I've got to learn about this so maybe from your perspective and I asked the this most basic question yeah how do you think of a neural network what is it and you're on the 1 yeah ok so can I start with a idea about deep learning what does that mean sure what is deep learning what is deep learning yeah so so we're trying to learn from all this day that we're trying to learn what's important what was some What's it telling us so you've you've got data you've got some inputs for which you know the right outputs the question is can you see the pattern there can you figure out a way for a new input which we haven't seen to to get the to understand what the output will be from that new input so we've got a million inputs with their out so we're trying to create some patterns some rule that'll take those inputs those million training inputs which we know about to the correct million outputs and this idea of a neural net is part of the structure of the of our new way to create a create a rule we're looking for a rule that will take these training inputs to the known outputs and then we're going to use that rule on new inputs that we don't know the output and see what comes the linear algebra is a big part of defining a finding that rule that's right linear algebra is a big part not all the part people were leaning on matrices that's good still do linear is something special it's all about straight lines and flat planes and and and data isn't quite like that you know it's it's more complicated so you got to introduce some complication so you have to have some function that's not a straight line and it not only doubt it on linear nonlinear nonlinear and it turned out that the it was enough to use the function that's one straight line and then a different one halfway that's so piecewise then he said one piece has one slope one piece the other piece has the second slope and so that introduced getting that nonlinear simple non-linearity in blue the problem open that little piece makes it sufficiently complicated to make things interesting because you're gonna use that piece over and over a million times so you so you it has a it has a fold in the in the graph the graph two pieces and but when you fold something a million times you've got you've got a pretty complicated function that's pretty realistic so that's the thing about neural networks is they have a lot of these a lot of these that's so why do you think neural networks by using a sort of formulating an objective function very not a plane yeah function holds lots of folds of the inputs the outputs why do you think they work to be able to find a rule that we don't know is optimal but it just seems to be pretty good in a lot of cases what's your intuition is it surprising to you as it is to many people you have an intuition of why this works at all well I'm beginning to have a better intuition this idea of things that are piecewise linear flat pieces but but with folds between them like think of a roof of a complicated infinitely complicated house or something that curved it almost curved but every piece is flat that that's been used by engineers that ideas been used by engineers is used by engineers big time something called the finite element method if you want to if you want to design a bridge design a building design airplane you're using this idea of piecewise flat as a good simple computable approximation to pay your you have a sense that that there's a lot of expressive power in this kind of piecewise linear yeah well that's combined together you use the right word if you measure the expressivity how how many how complicated a thing can can this piecewise flat guys express the answer is very complicated yeah what do you think are the limits of such piecewise linear or just neural networks its passivity of nool nose well you would have said a while ago that they're just computational limits it you you know you the problem beyond a certain size a supercomputer isn't going to do it but that does keep getting more powerful so that's that limit has been moved to allow more and more complicated surfaces so in terms of just mapping from inputs to the outputs looking at data yeah what do you think of you know in a context in your networks in general data is just tensor vectors matrices tensors how do you think about learning from data what how much of our world can be expressed in this way how useful is this process is the I guess that's another way to asking what are the limits of this well that's a good question yeah so I guess the whole idea of deep learning is that there's something there to learn if the data is totally random just produced by random number generators then the we're not going to find a useful rule because there isn't one so the extreme of having a rule is like knowing Newton's law you know if you hit a hit a ball and moves so that's where you had laws of physics Newton and and Einstein and other great great people have have found those laws and laws of the the the distribution of oil in a underground thing I mean that so so engineers petroleum engineers and understand how how oil will sit in a in an underground basin so there were rules now now the the new idea of artificial intelligence is learn the rules instead of instead of figuring out the rules by with help from Newton or Einstein the computer is looking for the rules so that's another step but if there are no rules at all for that the computer could find if it's totally random data well you've got nothing you've got no science to discover it's the automated search for the underlying rules yeah search for the rules yeah exactly yeah there will be a lot of random parts a lot I'm not knocking random because the that's there the the the there's a lot of randomness built in but there's got to be some basic it's almost always signature right in most there's got to be some signal yeah if it's all noise then there's there's you're not gonna get it anywhere well this world around us does seem to be this seem to always have a signal some kind yeah yeah they discovered right that's it so what excites you more the we just talked about a little bit of application what excites me more theory or the application of mathematics well for myself I'm probably a theory person I'm not I'm speaking here pretty freely about applications but I'm not a person who really I'm not a physicist or a chemist or a neuroscientist so for myself I like this structure and this flat subspaces and and and the relation of matrices columns to rows that's my part in the spectrum so the really science is a big spectrum of people from asking practical practical questions and answering them using some math than some math guys like myself or in the middle of it and then the geniuses of math and physics and chemistry and who are finding fundamental rules and doing doing really understanding nature that's at its lowest simplest level maybe just a quick in broad strokes from your perspective what is uh where does the linear algebra sit as a subfield of mathematics what what are the various subfields a year okay a you think about in relation to linear algebra so the big fields of math or algebra as a whole and problems like calculus and differential equations so that's a second quite different field then maybe geometry deserves to be under sort of as a different field to understand the geometry of high dimensional surfaces so I think am I allowed to say this here I think this is where personal view comes and I think math for thinking about undergraduate math what millions of students study I think we overdo the calculus at at the cost of the algebra at the cost of linear dog titled calculus versus linear that's right and and you say that linear algebra wins so you can you want can you dig into that a little bit why does linear algebra win right well ok I'm the viewer is gonna think this guy is biased not true I'm just telling the truth as it is yeah so I feel linear algebra is just a nice part of math that people can get the idea of they can understand something it's a little bit abstract because once you get to ten or a hundred dimensions and very very very useful that's what's happened in in my lifetime is the the the importance of data which does come in matrix form so it's really set up for algebra it's not set up for a differential equation and now let me fairly add probability they're ideas of probability and statistics have become very very important i've also jumped forward so and that's not that's different from linear algebra quite different so now we really have three major areas to me calculus linear algebra of matrices and probability statistics and they all deserve a important place and and calculus has traditionally had a had a lion's share of the time and disproportionate share yes but thank you proportionate that's a good work of the the love and attention from the excited young minds yeah I know it's hard to pick favorites but what is your favorite matrix what's my favorite matrix okay so my favorite matrix is square I admit it's a square bunch of numbers and it has twos running down the main diagonal and on the next diagonal so think of top left to bottom right twos down down the middle of the matrix and minus ones just above those twos and minus ones just below those twos and otherwise all zeros so mostly zeros just three nonzero diagonals coming down what is interesting about it well all the different ways it comes up you see it in engineering you see it as analogous in calculus to second derivative so calculus learns about taking the derivative the figuring out how much how fast something's changing but second derivative now that's also important that's how fast the change is changing how fast the graph is bending how fast it's it's curving and my Feinstein showed that that's fundamental to understand space so second derivatives should have a bigger place in calculus second mice matrices which are like the linear algebra version of second derivatives are neat in in linear algebra yeah just everything comes out right with those guys beautiful what did you learn about the process of learning by having taught so many students math over the years whoo that is hard I'll have to admit here that I'm not I'm not really a good teacher because I don't get into the exam part the exams the part of my life that I don't like and grading them and giving the students a or B or whatever I do it because it's I'm supposed to do it but but I tell the class at the beginning I don't know if they believe me probably they don't I tell the class I'm here to teach you I'm here to teach you math and not to grade you and but they're thinking okay this guy it's gonna you know when's he gonna kids he's gonna give me an A - is he gonna give me a b-plus what what would have you learn about the process of learning of learning yeah well maybe to be elated to give you a legitimate answer about learning I should have paid more attention to the assessment the evaluation part at the end but I like the teaching part at the start that's the sexy part to tell somebody for the first time about a matrix Wow but is there are there moments so you are teaching a concept are there moments of learning that you just see in the students eyes you don't need to look at the grades yeah you see in their eyes that that you hooked them that you know that you connect with them in a way where you know what they fall in love with this yes beautiful world amazing see that it's got some beauty it's yeah or conversely yeah that they give up at that point is the opposite the darkest a the math I'm just not good at math and alcohol yeah yeah maybe because of the approach in the past they were discouraged but don't be discouraged it's it's too good to miss yeah I well if I'm teaching a big class do I know when I think maybe I do sort of I mentioned at the very start the four fundamental subspaces and the structure of the fundamental theorem of linear algebra the fundamental theorem of linear algebra that is the relation of those four subspaces those four spaces yeah so I think that I feel that the class gets it when they want to see the what advice do you have to a student just starting their journey mathematics today how do they get started Oh No yeah that's hard well I hope you have a teacher professor who is still enjoying what he's doing and what he's teaching they're still looking for new ways to teach and and to understand math because that's the pleasure to the moment when you see oh yeah that works so it's s about the material you yeah you study it's more about the source of the teacher being full of passion yeah more about the fun yeah there's a moment of of getting it but in terms of topics linear algebra well that's not my topic but oh there's beautiful things in geometry to understand what's wonderful is that in the end there there's a pattern there there's their rules that that that are followed in biology as there are in every field you describe imitation as as a hundred percent wonderful except for the great stuff yeah and the grades were great yeah when you look back at your life yeah what memories bring you the most joy and pride well that's a good question I certainly feel good when I maybe I'm giving a class in in 1806 that's mi t--'s linear algebra course that I started so sort of there's a good feeling that okay I started this course a lot of students take it quite a few like it yeah so I'm I'm sort of happy when I feel I'm helping helping make a connection between ideas and students between theory and the reader yeah it's I get a lot of very nice messages from people who've watched the videos and it's inspiring I just not maybe it's take this chance to say thank you well there's millions of students who you've taught and I am grateful to be one of them so good birth thank you so much has been an honor thank you for talking to it was a pleasure thanks thank you for listening to this conversation with Gilbert Strang and thank you to our presenting sponsor cash app downloaded used collects podcast you'll get ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future if you enjoy this podcast subscribe on youtube we had five stars in an apple podcast support on patreon I'll connect with me on Twitter finally some closing words of advice from the great Richard Fineman study hard would interest you the most in the most undisciplined irreverent an original manner possible thank you for listening and hope to see you next time you |
Dava Newman: Space Exploration, Space Suits, and Life on Mars | Lex Fridman Podcast #51 | the following is a conversation with David Newman she's the Apollo program professor at MIT and the former deputy administrator of NASA and has been a principal investigator on for spaceflight missions her research interests are an aerospace biomedical engineering investigating human performance in varying gravity environments she has designed and engineered and built some incredible spacesuit technology namely the biosuit that we talk about in this conversation due to some scheduling challenges on both our parts we only had about 40 minutes together and in true engineering style she said I talk fast you picked the best questions let's get it done and we did it was a fascinating conversation about space exploration and the future of space suits this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars an apple podcast supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M a.m. for the first time this show is presented by cash app the number one finance app in the App Store cash wrap is the easiest way to send money to your friends and this is also the easiest way to buy sell and deposit a big coin most Bitcoin exchanges take days for bank transfer to become investable so cash up it takes seconds lest as little as $1 and now you own Bitcoin have several conversations about bitcoin coming up on this podcast decentralized digital currency is a fascinating technology in general to explore both at the technical and the philosophical level cash app is also the easiest way to try and grow your money with their new investing feature unlike investing tools that force you to buy entire shares of stock cash app amazingly lets you instantly invest as little or as much as you want some stocks in the market are hundreds if not thousands of dollars per share and now you can still own a piece with as little as one dollar 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conversation with daiva Neumann you circumnavigated the globe on boat so let's look back in history 500 years ago Ferdinand Magellan's crew was first to circumnavigate the globe but he died I think people don't know like halfway through and so did 242 of the 260 sailors that took that three-year journey what do you think it was like for that crew at that time heading out into the unknown to face probably likely death do you think they were filled with fear with excitement probably not fear I think in all of exploration is the challenge and the unknown so probably wonderment and then just the when you really are sailing the world's oceans you have extreme weather of all kinds when we were circumnavigating it was challenging a new dynamic you really appreciate Mother Earth you appreciate the winds of the ways so back to Magellan his crew since they really didn't have you know a three-dimensional of the globe of the earth when they went out just probably looking over the horizon thinking what's there what's there so I would say the challenge that had to be really important in terms of the team dynamics on that leadership had to be incredibly important team dynamics too how do you keep people focused on the mission do you think the psychology that's interesting that's probably echoes of that and the space exploration stuff we'll talk about so the psychology of the dynamics between the human beings on the mission is important absolutely for a Mars mission it's there's lots of challenges technology but you know since I specialize in keep my astronauts alive the cycle social issues the psychology of a psychosocial Team Dynamics leadership that's you know we're all people so that's gonna be that's a he always a huge impact one of the top three I think of any isolated confined environment it can any mission that is really pretty extreme so your twitter handle is david explorer so when did you first fall in love with the idea of exploration ah that's a great question maybe as long as I can remember as I grew up in Montana in the Rocky Mountains and Helena and the capital is so literally a mount Helen it was my backyard was right up there so exploring being in the mountains looking at caves just running around but always being in nature so since my earliest memories I you know think of myself is kind of exploring the natural beauty of the Rocky Mountains where I grew up so exploration is not living at changing domain it's just anything so the natural domain of any kind but going out to the woods into the place you haven't been it's all exploration I think so yeah I have a pretty all-encompassing definition what about space exploration when we first captivated by the idea that we little humans couldn't venture out into the space into the great unknown enough space so it's a great year to talk about that the 50th anniversary of Apollo 11s I was alive during Apollo and specifically Apollo when I was 5 years old and I distinctly remember that I remembered that humanity I'm sure I probably didn't know their names at the time you know there's Neil Armstrong Buzz Aldrin and never forget Michael Collins in orbit no those three man you know doing something that just seemed impossible seemed impossible a decade earlier even a year earlier but the Apollo program really inspired me and then I think it actually just taught me to dream to any impossible mission could be possible with enough focus yeah I'm sure you need some luck but you definitely need the leadership you need the the focus of the mission so since an early age I thought of course people should be interplanetary of course people we need people on earth and we're gonna have people exploring space as well that seemed obvious you know at that age it opened it up before we saw men on the moon it was not obvious to me at all but once we understood that yes absolutely astronauts that's what they do they explore they go into space and they land on other planets or moons so again maybe a romanticized philosophical question but when you look up at the stars knowing that you know there's at least a hundred billion of them in the Milky Way galaxy right so we're really a small speck in this giant thing that's the visible universe how does that make you feel about our efforts here I love the perspective I love that perspective I always opened my public talks with a big Hubble Space Telescope image looking out until you mentioned just now the solar system the Milky Way because I really think it's really important to know that we're just a small pill blue dot we're really fortunate we're on the best planet by far life is fantastic that we know of you're confident this is the best planet that we know of I mean I searched my research as you know in mission worlds and when will we find life I think actually in probably the next decade we find probably past life probably the evidence of past life on Mars let's say you think there was pretty like once life on Mars or do you think there's currently I'm more comfortable saying about 3.5 billion years ago feel pretty confident there was life on Mars just because then it had an electromagnetic shield it had an atmosphere has wonderful gravity level three 3s jeez fantastic you know you're all super human we can all slam dunk a basketball I mean it's gonna be fun to play sports on Mars but so I think we'll find past that no fossilize probably the evidence of past life on Mars currently that's again we need the next decade but the evidence is mounting for sure we do have the organics we're finding organics we have water seasonal water on Mars we used to just know about the ice caps you know north and south pole now we have seasonal water we do have the building blocks for life on Mars we really need to dig down into the soil because everything on the top surface is radiated but once we find down will we see any any life form so we see any bugs I leave it open as a possibility but I feel pretty certain that past life or you know fossilized life forms will find and then we have to get to all these ocean worlds these these beautiful moons of other other planets since we know they have water and we're looking for since simple search for life or follow the water you know carbon-based life that's the only life we know there could be other life forms that we don't know about but it was hard to search for them because we don't know so in our search for life in the solar system it's definitely you know search you know let's follow the water and look for the building blocks of life do you think in the next decade we might see hints of past life or even currently I think so I'm pretty active you humans have to be involved or can this be robots and Rovers and probably teams I mean we've been at it on Mars in particularly 50 years we've been exploring Mars for 50 years great day that right our images of Mars today are phenomenal now we know how Mars lost its atmosphere you know we're starting to know because of the lack of the electromagnetic shield we know about the water in Mars so we've been studying 50 years with our robots we still haven't found it so I think once we have a human mission there we just accelerate things it's always humans and our Rovers and robots together but we just have to think that 50 years we've been looking at Mars Mars and taking images and doing the best science that we can people need to realise Mars this really far away it's really hard to get to you know this is extreme extreme exploration we mentioned Magellan first or all of the wonderful explorers and sailors of the past which kind of are lots of my inspiration for exploration Mars is a different ballgame I mean no sir eight months to get there year and a half to get home I mean it's really extreme environment in all kinds of ways but the kind of organism might be able to see himself on Mars or kind of microorganisms perhaps yeah I remember that humans were canal you know we're hosts right we're hosts all of our bacteria and viruses right do you think it's a big leap from the viruses in the bacteria to us humans put another way do you think on all those moons beautiful wet moons that you mentioned you think there's intelligent life out there I hope so I mean that's that's the hope but you know we don't have the scientific evidence for that now I think all the evidence we have in terms of life existing is much more compelling again because we have the building blocks of life now when that life turns into intelligence that's a big unknown if we ever meet do you think we would be able to find a common language I hope so we haven't met yet it's just so far I mean do physics just play a role here look at all these exoplanets 6000 exoplanets I mean even the couple dozen earth-like planets or exoplanets that really look like habitable planets these are very earth-like they look like they have all the building blocks I can't wait to get there the only thing is they're 10 to 100 light years away so scientifically we know they're there we know that they're habitable they have you know everything going from right you know we call the Goldilocks zone not too hot not too cold just perfect for how habitability for life but now the reality is if they're ten at the best to a hundred to thousands of light-years away so what's out there but I just can't think that we're not the only ones so absolutely life life in the universe probably intelligent life as well do you think there needs to be fundamental revolutions and how we the tools we use to travel through space in order for us to venture outside of our solar system or do you think the the ways the Rockets the ideas we have now the engineering ideas we have now will be enough to venture out well it's a good question right now yokas can speed of light is it is it is the limit we don't have a warp speed warp drive to explore our solar system to get to Mars to explore all the planets then we need a technology push but technology push here is just advanced propulsion would be great I could get humans to Mars and say you know three to four months not eight months I mean have the time 50% reduction that's great in terms of safety and wellness of the orbital my County but physics rules in orbital mechanics we can't defy physics I love that so the new physics I mean look at quantum you know look at quantum theories so you never know exactly I mean we are always learning so we definitely don't know all the physics that exists too but where we still have to it's not science fiction you know we still have to pay attention to physics in terms of our speed of travel for space flight so you were the deputy administrator of NASA during the Obama administration there's a current Artemis program that's what kind of cooed mission to the moon and then perhaps the Mars what are you excited about there what are your thoughts on this program what are the biggest challenges do you think of getting to the moon of landing to the moon once again and then the big step to Mars well I love you know the moon program now Artemis we it is definitely we've been in low-earth orbit I love low Earth orbit too but I just always look at those three phases so Laura Thoren where we've been 40 years so definitely time to get back to deep space time to get to the moon there's so much to do on the moon I hope we don't get stuck on the moon for 50 years I really want to get to the moon spent the next decade first with the lander then humans there's just a lot to explore but to me is a big technology push it's only three days away so the moon is definitely the right place so we kind of buy down our technology we invest in specifically habitats life support systems so we need suits we really need to understand really how to live off planet we've been off planet and low Earth orbit but still that's only you know 400 kilometers up 20 or 50 miles right so we get to the moon is really is a great proving ground for the technologies and now we're in deep space radiation becomes a huge issue can to keep our astronauts well alive and I look at all of that investment for moon moon exploration to the ultimate goal you know the horizon goals we call it to get people to Mars but we just don't go to Mars tomorrow right we really need a decade on the moon I think investing in the technologies learning making sure the astronauts are their health you know they're safe and well and also learning so much institute research you know utilization is are you in situ resource utilization is huge when it comes to exploration for the moon and Marceau was need a testbed and to me it really is a lunar testbed and then we use those same investments to think about getting people to Mars in the 2030s so developing sort of a platform of all the kind of research tools of all the what's the resource you know the can you speak to that yeah so is are you for the moon it's will go to the South Pole and fascinating we have images of it of course we know there's permanently shaded areas and Shackleton crater and there's areas that are permanently in the Sun well it seems that there's a lot of water ice you know water that's in trapped in ice and the lunar craters that's the first place you go why because it's water and when you want to try to it could be fuel you know life-support systems so you kind of get in you go where the water is and so when the moon is kind of for resources utilization but to learn how to it can we make the fuels out of the resources that are on the moon we have to think about 3d printing right you don't get to bring all this mass with you you have to learn how to literally live off the land we need a pressure shell we need to have an atmosphere for people to to live in so all of that is going to bind down the technology doing the investigation doing the science what are the basically the lunar volatiles you know what is that ice on the moon how much of it is there what are the resources look like to me that helps us that's just the next step in getting humans to Mars and it's cheaper and more effective to sort of develop some of these difficult challenges like solve some of these challenges practice develop test and so on on the moon absolutely so Mars absolutely people are gonna love to get to the moon you get to you have a beautiful earth rise I mean you have the most magnificent view of Earth being off planet so it just makes sense I think we're gonna have thousands lots of people hopefully tens of thousands in low-earth orbit because Laura Thoren it's a beautiful place to go and look down on the earth but people want to return home I think that the lunar explorers will also want to do round trips and you know beyond beyond the moon three-day trip explore do science also because the lunar day is 14 days in a lunar Nights also 14 days so in that 28-day cycle half of it is in light half of us in dark so people would probably want to do you know a couple week trips month long trips not longer than that what I mean by people what do you think explorers yeah astronauts are gonna be civilians in the future too not all not all astronauts are gonna be government astronauts actually when I was at NASA we changed we actually got the law changed to recognize astronauts that are not only government employees you know NASA astronauts or European Space Agency astronaut or Russian space agency that astronauts because of the big push we put in the private sector that astronauts essentially you're gonna be astronauts you get over a hundred kilometres up and I think once you've done orbital orbital flight then you're an astronaut so a lot of private citizens are going to become astronauts do you think one day you might step foot on the moon Mars I'm gonna it's my life's work to get the next generation to Mars that's that's that's you are even younger than you you know my students generation yes will be the Martian explorers I'm just working to facilitate that but that's not gonna be me hey the moon is pretty good and it's a lot tough I mean it's still a really tough mission it is an extreme mission exactly it's great for exploration but doable but again before Apollo we didn't think getting humans to the moon was even possible so we kind of made that possible but we need to go back we absolutely need to go back we're investing in the heavy lift launch capabilities that we need to get there we haven't had that you know since the Apollo days since since Saturn five so now we have three options on the board that's what's so fantastic NASA has its you know Space Launch System SpaceX is gonna have its it's heavy capability and Blue Origin is coming along too with heavy lifts so that's pretty fantastic from where I said I'm the Apollo program professor today I have zero heavy lift launch capability I can't wait just in a few years we'll have three different heavy lift launch capabilities so that's pretty exciting you know your heart is perhaps with NASA but you mentioned SpaceX and Blue Origin what are your what are your thoughts of SpaceX and the innovative efforts they're from the sort of private company aspect oh they're great they're mine remember that the investments in SpaceX is government funding it's NASA funding is US Air Force funding just as it should be because you're bettin on a company who is moving fast has some new technology development so I love it so when as it really was under our public-private partnerships so necessarily the government needs to fund these these startups now SpaceX is no longer a start-up but you know it's been at it for for ten years this has some axis learned a lot of lessons but it's great because it's the way you move faster and also some private industry folks and businesses will take a lot more risk that's also really important for the government what do you think about that culture of risk I mean sort of NASA and the government are exceptionally good at delivering sort of safe like there's a little bit more of a culture of caution and safety and sort of this kind of solid engineering and I think SpaceX wall has the same kind of stuff it has a little bit more of that startup feel where they take the bigger risk is that exciting for you to see seeing bigger risks in this case absolutely and the best scenario is both of them working together because there's really important lessons learned especially when you talk about human spaceflight safety quality assurance these things are the utmost importance but both aviation and space you know when human lives are at stake on the other hand government agencies NASA it can be European Space Agency you name it they become very bureaucratic pretty risk-averse move pretty slowly so I think the best is when you you combine the partnerships from both sides industry necessarily has to push the government take some more risks you know I got me they're smart risk or actually gave an award at NASA for failing smart I love that you've seen kind of break up when the cultures say no that they don't look Apollo that was a huge risk it was done well yeah so there's always a culture of safety quality assurance you know engineering you know edit at its best but on the other hand you want to get things done and you have to also get them you have to bring the cost down you know for when it comes to launch we really have to bring the cost down and get the frequency up and so that's what the newcomers are doing they're really pushing that so it's about the most exciting time I can imagine for for spaceflight again a little bit it really is the democratization of spaceflight opening it up not just because the launch capability but the science we can do on a CubeSat what you can do now for very those used to be you know student projects that we would go through conceive design implement and think about what a small satellite would be now they're the most you know there's a really advanced instrument science instruments are flying on little team cube sets that pretty much anyone can afford so there's not a there's every nation you know every place in the world can fly a cube set and so that's cube set Oh CubeSat is a this is called one YouYube says we measure in terms of units so you know just in terms of I put my both my hands together that's one unit two units trees so little small satellites so cube sets are for small satellites and we actually go by mass as well you know small satellite might be 100 kilos 200 kilos all well under a thousand kilos cube sets then our the next thing down from small sets you know basically you know kilos a tens of kilos things like that but kind of the building blocks cube sets are fantastic designs kind of modular design so I can take a1 u1 1 unit of CubeSat and you know but what if I have a little bit more money and payload I can fly three of them and just basically put a lot more instruments on it but essentially think about something the size of a shoebox if you will you know that would be a cube set and those how do those help empower you in terms of doing size doing exponents oh right now there's getting back to private industry planet the company is you know flying cube sets and literally looking down on earth and orbiting or taking a picture if you will of Earth every day every 24 hours covering the entire Earth so terms of earth observations in terms of climate change in terms of our changing earth it's revolutionising because they're affordable we can put a whole bunch of them up the telecoms we're all you know on our cell phones and GPS we have our telecoms but those used to be very expensive satellites providing that service now we can fly a whole bunch of modular cube sets so it really is breakthrough in terms of modularity as well as cost reduction so so that's one exciting set of developments is there something else that you've been excited about and like reusable rockets perhaps that you've seen in the last few years yeah well the reusability you had your usability is awesome I mean is the best now we have to remember the shuttle was a reusable vehicle yes which an shuttle is an amazing aerospace engineer I mean the shuttle is still just the most gorgeous elegant extraordinary design of a space vehicle it was reusable it just wasn't affordable but the reusability of it was really critical because we flew it up it did come back so the notion of usability and I think absolutely now what we're doing with we you know a global we but with SpaceX of origin sitting the Rockets up recovering the first stages where if they can regain seventy percent cost savings that's huge and just seeing the control you know the convenient control and dynamics person is just seeing that rocket come back and land oh yeah that's it never gets old it's exciting so it's so cool give me the landing is when I stand up start clapping he's just just the control control I go and hit that landing it's you know it's gymnastics for for a rocket ships better see these guys stick a landing or foot it's just wonderful so every time like I said every time I see ya the reusability and the rockets coming back and landing so precisely it's really exciting so it is it is actually that's a game-changer we are in a new era of lower costs and a lot the higher frequency and it's the world not just NASA it's many nations are really upping their frequency of launches you've done a lot of exciting research design engineering on spacesuits what does the spacesuit of the future look like very tight fitting suit we use them a chemical counter pressure to pressurize right directly on the skin seems that it's technically feasible we're still at the research and development stage we don't have a flight system but technically is feasible so we do a lot of work in the materials you know what materials do we need to pressurize someone what's the patterning we need that's what our patents are in the patterning kind of how we apply this is a third of an atmosphere just to sort of take a step back you have this incredible bio suit wear them it's tight fitting so it allows more mobility and so on so maybe even to take a bigger step back like what are the functions that a space it should perform here so start from the beginning a spacesuit is the world's smallest spacecraft so I really that's the best definition I can give you right now we fly gas pressurized suits but think of developing and designing an entire spacecraft so then you take all those systems and you shrink them around a person provide them with oxygen to breathe scrub out their carbon I know make sure they have pressure they need a pressure environment to live on so really a spacesuit is a shrunken you know spacecraft in its entirety has communications exactly so you really thermal control a little bit of radiation not so much radiation protection but thermal control humidity you know oxygen breeze so all those life support systems as well as the pressure production so it's an engineering marvel you know the spacesuits that have flown because they really are entire spacecraft that a small spacecraft that we have around a person but they're very massive but 140 kilo is the current suit and they're not mobility suits so since we're going back to the Moon and Mars we need a planetary suit we need a mobility suit so that's where we've kind of flipped the design paradigm I study astronauts I study humans in motion and if we can map that motion I want to give you a full flexibility you know move your arms and legs I really want you to be like a Olympic athlete in extreme Explorer I don't want to waste any of your energy so we take it from the human design so I take a look at humans we measure them we model them and then I say okay can I put a spacesuit on them that goes from the skin out so rather than a gas pressurized shrinking that spacecraft around the person so here's how humans perform can I design a spacesuit literally from the skin out that's what we've come up with mechanical counter-pressure some patterning and that way it could be order of magnitude less in terms of the mass and it should provide maximum mobility for moon or mars what's mechanical cano pressure like how the heck can you even begin to create something that's tight-fitting so and still doesn't protect you from the elements and so on and the hold of the pressure thing design channels we've been working on it from so you can either put someone in a balloon that's one way to do it that's conventional that's me that means the balloon doesn't get fresher eyes soon so put someone in a blue it's only a third of an atmosphere to keep someone alive so that's what the current system is so depending on what units you think in 30 kilo Pascal's you know 4.3 pounds per square so much less than the the pressure that's on earth you can still be a human alive with 0.3 and it's alive and happy alive in half India you mix the gases you need here we're we're having this chat and we're both we're at one sea level in Boston it you know one atmosphere but assume nitrogen arsenide you didn't you put a suit if we put someone to a third of an atmosphere so for mechanical counter pressure now so one ways to do it with a balloon and that's what we currently have or you can apply the pressure directly to the skin I only have to give you a third of an atmosphere right now you and I are very happy in one atmosphere so so you know we can so if I put that pressure a third of an atmosphere on you I just have to do it consistently you know across you know all of your body and your limbs and it'll be a gas pressurized helmet doesn't make sense to shrink wrap the head we don't need to there's no benefits of like shrink wrapping have you put on gas pressurized helmet because the helmet then the future of suits you asked me about the helmet just becomes your information portal yes so we'll have augmented reality you'll have all the information you need should have you know the maps that I need I'm on the moon okay well hey smart helmet then show me the map show me the topography hopefully it has the lab embedded too if it has really great cameras maybe I can see with that regolith that's just lunar dust and dirt what's that made of we talked about the water so the helmet then really becomes this information portal is how I see kind of the IT architecture the helmet is really allowing me to you know use all of my modalities of an explorer that I'd like to so cameras voiceover images if it were really good it would kind of be would have lab capabilities as well okay so the pressure comes for the body comes from the mechanical pressure just fascinating now what aspect when I look at BIOS they just the suits you're working on sort of from a fashion perspective they look awesome is that is that a small part of it too oh absolutely because the teams that we work with of course I'm an engineer there's engineering students there's design students there's architects so it really is a very much a multidisciplinary team so sure colors aesthetics materials all those things we pay attention to so it's not just an engineering solution it really is a much more holistic it's a suit it's a suit you're you know so we really have to pay attention to all those things and so that's the design team that we work with and my partner get rowdy you know we were partners in this in terms of he comes from an architect or industrial design background so bringing those skills to bear as well we team up with industry folks who are in athletic performance and designers so it really is a team that brings all those skills together so what role does the spacesuit play in our long-term staying in Mars sort of exploring the doing all the work that astronauts do but also perhaps civilians one day almost like taking steps towards colonization of Mars what world is a spacesuit play there so you always need life-support system pressurized habitat and I like to say we're not going to Mars to sit around you know even if you land and have the lander you're not going there to stay inside that's for darn sure we're going there to search for the evidence of life that's why we're going to Mars so you need a lot of mobility so for me the suit is the best way to give the human mobility we're always so gonna need Rovers we're gonna need robots so for me exploration is always a suite of explorers some people are gonna some of the suite of explorers or humans but many are gonna be robots smart systems things like that but I look at it it's kind of all those capabilities together make the best exploration team so let me ask I loved artificial intelligence and you thought I've also saw that you've enjoyed the movie space obviously 2001 a Space Odyssey let me ask the question about Hal 9000 that makes a few decisions there that prioritizes the mission over the the astronauts do you think from a high philosophical question do you think hell did the right thing prioritizing the mission I think our artificial intelligence will be smarter in the future for a Mars mission it's a great question of is that the reality isn't for a Mars mission you know we need fully autonomous systems we will get humans but they have to be fully autonomous and that's a really important concept because you know there's not going to be a Mission Control on earth you know I'd you know 20-minute time leg there's just no way you're gonna control so fully a ton so people have to be fully autonomous as well but all of our systems as well and so that's that's the big design challenge so that's why we test them out on the moon as well when we have a okay a few seconds you know a three-second time leg you can test him out we have to really get autonomous exploration down you asked me earlier about Magellan and Magellan and his crew they they left right they were autonomous mm-hmm you know they were autonomous they left and they were on their own to figure out that mission then when they hit land they have resources as Institue resource utilization and everything else they brought with them so we have to I think have that mindset for expression again back to the moon it's more the testing ground the proving ground with technologies but when we get to Mars it's so far away that we need fully autonomous systems so I think that's that's where again AI and autonomy come in really robust autonomy things that we don't have today yet so they're on the drawing boards but we really need to test them out because that's that's what we're up against so fully autonomous meaning like self-sufficient there's still a role for the human in that picture do you think there will be a time when AI systems just beyond doing fully autonomous flight control will also help or even take mission decisions like how did that's interesting it depends I mean they're gonna be designed by humans as you mentioned humans are always in the loop I mean we might be on earth we might be in orbit on Mars maybe the systems the Landers down on the surface of Mars but I think we're gonna get we are right now just on earth-based systems you know AI systems that are incredibly capable and you know training them with all the data that we have now you know petabytes of data from Earth what I care about for the autonomy and AI right now how we're applying it and research is to look at earth and look at climate systems I mean that's the it's not for Mars to me today right now AI is to eyes on earth all of our space data compiling that using supercomputers because we have so much information and knowledge and we need to get that into people's hands we need first there's the educational issue with climate and our changing climate then we need to change human behavior that's the biggie so this next decade it's urgent we take care of our own spaceship which is spaceship earth so that's to me where my focus has been for AI systems using whatever is out there kind of imagining also what the future situation is the satellite imagery of Earth of the future if you can hold that in your hands that's gonna be really powerful will that help people accelerate positive change for Earth and for us to live in balance with earth I hope so and kind of start with the ocean systems so oceans to land to air and kind of using all the space data so it's a huge role for artificial telogen to help us analyze I call it curating the data using the data it has a lot - of visualizations as as well do you think and a weird dark question do you think human species can survive if we don't become interplanetary in the next century or a couple of centuries absolutely we can survive I don't think Mars is option B actually I think is all about saving spaceship earth and humanity I simply put you know earth doesn't need us but we really need our you know all humanity needs to live in balance with earth because earth has been here a long time before we ever showed up and it'll be here a long time after it's just a matter of how do we want to live with all living beings you know much more in balance because we need to take care of the earth and right now we're we're not so that's the urgency and I think it is the next decade to try to live much more sustainably live more in balance with earth I think the human species has a great long optimistic future but we have to act it's urgent we you know it we have to change behavior we we have to work we have to realize that we're all in this together it's just one blue bubble it's for Humanity so when I think people realize that we're all astronauts that's the great news is everyone's be an astronaut you birth we're all on we're all astronauts of spaceship earth and okay this is our mission this is our mission to take care of the planet and yet as we explore out from our from our spaceship earth here out into the space what do you think the next 50 hundred 200 years look like for space exploration I'm optimistic so I think that we'll have lots of people thousands of people tens of thousands people who knows maybe millions in low-earth orbit that's just a place that we're gonna have people and actually some industry manufacturing things like that that that dream I hope we realize getting people to the moon so I can envision a lot of people on the moon again it's great place to living or visiting probably visiting and living if you want to most people are gonna want to come back to to earth I think but there'll be some people and it's not such a long it's a good view it's a beautiful view so I think that we will have you know many people on the moon as well I think there'll be some people you told me well you know hundreds of years out so we'll have people will be interplanetary for sure as a species so I think we'll be on the moon I think we'll be on Mars Venus no it's already a runaway greenhouse gas so not a great great place for science you know Jupiter all of in within the solar system great place for all of our scientific probes I don't see so much in terms of human physical presence we'll be exploring them so we we live in our minds there because we're exploring them and going on those journeys but it's really our choice in terms of our decisions of how in balance you know we're gonna be living here on the earth when do you think the first woman first person will step on Mars I asked about Mars Vaughn I'm gonna do everything I can to make sure it happens in the 2030s so I say mid you know 2020 mid 20 you know 2025 2030 five will be on the moon and hopefully with more people than less but first with you know a few astronauts it'll be global international folks but we really need those 10 years I think on the moon and then so by the way later in the decade in the 2030s we will have all the technology and know-how and we need to get that you know human mission to Mars 10 live in exciting times and David thank you so much for leading the way and thank you for talking today thank you my pleasure thanks for listening to this conversation and thank you to our presenting sponsor cash app remember to use code Lexx podcast when you download cash out from the App Store Google Play Store you'll get ten bucks ten dollars and ten dollars will go to first a stem education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future thank you and hope to see you next time you |
Michael Kearns: Algorithmic Fairness, Privacy & Ethics | Lex Fridman Podcast #50 | the following is a conversation with Michael Kern's he's a professor at the University of Pennsylvania and a co-author of the new book ethical algorithm that is the focus of much of this conversation it includes algorithmic fairness bias privacy and ethics in general but that is just one of many fields that Michael's a world-class researcher in some of which would touch on quickly including learning theory or the theoretical foundation of machine learning game theory quantitative finance computational social science and much more but on a personal note when I was an undergrad early on I worked with Michael on an algorithmic trading project in competition that he led that's when I first fell in love with algorithmic game theory while most of my research life has been a machine learning human robot interaction the systematic way that game theory reveals the beautiful structure and our competitive and cooperating world of humans has been a continued and inspiration to me so for that and other things I'm deeply thankful to Michael and really enjoyed having this conversation again in person after so many years this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars on Apple podcasts supported on patreon or simply connect with me on Twitter at lex Friedman's both Fri D ma n this episode is supported by an amazing podcast called pessimists archive Jason the host the show reached out to me looking to support this podcast and so I listened to it to check it out and I listened I mean I went through it Netflix binge style at least 5 episodes in a row it's not one of my favorite podcast and I think it should be one of the top podcasts in the world frankly it's a history show about why people resist new things each episode looks at a moment in history when something new was introduced something that today we think of as commonplace like recorded music umbrellas bicycles cars chests coffee the elevator and the show explores why freaked everyone out the latest episode on mirrors and vanity still stays with they think about vanity in the modern day of the Twitter world that's the fascinating thing about the show is that stuff that happened long ago especially in terms of our fear of new things repeats itself in the modern day and so has many lessons for us to think about in terms of human psychology and the role of Technology in our society anyway you should subscribe but listen the pessimist archive I highly recommended and now here's my conversation with Michael Kern's you mentioned reading Fear and Loathing in Las Vegas in high school and having more or a bit more of a literary mind so what books non-technical non computer science would you say had the biggest impact on your life either intellectually or emotionally you've dug deep into my history I see deep yeah I think well my favorite novel is Infinite Jest by David Foster Wallace which actually coincidentally much of it takes place in the halls of buildings right around us here at MIT so that certainly had a big influence on me and as you noticed like when I was in high school I actually Stephen started college as an English major so was very influenced by sort of badge genre of journalism at the time and thought I wanted to be a writer and then realized that an English major teaches you to read but it doesn't teach you how to write and then I became interested in math and computer science instead well in your new book ethical algorithm you kind of sneak up from a algorithmic perspective on these deep profound philosophical questions of fairness of privacy in thinking about these topics how often do you return to that literary mind that either you had yeah I'd like to claim there was a deeper connection but but there you know I think both Aaron and I kind of came at these topics first and foremost from a technical angle I mean you know I'm kind of consider myself primarily and originally a machine learning researcher and I think as we just watched like the rest of the society the field technically advanced and then quickly on the heels of that kind of the the buzzkill of all the antisocial behavior by algorithms just kind of realized there was an opportunity for us to do something about it from a research perspective you know a more to the point in your question I mean I do have an uncle who is literally a moral philosopher and so in the early days of our technical work on fairness topics I would occasionally you know run ideas behind him so I mean I remembered an early email I sent to him in which I said like oh you know here's a specific definition of algorithmic fairness that we think is some sort of variants of Rawls II in fairness what do you think and I thought I was asking a yes-or-no question and I got back there kind of classical philosophers responsive well it depends if you look at it this way then you might conclude this and that's when I realized that there was a real kind of rift between the ways philosophers and others had thought about things like fairness you know from sort of a humanitarian perspective and the way that you needed to think about it as a computer scientist if you were going to kind of implement actual algorithmic solutions but I would say the algorithmic solutions take care of some of the low-hanging fruit sort of the problem is a lot of algorithms when they don't consider fairness they are just terribly unfair and when they don't consider privacy they're terribly they violate privacy sort of algorithmic approach fixes big problems but there's though you get when you start pushing into the gray area that's when you start getting into this philosophy of what it means to be fair that's starting from Plato what what is justice kind of questions yeah I think that's right and I mean I would even not go as far as you want to say that that sort of the algorithmic work in these areas is solving like the biggest problems and you know we discussed in the book the fact that really we are there's a sense in which we're kind of looking where the light is in that you know for example if police are racist in who they decide to stop and frisk and that goes into the data there's sort of no undoing that Downs by kind of clever algorithmic methods and I think especially in fairness I mean I think less so in privacy where we feel like the community kind of really has settled on the right definition which is differential privacy if you just look at the algorithmic fairness literature already you can see it's gonna be much more of a mess and you know you've got these theorems saying here are three entirely reasonable desirable notions of fairness and you know here's a proof that you cannot simultaneously have all three of them so I think we know that algorithmic fairness compared to algorithmic privacy is gonna be kind of a harder problem and it will have to revisit I think things that have been thought about by you know many generations of scholars before us so it's very early days for fairness I think so before we get into the details of differential privacy and then the fairness side I mean linger on the philosophy but do you think most people are fundamentally good or do most of us have both the capacity for good and evil within us I mean I'm an optimist I tend to think that most people are good and want to do to do right and that deviations from that or you know kind of usually due to circumstance to people being bad at heart with people with power are people at the heads of governments people at the heads of companies people at the heads of maybe so financial power markets do you think the distribution there is also most people are good and have good intent yeah I do I mean my statement wasn't qualified to people not in positions of power I mean I think what happens in a lot of the you know the the cliche about absolute power corrupts absolutely I mean you know I think even short of that you know having spent a lot of time on Wall Street and also in arenas very very different from Wall Street like academia you know one of the things I think I've benefited from by moving between two very different worlds is you you become aware that you know these were it's kind of developed their own social norms and they develop their own rationales for you know behavior for instance that might look unusual to outsiders but when you're in that world it doesn't feel unusual at all and I think this is true of a lot of you know professional cultures for instance and and you know so then you're maybe slippery slope is too strong of a word but you know you're in some world where you're mainly around other people with the same kind of viewpoints and training and worldview as you and I think that's more of a source of you know kind of abuses of power then sort of you know there being good people and evil people and and it's somehow the evil people are the ones that somehow rise to power that's really interesting so it's the within the social norms constructed by that particular group of people you're all trying to do good but because it's a group you might be you might drift into something that for the broader population it does not align with the values of society that kind of that's the word yeah I mean or nothing you drift but even the things that don't make sense to the outside world don't seem unusual to you so it's not sort of like a good or a bad thing but you know like so for instance you know on on in the world of finance right there's a lot of complicated types of activity that if you are not immersed in that world you cannot see why the purpose of that you know that activity exists at all it just seems like you know completely useless and people just like you know pushing money around and when you're in that world right you're you and you learn more you your view does become more nuanced right you realize okay there is actually a function to this activity and force in some cases you would conclude that actually if magically we could eradicate this activity tomorrow it would come back because it actually is like serving some useful purpose it's just a useful purpose that's very difficult for outsiders to see and so I think you know lots of professional work environments or cultures as I might put it kind of have these social norms that you know domain sense to the outside world academia is the same right I mean lots of people look at academia and say you know what the hell are all of you people doing why are you paid so much in some cases at taxpayer expenses to do you know to publish papers and military reads you know but when you're in that world you come to see the value for it and but even though you might not be able to explain it to you know the person in the street alright and in the case of the financial sector tools like credit might not make sense to people like is it's a good example of something that does seem to pop up and be useful or or just the power of markets and just in general capitalism yeah and Finance I think the primary example I would give is leverage right so being allowed to borrow to sort of use ten times as much money as you've actually borrowed right so so that's an example of something that before I had any experience in financial markets I might have looked at and said well what is the purpose of that that just seems very dangerous and it is dangerous and it has proven dangerous but you know if the fact of the matter is that you know sort of on some particular time scale you are holding positions that are you know very unlikely to you know loo you know they're you know that your value at risk their variance is like 1 or 5 percent then it kind of makes sense that you would be allowed to use a little bit more than you have because you have you know some confidence that you're not going to lose it all in a single day now of course when that happens we've seen what happens you know not not too long ago but but you know but the idea that it serves no useful economic purpose under any circumstances is definitely not true we'll return to the other side of the coast Silicon Valley and the problems there as we talk about privacy as we talk about fairness at the high level and I'll ask some sort of basic questions with the hope to get at the fundamental nature of reality but from a very high level what is an ethical algorithm so I can say that an algorithm has a running time of using Big Oil notation and login I can say that a machine learning algorithm classified cat versus dog with 97% accuracy do you think there will one day be a way to measure sort of in the same compelling way as the big ol notation of this algorithm is 97% ethical first of all many rif for a second on your specific and login examples so because early in the book when we're just kind of trying to describe algorithms period we say like ok you know what's an example of an algorithm or an algorithmic problem first of all I could sorting right yeah I'm a bunch of index cards with numbers on them and you want to sort them and we describe you know an algorithm that sweeps all the way through finds the the smallest number puts it at the front then sweeps through again finds the second smallest number so we make the point that this is an algorithm and it's also a bad algorithm in the sense that you know it's quadratic rather than n log n which we know is optimal for sorting and we make the point that sort of like you know so even within the confines of a very precisely specified problem there's you know there might be many many different algorithms for the same problem with different properties like some might be faster in terms of running time some I use less memory some might have you know better distributed implementations and and so the point is is that already we're used to you know in computer science thinking about trade-offs between different types of quantities and resources and there being you know better and worse algorithms and and our book is about that part of algorithmic ethics that we know how to kind of put on that same kind of quantitative footing right now so you know just to say something that our book is not about our book is not about kind of broad fuzzy notions of fairness it's about very specific notions of fairness there's more than one of them there are tensions between them right but if you pick one of them you can do something akin to saying this algorithm is 97% ethical you can say for instance the you know for this lending model the false rejection rate on black people and white people is within 3 percent right so we might call that to a 97% ethical algorithm in a 100% ethical algorithm would mean that that difference is 0% in that case fairness is specified when two groups however they're defined are given to you that's right so the and and then you can sort of mathematically start describing the algorithm but nevertheless the the part where the two groups are given to you I mean unlike running time you know we don't in a computer science talk about how fast an algorithm feels like when it runs true we measure an ethical starts getting into feelings so for example an algorithm runs you know if it runs in the background it doesn't disturb the performance of my system it'll feel nice I'll be okay with it but if it overloads the system will feel unpleasant so in that same way ethics there's a feeling of how socially acceptable it is how does it represent the moral standards of our society today so in that sense and sorry to linger on that for some high low philosophical question is do you have a sense we'll be able to measure how ethical and algorithm is first of all I didn't certainly didn't mean to give the impression that you can kind of measure you know memory speed trade-offs you know and and that there's a complete you know mapping from that on to kind of fairness for instance or ethics and and accuracy for example in the type of fairness definitions that are largely the objects of study today and starting to be deployed you as the user of the definitions you need to make some hard decisions before you even get to the point of designing fair algorithms one of them for instance is deciding who it is that you're worried about protecting who you're worried about being harmed by for instance some notion of discrimination or unfairness and then you need to also decide what constitutes harm so for instance in a lending application maybe you decide that you know falsely rejecting a credit worthy individual you know sort of a false negative is the real harm and that false positives ie people that are not credit worthy or are not going to repay your loan to get a loan you might think of them as lucky and so that's not a harm although it's not clear that if you are don't have the means to repay a loan that being given a loan is not also a harm so you know you know the literature is sort of so far quite limited in that you sort of need to say who do you want to protect and what would constitute harm to that group and when you ask questions like will algorithms feel ethical one way in which they won't under the definitions that I'm describing is if you know if you are an individual who is falsely denied alone incorrectly denied a loan all of these definitions basically say like well you know your compensation is the knowledge that we are we are also falsely denying loans to other people you know other groups at the same rate that we're doing it's to you and and you know there and so there is actually this interesting even technical tension in the field right now between these sort of group notions of fairness and notions of fairness that might actually feel like real fairness to individuals right they they might really feel like their particular interests are being protected or thought about by the algorithm rather than just you know the groups that they happen to be members of is there parallels to the big o-notation of worst-case analysis so is it important to looking at the worst violation of fairness for an individual is important to minimize that one individual so like worst case analysis is that something you think about or I mean I think we're not even at the point where we can sensibly think about that so first of all you know we're talking here both about fairness applied at the group level which is a relatively weak thing but it's better than nothing and also the more ambitious thing of trying to give some individual promises but even that doesn't incorporate I think something that you're hinting at here is what a chime I'll call subjective fairness right right so a lot of the definitions I mean all of the definitions in the algorithmic fairness literature are what I would kind of call received wisdom definitions it's sort of you know somebody like me sits around and things like okay you know I think here's a technical definition of fairness that I think people should want or that they should you know think of as some notion of fairness maybe not the only one maybe not the best one maybe not the last one but we really actually don't know from a subjective standpoint like what people really think is fair there's you know we've we've just started doing a little bit of work in in our group that actually doing kind of human subject experiments in which we you know ask people about you know we ask them questions about fairness we survey them we you know we show them pairs of individuals in let's say a criminal recidivism prediction setting and we ask them do you think these two individuals should be treated the same as a matter of fairness and to my knowledge there's not a large literature in which ordinary people are asked about you know they they have sort of notions of their subjective fairness elicited from them it's mainly you know kind of scholars who think about fairness no right and I'm making up their own definitions and I think I think this needs to change actually for many social norms not just for fairness right so there's a lot of discussion these days in the AI community about interpretable AI or understandable AI and as far as I can tell everybody agrees that deep learning or at least the outputs of deep learning are not very understandable and people might agree that sparse linear models with integer coefficients are more understandable but nobody's really asked people you know there's very little literature on you know sort of showing people models and asking them do they understand what the model is doing and I think that in all these topics as these fields mature we need to start doing more behavioral work yeah which is so one of my deep passions of psychology and I always thought computer scientists will be the the best future psychologists in a sense that data is especially in this modern world the data is a really powerful way to understand and study human behavior and you've explored that with your game theory side of work as well yeah I'd like to think that what you say is true about computer scientists and psychology from my own limited wandering into human subject experiments we have a great deal to learn not just computer science but AI and machine learning more specifically I kind of think of as imperialist research communities in that you know kind of like physicists in an earlier generation computer scientists kind of don't think of any scientific topic as off limits to them they will like freely wander into areas that others have been thinking about for decades or longer and you know we usually tend to embarrass ourselves yes in those efforts for for some amount of time like you know I think reinforcement learning is a good example right so a lot of the early work in reinforcement learning I have complete sympathy for the control theorist that looked at this and said like okay you are reinventing stuff that we've known since like the 40s right but you know in my view eventually this sort of you know computer scientists have made significant contributions to that field even though we kind of embarrassed ourselves for the first decade so I think if computer scientists are gonna start engaging in kind of psychology human subjects type of research we should expect to be embarrassing ourselves for a good ten years or so and then hope that it turns out as well as you know some other areas that we've waded into so you kind of mentioned this just the linger on the idea of an ethical algorithm of idea of group sort of group thinking an individual thinking and we're struggling that there's one of the amazing things about algorithms and your book and just this field of study is it gets us to ask like forcing machines converting these ideas into algorithms is forcing us to ask questions of ourselves as a human civilization so there's a lot of people now in public discourse doing sort of group thinking thinking like there's particular sets of groups that we don't want to discriminate against and so on and then there is individuals sort of in the individual life stories the struggles they went through and so on now like in philosophy it's easier to do group thinking because you don't you know it's very hard to think about individuals there's so much variability but with data you can start to actually say you know what group thinking is too crude you're actually doing more discrimination by thinking in terms of groups and individuals can you linger on that kind of idea of group versus individual and ethics and and is it good to continue thinking in terms of groups in in algorithms so let me start by answering a very good high level question with a slightly narrow technical response which is these group definitions of fairness like here's a few groups like different racial groups may be gender groups may be age what-have-you and let's make sure that you know from none of these groups do we you know have a false negative rate which is much higher than any other one of these groups okay so these are kind of classic group aggregate notions of fairness and you know but at the end of the day an individual you can think of as a combination of all of their attributes right they're a member of a racial group they're they have a gender they have an age you know and many other you know demographic properties that are not biological but that you know are are still you know very strong determinants of outcome and personality in the light so one I think useful spectrum is to sort of think about that array between the group and this individual and to realize that in some ways asking for fairness at the individual level is to sort of ask for group fairness simultaneously for all possible combinations of groups so in particular so in particular yes you know if I build a predictive model that meets some definition of fairness by race by gender by age by what-have-you marginally to get a slightly technical sort of independently I shouldn't expect that model to not to discriminate against disabled Hispanic women over age 55 making less than fifty thousand dollars a year or annually even though I might have protected each one of those attributes marginally so the optimization actually that's a fascinating way to put it so you're just optimizing the one way to achieve the optimizing fairness for individuals just to add more and more definitions of groups at each and it's right along so you know at the end of the day we could think of all of ourselves as groups of size one because eventually there's some attribute that separates you from me and everybody from everybody else in the world okay and so it is possible to put you know these incredibly coarse ways of thinking about their nests and these very very individualistic specific ways on a common scale and you know one of the things we've worked on from a research perspective is you know so we sort of know how to you know we in relative terms we know how to provide fairness guarantees at the coarsest end of the scale we don't know how to provide kind of sensible tractable realistic fairness guarantees at the individual level but maybe we could start creeping towards that by dealing with more you know refined subgroups I mean we we gave a name to this phenomenon where you know you protect you you you enforce some definite definition of fairness for a bunch of marginal attributes or features but then you find yourself discriminating against a combination of them we call that fairness gerrymandering because like political gerrymandering you know you're giving some guarantee at the aggregate level yes but that when you kind of look in a more granular way at what's going on you realize that you're achieving that aggregate guarantee by sort of favoring some groups in discriminating against other ones and and so there are you know it's early days but there are algorithmic approaches that let you start creep and creeping towards that you know individual end of the spectrum does there need to be human input in the form of weighing the value of the importance of each kind of group so for example is it is it like so gender say crudely speaking male and female and then different races are we as humans supposed to put value on saying gender is 0.6 and racist 0.4 in terms of in the big optimization of achieving fairness is that kind of what humans I mean most of you know I mean of course you know I don't need to tell you that of course technically one could incorporate such weights if you wanted to into a definition of fairness you know fairness is an interesting topic in that having worked in in the book being about both fairness privacy and many other social norms fairness of course is a much much more loaded topic so privacy I mean people want privacy people don't like violations of privacy violations of privacy cause damage angst and and bad publicity for the companies that are victims of them but sort of everybody agrees more data privacy would be better than less data privacy and and you don't have these somehow the discussions of fairness don't become politicized along other dimensions like race and about gender and you know you know whether we you and you know did you quickly find yourselves kind of revisiting topics that have been kind of unresolved forever like affirmative action right sort of you know like why are you protecting and some people will say why are you protecting this particular racial group and and others will say what we need to do that as a matter of retribution other people will say it's a matter of economic opportunity and I don't know which of you know whether any of these are the right answers but you sort of fairness is sort of special in that as soon as you start talking about it you inevitably have to participate in debates about fair to whom at what expense to who else I mean even in criminal justice right um you know where people talk about fairness in criminal sentencing or you know predicting failures to appear or making parole decisions or the like they will you know they'll point out that well these definitions of fairness are all about fairness for the criminals and what about fairness for the victims right so when I basically say something like well the the false incarceration rate for black people and white people needs to be roughly the same you know there's no mention of potential victims of criminals in such a fairness definition and that's the realm of public discourse I just listened to two people listening intelligent squares debates us edition just had a debate they have this structure we have a old Oxford style or whatever they're called debates those two versus two and they talked about affirmative action and it was the is incredibly interesting that it's still there's really good points on every side of this issue which is fascinating to listen yeah yeah I agree and so it's it's interesting to be a researcher trying to do for the most part technical algorithmic work but Aaron and I both quickly learned you cannot do that and then go out and talk about and expect people to take it seriously if you're unwilling to engage in these broader debates that are entirely extra algorithmic right there they're not about you know algorithms and making algorithms better they're sort of you know as you said sort of like what should society be protecting in the first place when you discuss the fairness an algorithm that uh that achieves fairness whether in the constraints and the objective function there's an immediate kind of analysis you can perform which is saying if you care about fairness in gender this is the amount that you have to pay for in terms of the performance of the system like do you is there a role for the statements like that in a table and a paper or do you want to really not touch that like you know we want to touch that and we do touch it so I mean just just again to make sure I'm not promising your your viewers more than we know how to provide but if you pick a definition of fairness like I'm worried about gender discrimination and you pick a notion of harm like false rejection for a loan for example and you give me a model I can definitely first of all go on at that model it's easy for me to go you know from data to kind of say like okay your false rejection rate on women is this much higher than it is on men okay but you know once you also put the fairness in to your objective function I mean I think the table that you're talking about is you know what we would call the Pareto curve right you can literally trace out and we give examples of such plots on real datasets in the book you have two axes on the x-axis is your error on the y-axis is unfairness by whatever you know if it's like the disparity between false rejection rates between two groups and you know your algorithm now has a knob that basically says how strongly do I want to enforce fairness and the less unfairly you know we you know if the two axes are err and unfairness we'd like to be at 0-0 we'd like to zero error and zero fair unfairness simultaneously anybody who works in machine learning knows that you're generally not going to get to zero error period without any fairness constrain whatsoever so that's that that's not gonna happen but in general you know you'll get this you'll get some kind of convex curve that specifies the numerical trade-off you face you know if I want to go from 17 percent error down to 16 percent error what will be the increase in unfairness that I've experienced as a result of that and and so this curve kind of specifies the you know kind of undaunted models models that are off that curve are you know can be strictly improved in one or both dimensions you can you know either make the error better or the unfairness better or both and I think our view is that not only are are these objects these Pareto curves you know there's efficient frontiers as you might call them not only are they valuable scientific objects I actually think that they in the near term might need to be the interface between researchers working in the field and and stakeholders and given problems so you know you could really imagine telling a criminal jurisdiction look if you're concerned about racial fairness but you're also concerned about accuracy you want to you know you want to release on parole people that are not going to recommit a violent crime and you don't want to release the ones who are so you know that's accuracy but if you also care about those you know the mistakes you make not being disproportionately on one racial group or another you can you can show this curve I'm hoping that in the near future it'll be possible to explain these curves to non-technical people that have that are the ones that have to make the decision where do we want to be on this curve like what are the relative merits or value of having lower error versus lower unfairness you know that's not something computer scientists should be deciding for society right that you know the people in the field so to speak the policymakers the regulator's that's who should be making these decisions but I think and hope that they can be made to understand that these trade-offs generally exist and that you need to pick a point and like and ignoring the trade-off you know you're implicitly picking a point anyway right right you just don't know it and you're not admitting it it's just a link out on the point of trade-offs I think that's a really important thing to sort of think about so you think when we start to optimize for fairness there's almost always in most system going to be trade-offs can you like what's the trade-off between just to clarify they've been some sort of technical terms thrown around but a sort of a perfectly fair world why is that why will somebody be upset about that the specific trade-off I talked about just in order to make things very concrete was between numerical error and some numerical measure of unfairness in what is numerical error in the case of just likes a predictive error like you know the probability or frequency with which you release somebody on parole who then goes on to recommit a violent crime or keep incarcerated somebody who would not have recommitted a violent crime so in case of awarding somebody parole or giving somebody Perl or letting them out on parole you don't want them to recommit a crime so it's your system failed in prediction if they happen to do a crime okay so that's the performer that's one axis right and what's the fairness axis so then the fairness axis might be the difference between racial groups in the kind of false false positive predictions namely people that I kept incarcerated predicting that they would recommit a violent-crime when in fact they wouldn't have right and the the unfairness of that just to linger it and allow me to in eloquently to try to sort of describe why that's unfair why unfairness is there the the unfairness you want to get rid of is the in the judges mind the bias of having being brought up to society the slight racial bias the racism that exists in the society you want to remove that from the system another way that's been debated is equality of opportunity versus equality of outcome and there's a weird dance there that's really difficult to get right and we don't as what the firm ative action is exploring that space right and then we this also quickly you know bleeds into questions like well maybe if one group really does recommit crimes at a higher rate the reason for that is that at some earlier point in the pipeline or earlier in their lives they didn't receive the same resources that the other group did right and that and so you know there's always in in kind of fairness discussions the possibility that the the real injustice came earlier right earlier in this individuals life earlier in this group's history etc etc and and so a lot of the fairness discussion is almost the goal is for it to be a corrective mechanism to account for the injustice earlier in life by some definitions of fairness or some theories of fairness yeah others would say like look it's it's you know it's not to correct that injustice it's just to kind of level the playing field right now and Nanyan coarser a falsely incarcerate more people of one group than another group but I mean do you think just it might be helpful just to demystify a little bit about the diff bias or unfairness can come into algorithms especially in the machine learning era right and you know I think many of your viewers have probably heard these examples before but you know let's say I'm building a face recognition system right and so I'm you know kind of gathering lots of images of faces and you know trying to train the system to you know recognize new faces of those individuals from training on you know a training set of those faces of individuals and you know it shouldn't surprise anybody or certainly not anybody in the field of machine learning if my training dataset was primarily white males and I'm training that mmm the model to maximize the overall accuracy on my training data set that you know the model can reduce its air or most by getting things right on the white males that constitute the majority of the data set even if that means that on other groups they will be less accurate okay now there's a bunch of ways you could think about addressing this one is to deliberately put into the objective of the algorithm not to not to optimize the air or at the expense of this discrimination and then you're kind of back in the land of these kind of two-dimensional numerical trade-offs a valid counter-argument is to say like well no you don't have to there's no you know the the notion of the tension between air and Acuras here is a false one you could instead just go out and get much more data on these other groups that are in the minority and you know equalize your dataset or you could train a separate model on those subgroups and you know have multiple models the point I think we would you know we try to make in the book is that those things have cost too right going out and gathering more data on groups that are relatively rare compared to your plurality or more majority group that you know it may not cost you in the accuracy of the model but it's gonna cost you know it's gonna cost the company developing this model more money to develop that and it has also cost more money to build separate predictive models and to implement and deploy them so even if you can find a way to avoid the tension between error and accuracy training a model you might push the cost somewhere else like money like development time research time and alike there are fundamentally difficult philosophical questions in fairness and we live in a very divisive political climate outrage culture there is uh all right folks on 4chan trolls there is social justice warriors on Twitter there is very divisive outraged folks and all sides of every kind of system how do you how do we as engineers build ethical algorithms in such divisive culture do you think they could be disjoint the human has to inject your values and then you can optimize over those values but in our times when when you start actually applying these systems things get a little bit challenging for the public discourse how do you think we can proceed yeah I mean for the most part in the book you know a point that we try to take some pains to make is that we don't view ourselves or people like us as being in the position of deciding for society what the right social norms are what the right definitions of fairness are our main point is to just show that if society or the relevant stakeholders in a particular domain can come to agreement on those sorts of things there's a way of encoding that into algorithms in many cases not in all cases one other misconception though hopefully we definitely dispel is sometimes people read the title of the book and I think not unnaturally fear that what we're suggesting is that the algorithms themselves should decide what those social norms are and develop their own notions of fairness and privacy or ethics and we're definitely not suggesting that the title of the book is ethical algorithm by the way and they didn't think of that interpretation of the title that's interesting yeah yeah I mean especially these days were people are you know concerned about the robots becoming our overlords the idea that the robots would also like sort of develop their own social norms is you know just one step away from that but I do think you know obviously despite disclaimer that people like us shouldn't be making those decisions for society we are kind of living in a world where in many ways computer scientists have made some decisions that have fundamentally changed the nature of our society and democracy and in sort of civil discourse and deliberation in ways that I think most people generally feel are bad these days right so but they had to make so if we look at people at the heads of companies and so on they had to make those decisions right there has to be decisions so there's there's two options either you kind of put your head in the sand and don't think about these things and just let they all go and do what it does or you make decisions about what you value you know open injecting moral values into that with look I don't never mean to be an apologist for the tech industry but I think it's it's a little bit too far to sort of say that explicit decisions were made about these things so let's for instance take social media platforms right so like many inventions in technology and computer science a lot of these platforms that we now use regularly kind of started as curiosities right I remember when things like Facebook came out in its predecessors like Friendster which nobody even remembers now the people people really wonder like what why would anybody want to spend time doing that you know what I mean even even the web when it first came out when it wasn't populated with much content and it was largely kind of hobbyists building their own kind of ramshackle websites a lot of people looked at this this is like what is the purpose of this thing why is this interesting who would want to do this and so even things like Facebook and Twitter yes technical decisions were made by engineers by scientists by executives in the design of those platforms but you know I don't I don't think 10 years ago anyone anticipated that those platforms for instance might kind of acquire undo you know influence on political discourse or on the outcomes of election and I think the scrutiny that these companies are getting now is entirely appropriate but I think it's a little too harsh to kind of look at history and sort of say like oh you should have been able to anticipate that this would happen with your platform and in this sort of gaming chapter of the book one of the points we're making is that you know these platforms right they don't operate in isolation so like that unlike the other topics we're discussing like fairness and privacy like those are really cases where algorithms can operate on your data and make decisions about you and you're not even aware of it okay things like Facebook and Twitter these are you know these are these are systems right these are social systems and their evolution even their technical evolution because machine learning is involved is driven in no small part by the behavior of the users themselves and how the users decide to adopt them and how to use them and so you know you know I'm kind of like who really knew that the you know in until until we saw it happen who knew that these things might be able to influence the outcome of elections who knew that you know they might polarize political discourse because of the ability to you know decide who you interact with on the platform and also with the platform naturally using machine learning to optimize for your own interest that they would further isolate us from each other and you know like feed us all basically just the stuff that we already agreed with and I think it you know we've come to that outcome I think largely but I think it's something that we all learned together including the companies as these things happen you asked like well are there algorithmic remedies to these kinds of things and again these are big problems that are not going to be solved with you know somebody going in and changing a few lines of code somewhere in a social media platform but I do think in many ways there are there are definitely ways of making things better I mean like an obvious recommendation that we we make at some point in the book is like look you know to the extent that we think that machine learning applied for person purposes in things like newsfeed you know or other platforms has led to polarization and intolerance of opposing viewpoints as you know right these these algorithms have models right and they kind of place people in some kind of metric space and and they place content in that space and they sort of know the extent to which I have an affinity for a particular type of content and by the same token they also probably have that that same model probably gives you a good idea of the stuff I'm likely to violently disagree whether it be offended by okay so you know in this case there really is some nod you could tune it says like instead of showing people only what they like and what they want let's show them some stuff that we think that they don't like or that's a little bit further away and you could even imagine users being able to control this you know just like a everybody gets a slider and that slider says like you know how much stuff do you want to see that's kind of you know you might disagree with or is at least further from your interests I can it's almost like an exploration button so just get your intuition do you think engagement so like you staying on the platform you because thing engaged do you think fairness ideas of fairness won't emerge like how bad is it to just optimize for engagement do you think we'll run into big trouble if we're just optimizing for how much you love the platform well I mean optimizing for engagement kind of got us where we are so do you one have faith that it's possible to do better and two if it is how do we do better I mean it's definitely possible to do different right and again you know it's not as if I think that doing something different than optimizing for engagement won't cost these companies in real ways including revenue and profitability potentially short-term at least yeah in the short term right and again you know if I worked at these companies I'm sure that it it would have seemed like the most natural thing in the world also to want to optimize engagement right and that's good for users in some sense you want them to be you know vested in the platform and enjoying it and finding it useful interesting and or productive but you know my point is is that the idea that there is that it's sort of out of their hands as you said or that there's nothing to do about it Never Say Never but that strikes me as implausible as a machine-learning person right I mean these companies are driven by machine learning and this optimization of engagement is essentially driven by machine learning right it's driven by not just machine learning but you know very very large-scale a be experimentation where you gonna have tweaked some element of the user interface or tweaked some component of an algorithm or tweak some component or feature of your click-through prediction model and my point is is that anytime you know how to optimize for something you'll you you know by def almost by definition that solution tells you how not to optimize for it or to do something different engagement can be measured so sort of optimizing for sort of minimizing divisiveness or maximizing intellectual growth over the lifetime of a human being very difficult to measure that that's right so I'm not I'm not claiming that doing something different will immediately make it apparent that this is a good thing for society and in particular I mean ethical one way of thinking about where we are on some of these social media platforms is it you know it kind of feels a bit like we're in a bad equilibrium right that these systems are helping us all kind of optimize something myopically and selfishly for ourselves and of course from an individual standpoint at any given moment like what why would I want to see things in my newsfeed that I found irrelevant offensive or you know or the like okay but you know maybe by all of us you know having these platforms myopically optimized in our interests we have reached a collective outcome as a society that were unhappy with in different ways let's say with respect to things like you know political discourse and tolerance of opposing viewpoints and if Mark Zuckerberg gave you a call and said I'm thinking of taking a sabbatical could you run Facebook for me for four six months what would you how I think no thanks would be the first response but there are many aspects of being the head of the the entire company there are kind of entirely exogenous to many of the things that we're discussing here yes and so I don't really think I would need to be CEO at Facebook to kind of implement the you know more limited set of solutions that I might imagine but I think one one concrete thing they could do is they could experiment with letting people who chose to to see more stuff in their newsfeed that is not entirely kind of chosen to optimize for their particular interests beliefs etc so the the kind of thing is I could speak to YouTube but I think Facebook probably does something similar is they're quite effective at automatically finding what sorts of groups you belong to not based on race or gender so on but based on the kind of stuff you enjoy watching and it gets a YouTube serve it's a it's a difficult thing for Facebook or YouTube to then say well you know what we're going to show you something from a very different cluster even though we believe algorithmically you're unlikely to enjoy that thing so if that's a weird jump to make there has to be a human like at the very top of that system that says well that will be long-term healthy for you that's more than an algorithmic decision or or that same person could say that'll be long-term healthy for the platform the platform for the platform's influence on society outside of the platform right and they you know it's easy for me to sit here and say these things yes but conceptually I do not think that these are kind of totally or should they shouldn't be kind of completely alien ideas right there you know we you could try things like this and it wouldn't be you know we wouldn't have to invent entirely new science to do it because if we're all already embedded in some metric space and there's a notion of distance between you and me and every other every piece of content then you know we know exactly you know the same model that tells you know that dictates how to make me really happy also tells how to make me as unhappy as possible as well right the the focus in your book and algorithmic fairness research today in general is on machine learning like we said is data but and just even the entire AI feel right now is captivated with machine learning with deep learning do you think ideas in symbolic AI or totally other kinds of approaches are interesting useful in the space have some promising ideas in terms of fairness I haven't thought about that question specifically in the context of fairness I definitely would agree with that statement in the large right I mean I am you know one of many machine learning researchers who do believe that the great successes that have been shown in machine learning recently are great successes but they're on a pretty narrow set of tasks I mean I don't I don't think were kind of notably closer to general artificial intelligence now than we were when I started my career I mean there's been progress and and I do think that we are kind of as a community maybe looking a bit where the light is but the light is shining pretty bright there right now and we're finding a lot of stuff so I don't want to like argue with the progress that's been made in areas like deep learning for example this touches another sort of related thing that you mentioned and that people might misinterpret from the title of your book ethical algorithm is it possible for the algorithm to automate some of those decisions sort of higher-level decisions of what kind of like what what should be fair what should be fair the more you know about a field the more aware you are of its limitations and so I'm pretty leery of sort of trying you know there's there's so much we don't all we don't know in fairness even when were the ones picking the fairness definitions and you know comparing alternatives and thinking about the tensions between different definitions that the idea of kind of letting the algorithm start exploring as well I definitely think you know this is a much narrower statement I definitely think the kind of algorithmic auditing for different types of unfairness right so like in this gerrymandering example where I might want to prevent not just discrimination against very broad categories but against combinations of broad categories you know you quickly get to a point where there's a lot of a lot of categories there's a lot of combinations of n features and you know you can use algorithmic techniques to sort of try to find the subgroups on which you're discriminating the most and try to fix that that's actually kind of the form of one of the algorithms we developed for this fairness gerrymandering problem but I'm you know partly because of our technology our sort of our scientific ignorance on these topics right now and also partly just because these topics are so loaded emotionally for people that I just don't see the value I mean again Never Say Never but I just don't think we're at a moment where it's a great time for computer scientists to be rolling out the idea like hey you know you know not only have we kind of figured fairness out but you know we think the algorithm should start deciding what's fair or giving input on that decision I just don't laugh it's like the the cost-benefit analysis to the field of kind of going there right now it just doesn't seem worth it to me that said I should say that I think computer scientists should be more philosophically like should enrich their thinking about these kinds of things I think it's been too often used as an excuse for roboticists or cantatas vehicles for example to not think about the human factor or psychology or safety in the same way like computer science design algorithms that be sort of using is an excuse and I think it's time for basically everybody to become computer scientists I was about to agree with everything you said except that last point I think that the other way of looking at is that I think computer scientists you know and and and many of us are but we need to wait out into the world more right I mean just the the influence that computer science and therefore computer scientists have had on society at large just like has exponentially magnified in the last 10 or 20 years or so and you know you know before when we were just thinking tinkering around amongst ourselves and it didn't matter that much there was no need for sort of computer scientists to be citizens of the world more broadly and I think those days need to be over very very fast and I'm not saying everybody needs to do it but to me like the right way of doing it is to not to sort of think that everybody else is going to become a computer scientist but you know I think you know people are becoming more sophisticated about computer science even laypeople yeah you know though I think one of the reasons we decided to write this book as we thought 10 years ago I wouldn't have tried this because I I just didn't think that sort of people's awareness of algorithms and machine learning you know the general population would have been high and I mean would you would have had to first you know write one of the many books kind of just explicate alais audience first now I think we're at the point where like lots of people without any technical training at all know enough about algorithms machine learning that you can start getting to these nuances of things like ethical algorithms I think we agree that there needs to be much more mixing but I think I think a lot of the onus of that mixing needs to be on the computer science community yeah so just to linger on the disagreement because I do disagree with you on the point that I think if you're a biologist if you're a chemist if you are an MBA business person all of those things you can like if you learn to program and not only program if you learn to do machine learning if you know energy data science you immediately become much more powerful the kinds of things you can do and therefore literature like the library Sciences like so you're speaking I think deaf I think it holds true well you're saying for the next two years but long term if you're interested to me if you're interested in philosophy you should learn to program because then you can scrape data you can and study what people are thinking about on Twitter and then start making those awful conclusions about the meaning of life right I just I just feel like the access to data the digitization of whatever problem you're trying to solve is a fundamentally change what it means to be a computer scientist I mean computer scientists in 20 30 years will go back to being donald knuth style theoretical computer science and everybody would be doing basically they kind of exploring the kinds of ideas the exploring in your book it won't be a computer sighs yeah yeah I mean I don't think I disagree not but I think that that trend of more and more people and more and more disciplines adopting ideas from computer science learning how to code I think that that trend seems firmly underway I mean you know like an interesting digressive question along these lines is maybe in 50 years there won't be computer science departments anymore because the field will just sort of be ambient in all of the different disciplines and you know people will look back and you know having a computer science department will look like having an electricity department or something that's like you know everybody uses this it's just out there I mean I do think there will always be that kind of canoe style core - yeah but it's not an implausible half that we kind of get to the point where the academic discipline of computer science becomes somewhat marginalized because of its very success in kind of infiltrating all of science and society and the humanities etc what is differential privacy or more broadly algorithmic privacy algorithmic privacy more broadly is just the study or the notion of privacy definitions or norms being encoded inside of algorithms and so you know I think we count among this body of work just you know the literature and practice of things like data anonymization which we kind of at the beginning of our discussion of privacy say like okay this is this is sort of a notion of algorithmic privacy it kind of tells you you know something to go do with data but but you know our view is that it's and I think this is now you know quite widespread that it's you know despite the fact that those notions of anonymization kind of redact the in coarsening are the most widely adopted technical solutions for data privacy they are like deeply fundamentally flawed and so you know to your first question what is differential privacy differential privacy seems to be a much much better notion of privacy that kind of avoids a lot of the weaknesses of anonymization notions well while still letting us do useful stuff with data what's anonymization of data so by anonymous a ssin i'm you know kind of referring to techniques like i have a database the rows of that database are let's say individual people's medical records okay and i want to let people use that data maybe i want to let researchers access that data to build predictive models for some disease but i'm worried that that will leak you know sensitive information about specific people's medical records so anonymization broadly refers to the set of techniques where i say like okay i'm first gonna like like i'm gonna delete the column with people's names I'm going to not put you know so that would be like a redaction right I'm just redacting that information I am going to take ages and I'm not gonna like say your exact age I'm gonna say whether you're you know zero to 10 10 to 20 20 to 30 I might put the first three digits of your zip code but not the last two etc etc and so the idea is that through some series of operations like this on the data I anonymize it you know another term of art that's used is removing personally identifiable information and you know this is basically the most common way of providing data privacy but that's in a way that still lets people access the some variant form of the data so at a slightly broader picture as you talk about what does the not immunization mean when you have multiple database like with a Netflix prize when you can start combining stuff together so this is exactly the problem with these notions right is that notions of Adana anonymization removing personally identifying information the kind of fundamental conceptual flaw is that you know these definitions kind of pretend as if the data set in question is the only data set that exists in the world or that ever will exist in the future and of course things like the Netflix prize and many many other examples since the Netflix applies I think that was one of the earliest ones though you know you can redefine oh that were anonymized in the data set by taking that anonymized data set and combining with other allegedly anonymized data sets and may be publicly available information about you for people who don't know the Netflix prize was what was being publicly released this data so the names from those rows were removed but what was released is the preference or the ratings of what movies you like and you don't like and from that combined with other things I think foreign posts and so on you can case it was specifically the Internet Movie Database where where lots of Netflix users publicly rate their move you know their movie preferences and so the anonymized data in Netflix when kaneen and it's it's just this phenomenon I think that we've all come to realize in the last decade or so is that just knowing a few apparently irrelevant innocuous things about you can often act as a fingerprint like if I know you know what what rating you gave to these 10 movies and the date on which you entered these movies this is almost like a fingerprint for you is the see of all Netflix users there were just another paper on this in science or nature of about a month ago that you know kind of 18 attributes I mean my favorite example of this this was actually a paper from several years ago now where it was shown that just from your likes on Facebook just from the taunt you know the things on which you clicked on the thumbs up button on the platform not using any information demographic information nothing about who your friends are just knowing the content that you had liked was enough to you know in the aggregate accurately predict things like sexual orientation drug and alcohol use whether you were the childhood divorced parents so we live in this era where you know even the apparently irrelevant data that we offer about ourselves on public platforms and forums often unbeknownst to us more or less acts as signature or you know fingerprint and that if you can kind of you know do a join between that kind of data and allegedly anonymize data you have real trouble so is there hope for any kind of privacy in a world where a few likes can can identify you so there is differential privacy right what is differential differential privacy basically is a kind of alternate much stronger notion of privacy than these anonymization ideas and it you know it's a technical definition but like the spirit of it is we we compare to to alternate worlds okay so let's suppose I'm a researcher and I want to do you know I there's a database of medical records and one of them's yours and I want to use that database of medical records to build a predictive model for some disease so based on people's symptoms and test results and the like I want to you know build a Probab you know model predicting the probability that people have disease so you know this is the type of scientific research that we would like to be allowed to continue and in differential privacy you act ask a very particular counterfactual question we basically compare two alternatives one is when I do this I build this model on the database of medical records including your medical record and the other one is where I do the same exercise with the same database with just your medical record removed so basically you know it's two databases one with n records in it and one with n minus one records in it the N minus one records are the same and the only one that's missing in the second case is your medical record so differential privacy basically says that any harms that might come to you from the analysis in which your data was included are essentially nearly identical to the harms that would have come to you if the same analysis had done been done without your medical record included so in other words this doesn't say that bad things cannot happen to you as a result of data analysis it just says that these bad things were going to happen to you already even if your data wasn't included and to give a very concrete example right you know um you know like we discussed at some length the the study that you know the in the 50s that was done that created the that established the link between smoking and lung cancer and we make the point that like well if your data was used in that analysis and you know the world kind of knew that you were a smoker because you know there was no stigma associated with smoking before that those findings real harm might have come to you as a result of that study that your data was included in in particular your insurer now might have a higher posterior belief that you might have lung cancer and raise your premiums so you've suffered economic damage but the point is is that if the same analysis been done without with all the other n minus-1 medical records and just yours missing the outcome would have been the same your your data was an idiosyncratic eleum crucial to establishing the link between smoking and lung cancer because the link between smoking and lung cancer is like a fact about the world that can be discovered with any sufficiently large database of medical records but that's a very low value of harm yeah so that's showing that very little harm is done great but how what is the mechanism of differential privacy so that's the kind of beautiful statement of it well what's the mechanism by which privacy's preserve yeah so it's it's basically by adding noise to computations right so the basic idea is that every differentially private algorithm first of all or every good differentially private album every useful one is a probabilistic algorithm so it doesn't on a given input if you gave the algorithm the same input multiple times it would give different outputs each time from some distribution and the way you achieve differential privacy algorithmically is by kind of carefully and tastefully adding noise to a computation in the right places and you know to give a very concrete example if I want to compute the average of a set of numbers right the non private way of doing that is to take those numbers and average them and release like a numerically precise value for the average okay in differential privacy you wouldn't do that you would first compute that average to numerical Precision's and then you'd add some noise to it right you'd add some kind of zero mean you know gaussian or exponential noise to it so that the actual value you output is not the exact mean but it'll be close to the mean but it'll be close the noise the you add will sort of prove that nobody can kind of reverse engineer any particular value that went into the average so noise noise is the Savior how many algorithms can be aided by making by adding noise yeah so I'm a relatively recent member of the differential privacy community my co-author Aaron Roth is you know really one of the founders of the field and has done a great deal of work and I've learned a tremendous amount working with him on it growing up field already yeah but it's now it's pretty mature but I must admit the first time I saw the definition of deferential privacy my reaction was like well that is a clever definition and it's really making very strong promises and my you know you know at first saw the definition in much earlier days and my first reaction was like well my worry about this definition would be that it's a great definition of privacy but that it'll be so restrictive that we won't really be able to use it like you know we won't be able to do compute many things in a differentially private way so that that's one of the great successes of the field I think isn't showing that the opposite is true and that you know most things that we know how to compute absent any privacy considerations can be computed in a differentially private way so for example pretty much all of statistics and machine learning can be done differentially privately so pick your favorites machine learning algorithm back propagation and neural networks you know cart for decision trees support vector machines boosting you name it as well as classic hypothesis testing and the like and statistics none of those algorithms are differentially private in their original form all of them have modifications that add noise to the computation in different places in different ways that achieve differential privacy so this really means that to the extent that you know we've become a you know a scientific community very dependent on the use of machine learning and statistical modeling and data analysis we really do have a path to kind of provide privacy guarantees to those methods and and sort of we can still you know enjoy the benefits of kind of the data science era while providing you know rather robust privacy guarantees to individuals so perhaps a a slightly crazy question but if we take that the ideas of differential privacy and take it to the nature of truth that's being explored currently so what's your most favorite and least favorite food hmm I'm not a real foodie so I'm a big fan of spaghetti I forget it yeah on what what do you really don't like umm I really don't like cauliflower well I love golf okay but is one way to protect your preference for spaghetti by having in formation campaign bloggers and so on a boat's saying that you like cauliflower so like this kind of the same kind of noise ideas I mean if you think of in our politics today there's this idea of Russia hacking our elections what's meant there I believe is BOTS spreading different kinds of information is that a kind of privacy or is that too much of a stretch no it's not a stretch I have not seen those idea you know that is not a technique that to my knowledge will provide differential privacy but but to give an example like one very specific example about what you're discussing is there was a very interesting project at NYU I think led by a Helen missin bomb there in which they basically built a browser plugin that tried to essentially obfuscate your Google searches so to the extent that you're worried that Google is using your searches to build you know predictive models about you to decide what ads to show you which they might very reasonably want to do but if you object to that they built this widget you could plug in and basically whenever you put in a query into Google it would send that query to Google but in the background all the time from your browser it would just be sending this torrent of irrelevant queries to the search engine so you know it's like a weed and chaff thing so you know out of every thousand queries let's say that Google was receiving from your browser one of them was one that you put in but the other 999 were not okay so it's the same kind of idea kind of you know privacy by obfuscation so I think that's an interesting idea doesn't give you differential privacy it's also I was actually talking to somebody at one of the large tech companies recently about the fact that you know just this kind of thing that there are some times when the response to my data needs to be very specific to my data right like I type mountain biking into Google I want results on mountain biking and I really want Google to know that I typed in biking I don't want noise adage to that and so I think there's sort of maybe even interesting technical questions around notions of privacy that are appropriate where you know it's not that my date is part of some aggregate like medical records and that we're trying to discover important correlations and facts about the world at large but rather you know there's a service that I really want to you know pay attention to my specific data yet I still want some kind of privacy guarantee and I think these kind of obfuscation ideas are sort of one way of getting at that but maybe there are others as well so where do you think will land in this algorithm driven society in terms of privacy so sort of China like Chi Fuli describes you know it's collecting a lot of data on its citizens but in the best form it's actually able to provide a lot of sort of protects human rights and provide a lot of amazing services and its worst forms it can violate those human rights and and limit services so what do you think will land on so algorithms are powerful when they use data so as a society do you think we'll give over more data is it possible to protect the privacy of that data so I'm optimistic about the possibility of you know balancing the desire for individual privacy and individual control of privacy with kind of societally and commercially beneficial uses of data not unrelated to differential privacy or suggestions that say like well individuals should have control of their data they should be able to limit the uses of that data they should even you know there's there's you know fledgling discussions going on in research circles about allowing people selective use of their data and being compensated for it and then you get to sort of very interesting economic questions like pricing right and one interesting idea is that maybe differential privacy would also you know be Bo a conceptual framework in which you could talk about the relative value of different people's data like you know to demystify this a little bit if I front of build a predictive model for some rare disease and I'm trying to you I'm gonna use machine learning to do it it's easy to get negative examples because the disease is rare right but I really want to have lots of people with the disease in my data set okay but but and so somehow those people's data with respect to this application is much more valuable to me than just like the background population and so maybe they should be compensated more for it and so you know I think these are kind of very very fledgling conceptual questions that maybe will have kind of technical thought on them sometime in the coming years but but I do think well you know to kind of get more directly answer your question I think I'm optimistic at this point from what I've seen that we will land at some you know better compromise than we're at right now where again you know privacy guarantees are a few far between and weak and users have very very little control and I'm optimistic that we'll land in something that you know provides better privacy overall and more individual control of data and privacy but you know I think to get there it's again just like fairness it's not going to be enough to propose algorithmic solutions there's gonna have to be a whole kind of regulatory legal process that prods companies and other parties to kind of adopt solutions and I think you've mentioned the word control and I think giving people control that's something that people don't quite have and a lot of these algorithms that's a really interesting idea of giving them control some of that is actually literally an interface design question sort of just enabling because I think it's good for everybody to give users control it's not it's not a it's almost not a trade off except you have to hire people that are good at interface design yeah I mean the other thing that has to be said right is that you know it's a cliche but you know we who is the users of many systems platforms and apps you know we are the product we are not the customer the customer our advertisers and our data is the prod okay so it's one thing to kind of suggest more individual control of data and privacy and uses but this you know if this happens in sufficient degree it will upend the entire economic model that has supported the internet to date and so some other economic model will have to be you know will have to replace it so the idea of markets you mentioned by exposing the economic model to the people they will then become a market they can be participants in participants in and and you know this isn't you know this is not a weird idea right because there are markets for data already it's just that consumers are not participants in there's like you know there's sort of you know publishers and content providers on one side that have inventory and then they're advertised on the others and you know you know Google and Facebook are running you know they're pretty much their entire revenue stream is by running two-sided markets between those parties right and so it's not a crazy idea that there would be like a three sided market or that you know that on one side of the market or the other we would have proxies representing our interest it's not you know it's not a crazy idea but it would it it's not a crazy technical idea but it would have pretty extreme economic consequences speaking of markets a lot of fascinating aspects of this world arise not from individual humans but from the interaction of human beings you've done a lot of work in game theory first can you say what is game theory and how does help us model and study yeah game theory of course let us give credit where it's due they don't comes from the economist first and foremost but as I've mentioned before like you know computer scientists never hesitate to wander into other people's turf and so there is now this 20 year old field called algorithmic game theory but you know game game theory first and foremost is a mathematical framework for reasoning about collective outcomes in systems of interacting individuals you know so you need at least two people to get started in game theory and many people are probably familiar with prisoner's dilemma as kind of a classic example of game theory and a classic example where everybody looking out for their own individual interests leads to a collective outcome that's kind of worse for everybody then what might be possible if they cooperated for example but cooperation is not an equilibrium in prisoner's dilemma and so my work and the field of algorithmic game theory more generally in these areas kind of looks at settings in which the number of actors is potentially extraordinarily large and their incentives might be quite complicated and kind of hard to model directly but you still want kind of algorithmic ways of kind of predicting what will happen or influencing what will happen in the design of platforms so what to you is the most beautiful idea that you've encountered in game theory there's a lot of them I'm a big fan of the field I mean you know I mean technical answers to that of course would include Nash's work just establishing that you know there there's a competitive equilibrium under very very general circumstances which in many ways kind of put the field on a firm conceptual footing because if you don't have equilibria it's kind of hard to ever reason about what might happen since you know there's just no stability so just the idea that stability can emerge when there's multiple or that it means not that it will necessarily emerge just that it's possible right it's like the existence of equilibrium doesn't mean that sort of natural iterative behavior will necessarily lead to it in the real world yeah maybe answering a slightly less personally than you asked the question I think within the field of algorithmic game theory perhaps the single most important kind of technical contribution that's been made is the real the the realization between close connections between machine learning and game theory and in particular between game theory and the branch of machine learning that's known as no regret learning and and this sort of provides a fray a very general framework in which a bunch of players interacting in a game or a system each one kind of doing something that's in their self-interest will actually kind of reach an equilibrium and actually reach an equilibrium in a you know a pretty you know a rather you know short amount of steps so you kind of mentioned acting greedily can somehow end up pretty good for everybody or pretty bad or pretty bad it will end up stable yeah right and and you know stability or equilibrium by itself is neither is not necessarily either a good thing or a bad thing so what's the connection between machine learning and the ideas well if we kind of talked about these ideas already in in kind of a non-technical way which is maybe the more interesting way of understanding them first which is you know we have many systems platforms and apps these days that work really hard to use our data and the data of everybody else on the platform to selfishly optimize on behalf of each user okay so you know let me let me give what the the cleanest example which is just driving apps navigation apps like you know Google Maps and ways where you know miraculously compared to when I was growing up at least you know the objective would be the same when you wanted to drive from point A to point B spend the least time driving not necessarily minimize the distance but minimize the time right and when I was growing up like the only resources you had to do that were like maps in the car which literally just told you what roads were available and then you might have like half hourly traffic reports just about the major freeways but not about side roads so you were pretty much on your own and now we've these apps you pull it out and you say I want to go from point A to point B and in response kind of to what everybody else is doing if you like what all the other players in this game are doing right now here's the the you know the the route that minimizes your driving time so it is really kind of computing a selfish best response for each of us in response to what all of the rest of us are doing at any given moment and so you know I think it's quite fair to think of these apps as driving or nudging us all towards the competitive or Nash equilibrium of that game now you might ask like well that sounds great why is that a bad thing well you know it's it's known both in theory and with some limited studies from actual like traffic data that all of us being in this competitive equilibrium might cause our collective driving time to be higher may be significantly higher than it would be under other solutions and then you have to talk about what those other solutions might be and what what the algorithms to implement them are which we do discuss in the kind of game theory chapter of the book but but similarly you know on social media platforms or on Amazon you know all these algorithms that are essentially trying to optimize our behalf they're driving us in a colloquial sense towards some kind of competitive equilibrium and you know one of the most important lessons of game theory is that just because we're at equilibrium doesn't mean that there's not a solution in which some or maybe even all of us might be better off and then the connection to machine learning of course is that in all these platforms I've mentioned the optimization that they're doing on our behalf is driven by machine learning you know like predicting where the traffic will be predicting what products I'm gonna like predicting what would make me happy in my newsfeed now in terms of the stability and the promise of that I have to ask just out of curiosity how stable are these mechanisms that you game theories just The Economist's came up with and we all know that economists don't live in the real world just kidding sort of what's do think when we look at the fact that we haven't blown ourselves up from the from a game theoretic concept of mutually assured destruction what are the odds that we destroy ourselves with nuclear weapons as one example of a stable game theoretic system just to prime your viewers a little bit I mean I think you're referring to the fact that game theory was taken quite seriously back in the 60s as a tool for reasoning about kind of Soviet US nuclear armament disarmed ative date on things like that I'll be honest as huge of a fan as I am of game theory and it's kind of rich history it still surprises me that you know you had people at the RAND Corporation back in those days kind of drawing up you know two by two tables and one the row player is weekend oh the US and the column player is Russia and that they were taking seriously you know you know I'm sure if I was there maybe it wouldn't have seemed as as naive as it does at the time you know seems to have worked which is why it seems naive well we're still here we're still here in that sense yeah even though I kind of laugh at those efforts they were more sensible than than they would be now right because there were sort of only two nuclear powers at the time and you didn't have to worry about deterring new entrants and who was developing the capacity and so we have many we have this it's definitely a game with more players now and more potential entrants I'm not in general somebody who advocates using kind of simple mathematical models when the stakes are as high as things like that and the complexities are very political and social but but we are still here so you've worn many hats one of which the one that first caused me to become a big fan of your work many years ago is algorithmic trading so I have to just ask a question about this because you have so much fascinating work there in the 21st century would what role do you think algorithms have in space of trading investment in the financial sector yeah it's a good question I mean in the time I've spent on Wall Street and in finance you know I've seen a clear progression and I think it's a progression that kind of models the use of algorithms and automation more generally in society which is you know the things that kind of get taken over by the algos first are sort of the things that computers are obviously better at than people right so you know so first of all there needed to be this era of automation right we're just you know financial exchanges became largely electronic which then enabled the possibility of you know trading becoming more algorithmic because once you know the exchanges are electronic an algorithm can submit an order through an API just as well as a human can do at a monitor quickly it can read all the data so yeah and so you know I think the the places where algorithmic trading have had the greatest inroads and had the first inroads were in in kind of execution problems kind of optimized execution problems so what I mean by that is at a large brokerage firm for example one of the lines of business might be on behalf of large institutional clients taking you know what we might consider difficult trade so it's not like a mom-and-pop investor saying I want to buy a hundred shares of Microsoft it's a large hedge fund saying you know I want to buy a very very large stake in Apple and I want to do it over the span of a day and it's such a large volume that if you're not clever about how you break that trade up not just over time but over perhaps multiple different electronic exchanges that all let you trade Apple on their platform you know you will you will move you'll push prices around in a way that hurts your your execution so you know this is the kind of you know this is an optimization problem this is a control problem right and so machines are a better we know how to design algorithms you know that are better at that kind of thing then a person is going to be able to do because we can take volumes of historical and real-time data to kind of optimize the schedule with which we trade and you know similarly high frequency trading you know which is closely related but not this optimized execution where you're just trying to spot very very temporary you know miss pricings between exchanges or within an asset itself or just predict directional movement of a stock because of the kind of very very low-level granular buying and selling data in in the exchange machines are good at this kind of stuff it's kind of like the mechanics of trading what about the can machines do long terms of prediction yeah so I think we are in an era where you know clearly there have been some very successful you know quant hedge funds that are you know in what we would traditionally call you know still in this the stat ARB regime like so you know stat are referring to statistical arbitrage but but for the purposes of this conversation what it really means is making directional predictions in asset price movement or returns your prediction about that directional movement is good for you know you you have a view that it's valid for some period of time between a few seconds and a few days and that's the amount of time that you're gonna kind of get into the position hold it and then hopefully be right about the directional movement and you know buy low and sell high as the cliche goes so that is a you know kind of a sweet spot I think for quant trading and investing right now and has been for some time when you really get to kind of more warren buffett style timescales right like you know my cartoon of warren buffett is that you know warren buffett sits and thinks what the long-term value of Apple really should be and he doesn't even look at what Apple's doing today he just decides you know yeah you know I think that this was what its long-term value is and it's far from that right now and so I'm gonna buy some Apple or you know shorts and Apple and I'm gonna I'm gonna sit on that for 10 or 20 years okay so when you're at that kind of time scale or even more than just a few days all kinds of other sources of risk and information you know so now are talking about holding things through recessions and economic cycles wars can break out so there you have to install a human nature at 11:00 yeah and you need to just be able to ingest many many more sources of data that are on wildly different timescales right so if I'm an hft I'm a high-frequency trader like I don't I don't I really my main source of data is just the data from the exchanges themselves about the activity in the exchanges right and maybe I need to pay you know I need to keep an eye on the news right because you know that can sudden cause sudden you know the the you know CEO gets caught in a scandal or you know gets run over by a bus or something that can cause very sudden changes in but you know I don't need to understand economic cycles I don't need to understand recessions I don't need to worry about the political situation or war breaking out in this part of the world because you know all you need to know is as long as that's not gonna happen in the left next 500 milliseconds then you know my models good when you get to these longer timescales you really have to worry about that kind of stuff and people in the machine learning community are starting to think about this we held a we did we jointly sponsored a workshop at 10:00 with the Federal Reserve Bank of Philadelphia a little more than a year ago on you know I think the title is something like machine learning for macroeconomic prediction you know macroeconomic referring specifically to these longer timescales and you know it was an interesting conference but it you know my it left me with greater confidence that we have a long way to go to you know and so I think that people that you know in the grand scheme of things you know if somebody asked me like well whose job on Wall Street is safe from the bots I think people that are at that longer you know the time scale and have that appetite for all the risks involved in long term investing and that really need kind of not just algorithms that can optimize from data but they need views on stuff they need views on the political landscape economic cycles and the like and I think you know they're they're they're pretty safe for a while as far as I can tell so Warren Buffett yeah I'm not seeing you know a robo Warren Buffett anytime so she'd give him comfort last question if you could go back to if there's a day in your life you could relive because I made you truly happy maybe you outside family boy otherwise do you know what what day would it be what can you look back you remember just being profoundly transformed in some way or blissful I'll answer a slightly different question which is like what's a day in my life or my career that was kind of a watershed moment I went straight from undergrad to doctoral studies and you know that's not at all a typical and I'm also from an academic family like my dad was a professor or my uncle on his side as a professor both my grandfather's were professors all kinds of majors to philosophy yeah all over the map yeah and I was a grad student here just up the river at Harvard and came to study with less valiant which was a wonderful experience but you know I remember my first year of graduate school I was generally pretty unhappy and I was unhappy because you know at Berkeley as an undergraduate you know yeah I studied a lot of math and computer science but it was a huge school first of all and I took a lot of other courses as we've discussed I started as an English major and took history courses and art history classes and had friends you know that did all kinds of different things and you know Harvard's a much smaller institution than Berkeley and it's computer science department especially at that time was was a much smaller place than it is now and I suddenly just felt very you know like I'd gone from this very big world to this highly specialized world and now all of the classes I was taking were computer science classes and I was only in classes with math and computer science people and so I was you know I thought often in that first year of grad school about whether I really wanted to stick with it or not and you know I thought like oh I could you know stop with a masters I could go back to the Bay Area into California and you know this was from one of the early periods where there was you know like you could definitely get a relatively good job paying job at one of the one of the tech companies back you know that were the the big tech companies back then and so I distinctly remember like kind of a late spring day when I was kind of you know sitting in Boston Common and kind of really just kind of chewing over what I wanted to do with my life and I realized like okay you know and I think this is where my academic background helped me a great deal I sort of realized you know yeah you're not having a great time right now this feels really narrowing but you know that you're here for research eventually and to do something original and to try to you know carve out a career where you kind of you know choose what you want to think about you know and have a great deal of Independence and so you know at that point I really didn't have any real research experience yet I mean it was trying to think about some problems with very little success but but I knew that like I I hadn't really tried to do the thing that I knew I'd come to do and so I thought you know I'm gonna I'm gonna stick I'm gonna you know stick through it for the summer and you know and and and that was very formative because I went from kind of contemplating quitting to you know a year later it being very clear to me I was going to finish because I still had a ways to go but I kind of started doing research it was going well it was really interesting and it was sort of a complete transformation you know it's just that transition that I think every doctoral student makes at some point which is to sort of go from being like a student of what's been done before to doing you know your own thing and figure out what makes you interested in what your strengths and weaknesses are as a researcher and once you know I kind of made that decision on that particular day at that particular moment in Boston Common you know the I'm glad I made that decision and also just accepting the painful nature of that journey yeah exactly exactly and in that moment said I'm gonna I'm gonna stick it out yeah I'm gonna stick around for a while well Michael looked up do you work for a long time it's really talk to you separation get back in touch with you - and see how great you're doing as well thank thanks a lot appreciate you |
Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot | Lex Fridman Podcast #49 | the following is a conversation with Elon Musk part two the second time we spoke in the podcast with parallels if not in quality then an outfit to the objectively speaking great a sequel of all-time Godfather Part two as many people know Elon Musk is a leader of Tesla SpaceX your link and the boring company well maybe less known is that he's a world-class engineer and designer constantly emphasizing first principles thinking in taking on big engineering problems that many before him will consider impossible as scientists and engineers most of us don't question the way things are done we simply follow the momentum of the crowd of revolutionary ideas that change the world on the small and large scales happen when you return to the fundamentals and ask is there a better way this conversation focuses on the incredible engineering and innovation done in brain computer interfaces and neural link this work promises to help treat neurobiological diseases to help us further understand the connection between the individual neuron to the high-level function of the human brain and finally to one day expand the capacity of the brain through two-way communication with computational devices the internet and artificial intelligence systems this is the artificial intelligence podcast if you enjoy it subscribe on YouTube apple podcasts Spotify supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma M and now as an anonymous youtube commenter refer to our previous conversation as the quote historical first video of two robots conversing without supervision here's the second time the second conversation with Elon Musk let's start with an easy question about consciousness in your view is consciousness something that's unique to humans there's is something that permeates all matter almost like a fundamental force of physics I don't think consciousness permeates all matter pants I just believe that yeah there's a philosophical how would you tell that's true that's a good point I believe in scientific message don't blow your mind anything but the scientific method it's like you can't test the hypothesis then you cannot reach meaningful conclusion that it is true do you think consciousness understanding consciousness is within the reach of science of the scientific method we can dramatically improve our understanding of consciousness you know hard pressed to say that we understand anything with complete accuracy but can we dramatically improve ours that any consciousness I believe the answer is yes this Nai system in your view I have to have consciousness in order to achieve human-level or superhuman level intelligence does it need to have some of these human qualities that consciousness may be a body may be a fear of mortality capacity love those kinds of silly human things it's different you know there's this the scientific method which I very much believe in where something is true to the degree that it is test ibly so and and otherwise you're really just talking about you know preferences or full-on untestable beliefs or that you know that kind of thing so ends up being somewhat of a semantic question where we were conflating a lot of things with the word intelligence if we parse them out and say you know all we headed towards the future where an AI will be able to out think us in every way then the answer is unequivocally yes in order for an AI system that needs to out think us in every way it also needs to have a capacity to have consciousness self-awareness and Anjali will be self-aware yes that's different from consciousness I need to be in terms words that what consciousness feels like it feels like consciousness is in a different dimension but this is this could be just an illusion you know if you damnit damage your brain in some way physically you get you you damage your consciousness which implies that consciousness is a physical phenomenon and in my view the thing is that that I think are really quite quite likely is that digital intelligence will be able to out think us in every way and it will soon be able to simulate what we consider consciousness so to agree that you would not be able to tell the difference and from the from the aspect of the scientific method it's it might as well be consciousness if we can simulate it perfectly if you can't tell the difference and this is sort of the Turing test but think of a more sort of advanced version of the Turing test if you if you're if you're talking to a digital super intelligence and can't tell if that is a computer or a human like let's say just having conversation of a phone or a video conference or something where you're you you think you're talking look looks like person makes all of the right inflections and movements and and all the small subtleties that constitute a human and talks like human makes mistakes like you're hearing like look at that and you literally just can't tell is this are you really conversing with a person or or an AI might as well wear as well be human so on a darker topic you've expressed serious concern about existential threats of AI it's perhaps one of the greatest challenges our civilization faces but since I would say we're kind of an optimistic descendants of apes perhaps we can find several paths of escaping the harm of AI so if I can give you three options maybe can comment which do you think is the most promising so one is scaling up efforts on AI safety and beneficial I research and in hope of finding an algorithmic or maybe a policy solution to is becoming a multiplanetary species as quickly as possible and three is merging with AI and and riding the wave of that increasing intelligence as it continuously improves what do you think is most promising most interesting as a civilization that we should invest in I think that's this a lot that responder investment going on nai whereas a lack of investment is in AI safety and there should be in my view a cup an agency that oversees anything related to AI to confirm that it is does not represent a public safety risk just as there is a regulatory authority for this like the Food and Drug Administration is that's the four corner automotive safety there's the FA for aircraft safety which generally comes a conclusion that it is important to have a government referee or a referee that is serving the public interest in ensuring that things are safe when when there's a potential danger to the public I would argue that AI is unequivocally something that has potential to be dangerous to the public and therefore should have a regulatory agency just as other things that are dangerous to the public have a regulatory agency but let me tell you problems with this is that the government was very slowly and the rate of the usually way a regulatory agency comes into being is that something terrible happens there's a huge public outcry and years after that there's a regulatory agency or rule put in place takes something like like seatbelts it was known for on a decade or more that seatbelts would have a massive impact on safety and and save so many lives in serious injuries and the car industry fought the requirements put seatbelts in tooth and nail that's crazy yeah and and honor hundreds of thousands of people probably died because of that and they said people wouldn't buy cars if their seatbelts just obviously absurd you know or look at the back tobacco industry and how long they fought any thing about smoking that's part of why I helped make that movie thank you for smoking you can sort of see just how pernicious it can be when you have these companies that effectively achieve regulatory capture of government the bad people in the AG community refer to the advent of digital superintelligence as a singularity that that is not to say that it is good or bad but it that it is very difficult to predict what will happen after that point and and that there's some probability it will be bad some probably will be it will be good or if they want you to affect that probability and have it be more good than bad well let me on the merger with AI question and the incredible work that's being done in your link there's a lot of fascinating innovation here across different disciplines going on so the flexible wires the robotic sewing machine that responds to brain movement everything around ensuring safety and so on so we currently understand very little about the human brain do you also hope that the work at neural link will help us understand more about our about the human mind about the brain yeah the work in your like will definitely shut a lot of insight into how the brain the mind works right now just the data we have regarding the how the brain works is very limited we've collect fMRI which is that that's kind of like putting us you know a stethoscope on the outside of a factory wall and then putting it like all over the factory wall and you can sort of hear the sounds but you don't know what machines are doing really yeah it's hard you can infer a few things but it's very poor brushstroke in order to really know what's going on in the brain you really need you have to have high precision sensors and then you want to have stimulus and response like if you trigger a new one what how do you feel what do you see how does it change your perception of the world you're speaking to physically just getting close to the brain being able to measure signals on the brain yeah will give us sort of open the door and inside the factory yes being able to have high precision sensors that tell you what individual neurons are doing and then being able to trigger a neuron and see what the responses in the brain so you can see the consequences of if you fire this neuron what happens how do you feel what is change it'll be really profound to have this in people because people can articulate their change like if there's a change in mood or if they've you know if they can tell you if they can see better or hear better or be able to form sentences better or worse or you know their memories are jogged or that kinda kind of thing so on the human side there's this incredible general malleability plasticity of the human brain the human brain adapts adjusts and so on so it's not that plastic to be totally Frank so there's a firm structure but there nevertheless there's some plasticity and the open question is so if I could ask a broad question is how much that plasticity can be utilized sort of on the human side there's some plasticity in human brain and on the machine side we have neural networks machine learning artificial intelligence it's able to adjust and figure out signals so there's a mysterious language that we don't perfectly understand that's within the human brain and then we're trying to understand that language to communicate both directions so the brain is adjusting a little bit we don't know how much and the machine is adjusting where do you see as they try to sort of reach together almost like with an alien species try to find a protocol communication protocol that works where do you see the biggest the the biggest benefit arriving from on the machine side or the human side do you see both of them working together I think the machine side is far more malleable and the biological side well huge around so it'll be the machine that adapts to the brain that's the only thing that's possible the brain can adapt that well to to the machine you can't have neurons start to regard an electrode as a nook another neuron because you're not just dislike the pulse and so something else is pulsing see so this there is that there is that that elasticity in the inner which we believe is something that can happen but the vast majority of malleability will have to be on the machine side but it's interesting when you look at that synaptic plasticity at the interface ID there might be like an emergent plasticity because it's a whole nother it's not like in the brain it's a whole nother extension of the brain you know we might have to redefine what it means to be malleable for the brain so maybe the brain is able to adjust to external interfaces there will be some adjustment to the brain because there's gonna be something reading and simulating the the brain and so it will adjust to to that thing but but well if the vast majority the adjustment will be on the machine side this is just if this is just it has to be that otherwise it will not work ultimately like we don't currently operate on two layers we have sort of lamech you like prime primitive brain layer which is where all of our kind of impulses or coming from it's sort of like we've got we've got like a monkey brain with a computer stuck on it that's that's the human brain and a lot of our impulses and everything are driven by the monkey brain and the computer of the cortex is constantly trying to make the Montek monkey brain happy it's not the cortex that's steering the monkey right it's the monkey brain steering the cortex you know so the cortex is the part that tells the story of the whole thing so we convince ourselves it's more interesting than just the monkey brain the cortex just like what we'll call like human intelligence you know it's like that's like the advanced computer relative to other creatures like other creatures do not have either we're really they don't they don't have the computer or they have a very weak computer relative to humans but but it's just it's like it sort of seems like surely the really smart thing should control the dumb thing but actually don't think it rolls this one thing so do you think some of the same kind of machine learning methods whether that's natural language processing applications are going to be applied for the communication between the Machine and the brain in to learn how to do certain things like movement of the body how to process visual stimuli and so on do you see the value of using machine learning to understand the language of the two-way communication with the brain yeah absolutely maybe we're a neural net and that you know AI is basically known that so it's like digital neural net will interface with biological neural net and hopefully bring us along for the ride yeah but the vast majority of aren't of our intelligence will be digital there's no like so like things like the the difference in intelligence between your the cortex and limbic system is gigantic your living system really has no comprehension of what the hell the cortex is doing it's just literally hungry you know or tired or angry or sexy or something you know it's an ad just and then it that communicates that's that impulse to the cortex and Tails the cortex to go satisfy that then a great deal of like a massive amount of thinking like truly this stupendous amount of thinking has gone into sex without purpose without provocation without procreation which which is actually quite a silly action in the absence of procreation it's a bit silly the one why you doing it that's because it makes the limbic system happy that's why that's why but it's pretty absurd really well the whole of existence is pretty absurd in some kind of sense yeah but I mean this does a lot of computation has gone into how can I do more of that with the co-creation not even being a factor this is I think a very important area of research for NSFW an agency that should receive a lot of funding especially after this decision if I propose the formation of a new agency oh boy what is the most exciting or some of the most exciting things that you see in the future impact of neural link both on the size engineering a societal broad impact so in your link I think that first will solve a lot of brain related diseases so creating from like autism schizophrenia memory loss like everyone experiences memory loss that at certain point in in age parents can't remember their kids names and that kind of thing so there's like mount of good that neural link can do in solving a critical critical damage to brain or the spinal cord there's a lot that can be done to improve quality of life of individuals and that will be those three steps along the way and then ultimately it's intended to address the the risk of the existential risks associated with digital super intelligence like we will not feel to be smarter than a digital supercomputer so therefore if you cannot beat them join them and released we won't have that option so you have hope that your link will be able to be a kind of connection to allow us to to merge to ride the wave of the improving AI systems I think the chances above zero percent it's nonzero yeah there's a chance and that's so what I've seen dumb and dumber yes so I'm saying there's a chance he's saying one in a billion or one in a million whatever it was the dumb and dumber you know it went from maybe one a million to improving maybe it'll be one in a thousand and then 100 then one in ten depends on the rate of improvement of neural link and how fast we're able to do make progress you know well I've talked to a few folks here quite brilliant engineers some I'm excited yeah I think it's like fundamentally good you know who you know giving somebody back full motor control after they've had a spinal cord injury you know restoring brain functionality after a stroke solving debilitating genetically orange brain diseases these are all incredibly great I think and in order to do these you have to be able to interface with the neurons at detail level and each build fire they're not write neurons read the write neurons and and then effectively you can create a circuit replace what's broken with with silicon and actually fill in them the missing functionality and then over time we can have with develop a tertiary layer so if like limbic system is a primary layer then the cortex is like a sector the second layer now and I said that you know the cortex is vastly more intelligent than the limbic system but people generally like the fact that they have a living system and a cortex I've met anyone who wants to lead either one of them there like a girl keeping both that's cool the limbic system is kind of fun tell us what the fun is absolutely and then you people generally don't lose the cortex either all right they're like having the cortex and the limbic system yeah and and then there's a tertiary layer which will be digital super intelligence and I think there's room for optimism given that the cortex the cortex is very intelligent and limbic system is not and yet they work together well perhaps they can be a tertiary layer where digital super intelligence lies and that that will be vastly more intelligent than the cortex but still coexist peacefully and in the end of an EIN manner with the cortex and limbic system that's a super exciting future both on the low-low of engineering that I saw is being done here and actual possibility in the next few decades it's important that Norling solved this problem sooner rather than later because the point at which we have digital super intelligence that's when we pass the singularity and and things become just very uncertain it doesn't mean that they're necessarily bad or good for the point which we passed singularity things become extremely unstable so we want to have a human brain interface before the singularity or at least not long after it to minimize existential risk for Humanity and consciousness as we know it but there's a lot of fascinating actual engineering a low-level problems here at your link that yeah quite quite exciting what the problems that we face in your like art material science Electrical Engineering software mechanical engineering micro fabrication it's a bunch of engineering disciplines essentially that's where it comes down to you have to have a a tiny electrode so so small it doesn't hurt hurt neurons but it's got to last for as long as a person so it's gonna last for decades and then you've got to take that signal you've got to process that single looks signal locally at low power so we need a lot of chip design engineers that you know cuz we're gonna do signal processing and do so in a very power efficient way so that we don't heat your brain up because the brain is very heat sensitive and then and then we're going to take those signals I'm going to do something with them and then we better stimulate interest of stimulate the back too you know so you could buy directional communication so he's good at material science software mechanical engineering Electrical Engineering trip design micro fabrication that's what those are the things we need to work on we need to a good material science so that the we can have tiny electrodes that last a long time and as the tough thing with the science problems a tough one because you're trying to read and simulate electrically in a an electrically active area your brain is very electrically active in electro chemically active so how do you have a coating on the electrode that doesn't dissolve over time and and is safe in the brain this is a very hard problem and then and then how do you collect those signals in a way that is most efficient because you really just have very tiny amounts of power to process those signals you know and then we need to automate the whole thing so it's like LASIK you know so it's just it's it's not if this is done by neurosurgeons there's no way it can scale to large numbers of people and it needs to scales large numbers of people because I think ultimately we want the future repeated to be determined by a large number of the of humans do you think that this has a chance to revolutionize surgery period so neurosurgery and Ellis yeah for sure it's gotta be like lazy like you met if LASIK had to be hand done not done by hand by a person that wouldn't be great you know it's done by a robot and they'll off the mall it just kind of just needs to make sure yo-you heads in my position and then they just press button and go it's a smart summon and soon Auto Park takes on the full beautiful mess of parking lots and their human human nonverbal communication I think it has actually the potential to have a profound impact in changing how our civilization looks at AI in robotics because this is the first time human beings people that don't own and test them Eve never seen it doesn't hurt about a Tesla get to watch hundreds of thousands of cars without a driver yeah do you see it this way almost like an education tool for the world about AI do you feel the burden of that the excitement of that or do you just think it's a smart parking feature I do think you are getting at something important which is most people have never really seen a robot or at and what what is the card that is autonomous it's a four wheeled robot yeah the it communicates a certain sort of message with everything from safety to the possibility of what AI could bring his current limitations its current challenges its what's possible do you feel the burden of that almost like a communicator educator to the world about AI we were just really trying to make fuels lives easier with autonomy but now you mention it I think it will be an eye-opener to people about robotics because they have really never seen most people never seen a robot and are hundreds of thousands of Tesla's won't be long before there's a million of them that have autonomous capability and the drive without a person in it and you use you can see the kind of evolution of the cars personality and and thinking with each iteration of autopilot you can see it's it's uncertain about this or it gets it but now it's more certain now now it's moving in a slightly different way like I can tell immediately if a car is on tells autopilot because got just little nuances of movement it just moves in a slightly different way it will cause aunt Ella for example on the highway are far more precise about being in the center of the lane than a person if you drive down the highway and look at how at where cars are the human driven cars are in within their lane that like bumper cars then like moving all over the place the car and autopilot dead center yes of the incredible work that's going into that in your network it's learning fast autonomy is still very very hard we don't actually know how hard it is fully of course you look at the most problems you tackle this one included in with an exponential lens but even with an exponential improvement things can take longer than expected sometimes so where does Tesla currently stand on its quest for full autonomy what's your sense when can we see successful deployment of full autonomy well on the highway already the the probability of an intervention is extremely low yes so for highway autonomy with latest release especially the probability of need to intervene is this query is really quite low in fact I'd say for stop-and-go traffic did its Matt as far safer than a person right now it's not forget the probability of an injury or an impact is much much lower for a pilot in a person and it was navigating change lanes take highway interchanges and then we're coming at it from the other direction which is low speed full autonomy and in a way this is like it's like how does a person learn to drive you learn to drive in parking lot you know you know first time you learn to drive probably wasn't jumping on Wolcott Street in San Francisco that'd be crazy you're driving in the parking lot get things get things right at low speed and and then the missing piece that were working on is traffic lights and stuff streets dr. Esau streets obviously actually also relatively easy because you know you kind of know where the stuff Street is was casing geocoded and then use visualization to see where the line is and stop the line to illuminate the GPS are so it actually this is probably complex traffic lights and very windy roads are the two things that need to get sold what's harder perception of control for these problems so being able to perfectly perceive everything or figuring out a plan once you perceive everything how to interact with all the agents in the environment in your sense from a learning perspective is perception or action harder and then giant beautiful multitask learning neural network the hardest thing is having a kur representation of the physical objects in vector space so transportation the visual input primarily visual input some sonar and radar and and then at creating the an accurate vector space representation of the objects around you once you have an accurate vectors based representation the flanker and control is relatively easier it is relatively easy basically once you have accurate vector representation then then you're kind of like a video game like it cars in like Grand Theft Auto or something like they work pretty well they drive down the road they don't crash you know pretty much unless you crash into them that's because they've they've got an accurate vectors based representation of where the cars are and they're just bent and then they're rendering that as the as the output you have a sense high level that Tesla's on track on being able to achieve full autonomy so on the highway yeah yeah absolutely and still no driver state as a driver sensing and we have driver sensing with talk in the wheel that's right yeah by the way just a quick comment on karaoke most people think it's fun but I also think it's a driving feature I've been saying for a long time singing in a car is really good for attention management and vigilance management uh sorry Tesla karaoke again it's great it's the one of the most fun features of the car do you think of a connection between fun and safety sometimes yeah they're both the same time that's great I just met with and ruin wife of uh Carl Sagan oh yeah directed cut cosmos I'm generally a big fan of Paul Sagan he's super cool and they had a great way of bringing things all that consciousness all civilization everything we've ever known and done is on this tiny blue dot people also get they get too trapped in there this is like squabbles amongst humans and this don't think of a big picture they take civilization and not continuing existence for granted I shouldn't do that look at the history of civilizations their eyes and they fall and now civilization is all it's globalized and so we're civilization I think now rises and falls together there's no there's not geographic isolation this is a big risk things don't always go up that should be that's an important lesson of history in 1990 at the request of Carl Sagan the Voyager 1 spacecraft which is a spacecraft that's reaching out farther than anything human made into space turned around to take a picture of Earth from 3.7 billion the way and as you're talking about the pale blue dot that picture there takes up less than a single pixel in that image you know appearing as a tiny blue dot as pale blue dot as Carl Sagan called it so he spoke about this dot of ours in 1994 and if you could humor me I was wondering if in the last two minutes you could read the words that he wrote described in this buildup sure yes finally the universe appears to be 13.8 billion years old earth-like four-and-a-half billion years old you know another half billion years or so the Sun will expand and probably evaporate the oceans and make life impossible on earth which means that if it had taken consciousness temp sent longer to evolve it would never have balled it all its attempts and longer and I wonder I wonder how many dead one planet civilizations that are out there in the cosmos that never made it to the other planet and ultimately extinguish themselves or were destroyed by external factors probably a few it's only just possible to try to travel to Mars just barely if G was 10% more wouldn't work really if it empty was 10% lower it would be easy plucking go single stage from surface of module away surface of the earth there's Mars it's 37-cent with gravity they're about a giant blue stick you know forth channeling Costigan look again at that dot that's here that's home that's us on it everyone you love everyone you know everyone you've ever heard of every human being who ever was lived out their lives the aggregate of our joy and suffering thousands of confident religions ideologies and economic doctrines every hunter and forager every hero and coward every creator and destroyer of civilization every King and peasant every young couple in love every mother and father hopeful child inventor and Explorer every teacher of morals every corrupt politician every superstar every Supreme Leader every saint and sinner in the history of our species lived there on a mote of dust suspended in a sunbeam our planet is a lonely speck in the great enveloping cosmic dark in our obscurity in all this vastness there is no hint that help will come from elsewhere to save us from ourselves the earth is the only world known so far to harbor life there is nowhere else at least in the near future to which our species could migrate this is not true this is Fault Mars and I think Carl Sagan would agree with that he couldn't even imagine it at that time so thank you for making the world dream and thank you for talking today I really appreciate it thank you you |
Bjarne Stroustrup: C++ | Lex Fridman Podcast #48 | the following is a conversation with BR install stroke he's the creator of C++ programming language that after 40 years is still one of the most popular and powerful languages in the world it's focused on fast stable robust code underlies many of the biggest systems in the world that we have come to rely on as a society if you're watching this on YouTube for example many of the critical backend components of YouTube are written in C++ same goes for Google Facebook Amazon Twitter most Microsoft applications Adobe applications most database systems and most physical systems that operate in the real world like cars robots rockets that launches into space and one day when landis on Mars C++ also happens to be the language that I used more than any other in my life I've written several hundred thousand lines of C++ source code of course lines of source code don't mean much but they do give hints of my personal journey through the world of software I've enjoyed watching the development of C++ as a programming language leading up to the big update in a standard in 2011 and those that followed in 1417 and told me the new C++ 20 standard hopefully coming out next year this is the artificial intelligence podcast if you enjoy it subscribe I knew to give it five stars and iTunes supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. and now here's my conversation with Bjorn straw stroke what was the first program you've ever written do you remember it was my second year in university first year of computer science and it was an alcohol 60 I calculated the shape of super lips and then connected points on the on the perimeter creating star patterns it was with a with a wedding on paper printer and I was in college university yeah yeah I learned to program the second year in university and what was the first programming language if I may ask it this way that you fell in love with I I think I'll call 60 and after that I remember I remember snowboard I remember Fortran didn't fall in love with that I remember Pascal didn't fall in love with that it all gotten away of me and then I just covered a simpler and that was much more fun and from there I went to micro micro code so you were drawn to the you found the low level stuff beautiful I went through a lot of languages and then I spent significant time in in a simpler and micro code that was sort of the first really profitable things I paid for my Master's actually and then I discovered Simula which was absolutely great Simula simulation of Albert 60 done primarily for simulation but basically they invented up to Tory into programming at inheritance and runtime polymorphism when they were while they were doing it and that was a language that taught me that you could have the sort of the problems of a program grow with size of the program rather than with the square of the size of program that is you can actually module arise very nicely and that that that was a surprise to me it was also a surprise to me that a stricter type system than Pascal's was helpful whereas Pascal's type system got in my way all the time so you need a strong type system to organize your code well which has to be extensible and flexible let's get into the details a little bit what kind of if you remember what kind of type system to Pascal have what type system typing system did the Algol 60 have basically Pascal was sort of the simplest language that Niklaus yet could define that served the needs of Niklaus Viet at the time and it has a sort of our highly moral tone to it that is if you can say it in Pascal it's good and if you can't it's not so good whereas Simula large is basically to build your own type system so instead of trying to fit yourself into Niklaus pierce'sworld Christ knew God's language and Orion dance language allowed you to build your own so it's sort of close to the original idea of you you you build a domain-specific language as a matter of fact what you build is a set of types and relations among types that allows you to express something that suitable for an application the when you say types the stuff you're saying has echoes of object-oriented programming Kjetil they invented it every language that uses the word class for type is a descendant of Simula directly or indirectly Christ knew gone orientale were mathematicians and they didn't think in terms of type C but they understood sets and classes of elements and so they caught their types classes and basically in C++ as in similar classes are user defined type so can you try the impossible task and give a brief history of programming languages from your perspective so we started with Algol 60 Simula Pascal but that's just the 60s and seven I can try the most sort of interesting and major improvement of programming languages was Fortran the first Fortran because before that all code was written for a specific machine and each specific machine had a language a simply language or cross embro or some extension of that idea but it you are writing for a specific machine in the term in the language of that machine and parker's and his team at IBM built a language that would allow you to to write what you really wanted that is you can write it in a language that was natural for people now these people happen to be engineers and physicists so the language I came out was somewhat unusual for the rest of the world but basically they said formula translation because they wanted to have the mathematical formulas translated into the machine and as a side effect they got portability because now they are writing in the terms that the humans used and the way humans thought and then they had a program that translated it into the machines needs and that was new and that was great and it's something to remember we want to raise the language to the human level but we don't want to lose the efficiency so and the last first step towards the human that was the first step and of course they were very particular kind of humans business people MIT is different so they got COBOL instead and etc etc and simular came out no let's not go to simulate yet let's go to Al Gore Fortran didn't have at the time the notions of not a precise notion of type not a precise notion of scope not a set of translation phases that was what we have today lexical since heck semantics it was sort of a bit of a model in the early days but hey they're just done the biggest breakthrough and history of programming right so you can't criticize them for not having gotten all the technical details right so we got alcohol that was very pretty and most people in Commerce and science considered it useless because it was not flexible enough and it wasn't efficient enough and etc etc but that was the breakthrough from a technical point of view then similar came along to make that idea more flexible and you could define your own types and that's where where I got very interested first Nicole was the main idea and behind Simula I was late 60s this was late 60s was a visiting professor in Oz and so I learned object-oriented programming by sitting around well in theory discussing with with Christ Mughal but Kristin once you get started and then full flow it's very hard to get a word in edgeways where you're just listed so it was great I learned it from them not to romanticize the notion but it seems like a big leap to think about object-oriented programming it's really a leap of abstraction it's yes and was that as big and beautiful of a leap as it seems from now in retrospect I was in an obvious one at the time it was not obvious and many people have tried to do something like that and most people didn't come up with something as wonderful as similar lots of people got their PhDs and made their careers out of forgetting about Simula or never knowing it for me the key idea was basically I could get my own types and that's the idea that goes for a lines of C++ where I can get better types and more flexible types and more efficient types but it's still the fundamental idea when I want to write a program I want to write it with my types that is appropriate to my problem and under the constraints that I'm under with hardware software environment etc and that's that's the key idea people picked up on hierarchy is in the virtual functions and the inheritance and that was only part of it it was an interesting and major part and still a major part and a lot of graphic stuff but it was not the most fundamental it it was when you wanted to relate one type to another you don't want the more to be independent that the classical example is that you don't actually want to write city simulation with vehicles where you say well if it's a buy signal to write the code for turning a bicycle to the left if it's a normal car turn right a normal car way if it's a fire engine and right the fire engine way da da da da da you get these big case statements and bunches of if statement and such instead you tell the other the base class that that's the Viacom saying turn turn left the way you want to and this is actually a real example they they used it to simulate and optimize the emergency the emergency services for somewhere Norway back in the 60s Wow so this was one of the early examples for why you needed inheritance and and you needed runtime polymorphism because you wanted to handle this set of vehicles in a manageable way you you you can't just rewrite your code each time a new kind of vehicle comes along yeah that's a beautiful powerful idea and of course that it stretches through your work who C++ as we'll talk about but I think you structured it nicely what other breakthroughs came along in the history of programming languages they if we were to tell the history in that way obviously I'm bitter telling the part of the history that that is the path I'm on as opposed to all the path yeah you skipped the hippy John McCarthy and Lisp or my favorite languages but listen what Lisp is not one of my favorite language yes it's obviously important it's obviously interesting lots of people write code in it and then they rewrite it into C or C++ when they want to go to production yes it's in the world I met which are constrained by performance reliability issues deployability cost of hardware I I don't like things to be too dynamic it is really hard to write a piece of code that's perfectly flexible that you can also deploy on a small computer and that you can also put in say a telephone switch in Bogota what's the chance if you get an error and you find yourself in the debugger that the telephone switch in pockets are on late Sunday night has a programmer around right their chance is zero and so a lot of things I think most about can't afford that flexibility and I'm quite aware that maybe 70 80 percent of all code are not under the kind of constraints I'm interested in but somebody has to do the job I'm doing because you have to get from these high level flexible languages to the hardware the stuff that lasts for 10 20 30 years is robust yeah operates under very constrained conditions yes absolutely that's right and it's fascinating and beautiful in its own way it's C++ is one of my favorite languages and so is Lisp so I can I can embody two for different reasons as as a programmer I understand why it is popular and I can see the beauty of the ideas and similarly with this more talk it's just know this relative thank it it's not as relevant in my world and by the way I distinguish between those and the functional languages where I go to things like ml and Hesco different different kind of languages they have a different kind of huge in there very interesting and I actually try to learn from all the languages I encounter to see what is layer that would make working on the kind of problems I'm interested in with the kind of constraints that that I'm interested in what can actually be done better because we can surely do better than we do today you've you've said that it's good for any professional programmer to know at least five languages speaking about a variety of languages that you've taken inspiration from and you've listed the yours as being at least at the time C++ obviously Java Python Ruby and JavaScript can you first of all update that list modify it if you don't have to be constrained to just five but can you describe what you picked up also from each of these languages how you see them as inspirations for even you're working with C++ this is a very hard question to answer so about languages you should know languages I I reckon I knew about twenty-five or there abouts when I did C++ it was easier than those days because the languages were smaller and you didn't have to learn a whole programming environment and such to do it you you could learn the language quite easily and it's good to learn so many languages and I imagine just like with natural language for communication there's different paradigms that emerge in all of them yeah that there's commonalities and so on so I picked fire out of a head so far ahead obviously well the important thing that the number is not one that's right it's like I don't like I mean if you're mono clot you are likely to think that your own culture is the only ones peer is everybody else's a good learning of a foreign language and a foreign culture is important it helps you think and be a better person with programming languages you become a better programmer better designer with the second language now once you've got to the wage of five is not that long it's the second one that's most important and then when I had to pick five I sort of thinking what kinds of languages are there well there's a really low level stuff it's good it's actually good to know machine code movie very still sorry even today even today the C++ optimizer is right there a machine code than I do yes but I don't think I could appreciate them if I actually didn't understand machine code and machine architecture at least in in my position I have to understand a bit of it because you mess up the cash and you're off in performance by a factor of a hundred right shouldn't be that if you are interested in higher performance or the size of the computer you have to deploy so so I would go there's a simpler I used to mention C but these days going low-level is not actually what gives you the performance it is to express your ideas so cleanly that you can think about it and the optimizer can understand what you're up to my favorite way of optimizing these days is to throw out the clever bits and see if it's dawn runs fast and sometimes it runs faster so I need the abstraction mechanisms or something like C++ to write compact high-performance code there was a beautiful keynote by Jason Turner the CPP con a couple of years ago where he decided he was going to program pong on Motorola 6800 I think it was and he says well this is relevant because it looks like a microcontroller it has specialized hardware it has not very much memory and it's relatively slow and so he shows in real time how he writes pong starting with fairly straightforward low-level stuff improving his abstractions and what he's doing he's writing C++ and it translate into in 286 assembler which you can do with playing and you can see it in real-time it's the compiled explora which you can use on the web and then he wrote a little program that translated 86 assembler into Motorola has simpler and so he types and you can see this thing in real time while you can see it in real time and even if you can't read the assembly code you can just see it his code gets better the code the assembler gets Kimura he increases the abstraction level uses C++ 11 as it were better this code gets clean that gets easier maintain the code shrinks and it keeps shrinking and I could not in any reasonable amount of time write that a simpler as good as the compiler generated from really a quite nice modern C++ and I'll go as far as to say the the thing that looked like C was significantly uglier and and smaller when it becames and and larger when it became machine code so what the the abstractions that can be optimized important I would love to see that kind of visualization larger code bases yeah there might be blood a few can't show a larger code base in a one-hour talk and to have it fit on screen right so that C is if you love so my two languages would be machine code and C++ and then I think you can learn a lot from the functional languages so pig has pralaya male I don't care which I think actually you you'll you'll learn the same lessons of expressing especially mathematical notions really clearly and having the type system that's really strict and then you should probably have a language for sort of quickly churning out something you could pick JavaScript you could pick Python you could pick Ruby really make of JavaScript in general so you kind of you're talking in the Platonic sense of all languages about what they're good at what their philosophy design is but there's also a large user base behind each of these languages and they use it in the way maybe it wasn't really designed for that's right javascript is used way beyond I probably put hooks design for it let let me say it this way when you build a tool you do not know how it's going to be used you try to improve the tool by looking at how it's being used and when people cut their fingers off and try and stop that from happening but really you have no control over how something is used so I'm very happy and proud of some of the things he plus plaus being used at and some of the things I wish people wouldn't do Bitcoin mining being my favorite example uses as much energy as Switzerland and mostly serves criminals yeah but back to back to the languages I actually think that having JavaScript run in the browser what was was an enabling thing for a lot of things yes you could have done it better but people were trying to do it better they were using proof sort of more principles language designs but they just couldn't do it right and the non professional programmers that write or lots of that code just couldn't understand them so it did amazing job for what it was it's not the prettiest language and I don't think it ever will be the prettiest language but that's not be bigots here so what was the origin story of C++ you you basically gave a few perspectives of your inspiration of object-oriented programming that's you had a connection with C in performance efficiency was an important thing you were drawn to efficiency and reliability reliability you have to get both what what's reliability I I really want my telephone calls to get through and I want the quality of what I am talking coming out with the other end the other end might be in London or wherever so and you don't want the system to be crashing if you're doing a bank here is you must not crash it might be your your bank account that is in trouble there's different constraints like in games it doesn't matter too much if there's a crash nobody dies and nobody gets ruined but I am interested in the combination of performance partly because of sort of speed of things being done part of being able to do things that is necessary to do to have reliable energy of larger systems if you spend all your time interpreting a simple function call you are not going to have enough time to do proper signal processing to get the telephone calls to sound right I know that or you have to have 10 times as many computers and you can't afford your phone anymore it's a ridiculous idea in the modern world because we have solved all of those problems I mean they keep popping up in different ways as we tackle bigger and bigger problems efficiency remains always an important aspect but you have to think about efficiency not just as speed but as an enabler to things and women thinks it enables is this reliability is dependability you won when I press the pedal the brake pedal of a car it is not actually connect it directly to to anything but a computer that computer better work let's talk about reliability just a little bit so modern cars have ECU's millions of lines of code Mme so this is certainly especially true of autonomous vehicles where some of the aspects of the control or driver assistance systems that steer the car the key panel and so on so how do you think you know I talk to regulators people in government who are very nervous about testing the safety of these systems of software ultimately software that makes decisions that could lead to fatalities so how do you how do we test software systems like these first of all safety like performance and like security is a systems property people tend to look at one part of a system at a time and saying something like this is secure that's all right I don't need to do that yeah that piece of code is secure I'll buy your operator right if you want to have reliability if you want to have performance if you want to have security you have to look at the whole system I did not expect you to say that but that's very true yes I'm dealing with one part of the system and I want my part to be really good but I know it's not the whole system furthermore if making an individual part perfect may actually not be the best way of getting the highest degree of reliability and performance and such the spumone says super cross type say not type safe you can break it sure I can break anything that runs on a computer I may not go through your type system if I wanted to break into your computer I'll probably try SQL injection and it's very true if you think about safety or even reliability at its system level especially when a human being is involved it's starts becoming hopeless pretty quickly in terms of proving that something is safe to a certain level yeah there's so many variables it's so complex well let's get back to something we can talk about and it actually makes some progress on yes we look at C++ programs and we can try and make sure the crash less often the way you do that is largely by simplification it is not the first step is to simplify the code have less code have code that are less likely to go wrong it's not by runtime testing everything it is not by big test frameworks that you're using yes we do that also but the first step is actually to make sure that when you want to express something you can express it directly in code rather than going through endless loops and convolutions in your head before it gets down the code that if if the way you are thinking about a problem is not in the code there is a missing piece that's just in your head and the code you can see what it does but it cannot see what you thought about it unless you have expressed things directly when you express things directly you can maintain it it's these years to find errors is easier to make modifications it's actually easier to test it and lo and behold it runs faster and therefore you can use a smaller number of computers which means there's less hardware that could possibly break so I think the key here is simplification but it has to be to use the Einstein code as simple as possible and no simpler not simpler well there are other areas with under constraints where you can be simpler than you can be in C++ but in the domain I'm dealing with that's the simplification I'm after so how do you inspire or ensure that the Einstein level simplification is reached so okay can you do code review can you look at code is there if I gave you the code for the Ford f-150 and said here is this a mess or is this okay is it possible to tell is it possible to regulate an experienced developer can do it code and see if it smells you know I'm mixed metaphors deliberately yes the the point is that it is hard to generate something that is really obviously clean and can be appreciated but you can usually recognize when you haven't reached that point and so if I I've never looked at me if 150 code so I wouldn't know but but I know what I ought to be looking for there I'll be looking for some tricks that correlates with bugs and elsewhere and I have tried to formulate rules for what what good code looks like and the current version of that is called the C++ core guidelines one thing people should remember is there's what you can do in a language and what you should do in a language you have lots of things that is necessary in some context but not another's as things that exist just because there's 30 year old code out there and you can't get rid of it but you can't have rules it says when you create it try and follow these rules this does not create good programs by themselves but it limits the damage and off for mistakes it limits the possibilities of the mistakes and basically we are trying to say what is it that a good programmer does at the fairly simple level of where you use the language and how you use it now I can move all the rules for chiseling in my marble it doesn't mean that somebody who follows all of those rules can do a masterpiece by Machine Angelo that is there something else to write a good program just is there something else to create important work of art that is there's some kind of inspiration understanding gift but we can approach the sort of technical the the craftsmanship level of it the the the famous painters the famous cultures was among other things superb craftsmen they could express their ideas using their tools very well and so these days I think what I'm doing what a lot of people are doing we're still trying to figure out how it is to use our tools very well for a really good piece of code you need a spark of inspiration and you can't I think regulate that you you cannot say that I'll take a picture only I'll buy your picture only if you're at least then go there are things you can regulate but not the inspiration I think that's quite beautifully put it is true that there is there's an experienced programmer when you see code that's inspired that's like Michelangelo you know it when you see it and the opposite of that is code that is messy code that smells you know when you see it and I'm not sure you can describe it in words except vaguely through guidelines and so on yes it's easier to recognize ugly than to recognize beauty in code and for the reason is that sometimes beauty comes from something that's innovative and unusual and you have to sometimes think reasonably hard to appreciate that on the other hand the misses have things in common and you can you can have static checkers dynamic checkers that finds large number of the most common mistakes you can catch a lot of sloppiness mechanically I'm a great fan of static analysis in particular because you can check for not just the language rules but for the usage of language rules and I think we will see much more static analysis in the coming decade clear the drive word static analysis you represent a piece of code so that you can write a program that goes or that representation and look for things that are right and not right so for instance you can analyze a program to see if resources are leaked that's one of my favorite problems it's not actually all that hard and one C++ but you can do it if you were writing in the C level you have to have a Murloc and a free and they have to match if you have them in a single function you can usually do it very easily if there's a man log here there should be a free there on the other hand in between can be drawing complete code and then it becomes impossible yeah if you pass that pointer to the memory out of a function and then want to make sure that the free is done somewhere else now it gets really difficult and so for static analysis you can run through a program and you can try and figure out if there's any leaks and what you will properly find is that you will find some leaks and you'll find quite a few places where your analysis can't be complete it might depend on runtime it might depend on the cleverness of your analyzer and it might take a long time some of these programs run for a long time but if you combine such analysis with a set of rules it says how people could use it you can actually see why the rules are violated and that stops you from getting into the impossible complexities you don't want to solve the halting problem the static analysis is looking at the code without running the code yes and thereby it's almost not in production code but it's almost like an educational tool of how the language should be used it's guys you like it is best right it would guide you in how you write future code as well and you learn together yes so basically you need a set of rules for how you use the language then you need a static analysis that catches your mistakes when you violate the rules or when your code ends up doing things that it shouldn't despite the rules because there's the language rules you can go further and again it's back to my idea that I would much rather find errors before I start running the code if nothing else once the code runs if it catches an error at run times I have to have an error handler and one of the hardest things to write in code is their handling code because you know something went wrong do you know really exactly what went wrong usually not how can you recover when you don't know what the problem was you can't be a hundred percent sure what the problem was in many many cases and this is this is part of it so yes we need good languages or good type systems we need rules for how to use them we need static analysis and the ultimate for static analysis is of course program proof but that still doesn't scale so the kind of systems we deploy then we start needing testing and the rest of the stuff so C++ is an object-oriented programming language that creates especially with its newer versions as we'll talk about higher and higher levels of abstraction so how do you design let's even go back to the origin C++ how you design something with so much abstraction that's still efficient and is still something that you can manage do static analysis on you can have constraints on they can be reliable those things we've talked about so create the to me slightly there's a slight tension between high-level abstraction and efficiency that's a good question I could probably have a year's course just trying to answer it yes there's a tension between efficiency and abstraction but you also get the interesting situation that you get the best efficiency out of the best abstraction and my main tool for efficiency for performance actually is abstraction so let's go back to how C++ got there yeah you said it was up to Rory in the programming language I actually never said that it's always quoted but I never did I said C++ supports object-oriented programming but it's nine other techniques and that that's important because I think that the best solution to most complex interesting problems require ideas and techniques from things that has been called object-oriented data abstraction function or traditional C style code all of the above and so when I was designing C++ I soon realized I couldn't just add features if you just add what looks pretty or what people ask for or what you think is good one by one you're not going to get a coherent whole what you need is a set of guidelines that that that guides your decisions should this feature Vienna should this feature be out how should a feature be modified before it can go in and such and there's a in in the book I wrote about that that sign evolution of si+ process a whole bunch of rules like that most of them are not language technical they they they're they're things like don't violate static type system because I like static type system for the obvious reason that I like things to be reliable on reasonable amounts of hardware but one of these rules is the zero overhead principle the were kind of put a zero overhead principle it basically says that if you have an abstraction it should not cost anything compared to write the equivalent code at a lower level so if I have say a matrix multiplied it should be written in such a way that you could not drop to the C level of abstraction and use arrays and pointers and such and run faster and so people have written such matrix multiplications and we have actually gotten code that ran faster than Fortran because once you had the right abstraction you can eliminate you can eliminate temporaries and you can do loop fusion and other good stuff like that that's quite hard to do by hand and in a lower level language and there's some really nice examples of that and the key here is that that matrix multiplication the matrix abstraction allows you to write code that's simple and easy you can do that in any language but with C++ it has the features so that you can also have this thing run faster than if you hand coded it now people have given that lecture many times I and others and a very common on question after the talk where you have demonstrated that you can outperform Fortran for dense matrix multiplication people come up and says yeah but there are C++ if I rewrote your code and see how much faster would have run the answer is much slower this happened the first time actually back in the ages with a friend of mine called Doug McIlroy who demonstrated exactly this effect and so the principle is you should give programmers the tools so that the abstractions can follow the 0oi principle furthermore when you put in a language feature in C++ or a standard library feature you try to meet this it doesn't mean it's absolutely optimal but it means if you're hand coded with the usual the facilities in the language in C++ in C you should not be able to better it usually you can do better if you use embedded a simpler for machine code for some of the details to utilize part of a computer that the compiler doesn't know about but you should get to that point before you be to the abstraction so that's that's a beautiful ideal to reach for and we meet it quite often quite often so where's the magic of that coming from there's some of it is the compilation process so the implementation is C++ some of it is the design of the feature itself the guidelines so I've recently an often talk of Chris Ladner so clang what just out of curiosity is your relationship in general with the different implementations in C++ as you think about you and committee and other people C++ think about the design of new features or design of previous features the in in trying to reach the ideal of zero overhead who does the magic come from the design the guidelines or from the implementations and and not all you have you you are you you you you go for programming technique program language features and implementation techniques you need all three and how can you think about all three at the same time it takes some experience takes some practice and sometimes you get it wrong but after a while you sort of get it right I don't write compilers anymore but Brian Kearney and pointed out that one of the reason c++ succeeded was some of the craftsmanship I put into the early compilers and of course I did the languages sign of course I wrote a fair amount of code using this kind of stuff and I think most of the successes involves progress in all three areas together a small group of people can do that two three people can can work together to do something like that it's ideal if it's one person that has all the skills necessary but nobody has all the skills necessary in all the fields where C++ is used so if you want to approach my idea in say concurrent programming you need to know about algorithms of my current programming you need to know the the triggering of lock-free programming you need to know something about compiler techniques and then you have to know some of the program error the sorry the application areas what this is like some forms of graphics or some forms of what are called the web server and kind of stuff and that's very hard to get into a single head but small groups can do it too it says there differences in your view not saying which is better or so on but difference in the different implementations of C++ why are there several sort of many of you naive questions for me GCC clang so this is a very reasonable question when I designed C++ most languages have multiple implementations because if you wanna I p.m. if you run on a Sun if you wanna Motorola that those just many many companies and they each have their own compilation structure the old compilers it was just fairly common that those many of them and I wrote C front assuming that other people would write compilers for C++ if I was successful and furthermore I wanted to utilize all the backend infrastructure were available I soon realized that my users were using 25 different linkers I couldn't write my own linker yes I could but I couldn't write 25 linkers and also get any work done on the language and so it came from a world where there was many linkers many optimizers many compiler front ends not not to start but over at many operating systems the whole world was not an 86 and linux box or something whatever is the standard today in the old days they said a set of X so basically I assumed there'd be lots of compilers it was not a decision that there should be many compilers it was just a fact that's the way the world is and yes many compilers emerged and today there's at least four front ends playing GCC Microsoft and EDG it is Design Group they they supply a lot of the independence organizations and the embedded systems industry and there's lots and lots of backends we have to think about how many dozen begins there are because different machines have different things especially in the embedded world their machines are very different the architectures are very different and so having a single implementation was never an option now I also happen to dislike monocultures monocultures they are dangerous because whoever owns the monoculture can go stale and there's no competition and there's no incentive to innovate there's a lot of incentive to put barriers in the way of change because hey we own the world and it's a very comfortable world for us and who are you to to mess with that so I really am very happy that this for front-ends for C++ clanks great but GCC was great but then it got somewhat stale Tran came along and GCC's much better now competition my Microsoft is much better now so hello at least a low number our front end puts a lot of pressure on stand-ups compliance and also on performance and error messages and compile time speed all this good stuff that we want do you think crazy question there might come along you hope that might come along implementation of C++ written given all its history written from scratch so written today from scratch well playing and the LLVM this more less written by from scratch but there's been c++ 11 14 17 20 you know there's been a lot you know later somebody's going to try again there has been attempts to write new C++ compilers and some of them has been used and some of them has been absorbed into others and so yeah I don't happen so what are the key features of C++ and let's use that as a way to sort of talk about the evolution of C++ the new feature so at the highest level what are the features that were there in the beginning what features got added its first get a principal on aim in place C++ is for people who want to use hardware really well and then manage the complexity of doing that through abstraction and so the first facility you you have is a way of manipulating the machines at a fairly low level that looks very much like see it has loops it has variables it has pointers like machine addresses it can access memory directly it can allocate stuff in the absolute minimum of space needed on the machine there's a machine facing part of C++ which is roughly equivalent to C I said C++ could beat C and it can doesn't mean I dislike see if I disliked C wouldn't have built on it furthermore after Dennis Ritchie I'm probably the major contributor to modern C and well I had lunch with Dennis most days for 16 years and we never had a harsh word between us so these C versus C++ fights are for people who don't quite understand what's going on then the other part is the abstraction and there the key is the class which is a user defined type and my idea for the class is that you should be able to build a type that's just like the building types in in the way you use them in the way you declare them and the way you get the memory and you can do just as well so in C++ there's an int as in C you should be able to build an abstraction a class which we can call capital int that you could use exactly like an integer and run just as fast as an integer there's the idea right there and of course you probably don't want to use the int itself but it has happened people have wanted integers that were range checked so that you couldn't overflow one such especially for very safety critical applications like the fuel injection for a marine diesel engine for the largest ships this is a real example by the way this has been done they they built themselves an integer that was just like integer except that couldn't overflow if there's no or flow you went into the error handling and then you built more interesting types you can build a matrix which you need to do graphics or you could build a gnome for a for a video game and all these are classes and they appear just like the built-in types exciting terms of efficiency and so on so what else is there and flexibility so I don't know for people who are not familiar with object-oriented programming there's inheritance there's a hierarchy of classes you you can just like you said create a generic vehicle that can turn left so what people found was that you don't actually know how do I say this a lot of types are related that is the vehicles all the accounts are related bicycles cars fire engines tanks they have some things in common and some things that differ and you would like to have the common things common and having the differences specific and when you didn't want to know about the differences like just turn left uuuuu you don't have to worry about it that's how you get the traditional object-oriented programming coming out of simulate opted by small talk and C++ and all the other languages the other kind of obvious similarity between types comes when you have something like a vector fortune gave us the vector as called array of doubles but the minute you have a vector of doubles you want a vector or double precision doubles and for short doubles for graphics and why should you have not have a vector of integers while you're added or vector of vectors and vector of vectors of chess pieces now we have a board right so this is you express array the commonality as the idea of a vector and the variations come through parameterization and so here we get the two fundamental ways of abstracting or of having similarities of types in C++ there's the inheritance and there's a parameterization there's the object-oriented programming in this generic programming with the templates for the generic program yeah so you you've presented it very nicely but now you have to make all that happen and make it efficient so generic programming with templates there's all kinds of magic going on especially recently that you can help catch up on but it feels to me like you can do way more than what you just said with templates you can start doing this kind of meta programming this kind you can do meta programming also I I didn't go there and in that explanation we're trying to be very basics but go back on so the implementation implementation if you couldn't implement this efficiently if you couldn't use it so that it became efficient it has no place in C++ because it were violates the zero overhead principle so when I had to get up during programming inheritance I took the idea of virtual functions from Simula virtual functions is a similar term class is a similar term if you ever use those words say thanks to question you go and all you and I'll and I did the simplest implementation I knew off which was basically a jump table so you get the virtual function table or the function goes in do it does an indirection through a table and get the right function that's how you pick the right thing there and I thought that was trivial it's close to optimal it's endo is obvious it turned out the Simula had a more complicated way of doing it therefore slower and it turns out that most languages have something that's a little bit more complicated sometimes more flexible but you pay for it and one of the strengths of C++ was that you could actually do this object-oriented stuff and your overhead compared to ordinary functions there's no interactions it's not open five ten twenty five percent for just the core it sits down there it's not too and that means you can afford to use it furthermore in C++ you have the distinction between a virtual function and a non-virtual function if you don't want any overhead if you don't need the interaction that gives you the flexibility in object-oriented programming just don't ask for it so the idea is that you only use virtual functions if you actually need the flexibility so it's not zero overhead but zero overhead compared to any other way of achieving the flexibility now also parameterization basically the compiler looks at at the the template say the vector and it looks at the parameter and then combines the two and generates a piece of code that is exactly as if you're written a vector off that specific type yes so that's the that's the minimal overhead if you have many template parameters you can actually combine code that the compiler couldn't usually see at the same time and therefore get code that is faster then if you had handwritten stuff on this you are very very clever so the thing is Parature i's code the compiler fills stuff in during the compilation process not during runtime that's right and so in furthermore it gives all the information it's gotten which is the template the parameter and the context of use it combines the three and generates good code but it can generate now it's a little outside of what I'm even comfortable thinking about but it can generate a lot of code yes and how do you remember being both amazed at the power of that idea and how ugly the debugging look the debugging can be truly horrid come back to this because I have a solution anyway the debugging was ugly the code generated by C++ has always been ugly because there's these inherent optimizations a modern C++ compiler has runned in middle-end and beckoned optimizations even C front back in 83 had front end and back end optimizations I actually took the code generated an internal representation munch that implements a representation to generate good code so people says it's not a compiler I generate see if the reason it generated C was a one that you used to C's code generators that are really good at backend optimizations but I need a front end of two eyes Asians and therefore the C I generated was optimized C hmm the way really good up a handcrafted optimize a human who could could generate it and it was not meant for humans it was the output of a program and it's much worse today and with templates it gets much worse still so it's hard to do it's hard to combine simple debugging with simple with the optimal code because the idea is to drag in information from different parts of the code to generate good code machine code and that's not readable so what people often do for debugging is they turn the optimizer off and so you get code that when you when when something in your source code looks like a function call it is a function call when the optimizer is turned on it may disappear the function call it may inline and so one of the things you can do is you can actually get code that is smaller than the function call because you eliminate the function preamble and returned and that's just the operation there one of the key things when I did templates was I wanted to make sure that if you have say a sort algorithm and you give it a sorting criteria if that sorting criteria is simply comparing things with lesson the code generators should be the less than not a indirect function call to a compression object which is what it is in the source code but we really want down to the single instruction and but anyway turn off the optimizer and and you can you can debug the first level of debugging can be done and I always do without the optimization on because then I can see what's going on and then there's this idea of concepts that puts some now I've never even the I don't know if it was ever available in any form but it puts some constraints on the stuff you can parameterize essentially let me try and explain yes so yes it wasn't there ten years ago we have had versions of it that actually work for the last four or five years it was a design by Gabby does raise true certain and me we were professors and postdocs in Texas at the time and the implementation by Andrew Sutton has been available for at that time and it is part of C++ 20 and the standard library that uses it so this is becoming really very real it's available in clang and GCC GCC for a couple of years and I believe Microsoft zum-zum going to do it expect a wall of C++ 20 to be available so in all the major compilers in 20 but this kind of stuff is it's available now I'm just saying that because otherwise people might think I was talking about science fiction and so what I'm going to say Israel on Crete you can write it today and there's production users of it so the basic idea is that when you have a a generic component like a sort function the sort function will will require at least two parameters one a data structure with a given type and comparison criteria and these things are related but obviously you can't compare things if you don't know what the type of things you compare and so you want to be able to say I'm going to sort something and did this to be sortable what does it mean to be sortable you look it up in the standard it has to have it has to be a sequence with a beginning and an end there has to be random access to that sequence and there has to be the element types has to be comparable like you more like an operator can I do it yes what illogical already cannot basically what concepts are there compile-time predicates there predicates you can ask are you a sequence yes I have begin an end are you a random exit sequence yes I have subscripting and plus it's your element type something that has a less then yes I have a less than hits and so basically that's the system and so instead of saying I will take a parameter of any type it'll say I'll take something that's audible and it's well defined and so we say okay you can sorta less then I don't want less then I want greater then also something I invent so you have two parameters the sortable thing and the compassion criteria and the comparison criteria will say well I can you you can write it saying it should operate on the element type and it has the compassion operations so that's the simply the fundamental thing it's compile-time predicates do you have the properties I need so it specifies the requirements of the code on the parameters that gets yes there are lots of types actually but operating in the space of concepts concepts the word concept was used by Alec Stephan of who is sort of the father of generic programming in the context of C++ there's other places that use that word but the way we call Genetic Programming is Alex's and he called them concepts because he said there they are the sort of the fundamental concepts of an area so they should be called concepts and we've had concepts all the time if you look at the knr book about si si has arithmetic types and it has integral types it says so in the book and then it lists what they are and they have certain properties the difference today is that we can actually write a concept that will ask a type are you an integral type do you have the properties necessary to be an integral type do you have Proust - divide so what may be the story of concepts because I thought it might be part of C++ 11 C C C's o X or whatever it was at the time what was the why didn't it look like what we'll talk a little bit about this fascinating process of standards because I think it's really interesting for people it's interesting for me but why did it take so long what shapes the the idea of concepts take what were the challenges back in 87 of there abouts 97 well 1987 like they are about so when I was designing templates obviously I wanted to express the notion of what is required by a template of its arguments and so I looked at this and basically for for templates I wanted three properties I wanted to be very flexible it had to be able to express things I couldn't imagine because I know I can't imagine everything and I've been suffering from languages and try to constrain you to only do what you're the designer thought good didn't want to do that secondly it had to run faster as faster faster that hand written code so basically if I have a vector of T and I take a vector of cha it should run as fast as you built a vector of cha yourself without parameterization and second and thirdly I wanted to be able to express the constraints of of the arguments have proper type checking of the interfaces and neither I nor anybody else at the time knew how to get all three and I thought for C++ I must have the two first otherwise it's not C++ and it bothered me for an hour a couple of decades that I couldn't solve the third one I mean I was the one that put function argument type checking in to see I know the value of good interfaces I didn't invent that idea it's very common but I did it and I wanted to do the same for templates of course and I could so it bothered me then we try it again mm of to 2003 cavitus raised and I started analyzing the problem explained possible solutions there was not a complete design a group in University of Indiana an old friend of mine they started a project at Indiana and we thought we could get a good system of concepts in another two or three years that would have made C++ la 11 to C++ Oh 607 well it turns out that I think we got a lot of the fundamental ideas are wrong they were took on conventional they didn't quite fit C++ in my opinion didn't serve implicit conversions very well it didn't of mixed makes type arithmetic mix type computation computations very well a lot of stuff came out of the functional community and it that community didn't deal with multiple types in in the same way as C++ does had more constraints on on what you could express and didn't have the draconian performance requirements and basically we tried we tried very hard we had some successes but it just in the end wasn't didn't compile fast enough was too hard to use and didn't run fast enough unless you had optimizes that was beyond the state of the art they still are so we had to do something else basically it was the idea that a set of parameters has defines a set of operations and you go through an interaction table just like for virtual functions and then you try to optimize the interaction away to get performance and we just couldn't do all of that but get back to the standardization we are standardizing C++ on the ISO rules which a very open process people come in there's no requirements for education or experience they start develop C++ and there's a hope when was the first standard established what is that like the ISO standard is there committee that you're referring to she was a group of people what it was that like how often do you meet what's the disguise I'll try and explain that so sometime in early 1989 two people one from IBM one from HP turned up in my office and told me I would like to standardize it PLAs PLAs this was a new idea to me and I pointed out that it wasn't finished yet it wasn't ready for former standardization and such and they say no beyond even gotten it you you really want to do this our organizations depend on c++ we cannot depend on something that's owned by another corporation that might be a competitor of course we could rely on you but you might get run over by a bus right the old really needs to get this out new it has to be standardized under formal rules and we are going to standardize it under ISO rules and you really want to be part of it because basically otherwise we will do it ourselves and we know you can do it better so through a combination of arm-twisting and flattery Carolus started so in late in late 89 there was a meeting in DC at the x-ray no it was not ISO then it was an SI the American national standard were doing we met there we were lectured on the rules of how to do when ANSI standard there was about 25 of us there which apparently was a new record for that kind of meeting and some of the old see guys that it's been standardizing see was there so we got some expertise in so the way this works is that it's an open process anybody can consign up if they pay the minimal fee which is about a thousand dollars still less then just a little bit more now and I think it's twelve hundred and eighty dollars it's not it's not going to kill you and we have three meetings a year this is fairly standard we try to meetings a year for a couple years that didn't work too well so three weeks is three one-week meetings a year and you meet and you have taken meet technical discussions and then you bring proposals forward for votes the votes are done one person per one vote per organization so you can't have say IBM come in with 10 people and dominate things that's not allowed and these organizations that extends to the UC bus bus this yes this is all individuals or individuals I mean it's a it's a bunch of people in room deciding the design of a language based on which a lot of the world's systems run right well I think most people would agree it's better than if I decided it or better than if a single organization like agency decides it I don't know if everyone agrees to that by the way bureaucracies have their critics - yes they they're that look standardization is not pleasant it's it's it's horrifying like democracy what we exactly as Churchill says democracy is the worst way except for or the others right and it's about say the same reforms but anyway so we meet and we we have these votes and that determines what the standard is couple of years later we extended this so it became worldwide we have stand out of organizations that are active in currently 15 to 20 countries and another fifteen to twenty are sort of looking and and voting based on the rest of the work on it and we meet three times a year next week I'll be in Cologne Germany spending a week doing standardization and we'll vote out the committee draft or c plus plus 20 which goes to the national standards committees for comments and requests for changes and improvements then we do that and there's a second set of votes where hopefully everybody votes in favor this has happened several times the first time we finished we started in the first technical meeting was in 1990 the last was in 98 we voted it out that was suspended that people used till 11:00 or a little bit past 11:00 and was an international standard all the countries voted in favor it took longer with 11 I'll mention why what all the nations voted in favor and we work on the basis of consensus that is we do not want something that passes 6040 because then we're going to get dialects and opponents and people complain too much they don't complain so much but basically it no real effect the the standards has been obeyed they have been working to make it easier to use many compilers many computers and all of that kind of stuff and so the first the traditional with ISO standards to take ten years we did the first one and eight brilliant and we thought we were going to do the next one and six because now we're good at it right it took 13 yeah it was named Oh X he was named Oh X hoping that you would at least get it in within the single within the arts the single day I thought we would get yeah I thought would gets six seven or eight the confidence of youth yes right well the point is that this was sort of like a second system effect that is we now knew how to do it and so we're going to do it much better and we got more ambitious and bish han dicho penguia furthermore there is this tendency because it's a 10-year cycle or age doesn't matter just before you're out to ship somebody has a bright idea yeah and so we really really must get that in we did that successfully with the STL we got the the standard Liars all the STL stuff that that my base be I think it saved C++ it was beautiful yes and then people tried it with all our things and it didn't work so well they got things in but it wasn't as dramatic and it took longer and longer and longer so after C++ 11 which was a huge improvement and what basically what most people are using today we decided ever again and so how do you avoid those slips and the answer is that you shipped more often so that if you if you if you have a slip on the 10-year cycle by the time you know it's a slip there's 11 years till you get it yeah now with a three year cycle there is about three or four years till you get it like the delay between feature freeze and shipping so you always get one or two years more and so we were shipped fourteen on time we shipped seventeen on time and we ship we will ship 20 on time it's it'll happen and furthermore this allow this gives a predictability that allows the implementers the compiler implementers the library implementers so they have a target and they deliver on it 11 took two years before most compilers were good enough 14 most compilers were actually getting pretty good in 14 17 everybody shipped in 17 well we are going to have at least almost everybody's ship almost everything in 20 and I know this because they're shipping in nineteen predictably this is good delivery on time is good and so yeah that's great those how it works there's a lot of features that came in in C++ 11 there's a lot of features at the birth of C++ they were amazing and ideas with concepts in 2020 what to you is the most justjust to you personally beautiful or just you sit back and think wow that's just nice and clean feature of C++ I have written two papers for the history of programming languages conference which basically asked me such questions and I'm writing a third one which I will deliver at the history of programming languages conference in London next year so I've been thinking about that and there is one play answer constructors and destructors the way a constructor can establish the environment for the use of the Java type for object and the destructor that cleans up any messes at the end of it that is the key to C++ that's why we don't have to use garbage collection that's how we can get predictable performance that's how you can get the minimal overhead in many many cases and have really clean types it's the idea of constructor destructor pairs sometimes it comes out under the name our high AIII resource acquisition is initialization which is the idea that you grab resources and the constructor and release them and destructor it's also the best example of why I shouldn't be in advertising I get the best idea and I call it resource acquisition is initialization not the greatest naming I've ever heard so it's types abstraction of types you said I want to create my own types so types is an essential part of C++ and making them efficient as the if it is the key part and GU the this is almost getting philosophical but the construction and the destruction the creation of an instance of a type and the freeing of resources from that instance of a type is what defines the object is uh that's like birth and death is what defines human life yeah that's right by the way philosophy is important you can't do good language design without philosophy because what you are determining is what people can express this is very important by the way constructors destructors came into C++ in 79 in about the second week of my work with what was then Corsi of the classes it is a fundamental idea next comes the fact that you need to control copying because once you control as you says birth and death you have to control taking copies which is another way of creating an object and finally you have to be able to move things around so you get the move operations and that's the set of key operations you can define on a C++ type inserts you those things are just a beautiful part of C++ that is at the core of it all yes you mentioned that you hope there will be one unified set of guidelines in the future for how to construct the programming language so perhaps not one programming language but a unification of how we build programming languages if you remember the statement I I have some trouble remembering it but I know the origin of that idea so maybe you can talk about sort of C++ has been improving there's been a lot of programming language do you word is the arc of history taking us do you hope that there is a unification about the languages with which we communicate in the digital space well III think that languages should be designed not by clobbering language features together and doing slightly different versions or somebody else's ideas but through the creation of a set of principles rules of thumbs whatever you call them I I made them for C++ and we're trying to teach people in the Standards Committee about these rules because a lot of people come in and says I've got a great idea let's put it in language and then you have to ask why does it fit in the language why does it fit in this language it may fit in on our language and not here or may fit here not the other language so you have to work from a set of principles and you have to develop that set of principles and it's one example that I sometimes remember is I was sitting down with some of the designers of common lisp and we are talking about languages and language features and obviously we didn't agree about anything because well this was not C++ and vice versa too many parenthesis but suddenly we started making progress I said I had this problem and I developed it according to these ideas and they said what why we had that problem different problem and we develop it the same kind of principles and so we worked through large chunks of C++ and large chunks of Common Lisp and figure out we actually had similar sets of principles of how to do it but the constraints on our designs were very different and the aims for the usage was very different but there was commonality in the way you reason about language features and the fundamental principles you are trying to do so do you think that's possible to so they're just like there is perhaps a unified theory of physics of the fundamental forces of physics now I'm sure there is commonalities among the languages but there's also people involved you know that help drive these developing these languages do you have a hope or an optimism that there will be a unification if you think about physics and Einstein towards a simplified language do you think that it's possible let's remember sort of modern physics I think started with Galileo in the 1300s so they have had seven hundred years to get going modern computing started in about 49 we've got what's that 70 years they have 10 10 times yeah and furthermore they they are not as bothered with people using physics the way we are worried about programming it's done by humans so each have problems and constraints the others have but we are very immature compared to physics so I would look at sort of the philosophical level and and look for fundamental principles like you don't leak resources you shouldn't you don't take errors at runtime that you don't need to you don't violate some kind of type system there's many kinds of type systems but when you have one you don't break it etc etc there will be quite a few and it will not be be the same for all languages but I think if we step back at some kind of philosophical level we can we would be able to agree on sets of principles that applied to two sets of problem areas and within an area of use by in C++ this case what used to be called systems programming the area between the hardware and the the the fluffier parts of the system you you might very well see a convergence so these days you see rust having a adopted ra íí- and sometime accuses me for having borrowed it 20 years before they discovered it but it's we're seeing some kind of conversion convergence here instead of relying on garbage collection all the time the garbage collection languages are doing things like the dispose patterns and such that imitates some of the construction destruction stuff and they're trying not to use the garbage collection all the time things like that so there's there there's conversion but I think we have to step back to the philosophical level and agree on principles and then we'll see some conversions convergences and it will be application domain-specific so a crazy question but I work a lot with machine learning with deep learning I'm not sure if you touch that world that much but you could think of programming is the thing that takes some input programming is the task of creating a program and a program takes some input and produces some output so machine learning systems train on data in order to be able to take an input and produce output but they're messy fuzzy things much like we as children grow up you know we take some input make some output but we're noisy we mess up a lot we're definitely not reliable biological system or a giant mess so there's a sense in which machine learning is a kind of way of programming but just fuzzy it's very very very different than C++ because C++ is a like it's just like you said it's extremely reliable it's efficient it's you know you can you can measure you can test in a bunch of different ways with biological systems or machine learning systems you can't say much except sort of empirically saying that ninety-nine point eight percent of the time it seems to work what do you think about this fuzzy kind of programming indeed even see it as programming is it solely and totally another kind of world I I think it's a different kind of world and it is fuzzy and in my domain I don't like fuzziness that is people say things like they want everybody to be able to program but I don't want everybody to program my my aeroplane controls or the car controls I want that to be done by engineers I want that to be done with people that are specifically educated and trained for doing building things and it is not for everybody similarly a language like C++ is not for everybody it is generated via sharp and effective tool for professionals basically and definitely for people who who aim at some kind of precision you don't have people doing calculations without understanding math right counting on your fingers not going to cut it if you want to fly to the moon and so there are areas where and eighty-four percent accuracy rate 16 percent false positive rate it's perfectly acceptable and where people will probably get no more than 70 you said 98% I what I have seen is more like 84 and by by really a lot of blood sweat and tears you can get up to the 92 and a half right so this is fine if it is say pre-screening stuff before the human look at it it is not good enough for for life-threatening situations and so there's lots of areas where where the fuzziness is perfectly acceptable and good and better than humans cheaper than humans but it's not the kind of engineering stuff I'm mostly interested in I worry a bit about machine learning the context of cars you know much more about this than I do I worry too but I'm I'm sort of a an amateur here I've read some of the papers but I have not ever done it and the the idea that scares me the most is the one I have heard and I don't know how common it is that you have this AI system machine learning all of these trained neural nets and when they're something is too complicated they asked the human for help but human is reading a book or sleep and he has 30 seconds or three seconds to figure out what the problem was that the AI system couldn't handle and do the right thing this is scary I mean how do you do the cutter walk between the Machine and the human it's very very difficult and for the designer or one of the most reliable efficient and powerful programming languages C++ I can understand why that world is actually unappealing it is for most engineers to me it's extremely appealing because we don't know how to get that interaction right but I think it's possible but it's very very hard it is and I was stating a problem no yes that is the nostril I mean I would much rather never rely on a human if you're driving a nuclear reactor if you're or an autonomous vehicle it would it's much better to design systems written in C++ that never asked human for help let's just get one fact in yeah all of this AI star Suns help us constructs so so that's one reason I have to keep a weather eye out or what's going on in that field but I will never become an expert area but it's a good example of how you separate different areas of applications and you have to have different tools different principles and then they interact no major system today is written in one language and there are good reasons for that when you look back at your life work what is uh what is the moment what is a event creation that you're really proud of they say damn I did pretty good there is it as obvious as the creation of C++ and so obvious I've spent a lot of time with C++ and there's a combination of a few good ideas a lot of hard work and a bit of luck and I try to get away from it a few times but I get tracked in again partly because I'm most effective in this area and partly because what I do has much more impact if I do it in the context of C++ I I have four and a half million people that pick it up tomorrow if I get something right if I did it in another field I would have to start learning then I have to build it and then or see if anybody wants to use it one of the things that has kept me going for all of these years is one the good things that people do with it and the interesting things they do with it and also I get to see a lot of interesting stuff and talk to a lot of interesting people I mean if it has just been statements on paper on a screen I I don't think I could have kept going but I get to see the telescopes up on Mauna Kea and I actually went and see how Ford built cars and I got to JPL and see how they do the the Mars rovers there's so much cool stuff going on and most of the cool stuff is done by pretty nice people and sometimes in very nice places cambridge sophia antipolis silicon valley yeah it's there there's more to it than just code but code is central on top of the code are the people in very nice places well I think I speak for millions of people we aren't in saying thank you for creating this language that so many systems are built on top of them that make a better world so thank you and thank you for talking today yeah thanks and we'll make it even better good you |
Sean Carroll: Quantum Mechanics and the Many-Worlds Interpretation | Lex Fridman Podcast #47 | the following is a conversation with Sean Carroll part 2 the second time we've spoken on the podcast you can get the link to the first time in the description this time we focus on quantum mechanics and the many-worlds interpretation that he details elegantly in his new book titled something deeply hidden I own and enjoy both the ebook and audiobook versions of it listening to Sean read about entanglement complementarity and the emergence of space-time reminds me of bob ross teaching the world how to paint and his own television show if you don't know who Bob Ross is you're truly missing out look him up he'll make you fall in love with painting Sean Carroll is the Bob Ross of theoretical physics he's the author of several popular books a host of a great podcast called mindscape and is a theoretical physicist at Caltech and the Santa Fe Institute specializing in quantum mechanics arrow of time cosmology and gravitation this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars of iTunes supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma N and now here's my conversation with Sean Carroll Isaac Newton developed what we now call classical mechanics that you describe very nicely in your new book because you do with a lot of basic concepts in physics so was classical mechanics I can throw a rock and can predict the trajectory of that rocks flight but if we could put ourselves back into Newton's time his theories work to predict things but as I understand he himself thought that they were their interpretations of those predictions were absurd perhaps he just said it for religious reasons and so on but in particular sort of a world of interaction without contact so action at a distance it didn't make sense to them in a sort of a human interpretation level does it make sense to you that things can affect other things at a distance it does but you know that so that was one of Newton's worries you're actually right in a slightly different way about the religious worries he he was smart enough this is off the topic with still fascinating Newton almost invented chaos theory as soon as he invented classical mechanics he realized that in the solar system so he was able to explain how planets move around the Sun but typically you would describe the orbit of the earth ignoring the effects of Jupiter and Saturn and so forth just doing the earth and the Sun he he kind of knew even though he couldn't do the math that if you included the effects of Jupiter and Saturn the other planets the solar system would be unstable like the orbits of the planets would get out of whack so he thought that God would intervene occasionally to sort of move the planets back into orbit which is how you could only way you could explain how they were there presumably forever but the worries about classical mechanics were a little bit different they worried about gravity in particularly wasn't it worried about classical mechanics worried about gravity how in the world does the earth know that there's something called the Sun 93 million miles away that is exerting gravitational force on it and he said he literally said you know I leave that for future generations to think about because I don't know what the answer is and in fact the people under emphasize this but future generations figured it out Pierre Simone Laplace in circa 1800 showed that you could rewrite Newtonian gravity as a field theory so instead of just talking about the force due to gravity you can talk about the gravitational field or the gravitational potential field and then there's no action at a distance it's exactly the same theory empirically it makes exactly the same predictions but what's happening is instead of the Sun just reaching out across the void there is a gravitational field in between the Sun and the earth that obeys an equation Laplace's equation cleverly enough and that tells us exactly what the field does so even in Newtonian gravity you don't need action at a distance now what many people say is that Einstein solved this problem because he invented general relativity and general relativity there's certainly a field in between the Earth and the Sun but also there's the speed of light as a limit in Laplace's theory which was exactly Newton's theory just in a different mathematical language there could still be instantaneous action across the universe whereas in general relativity if you shake something here its gravitational impulse radiates out at the speed of light and we call that a gravitational wave and we can detect those so but I I really it rubs me the wrong way to think that we should presume the answer should look one way or the other like if it turned out that there was action at a distance in physics and that was the best way to describe things that I would do it that way it's actually a very deep question because when we don't know what the right laws of physics are when we're guessing at them when we're hypothesizing at what they might be we are often guided by our intuitions about what they should be I mean Einstein famously was very guided by his intuitions and he did not like the idea of action at a distance we don't know whether he was right or not it depends on your interpretation of quantum mechanics and it depends on even how you talk about quantum mechanics within any one interpretation if you see every forces of field or any other interpretation of action at a distance he's just stepping back to sort of caveman thinking like do you really can you really sort of understand what it means for a force to be a field as everywhere so if you look at gravity like what do you think about I think so it's just something that you've been can and by society to think that to map the fact that science is extremely well predictive of something to believing that you actually understand it like you can intuitively under the how as the degree that human beings can understand anything that you actually understand it are you just trusting the beauty and the power of the predictive power science that depends on what you mean by this idea of truly understandings right right you know I mean can I Lily understand four months Last Theorem you know it's easy to state it but do I really appreciate what it means for incredibly large numbers right yeah I think yes I think I do understand it but like if you want to just push people on well you put your intuition doesn't go to the places where Andrew Wiles needed to go to prove Fermat's Last Theorem and I can say fine by something I understand the theorem and likewise I think that I do have a pretty good intuitive understanding of fields pervading space time whether it's the gravitational field or the electromagnetic field or whatever the Higgs field of course one's intuition gets worse and worse as you get trickier in the quantum field theory and all sorts of new phenomena that come up in quantum field theory so our intuitions aren't perfect but I think it's also okay to say that our intuitions get trained right like you know I have different intuitions now that I had when I was a baby that's okay that's not an intuition is not necessarily intrinsic to who we are we can we can train it a little bit so that's where I'm gonna bring in norm Chomsky for a second who thinks that our cognitive abilities are sort of evolved through time and so they're they're biologically constrained and so there's a clear limit as he puts it to our cognitive abilities and it's a very harsh limit but you actually kind of said something interesting and nature versus nurture thing here is we can train our intuitions to sort of build up the cognitive muscles to be able to understand some of these tricky casas so do you think there's limits to our understanding that's deeply rooted hard-coded into our biology that we can't overcome there could be limits to things like our ability to visualize okay but when someone like Ed Witten proves a theorem about you know hundred dimensional mathematical spaces he's not visualizing it he's doing the math that doesn't stop him from understanding the result I think and I would love to understand this better but my rough feeling which is not very educated is that you know there's some threshold that one crosses in abstraction when one becomes kind of like a Turing machine right one has the ability to contain in one's brain logical formal symbolic structures and manipulate them and that's a leap that we can make as human beings that that dogs and cats haven't made and once you get there I'm not sure there are any limits to our ability to understand the scientific world at all maybe there are there's certainly a ability limits on our ability to calculate things right you know people are not very good at taking cube roots of million digit numbers in their head but that's not an element of understanding it's certainly not a little bit in principle so of course there's a human you would say that doesn't feel to be limits to our understanding but sort of hey have you thought that the universe is actually a lot simpler than it appears to us and we just will never be able to like it's outside of our okay so us our cognitive abilities combined with our mathematical prowess and whatever kind of experimental simulation devices we can put together is there limits to that is is it possible there's limits to that well of course it's possible there is or is there any good reason to think that we're anywhere close to the limits is a harder question look imagine asking this question 500 years ago to the world's greatest thinkers right like are we approaching the limits of our ability to understand the natural world and by definition there are questions about the natural world that are most interesting to us that are the ones we but yet understand right so there's always we're always faced with these puzzles we don't yet know and I don't know what they would have said five hundred years ago but they didn't even know about classical mechanics much less quantum mechanics so we know that they were nowhere close to how well they could do right they could do normally better than they were doing at the time I see no reason why the same thing isn't true for us today so of all the worries that keep me awake at night the human minds inability to rationally comprehend the world is low on the list well put so one interesting philosophical point and quantum mechanics bring up is the that you talk about the distinction between the world as it is and the world as we observe it so staying at the human level for a second how big is the gap between what our perception system allows us to see and the world as it is outside our minds I sort of so if not at the quantum mechanical level yeah as just are these particular tools we have which is a few senses and cognitive abilities to process those senses well that last phrase having the cognitive abilities to process them carries a lot right I mean there is our sort of intuitive understanding of the world you don't need to teach people about gravity for them to know that apples fall from trees right that's something that we figure out pretty quickly object permanence things like that the three dimensionality of space even if we don't have the mathematical language to say that we kind of know that it's true on the other hand no one opens their eyes and sees atoms all right or molecules for ourselves for that matter forget about quantum mechanics so but we got there we got to understanding that there are atoms and cells using the combination of our senses and our cognitive capacities so adding the ability of our cognitive capacities to our senses is adding an enormous amount and I don't think there's a hard and fast boundary you know if you believe in cells if you believe that we understand those then there's no reason you believe we can't believe in quantum mechanics just as well what to you is the most beautiful idea in physics conservation of momentum can you elaborate yeah if you were Aristotle when Aristotle wrote his book on physics he made the following very obvious point we're on video here right so people can see this so if I push the bottle let me cover this bottle so we do not have a mess but okay so I push the bottle it moves and if I stop pushing itself moving yes and this is this kind of thing is repeated a large number of times all over the place if you don't keep pushing things they stop moving this is a indisputably true fact about our everyday environment okay and for Aristotle this blew up into a whole picture of the world in which things had natures and teleology x' and they had places they wanted to be and when you were pushing them you were moving them away from where they wanted to be and they would return and stuff like that and it took a thousand years or fifteen hundred years for people to say actually if it weren't for things like dissipation and air resistance and friction and so forth the natural thing is for things to move forever in a straight line there's a constant velocity right conservation of momentum and that is the reason why I think that's the most beautiful idea in physics is because it shifts us from a view of nature's and teleology to a view of patterns in the world so when you were Aristotle you needed to talk a vocabulary of why is this happening what's the purpose of it what's the cause etc because you know it's nature does or does not want to do that whereas once you believe in conservation of momentum things just happen they they just follow the pattern you give me you have Laplace's deamon ultimately right you give me the state of the world today I can predict what's gonna do in the future I can predict where it was in the past it's impersonal and it's also instantaneous it's not directed toward any future goals it's just doing what it does given the current state of the universe that I think even more than either classical mechanics or quantum mechanics and that is the profound deep insight that gets modern science off the ground you don't need nature's and purposes and goals you just need some patterns so it's the first moment in our understanding of the way the universe works where you branch from the intuitive physical space to kind of the space of ideas and also the other point you said which is conveniently most of the interesting ideas are acting in the moment you don't need to know the history of time or the future then of course this took a long time to get there right I mean the conservation momentum itself took hundreds of years it's weird just like someone would say something interesting and then the next interesting thing would be said like 150 or 200 years later right they weren't even talking to each other there was reading each other's books and probably the first person to directly say that in outer space in the vacuum projectile would move at a constant velocity was Avicenna even Sina and the Persian Golden Age circa 1000 and he didn't like the idea he used that just like furniture used Schrodinger's cat to studies freely you don't believe that right even Sina was saying surely you don't believe there really is a vacuum because if there was a really vacuum things could keep moving forever right but still he got right the idea that there was this conservation of something impetus or mile he would call it and that's 500 years 600 600 years before classical mechanics and Isaac Newton so you know Galileo played a big role in this but he didn't exactly get it right and so it just takes a long time for this to sink in because it is so against our everyday experience do you think it was a big leap a brave or a difficult leap of sort of math and science to be able to say that momentum was conserved I do you know I think it's a example of human reason in action you know even Aristotle knew that his theory had issues because you could fire an arrow and it would go a long way before it stopped so if his theory was things just automatically stopped what's going on and he had this elaborate story I don't know if you've heard the story but the arrow would push the air in front of it away and the molecules of air would run around to the back of the arrow and push it again and anyone reading this is going like really that's that's what you thought but it was that kind of thought experiment that we got people to say like actually know if it weren't for the air molecules at all there I would just go on by itself and it's always this give-and-take between thought and experience back and forth right theory and experiment we would say today another big question that I think comes up certainly with quantum mechanics is what's the difference between math and physics to you to me you know very very roughly math is about the logical structure of all possible worlds and physics is about our actual world and it just feels like our actual world is a gray area when you start talking about interpretations of quantum mechanics or no I'm certainly using the word world in the broadest sense all of reality so I think the reality is specific I don't think that there's every possible thing going on in reality I think there are rules whether it's the Schrodinger equation or whatever so i think i think that there's a sensible notion of the set of all possible worlds and we live in one of them the world that we're talking about might be a multiverse might be many worlds of quantum mechanics might be much bigger than the world of our everyday experience but it's still one physically contiguous world in some sense but so if you look at the overlap of math and physics it feels like when physics tries to reach for understanding of our world it uses the tools of math to sort of reach beyond the limit of our current understanding what do you make of that process of sort of using math to so you start maybe with intuition or you might start with the math and then build up an intuition or but this kind of reaching into the darkness into the mystery of the world would math well I think I would put it a little bit differently I think we have theories theories of the physical world which we then extrapolate and ask you know what do we conclude if we take these seriously well beyond where we've actually tested them it is separately true that math is really really useful when we construct physical theories and you know famously Eugene Wigner asked about the unreasonable success of method Mattox and physics I think that's a little bit wrong because anything that could happen any other theory of physics that wasn't the real world with some other world you could always describe it mathematically it's just it might be a mess the surprising thing is not that math works but that the math is so simple and easy that you can write it down on a t-shirt right I mean that's what is amazing that's an enormous compression of information that seems to be valid in the real world so that's an interesting fact about our world which maybe we could hope to explain or just take as a brute fact I don't know but once you have that you know it there's this the indelible relationship between math and physics but but philosophically I do want to separate them well we what we extrapolate we don't extrapolate math because there's a whole bunch of wrong math you know that doesn't apply to our world right we extrapolate the physical theory that we best think explains our world again an unanswerable question why do you think our world is so easily compressible into beautiful equations yeah I mean like I just hinted at I don't know if there's an answer to that question there could be what would an answer look like well an answer could look like if you showed that there was something about our world that maximized something you know the the mean of the simplicity and the powerfulness of the laws of physics or you know with maybe we're just generic maybe in the set of all possible worlds this is what the world would look like right like I were I don't really know I tend to think not I tend to think that there is something specific and rock-bottom about the facts of our world that don't have further explanation like the fact of the world exists at all and furthermore the specific laws of physics that we have I think in some sense we're just gonna at some level we're gonna say and that's how it is and you know we can't explain anything more we I don't know how if we're anywhere close to that right now but that seems plausible to me and speaking of rock bottom one of the things so your book kind of reminded me a reveal to me is that what's fundamental and what's emergent it just feels like I don't even know anymore what's fundamental in in physics if there's anything it feels like everything especially with quantum mechanics is revealing to us is that most interesting things that I would as a he as a limited human would think are fundamental or it can actually be explained as emergent from the the more deeper laws I mean we don't know of course is you had to get that on the table like we don't know what is fundamental we do know we do have reason to say that certain things are more fundamental than others right atoms and molecules are more fundamental than cells and organs quantum fields are more fundamental than atoms and molecules we don't know if that ever bottoms out I I do think that there's sensible ways to think about this the if you if you describe something like this table as a table it has a height and a width and it's made of a certain material and has a certain solidity and weight and so forth that's the very useful description as far as it goes there's a whole nother description at this table in terms of a whole collection of atoms strung together in certain ways the language of the atoms is more comprehensive than the language of the table you could break apart to the table smash it to pieces still talk about it as atoms but you could no longer talk about it as a table right so I think of this comprehensiveness the domain of validity of a theory gets broader and broader as the theory gets more and more fundamental so what do you think Newton would say maybe write in a book review if you read your latest book on quantum mechanics something deeply hidden would take a long time for him to think that any of this was making any sense you catch him up pretty quick in the beginning yeah give him a shout out that's right I mean he used the man I'm happy to say that Newton was the greatest scientists who ever lived I mean he met in calculus in his spare time which would have made it the greatest mathematician just all by himself right I'll buy that one thing but of course you know it's funny because Newton was in some sense still a pre-modern thinker rocky Kolb who is a cosmologists at at the University of Chicago said that you know Galileo even though he can be for Newton was a more modern thinker than than Newton was like if he got Galileo and brought him to the present day you take him six months to catch up and then he be in your office telling you while your most recent paper was wrong whereas Newton just thought in this kind of more mystical way you know he wrote a lot more about the Bible and alchemy didn't he ever did about physics and but he was also more brilliant than anybody else and and way more mathematically astute than Galileo so I really don't know you know he might have he might just yeah say like give me the textbooks leave me alone for a few months and then be caught up but he but he or he might have had mental blocks against against seeing the world in this way I really don't know or perhaps find an interesting mystical interpretation of quantum mechanics very possible yeah is there any other scientists or philosophers through history that you would like to know their opinion of your book that's against a good question um I mean Einstein is the obvious one right y'all and he was not that long ago but speculate at the end of my book about what his opinion would be I am curious as to you know what about older philosophers like Hume or Conte right like what would they have thought or Aristotle you know what would they thought about modern physics because they do in philosophy your predilections end up paint playing a much bigger role in your ultimate conclusions cuz you're not as tied down by what the data is in physics you know physics is lucky because we can't stray too far off the reservation as long as we're trying to explain the world that we actually see in our telescopes and microscopes but it's it's just not fair to play that game because the people were thinking about didn't know a whole bunch of things that we know right like we lived through a lot that they didn't live through so by the time we got them caught up they'd be different people so let me ask a bunch of basic questions I think it would be interesting useful for people are not familiar but even for people who are extremely well familiar let's start with what is quantum mechanics quantum mechanics is the paradigm of physics that came into being in the early part of the 20th century that replaced classical mechanics and it replaced classical mechanics in a weird way that we're still coming to terms with so in classical mechanics you have an object it as a location has a velocity and if you know the location and velocity of everything in the world you can say what everything's gonna do quantum mechanics has an aspect of it that is kind of on the same lines there's something called a quantum state or the wave function and there's an equation governing what the quantum state does so it's very much like classical mechanics the wave function is different it's sort of a wave it's a vector in a huge dimensional vector space rather than a position in a velocity but okay that's a detail and the equation is the Schrodinger equation not Newton's laws but okay again a detail where quantum mechanics really becomes weird and different is that there's a whole nother set of rules in our textbook formulation of quantum mechanics in addition to saying that there's a quantum state and it evolves in time and all these new rules have to do with what happens when you look at the system when you observe it when you measure it in classical mechanics there were no rules about observing you just look at it and you see what's going on that that was that right in quantum mechanics the way we teach it there's something profoundly fundamental about the act of measurement or observation and the system dramatically changes its state even though it has a wave function like the electron in an atom is not orbiting in a circle as sort of spread out in a cloud when you look at it you don't see that cloud when you look at it it looks like a particle with a location so it dramatically changes its state right away and the effects of that change can be instantly seen and what the electron does next so that's the again we need to be careful because we don't agree on what quantum mechanics says that's what I need to say like in the textbook view etc right but in the textbook view quantum mechanics unlike any other theory of physics places uh gives a fundamental role to the act of measurement so maybe even more basic what is an atom and what is an electron sure this all came together you know in a few years around the turn of the last century right around the year 1900 Adams predated then of course the word Adam goes back to the ancient Greeks but it was the chemists in the 1800's that really first got experimental evidence for atoms they realized you know that there were two different types of tin oxide and in these two different types of tin oxide there was exactly twice as much oxygen in one type as the other and like why is that why is it all why is it never 1.5 times as much right and so Dalton said well it's because there are 10 atoms and oxygen atoms and one form of tin oxide is one atom of tin and one atom of oxygen and the other is one atom obtained and two atoms of oxygen and on the basis of this is you know speculation a theory right a hypothesis but then on the basis of that you make other predictions and the chemists became quickly convinced that atoms were real the physicists took a lot longer to catch on but eventually they did and I mean Boltzmann who believed in atoms was God he had a really tough time his whole life because he worked in Germany where atoms were not popular they were popular in England but not in Germany and there in general the idea of atoms is it's the most the smallest building block of the universe for for them that's the kind of how the Greek idea but the chemists in the 1800's jumped the gun a little bit so these days in atom is the smallest building block of a chemical element right hydrogen tin oxygen carbon whatever but we know that atoms can be broken up further than that and that's what physicists discovered in the early 1900's Rutherford especially and and his colleagues so the atom that we think about now the cartoon is that picture you you always seen of a little nucleus and then electrons orbiting it like a little solar system and we now know the nucleus is made of protons and neutrons so the weight of the atom the mass is almost all in its nucleus protons and neutrons or something like 1,800 times as heavy as electrons are electrons are much lighter but they're because they're lighter they give all the life to the atoms so when atoms get together combine chemically when electricity flows through a system it's all the electrons that are doing all the work and we're quantum mechanic steps in as you mentioned with position or velocity with classical mechanics and quantum mechanics is modeling the behavior of the electron I mean you can model the behavior of anything but the electron because that's where the fun is the electron was it was the biggest challenge right from the start yeah so what's a wavefunction you said it's an interesting detail yeah but in any interpretation what is the wave function in quantum mechanics well you know we had this idea from Rutherford that atoms look like little solar systems but people very quickly realize that can't possibly be right because if an electron is orbiting in a circle it will give off light all the light that we have in this room comes from electrons zooming up and down and wiggling and that's what electromagnetic waves are and you can calculate how long would it take for the electron just to spiral into the nucleus and the answer is 10 to the minus 11 seconds okay a hundred billions of a second so that's not right meanwhile people had realized that light which we understood from the 1800s was a wave had properties that were similar to that of particles right this is Einstein and plunk and stuff like that so if something that we agree was a wave had particle-like properties then maybe something we think is a particle the electron has wave-like properties right and so a bunch of people eventually came to the conclusion don't think about the electron as a little point particle orbiting in like a solar system think of it as a wave that is spread out they cleverly gave this the name the wave function which is the dopiest name in the world for one of the most profound things in the universe the there's literally you know a number at every point in space which is the value of the electrons wave function at that point and there's only there's only one wave function that yeah they eventually figured that out that took longer but when you have two electrons you do not have a wave function for electron one in a wave function for electron two you have one combined wave function for both of them and indeed as you say there's only one wave function for the entire universe at once and that's where this beautiful dance can you say what is entanglement it seems one of the most fundamental ideas of quantum again well let's temporarily buy into the textbook interpretation of quantum mechanics and what that says is that this wave function so it's very small outside the atom very big in the atom basically the wave function you take it and you square it you squared the number that gives you the probability of observing the system at that location so if you say that for two electrons there's only one wave function and that wave function gives you the probability of observing both electrons at once doing something okay so maybe the electron can be here or here here here and the other electron can also be there but we have a wave function setup where we don't know where either electron is going to be seen but we know they'll both be seen in the same place okay so we don't know exactly what we're gonna see for either electron but there's entanglement between the two of them there's a sort of conditional statement if we see one in one location then we know the other one's going to be doing a certain thing so that's a feature of quantum mechanics that is nowhere to be found in classical mechanics in classical mechanics there's no way I can say well I don't know where either one of these particles is but if I know if I find out where this one is then I know where the other one is that just never happens they're truly separate and in general it feels like if you think of a wave function like as a dance floor it seems like entanglement is strongest between things that are dancing together closest so there's a there's a closeness that's important well that's not that that's another step we have to be careful here should cause in principle if you if you're talking my the entanglement of two electrons for example they can be totally entangled or totally unentangled no matter where they are in the universe there's no relationship between the amount of entanglement and the distance between two electrons but we now know that you know the reality of our best way of understanding the world is through quantum fields not through particles so even the electron not just gravity and electromagnetism but even the electron and the quarks and so forth are really vibrations in quantum fields so even empty space is full of vibrating quantum fields and those quantum fields in empty space are entangled with each other in exactly the way you just said if they're nearby if you have like two vibrating quantum fields that are nearby them it'll be highly entangled if they're far away they will not be entangled so what do quantum fields in a vacuum look like empty space just so like empty space it's as empty as it can be but there's still a field it's just yeah it uh what is nothing just like right here or this location in space there's a gravitational field which I can detach by dropping something yeah I don't see it but there it is so we got a little bit of idea of entanglement now what is Hilbert space and Euclidean space yeah you know I think that people are very welcoming over their lives not knowing what Hilbert space is but if you if you what I dig in a little bit more into quantum mechanics it becomes necessary you know the English language was invented long before quantum mechanics or various forms of higher mathematics were invented so we use the word space to mean different things of course most of us think of space as this three dimensional world in which we live right I mean some of us just think of it as outer space okay but space around us it gives us the three-dimensional location of things and objects but mathematicians use any generic abstract collection of elements as a space okay a space of possibilities you know momentum space etc so Hilbert space is the space of all possible quantum wave functions either for the universe or for some specific system and it could be an infinite dimensional space or it could be just really really large dimensional but finite we don't know because we don't know the final theory of everything but this abstract hilbert space is really really really big and has no immediate connection to the three-dimensional space in which we live what what do dimensions in hilbert space mean you know it's just a way of mathematically representing how much information is contained in the state of the system how many numbers do you have to give me to specify what the thing is doing so in classical mechanics I give you the location of something by giving you three numbers right up down left likes XYZ coordinates but then I might want to give you its entire state physical state which means both its position and also its velocity the velocity also has three components so it's state lives in something called phase space which is six dimensional three dimensions of position three dimensions of velocity and then if it also has an orientation in space that's another three dimensions and so forth so as you describe more and more information about the system you have an abstract mathematical space that has more and more numbers that you need to give and each one of those numbers corresponds to a dimension in that space so in terms of that amount of information what is entropy this mystical word that's overused in math and physics but has a very specific meaning in this context sadly it has more than one very specific meeting this is this is reason why it is hard and roomy means different things even to different physicists but one way of thinking about it is a measure of how much we don't know about the state of a system right so if I have a bottle of water molecules and I know that okay there's a certain number of water molecules I could weigh it right and figure out I know the volume of it and I know the temperature and pressure and things like that I certainly don't know the exact position and velocity of every water molecule right so there's a certain amount of information I know certain amount that I don't know that is that is part of the complete state of the system and that's what the entropy characterizes how much unknown information there is the difference between what I do know about the system and its full exact microscopic state so when we try to describe a quantum mechanical system is infinite or finite but very large yeah we don't know that depends on the system you know it's easy to mathematically write down a system that would have a potentially infinite entropy an infinite dimensional hilbert space so let's let's go back a little bit we said that the hilbert space was the space in which quantum wave functions lived for different systems that will be different sizes they could be infinite or finite so that's the number of numbers the number of pieces information you could potentially give me about the system so the bigger hilbert spaces the bigger the entropy of that system could be depending on what I know about it if I don't know anything about it then you know as a huge entropy right but only up to the size of its hilbert space so we don't know in in the real physical world whether or not you know this region of space that contains that water bottle has potentially an infinite entropy or just a finite entropy we have we have different arguments on different sides so if it's infinite how do you think about infinity is this something you can your cognitive abilities are able to process or is it just a mathematical tool it's somewhere in between right I mean we can say things about it we can use mathematical tools to manipulate infinity very very accurately we can define what we mean you know for any number n there's a number bigger than it so there's no biggest number right so there's something called the total number of all numbers that's infinite but it is hard to wrap your brain around that and I think that gives people pause because we talk about infinity as if it's a number but it has plenty of properties that real numbers don't have you know if you multiply infinity by 2 you get infinity again right that's a little bit different than what we're used to okay but are you comfortable with the idea that in thinking of what the real world actually is that infinity could be part of that world are you comfortable that a world in some dimension and somehow comfortable with lots of things I mean you know I don't want my level of comfort to affect what I think about the world you know I'm pretty open-minded about what the world could be at the fundamental level yeah but infinity is a is a tricky one it's not almost a question of comfort it's a question of is it an overreach of our intuition sort of it could be a convenient almost like when you add a constant to an equation just because it'll help it just feels like it's useful to at least be able to imagine a concept not directly but in some kind of way that this feels like it's a description of the real world think of it this way there's only three numbers that are simple there's zero there's one and there's infinity a number like 318 it's just bizarre like that that you need a lot of bits to give me what that number is yeah but zero and one infinity like once you have 300 things you might as well have infinity things right otherwise yet to say how when to stop making the thing that's right so there's a sense in which infinity is a very natural number of things to exist that I was never comfortable with it because it's just such a kick but it was a too good to be true mmm because in math it just helps make things work out when things get very it's when things get very large close to infinity things seem to work out nicely it's kind of like because of my deepest passion it's probably psychology and I'm uncomfortable how in the average the the beauty of the very very the how much we vary is lost in that same kind of sense infinity seems like convenient way to erase the details but the thing about infinity is you it seems to pop up whether we like it or not right right like you're trying to be a computer scientist you ask yourself well how long will it take this program to run and you realize well for some of them the answer is infinitely long it's not because you tried to get there you wrote a five line computer program it doesn't halt so coming back to the textbook definition of quantum mechanics this idea that we I don't think we talked about can you this one of the most interesting philosophical points we talked at the human level but at the at the physics level that it that at least the textbook definition of quantum mechanics separates what is observed and what is real one how does that make you feel and and two what does it then mean to observe something and why is it different that what is real yeah you know I my personal feelings such as it is is that things like measurement and observers and stuff like that are not going to play a fundamental role in the ultimate laws of physics but my feeling that way is because so far that's where all the evidence has been pointing I could be wrong and there's certainly a sense in which it would be infinitely cool if somehow observation or mental cogitation did play a fundamental role in the in the nature of reality but I don't think so I can I don't see any evidence for it so I'm not spending a lot of time worrying about that possibility so what do you do about the fact that in the textbook interpretation of quantum mechanics this idea of measurement or looking at things seems to play an important role well you you come up with better interpretations of quantum mechanics and there are several alternatives my favorite is the many-worlds interpretation which says two things number one you the observer are just a quantum system like anything else there's nothing special about you don't get so proud of yourself you know you're just a bunch of atoms you have a wavefunction you obey the Schrodinger equation like everything else and number two when you think you're measuring something or observing something what's really happening is you're becoming entangled with that thing so when you think there's a wavefunction for the electron it's all spread out but you look at it and you only see it in one location what's really happening is that there's still the wave functions the electron in all those locations but now it's entangled with the wave function of you in the following way there's part of the wave function that says the electron was here and you think you saw it there the electron was there and you think you saw it there the electron was over there and you think you saw it there etc so and all of those different parts of the wave function once they come into being no longer talk to each other they no longer interact or influence each other it says if they are separate worlds so this was the invention of Hugh Everett the third who was a graduate student at Princeton in the 1950s and he said basically look you don't need all these extra rules about looking at things just listen to what the Schrodinger equation is telling you it's telling you that you have a wavefunction that you become entangled and that the different versions of you no longer talk to each other so just accept it it's just he did therapy more than anything else you know he said like it's okay you know you don't need all these extra rules all you need to do is believe the Schrodinger equation the cost is there's a whole bunch of extra worlds out there so how the worlds being created whether there's an observer or not the worlds are created anytime a quantum system that's in a superposition becomes entangled with the outside world what's the outside world it depends let's back out yeah whatever it really says what his theory is is there's a wave function of the universe and a base the Schrodinger equation all the time that's it that's the full theory right there okay the question all of the work is how in the world do you map that theory on to reality on to what we observe right so part of it is carving up the wavefunction into these separate worlds saying look look it describes a whole bunch of things that don't interact with each other let's call them separate worlds another part is distinguishing between systems and their environments and the environment is basically all the degrees of freedom all the things going on in the world that you don't keep track of so again in the bottle of water I might keep track of the total amount of water and the volume I don't keep track of the individual positions and velocities I don't keep track of all the photons or the air molecules in this room so that's the outside world the outside world is all the parts of the universe that you're not keeping track of when you're asking about the behavior of some subsystem of it so how many worlds are there you want to know that one either there could be an infinite number there could be only a finite number but it's a big number one way or the other it's a very very big number one of you talked somebody asked well if it's a if it's finite so actually I'm not sure exactly the logic you used to derive this but is there you know going to be the you know overlap a duplicate world that you return to so you've mentioned and I'd love if you can elaborate on sort of idea that it's possible that there's some kind of equilibrium that these splitting worlds arrive at and then maybe over time maybe somehow connected to entropy you get a large number of worlds they're very similar to each other yeah so this question of whether or not Hilbert space is finite or infinite dimensional is actually secretly connected to gravity and cosmology this is a the part that we're still struggling to understand right now but we discovered back in 1998 that our universe is accelerating and what that means if it continues which we think it probably will but we're not sure but if it does that means there's a horizon around us there there's because the universe not only expanding but expanding faster and faster things can get so far away from us that from our perspective it looks like they're moving away faster than the speed of light you'll never see them again so there's literally a horizon around us and that horizon approaches some fixed distance away from us and you can then argue that within that horizon there's only a finite number of things that can possibly happen the finite dimensional hilbert space in fact we even have a guess for what the dimensionality is it's 10 to the power of 10 to the power of 122 that's a very large number yes just to compare the age of the universe is something like 10 to the 14 seconds 10 to the 17 or 18 seconds maybe the number of particles in the universe is 10 to the 88th but the number of dimensions of Hilbert space is 10 to the 10 to the 120 - so that's just crazy thing if that story is right that in our observable horizon there's only a finite dimensional hilbert space then this idea of branching of the wavefunction the universe into multiple distinct separate branches has to reach a limit at once you read branched that many times you've run out of room in hilbert space and roughly speaking that corresponds to the universe just expanding and emptying out and cooling off and and entering a phase where it's just empty space literally forever what's the difference between splitting and copying do you think like in terms of a lot of this is an interpretation that's that helps us sort of model the world so perhaps shouldn't be thought of as like you know philosophically or metaphysically but in even at the physics level do you see a difference between two generating new copies of the world or splitting I think it's better to think of in quantum mechanics in many worlds the universe splits rather than new copies because people otherwise worry about things like energy conservation and no one who understands quantum mechanics worries about energy conservation because the equation is perfectly clear but if all you know is that someone told you the universe duplicates then you have a reasonable worry about where all the energy for that came from so a pre-existing universe splitting into two skinnier universes is a better way of thinking about it and mathematically it's just like you know if you draw an x and y axis and you draw a vector of length 1 45-degree angle you you know that you can write that vector of length 1 as the sum of two vectors pointing along x and y of length 1 over the square root of 2 ok so I write one arrow as the sum of two arrows but there's a conservation of air Onis right like if now two arrows but the length is the same I just I'm describing it in a different way and that's exactly what happens when the universe branches the the wave function of the universe is a big old vector so to somebody who brings up a question of saying doesn't this violate the conservation of energy can you give further elaboration right so let's just be SuperDuper perfectly clear yeah there's zero question about whether or not many-worlds violates conservation of energy yes it does not great and I say this definitively because there are other questions I think there's answers too but they're legitimate questions right about you know where does probability come from and things like that this conservation of energy question we know the answer to it and the answer to it is that energy is conserved all of the effort goes into how best to translate what the equation unambiguously says into think plain English right so this idea that there's a universe that has that that the universe comes equipped with a thickness and it sort of divides up into thinner pieces but the total amount of universe is is conserved over time is a reasonably good way of putting English words to the underlying mathematics so one of my favorite things about many worlds is I mean I love that there's something controversial in science and for some reason it makes people actually not like upset but just get excited why do you think it is a controversial idea so there's there's a lot of it's actually one of the cleanest ways to think about quantum mechanics yeah so why do you think there's a discomfort a little bit among certain people well I draw the distinction of my book between two different kinds of simplicity in a physical theory there's simplicity in the theory itself right how we describe what's going on according to the theory by its own rights but then you know a theory is just some sort of abstract mathematical formalism you have to map it onto the world somehow right and sometimes like for Newtonian physics it's pretty obvious like okay here is a bottle and as a center of mass and things like that sometimes it's a little bit harder with general relativity curvature of space-time is a little bit harder to grasp quantum mechanics is very hard to map what you're the language you're talking into wave functions and things like that on to reality and many worlds is the version of quantum mechanics where it is hardest to map on the underlying formalism to reality so that's where the lack of simplicity comes in not in the theory but in how we use the theory to map on to reality and in fact all of the work in sort of elaborating many-worlds quantum mechanics is in the this effort to map it on to the world that we see so it's perfectly legitimate to be bugged by that right to say like well no that's just too far away from my experience I I am therefore intrinsically skeptical of it of course you should give up on that skepticism if there are no alternatives and this theory always keeps working then eventually you should overcome your skepticism but right now there are alternatives and that are that you know people work to make alternatives that are by their nature closer to what we observe directly can you describe the alternatives I don't think we touched on it so the the Copenhagen interpretation and the many-worlds maybe there's a difference between the effort I've already in many worlds and many worlds it is now like has the idea sort of developed and so on and just in general what is the space of promising contenders we have democratic debates now there's a bunch of candidate well family of candidates on stage what are the quantum-mechanical candidates on stage for the debate so if you had a debate between quantum-mechanical contenders there would be no problem getting 12 people up there on stage but there would still be only three frontrunners and right now the frontrunners would be Evert hidden variable theories are another one so the hidden variable theories say that the wavefunction is real but there's something in addition to the wave function the wave function is not everything is part of reality but it's not everything what else is there we're not for but in the simplest version of the theory there are literally particles so many world says that quantum systems are sometimes are wave-like in some ways and particle-like in another because they really really are waves but under certain observational circumstances they look like particles whereas invariable says there they look like waves and particles because there are both waves and particles involved in the dynamics and that's easy to do if your particles are just nonrelativistic Newtonian particles moving around they get pushed around by the wave function roughly it becomes much harder when you take quantum field theory or quantum gravity into account the other big contender are spontaneous collapse theories so in the conventional textbook interpretation we say when you look at a quantum system its wavefunction collapses and you see it in one location a spontaneous collapse theory says that every particle has a chance per second of having its wavefunction spontaneously collapse the chance is very small for a typical particle it will take hundreds of millions of years before it happens even once but in a table or some macroscopic object there are way more than a hundred million particles and they're all entangled with each other so when one of them clacks it collapses it brings everything else along with it there's a slight variation of this that's a spontaneous collapse theory there are also induced collapse theories like Roger Penrose thinks that when the gravitational difference between two parts of the wave function becomes too large the wavefunction collapses automatically so those are basically in my mind the three big alternatives many worlds which is just there's a wave function and always a basis reading your equation hidden variables there's a wave function that always the basis Schrodinger equation but there are also new variables or collapse theories which the wave function sometimes obeys the Schrodinger equation and sometimes it collapses so you can see that the alternatives are more complicated in their formalism than many-worlds is but they are closer to our experience so just this moment of collapse do you think of it as so is a wave function fundamentally sort of a probabilistic description of the world and its collapse sort of reducing that part of the world into something deterministic or again you can now describe the position in the velocity in this simple classical model well there is a hard thing about collapse there is a fourth category is a 4th contender there's a mayor Pete of quantum mechanical interpretations which are called epistemic interpretations and what they say is all the wavefunction is is a way of making predictions for experimental outcomes it's not mapping on to an element of reality in any real sense and in fact two different people might have two different wave functions for the same physical system because they know different things about it right the wave function is really just a prediction mechanism and then the problem with those epistemic interpretations is if you say okay but it's predicting about what like what is the thing that is being predicted and I say no no that's not what we're here for we're just here to tell you what the observational outcomes are gonna be but the other the other interpretation is kind of think that the wavefunction is real yes that's right so that's an antic interpretation of the wavefunction ontology being the study of what is real what exists as opposed to an epistemic interpretation of the wavefunction epistemology being the study what we know now actually just love to see that debate on stage there was a version of it on stage at the world science festival a few years ago that you can look up online I need you yep that's all you do okay awesome I'll link it and watch it anyone I won there was no vote those there's Brian Greene was the moderator and David Albert stood up for spontaneous collapse and Shelley Goldstein was there for hidden variables and Ruettiger shock was there for epistemic approaches why do you I think you mentioned it but just why do you find many worlds so compelling well there's two reasons actually one is like I said it is the simplest right it's like the most bare-bones austere pure version of quantum mechanics and I am someone who is very willing to put a lot of work into mapping the formalism onto reality I'm less willing to complicate the formalism itself but the other big reason is that there's something called modern physics with quantum fields and quantum gravity and holography and space-time doing things like that and when you take any of the other versions of quantum theory they bring along classical baggage all of the other versions of quantum mechanics prejudice or privilege some version of classical reality like locations in space okay and I think that that's a barrier to doing better at understanding the theory of everything and understanding quantum gravity and the emergence of space-time whenever if you change your theory from you know here's a harmonic oscillator oh there's a spin here's an electromagnetic field in hidden variable theories or dynamical collapse theories you have to start from scratch what are the hidden variables for this theory or how does he collapse or whatever whereas many-worlds is plug-and-play you tell me the theory and I can give you as many worlds version so when we have a situation like we have with gravity and space-time where the classical description seems to break down in a dramatic way then I think you should start from the most quantum theory that you have which is really many worlds so start with the quantum theory and try to build up a model of space-time the emergence of space-time that's okay so I thought space-time was fundamental yeah I know so this sort of dream that Einstein had that everybody had and everybody has of you know the theory of everything so how do we build up from many worlds from quantum mechanics a model of space-time model of gravity well yeah I mean let me first mention very quickly why we think it's necessary you know we've had gravity in the form that Einstein bequeathed it to us for over a hundred years now like 1915 or 1916 he put general relativity in the final form so gravity is the curvature of space-time and there's a field that pervades all the universe that tells us how curved space-time is and that's a fundamentally classical that's totally classical right exactly but we also have a formalism an algorithm for taking a classical theory and quantizing it this is how we get quantum electrodynamics for example and it could be tricky I mean you think your quantizing something so that means taking a classical theory and promoting it to a quantum mechanical theory but you can run into problems so they ran into problems and you did that with electromagnetism namely that certain quantities were infinity and you don't like infinity right so Fineman and tominaga and Schwinger won the nobel prize for teaching us how to deal with the infinities and then Ken Wilson won another Nobel Prize for saying you shouldn't have been worried about those infinities after all but still that was the it's always the thought that that's how you will make a good quantum theory you'll start with the classical theory and quantize it so if we have a classical theory general relativity we can quantize it or we can try to but we run into even bigger problems with gravity than we ran into with electromagnetism and so far those problems are we've not been able to get a successful theory of gravity quantum gravity by starting with classical general relativity and quantum it and there's evidence that there's a good reason why this is true that the whatever the quantum theory of gravity is it's not a field theory it's something that has weird non-local features built into it somehow that we don't understand and we get this idea from black holes and Hawking radiation and information conservation and a whole bunch of other ideas I talked about in the book so if that's true if the fundamental theory isn't even local in the sense that an ordinary quantum field theory would be then we just don't know where to start in terms of getting a classical precursor and quantizing so the only sensible thing is at least the next obvious sensible thing to me would be to say okay let's just start intrinsically quantum and work backwards see if we can find a classical limit so the idea of locality the the fact that locality is not fundamental to the nature of our existence sort of you know I guess in that sense modeling everything's the field makes sense to me stuff that's close by interact stuff that's far away doesn't so what's what's locality and why is it not fundamental and how is that even possible yeah I mean locality is the answer to the question that Isaac Newton was worried about back in the beginning of our conversation right I mean how can the earth know what the gravitational field of the Sun is when the answer has spelled out by Laplace and Einstein and others is that there's a field in between and the way a field works is that what's happening to the field at this point in space only depends directly on what's happening at points right next to it but what's happening at those points depends on what's happening right next to those right is you can build up an influence across space through only local interactions that's what locality means what happens here is only affected by what's happening right next to it that's locality the idea of locality is built into every field theory including general relativity as a classical theory it seems to break down when we talk about black holes and you know Hawking taught us in the 1970s the black holes radiate they give off they'll eventually evaporate away they're not completely black once we take quantum mechanics into account and we think we don't know for sure but most of us think that if you make a black hole out of certain stuff then like Laplace's Demon taught us you should be able to predict what that black hole will turn into if it's just obeying the Schrodinger equation and if that's true there are good arguments that can't happen while preserving locality at the same time it's just that their information seems to be spread out non locally in interesting ways and people should you talk about holography with the Leonard Susskind on your - a podcast yes I have a podcast I didn't even mention that I'm terrible no I'm gonna I'm gonna ask you questions about that too and I've been not shutting up about it's my favorite science podcast so or not it's a famous science podcast it's like it's a scientist doing absolutely yes yeah anyway yeah so holography is this idea when you have a black hole and black hole is a region of space inside of which gravity is so strong that you can't escape and there's this weird feature of black holes that again is a totally a thought experiment feature cuz we haven't gone and probed any yet but there seems to be one way of thinking about what happens inside a black hole as seen by an observer who's falling in which is actually pretty normal like everything looks pretty normal until you get the singularity and you die but from the point of the view of the outside observer it seems like all the information that that fell in is actually smeared over the horizon in a non-local way and that's puzzling and that's a lot so holography because that's a two-dimensional surface that is encapsulating the whole three-dimensional thing inside right still trying to deal with that still trying to figure out how to get there but it's an indication that we need to think a little more subtly when we quantize gravity so because you can describe everything that's going on in the in three-dimensional space by looking at the two-dimensional projection of it that means that locality doesn't it's not necessary well it means it's somehow it's only a good approximation it's not really what's going on how we're supposed to feel about that supposed to be liberated you know space is just a good approximation and this was always gonna be true once you started quantizing gravity so we're just beginning now to face up to the dramatic implications of quantizing gravity is there other weird stuff that happens to quantum mechanics in black hole I don't think that anything weird happen with quantum mechanics thinking weird things happen with space-time I mean that's what it is like quantum mechanics is still just quantum mechanics but our ordinary notions of space-time don't really quite work and there's a principle that goes hand in hand with holography called complementarity which says that there's no one unique way to describe what's going on inside a black hole different observers will have different descriptions both of which are accurate but sound completely incompatible with each other so depends on how you look at it you know the word complementarity in this context is borrowed from Niels Bohr who points out you can measure the position or you can measure the momentum you can't measure both at the same time in quantum mechanics so a couple questions on many worlds how does many worlds help us understand our particular branch of reality so ok that's fine and good that is everything is splitting we're just traveling down a single branch of it so how does it help us understand our little unique branch yeah I mean that's a great question but that's the point is that we didn't invent many worlds cuz you thought it was cool to have a whole bunch of worlds right we invented it because we were trying to account for what we observe here in our world and what we observe here in our world are wave functions collapsing ok we do have a position as a situation where the electron seems to be spread out but then when we look at it we don't see it spread out we see it located somewhere so what's going on that's the measurement problem of quantum mechanics that's what we have to face up to so many worlds is just a proposed solution to that problem and the answer is nothing special is happening it's still just the Schrodinger equation but you have a wave function - and that's a different answer than would be given in hidden variables or dynamical collapse theories or whatever so the entire point of many world's is to explain what we observe but it tries to explain what we already have observed right it's not trying to be different from what we've observed because that would be something other than quantum mechanics but you know the idea that there's worlds that we didn't observe they keep branching off it's kind of it is uh you know it's stimulating to the imagination so is it possible to hop from you mentioned the branches are independent yes is it possible to hop from one to the other no it's so physical limit then the theory says it's impossible there's already a copy of you in the other world don't worry yes leave them alone no but there's a there's a fear of missing out form oh yes that I feel like immediately start to wander if that other copy is having more or less fun well the downside in many worlds is that you're missing out on an enormous and that's always what it's gonna be like and I mean there's a certain stage of acceptance and that yes in terms of rewinding you think we can rewind the system back sort of the the nice thing about many worlds I guess is it really emphasizes the maybe you can correct me but to determine it the deterministic nature of a branch and it feels like it could be a while back is it is do you see is this something that could be perfectly won back rewinded back yeah you know if you're at a fancy French restaurant yeah there's a nice linen white tablecloth and you have your glass of Bordeaux and you knock it over and the wine spills across the tablecloth if the world were classical okay it would be possible that if you just lifted the wine glass up you'd be lucky enough that every molecule of wine would hop back into the glass right but guess what it's not going to happen in the real world and the quantum wave function is exactly the same way it is possible in principle to rewind everything if you start from perfect knowledge of the entire wave function of the universe in practice that's never gonna happen so time travel not possible nope at least one mechanic says no help what about memory does the universe have a memory of itself where we could in in it's a not time travel but peek back in time and do a little like replay well it's exactly the same in quantum mechanics as classical mechanics so whatever you want to say about that you know the fundamental laws of physics in either many worlds quantum mechanics or Newtonian physics conserve information so if you have all the information about the quantum state of the world right now your Laplace's demon-like in your knowledge and calculational capacity you can wind the clock backward but none of us is right and you know so in practice you could never do that you can do experiments over and over again starting from the same initial conditions for small systems but once things get to be large Avogadro's number of particles write bigger than a cell no chance we we've talked a little bit about arrow of time last time but in many worlds that there is a kind of implied arrow of time right so you've talked about the arrow of time that has to do with the second law of thermodynamics that's the arrow of time that's emergent or fundamental we don't know I guess no it's emergent it's a is that there's everyone agree on that well nobody's everything so that area of time is that different in the arrow of time that's implied by many worlds it's not different actually no in both cases you have fundamental laws of physics that are completely reversible if you give me the state of the universe at one moment in time I can run the clock forward or backward equally well there's no arrow of time built into the laws of physics at the most fundamental level but what we do have are special initial conditions 14 billion years ago near the Big Bang in thermodynamics those special initial conditions take the form of things were low entropy and entropy has been increasing ever since making the universe more disorganized and chaotic and that's the arrow of time in quantum mechanics these special initial conditions take the form of there was only one branch of the wavefunction and the universe has been branching more and more ever since ok so if time is emergent so it seems like our human cognitive capacity likes to take things that are emergent and assume in feel like they're fundamental so what it sequence of times emergent and locality like space emergent yes ok but I didn't say time was merge and I said the arrow of time was emergent those are different what's the difference between the arrow of time and time are using arrow of time to simply mean this the synonymous with the second law thermodynamics no but the arrow of time is the difference between the past and future so all right there's space but there's no arrow of space you don't feel that space has to have an arrow right you could live in thermodynamic equilibrium there be no arrow of time but there'd still be time it'd still be a difference between now and the future also ok so if nothing changes there's still time well things could even change like if the whole universe consisted of the earth going around the Sun yeah ok it would just go in circles or ellipses right that's not every things would change but it's not increasing entropy there's no arrow if you took a movie of that and I played you the movie backward you would never know so the arrow of time can theoretically point in the other direction for brief briefly so intent that it points in different directions it's not a very good arrow I mean the arrow of time in the macroscopic world is so powerful that there's just no chance of going back when you get down to tiny systems with only three or four moving parts then entropy can fluctuate up and down what does it mean for space to be an emergent phenomena it means that the fundamental description of the world does not include the word space it'll be something like a vector in Hilbert space right and you have to say well why is there a good approximation scription which involves three dementia space and stuff inside it okay so time and space or immersion we kind of mentioned it in the beginning but can you elaborate what do you feel hope is fundamental in our universe a wavefunction living in hilbert space wave function and hilbert space that we can't intellectualize or visualize really we can't visualize it we can intellectualize it very easily like well how do you think about it's a vector in a 10 to the 10 to the 120 2-dimensional vector space it's a complex vector unit norm it evolves according the Schrodinger equation got it when you put it that way what's so hard really yep quantum computers there's some excitement actually a lot of excitement with people that it will allow us to simulate quantum mechanical systems what kind of questions do about quantum mechanics about the things we've been talking about do you think do you hope we can answer through quantum simulation well I think that there are there's a whole fascinating frontier of things you can do with quantum computers both sort of practical things with cryptography or money privacy eavesdropping sorting things simulating quantum systems right so it's a it's a broader question maybe even outside of quantum computers some of the theories that we've been talking about what's your hope what's most promising to test these theories what are what are kind of experiments we can conduct whether in simulation or in the physical world that would validate or disprove or expand these theories well I think for the there's two parts of that question one is many worlds and the other one is sort of emergent space-time for many worlds you know there are experiments on going to test whether or not wavefunction spontaneously collapse and if they do then that rules out many worlds and that will be falsified what if there are hidden variables there's a theorem that seems to indicate that the predictions will always be the same as many worlds I'm a little skeptical this theorem I'm not completely I haven't internalized it haven't made it in part of my intuitive view of the world yet so there might be loopholes to that theorem I'm not sure about that I part of me thinks that there should be different experimental predictions if there are hidden variables but I'm not sure but otherwise it's just quantum mechanics all the way down and so there's there's this cottage industry in science journalism of writing breathless articles that say you know quantum mechanics shown to be more astonishing than ever before thought and really it's the same quantum mechanics we've been doing since 1926 whereas with the emergent space-time stuff we know a lot less about what the theory is it's in a very primitive state we don't even really have a safely written down respectable honest theory yet so there could very well be experimental predictions we just don't know about yet that is one of the things that we're trying to figure out me before emergence space-time you need a really big stuff all right well or really fast stuff or really energetic stuff we don't know that that's the thing you know so there could be violations of the speed of light if you have a version space-time not going faster than the speed of light but the speed of light could be different for light of different wavelengths right that would be a dramatic violation of physics as we know it but it could be possible or not I mean it's not an absolutely prediction as that's that's the problem the theories are just not well developed enough yet to say is there anything that quantum mechanics can teach us about human nature or the human mind do you think about sort of consciousness and these kinds of topics is there it's certainly excessively used as you point out the word quantum is used for everything besides quantum mechanics but in more seriousness is there something that goes to the human level and can help us understand our mind not really is the short answer you know minds are pretty classical I don't think we don't know this for sure but I don't think that phenomena like entanglement are crucial to how the human mind works or about consciousness so you mentioned I think early on in the Commerce you said it would be I'm a it would be unlikely but incredible if sort of the observer somehow a fundamental part yeah so observer not to romanticize the notion but seems interlink to the idea of consciousness so if consciousness as the pant site because believe is fundamental to the universe is that possible is that wait I mean every possible just say Joe Rogan likes to say it's entirely possible but ok but is it on a spectrum of crazy out there how how the statistic is speaking how often do you ponder the possibility that consciousness is fundamental or the observer is fundamental to personally don't at all there are people who do I'm a thorough physical estate company side I do not think that there are any separate mental states or mental properties I think they're all emergent just like space-time is and you know space-time is hard enough to understand so the fact that we don't yet understand consciousness is not at all surprising to you as we mentioned have an amazing podcast called mindscape it's as I said on my favorite podcast sort of both for your explanation of physics which a lot of people of and when you venture out into things that are beyond your expertise but it's just a really smart person exploring even questions like you know morality for example it's very interesting I think you did a solo episode and so on I mean there's a lot of really interesting conversations that you have what are what are some from memory amazing conversations that pop to mind you've had what did you learn from them something that maybe changed your mind and just inspired you or just what do this whole experience of having conversations what stands out to you it's an unfair question totally unfair that's okay that's alright you know it's often the ones I feel like the the ones I do on physics and closely related science or even philosophy ones are like I know this stuff and I'm helping people learn about it but I learned more from the ones that nothing to do with physics or philosophy right so talking to Wynton Marsalis about jazz or talking to a Master Sommelier about wine talking to will Wilkinson about partisan polarization and the urban-rural divide talking to psychologists like Carol Tavarez about cognitive dissonance and and how those things work scott derrickson who is the director of the movie dr. strange I had a wonderful conversation with him where we went through the mechanics of making a blockbuster superhero movie right and he's also not a naturalist he's a he's a evangelical Christian so we talked about the nature of reality there I want to have a couple more you know discussions with highly educated theists who know the theology really well but I haven't quite arranged those yet I would love to hear that I mean that's how comfortable are you venturing into questions of religion well I'm totally comfortable doing it you know I did talk with Alan Lightman who is also an atheist but he he is trying to rescue the sort of spiritual side of things for atheism and I did talk to very vocal atheists like Alex Rosenberg so I need to talk to some I talked to some religious believers and he talked more how have you changed through having all these conversations you know part of the motivation was I had a long stack of books that I hadn't read and I couldn't find time to read them and I figured if I interviewed their authors forcing me to read them right and that's that is totally worked by the way now I'm annoyed that people write such long books I think I'm still very much learning how to be a good interviewer I think that's a skill that uh you know I I think I have good questions but you know there's the give-and-take that is still I think I could be better at like I want to offer something to the conversation but not too much right I've had conversations where I barely talked at all and I have conversations where I talked half the time I think there's a happy medium in between there so I think I remember listening to without mentioning names some of your conversations where I wish you would have disagreed more yeah as a listener it's more fun sometimes it well this is that's a very good question because you know my everyone has an attitude toward that like some people are really there to basically give their point of view and the they're their guest is supposed to you know respond accordingly I I want to sort of get my view on the record but I don't want to dwell on it when I'm talking to someone like David Chalmers who I disagree with a lot you know I want to say like here's why I disagree with you but you know I want we're here to listen to you like I have a Pepa sowed every week and you only own once a week right and so I have enough coming podcast episode with Philip golf who is much more dedicated pants I kissed and so there we really get into it I think that I probably have disagreed with him more on that episode than I ever have with another podcast guest but that's what he wanted so it worked very well yes yeah that kind of debate structure is beautiful when it's done right like when you're when you can detect that the intent is that you have fundamental respect for the person yeah that and that's for some reason it's super fun to listen to when two really smart people are just arguing and sometimes lose their a little bit if I may say well there's a fine line because I have zero interest in bringing I mean like I mean it may be maybe you implied this I have zero interest in bringing on people for whom I don't have any intellectual respect like I constantly get requests like you know bring on a flat earth or whatever and really slap them down or a creationist like I'm at zero interest I'm happy to bring on you know a religious person a believer but I want someone who's smart and can act in good faith and can talk not a charlatan or a lunatic right so I will only I will happily bring on people with whom I disagree but only people from who I think the audience can learn something interesting so let me ask the idea of Charlton is an interesting idea you might be more educated on this topic than me but there's um there's folks for example who argue of various aspects of evolution sort of try to approach and say that evolution sort of our current theory of evolution has many holes in it as many flaws and they argue that I think like Cambridge Cambrian explosion that which is like a huge added variability of species doesn't make sense under our current description of evolution to a theory of evolution sort of if you had were to have the conversation with people like that how do you know that they're the difference being outside the box thinkers and people who are fundamentally unscientific and even bordering on charlatans it's a great question and you know the further you get away from my expertise the harder it is for me to really judge exactly those things and you know yeah I don't have a satisfying answer for that one because I think the example you use of someone who you know believes in the basic structure of natural selection but thinks that you know this particular thing cannot be understood in the terms of our current understanding of Darwinism that's a perfect edge case where it's hard to tell right and I would have to I would try to talk to people who I do respect and who do know things and I would have to you know given that I'm a physicist I know that physicists will sometimes be too dismissive of alternative points of view I have to take into account that biologists can also be too dismissive of alternative points of view so yeah that's a tricky one have you gotten heat yet yeah all the time like there's always something I mean it's it's hilarious cuz I do have I try very hard not to like have the same topic several times in a row I did have like to climate change episodes but they were from very different perspectives but I like to mix it up that's the whole puzzle I'm having fun and every time I do an episode someone says oh the person you should really get on to talk about exactly that is this other person like well I don't but I did that now I want to do that well I hope you keep doing it you're inspiring millions of people your books your podcasts Sean it's an honor to talk to you thank you so much thanks very much like you |
Garry Kasparov: Chess, Deep Blue, AI, and Putin | Lex Fridman Podcast #46 | the following is a conversation with Gary Kasparov he's considered by many to be the greatest chess player of all time from 1986 until his retirement in 2005 he dominated the chess world ranking world number one for most of those 19 years while he has many historical matches against human chess players in a long arc of history he may be remembered for his match against the machine IBM's deep blue his initial victories and eventual loss to deep blue captivated the imagination of the world of what role artificial intelligence systems may play in our civilizations future that excitement inspired an entire generation of AI researchers including myself to get into the field gary is also a pro-democracy political thinker and leader a fearless human rights activist and author of several books including how life imitates chess which is a book on strategy and decision-making winter is coming which is a book articulating his opposition to the Putin regime and deep thinking which is a book on the role of both artificial intelligence and human intelligence in defining our future this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars and iTunes support it on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D ma a.m. and now here's my conversation with Garry Kasparov as perhaps the greatest chess player of all time when you look introspectively your psychology throughout your career what was the bigger motivator the love of winning or the hatred of losing tough question I have to confess I never heard it before each is again congratulations it's quite an accomplishment losing was always painful for me it was almost like a physical pain because I knew that if I lost the game it's just because I made a mistake so it I always believed that the result of the game had to be decided by the quality of my play okay you may say it sounds arrogant but it helped me to move forward because I always knew that there was room for improvement so it's the was there the fear the mistake actually fear of mistake guarantees mistakes and the difference between top players and very top is that it's the ability to make a decision without predictable consequences you don't know what's happening it's intuitively I can go this way or that way and they're always hesitations people like your you're just you know at the crossroad you can go right you can go left you can go straight you can turn and go back and the consequences are just very uncertain yes you have certain ideas what happens on the right or on the left or on just you know if you go straight but it's not enough to make well calculated choice and when you play chess at the very top is it's it's it's about your inner strength so I can make this decision I will stand firm and I'm not going to waste my time because I feel confidence that I will go through going back to the original question is I would say neither it's just it's the it's love for winning hateful losing there were important elements psychological elements but the key element it's the I would say the the driving force was always my passion for for making it make any difference it's just I can move forward and I can always its I can always enjoy not just playing but creating something new creating something new how do you think about that it's just finding new ideas in the openings you know some regional plan in the middle game it's actually that helped me to make the transition from the game of chess where I wasn't a very top two to another life where I knew I would not be number one I would don't be necessarily on the top but I could still be very active and productive by my ability to make the difference by influencing people say joining the democratic movement in Russia or talking to people about human-machine relations there's so many things were I knew my influence may not be as decisive as in chess but still strong enough to help people to make their choices so you can still create something new that makes a difference in the world outside of chess but wait you've kind of painted a beautiful picture of your motivations to chess to create something new to look for those moments of some brilliant new ideas but were you haunted by something see you make it seem like to be at the level you are at you can get away without having demons without without having fears without being driven if by some of the darker forces I mean you sound almost religious you know dark forces to reach you know humans and we do have a pole for a priest now just let's go back to you to to these crucial chess moments where I had to make big decisions as I said it's it's you know it was all about my belief from very early days that I can make all the difference by playing well or by making mistakes so the yes I I always had an opponent across the chessboard opposite me but no matter how strong their point was well they just were ordered player or another wall champion I can't leak or proof I haven't called respect for my opponent I still believe that it's it's up to me to make the difference and I I knew I I was not invincible I made mistakes I made some blunders and you know with age I mean more blunders okay good I knew it but it's it's still you know it's it's very much for me to be decisive factor in the game I mean even now look I just you know my latest chess experience was horrible I mean I get played carolallan Khurana fatphobia Khurana it's number two number two number three player well these days we play this 960 which they fish for so call Fisher a random chairs from shuffling pieces yeah I lost very badly but it's because I made mistakes I mean I had so many winning positions I mean 15 years ago I would have crushed him so and it's it's you know while I lost I got so much upset I mean I know as I said in my interview I can fight any opponent but not my biological clock it's fighting time with is is is always a losing proposition but even today at age 56 you know I I knew that you know I could play great game I couldn't finish it because I didn't have enough energy or just you know I couldn't have the same level concentration but you know in number of games where I completely outplayed one of the top players in the world I mean gave me a certain amount of pleasure that is even today I haven't lost my touch not the same you know okay the jaws are not as as strong and DTS are another sharp but I could get him just you know almost you know two on the ropes Oh got it it's still got it and that's you know and it's it's my wife said it well I mean she said look Gary it's somehow it's something you just fighting viola your biological clock it's just you know maybe it's a signal because you know the goddess of chess since you spoke lean religious the goodness of chess Keysha maybe she didn't wound you twin because you know if you could beat number - number three pride in the world I mean this is this one of the better top players who just recently played World Championship match if you could beat him it's that was really bad for the game of chess just what people who say oh look the game of chess you know it's it's it's not make any progress the game is just you know it's it's totally devalued because Italy the guy coming out of retirement you know just you know winning games maybe that was good for chess not good for you but it's okay I've been following your logic we should always look for you know demons you know superior forces and other things that did you know if not dominate our lives but somehow in a play a significant role in in the outcome yeah so the goddess's chess had to send a message yeah okay okay so Gary you should do something else time now for a question that you have heard before but give me a chance you've dominated the chess world for twenty years even still got it is there a moment you said you always look to create something new is there is there games or moments where you're especially proud of in terms of your brilliance of a new creative move we've talked about mikhail tall as somebody who was aggressive and creative chess player in your own game look you mentioned mikhail call it's very aggressive very sharp player famous ways combinations and sacrifices even called magician from riga so for his very unique style but any any world champion you know it's yeah was a creator some of them were so flamboyant and flash like call some of their world no just you know less discerned at the chessboard like Tigran Petrosian but every world champion every top player brought something into the game of chess and each contribution was priceless because it's not just about sacrifices of course amateurs they enjoy you know the brilliant games where pieces being sacrificed it's all just you know pieces are hanging and and it's all of a sudden you know being material down rube or just you know queen down the the the weaker side delivers the the final blow on just you know amazing opponent's king but this there are other kinds of beauty slow positioning when you ring you know looking for witnesses and just and and gradually really strangling your opponent and eventually delivering sort of a positional masterpiece yeah so I think I I made more difference in the game of chess then I could I could have imagined when I started playing and the reason I thought it was time for me to leave is just I mean I knew that I was not I was not no longer the position to bring bring the same kind of contribution the same kind of new knowledge into the game so and going back I could immediately look at my games again sounds only corpus not just I won the match in 1985 and became world champion at age 22 but there were at least two games in that match of course the last one game 24 that was decisive game of the match i won and became world champion but also the way a wise was it was a very hard game and i found a unique maneuver that was absolutely new and it became some sort of just a typical now though just when the move was made was made at the on the board and put on display a lot of people thought it was ugly so and another game game 16 and the match or I just also managed to outlay Karpov completely was black pieces just you know paralyzing his entire army in its own its own camp technically or psychologically or was that a mix of both in game 16 yeah it I think it was a big blow to Karpov I think it was a big psychological victory for a number of reasons one the score was equal at a time and the world champion you know by the rules could retain his title in case of a tie so we still have no before game 16 we have nine games to go and also it was some sort of a bluff because neither me nor Karpov saw the reputation of this opening idea and and I think it says for carpel it was double blow because not that he lost the game I should triple blow he lost the game it was a brilliant game and I played impeccably after you know justice this opening Bluff and then you know they discovered that it was a bluff so it's the again I didn't know it I wasn't bluffing so that's why by it happens very often it's when you know some ideas could be refuted and it's just what I found out and this is again going back to your you know spiritual theme is that and it's you could spend a lot of time working and when I say you could it's just it's it's in the 80s in the 90s it does happen these days because everybody has a computer you could immediately see if it works or it doesn't work machines show the refutation in the split of a second but many of the our analysis in the eighties or in the 90s they were not perfect simply because we're humans and they're just you you analyze the game you look for some fresh ideas and then test it happens that there was something that you missed because the level of concentration at the chessboard it's different from one that when you analyze the game just moving the pieces around but somehow if you spend a lot of time at the chessboard preparing so in your studies with your coaches hours and hours and hours and nothing of what you found could had materialized on the our own chests on the chess board somehow these hours helped I don't know I always helped you it's it's as if you know the amount of work you did could be transformed into some sort of spiritual energy that helped you to come up with other great ideas during the board again even if it was there was no direct connection between your preparation and your victory in the game there was always some sort of invisible connection between the amount of work you did your dedication to actually to you and your passion to discover new ideas and your ability during the game add the chess board when the clock was ticking we still had ticking clock not so to come up with some some some brilliancy and them and I also can mention many games from the 90s so it's the obviously all amateurs would pick up my game against Veselin Topalov in 1999 and we can say again because it was a Bruin game the black king traveled from from its own camp to into D into in the white scam across the entire board it doesn't happen often trust me as you know in in in indie games were professional players top professional players so that's why I visually it was one of the most impressive victories but I could bring to your attention many other games that were not so impressive for for amateurs not so note so beautiful just guess it's sacrifice always beautiful you sacrificed asses and then and then eventually you have so there are very few resources left and you you you use them just to to to to crush your your opponent basically to it's you have to make the kink because you have almost almost nothing nothing nothing left at your disposal but I you know I up to the very end in less and less but still up to the very end I always had games with some sort of you know interesting ideas and and games that gave me great satisfaction but I think it's what happened from 2005 up to you these days was also a very very big accomplishment since you know I had to find myself to sort of relocate myself yeah we channel the creative energies exactly do you find something worth feel comfortable even confident that my participation still makes the difference beautifully put so let me ask perhaps a silly question but sticking our chests for just a little longer where do you put Magnus Carlsen in the current world champion in a list of all time greats in terms of style moments of brilliance consistency it's a tricky question you know the moment you start ranking yeah well do something it's the I think it's it's it's not fair because it's any new generation knows much more about the game than their previous one so when people say Gary was the greatest Fischer was the greatest Magnus was the greatest it disregard the fact that the great players of the past where the last year have a plank looking I mean they knew so little about chess by today's standards today just any kid you know that spent few years you know and uh with his or her chess computer when knows much more about the game simply just because you actually have access to this information and it has been discovered generation after generation we added more and more knowledge to the game of chess it's about the gap between the world champion and the rest of the field so it's the now if you look at the gap then proud official you know could be on top but very short period of time then you should also add a time factor yeah I was on top not as big as but but much longer so so and also unlike Fischer I will succeed in beating next generation yeah here's the question yeah let's see if you still got the fire speaking of the next generation because you did succeed beating the next generation it's close okay well Anand short Anand the sheer of chromic is already 12 years younger so that's a neck that's but still yet I I competed with them and I just had beat most of them and and I was still dominant when I left at age of the 41 so back to Magnus Madras right consistency is phenomenal the reason Magnus is on top and it seems unbeatable today Magnus is is a lethal combination of Fischer on Karpov but just very it's very unusual because Fischer style was very dynamic just fighting to the last point just using every resource available Karpov was very different as just yet an unparalleled ability to use the every piece with a maximum effect just it's minimal resources always produce maximum effects just so now imagine that you merge these two styles say oh it is it's it's like you know it's a squeezing every stone for drop of water but but doing it you know just you know for 50 60 70 80 moves I mean mangas could go on as long as Fisher who is always passion and energy and at the same time being as meticulous and and and and deadly as corporal by just you know using every little advantage so and yes good you know very good else it's important I mean physical conditions are by the way very important so a lot of people don't recognize it their latest study shows that chess players burn thousands of calories during the game so that puts him on the top of this fuel of of the wall chambers but again it's the discussion that is I so recently in internet whether garry kasparov always peek let's say late 80s could be Magnus Carlsen today I mean something irrelevant because garriga's probably 1989 okay it's played great chess but still I knew very little about chess compared to Magnus crossing 2019 who Biden will learn from me as well so that's why yeah I'm extremely cautious in making any judgment that involves you know time gaps you ask you know soccer fans so who is your favorite Pele Maradona or Messi yeah yeah who's your favorite Messi miss because maybe because he's younger but that's simple your instinct answer is correct because you saw you didn't say marathon in action I saw all of them in action so that's why but it's but since you know when I was you know just following it in air just it's pillion and Maradona they were just you know there were big stars and it's Macy's already just get I I was gradually losing interest other things so I remember Pele 1970 the final match Brazil Italy so that's the first world war World Cup soccer I watched so that's the and and actually my answer when it just where that just you know I because I I was asked this question as well so I say that is this while it's impossible to make a choice I would sue probably go with Maradona for simple reason the Brazilian team in 1970 could have won without Collette it was absolutely great still could have won maybe but it is the Argentinian team in 1986 without Maradona would not be in the 5s so this is and Messi he still has that's not good argue for that for an hour but yes you could say if you ask Maradona if you look in his eyes especially let's say Gary Kasparov 99 he would have said I was sure as hell would be magnus carlsen it's just simply the confidence fire simply because simply because again it's just a so mean action so this again it's it's the age factor as important therefore is a passion and energy and and being equipped with all modern ideas but again then you make in a very just important assumption that you could empower Gary Kasparov 89 with all ideas that have been accumulated over 30 years that would not be Garrigus part that would be someone else because again I belong to 1989 I was way ahead of the field and I you know a bit Karpov several times in World Championship matches and I crossed 2,800 which by the way if you look at the chest in rating which is just it's even today so this is this is the rating that I retire so that says it's still you know it's just it's a it's a top two to three so that says this is kerwin and eaglets about the same rating now and I crossed 2,100 in 1990 we just look at the inflation when I cross 2,800 in in 1990 there was only one player in 2700 category Anatoly Karpov now he had more than 50 so just you see this so if you add inflation so I think my 28:51 it could probably could be more valuable as Magnus 2882 which was highest rating but anyway yeah you know so many hypotheticals you're lost to IBM gee blue in 1997 in my eyes there's one of the most seminal moments in the history again I apologize for being romanticized in the notion but in the history of our civilization because humans as the civilizations for century saw chess as you know the peak of what man can accomplish of intellectual mastery right and that moment when a machine could beat a human being was inspiring to just an entire anyone who cares about science innovation the entire generation of AI researchers and yet to you that laws at least if reading your face was seemed like a tragedy extremely painful like you said physically painful why when you look back at your psychology that lost why was it so painful when you're not able to see the seminal nature of that moment Oh or was that exactly why was that powerful as I already said losing was painful physically passing and the match I lost in 1997 was not the first match I lost to a machine it was the first match I lost period yes that's oh yeah it's right yeah that makes all the difference to me yes first time I lost it's just now I lost and the reason I was so angry that I just you know I had suspicions that my loss was not just the result of my bad play yes SoDo I played quite poorly you know just when you started looking at the games today I made tons of mistakes but you know I had all reasons to believe that you know there were other other factors that had nothing to do with the game of chess and that's what I was angry but look it was 22 years ago it's what under the bridge we can analyze this match and this is with everything you said I I agree it was probably one exception is that considering chess you know as the sort of as a pinnacle of intellectual activities what's our mistake because you know we just thought oh it's a it's a game of the highest intellect and I just you know you have to be so you know intelligent and as you could see things that you know the or the ordinary ordinary mortals could not see it's a game and all machines had to do with this game is just to make fewer mistakes not to solve the game because the game cannot be solved I mean according to Shannon the number of legal moves is ten to the 46 power too many zeroes for any computer to finish the job you know in in in neck billion years but it doesn't have to it's all about making fewer mistakes and I think that's the this match actually and what's happened afterwards with other games with go with shrug II with video games it's a demonstration that it's the machines will always beat humans in what I call closed systems the moment you build a closed system no matter how this system is called chess go froggie daughter machines will prevail simply because they will bring down number of mistakes machines don't have to solve it they just have to it's the way they outplay us it's not by just being more intelligent it's just by by doing something else but eventually it's just it's capitalizing on our mistakes when you look at the chess machines ratings today in compare compare this to Magnus Carlsen is the same as comparing Ferrari to Hussein bold it's the the gap is is I meant by chess standards is insane thirty four thirty five hundred to twenty eight hundred twenty eight twenty eight twenty eight fifty one man knows it's like difference between macros and AB and an ordinary player from an open international tournament it's not because machine understands better than magnus carlsen but simply because it's steady machine has steady hand and I think that is what we we we have to learn from 1997 experience and from further encounters with computers and sort of the the current state state of affairs was alpha zero you beating other machines the idea that we can compete with computers in so-called intellectual fields it's it was wrong from the very beginning it's just it's by the way if 1997 match was not the first victory of machines over our masters or masters yeah no actually it's I played against first decent chess computers from late from late 80s so I played with the prototype of deep blue called deep thought in 1989 to repeat chest in New York I want handily those games we played against new chess engines like Fritz and other programs and then it Steve was Israeli problem jr. that appeared in yeah so there were several problems I you know I lost few games in blitz I lost one match against the computer a chess engine 1994 rapid chess so I lost one game 2d blue in 1996 match the manner the match chef I want some people you know tend to forget about it that I won the first match yes but it's it's we we made a very important psychological mistake thinking that the reason we lost blitz matches five five minutes games the reason we lost some of the rapid chess matches twenty five minutes just because we didn't have enough time if you play a longer match we will not make the same mistake nonsense so this yeah we had more time but we still make mistakes and machine also has more time and machines machine will always you know I will always be stated inconsistent compared to humans instabilities and inconsistencies and today we are at a point where yes nobody talks about you know humans playing use machines machines can offer handicap two to two top players still you know will will will be favoring I think we're just learning that is it's it's no longer human versus machines it's about human working with machines that's what I recognized in 1998 just after licking my wounds and spending one year in just in a ruminating Saudi so what's happened at in this match and I knew that though we still could play against the machines I had two more matches in 2003 playing both a deep freeze and deep jr. both matches and there's a tie mmm-hmm though this machines were not weaker at least I promise stronger and II blue and by the way today just app on your mobile phone is probably stronger than the blue individual I'm not speaking of any bit about chess engines that are so much superior and by the way when you analyze games who played against the blue 90 97 on your chess engine they'll be laughing yeah so this is and it's also shows that's how it just changed because just commentators they look at some of our games like game for Game five and idea now you asked stockfish you asked Houdini you asked Commodore all the leading chess engines yeah within 30 seconds they will show you how many mistakes booze Gary and D blue mate in the game that was from Pettitte as the as a great chess match in 1997 well okay so you've made an interesting if you can untangle that comment so now in retrospect it was a mistake to see chess as the peak of human intellect nevertheless that was done for centuries so even in Europe because you know you move to the far east they will go there shogi games again I guess some of the games like you look our board games yes yes yeah so if I push back a little bit so now you say that okay but it was a mistake to see chess as the epitome and now and then now there's other things maybe like language that conversation like some of the things that in your view is still way out of reach of computers but inside humans do you think can you talk about what those things might be and do you think just like chess that might fall soon with the same set of approaches if you look at alpha zero the same kind of learning approaches as the machines grow in size no no it's not about in size it's about again it's about understanding the difference but in closed system an open-ended system so you think that key difference so the board games are closed in terms of the rules that they actions simple the state space everything is just constrained you think once you open it the machines are lost not lost but again the effectiveness is very different because machine does not understand the moment it's reaching the territory of diminishing returns hmm it's the simple in a different way machine doesn't know how to ask right questions it can ask questions but we'll never tell you which questions are relevant so this D it's like about the it's the it's a direction so these it's I think is in human relations we have to consider so our role and people many people feel uncomfortable that is the territory that that belongs to us is is shrinking I'm saying so what you know is this is eventually will belong to the last few decimal points but it's like having so very powerful gun that's and and and and all you can do there is slightly you know alter direction of the bullet maybe you know point one the degree of this angle but that means a mile away ten meters of tourists so so that's we have to recognize that is a certain unique human qualities that machine's in the foreseeable future will not be able to reproduce and and the effectiveness of this cooperation collaboration depends on our understanding what exactly we can bring into the game so the greatest danger is when we try to interfere with machines superior knowledge so that's why I always say that sometimes you'd rather have by reading these pictures in radiology you may probably prefer an experienced nurse then rather than having top professor because she will not try to interfere with machines understanding so this it's very important to know that if machines knows how to do better things in 95% 96% of territory we should not touch it because it's it happened we it's like in chess recognize they they do it better see where we can make the difference you mentioned alpha 0 alpha 0 it's a it's actually a first step into what you may call AI because everything that's being called AI today is just it's it's it's one or another variation of what Claude Shannon characterized as a brute force is a type a machine whether it's deep blue whether its what's in it and all these the modern technologies that are being competitors as AI it's still boot force it's the all video it's they do optimization it's this they are you know they they keep you know improving the way to process human generated data hmm now alpha zero is is the first step towards you know machine produced knowledge yes which is why what by the way it's quite ironic that the first company that jumped on that was ideal oh it's in backgammon interesting in that again yes you just you should you should you should look at IBM is this it's a new gammon it's the it's the he's still working IBM they had in early nineties it says it's the it's in the program that played in LD alpha 0 type so just trying to come up with own strategies but because of success of the blue this project had been not abandoned but just you know it's it's it wasn't was put on call and now it just you know it's it's it's you know it's every talks about about this t the machines generated knowledge so as a revolutionary and it is but there's still you know many open-ended questions yes alpha 0 generates its own data many ideas that alpha 0 generating chess work quite intriguing so I I looked at these games was not just with interest but was no it was quite exciting to learn how machine could actually you know juggle all the pieces and just play positions with a broken material balance sacrificing material always being ahead of other programs you know one or two moves ahead by by foreseeing the consequence not over calculating because machines other machines were at least as powerful in calculating but it's having this unique knowledge based on discovered patterns after playing 60 million games almost something like feels like intuition exactly but there's one problem yeah now the simple question if if alpha 0 faces superior point let's say another powerful computer accompanied by human who could help just to discover certain problems because I already I look at many alpha 0 games I visited their lab spoke to demis hassabis and his team and I I know that certain witnesses there now if these wings are exposed and that question is how many games will it take for alpha zero to correct it the answer is hundreds of thousands even if it keeps losing it it's this because the whole system is based yes so it's now imagine so that says you can have a human by just making few tweaks so humans are still more flexible and and as long as we recognize what is what is our raw where we can play sort of so the most valuable part in this collaboration so it's it will help us to understand what are the next steps in human machine collaboration beautifully put so let's talk about the thing that machine's certainly don't know how to do yet which is morality machines and morality but it's another question that I know just it's that's as being asked all the time these days and I I think it's another phantom that is haunting a general public because it's just being fed with this you know illusions is that how can we vote machines you know having bias need prejudices you cannot because it's like looking in the mirror and complaining about what you see if you have certain bias in the society machine will will just follow it it's just it's it's you know you look at the mirror you don't like what you see there you can you know you can break it you can try to distort it or you can try to actually change something just itself yes by yourself yes so it's very important to understand is this is you cannot expect machines to to improve the ease of our society and moreover machines will simply know just you know amplified yes yeah but the thing is people are more comfortable with other people doing injustice would being biased we're not comfortable with machines having the same kind of bias so that's a that's an interesting standard that we place on machines with autonomous vehicles they have to be much safer with automated systems because they're much safer statistically they're much safer than then of course why would they it's not of course it's it's not given autonomous vehicles you have to work really hard to make them is safer i I think it just goes without saying is the the outcome of the of this alcohol competition but comparison is very clear but the problem is not about being in a safer it's the forty thousand people will show every year died in car accidents United States and it's its statistics one accident ways with autonomous vehicle and it's front page of a newspaper yeah this was cycle so it's while people you know kill each other in car accidents because they make mistakes they make more mistakes for me it's it's it's not a question of course we make more mistakes because we human yes machines old and by the way no machine will ever reach hundred percent perfection that's not that that's another important take story that that that is being fed to the public if machine doesn't reach hundreds and performance is not safe no all you can ask any computer whether it's you know playing chess or or doing the stock market calculations or driving your autonomous vehicle it's to make fewer mistakes and yes I know it's not you know it's not easy for us to accept because ah if you know if you have to humans you know colliding in their cars okay it's like if one of one of these cars is autonomous very vehicle and by the way even if it's humans fault terrible how could you allow a machine to do it you to run without driver ID at the wheel so you know let's think of that for a second that double standard the way you felt with your first loss against D blue were you treating the Machine differently than you would have a human or so what do you think about that difference between the way we see machines and humans no it's a match and that's why I was angry because I believe they're lost the match was not you know fairly organized so the states definitely they were unfair advantages for for IBM and I want to play there another match like rubble mess so you're angered or displeasure was a more like at the humans behind IBM versus the actual your absolute algorithm absolutely look I I knew at the time and by the way I was objectively speaking I was stronger at that time so that's that we added to my anger because I knew I could beat machine yeah yeah so this and that's the and I lost and I knew I was not well prepared so because they I have to give them credit they did some good work from 1996 and I but I still could beat the machine so I made too many mistakes also this is the hole is this the publicity around the match so I underestimated the effect you know just it's Andy and being called the you know the the brains lost and ounce okay no pressure okay well let me ask so I was born also in the Soviet Union what lessons do you draw from the rise and fall of the Soviet Union in the 20th century when you just look at this nation that is now look I'm pushing forward into what Russia is if you look at the long arc of history of the 20th century what do we take away what do we take away from that I think the lesson of history is clear undemocratic systems totalitarian regimes systems that are based on controlling their citizens and just every aspect of their life not offering opportunities to for private initiative central planning systems they duped they just you know they they cannot be driving force for innovation so they in in history timeline I mean they could cause certain you know distortion of the concept of progress they by the way call themselves progressive but we know that is this the damage that they cost to to humanity is just it's it's it's yet to be measured but at the end of the day they fail they fail and it's and the end of the Cold War was a great triumph of the free world it's not that the free world is perfect it's very important to recognize its factors I always like to mention you know one of my favorite books a lot of the Rings daddy there's no there's no absolute good but there's an absolutely good you know it comes in many forms but we all you know it's humans or being even you know humans from fairy tales or just some sort of mystical creatures it's they you can always find spots on the song so this is conducting war and just and fighting you for justice there are always things that you know can be easily criticized and human history is the is a never-ending quest for perfection but we know that there is absolutely you we know it's for me it's now clear that's I mean it's nobody argues about Hitler being absolutely well but I think it's very poor against Stalin was absolutely communism caused more damage than any other ideology in the 20th century and unfortunately while we all know that fascist was condemned but there was no nerble for common communism and that's why we could see you know still is the these the successors of Stalin are feeling far more comfortable so you is one of them you highlight a few interesting connections actually between Stalin and Hitler I mean there that in in terms of the adjusting or clarifying the the history of war to which they're interesting of course we don't have time so let me ask you I just I just recently delivered a speech in Toronto yeah at a decent roast of Malta ribbon from pact it's something that I believe you know just you know has must must be taught in the schools and the world what you had been started by to dictators by signing these these criminal criminal treaty collusion of two tyrants in August 1939 that the beginning of the world World War two and the fact that eventually Stalin had no choice but to join allies because Hitler attack him so it just doesn't you know eliminated the fact that Stalin helped Hitler to start World War two and he was one of the beneficiary said early at early stage by annexing part of Eastern Europe and as a result of the war with you he annexed always entire Eastern Europe and for many Eastern European nations the end of the world would you was the beginning of communist occupation hmm so Putin you've talked about as a man who stands between Russia and democracy essentially today you've been a strong opponent and critic of Putin let me ask again how much does fear enter your mind and heart so in 2007 there's this interesting comment from Oleg Kalugin KGB general he said that I do not talk details people who knew them are all dead now because they were vocal I'm quiet there's only one man who's vocal and he may be in trouble World Chess Champion Kasparov he has been very outspoken in his attacks on Putin and I believe he's probably next on the list so clearly your life has been and perhaps continues to be in danger how do you think about having the views you have the ideas you have being in opposition as you are in this kind of context when your life could be in danger oh that's the reason I live in New York so what's they was not my first choice but I knew I had to leave Russia at one point and among other places New York is the safest is it safe no I mean interested Steve I know what happens what happened what is happening who is many of Putin enemies but at the end of the day I mean what can I do it it's I I could be very proactive by trying to change things I can influence but here are way effects I I cannot stop doing what I've been doing for a long time it's the right thing to do I grew up with my family teaching me sort of the wisdom of Soviet dissidents do what you must and so be it I could try to be cautious by not traveling to certain places were you know my security could be at risk there's so many invitations to speak at different locations in the world and I have to say that many countries are just now are not destinations that I can afford to travel my mother still lives in Moscow and meet her a few times a year she was devastated when I had to leave Russia because since my father died in 1971 so she was 33 and she dedicated her entire life to her only son but she recognized in just a year or so since I left Russia that it was the only chance for me to continue my normal life so just is to I mean to be relatively safe and to to do what she taught me to do to make the difference do you think you will ever return to Russia or oh I'm sure when it won't sooner than many people think because I think Putin regime is facing insurmountable different difficulties and again I read enough historical books to know that dictatorships they they end suddenly it's just on Sunday dictator feels comfortable he believes he's popular on Monday morning his bust the good news and bad news I mean the bad news is that I don't know when and how Putin rule ends the good news he also doesn't know okay well put let me ask a question that seems to preoccupy the American mind from the perspective of Russia one did Russia interfere in the 2016 US election government-sanctioned and future two will rush into fear in the 2020 US election and what does that interference look like it's very old you know we had such an intelligent conversation and you are ruining everything by asking such as healthy but it's it's insulting for my intellect okay of course they did interfere over horse they did absol everything to elect Trump I mean they said it many times he this is you know I met enough KGB Colonels in my life to tell you that you know just the way put it looks at Trump yeah this is the way Luke said I don't have to hear what he says what Trump says it just is I don't need to go through congressional instigations the way he put it looks at Trump it's the way the KGB officers looked at the assets it's just and following to 20/20 of course they will do absolutely everything to help Trump to survive because I think they damage that Trump's relations could cause to America and to the free world it's just it's beyond one's imagination I think basically from was reelected she'll ruin NATO because he's already heading in this direction but now he's just he's still limited by the re-election hurdles if he's still in the office after November 2020 okay January 2021 I don't think about it my problem is not just Trump because Trump is basically it's a symptom but the problem is that I don't see it just it's the in American political horizon politicians who could take on Trump for for all damage that he's doing for the free world not just things that that's happened that went wrong in America so this the it seems to me that the campaign political campaign on the Democratic side is is fixed on certain important but still second duration guess when you have the foundation the Republican jeopardy I mean you cannot talk about health care I mean understand how important it is but it's still secondary because the a framework familiar political life is at risk and you have rather intrusion just you know just it's having the free hands bye-bye he's by attacking America and other free countries and by doing we have so much evidence about Russia intervals and brexit in elections in almost every European country and thinking that they will be shy of attacking America in 2020 now is we strong in the office yeah I think it's um yeah it definitely diminishes the intellectual quality falklands I do what I can last question if you can go back just look at the entirety of your life you accomplished more than most humans will ever do if you could go back and relive a single moment in your life what would that moment be there are moments in my life when I think about what could be done differently but no experience happiness and joy and pride just-just-just is this it's the it's look I made many mistakes in my life so I just it's there I know that at the end of the day it's I believe in the butterfly effect so is the it's the I knew moments where I could now if I'm there at that point in 89 in 93 pick up a year I could improve my actions by not doing this stupid thing but then how do you know that I will have all other compliments yeah I just I'm I'm afraid that you know we just have to just follow this if you make all wisdom before is Gumpy know it's the life as this you know it's this it's a box of affair of chocolate and you don't know what's inside but you have to go one by one so it's the I'm I'm happy with who I am and where I am today and I am very proud not only with my chess accomplishments but that I made this transition and since I left chess you know i built my own reputation that had some influence of the game of chess but not it's not you know directly derived from from the game I'm grateful for my wife so who helped me to build his life we actually married in 2005 it was my sure marriage that's why I said that make mistakes in my wife but I died by the way I'm close with two kids from my previous marriages so that's tasty I mean I managed to sort of to balance my life and and hear it I live in New York so we have our two kids born here in New York it's its new life and it's you know it's it's busy sometimes I wish I could you know I could limit my engagement in many other things that said I still you know taking time and energy but life is exciting and as long as I can feel that I've energy I have strengths I have passion to make the difference I'm happy I think that's a beautiful moment and on Gary spicy buh-bye sure thank you very much for talking to me thank you possible you |
Michio Kaku: Future of Humans, Aliens, Space Travel & Physics | Lex Fridman Podcast #45 | the following is a conversation with Michio Kaku he's a theoretical physicist futurist and professor at the City College of New York he's the author of many fascinating books that explored the nature of our reality and the future of our civilization they include Einsteins cosmos physics of the impossible feature of the mind parallel worlds and his latest the future of humanity terraforming Mars interstellar travel immortality and our destiny beyond earth I think is beautiful and important when a scientific mind can fearlessly explore through conversation subjects just outside of our understanding that to me is where artificial intelligence is today just outside of our understanding a place we have to reach for it for to uncover the mysteries of the human mind and build human level and superhuman level AI systems that transform our world for the better this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars on iTunes supported on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M am and now here's my conversation with Michio Kaku you've mentioned that we just might make contact with aliens or at least hear from them within this century can you elaborate on your intuition behind that optimism well this is a pure speculation of course of course but given the fact that we've already identified 4,000 exoplanets orbiting other stars and we have a census of the Milky Way galaxy for the first time we know that on average every single star on average has a planet going around it and about 1/5 or so of them have earth sized planets going around them so just do the math we're talking about out of a hundred billion stars in the Milky Way galaxy we're talking about billions of potential Earth size planets and to believe that we're the only one is I think rather ridiculous given the odds and how many galaxies are there within sight of the Hubble Space Telescope there are about a hundred billion galaxies so do the math how many stars are there in the visible universe a hundred billion galaxies times a hundred billion stars per galaxy we're talking about a number beyond human imagination and to believe that we're the only ones I think is is rather ridiculous so you've talked about different types of types zero one two three four and five even of the car - of scale of the different kind of civilizations do what do you think it takes if it is indeed a ridiculous notion that we're alone in the universe what do you think it takes to reach out first to reach out through communication and connect well first of all we have to understand the level of sophistication of an alien life-form if we make contact with them I think in this century we'll probably pick up signals signals from an extraterrestrial civilization we'll pick up there I Love Lucy and their Leave It to Beaver just ordinary day-to-day transmissions that they emit and the first thing we want to do is to a decipher their language of course but be figure out at what level they are advanced on the Kardashev scale I'm a physicist we rank things by two parameters energy and information that's how we rank black holes that's how you rank stars that's how you rank civilizations in outer space so a type one civilization is capable of harnessing planetary power they control the weather for example earthquakes volcanoes they can modify the course of geologic events sort of like Flash Gordon or Buck Rogers type 2 would be stellar they play with stars entire stars they use the entire energy output of a star sort of like Star Trek the Federation of Planets have colonized the nearby stars so a type 2 would be somewhat similar to Star Trek type 3 would be galactic they roam the Galactic space lanes and type 3 would be like Star Wars a galactic civilization then one day I was giving this talk in London at the planetarium there and the little boy comes up to me and he says professor you're wrong you're wrong this type 4 and I told them look kid there are planets stars and galaxies that's it folks and he kept persisting and saying no there's time for the power of the continuum and I thought about it for a moment and I said to myself is there an extra galactic source of energy the continuum of Star Trek and the answer is yes there could be a type 4 and that's dark energy we now know that 73% of the energy of the universe is dark energy dark matter represents maybe 23 percent or so and we only represent 4% we're the oddballs and so you begin to realize that yeah they could be type 4 maybe even type 5 so type 4 you're saying being able to harness sort of like dark energy something that permeates the entire universe so be able to plug into the entire entire universe is a source of energy that's right and dark energy is the energy of the Big Bang it's why the galaxies are being pushed apart it's the energy of nothing the more nothing you have the more dark energy that's repulsive and so the acceleration of the universe is accelerating because the more you have the more you can have and that of course is by definition and exponential curve it's called a discerner expansion and that's the current state of the universe and then type 5 would that be would that be able to seek energy sources somehow outside of our universe however that idea yeah what time five will be the multiverse multiverse I'm a quantum physicist and we quantum physicists don't believe that the Big Bang happen once that would violate the Heisenberg uncertainty principle and that means that there could be multiple bangs happening all the time even as we speak today universes are being created and that fits the data the inflationary universe is a quantum theory so there's a certain finite probability that universes are being created all the time and for me this is actually rather aesthetically pleasing because you know I was raised as a presbyterian but my parents were Buddhists and there's two diametrically opposed ideas about the universe in Buddhism there's only nirvana there's no beginning there's no end there's only timelessness but in Christianity there is the instant when God said let there be light in other words an instant of creation so I've had these two mutually exclusive ideas in my head and I now realize that it's possible to Mel them into a single theory either the universe had a beginning or it didn't right wrong you see our universe had a beginning our universe had an instant where somebody might have said let there be light but there other bubble universes out there in a bubble bath of universes and that means that these universes are expanding into a dimension beyond our three-dimensional comprehension in other words is hyperspace in other words 11 dimensional hyperspace so Nirvana would be this timeless 11 dimensional hyperspace where big bangs are happening all the time so we can now combine two mutually exclusive theories of creation and Stephen Hawking for example even in his last book even said that this is an argument against the existence of God he said there is no God because there was not enough time for God to create the universe because the Big Bang happened in an instant of time therefore there was no time available for him to create the universe but he see the multiverse idea means that there was a time before time and there multiple times each bubble has its own time and so it means that there could actually be a universe before the beginning of our universe so if you think of a bubble bath when two bubbles collide well when two bubbles fission to create a baby bubble that's called the Big Bang so the Big Bang is nothing but the collision of universes or the budding of universes this is a beautiful picture of our incredibly mysterious existence so is that humbling to you exciting the idea of multiverses I don't even know how to even begin well you wrap my mind around citing for me because what I do for a living is string theory that's my day job I get paid by the city of New York to work on string theory yes and you see string theory is a multiverse theory so people say first of all what is string theory string theory simply says that all the particles we see in nature the electron the proton the quarks what have you or nothing with vibrations on a musical string on a tiny tiny little string you know D Robert Oppenheimer the creator of the atomic bomb was so frustrated in the 1950s with all these subatomic particles being created in our atom smashers that he announced he announced one day that the Nobel Prize in Physics should go to the physicist who does not discover a new particle that year well today we think they're nothing but musical notes on these tiny little vibrating strings so what is physics physics is the harmonies you can write on vibrating strings what is chemistry chemistry is the melodies you can play on these strings what is the universe the universe is a symphony of strings and then what is the mind of God that Albert Einstein's so eloquently wrote about for the last thirty years of his life the mind of God would be cosmic music resonating through eleven dimensional hyperspace so beautifully put what do you think is the mind of Einstein's God do you think there's a way that we could untangle from this from this universe of strings why are we here what is the meaning of it all well Steven Weinberg winner of the Nobel Prize once said that the more we learned about the universe the more we learned that is pointless well I don't know I don't profess to understand the great secrets of the universe however let me say two things about what the Giants of physics have said about this question Einstein believed in two types of God one was the God of the Bible the personal God the God that answers prayers walks on water as performs miracles smites the Philistines that's the personal God that he didn't believe in he believed in the God of Spinoza the God of order simplicity harmony Beauty the universe could have been ugly the universe could have been messy random but it's gorgeous you realize that on a single sheet of paper we can write down all the known laws of the universe it's amazing on one sheet of paper Einstein's equation is one-inch long string theory is a lot longer and so it's a standard model but you could put all these equations on one sheet of paper it didn't have to be that way it could have been messy and so Einstein thought of himself as a young boy entering this huge library for the first time being overwhelmed by the simplicity elegance and beauty of this library but all he could do was read the first page of the first volume well that library is the universe with all sorts of mysterious magical things that we have yet to find and then Galileo was asked about this Galileo said that the purpose of science the purpose of science is to determine how the heavens ago the purpose of religion is to determine how to go to heaven so in other words science is about natural law and religion is about ethics how to be a good person how to go to heaven as long as we keep these two things apart we're in great shape the problem occurs when people from the Natural Sciences begin to pontificate about ethics and people from religion begin to pontificate about natural law that's where we get into big trouble you think they're fundamentally distinct morality and ethics and our our idea of what is right and what is wrong that's something that's outside the reach of string theory in physics that's right if you talk to a squirrel about what is right and what is wrong yes there there's no reference frame for a squirrel and realize that aliens from out of space if they ever come visit us they'll try to talk to us like we talked to squirrels in the forest but eventually we get bored talking to the squirrels because they don't talk back to us same thing with aliens from out of space and they come down to earth they'll be curious about us to a degree but after a while they just get bored because we have nothing to offer them so our sense of right and wrong what does that mean compared to a squirrels sense of right and wrong now we of course do have an ethics that keeps civilizations in line enriches our life and makes civilization possible and I think that's a good thing but it's not mandated by a law of physics so if aliens do alien species were to make contact forgive me for staying on aliens for a bit longer do you think they're more likely to be friendly to befriend us or to destroy us well I think for the most part our they'll pretty much ignore us if you were deer in the forest who do you fear the most do fear the hunter with his gigantic 16 gauge shotgun or do you fear the guy with a briefcase and glasses well the guy with a briefcase could be a developer about to basically flatten the entire forest destroying your livelihood so instinctively you may be afraid of the hunter but actually the problem with deers in the forest is that they should fear developers in developing because developers look at deer as simply getting in the way I mean in war the world's by hto wells the aliens did not hate us if you read the book the aliens did not have evil intentions toward him Homo sapiens no we were in the way so I think we have to realize that alien civilizations made viewers quite differently than in science fiction novels however I personally believe and I cannot prove any of this I personally believe that they're probably going to be peaceful because there's nothing that they want from our world I mean what are they gonna kick us what are they gonna take us for gold no gold is a useless metal for the most part it's silver I mean is gold golden color but that only affects Homo sapiens squirrels don't care about gold and so gold is a rather useless element rare earths may be platinum-based elements rare earths for their electronics yeah maybe but other than that we have nothing to offer them I mean think about it for a moment people love Shakespeare and they love the arts and poetry but outside of the earth they mean nothing absolutely nothing I mean when I write down an equation in string theory I would hope that on the other side of the galaxy there's an alien writing down that very same equation in different notation but that alien on the other side of the galaxy Shakespeare poetry Hemingway it would be nothing to him or her or it when you think about entities that's out there extraterrestrial do you think they would naturally look something that even is recognizable to us as his life or can it would they be radically different well how did we become intelligent basically three things made us intelligent one is our eyesight stereo eyesight we have the eyes of a hunter stereo emissions will be lock-in on targets and and who is smarter predator or prey predators are smarter than prey they have their eyes at the front of their face like lions tigers wild rabbits have eyes to the side of their face why is that hunters have to zero in on the target they have to know how to ambush they have to know how to hide camouflage sneak up stealth deceit that takes a lot of intelligence rabbits all they have to do is run so that's the first criterion stereo eyesight of some sort second is the thumb the opposable thumb of some sort could be a claw or tentacle so a hand-eye coordination and eye coordination is the way we manipulate the environment and then three language because you know mama bear never tells baby bear to avoid the human hunter bears just learned by themselves they never hand on information from one generation to the next so these are the three basic ingredients of intelligence eyesight of some sort an opposable thumb or tentacle or claw of some sort and language now ask yourself a simple question how many animals have all three just us it's just us I mean the primates they have a language yeah they may get up to maybe 20 words but a baby learns a word-a-day several words a day a baby learns and a typical adult knows about almost 5,000 words while the maximum number words that you can teach a gorilla in any language including their own language is about 20 or so and so we see the difference in intelligence so when we meet aliens from outer space chances are they will have been descended from predators of some sort they'll have some way to manipulate the environment and communicate their knowledge to the next generation that's it folks so functionally that would that would be similar they would we would be able to recognize them well not necessarily because I think even with Homo sapiens we are eventually going to perhaps become part cybernetic and genetically enhanced already robots are getting smarter and smarter right now robots have the intelligence of a cockroach but in the coming years our robots will be as smart as a mouse then maybe as smart as a rabbit if we're lucky maybe as smart as a cat or a dog and by the end of the century who knows for sure our robots will be probably as smart as a monkey now at that point of course they could be dangerous you see monkeys are self-aware they know they are monkeys they may have a different agenda than us while dogs dogs are confused you see dogs think that we are a dog that we're the top dog they're the underdog that's why they whimper and follow us and lick us all the time for the top dog monkeys have no illusion at all they know who we are not monkeys and so I think that in the future we'll have to put a chip in their brain to shut them off once our robots have murderous thoughts but that's in a hundred years in 200 years the robots will be smart enough to remove that failsafe chip in their brain and then watch out at that point I think rather than compete with our robots we should merge with them we should become part cybernetic so I think we'll be beat alien life from outer space they may be genetically and and cybernetically enhanced genetically and cybernetically enhanced Wow so let's talk about that full range in the near term and 200 years from now how promising in the near term in your view is brain machine interfaces those starting to allow computers to talk directly to the brains Elon Musk is working on that with neural link and there's other companies working on this idea do you see promise there do you see hope for near-term impact well every technology has pluses and minuses already we can be core memories I have a book the future of the mine or I detail some of these breakthroughs we can now record simple memories of mice and send these memories on the Internet eventually we're going to do this with primates at Wake Forest University and also in Los Angeles and then after that we'll have a memory chip for Alzheimer's patients well test it out in alzheimerís patients because of course when Alzheimer is patients lose their memory they wander they create all sorts of havoc wandering around oblivious to their surroundings and they'll have a chip they'll push the button and memories memories will come flooding into their hippocampus and the chip telling them where they live and who they are and so a memory chip is definitely in the cards and I think this will eventually affect human civilization what is the future of the Internet the future of the Internet is brain net brain net is when we send emotions feelings sensations on the internet and we will telepathically communicate with other humans this way this is gonna affect everything look at entertainment remember the silent movies a Charlie Chaplin was very famous during the era of silent movies but when the talkies came in nobody wanted to see Charlie Chaplin anymore because he never talked in the movies and so a whole generation of actors lost their job and a new series of actors came in next we're gonna have the movies replaced by rain net because in the future people will say who wants to see a screen with images that's it sound an image that's called the movies yeah our entertainment industry this multi-billion dollar industry is based on screens with moving images and sound but what happens when emotions feelings sensations memories can be conveyed on the Internet it's going to change everything human relations will change because you'll be able to empathize and feel the suffering of other people will be able to communicate telepathically and this is this is coming you describe brain that in feature of the mind this is an interesting concept do you think so you mentioned entertainment but what kind of effect would it have on our personal relationships hopefully it will deepen it you realize that for most of human history for over 90% of human history we only knew maybe 20 a hundred people yeah that's it folks that was your tribe that was everybody you knew in the universe was only maybe 50 or a hundred with the coming of towns of course it expanded to a few thousand with the coming of the telephone all of a sudden you could reach thousands of people with a telephone and now with the internet you can reach the entire population of the planet Earth and so I think this is a normal progression and you you think that kind of sort of connection to the rest of the world and then adding sensations like being able to share telepathically emotions and so on that would just further deepen our connection to our fellow humans yes right in fact I disagree with many scientists on this question most scientists would say that technology is neutral a double-edged sword one sword one side of the sword can cut against people the other side of the sword can cut against ignorance and disease I disagree I think technology does have a moral direction look at the Internet the internet spreads knowledge awareness and that creates empowerment people act on knowledge when they begin to realize that they don't have to live that way they don't have to suffer under a dictatorship that there are other ways of living under freedom then they begin to take things take power and that spreads democracy and democracies do not war with other democracies I'm a scientist I believe in data so let's take a sheet of paper and write down every single war you had to learn since you were an elementary school every single war hundreds of kings queens emperors dictators all these wars were between kings queens emperors and dictators never between two major democracies and so I think with the spread of this technology and which would accelerate with the coming of brain net it means that well we will still have wars wars of course as politics by other means but there'll be less intense and less frequent do you have worries of longer-term existential risk from technology from AI so I think that's a wonderful vision of a future where war is a distant memory but now there's another agent there's there's there's somebody else that's able to create conflict that's able to create harm AI systems so do you have worry about such AI systems well yes that is an existential risk but again I think an existential risk not for this century I think our grandkids are gonna have to confront this question as robots gradually approach the intelligence of a dog a cat and finally that of a monkey however I think we will digitize ourselves as well not only are we gonna merge with our technology it will also digitize our personality our memories our feelings you realize who did during the Middle Ages there was something called dualism dualism meant that the soul was separate from the body when the body died the soul went to heaven that's dualism then in the 20th century neuroscience came in and said bah humbug every time we look at the brain it's just neurons that's it folks period end of story bunch of neurons firing now we're going back to dualism now we realize that we can digitize human memories feelings sensations and create a digital copy of ourselves and that's called the connectome project billions of dollars are now being spent to do not just the genome project of sequencing the genes of our body but the connectome project which is to map the entire connections of the human brain and even before then already in Silicon Valley today at this very moment you can contact Silicon Valley companies that are willing to digitize your relatives because some people want to talk to their parents there are unresolved issues with their parents and one day yes firms will digitize people and you'll be able to talk to them a reasonable facsimile we Lea we leave a digital trail our ancestors did not our ancestors were lucky if they had one line just one line in a church book saying the day they were baptized and the day they died that's it that was their entire digital memory I mean their entire digital existence summarized in just a few letters of the alphabet a whole life now we digitized everything every time you sneeze you digitized it you put it on the Internet and so I think that we are going to digitize ourselves and give us digital immortality will not only have biologic genetic immortality of some sort but also digital immortality and what are we going to do with it I think we should send it into outer space if you digitize the human brain and put it on a laser beam and shoot it to the moon you're on the moon in one second shoot it to Mars you're on Mars in 20 minutes shoot it to Pluto you're on Pluto in eight hours think about it for a moment you can have breakfast in New York and for a morning snack vacation on the moon then zap your way to Mars by noontime journey through the asteroid belt of the afternoon and they come back for dinner in New York at night all in a day's work it's at the speed of light now this means that you don't need booster rockets you don't need weightlessness problems you don't need to worry about meteorites and what's on the moon on the moon there is a mainframe that downloads your laser beams information and where does it download the information into an avatar now what does it ever try look like anything you want yeah think about it for a moment you could be Superman superwoman on the moon on Mars traveling throughout the universe at the speed of light downloading your personality into any vehicle you want now let me stick my neck out so for everything I've been saying is well within the laws of physics well within the laws of physics now let me go outside the laws of physics here we go I think this already exists I think outside the earth there could be a superhighway a laser highway of laser pointing with billions of souls of aliens zapping their way across the galaxy now let me ask you a question are we smart enough to determine whether such a thing exists or not no this could exist right outside the orbit of the planet Earth and we're too stupid in our technology to even prove it or disprove it we would need the aliens on this laser superhighway to help us out just to send us a human interpretable signal I mean it ultimately boils down to the language of communication but that's an exciting possibility that actually the sky is filled with aliens should already be here and we're just so oblivious that we're too stupid to know it see they don't have to be an alien form with with little green men they could be in any form they want in an avatar of their creation or in fact they could very well be they look like us exactly he'd never know one of us could be an alien you know in a zoo did you know that we sometimes have zookeepers that imitate animals we create a fake animal and we put it in so that the animal is not afraid of this fake animal and of course these animals brains their brain is about as big as a walnut they accept these dummies as if they were real so an alien civilization in outer space would say oh yeah human brains are so tiny we could put a dummy on their world and avatar and they never know it that would be an entertaining thing to watch from the alien perspective so you kind of implied that with it was a digital form of our being but also biologically do you think one day technology will allow individual human beings to become immortal besides just through the ability to digitize our essence yeah I think that artificial intelligence will give us the key to to genetic immortality you see in the coming decades everyone's going to have their gene sequence will have billions of genomes of old people billions of genomes of young people and what are we going to do with it we're gonna run into an AI machine which has a pattern recognition to look for the Aged genes in other words the Fountain of Youth that Emperor's kings and queens lusted a ver over the Fountain of Youth will be found by artificial intelligence artificial intelligence will identify where these aged genes are located first of all what is aging we now know what aging is aging is the build-up of errors that's all aging is the buildup of genetic errors this means that cells eventually become slower sluggish if they go into senescence and they die in fact that's why we die we die because of the build up of mistakes in our genome in our cellular activity but you've seen the future we'll be able to fix those genes with CRISPR type technologies and perhaps even live forever so let me ask you a question we're just aging take place in a car given a car where does aging take place well it's obvious the engine right a that's where you have a lot of moving parts B that's where you have combustion well where in the cell do we have combustion the mitochondria we know know where ageing takes place and if we cure many of the mistakes that build up in the mitochondria of the cell we could become immortal let me ask you if you self could become immortal would you damn straight now I think about it for a while because of course if the term it depends on how you become immortal you know there's a famous myth of Tiffany's it turns out that years ago the in the Greek mythology there was the saga of Tiffany's and Aurora Aurora was the goddess of the dawn and she fell in love with a mortal a human called Athena's and so Aurora begged big Zeus to grant her the the gift of immortality to give to her lover so Zeus took pity on Aurora and made Tiffany's immortal but you see Aurora made a mistake a huge mistake she asked for immortality but she forgot to ask for eternal youth so port Athena's got older and older and older every year decrepit a bag of bones but he could never die never done quality of life is important so I think immortality is a great idea as long as you also have immortal youth as well now I personally believe and I cannot prove this but I personally believe that our grandkids may have the option of reaching the age of 30 and then stopping they may like being age 30 is you have wisdom you have all the benefits of age and maturity and you still live forever with a healthy body our descendants may like being 30 for several centuries is there an aspect of human existence that is meaningful only because we're mortal well every waking moment we don't think about it this way but every waking moment actually we are aware of our death and our mortality think about it for a moment when you go to college you realize that you're in a period of time where soon you will reach middle age and have a career and after that you'll retire and then you'll die and so even as a youth even as a child without even thinking about it you are aware of your own death because it sets limits to your lifespan I got a graduate from high school I got a graduate from college why because you're gonna die because unless you graduate from high school unless you graduate from college you're not gonna enter old age with enough money to retire and then die and so yeah people think about it unconsciously because it affects every aspect of your being the fact that you go to high school college get married have kids miss a clock a clock ticking even without your permission it gives a sense of urgency do you do you yourself I mean there's so much excitement and passion in the way you talk about physics and we talk about technology in the future do you yourself meditate on your own mortality do you think about this clock that's ticking well I try not to because it begins to affect your behavior you begin to alter your behavior to to match your expectation of when you're gonna die so let's talk about youth and then let's talk about death okay when I interview scientists on radio I often ask them what made the difference how old were you what changed your life and they always say more or less the same thing no these are Nobel Prize winners directors of major laboratories very distinguished scientists they always say when I was 10 when I was 10 something happened it was a visit to the planetarium it was the telescope for Steven Weinberg winner of the Nobel Prize it was the chemistry kid for Heinz piggles it was a visitor to the planetarium for Isidor Rabi it was a book what the planets for Albert Einstein it was a compass something happened which gives them this existential shock because you see before the age of 10 everything is mommy and daddy mommy and dad that's your universe maja me and daddy around the age of 10 you begin to wonder what's beyond me and daddy and that's when you have this epiphany when you realize oh my god there's a universe out there a universe of discovery that sensation stays with you for the rest of your life you still remember that shock that you felt gazing at the universe and then you hit the greatest destroyer of scientists known to science the greatest destroyer of scientists known to science is junior high school we knew hit junior high school folks it's all over yeah it's all over because in junior high school people say hey stupid I mean you like that nerdy stuff and your friends shun you all of a sudden you people think you're a weirdo and scientists made boring you know Richard Feynman the Nobel Prize winner when he was a child his father would take him into the forest and the father would teach him everything about birds why do you shape the way they are their wings the coloration the shape of their beak everything about birds so one day a bully comes up to the future Nobel Prize winner and says hey dick what's the name of that bird over there well he didn't know he knew everything about that bird except his name so he said I don't know and then the bully said what's the matter dick you stupid or something and then in that instant he got it he got it he realized that for most people science is giving names to birds that's what science is you know lots of names of obscure things Hey people say you're smart you're smart you know all the names of the dinosaurs you know all the names of the plants no that's not science at all science is about principles concepts physical pictures that's what science is all about my favorite quote from Einstein is that unless you can explain a theory to a child the theory is probably worthless meaning that all great theories are not big words all great theories are simple concepts principles basic physical pictures our relativity is all about clocks meter sticks rocket ships and locomotives Newton's laws of gravity are all about balls and spinning wheels and things like that that's what physics and science is all about not memorizing things and that stays with you for the rest of your life so even in old age I've noticed that these scientists when they sit back they still remember they still remember that flush that flush of excitement they felt with that first telescope that first moment when they encountered the universe that keeps them going that keeps them going by the way I should point out that when I was 8 something happened to me as well when I was 8 years old it was in all the papers that a great scientist had just died and they put a picture of his desk on the front page that's it just a simple picture of the front page of the newspapers of his desk that desk had a book on it which was opened and the caption said more or less this is the unfinished manuscript from the greatest scientists of our time so I said to myself well why couldn't you finish it what's so hard that you can't finish it if you're a great scientist it's a homework problem right you go home you solve it or you ask your mom why couldn't he solve it so to me this was a murder mystery this was greater than any adventure story I had to know why the greatest scientists of our time couldn't finish something and then over the years I found out the guy had a name Albert Einstein and that book was the theory of everything it was unfinished well today I can read that book I can see all the dead ends and false starts that he made and I began to realize that he lost his way because he didn't have a physical picture to guide him on the 3rd try on the first try he talked about clocks and lightning bolts and meter sticks and they gave us special relativity which gave us the atomic bomb the second great picture was gravity with balls rolling on curved surfaces and they gave us the big bang creation of the universe black holes on the third try he missed it he had no picture at all to guide him in fact there's a quote I have where he said I'm still looking I'm still looking for that picture he never found it well today we think that picture is string theory the string theory can unify gravity and this mysterious thing that ice tide didn't like which is mechanics Oh couldn't couldn't quite pin down and make sense of that's right mother nature has two hands the left hand and a right hand the left hand is a theory of the small the right hand is a theory of the big the theory the small is the quantum theory the theory of atoms and quarks the theory of the big is relativity the theory of black holes big bangs the problem is the left hand does not talk to the right hand they hate each other the left hand is based on discrete particles the right hand is based on flute smooth surfaces how do you put these two things together into a single theory they hate each other the greatest minds of our time the greatest minds of our time worked on this problem and failed today the only one the only theory that has survived every challenge so far is string theory that doesn't mean string theory is correct it could very well be wrong but right now is the only game in town some people come up to me and say professor I don't believe in the string theory give me an alternative and I tell them there is none get used to it it's the best theory we got it's the only theory we have it's the only theory we have do you see you know the strings kind of inspire a view as did atoms and particles and quarks but especially strings inspire view of a universe as a kind of information processing system as a as a computer of sorts do you see the universe in this way no some people think in fact the whole universe is a computer of some sort yes and they believe that perhaps everything therefore is a simulation yes I don't think so I don't think that there is a super video game where we are nothing but puppets dancing on the screen and somebody hit the play button and here we are talking about simulations no even Newtonian mechanics says that the weather the simple weather is so complicated with trillions upon trillions of atoms that it cannot be simulated in a find out an amount of time in other words the smallest object which can describe the weather and simulate the weather is the weather itself the smallest object that can simulate a human is the human itself and if you had quantum mechanics it becomes almost impossible to simulate it with a conventional computer is quantum mechanics deals with all possible universes parallel universes a multiverse of universes and so the calculation just spirals out of control now they're at so far there's only one way where you might be able to argue that the universe is a simulation and this is still being debated by quantum physicists it turns out that if you throw the Encyclopedia into a black hole the information is not lost eventually it winds up on the surface of the black hole now the surface of the what I call is finite in fact you can calculate the maximum amount of information you can store in a black hole it's a finite number it's a calculable number believe it or not now if the universe were made out of black holes which is the maximum universe you can conceive of each universe each black hole has a finite amount of information therefore our go that uh our go the total amount of information in a universe is finite this is mind-boggling this I consider mind-boggling that all possible universes are countable and all possible universes can be summarized in a number a number you can write on a sheet of paper all possible universes and it's a finite number now is huge it's a number beyond human imagination it's a number based on what is called the Planck length but it's a number and so if a computer could ever simulate that number then it would the universe would be a simulation so theoretically because it's because the amount of information is finite there well there necessarily must be able to exist a computer it's just from an engineering perspective maybe impossible to be yes so no computer can build a universe capable of simulating the entire universe except the universe itself so that's your intuition that our universe is very efficient and so there's no shortcuts right - two reasons why I believe the universe is not a simulation first the calculational numbers are just incredible no finite the Turing machine can simulate the universe and second why would any super intelligent being simulate humans if you think about it most humans are kind of stupid I mean we do all sorts of crazy stupid things right and we call it art we call it humor we call it human civilization so why should an advanced civilization go through all that effort just to simulate Saturday Night Live well that's a funny idea it's also do you think it's possible that the act of creation cannot anticipate humans you simply set the initial conditions and set a bunch of physical laws and just for the fun of it see what happens you'll launch the thing so you're not necessarily simulating everything you're not simulating every little bit in in the same in the sense that you could predict what's going to happen but you set the initial conditions set the laws and see what kind of fun stuff happens well some in some sense that's how life got started in the 1950s Stanley did what is called the Miller experiment he put a bunch of hydrogen gas methane toxic gases with liquid and a spark in a small glass beaker and then he just walked away for a few weeks came back a few weeks later and bingo out of nothing in chaos came amino acids if he had left it there for a few years he might have gotten protein protein molecules for free that's probably how life got started as a accident and if he had left it there for perhaps a few million years DNA might have formed in that beaker and so we think that yeah DNA life all that could have been an accident if you wait long enough and remember our universe is roughly 13.8 billion years old that's plenty of time for lots of random things to happen including life itself yeah we could be just a beautiful little random moment and there could be a nearly infinite number of those in throughout the history of the universe many many creatures like us we perhaps are not the epitome of what the universe is created for her thank God let's hope not just look around yeah you're right what do you think the first human will step foot on Mars I think it's a good chance in 2030s that we will be on Mars in fact there's no physics reason why we can't do it it's an engineering problem it's a very difficult and dangerous engineering problem but it is an engineering problem and in my book future of humanity I even speculate beyond that that by the end of the century we'll probably have the first starships the first starships will not look like the enterprise at all they'll probably be small computer chips that are fired by laser beams with parachutes and like what Stephen Hawking advocated the breakthrough starshot program could send ships ship to the nearby stars traveling at 20% of speed of light reaching Alpha Centauri in about 20 years time beyond that we should have fusion power using power is in some sense one of the ultimate sources of energy but it's unstable and we don't have fusion power today now why is that first of all stars for mammals for free you get a bunch of gas large enough it becomes a star I mean you didn't have to do anything to it and it becomes a star why is fusion so difficult to put on the earth because you're not a space stars our mana poles they are pole single poles that sphere are there a spherically symmetric and it's very easy to get spherical symmetric configurations of gas to compress into a star he just happens naturally all by itself the problem is magnetism is bipolar you have a North Pole and a South Pole and it's like trying to squeeze a long balloon take a long balloon and trying to squeeze it you squeeze one side it bulges out the other side well that's the problem with fusion machines we use magnetism with the North Pole in the South Pole to squeeze gas and all sorts of anomalies and horrible configurations can take place because we're not squeezing something uniformly like in a star stars in some sense or for free fusion on the earth is very difficult but I think it's inevitable and it'll eventually gave us unlimited power from seawater so seawater will be the ultimate source of energy for the planet Earth why what's the intuition there because we'll extract hydrogen from seawater burn hydrogen in the fusion reactor to get give us unlimited energy without the meltdown without the nuclear waste why do we have meltdowns we have meltdowns because in the fission reactors every time you split the uranium atom you get nuclear waste tons of it 30 tons of nuclear waste per reactor per year and it's hot it's hot for thousands millions of years that's why we have meltdowns but you see the waste product of a fusion reactor is helium gas helium gas is actually commercially valuable you can make money selling helium gas and so the waste product of a fusion reactor is helium not nuclear waste that we find in a commercial fission plant in that controlling mastering controlling fusion allows us to converse us into a type 1 I guess civilization right yeah probably the backbone of a type one civilization will be fusion power we by the way are type zero we don't even rate on this scale we get our energy from dead plants for God's sake oil and coal but we are about a hundred years from being type one you know get a calculator in fact Carl Sagan calculated that we are about 0.7 fairly close to a 1.0 for example what is the internet the Internet is the beginning of the first type one technology to enter into our century the first planetary technology is the Internet what is the language of type 1 on the internet already English and Mandarin Chinese are the most dominant languages on the Internet and what about the culture we're seeing a type 1 Sports soccer the Olympics a type 1 music a youth culture rock and roll rap music type 1 fashion Gucci Chanel a type 1 economy the European Union NAFTA what have you so we're beginning to see the the beginnings of a type 1 culture in a type one civilization and inevitably it will spread beyond this planet so you talked about sending at 20% the speed of light on a chip into Alpha Centauri but in a slightly nearer term what do you think about the idea when we still have to send biological our biological bodies the colonization of planets colonization of Mars DC is becoming a two-planet species ever or any time soon well just remember the dinosaurs did not have a space program now and that's why they're not here today how come there are no dinosaurs in this room today because they didn't have a space program we do have a space program which means that we have an insurance policy now I don't think we should bankrupt the earth or deplete the earth to go to Mars that's too expensive and not practical but we need a settlement a settlement on Mars in case something bad happens to the planet Earth and that means we have to terraform Mars now to terraform Mars if we get raised a temperature of Mars by 6 degrees 6 degrees then the polar icecaps begin to melt releasing water vapor water vapor is the greenhouse gas it causes even more melting of the ice caps so it becomes a self-fulfilling see it feeds on itself it becomes autocatalytic and so once you hit six degrees were rising of the temperature on Mars by six degrees it takes off and we melt the polar ice caps and liquid water once again flows in the rivers the canals are the channels and the oceans of Mars Mars once had an ocean we think about the size of the United States and so that is a possibility now how do we get there how do we raise the temperature of Mars by six degrees Elon Musk would like it didn't a hydrogen warheads on the polar icecaps yes well I'm not sure about that because we don't know that much about the effects of detonating hydrogen warheads to melt the polar ice caps and who wants to glow in the dark at night reading the newspaper so I think there are other ways to do it with solar satellites you can have satellites orbiting Mars that beam sunlight onto the polar ice caps melting the polar ice caps Mars has plenty of water it's just frozen I think you paint and inspiring in a wonderful picture of the future it's I think you've inspired and educated thousands if not millions Michio it's been an honor thank you so much for talking today my pleasure you |
David Ferrucci: IBM Watson, Jeopardy & Deep Conversations with AI | Lex Fridman Podcast #44 | following is a conversation with David Ferrucci he led the team that built Watson the IBM question-answering system that beat the top humans in the world at the game of Jeopardy for spending a couple hours of David I saw a genuine passion not only for abstract understanding of intelligence but for engineering it to solve real-world problems under real-world deadlines and resource constraints where science meets engineering is where brilliant simple ingenuity emerges people who work adjoining it to have a lot of wisdom earned two failures and eventual success David is also the founder CEO and chief scientist of elemental cognition a company working to engineer AI systems that understand the world the way people do this is the artificial intelligence podcast if you enjoy it subscribe on YouTube give it five stars and iTunes support it on patreon or simply connect with me on Twitter Alex Friedman spelled Fri D M a.m. and now here's my conversation with David Ferrucci your undergrad was in biology with a with an eye toward medical school before you went on for the PhD in computer science so let me ask you an easy question what is the difference between biological systems and computer systems in your when you sit back look at the Stars and think philosophically I often wonder I often wonder whether or not there is a substantive difference and I think the thing that got me into computer science and artificial intelligence was exactly this presupposition that if we can get machines to think or I should say this question this philosophical question if we can get machines to think to understand to process information the way do we do so if we can describe a procedure or describe a process even if that process where the intelligence process itself then what would be the difference so from philosophical standpoint I'm not trying to convince that there are there is I mean you can go in the direction of spirituality you can go in the direction of a soul but in terms of you know what we can what we can experience from an intellectual and physical perspective I'm not sure there is clearly there implement there are different implementations but if you were to say as a biological information processing system fundamentally more capable than one we might be able to build out of silicon or or some other substrate I don't I don't know that there is how distant do you think is the biological implementation so fundamentally they may have the same capabilities but is it really a far mystery where a huge number of breakthroughs are needed to be able to understand it or is that something that for the most part in the important aspects echoes are the same kind of characteristics yeah that's interesting I mean I so you know your question presupposes that there's this goal to recreate you know what we perceive is biological intelligence I'm not I'm not sure that's the I'm not sure that that's how I would state the goal I mean I think that studying the goal good so I think there are a few goals I think that understanding the human brain and how it works is important for us to be able to diagnose and treat issues for us to understand our own strengths and weaknesses both intellectual psychological and physical so neuroscience and on sending the brain from that perspective has a there's a clear clear goal there from the perspective of saying I want to I want to I want to mimic human intelligence that one's a little bit more interesting human intelligence certainly has a lot of things we Envy it's also got a lot of problems too so I think we're capable of sort of stepping back and saying what do we want out of it what do we want out of an intelligence how do we want to communicate with that intelligence how do we want to behave how do we want it to perform now of course it's it's somewhat of an interesting argument because I'm sitting here as a human with a biological brain and I'm critiquing this trends and weaknesses of human intelligence and saying that we have the capacity just the capacity to step back and say gee what what is intelligence is what do we really want out of it and that even in and of itself suggests that human intelligence is something quite amiable that it could you know it can it can it can introspect that it could introspect that way and the flaws you mentioned the flaws the human self yeah but I think I think that flaws that humans wholeness house is extremely prejudicial and bias and the way it draws many inferences do you think those are sorry to interrupt you think those are features or are those bugs do you think the the prejudice the forgetfulness the fear what other flaws list them all what love maybe that's a flaw you think those are all things that can be get gotten getting in the way of intelligence or the essential components of and well again if you go back and you define intelligence as being able to sort of accuracy accurately precisely rigorously reason develop answers and justify those answers in an objective way yeah then human intelligence has these flaws and that it tends to be more influenced by some of the things you said and it's and it's largely an inductive process meaning it takes past data uses that to predict the future very advantageous in some cases but fundamentally biased and prejudicial in other cases because it's gonna be strongly influenced by its priors whether they're whether they're right or wrong from some you know objective reasoning perspective you're gonna favor them because that's those are the decisions or those are the paths that succeeded in the past and I think that mode of intelligence makes a lot of sense for when your primary goal is to act quickly and and and survive and make fast decisions and I think those create problems when you want to think more deeply and make more objective and reasons that decisions of course humans capable of doing both they do sort of one more naturally than they do the other but they're capable of doing both you're saying they do the one that responds quickly in it more naturally right because that's the thing you kind of need to not be eaten by the Predators in the world for example but I mean better than we've we've learned to reason through logic we've developed science we train people to do that I think that's harder for the individual to do I think it requires training and you know and and and teaching I think we are human - certainly is capable of it but we find more difficult and then there are other weaknesses if you will as you mentioned earlier it's just memory capacity and how many chains of inference can you actually go through without like losing your way so just focus and so the way you think about intelligence and we're really sort of floating this philosophical slightly but I think you're like the perfect person to talk about this because we'll get to jeopardy and beyond that's like an incredible one of the most incredible accomplishments in AI in the history of AI but hence the philosophical discussion so let me ask you've kind of alluded to it but let me ask again what is intelligence underlying the discussions we'll have with with jeopardy and beyond how do you think about intelligence is it a sufficiently complicated problem being able to reason your way through solving that problem is that kind of how you think about what it means to be intelligent so I think of intelligence to primarily two ways one is the ability to predict so in other words if I have a problem what's gonna can I predict what's going to happen next whether it's to you know predict the answer of a question or to say look I'm looking at all the market dynamics and I'm going to tell you what's going to happen next or you're in a in a room and somebody walks in and you're going to predict what they're going to do next or what they're going to say next doing that in a highly dynamic environment full of uncertainty be able to lots of lockdown the more the more variables the more complex the more possibilities the more complex but can I take a small amount of prior data and learn the pattern and then predict what's going to happen next accurately and consistently that's a that's certainly a form of intelligence what do you need for that by the way you need to have an understanding of the way the world works in order to be able to unroll it into the future all right thank you one thing is needed to predict depends what you mean by understanding IIIi need to be able to find that function and this is very much like what function deep learning does machine learning does is if you give me enough prior data and you tell me what the output variable is that matters I'm going to sit there and be able to predict it and if I can predict you predict it accurately so that I can get it right more often than not I'm smart if I do that with less data and less training time I'm even smarter if I can figure out what's even worth predicting I'm smarter meaning I'm figuring out what path is gonna get me toward a goal what about picking a goal so again well that's interesting about picking our goal sort of an interesting thing I think that's where you bring in what do you pre-programmed to do we talked about humans and humans a pre-programmed to survive so sort of their primary you know driving goal what do they have to do to do that and that that could be very complex right so it's not just it's not just figuring out that you need to run away from their ferocious tiger but we survive in social context as an example so understanding the subtleties of social dynamics becomes something that's important for surviving finding a mate reproducing right so we're continually challenged with complex sets of variables complex constraints rules if you will that we we or patterns and we learn how to find the functions and predict the things in other words represent those patterns efficiently and be able to predict what's going to happen that's a form of intelligence that doesn't really record that doesn't really require anything specific other than ability to find that function and and predict that right answer it's certainly a form of intelligence but then when we when we say well do we understand each other in other words do would you perceive me as as intelligent beyond that ability to predict so now I can predict but I can't really articulate how I'm going to that process what my underlying theory is for predicting and I can't get you to understand what I'm doing so that you can follow you can figure out how to do this yourself if you hadn't if you did not have for example the right pattern matching machinery that I did and now we have potentially have this breakdown where in effect I'm intelligent but I'm sort of an alien intelligence relative to you you're intelligent but nobody knows about it or I can see the I can see the output knowing so so you're saying let's to separate the two things one is you explaining why you were able to predict the future and and the second is me being able to like impressing me that you're intelligent me being able to know that you successfully predicted the future do you think that's well it's not a pressing you item intelligent in other words you may be convinced that I'm intelligent in some form so high well because of my ability to predict so I would imagine that wow wow you're right all here you're you're right more times than I am you're doing something interesting that's a form that's a form of intelligence but then what happens is if I say how are you doing that and you can't communicate with me and you can't describe that to me now I'm a label you a savant I mean I may say well you're doing something weird and it's and it's just not very interesting to me because you and I can't really communicate and and so now this is interesting right because now this is you're in this weird place where for you to be recognized as intelligent the way I'm intelligent then you and I sort of have to be able to communicate and then my we start to understand each other and then my respect and my my appreciation my ability to relate to you starts to change so now you're not an alien intelligence anymore yours you're our human intelligence now because you and I can communicate and so I think when we look at when we look at when we look at animals for example animals can do things we can't quite comprehend we don't quite know how they do them but they can't really communicate with us they can't put what they're going through in our terms and so we think of them in sort of low there are these alien intelligences and they're not really worthless so what we're worth we don't treat them the same way as a result of that but it's it's hard because who knows what you know what's going on so just a quick elaboration on that the explaining that you're intelligent the explaining the the reasoning the one end to the prediction is not some kind of mathematical proof if we look at humans look at political debates and discourse on Twitter it's mostly just telling stories so you usually your task is sorry that your task is not to tell an accurate depiction of how you reason but to tell a story real or not that convinces me that there was a mechanism by which you ultimately that's what a proof is I mean even a mathematical proof is is that because ultimately the other mathematicians have to be convinced by your proof otherwise in fact they're been that the measurement success yeah yeah there have been several proofs out there where mathematicians would study for a long time before they were convinced that it actually proved anything right you never know if it proved anything until the community of mathematicians decided that it did so I mean so it's but it's it's a real thing yeah and and that's sort of the point right is that ultimately on you know this notion of understanding us understanding something there's ultimately a social concept in other words you I have to convince enough people that I I did this in a reasonable way I did this in a way that other people can understand and and replicate and that make sense to them so we're very human Houghton's is bound together in that way we're bound up in that sense we sort of never really get away with it until we can consider convince others that our thinking process you know make sense did you think the general question of intelligence is then also social constructs so if we task asked questions of an artificial intelligence system is this system intelligent the answer will ultimately be a socially constructed I think I think so I so I think you're making to be a mess I'm saying we can try to define intelligence in this super objective way that says here here's this data I want to predict this type of thing learn this function and then if you get it right often enough we consider you intelligent but that's more like a stepfather that I think it I think it is it doesn't mean it's useful if it could be incredible useful it could be solving a problem we can't otherwise solve and can solve it more reliably than we can but then there's this notion of can humans take responsibility for the decision that you're that you're making can we make those decisions ourselves can we relate to the process that you're going through and now you as an agent whether you're a machine or another human frankly are now obliged to make me understand how it is that you're arriving at that answer and allow me I mean me or the obviously a community or a judge of people to decide whether or not whether or not that makes sense and by the way that happens with the humans as well you're sitting down with your staff for example and you ask for suggestions about what to do next and someone says well I think you should buy and I think you should buy this much or would have or sell or whatever it is or I think you should launch the product today or tomorrow or launch this product versus that product whatever decision may be and you ask why and the person so I just have a good feeling about it and it's not you're not very satisfied now that person could be you know you might say well you've been right you know before but I'm gonna put the company on the line can you explain to me why I should believe this and that explanation may have nothing to do with the truth just them and all them convinced the wrong yes they'll be wrong she's got to be convincing but it's ultimately got to be convinced and that's why I'm saying it's we're bound together right our intelligences are bound together in that sense we have to understand each other and and if for example you're giving me an explanation I mean this is a very important point right you're giving me an explanation and I'm and I and I and I have iton I'm not good and then I'm not good at reasoning well and being objective and following logical paths and consistent paths and I'm not good at measuring and sort of computing probabilities across those paths what happens is collectively we're not going to do we're not going to do well how hard is that problem the second one so we I think will talk quite a bit about the the first on a specific objective metric benchmark performing well but being able to explain the steps the reasoning how hard is that probably that's I think that's very hard I mean I think that that's um well it's hard for humans the thing that's hard for humans as you know may not necessarily be hard for computers and vice-versa so sorry so how hard is that problem for computers I think it's hard for computers and the reason why are related to or saying that it's also hard for humans is because I think when we step back and we say we want to design computers to do that one of the things we have to recognize is we're not sure how to do it well I'm not sure we have a recipe for that and even if you wanted to learn it it's not clear exactly what data we use and what judgments we use to learn that well and so what I mean by that is if you look at the entire enterprise of science science is supposed to be at a bad objective reason and reason right so we think about who's the most intelligent person or group of people in the world do we think about the savants who can close their eyes and give you a number we'd think about the think tanks or the scientists of the philosophers who kind of work through the details and write the papers and come up with the thoughtful logical proves and use the scientific method and I think it's the latter and my point is that how do you train someone to do that and that's what I mean by it's hard how do you what's the process of training people to do that well that's a hard process we work as a society we work pretty hard to get other people to understand our thinking and to convince them of things now we could for so weighed them obviously talked about this like human flaws or weaknesses we can persuade through persuade then through emotional means but to but to get them to understand and connect to and follow a logical argument is difficult we try it we do it we do it as scientists we try to do it as journalists we know we try to do it as you know even artists in many forms as writers as teachers we go to a fairly significant training process to do that and then we could ask what why is that so hard but it's hard and for humans it takes a lot of work and when we step back and say well step back and say well how do we get a machine - how do we get a machine to do that it's a vexing question how would you begin to try to solve that and maybe just a quick pause because there's an optimistic notion in the things you're describing which is being able to explain something through reason but if you look at algorithms that recommend things that we look at next well there's Facebook Google advertising based companies you know their goal is to convince you to buy things based on anything so that could be reason because the best of advertisement is showing you things that you really do need and explain why you need it but it could also be through emotional manipulation the algorithm that describes why a certain reason a certain decision was was made how hard is it to do it through emotional manipulation and why is that a good or a bad thing so you've kind of focused on reason logic really showing in a clear way why something is good one is that even a thing that us humans do and and and - how do you think of the differences in the reasoning aspect and the emotional manipulation well they you know so you call it emotional manipulation but more objectively is essentially saying you know thing you know there are certain features of things that seem to attract your attention I'm gonna kind of give you more of that stuff manipulation is a bad word yeah I mean I'm not saying it's good right or wrong is it it works to get your attention and it works to get you to buy stuff and when you think about algorithms that look at the patterns of the you know patterns of features that you seem to be spending your money on and is there going to give you something with a similar pattern so I'm going to learn that function because the objective is to get you to click on and/or get you to buy and or whatever it is I don't know I mean that it is like it is what it is I mean that's what the algorithm does you can argue whether it's good or bad it depends what your you know what your what your goal is I guess this seems to very useful for convincing telling us the thing for convincing humans yeah it's good because you gives again this goes back to how does a human you know what is the human behavior like how does a human you know brain respond to things I think there's a more optimistic view of that too which is that if you're searching for certain kinds of things you've already reasoned that you need them and these these algorithms are saying look that's up to you the reason whether you need something or not that's your job you know you you met you may have an unhealthy addiction to this stuff or you may have a reasoned and thoughtful explanation for why it's important to you and the algorithms are saying hey that's like whatever like that's your problem all I know is you're buying stuff like that you're interested in stuff like that could be a bad reason could be a good reason that's up to you I'm gonna show you more of that stuff and so and I and I and I think that that's it's not good or bad it it's not reason or not reason the algorithm is doing what it does which is saying you seems to be interested in this I'm going to show you more that stuff and I think we're seeing it's not just in buying stuff but even in social media you're reading this kind of stuff I'm not judging on whether it's good or bad I'm not reasoning at all I'm just saying I'm gonna show you other stuff with similar features and you know and like and that's it and I wash my hands from it and I say that's all you know that's all what's going on you know there is you know people are so harsh on AI systems so one the bar of performance is extremely high and yet we also asked them to in the case of social media to help find the better angels of our nature and help make a better society so what do you think about the role of it that so that agrees you that's that's the interesting dichotomy right because on one hand we're sitting there and we're sort of doing the easy part which is finding the patterns we're not building the systems not building a theory that it's consumable and understandable other humans that could being explained and justified and and so on one hand to say oh you know AI is doing this why isn't doing this other thing well those other things a lot harder and it's interesting to think about why why why it's harder and because you're interpreting you're interpreting the data in the context of prior models in other words understandings of what's important in the world what's not important what are all the other abstract features that drive our decision-making what's sensible what's not sensible what's good what's bad what's moral what's valuable what is it where is that stuff no one's applying the interpretation so when I when I see you clicking on a bunch of stuff and I look at these simple features the raw features the features that are there in a data like what words are being used or how long the material is more other very superficial features what colors are being used in the material like I don't know why you're clicking on the stuff you're looking or if it's products what the price of what the price is or what the categories or stuff like that and I just feed you more of the same stuff that's very different than kind of getting in there and saying what does this mean what the stuff you're reading like why are you reading it what assumptions are you bringing to the table are those assumptions sensible is the miss the material make any sense does it does it lead you to thoughtful good conclusions again there's judgment this interpretation judgment involved in that process that isn't really happening in in in the AI today that's harder right because you have to start getting at the meaning of this of the of the stop of the content you have to get at how humans interpret the content relative to their value system and deeper thought processes so that's what meaning means is not just some kind of deep timeless semantic thing that the statement represents but also how a large number of people are likely to interpret so that's again even meaning is a social construct it's so you have to try to predict how most people would understand this kind of statement yeah meaning is often relative but meaning implies that the connections go beneath the surface of the artifact so if I show you a painting it's a bunch of colors in a canvas what does it mean to you and it may mean different things at different people because of their different experiences it may mean something even different to the artist to who painted it as we try to get more rigorous with our communication we try to really nail down that meaning so we go from abstract art to precise mathematics precise engineering drawings and things like that we're really trying to say I want to narrow that that space of possible interpretations because the precision of the communication ends up becoming more and more important and so that means that I have to specify and I think that's why this becomes really hard because if I'm just showing you an artifact and you're looking at it superficially whether it's a bunch of words on a page or whether it's you know brushstrokes on a canvas or pixels on a photograph you can sit there and you can interpret lots of different ways at many many different levels but when I want to when I want to align our understanding of that I have to specify a lot more stuff that's actually not in it not directly in the artifact now I have to say well how you were how are you interpreting this image and that image and what about the colors and what do they mean to you what's what perspective are you bringing to the table what are your prior experiences with those artifacts what are your fundamental assumptions and values what what is your ability to kind of reason to chain together logical implication as you're sitting there and saying well if this is the case then I would conclude this and if that's the case then I would conclude that and it so your reasoning processes and how they work your prior models and what they are your values and your assumptions all those things now come together into the interpretation getting in sick of that is hard and yet humans able to intuit some of that without any pre because they have the shared experience me and we're not talking about shared two people have any shares know me as a society that's correct we have this shared experience and we have similar brains so we tend to Institute in other words part of our shared experiences are shared local experience like we may live in the same culture we may live in the same society and therefore we have similar education we have similar what we like to call prior models about the world prior experiences and we use that as a think of it as a wide collection of interrelated variables and they're all bound to similar things and so we take that as our background and we start interpreting things similarly but as humans we have it we have a lot of shared experience we do have similar brains similar goals similar emotions under similar circumstances because we're both humans so now one of the early questions you ask well how is biological and you know computer information systems fundamentally different well one is you know one is come you means come with a lot of pre-programmed stuff yeah a ton of program stuff and they were able to communicate because they have a lot of it because they share that stuff do you think that shared knowledge if it can maybe escape the hardware question how much is encoded in the hardware just the shared knowledge in the software the the history the many centuries of wars and so on that came to today that shared knowledge how hard is it to encode and did you have a hope can you speak to how hard is it to encode that knowledge systematically in a way that could be used by a computer so I think it is possible to learn to form machine to program machine to acquire that knowledge with a similar foundation in other words in a similar interpretive interpretive foundation for processing that knowledge but what do you mean by that so in other in other words foundation we view the world in a particular way and so in other words we we have i if you will as humans we have a frame reference for bringing the world around us so we have multiple frameworks for interpreting the world around us but if you're interpreting for example social political interactions you're thinking about what there's people there's collections and groups of people they have goals the goals largely built around survival and quality of life that are their fundamental economics around scarcity of resources and when when humans come and start interpreting a situation like that because you've brought you've grown up like historical events they start interpreting situations like that they apply a lot of this a lot of this this fundamental framework for interpreting that well who are the people what were their goals what users did they have how much power influence that they have over the other like this fundamental substrate if you will for interpreting and reasoning about that so I think it is possible to in view a computer with that that stuff that humans like take for granted when they go and sit down and try to interpret things and then and then with that with that foundation they acquire they start acquiring the details the specifics in any given situation are then able to interpret it with regard to that framework and then given that interpretation they can do what they can predict but not only can they predict they can predict now with an explanation that can be given in those terms in the terms of that underlying framework that most humans share now you could find humans that come in interpret events very differently than other humans because they're like using a different different framework you know movie matrix comes to mind where you know they decided the humans were really just batteries and that's how they interpreted the value of humans as a source of electrical energy so but um but I think that you know for the most part we we have a way of interpreting the events or do social events around us because we have to share at framework it comes from again the fact that we're we're similar beings that have similar goals similar emotions and we is we can make sense out of these these frameworks make sense to us so how much knowledge is there do you think so it's you said it's possible well there's all its tremendous amount of detailed knowledge in the world there you know you can imagine you know effectively infinite number of unique situations and unique configurations of these things but the the knowledge that you need what I refer to as like the frameworks for you for interpreting them I don't think I think that's those are finite you think the frameworks I'm more important than the bulk of them now so it's like framing yeah because the frameworks do is they give you now the ability to interpret and reason and to interpret and reasoning to interpret and reason over the specific in ways that other humans would understand what about the specifics you know who acquired the specifics by reading and by talking to other people and so mostly actually just even if we can focus on even the beginning the common-sense stuff the stuff that doesn't even require reading or animalistic requires playing around with the world or something just being able to sort of manipulate objects drink water and so on all does that every time we try to do that kind of thing in robotics or AI it seems to be like an onion you seem to realize how much knowledge is really required to perform you in some of these basic tasks do you have that sense as well and if so how do we get all those details are they written down somewhere idea they have to be learned through experience so I think when like if you're talking about sort of the physics the basic physics around us for example acquiring information about for acquiring how that works yeah I think that I think there's a combination of things going I think there's a combination of things going on I think there is like fundamental pattern matching like what were you talking about before where you see enough examples enough data about something you start assuming that and with similar input I'm going to predict similar outputs you don't can't necessarily explain it at all you may learn very quickly that when you let something go it falls to the ground that's a that's a sickness is horribly explained that but that's such a deep idea if you let something go like they do gravity I mean people were letting things go and counting on them falling well before they understood gravity but that seems to be a that's exactly what I mean is before you take a physics class or the or study anything about Newton just the idea that stuff falls to the ground and they be able to generalize that other all kinds of stuff falls to the ground it just seems like a non if without encoding it like hard coding it in it seems like a difficult thing to pick up it seemed like gift of Allah of different knowledge to be able to integrate that into the framework sort of into everything else so both know that stuff falls to the ground and start to reason about social political discourse so both like the very basic and the high-level reasoning decision-making I guess my question is how hard is this problem and sorry to linger on it because again and we'll get to it for sure as well Watson with jeopardy did its take on a problem that's much more constrained but has the same hugeness of scale at least from the outsider's perspective so I'm asking the general life question of to be able to be an intelligent being and reason in the in the world about both gravity and politics how hard is that problem so I think it's solvable okay now beautiful so what about what about time travel okay convinced not as convinced yet okay no I said I I think it is I mean I I took it as solvable I mean I think that it's alert it's versatile it's about getting machines to learn learning is fundamental and I think we're already in a place that we understand for example how machines can learn in various ways right now our learning our learning stuff is sort of primitive in that we haven't sort of taught machines to learn the frameworks we don't communicate our frameworks because of our shared in some cases we do but we don't annotate if you will all the data in the world with the frameworks that are inherent or underlying our understanding instead we just operate with the data so if we want to be able to reason over the data in similar terms in the common frameworks we need to be able to teach the computer or at least we need to program the computer to require to have access to and acquire learn the frameworks as well and connect the frameworks to the data I think this I think this can be done I think we can start I think machine learnings for example with enough examples can start to learn these basic dynamics will they relate the necessary to gravity not unless they can also acquire those theories as well and put the experiential knowledge and connected back to the theoretical knowledge I think if we think in terms of these class of architectures that are are designed to both learn the specifics find the patterns but also acquire the frameworks and connect the data to the frameworks if we think in terms of robust architectures like this I think there is a path toward getting there jeez in terms of encoding architectures like that do you think systems they were able to do this will look like and you know that works or representing if you look back to the eighties and nineties of the expert systems so more like graphs the systems that are based in logic able to contain a large amount of knowledge where the challenge was the automated acquisition of that knowledge the I guess the question is when you collect both the frameworks and the knowledge from the data what do you think that thing will look like yeah so I mean I think think is asking a question they look like neural networks is a bit of a red herring I mean I think that they they will they will certainly do inductive or pattern match based reasoning and I've already experimented with architectures that combine both that use machine learning and neural networks to learn certain classes of knowledge in other words to find repeated patterns in order or in order for it to make good inductive guesses but then ultimately to try to take those learnings and and marry them in other words connect them to frameworks so that it can then reason over that in terms of their humans understand so for example at elemental cognition we do both we have architectures that that do both but both those things but also have a learning method for acquiring the frameworks themselves and saying look ultimately I need to take this data I need to interpret it in the form of these frameworks so they can reason over it so there is a fundamental knowledge representation like what you saying like these graphs of logic if you will there are also neural networks that acquire certain class of information they then they they and align them with these frameworks but there's also a mechanism to acquire the frameworks themselves yes so it seems like the idea of framework requires some kind of collaboration with humans absolutely so do you think of that collaboration as well and unless to be clear let's be clear only for the for the express purpose that you're designing you you're designing machine designing and intelligence that can ultimately communicate with humans in terms of frameworks that help them understand things right so so now to be really clear you can create you can independently create an a machine learning system and an intelligent intelligence that I might call an alien's elegans that does a better job than you with some things but can't explain the framework to you that doesn't mean is it might be better than you at the thing it might be that you cannot comprehend the framework that it may have created for itself that is inexplicable to you that's a reality but you're more interested in a case where you can I I am yeah I per might sort of approach to AI is because I've set the goal for myself I want machines to be able to ultimately communicate understanding with human I want to meet would acquire and communicate acquire knowledge from humans and communicate knowledge to humans they should be using what you know inductive machine learning techniques are good at which is to observe patterns of data whether it be in language or whether it be in images or videos or whatever to acquire these patterns to induce the generalizations from those patterns but then ultimately work with humans to connect them to frameworks interpretations if you will that ultimately make sense to humans of course the machine is gonna have the strength egg it has the richer or longer memory but that you know it has the more rigorous reasoning abilities the deeper reasoning abilities so be it interesting you know complementary relationship between the human and the machine do you think that ultimately needs explained ability like a machine so if we look we study for example Tesla autopilot a lot or humans I don't know if you've driven the vehicle or are aware of what is it so you basically the human and machine are working together there and the human is responsible for their own life to monitor the system and you know the system fails every few miles and so there's there's hundreds of there's millions of those failures a day and so that's like a moment of interaction DC yeah that's exactly right that's a moment of interaction where you know the the the machine has learned some stuff it has a failure somehow the failures communicated the human is now filling in the mistake if you will or maybe correcting or doing something that is more successful in that case the computer takes that learning so I believe that the collaboration between human and machine I mean that's sort of a permanent example of sort of a more another example is where the machine is literally talking to you and saying look I'm I'm reading this thing I know I know that like the next word might be this or that but I don't really understand why I have my gas can you help me understand the framework that supports this and then can kind of take acquire that take that and reason about it and reuse it the next time it's reading to try to understand something not on not unlike a human student might do I mean I remember like when my daughter was the first great in she was had a reading assignment about electricity and you know somewhere in in the text it says and electricity is produced by water flowing over turbines or something like that and then there's a question that says well how was electricity created and so my daughter comes to me and says I mean I could you know created and produced or kind of synonyms in this case so I can go back to the text and I can copy by water flowing over turbines but I have no idea what that means like I don't know how to interpret water flowing over turbines and what electricity even is I mean I can get the answer right by matching the text but I don't have any framework for understanding what this means at all and framework really I mean it's a set of not to be mathematical but axioms of ideas that you bring to the table and interpreting stuff and then you build those up somehow you build them up with the expert that there's a shared understanding of what they are Sheriff it's the social network that us humans do you have a sense that humans on earth in general share a set of like how many frameworks are there I mean it depends on how you bound them right so in other words how big or small like their their individual scope but there's lots and there are new ones I think they're I think the way I think about is kind of an a layer I think that the architectures are being layered in that there's there's a small set of primitives that allow you the foundation to build frameworks and then there may be you know many frameworks but you have the ability to acquire them and then you have the ability to reuse them I mean one of the most compelling ways of thinking about this is or reasoning by analogy where I could say oh wow I've learned something very similar you know I never heard of this I never heard of this game soccer but if it's like basketball in the sense that the goals like the hoop and I have to get the ball in the hoop and I have guards and I have this and I have that like we're weird is the where where are the similarities and where the difference is and I have a foundation now for interpreting this new information and then the different groups like the Millennials will have a framework and then and then well that you never you know yeah well Kratz and Republicans well I Neal's nobody wants that framework well I mean I think understands it right I mean you're talking about political and social ways of interpreting the world around them and I think these frameworks are still largely largely similar I think they differ in maybe what some fundamental assumptions and values are now from a reasoning perspective like the ability to process the framework of Magna might not be that different the implications of different fundamental values or fundamental assumptions in those framework frameworks may reach very different conclusions so from so from a social perspective that conclusions may be very different from an intelligence perspective I you know I just followed where my assumptions took me yeah the product the process itself would look similar but that's a fascinating idea that frameworks really helped carve how a statement will be interpreted I mean having a Democrat and the Republican framework and read the exact same statement and the conclusions that you derive would be totally different from an ad respective is fascinating what we would want out of the AI is to be able to tell you that this perspective one perspective one set of assumptions is going to lead you here in other setups as luncheons is gonna leave you there and to and in fact you know to help people reason and say oh I see where I see where our differences lie yeah you know I have this fundamental belief about that I have this fundamental belief about that yeah that's quite brilliant from my perspective and NLP there's this idea that there's one way to really understand a statement but there probably isn't there's probably an infinite number of ways then just as well well there's a lot finding on there's lots of different interpretations and the you know the the broader you know the broader to the the contents the richer it is and so you know you you and I can have very different experiences with the same text obviously and if we're committed to understanding each other we start and that's the other important point like if we're committed to understanding each other we start decomposing and breaking down our interpretation towards more and more primitive components until we get to that point where we say oh I see why we disagree and we try to understand how fundamental that disagreement really is but that requires a commitment to breaking down that interpretation in terms of that framework in a logical way otherwise you know and this is why I like I think of a eyes is really complementing and helping human intelligence to overcome some of its biases and its predisposition to be persuaded by you know buys but more shallow reasoning in the sense that like we get over this idea well I you know you know I'm right because I'm a Republican or I'm right because I'm democratic and someone labeled this is democratic point of view or it has the following keywords in it and and if the machine can help us break that argument down and say wait a second you know what do you really think about this right so essentially holding us accountable to doing more critical thinking to sit and think about that as fast that's I love that I think that's really empowering use of AI for the public discourse it's completely disintegrating currently I don't know as we learn how to do it on social medias right so one of the greatest accomplishments in the history of AI is Watson competing against in a game of Jeopardy against humans and you were a lead in that accrue at a critical part of that let's start the very basics what is the game of Jeopardy the game for us humans human versus human right so it's to take a question and answer it actually no but it's not right it's really not it's really it's really to get a question and answer but it's what we call a factoid questions so this notion of like it's it really relates to some fact that everything few people would argue whether the facts are true or not in fact most people what and jeopardy kind of counts on the idea that these these statements have factual answers and and the idea is to first of all determine whether or not you know the answer which is sort of an interesting twist so first of all understand the question you have to understand the question what is it asking and that's a good point because the questions are not asked directly right they're all like the way the questions are asked is nonlinear it's like it's a little bit witty it's a little bit playful sometimes it's a it's a little bit tricky yeah they're asked and exactly in numerous witty tricky ways exactly what they're asking is not obvious it takes it takes an experienced humans a while to go what is it even asking right and it's sort of an interesting realization that you have was a missus Oh what's the Jeopardy is a question answering Shou and there's a go like I know a lot and then you read it and you're you're still trying to process the question and the champions have answered and moved on there's like there's three questions ahead at the time you figured out what the question even met so there's there's definitely an ability there to just parse out what the question even is so that was certainly challenging it's interesting historically though if you look back at the jeopardy games much earlier you know 63 yeah and I think the questions were much more direct it weren't quite like that they got sort of more and more interesting the way they asked them that sort of got more and more interesting and subtle and nuanced and humorous and witty over time which really required the human to kind of make the right connections and figuring out what the question was even asking so yeah you have to figure out the questions even asking then you have to determine whether or not you think you know the answer and because you have to buzz in really quickly you sort of have to make that determination as quickly as you possibly can otherwise you lose the opportunity buzz in you've been going before you really know if you know the answer I think well I think a lot of humans will will assume they'll they'll look at the look at their process of very superficially in other words what's the topic what are some key words and just say do I know this area or not before they actually know the answer then they'll buzz in and then I'll buzz in and think about it it's interesting what humans do now some people who know all things like Ken Jennings or something or the more recent big jeopardy player that knows about that though just assume they know although jeopardy and I'll just pose it you know Watson interestingly didn't even come close to knowing all of Jeopardy right Watson even at the peak even at that's been yeah so for example I mean we had this thing called recall which is like how many of all the Jeopardy questions you know how many did could we even find like find the right answer for like anywhere like could we come up with if we look you know we had up a big body of knowledge some of the order of several terabytes I mean from from a web scale was actually very small but from like a book scales talking about millions in bucks right so the equivalent millions of books and cyclopædia is dictionaries books it's a ton of information and you know for I think was 80 only 85% was the answer anywhere to be found hmm so you're ready down you're ready down at that level just to get just to get started right so and so was important to get a very quick sense of do you think you know the right answer to this question so we have to compute that confidence as quickly as we possibly could so it's in effect to answer it and at least you know spend some time essentially answering it and then judging the confidence that we you know that that our answer was right and in deciding whether or not we were confident enough to buzz in and that would depend on what else was going on in the game it could because it was a risk so like if you're really in a situation where I have to take a gas I have very little to lose then you'll buzz in with less confidence so that was the counter for the the financial standings of the different competitors cracks yeah how much of the game was laughs how much time was left and where were you were in the standings things like that what how many hundreds of milliseconds that we're talking about here do you have a sense of what is we targets because we yeah was the targeted so I mean we targeted answering and under three seconds and buzzing it so the decision to buzz in and then the actual answering are those two yes there were two there were two different things in fact we had multiple stages whereas like we would say let's estimate our confidence which which is sort of a shallow answering process and then ultimate and then ultimately decide to buzz in and then we may take another second or something it's kind of go in there and and do that but by and large we're saying like we can't play the game we can't even compete if we can't on average answer these questions and around three seconds or less so you stepped in so there's this there's these three humans playing a game and you stepped in with the idea that IBM Watson would be one of replaced one of the humans and compete against two can you tell the story of Watson taking on this game sure seems exceptionally difficult yeah so the story was that um it was or it was coming up I think the 10-year anniversary of a big blue an optical deep blues IBM wanted to do sort of another kind of really you know fun challenge public challenge that can bring attention to IBM research and the kind of cool stuff that we were doing I had been working in an AI at IBM for some time I had a team doing what's called open domain factoids question-answering which is you know we're not gonna tell you what the questions are we're not even gonna tell you what they're about can you go off and get accurate answers to these questions and it was an area of AI research that I was involved in and so it was a big Pat it was a very specific passion of mine language understanding and always always been a passion of mine one sort of narrow slice on whether or not you could do anything was language was this notion of open domain and meaning I could ask anything about anything factoids meaning it essentially had an answer and and you know being able to do that accurately and quickly so that was a research area that might even already been in and so completely independently several you know IBM exactly there's like what are we gonna do what's the next cool thing to do and Ken Jennings was on his winning streak this was like whatever was 2004 I think was on his win winning streak when someone thought hey that'd be really cool um if the computer can play jeopardy and so this was like in 2004 they were shopping this thing around and everyone who's telling the the research execs no way like this is crazy and we had some pretty you know senior people know if you'll understand the others crazy and he'll come across my desk and I was like but that's kind of what what I'm really interested in doing and but there was such this prevailing sense of this is nots we're not going to risk IBM's reputation on this we're just not doing it and this happened in 2004 it happened in 2005 at the end of 2006 it was coming around again and I was coming off of a I was doing that the open domain question-answering stuff but I was coming off a couple other projects I had a lot more time to put into this and I argued that it could be done and I argue it would be crazy not to do this can I you could be honest at this point so even though you argued for it what's the confidence that you had yourself privately that this could be done it was we just totally told the story of how you tell stories to convince others how confident were you what was your estimation of the problem at that time so I thought it was possible and a lot of people thought it was impossible I thought it was possible a reason why I thought it was possible is because I did some brief experimentation I knew a lot about how we were approaching on open domain factoids question asked me we have been doing it for some years I looked at the Japanese stuff I said this is going to be hard for a lot of the points that you mentioned earlier hard to interpret the question hard to do it quickly enough hard to compute an accurate confidence none of this stuff had been done well enough before but a lot of the technologies were building with the kinds of technologies that should work but more to the point what was driving me was I was an IBM research I was a senior leader in IBM Research and this is the kind of stuff we were supposed to do we were basically supposed to the moonshot this is I mean we were supposed to take things and say this is an active research area it's our obligation to kind of if we have the opportunity to push it to the limits and if it doesn't work to understand more deeply why we can't do it and so I was very committed to that notion saying folks this is what we do it's crazy not not to do this is an active research area we've been in this for years why wouldn't we take this Grand Challenge and and push it as hard as we can at the very least we'd be able to come out and say here's why this problem is is way hard here's what we've tried and here's how we failed so I was very driven as a scientist from that perspective and then I also argued based on what we did a feasibility study oh why I thought it was hard but possible and I showed examples of you know where it succeeded where it failed why it failed and sort of a high level architecture approach for why we should do it but for the most part that at that point the execs really were just looking for someone crazy enough to say yes because for several years at that point everyone has said no I'm not willing to risk my reputation and my career you know on this thing clearly you did not have such fears okay I did not say you died right in and yet for what I understand it was performing very poorly in the beginning so what were the initial approaches and why did they fail well there were lots of hard aspects to it I mean one of the reasons why prior approaches that we had worked on in the past um failed was because of because the questions were difficult difficult to interpret like what are you even asking for right very often like if if the question was very direct like what city you know or what you know even then it could be tricky but but you know what city or what person was often when it would name it very clearly you would know that and and if there was just a small set of them in other words we're gonna ask about these five types like it's gonna be an answer and the answer will be a city in this state or a city in this country the answer will be a person of this type right like an actor or whatever it is but turns out that in jeopardy there were like tens of thousands of these things and it was a very very long tale meaning you know that it just went on and on and and so even if you focused on trying to encode the types at the very top like there's five that were the most let's say five of the most frequent you still cover a very small percentage of the data so you couldn't take that approach of saying I'm just going to try to collect facts about these five or ten types or twenty types or fifty types or whatever so that was like one of the first things like what do you do about that and so we came up with a an approach toward that and the approach to look promising and we we continue to improve our abilities to handle that problem throughout the project the other issue was that right from the outside I said we're not going to I committed to doing this in three five years so we did in four so I got lucky um but one of the things that that putting that like stake in the ground was I and I knew how hard the language of the standard problem was I said we're not going to actually understand language to solve this problem we are not going to interpret the question and the domain of knowledge the question refers to in reason over that to answer these questions were obviously we're not going to be doing that at the same time simple search wasn't good enough to confidently answer with this you know a single correct answer first others like brilliant that's such a great mix of innovation in practical engineering three three four eight so you're not you're not trying to solve the general NLU problem you're saying let's solve this in any way possible oh yeah no I was committed to saying look we're gonna solving the open the main question answering problem we're using jeopardy as a driver for that management hard enough big benchmark exactly and now we're how do we do it we're just like whatever like just figure out what works because I want to be able to go back to the académica scientific community and say here's what we tried here's what work here's what didn't work I don't want to go in and say oh I only have one technology hammer and only gonna use this I'm gonna do whatever it takes I'm like I'm gonna think out of the box do whatever it takes one um and I also Baloo's another thing I believed I believe that the fundamental NLP technologies and machine learning technologies would be would be adequate and this was an issue of how do we enhance them how do we integrate them how do we advance them so I had one researcher and came to me who had been working on question answering with me for a very long time who had said we're gonna need Maxwell's equations for question-answering and I said if we if we need some fundamental formula that breaks new ground and how we understand language we're screwed yeah we're not gonna get there from here like we I am not counting I am that my assumption is I'm not counting on some brand new invention what I'm counting on is the ability to take everything that has done before to figure out a an architecture on how to integrate it well and then see where it breaks and make the necessary advances we need to make and sold this thing works yeah push it hard to see where it breaks and then patch it up I mean that's how people change the world and that's the you know mosque approaches Rockets SpaceX that's the Henry Ford and so on a lot and and I happen to be and in this case I happen to be right but but like we didn't know right but you kind of have to put a second or so how you gonna run the project so yep and backtracking to search so if you were to do what's the brute force solution what what would you search over so you have a question how would you search the possible space of answers look web search has come a long way even since then but at the time like you know you first of all I mean there are a couple of other constraints around the problems interesting so you couldn't go out to the web you couldn't search the Internet in other words the AI experiment was we want a self-contained device device if devices as big as a room fine it's as big as a room but we want a self-contained advice contained device you're not going out the internet you don't have a life lifeline to anything so it had to kind of fit in a shoebox if you will or at least the size of a few refrigerators whatever it might be see but also you couldn't just get out there you couldn't go off Network right to kind of go so there was that limitation but then we did it but the basic thing was go go do what go do a web search the problem was even when we went and did a web search I don't remember exactly the numbers but someone the order of 65% at a time the answer would be somewhere you know in the top 10 or 20 documents so first of all that's not even good enough to play Jack pretty you know the words even if you could pull the avian if you could perfectly pull the answer out of the top 20 documents top 10 documents whatever was which we didn't know how to do but even if you could that do that your you'd be at and you knew it was Ryan Lizza we've had enough confidence in it right so you have to pull out the right answer you have you depth of confidence it was the right answer and and then you'd have to do that fast enough to now go buzz in and you'd still only get 65% of them right with nine doesn't even put you in the winner's circle winner's circle you have to be up over 70 and you have to do it really quick and you do really quickly but now the problem is well even if I had somewhere in the top 10 documents how do I figure out where in the top 10 documents that answer is and how do i compute a confidence of all the possible candidates so it's not like I go in knowing the right answer and I have to pick it I don't know the right answer I have a bunch of documents somewhere in there's the right answer how do i as a machine go out and figure out which ones right and then how do I score it so and now how do I deal with the fact that I can't actually go out to the web first of all if you pause and then just think about it if you could go to the web do you think that problem is solvable if you just pause on it just thinking even beyond jeopardy do you think the problem of reading text defined where the answer is but we saw we solved that and some definition of solves given the Jeopardy challenge how did you do it forever so how did you take a body of work and a particular topic and extract the key pieces of information so what so now forgetting about the the huge volumes that are on the web right so now we have to figure out we did a lot of source research in other words what body of knowledge is gonna be small enough but broad enough to answer Jeffrey and we ultimately did find the body of knowledge that did that I mean it included Wikipedia and a bunch of other stuff so like encyclopedia type of stuff I don't know if you use Mary's different types of semantic resources unlike wordnet and other types of Mantic resources like that as well as like some web crawls in other words where we went out and took that content and then expanded it based on producing statistical see you know statistically producing sees using those sees for other searchers searches and then expanding that so using these like expansion techniques we went out and had found enough content and we're like okay this is good and we even up and totally and you know we had a threat of resources always trying to figure out what content could we efficiently include I mean there's a lot of popular cut like what is the church lady well I think was one of the end hey yeah what we ready I guess that's probably an encyclopedia so it's a pepino is that but then we would but then we would take that stuff when we would go out and we would expand in other words we go find other content that wasn't in the core resources and expanded you know the amount of content will grew it by an order of magnitude but still so again from a web scale perspective this is very small amount of content it's very select we then we then took all that content so we we pre analyzed the crap out of it meaning we we we parsed it you know broke it down into all this individual words and then we did semantic static and semantic parses on it you know had computer algorithms that annotated it and we in that we indexed that in a very rich and very fast index so we have a relatively huge amount of you know let's say the equivalent of for the sake of argument two to five million bucks we've now analyzed all that blowing up at size even more because now with all this metadata and we then we richly indexed all of that and in by way in a giant in-memory cache so Watson did not go to disk so the infrastructure component there if you just speak to it how tough it I mean I know mm maybe this is 2089 you know that that's kind of a long time ago right how hard is it to use multiple machines Olivia how hard is the infrastructure part of the hardware component we used IBM we so we used IBM hardware we had something like I figured exactly but 2,000 to 3,000 cores completely connected so had a switch were you know every CPU was connected to every other scene they were sharing memory in some kind of way Lauren up close shared memory right and all this data was pre analyzed and put into a very fast indexing structure that was all all all in all in memory and then we took that question we would analyze the question so all the content was now pre analyzed so if I so if I went and tried to find a piece of content it would come back with all the metadata that we had pre computed how do you shove that question how do you connect the the big stuff with the meta the the big knowledgebase of the metadata and that's indexed to the simple little witty confusing question right so therein lies you know the Watson architects right so we would take the question we would analyze the question so which means that we would parse it and interpret it a bunch of different ways we try to figure out what is it asking about so we would come we had multiple strategies to kind of determine what was it asking for that might be represented as a simple string and character string or was something we would connect back to different semantic types that were from existing resources so anyway the bottom line is we would do a bunch of analysis and the question and question analysis had to finish and had to finish fast so we do the question analysis because then from the question analysis we would now produce searches so we would and we had built using open source search engines we modified them we had a number of different search engines we would use that had different characteristics we went in there and engineered and modified those search engines ultimately to now take our question analysis produce multiple queries based on different interpretations of the question and fire out a whole bunch of searches in parallel and they would produce combate with passages so this is these are passive search algorithms they would come back with passages and so now you let's say you had a thousand passages now for each passage you you parallel eyes again so you went out and you paralyze those paralyze the search each search would now come back with a whole bunch of passages maybe you had a total of a thousand or five thousand different passages for each passage now you don't figure out whether or not there was a candidate it would call it candidate answer in there so you had a whole bunch of other a whole bunch of other algorithms that would find candidate answers possible answers to the question and so you had candidate answers jet cold candidate answers generators a whole bunch of those so for every one of these components the team was constantly doing research coming up better ways to generate search queries from the questions better ways to analyze the question better ways to generate candidates and speed so better is accuracy and speed cracked so right and speed and accuracy for the most part we're separated we handle that sort of in separate ways like I focus purely on accuracy and to an accuracy are we ultimately getting more questions and producing more accurate confidences and they had a whole nother team that was constantly analyzing the workflow to find the bottlenecks and then if you're getting out of both parallel eyes and drive the algorithm speed but anyway so so now think of it like you have this big fan out now right because you have you had multiple queries now you have now you have thousands of candidate answers for each candidate answer you're gonna score it so you're gonna use all the data that built up you're gonna use the question analysis you can use how the query was generated you're going to use the passage itself and you're going to use the candidate answer that was generated and you're gonna score that so now we have a group of researchers coming up with scores there are hundreds of different scores so now you're getting a fan at it again from however many candidate answers you have to all the different scorers so if you have a 200 different scores and you never a thousand candidates now you have two thousand scores and and so now you got to figure out you know how do I now rank these rank these answers based on the scores that came back and I want to rank them based on the likelihood that there are correct answer to the question so every score was its own research project what do you mean by score so is that the annotation process of basically human being saying that this this answer do you think you think of if you want to think of it what you're doing you know if you want to think about what a human would be doing human would be looking at a possible answer they'd be reading the you know Emily Dixon Dickinson they've been reading the passage in which that occurred they'd be looking at the question they'd be making a decision of how likely it is that Emily Dixon Dickinson given this evidence in this passage is the right answer to that quad got it so that that's the annotation task that Stan Johnson scoring task so but scoring implies zero to one kind of trite continuance is not a binary no give it a score give it a zero yeah exactly so it's what humans did give different scores so that you have to somehow normalize and all that kind of stuff that deal with all that depends on what your strategy is we both we could be relative to it could be we actually looked at the raw scores as well standardized scores because humans are not involved in this humans are not involved sorry so I mean I'm misunderstanding the the the process here this is passages where is the ground truth coming from grass root there's only there were answers to the questions so it's end to end it's end to end so we also I was always driving and and performance a very interesting a very interesting you know engineering approach and ultimately scientific and researcher personal always driving in 10 now that's not to say we wouldn't make hypotheses that individual component performance was related in some way to n10 performance of course we would because people would have to build individual components but ultimately to get your component integrates with the system you had to show impact on end-to-end performance question-answering performance as there's many very smart people work on this and they're basically trying to sell their ideas as a component that should be part of the system that's right and and they would do research on their component and they would say things like you know I'm going to improve this as a candidate generator I'm going to improve this as a question score or as a passive scorer I'm going to proved as or as a parser and I can improve it by two percent on its component metric like a better parse or better candidate or a better type estimation or whatever it is and then I would say I need to understand how the improvement on that computer metric is going to affect the end-to-end performance if you can't estimate that and can't do experiments to demonstrate that it doesn't get in that's like the best run AI project I've ever heard that's awesome okay what breakthrough would you say like I'm sure there's a lot of day to day break this but it was there like a breakthrough that really helped improve performance like wait what people began to believe or is it just a gradual process well I think it was a gradual process but one of the things that I think gave people confidence that we can get there was that as we fouled as as we follow this procedure of different ideas build different components plug them into the architecture run the system see how we do do the error analysis start off new research projects to improve things and the and and and the very important idea that the individual component work did not have to deeply understand everything that was going on with every other component and this is where we we leverage machine learning in a very important way so while individual components could be statistically driven machine learning components some of them were your wrist ik some of them were machine learning components the system has a whole combined all the scores using machine learning this was critical because that way you can divide and conquer so you can say okay you work on your candidate generator or you work on this approach to answer scoring you work on this approach to type scoring you work on this approach to passage search or the passive selection and so forth but when we you just plug it in and we had enough training data to say now we can we can train and figure out how do we weigh all the scores relative to each other based on the predicting the outcome which is right right or wrong on jeopardy and we had enough training data to do that so this enabled people to work independently and to let the machine learning do the integration beautiful so that yeah the machine learning is doing the fusion and then it's a human orchestrated ensemble that's right friend approaches as a great still impressive they were able to get it done a few years that not obvious to me that it's doable if I just put myself in that mindset but when you look back at the Jeopardy challenge again when you're looking up at the stars what are you most proud of looking back at those days I'm most proud of my um my commitment and my team's commitment to be true to the science to not be afraid to fail that's beautiful because there's so much pressure because it is a public event this is a public show that you were dedicated to the idea that's right do you think it was a success in the eyes of the world it was a success by your I'm sure exceptionally high standards is there something you regret you would do differently it was a success it was a success for our goal our goal was to build the most advanced open domain question-answering system we went back to the old problems that we used to try to solve and we did dramatically better on all of them as well as we beat jeopardy so we wanted jeopardy so it was it was a success it was I worried that the world would not understand that has success because it came down to only one game and I knew statistically speaking this can be a huge technical success and we could still lose that one game and that's a whole nother theme of this of the journey but it was a success it was not a success in natural language understanding but that was not the goal yeah that was but I would argue I understand what you're saying in terms of the science but I would argue that the inspiration of it right the they not a success in terms of solving natural language understanding there was a success of being an inspiration to future challenges absolutely drive future efforts what's the difference between how human being compete in jeopardy and how Watson does it that's important in terms of intelligence yeah so thats that actually came out very early on in the project also in fact I had people who wanted to be on the project who were early on who has sort of approached me once I committed to do it had wanted to think about how humans do it and they were you know from a cognition perspective like human cognition and how that should play and I would not take them on the project because another assumption or another stake I put in the ground was I don't really care are you into this at least in the context of this prior need to build in the context to this project in NLU and in building an AI that understands how it needs to alter that communicate with humans I very much care yeah so wasn't that I didn't care in general in fact as an AI scientist I care a lot about that but I'm also a practical engineer and I committed to getting this thing done and I wasn't gonna get distracted I had to kind of say look if I'm gonna get this done and when it charts this path and this path says we're gonna engineer a machine that's gonna get this thing done and we know what search and NLP can do we have to build on that foundation if I come in and take a different approach and start wondering about how the human mind might or might not do this I'm not going to get there from here in the time and you know in the timeframe I think that's a great way to lead the team but now there's done and then one when you look back right so analyse what's the difference sexy right so so I was a little bit surprised actually to discover over time as this would come up from time to time and would reflect on it that and and talking to Ken Jennings a little bit and hearing Ken Jennings talk about it about how he answered questions that it might have been closer to the way humans answer questions than I might have imagined previously because humans are probably in the game of Jeopardy at the level of Ken Jennings probably also cheating their weight into winning right now one else is shallow they're doing that fast as possible they're doing shallow analysis so they are very quickly analyzing the question and coming up with some you know key you know key vectors or cues if you will and they're taking those cue they're very quickly going through like their library of stuff not deeply reasoning about what's going on and then sort of like a lots of different like what we call these these scores which kind of score that in a very shallow way and then say oh boom you know that's what it is and and so it's interesting as we reflected on that so we may be doing something that's not too far off from the way humans do it but we certain certainly didn't approach it by saying you know how would you even do this now in an elemental cognition like the project I'm leading now we asked those questions all the time because ultimately we're trying to do something that is to make the the the intelligence in the machine and the intelligence of the human very compatible well compatible in the sense they can communicate with one another and they can reason with this shared understanding so how they think about things and how they build answers how they build explanations becomes a very important question to consider so what's the difference between this open domain but cold constructed question answering or jeopardy and more something that requires understanding for shared communication with humans and machines yeah well this goes back to the interpretation of what we were talking about before anyway jeopardy the systems on trying to interpret the question and that's not interpreting the content that's reasoning and with regard to any particular framework I mean it's it is parsing it and like parsing the contents and using grammatical cues and stuff like that so if you think of grammar as a human framework in some sense and as that but when you get into the richer semantic frameworks what are people how do they think what motivates them what are the events that are occurring and why are they occurring and what causes what else to happen and and and when it where are things in time and space and it's like when you started thinking about how humans formulate and structure the knowledge that they acquire in their head and wasn't doing any of that what do you think are the essential challenges of like free flowing communication free flowing log versus question-answering even with the framework of the interpretation dialogue yep do you see free-flowing dialogue as a fundamentally more difficult than question answering even with shared so dialogue is as important in number of different ways I mean it's a challenge so first of all when I think about the machine that when I think about a machine that understands language and ultimately can reason in an objective way that can take the information that it perceives through language or other means and connects it back to these frameworks reason and explain itself that system ultimately needs to be able to talk to humans or I needs to be able to interact with humans so in some sentence to dialogue that doesn't mean that it it that like sometimes people talk about dialogue and they think you know how do humans talk how do you montork talk to each other in a casual conversation then you could mimic casual conversations we're not trying to mimic casual conversations we're really trying to produce the machine as goal is it is to help you think and help you reason about your answers and explain why so instead of like talking to your friend down the street about having a smoke having a small talk conversation with your friend down the street this is more about like you would be communicating to the commuter computer on Star Trek we're like what do you want to think about like what do you want to reason about I'm going to tell you the information I have I'm gonna have to summarize it I'm gonna ask you questions you're gonna answer those questions I'm gonna go back and forth with you I'm gonna figure out what your mental model is I'm gonna I'm gonna now relate that to the information I have and present it to you in a way that you can understand it and we could ask follow-up questions so it's that type of dialogue that you want to construct it's more structured it's more goal oriented but it needs to be fluid in other words it can't it can't it has to be engaging and fluid it has to be productive and not distracting so there has to be a model of the words the machine has to have a model of how humans think through things and discuss them so basically a productive rich conversation unlike this part yes but what I'd like to think it's more similar to this pocket as in joking I'll ask you about humor as well actually but what's the hardest part of that because it seems we were quite far away as a community from thats though to be able to so one is having a shared understanding as i think a lot of the stuff you said with frameworks is quite brilliant but just creating a smooth discourse yeah it feels clunky right now well which aspects of this whole problem you just specified all having a productive conversation is the hardest and that were or maybe maybe any aspect of it you can comment on because it's so shrouded in mystery so I think do this you kind of have to be creative in the following sense if I were to do this is purely a machine learning approach and someone said learn how to have a good flue in structured knowledge acquisition conversation I'd go out and say okay I have to collect a bunch of data of people doing that people reasoning well having a good structured conversation that both acquires knowledge efficiently as well as produces answers and explanations as part of the process and you struggle I don't know elect a day to collect the data because I don't know how much data is like that I think okay okay so this one there's a human but also even if it's out there say was out there how do you like alright so I think I think like an accessible right so I think any like any problem like this where you don't have enough data to represent the phenomenon you want to learn in other words you want you if you have enough data you could potentially learn the pattern in an example like this it's hard to do it this is the you know Susie sort of a human sort of thing to do what you recently came out IBM was the debate or projects and surest thing right because now you had you do have these structured dialogues these debate things where they did use machine learning techniques to generate the you know generate these debates dialogues are a little bit tougher in my opinion than generating a a structured argument where you have lots of other structural arguments like this you could potentially annotate that data and you could say this is a good response a bad response in a particular domain here I have to be responsive and I have to be opportunistic with regard to what is the human saying what so I'm goal-oriented and saying I want to solve the problem I want to acquire the knowledge necessary but I also have to be opportunistic and responsive to what the human is saying so I think that it's not clear that we could just train on a body of data to do this but we could bootstrap it in other words we can be creative and we could say what do we think what do we think the structure of a good dialogue is that does this well and we can start to create that if we can if we can create that more programmatic programmatically at least to get this process started and I can create a tool that now engages humans effectively I could start both I could start generating data I could start with the human learning process and I can update my machine but I can also start the automatic learning process as well but I have to understand what features to even learn over so I have to bootstrap the process a little bit first and that's a creative design task that I could then use as input into a more automatic learning task this is some creativity and bootstrapping all right what elements of conversation do you think you would like to see so one of the benchmarks for me is humor right that seems to be one of the hardest if you end to me the biggest contrast is from Watson so one of the greatest sketches of comedy sketches of all time right is the SNL celebrity jeopardy with uh with with Alex Trebek and Sean Connery and Burt Reynolds and so on with uh with the Sean Connery commentating on Alex Trebek smile there a lot so and I think all of them are in the negative point what's why so they're clearly all losing in terms of the game of Jeopardy but they're winning in terms of comedy so what do you think about humor in this whole interaction in the dialogue that's productive or even just whatever what human represents to me is it the same idea that you're saying about a framework because humor only exists within a particular human framework so what do you think about humor what do you think about things like humor that connect to the kind of creativity you mentioned that's needed I think there's a couple things going on there so I I I sort of feel like and I might be too optimistic this way but I think that there are we did a little bit about with with this and with puns and in jeopardy we literally sat down and said well you know how do puns work and you know it's like wordplay and you could formalize these things so I think there's a lot aspects of humor that you could formalize you could also learn new Murr you could just say what do people laugh at and if you have enough again if you have enough data to represent the phenomenon you know might be able to you know weigh the features and figure out you know what humans find funny and what they don't find funny you might the Machine might not be able to explain why the my buddy unless we unless we sit back and think about that more formally I think again I think you do a combination of both and I'm always a big proponent that I think you know robust architectures and approaches are always a little bit combination of us reflecting and being creative about how things are structured and how to formalize them and then taking advantage of large data and doing learning and figuring how to combine these two approaches I think there's another aspect of human to human though which goes to the idea that I feel like I can relate to the person telling the story telling the person telling the story and I think that's that's a interesting theme in the whole AI theme which is do I feel differently when I know it's a robot and when I know when I imagine there's a row but is not conscious the way I'm conscious when they imagine the robot does not actually have the experiences that I experience do I find it you know funny or do because it's not as related I don't imagine that the person is relating it to it the way I relate to it I think this also you see this in in the arts and in entertainment where like you know sometimes you have savants who are remarkable at a thing whether it's sculpture it's music or whatever but the people who get the most attention are the people who can't who can evoke a similar emotional response who can get you to emote right about the way they in other words who can basically make the connection from the artifact from the music of the painting of the sculpture to the to the emotion and get you to share that emotion with them and then and that's when it becomes compelling so they're communicating at a whole different level they're just not communicating the artifact they're communicating their emotional response to the artifact and then you feel like oh wow I can relate to that person I can connect to that I can connect to that person so I think humor has that has that aspect as well so the idea that you can connect to that person person being the critical thing but we're also able to anthropomorphize objects pretty robots and AI systems pretty well so we're almost looking to make them human there may be from your experience with Watson maybe you can comment on did you consider that as part well obviously the problem of Jeopardy doesn't require int the promotoras ation but nevertheless well there was some interest in doing that and I've that's an that's another thing I didn't want to do so I didn't want to distract from the from the actual scientific test nights so you're absolutely right I mean humans do anthropomorphize and and without necessarily a lot of work I mean just put some eyes in a couple of eyebrow movements and you're getting humans to react emotionally and I and I think you can do that so I didn't mean to suggest that that that connection can't cannot be mimicked I think that connection can be mimicked and can get you to can produce that emotional response I just wonder though if you're told what's really going on if you know that the machine is not conscious not having the same richness of emotional reactions and understanding that doesn't really share the understanding but is essentially just moving inside brow or drooping its eyes or making them big or whatever it's doing that's getting the emotional response will you still feel it interesting I think you probably would for a while and then when it becomes more important that there's a deeper under depreciate understanding it may run flat but I don't know I'm pretty I'm pretty confident that it will the majority of the world even if you tell them how no matter well it will not matter especially if the Machine herself says that she is cautious that's very possible so you the scientists that made the machine is saying that this is how the algorithm works everybody will just assume you're lying and that there's a conscious being there so you're deep into the science fiction shop you're on right now but yeah I think it's actually psychology I think it's not science fiction I think it's reality I think it's a really powerful one that will have to be exploring in the next few decades it's a very interesting element of intelligence so what do you think we've talked about social constructs of intelligences and and frameworks and the way humans kind of interpret information what do you think is a good test of intelligence in your view so there's the Alan Turing with the Turing test Watson accomplished something very impressive with Jeopardy what do you think is a test that would impress the heck out of you that you saw that a computer could do they say this is crossing a kind of threshold that's that gives me pause in a good way expectations for a are generally high what does high look like by the way so not the threshold test as a threshold what do you think is the destination what do you think is the ceiling I think machines will in many measures will be better than us will become more effective in other words better predictors about a lot of things and then then then ultimately we can do I think where they're gonna struggle is what we talked about before which is relating to communicating with and understanding humans in deeper ways and and so I think that's a key point like we can create the super parrot what I mean by the super parrot is given enough data a machine can mimic your emotional response can even generate language that will sound smart and what someone else might say under similar circumstances look how its paws on that like that's a super parrot right so given similar circumstances moves its face its faces in similar ways changes its tone of voice in similar ways produce the strings of language that you know would similar that a human might say not necessarily being able to produce a logical interpretation or understanding that would ultimately satisfy a critical interrogation or a critical understanding I think you guys describe me in a nutshell I think I think philosophically speaking you could argue that that's all we're doing as human beings to war so I was gonna say it's very possible you know humans do behave that way too and so upon deeper probing and deeper interrogation you may find out that there isn't a shared understanding because I think humans do both like humans are statistical language model machines and and and they are capable reasoner's you know they're they're both and you don't know which is going on right so and I think it's I think it's an interesting problem we talked earlier about like where we are in our social and political landscape can you distinguish some who can string words together and sound like they know what they're talking about from someone who actually does can you do that without dialogue without integrity of a programming dialogue so it's interesting because humans are really good at in their own mind justifying or explaining what they hear because they project their understanding on onto yours so you could say you could put together a string of words and and someone will sit there and interpret in a way that's extremely biased this is the way they want to interpret it they want to assuming you're an idiot and they'll true put it one way they've all seen you're a genius and interpreted another way that suits their needs so this is tricky business so I think the answer your question as AI gets better and better at better and better mimic you we create the super parrots we're challenged just as we are with we're challenged with humans do you really know what you're talking about do you have a meaningful interpretation a powerful framework that you could reason over and justify your answers justify your predictions and your beliefs why you think they make sense can you convince me what the implications are you know can you so can you reason intelligently and make me believe that those um the implications of your prediction and so forth so what happens is it becomes reflective my standard for judging your intelligence depends a lot on mine but you're saying that there should be a large group of people with a certain standard of intelligence that would be convinced by this particular AI system then there should be by I think one of the depending on the content one of the problems we have there is that if that large community of people are not judgment judging it with regard to a rigorous standard of objective logic and reason you still have a problem like masses of people can be persuaded the Millennials yeah to turn them turn their brains off right okay sorry I have nothing against the warning I just so you you're a part of one of the great benchmarks challenges of AI history what do you think about alpha zero open AI five alpha star accomplishments on video games recently which are also I think at least in the case of go without fagala now for zero playing go was a monumental accomplishment as well what are your thoughts about that challenge I think it was a giant lamare I I think it was phenomenal I mean as one of those other things nobody thought like solving go was gonna be easy particularly because it's again it's hard for particularly hard for humans our team is to learn how for humans to excel at and so it was up another measure a measure of intelligence it's very cool I mean it's very interesting you know what they did I mean and I loved how they solved like the data problem which again they bootstrapped it and got the machine to play itself to generate enough data to learn from I think that was brilliant I think that was great and and and of course the result speaks for itself I think it makes us think about again it is okay what's intelligence what aspects of intelligence are important can the can the go machine help me make me a better go player is it an alien intelligence it was is am I even capable of like again if we if we put in very simple terms it found the function we found the go function can I even comprehend the go function can I talk about the go function can i conceptualize the go function like whatever it might be so one of the interesting ideas of that system is it plays against itself right yeah but there's no human in the loop there so like you're saying it could have by itself created an alien intelligence how torta torta gorrik imagine you're sentencing you're judging you're sentencing people or you're setting policy or you're you know you're making medical decisions and you can't explain you can't get anybody to understand what you're doing or why so it's it's it's an interesting dilemma for the applications of AI do we hold AI to this accountability that says you know humans have to be humans have to be able to take responsibility you know for for the decision in other words can you explain why you would do the thing well you will use get up and speak to other humans and convince them that this was a smart decision is the AI enabling you to do that can you get behind the logic that was made there do you think sorry to link on this point because it's a there's a fascinating one that's a great goal for AI do you think it's achievable in many cases or do you okay there's two possible worlds that we have in the future one is where AI systems do like medical diagnosis or things like that would drive a car without ever explaining to you why it fails when it does that's one possible world then we're okay with it or the other where we are not okay with it and we really hold back the technology from getting to good before it gets able to explain which of those worlds are more likely do you think and which are concerning to you or not I think the reality is it's gonna be a mix you know I'm not trying a problem with that I mean I think there are tasks that perfectly fine with machines show a certain level of performance and that level of performance is already better it is already better than humans so for example I don't know that I get tape driverless cars if driverless cars learn how to be more effective drivers than humans but can't explain what they're doing but bottom line statistically speaking there you know ten times safer than humans I I don't know that I care I think when we we have these edge cases when something bad happens and we want to decide who's liable for that thing and who made that mistake in what we do about that and I think in those those educators are interesting cases and now do we go to designers of the AI and the I says I don't know if that's what it learned to do and it says well you didn't train it properly you know you you were you were negligent in the training data that you gave that machine like how do we drive down and realize oh so I think those are I think those are interesting questions so the optimization problem there sorry is to create a system that's able to explain the lawyers away there you go um I think that uh uh I think it's gonna be interesting I mean I think this is where technology and social discourse are gonna get like deeply intertwined and how we start thinking about problems decisions and problems like that I think in other cases it becomes more obvious where you know it's I got like why did you decide to give that person you know a longer sentence or or to deny them parole again policy decisions or why did you pick that treatment like that treatment up killing that guy like why was that a reasonable choice to make so so and people are gonna demand explanations now there's a reality though here and the reality is that it's not I'm not sure humans are making reasonable choices when they do these things they are using statistical hunches biases or even systematically using statistical averages to make Osmonds is what happened my dad if you saw that target gave about that but you know I mean they decided that my father was brain dead he had went into cardiac arrest and it took a long time for the ambulance to get there and wasn't not resuscitated right away and so forth and they came they told me he was brain dead and why was he brain dead because essentially they gave me a purely statistical argument under these conditions with these four features 98% chance he's brain dead innocent but can you just tell me not inductively but deductively go there and tell me his brain stopped functioning is the way for you to do that and they and and their the the protocol in response was no this is how we make this decision I said this is adequate for me I understand the statistics and I don't have you know there's a two percent chance he's so like I just don't know the specifics I need the specifics of this case and I want the deductive logical argument about why you actually know he's brained it so I wouldn't sign that do not resuscitate and I don't know it was like they went through lots of procedures as a big long story but the bottom was a fascinating story by the way but how I reasoned and how the doctors reasoned through this whole process but I don't know somewhere around 24 hours later or something he was sitting up that would zero bushido brain damage any what lessons do you draw from that story that experience that the data that they're you that the data that's being used to make sophistical inferences doesn't adequately reflect the phenomenon so in other words you're getting shit Ramsar you're getting stuff wrong because you're your model is not robust enough and you might be better off not using statistical inference and statistical averages in certain cases when you know the models insufficient and that you should be reasoning at about the specific case more logically and more deductively and hold yourself responsible to hold yourself accountable to doing that and perhaps AI has a role to say the exact thing we just said which is perhaps this is a case you should think for yourself you should reason deductively so it's hard it's it's so it's hard because it's hard to know that you know you'd have to go back and you'd have to have enough data to essentially say and this goes back to how do we this goes back to the case of how do we decide whether the AI is good enough to do a particular task and regardless of whether or not it produces an explanation so um and and what standards do we hold right for that so um you know if you look at you you look more broadly for example as my father as a metal kick medical case the medical system ultimately helped him a lot throughout his life without it he probably would have died much sooner so overall sort of you know work for him and sort of a net in that kind of way actually I don't know that's fair um but it maybe not in that particular case but overall like oh the medical system overall that's more given a system overall you know was doing more more good than bad now is another argument that suggests that wasn't the case but for the for the sake of argument let's say like that's let's say a net positive and I think you have to sit there and there and take take that into consideration now you look at a particular use case like for example making this this decision have you done enough studies to know how good that prediction really is right and how you have you done enough studies to compare it to say well what if we what if we dug in and in a more direct you know let's get the evidence let's let's do the deductive thing and not use the statistics here how often would that have done better right you just so you have to do this studies to know how good the AI actually is and it's complicated because depends how fast you have to make decision so if you have to make the decision superfast do you have no choice right if you have more time right but if you're ready to pull the plug and this is a lot of the argument that I had was a doctor I said what's he gonna do if you do it what's gonna happen to him in that room if you do it my way you know if you do well he's gonna die anyway so let's do it my way though I mean it raises questions for our society to struggle with as was the case with your father but also when things like race and gender start coming into play when when certain when when judgments are made made based on things that are complicated in our society at least in this course and it starts you know I think I think I'm safe to say that most of the violent crimes committed by males so if you discriminate based you know as a male versus female saying that if it's a male more likely to commit the crime so this is one of my my very positive and optimistic view views of why the study of artificial intelligence the process of thinking and reasoning logically and statistically and how to combine them is so important for the discourse today because it's causing a regardless of what what state AI device devices are or not it's causing this dialogue to happen this is one of the most important dialogues that in my view the human species can have right now which is how to think well yeah how to reason well how to understand our own cognitive biases and what to do about them that has got to be one of the most important things we as as as a species can be doing honestly we are reached we've created an incredibly complex society we've created amazing abilities to amplify noise faster than we can play amplifies signal we are challenged we are deeply deeply challenged we have you know big segments of the population getting hit with enormous amounts of information do they know how to do critical thinking do they know how to objectively objectively reason do they understand what they are doing nevermind with their AI is doing this is such an important dialogue you know to be having and and and you know we are fundamentally are thinking can be and easily becomes fundamentally bias and there are statistics and we shouldn't blind our so we shouldn't discard statistical inference but we should understand the nature of such this conference as us as a society as you know we decided to reject statistical inference to favor individual understanding and and deciding on the individual yes we we consciously make that choice so even if the statistics said even if the Cystic said males are more likely to have you know to be violent criminals we still take each person as an individual and we treat them based on the logic and the knowledge of that situation we purposefully and intentionally reject the statistical once we do that at a respect for the individual for the individual yeah and then that requires reasoning and cracking looking forward what Grand Challenges would you like to see in the future because the the Jeopardy challenge you know captivated the world alpha go alpha zero cap day of the world deep blue certainly beating Kasparov Gary's bitterness aside and captivated the world what do you think do you have ideas for next grand challenges for future challenges of that oh you know I look I mean I think there are lots of really great ideas for Grand Challenges I'm particularly focused on one right now which is Kent you know can you demonstrate that they understand that they could read and understand that they can they can acquire these frameworks and communicate you know reason and communicate with humans so it is kind of like the Turing test but it's a little bit more demanding than the Turing test it's not enough it's not enough to convince me that you might be human because you could you know you can parrot a conversation I think you know the the this standard is a little bit higher is for example can you you know the santa is higher and I think one of the challenges of devising this grand challenge is that we're not sure what intelligence is we're not sure how to determine whether or not two people actually understand each other and then what depth they understand it they you know and what to what depth they understand each other so the challenge becomes something along the lines of can you satisfy me that we have a shared understanding so if I were to probe and probe and you probe me can can can can machines really act like thought partners where they could satisfy me that they that we have a share our understanding is shared enough that we can collaborate and produce the answers together and that you know they they can help me explain and justify those answers so maybe here's an idea so we'll have a Isis run for president and convinced that's too easy from sorry oh no you have to convince the voters that they should vote for it so they s what I would again again I that's why I think this is such a challenge because we go back to the emotional persuasion we go back to you know now we're checking off an aspect of human cognition that is in many ways weak or flawed right we're so easily manipulated our minds are drawn for often the wrong reasons right not the reasons that ultimately matter to us but the reasons that can easily persuade us I think we can be persuaded to believe one thing or another for reasons that ultimately don't serve us well in the long term and a good benchmark should not play with those elements of emotional manipulation I don't think so I think that's where we have to set the set the higher standard for ourselves of what you know what does it mean this goes back to rationality and it goes back to objective thinking and can you produce can you acquire information and produce reasoned arguments and to those reasons arguments pass a certain amount of muster and is it and can you acquire new knowledge you know can you can you under can you reason oh I have acquired new knowledge can you identify where it's consistent or contradictory with other things you've learned and can you explain that to me and get me to understand that so I think another way to think about it perhaps is kind of machine teach you can the hell really nice less than that's where to put it can you understand something that you didn't really understand before where's where is you know it's taking it so you're not you know again it's almost like can it can it teach you can it help you learn and and in an arbitrary space so it can open those domain space so can you tell the Machine and again this borrows from some science fiction's abut can you go off and learn about this topic that I'd like to understand better and then work with me to help me understand it that's quite brilliant what the machine that passes that kind of test do you think it would need to have self-awareness or even consciousness what do you think about consciousness and the importance of it maybe in relation to having a body having a presence an entity do you think that's important you know people used to ask if Watson was conscious and I used to think and he said he's the conscious of what exactly I mean I think you know main cell it depends what it is that you're conscious I mean like so you know did it if you you know it's certainly easy for it to answer questions about it would be trivial to program it so the answer questions about whether or not it was playing jeopardy I mean it could certainly answer questions that will imply that it was aware of things exactly what does it mean to be aware and what does it mean to conscious and it's sort of interesting I mean I think that we differ from one another based on what we're conscious of but wait wait for sure there's degrees of consciousness in there so it well in those areas like it's not just agrees what do you what do you what are you aware of like what are you not aware but nevertheless there's a very subjective element to our experience let me even not talk about consciousness let me talk about another to me really interesting topic immortality fear or mortality Watson as far as I could tell did not have a fear of death certainly not most most humans do wasn't conscious of death it wasn't that so there's an element of finiteness to our existence that I think like we like I mentioned survival that adds to the whole thing that I mean consciousness is tied up with that that we are us thing it's a subjective thing that ends and that seems to add a color and flavor to our motivations in a way that seems to be fundamentally important for intelligence or at least the kind of human intelligence well I take for generating goals again I think you could have you could have an intelligence capability and a capability to learn I capability to predict but I think without I mean again you get a fear but essentially without the goal to survive so you think you can just encode that without having to million code I mean can you create a robot now and you could say you know and plug it in and say protect your power source you know and give it some capabilities and we'll sit there and operate to try to protect this power source and survive I mean I so I don't know that that's false awfully a hard thing to demonstrate it sounds like a fairly easy thing to demonstrate that you can give it that goal we'll come up with that goal by itself as you have to program that goal in but there's something because I think as we touched on intelligence is kind of like a social construct the the fact that a robot will be protecting its power source would would add depth and grounding to its intelligence in terms of us being able to respect I mean ultimately it boils down to us acknowledging that it's intelligent and the fact that it can die I think is an important part of that the interesting thing to reflect on is how trivial that would be and and I don't think if you knew how trivial that was you would associate that with being intelligence I mean I literally put in a statement of code that says you know you have the following actions you can take you give it a bunch of actions like you mount a laser gun on her or you may do you the ability to scream a screech or whatever and you know and you you say you know if you see your power source then you could program that in and you know you're gonna print it you're gonna take these actions to protect it you know you teach it checking it on a bunch of things so and and now you're gonna look at that and you say well you know that's intelligence because it's protecting power source maybe but that's again at this human bias that says the thing I had then I identify my intelligence and my conscious so fundamentally with the desire or at least the behaviors associated with the desire to survive that if I see another thing doing that I'm going to assume it's intelligent what timeline year will society have a something that would that you would be comfortable calling an artificial general intelligence system well what's your intuition nobody can predict the future certainly not next few months or twenty years away but what's your intuition how far away are we I the ideas hearts make these predictions and I would be you know I would be guessing and there's so many different variables including just how much we want to invest in it and how important it you know and how important we think it is what kind of investment are willing to make in it what kind of talent we end up bringing to the table all you know the incentive structure all these things so I think it is possible to do this sort of thing I think it's I think trying to sort of ignore many of the variables and things like that is it a ten-year thing as a 23 it's probably closer to a 20-year thing I guess but not as little no I don't think it's several hundred years I don't think it's several hundred years but again so much depends on how committed we are to investing and incentivizing this type of work this type of work and it's sort of interesting like I don't think it's obvious how incentivize we are I think from a task perspective you know if we see business opportunities to take this technique is a technique to solve that problem I think that's the main driver for many from any of these things from a from a general Tosta seems kind of an interesting question are we really motivated to do that and and like we just struggled ourselves right now to even define what it is so it's hard to incentivize when we don't even know what it is we're incentivized to create and if you said mimic a human intelligence I just think there are so many challenges with the the significance and meaning of that there's not a clear directive there's no clear directive to do precisely that thing so assistance in a larger and larger number of tasks so being able to a system that's particularly able to operate my microwave and making a grilled cheese sandwich I don't even know how to make one of those and then the same system would be doing the vacuum cleaning and then the same system would be teaching my kids that I don't have math I think that when when when you get into a general intelligence for learning physical tasks and again yeah I want to go back to your body questions it's on your body question was interesting but you want to go back to you know learning abilities do physical tasks you might have we might get Majan in that timeframe we will get better and better at learning these kinds of tasks whether it's mowing your lawn or driving a car or whatever it is I think we will get better and better at that where it's learning how to make predictions over large bodies of data as if we're going to continue to get better and better at that and machines will out you know outpace humans and and a variety of those things the underlying mechanisms for doing that may be the same meaning that you know maybe these are deep Nats there's infrastructure to train them reusable components to get them to different classes of tasks and we get better and better at building these kinds of machines you could see argue that the general learning infrastructure in there is a form of a general type of intelligence I think what starts getting harder is this notion of you know can we can we effectively communicate and understand and build that shared understanding because of the layers of interpretation that are required to do that and the need for the machine to be engaged with humans at that level at a continuous basis so how do you get in how do you get the machine in the game how do you get the machine in the intellectual game yeah and to solve AGI you probably have to solve that problem you have to get the machine so it's a little bit of a bootstrapping can we get the machine engaged and you know in the intellectual calling a game but in the intellectual dialogue with the humans are the humans sufficiently an intellectual dialogue with each other to generate enough to generate enough data in this context and how do you bootstrap that because every one of those conversations every one of those conversations those intelligent interactions require so much prior knowledge that is a challenge to bootstrap it so that's so as so the question is and how committed so I think that's possible but when I go back to are we incentivized to do that I know we're incentivized to do the former are we incentivize to do the latter significantly enough to people understand what the latter really is well enough part of the elemental cognition mission is to try to articulate that better and better you know through demonstrations and to trying to craft these grand challenges and get people to say look this is a class of intelligence this is a class of AI do we do we want this what what is the potential of this what are the business what's the business potential what's the societal potential to that and so you know and to build up that incentive system around that yeah I think if people don't understand yet I think they will and is a huge business potential here so it's exciting that you're working on it you've kind of skipped over but I'm a huge fan of physical presence of things do you think you know Watson head of body do you think having a body as to the interactive element between the AI system and a human or just in general to intelligence so I think I think going back to that shared understanding bit humans are very connected to their bodies I mean is one of the reasons one of the challenges in getting an AI to kind of be a compatible human intelligence is that our physical bodies are generating a lot of features that make up the input so in other words where our bodies are are the the tool we use to affect output but they're also but they also generate a lot of input for our brains so we generate emotion we generate all these feelings we generate all these signals that machines don't have so missions that have this as the input data and they don't have the the feedback that says okay I've gotten this I've gotten this emotion or I've gotten this idea I now want to process that and then I can it then affects me as a physical being and then I and I and I can play that out in other words I could realize the implications of tax implications again on my bond mind body complex I then process that and the implications again are internal features are generated I learned from them they have an effect on my mind body complex so it's interesting when we think do we want a human intelligence well if we want a human compatible intelligence probably the best thing to do is to embed it embedded in a human body just to clarify and both concepts beautiful is humanoid robots so robots that look like humans is one or did you mean actually sort of what Hamas was working with neural link really embedding intelligence systems that the ride-alongs human bodies know I was riding along is different I meant like if you want to create an intelligence that is human compatible meaning that it can learn and develop a shared understanding of the world around it you have to give it a lot of the same substrate part of that substrate you know is the idea that it generates these kinds of internal features like sort of emotional stuff it has similar senses it has to do a lot of the same things with those same sentences um right so I think if you want that again I don't know that you want that like man like that's not my specific goal I think that's a fascinating scientific goal I think it has all kinds of other implications that's sort of not to go like I want it I want to create I think of it as I create intellectual thought martyrs for humans so that kind of that kind of intelligence I know other companies that are creating physical thought partners the fiscal partners to figure out for you but that's kind of not where we're you know I'm at but but but the the important point is that a big part of how of what we process is that physical experience of the world around us on the point of thought partners what role does an emotional connection or forgive me love have to play in that thought partnership is that something you're interested in put another way sort of having a deep connection beyond intellectual with the AI yeah with the a between human and ass is that something that gets in the way of the the rational discourse is there something that's useful I worry about biases you know obviously so in other words if you develop an emotional relationship with the machines do all of a sudden you start are more likely to believe what it's saying even if it doesn't make any sense so I you know I worry about that but at the same time I think the opportunity to use machines to provide human companionship is actually not crazy and it's again the intellectual and social companionship is not crazy the idea do you have concerns as a few people do you know Musk Sam Harris about long-term existential threats of AI and perhaps short-term threats of AI we talked about bias we talked about different misuses but do you have concerns about thought partners systems that are able to help us make decisions together humans somehow having a significant negative impact on society in the long term I think there aren't things to worry about I think the giving machines too much leverage is a problem and what I mean by leverage is is too much control for things that can hurt us whether it's socially psychological intellectually or physically and if you give them machines too much control I think that's a concern you forget about the AI just when you give them too much control human bad actors can hack them and produce havoc so um you know that's a problem and you imagine hackers taking over the driverless car Network and you know creating all kinds of havoc but you could also imagine given given the ease at which humans could be persuaded one way or the other and now we have algorithms that can easily take control over over that over that and amplify noise and move people one direction or another I mean humans do that to other humans all the time and we have marketing campaigns we have political campaigns that take it to image of our our emotions or our fears and this is done all the time when but with machines machines are like giant mecha phones right we can amplify this and orders of magnitude and can fine-tune its control so we can tailor the message we can now very rapidly and efficiently tailor the message to the audience taking taking advantage of you know of their biases and amplifying them and using them to pursue a them in one direction or another in ways that are not fair not logical not objective not meaningful and humans the machines and power that so so that's what I mean by leverage like it's not new but wow it's powerful because machines can do it more effectively more more you know more quickly and we see that already going on and and and social media not the plays and other places that's scary and and that's why like I'm I'm that's why I go back to saying one of the most important public dialogues we could be having is about the nature of intelligence and the nature of inference and logic and reason and rationality and us understanding our own biases us understanding our own cognitive biases and how they work and then how machines work and how do we use them to complement and sit basically so that in the end we have a stronger overall system that's just incredibly important I don't most people understand that so so like telling telling your kids or telling your students this goes back to the cognition here's how your brain works here's how easy it is to trick your brain right there are fundamental cognitive but you should appreciate the different the different types of thinking and how they work and what you're prone to and you know and what and what do you prefer and under what conditions does this make sense versus that makes sense and then say here's what AI can do here's how it can make this worse and here's how it can make this better and then that's where the as a role is to reveal that then the that trade-off so if you imagine a system that is able to beyond any definition of the Turing test of the benchmark really an AGI system as a thought partner that you one day will create what question what topic of discussion if you get to pick one would you have with that system what would you ask and you get to find out the truth together so you threw me a little bit with finding the truth at the end but this is a whole nother topic but the I think the beauty of it I think what excites me is the beauty of it is if I really have that system I don't have to pick so in other words I can you know I can go to and say this is where I care about today and and and that's what we mean by like this general capability go out read this stuff in the next three milliseconds and I want to talk to you about it I want to draw analogies I want to understand how this affects this decision or that decision what if this were true what if that were true what what knowledge should I be aware of that could impact my decision here's what I'm thinking is the main implication can you find can you prove that out can you give me the evidence that supports that can you give me evidence supports this oh there's a boy that would that be incredible you would that be just incredible just a long discourse just to be part of whether it's a medical diagnosis or whether it's you know the various treatment options or whether it's a legal case or whether it's a social problem that people are discussing like be part of the dialogue one that holds itself and us accountable to reasons an objective dialogue you know I just I get goosebumps talking about it right so when when you create it please come back on the podcast well the discussion together and make it even longer this is a record for the longest conversation now there's an honor it was a pleasure David thank you so much for thanks so much a lot of fun you |
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